The Hopf Rings for KO and KU

We compute the mod two homology Hopf rings of the spectra KO and KU. The spaces in these spectra are the infinite classical groups and their coset spaces, and their homology was first calculated in the Cartan seminars, but the Hopf ring structure was first determined in the second author's unpublished PhD thesis. The presentation given here serves as an introduction to the first author's much more intricate work on the connective spectrum bo. The Hopf ring viewpoint turns out to be very convenient for understanding the homological effect of various maps between classical groups and fibrations of their connective covers.Comment: 20 pages; to appear in JPA

Genetic diversity of midwestern oat germplasm

Nine oat cultivars and experimental lines from four germplasm sources were crossed in a diallel mating design without reciprocals. F(,1) heterosis for grain yield was evaluated in two experiments, and 48 F(,2)-derived lines from each of the 36 matings were evaluated for bundle weight, grain yield, straw yield, harvest index, height, and heading date in two experiments. Number of transgressive segregates per trait and generalized genetic variance were calculated for each mating. Four measures of genetic distance between the parents were calculated: geneological distance, Euclidean distance based upon principal components, and the distance measures proposed by Hanson and Casas and Cervantes et al. The relationships between the four distance measures and the three types of breeding behavior were examined via correlation and regression. Correlations, where significant, were low to moderate. Regressions, where significant, were primarily linear with low R(\u272) values. The regression of heterosis on Euclidean distance in one experiment was quadratic with a high R(\u272) value. Using information from more than one distance measure improved the R(\u272) values for polynomial regression

Disease, Normality, and Current Pharmacological Moral Modification

3 page(s

Treatment-resistant depression and peripheral C-reactive protein.

BACKGROUND: C-reactive protein (CRP) is a candidate biomarker for major depressive disorder (MDD), but it is unclear how peripheral CRP levels relate to the heterogeneous clinical phenotypes of the disorder.AimTo explore CRP in MDD and its phenotypic associations. METHOD: We recruited 102 treatment-resistant patients with MDD currently experiencing depression, 48 treatment-responsive patients with MDD not currently experiencing depression, 48 patients with depression who were not receiving medication and 54 healthy volunteers. High-sensitivity CRP in peripheral venous blood, body mass index (BMI) and questionnaire assessments of depression, anxiety and childhood trauma were measured. Group differences in CRP were estimated, and partial least squares (PLS) analysis explored the relationships between CRP and specific clinical phenotypes. RESULTS: Compared with healthy volunteers, BMI-corrected CRP was significantly elevated in the treatment-resistant group (P = 0.007; Cohen's d = 0.47); but not significantly so in the treatment-responsive (d = 0.29) and untreated (d = 0.18) groups. PLS yielded an optimal two-factor solution that accounted for 34.7% of variation in clinical measures and for 36.0% of variation in CRP. Clinical phenotypes most strongly associated with CRP and heavily weighted on the first PLS component were vegetative depressive symptoms, BMI, state anxiety and feeling unloved as a child or wishing for a different childhood. CONCLUSIONS: CRP was elevated in patients with MDD, and more so in treatment-resistant patients. Other phenotypes associated with elevated CRP included childhood adversity and specific depressive and anxious symptoms. We suggest that patients with MDD stratified for proinflammatory biomarkers, like CRP, have a distinctive clinical profile that might be responsive to second-line treatment with anti-inflammatory drugs.Declaration of interestS.R.C. consults for Cambridge Cognition and Shire; and his input in this project was funded by a Wellcome Trust Clinical Fellowship (110049/Z/15/Z). E.T.B. is employed half time by the University of Cambridge and half time by GlaxoSmithKline; he holds stock in GlaxoSmithKline. In the past 3 years, P.J.C. has served on an advisory board for Lundbeck. N.A.H. consults for GlaxoSmithKline. P.d.B., D.N.C.J. and W.C.D. are employees of Janssen Research & Development, LLC., of Johnson & Johnson, and hold stock in Johnson & Johnson. The other authors report no financial disclosures or potential conflicts of interest.This work was funded by a Wellcome Trust strategy award to the Neuroimmunology of Mood Disorders and Alzheimer’s Disease (NIMA) Consortium which is also funded by Janssen, GlaxoSmithKline, Lundbeck and Pfizer. Recruitment of patients was supported by the National Institute of Health Research (NIHR) Clinical Research Network: Kent, Surrey and Sussex & Eastern. SRC consults for Cambridge Cognition and Shire; and his input in this project was funded by a Wellcome Trust Clinical Fellowship (110049/Z/15/Z). ETB is employed half-time by the University of Cambridge and half-time by GlaxoSmithKline; he holds stock in GSK. In the last three years PJC has served on an advisory board for Lundbeck. NAH consults for GSK. PdB, DJ and WCD are employees of Janssen Research & Development, LLC., of Johnson & Johnson, and hold stock in Johnson & Johnson

No evidence for differential gene expression in major depressive disorder PBMCs, but robust evidence of elevated biological ageing.

The increasingly compelling data supporting the involvement of immunobiological mechanisms in Major Depressive Disorder (MDD) might provide some explanation forthe variance in this heterogeneous condition. Peripheral blood measures of cytokines and chemokines constitute the bulk of evidence, with consistent meta-analytic data implicating raised proinflammatory cytokines such as IL6, IL1β and TNF. Among the potential mechanisms linking immunobiological changes to affective neurobiology is the accelerated biological ageing seen in MDD, particularly via the senescence associated secretory phenotype (SASP). However, the cellular source of immunobiological markers remains unclear. Pre-clinical evidence suggests a role for peripheral blood mononuclear cells (PBMC), thus here we aimed to explore the transcriptomic profile using RNA sequencing in PBMCs in a clinical sample of people with various levels of depression and treatment response comparing it with that in healthy controls (HCs). There were three groups with major depressive disorder (MDD): treatment-resistant (n = 94), treatment-responsive (n = 47) and untreated (n = 46). Healthy controls numbered 44. Using PBMCs gene expression analysis was conducted using RNAseq to a depth of 54.5 million reads. Differential gene expression analysis was performed using DESeq2. The data showed no robust signal differentiating MDD and HCs. There was, however, significant evidence of elevated biological ageing in MDD vs HC. Biological ageing was evident in these data as a transcriptional signature of 888 age-associated genes (adjusted p  0.6) that also correlated strongly with chronological age (spearman correlation coefficient of 0.72). Future work should expand clinical sample sizes and reduce clinical heterogeneity. Exploration of RNA-seq signatures in other leukocyte populations and single cell RNA sequencing may help uncover more subtle differences. However, currently the subtlety of any PBMC signature mitigates against its convincing use as a diagnostic or predictive biomarker

Peripheral Blood Cell-Stratified Subgroups of Inflamed Depression.

BACKGROUND: Depression has been associated with increased inflammatory proteins, but changes in circulating immune cells are less well defined. METHODS: We used multiparametric flow cytometry to count 14 subsets of peripheral blood cells in 206 depression cases and 77 age- and sex-matched controls (N = 283). We used univariate and multivariate analyses to investigate the immunophenotypes associated with depression and depression severity. RESULTS: Depression cases, compared with controls, had significantly increased immune cell counts, especially neutrophils, CD4+ T cells, and monocytes, and increased inflammatory proteins (C-reactive protein and interleukin-6). Within-group analysis of cases demonstrated significant associations between the severity of depressive symptoms and increased myeloid and CD4+ T-cell counts. Depression cases were partitioned into 2 subgroups by forced binary clustering of cell counts: the inflamed depression subgroup (n = 81 out of 206; 39%) had increased monocyte, CD4+, and neutrophil counts; increased C-reactive protein and interleukin-6; and more severe depression than the uninflamed majority of cases. Relaxing the presumption of a binary classification, data-driven analysis identified 4 subgroups of depression cases, 2 of which (n = 38 and n = 100; 67% collectively) were associated with increased inflammatory proteins and more severe depression but differed in terms of myeloid and lymphoid cell counts. Results were robust to potentially confounding effects of age, sex, body mass index, recent infection, and tobacco use. CONCLUSIONS: Peripheral immune cell counts were used to distinguish inflamed and uninflamed subgroups of depression and to indicate that there may be mechanistically distinct subgroups of inflamed depression.This work was supported by the Wellcome Trust [104025]. M Lynall was supported by a fellowship and grant from Addenbrooke’s Charitable Trust, Cambridge and a fellowship from the Medical Research Council (MR/S006257/1). M. R. Clatworthy is supported by the NIHR Cambridge Biomedical Research Centre (Transplant and Regenerative Medicine), NIHR Blood and Transplant Research Unit, MRC New Investigator Research Grant, MR/N024907/1; Arthritis Research UK Cure Challenge Research Grant, 21777), and an NIHR Research Professorship (RP-2017-08-ST2-002). E. T. Bullmore and C. M. Pariante are each supported by a NIHR Senior Investigator award. This work was also supported by the NIHR Cambridge Biomedical Research Centre (Mental Health) and the Cambridge NIHR BRC Cell Phenotyping Hub, as well as the NIHR BRC at the South London and Maudsley NHS Foundation Trust and King's College London, London