Miracle-dz/UniFAR-FTUs huggingface dataset:
Interspecific Y chromosome introgressions disrupt testis-specific gene expression and male reproductive phenotypes in Drosophila

The Drosophila Y chromosome is a degenerated, heterochromatic chromosome with few functional genes. Nonetheless, natural variation on the Y chromosome in Drosophila melanogaster has substantial trans-acting effects on the regulation of X-linked and autosomal genes. However, the contribution of Y chromosome divergence to gene expression divergence between species is unknown. In this study, we constructed a series of Y chromosome introgression lines, in which Y chromosomes from either Drosophila sechellia or Drosophila simulans are introgressed into a common D. simulans genetic background. Using these lines, we compared genome-wide gene expression and male reproductive phenotypes between heterospecific and conspecific Y chromosomes. We find significant differences in expression for 122 genes, or 2.84% of all genes analyzed. Genes down-regulated in males with heterospecific Y chromosomes are significantly biased toward testis-specific expression patterns. These same lines show reduced fecundity and sperm competitive ability. Taken together, these results imply a significant role for Y/X and Y/autosome interactions in maintaining proper expression of male-specific genes, either directly or via indirect effects on male reproductive tissue development or function.
Pharmacological treatment of schizophrenia

Abstract Background: A lack of human and financial resources, as well as effective health systems, leads to a worldwide treatment gap for schizophrenia. The aim of this paper is to propose evidence-based antipsychotics interventions for people with schizophrenia with special focus in low and middle income countries (LAMIC) reality. Method: A comprehensive search was conducted to locate the main clinical trials, reviews and relevant meta-analyses, and a number of the main recent international clinical practice guidelines. Results: First- and second-generation antipsychotics are similarly effective in the acute treatment of psychotic symptoms. In LAMIC, the treatment of choice for medical treatment of psychotic conditions is the group of so-called ‘first generation antipsychotics’ (FGAs) preferentially delivered in a community-based service model. Conclusions: Although the symptomatic control is essential, it is not the ultimate goal of treatment. The main aim of treatment is to improve functional recovery and social reintegration of patients.
Spanish Word Vectors from Wikipedia

Contents analisys from text data requires semantic representations that are difficult to obtain automatically, as they may require large handcrafted knowledge bases or manually annotated examples. Unsupervised autonomous methods for generating semantic representations are of greatest interest in face of huge volumes of text to be exploited in all kinds of applications. In this work we describe the generation and validation of semantic representations in the vector space paradigm for Spanish. The method used is GloVe (Pennington, 2014), one of the best performing reported methods , and vectors were trained over Spanish Wikipedia. The learned vectors evaluation is done in terms of word analogy and similarity tasks (Pennington, 2014; Baroni, 2014; Mikolov, 2013a). The vector set and a Spanish version for some widely used semantic relatedness tests are made publicly available.
Direct activation by dopamine of recombinant human 5‐HT1A receptors: Comparison with human 5‐HT2C and 5‐HT3 receptors

The effects of dopamine (DA) on the function of human 5‐HT1A receptors expressed in Xenopus oocytes and CHO‐K1 cells were investigated. In addition, the effect of DA on the activation of three different types of human 5‐HT receptors (5‐HT1A, 5‐HT2C, and 5‐HT3) were studied comparatively in Xenopus oocyte expression system. Application of 5‐HT or DA in oocytes coexpressing 5‐HT1A receptors and G‐protein‐activated inwardly rectifying potassium channels (GIRK1) induced inward currents with respective EC50 values of 4.2 nM and 11.2 μM. Maximal responses induced by DA were 85 ± 4% of maximal 5‐HT currents and DA responses were blocked by the specific 5‐HT1A antagonist, WAY‐100635 (50 nM). In CHO‐K1 cells expressing 5‐HT1A receptors, 5‐HT and DA inhibited the specific binding of selective antagonist [3H]‐8‐OH‐DPAT with IC50 values of 10.2 nM and 1.4 μM, and both 5‐HT and DA inhibited the forskolin‐induced accumulation of cAMP. In oocytes expressing 5‐HT2C receptors, 5‐HT and DA induced inward currents with respective EC50 values of 6.2 nM and 67.7 μM. Magnitudes of maximal DA induced currents were 42 ± 3% of maximal 5‐HT responses and blocked by the 5‐HT2 antagonist, piperazine (1 μM). In oocytes expressing 5‐HT3 receptors, 5‐HT and DA induced fast inward currents with respective EC50 values of 2.1 μM and 266.3 μM. Maximal DA induced currents were 37 ± 3% of maximal 5‐HT responses and blocked the specific 5‐HT3 antagonist LY‐278584 (0.1 μM). Comparison of the potencies and efficacies of 5‐HT and DA indicated that the relative potency of DA increased in the order of 5‐HT3 > 5‐HT1A > 5‐HT2C, and relative efficacy increased in the order of 5‐HT1A > 5‐HT2C > 5‐HT3. These results suggest that although DA activates different subtypes of human 5‐HT receptors directly, the potency and efficacy of the binding site varies significantly among different receptors. Synapse 50:303–313, 2003. Published 2003 Wiley‐Liss, Inc.
Precision of measurement by dual‐energy X‐ray absorptiometry of bone mineral density and content in rat hindlimb in vitro

Dual‐energy x‐ray absorptiometry (DXA) is a precise and effective method for measuring bone mineral density (BMD) and content (BMC) at various skeletal sites in the human, but its precision for measuring low BMD and BMC in tiny rat bones has scarcely been evaluated. The short‐term precision of DXA (Norland XR‐26) for eight regions of interest (ROI) was determined by measuring dissected, not totally defleshed hindlimbs from four rats of differently weights 10 times consecutively. The accuracy of the BMD (area) measurement was also evaluated. The following average precision values (coefficients of variation) with negligible reanalysis error were obtained for BMD and BMC measurements: 0.7 and 1.2% (total); 0.9 and 1.2% (femur); 1.3 and 2.8% (tibia); 1.3 and 2.1% (foot); 2.1 and 4.7% (proximal femur); 1.4 and 2.9% (femoral shaft); 1.8 and 5.6% (distal femur); and 2.7 and 7.6% (proximal tibia). As for the accuracy, BMD measured in tiny bones is likely to be markedly underestimated. We conclude that the standard DXA technique without additional modification for small animal measurements is a precise method for BMD and BMC measurements at multiple sites in rat hindlimb in vitro.
Thematic review series: Lipid Posttranslational Modifications. Structural biology of protein farnesyltransferase and geranylgeranyltransferase type I Published, JLR Papers in Press, February 13, 2006.

More than 100 proteins necessary for eukaryotic cell growth, differentiation, and morphology require posttranslational modification by the covalent attachment of an isoprenoid lipid (prenylation). Prenylated proteins include members of the Ras, Rab, and Rho families, lamins, CENPE and CENPF, and the γ subunit of many small heterotrimeric G proteins. This modification is catalyzed by the protein prenyltransferases: protein farnesyltransferase (FTase), protein geranylgeranyltransferase type I (GGTase-I), and GGTase-II (or RabGGTase). In this review, we examine the structural biology of FTase and GGTase-I (the CaaX prenyltransferases) to establish a framework for understanding the molecular basis of substrate specificity and mechanism. These enzymes have been identified in a number of species, including mammals, fungi, plants, and protists. Prenyltransferase structures include complexes that represent the major steps along the reaction path, as well as a number of complexes with clinically relevant inhibitors. Such complexes may assist in the design of inhibitors that could lead to treatments for cancer, viral infection, and a number of deadly parasitic diseases.
Is essence a measure of maintainability?

We recently published a paper at ECOOP presenting a new software design metric, essence, that quantifies the amount of indirection in a software design. The reviews were overwhelmingly positive and included statements such as “The evaluation of the metric is fantastic. ” However, we also received feedback from senior researchers who do not believe that we have meaningfully evaluated our metric. This paper represents our effort towards a meaningful evaluation of essence. Given our lack of experience in human-subject studies, we hope to receive valuable feedback on our proposed study design.
Chatting in distributed quantization networks

Several key results in source coding offer the intuition that distributed encoding via vector-quantize-and-bin is only slightly suboptimal to joint encoding and oftentimes is just as good. However, when source acquisition requires the block length to be small, collaboration between sensors can greatly reduce distortion. For a distributed acquisition network where sensors are allowed to “chat” using a side channel, we provide exact characterization of distortion performance and quantizer design in the high-resolution (low-distortion) regime using a framework called distributed functional scalar quantization (DFSQ). The key result is that chatting can dramatically improve performance even when the intersensor communication is at very low rate. We also solve the rate allocation problem when communication links have heterogeneous costs and provide examples to demonstrate that this theory predicts performance at practical communication rates.
Cumulative Voting Consensus Method for Partitions with Variable Number of Clusters

Over the past few years, there has been a renewed interest in the consensus clustering problem. Several new methods have been proposed for finding a consensus partition for a set of n data objects that optimally summarizes an ensemble. In this paper, we propose new consensus clustering algorithms with linear computational complexity in n. We consider clusterings generated with a random number of clusters, which we describe by categorical random variables. We introduce the idea of cumulative voting as a solution for the problem of cluster label alignment, where unlike the common one-to-one voting scheme, a probabilistic mapping is computed. We seek a first summary of the ensemble that minimizes the average squared distance between the mapped partitions and the optimal representation of the ensemble, where the selection criterion of the reference clustering is defined based on maximizing the information content as measured by the entropy. We describe cumulative vote weighting schemes and corresponding algorithms to compute an empirical probability distribution summarizing the ensemble. Given the arbitrary number of clusters of the input partitions, we formulate the problem of extracting the optimal consensus as that of finding a compressed summary of the estimated distribution that preserves the maximum relevant information. An efficient solution is obtained using an agglomerative algorithm that minimizes the average generalized Jensen-Shannon divergence within the cluster. The empirical study demonstrates significant gains in accuracy and superior performance compared to several recent consensus clustering algorithms.
Collecting Conceptualized Relations from Terabytes of Web Texts for Understanding Unknown Terms

This paper describes our attempt to extract various relations between super ordinate concepts from terabytes of Web corpus for human-like speculation of the meaning of unknown terms. In order to discover various conceptualized relations, we focus on Web-scale text corpora and introduce a simple string-matching method to process them. To derive relations between concepts, our method first extracts relations between terms and next replaces each term by appropriate concepts using Wikipedia, Word Net, and YAGO knowledge. We extracted over 10 million relations between concepts in a day from more than 10TB of Web texts using 100 machines. Experimental results revealed that extracted relations by our method contained much more meaningless relations than those by NLP-based methods. Nevertheless, they were useful in an application of speculating the meaning of unknown terms, improving the recall by more than 0.06 points and decreasing the accuracy by only 0.04 points (the improvement of the F1-measure was 0.03 points). We found from the results that the coverage of conceptualized relations is important to improve the precision in the application. This is because the lack of knowledge (conceptualized relations) leads to misunderstanding of the meaning of unknown terms, as we humans misunderstand things with our insufficient knowledge.
BACE2 degradation mediated by the macroautophagy–lysosome pathway

Neuritic plaque is the pathological hallmark in Alzheimer's disease (AD). Amyloid‐β protein (Aβ), the central component of neuritic plaques, is generated from amyloid‐β precursor protein (APP) by β‐site APP cleaving enzyme 1 (BACE1) and γ‐secretase. β‐site APP cleaving enzyme 2 (BACE2), a homolog of BACE1, functions differently from BACE1 in APP processing. BACE1 is the β‐secretase essential for Aβ production, and BACE2, a θ‐secretase, cleaves APP within the Aβ domain, preventing Aβ production. Elucidation of the mechanism underlying BACE2 degradation is important for defining its biological features and its potential role in Alzheimer's disease drug development. In this report we first showed that the half‐life of BACE2 is approximately 20 h. Lysosomal inhibition increased BACE2 protein levels whereas proteasomal inhibition had no effect on BACE2 protein expression. Furthermore, we identified that macroautophagy mediated BACE2 degradation. Finally, we showed that lysosomal inhibition increased BACE2 cleavage of APP. Taken together, our in vitro study showed that BACE2 is degraded through the macrophagy–lysosome pathway and that lysosomal inhibition affects BACE2 processing of APP. Modulation of BACE2 degradation via the lysosomal pathway could be a new target for AD drug development.
Cross-kingdom Amplification Using Bacterial-specific Primers: Complications for 1 Coral Microbial Ecology 2 3

9 PCR amplification of pure bacterial DNA is vital to the study of bacterial interactions 10 with corals. Commonly used bacterial-specific primers 8F and 27F paired with universal 11 primer 1492R amplify both eukaryotic and prokaryotic rDNA. An alternative primer set, 12 63F/1542R, is suggested to resolve this problem. 13
Zebralocalizer: identification and localization of pedestrian crossings

Independent mobility in unfamiliar environments is a significant challenge for people with severe vision impairment. Among other problems, one specific issue concerns the identification of those road signs that can be recognized by sight only. In this paper we present ZebraLocalizer, an application for mobile devices that identifies zebra crossings and guides the user towards them. Two main problems are discussed in this contribution: the identification and localization of the crosswalks, performed by processing data acquired both from the camera and the accelerometers, and the design of an interaction paradigm specifically addressed to blind users. Experimental results, conducted both on a dataset of images and with blind users, validate the applicability of the proposed solution.
A Gabor-Block-Based Kernel Discriminative Common Vector Approach Using Cosine Kernels for Human Face Recognition

In this paper a nonlinear Gabor Wavelet Transform (GWT) discriminant feature extraction approach for enhanced face recognition is proposed. Firstly, the low-energized blocks from Gabor wavelet transformed images are extracted. Secondly, the nonlinear discriminating features are analyzed and extracted from the selected low-energized blocks by the generalized Kernel Discriminative Common Vector (KDCV) method. The KDCV method is extended to include cosine kernel function in the discriminating method. The KDCV with the cosine kernels is then applied on the extracted low-energized discriminating feature vectors to obtain the real component of a complex quantity for face recognition. In order to derive positive kernel discriminative vectors, we apply only those kernel discriminative eigenvectors that are associated with nonzero eigenvalues. The feasibility of the low-energized Gabor-block-based generalized KDCV method with cosine kernel function models has been successfully tested for classification using the L 1, L2 distance measures; and the cosine similarity measure on both frontal and pose-angled face recognition. Experimental results on the FRAV2D and the FERET database demonstrate the effectiveness of this new approach.
The Ability of Children with Low Vision to Recall Pictures

This article reports three experiments that tested the ability of 11 6–10-year-old children with low vision to recall black-and-white line drawings. Unlike the 22 fully sighted children who were also tested, the children with low vision recalled best when they were left to study the pictures without verbal intervention. Compared with the fully sighted children, the children with low vision named significantly fewer of the remembered pictures correctly.
Evidence for the Re-Enactment of a Recently Learned Behavior during Sleepwalking

Animal studies have shown that sequenced patterns of neuronal activity may be replayed during sleep. However, the existence of such replay in humans has not yet been directly demonstrated. Here we studied patients who exhibit overt behaviors during sleep to test whether sequences of movements trained during the day may be spontaneously reenacted by the patients during sleep. We recruited 19 sleepwalkers (who displayed complex and purposeful behaviors emerging from non REM sleep), 20 patients with REM sleep behavior disorder (who enacted their dreams in REM sleep) and 18 healthy controls. Continuous video sleep recordings were performed during sleep following intensive training on a sequence of large movements (learned during a variant of the serial reaction time task). Both patient groups showed learning of the intensively trained motor sequence after sleep. We report the re-enactment of a fragment of the recently trained motor behavior during one sleepwalking episode. This study provides, to our knowledge, the first evidence of a temporally-structured replay of a learned behavior during sleep in humans. Our observation also suggests that the study of such sleep disorders may provide unique and critical information about cognitive functions operating during sleep.
An Autopsy Study of Maternal Mortality in Mozambique: The Contribution of Infectious Diseases

Background Maternal mortality is a major health problem concentrated in resource-poor regions. Accurate data on its causes using rigorous methods is lacking, but is essential to guide policy-makers and health professionals to reduce this intolerable burden. The aim of this study was to accurately describe the causes of maternal death in order to contribute to its reduction, in one of the regions of the world with the highest maternal mortality ratios. Methods and Findings We conducted a prospective study between October 2002 and December 2004 on the causes of maternal death in a tertiary-level referral hospital in Maputo, Mozambique, using complete autopsies with histological examination. HIV detection was done by virologic and serologic tests, and malaria was diagnosed by histological and parasitological examination. During 26 mo there were 179 maternal deaths, of which 139 (77.6%) had a complete autopsy and formed the basis of this analysis. Of those with test results, 65 women (52.8%) were HIV-positive. Obstetric complications accounted for 38.2% of deaths; haemorrhage was the most frequent cause (16.6%). Nonobstetric conditions accounted for 56.1% of deaths; HIV/AIDS, pyogenic bronchopneumonia, severe malaria, and pyogenic meningitis were the most common causes (12.9%, 12.2%, 10.1% and 7.2% respectively). Mycobacterial infection was found in 12 (8.6%) maternal deaths. Conclusions In this tertiary hospital in Mozambique, infectious diseases accounted for at least half of all maternal deaths, even though effective treatment is available for the four leading causes, HIV/AIDS, pyogenic bronchopneumonia, severe malaria, and pyogenic meningitis. These observations highlight the need to implement effective and available prevention tools, such as intermittent preventive treatment and insecticide-treated bed-nets for malaria, antiretroviral drugs for HIV/AIDS, or vaccines and effective antibiotics for pneumococcal and meningococcal diseases. Deaths due to obstetric causes represent a failure of health-care systems and require urgent improvement.
Classification of Short Messages Initiated by Mobile Malware

In this paper we show that supervised machine learning algorithms can reliably detect short messages initiated by mobile malware based on features derived from the content of short messages. In particular, we compare the detection capabilities of the classifiers Support Vector Machines, K-Nearest Neighbor, Decision Trees, Random Forests, and Multinomial Naive Bayes in three different evaluation scenarios. The first scenario is the standard k-fold cross validation, treating all short messages as independent from each other. In the second scenario, we evaluate, how the classifiers perform if only a certain portion of malware families are known during training. Here, we are able to show that training with only 50% of the the malware families already lead to an accuracy of over 90%. Finally, in the third scenario we evaluate the performance chronologically, i.e. the classifiers are trained with the short messages available at a certain point in time and tested on the newly arriving messages. Here, we show that classifiers can detect the majority of new short messages initiated by mobile malware even months after the training.
Reducing hospital inpatient complications: A four year experience

This study described the use of administrative data and a computer software algorithm, Potentially Preventable Complications, to support reduction of inpatient hospital complications. The study was carried out between 2008 and2012 inSt. Joseph’s Hospital Health Center in Syracuse, New York. The hospital generates approximately 23,000 inpatient discharges annually. The study employed summary tables for individual inpatient complications and patient specific spreadsheets to evaluate and follow adverse outcomes. The spreadsheets were employed by hospital staff to determine whether patient medical records confirm each complication identified by the software. This process resulted in improvement of the accuracy of administrative data describing inpatient complications. The administrative data and the software were also used in conjunction with medical records to Identify patients who received program interventions and still experienced inpatient complications. This process enabled hospital staff to ensure that interventions were being provided and evaluate their effecttiveness. The study demonstrated that, at the aggregate level, the inpatient complication rate per 1000 discharges declined by 33.4 percent, from 56.11 to 37.37 between 2008 and 2011. The principal drivers of this decline were high volume complications such as pneumonia, where the rate declined by 45.7 percent and urinary tract infection where the rate declined by 23.7 percent. The project provided a means of communicating and managing outcomes data that could be implemented and understood by a wide range of health care providers.