Gene expression is regulated mainly by transcription factors (TFs) that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS) using position weight matrices (PWMs) that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions.We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI) against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster), we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI.Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1) those that show TFBS clustered in promoters associated with CGI, and (2) those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in regulatory regions.
The strong familiality of living to extreme ages suggests that human longevity is genetically regulated. The majority of genes found thus far to be associated with longevity primarily function in lipoprotein metabolism and insulin/IGF-1 signaling. There are likely many more genetic modifiers of human longevity that remain to be discovered.
In order to know how to live longer and healthy, we conducted centenarian study with multidisciplinary approach since 2000. We presented here the results of our study. The characteristics of centenarians are 1) low prevalence of diadetes mellitus, 2) frequency of illness is 97%,3) prevalence of dementia free and independent centenarian is 18%, 4)low level of albumin, 5) low-grade activation of inflammation, 6) high level of adiponectin. We proposed aging-inflammation hypothesis. Since centenarian is not the model of healthy longevity, we began to study semisupercentenarians (SSC). SSC are considered to be a real model of human longevity. Whole genome scan of both SSC and control group, is now in progress. We hope that longevity genes will identified within a few years.
A 79-year-old male with phenacetin abuse was admitted to our University Hospital for treatment of asymptomatic gross hematuria. Intravenous urograpdy and computed tomography revealed synchronous right renal pelvic carcinoma and bladder carcinoma. Right nephroureterectomy and transurethral resection of bladder tumor (TUR-Bt) were performed. Histologically, right renal pelvic tumor and bladder tumor were both transitional cell carcinomas of grade 2, pT1, and grade 1 = 2, Ta, respectively. Additionally, pathological examination revealed two distal ureteral tumors, which were transitional cell carcinomas of grade 2, pTa. He also had a history of heavy tobacco-smoking (20 cigarettes per day for 50 years). We discuss the relationship between transitional cell carcinoma and phenacetin abuse as well as the influence of tobacco-smoking, and review the literature.
To integrate CAD and CAM systems, data for CAM system such as dimensional tolerance, geometric tolerance and surface roughness must be generated from CAD data. This sort of technical information is generally obtained in the course of detailing part specifications from assembly drawing. This study discusses a method of automatic determination of part specification for a rotational functional units of machines such as spindle head or gear box. The determination of technical information for machining is based on the assembly data model which consists of fit and contact relations among parts. The method of dimensional tolerancing along shaft axis proposed is formulated not to violate the clamping function which is realized by bolts and nuts. It is formulated as a set of rules which extracts the loops of connective relations and sets dimensional tolerance. The rule to set radial tolerance, geometric tolerance and surface roughness from connective relations and part function is also described. An experimental prolog program, which automatically generates tolerance information by using the rules mentioned above, proved itself to work properly through examples.
