This paper investigates the impact of the model top and damping layer on the numerical simulation of tropical cyclones(TCs)and reveals the significant role of stratospheric gravity waves(SGWs).TCs can generate SGWs,wh...This paper investigates the impact of the model top and damping layer on the numerical simulation of tropical cyclones(TCs)and reveals the significant role of stratospheric gravity waves(SGWs).TCs can generate SGWs,which propagate upward and outward into the stratosphere.These SGWs can reach the damping layer,which is a consequence of the numerical scheme employed,where they can affect the tangential circulation through the dragging and forcing processes.In models with a higher top boundary,this tangential circulation develops far from the TC and has minimal direct impact on TC intensity.By comparison,in models with a lower top(e.g.,20 km),the damping layer is located just above the top of the TC.The SGW dragging in the damping layer and the consequent tangential force can thus induce ascent outside the eyewall,promote latent heat release,tilt the eyewall,and enlarge the inner-core radius.This process will reduce inner-core vorticity advection within the boundary layer,and eventually inhibits the intensification of the TC.This suggests that when the thickness of the damping layer is 5 km,the TC numerical model top height should be at least higher than 20 km to generate more accurate simulations.展开更多
The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top,refining the vertical resolution,and the assimilation of operationally available observations,includ...The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top,refining the vertical resolution,and the assimilation of operationally available observations,including conventional and satellite observations,on continental U.S.winter short-range weather forecasting,were investigated in this study.The initial and predicted wind and temperature profiles were analyzed against conventional observations.Generally,the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used.Negative impacts were also observed in both the initial wind and temperature profiles,over the lower troposphere.Different from the results by only raising the model top,the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used.Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill.The major improvements caused by raising the model top with refined vertical resolution,as well as those caused by data assimilation,were in both cases located in the tropopause and lower stratosphere.Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature.These negative impacts were related to the uncertainties caused by more stratospheric information,as well as to some physical processes.A case study shows that when we raise the model top,put more vertical layers in stratosphere and apply data assimilation,the precipitation scores can be slightly improved.However,more analysis is needed due to uncertainties brought by data assimilation.展开更多
Objective:To analyze the impact of nursing interventions based on quantitative assessment using the Kano model on the quality of rehabilitation in patients with early-stage ovarian cancer following laparoscopic radica...Objective:To analyze the impact of nursing interventions based on quantitative assessment using the Kano model on the quality of rehabilitation in patients with early-stage ovarian cancer following laparoscopic radical surgery.Methods:A prospective clinical study was conducted involving 96 patients with newly diagnosed early-stage ovarian cancer who underwent laparoscopic radical surgery from December 2023 to December 2025.Patients were randomly assigned to groups using a random number table method before surgery.After surgery,the control group(n=48)received routine quantitative assessment nursing interventions,while the observation group(n=48)received nursing interventions based on quantitative assessment using the Kano model.Both groups received continuous nursing care until discharge.Differences between the groups were compared in terms of negative emotions,quality of life scores before and after postoperative intervention,postoperative recovery indicators,and nursing satisfaction evaluations on the day of discharge.Results:After intervention,the observation group had lower scores on the Self-Rating Anxiety Scale(SAS)and Self-Rating Depression Scale(SDS),as well as shorter recovery times for gastrointestinal function and food intake,and a shorter hospital stay compared to the control group.Additionally,the observation group had higher scores on the Quality-of-Life Instrument for Cancer Patients-Ovarian Cancer(QLICP-OV)than the control group,with statistically significant differences(p<0.05).The overall satisfaction with nursing care in the observation group was also higher than that in the control group,with a statistically significant difference(p<0.05).Conclusion:Implementing quantitative evaluation nursing interventions based on the Kano model for patients with early-stage ovarian cancer after laparoscopic radical surgery can,by addressing their postoperative basic health,disease awareness,and other intervention content needs to a comprehensive degree,actively promote postoperative recovery and improve their mental health and quality of life.展开更多
The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These...The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.展开更多
The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is m...The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.展开更多
A novel fractional elastoplastic constitutive model is proposed to accurately characterize the deformation of sandstone under true-triaxial stress states.This model is founded on the yield function and the fractional ...A novel fractional elastoplastic constitutive model is proposed to accurately characterize the deformation of sandstone under true-triaxial stress states.This model is founded on the yield function and the fractional flow rule.The yield function includes parameters that govern the evolution of yield surface,enabling an accurate description of three-dimensional stress states.The direction of plastic flow is governed by the two different fractional orders,which are functions of the plastic internal variable.Additionally,a detailed process is proposed for identifying the yield function parameters and fractional orders.Subsequently,the relationship between the fractional order and the direction of plastic flow in the meridian and deviatoric planes is examined,characterized by the dilation angle and the plastic deflection angle,respectively.The non-orthogonal flow rule,also referred to as the fractional flow rule,allows for a border range of plastic deflection and dilation angles compared to the orthogonal flow rule,thereby significantly enhancing its applicability.The validity and accuracy of proposed model are verified by comparing the analytical solution of the constitutive model with the experimental data.A comparison between the non-orthogonal flow rule and orthogonal flow rule is conducted in both the deviatoric and meridian planes.The further comparison of the stress-strain curves for the non-orthogonal and orthogonal flow rules demonstrates the superiority of the fractional constitutive model.展开更多
BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To...BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.展开更多
Concrete material model plays an important role in numerical predictions of its dynamic responses subjected to projectile impact and charge explosion.Current concrete material models could be distinguished into two ki...Concrete material model plays an important role in numerical predictions of its dynamic responses subjected to projectile impact and charge explosion.Current concrete material models could be distinguished into two kinds,i.e.,the hydro-elastoplastic-damage model with independent equation of state and the cap-elastoplastic-damage model with continuous cap surface.The essential differences between the two kind models are vital for researchers to choose an appropriate kind of concrete material model for their concerned problems,while existing studies have contradictory conclusions.To resolve this issue,the constitutive theories of the two kinds of models are firstly overviewed.Then,the constitutive theories between the two kinds of models are comprehensively compared and the main similarities and differences are clarified,which are demonstrated by single element numerical examples.Finally,numerical predictions for projectile penetration and charge explosion experiments on concrete targets are compared to further demonstrate the conclusion made by constitutive comparison.It is found that both the two kind models could be used to simulate the dynamic responses of concrete under projectile impact and blast loadings,if the parameter needed in material models are well calibrated,although some discrepancies between them may exist.展开更多
Topic modeling is a fundamental technique of content analysis in natural language processing,widely applied in domains such as social sciences and finance.In the era of digital communication,social scientists increasi...Topic modeling is a fundamental technique of content analysis in natural language processing,widely applied in domains such as social sciences and finance.In the era of digital communication,social scientists increasingly rely on large-scale social media data to explore public discourse,collective behavior,and emerging social concerns.However,traditional models like Latent Dirichlet Allocation(LDA)and neural topic models like BERTopic struggle to capture deep semantic structures in short-text datasets,especially in complex non-English languages like Chinese.This paper presents Generative Language Model Topic(GLMTopic)a novel hybrid topic modeling framework leveraging the capabilities of large language models,designed to support social science research by uncovering coherent and interpretable themes from Chinese social media platforms.GLMTopic integrates Adaptive Community-enhanced Graph Embedding for advanced semantic representation,Uniform Manifold Approximation and Projection-based(UMAP-based)dimensionality reduction,Hierarchical Density-Based Spatial Clustering of Applications with Noise(HDBSCAN)clustering,and large language model-powered(LLM-powered)representation tuning to generate more contextually relevant and interpretable topics.By reducing dependence on extensive text preprocessing and human expert intervention in post-analysis topic label annotation,GLMTopic facilitates a fully automated and user-friendly topic extraction process.Experimental evaluations on a social media dataset sourced from Weibo demonstrate that GLMTopic outperforms Latent Dirichlet Allocation(LDA)and BERTopic in coherence score and usability with automated interpretation,providing a more scalable and semantically accurate solution for Chinese topic modeling.Future research will explore optimizing computational efficiency,integrating knowledge graphs and sentiment analysis for more complicated workflows,and extending the framework for real-time and multilingual topic modeling.展开更多
Background:In view of the ever-increasing representation of Staphylococcus spp.strains resistant to various antibiotics,the development of in vivo models for evaluation of novel antimicrobials is of utmost importance....Background:In view of the ever-increasing representation of Staphylococcus spp.strains resistant to various antibiotics,the development of in vivo models for evaluation of novel antimicrobials is of utmost importance.Methods:In this article,we describe the development of a fully immunocompetent porcine model of extensive skin and soft tissue damage suitable for testing topical anti-microbial agents that matches the real clinical situation.The model was developed in three consecutive stages with protocols for each stage amended based on the results of the previous one.Results:In the final model,10 excisions of the skin and underlying soft tissue were created in each pig under general anesthesia,with additional incisions to the fascia performed at the base of the defects and immediately inoculated with Staphylococcus aureus suspension.One pig was not inoculated and used as the negative control.Subsequently,the bandages were changed on Days 4,8,11,and 15.At these time points,a filter paper imprint technique(FPIT)was made from each wound for semi-quantitative microbiological evaluation.Tissue samples from the base of the wound together with the adjacent intact tissue of three randomly selected defects of each pig were taken for microbiological,histopathological,and molecular-biological examination.The infection with the inoculated S.aureus strains was sufficient during the whole experiment as confirmed by both FPIT and from tissue samples.The dynamics of the inflammatory markers and clinical signs of infection are also described.Conclusions:A successfully developed porcine model is suitable for in vivo testing of novel short-acting topical antimicrobial agents.展开更多
Background:It is well recognized that developing new animal models,refining the existing mouse models,and thoroughly characterizing their features are essential for gaining a deeper understanding of rosacea pathogenes...Background:It is well recognized that developing new animal models,refining the existing mouse models,and thoroughly characterizing their features are essential for gaining a deeper understanding of rosacea pathogenesis and for advancing therapeutic strategies in this direction.Accordingly,we aimed to characterize the pathological features of a long-term LL-37-induced mouse model of rosacea and to compare the disease manifestations and pathophysiological characteristics between short-term and long-term LL-37-induced models.A key focus was to investigate differential gene expression and the underlying mechanisms of immune system dysregulation in these models.Methods:We comparatively assessed skin lesion manifestations,the extent of inflammatory infiltration,sebaceous gland alterations,fibrosis,and angiogenesis in both models.Assessments were performed using photographic documentation,hematoxylin-eosin(HE)staining,Van Gieson's(VG)staining,immunohistochemistry,and Western blotting.Furthermore,we employed RNA sequencing to analyze differential gene expression in mouse skin.The RNA sequencing data were validated using immunofluorescence staining and Western blotting,with a specific focus on gene variations and mechanisms related to immune system dysregulation.Results:Mice subjected to long-term LL-37 induction developed rosacea-like pathological features,including angiogenesis,thickened skin tissue,and sebaceous gland hypertrophy.In the short-term LL-37-induced model,immune dysregulation primarily involved the innate immune response.However,long-term LL-37 induction resulted in significant activation of both innate and adaptive immune responses.Conclusion:The long-term LL-37-induced mouse model offers a valuable animal model for the detailed investigation of the pathological mechanisms driving moderate-to-severe rosacea with prolonged disease duration.Importantly,this model provides a significant experimental foundation for exploring the potential role of immune system dysregulation in rosacea pathogenesis.展开更多
Large models,such as large language models(LLMs),vision-language models(VLMs),and multimodal agents,have become key elements in artificial intelli⁃gence(AI)systems.Their rapid development has greatly improved percepti...Large models,such as large language models(LLMs),vision-language models(VLMs),and multimodal agents,have become key elements in artificial intelli⁃gence(AI)systems.Their rapid development has greatly improved perception,generation,and decision-making in various fields.However,their vast scale and complexity bring about new security challenges.Issues such as backdoor vulnerabilities during training,jailbreaking in multimodal rea⁃soning,and data provenance and copyright auditing have made security a critical focus for both academia and industry.展开更多
Background:Colocasia esculenta(L.)Schott,known as the taro vegetable,possesses various beneficial effects and is traditionally used in folk medicine.This study explores the ameliorative antioxidant and hepatoprotectiv...Background:Colocasia esculenta(L.)Schott,known as the taro vegetable,possesses various beneficial effects and is traditionally used in folk medicine.This study explores the ameliorative antioxidant and hepatoprotective effect of a methanolic extract of the C.esculenta flower(ME-CEF)against oxidative damage and hepatotoxicity in mice.Methods:The antioxidant efficacy of ME-CEF was assessed using 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic)(ABTS)and 2,2-diphenyl-1-picrylhydrazyl(DPPH)scavenging assay.The hepatoprotective effect was investigated by an assessment of liver injury indicators(amino transferase[ALT],aspartate amino transferase[AST],alkaline phosphatase[ALP],bilirubin,creatinine)and normalizing lipid profiles(cho-lesterol[CHO],triglyceride[TG],high-density lipoprotein[HDL],and low-density li-poprotein[LDL])along with histopathological study and antioxidant enzymes(CAT).A phytochemical analysis,both qualitative and quantitative,was conducted,including gas chromatography-tandem mass spectrometry(GC-MS/MS)analysis and an in silico molecular docking study.Results:The Result Showed that ME-CEF Possesses Moderate ABTS and DPPH Scavenging Activity with IC_(50) Values of 117.18 and 160.41μg/mL.As Illustrated by Reducing Liver Enzymes(ALT,AST,ALP,Bilirubin,Creatinine)and Lipid Profile(CHO,TG,LDL)and Raising HDL Levels(p<0.01),ME-CEF Dose Dependently Mitigated CCl_(4)-Induced Acute Liver Injury.Furthermore,ME-CEF Blocked Hepatic Oxidative Stress by Boosting Antioxidant Enzymes(CAT)and Preventing Liver Tissue Damage and Apoptosis.In Silico Investigations Also Showed a Promising Binding Affinity with Tumor Necrosis Factor α(TNF-α),Interleukin 6(IL-6),PRAP-1,and Xanthin Oxidoreductase,which Displayed Antioxidant and Hepatoprotective Candidacy while Notable Safety and Efficacy Profile Was Also Documented through ADME/T Studies.Histopathological Analysis Showed Reduced Hepatocellular Necrosis and Vascular Congestion in Silymarin and Extract Groups.Conclusion:Based on these results,our findings strongly recommend the medicinal use of the plant,highlighting its antioxidant and hepatoprotective potentials.展开更多
Background: Pancreatic cancer is one of the most lethal malignancies, with postoperative recurrence severely affecting patient survival and prognosis. This study aims to develop and validate a clinical prediction mode...Background: Pancreatic cancer is one of the most lethal malignancies, with postoperative recurrence severely affecting patient survival and prognosis. This study aims to develop and validate a clinical prediction model for postoperative recurrence in pancreatic cancer patients, incorporating multiple preoperative, intraoperative, and postoperative factors to assist clinical decision-making. Methods: A retrospective study was conducted on 216 patients who underwent surgical treatment for pancreatic malignancy at the First Affiliated Hospital of Chongqing Medical University between January 2015 and January 2023. An independent external validation cohort of 76 patients from the Second Affiliated Hospital of Chongqing Medical University was used to validate the model. Seven independent risk factors for postoperative recurrence were identified through univariate and multivariate Cox regression analyses. The model’s performance was evaluated using the concordance index (C-index) and ROC curves, and its accuracy and clinical value were assessed using calibration curves and decision curve analysis (DCA). Results: The predictive model demonstrated good discriminatory power, with a C-index of 0.72 in the training cohort and 0.66 in the validation cohort. The ROC curves for predicting recurrence at 3, 6, and 12 months postoperatively showed AUC values ranging from 0.72 to 0.83, indicating strong predictive value. Calibration curves and DCA confirmed the model’s accuracy and clinical utility. Conclusion: This study successfully developed and validated a clinical prediction model that incorporates seven independent risk factors for postoperative recurrence in pancreatic cancer. The model provides a useful tool for predicting recurrence risk, aiding in the identification of high-risk patients, and informing clinical decision-making.展开更多
BACKGROUND In cases of colorectal cancer(CRC)with obstruction,patients experience local tissue edema due to intestinal obstruction.This condition stimulates the accumulation of inflammatory factors,activates cancer ce...BACKGROUND In cases of colorectal cancer(CRC)with obstruction,patients experience local tissue edema due to intestinal obstruction.This condition stimulates the accumulation of inflammatory factors,activates cancer cells,and increases the risk of tumor recurrence.At present,analyses and evaluation tools for factors influencing early postoperative recurrence in patients with CRC and obstruction are limited.AIM To explore the influencing factors and construct a predictive model of the early postoperative recurrence of CRC with obstruction.METHODS Data from 181 patients with CRC and obstruction who underwent surgery in the Department of Gastrointestinal Surgery,Suzhou Ninth Hospital Affiliated to Soochow University,between January 2017 and May 2023 were retrospectively collected.Patients with CRC and obstruction were divided into a recurrence group and a non-recurrence group based on whether recurrence occurred during the 2-year follow-up after surgery.Datasets from the two groups were compared.Subsequently,multiple logistic regression was employed to analyze the influencing factors of the early postoperative recurrence of CRC with obstruction.The nomogram prediction model was drawn using R software,and its performance was evaluated by the goodness of fit test and receiver operating characteristic(ROC)curve analysis.The clinical benefit rate of the model was evaluated by decision curves.RESULTS Among the 181 patients with CRC and obstruction,52(28.73%)experienced tumor recurrence within 2 years after surgery.Significant differences were observed in preoperative carcinoembryonic antigen(CEA),preoperative systemic immuneinflammation index(SII),tumor,node,and metastasis(TNM)stage,differentiation degree,nerve infiltration,and Ki-67 expression between the recurrence and non-recurrence groups(P<0.05).Multivariate logistic regression analysis showed that high preoperative CEA(OR=2.094,P=0.008),high preoperative SII(OR=2.795,P<0.001),TNM stage III(OR=1.644,P=0.027),poor differentiation(OR=1.861,P=0.035),and high Ki-67 expression(OR=2.467,P=0.001)were all influencing factors for early postoperative recurrence of CRC with obstruction.The area under the ROC curve of the nomograph model constructed based on this was 0.890,the goodness of fit deviation test was conducted(χ^(2)=3.903,P=0.866),and the decision curve display model demonstrated practical value in clinical practice.CONCLUSION The early recurrence rate of CRC with obstruction is high.CEA,SII,TNM staging,differentiation degree,and Ki-67 expression are factors related to early postoperative recurrence.A nomogram prediction model incorporating these factors can effectively evaluate the risk of early postoperative recurrence in patients with CRC.展开更多
BACKGROUND Patients with cirrhosis with hepatopulmonary syndrome(HPS)have a poorer prognosis.The disease has a subtle onset,symptoms are easily masked,clinical attention is insufficient,and misdiagnosis rates are high...BACKGROUND Patients with cirrhosis with hepatopulmonary syndrome(HPS)have a poorer prognosis.The disease has a subtle onset,symptoms are easily masked,clinical attention is insufficient,and misdiagnosis rates are high.AIM To compare the clinical characteristics of patients with cirrhosis,cirrhosis combined with intrapulmonary vascular dilatation(IPVD),and HPS,and to establish predictive models for IPVD and HPS.METHODS Patients with cirrhosis were prospectively screened at a liver-specialized university teaching hospital.Clinical information and blood samples were collected,and biomarker levels in blood samples were measured.Patients with cirrhosis were divided into three groups:Those with pure cirrhosis,those with combined IPVD,and those with HPS based on contrast-enhanced transthoracic echocardiography results and the pulmonary alveolar-arterial oxygen gradient values.Univariate logistic regression and Least Absolute Shrinkage and Selection Operator(LASSO)regression methods were utilized to identify risk factors for IPVD and HPS,and nomograms were constructed to predict IPVD and HPS.RESULTS A total of 320 patients were analyzed,with 101 diagnosed with IPVD,of whom 54 were diagnosed with HPS.There were statistically significant differences in clinical parameters among these three groups of patients.Among the tested biomarkers,sphingosine 1 phosphate,angiopoietin-2,and platelet-derived growth factor BB were significantly associated with IPVD and HPS in patients with cirrhosis.Following LASSO logistic regression screening,prediction models for IPVD and HPS were established.The area under the receiver operating characteristic curve for IPVD prediction was 0.792(95%confidence interval[CI]:0.737-0.847),and for HPS prediction was 0.891(95%CI:0.848-0.934).CONCLUSION This study systematically compared the clinical characteristics of patients with cirrhosis,IPVD,and HPS,and constructed predictive models for IPVD and HPS based on clinical parameters and laboratory indicators.These models showed good predictive value for IPVD and HPS in patients with cirrhosis.They can assist clinicians in the early prognosis assessment of patients with cirrhosis,ultimately benefiting the patients.展开更多
Background:There are many forms of anabolic steroids,including stanozolol(Winstrol),which are popular for their muscle-building effects but dangerous to the heart.This pre-sent work is aimed at evaluating the pharmaco...Background:There are many forms of anabolic steroids,including stanozolol(Winstrol),which are popular for their muscle-building effects but dangerous to the heart.This pre-sent work is aimed at evaluating the pharmacologica impact of allicin,a natural attribute obtained from garlic,on obstructing cardiac injury in rabbits that received stanozolol.Methods:Thirty rabbits were divided into three groups:control,stanozolol-treated,and stanozolol plus allicin.Cardiac function was assessed by measuring troponin,creatine kinase(CK),Galectin-3,and GDF-15.Oxidative stress and antioxidant markers,includ-ing malondialdehyde(MDA),glutathione,and catalase,were analyzed.Inflammatory mediators such as C-reactive protein(CRP),interleukin-6(IL-6),NF-κB,iNOS,nitric oxide(NO),tumor necrosis factor-alpha(TNF-α),and interleukin-1 beta(IL-1β)were evaluated.Lipid profile parameters,including total cholesterol,low-density lipoprotein(LDL),and high-density lipoprotein(HDL),were measured.Histopathological examina-tion assessed myocardial damage,fibrosis,and collagen deposition.Results:Stanozolol administration significantly increased cardiac damage markers,oxidative stress,and inflammatory mediators while causing dyslipidemia,characterized by elevated LDL and total cholesterol and reduced HDL.Allicin co-administration effectively countered these effects by reducing oxidative stress and inflammation,restoring antioxidant balance,and improving lipid profiles.Histopathological analysis revealed severe myocardial disor-ganization,necrosis,and fibrosis in the stanozolol group,whereas the allicin-treated group exhibited preserved myocardial structure with reduced collagen deposition.Conclusion:Allicin significantly mitigates stanozolol-induced cardiotoxicity by reduc-ing oxidative stress,inflammation,lipid dysregulation,and myocardial damage,as evidenced by biochemical and histopathological findings.These results suggest that allicin may serve as a potential therapeutic agent to counteract the cardiovascular risks associated with anabolic steroid use.展开更多
Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel beha...Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel behaviors,e.g.,large-scale/small-scale fading,spatio-temporal-frequency non-stationarity,through mathematical and data-driven methods.This enables simulation-based validation across system development stages—from protocol design to network optimization-without costly physical testing.展开更多
BACKGROUND Colorectal cancer(CRC)is one of the most prevalent and lethal malignant tumors worldwide.Currently,surgical intervention was the primary treatment modality for CRC.However,increasing studies have revealed t...BACKGROUND Colorectal cancer(CRC)is one of the most prevalent and lethal malignant tumors worldwide.Currently,surgical intervention was the primary treatment modality for CRC.However,increasing studies have revealed that CRC patients may experience postoperative cognitive dysfunction(POCD).AIM To establish a risk prediction model for POCD in CRC patients and investigate the preventive value of dexmedetomidine(DEX).METHODS A retrospective analysis was conducted on clinical data from 140 CRC patients who underwent surgery at the People’s Hospital of Qian Nan from February 2020 to May 2024.Patients were allocated into a modeling group(n=98)and a validation group(n=42)in a 7:3 ratio.General clinical data were collected.Additionally,in the modeling group,patients who received DEX preoperatively were incorporated into the observation group(n=54),while those who did not were placed in the control group(n=44).The incidence of POCD was recorded for both cohorts.Data analysis was performed using statistical product and service solutions 20.0,with t-tests orχ^(2) tests employed for group comparisons based on the data type.Least absolute shrinkage and selection operator regression was applied to identify influencing factors and reduce the impact of multicollinear predictors among variables.Multivariate analysis was carried out using Logistic regression.Based on the identified risk factors,a risk prediction model for POCD in CRC patients was developed,and the predictive value of these risk factors was evaluated.RESULTS Significant differences were observed between the cognitive dysfunction group and the non-cognitive dysfunction group in diabetes status,alcohol consumption,years of education,anesthesia duration,intraoperative blood loss,intraoperative hypoxemia,use of DEX during surgery,intraoperative use of vasoactive drugs,surgical time,systemic inflammatory response syndrome(SIRS)score(P<0.05).Multivariate Logistic regression analysis identified that diabetes[odds ratio(OR)=4.679,95%confidence interval(CI)=1.382-15.833],alcohol consumption(OR=5.058,95%CI:1.255-20.380),intraoperative hypoxemia(OR=4.697,95%CI:1.380-15.991),no use of DEX during surgery(OR=3.931,95%CI:1.383-11.175),surgery duration≥90 minutes(OR=4.894,95%CI:1.377-17.394),and a SIRS score≥3(OR=4.133,95%CI:1.323-12.907)were independent risk factors for POCD in CRC patients(P<0.05).A risk prediction model for POCD was constructed using diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score as factors.A receiver operator characteristic curve analysis of these factors revealed the model’s predictive sensitivity(88.56%),specificity(70.64%),and area under the curve(AUC)(AUC=0.852,95%CI:0.773-0.919).The model was validated using 42 CRC patients who met the inclusion criteria,demonstrating sensitivity(80.77%),specificity(81.25%),and accuracy(80.95%),and AUC(0.805)in diagnosing cognitive impairment,with a 95%CI:0.635-0.896.CONCLUSION Logistic regression analysis identified that diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score vigorously influenced the occurrence of POCD.The risk prediction model based on these factors demonstrated good predictive performance for POCD in CRC individuals.This study offers valuable insights for clinical practice and contributes to the prevention and management of POCD under CRC circumstances.展开更多
Objective:To systematically evaluate prediction models for postoperative deep vein thrombosis(DVT)in elderly hip fracture patients and assess their methodological quality and predictive performance.Methods:Following P...Objective:To systematically evaluate prediction models for postoperative deep vein thrombosis(DVT)in elderly hip fracture patients and assess their methodological quality and predictive performance.Methods:Following PRISMA guidelines,we searched eight databases(PubMed,Embase,Cochrane Library,Web of Science,CINAHL,CNKI,Wanfang,VIP)from inception to May 2025.Studies developing or validating DVT prediction models in elderly hip fracture patients were included.Two reviewers independently screened studies,extracted data,and assessed risk of bias and applicability using the PROBAST tool.Results:Eleven studies were included,all conducted in China between 2021 and 2025.Sample sizes ranged from 101 to 504 patients(total n=3,286).Models incorporated 3 to 9 predictors,with D-dimer,age,and time from injury to surgery being most common.All 11 studies(100%)were rated as high risk of bias,primarily due to small sample sizes,lack of validation,and inadequate missing data handling.Applicability concerns were low in 8 studies(72.7%).AUC values ranged from 0.648 to 0.967,with 10 studies(90.9%)reporting AUC>0.7.Meta-analysis identified time from injury to surgery(OR=4.63,95%CI:2.58–6.68),age(OR=1.99),D-dimer(OR=1.51),and Caprini score(OR=1.75)as significant predictors.Conclusion:Current DVT prediction models for elderly hip fracture patients demonstrate acceptable discrimination but are limited by high risk of bias and lack of external validation.Prospective,multicenter studies with rigorous validation are needed to develop clinically applicable models.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42475016,42192555 and 42305085)the China Postdoctoral Science Foundation(Grant No.2023M741615)the 2023 Graduate Research Innovation Project of Hunan Province(Grant No.CX20230011)。
文摘This paper investigates the impact of the model top and damping layer on the numerical simulation of tropical cyclones(TCs)and reveals the significant role of stratospheric gravity waves(SGWs).TCs can generate SGWs,which propagate upward and outward into the stratosphere.These SGWs can reach the damping layer,which is a consequence of the numerical scheme employed,where they can affect the tangential circulation through the dragging and forcing processes.In models with a higher top boundary,this tangential circulation develops far from the TC and has minimal direct impact on TC intensity.By comparison,in models with a lower top(e.g.,20 km),the damping layer is located just above the top of the TC.The SGW dragging in the damping layer and the consequent tangential force can thus induce ascent outside the eyewall,promote latent heat release,tilt the eyewall,and enlarge the inner-core radius.This process will reduce inner-core vorticity advection within the boundary layer,and eventually inhibits the intensification of the TC.This suggests that when the thickness of the damping layer is 5 km,the TC numerical model top height should be at least higher than 20 km to generate more accurate simulations.
基金National Key Research and Development Project(2018YFC1505706)Fund of Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)(ZJW-2019-08)+3 种基金Program for Scientific Research Start-up Funds of GDOU(R17061)Project of Enhancing School with Innovation of GDOU(230419053)Projects(Platforms)for Construction of Top-ranking Disciplines of GDOU(231419022)Special Funds of Central Finance to Support the Development of Local Colleges and Universities(000041)
文摘The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top,refining the vertical resolution,and the assimilation of operationally available observations,including conventional and satellite observations,on continental U.S.winter short-range weather forecasting,were investigated in this study.The initial and predicted wind and temperature profiles were analyzed against conventional observations.Generally,the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used.Negative impacts were also observed in both the initial wind and temperature profiles,over the lower troposphere.Different from the results by only raising the model top,the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used.Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill.The major improvements caused by raising the model top with refined vertical resolution,as well as those caused by data assimilation,were in both cases located in the tropopause and lower stratosphere.Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature.These negative impacts were related to the uncertainties caused by more stratospheric information,as well as to some physical processes.A case study shows that when we raise the model top,put more vertical layers in stratosphere and apply data assimilation,the precipitation scores can be slightly improved.However,more analysis is needed due to uncertainties brought by data assimilation.
文摘Objective:To analyze the impact of nursing interventions based on quantitative assessment using the Kano model on the quality of rehabilitation in patients with early-stage ovarian cancer following laparoscopic radical surgery.Methods:A prospective clinical study was conducted involving 96 patients with newly diagnosed early-stage ovarian cancer who underwent laparoscopic radical surgery from December 2023 to December 2025.Patients were randomly assigned to groups using a random number table method before surgery.After surgery,the control group(n=48)received routine quantitative assessment nursing interventions,while the observation group(n=48)received nursing interventions based on quantitative assessment using the Kano model.Both groups received continuous nursing care until discharge.Differences between the groups were compared in terms of negative emotions,quality of life scores before and after postoperative intervention,postoperative recovery indicators,and nursing satisfaction evaluations on the day of discharge.Results:After intervention,the observation group had lower scores on the Self-Rating Anxiety Scale(SAS)and Self-Rating Depression Scale(SDS),as well as shorter recovery times for gastrointestinal function and food intake,and a shorter hospital stay compared to the control group.Additionally,the observation group had higher scores on the Quality-of-Life Instrument for Cancer Patients-Ovarian Cancer(QLICP-OV)than the control group,with statistically significant differences(p<0.05).The overall satisfaction with nursing care in the observation group was also higher than that in the control group,with a statistically significant difference(p<0.05).Conclusion:Implementing quantitative evaluation nursing interventions based on the Kano model for patients with early-stage ovarian cancer after laparoscopic radical surgery can,by addressing their postoperative basic health,disease awareness,and other intervention content needs to a comprehensive degree,actively promote postoperative recovery and improve their mental health and quality of life.
基金supported by the grants to Min Qiu and Ming Wang from the National Natural Science Foundation of China(32100160 and 32100044)the grants to Ming Wang from the Jiangsu“Innovative and Entrepreneurial Talent”Program,China(JSSCRC2021510)the grants to Yuanchao Wang from the Chinese Modern Agricultural Industry Technology System(CARS-004-PS14)。
文摘The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.
基金supported by the Science and Technology Research Project of Henan Province(242102241055)the Industry-University-Research Collaborative Innovation Base on Automobile Lightweight of“Science and Technology Innovation in Central Plains”(2024KCZY315)the Opening Fund of State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ2024A03-ZZU).
文摘The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.
基金sponsored by the National Natural Science Foundation of China(Grant No.42141010).
文摘A novel fractional elastoplastic constitutive model is proposed to accurately characterize the deformation of sandstone under true-triaxial stress states.This model is founded on the yield function and the fractional flow rule.The yield function includes parameters that govern the evolution of yield surface,enabling an accurate description of three-dimensional stress states.The direction of plastic flow is governed by the two different fractional orders,which are functions of the plastic internal variable.Additionally,a detailed process is proposed for identifying the yield function parameters and fractional orders.Subsequently,the relationship between the fractional order and the direction of plastic flow in the meridian and deviatoric planes is examined,characterized by the dilation angle and the plastic deflection angle,respectively.The non-orthogonal flow rule,also referred to as the fractional flow rule,allows for a border range of plastic deflection and dilation angles compared to the orthogonal flow rule,thereby significantly enhancing its applicability.The validity and accuracy of proposed model are verified by comparing the analytical solution of the constitutive model with the experimental data.A comparison between the non-orthogonal flow rule and orthogonal flow rule is conducted in both the deviatoric and meridian planes.The further comparison of the stress-strain curves for the non-orthogonal and orthogonal flow rules demonstrates the superiority of the fractional constitutive model.
文摘BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.
基金supported by the National Natural Science Foundations of China (Grant Nos. 52178515, 52078133)
文摘Concrete material model plays an important role in numerical predictions of its dynamic responses subjected to projectile impact and charge explosion.Current concrete material models could be distinguished into two kinds,i.e.,the hydro-elastoplastic-damage model with independent equation of state and the cap-elastoplastic-damage model with continuous cap surface.The essential differences between the two kind models are vital for researchers to choose an appropriate kind of concrete material model for their concerned problems,while existing studies have contradictory conclusions.To resolve this issue,the constitutive theories of the two kinds of models are firstly overviewed.Then,the constitutive theories between the two kinds of models are comprehensively compared and the main similarities and differences are clarified,which are demonstrated by single element numerical examples.Finally,numerical predictions for projectile penetration and charge explosion experiments on concrete targets are compared to further demonstrate the conclusion made by constitutive comparison.It is found that both the two kind models could be used to simulate the dynamic responses of concrete under projectile impact and blast loadings,if the parameter needed in material models are well calibrated,although some discrepancies between them may exist.
基金funded by the Natural Science Foundation of Fujian Province,China,grant No.2022J05291.
文摘Topic modeling is a fundamental technique of content analysis in natural language processing,widely applied in domains such as social sciences and finance.In the era of digital communication,social scientists increasingly rely on large-scale social media data to explore public discourse,collective behavior,and emerging social concerns.However,traditional models like Latent Dirichlet Allocation(LDA)and neural topic models like BERTopic struggle to capture deep semantic structures in short-text datasets,especially in complex non-English languages like Chinese.This paper presents Generative Language Model Topic(GLMTopic)a novel hybrid topic modeling framework leveraging the capabilities of large language models,designed to support social science research by uncovering coherent and interpretable themes from Chinese social media platforms.GLMTopic integrates Adaptive Community-enhanced Graph Embedding for advanced semantic representation,Uniform Manifold Approximation and Projection-based(UMAP-based)dimensionality reduction,Hierarchical Density-Based Spatial Clustering of Applications with Noise(HDBSCAN)clustering,and large language model-powered(LLM-powered)representation tuning to generate more contextually relevant and interpretable topics.By reducing dependence on extensive text preprocessing and human expert intervention in post-analysis topic label annotation,GLMTopic facilitates a fully automated and user-friendly topic extraction process.Experimental evaluations on a social media dataset sourced from Weibo demonstrate that GLMTopic outperforms Latent Dirichlet Allocation(LDA)and BERTopic in coherence score and usability with automated interpretation,providing a more scalable and semantically accurate solution for Chinese topic modeling.Future research will explore optimizing computational efficiency,integrating knowledge graphs and sentiment analysis for more complicated workflows,and extending the framework for real-time and multilingual topic modeling.
基金Supported by the Ministry of Health of the Czech Republic,Grant/Award Number:NU22-05-00475 and NV19-05-00214。
文摘Background:In view of the ever-increasing representation of Staphylococcus spp.strains resistant to various antibiotics,the development of in vivo models for evaluation of novel antimicrobials is of utmost importance.Methods:In this article,we describe the development of a fully immunocompetent porcine model of extensive skin and soft tissue damage suitable for testing topical anti-microbial agents that matches the real clinical situation.The model was developed in three consecutive stages with protocols for each stage amended based on the results of the previous one.Results:In the final model,10 excisions of the skin and underlying soft tissue were created in each pig under general anesthesia,with additional incisions to the fascia performed at the base of the defects and immediately inoculated with Staphylococcus aureus suspension.One pig was not inoculated and used as the negative control.Subsequently,the bandages were changed on Days 4,8,11,and 15.At these time points,a filter paper imprint technique(FPIT)was made from each wound for semi-quantitative microbiological evaluation.Tissue samples from the base of the wound together with the adjacent intact tissue of three randomly selected defects of each pig were taken for microbiological,histopathological,and molecular-biological examination.The infection with the inoculated S.aureus strains was sufficient during the whole experiment as confirmed by both FPIT and from tissue samples.The dynamics of the inflammatory markers and clinical signs of infection are also described.Conclusions:A successfully developed porcine model is suitable for in vivo testing of novel short-acting topical antimicrobial agents.
基金The National Natural Science Foundation of China,Grant/Award Number:82204006Science and Technology Project of Hebei Education Department,Grant/Award Number:QN2022009+1 种基金Medical Science Research Project of Hebei,Grant/Award Number:20221534National Natural Science Foundation of Hebei Province,Grant/Award Number:H2024209038。
文摘Background:It is well recognized that developing new animal models,refining the existing mouse models,and thoroughly characterizing their features are essential for gaining a deeper understanding of rosacea pathogenesis and for advancing therapeutic strategies in this direction.Accordingly,we aimed to characterize the pathological features of a long-term LL-37-induced mouse model of rosacea and to compare the disease manifestations and pathophysiological characteristics between short-term and long-term LL-37-induced models.A key focus was to investigate differential gene expression and the underlying mechanisms of immune system dysregulation in these models.Methods:We comparatively assessed skin lesion manifestations,the extent of inflammatory infiltration,sebaceous gland alterations,fibrosis,and angiogenesis in both models.Assessments were performed using photographic documentation,hematoxylin-eosin(HE)staining,Van Gieson's(VG)staining,immunohistochemistry,and Western blotting.Furthermore,we employed RNA sequencing to analyze differential gene expression in mouse skin.The RNA sequencing data were validated using immunofluorescence staining and Western blotting,with a specific focus on gene variations and mechanisms related to immune system dysregulation.Results:Mice subjected to long-term LL-37 induction developed rosacea-like pathological features,including angiogenesis,thickened skin tissue,and sebaceous gland hypertrophy.In the short-term LL-37-induced model,immune dysregulation primarily involved the innate immune response.However,long-term LL-37 induction resulted in significant activation of both innate and adaptive immune responses.Conclusion:The long-term LL-37-induced mouse model offers a valuable animal model for the detailed investigation of the pathological mechanisms driving moderate-to-severe rosacea with prolonged disease duration.Importantly,this model provides a significant experimental foundation for exploring the potential role of immune system dysregulation in rosacea pathogenesis.
文摘Large models,such as large language models(LLMs),vision-language models(VLMs),and multimodal agents,have become key elements in artificial intelli⁃gence(AI)systems.Their rapid development has greatly improved perception,generation,and decision-making in various fields.However,their vast scale and complexity bring about new security challenges.Issues such as backdoor vulnerabilities during training,jailbreaking in multimodal rea⁃soning,and data provenance and copyright auditing have made security a critical focus for both academia and industry.
基金partially funded by the Bangladesh Council of Scientific and Industrial Research (BCSIR) as an R&D project work of the 2022–2023 fiscal year,reference no.:39.02.0000.011.14.157.2022/172 (Date:10.11.2022).
文摘Background:Colocasia esculenta(L.)Schott,known as the taro vegetable,possesses various beneficial effects and is traditionally used in folk medicine.This study explores the ameliorative antioxidant and hepatoprotective effect of a methanolic extract of the C.esculenta flower(ME-CEF)against oxidative damage and hepatotoxicity in mice.Methods:The antioxidant efficacy of ME-CEF was assessed using 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic)(ABTS)and 2,2-diphenyl-1-picrylhydrazyl(DPPH)scavenging assay.The hepatoprotective effect was investigated by an assessment of liver injury indicators(amino transferase[ALT],aspartate amino transferase[AST],alkaline phosphatase[ALP],bilirubin,creatinine)and normalizing lipid profiles(cho-lesterol[CHO],triglyceride[TG],high-density lipoprotein[HDL],and low-density li-poprotein[LDL])along with histopathological study and antioxidant enzymes(CAT).A phytochemical analysis,both qualitative and quantitative,was conducted,including gas chromatography-tandem mass spectrometry(GC-MS/MS)analysis and an in silico molecular docking study.Results:The Result Showed that ME-CEF Possesses Moderate ABTS and DPPH Scavenging Activity with IC_(50) Values of 117.18 and 160.41μg/mL.As Illustrated by Reducing Liver Enzymes(ALT,AST,ALP,Bilirubin,Creatinine)and Lipid Profile(CHO,TG,LDL)and Raising HDL Levels(p<0.01),ME-CEF Dose Dependently Mitigated CCl_(4)-Induced Acute Liver Injury.Furthermore,ME-CEF Blocked Hepatic Oxidative Stress by Boosting Antioxidant Enzymes(CAT)and Preventing Liver Tissue Damage and Apoptosis.In Silico Investigations Also Showed a Promising Binding Affinity with Tumor Necrosis Factor α(TNF-α),Interleukin 6(IL-6),PRAP-1,and Xanthin Oxidoreductase,which Displayed Antioxidant and Hepatoprotective Candidacy while Notable Safety and Efficacy Profile Was Also Documented through ADME/T Studies.Histopathological Analysis Showed Reduced Hepatocellular Necrosis and Vascular Congestion in Silymarin and Extract Groups.Conclusion:Based on these results,our findings strongly recommend the medicinal use of the plant,highlighting its antioxidant and hepatoprotective potentials.
文摘Background: Pancreatic cancer is one of the most lethal malignancies, with postoperative recurrence severely affecting patient survival and prognosis. This study aims to develop and validate a clinical prediction model for postoperative recurrence in pancreatic cancer patients, incorporating multiple preoperative, intraoperative, and postoperative factors to assist clinical decision-making. Methods: A retrospective study was conducted on 216 patients who underwent surgical treatment for pancreatic malignancy at the First Affiliated Hospital of Chongqing Medical University between January 2015 and January 2023. An independent external validation cohort of 76 patients from the Second Affiliated Hospital of Chongqing Medical University was used to validate the model. Seven independent risk factors for postoperative recurrence were identified through univariate and multivariate Cox regression analyses. The model’s performance was evaluated using the concordance index (C-index) and ROC curves, and its accuracy and clinical value were assessed using calibration curves and decision curve analysis (DCA). Results: The predictive model demonstrated good discriminatory power, with a C-index of 0.72 in the training cohort and 0.66 in the validation cohort. The ROC curves for predicting recurrence at 3, 6, and 12 months postoperatively showed AUC values ranging from 0.72 to 0.83, indicating strong predictive value. Calibration curves and DCA confirmed the model’s accuracy and clinical utility. Conclusion: This study successfully developed and validated a clinical prediction model that incorporates seven independent risk factors for postoperative recurrence in pancreatic cancer. The model provides a useful tool for predicting recurrence risk, aiding in the identification of high-risk patients, and informing clinical decision-making.
文摘BACKGROUND In cases of colorectal cancer(CRC)with obstruction,patients experience local tissue edema due to intestinal obstruction.This condition stimulates the accumulation of inflammatory factors,activates cancer cells,and increases the risk of tumor recurrence.At present,analyses and evaluation tools for factors influencing early postoperative recurrence in patients with CRC and obstruction are limited.AIM To explore the influencing factors and construct a predictive model of the early postoperative recurrence of CRC with obstruction.METHODS Data from 181 patients with CRC and obstruction who underwent surgery in the Department of Gastrointestinal Surgery,Suzhou Ninth Hospital Affiliated to Soochow University,between January 2017 and May 2023 were retrospectively collected.Patients with CRC and obstruction were divided into a recurrence group and a non-recurrence group based on whether recurrence occurred during the 2-year follow-up after surgery.Datasets from the two groups were compared.Subsequently,multiple logistic regression was employed to analyze the influencing factors of the early postoperative recurrence of CRC with obstruction.The nomogram prediction model was drawn using R software,and its performance was evaluated by the goodness of fit test and receiver operating characteristic(ROC)curve analysis.The clinical benefit rate of the model was evaluated by decision curves.RESULTS Among the 181 patients with CRC and obstruction,52(28.73%)experienced tumor recurrence within 2 years after surgery.Significant differences were observed in preoperative carcinoembryonic antigen(CEA),preoperative systemic immuneinflammation index(SII),tumor,node,and metastasis(TNM)stage,differentiation degree,nerve infiltration,and Ki-67 expression between the recurrence and non-recurrence groups(P<0.05).Multivariate logistic regression analysis showed that high preoperative CEA(OR=2.094,P=0.008),high preoperative SII(OR=2.795,P<0.001),TNM stage III(OR=1.644,P=0.027),poor differentiation(OR=1.861,P=0.035),and high Ki-67 expression(OR=2.467,P=0.001)were all influencing factors for early postoperative recurrence of CRC with obstruction.The area under the ROC curve of the nomograph model constructed based on this was 0.890,the goodness of fit deviation test was conducted(χ^(2)=3.903,P=0.866),and the decision curve display model demonstrated practical value in clinical practice.CONCLUSION The early recurrence rate of CRC with obstruction is high.CEA,SII,TNM staging,differentiation degree,and Ki-67 expression are factors related to early postoperative recurrence.A nomogram prediction model incorporating these factors can effectively evaluate the risk of early postoperative recurrence in patients with CRC.
基金Supported by the National Key Research and Development Program of China,No.2022YFC2305002Beijing Natural Science Foundation,No.7232079+1 种基金Middle-aged and Young Talent Incubation Programs(Clinical Research)of Beijing Youan Hospital,No.BJYAYY-YN2022-12,No.BJYAYY-YN2022-13,and No.BJYAYY-YN2022-01the China Postdoctoral Science Foundation,No.2023M732410 and No.2024T170595.
文摘BACKGROUND Patients with cirrhosis with hepatopulmonary syndrome(HPS)have a poorer prognosis.The disease has a subtle onset,symptoms are easily masked,clinical attention is insufficient,and misdiagnosis rates are high.AIM To compare the clinical characteristics of patients with cirrhosis,cirrhosis combined with intrapulmonary vascular dilatation(IPVD),and HPS,and to establish predictive models for IPVD and HPS.METHODS Patients with cirrhosis were prospectively screened at a liver-specialized university teaching hospital.Clinical information and blood samples were collected,and biomarker levels in blood samples were measured.Patients with cirrhosis were divided into three groups:Those with pure cirrhosis,those with combined IPVD,and those with HPS based on contrast-enhanced transthoracic echocardiography results and the pulmonary alveolar-arterial oxygen gradient values.Univariate logistic regression and Least Absolute Shrinkage and Selection Operator(LASSO)regression methods were utilized to identify risk factors for IPVD and HPS,and nomograms were constructed to predict IPVD and HPS.RESULTS A total of 320 patients were analyzed,with 101 diagnosed with IPVD,of whom 54 were diagnosed with HPS.There were statistically significant differences in clinical parameters among these three groups of patients.Among the tested biomarkers,sphingosine 1 phosphate,angiopoietin-2,and platelet-derived growth factor BB were significantly associated with IPVD and HPS in patients with cirrhosis.Following LASSO logistic regression screening,prediction models for IPVD and HPS were established.The area under the receiver operating characteristic curve for IPVD prediction was 0.792(95%confidence interval[CI]:0.737-0.847),and for HPS prediction was 0.891(95%CI:0.848-0.934).CONCLUSION This study systematically compared the clinical characteristics of patients with cirrhosis,IPVD,and HPS,and constructed predictive models for IPVD and HPS based on clinical parameters and laboratory indicators.These models showed good predictive value for IPVD and HPS in patients with cirrhosis.They can assist clinicians in the early prognosis assessment of patients with cirrhosis,ultimately benefiting the patients.
基金the College of Pharmacy, Mustansiriyah University, for providing the necessary facilities and support to carry out this research.
文摘Background:There are many forms of anabolic steroids,including stanozolol(Winstrol),which are popular for their muscle-building effects but dangerous to the heart.This pre-sent work is aimed at evaluating the pharmacologica impact of allicin,a natural attribute obtained from garlic,on obstructing cardiac injury in rabbits that received stanozolol.Methods:Thirty rabbits were divided into three groups:control,stanozolol-treated,and stanozolol plus allicin.Cardiac function was assessed by measuring troponin,creatine kinase(CK),Galectin-3,and GDF-15.Oxidative stress and antioxidant markers,includ-ing malondialdehyde(MDA),glutathione,and catalase,were analyzed.Inflammatory mediators such as C-reactive protein(CRP),interleukin-6(IL-6),NF-κB,iNOS,nitric oxide(NO),tumor necrosis factor-alpha(TNF-α),and interleukin-1 beta(IL-1β)were evaluated.Lipid profile parameters,including total cholesterol,low-density lipoprotein(LDL),and high-density lipoprotein(HDL),were measured.Histopathological examina-tion assessed myocardial damage,fibrosis,and collagen deposition.Results:Stanozolol administration significantly increased cardiac damage markers,oxidative stress,and inflammatory mediators while causing dyslipidemia,characterized by elevated LDL and total cholesterol and reduced HDL.Allicin co-administration effectively countered these effects by reducing oxidative stress and inflammation,restoring antioxidant balance,and improving lipid profiles.Histopathological analysis revealed severe myocardial disor-ganization,necrosis,and fibrosis in the stanozolol group,whereas the allicin-treated group exhibited preserved myocardial structure with reduced collagen deposition.Conclusion:Allicin significantly mitigates stanozolol-induced cardiotoxicity by reduc-ing oxidative stress,inflammation,lipid dysregulation,and myocardial damage,as evidenced by biochemical and histopathological findings.These results suggest that allicin may serve as a potential therapeutic agent to counteract the cardiovascular risks associated with anabolic steroid use.
文摘Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel behaviors,e.g.,large-scale/small-scale fading,spatio-temporal-frequency non-stationarity,through mathematical and data-driven methods.This enables simulation-based validation across system development stages—from protocol design to network optimization-without costly physical testing.
基金Supported by the Research Fund of Qiannan Medical College for Nationalities,No.Qnyz202222.
文摘BACKGROUND Colorectal cancer(CRC)is one of the most prevalent and lethal malignant tumors worldwide.Currently,surgical intervention was the primary treatment modality for CRC.However,increasing studies have revealed that CRC patients may experience postoperative cognitive dysfunction(POCD).AIM To establish a risk prediction model for POCD in CRC patients and investigate the preventive value of dexmedetomidine(DEX).METHODS A retrospective analysis was conducted on clinical data from 140 CRC patients who underwent surgery at the People’s Hospital of Qian Nan from February 2020 to May 2024.Patients were allocated into a modeling group(n=98)and a validation group(n=42)in a 7:3 ratio.General clinical data were collected.Additionally,in the modeling group,patients who received DEX preoperatively were incorporated into the observation group(n=54),while those who did not were placed in the control group(n=44).The incidence of POCD was recorded for both cohorts.Data analysis was performed using statistical product and service solutions 20.0,with t-tests orχ^(2) tests employed for group comparisons based on the data type.Least absolute shrinkage and selection operator regression was applied to identify influencing factors and reduce the impact of multicollinear predictors among variables.Multivariate analysis was carried out using Logistic regression.Based on the identified risk factors,a risk prediction model for POCD in CRC patients was developed,and the predictive value of these risk factors was evaluated.RESULTS Significant differences were observed between the cognitive dysfunction group and the non-cognitive dysfunction group in diabetes status,alcohol consumption,years of education,anesthesia duration,intraoperative blood loss,intraoperative hypoxemia,use of DEX during surgery,intraoperative use of vasoactive drugs,surgical time,systemic inflammatory response syndrome(SIRS)score(P<0.05).Multivariate Logistic regression analysis identified that diabetes[odds ratio(OR)=4.679,95%confidence interval(CI)=1.382-15.833],alcohol consumption(OR=5.058,95%CI:1.255-20.380),intraoperative hypoxemia(OR=4.697,95%CI:1.380-15.991),no use of DEX during surgery(OR=3.931,95%CI:1.383-11.175),surgery duration≥90 minutes(OR=4.894,95%CI:1.377-17.394),and a SIRS score≥3(OR=4.133,95%CI:1.323-12.907)were independent risk factors for POCD in CRC patients(P<0.05).A risk prediction model for POCD was constructed using diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score as factors.A receiver operator characteristic curve analysis of these factors revealed the model’s predictive sensitivity(88.56%),specificity(70.64%),and area under the curve(AUC)(AUC=0.852,95%CI:0.773-0.919).The model was validated using 42 CRC patients who met the inclusion criteria,demonstrating sensitivity(80.77%),specificity(81.25%),and accuracy(80.95%),and AUC(0.805)in diagnosing cognitive impairment,with a 95%CI:0.635-0.896.CONCLUSION Logistic regression analysis identified that diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score vigorously influenced the occurrence of POCD.The risk prediction model based on these factors demonstrated good predictive performance for POCD in CRC individuals.This study offers valuable insights for clinical practice and contributes to the prevention and management of POCD under CRC circumstances.
文摘Objective:To systematically evaluate prediction models for postoperative deep vein thrombosis(DVT)in elderly hip fracture patients and assess their methodological quality and predictive performance.Methods:Following PRISMA guidelines,we searched eight databases(PubMed,Embase,Cochrane Library,Web of Science,CINAHL,CNKI,Wanfang,VIP)from inception to May 2025.Studies developing or validating DVT prediction models in elderly hip fracture patients were included.Two reviewers independently screened studies,extracted data,and assessed risk of bias and applicability using the PROBAST tool.Results:Eleven studies were included,all conducted in China between 2021 and 2025.Sample sizes ranged from 101 to 504 patients(total n=3,286).Models incorporated 3 to 9 predictors,with D-dimer,age,and time from injury to surgery being most common.All 11 studies(100%)were rated as high risk of bias,primarily due to small sample sizes,lack of validation,and inadequate missing data handling.Applicability concerns were low in 8 studies(72.7%).AUC values ranged from 0.648 to 0.967,with 10 studies(90.9%)reporting AUC>0.7.Meta-analysis identified time from injury to surgery(OR=4.63,95%CI:2.58–6.68),age(OR=1.99),D-dimer(OR=1.51),and Caprini score(OR=1.75)as significant predictors.Conclusion:Current DVT prediction models for elderly hip fracture patients demonstrate acceptable discrimination but are limited by high risk of bias and lack of external validation.Prospective,multicenter studies with rigorous validation are needed to develop clinically applicable models.
