AIMC Topic: Fatty Acids, Volatile
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Comprehensive multi-omics analysis reveals the core role of glycerophospholipid metabolism in the influence of short-chain fatty acids on the development of sepsis.
Scientific reports
Aug 9, 2025
Sepsis is a systemic inflammatory response syndrome caused by infection, which has a high morbidity and mortality. Short-chain fatty acids (SCFAs) have been proved to improve the outcome of sepsis by regulating immunity and metabolism, but its specif...
Gut microbiota and SCFAs improve the treatment efficacy of chemotherapy and immunotherapy in NSCLC.
NPJ biofilms and microbiomes
Jul 28, 2025
The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on the therapeutic efficacy of chemotherapy and immunotherapy combinations remains poorly understood. We analyzed gut microbiota in non-small cell lung ca...
Micronutrient supplementation influences the composition and diet-originating function of the gut microbiome in healthy adults.
Clinical nutrition (Edinburgh, Scotland)
Jun 25, 2025
BACKGROUND & AIMS: Studies in-vitro and in animals propose that vitamins and minerals can alter the human gut microbiome. Human trials replicating these findings are scarce or used micronutrient supplementation in supraphysiological doses. We explore...
Brassica microgreens shape gut microbiota and functional metabolite profiles in a species-related manner: A multi-omics approach following in vitro gastrointestinal digestion and large intestine fermentation.
Microbiological research
May 19, 2025
Brassicaceae microgreens constitute a novel and promising source of bioactive compounds, such as polyphenols and glucosinolates. In this work, an integrative computational approach was performed to decipher the interaction between bioaccessible micro...
Graph-based deep learning for predictions on changes in microbiomes and biogas production in anaerobic digestion systems.
Water research
Jan 13, 2025
Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challe...
Exploring interactive effects of environmental and microbial factors on food waste anaerobic digestion performance: Interpretable machine learning models.
Bioresource technology
Nov 6, 2024
Biogas yield in anaerobic digestion (AD) involves continuous and complex biological reactions. The traditional linear models failed to quantitatively assess the interactive effects of these factors on AD performance. To further explore the internal r...
Enhancing corn stalk-based anaerobic digestion with different types of zero-valent iron added during the acidification stage: Performance and mechanism.
Journal of environmental sciences (China)
Aug 5, 2023
Anaerobic digestion has been defined as a competitive approach to facilitate the recycling of corn stalks. However, few studies have focused on the role of direct interspecies electron transfer (DIET) pathway in the acidification stage under the addi...
Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis.
Genome
Oct 8, 2020
The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimental evidence suggests gut microbiota as a key regulator of the GBA. Microbes living in the gut not o...
An integrated approach based on virtual data augmentation and deep neural networks modeling for VFA production prediction in anaerobic fermentation process.
Water research
Jun 30, 2020
Data-driven models are suitable for simulating biological wastewater treatment processes with complex intrinsic mechanisms. However, raw data collected in the early stage of biological experiments are normally not enough to train data-driven models. ...
Using artificial neural networks to predict pH, ammonia, and volatile fatty acid concentrations in the rumen.
Journal of dairy science
Aug 1, 2019
The objectives of this study were (1) to predict ruminal pH and ruminal ammonia and volatile fatty acid (VFA) concentrations by developing artificial neural networks (ANN) using dietary nutrient compositions, dry matter intake, and body weight as inp...
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