Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid and Visual Detection of Trichinella Spp. Using a Lateral Flow Strip-Based Recombinase Polymerase Amplification (LF-RPA) Assay

Trichinella spp. , are amongst the most widespread parasitic nematodes, primarily live in the muscles of a wide range of vertebrate animals and humans. Human infection occurs by ingestion of raw or undercooked meat containing Trichinella larvae. Accurate diagnosis of Trichinella spp. infection in domestic animals is crucial for the effective prevention and control of human trichinellosis. In the present study, a simple, rapid and accurate diagnostic assay was developed combining recombinase polymerase amplification and a lateral flow strip (LF-RPA) to detect Trichinella spp. infection. The LF-RPA assay targets Trichinella spp. mitochondrial small-subunit ribosomal RNA (rrnS) gene and can detect as low as 100 fg DNA of Trichinella strains, which was approximately 10 times more sensitive than a conventional PCR assay. The LF-RPA assay can be performed within 10–25 min, at a wide range of temperatures (25–45°C) and showed no cross-reactivity with DNA of other parasites and related host species of Trichinella. The performance of the LF-RPA assay in the presence of high concentration of PCR inhibitor was better than that of a conventional PCR assay. Results obtained by LF-RPA assay for the detection of experimentally infected mice were comparable to the results obtained by using a conventional PCR, achieving 100% specificity and high sensitivity. These results present the developed LF-RPA assay as a new simple, specific, sensitive, rapid and convenient method for the detection of Trichinella infection in domestic animals.
miR-499-5p Attenuates Mitochondrial Fission and Cell Apoptosis via p21 in Doxorubicin Cardiotoxicity

Doxorubicin (DOX) is a broad-spectrum anti-tumor drug, but its cardiotoxicity limits its clinical application. A better understanding of the molecular mechanisms underlying DOX cardiotoxicity will benefit clinical practice and remedy heart failure. Our present study observed that DOX caused cardiomyocyte (H9c2) apoptosis via the induction of abnormal mitochondrial fission. Notably, the expression levels of p21 increased in DOX-treated cardiomyocytes, and the silencing of p21 using siRNA greatly attenuated mitochondrial fission and apoptosis in cardiomyocytes. We also found that miR-499-5p could directly target p21 and attenuated DOX-induced mitochondrial fission and apoptosis. The role of the miR-499-5p-p21 axis in the prevention of DOX cardiotoxicity was also validated in the mice model. DOX treatment induced an upregulation of p21, which induced subsequent abnormal mitochondrial fission and myocardial apoptosis in mouse heart. Adenovirus-harboring miR-499-5p-overexpressing mice exhibited significantly reduced p21 expression, mitochondrial fission and myocardial apoptosis in hearts following DOX administration. The miR-499-5p-overexpressing mice also exhibited improved cardiomyocyte hypertrophy and cardiac function after DOX treatment. However, miR-499-5p was not involved in the DOX-induced apoptosis of cancer cells. Taken together, these findings reveal an emerging role of p21 in the regulation of mitochondrial fission program. miR-499-5p attenuated mitochondrial fission and DOX cardiotoxicity via the targeting of p21. These results provide new evidence for the miR-499-5p-p21 axis in the attenuation of DOX cardiotoxicity. The development of new therapeutic strategies based on the miR-499-5p-p21 axis is a promising path to overcome DOX cardiotoxicity as a chemotherapy for cancer treatment.
Identification of Serum MicroRNAs as Novel Biomarkers in Esophageal Squamous Cell Carcinoma Using Feature Selection Algorithms

Introduction: Circulating microRNAs (miRNAs) are promising molecular biomarkers for the early detection of esophageal squamous cell carcinoma (ESCC). We investigated the serum miRNA expression profiles from microarray-based technologies and evaluated the diagnostic value of serum miRNAs as potential biomarkers for ESCC by using feature selection algorithms. Methods: Serum miRNA expression profiles were obtained from 52 ESCC patients and 52 age- and sex-matched controls via performing a high-throughput microarray assay. Five representative feature selection algorithms including the false discovery rate procedure, family-wise error rate procedure, Lasso logistic regression, hybrid huberized support vector machine (SVM), and SVM using the squared-error loss with the elastic-net penalty were jointly carried out to select the significantly differentially expressed miRNAs based on the miRNA profiles. Results: Three miRNAs including miR-16-5p, miR-451a, and miR-574-5p were identified as the powerful biomarkers for the diagnosis of ESCC. The diagnostic accuracy of the combination of these three miRNAs was evaluated by using logistic regression and the SVM. The averages of the area under the receiver operating curve and classification accuracies based on different classifiers were more than 0.80 and 0.79, respectively. The cross-validation results suggested that the three-miRNA-based classifiers could clearly distinguish ESCC patients from healthy controls. Moreover, the classifying performance of the miRNA panel persisted in discriminating the healthy group from patients with ESCC stage I-II (AUC > 0.76) and patients with ESCC stage III-IV (AUC > 0.80). Conclusions: These results in this study have moved forward the identification of novel biomarkers for the diagnosis of ESCC.
A fuzzy block replacement algorithm for disk caches

In this paper, we present a new block replacement algorithm for disk caches. Our Fuzzy Block Replacement Algorithm (fuzzy block-RA) utilizes nine fuzzy rules to pick out the block to be evicted when an I/O reference causes a miss on a filled up disk cache. The decision making process is based on the age of a block and the frequency at which references are made to it. Optimization of the knowledge base to specific applications is easily possible by modifying the inference rules or tuning of the membership functions. The simulations performed using our algorithm shows that the miss rate improves with a fuzzy block-RA when compared with standard algorithms. The use of disk traces gathered from a commercial disk subsystem in the simulation ensures the practical validity of the results.
Designing an Algorithm for Role Analysis

This thesis presents a system for specifying constraints on dynamically changing referencing relationships of heap objects, and an analysis for static verification of these constraints. The constraint specification system is based on the concept of role. The role of an object depends, in large part, on its aliasing relationships with other objects, with the role of each object changing as its aliasing relationships change. In this way roles capture object and data structure properties such as unique references, membership of objects in data structures, disjointness of data structures, absence of representation exposure, bidirectional associations, treeness, and absence or presence of cycles in the heap. Roles generalize linear types by allowing multiple aliases of heap objects that participate in recursive data structures. Unlike graph grammars and graph types, roles contain sufficiently general constraints to conservatively approximate any data structure. We give a semantics for mutually recursive role definitions and derive properties of roles as an invariant specification language. We introduce a programming model that allows temporary violations of role constraints. We describe a static role analysis for verifying that a program conforms to the programming model. The analysis uses fixpoint computation to synthesize loop invariants in each procedure. We introduce a procedure interface specification language and its semantics. We present an interprocedural, compositional, and context-sensitive role analysis that verifies that a program respects the role constraints across procedure calls. Thesis Supervisor: Martin C. Rinard Title: Associate Professor
[Prevalence and factors associated with overweight and obesity in Peruvian primary school children].

OBJECTIVES To determine the prevalence and factors associated with overweight and obesity in Peruvian schoolchildren. MATERIALS AND METHODS Cross-sectional study carried out between 2013 and 2014. The probabilistic, multistage stratified sampling included 1 191 conglomerates with 7 914 dwellings (4 842 in the urban area and 3 072 in the rural area) of Peru. A total of 2 801 schoolchildren aged between 5 and 13 years were evaluated. The Z score of the body mass index by age (ZBMI) was used according to the WHO. Overweight was considered (ZBMI> 1 and ≤2) and obesity (ZBMI >2). RESULTS 18.1% of the sample was overweight and 14.1% were obese. Overweight predominated in males (18.7%), schoolchildren aged 8 to 10 years (19.6%), non-poor (21.2%), residing in the urban area (21.6%), from Metropolitan Lima (22.8%) and Costa (22.7%). The factors associated with overweight included non-poverty (OR=1.9), living in urban areas (OR=1.7), Metropolitan Lima (OR=1.9) and Costa (OR=1.6). On the other hand, factors associated with obesity included male sex (OR=3.1), secondary education level of the head of the household (OR=1.8), higher education (OR=2.5), non-poor (OR=9.2), residing in an urban area (OR=3.4), Metropolitan Lima (OR=4.8) and Costa (OR=2.9). CONCLUSIONS The prevalence of obesity or overweight in schoolchildren is high. Non-poverty, living in urban areas, Metropolitan Lima and Costa are associated with overweight. Being a man, non-poor, the highest educational level of the head of the household, living in the urban area, Metropolitan Lima and Costa were associated with obesity.
Placing genocide in context: research priorities for the Rwandan genocide

Prior to 1994, the country of Rwanda was little known outside the limited circle of African studies scholars. A reference in conversation to Rwanda, a small, landlocked country with few natural resources and no strategic importance, was likely to be met with blank stares. The 1994 genocide, however, has bestowed on Rwanda a new notoriety. The extensive press coverage of the genocide and its brutalities, and especially the television coverage of millions of refugees fleeing across the borders, brought Rwanda to the consciousness of much of the world, making it synonymous with violence and disaster. This notoriety has attracted the attention of numerous journalists and other researchers, but unfortunately, not all of the numerous texts on Rwanda that have appeared since the genocide add substantially to one’s understanding of the country and the terrible tragedy that has taken place there. Few of the texts are based on rigorous empirical research. Many of them rely overwhelmingly on secondary sources, peppered with a smattering of impressionistic accounts and a small number of original interviews. Many of the recent rash of publications simply rehash myths and inaccuracies from earlier accounts of Rwanda that have long been disproved, serving more to obfuscate than to clarify the situation. At the same time, some excellent scholarship is slowly appearing. Despite its international obscurity, Rwanda was long a welcoming place for scholars—easy to navigate because of its small size and good roads, with a temperate climate and a government that placed few restrictions on researchers. As a result, a rich body of scholarship on Rwanda has appeared over the last several decades. Among the numerous publications that have appeared on Rwanda since the genocide, a small number follow in this tradition of fine scholarship, drawing on extensive original research. A series of promising empirical studies are currently being carried out, mostly by PhD students. Yet much remains to be explored. The genocide was a complex and catastrophic event that cannot be explained with simplistic accounts. This article will review literature of interest to those seeking to understand the
A Review of Cardiovascular Disease and Treatment Differences in Women

Cardiovascular disease (CVD) is a significant health care problem in the United States today. Women comprise an increasing component of the population affected by this disease. Recent reports have suggested that women are not enrolled in adequate numbers in major clinical studies and, furthermore, are less likely to receive treatment as recommended by evidence-based medicine guidelines. Historical differences in the investigation and treatment of cardiovascular disease between women and men are discussed. Reasons for differences in study enrollment of women are proposed. Efforts by the Food and Drug Administration to improve data collection in women are outlined. The influence of major risk factors, including smoking, hyperlipidemia, and hypertension, on development and progression of CVD is addressed. Major trials of CVD and heart failure are examined. An assessment of progress toward a goal of gender treatment equality is made.
A high-performance architecture for an RLS-like eigenvector algorithm

We present a high-performance realization of the PAST algorithm for tracking the largest eigenvector of a correlation matrix. Delayed updating is applied to generate the necessary latches for pipelining. A step size approximation scheme is adopted to replace the division operation normally required by the algorithm. The resulting architecture is simulated and synthesized to assess its validity and efficiency.
Structural adaptations of photosynthetic complex I enable ferredoxin-dependent electron transfer

Plugging into the pump Photosynthetic organisms use light to fix carbon dioxide in a process that requires both chemical reducing equivalents and adenosine triphosphate (ATP). Balancing the ratio of these inputs is accomplished by a short circuit in electron flow through photosynthetic complex I, a proton pump that contributes to ATP production but does not increase net reducing equivalents in the cell. Schuller et al. solved a cryo–electron microscopy structure of photosynthetic complex I (see the Perspective by Brandt) and went on to reconstitute electron transfer using the electron carrier protein ferredoxin. Science, this issue p. 257; see also p. 230 A proton-pumping machine in photosynthesis uses the common electron carrier ferredoxin. Photosynthetic complex I enables cyclic electron flow around photosystem I, a regulatory mechanism for photosynthetic energy conversion. We report a 3.3-angstrom-resolution cryo–electron microscopy structure of photosynthetic complex I from the cyanobacterium Thermosynechococcus elongatus. The model reveals structural adaptations that facilitate binding and electron transfer from the photosynthetic electron carrier ferredoxin. By mimicking cyclic electron flow with isolated components in vitro, we demonstrate that ferredoxin directly mediates electron transfer between photosystem I and complex I, instead of using intermediates such as NADPH (the reduced form of nicotinamide adenine dinucleotide phosphate). A large rate constant for association of ferredoxin to complex I indicates efficient recognition, with the protein subunit NdhS being the key component in this process.
Targeting hepatic glucokinase to treat diabetes with TTP399, a hepatoselective glucokinase activator

A hepatoselective glucokinase activator reduced hyperglycemia without hypoglycemia or adverse effects on lipids, liver enzymes, or blood pressure. Diabetes drug homing in on the liver Although glucokinase is a known therapeutic target in type 2 diabetes, previous attempts to activate it have not been clinically successful because of side effects and limited efficacy. To improve the effectiveness of the treatment while minimizing adverse reactions such as hypoglycemia, Vella et al. designed a hepatoselective activator of glucokinase for oral treatment. They tested this activator in rats and in minipigs and then ran a clinical trial with it in human patients, showing evidence of both efficacy and safety. The therapeutic success of interventions targeting glucokinase (GK) activation for the treatment of type 2 diabetes has been limited by hypoglycemia, steatohepatitis, and loss of efficacy over time. The clinical characteristics of patients with GK-activating mutations or GK regulatory protein (GKRP) loss-of-function mutations suggest that a hepatoselective GK activator (GKA) that does not activate GK in β cells or affect the GK-GKRP interaction may reduce hyperglycemia in patients with type 2 diabetes while limiting hypoglycemia and liver-associated adverse effects. Here, we review the rationale for TTP399, an oral hepatoselective GKA, and its progression from preclinical to clinical development, with an emphasis on the results of a randomized, double-blind, placebo- and active-controlled phase 2 study of TTP399 in patients with type 2 diabetes. In this 6-month study, TTP399 (800 mg/day) was associated with a clinically significant and sustained reduction in glycated hemoglobin, with a placebo-subtracted least squares mean HbA1c change from baseline of −0.9% (P < 0.01). Compared to placebo, TTP399 (800 mg/day) also increased high-density lipoprotein cholesterol (3.2 mg/dl; P < 0.05), decreased fasting plasma glucagon (−20 pg/ml; P < 0.05), and decreased weight in patients weighing ≥100 kg (−3.4 kg; P < 0.05). TTP399 did not cause hypoglycemia, had no detrimental effect on plasma lipids or liver enzymes, and did not increase blood pressure, highlighting the importance of tissue selectivity and preservation of physiological regulation when targeting key metabolic regulators such as GK.
Cadherin-11–mediated adhesion of macrophages to myofibroblasts establishes a profibrotic niche of active TGF-β

Adhesion with macrophages promotes the activation of fibroblasts into myofibroblasts and creates a self-sustaining profibrotic niche. Macrophage-myofibroblast adhesion creates a profibrotic niche The reversible activation of fibroblasts into extracellular matrix–secreting myofibroblasts is a consequence of inflammation and is critical for wound healing and tissue repair; however, persistent myofibroblast activity causes fibrosis. Inflammatory macrophages produce transforming growth factor–β (TGF-β), a cytokine that induces the fibroblast-to-myofibroblast transition. Lodyga et al. found that the adhesion protein cadherin-11 (CDH11) was enriched at points of contact between macrophages and myofibroblasts in fibrotic lung tissues from mice and human patients. Cdh11-mediated adhesion between primary mouse macrophages and lung fibroblasts promoted the activation of fibroblasts into myofibroblasts and supported myofibroblast activity by acting as a local source of latent TGF-β that was activated by the myofibroblasts. Thus, Cdh11-mediated adhesion prolongs and targets the delivery of macrophage-produced TGF-β to myofibroblasts, creating a self-sustaining profibrotic niche. Macrophages contribute to the activation of fibroblastic cells into myofibroblasts, which secrete collagen and contract the collagen matrix to acutely repair injured tissue. Persistent myofibroblast activation leads to the accumulation of fibrotic scar tissue that impairs organ function. We investigated the key processes that turn acute beneficial repair into destructive progressive fibrosis. We showed that homotypic cadherin-11 interactions promoted the specific binding of macrophages to and persistent activation of profibrotic myofibroblasts. Cadherin-11 was highly abundant at contacts between macrophages and myofibroblasts in mouse and human fibrotic lung tissues. In attachment assays, cadherin-11 junctions mediated specific recognition and strong adhesion between macrophages and myofibroblasts. One functional outcome of cadherin-11–mediated adhesion was locally restricted activation of latent transforming growth factor–β (TGF-β) between macrophage-myofibroblast pairs that was not observed in cocultures of macrophages and myofibroblasts that were not in contact with one another. Our data suggest that cadherin-11 junctions maintain latent TGF-β–producing macrophages and TGF-β–activating myofibroblasts in close proximity to one another. Inhibition of homotypic cadherin-11 interactions could be used to cause macrophage-myofibroblast separation, thereby destabilizing the profibrotic niche.
Performance Estimation for Face Recognition Using SVD

This paper is presented here for applied theory of linear algebra called"singular value decomposition (SVD)" to digital image processing. Two specific areas of digital image processing are investigated and tested. One is digital image compression, and other is face recognition. In this paper we are measuring the FAR & FRR at different Threshold Level using Singular Value Decomposition by LDA in Own Database. SVD method can transform matrix a into product USV T , which allows us to refactoring a digital image in three matrices. The using of singular values of such refactoring allows us to represent the image with a smaller set of values, which can preserve useful features of the original image, but use less storage space in the memory. To perform face recognition with SVD, we treated the set of Training faces as vectors in a subspace, called "face space", spanned by a small group of "base faces". The projection of a new image onto the base face is then compared to the set of known faces to identify the face. All tests and experiments are carried using MATLAB as computing environment and programming language.
Learning to Fuse Multiscale Features for Visual Place Recognition

Efficient and robust visual place recognition is of great importance to autonomous mobile robots. Recent work has shown that features learned from convolutional neural networks achieve impressed performance with efficient feature size, where most of them are pooled or aggregated from a convolutional feature map. However, convolutional filters only capture the appearance of their perceptive fields, which lack the considerations on how to combine the multiscale appearance for place recognition. In this paper, we propose a novel method to build a multiscale feature pyramid and present two approaches to use the pyramid to augment the place recognition capability. The first approach fuses the pyramid to obtain a new feature map, which has an awareness of both the local and semi-global appearance, and the second approach learns an attention model from the feature pyramid to weight the spatial grids on the original feature map. Both approaches combine the multiscale features in the pyramid to suppress the confusing local features while tackling the problem in two different ways. Extensive experiments have been conducted on benchmark datasets with varying degrees of appearance and viewpoint variations. The results show that the proposed approaches achieve superior performance over the networks without the multiscale feature fusion and the multiscale attention components. Analyses on the performance of using different feature pyramids are also provided.
Framework of Semantic Web Service Discovery Based on Fuzzy Logic and Multi-phase Matching ⋆

Web service discovery has become increasingly more important as the prevailing use of web service. According to the inadequateness of current discovery methods to deal with the vague information of web service, a framework of semantic web service discovery based on fuzzy logic and multi-phase matching is proposed in this paper, which exploits domain ontology, fuzzy logic and linguistic variable to present web service capability and vague information in formal description and implements approximately reasoning. Firstly, an abstract level-based service description model is given to describe web service information. Then, multi-phase matching process, including two-stage filtering and two-level matching, is detailed expressed. A case study is conducted to describe the process details of the proposed method, and the results show that it can manage web service vague information and improve the efficiency of web service discovery.