Ultrastructure of spermatogenesis, spermatozoon and processes of testicular regression and recrudescence in Eptesicus furinalis (Chiroptera: Vespertilionidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Is there difference of Streptococcus mutans count and adherence on amalgam and resin occlusal restorations? A blind clinical study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spermatozoon ultrastructure and semen parameters of Brycon vermelha (Characiformes, Characidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Space–time zero-inflated count models of Harbor seals

Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space–time random effects in zero-inflated Poisson (ZIP) and ‘hurdle’ models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space–time ZIP and hurdle models in a Bayesian hierarchical model. Space–time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space–time ZIP and hurdle models.

Changes in Complete Blood Count in Patients With Surgically Treated Facial Fractures

The purpose of this prospective study was to verify the changes in the preoperative and postoperative complete blood counts of patients with surgically treated facial fractures. Fifty consecutive patients with a mean age of 34 years who presented facial fractures and underwent surgical treatment were included. A complete blood count was performed, comprising the red and white blood cell count (cells/mu L), hemoglobin (g/dL), and hematocrit (%) levels. These data were obtained preoperatively and postoperatively during a 6-week period. Statistical analyses were performed using the Kruskal-Wallis and Mann-Whitney tests to identify the possible differences among the groups and among the periods of observation using the Friedman and Wilcoxon matched-pairs signed-ranks tests. The most common location of the fractures was the mandible (42.3%), followed by the zygomatic-orbital (36.5%) and associated locations (21.2%). Leukocytosis was associated with neutrophilia in the immediate postoperative period in all of the groups. There were no values below the reference limits of the values of hemoglobin, hematocrit, and erythrocytes, and no values above the reference limits for the remaining white blood cells, although significant differences among periods were observed in most cells, depending on the type of fracture. The primary findings were leukocytosis associated with neutrophilia, verified in the immediate postoperative period in all of the groups, and the influence of the type of fracture on the significant alterations observed among studied periods on the values of hemoglobin, hematocrit, erythrocytes, leukocytes, neutrophils, and lymphocytes.

Polymorphonuclear leukocytes CH138+apoptosis evaluation in milk with high and low somatic cell count - preliminary data

Polymorphonuclear leukocyte (PMNL) apoptosis is central to the successful resolution of inflammation. Since Somatic Cell Count (SCC) is an indicator of the mammary gland's immune status, this study sought to clarify the influence that these factors have on each other and on the evolution of the inflammatory process. Milk samples were stained with annexin-V, propidium iodide (PI), primary antibody anti-CH138A. Negative correlation between SCC and PMNL apoptosis was found, and a statistical difference between high SCC group and low SCC group was observed concerning the rate of viable PMNL, apoptotic PMNL, necrotic PMNL and necrotic and/or apoptotic PMNL. Overall, the high cellularity group presented lower proportions of CH138+ cells undergoing apoptosis and higher proportions of viable and necrotic CH138+ cells. Thus, it can be concluded that PMNL apoptosis and SCC are related factors, and that in high SCC, milk apoptosis is delayed. Although there is a greater amount of active phagocytes in this situation, apoptosis' anti-inflammatory effects are decreased, while necrosis' pro-inflammatory effects are increased, which can contribute to chronic inflammation.

WBC count and functional changes induced by co-administration of clofazimine and clarithromycin, in single and multiple doses, in Wistar rats

Clofazimine and clarithromycin are used to treat leprosy and infections caused by Mycobacterium avium complex. Little data on the toxicity of co-administration of these two drugs are available. Here we evaluated the potential adverse effects of polytherapy with these two drugs in male Wistar rats by determining WBCs counts and other blood cell counts, neutrophilic phagocytosis, and burst oxidative, by flow cytometry. We observed an increase in WBCs, in multiple-dose regimens, and in polymorphonuclear cells, in both single- clarithromycin only and multiple dose regimens. We also observed a reduction in mononuclear cell counts in single and multiple doses. The drugs seem to reverse the mononuclear and polymorphonuclear cell ratio. An increase in oxidative burst was observed in animals treated with the drugs administered either individually or combined. In conclusion, clofazimine and clarithromycin change WBCs counts. Our results may contribute for a better understanding of the mechanisms related to the effects of co-administrating the two drugs.

Effect of somatic cell count and mastitis pathogens on milk composition in Gyr cows

Abstract Background Gyr cows are well adapted to tropical conditions, resistant to some tropical diseases and have satisfactory milk production. However, Gyr dairy herds have a high prevalence of subclinical mastitis, which negatively affects their milk yield and composition. The objectives of this study were (i) to evaluate the effects of seasonality, mammary quarter location (rear x front), mastitis-causing pathogen species, and somatic cell count (SCC) on milk composition in Gyr cows with mammary quarters as the experimental units and (ii) to evaluate the effects of seasonality and somatic cell count (SCC) on milk composition in Gyr cows with cows as the experimental units. A total of 221 lactating Gyr cows from three commercial dairy farms were selected for this study. Individual foremilk quarter samples and composite milk samples were collected once a month over one year from all lactating cows for analysis of SCC, milk composition, and bacteriological culture. Results Subclinical mastitis reduced lactose, nonfat solids and total solids content, but no difference was found in the protein and fat content between infected and uninfected quarters. Seasonality influenced milk composition both in mammary quarters and composite milk samples. Nevertheless, there was no effect of mammary quarter position on milk composition. Mastitis-causing pathogens affected protein, lactose, nonfat solids, and total solids content, but not milk fat content. Somatic cell count levels affected milk composition in both mammary quarters and composite samples of milk. Conclusions Intramammary infections in Gyr cows alter milk composition; however, the degree of change depends on the mastitis-causing pathogen. Somatic cell count is negatively associated with reduced lactose and nonfat solids content in milk. Seasonality significantly affects milk composition, in which the concentration of lactose, fat, protein, nonfat solids and total solids differs between dry and wet seasons in Gyr cows.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

Is it safe to discontinue primary Pneumocystis jiroveci pneumonia prophylaxis in patients with virologically suppressed HIV infection and a CD4 cell count <200 cells/microL?

Current guidelines suggest that primary prophylaxis for Pneumocystis jiroveci pneumonia (PcP) can be safely stopped in human immunodeficiency virus (HIV)-infected patients who are receiving combined antiretroviral therapy (cART) and who have a CD4 cell count >200 cells/microL. There are few data regarding the incidence of PcP or safety of stopping prophylaxis in virologically suppressed patients with CD4 cell counts of 101-200 cells/microL.

Development and validation of decision rules to guide frequency of monitoring CD4 cell count in HIV-1 infection before starting antiretroviral therapy

Background Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study. Methodology/Principal Findings We built up two prediction rules (“Snap-shot rule” for a single sample and “Track-shot rule” for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior ≥5% or <5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200×106/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold. Conclusions/Significance Frequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count >650 for a threshold of 200, >900 for 350, or >1150 for 500×106/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.