SCRN: Single-cell Gene Regulatory Network Identification in Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disease, and it consumes considerable medical resources with increasing number of patients every year. Mounting evidence show that the regulatory disruptions altering the intrinsic activity of genes in brain cells contribute to AD pathogenesis. To gain insights into the underlying gene regulation in AD, we proposed a graph learning method, Single-Cell based Regulatory Network (SCRN), to identify the regulatory mechanisms based on single-cell data. SCRN implements the γ-decaying heuristic link prediction based on graph neural networks and can identify reliable gene regulatory networks using locally closed subgraphs. In this work, we first performed UMAP dimension reduction analysis on single-cell RNA sequencing (scRNA-seq) data of AD and normal samples. Then we used SCRN to construct the gene regulatory network based on three well-recognized AD genes (APOE, CX3CR1, and P2RY12). Enrichment analysis of the regulatory network revealed significant pathways including NGF signaling, ERBB2 signaling, and hemostasis. These findings demonstrate the feasibility of using SCRN to uncover potential biomarkers and therapeutic targets related to AD.

Cross shard leader accountability protocol based on two phase atomic commit.

Sharding blockchain is a technology designed to improve the performance and scalability of traditional blockchain systems. However, due to its design, communication between shards depends on shard leaders for transmitting information, while shard members are unable to detect communication activities between shards. Consequently, Byzantine nodes can act as shard leaders, engaging in malicious behaviors to disrupt message transmission. To address these issues, we propose the Cross shard leader accountability protocol (CSLAP), which is based on the two-phase atomic commit protocol (2PC). CSLAP employs byzantine broadcast/byzantine agreement (BB/BA) for Byzantine fault tolerance to generate cross-shard leader re-election certificates, thereby reducing the impact of shard leaders on inter-shard communication. It also uses Round-robin mechanism to facilitate leader re-election. Moreover, we demonstrate that CSLAP maintains the security and liveness of sharding transactions while providing lower communication latency. Finally, we conducted an experimental comparison between CSLAP and other cross-shard protocols. The results indicate that CSLAP exhibits superior performance in reducing communication latency.

Smoking may increase the usage of antidepressant: evidence from genomic perspective analysis.

This study uses the two-sample Mendelian randomization (TSMR) method to explore the causal relationships between smoking initiation (SMKI), never smoking (NSMK), past tobacco smoking (PTSMK), and the usage of antidepressants (ATD). Single-nucleotide polymorphisms (SNPs) with genome-wide significance (P < 5E-08) related to SMKI, NSMK, and PTSMK were selected from the genome-wide association study (GWAS) database as instrumental variables (IVs). The main method, inverse variance weighted (IVW), was utilized to investigate the causal relationship. The results demonstrated a positive causal relationship between SMKI and ATD use, where SMKI leads to an increase in ATD use. Conversely, NSMK and PTSMK showed a negative causal relationship with ATD use, meaning that NSMK and PTSMK lead to a reduction in ATD use. Additionally, sensitivity analysis showed that the results of this study were robust and reliable. Using the TSMR method and from a genetic perspective, this study found that SMKI leads to an increase in ATD use, while NSMK and PTSMK reduce ATD use.

Analysis of antimicrobial drug usage in psychiatric specialized hospitals during the pandemic in China.

BACKGROUND: This study aims to compare antimicrobial drug usage in our hospital to Jiangsu Province and China from 2020 to 2022. RESEARCH DESIGN AND METHODS: A detailed analysis was performed using data from the National Antimicrobial Drug Clinical Application Monitoring Network. Several parameters were studied: the rate of antimicrobial drug use, number and types of drugs used, the rate of combined use, rate of microbiological examinations, drug use intensity, and cumulative Defined Daily Doses (DDDs). RESULTS: From 2020 to 2022, our hospital's antimicrobial drug usage rate was consistently lower than Jiangsu Province and China. The average number of drug types and the combined drug use rate were higher in 2020 but fell below those in Jiangsu Province and China in 2021 and 2022. Our microbiological examination rate consistently surpassed that of Jiangsu Province and China. Furthermore, our Antimicrobial Usage Density and cumulative DDDs were notably lower. While AUD remained stable, DDDs showed a decreasing trend. The most dominant drug in DDDs was cefditoren, a third-generation cephalosporin. CONCLUSIONS: During the pandemic years, our hospital not only met the requirements for antimicrobial drug usage, microbiological examination, AUD, and cumulative DDDs but also demonstrated a consistent year-by-year decrease in drug usage and DDDs.

Residual network improves the prediction accuracy of genomic selection.

Genetic improvement of complex traits in animal and plant breeding depends on the efficient and accurate estimation of breeding values. Deep learning methods have been shown to be not superior over traditional genomic selection (GS) methods, partially due to the degradation problem (i.e. with the increase of the model depth, the performance of the deeper model deteriorates). Since the deep learning method residual network (ResNet) is designed to solve gradient degradation, we examined its performance and factors related to its prediction accuracy in GS. Here we compared the prediction accuracy of conventional genomic best linear unbiased prediction, Bayesian methods (BayesA, BayesB, BayesC, and Bayesian Lasso), and two deep learning methods, convolutional neural network and ResNet, on three datasets (wheat, simulated and real pig data). ResNet outperformed other methods in both Pearson's correlation coefficient (PCC) and mean squared error (MSE) on the wheat and simulated data. For the pig backfat depth trait, ResNet still had the lowest MSE, whereas Bayesian Lasso had the highest PCC. We further clustered the pig data into four groups and, on one separated group, ResNet had the highest prediction accuracy (both PCC and MSE). Transfer learning was adopted and capable of enhancing the performance of both convolutional neural network and ResNet. Taken together, our findings indicate that ResNet could improve GS prediction accuracy, affected potentially by factors such as the genetic architecture of complex traits, data volume, and heterogeneity.

Exploring adverse events of Vilazodone: evidence from the FAERS database.

OBJECTIVE: This study aims to conduct an exhaustive evaluation of Vilazodone's safety in clinical application and to unearth the potential adverse event (AE) risks associated with its utilization based on FDA Adverse Event Reporting System (FAERS) database. METHODS: This research employed data spanning from the first quarter of 2011 to the third quarter of 2023 from the FAERS database. Various signal detection methodologies, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM), were utilized to ascertain the correlation between Vilazodone and specific AEs. RESULTS: The study compiled a total of 17,439,268 reports of drug AEs, out of which 5,375 were related to Vilazodone. Through signal mining, 125 Preferred Terms (PTs) encompassing 27 System Organ Classes (SOCs) were identified. The findings indicated a higher prevalence among females and patients within the 45 to 65 age bracket. The principal categories of AEs included Psychiatric disorders, Nervous system disorders, and Gastrointestinal disorders, with prevalent incidents of Diarrhoea, Nausea, and Insomnia. Moreover, the study identified robust signals of novel potential AEs, notably in areas such as sleep disturbances (Sleep paralysis, Hypnagogic hallucination, Rapid eye movements sleep abnormal, Sleep terror, Terminal insomnia, Tachyphrenia), sexual dysfunctions (Female orgasmic disorder, Orgasm abnormal, Disturbance in sexual arousal, Spontaneous penile erection, Anorgasmia, Sexual dysfunction, Ejaculation delayed), and other symptoms and injuries (Electric shock sensation, Violence-related symptom, Gun shot wound). CONCLUSION: Although Vilazodone presents a positive prospect in the management of MDD, the discovery of AEs linked to its use, particularly the newly identified potential risks such as sleep and sexual dysfunctions, necessitates heightened vigilance among clinicians.

Valine induces inflammation and enhanced adipogenesis in lean mice by multi-omics analysis.

Introduction: The branched-chain amino acids (BCAAs) are essential to mammalian growth and development but aberrantly elevated in obesity and diabetes. Each BCAA has an independent and specific physio-biochemical effect on the host. However, the exact molecular mechanism of the detrimental effect of valine on metabolic health remains largely unknown. Methods and results: This study showed that for lean mice treated with valine, the hepatic lipid metabolism and adipogenesis were enhanced, and the villus height and crypt depth of the ileum were significantly increased. Transcriptome profiling on white and brown adipose tissues revealed that valine disturbed multiple signaling pathways (e.g., inflammation and fatty acid metabolism). Integrative cecal metagenome and metabolome analyses found that abundances of Bacteroidetes decreased, but Proteobacteria and Helicobacter increased, respectively; and 87 differential metabolites were enriched in several molecular pathways (e.g., inflammation and lipid and bile acid metabolism). Furthermore, abundances of two metabolites (stercobilin and 3-IAA), proteins (AMPK/pAMPK and SCD1), and inflammation and adipogenesis-related genes were validated. Discussion: Valine treatment affects the intestinal microbiota and metabolite compositions, induces gut inflammation, and aggravates hepatic lipid deposition and adipogenesis. Our findings provide novel insights into and resources for further exploring the molecular mechanism and biological function of valine on lipid metabolism.

Highly homogeneous and stable single-walled carbon nanotubes dispersion modified by polyvinylpyrrolidone and alkanolamine in water.

A novel noncovalent surface modification of commercial single-walled carbon nanotubes (SWCNTs) was successfully carried out by using ball grinding technology between SWCNTs and mixed dispersants (polyvinylpyrrolidone (PVP) and alkanolamine), affording a highly homogeneous and stable PA-SWCNTs dispersion in water. The homogeneous dispersibility and long storage stability were systematically investigated by transmittance spectroscopy, absorption spectroscopy, zeta potential analyzer, sedimentation photo and transmittance electron microscopy. Under the optimized conditions, the PA-SWCNTs dispersion modified with 0.7 wt% PVP and 0.25 wt% alkanolamine under the condition of total 6 h ball grinding time using paint shaker can be easily well-dispersed in water and has good storage stability, and no sedimentation is observed more than one month. From an industrial perspective, this method is green and easy to operate in industry.

Mining and analysis of security alert signals of valbenazine based on the Food and Drug Administration Adverse Event Reporting System database.

BACKGROUND: Valbenazine is used for tardive movement disorders in adults. Current studies on its safety are mostly from clinical trials and small case reports, limiting information on rare adverse reactions. This study investigated valbenazine-related adverse event (AE) risk signals using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database. METHODS: Valbenazine AEs data were collected from the FAERS database from 2017 Q2 to 2023 Q1, employing methods like reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network, and empirical Bayesian geometric mean. RESULTS: After data cleaning and drug screening, there were 20,837 AEs primarily suspecting valbenazine, involving 26 system organ classes and 125 AEs related to valbenazine at the preferred terms level. AEs related to valbenazine were mainly concentrated in nervous system disorders, general disorders and administration site conditions, and psychiatric disorders. Eye disorders and gastrointestinal disorders are new AEs not labeled in the valbenazine instructions. In addition, some new potential AE signals were found, such as Tardive dyskinesia and eyelid function disorder. CONCLUSION: The common AEs of valbenazine in the real world are consistent with the instructions, but there are some newly discovered suspicious AEs.

Unveiling potential adverse events associated with escitalopram oxalate: A real-world analysis based FDA adverse event reporting system database.

OBJECTIVE: The study aimed to conduct a multidimensional evaluation of potential adverse events (AEs) of escitalopram oxalate based on the FDA adverse event reporting system (FAERS) database. METHODS: This study utilized the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma-poisson shrinker (MGPS) to mine and analyze data from the FAERS database from the first quarter of 2004 to the second quarter of 2023. RESULTS: There was a total of 19,854 AE reports related to escitalopram oxalate, extracting 625 preferred terms (PTs), and covering 27 system organ classes (SOCs). The results showed that the number of reports by females was significantly higher than males, accounting for 57.68%. The reporting number was higher in 2018 and 2019, accounting for 9.50% and 10.18% of the total reports, respectively. The main reporters were consumers and other health professionals, accounting for 26.99% and 26.75% respectively. The majority of the reports were primarily from the United States. Newly emerging AE signals such as intentional overdose (n = 691, ROR 8.51, PRR 8.45, IC 3.05, Empirical Bayesian Geometric Mean (EBGM) 8.35), suicide attempt (n = 665, ROR 8.58, PRR 8.52, IC 3.06, EBGM 8.42), serum serotonin (n = 5, ROR 1044.78, PRR 1044.71, IC 2.56, EBGM 392.39), anti-actin antibody positive (n = 5, ROR 626.87, PRR 626.83, IC 2.56, EBGM 313.91), among others, were not mentioned in the drug's label. CONCLUSION: While escitalopram oxalate has clear benefits in the treatment of depression and other mental health disorders, the presence of AEs also suggests risks associated with its use. Particularly concerning are risks of suicide and changes in serum serotonin levels.

Deciphering the Enhancing Impact of Exogenous Brassinolide on Physiological Indices of Melon Plants under Downy Mildew-Induced Stress.

Melon (Cucumis melo L.) is a valuable horticultural crop of the Cucurbitaceae family. Downy mildew (DM), caused by Pseudoperonospora cubensis, is a significant inhibitor of the production and quality of melon. Brassinolide (BR) is a new type of phytohormone widely used in cultivation for its broad spectrum of resistance- and defense-mechanism-improving activity. In this study, we applied various exogenous treatments (0.5, 1.0, and 2.0 mg·L-1) of BR at four distinct time periods (6 h, 12 h, 24 h, and 48 h) and explored the impact of BR on physiological indices and the genetic regulation of melon seedling leaves infected by downy-mildew-induced stress. It was mainly observed that a 2.0 mg·L-1 BR concentration effectively promoted the enhanced photosynthetic activity of seedling leaves, and quantitative real-time polymerase chain reaction (qRT-PCR) analysis similarly exhibited an upregulated expression of the predicted regulatory genes of photosystem II (PSII) CmHCF136 (MELO3C023596.2) and CmPsbY (MELO3C010708.2), thus indicating the stability of the PSII reaction center. Furthermore, 2.0 mg·L-1 BR resulted in more photosynthetic pigments (nearly three times more than the chlorophyll contents (264.52%)) as compared to the control and other treatment groups and similarly upregulated the expression trend of the predicted key enzyme genes CmLHCP (MELO3C004214.2) and CmCHLP (MELO3C017176.2) involved in chlorophyll biosynthesis. Meanwhile, the maximum contents of soluble sugars and starch (186.95% and 164.28%) were also maintained, which were similarly triggered by the upregulated expression of the predicted genes CmGlgC (MELO3C006552.2), CmSPS (MELO3C020357.2), and CmPEPC (MELO3C018724.2), thereby maintaining osmotic adjustment and efficiency in eliminating reactive oxygen species. Overall, the exogenous 2.0 mg·L-1 BR exhibited maintained antioxidant activities, plastid membranal stability, and malondialdehyde (MDA) content. The chlorophyll fluorescence parameter values of F0 (42.23%) and Fv/Fm (36.67%) were also noticed to be higher; however, nearly three times higher levels of NPQ (375.86%) and Y (NPQ) (287.10%) were observed at 48 h of treatment as compared to all other group treatments. Increased Rubisco activity was also observed (62.89%), which suggested a significant role for elevated carbon fixation and assimilation and the upregulated expression of regulatory genes linked with Rubisco activity and the PSII reaction process. In short, we deduced that the 2.0 mg·L-1 BR application has an enhancing effect on the genetic modulation of physiological indices of melon plants against downy mildew disease stress.

Multidimensional assessment of adverse events of bupropion: A large-scale data analysis from the FAERS database.

OBJECTIVE: Bupropion, a monocyclic antidepressant, aids in smoking cessation, treats major depression, and prevents severe depression in seasonal affective disorder patients. Yet, its adverse reactions remain insufficiently studied. METHODS: All data from the raw data packages for 78 quarters from the 1st quarter of 2004 to the 2nd quarter of 2023 were extracted from the FDA Adverse Event Reporting System (FAERS) database and imported into the SAS9.4 software for data cleaning and analysis. The Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS) methods were used to analyze drug adverse events and assess their compliance with various screening criteria. RESULTS: The results showed a total of 36,862 reports related to Bupropion use, identifying 364 positive reaction terms (PT) covering 23 System Organ Classes (SOCs). In addition to known side effects, some new potential adverse reactions were found, such as Stool analysis abnormal, Oculocephalogyric reflex absent, Suspected suicide, and so on. At the same time, reactions like Encephalopathy neonatal, Hyponatraemic coma, and Electrocardiogram QRS complex prolonged were prominently ranked. Notably, occurrences such as Urine amphetamine positive and Amphetamines positive were relatively high, suggesting extra caution for these potential adverse reactions during clinical use of Bupropion. CONCLUSION: These findings highlight the potential health risks of long-term Bupropion use, especially concerning efficacy, positive drug tests, and suicidal tendencies. Therefore, it is recommended to monitor and assess patients using Bupropion more stringently to use this therapeutically potential drug more safely and effectively.

Investigating the Mechanism of Chufan Yishen Formula in Treating Depression through Network Pharmacology and Experimental Verification.

Objective: To investigate the antidepressant effect and potential mechanism of the Chufan Yishen Formula (CFYS) through network pharmacology, molecular docking, and experimental verification. Methods: The active ingredients and their target genes of CFYS were identified through Traditional Chinese Medicine Systems Pharmacology (TCMSP) and TCM-ID. We obtained the differentially expressed genes in patients with depression from the GEO database and screened out the genes intersecting with the target genes of CFYS to construct the PPI network. The key pathways were selected through STRING and KEGG. Then, molecular docking and experimental verification were performed. Results: A total of 113 effective components and 195 target genes were obtained. After intersecting the target genes with the differentially expressed genes in patients with depression, we obtained 37 differential target genes, among which HMOX1, VEGFA, etc., were the key genes. After enriching the differential target genes by KEGG, we found that the "chemical carcinogenesis-reactive oxygen species" pathway was the key pathway for the CFYS antidepressant effect. Besides, VEGFA might be a key marker for depression. Experimental verification found that CFYS could significantly improve the behavioral indicators of rats with depression models, including improving the antioxidant enzyme activity and increasing VEGFA levels. The results are consistent with the network pharmacology analysis. Conclusions: CFYS treatment for depression is a multicomponent, multitarget, and multipathway complex process, which may mainly exert an antidepressant effect by improving the neuron antioxidant stress response and regulating VEGFA levels.

Causal relationship between diabetes and depression: A bidirectional Mendelian randomization study.

OBJECTIVE: This study explores the causal relationship between diabetes and depression using a two-sample Mendelian Randomization (TSMR) method. METHODS: The study selected single nucleotide polymorphisms (SNPs) closely associated with diabetes and depression in European populations from the Genome-Wide Association Study (GWAS) database, to serve as instrumental variables (IVs). The main evaluation method was inverse variance weighted analysis (IVW), supplemented by verification using Weighted median, Weighted mode, and MR Egger methods. The Odds Ratio (OR) and 95 % Confidence Interval (CI) were used as the main evaluation indicators, along with sensitivity analysis. RESULTS: This study found a negative correlation between diabetes and depression, suggesting that diabetes may reduce the risk of depression [IVW(FE): OR: 0.901, 95 % CI: 0.823 to 0.987; P = 0.025 < 0.05]. This finding was further confirmed by the Weighted median [OR: 0.844, 95 % CI: 0.730 to 0.974; P = 0.021 < 0.05] and Weighted mode method [OR: 0.766, 95 % CI: 0.637 to 0.921; P = 0.006 < 0.05]. However, the reverse showed no causal relationship between depression and diabetes (P > 0.05). Sensitivity analysis found no pleiotropy, and there were no large influences from individual SNPs on the result's robustness; the results are stable and reliable. CONCLUSION: For the first time, this study using TSMR analysis found a negative correlation between diabetes and the risk of depression onset in European populations, suggesting that diabetes might reduce the risk of depression. But as the mechanisms are still unclear, these findings warrant further study.

Triangular pulley traction facilitates endoscopic full-thickness resection of exogenous gastric tumor in the fornix of the stomach.

A 65-year-old woman was diagnosed with an exogenous submucosal tumor located in the fornix of the stomach, on the basis of the endoscopic ultrasound and enhanced CT findings. She refused surgery and referred for EFTR. It is difficult to perform EFTR at the gastric fornix and suture the large surgical defect. Therefore, we created technique of triangular pulley traction combined with pre-closure.