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Background: ChatGPT is a large language model (LLM) based on artificial intelligence (AI) capable of responding in multiple languages and generating nuanced and highly complex responses. While ChatGPT holds promising applications in medical education, its limitations and potential risks cannot be ignored.Methods: A scoping review was conducted for English articles discussing ChatGPT in the context of medical education published after 2022. A literature search was performed using PubMed/MEDLINE, Embase, and Web of Science databases, and information was extracted from the relevant studies that were ultimately included.Results: ChatGPT exhibits various potential applications in medical education, such as providing personalized learning plans and materials, creating clinical practice simulation scenarios, and assisting in writing articles. However, challenges associated with academic integrity, data accuracy, and potential harm to learning were also highlighted in the literature. The paper emphasizes certain recommendations for using ChatGPT, including the establishment of guidelines. Based on the review, 3 key research areas were proposed: cultivating the ability of medical students to use ChatGPT correctly, integrating ChatGPT into teaching activities and processes, and proposing standards for the use of AI by medical students.Conclusion: ChatGPT has the potential to transform medical education, but careful consideration is required for its full integration. To harness the full potential of ChatGPT in medical education, attention should not only be given to the capabilities of AI but also to its impact on students and teachers.

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at \"http://rna.physics.missouri.edu\".

The task of epitope discovery and vaccine design is increasingly reliant on bioinformatics analytic tools and access to depositories of curated data relevant to immune reactions and specific pathogens. The Immune Epitope Database and Analysis Resource (IEDB) was indeed created to assist biomedical researchers in the development of new vaccines, diagnostics, and therapeutics. The Analysis Resource is freely available to all researchers and provides access to a variety of epitope analysis and prediction tools. The tools include validated and benchmarked methods to predict MHC class I and class II binding. The predictions from these tools can be combined with tools predicting antigen processing, TCR recognition, and B cell epitope prediction. In addition, the resource contains a variety of secondary analysis tools that allow the researcher to calculate epitope conservation, population coverage, and other relevant analytic variables. The researcher involved in vaccine design and epitope discovery will also be interested in accessing experimental published data, relevant to the specific indication of interest. The database component of the IEDB contains a vast amount of experimentally derived epitope data that can be queried through a flexible user interface. The IEDB is linked to other pathogen-specific and immunological database resources.

The accurate predicting of physical properties and bioactivity of drug molecules in deep learning depends on how molecules are represented. Many types of molecular descriptors have been developed for quantitative structure-activity/property relationships quantitative structure-activity relationships (QSPR). However, each molecular descriptor is optimized for a specific application with encoding preference. Considering that standalone featurization methods may only cover parts of information of the chemical molecules, we proposed to build the conjoint fingerprint by combining two supplementary fingerprints. The impact of conjoint fingerprint and each standalone fingerprint on predicting performance was systematically evaluated in predicting the logarithm of the partition coefficient (logP) and binding affinity of protein-ligand by using machine learning/deep learning (ML/DL) methods, including random forest (RF), support vector regression (SVR), extreme gradient boosting (XGBoost), long short-term memory network (LSTM), and deep neural network (DNN). The results demonstrated that the conjoint fingerprint yielded improved predictive performance, even outperforming the consensus model using two standalone fingerprints among four out of five examined methods. Given that the conjoint fingerprint scheme shows easy extensibility and high applicability, we expect that the proposed conjoint scheme would create new opportunities for continuously improving predictive performance of deep learning by harnessing the complementarity of various types of fingerprints.

Osthole is an active compound isolated from Chinese herb Cnidium monnieri (L.) Cusson, and had been reported to possess antitumor effect. However, the effect of osthole on the gastric cancer cells has not been investigated. In this study, the effects of osthole on the proliferation of human gastric cancer cells were tested. The data showed that osthole treatment significantly inhibited the proliferation of gastric cancer cells and resulted in the cell cycle arrest at G2/M phase in a dose-dependent manner. Western-blot study showed that the expression of cyclin B1 and cdc2 was markedly reduced by osthole. Moreover, expression of PI3K and pAKT was also significantly suppressed, and the results indicated that the inhibition of pAKT, cyclin B1, and cdc2 levels by osthole was notably enhanced by a PI3K inhibitor. These results demonstrate that osthole could inhibit gastric cancer cells proliferation via induction of cell cycle arrest at G2/M phase by the reduction of PI3K/AKT.

•Greater age-related CBF decline in hippocampal subfields observed in females.•Males showed age-related CBF increase in the subiculum.•Hypothalamic atrophy post-menopause with ATT prolongation only in females.•CA1 exhibited the lowest hemodynamic level among all hippocampal subfields. Sex differences in hippocampal aging have been increasingly recognized, with females showing greater vulnerability to neurodegeneration, particularly after menopause. However, the underlying neurobiological mechanisms remain unclear, especially at the level of hippocampal subfields. Leveraging high-resolution T1-, T2-weighted, and multi-delay arterial spin labeling MRI from 650 adults in the Human Connectome Project-Aging dataset, we examined sex-specific alterations in hippocampal subfield volume, arterial transit time (ATT), and cerebral blood flow (CBF) across the adult lifespan. All hippocampal subfields showed age-related atrophy and ATT prolongation. An age × sex interaction effect on ATT was observed in CA1 and CA2, indicating that age-related increases in ATT were more pronounced in females than in males in these subfields. Moreover, females exhibited more pronounced hippocampal subfields CBF reductions with aging and atrophy, while males showed relatively preserved CBF, with an increase in subiculum perfusion. Furthermore, CA1 showed the lowest perfusion and the strongest association with atrophy among hippocampal subfields. To investigate the potential impact of menopausal hormonal changes on sex-specific patterns, we explored the hypothalamic structure and hemodynamic alterations during aging and their effects on the hippocampus, given that hypothalamus regulates gonadal hormone secretion through the hypothalamic-pituitary-gonadal axis. We found significant hypothalamic atrophy during aging in both sexes, accompanied by ATT prolongation exclusively in females, which was associated with hippocampal atrophy and impaired hemodynamics. Our study highlights the intricate interplay between hippocampal structure and vascular function, revealing sex- and subfield-specific aging trajectories. These findings provide a normative quantitative imaging reference to age-related neurodegenerative diseases such as Alzheimer’s Disease.

Neutrophils are significant compositions of solid tumors and exert distinct functions in different types of tumors. However, the precise role of neutrophils in the progression of breast cancer (BC) is presently unclear. In this study, by investigating the single-cell RNA sequencing data, we identify a new neutrophil subset, C5aR1-positive neutrophils, that correlates with tumor progression and poor survival for BC patients. Furthermore, it is discovered that C5aR1-positive neutrophils enhance BC cell glycolysis via upregulating ENO1 expression. Mechanically, C5aR1-positive neutrophil-secreted IL1β and TNFα cooperatively activate ERK1/2 signaling, which phosphorylates WTAP at serine341 and thereby stabilizes WTAP protein. The stabilization of WTAP further promotes RNA m6A methylation of ENO1, impacting the glycolytic activity of BC cells. Importantly, C5aR1-positive neutrophils also promote breast cancer growth in vivo, and this effect is abolished by WTAP silencing. In clinical BC samples, increased C5aR1-positive neutrophils correlate with elevated IL1β, TNFα, and ENO1 expression. A high co-expression of C5aR1-positive neutrophil gene signature and ENO1 predicts worse prognosis of BC patients compared with a low co-expression. Collectively, our study reveals a novel subset of C5aR1-positive neutrophils that induces breast cancer glycolysis via increasing ERK1/2-WTAP-dependent m6A methylation of ENO1. These findings support the potential for exploration of C5aR1-positive neutrophils as a therapeutic target in breast cancer.

COVID-19 can cause different neurological symptoms in some people, including smell, inability to taste, dizziness, confusion, delirium, seizures, stroke, etc. Owing to the issue of vaccine effectiveness, update and coverage, we still need one or more diversified strategies as the backstop to manage illness. Characterizing the structural basis of ligand recognition in the main protease (Mpro) of SARS-CoV-2 will facilitate its rational design and development of potential drug candidates with high affinity and selectivity against COVID-19. Up to date, covalent-, non-covalent inhibitors and allosteric modulators have been reported to bind to different active sites of Mpro. In the present work, we applied the molecular dynamics (MD) simulations to systematically characterize the potential binding features of catalytic active site and allosteric binding sites in Mpro using a dataset of 163 3D structures of Mpro-inhibitor complexes, in which our results are consistent with the current studies. In addition, umbrella sampling (US) simulations were used to explore the dissociation processes of substrate pathway and allosteric pathway. All the information provided new insights into the protein features of Mpro and will facilitate its rational drug design for COVID-19.

The CRISPR/Cas9 complex, a bacterial immune response system, has been widely adopted for RNA-guided genome editing and transcription regulation in applications such as targeted genome modification and site-directed mutagenesis. However, the physical basis for its target specificity is not fully understood. In this study, based on a statistical mechanical analysis for the whole ensemble of sgRNA-target complex conformations, we identify a strong correlation between Cas9 cleavage efficiency and the stability of the DNA-RNA (R-loop) complex structures, with a Pearson correlation coefficient ranging from 0.775 to 0.886 for the tested systems. The finding leads to quantitative insights into important experimental results, such as the greater Cas9 tolerance to single-base mismatches in PAM-distal region than to PAM-proximal region and the high specificity and efficiency for shorter protospacers. Moreover, the results from the genome-wide off-target assessments, compared with other off-target scoring tools, indicate that the statistical mechanics-based approach provides more reliable off-target analyses and sgRNA design. To facilitate the genome engineering applications, a new web-based tool for genome-wide off-target assessment is established.

Using the 8.5‐year Venus Express measurements, we demonstrate the asymmetric plasma distributions in the Venusian magnetosheath. An escaping plume is formed by pickup oxygen ions in the hemisphere where the motional electric field points outward from Venus, while the velocity of solar wind protons is faster in the opposite hemisphere. The pickup O+ escape rate is estimated to be (3.6 ± 1.4) × 1024 s−1 at solar maximum, which is comparable to the ion loss rate through the magnetotail, and (1.3 ± 0.4) × 1024 s−1 at solar minimum. The increase of O+ fluxes with extreme ultraviolet (EUV) intensity is significant upstream of the bow shock, partially attributed to the increase of exospheric neutral oxygen density. However, the solar wind velocity just has a slight effect on the pickup O+ escape rate in the magnetosheath, while the effect of solar wind density is not observed. Our results suggest the pickup O+ escape rate is mainly controlled by EUV radiation. Plain Language Summary The atmospheric evolution and water escape of Venus might be influenced by the solar wind‐Venus interaction. The atoms outside the induced magnetosphere are ionized by the solar radiation and accelerated to the escape velocity by solar wind electric field. In this way, the oxygen ions are picked up by solar wind and lost from the atmosphere to space. We use the data from Venus Express spacecraft to analyze the distribution of pickup oxygen ions in the vicinity of the planet. The planetary oxygen ions form a strong escaping plume, indicating the pickup process is an efficient escape channel removing the atmospheric particles. With an enhanced solar extreme ultraviolet radiation, the escape rate through this channel would be higher because more ions are produced and then picked up. This indicates an enhanced ion loss billions of years ago since the young Sun is more active, which might be a reason for the disappearance of a presumably‐existed ocean. Key Points The pickup O+ escape rate at Venus increases with solar activity, and it is comparable to the ion loss rate through the magnetotail The solar wind velocity has a slight effect on the pickup O+ escape rate in the magnetosheath The neutral oxygen density upstream of the bow shock might increase by a factor of two from solar minimum to maximum