Discriminating active from latent tuberculosis in patients presenting to community clinics.

BACKGROUND: Because of the high global prevalence of latent TB infection (LTBI), a key challenge in endemic settings is distinguishing patients with active TB from patients with overlapping clinical symptoms without active TB but with co-existing LTBI. Current methods are insufficiently accurate. Plasma proteomic fingerprinting can resolve this difficulty by providing a molecular snapshot defining disease state that can be used to develop point-of-care diagnostics. METHODS: Plasma and clinical data were obtained prospectively from patients attending community TB clinics in Peru and from household contacts. Plasma was subjected to high-throughput proteomic profiling by mass spectrometry. Statistical pattern recognition methods were used to define mass spectral patterns that distinguished patients with active TB from symptomatic controls with or without LTBI. RESULTS: 156 patients with active TB and 110 symptomatic controls (patients with respiratory symptoms without active TB) were investigated. Active TB patients were distinguishable from undifferentiated symptomatic controls with accuracy of 87% (sensitivity 84%, specificity 90%), from symptomatic controls with LTBI (accuracy of 87%, sensitivity 89%, specificity 82%) and from symptomatic controls without LTBI (accuracy 90%, sensitivity 90%, specificity 92%). CONCLUSIONS: We show that active TB can be distinguished accurately from LTBI in symptomatic clinic attenders using a plasma proteomic fingerprint. Translation of biomarkers derived from this study into a robust and affordable point-of-care format will have significant implications for recognition and control of active TB in high prevalence settings

A P-type ATPase importer that discriminates between essential and toxic transition metals

Transition metals, although being essential cofactors in many physiological processes, are toxic at elevated concentrations. Among the membrane-embedded transport proteins that maintain appropriate intracellular levels of transition metals are ATP-driven pumps belonging to the P-type ATPase superfamily. These metal transporters may be differentiated according to their substrate specificities, where the majority of pumps can extrude either silver and copper or zinc, cadmium, and lead. In the present report, we have established the substrate specificities of nine previously uncharacterized prokaryotic transition-metal P-type ATPases. We find that all of the newly identified exporters indeed fall into one of the two above-mentioned categories. In addition to these exporters, one importer, Pseudomonas aeruginosa Q9I147, was also identified. This protein, designated HmtA (heavy metal transporter A), exhibited a different substrate recognition profile from the exporters. In vivo metal susceptibility assays, intracellular metal measurements, and transport experiments all suggest that HmtA mediates the uptake of copper and zinc but not of silver, mercury, or cadmium. The substrate selectivity of this importer ensures the high-affinity uptake of essential metals, while avoiding intracellular contamination by their toxic counterparts

Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria

Biomarker discovery aims to find small subsets of relevant variables in ‘omics data that correlate with the clinical syndromes of interest. Despite the fact that clinical phenotypes are usually characterized by a complex set of clinical parameters, current computational approaches assume univariate targets, e.g. diagnostic classes, against which associations are sought for. We propose an approach based on asymmetrical sparse canonical correlation analysis (SCCA) that finds multivariate correlations between the ‘omics measurements and the complex clinical phenotypes. We correlated plasma proteomics data to multivariate overlapping complex clinical phenotypes from tuberculosis and malaria datasets. We discovered relevant ‘omic biomarkers that have a high correlation to profiles of clinical measurements and are remarkably sparse, containing 1.5–3% of all ‘omic variables. We show that using clinical view projections we obtain remarkable improvements in diagnostic class prediction, up to 11% in tuberculosis and up to 5% in malaria. Our approach finds proteomic-biomarkers that correlate with complex combinations of clinical-biomarkers. Using the clinical-biomarkers improves the accuracy of diagnostic class prediction while not requiring the measurement plasma proteomic profiles of each subject. Our approach makes it feasible to use omics' data to build accurate diagnostic algorithms that can be deployed to community health centres lacking the expensive ‘omics measurement capabilities

Severe childhood malaria syndromes defined by plasma proteome profiles

BACKGROUND Cerebral malaria (CM) and severe malarial anemia (SMA) are the most serious life-threatening clinical syndromes of Plasmodium falciparum infection in childhood. Therefore it is important to understand the pathology underlying the development of CM and SMA, as opposed to uncomplicated malaria (UM). Different host responses to infection are likely to be reflected in plasma proteome-patterns that associate with clinical status and therefore provide indicators of the pathogenesis of these syndromes. METHODS AND FINDINGS Plasma and comprehensive clinical data for discovery and validation cohorts were obtained as part of a prospective case-control study of severe childhood malaria at the main tertiary hospital of the city of Ibadan, an urban and densely populated holoendemic malaria area in Nigeria. A total of 946 children participated in this study. Plasma was subjected to high-throughput proteomic profiling. Statistical pattern-recognition methods were used to find proteome-patterns that defined disease groups. Plasma proteome-patterns accurately distinguished children with CM and with SMA from those with UM, and from healthy or severely ill malaria-negative children. CONCLUSIONS We report that an accurate definition of the major childhood malaria syndromes can be achieved using plasma proteome-patterns. Our proteomic data can be exploited to understand the pathogenesis of the different childhood severe malaria syndromes

Cloning of CDP-Diacylglycerol Synthase from a Human Neuronal Cell Line

A critical step in the supply of substrate for the phosphoinositide signal transduction pathway is the formation of the liponucleotide intermediate, CDP-diacylglycerol, catalyzed by CDP-diacylglycerol synthase. Further insight into the regulation of phosphoinositide biosynthesis was sought by cloning of the gene for the vertebrate enzyme. Sequence of the corresponding gene from Drosophila was used to prepare a probe for screening of a human neuronal cell cDNA library. A cDNA was isolated with a predicted open reading frame of 1,332 bases, encoding a protein of 51 kDa. The amino acid sequence showed 50% identity (75% similarity) to that of Drosophila eye CDP-diacylglycerol synthase and substantial similarity to the Saccharomyces cerevisiae and Escherichia coli homologues. Northern blot analysis, with human cDNA riboprobes, suggested that the corresponding mRNA was expressed in all human tissues examined. Expression of the human cDNA in COS cells resulted in a more than fourfold increase in CDP-diacylglycerol synthase activity. Knowledge of the sequence of vertebrate CDP-diacylglycerol synthase should facilitate further investigations into its regulation and the possible existence of distinct isoforms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65959/1/j.1471-4159.1996.67052200.x.pd

Boosting Long-term Memory via Wakeful Rest: Intentional Rehearsal is not Necessary, Automatic Consolidation is Sufficient.

<div><p>People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as ‘foreign names in a bridge club abroad’ and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is <i>not</i> dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is <i>sufficient</i> for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition.</p></div

Management Capabilities and Policy Capacity Where are the Links?

1-1

Gender-dependent differences in plasma matrix metalloproteinase-8 elevated in pulmonary tuberculosis.

Tuberculosis (TB) remains a global health pandemic and greater understanding of underlying pathogenesis is required to develop novel therapeutic and diagnostic approaches. Matrix metalloproteinases (MMPs) are emerging as key effectors of tissue destruction in TB but have not been comprehensively studied in plasma, nor have gender differences been investigated. We measured the plasma concentrations of MMPs in a carefully characterised, prospectively recruited clinical cohort of 380 individuals. The collagenases, MMP-1 and MMP-8, were elevated in plasma of patients with pulmonary TB relative to healthy controls, and MMP-7 (matrilysin) and MMP-9 (gelatinase B) were also increased. MMP-8 was TB-specific (p<0.001), not being elevated in symptomatic controls (symptoms suspicious of TB but active disease excluded). Plasma MMP-8 concentrations inversely correlated with body mass index. Plasma MMP-8 concentration was 1.51-fold higher in males than females with TB (p<0.05) and this difference was not due to greater disease severity in men. Gender-specific analysis of MMPs demonstrated consistent increase in MMP-1 and -8 in TB, but MMP-8 was a better discriminator for TB in men. Plasma collagenases are elevated in pulmonary TB and differ between men and women. Gender must be considered in investigation of TB immunopathology and development of novel diagnostic markers

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