Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Estado-da-arte da simulação da taxa de fixação de carbono de ecossistemas tropicais State-of-the-art of the simulation of carbon fixation rates by tropical ecosystems

Este trabalho avalia o estado-da-arte de modelos de simulação da taxa de fixação de carbono, ou produção primária liquida (NPP), de ecossistemas tropicais em duas configurações diagnósticas (simulação em sítios micrometeorológicos e simulação forçada por dados climáticos e por produtos de sensoriamento remoto) e uma prognóstica (simulação por um modelo acoplado clima-vegetação). Os resultados indicam que os modelos de estimativa de NPP atingiram capacidade de fazer estimativas não-viesadas de valores médios regionais de NPP, tanto no modo diagnóstico, quanto no modo prognóstico, com erros inferiores a 5%, enquanto o valor esperado do erro em cada sítio é inferior a 10% no modo diagnóstico e inferior a 20% no modo prognóstico. Os modelos estado-da-arte são capazes de monitorar a taxa de fixação de carbono por ecossistemas tropicais de maneira rotineira, sendo esperados baixos erros para essas estimativas.<br>This work evaluates the state-of-the-art of the simulation of carbon fixation rates, or net primary production (NPP) by tropical ecosystems in two diagnostic configurations (simulation at micrometeorological sites and simulation forced by climate datasets and remote sensing products) and one prognostic (simulation by a coupled climate-biosphere model). The results indicate that the NPP simulation models are capable of unbiased estimates of average regional values of NPP, both in diagnostic and in prognostic mode, with errors smaller than 5%, while the expected value of the error in each site is smaller than 10% in the diagnostic mode and smaller than 20% in the prognostic mode. State-of-the-art models are capable of routinely monitoring the net primary production of tropical ecosystems, with low errors expected for these estimates

Three-Dimensional Coordinate Calibration Models for Augmented Reality Applications in Indoor Industrial Environments

The calibration of three-dimensional (3D) coordinates in augmented reality systems is a complex activity. It involves the recognition of environmental characteristics and technology that models the 3D space of the device, determining its position and orientation. Single markers suffer from numerical instability, particularly when they are small within the camera image. In the industrial environment, it is common for augmented reality applications to cover large spaces, making it difficult to maintain attributes such as precision and accuracy. To address this issue, our study proposes a two-step calibration model that leverages multiple markers for accurate localization in a larger indoor environment. We developed the calibration model using Unity3D, Mixed Reality ToolKit, and Vuforia and evaluated it in terms of precision and accuracy in a proof of concept using the MS Hololens device. Our findings reveal that employing two markers significantly reduces angular discrepancies between points in the real and augmented environments. Moreover, our results underscore that registration accuracy improves as the number of calibration points increases. The results show improvements in determining the axes that define the 3D space, with a direct influence on the position of the points observed in the experiment