This protocol presents methods for isolating and identifying novel nucleic acid–binding proteins. We focus on bacterial DNA-binding proteins, although the methods can be readily adapted to identify n....

This study aimed to develop and validate two simplified, one-step extraction methods coupled with liquid chromatography-tandem mass spectrometry (LC–MS/MS) for the simultaneous segmental analysis of p...

AbstractBACKGROUND. Lung Cancer Leptomeningeal Metastasis (LC-LM) severely impacts patient survival and quality of life, yet current diagnostic methods lac

Amyloid typing, particularly in monoclonal gammopathies of renal significance, can be technically challenging. Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has ...

Background Hypoxic-ischemic encephalopathy (HIE) is a leading cause of neonatal mortality and morbidity, yet no validated biomarkers currently exist to predict long-term outcomes. We investigated the ...

BMC Oral Health - Oral squamous cell carcinoma (OSCC) is the most common form of head and neck cancer. It is of great significance to search for biomarkers associated with OSCC progression through...

Glycosaminoglycans (GAGs) are linear polysaccharide chains that are usually linked to proteins to create proteoglycans and play an essential role in the extracellular matrix (ECM). Mucopolysaccharidos...

The ability to distinguish menstrual blood from venous blood can prove important in forensic investigations, provide evidence in criminal and sexual assault cases and give context to what may have occ...

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...

IntroductionFinger millet (Eleusine coracana) is gaining increasing recognition as a functional food and a promising source of nutraceuticals for mitigating ...

Endocannabinoids (eCBs) are crucial to regulating physiological function in the human body. This study investigates the applicability of volumetric absorptive microsampling (VAMS) for eCB analysis in blood samples. First, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated to quantify a series of primary eCBs and eCB-like lipid mediators (i.e., AEA, OEA, SEA, PEA, LEA, 2-AG, and 2-OG). We then evaluated VAMS, considering several key parameters such as temperature, humidity, and hematocrit levels. This research systematically compared, for the first time, eCB levels in whole blood and plasma samples. We demonstrated an accuracy between 72.5% and 98.9%, with an interday and intraday precision below 8%, for all eCBs and eCB-like lipid mediators. The method exhibited minimal matrix effects, ranging from −15.0% to +9.0%. Most eCBs were stable under varying temperatures and storage conditions. However, drying time significantly affected the detected levels of 2-AG and 2-OG, suggesting that ex vivo biosynthesis may occur during drying. Interestingly, substantial differences in eCB levels were found between whole blood and plasma samples, emphasizing the importance of cellular components in eCB distribution. For example, 2-AG levels in whole blood ranged from 219–1,143 ng mL–1; plasma samples exhibited lower levels, ranging from 1.73–8.44 ng mL–1. These results highlight the need for standardized sampling methods to ensure accurate and consistent measurements of eCBs in both blood and plasma samples. While this work has significant implications for clinical eCB research, further investigation is necessary to understand the underlying mechanisms and clinical impact of eCB and eCB-like lipid mediators research.

Mungbean yellow mosaic India virus (MYMIV), the causal agent of yellow mosaic disease in soybean (Glycine max L. Merr.), causes substantial yield losses. This study used targeted metabolomics to profi...

The metabolomic composition of beetroot (Beta vulgaris L.) is strongly shaped by environment, supporting geographical origin authentication. This stud…

The Amazon rainforest is the largest tropical rainforest in the world. Amazonian Podzol soils, characteristic of this region, are known to store substantial amounts of organic carbon in both their sur...

Sulfur (S)-containing compounds can be unambiguously identified by their distinctive isotope patterns in mass spectrometry (MS) when the instrument has a mass resolution exceeding 500,000. However, many environmental research laboratories that perform nontargeted analysis rely on high-resolution mass spectrometry (HRMS) instruments, such as quadrupole time-of-flight mass spectrometry (QTOF MS). These HRMS instruments typically operate at a mass resolution of less than 50,000. At such limited resolution, confidently recognizing sulfur isotope patterns is challenging. This work develops a machine learning (ML) strategy for recognizing and predicting the number of S present using HRMS at a mass resolution as low as 25,000. We benchmarked our ML strategy on experimental data, where 200 S-containing standard compounds were mixed into complex environmental samples. In positive electrospray ionization (ESI) mode, our ML strategy achieved accuracies ranging from 87.4 to 95.0% for S recognition and accuracies ranging from 86.3 to 96.6% for S number prediction. Notably, the ML method performed similarly well in negative ESI mode. Our ML strategy was further evaluated on an external experimental water dataset where it correctly recognized the presence of S for all 24 previously reported 2-mercaptobenzothiazole disinfection byproducts (DBPs). The developed ML strategy was implemented into SulfurFinder, an R program, to facilitate automated data cleaning, S recognition, and S number prediction in HRMS data. SulfurFinder combined with HPLC-HRMS analysis of a wastewater sample tentatively identified 169 potential S-containing features. Of these, three were confirmed as S-containing pharmaceuticals. An additional S-containing drug was also putatively annotated using molecular networking. The development of SulfurFinder significantly boosts the capability of conventional HRMS to address the challenge of S recognition in the era of exposomics, supporting a wide range of environmental applications.

Interventional oncology procedures are commonly performed without a fundamental understanding of intratumoral mechanisms at the cellular and molecular levels. Mass spectrometry imaging (MSI) is a labe...

This study aimed to comparatively characterize the chemical composition of four commercial 3D-printed resin composites and quantify residual monomer e…

Phthalates and DINCH are non-persistent chemicals widely used in consumer products. In utero exposure to these compounds has been linked to adverse re…

The growing complexity and ubiquity of environmental contaminants demands sensitive, mechanistically informative tools for exposure science. Metabolom…

Crude oil constitutes one of the most complex mixtures in the world and its characterization is challenging yet absolutely essential in any upstream r…

The response surface methodology (RSM) was used to optimize the separation conditions in a supercritical fluid chromatography-mass spectrometry (SFC/M…

A fingernail clipping is a promising specimen for evaluating the medium-to-long term status of low-molecular weight hormones. However, the nail concen…

The aberrant arachidonic acid (ARA) metabolism may contribute to the pathogenesis of type 2 diabetes mellitus (T2DM), and some metabolites from ARA ma…

Mass spectrometry (MS), particularly mass spectrometry imaging (MSI), is an important analytical technique that facilitates the detection and spatial …