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Resident memory T cells (T RM ) positioned within the respiratory tract are probably required to limit SARS-CoV-2 spread and COVID-19. Importantly, T RM are mostly non-recirculating, which reduces the window of opportunity to examine these cells in the blood as they move to the lung parenchyma. Here, we identify circulating virus-specific T cell responses during acute infection with functional, migratory and apoptotic patterns modulated by viral proteins and associated with clinical outcome. Disease severity is associated predominantly with IFNγ and IL-4 responses, increased responses against S peptides and apoptosis, whereas non-hospitalized patients have increased IL-12p70 levels, degranulation in response to N peptides and SARS-CoV-2-specific CCR7 + T cells secreting IL-10. In convalescent patients, lung-T RM are frequently detected even 10 months after initial infection, in which contemporaneous blood does not reflect tissue-resident profiles. Our study highlights a balanced anti-inflammatory antiviral response associated with a better outcome and persisting T RM cells as important for future protection against SARS-CoV-2 infection. Lung resident memory T (T RM ) cells are important for protection from viral infection in the lungs. Here the authors use paired lung biopsy material and blood to characterize T cell responses in patients with COVID-19 over time and find persistence of antiviral lung T RM cells that might be important to limit reinfection.

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient’s immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome.

Graves' disease (GD) involves the presence of agonistic auto-antibodies against the thyrotropin receptor (TSHR), which are responsible for the clinical symptoms. While failure of TSHR tolerance is central to GD pathogenesis, the process leading to this failure remains poorly understood. Two mechanisms intimately linked to tolerance have been proposed to explain the association of SNPs located in intron 1 to GD: (1) differential alternative splicing in the thyroid; and (2) modulation of expression in the thymus. To elucidate the relative contribution to these two mechanisms to GD pathogenesis, we analyzed the level of full-length and ST4 and ST5 isoform expression in the thyroid ( = 49) and thymus ( = 39) glands, and the influence of intron 1-associated SNPs on such expression. The results show that: (1) the level of flTSHR and ST4 expression in the thymus was unexpectedly high (20% that of the thyroid); (2) while flTSHR is the predominant isoform, the levels are similar to ST4 (ratio flTSHR/ST4 = 1.34 in the thyroid and ratio flTSHR/ST4 in the thymus = 1.93); (3) next-generation sequencing confirmed the effect of the TSHR intron 1 polymorphism on TSHR expression in the thymus with a bias of 1.5 ± 0.2 overexpression of the protective allele in the thymus compared to the thyroid; (4) GD-associated intron 1 SNPs did not influence alternative splicing of ST4 and ST5 in the thyroid and thymus; and (5) three-color confocal imaging showed that TSHR is associated with both thymocytes, macrophages, and dendritic cells in the thymus. Our findings confirm the effect of intron 1 polymorphisms on thymic TSHR expression and we present evidence against an effect on the relative expression of isoforms. The high level of ST4 expression in the thymus and its distribution within the tissue suggest that this would most likely be the isoform that induces central tolerance to TSHR thus omitting most of the hinge and transmembrane portion. The lack of central tolerance to a large portion of TSHR may explain the relatively high frequency of autoimmunity related to TSHR and its clinical consequence, GD.

The presence and localization of plant metabolites are indicative of physiological processes, e.g., under biotic and abiotic stress conditions. Further, the chemical composition of plant parts is related to their quality as food or for medicinal applications. Mass spectrometry imaging (MSI) has become a popular analytical technique for exploring and visualizing the spatial distribution of plant molecules within a tissue. This review provides a summary of mass spectrometry methods used for mapping and identifying metabolites in plant tissues. We present the benefits and the disadvantages of both vacuum and ambient ionization methods, considering direct and indirect approaches. Finally, we discuss the current limitations in annotating and identifying molecules and perspectives for future investigations.

The thyroid functions as an apex endocrine organ that controls growth, differentiation and metabolism 1 , and thyroid diseases comprise the most common endocrine disorders 2 . Nevertheless, high-resolution views of the cellular composition and signals that govern the thyroid have been lacking 3 , 4 . Here, we show that Notch signalling controls homeostasis and thermoregulation in adult mammals through a mitochondria-based mechanism in a subset of thyrocytes. We discover two thyrocyte subtypes in mouse and human thyroids, identified in single-cell analyses by different levels of metabolic activity and Notch signalling. Therapeutic antibody blockade of Notch in adult mice inhibits a thyrocyte-specific transcriptional program and induces thyrocyte defects due to decreased mitochondrial activity and ROS production. Thus, disrupting Notch signalling in adult mice causes hypothyroidism, characterized by reduced levels of circulating thyroid hormone and dysregulation of whole-body thermoregulation. Inducible genetic deletion of Notch1 and 2 in thyrocytes phenocopies this antibody-induced hypothyroidism, establishing a direct role for Notch in adult murine thyrocytes. We confirm that hypothyroidism is enriched in children with Alagille syndrome, a genetic disorder marked by Notch mutations, suggesting that these findings translate to humans. Mosteiro et al. show that inhibition of Notch, a signaling pathway frequently associated with cell-fate decisions during development, impairs thyrocyte homeostasis in an active subset of thyrocytes in adult mice through mitochondrial dysfunction and decreased ROS, thereby causing hypothyroidism.

BackgroundTwo years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited.ObjectivesTo measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively.Findings1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests.ConclusionsLaboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible.

Resident memory T cells (T RM ) positioned within the respiratory tract are probably required to limit SARS-CoV-2 spread and COVID-19. Importantly, T RM are mostly non-recirculating, which reduces the window of opportunity to examine these cells in the blood as they move to the lung parenchyma. Here, we identify circulating virus-specific T cell responses during acute infection with functional, migratory and apoptotic patterns modulated by viral proteins and associated with clinical outcome. Disease severity is associated predominantly with IFNγ and IL-4 responses, increased responses against S peptides and apoptosis, whereas non-hospitalized patients have increased IL-12p70 levels, degranulation in response to N peptides and SARS-CoV-2-specific CCR7 + T cells secreting IL-10. In convalescent patients, lung-T RM are frequently detected even 10 months after initial infection, in which contemporaneous blood does not reflect tissue-resident profiles. Our study highlights a balanced anti-inflammatory antiviral response associated with a better outcome and persisting T RM cells as important for future protection against SARS-CoV-2 infection.

Cassava ( Manihot esculenta Crantz) biofortification with provitamin A carotenoids is an ongoing process that aims to alleviate vitamin A deficiency. The moderate content of provitamin A carotenoids achieved so far limits the contribution to providing adequate dietary vitamin A levels. Strategies to increase carotenoid content focused on genes from the carotenoids biosynthesis pathway. In recent years, special emphasis was given to ORANGE protein (OR), which promotes the accumulation of carotenoids and their stability in several plants. The aim of this work was to identify, characterize and investigate the role of OR in the biosynthesis and stabilization of carotenoids in cassava and its relationship with phytoene synthase (PSY), the rate-limiting enzyme of the carotenoids biosynthesis pathway. Gene and protein characterization of OR, expression levels, protein amounts and carotenoids levels were evaluated in roots of one white (60444) and two yellow cassava cultivars (GM5309-57 and GM3736-37). Four OR variants were found in yellow cassava roots. Although comparable expression was found for three variants, significantly higher OR protein amounts were observed in the yellow varieties. In contrast, cassava PSY1 expression was significantly higher in the yellow cultivars, but PSY protein amount did not vary. Furthermore, we evaluated whether expression of one of the variants, MeOR_X1 , affected carotenoid accumulation in cassava Friable Embryogenic Callus (FEC). Overexpression of maize PSY1 alone resulted in carotenoids accumulation and induced crystal formation. Co-expression with MeOR_X1 led to greatly increase of carotenoids although PSY1 expression was high in the co-expressed FEC. Our data suggest that posttranslational mechanisms controlling OR and PSY protein stability contribute to higher carotenoid levels in yellow cassava. Moreover, we showed that cassava FEC can be used to study the efficiency of single and combinatorial gene expression in increasing the carotenoid content prior to its application for the generation of biofortified cassava with enhanced carotenoids levels.