Bidirectional regulation of the brain-gut-microbiota axis following traumatic brain injury.

JOURNAL/nrgr/04.03/01300535-202508000-00002/figure1/v/2024-09-30T120553Z/r/image-tiff Traumatic brain injury is a prevalent disorder of the central nervous system. In addition to primary brain parenchymal damage, the enduring biological consequences of traumatic brain injury pose long-term risks for patients with traumatic brain injury; however, the underlying pathogenesis remains unclear, and effective intervention methods are lacking. Intestinal dysfunction is a significant consequence of traumatic brain injury. Being the most densely innervated peripheral tissue in the body, the gut possesses multiple pathways for the establishment of a bidirectional "brain-gut axis" with the central nervous system. The gut harbors a vast microbial community, and alterations of the gut niche contribute to the progression of traumatic brain injury and its unfavorable prognosis through neuronal, hormonal, and immune pathways. A comprehensive understanding of microbiota-mediated peripheral neuroimmunomodulation mechanisms is needed to enhance treatment strategies for traumatic brain injury and its associated complications. We comprehensively reviewed alterations in the gut microecological environment following traumatic brain injury, with a specific focus on the complex biological processes of peripheral nerves, immunity, and microbes triggered by traumatic brain injury, encompassing autonomic dysfunction, neuroendocrine disturbances, peripheral immunosuppression, increased intestinal barrier permeability, compromised responses of sensory nerves to microorganisms, and potential effector nuclei in the central nervous system influenced by gut microbiota. Additionally, we reviewed the mechanisms underlying secondary biological injury and the dynamic pathological responses that occur following injury to enhance our current understanding of how peripheral pathways impact the outcome of patients with traumatic brain injury. This review aimed to propose a conceptual model for future risk assessment of central nervous system-related diseases while elucidating novel insights into the bidirectional effects of the "brain-gut-microbiota axis."

Longitudinal Patterns of Ankle-Brachial Index and Their Association With Progression of CKD in Patients With Type 2 Diabetes and Elevated Body Mass Index.

RATIONALE & OBJECTIVE: Ankle-brachial index (ABI) is used to screen for vascular complications in the setting of diabetes. This study sought to examine the relationship of longitudinal ABI data and chronic kidney disease (CKD) progression in patients with type 2 diabetes (T2D) and elevated body mass index (BMI). STUDY DESIGN: A post-hoc analysis of the Look AHEAD trial. SETTING & PARTICIPANTS: This study included 3,631 participants in the Look AHEAD trial with a baseline glomerular filtration rate (eGFR) >60 ml/min/1.73 m2. EXPOSURES: Average ABI and average annual change in ABI were calculated based on annual ABI measurements during the first 4 years of the study. OUTCOME: CKD progression, defined as kidney failure requiring maintenance dialysis or the occurrence of eGFR<60 ml/min/1.73 m2 with a drop of ≥30% at a follow-up visit relative to the first eGFR measurement. ANALYTICAL APPROACH: Restricted cubic spline and Cox proportional hazards models were fit to estimate associations and to explore non-linearity. RESULTS: Over a median follow-up of 10.1 years, 1,051 participants developed CKD progression. There was a reversed J-shaped relationship of CKD progression with average ABI (when ABI <1.17: HR (per SD decrement), 1.23; 95%CI, 1.06-1.42; when ABI ≥ 1.17: HR (per SD increment), 1.10; 95%CI, 1.00-1.22) and average annual change in ABI (when change in ABI <-0.007: HR (per SD decrement), 1.37; 95%CI, 1.12-1.66; when change in ABI ≥-0.007: HR (per SD increment), 1.13; 95%CI, 1.03-1.24). LIMITATIONS: Observational study, potential unmeasured confounding. CONCLUSIONS: Low and high average ABI, even at clinically normal values, as well as decreasing and increasing average annual ABI, were associated a higher risk of CKD progression in patients with T2D and elevated BMI. Monitoring ABI and its changes over time may facilitate CKD risk stratification in patients with T2D.

Serum 25-hydroxyvitamin D, genetic susceptibility and abdominal aortic aneurysm risk.

CONTEXT: The association of serum 25-hydroxyvitamin D [25(OH)D] and genetic polymorphisms of the vitamin D receptor (VDR), and the vitamin D binding protein (VDBP) with incident abdominal aortic aneurysm (AAA) remains uncertain. OBJECTIVE: To investigate whether serum 25(OH)D, genetic polymorphisms of VDR and VDBP, genetic susceptibility to AAA, and the interactions among these factors influence the risk of incident AAA. DESIGN: Retrospective cohort study. SETTING: UK Biobank. PARTICIPANTS: 447,529 participants without a diagnosis of prevalent aortic aneurysm or aortic dissection at baseline. EXPOSURE: Serum 25(OH)D concentration. MAIN OUTCOME MEASURE: Incident AAA. RESULTS: During a median follow-up of 12.5 years, 2,042 participants developed incident AAA. A significant inverse association between serum 25(OH)D and incident AAA was observed (per SD increment, HR, 0.92; 95%CI, 0.88-0.96), which was particularly pronounced in older individuals and those without diabetes (both P for interaction <0.05). Compared to participants with serum 25(OH)D ≥ 50 nmol/L, those with serum 25(OH)D between 25 and <50 nmol/L and <25 nmol/L exhibited a significant higher risk of incident AAA. In the 371,621 participants with genetics assessment, individuals carrying AA alleles of ApaI SNP had a significant increased risk of incident AAA compared to those carrying CC alleles (HR, 1.16; 95%CI, 1.02-1.32). The inverse association between serum 25(OH)D and incident AAA was stronger in individuals with intermediate or high genetic risk for AAA (P for interaction = 0.048). CONCLUSIONS: There was a significant inverse association between serum 25(OH)D and AAA incidence, particularly among individuals with higher genetic risk for AAA, older age, and without diabetics.

Chromosome-level genome assembly of the cashmere goat.

The goat, an early domesticated ruminant, is a reliable source of cashmere, meat and milk in global agricultural production. Despite this, the genome of cashmere-rich goats has yet to be characterized. Here, we assembled the nearly complete genome of a cashmere goat from a highly economically valuable Inner Mongolian Cashmere buck, utilizing a combination of PacBio HiFi, ONT ultra-long reads, and Hi-C technologies. The size of this genome is 2.76 Gb, with a contig N50 of 95.22 Mb. All assembled sequences were anchored onto 29 autosomes and both sex chromosomes, with only two gaps present on the X chromosome. We identified 1,333.29 Mb (48.26%) of repetitive sequences and predicted 22,480 protein-coding genes. Assembly quality assessment of the genome demonstrated that our assembled cashmere goat genome surpasses the continuity, completeness, and accuracy of other published goat genomes. Taken together, we provided the first cashmere goat assembly, bridging the gap in the genome of important economic breeds of domestic goats, and providing a valuable reference resource for goat genetics and genome research.

High-risk nuclide screening and parameter sensitivity analysis based on numerical simulation and machine learning.

During nuclear accidents, large quantities of radionuclides will be released into the environment, posing serious health hazards to local residents. The screening of high-risk nuclides is critical for the development of subsequent nuclear emergency response measures. In order to overcome the shortcomings of traditional screening methods, a machine learning method was proposed to screen high-risk nuclides and predict their contamination to groundwater more effectively. The performances of Support Vector Machine (SVM), Random Forest (RF) and Back Propagation Neural Network (BPNN) algorithms were compared, and sensitivity analyses of the initial leakage concentration ratio (C0/Cp), distribution coefficient (Kd) and decay coefficient (λ) on the model outputs were performed. Results showed that RF classification model achieved the highest prediction accuracy for screening high-risk nuclides. The contribution of the input parameters ranked as Kd > λ > C0/Cp. BPNN regression model was found to be the best for predicting when high-risk nuclides would pollute groundwater. The output was negatively correlated with C0/Cp and positively correlated with Kd and λ, with the parameter influence ranking as Kd > C0/Cp > λ. The contribution of Kd mainly came from itself, and the contribution of C0/Cp and λ mainly due to their interaction with other parameters.

MAT2B regulates the protein level of MAT2A to preserve RNA N6-methyladenosine.

MAT2B works together with MAT2A to synthesize S-Adenosyl methionine (SAM) as the primary methyl donor. MAT2B, despite lacking catalytic activity, exerts regulatory control over the enzymatic activity of MAT2A. In addition to the enzymatic activity regulation, we find that, in an NADP+-dependent manner, MAT2B binds and stabilizes MAT2A. Disruption of the cellular NADP+ remodels the protein level of MAT2A. The pentose phosphatase pathway regulates the level of MAT2A protein through the interaction of NADP+ with MAT2B. Additionally, MAT2B-MAT2A interaction regulates the mRNA m6A modification and stability. In liver tumors, the Mat2a mRNA level is elevated but the protein level is decreased by the restricted NADP+. Blocking the interaction between MAT2B and MAT2A by the keto diet can suppress liver tumor growth. These findings reveal that MAT2B is essential for regulating the protein levels of MAT2A and connecting SAM synthesis to mRNA m6A.

Combined Genome-Wide Association Study and Haplotype Analysis Identifies Candidate Genes Affecting Growth Traits of Inner Mongolian Cashmere Goats.

In this study, genome-wide association analysis was performed on the growth traits (body height, body length, chest circumference, chest depth, chest width, tube circumference, and body weight) of Inner Mongolian cashmere goats (Erlangshan type) based on resequencing data. The population genetic parameters were estimated, haplotypes were constructed for the significant sites, and association analysis was conducted between the haplotypes and phenotypes. A total of two hundred and eighty-four SNPs and eight candidate genes were identified by genome-wide association analysis, gene annotation, and enrichment analysis. The phenotypes of 16 haplotype combinations were significantly different by haplotype analysis. Combined with the above results, the TGFB2, BAG3, ZEB2, KCNJ12, MIF, MAP2K3, HACD3, and MEGF11 functional candidate genes and the haplotype combinations A2A2, C2C2, E2E2, F2F2, I2I2, J2J2, K2K2, N2N2, O2O2, P2P2, R1R1, T1T1, W1W1, X1X1, Y1Y1, and Z1Z1 affected the growth traits of the cashmere goats and could be used as molecular markers to improve the accuracy of early selection and the economic benefits of breeding.

Accelerometer-derived moderate-to-vigorous physical activity and incident nonalcoholic fatty liver disease.

BACKGROUND: The liver effects of concentrated vs. more evenly distributed moderate-to-vigorous physical activity (MVPA) patterns remain unclear. We aimed to examine the association of accelerometer-measured MVPA and different MVPA patterns with liver outcomes. METHODS: Eighty-eight thousand six hundred fifty-six participants without prior liver diseases from UK Biobank were included. MVPA was measured by a wrist-worn accelerometer. Based on the guideline-based threshold (≥ 150 min/week), MVPA patterns were defined as inactive (< 150 min/week), active weekend warrior (WW; ≥ 150 min/week with ≥ 50% of total MVPA achieved within 1-2 days), and regularly active (≥ 150 min/week but not active WW) patterns. The primary outcome was incident nonalcoholic fatty liver disease (NAFLD). RESULTS: During a median follow-up of 6.8 years, 562 participants developed NAFLD. Overall, there was a nonlinear inverse association of total MVPA with incident NAFLD (P for nonlinearity = 0.009): the risk of NAFLD rapidly decreased with the increment of MVPA (per 100 min/week increment: HR = 0.68; 95%CI, 0.57-0.81) when MVPA < 208 min/week, while moderately declined (HR = 0.91; 95%CI, 0.84-0.99) when MVPA ≥ 208 min/week. For MVPA patterns, compared with inactive group, both active WW (HR = 0.55, 95%CI, 0.44-0.67) and active regular (HR = 0.49, 95%CI, 0.38-0.63) group were associated with a similar lower risk of NAFLD. Similar results were observed for each secondary outcome, including incident severe liver diseases, incident liver cirrhosis, and liver magnetic resonance imaging-based liver steatosis and fibrosis. CONCLUSIONS: Regardless of whether MVPA was concentrated within 1 to 2 days or spread over most days of the week, more MVPA was associated with a lower risk of incident liver outcomes, including NAFLD, liver cirrhosis, liver steatosis, and fibrosis, to MVPA more evenly distributed.

Monitoring Partial EMT Dynamics through Cell Mechanics Using Scanning Ion Conductance Microscopy.

Tumor cells undergo an epithelial-mesenchymal transition (EMT) accompanied by a reduction in elasticity to initiate metastasis. However, in vivo, tumor cells typically exhibit partial EMT rather than fully EMT. Whether cell mechanics can accurately identify the status of partial EMT, especially the dynamic process, remains unclear. To elucidate the relationship between cell mechanics and partial EMT, we employed scanning ion conductance microscopy (SICM) to analyze the dynamic changes in cell mechanics during the TGFß-induced partial EMT of HCT116 colon cancer cells. Cells undergoing partial EMT, characterized by increased expression of EMT transcription factors, Snai1 and Zeb1, and EMT-related genes, Fn1 and MMP9, while retaining the expression of the epithelial markers E-cadherin (E-cad) and EpCAM, did not exhibit significant changes in cell morphology, suggesting that morphological changes alone were inadequate for identifying partial EMT status. However, cell elasticity markedly decreased in partial EMT cells, and this reduction was reversed with the reversible transition of partial EMT. These findings suggest a strong correlation between cell mechanics and the dynamic process of partial EMT, indicating that cell mechanics could serve as a valuable label-free marker for identifying the status of partial EMT while preserving the physiological characteristics of tumor cells.

Global progress in clinical research on human respiratory syncytial virus vaccines.

Human respiratory syncytial virus (hRSV) not only affects newborns but also older adults, contributing to a substantial worldwide burden of disease. However, only three approved hRSV vaccines remain commercially available to date. The development of a safe, practical and broad-spectrum vaccine suitable for all age groups remains extremely challenging. Using five different approaches-live-attenuated, recombinant-vector, subunit, particle-based, and mRNA-nearly 30 hRSV vaccine candidates are currently conducting clinical trials worldwide; moreover, > 30 vaccines are under preclinical evaluation. This review presents a comprehensive overview of these hRSV vaccines along with prospects for the development of infectious disease vaccines in the post-COVID-19 pandemic era.

Inner strength, coping self-efficacy and coping strategy of patients with peritoneal dialysis: A exploratory cross-sectional study.

AIM: The purpose of the study was to investigate and analyse inner strength of patients with peritoneal dialysis, explore the associations among inner strength, coping self-efficacy (CSE) and medial coping modes. DESIGN: This was a cross-sectional study which was conducted in nephrology departments of two affiliated hospitals of a comprehensive university in China. Convenience sampling was chosen to collect data. METHODS: A total of 191 patients undergoing peritoneal dialysis were recruited by convenience sampling in two hospitals. Data involved of sociodemographic and clinical materials, inner strength, CSE and medical coping modes were collected from the patients. IBM SPSS Statistics 21.0 was used to process and analyse the data. RESULTS: The averaged score of inner strength was 95.74 (SD = 13.52). The inner strength, CSE and confrontation coping had positive associations with each other. Besides, inner strength and CSE was negatively associated with acceptance-resignation coping strategy, respectively.

Regular Mobile Phone Use and Incident Cardiovascular Diseases: Mediating Effects of Sleep Patterns, Psychological Distress, and Neuroticism.

BACKGROUND: The relationship between mobile phone use and incident cardiovascular disease (CVD) is uncertain. We aimed to examine the association of regular mobile phone use with incident CVD and explore the mediating effects of sleep and mental health. METHODS: A total of 444,027 individuals from the UK Biobank without a history of CVD were included. Regular mobile phone use was defined as at least 1 call per week. Weekly mobile phone usage time was self-reported as the average time of calls per week over the previous 3 months. The primary outcome was incident CVD. The secondary outcomes included each component of CVD and increased carotid intima-media thickness (CIMT). We applied Cox proportional hazard models to assess the association between mobile phone use and incident CVD, and mediation analyses to investigate the role of sleep patterns, psychologic distress, and neuroticism. RESULTS: In a median follow-up period of 12.3 years, 56,181 individuals developed incident CVD. Compared with nonregular mobile phone users, regular mobile phone users had a significantly higher risk of incident CVD (hazard ratio 1.04, 95% confidence interval 1.02-1.06) and increased CIMT (odds ratio 1.11, 95% CI 1.04-1.18). Among regular mobile phone users, weekly mobile phone usage time was positively associated with the risk of incident CVD, especially in current smokers (P for interaction = 0.001) and diabetic individuals (P for interaction = 0.037). Of the relationship between weekly mobile phone usage time and incident CVD, 5.11% was mediated by sleep patterns, 11.5% by psychological distress, and 2.25% by neuroticism. CONCLUSIONS: Weekly mobile phone usage time was positively associated with incident CVD risk, which was partly explained by poor sleep, psychologic distress, and neuroticism.

A Study on the Binding Mechanism and the Impact of Key Residue Mutations between SND1 and MTDH Peptide through Molecular Dynamics Simulations.

Metastasis of breast cancer is the main cause of death for patients with breast cancer. The interaction between metadherin (MTDH) and staphylococcal nuclease domain 1 (SND1) plays a pivotal role in promoting breast cancer development. However, the binding details between MTDH and SND1 remain unclear. In this study, we employed all-atom molecular dynamics simulations (MDs) and conducted binding energy calculations to investigate the binding details and the impact of key residue mutations on binding. The mutations in key residues have not significantly affected the overall stability of the structure and the fluctuation of residues near the binding site; they have exerted a substantial impact on the binding of SND1 and MTDH peptide. The electrostatic interactions and van der Waals interactions play an important role in the binding of SND1 and the MTDH peptide. The mutations in the key residues have a significant impact on electrostatic and van der Waals interactions, resulting in weakened binding. The energy contributions of key residues mainly come from the electrostatic energy and van der Waals interactions of the side chain. In addition, the key residues form an intricate and stable network of hydrogen bonds and salt-bridge interactions with the MTDH peptide. The mutations in key residues have directly disrupt the interactions formed between SND1 and MTDH peptide, consequently leading to changes in the binding mode of the MTDH peptide. These analyses unveil the detailed atomic-level interaction mechanism between SND1 and the MTDH peptide, providing a molecular foundation for the development of antibreast cancer drugs.

Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores.

BACKGROUND: Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank. METHODS: We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score. RESULTS: Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively). CONCLUSIONS: A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.

Pickering emulsion of camellia oil stabilized by Octenyl succinic acid starch: Interaction, lipid oxidation and digestibility.

The application of camellia oil is limited by its susceptibility to oxidation and insolubility in water, particularly under high humidity and temperature conditions. In order to effectively reduce the oxidation rate of camellia oil, prolong the shelf life in order to improve the stability in storage under different conditions, this study encapsulates camellia oil in Pickering emulsions stabilized by Octenyl succinic acid (OSA) starch, achieving a 100-fold reduction in release rate and enhanced lipid oxidation stability. The smooth surface and complete particles of the emulsion were observed and no new chemical bonds were formed. The minimum particle sizes were 1.72 µm and 2.73 µm, when the Pickering emulsion was set at pH 6 and 0.1 M NaCl. In the digestion process, the microstructures observed that Pickering emulsion possessed super stability against oral and gastric digestions, prolonged the release time and improved the bioavailability compared with camellia oil, and the digestibility of the emulsion was 56.16 % within 120 min. All these results indicate that OSA-starch stabilized camellia oil can effectively increase solubility, improve stability and expand the application range.

Plasma proteomics for risk prediction of Alzheimer's disease in the general population.

We aimed to develop and validate a protein risk score for predicting Alzheimer's disease (AD) and compare its performance with a validated clinical risk model (Cognitive Health and Dementia Risk Index for AD [CogDrisk-AD]) and apolipoprotein E (APOE) genotypes. The development cohort, consisting of 35,547 participants from England in the UK Biobank, was randomly divided into a 7:3 training-testing ratio. The validation cohort included 4667 participants from Scotland and Wales in the UK Biobank. In the training set, an AD protein risk score was constructed using 31 proteins out of 2911 proteins. In the testing set, the AD protein risk score had a C-index of 0.867 (95% CI, 0.828, 0.906) for AD prediction, followed by CogDrisk-AD risk factors (C-index, 0.856; 95% CI, 0.823, 0.889), and APOE genotypes (C-index, 0.705; 95% CI, 0.660, 0.750). Adding the AD protein risk score to CogDrisk-AD risk factors (C-index increase, 0.050; 95% CI, 0.008, 0.093) significantly improved the predictive performance for AD. However, adding CogDrisk-AD risk factors (C-index increase, 0.040; 95% CI, -0.007, 0.086) or APOE genotypes (C-index increase, 0.000; 95% CI, -0.054, 0.055) to the AD protein risk score did not significantly improve the predictive performance for AD. The top 10 proteins with the highest coefficients in the AD protein risk score contributed most of the predictive power for AD risk. These results were verified in the external validation cohort. EGFR, GFAP, and CHGA were identified as key proteins within the protein network. Our result suggests that the AD protein risk score demonstrated a good predictive performance for AD risk.

Matrix Viscoelasticity Tunes the Mechanobiological Behavior of Chondrocytes.

In articular cartilage, the pericellular matrix acting as a specialized mechanical microenvironment modulates environmental signals to chondrocytes through mechanotransduction. Matrix viscoelastic alterations during cartilage development and osteoarthritis (OA) degeneration play an important role in regulating chondrocyte fate and cartilage matrix homeostasis. In recent years, scientists are gradually realizing the importance of matrix viscoelasticity in regulating chondrocyte function and phenotype. Notably, this is an emerging field, and this review summarizes the existing literatures to the best of our knowledge. This review provides an overview of the viscoelastic properties of hydrogels and the role of matrix viscoelasticity in directing chondrocyte behavior. In this review, we elaborated the mechanotransuction mechanisms by which cells sense and respond to the viscoelastic environment and also discussed the underlying signaling pathways. Moreover, emerging insights into the role of matrix viscoelasticity in regulating chondrocyte function and cartilage formation shed light into designing cell-instructive biomaterial. We also describe the potential use of viscoelastic biomaterials in cartilage tissue engineering and regenerative medicine. Future perspectives on mechanobiological comprehension of the viscoelastic behaviors involved in tissue homeostasis, cellular responses, and biomaterial design are highlighted. Finally, this review also highlights recent strategies utilizing viscoelastic hydrogels for designing cartilage-on-a-chip.

Molecular mechanisms of mitochondrial homeostasis regulation in neurons and possible therapeutic approaches for Alzheimer's disease.

Alzheimer's disease (AD) is a neurological disease with memory loss and cognitive decline, which affects a large proportion of the aging population. Regrettably, there are no drug to reverse or cure AD and drug development for the primary theory of amyloid beta deposition has mostly failed. Therefore, there is an urgent need to investigate novel strategies for preventing AD. Recent studies demonstrate that imbalance of mitochondrial homeostasis is a driver in Aß accumulation, which can lead to the occurrence and deterioration of cognitive impairment in AD patients. This suggests that regulating neuronal mitochondrial homeostasis may be a new strategy for AD. We summarize the importance of mitochondrial homeostasis in AD neuron and its regulatory mechanisms in this review. In addition, we summarize the results of studies indicating mitochondrial dysfunction in AD subjects, including impaired mitochondrial energy production, oxidative stress, imbalance of mitochondrial protein homeostasis, imbalance of fusion and fission, imbalance of neuronal mitochondrial biogenesis and autophagy, and altered mitochondrial motility, in hope of providing possible therapeutic approaches for AD.

Estimation of Genetic Parameters of Early Growth Traits in Dumeng Sheep.

This study aimed to estimate the genetic and non-genetic factors that affect the nine early growth traits of Dumeng sheep, as well as to estimate the variance components and genetic parameters associated with these traits. A dataset containing detailed information on 17,896 preweaning trait records of 4474 lambs was collected. In addition, 5015 postweaning trait records of 1003 lambs were documented. The effects of recipient dam age, sex, year, season, and herd on the early growth traits were assessed using the general linear model procedure of the statistical analysis system, revealing different levels of significance across different traits. To determine the most suitable model for estimating the genetic parameters, the likelihood ratio (LR) test was employed, fitting six animal models that either excluded or included maternal genetic and maternal permanent environmental effects within the average information restricted maximum likelihood (AIREML) framework using WOMBAT software (Version: 23/11/23). The model incorporating direct additive genetic effects, maternal genetic effects, and maternal permanent environment effects as random effects (model 6) provided the best fit for birth weight (BW) estimation. In contrast, the model combining direct additive genetic effects and maternal permanent environment effects as random effects (model 2) demonstrated a superior fit for estimating the genetic parameters of weaning weight (WW), average daily gain weight from birth to weaning (ADG1), and Kleiber ratio from birth to weaning (KR1). With regard to the genetic parameters of body weight at 6 months of age (6MW), average daily gain weight from weaning to 6 months (ADG2), average daily gain weight from birth to 6 months (ADG3), Kleiber ratio from weaning to 6 months (KR2), and Kleiber ratio from birth to 6 months (KR3), model 1, which incorporates only direct additive genetic effects, was identified as the optimal choice. With the optimal model, the heritability estimates ranged from 0.010 ± 0.033 for 6MW to 0.1837 ± 0.096 for KR3. The bivariate analysis method was employed to estimate the correlation between various traits using the most suitable model. The absolute values of genetic correlation coefficients among the traits spanned a range from 0.1460 to 0.9998, highlighting both weak and strong relationships among the studied traits. Specifically, the estimated genetic correlations between WW and ADG1, ADG3, KR1, and KR3 were 0.9859, 0.9953, 0.9911, and 0.9951, respectively, while the corresponding phenotypic correlations were 0.9752, 0.7836, 0.8262, and 0.5767. These findings identified that WW could serve as an effective selection criterion for enhancing early growth traits.

Semi-supervised lung adenocarcinoma histopathology image classification based on multi-teacher knowledge distillation.

Objective.In this study, we propose a semi-supervised learning (SSL) scheme using a patch-based deep learning (DL) framework to tackle the challenge of high-precision classification of seven lung tumor growth patterns, despite having a small amount of labeled data in whole slide images (WSIs). This scheme aims to enhance generalization ability with limited data and reduce dependence on large amounts of labeled data. It effectively addresses the common challenge of high demand for labeled data in medical image analysis.Approach.To address these challenges, the study employs a SSL approach enhanced by a dynamic confidence threshold mechanism. This mechanism adjusts based on the quantity and quality of pseudo labels generated. This dynamic thresholding mechanism helps avoid the imbalance of pseudo-label categories and the low number of pseudo-labels that may result from a higher fixed threshold. Furthermore, the research introduces a multi-teacher knowledge distillation (MTKD) technique. This technique adaptively weights predictions from multiple teacher models to transfer reliable knowledge and safeguard student models from low-quality teacher predictions.Main results.The framework underwent rigorous training and evaluation using a dataset of 150 WSIs, each representing one of the seven growth patterns. The experimental results demonstrate that the framework is highly accurate in classifying lung tumor growth patterns in histopathology images. Notably, the performance of the framework is comparable to that of fully supervised models and human pathologists. In addition, the framework's evaluation metrics on a publicly available dataset are higher than those of previous studies, indicating good generalizability.Significance.This research demonstrates that a SSL approach can achieve results comparable to fully supervised models and expert pathologists, thus opening new possibilities for efficient and cost-effective medical images analysis. The implementation of dynamic confidence thresholding and MTKD techniques represents a significant advancement in applying DL to complex medical image analysis tasks. This advancement could lead to faster and more accurate diagnoses, ultimately improving patient outcomes and fostering the overall progress of healthcare technology.