ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

ObjectiveMultiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS); however, its underlying neurological pathogenic mechanisms remain incompletely understood. Endogenous formaldehyde (FA), a metabolic byproduct of methylation-demethylation cycles, has recently been implicated in neurotoxicity, oxidative damage, and cognitive impairment. This study aimed to investigate whether excessive FA contributes to myelin sheath demyelination in mice and to evaluate the protective effects and mechanisms of two FA-elimination strategies: sodium bisulfite (NaHSO₃), a classical FA scavenger, and polyethylene glycol-modified astaxanthin nanoparticles (PEG-ATX@NPs), a brain-targeted nano-antioxidant formulation. MethodsA chronic demyelination model was established by feeding female C57BL/6J mice a diet containing 0.2% cuprizone (CPZ) for four weeks, followed by a two-week intervention period. Eighty mice were randomly assigned to four groups: NS (normal saline), CPZ+NS, CPZ+NaHSO₃, and CPZ+PEG-ATX@NPs. Behavioral tests, including open-field, Y-maze, and pole-climbing assays, were conducted to assess locomotor activity, motor coordination, and working memory. FA levels in serum, corpus callosum, and spinal cord were measured using an Na-FA fluorescent probe and quantified via in vivo and ex vivo fluorescence imaging. Neuroinflammatory responses were evaluated by measuring TNF-α, IL-1β, and IL-6 levels using ELISA, while oxidative stress was assessed by reactive oxygen species (ROS) fluorescence intensity. Demyelination was examined via Luxol fast blue staining, and microglial activation was analyzed by Iba1 immunofluorescence. Correlation analyses were performed to explore relationships among FA levels, inflammatory cytokines, ROS intensity, and behavioral parameters. ResultsCompared with the NS group, mice in the CPZ+NS group exhibited significant weight loss, impaired motor coordination and memory, and markedly reduced myelin regeneration (P<0.05). FA levels and pro-inflammatory cytokines were significantly elevated in serum, corpus callosum, and spinal cord (P<0.05). FA-associated fluorescence in brain and spinal tissues, as well as ROS intensity across all tissues examined, also increased substantially (P<0.05). CPZ treatment induced pronounced microglial activation and severe demyelination in the corpus callosum (P<0.01). Both NaHSO₃ and PEG-ATX@NPs effectively reduced FA accumulation in the brain and spinal cord, attenuated demyelination, suppressed microglial activation, decreased inflammatory cytokine levels, and improved motor and cognitive performance. These results confirm that CPZ induced severe demyelination accompanied by oxidative stress, neuroinflammation, and abnormal FA accumulation. Following intervention with either NaHSO₃ or PEG-ATX@NPs, endogenous FA levels in the CNS were substantially reduced. Both treatments alleviated demyelination and significantly decreased the number of activated microglia. Levels of TNF-α, IL-1β, and IL-6 in serum, corpus callosum, and spinal cord were downregulated. Behavioral performance improved significantly, as evidenced by enhanced locomotor activity, better coordination, and improved memory function. These findings indicate that both FA-scavenging agents mitigate CPZ-induced biochemical and behavioral abnormalities. ConclusionThis study demonstrates that excessive endogenous FA is closely associated with cognitive impairment, inflammatory dysregulation, and demyelination in a CPZ-induced chronic demyelination mouse model. Clearing abnormally elevated FA effectively reduces neuroinflammation, suppresses microglial overactivation, decreases oxidative stress, and alleviates demyelination, ultimately improving motor and cognitive outcomes in mice. These results suggest that targeting endogenous FA represents a promising therapeutic strategy for MS and other demyelinating disorders. Further investigations are warranted to explore the long-term safety, dosage optimization, and molecular pathways involved in FA-mediated neurotoxicity.

ObjectiveMultiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS); however, its underlying neurological pathogenic mechanisms remain incompletely understood. Endogenous formaldehyde (FA), a metabolic byproduct of methylation-demethylation cycles, has recently been implicated in neurotoxicity, oxidative damage, and cognitive impairment. This study aimed to investigate whether excessive FA contributes to myelin sheath demyelination in mice and to evaluate the protective effects and mechanisms of two FA-elimination strategies: sodium bisulfite (NaHSO₃), a classical FA scavenger, and polyethylene glycol-modified astaxanthin nanoparticles (PEG-ATX@NPs), a brain-targeted nano-antioxidant formulation. MethodsA chronic demyelination model was established by feeding female C57BL/6J mice a diet containing 0.2% cuprizone (CPZ) for four weeks, followed by a two-week intervention period. Eighty mice were randomly assigned to four groups: NS (normal saline), CPZ+NS, CPZ+NaHSO₃, and CPZ+PEG-ATX@NPs. Behavioral tests, including open-field, Y-maze, and pole-climbing assays, were conducted to assess locomotor activity, motor coordination, and working memory. FA levels in serum, corpus callosum, and spinal cord were measured using an Na-FA fluorescent probe and quantified via in vivo and ex vivo fluorescence imaging. Neuroinflammatory responses were evaluated by measuring TNF-α, IL-1β, and IL-6 levels using ELISA, while oxidative stress was assessed by reactive oxygen species (ROS) fluorescence intensity. Demyelination was examined via Luxol fast blue staining, and microglial activation was analyzed by Iba1 immunofluorescence. Correlation analyses were performed to explore relationships among FA levels, inflammatory cytokines, ROS intensity, and behavioral parameters. ResultsCompared with the NS group, mice in the CPZ+NS group exhibited significant weight loss, impaired motor coordination and memory, and markedly reduced myelin regeneration (P<0.05). FA levels and pro-inflammatory cytokines were significantly elevated in serum, corpus callosum, and spinal cord (P<0.05). FA-associated fluorescence in brain and spinal tissues, as well as ROS intensity across all tissues examined, also increased substantially (P<0.05). CPZ treatment induced pronounced microglial activation and severe demyelination in the corpus callosum (P<0.01). Both NaHSO₃ and PEG-ATX@NPs effectively reduced FA accumulation in the brain and spinal cord, attenuated demyelination, suppressed microglial activation, decreased inflammatory cytokine levels, and improved motor and cognitive performance. These results confirm that CPZ induced severe demyelination accompanied by oxidative stress, neuroinflammation, and abnormal FA accumulation. Following intervention with either NaHSO₃ or PEG-ATX@NPs, endogenous FA levels in the CNS were substantially reduced. Both treatments alleviated demyelination and significantly decreased the number of activated microglia. Levels of TNF-α, IL-1β, and IL-6 in serum, corpus callosum, and spinal cord were downregulated. Behavioral performance improved significantly, as evidenced by enhanced locomotor activity, better coordination, and improved memory function. These findings indicate that both FA-scavenging agents mitigate CPZ-induced biochemical and behavioral abnormalities. ConclusionThis study demonstrates that excessive endogenous FA is closely associated with cognitive impairment, inflammatory dysregulation, and demyelination in a CPZ-induced chronic demyelination mouse model. Clearing abnormally elevated FA effectively reduces neuroinflammation, suppresses microglial overactivation, decreases oxidative stress, and alleviates demyelination, ultimately improving motor and cognitive outcomes in mice. These results suggest that targeting endogenous FA represents a promising therapeutic strategy for MS and other demyelinating disorders. Further investigations are warranted to explore the long-term safety, dosage optimization, and molecular pathways involved in FA-mediated neurotoxicity.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

AIM To investigate the in vivo pharmacokinetics of chlorogenic acid,isoquercetin,ferulic acid,isorhamnetin and shionone in Asteris Radix et Rhizoma in rats.METHODS Twelve rats were randomly assigned into 2 groups and given intragastric administration of conventional dose(0.63 g/kg)and large dose(3.3 g/kg)of Asteris Radix et Rhizoma extracts,respectively,after which blood collection was made at 0.083,0.167,0.33,0.5,0.75,1,1.5,2,4,6,8,12,24 h,UPLC-MS/MS was adopted in the plasma concentration determination of various effective constituents,and main pharmacokinetic parameters were calculated.RESULTS Various effective constituents in the large dose group demonstrated prolonged t1/2,MRT0-∞ as compared with those in the conventional dose group(P＜0.05).After dose correction,Cmax of chlorogenic acid,isoquercetin,shionone in the large dose group displayed no obvious changes(P＞0.05),while Cmax of ferulic acid,isorhamnetin,and AUC0-t,AUC0-∞ of various effective constituents were higher than those in the conventional dose group(P＜0.05).CONCLUSION Various effective constituents in the high dose of Asteris Radix et Rhizoma can maintain high-concentration and long-time effects on rat bladder tissue.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

This study systematically investigated the molecular mechanisms underlying the involvement of mesoderm development-associated genes in melanoma progression through integrated bioinformatics analy-sis and experimental validation.Utilizing the GSVA(gene set variation analysis)algorithm to perform enrichment analysis of 7 752 biological functions in 406 skin cutaneous melanoma(SKCM)cases,we i-dentified for the first time the significant activation of mesoderm development pathways during SKCM pathogenesis.Four core regulatory genes(SMAD4,NODAL,BMPR1A,and ZFP36L1)were screened using LASSO-COX regression analysis and a prognostic risk-scoring system was established.Gene Ontolo-gy(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses revealed predomi-nant enrichment of these genes in mRNA metabolic processes and TGF-β signaling pathways.Experimen-tal validation through Quantitative Polymerase Chain Reaction(qPCR),Western blotting,and immuno-histochemistry(IHC)demonstrated that:(1)Downregulation of SMAD4 and BMPR1A in tumor tissues was significantly correlated with poor prognosis(P＜0.05);(2)NODAL promoted tumor invasion and metastasis by regulating epithelial-mesenchymal transition(EMT);(3)High ZFP36L1 expression was associated with enhanced chemotherapy sensitivity.Further analyses revealed significant correlations be-tween core gene expression levels and tumor immune infiltration characteristics as well as immune check-point molecules.By integrating multi-omics analysis with experimental validation,this study elucidates the critical roles of mesoderm development-associated genes in SKCM progression,particularly clarifying the molecular mechanisms through which SMAD4/NODAL/BMPR1A/ZFP36L1 influence tumor biologi-cal behaviors via immune microenvironment regulation and EMT processes.These findings provide novel theoretical foundations for molecular subtyping and targeted therapy in melanoma.

This study systematically investigated the molecular mechanisms underlying the involvement of mesoderm development-associated genes in melanoma progression through integrated bioinformatics analy-sis and experimental validation.Utilizing the GSVA(gene set variation analysis)algorithm to perform enrichment analysis of 7 752 biological functions in 406 skin cutaneous melanoma(SKCM)cases,we i-dentified for the first time the significant activation of mesoderm development pathways during SKCM pathogenesis.Four core regulatory genes(SMAD4,NODAL,BMPR1A,and ZFP36L1)were screened using LASSO-COX regression analysis and a prognostic risk-scoring system was established.Gene Ontolo-gy(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses revealed predomi-nant enrichment of these genes in mRNA metabolic processes and TGF-β signaling pathways.Experimen-tal validation through Quantitative Polymerase Chain Reaction(qPCR),Western blotting,and immuno-histochemistry(IHC)demonstrated that:(1)Downregulation of SMAD4 and BMPR1A in tumor tissues was significantly correlated with poor prognosis(P＜0.05);(2)NODAL promoted tumor invasion and metastasis by regulating epithelial-mesenchymal transition(EMT);(3)High ZFP36L1 expression was associated with enhanced chemotherapy sensitivity.Further analyses revealed significant correlations be-tween core gene expression levels and tumor immune infiltration characteristics as well as immune check-point molecules.By integrating multi-omics analysis with experimental validation,this study elucidates the critical roles of mesoderm development-associated genes in SKCM progression,particularly clarifying the molecular mechanisms through which SMAD4/NODAL/BMPR1A/ZFP36L1 influence tumor biologi-cal behaviors via immune microenvironment regulation and EMT processes.These findings provide novel theoretical foundations for molecular subtyping and targeted therapy in melanoma.

Objective:Based on outpatient and emergency visit data,this study employs a staged VaDE model to uncover the heterogeneity structure of residents'healthcare-seeking behaviors and reveal cross-district mobility patterns.Methods:Outpatient and emergency visit records of permanent residents in District A,Shanghai,in 2024 were used.Each individual visit served as the analytical unit.A staged VaDE approach was applied for nonlinear dimensionality reduction and clustering,followed by feature analysis with cross-district visit rates.Results:The proposed model outperformed K-Means and VAE+K-Means in clustering performance,identifying seven typical healthcare-seeking patterns with significant differences in cross-district rates,demographic characteristics,care structures,and disease profiles.Cluster 1 comprised elderly patients with severe conditions and high cross-district rates;Cluster 2,young and middle-aged cross-district commuters;Cluster 3,mild-case or maternity-oriented visits;Cluster 4,infrequent visits by middle-aged and elderly patients;and Clusters 5～7,local chronic disease or low-burden visits.Conclusion:The staged VaDE model demonstrates strong capability in characterizing behavioral heterogeneity and identifying key cross-district mobility types,providing evidence for refined healthcare service management and regional coordination.