AIMC Topic: Animals
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Ultradeep N-glycoproteome atlas of mouse reveals spatiotemporal signatures of brain aging and neurodegenerative diseases.
Nature communications
Jul 1, 2025
The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosylation events in biological samples. Herein, we achieve an ultradeep and precision analysis of the N-glycoproteome of mouse tissues by integrating multi...
Brain-wide input-output analysis of tuberal nucleus somatostatin neurons reveals hierarchical circuits for orchestrating feeding behavior.
Nature communications
Jul 1, 2025
Feeding is an innate behavior critical for survival but is also influenced by many non-nutritional factors such as emotion, social context and environmental conditions. Recently, tuberal nucleus somatostatin (SST) neurons have been identified as a ke...
A FPGA based recurrent neural networks-based impedance spectroscopy system for detection of YAKE in tuna.
Scientific reports
Jul 1, 2025
This paper evaluates the use of impedance spectroscopy combined with artificial intelligence. Both technologies have been widely used in food classification and it is proposed a way to improve classifications using recurrent neural networks that trea...
Identification of pyroptosis related genes and subtypes in atherosclerosis using multiomic and single cell analysis.
Scientific reports
Jul 1, 2025
Atherosclerosis (AS), the leading cause of cardiovascular diseases, is a chronic inflammatory disorder involving lipid metabolism, immune dysregulation, and cell death. Pyroptosis, a form of inflammatory programmed cell death, is implicated in AS pro...
Therapeutic horizons in metabolic dysfunction-associated steatohepatitis.
The Journal of clinical investigation
Jul 1, 2025
Metabolic dysfunction-associated steatohepatitis (MASH), the progressive inflammatory form of MASLD, is now a leading cause of chronic liver disease worldwide. Driven by obesity and type 2 diabetes, MASH significantly increases the risk of cirrhosis,...
Identification of key genes and development of an identifying machine learning model for sepsis.
Inflammation research : official journal of the European Histamine Research Society ... [et al.]
Jun 30, 2025
OBJECTIVE AND DESIGN: This study aims to identify key genes of sepsis and construct a model for sepsis identification through integrated multi-organ single-cell RNA sequencing (scRNA-seq) and machine learning.
In-silico guided identification and studies of potential FFAR4 agonists for type 2 diabetes mellitus therapy.
Expert opinion on drug discovery
Jun 28, 2025
BACKGROUND: The activation of free fatty acid receptor 4 (FFAR4) enhances insulin sensitivity and glucose uptake while mitigating inflammation. It is a promising therapeutic approach for managing type 2 diabetes mellitus (T2DM).
Artificial intelligence meets brain theory (again).
Biological cybernetics
Jun 28, 2025
After noting the cybernetic origins of Kybernetik/ Biological Cybernetics, we respond to the Editorial by Fellous et al. (2025) and then analyze talks from the NIH BRAIN NeuroAI 2024 Workshop to get one "snapshot" of the state of the conversation bet...
Artificial intelligence - based approaches based on random forest algorithm for signal analysis: Potential applications in detection of chemico - biological interactions.
Chemico-biological interactions
Jun 27, 2025
Random Forest (RF) is a powerful ensemble-based supervised machine learning technique that builds multiple decision trees using bootstrap aggregating and random feature selection to improve classification and regression accuracy while reducing overfi...
Multi-level evidence reveals PANK2 as a potential target of PFOA/PFOS-induced bone metabolism disruption: From network toxicology to in vitro validation.
Ecotoxicology and environmental safety
Jun 27, 2025
Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are two representative per- and polyfluoroalkyl substances (PFAS) that have attracted increasing attention due to their environmental persistence and potential health risks, while ...
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