Study protocol of a randomized controlled trial to assess safety of teleconsultation compared with face-to-face consultation: the ECASeT study.

BACKGROUND: The use of remote consultation modalities has exponentially grown in the past few years, particularly since the onset of the COVID-19 pandemic. Although a huge body of the literature has described the use of phone (tele) and video consultations, very few of the studies correspond to randomized controlled trials, and none of them has assessed the safety of these consultation modalities as the primary objective. The primary objective of this trial was to assess the safety of remote consultations (both video and teleconsultation) in the follow-up of patients in the hospital setting. METHODS: Multicenter, randomized controlled trial being conducted in four centers of an administrative healthcare area in Catalonia (North-East Spain). Participants will be screened from all individuals, irrespective of age and sex, who require follow-up in outpatient consultations of any of the departments involved in the study. Eligibility criteria have been established based on the local guidelines for screening patients for remote consultation. Participants will be randomly allocated into one of the two study arms: conventional face-to-face consultation (control) and remote consultation, either teleconsultation or video consultation (intervention). Routine follow-up visits will be scheduled at a frequency determined by the physician based on the diagnostic and therapy of the baseline disease (the one triggering enrollment). The primary outcome will be the number of adverse reactions and complications related to the baseline disease. Secondary outcomes will include non-scheduled visits and hospitalizations, as well as usability features of remote consultations. All data will either be recorded in an electronic clinical report form or retrieved from local electronic health records. Based on the complications and adverse reaction rates reported in the literature, we established a target sample size of 1068 participants per arm. Recruitment started in May 2022 and is expected to end in May 2024. DISCUSSION: The scarcity of precedents on the assessment of remote consultation modalities using randomized controlled designs challenges making design decisions, including recruitment, selection criteria, and outcome definition, which are discussed in the manuscript. TRIAL REGISTRATION: NCT05094180. The items of the WHO checklist for trial registration are available in Additional file 1. Registered on 24 November 2021.

Prevalence of Listeria monocytogenes in RTE Meat Products of Quevedo (Ecuador).

Listeria monocytogenes is a foodborne pathogen that causes listeriosis and can be a problem in areas where meat products are sold at unregulated storage temperatures. In this work, the prevalence of L. monocytogenes was determined in the five most widely traded meat products in the province of Quevedo (Ecuador): bacon, "chorizo paisa", grilled hamburger meat, mortadella, and salami. A total of 1000 samples of these products were analyzed in two seasons of the year (dry season/rainy season). All L. monocytogenes isolates were confirmed by PCR with primers designed for the iap gene. Furthermore, the positive samples were quantified for L. monocytogenes. Of the 1000 meat products analyzed, 163 were positive for L. monocytogenes (16.3%). The prevalence of L. monocytogenes in the two seasons in different meat products was as follows: 22.5% in mortadella, 19% in hamburger meat, 15% in bacon, 14.5% in chorizo paisa and 10.5% in salami. In addition, the concentration of L. monocytogenes in most of the positive samples was in the range of 4-6 log CFU/g or even higher. The results show the need for improvements in the hygienic measures and meat storage temperatures in Quevedo (Ecuador) to avoid risks of foodborne listeriosis.

A Two-Filter Approach for State Estimation Utilizing Quantized Output Data.

Filtering and smoothing algorithms are key tools to develop decision-making strategies and parameter identification techniques in different areas of research, such as economics, financial data analysis, communications, and control systems. These algorithms are used to obtain an estimation of the system state based on the sequentially available noisy measurements of the system output. In a real-world system, the noisy measurements can suffer a significant loss of information due to (among others): (i) a reduced resolution of cost-effective sensors typically used in practice or (ii) a digitalization process for storing or transmitting the measurements through a communication channel using a minimum amount of resources. Thus, obtaining suitable state estimates in this context is essential. In this paper, Gaussian sum filtering and smoothing algorithms are developed in order to deal with noisy measurements that are also subject to quantization. In this approach, the probability mass function of the quantized output given the state is characterized by an integral equation. This integral was approximated by using a Gauss-Legendre quadrature; hence, a model with a Gaussian mixture structure was obtained. This model was used to develop filtering and smoothing algorithms. The benefits of this proposal, in terms of accuracy of the estimation and computational cost, are illustrated via numerical simulations.

Reactive oxygen species, essential molecules, during plant-pathogen interactions.

Reactive oxygen species (ROS) are continually generated as a consequence of the normal metabolism in aerobic organisms. Accumulation and release of ROS into cell take place in response to a wide variety of adverse environmental conditions including salt, temperature, cold stresses and pathogen attack, among others. In plants, peroxidases class III, NADPH oxidase (NOX) locates in cell wall and plasma membrane, respectively, may be mainly enzymatic systems involving ROS generation. It is well documented that ROS play a dual role into cells, acting as important signal transduction molecules and as toxic molecules with strong oxidant power, however some aspects related to its function during plant-pathogen interactions remain unclear. This review focuses on the principal enzymatic systems involving ROS generation addressing the role of ROS as signal molecules during plant-pathogen interactions. We described how the chloroplasts, mitochondria and peroxisomes perceive the external stimuli as pathogen invasion, and trigger resistance response using ROS as signal molecule.