从抗体阳性的甲型肝炎接触者粪便中分离出一株甲型肝炎病毒

几年来,国内外已相继用组织培养法分离多株甲型肝炎病毒(HAV),并已证实了甲型肝炎患者及亚临床型感染在传染本病中的重要性。但HAV在流行点的正常人群中存在短期携带的问题还尚未见报道。本文采用人胚肺二倍体细胞(2BS)从甲型肝炎接触者粪便中分离出一株HAV,并经免疫电镜、免疫荧光及参比血清鉴定等证实。现将结果报告如下。     

牙龈卟啉杆菌W83单克隆抗体的研制与鉴定

牙龈类杆菌曾是重要的产黑色素类杆菌群菌株,最近重新命名为牙龈卟啉杆菌,该菌为牙周病龈下菌斑中关键性厌氧菌,与成人慢性牙周炎的发生、发展有密切关系。作者用牙龈卟啉杆菌侵袭型菌株W83,作为免疫原,通过免疫小鼠、细胞融合、筛选、克隆化,最后得到一株能够稳定分泌抗牙龈卟啉杆菌W83的单克隆抗体杂交瘤细胞系,经鉴定该单抗特异性良好,可用于临床该菌的检出和生态学研究。     

Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study

Typically twin studies are used to investigate the aggregate effects of genetic and environmental influences on brain phenotypic measures. Although some phenotypic measures are highly heritable in twin studies, SNPs (single nucleotide polymorphisms) identified by genome-wide association studies (GWAS) account for only a small fraction of the heritability of these measures. We mapped the genetic variation (the proportion of phenotypic variance explained by variation among SNPs) of volumes of pre-defined regions across the whole brain, as explained by 512,905 SNPs genotyped on 747 adult participants from the Alzheimer''s Disease Neuroimaging Initiative (ADNI). We found that 85% of the variance of intracranial volume (ICV) (p = 0.04) was explained by considering all SNPs simultaneously, and after adjusting for ICV, total grey matter (GM) and white matter (WM) volumes had genetic variation estimates near zero (p = 0.5). We found varying estimates of genetic variation across 93 non-overlapping regions, with asymmetry in estimates between the left and right cerebral hemispheres. Several regions reported in previous studies to be related to Alzheimer''s disease progression were estimated to have a large proportion of volumetric variance explained by the SNPs.     

Using Manifold Learning for Atlas Selection in Multi-Atlas Segmentation

Multi-atlas segmentation has been widely used to segment various anatomical structures. The success of this technique partly relies on the selection of atlases that are best mapped to a new target image after registration. Recently, manifold learning has been proposed as a method for atlas selection. Each manifold learning technique seeks to optimize a unique objective function. Therefore, different techniques produce different embeddings even when applied to the same data set. Previous studies used a single technique in their method and gave no reason for the choice of the manifold learning technique employed nor the theoretical grounds for the choice of the manifold parameters. In this study, we compare side-by-side the results given by 3 manifold learning techniques (Isomap, Laplacian Eigenmaps and Locally Linear Embedding) on the same data set. We assess the ability of those 3 different techniques to select the best atlases to combine in the framework of multi-atlas segmentation. First, a leave-one-out experiment is used to optimize our method on a set of 110 manually segmented atlases of hippocampi and find the manifold learning technique and associated manifold parameters that give the best segmentation accuracy. Then, the optimal parameters are used to automatically segment 30 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For our dataset, the selection of atlases with Locally Linear Embedding gives the best results. Our findings show that selection of atlases with manifold learning leads to segmentation accuracy close to or significantly higher than the state-of-the-art method and that accuracy can be increased by fine tuning the manifold learning process.     

Life Expectancies of South African Adults Starting Antiretroviral Treatment: Collaborative Analysis of Cohort Studies

Background

Few estimates exist of the life expectancy of HIV-positive adults receiving antiretroviral treatment (ART) in low- and middle-income countries. We aimed to estimate the life expectancy of patients starting ART in South Africa and compare it with that of HIV-negative adults.

Methods and Findings

Data were collected from six South African ART cohorts. Analysis was restricted to 37,740 HIV-positive adults starting ART for the first time. Estimates of mortality were obtained by linking patient records to the national population register. Relative survival models were used to estimate the excess mortality attributable to HIV by age, for different baseline CD4 categories and different durations. Non-HIV mortality was estimated using a South African demographic model. The average life expectancy of men starting ART varied between 27.6 y (95% CI: 25.2–30.2) at age 20 y and 10.1 y (95% CI: 9.3–10.8) at age 60 y, while estimates for women at the same ages were substantially higher, at 36.8 y (95% CI: 34.0–39.7) and 14.4 y (95% CI: 13.3–15.3), respectively. The life expectancy of a 20-y-old woman was 43.1 y (95% CI: 40.1–46.0) if her baseline CD4 count was ≥200 cells/µl, compared to 29.5 y (95% CI: 26.2–33.0) if her baseline CD4 count was <50 cells/µl. Life expectancies of patients with baseline CD4 counts ≥200 cells/µl were between 70% and 86% of those in HIV-negative adults of the same age and sex, and life expectancies were increased by 15%–20% in patients who had survived 2 y after starting ART. However, the analysis was limited by a lack of mortality data at longer durations.

Conclusions

South African HIV-positive adults can have a near-normal life expectancy, provided that they start ART before their CD4 count drops below 200 cells/µl. These findings demonstrate that the near-normal life expectancies of HIV-positive individuals receiving ART in high-income countries can apply to low- and middle-income countries as well. Please see later in the article for the Editors'' Summary