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 explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Aim To investigate the effects of m6A demethylase ALKBH5 on cardiomyocytes pyroptosis in mice with myocardial infarction(MI).Methods The MI model of left anterior descending coronary artery ligation surgery was established by knocking down ALKBH5 using adeno-associated virus,and the hypox-ia model of mouse cardiomyocytes(HL-1)was estab-lished by knocking down small interfering RNA.The effects of ALKBH5 on the pyroptosis of MI mice and hypoxic HL-1 cells were observed.Subsequently,mechanism studies were conducted at the cellular lev-el,and the binding of ALKBH5 and IGF2BP2 to NL-RP3 mRNA was detected through RNA pull down and RNA immunoprecipitation(RIP)experiments.The MeRIP-qPCR method was used to determine the effects of ALKBH5 on the mRNA m6A level of NLRP3.Acti-nomycin D for RNA stability experiments were conduc-ted to detect the effects of ALKBH5 and IGF2BP2 on the stability of NLRP3 mRNA.Results Knocking down ALKBH5 in vivo and in vitro both inhibited NL-RP3 inflammasome activation and alleviated pyroptosis in MI mice and hypoxic HL-1 cells.Mechanistically,the results showed that NLRP3 mRNA could bind to ALKBH5 protein in HL-1 cells;knocking down ALK-BH5 could increase the m6A level of NLRP3 and re-duce the stability of NLRP3 mRNA;subsequently,it was confirmed that NLRP3 mRNA and IGF2BP2 pro-tein bound to each other;knocking down IGF2BP2 in-creased the mRNA stability of NLRP3.The Rescue ex-periment showed that knocking down IGF2BP2 re-versed the decrease in NLRP3 mRNA expression caused by knocking down ALKBH5.Conclusions ALKBH5 mediated m6A modification of NLRP3 pro-motes cardiomyocytes pyroptosis in mice with myocardi-al infarction.

AIM To explore the relieving effect of Er Miao Wan on atopic dermatitis in mice.METHODS In vivo experiment:BALB/c mice were randomly divided into normal group,model group,dexamethasone group(2 mg/kg)and high,medium and low dose groups of Er Miao Wan(4.68,2.34 and 1.17 g/kg).The mouse model of atopic dermatitis was established by repeatedly smearing DNCB solution,and the model was given orally for 21 days.The skin lesion condition on the back of mice,ear swelling degree,and the weight difference between ear lobes were observed and recorded.HE staining was used to observe the histopathological changes in the skin lesion tissues of mice.Toluidine blue(TB)staining was used to observe the infiltration of mast cells in skin lesions.The expression of macrophage marker F4/80 in skin lesions was detected by IHC.The serum levels of TSLP,IL-4,IL-5 and total IgE were detected by ELISA.In vitro experiment:RAW264.7 cells in logarithmic growth period were given 400,200 and 100 μg/mL Er Miao Wan for intervention.Cell proliferation was detected by CCK-8 method.NO level in cell supernatant was detected by Griess method.TNF-α,IL-1 β and IL-6 levels in cell supernatant were detected by ELISA method.The expressions of proteins related to the MAPK/NF-κB signaling pathway in cells was detected by Western blot.RESULTS In vivo experiment:Compared with the model group,the scores of back skin lesions,the swelling degree of right ear and the weight difference between left and right ear pieces in the high-dose group of Er Miao Wan decreased(P＜0.05,P＜0.01),the thickness of skin lesions decreased,the infiltration of mast cells and macrophages decreased(P＜0.05,P＜0.01),and the inflammatory factors TSLP,IL-4,IL-5 and total IgE levels in serum decreased(P＜0.05,P＜0.01),and the expression of F4/80 in the skin lesions decreased(P＜0.01).In vitro experiment:Compared with the model group,the levels of NO,TNF-α,IL-1 β and IL-6 in Er Miao Wan 400 and 200 μg/mL groups decreased(P＜0.05,P＜0.01),and the phosphorylation levels of P38,JNK and P65 proteins decreased(P＜0.05,P＜0.01).CONCLUSION Er Miao Wan can alleviate skin lesion inflammation in DNCB-induced atopic dermatitis mice,and its mechanism may be related to inhibiting the activation of MAPK/NF-κB signaling pathway of macrophage,reducing macrophage infiltration and reducing Th2 cytokines.

Objective:To evaluate the effects of the Chinese visceral adiposity index(CVAI)and the Triglyceride-Glucose(TyG)index on the risk of hypertension among the elderly in the Zhengxiangbai Banner community of Inner Mongolia.Methods:This study selected elderly individuals who underwent physical examinations at the community health service center in Zhengxiangbai Banner, Inner Mongolia, from January 2024 to July 2024 as the study population.Based on the diagnostic criteria for hypertension, participants were divided into hypertensive and non-hypertensive groups.Data on demographics, body mass index(BMI), waist circumference(WC), fasting blood glucose(FSG), and blood lipids were collected.The CVAI, TyG, Triglyceride Glucose-Body Waist Circumference(TyG-WC), and Triglyceride Glucose-Body Mass Index(TyG-BMI)were calculated.Subjects were categorized into quartiles(1st to 4th)based on CVAI, TyG, TyG-WC, and TyG-BMI.Multivariate logistic regression analysis was employed to explore the relationship between these indicators and the risk of hypertension in the elderly.Results:This study included a total of 3, 319 elderly subjects, comprising 1, 743 individuals in the hypertensive group and 1, 576 in the non-hypertensive group.Multivariate logistic regression analysis indicated that the fourth quartile of the CVAI was a risk factor for hypertension when compared to the first quartile.Additionally, the second, third, and fourth quartiles of the TyG-BMI were identified as risk factors for hypertension relative to the first quartile.The analysis of the correlation strength between various obesity indexes and hypertension revealed that CVAI, TyG-WC, and TyG-BMI were independently correlated with the risk of hypertension.Notably, TyG-BMI exhibited a stronger association with hypertension( OR=1.006, 95% CI: 1.004-1.008).ROC curve analysis demonstrated that TyG-BMI possessed superior predictive ability for hypertension, with an AUC of 0.587(95% CI: 0.568-0.607).Furthermore, Decision Curve Analysis(DCA)also indicated that TyG-BMI had enhanced predictive capability.Further stratification by gender revealed that TyG-BMI in elderly men was independently correlated with the risk of hypertension( P<0.001), while CVAI in elderly women was independently correlated with the risk of hypertension( P<0.05).ROC curve analysis indicated that TyG-BMI in elderly men had better predictive ability for hypertension(AUC=0.582, 95% CI: 0.554~0.610).The difference in AUC compared to CVAI was statistically significant( P<0.01).DCA analysis further confirmed that TyG-BMI exhibited superior predictive ability. Conclusions:Our findings suggest that both CVAI and TyG-BMI exhibit superior predictive value for hypertension, with TyG-BMI demonstrating a particularly strong predictive capability in elderly men.

Objective:This study aims to initially establish a scoring system for comprehensively reflecting the severity of intracranial atherosclerotic lesions and to explore the correlation between this score and atherosclerotic risk factors as well as stroke events.Methods:This study retrospectively analyzed patients who underwent head and neck computer tomography angiography(CTA)examinations and had head MRI examinations within one month before or after the CTA examination from January 2021 to August 2024 in Beijing Hospital.An intracranial atherosclerosis disease score(ICADS)system was constructed based on the degree and number of vascular stenosis.The relationship between ICADS and atherosclerotic risk factors was explored by grouping patients according to the quartile of ICADS.Patients were divided into acute stroke group and non-acute stroke group to compare differences in ICADS and cerebrovascular disease risk factors between the two groups, and to investigate the correlation between stroke events and ICADS.Results:There were statistically significant differences in the proportions of patients with hypertension and diabetes among different ICADS groups.Multiple linear regression analysis showed that hypertension( B=1.17, 95% CI: 0.20-2.14, P<0.05)and diabetes( B=2.75, 95% CI: 1.85-3.64, P<0.001)were risk factors for higher ICADS.The ICADS was higher in the acute stroke group than in the non-acute stroke group(9 vs.6, P<0.001), and a higher ICADS was identified as a risk factor for stroke( OR=1.10, 95% CI: 1.07-1.14, P<0.001). Conclusions:ICADS can comprehensively reflect the severity of intracranial atherosclerotic lesions and is correlated with stroke events, making it useful for clinical screening of high-risk patients for stroke.

Objective To identify and analyze risk factors for acute renal failure (ARF) following lung transplantation and to develop a predictive model. Methods Data for this study were obtained from the United Network for Organ Sharing (UNOS) database, encompassing patients who underwent unilateral or bilateral lung transplantation between 2015 and 2022. We analyzed both preoperative and postoperative clinical characteristics of the patients. A combined approach utilizing random forest and least absolute shrinkage and selection operator (LASSO) regression was employed to identify key factors associated with the incidence of ARF post-transplantation, based on which a nomogram model was developed. The predictive performance of the constructed model was evaluated in both training and validation sets, using receiver operating characteristic (ROC) curves and area under the curve (AUC) metrics to verify and compare model effectiveness. Results A total of 15 110 lung transplantation patients were included in the study, consisting of6 041 males and 9 069 females, with a median age of 62.00 years (interquartile range: 54.00 to 67.00). The analysis revealed statistically significant differences between postoperative renal dialysis and non-dialysis patients regarding preoperative lung diagnosis, estimated glomerular filtration rate (eGFR), mechanical ventilation, preoperative ICU treatment, extracorporeal membrane oxygenation (ECMO) support, infections occurring within two weeks prior to transplantation, Karnofsky Performance Status (KPS) score, waitlist duration, double-lung transplantation, and ischemia time (P<0.05). Five key variables associated with ARF after lung transplantation were identified through random forest and LASSO regression: recipients’ eGFR, preoperative ICU treatment, ECMO support, bilateral lung transplantation, and ischemia time. A nomogram model was subsequently established. Model evaluation demonstrated that the constructed predictive model achieved high accuracy in both training and validation sets, with favorable AUC values, confirming its validity and reliability. Conclusion This study identifies common risk factors for ARF following lung transplantation and introduces an effective predictive model with potential clinical applications.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins