Association between alcohol consumption and sleep traits: observational and mendelian randomization studies in the UK biobank.

Previous studies have shown that excessive alcohol consumption is associated with poor sleep. However, the health risks of light-to-moderate alcohol consumption in relation to sleep traits (e.g., insomnia, snoring, sleep duration and chronotype) remain undefined, and their causality is still unclear in the general population. To identify the association between alcohol consumption and multiple sleep traits using an observational and Mendelian randomization (MR) design. Observational analyses and one-sample MR (linear and nonlinear) were performed using clinical and individual-level genetic data from the UK Biobank (UKB). Two-sample MR was assessed using summary data from genome-wide association studies from the UKB and other external consortia. Phenotype analyses were externally validated using data from the National Health and Nutrition Examination Survey (2017-2018). Data analysis was conducted from January 2022 to October 2022. The association between alcohol consumption and six self-reported sleep traits (short sleep duration, long sleep duration, chronotype, snoring, waking up in the morning, and insomnia) were analysed. This study included 383,357 UKB participants (mean [SD] age, 57.0 [8.0] years; 46% male) who consumed a mean (SD) of 9.0 (10.0) standard drinks (one standard drink equivalent to 14 g of alcohol) per week. In the observational analyses, alcohol consumption was significantly associated with all sleep traits. Light-moderate-heavy alcohol consumption was linearly linked to snoring and the evening chronotype but nonlinearly associated with insomnia, sleep duration, and napping. In linear MR analyses, a 1-SD (14 g) increase in genetically predicted alcohol consumption was associated with a 1.14-fold (95% CI, 1.07-1.22) higher risk of snoring (P < 0.001), a 1.28-fold (95% CI, 1.20-1.37) higher risk of evening chronotype (P < 0.001) and a 1.24-fold (95% CI, 1.13-1.36) higher risk of difficulty waking up in the morning (P < 0.001). Nonlinear MR analyses did not reveal significant results after Bonferroni adjustment. The results of the two-sample MR analyses were consistent with those of the one-sample MR analyses, but with a slightly attenuated overall estimate. Our findings suggest that even low levels of alcohol consumption may affect sleep health, particularly by increasing the risk of snoring and evening chronotypes. The negative effects of alcohol consumption on sleep should be made clear to the public in order to promote public health.

Strong effect-correlated electrochemical CO2 reduction.

Electrochemical CO2 reduction (ECR) holds great potential to alleviate the greenhouse effect and our dependence on fossil fuels by integrating renewable energy for the electrosynthesis of high-value fuels from CO2. However, the high thermodynamic energy barrier, sluggish reaction kinetics, inadequate CO2 conversion rate, poor selectivity for the target product, and rapid electrocatalyst degradation severely limit its further industrial-scale application. Although numerous strategies have been proposed to enhance ECR performances from various perspectives, scattered studies fail to comprehensively elucidate the underlying effect-performance relationships toward ECR. Thus, this review presents a comparative summary and a deep discussion with respect to the effects strongly-correlated with ECR, including intrinsic effects of materials caused by various sizes, shapes, compositions, defects, interfaces, and ligands; structure-induced effects derived from diverse confinements, strains, and fields; electrolyte effects introduced by different solutes, solvents, cations, and anions; and environment effects induced by distinct ionomers, pressures, temperatures, gas impurities, and flow rates, with an emphasis on elaborating how these effects shape ECR electrocatalytic activities and selectivity and the underlying mechanisms. In addition, the challenges and prospects behind different effects resulting from various factors are suggested to inspire more attention towards high-throughput theoretical calculations and in situ/operando techniques to unlock the essence of enhanced ECR performance and realize its ultimate application.

Development and experimental validation of a machine learning-based disulfidptosis-related ferroptosis score for hepatocellular carcinoma.

Disulfidoptosis and ferroptosis are two distinct programmed cell death pathways that have garnered considerable attention due to their potential as therapeutic targets. However, despite their significance of these pathways, the role of disulfidoptosis-related ferroptosis genes in hepatocellular carcinoma (HCC) remains unclear. In this study, we employed a comprehensive approach that utilized various sophisticated techniques such as Pearson analysis, differential analysis, uniCox regression, lasso, ranger, and multivariable Cox regression to develop the disulfidoptosis-related ferroptosis (DRF) score. We then classified patients with HCC into high- and low-score groups to examine the association between the DRF score and various outcomes, including prognosis, functional enrichment, immune infiltration, immunotherapy, TACE sensitivity, drug sensitivity, and single-cell level function. Finally, we conducted in vitro experiments to validate the function of KIF20A. Our analysis revealed that KIF20A, G6PD, SLC7A11, and SLC2A1 were integral to constructing the DRF score. Our findings showed that patients with low DRF scores had significantly better prognoses and were more responsive to immunotherapy, TACE, and chemotherapy than those with high DRF scores. Based on our results obtained from bulk RNA-seq, single-cell RNA-seq, and in vitro experiments, we identified the cell cycle pathway as the primary distinguished factor between high-score and low-score groups. This study sheds light on the contribution of disulfidoptosis-related ferroptosis genes to the development and progression of HCC. The information gleaned from this study can be leveraged to improve our understanding of their potential as therapeutic targets for HCC treatment.

CD133 expression is associated with less DNA repair, better response to chemotherapy and survival in ER-positive/HER2-negative breast cancer.

PURPOSE: CD133, a cancer stem cells (CSC) marker, has been reported to be associated with treatment resistance and worse survival in triple-negative breast cancer (BC). However, the clinical relevance of CD133 expression in ER-positive/HER2-negative (ER + /HER2-) BC, the most abundant subtype, remains unknown. METHODS: The BC cohorts from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1904) and The Cancer Genome Atlas (TCGA, n = 1065) were used to obtain biological variables and gene expression data. RESULTS: Epithelial cells were the exclusive source of CD133 gene expression in a bulk BC. CD133-high ER + /HER2- BC was associated with CD24, NOTCH1, DLL1, and ALDH1A1 gene expressions, as well as with WNT/ß-Catenin, Hedgehog, and Notch signaling pathways, all characteristic for CSC. Consistent with a CSC phenotype, CD133-low BC was enriched with gene sets related to cell proliferation, such as G2M Checkpoint, MYC Targets V1, E2F Targets, and Ki67 gene expression. CD133-low BC was also linked with enrichment of genes related to DNA repair, such as BRCA1, E2F1, E2F4, CDK1/2. On the other hand, CD133-high tumors had proinflammatory microenvironment, higher activity of immune cells, and higher expression of genes related to inflammation and immune response. Finally, CD133-high tumors had better pathological complete response after neoadjuvant chemotherapy in GSE25066 cohort and better disease-free survival and overall survival in both TCGA and METABRIC cohorts. CONCLUSION: CD133-high ER + /HER2- BC was associated with CSC phenotype such as less cell proliferation and DNA repair, but also with enhanced inflammation, better response to neoadjuvant chemotherapy and better prognosis.

Emerging Nanomaterials toward Uranium Extraction from Seawater: Recent Advances and Perspectives.

Nuclear energy holds great potential to facilitate the global energy transition and alleviate the increasing environmental issues due to its high energy density, stable energy output, and carbon-free emission merits. Despite being limited by the insufficient terrestrial uranium reserves, uranium extraction from seawater (UES) can offset the gap. However, the low uranium concentration, the complicated uranium speciation, the competitive metal ions, and the inevitable marine interference remarkably affect the kinetics, capacity, selectivity, and sustainability of UES materials. To date, massive efforts have been made with varying degrees of success to pursue a desirable UES performance on various nanomaterials. Nevertheless, comprehensive and systematic coverage and discussion on the emerging UES materials presenting the fast-growing progress of this field is still lacking. This review thus challenges this position and emphatically focuses on this topic covering the current mainstream UES technologies with the emerging UES materials. Specifically, this review elucidates the causality between the physiochemical properties of UES materials induced by the intellectual design strategies and the UES performances and further dissects the relationships of materials-properties-activities and the corresponding mechanisms in depth. This review is envisaged to inspire innovative ideas and bring technical solutions for developing technically and economically viable UES materials.

Confinement loss prediction in diverse anti-resonant fibers through neural networks.

In this work, genetic algorithm (GA) is employed to optimize convolutional neural networks (CNNs) for predicting the confinement loss (CL) in anti-resonant fibers (ARFs), achieving a prediction accuracy of CL magnitude reached 90.6%, which, to the best of our knowledge, represents the highest accuracy to date and marks the first instance of using a single model to predict CL across diverse ARF structures. Different from the previous definition of ARF structures with parameter groups, we use anchor points to describe these structures, thus eliminating the differences in expression among them. This improvement allows the model to gain insight into the specific structural characteristics, thereby enhancing its generalization capabilities. Furthermore, we demonstrate a particle swarm optimization algorithm (PSO), driven by our model, for the design of ARFs, validating the model's robust predictive accuracy and versatility. Compared with the calculation of CL by finite element method (FEM), this model significantly reduces the cost time, and provides a speed-up method in fiber design driven by numerical calculation.

Efficacy of prophylactic antibiotics for the prevention of neutropenic fever in patients with multiple myeloma receiving high-dose cyclophosphamide for stem cell mobilization.

High-dose cyclophosphamide (HD-Cy) (3 g/m2) plus granulocyte colony-stimulating factor (G-CSF) is a very effective regimen for peripheral blood stem cell (PBSC) mobilization. Unfortunately, it is associated with an increased risk of neutropenic fever (NF). We analyzed the effect of NF on PBSC apheresis results and the efficacy of prophylactic antibiotics for the prevention of NF associated with HD-Cy plus G-CSF for PBSC mobilization in patients with newly diagnosed multiple myeloma (MM). First, patients were divided into NF ( +) and NF ( -) groups according to whether they suffered from NF during mobilization. Second, we divided patients into an antibiotic prophylaxis group and a nonantibiotic prophylaxis group according to whether antibiotic prophylaxis was used during the mobilization period. Our study showed that NF( +) patients (n = 44) had lower CD34 + cell dose collection (median 2.60 versus 5.34 × 106/kg, P < 0.001) and slower neutrophil engraftment and platelet engraftment (median 11 versus 10 days, P = 0.002, and median 13 versus 11 days, P = 0.043, respectively) than NF( -) patients (n = 234). Of note, the nonantibiotic prophylaxis group patients (n = 30) had a 26.7% incidence of NF. In the patients receiving antibiotic prophylaxis (n = 227), the incidence was reduced to 9.3% (P = 0.01). The antibiotic prophylaxis patients had higher CD34 + cell collection (median 5.41 versus 2.27 × 106/kg, P < 0.001) and lower hospitalization cost of mobilization ($ median 3108.02 versus 3702.39, p = 0.012). Thus, our results demonstrate that NF is associated with lower CD34 + cell collection and that antibiotic prophylaxis can reduce the incidence of NF and improve stem cell mobilization and collection outcomes, which reduces the hospitalization cost of mobilization.

M2 macrophage-derived exosomes carry miR-142-3p to restore the differentiation balance of irradiated BMMSCs by targeting TGF-ß1.

Radiotherapy is essential to cancer treatment, while it inevitably injures surrounding normal tissues, and bone tissue is one of the most common sites prone to irradiation. Bone marrow mesenchymal stem cells (BMMSCs) are sensitive to irradiation and the irradiated dysfunction of BMMSCs may be closely related to irradiation-induced bone damage. Macropahges play important role in regulating stem cell function, bone metabolic balance and irradiation response, but the effects of macrophages on irradiated BMMSCs are still unclear. This study aimed to investigate the role of macrophages and macrophage-derived exosomes in restoring irradiated BMMSCs function. The effects of macrophage conditioned medium (CM) and macrophage-derived exosomes on osteogenic and fibrogenic differentiation capacities of irradiated BMMSCs were detected. The key microribonucleic acids (miRNAs) and targeted proteins in exosomes were also determined. The results showed that irradiation significantly inhibited the proliferation of BMMSCs, and caused differentiation imbalance of BMMSCs, with decreased osteogenic differentiation and increased fibrogenic differentiation. M2 macrophage-derived exosomes (M2D-exos) inhibited the fibrogenic differentiation and promoted the osteogenic differentiation of irradiated BMMSCs. We identified that miR-142-3p was significantly overexpressed in M2D-exos and irradiated BMMSCs treated with M2D-exos. After inhibition of miR-142-3p in M2 macrophage, the effects of M2D-exos on irradiated BMMSCs differentiation were eliminated. Furthermore, transforming growth factor beta 1 (TGF-ß1), as a direct target of miR-142-3p, was significantly decreased in irradiated BMMSCs treated with M2D-exos. This study indicated that M2D-exos could carry miR-142-3p to restore the differentiation balance of irradiated BMMSCs by targeting TGF-ß1. These findings pave a new way for promising and cell-free method to treat irradiation-induced bone damage.

Neck circumference as an additional predictor of cardiovascular disease mortality: A multi-center prospective population-based study in northeastern China.

BACKGROUND AND AIMS: This study aimed to assess the potential of neck circumference (NC) and neck-to-height ratio (NHR) as predictors of future cardiovascular disease (CVD) mortality in a general population from Northeastern China. METHODS: A multi-center prospective study was conducted in Northeastern China, involving 18, 796 participants. The associations between NC or NHR and the incidence of overall CVD mortality, stroke mortality, and coronary heart disease (CHD) mortality were examined using multivariate Cox regression models. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were calculated. Reclassification analyses were conducted to determine the incremental predictive value of NC or NHR. RESULTS: NC was significantly associated with the risk of CVD mortality, independent of other anthropometric measurements for obesity. Individuals in the highest quartile of NC had a 1.83-fold (95% CI 1.29 to 2.61) and a 2.40-fold (95% CI 1.45 to 4.00) higher risk of overall CVD mortality and CHD mortality, respectively. Larger NC was significantly related to a heightened risk of ischemic stroke mortality, although no such association was observed with hemorrhagic stroke mortality. Furthermore, the risk of overall CVD mortality, stroke mortality, and CHD mortality increased by approximately 1.21 to 1.25 times per 1-SD change in NC. Similar findings were observed for NHR. The percentages of correct classification of overall CVD mortality improved by 12.1% and 16.3% after the addition of NC or NHR into established models, respectively. CONCLUSIONS: NC and NHR might be promising predictors of CVD mortality, with higher values indicating greater risk.

Highly Selective Protic-Solvent-Mediated Organic-Inorganic Hybrid Cuprous Bromides Achieving Structural Transformation.

The potential application of stimuli-responsive hybrid copper halides in information storage and switch devices has generated significant interest. However, their transformation mechanism needs to be further studied deeply. Herein, two zero-dimensional (0D) organic-inorganic hybrids, namely, (TBA)CuBr2 (1) with linear [CuBr2]- units and (TBA)2Cu4Br6 (2) with [Cu4Br6]2- clusters (TBA+ = (C4H9)4N+), are synthesized using simple solvent evaporation approaches. Interestingly, upon exposure to distinct protic solvents, such as methanol, ethanol, ethylene glycol, or hot water, 1 undergoes a transformation into 2 with varying degrees of transition, accompanied by a change in luminescence color from cyan to orange (or mixed color) under high-energy emission (e.g., 254 nm) excitation. Hot water can trigger 1 to completely transform into 2 because of its large contact angle difference in the solvents. Furthermore, 2 can be converted back to 1 through a simple solid-state mechanochemical reaction. Additionally, the structure of 2 remains unchanged even after immersion in 80 °C H2O for 168 h due to the dense organic framework. This study provides valuable insights for exploring reversible structural transformation materials in the 0D metal halide system.