A Bayesian Approach for Modeling and Forecasting Solar Photovoltaic Power Generation.

In this paper, we propose a Bayesian approach to estimate the curve of a function f(·) that models the solar power generated at k moments per day for n days and to forecast the curve for the (n+1)th day by using the history of recorded values. We assume that f(·) is an unknown function and adopt a Bayesian model with a Gaussian-process prior on the vector of values f(t)=f(1),…, f(k). An advantage of this approach is that we may estimate the curves of f(·) and fn+1(·) as "smooth functions" obtained by interpolating between the points generated from a k-variate normal distribution with appropriate mean vector and covariance matrix. Since the joint posterior distribution for the parameters of interest does not have a known mathematical form, we describe how to implement a Gibbs sampling algorithm to obtain estimates for the parameters. The good performance of the proposed approach is illustrated using two simulation studies and an application to a real dataset. As performance measures, we calculate the absolute percentage error, the mean absolute percentage error (MAPE), and the root-mean-square error (RMSE). In all simulated cases and in the application to real-world data, the MAPE and RMSE values were all near 0, indicating the very good performance of the proposed approach.

On the Nuisance Parameter Elimination Principle in Hypothesis Testing.

The Non-Informative Nuisance Parameter Principle concerns the problem of how inferences about a parameter of interest should be made in the presence of nuisance parameters. The principle is examined in the context of the hypothesis testing problem. We prove that the mixed test obeys the principle for discrete sample spaces. We also show how adherence of the mixed test to the principle can make performance of the test much easier. These findings are illustrated with new solutions to well-known problems of testing hypotheses for count data.

Modeling Overdispersed Dengue Data via Poisson Inverse Gaussian Regression Model: A Case Study in the City of Campo Grande, MS, Brazil.

Dengue fever is a tropical disease transmitted mainly by the female Aedes aegypti mosquito that affects millions of people every year. As there is still no safe and effective vaccine, currently the best way to prevent the disease is to control the proliferation of the transmitting mosquito. Since the proliferation and life cycle of the mosquito depend on environmental variables such as temperature and water availability, among others, statistical models are needed to understand the existing relationships between environmental variables and the recorded number of dengue cases and predict the number of cases for some future time interval. This prediction is of paramount importance for the establishment of control policies. In general, dengue-fever datasets contain the number of cases recorded periodically (in days, weeks, months or years). Since many dengue-fever datasets tend to be of the overdispersed, long-tail type, some common models like the Poisson regression model or negative binomial regression model are not adequate to model it. For this reason, in this paper we propose modeling a dengue-fever dataset by using a Poisson-inverse-Gaussian regression model. The main advantage of this model is that it adequately models overdispersed long-tailed data because it has a wider skewness range than the negative binomial distribution. We illustrate the application of this model in a real dataset and compare its performance to that of a negative binomial regression model.

Adaptive Significance Levels in Tests for Linear Regression Models: The e-Value and P-Value Cases.

The full Bayesian significance test (FBST) for precise hypotheses is a Bayesian alternative to the traditional significance tests based on p-values. The FBST is characterized by the e-value as an evidence index in favor of the null hypothesis (H). An important practical issue for the implementation of the FBST is to establish how small the evidence against H must be in order to decide for its rejection. In this work, we present a method to find a cutoff value for the e-value in the FBST by minimizing the linear combination of the averaged type-I and type-II error probabilities for a given sample size and also for a given dimensionality of the parameter space. Furthermore, we compare our methodology with the results obtained from the test with adaptive significance level, which presents the capital-P P-value as a decision-making evidence measure. For this purpose, the scenario of linear regression models with unknown variance under the Bayesian approach is considered.

Piecewise Modeling the Accumulated Daily Growth of COVID-19 Deaths: The Case of the State of São Paulo, Brazil.

The pandemic scenery caused by the new coronavirus, called SARS-CoV-2, increased interest in statistical models capable of projecting the evolution of the number of cases (and associated deaths) due to COVID-19 in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agencies in making decisions in relation to procedures of prevention of the disease. Since the growth of the number of cases (and deaths) of COVID-19, in general, has presented a heterogeneous evolution over time, it is important that the modeling procedure is capable of identifying periods with different growth rates and proposing an adequate model for each period. Here, we present a modeling procedure based on the fit of a piecewise growth model for the cumulative number of deaths. We opt to focus on the modeling of the cumulative number of deaths because, other than for the number of cases, these values do not depend on the number of diagnostic tests performed. In the proposed approach, the model is updated in the course of the pandemic, and whenever a "new" period of the pandemic is identified, it creates a new sub-dataset composed of the cumulative number of deaths registered from the change point and a new growth model is chosen for that period. Three growth models were fitted for each period: exponential, logistic and Gompertz models. The best model for the cumulative number of deaths recorded is the one with the smallest mean square error and the smallest Akaike information criterion (AIC) and Bayesian information criterion (BIC) values. This approach is illustrated in a case study, in which we model the number of deaths due to COVID-19 recorded in the State of São Paulo, Brazil. The results have shown that the fit of a piecewise model is very effective for explaining the different periods of the pandemic evolution.

Data Science: Measuring Uncertainties.

With the increase in data processing and storage capacity, a large amount of data is available [...].

HSP70 expression in Biomphalaria glabrata snails exposed to cadmium.

In this study, the effects of the heavy metal cadmium on the stress protein HSP70 are investigated in freshwater mollusks Biomphalaria glabrata. Adult snails were exposed for 96h to CdCl2 at concentrations ranging from 0.09 to 0.7mgL-1 (LC50/96h=0.34 (0.30-0.37). Time and concentration-dependent increases in the expression of HSP70 were observed at sub-lethal levels in the immunoblotting assay. Further, an increased survival to a lethal heat shock was observed in animals pre-exposed to a nonlethal concentration of cadmium, evidencing the induction of acquired tolerance. The present study demonstrated the inducibility of B. glabrata HSP70 by cadmium, a relevant environmental contaminant, at non-lethal levels, providing evidences that the assessment of HSP70 in B. glabrata can be regarded as a suitable biomarker for ecotoxicological studies.

Testing allele homogeneity: the problem of nested hypotheses.

BACKGROUND: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice. RESULTS: We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent. CONCLUSIONS: Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations.

Are the 50's, the transition decade, in choroid plexus aging?

The choroid plexus (CP) is an important structure for the brain. Besides its major role in the production of cerebrospinal fluid (CSF), it conveys signals originating from the brain, and from the circulatory system, shaping brain function in health and in pathology. Previous studies in rodents have revealed altered transcriptome both during aging and in various diseases of the central nervous system, including Alzheimer's disease. In the present study, a high-throughput sequencing of the CP transcriptome was performed in postmortem samples of clinically healthy individuals aged 50's through 80's. The data shows an age-related profile, with the main changes occurring in the transition from the 50's to the 60's, stabilizing thereafter. Specifically, neuronal and membrane functions distinguish the transcriptome between the 50's and the 60's, while neuronal and axon development and extracellular structure organization differentiate the 50's from the 70's. These findings suggest that changes in the CP transcriptome occur early in the aging process. Future studies will unravel whether these relate with processes occurring in late- onset brain diseases.

Initial findings of striatum tripartite model in OCD brain samples based on transcriptome analysis.

Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by obsessions and/or compulsions. Different striatal subregions belonging to the cortico-striato-thalamic circuitry (CSTC) play an important role in the pathophysiology of OCD. The transcriptomes of 3 separate striatal areas (putamen (PT), caudate nucleus (CN) and accumbens nucleus (NAC)) from postmortem brain tissue were compared between 6 OCD and 8 control cases. In addition to network connectivity deregulation, different biological processes are specific to each striatum region according to the tripartite model of the striatum and contribute in various ways to OCD pathophysiology. Specifically, regulation of neurotransmitter levels and presynaptic processes involved in chemical synaptic transmission were shared between NAC and PT. The Gene Ontology terms cellular response to chemical stimulus, response to external stimulus, response to organic substance, regulation of synaptic plasticity, and modulation of synaptic transmission were shared between CN and PT. Most genes harboring common and/or rare variants previously associated with OCD that were differentially expressed or part of a least preserved coexpression module in our study also suggest striatum subregion specificity. At the transcriptional level, our study supports differences in the 3 circuit CSTC model associated with OCD.

Anxiety disorders and rheumatic Fever: is there an association?

INTRODUCTION: Findings suggest that obsessive-compulsive disorder (OCD) and related disorders, referred to as obsessive-compulsive spectrum disorders (OCSDs), are more common in patients with rheumatic fever (RF). OBJECTIVES: To determine whether RF or Sydenham's chorea increases the probability of anxiety disorders in the relatives of individuals with RF with and without SC. METHODS: This was a case-control family study in which 98 probands and 389 first-degree relatives (FDRs) were assessed using structured psychiatric interviews. A Poisson regression model was used to determine whether the presence of any disorder in one family member influences the rate of disorders in the remaining family members. RESULTS: Generalized anxiety disorder (GAD) occurred more frequently in the FDRs of RF probands than in those of control probands (P=.018). The presence of RF, GAD, or separation anxiety disorder in one family member significantly increased the chance of OCSDs in another member of the family. CONCLUSION: We found familial aggregation among RF, GAD, and OCSDs. Clinicians should be aware of the possible familial relationship between GAD and OCSDs in their RF patients and their family members, which may suggest a genetic component between them. Further studies on OCD should include anxiety disorders to better define OCD spectrum.

Obsessive-compulsive disorder: influence of age at onset on comorbidity patterns.

PURPOSE: This study investigates the influence of age at onset of OCS on psychiatric comorbidities, and tries to establish a cut-off point for age at onset. METHODS: Three hundred and thirty OCD patients were consecutively recruited and interviewed using the following structured interviews: Yale-Brown Obsessive Compulsive Scale; Yale Global Tic Severity Scale and the Structured Clinical Interview for DSM-IV. Data were analyzed with regression and cluster analysis. RESULTS: Lower age at onset was associated with a higher probability of having comorbidity with tic, anxiety, somatoform, eating and impulse-control disorders. Longer illness duration was associated with lower chance of having tics. Female gender was associated with anxiety, eating and impulse-control disorders. Tic disorders were associated with anxiety disorders and attention-deficit/hyperactivity disorder. No cut-off age at onset was found to clearly divide the sample in homogeneous subgroups. However, cluster analyses revealed that differences started to emerge at the age of 10 and were more pronounced at the age of 17, suggesting that these were the best cut-off points on this sample. CONCLUSIONS: Age at onset is associated with specific comorbidity patterns in OCD patients. More prominent differences are obtained when analyzing age at onset as an absolute value.

Adaptive treatment strategies for children and adolescents with Obsessive-Compulsive Disorder: A sequential multiple assignment randomized trial.

OBJECTIVE: This sequential multiple assignment randomized trial (SMART) tested the effect of beginning treatment of childhood OCD with fluoxetine (FLX) or group cognitive-behavioral therapy (GCBT) accounting for treatment failures over time. METHODS: A two-stage, 28-week SMART was conducted with 83 children and adolescents with OCD. Participants were randomly allocated to GCBT or FLX for 14 weeks. Responders to the initial treatment remained in the same regimen for additional 14 weeks. Non-responders, defined by less than 50% reduction in baseline Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) scores, were re-randomized to either switch to or add the other treatment. Assessments were performed at baseline, 7, 14, 21, and 28 weeks. RESULTS: Among the 43 children randomized to FLX who completed the first stage, 15 (41.7%) responded to treatment and 21 non-responders were randomized to switch to (N = 9) or add GCBT (N = 12). Among the 40 children randomized to GCBT who completed the first stage, 18 (51.4%) responded to treatment and 17 non-responders were randomized to switch to (N = 9) or add FLX (N = 8). Primary analysis showed that significant improvement occurred in children initially treated with either FLX or GCBT. Each time point was statistically significant, showing a linear trend of symptom reduction. Effect sizes were large within (0.76-0.78) and small between (-0.05) groups. CONCLUSIONS: Fluoxetine and GCBT are similarly effective initial treatments for childhood OCD considering treatment failures over time. Consequently, provision of treatment for childhood OCD could be tailored according to the availability of local resources.

Quantifying dimensional severity of obsessive-compulsive disorder for neurobiological research.

Current research to explore genetic susceptibility factors in obsessive-compulsive disorder (OCD) has resulted in the tentative identification of a small number of genes. However, findings have not been readily replicated. It is now broadly accepted that a major limitation to this work is the heterogeneous nature of this disorder, and that an approach incorporating OCD symptom dimensions in a quantitative manner may be more successful in identifying both common as well as dimension-specific vulnerability genetic factors. As most existing genetic datasets did not collect specific dimensional severity ratings, a specific method to reliably extract dimensional ratings from the most widely used severity rating scale, the Yale-Brown Obsessive Compulsive Scale (YBOCS), for OCD is needed. This project aims to develop and validate a novel algorithm to extrapolate specific dimensional symptom severity ratings in OCD from the existing YBOCS for use in genetics and other neurobiological research. To accomplish this goal, we used a large data set comprising adult subjects from three independent sites: the Brazilian OCD Consortium, the Sunnybrook Health Sciences Centre in Toronto, Canada and the Hospital of Bellvitge, in Barcelona, Spain. A multinomial logistic regression was proposed to model and predict the quantitative phenotype [i.e., the severity of each of the five homogeneous symptom dimensions of the Dimensional YBOCS (DYBOCS)] in subjects who have only YBOCS (categorical) data. YBOCS and DYBOCS data obtained from 1183 subjects were used to build the model, which was tested with the leave-one-out cross-validation method. The model's goodness of fit, accepting a deviation of up to three points in the predicted DYBOCS score, varied from 78% (symmetry/order) to 84% (cleaning/contamination and hoarding dimensions). These results suggest that this algorithm may be a valuable tool for extracting dimensional phenotypic data for neurobiological studies in OCD.

Dominant lethal effects of 2,4-D in Biomphalaria glabrata.

Dominant lethal effects of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) were evaluated in the freshwater snail Biomphalaria glabrata. Wild-type snails were exposed during 10 days to 50, 75 and 100ppm of 2,4-D dimethylamine salt (2,4-D DMA) and paired with non-exposed albino snails 1, 11, 25 and 40 days after the exposure. The offspring of the non-exposed albino snails was scored for lethal malformations. One day after the exposure, a significant effect was observed at 75 and 100ppm without a dose-response relationship. After 11 days, the effect was observed only at the highest dose. After 25 days, significant increases in the dominant lethal effects occurred at 50 and 75ppm; effects were directly related to the doses. Background levels of lethal malformations were resumed after 40 days. Although the major and direct measure of dominant lethal mutations is the rate of lethal malformations in the heterozygous offspring of the albino snails, the sensitivity of the assay was substantially increased with the evaluation of all non-viable embryos, that are the sum of those with lethal malformations, identified or not as wild-type.

Adrenocortical carcinoma: prognostic indices based on clinical and immunohistochemical markers.

Adrenocortical carcinoma is a rare condition with an unpredictable prognosis as a rule. The authors retrospectively analyzed the clinical outcome of 46 patients (31 F, 15 M) during 16 years building up a numerical index for the prognosis, based on clinical and immunohistochemical data. Four indices were analyzed: J1= (Y + 2L + 4H)/T; J2 = (J1) square root of W/200; J3 = (O + Y + 2L + 4H)/T; J4 = (J3) square root W/200. Y = 1 when chronological age (CA) >33 mo, Y = 0 when CA < or =33 mo; L = 1 for right sided tumor and L = 0 for left sided tumor; H = 1 in presence of hypertension and H = 0 for normal blood pressure; T = length of disease in months; W = weight of tumor (g); O = 1 in the absence of p53 protein and O = 0 in the presence of p53. The chance of bad prognosis was observed when age is >33 mo, tumor is on the right side, systemic hypertension is present, tumor weight >250 g, in the absence of p53, J1, J2, J3 >0.4 (p <0.001) and J4 >0.5 (p <0.01). Clinical data and the mathematical model enabled us to establish probabilities of good prognosis in 78-96% and bad prognosis in 63-83%.

COMT and MAO-A polymorphisms and obsessive-compulsive disorder: a family-based association study.

OBJECTIVE: Obsessive-compulsive disorder (OCD) is a common and debilitating psychiatric illness. Although a genetic component contributes to its etiology, no single gene or mechanism has been identified to the OCD susceptibility. The catechol-O-methyltransferase (COMT) and monoamine oxidase A (MAO-A) genes have been investigated in previous OCD studies, but the results are still unclear. More recently, Taylor (2013) in a comprehensive meta-analysis of genetic association studies has identified COMT and MAO-A polymorphisms involved with OCD. In an effort to clarify the role of these two genes in OCD vulnerability, a family-based association investigation was performed as an alternative strategy to the classical case-control design. METHODS: Transmission disequilibrium analyses were performed after genotyping 13 single-nucleotide polymorphisms (eight in COMT and five in MAO-A) in 783 OCD trios (probands and their parents). Four different OCD phenotypes (from narrow to broad OCD definitions) and a SNP x SNP epistasis were also analyzed. RESULTS: OCD, broad and narrow phenotypes,were not associated with any of the investigated COMT and MAO-A polymorphisms. In addition, the analyses of gene-gene interaction did not show significant epistatic influences on phenotype between COMT and MAO-A. CONCLUSIONS: The findings do not support an association between DSM-IV OCD and the variants of COMT or MAO-A. However, results from this study cannot exclude the contribution of these genes in the manifestation of OCD. The evaluation of broader spectrum phenotypes could help to understand the role of these and other genes in the pathophysiology of OCD and its spectrum disorders.

DNA microarrays for comparative genomics and analysis of gene expression in Trypanosoma cruzi.

Trypanosoma cruzi presents high genetic diversity and parasite isolates show remarkable differences in biological parameters. In this study, we evaluated whether DNA microarrays containing CL Brener cDNAs can be used for comparative genomics and for the analysis of gene expression in T. cruzi. We constructed a prototype microarray with 710 expression sequence tags of CL Brener and 20 sequences of T. cruzi strains. These probes represent 665 unique genes. Results from four hybridisations with genomic DNA of Silvio (T. cruzi I) and CL Brener (hybrid genotype) identified 9.3% of the probes (68/730) differentially represented in the two genomes. Data from eight hybridisations with cDNA obtained from three independent parasite harvests of Silvio and CL Brener disclosed 84 sequences of 730 (11.5%) that showed statistical significant (P < or = 0.01) changes in expression (1.6-6.5-fold). Some of the array-identified sequences were confirmed by Southern and Northern blot analysis. Only 20% of the probes with increased expression in Silvio or CL Brener presented higher hybridisation with genomic DNA of either strain. Approximately 2.5% (18/730) and 9.0% (65/730) of the probes were differentially expressed (P < or = 0.01), respectively, in epimastigotes and metacyclic trypomastigotes of two T. cruzi II strains isolated from chronic chagasic patients. Microarrays identified several sequences for which differences in gene copy number and/or in the levels of RNA transcripts were previously demonstrated by different approaches. The data indicate that DNA microarrays are a useful tool for comparative studies between strains and provide further evidence for a high level of post-transcriptional regulation of RNA abundance in T. cruzi.

Dominant lethal effect of 60Co gamma radiation in Biomphalaria glabrata (SAY, 1818).

The dominant lethal effects of gamma radiation of 60Co in the snail Biomphalaria glabrata were studied. Three groups of 13 wild-type snails were irradiated with single doses of 2.5; 10 and 20 Gy. Crossings were carried out at intervals of 7, 17, 23, 30 and 36 days after irradiation. The dominant lethal effect was observed only at the first crossing occurring 7 days after irradiation with 2.5 Gy. With 10 and 20 Gy, the induction of lethal mutations was detected at 7, 17 and 23 days after irradiation; a dose-response effect was observed. The effect was stronger 7 days after irradiation, decreasing in the succeeding crossings up to 30 days. Cell-killing effects on germ cells were detected in the crossings at 23 days and 30 days after irradiation with 20 Gy. After 36 days, frequencies of malformations resumed background levels; crossing rates partially recovered. These results show that gamma radiation affected all the stages of spermatogenesis. Germ cells at later phases were more sensitive to the mutagenic effect of radiation and the cell killing effects were observed on the youngest cells. This response was similar to the highly homogeneous pattern observed in widely different species and allowed us to estimate some parameters of spermatogenesis in B. glabrata.

Repair of oxidative DNA damage, cell-cycle regulation and neuronal death may influence the clinical manifestation of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by progressive cognitive decline associated with a featured neuropathology (neuritic plaques and neurofibrillary tangles). Several studies have implicated oxidative damage to DNA, DNA repair, and altered cell-cycle regulation in addition to cell death in AD post-mitotic neurons. However, there is a lack of studies that systematically assess those biological processes in patients with AD neuropathology but with no evidence of cognitive impairment. We evaluated markers of oxidative DNA damage (8-OHdG, H2AX), DNA repair (p53, BRCA1, PTEN), and cell-cycle (Cdk1, Cdk4, Cdk5, Cyclin B1, Cyclin D1, p27Kip1, phospho-Rb and E2F1) through immunohistochemistry and cell death through TUNEL in autopsy hippocampal tissue samples arrayed in a tissue microarray (TMA) composed of three groups: I) "clinical-pathological AD" (CP-AD)--subjects with neuropathological AD (Braak ≥ IV and CERAD = B or C) and clinical dementia (CDR ≥ 2, IQCODE>3.8); II) "pathological AD" (P-AD)--subjects with neuropathological AD (Braak ≥ IV and CERAD = B or C) and without cognitive impairment (CDR 0, IQCODE<3.2); and III) "normal aging" (N)--subjects without neuropathological AD (Braak ≤ II and CERAD 0 or A) and with normal cognitive function (CDR 0, IQCODE<3.2). Our results show that high levels of oxidative DNA damage are present in all groups. However, significant reductions in DNA repair and cell-cycle inhibition markers and increases in cell-cycle progression and cell death markers in subjects with CP-AD were detected when compared to both P-AD and N groups, whereas there were no significant differences in the studied markers between P-AD individuals and N subjects. This study indicates that, even in the setting of pathological AD, healthy cognition may be associated with a preserved repair to DNA damage, cell-cycle regulation, and cell death in post-mitotic neurons.