Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Integrins are transmembrane receptors that can coordinate signal transduction between cells and extracellular matrix or between cells.The abnormal function of integrins is one of the recognized mechanisms of tumor development.As an important regulatory mode,post-translational modification can change the conformation and physicochemical properties of proteins,thus affecting their activities,stability and functions.After the modification of the integrin,such as glycosylation and methylation,the corresponding signal transduction pathway changes,and then affects cell adhesion,migration,differentiation and other life activities,involving in diverse physiology and pathological processes.Post-translational modifications of integrins are abundant in tumor progression and play a key role in regulating the growth,metastasis and drug resistance of different tumor cells.In this review,the structure and function,post-translational modification of integrins,and their relationship with occurrence and development of tumors will be discussed,in order to provide more explorable targets for the treatment of cancer.

AIM To explore the effects of Dahuang Lingxian Recipe on Th1/Th2 cell immune imbalance in a rat model of cholestatic liver fibrosis(CLF).METHODS 20 SD rats were randomly divided into the normal group,the model group,the ursodeoxycholic acid group(0.063 g/kg)and the Dahuang Lingxian Recipe group(4.8 g/kg),with 5 rats in each group.Except for those of the normal group,the rats of all other groups had open surgery of common bile duct ligation,followed by the gavage of corresponding drug two days later,and the procurement of the samples after gavage in the third week.The rats had their degree of liver fibrosis observed by HE and Masson stainings;their levels of serum total bile acid(TBA),alkaline phosphatase(AKP),γ-glutamyltransferase(γ-GT),alanine aminotransferase(ALT),aspartate aminotransferase(AST)and total bilirubin(TBil)measured by the kit;their hepatic percentage of TGF-β1,p-Smad2 and p-Smad3 positive cells detected by immunofluorescence and immunohistochemical staining;their.hepatic expressions of TGF-β1,Smad4,NF-κB p65,Collagen Ⅰ and Collagen Ⅲ protein and mRNA detected by Western blot and RT-qPCR;their levels of helper T cell 1(Th1)and helper T cell 2(Th2)in peripheral blood detected by flow cytometry,and their ratio of Th1/Th2 calculated as well.RESULTS Compared with the model group,the groups intervened with either ursodeoxycholic acid or Dahuang Lingxian Recipe displayed well-ordered liver cells,hepatic lobules and hepatic cords;a small amount of fatty degeneration;significantly reduced connective hyperplasia of hepatic fibers;significantly narrowed fibrous cords;a small amount of blue fibrous septa;greatly improved pathological injuries including inflammatory infiltration of central vein and portal area;decreased levels of serum TBA,TBil,AKP,γ-GT,ALT and AST(P＜0.05);decreased hepatic expressions of TGF-β1,p-Smad2 and p-Smad3(P＜0.05);decreased hepatic expressions of TGF-β1,Smad4,NF-κB p65,Collagen Ⅰ and Collagen Ⅲ protein and mRNA(P＜0.05);and increased counts of Th1 cells in peripheral blood,decreased counts of Th2 cells,resultsing increased Th1/Th2 ratio(P＜0.05).And an even better effect was observed in the Dahuang Lingxian Recipe group.CONCLUSION Dahuang Lingxian Recipe can reduce or reverse CLF by inhibiting hepatic stellate cell activation through maintaining Th1/Th2 cell immune balance via the NF-κB/TGF-β1 signaling pathway.

On the basis of that the fluorescence wavelength of copper nanoclusters(CuNCs)could cover the entire visible region,multicolor fluorescent CuNCs/starch composites were prepared and applied in fingermark development.With L-glutathione as the reducing agent and protective ligand,blue emissive and orange emissive CuNCs solutions were obtained in alkaline solutions at 90℃and 25℃,respectively.With the aggregation-induced emission effect induced by ethanol as a poor solvent,the fluorescence of orange emissive CuNCs with a higher intensity was achieved in an ethanol-water solution.With ascorbic acid as the reducing agent and 3-mercaptopropionic acid as the protective agent,green emissive CuNCs solution was prepared in an acid solution.Particle morphologies,chemical compositions and optical properties of these three CuNCs above were investigated using physical characterization and spectroscopic analysis,indicating that well-dispersed CuNCs had excellent photoluminescent properties.These CuNCs solutions were combined with starch to form composite powders by simply drying.The influences of the type of CuNCs and the ratio of CuNCs to starch on the emission wavelength and fluorescence intensity of the products were studied.The obtained CuNCs/starch composites could emit blue,green and orange fluorescence under 365 nm ultraviolet light,respectively,which were suitable for fingermark development.Minutiae and partial level-3 features of latent fingermarks could be effectively developed.High-quality fluorescence fingermark images would be captured using appropriate optical filters to eliminate background interference of various substrates.

This study aimed to address the limitations of current diagnostic methods for well leg compartment syndrome(WLCS),including invasiveness,high costs,and insufficient accuracy,by proposing a solution based on electrical impedance tomography(EIT)technology.The electrical response characteristics of the human calf muscle to changes in compartment pressure using EIT were investigated,aiming to visualize the effects of pressure variations on the electrical properties within the compartment and to provide technical support for early non-invasive detection of WLCS.EIT sensors were placed on the right calf of the experimental subjects,with pressure applied externally to the right thigh.Measurements were conducted in two phases:pre-pressure(pre)and post-pressure(post).Pre-pressure,the conductivity distribution image σpre was measured when the calf was placed horizontally.Post-pressure,the calf was raised at an angle of approximately 30°,and pressures of 0,40,80,and 120 mmHg were applied to the right thigh,and the corresponding conductivity distribution images σP=0,σP=40,σP=80,andσP=120were recorded.To quantitatively analyze the pressure effects on the compartment response,paired sample t-test was used to assess the spatial-mean conductivity((σ))from the EIT reconstructed images.Compared to the horizontal position of the right calf,raising the calf at approximately 30° resulted in a significant increase in the spatial-mean conductivity(σ)of the M1 compartment.Furthermore,when pressure was applied to the right thigh while the calf remained at a 30° angle,the spatial-mean conductivity of the M1 compartment σM1 showed an increasing trend with rising pressure.The results indicated that as compartment pressure increased,the volume of extracellular fluid and ion concentration significantly increased,leading to an increase in conductivity,which reflected ischemia and hypoxia in muscle tissue and the related pathophysiological changes.EIT,due to its high sensitivity to conductivity changes,offered a potential effective diagnostic method for non-invasively monitoring the onset and progression of muscle compartment syndrome.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.

Five saponins were isolated from the kernels of Momordica cochinchinensis, by macroporous resin, silica gel, ODS column chromatography, and semi preparative HPLC. Based on MS and NMR analysis, combining with alkaline hydrolysis and acid hydrolysis, their structures were identified as: gypsogenin-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (1), quillaic acid-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (2), gypsogenin-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (3), quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (4), 18α-quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside (5). Compounds 1-5 were new compounds, and named as mubezhisides A, B, C, D, E, respectively. They all could obviously inhibited the growth of Candida albicans, C. parapsilosis, and C. tropicalis.

Isoliquiritigenin (ISL) is a chalcone compound isolated from licorice, known for its anti-diabetic, anti-cancer, and antioxidant properties. Our previous study has demonstrated that ISL effectively lowers blood glucose levels in type 2 diabetes mellitus (T2DM) mice and improves disturbances in glucolipid and energy metabolism induced by T2DM. This study aims to further investigate the effects of ISL on alleviating abnormal endoplasmic reticulum stress (ERS) caused by T2DM and to elucidate its molecular mechanisms. In vivo experiments were conducted using 8-week-old SPF male C57BL/6J mice. The T2DM animal model was established by high-fat and high-sugar diet combined with intraperitoneal injections of streptozotocin (STZ), in compliance with the ethical guidelines set by the Animal Welfare Committee of Beijing University of Chinese Medicine (approval number: BUCM-2022021503-1134). In vitro experiments employed human liver cancer HepG2 cells, which were induced with tunicamycin (TM) to establish the ERS cell model. Transcriptomic sequencing was used to analyze changes in gene expression in the liver samples of T2DM mice following ISL treatment. Real-time quantitative polymerase chain reaction (RT-qPCR) was employed to assess the regulatory effects of ISL on key ERS genes. Enzyme-linked immunosorbent assay (ELISA), Western blot (WB), and immunofluorescence techniques were used to evaluate ISL's effects on ERS-related proteins. Results indicate that ISL significantly downregulates the expression of ERS-related genes, reduces the level of glucose-regulated protein 78 (GRP78), and inhibits the phosphorylation of protein kinase RNA-like endoplasmic reticulum kinase (PERK), thereby alleviating abnormal ERS induced by T2DM. Additionally, ISL increases the protein levels of insulin receptor substrate (IRS) 1 and IRS2 and enhances the phosphorylation of protein kinase B (Akt), thereby improving insulin sensitivity. In conclusion, ISL is able to alleviate T2DM associated symptoms by improving abnormal ERS and enhancing insulin sensitivity.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.