Varying association of nutrient intakes with quality of life in patients receiving different modes of dialysis

BackgroundNutrients are crucial for dialysis patients, especially elderly patients. Nutrition-related complications in dialysis patients are often closely related to cardiovascular aging. However, we know little about the effect of different nutrients on the commonly used outcome predictor, health-related quality of life (HRQOL). Therefore, this study investigated the associations between different nutrients and HRQOL among dialysis patients.MethodsA cross-sectional study was conducted on 123 dialysis adults at multiple dialysis centers. The Short Form-36 Health Survey (SF-36) assesses HRQOL. Modified quantitative subjective global assessment (MQSGA) evaluates nutritional status. A 3-day dietary record evaluated nutrient intakes.ResultsAmong the 123 participants, 79 received hemodialysis (HD), and 44 were on peritoneal dialysis (PD). Patients with PD had a higher SF-36 score than HD (525 ± 136 vs. 375 ± 179, P < 0.001). A negative association between nutrition status and HRQOL was observed in HD (regression coefficient β = −17.4, P < 0.001) but not in PD (β = −12.3, P = 0.07). For HD patients, the nutrition status was negatively correlated with intakes of carbohydrates, fiber, selenium, copper, and Manganese (β = −0.02, P = 0.032; β = −0.3, P = 0.031; β = −0.1, P = 0.006; β = −2.3, P = 0.025; β = −1.3, P = 0.003, respectively). Their HRQOL was positively associated with calories, fat, niacin, and vitamin E (β = 2.19, P = 0.035; β = 2.4, P = 0.043; β = 8.5, P = 0.044; β = 6.9, P = 0.017, respectively). Conversely, for patients with PD, only vitamin B2 was found to be adversely correlated with their nutritional status (β = −5.2, P = 0.037), and increased intakes of vitamin A, vitamin C and fiber (β = 0.1, P = 0.031; β = 0.8, P = 0.028; β = 15.8, P = 0.045, respectively) were associated with a better HRQOL.ConclusionsThe nutritional intake of PD patients and HD patients affects their quality of life differently. Macronutrients significantly impact HRQOL in HD patients, while vitamins have a more substantial impact on PD patients

Artificial Intelligence Framework Identifies Candidate Targets for Drug Repurposing in Alzheimer’s Disease

Background: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer’s disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein–protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein–protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Results: Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861–0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862–0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. Conclusions: In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD

Loss of FBP1 by Snail-Mediated Repression Provides Metabolic Advantages in Basal-Like Breast Cancer

The epithelial-mesenchymal transition (EMT) enhances cancer invasiveness and confers tumor cells with cancer stem cell (CSC)-like characteristics. We show that the Snail-G9a-Dnmt1 complex, which is critical for E-cadherin promoter silencing, is also required for the promoter methylation of fructose-1,6-biphosphatase (FBP1) in basal-like breast cancer (BLBC). Loss of FBP1 induces glycolysis and results in increased glucose uptake, macromolecule biosynthesis, formation of tetrameric PKM2, and maintenance of ATP production under hypoxia. Loss of FBP1 also inhibits oxygen consumption and reactive oxygen species production by suppressing mitochondrial complex I activity; this metabolic reprogramming results in an increased CSC-like property and tumorigenicity by enhancing the interaction of β-catenin with T-cell factor. Our study indicates that the loss of FBP1 is a critical oncogenic event in EMT and BLBC

Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment

Background Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive and therapeutic interventions. Methods In this study, we conducted a network-based, multimodal omics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9-based genetic assay results and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer’s disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2. Results We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Overall, individuals with the AD risk allele APOE E4/E4 displayed reduced expression of antiviral defense genes compared to APOE E3/E3 individuals. Conclusion Our results suggest significant mechanistic overlap between AD and COVID-19, centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions, although causal relationship and mechanistic pathways between COVID-19 and AD need future investigations

Multimodal Single-Cell/Nucleus RNA Sequencing Data Analysis Uncovers Molecular Networks Between Disease-Associated Microglia and Astrocytes With Implications for Drug Repurposing in Alzheimer’s Disease

Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer\u27s disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network-based methodology that leverages single-cell/nucleus RNA sequencing data from both transgenic mouse models and AD patient brains, as well as drug-target network, metaboliteenzyme associations, the human protein-protein interactome, and large-scale longitudinal patient data. Through this approach, we find both common and unique gene network regulators between DAM (i.e., PAK1, MAPK14, and CSF1R) and DAA (i.e., NFKB1, FOS, and JUN) that are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1). We identify shared immune pathways between DAM and DAA, including Th17 cell differentiation and chemokine signaling. Last, integrative metabolite-enzyme network analyses suggest that fatty acids and amino acids may trigger molecular alterations in DAM and DAA. Combining network-based prediction and retrospective case-control observations with 7.2 million individuals, we identify that usage of fluticasone (an approved glucocorticoid receptor agonist) is significantly associated with a reduced incidence of AD (hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.83-0.89, P \u3c 1.0 × 10 - 8). Propensity score-stratified cohort studies reveal that usage of mometasone (a stronger glucocorticoid receptor agonist) is significantly associated with a decreased risk of AD (HR = 0.74, 95% CI 0.68-0.81, P \u3c 1.0 × 10 - 8) compared to fluticasone after adjusting age, gender, and disease comorbidities. In summary, we present a network-based, multimodal methodology for single-cell/nucleus genomics-informed drug discovery and have identified fluticasone and mometasone as potential treatments in AD

Evidence for e+e−→γχc1,2e^+e^-\to\gamma\chi_{c1, 2} at center-of-mass energies from 4.009 to 4.360 GeV

Using data samples collected at center-of-mass energies of $\sqrt{s}$ = 4.009, 4.230, 4.260, and 4.360 GeV with the BESIII detector operating at the BEPCII collider, we perform a search for the process $e^+e^-\to\gamma\chi_{cJ}$ $(J = 0, 1, 2)$ and find evidence for $e^+e^-\to\gamma\chi_{c1}$ and $e^+e^-\to\gamma\chi_{c2}$ with statistical significances of 3.0$\sigma$ and 3.4$\sigma$, respectively. The Born cross sections $\sigma^{B}(e^+e^-\to\gamma\chi_{cJ})$, as well as their upper limits at the 90% confidence level are determined at each center-of-mass energy.Comment: 8 pages, 7 figures, 3 table

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data