Objective:Immune checkpoint inhibitor-related pneumonitis(ICIP)is a common and potentially lifethreatening adverse event with non-specific symptoms.It is of significance to identify high-risk population of ICIP.Howeve...Objective:Immune checkpoint inhibitor-related pneumonitis(ICIP)is a common and potentially lifethreatening adverse event with non-specific symptoms.It is of significance to identify high-risk population of ICIP.However,existing prediction models for ICIP are often limited by their reliance on clinically inaccessible variables and homogeneous methodologies,hindering their clinical utility.This study aimed to develop a clinical riskprediction model for ICIP in patients with gastrointestinal(GI)cancer based on four machine learning(ML)methods.Methods:We conducted a retrospective analysis of data from GI cancer patients who received immune checkpoint inhibitors(ICIs)between 2018 and 2022 in Beijing Cancer Hospital.For each patient,36 clinical indicators associated with pneumonia risk were gathered.The dataset was split into training and testing sets in a ratio of 7:3.Variable selection was first performed using Least Absolute Shrinkage and Selection Operator(LASSO)regression.Subsequently,four ML algorithms:logistic regression(LR),random forest(RF),Support vector machine(SVM),and Adaptive Boosting(AdaBoost),were employed to develop and validate ICIP prediction models.The models'performance was assessed using sensitivity,specificity,precision,F1-score,and the area under the receiver operating characteristic curve(AUC)value.The optimal cutoff point for the best model was determined and a web-based tool was developed based on it.Results:We collected medical data from 1,101 GI cancer patients.Ten predictive variables were identified as significant:gender,age,treatment line,smoking index,drinking history,lung metastasis,neutrophil-to-lymphocyte ratio,platelet-to-lymphocyte ratio,hemoglobin,and albumin.After constructing and comparing four ML models,the RF model demonstrated best performance with an AUC of 0.899.The web-based tool for ICIP risk prediction is available at https://healthy.aistarfish.com/business/pneumonia-prediction/#/home.Conclusions:We analyzed 36 clinical predictors of ICIP in 1,101 patients treated with ICIs,and 10 variables were included.The smoking index,albumin and hemoglobin emerged as novel predictors specific to GI cancers.Among the models constructed using four ML methods,the RF model showed the best performance.Additionally,a web-based tool was developed to facilitate the early clinical identification of populations at high risk of ICIP.Future directions include external validation of the model to enhance clinical usability.展开更多
This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in ...This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.展开更多
Many existing immune detection algorithms rely on a large volume of labeled self-training samples,which are often difficult to obtain in practical scenarios,thus limiting the training of detection models.Furthermore,n...Many existing immune detection algorithms rely on a large volume of labeled self-training samples,which are often difficult to obtain in practical scenarios,thus limiting the training of detection models.Furthermore,noise inherent in the samples can substantially degrade the detection accuracy of these algorithms.To overcome these challenges,we propose an immune generation algorithm that leverages clustering and a rebound mechanism for label propagation(LP-CRI).The dataset is randomly partitioned into multiple subsets,each of which undergoes clustering followed by label propagation and evaluation.The rebound mechanism assesses the model’s performance after propagation and determines whether to revert to its previous state,initiating a subsequent round of propagation to ensure stable and effective training.Experimental results demonstrate that the proposed method is both computationally efficient and easy to train,significantly enhancing detector performance and outperforming traditional immune detection algorithms.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises stru...Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.展开更多
Objective Sepsis patients exhibit diverse immune states,making it crucial to identify subtypes with distinct inflammatory profiles through Th1/Th2 cytokine data for personalized treatment and improved prognosis.Method...Objective Sepsis patients exhibit diverse immune states,making it crucial to identify subtypes with distinct inflammatory profiles through Th1/Th2 cytokine data for personalized treatment and improved prognosis.Methods We retrieved data from sepsis patients who underwent Th1/Th2 cytokine testing in Nanfang Hospital,Southern Medical University from June 1,2020,to February 1,2022.An unsupervised K-means clustering method classified participants based on Th1/Th2 cytokine levels,with the primary outcome being the 7-day mortality rate post-ICU admission.Cox proportional hazards and Restricted Mean Survival Time(RMST)analyses were utilized to explore survival outcomes.Results A total of 321 sepsis patients were included.IL-6(HR 1.69,95%CI:1.22,2.34)and IL-10(HR 1.81,95%CI:1.37,2.40)emerged as independent predictors of 7-day mortality.Unsupervised K-means clustering revealed 3 inflammatory/immune subgroups:Cluster 1(n=166,low inflammatory response),Cluster 2(n=99,moderate inflammatory response with immune suppression),and Cluster 3(n=56,strong inflammatory and immune suppression).Compared to Cluster 1,Clusters 2 and 3 had higher 7-day mortality risks(14.4%vs 23.2%,HR=4.30,95%CI:1.51-12.26;14.4%vs 35.7%,HR=7.32,95%CI:2.57-20.79).Conclusion Septic patients in a protective immune response state(Cluster 1)exhibit better short-term prognoses,suggesting the importance of understanding inflammatory/immune states for precise treatment and improved outcomes.展开更多
This paper introduces a novel nature-inspired metaheuristic algorithm called the Gekko japonicus algorithm.The algo-rithm draws inspiration mainly from the predation strategies and survival behaviors of the Gekko japo...This paper introduces a novel nature-inspired metaheuristic algorithm called the Gekko japonicus algorithm.The algo-rithm draws inspiration mainly from the predation strategies and survival behaviors of the Gekko japonicus.The math-ematical model is developed by simulating various biological behaviors of the Gekko japonicus,such as hybrid loco-motion patterns,directional olfactory guidance,implicit group advantage tendencies,and the tail autotomy mechanism.By integrating multi-stage mutual constraints and dynamically adjusting parameters,GJA maintains an optimal balance between global exploration and local exploitation,thereby effectively solving complex optimization problems.To assess the performance of GJA,comparative analyses were performed against fourteen state-of-the-art metaheuristic algorithms using the CEC2017 and CEC2022 benchmark test sets.Additionally,a Friedman test was performed on the experimen-tal results to assess the statistical significance of differences between various algorithms.And GJA was evaluated using multiple qualitative indicators,further confirming its superiority in exploration and exploitation.Finally,GJA was utilized to solve four engineering optimization problems and further implemented in robotic path planning to verify its practical applicability.Experimental results indicate that,compared to other high-performance algorithms,GJA demonstrates excep-tional performance as a powerful optimization algorithm in complex optimization problems.We make the code publicly available at:https://github.com/zhy1109/Gekko-japonicusalgorithm.展开更多
The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,convention...The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,conventional clustering-based methods face notable drawbacks,including poor scalability in handling high-dimensional datasets and a strong dependence of outcomes on initial conditions.To overcome the performance limitations of existing methods,this study proposes a novel quantum-inspired clustering algorithm that relies on a similarity coefficient-based quantum genetic algorithm(SC-QGA)and an improved quantum artificial bee colony algorithm hybrid K-means(IQABC-K).First,the SC-QGA algorithmis constructed based on quantum computing and integrates similarity coefficient theory to strengthen genetic diversity and feature extraction capabilities.For the subsequent clustering phase,the process based on the IQABC-K algorithm is enhanced with the core improvement of adaptive rotation gate and movement exploitation strategies to balance the exploration capabilities of global search and the exploitation capabilities of local search.Simultaneously,the acceleration of convergence toward the global optimum and a reduction in computational complexity are facilitated by means of the global optimum bootstrap strategy and a linear population reduction strategy.Through experimental evaluation with multiple algorithms and diverse performance metrics,the proposed algorithm confirms reliable accuracy on three datasets:KDD CUP99,NSL_KDD,and UNSW_NB15,achieving accuracy of 98.57%,98.81%,and 98.32%,respectively.These results affirm its potential as an effective solution for practical clustering applications.展开更多
In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic h...In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic heterogeneous infrastructures,unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy.Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service(QoS).As the transport network is built of ad hoc nodes,there is no guarantee about their trustworthiness or behavior,and transversal functionalities are delegated to the extreme nodes.However,while security can be guaranteed in extreme-to-extreme solutions,privacy cannot,as all intermediate nodes still have to handle the data packets they are transporting.Besides,traditional schemes for private anonymous ad hoc communications are vulnerable against modern intelligent attacks based on learning models.The proposed scheme fulfills this gap.Findings show the probability of a successful intelligent attack reduces by up to 65%compared to ad hoc networks with no privacy protection strategy when used the proposed technology.While congestion probability can remain below 0.001%,as required in 6G services.展开更多
Post-translational modifications(PTMs)regulate the occurrence and development of cancer,and lactylation modification is a new form of PTMs.Recent studies have found that lactic acid modification can regulate the immun...Post-translational modifications(PTMs)regulate the occurrence and development of cancer,and lactylation modification is a new form of PTMs.Recent studies have found that lactic acid modification can regulate the immune tolerance of cancer cells.The classical theory holds that prostate apoptosis response-4(PAR-4)is a tumor suppressor protein.However,our recent research has found that PAR-4 has a biological function of promoting cancer in hepatocellular carcinoma(HCC),and our analysis shows that PAR-4 can be modified of lactic acid.These research evidences suggest that PAR-4 lactylation modification may drive immune tolerance in HCC.Therefore,inhibiting PAR-4 lactylation modification is very likely to increase the sensitivity of HCC to immunotherapy.展开更多
The red imported fire ant,Solenopsis invicta Buren,is a highly invasive eusocial insect pest that threatens native biodiversity,agriculture,and human health.The innate immune system and intricate social immune respons...The red imported fire ant,Solenopsis invicta Buren,is a highly invasive eusocial insect pest that threatens native biodiversity,agriculture,and human health.The innate immune system and intricate social immune responses of S.invicta pose challenges to the development of effective control strategies.Micro RNAs(mi RNAs)play critical roles in the post-transcriptional regulation of gene expression,which influences various biological processes,including immunity and host-pathogen interactions.While the mi RNA-mediated response of insects to pathogens has been extensively studied in solitary insects,little is known about the innate immune responses of individual members within a colony.To address this gap,we constructed small RNA libraries from Metarhizium anisopliae-infected S.invicta workers and investigated the temporal dynamics of mi RNA-mediated immune responses to the entomopathogen.Several differentially expressed mi RNAs were identified,and they were found to regulate genes involved in the Toll,IMD,and melanization immune pathways.Quantitative real-time PCR(q RT-PCR)was employed to analyze the spatiotemporal dynamics of key mi RNAs/target genes,specifically mi R-71/Mod SP1-Relish and mi R-7/Lysozyme2-Serine protease7.A dual luciferase assay(in vitro)was performed to validate the interactions between mi RNAs and their target genes.Overexpression of mi R-71 and mi R-7(via mi RNA mimics)efficiently suppressed their target genes,impaired the antifungal immune response of S.invicta and increased the susceptibility to M.anisopliae infection compared to controls.Furthermore,RNA interference-based gene silencing elucidated the roles of these immune genes in regulating fungal susceptibility,thus providing vital clues for developing virulent and effective mycoinsecticides using modern genetic engineering tools.展开更多
Pulmonary fibrosis(PF)is a progressive,fatal fibrotic disease caused by respiratory conditions.The condition can ultimately lead to severe organ failure and mortality,and is associated with multiple risk factors.Growi...Pulmonary fibrosis(PF)is a progressive,fatal fibrotic disease caused by respiratory conditions.The condition can ultimately lead to severe organ failure and mortality,and is associated with multiple risk factors.Growing evidence highlights the immune system’s role in PF,with various immune components participating in inflammatory and fibrotic processes.Different immune cells,including neutrophils,lymphocytes,and macrophages,demonstrate distinct effects on PF progression and development.Furthermore,key immune system cytokines,including the interleukin(IL)family,tumor necrosis factor(TNF)-α,interferon(IFN)-γ,transforming growth factor(TGF)-β,and connective tissue growth factor(CTGF),contribute to PF initiation and progression through independent mechanisms and mutual regulation.Currently,limited effective treatments exist for PF,with several treatments causing severe adverse reactions.Natural products,characterized by multi-target effects,holistic regulation,and low toxicity,have emerged as a research focus.This review compiles the mechanisms,therapeutic potential,and active components of various natural products.These compounds can ameliorate pulmonary inflammation,epithelial-mesenchymal transition,and collagen deposition through diverse immune mechanisms,acting at specific stages or throughout the fibrotic process,thereby supporting PF management.This review examines current scientific understanding of natural products’immunological effects in PF,which is crucial for developing future anti-PF therapeutics.展开更多
Objectives:Postmenopausal osteoporosis is the most common form of osteoporosis in clinical practice,affecting millions of postmenopausal women worldwide.Postmenopausal osteoporosis demands safe and effective therapies...Objectives:Postmenopausal osteoporosis is the most common form of osteoporosis in clinical practice,affecting millions of postmenopausal women worldwide.Postmenopausal osteoporosis demands safe and effective therapies.This study aimed to evaluate the potential of hederagenin(Hed)for treating osteoporosis and to elucidate its underlying mechanisms of action.Methods:The anti-osteoporotic potential of Hed was assessed by investigating its effects on ovariectomy(OVX)-induced bone loss in mice and on receptor activator of NF-kappaB ligand(RANKL)-induced osteoclast differentiation in RAW264.7 cells.Network pharmacology analysis and molecular docking were employed to identify key targets,which were subsequently validated experimentally.Results:In vitro,Hed suppressed osteoclastogenesis by inhibiting the formation of osteoclasts and F-actin rings and by down-regulating osteoclastspecific genes(Atp6v0d2 and Acp5).In vivo,Hed significantly amelioratedOVX-induced bone loss,restoring trabecular bone volume fraction(BV/TV)and trabecular number(Tb.N),while reducing trabecular separation(Tb.Sp).Network pharmacology analysis identified 142 overlapping targets linking Hed to osteoporosis,including tumor necrosis factor alpha(TNF-α),interleukin-6(IL-6),and IL-1β,with enrichment in innate immune signaling and osteoclast differentiation.Molecular docking analysis indicated strong binding affinities between Hed and targets such as TNF-α,IL-6,and IL-1β.Experimentally,Hed was found to decrease RANKL,elevate osteoprotegerin(OPG),and suppress intestinalmRNA levels of pro-inflammatory cytokines such as IL-1β,IL-6,IL-17A,and TNF-α.Conclusion:Hed exerts significant anti-osteoporotic effects inOVX-induced osteoporosis through a dualmechanism involving the suppression of both osteoclastogenesis and innate immune signaling pathways.These findings highlighted Hed’s novel role in modulating immune-bone crosstalk,offering a promising strategy for treating osteolytic diseases without estrogenic side effects.展开更多
Hepatocellular carcinoma presents with three distinct immune phenotypes,including immune-desert,immune-excluded,and immune-inflamed,indicating various treatment responses and prognostic outcomes.The clinical applicati...Hepatocellular carcinoma presents with three distinct immune phenotypes,including immune-desert,immune-excluded,and immune-inflamed,indicating various treatment responses and prognostic outcomes.The clinical application of multi-omics parameters is still restricted by the expensive and less accessible assays,although they accurately reflect immune status.A comprehensive evaluation framework based on“easy-to-obtain”multi-model clinical parameters is urgently required,incorporating clinical features to establish baseline patient profiles and disease staging;routine blood tests assessing systemic metabolic and functional status;immune cell subsets quantifying subcluster dynamics;imaging features delineating tumor morphology,spatial configuration,and perilesional anatomical relationships;immunohistochemical markers positioning qualitative and quantitative detection of tumor antigens from the cellular and molecular level.This integrated phenomic approach aims to improve prognostic stratification and clinical decision-making in hepatocellular carcinoma management conveniently and practically.展开更多
The interplay between gut microbiota and host health has attracted significant interest in the animal science community.Maintaining gut microbiota homeostasis by supplementing probiotics to treat clinical conditions l...The interplay between gut microbiota and host health has attracted significant interest in the animal science community.Maintaining gut microbiota homeostasis by supplementing probiotics to treat clinical conditions like calf diarrhea is an emerging area of research nowadays because of increased concerns regarding antimicrobial resistance(AMR)and drug residues in animal products.Probiotics reduce the incidence of calf diarrhea by increasing the gut microbiota diversity and richness with more commensal bacteria such as Lactobacillus and Bifidobacterium that produce antimicrobial compounds,as well as modulating the immune response by increasing cytokines,Interleukin-2(IL-2),IL-4,IL-6,IL-10,and reducing tumor necrosis factor-α(TNF-α),by increasing production of antibodies,especially immunoglobulin E(Ig E),also Ig G,differentiating naive Th lymphocytes(Tho)into Th1,hence stimulate innate immunity and prime the adaptive immune response.Specific probiotic strains of bacteria and yeast(Saccharomyces cerevisiae)derived probiotics maintain the integrity of the intestinal barrier.In this review,data are being organized to address the role of probiotics in treating calf diarrhea by modulating gut microbiota and stimulating an immune response against notorious pathogens,to present animal and veterinary scientists and nutritionists with a new concept to treat infectious diseases from the perspective of the gut microbiota,increasing animal health,performance,and welfare.In conclusion,health status and gut microbiome are strongly interlinked.Research data indicated a significant reduction in the incidence of diarrhea after probiotic administration.If interrelations between probiotics and existing gut microbiota are explored more quantitatively,novel antibiotic substitutes can emerge in the future.展开更多
Polyfluoroalkyl substances(PFAS)have emerged as persistent environmental contaminants because of their chemical stability,degradation-resistance and bioaccumulation potential.However,current studies mainly focus on th...Polyfluoroalkyl substances(PFAS)have emerged as persistent environmental contaminants because of their chemical stability,degradation-resistance and bioaccumulation potential.However,current studies mainly focus on the toxicity of single PFAS such as perfluorooctanoic acid(PFOA)and perfluorobutanoic acid(PFBA),the knowledge of their combined effects is relatively limited.In this study,we explored the immune response of the gut in large yellow croaker(Larimichthys crocea)under the combined stress of PFOA and PFBA.Histologicalanalyses revealed that the combined effect induced intestinal vacuolization and decreased the length of intestinal villi.And it significantly activated pro-inflammatory pathways with marked upregulation of tnfα,il1β,il6 and myd88 expressions,particularly after 14 days of exposure.Gut microbiota analysis revealed substantial dysbiosis,including 1)reduced alpha diversity,2)increased abundance of potential pathogenic taxa(Proteobacteria and Spirochaetota),and 3)depletion of beneficial Firmicutes.PICRUSt-based functional prediction indicated temporal metabolic shifts,with upregulation of DNA repair pathways at day 3 and enhanced bacterial motility protein activity at days 7 and 14 of post-exposure.The Pearson correlation analysis further indicated that these immune genes had significant positive correlations with Vibrio and Brevinema,and negative correlations with Streptococcus.Our present study will provide novel insights into the microbiome-mediated immunomodulation in the larger yellow croaker exposed to combined PFAS,which will be helpful for healthy farming of economically important marine species.展开更多
Objective:To investigate the correlation between the expression of glucose-6-phosphate dehydrogenase(G6PD)and the clinicopathological characteristics,prognosis and immune cell infiltration of hepatocellular carcinoma(...Objective:To investigate the correlation between the expression of glucose-6-phosphate dehydrogenase(G6PD)and the clinicopathological characteristics,prognosis and immune cell infiltration of hepatocellular carcinoma(HCC).Methods:The expression of G6PD in liver cancer tissues and normal tissues is extracted from TCGA and GEO databases,validated by immunohistochemistry,and the correlation between G6PD expression and clinical features is analyzed.The clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier,Cox regression,and prognostic line graph models.Functional enrichment analysis is performed by protein-protein interaction(PPI)network,GO/KEGG,GSEA and for G6PD-associated differentially expressed genes(DEGs).TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results:Analysis of TCGA and GEO datasets revealed that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues(P<0.001).G6PD expression is associated with histological grade,pathological stage,T-stage,vascular infiltration,and AFP level(P<0.05);HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group(P<0.05).The level of G6PD expression affects the levels of macrophages,dendritic cells,B cells,and follicular helper T cells in the tumor microenvironment.Conclusion:High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma,and G6PD may be a target for immunotherapy of HCC.展开更多
AIM:To identify metastasis-associated prognostic genes and construct a robust molecular signature for survival prediction in uveal melanoma(UVM)patients.METHODS:Transcriptomic data and clinical information from 80 UVM...AIM:To identify metastasis-associated prognostic genes and construct a robust molecular signature for survival prediction in uveal melanoma(UVM)patients.METHODS:Transcriptomic data and clinical information from 80 UVM patients in the Cancer Genome Atlas(TCGA)-UVM cohort and an external Gene Expression Omnibus(GEO)microarray dataset(GSE73652;8 non-metastatic vs 5 metastatic cases)were analyzed to identify differentially expressed genes(DEGs).Functional enrichment,proteinprotein interaction(PPI)network construction,and survival analyses identified seven metastasis-and prognosisrelated genes.Their expression was further examined using public single-cell RNA-seq data(GSE139829;11 tumors).Experimental validation was performed in UVM cell lines(92.1,OMM1,MEL270)and adult retinal pigment epithelial(ARPE-19)cells using quantitative real-time polymerase chain reaction(qRT-PCR)and Western blotting to confirm transcriptomic trends.A LASSO Cox model was applied to construct a metastasis-related risk Score signature.Tumor immune microenvironment characteristics were evaluated via single-sample gene set enrichment analysis(ssGSEA)and ESTIMATE.Somatic mutation and copy number variation(CNV)profiles were also examined.RESULTS:Seven key genes(UBE2T,KIF20A,DLGAP5,KLC3,TPX2,UBE2C,AURKA)were significantly associated with overall survival and used to construct a metastasisrelated riskScore signature,which effectively stratified patients into high-and low-risk groups and served as an independent prognostic factor.qRT-PCR and Western blot results confirmed that the expression levels of selected key genes in UVM cell lines showed significant differences compared to ARPE-19 cells,which were largely consistent with the transcriptomic findings.The high-risk group exhibited reduced immune infiltration and stromal activity.Single-cell analysis revealed these genes were predominantly expressed in a tumor cell cluster characterized by BAP1 loss and high metastatic potential.Mutation and CNV analyses further supported the relevance of these genes to UVM progression.CONCLUSION:This study establishes and validates a seven-gene signature associated with metastasis and prognosis in UVM.The findings provide a framework for understanding molecular determinants of tumor progression and immune microenvironment alterations,and may offer guidance for future mechanistic studies and therapeutic exploration.展开更多
Background:Aberrant expression of transcription factors(TFs)is a key mechanism mediating tumor immune escape and therapeutic resistance.The involvement of E26 transformation-specific(ETS)family of TFs in immune regula...Background:Aberrant expression of transcription factors(TFs)is a key mechanism mediating tumor immune escape and therapeutic resistance.The involvement of E26 transformation-specific(ETS)family of TFs in immune regulation is not fully understood.The study aimed to elucidate the function of E-twenty-six variant 4(ETV4)in tumor immune evasion and its potential as a predictive biomarker for immunotherapy in melanoma.Methods:The expression patterns of ETS family TFs were analyzed in melanoma and hepatocellular carcinoma(HCC).Single-cell RNA sequencing(scRNA-seq)was used to dissect the cellular expression and function of ETV4 in the tumor microenvironment.Functional studies and murine models were employed to investigate the role of ETV4 in T cell-mediated tumor killing and tumor growth.The correlation between ETV4 expression level and patient responsiveness to programmed cell death protein 1(PD-1)blockade therapy was evaluated.Results:TFs in the ETS family were found to effectively stratify melanoma and HCC patients into prognostic subgroups.In melanoma,the polyoma enhancer activator 3(PEA3)subfamily,particularly ETV4 and ETV5,showed a negative correlation with immune infiltration.scRNA-seq analysis showed that ETV4 is preferentially expressed in melanoma cells and involves in mediating tumor-immunocyte interactions.Functional studies demonstrated that ETV4 impairs T cell-mediated tumor killing by transcriptionally upregulating programmed death-ligand 1(PD-L1).In immunocompetent murine models,ETV4 downregulation significantly suppressed tumor growth.Furthermore,high ETV4 expression correlated with poor responses to anti-PD-1 therapy.Conclusion:Our findings identify ETV4 as a key transcriptional regulator of immune evasion in melanoma by controlling PD-L1 expression.ETV4 may act as a predictive biomarker for immunotherapy outcomes.展开更多
Background:Exercise exerts tumor-suppressive effects across multiple malignancies,partly through exerkines—exercise-induced secreted factors with immunomodulatory and metabolic functions.However,the prognostic releva...Background:Exercise exerts tumor-suppressive effects across multiple malignancies,partly through exerkines—exercise-induced secreted factors with immunomodulatory and metabolic functions.However,the prognostic relevance of exerkines across cancer types remains unclear,and the molecular determinants of exercise responsiveness are poorly defined.Methods:We systematically profiled 183 curated exerkine-related genes across 33 cancer types from The Cancer Genome Atlas(TCGA)using non-negative matrix factorization(NMF)to define molecular subtypes.Prognostic significance was evaluated via Kaplan-Meier analysis.For five cancers with consistent survival divergence(LGG,KIRC,LUAD,PAAD,ACC),we developed an Exerkine Prognostic Index(EPI)using LASSO Cox regression and validated its predictive performance through time-dependent ROC analysis.Immune cell infiltration(CIBERSORT),stromal/immune scores(ESTIMATE),and immune checkpoint expression were assessed to characterize immune landscape differences between EPI subgroups.Results:Exerkine-based NMF clustering identified prognostically distinct subtypes in 25 cancers.The EPI robustly stratified patients into high-and low-risk groups with significant differences in overall survival(p<0.001).High-EPI subgroups were associated with elevated infiltration of immunosuppressive cells(e.g.,Tregs,M0 macrophages),altered immune/stromal scores,and differential expression of immune checkpoints such as PD-L1 and CTLA4 in a cancer-type-specific manner.Discussion:Our findings reveal that exerkine expression patterns capture biologically and clinically relevant heterogeneity across cancers.The EPI provides a robust molecular tool to stratify patients by prognosis and immune contexture,offering insights into differential exercise responsiveness.Conclusions:Exerkines represent promising biomarkers for risk stratification and precision-guided exercise interventions in oncology.展开更多
基金supported by Beijing Cancer hospital(No.KC2408)。
文摘Objective:Immune checkpoint inhibitor-related pneumonitis(ICIP)is a common and potentially lifethreatening adverse event with non-specific symptoms.It is of significance to identify high-risk population of ICIP.However,existing prediction models for ICIP are often limited by their reliance on clinically inaccessible variables and homogeneous methodologies,hindering their clinical utility.This study aimed to develop a clinical riskprediction model for ICIP in patients with gastrointestinal(GI)cancer based on four machine learning(ML)methods.Methods:We conducted a retrospective analysis of data from GI cancer patients who received immune checkpoint inhibitors(ICIs)between 2018 and 2022 in Beijing Cancer Hospital.For each patient,36 clinical indicators associated with pneumonia risk were gathered.The dataset was split into training and testing sets in a ratio of 7:3.Variable selection was first performed using Least Absolute Shrinkage and Selection Operator(LASSO)regression.Subsequently,four ML algorithms:logistic regression(LR),random forest(RF),Support vector machine(SVM),and Adaptive Boosting(AdaBoost),were employed to develop and validate ICIP prediction models.The models'performance was assessed using sensitivity,specificity,precision,F1-score,and the area under the receiver operating characteristic curve(AUC)value.The optimal cutoff point for the best model was determined and a web-based tool was developed based on it.Results:We collected medical data from 1,101 GI cancer patients.Ten predictive variables were identified as significant:gender,age,treatment line,smoking index,drinking history,lung metastasis,neutrophil-to-lymphocyte ratio,platelet-to-lymphocyte ratio,hemoglobin,and albumin.After constructing and comparing four ML models,the RF model demonstrated best performance with an AUC of 0.899.The web-based tool for ICIP risk prediction is available at https://healthy.aistarfish.com/business/pneumonia-prediction/#/home.Conclusions:We analyzed 36 clinical predictors of ICIP in 1,101 patients treated with ICIs,and 10 variables were included.The smoking index,albumin and hemoglobin emerged as novel predictors specific to GI cancers.Among the models constructed using four ML methods,the RF model showed the best performance.Additionally,a web-based tool was developed to facilitate the early clinical identification of populations at high risk of ICIP.Future directions include external validation of the model to enhance clinical usability.
基金supported by the P.G.Senapathy Center for Computing Resources at IIT Madrasfunding provided by the Ministry of Education,Government of Indiasupported by the National Natural Science Foundation of China(Grant Nos.12388101,12472224 and 92252104).
文摘This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.
基金granted by Key Project of Beijing Municipal Social Science Foundation(No.15ZHA004)Key Project of Beijing Municipal Social Science Foundation and Beijing Municipal Education Commission Social Science Program(No.SZ20231123202).
文摘Many existing immune detection algorithms rely on a large volume of labeled self-training samples,which are often difficult to obtain in practical scenarios,thus limiting the training of detection models.Furthermore,noise inherent in the samples can substantially degrade the detection accuracy of these algorithms.To overcome these challenges,we propose an immune generation algorithm that leverages clustering and a rebound mechanism for label propagation(LP-CRI).The dataset is randomly partitioned into multiple subsets,each of which undergoes clustering followed by label propagation and evaluation.The rebound mechanism assesses the model’s performance after propagation and determines whether to revert to its previous state,initiating a subsequent round of propagation to ensure stable and effective training.Experimental results demonstrate that the proposed method is both computationally efficient and easy to train,significantly enhancing detector performance and outperforming traditional immune detection algorithms.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
文摘Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.
文摘Objective Sepsis patients exhibit diverse immune states,making it crucial to identify subtypes with distinct inflammatory profiles through Th1/Th2 cytokine data for personalized treatment and improved prognosis.Methods We retrieved data from sepsis patients who underwent Th1/Th2 cytokine testing in Nanfang Hospital,Southern Medical University from June 1,2020,to February 1,2022.An unsupervised K-means clustering method classified participants based on Th1/Th2 cytokine levels,with the primary outcome being the 7-day mortality rate post-ICU admission.Cox proportional hazards and Restricted Mean Survival Time(RMST)analyses were utilized to explore survival outcomes.Results A total of 321 sepsis patients were included.IL-6(HR 1.69,95%CI:1.22,2.34)and IL-10(HR 1.81,95%CI:1.37,2.40)emerged as independent predictors of 7-day mortality.Unsupervised K-means clustering revealed 3 inflammatory/immune subgroups:Cluster 1(n=166,low inflammatory response),Cluster 2(n=99,moderate inflammatory response with immune suppression),and Cluster 3(n=56,strong inflammatory and immune suppression).Compared to Cluster 1,Clusters 2 and 3 had higher 7-day mortality risks(14.4%vs 23.2%,HR=4.30,95%CI:1.51-12.26;14.4%vs 35.7%,HR=7.32,95%CI:2.57-20.79).Conclusion Septic patients in a protective immune response state(Cluster 1)exhibit better short-term prognoses,suggesting the importance of understanding inflammatory/immune states for precise treatment and improved outcomes.
基金CHINA POSTDOCTORAL SCIENCE FOUNDATION(Grant No.2025M771925)Young Scientists Fund(C Class)(Grant No.32501636)Special Fund of Fundamental Scientific Research Business Expense for Higher School of Central Government(Grant No.2572025JT04).
文摘This paper introduces a novel nature-inspired metaheuristic algorithm called the Gekko japonicus algorithm.The algo-rithm draws inspiration mainly from the predation strategies and survival behaviors of the Gekko japonicus.The math-ematical model is developed by simulating various biological behaviors of the Gekko japonicus,such as hybrid loco-motion patterns,directional olfactory guidance,implicit group advantage tendencies,and the tail autotomy mechanism.By integrating multi-stage mutual constraints and dynamically adjusting parameters,GJA maintains an optimal balance between global exploration and local exploitation,thereby effectively solving complex optimization problems.To assess the performance of GJA,comparative analyses were performed against fourteen state-of-the-art metaheuristic algorithms using the CEC2017 and CEC2022 benchmark test sets.Additionally,a Friedman test was performed on the experimen-tal results to assess the statistical significance of differences between various algorithms.And GJA was evaluated using multiple qualitative indicators,further confirming its superiority in exploration and exploitation.Finally,GJA was utilized to solve four engineering optimization problems and further implemented in robotic path planning to verify its practical applicability.Experimental results indicate that,compared to other high-performance algorithms,GJA demonstrates excep-tional performance as a powerful optimization algorithm in complex optimization problems.We make the code publicly available at:https://github.com/zhy1109/Gekko-japonicusalgorithm.
基金supported by the NSFC(Grant Nos.62176273,62271070,62441212)The Open Foundation of State Key Laboratory of Networking and Switching Technology(Beijing University of Posts and Telecommunications)under Grant SKLNST-2024-1-062025Major Project of the Natural Science Foundation of Inner Mongolia(2025ZD008).
文摘The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,conventional clustering-based methods face notable drawbacks,including poor scalability in handling high-dimensional datasets and a strong dependence of outcomes on initial conditions.To overcome the performance limitations of existing methods,this study proposes a novel quantum-inspired clustering algorithm that relies on a similarity coefficient-based quantum genetic algorithm(SC-QGA)and an improved quantum artificial bee colony algorithm hybrid K-means(IQABC-K).First,the SC-QGA algorithmis constructed based on quantum computing and integrates similarity coefficient theory to strengthen genetic diversity and feature extraction capabilities.For the subsequent clustering phase,the process based on the IQABC-K algorithm is enhanced with the core improvement of adaptive rotation gate and movement exploitation strategies to balance the exploration capabilities of global search and the exploitation capabilities of local search.Simultaneously,the acceleration of convergence toward the global optimum and a reduction in computational complexity are facilitated by means of the global optimum bootstrap strategy and a linear population reduction strategy.Through experimental evaluation with multiple algorithms and diverse performance metrics,the proposed algorithm confirms reliable accuracy on three datasets:KDD CUP99,NSL_KDD,and UNSW_NB15,achieving accuracy of 98.57%,98.81%,and 98.32%,respectively.These results affirm its potential as an effective solution for practical clustering applications.
基金funding from the European Commission by the Ruralities project(grant agreement no.101060876).
文摘In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic heterogeneous infrastructures,unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy.Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service(QoS).As the transport network is built of ad hoc nodes,there is no guarantee about their trustworthiness or behavior,and transversal functionalities are delegated to the extreme nodes.However,while security can be guaranteed in extreme-to-extreme solutions,privacy cannot,as all intermediate nodes still have to handle the data packets they are transporting.Besides,traditional schemes for private anonymous ad hoc communications are vulnerable against modern intelligent attacks based on learning models.The proposed scheme fulfills this gap.Findings show the probability of a successful intelligent attack reduces by up to 65%compared to ad hoc networks with no privacy protection strategy when used the proposed technology.While congestion probability can remain below 0.001%,as required in 6G services.
基金supported by the National Natural Science Foundation of China(Nos.82573045,82460602,82560459)the Hainan Provincial Graduate Student Innovative Research Project(No.Qhys2024-440).
文摘Post-translational modifications(PTMs)regulate the occurrence and development of cancer,and lactylation modification is a new form of PTMs.Recent studies have found that lactic acid modification can regulate the immune tolerance of cancer cells.The classical theory holds that prostate apoptosis response-4(PAR-4)is a tumor suppressor protein.However,our recent research has found that PAR-4 has a biological function of promoting cancer in hepatocellular carcinoma(HCC),and our analysis shows that PAR-4 can be modified of lactic acid.These research evidences suggest that PAR-4 lactylation modification may drive immune tolerance in HCC.Therefore,inhibiting PAR-4 lactylation modification is very likely to increase the sensitivity of HCC to immunotherapy.
基金supported by grants from the National Natural Science Foundation of China(32172498 and W2433052)the National Key R&D Program of China(2021YFD1000500)the Natural Science Foundation of Guangdong,China(2023A1515010305)。
文摘The red imported fire ant,Solenopsis invicta Buren,is a highly invasive eusocial insect pest that threatens native biodiversity,agriculture,and human health.The innate immune system and intricate social immune responses of S.invicta pose challenges to the development of effective control strategies.Micro RNAs(mi RNAs)play critical roles in the post-transcriptional regulation of gene expression,which influences various biological processes,including immunity and host-pathogen interactions.While the mi RNA-mediated response of insects to pathogens has been extensively studied in solitary insects,little is known about the innate immune responses of individual members within a colony.To address this gap,we constructed small RNA libraries from Metarhizium anisopliae-infected S.invicta workers and investigated the temporal dynamics of mi RNA-mediated immune responses to the entomopathogen.Several differentially expressed mi RNAs were identified,and they were found to regulate genes involved in the Toll,IMD,and melanization immune pathways.Quantitative real-time PCR(q RT-PCR)was employed to analyze the spatiotemporal dynamics of key mi RNAs/target genes,specifically mi R-71/Mod SP1-Relish and mi R-7/Lysozyme2-Serine protease7.A dual luciferase assay(in vitro)was performed to validate the interactions between mi RNAs and their target genes.Overexpression of mi R-71 and mi R-7(via mi RNA mimics)efficiently suppressed their target genes,impaired the antifungal immune response of S.invicta and increased the susceptibility to M.anisopliae infection compared to controls.Furthermore,RNA interference-based gene silencing elucidated the roles of these immune genes in regulating fungal susceptibility,thus providing vital clues for developing virulent and effective mycoinsecticides using modern genetic engineering tools.
基金supported by the National Natural Science Foundation of China(No.82260820)the Natural Science Foundation of Jilin Province,Jilin,China(No.YDZJ202201ZYTS155).
文摘Pulmonary fibrosis(PF)is a progressive,fatal fibrotic disease caused by respiratory conditions.The condition can ultimately lead to severe organ failure and mortality,and is associated with multiple risk factors.Growing evidence highlights the immune system’s role in PF,with various immune components participating in inflammatory and fibrotic processes.Different immune cells,including neutrophils,lymphocytes,and macrophages,demonstrate distinct effects on PF progression and development.Furthermore,key immune system cytokines,including the interleukin(IL)family,tumor necrosis factor(TNF)-α,interferon(IFN)-γ,transforming growth factor(TGF)-β,and connective tissue growth factor(CTGF),contribute to PF initiation and progression through independent mechanisms and mutual regulation.Currently,limited effective treatments exist for PF,with several treatments causing severe adverse reactions.Natural products,characterized by multi-target effects,holistic regulation,and low toxicity,have emerged as a research focus.This review compiles the mechanisms,therapeutic potential,and active components of various natural products.These compounds can ameliorate pulmonary inflammation,epithelial-mesenchymal transition,and collagen deposition through diverse immune mechanisms,acting at specific stages or throughout the fibrotic process,thereby supporting PF management.This review examines current scientific understanding of natural products’immunological effects in PF,which is crucial for developing future anti-PF therapeutics.
基金supported by the Scientific Research Project of Anhui ProvincialHealth Commission(Grant No.AHWJ2021b063)National Natural Scientific Foundation of China(Grant No.82160048)+1 种基金Natural Science Foundation Project of Anhui Province(Grant No.2308085MH265)Major Scientific Research Project of Anhui Provincial Department of Education(Grant No.2024AH040205).
文摘Objectives:Postmenopausal osteoporosis is the most common form of osteoporosis in clinical practice,affecting millions of postmenopausal women worldwide.Postmenopausal osteoporosis demands safe and effective therapies.This study aimed to evaluate the potential of hederagenin(Hed)for treating osteoporosis and to elucidate its underlying mechanisms of action.Methods:The anti-osteoporotic potential of Hed was assessed by investigating its effects on ovariectomy(OVX)-induced bone loss in mice and on receptor activator of NF-kappaB ligand(RANKL)-induced osteoclast differentiation in RAW264.7 cells.Network pharmacology analysis and molecular docking were employed to identify key targets,which were subsequently validated experimentally.Results:In vitro,Hed suppressed osteoclastogenesis by inhibiting the formation of osteoclasts and F-actin rings and by down-regulating osteoclastspecific genes(Atp6v0d2 and Acp5).In vivo,Hed significantly amelioratedOVX-induced bone loss,restoring trabecular bone volume fraction(BV/TV)and trabecular number(Tb.N),while reducing trabecular separation(Tb.Sp).Network pharmacology analysis identified 142 overlapping targets linking Hed to osteoporosis,including tumor necrosis factor alpha(TNF-α),interleukin-6(IL-6),and IL-1β,with enrichment in innate immune signaling and osteoclast differentiation.Molecular docking analysis indicated strong binding affinities between Hed and targets such as TNF-α,IL-6,and IL-1β.Experimentally,Hed was found to decrease RANKL,elevate osteoprotegerin(OPG),and suppress intestinalmRNA levels of pro-inflammatory cytokines such as IL-1β,IL-6,IL-17A,and TNF-α.Conclusion:Hed exerts significant anti-osteoporotic effects inOVX-induced osteoporosis through a dualmechanism involving the suppression of both osteoclastogenesis and innate immune signaling pathways.These findings highlighted Hed’s novel role in modulating immune-bone crosstalk,offering a promising strategy for treating osteolytic diseases without estrogenic side effects.
文摘Hepatocellular carcinoma presents with three distinct immune phenotypes,including immune-desert,immune-excluded,and immune-inflamed,indicating various treatment responses and prognostic outcomes.The clinical application of multi-omics parameters is still restricted by the expensive and less accessible assays,although they accurately reflect immune status.A comprehensive evaluation framework based on“easy-to-obtain”multi-model clinical parameters is urgently required,incorporating clinical features to establish baseline patient profiles and disease staging;routine blood tests assessing systemic metabolic and functional status;immune cell subsets quantifying subcluster dynamics;imaging features delineating tumor morphology,spatial configuration,and perilesional anatomical relationships;immunohistochemical markers positioning qualitative and quantitative detection of tumor antigens from the cellular and molecular level.This integrated phenomic approach aims to improve prognostic stratification and clinical decision-making in hepatocellular carcinoma management conveniently and practically.
基金financial support from the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20230718)。
文摘The interplay between gut microbiota and host health has attracted significant interest in the animal science community.Maintaining gut microbiota homeostasis by supplementing probiotics to treat clinical conditions like calf diarrhea is an emerging area of research nowadays because of increased concerns regarding antimicrobial resistance(AMR)and drug residues in animal products.Probiotics reduce the incidence of calf diarrhea by increasing the gut microbiota diversity and richness with more commensal bacteria such as Lactobacillus and Bifidobacterium that produce antimicrobial compounds,as well as modulating the immune response by increasing cytokines,Interleukin-2(IL-2),IL-4,IL-6,IL-10,and reducing tumor necrosis factor-α(TNF-α),by increasing production of antibodies,especially immunoglobulin E(Ig E),also Ig G,differentiating naive Th lymphocytes(Tho)into Th1,hence stimulate innate immunity and prime the adaptive immune response.Specific probiotic strains of bacteria and yeast(Saccharomyces cerevisiae)derived probiotics maintain the integrity of the intestinal barrier.In this review,data are being organized to address the role of probiotics in treating calf diarrhea by modulating gut microbiota and stimulating an immune response against notorious pathogens,to present animal and veterinary scientists and nutritionists with a new concept to treat infectious diseases from the perspective of the gut microbiota,increasing animal health,performance,and welfare.In conclusion,health status and gut microbiome are strongly interlinked.Research data indicated a significant reduction in the incidence of diarrhea after probiotic administration.If interrelations between probiotics and existing gut microbiota are explored more quantitatively,novel antibiotic substitutes can emerge in the future.
基金supported by the Ningbo Natural Science Foundation(Youth Foundation,No.2024J449)the Scientific Research Foundation for Introduced Talents of Ningbo University(Nos.ZX2022000602 and ZX2024000043)。
文摘Polyfluoroalkyl substances(PFAS)have emerged as persistent environmental contaminants because of their chemical stability,degradation-resistance and bioaccumulation potential.However,current studies mainly focus on the toxicity of single PFAS such as perfluorooctanoic acid(PFOA)and perfluorobutanoic acid(PFBA),the knowledge of their combined effects is relatively limited.In this study,we explored the immune response of the gut in large yellow croaker(Larimichthys crocea)under the combined stress of PFOA and PFBA.Histologicalanalyses revealed that the combined effect induced intestinal vacuolization and decreased the length of intestinal villi.And it significantly activated pro-inflammatory pathways with marked upregulation of tnfα,il1β,il6 and myd88 expressions,particularly after 14 days of exposure.Gut microbiota analysis revealed substantial dysbiosis,including 1)reduced alpha diversity,2)increased abundance of potential pathogenic taxa(Proteobacteria and Spirochaetota),and 3)depletion of beneficial Firmicutes.PICRUSt-based functional prediction indicated temporal metabolic shifts,with upregulation of DNA repair pathways at day 3 and enhanced bacterial motility protein activity at days 7 and 14 of post-exposure.The Pearson correlation analysis further indicated that these immune genes had significant positive correlations with Vibrio and Brevinema,and negative correlations with Streptococcus.Our present study will provide novel insights into the microbiome-mediated immunomodulation in the larger yellow croaker exposed to combined PFAS,which will be helpful for healthy farming of economically important marine species.
文摘Objective:To investigate the correlation between the expression of glucose-6-phosphate dehydrogenase(G6PD)and the clinicopathological characteristics,prognosis and immune cell infiltration of hepatocellular carcinoma(HCC).Methods:The expression of G6PD in liver cancer tissues and normal tissues is extracted from TCGA and GEO databases,validated by immunohistochemistry,and the correlation between G6PD expression and clinical features is analyzed.The clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier,Cox regression,and prognostic line graph models.Functional enrichment analysis is performed by protein-protein interaction(PPI)network,GO/KEGG,GSEA and for G6PD-associated differentially expressed genes(DEGs).TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results:Analysis of TCGA and GEO datasets revealed that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues(P<0.001).G6PD expression is associated with histological grade,pathological stage,T-stage,vascular infiltration,and AFP level(P<0.05);HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group(P<0.05).The level of G6PD expression affects the levels of macrophages,dendritic cells,B cells,and follicular helper T cells in the tumor microenvironment.Conclusion:High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma,and G6PD may be a target for immunotherapy of HCC.
基金Supported by the National Natural Science Foundation of China(No.82460215)National Natural Science Foundation of China Pre-experimental Project(No.2025GZRYSY006)+4 种基金2025 Youth Training Project of the Xi’an Municipal Health Commission(No.2025qn05)Xi’an Medical Research-Discipline Capacity Building Project(No.23YXYJ0002)Key R&D Plan of Shaanxi Province:Key Industrial Innovation Chain(Cluster)-Social Development Field(No.2022ZDLSF03-10)Research Incubation Fund of Xi’an People’s Hospital(Xi’an Fourth HospitalNo.LH-13).
文摘AIM:To identify metastasis-associated prognostic genes and construct a robust molecular signature for survival prediction in uveal melanoma(UVM)patients.METHODS:Transcriptomic data and clinical information from 80 UVM patients in the Cancer Genome Atlas(TCGA)-UVM cohort and an external Gene Expression Omnibus(GEO)microarray dataset(GSE73652;8 non-metastatic vs 5 metastatic cases)were analyzed to identify differentially expressed genes(DEGs).Functional enrichment,proteinprotein interaction(PPI)network construction,and survival analyses identified seven metastasis-and prognosisrelated genes.Their expression was further examined using public single-cell RNA-seq data(GSE139829;11 tumors).Experimental validation was performed in UVM cell lines(92.1,OMM1,MEL270)and adult retinal pigment epithelial(ARPE-19)cells using quantitative real-time polymerase chain reaction(qRT-PCR)and Western blotting to confirm transcriptomic trends.A LASSO Cox model was applied to construct a metastasis-related risk Score signature.Tumor immune microenvironment characteristics were evaluated via single-sample gene set enrichment analysis(ssGSEA)and ESTIMATE.Somatic mutation and copy number variation(CNV)profiles were also examined.RESULTS:Seven key genes(UBE2T,KIF20A,DLGAP5,KLC3,TPX2,UBE2C,AURKA)were significantly associated with overall survival and used to construct a metastasisrelated riskScore signature,which effectively stratified patients into high-and low-risk groups and served as an independent prognostic factor.qRT-PCR and Western blot results confirmed that the expression levels of selected key genes in UVM cell lines showed significant differences compared to ARPE-19 cells,which were largely consistent with the transcriptomic findings.The high-risk group exhibited reduced immune infiltration and stromal activity.Single-cell analysis revealed these genes were predominantly expressed in a tumor cell cluster characterized by BAP1 loss and high metastatic potential.Mutation and CNV analyses further supported the relevance of these genes to UVM progression.CONCLUSION:This study establishes and validates a seven-gene signature associated with metastasis and prognosis in UVM.The findings provide a framework for understanding molecular determinants of tumor progression and immune microenvironment alterations,and may offer guidance for future mechanistic studies and therapeutic exploration.
基金funded by the National Natural Science Foundation of China(Grant Nos.82204517 to T.Z.and 82404756 to J.Z.)the Science and Technology Program in Medicine and Health of Zhejiang Province(Grant No.2023KY726 to T.Z.).
文摘Background:Aberrant expression of transcription factors(TFs)is a key mechanism mediating tumor immune escape and therapeutic resistance.The involvement of E26 transformation-specific(ETS)family of TFs in immune regulation is not fully understood.The study aimed to elucidate the function of E-twenty-six variant 4(ETV4)in tumor immune evasion and its potential as a predictive biomarker for immunotherapy in melanoma.Methods:The expression patterns of ETS family TFs were analyzed in melanoma and hepatocellular carcinoma(HCC).Single-cell RNA sequencing(scRNA-seq)was used to dissect the cellular expression and function of ETV4 in the tumor microenvironment.Functional studies and murine models were employed to investigate the role of ETV4 in T cell-mediated tumor killing and tumor growth.The correlation between ETV4 expression level and patient responsiveness to programmed cell death protein 1(PD-1)blockade therapy was evaluated.Results:TFs in the ETS family were found to effectively stratify melanoma and HCC patients into prognostic subgroups.In melanoma,the polyoma enhancer activator 3(PEA3)subfamily,particularly ETV4 and ETV5,showed a negative correlation with immune infiltration.scRNA-seq analysis showed that ETV4 is preferentially expressed in melanoma cells and involves in mediating tumor-immunocyte interactions.Functional studies demonstrated that ETV4 impairs T cell-mediated tumor killing by transcriptionally upregulating programmed death-ligand 1(PD-L1).In immunocompetent murine models,ETV4 downregulation significantly suppressed tumor growth.Furthermore,high ETV4 expression correlated with poor responses to anti-PD-1 therapy.Conclusion:Our findings identify ETV4 as a key transcriptional regulator of immune evasion in melanoma by controlling PD-L1 expression.ETV4 may act as a predictive biomarker for immunotherapy outcomes.
基金supported by Beijing Sport University Graduate Innovation Programme(2024013).
文摘Background:Exercise exerts tumor-suppressive effects across multiple malignancies,partly through exerkines—exercise-induced secreted factors with immunomodulatory and metabolic functions.However,the prognostic relevance of exerkines across cancer types remains unclear,and the molecular determinants of exercise responsiveness are poorly defined.Methods:We systematically profiled 183 curated exerkine-related genes across 33 cancer types from The Cancer Genome Atlas(TCGA)using non-negative matrix factorization(NMF)to define molecular subtypes.Prognostic significance was evaluated via Kaplan-Meier analysis.For five cancers with consistent survival divergence(LGG,KIRC,LUAD,PAAD,ACC),we developed an Exerkine Prognostic Index(EPI)using LASSO Cox regression and validated its predictive performance through time-dependent ROC analysis.Immune cell infiltration(CIBERSORT),stromal/immune scores(ESTIMATE),and immune checkpoint expression were assessed to characterize immune landscape differences between EPI subgroups.Results:Exerkine-based NMF clustering identified prognostically distinct subtypes in 25 cancers.The EPI robustly stratified patients into high-and low-risk groups with significant differences in overall survival(p<0.001).High-EPI subgroups were associated with elevated infiltration of immunosuppressive cells(e.g.,Tregs,M0 macrophages),altered immune/stromal scores,and differential expression of immune checkpoints such as PD-L1 and CTLA4 in a cancer-type-specific manner.Discussion:Our findings reveal that exerkine expression patterns capture biologically and clinically relevant heterogeneity across cancers.The EPI provides a robust molecular tool to stratify patients by prognosis and immune contexture,offering insights into differential exercise responsiveness.Conclusions:Exerkines represent promising biomarkers for risk stratification and precision-guided exercise interventions in oncology.
