Downstream scour of combined flow over weirs and below gates

River morphodynamics and sediment transportSediment-structure interactio

A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders

Publicado en Lecture Notes in Computer Science.The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with. With the main aim of fitting the more appropriate treatments, current personalized medicine focuses on using data from heterogeneous sources to estimate the evolu- tion of a given disease for the particular case of a certain patient. In recent years, next-generation sequencing data have boosted cancer prediction by supplying gene-expression information that has allowed diverse machine learning algorithms to supply valuable solutions to the problem of cancer subtype classification, which has surely contributed to better estimation of patient’s response to diverse treatments. However, the efficacy of these models is seriously affected by the existing imbalance between the high dimensionality of the gene expression feature sets and the number of sam- ples available for a particular cancer type. To counteract what is known as the curse of dimensionality, feature selection and extraction methods have been traditionally applied to reduce the number of input variables present in gene expression datasets. Although these techniques work by scaling down the input feature space, the prediction performance of tradi- tional machine learning pipelines using these feature reduction strategies remains moderate. In this work, we propose the use of the Pan-Cancer dataset to pre-train deep autoencoder architectures on a subset com- posed of thousands of gene expression samples of very diverse tumor types. The resulting architectures are subsequently fine-tuned on a col- lection of specific breast cancer samples. This transfer-learning approach aims at combining supervised and unsupervised deep learning models with traditional machine learning classification algorithms to tackle the problem of breast tumor intrinsic-subtype classification.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

DprE2 is a molecular target of the anti-tubercular nitroimidazole compounds pretomanid and delamanid

Abstract Mycobacterium tuberculosis is one of the global leading causes of death due to a single infectious agent. Pretomanid and delamanid are new antitubercular agents that have progressed through the drug discovery pipeline. These compounds are bicyclic nitroimidazoles that act as pro-drugs, requiring activation by a mycobacterial enzyme; however, the precise mechanisms of action of the active metabolite(s) are unclear. Here, we identify a molecular target of activated pretomanid and delamanid: the DprE2 subunit of decaprenylphosphoribose-2’-epimerase, an enzyme required for the synthesis of cell wall arabinogalactan. We also provide evidence for an NAD-adduct as the active metabolite of pretomanid. Our results highlight DprE2 as a potential antimycobacterial target and provide a foundation for future exploration into the active metabolites and clinical development of pretomanid and delamanid

Development of NMR and thermal shift assays for the evaluation of Mycobacterium tuberculosis isocitrate lyase inhibitors.

The enzymes isocitrate lyase (ICL) isoforms 1 and 2 are essential for Mycobacterium tuberculosis survival within macrophages during latent tuberculosis (TB). As such, ICLs are attractive therapeutic targets for the treatment of tuberculosis. However, there are few biophysical assays that are available for accurate kinetic and inhibition studies of ICL in vitro. Herein we report the development of a combined NMR spectroscopy and thermal shift assay to study ICL inhibitors for both screening and inhibition constant (IC50) measurement. Operating this new assay in tandem with virtual high-throughput screening has led to the discovery of several new ICL1 inhibitors

Performance comparison of machine learning techniques in sleep scoring based on wavelet features and neighboring component analysis

Introduction: Sleep scoring is an important step in the treatment of sleep disorders. Manual annotation of sleep stages is time-consuming and experience-relevant and, therefore, needs to be done using machine learning techniques. Methods: Sleep-EDF polysomnography was used in this study as a dataset. Support vector machines and artificial neural network performance were compared in sleep scoring using wavelet tree features and neighborhood component analysis. Results: Neighboring component analysis as a combination of linear and non-linear feature selection method had a substantial role in feature dimension reduction. Artificial neural network and support vector machine achieved 90.30 and 89.93 accuracy, respectively. Discussion and Conclusion: Similar to the state of the art performance, the introduced method in the present study achieved an acceptable performance in sleep scoring. Furthermore, its performance can be enhanced using a technique combined with other techniques in feature generation and dimension reduction. It is hoped that, in the future, intelligent techniques can be used in the process of diagnosing and treating sleep disorders. © 2018 Alizadeh Savareh et al

NK cells armed with chimeric antigen receptors (CAR): roadblocks to successful development

In recent years, cell-based immunotherapies have demonstrated promising results in the treatment of cancer. Chimeric antigen receptors (CARs) arm effector cells with a weapon for targeting tumor antigens, licensing engineered cells to recognize and kill cancer cells. The quality of the CAR-antigen interaction strongly depends on the selected tumor antigen and its expression density on cancer cells. CD19 CAR-engineered T cells approved by the Food and Drug Administration have been most frequently applied in the treatment of hematological malignancies. Clinical challenges in their application primarily include cytokine release syndrome, neurological symptoms, severe inflammatory responses, and/or other off-target effects most likely mediated by cytotoxic T cells. As a consequence, there remains a significant medical need for more potent technology platforms leveraging cell-based approaches with enhanced safety profiles. A promising population that has been advanced is the natural killer (NK) cell, which can also be engineered with CARs. NK cells which belong to the innate arm of the immune system recognize and kill virally infected cells as well as (stressed) cancer cells in a major histocompatibility complex I independent manner. NK cells play an important role in the host’s immune defense against cancer due to their specialized lytic mechanisms which include death receptor (i.e., Fas)/death receptor ligand (i.e., Fas ligand) and granzyme B/perforin-mediated apoptosis, and antibody-dependent cellular cytotoxicity, as well as their immunoregulatory potential via cytokine/chemokine release. To develop and implement a highly effective CAR NK cell-based therapy with low side effects, the following three principles which are specifically addressed in this review have to be considered: unique target selection, well-designed CAR, and optimized gene delivery

Correction to: Destructive Roles of Fibroblast-Like Synoviocytes in Chronic Inflammation and Joint Damage in Rheumatoid Arthritis (Inflammation, (2021), 44, 2, (466-479), 10.1007/s10753-020-01371-1)

Following the publication of the original article, the corresponding author noticed that the second corresponding author has not been mentioned. The below statement must be added to the correspondence section: Jafar Karami; Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. E-mail: [email protected]; [email protected] The original article has been corrected. © 2020, Springer Science+Business Media, LLC, part of Springer Nature

An evaluation model for the implementation of hospital information system in public hospitals using multi-criteria-decision-making (MCDM) approaches

Background: Hospital Information System (HIS) is implemented to provide high-quality patient care. The aim of this study is to identify significant dimensional factors that influence the hospital decision in adopting the HIS. Methods: This study designs the initial integrated model by taking the three main dimensions in adopting HIS technology. Accordingly, DEMATEL was utilized to test the strength of interdependencies among the dimensions and variables. Then ANP approach is adapted to determining how the factors are weighted and prioritized by professionals and main users working in the Iranian public hospitals, in-volved with the HIS system. Results: The results indicated that "Perceived Technical Competence" is a key factor in the Human dimension. The respondents also believed that "Relative Advantage," "Compatibility" and "Security Concern" of Technology dimension should be further assessed in relation to other factors. With respect to Organization dimension, "Top Management Support" and "Vendor Support" are considered more important than others. Conclusion: Applying the TOE and HOT-fit models as the pillar of our developed model with significant findings add to the growing literature on the factors associated with the adoption of HIS and also shed some light for managers of public hospitals in Iran to success-fully adopt the HIS

Mutations in NKX6-2 Cause Progressive Spastic Ataxia and Hypomyelination

Progressive limb spasticity and cerebellar ataxia are frequently found together in clinical practice and form a heterogeneous group of degenerative disorders that are classified either as pure spastic ataxia or as complex spastic ataxia with additional neurological signs. Inheritance is either autosomal dominant or autosomal recessive. Hypomyelinating features on MRI are sometimes seen with spastic ataxia, but this is usually mild in adults and severe and life limiting in children. We report seven individuals with an early-onset spastic-ataxia phenotype. The individuals come from three families of different ethnic backgrounds. Affected members of two families had childhood onset disease with very slow progression. They are still alive in their 30s and 40s and show predominant ataxia and cerebellar atrophy features on imaging. Affected members of the third family had a similar but earlier-onset presentation associated with brain hypomyelination. Using a combination of homozygozity mapping and exome sequencing, we mapped this phenotype to deleterious nonsense or homeobox domain missense mutations in NKX6-2. NKX6-2 encodes a transcriptional repressor with early high general and late focused CNS expression. Deficiency of its mouse ortholog results in widespread hypomyelination in the brain and optic nerve, as well as in poor motor coordination in a pattern consistent with the observed human phenotype. In-silico analysis of human brain expression and network data provides evidence that NKX6-2 is involved in oligodendrocyte maturation and might act within the same pathways of genes already associated with central hypomyelination. Our results support a non-redundant developmental role of NKX6-2 in humans and imply that NKX6-2 mutations should be considered in the differential diagnosis of spastic ataxia and hypomyelination.Fil: Chelban, Viorica. University College London; Estados Unidos. Institute of Emergency Medicine; MoldaviaFil: Patel, Nisha. King Faisal Specialist Hospital and Research Center; Arabia SauditaFil: Vandrovcova, Jana. University College London; Estados UnidosFil: Zanetti, Maria Natalia. University College London; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Lynch, David S.. University College London; Estados UnidosFil: Ryten, Mina. University College London; Estados Unidos. King’s College London; Reino UnidoFil: Botía, Juan A.. University College London; Estados Unidos. Universidad de Murcia; EspañaFil: Bello, Oscar Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. University College London; Estados UnidosFil: Tribollet, Eloise. University College London; Estados UnidosFil: Efthymiou, Stephanie. University College London; Estados UnidosFil: Davagnanam, Indran. University College London; Estados UnidosFil: Bashiri, Fahad A.. King Saud University; Arabia SauditaFil: Wood, Nicholas W.. University College London; Estados Unidos. The National Hospital for Neurology and Neurosurgery; Reino UnidoFil: Rothman, James E.. University of Yale. School of Medicine; Estados Unidos. University College London; Estados UnidosFil: Alkuraya, Fowzan S.. King Faisal Specialist Hospital and Research Center; Arabia Saudita. Alfaisal University; Arabia Saudita. King Abdulaziz City for Science and Technology; Arabia SauditaFil: Houlden, Henry. The National Hospital for Neurology and Neurosurgery; Reino Unido. University College London; Estados Unido

Risk factor investigation for cardiovascular health through WHO STEPS approach in Ardabil, Iran

Objectives: Reliable evidence is the keystone for any noncommunicable disease (NCD) prevention plan to be initiated. In this study we carried out a risk factor investigation based on the WHO Stepwise approach to Surveillance (STEPS). Methods: The study was conducted on 1000 adults between 15 and 64 years of age living in Ardabil province, north-west Iran during 2006, based on the WHO STEPS approach to surveillance of risk factors for NCD. At this stage only the first and second steps were carried out. Data were collected through standard questionnaires and methods analyzed using STATA version 8 statistical software package. Results: 29.0% of men and 2.6% of women were current daily tobacco smokers. The mean number of manufactured cigarettes smoked per day was 18.9 among current daily smokers. Smoking was most prevalent among men of low-income families and those of lower education The mean body mass index (BMI) was 26.6 kg/m2, and was significantly correlated with systolic blood pressure. 58.9% were overweight or obese; 18.0% had raised blood pressure and 3.7% had isolated systolic hypertension. The mean number of servings of fruit consumed per day was 1.1; 33.1% had low levels of activity. Combined risk factor analysis showed that 4.1%of participants were in the low-risk group (up to 5.1% among men and 3.2% among women).Those in the high-risk group comprised 25.6% in the 25- to 44-year age group and 49.7%in the 45- to 64-year age group. Mean BMI increased by age in both sexes at least at the firstthree decades of adult life. Conclusion: Based on observed status of risk for cardiovascular health, burden of cardiovascular diseases is expected to increase if an effective prevention strategy is not undertaken