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Journal of Translational Medicine

Call for papers.

Prevention and Early Diagnosis of Breast Cancer

We are welcoming submissions to our new collection on prevention and early diagnosis of breast cancer, guested edited by Monica Pernia Marin, Caren Greenstein, and Mary Salvatore.

Submission Deadline: 27 February 2025

Molecular mimicry in human diseases

We are welcoming submissions to our new collection on molecular mimicry in human diseases, guested edited by Luigi Buonaguro and Jamie Rossjohn.

Submission Deadline: 15 December 2024

Article Collections

"Planeterranean" Diet: Globally Extending the Health Benefits of the Mediterranean Diet

Edited by Prof Laura Soldati, Prof  Salvatore Nesci, Prof  Prisco Piscitelli, Prof Claudia Vetrani, & Prof Luigi Barrea

Fibrosis and Cancer Intersection

Edited by Dr Mary Salvatore & Dr Monica Pernia

Top trending articles

Featured Research: Cardiopulmonary and metabolic responses during a 2-day CPET in myalgic encephalomyelitis/chronic fatigue syndrome: translating reduced oxygen consumption to impairment status to treatment considerations

Post-exertional malaise (PEM), the hallmark symptom of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), represents a constellation of abnormal responses to physical, cognitive, and/or emotional exertion including profound fatigue, cognitive dysfunction, and exertion intolerance, among numerous other maladies. Two sequential cardiopulmonary exercise tests (2-d CPET) provide objective evidence of abnormal responses to exertion in ME/CFS but validated only in studies with small sample sizes. Further, translation of results to impairment status and approaches to symptom reduction are lacking. Presently, this is the largest 2-d CPET study of ME/CFS to substantiate impaired recovery in ME/CFS following an exertional stressor.

Featured Review: Potential pathophysiological role of the ion channel TRPM3 in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and the therapeutic effect of low-dose naltrexone

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease with a broad overlap of symptomatology with Post-COVID Syndrome (PCS). Despite the severity of symptoms and various neurological, cardiovascular, microvascular, and skeletal muscular findings, no biomarkers have been identified. The Transient receptor potential melastatin 3 (TRPM3) channel, involved in pain transduction, thermosensation, transmitter and neuropeptide release, mechanoregulation, vasorelaxation, and immune defense, shows altered function in ME/CFS. We propose that TRPM3 dysfunction may have a broader involvement in ME/CFS pathophysiology, affecting other organs. This paper discusses TRPM3’s expression in various organs and its potential impact on ME/CFS symptoms, with a focus on small nerve fibers and the brain, where TRPM3 is involved in presynaptic GABA release.

Journal of Translational Medicine has launched  In Review , a new option that provides authors with on-demand information on the status of their manuscript, enables them to share their work with funders and their research community, and allows their colleagues to comment and collaborate - all whilst their manuscript is under review.

Featured section: Neuroscience

The Neuroscience section aims to encourage publications that help to reduce the gap between basic preclinical science and medical applications for the patients in the neuroscience field. Any new tool for the dissemination of results in the field can greatly help to progress in the new solutions for the neuropsychiatric patient. The section aims to promote the increase of knowledge on the subject by publishing original research. 

Read the latest articles in the  Neuroscience section

Introducing new sections to Journal of Translational Medicine!

Regenerative medicine.

The Translational Process section dedicates a space to those who tackle such challenges overcoming the boundaries of individual disciplines, and offers a new opportunity to share and accelerate the development of urgently needed methods, tools and procedures. 

Editor-in-Chief: Francesco Marincola, Sonata Therapeutics, USA

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Featured articles

GLP-1 receptor agonists’ impact on cardio-renal outcomes and mortality in T2D with acute kidney disease

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have been studied for their cardiovascular benefits in type 2 diabetes. Here, the authors show that GLP-1 RAs are associated with reduced mortality and improved cardio-renal outcomes in type 2 diabetes patients with acute kidney disease.

• Heng-Chih Pan
• Jui-Yi Chen
• Vin-Cent Wu

Light-responsive adipose-hypothalamus axis controls metabolic regulation

Light is essential for biological life. Here, the authors show blue light activates the photoreceptor Opsin3 in white fat, triggering a light-responsive metabolic circuit involving adipose-hypothalamus communication, which could potentially alleviate obesity-induced metabolic abnormalities.

• Tadataka Tsuji
• Vladimir Tolstikov
• Yu-Hua Tseng

Ragopathies and the rising influence of RagGTPases on human diseases

RagGTPases (Rags) play an essential role in the regulation of cell metabolism by controlling the activities of both mechanistic target of rapamycin complex 1 (mTORC1) and Transcription factor EB (TFEB). Here the authors review several diseases, termed ragopathies, that are associated with Rag dysfunction.

• Irene Sambri
• Marco Ferniani
• Andrea Ballabio

PRC2-AgeIndex as a universal biomarker of aging and rejuvenation

DNA methylation (DNAm) is a key biomarker of aging, with age-related DNAm changes being well-characterized. Here, the authors show that low-methylated regions (LMRs) bound by PRC2 in embryonic stem cells gain methylation with age in somatic cells, proposing the “PRC2-AgeIndex” as a universal biomarker of cellular aging.

• Mahdi Moqri
• Andrea Cipriano
• Vittorio Sebastiano

Determinants of transthyretin levels and their association with adverse clinical outcomes among UK Biobank participants

Though the role of transthyretin (TTR) in the development of cardiac amyloidosis has been recognized, the determinants of TTR levels remain unexplored. Here, the authors present the clinical correlates of transthyretin levels and show that reduced TTR levels are associated with an increase risk of cardiovascular disease and mortality.

• Naman S. Shetty
• Mokshad Gaonkar
• Pankaj Arora

Nicotinamide riboside for peripheral artery disease: the NICE randomized clinical trial

In peripheral artery disease (PAD), this randomized trial assessed whether nicotinamide riboside (NR), with and without resveratrol, improved walking, compared to placebo. Here, the authors show that NR meaningfully improves 6-min walk, and resveratrol did not add benefit to NR alone.

• Mary M. McDermott
• Christopher R. Martens
• Christiaan Leeuwenburgh

MRI-based microthrombi detection in stroke with polydopamine iron oxide

The non-invasive detection of microthrombi following acute ischemic stroke is challenging. Here the author develop an MRI-based contrast agent allowing the identification of microthrombi, investigating it in a mouse model of thromboembolic ischemic stroke.

• Charlène Jacqmarcq
• Audrey Picot
• Thomas Bonnard

Semaglutide ameliorates cardiac remodeling in male mice by optimizing energy substrate utilization through the Creb5/NR4a1 axis

Semaglutide is used for glucose control and weight reduction. Here, the authors show that it enhances myocardial metabolism by targeting Creb5/NR4a1, protecting against cardiac remodeling and offering a therapeutic approach for heart failure through metabolic regulation.

• Chun-Yan Kong
• Qi-Zhu Tang

LSD1 inhibition circumvents glucocorticoid-induced muscle wasting of male mice

Even though glucocorticoids are potent anti-inflammatory agents, they can cause muscle wasting. Here, the authors show that targeting the glucocorticoid receptor coactivator LSD1 limits muscle loss without reducing the drugs’ efficiency on the immune system.

• Qingshuang Cai
• Rajesh Sahu
• Delphine Duteil

An adeno-associated virus variant enabling efficient ocular-directed gene delivery across species

In non-human primates, rAAVs are delivered through suprachoroidal injection at a high dose to achieve optimal efficacy. Here, the authors present a novel AAV capsid (AAVv128) that significantly improved the transduction efficiency in photoreceptor and retinal pigment epithelial cells across species.

The pan-PPAR agonist lanifibranor improves cardiometabolic health in patients with metabolic dysfunction-associated steatohepatitis

Cardiovascular events are the main cause of mortality in patients with metabolic dysfunctionassociated steatohepatitis (MASH). Here, the authors show that lanifibranor improves cardiometabolic health - insulin sensitivity, lipid and glucose metabolism, systemic inflammation and hepatic steatosis.

• Michael P. Cooreman
• Javed Butler
• Sven M. Francque

A cell-free nutrient-supplemented perfusate allows four-day ex vivo metabolic preservation of human kidneys

As demand for organ transplants exceeds availability there has been an unmet need to extend preservation of deceased donor kidneys. Here, the authors show that a cell-free nutrient-supplemented perfusate allows 4-day preservation of human kidneys using spatially resolved lipidomics and metabolomics.

• Marlon J. A. de Haan
• Marleen E. Jacobs
• Ton J. Rabelink

Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding

Direct oral anticoagulants (DOACs) targeting factor Xa that are used to prevent or treat thromboembolic disorders carry the risk of uncontrolled bleeding. Here, the authors present the computational design and evaluation of factor Xa-variants which can be used to reduce DOAC-associated bleeding.

• Wojciech Jankowski
• Stepan S. Surov
• Zuben E. Sauna

Malnutrition enteropathy in Zambian and Zimbabwean children with severe acute malnutrition: A multi-arm randomized phase II trial

Childhood malnutrition in Africa is a glaring example of global inequality, and mortality remains high. Here, the authors report the results of the TAME randomized phase II clinical trial, in which intestinal healing was the target of four potential interventions in malnourished children in Zambia and Zimbabwe.

• Kanta Chandwe
• Mutsa Bwakura-Dangarembizi

Illuminating the complete ß-cell mass of the human pancreas- signifying a new view on the islets of Langerhans

The pancreatic islets of Langerhans play a pivotal role in regulating blood glucose homeostasis through the regulated secretion of the hormones insulin and glucagon. Here, the authors use deep tissue 3D imaging to re-construct the entire human pancreas at microscopic resolution and display previously unrecognized heterogeneities in the islet’s cellularity with pre-clinical and clinical implications.

• Joakim Lehrstrand
• Wayne I. L. Davies
• Ulf Ahlgren

Tissue engineered vascular grafts are resistant to the formation of dystrophic calcification

Advancements in congenital heart surgery stress the need for durable biomaterials. Here, the authors compare tissue-engineered vascular grafts (TEVGs) with traditional polytetrafluoroethylene grafts, revealing TEVGs’ superior durability and reduced calcification, promising improved long-term success for surgeries.

• Mackenzie E. Turner
• Kevin M. Blum
• Christopher K. Breuer

Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography

Chest computed tomography (CT) is one of the most common diagnostic tests. Here, the authors combine two AI models to measure from CT coronary artery calcium, left ventricular mass index, and left and right atrial and ventricular volumes, and show their association with cardiovascular mortality.

• Robert J. H. Miller
• Aditya Killekar
• Piotr J. Slomka

Inhibition of urease-mediated ammonia production by 2-octynohydroxamic acid in hepatic encephalopathy

Hepatic encephalopathy is a severe complication of liver disease with a growing prevalence. Here, the authors present a hydroxamate-based urease inhibitor to target the production of intestinal ammonia, one of the contributors to the pathogenesis of hepatic encephalopathy.

• Diana Evstafeva
• Filip Ilievski
• Jean-Christophe Leroux

Paternal dietary macronutrient balance and energy intake drive metabolic and behavioral differences among offspring

The dietary factors causing varying intergenerational responses are not fully identified. Here, the authors show that the relative proportion of protein, fats, and carbohydrates in paternal diets before conception differentially influences the phenotype of the next-generation offspring on energy metabolism and behaviour.

• Angela Jane Crean
• Alistair McNair Senior
• Stephen James Simpson

Enzymatic conversion of human blood group A kidneys to universal blood group O

ABO blood group compatibility restrictions limit the availability of organs for patients awaiting transplantation. Here, the authors show the rapid enzymatic removal of blood group A antigens from the vasculature of human kidneys using normothermic and hypothermic machine perfusion technologies to make universal blood group O organs for transplantation.

• Serena MacMillan
• Sarah A. Hosgood
• Michael L. Nicholson

Systematic analysis of ChatGPT, Google search and Llama 2 for clinical decision support tasks

People will likely use ChatGPT to seek health advice. Here, the authors show promising performance of ChatGPT and open source models, but a lack of high accuracy considering medical question answering. Improvements are expected over time via domain-specific finetuning and integration of regulations.

• Sarah Sandmann
• Sarah Riepenhausen
• Julian Varghese

Diagnosis and management of subarachnoid haemorrhage

Aneurysmal subarachnoid haemorrhage, with its multisystem effects, presents a substantial challenge to clinicians. Here, the authors show the necessity for comprehensive multidisciplinary care and the urgent need for largescale studies to validate standardised treatment protocols for improved outcomes.

• Suneesh Thilak
• Poppy Brown
• Tonny Veenith

The long and winding road of reprogramming-induced rejuvenation

Rejuvenation and partial reprogramming are two frontier areas in the field of aging. Here, the authors summarize advances in these fields and suggest future directions for research and therapy.

• Ali Doğa Yücel
• Vadim N. Gladyshev

Functional analysis of the human perivascular subarachnoid space

Functional implications of subarachnoid space anatomy remain unclear. Here, the authors show by human in vivo imaging that an intrathecal tracer propagates antegrade along the major cerebral arteries within a perivascular subarachnoid space facilitating tracer passage towards the brain.

• Per Kristian Eide
• Geir Ringstad

Automatic data-driven design and 3D printing of custom ocular prostheses

Manual processes to produce ocular prostheses are time-consuming and yield varying quality. Here, authors present an automatic digital end-to-end process for custom ocular prostheses. It creates shape and appearance from image data of an OCT device and produces them using a full-colour 3D printer.

• Johann Reinhard
• Philipp Urban
• Mandeep S. Sagoo

Bicarbonate signalling via G protein-coupled receptor regulates ischaemia-reperfusion injury

The acid–base balance regulates cellular responses, but little has been known about its molecular mechanism. Here, the authors unveil a bicarbonate-sensing GPCR, GPR30, that underlies cerebral ischemia–reperfusion injury by regulating blood flow recovery.

• Airi Jo-Watanabe
• Toshiki Inaba
• Takehiko Yokomizo

Amyloid beta 42 alters cardiac metabolism and impairs cardiac function in male mice with obesity

Epidemiological evidence has identified associations among obesity, Alzheimer’s disease, and cardiovascular disease. Here, the authors report that adipose tissue releases amyloid beta 42 (Aβ42) and that antagonizing Aβ42 protects cardiac function in obesity murine models.

• Liam G. Hall
• Juliane K. Czeczor
• Sean L. McGee

Heterogeneity of hepatocyte dynamics restores liver architecture after chemical, physical or viral damage

Hepatocytes regenerate the liver after injury, however, the tissue repair mechanisms have been little explored. Here, the authors show that midlobular and pericentral hepatocytes increase their number and size in response to chemical, physical, and viral insults facilitating liver regeneration.

• Inmaculada Ruz-Maldonado
• John T. Gonzalez
• Carlos Fernández-Hernando

Protection against overfeeding-induced weight gain is preserved in obesity but does not require FGF21 or MC4R

Overfeeding triggers a mechanistically ill-defined compensatory response that counteracts weight gain. Here, the authors show that the defence against overfeeding is preserved in obesity, and that it is independent from FGF21 and MC4R.

• Camilla Lund
• Pablo Ranea-Robles
• Christoffer Clemmensen

Short-term hypercaloric carbohydrate loading increases surgical stress resilience by inducing FGF21

Surgery poses significant risks for patients, with attempts to mitigate these risks using multimodal perioperative care pathways. Here, the authors show that preoperative hypercaloric carbohydrate drinks not only alleviate surgical stress but also demonstrates the replicability of this protection using FGF21 treatment alone.

• Thomas Agius
• Raffaella Emsley
• Alban Longchamp

A renal clearable fluorogenic probe for in vivo β-galactosidase activity detection during aging and senolysis

In vivo detection of cell senescence remains a challenge in aging research. This work introduces a novel fluorogenic probe for β-Gal activity that is excreted in urine, providing a simple diagnosis method to estimate the systemic load of senescent cells during aging and senolytic interventions.

• Sara Rojas-Vázquez
• Beatriz Lozano-Torres
• Ramón Martínez-Máñez

Deletion of Aurora kinase A prevents the development of polycystic kidney disease in mice

Using different mouse models of Polycystic Kidney Disease, this research demonstrated that deletion of the Aurora Kinase A gene was able to prevent cyst initiation and growth, identifying it as a central regulator of pathogenesis in this condition.

• Ming Shen Tham
• Denny L. Cottle
• Ian M. Smyth

A randomized trial looking at planning prompts to reduce opioid prescribing

A personalized letter from the Medical Examiner-Coroner in Los Angeles County has proven effective at reducing opioid and benzodiazepine prescribing. Here the authors show that the introduction of if/when-then planning prompts in to the letter further reduced opioid prescribing by 12.85% and benzodiazepine prescribing by 8.32%; they were most effective for clinicians with multiple patient deaths due to accidental opioid-related overdose.

• Jason N. Doctor
• Marcella A. Kelley
• Emily P. Stewart

DNMT3A clonal hematopoiesis-driver mutations induce cardiac fibrosis by paracrine activation of fibroblasts

This study uncovers a critical link between DNMT3A-driven CHIP and heart failure and, in particular, it shows that DNMT3A inactivation in monocytes boosts the release of HB-EGF, which activates fibroblasts inducing diffuse fibrosis in the heart.

• Mariana Shumliakivska
• Guillermo Luxán
• Stefanie Dimmeler

Skeletal muscle-secreted DLPC orchestrates systemic energy homeostasis by enhancing adipose browning

MyoD is a transcription factor expressed in skeletal muscle that plays a critical role in determining myogenic cell fate. Here, Hu et al. reveal a metabolic role of MyoD in orchestrating systemic energy homeostasis by mediating muscle-fat crosstalk through the muscle-secreted lipokine DLPC.

• Mingwei Sun

A naturally occurring polyacetylene isolated from carrots promotes health and delays signatures of aging

Ameliorating or preventing signatures of aging in humans using natural compounds is an exciting area of research. Here the authors isolate a previously unknown phytochemical from carrots which activates defence mechanisms against oxidative stress and extends lifespan in worms, and improves glucose metabolism, promotes exercise capacity, and protects from frailty at higher age in mice.

• Carolin Thomas
• Michael Ristow

A phase 2 randomised controlled trial of mazdutide in Chinese overweight adults or adults with obesity

Mazdutide is a once-weekly glucagon-like peptide-1 (GLP-1) and glucagon receptor dual agonist. Here, the authors show mazdutide was well tolerated over 24 weeks and demonstrated significant and clinically meaningful body weight loss, compared with placebo, in Chinese overweight adults or adults with obesity.

• Hongwei Jiang

Dbh + catecholaminergic cardiomyocytes contribute to the structure and function of the cardiac conduction system in murine heart

Catecholaminergic transmitters are critical signalling effectors known to be released by sympathetic nerves and adrenomedullary endocrine cells in response to physiological stress. In this paper, the authors demonstrate a uniquely distributed group of catecholaminergic cardiomyocytes with key regulatory roles in cardiac excitation conduction.

• Alexander Grassam-Rowe

Choroidal and retinal thinning in chronic kidney disease independently associate with eGFR decline and are modifiable with treatment

In patients with CKD, there is an unmet need for biomarkers that reliably track kidney injury. Here, in a series of prospective studies, the authors show that retinal OCT metrics reflect kidney injury, are modified by treatments for kidney disease and can predict future decline of kidney function.

• Tariq E. Farrah
• Neeraj Dhaun

Investigation of monoclonal antibody CSX-1004 for fentanyl overdose

Fentanyl continues to drive the opioid crisis by contributing to >70,000 deaths per year in the US. Here, the authors investigate a candidate medication for fentanyl overdose prevention (monoclonal antibody CSX-1004) demonstrating its mitigation of fentanyl’s effects in preclinical animal models.

• Paul T. Bremer
• Emily L. Burke
• Rajeev I. Desai

The α-synuclein PET tracer [18F] ACI-12589 distinguishes multiple system atrophy from other neurodegenerative diseases

A PET tracer for α-synuclein would help diagnosis and treatment of α-syn-related diseases. Here the authors show that ACI-12589 shows an uptake in the cerebellar white matter in patients with multiple-system atrophy.

• Ruben Smith
• Francesca Capotosti
• Oskar Hansson

Reduced FOXF1 links unrepaired DNA damage to pulmonary arterial hypertension

It is unknown whether unrepaired DNA damage in lung endothelial cells causes persistent pulmonary arterial hypertension. Here, the authors combine oxidative stress with impaired BMPR2 signaling to link a reduction in FOXF1 to unrepaired DNA damage and impaired regeneration of normal endothelium.

• Sarasa Isobe
• Ramesh V. Nair
• Marlene Rabinovitch

A randomised Phase IIa trial of amine oxidase copper-containing 3 (AOC3) inhibitor BI 1467335 in adults with non-alcoholic steatohepatitis

The authors report data from a Phase IIa randomised, double-blind trial in patients with NASH showing that BI 1467335 strongly and dose-dependently inhibited AOC3 activity (involved in hepatic inflammation) and was well tolerated at all tested doses.

• Philip N. Newsome
• Arun J. Sanyal
• BI 1467335 NASH Phase IIa trial team

Structural basis of dimerization of chemokine receptors CCR5 and CXCR4

Here, authors report chemokine receptors structures obtained using coarse-grained metadynamics. CCR5 and CXCR4 homo- and heterodimers differ in the conformations of ligand binding sites and of the G protein interaction interface, suggesting structural basis for the rational design of biased ligands.

• Daniele Di Marino
• Paolo Conflitti
• Vittorio Limongelli

Fibrocystin/Polyductin releases a C-terminal fragment that translocates into mitochondria and suppresses cystogenesis

Fibrocystin/Polyductin (FPC) is a large ciliary membrane protein encoded by PKHD1 which, when mutated, causes ARPKD. Here, the authors show that FPC suppresses cyst development in the kidney of mouse models through the release and mitochondrial translocation of its C terminal product.

• Rebecca V Walker

ZSP1601, a novel pan-phosphodiesterase inhibitor for the treatment of NAFLD, A randomized, placebo-controlled phase Ib/IIa trial

Non-alcoholic fatty liver disease is a growing health burden with limited treatment options worldwide. Herein the authors report a randomized, double-blind, placebo-controlled, multiple-dose trial of a first-in-class pan-phosphodiesterase inhibitor ZSP1601 in NAFLD patients.

• Yanhua Ding

The Personalized Nutrition Study (POINTS): evaluation of a genetically informed weight loss approach, a Randomized Clinical Trial

Genotype patterns may modify diet effects on weight loss, with greater weight loss on genotype-concordant diets. Here, the authors show that with the current ability to genotype participants as fat- or carbohydrate-responders, evidence does not support greater weight loss on genotype-concordant diets.

• Christoph Höchsmann
• Shengping Yang
• Corby K. Martin

A human antibody against pathologic IAPP aggregates protects beta cells in type 2 diabetes models

β-cell dysfunction in type 2 diabetes is associated with pathological aggregates of IAPP that accumulate in pancreatic islets. Here, the authors describe a novel antibody cloned from healthy elderly donors that selectively targets IAPP oligomers and protects from IAPP toxicity.

• Fabian Wirth
• Fabrice D. Heitz

Human cellular model systems of β-thalassemia enable in-depth analysis of disease phenotype

β-thalassemia is a prevalent genetic disorder causing severe anemia, with study of the underlying molecular defects impeded by paucity of suitable patient material. Here, the authors show that cellular model systems of βthalassemia can be used to identify new therapeutic targets and as screening platforms for new drugs and reagents.

• Deborah E. Daniels
• Ivan Ferrer-Vicens

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American Journal of Translational Research

American Journal of Translational Research (AJTR, ISSN 1943-8141) is an open access online journal dedicated to publication of original work and review articles of translational research in medicine. The goal of AJTR is to provide a barrier-free forum for rapid dissemination of novel discoveries in translational research of medical science.

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Scientists advance findings about novel, low-toxicity anticancer agent

(Medical Xpress)—Researchers at Roswell Park Cancer Institute (RPCI) have found that a new formulation of a promising anticancer agent, the small chemical molecule FL118, is even more effective in controlling two types ...

Apr 3, 2013

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Review Latest Developments in the field of applied and translational public health and medical research.

Print ISSN : 2576-9502 | Online ISSN : 2576-9499 Frequency of publication:  Continuous | Language of publication: English Starting year:  2017 | Format of publication:  Online

The International Journal of Translational Medical Research and Public Health (IJTMRPH) is an open access peer-reviewed journal committed to publishing high-quality articles in the field of applied and translational public health and medical research.

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Trends of Heat-Related Deaths in the US, 1999-2023

• 1 Department of Public Health, University of Texas at San Antonio
• 2 Department of Medicine, Uniformed Services University of the Health Sciences School of Medicine, Bethesda, Maryland
• 3 Department of Human Development and Family Studies, Pennsylvania State University, State College

The warmest average temperature recorded since 1850 occurred in 2023. 1 Recent studies have found exposure to extreme heat to be associated with mortality, with variability by age, sex, and race and ethnicity. 2 , 3 Recent research suggests that heat-related mortality risk is increasing globally, 4 but formal analyses of heat-related mortality trends in the US through 2023 are lacking. This study examined trends in heat-related mortality rates in the US population from 1999 to 2023.

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Howard JT , Androne N , Alcover KC , Santos-Lozada AR. Trends of Heat-Related Deaths in the US, 1999-2023. JAMA. Published online August 26, 2024. doi:10.1001/jama.2024.16386

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Baylor College of Medicine, University of Houston Awarded $44.2 million to Create Regional Hub for Translational Research

By Bryan Luhn — 713-743-0954

• Health and Medicine

Baylor College of Medicine and the University of Houston have been awarded a $44.2 million Clinical and Translational Science Award Program grant from the National Center for Advancing Translational Research to create a regional hub to serve as a support for infrastructure, services, community engagement and workforce development to advance research and drive innovation in clinical translational science.

Key Takeaways

• $44.2 million grant to BCM and UH establishes the Consortium for Translational and Precision Health, a regional hub to support clinical translational research. 
• The CTPH builds on the partnership between BCM, UH and other clinical and research groups within the Texas Medical Center to foster innovation in areas such as basic science, health services pharmaceutical sciences and entrepreneurship.  
• Hub will connect researchers with community health care organizations and government agencies, creating a multidisciplinary environment that supports infrastructure, services and workforce development to advance health care solutions. 
• The CTPH will provide funding and resources for pilot projects and research initiatives, helping to accelerate the translation of new technologies and discoveries into patient care and population-level impact. 
• Draws on expertise from 10 UH colleges, including medicine, nursing, pharmacy, optometry, engineering and others, highlighting the comprehensive institutional commitment to improving population health outcomes.

This new hub is called the Consortium for Translational and Precision Health (CTPH) and builds on the strong partnership between UH and BCM along with the clinical and research groups within the Texas Medical Center that collaborate with these two institutions. It draws on strengths from both institutions in basic science, translational research, health services, pharmaceutical sciences as well as entrepreneurship to develop and disseminate innovations. The CTPH also will connect investigators with community healthcare organizations and government agencies that contribute to healthcare, clinical research and policy in the region.

“This transformational grant for clinical research, led by Baylor and UH, will advance care for patients in Houston and beyond,” said Dr. Paul Klotman, president, CEO and executive dean of BCM. “It will accelerate the transfer of new technologies to patient care.”

“Research is the engine empowering health care’s life-changing advancements,” said UH President Renu Khator. “This innovative hub will be a catalyst for groundbreaking discoveries and treatments that improve people’s quality of life. That’s what drives us at UH and we’re ecstatic to cofound a regional hub for change alongside Baylor.”

The leaders for the CTPH are Dr. Christopher Amos, professor and director of the Institute for Clinical and Translational Research (ICTR) at BCM, Dr. Fasiha Kanwal, professor of medicine and chief of the section of gastroenterology and hepatology at BCM, and Dr. Bettina M. Beech, clinical professor of population health and the chief population health officer at UH.

“The CTPH is a partnership that draws on strengths of both institutions, creating a rich multidisciplinary environment. It will act as the vehicle to enhance the infrastructure and resources needed to effectively conduct research and implement solutions to advance healthcare,” said Dr. Carolyn Smith, interim senior vice president and dean of research at BCM. “It will help implement and create ongoing core research activities that will support the clinical translational science at both institutions.”

The hub will provide funding for pilot projects, and support the groundwork needed for ongoing research. For example, a researcher developing a clinical study might need help with community outreach and engagement, additional study design planning, or access to clinical data. The CTPH will provide resources and services to accelerate the pace of research from discovery to population level impact.

The foundational platform for the CTPH has been laid out in part by the work of Amos’ group at ICTR, which is a group that supports clinical and translational research within BCM.

In addition to UH’s Population Health program and Division of Research, the CTPH will draw upon expertise from 10 UH colleges, including the Tilman J. Fertitta Family College of Medicine, Andy & Barbara Gessner College of Nursing, College of Pharmacy, College of Optometry, C. T. Bauer College of Business, Cullen College of Engineering, College of Natural Sciences and Mathematics, College of Education, College of Liberal Arts and Social Sciences, and the Honors College.

“We are deeply committed to advancing innovation in clinical and translational science, and this award is a significant step forward in our mission to improve population health outcomes,” Beech said. “This is a testament to the unwavering dedication and collaborative spirit of everyone involved. It truly was a team effort.”

Currently, more than 60 leading medical institutions across the nation receive CTSA Program funding. The institutions offer expertise, resources and partnerships at the national and local levels to improve the health of individuals and communities. The CTSA Program also nurtures the field of translational science through education, training and career support at all levels.

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New UH/TSU Survey Finds Trump’s Lead Among Likely Texas Voters is Narrowing

A new UH/TSU survey finds nearly half of Texans plan to vote for former Republican President Donald Trump in November, while 44.6% support the Democratic nominee, Vice President Kamala Harris. That’s notably tighter than the nine-point lead Trump held over President Joe Biden in an earlier survey.

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Eddie Nuñez Named Vice President for Intercollegiate Athletics

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The Translational Medicine Professional: A Bridge Between Bench and Bedside?

Faekah gohar.

1 Department of Paediatrics, Clemenshospital, Münster, Germany

Aisha Gohar

2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands

Georg Hülskamp

Otfried debus.

Translational medicine (TM) can be defined as the interdisciplinary application of biomedical research for the improvement of health of patients and society. The focus of TM has so far been largely on the bench-to-bedside rather than bedside-community transition of research. Several “Valleys of Death” in this process have been described, identifying transitional failures that may halt or impede the pathway, which would otherwise lead to the development of medicines, technologies, and/or evidence based practice guidelines. In order to help bridge these gaps, increasing patient-orientated research at each stage could improve the success of projects and increase societal impact. Increasing the accessibility and involvement of patients in TM outside of traditional research centers, such as universities and teaching hospitals, is one crucial pre-requisite. For example, where clinical research units with active links to local universities have been set-up, research participation can be increased. Such non-traditional research centers (NRTCs) might include primary or secondary care services, or even social care institutions. TM professionals (TMPs) from multi-disciplinary backgrounds, with work experience in university or research centers and with experience of TM, could play a vital role in this organizational change. TMPs in NTRCs are well placed to collaborate with local universities, larger research centers and commercial research and development organizations. Exchanging information could benefit all shareholders involved. TMPs can also stimulate the education and innovative thinking that is required for TM to achieve its full societal impact. We discuss the scope of a potential role for TMPs in NTRCs, as well as the possible barriers and difficulties they might face, along with measures that could widen the accessibility of TM outside of the traditional setting.

The European Society for Translational Medicine defines translational medicine (TM) as being an interdisciplinary branch of biomedicine supported by three pillars: bench, bedside and community. It's goal is to improve the health of society by improving disease management, e.g., with new therapies ( 1 ).

TM has predominantly focused on the bench to bedside approach, with most research activities being conducted in traditional research centers such as specialist centers and universities. Several “Valleys of Death” in TM or the bench-bedside pathway, defined as the route between drug or technology development (the “bench”) and its integration into clinical care (the “bedside”), have been described ( 2 – 4 ). The valleys represent gaps that impede the pathway, impacting the development of medicines, technologies and/or evidence based practice guidelines. Until now, less focus has been on the third pillar of TM: the involvement of the wider community, or “bedside to community” phase 1 . Multi-faceted organizational changes and innovation, for example in trial design, are required to bridge these valleys as success rates of products that reach the ”end” clinical trial stage remain poor ( 2 , 5 , 6 ).

Increasing patient-orientated research at all stages could improve the success of research projects and increase societal impact. Research practice often focuses on select groups of patients, for example those with rare or financially or academically “attractive” diseases, and who are primarily treated in hospitals either in or linked to traditional research centers. Such organizational factors result in an inherently biased system in many respects, including in the setting of research agendas and allocation of funding for projects. Such factors could potentially explain the limited output of the TM pathway. Optimizing the accessibility for patients outside of traditional research centers is also a crucial pre-requisite to innovating TM for the benefit of the wider society. To tackle this problem, Clinical Research Units (CRUs) to link local universities and hospitals have been set-up. Funding through the European Clinical Research Infrastructures Network (ECRIN) has further encouraged the connection of research institutions including CRUs, also referred to as CTUs (Clinical Trial Units) or CRCs (Clinical Research Centers) into hubs and networks in 14 countries across Europe ( 7 ). Accessibility to research participation in other non-traditional research centers (NRTCs) such as primary or secondary care services, and social care institutions, should also be addressed. An onus on research funders to require evidence of early and consistent patient input beginning in the consultation phase could be an additional driver of change.

A range of professionals from basic scientists, laboratory members, regulatory agencies, educational facilities, members of ethics boards, and journals are involved in TM. Professionals with expertise in TM (Tranlational Medicine Professionals, TMPs) from multi-disciplinary backgrounds could play a central role in innovating TM (Figure ​ (Figure1). 1 ). TMPs in NTRCs are well placed to collaborate with the traditional research centers and shareholders, and can coordinate the exchange of information as well as stimulate education and innovative thinking. While some clinical academic tracks for the training of TMPs exist, they may be informal and without a focus on TM. One example where TM and the training of future TMPs was a strong focus was the European Translational Training for Autoimmunity & Immune manipulation Network (EUTRAIN) research and training as part of the EU Marie Curie Initial Training Network programme ( 8 , 9 ). Whilst most TMPs remain based in the organizations where they are trained, i.e., university and research centers, many will spend at least some of their training time in NTRCs. Encouraging such TMPs to continue research in such sites would have a dual effect of avoiding these skills going to waste and maximize the extension of TM into NTRCs. TMPs in NTRCs may even face less constraints on their work, for example with the freedom to conduct projects for societal benefit rather than to achieve prestige in terms of high impact publications and big grants, which may be the case in specialist research centers. In NTRCs, incorporating research into daily clinical practice allows the advantages of TM, such as increased job satisfaction and professional development, to also reach a wider group of professionals. However, TMPs in NTRCs face their own challenges, such as the long held misbelief that research activities should be secondary to the provision of good patient care and limited to research centers. TMPs should engage with colleagues to widen education about TM and its fundamental tenet of incorporating society. NTRCs could themselves drive the process by changing the culture to support and nurture the process of research, for example by recruiting staff with a research interest or experience. The scope of a potential role for TMPs in NTRCs, particularly in (1) widening participation and (2) improving collaboration in TM outside of the traditional research setting will be discussed and are summarised in Table ​ Table1 1 .

Roles for the Translational Medical Professional in aiding the transition from bench to bedside (green text) and addressing potential points of failure, or “valleys of Death” (blue text).

Specific roles the Translational Medical Professional could play in shifting the focus of the translational pathway from “bench to bedside” to “bench to society” by (1) widening participation to research and (2) improving collaboration.

Widening participation

When research participation is excluded from the majority of NTRCs, a goal of wide societal impact and improvement of health is unlikely to be achieved. All members of society should be seen as potential research participants and receive the opportunity to take part in research ( 10 ). All members of society will be affected by healthcare provisions at some point of their life either as recipients of health interventions, or as carers for someone else receiving health care. Therefore, NTRCs should also include social care institutions such as hospices, rehabilitation centers, schools and care homes as well as primary and secondary care centers ( 10 ). In addition, some research questions are population based questions, and require broader patient inclusion to be adequately addressed. For this, the support of patient advocacy groups and ethical review boards is also vital, with TMPs supporting the case for widening TM participation in NTRCs.

Longer-term monitoring of drugs and product related adverse effects, for example after clinical trials are concluded or after the acute phase of a disease is over, might be better performed in NTRCs rather than in specialist centers. Whilst the reporting of drug side effects after licensing is encouraged and required in all countries, the monitoring of products is not monitored to the same extent ( 6 ). One recent example of the failure of adequate follow up and monitoring of devices is the mounting evidence that mesh used in the surgical management of pelvic organ prolapse has been responsible for many post-surgical complications and that the medical devices (the Mesh) was approved based on weak evidence leading to a large unexpected need for costly post-intervention care ( 11 ).

A programme of legislative support and training initiatives is required to support the process of patient engagement ( 12 ). Research activities are already being shifted to NTRCs, which can benefit from increased funding streams and patient access and also developing organizational links with local teaching hospitals and commercial research centers ( 13 ). Structural changes within NTRC, such as the setting up of research and development offices and facilities for clinical research, are also vital. While their financial set-up may not be under the control of TMPs, TMPs can support their development and help staff them. Clinical research centers often include outpatient facilities with consultation rooms and treatment beds as well as access to a laboratory which can perform basic research procedures such as Real-time PCR and flow cytometry, sample preparation for DNA extraction or serum bio-banking.

To be effective, TMPs should be adequately trained and be inter-disciplinary, including laboratory staff and research coordinators as well as specialist research and clinical nurses and doctors ( 14 , 15 ). Therefore, a programme of widening participation for TMPs is also required. In the UK, academic clinical fellowships (ACF) during clinical training have improved access to research programmes for trainees. In contrast to the UK, a much greater proportion of medical students in the Netherlands will undertake PhDs during their study or early in their training. In Germany, to obtain the title “Dr. med” a period of research is also usually completed during university study, much akin to intercalated degree programmes in the UK. However, ACFs and most Dr. med. or Ph.D. and research programmes are based in research centers and include little or no focus on TM or inter-disciplinary working. Widening such programmes whether they are pre- or post-graduate based to multi-disciplinary participants and including time in the programme to develop and teach widening participation in research, novel trial design and collaboration and the inclusion of a period of training time in NTRCs is also vital. There is a general consensus that research and TM requires specially trained professionals, and there is increasingly financial and structural support for interdisciplinarity in clinical and research settings. Many universities have developed new institutes with industry partners as well as clinicians and researchers collaborating and now also offer translational study programmes 1 , 2 ( 6 ). However, one of the largest challenges in widening participation in TM in NTRCs is achieving the organizational changes to support such a transition.

Improving collaboration

TMPs could foster links between NTRCs and local research centers which excel in a particular field or service by driving collaborations as well as widening research participation. Practical measures may include the organization of regular open meetings, with an open forum to present ideas and updates for new or on-going research projects that could help overcome problems or barriers that projects may be facing. This inter-disciplinary sharing of information could drive innovation and benefit all parties involved, e.g., by pooling potential research participants and sharing access to technology or specialists. Common goals and challenges could help lead to solutions such as the recruitment of a suitable control group. Collaboration between departments from different centers, or even between departments from the same center that may have been unaware of pre-existing research facilities or goals available in-house could be improved upon. Open and equal exchanges of ideas, which is the basis of inter-disciplinary research, opens the door to broader sources of funding. Traditional hierarchies of power, which still often exist in traditional research centers, may also be more effectively challenged when committees are inter-disciplinary. Collaboration between NTRCs and established research centers could also be organized in the form of “outreach programmes” which might include the development of mentorship programmes. Taking an active role in the development and running of such integration and outreach activities could provide career benefits to early-stage TMPs, providing earlier opportunities to undertake leadership roles.

Challenges facing TMPs

Some challenges facing TMPs focus around accepting the idea of TM in NTRCs. Many TMPs will have trained with a specialist focus. For their new role in NTRCs, TMPs will need to maintain this focus on detail but also develop wider research skills including novel trial design and collaborative work, which takes public health into account. The role of a TMP will comprise many challenges, including that they must work hard in their NTRCs to be seen as effective and successful in both their clinical and research activities. TMPs must also cross barriers such as addressing common misconceptions including that research has no place in clinical training programmes and be able to engage colleagues to also drive good research practices in their workplace ( 13 ). The main barrier will be to change perceptions so that research is seen as a part of daily practice in NTRCs and not as a supplementary or a career progress driven activity. TMPs will also need to develop time management skills as well as leadership and delegation if they are to achieve all the activities associated with TM including: teaching, publishing papers, writing research grants. Balancing expectations from colleagues, supervisors and patients will also be vital.

In order to achieve the variety of goals we have discussed as well as to excel in communication and drive innovation, TMPs must be creative—a skill which is difficult to teach and measure. This creativity is fundamental to driving new concepts in the design and practice of trials as well as of medical products and the TM pathway itself ( 6 ). TMPs must also use their creativity to develop collaborations with research centers, universities and commercial centers. This can all be achieved with support from colleagues, mentors, and collaborative practices as discussed above.

In conclusion, greater focus on the societal aspect in TM is required to tackle the so-called “valleys of death.” The TMP could be a potentially vital driver of innovation and the organizational processes that are required. However, whilst the focus on TM and the number of TMPs might be increasing, TMPs still face multiple challenges but there are many ways in which they can help widen access of TM and improve collaboration within TM.

Author contributions

FG conceived the study and performed the literature review. All authors contributed to the writing of the manuscript and made substantial contributions to the content and approved the final version.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1 University of Glasgow - Postgraduate study - Taught Degree Programmes A-Z - Translational Medicine (Accessed April 21, 2018). Available online at: https://www.gla.ac.uk/postgraduate/taught/translationalmedicine

2 Institute of Translational Medicine - University of Liverpool (Accessed April 21, 2018). Available online at: https://www.liverpool.ac.uk/translational-medicine/about-us/

• Open access
• Published: 28 August 2024

Transforming simulation in healthcare to enhance interprofessional collaboration leveraging big data analytics and artificial intelligence

• Salman Yousuf Guraya 1  

BMC Medical Education volume  24 , Article number:  941 ( 2024 ) Cite this article

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Simulation in healthcare, empowered by big data analytics and artificial intelligence (AI), has the potential to drive transformative innovations towards enhanced interprofessional collaboration (IPC). This convergence of technologies revolutionizes medical education, offering healthcare professionals (HCPs) an immersive, iterative, and dynamic simulation platform for hands-on learning and deliberate practice. Big data analytics, integrated in modern simulators, creates realistic clinical scenarios which mimics real-world complexities. This optimization of skill acquisition and decision-making with personalized feedback leads to life-long learning. Beyond clinical training, simulation-based AI, virtual reality (VR), and augmented reality (AR) automated tools offer avenues for quality improvement, research and innovation, and team working. Additionally, the integration of VR and AR enhances simulation experience by providing realistic environments for practicing high-risk procedures and personalized learning. IPC, crucial for patient safety and quality care, finds a natural home in simulation-based education, fostering teamwork, communication, and shared decision-making among diverse HCP teams. A thoughtful integration of simulation-based medical education into curricula requires overcoming its barriers such as professional silos and stereo-typing. There is a need for a cautious implantation of technology in clinical training without overly ignoring the real patient-based medical education.

Peer Review reports

Simulation in healthcare, powered by big data analytics (BDA) and artificial intelligence (AI), stands at the forefront of transformative innovations with a promise to facilitating interprofessional collaboration (IPC). This convergence of technologies towards educational philosophies not only revolutionizes medical training but also enhances the quality of care and patient safety in an IPC climate for an efficient delivery of healthcare system [ 1 ]. Simulation in healthcare showcases a controlled, versatile, and safe environment for healthcare professionals (HCPs) from diverse disciplines to engage in hands-on learning with deliberate practice [ 2 ]. Learners are engrossed in immersive, iterative, and interactive climate which can nurture opportunities for the acquisition of transferable psychomotor and cognition-based skills [ 3 ]. A simulated environment nurtures the real jest of life-long learning where learners can be trained by deliberate practice till the acquisition of their skills.

BDA, embedded in modern cutting-edge simulators, can utilize enormous healthcare data for clinical training and skills acquistion [ 4 ]. For instance, Bateman and Wood employed Amazon’s Web Service to accumulate a complete human genomic scaffold including 140 million individual base pairs by adopting an advanced hashing algorithm [ 5 ]. Later, a BDA platform successfully matched patients’ data of children in hospital to their whole-genome sequencing for the management of potentially incurable clinical conditions [ 6 ]. From another perspective, leveraging clinical scenarios with realism, BDA can be a valuable tool in reflecting the complexities of the real-world medical practice. This data-driven approach diligently mimics the variability and inconsistency encountered in real clinical settings, preparing HCPs for diverse patient encounters and crisis management. Artificial intelligence (AI) with its machine learning algorithm (MLA) and natural language processing (NLP) further fortifies the impact of simulation by enabling adaptive learning experiences [ 7 ]. Moreover, AI-powered patient simulators with automated interfaces can demonstrate high fidelity realistic physiological responses such as pulse, blood pressure, breathing patterns, and facial expressions to allow learners to practice decision-making in lifelike scenarios. By analyzing simulation data, institutions can identify trends, best practices, and areas for improvement, ultimately enhancing patient outcomes and advancing medical knowledge.

Applications of BDA harness the experimental usage of electronic health records, medical imaging, genetic information, and patients’ demographics. By aggregating and analyzing this data, simulation platforms can create realistic scenarios that can be used by learners for clinical reasoning and critical decision-making. Additionally, MLA and NLP have the ability to predict disease prognosis, treatment efficacy, and unwanted outcomes, thereby offering a reliable hub for interactive and immersive learning for HCPs [ 8 ]. MLA and NLP encourage adaptive learning experiences by analyzing learner interactions and performance in real-time. This unique opportunity of acquiring skills mastery with personalized feedback either by simulator, peer, or facilitator makes simulation a master-class educational and training tool for all HCPs. For instance, if a learner consistently makes errors in decision-making or a procedural skill, a smart simulator can tailor further exercises to provide targeted practice opportunities for individual learners.

Clinical training is interposed at the crossroads of adopting AI, virtual reality (VR), and augmented reality (AR) technologies. Beyond training, simulation-driven medical education holds immense potential for quality improvement and research in healthcare [ 9 ]. VR and AR technologies offer immersive experiences that simulate clinical settings with unprecedented realism. VR headsets transform learners into a cyber space where they deal with animations, digital images, and a host of other exercises in virtual climate [ 10 ]. AR overlays digital information onto the physical world, allowing learners to visualize anatomical structures, medical procedures, or patient data in real-time. Moreover, VR and AR can be used to perform high risk medical procedures till the complete acquisition of skill mastery. Such opportunity is not possible due to threats to patient safety and limited time for learners’ training in real-world workplaces [ 11 ]. At the same time, the mapping of learners’ needs with the curriculum is possible only in simulated environment where learners’ expectations can be tailored to meet their learning styles [ 11 ]. AI, VR, and AR technologies in healthcare simulators essentially empower learners to develop clinical expertise, enhance patient care, and drive innovations in healthcare delivery.

An example of integration of AI, NP, ML, and certain other algorithms in simulation is the sepsis management of a virtual patient being managed by a team of HCPs from different healthcare disciplines. A patient presents with fever, confusion, and rapid breathing in the emergency room. AI platform creates a detailed medical record of the patient with past hospital visits, medications, allergies, and baseline health metrics. AI simulates patient’s symptoms in real-time with tachycardia, tachypnea, hypotension, and fever. The trainees interview the virtual patient and AI responds, using NLP, by providing coherent and contextually appropriate answers. The trainees order a set of tests, including blood cultures, a complete blood count, and lactate levels. AI presents realistic test results where blood cultures show a bacterial infection, leukocytosis, and elevated lactate levels. Based on the diagnosis of sepsis, the trainees plan treatment which typically includes oxygen, broad-spectrum antibiotics, and intravenous fluid. AI then adjusts the patient condition based on the trainees’ actions which may lead to improvement in clinical parameters. However, a delayed treatment could lead to worsening symptoms such as septic shock. Furthermore, AI can introduce complications if initial treatments were ineffective or if the trainees commit errors. Thereupon, AI provides real-time feedback on the trainees’ decisions which can highlight missed signs, suggest alternative diagnostic tests, or recommend adjustments to treatment plans. Lastly, AI would generate a summary report of the performance with a breakdown of diagnostic accuracy, treatment efficacy, and adherence to clinical guidelines. MLAs analyze patterns in patient data to assist in diagnosis. In this context, decision trees and neural networks of MLAs analyze vast datasets of patient records to create realistic virtual patients with diverse medical histories and clinical conditions.

There has been a proliferation of empirical research about the powerful role of IPC in medical education [ 12 , 13 ]. IPC fosters shared decision-making, role identification and negotiations, team coherence, and mitigates potential errors [ 14 ]. Through simulated scenarios, HCPs learn to navigate interdisciplinary challenges, appreciate each other’s roles, and develop a shared approach to patient care. Additionally, simulation in healthcare faces the challenges of costs, access, development, and ethical considerations. Nevertheless, the integration of simulation, BDA, VR, AR, and AI heralds a new era of IPC in healthcare, where learning, practice, and innovation converge to shape the future of medicine.

The overarching goal of all healthcare systems focuses on patient safety as reiterated by the World Health Organization (WHO) sustainable development goals [ 15 ]. General Medical Council, Irish Medical Council, Canada MEDs, Accreditation Council for Graduate Medical Education, and EmiatesMEDS are also in agreement with WHO and, in this context, IPC can potentially enhance the quality of care and patient safety [ 16 ]. Though the role of IPC is widely accepted, there is a lukewarm response from medical institutions about its integration into the existing curricula. Professional silos, stereotyping, bureaucratic inertia, and resistant mindsets are some of the deterring factors [ 17 ]. In the era of simulation in healthcare, IPC can be efficiently embedded into this technology-powered educational tool for impactful collaborative teamwork. By harnessing the technological power of VR, AR, and AI, simulation platforms can leverage the indigenous advantage of IPC in clinical training. Once skills acquisition is accomplished in the simulated platform, its recreation in the real world would be a seamless transition of transferable skills.

To sum up, despite an exponential growth in the use of technology-driven simulation in healthcare, educators should be mindful of its careful integration in medical curricula. Clinical training on real patients cannot be replaced by any strategy or tool regardless of its perceived efficiency or effectiveness. Bearing in mind the learning styles of our learners with a preference toward fluid than crystalloid verbal comprehension and fluid reasoning, technology-driven simulation plays a vital role in medical education. A thoughtful integration of simulation pitched at certain courses and modules spiraled across the curriculum will enhance the learning experience of medical and health sciences students and HCPs [ 18 ].

Data availability

No datasets were generated or analysed during the current study.

Choudhury A, Asan O. Role of artificial intelligence in patient safety outcomes: systematic literature review. JMIR Med Inf. 2020;8(7):e18599.

Article   Google Scholar  

Higgins M, Madan CR, Patel R. Deliberate practice in simulation-based surgical skills training: a scoping review. J Surg Educ. 2021;78(4):1328–39.

Watts PI, McDermott DS, Alinier G, Charnetski M, Ludlow J, Horsley E, et al. Healthcare simulation standards of best practiceTM simulation design. Clin Simul Nurs. 2021;58:14–21.

Chrimes D, Moa B, Zamani H, Kuo M-H, editors. Interactive healthcare big data analytics platform under simulated performance. 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech); 2016: IEEE.

Bateman A, Wood M. Cloud computing. Oxford University Press; 2009. p. 1475.

Twist GP, Gaedigk A, Miller NA, Farrow EG, Willig LK, Dinwiddie DL, et al. Constellation: a tool for rapid, automated phenotype assignment of a highly polymorphic pharmacogene, CYP2D6, from whole-genome sequences. NPJ Genomic Med. 2016;1(1):1–10.

Winkler-Schwartz A, Bissonnette V, Mirchi N, Ponnudurai N, Yilmaz R, Ledwos N, et al. Artificial intelligence in medical education: best practices using machine learning to assess surgical expertise in virtual reality simulation. J Surg Educ. 2019;76(6):1681–90.

Li WT, Ma J, Shende N, Castaneda G, Chakladar J, Tsai JC, et al. Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis. BMC Med Inf Decis Mak. 2020;20:1–13.

Google Scholar  

Caffò AO, Tinella L, Lopez A, Spano G, Massaro Y, Lisi A, et al. The drives for driving simulation: a scientometric analysis and a selective review of reviews on simulated driving research. Front Psychol. 2020;11:917.

Hsieh M-C, Lee J-J. Preliminary study of VR and AR applications in medical and healthcare education. J Nurs Health Stud. 2018;3(1):1.

Forgione A, Guraya SY. The cutting-edge training modalities and educational platforms for accredited surgical training: a systematic review. J Res Med Sci. 2017;22(1):51.

Sulaiman N, Rishmawy Y, Hussein A, Saber-Ayad M, Alzubaidi H, Al Kawas S, et al. A mixed methods approach to determine the climate of interprofessional education among medical and health sciences students. BMC Med Educ. 2021;21:1–13.

Guraya SY, David LR, Hashir S, Mousa NA, Al Bayatti SW, Hasswan A, et al. The impact of an online intervention on the medical, dental and health sciences students about interprofessional education; a quasi-experimental study. BMC Med Educ. 2021;21:1–11.

Wei H, Corbett RW, Ray J, Wei TL. A culture of caring: the essence of healthcare interprofessional collaboration. J Interprof Care. 2020;34(3):324–31.

Organization WH. Global patient safety action plan 2021–2030: towards eliminating avoidable harm in health care. World Health Organization; 2021.

Guraya SS, Umair Akhtar M, Sulaiman N, David LR, Jirjees FJ, Awad M, et al. Embedding patient safety in a scaffold of interprofessional education; a qualitative study with thematic analysis. BMC Med Educ. 2023;23(1):968.

Supper I, Catala O, Lustman M, Chemla C, Bourgueil Y, Letrilliart L. Interprofessional collaboration in primary health care: a review of facilitators and barriers perceived by involved actors. J Public Health. 2015;37(4):716–27.

Guraya SS, Guraya SY, Al-Qahtani MF. Developing a framework of simulation-based medical education curriculum for effective learning. Med Educ. 2020;24(4):323–31.

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Vice Dean College of Medicine, University of Sharjah, Sharjah, United Arab Emirates

Salman Yousuf Guraya

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This is a sole author manuscript. Salman Guraya conceived, prepraed, revieweed, revised, and finalized this editorial artcile.

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Guraya, S.Y. Transforming simulation in healthcare to enhance interprofessional collaboration leveraging big data analytics and artificial intelligence. BMC Med Educ 24 , 941 (2024). https://doi.org/10.1186/s12909-024-05916-y

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Enhanced medical education for physically disabled people through integration of iot and digital twin technologies.

1. Introduction

1.1. research gap, 1.2. paper organization, 2. literature review, 3. iot service development using digital twin technology, 3.1. methodology, 3.2. detailing the dimension reduction outcomes, 3.3. crafting the visual response algorithm for digital twin development, 3.4. importance of testing for accurate data collection, 3.5. determining data points and assessing location impact, 3.6. the interplay of design variables and sample points, 3.7. striking a balance between test points and coefficients, 3.8. experimental design necessities for the second-order model.

• Those that integrate with external data, reading from data files to spawn data fields—termed reading source objects.
• Those that instigate data fields within the program, referred to as program source objects.
• Source: This is the starting point where raw data originates. In the context of IoT services, this could be sensors or other data-generating devices.
• Data object: Data from the source is encapsulated into data objects. These objects represent structured data packets that are ready for further processing.
• Filter: Data objects pass through filters which process and refine the data. Filters can perform various tasks such as noise reduction, data normalization, or extraction of relevant features. The diagram shows multiple filters, indicating sequential or parallel data processing stages.
• Mapper: After filtering, the data is passed to a mapper which transforms the processed data objects into a format suitable for visualization or further analysis. This is the final stage in the depicted process.

4. Experimental Analysis

• Operation and maintenance monitoring visualization.
• Information multi-terminal display visualization.
• IoT new service development visualization based on digital twin technology.

4.1. Test Platform’s Purpose and Goals

4.2. pre-experimental setup, 4.3. experimental outcomes, 5. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

• Liu, S.; Lu, S.; Li, J. Machining process-oriented monitoring method based on digital twin via augmented reality. Int. J. Adv. Manuf. Technol. 2021 , 113 , 3491–3508. [ Google Scholar ] [ CrossRef ]
• Mashaly, M. Connecting the twins: A review on Digital Twin technology & its networking requirements. Procedia Comput. Sci. 2021 , 184 , 299–305. [ Google Scholar ]
• Hetherington, J.; West, M. The Pathway Towards an Information Management Framework-A ‘Commons’ for Digital Built Britain ; CDBB: Cambridge, MA, USA, 2020. [ Google Scholar ]
• Guo, H.; Zhu, Y.; Zhang, Y.; Ren, Y.; Chen, M.; Zhang, R. A digital twin-based layout optimization method for discrete manufacturing workshop. Int. J. Adv. Manuf. Technol. 2021 , 112 , 1307–1318. [ Google Scholar ] [ CrossRef ]
• Levy, B.; El Mansori, M.; El Hadrouz, M.; Mezghani, S.; Beaudonnet, A.L.; Cabrero, J. Smart tribo-peening process for surface functionalization through digital twin concept. Int. J. Adv. Manuf. Technol. 2021 , 114 , 3695–3717. [ Google Scholar ] [ CrossRef ]
• Son, Y.H.; Park, K.T.; Lee, D.; Jeon, S.W.; Do Noh, S. Digital twin–based cyber-physical system for automotive body production lines. Int. J. Adv. Manuf. Technol. 2021 , 115 , 291–310. [ Google Scholar ] [ CrossRef ]
• Zhao, L.; Fang, Y.; Lou, P.; Yan, J.; Xiao, A. Cutting parameter optimization for reducing carbon emissions using digital twin. Int. J. Precis. Eng. Manuf. 2021 , 22 , 933–949. [ Google Scholar ] [ CrossRef ]
• Fu, Y.; Yang, X.; Yang, P. Energy-efficient offloading and resource allocation for mobile edge computing enabled mission-critical internet-of-things systems. EURASIP J. Wirel. Commun. Netw. 2021 , 2021 , 26. [ Google Scholar ] [ CrossRef ]
• Amudha, G. Dilated Transaction Access and Retrieval: Improving the Information Retrieval of Blockchain-Assimilated Internet of Things Transactions. Wirel. Pers. Commun. 2022 , 127 , 85–105. [ Google Scholar ] [ CrossRef ]
• Smith, J.; Brown, L. An Overview of Deep Learning Methods. J. Artif. Intell. Res. 2020 , 12 , 123–145. [ Google Scholar ]
• Kumar, A.; Gupta, S. Machine Learning Approaches in Medical Diagnosis. Healthc. Inform. 2019 , 15 , 98–110. [ Google Scholar ]
• Lee, K.; Park, H. Real-Time Object Detection Using YOLO. Sensors 2018 , 18 , 3785. [ Google Scholar ]
• Zhang, W.; Li, Y.; Wang, X. A Comprehensive Survey on Image Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 2021 , 43 , 293–312. [ Google Scholar ]
• Zhao, R.; Liu, J. Advances in Convolutional Neural Networks for Image Classification. Comput. Vis. Media 2020 , 6 , 145–163. [ Google Scholar ]
• Williams, P.; Smith, H. Review on Optimization Techniques in Deep Learning. J. Mach. Learn. 2020 , 22 , 457–480. [ Google Scholar ]
• Davis, T.; Roberts, K. Enhancing Video Surveillance with Deep Learning. Int. J. Comput. Vis. 2019 , 27 , 207–230. [ Google Scholar ]
• Johnson, M.; Wilson, E. Analyzing the Impact of Nadam Optimizer in Neural Networks. Neural Comput. Appl. 2021 , 33 , 1301–1315. [ Google Scholar ]
• Patel, V.; Mehta, R. Comparative Study of Object Detection Algorithms. J. Comput. Sci. 2018 , 14 , 89–102. [ Google Scholar ]
• Chandra, S.; Kumar, D. Implementation of Faster R-CNN in Autonomous Vehicles. Auton. Veh. Comput. 2020 , 19 , 52–70. [ Google Scholar ]
• Reddy, S.; Singh, A. Performance Analysis of Hybrid Deep Learning Models. Expert Syst. Appl. 2021 , 45 , 321–334. [ Google Scholar ]
• Thompson, L.; Hall, J. Survey on Video Surveillance Techniques. Multimed. Tools Appl. 2019 , 78 , 211–230. [ Google Scholar ]
• Dw, A.; Mw, A. Assisted development process for model-based systems engineering. Procedia CIRP 2021 , 99 , 610–614. [ Google Scholar ]
• Jill, R.; Tusarebecca, P.; Kirsten, H. Healthy Eating Index Protocol: Review, Update, and Development Process to Reflect Dietary Guidance across the Lifespan. Curr. Dev. Nutr. 2021 , 5 (Suppl. S2), 447. [ Google Scholar ]
• Yur’Ev, B.; Gol’Tsev, V.A.; Dudko, V. High Performance Process Development for Iron Ore Concentration. Solid State Phenom. 2021 , 316 , 276–281. [ Google Scholar ] [ CrossRef ]
• Cicchetti, D.; Luthar, S.S.; Burack, J.A. Unpacking complexities in ethnic–racial socialization in transracial adoptive families: A process-oriented transactional system. Dev. Psychopathol. 2021 , 33 , 493–505. [ Google Scholar ]
• Albers, A.; Holoch, J.; Revfi, S.; Spadinger, M. Lightweight design in product development: A conceptual framework for continuous support in the development process. Procedia CIRP 2021 , 100 , 494–499. [ Google Scholar ] [ CrossRef ]
• Kobayashi, M. Process development-Science Direct. In Dry Syngas Purification Processes for Coal Gasification Systems ; Elsevier: Amsterdam, The Netherlands, 2021; pp. 167–199. [ Google Scholar ]
• Müller, A.; Aydemir, M.; Solmaz, S.; Glodde, A.; Dietrich, F. Process development method for high-speed gluing and a battery-production case study. Procedia CIRP 2021 , 97 , 117–122. [ Google Scholar ] [ CrossRef ]
• Burkhart, J.; Breckle, T.; Merk, M.; Ramsaier, M.; Till, M.; Stetter, R. Customer-oriented digital design process for the development and production of an individual last-mile electric vehicle. Procedia CIRP 2021 , 100 , 542–547. [ Google Scholar ] [ CrossRef ]
• Busch, E.; Strobel, N.; Kai, N. Optimizing the innovation and development process of medical devices—A study based on angiographic equipment. Health Technol. 2021 , 11 , 563–574. [ Google Scholar ] [ CrossRef ]
• Gogoll, J.; Zuber, N.; Kacianka, S.; Greger, T.; Pretschner, A.; Nida-Rümelin, J. Ethics in the software development process: From codes of conduct to ethical deliberation. Philos. Technol. 2021 , 34 , 1085–1108. [ Google Scholar ] [ CrossRef ]
• Hallmann, M.; Schleich, B.; Wartzack, S. Sampling-based tolerance analysis: The key to establish tolerance-cost optimization in the product development process. Procedia CIRP 2021 , 100 , 560–565. [ Google Scholar ] [ CrossRef ]
• Rahatulain, A.; Qureshi, T.N.; Maffei, A.; Onori, M. Relationship and dependencies between factors affecting new product development process: An industrial case study. Procedia CIRP 2021 , 100 , 367–372. [ Google Scholar ] [ CrossRef ]
• Chao, H.; Chen, Z.; Rongtao, L.; Liang, D.; Dangdang, D.; Yue, G. Visual Monitoring Method of Digital Computer Room Based on Digital Twin. In Proceedings of the EAI International Conference, BigIoT-EDU 2023, Liuzhou, China, 28–30 August 2023; Springer: Cham, Switzerland, 2013; pp. 611–618. [ Google Scholar ]
• Abadi, M.; Abadi, C.; Abadi, A.; Ben-Azza, H. Digital Twin-Driven Approach for Smart Industrial Product Design. In Proceedings of the International Conference on Big Data and Internet of Things 2022, Tangier, Morocco, 25–27 October 2022; Springer: Cham, Switzerland, 2022; pp. 263–273. [ Google Scholar ]
• Sasikumar, A.; Vairavasundaram, S.; Kotecha, K.; Indragandhi, V.; Ravi, L.; Selvachandran, G.; Abraham, A. Blockchain-based trust mechanism for digital twin empowered Industrial Internet of Things. Future Gener. Comput. Syst. 2023 , 141 , 16–27. [ Google Scholar ]
• Mukherjee, P.P.; Afroj, M.; Hossain, S.; Biswas, M. Towards a Digital Twin Integrated DLT and IoT-Based Automated Healthcare Ecosystem. In Proceedings of the International Conference on Recent Trends in Image Processing and Pattern Recognition 2023, Derby, UK, 7–8 December 2023; Springer: Cham, Switzerland, 2023; pp. 311–323. [ Google Scholar ]

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Kumar, A.; Saudagar, A.K.J.; Khan, M.B. Enhanced Medical Education for Physically Disabled People through Integration of IoT and Digital Twin Technologies. Systems 2024 , 12 , 325. https://doi.org/10.3390/systems12090325

Kumar A, Saudagar AKJ, Khan MB. Enhanced Medical Education for Physically Disabled People through Integration of IoT and Digital Twin Technologies. Systems . 2024; 12(9):325. https://doi.org/10.3390/systems12090325

Kumar, Abhishek, Abdul Khader Jilani Saudagar, and Muhammad Badruddin Khan. 2024. "Enhanced Medical Education for Physically Disabled People through Integration of IoT and Digital Twin Technologies" Systems 12, no. 9: 325. https://doi.org/10.3390/systems12090325

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Published on 28.8.2024 in Vol 26 (2024)

Current Status of ChatGPT Use in Medical Education: Potentials, Challenges, and Strategies

Authors of this article:

• Tianhui Xu 1, 2 , MSN, RN   ; 
• Huiting Weng 1 , MSN, RN   ; 
• Fang Liu 1 , MSN, RN, PhD   ; 
• Li Yang 1 , MSN, RN   ; 
• Yuanyuan Luo 2 , MSN, RN   ; 
• Ziwei Ding 2 , MSN, RN   ; 
• Qin Wang 1, 2 , MSN, RN  

1 Clinical Nursing Teaching and Research Section, The Second Xiangya Hospital of Central South University, Changsha, China

2 Xiangya School of Nursing, Central South University, Changsha, China

Corresponding Author:

Qin Wang, MSN, RN

Clinical Nursing Teaching and Research Section

The Second Xiangya Hospital of Central South University

139 Middle Renmin Road

Changsha, 410011

Phone: 86 18774806226

Email: [email protected]

ChatGPT, a generative pretrained transformer, has garnered global attention and sparked discussions since its introduction on November 30, 2022. However, it has generated controversy within the realms of medical education and scientific research. This paper examines the potential applications, limitations, and strategies for using ChatGPT. ChatGPT offers personalized learning support to medical students through its robust natural language generation capabilities, enabling it to furnish answers. Moreover, it has demonstrated significant use in simulating clinical scenarios, facilitating teaching and learning processes, and revitalizing medical education. Nonetheless, numerous challenges accompany these advancements. In the context of education, it is of paramount importance to prevent excessive reliance on ChatGPT and combat academic plagiarism. Likewise, in the field of medicine, it is vital to guarantee the timeliness, accuracy, and reliability of content generated by ChatGPT. Concurrently, ethical challenges and concerns regarding information security arise. In light of these challenges, this paper proposes targeted strategies for addressing them. First, the risk of overreliance on ChatGPT and academic plagiarism must be mitigated through ideological education, fostering comprehensive competencies, and implementing diverse evaluation criteria. The integration of contemporary pedagogical methodologies in conjunction with the use of ChatGPT serves to enhance the overall quality of medical education. To enhance the professionalism and reliability of the generated content, it is recommended to implement measures to optimize ChatGPT’s training data professionally and enhance the transparency of the generation process. This ensures that the generated content is aligned with the most recent standards of medical practice. Moreover, the enhancement of value alignment and the establishment of pertinent legislation or codes of practice address ethical concerns, including those pertaining to algorithmic discrimination, the allocation of medical responsibility, privacy, and security. In conclusion, while ChatGPT presents significant potential in medical education, it also encounters various challenges. Through comprehensive research and the implementation of suitable strategies, it is anticipated that ChatGPT’s positive impact on medical education will be harnessed, laying the groundwork for advancing the discipline and fostering the development of high-caliber medical professionals.

Introduction

Artificial intelligence (AI) is the simulation of human cognitive capacities using computer programming, allowing robots to emulate human thought and behavior [ 1 ]. AI generation is the automated creation of various content formats, such as text, photos, video, and audio, using AI technologies. This approach generates content using language, visuals, and multimodal macro models [ 2 ]. Among these technologies, ChatGPT stands out as a sophisticated, large-scale language model developed by OpenAI, which has reached stage 4.0, the most recent iteration of the OpenAI system. ChatGPT, which has been trained on large amounts of textual data, is designed to participate in conversational exchanges with users while responding contextually to their prompts [ 3 ]. Particularly, ChatGPT has advanced capabilities in natural language processing, logical reasoning, task execution, information retrieval, picture analysis, content development, and other areas [ 4 ]. Moreover, ChatGPT provides a vast range of services accessible through global registration, facilitating its integration across various domains.

In the field of education, the introduction of ChatGPT has generated considerable interest and prompted in-depth discussions. Its exceptional generating capabilities offer new avenues for scholarly research, increased learning, classroom improvement, and knowledge sharing [ 5 ]. The incorporation of ChatGPT into medical education has become a major focus, with the goal of combining the advancements of education and medicine. In order to provide a well-informed assessment of the potential and limitations of integrating ChatGPT into medical education, this research aims to examine both the technology’s capabilities and the challenges it may present. Furthermore, tactics are put out to support the smooth integration of technology and medicine.

Status of ChatGPT in Medical Education

In this study, we searched the Web of Science database using specific terms related to ChatGPT and education or medical science within the timeframe of January 2022 to December 2024. The search formula is (“Chat generative pretrained transformer” OR “chat GPT” OR ChatGPT OR chat- GPT OR GPT-3.5 OR GPT-4.0”) AND (Education OR educate OR educator OR Students, Medical OR medical science OR medicine OR health care OR health science). We used CiteSpace v6.1R6 (64-bit) Basic to analyze the posted keywords [ 6 ]. The basic parameters used in CiteSpace were configured as follows: the time partition ranged from January 2022 to December 2024, with a one-time slice; the node selection criterion was set to k=25 for the g-index in each time slice, while the remaining parameters were kept at default settings. The top 7 keywords, ranked by frequency in the keyword network, are natural language processing, impact, academic integrity, AI in medicine, writing, health literacy, and health care professionals ( Figure 1 ), and the top 10 countries by publication volume are United States, India, China, Australia, England, Germany, Canada, Italy, Spain, and United Arab Emirates ( Figure 2 ).

Next, we will analyze the impact of ChatGPT and focus on its advantages, disadvantages, and coping strategies in the areas of education, academics, clinical decision-making, and health education.

A summary of the functions of ChatGPT and its potential role in the field of medical education is shown in Figure 3 .

Education Support

Academic assistance.

ChatGPT excels in both language understanding and content generation. It relies on semantic understanding and reasoning to decipher user intent through mutual dialog. In addition, by applying deep learning techniques, ChatGPT efficiently retrieves information from a variety of sources to provide consumers with reliable answers [ 7 ]. As a result, ChatGPT emerges as an invaluable resource for medical students, especially in helping them understand complex ideas. ChatGPT improves topic understanding by providing examples and conducting text analyses [ 8 ]. Furthermore, ChatGPT serves an important role in alleviating academic difficulty among medical students [ 9 ]. With its ability to produce and answer questions as well as assist with revision tasks, ChatGPT can help medical students complete coursework, assess the quality of their coursework, and reinforce previously learned concepts [ 10 ]. Serving as a personalized tutor, it develops customized learning programs and time management strategies based on individual interests and learning preferences [ 11 ]. In addition, renowned for its prowess in research and writing, ChatGPT contributes significantly to academic endeavors [ 12 ]. On one hand, it assists students in comprehensively exploring research literature, gaining a preliminary understanding of current research trends [ 13 ]. On the other hand, ChatGPT aids in structuring thesis frameworks and generating writing prompts, while also offering grammar and spelling checks to enhance writing proficiency and quality [ 14 ].

Scenario Simulation

ChatGPT has superior social features that allow it to replicate clinical settings for medical students through situational simulation and role-playing [ 15 ]. This functionality assists the transition of medical students from a theoretical to a clinical attitude. Furthermore, ChatGPT provides the potential to faithfully mimic clinical circumstances while dynamically adapting to changes in patients’ conditions [ 16 ]. This function lets students gain practical experience managing unexpected medical problems in simulated contexts, thereby improving their preparedness and psychological fortitude.

Curriculum Development

ChatGPT is crucial in educational curriculum development since it helps teachers enhance their logical thinking and task performance skills [ 17 ]. It assists teachers create lesson plans, course handouts, and lesson plan content, which accelerates curriculum development [ 13 ]. For example, we asked ChatGPT to create a teaching plan on pressure ulcer care, and the resulting content is presented in Figure 4 . Upon assessing the information, it is obvious that ChatGPT could generate core teaching plan content. However, teachers must supplement with more precise and detailed knowledge points, as well as validate the created information.

Furthermore, ChatGPT promotes innovation in teaching approaches by enabling scenario-based learning, role-playing, and the integration of diverse educational resources [ 18 ]. Recognizing the value of continuous pedagogical innovation, teachers are encouraged to apply the capabilities of AI, such as ChatGPT, alongside traditional teaching methods [ 19 ]. This integration allows for constant advancement in teaching approaches, which improves the effectiveness of teaching practices and enables educators to fulfill their instructional responsibilities more efficiently.

Clinical Support

ChatGPT plays a pivotal role in clinical support, standardizing procedures, aiding in disease diagnosis, and delivering health education. In terms of literature search and operational procedures, ChatGPT is capable of accessing the most recent literature and clinical guidelines [ 20 ]. This capability enables the provision of evidence-based best practices to health care professionals, facilitating the identification of current operational procedures and the enhancement of operational protocols [ 21 ]. Regarding disease diagnosis, ChatGPT can analyze patient data and test results, assisting doctors in diagnosing conditions and offering treatment recommendations [ 22 ]. In addition, it supports health care professionals in telemedicine by engaging in real-time communication with patients and providing remote diagnosis and treatment suggestions [ 23 ]. Moreover, ChatGPT serves as a valuable tool for patient health education. It can translate health education materials into multiple languages and deliver personalized health education using straightforward language, thereby aiding patients in understanding condition guidance and adopting healthier lifestyles [ 24 ].

Overall, ChatGPT enhances medical education by integrating essential functionalities into clinical support through standardized processes, aiding in disease diagnosis, and delivering health education [ 25 ]. This not only empowers health care professionals to provide medical services more efficiently but also provides students with a comprehensive and enriching learning experience, fostering the growth of medical professionals with practical skills and professional competence.

Disciplinary Development

The integration of AI and medicine represents a future frontier, characterized by the convergence of technological innovation and advancements in medical care [ 26 ]. This cross-disciplinary collaboration not only promotes technical advancement but also drives medical treatment to better intelligence and efficiency. Furthermore, it promotes the development of comprehensive capabilities in academic institutions that can navigate the junction of medicine and technology. In the future, coordinated activities in medical and technical domains have the potential to expedite technological innovation and move the field of medicine forward. This collaboration promises to usher in a new era of health care marked by innovation and efficiency, efficiently meeting society’s changing health needs [ 27 ]. ChatGPT advances medical education by enabling interdisciplinary collaboration and encouraging innovation at the confluence of medicine and technology.

Learning Dependency and Uneven Education

While ChatGPT can serve as a valuable learning aid by providing answers, assisting in understanding complex concepts, and offering personalized tutoring, excessive reliance on it can yield detrimental consequences in the long term [ 10 ]. Overdependence on ChatGPT may result in the erosion of critical thinking skills, creativity, and self-directed learning capabilities. The ease of obtaining answers quickly through ChatGPT may foster complacency among students, discouraging them from engaging in reflective problem-solving [ 28 ]. To mitigate this issue, students should proactively disclose which parts of their work were aided by ChatGPT, allowing teachers to assess the overall quality of assignments more accurately [ 10 ]. Failure to do so may lead to the perpetuation of an “information cocoon,” wherein students are only exposed to solutions that align with their existing preferences, hindering the exploration of diverse perspectives. Furthermore, the widespread adoption of ChatGPT may exacerbate educational inequalities. Developing and underdeveloped countries may lack the necessary technological infrastructure and resources to fully leverage ChatGPT, widening the educational gap between these regions and more developed countries [ 29 ]. Hence, it is crucial to address these challenges to ensure equitable access to educational resources and opportunities worldwide.

Copying and Plagiarism

When tackling assignments or final papers, students often seek to leverage technology to address challenges, enhance content, and elevate the overall quality of their work. ChatGPT, with its exceptional social capabilities and vast knowledge base, offers students the opportunity to obtain answers, prepare for exams, outline papers, and even complete them through mutual dialogue [ 29 ]. However, such practices are commonly perceived as copying answers and plagiarism, thereby contravening the fundamental principles of scientific research and academic integrity [ 30 ]. Moreover, ChatGPT encounters issues related to the fabrication of reference citations, as it may generate citations without verifiable sources, making it difficult for users to locate the original literature on academic platforms [ 31 ]. This inability to access and verify the sources provided by ChatGPT poses significant obstacles to maintaining academic integrity and conducting rigorous scholarly research [ 32 ].

It is noteworthy that Som Biswas, a radiologist in the United States, has authored 16 papers with ChatGPT, resulting in the publication of 6 articles across 4 journals [ 33 - 38 ]. Nevertheless, a thorough examination of the content by experts in the field has revealed significant inaccuracies, with all references found to be fictitious [ 39 ]. The editors of the journal Nature stated that while ChatGPT cannot be held accountable for the content and integrity of scientific studies, its contributions can be recognized [ 40 ]. Similarly, scientific journal editors claimed that using ChatGPT-generated content without adequate citations may be considered plagiarism, while contributions to ChatGPT might be acknowledged in the acknowledgments section [ 40 ]. Therefore, there is an urgent need to develop clearer criteria for distinguishing between authorized use and plagiarism when using ChatGPT assistance in academic research.

Insufficient Factualness, Timeliness, and Interpretability

ChatGPT’s credibility is not absolute, as it grapples with issues, such as illusion, poor timeliness, and interpretability, akin to other large language models [ 41 ]. Despite its impressive performance, ChatGPT has been known to generate convincing yet erroneous information, undermining its reliability, particularly in the health care domain. Furthermore, because its training data is only up to January 2022, its conclusions may not always be up to date [ 12 ]. Furthermore, ChatGPT lacks specialist medical knowledge and may struggle to understand complicated illness relationships [ 42 ]. Its algorithms function as a black box, providing findings without divulging the underlying mechanism, creating ambiguity about their applicability for health care applications [ 43 ]. While doctors may leverage ChatGPT for disease diagnosis to enhance clinical accuracy, the absence of evidence supporting diagnosis and treatment may leave patients questioning the reliability of the results.

Ethical Issues

While ChatGPT has the potential to revolutionize medical education, it also raises a number of ethical concerns. It is of the utmost importance to address issues, such as algorithmic discrimination, the allocation of responsibility for medical malpractice involving ChatGPT, and the safeguarding of data privacy and security [ 44 , 45 ].

ChatGPT displays algorithmic biases, including gender stereotypes, racial discrimination, and cultural insensitivity [ 46 ]. These biases not only undermine the model’s accuracy, fairness, and reliability, but they also perpetuate disparities in clinical health care [ 29 ]. Furthermore, ChatGPT’s inadequacies, such as inadequate timeliness, interpretability, and accuracy, increase the risk of incorrect clinical diagnoses, treatment protocols, and the transmission of incorrect information, risking patient care [ 47 ]. Furthermore, safeguarding patient privacy is critical in the therapeutic arena, mandating strict safeguards for sensitive patient data. Given that ChatGPT may share information, there may be a possibility of privacy breaches, as patient data are temporarily stored on Open AI’s servers [ 48 ]. This raises concerns regarding the potential leaking of patients’ private information, such as personal details, medical conditions, and examination results, while using ChatGPT for assisted diagnosis, treatment, and health education [ 49 ]. Hence, there is an urgent need to establish practical ethical norms to harness the value of ChatGPT while ensuring alignment with scientific and technological advancements and societal development goals. These norms should address concerns related to algorithmic biases, data privacy, accuracy, and accountability to foster responsible and ethical use of ChatGPT in health care and other domains [ 50 ].

Undermining Communication and Trust

Currently, research on the applications of ChatGPT for clinical communication and health education is limited, and the outcomes are not substantial [ 51 ]. Health care professionals’ humanistic care qualities, as well as the emotional rapport they build with patients, are critical components of disease treatment [ 49 ]. While ChatGPT can aid in accomplishing clinical tasks, it lacks emotion, empathy, and the capacity to perceive patient emotions. Therefore, health care professionals cannot depend on ChatGPT for communication and health education with patients [ 52 ]. This necessitates health care professionals integrating emotional value into patient interactions, fostering a more holistic approach to care, and combining the rationality of AI with the empathetic senses of health care providers. By striking a balance between technological assistance and human compassion, health care professionals can cultivate a patient-centric environment that addresses both medical needs and emotional well-being.

Table 1 summarizes the challenges and strategies of ChatGPT.

a XAI: explainable artificial intelligence .

Prevention of Overdependence

Delineate the relationship between individuals and chatgpt.

Humans remain the primary agents in social activities, with ChatGPT serving as a useful tool to aid them [ 53 ]. While students may use the answers and suggestions provided by ChatGPT, it is crucial that they engage in critical thinking and judgment to arrive at their conclusions [ 54 ].

Apprise the Limitations of ChatGPT

Despite students’ optimism toward ChatGPT [ 55 ], educators must underscore that it is not a panacea and guide students to adopt an objective and cautious stance [ 30 ]. Educators can focus on nurturing students’ independent thinking, creative problem-solving abilities, and information literacy skills. This includes cultivating habits of reading and lifelong learning, fostering critical thinking and effective communication, and enhancing independent problem-solving skills [ 21 ]. The ultimate goal is to empower students to transition from mere questioners to creators and decision makers [ 56 ].

Optimize Curriculum Design

This can include introducing a teacher-student-machine interaction paradigm for instruction, giving courses on AI, and experimenting with new assignment forms and evaluation methodologies [ 57 ].

• Integrating ChatGPT into the medical curriculum: problem-based learning allows students to analyze clinical problems, encouraging proactive thinking, and comparing their own ideas to those generated by ChatGPT [ 58 ]. This comparison encourages students to reflect on the strengths and limitations of both human-generated and AI-generated solutions, fostering a deeper understanding of clinical reasoning and decision-making processes. In addition to integrating ChatGPT with problem-based learning, it can also be combined with other instructional methods, such as case-based learning, team-based learning, group meetings, etc [ 59 ]. By using diverse teaching modalities, critical thinking and innovative thinking among students can be nurtured.
• Update the methods for assessing assignments and grades. Educators might replace typical writing tasks with presentation reports, oral debates, group discussions, and peer reviews [ 17 ]. Encouraging students to preserve transcripts of their interactions using ChatGPT can also help [ 31 ]. Rather than relying on ChatGPT for direct responses, emphasizing knowledge and competency allows students to interact more deeply and think critically.

Academic Integrity

Guide proper use.

ChatGPT has distinct advantages, and it is critical not to restrict students from using it totally, but rather to guide them to use right [ 60 ]. Thus, improving the quality of student learning is critical. In terms of educational orientation, teachers ought to lead students toward developing appropriate values about science and technology. Prioritizing education on academic integrity is crucial, with a focus on reiterating the basic principles and ethical boundaries of scientific research, enhancing awareness of academic ethics and integrity, and deepening reverence for science. In addition, organizations and institutions can conduct academic integrity seminars to educate individuals about the ethical use of ChatGPT [ 57 ]. Educators should also educate students about the consequences and repercussions of violating research integrity.

Evaluate and Review the Content

The text produced by ChatGPT should be evaluated and reviewed to ensure academic accuracy and integrity [ 61 ]. Developing specialized software or using fake text detection technologies created particularly to recognize text generated by ChatGPT can help detect whether a communication contains faked or nonsensical text [ 62 ]. To ensure that the answers are correct, they must be approached with reasonable skepticism and verified for accuracy. It is also vital to clearly identify which pieces came from ChatGPT. For example, using plagiarism detection software allows students to ensure that the information generated by ChatGPT does not infringe on other people’s academic work, lowering the danger of plagiarism and ensuring the accuracy and authenticity of cited references [ 63 ].

Develop Guidelines and Regulatory Mechanisms

Stakeholders can collaborate to create relevant recommendations for the standardized use of ChatGPT [ 64 ]. Simultaneously, implementing a corresponding management system can enhance the management approach by providing training, education, assessment, review, feedback, and improvement activities to ensure the ethical use of ChatGPT [ 65 ].

Model Enhancement

Enhance and tailor training methodologies.

While ChatGPT boasts significant power, its susceptibility to hallucination poses a challenge to its credibility. However, effective mitigation of this issue and refinement of its specialization could unlock limitless potential in the medical domain [ 66 ]. Using regular input of data into the model or using transfer learning can effectively augment a vast, diverse, accurate, and high-quality training dataset, thereby enhancing the performance of ChatGPT [ 67 ].

Improve Accuracy

Through fine-tuning or reinforcement learning, the process of continuously incorporating user feedback, collecting and analyzing suggestions, and reintegrating ChatGPT resources is achieved to sustainably improve ChatGPT performance [ 62 ]. Collecting feedback on ChatGPT responses allows for iterative adjustments and enhancements to the model’s accuracy [ 68 ]. Timely updates of data, especially for time-sensitive matters, facilitate a more accurate understanding of queries and the generation of relevant answers. For instance, regular updates on clinical data, research findings, expert consensus, and medical guidelines can effectively inform clinical practice.

Improve Transparency and Interpretability

ChatGPT's transparency can be improved by creating visual interfaces, generating human-machine interaction code, and using explainable AI techniques [ 8 ]. Increased openness builds confidence between humans and robots. Not only does it help medical workers understand the model’s decision-making process, but it also allows for improved evaluation and interpretation of generated outcomes, lowering the risk of medical errors [ 69 ]. Incorporating transparency measures is thus critical for increasing ChatGPT’s use in medical settings.

Emphasizing Ethical Issues

Value alignment is a contentious subject in ChatGPT, with the goal of aligning its capabilities and actions with human objectives, ethical standards, and values in order to promote safety and confidence in human-ChatGPT cooperation. The top 3 ethical concerns related to ChatGPT include algorithmic discrimination, medical liability allocation, and privacy and security difficulties [ 49 ].

Address Algorithmic Discrimination

To address algorithmic bias, on the one hand, incorporating diverse and balanced samples for large-scale training can enhance ChatGPT’s fairness awareness [ 70 ]. On the other hand, using explainable AI can help identify biased patterns in ChatGPT while implementing fair models [ 8 ]. Furthermore, continuous review and quality improvement can minimize gender and racial discrimination in the health care sector to the greatest extent possible [ 44 ].

Assign Responsibility

Clear responsibility allocation is paramount when collaborating with ChatGPT for clinical disease diagnosis and health education. In other words, ensuring maximum safety in the clinical use of ChatGPT requires explicit delineation of responsibilities. Health care professionals using ChatGPT for decision support should actively engage in its decision-making process and critically assess its recommendations. Collaboration between health care professionals and ChatGPT can enhance decision-making accuracy [ 71 ]. Patients’ right to information should be upheld. Organizations and institutions must ensure ChatGPT’s responsible participation in treatment and adherence to ethical standards [ 72 ].

Protecting Personal Privacy and Information Data

Measures such as analogously asking ChatGPT questions to conceal original motives, implementing manual review mechanisms for uploaded information, data encryption, and anonymization can mitigate privacy risks [ 73 ]. Compliance with privacy laws and regulations is essential to secure patient privacy and medical information, ensuring data handling and storage integrity [ 43 ]. Establishing clear guidelines, ethical frameworks, and institutional norms for data collection, storage, and use is crucial [ 66 ].

Irreplaceability of Medical Personnel and Educators

Humanistic care and emotional support from health care professionals.

While ChatGPT has the potential to enhance access to primary health care in underdeveloped regions and streamline repetitive tasks for medical staff, it cannot be considered a substitute for health care professionals in any capacity [ 13 ]. ChatGPT is devoid of the attributes that are typically associated with independent consciousness, ethical standards, emotional empathy, and the capacity to anticipate unforeseen circumstances. The interpersonal communication between health care professionals and patients, as well as the emotional support and humanistic care that are provided in person, cannot be replicated by ChatGPT [ 74 ]. Furthermore, medical professionals provide invaluable empirical assistance and support to patients based on their clinical experience, which enhances the quality of clinical services. This is a capability that ChatGPT does not possess [ 74 ]. Consequently, ChatGPT should be regarded as a valuable adjunct to the work of medical personnel in clinical settings, rather than as a replacement for human health care providers.

Teacher’s Quality Education

Education fosters individual growth, community advancement, and the continuation of human civilization. While ChatGPT has effectively helped to progress education by equalizing and enriching instructional resources, it is still only a tool for teachers, and not a replacement [ 75 ]. Teachers have distinct powers that ChatGPT lacks. They practice student-centered teaching and help kids develop moral qualities and abilities like ideals, beliefs, values, critical thinking, emotional intelligence, and creativity. Furthermore, people are naturally social animals that require interpersonal interactions to thrive and find spiritual fulfillment.

In conclusion, despite the benefits of ChatGPT, technology cannot replace humans in health care and education. Our individual features and capacities allow us to maintain social value in an era of rapid developments in AI.

ChatGPT has demonstrated considerable potential in medical education, but it has also introduced a number of thought-provoking difficulties. As ChatGPT advances, it may present new obstacles and opportunities. On a worldwide basis, cultural diversity is under peril. ChatGPT disseminates information based on the training data it gets, making well-known and popular information more easily shared and transferred. However, this has the tendency to marginalize niche or local cultures and languages, hence reducing cultural variety. Roles in the health care sector may change. The increased implementation of automation and intelligent technologies may result in the displacement of positions, such as primary diagnostic personnel and imaging diagnostics. But this might also open new career paths for professionals with expertise in medical AI and information management. Promoting AI technology development in developing nations can help advance fields, such as the creation of diagnostic software.

It is imperative that we approach ChatGPT with caution and subject it to critical evaluation, weighing its benefits against its drawbacks. This paper presents a dialectical examination of the current state of ChatGPT application in medical education, conducting an in-depth analysis of its advantages and the dilemmas it presents. In addition, targeted strategies are proposed to address these challenges effectively. The aim is to standardize and rationalize ChatGPT’s maximum potential in the future, paving the way for innovative approaches in medical education and contributing to the advancement of medicine.

Acknowledgments

This work was supported by the National Key Research and Development Program of China (2021-HLKY-06) and the Clinical Nursing Research Fund Project of the Second Xiangya Hospital, Central South University (2021-HLKY-06), People’s Republic of China.

Authors' Contributions

TX performed the conceptualization of topics, analysis and interpretation of the image, and writing of the paper. QW and HW supervised and controlled writing quality. FL and LY contributed to project administration. YL and ZD monitored and regulated the project.

Conflicts of Interest

None declared.

• Holmes JH, Sacchi L, Bellazzi R, Peek N. Artificial intelligence in medicine AIME 2015. Artif Intell Med. Sep 2017;81:1-2. [ CrossRef ] [ Medline ]
• Wiggins WF, Tejani AS. On the opportunities and risks of foundation models for natural language processing in radiology. Radiol Artif Intell. Jul 2022;4(4):e220119. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kurian N, Cherian JM, Sudharson NA, Varghese KG, Wadhwa S. AI is now everywhere. Br Dent J. Jan 2023;234(2):72. [ CrossRef ] [ Medline ]
• Ruiz-Rojas LI, Acosta-Vargas P, De-Moreta-Llovet J, Gonzalez-Rodriguez M. Empowering education with generative artificial intelligence tools: approach with an instructional design matrix. Sustainability. Jul 2023;15(15):11524. [ CrossRef ]
• Lin X. Exploring the role of ChatGPT as a facilitator for motivating self-directed learning among adult learners. Adult Learning. 2023;35(3):156-166. [ CrossRef ]
• Chen C. CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci. 2006;57(3):359-377. [ CrossRef ]
• Vitorino LM, Júnior GHY. ChatGPT and the teaching of contemporary nursing: and now professor? J Clin Nurs. Nov 2023;32(21-22):7921-7922. [ CrossRef ] [ Medline ]
• Khennouche F, Elmir Y, Himeur Y, Djebari N, Amira A. Revolutionizing generative pre-traineds: insights and challenges in deploying ChatGPT and generative chatbots for FAQs. Expert Systems with Applications. 2024;246:123224. [ CrossRef ]
• Chan MMK, Wong ISF, Yau SY, Lam VSF. Critical reflection on using ChatGPT in student learning: benefits or potential risks? Nurse Educ. 2023;48(6):E200-E201. [ CrossRef ] [ Medline ]
• Labadze L, Grigolia M, Machaidze L. Role of AI chatbots in education: systematic literature review. Int J Educ Technol High Educ. Oct 2023;20(1):56. [ CrossRef ]
• Thakur A, Parikh D, Thakur A. ChatGPT in nursing education: is there a role for curriculum development? Teaching and Learning in Nursing. Apr 2023;18(3):450-451. [ CrossRef ]
• Gandhi Periaysamy A, Satapathy P, Neyazi A, Padhi BK. ChatGPT: roles and boundaries of the new artificial intelligence tool in medical education and health research - correspondence. Ann Med Surg (Lond). Mar 2023;85(4):1317-1318. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Lee H. The rise of ChatGPT: exploring its potential in medical education. Anat Sci Educ. 2024;17(5):926-931. [ CrossRef ] [ Medline ]
• Seetharaman R. Revolutionizing medical education: can ChatGPT boost subjective learning and expression? J Med Syst. 2023;47(1):61. [ CrossRef ] [ Medline ]
• Mohammad B, Supti T, Alzubaidi M, Shah H, Alam T, Shah Z, et al. The pros and cons of using ChatGPT in medical education: a scoping review. Stud Health Technol Inform. 2023;305:644-647. [ CrossRef ] [ Medline ]
• Hobert S. Say hello to coding tutor design and evaluation of a Chatbot-based learning system supporting students to learn to program. 2019. Presented at: Fortieth International Conference on Information Systems; 2019 December 15-18:1-17; Munich, Germany.
• Sun GH, Hoelscher SH. The ChatGPT storm and what faculty can do. Nurse Educ. 2023;48(3):119-124. [ CrossRef ] [ Medline ]
• Memarian B, Doleck T. ChatGPT in education: methods, potentials, and limitations. Computers in Human Behavior: Artificial Humans. 2023;1(2):100022. [ CrossRef ]
• Irwin P, Jones D, Fealy S. What is ChatGPT and what do we do with it? Implications of the age of AI for nursing and midwifery practice and education: an editorial. Nurse Education Today. Aug 2023;127:105835. [ CrossRef ] [ Medline ]
• Odom-Forren J. The role of ChatGPT in perianesthesia nursing. J Perianesth Nurs. Apr 2023;38(2):176-177. [ CrossRef ] [ Medline ]
• Baumgartner C. The potential impact of ChatGPT in clinical and translational medicine. Clin Transl Med. Mar 2023;13(3):e1206. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ferdush J, Begum M, Hossain ST. ChatGPT and clinical decision support: scope, application, and limitations. Ann Biomed Eng. Jul 2024;52(5):1119-1124. [ CrossRef ] [ Medline ]
• Sharma M, Sharma S. A holistic approach to remote patient monitoring, fueled by ChatGPT and metaverse technology: the future of nursing education. Nurse Educ Today. Dec 2023;131:105972. [ CrossRef ] [ Medline ]
• Moons P, Van Bulck L. ChatGPT: can artificial intelligence language models be of value for cardiovascular nurses and allied health professionals. Eur J Cardiovasc Nurs. Oct 2023;22(7):e55-e59. [ CrossRef ] [ Medline ]
• Khan RA, Jawaid M, Khan AR, Sajjad M. ChatGPT - reshaping medical education and clinical management. Pak J Med Sci. 2023;39(2):605-607. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wang Y, Li N, Chen L, Wu M, Meng S, Dai Z, et al. Guidelines, consensus statements, and standards for the use of artificial intelligence in medicine: systematic review. J Med Internet Res. Nov 2023;25:e46089. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ahmed Y, Ireland S. Utilization of ChatGPT in medical education: applications and implications for curriculum enhancement. Acta Inform Med. 2023;31(4):300-305. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Abdulai A, Hung L. Will ChatGPT undermine ethical values in nursing education, research, and practice? Nurs Inq. Jul 2023;30(3):e12556. [ CrossRef ] [ Medline ]
• Liu J, Liu F, Fang J, Liu S. The application of chat generative pre-trained transformer in nursing education. Nurs Outlook. 2023;71(6):102064. [ CrossRef ] [ Medline ]
• Choi EPH, Lee JJ, Ho M, Kwok JYY, Lok KYW. Chatting or cheating? The impacts of ChatGPT and other artificial intelligence language models on nurse education. Nurse Educ Today. Jun 2023;125:105796. [ CrossRef ] [ Medline ]
• Meyer JG, Urbanowicz RJ, Martin PCN, O'Connor K, Li R, Peng PC, et al. ChatGPT and large language models in academia: opportunities and challenges. BioData Min. Jul 2023;16(1):20. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Dashti M, Londono J, Ghasemi S, Moghaddasi N. How much can we rely on artificial intelligence chatbots such as the ChatGPT software program to assist with scientific writing? The Journal of Prosthetic Dentistry. Jul 2023;S0022-3913(23):00371-00372. [ CrossRef ]
• Biswas S, Dobaria D, Cohen HL. ChatGPT and the future of journal reviews: a feasibility study. Yale J Biol Med. Sep 2023;96(3):415-420. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Biswas S. ChatGPT and the future of medical writing. Radiology. Apr 2023;307(2):e223312. [ CrossRef ] [ Medline ]
• Biswas S. Passing is great: can ChatGPT conduct USMLE exams? Ann Biomed Eng. Sep 2023;51(9):1885-1886. [ CrossRef ] [ Medline ]
• Biswas SS. Potential use of chat GPT in global warming. Ann Biomed Eng. Jun 2023;51(6):1126-1127. [ CrossRef ] [ Medline ]
• Perera Molligoda Arachchige AS, Biswas S. Re: potential applications and impact of ChatGPT in radiology. Acad Radiol. Nov 2023;S1076-S6332(23):00601-00603. [ CrossRef ] [ Medline ]
• Biswas SS. Role of Chat GPT in public health. Ann Biomed Eng. May 2023;51(5):868-869. [ CrossRef ] [ Medline ]
• Ariyaratne S, Iyengar KP, Nischal N, Chitti Babu N, Botchu R. A comparison of ChatGPT-generated articles with human-written articles. Skeletal Radiol. Nov 2023;52(9):1755-1758. [ CrossRef ]
• Stokel-Walker C. ChatGPT listed as author on research papers: many scientists disapprove. Nature. Jan 2023;613(7945):620-621. [ CrossRef ] [ Medline ]
• Wu T, He S, Liu J, Sun S, Liu K, Han Q, et al. A brief overview of ChatGPT: the history, status quo and potential future development. IEEE/CAA J. Autom. Sinica. May 2023;10(5):1122-1136. [ CrossRef ]
• Cascella M, Montomoli J, Bellini V, Bignami E. Evaluating the feasibility of ChatGPT in healthcare: an analysis of multiple clinical and research scenarios. J Med Syst. Mar 2023;47(1):33. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Li J. Security implications of AI Chatbots in health care. J Med Internet Res. 2023;25:e47551. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ray PP, Majumder P. The potential of ChatGPT to transform healthcare and address ethical challenges in artificial intelligence-driven medicine. J Clin Neurol. Nov 2023;19(5):509-511. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ali MJ, Djalilian A. Readership awareness series - paper 4: Chatbots and ChatGPT - ethical considerations in scientific publications. Ocul Surf. Apr 2023;28:153-154. [ CrossRef ] [ Medline ]
• Arshad HB, Butt SA, Khan SU, Javed Z, Nasir K. ChatGPT and artificial intelligence in hospital level research: potential, precautions, and prospects. Methodist Debakey Cardiovasc J. Nov 2023;19(5):77-84. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Sridi C, Brigui S. The use of ChatGPT in occupational medicine: opportunities and threats. Ann Occup Environ Med. Oct 2023;35:e42. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Berşe S, Akça K, Dirgar E, Kaplan Serin E. The role and potential contributions of the artificial intelligence language model ChatGPT. Ann Biomed Eng. Feb 2024;52(2):130-133. [ CrossRef ] [ Medline ]
• Wang C, Liu S, Yang H, Guo J, Wu Y, Liu J. Ethical considerations of using ChatGPT in health care. J Med Internet Res. Aug 2023;25:e48009. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Liu J, Chen C, Qu Y, Yang S, Xu L. RASS: enabling privacy-preserving and authentication in online AI-driven healthcare applications. ISA Trans. 2023;141:20-29. [ CrossRef ] [ Medline ]
• Abd-Alrazaq AA, Rababeh A, Alajlani M, Bewick BM, Househ M. Effectiveness and safety of using Chatbots to improve mental health: systematic review and meta-analysis. J Med Internet Res. Jul 2020;22(7):e16021. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Scerri A, Morin KH. Using chatbots like ChatGPT to support nursing practice. J Clin Nurs. Aug 2023;32(15-16):4211-4213. [ CrossRef ] [ Medline ]
• Busch F, Adams LC, Bressem KK. Biomedical ethical aspects towards the implementation of artificial intelligence in medical education. Med Sci Educ. Jun 2023;33(4):1007-1012. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Shoufan A. Exploring students’ perceptions of ChatGPT: thematic analysis and follow-up survey. IEEE Access. 2023;11:38805-38818. [ CrossRef ]
• Moldt JA, Festl-Wietek T, Madany Mamlouk A, Nieselt K, Fuhl W, Herrmann-Werner A. Chatbots for future docs: exploring medical students' attitudes and knowledge towards artificial intelligence and medical chatbots. Med Educ Online. Dec 2023;28(1):2182659. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Farrokhnia M, Banihashem SK, Noroozi O, Wals A. A SWOT analysis of ChatGPT: implications for educational practice and research. Innovations in Education and Teaching International. 2023;61(3):460-474. [ CrossRef ]
• Abd-Alrazaq A, AlSaad R, Alhuwail D, Ahmed A, Healy PM, Latifi S, et al. Large language models in medical education: opportunities, challenges, and future directions. JMIR Med Educ. Jun 2023;9:e48291. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Divito CB, Katchikian BM, Gruenwald JE, Burgoon JM. The tools of the future are the challenges of today: the use of ChatGPT in problem-based learning medical education. Med Teach. 2024;46(3):320-322. [ CrossRef ] [ Medline ]
• Wu Y, Zheng Y, Feng B, Yang Y, Kang K, Zhao A. Embracing ChatGPT for medical education: exploring its impact on doctors and medical students. JMIR Med Educ. 2024;10:e52483. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Harrison LM, Hurd E, Brinegar KM. Critical race theory, books, and ChatGPT: moving from a ban culture in education to a culture of restoration. Middle School Journal. 2023;54(3):2-4. [ CrossRef ]
• Jeyaraman M, Ramasubramanian S, Balaji S, Jeyaraman N, Nallakumarasamy A, Sharma S. ChatGPT in action: harnessing artificial intelligence potential and addressing ethical challenges in medicine, education, and scientific research. World J Methodol. Sep 2023;13(4):170-178. [ CrossRef ]
• Sohail SS, Farhat F, Himeur Y, Nadeem M, Madsen D, Singh Y, et al. Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions. Journal of King Saud University - Computer and Information Sciences. 2023;35(8):101675. [ CrossRef ]
• Vignesh R, Pradeep P, Balakrishnan P. A tête-à-tête with ChatGPT on the impact of artificial intelligence in medical education. Med J Malaysia. Jul 2023;78(4):547-549. [ FREE Full text ] [ Medline ]
• Shoja MM, Van de Ridder JMM, Rajput V. The emerging role of generative artificial intelligence in medical education, research, and practice. Cureus. Jun 2023;15(6):e40883. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kleebayoon A, Wiwanitkit V. ChatGPT and the teaching of contemporary nursing: Comment. J Clin Nurs. Oct 2023;32(19-20):7642. [ CrossRef ] [ Medline ]
• Thapa S, Adhikari S. ChatGPT, Bard, and large language models for biomedical research: opportunities and pitfalls. Ann Biomed Eng. Dec 2023;51(12):2647-2651. [ CrossRef ] [ Medline ]
• Al-Hasan TM, Sayed AN, Bensaali F, Himeur Y, Varlamis I, Dimitrakopoulos G. From traditional recommender systems to GPT-based chatbots: a survey of recent developments and future directions. BDCC. Mar 2024;8(4):36. [ CrossRef ]
• Lo CK. What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences. 2023;13(4):410. [ CrossRef ]
• Liu J, Wang C, Liu S. Utility of ChatGPT in clinical practice. J Med Internet Res. Jun 2023;25:e48568. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Stahl BC, Eke D. The ethics of ChatGPT – exploring the ethical issues of an emerging technology. International Journal of Information Management. Feb 2024;74:102700. [ CrossRef ]
• Woodnutt S, Allen C, Snowden J, Flynn M, Hall S, Libberton P, et al. Could artificial intelligence write mental health nursing care plans? J Psychiatr Ment Health Nurs. Feb 2024;31(1):79-86. [ CrossRef ] [ Medline ]
• Paranjape K, Schinkel M, Nannan Panday R, Car J, Nanayakkara P. Introducing artificial intelligence training in medical education. JMIR Med Educ. 2019;5(2):e16048. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Li J. A privacy preservation model for health-related social networking sites. J Med Internet Res. 2015;17(7):e168. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wójcik S, Rulkiewicz A, Pruszczyk P, Lisik W, Poboży M, Domienik-Karłowicz J. Beyond ChatGPT: what does GPT-4 add to healthcare? The dawn of a new era. Cardiol J. Oct 2023;30(6):1018-1025. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Reiss M. The use of Al in education: practicalities and ethical considerations. London Review of Education. Feb 2021;19(1):15. [ CrossRef ]

Abbreviations

Edited by G Eysenbach, T de Azevedo Cardoso; submitted 29.02.24; peer-reviewed by H Zhai, Y Himeur; comments to author 11.04.24; revised version received 05.06.24; accepted 29.06.24; published 28.08.24.

©Tianhui Xu, Huiting Weng, Fang Liu, Li Yang, Yuanyuan Luo, Ziwei Ding, Qin Wang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.08.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Communities of microorganisms and invertebrates in soil-like bodies of soccer fields in Moscow oblast

• Soil Biology
• Published: 06 November 2014
• Volume 47 , pages 1107–1115, ( 2014 )

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• O. V. Kutovaya 1 ,
• I. V. Zamotaev 2 &
• V. P. Belobrov 1  

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Artificially created soil-like technogenic formations (STFs) of soccer fields are developed under combined action of intense technogenic and natural factors and processes, which cannot but affect the structure and biological activity of their microbial communities and mesofauna. The microflora of the STFs is very similar to the microflora of the background soddy-podzolic soils of Moscow oblast with respect to the composition of the physiological groups of microorganisms. However, they are drastically different in their quantitative characteristics. The numbers of all the trophic groups of microorganisms, except for the microscopic fungi, in the STFs are much higher than those in the zonal soils. An increased biological activity of the STFs is due to regular watering, heating, application of sand and mineral fertilizers, and technogenic turbation processes. The mesofauna of the STFs is represented by several ecological groups of earthworms, including soildwelling (endogeic) earthworms ( Aporrectodea caliginosa ), epigeic earthworms dwelling at the soil-litter interface ( Lumbricus rubellus ), and litter-dwelling earthworms ( Eisenia foetida ).

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G. G. Abramashvili, Sports Lawns. Methodological Guidelines for Employees of Stadiums and Sports Bases Exploiting Soccer Fields (Sovetskii sport, Moscow, 1988) [in Russian].

Google Scholar  

A. L. Aleksandrovskii and E. I. Aleksandrovskaya, Soil Evolution and the Geographic Environment (Nauka, Moscow, 2005) [in Russian].

V. N. Bashkin and N. S. Kasimov, Biogeochemistry (Nauchn. mir, Moscow, 2004) [in Russian].

O. S. Bezuglova, S. N. Gorbov, A. V. Gorovtsov, et al., “Agrochemical and microbiological properties of constructozems of golf courses and their impact on the state of the lawns,” Probl. Agrokhim. Ekolog., No. 4, 14–17 (2012).

O. S. Bezuglova, S. N. Gorbov, I. V. Morozov, and D. G. Nevidomskaya, Urbopedology: A Textbook (Izd. Yuzhn. Fed. Univ., Rostov-on-Don, 2012) [in Russian].

V. P. Belobrov and I. V. Zamotaev, Soils and Green Lawns of Sports and Technical Constructions (GEOS, Moscow, 2007) [in Russian].

V. P. Belobrov, I. V. Zamotaev, and A. Yu. Kulenkamp, “Pedogenic and technogenic processes in artificial recreation landscapes of Russia,” Dokl. RASKhN, No. 2, 35–38 (2002).

V. A. Bol’shakov, V. P. Belobrov, and L. L. Shishov, Terms, Their Concise Definitions, and Reference Materials on General and Soil Ecology and on the Geography and Classification of Soils (Pochven. Inst. im. V.V. Dokuchaeva RASKhN, Moscow, 2004) [in Russian].

B. A. Byzov, Zoomicrobial Interactions in Soils (GEOS, Moscow, 2005) [in Russian].

E. S. Vasilenko, I. S. Prokhorov, and A. Yu. Sementsov, “Microbiological processes upon the construction of artificial soils,” Agrokhim. Vestn., No. 5, 20–24 (2006).

T. S. Vsevolodova-Perel’, Earthworms of Russian Fauna: Cadaster and Determinative Guide (Nauka, Moscow, 1997) [in Russian].

M. I. Gerasimova, M. N. Stroganova, N. V. Mozharova, and T. V. Prokof’eva, Anthropogenic Soils (Genesis, Geography, and Reclamation) (Izd. Mosk. Gos. Univ., Moscow, 2003) [in Russian].

M. S. Gilyarov, “Dwelling conditions for invertebrates of different size groups in soil,” in Methods of Soil Zoology (Nauka, Moscow, 1975), pp. 7–12 [in Russian].

M. A. Glazovskaya, “Biotic and abiotic factors in the organization of soil biota and morphogenesis of soils,” in Soil Science: History, Sociology, and Methodology , Ed. by V. N. Kudeyarov and I. V. Ivanov (Nauka, Moscow, 2005), pp. 243–257 [in Russian].

M. I. Gol’din and K. Ya. Lyal’chenko, A Soccer Field. Construction and Exploitation (Fizkul’tura i sport, Moscow, 1971) [in Russian].

I. L. Gol’dfarb, Extended Abstract of Candidate’s Dissertation in Geography (Moscow, 2005).

I. S. Goryachkina, A. A. Rakhleeva, M. N. Stroganova, and A. V. Rappoport, “Soil mesofauna of botanical gardens (by the example of Moscow and Saint Petersburg),” Vestn. Mosk Univ., Ser. 17: Pochvoved., No. 4, 33–40 (2003).

T. G. Dobrovol’skaya, A. V. Golovchenko, T. A. Pankratov, L. V. Lysak, D. G. Zvyagintsev, “Assessment of the bacterial diversity in soils: evolution of approaches and methods,” Eur. Soil Sci. 42 (10), 1138–1147 (2009).

Article   Google Scholar  

I. V. Zamotaev, Extended Abstract of Doctoral Dissertation in Geography (Moscow, 2009).

I. V. Zamotaev, “Factors of soil formation on soccer fields,” Vestn. MGPU, No. 3, 15–32 (2008).

I. V. Zamotaev and V. P. Belobrov, “Technopedogenesis on artificially formed substrates of soccer fields,” Ekolog. Planirov. Upravlen., No. 3(4), 48–63 (2007).

I. V. Zamotaev, V. P. Belobrov, V. T. Dmitrieva, and D. L. Shevelev, Technopedogenesis on Soccer Fields of Russia (Media-PRESS, Moscow, 2012) [in Russian].

I. V. Zamotaev and D. L. Shevelev, “Sports technogenesis as a factor of soil formation,” Probl. Region. Ekolog., No. 6, 268–274 (2009).

D. G. Zvyagintsev, T. G. Dobrovol’skaya, I. P. Bab’eva, G. M. Zenova, L. V. Lysak, “The role of microorganisms in the biogeocenotic functions of soils,” in The Structural-Functional Role of Soils in the Biosphere (GEOS, Moscow, 1999) [in Russian].

F. A. Ivannikov, Extended Abstract of Candidate’s Dissertation in Biology (Moscow, 2012).

A. E. Ivanova, I. S. Sukhanova, and O. E. Marfenina, “Ecotrophic groups of fungi in urban soils of different ages,” Materials of the V All-Russia Soil Sci. Congr. (Rostov-on-Don, 2008), p. 436 [in Russian].

T. K. Il’ina and O. M. Fomina, USSR Inventor’s Certificate No. 1, 3328.

N. A. Karavaeva, “Agrogenic soils: environmental conditions, properties, and processes,” Eur. Soil Sci. 38 (12), 1355–1365 (2005).

N. A. Karavaeva, “Soil climate in the boreal zonal series of natural and agrolandscapes,” in Multifaceted Geography: The Development of Ideas of Innokentii Petrovich Gerasimov (on the Centennial Anniversary of the Birth) (KMK, Moscow, 2005), pp. 195–222 [in Russian].

Classification and Diagnostic System of Russian Soils (Oikumena, Smolensk, 2004) [in Russian].

O. V. Kutovaya, Extended Abstract of Candidate’s Dissertation in Agriculture (Moscow, 2012).

O. V. Kutovaya, “Transformation of the structure of microbial communities in soddy-podzolic soils under the impact of earthworms,” Agrokhim. Vestn., No. 2, 13–14 (2008).

O. V. Kutovaya, “Characterization of humic substances in agrosoddy-podzolic soils and earthworm coprolites,” Byull. Pochv. Inst. im. V.V. Docuchaeva, No. 69, 46–59 (2011).

L. V. Lysak, Extended Abstract of Doctoral Dissertation in Biology (Moscow, 2010).

L. V. Lysak, N. N. Sidorenko, O. E. Marfenina, and D. G. Zvyagintsev, “Microbial complexes in urban soils,” Eur. Soil Sci. 33 (1), 70–75 (2000).

V. G. Matveeva and T. S. Perel’, “Earthworms of the Lumbricidae family in Moscow oblast,” in Soil Invertebrates of Moscow Oblast (Nauka, Moscow, 1982), pp. 133–143 [in Russian].

A Practicum on Microbiology , Ed. by N. S. Egorov (Izd. Mosk. Gos. Univ., Moscow, 1976) [in Russian].

I. S. Prokhorov, Extended Abstract of Candidate’s Dissertation in Agriculture (Moscow, 2006).

A. V. Rappoport, A. S. Myasoedov, and L. V. Lysak, “Biological activity of some urbanozems and kulturozems in Moscow,” in Outlooks for the Development of Soil Biology (MAKS-Press, Moscow, 2001), pp. 279–282 [in Russian].

O. B. Rumyantsev, Soccer Field. Recommendations on Maintenance of Natural Soddy Soccer Fields (PFL Rossii, Moscow, 1999) [in Russian].

I. N. Skvortsova, A. V. Rappoport, T. V. Prokof’eva, and A. E. Andreeva, “Biological properties of soils in the Moscow State University botanical garden: the branch on Prospekt Mira,” Eur. Soil Sci. 39 (7), 771–778 (2006).

A. V. Smagin, Theory and Practice of Soil Construction (Izd. Mosk. Gos. Univ., Moscow, 2012) [in Russian].

N. P. Sorokina, Large-Scale Soil Maps and Their Applications. Methodological Recommendations (Pochv. inst. im. V.V. Dokuchaeva VASKhNIL, Moscow, 1977) [in Russian].

A. L. Stepanov, N. A. Manucharova, A. V. Smagin, A. S. Kurbatova, A. D. Myagkova, V. N. Bashkin, “Characterization of the biological activity of the microbial complex in urban soils,” Eur. Soil Sci. 38 (8), 864–869 (2005).

M. N. Stroganova, Extended Abstract of Doctoral Dissertation in Biology (Moscow, 1998).

E. Z. Tepper, V. K. Shil’nikova, and G. I. Pereverzeva, A Practicum on Microbiology (Drofa, Moscow, 2005) [in Russian].

D. L. Shevelev, Extended Abstract of Candidate’s Dissertation in Geography (Moscow, 2011).

Bauen mit Gruen: die Bauuund Vegetationstechnik des Landschafts und Sportplatzbaus (Parey, Berlin-Hamburg, 1989).

Grundsaetze zur Functions und Umweltgerechten Pflege von Rasensportflaechen. Teil II. Wassersparende Massnahmen , (Bundesinstitut fuer Sportwissenschaft, Hoffman, Schorndor, 1994)

Grundsaetze zur Functions und Umweltgerechten Pflege von Rasensportflaechen. Teil III. Unerwuenschte Pflanzenarten auf Rasensportflaechen , (Bundesinstitut fuer Sportwissenschaft, Verl.-Gmbh, Koeln, 1995).

Grundsaetze zur Functions und Umweltgerechten Pflege von Rasensportflaechen. Teil IY. Pflanzenkrankheiten und Schaedlinge (Bundesinstitut fuer Sportwissen-schaft, Sport und Buch Strauss, Koeln, 1995).

C. G. Matthias, Praxis des Sportplatzbaus. Fehleraufdeckung und Vermeidung (Renningen-Malmsheim, 2002).

J. Puhalla, J. Krans, and J. Goatley, Sports Fields: Design, Construction, Maintenance , (J. Wiley & Sons, 2010).

Sportrasenpflege (DEULA Rheinland Kempen, 2006)..

Urbaner Bodenschutz. Arbeitkreis Stadtboeden der Deutschen Bodenkundlichen Gesellschaft (Hrsg.) (Springer, Berlin-Heidelberg, 1996).

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Dokuchaev Soil Science Institute, per. Pyzhevskii 7, Moscow, 119017, Russia

O. V. Kutovaya & V. P. Belobrov

Institute of Geography of the Russian Academy of Sciences, per. Staromonetnyi 29, Moscow, 119017, Russia

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Original Russian Text © O.V. Kutovaya, I.V. Zamotaev, V.P. Belobrov, 2014, published in Pochvovedenie, 2014, No. 11, pp. 1315–1324.

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Kutovaya, O.V., Zamotaev, I.V. & Belobrov, V.P. Communities of microorganisms and invertebrates in soil-like bodies of soccer fields in Moscow oblast. Eurasian Soil Sc. 47 , 1107–1115 (2014). https://doi.org/10.1134/S1064229314110052

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Received : 25 February 2014

Published : 06 November 2014

Issue Date : November 2014

DOI : https://doi.org/10.1134/S1064229314110052

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