Influence of agronomic design on boron accumulation in early‐season lemon trees ʹFino 49ʹ

La  Región  de  Murcia  es  la  principal  productora  de  limón  de  España.  Sin  embargo,  la  climatología en esta región es semiárida, y bajo estas condiciones, la viabilidad de las explotaciones agrícolas depende principalmente de la disponibilidad y manejo agronómico de los recursos hídricos. En la actualidad, los agricultores complementan parte de los recursos hídricos convencionales disponibles con otros recursos no convencionales, como el agua de mar desalada o las aguas depuradas. Sin embargo, estos recursos no convencionales pueden presentar  elevadas  concentraciones  de  cloro,  sodio  y  especialmente  boro  (B),  que  puede  reducir la productividad de cultivos especialmente sensibles, como los cítricos, que presentan bajos umbrales de fitotoxicidad por boro (0,5 mg L‐1 en el agua de riego). Respecto al manejo agronómico,  mejoras  en  el  diseño  agronómico  de  la  instalación  de  riego  buscando  un  incremento de la superficie mojada pueden, por un lado, ayudar a aumentar la capacidad hidráulica de la planta, lo que podría favorecer la productividad del cultivo, pero también favorecen la acumulación en hoja de diferentes elementos minerales. Por lo tanto, el objetivo del experimento fue evaluar si un aumento en el volumen mojado del suelo al incrementar el número de goteros por árbol puede favorecer la acumulación de boro en hoja y cómo responde agronómicamente el cultivo. El ensayo se llevó a cabo durante tres campañas (2017‐2019) en una parcela experimental en Torre Pacheco (Murcia), en árboles adultos de limonero ‘Fino 49’ injertados sobre Citrus macrophylla. Se han evaluado dos diseños del sistema de riego: diseño convencional (2L), con dos tuberías portagoteros (6 goteros árbol‐1); y un diseño con mayor superficie mojada (3L), con tres tuberías (9 goteros árbol‐1), aplicando la misma cantidad de agua de riego en ambos tratamientos. Se realizó un seguimiento periódico de la calidad del agua de riego recibida en el embalse de la parcela (pH, CE, Na, Cl, Ca, Mg, y principalmente B). En noviembre de cada campaña se realizó un muestro foliar en 12 árboles por tratamiento para  el  análisis  de  contenido  mineral  en  hoja  de  macronutrientes  y  micronutrientes  (principalmente B). En los mismos árboles, se realizó la cosecha, determinando el número de frutos cosechados y los kilogramos obtenidos por árbol. Los principales resultados indicaron que los valores promedio de B en el agua de riego durante el periodo experimental estuvieron muy  cercanos  a  los  0,50  mg  L‐1.  Esto  se  vio  reflejado  en  los  niveles  de  B  en  hoja,  que  se  incrementaron anualmente, hasta alcanzar en la última campaña valores de 197 ppm y 179 ppm  en  el tratamiento 2L  y 3L  respectivamente,  más  del doble  de  los  registrados  en 2017.  Dicho aumento del contenido de B en hoja estuvo relacionado significativamente con una reducción de la producción, en un 44% y 41%, debido a una disminución del número de frutos cosechados del 50% y 47% en el tratamiento 2L y 3L respectivamente, respecto a la primera campaña. Por lo tanto, los diferentes diseños agronómicos estudiados respondieron de manera similar a la acumulación de boro en hoja con similares efectos sobre la producción

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways

Using case-based reasoning to detect risk scenarios of elderly people living alone at home

In today's ageing societies, the proportion of elderly people living alone in their own homes is dramatically increasing. Smart homes provide the appropriate environment for keeping them independent and, therefore, enhancing their quality of life. One of the most important re-\ud quirements of these systems is that they have to provide a pervasive environment without disrupting elderly people's daily activities. The present paper introduces a CBR agent used within a commercial Smart Home system, designed for detecting domestic accidents that may lead to serious complications if the elderly resident is not attended quickly. The approach is based on cases composed of event sequences. Each event sequence represents the different locations visited by the resident during his/her daily activities. Using this approach, the system can decide\ud whether the current sequence represent an unsafe scenario or not. It does so by comparing the current sequence with previously stored sequences. Several experiments have been conducted with different CBR agent con-\ud figurations in order to test this approach. Results from these experiments show that the proposed approach is able to detect unsafe scenarios

Viabilidade da irrigação do meloeiro com águas salinas em diferentes fases fenológicas Feasibility of irrigation of musk melon with salinity water in different phenological stages

Com o objetivo de estudar os efeitos da aplicação de águas de irrigação de diferentes salinidades no rendimento do melão irrigado por gotejamento e de associar a produção obtida com o custo da água utilizada, desenvolveu-se este trabalho em Mossoró-RN. Águas de diferentes salinidades (S1=0,6, S2=1,9, S3=3,2 e S4=4,5dS m-1), utilizadas de forma incremental em três estádios de desenvolvimento ou sem variar durante o ciclo da cultura, formaram dez tratamentos arranjados em blocos inteiramente casualizados com quatro repetições. O uso de águas salinas por longos períodos afetou a produção de melão. Substituições tardias na salinidade da água tenderam a não exercer efeito significativo sobre a produção do meloeiro. O tratamento irrigado com a água de menor salinidade durante todo ciclo apresentou, simultaneamente, o maior custo com água de irrigação e o maior lucro na produção de melão.<br>This study was carried out in Mossoró, RN, Brazil, to evaluate the effects of different irrigation water salinity levels on yield of drip irrigated melon, and to relate yield with the cost of water. The waters of different salinities (S1=0.6, S2=1.9, S3=3.2 e S4=4.5dS m-1) were used both in incremental way in three different phenological stages and without replacement during the crop cycle totalizing ten treatments arranged in a completely randomized block design with four repetitions. The use of saline waters without substitutions affected melon production. The treatments irrigated with low salinity water presented simultaneously the higher cost of irrigation water and higher profits of melon cultivation

Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome

Parkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development