Strengths and Weaknesses of Global Positioning System (GPS) Data-Loggers and Semi-structured Interviews for Capturing Fine-scale Human Mobility: Findings from Iquitos,Peru

Quantifying human mobility has significant consequences for studying physical activity, exposure to pathogens, and generating more realistic infectious disease models. Location-aware technologies such as Global Positioning System (GPS)-enabled devices are used increasingly as a gold standard for mobility research. The main goal of this observational study was to compare and contrast the information obtained through GPS and semi-structured interviews (SSI) to assess issues affecting data quality and, ultimately, our ability to measure fine-scale human mobility. A total of 160 individuals, ages 7 to 74, from Iquitos, Peru, were tracked using GPS data-loggers for 14 days and later interviewed using the SSI about places they visited while tracked. A total of 2,047 and 886 places were reported in the SSI and identified by GPS, respectively. Differences in the concordance between methods occurred by location type, distance threshold (within a given radius to be considered a match) selected, GPS data collection frequency (i.e., 30, 90 or 150 seconds) and number of GPS points near the SSI place considered to define a match. Both methods had perfect concordance identifying each participant''s house, followed by 80–100% concordance for identifying schools and lodgings, and 50–80% concordance for residences and commercial and religious locations. As the distance threshold selected increased, the concordance between SSI and raw GPS data increased (beyond 20 meters most locations reached their maximum concordance). Processing raw GPS data using a signal-clustering algorithm decreased overall concordance to 14.3%. The most common causes of discordance as described by a sub-sample (n = 101) with whom we followed-up were GPS units being accidentally off (30%), forgetting or purposely not taking the units when leaving home (24.8%), possible barriers to the signal (4.7%) and leaving units home to recharge (4.6%). We provide a quantitative assessment of the strengths and weaknesses of both methods for capturing fine-scale human mobility.     

Long-Term and Seasonal Dynamics of Dengue in Iquitos,Peru

Introduction

Long-term disease surveillance data provide a basis for studying drivers of pathogen transmission dynamics. Dengue is a mosquito-borne disease caused by four distinct, but related, viruses (DENV-1-4) that potentially affect over half the world''s population. Dengue incidence varies seasonally and on longer time scales, presumably driven by the interaction of climate and host susceptibility. Precise understanding of dengue dynamics is constrained, however, by the relative paucity of laboratory-confirmed longitudinal data.

Methods

We studied 10 years (2000–2010) of laboratory-confirmed, clinic-based surveillance data collected in Iquitos, Peru. We characterized inter and intra-annual patterns of dengue dynamics on a weekly time scale using wavelet analysis. We explored the relationships of case counts to climatic variables with cross-correlation maps on annual and trimester bases.

Findings

Transmission was dominated by single serotypes, first DENV-3 (2001–2007) then DENV-4 (2008–2010). After 2003, incidence fluctuated inter-annually with outbreaks usually occurring between October and April. We detected a strong positive autocorrelation in case counts at a lag of ∼70 weeks, indicating a shift in the timing of peak incidence year-to-year. All climatic variables showed modest seasonality and correlated weakly with the number of reported dengue cases across a range of time lags. Cases were reduced after citywide insecticide fumigation if conducted early in the transmission season.

Conclusions

Dengue case counts peaked seasonally despite limited intra-annual variation in climate conditions. Contrary to expectations for this mosquito-borne disease, no climatic variable considered exhibited a strong relationship with transmission. Vector control operations did, however, appear to have a significant impact on transmission some years. Our results indicate that a complicated interplay of factors underlie DENV transmission in contexts such as Iquitos.     

Large multiethnic Candidate Gene Study for C-reactive protein levels: identification of a novel association at CD36 in African Americans

C-reactive protein (CRP) is a heritable biomarker of systemic inflammation and a predictor of cardiovascular disease (CVD). Large-scale genetic association studies for CRP have largely focused on individuals of European descent. We sought to uncover novel genetic variants for CRP in a multiethnic sample using the ITMAT Broad-CARe (IBC) array, a custom 50,000 SNP gene-centric array having dense coverage of over 2,000 candidate CVD genes. We performed analyses on 7,570 African Americans (AA) from the Candidate gene Association Resource (CARe) study and race-combined meta-analyses that included 29,939 additional individuals of European descent from CARe, the Women’s Health Initiative (WHI) and KORA studies. We observed array-wide significance (p < 2.2 × 10^?6) for four loci in AA, three of which have been reported previously in individuals of European descent (IL6R, p = 2.0 × 10^?6; CRP, p = 4.2 × 10^?71; APOE, p = 1.6 × 10^?6). The fourth significant locus, CD36 (p = 1.6 × 10^?6), was observed at a functional variant (rs3211938) that is extremely rare in individuals of European descent. We replicated the CD36 finding (p = 1.8 × 10^?5) in an independent sample of 8,041 AA women from WHI; a meta-analysis combining the CARe and WHI AA results at rs3211938 reached genome-wide significance (p = 1.5 × 10^?10). In the race-combined meta-analyses, 13 loci reached significance, including ten (CRP, TOMM40/APOE/APOC1, HNF1A, LEPR, GCKR, IL6R, IL1RN, NLRP3, HNF4A and BAZ1B/BCL7B) previously associated with CRP, and one (ARNTL) previously reported to be nominally associated with CRP. Two novel loci were also detected (RPS6KB1, p = 2.0 × 10^?6; CD36, p = 1.4 × 10^?6). These results highlight both shared and unique genetic risk factors for CRP in AA compared to populations of European descent.     

Transcriptomic Meta-Analysis of Multiple Sclerosis and Its Experimental Models

Background

Multiple microarray analyses of multiple sclerosis (MS) and its experimental models have been published in the last years.

Objective

Meta-analyses integrate the information from multiple studies and are suggested to be a powerful approach in detecting highly relevant and commonly affected pathways.

Data sources

ArrayExpress, Gene Expression Omnibus and PubMed databases were screened for microarray gene expression profiling studies of MS and its experimental animal models.

Study eligibility criteria

Studies comparing central nervous system (CNS) samples of diseased versus healthy individuals with n >1 per group and publically available raw data were selected.

Material and Methods

Included conditions for re-analysis of differentially expressed genes (DEGs) were MS, myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis (EAE) in rats, proteolipid protein-induced EAE in mice, Theiler’s murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD), and a transgenic tumor necrosis factor-overexpressing mouse model (TNFtg). Since solely a single MS raw data set fulfilled the inclusion criteria, a merged list containing the DEGs from two MS-studies was additionally included. Cross-study analysis was performed employing list comparisons of DEGs and alternatively Gene Set Enrichment Analysis (GSEA).

Results

The intersection of DEGs in MS, EAE, TMEV-IDD, and TNFtg contained 12 genes related to macrophage functions. The intersection of EAE, TMEV-IDD and TNFtg comprised 40 DEGs, functionally related to positive regulation of immune response. Over and above, GSEA identified substantially more differentially regulated pathways including coagulation and JAK/STAT-signaling.

Conclusion

A meta-analysis based on a simple comparison of DEGs is over-conservative. In contrast, the more experimental GSEA approach identified both, a priori anticipated as well as promising new candidate pathways.     

Phenotypic Characterization of a Leishmania donovani Cyclophilin 40 Null Mutant

Protozoan parasites of the genus Leishmania adapt to their arthropod and vertebrate hosts through the development of defined life cycle stages. Stage differentiation is triggered by environmental stress factors and has been linked to parasite chaperone activities. Using a null mutant approach we previously revealed important, nonredundant functions of the cochaperone cyclophilin 40 in L. donovani‐infected macrophages. Here, we characterized in more detail the virulence defect of cyp40?/? null mutants. In vitro viability assays, infection tests using macrophages, and mixed infection experiments ruled out a defect of cyp40?/? parasites in resistance to oxidative and hydrolytic stresses encountered inside the host cell phagolysosome. Investigation of the CyP40‐dependent proteome by quantitative 2D‐DiGE analysis revealed up regulation of various stress proteins in the null mutant, presumably a response to compensate for the lack of CyP40. Applying transmission electron microscopy we showed accumulation of vesicular structures in the flagellar pocket of cyp40?/? parasites that we related to a significant increase in exosome production, a phenomenon previously linked to the parasite stress response. Together these data suggest that cyp40?/? parasites experience important intrinsic homeostatic stress that likely abrogates parasite viability during intracellular infection.     

Checking and fixing the cellular nanomachinery: towards medical nanoscopy

Most diseases, regardless of their diverse etiologies, manifest themselves as defects of cellular proteins. Cellular proteins have been recently shown to form specific complexes exerting their functions as if they were nanoscopic machines. Such nanoscopic protein machines cooperate in functional modules, yielding extended, highly compartmentalized networks. The classical resolution limits of fluorescence microscopy have also been recently overcome, opening the nanometer domain to live-cell imaging. Together, progress in functional proteomics and live-cell imaging provide novel possibilities for directly analyzing and modifying nanoscopic protein machines in living cells and tissues.