Mitochondrial dysfunction gene expression, DNA methylation, and inflammatory cytokines interaction activate Alzheimer's disease: a multi-omics Mendelian randomization study.

BACKGROUND: Mitochondrial dysfunction (MD) is increasingly recognized as a key pathophysiological contributor in Alzheimer disease (AD). As differential MD genes expression may serve as either a causative factor or a consequence in AD, and expression of these genes could be influenced by epigenetic modifications or interact with inflammatory cytokines, hence, the precise role of MD in AD remains uncertain. METHODS: Meta-analysis of brain transcriptome datasets was conducted to pinpoint differentially expressed genes (DEGs) associated with MD in AD. We utilized three-step SMR to analyze the AD genome-wide association study summaries with expression quantitative trait loci (eQTLs) and DNA methylation QTLs from the blood and brain tissues, respectively. Through SMR and colocalization analysis, we further explored the interactions between brain eQTLs and inflammatory cytokines. RESULTS: Five datasets were meta-analyzed to prioritize 825 DEGs in AD from 1339 MD-related genes. Among these, seven genes from blood samples such as NDUFS8 and SPG7 and thirty-two genes from brain tissue including CLU and MAPT were identified as candidate AD-causal MD genes and regulated by methylation level. Furthermore, we revealed 13 MD gene expression-inflammatory pathway pairs involving LDLR, ACE and PTPMT1 along with interleukin-17C, interleukin-18 and hepatocyte growth factor. CONCLUSIONS: This study highlighted that the AD-causal MD genes could be regulated by epigenetic changes and interact with inflammatory cytokines, providing evidence for AD prevention and intervention.

Correlation Between Symptom Clusters and Self-Management Among Maintenance Haemodialysis Patients: A Cross-Sectional Study.

AIMS AND OBJECTIVES: The purpose of this study was to explore the relationship between symptom clusters and self-management among maintenance haemodialysis (MHD) patients. BACKGROUND: MHD patients experience disease progression and multiple symptom burdens that severely impact quality of life, and self-management of symptoms may significantly improve patient-reported outcomes. DESIGN: A cross-sectional study. METHODS: This cross-sectional descriptive study included 194 patients undergoing MHD. The patients were assessed using the Dialysis Symptom Index (DSI) and the Haemodialysis Self-Management Instrument (HD-SMI). We used descriptive analysis, exploratory factor analysis, Pearson's correlation analysis and linear regression analysis to examine (1) the level of individual self-management, (2) the presence of symptom clusters by symptom severity and (3) the correlation between symptom clusters and self-management behaviours. This study was conducted in accordance with the STROBE checklist. RESULTS: The top five most severe symptoms among the patients were itching, feeling tired or lack of energy, difficulty sleeping, dry mouth and dry skin. We identified five groups of symptoms: (1) poor sleep, (2) neuromuscular, (3) gastrointestinal, (4) skin irritation and (5) psychological. In the present study, MHD patients reported low to moderate levels of self-management behaviours (50.84 ± 10.56), and low self-management ability was correlated with greater severity of the five symptom clusters (p < 0.01). Linear regression analysis revealed that all five symptom clusters were included in the regression equation, explaining 30% of the total variance in self-management skills among MHD patients. CONCLUSION: Enhanced awareness of symptom clusters and comprehensive symptom management are necessary to improve patients' quality of life. CLINICAL RELEVANCE: Nursing practices should incorporate comprehensive symptom assessments to help patients develop effective self-management strategies to improve quality of life.

The impact of work-family conflict on Chinese women's fertility intention: the role of fertility attitude, income class, and child-rearing burden.

The struggle women face in balancing work and family roles is a significant factor contributing to the decline in their fertility intentions. Therefore, work-family conflict serves as a crucial determinant influencing women's fertility intentions. This study aims to explore the internal mechanism between work-family conflict and the fertility intentions of Chinese women, using data obtained from 334 questionnaires. Data analysis was conducted using Mplus 8.0. The following conclusions were drawn: (1) There is a negative correlation between work-family conflict and women's fertility intentions. (2) Fertility attitudes play a mediating role in the relationship between work-family conflict and women's fertility intentions. (3) The relationship between work-family conflict and women's fertility intentions is moderated by income class. (4) The relationship between work-family conflict and women's fertility intentions is moderated by women's child-rearing burden. The findings of this study provide a foundation for governments at all levels to formulate population policies.

Assist me or replace me? Uncovering the influence of AI awareness on employees' counterproductive work behaviors.

Objective: Drawing on the conservation of resources theory (COR), the research aims to reveal the influence of artificial intelligence (AI) awareness on employees' mental health and behaviors, particularly examining whether and how employees' AI awareness impacts their counterproductive work behaviors (CWB) in human-intelligence collaborations. Methods: Data was collected from 327 Chinese employees who collaborated with AI in sales, manufacturing, logistics, and other industries. The measurement instruments included scales for AI awareness, psychological contract (PC), emotional exhaustion (EE), and counterproductive work behavior (CWB). We used Hayes's PROCESS macro to analyze the data. Findings: AI awareness had a significant positive impact on CWB (ß = 0.448, p < 0.01). PC and EE play a role as partial mediators in the relationship between AI awareness and CWB. The mediating pathways consist of three sequences: "AI awareness → PC → CWB," "AI awareness → EE → CWB" and "AI awareness → PC → EE → CWB," with the respective contributions to the overall effect amounting to 8.04, 18.53, and 4.91%. Discussion: Our research contributes to the study of AI in the management field by elucidating the relationship between AI awareness and CWB, as well as the mediating mechanisms of this relationship, which enriches the literature on CWB and expands the understanding of the associations between AI and CWB.

Genome-Wide Association Study on Body Conformation Traits in Xinjiang Brown Cattle.

Body conformation traits are linked to the health, longevity, reproductivity, and production performance of cattle. These traits are also crucial for herd selection and developing new breeds. This study utilized pedigree information and phenotypic (1185 records) and genomic (The resequencing of 496 Xinjiang Brown cattle generated approximately 74.9 billion reads.) data of Xinjiang Brown cattle to estimate the genetic parameters, perform factor analysis, and conduct a genome-wide association study (GWAS) for these traits. Our results indicated that most traits exhibit moderate to high heritability. The principal factors, which explained 59.12% of the total variance, effectively represented body frame, muscularity, rump, feet and legs, and mammary system traits. Their heritability estimates range from 0.17 to 0.73, with genetic correlations ranging from -0.53 to 0.33. The GWAS identified 102 significant SNPs associated with 12 body conformation traits. A few of the SNPs were located near previously reported genes and quantitative trait loci (QTLs), while others were novel. The key candidate genes such as LCORL, NCAPG, and FAM184B were annotated within 500 Kb upstream and downstream of the significant SNPs. Therefore, factor analysis can be used to simplify multidimensional conformation traits into new variables, thus reducing the computational burden. The identified candidate genes from GWAS can be incorporated into the genomic selection of Xinjiang Brown cattle, enhancing the reliability of breeding programs.

Potential diagnostic value of circulating miRNAs in HFrEF and bioinformatics analysis.

Background: Few studies have compared the performances of those reported miRNAs as biomarkers for heart failure with reduced EF (HFrEF) in a population at high risk. The purpose of this study is to investigate comprehensively the performance of those miRNAs as biomarkers for HFrEF. Methods: By using bioinformatics methods, we also examined these miRNAs' target genes and possible signal transduction pathways. We collected serum samples from patients with HFrEF at Zhongshan Hospital. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of those miRNAs as biomarkers for HFrEF. miRWALK2.0, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to predict the target genes and pathways of selected miRNAs. Results: The study included 48 participants, of whom 30 had HFrEF and 18 had hypertension with normal left ventricular ejection fraction (LVEF). MiR-378, miR-195-5p were significantly decreased meanwhile ten miRNAs were remarkably elevated (miR-21-3p, miR-21-5p, miR-106-5p, miR-23a-3p, miR-208a-3p, miR-1-3p, miR-126-5p, miR-133a-3p, miR-133b, miR-223-3p) in the serum of the HFrEF group. Conclusion: The combination of miR 133a-3p, miR 378, miR 1-3p, miR 106b-5p, and miR 133b has excellent diagnostic performance for HFrEF, and there is a throng of mechanisms and pathways by which regulation of these miRNAs may affect the risk of HFrEF.

Machine learning identifies a 5-serum cytokine panel for the early detection of chronic atrophy gastritis patients.

BACKGROUND: Chronic atrophy gastritis (CAG) is a high-risk pre-cancerous lesion for gastric cancer (GC). The early and accurate detection and discrimination of CAG from benign forms of gastritis (e.g. chronic superficial gastritis, CSG) is critical for optimal management of GC. However, accurate non-invasive methods for the diagnosis of CAG are currently lacking. Cytokines cause inflammation and drive cancer transformation in GC, but their utility as a diagnostic for CAG is poorly characterized. METHODS: Blood samples were collected, and 40 cytokines were quantified using a multiplexed immunoassay from 247 patients undergoing screening via endoscopy. Patients were divided into discovery and validation sets. Each cytokine importance was ranked using the feature selection algorithm Boruta. The cytokines with the highest feature importance were selected for machine learning (ML), using the LightGBM algorithm. RESULTS: Five serum cytokines (IL-10, TNF-α, Eotaxin, IP-10 and SDF-1a) that could discriminate between CAG and CSG patients were identified and used for predictive model construction. This model was robust and could identify CAG patients with high performance (AUC = 0.88, Accuracy = 0.78). This compared favorably to the conventional approach using the PGI/PGII ratio (AUC = 0.59). CONCLUSION: Using state-of-the-art ML and a blood-based immunoassay, we developed an improved non-invasive screening method for the detection of precancerous GC lesions. FUNDING: Supported in part by grants from: Jiangsu Science and Technology Project (no. BK20211039); Top Talent Support Program for young and middle-aged people of Wuxi Health Committee (BJ2023008); Medical Key Discipline Program of Wuxi Health Commission (ZDXK2021010), Wuxi Science and Technology Bureau Project (no. N20201004); Scientific Research Program of Wuxi Health Commission (Z202208, J202104).

The diagnostic value of serum trefoil factor 3 and pepsinogen combination in chronic atrophic gastritis: a retrospective study based on a gastric cancer screening cohort in the community population.

BACKGROUND: Chronic atrophic gastritis (CAG) is an important precursor of gastric cancer(GC), and there is currently a lack of reliable non-invasive diagnostic markers. This study aims to find a biomarker for non-invasive screening of CAG in the community. METHODS: A total of 540 individuals were enrolled (test set = 385, validation set = 155). ROC curve analysis was used to evaluate the diagnostic significance of serum Trefoil Factor 3 (TFF3) alone or in combination with pepsinogen (PG) for CAG in the test and validation set. Furthermore, the diagnostic value of TFF3 and PG in different Helicobacter pylori (H. pylori) infection states was studied. RESULTS: When compared with chronic superficial gastritis (CSG), the expression level of serum TFF3 in the CAG was higher (27 ng/ml vs 19.61, P < 0.001). ROC curve analysis found that the sensitivity, specificity, and area under the curve (AUC) of CAG diagnosis using serum TFF3 alone at the optimal cut-off value of 26.55 ng/ml were 0.529, 0.87, and 0.739, respectively. When TFF3 was combined with The Ratio of PGI to PGII (PGR), the AUC and specificity reached 0.755 and 0.825, respectively. TFF3 individual or combined with PGR had good predictive value, especially in the H. Pylori negative patients. CONCLUSION: TFF3 combined with PGR can effectively predict CAG, especially in patients with H. pylori negative.

Streamlined process for effective and strand-selective mitochondrial base editing using mitoBEs.

Mitochondrial base editing tools hold great promise for the investigation and treatment of mitochondrial diseases. Mitochondrial DNA base editors (mitoBEs) integrate a programmable transcription-activator-like effector (TALE) protein with single-stranded DNA deaminase (TadA8e-V106W, APOBEC1, etc.) and nickase (MutH, Nt.BspD6I(C), etc.) to achieve heightened precision and efficiency in mitochondrial base editing. This innovative mitochondrial base editing tool exhibits a number of advantages, including strand-selectivity for editing, high efficiency, and the capacity to perform diverse types of base editing on the mitochondrial genome by employing various deaminases. In this context, we provide a detailed experimental protocol for mitoBEs to assist others in achieving proficient mitochondrial base editing.

Multiplex PCR System for the Diagnosis of Plague.

The plague caused by Yersinia pestis has a high case fatality rate. It is often transmitted from person to person through mosquito bites, causing serious disease transmission. Due to its clinical symptoms being very similar to influenza, it is difficult to detect by people. Traditional detection methods for Y. pestis mainly include bacterial culture and serological identification, which are cumbersome and require high experimental conditions. Therefore, a fast and effective detection method is very important. At present, polymerase chain reaction (PCR) is one of the methods for rapid detection of Y. pestis. In this review, we focus on the application, advantages, and disadvantages of multiplex PCR technology in clinical detection.

A Pan-Cancer Analysis of the Oncogenic Role of Methyltransferase-Like 1 in Human Tumors.

BACKGROUND AND OBJECT: Although emerging cell- or animal-based evidence supports the relationship between methyltransferase-like 1 (METTL1) and cancers, no pan-cancer analysis is available. METHODS: We thus first explored the potential oncogenic roles of METTL1 across 33 tumors based on the datasets of The Cancer Genome Atlas and Gene Expression Omnibus. RESULTS: METTL1 is highly expressed in most cancers, and distinct associations exist between METTL1 expression and prognosis of tumor patients. METTL1 level is related with the dendritic and B-cell infiltration levels in most tumors. Moreover, RNA processing- and RNA metabolism-associated functions were involved in the functional mechanisms of METTL1. CONCLUSION: Our pan-cancer study offers a relatively comprehensive understanding of the oncogenic roles of METTL1 across different tumors.

Cardiac magnetic resonance imaging for discrimination of hypertensive heart disease and hypertrophic cardiomyopathy: a systematic review and meta-analysis.

Introduction: Differentiating hypertensive heart disease (HHD) from hypertrophic cardiomyopathy (HCM) is crucial yet challenging due to overlapping clinical and morphological features. Recent studies have explored the use of various cardiac magnetic resonance (CMR) parameters to distinguish between these conditions, but findings have remained inconclusive. This study aims to identify which CMR parameters effectively discriminate between HHD and HCM and to investigate their underlying pathophysiological mechanisms through a meta-analysis. Methods: The researchers conducted a systematic and comprehensive search for all studies that used CMR to discriminate between HHD and HCM and calculated the Hedges'g effect size for each of the included studies, which were then pooled using a random-effects model and tested for the effects of potential influencing variables through subgroup and regression analyses. Results: In this review, 26 studies encompassing 1,349 HHD and 1,581 HCM cases were included for meta-analysis. Analysis revealed that HHD showed a significant lower in T1 mapping (g = -0.469, P < 0.001), extracellular volume (g = -0.417, P = 0.024), left ventricular mass index (g = -0.437, P < 0.001), and maximal left ventricular wall thickness (g = -2.076, P < 0.001), alongside a significant higher in end-systolic volume index (g = 0.993, P < 0.001) and end-diastolic volume index (g = 0.553, P < 0.001), compared to HCM. Conclusion: This study clearly demonstrates that CMR parameters can effectively differentiate between HHD and HCM. HHD is characterized by significantly lower diffuse interstitial fibrosis and myocardial hypertrophy, along with better-preserved diastolic function but lower systolic function, compared to HCM. The findings highlight the need for standardized CMR protocols, considering the significant influence of MRI machine vendors, post-processing software, and study regions on diagnostic parameters. These insights are crucial for improving diagnostic accuracy and optimizing treatment strategies for patients with HHD and HCM. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023470557, PROSPERO (CRD42023470557).

Identification and Prognostic Value of m6A-Related Genes in Glioblastoma.

BACKGROUND: N6-methyladenosine (m6A) is one of the most common forms of mRNA modification, which is dynamically regulated by the m6A-related genes; however, its effect in glioblastoma (GBM) is still unknown. OBJECTIVE: We sought to investigate the association between m6A-related genes (m6A-RGs) and GBM. METHODS: Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The m6A-RGs were identified from differently expressed genes, and COX and lasso regression models were applied to locate the prognosis-related genes. RESULTS: We identified 15 out of 19 m6A-RGs differentially expressed between GBM and nontumor tissues. We identified two subgroups of GBM (clusters 1 and 2) by applying consensus clustering. Compared with the cluster 1 subgroup, the cluster 1 subgroup correlates with a poorer prognosis, and most of the 19 m6A-RGs are higher expressed in cluster 1. Through univariate Cox and lasso regression model, we identified three m6A-RGs, namely HNRNPC, ALKBH5, and FTO, which were used to construct a Cox regression risk model to predict the prognosis of GBM patients. CONCLUSION: We identified a valuable m6A model for predicting the prognosis of GBM patients, which can provide useful epigenetic biomarkers.

Alternative Splicing in Glioblastoma and its Clinical Implication in Outcome Prediction.

BACKGROUND AND OBJECTIVE: Alternative splicing (AS) offers an important mechanism to form protein polymorphism. A growing body of evidence indicates the correlation between splicing abnormality and carcinoma. Nevertheless, an overall analysis of AS signatures in glioblastoma (GBM) is absent and urgently needed. METHODS: TCGA SpliceSea data was used to evaluate the AS profiles and further classified into different AS events. The survival analysis was based on these AS events, and AS-related genes were identified and performed with enrichment analysis. At last, the splicing factor-AS regulatory network was established in Cytoscape. RESULTS: Eight hundred forty-two splicing events were confirmed as prognostic molecular events in GBM. Furthermore, the final prognostic signature constructed by seven AS events gave good result with an area under the curve (AUC) of receiver operating characteristic (ROC) curve up to 0.935 for five years, showing high potency in predicting patients' outcome. We built the splicing regulatory network to show the internal relationship of splicing events in GBM. PC4 and SFRS1 interacting protein 1 (PSIP1) and histone H4 acetylation may play a significant part in the prognosis induced by splicing events. CONCLUSION: In our study, a high-efficiency prognostic prediction model was built for GBM patients based on AS events, which could become potential prognostic biomarkers for GBM. Meanwhile, PSIP1 may be a critical target for pharmaceutical treatment.

Ultrasound-based radiomics nomogram for predicting axillary lymph node metastasis in invasive breast cancer.

OBJECTIVE: To develop a nomogram for predicting axillary lymph node metastasis (ALNM) in patients with invasive breast cancer. METHODS: We included 307 patients with clinicopathologically confirmed invasive breast cancer. The cohort was divided into a training group (n=215) and a validation group (n=92). Ultrasound images were used to extract radiomics features. The least absolute shrinkage and selection operator (LASSO) algorithm helped select pertinent features, from which Radiomics Scores (Radscores) were calculated using the LASSO regression equation. We developed three logistic regression models based on Radscores and 2D image features, and assessed the models' performance in the validation group. A nomogram was created from the best-performing model. RESULTS: In the training set, the area under the curve (AUC) for the Radscore model, 2D feature model, and combined model were 0.76, 0.85, and 0.88, respectively. In the validation set, the AUCs were 0.71, 0.78, and 0.83, respectively. The combined model demonstrated good calibration and promising clinical utility. CONCLUSION: Our ultrasound-based radiomics nomogram can accurately and non-invasively predict ALNM in breast cancer, suggesting potential clinical applications to optimize surgical and medical strategies.

DNA methylation patterns in the peripheral blood of Xinjiang brown cattle with variable somatic cell counts.

The use of wide-ranging dairy herd improvement (DHI) measurements has resulted in the investigation of somatic cell count (SCC) and the identification of many genes associated with mastitis resistance. In this study, blood samples of Xinjiang brown cattle with different SCCs were collected, and genome-wide DNA methylation was analyzed by MeDIP-seq. The results showed that peaks were mostly in intergenic regions, followed by introns, exons, and promoters. A total of 1,934 differentially expressed genes (DEGs) associated with mastitis resistance in Xinjiang brown cattle were identified. The enrichment of differentially methylated CpG islands of the TRAPPC9 and CD4 genes was analyzed by bisulfate genome sequencing. The methylation rate of differentially methylated CpGs was higher in the TRAPPC9 gene of cattle with clinical mastitis (mastitis group) compared with healthy cattle (control group), while methylation of differentially methylated CpGs was significantly lower in CD4 of the mastitis group compared with the control group. RT-qRCR analysis showed that the mastitis group had significantly reduced expression of CD4 and TRAPPC9 genes compared to the control group (p < 0.05). Furthermore, Mac-T cells treated with lipopolysaccharide and lipoteichoic acid showed significant downregulation of the TRAPPC9 gene in the mastitis group compared with the control group. The identified epigenetic biomarkers provide theoretical reference for treating cow mastitis, breeding management, and the genetic improvement of mastitis resistance in Xinjiang brown cattle.

RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer (RIGAIN): a study protocol for a multicentre, open-label, randomised controlled prospective, phase III trial.

INTRODUCTION: Postoperative radiotherapy in patients with breast cancer with one to three lymph node metastases, particularly within the pT1-2N1M0 cohort with a low clinical risk of local-regional recurrence (LRR), has incited a discourse surrounding personalised treatment strategies. Multigene testing for Recurrence Index (RecurIndex) model capably differentiates patients based on their level of LRR risk. This research aims to validate whether a more aggressive treatment approach can enhance clinical outcomes in N1 patients who possess a clinically low risk of LRR, yet a high RecurIndex-determined risk of LRR. Specifically, this entails postoperative whole breast irradiation combined with regional lymph node irradiation (RNI) following breast-conserving surgery or chest wall irradiation with RNI after mastectomy. METHODS AND ANALYSIS: The RIGAIN (RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer) Study is a multicentre, prospective, randomised, open-label, phase III clinical trial that is being conducted in China. In this study, patients with low clinical LRR risk but high RecurIndex-LRR risk are randomly assigned in a 1:1 ratio to the experimental group or the control group. In the experimental group, RNI is performed and the control group omits RNI. Efficacy and safety analyses will be conducted, enrolling a total of 540 patients (270 per group). The primary endpoint is invasive disease-free survival, and secondary endpoints include any first recurrence, LRR-free survival, distant metastasis-free survival, recurrence-free survival, overall survival, disease-free survival, breast cancer-specific mortality and assessment of patient quality of life. The study began in April 2023 and with a follow-up period of 60 months after the last participant completes radiation therapy. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University (SYSKY-2022-097-02, V.3.1). It adheres to the Helsinki Declaration and Good Clinical Practice. Research findings will be submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04069884.

Programmable DNA pyrimidine base editing via engineered uracil-DNA glycosylase.

DNA base editing technologies predominantly utilize engineered deaminases, limiting their ability to edit thymine and guanine directly. In this study, we successfully achieve base editing of both cytidine and thymine by leveraging the translesion DNA synthesis pathway through the engineering of uracil-DNA glycosylase (UNG). Employing structure-based rational design, exploration of homologous proteins, and mutation screening, we identify a Deinococcus radiodurans UNG mutant capable of effectively editing thymine. When fused with the nickase Cas9, the engineered DrUNG protein facilitates efficient thymine base editing at endogenous sites, achieving editing efficiencies up to 55% without enrichment and exhibiting minimal cellular toxicity. This thymine base editor (TBE) exhibits high editing specificity and significantly restores IDUA enzyme activity in cells derived from patients with Hurler syndrome. TBEs represent efficient, specific, and low-toxicity approaches to base editing with potential applications in treating relevant diseases.