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Background Abies beshanzuensis , an endemic fir native to the subtropical high mountains of eastern China, is classified as a first-class nationally protected wild plant and is listed as Critically Endangered (CR) by the International Union for Conservation of Nature (IUCN). Taxonomic controversies have long persisted among A. beshanzuensis , A. ziyuanensis , and A. dayuanensis , yet studies focusing on their mitochondrial DNA remain limited. Results In this study, the complete mitochondrial genome of A. beshanzuensis was assembled using a combination of Oxford Nanopore long-read sequencing and Illumina short-read sequencing technologies. The mitochondrial genome is 1.06 Mb in size with a GC content of 45.97%, and consists of nine linear chromosomes and one circular chromosome. Comprehensive analyses, including genome annotation, structural comparisons, RNA editing site prediction, and phylogenetic reconstruction, were subsequently conducted. Conclusion The results provide important insights into the mitochondrial genome architecture of A. beshanzuensis , offering a valuable resource for clarifying its controversial taxonomic status and advancing the understanding of evolutionary relationships within the genus Abies .

Public participation in community-organized disaster mitigation activities is important for improving disaster mitigation capacity. With data from 260 questionnaires, this study compared the current status of public participation in model disaster mitigation communities and nonmodel communities in a geological-disaster-prone area. Three community-organized disaster mitigation education activities were compared cross-sectionally. A binary logistic regression was used to analyze the effects of attitude, perceived behavioral control, disaster experience, and other key factors on the public’s choice to participate in community disaster mitigation activities. The analysis results indicated that model communities had higher public participation in two efforts, evacuation drills and self-help skills training, and lower participation in activities that invited them to express their feedback than nonmodel communities. The influence of attitudinal factors on the decision to participate in disaster mitigation activities had a high similarity across community types. The public participation in model disaster mitigation communities is influenced by factors such as subjective norms and participation cognition; the behavior of people in nonmodel communities is influenced by factors such as previous experience with disasters, perceived behavioral control, risk perception, and participation cognition and has a greater potential for disaster mitigation community construction. This study provides practical evidence and theoretical support for strengthening the sustainable development of disaster mitigation community building.

Thymosin α1 (Tα1) is an immunostimulatory peptide that is commonly used as an immune enhancer in viral infectious diseases such as hepatitis B, hepatitis C, and acquired immune deficiency syndrome (AIDS). Tα1 can influence the functions of immune cells, such as T cells, B cells, macrophages, and natural killer cells, by interacting with various Toll-like receptors (TLRs). Generally, Tα1 can bind to TLR3/4/9 and activate downstream IRF3 and NF-κB signal pathways, thus promoting the proliferation and activation of target immune cells. Moreover, TLR2 and TLR7 are also associated with Tα1. TLR2/NF-κB, TLR2/p38MAPK, or TLR7/MyD88 signaling pathways are activated by Tα1 to promote the production of various cytokines, thereby enhancing the innate and adaptive immune responses. At present, there are many reports on the clinical application and pharmacological research of Tα1, but there is no systematic review to analyze its exact clinical efficacy in these viral infectious diseases via its modulation of immune function. This review offers an overview and discussion of the characteristics of Tα1, its immunomodulatory properties, the molecular mechanisms underlying its therapeutic effects, and its clinical applications in antiviral therapy.

During the diagnosis and treatment of non-small cell lung cancer (NSCLC), detecting the risk of its recurrence in an early phase is still challenging. Recent studies have investigated the radiomics-based machine learning (ML) models for detecting the risk of recurrence in NSCLC. However, there is still insufficient systematic evidence to prove its efficiency. This study is designed to systematically evaluate the effectiveness of radiomics-based ML in predicting the risk of recurrence in NSCLC, aiming to provide evidence-based support for the subsequent development of scoring tools to forecast recurrence risk. For acquiring research on radiomics-based models for forecasting the risk of recurrence in NSCLC, Cochrane Library, Web of Science, PubMed, and Embase were systematically retrieved, up to October 24, 2025. Studies on analyzing the recurrence of NSCLC using radiomics-based ML were included, while those in which only texture analysis was conducted or radiomics-based ML was not constructed were excluded. The Radiomics Quality Score (RQS) was used to appraise the eligible studies. Subgroup analyses were conducted according to the variables of the model, the background of treatment, the stage of lung cancer, and the pathological type. Ultimately, 30 eligible studies in total were included, covering 7964 patients with NSCLC. According to the meta-analysis, the c-index of radiomics-based ML models for forecasting the risk of recurrence in NSCLC was 0.850 (95% CI 0.834-0.866, 95% prediction interval [PI] 0.623-1.004) in the training set. Specifically, the pooled c-index was 0.876 (95% CI 0.853-0.900) among the patients receiving the stereotactic body radiation therapy and 0.825 (95% CI 0.804-0.848) among those who received surgeries combined with other adjuvant treatment regimens. The c-index of the radiomics-based ML models combined with clinical features for forecasting the risk of recurrence in NSCLC was 0.833 (95% CI 0.822-0.854, 95% PI 0.717-0.945) in the training set. In contrast, the c-index of radiomics-based ML models for forecasting the risk of recurrence in NSCLC was 0.878 (95% CI 0.854-0.902, 95% PI 0.681-1.000) in the validation set. The c-index of radiomics-based ML models combined with clinical features for forecasting the risk of recurrence in NSCLC was 0.854 (95% CI 0.830-0.878, 95% PI 0.655-0.992) in the validation set. The average RQS across the included studies was 27.4%, revealing methodological limitations and an absence of standardization. This study is the first to confirm that radiomics-based ML models effectively predict the risk of recurrence in NSCLC. This study provides evidence-based support for the subsequent development or updating of radiomics-based ML models. However, the current methodological application of radiomics remains concerning. Therefore, in the future, research should standardize the workflow for implementing radiomics-based ML and incorporate multicenter imaging data to enhance its generalizability.

Cardiomyocyte pyroptosis and apoptosis play a vital role in the pathophysiology of several cardiovascular diseases. Our recent study revealed that gasdermin D (GSDMD) can promote myocardial I/R injury via the caspase-11/GSDMD pathway. We also found that GSDMD deletion attenuated myocardial I/R and MI injury by reducing cardiomyocyte apoptosis and pyroptosis. However, how GSDMD mediates cardiomyocyte apoptosis and protects myocardial function remains unclear. Here, we found that doxorubicin (DOX) treatment resulted in increased apoptosis and pyroptosis in cardiomyocytes and that caspase-11/GSDMD could mediate DOX-induced cardiotoxicity (DIC) injury. Interestingly, GSDMD overexpression promoted cardiomyocyte apoptosis, which was attenuated by GSDMD knockdown. Notably, GSDMD overexpression exacerbated DIC injury, impaired cardiac function in vitro and in vivo, and enhanced DOX-induced cardiomyocyte autophagy. Mechanistically, GSDMD regulated the activity of FAM134B, an endoplasmic reticulum autophagy receptor, by pore formation on the endoplasmic reticulum membrane via its N-terminus, thus activating endoplasmic reticulum stress. In turn, FAM134B interacted with autophagic protein LC3, thus inducing cardiac autophagy, promoting cardiomyocyte apoptosis, and aggravating DIC. These results suggest that GSDMD promotes autophagy and induces cardiomyocyte apoptosis by modulating the reaction of FAM134B and LC3, thereby promoting DIC injury. Targeted regulation of GSDMD may be a new target for the prevention and treatment of DIC.

Purpose To explore how diabetes influences the association between stress hyperglycemia (SH) and functional outcomes in acute ischemic stroke (AIS), and to develop a nomogram based on the stress hyperglycemia ratio (SHR) to predict the prognosis of AIS patients. Methods Patients were divided into diabetic mellitus (DM) and non-diabetic mellitus (non-DM) groups. SH was calculated using the ratio of fasting blood sugar (FBG) to glycosylated hemoglobin A1c (HbA1c). Poor functional outcomes were defined as a modified Rankin Scale (mRS) score > 2 at a 3-month follow-up. Multivariable logistic regression analysis was used to identify the relationship between SHR and functional outcomes in diabetic and non-diabetic groups. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis and logistic regression analysis were employed to build a nomogram. Results In the DM group, severe stress hyperglycemia showed no significant association with poor function outcomes at 3 months. However, in the non-DM group, severe stress hyperglycemia was associated with poor function outcomes [odds ratio (OR) = 2.21, 95% confidence interval CI 1.61–3.02, p < 0.001]. After adjusting for covariates, the differences remained statistically significant (adjusted OR = 1.62, 95% CI 1.09–2.42, p = 0.0181). Lasso regression identified 8 predictive factors, while logistic regression highlighted age, NIHSS, and SHR as independent predictors, forming a nomogram. The receiver operating characteristic curve assessed the discriminative ability of the nomogram, calibration, and clinical decision curves to evaluate model fitting and net benefit. Conclusion Severe stress hyperglycemia is linked to worse outcomes in non-diabetic patients but not significantly correlated in diabetic patients. A nomogram incorporating age, SHR, and NIHSS predicts poor outcomes in non-diabetic patients.

Background Age-related hearing loss (ARHL) is one of the main illnesses afflicting the aged population and has a significant negative impact on society, economy, and health. However, there is presently no appropriate therapeutic treatment of ARHL due to the absence of comprehensive trials. Objectives The goal of this review is to systematically evaluate and analyze recent statistics on the pathologic classifications, risk factors, treatment strategies, and drug candidates of ARHL, including that from traditional Chinese medicine (TCM), to provide potential new approaches for preventing and treating ARHL. Methods Literature related to ARHL was conducted in databases such as PubMed, WOS, China National Knowledge Infrastructure (CNKI), and Wanfang from the establishment of the database to Jan, 2023. The pathology, causal factor, pathophysiological mechanism, treatment strategy, and the drug candidate of ARHL were extracted and pooled for synthesis. Results Many hypotheses about the etiology of ARHL are based on genetic and environmental elements. Most of the current research on the pathology of ARHL focuses on oxidative damage, mitochondrial dysfunction, inflammation, cochlear blood flow, ion homeostasis, etc. In TCM, herbs belonging to the kidney, lung, and liver meridians exhibit good hearing protection. Seven herbs belonging to the kidney meridian, 9 belonging to the lung meridian, and 4 belonging to the liver meridian were ultimately retrieved in this review, such as Polygonum multiflorum Thunb., Panax ginseng C.A. Mey, and Pueraria lobata (Willd.) Ohwi. Their active compounds, 2,3,4',5-Tetrahydroxystilbene-2-O-D-glucoside, ginsenoside Rb1, and puerarin, may act as the molecular substance for their anti-ARHL efficacy, and show anti-oxidative, neuroprotective, anti-inflammatory, anti-apoptotic, or mitochondrial protective effects. Conclusion Anti-oxidants, modulators of mitochondrial function, anti-inflammation agents, vasodilators, K + channel openers, Ca 2+ channel blockers, JNK inhibitors, and nerve growth factors/neurotrophic factors all contribute to hearing protection, and herbs are an important source of potential anti-ARHL drugs.

Studying the spatiotemporal trends and influencing factors of vegetation coverage is essential for assessing ecological quality and monitoring regional ecosystem dynamics. The existing research on vegetation coverage variations and their driving factors predominantly focused on inland ecologically vulnerable regions, while coastal areas received relatively little attention. However, coastal regions, with their unique geographical, ecological, and anthropogenic activity characteristics, may exhibit distinct vegetation distribution patterns and driving mechanisms. To address this research gap, we selected Shandong Province (SDP), a representative coastal province in China with significant natural and socioeconomic heterogeneity, as our study area. To investigate the coastal–inland differentiation of vegetation dynamics and its underlying mechanisms, SDP was stratified into four geographic sub-regions: coastal, eastern, central, and western. Fractional vegetation cover (FVC) derived from MOD13A3 v061 NDVI data served as the key indicator, integrated with multi-source datasets (2000–2023) encompassing climatic, topographic, and socioeconomic variables. We analyzed the spatiotemporal characteristics of vegetation coverage and their dominant driving factors across these geographic sub-regions. The results indicated that (1) the FVC in SDP displayed a complex spatiotemporal heterogeneity, with a notable coastal–inland gradient where FVC decreased from the inland towards the coast. (2) The influence of various factors on FVC significantly varied across the sub-regions, with socioeconomic factors dominating vegetation dynamics. However, socioeconomic factors displayed an east–west polarity, i.e., their explanatory power intensified westward while resurging in coastal zones. (3) The intricate interaction of multiple factors significantly influenced the spatial differentiation of FVC, particularly dual-factor synergies where interactions between socioeconomic and other factors were crucial in determining vegetation coverage. Notably, the coastal zone exhibited a high sensitivity to socioeconomic drivers, highlighting the exceptional sensitivity of coastal ecosystems to human activities. This study provides insights into the variations in vegetation coverage across different geographical zones in coastal regions, as well as the interactions between socioeconomic and natural factors. These findings can help understand the challenges faced in protecting coastal vegetation, facilitating deeper insight into ecosystems responses and enabling the formulation of effective and tailored ecological strategies to promote sustainable development in coastal areas.

Sensitive simultaneous electrochemical sensing of phytohormones indole-3-acetic acid and salicylic acid based on a novel poly(L-Proline) nanoparticles–carbon dots composite consisting of multiwalled carbon nanotubes was reported in this study. The poly(L-Proline) nanoparticles–carbon dots composite was facilely prepared by the hydrothermal method, and L-Proline was used as a monomer and carbon source for the preparation of poly(L-Proline) nanoparticles and carbon dots, respectively. Then, the poly(L-Proline) nanoparticles–carbon dots–multiwalled carbon nanotubes composite was prepared by ultrasonic mixing of poly(L-Proline) nanoparticles–carbon dots composite dispersion and multiwalled carbon nanotubes. Scanning electron microscope, transmission electron microscope, Fourier transform infrared spectroscopy, ultraviolet visible spectroscopy, energy dispersive spectroscopy, cyclic voltammetry, electrochemical impedance spectroscopy, and linear sweep voltammetry were used to characterize the properties of the composite. poly(L-Proline) nanoparticles were found to significantly enhance the conductivity and sensing performance of the composite. Under optimal conditions, the composite-modified electrode exhibited a wide linear range from 0.05 to 25 μM for indole-3-acetic acid and from 0.2 to 60 μM for salicylic acid with detection limits of 0.007 μM and 0.1 μM (S/N = 3), respectively. In addition, the proposed sensor was also applied to simultaneously test indole-3-acetic acid and salicylic acid in real leaf samples with satisfactory recovery.

Chronic obstructive pulmonary disease (COPD) concurrent with respiratory failure (RF) is devastating, and may result in death and disability. Systemic immune-inflammation index (SII) is a new prognostic biomarker linked to unfavorable outcomes of acute coronary syndrome, ischemic stroke, and heart failure. Nonetheless, its role in COPD is rarely investigated. Consequently, this study intends to assess the accuracy of SII in predicting the prognosis of COPD. The clinical information was retrospectively acquired from the Medical Information Mart for Intensive Care-IV database. The outcomes encompassed the incidence of RF and mortality. The relationship between different SII and outcomes was examined utilizing the Cox proportional-hazards model and restricted cubic splines. Kaplan-Meier analysis was employed for all-cause mortality. The present study incorporated 1653 patients. During hospitalization, 697 patients (42.2%) developed RF, and 169 patients (10.2%) died. And 637 patients (38.5%) died during long-term follow-up. Higher SII increased the risk of RF (RF: HR: 1.19, 95% CI 1.12-1.28, P<0.001), in-hospital mortality (HR: 1.22, 95% CI 1.07-1.39, P=0.003), and long-term follow-up mortality (HR: 1.12, 95% CI 1.05-1.19, P<0.001). Kaplan-Meier analysis suggested a significantly elevated risk of all-cause death (log-rank P<0.001) in patients with higher SII, especially during the short-term follow-up period of 21 days. SII is closely linked to an elevated risk of RF and death in COPD patients. It appears to be a potential predictor of the prognosis of COPD patients, which is helpful for the risk stratification of this population. However, more prospective studies are warranted to consolidate our conclusion.