The HIV-1 incidence in IDU in city C was stable and relatively low. In contrast, there is a high HIV-1 incidence among IDU in cities D and E. The adjusted BED-CEIA estimated incidence rates indicate clearly that interventions must be strengthened continuously in IDU, especially in two Chinese cities.

ObjectiveTo determine the prevalence of virological failure and HIV drug resistance among Chinese patients one year after initiating lamivudine-based first-line antiretroviral treatment.MethodsA prospective cohort study with follow-up at 12 months was conducted in four urban sentinel sites in China. Antiretroviral naive patients ≥18 years old were recruited. Blood samples were collected for testing CD4 cell count, viral load, and (for samples with HIV-1 RNA ≥1000 copies/ml) genotyping of drug resistance.ResultsA total of 513 patients were enrolled in this cohort, of whom 448 (87.3%) were retained at 12 months. The median final CD4 cell count was 313 cells/mm3, which increased from 192 cells/mm3 at baseline (P<0.0001). Of the 448 remaining subjects, 394 (87.9%) had successful virological suppression (HIV RNA <1000 copies/ml). Among 54 samples with viral load ≥1000 copies/ml, 40 were successfully genotyped, and 11 were found with detectable HIV drug resistance mutations. Of these, the proportions of drug resistance to NNRTIs, NRTIs and PIs were 100%, 81.8% and 0%, respectively. Injecting drug use (AOR = 0.40, 95% CI: 0.19,0.84; P = 0.0154), CD4 count at baseline ≥350 cells/mm3 (AOR = 0.32, 95% CI: 0.14,0.72; P = 0.0056), and missed doses in the past month (AOR = 0.30, 95% CI: 0.15,0.60; P = 0.0006) were significantly negatively associated with HIV RNA <1000 copies/ml.ConclusionsOur study demonstrates effective virological and immunological outcomes at 12 months among these who initiated first-line ART treatment. However, patients infected through drug injection, who missed doses, or with higher CD4 count at baseline are at increased risk for poor virological response.

IntroductionData provenance is information about the entities, activities and people who have effected some type of transformation on a data product through the product's lifecycle. Data provenance captured from scientific applications is a critical precursor to data sharing and reuse. For researchers wanting to repurpose and reuse data, it is a source of information about the lineage and attribution of the data and this is needed in order to establish trust in a data set. Data provenance has been shown useful in results validation, failure tracing, and reproducibility. The Komadu provenance capture system is standalone, meaning it is not coupled to or dependent upon any database management system, repository, or scientific workflow system. It provides an ingest API through which provenance notifications are fed into the system at high speeds, and a query API through which provenance information can be queried. The data model is both event oriented and graph oriented, in that graphs are pieced together in Komadu based on the events received from the environment.Komadu has its roots in the Karma [2] provenance capture system, an earlier version that complied with the OPM community standard [3] both for defining the type of provenance notifications that the system accepted, and for defining the format of the results. Komadu, on the other hand, supports the W3C PROV specification [1] which provides far richer types of relationships and has a more formal model for handling time than does OPM. Karma was additionally limited by assuming that every notification belonging to the same external activity shared a common global identifier that is shared across all components (services, methods etc.) of the external environment. This limitation was found to be severe in applications where provenance is not only captured at the application level, but also at in the larger environment where the application runs. Take for instance a distributed application running in PlanetLab [7] and running under Twister [8]; it is highly limiting to expect provenance events generated from the application, from PlanetLab, and from Twister to all have shared knowledge about any single global identifier. This limitation derives from Karma's early days where it tracked provenance for applications running within a single workflow system. Additionally, a researcher may be interested in tracking lineage starting from some data product or agent. Such scenarios are not supported by Karma.In this paper, we introduce Komadu [9] provenance capture and visualization system. Komadu is a complete redesign and reimplementation of Karma that supports new features while addressing the above mentioned limitations of Karma. The main contributions of Komadu are as follows. . Even though Komadu has been used most extensively in relation to scientific research, its interfaces are designed to collect and visualize provenance of any kind of application needing provenance.

BackgroundThe human immunodeficiency virus type 1(HIV-1) epidemic in Chongqing, China, is increasing rapidly with the dominant subtype of CRF07_BC over the past 3 years. Since human leukocyte antigen (HLA) polymorphisms have shown strong association with susceptibility/resistance to HIV-1 infection from individuals with different ethnic backgrounds, a recent investigation on frequencies of HLA class I and class II alleles in a Chinese cohort also indicated that similar correlation existed in HIV infected individuals from several provinces in China, however, such information is unavailable in Chongqing, southwest China.MethodsIn this population-based study, we performed polymerase chain reaction analysis with sequence-specific oligonucleotide probes (PCR-SSOP) for intermediate-low-resolution HLA typing in a cohort of 549 HIV-1 infected individuals, another 2475 healthy subjects from the Han nationality in Chongqing, China, were selected as population control. We compared frequencies of HLA-A, B, DRB1 alleles, haplotypes and genotypes between the two groups, and analyzed their association with HIV-1 susceptibility or resistance.ResultsThe genetic profile of HLA (A, B, DRB1) alleles of HIV-1 infected individuals from Chongqing Han of China was obtained. Several alleles of HLA-B such as B*46 (P = 0.001, OR = 1.38, 95%CI = 1.13-1.68), B*1501G(B62) (P = 0.013, OR = 1.42, 95%CI = 1.08-1.88), B*67 (P = 0.022, OR = 2.76, 95%CI = 1.16-6.57), B*37 (P = 0.014, OR = 1.93, 95%CI = 1.14-3.28) and B*52 (P = 0.038, OR = 1.64, 95%CI = 1.03-2.61) were observed to have association with susceptibility to HIV-1 infection in this population. In addition, the haplotype analysis revealed that A*11-B*46, A*24-B*54 and A*01-B*37 for 2-locus, and A*11-B*46-DRB1*09, A*02-B*46-DRB1*08, A*11-B*4001G-DRB1*15, A*02-B*4001G-DRB1*04, A*11-B*46-DRB1*08 and A*02-B*4001G-DRB1*12 for 3-locus had significantly overrepresented in HIV-1 infected individuals, whereas A*11-B*1502G, A*11-B*1502G-DRB1*12 and A*33-B*58-DRB1*13 were underrepresented. However, the low-resolution homozygosity of HLA-A, B, DRB1 loci and HLA-Bw4/Bw6 genotypes did not differ significantly between the two groups.ConclusionThese results may contribute to the database of HLA profiles in HIV-1 infected Chinese population, consequently, the association of certain HLA alleles with susceptibility or resistance to HIV-1 infection would provide with clues in choosing proper preventive strategies against HIV-1 infection and developing effective HIV-1 vaccines in Chinese population, especially for those in southwest China.

Background Parental rearing is well documented as an important influencing factor of interpersonal sensitivity (IS). However, little research has focused on the extent by which various aspects of parental rearing in fluence IS. This study aimed to analyze the effects of parental rearing on IS, using quantile regression. We analyzed the extent of the influence of parental rearing on IS by quantile regression to provide definitive evidence on the family education of adolescents with IS problems. Methods The multiple cross-sectional studies were conducted among 3345 adolescents from Harbin, China, in 1999, 2006, 2009 and 2016. Furthermore, a multistage sampling method (stratified random cluster) was used to select participants. IS was assessed using a subscale of the Symptom Checklist-90-Revision. Perceived parental rearing was assessed using the Egna Minnen av. Barndoms Uppfostran. The ordinary least squares (OLS) linear regression was used to determine the average effect of parental rearing on IS. The quantile regression was conducted to examine the established associations and to further explain the association. Results Paternal emotional warmth was found to be associated with IS across the quantile, especially after the 0.6 quantiles; however, this association was not found for maternal emotional warmth. Paternal punishment was associated with IS at the 0.22–0.27 and 0.60 quantile; however, maternal punishment had no significant effect on IS. QR method found that paternal overinvolvement was associated with IS at the 0.48–0.65 quantiles, but paternal overprotection was associated with IS across the quantile; however, maternal overinvolvement and overprotection was positively correlated with IS at the 0.07–0.95 quantiles. The correlation between paternal rejection and IS was found at the 0.40–0.75 and > 0.90 quantiles; maternal rejection was associated with IS within the 0.05–0.92 quantiles. Conclusions Parental rearing practices predict different magnitudes of IS at varying levels. This study provides suggestions for parents to assess purposefully and systematically, intervene, and ameliorate adolescent IS problems. We also highlight the role of paternal rearing in children’s IS problems, providing new ideas for family education.