Child bed net use before, during, and after a bed net distribution campaign in Bo, Sierra Leone

Background: This analysis examined how the proportion of children less than 5-years-old who slept under a bed net the previous night changed during and after a national long-lasting insecticidal net (LLIN) distribution campaign in Sierra Leone in November–December 2010. Methods: A citywide cross-sectional study in 2010–2011 interviewed the caregivers of more than 3000 under-five children from across urban Bo, Sierra Leone. Chi squared tests were used to assess change in use rates over time, and multivariate regression models were used to examine the factors associated with bed net use. Results: Reported rates of last-night bed net use changed from 38.7 % (504/1304) in the months before the LLIN campaign to 21.8 % (78/357) during the week of the campaign to 75.3 % (1045/1387) in the months after the national campaign. The bed net use rate significantly increased (p \u3c 0.01) from before the campaign to after the universal LLIN distribution campaign in all demographic, socioeconomic, and health behaviour groups, even though reported use during the campaign dropped significantly. Conclusion: Future malaria prevention efforts will need to promote consistent use of LLINs and address any remain- ing disparities in insecticide-treated bed net (ITN) use

Enabling methods for community health mapping in developing countries

<p>Abstract</p> <p>Background</p> <p>Spatial epidemiology is useful but difficult to apply in developing countries due to the low availability of digitized maps and address systems, accurate population distributions, and computational tools. A community-based mapping approach was used to demonstrate that participatory geographic information system (PGIS) techniques can provide information helpful for health and community development.</p> <p>Results</p> <p>The PGIS process allowed for the rapid determination of sectional (neighborhood) boundaries within the city of Bo, Sierra Leone. When combined with data about hospital laboratory visits, a catchment area for one hospital in Bo could be established. A survey of households from within the catchment area determined that the average population per household (about 6 individuals) was similar to that found in the 2004 census. However, we also found that the average house was inhabited by more than one household, for an average of 17.5 inhabitants per residential building, which is critical information to know when estimating population size using remote imagery that can detect and enumerate buildings.</p> <p>Conclusions</p> <p>The methods developed in this paper serve as a model for the involvement of communities in the generation of municipal maps and their application to community and health concerns.</p

Using the Systemic Immune-Inflammation Index (SII) as a mid-treatment marker for survival among patients with stage-III locally advanced non-small cell lung cancer (NSCLC)

The Systemic Immune-Inflammation Index (SII) is an important marker of immune function, defined as the product of neutrophil-to-lymphocyte ratio (NLR) and platelet count (P). Higher baseline SII levels have been associated with improved survival in various types of cancers, including lung cancer. Data were obtained from PROCLAIM, a randomized phase III trial comparing two different chemotherapy regimens pemetrexed + cisplatin (PEM) vs. etoposide + cisplatin (ETO), in combination with radiotherapy (RT) for the treatment of stage III non-squamous non-small cell lung cancer (NSCLC). We aimed to determine if SII measured at the mid-treatment window for RT (weeks 3-4) is a significant predictor of survival, and if the effect of PEM vs. ETO differs by quartile (Q) level of SII. Hazard-ratios (HR) for survival were estimated using a proportional hazards model, accounting for the underlying correlated structure of the data. A total of 548 patients were included in our analysis. The median age at baseline was 59 years. Patients were followed for a median of 24 months. Adjusting for age, body mass index, sex, race, and chemotherapy regimen, SII was a significant mid-treatment predictor of both overall (adjusted HR (aHR) = 1.6

Pretreatment neutrophil-to-lymphocyte ratio as an important prognostic marker in stage III locally advanced non-small cell lung cancer: Confirmatory results from the PROCLAIM phase III clinical trial

Background: Neutrophil-to-lymphocyte ratio (NLR) is an important pretreatment marker of systemic inflammation and tumor aggressiveness. Increased levels of this ratio have been associated with reduced survival in several observational studies of lung cancer. However, supporting analyses from large clinical trial data are lacking. Methods: To validate the prognostic role of NLR, the current study evaluated data from a randomized phase III study (PROCLAIM; clinicaltrial.gov ID: NCT00686959) of patients with stage IIIA/B, unresectable, non-squamous, non-small cell lung cancer (NSCLC), originally comparing combination pemetrexed-cisplatin chemoradiotherapy with etoposide-cisplatin chemoradiotherapy. Adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for survival were estimated using a Cox proportional hazards model. Models were adjusted for age, race, sex, stage, treatment, and body mass index (BMI). Patients were followed for a median of 24 months. Results: Increased NLR levels at baseline were associated with reduced overall ( Conclusions: These findings provide substantiating evidence that NLR, which is routinely available from standard blood testing of patients diagnosed with NSCLC, is an important inflammation-based prognostic marker for survival among patients with locally advanced disease undergoing chemoradiation. Future research will benefit by assessing the prognostic potential of NLR in the context of genetic mutations and molecular markers

Immunoprevention of Basal Cell Carcinomas with Recombinant Hedgehog-interacting Protein

Basal cell carcinomas (BCCs) are driven by abnormal hedgehog signaling and highly overexpress several hedgehog target genes. We report here our use of one of these target genes, hedgehog-interacting protein (Hip1), as a tumor-associated antigen for immunoprevention of BCCs in Ptch1+/− mice treated with ionizing radiation. Hip1 mRNA is expressed in adult mouse tissues at levels considerably lower than those in BCCs. Immunization with either of two large recombinant Hip1 polypeptides was well tolerated in Ptch1+/− mice, induced B and T cell responses detectable by enzyme-linked immunosorbent assay, Western blot, delayed type hypersensitivity, and enzyme-linked immunospot assay, and reduced the number of BCCs by 42% (P < 0.001) and 32% (P < 0.01), respectively. We conclude that immunization with proteins specifically up-regulated by hedgehog signaling may hold promise as a preventive option for patients such as those with the basal cell nevus syndrome who are destined to develop large numbers of BCCs

Crossing Boundaries: Tapestry Within the Context of the 21st Century

International audienceGraphical model processing is a central problem in artificial intelligence. The optimization of the combined cost of a network of local cost functions federates a variety of famous problems including CSP, SAT and Max-SAT but also optimization in stochastic variants such as Markov Random Fields and Bayesian networks. Exact solving methods for these problems typically include branch and bound and local inference-based bounds.In this paper we are interested in understanding when and how dynamic programming based optimization can be used to efficiently enforce soft local consistencies on Global Cost Functions, defined as parameterized families of cost functions of unbounded arity. Enforcing local consistencies in cost function networks is performed by applying so-called Equivalence Preserving Transformations (EPTs) to the cost functions. These EPTs may transform global cost functions and make them intractable to optimize.We identify as tractable projection-safe those global cost functions whose optimization is and remains tractable after applying the EPTs used for enforcing arc consistency. We also provide new classes of cost functions that are tractable projection-safe thanks to dynamic programming.We show that dynamic programming can either be directly used inside filtering algorithms, defining polynomially DAG-filterable cost functions, or emulated by arc consistency filtering on a Berge-acyclic network of bounded-arity cost functions, defining Berge-acyclic network-decomposable cost functions. We give examples of such cost functions and we provide a systematic way to define decompositions from existing decomposable global constraints.These two approaches to enforcing consistency in global cost functions are then embedded in a solver for extensive experiments that confirm the feasibility and efficiency of our proposal

Control of Stereoselectivity in Diverse Hapalindole Metabolites is Mediated by Cofactor‐Induced Combinatorial Pairing of Stig Cyclases

Stereospecific polycyclic core formation of hapalindoles and fischerindoles is controlled by Stig cyclases through a three‐step cascade involving Cope rearrangement, 6‐exo‐trig cyclization, and a final electrophilic aromatic substitution. Reported here is a comprehensive study of all currently annotated Stig cyclases, revealing that these proteins can assemble into heteromeric complexes, induced by Ca2+, to cooperatively control the stereochemistry of hapalindole natural products.Die stereospezifische Bildung des polycyclischen Kerns der Hapalindole und Fischerindole wird durch Stig‐Cyclasen gesteuert, die eine dreistufige Kaskade aus Cope‐Umlagerung, 6‐exo‐trig‐Cyclisierung und elektrophiler aromatischer Substitution vermitteln. Die Proteine können sich induziert durch Ca2+ zu heterotrimeren Komplexen zusammenlagern, um auf kooperative Weise die Stereochemie zu steuern.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155506/1/ange201913686.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155506/2/ange201913686-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155506/3/ange201913686_am.pd

Regional scale cropland carbon budgets: Evaluating a geospatial agricultural modeling system using inventory data

Accurate quantification and clear understanding of regional scale cropland carbon (C) cycling is critical for designing effective policies and management practices that can contribute toward stabilizing atmospheric CO2 concentrations. However, extrapolating site-scale observations to regional scales represents a major challenge confronting the agricultural modeling community. This study introduces a novel geospatial agricultural modeling system (GAMS) exploring the integration of the mechanistic Environmental Policy Integrated Climate model, spatially-resolved data, surveyed management data, and supercomputing functions for cropland C budgets estimates. This modeling system creates spatiallyexplicit modeling units at a spatial resolution consistent with remotely-sensed crop identification and assigns cropping systems to each of them by geo-referencing surveyed crop management information at the county or state level. A parallel computing algorithm was also developed to facilitate the computationally intensive model runs and output post-processing and visualization. We evaluated GAMS against National Agricultural Statistics Service (NASS) reported crop yields and inventory estimated county-scale cropland C budgets averaged over 2000e2008. We observed good overall agreement, with spatial correlation of 0.89, 0.90, 0.41, and 0.87, for crop yields, Net Primary Production (NPP), Soil Organic C (SOC) change, and Net Ecosystem Exchange (NEE), respectively. However, we also detected notable differences in the magnitude of NPP and NEE, as well as in the spatial pattern of SOC change. By performing crop-specific annual comparisons, we discuss possible explanations for the discrepancies between GAMS and the inventory method, such as data requirements, representation of agroecosystem processes, completeness and accuracy of crop management data, and accuracy of crop area representation. Based on these analyses, we further discuss strategies to improve GAMS by updating input data and by designing more efficient parallel computing capability to quantitatively assess errors associated with the simulation of C budget components. The modularized design of the GAMS makes it flexible to be updated and adapted for different agricultural models so long as they require similar input data, and to be linked with socio-economic models to understand the effectiveness and implications of diverse C management practices and policies

A Tandem Mass Spectrometry Sequence Database Search Method for Identification of O-Fucosylated Proteins by Mass Spectrometry.

Thrombospondin type 1 repeats (TSRs), small adhesive protein domains with a wide range of functions, are usually modified with O-linked fucose, which may be extended to O-fucose-β1,3-glucose. Collision-induced dissociation (CID) spectra of O-fucosylated peptides cannot be sequenced by standard tandem mass spectrometry (MS/MS) sequence database search engines because O-linked glycans are highly labile in the gas phase and are effectively absent from the CID peptide fragment spectra, resulting in a large mass error. Electron transfer dissociation (ETD) preserves O-linked glycans on peptide fragments, but only a subset of tryptic peptides with low m/ z can be reliably sequenced from ETD spectra compared to CID. Accordingly, studies to date that have used MS to identify O-fucosylated TSRs have required manual interpretation of CID mass spectra even when ETD was also employed. In order to facilitate high-throughput, automatic identification of O-fucosylated peptides from CID spectra, we re-engineered the MS/MS sequence database search engine Comet and the MS data analysis suite Trans-Proteomic Pipeline to enable automated sequencing of peptides exhibiting the neutral losses characteristic of labile O-linked glycans. We used our approach to reanalyze published proteomics data from Plasmodium parasites and identified multiple glycoforms of TSR-containing proteins