No abstract available.

No abstract available.
Clubfoot*

No abstract available.
Carcinoma, Basal Cell* ; Mohs Surgery* ; Sutures*

No abstract available.

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional FST measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the FST estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.
Bayes Theorem ; Coat Protein Complex I ; DNA Copy Number Variations ; Ethnic Groups ; Gene Frequency ; Genome ; Humans ; Markov Chains ; Selection, Genetic

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional FST measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the FST estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.
Bayes Theorem ; Coat Protein Complex I ; DNA Copy Number Variations ; Ethnic Groups ; Gene Frequency ; Genome ; Humans ; Markov Chains ; Selection, Genetic

The subjects, under 18 old, 2,694 children who visited ER during 199H, were surveyed by the Triage and other statical data. The results were as follows : 1. The male to female ratio was 1.7 : 1, and the toddler(1-4 old) was the majority. 2. Triage : critical 1.3%, acute 14.6%, urgent 29.5%, nonemergent 54.6%. 3. The reasons of visiting ER : 1) The children had diseases(46.5%), injury (36.9%), TA(5.6%) and toxication(1.0%). 2) In diseases, male to female ratio was 1.5 : 1 and in injury, male to female was 2 : 1. 3) Among the children having in TA, 12-18 old groups was the majority(34.9%). 4. The time of visiting ; the 20 : 00-22 : 00 was the majority(16.9%). 5. By monthly and seasonal distribution ; Jan. (9.7%?), Mar. and May(9%) respectively, Dec. and July(6.7%) respectively. The children who visited ER in spring and autumn showed higher portion than those of summer and winter. 6. Results : admission(27.4%), discharge(68.4%), operations(2.8%), and DOA and DAA(0.4%). The mortality of the infancy and toddler groups was 83.3%. The infancy group showed the highest rate of admission. 7. The time of staying in ER : 1-2 hrs was the major group(23.3%) and the average was 4.6 hours. 8. By clinical departments ; Ped, was 34.4%, PS was 20.8.%, Dental Surgery was 10.3% and Dermatology was 0.9%. 9. The types of visiting : the group who visited by themselves was 80%, transfer from the primary and secondary clinic was 17% and OPD was 3.0%. 10. The traffic means ; by the own cars and taxi were 87.6%, by hospital ambulance was 6.1% and by 119 ambulance was 4.3%.
Ambulances ; Child* ; Dermatology ; Emergencies* ; Emergency Service, Hospital* ; Female ; Humans ; Male ; Mortality ; Seasons ; Triage* ; Child Health

MDCT has recently been used as a diagnostic tool to evaluate coronary artery stenosis and to detect coronary artery anomalies. The accuracy of MDCT has improved the assessment of stenosis as the number of detectors has increased. In addition to its excellent role in evaluating coronary artery stenosis, MDCT can provide information regarding the left ventricular function without having to perform additional scanning, and the myocardial viability of the left ventricle can be assessed on a delayed scan. MDCT has several disadvantages such as the amount of radiation exposure and the use of an iodine contrast medium, which might cause an adverse reaction, when combined with the reconstruction of the systolic and diastolic phases and the delayed scan. Yet MDCT may provide the opportunity to evaluate the coronary anatomy, the left ventricular function and the tissue characterization in one single imaging session that lasts less than 15 minutes.
Constriction, Pathologic ; Coronary Stenosis ; Coronary Vessels ; Heart Ventricles ; Infarction ; Iodine ; Myocardium ; Perfusion* ; Tomography, X-Ray Computed ; Ventricular Function, Left*

The purpose of this study is to analyze ER patient's Triage and other statistical data. The subjects were 12,618 patients who visited the ER during the year 1998. The study showed the following results; 1. The male vs female ratio was 1.3 : 1.0, the male were in the majority (56.6%), and the age range of 20-29 old was the majority (15.3). The patients who visited ER at 8-10 pm were the majority (11.5%). On Sunday the number of patients who visited the ER were 2,189, and the majority were 17.4%. On Saturday the number of patients was visited the ER were 1,944 patients the second majority (15.4%). Their traffic means : the general passenger cars (75.5%), 119 or hospital ambulance (11.3%). 2. The reasons of visiting ER were : diseases (59.2%), injuries (23.7%). The disease vs injury ratio was 100 : 69. 3. Triage : urgent 40.7%, non-urgent 38.2%, acute 17.8%, and critical 3.2%. 4. The time of waiting and staying in the ER by the Triaget: the average time was 572 minutes (9.53 hrs.). The majority of critical patients (20.5%), acute patients (24.7%) and urgent patients (21.2%) stayed 12-24 hrs., but the majority of non-emergent (27.8%) stayed not longer than one hour. 5. Treatments by the Triage : the 42.9% of critical patients, and 61.3% of acute patients, 57.5% of urgent patients were admitted. But 91.8% of the non-emergents were discharged and 4.7% was admitted. Mortality of total ER visiter were 1.7%. DAA portion was 0.86%. 26.6% of the critical patients were DAA. DAA vs DOA ratio was 1.3 : 1.0. 6. Visiting time, monthly and seasonal distribution by the Triage : the majority of critical patients (12.2%), visited 10-12 am. The majority of acute (12.9%) and urgent (11.7%) visited 4-6 pm, but the majority of non-emergents (15.1%) visited during 8-10 pm. Autumn visiter were the majority (27.6%). The percentage of non-emergent visited in Spring was 41.4% and Autumn was 41.3%. The percentage of urgents who visited in the Summer was 45.3% and the Winter was 40.4%. By clinical departments: the 48.0% of critical patients was NS. The 45.5% of acute and the 33.6% of urgent patients were IM. But the majority of non-emergent patients was PS (21.2%), and the second majority of non-emergent patients was oral Surgery (12.8%).
Ambulances ; Emergencies* ; Emergency Service, Hospital* ; Female ; Humans ; Male ; Mortality ; Seasons ; Surgery, Oral ; Triage*

No abstract available.
Foot* ; Neuroma*