AIMC Topic: Mass Spectrometry

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Screening of bioactive compounds and deep learning-driven quality control of Angong Niuhuang pills.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Angong Niuhuang Pills (AGNHP), a famous Chinese medicine compound preparation, is widely used to treat stroke and other brain disorders. However, owing to the complexity of herbal components and diversity of production...

Insights Powered by Artificial Intelligence: Analyzing the Extent of Method Validation in Pesticide Residue Literature.

Journal of agricultural and food chemistry
Validation of analytical methods to assess figures of merit and other key performance parameters is a fundamental requirement within the fitness-for-purpose concept. By combining generative AI and subject matter review, this perspective article provi...

A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy.

Nature communications
Quantifying protein turnover is fundamental to understanding cellular processes and advancing drug discovery. Multiplex-DIA mass spectrometry (MS), combined with dynamic SILAC labeling (pulse-SILAC, or pSILAC) reliably measures protein turnover and d...

Integrative proteomic profiling of tumor and plasma extracellular vesicles identifies a diagnostic biomarker panel for colorectal cancer.

Cell reports. Medicine
The lack of reliable non-invasive biomarkers for early colorectal cancer (CRC) diagnosis underscores the need for improved diagnostic tools. Extracellular vesicles (EVs) have emerged as promising candidates for liquid-biopsy-based cancer monitoring. ...

Bioanalysis of antihypertensive drugs by LC-MS: a fleeting look at the regulatory guidelines and artificial intelligence.

Bioanalysis
Hypertension is a multifaceted cardiovascular disease, a significant risk factor for stroke, heart attack, heart failure, and renal damage. An essential phase in the drug development process is the exploration of effective bioanalytical approaches to...

SagMSI: A graph convolutional network framework for precise spatial segmentation in mass spectrometry imaging.

Analytica chimica acta
BACKGROUND: Mass Spectrometry Imaging (MSI) is a label-free imaging technique used in spatial metabolomics to explore the distribution of various metabolites within biological tissues. Spatial segmentation plays a crucial role in the biochemical inte...

Integrating mass defect filtering and targeted molecular networking for foodomics research: A case study of Magnolia officinalis cortex.

Food research international (Ottawa, Ont.)
Mass spectrometry (MS)-based foodomics is widely used to tackle complex challenges in food science, although its effectiveness is often hampered by extensive data redundancy. To address this limitation, a novel MS-based foodomics strategy, integratin...

Peptide Property Prediction for Mass Spectrometry Using AI: An Introduction to State of the Art Models.

Proteomics
This review explores state of the art machine learning and deep learning models for peptide property prediction in mass spectrometry-based proteomics, including, but not limited to, models for predicting digestibility, retention time, charge state di...

Prioritization strategies for non-target screening in environmental samples by chromatography - High-resolution mass spectrometry: A tutorial.

Journal of chromatography. A
Non-target screening (NTS) using chromatography coupled to high-resolution mass spectrometry (HRMS), has become fundamental for detecting and prioritizing chemicals of emerging concern (CECs) in complex environmental matrices. The vast number of gene...

FACT: foundation model for assessing cancer tissue margins with mass spectrometry.

International journal of computer assisted radiology and surgery
PURPOSE: Accurately classifying tissue margins during cancer surgeries is crucial for ensuring complete tumor removal. Rapid Evaporative Ionization Mass Spectrometry (REIMS), a tool for real-time intraoperative margin assessment, generates spectra th...