A novel INDEL mutation in the EDA gene resulting in a distinct X- linked hypohidrotic ectodermal dysplasia phenotype in an Italian family

A novel INDEL mutation in theEDA gene resulting in a distinctX- linked hypohidroticectoder mal dysplasia phenotypein an Italian familyEditorX-Linked Hypohidrotic Ectodermal Dysplasia (XL-HED; MIM305100) is characterized by hypodontia, misshaped teeth, hypo-hidrosis, sparse hair, peculiar facial features,1,2and occurs in lessthan 1 in every 100.000 individuals.1XL-HED is caused bymutations in the Ectodysplasin-A (EDA) gene located at Xq12-q13 with more than 100 causative mutations reported todate.1,3,4The identification of disease-causing mutations con-firms the diagnosis, however, does not automatically imply agenotype\u2013phenotype correlation

Анализ технологических параметров работы мембранных систем извлечения гелия из природного газа в процессе разработки газовых месторождений

Объектом исследования являются технологии выделения гелия из состава природного газа. Цель исследования – анализ технологических параметров работы мембранных систем выделения гелия из природного газа в процессе разработки газовых месторождений. В процессе исследования были рассмотрены существующие технологии выделения гелиевого концентрата, проанализированы основные производственные характеристики данных систем. Проведен анализ технологии мембранного выделения гелиевого концентрата и рассмотрены перспективы в использовании современных установок на основе мембранного разделения. В результате проведенного анализа был выявлен положительный эффект от внедрения модульных установок мембранного выделения гелиевого концентрата.The object of the research is technologies for the separation of helium from natural gas. The aim of the study is to analyze the technological parameters of the operation of membrane systems for the extraction of helium from natural gas during the development of gas fields. In the course of the research, the existing technologies for the separation of helium concentrate were considered, the main production characteristics of these systems were analyzed. The analysis of the technology of membrane separation of helium concentrate is carried out and the prospects for the use of modern installations based on membrane separation are considered

Systematic analysis of factors that improve homologous direct repair (HDR) efficiency in CRISPR/Cas9 technique

The CRISPR/Cas9 bacterial system has proven to be an powerful tool for genetic manipulation in several organisms, but the efficiency of sequence replacement by homologous direct repair (HDR) is substantially lower than random indel creation. Many studies focused on improving HDR efficiency using double sgRNA, cell synchronization cycle, and the delivery of single-stranded oligo DNA nucleotides (ssODN) with a rational design. In this study, we evaluate these three methods' synergistic effects to improve HDR efficiency. For our tests, we have chosen the TNF\u3b1 gene (NM_000594) for its crucial role in various biological processes and diseases. For the first time, our results showed how the use of two sgRNA with asymmetric donor design and triple transfection events dramatically increase the HDR efficiency from an undetectable HDR event to 39% of HDR efficiency and provide a new strategy to facilitate CRISPR/Cas9-mediated human genome editing. Besides, we demonstrated that the TNF\u3b1 locus could be edited with CRISPR/Cas9 methodology, an opportunity to safely correct, in the future, the specific mutations of each patient

A physics-informed machine learning framework for predictive maintenance applied to turbomachinery assets

The paper presents an overview of an analytics framework for predictive maintenance service boosted by Machine Learning and asset knowledge, applied to turbomachinery assets. Optimization of the maintenance scenario is performed through a risk model that assesses online health status and probability of failure, by detecting functional anomalies or aging phenomena and evaluating their impact on asset serviceability. Turbomachinery domain knowledge is used to create physics-based models, to configure a severity assessment layer and to properly map maintenance actions to anomaly types. The implemented analytics framework is able also to fore-cast engine behaviour over the future in order to optimize asset operation and maintenance, minimizing downtime and residual risk. Predictive cap-abilities are optimized thanks to the hybrid approach, where physics-based knowledge empowers long term prediction accuracy while data-driven analytics ensure fast-events prognostics. Accuracy of the hybrid approach improves maintenance optimization, allowing activities to be planned properly and in early advance with respect to outage execution