CD36 deficiency leads to choroidal involution via COX2 down-regulation in rodents.

BACKGROUND: In the Western world, a major cause of blindness is age-related macular degeneration (AMD). Recent research in angiogenesis has furthered the understanding of choroidal neovascularization, which occurs in the "wet" form of AMD. In contrast, very little is known about the mechanisms of the predominant, "dry" form of AMD, which is characterized by retinal atrophy and choroidal involution. The aim of this study is to elucidate the possible implication of the scavenger receptor CD36 in retinal degeneration and choroidal involution, the cardinal features of the dry form of AMD. METHODS AND FINDINGS: We here show that deficiency of CD36, which participates in outer segment (OS) phagocytosis by the retinal pigment epithelium (RPE) in vitro, leads to significant progressive age-related photoreceptor degeneration evaluated histologically at different ages in two rodent models of CD36 invalidation in vivo (Spontaneous hypertensive rats (SHR) and CD36-/- mice). Furthermore, these animals developed significant age related choroidal involution reflected in a 100%-300% increase in the avascular area of the choriocapillaries measured on vascular corrosion casts of aged animals. We also show that proangiogenic COX2 expression in RPE is stimulated by CD36 activating antibody and that CD36-deficient RPE cells from SHR rats fail to induce COX2 and subsequent vascular endothelial growth factor (VEGF) expression upon OS or antibody stimulation in vitro. CD36-/- mice express reduced levels of COX2 and VEGF in vivo, and COX2-/- mice develop progressive choroidal degeneration similar to what is seen in CD36 deficiency. CONCLUSIONS: CD36 deficiency leads to choroidal involution via COX2 down-regulation in the RPE. These results show a novel molecular mechanism of choroidal degeneration, a key feature of dry AMD. These findings unveil a pathogenic process, to our knowledge previously undescribed, with important implications for the development of new therapies.

Epidemic models with an infected-infectious period

The introduction of an infective-infectious period on the geographic spread of epidemics is considered in two different models. The classical evolution equations arising in the literature are generalized and the existence of epidemic wave fronts is revised. The asymptotic speed is obtained and improves previous results for the Black Death plague

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Objective: To assess the factorial validity of the Portuguese version of the Maslach Burnout Inventory - Human Services Survey (MBI-HSS). Methods: Between November 2010 and November 2011 a Portuguese version of the MBI-HSS was applied to 151 Portuguese family doctors (55% women, median age 54 years). The factorial structure of the MBI-HSS was examined by principal component analysis (PCA) and confirmatory factor analysis (CFA). Internal consistency estimates of the MBI-HSS were determined with Cronbach's alpha. Results: The fit of the hypothesized three-factor model to the data was superior to the alternative two-factor and four-factor models. CFA supported MBI-HSS as an acceptable measure to evaluate burnout and deletion of items 12 and 16 improved the goodness of fit of the model. In PCA, the three-factor model explained 50.58% of the variance and the four-factor model did not lead to understandable components. Item 12 was also found to be problematic in PCA. The Cronbach's alpha was satisfactory for emotional exhaustion (alpha=0.90), lack of personal accomplishment (alpha=0.73), and depersonalization (alpha=0.64). Conclusion: The Portuguese version of the MBI-HSS was found to be reliable to measure burnout among Portuguese medical doctors. We also recommend the deletion of items 12 and 16 from the MBI-HSS.

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Hierarchical location-allocation models for congested systems

In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and theirlocations that will cover a given region with a distance or time standard. The second model is cast as a Maximal Covering Location formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered.

Regional variations in ABC transporter expression along the mouse intestinal tract.

The ATP-binding cassette (ABC) family of proteins comprise a group of membrane transporters involved in the transport of a wide variety of compounds, such as xenobiotics, vitamins, lipids, amino acids, and carbohydrates. Determining their regional expression patterns along the intestinal tract will further characterize their transport functions in the gut. The mRNA expression levels of murine ABC transporters in the duodenum, jejunum, ileum, and colon were examined using the Affymetrix MuU74v2 GeneChip set. Eight ABC transporters (Abcb2, Abcb3, Abcb9, Abcc3, Abcc6, Abcd1, Abcg5, and Abcg8) displayed significant differential gene expression along the intestinal tract, as determined by two statistical models (a global error assessment model and a classic ANOVA, both with a P < 0.01). Concordance with semiquantitative real-time PCR was high. Analyzing the promoters of the differentially expressed ABC transporters did not identify common transcriptional motifs between family members or with other genes; however, the expression profile for Abcb9 was highly correlated with fibulin-1, and both genes share a common complex promoter model involving the NFkappaB, zinc binding protein factor (ZBPF), GC-box factors SP1/GC (SP1F), and early growth response factor (EGRF) transcription binding motifs. The cellular location of another of the differentially expressed ABC transporters, Abcc3, was examined by immunohistochemistry. Staining revealed that the protein is consistently expressed in the basolateral compartment of enterocytes along the anterior-posterior axis of the intestine. Furthermore, the intensity of the staining pattern is concordant with the expression profile. This agrees with previous findings in which the mRNA, protein, and transport function of Abcc3 were increased in the rat distal intestine. These data reveal regional differences in gene expression profiles along the intestinal tract and demonstrate that a complete understanding of intestinal ABC transporter function can only be achieved by examining the physiologically distinct regions of the gut.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Pattern recognition ecological niche models fit to presence-only and presence-absence data

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.

The role of microRNAs in the development of type 2 diabets

Pancreatic ß cells are highly specialized endocrine cells located within the islets of Langerhans in the pancreas. Their main role is to produce and secrete insulin, the hormone essential for the regulation of glucose homeostasis and body's metabolism. Diabetes mellitus develops when the amount of insulin released by ß cells is not sufficient to cover the metabolic demand. In type 1 diabetes (5-10% of diagnoses) insulin deficiency is caused by the autoimmune destruction of pancreatic ß cells. Type 2 diabetes (90% of diagnoses) results from a genetic predisposition and from the presence of adverse environmental conditions. The combination of these factors reduces insulin sensitivity of peripheral target tissues, causes impairment in ß-cell function and can lead to partial loss of ß cells. The development of novel therapeutic strategies for the treatment of diabetes necessitates the comprehension of the cellular processes involved in dysfunction and loss of ß cells. My thesis was focused on the involvement in the physiopathological processes leading to the development of diabetes of a class of small regulatory RNA molecules, called microRNAs (miRNAs) that post- transcriptionally regulate gene expression. Global miRNA profiling in pancreatic islets of two animal models of diabetes, the db/db mice and mice that were fed a high fat diet (HFD), characterized by obesity and insulin resistance, led us to identify two groups of miRNAs displaying expression changes under pre-diabetic and diabetic conditions. Among the miRNAs already upregulated in pre-diabetic db/db mice and HFD mice, miR- 132 was found to have beneficial effects on pancreatic ß cell function and survival. Indeed, mimicking the upregulation of miR-132 in primary pancreatic islet cells and ß-cell lines improved glucose- induced insulin secretion and favored survival of the cells upon exposure to pro-apoptotic stimuli such as palmitate and cytokines. MiR-132 was found to exert its action by enhancing the expression of MafA, a transcription factor essential for ß-cell function, survival and identity. On the other hand, up-regulation of miR-199a-5p and miR-199a-3p was detectable only in the islets of diabetic db/db mice and resulted in impaired insulin secretion and sensitization of the cells to apoptosis. MiR-199a- 5p was found to decrease insulin secretion by inducing the expression of granuphilin, a potent inhibitor of ß cell exocytosis. In contrast, miR-199a-3p was demonstrated to directly target and reduce the expression of two key ß-cell genes, mTOR and cMET, resulting in impaired ß-cell adaptation to metabolic demands and loss by apoptosis. Our findings suggest that miRNAs are important players in the onset of type 2 diabetes. MiRNA expression is adjusted in pancreatic ß cells exposed to a diabetogenic environment. These changes initially concern miRNAs responsible for adaptive processes aimed at compensating the onset of insulin resistance, but later such changes can be overlapped by modifications in the level of several additional miRNAs that favor ß-cell failure and the onset of type 2 diabetes.

On the problematic of reserving and stochastic loss models

Abstract Traditionally, the common reserving methods used by the non-life actuaries are based on the assumption that future claims are going to behave in the same way as they did in the past. There are two main sources of variability in the processus of development of the claims: the variability of the speed with which the claims are settled and the variability between the severity of the claims from different accident years. High changes in these processes will generate distortions in the estimation of the claims reserves. The main objective of this thesis is to provide an indicator which firstly identifies and quantifies these two influences and secondly to determine which model is adequate for a specific situation. Two stochastic models were analysed and the predictive distributions of the future claims were obtained. The main advantage of the stochastic models is that they provide measures of variability of the reserves estimates. The first model (PDM) combines one conjugate family Dirichlet - Multinomial with the Poisson distribution. The second model (NBDM) improves the first one by combining two conjugate families Poisson -Gamma (for distribution of the ultimate amounts) and Dirichlet Multinomial (for distribution of the incremental claims payments). It was found that the second model allows to find the speed variability in the reporting process and development of the claims severity as function of two above mentioned distributions' parameters. These are the shape parameter of the Gamma distribution and the Dirichlet parameter. Depending on the relation between them we can decide on the adequacy of the claims reserve estimation method. The parameters have been estimated by the Methods of Moments and Maximum Likelihood. The results were tested using chosen simulation data and then using real data originating from the three lines of business: Property/Casualty, General Liability, and Accident Insurance. These data include different developments and specificities. The outcome of the thesis shows that when the Dirichlet parameter is greater than the shape parameter of the Gamma, resulting in a model with positive correlation between the past and future claims payments, suggests the Chain-Ladder method as appropriate for the claims reserve estimation. In terms of claims reserves, if the cumulated payments are high the positive correlation will imply high expectations for the future payments resulting in high claims reserves estimates. The negative correlation appears when the Dirichlet parameter is lower than the shape parameter of the Gamma, meaning low expected future payments for the same high observed cumulated payments. This corresponds to the situation when claims are reported rapidly and fewer claims remain expected subsequently. The extreme case appears in the situation when all claims are reported at the same time leading to expectations for the future payments of zero or equal to the aggregated amount of the ultimate paid claims. For this latter case, the Chain-Ladder is not recommended.

Cellular localization, expression and regulation of neuropeptide Y in kidneys of hypertensive rats.

Neuropeptide Y (NPY) is a key modulator of the autonomic nervous system playing pivotal roles in cardiovascular and neuronal functions. In this study, we assessed the cellular localization and gene expression of NPY in rat kidneys. We also examined the relationship between NPY gene expression and renin in two rat models of hypertension (two-kidney, one-clip renal hypertension (2K1C), and deoxycorticosterone-salt-induced hypertension (DOCA-salt)) characterized by a similar blood pressure elevation. In situ hybridization and immunohistochemistry, using anti-NPY or anti-C-flanking peptide of NPY (CPON) antibodies, showed that NPY transcript and protein were colocalized in the tubules of rat kidneys. During experimental hypertension, NPY mRNA was decreased in both kidneys of the 2K1C animals, but not in the kidney of DOCA-salt rats. In 2K1C rats, renal NPY content was also decreased. The difference in NPY gene expression between 2K1C rats (a high renin model of hypertension) and DOCA-salt rats (a low renin model of hypertension) suggests that circulating angiotensin II plays a role in local renal NPY gene expression and that the elevated blood pressure per se is not the primary factor responsible for the control of NPY gene expression in the kidney.

Cardiovascular effects in patrol officers are associated with fine particulate matter from brake wear and engine emissions

Background: Exposure to fine particulate matter air pollutants (PM2.5) affects heart rate variability parameters, and levels of serum proteins associated with inflammation, hemostasis and thrombosis. This study investigated sources potentially responsible for cardiovascular and hematological effects in highway patrol troopers. Results: Nine healthy young non-smoking male troopers working from 3 PM to midnight were studied on four consecutive days during their shift and the following night. Sources of in-vehicle PM2.5 were identified with variance-maximizing rotational principal factor analysis of PM2.5-components and associated pollutants. Two source models were calculated. Sources of in-vehicle PM2.5 identified were 1) crustal material, 2) wear of steel automotive components, 3) gasoline combustion, 4) speed-changing traffic with engine emissions and brake wear. In one model, sources 1 and 2 collapsed to a single source. Source factors scores were compared to cardiac and blood parameters measured ten and fifteen hours, respectively, after each shift. The "speed-change" factor was significantly associated with mean heart cycle length (MCL, +7% per standard deviation increase in the factor score), heart rate variability (+16%), supraventricular ectopic beats (+39%), % neutrophils (+7%), % lymphocytes (-10%), red blood cell volume MCV (+1%), von Willebrand Factor (+9%), blood urea nitrogen (+7%), and protein C (-11%). The "crustal" factor (but not the "collapsed" source) was associated with MCL (+3%) and serum uric acid concentrations (+5%). Controlling for potential confounders had little influence on the effect estimates. Conclusion: PM2.5 originating from speed-changing traffic modulates the autonomic control of the heart rhythm, increases the frequency of premature supraventricular beats and elicits proinflammatory and pro-thrombotic responses in healthy young men. [Authors]

Two-kidney, one clip and one-kidney, one clip hypertension in mice.

The mouse remains the animal of choice in transgenic experiments, creating a need for methods of evaluating the physiology of genetically modified animals. We have established and characterized two murine models of renovascular hypertension known as the two-kidney, one clip and one-kidney, one clip models. The appropriate size of the clip lumen needed to induce high blood pressure was determined to be 0.12 mm. Clips with a lumen of 0.11 mm induced a high percentage of renal infarction, and clips with a 0.13-mm opening did not produce hypertension. Four weeks after clipping, two-kidney, one clip hypertensive mice exhibited blood pressure approximately 20 mm Hg higher than their sham-operated controls. After a similar period, this increase reached almost 35 mm Hg in the one-kidney, one clip model. Depending on the model, mice develop either renin-dependent or renin-independent hypertension. Both models are characterized by the development of cardiovascular hypertrophy.

Corporate governancen vaikutus osuustoiminnallisten yritysten riskienhallintaan

Tutkimuksen tarkoituksena on osallistua corporate governance -keskusteluun tuomalla esiin riskienhallinnan näkökulma osuustoiminnallisessa yritystoiminnassa. Tutkimuksen tavoitteena on kuvata corporate governancen vaikutuksia tuottajaosuustoiminnallisten yritysten riskienhallintaan, selvittää tuottajaosuustoiminnan riskienhallinnan tilaa ja toteutusta ja siihen vaikuttavia tekijöitä sekä tuoda esille näkökulmia riskienhallinnan kehittämiseksi tuottajaosuustoiminnallisissa yrityksissä. Tutkimus on luonteeltaan laadullinen tapaustutkimus. Tutkimuksen empiirinen aineisto kerättiin haastattelemalla kolmea osuustoiminnan asiantuntijaa ja seitsemää riskienhallinnan ja hallinnon vastuuhenkilöä. Haastattelut tehtiin vuoden 2006 kesän ja alkusyksyn aikana. Tutkimuksen perusteella corporate governancen vaikutus organisaatioiden riskienhallintaan on ollut rajallinen. Myös riskienhallintaan sidoksissa olevien toimi- ja hallintoelinten osalta suosituksilla on ollut vähäinen vaikutus. Huolimatta corporate governancen ja riskienhallinnan merkityksen lisääntymisestä tuottajaosuustoiminnallisissa yrityksissä, konkreettisella tasolla riskienhallinta ei toteudu corporate governance -periaatteiden edellyttämällä tavalla niin, että riskienhallintaa voisi kuvata kokonaisvaltaiseksi, periaatteiltaan määritellyksi ja suunnitelmalliseksi prosessiksi. Tutkimuksessa on myös pyritty nostamaan esiin riskienhallinnan eroja eri organisaatiomallien välillä. Tarkastelussaolleiden perusosuuskuntien sekä hybridimallien väliset erot liittyvät lähinnä yritysten resurssien ja koon vaikutuksista syntyviin eroihin riskienhallinnan toteutuksessa ja organisoinnissa. Merkittävään rooliin tuottajaosuustoiminnallistenyritysten riskienhallinnassa nousee erillisen riskienhallintatoiminnon osaaminen ja sen hyödyntäminen organisaatioiden riskienhallintatyössä.

Predicción de la resistencia al flujo en ríos de montaña

Se han calibrado, validado y comparado tres modelos de resistencia al flujo de contorno granular: un modelo potencial y otros dos modelos desarrollados para condiciones de alta rugosidad relativa (uno basado en una modificación de la ley logarítmica de Prandtl-von Karman y otro fundamentado en un perfil de velocidad configurado en dos zonas: una uniforme en las proximidades de los elementos de rugosidad y otra superior que sigue una distribución logarítmica). Se ha empleado para ello un numeroso conjunto de 1.533 datos tomados en ríos y en canales de laboratorio, representativo de un amplio intervalo hidráulico y geomorfológico en el ámbito de ríos de grava y de montaña. Han resultado preferibles las ecuaciones ajustadas con los percentiles granulométricos mayores (d90 o d84) que las ajustadas con el diámetro mediano (d50), debido a la mayor capacidad explicativa alcanzada dado un modelo, la menor diferencia en la bondad de ajuste entre los diferentes modelos y la menor influencia del origen de los datos (río o canal de laboratorio). Las ecuaciones ajustadas de acuerdo con los modelos en donde se contemplan condiciones de alta rugosidad relativa presentan predicciones similares, exceptuando el intervalo macrorrugoso (y/d90 < 1), en el que es preferible la correspondiente al modelo fundamentado en el perfil de velocidad configurado en dos zonas. Se recomienda restringir la aplicación de la ecuación ajustada con arreglo a la ley potencial al intervalo de y/d90 comprendido entre uno y veinte, puesto que fuera de dicho intervalo tiende a infraestimar notablemente la resistencia al flujo.