Plant water relations, crop yield and quality of arabica coffee (Coffea arabica) as affected by supplemental deficit irrigation.

Low amount and erratic distribution of the seasonal precipitation and recurrent droughts are major threats to coffee production in Ethiopia. This necessitates application of supplemental deficit irrigation for coffee production. This study evaluated the impact of two supplemental irrigations, viz. supplemental full (SFI) and deficit irrigation (SDI) in comparison to rain-fed (RF) control on plant water relations, yield and quality of Coffea arabica L. during the dry season using three cultivars (cv. F-59, 74110 and 75227). Supplemental full irrigation consistently improved soil and plant water status and stomatal conductance (gs) during the dry season and resulted in significantly higher yield. However, the difference between SFI and SDI was not significant for crop yield, but had higher yield than RF control. Overall quality in terms of raw appearance and total quality of coffee beans was substantially improved and the amount of irrigation water applied was considerably reduced by SDI compared to SFI practice. Therefore, SDI appears to be more effective than SFI for coffee production in areas of frequent water scarcity and recurrent drought as for eastern and northern parts of Ethiopia

Iodine supplementation of lactating women and assessment of infant visual information processing and maternal and infant thyroid function: A randomized trial

Iodine deficiency is one of the major causes of brain damage in childhood. However, iodine supplementation during early pregnancy and lactation can prevent the ill effects of iodine deficiency. This study evaluated maternal and infant thyroid function and infant visual information processing (VIP) in the context of maternal iodine supplementation. A community-based, randomized, supplementation trial was conducted. Mother infant dyads (n = 106) were enrolled within the first 10 days after delivery to participate in this study. Mothers were randomly assigned either to receive a potassium iodide capsule (225 μg iodine) daily for 26 weeks or iodized salt weekly for 26 weeks. Maternal thyroxine (T4), triiodothyronine (T3), thyroid stimulating hormone (TSH), thyroglobulin (Tg), urinary iodine concentration (UIC), breast milk iodine concentration (BMIC) and infant T4, TSH, UIC and VIP were measured as outcome variables. At baseline, neither mothers nor infants in the two groups were significantly different in any of the biomarkers or anthropometric measurements. Maternal TSH and goiter prevalence significantly decreased following iodine supplementation. The percentage of infants who preferentially remembered the familiar face was 26% in the capsule and 51% in the I-salt groups. Infant sex, length for age Z score, BMIC, maternal education and household food security were strong predictors of novelty quotient. In conclusion supplementation daily for six months with an iodine capsule or the use of appropriately iodized salt for an equivalent time was sufficient to reduce goiter and TSH in lactating women. Higher BMIC and LAZ as well as better household food security, maternal education, and male sex predicted higher novelty quotient scores in the VIP paradigm

Noninvasive Evaluation of Neural Impairment in Subjects With Impaired Glucose Tolerance

OBJECTIVE—To evaluate neural dysfunction in subjects with impaired glucose tolerance (IGT)

New perspective in diabetic neuropathy: From the periphery to the brain, a call for early detection, and precision medicine

Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes mellitus. It leads to distressing and expensive clinical sequelae such as foot ulceration, leg amputation, and neuropathic pain (painful-DPN). Unfortunately, DPN is often diagnosed late when irreversible nerve injury has occurred and its first presentation may be with a diabetic foot ulcer. Several novel diagnostic techniques are available which may supplement clinical assessment and aid the early detection of DPN. Moreover, treatments for DPN and painful-DPN are limited. Only tight glucose control in type 1 diabetes has robust evidence in reducing the risk of developing DPN. However, neither glucose control nor pathogenetic treatments are effective in painful-DPN and symptomatic treatments are often inadequate. It has recently been hypothesized that using various patient characteristics it may be possible to stratify individuals and assign them targeted therapies to produce better pain relief. We review the diagnostic techniques which may aid the early detection of DPN in the clinical and research environment, and recent advances in precision medicine techniques for the treatment of painful-DPN

Transcript profiling of two alfalfa genotypes with contrasting cell wall composition in stems using a cross-species platform: optimizing analysis by masking biased probes

<p>Abstract</p> <p>Background</p> <p>The GeneChip^®<it>Medicago </it>Genome Array, developed for <it>Medicago truncatula</it>, is a suitable platform for transcript profiling in tetraploid alfalfa [<it>Medicago sativa </it>(L.) subsp. <it>sativa</it>]. However, previous research involving cross-species hybridization (CSH) has shown that sequence variation between two species can bias transcript profiling by decreasing sensitivity (number of expressed genes detected) and the accuracy of measuring fold-differences in gene expression.</p> <p>Results</p> <p>Transcript profiling using the <it>Medicago </it>GeneChip^®was conducted with elongating stem (ES) and post-elongation stem (PES) internodes from alfalfa genotypes 252 and 1283 that differ in stem cell wall concentrations of cellulose and lignin. A protocol was developed that masked probes targeting inter-species variable (ISV) regions of alfalfa transcripts. A probe signal intensity threshold was selected that optimized both sensitivity and accuracy. After masking for both ISV regions and previously identified single-feature polymorphisms (SFPs), the number of differentially expressed genes between the two genotypes in both ES and PES internodes was approximately 2-fold greater than the number detected prior to masking. Regulatory genes, including transcription factor and receptor kinase genes that may play a role in development of secondary xylem, were significantly over-represented among genes up-regulated in 252 PES internodes compared to 1283 PES internodes. Several cell wall-related genes were also up-regulated in genotype 252 PES internodes. Real-time quantitative RT-PCR of differentially expressed regulatory and cell wall-related genes demonstrated increased sensitivity and accuracy after masking for both ISV regions and SFPs. Over 1,000 genes that were differentially expressed in ES and PES internodes of genotypes 252 and 1283 were mapped onto putative orthologous loci on <it>M. truncatula </it>chromosomes. Clustering simulation analysis of the differentially expressed genes suggested co-expression of some neighbouring genes on <it>Medicago </it>chromosomes.</p> <p>Conclusions</p> <p>The problems associated with transcript profiling in alfalfa stems using the <it>Medicago </it>GeneChip as a CSH platform were mitigated by masking probes targeting ISV regions and SFPs. Using this masking protocol resulted in the identification of numerous candidate genes that may contribute to differences in cell wall concentration and composition of stems of two alfalfa genotypes.</p

Modeling of Multivariate Longitudinal Phenotypes in Family Genetic Studies with Bayesian Multiplicity Adjustment

Genetic studies often collect data on multiple traits. Most genetic association analyses, however, consider traits separately and ignore potential correlation among traits, partially because of difficulties in statistical modeling of multivariate outcomes. When multiple traits are measured in a pedigree longitudinally, additional challenges arise because in addition to correlation between traits, a trait is often correlated with its own measures over time and with measurements of other family members. We developed a Bayesian model for analysis of bivariate quantitative traits measured longitudinally in family genetic studies. For a given trait, family-specific and subject-specific random effects account for correlation among family members and repeated measures, respectively. Correlation between traits is introduced by incorporating multivariate random effects and allowing time-specific trait residuals to correlate as in seemingly unrelated regressions. The proposed model can examine multiple single-nucleotide variations simultaneously, as well as incorporate familyspecific, subject-specific, or time-varying covariates. Bayesian multiplicity technique is used to effectively control false positives. Genetic Analysis Workshop 18 simulated data illustrate the proposed approach\u27s applicability in modeling longitudinal multivariate outcomes in family genetic association studies