Towards Automated Design of Riboswitches

Experimental screening and selection pipelines for the discovery of novel riboswitches are expensive, time-consuming, and inefficient. Using computational methods to reduce the number of candidates for the screen could drastically decrease these costs. However, existing computational approaches do not fully satisfy all requirements for the design of such initial screening libraries. In this work, we present a new method, libLEARNA, capable of providing RNA focus libraries of diverse variable-length qualified candidates. Our novel structure-based design approach considers global properties as well as desired sequence and structure features. We demonstrate the benefits of our method by designing theophylline riboswitch libraries, following a previously published protocol, and yielding 30% more unique high-quality candidates.Comment: 9 pages, Accepted at the 2023 ICML Workshop on Computational Biolog

Rethinking Performance Measures of RNA Secondary Structure Problems

Accurate RNA secondary structure prediction is vital for understanding cellular regulation and disease mechanisms. Deep learning (DL) methods have surpassed traditional algorithms by predicting complex features like pseudoknots and multi-interacting base pairs. However, traditional distance measures can hardly deal with such tertiary interactions and the currently used evaluation measures (F1 score, MCC) have limitations. We propose the Weisfeiler-Lehman graph kernel (WL) as an alternative metric. Embracing graph-based metrics like WL enables fair and accurate evaluation of RNA structure prediction algorithms. Further, WL provides informative guidance, as demonstrated in an RNA design experiment.Comment: 12 pages, Accepted at the Machine Learning for Structural Biology Workshop, NeurIPS 202

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design

Our world is ambiguous and this is reflected in the data we use to train our algorithms. This is especially true when we try to model natural processes where collected data is affected by noisy measurements and differences in measurement techniques. Sometimes, the process itself can be ambiguous, such as in the case of RNA folding, where a single nucleotide sequence can fold into multiple structures. This ambiguity suggests that a predictive model should have similar probabilistic characteristics to match the data it models. Therefore, we propose a hierarchical latent distribution to enhance one of the most successful deep learning models, the Transformer, to accommodate ambiguities and data distributions. We show the benefits of our approach on a synthetic task, with state-of-the-art results in RNA folding, and demonstrate its generative capabilities on property-based molecule design, outperforming existing work.Comment: Preprint, currently under revie

Laser-assisted material composition engineering of SiGe planar waveguides

We report the compositional engineering of silicon-germanium planar microstructures through laser processing. The effects of the laser treatment are assessed through microscope imaging and Raman spectroscopy. Our results reveal that the laser-exposed regions display a significant change in the material composition

Cultivated grapes in Roman Gaul

International audienc

Towards high speed and low power silicon photonic data links

Silicon is a low-cost material platform in which it is possible to form photonic integrated circuits serving a number of applications from optical communications to sensing. For optical communications applications, e.g. short reach data communication within data centres, the optical modulator is a key component with its capabilities having a significant bearing on the overall performance of the photonic circuit. In this paper we report our recent work on optical modulators in silicon and their integration with CMOS electronics on silicon

Hydrocortisone plus fludrocortisone for community acquired pneumonia-related septic shock: a subgroup analysis of the APROCCHSS phase 3 randomised trial

International audienceBackground: Glucocorticoids probably improve outcomes in patients hospitalised for community acquired pneumonia (CAP). In this a priori planned exploratory subgroup analysis of the phase 3 randomised controlled Activated Protein C and Corticosteroids for Human Septic Shock (APROCCHSS) trial, we aimed to investigate responses to hydrocortisone plus fludrocortisone between CAP and non-CAP related septic shock.Methods: APROCCHSS was a randomised controlled trial that investigated the effects of hydrocortisone plus fludrocortisone, drotrecogin-alfa (activated), or both on mortality in septic shock in a two-by-two factorial design; after drotrecogin-alfa was withdrawn on October 2011, from the market, the trial continued on two parallel groups. It was conducted in 34 centres in France. In this subgroup study, patients with CAP were a preselected subgroup for an exploratory secondary analysis of the APROCCHSS trial of hydrocortisone plus fludrocortisone in septic shock. Adults with septic shock were randomised 1:1 to receive, in a double-blind manner, a 7-day treatment with daily administration of intravenous hydrocortisone 50 mg bolus every 6h and a tablet of 50 μg of fludrocortisone via the nasogastric tube, or their placebos. The primary outcome was 90-day all-cause mortality. Secondary outcomes included all-cause mortality at intensive care unit (ICU) and hospital discharge, 28-day and 180-day mortality, the number of days alive and free of vasopressors, mechanical ventilation, or organ failure, and ICU and hospital free-days to 90-days. Analysis was done in the intention-to-treat population. The trial was registered at ClinicalTrials.gov (NCT00625209).Findings: Of 1241 patients included in the APROCCHSS trial, CAP could not be ruled in or out in 31 patients, 562 had a diagnosis of CAP (279 in the placebo group and 283 in the corticosteroid group), and 648 patients did not have CAP (329 in the placebo group and 319 in the corticosteroid group). In patients with CAP, there were 109 (39%) deaths of 283 patients at day 90 with hydrocortisone plus fludrocortisone and 143 (51%) of 279 patients receiving placebo (odds ratio [OR] 0·60, 95% CI 0·43-0·83). In patients without CAP, there were 148 (46%) deaths of 319 patients at day 90 in the hydrocortisone and fludrocortisone group and 157 (48%) of 329 patients in the placebo group (OR 0·95, 95% CI 0·70-1·29). There was significant heterogeneity in corticosteroid effects on 90-day mortality across subgroups with CAP and without CAP (p=0·046 for both multiplicative and additive interaction tests; moderate credibility). Of 1241 patients included in the APROCCHSS trial, 648 (52%) had ARDS (328 in the placebo group and 320 in the corticosteroid group). There were 155 (48%) deaths of 320 patients at day 90 in the corticosteroid group and 186 (57%) of 328 patients in the placebo group. The OR for death at day 90 was 0·72 (95% CI 0·53-0·98) in patients with ARDS and 0·85 (0·61-1·20) in patients without ARDS (p=0·45 for multiplicative interaction and p=0·42 for additive interaction). The OR for observing at least one serious adverse event (corticosteroid group vs placebo) within 180 days post randomisation was 0·64 (95% CI 0·46-0·89) in the CAP subgroup and 1·02 (0·75-1·39) in the non-CAP subgroup (p=0·044 for multiplicative interaction and p=0·042 for additive interaction).Interpretation: In a pre-specified subgroup analysis of the APROCCHSS trial of patients with CAP and septic shock, hydrocortisone plus fludrocortisone reduced mortality as compared with placebo. Although a large proportion of patients with CAP also met criteria for ARDS, the subgroup analysis was underpowered to fully discriminate between ARDS and CAP modifying effects on mortality reduction with corticosteroids. There was no evidence of a significant treatment effect of corticosteroids in the non-CAP subgroup.Funding: Programme Hospitalier de Recherche Clinique of the French Ministry of Health, by Programme d'Investissements d'Avenir, France 2030, and IAHU-ANR-0004