Regarding Bioanalysis Lasting a Few Minutes: Automated Cooling-SPME and Fast-GC for Urinary 2-Phenyl-2-Propanol Monitoring.

An innovative SPME head space GC-MS method, in cooling mode, using a fully automated routine, was developed to detect 2-phenyl-2-propanol, a representative urinary metabolite of cumene. Following an acid hydrolysis and derivatization step with lowered quantities of reagents, acetic anhydride and pyridine, a 30 μm polydimethylsiloxane SPME fiber was used to sample derivatized 2-phenyl-2-propanol, such as benzenemethanol,α,α-dimethyl-acetate, from the headspace. Performances of the method, optimized through experimental design, provide an LOD of 0.

Accidental bufotoxin intoxication: Arenobufagin identification by liquid chromatography coupled to mass spectrometry.

Since ancient times, poisoning, even serious poisoning, has been known to occur during nature walks. Intentional or unintentional ingestion of toxins of animal origin is one of the possible causes of poisoning. Bufadienolide poisoning is a critical case.

Comparison of ELISA with automated ECLIA for IL-6 determination in COVID-19 patients: An Italian real-life experience.

Objectives: Coronavirus disease 2019 (COVID-19) has a wide spectrum of clinical severity. A cytokine storm is associated with COVID-19 severity. Of these, IL-6 is significantly associated with higher mortality and is also a marker for predicting disease prognosis.

Evaluation of the risk of occupational exposure to antineoplastic drugs in healthcare sector: part II - the application of the FMECA method to compare manual vs automated preparation.

Healthcare workers handling antineoplastic drugs (ADs) in preparation units run the risk of occupational exposure to contaminated surfaces and associated mutagenic, teratogenic, and oncogenic effects of those drugs. To minimise this risk, automated compounding systems, mainly robots, have been replacing manual preparation of intravenous drugs for the last 20 years now, and their number is on the rise. To evaluate contamination risk and the quality of the working environment for healthcare workers preparing ADs, we applied the Failure Mode Effects and Criticality Analysis (FMECA) method to compare the acceptable risk level (ARL), based on the risk priority number (RPN) calculated from five identified failure modes, with the measured risk level (MRL).