piRBase: integrating piRNA annotation in all aspects.

Piwi-interacting RNAs are a type of small noncoding RNA that have various functions. piRBase is a manually curated resource focused on assisting piRNA functional analysis. piRBase release v3.0 is committed to providing more comprehensive piRNA related information. The latest release covers >181 million unique piRNA sequences, including 440 datasets from 44 species. More disease-related piRNAs and piRNA targets have been collected and displayed. The regulatory relationships between piRNAs and targets have been visualized. In addition to the reuse and expansion of the content in the previous version, the latest version has additional new content, including gold standard piRNA sets, piRNA clusters, piRNA variants, splicing-junction piRNAs, and piRNA expression data. In addition, the entire web interface has been redesigned to provide a better experience for users. piRBase release v3.0 is free to access, browse, search, and download at http://bigdata.ibp.ac.cn/piRBase.

Prematurely delivering mothers show reductions of lachnospiraceae in their gut microbiomes.

BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality. Despite evidence shows that imbalances in the maternal microbiome associates to the risk of preterm birth, the mechanisms underlying the association between a perturbed microbiota and preterm birth remain poorly understood. METHOD: Applying shotgun metagenomic analysis on 80 gut microbiotas of 43 mothers, we analyzed the taxonomic composition and metabolic function in gut microbial communities between preterm and term mothers. RESULTS: Gut microbiome of mothers delivering prematurely showed decreased alpha diversity and underwent significant reorganization, especially during pregnancy. SFCA-producing microbiomes, particularly species of Lachnospiraceae, Ruminococcaceae, and Eubacteriaceae, were significantly depleted in preterm mothers. Lachnospiraceae and its species were the main bacteria contributing to species' differences and metabolic pathways. CONCLUSION: Gut microbiome of mothers delivering prematurely has altered and demonstrates the reduction of Lachnospiraceae.

The role of genetic predisposition in cardiovascular risk after cancer diagnosis: a matched cohort study of the UK Biobank.

BACKGROUND: Evidence is scarce regarding the potential modifying role of disease susceptibility on the association between a prior cancer diagnosis and cardiovascular disease (CVD). METHODS: We conducted a matched cohort study of UK Biobank including 78,860 individuals with a cancer diagnosis between January 1997 and January 2020, and 394,300 birth year and sex individually matched unexposed individuals. We used Cox model to assess the subsequent relative risk of CVD, which was further stratified by individual genetic predisposition. RESULTS: During nearly 23 years of follow-up, an elevated risk of CVD was constantly observed among cancer patients, compared to their matched unexposed individuals. Such excess risk was most pronounced (hazard ratio [HR] = 5.28, 95% confidence interval [CI] 4.90-5.69) within 3 months after a cancer diagnosis, which then decreased rapidly and stabilised for >6 months (HR = 1.22, 95% CI 1.19-1.24). For all the studied time periods, stratification analyses by both levels of polygenic risk score for CVD and by family history of CVD revealed higher estimates among individuals with lower genetic risk predisposition. CONCLUSIONS: Our findings suggest that patients with a recent cancer diagnosis were at an increased risk of multiple types of CVD and the excess CVD risk was higher among individuals with lower genetic susceptibility to CVD, highlighting a general need for enhanced psychological assistance and clinical surveillance of CVD among newly diagnosed cancer patients.

Genetic predispositions to psychiatric disorders and the risk of COVID-19.

BACKGROUND: Whether a genetic predisposition to psychiatric disorders is associated with coronavirus disease 2019 (COVID-19) is unknown. METHODS: Our analytic sample consisted of 287,123 white British participants in UK Biobank who were alive on 31 January 2020. We performed a genome-wide association study (GWAS) analysis for each psychiatric disorder (substance misuse, depression, anxiety, psychotic disorder, and stress-related disorders) in a randomly selected half of the study population ("base dataset"). For the other half ("target dataset"), the polygenic risk score (PRS) was calculated as a proxy of individuals' genetic predisposition to a given psychiatric phenotype using discovered genetic variants from the base dataset. Ascertainment of COVID-19 was based on the Public Health England dataset, inpatient hospital data, or death registers in UK Biobank. COVID-19 cases from hospitalization records or death records were considered "severe cases." The association between the PRS for psychiatric disorders and COVID-19 risk was examined using logistic regression. We also repeated PRS analyses based on publicly available GWAS summary statistics. RESULTS: A total of 143,562 participants (including 10,868 COVID-19 cases) were used for PRS analyses. A higher genetic predisposition to psychiatric disorders was associated with an increased risk of any COVID-19 and severe COVID-19. The adjusted odds ratio (OR) for any COVID-19 was 1.07 (95% confidence interval [CI] 1.02-1.13) and 1.06 (95% CI 1.01-1.11) among individuals with a high genetic risk (above the upper tertile of the PRS) for substance misuse and depression, respectively, compared with individuals with a low genetic risk (below the lower tertile). Slightly higher ORs were noted for severe COVID-19, and similar result patterns were obtained in analyses based on publicly available GWAS summary statistics. CONCLUSIONS: Our findings suggest a potential role of genetic factors in the observed phenotypic association between psychiatric disorders and COVID-19. Our data underscore the need for increased medical surveillance for this vulnerable population during the COVID-19 pandemic.

Public awareness, emotional reactions and human mobility in response to the COVID-19 outbreak in China - a population-based ecological study.

BACKGROUND: The outbreak of COVID-19 generated severe emotional reactions, and restricted mobility was a crucial measure to reduce the spread of the virus. This study describes the changes in public emotional reactions and mobility patterns in the Chinese population during the COVID-19 outbreak. METHODS: We collected data on public emotional reactions in response to the outbreak through Weibo, the Chinese Twitter, between 1st January and 31st March 2020. Using anonymized location-tracking information, we analyzed the daily mobility patterns of approximately 90% of Sichuan residents. RESULTS: There were three distinct phases of the emotional and behavioral reactions to the COVID-19 outbreak. The alarm phase (19th-26th January) was a restriction-free period, characterized by few new daily cases, but a large amount public negative emotions [the number of negative comments per Weibo post increased by 246.9 per day, 95% confidence interval (CI) 122.5-371.3], and a substantial increase in self-limiting mobility (from 45.6% to 54.5%, changing by 1.5% per day, 95% CI 0.7%-2.3%). The epidemic phase (27th January-15th February) exhibited rapidly increasing numbers of new daily cases, decreasing expression of negative emotions (a decrease of 27.3 negative comments per post per day, 95% CI -40.4 to -14.2), and a stabilized level of self-limiting mobility. The relief phase (16th February-31st March) had a steady decline in new daily cases and decreasing levels of negative emotion and self-limiting mobility. CONCLUSIONS: During the COVID-19 outbreak in China, the public's emotional reaction was strongest before the actual peak of the outbreak and declined thereafter. The change in human mobility patterns occurred before the implementation of restriction orders, suggesting a possible link between emotion and behavior.

Disease trajectories and mortality among individuals diagnosed with depression: a community-based cohort study in UK Biobank.

Patients with depression are at increased risk for a range of comorbid diseases, with, however, unclear explanations. In this large community-based cohort study of the UK Biobank, 24,130 patients diagnosed with depression were compared to 120,366 matched individuals without such a diagnosis. Follow-up was conducted from 6 months after the index date until death or the end of 2019, for the occurrence of 470 medical conditions and 16 specific causes of death. The median age at the time of the depression diagnosis was 62.0 years, and most of the patients were female (63.63%). During a median follow-up of 4.94 years, 129 medical conditions were found to be significantly associated with a prior diagnosis of depression, based on adjusted Cox regression models. Using disease trajectory network analysis to visualize the magnitude of disease-disease associations and the temporal order of the associated medical conditions, we identified three main affected disease clusters after depression (i.e., cardiometabolic diseases, chronic inflammatory diseases, and diseases related to tobacco abuse), which were further linked to a wider range of other conditions. In addition, we also identified three depression-mortality trajectories leading to death due to cardiovascular disease, respiratory system disease and malignant neoplasm. In conclusion, an inpatient diagnosis of depression in later life is associated with three distinct network-based clusters of medical conditions, indicating alterations in the cardiometabolic system, chronic status of inflammation, and tobacco abuse as key pathways to a wide range of other conditions downstream. If replicated, these pathways may constitute promising targets for the health promotion among depression patients.

COVID-19 related outcomes among individuals with neurodegenerative diseases: a cohort analysis in the UK biobank.

BACKGROUND: An increased susceptibility to COVID-19 has been suggested for individuals with neurodegenerative diseases, but data are scarce from longitudinal studies. METHODS: In this community-based cohort study, we included 96,275 participants of the UK Biobank who had available SARS-CoV-2 test results in Public Health England. Of these, 2617 had a clinical diagnosis of neurodegenerative diseases in the UK Biobank inpatient hospital data before the outbreak of COVID-19 (defined as January 31st, 2020), while the remaining participants constituted the reference group. We then followed both groups from January 31st, 2020 to June 14th, 2021 for ascertainment of COVID-19 outcomes, including any COVID-19, inpatient care for COVID-19, and COVID-19 related death. Logistic regression was applied to estimate the association between neurogenerative disease and risks of COVID-19 outcomes, adjusted for multiple confounders and somatic comorbidities. RESULTS: We observed an elevated risk of COVID-19 outcomes among individuals with a neurodegenerative disease compared with the reference group, corresponding to a fully adjusted odds ratio of 2.47 (95%CI 2.25-2.71) for any COVID-19, 2.18 (95%CI 1.94-2.45) for inpatient COVID-19, and 3.67 (95%CI 3.11-4.34) for COVID-19 related death. Among individuals with a positive test result for SARS-CoV-2, individuals with neurodegenerative diseases had also a higher risk of COVID-19 related death than others (fully adjusted odds ratio 2.08; 95%CI 1.71-2.53). CONCLUSION: Among UK Biobank participants who received at least one test for SARS-CoV-2, a pre-existing diagnosis of neurodegenerative disease was associated with a subsequently increased risk of COVID-19, especially COVID-19 related death.

COVID-19 and risk of subsequent life-threatening secondary infections: a matched cohort study in UK Biobank.

BACKGROUND: With the increasing number of people infected with and recovered from coronavirus disease 2019 (COVID-19), the extent of major health consequences of COVID-19 is unclear, including risks of severe secondary infections. METHODS: Based on 445,845 UK Biobank participants registered in England, we conducted a matched cohort study where 5151 individuals with a positive test result or hospitalized with a diagnosis of COVID-19 were included in the exposed group. We then randomly selected up to 10 matched individuals without COVID-19 diagnosis for each exposed individual (n = 51,402). The life-threatening secondary infections were defined as diagnoses of severe secondary infections with high mortality rates (i.e., sepsis, endocarditis, and central nervous system infections) from the UK Biobank inpatient hospital data, or deaths from these infections from mortality data. The follow-up period was limited to 3 months after the initial COVID-19 diagnosis. Using a similar study design, we additionally constructed a matched cohort where exposed individuals were diagnosed with seasonal influenza from either inpatient hospital or primary care data between 2010 and 2019 (6169 exposed and 61,555 unexposed individuals). After controlling for multiple confounders, Cox models were used to estimate hazard ratios (HRs) of life-threatening secondary infections after COVID-19 or seasonal influenza. RESULTS: In the matched cohort for COVID-19, 50.22% of participants were male, and the median age at the index date was 66 years. During a median follow-up of 12.71 weeks, the incidence rate of life-threatening secondary infections was 2.23 (123/55.15) and 0.25 (151/600.55) per 1000 person-weeks for all patients with COVID-19 and their matched individuals, respectively, which corresponded to a fully adjusted HR of 8.19 (95% confidence interval [CI] 6.33-10.59). The corresponding HR of life-threatening secondary infections among all patients with seasonal influenza diagnosis was 4.50, 95% CI 3.34-6.08 (p for difference < 0.01). Also, elevated HRs were observed among hospitalized individuals for life-threatening secondary infections following hospital discharge, both in the COVID-19 (HR = 6.28 [95% CI 4.05-9.75]) and seasonal influenza (6.01 [95% CI 3.53-10.26], p for difference = 0.902) cohorts. CONCLUSION: COVID-19 patients have increased subsequent risks of life-threatening secondary infections, to an equal extent or beyond risk elevations observed for patients with seasonal influenza.

Development of a microfluidic wearable electrochemical sensor for the non-invasive monitoring of oxidative stress biomarkers in human sweat.

Oxidative stress is widely recognized as a pivotal factor contributing to numerous Central Nervous System (CNS) ailments. The concentrations of hydrogen peroxide (H2O2) and phosphorylated proteins within the human body serve as crucial indicators of oxidative stress. As such, the real-time monitoring of H2O2 and phosphorylated proteins in sweat is vital for the early identification, diagnosis, and management of diseases linked to oxidative stress. In this context, we present a novel microfluidic wearable electrochemical sensor by modifying the electrode with Prussian blue (PB) and loading sulfur-rich vacancy-containing molybdenum disulfide (MoS2-X) onto Multi-walled carbon nanotube (CNTs) to form coaxially layered CNTs/MoS2-X, which was then synthesized with highly dispersed titanium dioxide nanoparticles (TiO2) to synthesize CNTs/MoS2-X/TiO2 composites for the detection of human sweat H2O2 and phosphorylated proteins, respectively. This structure, with its sulfur vacancies and coaxial layering, significantly improved sensitivity of electrochemical sensors, allowing it to detect H2O2 in a range of 0.01-1 mM with a detection limit of 4.80 µM, and phosphoproteins in a range of 0.01-1 mg/mL with a threshold of 0.917 µg/mL. Furthermore, the miniature sensor demonstrates outstanding performance in detecting analytes in both simulated and real sweat. Comprehensive biosafety assessments have validated the compatibility of the electrode material, underscoring the potential of sensor as a reliable and non-invasive method for tracking biomarkers linked to CNS disorders. This microfluidic wearable electrochemical biosensor with high performance and biosafety features shows great promise for the development of cutting-edge wearable technology devices for tracking CNS disease indicators.

Inspecting mother-to-infant microbiota transmission: disturbance of strain inheritance by cesarian section.

Introduction: The initial acquisition and subsequent development of the microbiota in early life is crucial to future health. Cesarean-section (CS) birth is considered to affect early microbial transmission from mother to infant. Methods: In this study, we collected fecal samples from 34 CS infants and their mothers from West China Second Hospital, Sichuan University to assess the microbiota developmental trajectory of mothers and infants. We explored mother-infant gut microbiome transmission via comparison with corresponding Finnish data. Results: Metagenomic analysis of gut microbiota profiles indicated that the communities of mothers and infants were distinct. The composition of the infant gut microbiome was highly variable but also followed predictable patterns in the early stages of life. Maternal communities were stable and mainly dominated by species from Bacteroidacea spp. We used PStrain to analyze and visualize strain transmission in each mother-infant pair. Excluding missing data, we included 32 mother-infant pairs for analysis of strain transmission. Most CS deliveries (65.6%, 21/32) did not demonstrate transmission of strains from mother to infant. To further explore the mother-infant strain transmission, we analyzed metagenomics data from Finnish mother-infant pairs. A total of 32 mother-infant pairs were included in the analysis, including 28 vaginal delivery (VD) infants and four CS infants. Strain transmission was observed in 30 infants, including 28 VD infants and two CS infants. All VD infants received transmitted stains from their mothers. Finally, a total of 193 strain transmission events were observed, comprising 131 strains and 45 species. Discussion: Taken together, our data suggested that delivery mode was an important factor influencing the mother-infant strain transmission.

Causal association and mediating effect of blood biochemical metabolic traits and brain image-derived endophenotypes on Alzheimer's disease.

Background: Recent genetic evidence supports that circulating biochemical and metabolic traits (BMTs) play a causal role in Alzheimer's disease (AD), which might be mediated by changes in brain structure. Here, we leveraged publicly available genome-wide association study data to investigate the intrinsic causal relationship between blood BMTs, brain image-derived phenotypes (IDPs) and AD. Methods: Utilizing the genetic variants associated with 760 blood BMTs and 172 brain IDPs as the exposure and the latest AD summary statistics as the outcome, we analyzed the causal relationship between blood BMTs and brain IDPs and AD by using a two-sample Mendelian randomization (MR) method. Additionally, we used two-step/mediation MR to study the mediating effect of brain IDPs between blood BMTs and AD. Results: Twenty-five traits for genetic evidence supporting a causal association with AD were identified, including 12 blood BMTs and 13 brain IDPs. For BMTs, glutamine consistently reduced the risk of AD in 3 datasets. For IDPs, specific alterations of cortical thickness (atrophy in frontal pole and insular lobe, and incrassation in superior parietal lobe) and subcortical volume (atrophy in hippocampus and its subgroups, left accumbens and left choroid plexus, and expansion in cerebral white matter) are vulnerable to AD. In the two-step/mediation MR analysis, superior parietal lobe, right hippocampal fissure and left accumbens were identified to play a potential mediating role among three blood BMTs and AD. Conclusions: The results obtained in our study suggest that 12 circulating BMTs and 13 brain IDPs play a causal role in AD. Importantly, a subset of BMTs exhibit shared genetic architecture and potentially causal relationships with brain structure, which may contribute to the alteration of brain IDPs in AD.

The Causal Association of Irritable Bowel Syndrome with Multiple Disease Outcomes: A Phenome-Wide Mendelian Randomization Study.

BACKGROUND: This study aimed to identify novel associations between irritable bowel syndrome (IBS) and a broad range of outcomes. METHODS: In total, 346,352 white participants in the U.K. Biobank were randomly divided into two halves, in which a genome-wide association study (GWAS) of IBS and a polygenic risk score (PRS) analysis of IBS using GWAS summary statistics were conducted, respectively. A phenome-wide association study (PheWAS) based on the PRS of IBS was performed to identify disease outcomes associated with IBS. Then, the causalities of these associations were tested by both one-sample (individual-level data in U.K. Biobank) and two-sample (publicly available summary statistics) Mendelian randomization (MR). Sex-stratified PheWAS-MR analyses were performed in male and female, separately. RESULTS: Our PheWAS identified five diseases associated with genetically predicted IBS. Conventional MR confirmed these causal associations between IBS and depression (OR: 1.07, 95%CI: 1.01-1.14, p = 0.02), diverticular diseases of the intestine (OR: 1.13, 95%CI: 1.08-1.19, p = 3.00 × 10-6), gastro-esophageal reflux disease (OR: 1.09, 95%CI: 1.05-1.13, p = 3.72 × 10-5), dyspepsia (OR: 1.21, 95%CI: 1.13-1.30, p = 9.28 × 10-8), and diaphragmatic hernia (OR: 1.10, 95%CI: 1.05-1.15, p = 2.75 × 10-5). The causality of these associations was observed in female only, but not men. CONCLUSIONS: Increased risks of IBS is found to cause a series of disease outcomes. Our findings support further investigation on the clinical relevance of increased IBS risks with mental and digestive disorders.

Genetic impact on the association of sleep patterns and chronic kidney disease: A prospective cohort study of 157,175 UK Biobank participants.

OBJECTIVES: The association between sleep pattern and chronic kidney disease (CKD) incidence, and whether the association is dependent on the genetic backgrounds has not been addressed. We sought to investigate the association of multidimensional sleep pattern with CKD in consideration of genetic polymorphisms. METHODS: In this prospective cohort study of 157,175 participants from the UK Biobank, sleep patterns were derived by multiple correspondence analysis (MCA) and k-means clustering of individual sleep traits (sleep duration, insomnia, chronotype, daytime sleepiness, snoring, and night shift status). Cox proportional hazard regression was used to estimate the association between sleep patterns and CKD incidence. Gene-environment-wide interaction study (GEWIS) was performed to detect whether gene polymorphisms were modifiers on this association. RESULTS: Compared with "healthy sleep" pattern, increased CKD incidence was observed in the clusters with "long sleep duration" (hazard ratios (HR) 1.42, 95% confidence intervals (CI), 1.18-1.72) and "night shift" (HR 1.23, 95% CI, 1.05-1.45) patterns, but not with the "short sleep duration" pattern. By GEWIS, we identified 167 SNPs as suggestive effect modifiers that interacted with unhealthy sleep patterns and affected the risk of CKD. CONCLUSIONS: Unhealthy sleep patterns, with features of long sleep duration and night shift, may increase the risk of CKD. The study highlights the interaction of sleep and individual genetic risk to affect health outcomes.

DASES: a database of alternative splicing for esophageal squamous cell carcinoma.

Esophageal carcinoma ranks as the sixth leading cause of cancer-related mortality globally, with esophageal squamous cell carcinoma (ESCC) being particularly prevalent among Asian populations. Alternative splicing (AS) plays a pivotal role in ESCC development and progression by generating diverse transcript isoforms. However, the current landscape lacks a specialized database focusing on alternative splicing events (ASEs) derived from a large number of ESCC cases. Additionally, most existing AS databases overlook the contribution of long non-coding RNAs (lncRNAs) in ESCC molecular mechanisms, predominantly focusing on mRNA-based ASE identification. To address these limitations, we deployed DASES (http://www.hxdsjzx.cn/DASES). Employing a combination of publicly available and in-house ESCC RNA-seq datasets, our extensive analysis of 346 samples, with 93% being paired tumor and adjacent non-tumor tissues, led to the identification of 257 novel lncRNAs in esophageal squamous cell carcinoma. Leveraging a paired comparison of tumor and adjacent normal tissues, DASES identified 59,094 ASEs that may be associated with ESCC. DASES fills a critical gap by providing comprehensive insights into ASEs in ESCC, encompassing lncRNAs and mRNA, thus facilitating a deeper understanding of ESCC molecular mechanisms and serving as a valuable resource for ESCC research communities.

Genetic characteristics of common variable immunodeficiency patients with autoimmunity.

Background: The pathogenesis of common variable immunodeficiency disorder (CVID) is complex, especially when combined with autoimmunity. Genetic factors may be potential explanations for this complex situation, and whole genome sequencing (WGS) provide the basis for this potential. Methods: Genetic information of patients with CVID with autoimmunity, together with their first-degree relatives, was collected through WGS. The association between genetic factors and clinical phenotypes was studied using genetic analysis strategies such as sporadic and pedigree. Results: We collected 42 blood samples for WGS (16 CVID patients and 26 first-degree relatives of healthy controls). Through pedigree, sporadic screening strategies and low-frequency deleterious screening of rare diseases, we obtained 9,148 mutation sites, including 8,171 single-nucleotide variants (SNVs) and 977 Insertion-deletions (InDels). Finally, we obtained a total of 28 candidate genes (32 loci), of which the most common mutant was LRBA. The most common autoimmunity in the 16 patients was systematic lupus erythematosis. Through KEGG pathway enrichment, we identified the top ten signaling pathways, including "primary immunodeficiency", "JAK-STAT signaling pathway", and "T-cell receptor signaling pathway". We used PyMOL to predict and analyse the three-dimensional protein structures of the NFKB1, RAG1, TIRAP, NCF2, and MYB genes. In addition, we constructed a PPI network by combining candidate mutants with genes associated with CVID in the OMIM database via the STRING database. Conclusion: The genetic background of CVID includes not only monogenic origins but also oligogenic effects. Our study showed that immunodeficiency and autoimmunity may overlap in genetic backgrounds. Clinical Trial Registration: identifier ChiCTR2100044035.

Adverse health consequences of undiagnosed hearing loss at middle age: A prospective cohort study with the UK Biobank.

OBJECTIVES: Hearing impairment is common in the middle-aged population but remains largely undiagnosed and untreated. The knowledge about to what extent and how hearing impairment matters for health is currently lacking. Thus, we aimed to comprehensively examine the adverse health consequences as well as the comorbidity patterns of undiagnosed hearing loss. STUDY DESIGN: Based on the prospective cohort of the UK Biobank, we included 14,620 individuals (median age 61 years) with audiometry-determined (i.e., speech-in-noise test) objective hearing loss and 38,479 individuals with subjective hearing loss (i.e., tested negative but with self-reported hearing problems; median age 58 years) at recruitment (2006-2010), together with 29,240 and 38,479 matched unexposed individuals respectively. MAIN OUTCOME MEASURES: Cox regression was used to determine the associations of both hearing-loss exposures with the risk of 499 medical conditions and 14 cause-specific deaths, adjusting for ethnicity, annual household income, smoking and alcohol intake, exposure to working noise, and BMI. Comorbidity patterns following both exposures were visualized by comorbidity modules (i.e., sets of connected diseases) identified in the comorbidity network analyses. RESULTS: During a median follow-up of 9 years, 28 medical conditions and mortality related to nervous system disease showed significant associations with prior objective hearing loss. Subsequently, the comorbidity network identified four comorbidity modules (i.e., neurodegenerative, respiratory, psychiatric, and cardiometabolic diseases), with the most pronounced association noted for the module related to neurodegenerative diseases (meta-hazard ratio [HR] = 2.00, 95%confidence interval [CI] 1.67-2.39). For subjective hearing loss, we found 57 associated medical conditions, which were partitioned into four modules (i.e., diseases related to the digestive, psychiatric, inflammatory, and cardiometabolic systems), with meta-HRs varying from 1.17 to 1.25. CONCLUSIONS: Undiagnosed hearing loss captured by screening could identify individuals with at greater risk of multiple adverse health consequences, highlighting the importance of screening for speech-in-noise hearing impairment in the middle-aged population, for potential early diagnosis and intervention.

SurgSmart: an artificial intelligent system for quality control in laparoscopic cholecystectomy: an observational study.

BACKGROUND: The rate of bile duct injury in laparoscopic cholecystectomy (LC) continues to be high due to low critical view of safety (CVS) achievement and the absence of an effective quality control system. The development of an intelligent system enables the automatic quality control of LC surgery and, eventually, the mitigation of bile duct injury. This study aims to develop an intelligent surgical quality control system for LC and using the system to evaluate LC videos and investigate factors associated with CVS achievement. MATERIALS AND METHODS: SurgSmart, an intelligent system capable of recognizing surgical phases, disease severity, critical division action, and CVS automatically, was developed using training datasets. SurgSmart was also applied in another multicenter dataset to validate its application and investigate factors associated with CVS achievement. RESULTS: SurgSmart performed well in all models, with the critical division action model achieving the highest overall accuracy (98.49%), followed by the disease severity model (95.45%) and surgical phases model (88.61%). CVSI, CVSII, and CVSIII had an accuracy of 80.64, 97.62, and 78.87%, respectively. CVS was achieved in 4.33% in the system application dataset. In addition, the analysis indicated that surgeons at a higher hospital level had a higher CVS achievement rate. However, there was still considerable variation in CVS achievement among surgeons in the same hospital. CONCLUSIONS: SurgSmart, the surgical quality control system, performed admirably in our study. In addition, the system's initial application demonstrated its broad potential for use in surgical quality control.

Trends in incident diagnoses and drug prescriptions for anxiety and depression during the COVID-19 pandemic: an 18-month follow-up study based on the UK Biobank.

Serious concerns have been raised about the negative effects of the COVID-19 pandemic on population psychological well-being. However, limited data exist on the long-term effects of the pandemic on incident psychiatric morbidities among individuals with varying exposure to the pandemic. Leveraging prospective data from the community-based UK Biobank cohort, we included 308,400 participants free of diagnosis of anxiety or depression, as well as 213,757 participants free of anxiolytics or antidepressants prescriptions, to explore the trends in incident diagnoses and drug prescriptions for anxiety and depression from 16 March 2020 to 31 August 2021, compared to the pre-pandemic period (i.e., 1 January 2017 to 31 December 2019) and across populations with different exposure statuses (i.e., not tested for COVID-19, tested negative and tested positive). The age- and sex-standardized incidence ratios (SIRs) were calculated by month which indicated an increase in incident diagnoses of anxiety or depression among individuals who were tested for COVID-19 (tested negative: SIR 3.05 [95% confidence interval 2.88-3.22]; tested positive: 2.03 [1.76-2.34]), especially during the first six months of the pandemic (i.e., March-September 2020). Similar increases were also observed for incident prescriptions of anxiolytics or antidepressants (tested negative: 1.56 [1.47-1.67]; tested positive: 1.41 [1.22-1.62]). In contrast, individuals not tested for COVID-19 had consistently lower incidence rates of both diagnoses of anxiety or depression (0.70 [0.67-0.72]) and prescriptions of respective psychotropic medications (0.70 [0.68-0.72]) during the pandemic period. These data suggest a distinct rise in health care needs for anxiety and depression among individuals tested for COVID-19, regardless of the test result, in contrast to a reduction in health care consumption for these disorders among individuals not tested for and, presumably, not directly exposed to the disease.

A Population-Based Outcome-Wide Association Study of the Comorbidities and Sequelae Following COVID-19 Infection.

BACKGROUND: Immense attention has been given to the outcome of COVID-19 infection. However, comprehensive studies based on large populational cohort with long-term follow-up are still lacking. This study aimed to investigate the risk of various short-term comorbidities (within one month) and long-term sequelae (above one month) after COVID-19 infection. METHODS: In this large prospective cohort study with 14 months follow-up information based on UK biobank, we included 16,776 COVID-19-positive participants and 58,281 COVID-19-negative participants matched for comparison. The risk of each comorbidity and sequela was evaluated by multivariable logistic regression analysis and presented as hazard ratio (HR) and 95% confidence interval (95% CI). RESULTS: COVID-19-positive individuals had a higher risk of 47 types of comorbidities within one month following COVID-19 infection, especially those who were older, male, overweight/obese, ever-smoked, with more pre-existing comorbidities and hospitalized. About 70.37% of COVID-19 patients with comorbidities had more than one co-occurring comorbidities. Additionally, only 6 high-risk sequelae were observed after one month of COVID-19 infection, and the incidence was relatively low (< 1%). CONCLUSION: In addition to long-term sequelae following COVID-19 infection, plenty of comorbidities were observed, especially in patients with older age, male gender, overweight/obese, more pre-existing comorbidities and severe COVID-19, indicating that more attention should be given to these susceptible persons within this period.

Proliferative exhausted CD8+ T cells exacerbate long-lasting anti-tumor effects in human papillomavirus-positive head and neck squamous cell carcinoma.

The survival prognosis of human papillomavirus (HPV)-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) is largely different, and little is known about the anti-tumor mechanism of tumor-infiltrated exhausted CD8+ T cells (Tex) in HNSCC. We performed cell-level multi-omics sequencing on human HNSCC samples to decipher the multi-dimensional characteristics of Tex cells. A proliferative exhausted CD8+ T cell cluster (P-Tex) which was beneficial to survival outcomes of patients with HPV-positive HNSCC was identified. Interestingly, P-Tex cells expressed CDK4 genes as high as cancer cells, which could be simultaneously inhibited by CDK4 inhibitors and might be a potential reason for the ineffectiveness of CDK4 inhibitors in treating HPV-positive HNSCC. P-Tex cells could aggregate in the antigen-presenting cell niches and activate certain signaling pathways. Together, our findings suggest a promising role for P-Tex cells in the prognosis of patients with HPV-positive HNSCC by providing modest but persistent anti-tumor effects.