The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often ...available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity within the cluster and exceptionally high variability of the loci. Established approaches, therefore, rely on specific HLA enrichment and sequencing techniques, coming at an additional cost and extra turnaround time.
We present OptiType, a novel HLA genotyping algorithm based on integer linear programming, capable of producing accurate predictions from NGS data not specifically enriched for the HLA cluster. We also present a comprehensive benchmark dataset consisting of RNA, exome and whole-genome sequencing data. OptiType significantly outperformed previously published in silico approaches with an overall accuracy of 97% enabling its use in a broad range of applications.
Allergen immunotherapy (AIT) has been in use for the treatment of allergic disease for more than 100 years. Asthma treatment relies mainly on corticosteroids and other controllers recommended to ...achieve and maintain asthma control, prevent exacerbations, and improve quality of life. AIT is underused in asthma, both in children and in adults. Notably, patients with allergic asthma not adequately controlled on pharmacotherapy (including biologics) represent an unmet health need. The European Academy of Allergy and Clinical Immunology has developed a clinical practice guideline providing evidence‐based recommendations for the use of house dust mites (HDM) AIT as add‐on treatment for HDM‐driven allergic asthma. This guideline was developed by a multi‐disciplinary working group using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. HDM AIT was separately evaluated by route of administration and children and adults: subcutaneous (SCIT) and sublingual AIT (SLIT), drops, and tablets. Recommendations were formulated for each. The important prerequisites for successful treatment with HDM AIT are (a) selection of patients most likely to respond to AIT and (b) use of allergen extracts and desensitization protocols of proven efficacy. To date, only AIT with HDM SLIT‐tablet has demonstrated a robust effect in adults for critical end points (exacerbations, asthma control, and safety). Thus, it is recommended as an add‐on to regular asthma therapy for adults with controlled or partially controlled HDM‐driven allergic asthma (conditional recommendation, moderate‐quality evidence). HDM SCIT is recommended for adults and children, and SLIT drops are recommended for children with controlled HDM‐driven allergic asthma as the add‐on to regular asthma therapy to decrease symptoms and medication needs (conditional recommendation, low‐quality evidence).
Allergic diseases are common and frequently coexist. Allergen immunotherapy (AIT) is a disease‐modifying treatment for IgE‐mediated allergic disease with effects beyond cessation of AIT that may ...include important preventive effects. The European Academy of Allergy and Clinical Immunology (EAACI) has developed a clinical practice guideline to provide evidence‐based recommendations for AIT for the prevention of (i) development of allergic comorbidities in those with established allergic diseases, (ii) development of first allergic condition, and (iii) allergic sensitization. This guideline has been developed using the Appraisal of Guidelines for Research & Evaluation (AGREE II) framework, which involved a multidisciplinary expert working group, a systematic review of the underpinning evidence, and external peer‐review of draft recommendations. Our key recommendation is that a 3‐year course of subcutaneous or sublingual AIT can be recommended for children and adolescents with moderate‐to‐severe allergic rhinitis (AR) triggered by grass/birch pollen allergy to prevent asthma for up to 2 years post‐AIT in addition to its sustained effect on AR symptoms and medication. Some trial data even suggest a preventive effect on asthma symptoms and medication more than 2 years post‐AIT. We need more evidence concerning AIT for prevention in individuals with AR triggered by house dust mites or other allergens and for the prevention of allergic sensitization, the first allergic disease, or for the prevention of allergic comorbidities in those with other allergic conditions. Evidence for the preventive potential of AIT as disease‐modifying treatment exists but there is an urgent need for more high‐quality clinical trials.
The seventh “Future of the Allergists and Specific Immunotherapy (FASIT)” workshop held in 2019 provided a platform for global experts from academia, allergy clinics, regulatory authorities and ...industry to review current developments in the field of allergen immunotherapy (AIT). Key domains of the meeting included the following: (a) Biomarkers for AIT and allergic asthma; (b) visions for the future of AIT; (c) progress and data for AIT in asthma and the updates of GINA and EAACI Asthma Guidelines (separated for house dust mite SCIT, SLIT tablets and SLIT drops; patient populations) including a review of clinically relevant endpoints in AIT studies in asthma; (d) regulatory prerequisites such as the “Therapy Allergen Ordinance” in Germany; (e) optimization of trial design in AIT clinical research; (f) challenges planning and conducting phase III (field) studies and the future role of Allergen Exposure Chambers (AEC) in AIT product development from the regulatory point of view. We report a summary of panel discussions of all six domains and highlight unmet needs and possible solutions for the future.
This paper presents a coincident and a leading composite monthly indicator for the world business cycle—the Global Economic Barometers. Both target the world’s output growth rate and consist of ...economic tendency surveys results from many countries around the world. The calculation of these indicators comprises two main stages. The first consists of a variable selection procedure, in which a pre-set correlation threshold and the targeted leads to the reference series are used as selection criteria. In the second stage, the selected variables are combined and transformed into the respective composite indicators, computed as the first partial least squares factor with the reference series as response variable. We analyse the characteristics of the two new indicators in a pseudo real-time setting and demonstrate that both are useful additions to the small number of indicators for the global business cycle published so far. Finally, yet importantly, the Barometers were quick to plunge in the beginning of March 2020 and have since then given a reliable real-time reflection of the economic consequences of the Covid-19 pandemic.
Cassava (
Manihot esculenta Crantz
) is one of the oldest root and tuber crops, used by humans to produce food, feed and beverages. Currently, cassava is produced in more than 100 countries and ...fulfils the daily caloric demands of millions of people living in tropical America, Africa, and Asia. Its importance as a food security crop is high in Western, Central and Eastern Africa due to its ability to produce reasonable yields (~10 t/ha) in poor soils and with minimal inputs. Traditionally a famine reserve and a subsistence crop, the status of cassava is now evolving fast as a cash crop and as raw material in the production of starch (and starch based products), energy (bio-ethanol) and livestock feed in the major producing countries. Cassava leaves, which are rich in protein and beta-carotenoids, are also used as a vegetable and forage (fresh or dehydrated meal) in various parts of the world. In recent years, some of the problems in the production of cassava have been increasing infection with cassava mosaic disease (CMD), cassava brown streak disease (CBSD) and cassava bacterial blight (CBB). Inherent post-harvest physiological disorder (PPD) and cyanogenic glycosides (CG) are some of the most prominent challenges for scientists, producers and consumers in the post-production systems. Collaborative research in participatory plant breeding is ongoing at leading international research institutes such as IITA and CIAT to improve crop resistance to virus diseases, reduce PPD and CG, and improve the overall nutritional characteristics. Further research should also focus on post-production systems by developing enhanced storage and transportation techniques, mechanisation (peeling, size reduction, drying and dewatering) and improved packaging. Moreover, a robust national policy, market development, and dissemination and extension program are required to realise the full potential of innovations and technologies in cassava production and processing.
This study aims at improving upon existing activity predictions methods by augmenting chemical structure fingerprints with bio-activity based fingerprints derived from high-throughput screening (HTS) ...data (HTSFPs) and thereby showcasing the benefits of combining different descriptor types. This type of descriptor would be applied in an iterative screening scenario for more targeted compound set selection. The HTSFPs were generated from HTS data obtained from PubChem and combined with an ECFP4 structural fingerprint. The bioactivity-structure hybrid (BaSH) fingerprint was benchmarked against the individual ECFP4 and HTSFP fingerprints. Their performance was evaluated via retrospective analysis of a subset of the PubChem HTS data. Results showed that the BaSH fingerprint has improved predictive performance as well as scaffold hopping capability. The BaSH fingerprint identified unique compounds compared to both the ECFP4 and the HTSFP fingerprint indicating synergistic effects between the two fingerprints. A feature importance analysis showed that a small subset of the HTSFP features contribute most to the overall performance of the BaSH fingerprint. This hybrid approach allows for activity prediction of compounds with only sparse HTSFPs due to the supporting effect from the structural fingerprint.
Posture detection targeted towards providing assessments for the monitoring of health and welfare of pigs has been of great interest to researchers from different disciplines. Existing studies ...applying machine vision techniques are mostly based on methods using three-dimensional imaging systems, or two-dimensional systems with the limitation of monitoring under controlled conditions. Thus, the main goal of this study was to determine whether a two-dimensional imaging system, along with deep learning approaches, could be utilized to detect the standing and lying (belly and side) postures of pigs under commercial farm conditions. Three deep learning-based detector methods, including faster regions with convolutional neural network features (Faster R-CNN), single shot multibox detector (SSD) and region-based fully convolutional network (R-FCN), combined with Inception V2, Residual Network (ResNet) and Inception ResNet V2 feature extractions of RGB images were proposed. Data from different commercial farms were used for training and validation of the proposed models. The experimental results demonstrated that the R-FCN ResNet101 method was able to detect lying and standing postures with higher average precision (AP) of 0.93, 0.95 and 0.92 for standing, lying on side and lying on belly postures, respectively and mean average precision (mAP) of more than 0.93.
•Gaussian Process Regression models accurately predicted moisture content and aw.•MC variations dominate the NIR region, potentially masking phenolic compounds.•The GPR model is feasible to predict ...moisture content for many commodities.
The potential of Visual-NIR hyperspectral imaging (VNIR-HSI, 425–1700 nm) to predict celeriac quality attributes during the drying process was investigated. The HSI-Gaussian Process Regression (GPR) fusion method excellently predicted moisture content (MC, R2 ≈ 1.00, RMSE = 0.77 gw 100 gs-1) and water activity (aw, R2 = 0.98, RMSE = 0.04). Moreover, the rehydration ratio (RR, R2 = 0.89, RMSE = 0.04) and colour indices (R2 = 0.80–0.93, RMSE = 0.17–1.45) were reasonably predicted. However, antioxidant activity (AA) and total phenolic compounds (TPC) were poorly predicted. These results are potentially due to MC variations dominating the NIR region, masking phenolic compounds. Finally, the celeriac-based-trained model was assessed by predicting the MC of apple, cocoyam, and carrot slices. The results were encouraging; however, a GPR model trained on the data of all four commodities was more robust (R2 ≈ 1.00, RMSE = 1–2 gw 100 gs-1).
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