Inference of molecular divertor density from filtered camera analysis of molecularly induced Balmer line emission during detachment in JET L-mode plasmas

A previously presented Monte Carlo method for estimating local plasma conditions in 2D based on intensity ratios of deuterium Balmer D α , D γ and D ɛ lines was amended to consider also the D α and D γ emission contributions arising from molecular processes. The obtained estimates were used to infer the molecular divertor density with the help of the molecular databases of EIRENE. The method was benchmarked against EDGE2D-EIRENE simulations and observed to reproduce the molecularly induced emission fractions and the molecular divertor densities primarily within 25% of the references. Experimental analysis of a JET L-mode density scan suggested molecularly induced D α and D γ contributions of up to 60–70% and 20%, respectively, during the process of detachment. The independent estimates of the molecular divertor density inferred from the obtained molecularly induced D α and D γ intensities agree within uncertainties with each other. Both estimates show the molecular density increasing up to approximately 1.0–2.0 × 1020 m−3 at the outer strike point in deep detachment with its ratio to the local electron density agreeing with EDGE2D-EIRENE predictions within the scatter of the experimental data.

Using Stochastic Computing for Virtual Screening Acceleration

Stochastic computing is an emerging scientific field pushed by the need for developing high-performance artificial intelligence systems in hardware to quickly solve complex data processing problems. This is the case of virtual screening, a computational task aimed at searching across huge molecular databases for new drug leads. In this work, we show a classification framework in which molecules are described by an energy-based vector. This vector is then processed by an ultra-fast artificial neural network implemented through FPGA by using stochastic computing techniques. Compared to other previously published virtual screening methods, this proposal provides similar or higher accuracy, while it improves processing speed by about two or three orders of magnitude.

Increasing the power of interpretation for soil metaproteomics data

Background Soil and sediment microorganisms are highly phylogenetically diverse but are currently largely under-represented in public molecular databases. Their functional characterization by means of metaproteomics is usually performed using metagenomic sequences acquired for the same sample. However, such hugely diverse metagenomic datasets are difficult to assemble; in parallel, theoretical proteomes from isolates available in generic databases are of high quality. Both these factors advocate for the use of theoretical proteomes in metaproteomics interpretation pipelines. Here, we examined a number of database construction strategies with a view to increasing the outputs of metaproteomics studies performed on soil samples. Results The number of peptide-spectrum matches was found to be of comparable magnitude when using public or sample-specific metagenomics-derived databases. However, numbers were significantly increased when a combination of both types of information was used in a two-step cascaded search. Our data also indicate that the functional annotation of the metaproteomics dataset can be maximized by using a combination of both types of databases. Conclusions A two-step strategy combining sample-specific metagenome database and public databases such as the non-redundant NCBI database and a massive soil gene catalog allows maximizing the metaproteomic interpretation both in terms of ratio of assigned spectra and retrieval of function-derived information.

Retrospective Case Series Analysis of RAF Family Alterations in Pancreatic Cancer: Real-World Outcomes From Targeted and Standard Therapies

PURPOSE In pancreatic cancer (PC), the RAF family alterations define a rare subset of patients that may predict response to inhibition of the BRAF/MEK/ERK signaling pathway. A comprehensive understanding of the molecular and clinical characteristics of RAF-mutated PC may support future development of RAF-directed strategies. METHODS Clinical outcomes were assessed across a multi-institutional case series of 81 patients with RAF family-mutated PC. Mutational subgroups were defined on the basis of RAF alteration hotspots and therapeutic implications. RESULTS The frequency of RAF alterations in PC was 2.2% (84 of 3,781) within a prevalence cohort derived from large molecular databases where BRAF V600E (Exon 15), BRAF ΔNVTAP (Exon 11), and SND1-BRAF fusions were the most common variants. In our retrospective case series, we identified 17 of 81 (21.0%) molecular profiles with a BRAF V600/Exon 15 mutation without any confounding drivers, 25 of 81 (30.9%) with BRAF or RAF1 fusions, and 18 of 81 (22.2%) with Exon 11 mutations. The remaining 21 of 81 (25.9%) profiles had atypical RAF variants and/or multiple oncogenic drivers. Clinical benefit from BRAF/MEK/ERK inhibitors was observed in 3 of 3 subjects within the V600 subgroup (two partial responses), 4 of 6 with fusions (two partial responses), 2 of 6 with Exon 11 mutations (one partial response), and 0 of 3 with confounding drivers. Outcomes analyses also suggested a trend favoring fluorouracil-based regimens over gemcitabine/nab-paclitaxel within the fusion subgroup ( P = .027). CONCLUSION Prospective evaluation of RAF-directed therapies is warranted in RAF-mutated PC; however, differential responses to targeted agents or standard regimens for each mutational subgroup should be a consideration when designing clinical trials.

VSPrep: A KNIME Workflow for the Preparation of Molecular Databases for Virtual Screening

Drug discovery is a challenging and expensive field. Hence, novel in silico tools have been developed in early discovery stage to identify and prioritize novel molecules with suitable physicochemical properties. In many in silico drug design projects, molecular databases are screened by virtual screening tools to search for potential bioactive molecules. The preparation of the molecules is therefore a key step in the success of well-established techniques such as docking, similarity or pharmacophore searching. We review here the lists of several toolkits used in different steps during the cleaning of molecular databases, integrated within a KNIME workflow. During the first step of the automatic workflow, salts are removed, and mixtures are split to get one compound per entry. Then compounds with unwanted features are filtered. Duplicated entries are then deleted while considering stereochemistry. As a compromise between exhaustiveness and computational time, most distributed tautomers at physiological pH are computed. Additionally, various flags are applied to molecules by using either classical molecular descriptors, similarity search to known libraries or substructure search rules. Moreover, stereoisomers are enumerated depending on the unassigned chiral centers. Then, three-dimensional coordinates, and optionally conformers, are generated. This workflow has been already applied to several drug design projects and can be used for molecular database preparation upon request.

BASECOL2020 New Technical Design

The BASECOL database has been created and scientifically enriched since 2004. It contains collisional excitation rate coefficients of molecules for application to the interstellar medium and to cometary atmospheres. Recently, major technical updates have been performed in order to be compliant with international standards for management of data and in order to provide a more friendly environment to query and to present the data. The current paper aims at presenting the key features of the technical updates and to underline the compatibility of BASECOL database with the Virtual Atomic and Molecular Data Center. This latter aims to interconnect atomic and molecular databases, thus providing a single location where users can access atomic and molecular data.

The Spectroscopic Atomic and Molecular Databases at the Paris Observatory

This paper is intended to give a comprehensive overview of the current status and developments of the Paris Observatory STARK-B, MOLAT and SESAM databases which can be interrogated thanks to interoperability tools. The STARK-B database provides shifting and broadening parameters of different atomic and ionic transitions due to impacts with charged particles (the so-called Stark broadening) for different temperatures and densities. The spectroscopic MOLAT and SESAM databases provide the wavelengths, the oscillator strengths or Einstein spontaneous emission coefficients of H 2 , CO and isotopologues molecules.

Applying HT-NGH Algorithm On A Shared Memory Architecture For Time Performance Improvement

Background: Sequence comparison and alignment plays an important role in computational biology as they allow for rating the similarities between molecular sequences. Pair-wise alignment contributes significantly in calculating the similarity between sequences by constructing the optimal alignment. The Hash Table-N-Gram-Hirschberg (HT-NGH) algorithm, which is an extension to the Hashing-N-Gram-Hirschberg (HNGH) and N-Gram-Hirschberg (NGH) algorithms, represents a pair-wise alignment method that uses the capabilities of the hash table technique for the purpose of building the alignment. Due to the current technology, molecular databases have exponentially grown to highlight the needs for faster and efficient methods that can handle these amounts of data. On the other hand, the present technology provides a verity of high performance architectures and tools. Results: This paper presents a parallel shared memory algorithm for protein pair-wise alignment method, namely, the HT-NGH algorithm in order to enhance the time performance of sequences’ comparisons and alignments. The proposed parallel algorithm targets the transformation phase of the HT-NGH algorithm since it consumes about 10% of alignment’s executional time. Datasets are decomposed up to sequence level for a more efficient utilization of processing units (no idle processing unit). Conclusions: As a result, the proposed algorithm demonstrates a significant improvement in terms of time performance without sacrificing accuracy. The speed up pertaining to the parallel algorithm reaches 2.08, 2.88, and 3.87 when using 2, 3, and 4 cores, respectively. Furthermore, this algorithm gains high efficiency as it reaches 1.04, 0.96, and 0.97 when using 2, 3, and 4 cores, respectively.

Challenges for the future of taxonomy: talents, databases and knowledge growth

In this essay we want to shed some light on selected subjects of taxonomy that we think are worth looking at: the problems of the taxonomic workforce, the taxonomic knowledge growth based on the use of databases and web-portals and some suggestions for quality improvements in molecular databases for the benefit of the scientific community, conservation practitioners, regulators, policy-makers and citizen-scientists.