Development of spatial statistical methods for modelling point-referenced spatial data in malaria epidemiology

Plasmodium falciparum malaria is the world’s most important parasitic disease and a major cause of morbidity and mortality in Africa. However figures for the burden of malaria morbidity and mortality are very uncertain, since reliable maps of the distribution of malaria transmission and the numbers of affected individuals are not available for most of the African continent. Accurate statistics on the geographical distribution of different endemicities of malaria, on the populations at risk, and on the implications of given levels of endemicity for morbidity and mortality are important for effective malaria control programs. These estimates can be obtained using appropriate statistical models which relate infection, morbidity, and mortality rates to risk factors, measured at individual level, but also to factors that vary gradually over geographical locations. Statistical models which incorporate geographical or individual heterogeneity are complex and highly parameterized. Limitations in statistical computation have until recently made the implementation of these models impractical for non-normal response data, sampled at large numbers of geographical locations. Modern developments in Markov chain Monte Carlo (MCMC) inference have greatly advanced spatial modelling, however many methodological and theoretical problems still remain. For data collected over a fixed number of locations (point-referenced or geostatistical data) such as malaria morbidity and mortality data used in this study, spatial correlation is best specified by parameterizing the variance-covariance matrix of the outcome of interest in relation to the spatial configuration of the locations (variogram modelling). This has been considered infeasible for a large number of locations because of the repeated inversion of the variance-covariance matrix involved in the likelihood. In addition the spatial correlation in malariological data could be dependent not only on the distance between locations but on the locations themselves. Variogram models need to be further developed to take into account the above property which is known as non-stationarity. This thesis reports research with the objectives of: a) developing Bayesian hierarchical models for the analysis of point-referenced malaria prevalence, malaria transmission and mortality data via variogram modelling for a large number of locations taking into account non-stationarity and misalignment, while present in the data; b) producing country specific and continent-wide maps of malaria transmission and malaria prevalence in Africa, augmented by the use of climatic and environmental data; c) assessing the magnitude of the effects of malaria endemicity on infant and child mortality after adjusting of socio-economic factors and geographical patterns. A comparison of the MCMC and the Sampling-Importance-Resampling approach for Bayesian fitting of variogram models showed that the latter was no easier to implement, did not improve estimation accuracy and did not lead to computationally more efficient estimation. Different approaches were proposed to overcome the inversion of large covariance matrices. Numerical algorithms especially suited within the MCMC framework were implemented to convert large covariance matrices to sparse ones and to accelerate inversion. A tesselation-based model was developed which partition the space into random Voronoi tiles. The model assumes a separate spatial process in each tile and independence between tiles. Model fit was implemented via reversible jump MCMC which takes into account the varying number of parameters arised due to random number of tiles. This approach facilitates inversion by converting the covariance matrix to block diagonal form. In addition, this model is well suited for non-stationary data. An accelerated failure time model was developed for spatially misaligned data to assess malaria endemicity in relation to child mortality. The misalignment arised because the data were extracted from databases which were collected at a different set of locations. The newly developed statistical methodology was implemented to produce smooth maps of malaria transmission in Mali and West- and Central Africa, using malaria survey data from the Mapping Malaria Risk in Africa (MARA) database. The surveys were carried out at arbitrary locations and include non-standardized and overlapping age groups. To achieve comparability between different surveys, the Garki transmission model was applied to convert the heterogeneous age prevalence data to a common scale of a transmission intensity measure. A Bayesian variogram model was fitted to the transmission intensity estimates. The model adjusted for environmental predictors which were extracted from remote sensing. Bayesian kriging was used to obtain smooth maps of the transmission intensity, which were converted to age-specific maps of malaria risk. TheWest- and Central African map was based on a seasonality model we developed for the whole of Africa. Expert opinion suggests that the resulting maps improve previous mapping efforts. Additional surveys are needed to increase the precision of the predictions in zones were there are large disagreement with previous maps and data are sparse. The survival model for misaligned data was implemented to produce a smooth mortality map in Mali and assess the relation between malaria endemicity and child and infant mortality by linking the MARA database with the Demographic and Health Survey (DHS) database. The model was adjusted for socio-economic factors and spatial dependence. The analysis confirmed that mothers education, birth order and preceding birth interval, sex of infant, residence and mothers age at birth have a strong impact on infant and child mortality risk, but no statistically significant effect of P. falciparum prevalence could be demonstrated. This may reflect unmeasured local factors, for instance variations in health provisions or availability of water supply in the dry Sahel region, which could have a stronger influence than malaria risk on mortality patterns

Fitting Generalized Linear Mixed Models For Point-Referenced Spatial Data

Non-Gaussian point-referenced spatial data are frequently modeled using generalized linear mixed models (GLMM) with location-specific random effects. Spatial dependence can be introduced in the covariance matrix of the random effects. Maximum likelihood-based or Bayesian estimation implemented via Markov chain Monte Carlo (MCMC) for such models is computationally demanding especially for large sample sizes because of the large number of random effects and the inversion of the covariance matrix involved in the likelihood. We review three fitting procedures, the Penalized Quasi Likelihood method, the MCMC, and the Sampling-Importance-Resampling method. They are assessed in terms of estimation accuracy, ease of implementation, and computational efficiency using a spatially structured dataset on infant mortality from Mali

Malaria Mapping Using Transmission Models: Application to Survey Data from Mali

Geographic mapping of the distribution of malaria is complicated by the limitations of the available data. The most widely available data are from prevalence surveys, but these surveys are generally carried out at arbitrary locations and include nonstandardized and overlapping age groups. To achieve comparability between different surveys, the authors propose the use of transmission models, particularly the Garki model, to convert heterogeneous age prevalence data to a common scale of estimated entomological inoculation rates, vectorial capacity, or force of infection. They apply this approach to the analysis of survey data from Mali, collected in 1965-1998, extracted from the Mapping Malaria Risk in Africa database. They use Bayesian geostatistical models to produce smooth maps of estimates of the entomological inoculation rates obtained from the Garki model, allowing for the effect of environmental covariates. Again using the Garki model, they convert kriged entomological inoculation rates values to age-specific malaria prevalence. The approach makes more efficient use of the available data than do previous malaria mapping methods, and it produces highly plausible maps of malaria distributio

The effect of botulinum toxin type A injection in the viability of dorsal flap in rats

Purpose: Botulinum toxin A (BoNTA) increased the viability of skin flap in healthy rats. Most of the studies injected this substance some days (7-15) before the flap surgery. This treatment is used only for elective surgery, there was no data about the efficacy of BontA when injected in the surgical period. This study aimed to analyze the effect of BontA on the viability of Random flap in a intra surgical injection. Methods: Twenty male Wistar rats (250–300 g) were randomly divided into four groups: saline injection 15 days prior the surgery (G1), BoNTA injection 15 days prior the surgery (G2), saline injection intraoperative period (G3), BoNTA injection intraoperative (G4). A dorsal cutaneous flap (3×10cm) was performed. Survival area and total area of the flaps were measured. Lumen diameter, external arterial diameter and lumen/wall thickness ratio were recorded. Results: Viable area increased in Bonta 15days group when compared to saline-15days (1080.7 ± 307.5 mm2 vs. 1594.5 ± 419.7mm2, p= 0.01) and in the Bonta –intraoperative injection when compared to saline intraoperative injection (1133.3 ± 462.0 mm2 vs. 1389.9 ± 320.4 mm2, p=0.014). The ratio viable area/total area showed similar results (G1 versus G2, 0.43 vs. 0.74; p<0.001, respectively) and G3 versus G4 (0.44 vs. 0.61 p= 0,04). We did not find any difference in the microscopic analysis (lumen diameter, external arterial diameter and lumen/wall thickness ratio). Conclusion: BoNTA injected fifteen days before the surgery increased skin flap viability. However, BontA injected intraoperatory time did not increased the flap viability

Amelogenin Peptide Extract Increases Differentiation and Angiogenic and Local Factor Production and Inhibits Apoptosis in Human Osteoblasts

Enamel matrix derivative (EMD), a decellularized porcine extracellular matrix (ECM), is used clinically in periodontal tissue regeneration. Amelogenin, EMD’s principal component, spontaneously assembles into nanospheres in vivo, forming an ECM complex that releases proteolytically cleaved peptides. However, the role of amelogenin or amelogenin peptides in mediating osteoblast response to EMD is not clear. Human MG63 osteoblast-like cells or normal human osteoblasts were treated with recombinant human amelogenin or a 5 kDa tyrosine-rich amelogenin peptide (TRAP) isolated from EMD and the effect on osteogenesis, local factor production, and apoptosis assessed. Treated MG63 cells increased alkaline phosphatase specific activity and levels of osteocalcin, osteoprotegerin, prostaglandin E2, and active/latent TGF-β1, an effect sensitive to the effector and concentration. Primary osteoblasts exhibited similar, but less robust, effects. TRAP-rich 5 kDa peptides yielded more mineralization than rhAmelogenin in osteoblasts in vitro. Both amelogenin and 5 kDa peptides protected MG63s from chelerythrine-induced apoptosis. The data suggest that the 5 kDa TRAP-rich sequence is an active amelogenin peptide that regulates osteoblast differentiation and local factor production and prevents osteoblast apoptosis

Isolation, Purification, and Genomic Analysis of the Novel Bacteriophage Kradal

From the Washington University Office of Undergraduate Research Digest (WUURD), Vol. 13, 05-01-2018. Published by the Office of Undergraduate Research. Joy Zalis Kiefer, Director of Undergraduate Research and Associate Dean in the College of Arts & Sciences; Lindsey Paunovich, Editor; Helen Human, Programs Manager and Assistant Dean in the College of Arts and Sciences Mentor(s): Chris Schaffe

Transport of Na+ and K+ by an antiporter-related subunit from the Escherichia coli NADH dehydrogenase I produced in Saccharomyces cerevisiae

The NADH dehydrogenase I from Escherichia coli is a bacterial homolog of the mitochondrial complex I which translocates Na+ rather than H+. To elucidate the mechanism of Na+ transport, the C-terminally truncated NuoL subunit (NuoLN) which is related to Na+/H+ antiporters was expressed as a protein A fusion protein (ProtA-NuoLN) in the yeast Saccharomyces cerevisiae which lacks an endogenous complex I. The fusion protein inserted into membranes from the endoplasmatic reticulum (ER), as confirmed by differential centrifugation and Western analysis. Membrane vesicles containing ProtA-NuoLN catalyzed the uptake of Na+ and K+ at rates which were significantly higher than uptake by the control vesicles under identical conditions, demonstrating that ProtA-NuoLN translocated Na+ and K+ independently from other complex I subunits. Na+ transport by ProtA-NuoLN was inhibited by EIPA (5-(N-ethyl-N-isopropyl)-amiloride) which specifically reacts with Na+/H+ antiporters. The cation selectivity and function of the NuoL subunit as a transporter module of the NADH dehydrogenase complex is discusse

Negative hybrid capture in a single intraepithelial corneal dysplasia

As displasias intraepiteliais de córnea correspondem a lesões de baixo risco de malignidade, dentro do espectro das neoplasias intraepiteliais da superfície ocular. Essas displasias se apresentam como áreas leucoplásicas e têm como um dos principais fatores de risco o papilomavírus humano (HPV). No presente trabalho, os autores descrevem um caso de displasia intraepitelial isolada de córnea, tratada através de excisão cirúrgica, com confirmação histológica e resultado negativo de hibridização de DNA para HPV.Cornea intraepithelial dysplasias are lesions with low risk of malignancy within the spectrum of intraepithelial neoplasia of the ocular surface. These areas are presented as dysplasias or leukoplasias and are associated with the presence of human papillomavirus (HPV), a major risk factor. In this report, the authors describe a case of a corneal intraepithelial dysplasia treated by surgical excision, with histological confirmation and negative DNA hybridization for HPV

Learning methodology in surgical training

This manuscript aimed to review the literature data related to the surgical training program. This review showed some of the requirements to perform effective surgical training were direct supervision, predetermined repetitions according to surgical skill complexity, valid simulator models, number of students per model. This manuscript discussed how the surgical program could achieve competence using a critical thinking framework, integrated curriculum based on the rationale behind simulation training program.Esse manuscrito tem como objetivo revisar dados da literatura relacionados ao treinamento cirúrgico para  alunos de graduação me medicina.  Essa revisão demostrou que  alguns  pré requesitos são necessários para se realizar treinamento cirúrgico de maneira eficaz: supervisão direta, repetições  pré-determinadas de acordo com a complexidade  da atividade a ser ensinada, modelos de simuladores válidos, número de alunos por modelo. Esse manuscrito também  discutiu como o programa cirúrgico pode levar a competência  pelo desenvolvimento do pensamento crítico e pela integração curricular baseado no racional da  utilização de um programa de treinamento por  simuladores