Are nitrate concentrations in leafy vegetables within safe limits?

Leafy vegetables are an important source of nutrition in the human diet. Estimation of nitrate concentration in samples of leafy vegetables collected from the local markets of Delhi has revealed that a significant number of spinach and chenopodium samples contained nitrate in concentrations higher than the Acceptable Daily Intake (ADI) limit for an average 60 kg person (if consumed @ 100 g/day). However, nitrate concentration in fenugreek, coriander and sowa samples was well within the safe limits for consumption. On the basis of our findings with market samples, extensive studies were conducted in nine genotypes of spinach (Spinacia oleracea L.) grown under greenhouse conditions. The genotypes varied markedly in their nitrate concentration as well as nitrate reductase activity. At the threeweek stage of plant growth, one genotype, and at the six-week stage, six of the nine genotypes under investigation exceeded the ADI limit. Petioles possessed several times higher level of nitrate than the leaf laminae in market samples as well as in the genotypes. All the genotypes showed diurnal variation in nitrate accumulation with minimum concentration at noon. These findings warrant thorough investigation of nitrate levels in other leafy vegetables consumed regularly and the ways and means to control them

A case study of bilayered spin-1/21/2 square lattice compound [VO(HCOO)2⋅_2\cdot(H2_2O)]

We present the synthesis and a detail investigation of structural and magnetic properties of polycrystalline [VO(HCOO)$_2\cdot$(H$_2$O)] by means of x-ray diffraction, magnetic susceptibility, high-field magnetization, heat capacity, and electron spin resonance measurements. It crystallizes in a orthorhombic structure with space group $Pcca$. It features distorted VO$_6$ octahedra connected via HCOO linker (formate anions) forming a two-dimensional square lattice network with a bilayered structure. Analysis of magnetic susceptibility, high field magnetization, and heat capacity data in terms of the frustrated square lattice model unambiguously establish quasi-two-dimensional nature of the compound with nearest neighbour interaction $J_1/k_{\rm B} \simeq 11.7$~K and next-nearest-neighbour interaction $J_2/k_{\rm B} \simeq 0.02$~K. It undergoes a N\'eel antiferromagnetic ordering at $T_{\rm N} \simeq 1.1$~K. The ratio $\theta_{\rm CW}/T_{\rm N} \simeq 10.9$ reflects excellent two-dimensionality of the spin-lattice in the compound. A strong in-plane anisotropy is inferred from the linear increase of $T_{\rm N}$ with magnetic field, consistent with the structural data.Comment: 9 pages, 7 figures, 1 tabl

Liver transplantation for hepatocellular carcinoma: Management after the transplant

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153700/1/ajt15697.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153700/2/ajt15697_am.pd

User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians’ expertise and computers’ potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the “strokes” and the “contour”, to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease

Effects of CuO additives and sol-gel technique on NiNb2O6 dielectric ceramics for LTCC application

The effects of CuO additives and sol–gel method synthesis on the sintering behavior, microstructure and the microwave dielectric properties of NiNb2O6 ceramics were investigated systematically. The NiNb2O6 ceramics were synthesized with traditional solid state method and sol–gel method, and the CuO additives were used in the solid state method for comparison. The sintering temperature of NiNb2O6 ceramics with the highest densification can be effectively reduced from about 1275 °C to 1050 and 1100 °C respectively by using CuO additions and sol–gel technique. To study their applicability in low temperature co-fired ceramic technology, dielectric properties have been characterized. The dielectric properties exhibited a significant dependence on the sintering condition, composition and crystal structure of the ceramics. In particular, the 2.5 wt% CuO-doped NiNb2O6 ceramics sintered at 1050 °C have excellent microwave dielectric properties: εr = 21.45, Q × f = 23,531 GHz, τf = −27.9 ppm/°C. While the NiNb2O6 ceramics prepared by sol–gel method obtain microwave dielectric properties as: εr = 19.16, Q × f = 11,149 GHz, τf = −27.3 ppm/°C after sintered at 1100 °C for 2 h

Young onset diabetes in Asian Indians is associated with lower measured and genetically determined beta-cell function:an INSPIRED study

Aims/hypothesis: South Asians in general, and Asian Indians in particular, have higher risk of type 2 diabetes compared with white Europeans, and a younger age of onset. The reasons for the younger age of onset in relation to obesity, beta cell function and insulin sensitivity are under-explored. Methods: Two cohorts of Asian Indians, the ICMR-INDIAB cohort (Indian Council of Medical Research-India Diabetes Study) and the DMDSC cohort (Dr Mohan’s Diabetes Specialties Centre), and one of white Europeans, the ESDC (East Scotland Diabetes Cohort), were used. Using a cross-sectional design, we examined the comparative prevalence of healthy, overweight and obese participants with young-onset diabetes, classified according to their BMI. We explored the role of clinically measured beta cell function in diabetes onset in Asian Indians. Finally, the comparative distribution of a partitioned polygenic score (pPS) for risk of diabetes due to poor beta cell function was examined. Replication of the genetic findings was sought using data from the UK Biobank. Results: The prevalence of young-onset diabetes with normal BMI was 9.3% amongst white Europeans and 24–39% amongst Asian Indians. In Asian Indians with young-onset diabetes, after adjustment for family history of type 2 diabetes, sex, insulin sensitivity and HDL-cholesterol, stimulated C-peptide was 492 pmol/ml (IQR 353–616, p<0.0001) lower in lean compared with obese individuals. Asian Indians in our study, and South Asians from the UK Biobank, had a higher number of risk alleles than white Europeans. After weighting the pPS for beta cell function, Asian Indians have lower genetically determined beta cell function than white Europeans (p<0.0001). The pPS was associated with age of diagnosis in Asian Indians but not in white Europeans. The pPS explained 2% of the variation in clinically measured beta cell function, and 1.2%, 0.97%, and 0.36% of variance in age of diabetes amongst Asian Indians with normal BMI, or classified as overweight and obese BMI, respectively. Conclusions/interpretation: The prevalence of lean BMI in young-onset diabetes is over two times higher in Asian Indians compared with white Europeans. This phenotype of lean, young-onset diabetes appears driven in part by lower beta cell function. We demonstrate that Asian Indians with diabetes also have lower genetically determined beta cell function