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.

ObjectiveThis study aims to systematically review the marketed traditional Chinese patent medicines for treating chronic gastritis （CG） in China. By analyzing their variety characteristics and prescription patterns， it seeks to provide references for clinical syndrome differentiation-based drug selection， treatment method optimization， and the design of high-quality clinical research. MethodsInformation on marketed traditional Chinese patent medicines for treating CG was collected. Microsoft Excel software was used to collate and statistically analyze representative drugs for each pathological stage， market status， syndrome types， and other contents. The Ancient and Modern Medical Case Cloud Platform （V2.3.9） was employed to analyze the formula composition patterns of standardized prescriptions. ResultsA total of 141 marketed traditional Chinese patent medicines for treating CG in China were included. Based on the disease's pathological progression， they can be classified into drugs for non-atrophic gastritis， atrophic gastritis， and precancerous lesions. Post-marketing research reveals that relevant evaluation is only conducted on 17 drugs， of which 2 involve pharmacoeconomic studies and 14 possess standardized evidence-based evidence. The primary dosage forms were capsules， granules， and tablets. From the 100 prescriptions screened according to inclusion/exclusion criteria， the varieties indicated for the stomach collateral stasis syndrome in atrophic gastritis accounted for the highest proportion. The main efficacy distributions were clearing heat， detoxifying， and relieving pain by promoting Qi circulation. Core drugs included Glycyrrhizae Radix et Rhizome， Paeoniae Radix Alba， and Aucklandiae Radix. Medicinal properties were predominantly warm and neutral. Flavors were mainly bitter， pungent， and sweet. The drugs primarily entered the spleen and stomach meridians. Analysis of the package inserts reveals that 67 products list "contraindications"， 110 include "precautions"， and 23 explicitly state "adverse reactions". ConclusionTraditional Chinese patent medicines for treating CG hold unique value in clinical practice. However， currently there are challenges such as insufficient clarity in syndrome type descriptions within package inserts and a relative lack of high-level evidence-based medical evidence， as well as pharmacoeconomic evaluations. Future efforts should focus on addressing these shortcomings by advancing research on syndrome characteristics and medication patterns based on syndrome differentiation， systematically conducting pharmacoeconomic evaluations， strengthening the accumulation of high-level evidence-based evidence， and， on this basis， improving patient medication adherence. This will comprehensively enhance the clinical application value and scientific connotation of this category of drugs.

Chronic heart failure is the terminal stage of various cardiovascular diseases， and cardiomyocyte apoptosis is the turning point of decompensation. Studies have shown that traditional Chinese medicine （TCM） could regulate apoptosis-related signaling pathways and factors and inhibit or up-regulate the expression of apoptosis-related proteins. Thus， TCM can reduce cardiomyocyte apoptosis， protect the myocardial tissue and improve the cardiac function， demonstrating remarkable clinical effects. In recent years， the research on the treatment of chronic heart failure based on the inhibition of cardiomyocyte apoptosis is increasing and becomes the current research hotspot. On the basis of literature review， this paper discovers that TCM regulates apoptosis factors and multiple signaling pathways to inhibit apoptosis and inflammation and delay the progression of chronic heart failure through classical pathways such as the death receptor pathway， the mitochondrial pathway， and the endoplasmic reticulum pathway. At the same time， the studies in this field have the following problems： Repeated studies with shallow， simple， and fragmented contents， treating animal models with TCM prescriptions without syndrome differentiation， treating diseases with drugs at only one concentration which is insufficient to indicate efficacy， and lacking comprehensive， holistic， and systematic studies on the relationships of apoptosis with inflammatory responses， pyroptosis， ferroptosis， and autophagy. In the future， more scientific， reasonable， comprehensive， and feasible experimental schemes should be designed on the basis of comprehensively mastering the research progress in this field， and the communication and cooperation between researchers in different disciplines should be strengthened. The specific pathological mechanism of cardiomyocyte apoptosis in chronic heart failure and the signaling pathways， active components， and action targets of TCM in inhibiting cardiomyocyte apoptosis in chronic heart failure should be elucidated. Such efforts are expected to provide sufficient reference for the clinical treatment of chronic heart failure.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

BACKGROUND: Urolithiasis is a widespread disease with a high prevalence worldwide. This study aims to evaluate the disease burden of urolithiasis and its trends from 1990 to 2021 globally, based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 database. METHODS: The numbers and age-standardized rates (ASRs) of incidence, disability-adjusted life years (DALYs), and mortality of urolithiasis were extracted from GBD 2021 to represent the disease burden. Joinpoint regression analyses were conducted to assess the temporal trends in the burden of urolithiasis. The male-to-female ASR ratio indices were used to evaluate sex disparities. Additionally, we explored the relationship between the ASR ratio and the sociodemographic index (SDI). RESULTS: The total numbers of incidence, DALY, and mortality of urolithiasis were 105,983,780 cases (95% uncertainty interval [UI] = 88,349,356-128,645,155 cases), 693,444 cases (95% UI = 567,765-850,490 cases), and 17,672 cases (95% UI = 13,932-21,241 cases), respectively, in 2021. There is an increasing trend in the number of these measures globally, whereas the ASRs have decreased over the past 30 years. The age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) were significantly higher in males than in females in 2021. The sex disparities in the age-standardized DALY rate (ASDR) and ASMR of urolithiasis were negatively correlated with the SDI. In 2021, the ASIR of urolithiasis was 964.70 (95% UI = 801.26-1175.09) per 100,000 people in China, which is much lower than the global average (1242.84 [95% UI = 1034.94-1506.99] per 100,000 people). Compared with the global average, a more pronounced decline in ASIR was observed in China from 1793.16 (1446.0-2235.14) in 1990 to 964.70 (801.26-1175.09) per 100,000 people in 2021. CONCLUSIONS Urolithiasis poses a significant healthcare burden worldwide. More robust global and national strategies are warranted to address the prevention and treatment, especially in low SDI countries and regions.
Humans ; Urolithiasis/mortality* ; Male ; Female ; Incidence ; Global Burden of Disease ; Disability-Adjusted Life Years ; Adult ; Middle Aged ; Risk Factors ; Sex Factors