The use of the scintillation technique for monitoring seasonal water consumption of olive orchards in a semi-arid region

To monitor seasonal water consumption of agricultural fields at large scale, spatially averaged surface fluxes of sensible heat (H) and latent heat (LvE) are required. The scintillation method is shown to be a promising device for obtaining the area-averaged sensible heat fluxes, on a scale of up to 10 km. These fluxes, when combined with a simple available energy model, can be used to derive area-averaged latent heat fluxes. For this purpose, a Large Aperture Scintillometer (LAS) was operated continuously for more than one year over a tall and sparse irrigated oliveyard located in south-central Marrakesh (Morocco). Due to the flood irrigation method used in the site, which induces irregular pattern of soil moisture both in space and time, the comparison between scintillometer-based estimates of daily sensible heat flux (HLAS) and those measured by the classical eddy covariance (EC) method (HEC) showed a large scatter during the irrigation events, while a good correspondence was found during homogenous conditions (dry conditions and days following the rain events). We found, that combining a simple available energy model and the LAS measurements, the latent heat can be reliably predicted at large scale in spite of the large scatter (R2 = 0.72 and RMSE = 18.25Wm2) that is obtained when comparing the LAS against the EC. This scatter is explained by different factors: the difference in terms of the source areas of the LAS and EC, the closure failure of the energy balance of the EC, and the error in available energy estimates. Additionally, the irrigation efficiency was investigated by comparing measured seasonal evapotranspiration values to those recommended by the FAO. It was found that the visual observation of the physical conditions of the plant is not sufficient to efficiently manage the irrigation, a large quantity of water is lost (37% of total irrigation). Consequently, the LAS can be considered as a potentially useful tool to monitor the water consumption in complex conditions

Endoplasmic Reticulum Stress Links Oxidative Stress to Impaired Pancreatic Beta-Cell Function Caused by Human Oxidized LDL.

Elevated plasma concentration of the pro-atherogenic oxidized low density lipoprotein cholesterol (LDL) triggers adverse effects in pancreatic beta-cells and is associated with type 2 diabetes. Here, we investigated whether the endoplasmic reticulum (ER) stress is a key player coupling oxidative stress to beta-cell dysfunction and death elicited by human oxidized LDL. We found that human oxidized LDL activates ER stress as evidenced by the activation of the inositol requiring 1α, and the elevated expression of both DDIT3 (also called CHOP) and DNAJC3 (also called P58IPK) ER stress markers in isolated human islets and the mouse insulin secreting MIN6 cells. Silencing of Chop and inhibition of ER stress markers by the chemical chaperone phenyl butyric acid (PBA) prevented cell death caused by oxidized LDL. Finally, we found that oxidative stress accounts for activation of ER stress markers induced by oxidized LDL. Induction of Chop/CHOP and p58IPK/P58IPK by oxidized LDL was mimicked by hydrogen peroxide and was blocked by co-treatment with the N-acetylcystein antioxidant. As a conclusion, the harmful effects of oxidized LDL in beta-cells requires ER stress activation in a manner that involves oxidative stress. This mechanism may account for impaired beta-cell function in diabetes and can be reversed by antioxidant treatment

KAT2B Is Required for Pancreatic Beta Cell Adaptation to Metabolic Stress by Controlling the Unfolded Protein Response.

The endoplasmic reticulum (ER) unfolded protein response (UPR(er)) pathway plays an important role in helping pancreatic β cells to adapt their cellular responses to environmental cues and metabolic stress. Although altered UPR(er) gene expression appears in rodent and human type 2 diabetic (T2D) islets, the underlying molecular mechanisms remain unknown. We show here that germline and β cell-specific disruption of the lysine acetyltransferase 2B (Kat2b) gene in mice leads to impaired insulin secretion and glucose intolerance. Genome-wide analysis of Kat2b-regulated genes and functional assays reveal a critical role for Kat2b in maintaining UPR(er) gene expression and subsequent β cell function. Importantly, Kat2b expression is decreased in mouse and human diabetic β cells and correlates with UPR(er) gene expression in normal human islets. In conclusion, Kat2b is a crucial transcriptional regulator for adaptive β cell function during metabolic stress by controlling UPR(er) and represents a promising target for T2D prevention and treatment

Alpha-band rhythms in visual task performance: phase-locking by rhythmic sensory stimulation

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8-12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data

Summary: TREAT (Targeted RE-sequencing Annotation Tool) is a tool for facile navigation and mining of the variants from both targeted resequencing and whole exome sequencing. It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments

Zoonotic hepatitis E: animal reservoirs and emerging risks

Hepatitis E virus (HEV) is responsible for enterically-transmitted acute hepatitis in humans with two distinct epidemiological patterns. In endemic regions, large waterborne epidemics with thousands of people affected have been observed, and, in contrast, in non-endemic regions, sporadic cases have been described. Although contaminated water has been well documented as the source of infection in endemic regions, the modes of transmission in non-endemic regions are much less known. HEV is a single-strand, positive-sense RNA virus which is classified in the Hepeviridae family with at least four known main genotypes (1–4) of mammalian HEV and one avian HEV. HEV is unique among the known hepatitis viruses, in which it has an animal reservoir. In contrast to humans, swine and other mammalian animal species infected by HEV generally remain asymptomatic, whereas chickens infected by avian HEV may develop a disease known as Hepatitis-Splenomegaly syndrome. HEV genotypes 1 and 2 are found exclusively in humans while genotypes 3 and 4 are found both in humans and other mammals. Several lines of evidence indicate that, in some cases involving HEV genotypes 3 and 4, animal to human transmissions occur. Furthermore, individuals with direct contact with animals are at higher risk of HEV infection. Cross-species infections with HEV genotypes 3 and 4 have been demonstrated experimentally. However, not all sources of human infections have been identified thus far and in many cases, the origin of HEV infection in humans remains unknown