AIMC Topic: Lipids

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Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data.

EBioMedicine
BACKGROUND: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic opti...

Shortwave infrared diffuse optical wearable probe for quantification of water and lipid content in emulsion phantoms using deep learning.

Journal of biomedical optics
SIGNIFICANCE: The shortwave infrared (SWIR, to 2000 nm) holds promise for label-free measurements of water and lipid content in thick tissue, owed to the chromophore-specific absorption features and low scattering in this range. water and lipid est...

Comparative study of lipid nanoparticle-based mRNA vaccine bioprocess with machine learning and combinatorial artificial neural network-design of experiment approach.

International journal of pharmaceutics
To develop a combinatorial artificial-neural-network design-of-experiment (ANN-DOE) model, the effect of ionizable lipid, an ionizable lipid-to-cholesterol ratio, N/P ratio, flow rate ratio (FRR), and total flow rate (TFR) on the outcome responses of...

The antidiabetic drug pioglitazone ameliorates betel-nut-induced carcinogenesis in mice by restoring normal lipid metabolism, reducing oxidative stress, and inducing apoptosis.

Journal of cancer research and therapeutics
CONTEXT: Oral administration (2 mg mL-1) of aqueous extract of betel nut (AEBN) for 24 weeks induced oncogenic alterations in the liver of female Swiss Albino mice concomitant with aberrant lipid metabolism, overactivation of Akt/mTOR signaling, and ...

Acute Stress-Induced Changes in the Lipid Composition of Cow's Milk in Healthy and Pathological Animals.

Molecules (Basel, Switzerland)
Producers of milk and dairy products have been faced with the challenge of responding to European society's demand for guaranteed animal welfare production. In recent years, measures have been taken to improve animal welfare conditions on farms and e...

Deep Learning for Chondrogenic Tumor Classification through Wavelet Transform of Raman Spectra.

Sensors (Basel, Switzerland)
The grading of cancer tissues is still one of the main challenges for pathologists. The development of enhanced analysis strategies hence becomes crucial to accurately identify and further deal with each individual case. Raman spectroscopy (RS) is a ...

Implementation of Machine Learning Mechanism for Recognising Prostate Cancer through Photoacoustic Signal.

Contrast media & molecular imaging
Biological tissues may be studied using photoacoustic (PA) spectroscopy, which can yield a wealth of physical and chemical data. However, it is really challenging to directly analyse these tissues because of a lot of data. Data mining techniques can ...

Predicting H NMR acyl chain order parameters with graph neural networks.

Computational biology and chemistry
H NMR order parameters of the acyl chain of phospholipid membranes are an important indicator of the effects of molecules on membrane order, mobility, and permeability. So far, the evaluation procedures are case-by-case studies for every type of smal...

Formulation design and optimization of cationic-charged liposomes of brimonidine tartrate for effective ocular drug delivery by design of experiment (DoE) approach.

Drug development and industrial pharmacy
OBJECTIVE: The present study was aimed to design and optimize brimonidine tartrate (BRT) loaded cationic-charged liposome formulation with enhanced trans-corneal drug permeation, prolonged corneal residence, and sustained drug release for effective o...

Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics.

Journal of ultrasound
AIMS: We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.