Knowledge,Attitudes, and Practices Regarding Cervical Cancer Screening among HIV-infected Women at Srinagarind Hospital: A Cross-Sectional Study

Introduction: In recent years, the lives of HIV-infected patients in Thailand have improved significantly due to continuous advances in treatment. However, the rate of cancer related to HIV infection (especially cervical cancer) is likely to increase. Although the World Health Organization (WHO) recommends Papanicolaou testing in all HIV-infected women, few of these patients receive this kind of screening in Thailand. Therefore, we conducted this study to evaluate the knowledge, attitudes, and practices of these patients with regard to cervical cancer screening. Materials and Methods: This cross-sectional study was conducted in HIV-infected women aged 18-65 years from April to November 2019 via a self-administered cervical cancer screening questionnaire, which consisted of four parts: demographic data, knowledge, attitudes, and practices. Results: Three hundred HIV-infected women were recruited. Most of the participants had good attitudes toward screening and practiced adequate screening (75.3% and 71.3%, respectively). However, only 62 participants (20.7%) demonstrated adequate knowledge. The crucial factors that were associated with adequate screening practice were age 40-49 years-old (AOR =3.26, 95%CI=1.02-10.37), CD4 cell count (AOR = 3.41, 95%CI = 1.29-8.99), having been advised about cervical cancer screening (AOR= 6.23, 95%CI 1.84-21.07), and attitude toward screening (AOR= 5.7, 95%CI = 2.23-14.55). The major reasons for not undergoing screening were embarrassment (41.86%), lack of symptoms (41.86%), fear of the results (36.04%), and fear of pain (36.04%). Conclusion: The reasons for inadequate testing were disregard and misconceptions about the procedure. To prevent invasive cervical lesions in HIV-infected women, health care providers should inform these patients about the importance of regular cervical cancer screening.     

CyclinA1 Promoter Methylation in Self-Sampling Test

Background: Self sampled HPV testing is a cervical cancer screening method . However, cytology in self-sampled specimen cannot be used as a triage test.  Therefore, other methods for triage should be considered. CyclinA1 (CCNA1) promoter methylation has strong association with cervical precancerous and cancerous lesion. The objective of this study was to compare the diagnostic value of CCNA1 and self-sampled specimen for detecting high-grade cervical intraepithelial lesions or worse (CIN2+). Materials and Methods: A cross sectional study was conducted. Women with abnormal cytology or positive for high risk HPV (hrHPV) indicated for colposcopic examination were enrolled.  Self-collected sampling for hrHPV DNA (SS-HPV) and CCNA1 were performed. hrHPV DNA testing was done by Cobas 4800 method. CCNA1 promoter methylation was detected by CCNA1 duplex methylation specific PCR. Histopathologic result as CIN2+ obtaining from colposcopic directed biopsy or excisional procedure  was considered as positive a gold standard. The results of hrHPV and CCNA1 were reported as positive or negative. Sensitivity specificity, positive predictive value, and negative predictive value of SS-HPV and CCNA1 were calculated by comparing the results with the gold standard. Results: Two hundreds and eighty women were recruited. High-grade cervical lesions and cervical cancer (CIN2+) were diagnosed in 21.8% (61 cases) of the patients. The most common type of hrHPV was non 16, 18 subtype, followed by HPV16 and 18. CCNA1 was positive in 13 patients out of whom, twelve were CIN2+. Sensitivity of CCNA1 was 19.7 % and its  specificity and accuracy were 99.5% and 82.14%, respectively.  The sensitivity of SS-HPV was 70.5%, and its  specificity and accuracy were 39.2% and 43.3%, respectively. Conclusion:  Due to high specificity and positive predictive value of CCNA1, it can be used as alarming sign of having high-grade cervical intraepithelial lesions, especially in patient who has positive hrHPV DNA test based on self-collected sampling.     

2014年中国农村基于超声乳腺癌筛查多中心数据分析

目的为提高国家农村妇女乳腺癌筛查项目效果,第2个周期(2012-2014年)筛查模式调整为基于超声的乳腺癌筛查,本研究通过对2014年度农村妇女乳腺癌筛查数据进行分析,了解基于超声的乳腺癌筛查模式的质量和效果,为完善筛查流程、提高筛查质量和管理水平提供依据。方法采用基于超声的乳腺癌筛查模式为全国35~64岁农村户籍女性进行群体性乳腺癌筛查:先为符合条件的农村女性进行乳腺临床检查联合乳腺超声检查,超声BI-RADS 0、4、5级者进行乳腺X射线检查(mammography,MG),X射线BI-RADS 0、4、5级者进行组织病理检查,乳腺超声、X射线BI-RADS 1、2、3级者进行1年随访。检查数据以统计报表和个案表(筛出乳腺癌患者)形式录入《国家妇幼重大公共卫生项目信息直报系统》。分东、中、西部地区计算乳腺癌召回率、活检率、活检阳性预测值、检出率、早诊率、原位癌比例、早期癌比例、漏检率、假阳性率等主要评估指标;使用χ^2检验对地区间指标结果进行比较。结果2014年为30个省(市、区)697个项目县共1373524名35~64岁农村女性进行了乳腺癌筛查。检出乳腺癌1190例,检出率为0.87‰;东、中、西部地区检出乳腺癌例数分别为404、375和411例,检出率分别为0.90‰、0.86‰和0.84‰,地区间检出率差异无统计学意义,χ^2=1.215,P>0.05。共检出早期乳腺癌1014例,早诊率为85.21%;东、中、西部地区检出早期乳腺癌例数分别为353、323和338例,早诊率分别为87.38%、86.13%和82.24%,地区间早诊率差异无统计学意义,χ^2=4.638,P>0.05。检出原位癌82例,原位癌比例为6.89%;东、中、西部地区分别检出原位癌39、23和20例,原位癌比例分别为9.65%、6.13%和4.87%,原位癌比例地区间差异有统计学意义,χ^2=7.767,P<0.05。检出早期癌(0+Ⅰ期)387例,早期癌比例为32.52%;东、中、西部地区早期癌例数分别为159、115和113例,早期癌比例分别为39.36%、30.67%和27.49%,地区间差异有统计学意义,χ^2=13.922,P<0.01。MG复筛人数为33129人,召回率为2.41%;东、中、西部地区MG复筛人数分别为12827、11616和8686人,召回率分别为2.87%、2.67%和1.77%,地区间差异有统计学意义,χ^2=1386,P<0.01。3088人接受活检,活检率为0.22%;东、中、西部地区接受活检人数分别为1106、1006和976人,活检率分别为0.25%、0.23%和0.20%,地区间差异有统计学意义,χ^2=25.910,P<0.01。超声初筛漏检率为7.23%,其中BI-RADS 3级漏检率为6.89%;MG复筛BI-RADS 3级漏检率3.99%;仅超声检出乳腺癌比例为5.58%。结论2014年中国农村妇女乳腺癌检查项目检出和早诊情况符合相关质控要求,说明基于超声的乳腺癌筛查在中国农村地区可行且有效。但本筛查流程的漏检率仍较高,需进行流程优化。应加强MG和活检设备配置及技术培训,以提高乳腺癌筛查服务能力,从而进一步提高检出率和早诊率。     

Spot双目视力筛查仪和自动电脑验光仪在近视筛查中结果的比较

目的：:比较Spot双目视力筛查仪和自动电脑验光仪在近视筛查中结果的差异、相关性和一致性。方法：:横断面研究。采用分层随机方法抽取徐州某学校6～19岁的学生共500人,分别用Spot双目视力筛查仪（VS100,美国伟伦公司）和自动电脑验光仪（KR800,日本拓普康公司）进行验光检查。记录睫状肌麻痹（1%复方托吡卡胺眼药...     

Modeling for COVID-19 college reopening decisions: Cornell,a case study

We consider epidemiological modeling for the design of COVID-19 interventions in university populations, which have seen significant outbreaks during the pandemic. A central challenge is sensitivity of predictions to input parameters coupled with uncertainty about these parameters. Nearly 2 y into the pandemic, parameter uncertainty remains because of changes in vaccination efficacy, viral variants, and mask mandates, and because universities’ unique characteristics hinder translation from the general population: a high fraction of young people, who have higher rates of asymptomatic infection and social contact, as well as an enhanced ability to implement behavioral and testing interventions. We describe an epidemiological model that formed the basis for Cornell University’s decision to reopen for in-person instruction in fall 2020 and supported the design of an asymptomatic screening program instituted concurrently to prevent viral spread. We demonstrate how the structure of these decisions allowed risk to be minimized despite parameter uncertainty leading to an inability to make accurate point estimates and how this generalizes to other university settings. We find that once-per-week asymptomatic screening of vaccinated undergraduate students provides substantial value against the Delta variant, even if all students are vaccinated, and that more targeted testing of the most social vaccinated students provides further value.

When is it safe to offer in-person university instruction during the COVID-19 pandemic? What interventions, if any, provide the level of safety required? Colleges and universities across the globe faced this question in summer 2020 as they considered whether to offer in-person instruction. They continue to face this question today as they contemplate partially vaccinated student populations, waning immunity, booster shots, and the potential for new variants to emerge.These questions are significant because outbreaks in university student populations have occurred regularly (1) and may harm the health of students and more-vulnerable employees and community members that interact with them (2). Even when vaccination protects the bulk of the population against the most severe health outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, widespread breakthrough infections would threaten the health of unvaccinated and immunocompromised individuals in their midst. At the same time, social distancing, masking, asymptomatic screening, the migration of in-person instruction to a virtual format, vaccine mandates, and other interventions that can be brought to bear against university outbreaks all incur social and financial costs (3, 4). Better understanding the protection offered by these interventions would support providing safety while minimizing these costs.These questions remain difficult to answer because vaccination levels, SARS-CoV-2 variants, and other conditions continue to change and because experiences at the city, state, and national level do not easily generalize to university populations. Indeed, university populations are younger than the general population and thus have increased rates of contact (5) that may elevate virus transmission (2, 6). In addition, universities can implement interventions that would be substantially more difficult for the general population, such as mandatory vaccination and mandatory asymptomatic screening (7, 8).Universities have responded to this central question in dramatically different ways. In the 2020–2021 academic year, many schools went fully online, while many others opened for in-person instruction with a modest set of interventions centered around symptomatic testing, contact tracing, and social distancing (9). Moreover, those schools that opened for in-person instruction pursued dramatically different testing strategies (10). Some tested only symptomatic students, others tested all students once on arrival, and others tested all students at least once per week. In the fall 2021 semester, schools differ in whether they mandate vaccines, their testing strategies, and masking policies (11).This diversity in approach reflects, in part, a diversity of circumstance, such as proximity to, and interaction with, population centers, prevalence in those population centers, availability of housing to quarantine students, and the desires of the surrounding community (12). However, it also reflects substantial continued uncertainty about how policy translates into outcomes. Such uncertainty and diversity in approach among universities reflects the larger response to the pandemic, in which US states and national governments adopted dramatically different responses to the pandemic despite apparently similar circumstances.Simulation-based epidemic models would seem to offer the power to resolve this uncertainty in support of high-quality decisions. They allow prediction, customized to the circumstances of a university, city, state, or nation. By varying the interventions in silico and observing predicted outcomes, one can hope to choose the best course of action. Unfortunately, epidemic models only approximate reality (13). Ever-present uncertainty in model input parameters coupled with the potential for exponential growth significantly limit accuracy. Small differences in behavioral and biological parameters can cause huge differences in predicted case counts. As a consequence, epidemic models have been maligned for producing inaccurate point estimates (13, 14).This article demonstrates that simulation models can support effective selection of COVID-19 interventions even when they are unable to provide accurate point estimates of epidemic outcomes. We demonstrate this through a case study of how simulation models supported the design of COVID-19 interventions that were subsequently implemented at Cornell University. We also present a modeling framework that can support decisions at other universities. (The use of epidemic models in the presence of significant parameter uncertainty is also discussed in, for example, ref. 15. In such settings, clear communication of uncertainties is key; see, for example, ref. 16).)In close communication with Cornell University’s administration, we conducted a simulation-based analysis in summer 2020 using a compartmental Susceptible, Exposed, Infectious, and Recovered model with multiple subpopulations; see refs. 17–19 for closely related models. Our work was the basis for the decision to reopen Cornell’s Ithaca campus for residential instruction in fall 2020 (20) and was used to design an asymptomatic screening program that was and remains a critical part of Cornell’s strategy.Based on these modeling recommendations, all students were invited to return to Cornell’s Ithaca campus for residential instruction during the 2020–2021 school year under an asymptomatic screening program, and 75% of students returned (21). The surveillance program used pooled PCR testing with the testing frequencies obtained through our modeling. The surveillance program used less-sensitive but more-comfortable anterior nares (AN) sampling over nasopharyngeal (NP) sampling, because modeling suggested that the benefits of comfort to test compliance outweighed a potential loss in sensitivity. Asymptomatic surveillance was enabled at Cornell through a major effort to support large-scale sample collection and develop a new COVID-19 testing laboratory based on diagnostic expertise in Cornell’s College of Veterinary Medicine, and through a unique partnership with a local health care provider. Based on recommendations from our simulation modeling approach, this strategy was updated for the spring 2021 semester to test varsity athletes and students in Greek-life organizations more frequently (contact tracing data showed them to have more social contact than other individuals) and again in fall 2021 to adjust for the Delta variant, changes in social distancing policies, and the protection offered by vaccination. Over the course of the 2020–2021 academic year, there were fewer than 1,044 infections among students and employees, fewer than many schools with similar student populations offering only virtual instruction (1, 22).Our modeling approach hinges on delineating those simulation model input parameters yielding epidemics that can be successfully controlled versus those that cannot. If the set of plausible input parameters are contained within the set of safe parameters, then we can be highly confident, although never certain, that the epidemic can be controlled. At Cornell in summer 2020, we demonstrated this to the university administration for a suite of interventions available with in-person instruction: frequent asymptomatic screening, testing students on arrival to campus, contact tracing, social distancing on campus, limits on student and employee travel, masking requirements, and a behavioral compact curtailing student social gatherings. It was also possible that we would have found that plausible ranges of the input parameters overlapped the portion of parameter space where epidemics would grow out of control, in which case we would not have been able to recommend reopening.We found that access to regular asymptomatic screening (7, 23), with an ability to increase testing frequency if needed, was critical. Indeed, those few universities employing a similar asymptomatic screening approach succeeded, by and large, in controlling campus outbreaks (24–27). See also refs. 28–33 for explorations of the interaction of pooled testing and asymptomatic surveillance for controlling epidemics.We also found it was critical to analyze epidemic growth if in-person instruction were not offered, to quantify the relative merits of the alternative to in-person instruction. Survey results (20, 34) suggested that a significant number of students would return to the Ithaca area even if in-person instruction were not offered. Without the benefits of the legal framework offered by in-person instruction, frequent asymptomatic screening would have been difficult to mandate for this population. Moreover, our analysis suggested that many of those parameter settings in which asymptomatic screening would not ensure safe in-person instruction would also be ones in which a significant outbreak would occur in the local student population under virtual instruction. This resulted in the decision to reopen Cornell’s Ithaca campus with a fully residential semester in fall 2020 (20).We additionally measure key parameters of a university population needed for understanding the dynamics of epidemic spread, including university subpopulations’ intergroup and intragroup rates of viral transmission and how it has changed over time with vaccination, the Delta variant, and relaxation in social distancing. We find that a small group of students has significantly more intergroup viral transmission than other groups and plays an important role in determining the risk of an outbreak. We find that targeting interventions to this group provides substantial protection against outbreaks. Unlike students, we find that employees have very little transmission at work and are well separated from students, with extremely little transmission across the two groups. This has implications for understanding the risk to older and more vulnerable individuals from student infections.When considering a range of interventions against the Delta variant, we find that achieving high levels of vaccination provides significant protection, but that, even in a 100% vaccinated student population, there is significant potential for breakthrough outbreaks in the absence of asymptomatic screening and social distancing. This is consistent with findings from other modeling studies (19). While once per week asymptomatic screening of vaccinated students might be sufficient in many situations, we find that testing vaccinated student groups with high rates of social contact twice per week substantially reduces risk even when the entire population is vaccinated. We also find that moving from 75% vaccination to full vaccination provides substantial additional protection.To summarize, the key contributions of this paper are 1) providing a simulation framework for supporting the design of COVID-19 interventions despite parameter uncertainty; 2) demonstrating this framework through its implementation at Cornell University; 3) measuring key parameters of the dynamics of the spread of SARS-CoV-2 in university populations and the effectiveness of interventions; and 4) providing a framework for making decisions moving forward, including the design of asymptomatic screening strategies in the presence of partial vaccination and the Delta variant.Our work adds to the broader literature using epidemic modeling in the context of universities. See, for example, ref. 35 for a perspective on the challenges of reopening as informed by a variety of epidemic models, refs. 36 and 37 for the use of agent-based modeling to evaluate mitigation strategies to enable safe in-person instruction, ref. 38 for probabilistic modeling of strategies to suppress virus spread in dorms and classrooms, and ref. 39 for a study of interventions for generic small residential campuses.     

Mutation in the Cadherin Gene Is a Key Factor for Pink Bollworm Resistance to Bt Cotton in China

Transgenic crops producing Bacillus thuringiensis (Bt) toxins are widely planted for insect control, but their efficacy may decrease as insects evolve resistance. Understanding the genetic basis of insect resistance is essential for developing an integrated strategy of resistance management. To understand the genetic basis of resistance in pink bollworm (Pectinophora gossypiella) to Bt cotton in the Yangtze River Valley of China, we conducted an F2 screening for alleles associated with resistance to the Bt (Cry1Ac) protein for the first time. A total of 145 valid single-paired lines were screened, among which seven lines were found to carry resistance alleles. All field parents in those seven lines carried recessive resistance alleles at the cadherin locus, including three known alleles, r1, r13 and r15, and two novel alleles, r19 and r20. The overall frequency of resistance alleles in 145 lines was 0.0241 (95% CI: 0.0106–0.0512). These results demonstrated that resistance was rare and that recessive mutation in the cadherin gene was the primary mechanism of pink bollworm resistance to Bt cotton in the Yangtze River Valley of China, which will provide a scientific basis for implementing targeted resistance management statics of pink bollworm in this region.     

Remote microphone systems for preschool-age children who are hard of hearing: access and utilization

Objectives: Children who are hard of hearing (CHH) have restricted access to auditory-linguistic information. Remote-microphone (RM) systems reduce the negative consequences of limited auditory access. The purpose of this study was to characterise receipt and use of RM systems in young CHH in home and school settings.

Design: Through a combination of parent, teacher, and audiologist report, we identified children who received RM systems for home and/or school use by 4?years of age or younger. With cross-sectional surveys, parents estimated the amount of time the child used RM systems at home and school per day.

Study Sample: The participants included 217 CHH.

Results: Thirty-six percent of the children had personal RMs for home use and 50% had RM systems for school. Approximately, half of the parents reported that their children used RM systems for home use for 1–2?hours per use and RM systems for school use for 2-4?hours per day.

Conclusions: Results indicated that the majority of the CHH in the current study did not receive RM systems for home use in early childhood, but half had access to RM technology in the educational setting. High-quality research studies are needed to determine ways in which RM systems benefit pre-school-age CHH.     

乳腺癌的影像普查技术进展

介绍了用于常规乳腺检测的X线摄影、超声成像和红外成像等各种影像学技术,通过分析这些技术的病理学以及影像学特征,找到它们在普查学中的意义。此外,还介绍了一种新兴的技术——热断层成像。