Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac Autonomic Control Mechanisms in the Pathogenesis of Chagas' Heart Disease

Primary abnormalities of the autonomic nervous system had been postulated as the pathogenic mechanisms of myocardial damage, in patients with Chagas disease. However, recent investigations indicate that these abnormalities are secondary and amenable to treatment with beta-adrenergic blockers. Moreover, muscarinic cardiac autoantibodies appear to enhance parasympathetic activity on the sinus node. Therefore, the purpose of this paper is to analyze how knowledge on Chagas' disease evolved from being initially considered as a primary cardioneuromyopathy to the current status of a congestive cardiomyopathy of parasitic origin.
Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition

Offline handwriting recognition systems require cropped text line images for both training and recognition. On the one hand, the annotation of position and transcript at line level is costly to obtain. On the other hand, automatic line segmentation algorithms are prone to errors, compromising the subsequent recognition. In this paper, we propose a modification of the popular and efficient multi-dimensional long short-term memory recurrent neural networks (MDLSTM-RNNs) to enable end-to-end processing of handwritten paragraphs. More particularly, we replace the collapse layer transforming the two-dimensional representation into a sequence of predictions by a recurrent version which can recognize one line at a time. In the proposed model, a neural network performs a kind of implicit line segmentation by computing attention weights on the image representation. The experiments on paragraphs of Rimes and IAM database yield results that are competitive with those of networks trained at line level, and constitute a significant step towards end-to-end transcription of full documents.
Semiotic prediction of driving behavior using unsupervised double articulation analyzer

In this paper, we propose a novel semiotic prediction method for driving behavior based on double articulation structure. It has been reported that predicting driving behavior from its multivariate time series behavior data by using machine learning methods, e.g., hybrid dynamical system, hidden Markov model and Gaussian mixture model, is difficult because a driver's behavior is affected by various contextual information. To overcome this problem, we assume that contextual information has a double articulation structure and develop a novel semiotic prediction method by extending nonparametric Bayesian unsupervised morphological analyzer. Effectiveness of our prediction method was evaluated using synthetic data and real driving data. In these experiments, the proposed method achieved long-term prediction 2-6 times longer than some conventional methods.
PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor–positive breast cancer

PIK3CA mutations are reported to be present in approximately 25% of breast cancer (BC), particularly the estrogen receptor–positive (ER+) and HER2-overexpressing (HER2+) subtypes, making them one of the most common genetic aberrations in BC. In experimental models, these mutations have been shown to activate AKT and induce oncogenic transformation, and hence these lesions have been hypothesized to render tumors highly sensitive to therapeutic PI3K/mTOR inhibition. By analyzing gene expression and protein data from nearly 1,800 human BCs, we report that a PIK3CA mutation–associated gene signature (PIK3CA-GS) derived from exon 20 (kinase domain) mutations was able to predict PIK3CA mutation status in two independent datasets, strongly suggesting a characteristic set of gene expression–induced changes. However, in ER+/HER2− BC despite pathway activation, PIK3CA mutations were associated with a phenotype of relatively low mTORC1 signaling and a good prognosis with tamoxifen monotherapy. The relationship between clinical outcome and the PIK3CA-GS was also assessed. Although the PIK3CA-GS was not associated with prognosis in ER− and HER2+ BC, it could identify better clinical outcomes in ER+/HER2− disease. In ER+ BC cell lines, PIK3CA mutations were also associated with sensitivity to tamoxifen. These findings could have important implications for the treatment of PIK3CA-mutant BCs and the development of PI3K/mTOR inhibitors.
Histological Evaluation of Wound Healing Process after Photodynamic Therapy of Rat Oral Mucosal Ulcer

Statement of the Problem When the body defense is compromised, wounds can act as a route for entrance and colonization of microorganisms in the body. Photodynamic therapy with methylene blue is known as a promising antimicrobial modality. Purpose The present study aimed to investigate the effects of this procedure on wound healing processes. Materials and Method In this experimental study, 48 male Wistar rats were recruited. Experimental wounds were surgically made on their buccal mucosa. Based on the treatment modality, they were divided into 3 groups (n=16) of control (CG), laser (LG), photosensitizer+ laser (PLG) by methylene blue (MB). The treatment procedure in the two latter groups was done in days 1-4 and 6-9. After sacrificing on 2, 4, 7 and 14-day follow-ups, the microscopic grade of healing of the wounds was assigned on each interval according to histological grading criteria. Results A qualitative result was obtained that showed a healing progression in PLG at day 2 of follow-up. At day 4 of follow-up, no difference was seen in healing stage among the groups. However on day 7 of follow-up, samples of the LG showed a lower degree of healing compared with the other two groups. Likewise, on day 14 of follow- up, both PLG and LG showed lower degree of healing than CG. Conclusion This study qualitatively showed that MB- mediated photodynamic therapy would have an inhibitory effect on healing process after 14 days of the wound creation.
A General Method for Site Specific Fluorescent Labeling of Recombinant Chemokines

Chemokines control cell migration in many contexts including development, homeostasis, immune surveillance and inflammation. They are also involved in a wide range of pathological conditions ranging from inflammatory diseases and cancer, to HIV. Chemokines function by interacting with two types of receptors: G protein-coupled receptors on the responding cells, which transduce signaling pathways associated with cell migration and activation, and glycosaminoglycans on cell surfaces and the extracellular matrix which organize and present some chemokines on immobilized surface gradients. To probe these interactions, imaging methods and fluorescence-based assays are becoming increasingly desired. Herein, a method for site-specific fluorescence labeling of recombinant chemokines is described. It capitalizes on previously reported 11–12 amino acid tags and phosphopantetheinyl transferase enzymes to install a fluorophore of choice onto a specific serine within the tag through a coenzyme A-fluorophore conjugate. The generality of the method is suggested by our success in labeling several chemokines (CXCL12, CCL2, CCL21 and mutants thereof) and visualizing them bound to chemokine receptors and glycosaminoglycans. CXCL12 and CCL2 showed the expected co-localization on the surface of cells with their respective receptors CXCR4 and CCR2 at 4°C, and co-internalization with their receptors at 37°C. By contrast, CCL21 showed the presence of large discrete puncta that were dependent on the presence of both CCR7 and glycosaminoglycans as co-receptors. These data demonstrate the utility of this labeling approach for the detection of chemokine interactions with GAGs and receptors, which can vary in a chemokine-specific manner as shown here. For some applications, the small size of the fluorescent adduct may prove advantageous compared to other methods (e.g. antibody labeling, GFP fusion) by minimally perturbing native interactions. Other advantages of the method are the ease of bacterial expression, the versatility of labeling with any maleimide-fluorophore conjugate of interest, and the covalent nature of the fluorescent adduct.
A strategy for the use of cardiac injury markers (troponin I and T, creatine kinase-MB mass and isoforms, and myoglobin) in the diagnosis of acute myocardial infarction.

OBJECTIVE To design a strategy for cardiac injury marker testing in the diagnosis of acute myocardial infarction. DESIGN Prospective study. Group I (n=54 patients): evaluation of clinical performance. Specimens collected at 0, 3, 6, and 12 (+/-1.5) hours after presentation. World Health Organization criteria were used for diagnosis of acute myocardial infarction. Group II (n=57 patients): evaluation of temporal evolution. Time intervals 0 to 1.5, 1.5 to 4.5, 4.5 to 7.5, and 7.5 to 13.5 hours. Patients identified by positive creatine kinase-MB (CK-MB) mass or myoglobin. Fourteen patients in Group I qualified for Group II. Hence, the total number of patients was 97. SETTING A team of laboratorians and clinicians at the University of California, Davis, hospital assessed the clinical performance and temporal evolution of serial CK-MB isoform, troponin I, and troponin T results in comparison to parallel CK-MB mass and myoglobin results. MAIN OUTCOME MEASURES Group I: sensitivity, specificity, and positive and negative predictive values. Group II: the time interval of the first positive result for each cardiac injury marker. Strategy and conclusions were based on study results and a literature review. PARTICIPANTS Emergency department patients with acute onset of chest pain and other complaints, possibly indicative of myocardial ischemia, who were under evaluation for admission. RESULTS Twenty-seven cases of acute myocardial infarction were documented. Group I: troponin I had the highest specificity (100%) and the highest positive predictive value (100%); troponin I, troponin T, and CK-MB mass had the highest sensitivity (90.0%); and the negative predictive values of troponin I, troponin T, and CK-MB mass were comparable (97.8%, 97.6%, and 97.6%, respectively). Group II: early diagnosis (within 1.5 hours) was provided by both CK-MB isoforms and CK-MB mass, and then by myoglobin and troponins, in order of decreasing frequency. CONCLUSIONS Creatine kinase-MB mass, myoglobin, and troponin I were selected as the cardiac injury markers of choice at our institution. The strategy calls for serial testing of myoglobin and CK-MB mass initially-and serially if warranted by heightened clinical suspicion--with troponin I added if indicated for (1) specific confirmation, (2) late presentation, or (3) risk stratification.
Prevalence and risk factors of domestic violence among Mongolian Women.

AIMS The purpose of this study was to investigate the prevalence and determinants of domestic violence in Mongolian women. METHODS The survey was administered to 5500 people in 1000 households randomly selected from two districts of Ulaanbaatar, Mongolia. RESULTS The response rate was 90.3% (total of 4967, and 3338 were women.). About 37.7% of respondents reported that they were affected by some type of domestic violence during the previous 6 months; 17.9% of all respondents reported physical violence, 21.9% reported emotional violence, 10% reported sexual abuse, and 6.9% reported financial violence. Major risk factors for violence against women included having only a primary education or less, low income, living in a rented house, and living with an unemployed partner who uses alcohol. CONCLUSIONS Domestic or intimate partner violence (IPV) is widespread in Mongolia and is usually committed in family circles, often away from public view. This study suggests that increasing employment for men may help reduce poverty and alcohol abuse and, thus, IPV.
Expensive optimization, uncertain environment: an EA-based solution

Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations.allUse of any population based iterative technique such as evolutionary algorithmall in such problem domains is thus practically prohibitive. A feasible alternative is to build surrogates or use an approximation of the actual fitness functions to be evaluated. Naturally these surrogate or meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. This paper presents two evolutionary algorithm frameworks which involve surrogate based fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [1] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the meta-model are generated from a single uniform model. This does not take into account problem domains involving uncertain environment. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle uncertain environment [2]. Empirical evaluation results have been presented based on application of the frameworks to commonly used benchmark functions.
Being Mexican: Strengths and Challenges of Mexican-Origin Adolescents.

This article provides outcomes of a qualitative inquiry with 20 adolescents of Mexican origin, all of whom have lived in the United States at least two years. Questions addressed the perceived strengths and challenges related to the participants’ ethnic heritage. Findings indicated the greatest perceived challenge was discrimination. Strengths were identified as pride in one’s heritage and the ability to overcome difficulties and to respond effectively to discrimination. Suggestions for applying findings to school counselor practices are provided.
Abnormal Event Detection at 150 FPS in MATLAB

Speedy abnormal event detection meets the growing demand to process an enormous number of surveillance videos. Based on inherent redundancy of video structures, we propose an efficient sparse combination learning framework. It achieves decent performance in the detection phase without compromising result quality. The short running time is guaranteed because the new method effectively turns the original complicated problem to one in which only a few costless small-scale least square optimization steps are involved. Our method reaches high detection rates on benchmark datasets at a speed of 140-150 frames per second on average when computing on an ordinary desktop PC using MATLAB.
Towards Framework-Independent Evaluation of Deep Linguistic Parsers

This paper describes practical issues in the framework-independent evaluation of deep and shallow parsers. We focus on the use of two dependencybased syntactic representation formats in parser evaluation, namely, Carroll et al. (1998)’s Grammatical Relations and de Marneffe et al. (2006)’s Stanford Dependency scheme. Our approach is to convert the output of parsers into these two formats, and measure the accuracy of the resulting converted output. Through the evaluation of an HPSG parser and Penn Treebank phrase structure parsers, we found that mapping between different representation schemes is a non-trivial task that results in lossy conversions that may obscure important differences between different parsing approaches. We discuss sources of disagreements in the representation of syntactic structures in the two dependency-based formats, indicating possible directions for improved framework-independent parser evaluation.
Molecular evidence for sediment nitrogen fixation in a temperate New England estuary

Primary production in coastal waters is generally nitrogen (N) limited with denitrification outpacing nitrogen fixation (N2-fixation). However, recent work suggests that we have potentially underestimated the importance of heterotrophic sediment N2-fixation in marine ecosystems. We used clone libraries to examine transcript diversity of nifH (a gene associated with N2-fixation) in sediments at three sites in a temperate New England estuary (Waquoit Bay, Massachusetts, USA) and compared our results to net sediment N2 fluxes previously measured at these sites. We observed nifH expression at all sites, including a site heavily impacted by anthropogenic N. At this N impacted site, we also observed mean net sediment N2-fixation, linking the geochemical rate measurement with nifH expression. This same site also had the lowest diversity (non-parametric Shannon = 2.75). At the two other sites, we also detected nifH transcripts, however, the mean N2 flux indicated net denitrification. These results suggest that N2-fixation and denitrification co-occur in these sediments. Of the unique sequences in this study, 67% were most closely related to uncultured bacteria from various marine environments, 17% to Cluster III, 15% to Cluster I, and only 1% to Cluster II. These data add to the growing body of literature that sediment heterotrophic N2-fixation, even under high inorganic nitrogen concentrations, may be an important yet overlooked source of N in coastal systems.
Functional analysis of promoter variants in the microsomal triglyceride transfer protein (MTTP) gene

The microsomal triglyceride transfer protein (MTTP) is required for the assembly and secretion of apolipoprotein B (apoB)‐containing lipoproteins from the intestine and liver. According to this function, polymorphic sites in the MTTP gene showed associations to low‐density lipoprotein (LDL) cholesterol and related traits of the metabolic syndrome. Here we studied the functional impact of common MTTP promoter polymorphisms rs1800804:T>C (−164T>C), rs1800803:A>T (−400A>T), and rs1800591:G>T (−493G>T) using gene‐reporter assays in intestinal Caco‐2 and liver Huh‐7 cells. Significant results were obtained in Huh‐7 cells. The common MTTP promoter haplotype −164T/−400A/−493G showed about two‐fold lower activity than the rare haplotype −164C/−400T/−493T. MTTP promoter mutant constructs −164T/−400A/−493T and −164T/−400T/−493T exhibited similar activity than the common haplotype. Activities of mutants −164C/−400A/−493G and −164C/−400A/−493T resembled the rare MTTP promoter haplotype. Electrophoretic mobility shift assays (EMSAs) revealed higher binding capacity of the transcriptional factor Sterol regulatory element binding protein1a (SREBP1a) to the −164T probe in comparison to the −164C probe. In conclusion, our study indicates that the polymorphism −164T>C mediates different activities of common MTTP promoter haplotypes via SREBP1a. This suggested that the already described SREBP‐dependent modulation of MTTP expression by diet is more effective in −164T than in −164C carriers. Hum Mutat 29(1), 123–129, 2008. © 2007 Wiley‐Liss, Inc.
Insecticide resistance, control failure likelihood and the First Law of Geography.

Insecticide resistance is a broadly recognized ecological backlash resulting from insecticide use and is widely reported among arthropod pest species with well-recognized underlying mechanisms and consequences. Nonetheless, insecticide resistance is the subject of evolving conceptual views that introduces a different concept useful if recognized in its own right - the risk or likelihood of control failure. Here we suggest an experimental approach to assess the likelihood of control failure of an insecticide allowing for consistent decision-making regarding management of insecticide resistance. We also challenge the current emphasis on limited spatial sampling of arthropod populations for resistance diagnosis in favor of comprehensive spatial sampling. This necessarily requires larger population sampling - aiming to use spatial analysis in area-wide surveys - to recognize focal points of insecticide resistance and/or control failure that will better direct management efforts. The continuous geographical scale of such surveys will depend on the arthropod pest species, the pattern of insecticide use and many other potential factors. Regardless, distance dependence among sampling sites should still hold, following the maxim that the closer two things are, the more they resemble each other, which is the basis of Tobler's First Law of Geography. © 2016 Society of Chemical Industry.
Properties of optimum binary message-passing decoders

We consider a class of message-passing decoders for low-density parity-check (LDPC) codes whose messages are binary valued. We prove that if the channel is symmetric and all codewords are equally likely to be transmitted, an optimum decoding rule (in the sense of minimizing message error rate) should satisfy certain symmetry and isotropy conditions. Using this result, we prove that Gallager's Algorithm B achieves the optimum decoding threshold among all binary message-passing decoding algorithms for regular codes. For irregular codes, we argue that when the nodes of the message-passing decoder do not exploit knowledge of their decoding neighborhood, optimality of Gallager's Algorithm B is preserved. We also consider the problem of designing irregular LDPC codes and find a bound on the achievable rates with Gallager's Algorithm B. Using this bound, we study the case of low error-rate channels and analytically find good degree distributions for them.
Obesity in Urban Food Markets: Evidence from Geo-referenced Micro Data

This paper provides quantitative estimates of the effect of proximity to fast food restaurants and grocery stores on obesity in urban food markets. Our empirical model combined georeferenced micro data on access to fast food restaurants and grocery stores with data about salient personal characteristics, individual behaviors, and neighborhood characteristics. We defined a "local food environment" for every individual utilizing 0.5-mile buffers around a person's home address. Local food landscapes are potentially endogenous due to spatial sorting of the population and food outlets, and the body mass index (BMI) values for individuals living close to each other are likely to be spatially correlated because of observed and unobserved individual and neighborhood effects. The potential biases associated with endogeneity and spatial correlation were handled using spatial econometric estimation techniques. Our policy simulations for Indianapolis, Indiana, focused on the importance of reducing the density of fast food restaurants or increasing access to grocery stores. We accounted for spatial heterogeneity in both the policy instruments and individual neighborhoods, and consistently found small but statistically significant effects for the hypothesized relationships between individual BMI values and the densities of fast food restaurants and grocery stores.