Commercial Chinese polyherbal preparation Zao Ren An Shen prescription for primary insomnia: a systematic review with meta-analysis and trial sequential analysis.

Background: Natural products are widely used for primary insomnia (PI). This systematic review with trial sequential analysis (TSA) aimed to summarize evidence pertaining to the effectiveness and safety of Zao Ren An Shen (ZRAS) prescription, a commercial Chinese polyherbal preparation, for treating PI. Methods: Controlled clinical trials appraising ZRAS compared to controls or as an add-on treatment were systematically searched across seven databases until January 2024. Cochrane ROB 2.0 and ROBINS-I tools were adopted to determine risk of bias. Quality of evidence was assessed using the GRADE framework. Results: We analyzed 22 studies, involving 2,142 participants. The effect of ZRAS in reducing Pittsburgh Sleep Quality Index scores was found to be comparable to benzodiazepines [MD = 0.39, 95%CI (-0.12, 0.91), p = 0.13] and superior to Z-drugs [MD = -1.31, 95%CI (-2.37, -0.24), p = 0.02]. The addition of ZRAS to hypnotics more significantly reduced polysomnographically-recorded sleep onset latency [MD = -4.44 min, 95%CI (-7.98, -0.91), p = 0.01] and number of awakenings [MD = -0.89 times, 95%CI (-1.67, -0.10), p = 0.03], and increased total sleep time [MD = 40.72 min, 95%CI (25.14, 56.30), p < 0.01], with fewer adverse events than hypnotics alone. TSA validated the robustness of these quantitative synthesis results. However, the quality of evidence ranged from very low to low. The limited data available for follow-up did not support meta-synthesis. Conclusion: While ZRAS prescription shows promising effectiveness in treating PI, the overall quality of evidence is limited. Rigorously-designed randomized control trials are warranted to confirm the short-term efficacy of ZRAS and explore its medium-to-long-term efficacy. Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=471497), identifier (CRD42023471497).

Early blood immune molecular alterations in cynomolgus monkeys with a PSEN1 mutation causing familial Alzheimer's disease.

INTRODUCTION: More robust non-human primate models of Alzheimer's disease (AD) will provide new opportunities to better understand the pathogenesis and progression of AD. METHODS: We designed a CRISPR/Cas9 system to achieve precise genomic deletion of exon 9 in cynomolgus monkeys using two guide RNAs targeting the 3' and 5' intron sequences of PSEN1 exon 9. We performed biochemical, transcriptome, proteome, and biomarker analyses to characterize the cellular and molecular dysregulations of this non-human primate model. RESULTS: We observed early changes of AD-related pathological proteins (cerebrospinal fluid Aß42 and phosphorylated tau) in PSEN1 mutant (ie, PSEN1-ΔE9) monkeys. Blood transcriptome and proteome profiling revealed early changes in inflammatory and immune molecules in juvenile PSEN1-ΔE9 cynomolgus monkeys. DISCUSSION: PSEN1 mutant cynomolgus monkeys recapitulate AD-related pathological protein changes, and reveal early alterations in blood immune signaling. Thus, this model might mimic AD-associated pathogenesis and has potential utility for developing early diagnostic and therapeutic interventions. HIGHLIGHTS: A dual-guide CRISPR/Cas9 system successfully mimics AD PSEN1-ΔE9 mutation by genomic excision of exon 9. PSEN1 mutant cynomolgus monkey-derived fibroblasts exhibit disrupted PSEN1 endoproteolysis and increased Aß secretion. Blood transcriptome and proteome profiling implicate early inflammatory and immune molecular dysregulation in juvenile PSEN1 mutant cynomolgus monkeys. Cerebrospinal fluid from juvenile PSEN1 mutant monkeys recapitulates early changes of AD-related pathological proteins (increased Aß42 and phosphorylated tau).

Ribonuclease 4 functions as an intestinal antimicrobial protein to maintain gut microbiota and metabolite homeostasis.

Antimicrobial proteins contribute to host-microbiota interactions and are associated with inflammatory bowel disease (IBD), but our understanding on antimicrobial protein diversity and functions remains incomplete. Ribonuclease 4 (Rnase4) is a potential antimicrobial protein with no known function in the intestines. Here we find that RNASE4 is expressed in intestinal epithelial cells (IEC) including Paneth and goblet cells, and is detectable in human and mouse stool. Results from Rnase4-deficient mice and recombinant protein suggest that Rnase4 kills Parasutterella to modulate intestinal microbiome, thereby enhancing indoleamine-2,3-dioxygenase 1 (IDO1) expression and subsequently kynurenic and xanthurenic acid production in IECs to reduce colitis susceptibility. Furthermore, deceased RNASE4 levels are observed in the intestinal tissues and stool from patients with IBD, correlating with increased stool Parasutterella. Our results thus implicate Rnase4 as an intestinal antimicrobial protein regulating gut microbiota and metabolite homeostasis, and as a potential diagnostic biomarker and therapeutic target for IBD.

Development and validation of a TAAbs and TAAs based non-invasive model for diagnosing lung cancer.

Background: Single Tumor-associated autoantibodies (TAAbs) and tumor-associated antigens (TAAs) have been found to have lower diagnostic efficacy in lung cancer. Our objective is to develop and validate a lung cancer prediction model that utilizes TAAbs and TAAs and to enhance the accuracy of lung cancer detection. Methods: 1830 subjects were randomly divided into training and validation sets at a 7:3 ratio for this study. Lasso regression analysis was used to remove collinear variables, whereas univariate logistic regression analysis was employed to identify potential independent risk factors for lung cancer. A diagnostic model was constructed using multivariate logistic analysis. The results were presented as a nomogram and assessed for various performance measures, including area under the curve, calibration curve, and decision curve analysis. Results: The diagnostic model was developed using gender, age, GAGE7, MAGE-A1, CA125, and CEA as variables. The training set had an AUC of 0.787, while the validation set had an AUC of 0.750. The calibration curves of the training and validation sets showed a strong agreement between anticipated and observed values. The nomogram performed better than any individual variable in both the training and validation sets in terms of net benefits for lung cancer detection, according to DCA analysis. Conclusions: This study proposes a diagnostic model for lung cancer that uses TAAbs and TAAs and incorporates individual characteristics. This model can be easily applied to personalized diagnosis.

Dietary fiber alleviates alcoholic liver injury via Bacteroides acidifaciens and subsequent ammonia detoxification.

The gut microbiota and diet-induced changes in microbiome composition have been linked to various liver diseases, although the specific microbes and mechanisms remain understudied. Alcohol-related liver disease (ALD) is one such disease with limited therapeutic options due to its complex pathogenesis. We demonstrate that a diet rich in soluble dietary fiber increases the abundance of Bacteroides acidifaciens (B. acidifaciens) and alleviates alcohol-induced liver injury in mice. B. acidifaciens treatment alone ameliorates liver injury through a bile salt hydrolase that generates unconjugated bile acids to activate intestinal farnesoid X receptor (FXR) and its downstream target, fibroblast growth factor-15 (FGF15). FGF15 promotes hepatocyte expression of ornithine aminotransferase (OAT), which facilitates the metabolism of accumulated ornithine in the liver into glutamate, thereby providing sufficient glutamate for ammonia detoxification via the glutamine synthesis pathway. Collectively, these findings uncover a potential therapeutic strategy for ALD involving dietary fiber supplementation and B. acidifaciens.

Cuproptosis-related gene DLAT is a biomarker of the prognosis and immune microenvironment of gastric cancer and affects the invasion and migration of cells.

OBJECTIVE: Cuproptosis is a novel cell death dependent on mitochondrial respiration and regulated by copper. This study aimed to investigate the cuproptosis-related gene DLAT potential value in gastric cancer (GC). METHODS: Bioinformatics was used to analyze DLAT expression. DLAT expression in GC cell lines was detected using qRT-PCR. Cell proliferation ability was assessed using CCK8 and cell cycle assay. Cell migration and invasion were assessed using wound healing and transwell assay. A prognostic assessment was performed through survival and Cox regression analysis. DLAT protein expression was analyzed through HPA immunohistochemistry. Biological functions and processes were analyzed through GO and KEGG enrichment analysis and PPI. Correlation with immune cell infiltration and immune checkpoint genes was analyzed for DLAT. RESULTS: DLAT expression was upregulated in GC tissues and cells and correlated with shorter survival for patients. Age, gender, histological typing, lymph node metastasis, and distant metastasis were identified as independent prognostic factors affecting OS in GC. DLAT protein was upregulated in GC. The biological functions and pathways enriched in DLAT were mainly linked to mitochondrial respiration and the TCA cycle. The expression of DLAT was found to be positively correlated with the infiltration of Th and Th2 immune cells and only positively correlated with the expression of the BTN2A1 immune checkpoint gene. CONCLUSION: DLAT has the potential to serve as a prognostic assessment factor in GC. The expression of DLAT was correlated with immune infiltration and tumor immune escape, providing a new target for immunotherapy of GC.

Temporal Dynamic Synchronous Functional Brain Network for Schizophrenia Classification and Lateralization Analysis.

Available evidence suggests that dynamic functional connectivity can capture time-varying abnormalities in brain activity in resting-state cerebral functional magnetic resonance imaging (rs-fMRI) data and has a natural advantage in uncovering mechanisms of abnormal brain activity in schizophrenia (SZ) patients. Hence, an advanced dynamic brain network analysis model called the temporal brain category graph convolutional network (Temporal-BCGCN) was employed. Firstly, a unique dynamic brain network analysis module, DSF-BrainNet, was designed to construct dynamic synchronization features. Subsequently, a revolutionary graph convolution method, TemporalConv, was proposed based on the synchronous temporal properties of features. Finally, the first modular test tool for abnormal hemispherical lateralization in deep learning based on rs-fMRI data, named CategoryPool, was proposed. This study was validated on COBRE and UCLA datasets and achieved 83.62% and 89.71% average accuracies, respectively, outperforming the baseline model and other state-of-the-art methods. The ablation results also demonstrate the advantages of TemporalConv over the traditional edge feature graph convolution approach and the improvement of CategoryPool over the classical graph pooling approach. Interestingly, this study showed that the lower-order perceptual system and higher-order network regions in the left hemisphere are more severely dysfunctional than in the right hemisphere in SZ, reaffirmings the importance of the left medial superior frontal gyrus in SZ. Our code was available at: https://github.com/swfen/Temporal-BCGCN.

Structural characterization and potential anti-tumor activity of a polysaccharide from the halophyte Salicornia bigelovii Torr.

Plant polysaccharides are highly potent bioactive molecules. Clarifying the structural composition and bioactivities of plant polysaccharides will provide insights into their structure-activity relationships. Therefore, herein, we identified a polysaccharide produced by Salicornia bigelovii Torr. and analyzed the structure and anti-tumor activity of its component, SabPS-1. SabPS-1 was 3.24 × 104 Da, primarily composed of arabinose (24.96 %), galactose (30.39 %), and galacturonic acid (23.20 %), rhamnose (6.21 %), xylose (4.99 %), glucuronic acid (3.12 %), mannuronic acid (1.75 %), mannose (1.69 %), glucose (1.54 %), fucose (1.12 %), and guluronic acid (1.03 %). The backbone of SabPS-1 was a â†’ 4)-ß-D-GalpA-(1→, →5)-α-L-Araf-(1→, and→4)-ß-D-Galp-(1 â†’ molecule with a branched chain of α-L-Araf-(1 â†’ connected to sugar residues of →3,6)-ß-D-Galp-(1 â†’ in the O-3 position. SabPS-1 induced apoptosis and inhibited the growth of HepG-2 cells, with viability of 47.90 ± 4.14 (400 µg/mL), indicating anti-tumor activity. Apoptosis induced by SabPS-1 may be associated with the differential regulation of caspase 3, caspase 8, Bax, and Bcl-2. To the best of our knowledge, this is the first study to investigate the principal structures and anti-tumor biological activities of SabPS-1. Our findings demonstrated the excellent anti-tumor properties of SabPS-1, which will aid in the development of anti-tumor drugs utilizing Salicornia bigelovii Torr.

Functional validation of EIF2AK4 (GCN2) missense variants associated with pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is a disorder with a large genetic component. Biallelic mutations of EIF2AK4, which encodes the kinase GCN2, are causal in two ultra-rare subtypes of PAH, pulmonary veno-occlusive disease and pulmonary capillary haemangiomatosis. EIF2AK4 variants of unknown significance have also been identified in patients with classical PAH, though their relationship to disease remains unclear. To provide patients with diagnostic information and enable family testing, the functional consequences of such rare variants must be determined, but existing computational methods are imperfect. We applied a suite of bioinformatic and experimental approaches to sixteen EIF2AK4 variants that had been identified in patients. By experimentally testing the functional integrity of the integrated stress response (ISR) downstream of GCN2, we determined that existing computational tools have insufficient sensitivity to reliably predict impaired kinase function. We determined experimentally that several EIF2AK4 variants identified in patients with classical PAH had preserved function and are therefore likely to be non-pathogenic. The dysfunctional variants of GCN2 that we identified could be subclassified into three groups: misfolded, kinase-dead, and hypomorphic. Intriguingly, members of the hypomorphic group were amenable to paradoxical activation by a type-1½ GCN2 kinase inhibitor. This experiment approach may aid in the clinical stratification of EIF2AK4 variants and potentially identify hypomorophic alleles receptive to pharmacological activation.

Material Engineering Strategies for Efficient Hydrogen Evolution Reaction Catalysts.

Water electrolysis, a key enabler of hydrogen energy production, presents significant potential as a strategy for achieving net-zero emissions. However, the widespread deployment of water electrolysis is currently limited by the high-cost and scarce noble metal electrocatalysts in hydrogen evolution reaction (HER). Given this challenge, design and synthesis of cost-effective and high-performance alternative catalysts have become a research focus, which necessitates insightful understandings of HER fundamentals and material engineering strategies. Distinct from typical reviews that concentrate only on the summary of recent catalyst materials, this review article shifts focus to material engineering strategies for developing efficient HER catalysts. In-depth analysis of key material design approaches for HER catalysts, such as doping, vacancy defect creation, phase engineering, and metal-support engineering, are illustrated along with typical research cases. A special emphasis is placed on designing noble metal-free catalysts with a brief discussion on recent advancements in electrocatalytic water-splitting technology. The article also delves into important descriptors, reliable evaluation parameters and characterization techniques, aiming to link the fundamental mechanisms of HER with its catalytic performance. In conclusion, it explores future trends in HER catalysts by integrating theoretical, experimental and industrial perspectives, while acknowledging the challenges that remain.

Comprehensive investigation on the dynamic changes of volatile metabolites in fresh scent green tea during processing by GC-E-Nose, GC-MS, and GC × GC-TOFMS.

Processing technology plays a crucial role in the formation of tea aroma. The dynamic variations in volatile metabolites across different processing stages of fresh scent green tea (FSGT) were meticulously tracked utilizing advanced analytical techniques such as GC-E-Nose, GC-MS, and GC × GC-TOFMS. A total of 244 volatile metabolites were identified by GC-MS and GC × GC-TOFMS, among which 37 volatile compounds were concurrently detected by both methods. Spreading and fixation stages were deemed as pivotal processes for shaping the volatile profiles in FSGT. Notably, linalool, heptanal, 2-pentylfuran, nonanal, ß-myrcene, hexanal, 2-heptanone, pentanal, 1-octen-3-ol, and 1-octanol were highlighted as primary contributors to the aroma profiles of FSGT by combining odor activity value assessment. Furthermore, lipid degradation and glycoside hydrolysis were the main pathways for aroma formation of FSGT. The results not only elucidate the intricate variations in volatile metabolites but also offer valuable insights into enhancing the processing techniques for improved aroma quality of green tea.

Hybrid dual mean-teacher network with double-uncertainty guidance for semi-supervised segmentation of magnetic resonance images.

Semi-supervised learning has made significant progress in medical image segmentation. However, existing methods primarily utilize information from a single dimensionality, resulting in sub-optimal performance on challenging magnetic resonance imaging (MRI) data with multiple segmentation objects and anisotropic resolution. To address this issue, we present a Hybrid Dual Mean-Teacher (HD-Teacher) model with hybrid, semi-supervised, and multi-task learning to achieve effective semi-supervised segmentation. HD-Teacher employs a 2D and a 3D mean-teacher network to produce segmentation labels and signed distance fields from the hybrid information captured in both dimensionalities. This hybrid mechanism allows HD-Teacher to utilize features from 2D, 3D, or both dimensions as needed. Outputs from 2D and 3D teacher models are dynamically combined based on confidence scores, forming a single hybrid prediction with estimated uncertainty. We propose a hybrid regularization module to encourage both student models to produce results close to the uncertainty-weighted hybrid prediction to further improve their feature extraction capability. Extensive experiments of binary and multi-class segmentation conducted on three MRI datasets demonstrated that the proposed framework could (1) significantly outperform state-of-the-art semi-supervised methods (2) surpass a fully-supervised VNet trained on substantially more annotated data, and (3) perform on par with human raters on muscle and bone segmentation task. Code will be available at https://github.com/ThisGame42/Hybrid-Teacher.

A high level of uric acid is associated with long-term adverse cardiovascular outcomes in patients who received fractional flow reserve with coronary intermediate stenosis.

BACKGROUND AND AIMS: The role of fractional flow reserve (FFR) in coronary intermediate lesions is widely recommended by guidelines. The effect of uric acid (UA) on cardiovascular events is also well known. However, the relationship between UA and long-term cardiovascular outcomes in patients who received FFR with intermediate lesions remains unknown. METHODS AND RESULTS: We retrospectively included 428 patients who underwent both coronary angiography (CAG) and FFR. Participants were stratified into two groups based on the median UA. The primary endpoint was the composite of major adverse cardiovascular and cerebrovascular events (MACCEs), including repeat revascularization, nonfatal stroke, nonfatal myocardial infarction, and all-cause death. A Cox proportional hazards model was utilized to analyze the association between UA and the prevalence of MACCEs. During a median follow-up of 5.8 years, a higher MACCEs rate occurred in the high UA group compared to the low UA group (16.8% vs. 5.1%, p log-rank<0.01). Elevated UA was independently linked to a higher incidence of MACCEs, whether UA was treated as a categorical or continuous variable (hazard ratio [HR] 2.76, 95% confidence interval [CI] 1.27-6.03 or HR 1.01, 95% CI 1.01-1.02). The restricted cubic spline (RCS) analysis illustrated that the HR for MACCEs increased with increasing UA. CONCLUSION: The present study demonstrates that UA is associated with MACCEs risk and suggests that UA is a reliable predictor of long-term cardiovascular events in coronary intermediate stenosis patients.

Ring-Contracted Artemisinin Derivatives as Novel CDK 4/6 Inhibitors: Synthesis and Anti-Breast Cancer Evaluation.

The endoperoxide group of artemisinins is universally accepted an essential group for their anti-cancer effects. In this study, a series of D-ring-contracted artemisinin derivatives were constructed by combining ring-contracted artemisinin core with fragments of functional heterocyclic molecules or classical CDK4/6 inhibitors to identify more efficacious breast cancer treatment agents. Twenty-six novel hybridized molecules were synthesized and characterized by HRMS, IR, 1H-NMR and 13C NMR. In antiproliferative activities and kinase inhibitory effects assays, we found that the antiproliferative effects of B01 were close to those of the positive control Palbociclib, with GI50 values of 4.87±0.23 µM and 9.97±1.44 µM towards T47D cells and MDA-MB-436 cells respectively. In addition, the results showed that B01 was the most potent compound against CDK6/cyclin D3 kinase, with an IC50 value of 0.135±0.041 µM, and its activity was approximately 1/3 of the positive control Palbociclib.

Relationships between professional identity, motivation, and innovative ability among nursing intern students: A cross-sectional study.

Objective: To explore the relationships among motivation, professional identity, and innovative ability of nursing intern students. Background: Professional identity and innovative ability are important for nursing students' core competitiveness and care quality. During the internship, nursing students integrate theoretical knowledge and practice, and have a rapid growth. Motivation is positively associated with professional identity and innovative ability. However, there are limited studies examining the professional identity, motivation, and innovative ability of nursing intern students. Design: A descriptive cross-sectional online study. Methods: Students in the nursing schools in southwest and central of China were included in this study and conducted from June to July 2022. A total of 474 nursing intern students were recruited from 16 nursing schools. Research data were collected with "Participants' Demographics Form", "the Professional Identity Questionnaire for Nursing Students", "the Revised Life Goals Questionnaire", and "the Revised Multidimensional Innovative Questionnaire". Independent-sample t-tests, one-way analysis of variance, correlation coefficients, and structural equation modeling were used in data analysis. This study adhered to the STROBE guidelines. Results: A significantly positive correlation was determined among the professional identity (67.55 ± 8.42), motivation (53.38 ± 5.54), and innovative ability (47.99 ± 5.46) of nursing students (r > 0.4, P < 0.001). Motivation had a mediating effect on professional identity and innovative ability (P = 0.003), accounting for 10.9% (0.075/0.689) of the total effect. Conclusions: There was a positive correlation among professional identity, motivation, and innovative ability. Developing motivation and professional identity can enhance nursing intern students' ability to innovate.

Triglyceride to high-density lipoprotein cholesterol ratio associated with long-term adverse clinical outcomes in patients deferred revascularization following fractional flow reserve.

BACKGROUND: Guidelines on coronary intermediate lesions strongly recommend deferred revascularization after detecting a normal fractional flow reserve (FFR). Researches about triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) on cardiovascular diseases has also been well conducted. However, the association of TG/HDL-C and long-term adverse clinical outcomes remains unknown for patients deferred revascularization following FFR. METHODS: This study retrospectively included 374 coronary artery disease (CAD) patients with non-significant coronary lesions diagnosed by coronary angiography (CAG) and FFR. The main outcome measure was the combination of major adverse cardiovascular and cerebrovascular events (MACCEs). All patients were categorized into three subgroups in terms of TG/HDL-C tertiles (T1 < 0.96, 0.96 ≤ T2 < 1.58, T3 ≥ 1.58). Three different Cox regression models were utilized to reveal the association between TG/HDL-C and prevalence of MACCEs. RESULTS: 47 MACCEs were recorded throughout a median monitoring period of 6.6 years. The Kaplan-Meier survival curves showed a higher MACCEs rate occurred in the higher TG/HDL-C group (5.6% vs. 12.9% vs. 19.4%, log-rank P < 0.01). After adjustment, patients in T3 suffered a 2.6-fold risk compared to the T1 group (T3 vs. T1: HR 2.55, 95% CI 1.05-6.21, P = 0.038; T2 vs. T1: HR 1.71, 95% CI 0.65-4.49, P = 0.075; P for trend = 0.001). The restricted cubic spline (RCS) analysis demonstrated that the HR for MACCEs rose as TG/HDL-C increased. Both the receiver operating characteristic (ROC) and time-dependent ROC proved the excellent predictive ability of TG/HDL-C. CONCLUSION: The study illustrates that TG/HDL-C correlates with the risk of MACCEs in CAD patients deferred revascularization following FFR. TG/HDL-C could serve as a dependable predictor of cardiovascular events over the long term in this population.

Mutations causing premature termination codons discriminate and generate cellular and clinical variability in HHT.

ABSTRACT: For monogenic diseases caused by pathogenic loss-of-function DNA variants, attention focuses on dysregulated gene-specific pathways, usually considering molecular subtypes together within causal genes. To better understand phenotypic variability in hereditary hemorrhagic telangiectasia (HHT), we subcategorized pathogenic DNA variants in ENG/endoglin, ACVRL1/ALK1, and SMAD4 if they generated premature termination codons (PTCs) subject to nonsense-mediated decay. In 3 patient cohorts, a PTC-based classification system explained some previously puzzling hemorrhage variability. In blood outgrowth endothelial cells (BOECs) derived from patients with ACVRL1+/PTC, ENG+/PTC, and SMAD4+/PTC genotypes, PTC-containing RNA transcripts persisted at low levels (8%-23% expected, varying between replicate cultures); genes differentially expressed to Bonferroni P < .05 in HHT+/PTC BOECs clustered significantly only to generic protein terms (isopeptide-bond/ubiquitin-like conjugation) and pulse-chase experiments detected subtle protein maturation differences but no evidence for PTC-truncated protein. BOECs displaying highest PTC persistence were discriminated in unsupervised hierarchical clustering of near-invariant housekeeper genes, with patterns compatible with higher cellular stress in BOECs with >11% PTC persistence. To test directionality, we used a HeLa reporter system to detect induction of activating transcription factor 4 (ATF4), which controls expression of stress-adaptive genes, and showed that ENG Q436X but not ENG R93X directly induced ATF4. AlphaFold accurately modeled relevant ENG domains, with AlphaMissense suggesting that readthrough substitutions would be benign for ENG R93X and other less rare ENG nonsense variants but more damaging for Q436X. We conclude that PTCs should be distinguished from other loss-of-function variants, PTC transcript levels increase in stressed cells, and readthrough proteins and mechanisms provide promising research avenues.

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study.

Background: Observational studies have linked exposure to fine (PM2.5) and coarse (PM10) particulate matter air pollution with adverse COVID-19 outcomes, including higher incidence and mortality. However, some studies questioned the effect of air pollution on COVID-19 susceptibility, raising questions about the causal nature of these associations. To address this, a less biased method like Mendelian randomization (MR) is utilized, which employs genetic variants as instrumental variables to infer causal relationships in observational data. Method: We performed two-sample MR analysis using public genome-wide association studies data. Instrumental variables correlated with PM2.5 concentration, PM2.5 absorbance, PM2.5-10 concentration and PM10 concentration were identified. The inverse variance weighted (IVW), robust adjusted profile score (RAPS) and generalized summary data-based Mendelian randomization (GSMR) methods were used for analysis. Results: IVW MR analysis showed PM2.5 concentration [odd ratio (OR) = 3.29, 95% confidence interval (CI) 1.48-7.35, P-value = 0.0036], PM2.5 absorbance (OR = 5.62, 95%CI 1.98-15.94, P-value = 0.0012), and PM10 concentration (OR = 3.74, 95%CI 1.52-9.20, P-value = 0.0041) increased the risk of COVID-19 severity after Bonferroni correction. Further validation confirmed PM2.5 absorbance was associated with heightened COVID-19 severity (OR = 6.05, 95%CI 1.99-18.38, P-value = 0.0015 for RAPS method; OR = 4.91, 95%CI 1.65-14.59, P-value = 0.0042 for GSMR method) and hospitalization (OR = 3.15, 95%CI 1.54-6.47, P-value = 0.0018 for RAPS method). No causal links were observed between particulate matter exposure and COVID-19 susceptibility. Conclusions: Our study established a causal relationship between smaller particle pollution, specifically PM2.5, and increased risk of COVID-19 severity and hospitalization. These findings highlight the importance of improving air quality to mitigate respiratory disease progression.

Serum fetuin-a and risk of thoracic aortic aneurysms: a two-sample mendelian randomization study.

Background: Recent studies have revealed a significant decrease in serum fetuin-A levels in atherosclerotic aneurysms, indicating that fetuin-A may play a protective role in the progression of arterial calcification. However, the specific mechanism behind this phenomenon remains unclear. We aimed to examine the association between fetuin-A levels in thoracic aortic aneurysms (TAAs) and risk of TAAs and to evaluate whether this association was causal. Methods: A total of 26 SNPs were selected as instrumental variables for fetuin-A in 9,055 participants of European ancestry from the CHARGE consortium, and their effects on thoracic aortic aneurysm and decreased descending thoracic aortic diameter were separately estimated in 353,049 and 39,688 individuals from FinnGen consortium. We used two-sample Mendelian randomization (MR) analysis to examine the causal association. At the same time, we employed various methods, including random-effects inverse variance weighting, weighted median, MR Egger regression, and MR PRESSO, to ensure the robustness of causal effects. We assessed heterogeneity using Cochran's Q value and examined horizontal pleiotropy through MR Egger regression and retention analysis. Results: Fetuin-A level was associated with a significantly decreasing risk of thoracic aortic aneurysm (odds ratio (OR) 0.64, 95% CI 0.47 - 0.87, P = 0.0044). Genetically predicted fetuin-A was also correlated with the decreased descending thoracic aortic diameter (ß = -0.086, standard error (SE) 0.036, P = 0.017). Conclusions: Serum fetuin-A level was negatively associated with risk of TTAs and correlated with the decreased descending thoracic aortic diameter. Mendelian randomization provides support for the potential causal relationship between fetuin-A and thoracic aortic aneurysm.

Amino acid profile alteration in age-related atrial fibrillation.

BACKGROUND: Amino acids (AAs) are one of the primary metabolic substrates for cardiac work. The correlation between AAs and both atrial fibrillation (AF) and aging has been documented. However, the relationship between AAs and age-related AF remains unclear. METHODS: Initially, the plasma AA levels of persistent AF patients and control subjects were assessed, and the correlations between AA levels, age, and other clinical indicators were explored. Subsequently, the age-related AF mouse model was constructed and the untargeted myocardial metabolomics was conducted to detect the level of AAs and related metabolites. Additionally, the gut microbiota composition associated with age-related AF was detected by a 16S rDNA amplicon sequencing analysis on mouse fecal samples. RESULTS: Higher circulation levels of lysine (Student's t-test, P = 0.001), tyrosine (P = 0.002), glutamic acid (P = 0.008), methionine (P = 0.008), and isoleucine (P = 0.014), while a lower level of glycine (P = 0.003) were observed in persistent AF patients. The feature AAs identified by machine learning algorithms were glutamic acid and methionine. The association between AAs and age differs between AF and control subjects. Distinct patterns of AA metabolic profiles were observed in the myocardial metabolites of aged AF mice. Aged AF mice had lower levels of Betaine, L-histidine, L-alanine, L-arginine, L-Pyroglutamic acid, and L-Citrulline compared with adult AF mice. Aged AF mice also presented a different gut microbiota pattern, and its functional prediction analysis showed AA metabolism alteration. CONCLUSION: This study provided a comprehensive network of AA disturbances in age-related AF from multiple dimensions, including plasma, myocardium, and gut microbiota. Disturbances of AAs may serve as AF biomarkers, and restoring their homeostasis may have potential benefits for the management of age-related AF.