COVID-19 in a Patient Treated for Granulomatosis with Polyangiitis: Persistent Viral Shedding with No Cytokine Storm

Introduction: The coronavirus disease COVID-19 is considered a pandemic disease that has developed rapidly all over the world. As of today, it is unclear whether immunosuppression confers an increased risk for pulmonary complications, or conversely, whether it can be a protective factor with respect to a cytokine storm. Case description: We report the case of a 55-year-old male patient with granulomatosis with polyangiitis treated with rituximab who was infected with COVID-19 pneumonia. To the best of our knowledge, only 1 case has been reported in the literature with similar characteristics. The patient had a non-classic evolution of clinical symptoms with persistent fever and viral shedding, in addition to a negative serology.Conclusion: This case emphasizes the management and immunity response to COVID-19 pneumonia in such patients. Data are still needed regarding patients who have prolonged B-cell depletion, which may put the patient at a higher risk for reinfection

Field phenotyping for African crops: overview and perspectives

Improvements in crop productivity are required to meet the dietary demands of the rapidly-increasing African population. The development of key staple crop cultivars that are high-yielding and resilient to biotic and abiotic stresses is essential. To contribute to this objective, high-throughput plant phenotyping approaches are important enablers for the African plant science community to measure complex quantitative phenotypes and to establish the genetic basis of agriculturally relevant traits. These advances will facilitate the screening of germplasm for optimum performance and adaptation to low-input agriculture and resource-constrained environments. Increasing the capacity to investigate plant function and structure through non-invasive technologies is an effective strategy to aid plant breeding and additionally may contribute to precision agriculture. However, despite the significant global advances in basic knowledge and sensor technology for plant phenotyping, Africa still lags behind in the development and implementation of these systems due to several practical, financial, geographical and political barriers. Currently, field phenotyping is mostly carried out by manual methods that are prone to error, costly, labor-intensive and may come with adverse economic implications. Therefore, improvements in advanced field phenotyping capabilities and appropriate implementation are key factors for success in modern breeding and agricultural monitoring. In this review, we provide an overview of the current state of field phenotyping and the challenges limiting its implementation in some African countries. We suggest that the lack of appropriate field phenotyping infrastructures is impeding the development of improved crop cultivars and will have a detrimental impact on the agricultural sector and on food security. We highlight the prospects for integrating emerging and advanced low-cost phenotyping technologies into breeding protocols and characterizing crop responses to environmental challenges in field experimentation. Finally, we explore strategies for overcoming the barriers and maximizing the full potential of emerging field phenotyping technologies in African agriculture. This review paper will open new windows and provide new perspectives for breeders and the entire plant science community in Africa.BBSRC: BB/P016855/

Missense mutation of a class B heat shock factor is responsible for the tomato bushy root-2 phenotype

The bushy root-2 (brt-2) tomato mutant has twisting roots, and slower plant development. Here we used whole genome resequencing and genetic mapping to show that brt-2 is caused by a serine to cysteine (S75C) substitution in the DNA binding domain (DBD) of a heat shock factor class B (HsfB) encoded by SolycHsfB4a. This gene is orthologous to the Arabidopsis SCHIZORIZA gene, also known as AtHsfB4. The brt-2 phenotype is very similar to Arabidopsis lines in which the function of AtHsfB4 is altered: a proliferation of lateral root cap and root meristematic tissues, and a tendency for lateral root cap cells to easily separate. The brt-2 S75C mutation is unusual because all other reported amino acid substitutions in the highly conserved DBD of eukaryotic heat shock factors are dominant negative mutations, but brt-2 is recessive. We further show through reciprocal grafting that brt-2 exerts its effects predominantly through the root genotype even through BRT-2 is expressed at similar levels in both root and shoot meristems. Since AtHsfB4 is induced by root knot nematodes (RKN), and loss-of-function mutants of this gene are resistant to RKNs, BRT-2 could be a target gene for RKN resistance, an important trait in tomato rootstock breeding.Biotechnology and Biological Sciences Research Council (BBSRC): BB/L01954X/

Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods

Sustainable fertilizer management in precision agriculture is essential for both economic and environmental reasons. To effectively manage fertilizer input, various methods are employed to monitor and track plant nutrient status. One such method is hyperspectral imaging, which has been on the rise in recent times. It is a remote sensing tool used to monitor plant physiological changes in response to environmental conditions and nutrient availability. However, conventional hyperspectral processing mainly focuses on either the spectral or spatial information of plants. This study aims to develop a hybrid convolution neural network (CNN) capable of simultaneously extracting spatial and spectral information from quinoa and cowpea plants to identify their nutrient status at different growth stages. To achieve this, a nutrient experiment with four treatments (high and low levels of nitrogen and phosphorus) was conducted in a glasshouse. A hybrid CNN model comprising a 3D CNN (extracts joint spectral-spatial information) and a 2D CNN (for abstract spatial information extraction) was proposed. Three pre-processing techniques, including second-order derivative, standard normal variate, and linear discriminant analysis, were applied to selected regions of interest within the plant spectral hypercube. Together with the raw data, these datasets were used as inputs to train the proposed model. This was done to assess the impact of different pre-processing techniques on hyperspectral-based nutrient phenotyping. The performance of the proposed model was compared with a 3D CNN, a 2D CNN, and a Hybrid Spectral Network (HybridSN) model. Effective wavebands were selected from the best-performing dataset using a greedy stepwise-based correlation feature selection (CFS) technique. The selected wavebands were then used to retrain the models to identify the nutrient status at five selected plant growth stages. From the results, the proposed hybrid model achieved a classification accuracy of over 94% on the test dataset, demonstrating its potential for identifying nitrogen and phosphorus status in cowpea and quinoa at different growth stages

Machine learning methods for automatic segmentation of images of field-and glasshouse-based plants for high-throughput phenotyping

Image segmentation is a fundamental but critical step for achieving automated high- throughput phenotyping. While conventional segmentation methods perform well in homogenous environments, the performance decreases when used in more complex environments. This study aimed to develop a fast and robust neural-network-based segmentation tool to phenotype plants in both field and glasshouse environments in a high-throughput manner. Digital images of cowpea (from glasshouse) and wheat (from field) with different nutrient supplies across their full growth cycle were acquired. Image patches from 20 randomly selected images from the acquired dataset were transformed from their original RGB format to multiple color spaces. The pixels in the patches were annotated as foreground and background with a pixel having a feature vector of 24 color properties. A feature selection technique was applied to choose the sensitive features, which were used to train a multilayer perceptron network (MLP) and two other traditional machine learning models: support vector machines (SVMs) and random forest (RF). The performance of these models, together with two standard color-index segmentation techniques (excess green (ExG) and excess green–red (ExGR)), was compared. The proposed method outperformed the other methods in producing quality segmented images with over 98%-pixel classification accuracy. Regression models developed from the different segmentation methods to predict Soil Plant Analysis Development (SPAD) values of cowpea and wheat showed that images from the proposed MLP method produced models with high predictive power and accuracy comparably. This method will be an essential tool for the development of a data analysis pipeline for high-throughput plant phenotyping. The proposed technique is capable of learning from different environmental conditions, with a high level of robustness

Genes involved in auxin biosynthesis, transport and signalling underlie the extreme adventitious root phenotype of the tomato aer mutant

The use of tomato rootstocks has helped to alleviate the soaring abiotic stresses provoked by the adverse effects of climate change. Lateral and adventitious roots can improve topsoil exploration and nutrient uptake, shoot biomass and resulting overall yield. It is essential to understand the genetic basis of root structure development and how lateral and adventitious roots are produced. Existing mutant lines with specific root phenotypes are an excellent resource to analyse and comprehend the molecular basis of root developmental traits. The tomato aerial roots (aer) mutant exhibits an extreme adventitious rooting phenotype on the primary stem. It is known that this phenotype is associated with restricted polar auxin transport from the juvenile to the more mature stem, but prior to this study, the genetic loci responsible for the aer phenotype were unknown. We used genomic approaches to define the polygenic nature of the aer phenotype and provide evidence that increased expression of specific auxin biosynthesis, transport and signalling genes in different loci causes the initiation of adventitious root primordia in tomato stems. Our results allow the selection of different levels of adventitious rooting using molecular markers, potentially contributing to rootstock breeding strategies in grafted vegetable crops, especially in tomato. In crops vegetatively propagated as cuttings, such as fruit trees and cane fruits, orthologous genes may be useful for the selection of cultivars more amenable to propagation.The research was supported by BBSRC—UKRI funding; the RootLINK (BB/L01954X/1) and AdRoot (BB/S007970/1) projects

Exercise Capacity in Patients With Obstructive Hypertrophic Cardiomyopathy:SEQUOIA-HCM Baseline Characteristics and Study Design

Patients with obstructive hypertrophic cardiomyopathy (oHCM) have increased risk of arrhythmia, stroke, heart failure, and sudden death. Contemporary management of oHCM has decreased annual hospitalization and mortality rates, yet patients have worsening health-related quality of life due to impaired exercise capacity and persistent residual symptoms. Here we consider the design of clinical trials evaluating potential oHCM therapies in the context of SEQUOIA-HCM (Safety, Efficacy, and Quantitative Understanding of Obstruction Impact of Aficamten in HCM). This large, phase 3 trial is now fully enrolled (N = 282). Baseline characteristics reflect an ethnically diverse population with characteristics typical of patients encountered clinically with substantial functional and symptom burden. The study will assess the effect of aficamten vs placebo, in addition to standard-of-care medications, on functional capacity and symptoms over 24 weeks. Future clinical trials could model the approach in SEQUOIA-HCM to evaluate the effect of potential therapies on the burden of oHCM. (Safety, Efficacy, and Quantitative Understanding of Obstruction Impact of Aficamten in HCM [SEQUOIA-HCM]; NCT05186818).</p

A loss-of-function allele of a TAC1-like gene (SlTAC1) located on tomato chromosome 10 is a candidate for the Erectoid leaf (Erl) mutation

The genetic basis of an erectoid leaf phenotype was investigated in distinct tomato breeding populations, including one derived from Solanum lycopersicum ‘LT05’ (with the erectoid leaf phenotype and uniform ripening, genotype uu) × S. pimpinellifollium ‘TO-937’ (with the wild-type leaf phenotype and green fruit shoulder, genotype UU). The erectoid leaf phenotype was inherited as a semi-dominant trait and it co-segregated with the u allele of gene SlGLK2 (Solyc10g008160). This genomic location coincides with a previously described semi-dominant mutation named as Erectoid leaf (Erl). The genomes of ‘LT05’, ‘TO-937’, and three other unrelated accessions (with the wild-type Erl+ allele) were resequenced with the aim of identifying candidate genes. Comparative genomic analyses, including the reference genome ‘Heinz 1706’ (Erl+ allele), identified an Erectoid leaf-specific single nucleotide polymorphism (SNP) in the gene Solyc10g009320. This SNP caused a change of a glutamine codon (present in all the wild-type genomes) to a TAA (= ochre stop-codon) in the Erl allele, resulting in a smaller version of the predicted mutant protein (221 vs. 279 amino acids). Solyc10g009320, previously annotated as an ‘unknown protein’, was identified as a TILLER ANGLE CONTROL1-like gene. Linkage between the Erl and Solyc10g009320 was confirmed via Sanger sequencing of the PCR amplicons of the two variant alleles. No recombinants were detected in 265 F2 individuals. Contrasting S7 near-isogenic lines were also homozygous for each of the alternate alleles, reinforcing Solyc10g009320 as a strong Erl candidate gene and opening the possibility for fine-tuning manipulation of tomato architecture in breeding programs

A chromosome-level genome assembly of Solanum chilense, a tomato wild relative associated with resistance to salinity and drought

Introduction: Solanum chilense is a wild relative of tomato reported to exhibit resistance to biotic and abiotic stresses. There is potential to improve tomato cultivars via breeding with wild relatives, a process greatly accelerated by suitable genomic and genetic resources. Methods: In this study we generated a high-quality, chromosome-level, de novo assembly for the S. chilense accession LA1972 using a hybrid assembly strategy with ~180 Gbp of Illumina short reads and ~50 Gbp long PacBio reads. Further scaffolding was performed using Bionano optical maps and 10x Chromium reads. Results: The resulting sequences were arranged into 12 pseudomolecules using Hi-C sequencing. This resulted in a 901 Mbp assembly, with a completeness of 95%, as determined by Benchmarking with Universal Single-Copy Orthologs (BUSCO). Sequencing of RNA from multiple tissues resulting in ~219 Gbp of reads was used to annotate the genome assembly with an RNA-Seq guided gene prediction, and for a de novo transcriptome assembly. This chromosome-level, high-quality reference genome for S. chilense accession LA1972 will support future breeding efforts for more sustainable tomato production. Discussion: Gene sequences related to drought and salt resistance were compared between S. chilense and S. lycopersicum to identify amino acid variations with high potential for functional impact. These variants were subsequently analysed in 84 resequenced tomato lines across 12 different related species to explore the variant distributions. We identified a set of 7 putative impactful amino acid variants some of which may also impact on fruit development for example the ethylene-responsive transcription factor WIN1 and ethylene-insensitive protein 2. These variants could be tested for their ability to confer functional phenotypes to cultivars that have lost these variants.This work was jointly supported by the UK’s Biotechnology and Biological Sciences Research Council and the Indian Department of Biotechnology (BB/L011611/1)

Efficacy and safety of aficamten in symptomatic non-obstructive hypertrophic cardiomyopathy: results from the REDWOOD-HCM trial, cohort 4

Background This open-label phase 2 trial evaluated the safety and efficacy of aficamten in patients with nonobstructive hypertrophic cardiomyopathy (nHCM). Methods Patients with symptomatic nHCM (left ventricular outflow tract obstruction gradient ≤ 30 mmHg, left ventricular ejection fraction [LVEF] ≥ 60%, N-terminal pro-B-type natriuretic peptide [NT-proBNP] &gt; 300 pg/mL) received aficamten 5–15 mg once daily (doses adjusted according to echocardiographic LVEF) for 10 weeks. Results We enrolled 41 patients (mean ± SD age 56 ± 16 years; 59% female). At Week 10, 22 (55%) patients experienced an improvement of ≥ 1 New York Heart Association class; 11 (29%) became asymptomatic. Clinically relevant improvements in Kansas City Cardiomyopathy Questionnaire Clinical Summary Scores occurred in 22 (55%) patients. Symptom relief was paralleled by reductions in NT-proBNP levels (56%; P &lt; 0.001) and high-sensitivity cardiac troponin I (22%; P &lt; 0.005). Modest reductions in LVEF (mean ± SD) of −5.4% ± 10 to 64.6% ± 9.1 were observed. Three (8%) patients had asymptomatic reduction in LVEF &lt; 50% (range: 41%–48%), all returning to normal after 2 weeks of washout. One patient with prior history of aborted sudden cardiac death experienced a fatal arrhythmia during the study. Conclusions Aficamten administration for symptomatic nHCM was generally safe and was associated with improvements in heart failure symptoms and cardiac biomarkers