Translational Research Research Articles

Translation Research in the Arabic Language: A Bibliometric Study

Over the past two decades, Translation Studies has experienced exponential growth in published articles, with bibliometric analysis increasingly used to explore research trends. This study employs corpus-based bibliometric method to analyse translation research output in the Arabic language from 2000 to 2020. A total of 1043 articles published in the Arabic language were obtained and classified using research area classification proposed by Williams and Chesterman (2014). The results indicate a substantial focus on Genre Translation as the primary interest within the Arab world, while the Translation Process and Interpreting Studies have received less attention. Keyword analysis further highlights Quran Translation as the most prevalent topic among these publications; however, it remains largely isolated from English-language research, which rarely cites Arabic studies. Moreover, the study examines the geographical distribution of the research, highlighting significant disparities in output across the Arab world, which can be attributed to publishing practices that favour English over Arabic. This pattern suggests a disconnect that might impede the global discourse in Translation Studies, particularly concerning the integration of insights across linguistic divides. The study provides a comprehensive overview of the current state of Arabic Translation Studies and stresses the need for further comprehensive explorations into underrepresented areas within Arabic translation research.

Implementation of Obesity Science Into Clinical Practice: A Scientific Statement From the American Heart Association.

Obesity is a recognized public health epidemic with a prevalence that continues to increase dramatically in nearly all populations, impeding progress in reducing incidence rates of cardiovascular disease. Over the past decade, obesity science has evolved to improve knowledge of its multifactorial causes, identifying important biological causes and sociological determinants of obesity. Treatments for obesity have also continued to develop, with more evidence-based programs for lifestyle modification, new pharmacotherapies, and robust data to support bariatric surgery. Despite these advancements, there continues to be a substantial gap between the scientific evidence and the implementation of research into clinical practice for effective obesity management. Addressing barriers to obesity science implementation requires adopting feasible methodologies and targeting multiple levels (eg, clinician, community, system, policy) to facilitate the delivery of obesity-targeted therapies and maximize the effectiveness of guideline-driven care to at-need patient populations. This scientific statement (1) describes strategies shown to be effective or promising for enhancing translation and clinical application of obesity-based research; (2) identifies key gaps in the implementation of obesity science into clinical practice; and (3) provides guidance and resources for health care professionals, health care systems, and other stakeholders to promote broader implementation and uptake of obesity science for improved population-level obesity management. In addition, advances in implementation science that hold promise to bridge the know-do gap in obesity prevention and treatment are discussed. Last, this scientific statement highlights implications for health research policy and future research to improve patient care models and optimize the delivery and sustainability of equitable obesity-related care.

Osteoarthritis, adipokines and the translational research potential in small animal patients

Osteoartritis (OA) is a debilitating disease affecting both humans and animals. In the early stages, OA is characterized by damage to the extracellular matrix (ECM) and apoptosis and depletion of chondrocytes. OA progression is characterized by hyaline cartilage loss, chondrophyte and osteophyte formation, thickening of the joint capsule and function loss in the later stages. As the regenerative potential of cartilage is very limited and osteoarthritic changes are irreversible, prevention of OA, modulation of existing osteoarthritic joint inflammation, reducing joint pain and supporting joint function are the only options. Progression of OA and pain may necessitate surgical intervention with joint replacement or arthrodesis as end-stage procedures. In human medicine, the role of adipokines in the development and progression of OA has received increasing interest. At present, the known adipokines include leptin, adiponectin, visfatin, resistin, progranulin, chemerin, lipocalin-2, vaspin, omentin-1 and nesfatin. Adipokines have been demonstrated to play a pivotal role in joint homeostasis by modulating anabolic and catabolic balance, autophagy, apoptosis and inflammatory responses. In small animals, in terms of dogs and cats, naturally occurring OA has been clearly demonstrated as a clinical problem. Similar to humans, the etiology of OA is multifactorial and has not been fully elucidated. Humans, dogs and cats share many joint related degenerative diseases leading to OA. In this review, joint homeostasis, OA, adipokines and the most common joint diseases in small animals leading to naturally occurring OA and their relation with adipokines are discussed. The purpose of this review is highlighting the translational potential of OA and adipokines research in small animal patients.

Modeling social cognition in alcohol use disorder: lessons from schizophrenia.

A better understanding of social deficits in alcohol use disorder (AUD) has the potential to improve our understanding of the disorder. Clinical research shows that AUD is associated with interpersonal problems and the loss of a social network which impedes response to treatment. Translational research between animal models and clinical research may benefit from a discussion of the models and methods that currently guide research into social cognition in AUD. We propose that research in AUD should harness recent technological developments to improve ecological validity while maintaining experimental control. Novel methods allow us to parse naturalistic social cognition into tangible components, and to investigate previously neglected aspects of social cognition. Furthermore, to incorporate social cognition as a defining element of AUD, it is critical to clarify the timing of these social disturbances. Currently, there is limited evidence to distinguish factors that influence social cognition as a consequence of AUD, and those that precede the onset of the disorder. Both increasing the focus on operationalization of social cognition into objective components and adopting a perspective that spans the clinical spectrum will improve our understanding in humans, but also possibly increase methodological consistency and translational dialogue across species. This commentary underscores current challenges and perspectives in this area of research.

Integrating the Patient's Voice into the Research Agenda for Treatment of Chemosensory Disorders.

World-wide some 658 million people were infected with COVID-19 and millions suffer from chemosensory impairment associated with long COVID. Current treatments for taste and smell disorders are limited. Involving patients has the potential to catalyze the dynamic exchange and development of new ideas and approaches to facilitate biomedical research and therapeutics. We assessed patients' perceptions of the efficacy of treatments for chemosensory impairment using an online questionnaire completed by 5,815 people in the U.S. Logistic regression determined variables predictive of reported treatment efficacy for patients aged 18-24, 25-39, 40-60 and 60+ yrs. who were treated with nasal steroids, oral steroids, zinc, nasal rinse, smell training, theophylline, platelet rich plasma, and Omega 3. The most consistent predictor was age, with the majority of those 40-60 and 60+ reporting that nasal steroids, oral steroids, zinc, nasal rinse and smell training were only slightly effective or not effective at all. Many of these treatment strategies target regeneration and immune response, processes compromised by age. Only those under 40 reported more than slight efficacy of steroids or smell training. Findings emphasize the need to include patients of all ages in clinical trials. Older adults with olfactory impairment are at increased risk for Alzheimer's disease (AD). We speculate that olfactory impairment associated with long COVID introduces the potential for a significant rise in AD. Long COVID-associated chemosensory impairment increases the urgency for translational and clinical research on novel treatment strategies. Suggestions for high priority areas for epidemiological, basic, and clinical research on chemosensory impairment follow.

Role of Machine Learning and Artificial Intelligence in Arrhythmias and Electrophysiology.

Machine learning (ML), a subset of artificial intelligence (AI) centered on machines learning from extensive datasets, stands at the forefront of a technological revolution shaping various facets of society. Cardiovascular medicine has emerged as a key domain for ML applications, with considerable efforts to integrate these innovations into routine clinical practice. Within cardiac electrophysiology, ML applications, especially in the automated interpretation of electrocardiograms, have garnered substantial attention in existing literature. However, less recognized are the diverse applications of ML in cardiac electrophysiology and arrhythmias, spanning basic science research on arrhythmia mechanisms, both experimental and computational, as well as contributions to enhanced techniques for mapping cardiac electrical function and translational research related to arrhythmia management. This comprehensive review delves into various ML applications within the scope of this journal, organized into 3 parts. The first section provides a fundamental understanding of general ML principles and methodologies, serving as a foundational resource for readers interested in exploring ML applications in arrhythmia research. The second part offers an in-depth review of studies in arrhythmia and electrophysiology that leverage ML methodologies, showcasing the broad potential of ML approaches. Each subject is thoroughly outlined, accompanied by a review of notable ML research advancements. Finally, the review delves into the primary challenges and future perspectives surrounding ML-driven cardiac electrophysiology and arrhythmias research.

The Epidemiology of Errors in Data Capture, Management, and Analysis: A Scoping Review of Retracted Articles and Retraction Notices in Clinical and Translational Research

The Epidemiology of Errors in Data Capture, Management, and Analysis: A Scoping Review of Retracted Articles and Retraction Notices in Clinical and Translational Research

A Review of Elite Athlete Evidence-Based Knowledge and Preparation for Competing in the Heat

AbstractElite athletes will compete in extreme heat more frequently as global land and sea temperatures increase, alongside more intense, frequent and longer duration heatwaves. Best practices to protect athlete health and performance during competition include heat acclimation/acclimatisation [(HA); i.e., long-term pre-competition preparation] complemented by pre-planned and practised cooling and hydration strategies (i.e., short-term interventions immediately before or during competition). This review explores elite athletes’ current behaviours and practices when preparing for competition in the heat and assesses the level of knowledge that has been exhibited by athletes and their practitioners in this space. Recommendations for future research, discussions of current best practices, and methods to improve translation of research into practice are provided. Available research focuses on small samples of elite endurance athletes during a selection of World Championship/Olympic/Paralympic events (~6% of competing athletes). While generally an increase in the adoption of evidence-based HA is seen chronologically from 2015 onwards, universal adoption is not seen. HA adoption is lowest in those who live/train in cold/temperate environments with cost and access to facilities/equipment being the most commonly reported barriers. Further research is required across the sporting landscape to fully characterise elite athlete behaviours and practices in these spaces. International federations and national governing bodies should continue their efforts to educate athletes and focus on regularly updated and reinvigorated release of evidence-based guidelines (in multiple germane languages) for competing in the heat, to increase the adoption of HA and other heat related best practice.

O12 Macrophages enhance angiogenesis in an induced pluripotent stem cell-derived skin organoid model

Abstract Introduction and aims Hair-bearing skin organoids (SkOs) are a complex three-dimensional (3D) model that faithfully recapitulates human skin as a multicellular organ with appendage structures. The development of such models provides unique potential for investigating human skin development and translational dermatology. Although this model answers many demands of an investigative tool, one obvious limitation is the absence of immune cells in SkOs. Our aim is to generate coculture systems of SkOs with macrophages to investigate how macrophages influence skin development. Methods Our group, and others, generated single-cell (sc)RNA-Seq and spatial transcriptomic datasets to thoroughly characterize human skin cell populations across the human lifespan. We used these datasets to compare the dynamic tempo of induced pluripotent stem cell (iPSC)-derived SkO (n = 84) differentiation with human prenatal (n = 15) and adult skin. For functional assays, we generated 2D angiogenesis coculture assays with macrophages and endothelial cells (n = 3) and 3D coculture of SkOs with macrophages (n = 3). Macrophages, endothelial cells and SkOs were all derived from the same iPSC line following established protocols. SkO vasculature was analysed after immunowholemount staining of CD31+ endothelial cells. Results Analysis of scRNA-Seq data highlighted a paucity in endothelial cell heterogeneity in SkOs compared with prenatal skin. We hypothesized that this could be explained by the absence of immune cells, as spatial transcriptomics microenvironment analysis of prenatal skin demonstrated that endothelial cells collocate with macrophages. With this in mind, we generated functional assays to investigate interactions of macrophages and endothelial cells in skin development. The 2D and 3D assays revealed that presence of macrophages significantly increased endothelial cell sprouting and network formation. Conclusions Our findings suggest a vital role of macrophages in skin morphogenesis, specifically in relation to the guidance of tip cells during angiogenesis. In addition, we present the SkO as an excellent complex model for investigating skin development, cell–cell interactions, and disease modelling for translational research in regenerative medicine and beyond.

Neural Machine Translation for Low-Resource Languages from a Chinese-centric Perspective: A Survey

Machine translation—the automatic transformation of one natural language (source language) into another (target language) through computational means—occupies a central role in computational linguistics and stands as a cornerstone of research within the field of Natural Language Processing (NLP). In recent years, the prominence of Neural Machine Translation (NMT) has grown exponentially, offering an advanced framework for machine translation research. It is noted for its superior translation performance, especially when tackling the challenges posed by low-resource language pairs that suffer from a limited corpus of data resources. This article offers an exhaustive exploration of the historical trajectory and advancements in NMT, accompanied by an analysis of the underlying foundational concepts. It subsequently provides a concise demarcation of the unique characteristics associated with low-resource languages and presents a succinct review of pertinent translation models and their applications, specifically within the context of languages with low-resources. Moreover, this article delves deeply into machine translation techniques, highlighting approaches tailored for Chinese-centric low-resource languages. Ultimately, it anticipates upcoming research directions in the realm of low-resource language translation.

MicroRNA as a promising molecular biomarker in the diagnosis of breast cancer

Introduction: Breast cancer represents the most prevalent malignancy among women. Recent advancements in translational research have focused on the identification of novel biomarkers capable of providing valuable insights into patient outcomes. Furthermore, comprehensive investigations aimed at discovering novel miRNAs, unraveling their biological functions, and deciphering their target genes have significantly contributed to our understanding of the roles miRNAs play in tumorigenesis. Consequently, these investigations have facilitated the way for the development of miRNA-based approaches for breast cancer prognosis, diagnosis, and treatment. However, conducting a more extensive array of studies, particularly among diverse ethnic groups, is imperative to expand the scope of research and validate the significance of miRNAs. This study aimed to assess the expression patterns of circulating miRNAs in plasma as a prospective biomarker for breast cancer patients within a population primarily consisting of individuals from Black, Indigenous, and People of Color (BIPOC) communities.Methods: We evaluated 49 patients with breast cancer compared to 44 healthy women.Results and discussion: All miRNAs analyzed in the plasma of patients with breast cancer were downregulated. ROC curve analysis of miR-21 (AUC = 0.798, 95% CI: 0.682–0.914, p <0.0001), miR-1 (AUC = 0.742, 95% CI: 0.576–0.909, p = 0.004), miR-16 (AUC = 0.721, 95% CI: 0.581–0.861, p = 0.002) and miR-195 (AUC = 0.672, 95% CI: 0.553–0.792, p = 0.004) showed better diagnostic accuracy in discrimination of breast cancer patients in comparison with healthy women. miR-210, miR-21 showed the highest specificities values (97.3%, 94.1%, respectively). Following, miR-10b and miR-195 showed the highest sensitivity values (89.3%, and 77.8%, respectively). The panel with a combination of four miRNAs (miR-195 + miR-210 + miR-21 + miR-16) had an AUC of 0.898 (0.765–0.970), a sensitivity of 71.4%, and a specificity of 100.0%. Collectively, our results highlight the miRNA combination in panels drastically improves the results and showed high accuracy for the diagnosis of breast cancer displaying good sensitivity and specificity.

An Anticipatory Approach to Ethico-Legal Implications of Future Neurotechnology

This paper provides a justificatory rationale for recommending the inclusion of imagined future use cases in neurotechnology development processes, specifically for legal and policy ends. Including detailed imaginative engagement with future applications of neurotechnology can serve to connect ethical, legal, and policy issues potentially arising from the translation of brain stimulation research to the public consumer domain. Futurist scholars have for some time recommended approaches that merge creative arts with scientific development in order to theorise possible futures toward which current trends in technology development might be steered. Taking a creative, imaginative approach like this in the neurotechnology context can help move development processes beyond considerations of device functioning, safety, and compliance with existing regulation, and into an active engagement with potential future dynamics brought about by the emergence of the neurotechnology itself. Imagined scenarios can engage with potential consumer uses of devices that might come to challenge legal or policy contexts. An anticipatory, creative approach can imagine what such uses might consist in, and what they might imply. Justifying this approach also prompts a co-responsibility perspective for policymaking in technology contexts. Overall, this furnishes a mode of neurotechnology’s emergence that can avoid crises of confidence in terms of ethico-legal issues, and promote policy responses balanced between knowledge, values, protected innovation potential, and regulatory safeguards.

The Water Resources Rebound Effect Threatening the Achievement of Sustainable Development Goal 6 (SDG 6)

Coaction of climate change and human activities exerts a significant impact on the fate of water resources, provoking the rebound effect in water resources and threatening the achievement of SDG (sustainable development goal) 6. However, the mechanisms of interactions between this effect and SDG 6 and how to decrease this effect towards the achievement of SDG 6 are less known. In this paper, a water resources rebound effect (WRRE) model is integrated into a river basin sustainable development decision support system to simulate and project the interactions between the WRRE and SDG 6 under multiple combination scenarios. The results show that multiple drivers, including precipitation, technological advances, and ecological water flow, coaffect the WRRE, not the silo technology factor. The transfer fate of the saved water is a major root cause leading to the WRRE and harming the achievement of SDG 6, and the WRRE is positively correlated to SDG 6 overall, which, nevertheless, can sometimes be reversed by technological advances. Our outcomes indicate that decoupling SDG 6 from the WRRE can promote the achievement of SDG 6 and decrease the rebound effect, relying on holistic integration that couples climatic, socioeconomic, and behavioral interaction between SDG 6 and the WRRE and translation of scientific research into available decision-making information for strict scientific-research-based policy actions.

Geroscience: just another name or is there more to it?

The widespread use of the name 'geroscience' in the science of aging is sometimes met with a wary attitude by biogerontologists other than its inventors. Here, we provide an overview of its origin and evolution to assess what exactly it is and to discuss its theoretical and biological relationship to earlier movements of anti-aging medicine and biogerontology more generally. Geroscience posits that targeting aging may offer a cost-effective approach to improve late-life health in humans, and because aging is malleable in model organisms and what regulates this is sufficiently understood, the time is ripe for moving forward to translational and clinical research. The geroscience agenda has rebranded imagery of past traditions, yet the claim that therapies for human aging are ready or within the imminent future is contestable and on brand with tradition, even if biogerontology has made great progress in the past decades.

Speeding up Glioblastoma Cancer Research: Highlighting the Zebrafish Xenograft Model

Glioblastoma multiforme (GBM) is a very aggressive and lethal primary brain cancer in adults. The multifaceted nature of GBM pathogenesis, rising from complex interactions between cells and the tumor microenvironment (TME), has posed great treatment challenges. Despite significant scientific efforts, the prognosis for GBM remains very poor, even after intensive treatment with surgery, radiation, and chemotherapy. Efficient GBM management still requires the invention of innovative treatment strategies. There is a strong necessity to complete cancer in vitro studies and in vivo studies to properly evaluate the mechanisms of tumor progression within the complex TME. In recent years, the animal models used to study GBM tumors have evolved, achieving highly invasive GBM models able to provide key information on the molecular mechanisms of GBM onset. At present, the most commonly used animal models in GBM research are represented by mammalian models, such as mouse and canine ones. However, the latter present several limitations, such as high cost and time-consuming management, making them inappropriate for large-scale anticancer drug evaluation. In recent years, the zebrafish (Danio rerio) model has emerged as a valuable tool for studying GBM. It has shown great promise in preclinical studies due to numerous advantages, such as its small size, its ability to generate a large cohort of genetically identical offspring, and its rapid development, permitting more time- and cost-effective management and high-throughput drug screening when compared to mammalian models. Moreover, due to its transparent nature in early developmental stages and genetic and anatomical similarities with humans, it allows for translatable brain cancer research and related genetic screening and drug discovery. For this reason, the aim of the present review is to highlight the potential of relevant transgenic and xenograft zebrafish models and to compare them to the traditionally used animal models in GBM research.

The American College of Rheumatology White Paper: The Effects of Climate Change on Rheumatic Conditions - An Evolving Landscape and a Path Forward.

Increases in global temperatures and extreme weather events associated with climate change have complex yet poorly understood detrimental impacts on human health. We reviewed the current published literature on climate change-related effects and rheumatic conditions. To summarize our current understanding of the likely effects of climate change, including increased air pollution, on rheumatic disease, we searched the published, peer-reviewed English-language literature from January 2000-December 2022. Articles were reviewed by a team of rheumatologists and clinical and translational science researchers. Systematic review articles were not included but informed additional literature searches. After extensive examination and adjudication, 88 articles met inclusion criteria and were selected for review. Much of the epidemiologic investigations assessed associations between air pollution and increased risk of development of rheumatoid arthritis, anti-citrullinated protein antibodies, flares of gout and hospitalizations for systemic lupus erythematosus. Increased heat vulnerability was associated with higher odds of recurrent hospitalizations across rheumatic conditions. Mechanisms for observed associations are poorly understood but could include the effects of epigenetic changes, oxidative stress, and inflammatory cytokines. Studies had limitations including restricted geography and populations studied without focus on historically marginalized communities at highest risk for adverse effects from pollution and climate change, the relative lack of mechanistic evaluations, and most with only indirect links to climate change. To date, the published literature lacks studies that directly examine effects of climate change on rheumatic diseases. Collaborative translational and epidemiologic research is needed to enhance our understanding and awareness in this area.

A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a comprehensive database of inorganic NP research is not currently available, it is crucial for developing effective cancer therapies. In this context, machine learning (ML) has emerged as a transformative tool, but its adaptation to nanomedicine is hindered by inexistent or small datasets. Here we assembled a large database of inorganic NPs, comprising experimental datasets from 745 preclinical studies in cancer nanomedicine. Using descriptive statistics and explainable ML models we mined this database to gain knowledge of inorganic NP design patterns and inform future NP research for cancer treatment. Our analyses suggest that NP shape and therapy type are prominent features in determining in vivo efficacy, measured as a percentage of tumour reduction. Moreover, our database provides a large-scale open-access resource for discriminative ML that the broader nanotechnology community can utilize. Our work blueprints data mining for translational cancer research and offers evidence for standardizing NP reporting to accelerate and de-risk inorganic NP-based drug delivery, which may help to improve patient outcomes in clinical settings.

Laser Doppler Fluximetry in Cutaneous Vasculature: Methods for Data Analyses

Introduction: Acquisition of a deeper understanding of microvascular function across physiological and pathological conditions can be complicated by poor accessibility of the vascular networks and the necessary sophistication or intrusiveness of the equipment needed to acquire meaningful data. Laser Doppler fluximetry (LDF) provides a mechanism wherein investigators can readily acquire large amounts of data with minor inconvenience for the subject. However, beyond fairly basic analyses of erythrocyte perfusion (fluximetry) data within the cutaneous microcirculation (i.e., perfusion at rest and following imposed challenges), a deeper understanding of microvascular perfusion requires a more sophisticated approach that can be challenging for many investigators. Methods: This manuscript provides investigators with clear guidance for data acquisition from human subjects for full analysis of fluximetry data, including levels of perfusion, single- and multiscale Lempel-Ziv complexity (LZC) and sample entropy (SampEn), and wavelet-based analyses for the major physiological components of the signal. Representative data and responses are presented from a recruited cohort of healthy volunteers, and computer codes for full data analysis (MATLAB) are provided to facilitate efforts by interested investigators. Conclusion: It is anticipated that these materials can reduce the challenge to investigators integrating these approaches into their research programs and facilitate translational research in cardiovascular science.

The road less traveled: Developing pharmacist clinician-scientists through divergent training pathways.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Professional organizations have emphasized the growing need for pharmacists to possess advanced research skills; however, there is a scarcity of training programs aimed at nurturing clinician-scientists. This report outlines 3 critical care-focused research programs, each offering a unique approach to training clinician-scientists. Limited resources and formalized programs are available to bridge the gap between the demand for and availability of skilled clinician-scientists. Several programs have stepped forward to share their experiences in establishing and executing training initiatives aimed at cultivating skilled clinician-scientists in the critical care practice space. Enhancing the development of clinician-scientists for clinical and translational research is necessary in the critical care clinical pharmacy community.

Characterization in the rat of the individual tendency to rely on alcohol to cope with distress and the ensuing vulnerability to drink compulsively

Abstract Only some vulnerable individuals who recreationally drink alcohol eventually develop the compulsive drinking pattern that characterizes alcohol use disorder. A new frontier in biomedical research lies in understanding the neurobehavioral mechanisms of this individual vulnerability, a necessary step towards developing novel effective therapeutic strategies. Translational research has been hindered by the lack of valid, reliable and robust approaches that enable the study of the influence of the reliance on alcohol to cope with stress or self-medicate negative emotional states on the subsequent transition to alcohol use disorder. We have therefore developed a behavioral task in the rat that enables the investigation of the neural and cellular basis of the exacerbation of the vulnerability to develop compulsive alcohol drinking by the use of alcohol to develop an adjunctive, anxiolytic, polydipsic drinking behavior in a schedule-induced polydipsia procedure. Hence, in our task, alcohol is introduced in the schedule-induced polydipsia context after several weeks of training with water so that rats are exposed to alcohol for the first time in a distressing context and learn to drink alcohol as a coping strategy. Capitalizing on this protocol, we have consistently been able to identify a subpopulation of rats that were unable to learn to cope with negative states by drinking water and relied on alcohol to do so. This maladaptive reliance on alcohol-drinking to cope with distress has been shown to be associated with an exacerbation of the subsequent transition to compulsive drinking. Furthermore, these vulnerable rats reached blood alcohol levels comparable to that of intoxication in humans, thereby developing two key features of alcohol use disorder, namely excessive alcohol intake and compulsive drinking. Altogether, this behavioral task provides a novel and unique tool for the investigation of the neurobehavioral mechanisms underlying the exacerbation of the individual vulnerability to developing compulsive alcohol drinking by the use of alcohol as a strategy to cope with distress, and for the evaluation of the efficacy of potential therapeutic strategies in a personalized medicine approach. This procedure, which focuses on an understudied but key factor of the development of alcohol use disorder, may become widely used as it benefits the fields of alcohol, emotion regulation and stress, the interest in which has substantially increased since the evidence of a profound exacerbation of alcohol use and alcohol-related negative consequences by the distress and social isolation engendered by the various measures implemented worldwide in response to the COVID-19 pandemic.