MedComm - Future medicine最新文献

Recently, a study by Péter Nagy's team [1] published in Cell Metabolism identified that the upregulation of cystathionine γ-lyase (CSE) and the inhibition of cystathionine β-synthase (CBS) are key factors contributing to the development of resistance to B-Raf proto-oncogene, serine/threonine kinase (BRAF) inhibitors (BRAFi) in treatment. Coadministration of the CSE inhibitor d,l-propargylglycine (PAG) with BRAFi significantly improved therapeutic efficacy and delayed the onset of resistance, offering a novel therapeutic strategy for patients with BRAF V600E-mutant (a valine-to-glutamic acid substitution at position 600 in the BRAF protein) melanoma.

Malignant melanoma is a highly aggressive tumor originating from melanocytes, with approximately 50% of patients harboring the BRAF V600E mutation [1]. This mutation leads to the activation of the downstream mitogen-activated protein kinase kinase/extracellular-signal-regulated kinase (MEK/ERK) signaling pathway, which in turn results in an increase in aerobic glycolysis, thereby supporting the proliferation of melanoma cells [2]. BRAF V600E inhibitors, such as vemurafenib (V) and dabrafenib (D), have been approved by the Food and Drug Administration (FDA) for the treatment of melanoma. However, resistance to these therapies often develops. Even when combining dabrafenib with the MEK inhibitor trametinib, resistance remains an inevitable challenge [3].

Existing research has indicated that treatment with dabrafenib-trametinib (DT) inhibits the BRAF/MEK/ERK pathway, leading to a shift in melanoma cell metabolism from aerobic glycolysis to mitochondrial respiration, which is unfavorable for melanoma cell proliferation [4]. Concurrently, the increased mitochondrial oxidative phosphorylation and electron transport chain (ETC) pathways result in enhanced reactive oxygen species (ROS) production. Excessive ROS production can disrupt the cellular redox balance and trigger oxidative stress responses. Building on this, the study discovered significant expression of cytochrome P (CYP)450 enzymes in dabrafenib- and trametinib-treated cells (DTC), with upregulation of CYP1B1 and CYP2F1 in dabrafenib- and trametinib-double resistant cells (DTR). These enzymes contribute to ROS production. To counteract the effects of ROS accumulation, antioxidant enzymes, such as superoxide dismutase 2 (SOD2), thioredoxin reductase 1 (TrxR1), catalase, 14-kDa human thioredoxin (Trx)-related protein (TRP14), glucose-6-phosphate dehydrogenase (G6PD), and glutathione (GSH) peroxidase 1 and 4 (GPX1, 4), are upregulated in DTC. However, this antioxidant response is limited, and the cells become more sensitive to exogenous oxidants, making them more susceptible to oxidative stress-induced damage. To support the function of antioxidant enzymes, DTC increasingly rely on the pentose phosphate pathway (PPP) to generate more nicoti

The skin, the largest organ in the human body, serves both as a mechanical barrier and an autonomous lymphoid organ, protecting against various environmental threats while maintaining the balance and functionality of multiple bodily systems. This relationship extends beyond the skin itself, involving other organs closely linked to skin homeostasis and related diseases. However, systematic reviews in this area are still lacking. This review seeks to explore this bidirectional communication, with a particular focus on the critical role of the immune system. We present a comprehensive review of the latest evidence, highlighting the fundamental roles of immune cells and cytokines within the skin–organ axis, particularly IL-17A, which appears to interact with nearly all organs, illustrating their interplay and impact on skin health. Additionally, we discuss the implications of these interactions for the design and application of skin-on-a-chip and organ-on-a-chip technologies, emphasizing the importance of understanding these relationships for developing physiologically relevant in vitro models. By providing a comprehensive analysis of these complex interactions, this review establishes a solid theoretical foundation for the prevention, diagnosis, and treatment of diseases associated with the skin–organ axis, particularly regarding immune cells, cytokines, microorganisms, and their metabolites, ultimately aiming to advance research in related fields and offer new insights for clinical applications.

DeepSeek-R1 is an open-source Large Language Model (LLM) with advanced reasoning capabilities. It has gained significant attention for its impressive advantages including low costs and visualized reasoning steps. Recent advancements in reasoning LLMs like ChatGPT-o1 have significantly exhibited their considerable reasoning potential, but the closed-source nature of existing models limits customization and transparency, presenting substantial barriers to their integration into healthcare systems. This gap motivates the exploration of DeepSeek-R1 in the medical field. Thus, we comprehensively review the transformative potential, applications, and challenges of DeepSeek-R1 in healthcare. Specifically, we investigate how DeepSeek-R1 can enhance clinical decision support, patient engagement, and medical education to help for clinic, outpatient and medical research. Furthermore, we critically evaluate challenges including modality limitations (text-only), hallucination risks, and ethical issues, particularly related to patient autonomy and safety-focused recommendations. By assessing DeepSeek-R1′s integration potential, this perspective highlights promising opportunities for advancing medical AI while emphasizing necessary improvements to maximize clinical reliability and ethical compliance. This paper provides valuable guidance for future research directions and elucidates practical application scenarios for DeepSeek-R1′s successful integration into healthcare settings.

The release of ChatGPT in 2022 has catalyzed the adoption of large language models (LLMs) across diverse writing domains, including academic writing. However, this technological shift has raised critical questions regarding the prevalence of LLM usage in academic writing and its potential influence on the quality and impact of research articles. Here, we address these questions by analyzing preprint articles from arXiv, bioRxiv, and medRxiv between 2022 and 2024, employing a novel LLM usage detection tool. Our study reveals that LLMs have been widely adopted in biomedical and other types of academic writing since late 2022. Notably, we noticed that LLM usage is linked to an enhanced impact of research articles after examining their correlation, as measured by citation numbers. Furthermore, we observe that LLMs influence specific content types in academic writing, including hypothesis formulation, conclusion summarization, description of phenomena, and suggestions for future work. Collectively, our findings underscore the potential benefits of LLMs in scientific communication, suggesting that they may not only streamline the writing process but also enhance the dissemination and impact of research findings across disciplines.

Artificial intelligence (AI)-driven learning is transforming education, requiring educators to quickly develop the skills to integrate AI tools effectively so they complement rather than replace traditional teaching practices. The fast pace of generative AI development poses challenges, particularly for less tech-savvy teachers or those who delay learning about these tools, leaving them at risk of falling behind. This is further compounded by students' quick adaptation to widely available models such as ChatGPT-3.5 and Deepseek R1, which they increasingly use for learning, assignments, and assessments. Despite existing discussions on AI in education, there is a lack of practical guidance on how medical educators can effectively and responsibly implement AI tools in teaching. This perspective provides a practical guide for medical educators to effectively incorporate AI tools to complement their teaching strategies, generate student assessments and to adapt assignments suitable for the AI era. We address challenges such as data bias, accuracy, and ethics, ensuring AI enhances rather than undermines medical training when aligned with sound pedagogical principles. This review provides a practical, structured approach for educators, offering clear recommendations to help bridge the gap between AI advancements and effective teaching methodologies in medical education.

A recent study published in Nature by Lin et al. [1, 2], conducted at Xiamen University identified that lithocholic acid (LCA), a bile acid metabolite, mimics the anti-aging effects of caloric restriction (CR) by activating the TULP3-sirtuin-v-ATPase-AMPK axis. LCA binds to the receptor TUB-like protein 3 (TULP3), triggering allosteric activation of sirtuins (SIRT1-7), which deacetylate lysine residues (K52, K99, K191) on the V1E1 subunit of lysosomal v-ATPase. This deacetylation inhibits v-ATPase activity, activating AMPK through the lysosomal glucose-sensing pathway, fostering muscle rejuvenation in aged mice.

CR has long been associated with enhanced health and longevity in various species including yeasts, worms, flies, and mammals [3]. Although the precise underlying mechanisms of these benefits remain unclear, they potentially involve alterations in multiple metabolic, hormonal, and cellular signaling pathways. AMPK is at the core of this process as a crucial regulator that senses energy levels within cells. Despite the well-documented advantages of CR, long-term adherence to such a dietary regimens is often impractical for individuals [4]. Therefore, identifying pharmacological agents that could effectively mimic CR effects has emerged as a significant research area within the field of aging science. The presented study positions LCA as an effective analog for CR, offering a promising opportunity for therapeutic intervention.

Based on conventional wisdom, AMPK is primarily activated when energy stores are depleted and glucose levels are decreased [5]. However, the authors discovered that in CR mice, blood glucose did not fall to the levels that would reportedly trigger AMPK activation. This observation indicated that AMPK activation during CR was not directly driven by reduced glucose levels. To further explore this phenomenon, the authors added serum from CR mice to cell cultures and observed sustained AMPK activation even under high glucose concentrations (Figure 1A). This result suggests that a factor in the serum of CR mice can activate AMPK glucose level-independently. The authors conducted a comprehensive metabolomic analysis of the serum from CR mice using various mass spectrometric techniques, and registered significant changes in the abundance of 695 metabolites during CR. Notably, only LCA could recapitulate AMPK activation at physiological concentrations (compared to the control serum) (Figure 1B,C). Furthermore, AMPK activation has been observed in mice as well as in other model organisms, such as nematodes and Drosophila, upon LCA supplementation.

The authors further investigated the signaling pathway by which LCA activates AMPK. They observed that AMPK activation via either LCA or CR did not lead to an increase in AMP or cytosolic calcium levels. This finding ruled out traditional AMP- or calcium-dependent activation mechanisms. The authors explored the

Inflammation, as a complex biological response, can lead to tissue damage and pathological physiological changes, forming the basis for many chronic diseases. Stem cell-derived exosomes (SC-Exos), a type of nanoscale extracellular vesicle, possess advantages such as small volume, low immunogenicity, and drug-carrying capacity, demonstrating immense potential in the field of disease diagnostics and therapeutics. Current studies indicate that SC-Exos can not only alleviate inflammatory diseases by suppressing inflammatory cytokines and modulating the activation of macrophages through their immunomodulatory and regenerative properties but also show significant potential as carriers for anti-inflammatory drugs, presenting a promising therapeutic approach for inflammatory conditions. However, the current lack of systematic summaries of SC-Exos in the treatment of inflammatory diseases has impeded the development of standardized therapies and clinical applications. This review elucidates the methods of SC-Exo sourcing, isolation, characterization, and engineering, as well as their application, mechanisms of action, and efficacy in the treatment of inflammatory diseases such as periodontitis, osteoarthritis (OA), and inflammatory bowel disease. Integrating these findings, this review highlights that SC-Exos can attenuate a variety of inflammatory diseases by transporting a diverse range of molecules to modulate immune responses, thereby providing foundations for subsequent standardization of production and clinical trials.

Glioma, characterized by significant heterogeneity and aggressiveness, poses a formidable therapeutic challenge. Cuproptosis, a newly identified form of regulated cell death driven by copper imbalance, has recently emerged as a pivotal factor in tumor biology. However, its role in IDH1-mutant gliomas remains poorly understood. Through comprehensive bioinformatics analysis of publicly available datasets, we identified two distinct subtypes of IDH1-mutant gliomas based on cuproptosis regulator expression profiles. Subtype G1 exhibited elevated PD-L1 expression, increased pro-tumor immune infiltration, and worse clinical outcomes, whereas subtype G2 was enriched in antitumor immune cells and associated with improved prognosis. We identified FDX1 and SLC31A1 as critical prognostic markers, with their upregulation linked to PD-L1 expression. Mechanistically, we delineated a ceRNA regulatory axis involving COX10-AS1/miR-1-3p/FDX1 and SLC31A1 that drives glioma progression. Building on these insights, we developed a prognostic risk model integrating FDX1 and SLC31A1 expression, demonstrating robust predictive accuracy for patient outcomes and potential utility in guiding individualized treatment strategies. These findings advance our understanding of the molecular landscape in IDH1-mutant gliomas and underscore the potential of cuproptosis regulators as novel therapeutic targets and biomarkers for precision oncology.