Toward the prediction of flowering date of apple trees from unmanned aerial vehicle (UAV) imagery

Fruit tree flowering and reproduction processes are crucial for production. Flowering time is currently impacted by global warming affecting orchard production. The screening of genetic resources could provide new keys for fruit tree adaptation. Proxy-detection has great potential to help characterize plant cultivars and select the best performing ones. In this context, the ambition of this project is to develop new methodologies for predicting flowering dates using aerial images at regular time intervals. For this, we used a core-collection of 241 apple French cultivars with four repetitions per cultivar, planted in 2014 in Montpellier (south of France). RGB and multispectral images were acquired on the orchard, using drone-borne sensors, resulting in orthomosaics of the entire orchard. For each type of sensor, four periods of acquisition in 2021 (between June and November) were used to characterize different foliage phenological stages. In parallel, expert notations of the flowering dates were carried out in the following spring (2022). The eight orthomosaics were split into patches representing individual trees. Different methods of machine and deep learning were tested to predict the flowering dates from the patches. First, NDVI and NDRE were determined from each patch and regression methods, such as Lasso, Random Forest, Gradient Boosting, were applied. A convolutional neural network (CNN), inspired from U-Net, was then tested. This CNN was tested on individual patches and on concatenated patches of the different months. Finally, a clustering method was used to identify flowering periods by grouping trees with similar flowering dates and a CNN was trained to predict the flowering period of each tree. This last approach proved to be the most accurate with an RMSE of approximately 10 days. This work illustrates the interest and limitation of deep learning on images for the phenotyping of traits representing genotypic behavior at different tree developmental stages

Glass transition temperature variation, cross-linking and structure in network glasses

We give general topological rules which very accurately predict the chemical trends in glass transition temperature $T_g$ variation as a function of cross-linking. In multicomponent glasses, these chemical trends permit to distinguish homogeneous compositions (random network) from inhomogeneous ones (local phase separation). The stochastic origin of the Gibbs-Di Marzio equation is predicted at low connectivity and the analytical expression of its parameter emerges naturally from the calculation.Comment: 5 pages, Revtex, accepted for publication in Europhysics Letters, 2 figures not included, available at http://www.gcr.jussieu.fr/matthieu.htm#Researc

Omega-3 fatty acids for the primary and secondary prevention of cardiovascular disease

Background: Researchers have suggested that omega-3 polyunsaturated fatty acids from oily fish (long-chain omega-3 (LCn3), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)), as well as from plants (alpha-linolenic acid (ALA)) benefit cardiovascular health. Guidelines recommend increasing omega-3-rich foods, and sometimes supplementation, but recent trials have not confirmed this. Objectives: To assess effects of increased intake of fish- and plant-based omega-3 for all-cause mortality, cardiovascular (CVD) events, adiposity and lipids. Search methods: We searched CENTRAL, MEDLINE and Embase to April 2017, plus ClinicalTrials.gov and World Health Organization International Clinical Trials Registry to September 2016, with no language restrictions. We handsearched systematic review references and bibliographies and contacted authors. Selection criteria: We included randomised controlled trials (RCTs) that lasted at least 12 months and compared supplementation and/or advice to increase LCn3 or ALA intake versus usual or lower intake. Data collection and analysis: Two review authors independently assessed studies for inclusion, extracted data and assessed validity. We performed separate random-effects meta-analysis for ALA and LCn3 interventions, and assessed dose-response relationships through meta-regression. Main results: We included 79 RCTs (112,059 participants) in this review update and found that 25 were at low summary risk of bias. Trials were of 12 to 72 months' duration and included adults at varying cardiovascular risk, mainly in high-income countries. Most studies assessed LCn3 supplementation with capsules, but some used LCn3- or ALA-rich or enriched foods or dietary advice compared to placebo or usual diet. Meta-analysis and sensitivity analyses suggested little or no effect of increasing LCn3 on all-cause mortality (RR 0.98, 95% CI 0.90 to 1.03, 92,653 participants; 8189 deaths in 39 trials, high-quality evidence), cardiovascular mortality (RR 0.95, 95% CI 0.87 to 1.03, 67,772 participants; 4544 CVD deaths in 25 RCTs), cardiovascular events (RR 0.99, 95% CI 0.94 to 1.04, 90,378 participants; 14,737 people experienced events in 38 trials, high-quality evidence), coronary heart disease (CHD) mortality (RR 0.93, 95% CI 0.79 to 1.09, 73,491 participants; 1596 CHD deaths in 21 RCTs), stroke (RR 1.06, 95% CI 0.96 to 1.16, 89,358 participants; 1822 strokes in 28 trials) or arrhythmia (RR 0.97, 95% CI 0.90 to 1.05, 53,796 participants; 3788 people experienced arrhythmia in 28 RCTs). There was a suggestion that LCn3 reduced CHD events (RR 0.93, 95% CI 0.88 to 0.97, 84,301 participants; 5469 people experienced CHD events in 28 RCTs); however, this was not maintained in sensitivity analyses - LCn3 probably makes little or no difference to CHD event risk. All evidence was of moderate GRADE quality, except as noted. Increasing ALA intake probably makes little or no difference to all-cause mortality (RR 1.01, 95% CI 0.84 to 1.20, 19,327 participants; 459 deaths, 5 RCTs),cardiovascular mortality (RR 0.96, 95% CI 0.74 to 1.25, 18,619 participants; 219 cardiovascular deaths, 4 RCTs), and it may make little or no difference to CHD events (RR 1.00, 95% CI 0.80 to 1.22, 19,061 participants, 397 CHD events, 4 RCTs, low-quality evidence). However, increased ALA may slightly reduce risk of cardiovascular events (from 4.8% to 4.7%, RR 0.95, 95% CI 0.83 to 1.07, 19,327 participants; 884 CVD events, 5 RCTs, low-quality evidence), and probably reduces risk of CHD mortality (1.1% to 1.0%, RR 0.95, 95% CI 0.72 to 1.26, 18,353 participants; 193 CHD deaths, 3 RCTs), and arrhythmia (3.3% to 2.6%, RR 0.79, 95% CI 0.57 to 1.10, 4,837 participants; 141 events, 1 RCT). Effects on stroke are unclear. Sensitivity analysis retaining only trials at low summary risk of bias moved effect sizes towards the null (RR 1.0) for all LCn3 primary outcomes except arrhythmias, but for most ALA outcomes, effect sizes moved to suggest protection. LCn3 funnel plots suggested that adding in missing studies/results would move effect sizes towards null for most primary outcomes. There were no dose or duration effects in subgrouping or meta-regression. There was no evidence that increasing LCn3 or ALA altered serious adverse events, adiposity or lipids, although LCn3 slightly reduced triglycerides and increased HDL. ALA probably reduces HDL (high- or moderate-quality evidence). Authors' conclusions: This is the most extensive systematic assessment of effects of omega-3 fats on cardiovascular health to date. Moderate- and high-quality evidence suggests that increasing EPA and DHA has little or no effect on mortality or cardiovascular health (evidence mainly from supplement trials). Previous suggestions of benefits from EPA and DHA supplements appear to spring from trials with higher risk of bias. Low-quality evidence suggests ALA may slightly reduce CVD event risk, CHD mortality and arrhythmia

Risk of Kaposi's sarcoma and of other cancers in Italian renal transplant patients

A follow-up study of 1844 renal transplant patients in Italy showed a 113-fold increased risk for Kaposi's sarcoma. Kaposi's sarcoma risk was higher in persons born in southern than in northern Italy. Significant increases were also observed for cancers of the lip, liver, kidney and for non-Hodgkin's lymphoma

Increased cancer risk in patients undergoing dialysis: A population-based cohort study in North-Eastern Italy

Background: In southern Europe, the risk of cancer in patients with end-stage kidney disease receiving dialysis has not been well quantified. The aim of this study was to assess the overall pattern of risk for de novo malignancies (DNMs) among dialysis patients in the Friuli Venezia Giulia region, north-eastern Italy. Methods: A population-based cohort study among 3407 dialysis patients was conducted through a record linkage between local healthcare databases and the cancer registry (1998-2013). Person-years (PYs) were calculated from 30 days after the date of first dialysis to the date of DNM diagnosis, kidney transplant, death, last follow-up or December 31, 2013, whichever came first. The risk of DNM, as compared to the general population, was estimated using standardized incidence ratios (SIRs) and 95% confidence intervals (CIs). Results: During 10,798 PYs, 357 DNMs were diagnosed in 330 dialysis patients. A higher than expected risk of 1.3-fold was found for all DNMs combined (95% CI: 1.15-1.43). The risk was particularly high in younger dialysis patients (SIR = 1.88, 95% CI: 1.42-2.45 for age 40-59 years), and it decreased with age. Moreover, significantly increased DNM risks emerged during the first 3 years since dialysis initiation, especially within the first year (SIR = 8.52, 95% CI: 6.89-10.41). Elevated excess risks were observed for kidney (SIR = 3.18; 95% CI: 2.06-4.69), skin non-melanoma (SIR = 1.81, 95% CI: 1.46-2.22), oral cavity (SIR = 2.42, 95% CI: 1.36-4.00), and Kaposi's sarcoma (SIR = 10.29, 95% CI: 1.25-37.16). Conclusions: The elevated risk for DNM herein documented suggest the need to implement a targeted approach to cancer prevention and control in dialysis patients