Miracle-dz/UniFAR-FTUs huggingface dataset:
Gram-Positive Bacteria Are Potent Inducers of Monocytic Interleukin-12 (IL-12) while Gram-Negative Bacteria Preferentially Stimulate IL-10 Production

ABSTRACT Interleukin-10 (IL-10) and IL-12 are two cytokines secreted by monocytes/macrophages in response to bacterial products which have largely opposite effects on the immune system. IL-12 activates cytotoxicity and gamma interferon (IFN-γ) secretion by T cells and NK cells, whereas IL-10 inhibits these functions. In the present study, the capacities of gram-positive and gram-negative bacteria to induce IL-10 and IL-12 were compared. Monocytes from blood donors were stimulated with UV-killed bacteria from each of seven gram-positive and seven gram-negative bacterial species representing both aerobic and anaerobic commensals and pathogens. Gram-positive bacteria induced much more IL-12 than did gram-negative bacteria (median, 3,500 versus 120 pg/ml at an optimal dose of 25 bacteria/cell; P < 0.001), whereas gram-negative bacteria preferentially stimulated secretion of IL-10 (650 versus 200 pg/ml; P < 0.001). Gram-positive species also induced stronger major histocompatibility complex class II-restricted IFN-γ production in unfractionated blood mononuclear cells than did gram-negative species (12,000 versus 3,600 pg/ml; P < 0.001). The poor IL-12-inducing capacity of gram-negative bacteria was not remediated by addition of blocking anti-IL-10 antibodies to the cultures. No isolated bacterial component could be identified that mimicked the potent induction of IL-12 by whole gram-positive bacteria, whereas purified LPS induced IL-10. The results suggest that gram-positive bacteria induce a cytokine pattern that promotes Th1 effector functions.
Random homogenization for a fluid flow through a membrane

Effective boundary conditions for the flow of a viscous fluid across randomly leaky permeable membranes are studied. Threshold leak conditions of subgradient type, introduced by Fujita [Res. Inst. Math. Sci. Kokyuroku 888 (1994), 199–216, J. Comp. Appl. Math. 149(1) (2002), 56–79], are considered on the randomly distributed solid part of the membrane. The effective conditions are of subgradient type with an effective yield limit, in the case of a densely distributed solid part, or of Navier slip type, in the critical case; in the dilute case the tangential slip cancels, whereas the normal velocity and stress are continuous. We thus extend our results [Complex Variables and Elliptic Equations 57(2–4) (2012), 437–453], from the periodic permeable membrane, to a randomly permeable membrane model.
Gender Recognition Using Complexity-Aware Local Features

We propose a gender classifier using two types of local features, the gradient features which have strong discrimination capability on local patterns, and the Gabor wavelets which reflect the multi-scale directional information. The Real Ad a Boost algorithm with complexity penalty term is applied to choose meaningful regions from human face for feature extraction, while balancing the discriminative capability and the computation cost at the same time. Linear SVM is further utilized to train a gender classifier based on the selected features for accuracy evaluation. Experimental results show that the proposed approach outperforms the methods using single feature. It also achieves comparable accuracy with the state-of-the-art algorithms on both controlled datasets and real-world datasets.
Histopathology in the Diagnosis and Classification of Acute Myeloid Leukemia, Myelodysplastic Syndromes, and Myelodysplastic/Myeloproliferative Diseases

In spite of the impressive advances in the area of molecular pathology, bone marrow morphology remains the diagnosis cornerstone to identify the various subtypes of myeloid neoplasms. Morphological examination of the bone marrow requires both bone marrow aspirate and bone marrow trephine biopsy. Immunohistochemistry of bone marrow biopsy with markers reactive in paraffin-embedded tissues represents a powerful diagnostic tool; its results can be easily correlated with those obtained by other techniques such as flow cytometry and genetic analysis, and above all, the clinical findings. The role of the bone marrow biopsy will be particularly stressed in this review article. Particular emphasis is being given to the correct identification of cases of myeloid neoplasms associated with myelofibrosis and for which the bone marrow biopsy represents the only available diagnostic mean. Moreover, the often low cellular yield of the bone marrow aspirate in these cases may also be insufficient to obtain adequate cytogenetic information. Such cases include two subtypes of acute myeloid leukemia which typically cause diagnostic difficulties: acute megakaryoblastic leukemia and acute panmyelosis with myelofibrosis (acute myelosclerosis). Acute myeloid leukemia with multilineage dysplasia, therapy-related myelodysplastic syndrome/therapy-related acute myeloid leukemia and de novo myelodysplastic syndromes (MDS) will also be discussed. The value of bone marrow biopsy in this group of disorders is generally well established. In MDS, in particular, bone marrow biopsy may help in confirming a suspected diagnosis by excluding reactive conditions in which dyshematopoietic changes may also be observed. It can increase the diagnostic accuracy and helps in refining the IPPS risk evaluation system. Among the alterations detected by bone marrow biopsy, a prognostically important finding is the presence of aggregates or clusters of immature myeloid precursor cells (myeloblasts and promyelocytes). These can also be identified by immunohistochemistry with CD34, an antigen expressed in progenitor and early precursor marrow cells, which can be used to demonstrate pathological accumulations of blasts in aggressive subtypes of myeloid neoplasms. Immunohistologic analysis is especially helpful in cases of MDS with fibrosis and cases with hypocellular marrows (hypoplastic MDS). In both of these variants, the presence of reticulin fibrosis or fatty changes in the bone marrow can make accurate disease characterization very difficult or impossible using bone marrow aspirates. Finally, the important group of the myelodysplastic/myeloproliferative disorders can only be accurately categorized by a careful multiparametric approach in which the bone marrow biopsy exerts a pivotal role.
Petrography and geochemistry of Eocene cold-seep carbonates from Washington State, USA

Mineralbildung gebunden an sulfatabhangige anaerobe Methanoxidation (AMO) in marinen Sedimenten ist eine der faszinierendsten Entdeckungen der Marinen Geowissenschaften der letzten Jahrzehnte und hat das Interesse der internationalen Forschungsgemeinschaft geweckt. Die Zahl der Publikationen zu diesem Thema stieg rasch an und neue Entdeckungen werden bis heute gemacht. Die Rolle von Methan in mikrobiellen und geochemischen Prozessen in marinen Sedimenten ist mittlerweile anerkannt und AMO durch Archaeen und Bakterien wird als Hauptmechanismus der Mineralfallung an Methanaustritten (sog. „seeps“ oder auch „cold-seeps“) angesehen. Diese Arbeit beschreibt die Petrographie und Geochemie von eozanen Seep-Karbonaten der Siltstone of Shoalwater Bay Formation aus Washington State, USA. Hauptziele der Arbeit sind eine petrographische Beschreibung der Mineralphasen und eine geochemische Modellierung von Mineralneubildung mit Hilfe der hydrochemischen Software PHREEQC. Zusatzlich wurde Fluoreszenzmikroskopie und Geochemie der stabilen Isotope von Sauerstoff und Kohlenstoff in den Karbonatphasen eingesetzt. Ersteres wurde angewandt, um den Gehalt an organischem Material in den Phasen abzuschatzen, letzteres um die Genese der Phasen zu rekonstruieren. Spezielles Augenmerk wurde auf die Verkieselung der untersuchten Seep-Karbonaten gelegt. Mit Hilfe der Modellierung wurden verschiedene Parameter wie pH, heterogene Reaktionen von Festphasen sowie Auflosungskinetik und Thermodynamik und die Zusammensetzung der Losung untersucht, um Mechanismen der Silikatfallung und Losung an Seep-Karbonaten zu identifizieren und zu verstehen. Diese Erkenntnisse wurden dann mit Beobachtungen unter dem Mikroskop (i.e. Petrographie) in Verbindung gebracht, um ein Gesamtbild der Mineralgenese zu erlangen.
Alisertib, an Aurora kinase A inhibitor, induces apoptosis and autophagy but inhibits epithelial to mesenchymal transition in human epithelial ovarian cancer cells

Ovarian cancer is a leading killer of women, and no cure for advanced ovarian cancer is available. Alisertib (ALS), a selective Aurora kinase A (AURKA) inhibitor, has shown potent anticancer effects, and is under clinical investigation for the treatment of advanced solid tumor and hematologic malignancies. However, the role of ALS in the treatment of ovarian cancer remains unclear. This study investigated the effects of ALS on cell growth, apoptosis, autophagy, and epithelial to mesenchymal transition (EMT), and the underlying mechanisms in human epithelial ovarian cancer SKOV3 and OVCAR4 cells. Our docking study showed that ALS, MLN8054, and VX-680 preferentially bound to AURKA over AURKB via hydrogen bond formation, charge interaction, and π-π stacking. ALS had potent growth-inhibitory, proapoptotic, proautophagic, and EMT-inhibitory effects on SKOV3 and OVCAR4 cells. ALS arrested SKOV3 and OVCAR4 cells in G2/M phase and induced mitochondria-mediated apoptosis and autophagy in both SKOV3 and OVCAR4 cell lines in a concentration-dependent manner. ALS suppressed phosphatidylinositol 3-kinase/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) and p38 mitogen-activated protein kinase pathways but activated 5′-AMP-dependent kinase, as indicated by their altered phosphorylation, contributing to the proautophagic activity of ALS. Modulation of autophagy altered basal and ALS-induced apoptosis in SKOV3 and OVCAR4 cells. Further, ALS suppressed the EMT-like phenotype in both cell lines by restoring the balance between E-cadherin and N-cadherin. ALS downregulated sirtuin 1 and pre-B cell colony enhancing factor (PBEF/visfatin) expression levels and inhibited phosphorylation of AURKA in both cell lines. These findings indicate that ALS blocks the cell cycle by G2/M phase arrest and promotes cellular apoptosis and autophagy, but inhibits EMT via phosphatidylinositol 3-kinase/Akt/mTOR-mediated and sirtuin 1-mediated pathways in human epithelial ovarian cancer cells. Further studies are warranted to validate the efficacy and safety of ALS in the treatment of ovarian cancer.
Puberty as an accelerator for diabetes complications

Much is written about how difficult it is to deal with diabetes during adolescence, and rightly so. Less is understood as to how puberty may be an accelerator of vascular complications. With the increase in childhood diabetes, complication risks need to be revisited in relation to puberty and the secular increase in adiposity. Recent data suggest greater risk for severe vascular complications in those with diabetes during puberty, compared with young people who develop diabetes after puberty. It is also widely recognized that higher hemoglobin A1c (HbA1c) results are often seen during the pubertal period. This article will review complication outcomes in relation to puberty and examine mechanisms by which puberty may modify risk above glycemic exposure, and possible gender disparities in the risk of complications in the adolescent period.
Comparison of Campylobacter Levels in Crops and Ceca of Broilers at Slaughter

Abstract A considerable fraction of the poultry carcasses becomes contaminated with Campylobacter by cross-contamination from the digestive tract of colonized broilers at slaughter. Campylobacter in the crop may serve as a possible source of cross-contamination, because the crop may contain high numbers of Campylobacter and is more likely to rupture during the slaughtering process than intestines. In this study, the correlation between Campylobacter colonization levels in crop and cecum was assessed in 48 broilers of 31 days of age. In addition, the effect of drinking water supplemented with 0.2% volatile fatty acid (VFA) on these Campylobacter colonization levels was studied. No correlation between crop and cecal colonization levels was found (ρ = 0.09; P = 0.71), indicating that future studies on cross-contamination should include an examination of not only cecal colonization levels but also crop colonization levels. Supplementation of drinking water with VFA did not result in a significant reduction of colonization levels in either the crop (P = 0.50) or the ceca (P = 0.92), indicating that this is not an effective measure to reduce cross-contamination at slaughter.
The growth potential of startups over the business cycle

This paper shows that job creation of cohorts of U.S. firms is strongly influenced by aggregate conditions at the time of their entry. Using data from the Business Dynamics Statistics (BDS) we follow cohorts of young firms and document that their employment levels are very persistent and largely driven by the intensive margin (average firm size) rather than the extensive margin (number of firms). To differentiate changes in the composition of startup cohorts from post-entry choices and to evaluate aggregate effects, we estimate a general equilibrium firm dynamics model using BDS data. We find that even for older firms, the aggregate state at birth drives the vast majority of variations in employment across cohorts of the same age. The key force behind this result are fluctuations in the composition of startup cohorts with respect to firms' potential to grow large. At the aggregate level, factors determined at the startup phase account for the large low-frequency fluctuations observed in the employment rate.
Hybrid model for short term wind speed forecasting using empirical mode decomposition and artificial neural network

Wind speed modeling and prediction plays a critical role in wind related engineering studies. With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind speed forecasts. Accurate wind speed forecasts are necessary to schedule dispatchable generation and tariffs in the electricity market. In this paper a hybrid model named EMD-ANN for wind speed prediction is proposed based on the Empirical Mode Decomposition (EMD) and the Artificial Neural Networks (ANN) for renewable energy systems. All the models are analyzed with real data of wind speeds in Bilecik, Turkey using data measurement from the Turkish State Meteorological Service. Accuracy of the forecasting is evaluated in terms of MAE and MSE.
The Nuclear Receptor Coactivator AIB1 Mediates Insulin-like Growth Factor I-induced Phenotypic Changes in Human Breast Cancer Cells

The nuclear receptor coactivator AIB1 (amplified in breast cancer 1) is overexpressed in human breast cancers and is required for estrogen signaling. However, the role of AIB1 in breast cancer etiology is not known. Here, we show that AIB1 is rate-limiting for insulin-like growth factor I (IGF-I)-dependent phenotypic changes and gene expression in human breast cancer cells. Reduction of endogenous AIB1 levels by small interfering RNA in MCF-7 breast cancer cells prevented IGF-I–stimulated anchorage-independent growth by reducing IGF-I–dependent anti-anoikis. cDNA array and immunoblot analysis of gene expression revealed that reduction in AIB1 levels led to a significant decrease in the expression of several genes controlling the cell cycle and apoptosis. These AIB1-dependent changes were also observed in the presence of estrogen antagonist and were corroborated in the estrogen receptor-negative cell line MDA MB-231. AIB1 reduction decreased the expression of the IGF-I receptor and IRS-1 in MCF-7 but not in MDA MB-231 cells. IGF-I–stimulated activation of AKT was reduced by AIB1 small interfering RNA treatment, whereas mitogen-activated protein kinase (extracellular signal-regulated kinase 1/2) activation by IGF-I was unaffected. We conclude that AIB1 is required for IGF-I–induced proliferation, signaling, cell survival, and gene expression in human breast cancer cells, independent of its role in estrogen receptor signaling.
Some Evaluations about Use of Vermicompost in Agricultural Activity of Thrace Region, Turkey: A Review

Turkey is located in Asian and European continents (Eurasia) and the country’s population is nearly 81 million. Thrace Region which exists in European part of Turkey has a very important agricultural potential. Thrace, gateway of Turkey to Europe, also has an important position with its agricultural potential. Therefore, it is of strategic importance. Sunflower, rice, sugar beet and wheat are the major crops grown in the region. The main sources of income of people in Tekirdag, Kirklareli and Edirne provinces are coming from agriculture. In this region, livestock activities also increase day by day and a lot of waste comes out. Vermicomposting is an environmentally-friendly process used to animal and/or vegetal organic waste. The resulting vermicompost has been shown to have many positive effects on soil quality and plant growth. However, many important benefits of vermicompost on soil-plant systems are not yet fully understood. A case study is presented in which the beneficial effects of vermicompost on soil quality and plant growth are evaluated according to previous researches in the Thrace Region, Turkey. The use of vermicompost is important for the sustainability of agriculture. The structure of agriculture and fertilization, related to Thrace Region, is evaluated in this paper. The aim of the paper is to review recent developments, approaches and examples for use of vermicompost in the agricultural activity of Thrace Region, Turkey. The results can be used to manage next year growing strategies such as low chemical fertilizer and other agricultural input requirements.
Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach

Background Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. Results The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. Conclusions Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.
Rectifying Predictions of Classifiers by Local Rules

The main advantage of unordered classification rules is in their power to spot and explain local regularities. However, using them in classification often poses problems due to conflicts between rules, when some resolution principle needs to be applied. On the other hand, most of the machine learning methods try to learn conflict-free hypotheses covering the whole domain space and are not concerned with single patterns only. In this paper we propose an algorithm named PILAR that combines the advantages of both approaches. Our algorithm aims at improving any machine learning algorithm by comparing its predictions with predictions of rules, and applying changes to the predictions of initial model when necessary. Moreover, if a dummy classifier (e.g. majority classifier) is used, then this procedure acts as a classifier from rules only and can be compared to other methods for classification from rules. We experimentally validated our method with two basic classification methods. In the first one dummy classifier was used and in the second logistic regression.
Throughput Utility Optimization in HetNets

The deployment of pico cells to cover traffic hot spots within the footprint of a macro cell provides a powerful approach to meet the massive growth in traffic demands fueled by smartphones and bandwidth-hungry applications. Joint optimization of resource allocation and user association is of critical importance to achieve the maximal capacity benefits in such heterogeneous network deployments (HetNets). We specifically examine the problem of maximizing the aggregate throughput utility of the various users. We characterize the structure of the optimal solution, and identify a simple optimality condition in terms of the transmission rates of the edge users between the macro cell and the various pico cells. Exploiting the structural properties, we develop distributed online algorithms for the broad class of alpha-fair utility functions, which includes several common fairness notions. Numerical experiments are presented to illustrate the results.
Effectiveness and Safety of Dabigatran, Rivaroxaban, and Apixaban Versus Warfarin in Nonvalvular Atrial Fibrillation

Background The introduction of non–vitamin K antagonist oral anticoagulants has been a major advance for stroke prevention in atrial fibrillation; however, outcomes achieved in clinical trials may not translate to routine practice. We aimed to evaluate the effectiveness and safety of dabigatran, rivaroxaban, and apixaban by comparing each agent with warfarin. Methods and Results Using a large US insurance database, we identified privately insured and Medicare Advantage patients with nonvalvular atrial fibrillation who were users of apixaban, dabigatran, rivaroxaban, or warfarin between October 1, 2010, and June 30, 2015. We created 3 matched cohorts using 1:1 propensity score matching: apixaban versus warfarin (n=15 390), dabigatran versus warfarin (n=28 614), and rivaroxaban versus warfarin (n=32 350). Using Cox proportional hazards regression, we found that for stroke or systemic embolism, apixaban was associated with lower risk (hazard ratio [HR] 0.67, 95% CI 0.46–0.98, P=0.04), but dabigatran and rivaroxaban were associated with a similar risk (dabigatran: HR 0.98, 95% CI 0.76–1.26, P=0.98; rivaroxaban: HR 0.93, 95% CI 0.72–1.19, P=0.56). For major bleeding, apixaban and dabigatran were associated with lower risk (apixaban: HR 0.45, 95% CI 0.34–0.59, P<0.001; dabigatran: HR 0.79, 95% CI 0.67–0.94, P<0.01), and rivaroxaban was associated with a similar risk (HR 1.04, 95% CI 0.90–1.20], P=0.60). All non–vitamin K antagonist oral anticoagulants were associated with a lower risk of intracranial bleeding. Conclusions In patients with nonvalvular atrial fibrillation, apixaban was associated with lower risks of both stroke and major bleeding, dabigatran was associated with similar risk of stroke but lower risk of major bleeding, and rivaroxaban was associated with similar risks of both stroke and major bleeding in comparison to warfarin.