Evaluating the generalizability of graph neural networks for predicting collision cross section.

Ion Mobility coupled with Mass Spectrometry (IM-MS) is a promising analytical technique that enhances molecular characterization by measuring collision cross-section (CCS) values, which are indicative of the molecular size and shape. However, the effective application of CCS values in structural analysis is still constrained by the limited availability of experimental data, necessitating the development of accurate machine learning (ML) models for in silico predictions. In this study, we evaluated state-of-the-art Graph Neural Networks (GNNs), trained to predict CCS values using the largest publicly available dataset to date.

Natural Products Have Increased Rates of Clinical Trial Success throughout the Drug Development Process.

Natural products (NPs) or their derivatives represent a large proportion of drugs that successfully progress through clinical trials to approval. This study explores the presence of NPs in both early- and late-stage drug discovery to determine their success rate, and the factors or features of natural products that contribute to such success. As a proxy for early drug development stages, we analyzed patent applications over several decades, finding a consistent proportion of NP, NP-derived, and synthetic-compound-based patent documents, with the latter group outnumbering NP and NP-derived ones (approximately 77% vs 23%).

Cleft Laterality Dental Arch Relationship Outcomes for Children with Unilateral Cleft Lip and Palate in New Zealand.

Objectives: To investigate cleft laterality dental arch relationship outcomes of children with non-syndromic complete unilateral cleft lip and palate (UCLP) in New Zealand.

Design: A retrospective nationwide study.

Settings: Virtual 3D orthodontic study models collected prior to undertaking secondary alveolar bone grafting.

Weighting Low-Intensity MS/MS Ions and / Frequency for Spectral Library Annotation.

Calculating spectral similarity is a fundamental step in MS/MS data analysis in untargeted metabolomics experiments, as it facilitates the identification of related spectra and the annotation of compounds. To improve matching accuracy when querying an experimental mass spectrum against a spectral library, previous approaches have proposed increasing peak intensities for high / ranges. These high / values tend to be smaller in magnitude, yet they offer more crucial information for identifying the chemical structure.