Deep brain stimulation for Parkinson's disease: bibliometric analysis of the top 100 cited literature.

Background: Deep Brain Stimulation (DBS) has been widely applied and accepted in the treatment of neurological and psychiatric disorders. Despite numerous studies exploring the effects of DBS on the progression of neurodegenerative diseases and the treatment of advanced Parkinson's disease (PD), there is a limited number of articles summarizing this research. The purpose of this study is to investigate the current trends, hot topics, and potential in research surrounding DBS therapy for PD, as well as to anticipate the challenges of such research.

Causality between immunocytes and polymyositis: A Mendelian randomization analysis.

Polymyositis is a prominent subgroup of idiopathic inflammatory myopathy, considered to have an autoimmune etiology. However, research exploring the condition between immunocytes and polymyositis remains limited, indicating the need for further investigation to unravel these intricate associations. We employed bidirectional Mendelian randomization (MR) analysis to ascertain causality between 731 immunocytes and polymyositis.

Identification of potential drug targets for amyotrophic lateral sclerosis by Mendelian randomization analysis based on brain and plasma proteomics.

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.

Facial recognition for disease diagnosis using a deep learning convolutional neural network: a systematic review and meta-analysis.

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.

Biological Evaluation of Lysionotin: a Novel Inhibitor of 5-Lipoxygenase for Anti-glioma.

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.

Dietary factors and risk for amyotrophic lateral sclerosis: A two sample mendelian randomization study.

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.

Identification of potential drug targets for insomnia by Mendelian randomization analysis based on plasma proteomics.

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.

Efficacy of Acupuncture-Related Therapy for Migraine: A Systematic Review and Network Meta-Analysis.

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.

Assessing the causal relationship between psychiatric disorders and obstructive sleep apnea: a bidirectional Mendelian randomization.

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).

Causal relationship between gut microbiota and myasthenia gravis: a two-sample Mendelian randomization study.

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.

Screening and identification of key biomarkers associated with amyotrophic lateral sclerosis and depression using bioinformatics.

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.

Screening and identification of key biomarkers of depression using bioinformatics.

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.

The effect of acupuncture at the Yuji point on resting-state brain function in anxiety.

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.

Exploring the mechanism of astragalus membranaceus in the treatment of multiple system atrophy based on network pharmacology and molecular docking.

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.

Automatic Identification of Depression Using Facial Images with Deep Convolutional Neural Network.

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.

Efficacy and safety of Shumian capsules in treating insomnia: A systematic review and meta-analysis.

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.

The effectiveness of Tai Chi for postpartum depression: A protocol for systematic review and meta-analysis.

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.

Construction and comprehensive analysis of a competitive endogenous RNA network to reveal potential biomarkers for the malignant differentiation of glioma.

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.

[Overview of systematic reviews of Panax notoginseng saponins in treatment of acute cerebral infarction].

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.

Effectiveness and safety of Chinese herbal medicine Xiaoyao san for the treatment of insomnia: Protocol for a systematic review and meta-analysis.

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.

Comparison between heart rate variability and pulse rate variability during different sleep stages for sleep apnea patients.

Background: The usefulness of heart rate variability (HRV) in the clinical research has been verified in numerous studies. However, it is controversy that using pulse rate variability (PRV) as a surrogate of HRV in different clinical applications.

Objective: We aimed to investigate whether PRV extracted from finger pulse photoplethysmography (Pleth) signal could substitute HRV from ECG signal during different sleep stages by analyzing the common time-domain, frequency-domain and non-linear indices.

Electroencephalogram characteristics in patients with chronic fatigue syndrome.

Objective: To explore the electroencephalogram (EEG) characteristics in patients with chronic fatigue syndrome (CFS) using brain electrical activity mapping (BEAM) and EEG nonlinear dynamical analysis.

Methods: Forty-seven outpatients were selected over a 3-month period and divided into an observation group (24 outpatients) and a control group (23 outpatients) by using the non-probability sampling method. All the patients were given a routine EEG.

Morphology variability analysis of wrist pulse waveform for assessment of arteriosclerosis status.

In this paper, approximate entropy (ApEn) is applied to study the variability of pulse waveform for assessing coronary arteriosclerosis status. Having analyzed the wrist pulse waveforms taken from both normal subjects and the patients suffering from coronary arteriosclerosis (CA) disorders, we find that pulse morphology variability (PMV) is more efficient than pulse interval variability (PIV) in assessing the conditions of human coronary artery. Usually, the PMVs of the healthy are higher than those of the patients with CA diseases, and the PMVs of patients with CA diseases have more high frequency components than those of the healthy subjects.