Commensal microbiota has huge impact on the maintenance of human health, its dysregulation being associated with the development of a plethora of diseases. Release of bacterial extracellular vesicles (BEVs) is a fundamental mechanism of systemic microbiome influence on the host organism. Nevertheless, due to the technical challenges of isolation methods, BEV composition and functions remain poorly characterized. Hereby, we describe the up-to-date protocol for isolation of BEV-enriched samples from human feces. Fecal extracellular vesicles (EVs) are purified through the orthogonal implementation of filtration, size-exclusion chromatography (SEC), and density gradient ultracentrifugation. EVs are first separated from bacteria, flagella, and cell debris by size. In the next steps, BEVs are separated from host-derived EVs by density. The quality of vesicle preparation is estimated via immuno-TEM (transmission electron microscopy) for the presence of vesicle-like structures expressing EV markers and via NTA (nanoparticle tracking analysis) for assaying particle concentration and size. Distribution of EVs of human origin in gradient fractions is estimated using antibodies against human exosomal markers with Western blot and ExoView R100 imaging platform. The enrichment for BEVs in vesicle preparation is estimated by Western blot for the presence of bacterial OMVs (outer membrane vesicles) marker and OmpA (outer membrane protein A). Taken together, our study describes a detailed protocol for EV preparation with enrichment for BEVs from feces with a purity level suitable for bioactivity functional assays.
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http://dx.doi.org/10.1007/978-1-0716-3203-1_15 | DOI Listing |
J Mol Model
December 2024
Department of Physical and Numerical Sciences, Qurtuba University of Science and Information Technology, Peshawar, 25100, Pakistan.
Context: Vanadium hydride is of significant interest because of its potential applications in thermoelectric materials and hydrogen storage technologies. Understanding its structural, electronic, and thermoelectric properties is crucial for optimizing its performance in these applications. This study investigates these properties via density functional theory (DFT), revealing key insights into its stability and efficiency as a thermoelectric material.
View Article and Find Full Text PDFJ Phys Chem Lett
December 2024
Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States.
In this work, a machine learning mapping approach for predicting the properties of atomistic systems is reported. Within this approach, the atomic orbital overlap, density, or Kohn-Sham (KS) Fock matrix elements obtained at a low level of theory such as extended tight-binding have been used as input features to predict the electric field gradient (EFG) tensors at a higher level of theory such as those obtained with hybrid functionals. It is shown that the machine-learning-predicted EFG tensors can be used to compute spin relaxation rates of several ions in aqueous solutions.
View Article and Find Full Text PDFEnviron Monit Assess
December 2024
Wadia Institute of Himalayan Geology, Dehradun, India, 248001.
The Himalayas experiences several cloudburst events due to its varied physiographical, geomorphological, and geological conditions and high rainfall. Uttarakhand is one of the Indian states circumscribed by the Himalayan ranges and has experienced a rise in the number of cloudburst catastrophes in the last few decades. These events cause substantial loss of life and property; however, very few studies have characterized these unpredictable cloudburst-induced flash floods in different regions of Uttarakhand.
View Article and Find Full Text PDFMedicine (Baltimore)
December 2024
School of Informatics, Hunan University of Chinese Medicine, Changsha, China.
In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined with machine learning technology, to study the risk factors and better risk prediction model of diabetic retinopathy (DR), and provide basis for the screening and treatment of it. Through a retrospective study of DR cases in the real world, the electronic medical records of patients who met screening criteria were collected. Moreover, Recursive Feature Elimination with Cross-Validation (RFECV) was used for feature selection.
View Article and Find Full Text PDFBiodivers Data J
December 2024
Estación Biológica de Doñana-CSIC, Sevilla, Spain Estación Biológica de Doñana-CSIC Sevilla Spain.
Background: The long-term monitoring of the plant cover of Doñana shrublands is part of a harmonised protocol for the Long-term Ecological Monitoring Programme of Natural Resources and Processes targeting Terrestrial Vegetation. The general aim of this protocol is to monitor and assess the dynamics and trends of shrubland plant communities in Doñana. For shrublands, percentage cover is recorded annually, starting in 2008, by the Doñana Long-Term Monitoring Team in one field sampling campaign per year during the flowering season (between March and May) across 21 permanent square plots (15 m x 15 m).
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