DeepAnnotation: A novel interpretable deep learning-based genomic selection model that integrates comprehensive functional annotations.

Background: Genomic selection, which leverages genomic information to predict the breeding value of individuals, has dramatically accelerated the improvement of economically important traits. The growing availability of multiomics data in agricultural species offers an unprecedented opportunity to enrich this process with prior biological knowledge. However, fully harnessing these rich data sources for accurate phenotype prediction in genomic selection remains in its early stages.

Biomechanical evaluation of percutaneous cement discoplasty combined with percutaneous vertebroplasty: a finite element analysis.

Introduction: Since the introduction of percutaneous cement discoplasty (PCD), numerous studies have confirmed its clinical efficacy in elderly patients. However, PCD is also associated with risks such as bone cement leakage and vertebral fractures. The purpose of this study was to present a biomechanical evaluation of two modified versions of PCD performed in combination with percutaneous vertebroplasty (PVP).

Multi-omics analysis reveals critical -regulatory roles of transposable elements in livestock genomes.

Transposable elements (TEs) are important sources of genetic and regulatory variation, yet their functional roles in domesticated animals remain insufficiently explored. To address this gap, we comprehensively annotated TE types, ages, and distributions in the genomes of pig (Sus scrofa), cattle (Bos taurus), and chicken (Gallus gallus). Our analysis revealed species-specific patterns in TE abundance, amplification, and activity in modern genomes.

Analyzing super-enhancer temporal dynamics reveals potential critical enhancers and their gene regulatory networks underlying skeletal muscle development.

Super-enhancers (SEs) govern the expression of genes defining cell identity. However, the dynamic landscape of SEs and their critical constituent enhancers involved in skeletal muscle development remains unclear. In this study, using pig as a model, we employed cleavage under targets and tagmentation (CUT&Tag) to profile the enhancer-associated histone modification marker H3K27ac in skeletal muscle across two prenatal and three postnatal stages, and investigated how SEs influence skeletal muscle development.

A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity.

Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene therapy. Despite numerous high-throughput methods facilitating genome-wide enhancer identification, deciphering the sequence determinants of their activity remains challenging. Here, we present the DREAM (DNA cis-Regulatory Elements with controllable Activity design platforM) framework, a novel deep learning-based approach for synthetic enhancer design.

The characteristics of intestinal microbiota in patients with type 2 diabetes and the correlation with the percentage of T-helper cells.

Background: Type 2 diabetes (T2D) is related to intestinal microflora changes and immune inflammation. We aimed to investigate the pattern of intestinal flora-systematic T helper (Th) cell linkage in T2D patients.

Methods: Participants with T2D diagnosed by physicians and healthy controls were enrolled in the study.

Non-linear association and benchmark dose of blood pressure on carotid artery intima-media thickening in a general population of southern China.

Background And Aims: This study aimed to evaluate whether there is a J-curve association between blood pressure (BP) and carotid artery intima-media thickening (CAIT) and estimate the effect of the turning point of BP on CAIT.

Methods And Results: Data from 111,494 regular physical examinations conducted on workers and retirees (aged 18 years or older) between January 2011 and December 2016, exported from the hospital information system, were analyzed. Restricted cubic splines (RCS) logistic regression was employed to access the association of BP with CAIT, and Bayesian benchmark dose methods were used to estimate the benchmark dose as the departure point of BP measurements.

Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs.

Background: Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking.

Results: Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc.

Machine learning classifiers for screening nonalcoholic fatty liver disease in general adults.

Nonalcoholic fatty liver disease (NAFLD) is one of major causes of end-stage liver disease in the coming decades, but it shows few symptoms until it develops into cirrhosis. We aim to develop classification models with machine learning to screen NAFLD patients among general adults. This study included 14,439 adults who took health examination.

Oxidative stress-mediated influence of plasma DPP4 activity to BDNF ratio on mild cognitive impairment in elderly type 2 diabetic patients: results from the GDMD study in China.

Objective: Increased dipeptidyl peptidase-4 (DPP4) activity and reduced brain-derived neurotrophic factor (BDNF) in peripheral circulation are both associated with a high risk of mild cognitive impairment (MCI) in the elderly. Hence, we aimed to investigate the association between plasma DPP4 activity to BDNF ratio (DBR) and MCI in elderly patients with type 2 diabetes.

Design And Methods: We measured plasma DPP4 activity, BDNF levels, oxidative stress parameters, inflammatory markers and calculated DBR in 1833 elderly type 2 diabetic patients aged 60 years or older.

Strong Association between Plasma Dipeptidyl Peptidase-4 Activity and Impaired Cognitive Function in Elderly Population with Normal Glucose Tolerance.

Inflammation, oxidative stress, and decreased glucagon-like peptide-1 (GLP-1) are risk factors for cognitive impairment. Dipeptidyl peptidase-4 (DPP4) was identified as a novel adipokine capable of enhancing these risk factors. Hence, we investigated the relationship between plasma DPP4 activity and impaired cognitive function in elderly Chinese population with normal glucose tolerance (NGT).

Increased Dipeptidyl Peptidase-4 Activity Is Associated With High Prevalence of Depression in Middle-Aged and Older Adults: A Cross-Sectional Study.

Objective: Obesity, inflammation, and decreased neuropeptide Y (NPY) are risk factors for depression. Dipeptidyl peptidase-4 (DPP4), a newly identified adipokine, has been proved to promote inflammation and NPY degradation. Hence, we aimed to investigate the association between plasma DPP4 activity and depression symptoms in middle-aged and older adults.

Association of Plasma DPP4 Activity With Mild Cognitive Impairment in Elderly Patients With Type 2 Diabetes: Results From the GDMD Study in China.

Objective: Hyperglycemia, inflammation, and oxidative stress are thought to be involved in the pathogenesis of cognitive decline. Dipeptidyl peptidase-4 (DPP4) is a newly identified adipokine related to these risk factors. Hence, we aimed to investigate the association between plasma DPP4 activities and mild cognitive impairment (MCI) in elderly patients with type 2 diabetes.

Increased plasma dipeptidyl peptidase-4 activities are associated with high prevalence of diabetic nephropathy in Chinese patients with newly diagnosed type 2 diabetes: A cross-sectional study.

Objective: To investigate the association between plasma Dipeptidyl peptidase-4 (DPP4) activities and diabetic nephropathy in type 2 diabetes.

Research Design And Methods: A total of 1193 newly diagnosed type 2 diabetic subjects were studied. Plasma DPP4 activity, mannose 6-phosphate receptor, inflammatory markers and oxidative stress parameters were measured in all participants.

Plasma DPP4 Activities Are Associated With Osteoporosis in Postmenopausal Women With Normal Glucose Tolerance.

Context: Inflammation, insulin resistance, dyslipidemia, and glucagon-like peptide-1 (GLP-1) are risk factors for osteoporosis. Dipeptidyl peptidase-4 (DPP4) is a newly identified adipokine related to these risk factors.

Objective: To investigate the association between plasma DPP4 activities and osteoporosis.