Validation and calibration of models to estimate photosynthetically active radiation considering different time scales and sky conditions

Photosynthetically Active Radiation (PAR) is a fundamental parameter for developing plant productivity models. Nevertheless, instrumentation for measuring PAR and to record it is scarce at conventional meteorological stations. Several procedures have therefore been proposed for PAR estimation. In this work, 21 previously published analytical models that correlate PAR with easily available meteorological parameters are collected. Although longer time scales were considered in the original publications, a minute range was applied in this work to calibrate the PAR models. In total, more than 10 million input records were gathered from the SURFRAD station network from a 10-year long time series with data frequencies recorded every 1 min. The models were calibrated both globally, using data from all stations and locally, with data from each station. After calibration, the models were validated for minute, hourly and daily data, obtaining low fitting errors at the different stations in all cases, both when using the globally calibrated models and with the models calibrated for each location. Although the PAR results in general improved for locally calibrated models, the use of local models is not justified, since the global models presented offered very satisfactory PAR results for the different climatic conditions where the meteorological stations are located. Thus, PAR estimation model should then be selected, solely considering the meteorological variables available at the specific location. When applying the globally calibrated models to input data classified according to sky conditions (from clear to overcast), the PAR models continued to perform satisfactorily, although the error statistics of some models for overcast skies worsened.The authors gratefully acknowledge the financial support provided by the Spanish Ministry of Science & Innovation under the I + D+i state program “Challenges Research Projects” (Ref. RTI2018-098900-B-I00)

Transcriptomics reveals a distinct metabolic profile in T cells from severe allergic asthmatic patients

The reasons behind the onset and continuation of chronic inflammation in individuals with severe allergies are still not understood. Earlier findings indicated that there is a connection between severe allergic inflammation, systemic metabolic alterations and impairment of regulatory functions. Here, we aimed to identify transcriptomic alterations in T cells associated with the degree of severity in allergic asthmatic patients. T cells were isolated from severe (n = 7) and mild (n = 9) allergic asthmatic patients, and control (non-allergic, non-asthmatic healthy) subjects (n = 8) to perform RNA analysis by Affymetrix gene expression. Compromised biological pathways in the severe phenotype were identified using significant transcripts. T cells' transcriptome of severe allergic asthmatic patients was distinct from that of mild and control subjects. A higher count of differentially expressed genes (DEGs) was observed in the group of individuals with severe allergic asthma vs. control (4,924 genes) and vs. mild (4,232 genes) groups. Mild group also had 1,102 DEGs vs. controls. Pathway analysis revealed alterations in metabolism and immune response in the severe phenotype. Severe allergic asthmatic patients presented downregulation in genes related to oxidative phosphorylation, fatty acid oxidation and glycolysis together with increased expression of genes coding inflammatory cytokines (e.g. IL-19, IL-23A and IL-31). Moreover, the downregulation of genes involved in TGFβ pathway together with a decreased tendency on the percentage of T regulatory cell (CD4 + CD25+), suggest a compromised regulatory function in severe allergic asthmatic patients. This study demonstrates a transcriptional downregulation of metabolic and cell signalling pathways in T cells of severe allergic asthmatic patients associated with diminished regulatory T cell function. These findings support a link between energy metabolism of T cells and allergic asthmatic inflammation

Role of the first WHO mutation catalogue in the diagnosis of antibiotic resistance in Mycobacterium tuberculosis in the Valencia Region, Spain: a retrospective genomic analysis

9 páginas, 2 figuras, 1 tablaBackground: In June, 2021, WHO published the most complete catalogue to date of resistance-conferring mutations in Mycobacterium tuberculosis. Here, we aimed to assess the performance of genome-based antimicrobial resistance prediction using the catalogue and its potential for improving diagnostics in a real low-burden setting. Methods: In this retrospective population-based genomic study M tuberculosis isolates were collected from 25 clinical laboratories in the low-burden setting of the Valencia Region, Spain. Culture-positive tuberculosis cases reported by regional public health authorities between Jan 1, 2014, and Dec 31, 2016, were included. The drug resistance profiles of these isolates were predicted by the genomic identification, via whole-genome sequencing (WGS), of the high-confidence resistance-causing variants included in the catalogue and compared with the phenotype. We determined the minimum inhibitory concentration (MIC) of the isolates with discordant resistance profiles using the resazurin microtitre assay. Findings: WGS was performed on 785 M tuberculosis complex culture-positive isolates, and the WGS resistance prediction sensitivities were: 85·4% (95% CI 70·8–94·4) for isoniazid, 73·3% (44·9–92·2) for rifampicin, 50·0% (21·1–78·9) for ethambutol, and 57·1% (34·0–78·2) for pyrazinamide; all specificities were more than 99·6%. Sensitivity values were lower than previously reported, but the overall pan-susceptibility accuracy was 96·4%. Genotypic analysis revealed that four phenotypically susceptible isolates carried mutations (rpoB Leu430Pro and rpoB Ile491Phe for rifampicin and fabG1 Leu203Leu for isoniazid) known to give borderline resistance in standard phenotypic tests. Additionally, we identified three putative resistance-associated mutations (inhA Ser94Ala, katG Leu48Pro, and katG Gly273Arg for isoniazid) in samples with substantially higher MICs than those of susceptible isolates. Combining both genomic and phenotypic data, in accordance with the WHO diagnostic guidelines, we could detect two new multidrug-resistant cases. Additionally, we detected 11 (1·6%) of 706 isolates to be monoresistant to fluoroquinolone, which had been previously undetected. Interpretation: We showed that the WHO catalogue enables the detection of resistant cases missed in phenotypic testing in a low-burden region, thus allowing for better patient-tailored treatment. We also identified mutations not included in the catalogue, relevant at the local level. Evidence from this study, together with future updates of the catalogue, will probably lead in the future to the partial replacement of culture testing with WGS-based drug susceptibility testing in our setting. Funding: European Research Council and the Spanish Ministerio de Ciencia.This project received funding from the European Research Council under the European Union’s Horizon 2020 Research and Innovation Program Grant 101001038 (TB-RECONNECT; awarded to IC), from Ministerio de Ciencia (Spanish Government) Project PID2019-104477RB-I00 (awarded to IC), and from Generalitat Valenciana Project AICO/2018/113 (awarded to IC). AMG-M is funded by a Formación deProfesorado Universitario grant programme (FPU19/04562) from Ministerio de Universidades (Spanish Government). IC is also supported by the European Commission–NextGenerationEU, through Centro Superior de Investigaciones Científicas Global Health Platform (PTI Salud Global). We thank all the members of the Valencia RegionTuberculosis Working Group