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To describe the laboratory parameters and biomarkers of the cytokine storm syndrome associated with severe and fatal COVID-19 cases. A search with standardized descriptors and synonyms was performed on November 28.sup.th, 2020 of the MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, LILACS, and IBECS to identify studies of interest. Grey literature searches and snowballing techniques were additionally utilized to identify yet-unpublished works and related citations. Two review authors independently screened the retrieved titles and abstracts, selected eligible studies for inclusion, extracted data from the included studies, and then assessed the risk of bias using the Newcastle-Ottawa Scale. Eligible studies were those including laboratory parameters-including serum interleukin-6 levels-from mild, moderate, or severe COVID-19 cases. Laboratory parameters, such as interleukin-6, ferritin, hematology, C-Reactive Protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase, creatinine, and D-dimer, were extracted from the studies. Meta-analyses were conducted using the laboratory data to estimate mean differences with associated 95% confidence intervals. This review points to interleukin-6, ferritin, leukocytes, neutrophils, lymphocytes, platelets, C-Reactive Protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase, creatinine, and D-dimer as important biomarkers of cytokine storm syndrome. Elevated levels of interleukin-6 and hyperferritinemia should be considered as red flags of systemic inflammation and poor prognosis in COVID-19.

KEY MESSAGE: Genome resolution of a major QTL associated with the Rk locus in cowpea for resistance to root-knot nematodes has significance for plant breeding programs and R gene characterization. Cowpea (Vigna unguiculata L. Walp.) is a susceptible host of root-knot nematodes (Meloidogyne spp.) (RKN), major plant-parasitic pests in global agriculture. To date, breeding for host resistance in cowpea has relied on phenotypic selection which requires time-consuming and expensive controlled infection assays. To facilitate marker-based selection, we aimed to identify and map quantitative trait loci (QTL) conferring the resistance trait. One recombinant inbred line (RIL) and two F2:3 populations, each derived from a cross between a susceptible and a resistant parent, were genotyped with genome-wide single nucleotide polymorphism (SNP) markers. The populations were screened in the field for root-galling symptoms and/or under growth-chamber conditions for nematode reproduction levels using M. incognita and M. javanica biotypes. One major QTL was mapped consistently on linkage group VuLG11 of each population. By genotyping additional cowpea lines and near-isogenic lines derived from conventional backcrossing, we confirmed that the detected QTL co-localized with the genome region associated with the Rk locus for RKN resistance that has been used in conventional breeding for many decades. This chromosomal location defined with flanking markers will be a valuable target in marker-assisted breeding and for positional cloning of genes controlling RKN resistance.

Ash fall layers and vitroclastic-carrying sediments distributed throughout the entire Permian stratigraphic range of the Parana Basin (Brazil and Uruguay) occur in the Tubarao Supergroup (Rio Bonito Formation) and the Passa Dois Group (Irati, Estrada Nova/Teresina, Corumbatai, and Rio do Rasto Formations), which constitute the Gondwana 1 Supersequence. U-Pb zircon ages, acquired by SHRIMP and isotope-dissolution thermal ionization mass spectrometer (ID-TIMS) from tuffs within the Mangrullo and Yaguari Formations of Uruguay, are compatible with a correlation with the Irati and parts of the Teresina and Rio do Rasto Formations, respectively, of Brazil. U-Pb zircon ages suggest maximum depositional ages for the samples: (1) Rio Bonito Formation: ages ranging from 295.8±3.1 to 304.0±5.6 Ma (Asselian, lowermost Permian), consistent with the age range of the Protohaploxypinus goraiensis subzone; (2) Irati Formation: ages ranging from 279.9±4.8 to 280.0±3.0 Ma (Artinskian, Middle Permian), consistent with the occurrence of species of the Lueckisporites virkkiae zone; (3) Rio do Rasto Formation: ages ranging from 266.7±5.4 to 274.6±6.3 Ma (Wordian to Roadian, Middle Permian). All the SHRIMP U-Pb zircon ages are consistent with their superimposition order in the stratigraphy, the latest revisions to the Permian timescale (International Commission of Stratigraphy, 2018 version), and the most recent appraisals of biostratigraphic data. The ID-TIMS U-Pb zircon ages from the Corumbatai Formation suggest that U-Pb ages may be >10% younger than interpreted biostratigraphic ages.

Polystyrene and poly(vinyl alcohol) nanofibres containing cellulose nanocrystals (CNCs) were successfully produced by electrospinning. Knowledge of the local orientation of CNCs in electrospun fibres is critical to understand and exploit their mechanical properties. The orientation of CNCs in these electrospun fibres was investigated using transmission electron microscopy (TEM) and Raman spectroscopy. A Raman band located at ~1095 cm⁻¹, associated with the C–O ring stretching of the cellulose backbone, was used to quantify the orientation of the CNCs within the fibres. Raman spectra were fitted using a theoretical model to characterize the extent of orientation. From these data, it is observed that the CNCs have little orientation along the direction parallel to the axis of the fibres. Evidences for both oriented and non-oriented regions of CNCs in the fibres are presented from TEM images of nanofibres. These results contradict previously published work in this area and micromechanical modelling calculations suggest a uniform orientation of CNCs in electrospun polymer fibres. It is demonstrated that this explains why the mechanical properties of electrospun fibre mats containing CNCs are not always the same as that would be expected for a fully oriented system.

Key messageWe propose using probability concepts from Bayesian models to leverage a more informed decision-making process toward cultivar recommendation in multi-environment trials.Statistical models that capture the phenotypic plasticity of a genotype across environments are crucial in plant breeding programs to potentially identify parents, generate offspring, and obtain highly productive genotypes for target environments. In this study, our aim is to leverage concepts of Bayesian models and probability methods of stability analysis to untangle genotype-by-environment interaction (GEI). The proposed method employs the posterior distribution obtained with the No-U-Turn sampler algorithm to get Hamiltonian Monte Carlo estimates of adaptation and stability probabilities. We applied the proposed models in two empirical tropical datasets. Our findings provide a basis to enhance our ability to consider the uncertainty of cultivar recommendation for global or specific adaptation. We further demonstrate that probability methods of stability analysis in a Bayesian framework are a powerful tool for unraveling GEI given a defined intensity of selection that results in a more informed decision-making process toward cultivar recommendation in multi-environment trials.

The use of adhesive bonding in diverse industries such as the automotive and aerospace sectors has grown considerably. In structural construction, adhesive joints provide a unique combination of low structural weight, high strength and stiffness, combined with a relatively simple and easily automated manufacturing method, characteristics that are ideal for the development of modern and highly efficient vehicles. In these applications, ensuring that the failure mode of a bonded joint is cohesive rather than adhesive is important since this failure mode is more controlled and easier to model and to predict. This work presents a numerical technique that enables the precise prediction of the bonded joint’s behavior regarding not only its failure mode, but also the joint’s strength, when inorganic fillers are added to the adhesive. To that end, hollow glass particles were introduced into an epoxy adhesive in different amounts, and a numerical study was carried out to simulate their influence on single lap joint specimens. The numerical results were compared against experimental ones, not only in terms of joint strength, but also their failure pattern. The neat adhesive, which showed 9% and 20% variations in terms of failure load and displacement, respectively. However, looking at the doped configurations, these presented smaller variations of about 2% and 10% for each respective variable. In all cases, by adding glass beads, crack initiation tended to change from adhesive to cohesive but with lower strength and ductility, correctly modeling the general experimental behavior as intended.

Abstract It is a fact that the regions that cultivate the most maize crop do not have fully adequate technologies to measure productivity losses caused by irregularities in water availability. The objective of this study was to evaluate the physiological characteristics of maize hybrids tolerant (DKB 390) and sensitive (BRS 1030) to drought, at V5 growth stage and under water restriction, in order to understand the mechanisms involved in the induction of tolerance to drought by chitosan in contrasting maize genotypes. Plants were cultivated in pots at a greenhouse, and chitosan 100 ppm was applied by leaf spraying. The water restriction was imposed for 10 days and then leaf gaseous exchange and chlorophyll fluorescence were evaluated. The tolerant hybrid (DKB 390) showed higher photosynthesis, stomatal conductance, carboxylation efficiency, electron transport rate, and non-photochemical quenching when chitosan was used. Plants from tolerant genotype treated with chitosan were more tolerant to water stress because there were more responsive to the biopolymer. Resumo As regiões que cultivam milho como cultura principal ainda não possuem tecnologias adequadas para mensurar as perdas na produtividade decorrentes na disponibilidade irregular de água. O objetivo desse estudo foi avaliar as características fisiológicas de híbridos de milho tolerante (DKB 390) e sensível (BRS1030) à seca, no estádio de crescimento V5 e sob restrição hídrica, para compreender os mecanismos envolvidos na indução de tolerância à seca pela quitosana em genótipos contrastantes. As plantas foram cultivadas vasos na casa de vegetação e a quitosana 100 ppm foi aplicada por pulverização foliar. A restrição hídrica durou 10 dias e foram avaliadas as trocas gasosas e a fluorescência da clorofila. O híbrido tolerante (DKB 390) apresentou maior fotossíntese, condutância estomática, eficiência de carboxilação, taxa de transporte de elétrons e quenching não fotoquímico quando aplicada a quitosana. As plantas do genótipo tolerante tratadas com quitosana foram mais tolerantes ao déficit hídrico porque foram mais responsivas ao biopolímero.

Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotyping-by-sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum.

Abstract The aim of this study was to determine the acute toxicity of the essential oils (EOs) of Aloysia triphylla, Lippia gracilis and Piper aduncum in juvenile tambaqui (Colossoma macropomum), and evaluate the possible histopathological alterations in their gills. For the acute toxicity tests, juvenile tambaqui (n=24/treatment) were distributed in six treatments with three replicates, which comprised the control and five EO concentrations of A. triphylla (60, 80, 100, 120 and 140 mg L-1), L. gracilis (35, 40, 45, 50 and 55 mg L-1) and P. aduncum (42.5, 45, 47.5, 50 and 52.5 mg L-1), with an exposure period of 4 h. The mortality rate and severity of damage to the tambaqui gills were proportional to the increase in the concentration of the EO, with LC50-4 h values estimated at 109.57 mg L -1 for A. triphylla, 41.63 mg L -1 for L. gracilis and 48.17 mg L -1 for P. aduncum. The main morphological damages observed in the gills of the tambaqui exposed to the three EOs, were Grade I: hypertrophy and hyperplasia of lamellar epithelial cells, lamellar fusion, epithelial detachment, capillary dilation and constriction, proliferation of chloride cells and mucosal cells and edema; in low frequency Grade II damage as epithelial rupture and lamellar aneurysm. Necrosis (Grade III damage) was observed only in gill lamellae exposed to P. aduncum EO (47.5, 50.0 and 52.5 mg L-1). Concentrations of EOs below LC50-4 h can be used sparingly, for short periods of exposure for the treatment of diseases in tambaqui breeding. Resumo O objetivo deste estudo foi determinar a toxicidade aguda dos óleos essenciais (OEs) de Aloysia triphylla, Lippia gracilis e Piper aduncum em juvenis de tambaqui (Colossoma macropomum), e avaliar as possíveis alterações histopatológicas em suas brânquias. Para os testes de toxicidade aguda, juvenis de tambaqui (n=24/tratamento) foram distribuídos em 6 tratamentos, com três repetições, sendo o controle e cinco concentração do OE de A. triphylla (60, 80, 100, 120 e 140 mg L-1), L. gracilis (35, 40, 45, 50 e 55 mg L-1) e P. aduncum (42,5, 45, 47,5, 50 e 52,5 mg L-1), com exposição de 4 h. A taxa de mortalidade e a severidade dos danos nas brânquias de tambaqui foram proporcionais ao aumento da concentração do OE, com os valores de CL50-4 h estimados em 109,57 mg L-1 para A. triphylla, em 41,63 mg L-1 para L. gracilis e em 48,17 mg L-1 para P. aduncum. Os principais danos morfológicos observados nas brânquias de tambaqui, expostos aos três OEs, foram os de grau I: hipertrofia e hiperplasia das células do epitélio lamelar, fusão lamelar, descolamento epitelial, dilatação e constrição capilar, proliferação de células de cloreto e de células mucosas e edema; em baixa frequência os de grau II como ruptura epitelial e aneurisma lamelar. Necrose (dano de grau III) foi observado somente nas lamelas branquiais expostas ao OE de P. aduncum (47,5, 50,0 e 52,5 mg L-1). Concentrações do OEs abaixo dos valores de CL50-4 h podem ser utilizados com parcimônia, em curtos períodos de exposição para o tratamento de doenças na criação de tambaqui.

The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4–52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits.