Altered expression of glutamate signaling, growth factor, and glia genes in the locus coeruleus of patients with major depression.

Several studies have proposed that brain glutamate signaling abnormalities and glial pathology have a role in the etiology of major depressive disorder (MDD). These conclusions were primarily drawn from post-mortem studies in which forebrain brain regions were examined. The locus coeruleus (LC) is the primary source of extensive noradrenergic innervation of the forebrain and as such exerts a powerful regulatory role over cognitive and affective functions, which are dysregulated in MDD. Furthermore, altered noradrenergic neurotransmission is associated with depressive symptoms and is thought to have a role in the pathophysiology of MDD. In the present study we used laser-capture microdissection (LCM) to selectively harvest LC tissue from post-mortem brains of MDD patients, patients with bipolar disorder (BPD) and from psychiatrically normal subjects. Using microarray technology we examined global patterns of gene expression. Differential mRNA expression of select candidate genes was then interrogated using quantitative real-time PCR (qPCR) and in situ hybridization (ISH). Our findings reveal multiple signaling pathway alterations in the LC of MDD but not BPD subjects. These include glutamate signaling genes, SLC1A2, SLC1A3 and GLUL, growth factor genes FGFR3 and TrkB, and several genes exclusively expressed in astroglia. Our data extend previous findings of altered glutamate, astroglial and growth factor functions in MDD for the first time to the brainstem. These findings indicate that such alterations: (1) are unique to MDD and distinguishable from BPD, and (2) affect multiple brain regions, suggesting a whole-brain dysregulation of such functions

Heuristics in permutation GOMEA for solving the permutation flowshop scheduling problem

The recently introduced permutation Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) has shown to be an effective Model Based Evolutionary Algorithm (MBEA) for permutation problems. So far, permutation GOMEA has only been used in the context of Black-Box Optimization (BBO). This paper first shows that permutation GOMEA can be improved by incorporating a constructive heuristic to seed the initial population. Secondly, the paper shows that hybridizing with job swapping neighborhood search does not lead to consistent improvement. The seeded permutation GOMEA is compared to a state-of-the-art algorithm (VNS4) for solving the Permutation Flowshop Scheduling Problem (PFSP). Both unstructured and structured instances are used in the benchmarks. The results show that permutation GOMEA often outperforms the VNS4 algorithm for the PFSP with the total flowtime criterion

Gene expression profiling of mammary gland development reveals putative roles for death receptors and immune mediators in post-lactational regression

INTRODUCTION: In order to gain a better understanding of the molecular processes that underlie apoptosis and tissue regression in mammary gland, we undertook a large-scale analysis of transcriptional changes during the mouse mammary pregnancy cycle, with emphasis on the transition from lactation to involution. METHOD: Affymetrix microarrays, representing 8618 genes, were used to compare mammary tissue from 12 time points (one virgin, three gestation, three lactation and five involution stages). Six animals were used for each time point. Common patterns of gene expression across all time points were identified and related to biological function. RESULTS: The majority of significantly induced genes in involution were also differentially regulated at earlier stages in the pregnancy cycle. This included a marked increase in inflammatory mediators during involution and at parturition, which correlated with leukaemia inhibitory factor–Stat3 (signal transducer and activator of signalling-3) signalling. Before involution, expected increases in cell proliferation, biosynthesis and metabolism-related genes were observed. During involution, the first 24 hours after weaning was characterized by a transient increase in expression of components of the death receptor pathways of apoptosis, inflammatory cytokines and acute phase response genes. After 24 hours, regulators of intrinsic apoptosis were induced in conjunction with markers of phagocyte activity, matrix proteases, suppressors of neutrophils and soluble components of specific and innate immunity. CONCLUSION: We provide a resource of mouse mammary gene expression data for download or online analysis. Here we highlight the sequential induction of distinct apoptosis pathways in involution and the stimulation of immunomodulatory signals, which probably suppress the potentially damaging effects of a cellular inflammatory response while maintaining an appropriate antimicrobial and phagocytic environment

Largest lyapunov exponents of ankle, knee and hip flexion during gait

Chaos is the deterministic yet non-periodic behaviour of a system [1]: every chaotic cycle is physically determined by an unbroken chain of observations, but which gives results that appear unpredictable [2]. Chaos theory has been applied to gait variability previously (e.g. [3], [4]) and may be useful in providing an insight into the biomechanical effect of musculoskeletal pathology [3]. Current technology facilitates extensive data collection, ideal for gait variability studies, and we wished to utilise this capability to simultaneously investigate variability in ankle, knee and hip flexion over a 20 minute period

lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers

We assume data sampled from a mixture of d-dimensional linear subspaces with spherically symmetric distributions within each subspace and an additional outlier component with spherically symmetric distribution within the ambient space (for simplicity we may assume that all distributions are uniform on their corresponding unit spheres). We also assume mixture weights for the different components. We say that one of the underlying subspaces of the model is most significant if its mixture weight is higher than the sum of the mixture weights of all other subspaces. We study the recovery of the most significant subspace by minimizing the lp-averaged distances of data points from d-dimensional subspaces, where p>0. Unlike other lp minimization problems, this minimization is non-convex for all p>0 and thus requires different methods for its analysis. We show that if 0<p<=1, then for any fraction of outliers the most significant subspace can be recovered by lp minimization with overwhelming probability (which depends on the generating distribution and its parameters). We show that when adding small noise around the underlying subspaces the most significant subspace can be nearly recovered by lp minimization for any 0<p<=1 with an error proportional to the noise level. On the other hand, if p>1 and there is more than one underlying subspace, then with overwhelming probability the most significant subspace cannot be recovered or nearly recovered. This last result does not require spherically symmetric outliers.Comment: This is a revised version of the part of 1002.1994 that deals with single subspace recovery. V3: Improved estimates (in particular for Lemma 3.1 and for estimates relying on it), asymptotic dependence of probabilities and constants on D and d and further clarifications; for simplicity it assumes uniform distributions on spheres. V4: minor revision for the published versio

How diverse is your team? Investigating gender and nationality diversity in GitHub teams

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Background Building an effective team of developers is a complex task faced by both software companies and open source communities. The problem of forming a “dream” team involves many variables, including consideration of human factors and it is not a dilemma solvable in a mathematical way. Empirical studies might provide interesting insights to explain which factors need to be taken into account in building a team of developers and which levers act to optimise productivity among developers. Aim In this paper, we present the results of an empirical study aimed at investigating the link between team diversity (i.e., gender, nationality) and productivity (issue fixing time). Method We consider issues solved from the GHTorrent dataset inferring gender and nationality of each team’s members. We also evaluate the politeness of all comments involved in issue resolution. Results Results show that higher gender diversity is linked with a lower team average issue fixing time (higher productivity), that nationality diversity is linked with lower team politeness and that gender diversity is linked with higher sentiment.Peer reviewedFinal Published versio

The factor structure of the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen distinct populations

There is considerable evidence that self-criticism plays a major role in the vulnerability to and recovery from psychopathology. Methods to measure this process, and its change over time, are therefore important for research in psychopathology and well-being. This study examined the factor structure of a widely used measure, the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen nonclinical samples (N = 7510) from twelve different countries: Australia (N = 319), Canada (N = 383), Switzerland (N = 230), Israel (N = 476), Italy (N = 389), Japan (N = 264), the Netherlands (N = 360), Portugal (N = 764), Slovakia (N = 1326), Taiwan (N = 417), the United Kingdom 1 (N = 1570), the United Kingdom 2 (N = 883), and USA (N = 331). This study used more advanced analyses than prior reports: a bifactor item-response theory model, a two-tier item-response theory model, and a non-parametric item-response theory (Mokken) scale analysis. Although the original three-factor solution for the FSCRS (distinguishing between Inadequate-Self, Hated-Self, and Reassured-Self) had an acceptable fit, two-tier models, with two general factors (Self-criticism and Self-reassurance) demonstrated the best fit across all samples. This study provides preliminary evidence suggesting that this two-factor structure can be used in a range of nonclinical contexts across countries and cultures. Inadequate-Self and Hated-Self might not by distinct factors in nonclinical samples. Future work may benefit from distinguishing between self-correction versus shame-based self-criticism.Peer reviewe

Gene Expression Changes in the Prefrontal Cortex, Anterior Cingulate Cortex and Nucleus Accumbens of Mood Disorders Subjects That Committed Suicide

Suicidal behaviors are frequent in mood disorders patients but only a subset of them ever complete suicide. Understanding predisposing factors for suicidal behaviors in high risk populations is of major importance for the prevention and treatment of suicidal behaviors. The objective of this project was to investigate gene expression changes associated with suicide in brains of mood disorder patients by microarrays (Affymetrix HG-U133 Plus2.0) in the dorsolateral prefrontal cortex (DLPFC: 6 Non-suicides, 15 suicides), the anterior cingulate cortex (ACC: 6NS, 9S) and the nucleus accumbens (NAcc: 8NS, 13S). ANCOVA was used to control for age, gender, pH and RNA degradation, with P≤0.01 and fold change±1.25 as criteria for significance. Pathway analysis revealed serotonergic signaling alterations in the DLPFC and glucocorticoid signaling alterations in the ACC and NAcc. The gene with the lowest p-value in the DLPFC was the 5-HT2A gene, previously associated both with suicide and mood disorders. In the ACC 6 metallothionein genes were down-regulated in suicide (MT1E, MT1F, MT1G, MT1H, MT1X, MT2A) and three were down-regulated in the NAcc (MT1F, MT1G, MT1H). Differential expression of selected genes was confirmed by qPCR, we confirmed the 5-HT2A alterations and the global down-regulation of members of the metallothionein subfamilies MT 1 and 2 in suicide completers. MTs 1 and 2 are neuro-protective following stress and glucocorticoid stimulations, suggesting that in suicide victims neuroprotective response to stress and cortisol may be diminished. Our results thus suggest that suicide-specific expression changes in mood disorders involve both glucocorticoids regulated metallothioneins and serotonergic signaling in different regions of the brain

“For most of us Africans, we don’t just speak”: a qualitative investigation into collaborative heterogeneous PBL group learning

Collaborative approaches such as Problem Based Learning (PBL) may provide the opportunity to bring together diverse students but their efficacy in practice and the complications that arise due to the mixed ethnicity needs further investigation. This study explores the key advantages and problems of heterogeneous PBL groups from the students’ and teachers’ opinions. Focus groups were conducted with a stratified sample of second year medical students and their PBL teachers. We found that students working in heterogeneous groupings interact with students with whom they don’t normally interact with, learn a lot more from each other because of their differences in language and academic preparedness and become better prepared for their future professions in multicultural societies. On the other hand we found students segregating in the tutorials along racial lines and that status factors disempowered students and subsequently their productivity. Among the challenges was also that academic and language diversity hindered student learning. In light of these the recommendations were that teachers need special diversity training to deal with heterogeneous groups and the tensions that arise. Attention should be given to create ‘the right mix’ for group learning in diverse student populations. The findings demonstrate that collaborative heterogeneous learning has two sides that need to be balanced. On the positive end we have the ‘ideology’ behind mixing diverse students and on the negative the ‘practice’ behind mixing students. More research is needed to explore these variations and their efficacy in more detail