High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase.

Crop growth and phenology are driven by seasonal changes in environmental variables, with temperature as one important factor. However, knowledge about genotype-specific temperature response and its influence on phenology is limited. Such information is fundamental to improve crop models and adapt selection strategies. We measured the increase in height of 352 European winter wheat varieties in 4 years to quantify phenology, and fitted an asymptotic temperature response model. The model used hourly fluctuations in temperature to parameterize the base temperature (Tmin), the temperature optimum (rmax), and the steepness (lrc) of growth responses. Our results show that higher Tmin and lrc relate to an earlier start and end of stem elongation. A higher rmax relates to an increased final height. Both final height and rmax decreased for varieties originating from the continental east of Europe towards the maritime west. A genome-wide association study (GWAS) indicated a quantitative inheritance and a large degree of independence among loci. Nevertheless, genomic prediction accuracies (GBLUPs) for Tmin and lrc were low (r≤0.32) compared with other traits (r≥0.59). As well as known, major genes related to vernalization, photoperiod, or dwarfing, the GWAS indicated additional, as yet unknown loci that dominate the temperature response.

Modelling atopic dermatitis in healthy human skin for the characterization of topical compounds.

Suitable human models for the development and characterization of topical compounds for inflammatory skin diseases such as atopic dermatitis are not readily available to date. We describe here the development of a translational model involving healthy human skin mimicking major aspects of AD and its application for the characterization of topical Janus kinase inhibitors. Full thickness human abdominal skin obtained from plastic surgery stimulated in vitro with IL4 and IL13 shows molecular features of AD. This is evidenced by STAT6 phosphorylation assessed by immunohistochemistry and analysis of skin lysates. Broad transcriptome changes assessed by AmpliSeq followed by gene set variation analysis showed a consistent upregulation of gene signatures characterizing AD in this model. Topical application of experimental formulations of compounds targeting the JAK pathway to full thickness skin normalizes the molecular features of AD induced by IL4 and IL13 stimulation. The inhibitory effects of topical JAK inhibitors on molecular features of AD are supported by pharmacokinetic analysis. The model described here is suited for the characterization of topical compounds for AD and has the potential to be extended to other inflammatory skin diseases and pathophysiological pathways.

Image-based phenomic prediction can provide valuable decision support in wheat breeding.

KEY MESSAGE: Genotype-by-environment interactions of secondary traits based on high-throughput field phenotyping are less complex than those of target traits, allowing for a phenomic selection in unreplicated early generation trials. Traditionally, breeders' selection decisions in early generations are largely based on visual observations in the field. With the advent of affordable genome sequencing and high-throughput phenotyping technologies, enhancing breeders' ratings with such information became attractive. In this research, it is hypothesized that G[Formula: see text]E interactions of secondary traits (i.e., growth dynamics' traits) are less complex than those of related target traits (e.g., yield). Thus, phenomic selection (PS) may allow selecting for genotypes with beneficial response-pattern in a defined population of environments. A set of 45 winter wheat varieties was grown at 5 year-sites and analyzed with linear and factor-analytic (FA) mixed models to estimate G[Formula: see text]E interactions of secondary and target traits. The dynamic development of drone-derived plant height, leaf area and tiller density estimations was used to estimate the timing of key stages, quantities at defined time points and temperature dose-response curve parameters. Most of these secondary traits and grain protein content showed little G[Formula: see text]E interactions. In contrast, the modeling of G[Formula: see text]E for yield required a FA model with two factors. A trained PS model predicted overall yield performance, yield stability and grain protein content with correlations of 0.43, 0.30 and 0.34. While these accuracies are modest and do not outperform well-trained GS models, PS additionally provided insights into the physiological basis of target traits. An ideotype was identified that potentially avoids the negative pleiotropic effects between yield and protein content.

IL-17A is a pertinent therapeutic target for moderate-to-severe hidradenitis suppurativa: Combined results from a pre-clinical and phase II proof-of-concept study.

Hidradenitis Suppurativa (HS) is a chronic, recurrent, inflammatory, follicular skin disease whose pathology is complex and not fully understood. The objective of this study was to elucidate the role of IL-17A in moderate-to-severe HS. Transcriptomic and histological analyses were conducted on ex vivo HS (n = 19; lesional and non-lesional) and healthy control (n = 8) skin biopsies. Further, a Phase II exploratory, randomized, double-blind, placebo-controlled study was carried out in moderate-to-severe HS patients. Patients were treated with either CJM112 300 mg (n = 33), a fully human anti-IL-17A IgG1/κ monoclonal antibody, or placebo (n = 33). The main outcome of the translational analyses was to identify IL-17A-producing cells and indications of IL-17A activity in HS lesional skin. The primary objective of the clinical study was to determine the efficacy of CJM112 in moderate-to-severe HS patients by HS-Physician Global Assessment (HS-PGA) responder rate at Week 16. Transcriptomic and histopathologic analyses revealed the presence of heterogeneous cell types in HS lesional skin; IL-17A gene signatures were increased in HS lesional vs non-lesional or healthy skin. High expression of IL-17A was localized to T cells, neutrophils, and mast cells, confirming the transcriptional data. Clinically, the proportion of Week 16 HS-PGA responders was significantly higher (p = 0.03) in the CJM112 group vs placebo (32.3% vs 12.5%). This study elucidated the role of the IL-17A pathway in HS pathogenesis and clinically validated the IL-17A pathway in moderate-to-severe HS patients in a proof-of-concept study using the anti-IL-17A-specific antibody CJM112.

Rethinking temperature effects on leaf growth, gene expression and metabolism: Diel variation matters.

Plants have evolved to grow under prominently fluctuating environmental conditions. In experiments under controlled conditions, temperature is often set to artificial, binary regimes with constant values at day and at night. This study investigated how such a diel (24 hr) temperature regime affects leaf growth, carbohydrate metabolism and gene expression, compared to a temperature regime with a field-like gradual increase and decline throughout 24 hr. Soybean (Glycine max) was grown under two contrasting diel temperature treatments. Leaf growth was measured in high temporal resolution. Periodical measurements were performed of carbohydrate concentrations, carbon isotopes as well as the transcriptome by RNA sequencing. Leaf growth activity peaked at different times under the two treatments, which cannot be explained intuitively. Under field-like temperature conditions, leaf growth followed temperature and peaked in the afternoon, whereas in the binary temperature regime, growth increased at night and decreased during daytime. Differential gene expression data suggest that a synchronization of cell division activity seems to be evoked in the binary temperature regime. Overall, the results show that the coordination of a wide range of metabolic processes is markedly affected by the diel variation of temperature, which emphasizes the importance of realistic environmental settings in controlled condition experiments.

Facile generation of antibody heavy and light chain diversities for yeast surface display by Golden Gate Cloning.

Antibodies can be successfully engineered and isolated by yeast or phage display of combinatorial libraries. Still, generation of libraries comprising heavy chain as well as light chain diversities is a cumbersome process involving multiple steps. Within this study, we set out to compare the output of yeast display screening of antibody Fab libraries from immunized rodents that were generated by Golden Gate Cloning (GGC) with the conventional three-step method of individual heavy- and light-chain sub-library construction followed by chain combination via yeast mating (YM). We demonstrate that the GGC-based one-step process delivers libraries and antibodies from heavy- and light-chain diversities with similar quality to the traditional method while being significantly less complex and faster. Additionally, we show that this method can also be used to successfully screen and isolate chimeric chicken/human antibodies following avian immunization.

Monographs for medicines on WHO's Model List of Essential Medicines.

OBJECTIVE: To raise awareness about the importance of public pharmaceutical standards, identify if and, if so, where current pharmacopeias are falling short in the development of new and complete monographs and foster collaboration among the various pharmacopeias, to prioritize, develop and make available standards for those key medicines for which no complete monographs exist. METHODS: In August 2017, we mined eight pharmacopeias to identify which of the 669 medicines in the 20th edition of the World Health Organization's Model List of Essential Medicines were covered by complete or incomplete monographs. The pharmacopeias we included were the Brazilian Pharmacopoeia, the British Pharmacopoeia, the Indian Pharmacopeia Commission, the International Pharmacopoeia, the Japanese Pharmacopoeia, the Mexican Pharmacopoeia, the Pharmacopeia of the People's Republic of China and the United States Pharmacopeia. FINDINGS: For 99 (15%) of the medicines on the Model List, no monographs were available in any of the eight pharmacopeias investigated. Only 3% (1/30) of the cardiovascular medicines listed, but 28% (9/32) of the antiretroviral medicines and 23% (6/26) of the antimalarial medicines lacked monographs. CONCLUSION: There appear to be no public standards for many so-called essential medicines. To address this shortfall, a greater collaboration in the global health community is needed.

Global landscape assessment of screening technologies for medicine quality assurance: stakeholder perceptions and practices from ten countries.

BACKGROUND: The spread of substandard and falsified (SF) medical products constitutes a growing global public health concern. Some countries use portable, handheld screening technologies (STs) in the field to accelerate detection of SF medicines and reduce the number of medicine samples that undergo costly and time-consuming confirmatory analysis. METHODS: A multi-country, multi-stakeholder landscape assessment utilizing qualitative methodology was used to examine practices and perceptions related to the use of STs. Qualitative interview guides were designed using the results of a literature review and comprised of open-ended questions with the study participants, who were from national medicine regulatory authorities, pharmaceutical manufacturers, pharmacies, and distributors. Ten geographically and economically diverse countries were selected: Argentina, China, Egypt, India, Jordan, Mexico, Nigeria, Philippines, the United States, and Zimbabwe. Of the completed 53 interviews, 32 were in-person, 16 were phone interviews, and 5 were via written questionnaires. RESULTS: Data analysis shows a wide variation in understanding and usage of STs in different sectors. Virtually all of the study participants indicated a lack of objective, accessible information on STs to advise them on what technologies would be beneficial for their needs. Study participants also described their ideal capabilities of the next generation of STs, including shareable spectral libraries, lower acquisition costs, lesser training requirements, and in-country maintenance and technical support. CONCLUSION: The results and recommendations presented in this article can be used to help regulators communicate and justify their needs to acquire and invest in new STs. There is a need for additional standardized, trustworthy and scientifically sound evaluations of STs, and to support regulators to effectively deploy the most promising technologies. ST manufacturers can take into account some of the limitations of the technologies the interviewees identified in this article, such as a dearth of technologies, which provide quantitative information about the active ingredient, and take steps to address them to better serve their customers. These results and recommendations, can catalyze research and actionable interventions into the development, review, application, and use of STs.

Expanding global access to essential medicines: investment priorities for sustainably strengthening medical product regulatory systems.

Access to quality-assured medical products improves health and save lives. However, one third of the world's population lacks timely access to quality-assured medicines while estimates indicate that at least 10% of medicine in low- and middle-income countries (LMICs) are substandard or falsified (SF), costing approximately US$ 31 billion annually. National regulatory authorities are the key government institutions that promote access to quality-assured medicines and combat SF medical products but despite progress, regulatory capacity in LMICs is still insufficient. Continued and increased investment in regulatory system strengthening (RSS) is needed. We have therefore reviewed existing global normative documents and resources and engaged with our networks of global partners and stakeholders to identify three critical challenges being faced by NRAs in LMICs that are limiting access to medical products and impeding detection of and response to SF medicines. The challenges are; implementing value-added regulatory practices that best utilize available resources, a lack of timely access to new, quality medical products, and limited evidence-based data to support post-marketing regulatory actions. To address these challenges, we have identified seven focused strategies; advancing and leveraging convergence and reliance initiatives, institutionalizing sustainability, utilizing risk-based approaches for resource allocation, strengthening registration efficiency and timeliness, strengthening inspection capacity and effectiveness, developing and implementing risk-based post-marketing quality surveillance systems, and strengthening regulatory management of manufacturing variations. These proposed solutions are underpinned by 13 focused recommendations, which we believe, if financed, technically supported and implemented, will lead to stronger health system and as a consequence, positive health outcomes.

From Neglecting to Including Cultivar-Specific Per Se Temperature Responses: Extending the Concept of Thermal Time in Field Crops.

Predicting plant development, a longstanding goal in plant physiology, involves 2 interwoven components: continuous growth and the progression of growth stages (phenology). Current models for winter wheat and soybean assume species-level growth responses to temperature. We challenge this assumption, suggesting that cultivar-specific temperature responses substantially affect phenology. To investigate, we collected field-based growth and phenology data in winter wheat and soybean over multiple years. We used diverse models, from linear to neural networks, to assess growth responses to temperature at various trait and covariate levels. Cultivar-specific nonlinear models best explained phenology-related cultivar-environment interactions. With cultivar-specific models, additional relations to other stressors than temperature were found. The availability of the presented field phenotyping tools allows incorporating cultivar-specific temperature response functions in future plant physiology studies, which will deepen our understanding of key factors that influence plant development. Consequently, this work has implications for crop breeding and cultivation under adverse climatic conditions.

Frost Damage Index: The Antipode of Growing Degree Days.

Abiotic stresses such as heat and frost limit plant growth and productivity. Image-based field phenotyping methods allow quantifying not only plant growth but also plant senescence. Winter crops show senescence caused by cold spells, visible as declines in leaf area. We accurately quantified such declines by monitoring changes in canopy cover based on time-resolved high-resolution imagery in the field. Thirty-six winter wheat genotypes were measured in multiple years. A concept termed "frost damage index" (FDI) was developed that, in analogy to growing degree days, summarizes frost events in a cumulative way. The measured sensitivity of genotypes to the FDI correlated with visual scorings commonly used in breeding to assess winter hardiness. The FDI concept could be adapted to other factors such as drought or heat stress. While commonly not considered in plant growth modeling, integrating such degradation processes may be key to improving the prediction of plant performance for future climate scenarios.

Disease Association of Anti‒Carboxyethyl Lysine Autoantibodies in Hidradenitis Suppurativa.

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease characterized by recurring suppurating lesions of the intertriginous areas, resulting in a substantial impact on patients' QOL. HS pathogenesis remains poorly understood. An autoimmune component has been proposed, but disease-specific autoantibodies, autoantigens, or autoreactive T cells have yet to be described. In this study, we identify a high prevalence of IgM, IgG, and IgA antibodies directed against Nε-carboxyethyl lysine (CEL), a methylglyoxal-induced advanced glycation end-product, in the sera of patients with HS. Titers of anti-CEL IgG and IgA antibodies were highly elevated in HS compared with those in healthy controls and individuals with other inflammatory skin diseases. Strikingly, the majority of anti-CEL IgG was of the IgG2 subclass and correlated independently with both disease severity and duration. Both CEL and anti-CEL‒producing plasmablasts could be isolated directly from HS skin lesions, further confirming the disease relevance of this autoimmune response. Our data point to an aberration of the methylglyoxal pathway in HS and support an autoimmune axis in the pathogenesis of this debilitating disease.

Nuclear orphan receptor NR2F6 directly antagonizes NFAT and RORγt binding to the Il17a promoter.

Interleukin-17A (IL-17A) is the signature cytokine produced by Th17 CD4(+) T cells and has been tightly linked to autoimmune pathogenesis. In particular, the transcription factors NFAT and RORγt are known to activate Il17a transcription, although the detailed mechanism of action remains incompletely understood. Here, we show that the nuclear orphan receptor NR2F6 can attenuate the capacity of NFAT to bind to critical regions of the Il17a gene promoter. In addition, because NR2F6 binds to defined hormone response elements (HREs) within the Il17a locus, it interferes with the ability of RORγt to access the DNA. Consistently, NFAT and RORγt binding within the Il17a locus were enhanced in Nr2f6-deficient CD4(+) Th17 cells but decreased in Nr2f6-overexpressing transgenic CD4(+) Th17 cells. Taken together, our findings uncover an example of antagonistic regulation of Il17a transcription through the direct reciprocal actions of NR2F6 versus NFAT and RORγt.

Outdoor Plant Segmentation With Deep Learning for High-Throughput Field Phenotyping on a Diverse Wheat Dataset.

Robust and automated segmentation of leaves and other backgrounds is a core prerequisite of most approaches in high-throughput field phenotyping. So far, the possibilities of deep learning approaches for this purpose have not been explored adequately, partly due to a lack of publicly available, appropriate datasets. This study presents a workflow based on DeepLab v3+ and on a diverse annotated dataset of 190 RGB (350 x 350 pixels) images. Images of winter wheat plants of 76 different genotypes and developmental stages have been acquired throughout multiple years at high resolution in outdoor conditions using nadir view, encompassing a wide range of imaging conditions. Inconsistencies of human annotators in complex images have been quantified, and metadata information of camera settings has been included. The proposed approach achieves an intersection over union (IoU) of 0.77 and 0.90 for plants and soil, respectively. This outperforms the benchmarked machine learning methods which use Support Vector Classifier and/or Random Forrest. The results show that a small but carefully chosen and annotated set of images can provide a good basis for a powerful segmentation pipeline. Compared to earlier methods based on machine learning, the proposed method achieves better performance on the selected dataset in spite of using a deep learning approach with limited data. Increasing the amount of publicly available data with high human agreement on annotations and further development of deep neural network architectures will provide high potential for robust field-based plant segmentation in the near future. This, in turn, will be a cornerstone of data-driven improvement in crop breeding and agricultural practices of global benefit.

Immobilized Metal Affinity Chromatography as a Drug Discovery Platform for Metalloenzyme Inhibitors.

Immobilized metal-ion affinity chromatography (IMAC) used to purify recombinant proteins features a resin-bound 1:1 Ni(II)-iminodiacetic acid (IDA) complex. This hemi-saturated Ni(II)-IDA system containing exchangeable sites at the metal ion is re-cast as a surrogate of a coordinatively-unsaturated metalloenzyme active site, with utility for selecting compounds with metal-binding groups from mixtures as potential metalloenzyme inhibitors. Exchanging Ni(II) for other metal ions could broaden the scope of metalloenzyme target. This work examined the performance of Cu(II)-, Fe(III)-, Ga(III)-, Ni(II)-, or Zn(II)-IMAC resins to reversibly bind experimental or clinical metalloenzyme inhibitors of Zn(II)-ACE1, Zn(II)-HDAC, Fe(II)/(III)-5-LO or Cu(II)-tyrosinase from a curated mixture (1-17). Each IMAC system gave a distinct selection profile. The Zn(II)-IMAC system selectively bound the thiol-containing Zn(II)-ACE1 inhibitors captopril and omapatrilat, and the Fe(III)-IMAC system selectively bound the Fe(II)/(III)-5-LO inhibitor licofelone, demonstrating a remarkable IMAC-metalloenzyme metal ion match. IMAC provides a simple, water-compatible platform, which could accelerate metalloenzyme inhibitor discovery.

Isolation of Antigen-Specific VHH Single-Domain Antibodies by Combining Animal Immunization with Yeast Surface Display.

In addition to conventional hetero-tetrameric antibodies, the adaptive immune repertoire of camelids comprises the so-called heavy chain-only antibodies devoid of light chains. Consequently, antigen binding is mediated solely by the variable domain of the heavy chain, referred to as VHH. In recent years, these single-domain moieties emerged as promising tools for biotechnological and biomedical applications. In this chapter, we describe the generation of VHH antibody yeast surface display libraries from immunized Alpacas and Lamas as well as the facile isolation of antigen-specific molecules in a convenient fluorescence-activated cell sorting (FACS)-based selection process.

Repeated Multiview Imaging for Estimating Seedling Tiller Counts of Wheat Genotypes Using Drones.

Early generation breeding nurseries with thousands of genotypes in single-row plots are well suited to capitalize on high throughput phenotyping. Nevertheless, methods to monitor the intrinsically hard-to-phenotype early development of wheat are yet rare. We aimed to develop proxy measures for the rate of plant emergence, the number of tillers, and the beginning of stem elongation using drone-based imagery. We used RGB images (ground sampling distance of 3 mm pixel-1) acquired by repeated flights (≥ 2 flights per week) to quantify temporal changes of visible leaf area. To exploit the information contained in the multitude of viewing angles within the RGB images, we processed them to multiview ground cover images showing plant pixel fractions. Based on these images, we trained a support vector machine for the beginning of stem elongation (GS30). Using the GS30 as key point, we subsequently extracted plant and tiller counts using a watershed algorithm and growth modeling, respectively. Our results show that determination coefficients of predictions are moderate for plant count (R 2 = 0.52), but strong for tiller count (R 2 = 0.86) and GS30 (R 2 = 0.77). Heritabilities are superior to manual measurements for plant count and tiller count, but inferior for GS30 measurements. Increasing the selection intensity due to throughput may overcome this limitation. Multiview image traits can replace hand measurements with high efficiency (85-223%). We therefore conclude that multiview images have a high potential to become a standard tool in plant phenomics.

Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature.

Canopy temperature (CT) has been related to water-use and yield formation in crops. However, constantly (e.g., sun illumination angle, ambient temperature) as well as rapidly (e.g., clouds) changing environmental conditions make it difficult to compare measurements taken even at short time intervals. This poses a great challenge for high-throughput field phenotyping (HTFP). The aim of this study was to i) set up a workflow for unmanned aerial vehicles (UAV) based HTFP of CT, ii) investigate different data processing procedures to combine information from multiple images into orthomosaics, iii) investigate the repeatability of the resulting CT by means of heritability, and iv) investigate the optimal timing for thermography measurements. Additionally, the approach was v) compared with other methods for HTFP of CT. The study was carried out in a winter wheat field trial with 354 genotypes planted in two replications in a temperate climate, where a UAV captured CT in a time series of 24 flights during 6 weeks of the grain-filling phase. Custom-made thermal ground control points enabled accurate georeferencing of the data. The generated thermal orthomosaics had a high spatial accuracy (mean ground sampling distance of 5.03 cm/pixel) and position accuracy [mean root-mean-square deviation (RMSE) = 4.79 cm] over all time points. An analysis on the impact of the measurement geometry revealed a gradient of apparent CT in parallel to the principle plane of the sun and a hotspot around nadir. Averaging information from all available images (and all measurement geometries) for an area of interest provided the best results by means of heritability. Correcting for spatial in-field heterogeneity as well as slight environmental changes during the measurements were performed with the R package SpATS. CT heritability ranged from 0.36 to 0.74. Highest heritability values were found in the early afternoon. Since senescence was found to influence the results, it is recommended to measure CT in wheat after flowering and before the onset of senescence. Overall, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments.

Lipidomics Profiling of Hidradenitis Suppurativa Skin Lesions Reveals Lipoxygenase Pathway Dysregulation and Accumulation of Proinflammatory Leukotriene B4.

Hidradenitis suppurativa (HS) is a chronic, recurring inflammatory dermatosis characterized by abscesses, deep-seated nodules, sinus tracts, and fibrosis in skin lesions around hair follicles of the axillary, inguinal, and anogenital regions. Whereas the exact pathogenesis remains poorly defined, clear evidence suggests that HS is a multifactorial inflammatory disease characterized by innate and adaptive immune components. Bioactive lipids are important regulators of cutaneous homeostasis, inflammation, and resolution of inflammation. Alterations in the lipid mediator profile can lead to malfunction and cutaneous inflammation. We used targeted lipidomics to analyze selected omega-3 and omega-6 polyunsaturated fatty acids in skin of patients with HS and of healthy volunteers. Lesional HS skin displayed enrichment of 5-lipoxygenase (LO)‒derived metabolites, especially leukotriene B4. In addition, 15-LO‒derived metabolites were underrepresented in HS lesions. Changes in the lipid mediator profile were accompanied by transcriptomic dysregulation of the 5-LO and 15-LO pathways. Hyperactivation of the 5-LO pathway in lesional macrophages identified these cells as potential sources of leukotriene B4, which may cause neutrophil influx and activation. Furthermore, leukotriene B4-induced mediators and pathways were elevated in HS lesions, suggesting a contribution of this proinflammatory lipid meditator to the pathophysiology of HS.