Examining agreement between clinicians when assessing sick children.

BACKGROUND: Case management guidelines use a limited set of clinical features to guide assessment and treatment for common childhood diseases in poor countries. Using video records of clinical signs we assessed agreement among experts and assessed whether Kenyan health workers could identify signs defined by expert consensus. METHODOLOGY: 104 videos representing 11 clinical sign categories were presented to experts using a web questionnaire. Proportionate agreement and agreement beyond chance were calculated using kappa and the AC1 statistic. 31 videos were selected and presented to local health workers, 20 for which experts had demonstrated clear agreement and 11 for which experts could not demonstrate agreement. PRINCIPAL FINDINGS: Experts reached very high level of chance adjusted agreement for some videos while for a few videos no agreement beyond chance was found. Where experts agreed Kenyan hospital staff of all cadres recognised signs with high mean sensitivity and specificity (sensitivity: 0.897-0.975, specificity: 0.813-0.894); years of experience, gender and hospital had no influence on mean sensitivity or specificity. Local health workers did not agree on videos where experts had low or no agreement. Results of different agreement statistics for multiple observers, the AC1 and Fleiss' kappa, differ across the range of proportionate agreement. CONCLUSION: Videos provide a useful means to test agreement amongst geographically diverse groups of health workers. Kenyan health workers are in agreement with experts where clinical signs are clear-cut supporting the potential value of assessment and management guidelines. However, clinical signs are not always clear-cut. Video recordings offer one means to help standardise interpretation of clinical signs

Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway.

The ability to biosynthetically produce chemicals beyond what is commonly found in Nature requires the discovery of novel enzyme function. Here we utilize two approaches to discover enzymes that enable specific production of longer-chain (C5-C8) alcohols from sugar. The first approach combines bioinformatics and molecular modelling to mine sequence databases, resulting in a diverse panel of enzymes capable of catalysing the targeted reaction. The median catalytic efficiency of the computationally selected enzymes is 75-fold greater than a panel of naively selected homologues. This integrative genomic mining approach establishes a unique avenue for enzyme function discovery in the rapidly expanding sequence databases. The second approach uses computational enzyme design to reprogramme specificity. Both approaches result in enzymes with >100-fold increase in specificity for the targeted reaction. When enzymes from either approach are integrated in vivo, longer-chain alcohol production increases over 10-fold and represents >95% of the total alcohol products

Metabolomics Identifies multiple candidate biomarkers to diagnose and stage human African trypanosomiasis

Treatment for human African trypanosomiasis is dependent on the species of trypanosome causing the disease and the stage of the disease (stage 1 defined by parasites being present in blood and lymphatics whilst for stage 2, parasites are found beyond the blood-brain barrier in the cerebrospinal fluid (CSF)). Currently, staging relies upon detecting the very low number of parasites or elevated white blood cell numbers in CSF. Improved staging is desirable, as is the elimination of the need for lumbar puncture. Here we use metabolomics to probe samples of CSF, plasma and urine from 40 Angolan patients infected with Trypanosoma brucei gambiense, at different disease stages. Urine samples provided no robust markers indicative of infection or stage of infection due to inherent variability in urine concentrations. Biomarkers in CSF were able to distinguish patients at stage 1 or advanced stage 2 with absolute specificity. Eleven metabolites clearly distinguished the stage in most patients and two of these (neopterin and 5-hydroxytryptophan) showed 100% specificity and sensitivity between our stage 1 and advanced stage 2 samples. Neopterin is an inflammatory biomarker previously shown in CSF of stage 2 but not stage 1 patients. 5-hydroxytryptophan is an important metabolite in the serotonin synthetic pathway, the key pathway in determining somnolence, thus offering a possible link to the eponymous symptoms of “sleeping sickness”. Plasma also yielded several biomarkers clearly indicative of the presence (87% sensitivity and 95% specificity) and stage of disease (92% sensitivity and 81% specificity). A logistic regression model including these metabolites showed clear separation of patients being either at stage 1 or advanced stage 2 or indeed diseased (both stages) versus control

Models and average properties of scale-free directed networks

We extend the merging model for undirected networks by Kim et al. [Eur. Phys. J. B 43, 369 (2004)] to directed networks and investigate the emerging scale-free networks. Two versions of the directed merging model, friendly and hostile merging, give rise to two distinct network types. We uncover that some non-trivial features of these two network types resemble two levels of a certain randomization/non-specificity in the link reshuffling during network evolution. Furthermore the same features show up, respectively, in metabolic networks and transcriptional networks. We introduce measures that single out the distinguishing features between the two prototype networks, as well as point out features which are beyond the prototypes.Comment: 7 pages, 8 figure

A theory for the tissue specificity of BRCA1/2 related and other hereditary cancers

Women who inherit a defective BRCA1 or BRCA2 gene have risks for breast and ovarian cancer that are so high and seem so selective that many mutation carriers choose to have prophylactic surgery. There has been much conjecture to explain such apparently striking tissue specificity. All these suggestions share the assumption that some disabled function of normal tumor suppressor genes leads to a tissue specific cancer response. Here the idea is proposed and tested that major determinants of where BRCA1/2 hereditary cancers occur are related to tissue specificity of the cancer pathogen, the agent that causes chronic inflammation or the carcinogen. The target tissue may have receptors for the pathogen, become selectively exposed to an inflammatory process or to a carcinogen such as during digestion, metabolism or elimination. An innate genomic deficit in a tumor suppressor gene impairs normal responses to these extrinsic challenges and exacerbates the susceptibility to disease in organ targets. This hypothesis also fits data for several tumor suppressors beyond BRCA1/2. A major advantage of this model is that it suggests there may be some options in addition to prophylactic surgery

Single-shot 3D coherent diffractive imaging of core-shell nanoparticles with elemental specificity.

We report 3D coherent diffractive imaging (CDI) of Au/Pd core-shell nanoparticles with 6.1 nm spatial resolution with elemental specificity. We measured single-shot diffraction patterns of the nanoparticles using intense x-ray free electron laser pulses. By exploiting the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from these diffraction patterns. To extract 3D structural information beyond the diffraction signal, we implemented a super-resolution technique by taking advantage of CDI's quantitative reconstruction capabilities. We used high-resolution model fitting to determine the Au core size and the Pd shell thickness to be 65.0 ± 1.0 nm and 4.0 ± 0.5 nm, respectively. We also identified the 3D elemental distribution inside the nanoparticles with an accuracy of 3%. To further examine the model fitting procedure, we simulated noisy diffraction patterns from a Au/Pd core-shell model and a solid Au model and confirmed the validity of the method. We anticipate this super-resolution CDI method can be generally used for quantitative 3D imaging of symmetrical nanostructures with elemental specificity

Computational studies of biomembrane systems: Theoretical considerations, simulation models, and applications

This chapter summarizes several approaches combining theory, simulation and experiment that aim for a better understanding of phenomena in lipid bilayers and membrane protein systems, covering topics such as lipid rafts, membrane mediated interactions, attraction between transmembrane proteins, and aggregation in biomembranes leading to large superstructures such as the light harvesting complex of green plants. After a general overview of theoretical considerations and continuum theory of lipid membranes we introduce different options for simulations of biomembrane systems, addressing questions such as: What can be learned from generic models? When is it expedient to go beyond them? And what are the merits and challenges for systematic coarse graining and quasi-atomistic coarse grained models that ensure a certain chemical specificity

Assessing somatization in urologic chronic pelvic pain syndrome

BACKGROUND: This study examined the prevalence of somatization disorder in Urological Chronic Pelvic Pain Syndrome (UCPPS) and the utility of two self-report symptom screening tools for assessment of somatization in patients with UCPPS. METHODS: The study sample included 65 patients with UCPPS who enrolled in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Study at Washington University. Patients completed the PolySymptomatic PolySyndromic Questionnaire (PSPS-Q) (n = 64) and the Patient Health Questionnaire-15 Somatic Symptom Severity Scale (PHQ-15) (n = 50). Review of patient medical records found that only 47% (n = 30) contained sufficient documentation to assess Perley-Guze criteria for somatization disorder. RESULTS: Few (only 6.5%) of the UCPPS sample met Perley-Guze criteria for definite somatization disorder. Perley-Guze somatization disorder was predicted by definite PSPS-Q somatization with at least 75% sensitivity and specificity. Perley-Guze somatization disorder was predicted by severe (\u3e 15) PHQ-15 threshold that had \u3e 90% sensitivity and specificity but was met by only 16% of patients. The moderate (\u3e 10) PHQ-15 threshold had higher sensitivity (100%) but lower specificity (52%) and was met by 52% of the sample. CONCLUSIONS: The PHQ-15 is brief, but it measures symptoms constituting only one dimension of somatization. The PSPS-Q uniquely captures two conceptual dimensions inherent in the definition of somatization disorder, both number of symptoms and symptom distribution across multiple organ systems, with relevance for UCPPS as a syndrome that is not just a collection of urological symptoms but a broader syndrome with symptoms extending beyond the urological system