The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m...The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.展开更多
BACKGROUND:Breast hyperplasia is a common benign breast disease mainly caused by endocrine disorders,manifested as abnormal hyperplasia of breast tissue.In recent years,traditional Chinese medicine compounds and probi...BACKGROUND:Breast hyperplasia is a common benign breast disease mainly caused by endocrine disorders,manifested as abnormal hyperplasia of breast tissue.In recent years,traditional Chinese medicine compounds and probiotics have shown good potential in regulating the endocrine system and improving the intestinal microecology,providing new ideas for the treatment of breast hyperplasia.OBJECTIVE:To explore the effects and mechanisms of traditional Chinese medicine compounds and fermented probiotic compounds on breast hyperplasia in mice,providing new theoretical and experimental bases for the clinical treatment and prevention of breast hyperplasia.METHODS:(1)Network pharmacology tools were used to predict the anti-breast-hyperplasia activity of Herba Gueldenstaedtiae(Euphorbia humifusa),as well as its potential targets and signaling pathways.The databases included:TCMSP,OMIM,GeneCards database,UniProt website,Venny2.1.0 website,Metascape,HERB website,and STRING database,all of which are open-access databases.Network pharmacology can predict and screen key information such as the targets corresponding to the active ingredients of traditional Chinese medicine,disease targets,and action pathways through network analysis and computer-system analysis.Therefore,it has been increasingly widely used in the research of traditional Chinese medicine.(2)A breast hyperplasia model was induced in mice by injecting estrogen and progesterone.Mice in the normal blank group were injected intraperitoneally with normal saline every day.Mice in the model group and drugadministration groups were injected intraperitoneally with estradiol benzoate injection at a concentration of 0.5 mg/kg every day for 25 days.From the 26th day,the injection of estradiol benzoate injection was stopped.Mice in the normal blank group were injected intramuscularly with normal saline every day,and mice in the model group and drug-administration groups were injected intramuscularly with progesterone injection at a concentration of 5 mg/kg for 5 days.After the model was established,each group was given drugs respectively.The normal blank group and the model group were gavaged with 0.2 mL/d of normal saline;the positive blank group(Xiaozheng Pill group)was gavaged with an aqueous solution of Xiaozheng Pill at 0.9 mg/g;the low-,medium-and high-dose groups of Compound Herba Gueldenstaedtiae were gavaged with an aqueous solution of the compound medicine at 0.75,1.5,and 3.0 mg/(g·d)respectively;the low-,medium-and high-dose groups of traditional Chinese medicine-bacteria fermentation were gavaged with an aqueous solution of the compound medicine at 0.75,1.5,and 3.0 mg/(g·d)respectively.The administration was continuous for 30 days.RESULTS AND CONCLUSION:(1)The results of network pharmacology research showed that the Compound Herba Gueldenstaedtiae(Euphorbia humifusa)contained 46 active ingredients,which were related to 1213 potential targets.After comparison with 588 known breast-hyperplasia targets,it was speculated that 50 of these targets might be related to the direct effect of the compound on breast hyperplasia.(2)After drug intervention,there was no significant change in the high-dose group of Compound Herba Gueldenstaedtiae compared with the normal blank group.The liver indicators of the other intervention groups all significantly decreased(P<0.05).(3)In terms of kidney and uterine indicators,the medium-dose group of Compound Herba Gueldenstaedtiae decreased significantly compared with the normal blank group(P<0.05).In terms of the uterine index,the model group increased significantly compared with the normal blank group(P<0.01).(4)After 1-month drug treatment,the number of lobules and acini in the breast tissue of the Xiaozheng Pill group,the low,medium,and high-dose group of Compound Herba Gueldenstaedtiae,the low,medium,and highdose groups of traditional Chinese medicine-bacteria fermentation decreased,and the duct openings narrowed.With the increase of drug dose,diffuse hyperplasia of breast tissue was significantly improved.(5)The ELISA results showed that compared with the model group,the estrogen level was lower in the medium-dose group of traditional Chinese medicine-bacteria fermentation after the intervention(P<0.05).In addition,the follicle-stimulating hormone level in the low-dose group of Compound Herba Gueldenstaedtiae was lower than that of the model group(P<0.05).(6)The intervention in the mouse model led to changes in the abundance of short chain fatty acids and intestinal flora in all groups.To conclude,the Compound Herba Gueldenstaedtiae and its probiotic fermentation products significantly improved mammary gland hyperplasia in mice by regulating hormone levels,improving the structure of the gut microbiota,and increasing the content of shortchain fatty acids,providing new ideas and potential sources of drugs for the treatment of breast hyperplasia.展开更多
The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they ...The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they exhibit dense interconnectivity(Braitenburg and Schüz,1998;Campagnola et al.,2022).The strength and probability of connectivity depend on cell type,inter-neuronal distance,and species.Still,every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons.Second,communication between neurons occurs primarily via chemical or electrical synapses.展开更多
BACKGROUND Non-suicidal self-injury(NSSI)is common among adolescents with depressive disorders and poses a major public health challenge.Rumination,a key cognitive feature of depression,includes different subtypes tha...BACKGROUND Non-suicidal self-injury(NSSI)is common among adolescents with depressive disorders and poses a major public health challenge.Rumination,a key cognitive feature of depression,includes different subtypes that may relate to NSSI through distinct psychological mechanisms.However,how these subtypes interact with specific NSSI behaviors remains unclear.AIM To examine associations between rumination subtypes and specific NSSI behaviors in adolescents.METHODS We conducted a cross-sectional study with 305 hospitalized adolescents diagnosed with depressive disorders.The subjects ranged from 12-18 years in age.Rumi-nation subtypes were assessed using the Ruminative Response Scale,and 12 NSSI behaviors were evaluated using a validated questionnaire.Network analysis was applied to explore symptom-level associations and identify central symptoms.RESULTS The network analysis revealed close connections between rumination subtypes and NSSI behaviors.Brooding was linked to behaviors such as hitting objects and burning.Scratching emerged as the most influential NSSI symptom.Symptomfocused rumination served as a key bridge connecting rumination and NSSI.CONCLUSION Symptom-focused rumination and scratching were identified as potential intervention targets.These findings highlight the psychological significance of specific cognitive-behavioral links in adolescent depression and suggest directions for tailored prevention and treatment.However,the cross-sectional,single-site design limits causal inference and generalizability.Future longitudinal and multi-center studies are needed to confirm causal pathways and verify the generalizability of the findings to broader adolescent populations.展开更多
Background:Wenqing Yin(WQY)is a classic prescription used to treat skin diseases like atopic dermatitis(AD)in China,and the aim of this study is to investigate the therapeutic effects and molecular mechanisms of WQY o...Background:Wenqing Yin(WQY)is a classic prescription used to treat skin diseases like atopic dermatitis(AD)in China,and the aim of this study is to investigate the therapeutic effects and molecular mechanisms of WQY on AD.Methods:The DNFB-induced mouse models of AD were established to investigate the therapeutic effects of WQY on AD.The symptoms of AD in the ears and backs of the mice were assessed,while inflammatory factors in the ear were quantified using quantitative real-time-polymerase chain reaction(qRT-PCR),and the percentages of CD4^(+)and CD8^(+)cells in the spleen were analyzed through flow cytometry.The compounds in WQY were identified using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)analysis and the key targets and pathways of WQY to treat AD were predicted by network pharmacology.Subsequently,the key genes were tested and verified by qRT-PCR,and the potential active components and target proteins were verified by molecular docking.Results:WQY relieved the AD symptoms and histopathological injuries in the ear and back skin of mice with AD.Meanwhile,WQY significantly reduced the levels of inflammatory factors IL-6 and IL-1βin ear tissue,as well as the ratio of CD4^(+)/CD8^(+)cells in spleen.Additionally,a total of 142 compounds were identified from the water extract of WQY by UPLC-Orbitrap-MS/MS.39 key targets related to AD were screened out by network pharmacology methods.The KEGG analysis indicated that the effects of WQY were primarily mediated through pathways associated with Toll-like receptor signaling and T cell receptor signaling.Moreover,the results of qRT-PCR demonstrated that WQY significantly reduced the mRNA expressions of IL-4,IL-10,GATA3 and FOXP3,and molecular docking simulation verified that the active components of WQY had excellent binding abilities with IL-4,IL-10,GATA3 and FOXP3 proteins.Conclusion:The present study demonstrated that WQY effectively relieved AD symptoms in mice,decreased the inflammatory factors levels,regulated the balance of CD4^(+)and CD8^(+)cells,and the mechanism may be associated with the suppression of Th2 and Treg cell immune responses.展开更多
Epilepsy is a leading cause of disability and mortality worldwide. However, despite the availability of more than 20 antiseizure medications, more than one-third of patients continue to experience seizures. Given the ...Epilepsy is a leading cause of disability and mortality worldwide. However, despite the availability of more than 20 antiseizure medications, more than one-third of patients continue to experience seizures. Given the urgent need to explore new treatment strategies for epilepsy, recent research has highlighted the potential of targeting gliosis, metabolic disturbances, and neural circuit abnormalities as therapeutic strategies. Astrocytes, the largest group of nonneuronal cells in the central nervous system, play several crucial roles in maintaining ionic and energy metabolic homeostasis in neurons, regulating neurotransmitter levels, and modulating synaptic plasticity. This article briefly reviews the critical role of astrocytes in maintaining balance within the central nervous system. Building on previous research, we discuss how astrocyte dysfunction contributes to the onset and progression of epilepsy through four key aspects: the imbalance between excitatory and inhibitory neuronal signaling, dysregulation of metabolic homeostasis in the neuronal microenvironment, neuroinflammation, and the formation of abnormal neural circuits. We summarize relevant basic research conducted over the past 5 years that has focused on modulating astrocytes as a therapeutic approach for epilepsy. We categorize the therapeutic targets proposed by these studies into four areas: restoration of the excitation–inhibition balance, reestablishment of metabolic homeostasis, modulation of immune and inflammatory responses, and reconstruction of abnormal neural circuits. These targets correspond to the pathophysiological mechanisms by which astrocytes contribute to epilepsy. Additionally, we need to consider the potential challenges and limitations of translating these identified therapeutic targets into clinical treatments. These limitations arise from interspecies differences between humans and animal models, as well as the complex comorbidities associated with epilepsy in humans. We also highlight valuable future research directions worth exploring in the treatment of epilepsy and the regulation of astrocytes, such as gene therapy and imaging strategies. The findings presented in this review may help open new therapeutic avenues for patients with drugresistant epilepsy and for those suffering from other central nervous system disorders associated with astrocytic dysfunction.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
Alkali-free SiO_(2)-Al_(2)O_(3)-CaO-MgO with different SiO_(2)/Al_(2)O_(3)mass ratios was prepared by conventional melt quenching method.The glass network structure,thermodynamic properties and elastic modulus changes...Alkali-free SiO_(2)-Al_(2)O_(3)-CaO-MgO with different SiO_(2)/Al_(2)O_(3)mass ratios was prepared by conventional melt quenching method.The glass network structure,thermodynamic properties and elastic modulus changes with SiO_(2)and Al_(2)O_(3)ratios were investigated using various techniques.It is found that when SiO_(2)is replaced by Al_(2)O_(3),the Q^(4) to Q^(3) transition of silicon-oxygen network decreases while the aluminum-oxygen network increases,which result in the transformation of Si-O-Si bonds to Si-O-Al bonds and an increase in glass network connectivity even though the intermolecular bond strength decreases.The glass transition temperature(T_(g))increases continuously,while the thermal expansion coefficient increases and high-temperature viscosity first decreases and then increases.Meanwhile,the elastic modulus values increase from 93 to 102 GPa.This indicates that the elastic modulus is mainly affected by packing factor and dissociation energy,and elements with higher packing factors and dissociation energies supplant those with lower values,resulting in increased rigidity within the glass.展开更多
Aqueous alkali metal-ion batteries(AAMIBs)have been recognized as emerging electrochemical energy storage technologies for grid-scale applications owning to their intrinsic safety,cost-effectiveness,and environmental ...Aqueous alkali metal-ion batteries(AAMIBs)have been recognized as emerging electrochemical energy storage technologies for grid-scale applications owning to their intrinsic safety,cost-effectiveness,and environmental sustainability.However,the practical application of AAMIBs is still severely constrained by the tendency of aqueous electrolytes to freeze at low temperatures and decompose at high temperatures,limiting their operational temperature range.Considering the urgent need for energy systems with higher adaptability and resilience at various application scenarios,designing novel electrolytes via structure modulation has increasingly emerged as a feasible and economical strategy for the performance optimization of wide-temperature AAMIBs.In this review,the latest advancement of wide-temperature electrolytes for AAMIBs is systematically and comprehensively summarized.Specifically,the key challenges,failure mechanisms,correlations between hydrogen bond behaviors and physicochemical properties,and thermodynamic and kinetic interpretations in aqueous electrolytes are discussed firstly.Additionally,we offer forward-looking insights and innovative design principles for developing aqueous electrolytes capable of operating across a broad temperature range.This review is expected to provide some guidance and reference for the rational design and regulation of widetemperature electrolytes for AAMIBs and promote their future development.展开更多
Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-...Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.展开更多
The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities...The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.展开更多
An image processing and deep learning method for identifying different types of rock images was proposed.Preprocessing,such as rock image acquisition,gray scaling,Gaussian blurring,and feature dimensionality reduction...An image processing and deep learning method for identifying different types of rock images was proposed.Preprocessing,such as rock image acquisition,gray scaling,Gaussian blurring,and feature dimensionality reduction,was conducted to extract useful feature information and recognize and classify rock images using Tensor Flow-based convolutional neural network(CNN)and Py Qt5.A rock image dataset was established and separated into workouts,confirmation sets,and test sets.The framework was subsequently compiled and trained.The categorization approach was evaluated using image data from the validation and test datasets,and key metrics,such as accuracy,precision,and recall,were analyzed.Finally,the classification model conducted a probabilistic analysis of the measured data to determine the equivalent lithological type for each image.The experimental results indicated that the method combining deep learning,Tensor Flow-based CNN,and Py Qt5 to recognize and classify rock images has an accuracy rate of up to 98.8%,and can be successfully utilized for rock image recognition.The system can be extended to geological exploration,mine engineering,and other rock and mineral resource development to more efficiently and accurately recognize rock samples.Moreover,it can match them with the intelligent support design system to effectively improve the reliability and economy of the support scheme.The system can serve as a reference for supporting the design of other mining and underground space projects.展开更多
The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. Th...The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. The brain is made up of a complex network of different cell types that work in tandem to maintain systemic homeostasis.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
We read with great interest the study by Zhang et al on Yiyi Fuzi Baijiang powder(YFB),which exemplifies the power of modern methods to validate traditional Chinese medicine(TCM).The key insight is that YFB doesn’t m...We read with great interest the study by Zhang et al on Yiyi Fuzi Baijiang powder(YFB),which exemplifies the power of modern methods to validate traditional Chinese medicine(TCM).The key insight is that YFB doesn’t merely alter“good”or“bad”bacteria but restores the gut microbiota’s holistic equilibrium.This is powerfully shown by its paradoxical reduction of anaerobic probiotics like Bifidobacterium,rectifying the diseased,hypoxic environment,causing their aberrant overgrowth.This challenges the conventional probiotic paradigm and underscores a core TCM principle:Herbal formulas treat disease by restoring the body’s overall functional balance.Future research should focus on the interplay between herbal components,intestinal oxygen,and microbial metabolites to further unravel this sophisticated dialogue.展开更多
Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indice...Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.展开更多
基金National Natural Science Foundation of China(52175237)。
文摘The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.
文摘BACKGROUND:Breast hyperplasia is a common benign breast disease mainly caused by endocrine disorders,manifested as abnormal hyperplasia of breast tissue.In recent years,traditional Chinese medicine compounds and probiotics have shown good potential in regulating the endocrine system and improving the intestinal microecology,providing new ideas for the treatment of breast hyperplasia.OBJECTIVE:To explore the effects and mechanisms of traditional Chinese medicine compounds and fermented probiotic compounds on breast hyperplasia in mice,providing new theoretical and experimental bases for the clinical treatment and prevention of breast hyperplasia.METHODS:(1)Network pharmacology tools were used to predict the anti-breast-hyperplasia activity of Herba Gueldenstaedtiae(Euphorbia humifusa),as well as its potential targets and signaling pathways.The databases included:TCMSP,OMIM,GeneCards database,UniProt website,Venny2.1.0 website,Metascape,HERB website,and STRING database,all of which are open-access databases.Network pharmacology can predict and screen key information such as the targets corresponding to the active ingredients of traditional Chinese medicine,disease targets,and action pathways through network analysis and computer-system analysis.Therefore,it has been increasingly widely used in the research of traditional Chinese medicine.(2)A breast hyperplasia model was induced in mice by injecting estrogen and progesterone.Mice in the normal blank group were injected intraperitoneally with normal saline every day.Mice in the model group and drugadministration groups were injected intraperitoneally with estradiol benzoate injection at a concentration of 0.5 mg/kg every day for 25 days.From the 26th day,the injection of estradiol benzoate injection was stopped.Mice in the normal blank group were injected intramuscularly with normal saline every day,and mice in the model group and drug-administration groups were injected intramuscularly with progesterone injection at a concentration of 5 mg/kg for 5 days.After the model was established,each group was given drugs respectively.The normal blank group and the model group were gavaged with 0.2 mL/d of normal saline;the positive blank group(Xiaozheng Pill group)was gavaged with an aqueous solution of Xiaozheng Pill at 0.9 mg/g;the low-,medium-and high-dose groups of Compound Herba Gueldenstaedtiae were gavaged with an aqueous solution of the compound medicine at 0.75,1.5,and 3.0 mg/(g·d)respectively;the low-,medium-and high-dose groups of traditional Chinese medicine-bacteria fermentation were gavaged with an aqueous solution of the compound medicine at 0.75,1.5,and 3.0 mg/(g·d)respectively.The administration was continuous for 30 days.RESULTS AND CONCLUSION:(1)The results of network pharmacology research showed that the Compound Herba Gueldenstaedtiae(Euphorbia humifusa)contained 46 active ingredients,which were related to 1213 potential targets.After comparison with 588 known breast-hyperplasia targets,it was speculated that 50 of these targets might be related to the direct effect of the compound on breast hyperplasia.(2)After drug intervention,there was no significant change in the high-dose group of Compound Herba Gueldenstaedtiae compared with the normal blank group.The liver indicators of the other intervention groups all significantly decreased(P<0.05).(3)In terms of kidney and uterine indicators,the medium-dose group of Compound Herba Gueldenstaedtiae decreased significantly compared with the normal blank group(P<0.05).In terms of the uterine index,the model group increased significantly compared with the normal blank group(P<0.01).(4)After 1-month drug treatment,the number of lobules and acini in the breast tissue of the Xiaozheng Pill group,the low,medium,and high-dose group of Compound Herba Gueldenstaedtiae,the low,medium,and highdose groups of traditional Chinese medicine-bacteria fermentation decreased,and the duct openings narrowed.With the increase of drug dose,diffuse hyperplasia of breast tissue was significantly improved.(5)The ELISA results showed that compared with the model group,the estrogen level was lower in the medium-dose group of traditional Chinese medicine-bacteria fermentation after the intervention(P<0.05).In addition,the follicle-stimulating hormone level in the low-dose group of Compound Herba Gueldenstaedtiae was lower than that of the model group(P<0.05).(6)The intervention in the mouse model led to changes in the abundance of short chain fatty acids and intestinal flora in all groups.To conclude,the Compound Herba Gueldenstaedtiae and its probiotic fermentation products significantly improved mammary gland hyperplasia in mice by regulating hormone levels,improving the structure of the gut microbiota,and increasing the content of shortchain fatty acids,providing new ideas and potential sources of drugs for the treatment of breast hyperplasia.
基金supported in part by the Rosetrees Trust(#CF-2023-I-2_113)by the Israel Ministry of Innovation,Science,and Technology(#7393)(to ES).
文摘The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they exhibit dense interconnectivity(Braitenburg and Schüz,1998;Campagnola et al.,2022).The strength and probability of connectivity depend on cell type,inter-neuronal distance,and species.Still,every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons.Second,communication between neurons occurs primarily via chemical or electrical synapses.
基金Supported by Key Research and Development Program of Shaanxi Province,China,No.2024SF-YBXM-078.
文摘BACKGROUND Non-suicidal self-injury(NSSI)is common among adolescents with depressive disorders and poses a major public health challenge.Rumination,a key cognitive feature of depression,includes different subtypes that may relate to NSSI through distinct psychological mechanisms.However,how these subtypes interact with specific NSSI behaviors remains unclear.AIM To examine associations between rumination subtypes and specific NSSI behaviors in adolescents.METHODS We conducted a cross-sectional study with 305 hospitalized adolescents diagnosed with depressive disorders.The subjects ranged from 12-18 years in age.Rumi-nation subtypes were assessed using the Ruminative Response Scale,and 12 NSSI behaviors were evaluated using a validated questionnaire.Network analysis was applied to explore symptom-level associations and identify central symptoms.RESULTS The network analysis revealed close connections between rumination subtypes and NSSI behaviors.Brooding was linked to behaviors such as hitting objects and burning.Scratching emerged as the most influential NSSI symptom.Symptomfocused rumination served as a key bridge connecting rumination and NSSI.CONCLUSION Symptom-focused rumination and scratching were identified as potential intervention targets.These findings highlight the psychological significance of specific cognitive-behavioral links in adolescent depression and suggest directions for tailored prevention and treatment.However,the cross-sectional,single-site design limits causal inference and generalizability.Future longitudinal and multi-center studies are needed to confirm causal pathways and verify the generalizability of the findings to broader adolescent populations.
基金supported by grants from the National Natural Science Foundation of China(82004252)the Project of Administration of Traditional Chinese Medicine of Guangdong Province(202405112017596500)the Basic and Applied Basic Research Foundation of Guangzhou Municipal Science and Technology Bureau(202102020533).
文摘Background:Wenqing Yin(WQY)is a classic prescription used to treat skin diseases like atopic dermatitis(AD)in China,and the aim of this study is to investigate the therapeutic effects and molecular mechanisms of WQY on AD.Methods:The DNFB-induced mouse models of AD were established to investigate the therapeutic effects of WQY on AD.The symptoms of AD in the ears and backs of the mice were assessed,while inflammatory factors in the ear were quantified using quantitative real-time-polymerase chain reaction(qRT-PCR),and the percentages of CD4^(+)and CD8^(+)cells in the spleen were analyzed through flow cytometry.The compounds in WQY were identified using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)analysis and the key targets and pathways of WQY to treat AD were predicted by network pharmacology.Subsequently,the key genes were tested and verified by qRT-PCR,and the potential active components and target proteins were verified by molecular docking.Results:WQY relieved the AD symptoms and histopathological injuries in the ear and back skin of mice with AD.Meanwhile,WQY significantly reduced the levels of inflammatory factors IL-6 and IL-1βin ear tissue,as well as the ratio of CD4^(+)/CD8^(+)cells in spleen.Additionally,a total of 142 compounds were identified from the water extract of WQY by UPLC-Orbitrap-MS/MS.39 key targets related to AD were screened out by network pharmacology methods.The KEGG analysis indicated that the effects of WQY were primarily mediated through pathways associated with Toll-like receptor signaling and T cell receptor signaling.Moreover,the results of qRT-PCR demonstrated that WQY significantly reduced the mRNA expressions of IL-4,IL-10,GATA3 and FOXP3,and molecular docking simulation verified that the active components of WQY had excellent binding abilities with IL-4,IL-10,GATA3 and FOXP3 proteins.Conclusion:The present study demonstrated that WQY effectively relieved AD symptoms in mice,decreased the inflammatory factors levels,regulated the balance of CD4^(+)and CD8^(+)cells,and the mechanism may be associated with the suppression of Th2 and Treg cell immune responses.
基金supported by the National Key Research and Development Program of China,No. 2023YFF0714200 (to CW)the National Natural Science Foundation of China,Nos. 82472038 and 82202224 (both to CW)+3 种基金the Shanghai Rising-Star Program,No. 23QA1407700 (to CW)the Construction Project of Shanghai Key Laboratory of Molecular Imaging,No. 18DZ2260400 (to CW)the National Science Foundation for Distinguished Young Scholars,No. 82025019 (to CL)the Greater Bay Area Institute of Precision Medicine (Guangzhou)(to CW)。
文摘Epilepsy is a leading cause of disability and mortality worldwide. However, despite the availability of more than 20 antiseizure medications, more than one-third of patients continue to experience seizures. Given the urgent need to explore new treatment strategies for epilepsy, recent research has highlighted the potential of targeting gliosis, metabolic disturbances, and neural circuit abnormalities as therapeutic strategies. Astrocytes, the largest group of nonneuronal cells in the central nervous system, play several crucial roles in maintaining ionic and energy metabolic homeostasis in neurons, regulating neurotransmitter levels, and modulating synaptic plasticity. This article briefly reviews the critical role of astrocytes in maintaining balance within the central nervous system. Building on previous research, we discuss how astrocyte dysfunction contributes to the onset and progression of epilepsy through four key aspects: the imbalance between excitatory and inhibitory neuronal signaling, dysregulation of metabolic homeostasis in the neuronal microenvironment, neuroinflammation, and the formation of abnormal neural circuits. We summarize relevant basic research conducted over the past 5 years that has focused on modulating astrocytes as a therapeutic approach for epilepsy. We categorize the therapeutic targets proposed by these studies into four areas: restoration of the excitation–inhibition balance, reestablishment of metabolic homeostasis, modulation of immune and inflammatory responses, and reconstruction of abnormal neural circuits. These targets correspond to the pathophysiological mechanisms by which astrocytes contribute to epilepsy. Additionally, we need to consider the potential challenges and limitations of translating these identified therapeutic targets into clinical treatments. These limitations arise from interspecies differences between humans and animal models, as well as the complex comorbidities associated with epilepsy in humans. We also highlight valuable future research directions worth exploring in the treatment of epilepsy and the regulation of astrocytes, such as gene therapy and imaging strategies. The findings presented in this review may help open new therapeutic avenues for patients with drugresistant epilepsy and for those suffering from other central nervous system disorders associated with astrocytic dysfunction.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金Supported by the National Key Research Program(No.2024-1129-954-112)National Natural Science Foundation of China(No.52372033)Guangxi Science and Technology Major Program(No.AA24263054)。
文摘Alkali-free SiO_(2)-Al_(2)O_(3)-CaO-MgO with different SiO_(2)/Al_(2)O_(3)mass ratios was prepared by conventional melt quenching method.The glass network structure,thermodynamic properties and elastic modulus changes with SiO_(2)and Al_(2)O_(3)ratios were investigated using various techniques.It is found that when SiO_(2)is replaced by Al_(2)O_(3),the Q^(4) to Q^(3) transition of silicon-oxygen network decreases while the aluminum-oxygen network increases,which result in the transformation of Si-O-Si bonds to Si-O-Al bonds and an increase in glass network connectivity even though the intermolecular bond strength decreases.The glass transition temperature(T_(g))increases continuously,while the thermal expansion coefficient increases and high-temperature viscosity first decreases and then increases.Meanwhile,the elastic modulus values increase from 93 to 102 GPa.This indicates that the elastic modulus is mainly affected by packing factor and dissociation energy,and elements with higher packing factors and dissociation energies supplant those with lower values,resulting in increased rigidity within the glass.
基金supported by the National Natural Science Foundation of China(52002297)National Key R&D Program of China(2022VFB2404800)+1 种基金Wuhan Yellow Crane Talents Program,China Postdoctoral Science Foundation(No.2024M752495)the Postdoctoral Fellowship Program of CPSF(No.GZB20230552).
文摘Aqueous alkali metal-ion batteries(AAMIBs)have been recognized as emerging electrochemical energy storage technologies for grid-scale applications owning to their intrinsic safety,cost-effectiveness,and environmental sustainability.However,the practical application of AAMIBs is still severely constrained by the tendency of aqueous electrolytes to freeze at low temperatures and decompose at high temperatures,limiting their operational temperature range.Considering the urgent need for energy systems with higher adaptability and resilience at various application scenarios,designing novel electrolytes via structure modulation has increasingly emerged as a feasible and economical strategy for the performance optimization of wide-temperature AAMIBs.In this review,the latest advancement of wide-temperature electrolytes for AAMIBs is systematically and comprehensively summarized.Specifically,the key challenges,failure mechanisms,correlations between hydrogen bond behaviors and physicochemical properties,and thermodynamic and kinetic interpretations in aqueous electrolytes are discussed firstly.Additionally,we offer forward-looking insights and innovative design principles for developing aqueous electrolytes capable of operating across a broad temperature range.This review is expected to provide some guidance and reference for the rational design and regulation of widetemperature electrolytes for AAMIBs and promote their future development.
基金supported by the Natural Science Foundation of Hubei Provincial Department of Education(D20232101)Shandong Second Medical University 2024 Affiliated Hospital(Teaching Hospital)Scientific Research Development Fund Project(2024FYQ026)+3 种基金the innovative Research Programme of Xiangyang No.1 People’s Hospital(XYY2023ZY01)Faculty Development Grants of Xiangyang No.1 People’s Hospital Affiliated to Hubei University of Medicine(XYY2023D05)Joint supported by Hubei Provincial Natural Science Foundation and Xiangyang of China(2025AFD091)Traditional Chinese Medicine Scientific Research Project of Hubei Provincial Administration of Traditional Chinese Medicine(ZY2025D019).
文摘Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.
文摘The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.
基金financially supported by the National Science and Technology Major Project——Deep Earth Probe and Mineral Resources Exploration(No.2024ZD1003701)the National Key R&D Program of China(No.2022YFC2905004)。
文摘An image processing and deep learning method for identifying different types of rock images was proposed.Preprocessing,such as rock image acquisition,gray scaling,Gaussian blurring,and feature dimensionality reduction,was conducted to extract useful feature information and recognize and classify rock images using Tensor Flow-based convolutional neural network(CNN)and Py Qt5.A rock image dataset was established and separated into workouts,confirmation sets,and test sets.The framework was subsequently compiled and trained.The categorization approach was evaluated using image data from the validation and test datasets,and key metrics,such as accuracy,precision,and recall,were analyzed.Finally,the classification model conducted a probabilistic analysis of the measured data to determine the equivalent lithological type for each image.The experimental results indicated that the method combining deep learning,Tensor Flow-based CNN,and Py Qt5 to recognize and classify rock images has an accuracy rate of up to 98.8%,and can be successfully utilized for rock image recognition.The system can be extended to geological exploration,mine engineering,and other rock and mineral resource development to more efficiently and accurately recognize rock samples.Moreover,it can match them with the intelligent support design system to effectively improve the reliability and economy of the support scheme.The system can serve as a reference for supporting the design of other mining and underground space projects.
文摘The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. The brain is made up of a complex network of different cell types that work in tandem to maintain systemic homeostasis.
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.
文摘We read with great interest the study by Zhang et al on Yiyi Fuzi Baijiang powder(YFB),which exemplifies the power of modern methods to validate traditional Chinese medicine(TCM).The key insight is that YFB doesn’t merely alter“good”or“bad”bacteria but restores the gut microbiota’s holistic equilibrium.This is powerfully shown by its paradoxical reduction of anaerobic probiotics like Bifidobacterium,rectifying the diseased,hypoxic environment,causing their aberrant overgrowth.This challenges the conventional probiotic paradigm and underscores a core TCM principle:Herbal formulas treat disease by restoring the body’s overall functional balance.Future research should focus on the interplay between herbal components,intestinal oxygen,and microbial metabolites to further unravel this sophisticated dialogue.
基金supported by the National Natural Science Foundation of China,No.82071909(to GF)the Natural Science Foundation of Liaoning Province,No.2023-MS-07(to HL)。
文摘Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.
文摘现有的基于卷积神经网络(convolutional neural network,CNN)的环路滤波器倾向于将多个网络应用于不同的量化参数(quantization parameter,QP),消耗训练模型中的大量资源,并增加内存负担。针对这一问题,提出一种基于CNN的QP自适应环路滤波器。首先,设计一个轻量级分类网络,按照滤波难易程度将编码树单元(coding tree unit,CTU)划分为难、中、易3类;然后,构建3个融合了特征信息增强融合模块的基于CNN的滤波网络,以满足不同QP下的3类CTU滤波需求。将所提出的环路滤波器集成到多功能视频编码(versatile video coding,VVC)标准H.266/VVC的测试软件VTM 6.0中,替换原有的去块效应滤波器(deblocking filter,DBF)、样本自适应偏移(sample adaptive offset,SAO)滤波器和自适应环路滤波器。实验结果表明,该方法平均降低了3.14%的比特率差值(Bjøntegaard delta bit rate,BD-BR),与其他基于CNN的环路滤波器相比,显著提高了压缩效率,并减少了压缩伪影。
