Exposure from the Chernobyl accident had adverse effects on erythrocytes, leukocytes, and, platelets in children in the Narodichesky region, Ukraine: A 6-year follow-up study

<p>Abstract</p> <p>Background</p> <p>After the Chernobyl nuclear accident on April 26, 1986, all children in the contaminated territory of the Narodichesky region, Zhitomir Oblast, Ukraine, were obliged to participate in a yearly medical examination. We present the results from these examinations for the years 1993 to 1998. Since the hematopoietic system is an important target, we investigated the association between residential soil density of ¹³⁷Caesium (¹³⁷Cs) and hemoglobin concentration, and erythrocyte, platelet, and leukocyte counts in 1,251 children, using 4,989 repeated measurements taken from 1993 to 1998.</p> <p>Methods</p> <p>Soil contamination measurements from 38 settlements were used as exposures. Blood counts were conducted using the same auto-analyzer in all investigations for all years. We used linear mixed models to compensate for the repeated measurements of each child over the six year period. We estimated the adjusted means for all markers, controlling for potential confounders.</p> <p>Results</p> <p>Data show a statistically significant reduction in red and white blood cell counts, platelet counts and hemoglobin with increasing residential ¹³⁷Cs soil contamination. Over the six-year observation period, hematologic markers did improve. In children with the higher exposure who were born before the accident, this improvement was more pronounced for platelet counts, and less for red blood cells and hemoglobin. There was no exposure×time interaction for white blood cell counts and not in 702 children who were born after the accident. The initial exposure gradient persisted in this sub-sample of children.</p> <p>Conclusion</p> <p>The study is the first longitudinal analysis from a large cohort of children after the Chernobyl accident. The findings suggest persistent adverse hematological effects associated with residential ¹³⁷Cs exposure.</p

Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions

<p>Abstract</p> <p>Background</p> <p>Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered.</p> <p>Results</p> <p>To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-κB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies.</p> <p>To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA.</p> <p>Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies.</p> <p>Conclusion</p> <p>Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs.</p

The formation of human populations in South and Central Asia

By sequencing 523 ancient humans, we show that the primary source of ancestry in modern South Asians is a prehistoric genetic gradient between people related to early hunter-gatherers of Iran and Southeast Asia. After the Indus Valley Civilization’s decline, its people mixed with individuals in the southeast to form one of the two main ancestral populations of South Asia, whose direct descendants live in southern India. Simultaneously, they mixed with descendants of Steppe pastoralists who, starting around 4000 years ago, spread via Central Asia to form the other main ancestral population. The Steppe ancestry in South Asia has the same profile as that in Bronze Age Eastern Europe, tracking a movement of people that affected both regions and that likely spread the distinctive features shared between Indo-Iranian and Balto-Slavic languages