Gender disparities in multi-state health transitions and life expectancy among the ≥50-year-old population: A cross-national multi-cohort study.

Background: Understanding how disability progresses with ageing is important for shaping policies aimed at improving older adults' quality of life, especially when considering the global trends in ageing, life expectancy (LE), and gender disparity. We aimed to assess the health transition probabilities of daily living activities and their implications on LE and gender gaps in global middle-aged and elderly populations. Methods: In this multi-cohort study with a sample of 74 101 individuals aged ≥50 years, we analysed data from six international cohorts: the China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Study (HRS) in the USA, the Mexican Longitudinal Study of Ageing (MHAS), the Korean Longitudinal Study of Ageing (KLoSA), and the Survey of Health, Ageing and Retirement in Europe (SHARE). We estimated probabilities between robust health; disabilities related to instrumental activities of daily living (IADL) and basic activities of daily living (BADL); and mortality through multi-state Markov models. We included gender as a covariate in the models to calculate hazard ratios (HRs), while we calculated LE within the distinct health states of robust health, IADL disabilities, BADL disabilities, and mortality using the stochastic population analysis for complex events (SPACE) microsimulation. Results: Women had higher progressions to disability (IADL: HR = 1.392; BADL: HR = 1.356) compared to men, who conversely showed lesser progression from IADL to BADL disability (HR = 0.856) and lower mortality rates (span of HRs = 0.232-0.692). LE at age 50 favoured women (32.16-38.22 years) over men (28.99-33.58 years), yet they spent more time in states of disability. We otherwise observed significant regional and gender disparities in healthy LE. Conclusions: We identified ageing patterns in which longer lives are often coupled with extended periods of disability. Pronounced gender and regional differences indicate a need for targeted health interventions to address inequities and improve seniors' quality of life. Our findings highlight the necessity for policy interventions focussed on health equity to more completely respond to the demographic shift towards older populations.

Modifiable lifestyle factors and the risk of post-COVID-19 multisystem sequelae, hospitalization, and death.

Effective prevention strategies for post-COVID complications are crucial for patients, clinicians, and policy makers to mitigate their cumulative burden. This study evaluated the association of modifiable lifestyle factors (smoking, alcohol intake, BMI, physical activity, sedentary time, sleep duration, and dietary habits) with COVID-19 multisystem sequelae, death, and hospitalization in the UK Biobank cohort (n = 68,896). A favorable lifestyle (6-10 healthy factors; 46.4%) was associated with a 36% lower risk of multisystem sequelae (HR, 0.64; 95% CI, 0.58-0.69; ARR at 210 days, 7.08%; 95% CI, 5.98-8.09) compared to an unfavorable lifestyle (0-4 factors; 12.3%). Risk reductions spanned all 10 organ systems, including cardiovascular, coagulation, metabolic, gastrointestinal, kidney, mental health, musculoskeletal, respiratory disorders, and fatigue. This beneficial effect was largely attributable to direct lifestyle impacts independent of corresponding pre-infection comorbidities (71% for any sequelae). A favorable lifestyle was also related to the risk of post-COVID death (HR 0.59, 0.52-0.66) and hospitalization (HR 0.78, 0.73-0.84). These associations persisted across acute and post-acute infection phases, irrespective of hospitalization status, vaccination, or SARS-CoV-2 variant. These findings underscore the clinical and public health importance of adhering to a healthy lifestyle in mitigating long-term COVID-19 adverse impacts and enhancing future pandemic preparedness.

PredGCN: a Pruning-enabled Gene-Cell Net for automatic cell annotation of single cell transcriptome data.

MOTIVATION: The annotation of cell types from single-cell transcriptomics is essential for understanding the biological identity and functionality of cellular populations. Although manual annotation remains the gold standard, the advent of automatic pipelines has become crucial for scalable, unbiased, and cost-effective annotations. Nonetheless, the effectiveness of these automatic methods, particularly those employing deep learning, significantly depends on the architecture of the classifier and the quality and diversity of the training datasets. RESULTS: To address these limitations, we present a Pruning-enabled Gene-Cell Net (PredGCN) incorporating a Coupled Gene-Cell Net (CGCN) to enable representation learning and information storage. PredGCN integrates a Gene Splicing Net (GSN) and a Cell Stratification Net (CSN), employing a pruning operation (PrO) to dynamically tackle the complexity of heterogeneous cell identification. Among them, GSN leverages multiple statistical and hypothesis-driven feature extraction methods to selectively assemble genes with specificity for scRNA-seq data while CSN unifies elements based on diverse region demarcation principles, exploiting the representations from GSN and precise identification from different regional homogeneity perspectives. Furthermore, we develop a multi-objective Pareto pruning operation (Pareto PrO) to expand the dynamic capabilities of CGCN, optimizing the sub-network structure for accurate cell type annotation. Multiple comparison experiments on real scRNA-seq datasets from various species have demonstrated that PredGCN surpasses existing state-of-the-art methods, including its scalability to cross-species datasets. Moreover, PredGCN can uncover unknown cell types and provide functional genomic analysis by quantifying the influence of genes on cell clusters, bringing new insights into cell type identification and characterizing scRNA-seq data from different perspectives. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/IrisQi7/PredGCN and test data is available at https://figshare.com/articles/dataset/PredGCN/25251163.

Genomic, transcriptomic, and metabolomic analyses provide insights into the evolution and development of a medicinal plant Saposhnikovia divaricata (Apiaceae).

Saposhnikovia divaricata, 2n = 2x = 16, as a perennial species, is widely distributed in China, Mongolia, Russia, etc. It is a traditional Chinese herb used to treat tetanus, rubella pruritus, rheumatic arthralgia, and other diseases. Here, we assembled a 2.07 Gb and N50 scaffold length of 227.67 Mb high-quality chromosome-level genome of S. divaricata based on the PacBio Sequel II sequencing platform. The total number of genes identified was 42 948, and 42 456 of them were functionally annotated. A total of 85.07% of the genome was composed of repeat sequences, comprised mainly of long terminal repeats (LTRs) which represented 73.7% of the genome sequence. The genome size may have been affected by a recent whole-genome duplication event. Transcriptional and metabolic analyses revealed bolting and non-bolting S. divaricata differed in flavonoids, plant hormones, and some pharmacologically active components. The analysis of its genome, transcriptome, and metabolome helped to provide insights into the evolution of bolting and non-bolting phenotypes in wild and cultivated S. divaricata and lays the basis for genetic improvement of the species.

A novel SALL1 C757T mutation in a Chinese family causes a rare disease --Townes-Brocks syndrome.

BACKGROUND: Townes-Brocks syndrome (TBS) is a rare genetic disorder characterized by imperforate anus, dysplastic ears, thumb malformations, and other abnormalities. Previous studies have revealed that mutations in the SALL1 gene can disrupt normal development, resulting in the characteristic features of Townes-Brocks syndrome. Spalt-like transcription factors (SALLs) are highly conserved proteins that play important roles in various cellular processes, including embryonic development, cell differentiation, and cell survival. Over 400 different variants or mutations have been reported in the SALL1 gene in individuals with TBS. Most of these variants lead to the formation of premature termination codons (PTCs), also known as nonsense mutations. The majority of these PTCs occur in a specific region of the SALL1 gene called the "hotspot region", which is particularly susceptible to mutation. METHODS: In this study, we conducted whole-exome sequencing on a three-generation Chinese family with anorectal malformations. RESULTS: We identified a novel heterozygous mutation (chr16:51175376:c.757 C > T p.Gln253*) in the SALL1 gene. Molecular analysis revealed a heterozygous C to T transition at nucleotide position 757 in exon 2 of the SALL1 (NM_002968) gene. This mutation is predicted to result in the substitution of the Gln253 codon with a premature stop codon (p.Gln253*). The glutamine-rich domain forms a long alpha helix, enabling the mutant protein to interact with the wild-type SALL1 protein. This interaction may result in steric hindrance effects on the wild-type SALL1 protein. CONCLUSIONS: Our findings have expanded the mutation database of the SALL1 gene, which is significant for genetic counseling and clinical surveillance in the affected family. Furthermore, our study enhances the understanding of Townes-Brocks syndrome and has the potential to improve its diagnosis and treatment.

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes.

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.

Exhaustive Exploitation of Nature-Inspired Computation for Cancer Screening in an Ensemble Manner.

Accurate screening of cancer types is crucial for effective cancer detection and precise treatment selection. However, the association between gene expression profiles and tumors is often limited to a small number of biomarker genes. While computational methods using nature-inspired algorithms have shown promise in selecting predictive genes, existing techniques are limited by inefficient search and poor generalization across diverse datasets. This study presents a framework termed Evolutionary Optimized Diverse Ensemble Learning (EODE) to improve ensemble learning for cancer classification from gene expression data. The EODE methodology combines an intelligent grey wolf optimization algorithm for selective feature space reduction, guided random injection modeling for ensemble diversity enhancement, and subset model optimization for synergistic classifier combinations. Extensive experiments were conducted across 35 gene expression benchmark datasets encompassing varied cancer types. Results demonstrated that EODE obtained significantly improved screening accuracy over individual and conventionally aggregated models. The integrated optimization of advanced feature selection, directed specialized modeling, and cooperative classifier ensembles helps address key challenges in current nature-inspired approaches. This provides an effective framework for robust and generalized ensemble learning with gene expression biomarkers. Specifically, we have opened EODE source code on Github at https://github.com/wangxb96/EODE.

Docosahexaenoic Acid Supplementation for Neonatal Hyperbilirubinemia: A Double-Blind, Randomized Clinical Trial.

Docosahexaenoic acid (DHA) is an essential component for brain development during fetal and early postnatal life. Hyperbilirubinemia is characterized by abnormally high levels of bilirubin in the bloodstream, frequently leading to jaundice in newborns. In severe instances, this condition can progress to neurological damage or kernicterus, a form of brain damage. Initial cell-based experiments conducted by our research team revealed that DHA significantly enhances the survival rate of nerve cells treated with bilirubin and diminishes the oxidative stress indicated by reduced peroxide activity caused by unconjugated bilirubin (UCB). Further investigations through animal studies demonstrated that DHA effectively mitigates bilirubin-induced brain injury in neonatal rats. However, the potential of DHA to decrease the incidence of bilirubin-induced brain damage in clinical settings has not been previously explored or reported. Infants with neonatal hyperbilirubinemia (n = 30 per group) participated in a double-blind, randomized, placebo-controlled parallel study. They received either 100 mg/d DHA or placebo syrup immediately when they were diagnosed. The study found that the bilirubin level at 48 hours of treatment, serum neuron-specific enolase (NSE) levels, mean phototherapy duration, and abnormal rate of cranial magnetic resonance imaging (MRI) were lower in the DHA group than those in the control group (P < .05). These results suggested that DHA is effective as an adjuvant treatment for hyperbilirubinemia in children. It can reduce the incidence of neonatal hyperbilirubinemia brain injury and plays a certain protective role. Clinical study on protective effect of DHA on neonatal bilirubin injury is registered at Chinese Clinical Trial Registry as ChiCTR2300070250.

Effects of acupuncture and moxibustion on ulcerative colitis: An overview of systematic reviews.

Ulcerative colitis (UC) is a gastrointestinal disease with an unknown etiology that severely affects patients' quality of life. Acupuncture and moxibustion therapies are effective in the treatment of UC, but existing systematic reviews (SRs) and meta-analyses (MAs) on this subject have variable methodological and outcome quality. Therefore, this study aimed to summarize and evaluate the evidence of existing SRs and MAs to provide more reliable evidence for clinical practice. Data were extracted from seven databases through systematic search and evaluated in terms of the methodological quality, reporting quality, risk of bias, and quality of evidence using the AMSTAR-2, PRISMA, ROBIS, and GRADE systems, respectively. Ten studies were finally included, and all of them showed many problems with the overall design and quality of outcomes. Because of the lack of high-quality evidence to support the findings from the existing studies, we should take this conclusion with caution and strictly implement the registration, design, and implementation of trials based on evidence to provide high-quality results in future studies.

Association of longitudinal trajectories of general and abdominal adiposity during middle age with mental health and well-being in late life: A prospective analysis.

Single measures of adiposity markers, such as body mass index (BMI) and waist circumference (WC), are associated with adverse mental health outcomes; however, long-term patterns of adiposity and their health effects remain unclear. The current study assessed adiposity trajectories during a 14-year span beyond middle age and their relevance to mental well-being in late life, and the contribution of genetic and lifestyle factors to the trajectories. Based on a nationally representative sample with longitudinal anthropometric measures, adiposity trajectories were identified by latent mixture modeling, and logistic regression model was used to estimate their associations with mental well-being, with adjustment for confounders. Of the 3491 eligible participants included (mean [SD] age, 69.5 [8.9] years), five discrete BMI and four WC trajectory patterns were identified over 14 years. Compared with the low-stable BMI group (range, 22.8 to 22.9 kg/m²; representing stable healthy body weight), the high-stable group (range, 34.3 to 35.4 kg/m²; stable obese) was associated with increased risk of depression (odds ratio [OR], 1.63; 95 % CI, 1.28-2.07) and low subjective well-being (OR, 1.35; 95 % CI, 1.02-1.79). Compared with the low-stable WC group (range, 75 to 79 cm healthy WC), the high-increasing group (range, 114 to 121 cm) was associated with increased risk of depression (odds ratio [OR], 1.64; 95 % CI, 1.19-2.25) and low well-being (OR, 1.48; 95 % CI, 1.01-2.16). The adiposity trajectories, especially the high-stable/increasing groups, were driven by genetic factors in a dose-response manner, whereas the high/moderate-increasing groups were also behaviorally related. This longitudinal cohort study reveals that stably high trajectory patterns of central and general adiposity during middle age were associated with higher risk of depression and low well-being in late life. The findings indicate the importance of weight management beyond middle age, such as adherence to a healthy lifestyle, in promoting mental health and well-being.

Terpenes based hydrophobic deep eutectic solvents for dispersive liquid-liquid microextraction of aliphatic aldehydes in drinking water and alcoholic beverages.

Aliphatic aldehydes are a class of organic compounds containing aldehyde groups, which are widespread, and closely related to people's daily life and health. In this work, a series of terpenes based hydrophobic deep eutectic solvents were designed and synthesized using hexafluoroisopropanol as hydrogen bond donor and menthol/thymol as hydrogen bond acceptor. Then they are used as extraction solvent in dispersive liquid-liquid microextraction for extracting and determining seven aliphatic aldehydes from drinking water and alcoholic beverage combined with high performance liquid chromatography-ultraviolet. Due to the fact that these hydrophobic deep eutectic solvents are liquid at the room temperature, a density greater than that of water, a lower viscosity (≤26.10 mPa s, 25 °C), after extraction and centrifugation, the microvolume DES-rich phase in the bottom is convenient for collection and direct analysis without further dissolution or dilution with organic solvents. Some factors affecting the extraction recovery were optimized by one-variable-at-a-time and response surface methodology. Under the optimal conditions, the enrichment factors for the seven aliphatic aldehydes were 48-56. The method had good performance: linear ranges of 1.0-200, 0.5-200, 0.2-200, 0.4-400, 1.0-400, 0.4-400 and 0.4-400 µg L-1 for seven aliphatic aldehydes (r2 ≥ 0.9949), limits of detection of 0.1-0.5 µg L-1, intra-day and inter-day precisions <4.9%. The recoveries of seven aliphatic aldehydes ranged from 76.0 to 119.0%. The proposed dispersive liquid-liquid microextraction method is simple, rapid, highly efficient, and green, which effectively reduces the amount of toxic chemical reagents used and their impact on the environment. Rapid and efficient detection of aliphatic aldehydes helps ensure a healthy diet and has great application prospects in food safety analysis.

Long-term risk of psychiatric disorder and psychotropic prescription after SARS-CoV-2 infection among UK general population.

Despite evidence indicating increased risk of psychiatric issues among COVID-19 survivors, questions persist about long-term mental health outcomes and the protective effect of vaccination. Using UK Biobank data, three cohorts were constructed: SARS-CoV-2 infection (n = 26,101), contemporary control with no evidence of infection (n = 380,337) and historical control predating the pandemic (n = 390,621). Compared with contemporary controls, infected participants had higher subsequent risks of incident mental health at 1 year (hazard ratio (HR): 1.54, 95% CI 1.42-1.67; P = 1.70 × 10-24; difference in incidence rate: 27.36, 95% CI 21.16-34.10 per 1,000 person-years), including psychotic, mood, anxiety, alcohol use and sleep disorders, and prescriptions for antipsychotics, antidepressants, benzodiazepines, mood stabilizers and opioids. Risks were higher for hospitalized individuals (2.17, 1.70-2.78; P = 5.80 × 10-10) than those not hospitalized (1.41, 1.30-1.53; P = 1.46 × 10-16), and were reduced in fully vaccinated people (0.97, 0.80-1.19; P = 0.799) compared with non-vaccinated or partially vaccinated individuals (1.64, 1.49-1.79; P = 4.95 × 10-26). Breakthrough infections showed similar risk of psychiatric diagnosis (0.91, 0.78-1.07; P = 0.278) but increased prescription risk (1.42, 1.00-2.02; P = 0.053) compared with uninfected controls. Early identification and treatment of psychiatric disorders in COVID-19 survivors, especially those severely affected or unvaccinated, should be a priority in the management of long COVID. With the accumulation of breakthrough infections in the post-pandemic era, the findings highlight the need for continued optimization of strategies to foster resilience and prevent escalation of subclinical mental health symptoms to severe disorders.

Transition in metabolic health phenotypes across general adiposity categories and association with the risk of depression: a prospective analysis.

BACKGROUND: The association between obesity and depression may partly depend on the contextual metabolic health. The effect of change in metabolic health status over time on subsequent depression risk remains unclear. We aimed to assess the prospective association between metabolic health and its change over time and the risk of depression across body mass index (BMI) categories. METHODS: Based on a nationally representative cohort, we included participants enrolled at the wave 2 (2004-2005) of the English Longitudinal Study of Ageing and with follow-up for depression at wave 8 (2016-2017). Participants were cross-classified by BMI categories and metabolic health (defined by the absence of hypertension, diabetes, and hypercholesterolemia) at baseline or its change over time (during waves 3-6). Logistic regression model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of depression at follow-up stratified by BMI category and metabolic health status with adjustment for potential confounders. RESULTS: The risk of depression was increased for participants with metabolically healthy obesity compared with healthy nonobese participants, and the risk was highest for those with metabolically unhealthy obesity (OR 1.62, 95% CI 1.18-2.20). Particularly hypertension and diabetes contribute most to the increased risk. The majority of metabolically healthy participants converted to unhealthy metabolic phenotype (50.1% of those with obesity over 8 years), which was associated with an increased risk of depression. Participants who maintained metabolically healthy obesity were still at higher risk (1.99, 1.33-2.72), with the highest risk observed for those with stable unhealthy metabolic phenotypes. CONCLUSIONS: Obesity remains a risk factor for depression, independent of whether other metabolic risk factors are present or whether participants convert to unhealthy metabolic phenotypes over time. Long-term maintenance of metabolic health and healthy body weight may be beneficial for the population mental well-being.

Fecal calprotectin: A novel predictor of ulcerated esophageal injury after atrial fibrillation catheter ablation.

BACKGROUND: Atrial esophageal fistula (AEF) is a lethal complication that can occur post atrial fibrillation (AF) ablation. Esophageal injury (EI) is likely to be the initial lesion leading to AEF. Endoscopic examination is the gold standard for a diagnosis of EI but extensive endoscopic screening is invasive and costly. This study was conducted to determine whether fecal calprotectin (Fcal), a marker of inflammation throughout the intestinal tract, may be associated with the existence of esophageal injury. METHODS: This diagnostic study was conducted in a cohort of 166 patients with symptomatic AF undergoing radiofrequency catheter ablation from May 2020 to June 2021. Fcal tests were performed 1-7 days after ablation. All patients underwent endoscopic ultrasonography 1 or 2 days after ablation. RESULTS: The levels of Fcal were significantly different between the EI and non-EI groups (404.9 µg/g (IQR 129.6-723.6) vs. 40.4 µg/g (IQR 15.0-246.2), p < .001). Analysis of ROC curves revealed that a Fcal level of 125 µg/g might be the optimal cut-off value for a diagnosis of EI, giving a 78.8% sensitivity and a 65.4% specificity. The negative predictive value of Fcal was 100% for ulcerated EI. CONCLUSIONS: The level of Fcal is associated with EI post AF catheter ablation. 125 µg/g might be the optimal cut-off value for a diagnosis of EI. Negative Fcal could predict the absence of ulcerated EI, which could be considered a precursor to AEF.

Predicting recurrence and survival in patients with non-metastatic renal-cell carcinoma after nephrectomy: a prospective population-based study with multicenter validation.

BACKGROUND: Accurate prognostication of oncological outcomes is crucial for the optimal management of patients with renal cell carcinoma (RCC) after surgery. Previous prediction models were developed mainly based on retrospective data in the Western populations, and their predicting accuracy remains limited in contemporary, prospective validation. We aimed to develop contemporary RCC prognostic models for recurrence and overall survival (OS) using prospective population-based patient cohorts and compare their performance with existing, mostly utilized ones. METHODS: In this prospective analysis and external validation study, the development set included 11  128 consecutive patients with non-metastatic RCC treated at a tertiary urology center in China between 2006 and 2022, and the validation set included 853 patients treated at 13 medical centers in the USA between 1996 and 2013. The primary outcome was progression-free survival (PFS), and the secondary outcome was OS. Multivariable Cox regression was used for variable selection and model development. Model performance was assessed by discrimination [Harrell's C-index and time-dependent areas under the curve (AUC)] and calibration (calibration plots). Models were validated internally by bootstrapping and externally by examining their performance in the validation set. The predictive accuracy of the models was compared with validated models commonly used in clinical trial designs and with recently developed models without extensive validation. RESULTS: Of the 11  128 patients included in the development set, 633 PFS and 588 OS events occurred over a median follow-up of 4.3 years [interquartile range (IQR) 1.7-7.8]. Six common clinicopathologic variables (tumor necrosis, size, grade, thrombus, nodal involvement, and perinephric or renal sinus fat invasion) were included in each model. The models demonstrated similar C-indices in the development set (0.790 [95% CI 0.773-0.806] for PFS and 0.793 [95% CI 0.773-0.811] for OS) and in the external validation set (0.773 [0.731-0.816] and 0.723 [0.731-0.816]). A relatively stable predictive ability of the models was observed in the development set (PFS: time-dependent AUC 0.832 at 1 year to 0.760 at 9 years; OS: 0.828 at 1 year to 0.794 at 9 years). The models were well calibrated and their predictions correlated with the observed outcome at 3, 5, and 7 years in both development and validation sets. In comparison to existing prognostic models, the present models showed superior performance, as indicated by C-indices ranging from 0.722 to 0.755 (all P <0.0001) for PFS and from 0.680 to 0.744 (all P <0.0001) for OS. The predictive accuracy of the current models was robust in patients with clear-cell and non-clear-cell RCC. CONCLUSIONS: Based on a prospective population-based patient cohort, the newly developed prognostic models were externally validated and outperformed the currently available models for predicting recurrence and survival in patients with non-metastatic RCC after surgery. The current models have the potential to aid in clinical trial design and facilitate clinical decision-making for both clear-cell and non-clear-cell RCC patients at varying risk of recurrence and survival.

Deriving aquatic PNECs of endocrine disruption effects for PFOS and PFOA by combining species sensitivity weighted distributions and adverse outcome pathway networks.

Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), as emerging endocrine-disrupting chemicals (EDCs), pose adverse effects on aquatic organisms. Conventional ecological risk assessment (ERA) not fully considering the mode of toxicity action of PFOS and PFOA, may result in an underestimation of risks and confuse decision-makers. In the study, we developed species sensitivity weighted distribution (SSWD) models based on adverse outcome pathway (AOP) networks for deriving predicted no-effect concentrations (PNECs). Three kinds of weighting criteria (intraspecies variation, trophic level abundance, and data quality) and weighted log-normal distribution methods were adopted. The developed models considered the inter/intraspecies variation and integrated nontraditional endpoints of endocrine-disrupting effects. The PNECs of endocrine disruption effects were derived as 2.52 µg/L (95% confidence intervals 0.667-9.85 µg/L) for PFOS and 18.7 µg/L (5.40-71.0 µg/L) for PFOA, which were more conservative than those derived from the SSD method and were comparable with the values in the literature based on the chronic toxicity data. For PFOS, the effect of growth and development was the most sensitive; however, for PFOA, the effect of reproduction was the most sensitive in the effects of growth and development, reproduction, biochemistry and genetics, and survival. The endocrine-disrupting effects of PFOS and PFOA are significant and need to be fully recognized in the ERA. This study provided an ERA framework that can improve the ecological relevance and reduce the uncertainty of PNECs of EDCs.

Composite healthy lifestyle, socioeconomic deprivation, and mental well-being during the COVID-19 pandemic: a prospective analysis.

The adverse psychological and social impacts of COVID-19 pandemic are well characterized, but the role of composite, modifiable lifestyle factors that may interact to mitigate these impacts is not. The effect of socioeconomic deprivation on these lifestyle risks also remains unclear. Based on a nationally representative, longitudinal cohort, we assessed the association between a combination of pre-pandemic lifestyle factors and mental health conditions during pandemic, and the contribution of deprivation to it. Composite lifestyle factors included BMI, smoking status, alcohol consumption, physical activity, sedentary time, sleep duration, and fruit and vegetable intake, with lifestyle scores and lifestyle categories calculated for each participant. Symptoms of depression and anxiety, and personal well-being were assessed by validated scales during the pandemic. Socioeconomic deprivation was characterized by both individual-level (income, wealth, and education) and group-level factors (Index of Multiple Deprivation). Of the 5049 eligible participants (mean [SD] age, 68.1 [10.9] years; 57.2% were female) included in the study, 41.6% followed a favorable lifestyle, 48.9% followed an intermediate lifestyle, and 9.5% followed an unfavorable lifestyle. Compared with favorable lifestyle category, participants in the intermediate and unfavorable lifestyle category were at increased risk of mental health conditions, with the hazard ratio (HR) for trend per increment change towards unfavorable category of 1.17 (95% CI 1.09-1.26) for depression, 1.23 (1.07-1.42) for anxiety, and 1.39 (1.20-1.61) for low well-being. A significant trend of lower risk for mental health conditions with increasing number of healthy lifestyle factors was observed (P < 0.001 for trend). There were no significant interactions between lifestyle factors and socioeconomic deprivation for any of the outcomes, with similar HRs for trend per one increment change in lifestyle category observed in each deprivation group. Compared with those in the least deprived group with favorable lifestyle, participants in the most deprived group adherent to unfavorable lifestyle had the highest risk of mental health outcomes. These results suggest that adherence to a broad combination of healthy lifestyle factors was associated with a significantly reduced risk of mental health conditions during the COVID-19 pandemic. Lifestyle factors, in conjunction with socioeconomic deprivation, independently contribute to the risk of mental health issues. Although further research is needed to assess causality, the current findings support public health strategies and individual-level interventions that provide enhanced support in areas of deprivation and target multiple lifestyle factors to reduce health inequalities and promote mental well-being during the ongoing COVID-19 pandemic.

Percutaneous ballon compression for recurrent TN -a retrospective study of 33 cases.

Objective: To investigate the clinical efficacy of percutaneous microballoon compression in the treatment of recurrent TN. Methods: This retrospective study included 33 patients who underwent percutaneous microballoon compression for the treatment of recurrent TN from March 2019 to May 2022. Postoperative pain recurrence and facial numbness were assessed according to the Barrow Neurological Institute (BNI) pain score. Patients' anxiety and sleep status during follow-up were assessed according to the Self-rating Anxiety Scale (SAS) and Pittsburgh Sleep Quality Index (PSQI). Results: All patients (33 cases) were followed up for 12-38 months, with an average follow-up time of 23 months. On postoperative day 1, 31 patients (93.9%) reported no pain, and 2 patients were given drug treatment for pain relief, The total efficacy was 93.9%. Moreover, 2 patients (6.1%) reported significant pain relief 2 weeks postoperatively. There are many complications during and after PBC. The incidence of the trigeminocardiac reflex (TCR) during surgery was 100%, and the incidence of facial numbness, masseter muscle weakness, labial herpes and headache was 97, 60.6, 12.1 and 3%. No patient experienced severe facial numbness, hearing impairment, diplopia, injury to cranial nerves, Meningitis, intracranial haemorrhage or keratitis. 1 patient had recurrence of pain at 6 months post-op, which was relieved by oral medication. 81.8% suffered from anxiety and 54.5% had poor sleep quality before surgery. After the period of PBC, SAS and PSQI scores decreased continuously. There were significant improvements in anxiety and sleep status postoperatively compared with preoperatively. Conclusion: PBC is a safe and effective option for the treatment of recurrent TN. The arduous and demanding nature of the clinical course subjects the patient to severe pain, mental, and physical stress. Thankfully, it significantly improves the symptoms of anxiety, depression, and sleep quality.

Dynamic characterization and interpretation for protein-RNA interactions across diverse cellular conditions using HDRNet.

RNA-binding proteins play crucial roles in the regulation of gene expression, and understanding the interactions between RNAs and RBPs in distinct cellular conditions forms the basis for comprehending the underlying RNA function. However, current computational methods pose challenges to the cross-prediction of RNA-protein binding events across diverse cell lines and tissue contexts. Here, we develop HDRNet, an end-to-end deep learning-based framework to precisely predict dynamic RBP binding events under diverse cellular conditions. Our results demonstrate that HDRNet can accurately and efficiently identify binding sites, particularly for dynamic prediction, outperforming other state-of-the-art models on 261 linear RNA datasets from both eCLIP and CLIP-seq, supplemented with additional tissue data. Moreover, we conduct motif and interpretation analyses to provide fresh insights into the pathological mechanisms underlying RNA-RBP interactions from various perspectives. Our functional genomic analysis further explores the gene-human disease associations, uncovering previously uncharacterized observations for a broad range of genetic disorders.

Improving Lightweight AdderNet via Distillation From ℓ2 to ℓ1-norm.

To achieve efficient inference with a hardware-friendly design, Adder Neural Networks (ANNs) are proposed to replace expensive multiplication operations in Convolutional Neural Networks (CNNs) with cheap additions through utilizing l1 -norm for similarity measurement instead of cosine distance. However, we observe that there exists an increasing gap between CNNs and ANNs with reducing parameters, which cannot be eliminated by existing algorithms. In this paper, we present a simple yet effective Norm-Guided Distillation (NGD) method for l1 -norm ANNs to learn superior performance from l2 -norm ANNs. Although CNNs achieve similar accuracy with l2 -norm ANNs, the clustering performance based on l2 -distance can be easily learned by l1 -norm ANNs compared with cross correlation in CNNs. The features in l2 -norm ANNs are encouraged to achieve intra-class centralization and inter-class decentralization to amplify this advantage. Furthermore, the roughly estimated gradients in vanilla ANNs are modified to a progressive approximation from l2 -norm to l1 -norm so that a more accurate optimization can be achieved. Extensive evaluations on several benchmarks demonstrate the effectiveness of NGD on lightweight networks. For example, our method improves ANN by 10.43% with 0.25× GhostNet on CIFAR-100 and 3.1% with 1.0× GhostNet on ImageNet.