Machine learning mathematical models for incidence estimation during pandemics.

Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread; this leads to significant and systematic under-reporting of the real incidence. Here, we propose a machine learning approach to estimate the incidence of a pandemic in real-time, using reported cases and the overall test rate.

Real-life reliability of plasma pTau181, Aβ/Aβ, and pTau181/Aβ measured by Lumipulse G600II in predicting cerebrospinal fluid amyloid status.

Background: Alzheimer's disease (AD) is the most common neurodegenerative dementia, with diagnosis traditionally reliant on clinical criteria. Cerebrospinal fluid (CSF) biomarkers like pTau181 and Aβ/Aβ ratio significantly improve diagnostic accuracy but are invasive. Plasma biomarkers measured by automated assays offer a non-invasive alternative.

Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors.

In many applications, complex biological phenomena can be reproduced via structured mathematical models, which depend on numerous biotic and abiotic input parameters, whose effect on model outputs can be of paramount importance. The calibration of model parameters is crucial to obtain the best fit between simulated and experimental data. Sensitivity analysis and uncertainty quantification constitute essential tools in the field of biological systems modeling.

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.

Keratinous and corneous-based products towards circular bioeconomy: A research review.

Keratins and corneous proteins are key components of biomaterials used in a wide range of applications and are potential substitutes for petrochemical-based products. Horns, hooves, feathers, claws, and similar animal tissues are abundant sources of α-keratin and corneous β-proteins, which are by-products of the food industry. Their close association with the meat industry raises environmental and ethical concerns regarding their disposal.