Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

Objective To quantitatively assess the exposure-response association between exposure to heatwave and sudden death, estimate the attributable excess deaths, and identify potential vulnerable subgroups. Methods A time-stratified case-crossover study was conducted among residents who died from sudden death in Jiangsu Province, China between 2015 and 2021. Heatwave events in Jiangsu Province, defined using varying relative temperature thresholds and durations, were identified using temperature data from the China Meteorological Administration Land Data Assimilation System (CLDAS V2.0). Individual heatwave exposure was assessed based on each subject's residential address. The exposure-response association between heatwave and sudden death was evaluated using conditional logistic regression model combined with a Distributed Lag Nonlinear Model(DLNM). Heatwave-attributable excess deaths were estimated. Stratified analyses by sex and age were performed to assess potential effect modifications. Results Under all definitions, exposure to heatwave was significantly associated with an increased risk of sudden death, and the risk increased with the intensity of heatwave. Using the P95_3d definition (temperature exceeding the 95th percentile for ≥3 consecutive days), heatwave was significantlyassociated with a 56% increased risk of sudden death (95% CI: 31%, 86%). The population-attributable fraction of sudden death due to heatwave exposure was 1.45% (95% CI: 0.97%, 1.90%). Stratified analyses indicated no statistically significant differences in the association between heatwave exposure and sudden death across age or sex subgroups. Conclusion Heatwave exposure was associated with an increased risk of sudden death. Reducing heatwave exposure during summer may help lower the occurrence of sudden death.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

ObjectiveTo compare the differences between clinical and environmental sources of Acinetobacter baumannii （AB） at a tertiary hospital in Guangzhou in terms of molecular epidemiological characteristics， antimicrobial resistance， disinfectant tolerance， virulence and the distribution of related genes， as well as plasmid epidemiological characteristics； and to assess the association between environmental and clinical strains and the potential transmission risks associated with environmental contamination. MethodsA total of 118 clinical and 102 environmental AB isolates were collected from a tertiary hospital in Guangzhou between 2024 and 2025. Species identification was performed using mass spectrometry and 16S rRNA sequencing； minimum inhibitory concentrations （MICs） for eight antimicrobial agents were determined using the agar dilution method； biofilm formation capacity was assessed using the crystal violet staining method； A Galleria mellonella infection model was used to evaluate the virulence； whole-genome sequencing was employed for multilocus sequence typing （MLST）， phylogenetic analysis， and studies on the distribution of resistance， disinfectant resistance and virulence genes， and plasmid screening. ResultsA total of 38 known ST types were identified among the 220 AB strains， with ST2 and ST40 being the predominant lineages. Antimicrobial susceptibility testing revealed that the clinical infection group exhibited resistance to minocycline， imipenem and other antibiotics， as well as the tolerance levels to the disinfectants triclosan and benzalkonium bromide， were generally higher than those in the environmental group （P＜0.001）， and the detection rates of drug resistance genes such as bla_OXA-23 and adeB all exceeded 70.0%. Statistical analysis confirmed that the MIC values of TCS and BAB were significantly positively correlated with various antibiotic resistance phenotypes （P＜0.05）. In biofilm experiments， the proportion of strong biofilm-forming strains in the environmental group （64.7%） was significantly higher than that in the clinical infection group （11.9%；χ²=69.06， df=2， P＜0.000 1）， and the mortality rate of the strains increased with enhanced biofilm-forming ability. Furthermore， a total of 41 plasmid lineages and 219 insertion sequences were detected； ISs such as IS1006 and IS1007 were frequently co-occurring with resistance and virulence genes including bla_OXA-23 and katA. ConclusionsThe predominant lineages of AB in this tertiary hospital were ST2 and ST40. The clinical infection group generally exhibits higher levels of antibiotic resistance and tolerance to disinfectants compared to the environmental group， while biofilm-forming ability differs ： the environmental group dominates in strong biofilm formation， and the clinical group dominates in weak to moderate biofilm formation. Plasmids and ISs may be involved in the co-occurrence and dissemination control strategies and for the molecular epidemiological surveillance of multidrug-resistant bacteria.

Objective To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

Fungal keratitis represents a significant cause of blindness, with current therapeutic approaches yielding limited success. The disease's onset and progression are primarily driven by fungal virulence factors and the host's immune response. The innate immune system is the first to respond, with neutrophils playing a pivotal role in the antifungal defense. Although neutrophils are critical for pathogen clearance, their excessive or abnormal activation can lead to tissue damage, exacerbating the disease. Thus, elucidating the mechanisms underlying neutrophil activity in fungal keratitis is crucial for refining treatment strategies. This article aims to systematically review the principal antimicrobial mechanisms employed by neutrophils, including phagocytosis, degranulation, and the formation of neutrophil extracellular traps(NETs). Furthermore, it explores the crosstalk between neutrophils and macrophages, alongside their collective impact and underlying mechanisms in the context of fungal keratitis. Exploration of the mechanisms of fungal keratitis facilitates precise intervention and enhances the efficacy of treatment.

Perfluorobutyric acid (PFBA) is a representative short-chain compound of per- and polyfluoroalkyl substances (PFAS), which is widely used in fluorochemical manufacturing, food packaging, and outdoor textile processing industries. PFBA primarily enters into the human body via oral intake, inhalation, and dermal exposure and can be efficiently metabolized. PFBA exhibits cytotoxicity by disrupting cell proliferation, inducing oxidative stress, and disturbing lipid metabolism, thereby impairing cellular homeostasis. In addition, PFBA can induce abnormal activation of peroxisome proliferator-activated receptor α-dependent and/or independent pathways, leading to lipid metabolism disorders and subsequent liver injury. Animal studies have demonstrated that PFBA exposure alters renal biochemical parameters and induces epidermal inflammation, abnormal keratinization, and even necrosis, suggesting potential nephrotoxicity and dermal toxicity. PFBA is capable of crossing the placental barrier, and PFBA levels in umbilical cord blood have been negatively correlated with insulin and insulin-like growth factor 1. Moreover, plasma PFBA levels in patients infected with coronavirus disease 2019 have been associated with infection severity, indicating potential reproductive, developmental, and immunotoxic effects. At present, systematic occupational and environmental exposure monitoring data for PFBA remain limited, the toxic mechanisms in certain target organs have not been fully elucidated, and the molecular regulatory networks underlying reproductive and immune toxicity remain unclear. Future research should focus on improving PFBA monitoring strategies, strengthening studies on PFBA occupational exposure detection methods, toxic effects and mechanisms, and refining occupational risk assessment systems, to provide a scientific basis for establishing occupational exposure limits, optimizing risk management strategies, and safeguarding public health.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.