ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Retrograde urethrogram - a novel approach to diagnosing a posterior urethral polyp in a neonate

We present a case of antenatally detected fetal megacystis caused by an obstructing posterior urethral polyp. Antenatal and postnatal ultrasounds showed bladder wall thickening and bilateral hydroureteronephrosis, most marked antenatally. A working diagnosis of posterior urethral valves was therefore made. However, further postnatal assessment with a micturating cystourethrogram (MCUG) combined with a retrograde urethrogram identified a pedunculated urethral polyp as the cause. The addition of a retrograde urethrogram as an adjunct to the MCUG in the diagnosis of posterior urethral polyp has not previously been reported, and in this case provided diagnostic confidence of this rare condition, allowing for definitive surgical planning.
Social isolation induces succinate dehydrogenase dysfunction in anxious mice

We have previously reported social isolation induces anxiety-like behavior, cognitive decline, and reduction in brain ATP levels in mice. These changes were ameliorated by treatment with dihydromyricetin (DHM), a compound that positively modulates γ-aminobutyric A (GABAA) receptor. To gain further insight into the subcellular mechanisms underlying these changes, we utilized a social isolation-induced anxiety mouse model and investigated changes in mitochondrial oxidative capacity via the electron transport chain. We found that 4 weeks of social isolation decreased ATP levels by 43% and succinate dehydrogenase capacity by 52% of the control, while daily DHM (2 mg/kg oral) administration restored succinate dehydrogenase capacity. These results suggest that social isolation decreased mitochondrial capacity to generate ATP. DHM can be developed to be a therapeutic against anxiety and mitochondrial stress.
Compressed Holistic ConvNet Representations for Detecting Loop Closures in Dynamic Environments

Detecting loop closures in dynamic environments is a severe challenge for the simultaneous localization and mapping (SLAM) system. Convolutional neural networks (ConvNet) could provide high-level and abstract representations extracted directly from images as image descriptors. Some novel ConvNet-based methods have been presented. In dynamic environments, they perform better than the state-of-the-art methods which use hand-crafted features. In this paper, (1) We proposed a flexible loop closure detection workflow based on the holistic representations; (2) In this workflow, a post-processing method is applied to the raw holistic ConvNet representations for redundant information compression; (3) In addition, a compression ratio is introduced in (2) to determine how much information will be retained depending on background change and moving objects. We evaluated our workflow in four open datasets. The experimental results demonstrate that the proposed workflow performs better than many state-of-the-art methods and ConvNet-based approaches.
Teaching of practice innovation of new media interactive for art design training in college

The traditional education and teaching methods have limitations in professional talent training. With the rapid development of science and technology, the new media environment based on digital technology and featuring strong interactive communication and influence provides new ideas and paths for the cultivation of artistic design talents in colleges and universities. This study puts forward the innovation of the new media interactive teaching concept and mode in the process of training innovation in practice, through the analysis of the new media environment education in colleges and universities teaching use present situation and problem of university art and design professional talent training, the use of new media interactive and immediacy, mass and participatory, multimedia and hypertext, individual and social characteristics, puts forward the innovation of the new media interactive teaching concept and mode in the process of training innovation in practice. This research plays an important role in promoting the quality of art and design talents training in colleges and universities.
MiR-493-5p inhibits Th9 cell differentiation in allergic asthma by targeting FOXO1

The role of micro RNAs (miRNAs) in asthma remains unclear. In this study, we examined the role of miRNA in targeting FOXO1 in asthma. Results showed that miR-493-5p was one of the differentially expressed miRNAs in the PBMCs of asthmatic children, and was also associated with Th cell differentiation. The miR-493-5p expression decreased significantly in the OVA-induced asthma mice than the control groups. The miR-493-5p mimic inhibited the expression of the IL-9, IRF4 and FOXO1, while the inhibitor restored these effects. Moreover, the Dual-Luciferase analysis results showed FOXO1 as a novel valid target of miR-493-5p. According to the rescue experiment, miR-493-5p inhibited Th9 cell differentiation by targeting FOXO1. Then the exosomes in association with the pathogenesis of asthma was identified. Various inflammatory cells implicated in asthmatic processes including B and T lymphocytes, DCs, mast cells, and epithelial cells can release exosomes. Our results demonstrated that the DC-derived exosomes can inhibit Th9 cell differentiation through miR-493-5p, thus DC-derived exosomal miR-493-5p/FOXO1/Th9 may serve as a potential therapeutic target in the development of asthma.
Scaling and optimization of MOS optical modulators in nanometer SOI waveguides

In this paper, a very accurate model of optical modulators in silicon-on-insulator technology is developed and validated using experimental results reported in literature. Using an optimized nanometer MOS structure, a significant bandwidth increase (around 45%), length decrease (around four times), and power consumption reduction (three times) with respect to the state-of-the-art have been obtained.
Prospective Metabolomic Studies in Precision Medicine: The AKRIBEA Project

For a long time, conventional medicine has analysed biomolecules to diagnose diseases. Yet, this approach has proven valid only for a limited number of metabolites and often through a bijective relationship with the disease (i.e. glucose relationship with diabetes), ultimately offering incomplete diagnostic value. Nowadays, precision medicine emerges as an option to improve the prevention and/or treatment of numerous pathologies, focusing on the molecular mechanisms, acting in a patient-specific dimension, and leveraging multiple contributing factors such as genetic, environmental, or lifestyle. Metabolomics grasps the required subcellular complexity while being sensitive to all these factors, which results in a most suitable technique for precision medicine. The aim of this chapter is to describe how NMR-based metabolomics can be integrated in the design of a precision medicine strategy, using the Precision Medicine Initiative of the Basque Country (the AKRIBEA project) as a case study. To that end, we will illustrate the procedures to be followed when conducting an NMR-based metabolomics study with a large cohort of individuals, emphasizing the critical points. The chapter will conclude with the discussion of some relevant biomedical applications.
Exosomes derived from bone marrow mesenchymal stem cells inhibit human aortic vascular smooth muscle cells calcification via the miR-15a/15b/16/NFATc3/OCN axis

Cardiovascular events among patients with chronic kidney disease (CKD) are associated with vascular calcification (VC). Nevertheless, the process of vascular calcification is complicated. A mechanism of VC is cellular osteogenic transdifferentiation. The mechanism through which bone marrow mesenchymal stem cell-derived exosomes (BMSC-Exo) relieve VC is unknown. For the purpose of this study, we used human aortic vascular smooth muscle cells (HA-VSMCs) stimulated by high phosphate to investigate how BMSC-Exo works. Cell calcification was detected by Alizarin red S staining, AKP activity analysis, and the Ca2+ concentration test. The dual-luciferase reporter gene assays were utilized to confirm the targeting link between miR-15a-5p, miR-15b-5p, and miR-16-5p (miR-15a/15b/16) and nuclear factors of activated T cells 3 (NFATc3). The expression of osteogenic transdifferentiation biomarkers was detected using Western blot and RT-qPCR. Based on our findings, miR-15a/15b/16 plays a crucial role in BMSC-Exo's inhibitory effects on calcification and osteogenic transdifferentiation. We then confirmed that miR-15a/15b/16 specifically target the 3'UTR of NFATc3 mRNA and that three miRNAs are more effective than one miRNA. Moreover, we found that down-regulation of NFATc3 could inhibit osteocalcin (OCN) expression, thereby inhibiting the osteogenic transdifferentiation and calcification of HA-VSMCs. This study found that BMSC-Exo plays a role in calcification inhibition by transferring miR-15a/15b/16 and inhibiting their common target gene NFATc3, which down-regulates OCN expression and thus inhibits HA-VSMC osteogenic transdifferentiation. This study identifies a novel target for therapeutic therapy of CKD-VC.
Optimal Index Assignment for Multiple Description Scalar Quantization With Translated Lattice Codebooks

We design a K-description scalar quantizer, whose construction is based on a structure of translated scalar lattices and a lattice in K-1 dimensional space. The use of translated lattices provides a performance advantage by exploiting a so-called staggering gain. The use of the K-1 dimensional lattice facilitates analytic insight into the performance and significantly speeds up the computation of the index assignment compared to state-of-the-art methods. Using a common decoding method, the proposed index assignment is proven to be optimal for the K-description case. It is shown that the optimal index assignment is not unique. This is illustrated for the two-description case, where a periodic index assignment is selected from possible optimal assignments and described in detail. The performance of the proposed quantizer accurately matches theoretic analysis over the full range of operational redundancies. Moreover, the quantizer outperforms the state-of-the-art MD scheme as the redundancy among the description increases.
Differing associations between sex determination and sex-linked inversions in two ecotypes of Littorina saxatilis

Sexual antagonism is a common hypothesis for driving the evolution of sex chromosomes, whereby recombination suppression is favored between sexually antagonistic loci and the sex-determining locus to maintain beneficial combinations of alleles. This results in the formation of a sex-determining region. Chromosomal inversions may contribute to recombination suppression but their precise role in sex chromosome evolution remains unclear. Because local adaptation is frequently facilitated through the suppression of recombination between adaptive loci by chromosomal inversions, there is potential for inversions that cover sex-determining regions to be involved in local adaptation as well, particularly if habitat variation creates environment-dependent sexual antagonism. With these processes in mind, we investigated sex determination in a well-studied example of local adaptation within a species: the intertidal snail, Littorina saxatilis. Using SNP data from a Swedish hybrid zone, we find novel evidence for a female-heterogametic sex determination system that is restricted to one ecotype. Our results suggest that four putative chromosomal inversions, two previously described and two newly discovered, span the putative sex chromosome pair. We determine their differing associations with sex, which suggest distinct strata of differing ages. The same inversions are found in the second ecotype but do not show any sex association. The striking disparity in inversion-sex associations between ecotypes that are connected by gene flow across a habitat transition that is just a few meters wide indicates a difference in selective regime that has produced a distinct barrier to the spread of the newly discovered sex-determining region between ecotypes. Such sex chromosome-environment interactions have not previously been uncovered in L. saxatilis and are known in few other organisms. A combination of both sex-specific selection and divergent natural selection is required to explain these highly unusual patterns.
A Study on the Indoor Environment of the Main Building of the National Museum of Western Art, in Japan, for the Development of a Retrofit Scheme

The National Museum of Western Art is the only work of Le Corbusier in Japan and 50 years have already passed since its construction. In order to maintain the museum's value as a cultural asset, there is an urgent need to draft a thorough retrofit plan both to maintain the building's function as an art museum and to restore Le Corbusier's original design concept. This study, which carried out an indoor environmental investigation for the purpose of developing such a retrofit plan in the main building, confirms the current airflow characteristics on the basis of a survey of factors such as the flow rates of the air conditioning system, internal pressures, and the age of air distribution. Because the exhaust flow rate was greater than the supply of fresh air into the building, there was concern about air infiltration. It was found that the age of air was highest in the exhibition space, comparatively lower in the entrance hall, and lowest in the restaurant. The adjacent wall air velocities varied greatly according to the locations and the highest values were around 0.7 m/s. In order to separate the exhibition space from the entrance hall to avoid possible disturbance from outdoors, glass partitions that were not part of Le Corbusier's original design were added after the building was completed. CFD predictions were carried out to evaluate the air environment under the conditions of the original design using variable air conditioning zoning plans. Analysis indicated that if the original design were restored, using the present air conditioning zoning, there would be an increased risk of moisture condensation on the glass surface of the entrance hall. It was concluded, however, that this risk would be significantly reduced by subdividing the air conditioning zone and changing the air conditioning controls in each subdivided area.
One-Domain-One-Input: Adaptive Random Testing by Orthogonal Recursive Bisection With Restriction

One goal of software testing may be the identification or generation of a series of test cases that can detect a fault with as few test executions as possible. Motivated by insights from research into failure-causing regions of input domains, the even-spreading (even distribution) of tests across the input domain has been identified as a useful heuristic to more quickly find failures. This finding has encouraged a shift in focus from traditional random testing (RT) to its enhancement, adaptive random testing (ART), which retains the randomness of test input selection, but also attempts to maintain a more evenly distributed spread of test inputs across the input domain. Given that there are different ways to achieve the even distribution, several different ART methods and approaches have been proposed. This paper presents a new ART method, called ART by orthogonal recursive bisection (ART-ORB), which explores the advantages of repeated geometric bisection of the input domain, combined with restriction regions, to evenly spread test inputs. Experimental results show a better performance in terms of fewer test executions than RT to find failures. Compared with other ART methods, ART-ORB has comparable performance (in terms of required test executions), but incurs lower test input selection overheads, especially in higher dimensional input space. It is recommended that ART-ORB can be used in testing situations involving expensive test input execution.
New test structure to monitor contact-to-poly leakage in sub-90 nm CMOS technologies

The high leakage or even direct short between contact and gate is a serious problem after the feature sizes are shrunk to 65-nm technology and beyond. However, there is no suitable test structure to effectively monitor the leakage current between them. We have designed a new test structure which can eliminate the drawbacks of existing test structures and effectively monitor the leakage current between contact and gate electrode in state-of-the-art CMOS process technology.
Improving patch-based scene text script identification with ensembles of conjoined networks

This paper focuses on the problem of script identification in scene text images. Facing this problem with state of the art CNN classifiers is not straightforward, as they fail to address a key characteristic of scene text instances: their extremely variable aspect ratio. Instead of resizing input images to a fixed aspect ratio as in the typical use of holistic CNN classifiers, we propose here a patch-based classification framework in order to preserve discriminative parts of the image that are characteristic of its class. We describe a novel method based on the use of ensembles of conjoined networks to jointly learn discriminative stroke-parts representations and their relative importance in a patch-based classification scheme. Our experiments with this learning procedure demonstrate state-of-the-art results in two public script identification datasets. In addition, we propose a new public benchmark dataset for the evaluation of multi-lingual scene text end-to-end reading systems. Experiments done in this dataset demonstrate the key role of script identification in a complete end-to-end system that combines our script identification method with a previously published text detector and an off-the-shelf OCR engine. (C) 2017 Elsevier Ltd. All rights reserved.
Neuro-fuzzy ART-based document management system: application to mail distribution and digital libraries

A new document management system is proposed in this paper. Its kernel is based on a new set of neuro-fuzzy systems of the ART family: FasArt and RFasArt. The first one, FasArt, is used to support a simple Optical Character Recognition (OCR) that inherits fine properties of ART architectures. such as fast and incremental learning, stability and modularity. On the other hand, RFasArt is a new recurrent version of FasArt which efficiently exploits contextual information in the task of logical labeling. The proposed system is extensively tested in two real-world applications. i.e. E-mail of printed business letter and digital library of scientific papers. Experimental results show logical labeling and OCR rates over 90%. The proposed system is better compared to a previous system proposed by the group, where instead of using contextual information in an integrated way. a postprocessing Viterbi-based model was employed. (C) 2002 Elsevier Science Ltd. All rights reserved.
Fine mapping and marker development for the wheat leaf rust resistance gene Lr32

Wheat leaf rust is caused by the fungal pathogen Puccinia triticina and is one of the wheat diseases of concern globally. Among the known leaf rust resistance genes (Lr) genes, Lr32 is a broadly effective gene derived from the diploid species Aegilops tauschii coss. accession RL5497-1 and has been genetically mapped to chromosome arm 3DS. However, Lr32 resistance has not been utilized in current cultivars in part due to the lack of modern, predictive DNA markers. The goals of this study were to fine map the Lr32 region and develop SNP-based kompetitive allele-specific polymerase chain reaction markers. The genomic analysis was conducted by using doubled haploid and F2-derived mapping populations. For marker development, a 90K wheat chip array, 35K and 820K Axiom R SNPs, A. tauschii pseudomolecules v4.0 and International Wheat Genome Sequencing Consortium ReqSeq v2.1 reference genomes were used. Total 28 kompetitive allele-specific polymerase chain reaction and 2 simple sequence repeat markers were developed. The Lr32 region was fine mapped between kompetitive allele-specific polymerase chain reaction markers Kwh142 and Kwh355 that flanked 34-35 Mb of the diploid and hexaploid reference genomes. Leaf rust resistance mapped as a Mendelian trait that cosegregated with 20 markers, recombination restriction limited the further resolution of the Lr32 region. A total of 10-11 candidate genes associated with disease resistance were identified between the flanking regions on both reference genomes, with the majority belonging to the nucleotide-binding domain and leucine-rich repeat gene family. The validation analysis selected 2 kompetitive allele-specific polymerase chain reaction markers, Kwh147 and Kwh722, for marker-assisted selection. The presence of Lr32 along with other Lr genes such as Lr67 and Lr34 would increase the resistance in future wheat breeding lines and have a high impact on controlling wheat leaf rust.
Genetic factors contribute to medication-induced QT prolongation: A review

QT prolongation is a heart rhythm condition that impacts the lives of many people and when severe can be life-threatening. QT prolongation has been linked to variations in several genes, but it can also arise in the course of treatments with medications such as certain antipsychotics and antidepressants. However, it is unclear whether the risk of medication-induced QT prolongation (MIQTP) depends on specific genetic vulnerability. Here, we review the available literature on the interplay between genetic risk and medication exposure in the context of psychiatric treatment. A review was conducted on the genetic contribution to MIQTP in psychiatric patients. A literature search was conducted on the PubMed platform with 8 papers meeting criteria for review. A total of 3,838 patients from 8 studies meeting criteria for a psychotic or mood disorder were included in this review. All studies found evidence for the genetic contribution to MIQTP. The specific genes identified in these studies included the NOS1AP, ABCB1, KCNH2, SLC22A23, EPB41L4A, LEP, CACNA1C, CERKL, SLCO3A1, BRUNOL4, NRG3, NUBPL, PALLD, NDRG4 and PLN genes. The findings highlight both the importance of monitoring heart parameters in psychiatry and the possible role for genetic profiling to increase the treatment safety.
Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG) and principal component analyses are used to reduce the dimensionality of the feature vectors and linearly combine them. Subsequently, the GMM universal background model is trained by the expectation-maximization (EM) algorithm to purify the training data and reduce its size. Finally, a purified and reduced GMM-supervector is used to train the support vector machine classifier. The performance of the proposed method was evaluated for three different motor imagery datasets in terms of accuracy, kappa, mutual information, and computation time, and compared with the state-of-the-art algorithms. The results from the study indicate that the proposed method achieves high accuracy with a small amount of training data compared with the state-of-the-art algorithms in motor imagery EEG classification.