Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d...Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.展开更多
Background:Parkinson’s disease(PD)is one of the most common movement disorders worldwide.Ziyin Xifeng Decoction(ZYXFD),a traditional Chinese medicine compound formula,has shown therapeutic efficacy in treating PD,but...Background:Parkinson’s disease(PD)is one of the most common movement disorders worldwide.Ziyin Xifeng Decoction(ZYXFD),a traditional Chinese medicine compound formula,has shown therapeutic efficacy in treating PD,but its specific mechanisms of action have not been fully elucidated.Methods:Firstly,we employed network pharmacology and untargeted metabolomics analysis to identify the core targets,pathways,and key metabolites of ZYXFD in the treatment of PD.Subsequently,we evaluated the protective effects of ZYXFD and further investigated its anti-PD mechanisms by validating the analytical results.Results:Combined analyses of network pharmacology and metabolomics identify the core targets including EGFR,SRC,PTGS2,and CDK2,while the effects of ZYXFD against PD are likely mediated primarily through the PI3K/AKT/mTOR signaling pathway.Pharmacodynamic evaluation demonstrated that a high dose of ZYXFD significantly improved behavioral deficits in chronic PD mice,downregulatedα-synuclein protein expression,and protected dopaminergic neurons.It also regulated the expression of core targets,inhibited the PI3K/AKT/mTOR signaling pathway,promoted autophagy,and reduced apoptosis.In vitro experiments further verified that the therapeutic effect of ZYXFD on PD is dependent on autophagy regulation.Conclusion:The findings demonstrated that ZYXFD alleviates PD by modulating related proteins and metabolites,inhibiting the PI3K/AKT/mTOR signaling pathway,and enhancing autophagy.This provides a theoretical basis for its broader application in PD treatment.展开更多
Background:ZhiZi-BoPi Decoction(ZZBPD),a traditional prescription for liver and gallbladder protection,has garnered significant clinical interest due to its hepatoprotective properties.Despite its proven efficacy in m...Background:ZhiZi-BoPi Decoction(ZZBPD),a traditional prescription for liver and gallbladder protection,has garnered significant clinical interest due to its hepatoprotective properties.Despite its proven efficacy in mitigating intrahepatic cholestasis,the precise mechanisms underlying its therapeutic effects remain inadequately understood.This study aims to comprehensively investigate the pharmacological mechanisms underlying the therapeutic effects of ZZBPD in cholestatic liver injury(CLI).Methods:Firstly,we evaluated the hepatoprotective effects of ZZBPD on mice with CLI induced byα-naphthylisothiocyanate(ANIT),by measuring biochemical markers,inflammatory factors,and bile acid levels.Subsequently,we employed network pharmacology and single-cell RNA sequencing(scRNA-seq)to identify key targets and potential signaling pathways for the prevention and treatment of CLI.Finally,we further validated the mechanism of action of ZZBPD on these key targets through molecular docking,western blotting,and immunofluorescence techniques.Results:ZZBPD notably improved serum liver function,reduced hepatic inflammation,and restored bile acid balance.Through network pharmacology and scRNA-seq analysis,48 core targets were identified,including TNF,IL-6,and NFKB1,all of which are linked to the IL-17 and NF-κB signaling pathways,as shown by KEGG enrichment analysis.Molecular docking further confirmed stable interactions between ZZBPD’s key active components and molecules such as IL-6,IL-17,and NF-κB.Additionally,western blotting and immunofluorescence validated the downregulation of IL-17 and NF-κB protein expression in liver tissue.Conclusion:ZZBPD effectively treats CLI by activating pathways related to the bile acid receptor FXR,while also modulating the IL-17/NF-κB signaling pathway.This dual action enhances bile secretion and alleviates liver inflammation.These findings offer important insights into the pharmacological mechanisms of ZZBPD and underscore its potential as a promising therapeutic for CLI.展开更多
Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-targe...Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.展开更多
Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often stru...Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.展开更多
Hepatitis C virus(HCV)and hepatitis B virus(HBV)infections are increasingly recognized as significant etiological factors in the pathogenesis of B-cell non-Hodgkin’s lymphomas(B-NHLs).Epidemiological and molecular st...Hepatitis C virus(HCV)and hepatitis B virus(HBV)infections are increasingly recognized as significant etiological factors in the pathogenesis of B-cell non-Hodgkin’s lymphomas(B-NHLs).Epidemiological and molecular studies have demonstrated a consistent association between chronic viral infection and B-NHLs.Multiple pathogenic mechanisms have been implicated in lymphomagenesis,both direct and indirect,including chronic antigenic stimulation,direct infection of B cells,and viral protein-mediated oncogenic signaling,It is likely that a combination of several pathogenic conditions is required to eventually lead to the development of lymphoma.The prevalence of B-cell lymphomas among individuals with chronic HCV or HBV infection presents a complex pathogenetic scenario,given the tumor heterogeneity and variable clinical behavior,and poses therapeutic challenges,due to the partial efficacy of current treatment options.The advent of direct-acting antivirals(DAAs)for HCV and high-genetic barrier nucleos(t)ide analogues(NAs)for HBV has improved patient outcomes.In indolent HCV-associated B-NHLs,antiviral therapy with DAAs alone often achieves sustained virologic response and may lead to lymphoma regression.Conversely,aggressive subtypes like diffuse large B-cell lymphomas require combination treatment with immunochemotherapy.In the setting of HBV-associated lymphomas,antiviral prophylaxis with potent NAs(e.g.,entecavir or tenofovir)is essential to prevent HBV reactivation during rituximab-containing chemotherapy regimen.The integration of antiviral and anticancer therapies has been shown to enhance survival outcomes while mitigating hepatic toxicity.A comprehensive understanding of the biological interplay between chronic viral infection and B-cell transformation is critical for optimizing diagnostic and therapeutic strategies.Aim of this viewpoint is to provide evidence that early viral detection and prompt management remain the most effective strategies to improve survival rates and to reduce treatment-related morbidity in these patients.展开更多
Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,n...Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.展开更多
[Objectives]This study was conducted to explore the action mechanism of limonoids against Alzheimer s disease(AD)based on network pharmacology and molecular docking techniques.[Methods]Limonoid compounds were obtained...[Objectives]This study was conducted to explore the action mechanism of limonoids against Alzheimer s disease(AD)based on network pharmacology and molecular docking techniques.[Methods]Limonoid compounds were obtained through literature research(January 1942 to January 2021).Active components and potential targets of limonoids were retrieved from PubChem,TCMSP,and Swiss Target Prediction databases.AD-related targets were obtained from the GeneCards database,and intersecting targets were identified using Venny 2.1.0 to obtain the action targets of limonoids against AD.The protein-protein interaction(PPI)network was constructed using the String platform,and key targets were screened and visualized via network topology analysis with Cytoscape software.GO and KEGG pathway enrichment analyses were performed using the Metascape database,and a"drug-component-target-pathway-disease"network diagram was constructed using Cytoscape.AutoDock was empolyed for molecular docking to predict the binding properties of limonoid active components and their targets.[Results]A total of 60 limonoid compounds were obtained from literature research.Network pharmacology analysis showed 58 effective active components and 134 common targets between limonoids and AD.Key targets included AKT1(serine/threonine-protein kinase 1),TNF(tumor necrosis factor),STAT3(signal transducer and activator of transcription 3),BCL2(B-cell lymphoma 2),and EGFR(epidermal growth factor receptor).KEGG enrichment analysis revealed key signaling pathways such as pathways in cancer,Kaposi sarcoma-associated herpesvirus infection,PI3K-Akt signaling pathway,lipid and atherosclerosis,proteoglycans in cancer,MAPK signaling pathway,and Ras signaling pathway.Molecular docking results indicated that aphanamixoid A,obacunol,cipadesin C,harpertrioate A,xylogranatin A,11-oxocneorin G,evodulone,methyl angolensate,harrpemoid B and khivorin may be key components of limonoids against AD.[Conclusions]Limonoids exert anti-Alzheimer s effects through a multi-molecule,multi-target and multi-pathway mechanism.展开更多
OBJECTIVE:To investigate the mechanism underlying the effect of the Huanglian decoction(黄连汤,HLD)on morphine tolerance(MT),using network pharmacology,and to verify these mechanisms in vitro and in vivo.METHODS:Avail...OBJECTIVE:To investigate the mechanism underlying the effect of the Huanglian decoction(黄连汤,HLD)on morphine tolerance(MT),using network pharmacology,and to verify these mechanisms in vitro and in vivo.METHODS:Available biological data on each drug in the HLD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform.The target proteins of MT were retrieved from the GeneCards,PharmGkb,Therapeutic Target Database,DrugBank,and Online Mendelian Inheritance in Man databases.Information regarding MT and the drug targets was compared to obtain overlapping elements.This information was imported into the Search Tool for the Retrieval of Interacting Genes/Proteins platform to obtain a protein-protein interaction network diagram.Then,a“component-target”network diagram was constructed using screened drug components and target information,via Cytoscape(Institute for Systems Biology,Seattle,WA,USA).The database for annotation,visualization,and integrated discovery was used for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses.Pathway information predicted by network pharmacology was verified using animal studies and cell experiments.RESULTS:Network pharmacology analysis identified 22 active compounds of HLD and revealed that HLD partially ameliorated MT by modulating inflammatory,apoptosis,and nuclear factor kappa B(NF-κB)signaling pathways.Berberine(BBR),one of the main components of HLD,inhibited the development of MT in mice.BBR reduced cell viability while increasing B-cell lymphoma 2(Bcl-2)protein expression and decreasing CD86,NF-κB,Bax,and Caspase-3 protein expression in brain vascular 2(BV2)mcroglia cells treated with morphine.Additionally,BBR contributed to a reduction in pro-inflammatory cytokine release and apoptotic cell number.CONCLUSIONS:BBR,a key component of HLD,effectively suppressed microglial activation and neuroinflammation by regulating the NF-κB and apoptosis signaling pathways,thereby delaying MT.This study offers a novel approach to enhance the clinical analgesic efficacy of morphine.展开更多
基金The work described in this paper was fully supported by a grant from Hong Kong Metropolitan University(RIF/2021/05).
文摘Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.
基金funded by Zhejiang Province Traditional Chinese Medicine Science and Technology Program(No.2021ZZ012)The Changlin Qiu National Distinguished Senior Traditional Chinese Medicine Expert Heritage Workshop Project(No.GZS2021007).
文摘Background:Parkinson’s disease(PD)is one of the most common movement disorders worldwide.Ziyin Xifeng Decoction(ZYXFD),a traditional Chinese medicine compound formula,has shown therapeutic efficacy in treating PD,but its specific mechanisms of action have not been fully elucidated.Methods:Firstly,we employed network pharmacology and untargeted metabolomics analysis to identify the core targets,pathways,and key metabolites of ZYXFD in the treatment of PD.Subsequently,we evaluated the protective effects of ZYXFD and further investigated its anti-PD mechanisms by validating the analytical results.Results:Combined analyses of network pharmacology and metabolomics identify the core targets including EGFR,SRC,PTGS2,and CDK2,while the effects of ZYXFD against PD are likely mediated primarily through the PI3K/AKT/mTOR signaling pathway.Pharmacodynamic evaluation demonstrated that a high dose of ZYXFD significantly improved behavioral deficits in chronic PD mice,downregulatedα-synuclein protein expression,and protected dopaminergic neurons.It also regulated the expression of core targets,inhibited the PI3K/AKT/mTOR signaling pathway,promoted autophagy,and reduced apoptosis.In vitro experiments further verified that the therapeutic effect of ZYXFD on PD is dependent on autophagy regulation.Conclusion:The findings demonstrated that ZYXFD alleviates PD by modulating related proteins and metabolites,inhibiting the PI3K/AKT/mTOR signaling pathway,and enhancing autophagy.This provides a theoretical basis for its broader application in PD treatment.
基金supported by the National Science Foundation of China(No.82405004,82474253)the Natural Science Foundation postdoctoral project of Chongqing(CSTB2022NSCQ-BHX0709)+2 种基金Chongqing Wanzhou District doctoral“through train”scientific research project(wzstc-20220124)Natural Science Foundation of Chongqing,China(No.Cstc2021jcyj-msxmX0996)Chongqing Wanzhou District Science and Health Joint Medical Research Project(wzstc-kw2023032)。
文摘Background:ZhiZi-BoPi Decoction(ZZBPD),a traditional prescription for liver and gallbladder protection,has garnered significant clinical interest due to its hepatoprotective properties.Despite its proven efficacy in mitigating intrahepatic cholestasis,the precise mechanisms underlying its therapeutic effects remain inadequately understood.This study aims to comprehensively investigate the pharmacological mechanisms underlying the therapeutic effects of ZZBPD in cholestatic liver injury(CLI).Methods:Firstly,we evaluated the hepatoprotective effects of ZZBPD on mice with CLI induced byα-naphthylisothiocyanate(ANIT),by measuring biochemical markers,inflammatory factors,and bile acid levels.Subsequently,we employed network pharmacology and single-cell RNA sequencing(scRNA-seq)to identify key targets and potential signaling pathways for the prevention and treatment of CLI.Finally,we further validated the mechanism of action of ZZBPD on these key targets through molecular docking,western blotting,and immunofluorescence techniques.Results:ZZBPD notably improved serum liver function,reduced hepatic inflammation,and restored bile acid balance.Through network pharmacology and scRNA-seq analysis,48 core targets were identified,including TNF,IL-6,and NFKB1,all of which are linked to the IL-17 and NF-κB signaling pathways,as shown by KEGG enrichment analysis.Molecular docking further confirmed stable interactions between ZZBPD’s key active components and molecules such as IL-6,IL-17,and NF-κB.Additionally,western blotting and immunofluorescence validated the downregulation of IL-17 and NF-κB protein expression in liver tissue.Conclusion:ZZBPD effectively treats CLI by activating pathways related to the bile acid receptor FXR,while also modulating the IL-17/NF-κB signaling pathway.This dual action enhances bile secretion and alleviates liver inflammation.These findings offer important insights into the pharmacological mechanisms of ZZBPD and underscore its potential as a promising therapeutic for CLI.
基金supported by the National Natural Science Foundation of China(Grant Nos.:32271292,31872723,32200778,and 22377089)the Jiangsu Students Innovation and Entrepre-neurship Training Program,China(Program No.:202210285081Z)+6 种基金the Project of MOE Key Laboratory of Geriatric Diseases and Immunology,China(Project No.:JYN202404)Proj-ect Funded by the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions,Natural Science Foundation of Jiangsu Province,China(Project No.:BK20220494)Suzhou Medical and Health Technology Innovation Project,China(Grant No.:SKY2022107)the Clinical Research Center of Neuro-logical Disease in The Second Affiliated Hospital of Soochow University,China(Grant No.:ND2022A04)State Key Laboratory of Drug Research(Grant No.:SKLDR-2023-KF-05)Jiangsu Shuang-chuang Program for Doctor,Young Science Talents Promotion Project of Jiangsu Science and Technology Association(Program No.:TJ-2023-019)Young Science Talents Promotion Project of Suzhou Science and Technology Association,Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases,and startup funding(Grant Nos.:NH21500221,NH21500122,and NH21500123)to Qifei Cong.
文摘Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2025-02-01295).
文摘Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.
基金supported by the National Italian Research Council(CNR)“Progetto DSB.AD007.305.001”to Monica Rinaldi。
文摘Hepatitis C virus(HCV)and hepatitis B virus(HBV)infections are increasingly recognized as significant etiological factors in the pathogenesis of B-cell non-Hodgkin’s lymphomas(B-NHLs).Epidemiological and molecular studies have demonstrated a consistent association between chronic viral infection and B-NHLs.Multiple pathogenic mechanisms have been implicated in lymphomagenesis,both direct and indirect,including chronic antigenic stimulation,direct infection of B cells,and viral protein-mediated oncogenic signaling,It is likely that a combination of several pathogenic conditions is required to eventually lead to the development of lymphoma.The prevalence of B-cell lymphomas among individuals with chronic HCV or HBV infection presents a complex pathogenetic scenario,given the tumor heterogeneity and variable clinical behavior,and poses therapeutic challenges,due to the partial efficacy of current treatment options.The advent of direct-acting antivirals(DAAs)for HCV and high-genetic barrier nucleos(t)ide analogues(NAs)for HBV has improved patient outcomes.In indolent HCV-associated B-NHLs,antiviral therapy with DAAs alone often achieves sustained virologic response and may lead to lymphoma regression.Conversely,aggressive subtypes like diffuse large B-cell lymphomas require combination treatment with immunochemotherapy.In the setting of HBV-associated lymphomas,antiviral prophylaxis with potent NAs(e.g.,entecavir or tenofovir)is essential to prevent HBV reactivation during rituximab-containing chemotherapy regimen.The integration of antiviral and anticancer therapies has been shown to enhance survival outcomes while mitigating hepatic toxicity.A comprehensive understanding of the biological interplay between chronic viral infection and B-cell transformation is critical for optimizing diagnostic and therapeutic strategies.Aim of this viewpoint is to provide evidence that early viral detection and prompt management remain the most effective strategies to improve survival rates and to reduce treatment-related morbidity in these patients.
文摘Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.
基金Supported by Science and Technology Fund of Guizhou health and Health Committee(gzwkj2024-240)Anshun City Science and Technology Bureau(ASKS[2024]01).
文摘[Objectives]This study was conducted to explore the action mechanism of limonoids against Alzheimer s disease(AD)based on network pharmacology and molecular docking techniques.[Methods]Limonoid compounds were obtained through literature research(January 1942 to January 2021).Active components and potential targets of limonoids were retrieved from PubChem,TCMSP,and Swiss Target Prediction databases.AD-related targets were obtained from the GeneCards database,and intersecting targets were identified using Venny 2.1.0 to obtain the action targets of limonoids against AD.The protein-protein interaction(PPI)network was constructed using the String platform,and key targets were screened and visualized via network topology analysis with Cytoscape software.GO and KEGG pathway enrichment analyses were performed using the Metascape database,and a"drug-component-target-pathway-disease"network diagram was constructed using Cytoscape.AutoDock was empolyed for molecular docking to predict the binding properties of limonoid active components and their targets.[Results]A total of 60 limonoid compounds were obtained from literature research.Network pharmacology analysis showed 58 effective active components and 134 common targets between limonoids and AD.Key targets included AKT1(serine/threonine-protein kinase 1),TNF(tumor necrosis factor),STAT3(signal transducer and activator of transcription 3),BCL2(B-cell lymphoma 2),and EGFR(epidermal growth factor receptor).KEGG enrichment analysis revealed key signaling pathways such as pathways in cancer,Kaposi sarcoma-associated herpesvirus infection,PI3K-Akt signaling pathway,lipid and atherosclerosis,proteoglycans in cancer,MAPK signaling pathway,and Ras signaling pathway.Molecular docking results indicated that aphanamixoid A,obacunol,cipadesin C,harpertrioate A,xylogranatin A,11-oxocneorin G,evodulone,methyl angolensate,harrpemoid B and khivorin may be key components of limonoids against AD.[Conclusions]Limonoids exert anti-Alzheimer s effects through a multi-molecule,multi-target and multi-pathway mechanism.
基金Natural Science Foundation-funded Project:Study on the Mechanism of Mechanical Stress Sensing Element Piezo Type Mechanosensitive Ion Channel Component 2 Interacting with Nuclear Receptor Subfamily 4 Group A Member 2 Mediating Traumatic Brain Injury(No.82172190)。
文摘OBJECTIVE:To investigate the mechanism underlying the effect of the Huanglian decoction(黄连汤,HLD)on morphine tolerance(MT),using network pharmacology,and to verify these mechanisms in vitro and in vivo.METHODS:Available biological data on each drug in the HLD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform.The target proteins of MT were retrieved from the GeneCards,PharmGkb,Therapeutic Target Database,DrugBank,and Online Mendelian Inheritance in Man databases.Information regarding MT and the drug targets was compared to obtain overlapping elements.This information was imported into the Search Tool for the Retrieval of Interacting Genes/Proteins platform to obtain a protein-protein interaction network diagram.Then,a“component-target”network diagram was constructed using screened drug components and target information,via Cytoscape(Institute for Systems Biology,Seattle,WA,USA).The database for annotation,visualization,and integrated discovery was used for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses.Pathway information predicted by network pharmacology was verified using animal studies and cell experiments.RESULTS:Network pharmacology analysis identified 22 active compounds of HLD and revealed that HLD partially ameliorated MT by modulating inflammatory,apoptosis,and nuclear factor kappa B(NF-κB)signaling pathways.Berberine(BBR),one of the main components of HLD,inhibited the development of MT in mice.BBR reduced cell viability while increasing B-cell lymphoma 2(Bcl-2)protein expression and decreasing CD86,NF-κB,Bax,and Caspase-3 protein expression in brain vascular 2(BV2)mcroglia cells treated with morphine.Additionally,BBR contributed to a reduction in pro-inflammatory cytokine release and apoptotic cell number.CONCLUSIONS:BBR,a key component of HLD,effectively suppressed microglial activation and neuroinflammation by regulating the NF-κB and apoptosis signaling pathways,thereby delaying MT.This study offers a novel approach to enhance the clinical analgesic efficacy of morphine.
