Do Diagnosis Delays Impact Receipt of Test Results? Evidence from the HIV Early Infant Diagnosis Program in Uganda

Background

There is scant evidence on the association between diagnosis delays and the receipt of test results in HIV Early Infant Diagnosis (EID) programs. We determine the association between diagnosis delays and other health care system and patient factors on result receipt.

Methods

We reviewed 703 infant HIV test records for tests performed between January 2008 and February 2009 at a regional referral hospital and level four health center in Uganda. The main outcome was caregiver receipt of the test result. The primary study variable was turnaround time (time between sample collection and result availability at the health facility). Additional variables included clinic entry point, infant age at sample collection, reported HIV status and receipt of antiretroviral prophylaxis for prevention of mother-to-child transmission. We conducted a pooled analysis in addition to separate analyses for each facility. We estimated the relative risk of result receipt using modified Poisson regression with robust standard errors.

Results

Overall, the median result turnaround time, was 38 days. 59% of caregivers received infant test results. Caregivers were less likely to receive results at turnaround times greater than 49 days compared to 28 days or fewer (ARR = 0.83; 95% CI = 0.70–0.98). Caregivers were more likely to receive results at the PMTCT clinic (ARR = 1.81; 95% CI = 1.40–2.33) and less likely at the pediatric ward (ARR = 0.54; 95% CI = 0.37–0.81) compared to the immunization clinic. At the level four health center, result receipt was half as likely among infants older than 9 months compared to 3 months and younger (ARR= 0.47; 95% CI = 0.25–0.93).

Conclusion

In this study setting, we find evidence that longer turnaround times, clinic entry point and age at sample collection may be associated with receipt of infant HIV test results.     

Permanent Cerebral Vessel Occlusion via Double Ligature and Transection

Stroke is a leading cause of death, disability, and socioeconomic loss worldwide. The majority of all strokes result from an interruption in blood flow (ischemia) ¹. Middle cerebral artery (MCA) delivers a great majority of blood to the lateral surface of the cortex ², is the most common site of human stroke ³, and ischemia within its territory can result in extensive dysfunction or death ^1,4,5. Survivors of ischemic stroke often suffer loss or disruption of motor capabilities, sensory deficits, and infarct. In an effort to capture these key characteristics of stroke, and thereby develop effective treatment, a great deal of emphasis is placed upon animal models of ischemia in MCA.Here we present a method of permanently occluding a cortical surface blood vessel. We will present this method using an example of a relevant vessel occlusion that models the most common type, location, and outcome of human stroke, permanent middle cerebral artery occlusion (pMCAO). In this model, we surgically expose MCA in the adult rat and subsequently occlude via double ligature and transection of the vessel. This pMCAO blocks the proximal cortical branch of MCA, causing ischemia in all of MCA cortical territory, a large portion of the cortex. This method of occlusion can also be used to occlude more distal portions of cortical vessels in order to achieve more focal ischemia targeting a smaller region of cortex. The primary disadvantages of pMCAO are that the surgical procedure is somewhat invasive as a small craniotomy is required to access MCA, though this results in minimal tissue damage. The primary advantages of this model, however, are: the site of occlusion is well defined, the degree of blood flow reduction is consistent, functional and neurological impairment occurs rapidly, infarct size is consistent, and the high rate of survival allows for long-term chronic assessment.     

Trypsin Potentiates Human Fibrocyte Differentiation

Trypsin-containing topical treatments can be used to speed wound healing, although the mechanism of action is unknown. To help form granulation tissue and heal wounds, monocytes leave the circulation, enter the wound tissue, and differentiate into fibroblast-like cells called fibrocytes. We find that 20 to 200 ng/ml trypsin (concentrations similar to those used in wound dressings) potentiates the differentiation of human monocytes to fibrocytes in cell culture. Adding trypsin inhibitors increases the amount of trypsin needed to potentiate fibrocyte differentiation, suggesting that the potentiating effect is dependent on trypsin proteolytic activity. Proteases with other site specificities such as pepsin, endoprotease GluC, and chymotrypsin do not potentiate fibrocyte differentiation. This potentiation requires the presence of albumin in the culture medium, and tryptic fragments of human or bovine albumin also potentiate fibrocyte differentiation. These results suggest that topical trypsin speeds wound healing by generating tryptic fragments of albumin, which in turn potentiate fibrocyte differentiation.     

A Hybrid Likelihood Model for Sequence-Based Disease Association Studies

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.     

Distance-based analysis of variance for brain connectivity

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures, including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that might mask the salient features of high-dimensional distributions. In this work, we consider a general framework for two-sample testing of complex structures by studying generalized within-group and between-group variances based on distances between complex and potentially high-dimensional observations. We derive an asymptotic approximation to the null distribution of the ANOVA test statistic, and conduct simulation studies with scalar and graph outcomes to study finite sample properties of the test. Finally, we apply our test to our motivating study of structural connectivity in autism spectrum disorder.     

Making Sense of Human Ecology Mapping: An Overview of Approaches to Integrating Socio-Spatial Data into Environmental Planning

Ecosystem-based planning and management have stimulated the need to gather sociocultural values and human uses of land in formats accessible to diverse planners and researchers. Human Ecology Mapping (HEM) approaches offer promising spatial data gathering and analytical tools, while also addressing important questions about human-landscape connections. This article reviews and compares the characteristics of three HEM approaches that are increasingly used in natural resource management contexts, each focused on a particular aspect of human-environmental interactions. These aspects include tenure and resource use (TRU), local ecological knowledge (LEK), and sense of place (SOP). We discuss their origins, provide examples of their use, and identify challenges to their application. Our review serves as a guide for environmental managers, planners, and communities interested in gathering spatial data on aspects of human ecology important in ecosystem-based management and planning, and for scientists designing socioecological research.     

Homology Modeling of Wild-type,D516V,and H526L Mycobacterium Tuberculosis RNA Polymerase and Their Molecular Docking Study with Inhibitors

Abstract

Rifamicyns (Rifs) are antibiotic widely used for the treatment of tuberculosis (TB); nevertheless, their efficacy has been limited by a high percentage of mutations, principally in the rpoB gene. In this work, the first three-dimensional molecular model of the hypothetical structures for the wild-type and D516V and H526L mutants of Mycobacterium tuberculosis (mtRNAP) were elucidated by a homology modeling method. In addition, the orientations and binding affinities of some Rifs with those new structures were investigated. Our findings could be helpful for the design of new more potent rifamycin analogs.