Impact of accelerated biological aging and genetic variation on esophageal adenocarcinoma: Joint and interaction effect in a prospective cohort.

Accelerated biological aging may be associated with increased risk of esophageal adenocarcinoma (EAC). However, its relationship with genetic variation, and its effect on improving risk population stratification, remains unknown. We performed an exposome association study to determine potential associated factors associated with EAC. To quantify biological age and its difference from chronological age, we calculated the BioAge10 and Biological Age Acceleration (BioAgeAccel) based on chronological age and nine biomarkers. Multivariable Cox regression models for 362,310 participants from the UK Biobank with a median follow-up of 13.70 years were performed. We established a weighted polygenic risk score (wPRS) associated with EAC, to assess joint and interaction effects with BioAgeAccel. Four indicators were used to evaluate their interaction effects, and we fitted curves to evaluate the risk stratification ability of BioAgeAccel. Compared with biologically younger participants, those older had higher risk of EAC, with adjusted HR of 1.79 (95%CI: 1.52-2.10). Compared with low wPRS and biologically younger group, the high wPRS and biologically older group had a 4.30-fold increase in HR (95% CI: 2.78-6.66), at meanwhile, 1.15-fold relative excess risk was detected (95% CI: 0.30-2.75), and 22% of the overall EAC risk was attributable to the interactive effects (95% CI: 12%-31%). The 10-year absolute incidence risk indicates that biologically older individuals should begin screening procedures 4.18 years in advance, while youngers can postpone screening by 4.96 years, compared with general population. BioAgeAccel interacted positively with genetic variation and increased risk of EAC, it could serve as a novel indicator for predicting incidence.

Point-based risk score for the risk stratification and prediction of hepatocellular carcinoma: a population-based random survival forest modeling study.

Background: The precise associations between common clinical biomarkers and hepatocellular carcinoma (HCC) risk remain unclear but hold valuable insights for HCC risk stratification and prediction. Methods: We examined the linear and nonlinear associations between the baseline levels of 32 circulating biomarkers and HCC risk in the England cohort of UK Biobank (UKBB) (n = 397,702). The participants were enrolled between 2006 and 2010 and followed up to 31st October 2022. The primary outcome is incident HCC cases. We then employed random survival forests (RSF) to select the top ten most informative biomarkers, considering their association with HCC, and developed a point-based risk score to predict HCC. The performance of the risk score was evaluated in three validation sets including UKBB Scotland and Wales cohort (n = 52,721), UKBB non-White-British cohort (n = 29,315), and the Taizhou Longitudinal Study in China (n = 17,269). Findings: Twenty-five biomarkers were significantly associated with HCC risk, either linearly or nonlinearly. Based on the RSF model selected biomarkers, our point-based risk score showed a concordance index of 0.866 in the England cohort and varied between 0.814 and 0.849 in the three validation sets. HCC incidence rates ranged from 0.95 to 30.82 per 100,000 from the lowest to the highest quintiles of the risk score in the England cohort. Individuals in the highest risk quintile had a 32-73 times greater risk of HCC compared to those in the lowest quintile. Moreover, over 70% of HCC cases were detected in individuals within the top risk score quintile across all cohorts. Interpretation: Our simple risk score enables the identification of high-risk individuals of HCC in the general population. However, including some biomarkers, such as insulin-like growth factor 1, not routinely measured in clinical practice may increase the model's complexity, highlighting the need for more accessible biomarkers that can maintain or improve the predictive accuracy of the risk score. Funding: This work was supported by the National Natural Science Foundation of China (grant numbers: 82204125) and the Science and Technology Support Program of Taizhou (TS202224).

Isolation and characterization of porcine epidemic diarrhea virus with mutations in the spike gene in China.

Porcine epidemic diarrhea (PED) caused by porcine epidemic diarrhea virus (PEDV) has caused enormous economic losses to the global swine industry. Due to frequent mutations in the spike (S) gene of PEDV, commercial vaccines used today are gradually losing their protective efficacy against variants. It's significant to monitor the S gene of PEDV variants and understand its evolutionary trend. In this study, we report four novel PEDV strains isolated from Sichuan, Guangdong and Shanxi Provinces and determined their S gene sequences. Phylogenetic analysis showed that they all belong to GII genotype. Amino acid alignment revealed a unique mutation pattern. We also predicted their three-dimensional structures and continuous B-cell epitopes and compared them to those of the vaccine strain. Our study provides references for understanding the evolution of S gene and antigenic change of S protein, which are of great significance for formulating the prevention and control of PEDV.

The role of dietary modification in the prevention and management of metabolic dysfunction-associated fatty liver disease: An international multidisciplinary expert consensus.

Metabolic dysfunction-associated fatty liver disease (MAFLD) or metabolic dysfunction-associated steatotic liver disease (MASLD), has become the leading cause of chronic liver disease worldwide. Optimal dietary intervention strategies for MAFLD are not standardized. This study aimed to achieve consensus on prevention of MAFLD through dietary modification. A multidisciplinary panel of 55 international experts, including specialists in hepatology, gastroenterology, dietetics, endocrinology and other medical specialties from six continents collaborated in a Delphi-based consensus development process. The consensus statements covered aspects ranging from epidemiology to mechanisms, management, and dietary recommendations for MAFLD. The recommended dietary strategies emphasize adherence to a balanced diet with controlled energy intake and personalized nutritional interventions, such as calorie restriction, high-protein, or low-carbohydrate diets. Specific dietary advice encouraged increasing the consumption of whole grains, plant-based proteins, fish, seafood, low-fat or fat-free dairy products, liquid plant oils, and deeply colored fruits and vegetables. Concurrently, it advised reducing the intake of red and processed meats, saturated and trans fats, ultra-processed foods, added sugars, and alcohol. Additionally, maintaining the Mediterranean or DASH diet, minimizing sedentary behavior, and engaging in regular physical activity are recommended. These consensus statements lay the foundation for customized dietary guidelines and proposing avenues for further research on nutrition and MAFLD.

Investigating the link between gut microbiome and bone mineral density: The role of genetic factors.

Osteoporosis is a complex metabolic bone disease that severely undermines the quality of life and overall health of the elderly. While previous studies have established a close relationship between gut microbiome and host bone metabolism, the role of genetic factors has received less scrutiny. This research aims to identify potential taxa associated with various bone mineral density states, incorporating assessments of genetic factors. Fecal microbiome profiles from 605 individuals (334 females and 271 males) aged 55-65 from the Taizhou Imaging Study with osteopenia (n = 270, 170 women) or osteoporosis (n = 94, 85 women) or normal (n = 241, 79 women) were determined using shotgun metagenomic sequencing. The linear discriminant analysis was employed to identify differentially enriched taxa. Utilizing the Kyoto Encyclopedia of Genes and Genomes for annotation, functional pathway analysis was conducted to identify differentially metabolic pathways. Polygenic risk score for osteoporosis was estimated to represent genetic susceptibility to osteoporosis, followed by stratification and interaction analyses. Gut flora diversity did not show significant differences among various bone mineral groups. After multivariable adjustment, certain species, such as Clostridium leptum, Fusicatenibacter saccharivorans and Roseburia hominis, were enriched in osteoporosis patients. Statistically significant interactions between the polygenic risk score and taxa Roseburia faecis, Megasphaera elsdenii were observed (P for interaction = 0.005, 0.018, respectively). Stratified analyses revealed a significantly negative association between Roseburia faecis and bone mineral density in the low-genetic-risk group (ß = -0.045, P < 0.05), while Turicimonas muris was positively associated with bone mineral density in the high-genetic-risk group (ß = 4.177, P < 0.05) after multivariable adjustments. Functional predictions of the gut microbiome indicated an increase in pathways related to structural proteins in high-genetic-risk patients, while low-genetic-risk patients exhibited enrichment in enzyme-related pathways. This study emphasizes the association between gut microbes and bone mass, offering new insights into the interaction between genetic background and gut microbiome.

Epigenetic regulation of macrophage activation in chronic obstructive pulmonary disease.

Macrophages in the innate immune system play a vital role in various lung diseases such as asthma, chronic obstructive pulmonary disease (COPD), acute lung injury and pulmonary fibrosis. Macrophages involved in the process of immunity need to go through a process of activation, including changes in gene expression and cell metabolism. Epigenetic modifications are key factors of macrophage activation including DNA methylation, histone modification and non-coding RNA regulation. Understanding the role and mechanisms of epigenetic regulation of macrophage activation can provide insights into the function of macrophages in lung diseases and help identification of potential therapeutic targets. This review summarizes the latest progress in the epigenetic changes and regulation of macrophages in their development process and in normal physiological states, and the epigenetic regulation of macrophages in COPD as well as the influence of macrophage activation on COPD development.

Quantitative gait markers and the TUG time in chronic kidney disease.

Background: Poor gait performance results in more fall incidents among people with chronic kidney disease (CKD). It is unknown what specific quantitative gait markers contribute to high fall risk in CKD and the size of their mediation effects. Methods: We included 634 participants from the Taizhou Imaging Study who had complete gait and laboratory data. Quantitative gait assessment was conducted with a wearable insole-like device. Factor analysis was utilized to summarize fifteen highly correlated individual parameters into five independent gait domains. Prevalent CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 ml/min per 1.73 m2, which was calculated based on cystatin C. Regression models were created to examine the associations of prevalent CKD with quantitative gait markers and the TUG time. Mediation analysis was used to investigate whether poor quantitative gait parameters could be mediators and the proportion of their mediation effects. Results: Participants with prevalent CKD had a higher TUG time (odds ratio = 2.02, P = 0.025) and poor gait performance in the phase domain (standardized ß = -0.391, FDR = 0.009), including less time in the swing phase (standardized ß = -0.365, FDR = 0.027) and greater time in the double-support phase (standardized ß = 0.367, FDR = 0.027). These abnormalities mediated the association of prevalent CKD with a high TUG time (for the swing phase: 31.6 %, P mediation = 0.044; for the double-support phase: 29.6 %, P mediation = 0.042; for the phase domain: 26.9 %, P mediation = 0.048). Conclusion: Poor phase-related gait abnormalities mediated the relationship between CKD and a high TUG time, suggesting that incorporating quantitative gait markers in specific domains may improve fall prevention programs for individuals with CKD.

Nonlinear relationships of circulating polyunsaturated fatty acids with the complications of liver cirrhosis: A prospective, longitudinal cohort study.

BACKGROUND & AIMS: The role of circulating polyunsaturated fatty acids (PUFAs) in preventing liver cirrhosis complications remains unclear. METHODS: Between 2006 and 2010, 273,834 UK Biobank participants with plasma PUFA quantification data were enrolled and followed up until October 31, 2022. Plasma PUFAs were quantified using a high-throughput nuclear magnetic resonance-based metabolic profiling platform. Liver cirrhosis complications were defined as hospitalization for liver cirrhosis or presentation with hepatocellular carcinoma. RESULTS: During a median follow-up of 13.9 years, 2026 participants developed liver cirrhosis complications. Total plasma PUFAs, omega-3 PUFAs, docosahexaenoic acid (DHA), omega-6 PUFAs, and linoleic acid (LA) were inversely associated with the risk of liver cirrhosis complications, whereas the plasma omega-6/omega-3 ratio was positively associated. Nonparametrically restricted cubic spline regression showed nonlinear associations of plasma PUFAs with liver cirrhosis complications. The inflection points were 4.78 mmol/L for total PUFAs, 0.73 mmol/L for omega-3 PUFAs, 0.25 mmol/L for DHA, 4.07 mmol/L for omega-6 PUFAs, and 2.99 mmol/L for LA. Plasma omega-3 PUFAs were negatively associated with the risk of liver cirrhosis complications when omega-3 PUFAs were <0.73 mmol/L (adjusted hazard ratio [HR], 0.11 [0.08-0.16]), whereas the association was inverted when omega-3 PUFAs were ≥0.73 mmol/L (adjusted HR, 1.87 [1.20-2.92]). CONCLUSIONS: The protective effect of plasma omega-3 PUFAs on liver cirrhosis complications is reversed after passing the corresponding inflection point, suggesting an optimal dietary omega-3 PUFA supplementation dose.

Serum Branched-Chain Amino Acids and Long-Term Complications of Liver Cirrhosis: Evidence from a Population-Based Prospective Study.

BACKGROUND AND AIMS: The role of serum branched-chain amino acids (BCAAs) in long-term liver cirrhosis complication events remains unclear. We aimed to evaluate the associations between serum BCAAs and the risk of liver-related events. METHODS: We included a total of 64,005 participants without liver cirrhosis complication events at baseline from the UK Biobank. Cox proportional hazards regression models were utilized to estimate multivariable hazard ratios (HRs) and 95% CIs for the incidence of liver cirrhosis complication events, adjusting for potential confounders, including sociodemographic and lifestyle factors. Relationships between serum BCAAs and liver cirrhosis complications were examined using nonparametrically restricted cubic spline regression. RESULTS: During a median follow-up of 12.7 years, 583 participants developed liver cirrhosis complication events. The multivariable Cox regression model suggested that total BCAAs (HR = 0.88, 95% CI 0.82-0.95), serum leucine (HR = 0.88, 95% CI 0.81-0.95), serum isoleucine (HR = 0.88, 95% CI 0.82-0.96), and serum valine (HR = 0.87, 95% CI 0.82-0.96) were all independent protective factors for liver cirrhosis complications after adjustment for sociodemographic and lifestyle factors. Cox models with restricted cubic splines showed U-shaped associations between serum valine and liver cirrhosis complication incidence. Serum total BCAA and isoleucine concentrations might reduce the risk of liver cirrhosis complications by raising the risk of (type 2 diabetes mellitus) T2DM. CONCLUSION: Lower serum BCAA levels exacerbate the long-term risk of liver cirrhosis complications. Future studies should confirm these findings and identify the biological pathways of these associations.

Characteristics of auto-quantified tumor-infiltrating lymphocytes and the prognostic value in adenocarcinoma of the esophagogastric junction, gastric adenocarcinoma, and esophageal squamous cell carcinoma.

BACKGROUND: Adenocarcinoma of the esophagogastric junction (AEGJ) with a specific pathological profile and poor prognosis has limited therapeutic options. Previous studies have found that TILs exhibit distinct characteristics in different tumors and are correlated with tumor prognosis. We established cellular training sets to obtain auto-quantified TILs in pathological images. And we compared the characteristics of TILs in AEGJ with those in esophageal squamous cell carcinoma (ESCC) and gastric adenocarcinoma (GAC) to gain insight into the unique immune environments of these three tumors and investigate the prognostic value of TILs in these three tumors. METHODS: Utilizing a case-control study design, we analyzed 214 AEGJ, 256 GAC, and 752 ESCC cases. The TCGA dataset was used to validate prognostic value of auto-quantified TILs. The specific cellular training sets were established by experienced pathologists to determine TILs counts. Kruskal-Wallis test and multi-variable linear regression were conducted to explore TILs characteristics. Survival analyses were performed with Kaplan-Meier method and Cox proportional hazards model. RESULTS: The three cellular training sets of these cancers achieved a classification accuracy of 87.55 at least. The median auto-quantified TILs of AEGJ, GAC, and ESCC cases were 4.82%, 1.92%, and 0.12%, respectively. The TILs demonstrated varied characteristics under distinctive clinicopathological traits. The higher TILs proportion was associated with better prognosis in esophagogastric cancers (all P < 0.05) and was an independent prognostic biomarker on AEGJ in both datasets (Taixing: HR = 0.965, 95% CI = 0.938-0.994; TCGA: HR = 0.811, 95% CI = 0.712-0.925). CONCLUSIONS: We found variations in TILs across ESCC, GAC, and AEGJ, as assessed by image processing algorithms. Additionally, TILs in these three cancers are an independent prognostic factor. This enhances our understanding of the unique immune characteristics of the three tumors, improving patient outcomes.

Dietary α-linolenic acid supplementation enhances resistance to Salmonella Typhimurium challenge in chickens by altering the intestinal mucosal barrier integrity and cecal microbes.

Salmonella is an important foodborne pathogen. Given the ban on the use of antibiotics during the egg-laying period in China, finding safe and effective alternatives to antibiotics to reduce Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) infections in chickens is essential for the prevention and control of this pathogen and the protection of human health. Numerous studies have shown that unsaturated fatty acids have a positive effect on intestinal inflammation and resistance to infection by intestinal pathogens. Here we investigated the protective effect of α-linolenic acid (ALA) against S. Typhimurium infection in chickens and further explored its mechanism of action. We added different proportions of ALA to the feed and observed the effect of ALA on S. Typhimurium colonization using metagenomic sequencing technology and physiological index measurements. The role of gut flora on S. Typhimurium colonization was subsequently verified by fecal microbiota transplantation (FMT). We found that ALA protects chickens from S. Typhimurium infection by reducing intestinal inflammation through remodeling the gut microbiota, up-regulating the expression of ileocecal barrier-related genes, and maintaining the integrity of the intestinal epithelium. Our data suggest that supplementation of feed with ALA may be an effective strategy to alleviate S. Typhimurium infection in chickens.

Protein truncating variants in mitochondrial-related nuclear genes and the risk of chronic liver disease.

BACKGROUND: Mitochondrial (MT) dysfunction is a hallmark of liver diseases. However, the effects of functional variants such as protein truncating variants (PTVs) in MT-related genes on the risk of liver diseases have not been extensively explored. METHODS: We extracted 60,928 PTVs across 2466 MT-related nucleus genes using whole-exome sequencing data obtained from 442,603 participants in the UK Biobank. We examined their associations with liver dysfunction that represented by the liver-related biomarkers and the risks of chronic liver diseases and liver-related mortality. RESULTS: 96.10% of the total participants carried at least one PTV. We identified 866 PTVs that were positively associated with liver dysfunction at the threshold of P value < 8.21e - 07. The coding genes of these PTVs were mainly enriched in pathways related to lipid, fatty acid, amino acid, and carbohydrate metabolisms. The 866 PTVs were presented in 1.07% (4721) of participants. Compared with participants who did not carry any of the PTVs, the carriers had a 5.33-fold (95% CI 4.15-6.85), 2.82-fold (1.69-4.72), and 4.41-fold (3.04-6.41) increased risk for fibrosis and cirrhosis of liver, liver cancer, and liver disease-related mortality, respectively. These adverse effects were consistent across subgroups based on age, sex, body mass index, smoking status, and presence of hypertension, diabetes, dyslipidemia, and metabolic syndrome. CONCLUSIONS: Our findings revealed a significant impact of PTVs in MT-related genes on liver disease risk, highlighting the importance of these variants in identifying populations at risk of liver diseases and facilitating early clinical interventions.

A genome-wide association study reveals novel loci and candidate genes associated with plant height variation in Medicago sativa.

BACKGROUND: Plant height (PH) is an important agronomic trait influenced by a complex genetic network. However, the genetic basis for the variation in PH in Medicago sativa remains largely unknown. In this study, a comprehensive genome-wide association analysis was performed to identify genomic regions associated with PH using a diverse panel of 220 accessions of M. sativa worldwide. RESULTS: Our study identified eight novel single nucleotide polymorphisms (SNPs) significantly associated with PH evaluated in five environments, explaining 8.59-12.27% of the phenotypic variance. Among these SNPs, the favorable genotype of chr6__31716285 had a low frequency of 16.4%. Msa0882400, located proximal to this SNP, was annotated as phosphate transporter 3;1, and its role in regulating alfalfa PH was supported by transcriptome and candidate gene association analysis. In addition, 21 candidate genes were annotated within the associated regions that are involved in various biological processes related to plant growth and development. CONCLUSIONS: Our findings provide new molecular markers for marker-assisted selection in M. sativa breeding programs. Furthermore, this study enhances our understanding of the underlying genetic and molecular mechanisms governing PH variations in M. sativa.

Association of Sleep Pattern and Genetic Susceptibility with Obstructive Sleep Apnea: A Prospective Analysis of the UK Biobank.

Purpose: The prevalence of obstructive sleep apnea (OSA) is high worldwide. This study aimed to quantify the relationship between the incidence of OSA and sleep patterns and genetic susceptibility. Methods: A total of 355,133 white British participants enrolled in the UK Biobank between 2006 and 2010 with follow-up data until September 2021 were recruited. We evaluated sleep patterns using a customized sleep scoring method based on the low-risk sleep phenotype, defined as follows: morning chronotype, 7-8 hours of sleep per day, never/rarely experience insomnia, no snoring, no frequent daytime sleepiness, never/rarely nap, and easily getting up early. The polygenic risk score was calculated to assess genetic susceptibility to OSA. Cox proportional hazard models were used to evaluate the associations between OSA and sleep patterns and genetic susceptibility. Results: During a mean follow-up of 12.57 years, 4618 participants were diagnosed with OSA (age: 56.83 ± 7.69 years, women: 31.3%). Compared with those with a poor sleep pattern, participants with a normal (HR: 0.42, 95% CI: 0.38-0.46), ideal (HR: 0.21, 95% CI: 0.19-0.24), or optimal (HR: 0.15, 95% CI: 0.12-0.18) sleep pattern were significantly more likely to have OSA. The genetic susceptibility of 173,239 participants was calculated, and the results showed that poor (HR: 3.67, 95% CI: 2.95-4.57) and normal (HR: 1.89, 95% CI: 1.66-2.16) sleep patterns with high genetic susceptibility can increase the risk for OSA. Conclusion: This large-scale prospective study provides evidence suggesting that sleep patterns across seven low-risk sleep phenotypes may protect against OSA in individuals with varying degrees of genetic susceptibility.

Lipid metabolism mediates the association between body mass index change and bone mineral density: The Taizhou imaging study.

BACKGROUND: Limited research explores the impact of body mass index (BMI) change on osteoporosis, regarding the role of lipid metabolism. We aimed to cross-sectionally investigate these relationships in 820 Chinese participants aged 55-65 from the Taizhou Imaging Study. METHODS: We used the baseline data collected between 2013 and 2018. T-score was calculated by standardizing bone mineral density and was used for osteoporosis and osteopenia diagnosis. Multinomial logistic regression was used to examine the effect of BMI change on bone health status. Multivariable linear regression was employed to identify the metabolites corrected with BMI change and T-score. Exploratory factor analysis (EFA) and mediation analysis were conducted to ascertain the involvement of the metabolites. RESULTS: BMI increase served as a protective factor against osteoporosis (OR = 0.79[0.71-0.88], P-value<0.001) and osteopenia (OR = 0.88[0.82-0.95], P-value<0.001). Eighteen serum metabolites were associated with both BMI change and T-score. Specifically, high-density lipoprotein (HDL) substructures demonstrated negative correlations (ß = -0.08 to -0.06 and - 0.12 to -0.08, respectively), while very low-density lipoprotein (VLDL) substructions showed positive correlations (ß = 0.09 to 0.10 and 0.10 to 0.11, respectively). The two lipid factors (HDL and VLDL) extracted by EFA acted as mediators between BMI change and T-score (Prop. Mediated = 8.16% and 10.51%, all P-value<0.01). CONCLUSION: BMI gain among Chinese aged 55-65 is beneficial for reducing the risk of osteoporosis. The metabolism of HDL and VLDL partially mediates the effect of BMI change on bone loss. Our research offers novel insights into the prevention of osteoporosis, approached from the perspective of weight management and lipid metabolomics.

Association between biological aging and the risk of mortality in individuals with non-alcoholic fatty liver disease: A prospective cohort study.

BACKGROUND: The biological process of aging plays an important role in nonalcoholic fatty liver disease (NAFLD) development. However, epidemiological evidence about the association of biological aging with mortality risk among people with NAFLD is limited. METHODS: A total of 2199 participants with NAFLD from the National Health and Nutrition Examination Surveys (NHANES) III were included. The outcomes were all-cause and cause-specific (cardiovascular disease [CVD], cancer, and diabetes) mortality. We computed three BA measures, the Klemera-Doubal method (KDM) age, Phenotypic age, and homeostatic dysregulation (HD), by using 18 age-associated clinical biomarkers, and assessed their associations with mortality risk using Cox proportional hazards (CPH) models. RESULTS: After a median follow-up of 16 years, a total of 1077 deaths occurred. People with NAFLD who died during follow-up period exhibited higher baseline biological age (BA) and biological age accelerations (BAAs). The multivariate-adjusted CPH suggested that a one-standard deviation (SD) increase in KDM age acceleration, Phenotypic age acceleration, or HD was associated with a 3 %, 7 %, or 39 % elevated risk of all-cause mortality, respectively. The results of age-varying HRs showed that the associations of KDM age accelerations (AAs) and Phenotypic AAs with all-cause mortality appeared to be stronger in people with NAFLD younger than 45 years. CONCLUSIONS: Biological aging was positively associated with both all-cause and cause-specific mortality among people with NAFLD, particularly among younger individuals.

Evolutionary genomics of climatic adaptation and resilience to climate change in alfalfa.

Given the escalating impact of climate change on agriculture and food security, gaining insights into the evolutionary dynamics of climatic adaptation and uncovering climate-adapted variation can empower the breeding of climate-resilient crops to face future climate change. Alfalfa (Medicago sativa subsp. sativa), the queen of forages, shows remarkable adaptability across diverse global environments, making it an excellent model for investigating species responses to climate change. In this study, we performed population genomic analyses using genome resequencing data from 702 accessions of 24 Medicago species to unravel alfalfa's climatic adaptation and genetic susceptibility to future climate change. We found that interspecific genetic exchange has contributed to the gene pool of alfalfa, particularly enriching defense and stress-response genes. Intersubspecific introgression between M. sativa subsp. falcata (subsp. falcata) and alfalfa not only aids alfalfa's climatic adaptation but also introduces genetic burden. A total of 1671 genes were associated with climatic adaptation, and 5.7% of them were introgressions from subsp. falcata. By integrating climate-associated variants and climate data, we identified populations that are vulnerable to future climate change, particularly in higher latitudes of the Northern Hemisphere. These findings serve as a clarion call for targeted conservation initiatives and breeding efforts. We also identified pre-adaptive populations that demonstrate heightened resilience to climate fluctuations, illuminating a pathway for future breeding strategies. Collectively, this study enhances our understanding about the local adaptation mechanisms of alfalfa and facilitates the breeding of climate-resilient alfalfa cultivars, contributing to effective agricultural strategies for facing future climate change.

Pyrococcus furiosus Argonaute Based Detection Assays for Porcine Deltacoronavirus.

Porcine deltacoronavirus (PDCoV) is a major cause of diarrhea and diarrhea-related deaths among piglets and results in massive losses to the overall porcine industry. The clinical manifestations of porcine diarrhea brought on by the porcine epidemic diarrhea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV), and PDCoV are oddly similar to each other. Hence, the identification of different pathogens through molecular diagnosis and serological techniques is crucial. Three novel detection methods for identifying PDCoV have been developed utilizing recombinase-aided amplification (RAA) or reverse transcription recombinase-aided amplification (RT-RAA) in conjunction with Pyrococcus furiosus Argonaute (PfAgo): RAA-PfAgo, one-pot RT-RAA-PfAgo, and one-pot RT-RAA-PfAgo-LFD. The indicated approaches have a detection limit of around 60 copies/µL of PDCoV and do not cross-react with other viruses including PEDV, TGEV, RVA, PRV, PCV2, or PCV3. The applicability of one-pot RT-RAA-PfAgo and one-pot RT-RAA-PfAgo-LFD were examined using clinical samples and showed a positive rate comparable to the qPCR method. These techniques offer cutting-edge technical assistance for identifying, stopping, and managing PDCoV.

Establishment of a mild cognitive impairment risk model in middle-aged and older adults: a longitudinal study.

BACKGROUND: Early identification individuals at high risk of mild cognitive impairment (MCI) is essential for prevention and intervention strategies of dementia, such as Alzheimer's disease. MCI prediction considering the interdependence of predictors in longitudinal data needs to be further explored. We aimed to employ machine learning (ML) to develop and verify a prediction model of MCI. METHODS: In a longitudinal population-based cohort of China Health and Retirement Longitudinal Study (CHARLS), 8390 non-MCI participants were enrolled. The diagnosis of MCI was based on the aging-associated cognitive decline (AACD), and 13 factors (gender, education, marital status, residence, diabetes, hypertension, depression, hearing impairment, social isolation, physical activity, drinking status, body mass index and expenditure) were finally selected as predictors. We implemented a long short-term memory (LSTM) to predict the MCI risks in middle-aged and older adults within 7 years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model. RESULTS: Through 7 years of follow-up, 1925 participants developed MCI. The model for all incident MCI achieved an AUC of 0.774, and its deployment to the participants followed 2, 4, and 7 years achieved results of 0.739, 0.747, and 0.750, respectively. The model was well-calibrated with predicted probabilities plotted against the observed proportions of cognitive impairment. Education level, gender, marital status, and depression contributed most to the prediction of MCI. CONCLUSIONS: This model could be widely applied to medical institutions, even in the community, to identify middle-aged and older adults at high risk of MCI.