Species and seasonality can affect recent trends in beak and feather disease virus prevalence in captive psittacine birds.

Beak and feather disease virus (BFDV) is globally distributed in psittacine birds. BFDV is considered a key threat to biodiversity because it has the ability to transmit and shift between host species. Data from captive psittacine birds can help to identify potential risk factors for viral transmission management. Generalized Linear Models (GLM) were used to examine the association of sample type, species, and season on the prevalence of BFDV in captive exotic birds in Thailand. In this study, the overall prevalence of BFDV was 8.2 %, with 346 of 4243 birds being positive. The prevalence in feather samples (12.1 %) and pooled (dried blood and feather) samples (15.4 %) was higher than that in the dried blood samples (4.8 %). A GLM test revealed that the sample type, species, and season were significant factors influencing the prevalence of BFDV. Based on the model, two species (blue-eyed cockatoo; Cacatua ophthalmica, and ring-necked parakeet; Psittacula krameri) were associated with higher BFDV prevalence. By studying the seasonal BFDV prevalence, we can gather important insights into the environmental factors that contribute to its spread. The higher prevalence observed during the wet season suggest a possible affect between BFDV prevalence and environmental factors such as heavy rainfall and humidity. In conclusion, our analysis of the trends in BFDV prevalence offers valuable insights into the prevalence or distribution of BFDV in the studied population. By monitoring BFDV prevalence, identifying high-risk species, and understanding seasonal patterns, we can develop targeted management approaches to control the spread of the virus. This information is crucial for mitigating the impact of BFDV on aviculture.

Efecto de factores sociodemográficos en la mortalidad del COVID-19 en Costa Rica: un enfoque geográfico

Introducción: La enfermedad por coronavirus (COVID-19) se ha extendido entre la población de todo el país y ha tenido un gran impacto a nivel mundial. Sin embargo, existen diferencias geográficas importantes en la mortalidad de COVID-19 entre las diferentes regiones del mundo y en Costa Rica. Objetivo: Explorar el efecto de algunos de los factores sociodemográficos en la mortalidad de COVID-19 en pequeñas divisiones geográficas o cantones de Costa Rica. Métodos: Usamos registros oficiales y aplicamos un modelo de regresión clásica de Poisson y un modelo de regresión ponderada geográficamente. Resultados: Obtuvimos un criterio de información de Akaike (AIC) más bajo con la regresión ponderada (927.1 en la regresión de Poison versus 358.4 en la regresión ponderada). Los cantones con un mayor riesgo de mortalidad por COVID-19 tuvo una población más densa; bienestar material más alto; menor proporción de cobertura de salud y están ubicadas en el área del Pacífico de Costa Rica. Conclusiones: Una estrategia de intervención de COVID-19 específica debería concentrarse en áreas de la costa pacífica con poblaciones más densas, mayor bienestar material y menor población por unidad de salud.

Introduction: The coronavirus disease (COVID-19) has spread among the population of Costa Rica and has had a great global impact. However, there are important geographic differences in mortality from COVID-19 among world regions and within Costa Rica. Objective: To explore the effect of some sociodemographic factors on COVID-19 mortality in the small geographic divisions or cantons of Costa Rica. Methods: We used official records and applied a classical epidemiological Poisson regression model and a geographically weighted regression model. Results: We obtained a lower Akaike Information Criterion with the weighted regression (927.1 in Poisson regression versus 358.4 in weighted regression). The cantons with higher risk of mortality from COVID-19 had a denser population; higher material well-being; less population by health service units and are located near the Pacific coast. Conclusions: A specific COVID-19 intervention strategy should concentrate on Pacific coast areas with denser population, higher material well-being and less population by health service units.

Differentinating between non-transfusion dependant ß-thalassemia and iron deficinecy anemia in children using ROC and logistic regression analysis: two novel discrimination indices designed for pediatric patients.

Introduction: This cross-sectional study enrolled a group of 271 children with microcytic anemia in order to test the performance of 41 single and 2 composite formulas andindices in distinguishing between ß-thalassemia (ß-thal) and iron deficiency anemia (IDA) in the pediatric population. Methods: Optimal pediatric cut-off values from the previously published formulas and indices were generated using ROC analysis. Logistic regression in R using generalized linear models (GLM) generated two new indices. Results: Formulas and indices with optimal cut-offvalues in children with accuracy ≥90% were (in descending order): Matos & Carvalho index, MDHL(Telmissani) formula, England and Fraser formula, Pornprasert index, Sirachainan index, Telmissani (MCHD) formula, CRUISE index, Hameed index, Sargolzaie formula and Zaghloul II index. The CroThalDD-LM1 index has an accuracy of 93.36% (AUC 0.986, 95% CI 0.975-0.997), while the second CroThalDD-LM2 index utilizes absolute reticulocyte count alongside CBC variables, with an accuracy of 96.77% (AUC 0.985, 95% CI 0.988-0.999). Discussion and conclusion: We recommend using aforementioned formulas and indices with corrected cut-off values and accuracy >90% alongside two new proposed indices. A comparison of both native and these new indices is encouraged. These are the first discrimination indices generated and designed precisely for the pediatric population, which includes preschool children.

The Association Between Polymorphisms in Cell-Cycle Genes and Mitochondrial DNA Copy Number in Coke Oven Workers.

The mitochondrial DNA (mtDNA) copy number is a vital component in maintaining normal mitochondrial function. It is affected by environmental and occupational exposures, as well as polymorphisms in nuclear genes. Nonetheless, the specific roles of polymorphisms in cell-cycle genes and mtDNA copy number are still unknown. This study enrolled a sample of 544 coke oven workers and 238 non-exposed controls so as to assess the effect of exposure of coke oven emissions (COEs) and polymorphisms in cell-cycle genes on the mtDNA copy number. We found that the mtDNA copy number in the exposed group (0.60 ± 0.29) was significantly lower than that in the control group (1.03 ± 0.31) (t =18.931, P < 0.001). The analysis of covariance showed that both the rs1801270 (CA+CC) and the rs1059234 (CT+CC) in p21 gene were associated with lower mtDNA copy number in the exposed group (P = 0.001). Generalized linear models indicated COEs-exposure (ß = -0.432, P < 0.001) and rs1059234 (CT+CC) in p21 gene (ß = -0.060, P = 0.024) were the factors in mtDNA copy number reduction. In conclusion, this study suggests that the decrease of the mtDNA copy number is associated with COEs-exposure and the rs1059234 (CT+CC) in the p21 gene.

Using Tweedie distributions for fitting spike count data.

BACKGROUND: The nature of spike count distributions is of great practical concern for the analysis of neural data. These distributions often have a tendency for 'failures' and a long tail of large counts, and may show a strong dependence of variance on the mean. Furthermore, spike count distributions often show multiplicative rather than additive effects of covariates. We analyzed the responses of neurons in primary auditory cortex to transposed stimuli as a function of interaural time differences (ITD). In more than half of the cases, the variance of neuronal responses showed a supralinear dependence on the mean spike count. NEW METHOD: We explored the use of the Tweedie family of distributions, which has a supralinear dependence of means on variances. To quantify the effects of ITD on neuronal responses, we used generalized linear models (GLMs), and developed methods for significance testing under the Tweedie assumption. RESULTS: We found the Tweedie distribution to be generally a better fit to the data than the Poisson distribution for over-dispersed responses. COMPARISON WITH EXISTING METHODS: Standard analysis of variance wrongly assumes Gaussian distributions with fixed variance and additive effects, but even generalized models under Poisson assumptions may be hampered by the over-dispersion of spike counts. The use of GLMs assuming Tweedie distributions increased the reliability of tests of sensitivity to ITD in our data. CONCLUSIONS: When spike count variance depends strongly on the mean, the use of Tweedie distributions for analyzing the data is advised.