AIMC Topic: Lipids

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Machine-Learning Framework to Predict the Performance of Lipid Nanoparticles for Nucleic Acid Delivery.

ACS applied bio materials
Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability....

Lipid nanoparticle (LNP) mediated mRNA delivery in neurodegenerative diseases.

Journal of controlled release : official journal of the Controlled Release Society
Neurodegenerative diseases (NDD) are characterized by the progressive loss of neurons and the impairment of cellular functions. Messenger RNA (mRNA) has emerged as a promising therapy for treating NDD, as it can encode missing or dysfunctional protei...

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis.

Journal of mass spectrometry : JMS
Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to...

Understanding the Manufacturing Process of Lipid Nanoparticles for mRNA Delivery Using Machine Learning.

Chemical & pharmaceutical bulletin
Lipid nanoparticles (LNPs), used for mRNA vaccines against severe acute respiratory syndrome coronavirus 2, protect mRNA and deliver it into cells, making them an essential delivery technology for RNA medicine. The LNPs manufacturing process consists...

Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.

Journal of biomedical optics
SIGNIFICANCE: Coronary heart disease has the highest rate of death and morbidity in the Western world. Atherosclerosis is an asymptomatic condition that is considered the primary cause of cardiovascular diseases. The accumulation of low-density lipop...

Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a ...

Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

Proceedings of the National Academy of Sciences of the United States of America
RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-at...

Development of a periodontitis risk assessment model for primary care providers in an interdisciplinary setting.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Periodontitis (PD), a form of gum disease, is a major public health concern as it is globally prevalent and harms both individual quality of life and economic productivity. Global cost in lost productivity is estimated at US$54 billion an...

IMass Time: The Future, in Future!

Omics : a journal of integrative biology
Joseph John Thomson discovered and proved the existence of electrons through a series of experiments. His work earned him a Nobel Prize in 1906 and initiated the era of mass spectrometry (MS). In the intervening time, other researchers have also been...