多基因遗传风险评分指导肺癌个体化筛查的前瞻性队列研究

目的探索如何利用遗传风险评分,制订个体化的肺癌筛查方案。方法利用中国慢性病前瞻性研究(CKB)队列10个地区100615例具有全基因组基因分型信息的样本,根据前期课题组发表的19个遗传变异构建肺癌多基因遗传风险评分PRS-19。以55岁且吸烟剂量30包/年人群的5年绝对发病风险为参考届值,在吸烟者和非吸烟者中分别计算不同遗传风险人群5年肺癌绝对发病风险随年龄和吸烟剂量的变化趋势,并绘制5年绝对发病风险分布图,从而判断不同遗传风险人群达到参考界值时的理论年龄或吸烟剂量。根据上述结果给出不同遗传风险人群参加肺癌筛查起始年龄的具体建议。结果CKB队列中55岁吸烟者,当吸烟量为30包/年时,5年内发生肺癌的绝对风险为0.67%。在吸烟者中,随着遗传风险增加,其5年绝对发病风险呈不断上升趋势,对于高遗传风险人群应降低筛查起始年龄,遗传风险最高的1%人群建议从50岁开始进行筛查;若保持筛查起始年龄55岁不变,则应在高遗传风险人群中降低吸烟剂量标准;不管累积吸烟剂量为多少,遗传风险最高的1%人群都应纳入肺癌筛查。在非吸烟者中,高遗传风险人群同样具备筛查价值,建议遗传风险最高的1%人群从62岁起进行肺癌筛查,而对于遗传风险最低的5%人群,当年龄达到74岁时才可达到参考届值。结论对于不同遗传风险的个体,可采用个体化的肺癌筛查方案,对于高遗传风险的吸烟者可减小肺癌筛查起始年龄或吸烟剂量,而我国高遗传风险的非吸烟者同样具备筛查价值。     

时间序列模型应用于新型冠状病毒肺炎疫情预测效果比较研究

目的比较常见时间序列模型应用于新型冠状病毒肺炎(COVID-19)疫情预测的效果。方法收集2020年4月1日至9月30日美国、印度和巴西3个国家COVID-19每日确诊病例数,分别建立差分自回归移动平均(ARIMA)模型和循环神经网络(RNN)模型,使用平均绝对百分比误差(MAPE)和均方根误差(RMSE)等指标,比较不同模型预测9月21-30日确诊病例的表现。结果应用ARIMA模型预测美国、印度和巴西疫情的MAPE分别为13.18%、9.18%和17.30%,RMSE分别为6542.32、8069.50和3954.59;应用RNN模型预测美国、印度和巴西疫情的MAPE分别为15.27%、7.23%和26.02%,RMSE分别为6877.71、6457.07和5950.88。结论ARIMA和RNN模型的COVID-19预测效果存在地区差异,ARIMA模型的预测效果在美国和巴西较优,而RNN模型的预测效果在印度较优。     

Bivalent non-typhoidal Salmonella outer membrane vesicles immunized mice sera confer passive protection against gastroenteritis in a suckling mice model

Invasive non-typhoidal Salmonella (iNTS) serovars, especially Salmonella Typhimurium (ST) and Salmonella Enteritidis (SE), cause gastroenteritis worldwide. Due to the emergence of multi-drug resistance in iNTS, a broad-spectrum vaccine is urgently needed for the prevention of iNTS infection. Currently, there is no effective licensed vaccine against iNTS available in the market. We have formulated an outer membrane vesicles (OMVs) based bivalent immunogen as a vaccine candidate to generate broad-spectrum protective immunity against both recently circulating prevalent ST and SE. We have isolated OMVs from ST and SE and formulated the immunogen by mixing both OMVs (1:1 ratio). Three doses of bivalent immunogen significantly induced humoral immune responses against lipopolysaccharides (LPSs) and outer membrane proteins (OMPs) as well as a cell-mediated immune response in adult mice. We also observed that proteins of OMVs act as an adjuvant for generation of high levels of anti-LPS antibodies through T cell activation. We then characterized the one-day old suckling mice model for both ST and SE mediated gastroenteritis and used the model for a passive protection study. In the passive protection study, we found the passive transfer of bivalent OMVs immunized sera significantly reduced ST and SE mediated colonization and gastroenteritis symptoms in the colon of suckling mice compared to non-immunized sera recipients. The overall study demonstrated that OMVs based bivalent vaccine could generate broad-spectrum immunity against prevalent iNTS mediated gastroenteritis. This study also established the suckling mice model as a suitable animal model for vaccine study against iNTS mediated gastroenteritis.     

Importance of COVID-19 vaccine efficacy in older age groups

ImportanceAn effective vaccine against SARS-CoV-2 will reduce morbidity and mortality and allow substantial relaxation of physical distancing policies. However, the ability of a vaccine to prevent infection or disease depends critically on protecting older individuals, who are at highest risk of severe disease.ObjectiveWe quantitatively estimated the relative benefits of COVID-19 vaccines, in terms of preventing infection and death, with a particular focus on effectiveness in elderly people.DesignWe applied compartmental mathematical modelling to determine the relative effects of vaccines that block infection and onward transmission, and those that prevent severe disease. We assumed that vaccines showing high efficacy in adults would be deployed, and examined the effects of lower vaccine efficacy among the elderly population.Setting and participantsOur mathematical model was calibrated to simulate the course of an epidemic among the entire population of British Columbia, Canada. Within our model, the population was structured by age and levels of contact.Main outcome(s) and measure(s)We assessed the effectiveness of possible vaccines in terms of the predicted number of infections within the entire population, and deaths among people aged 65 years and over.Results In order to reduce the overall rate of infections in the population, high rates of deployment to all age groups will be critical. However, to substantially reduce mortality among people aged 65 years and over, a vaccine must directly protect a high proportion of people in that group.Conclusions and relevanceEffective vaccines deployed to a large fraction of the population are projected to substantially reduce infection in an otherwise susceptible population. However, even if transmission were blocked highly effectively by vaccination of children and younger adults, overall mortality would not be substantially reduced unless the vaccine is also directly protective in elderly people. We strongly recommend: (i) the inclusion of people aged 65 years and over in future trials of COVID-19 vaccine candidates; (ii) careful monitoring of vaccine efficacy in older age groups following vaccination.     

Extracellular vesicles released from irradiated neonatal mouse cheek tissue increased cell survival after radiation

Alopecia is one of the common symptoms after high-dose radiation exposure. In our experiments, neonatal mice that received 7 Gy X-ray exhibited defects in overall hair growth, except for their cheeks. This phenomenon might suggest that some substances were secreted and prevented hair follicle loss in the infant tissues around their cheeks after radiation damage. In this study, we focused on exosome-like vesicles (ELV) secreted from cheek skin tissues and back skin tissues, as control, and examined their radiation protective effects on mouse fibroblast cell lines. We observed that ELV from irradiated cheek skin showed protective effects from radiation. Our results suggest that ELV from radiation-exposed cheek skin tissue is one of the secreted factors that prevent hair follicle loss after high-dose radiation.     

Anhedonia,positive affect dysregulation,and risk and maintenance of binge-eating disorder

Low positive affect has been identified as an antecedent of binge-eating episodes among individuals with binge-eating disorder (BED), yet positive affect has received far less attention in eating disorders research than its counterpart, negative affect. In this article, we argue that the low levels of positive affect which occur with anhedonia (i.e., loss of interest or pleasure in activities) may contribute to the onset and maintenance of BED. We introduce a theoretical model in which anhedonia increases the risk for BED through its interrelationships with dysregulated eating and weight gain, and we describe potential direct (e.g., reward-related processes) as well as indirect (e.g., influences on depressive symptoms and physical activity) pathways by which anhedonia may lead to adverse eating- and weight-related outcomes. We also propose a momentary maintenance model in which low positive affect and positive affect dysregulation occurring with anhedonia maintain binge eating directly and indirectly through maladaptive health behaviors, such as decreased physical activity, less healthy eating, and fewer social interactions, which in turn maintain anhedonia. We draw upon outside literature to present evidence that aligns with the proposed risk and maintenance models and conclude by outlining avenues for future research—including methodological/measurement, theoretical, and clinical research directions.     

Analysis of time‐to‐event for observational studies: Guidance to the use of intensity models

This paper provides guidance for researchers with some mathematical background on the conduct of time‐to‐event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time‐dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.