Baseline human papillomavirus (HPV) prevalence and type distribution were evaluated in young Chinese women enrolled in a clinical trial of an HPV vaccine (ClinicalTrials.gov registration NCT00779766). Cervical specimens and blood samples were collected at baseline from women aged 18–25 years (n = 6,051) from four sites across Jiangsu province. Cervical specimens were tested for HPV DNA by SPF10 PCR-DEIA-LiPA25 version 1, and HPV-16/18 type-specific polymerase chain reaction. Anti-HPV-16 and anti-HPV-18 antibody titres were quantified by enzyme-linked immunosorbent assay. At baseline, 15.3% of women were DNA positive for any of 14 HPV high-risk (hr) types (HPV-16/18/31/33/35/39/45/51/52/56/58/59/66/68). The most commonly detected hrHPV types in cervical specimens were HPV-52 (4.0%) and HPV-16 (3.7%). High-risk HPV DNA-positivity increased with severity of cytological abnormalities: 39.3% in atypical squamous cells of undetermined significance, 85.0% in low-grade squamous intraepithelial lesions and 97.8% in high-grade squamous intraepithelial lesions (HSIL). The hrHPV types most frequently detected in HSIL were HPV-16 (63.0%), HPV-18 (17.4%), HPV-52 (17.4%), HPV-58 (15.2%) and HPV-33 (15.2%). The hrHPV types most frequently detected in cervical intraepithelial neoplasia 2+ were HPV-16 (66.1%), HPV-33 (16.1%), HPV-52 (16.1%), HPV-58 (14.5%) and HPV-51 (11.3%). Multiple hrHPV infections were reported for 24.4% of hrHPV DNA positive women. Regardless of baseline HPV DNA status, 30.5% and 16.0% of subjects were initially seropositive for anti-HPV-16 and anti-HPV-18, respectively. In conclusion, the high baseline seropositivity rate and intermediate prevalence of cervical hrHPV types in Chinese women aged 18–25 years underlines the importance of early HPV vaccination in this population.What's new?In China, cervical cancer is the second most frequent cancer among women aged 15–44 years. The authors collected baseline data on prevalence and type distribution of human papillomavirus (HPV) from more than 6,000 healthy Chinese women aged 18–25 years participating in a large vaccine efficacy trial. Regardless of cytology, 15.3% of women were positive for high-risk HPV types, with HPV-52 (4.0%), HPV-16 (3.7%), HPV-51 (1.7%) and HPV-58 (1.5%) being the most frequently detected. This high baseline prevalence of high-risk HPV types underscores the importance of early vaccination among Chinese women.

Background and objectives: Estimation of GFR in children from serum creatinine measures in regional databases is limited by a lack of height data. Furthermore, the ability of GFR estimating equations to quantify changes in GFR over time is unknown. Two methods of estimating GFR when height is unknown and the ability of several GFR equations to quantify GFR changes over time were evaluated. Design, setting, participants & measurements: This retrospective study included 195 children (mean age 11.9 ؎ 4.6 years, GFR ‫؍‬ 78.8 ؎ 34.5) who underwent iothalamate GFR, serum creatinine, and height measurements; 93 children underwent a second GFR measurement and 47 a third GFR measurement. Four equations were evaluated for bias and precision and for quantifying GFR change over time: (1) Schwartz, using measured height; (2) Schwartz, using estimated height (based on previous height percentile); (3) a locally derived modification of a previously derived height-independent equation.Results: The Schwartz (measured height) displayed the least bias (؊2 to ؉7%), followed by the modified height-independent equation and Schwartz (estimated height). All equations were imprecise. All equations performed similarly at capturing change in measured GFR over time, with no significant difference between estimated and measured GFR percentage change over time. The height-estimated Schwartz formula performed similarly to the height-measured Schwartz in all aspects of equation performance.Conclusions: Pediatric GFR follow-up studies may be possible using height-independent equations. Estimating height from prior height measurements enhances GFR estimation when height is unknown. These findings will hopefully help advance future pediatric renal function database studies.

Abstract:Cognitive radio (CR) has become a tempting technology that achieves significant improvement in spectrum utilization. To resolve the hidden terminal problem, collaborative spectrum sensing (CSS), which profits from spatial diversity, has been studied intensively in recent years. As CSS is vulnerable to the attacks launched by malicious secondary users (SUs), certain CSS security schemes based on the Dempster-Shafer theory of evidence have been proposed. Nevertheless, the available works only focus on the real-time difference of SUs, like the difference in similarity degree or SNR, to evaluate the credibility of each SU. Since the real-time difference is unilateral and sometimes inexact, the statistical information comprised in SUs' historical behaviors should not be ignored. In this paper, we propose a robust CSS method based on evidence theory and credibility calculation. It is executed in four consecutive procedures, which are basic probability assignment (BPA), holistic credibility calculation, option and amelioration of BPA and evidence combination via the Dempster-Shafer rule, respectively. Our scheme evaluates the holistic credibility of SUs from both the real-time difference and statistical sensing behavior of SUs. Moreover, considering that the transmitted data increase with the number of SUs increasing, we introduce the projection approximation approach to adjust the evidence theory to the binary hypothesis test in CSS; on this account, both the data volume to be transmitted and the workload at the data fusion center have been reduced. Malicious SUs can be distinguished from genuine ones based on their historical sensing behaviors, and SUs' real-time difference can be reserved to acquire a superior current performance. Abounding simulation results have proven that the proposed method outperforms the existing ones under the effect of different attack modes and different numbers of malicious SUs.

Abstract. The portable microAeth® MA200 (MA200) is widely applied for measuring black carbon in human exposure profiling and mobile air quality monitoring. Due to it being relatively new on the market, the field lacks a refined assessment of the instrument's performance under various settings and data post-processing approaches. This study assessed the mobile real-time performance of the MA200 to determine a suitable noise reduction algorithm in an urban area, Augsburg, Germany. Noise reduction and negative value mitigation were explored via different data post-processing methods (i.e., local polynomial regression (LPR), optimized noise reduction averaging (ONA), and centred moving average (CMA)) under common sampling interval times (i.e., 5, 10, and 30 s). After noise reduction, the treated data were evaluated and compared by (1) the amount of useful information attributed to retention of microenvironmental characteristics, (2) the relative number of negative values remaining, (3) the reduction and retention of peak samples, and (4) the amount of useful signal retained after correction for local background conditions. Our results identify CMA as a useful tool for isolating the central trends of raw black carbon concentration data in real time while reducing nonsensical negative values and the occurrence and magnitudes of peak samples that affect visual assessment of the data without substantially affecting bias. Correction for local background concentrations improved the CMA treatment by bringing nuanced microenvironmental changes into view. This analysis employs a number of different post-processing methods for black carbon data, providing comparative insights for researchers looking for black carbon data smoothing approaches, specifically in a mobile monitoring framework and data collected using the microAeth® series of Aethalometer.