MedComm - Future medicine最新文献

The activation of autophagy in endothelial cells is a key mechanism underlying vascular remodeling, leading to the development and progression of pulmonary hypertension (PH). In our previous studies, we developed ROC-325, a novel lysosomal autophagy inhibitor, and demonstrated its potent therapeutic effects in severe pulmonary arterial hypertension (PAH). However, its role in chronic hypoxia-induced PH (HPH) remains unknown. Here, we observed increased LC3B-II/I and decreased p62/SQSTM1 in lung tissues of hypoxic mice, indicative of autophagy activation. ROC-325 treatment suppressed this activation by inhibiting LC3B-II accumulation and restoring p62 levels. ROC-325 significantly reduced right ventricular systolic pressure (RVSP), right ventricular hypertrophy (RVH), and pulmonary artery medial thickening and muscularization, indicating a significantly protective effect against HPH. Endothelial hypoxia-inducible factor 2α (HIF-2α) upregulation, resulting from prolyl hydroxylase domain protein 2 (PHD2) deficiency, was implicated in autophagy activation. Endothelial conditional PHD2 knockout mice, a spontaneous PH model, exhibited elevated LC3B-II/I and HIF-2α levels, both of which were reduced by ROC-325, leading to significant PH attenuation. In vitro, ROC-325 inhibited the proliferation of pulmonary microvascular endothelial cells derived from PHD2-deficient mice and enhanced HIF-2α degradation in human pulmonary artery endothelial cells. These findings, in summary, identify ROC-325 as a promising therapeutic agent for hypoxia-induced PH by modulating both autophagy and endothelial HIF-2α signaling.

The activation of autophagy in endothelial cells is a key mechanism underlying vascular remodeling, leading to the development and progression of pulmonary hypertension (PH). In our previous studies, we developed ROC-325, a novel lysosomal autophagy inhibitor, and demonstrated its potent therapeutic effects in severe pulmonary arterial hypertension (PAH). However, its role in chronic hypoxia-induced PH (HPH) remains unknown. Here, we observed increased LC3B-II/I and decreased p62/SQSTM1 in lung tissues of hypoxic mice, indicative of autophagy activation. ROC-325 treatment suppressed this activation by inhibiting LC3B-II accumulation and restoring p62 levels. ROC-325 significantly reduced right ventricular systolic pressure (RVSP), right ventricular hypertrophy (RVH), and pulmonary artery medial thickening and muscularization, indicating a significantly protective effect against HPH. Endothelial hypoxia-inducible factor 2α (HIF-2α) upregulation, resulting from prolyl hydroxylase domain protein 2 (PHD2) deficiency, was implicated in autophagy activation. Endothelial conditional PHD2 knockout mice, a spontaneous PH model, exhibited elevated LC3B-II/I and HIF-2α levels, both of which were reduced by ROC-325, leading to significant PH attenuation. In vitro, ROC-325 inhibited the proliferation of pulmonary microvascular endothelial cells derived from PHD2-deficient mice and enhanced HIF-2α degradation in human pulmonary artery endothelial cells. These findings, in summary, identify ROC-325 as a promising therapeutic agent for hypoxia-induced PH by modulating both autophagy and endothelial HIF-2α signaling.

Mixed reality is an immersive visualization technology based on simultaneous localization and mapping systems and standalone head-mounted displays. It enables seamless integration and dynamic interaction among users, virtual elements, and the physical environment. Although numerous clinical studies and in vitro experiments have confirmed the value of mixed reality in surgical practice, the hierarchy of evidence remains limited. This review draws on published English-language literature to summarize its technical foundations, clinical applications, current innovations, and existing challenges. Specifically, the primary procedures of mixed reality-assisted surgery consist of three-dimensional reconstruction, holographic visualization, and spatial registration. Its clinical applications span preoperative planning, intraoperative navigation, surgical training, and postoperative rehabilitation. However, current limitations include insufficient computational and display capabilities of head-mounted displays, inadequate accuracy in spatial registration, high costs, workflow complexity, and unresolved ethical concerns. Therefore, we recommend increased resource allocation for technological innovations, multicenter randomized controlled clinical trials, and detailed risk-benefit assessments, aiming to establish and validate standardized clinical workflows. As the first comprehensive narrative review to compare the clinical applicability of mixed reality across all surgical specialties, this article outlines future research directions by analyzing representative clinical studies and offers a reliable report on current progress.

Air pollution poses a significant threat to respiratory health globally, contributing to the development and worsening of diseases, such as asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, and lung cancer. A key mechanism behind this involves epigenetic reprogramming, where environmental exposures alter gene activity without changing the underlying DNA sequence itself. This review deciphers the multilayered epigenetic mechanisms linking pollutants (e.g., PM_2.5, cigarette smoke, and ozone) to respiratory pathology, emphasizing reversible modifications that bridge environmental exposure and disease phenotypes. Air pollution-induced epigenetic reprogramming regulates critical biological processes, such as immune imbalance, chronic inflammation, oxidative stress, cellular dysfunction (senescence, apoptosis, and ferroptosis), tissue remodeling (epithelial–mesenchymal transition and fibrosis), and genomic instability. Specifically, aberrant DNA methylation, dysregulated RNA methylation, perturbed noncoding RNA networks, and histone modification abnormalities collectively drive disease pathogenesis. Furthermore, emerging epigenetic therapies targeting these modifications, such as DNA methyltransferase inhibitors (5-AZADC), histone deacetylase inhibitors, and RNA methylation regulators (methyltransferase-like 3 inhibitor STM2457), show promising therapeutic potential. This review highlights the reversibility of epigenetic changes as a strategic basis for intervention, emphasizing the need for future research on mixed exposures, tissue-specific mechanisms, and clinical translation to mitigate the global burden of pollution-related respiratory diseases.

Traditional Chinese Medicine (TCM), with its fragmented knowledge system, subjective diagnostics, and limited standardization, faces ongoing challenges in modernization. The rapid development of Large Language Models (LLMs) offers an unprecedented opportunity for the digitalization and standardization of TCM knowledge. By leveraging deep semantic understanding, contextual reasoning, and knowledge-graph–based inference, LLMs can systematize knowledge, integrate multimodal data, and support both standardized and personalized decision-making. Several TCM–LLMs, such as Qibo and MedChatZH, have been developed. Although previous reviews compared individual TCM–LLMs, a comprehensive analysis of common characteristics is lacking. This review addresses this gap by examining the “construction–application–challenges–prospects” paradigm of TCM–LLMs. Construction generally involves collecting authoritative data from diverse sources, standardizing textual content, training and fine-tuning on foundational LLMs, and subsequent evaluation. Key applications include auxiliary diagnosis and treatment, health management, medical education, and drug discovery. Five major challenges are data quality, reasoning performance, multimodal integration, ethical and regulatory compliance, and cultural adaptability. On the basis of this analysis, we propose a classification scheme that categorizes applications into four types and adopt the identified challenges as evaluation dimensions for future TCM–LLMs. This framework aims to clarify conceptual structures, guide methodology, and provide a foundation for innovation and cross-cultural integration in TCM research.

Urological cancers represent a significant and growing global health challenge. This study aims to provide a comprehensive assessment of the global burden, trends, and inequalities of prostate, bladder, and kidney cancers from 1990 to 2021, and to project their future burden to 2050. Utilizing data from the Global Burden of Disease Study 2021, we analyzed incidence, prevalence, mortality, and disability-adjusted life years (DALYs). We employed joinpoint regression to analyze temporal trends, frontier analysis to evaluate healthcare efficiency, and Bayesian age-period-cohort models to project future burden. Risk factor attributions were also quantified. In 2021, prostate cancer demonstrated the highest age-standardized rates across all metrics. From 1990 to 2021, age-standardized mortality and DALY rates declined for all three cancers. The burden was disproportionately higher among males and older populations, with smoking, high fasting plasma glucose, and high body-mass index identified as leading risk factors. Projections to 2050 indicate a continued decline in all age-standardized rates globally. Despite favorable trends in standardized rates, persistent sex disparities, growing absolute case numbers due to population aging, and the influence of modifiable risk factors necessitate targeted public health interventions and strategic healthcare planning.

The long-term survival benefit of neoadjuvant therapy (NAT) in breast cancer patients eligible for breast-conserving surgery (BCS) remains uncertain. This retrospective cohort study analyzed 94,677 BCS-eligible patients from the SEER database (2010–2020), including 8565 who received NAT. After propensity score matching (n = 5734 each), NAT significantly improved overall survival (OS) only in patients with triple-negative (HR = 0.79), ER-negative (HR = 0.80), and stage IIA (HR = 0.81) disease. No OS benefit was observed in HER2-positive patients despite high response rates. To guide treatment decisions, two machine learning models using Random Survival Forest were developed to predict 5-year OS, showing good discrimination (C-index: 0.743 for BCS, 0.690 for NAT-BCS). SHAP analysis identified age, stage, and breast subtype as key prognostic factors. Cross-stratification based on predicted OS revealed that 8.9% of BCS patients could benefit from NAT, while 90.8% of NAT-BCS patients might safely omit it. Patients whose treatment matched model recommendations had significantly better survival. These findings suggest that NAT provides limited survival benefit in BCS-eligible patients, with the advantage concentrated in specific subgroups. Predictive modeling offers a clinically useful approach to personalize NAT use, potentially reducing unnecessary treatment while identifying those most likely to benefit.