Plasticizer exposure in Germany from 1988 to 2022: Human biomonitoring data of 20 plasticizers from the German Environmental Specimen Bank.

The German Environmental Specimen Bank (ESB) annually archives 24-h urine samples since the early 1980s. In this study, we analyzed 420 of these samples from the years 2014 to 2022 for metabolites of 18 phthalates and two substitutes. We merged the new data with the data from previous measurement campaigns to a combined dataset of 1825 samples covering a 35-year period from 1988 to 2022 to investigate time trends, calculate daily intakes and perform an anti-androgenic mixture risk assessment.

RIOT-Rapid Immunoglobulin Overview Tool-annotation of nucleotide and amino acid immunoglobulin sequences using an open germline database.

Antibodies are a cornerstone of the immune system, playing a pivotal role in identifying and neutralizing infections caused by bacteria, viruses, and other pathogens. Understanding their structure, and function, can provide insights into both the body's natural defenses and the principles behind many therapeutic interventions, including vaccines and antibody-based drugs. The analysis and annotation of antibody sequences, including the identification of variable, diversity, joining, and constant genes, as well as the delineation of framework regions and complementarity-determining regions, is essential for understanding their structure and function.

Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews.

Background: PRISMA-based literature reviews require meticulous scrutiny of extensive textual data by multiple reviewers, which is associated with considerable human effort.

Objective: To evaluate feasibility and reliability of using GPT-4 API as a complementary reviewer in systematic literature reviews based on the PRISMA framework.

Methodology: A systematic literature review on the role of natural language processing and Large Language Models (LLMs) in automatic patient-trial matching was conducted using human reviewers and an AI-based reviewer (GPT-4 API).

The activity of CobB1 protein deacetylase contributes to nucleoid compaction in Streptomyces venezuelae spores by increasing HupS affinity for DNA.

Streptomyces are soil bacteria with complex life cycle. During sporulation Streptomyces linear chromosomes become highly compacted so that the genetic material fits within limited spore volume. The key players in this process are nucleoid-associated proteins (NAPs).

Benchmarking antibody clustering methods using sequence, structural, and machine learning similarity measures for antibody discovery applications.

Antibodies are proteins produced by our immune system that have been harnessed as biotherapeutics. The discovery of antibody-based therapeutics relies on analyzing large volumes of diverse sequences coming from phage display or animal immunizations. Identification of suitable therapeutic candidates is achieved by grouping the sequences by their similarity and subsequent selection of a diverse set of antibodies for further tests.

LAP: Liability Antibody Profiler by sequence & structural mapping of natural and therapeutic antibodies.

Antibody-based therapeutics must not undergo chemical modifications that would impair their efficacy or hinder their developability. A commonly used technique to de-risk lead biotherapeutic candidates annotates chemical liability motifs on their sequence. By analyzing sequences from all major sources of data (therapeutics, patents, GenBank, literature, and next-generation sequencing outputs), we find that almost all antibodies contain an average of 3-4 such liability motifs in their paratopes, irrespective of the source dataset.

Data integration through canonical correlation analysis and its application to OMICs research.

The subject of the paper is a review of multidimensional data analysis methods, which is the canonical analysis with its various variants and its use in omics data research. The dynamic development of high-throughput methods, and with them the availability of large and constantly growing data resources, forces the development of new analytical approaches that allow the review of the analyzed processes, taking into account data from various levels of the organization of living organisms. The multidimensional perspective allows for the assessment of the analyzed phenomenon in a more realistic way, as it generally takes into account much more data (including OMICs data).

Quantitative Metabolism and Urinary Elimination Kinetics of Seven Neonicotinoids and Neonicotinoid-Like Compounds in Humans.

Reverse dosimetry, i.e., calculating the dose of hazardous substances that has been taken up by humans based on measured analyte concentrations in spot urine samples, is critical for risk assessment and requires metabolic and kinetic data.

Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery.

AlphaFold2 has hallmarked a generational improvement in protein structure prediction. In particular, advances in antibody structure prediction have provided a highly translatable impact on drug discovery. Though AlphaFold2 laid the groundwork for all proteins, antibody-specific applications require adjustments tailored to these molecules, which has resulted in a handful of deep learning antibody structure predictors.

Quantitation of 6-chloronicotinic acid and 2-chloro-1,3-thiazole-5-carboxylic acid and their glycine conjugates in human urine to assess neonicotinoid exposure.

Neonicotinoids and neonicotinoid-like compounds (NNIs) are widely used insecticides and their ubiquitous occurrence in the environment requires methods for exposure assessment in humans. The majority of the NNIs can be divided into 6-chloropyridinyl- and 2-chlorothiazolyl-containing compounds, suggesting the formation of the group-specific metabolites 6-chloronicotinic acid (6-CNA), 2-chloro-1,3-thiazole-5-carboxylic acid (2-CTA), and their respective glycine derivatives (6-CNA-gly, 2-CTA-gly). Here, we developed and validated an analytical method based on gas chromatography coupled to mass spectrometry (GC-MS/MS) to simultaneously analyze these four metabolites in human urine.

Large extracellular vesicles do not mitigate the harmful effect of hyperglycemia on endothelial cell mobility.

Extracellular vesicles, especially the larger fraction (LEVs - large extracellular vesicles), are believed to be an important means of intercellular communication. Earlier studies on LEVs have shown their healing properties, especially in the vascular cells of diabetic patients. Uptake of LEVs by endothelial cells and internalization of their cargo have also been demonstrated.

Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery.

Antibodies are versatile molecular binders with an established and growing role as therapeutics. Computational approaches to developing and designing these molecules are being increasingly used to complement traditional lab-based processes. Nowadays, in silico methods fill multiple elements of the discovery stage, such as characterizing antibody-antigen interactions and identifying developability liabilities.

Visual Analytics for Human-Centered Machine Learning.

We introduce a new research area in visual analytics (VA) aiming to bridge existing gaps between methods of interactive machine learning (ML) and eXplainable Artificial Intelligence (XAI), on one side, and human minds, on the other side. The gaps are, first, a conceptual mismatch between ML/XAI outputs and human mental models and ways of reasoning, and second, a mismatch between the information quantity and level of detail and human capabilities to perceive and understand. A grand challenge is to adapt ML and XAI to human goals, concepts, values, and ways of thinking.

Human metabolism and urinary excretion of seven neonicotinoids and neonicotinoid-like compounds after controlled oral dosages.

Few human data on exposure and toxicity are available on neonicotinoids and neonicotinoid-like compounds (NNIs), an important group of insecticides worldwide. Specifically, exposure assessment of humans by biomonitoring remains a challenge due to the lack of appropriate biomarkers. We investigated the human metabolism and metabolite excretion in urine of acetamiprid (ACE), clothianidin (CLO), flupyradifurone (FLUP), imidacloprid (IMI), sulfoxaflor (SULF), thiacloprid (THIAC) and thiamethoxam (THIAM) after single oral dosages at the currently acceptable daily intake levels of the European Food Safety Authority.

Heroin-Related Compounds and Metabolic Ratios in Postmortem Samples Using LC-MS-MS.

Analysis of postmortem samples with the presence of morphine can sometimes be challenging to interpret. Tolerance complicates interpretation of intoxications and causes of death due to overlap in therapeutic and fatal concentrations. Determination of metabolites and metabolic ratios can potentially differentiate between abstinence, continuous administration, and perhaps time of administration.

OmicsON - Integration of omics data with molecular networks and statistical procedures.

A huge amount of atomized biological data collected in various databases and the need for a description of their relation by theoretical methods causes the development of data integration methods. The omics data analysis by integration of biological knowledge with mathematical procedures implemented in the OmicsON R library is presented in the paper. OmicsON is a tool for the integration of two sets of data: transcriptomics and metabolomics.

Constructing Spaces and Times for Tactical Analysis in Football.

A possible objective in analyzing trajectories of multiple simultaneously moving objects, such as football players during a game, is to extract and understand the general patterns of coordinated movement in different classes of situations as they develop. For achieving this objective, we propose an approach that includes a combination of query techniques for flexible selection of episodes of situation development, a method for dynamic aggregation of data from selected groups of episodes, and a data structure for representing the aggregates that enables their exploration and use in further analysis. The aggregation, which is meant to abstract general movement patterns, involves construction of new time-homomorphic reference systems owing to iterative application of aggregation operators to a sequence of data selections.

Identification of Differentiating Metabolic Pathways between Infant Gut Microbiome Populations Reveals Depletion of Function-Level Adaptation to Human Milk in the Finnish Population.

A variety of autoimmune and allergy events are becoming increasingly common, especially in Western countries. Some pieces of research link such conditions with the composition of microbiota during infancy. In this period, the predominant form of nutrition for gut microbiota is oligosaccharides from human milk (HMO).