AIMC Topic: Lipids

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Lipidomic profiling of human adiposomes identifies specific lipid shifts linked to obesity and cardiometabolic risk.

JCI insight
BACKGROUNDObesity, a growing health concern, often leads to metabolic disturbances, systemic inflammation, and vascular dysfunction. Emerging evidence suggests that adipose tissue-derived extracellular vesicles (adiposomes) may propagate obesity-rela...

Engineered multi-domain lipid nanoparticles for targeted delivery.

Chemical Society reviews
Engineered lipid nanoparticles (LNPs) represent a breakthrough in targeted drug delivery, enabling precise spatiotemporal control essential to treat complex diseases such as cancer and genetic disorders. However, the complexity of the delivery proces...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Analytical chemistry
Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprecedented detail. Virtual staining techniques, which rely on computational algorithms to map molecular ...

A lipid atlas of the human kidney.

Science advances
Tissue atlases provide foundational knowledge on the cellular organization and molecular distributions across molecular classes and spatial scales. Here, we construct a comprehensive spatiomolecular lipid atlas of the human kidney from 29 donor tissu...

Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.

Cardiovascular diabetology
BACKGROUND AND OBJECTIVE: Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six ...

Combining lipidomics and machine learning to identify lipid biomarkers for nonsyndromic cleft lip with palate.

JCI insight
Nonsyndromic cleft lip with palate (nsCLP) is a common birth defect disease. Current diagnostic methods comprise fetal ultrasound images, which are mainly limited by fetal position and technician skills. We aimed to identify reliable maternal serum l...

Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome.

World journal of urology
PURPOSE: To identify biomarkers for diagnosis and classification of interstitial cystitis/bladder pain syndrome (IC/BPS) by urinary lipidomics coupled with machine learning.

Milk lipidome alterations in first-lactation dairy cows with lameness: A biomarker identification approach using untargeted lipidomics and machine learning.

Journal of dairy science
Lameness, defined as an impaired gait, impacts cow welfare and performance, compromising future health and production, and increasing culling risk. Untargeted milk lipidomics, together with the use of machine learning methods, have shown promise in i...

Cancer Cell Line Classification Using Raman Spectroscopy of Cancer-Derived Exosomes and Machine Learning.

Analytical chemistry
Liquid biopsies are an emerging, noninvasive tool for cancer diagnostics, utilizing biological fluids for molecular profiling. Nevertheless, the current methods often lack the sensitivity and specificity necessary for early detection and real-time mo...

Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning.

Nature communications
Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluate the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lip...