Adiponectin levels in people with Latent Autoimmune Diabetes-a case control study

<p>Abstract</p> <p>Background</p> <p>To examine adiponectin levels in people with Latent Autoimmune Diabetes in Adults using a matched pair case control study.</p> <p>Findings</p> <p>Patients with LADA (n = 64), were matched for sex with type 2 diabetic and non-diabetic controls. A matched paired T-test was used to examine average adiponectin levels in the LADA patients' versus controls. The average adiponectin level for the LADA patients was 9.96 μg/ml compared to 6.4 μg/ml for Type 2 matched controls and 9.6 μg/ml for non-diabetic controls. Mean difference for the LADA-type 2 comparison was calculated after data was log transformed and showed a difference of 1.58 μg/ml (95%CI: 1.28-1.95, p = 0.0001). There was no significant difference between LADA and non-diabetic controls (p = 0.54).</p> <p>Conclusions</p> <p>Adiponectin levels are higher among people with LADA compared to those with type 2 diabetes and are equivalent to levels seen in non-diabetic controls. This suggests that risk of complications in LADA, as with type 1 diabetes may be related more to glycaemic control rather than to factors of the metabolic syndrome.</p

Differential Repair Protein Recruitment at Sites of Clustered and Isolated DNA Double-Strand Breaks Produced by High-Energy Heavy Ions

DNA double-strand break (DSB) repair is crucial to maintain genomic stability. The fidelity of the repair depends on the complexity of the lesion, with clustered DSBs being more difficult to repair than isolated breaks. Using live cell imaging of heavy ion tracks produced at a high-energy particle accelerator we visualised simultaneously the recruitment of different proteins at individual sites of complex and simple DSBs in human cells. NBS1 and 53BP1 were recruited in a few seconds to complex DSBs, but in 40% of the isolated DSBs the recruitment was delayed approximately 5 min. Using base excision repair (BER) inhibitors we demonstrate that some simple DSBs are generated by enzymatic processing of base damage, while BER did not affect the complex DSBs. The results show that DSB processing and repair kinetics are dependent on the complexity of the breaks and can be different even for the same clastogenic agent

Analysis of the relationships between vegetation water content obtained from field measurements and vegetation indices

Monitoring the plant moisture has a significant role in geographical research. It may be used, among the others, for climate modelling, agricultural predicting, rational water management, drought monitoring and determining vulnerability to the occurrence of the fire. Traditional methods, based on field measurements, are the most accurate, but also time-consuming. Therefore these methods can be applied only in a limited area. In order to explore bigger areas remote sensing methods are useful. To analyse plant condition and water content vegetation indices can be used. Their calculations are based on the reflectance in different bands. Despite many studies conducted on the development of remote sensing indices, still there is a need for verification of their accuracy and usefulness by comparing the results obtained through remote sensing tools with the results of field measurements. In this paper three indices are used: Moisture Stress Index (MSI), Normalized Difference Infrared Index (NDII) and transformation Tasseled Cap (the Wetness band). The aim of this study was to compare the value of vegetation indices calculated using images from Landsat 5 Thematic Mapper with the results of field measurement from five test areas of different type of land cover: cereal crops, non-cereal crops, forests, meadows and pastures. Research was carried out in province Ontario (Canada) and consisted of two stages. The first stage was the fi eld measurements, where the specified number of plant samples was collected and water content was calculated. The second stage consisted of the preparation of relevant satellite images (atmospheric correction and making the mosaic) and the calculation of vegetation indices. The study has shown, that statistical relationships between data sets obtained through remote sensing indices and calculated on the basis of field measurements are diverse for different indices. MSI and NDII values are significantly correlated with the water content in plants (R= -0.62 and 0.56, respectively). The correlation of TCW was rated as moderate (R=0.30). Spatial distribution of water content based on maps created using NDII and MSI is similar. It was noticed that TC Wetness transformation overestimates water content in cereal plants (smaller water content) and underestimates it in natural green plant ecosystems, which generally have higher water content. As a result, the range of water content values obtained from TCW is more narrow (dominates the class of 60-70% water in plants) than the range of values calculated using NDII and MSI. Both indices have more uniform distribution dominated by the classes of moderate water content (50-60%), rather wet plants (60-70%) and very wet plants (70-80%). Each index is characterized by different distribution of the water content. In general values calculated on the basis of NDII and MSI are higher than calculated using TCW. In order to perform more accurate analysis between values calculated using satellite images and the results of field measurements, the values of particular types of land cover should be compared

The type 2 diabetes-associated variant in TCF7L2 is associated with latent autoimmune diabetes in adult Europeans and the gene effect is modified by obesity: a meta-analysis and an individual study.

AIMS/HYPOTHESIS: The variants of transcription factor 7-like 2 (TCF7L2) gene have been proposed to be associated with latent autoimmune diabetes in adults (LADA). We sought to confirm the possible association in Europeans and to examine the interaction between one gene variant and clinical data. METHODS: The TCF7L2 rs7903146 C-to-T polymorphism was genotyped in 211 LADA, 1,297 type 2 diabetic, 545 type 1 diabetic and 1,497 control individuals from Hungary. A meta-analysis of our and previously published studies was performed to evaluate the size and the heterogeneity of the gene effect. RESULTS: The meta-analysis yielded a significant effect of TCF7L2 T allele (OR 1.28; p < 0.0001) on LADA risk without heterogeneity among Europeans. The T allele conferred equally strong susceptibility to LADA and type 2 diabetes. In the Hungarian dataset, the T allele was associated with LADA and type 2 diabetes, but not with type 1 diabetes. T allele carriers had significantly lower BMI than patients with the CC genotype in the LADA and type 2 diabetes groups (p = 0.0021 and p = 0.0013, respectively). In both diseases, the diabetes risk was significantly higher in the non-overweight than in the overweight BMI category (p = 0.0013 and p < 0.0001, respectively); susceptibility to LADA was increased by 2.84-fold in non-overweight individuals compared with overweight ones. CONCLUSIONS/INTERPRETATION: The meta-analysis demonstrates that TCF7L2 rs7903146 polymorphism is a population-independent susceptibility locus for LADA in Europeans. The effect size is similar for LADA and type 2 diabetes. The gene effect on diabetes risk may be modulated by BMI, such that the lower the BMI, the higher the gene effect