Human Papillomavirus Vaccine

Cervical cancer is the second most common cancer affecting women worldwide. Cervical cancer is caused by persistent infection with high-risk types of human papillomavirus (HPV). The most common oncogenic HPV genotypes are 16 and 18, causing approximately 70% of all cervical cancers. Recently, two HPV vaccines, quadrivalent (HPV 6, 11, 16, 18) and bivalent (HPV 16, 18) vaccines, have been licensed and are now marketed in Korea. HPV vaccines are prepared from virus-like particles (VLPs) produced by recombinant technology. Clinical trials have confirmed that both vaccines have high efficiency against persistent infection of HPV 16 or 18 and moderate to severe precancerous lesions. In women who have no evidence of past or current infection with the HPV genotypes in the vaccine, both vaccines show > 90% protection against persistent HPV infection for up to 5 years after vaccination. In addition, vaccine efficacy against precancerous lesions associated with HPV 16/18 was reported to be 100%. Although most clinical trials to date have investigated the effectiveness of HPV vaccines in young females, elderly females and males may also be candidates for HPV vaccines. Since HPV vaccines are prophylactic, the largest impact of vaccination is expected to result from high coverage of young adolescents before exposure to HPV. Cervical cancer screening will still be required, even after HPV vaccines are introduced, although the screening program may need to be adapted to achieve cost-effective reductions in the burden of cervical cancer prevention strategies.Munoz N, 2009, LANCET, V373, P1949, DOI 10.1016/S0140-6736(09)60691-7Brown DR, 2009, J INFECT DIS, V199, P926, DOI 10.1086/597307PAAVONEN J, 2009, LANCET, V374, P301, DOI 10.1016/S0140-6736(09)61248-4PATAJA T, 2009, J ADOLESCENT HEALTH, V44, P33Koshiol J, 2008, AM J EPIDEMIOL, V168, P123, DOI 10.1093/aje/kwn036Derkay CS, 2008, LARYNGOSCOPE, V118, P1236, DOI 10.1097/MLG.0b013e31816a7135Franekova M, 2008, UROL ONCOL-SEMIN ORI, V26, P1, DOI 10.1016/j.urolonc.2006.10.011RONCO G, 2008, BMC WOMENS HLTH, V8, P23Smith JF, 2007, HUM VACCINES, V3, P109Olsson SE, 2007, VACCINE, V25, P4931, DOI 10.1016/j.vaccine.2007.03.049Villa L, 2007, LANCET, V369, P1861Garland SM, 2007, NEW ENGL J MED, V356, P1928Dunne EF, 2007, JAMA-J AM MED ASSOC, V297, P8132007, N ENGL J MED, V356, P1915Villa LL, 2006, BRIT J CANCER, V95, P1459, DOI 10.1038/sj.bjc.6603469Chung HH, 2006, INT J GYNECOL CANCER, V16, P1833, DOI 10.1111/j.1525-1438.2006.00708.xHarper DM, 2006, LANCET, V367, P1247, DOI 10.1016/S01406736(06)68439-0Mao C, 2006, OBSTET GYNECOL, V107, P18STANLEY M, 2006, VACCINE S1, V24, pS16Villa LL, 2005, LANCET ONCOL, V6, P271, DOI 10.1016/S1470-2045(05)70101-7Clifford GM, 2003, BRIT J CANCER, V88, P63, DOI 10.1038/sj.bjc.6600688PARKIN DM, 2003, VACCINE S3, V24PARKIN DM, 2002, CA CANC J CLIN, V55, P74Carter JJ, 2000, J INFECT DIS, V181, P1911HAGENSEE ME, 1993, J VIROL, V67, P315

자궁내막암에서 mammalian target of rapamycin의 발현과 cyclooxygenase-2와의 관련성에 관한 연구

Thesis(master`s)--서울대학교 대학원 :의학과 산부인과학전공,2007.Maste

Efficient Sorting Architecture for Fast Simplified SC List Polar Decoder

학위논문(석사)--아주대학교 일반대학원 :전자공학과,2022. 2I. Introduction 1 II. Preliminaries 4 A. SC and SCL Decoding 4 B. Path Metric 5 C. FSSC Decoding 6 D. FSSCL Decoding 6 III. Proposed Path Selection Method 9 A. Candidate Paths Selection Analysis 9 B. Proposed Metric Sorting Network 10 C. Complexity Analysis 13 IV. Simulation Results and Comparisons 14 A. Error Correction Performances 14 B. Comparisons of Complexities 14 V. Conclusions 16 Reference 17MasterThe successive cancellation (SC) decoding algorithm of polar codes shows worse error correction performances than other codes and suffers from a long latency. The SC list (SCL) and fast simplified SC (FSSC) decoding algorithms have been proposed to improve the drawbacks. In addition, the FSSC list (FSSCL) decoding has been proposed as the state-of-the-art decoding algorithm for polar codes. However, the metric sorter of the SCL decoder expands when the list size L increases and dominantly determines the critical path of the decoder. As a result, the metric sorter of the FSSCL decoder expands drastically because the FSSCL algorithm decodes multiple bits at once. To solve this problem, this paper proposes a path selection method for reducing the number of candidate paths. We analyze the cumulative result of L candidate paths selection from L2 and eliminate the unnecessary candidate paths. Finally, we simplify the bitonic sorter for the FSSCL decoder. The number of inputs is reduced by 50%, and the error correction performance is degraded less than 0.1dB on frame error rate (FER) 10-3 in L=4 and 8. The proposed sorter has up to 40% lower compare-and-swap unit (CASU) stages and up to 67% lower CASUs compared to other sorters in L=4

Simple mathematical formulae for estimation of median values of fetal biometry at each gestational age

ObjectiveThe aim of this study was to propose simple mathematical formulae to estimate median values of fetal biometry including biparietal diameter (BPD), abdominal circumference (AC) and femur length (FL) at each gestational age (GA) easily without looking up the previously established reference values. MethodsSimple mathematical formulae to estimate median values of fetal biometric values at each gestational week were inferred. To validate these formulae, three different linear equations were derived from previously reported reference values of median BPD, AC and FL using regression analysis at each gestational week. Finally, calculated data through the inferred formula were compared to retrospectively collected data (observed data). ResultsThe equation revealing the relationship between BPD and GA was: median BPD (cm)=GA (wk)/4. Using this simple mathematical formula, the absolute percentage error between observed data and calculated data ranged from 0.12% to 7.50%. The equation between AC and GA was: median AC (cm)=GA (wk)-5. Through this formula, the absolute percentage error was analyzed same as above and it ranged from 0.30% to 4.76%. Lastly the derived formula between FL and GA was: median FL (cm)=GA (wk)/5 and the absolute percentage error ranged from 4.52% to 16.75%. ConclusionThe three simple formulae suggested in our study showed a significantly easy way to estimate the median values of fetal biometry at each gestational week with good reliability.N