RNA interference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design

A

A targeted next-generation sequencing assay for the molecular diagnosis of genetic disorders with orodental involvement.

BACKGROUND: Orodental diseases include several clinically and genetically heterogeneous disorders that can present in isolation or as part of a genetic syndrome. Due to the vast number of genes implicated in these disorders, establishing a molecular diagnosis can be challenging. We aimed to develop a targeted next-generation sequencing (NGS) assay to diagnose mutations and potentially identify novel genes mutated in this group of disorders. METHODS: We designed an NGS gene panel that targets 585 known and candidate genes in orodental disease. We screened a cohort of 101 unrelated patients without a molecular diagnosis referred to the Reference Centre for Oro-Dental Manifestations of Rare Diseases, Strasbourg, France, for a variety of orodental disorders including isolated and syndromic amelogenesis imperfecta (AI), isolated and syndromic selective tooth agenesis (STHAG), isolated and syndromic dentinogenesis imperfecta, isolated dentin dysplasia, otodental dysplasia and primary failure of tooth eruption. RESULTS: We discovered 21 novel pathogenic variants and identified the causative mutation in 39 unrelated patients in known genes (overall diagnostic rate: 39%). Among the largest subcohorts of patients with isolated AI (50 unrelated patients) and isolated STHAG (21 unrelated patients), we had a definitive diagnosis in 14 (27%) and 15 cases (71%), respectively. Surprisingly, COL17A1 mutations accounted for the majority of autosomal-dominant AI cases. CONCLUSIONS: We have developed a novel targeted NGS assay for the efficient molecular diagnosis of a wide variety of orodental diseases. Furthermore, our panel will contribute to better understanding the contribution of these genes to orodental disease. TRIAL REGISTRATION NUMBERS: NCT01746121 and NCT02397824.journal articleresearch support, non-u.s. gov't2016 Feb2015 10 26importe

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Etude et regulation des genes cel d'Erwinia chrysanthemi

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

“Prediction of Sleepiness Ratings from Voice by Man and Machine”: A Perceptual Experiment Replication Study

International audienceFollowing the release of the SLEEP corpus during the Interspeech 2019 paralinguistic continuous sleepiness estimation challenge, a paper presented at Interspeech 2020 by Huckvale et al. examined the reasons for the poor performance of the models proposed for this task. Careful analyses of the corpus led to the conclusion that its bias makes it hazardous to use for training machine learning systems, but a perceptual experiment on a subset of this corpus seemed to indicate that human hearing is however able to estimate sleepiness on this corpus.In this study, we present the results of the Endymion replication study, in which the same samples were rated by thirty French-speaking naive listeners. We then discuss the causes of the differences between the two studies and examine the effect of listener and sample characteristics on annotation performance

Postsynaptic chromatin is under neural control at the neuromuscular junction

In adult skeletal muscle, the nicotinic acetylcholine receptor (AChR) specifically accumulates at the neuromuscular junction, to allow neurotransmission. This clustering is paralleled by a compartmentalization of AChR genes expression to subsynaptic nuclei, which acquire a unique gene expression program and a specific morphology in response to neural cues. Our results demonstrate that neural agrin-dependent reprogramming of myonuclei involves chromatin remodelling, histone hyperacetylation and histone hyperphosphorylation. Activation of AChR genes in subsynaptic nuclei is mediated by the transcription factor GABP. Here we demonstrate that upon activation, GABP recruits the histone acetyl transferase (HAT) p300 on the AChR ɛ subunit promoter, whereas it rather recruits the histone deacetylase HDAC1 when the promoter is not activated. Moreover, the HAT activity of p300 is required in vivo for AChR expression. GABP therefore couples chromatin hyperacetylation and AChR activation by neural factors in subsynaptic nuclei

"Prediction of sleepiness ratings from voice by man and machine" : the Endymion replication perceptual study

International audienceFollowing the release of the SLEEP corpus during the Interspeech 2019 paralinguistic continuous sleepiness estimation challenge, a paper presented at Interspeech 2020 by Huckvale et al. examined the reasons for the poor performance of the models proposed for this task. They conducted a perceptual experiment on a subset of this corpus that seems to indicate that human hearing is, however, able to estimate sleepiness in this corpus. In this study, we present the results of the Endymion replication study, in which the same samples were rated by thirty French-speaking naive listeners. We then discuss the causes of the differences between the two studies and examine the effect of listener and sample characteristics on annotation performances

Using wavelets to capture deviations from smoothness in galaxy-scale strong lenses

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a large range in spatial scale, mass scale, and morphology. In this work, we address the problem with a novel multi-scale method based on wavelets. We test our method on simulated Hubble Space Telescope imaging data of strong lenses containing different types of mass substructures making them deviate from smooth models: (1) a localized small dark matter subhalo, (2) a Gaussian random field that mimics a non-localized population of subhalos along the line of sight, (3) galaxy-scale multipoles that break elliptical symmetry. We show that wavelets are able to recover all of these structures accurately. This is made technically possible by using gradient-informed optimization based on automatic differentiation over thousands of parameters, also allowing us to sample the posterior distributions of all model parameters simultaneously. By construction, our method merges all current modeling paradigms - analytical, pixelated, and deep learning - into a single modular framework. It is also well-suited for the fast modeling of large samples of lenses. All methods presented here are publicly available in our new Herculens package