Tolerance of peanuts and tree nuts in Spanish children with exclusive sensitization to lipid transfer proteins.

Background: Allergy to peanuts and tree nuts is a common cause of food allergy in Spain, with lipid transfer proteins (LTP) being the most frequently recognized panallergen. LTP sensitization often leads to multiple food group sensitivities, resulting in overly restrictive diets that hinder patient's quality of life. This study aimed to assess the tolerance of peanuts and tree nuts (hazelnuts and walnuts) in children sensitized to LTP, potentially mitigating the need for such diets.

Pupil size change in agricultural workers exposed to pesticides.

Clinical Relevance: Pupil size evaluation using clinical examination may be important for detecting and monitoring individuals at risk of neurotoxic effects from chemical exposure, as it may enable early intervention and the implementation of preventive measures.

Background: This work aimed to investigate the association between pesticide exposure and pupil size. Pupil size is regulated by muscarinic and nicotinic receptors, and it is well-established that common pesticide chemicals disrupt this regulation.

Low-Cost EEG Multi-Subject Recording Platform for the Assessment of Students' Attention and the Estimation of Academic Performance in Secondary School.

The level of student attention in class greatly affects their academic performance. Teachers typically rely on visual inspection to react to students' attention in time, but this subjective method leads to inconsistencies across classes. Online education exacerbates the issue as students can turn off cameras and microphones to keep their own privacy.

Impairment of visual and neurologic functions associated with agrochemical use.

To determine whether exposure to occupational levels of agrochemicals is associated with a range of low- (contrast and colour) and higher-level visual functions, particularly the detection of global form and motion coherence. We compared the performance of workers exposed to occupational levels of pesticides and non-exposed individuals on visual tasks that measured colour discrimination (Farnsworth Munsell 100 and Lanthony D15 desaturated) and the contrast sensitivity function (1-16 cpd). Global form and motion detection thresholds were measured using Glass-pattern and global dot motion stimuli.

Development and validation of predictive models for unplanned hospitalization in the Basque Country: analyzing the variability of non-deterministic algorithms.

Background: The progressive ageing in developed countries entails an increase in multimorbidity. Population-wide predictive models for adverse health outcomes are crucial to address these growing healthcare needs. The main objective of this study is to develop and validate a population-based prognostic model to predict the probability of unplanned hospitalization in the Basque Country, through comparing the performance of a logistic regression model and three families of machine learning models.

The Real Practice Prescribing Antibiotics in Outpatients: A Failed Control Case Assessed through the Simulated Patient Method.

The first level of medical care provides the largest number of consultations for the most frequent diseases at the community level, including acute pharyngitis (AP), acute diarrhoea (AD) and uncomplicated acute urinary tract infections (UAUTIs). The inappropriate use of antibiotics in these diseases represents a high risk for the generation of antimicrobial resistance (AMR) in bacteria causing community infections. To evaluate the patterns of medical prescription for these diseases in medical offices adjacent to pharmacies, we used an adult simulated patient (SP) method representing the three diseases, AP, AD and UAUTI.

Analysis of the impact of social determinants and primary care morbidity on population health outcomes by combining big data: A research protocol.

Background: In recent years, different tools have been developed to facilitate analysis of social determinants of health (SDH) and apply this to health policy. The possibility of generating predictive models of health outcomes which combine a wide range of socioeconomic indicators with health problems is an approach that is receiving increasing attention. Our objectives are twofold: (1) to predict population health outcomes measured as hospital morbidity, taking primary care (PC) morbidity adjusted for SDH as predictors; and (2) to analyze the geographic variability of the impact of SDH-adjusted PC morbidity on hospital morbidity, by combining data sourced from electronic health records and selected operations of the National Statistics Institute ().

Spirometry and Smoking Cessation in Primary Care: The ESPIROTAB STUDY, A Randomized Clinical Trial.

Unlabelled: This study aims to evaluate the effect of regularly reporting spirometry results during smoking cessation counseling from a primary care physician on the quit rate in adult smokers.

Methods: A randomized, two-arm intervention study was conducted at six primary care centers. A total of 350 smokers, ≥18 years of age, who consulted their primary care physician, participated in the study.

Knowledge, attitudes, perceptions, and COVID-19 hesitancy in a large public university in Mexico city during the early vaccination rollout.

Background: Vaccination against COVID-19 is a primary tool for controlling the pandemic. However, the spread of vaccine hesitancy constitutes a significant threat to reverse progress in preventing the disease. Studies conducted in Mexico have revealed that vaccination intention in Mexico among the general population ranges from 62 to 82%.

Multidimensional adaptive P-splines with application to neurons' activity studies.

The receptive field (RF) of a visual neuron is the region of the space that elicits neuronal responses. It can be mapped using different techniques that allow inferring its spatial and temporal properties. Raw RF maps (RFmaps) are usually noisy, making it difficult to obtain and study important features of the RF.

Artificial Intelligence on FDG PET Images Identifies Mild Cognitive Impairment Patients with Neurodegenerative Disease.

The purpose of this project is to develop and validate a Deep Learning (DL) FDG PET imaging algorithm able to identify patients with any neurodegenerative diseases (Alzheimer's Disease (AD), Frontotemporal Degeneration (FTD) or Dementia with Lewy Bodies (DLB)) among patients with Mild Cognitive Impairment (MCI). A 3D Convolutional neural network was trained using images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI dataset used for the model training and testing consisted of 822 subjects (472 AD and 350 MCI).

A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data.

High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data.

Fast Energy Dependent Scatter Correction for List-Mode PET Data.

Improvements in energy resolution of modern positron emission tomography (PET) detectors have created opportunities to implement energy-based scatter correction algorithms. Here, we use the energy information of auxiliary windows to estimate the scatter component. Our method is directly implemented in an iterative reconstruction algorithm, generating a scatter-corrected image without the need for sinograms.

Assessment of Toxic Metals (Al, Cd, Pb) and Trace Elements (B, Ba, Co, Cr, Cu, Fe, Mn, Mo, Li, Zn, Ni, Sr, V) in the Common Kestrel (Falco tinnunculus) from the Canary Islands (Spain).

The monitoring of trace elements and toxic metals in apical predators of the trophic chain provides data on the degree of contamination in ecosystems. The common kestrel is one of the most interesting raptors in this respect in the Canary Islands; therefore, the study of the levels of trace elements and toxic metals in this species is of much scientific value. The content of trace elements and toxic metals (B, Ba, Co, Cr, Cu, Fe, Mn, Mo, Li, Zn, Ni, Sr, V, Al, Cd, Pb) was determined in the liver, muscle, and feathers of 200 specimens of common kestrel carcasses (Falco tinnunculus canariensis) from Tenerife.

2D feasibility study of joint reconstruction of attenuation and activity in limited angle TOF-PET.

Several research groups are studying organ-dedicated limited angle positron emission tomography (PET) systems to optimize performance-cost ratio, sensitivity, access to the patient and/or flexibility. Often open systems are considered, typically consisting of two detector panels of various sizes. Such systems provide incomplete sampling due to limited angular coverage and/or truncation, which leads to artefacts in the reconstructed activity images.

Simulation Study of a Frame-Based Motion Correction Algorithm for Positron Emission Imaging.

Positron emission tomography (PET) is a functional non-invasive imaging modality that uses radioactive substances (radiotracers) to measure changes in metabolic processes. Advances in scanner technology and data acquisition in the last decade have led to the development of more sophisticated PET devices with good spatial resolution (1-3 mm of full width at half maximum (FWHM)). However, there are involuntary motions produced by the patient inside the scanner that lead to image degradation and potentially to a misdiagnosis.

Onset of Nut Allergy in a Pediatric Cohort: Clinical and Molecular Patterns in the AFRUSEN Study.

Background And Objective: Nut allergy is a growing problem, yet little is known about its onset in children. Objective: To characterize the onset of nut allergy in children in southern Europe.

Methods: The study population comprised consecutive patients up to 14 years of age who visited allergy departments with an initial allergic reaction to peanut, tree nut, or seed.

COVID-19: Clouds Over the Antimicrobial Resistance Landscape.

In recent years, the increase in antimicrobial resistance (AMR) has been recognized as a real threat to human and animal health. It is a problem that has been given the highest priority, uniting nations in the fight against its causes and effects. Among the actions that have been implemented are: clinical and microbiological surveillance, promotion of rational and controlled use of antibiotics, AMR stewardship programs in hospitals, development of tools for rapid diagnosis of infectious diseases to establish prompt and adequate treatment, and radically improving vaccination strategies.