Effect of two different house screening interventions on exposure to malaria vectors and on anaemia in children in The Gambia: a randomised controlled trial

Background: House screening should protect people against malaria. We assessed whether two types of house screening—full screening of windows, doors, and closing eaves, or installation of screened ceilings—could reduce house entry of malaria vectors and frequency of anaemia in children in an area of seasonal malaria transmission. Methods: During 2006 and 2007, 500 occupied houses in and near Farafenni town in The Gambia, an area with low use of insecticide-treated bednets, were randomly assigned to receive full screening, screened ceilings, or no screening (control). Randomisation was done by computer-generated list, in permuted blocks of five houses in the ratio 2:2:1. Screening was not treated with insecticide. Exposure to mosquitoes indoors was assessed by fortnightly light trap collections during the transmission season. Primary endpoints included the number of female Anopheles gambiae sensu lato mosquitoes collected per trap per night. Secondary endpoints included frequency of anaemia (haemoglobin concentration <80 g/L) and parasitaemia at the end of the transmission season in children (aged 6 months to 10 years) who were living in the study houses. Analysis was by modified intention to treat (ITT), including all randomised houses for which there were some outcome data and all children from those houses who were sampled for haemoglobin and parasitaemia. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN51184253. Findings: 462 houses were included in the modified ITT analysis (full screening, n=188; screened ceilings, n=178; control, n=96). The mean number of A gambiae caught in houses without screening was 37·5 per trap per night (95% CI 31·6–43·3), compared with 15·2 (12·9–17·4) in houses with full screening (ratio of means 0·41, 95% CI 0·31–0·54; p<0·0001) and 19·1 (16·1–22·1) in houses with screened ceilings (ratio 0·53, 0·40–0·70; p<0·0001). 755 children completed the study, of whom 731 had complete clinical and covariate data and were used in the analysis of clinical outcomes. 30 (19%) of 158 children from control houses had anaemia, compared with 38 (12%) of 309 from houses with full screening (adjusted odds ratio [OR] 0·53, 95% CI 0·29–0·97; p=0·04), and 31 (12%) of 264 from houses with screened ceilings (OR 0·51, 0·27–0·96; p=0·04). Frequency of parasitaemia did not differ between intervention and control groups. Interpretation: House screening substantially reduced the number of mosquitoes inside houses and could contribute to prevention of anaemia in children

Mutations of the BRAF gene in human cancer

Cancers arise owing to the accumulation of mutations in critical genes that alter normal programmes of cell proliferation, differentiation and death. As the first stage of a systematic genome-wide screen for these genes, we have prioritized for analysis signalling pathways in which at least one gene is mutated in human cancer. The RAS RAF MEK ERK MAP kinase pathway mediates cellular responses to growth signals. RAS is mutated to an oncogenic form in about 15% of human cancer. The three RAF genes code for cytoplasmic serine/threonine kinases that are regulated by binding RAS. Here we report BRAF somatic missense mutations in 66% of malignant melanomas and at lower frequency in a wide range of human cancers. All mutations are within the kinase domain, with a single substitution (V599E) accounting for 80%. Mutated BRAF proteins have elevated kinase activity and are transforming in NIH3T3 cells. Furthermore, RAS function is not required for the growth of cancer cell lines with the V599E mutation. As BRAF is a serine/threonine kinase that is commonly activated by somatic point mutation in human cancer, it may provide new therapeutic opportunities in malignant melanoma

Structural and Biochemical Evaluation of the Interaction of the Phosphatidylinositol 3-Kinase p85a Src Homology 2 Domains with Phosphoinositides and Inositol Polyphosphates

Macromolecular Biochemistr

What's the catch? Archaeological application of rapid collagen-based species identification for Pacific Salmon

YesPacific salmon (Oncorhynchus spp.) are ecological and cultural keystone species along the Northwest Coast of North America and are ubiquitous in archaeological sites of the region. The inability to morphologically identify salmonid post-cranial remains to species, however, can limit our understanding of the ecological and cultural role different taxa played in the seasonal subsistence practices of Indigenous groups in the past. Here, we present a rapid, cost-effective ZooMS method to distinguish salmonid species based on collagen peptide mass-fingerprinting. Using modern reference material and an assemblage of 28 DNA-identified salmonid bones from the pre-contact Yup'ik site of Nunalleq, Western Alaska, we apply high-resolution mass spectrometry (LC-MS/MS) to identify a series of potential collagen peptide markers to distinguish Pacific salmon. We then confirm these peptide markers with a blind ZooMS analysis (MALDI-TOF-MS) of the archaeological remains. We successfully distinguish five species of anadromous salmon with this ZooMS approach, including one specimen that could not be identified through ancient DNA analysis. Our biomolecular identification of chum (43%), sockeye (21%), chinook (18%), coho (11%) and pink (7%), confirm the exploitation of all five available species of salmonid at Nunalleq

Structural and biochemical characterization of the wild type PCSK9-EGF(AB) complex and natural familial hypercholesterolemia mutants

PCSK9 regulates low density lipoprotein receptor (LDLR) levels and consequently is a target for the prevention of atherosclerosis and coronary heart disease. Here we studied the interaction, of LDLR EGF(A/AB) repeats with PCSK9. We show that PCSK9 binds the EGF(AB) repeats in a pH-dependent manner. Although the PCSK9 C-terminal domain is not involved in LDLR binding, PCSK9 autocleavage is required. Moreover, we report the x-ray structure of the PCSK9 Delta C-EGF(AB) complex at neutral pH. Compared with the low pH PCSK9-EGF(A) structure, the new structure revealed rearrangement of the EGF( A) His-306 side chain and disruption of the salt bridge with PCSK9 Asp-374, thus suggesting the basis for enhanced interaction at low pH. In addition, the structure of PCSK9 Delta C bound to EGF(AB)(H306Y), a mutant associated with familial hypercholesterolemia (FH), reveals that the Tyr-306 side chain forms a hydrogen bond with PCSK9 Asp-374, thus mimicking His-306 in the low pH conformation. Consistently, Tyr-306 confers increased affinity for PCSK9. Importantly, we found that although the EGF(AB)(H306Y)-PCSK9 interaction is pH-independent, LDLRH306Y binds PCSK9 50-fold better at low pH, suggesting that factors other than His-306 contribute to the pH dependence of PCSK9-LDLR binding. Further, we determined the structures of EGF(AB) bound to PCSK9 Delta C containing the FH-associated D374Y and D374H mutations, revealing additional interactions with EGF(A) mediated by Tyr-374/His-374 and providing a rationale for their disease phenotypes. Finally, we report the inhibitory properties of EGF repeats in a cellular assay measuring LDL uptake

Establishing anchor-based minimally important differences for the EORTC QLQ-C30 in glioma patients

Background. Minimally important differences (MIDs) allow interpretation of the clinical relevance of health-related quality of life (HRQOL) results. This study aimed to estimate MIDs for all European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) scales for interpreting group-level results in brain tumor patients.Methods. Clinical and HRQOL data from three glioma trials were used. Clinical anchors were selected for each EORTC QLQ-C30 scale, based on correlation (>0.30) and clinical plausibility of association. Changes in both HRQOL and the anchors were calculated, and for each scale and time period, patients were categorized into one of the three clinical change groups: deteriorated by one anchor category, no change, or improved by one anchor category. Mean change method and linear regression were applied to estimate MIDs for interpreting within-group change and between-group differences in change over time, respectively. Distribution-based methods were applied to generate supportive evidence.Results. A total of 1687 patients were enrolled in the three trials. The retained anchors were performance status and eight Common Terminology Criteria for Adverse Events (CTCAE) scales. MIDs for interpreting within-group change ranged from 4 to 12 points for improvement and -4 to -14 points for deterioration. MIDs for between-group difference in change ranged from 4 to 9 for improvement and -4 to -16 for deterioration. Most anchor-based MIDs were closest to the 0.3 SD distribution-based estimates (range: 3-10).Conclusions. MIDs for the EORTC QLQ-C30 scales generally ranged between 4 and 11 points for both within-group mean change and between-group mean difference in change. These results can be used to interpret QLQ-C30 results from glioma trials.Neurolog

Establishing anchor-based minimally important differences for the EORTC QLQ-C30 in glioma patients

Background: Minimally important differences (MIDs) allow interpretation of the clinical relevance of health-related quality of life (HRQOL) results. This study aimed to estimate MIDs for all European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) scales for interpreting group-level results in brain tumor patients. Methods: Clinical and HRQOL data from three glioma trials were used. Clinical anchors were selected for each EORTC QLQ-C30 scale, based on correlation (>0.30) and clinical plausibility of association. Changes in both HRQOL and the anchors were calculated, and for each scale and time period, patients were categorized into one of the three clinical change groups: deteriorated by one anchor category, no change, or improved by one anchor category. Mean change method and linear regression were applied to estimate MIDs for interpreting within-group change and between-group differences in change over time, respectively. Distribution-based methods were applied to generate supportive evidence. Results: A total of 1687 patients were enrolled in the three trials. The retained anchors were performance status and eight Common Terminology Criteria for Adverse Events (CTCAE) scales. MIDs for interpreting within-group change ranged from 4 to 12 points for improvement and −4 to −14 points for deterioration. MIDs for between-group difference in change ranged from 4 to 9 for improvement and −4 to −16 for deterioration. Most anchor-based MIDs were closest to the 0.3 SD distribution-based estimates (range: 3-10). Conclusions: MIDs for the EORTC QLQ-C30 scales generally ranged between 4 and 11 points for both within-group mean change and between-group mean difference in change. These results can be used to interpret QLQ-C30 results from glioma trials

Biophysical studies of intracelluar signal transduction proteins Investigating the structure-function relationship

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN026420 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Can the buck always be passed to the highest level of clustering?

Background: Clustering commonly affects the uncertainty of parameter estimates in epidemiological studies. Cluster-robust variance estimates (CRVE) are used to construct confidence intervals that account for single-level clustering, and are easily implemented in standard software. When data are clustered at more than one level (e.g. village and household) the level for the CRVE must be chosen. CRVE are consistent when used at the higher level of clustering (village), but since there are fewer clusters at the higher level, and consistency is an asymptotic property, there may be circumstances under which coverage is better from lower- rather than higher-level CRVE. Here we assess the relative importance of adjusting for clustering at the higher and lower level in a logistic regression model. Methods: We performed a simulation study in which the coverage of 95 % confidence intervals was compared between adjustments at the higher and lower levels. Results: Confidence intervals adjusted for the higher level of clustering had coverage close to 95 %, even when there were few clusters, provided that the intra-cluster correlation of the predictor was less than 0.5 for models with a single predictor and less than 0.2 for models with multiple predictors. Conclusions: When there are multiple levels of clustering it is generally preferable to use confidence intervals that account for the highest level of clustering. This only fails if there are few clusters at this level and the intra-cluster correlation of the predictor is high