BACKGROUND:Sarcopenia is an age-related systemic skeletal muscle disease,which is associated with a variety of adverse outcomes such as falls,functional decline,frailty,and death.Postmenopausal women are one of the high-risk groups for sarcopenia.OBJECTIVE:To develop a predictive model for assessing the risk of sarcopenia in Chinese postmenopausal women based on high-quality database.METHODS:Data for this study were derived from 2 370 postmenopausal women from the China Health and Retirement Longitudinal Study(CHARLS),and sarcopenia was assessed using the Asian Working Group on Sarcopenia 2019(AWGS2019)recommended metrics.The study cohort was randomized into a training set(70％)and a validation set(30％).Risk factors for sarcopenia in postmenopausal women were screened using the least absolute shrinkage and selection operator,ten-fold cross-validation,and logistic regression.Nomogram predicting the risk of sarcopenia in postmenopausal women was constructed based on the risk factors,and the model efficacy was evaluated by the receiver operating characteristic curve and area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS AND CONCLUSION:The prevalence of sarcopenia in this study was 23.50％and age,place of residence,sleep quality,cognitive function,depression,and the number of chronic diseases were selected as predictors of sarcopenia in postmenopausal women.The nomogram model showed good discrimination between the training and validation sets,with an AUC value of 0.751(95％confidence interval=0.724-0.778,P＜0.001),a specificity of 72.2％,and a sensitivity of 63.2％in the training set,and an AUC value of 0.763(95％confidence interval=0.721-0.805,P＜0.001),with a specificity of 69.6％and a sensitivity of 70.8％.The calibration curve showed a relatively significant agreement between the nomogram model and the actual observations,and the decision curve analysis demonstrated broad and good clinical utility.To conclude,the nomogram to assess the risk of sarcopenia constructed based on age,place of residence,sleep quality,cognitive function,depression,and number of chronic diseases,provides an effective tool for identifying and eliminating risk factors for sarcopenia in Chinese postmenopausal women,and helps to reduce the incidence of sarcopenia.

BACKGROUND:Sarcopenia is an age-related systemic skeletal muscle disease,which is associated with a variety of adverse outcomes such as falls,functional decline,frailty,and death.Postmenopausal women are one of the high-risk groups for sarcopenia.OBJECTIVE:To develop a predictive model for assessing the risk of sarcopenia in Chinese postmenopausal women based on high-quality database.METHODS:Data for this study were derived from 2 370 postmenopausal women from the China Health and Retirement Longitudinal Study(CHARLS),and sarcopenia was assessed using the Asian Working Group on Sarcopenia 2019(AWGS2019)recommended metrics.The study cohort was randomized into a training set(70％)and a validation set(30％).Risk factors for sarcopenia in postmenopausal women were screened using the least absolute shrinkage and selection operator,ten-fold cross-validation,and logistic regression.Nomogram predicting the risk of sarcopenia in postmenopausal women was constructed based on the risk factors,and the model efficacy was evaluated by the receiver operating characteristic curve and area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS AND CONCLUSION:The prevalence of sarcopenia in this study was 23.50％and age,place of residence,sleep quality,cognitive function,depression,and the number of chronic diseases were selected as predictors of sarcopenia in postmenopausal women.The nomogram model showed good discrimination between the training and validation sets,with an AUC value of 0.751(95％confidence interval=0.724-0.778,P＜0.001),a specificity of 72.2％,and a sensitivity of 63.2％in the training set,and an AUC value of 0.763(95％confidence interval=0.721-0.805,P＜0.001),with a specificity of 69.6％and a sensitivity of 70.8％.The calibration curve showed a relatively significant agreement between the nomogram model and the actual observations,and the decision curve analysis demonstrated broad and good clinical utility.To conclude,the nomogram to assess the risk of sarcopenia constructed based on age,place of residence,sleep quality,cognitive function,depression,and number of chronic diseases,provides an effective tool for identifying and eliminating risk factors for sarcopenia in Chinese postmenopausal women,and helps to reduce the incidence of sarcopenia.

ObjectiveTo explore the inhibitory effect and related molecular mechanisms of Saponin of Schizocapsa plantaginea HanceⅠ （SSPHⅠ） on human nasopharyngeal carcinoma HONE-1 cells. MethodsThe effect of SSPHⅠ on HONE-1 cell viability was detected using the CCK-8 assay. Its inhibitory effect on cell proliferation was evaluated through a colony formation assay. Changes in cell invasion ability were analyzed using the Transwell assay. Intracellular reactive oxygen species （ROS） levels were measured using the DHE fluorescent probe. The extent of intracellular content release was reflected by the LDH release assay. The rate of cell pyroptosis was detected using the Annexin-V/PI double staining method. Changes in the expression of proteins related to the classical pyroptosis pathway were examined by Western Blot. ResultsCCK-8 assay showed that treatment with SSPHⅠ for 24 hours reduced HONE-1 cell viability in a concentration-dependent manner， with an IC50 value of 3.383 μmol/L. In the colony formation assay， the number of HONE-1 cell colonies gradually decreased with increasing concentrations of SSPHⅠ （P<0.01）. The Transwell assay revealed that the number of cells migrating through the chamber was reduced following SSPHⅠ treatment （P<0.01）. DHE fluorescence probe detection indicated that intracellular ROS fluorescence intensity increased after SSPHⅠ treatment （P<0.001）. The LDH release assay showed that LDH activity in the cell supernatant increased with higher concentrations of SSPHⅠ （P<0.001）. Annexin-V/PI double staining demonstrated that the proportion of Annexin-V/PI-positive cells increased after SSPHⅠ treatment （P<0.001）. Western blot analysis showed that， compared with the control group， the protein expression levels of cleaved-Caspase-1 and GSDMD-N-terminal were upregulated in SSPHⅠ-treated cells （P<0.05）， and NLRP3 protein expression levels also increased （P<0.05）. ELISA results showed that the levels of IL-1β and IL-18 in the cells increased with higher concentrations of SSPHⅠ （P<0.05）. ConclusionSSPHⅠ can induce pyroptosis in nasopharyngeal carcinoma HONE-1 cells by regulating the ROS/NLRP3/Caspase-1 signaling axis， thereby exerting an anti-nasopharyngeal carcinoma effect. This suggests that SSPHⅠ may serve as a potential therapeutic agent for nasopharyngeal carcinoma.

Objective: To systematically compare the types and contents of volatile organic compounds (VOCs) in purplish-brown and yellow-brown Ziziphi Spinosae Semen, and to provide a scientific basis for their rapid identification and quality evaluation.
Methods: Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was employed to determine the VOCs in two colored samples. GC-IMS spectra and fingerprint profiles were established, and chemometric methods including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied to visualize the differences in volatile components.
Results: A total of 44 VOCs were identified, including 1 aldehyde, 9 esters, 10 ketones, 2 enals, 14 alcohols, 3 acids, 2 furans, 1 disulfide, and 2 hydrocarbons. Alcohols and esters were the main volatile components. The fingerprint profiles showed high consistency within groups but significant differences between groups. Both PCA and PLS-DA effectively distinguished the two sample types. Compounds such as pentanol, methyl butyrate, 2-ethylfuran, 2-hexanol, and 2-methylpropenal were identified as key markers for differentiation.
Conclusion: HS-GC-IMS combined with chemometrics accurately distinguishes the volatile compounds of Ziziphi Spinosae Semen with different colors. This method is rapid, sensitive, and suitable for quality control and rapid authentication of Ziziphi Spinosae Semen.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Pancreatic cancers (PCs) is a common malignant tumor with poor prognosis in the digestive system. Its main treatment methods include surgery, radiotherapy, chemotherapy, and targeted therapy. The early diagnosis rate of hidden onset of PCs is low, and most patients have already lost the opportunity to undergo surgery when diagnosed with PCs. Chemotherapy is still the main treatment for advanced PCs, but the use of chemotherapy drugs in PCs can easily lead to drug resistance. The most significant feature that distinguishes PCs from other tumors is its rich and dense matrix, which not only hinders drug penetration but also impedes the infiltration of immune cells. The above reasons have led to a very low survival rate of PCs patients. Therefore, drug delivery systems are very important in the diagnosis and treatment of PCs. They can improve drug delivery, enhance biological barrier penetration, reduce side effects, and combine multiple treatment methods. Therefore, the treatment prospects of PCs are very broad. Currently, drug delivery systems widely applied in PCs primarily include nanodrug delivery systems, tumor microenvironment-targeted drug delivery system, immunotherapy drug delivery system, gene therapy drug delivery system, and combination therapy drug delivery system that synergize multiple therapeutic modalities. Emerging drug delivery systems (DDSs) have revolutionized PCs treatment by addressing these challenges through multiple mechanisms. Nanoformulations improve drug solubility, prolong circulation time, and reduce systemic toxicity via passive/active targeting. Smart DDSs responsive to PCs-specific stimuli enable extracellular matrix degradation, tumor-associated fibroblasts reprogramming, and vascular normalization to enhance drug accessibility. Last but not least, carrier systems loaded with myeloid-derived suppressor cell inhibitors or T cell activators can reverse immunosuppression and potentiate immunotherapy efficacy. Advanced platforms co-deliver chemotherapeutics with immunomodulators, gene-editing tools, or sonodynamic agents to achieve synergistic antitumor effects. These platforms aim to address critical challenges in PCs treatment, such as enhancing drug bioavailability, overcoming stromal barriers, reprogramming immunosuppressive niches, and achieving multi-mechanistic antitumor effects. This article provides a systematic summary and prospective analysis of the current development status, latest cutting-edge advances, opportunities, and challenges of the above-mentioned drug delivery systems in the field of PCs therapy.

Objective To screen for key genes and important pathways common for different etiologies of acute kidney injury(AKI)by pathway-associated deep neural network and multiple machine learning algorithms.Methods AKI microarray datasets GSE30718,GSE37838,GSE53769,GSE108113,GSE125779,GSE99325,and GSE174020 downloaded from the Gene Expression Omnibus(GEO)database were merged,including 60 kidney samples from AKI patients and 79 kidney samples from healthy controls.They were divided(8∶2)into training sets and test sets,and were used to train and evaluate pathway-associated deep neural network and 4 machine learning algorithms,including least absolute shrinkage and selection operator(LASSO),random forest(RF),support vector machine-recursive feature elimination(SVM-RFE),and extreme gradient boosting(XgBoost),to screen for common key genes and pathways of different etiologies of AKI.The downloaded datasets GSE99340 and GSE1563 were merged,including 43 kidney samples from AKI patients and 36 kidney samples from healthy controls,which were used as external validation sets for LASSO model and nomogram performance test based on the final screened genes.The pathway-associated deep neural network and machine learning algorithms were evaluated using receiver operating characteristic curves,precision,recall,accuracy,and F1-score.The immune cell infiltration characteristics were explored in AKI via cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT),and Pearson correlation coefficients were used to evaluate the correlation between the final screened common key genes and immune cell infiltration levels.Results The pathway-associated deep neural network trained by 5-fold cross validation produced an area under curve(AUC)of 0.914 5±0.007 0,a precision of 0.750 0±0.044 0,a recall of 0.923 1±0.048 0,an accuracy of 0.838 7±0.016 0,and an F1-score of 0.827 6±0.020 0 in the test set,yielding a robust and highly accurate classification performance for AKI,and identified key pathways and a subset of candidate genes.The 4 machine learning algorithms all achieved high discriminative performance for AKI in the test set with AUC≥0.860,precision≥0.750,recall≥0.800,and F1-score≥0.774,and screened 7 common key genes for AKI with different etiologies,including CD86,C-X-C motif chemokine ligand 10(CXCL10),dynamin 2(DNM2),proto-oncogene FOS,transcription factor 12(TCF12),VGF nerve growth factor inducible(VGF),and A kinase anchoring protein 5(AKAP5).Based on the final screened common key genes,the LASSO model had an AUC of 0.940 4 for the test set and an AUC of 0.944 4 for the external validation,and the model showed a very high discriminatory ability for the AKI,which demonstrated the overall regulatory performance of the genes.The nomogram constructed based on the screened 7 genes demonstrated the highest classification performance with an AUC of 0.928 9,validating the outstanding contribution and overall action performance of the screened individual genes.Immune cell infiltration analysis showed that there were significant differences in B cells na?ve,mast cells activated,monocytes,macrophages M1,B cells memory,and dendritic cells activated between AKI samples and healthy control samples(all P＜0.05).Macrophages M1 and monocytes were positively correlated with CD86 and CXCL10,mast cells activated were positively correlated with FOS,and B cells na?ve were negatively correlated with CD86 and CXCL10(all P＜0.01).Mast cells activated were positively correlated with VGF and negatively correlated with CD86 and TCF12,while memory B cells were positively correlated with CD86(all P＜0.05).Conclusion Strategy combining pathway-associated deep neural network and multiple machine learning classifiers can mine high-value key genes from high-dimensional,complex and heterogeneous transcriptomic data as potential targets for therapeutic interventions in AKI.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective:To compare the short-term clinical outcomes of robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) in treating gastric cancer, as well as the overall 5-year's survival rate.Methods:In this retrospective cohort study, 874 patients undergoing minimally invasive gastrectomy were recruited from Jan 2016 to Jan 2020 (LG: n=719; RG: n=155). A one-to-one propensity score matching analysis was applied to minimize the selection bias due to confounding factors, yielding 150 patients in each of the RG and LG groups. After matching, the short-term outcomes and 5-year overall survival were compared in the two groups. Results:The propensity score matching cohort analysis showed a similar 5-year overall survival between RG and LG groups ( P=0.235). Concerning the short-term outcomes, the RG compared to LG resulted in lower blood loss ( P=0.011), lower postoperative complications ( P=0.001), less postoperative pain ( P=0.014), earlier initiation of soft diet ( P=0.010), shorter hospital stay ( P=0.011), but higher hospitalization expenses ( P=0.004). Conclusions:RG had a similar overall survival outcome compared to LG while offering better safety and efficacy in terms of less blood loss, lower surgery complications, faster recovery, and less postoperative pain. Higher hospital expenses were the main disadvantage of RG that could limit its application.

High myopia is a refractive abnormality characterized by excessive elongation of the eye axis.The sclera,as an important part of the eye axis regulation,plays a key role in the occurrence and development of high myopia.In this pa-per,based on the domestic and international articles,the pathological changes and related regulatory molecules of the scle-ra in high myopia were systematically summarized from the features of scleral lesions in high myopia and the gene regula-tion and signaling pathways affecting the ultrastructure and mechanical properties of the sclera,thus providing a theoretical basis for the study of the pathological mechanism of high myopia.