Deep learning for retention time prediction in reversed-phase liquid chromatography.

Retention time prediction in high-performance liquid chromatography (HPLC) is the subject of many studies since it can improve the identification of unknown molecules in untargeted profiling using HPLC coupled with high-resolution mass spectrometry. Lots of approaches were developed for retention time prediction in liquid chromatography for a different number of molecules considering various molecular properties and machine learning algorithms. The recently built large retention time data set of standard compounds from the Metabolite and Chemical Entity Database (METLIN) allows researchers to create a model that can be used for retention time prediction of small molecules with wide varieties of structures and physicochemical properties. The ability to predict retention times using the largest data set was studied for different architectures of deep learning models that were trained on molecular fingerprints, and SMILES (string representation of a molecule) represented as one-hot matrices. The best result was achieved with a one-dimensional convolutional neural network (1D CNN) that uses SMILES as an input. The proposed model reached the mean absolute error and the median absolute error equal to 34.7 and 18.7 s, respectively, which outperformed the results previously obtained for this data set. The pre-trained 1D CNN on the METLIN SMRT data set was transferred on five other data sets to evaluate the generalization ability.

Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study.

Large-scale untargeted LC-MS-based metabolomic profiling is a valuable source for systems biology and biomarker discovery. Data analysis and processing are major tasks due to the high complexity of generated signals and the presence of unwanted variations. In the present study, we introduce an R-based open-source collection of scripts called OUKS (Omics Untargeted Key Script), which provides comprehensive data processing. OUKS is developed by integrating various R packages and metabolomics software tools and can be easily set up and prepared to create a custom pipeline. Novel computational features are related to quality control samples-based signal processing and are implemented by gradient boosting, tree-based, and other nonlinear regression algorithms. Bladder cancer biomarkers discovery study which is based on untargeted LC-MS profiling of urine samples is performed to demonstrate exhaustive functionality of the developed software tool. Unique examination among dozens of metabolomics-specific data curation methods was carried out at each processing step. As a result, potential biomarkers were identified, statistically validated, and described by metabolism disorders. Our study demonstrates that OUKS helps to make untargeted LC-MS metabolomic profiling with the latest computational features readily accessible in a ready-to-use unified manner to a research community.

Development of ELISA formats for polymyxin B monitoring in serum of critically ill patients.

Treating infections in critically ill patients often requires the use of last-line antibacterial drugs such as polymyxins with a narrow therapeutic window and high toxicity. In critically ill patients, the drug pharmacokinetics changes significantly, and as a result, the antibiotic concentrations in blood and infection foci become suboptimal, which leads to therapeutic failures or toxic manifestations. For timely dosage adjustments, a competitive ELISA-based method using antibodies to polymyxin В (PMB) was developed. Among the several considered assays, a direct antibody-coated format was selected for its short duration (1.5 h) and the best agreement with the LC-MS/MS data (R2 = 98 %). The assay dynamic measurement range (IC20-IC80) could be substantially shifted by changing the ratio of immunoreagents. To conveniently measure the therapeutic range of PMB concentrations, it was adjusted to 5.0-192 ng/mL, allowing the samples to be analyzed after a simple 100-fold dilution with the assay buffer. The ELISA sensitivity expressed in half-inhibition concentration (IC50) and the limit of detection were 30.6 and 1.8 ng/mL, respectively. The assay cross-reactivity towards the related analogue colistin (COL) was 95 %, and this compound could also be adequately quantified by the same assay. The PMB and COL recovery from the spiked serum samples was similar and constituted 98-109 %. The trial drug monitoring was carried out in 3 patients with Gram-negative sepsis, and the established pharmacokinetic profiles of PMB revealed the necessity for individual dosage adjustment.

Fused 1,2-Diboraoxazoles Based on closo-Decaborate Anion-Novel Members of Diboroheterocycle Class.

The novel members of the 1,2-diboraoxazoles family have been obtained. In the present work, we have carried out the intramolecular ring-closure reaction of borylated iminols of general type [B10H9N=C(OH)R]- (R = Me, Et, nPr, iPr, tBu, Ph, 4-Cl-Ph). This process is conducted in mild conditions with 83-87% yields. The solid-state structures of two salts of 1,2-diboraoxazoles were additionally investigated by X-ray crystallography. In addition, the phenomena of bonding interactions in the 1,2-diboraoxazole cycles have been theoretically studied by the Quantum Theory of Atoms in Molecules analysis. Several local and integral topological properties of the electron density involved in these interactions have been computed.