Amygdala subnuclei response and connectivity during emotional processing

The involvement of the human amygdala in emotion-related processing has been studied using functional magnetic resonance imaging (fMRI) for many years. However, despite the amygdala being comprised of several subnuclei, most studies investigated the role of the entire amygdala in processing of emotions. Here we combined a novel anatomical tracing protocol with event-related high-resolution fMRI acquisition to study the responsiveness of the amygdala subnuclei to negative emotional stimuli and to examine intra-amygdala functional connectivity. The greatest sensitivity to the negative emotional stimuli was observed in the centromedial amygdala, where the hemodynamic response amplitude elicited by the negative emotional stimuli was greater and peaked later than for neutral stimuli. Connectivity patterns converge with extant findings in animals, such that the centromedial amygdala was more connected with the nuclei of the basal amygdala than with the lateral amygdala. Current findings provide evidence of functional specialization within the human amygdala

Disease burden affects aging brain function

BACKGROUND: Most older adults live with multiple chronic disease conditions, yet the effect of multiple diseases on brain function remains unclear. METHODS: We examine the relationship between disease multimorbidity and brain activity using regional cerebral blood flow (rCBF) 15O-water PET scans from 97 cognitively normal participants (mean baseline age 76.5) in the Baltimore Longitudinal Study of Aging (BLSA). Multimorbidity index scores, generated from the presence of 13 health conditions, were correlated with PET data at baseline and in longitudinal change (n = 74) over 5.05 (2.74 SD) years. RESULTS: At baseline, voxel-based analysis showed that higher multimorbidity scores were associated with lower relative activity in orbitofrontal, superior frontal, temporal pole and parahippocampal regions, and greater activity in lateral temporal, occipital, and cerebellar regions. Examination of the individual health conditions comprising the index score showed hypertension and chronic kidney disease individually contributed to the overall multimorbidity pattern of altered activity. Longitudinally, both increases and decreases in activity were seen in relation to increasing multimorbidity over time. These associations were identified in orbitofrontal, lateral temporal, brainstem, and cerebellar areas. CONCLUSION: Together, these results show that greater multimorbidity is associated with widespread areas of altered brain activity, supporting a link between health and changes in aging brain function

Estimating HIV Incidence among Adults in Kenya and Uganda: A Systematic Comparison of Multiple Methods

CITATION: Kim, A. A. et al. 2011. Estimating HIV incidence among adults in Kenya and Uganda : a systematic comparison of multiple methods. PLos ONE, 6(3): e17535, doi:10.1371/journal.pone.0017535.The original publication is available at http://journals.plos.org/plosoneBackground: Several approaches have been used for measuring HIV incidence in large areas, yet each presents specific challenges in incidence estimation. Methodology/Principal Findings: We present a comparison of incidence estimates for Kenya and Uganda using multiple methods: 1) Epidemic Projections Package (EPP) and Spectrum models fitted to HIV prevalence from antenatal clinics (ANC) and national population-based surveys (NPS) in Kenya (2003, 2007) and Uganda (2004/2005); 2) a survey-derived model to infer age-specific incidence between two sequential NPS; 3) an assay-derived measurement in NPS using the BED IgG capture enzyme immunoassay, adjusted for misclassification using a locally derived false-recent rate (FRR) for the assay; (4) community cohorts in Uganda; (5) prevalence trends in young ANC attendees. EPP/Spectrum-derived and survey-derived modeled estimates were similar: 0.67 [uncertainty range: 0.60, 0.74] and 0.6 [confidence interval: (CI) 0.4, 0.9], respectively, for Uganda (2005) and 0.72 [uncertainty range: 0.70, 0.74] and 0.7 [CI 0.3, 1.1], respectively, for Kenya (2007). Using a local FRR, assay-derived incidence estimates were 0.3 [CI 0.0, 0.9] for Uganda (2004/2005) and 0.6 [CI 0, 1.3] for Kenya (2007). Incidence trends were similar for all methods for both Uganda and Kenya. Conclusions/Significance: Triangulation of methods is recommended to determine best-supported estimates of incidence to guide programs. Assay-derived incidence estimates are sensitive to the level of the assay's FRR, and uncertainty around high FRRs can significantly impact the validity of the estimate. Systematic evaluations of new and existing incidence assays are needed to the study the level, distribution, and determinants of the FRR to guide whether incidence assays can produce reliable estimates of national HIV incidence.http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0017535Publisher's versio

Sensitivity of IFN-γ Release Assay to Detect Latent Tuberculosis Infection Is Retained in HIV-Infected Patients but Dependent on HIV/AIDS Progression

BACKGROUND: Detection and treatment of latent TB infection (LTBI) in HIV infected individuals is strongly recommended to decrease morbidity and mortality in countries with high levels of HIV. OBJECTIVE: To assess the validity of a newly developed in-house ELISPOT interferon-gamma release assay (IGRA) for the detection of LTBI amongst HIV infected individuals, in comparison with the Tuberculin Skin Test (TST). METHODOLOGY/PRINCIPAL FINDINGS: ESAT6/CFP10 (EC) ELISPOT assays were performed, together with a TST, in 285 HIV infected individuals recruited in HIV clinics in Dakar, Senegal, who had no signs of active TB at time of enrolment. Thirty eight of the subjects (13.3%) failed to respond to PHA stimulation and were excluded from the analysis. In the 247 remaining patients, response to PHA did not vary according to CD4 cell count categories (p = 0.51). EC ELISPOT was positive in 125 (50.6%) subjects, while 53 (21.5%) had a positive TST. Concordance between EC ELISPOT and TST was observed in 151 patients (61.1%) (kappa = 0.23). The proportion of subjects with a positive response to the EC ELISPOT assay decreased with declining CD4 counts (p trend = 0.001), but were consistently higher than the proportion of TST responders. In multivariate analysis, the risk of being EC-ELISPOT positive in HIV infected individuals was associated with age, CD4 count and HIV-1 strain. CONCLUSION: Our study indicates that IGRAs using M. tuberculosis specific antigens are likely to retain their validity for the diagnosis of LTBI among HIV positive individuals, but may be impaired by T-cell anergy in severely immuno-suppressed individuals

Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time

Background: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. Methodology/Principal Findings: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8-16) weeks (2152 TCEs), 24 (16-32) weeks (2570 TCEs), and 48 (44-52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92±1.17, compared to Rega and ANRS, with 2.22±1.09 and 2.23±1.05, respectively. However, similar odds ratio's were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5-1.7] for HIVdb, 1.7 [1.5-1.8] for ANRS, and 1.7 [1.9-1.6] for Rega. Odds ratio's increased over time, but remained comparable (odds ratio's ranging between 1.9-2.1 at 24 weeks and 1.9-2.

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives