17 research outputs found
DECTIN-1: A modifier protein in CTLA-4 haploinsufficiency.
Autosomal dominant loss-of-function (LoF) variants in cytotoxic T-lymphocyte associated protein 4 (CTLA4) cause immune dysregulation with autoimmunity, immunodeficiency and lymphoproliferation (IDAIL). Incomplete penetrance and variable expressivity are characteristic of IDAIL caused by CTLA-4 haploinsufficiency (CTLA-4h), pointing to a role for genetic modifiers. Here, we describe an IDAIL proband carrying a maternally inherited pathogenic CTLA4 variant and a paternally inherited rare LoF missense variant in CLEC7A, which encodes for the β-glucan pattern recognition receptor DECTIN-1. The CLEC7A variant led to a loss of DECTIN-1 dimerization and surface expression. Notably, DECTIN-1 stimulation promoted human and mouse regulatory T cell (Treg) differentiation from naïve αβ and γδ T cells, even in the absence of transforming growth factor-β. Consistent with DECTIN-1's Treg-boosting ability, partial DECTIN-1 deficiency exacerbated the Treg defect conferred by CTL4-4h. DECTIN-1/CLEC7A emerges as a modifier gene in CTLA-4h, increasing expressivity of CTLA4 variants and acting in functional epistasis with CTLA-4 to maintain immune homeostasis and tolerance.S
What will cataract surgery look like in the future? Alternatives in the pipeline
Phacoemulsification is the most frequently performed surgery in the world. Over the past few years, this surgery seems to have reached a plateau with no further innovative breakthroughs. In this paper, we focus on alternatives techniques, the latest innovations, and the research and development pipeline in this field. (C) 2020 Elsevier Masson SAS. All rights reserved.Ophthalmic researc
Internet of things (IoT) for smart agriculture: Assembling and assessment of a low-cost IoT system for polytunnels.
Internet of things (IoT) applications in smart agricultural systems vary from monitoring climate conditions, automating irrigation systems, greenhouse automation, crop monitoring and management, and crop prediction, up to end-to-end autonomous farm management systems. One of the main challenges to the advancement of IoT systems for the agricultural domain is the lack of training data under operational environmental conditions. Most of the current designs are based on simulations and artificially generated data. Therefore, the essential first step is studying and understanding the finely tuned and highly sensitive mechanism plants have developed to sense, respond, and adapt to changes in their environment, and their behavior under field and controlled systems. Therefore, this study was designed to achieve two specific objectives; to develop low-cost IoT components from basic building blocks, and to study the performance of the developed systems, and generate real-time experimental data, with and without plants. Low-cost IoT devices developed locally were used to convert existing basic polytunnels to semi-controlled and monitoring-only polytunnels. Their performances were analyzed and compared with each other based on several matrices while maintaining the planted tomato variety and agronomic practices similar. The developed system performed as expected suggesting the possibility of commercial applications and research purposes