Mitigating matrix effects in oil and gas wastewater analysis: LC-MS/MS method for ethanolamines.

The high salinity and organic content in oil and gas wastewaters can cause ion suppression during liquid chromatography mass spectrometry (LC/MS) analysis, diminishing the sensitivity and accuracy of measurements in available methods. This suppression is severe for low molecular weight organic compounds such as ethanolamines (, monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA), -methyldiethanolamine (MDEA), and ,-ethyldiethanolamine (EDEA)). Here, we deployed solid phase extraction (SPE), mixed-mode LC, triple quadrupole MS with positive electrospray ionization (ESI), and a suite of stable isotope standards (, one per target compound) to correct for ion suppression by salts and organic matter, SPE losses, and instrument variability.

Deep learning MRI models for the differential diagnosis of tumefactive demyelination versus -wildtype glioblastoma.

Background And Purpose: Diagnosis of tumefactive demyelination can be challenging. The diagnosis of indeterminate brain lesions on MRI often requires tissue confirmation via brain biopsy. Noninvasive methods for accurate diagnosis of tumor and non-tumor etiologies allows for tailored therapy, optimal tumor control, and a reduced risk of iatrogenic morbidity and mortality.

Exploring fatigue in Marfan and hypermobile Ehlers-Danlos syndromes: an analytical cross-sectional study in two Italian healthcare centres.

Objective: This study investigates the prevalence and underlying factors of fatigue in individuals with Marfan syndrome (MFS) and hypermobile Ehlers-Danlos syndromes (hEDS), highlighting the necessity for focused research on this symptom within these patient populations.

Design: Cross-sectional, multicentre study.

Setting: Data were collected from participants diagnosed with MFS or hEDS across multiple healthcare centres.