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Amyotrophic lateral sclerosis as a fatal neurodegenerative disease currently lacks effective therapeutic agents. Thus, finding new therapeutic targets to drive disease treatment is necessary. In this study, we utilized brain and plasma proteins as genetic instruments obtained from genome-wide association studies to conduct a Mendelian randomization analysis to identify potential drug targets for amyotrophic lateral sclerosis. Additionally, we validated our results externally using other datasets. We also used Bayesian co-localization analysis and phenotype scanning. Furthermore, we constructed a protein-protein interaction network to elucidate potential correlations between the identified proteins and existing targets. Mendelian randomization analysis indicated that elevated levels of ANO5 (OR = 1.30; 95 % CI, 1.14-1.49; P = 1.52E-04), SCFD1 (OR = 3.82; 95 % CI, 2.39-6.10; P = 2.19E-08), and SIGLEC9 (OR = 1.05; 95% CI, 1.03-1.07; P = 4.71E-05) are associated with an increased risk of amyotrophic lateral sclerosis, with external validation supporting these findings. Co-localization analysis confirmed that ANO5, SCFD1, and SIGLEC9 (coloc.abf-PPH4 = 0.848, 0.984, and 0.945, respectively) shared the same variant with amyotrophic lateral sclerosis, further substantiating potential role of these proteins as a therapeutic target. There are interactive relationships between the potential proteins and existing targets of amyotrophic lateral sclerosis. Our findings suggested that elevated levels of ANO5, SCFD1, and SIGLEC9 are connected with an increased risk of amyotrophic lateral sclerosis and might be promising therapeutic targets. However, further exploration is necessary to fully understand the underlying mechanisms involved.

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BACKGROUND: With the rapid advancement of deep learning network technology, the application of facial recognition technology in the medical field has received increasing attention. OBJECTIVE: This study aims to systematically review the literature of the past decade on facial recognition technology based on deep learning networks in the diagnosis of rare dysmorphic diseases and facial paralysis, among other conditions, to determine the effectiveness and applicability of this technology in disease identification. METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for literature search and retrieved relevant literature from multiple databases, including PubMed, on 31 December 2023. The search keywords included deep learning convolutional neural networks, facial recognition, and disease recognition. A total of 208 articles on facial recognition technology based on deep learning networks in disease diagnosis over the past 10 years were screened, and 22 articles were selected for analysis. The meta-analysis was conducted using Stata 14.0 software. RESULTS: The study collected 22 articles with a total sample size of 57 539 cases, of which 43 301 were samples with various diseases. The meta-analysis results indicated that the accuracy of deep learning in facial recognition for disease diagnosis was 91.0% [95% CI (87.0%, 95.0%)]. CONCLUSION: The study results suggested that facial recognition technology based on deep learning networks has high accuracy in disease diagnosis, providing a reference for further development and application of this technology.

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OBJECTIVE: To explore the potential mechanism of lysionotin in treating glioma. METHODS: First, target prediction based on Bernoulli Naïve Bayes profiling and pathway enrichment was used to predict the biological activity of lysionotin. The binding between 5-lipoxygenase (5-LO) and lysionotin was detected by surface plasmon resonance (SPR) and molecular docking, and the inhibitory effects of lysionotin on 5-LO and proliferation of glioma were determined using enzyme inhibition assay in vitro and cell viability analysis, respectively. Furthermore, the pharmaceutical effect of lysionotin was explored by cell survival rate analysis and liquid chromatography with tandem mass spectrometry (LC-MS/MS). The protein expression, intracellular calcium ion concentration and cytoskeleton detection were revealed by Western blot, flow cytometry and fluorescence labeling, respectively. RESULTS: Target prediction and pathway enrichment revealed that lysionotin inhibited 5-LO, a key enzyme involved in the arachidonic acid metabolism pathway, to inhibit the proliferation of glioma. Molecular docking results demonstrated that 5-LO can be binding to lysionotin through hydrogen bonds, forming bonds with His600, Gln557, Asn554, and His372. SPR analysis further confirmed the interaction between 5-LO and lysionotin. Furthermore, enzyme inhibition assay in vitro and cell survival rate analysis revealed that 50% inhibition concentration of lysionotin and the median effective concentration of lysionotin were 90 and 16.58 µmol/L, respectively, and the results of LC-MS/MS showed that lysionotin inhibited the production of 5S-hydroperoxy-eicosatetraenoic acid (P<0.05), and moreover, the LC-MS/MS results indicated that lysionotin can enter glioma cells well (P<0.01) and inhibit their proliferation. Western blot analysis demonstrated that lysionotin can inhibit the expression of 5-LO (P<0.05) and downstream leukotriene B4 receptor (P<0.01). In addition, the results showed that lysionotin affected intracellular calcium ion concentration by inhibiting 5-LO to affect the cytoskeleton, as determined by flow cytometry and fluorescence labeling. CONCLUSION: Lysionotin binds to 5-LO could suppress glioma by inhibiting arachiodonic acid metabolism pathway.

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BACKGROUND: The challenges posed by an aging society are increasingly recognized, particularly regarding the potential impacts of high-fat diets and the trend toward younger ages of disease onset. The purpose of this study was to clarify the relationships between the prevalence of stroke in the general US population and PhenoAge (PA) and PhenoAgeAccel (PAA). METHODS: Key methods included a correlation heatmap to explore linear relationships between some of the variables and weighted multivariable logistic regression to assess associations between PA, PAA, and stroke. Restricted cubic spline (RCS) analysis was used to investigate nonlinear relationships and dose-response effects. The ability of the PAA to predict stroke risk was assessed by a nomogram model and a receiver operating characteristic curve. RESULTS: After adjusting for confounding variables, both continuous and categorical PA and PAA were significantly associated with stroke prevalence. RCS analysis revealed a significant nonlinear relationship between PA and stroke prevalence. Further subgroup RCS analysis indicated that maintaining PA below 31.6 could provide greater benefits across all races and genders, specifically for individuals aged 40-80 years and those who are overweight or obese. CONCLUSION: This study highlights the importance of stroke prevention in overweight and obese populations. Monitoring intermediary factors such as high-density lipoprotein cholesterol and waist circumference may reduce stroke risk. Additionally, PA and PAA may serve as novel markers for stroke, offering new directions for health management in an aging society.

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Correlations between dietary factors and amyotrophic lateral sclerosis (ALS) have been found in previous observational studies. However, no further studies have used Mendelian randomization to further explore the causal relationship between dietary factors and ALS. Clarifying these relationships is a crucial part of developing nutritional recommendations for ALS prevention. The exposure and outcome datasets employed in this study were extracted from the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/). The exposure datasets involved in our Mendelian analyses consisted of meat intake (processed meat intake, poultry intake, beef intake, pork intake, non-oily fish intake, and oily fish intake), staple foods intake (bread intake and cereal intake), vegetable intake (cooked vegetable intake, salad/raw vegetable intake), fruit intake (fresh fruit intake and dried fruit intake), and beverage intake (coffee intake and tea intake). The weighted median, MR-Egger, Inverse Variance Weighted, Simple mode and Weighted mode methods were all utilized. And we applied Inverse Variance Weighted method as the main judgement criterion for Mendelian randomization analysis. Heterogeneity and pleiotropy analyses were conducted to confirm the validity of the outcomes. Genetically predicted that oily fish intake (OR: 0.7648; 95% CI: 0.5905-0.9904; P = .0420), coffee intake (OR: 0.7385; 95% CI: 0.5660-0.9637; P = .0256), and fresh fruit intake (OR: 0.6165; 95% CI: 0.4007-0.9487; P = .0278) were causally associated with a decreased risk of ALS. Negative results (P > .05) were received for all other dietary factors. This study found that oily fish intake, coffee intake and fresh fruit intake reduced the risk of developing ALS. Additionally, other factors were not associated with ALS.

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Introduction: Insomnia, a common clinical disorder, significantly impacts the physical and mental well-being of patients. Currently, available hypnotic medications are unsatisfactory due to adverse reactions and dependency, necessitating the identification of new drug targets for the treatment of insomnia. Methods: In this study, we utilized 734 plasma proteins as genetic instruments obtained from genome-wide association studies to conduct a Mendelian randomization analysis, with insomnia as the outcome variable, to identify potential drug targets for insomnia. Additionally, we validated our results externally using other datasets. Sensitivity analyses entailed reverse Mendelian randomization analysis, Bayesian co-localization analysis, and phenotype scanning. Furthermore, we constructed a protein-protein interaction network to elucidate potential correlations between the identified proteins and existing targets. Results: Mendelian randomization analysis indicated that elevated levels of TGFBI (OR = 1.01; 95% CI, 1.01-1.02) and PAM ((OR = 1.01; 95% CI, 1.01-1.02) in plasma are associated with an increased risk of insomnia, with external validation supporting these findings. Moreover, there was no evidence of reverse causality for these two proteins. Co-localization analysis confirmed that PAM (coloc.abf-PPH4 = 0.823) shared the same variant with insomnia, further substantiating its potential role as a therapeutic target. There are interactive relationships between the potential proteins and existing targets of insomnia. Conclusion: Overall, our findings suggested that elevated plasma levels of TGFBI and PAM are connected with an increased risk of insomnia and might be promising therapeutic targets, particularly PAM. However, further exploration is necessary to fully understand the underlying mechanisms involved.

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Background: Extensive observational evidence suggests an association between psychiatric disorders (PDs) and obstructive sleep apnea (OSA), but their causal relationship remains unexplored. The objective of this study was to examine the causal relationship between PDs and OSA. Methods: Mendelian randomization (MR) analysis was conducted with summary genetic data from the FinnGen and Psychiatric Genomics Consortium (PGC). Inverse-variance weighted (IVW), MR-Egger, weighted median, and weighted mode methods were employed to ascertain causal influence. Sensitivity analysis employing various methodologies assessed the robustness of the findings. Furthermore, multivariable Mendelian randomization (MVMR) was used to clarify if the exposures independently caused OSA. Results: MR analysis showed that genetically determined major depressive disorder (MDD) increased the risk of OSA (IVW odds ratio [OR]: 1.377, 95% confidence interval [CI]: 1.242-1.526, P = 1.05×10-9). Sensitivity analysis showed no evidence of pleiotropy and heterogeneity. In MVMR, the significant association persisted after adjusting for BMI, smoking, and alcohol consumption. No conclusive evidence indicated the causal impact of other psychological characteristics on OSA. In the reverse MR analyses, there was no causal effect of OSA on PDs. Conclusion: This study suggests a causal effect of MDD on OSA risk. Further research is needed to confirm these findings and understand how MDD contributes to OSA development, potentially aiding in reducing OSA incidence.

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Objective: Migraine is a common neurological disorder, which resulting in significant societal and personal burdens. Acupuncture has attracted widespread attention in migraine prophylaxis and treatment in recent years. Although some studies have confirmed the effectiveness of acupuncture therapy in treating migraines, there is still a lack of comprehensive evaluation regarding the comparison between different types of migraines and various acupuncture therapies. Furthermore, certain special acupuncture methods have not received sufficient attention and research. Therefore, the objective of this study is to summarize and expand upon previous research, update existing evidence, and compare the efficacy of different acupuncture therapies for migraine. We aim to provide stronger evidence-based support for clinical practice through this study, thereby promoting wider application of acupuncture therapy in migraine treatment. Methods: A exhaustive and methodical search was conducted across the nine databases: PubMed, EMBASE, Web of Science, Scopus, the Cochrane Library, CBM, CNKI, WANFANG and VIP Data. The Visual Analog Scale (VAS) scores, migraine attack frequency, duration, days of attack and adverse effects were observation indicators. Results: This study included 34 studies involving a total of 3365 migraineurs. The results of the study demonstrated that acupuncture therapy reduced VAS scores of migraine patients better compared to medication (MD=-1.29, 95% CI=[-1.67,-0.92]) and exhibited greater efficacy in reducing the frequency of migraine attacks (MD=-1.95, 95% CI=[-3.06,-0.85]), the duration of attacks (MD=- 3.29, 95% CI=[-4.65,-1.93]), and days of attack (MD=-1.02, 95% CI=[-1.58,-0.47]). Significant heterogeneity suggested that different acupuncture therapies had varying effects, and that the efficacy of the same therapy may also vary in different migraine types. In the context of network meta-analysis, the SUCRA of acupuncture therapies for reducing VAS scores was ranked as special acupuncture method (98.3%), acupuncture plus medicine (71.9%), and acupuncture (54.5%). Blood-letting and cupping was the most effective treatment for lowering the frequency of migraine attacks. The most effective treatment for shortening the duration of migraine was acupuncture plus medication (81.2%). When it comes to decreasing the days of migraine, acupuncture (80.3%) came out on top. 14 studies reported the occurrence of adverse effects, of which 4 studies had no adverse effects in the test group. Conclusion: Initial findings indicate that acupuncture-related therapy exhibits superior effectiveness in the treatment of migraine and clinical decision-making should be patient-specific.

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Background: Previous observational studies have provided cumulative data linking gut microbiota to myasthenia gravis (MG). However, the causal link between the two remains unexplored. Hence, the current study was performed to explore the causal link between them. Methods: Mendelian randomization (MR) analysis was conducted using the summary statistics of 211 gut microbiota taxa and the largest genome-wide association studies (GWAS) for MG currently available. The inverse variance-weighted (IVW), MR-Egger, weighted median, and weighted mode methods were employed to ascertain the causal influence. Sensitivity studies utilizing several methodologies were then used to assess the robustness of the findings. Lastly, to evaluate reverse causality, a reverse MR analysis was performed. Results: Seven suggestive causal associations between the gastrointestinal microbiota and MG were identified based on the outcomes of the MR analysis. Specifically, phylum Actinobacteria (OR: 0.602, 95% CI: 0.405-0.896, p = 0.012), class Gammaproteobacteria (OR: 0.587, 95% CI: 0.357-0.968, p = 0.037), and families Defluviitaleaceae (OR: 0.695, 95% CI: 0.485-0.996, p = 0.047), Family XIII (OR: 0.614, 95% CI: 0.412-0.916, p = 0.017), and Peptococcaceae (OR: 0.698, 95% CI: 0.505-0.964, p = 0.029) had suggestive protective effects on MG, while order Mollicutes RF9 (OR: 1.424, 95% CI: 1.015-1.998, p = 0.041) and genus Faecalibacterium (OR: 1.763, 95% CI: 1.220-2.547, p = 0.003) were suggestive risk factors for MG. The outcomes indicate that neither heterogeneity nor horizontal pleiotropy had any discernible impact. Nevertheless, this reverse analysis did not reveal any apparent effect of MG on the gut microbiota composition. Conclusion: The MR investigation has substantiated the suggestive causal connection between gut microbiota and MG, which may provide helpful insights for innovative therapeutic and preventative approaches for MG. Further randomized controlled trials are needed to elucidate the gut microbiota's precise role and therapeutic potential in the pathogenesis of MG.

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This study aims to identify common molecular biomarkers between amyotrophic lateral sclerosis (ALS) and depression using bioinformatics methods, in order to provide potential targets and new ideas and methods for the diagnosis and treatment of these diseases. Microarray datasets GSE139384, GSE35978 and GSE87610 were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) between ALS and depression were identified. After screening for overlapping DEGs, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Furthermore, a protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software, and hub genes were identified. Finally, a network between miRNAs and hub genes was constructed using the NetworkAnalyst tool, and possible key miRNAs were predicted. A total of 357 genes have been identified as common DEGs between ALS and depression. GO and KEGG enrichment analyses of the 357 DEGs showed that they were mainly involved in cytoplasmic translation. Further analysis of the PPI network using Cytoscape and MCODE plugins identified 6 hub genes, including mitochondrial ribosomal protein S12 (MRPS12), poly(rC) binding protein 1 (PARP1), SNRNP200, PCBP1, small G protein signaling modulator 1 (SGSM1), and DNA methyltransferase 1 (DNMT1). Five possible target miRNAs, including miR-221-5p, miR-21-5p, miR-100-5p, miR-30b-5p, and miR-615-3p, were predicted by constructing a miRNA-gene network. This study used bioinformatics techniques to explore the potential association between ALS and depression, and identified potential biomarkers. These biomarkers may provide new ideas and methods for the early diagnosis, treatment, and monitoring of ALS and depression.

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We aimed to identify the molecular biomarkers of MDD disease progression to uncover potential mechanisms of major depressive disorder (MDD). In this study, three microarray data sets, GSE44593, GSE12654, and GSE54563, were cited from the Gene Expression Omnibus database for performance evaluation. To perform molecular functional enrichment analyses, differentially expressed genes (DEGs) were identified, and a protein-protein interaction network was configured using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. To assess multi-purpose functions and pathways, such as signal transduction, plasma membrane, protein binding, and cancer pathways, a total of 220 DEGs, including 143 upregulated and 77 downregulated genes, were selected. Additionally, six central genes were observed, including electron transport system variant transcription factor 6, FMS-related receptor tyrosine kinase 3, carnosine synthetase 1, solute carrier family 22 member 13, prostaglandin endoperoxide synthetase 2, and protein serine kinase H1, which had a significant impact on cell proliferation, extracellular exosome, protein binding, and hypoxia-inducible factor 1 signaling pathway. This study enhances our understanding of the molecular mechanism of the occurrence and progression of MDD and provides candidate targets for its diagnosis and treatment.

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BACKGROUND: The COVID-19 epidemic has placed a lot of mental burdens on school students, causing anxiety. Clinically, it has been found that the Yuji point (LU10) can relieve anxiety by regulating Qi. METHODS: Thirty-six volunteers with anxiety disorders were divided into 3 groups, all of whom underwent 2 MRI examinations. The Yuji and nonacupoint groups received acupuncture between functional magnetic resonance imagings. We used the amplitude of low-frequency fluctuation to analyze regional brain activity, and seed-based functional connectivity (FC) to analyze changes in brain networks. RESULTS: After acupuncture, the LU10 was able to activate the frontal lobe, medial frontal gyrus, anterior cingulate gyrus, temporal lobe, hippocampus, etc in the left brain compared to the control group. The frontal lobe, medial frontal gyrus, cingulate gyrus, and anterior cingulate gyrus in the left brain were activated compared to those in the nonacupoint group. Compared with the control group, LU10 showed increased FC in the right parietal lobe, right precuneus, left temporal lobe, left superior temporal gyrus, and with cingulate gyrus. FC was enhanced among the hippocampus with the left temporal lobe and the superior temporal gyrus and reduced in the right lingual gyrus and right occipital lobe. CONCLUSION: Acupuncture at LU10s can regulate anxiety by upregulating or downregulating the relevant brain regions and networks. LU10s can be used to treat not only lung disorders but also related mental disorders.

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Multiple system atrophy (MSA) is a fatal neurodegenerative disease, it causes functional degradation of multiple organs and systems throughout the body. Astragalus membranaceus (AM), a well-known traditional Chinese medicine, has been used to improve muscle wasting-related disorders for a long history. In this study, we used network pharmacology and molecular docking to predict the mechanism underlying AM for the treatment of MSA. We screened the active compounds of AM and its related targets, as well as the target proteins of MSA. We made a Venn diagram to obtain the intersecting targets and then constructed a protein-protein interaction network to find the core targets and build an active ingredient-target network map. After subjecting the intersecting targets to gene ontology and Kyoto encyclopedia of genes and genomes analysis, the binding ability of core compounds and core target proteins were validated by molecular docking. A total of 20 eligible compounds and 274 intersecting targets were obtained. The core components of treatment are quercetin, kaempferol, and isorhamnetin, and the core targets are TP53, RELA, and TNF. The main biological processes are related to cellular responses and regulation. Molecular functions are mainly associated with apoptosis, inflammation, and tumorigenesis. Molecular docking results show good and standard binding abilities. This study illustrates that AM treats MSA through multiple targets and pathways, and provides a reference for subsequent research.

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BACKGROUND Depression is a common disease worldwide, with about 280 million people having depression. The unique facial features of depression provide a basis for automatic recognition of depression with deep convolutional neural networks. MATERIAL AND METHODS In this study, we developed a depression recognition method based on facial images and a deep convolutional neural network. Based on 2-dimensional images, this method quantified the binary classification problem and distinguished patients with depression from healthy participants. Network training consisted of 2 steps: (1) 1020 pictures of depressed patients and 1100 pictures of healthy participants were used and divided into a training set, test set, and validation set at the ratio of 7: 2: 1; and (2) fully connected convolutional neural network (FCN), visual geometry group 11 (VGG11), visual geometry group 19 (VGG19), deep residual network 50 (ResNet50), and Inception version 3 convolutional neural network models were trained. RESULTS The FCN model achieved an accuracy of 98.23% and a precision of 98.11%. The Vgg11 model achieved an accuracy of 94.40% and a precision of 96.15%. The Vgg19 model achieved an accuracy of 97.35% and a precision of 98.13%. The ResNet50 model achieved an accuracy of 94.99% and a precision of 98.03%. The Inception version 3 model achieved an accuracy of 97.10% and a precision of 96.20%. CONCLUSIONS The results show that deep convolution neural networks can support the rapid, accurate, and automatic identification of depression.

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BACKGROUND: It is known to all that the incidence of insomnia is becoming higher and higher with the increase of people's life stress. To some extent, it has brought about bad effects on people's life, work, study, and health, such as mental exhaustion, low work efficiency, and mood irritability. Now there are medications and non-medications methods for insomnia. As one of the treatments for insomnia, western medicine is to prolong the sleeping time and improve the anxious mood. However, taking western medicine to treat insomnia can also be accompanied by some adverse reactions at the same time, such as drug dependence, an allergic reaction, and so on. Traditional Chinese medicine therapy is based on syndrome differentiation and holistic concept. Shumian capsules (SM) are a kind of proprietary Chinese medicine for insomnia, which have the effect of relieving depression and calming the mind. But there are no studies on the efficacy and safety of SM in the treatment of insomnia. Therefore, I will provide a systematic review and meta-analysis to evaluate the efficacy and safety of SM for insomnia. METHODS: All the studies searched were from PubMed, EMBASE, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, and WanFang databases, and the studies types included in the analysis were all randomized controlled trials. All the retrieval contents were completed independently by 2 researchers, and a third reviewer would be involved when there existed any disagreement. The eligible studies were screened out according to the inclusion criteria and exclusion criteria, and some useful information was extracted and made into a feature table, including the year of the included studies, the age, and disease course of the participants in the studies and intervention methods, etc. Cochrane risk-of-bias tool was used to evaluate the quality of literature and meta-analysis was conducted by RevMan 5.4 software. RESULTS: A total of 9 articles including 709 participants were included in the study after screening out. The primary outcomes of statistical analysis were cure rate and total effective rate, while the secondary outcomes included Pittsburgh sleep quality index score and incidence of adverse reactions. The results showed that Pittsburgh sleep quality index score of the SM group and Western medicine group were statistically significant (MD = -0.50, 95% confidence interval [CI] = [-0.78, -0.22], P = .0005). The total effective rate of the SM group was slightly higher than that of the Western medicine group, but there was no statistical significance (relative risk [RR] = 1.03, 95% CI = [0.95,1.13], P = .43). CONCLUSION: This meta-analysis provides evidence for the efficacy and safety of SM in the treatment of insomnia, and provides a new idea for the clinical treatment of insomnia. But more research is needed to support further evidence.

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BACKGROUND: As a specific type of depression, postpartum depression (PPD) causes an adverse hazard to the mother's physical and mental health. Considering the safety requirements for lactation and the expectation of the rapid response to treatment, the search for safe and effective alternative therapies has attracted wide attention. Tai Chi, a traditional Chinese exercise therapy, has been widely used to relieve the symptoms and complications of patients with PPD, which the clinical efficacy is questioned. We conduct a comprehensive systematic review and meta-analysis to find clinical medical evidence of Tai Chi in the treatment of PPD. METHODS: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, China Science, and Technology Journal Database and Chinese Biomedical Literature Database will be searched from their inception of databases to September 30, 2021. Two reviewers will select articles, extract data, and assess the risk of bias independently. Any disagreement will be resolved by discussion with the third reviewer. Review Manager 5.3 software will be used for data synthesis. The Cochrane risk of bias assessment tool will be used to assess the risk of bias. RESULTS: This study will conduct a comprehensive literature search and provide a systematic synthesis of current published data to explore the effectiveness of Tai Chi for PPD. CONCLUSIONS: The findings of our study will provide updated evidence to determine whether Tai Chi is an effective intervention for patients with PPD, which will help clinicians make a better alternative treatment schedule of PPD patients and provide a reliable basis for health-related policymakers. STUDY REGISTRATION NUMBER: CRD42021276676.

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BACKGROUND: Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered major components of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. This study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in the malignant differentiation of low-grade glioma (LGG) to glioblastoma (GBM) and their potential impact on the prognosis of patients with GBM. METHODS: LncRNA and messenger RNA (mRNA) data were extracted from the Cancer Genome Atlas (TCGA) database from 156 GBM samples and 529 LGG samples. Separately, the miRNA expression data were downloaded from the Gene Expression Omnibus database, with the GSE112009 dataset containing miRNA expression data from 10 GBM samples and 15 LGG samples. Weighted gene coexpression network analysis was performed to screen the glioma grade-related lncRNAs. Then, a ceRNA network was established. The database for annotation, visualization, and integrated discovery was adopted to conduct functional enrichment analysis based on 57 upregulated differentially expressed mRNAs in the ceRNA network. Finally, Kaplan-Meier curves were created for the survival analysis of 13 hub lncRNA by combining the clinical data of GBM patients in TCGA. RESULTS: A ceRNA network including 16 lncRNAs, 18 miRNAs, and 78 mRNAs specific to the malignant differentiation of LGG to GBM was established. The 57 upregulated differentially expressed mRNAs in the ceRNA network were significantly enriched in 35 gene ontology terms and 5 pathways. The survival analysis showed that 2 lncRNAs (LINC00261 and HOXA10-AS) were prognostic biomarkers for patients with GBM in TCGA. CONCLUSION: The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the malignant differentiation of LGG to GBM. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for GBM.

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To overview the systematic reviews of Panax notoginseng saponins in the treatment of acute cerebral infarction. CNKI, CBM, Wanfang, VIP, PubMed, Cochrane Library and EMbase databases were retrieved to collect the systematic reviews of the efficacy of P. notoginseng saponins in the treatment of acute cerebral infarction. The retrieval time was from the time of database establishment to January 2021. After two researchers independently screened out the literature and extracted the data, AMSTAR-2 scale was used to evaluate the methodological quality of the included systematic reviews, GRADE system was used to grade the quality of evidences of the outcome indicators, and the efficacy evaluation was summarized. A total of 5 systematic reviews were included. AMSTAR-2 evaluation results showed that 3 items were relatively complete, while 4 items had a poor overall quality. P. notoginseng saponins combined with conventional Western medicine therapy was superior to single conventional therapy in the recovery of neurological function, enhancement of the total effective rate in clinic, and improvement of activities of daily living. GRADE evaluation results showed that the quality of evidence was from low quality to very low quality. In conclusion, in the treatment of acute cerebral infarction, P. notoginseng saponins can improve the clinical efficacy, with a good safety but a not high methodological quality and a low evidence quality. It is suggested that high-quality clinical studies shall be further carried out to provide evidence-based basis for the application of P. notoginseng saponins in the treatment of acute cerebral infarction.

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OBJECTIVE: To assess the efficacy and safety of PNS on antiplatelet therapy in the treatment of AIS. METHODS: We searched 7 literature databases and 2 clinical studies databases for randomized controlled studies (RCTs) evaluating PNS as an adjuvant therapy for AIS. Relevant studies were retrieved and screened, and data were extracted independently by two reviewers. The quality of the included studies was assessed using the Cochrane Risk Assessment Tool. Meta-analysis was carried out with the Rev Man 5.4 software. RESULTS: Of 8267 records identified, 43 RCTs met our inclusion criteria (n = 4170 patients). Patients assigned to PNS with conventional treatments (CTs) had improved functional independence at 90 days compared with those assigned to CTs alone (RR = 1.87, 95% CI = 1.37, to 2.55, P < 0.0001). Patients who received PNS combined with CTs showed significantly high improvements in neurological function among individuals with AIS on the neurologic deficit score (NDS) (MD CSS = -5.71, 95% CI = -9.55 to -1.87, P=0.004; MD NIHSS = -3.94, 95% CI = -5.65 to -2.23, P < 0.00001). The results also showed PNS contributed to a betterment in activities of daily living (ADL) on the Barthel index (MD day 10 BI = 4.86, 95% CI = 2.18, to 7.54, P < 0.00001; MD day 14 BI = 13.92, 95% CI = 11.46 to 16.38, P < 0.00001; MD day 28 BI = 7.16, 95% CI = 0.60, to 13.72, P < 0.00001). In addition, PNS, compared with CTs alone, could significantly improve overall response rate (ORR) (RR NIHSS = 1.20, 95% CI = 1.16, to 1.24, P < 0.00001; RR CSS = 1.15, 95% CI = 1.08, to 1.24, P < 0.0001), hemorheological parameters, maximum platelet aggregation rate (MPAR) (MD = -6.82, 95% CI = -9.62 to -4.02, P < 0.00001), platelet parameters (MD PLT = 4.85, 95% CI = 1.82 to 7.84, P=0.002; MD MPV = -0.79, 95% CI = -1.09 to -0.48, P < 0.00001), and serum CD62P (MD = -0.21, 95% CI = -0.29 to -0.13, P < 0.00001). The incidence of adverse reactions in PNS was lower than that in the control group (RR = 0.62, 95% CI = 0.39 to 0.97, P=0.04). Adverse reactions in the PNS were mild adverse reactions. CONCLUSION: PNS may be effective and safe in treating AIS on ameliorating neurological deficit, improving activities of daily living function, and enhancing antiplatelet effects. However, more high-quality evidence is needed before it can be recommended for routine antiplatelet therapy in patients with AIS.

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BACKGROUND: Insomnia is one of the most common sleep problems, which can impact physical and mental quality of life, resulting in a heavy social and economic burden. Xiaoyao san, a Chinese Herbal Medicine product, has been widely used as an alternative to recommended treatments for insomnia, but still lack of evidence of evidence-based medicine, which the clinical efficacy and its safety are questioned. Accordingly, we provide a protocol to evaluate the efficacy and safety of Xiaoyao san to update the search and evaluation for the best available and security treatment for insomnia. METHODS: This review systematic and comprehensive retrieves of 8 related databases at home and abroad. Only randomized controlled trials (RCTs) of Xiaoyao san on Insomnia published in English and Chinese will be included. The quality of the included trials including randomization, allocation concealment, blinding, withdrawal, and loss of follow-up which was evaluated using internationally accepted evaluation criteria. And then systematically comprehensive analysis of the efficacy. RESULTS: This review will be to assess the efficacy and safety of Xiaoyao san for insomnia. CONCLUSION: This systematic review will provide strong evidence for the effectiveness and safety of Xiaoyao san in the treatment of insomnia. PROSPERO REGISTRATION NUMBER: CRD42019127326.

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