Evaluation of L-selectin expression and assessment of protein tyrosine phosphorylation in bovine polymorphonuclear neutrophil leukocytes around parturition.

Impaired polymorphonuclear neutrophil leukocyte (PMN) function around parturition has been associated with increased clinical mastitis in dairy cows. Rolling and attachment of PMN to the endothelium is the first step in the recruitment process and is accomplished by interaction between L-selectin on PMN and its ligand on endothelial cells. Furthermore, tyrosine phosphorylation is involved in the initiation of many PMN functions. The objective of this work was to determine changes in expression of L-selectin and tyrosine phosphorylation in the perinatal period. Eight clinically healthy Holstein cows were used as PMN donors at d-21, -14, -7,0 (calving), +1, +2, +7, +14, +28. Evaluation of L-selectin expression was carried out on activated and resting PMN. Anti-bovine L-selectin monoclonal antibody (MAB) and flow cytometric analysis were used to measure the percentage of PMN fluorescing and receptor expression (log mean fluorescent channel, LMFC). Activated and resting PMN showed similar trends in % PMN fluorescence and LMFC. The percentage of PMN fluorescing tended to decrease at parturition, followed by a significant increase at d +14 and +28 (P <0.02). For LMFC a decrease was observed on d +1 followed by an increase through d +28 (P < 0.01). Protein tyrosine phosphorylation of lysates prepared from PMN isolated throughout the study was detected by electrophoresis and western blotting using anti-phosphotyrosine MAB. Several protein bands were tyrosine phosphorylated. Two of these bands (42-44 kDa and 90 kDa) varied in intensity over time. The intensity of the 42-44 kDa band gradually increased from d -7, peaked at d +7 (P < 0.03), and steadily decreased to d +28 (P < 0.02). Antibody to activated mitogen protein kinase reacted with the 42-44 kDa band. Reduced PMN function during the periparturient period could be related to reduced L-selectin adhesion molecules on the cell surface, and to modulation in the phosphorylation of functionally important molecules

Gene expression and survival analysis of breast cancer sub types defined by immunohistochemistry

Introduction: Breast cancer in the clinical setting may be divided into four subtypes (luminal A, luminal B, HER2 and basal) by immunohistochemical (IHC) analysis. This project aims to 1) compare subtype classification by IHC vs. the PAM50 gene classifier, 2) investigate the gene expression profiles of the IHC subtypes and 3) investigate the prognostic implications of the IHC subtypes. Method: The concordance between the IHC and PAM50 classifiers was assessed in a group of 405 breast cancers used in a previous study by Breffer et al. [1]. For RNA-seq analysis, data for a group of 105 cancers subtyped by IHC were obtained from The Cancer Genome Atlas Program (TCGA), National Cancer Institute (NCI) [2]. The data were analysed with limma and edgeR to obtain the gene expression profiles for the IHC subtypes. An exploratory unsupervised hierarchical cluster analysis was performed to help understand the usefulness of these gene sets in providing information on IHC cancer subtypes. Lastly, breast cancer specific overall survival among the IHC subtypes was assessed in a cohort of 292 cancers from the Garvan Insititute. Results: The concordance between subtyping by PAM50 and IHC among the 405 tumours was 59%. For cancers classified as HER2 by IHC (HER2 IHC cancers), 94% (16 out of 17) were also classified as HER2 by PAM50. For basal IHC cancers the concordance with PAM50 was 86% (54 out of 63). For luminal A and luminal B IHC cancers, the concordance with PAM50 was 59% (148 out of 251) and 28% (21 out of 74) respectively. Linear modeling of RNA-seq data showed basal IHC cancers were enriched for genes associated with tumour hypoxia, activation of the beta-catenin pathway, progression through the cell cycle and stem cell proliferation. Whereas as luminal A cancers showed down-regulation of genes associated with progression through the cell cycle and cell migration. An exploratory unsupervised hierarchical cluster analysis by the PAM50 gene set supported the usefulness of these genes in understanding the differences between the subtypes. Survival analysis using the Cox regression model showed, compared to luminal A IHC cancers, basal (HR = 4.08, 95% CI: 2.02 – 5.77), and HER2 (HR = 4.08, 95% CI: 2.14 – 7.78) cancers were associated with shorter breast cancer specific overall survival (p = 0.018). A tendency for poorer survival was seen for luminal B IHC cancers (HR = 2.04, 95% CI: 0.98 – 4.25) was observed. Conclusion: Breast cancer IHC subtypes have distinctive gene expression profiles that relate to their biological behaviour. Subtyping by IHC yields important prognostic information that may aid the clinical management of breast cancers

Cell-specific and region-specific transcriptomics in the multiple sclerosis model: Focus on astrocytes.

Changes in gene expression that occur across the central nervous system (CNS) during neurological diseases do not address the heterogeneity of cell types from one CNS region to another and are complicated by alterations in cellular composition during disease. Multiple sclerosis (MS) is multifocal by definition. Here, a cell-specific and region-specific transcriptomics approach was used to determine gene expression changes in astrocytes in the most widely used MS model, experimental autoimmune encephalomyelitis (EAE). Astrocyte-specific RNAs from various neuroanatomic regions were attained using RiboTag technology. Sequencing and bioinformatics analyses showed that EAE-induced gene expression changes differed between neuroanatomic regions when comparing astrocytes from spinal cord, cerebellum, cerebral cortex, and hippocampus. The top gene pathways that were changed in astrocytes from spinal cord during chronic EAE involved decreases in expression of cholesterol synthesis genes while immune pathway gene expression in astrocytes was increased. Optic nerve from EAE and optic chiasm from MS also showed decreased cholesterol synthesis gene expression. The potential role of cholesterol synthesized by astrocytes during EAE and MS is discussed. Together, this provides proof-of-concept that a cell-specific and region-specific gene expression approach can provide potential treatment targets in distinct neuroanatomic regions during multifocal neurological diseases

Machine-Learning Non-Conservative Dynamics for New-Physics Detection

Energy conservation is a basic physics principle, the breakdown of which often implies new physics. This paper presents a method for data-driven "new physics" discovery. Specifically, given a trajectory governed by unknown forces, our Neural New-Physics Detector (NNPhD) aims to detect new physics by decomposing the force field into conservative and non-conservative components, which are represented by a Lagrangian Neural Network (LNN) and a universal approximator network (UAN), respectively, trained to minimize the force recovery error plus a constant $\lambda$ times the magnitude of the predicted non-conservative force. We show that a phase transition occurs at $\lambda$=1, universally for arbitrary forces. We demonstrate that NNPhD successfully discovers new physics in toy numerical experiments, rediscovering friction (1493) from a damped double pendulum, Neptune from Uranus' orbit (1846) and gravitational waves (2017) from an inspiraling orbit. We also show how NNPhD coupled with an integrator outperforms previous methods for predicting the future of a damped double pendulum.Comment: 17 pages, 7 figs, 2 tables; typo correctio