Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

Background: A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods: We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results: The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion: Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations

Unlocking Community Capabilities Across Health Systems in Low- and Middle-Income Countries: Lessons Learned from Research and Reflective Practice

The right and responsibility of communities to participate in health service delivery was enshrined in the 1978 Alma Ata declaration and continues to feature centrally in health systems debates today. Communities are a vital part of people-centred health systems and their engagement is critical to realizing the diverse health targets prioritised by the Sustainable Development Goals and the commitments made to Universal Health Coverage. Community members' intimate knowledge of local needs and adaptive capacities are essential in constructively harnessing global transformations related to epidemiological and demographic transitions, urbanization, migration, technological innovation and climate change. Effective community partnerships and governance processes that underpin community capability also strengthen local resilience, enabling communities to better manage shocks, sustain gains, and advocate for their needs through linkages to authorities and services. This is particularly important given how power relations mark broader contexts of resource scarcity and concentration, struggles related to social liberties and other types of ongoing conflicts.IS

Task shifting: the answer to the human resources crisis in Africa?

Ever since the 2006 World Health Report advocated increased community participation and the systematic delegation of tasks to less-specialized cadres, there has been a great deal of debate about the expediency, efficacy and modalities of task shifting

Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis

Background: Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. Methodology/Principal Findings: To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. Conclusions/Significance: The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.FINEP [01.06.1092.00]FINEPCNPq Universal [481506/2007-1]CNPq UniversalCNPqCNPqCapesCAPESad Associacao Alberto Santos Dumont para Apoio a Pesquisa (AASDAP)a'd Associacao Alberto Santos Dumont para Apoio a Pesquisa (AASDAP

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Characterising and Predicting Haploinsufficiency in the Human Genome

Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies

Association of the MAOA promoter uVNTR polymorphism with suicide attempts in patients with major depressive disorder

<p>Abstract</p> <p>Background</p> <p>The MAOA uVNTR polymorphism has been documented to affect the MAOA gene at the transcriptional level and is associated with aggressive impulsive behaviors, depression associated with suicide (depressed suicide), and major depressive disorder (MDD). We hypothesized that the uVNTR polymorphism confers vulnerability to MDD, suicide or both. The aim of this study was to explore the association between the MAOA uVNTR and depressed suicide, using multiple controls.</p> <p>Methods</p> <p>Four different groups were included: 432 community controls, 385 patients with MDD who had not attempted suicide, 96 community subjects without mental disorders who had attempted suicide, and 109 patients with MDD who had attempted suicide. The MAOA uVNTR polymorphism was genotyped by a PCR technique. The symptom profiles and personal characteristics in each group were also compared.</p> <p>Results</p> <p>The MAOA 4R allele was more frequent in males with MDD than in male community controls (χ²= 4.182, p = 0.041). Logistic regression analysis showed that, among the depressed subjects, those younger in age, more neurotic or who smoked had an increased risk of suicide (β = -0.04, p = 0.002; β = 0.15, p = 0.017; β = 0.79, p = 0.031, respectively). Moreover, among those who had attempted suicide, those younger in age, with more paternal overprotection, and more somatic symptoms were more likely to be in the MDD group than in the community group (β = -0.11, p < 0.001; β = 0.15, p = 0.026; β = 1.11, p < 0.001). Structural equation modeling (SEM) showed that nongenetic factors, such as age, paternal overprotection, and somatic symptoms, were associated with MDD, whereas depressed suicide were associated with severity of depression, personality traits, age, marital status, and inversely associated with anxiety symptoms. However, depression did not affect suicidal behavior in the community group.</p> <p>Conclusion</p> <p>The MAOA 4R allele is associated with enhanced vulnerability to suicide in depressed males, but not in community subjects. The MAOA 4R allele affects vulnerability to suicide through the mediating factor of depressive symptoms. Further large-scale studies are needed to verify the psychopathology of the relationships among MAOA uVNTR polymorphism, symptom profiles, and suicidal behavior.</p

Clinical application of stem cell therapy in Parkinson's disease

Cell replacement therapies in Parkinson's disease (PD) aim to provide long-lasting relief of patients' symptoms. Previous clinical trials using transplantation of human fetal ventral mesencephalic (hfVM) tissue in the striata of PD patients have provided proof-of-principle that such grafts can restore striatal dopaminergic (DA-ergic) function. The transplants survive, reinnervate the striatum, and generate adequate symptomatic relief in some patients for more than a decade following operation. However, the initial clinical trials lacked homogeneity of outcomes and were hindered by the development of troublesome graft-induced dyskinesias in a subgroup of patients. Although recent knowledge has provided insights for overcoming these obstacles, it is unlikely that transplantation of hfVM tissue will become routine treatment for PD owing to problems with tissue availability and standardization of the grafts. The main focus now is on producing DA-ergic neuroblasts for transplantation from stem cells (SCs). There is a range of emerging sources of SCs for generating a DA-ergic fate in vitro. However, the translation of these efforts in vivo currently lacks efficacy and sustainability. A successful, clinically competitive SC therapy in PD needs to produce long-lasting symptomatic relief without side effects while counteracting PD progression

Whole Genome Expression Array Profiling Highlights Differences in Mucosal Defense Genes in Barrett's Esophagus and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) has become a major concern in Western countries due to rapid rises in incidence coupled with very poor survival rates. One of the key risk factors for the development of this cancer is the presence of Barrett's esophagus (BE), which is believed to form in response to repeated gastro-esophageal reflux. In this study we performed comparative, genome-wide expression profiling (using Illumina whole-genome Beadarrays) on total RNA extracted from esophageal biopsy tissues from individuals with EAC, BE (in the absence of EAC) and those with normal squamous epithelium. We combined these data with publically accessible raw data from three similar studies to investigate key gene and ontology differences between these three tissue states. The results support the deduction that BE is a tissue with enhanced glycoprotein synthesis machinery (DPP4, ATP2A3, AGR2) designed to provide strong mucosal defenses aimed at resisting gastro-esophageal reflux. EAC exhibits the enhanced extracellular matrix remodeling (collagens, IGFBP7, PLAU) effects expected in an aggressive form of cancer, as well as evidence of reduced expression of genes associated with mucosal (MUC6, CA2, TFF1) and xenobiotic (AKR1C2, AKR1B10) defenses. When our results are compared to previous whole-genome expression profiling studies keratin, mucin, annexin and trefoil factor gene groups are the most frequently represented differentially expressed gene families. Eleven genes identified here are also represented in at least 3 other profiling studies. We used these genes to discriminate between squamous epithelium, BE and EAC within the two largest cohorts using a support vector machine leave one out cross validation (LOOCV) analysis. While this method was satisfactory for discriminating squamous epithelium and BE, it demonstrates the need for more detailed investigations into profiling changes between BE and EAC