Quantifying the natural inter-individual variation in DNA methylation patterns is important for identifying its contribution to phenotypic variation, but also for understanding how the environment affects variability, and for incorporation into statistical analyses. The inter-individual variation in DNA methylation patterns in female cattle and the effect that a prenatal stressor has on such variability have yet to be quantified. Thus, the objective of this study was to utilize methylation data from mature Brahman females to quantify the inter-individual variation in DNA methylation. Pregnant Brahman cows were transported for 2 h durations at days 60 ± 5; 80 ± 5; 100 ± 5; 120 ± 5; and 140 ± 5 of gestation. A non-transport group was maintained as a control. Leukocytes, amygdala, and anterior pituitary glands were harvested from eight cows born from the non-transport group (Control) and six from the transport group (PNS) at 5 years of age. The DNA harvested from the anterior pituitary contained the greatest variability in DNA methylation of cytosine-phosphate-guanine (mCpG) sites from both the PNS and Control groups, and the amygdala had the least. Numerous variable mCpG sites were associated with retrotransposable elements and highly repetitive regions of the genome. Some of the genomic features that had high variation in DNA methylation are involved in immune responses, signaling, responses to stimuli, and metabolic processes. The small overlap of highly variable CpG sites and features between tissues and leukocytes supports the role of variable DNA methylation in regulating tissue-specific gene expression. Many of the CpG sites that exhibited high variability in DNA methylation were common between the PNS and Control groups within a tissue, but there was little overlap in genomic features with high variability. The interaction between the prenatal environment and the genome could be responsible for the differences in location of the variable DNA methylation.

Knowledge of circadian rhythm clock gene expression outside the suprachiasmatic nucleus is increasing. The purpose of this study was to determine whether expression of circadian clock genes differed within or among the bovine stress axis tissues (e.g., amygdala, hypothalamus, pituitary, adrenal cortex, and adrenal medulla). Tissues were obtained at an abattoir from eight mature nonpregnant Brahman cows that had been maintained in the same pasture and nutritional conditions. Sample tissues were stored in RNase-free sterile cryovials at −80 °C until the total RNA was extracted, quantified, assessed, and sequenced (NovaSeq 6000 system; paired-end 150 bp cycles). The trimmed reads were then mapped to a Bos taurus (B. taurus) reference genome (Umd3.1). Further analysis used the edgeR package. Raw gene count tables were read into RStudio, and low-expression genes were filtered out using the criteria of three minimum reads per gene in at least five samples. Normalization factors were then calculated using the trimmed mean of M values method to produce normalized gene counts within each sample tissue. The normalized gene counts important for a circadian rhythm were analyzed within and between each tissue of the stress axis using the GLM and CORR procedures of the Statistical Analysis System (SAS). The relative expression profiles of circadian clock genes differed (p < 0.01) within each tissue, with neuronal PAS domain protein 2 (NPAS2) having greater expression in the amygdala (p < 0.01) and period circadian regulator (PER1) having greater expression in all other tissues (p < 0.01). The expression among tissues also differed (p < 0.01) for individual circadian clock genes, with circadian locomotor output cycles protein kaput (CLOCK) expression being greater within the adrenal tissues and nuclear receptor subfamily 1 group D member 1 (NR1D1) expression being greater within the other tissues (p < 0.01). Overall, the results indicate that within each tissue, the various circadian clock genes were differentially expressed, in addition to being differentially expressed among the stress tissues of mature Brahman cows. Future use of these findings may assist in improving livestock husbandry and welfare by understanding interactions of the environment, stress responsiveness, and peripheral circadian rhythms.

Background/Objectives: The experience of prenatal stress results in various physiological disorders due to an alteration of an offspring’s methylome and transcriptome. The objective of this study was to determine whether PNS affects DNA methylation (DNAm) and gene expression in the stress axis tissues of mature Brahman cows. Methods: Samples were collected from the paraventricular nucleus (PVN), anterior pituitary (PIT), and adrenal cortex (AC) of 5-year-old Brahman cows that were prenatally exposed to either transportation stress (PNS, n = 6) or were not transported (Control, n = 8). The isolated DNA and RNA samples were, respectively, used for methylation and RNA-Seq analyses. A gene ontology and KEGG pathway enrichment analysis of each data set within each sample tissue was conducted with the DAVID Functional Annotation Tool. Results: The DNAm analysis revealed 3, 64, and 99 hypomethylated and 2, 93, and 90 hypermethylated CpG sites (FDR < 0.15) within the PVN, PIT, and AC, respectively. The RNA-Seq analysis revealed 6, 25, and 5 differentially expressed genes (FDR < 0.15) in the PVN, PIT, and AC, respectively, that were up-regulated in the PNS group relative to the Control group, as well as 24 genes in the PIT that were down-regulated. Based on the enrichment analysis, several developmental and cellular processes, such as maintenance of the actin cytoskeleton, cell motility, signal transduction, neurodevelopment, and synaptic function, were potentially modulated. Conclusions: The methylome and transcriptome were altered in the stress axis tissues of mature cows that had been exposed to prenatal transportation stress. These findings are relevant to understanding how prenatal experiences may affect postnatal neurological functions.

Reliable pore detection in in situ monitoring is essential for quality control in additive manufacturing, particularly in safety-critical applications. However, existing automated approaches often struggle with low-quality images, computational inefficiency, and the lack of reliable uncertainty estimates to identify the pores accurately. To address these limitations, this paper proposes U-SAMNet, an Uncertainty-Aware Self-Attention Multi-Task Network. The model jointly performs pore segmentation, image-level classification, and denoising on in situ monitoring images, while deriving epistemic uncertainty via Monte Carlo dropout variance to dynamically suppress unreliable attention features. This study uses electron-optical (ELO) images from the E-PBF process. A novel Uncertainty Guidance Attention (UGA) block is introduced. It suppresses channel attention weights using inverted uncertainty estimates. Unlike prior methods that modulate classification weights, U-SAMNet operates on pixel-wise feature maps. The model has only 1.69 M parameters. A single forward pass takes 17.46 ms per image, while uncertainty estimation is performed through multiple Monte Carlo dropout passes. The model was evaluated on real E-PBF images and achieved 99.42% pixel accuracy, 85.31% F1-score, and 74.38% IoU on a held-out test set of 43 real images. It also generalizes to other industrial defect detection benchmarks, reaching 85.09% F1-score on DAGM 2007 and 82.32% on DeepCrack. GAN-synthesized training data improves the F1-score by 21.34 percentage points over rotation augmentation alone. Ablation studies confirm that each component contributes meaningfully to the final performance.

Background/Objectives: Alteration in gene expression caused by stress may serve as a potential mechanism behind a range of differences previously observed in progeny exposed to prenatal stress. The objective of this study was to examine the impact of prenatal transportation stress on differential exon usage in expressed genes of stress-axis tissues of control and prenatally stressed Brahman cattle at five years of age. Methods: Pregnant Brahman cows were transported for 2 h sessions at 20-day intervals from the 60th to the 140th day of gestation, while pregnant herdmates served as controls. Blood samples were collected from six prenatally stressed (PNS) and eight control (control) females obtained when they were 5 years of age. Tissue samples were harvested from the adrenal medulla, adrenal cortex, anterior pituitary and hypothalamic paraventricular nucleus of the PNS and control cows at 5 years of age. Differential exon usage was analyzed by the DEXSeq tool to identify genes that were not previously identified by RNA sequencing analyses. Results: Differential exon usage (FDR ≤ 0.05) was detected in three exons (two genes) in the adrenal medulla, six exons (five genes) in the adrenal cortex, 13 exons (12 genes) in the anterior pituitary, and 37 exons (33 genes) in the hypothalamic paraventricular nucleus. Conclusions: The correspondence of prenatal stress to changes in exon usage across multiple tissues and genes could indicate investigative opportunities in postnatally affected physiological processes, including myelination, brain development, stress responses and metabolism.