[Objective] To compare the diagnostic accuracy of three imaging modalities, inlducing CT urography (CTU), contrast-enhanced MRI (CE-MRI), and contrast-enhanced ultrasound (CEUS) in the qualitative diagnosis of renal space-occupying lesions. [Methods] A retrospective analysis was performed on 542 patients with renal lesions confirmed by surgical pathology in our hospital during Jan.2019 and May 2024.The diagnostic results of CTU, CE-MRI and CEUS were compared and analyzed based on the patients' clinical and pathological data. [Results] The diagnostic accuracy rate of CTU, CE-MRI and CEUS were 84.50%, 83.14% and 86.14%, respectively.For the 161 patients who underwent all three examinations, CEUS was significantly more accurate than CTU (84.16% vs. 77.02%, P=0.018), while there was no significant difference between CTU or CEUS and CE-MRI (79.81%) (P>0.05). Further analysis found that for lesions ≤4 cm, the accuracy of the three examinations was as follows: CEUS=CTU 79.55%, CE-MRI 76.14%, with no significant difference (P>0.05). However, for lesions >4 cm, CEUS ranked the first, followed by CE-MRI and CTU (89.73% vs. 84.25% vs. 73.97%), and CEUS and CE-MRI were better than CTU (P<0.05). Additionally, for the diagnosis of clear cell renal carcinoma and benign renal space-occupying lesions, there was no statistically significant difference among the three imaging modalities (P>0.05), while for the qualitative diagnosis of non-clear cell renal carcinoma, CEUS ranked the first, followed by CE-MRI and CTU (83.87% vs. 74.19% vs. 56.45%), and CE-MRI and CEUS were better than CTU (P<0.05). [Conclusion] All of them have important diagnostic value, and the appropriate selection should be based on patients' specifc conditions.CEUS and CE-MRI are more accurate in the qualitative diagnosis of renal space-occupying lesions than CTU, especially for large lesions and non-clear cell carcinoma.

Background The association between occupational physical activity (OPA) and cardiometabolic risk factors remains controversial, potentially due to differences in the associations between OPA and various cardiometabolic indicators, as well as the lack of a clearly defined optimal OPA range for multiple-indicator synergistic benefits. Objective To investigate the relationship between OPA and cardiometabolic risk factors in individuals at high risk of cardiovascular disease (CVD) in Hubei Province, and to explore an optimal OPA range for multi-indicator improvements. Methods Data were derived from the Hubei Province dataset of the China Health Evaluation And Risk Reduction Through Nationwide Teamwork from 2015 to 2023, including 19028 high-risk CVD individuals. OPA (metabolic equivalent·h·d⁻¹, MET·h·d⁻¹) was assessed using the China Kadoorie Biobank physical activity questionnaire, anthropometric measurements (height, weight, waist circumference) and cardiometabolic indicators (blood pressure, fasting blood glucose, lipid profiles) were measured. Multivariate logistic regression was used to analyze the association between logOPA quartiles (Q1-Q4) and abnormal cardiometabolic indicators, while restricted cubic spline (RCS) models were employed to explore their dose-response relationships. Subgroup and interaction analyses were also conducted by gender. Results The median OPA of all participants was 12.86 MET·h·d⁻¹ (male: 14.40 MET·h·d⁻¹, female: 11.14 MET·h·d⁻¹). After adjusting for confounders, compared with the Q1 group, logOPA in the Q4 group was associated with 20% (OR=0.80, 95%CI: 0.72, 0.89), 14% (OR=0.86, 95%CI: 0.78, 0.96), and 13% (OR=0.87, 95%CI: 0.79, 0.95) reduction in the risk of abdominal obesity, low high-density lipoprotein cholesterol (HDL-C), and metabolic syndrome (MS), respectively, and 33% (OR=1.33, 95%CI: 1.18, 1.49), 33% (OR=1.33, 95%CI: 1.18, 1.50), and 38% (OR=1.38, 95%CI: 1.21, 1.57) increase in the risk of high total cholesterol (TC), high low-density lipoprotein cholesterol (LDL-C), and high non-HDL-C, respectively. Similar trends were observed in males and females, with significant positive associations of logOPA with high TC and high non-HDL-C in males (P_interaction<0.05). The risk of low HDL-C decreased rapidly when logOPA was more than 2.213 (OPA>9.14 MET·h·d⁻¹), showing an inverted L-shaped trend. The risk of high TC, high LDL-C, and high non-HDL-C increased beyond logOPA thresholds of 3.244, 2.476, and 3.377 (OPA >25.64, 11.89, and 29.28 MET·h·d⁻¹), respectively, showing a J-shaped trend. However, logOPA exhibited a U-shaped nonlinear dose-response relationship with blood pressure and fasting blood glucose abnormalities (P_non-linear<0.05) , with minimal risks at logOPA 2.969 and 2.372 (OPA of 19.47 and 10.72 MET·h·d⁻¹). Conclusion OPA exhibits heterogeneous dose-response patterns across cardiometabolic indicators. Integrating the inverted L-, J-, and U-shaped association patterns, we suggest an optimal OPA range of 9.14−25.64 MET·h·d⁻¹ for multiple cardiometabolic indicators in total individuals at high-risk of CVD, with ranges of 9.61−31.34 MET·h·d⁻¹ for males and 8.97−22.87 MET·h·d⁻¹ for females. These findings provide critical evidence for developing OPA interventions strategies targeting high-risk population for CVD.

Positron emission tomography (PET) now plays an important role in the research and development (R&D) of central nervous system (CNS) drugs. PET could characterize the biodistribution, pharmacokinetics, and receptor binding of CNS drugs quantitatively. The present review summarized the quantitative methods of PET used in the pharmacokinetics and receptor occupancy analysis of CNS drugs. Moreover, the present review listed various applications of PET supporting R&D of CNS drugs, which could provide a new direction for the R&D of CNS drugs.

Purpose/Significance To explore the application and predictive accuracy of various models in predicting the risk of ather-osclerosis in diabetic patients.Method/Process Based on the biochemical data table from the"Diabetes Complications Warning Dataset"provided by the National Population Health Science Data Center,MATLAB software is used to construct risk prediction models for diabe-tes-induced atherosclerosis.The models are built by using k-nearest neighbors(KNN),decision trees,backpropagation(BP)neural networks,and Naive Bayes algorithms,and which are subjected to comparative analysis.Result/Conclusion In terms of effectiveness,the predictive accuracy of Naive Bayes algorithm is the highest(61.6％),followed by the decision tree model(58.2％),the KNN mod-el(57.7％),and the BP neural network model(55.9％).The results of the confusion matrix and the receiver operating characteristic(ROC)curve indicate that the Naive Bayes model performs best.When comparing the models in terms of effectiveness,performance and stability,the Naive Bayes model is superior.

Objective To investigate the correlation between thyroid function,neutrophil/lymphocyte ratio(NLR),platelet/lymphocyte ratio(PLR)and diabetic ketoacidosis(DKA).Methods A total of 272 diabetic patients admitted to the Department of Endocrinology,Anhui No.2 Provincial People's Hospital were enrolled in this study from January 2021 to March 2024 and divided into DKA group(n=74),diabetic ketosis group(DK group,n=100)and simple DM group(n=98)according to their disease conditions.Serum free triiodothyronine(FT3),free tetraiodothyronine(FT4),thyroid stimulating hormone(TSH),FPG,HbA1c,anion gap(AG),white blood cells(WBC),neutrophils(N),platelets(PLT)and lymphocytes(L)were detected in each group,and NLR and PLR were calculated.The influence factors of DKA were analyzed by logistic regression,and the diagnostic value of FT3,NLR and PLR in DKA was evaluated by receiver operating characteristic(ROC)curve.Results Hospitalization days,FPG,HbA1c,incidence of LT3S,AG,WBC,N,PLT,NLR,PLR were higher in DKA group than in DM and DK groups(P<0.05),Age,FT3,FT4,TSH,L were lower in DKA group than in DM and DK groups(P<0.05).Logistic regression analysis showed that FT3,AG,NLR and PLR were the influencing factors for DKA.ROC curve showed that the area under the curve of FT3,NLR,PLR and combined detection to predict DKA were 0.961,0.938,0.810 and 0.980,the sensitivity was 87.8%,90.5%,75.7%and 98.6%,the specificity was 95.5%,92.9%,76.3%,92.4%,and the combined detection was superior to the single detection.Conclusions FT3,NLR,PLR have a certain diagnostic value for DKA,and the combined detection of the three has a high diagnostic value,which can provide a reference for clinical diagnosis of DKA.

Carcinoma-associated fibroblasts (CAFs) are the main cellular components of the tumor microenvironment and promote cancer progression by modifying the extracellular matrix (ECM). The tumor-associated ECM is characterized by collagen crosslinking catalyzed by lysyl oxidase (LOX). Small extracellular vesicles (sEVs) mediate cell-cell communication. However, the interactions between sEVs and the ECM remain unclear. Here, we demonstrated that sEVs released from oral squamous cell carcinoma (OSCC)-derived CAFs induce collagen crosslinking, thereby promoting epithelial-mesenchymal transition (EMT). CAF sEVs preferably bound to the ECM rather than being taken up by fibroblasts and induced collagen crosslinking, and a LOX inhibitor or blocking antibody suppressed this effect. Active LOX (αLOX), but not the LOX precursor, was enriched in CAF sEVs and interacted with periostin, fibronectin, and bone morphogenetic protein-1 on the surface of sEVs. CAF sEV-associated integrin α2β1 mediated the binding of CAF sEVs to collagen I, and blocking integrin α2β1 inhibited collagen crosslinking by interfering with CAF sEV binding to collagen I. CAF sEV-induced collagen crosslinking promoted the EMT of OSCC through FAK/paxillin/YAP pathway. Taken together, these findings reveal a novel role of CAF sEVs in tumor ECM remodeling, suggesting a critical mechanism for CAF-induced EMT of cancer cells.
Humans ; Paxillin/metabolism* ; Protein-Lysine 6-Oxidase/metabolism* ; Carcinoma, Squamous Cell/pathology* ; Epithelial-Mesenchymal Transition ; Integrin alpha2beta1/metabolism* ; Mouth Neoplasms/pathology* ; Collagen/metabolism* ; Fibroblasts ; Extracellular Vesicles/metabolism* ; Cell Line, Tumor ; Tumor Microenvironment

Objective:Under the background of the high-quality development of public hospitals, the affiliated hospitals of universities need to explore the effective path of interdisciplinary integration based on the current development status of disciplines, adjust the orientation, mechanism and goal of disciplinary development, and achieve the coordinated development of disciplines. This paper aims to provide exploratory ideas for the formulation of relevant systems and strategies of interdisciplinary integration for hospitals.Methods:This paper analyzes the internal influencing factors of interdisciplinary integration and development of hospitals from the perspective of discipline construction participants, and combines the overall requirements of high-quality development of public hospitals with the GREP model to build a strategic analysis framework for interdisciplinary integration of university affiliated hospitals.Results:Hospitals can use this strategic analysis framework to find problems through discipline self-evaluation, interviews, interdisciplinary integration mode and horizontal comparison of typical experiences, and grasp the main problems according to the basic steps of GREP problem solving, propose solutions, and finally draw conclusions.Conclusions:Based on four dimensions, GREP model provides a strategic analysis framework for the implementation path of promoting interdisciplinary integration in hospital design, and has certain practical significance for the formulation of hospital related strategies.

In recent years, Traditional Chinese Medicine (TCM) treatment for Alzheimer's disease has been widely concerned. At present,there are more studies on the following 6 pathways: brain-derived neurotrophic factor (BDNF)/tyrosine kinase B (TrkB) signaling pathway, phosphatidy linositol-3-kinases (PI3K)/protein kinase B (Akt) signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, protein kinase A (PKA)/cAMP response Element binding protein (CREB) signaling pathway,nuclear factor-κB (NF-κB) signaling pathway, Wnt signaling pathway.

Antibody-drug conjugates(ADCs)are commonly heterogeneous and require extensive assessment of exposure-efficacy and exposure-safety relationships in preclinical and clinical studies.In this study,we report the generation of a monoclonal antibody against monomethyl auristatin E(MMAE)and the development,validation,and application of sensitive and high-throughput enzyme-linked immunosor-bent assays(ELISA)to measure the concentrations of MMAE-conjugated ADCs and total antibodies(tAb,antibodies in ADC plus unconjugated antibodies)in cynomolgus monkey sera.These assays were suc-cessfully applied to in vitro plasma stability and pharmacokinetic(PK)studies of SMADC001,an MMAE-conjugated ADC against trophoblast cell surface antigen 2(TROP-2).The plasma stability of SMADC001 was better than that of similar ADCs coupled with PEG4-Val-Cit,Lys(m-dPEG24)-Cit,and Val-Cit linkers.The developed ELISA methods for the calibration standards of ADC and tAb revealed a correlation be-tween serum concentrations and the OD450 values,with R2 at 1.000,and the dynamic range was 0.3-35.0 ng/mL and 0.2-22.0 ng/mL,respectively;the intra-and inter-assay accuracy bias％ranged from-12.2％to-5.2％,precision ranged from-12.4％to-1.4％,and the relative standard deviation(RSD)was less than 6.6％and 8.7％,respectively.The total error was less than 20.4％.The development and validation steps of these two assays met the acceptance criteria for all addressed validation parameters,which suggested that these can be applied to quantify MMAE-conjugated ADCs,as well as in PK studies.Furthermore,these assays can be easily adopted for development of other similar immunoassays.