Mature neutrophils and a NF-κB-to-IFN transition determine the unifying disease recovery dynamics in COVID-19.

Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome.

Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction.

Advanced protein structure prediction requires evolutionary information from multiple sequence alignments (MSAs) from evolutionary couplings that are not always available. Artificial intelligence (AI)-based predictions inputting only single sequences are faster but so inaccurate as to render speed irrelevant. Here, we described a competitive prediction of inter-residue distances (2D structure) exclusively inputting embeddings from pre-trained protein language models (pLMs), namely ProtT5, from single sequences into a convolutional neural network (CNN) with relatively few layers.

Tumour cell budding and spread through air spaces in squamous cell carcinoma of the lung - Determination and validation of optimal prognostic cut-offs.

Purpose: Prognostic stratification of patients with squamous cell carcinomas of the lung (SCC-L) is challenging. Therefore, we investigated several histomorphological parameters (tumour cell budding (TCB), spread through air spaces (STAS), tumour-stroma-ratio, immune cell infiltration) which could potentially serve as prognostic parameters in SCC-L. We aimed to systematically determine optimal cut-off-values and assess the prognostic capability of these patterns.

Fluorescence Labeling of Cellulose Nanocrystals-A Facile and Green Synthesis Route.

Efficient chemical modification of cellulose nanocrystals (CNCs) by grafting commonly involves aprotic solvents, toxic reactants, harsh reaction conditions, or catalysts, which have negative effects on the particle character, reduced dispersibility and requires further purification, if products are intended for biomedical applications. This work, in contrast, presents a robust, facile, and green synthesis protocol for the grafting of an amino-reactive fluorophore like fluorescein isothiocyanate (FITC) on aqueous CNCs, combining and modifying existent approaches in a two-step procedure. Comparably high grafting yields were achieved, which were confirmed by thermogravimetry, FTIR, and photometry.

Nutritional Composition of Beach-Cast Marine Algae from the Brazilian Coast: Added Value for Algal Biomass Considered as Waste.

In some coastal areas, large quantities of beach-cast macroalgae can accumulate and are usually considered waste and disposed of. However, due to their biofunctional and nutritional properties, they have great potential as a new source of raw materials. Increasing population growth has made the search for alternative raw materials with valuable nutritional properties urgent; here, beach-cast macroalgae could provide great potential.

Earthworms as catalysts in the formation and stabilization of soil microbial necromass.

Microbial necromass is a central component of soil organic matter (SOM), whose management may be essential in mitigating atmospheric CO concentrations and climate change. Current consensus regards the magnitude of microbial necromass production to be heavily dependent on the carbon use efficiency of microorganisms, which is strongly influenced by the quality of the organic matter inputs these organisms feed on. However, recent concepts neglect agents relevant in many soils: earthworms.

Transcriptomic and Drug Discovery Analyses Reveal Natural Compounds Targeting the KDM4 Subfamily as Promising Adjuvant Treatments in Cancer.

KDM4 proteins are a subfamily of histone demethylases that target the trimethylation of lysines 9 and 36 of histone H3, which are associated with transcriptional repression and elongation respectively. Their deregulation in cancer may lead to chromatin structure alteration and transcriptional defects that could promote malignancy. Despite that KDM4 proteins are promising drug targets in cancer therapy, only a few drugs have been described as inhibitors of these enzymes, while studies on natural compounds as possible inhibitors are still needed.

Description and optimization of a multiplex bead-based flow cytometry method (MBFCM) to characterize extracellular vesicles in serum samples from patients with hematological malignancies.

Extracellular Vesicles (EVs) are membranous vesicles produced by all cells under physiological and pathological conditions. In hematological malignancies, tumor-derived EVs might reprogram the bone marrow environment, suppress antileukemic immunity, mediate drug resistance and interfere with immunotherapies. EVs collected from the serum of leukemic samples might correlate with disease stage, drug-/immunological resistance, or might correlate with antileukemic immunity/immune response.

The distribution of carbon stocks between tree woody biomass and soil differs between Scots pine and broadleaved species (beech, oak) in European forests.

Unlabelled: While the impacts of forest management options on carbon (C) storage are well documented, the way they affect C distribution among ecosystem components remains poorly investigated. Yet, partitioning of total forest C stocks, particularly between aboveground woody biomass and the soil, greatly impacts the stability of C stocks against disturbances in forest ecosystems. This study assessed the impact of species composition and stand density on C storage in aboveground woody biomass (stem + branches), coarse roots, and soil, and their partitioning in pure and mixed forests in Europe.

Isolation and Characterization of Urinary Extracellular Vesicles for MicroRNA Biomarker Signature Development with Reference to MISEV Compliance.

Urine bears high potential for serving as biomarker repository for renal and urinary tract associated disorders. Besides various metabolites and salts, urine carries extracellular vesicles (EVs)-a heterogeneous group of cell-derived mediators comprising proteins, lipids, and nucleic acids such as microRNAs (miRNAs). Particularly, EV-derived miRNA biomarkers have already been identified for numerous disorders such as sepsis, various blood and solid cancer entities, respiratory and renal diseases.

Radical Scavenging Mechanisms of Phenolic Compounds: A Quantitative Structure-Property Relationship (QSPR) Study.

Due to their antioxidant properties, secondary plant metabolites can scavenge free radicals such as reactive oxygen species and protect foods from oxidation processes. Our aim was to study structural influences, like basic structure, number of hydroxyl groups and number of Bors criteria on the outcome of the oxygen radical absorbance capacity (ORAC) assay. Furthermore, similarities and differences to other antioxidant assays were analyzed by principal component analysis.

When fat meets the gut-focus on intestinal lipid handling in metabolic health and disease.

The regular overconsumption of energy-dense foods (rich in lipids and sugars) results in elevated intestinal nutrient absorption and consequently excessive accumulation of lipids in the liver, adipose tissue, skeletal muscles, and other organs. This can eventually lead to obesity and obesity-associated diseases such as type 2 diabetes (T2D), non-alcoholic fatty liver disease (NAFLD), cardiovascular disease, and certain types of cancer, as well as aggravate inflammatory bowel disease (IBD). Therefore, targeting the pathways that regulate intestinal nutrient absorption holds significant therapeutic potential.

Evaluation of Two Cosolvency Models to Predict Solute Partitioning between Polymers (LDPE) and Water - Ethanol Simulating Solvent Mixtures.

Purpose: Binary water - ethanol mixtures, by mimicking a clinically relevant medium's polarity-driven extraction strength, facilitate experimental modeling of patient exposure to chemicals which can potentially leach from a plastic material for pharmaceutical applications. Estimates of patient exposure could consequently benefit from a quantitative concept for tailoring the extraction strength of the simulating solvent mixture towards the one of the clinically relevant medium.

Methods: The hypothetical partition coefficient based upon the differential solubility between water-ethanol mixtures and water, [Formula: see text], has been calculated by the log-linear model from Yalkowsky and coworkers and a cosolvency model based on Abraham-type linear solvation energy relationships (LSERs).

Role of Reticulated Platelets in Cardiovascular Disease.

Human platelets differ considerably with regard to their size, RNA content and thrombogenicity. Reticulated platelets (RPs) are young, hyper-reactive platelets that are newly released from the bone marrow. They are larger and contain more RNA compared to older platelets.

Kupffer cells are protective in alcoholic steatosis.

Massive accumulation of lipids is a characteristic of alcoholic liver disease. Excess of hepatic fat activates Kupffer cells (KCs), which affect disease progression. Yet, KCs contribute to the resolution and advancement of liver injury.

Remodeling of Lipid A in pv. In Vitro.

species infect a variety of organisms, including mammals and plants. Mammalian pathogens of the Pseudomonas family modify their lipid A during host entry to evade immune responses and to create an effective barrier against different environments, for example by removal of primary acyl chains, addition of phosphoethanolamine (-EtN) to primary phosphates, and hydroxylation of secondary acyl chains. For pv.

Effects of slag and biochar amendments on microorganisms and fractions of soil organic carbon during flooding in a paddy field after two years in southeastern China.

Incorporating amendments of industrial waste such as biochar and steel slag in cropland has been used to enhance the storage of soil organic carbon (SOC) while sustaining crop production. Short-term laboratory and field studies have identified important influences of biochar on active SOC fractions associated with soil microbial activity in paddy soils, but the long-term effects remain poorly understood. To address these knowledge gaps, we examined the effects of slag, biochar, and slag+biochar treatments on total SOC concentration, active SOC fractions and soil microbial communities in a paddy field two years after incorporation.

Linear solvation energy relationships (LSERs) for robust prediction of partition coefficients between low density polyethylene and water. Part I: Experimental partition coefficients and model calibration.

When equilibrium of leaching is reached within a product's duty cycle, partition coefficients polymer/solution dictate the maximum accumulation of a leachable and thus, patient exposure by leachables. Yet, in the pharmaceutical and food industry, exposure estimates based on predictive modeling typically rely on coarse estimations of the partition coefficient, with accurate and robust models lacking. This first part of the study aimed to investigate linear solvation energy relationships (LSERs) as high performing models for the prediction of partition coefficients polymer/water.

Federated Random Forests can improve local performance of predictive models for various healthcare applications.

Motivation: Limited data access has hindered the field of precision medicine from exploring its full potential, e.g. concerning machine learning and privacy and data protection rules.

Spatial components of molecular tissue biology.

Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis.

CTCFL regulates the PI3K-Akt pathway and it is a target for personalized ovarian cancer therapy.

High-grade serous ovarian carcinoma (HGSC) is the most lethal gynecologic malignancy due to the lack of reliable biomarkers, effective treatment, and chemoresistance. Improving the diagnosis and the development of targeted therapies is still needed. The molecular pathomechanisms driving HGSC progression are not fully understood though crucial for effective diagnosis and identification of novel targeted therapy options.

Genotypic and phenotypic characterization of hydrogenotrophic denitrifiers.

Stimulating litho-autotrophic denitrification in aquifers with hydrogen is a promising strategy to remove excess NO , but it often entails accumulation of the cytotoxic intermediate NO and the greenhouse gas N O. To explore if these high NO and N O concentrations are caused by differences in the genomic composition, the regulation of gene transcription or the kinetics of the reductases involved, we isolated hydrogenotrophic denitrifiers from a polluted aquifer, performed whole-genome sequencing and investigated their phenotypes. We therefore assessed the kinetics of NO , NO, N O, N and O as they depleted O and transitioned to denitrification with NO as the only electron acceptor and hydrogen as the electron donor.

Squidpy: a scalable framework for spatial omics analysis.

Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Flexible tools are required to store, integrate and visualize the large diversity of spatial omics data. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins.