Comparative efficacy and safety of ginkgo-based Chinese patent medicines in patients with hypertension: A systematic review and network meta-analysis of randomized clinical trials.

BACKGROUND: The efficacy and safety of different oral ginkgo-based Chinese patent medicines (CPMs) regimens for hypertension patients were analyzed based on the network meta-analysis of the frequency framework. METHODS: We conducted a comprehensive search of PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, and Chinese Biomedical Literature Database to gather data on randomized controlled trials (RCTs) evaluating the efficacy of 8 ginkgo biloba oral preparations for the treatment of hypertension. The trials included in the analysis were conducted from the inception of the databases up to September 2023. Methodological quality and risk of bias were assessed using the RoB 2.0 evaluation tool, and a reticulated meta-analysis was conducted using STATA MP 14 software. The RCTs included in this study were published studies and therefore did not require ethics committee review or patient consent. RESULTS: We ultimately included 46 RCTs covering 8 CPMs including ginkgo biloba tablet (GBT), GB capsule (GBC), ginkgo biloba drop (GBD), ginkgo biloba ketone ester drop, Fufangyinxing capsule, fufangyinxingtongmai oral liquid, Yinxingmihuan oral liquid, Yindanxinanotong softgel capsule (YDXNT). GBD + CT demonstrated the highest effectiveness in reducing systolic blood pressure (surface under the cumulative ranking [SUCRA] = 78.7%) and improving total effective rate (SUCRA = 86.7%). GBC + CT exhibited the greatest efficacy in reducing diastolic blood pressure (SUCRA = 92.6%). GBT + CT was identified as the most effective in lowering total cholesterol (TC) (SUCRA = 100%). Additionally, YDXNT + CT demonstrated notable improvements in triglyceride levels (SUCRA = 92.2%), Nitric oxide (NO) (SUCRA = 93.9%), and ET-1 (SUCRA = 67.5%). In terms of safety, 14 studies reported the occurrence of adverse reactions with a high degree of clinical heterogeneity, which was only qualitatively analyzed in this study. CONCLUSION SUBSECTIONS: We found that a combination of 8 ginkgo-based CPMs + CT was effective in hypertension compared with CT. The evidence showed that GBD + CT were the best in improving systolic blood pressure and total effective rate, GBC + CT improved diastolic blood pressure, GBT + CT were the most effective in improving TC, and YDXNT + CT was the most effective in improving TG, NO, and ET-1. Adverse effects were only analyzed qualitatively, and the number of adverse effects of CPMs treatment was relatively low compared to CT. In addition, the quality of the literature included in the study was low, and further validation through RCTs with larger sample sizes, higher quality, and more rigorously designed is needed.

Pharmacological mechanism of natural antidepressants: The role of mitochondrial quality control.

BACKGROUND: Depression is a mental illness characterized by persistent sadness and a reduced capacity for pleasure. In clinical practice, SSRIs and other medications are commonly used for therapy, despite their various side effects. Natural products present distinct advantages, including synergistic interactions among multiple components and targeting multiple pathways, suggesting their tremendous potential in depression treatment. Imbalance in mitochondrial quality control (MQC) plays a significant role in the pathology of depression, emphasizing the importance of regulating MQC as a potential intervention strategy in addressing the onset and progression of depression. However, the role and mechanism through which natural products regulate MQC in depression treatments still need to be comprehensively elucidated, particularly in clinical and preclinical settings. PURPOSE: This review was aimed to summarize the findings of recent studies and outline the pharmacological mechanisms by which natural products modulate MQC to exert antidepressant effects. Additionally, it evaluated current research limitations and proposed new strategies for future preclinical and clinical applications in the depression domain. METHODS: To study the main pharmacological mechanisms underlying the regulation of MQC by natural products in the treatment of depression, we conducted a thorough search across databases such as PubMed, Web of Science, and ScienceDirect databases to classify and summarize the relationship between MQC and depression, as well as the regulatory mechanisms of natural products. RESULTS: Numerous studies have shown that irregularities in the MQC system play an important role in the pathology of depression, and the regulation of the MQC system is involved in antidepressant treatments. Natural products mainly regulate the MQC system to induce antidepressant effects by alleviating oxidative stress, balancing ATP levels, promoting mitophagy, maintaining calcium homeostasis, optimizing mitochondrial dynamics, regulating mitochondrial membrane potential, and enhancing mitochondrial biogenesis. CONCLUSIONS: We comprehensively summarized the regulation of natural products on the MQC system in antidepressants, providing a unique perspective for the application of natural products within antidepressant therapy. However, extensive efforts are imperative in clinical and preclinical investigations to delve deeper into the mechanisms underlying how antidepressant medications impact MQC, which is crucial for the development of effective antidepressant treatments.

Traditional Chinese exercises on depression: A network meta-analysis.

BACKGROUND: Exercise is an important factor for the treatment and rehabilitation of depression. Traditional Chinese exercise is considered as an effective treatment for depression. In recent years, many studies have shown that Chinese exercise therapy may be safe in the treatment of depression. To evaluate the therapeutic effect of traditional Chinese exercise on depression using network meta-analysis. METHODS: PubMed, Cochrane Library, Web of Science, China National Knowledge Infrastructure, VIP shop Database, China Biomedical Literature Database, and Wan Fang Data Knowledge Service Platform were included in randomized controlled studies on traditional Chinese exercises for the treatment of depression from the establishment of the library to July 2023. The literature was extracted and assessed for risk of bias using the Cochrane Risk of Bias Assessment and statistically analyzed using Review Manager 5.4 and Stata 14.2. RESULTS: A total of 25 studies involving 3 exercises with a total of 1605 cases were included. The results of the network meta-analysis showed that each exercise significantly reduced the 24-item Hamilton Depression Scale (HAMD-24), Hamilton Anxiety Scale, Beck Depression Inventory, and Self-rating Depression Scale scores. However, conventional treatments have the advantage of improving the sleep quality of patients with depression. CONCLUSIONS: The 3 exercises included in this study were effective for depression. Baduanjin and Tai Chi were better at improving the outcomes related to depression and anxiety. The effect of sleep quality intervention was slightly worse. Larger, high-quality randomized controlled trials are needed to compare interventions across exercises in a more granular manner.

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). 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.

Age-related differences in long-term potentiation-like plasticity and short-latency afferent inhibition and their association with cognitive function.

Background: The neurophysiological differences in cortical plasticity and cholinergic system function due to ageing and their correlation with cognitive function remain poorly understood. Aims: To reveal the differences in long-term potentiation (LTP)-like plasticity and short-latency afferent inhibition (SAI) between older and younger individuals, alongside their correlation with cognitive function using transcranial magnetic stimulation (TMS). Methods: The cross-sectional study involved 31 younger adults aged 18-30 and 46 older adults aged 60-80. All participants underwent comprehensive cognitive assessments and a neurophysiological evaluation based on TMS. Cognitive function assessments included evaluations of global cognitive function, language, memory and executive function. The neurophysiological assessment included LTP-like plasticity and SAI. Results: The findings of this study revealed a decline in LTP among the older adults compared with the younger adults (wald χ2=3.98, p=0.046). Subgroup analysis further demonstrated a significant reduction in SAI level among individuals aged 70-80 years in comparison to both the younger adults (SAI(N20): (t=-3.37, p=0.018); SAI(N20+4): (t=-3.13, p=0.038)) and those aged 60-70 (SAI(N20): (t=-3.26, p=0.025); SAI(N20+4): (t=-3.69, p=0.006)). Conversely, there was no notable difference in SAI level between those aged 60-70 years and the younger group. Furthermore, after employing the Bonferroni correction, the correlation analysis revealed that only the positive correlation between LTP-like plasticity and language function (r=0.61, p<0.001) in the younger group remained statistically significant. Conclusions: During the normal ageing process, a decline in synaptic plasticity may precede cholinergic system dysfunction. In individuals over 60 years of age, there is a reduction in LTP-like plasticity, while a decline in cholinergic system function is observed in those over 70. Thus, the cholinergic system may play a vital role in preventing cognitive decline during normal ageing. In younger individuals, LTP-like plasticity might represent a potential neurophysiological marker for language function.

Antidepressant mechanism of traditional Chinese medicine: Involving regulation of circadian clock genes.

Numerous studies have demonstrated an intimate relationship between circadian rhythm disorders and the development and prevention of depression. The biological clock genes, which constitute the molecular basis of endogenous circadian rhythms, hold promising prospects for depression treatment. Based on an extensive review of recent domestic and international research, this article presents a comprehensive analysis of how traditional Chinese medicine (TCM) intervenes in depression by regulating circadian rhythms. The findings indicate that TCM exerts its antidepressant effects by targeting specific biological clock genes such as Bmal1, clock, Arntl, Per1, Per2, Per3, Nr1d1, Cry2, and Dbp, as well as regulating circadian rhythms of hormone secretion. However, most current research is still confined to basic experimental studies, lacking clinical double-blind control trials to further validate these viewpoints. Furthermore, there is insufficient research on the signal transduction pathway between biological clock genes and pathological changes in depression. Additionally, further clarification is needed regarding the specific targets of TCM on the biological clock genes.

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. 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.

Insights into the effects of fixation methods on the sensory quality of straight-shaped green tea and dynamic changes of key taste metabolites by widely targeted metabolomic analysis.

Fresh leaves of Echa 1 were fixed by roller, steam/hot air and light-wave, and the effects of the three fixation methods on the chemical characteristics of straight-shaped green teas (GTs) were studied by widely targeted metabolomic analysis. 1001 non-volatile substances was identified, from which 97 differential metabolites were selected by the criteria of variable importance in projection (VIP) > 1, p < 0.05, and |log2(fold change)| > 1. Correlation analysis indicated that 14 taste-active metabolites were the major contributors to the taste differences between differently processed GTs. High-temperature fixation induces protein oxidation or degradation, γ-glutamyl peptide transpeptidation, degradation of flavonoid glycosides and epimerization of cis-catechins, resulting in the accumulation of amino acids, peptides, flavonoids and trans-catechins, which have flavor characteristics such as umami, sweetness, kokumi, bitterness and astringency, thereby affecting the overall taste of GTs. These findings provided a scientific basis for the directional processing technology of high-quality green tea.

Adult hippocampal neurogenesis: pharmacological mechanisms of antidepressant active ingredients in traditional Chinese medicine.

Depression is characterized by prominent indicators and manifestations, such as anhedonia, which refers to the inability to experience pleasure, and persistent feelings of hopelessness. In clinical practice, the primary treatment approach involves the utilization of selective serotonin reuptake inhibitors (SSRIs) and related pharmacological interventions. Nevertheless, it is crucial to recognize that these agents are associated with significant adverse effects. Traditional Chinese medicine (TCM) adopts a multifaceted approach, targeting diverse components, multiple targets, and various channels of action. TCM has potential antidepressant effects. Anomalies in adult hippocampal neurogenesis (AHN) constitute a pivotal factor in the pathology of depression, with the regulation of AHN emerging as a potential key measure to intervene in the pathogenesis and progression of this condition. This comprehensive review presented an overview of the pharmacological mechanisms underlying the antidepressant effects of active ingredients found in TCM. Through examination of recent studies, we explored how these ingredients modulated AHN. Furthermore, we critically assessed the current limitations of research in this domain and proposed novel strategies for preclinical investigation and clinical applications in the treatment of depression in future.

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. 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.

Effects of repetitive transcranial magnetic stimulation on episodic memory in patients with subjective cognitive decline: study protocol for a randomized clinical trial.

Introduction: Early decline of episodic memory is detectable in subjective cognitive decline (SCD). The left dorsolateral prefrontal cortex (DLPFC) is associated with encoding episodic memories. Repetitive transcranial magnetic stimulation (rTMS) is a novel and viable tool to improve cognitive function in Alzheimer's disease (AD) and mild cognitive impairment, but the treatment effect in SCD has not been studied. We aim to investigate the efficacy of rTMS on episodic memory in individuals with SCD, and to explore the potential mechanisms of neural plasticity. Methods: In our randomized, sham-controlled trial, patients (n = 60) with SCD will receive 20 sessions (5 consecutive days per week for 4 weeks) of real rTMS (n = 30) or sham rTMS (n = 30) over the left DLPFC. The primary outcome is the Auditory Verbal Learning Test-Huashan version (AVLT-H). Other neuropsychological examinations and the long-term potentiation (LTP)-like cortical plasticity evaluation serve as the secondary outcomes. These outcomes will be assessed before and at the end of the intervention. Discussion: If the episodic memory of SCD improve after the intervention, the study will confirm that rTMS is a promising intervention for cognitive function improvement on the early stage of dementia. This study will also provide important clinical evidence for early intervention in AD and emphasizes the significance that impaired LTP-like cortical plasticity may be a potential biomarker of AD prognosis by demonstrating the predictive role of LTP on cognitive improvement in SCD. Ethics and dissemination: The study was approved by the Human Research Ethics Committee of the hospital (No. 2023-002-01). The results will be published in peer-review publications. Clinical trial registration: https://www.chictr.org.cn/, identifier ChiCTR2300075517.

Antidepressant pharmacological mechanisms: focusing on the regulation of autophagy.

The core symptoms of depression are anhedonia and persistent hopelessness. Selective serotonin reuptake inhibitors (SSRIs) and their related medications are commonly used for clinical treatment, despite their significant adverse effects. Traditional Chinese medicine with its multiple targets, channels, and compounds, exhibit immense potential in treating depression. Autophagy, a vital process in depression pathology, has emerged as a promising target for intervention. This review summarized the pharmacological mechanisms of antidepressants by regulating autophagy. We presented insights from recent studies, discussed current research limitations, and proposed new strategies for basic research and their clinical application in depression.

Microbial Diversity and Characteristic Quality Formation of Qingzhuan Tea as Revealed by Metagenomic and Metabolomic Analysis during Pile Fermentation.

In order to analyze the changes in the microbial community structure during the pile fermentation of Qingzhuan tea and their correlation with the formation of quality compounds in Qingzhuan tea, this study carried out metagenomic and metabolomic analyses of tea samples during the fermentation process of Qingzhuan tea. The changes in the expression and abundance of microorganisms during the pile fermentation were investigated through metagenomic assays. During the processing of Qingzhuan tea, there is a transition from a bacterial dominated ecosystem to an ecosystem enriched with fungi. The correlation analyses of metagenomics and metabolomics showed that amino acids and polyphenol metabolites with relatively simple structures exhibited a significant negative correlation with target microorganisms, while the structurally complicated B-ring dihydroxy puerin, B-ring trihydroxy galloyl puerlin, and other compounds showed a significant positive correlation with target microorganisms. Aspergillus niger, Aspergillus glaucus, Penicillium in the Aspergillaceae family, and Talaromyces and Rasamsonia emersonii in Trichocomaceae were the key microorganisms involved in the formation of the characteristic qualities of Qingzhuan tea.

Digital Prediction of the Purchase Price of Fresh Tea Leaves of Enshi Yulu Based on Near-Infrared Spectroscopy Combined with Multivariate Analysis.

In this study, near-infrared spectroscopy (NIRS) combined with a variety of chemometrics methods was used to establish a fast and non-destructive prediction model for the purchase price of fresh tea leaves. Firstly, a paired t-test was conducted on the quality index (QI) of seven quality grade fresh tea samples, all of which showed statistical significance (p < 0.05). Further, there was a good linear relationship between the QI, quality grades, and purchase price of fresh tea samples, with the determination coefficient being greater than 0.99. Then, the original near-infrared spectra of fresh tea samples were obtained and preprocessed, with the combination (standard normal variable (SNV) + second derivative (SD)) as the optimal preprocessing method. Four spectral intervals closely related to fresh tea prices were screened using the synergy interval partial least squares (si-PLS), namely 4377.62 cm-1-4751.74 cm-1, 4755.63 cm-1-5129.75 cm-1, 6262.70 cm-1-6633.93 cm-1, and 7386 cm-1-7756.32 cm-1, respectively. The genetic algorithm (GA) was applied to accurately extract 70 and 33 feature spectral data points from the whole denoised spectral data (DSD) and the four characteristic spectral intervals data (FSD), respectively. Principal component analysis (PCA) was applied, respectively, on the data points selected, and the cumulative contribution rates of the first three PCs were 99.856% and 99.852%. Finally, the back propagation artificial neural (BP-ANN) model with a 3-5-1 structure was calibrated with the first three PCs. When the transfer function was logistic, the best results were obtained (Rp2 = 0.985, RMSEP = 6.732 RMB/kg) by 33 feature spectral data points. The detection effect of the best BP-ANN model by 14 external samples were R2 = 0.987 and RMSEP = 6.670 RMB/kg. The results of this study have achieved real-time, non-destructive, and accurate evaluation and digital display of purchase prices of fresh tea samples by using NIRS technology.

Factors associated with depression among healthcare workers during the COVID-19 pandemic: a systematic review and meta-analysis.

The COVID-19 pandemic has had a profound impact on the mental health of healthcare workers (HCWs). We aimed to identify the factors associated with depression among HCWs during the pandemic. We conducted literature search using eight electronic databases up to July 27 2022. Observational studies with more than 200 participants investigating correlates of depression in HCWs after COVID-19 outbreak were included. We used fixed- and random-effects models to pool odds ratios (ORs) across studies, and Cochran's chi-squared test and I 2 statistics to assess study heterogeneity. Publication bias was evaluated by funnel plots. Thirty-five studies involving 44,362 HCWs met the inclusion criteria. Female (OR=1.50, 95% CI [1.23,1.84]), single (OR=1.36, 95% CI [1.21,1.54]), nurse (OR=1.69, 95% CI [1.28,2.25]), history of mental diseases (OR=2.53, 95% CI [1.78,3.58]), frontline (OR=1.79, 95% CI [1.38,2.32]), health anxiety due to COVID-19 (OR=1.88, 95% CI [1.29,2.76]), working in isolation wards (OR=1.98, 95% CI [1.38,2.84]), and insufficient personal protective equipment (OR=1.49, 95% CI [1.33,1.67]) were associated with increased risk of depression. Instead, HCWs with a positive professional prospect (OR=0.34, 95% CI [0.24,0.49]) were less likely to be depressed. This meta-analysis provides up-to-date evidence on the factors linked to depression among HCWs during the COVID-19 pandemic. Given the persistent threats posed by COVID-19, early screening is crucial for the intervention and prevention of depression in HCWs.

Brain disease research based on functional magnetic resonance imaging data and machine learning: a review.

Brain diseases, including neurodegenerative diseases and neuropsychiatric diseases, have long plagued the lives of the affected populations and caused a huge burden on public health. Functional magnetic resonance imaging (fMRI) is an excellent neuroimaging technology for measuring brain activity, which provides new insight for clinicians to help diagnose brain diseases. In recent years, machine learning methods have displayed superior performance in diagnosing brain diseases compared to conventional methods, attracting great attention from researchers. This paper reviews the representative research of machine learning methods in brain disease diagnosis based on fMRI data in the recent three years, focusing on the most frequent four active brain disease studies, including Alzheimer's disease/mild cognitive impairment, autism spectrum disorders, schizophrenia, and Parkinson's disease. We summarize these 55 articles from multiple perspectives, including the effect of the size of subjects, extracted features, feature selection methods, classification models, validation methods, and corresponding accuracies. Finally, we analyze these articles and introduce future research directions to provide neuroimaging scientists and researchers in the interdisciplinary fields of computing and medicine with new ideas for AI-aided brain disease diagnosis.

NaCl template-assisted construction of a CoP-MoP heterostructured electrocatalyst for electrocatalytic nitrogen reduction.

The electrocatalytic nitrogen reduction reaction (NRR) to ammonia is a promising technology to store renewable energy and mitigate greenhouse gas emissions. However, it usually suffers from low ammonia yield and selectivity because of the lack of efficient electrocatalysts. Herein, we report that the construction of metal phosphide heterojunctions is an efficient strategy for NRR activity enhancement. A CoP-MoP heterojunction electrocatalyst, which is fabricated by a facile NaCl template-assisted strategy, exhibits a favorable ammonia yield rate of 77.8 µg h-1 mgcat-1 (38.9 µg h-1 cm-2) and a high faradaic efficiency of 11.16% at -0.50 V versus the reversible hydrogen electrode. The high NRR electrocatalytic activity can be attributed to the electronic coupling effects and interfacial synergistic effects of CoP and MoP at the heterojunction interface, which accelerates the electron transfer rate. Moreover, Mo doping changes the d-band centers of metal sites on the CoP surface, which is conducive to N2 adsorption and promotes N2* adsorption in the competition of occupying active sites, thus inhibiting the HER. This work manifests the high potential of phosphide electrocatalysts and opens an alternative route toward NRR electrocatalysis.

ELL associated factor 2 is a potential diagnostic and prognostic indicator: evidence from the in silico and in vitro experiments.

Due to the lack of sensitive biomarkers, cancer disease kill 9.6 million individuals each year around the globe. The present study aimed to explore the association between ELL Associated Factor 2 (EAF2) expression and its diagnostic and prognostic landscape across different human cancers using an in silico and in vitro approach. To achieve the defined goals of this study, we used the following online sources: UALCAN, KM plotter, TNMplot, cBioPortal, STRING, DAVID, MuTarget, Cytoscape, and CTD. In addition to this, we also used additional The Cancer Genome Atlas (TCGA) datasets via TIMER2, GENT2, and GEPIA to confirm the expression of EAF2 on additional cohorts. Finally, we performed RNA sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) techniques-based analysis using A549, ABC-1, EBC-1, LK-2 lung cancer cell lines, and MRC-9 normal control lung cell line for further validation of the results. On balance, EAF2 was elevated in 19 types of human cancers and its up-regulation was significantly correlated with shorter overall survival (OS), relapse-free survival (RFS), and metastasis in Liver Hepatocellular Carcinoma (LIHC) and Lung Squamous Cell Carcinoma (LUSC) patients. We further evaluated that EAF2 expression was also elevated across LIHC and LUSC patients belonging to different clinicopathological features. Through pathway analysis, EAF2 associations were observed with four important pathways. Moreover, some worth noticing correlations were also documented between EAF2 expression and its promoter methylation level, genetic alterations, other mutant genes, tumor purity, and different immune cells infiltration. The higher EAF2 expression contributes significantly to the tumorigenesis and metastasis of LIHC and LUSC. Therefore, it can be used as a common biomarker in these cancers.

Influence of gut microecology in the development of malignant tumors and its potential therapeutic application: A review.

A microbial ecosystem is a complex community of multiple bacterial interactions. The potential role of gut microbiota in human health has already attracted the attention of many researchers. Dysregulation of the gut microbial community has been suggested to be closely associated with the progression of various chronic diseases. Malignant neoplasms represent a major global health burden and are now the leading cause of death. The formation of tumors is often thought to be influenced by genetic and environmental factors. Recent research advances have indicated that multiple malignancies may also be attributed to the gut microbiota. In this review, we highlight the complex interactions between gut microbes and their metabolites, as well as the potential impact of gut microecology on the occurrence and development of tumors. In addition, potential strategies for targeted therapy of tumors using gut microecology are discussed. In the near future, intestinal microecology is likely to be used for early screening of tumors and subsequent clinical treatment.