BAG6 inhibits influenza A virus replication by inducing viral polymerase subunit PB2 degradation and perturbing RdRp complex assembly.

The interaction between influenza A virus (IAV) and host proteins is an important process that greatly influences viral replication and pathogenicity. PB2 protein is a subunit of viral ribonucleoprotein (vRNP) complex playing distinct roles in viral transcription and replication. BAG6 (BCL2-associated athanogene 6) as a multifunctional host protein participates in physiological and pathological processes. Here, we identify BAG6 as a new restriction factor for IAV replication through targeting PB2. For both avian and human influenza viruses, overexpression of BAG6 reduced viral protein expression and virus titers, whereas deletion of BAG6 significantly enhanced virus replication. Moreover, BAG6-knockdown mice developed more severe clinical symptoms and higher viral loads upon IAV infection. Mechanistically, BAG6 restricted IAV transcription and replication by inhibiting the activity of viral RNA-dependent RNA polymerase (RdRp). The co-immunoprecipitation assays showed BAG6 specifically interacted with the N-terminus of PB2 and competed with PB1 for RdRp complex assembly. The ubiquitination assay indicated that BAG6 promoted PB2 ubiquitination at K189 residue and targeted PB2 for K48-linked ubiquitination degradation. The antiviral effect of BAG6 necessitated its N-terminal region containing a ubiquitin-like (UBL) domain (17-92aa) and a PB2-binding domain (124-186aa), which are synergistically responsible for viral polymerase subunit PB2 degradation and perturbing RdRp complex assembly. These findings unravel a novel antiviral mechanism via the interaction of viral PB2 and host protein BAG6 during avian or human influenza virus infection and highlight a potential application of BAG6 for antiviral drug development.

Iron-based autotrophic denitrification driven by sponge iron for nitrite removal in an anaerobic bioreactor: Effect of iron and carbon source.

The study investigated the denitrification effect of the iron autotrophic denitrification process for removing nitrite under anaerobic conditions, utilizing sponge iron as the electron donor. When the C/N ratio equaled 1, defined as the ratio of chemical oxygen demand to total nitrogen (TN), and the influent nitrite nitrogen (NO2--N) was at 80 mg/L, the average steady-state TN effluent concentration of this system was 41.94 mg/L during the 79-day experiment. The TN value exhibited a significant decrease compared to both the sponge iron system (68.69 mg/L) and the carbon source system (56.50 mg/L). Sponge iron is beneficial for providing an electron donor and ensuring an anaerobic system, fostering an environment that promotes microorganism growth while effectively inhibiting the conversion of nitrite to nitrate. In addition, carbon sources play a vital role in ensuring microorganism growth and reproduction, thereby aiding in TN removal. The optimal parameters based on the effectiveness of TN removal in the iron autotrophic denitrification system were determined to be s-Fe0 dosage of 30 g/L and C/N = 1.5. These results suggest that the iron autotrophic denitrification process, driven by sponge iron, can effectively remove nitrite under anaerobic conditions.

Can the allocation of primary health care system resources affect efficiency? A spatial Dubin model study in China.

BACKGROUND: The primary health care (PHC) system plays an important role in China's health care system, but there are challenges such as irrational allocation of health resources and inefficient operation, which need to be improved. The purpose of this study was to explore the impact of resource allocation on the efficiency of the PHC system in China. METHODS: The data in 31 provinces were collected from the China Statistical Yearbook 2017-2021 and the China Health Statistical Yearbook 2017-2021. The comprehensive health resource density index (CHRDI) was constructed based on the entropy method and the health resource density index (HRDI), which was used to analyze the allocation of primary health resources in each province. The adjusted efficiency of the PHC system in each province was calculated by the bootstrap data envelopment analysis (DEA). Finally, the spatial Dubin model was used to explore the effect of the CHRDI on efficiency. RESULTS: From 2016 to 2020, the allocation of primary health resources in 31 provinces showed an increasing trend, and the average efficiency after correction showed a decreasing state year by year. The spatial direct effect and spatial spillover effect coefficients of CHRDI were 0.820 and 1.471, which positively affect the efficiency. Per capita Gross Domestic Product (GDP), urbanization rate, and the proportion of the elderly were the factors affecting the efficiency of the PHC system. CONCLUSIONS: The allocation of primary health resources in all provinces in China has improved each year, but there are still great differences, and efficiency must be further improved. Pay attention to the spatial spillover effect of the level of resource allocation and formulate differentiated measures for different regions. Attention should also be paid to the impact of population aging and economic development on the utilization of primary health resources by increasing health needs and choices.

Directional sound radiation from a rectangular panel and the high frequency limit.

Directional sound radiation focuses sound in a specific direction and reduces sound radiation in other directions. This study uses a flat panel driven by an actuator array to realize two-dimensional directional sound radiation by the acoustic contrast control algorithm. The aliasing effect at higher frequencies is analyzed based on the modal vibration of the panel, and a method for estimating the high frequency limit is proposed. Actuator arrays with different parameters are simulated to verify the efficacy of the proposed method and compare the acoustic contrast response with the conventional loudspeaker arrays.

Automated vertical cup-to-disc ratio determination from fundus images for glaucoma detection.

Glaucoma is the leading cause of irreversible blindness worldwide. Often asymptomatic for years, this disease can progress significantly before patients become aware of the loss of visual function. Critical examination of the optic nerve through ophthalmoscopy or using fundus images is a crucial component of glaucoma detection before the onset of vision loss. The vertical cup-to-disc ratio (VCDR) is a key structural indicator for glaucoma, as thinning of the superior and inferior neuroretinal rim is a hallmark of the disease. However, manual assessment of fundus images is both time-consuming and subject to variability based on clinician expertise and interpretation. In this study, we develop a robust and accurate automated system employing deep learning (DL) techniques, specifically the YOLOv7 architecture, for the detection of optic disc and optic cup in fundus images and the subsequent calculation of VCDR. We also address the often-overlooked issue of adapting a DL model, initially trained on a specific population (e.g., European), for VCDR estimation in a different population. Our model was initially trained on ten publicly available datasets and subsequently fine-tuned on the REFUGE dataset, which comprises images collected from Chinese patients. The DL-derived VCDR displayed exceptional accuracy, achieving a Pearson correlation coefficient of 0.91 (P = 4.12 × 10-412) and a mean absolute error (MAE) of 0.0347 when compared to assessments by human experts. Our models also surpassed existing approaches on the REFUGE dataset, demonstrating higher Dice similarity coefficients and lower MAEs. Moreover, we developed an optimization approach capable of calibrating DL results for new populations. Our novel approaches for detecting optic discs and optic cups and calculating VCDR, offers clinicians a promising tool that significantly reduces manual workload in image assessment while improving both speed and accuracy. Most importantly, this automated method effectively differentiates between glaucoma and non-glaucoma cases, making it a valuable asset for glaucoma detection.

The aquaporin-4 water channel and updates on its potential as a drug target for Alzheimer's disease.

INTRODUCTION: Although there are several FDA-approved treatments for Alzheimer's disease (AD), only recently have disease-modifying therapies received approval for use in patients. In this narrative review, we examine the history of aquaporin-4 (AQP4) as a therapeutic target for NMOSD (neuromyelitis optica spectrum disorder) and as a potential therapeutic target for AD. AREAS COVERED: We review the basic science and discovery of AQP4, a transmembrane water-channel essential to regulating water balance in the central nervous system (CNS). We also review the pathogenesis of NMOSD, an autoimmune disease characterized by the destruction of cells that express AQP4. Then, we review how AQP4 is likely involved in the pathogenesis of Alzheimer's disease (AD). Finally, we discuss future challenges with drug design that would modulate AQP4 to potentially slow AD development. The literature search for this article consisted of searching Google Scholar and PubMed for permutations of the keywords 'Alzheimer's disease,' 'aquaporin-4,' 'neuromyelitis optica,' and their abbreviations. EXPERT OPINION: We place research into AQP4 into context with other recent developments in AD research. A major difficulty with drug development for Alzheimer's is the lack of strategies to cleanly target the early pathogenesis of the disease. Targeting AQP4 may provide such a strategy.

Stroke-related risk factors during pregnancy in women who underwent metabolic and bariatric surgery compared with women who have not undergone metabolic and bariatric surgery.

BACKGROUND: Stroke during pregnancy is rare, occurring in 30 of 100,000 pregnancies and accounting for 7% of maternal deaths in the United States from 2016 to 2018. Metabolic and bariatric surgery (MBS) has been shown to reduce symptoms of chronic conditions that are risk factors for stroke, including hypertension, hypercholesterolemia, and diabetes in women. However, little is known about the impact of MBS on stroke risk during pregnancy. OBJECTIVES: To examine stroke and stroke risk factors including preeclampsia, eclampsia, gestational hypertension, and embolism/thrombosis in women of reproductive age who have had MBS. SETTING: We used the National Inpatient Sample, a publicly available data set from the Healthcare Cost and Utilization Project that samples 20% of hospital discharges in the United States. METHODS: This cross-sectional study included women between the ages of 20 and 44 years who had a maternal admission code. Weighted logistic regression was conducted to assess the odds of stroke and stroke risk factors in women with a history of MBS compared with other women of reproductive age. RESULTS: Women with a history of MBS have 12% lower adjusted odds of developing preeclampsia/eclampsia and 10% lower adjusted odds of gestational hypertension than women who did not undergo MBS. When stratified by race, the difference was significant in White women (preeclampsia/eclampsia: adjusted odds ratio [aOR] = .89; 95% confidence interval [CI], .81-.98; gestational hypertension: aOR = .91; 95% CI, .83-1.00). Latinas with MBS had significantly lower odds of preeclampsia/eclampsia (aOR = .75; 95% CI, .64-.90). CONCLUSIONS: MBS helps women lose weight and decrease the incidence of some pregnancy-related risk factors for stroke. However, there is a notable racial health disparity.

10 Years of GWAS in intraocular pressure.

Intraocular pressure (IOP) is the only modifiable risk factor for glaucoma, the leading cause of irreversible blindness worldwide. In this review, we summarize the findings of genome-wide association studies (GWASs) of IOP published in the past 10 years and prior to December 2022. Over 190 genetic loci and candidate genes associated with IOP have been uncovered through GWASs, although most of these studies were conducted in subjects of European and Asian ancestries. We also discuss how these common variants have been used to derive polygenic risk scores for predicting IOP and glaucoma, and to infer causal relationship with other traits and conditions through Mendelian randomization. Additionally, we summarize the findings from a recent large-scale exome-wide association study (ExWAS) that identified rare variants associated with IOP in 40 novel genes, six of which are drug targets for clinical treatment or are being evaluated in clinical trials. Finally, we discuss the need for future genetic studies of IOP to include individuals from understudied populations, including Latinos and Africans, in order to fully characterize the genetic architecture of IOP.

The Mediating Role of Positive Attitudes on the Relationship Between Esports Gaming Hours and Psychological Well-Being During the COVID-19 Pandemic.

Electronic sports game (esports) gaming has seen a surge in popularity, especially during the coronavirus disease 2019 (COVID-19) pandemic, with more young people turning to it as an alternative to physical activities. However, the impact of esports gaming on mental health is a matter of concern. Previous studies have produced inconsistent findings on the relationship between gaming hours and mental health, and the moderating factors involved remain unexplored. This study aimed to investigate the moderating effect of participants' subjective attitudes toward esports gaming on the relationship between daily gaming hours and psychological well-being (PWB) among Chinese young adults during the COVID-19 lockdown. A nationwide online survey was conducted on 550 Chinese young adults using the Credamo platform. Ryff's Psychological Well-Being Scales (42-Item version) were used to assess PWB levels. The analysis included 453 participants. Gaming hours were negatively correlated with PWB scores. However, when considering the moderating effect of subjective attitudes, the association between gaming hours and PWB scores was largely positive. Our study suggests that subjective attitudes toward esports gaming outweigh gaming hours in promoting personal psychological well-being. We propose practical recommendations for healthy esports participation patterns that prioritize positive attitudes, especially in similar future scenarios like COVID-19. Our findings may inform future psychological intervention and research in the esports domain.

Identification of novel genes for age-at-onset of Alzheimer's disease by combining quantitative and survival trait analyses.

INTRODUCTION: Our understanding of the genetic predisposition for age-at-onset (AAO) of Alzheimer's disease (AD) is limited. Here, we sought to identify genes modifying AAO and examined whether any have sex-specific effects. METHODS: Genome-wide association analysis were performed on imputed genetic data of 9219 AD cases and 10,345 controls from 20 cohorts of the Alzheimer's Disease Genetics Consortium. AAO was modeled from cases directly and as a survival outcome. RESULTS: We identified 11 genome-wide significant loci (P < 5 × 10-8 ), including six known AD-risk genes and five novel loci, UMAD1, LUZP2, ARFGEF2, DSCAM, and 4q25, affecting AAO of AD. Additionally, 39 suggestive loci showed strong association. Twelve loci showed sex-specific effects on AAO including CD300LG and MLX/TUBG2 for females and MIR4445 for males. DISCUSSION: Genes that influence AAO of AD are excellent therapeutic targets for delaying onset of AD. Several loci identified include genes with promising functional implications for AD.

A gene based combination test using GWAS summary data.

BACKGROUND: Gene-based association tests provide a useful alternative and complement to the usual single marker association tests, especially in genome-wide association studies (GWAS). The way of weighting for variants in a gene plays an important role in boosting the power of a gene-based association test. Appropriate weights can boost statistical power, especially when detecting genetic variants with weak effects on a trait. One major limitation of existing gene-based association tests lies in using weights that are predetermined biologically or empirically. This limitation often attenuates the power of a test. On another hand, effect sizes or directions of causal genetic variants in real data are usually unknown, driving a need for a flexible yet robust methodology of gene based association tests. Furthermore, access to individual-level data is often limited, while thousands of GWAS summary data are publicly and freely available. RESULTS: To resolve these limitations, we propose a combination test named as OWC which is based on summary statistics from GWAS data. Several traditional methods including burden test, weighted sum of squared score test [SSU], weighted sum statistic [WSS], SNP-set Kernel Association Test [SKAT], and the score test are special cases of OWC. To evaluate the performance of OWC, we perform extensive simulation studies. Results of simulation studies demonstrate that OWC outperforms several existing popular methods. We further show that OWC outperforms comparison methods in real-world data analyses using schizophrenia GWAS summary data and a fasting glucose GWAS meta-analysis data. The proposed method is implemented in an R package available at https://github.com/Xuexia-Wang/OWC-R-package CONCLUSIONS: We propose a novel gene-based association test that incorporates four different weighting schemes (two constant weights and two weights proportional to normal statistic Z) and includes several popular methods as its special cases. Results of the simulation studies and real data analyses illustrate that the proposed test, OWC, outperforms comparable methods in most scenarios. These results demonstrate that OWC is a useful tool that adapts to the underlying biological model for a disease by weighting appropriately genetic variants and combination of well-known gene-based tests.

Explainable machine learning aggregates polygenic risk scores and electronic health records for Alzheimer's disease prediction.

Alzheimer's disease (AD) is the most common late-onset neurodegenerative disorder. Identifying individuals at increased risk of developing AD is important for early intervention. Using data from the Alzheimer Disease Genetics Consortium, we constructed polygenic risk scores (PRSs) for AD and age-at-onset (AAO) of AD for the UK Biobank participants. We then built machine learning (ML) models for predicting development of AD, and explored feature importance among PRSs, conventional risk factors, and ICD-10 codes from electronic health records, a total of > 11,000 features using the UK Biobank dataset. We used eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), which provided superior ML performance as well as aided ML model explanation. For participants age 40 and older, the area under the curve for AD was 0.88. For subjects of age 65 and older (late-onset AD), PRSs were the most important predictors. This is the first observation that PRSs constructed from the AD risk and AAO play more important roles than age in predicting AD. The ML model also identified important predictors from EHR, including urinary tract infection, syncope and collapse, chest pain, disorientation and hypercholesterolemia, for developing AD. Our ML model improved the accuracy of AD risk prediction by efficiently exploring numerous predictors and identified novel feature patterns.

Post-COVID-19 human memory impairment: A PRISMA-based systematic review of evidence from brain imaging studies.

Many people with coronavirus disease 2019 (COVID-19) report varying degrees of memory impairment. Neuroimaging techniques such as MRI and PET have been utilized to shed light on how COVID-19 affects brain function in humans, including memory dysfunction. In this PRISMA-based systematic review, we compared and summarized the current literature looking at the relationship between COVID-19-induced neuropathological changes by neuroimaging scans and memory symptoms experienced by patients who recovered from COVID-19. Overall, this review suggests a correlational trend between structural abnormalities (e.g., cortical atrophy and white matter hyperintensities) or functional abnormalities (e.g., hypometabolism) in a wide range of brain regions (particularly in the frontal, parietal and temporal regions) and memory impairments in COVID-19 survivors, although a causal relationship between them remains elusive in the absence of sufficient caution. Further longitudinal investigations, particularly controlled studies combined with correlational analyses, are needed to provide additional evidence.

Whole-exome sequencing study identifies rare variants and genes associated with intraocular pressure and glaucoma.

Elevated intraocular pressure (IOP) is a major risk factor for glaucoma, the leading cause of irreversible blindness worldwide. IOP is also the only modifiable risk factor for glaucoma. Previous genome-wide association studies have established the contribution of common genetic variants to IOP. The role of rare variants for IOP was unknown. Using whole exome sequencing data from 110,260 participants in the UK Biobank (UKB), we conducted the largest exome-wide association study of IOP to date. In addition to confirming known IOP genes, we identified 40 novel rare-variant genes for IOP, such as BOD1L1, ACAD10 and HLA-B, demonstrating the power of including and aggregating rare variants in gene discovery. About half of these IOP genes are also associated with glaucoma phenotypes in UKB and the FinnGen cohort. Six of these genes, i.e. ADRB1, PTPRB, RPL26, RPL10A, EGLN2, and MTOR, are drug targets that are either established for clinical treatment or in clinical trials. Furthermore, we constructed a rare-variant polygenic risk score and showed its significant association with glaucoma in independent participants (n = 312,825). We demonstrated the value of rare variants to enhance our understanding of the biological mechanisms regulating IOP and uncovered potential therapeutic targets for glaucoma.

Enhanced stability of M1 protein mediated by a phospho-resistant mutation promotes the replication of prevailing avian influenza virus in mammals.

Avian influenza virus (AIV) can evolve multiple strategies to combat host antiviral defenses and establish efficient infectivity in mammals, including humans. H9N2 AIV and its reassortants (such as H5N6 and H7N9 viruses) pose an increasing threat to human health; however, the mechanisms involved in their increased virulence remain poorly understood. We previously reported that the M1 mutation T37A has become predominant among chicken H9N2 isolates in China. Here, we report that, since 2010, this mutation has also been found in the majority of human isolates of H9N2 AIV and its emerging reassortants. The T37A mutation of M1 protein enhances the replication of H9N2 AIVs in mice and in human cells. Interestingly, having A37 instead of T37 increases the M1 protein stability and resistance to proteasomal degradation. Moreover, T37 of the H9N2 M1 protein is phosphorylated by protein kinase G (PKG), and this phosphorylation induces the rapid degradation of M1 and reduces viral replication. Similar effects are also observed in the novel H5N6 virus. Additionally, ubiquitination at K187 contributes to M1-37T degradation and decreased replication of the virus harboring T37 in the M1 protein. The prevailing AIVs thereby evolve a phospho-resistant mutation in the M1 protein to avoid viral protein degradation by host factors, which is advantageous in terms of replication in mammalian hosts.

Nanosized FeS/ZnS heterojunctions derived using zeolitic imidazolate Framework-8 (ZIF-8) for pH-universal oxygen reduction and High-efficiency Zn-air battery.

Low-cost, stable, and highly active electrocatalysts for oxygen reduction reaction (ORR), especially for pH-universal ORR, are vital for developing numerous renewable energy devices. Herein, a hierarchical N, S-codoped porous carbon-based catalyst (ZFP-800) coupled with abundant FeS/ZnS heterojunctions was facilely prepared via direct pyrolysis of a Ferrocene-crosslinked pyrrole hydrogel composited with zeolitic imidazolate framework-8 (ZIF-8) templates. Compared with the heterojunction-free catalytic activity, the ZFP-800 catalytic activity was significantly higher in pH-universal ranges. Moreover, the ZFP-800 exhibited competitive ORR performance to commercial Pt/C (20%) in various electrolytes, in terms of onset (Eonset), half-wave potentials (E1/2), limiting current density (JL), durability, and methanol immunity. For instance, it exhibited super ORR catalytic activity on Eonset and E1/2, and exceeded that of the benchmark Pt/C in both the alkaline and neutral media. Furthermore, the application of ZFP-800 as a cathode catalyst in a home-made Zn-air battery demonstrated its operation capability in ambient conditions with a competitive performance on the specific energy density (828 mA·h·gZn-1), maximum discharge power density (205.6 mW·cm-2), rate performance, and the long-term stability (188 h at 5 mA·cm-2). This study can facilitate the development of advanced heterojunction-based materials for renewable energy applications.

Optimization of Ferroelectric Ordering and Thermal Stability in Na1/2Bi1/2TiO3-Based Lead-Free Single Crystal through Defect Engineering.

Environmentally friendly lead-free piezoelectric materials have been attracting significant attention in recent years. Na1/2Bi1/2TiO3-based relaxor ferroelectrics have found acceptance for application in promising lead-free transducers in high-power ultrasonic devices. However, their low thermal stability, i.e., their relatively low ferroelectric-relaxor transition temperature (TF-R), hinders their practical application. Herein, a thermal-quenching approach is applied on a Na1/2Bi1/2TiO3 (NBT)-based single crystal, which yields a large increase in TF-R and dramatic enhancement of its ferroelectric ordering, leading to excellent thermal stability of its dielectric, ferroelectric, and piezoelectric properties. This behavior is mainly attributed to quenching-induced domain evolution as well as its octahedral tilt, which is linked to the increased oxygen vacancies. The substitution of long-range ordered ferroelectric domains for short-range polar nanodomains contributes to its increased coherence length and, consequently, enhancement of TF-R. This work provides an approach to the optimization of the ferroelectric ordering and thermal stability of NBT as well as an in-depth understanding of the quenching effect on the local structure, which could be applied to other relaxor-based ferroelectrics for optimization of their macroscopic properties.

Identification of disease-linked hyperactivating mutations in UBE3A through large-scale functional variant analysis.

The mechanisms that underlie the extensive phenotypic diversity in genetic disorders are poorly understood. Here, we develop a large-scale assay to characterize the functional valence (gain or loss-of-function) of missense variants identified in UBE3A, the gene whose loss-of-function causes the neurodevelopmental disorder Angelman syndrome. We identify numerous gain-of-function variants including a hyperactivating Q588E mutation that strikingly increases UBE3A activity above wild-type UBE3A levels. Mice carrying the Q588E mutation exhibit aberrant early-life motor and communication deficits, and individuals possessing hyperactivating UBE3A variants exhibit affected phenotypes that are distinguishable from Angelman syndrome. Additional structure-function analysis reveals that Q588 forms a regulatory site in UBE3A that is conserved among HECT domain ubiquitin ligases and perturbed in various neurodevelopmental disorders. Together, our study indicates that excessive UBE3A activity increases the risk for neurodevelopmental pathology and suggests that functional variant analysis can help delineate mechanistic subtypes in monogenic disorders.