Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Profile of Pleural Mesothelioma versus Parietal and Visceral Pleura: The Emerging Gene Portrait of the Mesothelioma Phenotype

Background Malignant pleural mesothelioma is considered an almost incurable tumour with increasing incidence worldwide. It usually develops in the parietal pleura, from mesothelial lining or submesothelial cells, subsequently invading the visceral pleura. Chromosomal and genomic aberrations of mesothelioma are diverse and heterogenous. Genome-wide profiling of mesothelioma versus parietal and visceral normal pleural tissue could thus reveal novel genes and pathways explaining its aggressive phenotype. Methodology and Principal Findings Well-characterised tissue from five mesothelioma patients and normal parietal and visceral pleural samples from six non-cancer patients were profiled by Affymetrix oligoarray of 38 500 genes. The lists of differentially expressed genes tested for overrepresentation in KEGG PATHWAYS (Kyoto Encyclopedia of Genes and Genomes) and GO (gene ontology) terms revealed large differences of expression between visceral and parietal pleura, and both tissues differed from mesothelioma. Cell growth and intrinsic resistance in tumour versus parietal pleura was reflected in highly overexpressed cell cycle, mitosis, replication, DNA repair and anti-apoptosis genes. Several genes of the “salvage pathway” that recycle nucleobases were overexpressed, among them TYMS, encoding thymidylate synthase, the main target of the antifolate drug pemetrexed that is active in mesothelioma. Circadian rhythm genes were expressed in favour of tumour growth. The local invasive, non-metastatic phenotype of mesothelioma, could partly be due to overexpression of the known metastasis suppressors NME1 and NME2. Down-regulation of several tumour suppressor genes could contribute to mesothelioma progression. Genes involved in cell communication were down-regulated, indicating that mesothelioma may shield itself from the immune system. Similarly, in non-cancer parietal versus visceral pleura signal transduction, soluble transporter and adhesion genes were down-regulated. This could represent a genetical platform of the parietal pleura propensity to develop mesothelioma. Conclusions Genome-wide microarray approach using complex human tissue samples revealed novel expression patterns, reflecting some important features of mesothelioma biology that should be further explored.
Health related behaviour, stress and well-being during organisational change.

This study investigated whether some coping strategies are better or worse than others, by virtue of their links with health behaviours, or their stress buffering effects. It also investigated whether some ways of attributing for success and failure in health behaviour change are better or worse than others, through their effects upon feelings, expectations, and intentions. Employees of a hospital that was closing down completed questionnaires at two points in time, one year apart (baseline N= 109; of which 102 successfully followed up). Analysis was by a combination of multivariate analysis of variance, latent class analysis, exploratory and confirmatory factor analysis, and regression analysis. The evidence supported a four-dimensional view of coping (cf., Cox & Ferguson, 1991), and (less strongly) a two-type model of routine health behaviours. There was little evidence that coping strategies were linked to either routine health behaviours or to health behaviours used as ways of coping. However, the use of health damaging behaviours as ways of coping was predicted somewhat by avoidance coping. Having controlled for negative affectivity, there was little evidence that coping or resources buffered the effect of stressors on well-being, or that coping mediated between resources and well-being (cf., Cohen & Edwards, 1989). There were, however, main effects of coping on well-being (e. g., avoidance coping acted to increase mental symptoms); and main and interactive effects of stressors and resources on coping (e. g., stressors acted to increase avoidance coping but resources buffered this effect). The evidence supported a four-dimensional view of attributions (cf., McAuley, Duncan, & Russell, 1992), but with differences between attributions for success and failure. There was only limited support for Weiner's (1986) model applied to health behaviour change. Of particular interest were the interactive effects of attributions on affective reactions and on intention; these effects invariably involved the stability dimension.
Self-reported sickness absence as a risk marker of future disability pension. Prospective findings from the DWECS/DREAM study 1990-2004

Objectives: This prospective cohort study examines number of self-reported days of sickness absence as a risk marker for future disability pension among a representative sample of employees in Denmark 1990-2004. Material and methods: 4177 employees between 18 and 45 years were interviewed using a self-administered questionnaire in 1990 regarding sickness absence, age, gender, socioeconomic position, health behaviour, and physical and psychosocial work environment. They were followed for 168 months in a national disability pension register. Logistic regression analysis was performed in order to assess risk estimates for levels of absence and future disability pension. Results: During follow-up, a total of 140 persons (3.4%) received disability pension. Of these, 82 (58.6%) were women, 58 (41.4%) were men. There was a 2.5 fold risk of future disability pension for the part of the population reporting more than 6 days of sickness absence per annum at baseline, when taking into account gender, age, socioeconomic position, health behaviour, physical and psychosocial work environment. Conclusion: The findings suggest that information on self-reported days of sickness absence can be used to effectively identify “at risk” groups for disability pension.
Cross-lingual deep neural network based submodular unbiased data selection for low-resource keyword search

In this paper, we propose a cross-lingual deep neural network (DNN) based submodular unbiased data selection approach for low-resource keyword search (KWS). A small amount (e.g. one hour) of transcribed data is used to conduct cross-lingual transfer. The frame-level senone sequence activated by the cross-lingual DNN is used to represent each untranscribed speech utterance. The proposed submodular function considers utterance length normalization and the feature distribution matched to a development set. Experiments are conducted by selecting 9 hours of Tamil speech for the 2014 NIST Open Keyword Search Evaluation (OpenKWS14). The proposed data selection approach provides 35.8% relative actual term weighted value (ATWV) improvement over random selection on the OpenKWS14 Evalpartl data set. Further analysis of the experimental results shows that both utterance length normalization and the feature distribution estimated from a development set deployed in the submodular function can suppress the preference to select long utterances. The selected utterances can cover a more diverse range of tri-phones, words, and acoustic variations from a wider set of utterances. Moreover, the wider coverage of words also benefits the acquired linguistic knowledge, which also contributes to improving KWS performance.
A Dynamic Weighted Ensemble to Cope with Concept Drifting Classification

In the real world concepts are not stable and change with time and a lot of other hidden factors. Stream classifiers should be sensitive to the drifting of concept in an automatic way. In this paper, we proposed a new weighted majority strategy for the ensemble classifier. We periodically created and evaluated component classifiers that constitute the ensemble then we used the weighted ensemble to make global prediction. We empirically evaluated two kinds of concept drifting: the SEA concept drifting and the moving hyper-plane problem. Experiment results showed that our proposed method was very effective to deal with concept drifting.
Protein abundances can distinguish between naturally-occurring and laboratory strains of Yersinia pestis, the causative agent of plague

The rapid pace of bacterial evolution enables organisms to adapt to the laboratory environment with repeated passage and thus diverge from naturally-occurring environmental (“wild”) strains. Distinguishing wild and laboratory strains is clearly important for biodefense and bioforensics; however, DNA sequence data alone has thus far not provided a clear signature, perhaps due to lack of understanding of how diverse genome changes lead to convergent phenotypes, difficulty in detecting certain types of mutations, or perhaps because some adaptive modifications are epigenetic. Monitoring protein abundance, a molecular measure of phenotype, can overcome some of these difficulties. We have assembled a collection of Yersinia pestis proteomics datasets from our own published and unpublished work, and from a proteomics data archive, and demonstrated that protein abundance data can clearly distinguish laboratory-adapted from wild. We developed a lasso logistic regression classifier that uses binary (presence/absence) or quantitative protein abundance measures to predict whether a sample is laboratory-adapted or wild that proved to be ~98% accurate, as judged by replicated 10-fold cross-validation. Protein features selected by the classifier accord well with our previous study of laboratory adaptation in Y. pestis. The input data was derived from a variety of unrelated experiments and contained significant confounding variables. We show that the classifier is robust with respect to these variables. The methodology is able to discover signatures for laboratory facility and culture medium that are largely independent of the signature of laboratory adaptation. Going beyond our previous laboratory evolution study, this work suggests that proteomic differences between laboratory-adapted and wild Y. pestis are general, potentially pointing to a process that could apply to other species as well. Additionally, we show that proteomics datasets (even archived data collected for different purposes) contain the information necessary to distinguish wild and laboratory samples. This work has clear applications in biomarker detection as well as biodefense.
Neurons on the Move: Migration and Lamination of Cortical Interneurons

The modulation of cortical activity by GABAergic interneurons is required for normal brain function and is achieved through the immense level of heterogeneity within this neuronal population. Cortical interneurons share a common origin in the ventral telencephalon, yet during the maturation process diverse subtypes are generated that form the characteristic laminar arrangement observed in the adult brain. The long distance tangential and short-range radial migration into the cortical plate is regulated by a combination of intrinsic and extrinsic signalling mechanisms, and a great deal of progress has been made to understand these developmental events. In this review, we will summarize current findings regarding the molecular control of subtype specification and provide a detailed account of the migratory cues influencing interneuron migration and lamination. Furthermore, a dysfunctional GABAergic system is associated with a number of neurological and psychiatric conditions, and some of these may have a developmental aetiology with alterations in interneuron generation and migration. We will discuss the notion of additional sources of interneuron progenitors found in human and non-human primates and illustrate how the disruption of early developmental events can instigate a loss in GABAergic function.
Identification and Characterization of a Novel Intracellular Alkaline α-Amylase from the Hyperthermophilic Bacterium Thermotoga maritima MSB8

ABSTRACT The gene for a novel α-amylase, designated AmyC, from the hyperthermophilic bacterium Thermotoga maritima was cloned and heterologously overexpressed in Escherichia coli. The putative intracellular enzyme had no amino acid sequence similarity to glycoside hydrolase family (GHF) 13 α-amylases, yet the range of substrate hydrolysis and the product profile clearly define the protein as an α-amylase. Based on sequence similarity AmyC belongs to a subgroup within GHF 57. On the basis of amino acid sequence similarity, Glu185 and Asp349 could be identified as the catalytic residues of AmyC. Using a 60-min assay, the maximum hydrolytic activity of the purified enzyme, which was dithiothreitol dependent, was found to be at 90°C. AmyC displayed a remarkably high pH optimum of pH 8.5 and an unusual sensitivity towards both ATP and EDTA.
Tuning for shape dimensions in macaque inferior temporal cortex

It is widely assumed that distributed bell‐shaped tuning (e.g. Radial Basis functions) characterizes the shape selectivity of macaque inferior temporal (IT) neurons, analogous to the orientation or spatial frequency tuning found in early visual cortex. Demonstrating such tuning properties requires testing the responses of neurons for different values along dimensions of shape. We recorded the responses of single macaque IT neurons to variations of a rectangle and a triangle along simple shape dimensions, such as taper and axis curvature. The neurons showed systematic response modulation along these dimensions, with the greatest response, on average, to the highest values on the dimensions, e.g. to the most curved shapes. Within the range of values tested, the response functions were monotonic rather than bell‐shaped. Multi‐dimensional scaling of the neural responses showed that these simple shape dimensions were coded orthogonally by IT neurons: the degree and direction of responses modulation (i.e. the increase or decrease of responses along a dimension) was independent for the different dimensions. Furthermore, for combinations of curvature‐related and other simple shape dimensions, the joint tuning was separable, that is well predicted by the product of the tuning for each of the dimensions. The independence of dimensional tuning may provide the neural basis for the independence of psychophysical judgements of multidimensional stimuli.
Effective but Costly, Evolved Mechanisms of Defense against a Virulent Opportunistic Pathogen in Drosophila melanogaster

Drosophila harbor substantial genetic variation for antibacterial defense, and investment in immunity is thought to involve a costly trade-off with life history traits, including development, life span, and reproduction. To understand the way in which insects invest in fighting bacterial infection, we selected for survival following systemic infection with the opportunistic pathogen Pseudomonas aeruginosa in wild-caught Drosophila melanogaster over 10 generations. We then examined genome-wide changes in expression in the selected flies relative to unselected controls, both of which had been infected with the pathogen. This powerful combination of techniques allowed us to specifically identify the genetic basis of the evolved immune response. In response to selection, population-level survivorship to infection increased from 15% to 70%. The evolved capacity for defense was costly, however, as evidenced by reduced longevity and larval viability and a rapid loss of the trait once selection pressure was removed. Counter to expectation, we observed more rapid developmental rates in the selected flies. Selection-associated changes in expression of genes with dual involvement in developmental and immune pathways suggest pleiotropy as a possible mechanism for the positive correlation. We also found that both the Toll and the Imd pathways work synergistically to limit infectivity and that cellular immunity plays a more critical role in overcoming P. aeruginosa infection than previously reported. This work reveals novel pathways by which Drosophila can survive infection with a virulent pathogen that may be rare in wild populations, however, due to their cost.
Conversing Learning: Actively looking for human assistance to improve Machine Learning tasks

In Machine Learning (ML) systems we often apply techniques to learn about real world problems behavior from data. Traditionally, such data comes from instances of datasets (that represents the target problem) which we want to learn from. This approach has been broadly used in many different application domains such as recommending systems, meteorological prediction, medical diagnosis, etc. The recent years of quick development of communications technology, that made the Internet faster and available, made possible the acquisition of information to feed a growing number of Machine Learning applications and, in addition, brought light to the use of human computation and crowdsourcing approaches commonly applied to problems that are easy for human but difficult for computers. Thus, the Social Web has been the focus of many research in Artificial Intelligence (AI) and Machine Learning. In this work we want to show how we can take advantage from the Social Web to add value to Machine Learning systems which can actively and autonomously ask for web users help to improve learning performance.
Television Viewing in Child Care Programs: A National Survey

Although the amount of television that young children watch at home is well-described, to date no study has examined how much television preschool children watch in day care settings. We performed a cross-sectional analysis using the Profile of Child Care Settings Study, examining predictors of television viewing in center (n = 2089) and home-based (n = 583) child care programs. On average, preschool-aged children were reported to watch more than four times as much television while at home-based programs than at center-based programs (1.39 hours per day vs 0.36 hours per day); with significant differences between groups in the type of television content viewed, and in the proportions of programs in which no television viewing occurred at all. The proportion of programs where preschool-aged children watched no television during the child care day was 65% in center-based programs and 11% in home-based programs. The hours a program was open each day was associated with increased television viewing in both settings; provision of after-school care to older children and being in a county with high family poverty rates were only significant factors in center-based programs. Factors associated with decreased television viewing included post-secondary education of staff members, as well as the average staff volume of the program. Preschool children in day care settings watch a considerable amount of television in addition to what is viewed at home. These results further highlight the urgent need to better understand the effects of viewing on young children.
Alternative Activation of STAT1 and STAT3 in Response to Interferon-γ*

Interferon-γ (IFNγ) is a pluripotent cytokine whose major biological effects are mediated through a pathway in which STAT1 is the predominant and essential transcription factor. STAT3 can also be activated weakly by IFNγ, but the mechanism of activation and function of STAT3 as a part of the interferon response are not known. Here we show that STAT3 activation is much stronger and more prolonged in STAT1-null mouse embryo fibroblasts than in wild-type cells. In response to IFNγ, SRC-family kinases are required to activate STAT3 (but not STAT1) through tyrosine phosphorylation, whereas the receptor-bound kinases JAK1 and JAK2 are required to activate both STATs. Tyrosine 419 of the IFNγ receptor subunit 1 (IFNGR1) is required to activate both STATs, suggesting that STAT1 and STAT3 compete with each other for the same receptor phosphotyrosine motif. Activated STAT3 can replace STAT1 in STAT1-null cells to drive the transcription of certain genes, for example, socs-3 and c/ebpδ, which have γ-activated sequence motifs in their promoters. Work from Ian Kerr's laboratory reveals that the gp130-linked interleukin-6 receptor, which usually activates STAT3 predominantly, activates STAT1 efficiently when STAT3 is absent (Costa-Pereira, A. P., Tininini, S., Strobl, B., Alonzi, T., Schlaak, J. F., Is'harc, H., Gesualdo, I., Newman, S. J., Kerr, I. M., and Poli, V. (2002) Proc. Natl. Acad. Sci. U. S. A. 99, 8043–8047). Because STAT1 and STAT3 have opposing biological effects (STAT3 is an oncogene, and STAT1 is a tumor suppressor), the reciprocal activation of these two transcription factors in response to IFNγ or interleukin-6 suggests that their relative abundance, which may vary substantially in different normal cell types, under different conditions or in tumors is likely to have a major impact on how cells behave in response to different cytokines.
Culture-Independent Characterization of Bacteria and Fungi in a Poultry Bioaerosol Using Pyrosequencing: A New Approach

Work in animal production facilities often results in exposure to organic dusts. Previous studies have documented decreases in pulmonary function and lung inflammation among workers exposed to organic dust in the poultry industry. Bacteria and fungi have been reported as components of the organic dust produced in poultry facilities. To date, little is known about the diversity and concentration of bacteria and fungi inside poultry buildings. All previous investigations have utilized culture-based methods for analysis that identify only biota cultured on selected media. The bacterial tag-encoded flexible (FLX) amplicon pyrosequencing (bTEFAP) and fungal tag-encoded flexible (FLX) amplicon pyrosequencing (fTEFAP) are modern and comprehensive approaches for determining biodiversity of microorganisms and have not previously been used to provide characterization of exposure to microorganisms in an occupational environment. This article illustrates the potential application of this novel technique in occupational exposure assessment as well as other settings. An 8-hr area sample was collected using an Institute of Medicine inhalable sampler attached to a mannequin in a poultry confinement building. The sample was analyzed using bTEFAP and fTEFAP. Of the bacteria and fungi detected, 116 and 39 genera were identified, respectively. Among bacteria, Staphylococcus cohnii was present in the highest proportion (23%). The total inhalable bacteria concentration was estimated to be 7503 cells/m 3 . Among the fungi identified, Sagenomella sclerotialis was present in the highest proportion (37%). Aspergillus ochraceus and Penicillium janthinellum were also present in high proportions. The total inhalable fungi concentration was estimated to be 1810 cells/m 3 . These estimates are lower than what has been reported by others using standard epifluorescence microscope methods. However, no study has used non-culture-based techniques, such as bTEFAP and fTEFAP, to evaluate bacteria and fungi in the inhalable fraction of a bioaerosol in a broiler production environment. Furthermore, the impact of this bTEFAP and fTEFAP technology has yet to be realized by the scientific community dedicated to evaluating occupational and environmental bioaerosol exposure.
Race, Class, And Gender In Boys' Education: Repositioning Intersectionality Theory

Boys’ identities are distinctly gendered, racialized, and classed across disparate social and cultural contexts. Related intersectional identity processes are associated with boys’ academic success. While intersectionality has been utilized throughout boys’ education scholarship, a limited, “light touch” approach is often enacted. A critical logic of interpretation, intersectionality theory accounts for race, class, and gender within equity-based empirical studies. The authors contend insufficient engagement with intersectionality may lead educational research on boys’ social and learner identities to become static. Examining boys’ identities through intersectional approaches reveals more complex insights particularly as related to their school engagement. Critical of recent “boy crisis” literature, this article strives to compel theorists of boys’ education to more fully leverage the history, constructs, and epistemologies of intersectionality.