Multispectral retinal image analysis (MRIA) for the assessment of subretinal fibrosis in neovascular age-related macular degeneration (nAMD)

Purpose: To investigate the use of MRIA for quantitative characterisation of subretinal fibrosis secondary to nAMD. Methods: MRIA images of the posterior pole were acquired over 4 months from 20 eyes including those with inactive subretinal fibrosis and those being treated with ranibizumab for nAMD. Changes in morphology of the macula affected by nAMD were modelled and reflectance spectra at the MRIA acquisition wavelengths (507, 525, 552, 585, 596, 611 and 650nm) were computed using Monte Carlo simulation. Quantitative indicators of fibrosis were derived by matching image spectra to the model spectra of known morphological properties. Results: The model spectra were comparable to the image spectra, both normal and pathological. The key morphological changes that the model associated with nAMD were gliosis of the IS-OS junction, decrease in retinal blood and decrease in RPE melanin. However, these changes were not specific to fibrosis and none of the quantitative indicators showed a unique association with the degree of fibrosis. Moderate correlations were found with the clinical assessment, but not with the treatment program. Conclusion: MRIA can distinguish subretinal fibrosis from healthy tissue. The methods used show high sensitivity but low specificity, being unable to distinguish scarring from other abnormalities like atrophy. Quantification of scarring was not achieved with the wavelengths used due to the complex structural changes to retinal tissues in the process of nAMD. Further studies, incorporating other wavelengths, will establish whether MRIA has a role in the assessment of subretinal fibrosis in the context of retinal and choroidal pathology

Dynamic fault tree analysis with PEWMA modeling of event rates and Bayesian updating of material balance parameters using MCMC

This research explores Bayesian updating as a tool for estimating parameters probabilistically by dynamic analysis of data sequences. Two distinct Bayesian updating methodologies are assessed. The first approach focuses on Bayesian updating of failure rates for primary events in fault trees. A Poisson Exponentially Moving Average (PEWMA) model is implemnented to carry out Bayesian updating of failure rates for individual primary events in the fault tree. To provide a basis for testing of the PEWMA model, a fault tree is developed based on the Texas City Refinery incident which occurred in 2005. A qualitative fault tree analysis is then carried out to obtain a logical expression for the top event. A dynamic Fault Tree analysis is carried out by evaluating the top event probability at each Bayesian updating step by Monte Carlo sampling from posterior failure rate distributions. It is demonstrated that PEWMA modeling is advantageous over conventional conjugate Poisson-Gamma updating techniques when failure data is collected over long time spans. The second approach focuses on Bayesian updating of parameters in non-linear forward models. Specifically, the technique is applied to the hydrocarbon material balance equation. In order to test the accuracy of the implemented Bayesian updating models, a synthetic data set is developed using the Eclipse reservoir simulator. Both structured grid and MCMC sampling based solution techniques are implemented and are shown to model the synthetic data set with good accuracy. Furthermore, a graphical analysis shows that the implemented MCMC model displays good convergence properties. A case study demonstrates that Likelihood variance affects the rate at which the posterior assimilates information from the measured data sequence. Error in the measured data significantly affects the accuracy of the posterior parameter distributions. Increasing the likelihood variance mitigates random measurement errors, but casuses the overall variance of the posterior to increase. Bayesian updating is shown to be advantageous over deterministic regression techniques as it allows for incorporation of prior belief and full modeling uncertainty over the parameter ranges. As such, the Bayesian approach to estimation of parameters in the material balance equation shows utility for incorporation into reservoir engineering workflows.

Bayesian Emulation for Sequential Modeling, Inference and Decision Analysis

The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

The State of the Nation Debate as part of the democratic parliamentary ritual: Rajoy and Rubalcaba discourse analysis, 2014

In this article we analyze the Debate on the State of the Nation 2014. The methodology consists in coding the speeches of the prime minister, Mariano Rajoy (PP) and the then opposition leader Alfredo Perez Rubalcaba (PSOE) through extracting word clouds, branched maps and word trees that have shown the most common concepts and premises. This preliminary analysis of two dimensions, quantitative and qualitative, makes it much easier and viable subsequent discourse analysis where we focus on the different types of arguments in the communicative act: claim/solution, circumstantial premises, goal premises, value premises, meansgoal premises, alternative options/addressing alternative options.

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

Retinal nerve fiber layer analysis using GDx® in 49 patients with chronic phase DUSN

To describe retinal nerve fiber layer changes in late-stage diffuse unilateral subacute neuroretinitis eyes and compare these results with healthy eyes observed through nerve fiber analyzer (GDx®). Methods: This is a retrospective case-control study in which 49 eyes in late-stage diffuse unilateral subacute neuroretinitis were examined from May/97 to December/ 01. First, eyes with diffuse unilateral subacute neuroretinitis and healthy contralateral eyes (Control Group I) were statistically matched. Subsequently, eyes with diffuse unilateral subacute neuroretinitis were compared with eyes of healthy patients (Control Group II). Results: Eyes from Control Groups I and II had higher relative frequency of “within normal limits” status. Eyes from the diffuse unilateral subacute neuroretinitis (DUSN) Group had higher frequency of “outside normal limits” and “borderline” status. Control Groups I and II had absolute values different from the DUSN Group regarding all parameters (p<0.05), except for Symmetry in Control Groups I and II, Average thickness and Superior Integral in control group II. Conclusion: Patients with late-stage diffuse unilateral subacute neuroretinitis presented presumed decrease in nerve fiber layer thickness shown by GDx®. Retinal zones with larger vascular support and larger amount of nerve fibers presented higher decrease in the delay of the reflected light measured by the nerve fiber analyzer

Analysis on the connotation of probability in the artificial intelligence algorithm for economic decision making.

This paper analyzes the inner relations between classical sub-scheme probability and statistic probability, subjective probability and objective probability, prior probability and posterior probability, transition probability and probability of utility, and further analysis the goal, method, and its practical economic purpose which represent by these various probability from the perspective of mathematics, so as to deeply understand there connotation and its relation with economic decision making, thus will pave the route for scientific predication and decision making.

Identification and functional analysis of novel genes expressed in the Anterior Visceral Endoderm

During early vertebrate development, the correct establishment of the body axes is critical. The anterior pole of the mouse embryo is established when Distal Visceral Endoderm (DVE) cells migrate to form the Anterior Visceral Endoderm (AVE). Symmetrical expression of Lefty1, Cer1 and Dkk1 determines the direction of DVE migration and the future anterior side. In addition to the establishment of the Anterior-Posterior axis, the AVE has also been implicated in anterior neural specification. To better understand the role of the AVE in these processes, we have performed a differential screening using Affymetrix GeneChip technology with AVE cells isolated from cer1P-EGFP transgenic mouse embryos. We found 175 genes which were upregulated in the AVE and 36 genes in the Proximal-posterior sample. Using DAVID software, we characterized the AVE cell population regarding cellular component, molecular function and biological processes. Among the genes that were found to be upregulated in the AVE, several novel genes were identified. Four of these transcripts displaying high-fold change in the AVE were further characterized by in situ hybridization in early stages of development in order to validate the screening. From those four selected genes, one, denominated Adtk1, was chosen to be functionally characterized by targeted inactivation in ES cells. Adtk1 encodes for a serine/threonine kinase. Adtk1 null mutants are smaller and present short limbs due to decreased mineralization, suggesting a potential role in chondrogenesis during limb development. Taken together, these data point to the importance of reporting novel genes present in the AVE.

Retinal nerve fiber layer analysis using GDx® in 49 patients with chronic phase DUSN

To describe retinal nerve fiber layer changes in late-stage diffuse unilateral subacute neuroretinitis eyes and compare these results with healthy eyes observed through nerve fiber analyzer (GDx®). Methods: This is a retrospective case-control study in which 49 eyes in late-stage diffuse unilateral subacute neuroretinitis were examined from May/97 to December/ 01. First, eyes with diffuse unilateral subacute neuroretinitis and healthy contralateral eyes (Control Group I) were statistically matched. Subsequently, eyes with diffuse unilateral subacute neuroretinitis were compared with eyes of healthy patients (Control Group II). Results: Eyes from Control Groups I and II had higher relative frequency of “within normal limits” status. Eyes from the diffuse unilateral subacute neuroretinitis (DUSN) Group had higher frequency of “outside normal limits” and “borderline” status. Control Groups I and II had absolute values different from the DUSN Group regarding all parameters (p<0.05), except for Symmetry in Control Groups I and II, Average thickness and Superior Integral in control group II. Conclusion: Patients with late-stage diffuse unilateral subacute neuroretinitis presented presumed decrease in nerve fiber layer thickness shown by GDx®. Retinal zones with larger vascular support and larger amount of nerve fibers presented higher decrease in the delay of the reflected light measured by the nerve fiber analyzer

Use of posterior predictive assessments to evaluate model fit in multilevel logistic regression

Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.

Bayesian analysis of a mastitis control plan to investigate the influence of veterinary prior beliefs on clinical interpretation

The fundamental objective for health research is to determine whether changes should be made to clinical decisions. Decisions made by veterinary surgeons in the light of new research evidence are known to be influenced by their prior beliefs, especially their initial opinions about the plausibility of possible results. In this paper, clinical trial results for a bovine mastitis control plan were evaluated within a Bayesian context, to incorporate a community of prior distributions that represented a spectrum of clinical prior beliefs. The aim was to quantify the effect of veterinary surgeons’ initial viewpoints on the interpretation of the trial results. A Bayesian analysis was conducted using Markov chain Monte Carlo procedures. Stochastic models included a financial cost attributed to a change in clinical mastitis following implementation of the control plan. Prior distributions were incorporated that covered a realistic range of possible clinical viewpoints, including scepticism, enthusiasm and uncertainty. Posterior distributions revealed important differences in the financial gain that clinicians with different starting viewpoints would anticipate from the mastitis control plan, given the actual research results. For example, a severe sceptic would ascribe a probability of 0.50 for a return of <£5 per cow in an average herd that implemented the plan, whereas an enthusiast would ascribe this probability for a return of >£20 per cow. Simulations using increased trial sizes indicated that if the original study was four times as large, an initial sceptic would be more convinced about the efficacy of the control plan but would still anticipate less financial return than an initial enthusiast would anticipate after the original study. In conclusion, it is possible to estimate how clinicians’ prior beliefs influence their interpretation of research evidence. Further research on the extent to which different interpretations of evidence result in changes to clinical practice would be worthwhile.

Therapeutic efficacy of alternative primaquine regimens to standard treatment in preventing relapses by Plasmodium vivax : A systematic review and meta-analysis

Objective: To compare efficacy and safety of primaquine regimens currently used to prevent relapses by Plasmodium vivax. Methods: A systematic review was carried out to identify clinical trials evaluating efficacy and safety to prevent malaria recurrences by P. vivax of primaquine regimen 0.5 mg/kg/day for 7 or 14 days compared to standard regimen of 0.25 mg/kg/day for 14 days. Efficacy of primaquine according to cumulative incidence of recurrences after 28 days was determined. The overall relative risk with fixed-effects meta-analysis was estimated. Results: For the regimen 0.5 mg/kg/day/7 days were identified 7 studies, which showed an incidence of recurrence between 0% and 20% with follow-up 60-210 days; only 4 studies comparing with the standard regimen 0.25 mg/kg/day/14 days and no difference in recurrences between both regimens (RR= 0.977, 95% CI= 0.670 to 1.423) were found. 3 clinical trials using regimen 0.5 mg/kg/day/14 days with an incidence of recurrences between 1.8% and 18.0% during 330-365 days were identified; only one study comparing with the standard regimen (RR= 0.846, 95% CI= 0.484 to 1.477). High risk of bias and differences in handling of included studies were found. Conclusion: Available evidence is insufficient to determine whether currently PQ regimens used as alternative rather than standard treatment have better efficacy and safety in preventing relapse of P. vivax. Clinical trials are required to guide changes in treatment regimen of malaria vivax.

Therapeutic efficacy of alternative primaquine regimens to standard treatment in preventing relapses by Plasmodium vivax: A systematic review and meta-analysis

Objective: To compare efficacy and safety of primaquine regimens currently used to prevent relapses by Plasmodium vivax. Methods: A systematic review was carried out to identify clinical trials evaluating efficacy and safety to prevent malaria recurrences by P. vivax of primaquine regimen 0.5 mg/kg/day for 7 or 14 days compared to standard regimen of 0.25 mg/kg/day for 14 days. Efficacy of primaquine according to cumulative incidence of recurrences after 28 days was determined. The overall relative risk with fixed-effects meta-analysis was estimated. Results: For the regimen 0.5 mg/kg/day/7 days were identified 7 studies, which showed an incidence of recurrence between 0% and 20% with follow-up 60-210 days; only 4 studies comparing with the standard regimen 0.25 mg/kg/day/14 days and no difference in recurrences between both regimens (RR= 0.977, 95% CI= 0.670 to 1.423) were found. 3 clinical trials using regimen 0.5 mg/kg/day/14 days with an incidence of recurrences between 1.8% and 18.0% during 330-365 days were identified; only one study comparing with the standard regimen (RR= 0.846, 95% CI= 0.484 to 1.477). High risk of bias and differences in handling of included studies were found. Conclusion: Available evidence is insufficient to determine whether currently PQ regimens used as alternative rather than standard treatment have better efficacy and safety in preventing relapse of P. vivax. Clinical trials are required to guide changes in treatment regimen of malaria vivax.

Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants

Background: One of the global targets for non-communicable diseases is to halt, by 2025, the rise in the age-standardised adult prevalence of diabetes at its 2010 levels. We aimed to estimate worldwide trends in diabetes, how likely it is for countries to achieve the global target, and how changes in prevalence, together with population growth and ageing, are affecting the number of adults with diabetes. Methods: We pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence - defined as fasting plasma glucose of 7·0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs - in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. We also calculated the posterior probability of meeting the global diabetes target if post-2000 trends continue. Findings: We used data from 751 studies including 4 372 000 adults from 146 of the 200 countries we make estimates for Global age-standardised diabetes prevalence increased from 4·3% (95% credible interval 2·4-7·0) in 1980 to 9·0% (7·2-11·1) in 2014 in men, and from 5·0% (2·9-7·9) to 7·9% (6·4-9·7) in women. The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (28·5% due to the rise in prevalence, 39·7% due to population growth and ageing, and 31·8% due to interaction of these two factors). Age-standardised adult diabetes prevalence in 2014 was lowest in northwestern Europe, and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa. Between 1980 and 2014 there was little change in age-standardised diabetes prevalence in adult women in continental western Europe, although crude prevalence rose because of ageing of the population. By contrast, age-standardised adult prevalence rose by 15 percentage points in men and women in Polynesia and Micronesia. In 2014, American Samoa had the highest national prevalence of diabetes (>30% in both sexes), with age-standardised adult prevalence also higher than 25% in some other islands in Polynesia and Micronesia. If post-2000 trends continue, the probability of meeting the global target of halting the rise in the prevalence of diabetes by 2025 at the 2010 level worldwide is lower than 1% for men and is 1% for women. Only nine countries for men and 29 countries for women, mostly in western Europe, have a 50% or higher probability of meeting the global target. Interpretation Since 1980, age-standardised diabetes prevalence in adults has increased, or at best remained unchanged, in every country. Together with population growth and ageing, this rise has led to a near quadrupling of the number of adults with diabetes worldwide. The burden of diabetes, both in terms of prevalence and number of adults aff ected, has increased faster in low-income and middle-income countries than in high-income countries.

Analysis Of The Dna Fourier Transform-infrared Microspectroscopic Signature Using An All-reflecting Objective.

The Fourier transform-infrared (FT-IR) signature of dry samples of DNA and DNA-polypeptide complexes, as studied by IR microspectroscopy using a diamond attenuated total reflection (ATR) objective, has revealed important discriminatory characteristics relative to the PO2(-) vibrational stretchings. However, DNA IR marks that provide information on the sample's richness in hydrogen bonds have not been resolved in the spectral profiles obtained with this objective. Here we investigated the performance of an all reflecting objective (ARO) for analysis of the FT-IR signal of hydrogen bonds in DNA samples differing in base richness types (salmon testis vs calf thymus). The results obtained using the ARO indicate prominent band peaks at the spectral region representative of the vibration of nitrogenous base hydrogen bonds and of NH and NH2 groups. The band areas at this spectral region differ in agreement with the DNA base richness type when using the ARO. A peak assigned to adenine was more evident in the AT-rich salmon DNA using either the ARO or the ATR objective. It is concluded that, for the discrimination of DNA IR hydrogen bond vibrations associated with varying base type proportions, the use of an ARO is recommended.