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.

Background Metals and metalloids in fine particulate matter (PM_2.5) may cause damage to the respiratory and circulatory systems of the human body, and long-term exposure is prone to causing chronic poisoning, cancer, and other adverse effects. Objective To assess the distribution characteristics of metals and metalloids in outdoor PM_2.5 in a southern city of China, conduct source apportionment, and evaluate the associated health risks, thereby providing theoretical support for further pollution control measures. Methods PM_2.5 samples were collected in districts A, B, and C of a southern China city, and the concentrations of 17 metals and metalloids were detected by inductively coupled plasma-mass spectrometry (ICP-MS). Pollution sources were assessed through enrichment factor and principal components analysis, and the main pollution sources were quantified using absolute principal component scores-multivariate linear regression (APCS-MLR). Health risks were evaluated based on the Technical guide for environmental health risk assessment of chemical exposure (WS/T777—2021). Results The ambient air PM_2.5 concentrations in the city were higher in winter and spring, and lower in summer and autumn. The annual average concentrations of ambient PM_2.5 in districts A, B, and C were 36.7, 31.9, and 24.4 μg·m⁻³, respectively. The ambient PM_2.5 levels in districts B and C were below the second-grade limit set by the Ambient air quality standards (GB 3095—2012). The enrichment factors of cadmium (Cd), aluminum (Al), and antimony (Sb) were greater than 10, those of copper (Cu), lead (Pb), arsenic (As), nickel (Ni), mercury (Hg), and molybdenum (Mo) fell between 1 and 10, and those of manganese (Mn), vanadium (V), chromium (Cr), cobalt (Co), barium (Ba), beryllium (Be), and uranium (U) were below or equal to 1. The comprehensive evaluation of source analysis showed that the main pollution sources in districts A and C and the whole city were coal-burning. In district B, the main pollution source was also coal combustion, followed by industrial process sources and dust sources. The carcinogenic risks of As and Cr were between 1×10⁻⁶ and 1×10⁻⁴. However, the hazard quotients for 15 metals and metalloids in terms of non-carcinogenic risk were below 1. Conclusion Cr and As in the atmospheric PM_2.5 of the city present a certain risk of cancer and should be paid attention to. In addition, preventive control measures should be taken against relevant pollution sources such as industrial emission, dust, and coal burning.

Objective To establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. Methods Patients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. Results A total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. Conclusion For patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.

In November 2024， the Expert Group on Alcohol-related Liver Disease released a position statement on metabolic dysfunction and alcohol-related liver disease （MetALD）. MetALD is a new subtype of steatotic liver disease and refers to MASLD patients with a relatively large amount of alcohol consumption. The position statement points out the importance of accurate evaluation of alcohol consumption and recommends to quantify alcohol consumption using standard methods and alcohol biomarkers， and a comprehensive diagnosis should be made based on metabolic risk factors. In addition， the position statement analyzes the influence of drinking pattern on the diagnosis of MetALD and recommends to consider long-term drinking history during typing. The position statement also discusses the complex association between drinking and the diseases including metabolic syndrome， hepatic steatosis， fibrosis， and type 2 diabetes mellitus， and it is pointed out that the hierarchical management of patients should be optimized based on liver histological models and noninvasive models. The position statement elaborates on the definition of MetALD， drinking assessment， the interaction between alcohol use and metabolic dysfunction， and the methods for comprehensive management of MetALD， in order to facilitate learning and provide guidance for clinicians and researchers in clinical practice.

Objective To understand the influencing factors of chronic dyslipidemia in T2DM patients who signed a contract for diabetes point system management in Qingpu District, and to provide a basis for comprehensive intervention and prevention and control of dyslipidemia in T2DM patients and to optimize the management strategy of Qingpu District diabetes point system. Methods Among the T2DM patients who signed the diabetes point system from 2017 to 2023, patients with chronic dyslipidemia and normal blood lipids were selected and included in the case group and the control group, respectively. A case-control study was conducted with 1:1 matching by age and gender to analyze the factors influencing dyslipidemia. Results Multifactorial paired logistic regression analysis showed that overweight/obesity and central obesity and smoking in T2DM patients increased the risk of dyslipidemia by 1.93, 2.27, and 2.16 times, respectively. Long-term use of lipid-lowering drugs, duration of diabetes for 5 years or more, regular physical exercise, knowledge of blood lipid status, and married status could reduce the risk of dyslipidemia in T2DM patients (OR values were 0.547, 0.452, 0.685, 0.386 and 0.354, respectively). Current complications (history of stroke, coronary heart disease, and renal insufficiency) were also associated with dyslipidemia (OR=1.802, 95% CI:1.125-2.888). Conclusion The management of diabetes point system in Qingpu District should strengthen the feedback and interpretation of blood lipid monitoring results, improve patients’ health awareness of blood lipid management, and actively take comprehensive management of lifestyle intervention and drug treatment to effectively control blood lipid and reduce the occurrence of related complications.

OBJECTIVE To establish the fingerprint of Gerbera delavayi and the methods for the content determination of 11 components in G. delavayi. METHODS High-performance liquid chromatography（HPLC）was adopted to establish the fingerprints of 13 batches of G. delavayi（No. S1-S13）， and the similarities were evaluated according to Similarity Evaluation System of Chromatographic Fingerprint of TCM （2012 edition）， while the common peaks were identified. Hierarchical clustering analysis （HCA）， principal component analysis （PCA） and orthogonal partial least square-discriminant analysis （OPLS-DA） were carried out by using SPSS 25.0 software and SIMCA 14.1 software. The contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， 3，8-dihydroxy-4-methoxy-2-oxo-2H-1-benzopyran-5-carboxylic acid， caffeic acid， 3-hydroxy-4-methoxy-2- oxo-2H-1-benzopyran- 5-carboxylic acid， luteolin-7-O-β-D-glucoside， isochlorogenic acid A， apigenin-7-O-β-D-glucoside， isochlorogenic acid C and xanthotoxin were determined by HPLC. RESULTS The similarities in HPLC fingerprint of 13 batches of G. delavayi were 0.801-0.994； a total of 38 common peaks were identified and 13 common peaks were identified. The results of HCA showed that S1-S5 and S7 were clustered into one group， S6 into one category， S8 into one category， S9 and S11 into one category， S10， S12 and S13 into one category， and the results of PCA were consistent with them. The results of OPLS-DA showed that variable importance values for the projection of peak 7 （chlorogenic acid）， peak 21 （isochlorogenic acid A）， peak 26 （xanthotoxin）， peak 19 （isochlorogenic acid B）， peak 33， peak 13， peak 23 （isochlorogenic acid C）， peak 2 （new chlorogenic acid）， peak 17 （luteolin-7-O-β-D- glucoside） were greater than 1. The above 11 components had good linearity in their respective detection concentration ranges （r was greater than 0.999）. RSDs of precision， repeatability， and stability tests were not more than 2% （n＝6）. The average recovery rates were 92.54%-105.55%， and the RSDs were 0.83%-1.93% （n＝6）. The average contents of 11 components were 0.744， 5.014， 0.646， 0.431， 0.069， 0.582， 0.979， 2.754， 0.157， 1.284 and 2.943 mg/g， respectively. CONCLUSIONS The constructed HPLC fingerprint and content determination methods are simple， accurate and stable， which can provide reference for quality control of G. delavayi. Xanthotoxin， chlorogenic acid， isochlorogenic acid A， luteolin-7-O- β -D-glucoside， isochlorogenic acid C and new chlorogenic acid can be used as markers for G. delavayi.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

Background: Diabetic kidney disease (DKD) is recognized as a significant complication of diabetes mellitus and categorized into glomerular DKDs and tubular DKDs, each governed by distinct pathological mechanisms and biomarkers. Methods: Through the identification of common features observed in glomerular and tubular lesions in DKD, numerous differentially expressed gene were identified by the machine learning, single-cell transcriptome and mendelian randomization. Results: The diagnostic markers versican (VCAN) was identified, offering supplementary options for clinical diagnosis. VCAN significantly highly expressed in glomerular parietal epithelial cell and proximal convoluted tubular cell. It was mainly involved in the up-regulation of immune genes and infiltration of immune cells like mast cell. Mendelian randomization analysis confirmed that serum VCAN protein levels were a risky factor for DKD, while there was no reverse association. It exhibited the good diagnostic potential for estimated glomerular filtration rate and proteinuria in DKD. Conclusion VCAN showed the prospects into DKD pathology and clinical indicator.