A major problem with reviewing the statistical methodology in published medical articles is that extracting the necessary details from large sample sets is time-consuming. This paper demonstrates how a novel automated procedure can extract information about statistical reporting from literature. To illustrate this, we searched the PubMed Central database for original research articles published in 2021 and 2023 to identify the statistical software packages used for data analysis. A key element in terms of transparency and reproducibility is the reporting of the software used for statistical analysis. A freely available Shiny App was created with the help of generative artificial intelligence, and it was used to retrieve automatically information from randomly selected samples of articles indexed in PubMed Central. We analyzed a large sample of articles (n = 1740) to determine the reporting of statistical software for nine study designs. We found that, across different study types, proprietary software such as IBM SPSS Statistics still dominates. Despite multiple calls for greater use of open-source research software, these programs are not used as frequently. In addition, a surprising number of articles did not report the software used. Furthermore, this is the first application of the recent Vibe Coding concept to statistical research methods.

Bioinformatics is one of the main areas in the health sciences with great potential for the application of Large Language Models (LLMs), as it mainly involves computational analysis of results derived from experimental and high-throughput analysis of human, animal, and cellular models. Testing available general-purpose LLMs for the presence of inaccurate answers, such as confabulations, is of great interest in the fields of bioinformatics and computational genomics. In the current study, we carried out an analysis of the performance of six freely available LLMs (Gemini, ChatGPT, Grok, Claude, Llama, and DeepSeek) in a number of tasks commonly used in bioinformatics and computational genomics, with varying levels of difficulty. The selected tasks were: converting different identifiers (for two organisms), simulating a bisulfite conversion of DNA sequences, identifying the effects on amino acids of DNA polymorphisms, retrieving orthologues in mouse, identifying GO ontologies and KEGG pathways for lists of genes, interpreting a Volcano plot for gene expression, and automatically generating R code to visualize data. In general, our analysis identified a multiplicity of confabulations for different types of results generated by the tested LLMs. Our results highlighted a high number of errors in the output of the LLMs and identified automatic generation of code as a promising area. Future studies will be needed for a better understanding of the causes of confabulations of LLMs in research-related tasks.

Psychiatric disorders are highly heritable and polygenic, influenced by environmental factors and often comorbid. Large-scale genome-wide association studies (GWASs) through consortium efforts have identified genetic risk loci and revealed the underlying biology of psychiatric disorders and traits. However, over 85% of psychiatric GWAS participants are of European ancestry, limiting the applicability of these findings to non-European populations. Latin America and the Caribbean, regions marked by diverse genetic admixture, distinct environments and healthcare disparities, remain critically understudied in psychiatric genomics. This threatens access to precision psychiatry, where diversity is crucial for innovation and equity. This Review evaluates the current state and advancements in psychiatric genomics within Latin America and the Caribbean, discusses the prevalence and burden of psychiatric disorders, explores contributions to psychiatric GWASs from these regions and highlights methods that account for genetic diversity. We also identify existing gaps and challenges and propose recommendations to promote equity in psychiatric genomics.

Publication of articles in international scientific journals has been one of the main strategies for the communication of scientific findings and ideas. Prepublication peer review is a fundamental aspect of the publishing process in indexed scientific journals and, associated with the large growth in journals and articles, there has been a recent challenge in having adequate peer reviewers for international journals. In this article, we provide a short overview of the publishing process, give recommendations to early career researchers about writing peer reviews of adequate quality, and discuss some possibilities for the future.

Energy metabolism is a central topic in physical activity and sports sciences. However, some concepts still require biological contextualization and more precise terminology in scientific literature. In this regard, the purpose of this review was to highlight certain concepts that deserve to be reconsidered and possibly excluded from the vocabulary of exercise and sports sciences. It is argued that the terms “anaerobic” and “aerobic”, used to classify exercises or sports activities, are incorrect and imprecise. Similarly, the persistent use of the term “lactic acid” (i.e., the interchangeable use of lactate and lactic acid, often incorrectly considered the same) consequently leads to the misrepresentation of the phenomenon of “lactic acidosis”, which lacks rigorous biochemical support. Therefore, a conceptual reframing is needed to align with recent findings in exercise biochemistry and molecular biology. The following issues are addressed: i) The estimation of energy system contributions during physical exercise, with emphasis on the most commonly used methods in humans; ii) the classification of energy metabolism—and by extension, exercises—into “anaerobic” and “aerobic”, challenging this dichotomy and proposing a more precise classification into oxygen-independent energy systems (phosphagen and glycolytic) and oxygen-dependent energy systems (mitochondrial oxidative system); iii) the concepts of lactic acid production and lactic acidosis, refuting the idea that lactate accumulation results from oxygen deprivation and highlighting its role as an important metabolic intermediate; and iv) the interaction and contribution of energy systems during physical exertion, stating that energy systems are not activated sequentially but simultaneously, with their predominance depending on metabolic demands. By aligning terminology with contemporary findings in biochemistry and molecular biology, this perspective enhances the understanding and critical analysis of metabolic concepts in sports science education and professional practice, encouraging their adoption based on scientific evidence.

OBJECTIVES:To explore the performance of 4 large language model (LLM) chatbots for the analysis of 2 of the most commonly used tools for the advanced analysis of systematic reviews (SRs) and meta-analyses. MATERIALS AND METHODS:We explored the performance of 4 LLM chatbots (ChatGPT, Gemini, DeepSeek, and QWEN) for the analysis of ROBIS and AMSTAR 2 tools (sample sizes: 20 SRs), in comparison with assessments by human experts. RESULTS:Gemini showed the best agreement with human experts for both ROBIS and AMSTAR 2 (accuracy: 58% and 70%). The second best LLM chatbots were ChatGPT and QWEN, for ROBIS and AMSTAR 2, respectively. DISCUSSION:Some LLM chatbots underestimated the risk of bias or overestimated the confidence of the results in published SRs, which is compatible with recent articles for other tools. CONCLUSION:This is one of the first studies comparing the performance of several LLM chatbots for the automated analyses of ROBIS and AMSTAR 2.

Recent advances in high-throughput molecular methods have led to an extraordinary volume of genomics data. Simultaneously, the progress in the computational implementation of novel algorithms has facilitated the creation of hundreds of freely available online tools for their advanced analyses. However, a general overview of the most commonly used tools for the in silico analysis of genomics data is still missing. In the current article, we present an overview of commonly used online resources for genomics research, including over 50 tools. This selection will be helpful for scientists with basic or intermediate skills in the in silico analyses of genomics data, such as researchers and students from wet labs seeking to strengthen their computational competencies. In addition, we discuss current needs and future perspectives within this field.

Anxiety disorders are the most prevalent psychological conditions among adults worldwide. However, further research is needed on the role of variables such as health indices, stressful events, social cognition, and executive functioning in predicting anxiety symptoms. We conducted two studies to explore the association between these variables and anxiety symptoms in adults. In the first study, we evaluated 548 participants ranging in age from 18 to 73. We administered two anxiety scales and two instruments to assess physical and mental health dimensions and the number of threatening life events experienced. A subsample of 275 participants participated in the second study, where they completed tasks measuring working memory, verbal fluency, and emotion recognition. We used linear regression models to identify the relationship between participants’ anxiety levels and demographic, health, and psychosocial variables. In the first study, our findings revealed that participants with poorer mental and physical health and those who had experienced more stressful events displayed higher anxiety levels. Age, sex, physical and mental health were significant predictors of anxiety scores. In the second study, we identified negative correlations between anxiety and social cognition and executive function scores. However, only executive functions emerged as a predictor for anxiety. Overall, the factors of sex, age, mental and physical health, and executive function performance appear to be relevant in understanding anxiety levels and symptoms in adults.

In university hospitals, clinical care, teaching and research are the pillars of their missions. Scientometrics play a key role in the analysis of scientific productivity of researchers, laboratories or countries. However, there are no published articles about bibliometric studies of the scientific production of healthcare institutions in Latin America. To carry out a scientometric analysis of leading clinics and hospitals from five Latin American countries. We focused on five Latin American countries with the largest scientific production: Argentina, Brazil, Chile, Colombia and Mexico. We examined available information for international publications, citations, registered clinical trials, networks of collaborations and patent applications. The institutions with the highest numbers of published articles are: Hospital de Cl & iacute;nicas de Porto Alegre (Brazil), Instituto Nacional de Ciencias M & eacute;dicas y Nutrici & oacute;n Salvador Zubir & aacute;n (Mexico), Instituto Nacional De Cardiolog & iacute;a Ignacio Ch & aacute;vez (Mexico) and Hospital Italiano de Buenos Aires (Argentina). Highly cited articles, networks of collaborations and patents applications were also identified. Scientometric analysis of health research around the globe has been quite helpful, in terms of identification of priorities for funding and support. The higher scientific productivity for some of these Latin American institutions might be explained partially by their higher levels of collaborations with colleagues in institutions in high -income countries, which usually have larger funding. We provide several recommendations for strengthening clinical research in this world region.

Social cognition impairments may be associated with poor functional outcomes, symptoms, and disability in social anxiety disorder (SAD) and generalized anxiety disorder (GAD). This meta-analysis aims to determine if emotion recognition and theory of mind (ToM) are impaired in SAD or GAD compared to healthy controls. A systematic review was conducted in electronic databases (PubMed, PsycNet, and Web of Science) to retrieve studies assessing emotion recognition and/or ToM in patients with SAD or GAD, compared to healthy controls, up to March 2022. Meta-analyses using random-effects models were conducted. We identified 21 eligible studies: 13 reported emotion recognition and 10 ToM outcomes, with 585 SAD patients, 178 GAD patients, and 753 controls. Compared to controls, patients with SAD exhibited impairments in emotion recognition (SMD = −0.32, CI = −0.47 – −0.16, z = −3.97, p < 0.0001) and ToM (SMD = −0.44, CI = −0.83 –0.04, z = −2.18, p < 0.01). Results for GAD were inconclusive due to the limited number of studies meeting the inclusion criteria (two for each domain). Relevant demographic and clinical variables (age, sex, education level, and anxiety scores) were not significantly correlated with emotion recognition or ToM impairments in SAD and GAD. Further studies employing ecological measures with larger and homogenous samples are needed to better delineate the factors influencing social cognition outcomes in both SAD and GAD.

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but >95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity.

A recent article, based on the Global Burden of Disease Study 2019, estimated that about 970 million people were affected around the world by common psychiatric disorders and that anxiety and depressive disorders led to the largest numbers of disability-adjusted life-years (DALY) (2). A previous work analyzed the prevalence of psychiatric disorders in fourteen countries and found that México and Colombia had higher rates than several European countries (3). In terms of the global economic impact associated with psychiatric disorders, a recent paper estimated that it is around USD $5 trillion; for the global burden of disease region in which Colombia is located it is equivalent to 5.7 percent of the gross domestic product (GDP) (4). These major impacts on burden of disease, particularly on morbidity, is associated with the fact that common psychiatric disorders affect patients for many decades of life (2).

In recent decades, advances in methods in molecular biology and genetics have revolutionized multiple areas of the life and health sciences. However, there remains a global need for the development of more refined and effective methods across these fields of research. In this current Collection, we aim to showcase articles presenting novel molecular biology and genetics techniques developed by scientists from around the world.

Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasm of the pleural tissue that lines the lungs and is mainly associated with long latency from asbestos exposure. This tumor has no effective therapeutic opportunities nowadays and has a very low five-year survival rate. In this sense, identifying molecular events that trigger the development and progression of this tumor is highly important to establish new and potentially effective treatments. We conducted a meta-analysis of genome-wide expression studies publicly available at the Gene Expression Omnibus (GEO) and ArrayExpress databases. The differentially expressed genes (DEGs) were identified, and we performed functional enrichment analysis and protein–protein interaction networks (PPINs) to gain insight into the biological mechanisms underlying these genes. Additionally, we constructed survival prediction models for selected DEGs and predicted the minimum drug inhibition concentration of anticancer drugs for MPM. In total, 115 MPM tumor transcriptomes and 26 pleural tissue controls were analyzed. We identified 1046 upregulated DEGs in the MPM samples. Cellular signaling categories in tumor samples were associated with the TNF, PI3K-Akt, and AMPK pathways. The inflammatory response, regulation of cell migration, and regulation of angiogenesis were overrepresented biological processes. Expression of SOX17 and TACC1 were associated with reduced survival rates. This meta-analysis identified a list of DEGs in MPM tumors, cancer-related signaling pathways, and biological processes that were overrepresented in MPM samples. Some therapeutic targets to treat MPM are suggested, and the prognostic potential of key genes is shown.

Objective: There are several anxiety disorders leading to a high burden of disease around the world, including Generalized Anxiety Disorder (GAD). The heritability of GAD suggests that genetic factors play an important role in its development; however, further research in this area is needed in Latin America. This study aimed to analyze the possible association between two single nucleotide polymorphisms (SNPs), rs2244497 and rs1452789, located in the PRKCA and TCF4 genes with anxiety symptoms and GAD based on high anxiety scores in a sample of selected Colombian subjects. Methods: We evaluated 303 participants using the Hospital Anxiety and Depression Scale (HADS) and Zung’s Self-Rating Anxiety Scale (ZSAS). Subjects with high scores in both scales (according to established cut-off points) participated in a psychiatric evaluation for the diagnosis of GAD. TaqMan assays were employed to genotype the SNPs, and statistical analyses were performed using logistic and linear regression. Results: In a sample of Colombian subjects selected on the basis of high anxiety scores, we found a significant association between the rs2244497 SNP in the PRKCA gene and higher scores in anxiety symptoms, where people carrying the T/T genotype had the highest scores for HADS scale. However, we did not observe this association in people diagnosed with GAD. In addition, the SNP in TCF4 (rs1452789) did not have an association with anxiety symptoms or GAD diagnosis. Conclusion: This study contributes to the analysis of the molecular basis of anxiety disorders in selected Latin American samples. However, further studies are necessary to understand the role of rs2244497 SNP in the PRKCA gene and the risk for higher scores in anxiety symptoms.

Background: Major depressive disorder (MDD) is a common psychiatric entity, being characterized by alterations in mood and in other clinical dimensions. Several epigenome-wide association studies (EWAS) for MDD have been published. Here, we aimed to identify common genes in EWAS and their convergence with multiple lines of genomic evidence. Methods: We carried out a computational analysis using data of EWAS, which included a meta-analysis for brain samples of MDD, a convergence analysis for brain and blood samples, and top results from available genome-wide expression and association data. Functional enrichment and protein-protein interaction network analyses were also done. Results: The meta-analysis for brain samples detected a significant gene, FAM53B. A list of forty-four top differentially methylated (DM) candidate genes was found, including GRM8, NOTCH4 and SEMA6A, in addition to known druggable genes. The binding-sites for brain-expressed transcription factors, CREB and FOXO1, were enriched in the top DM genes. The protein-protein interaction networks showed that DM genes for MDD, such as RPRM and TMEM14B, play a central role. Conclusion: In this study, we found integrative evidence for the possible role of novel candidate genes and pathways. These genes are involved in mechanisms of synaptic plasticity, which have been associated with several psychiatric disorders. Analysis of epigenetic factors have a great potential for the identification of the mechanisms involved in the pathogenesis of MDD, taking into account their possible role in the interaction between genetic factors and the environment.

Physical exercise induces important system disturbances in the human body in a dose-response manner. Meta-analyses of genome-wide expression studies (GWES) might contribute to identify gene expression patterns and to a better understanding of the molecular mechanisms behind the complexity of adaptations to exercise, under a systems biology approach. Here, we aimed to analyze available data for human GWES that have evaluated the effect of exhaustive exercise in peripheral blood mononuclear cells (PBMC) and white blood cells (WBC). Three primary datasets retrieved from the NCBI Gene Expression Omnibus were meta-analyzed using a random effects model in the NetworkAnalyst software. After identifying nine differentially expressed genes (DEGs), we performed functional enrichment analyses to extract relevant biological information. A protein-protein interactions network on DEGs was built to evaluate the associated regulatory pathways. We found that five upregulated genes were members of the heat shock protein family, one of the top stress-response groups of genes. The enrichment analysis revealed key roles of the DEGs on the cellular adaptations to exercise-induced stress (i.e., temperature stimulus, topologically-incorrect and unfolded proteins). Our comparison analysis of DEG signatures found in blood cells with the expression pattern on muscle skeletal tissue showed some common genes. Thus, novel DEGs that might serve as hormetic mediators to exercise-induced adaptations were identified. Further experimental research is needed to validate these findings.

Introducción. El síndrome respiratorio agudo grave causado por el nuevo coronavirus SARSCoV-2 es causa de la emergencia sanitaria por la pandemia de COVID-19. Si bien el humano es el el principal huésped vulnerable, en estudios experimentales y reportes de infección natural, se han encontrado casos de zoonosis inversa de SARS-CoV-2 en animales.Objetivo. Evaluar la infección natural por SARS-CoV-2 en gatos y perros de propietarios con diagnóstico de COVID-19 en el Valle de Aburrá, Antioquia, Colombia.Materiales y métodos. La circulación del SARS-CoV-2 se evaluó por RT-qPCR y RT-PCR en muestras de frotis nasofaríngeos y orofaríngeos de gatos y perros cuyos propietarios se encontraban dentro del periodo de los 14 días de aislamiento. Los casos positivos se verificaron amplificando fragmentos de los genes RdRp, N y E; se secuenció el gen RdRp y se analizó filogenéticamente.Resultados. De 80 animales evaluados, seis gatos y tres perros fueron casos confirmados de infección natural por SARS-CoV-2. Los animales no presentaron signos clínicos y sus propietarios, que padecían la infección, reportaron únicamente signos leves de la enfermedad sin complicaciones clínicas. En el análisis de una de las secuencias, se encontró un polimorfismo de un solo nucleótido (SNP) con un cambio en la posición 647, con sustitución del aminoácido serina (S) por una isoleucina (I). Los casos se presentaron en los municipios de Caldas, Medellín y Envigado.Conclusiones. Se infiere que la infección natural en los gatos y perros se asocia al contacto directo con un paciente con COVID-19. No obstante, no es posible determinar la virulencia del virus en este huésped, ni su capacidad de transmisión zoonótica o entre especie.