Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

Summary .  We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a   ℓ₂   penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial.     

Bayesian Nonparametric Modeling for Comparison of Single-Neuron Firing Intensities

Summary .  We propose a fully inferential model-based approach to the problem of comparing the firing patterns of a neuron recorded under two distinct experimental conditions. The methodology is based on nonhomogeneous Poisson process models for the firing times of each condition with flexible nonparametric mixture prior models for the corresponding intensity functions. We demonstrate posterior inferences from a global analysis, which may be used to compare the two conditions over the entire experimental time window, as well as from a pointwise analysis at selected time points to detect local deviations of firing patterns from one condition to another. We apply our method on two neurons recorded from the primary motor cortex area of a monkey's brain while performing a sequence of reaching tasks.     

The Influence of Changes in Magnetic Variations and Light–Dark Cycle on Life-History Traits of Daphnia magna

Day–night cycle is the main zeitgeber (time giver) for biological circadian rhythms. Recently, it was suggested that natural diurnal geomagnetic variation may also be utilized by organisms for the synchronization of these rhythms. In this study, life-history traits in Daphnia magna were evaluated after short-term and multigenerational exposure to 16 h day/8 h night cycle, 32 h day/16 h night cycle, diurnal geomagnetic variation of 24 h, simulated magnetic variation of 48 h, and combinations of these conditions. With short-term exposure, the lighting mode substantially influenced the brood to brood period and the lifespan in daphnids. The brood to brood period, brood size, and body length of crustaceans similarly depended on the lighting mode during the multigenerational exposure. At the same time, an interaction of lighting mode and magnetic variations affected to a lesser extent brood to brood period, brood size, and newborn's body length. The influence of simulated diurnal variation on life-history traits in daphnids appeared distinctly as effects of synchronization between periods of lighting mode and magnetic variations during the multigenerational exposure. Newborn's body length significantly depended on the lighting regime when the periods of both studied zeitgebers were unsynchronized, or on the interaction of light regime with magnetic variations when the periods were synchronized. These results confirm the hypothesis that diurnal geomagnetic variation is an additional zeitgeber for biological circadian rhythms. Possible mechanisms for these observed effects are discussed. Bioelectromagnetics. © 2020 Bioelectromagnetics Society     

Optimization of pancreatic lipase inhibition by Cudrania tricuspidata fruits using response surface methodology

The fruits of Cudrania tricuspidata (Carr.) Bur. (Moraceae) significantly inhibited pancreatic lipase, which plays a key role in fat absorption. Optimization of extraction conditions with minimum pancreatic lipase activity and maximum yield was determined using response surface methodology with three-level-three-factor Box–Behnken design (BBD). Regression analysis showed a good fit of the experimental data and the optimal condition was obtained as ethanol concentration, 74.5%; temperature 61.9 °C and extraction time, 13.5 h. The pancreatic lipase activity and extraction yield under optimal conditions were found to be 65.5% and 54.0%, respectively, which were well matched with the predicted value of 65.8% and 47.1%. Further fractionation of C. tricuspidata extract resulted in the isolation of compound 1, which was identified as 5,7,4′-trihydroxy-6,8-diprenylisoflavone. It inhibited pancreatic lipase activity with IC₅₀ value of 65.0 μM. HPLC analysis suggested positive correlation between pancreatic lipase inhibition and 5,7,4′-trihydroxy-6,8-diprenylisoflavone of C. tricuspidata fruits.     

Analysis of potassium iodate reduction in tissue homogenates using high performance liquid chromatography–inductively coupled plasma-mass spectrometry

Potassium iodate (KIO₃) and potassium iodide (KI) are the major salt iodization agents used worldwide. Unlike iodide (I⁻), iodate (IO₃⁻) should be reduced to I⁻ before it can be effectively used by the thyroid. In this study, we developed a new method for analyzing IO₃⁻ and I⁻ in tissue homogenates using high performance liquid chromatography coupled to inductively coupled plasma mass spectrometry (HPLC–ICP-MS). We further applied the method to demonstrate the KIO₃ reduction process by tissues in vitro. The effects of KIO₃ on the total antioxidative activity (TAA) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) were also investigated here. Finally, we found that IO₃⁻ can be reduced to I⁻ by tissue homogenates and IO₃⁻ irreversibly decreases the antioxidant capability of tissues. Our studies suggest that KIO₃ might have a big effect on the redox balance of tissue and would further result in oxidative stress of organisms.     

Estimating the human appropriation of land in Brazil by means of an Input–Output Economic Model and Ecological Footprint analysis

As we confront the current environmental crisis, determining the biophysical base (e.g., materials, energy, land, and water) of nations has become paramount. With advanced economies benefiting from the import of resource-intensive primary goods originating from poorer parts of the world, especially emerging nations, these are dilapidating their natural capital. Brazil is one of such emerging economies, whose mining and farming activities, propping up its export-led economic growth, exert great pressure on the environment. In particular, farming has been shown to have one of the world's greatest environmental impacts, especially as a consequence of land use associated with cattle ranching. Since a nation-wide evaluation of land-use types across the whole sectorial spectrum of the country's economy is still lacking, we used the most recently available Input–Output Economic Model for Brazil and the Ecological Footprint method to identify those economic sectors with the greatest potential for appropriating portions of the natural world.Our results show that: (i) the biggest chunk of Brazil's Ecological Footprint is due to its Carbon Footprint and, in particular, emissions from cattle; (ii) only a few economic sectors exhibit high Ecological Footprint values, chiefly those belonging to livestock farming and energy production based on fossil fuels; (iii) excluding the soybeans and slaughter sectors, export-oriented sectors have below-average Ecological Footprint values; and (iv) the percentage of Brazil's Ecological Footprint due to household consumption (excluding imports) is three times bigger than that attributable to exports, with sectors belonging to livestock farming contributing the most to such disparity.These results underscore that the environmental impact of the Brazilian economy can be drastically reduced by tackling the emission-intensive production processes of a few sectors only and disincentivizing the domestic consumption of a narrow range of products, especially with respect to the livestock segment.     

Wildcat population density in NE Portugal: A regional stronghold for a nationally threatened felid

Population density data on depleted and endangered wildlife species are essential to assure their effective management and, ultimately, conservation. The European wildcat is an elusive and threatened species inhabiting the Iberian Peninsula, with fragmented populations and living in low densities. We fitted spatial capture–recapture models on camera-trap data, to provide the first estimate of wildcat density for Portugal and assess the most influential drivers determining it. The study was implemented in Montesinho Natural Park (NE Portugal), where we identified nine individuals, over a total effort of 3,477 trap-nights. The mean density estimate was 0.032 ± 0.012 wildcat/km², and density tended to increase with distance to humanized areas, often linked to lower human disturbance and domestic cat presence, with forest and herbaceous vegetation cover and with European rabbit abundance. Although, this density estimate is within the range of values estimated for protected areas elsewhere in the Iberian Peninsula, our estimates are low at the European level. When put in context, our results highlight that European wildcats may be living in low population densities across the Iberian Mediterranean biogeographic region. No phenotypic domestic or hybrid cats were detected, suggesting potentially low admixture rates between the two species, although genetic sampling would be required to corroborate this assertion. We provide evidence that Montesinho Natural Park may be a suitable area to host a healthy wildcat population, and thus be an important protected area in this species' conservation context.