Abbas Pak, M. E. Ghitany, Mohammad Reza Mahmoudi.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 4, 894--914.

Abstract:
This paper focuses on Bayesian estimation of the parameters and reliability function of the power Lindley distribution by using various symmetric and asymmetric loss functions. Assuming suitable priors on the parameters, Bayes estimates are derived by using squared error, linear exponential (linex) and general entropy loss functions. Since, under these loss functions, Bayes estimates of the parameters do not have closed forms we use lindley’s approximation technique to calculate the Bayes estimates. Moreover, we obtain the Bayes estimates of the parameters using a Markov Chain Monte Carlo (MCMC) method. Simulation studies are conducted in order to evaluate the performances of the proposed estimators under the considered loss functions. Finally, analysis of a real data set is presented for illustrative purposes.

Marco A. R. Ferreira.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 4, 734--744.

Abstract:
We study the limiting behavior of the one-at-a-time Gibbs sampler for the intrinsic conditional autoregressive model with centering on the fly. The intrinsic conditional autoregressive model is widely used as a prior for random effects in hierarchical models for spatial modeling. This model is defined by full conditional distributions that imply an improper joint “density” with a multivariate Gaussian kernel and a singular precision matrix. To guarantee propriety of the posterior distribution, usually at the end of each iteration of the Gibbs sampler the random effects are centered to sum to zero in what is widely known as centering on the fly. While this works well in practice, this informal computational way to recenter the random effects obscures their implied prior distribution and prevents the development of formal Bayesian procedures. Here we show that the implied prior distribution, that is, the limiting distribution of the one-at-a-time Gibbs sampler for the intrinsic conditional autoregressive model with centering on the fly is a singular Gaussian distribution with a covariance matrix that is the Moore–Penrose inverse of the precision matrix. This result has important implications for the development of formal Bayesian procedures such as reference priors and Bayes-factor-based model selection for spatial models.

Emilia Athayde, Assis Azevedo, Michelli Barros, Víctor Leiva.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 301--328.

Abstract:
The Birnbaum–Saunders (BS) distribution has been largely studied and applied. A random variable with BS distribution is a transformation of another random variable with standard normal distribution. Generalized BS distributions are obtained when the normally distributed random variable is replaced by another symmetrically distributed random variable. This allows us to obtain a wide class of positively skewed models with lighter and heavier tails than the BS model. Its failure rate admits several shapes, including the unimodal case, with its change-point being able to be used for different purposes. For example, to establish the reduction in a dose, and then in the cost of the medical treatment. We analyze the failure rates of generalized BS distributions obtained by the logistic, normal and Student-t distributions, considering their shape and change-point, estimating them, evaluating their robustness, assessing their performance by simulations, and applying the results to real data from different areas.

In this paper we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy measures. Further, we propose a new regression model with censored data based on the bimodal gamma distribution. This regression model can be very useful to the analysis of real data and could give more realistic fits than other special regression models. Monte Carlo simulations were performed to check the bias in the maximum likelihood estimation. The proposed models are applied to two real data sets found in literature.

Area under ROC curve (AUC) is a widely used performance measure for classification models. We propose two new distributionally robust AUC maximization models (DR-AUC) that rely on the Kantorovich metric and approximate the AUC with the hinge loss function. We consider the two cases with respectively fixed and variable support for the worst-case distribution. We use duality theory to reformulate the DR-AUC models and derive tractable convex optimization problems. The numerical experiments show that the proposed DR-AUC models -- benchmarked with the standard deterministic AUC and the support vector machine models - perform better in general and in particular improve the worst-case out-of-sample performance over the majority of the considered datasets, thereby showing their robustness. The results are particularly encouraging since our numerical experiments are conducted with training sets of small size which have been known to be conducive to low out-of-sample performance.

The Rosenbrock function is an ubiquitous benchmark problem for numerical optimisation, and variants have been proposed to test the performance of Markov Chain Monte Carlo algorithms. In this work we discuss the two-dimensional Rosenbrock density, its current $n$-dimensional extensions, and their advantages and limitations. We then propose a new extension to arbitrary dimensions called the Hybrid Rosenbrock distribution, which is composed of conditional normal kernels arranged in such a way that preserves the key features of the original kernel. Moreover, due to its structure, the Hybrid Rosenbrock distribution is analytically tractable and possesses several desirable properties, which make it an excellent test model for computational algorithms.

In causal settings, such as instrumental variable settings, it is well known that estimators based on ordinary least squares (OLS) can yield biased and non-consistent estimates of the causal parameters. This is partially overcome by two-stage least squares (TSLS) estimators. These are, under weak assumptions, consistent but do not have desirable finite sample properties: in many models, for example, they do not have finite moments. The set of K-class estimators can be seen as a non-linear interpolation between OLS and TSLS and are known to have improved finite sample properties. Recently, in causal discovery, invariance properties such as the moment criterion which TSLS estimators leverage have been exploited for causal structure learning: e.g., in cases, where the causal parameter is not identifiable, some structure of the non-zero components may be identified, and coverage guarantees are available. Subsequently, anchor regression has been proposed to trade-off invariance and predictability. The resulting estimator is shown to have optimal predictive performance under bounded shift interventions. In this paper, we show that the concepts of anchor regression and K-class estimators are closely related. Establishing this connection comes with two benefits: (1) It enables us to prove robustness properties for existing K-class estimators when considering distributional shifts. And, (2), we propose a novel estimator in instrumental variable settings by minimizing the mean squared prediction error subject to the constraint that the estimator lies in an asymptotically valid confidence region of the causal parameter. We call this estimator PULSE (p-uncorrelated least squares estimator) and show that it can be computed efficiently, even though the underlying optimization problem is non-convex. We further prove that it is consistent.

This paper revisits the problem of computing empirical cumulative distribution functions (ECDF) efficiently on large, multivariate datasets. Computing an ECDF at one evaluation point requires $mathcal{O}(N)$ operations on a dataset composed of $N$ data points. Therefore, a direct evaluation of ECDFs at $N$ evaluation points requires a quadratic $mathcal{O}(N^2)$ operations, which is prohibitive for large-scale problems. Two fast and exact methods are proposed and compared. The first one is based on fast summation in lexicographical order, with a $mathcal{O}(N{log}N)$ complexity and requires the evaluation points to lie on a regular grid. The second one is based on the divide-and-conquer principle, with a $mathcal{O}(Nlog(N)^{(d-1){vee}1})$ complexity and requires the evaluation points to coincide with the input points. The two fast algorithms are described and detailed in the general $d$-dimensional case, and numerical experiments validate their speed and accuracy. Secondly, the paper establishes a direct connection between cumulative distribution functions and kernel density estimation (KDE) for a large class of kernels. This connection paves the way for fast exact algorithms for multivariate kernel density estimation and kernel regression. Numerical tests with the Laplacian kernel validate the speed and accuracy of the proposed algorithms. A broad range of large-scale multivariate density estimation, cumulative distribution estimation, survival function estimation and regression problems can benefit from the proposed numerical methods.

Zhou Fan, Iain M. Johnstone.

Source: The Annals of Statistics, Volume 47, Number 5, 2855--2886.

Abstract:
We study the spectra of MANOVA estimators for variance component covariance matrices in multivariate random effects models. When the dimensionality of the observations is large and comparable to the number of realizations of each random effect, we show that the empirical spectra of such estimators are well approximated by deterministic laws. The Stieltjes transforms of these laws are characterized by systems of fixed-point equations, which are numerically solvable by a simple iterative procedure. Our proof uses operator-valued free probability theory, and we establish a general asymptotic freeness result for families of rectangular orthogonally invariant random matrices, which is of independent interest. Our work is motivated in part by the estimation of components of covariance between multiple phenotypic traits in quantitative genetics, and we specialize our results to common experimental designs that arise in this application.

Peng Shi, Zifeng Zhao.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 357--380.

Abstract:
In actuarial research a task of particular interest and importance is to predict the loss cost for individual risks so that informative decisions are made in various insurance operations such as underwriting, ratemaking and capital management. The loss cost is typically viewed to follow a compound distribution where the summation of the severity variables is stopped by the frequency variable. A challenging issue in modeling such outcomes is to accommodate the potential dependence between the number of claims and the size of each individual claim. In this article we introduce a novel regression framework for compound distributions that uses a copula to accommodate the association between the frequency and the severity variables and, thus, allows for arbitrary dependence between the two components. We further show that the new model is very flexible and is easily modified to account for incomplete data due to censoring or truncation. The flexibility of the proposed model is illustrated using both simulated and real data sets. In the analysis of granular claims data from property insurance, we find substantive negative relationship between the number and the size of insurance claims. In addition, we demonstrate that ignoring the frequency-severity association could lead to biased decision-making in insurance operations.

Lisa Schlosser, Torsten Hothorn, Reto Stauffer, Achim Zeileis.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1564--1589.

Abstract:
To obtain a probabilistic model for a dependent variable based on some set of explanatory variables, a distributional approach is often adopted where the parameters of the distribution are linked to regressors. In many classical models this only captures the location of the distribution but over the last decade there has been increasing interest in distributional regression approaches modeling all parameters including location, scale and shape. Notably, so-called nonhomogeneous Gaussian regression (NGR) models both mean and variance of a Gaussian response and is particularly popular in weather forecasting. Moreover, generalized additive models for location, scale and shape (GAMLSS) provide a framework where each distribution parameter is modeled separately capturing smooth linear or nonlinear effects. However, when variable selection is required and/or there are nonsmooth dependencies or interactions (especially unknown or of high-order), it is challenging to establish a good GAMLSS. A natural alternative in these situations would be the application of regression trees or random forests but, so far, no general distributional framework is available for these. Therefore, a framework for distributional regression trees and forests is proposed that blends regression trees and random forests with classical distributions from the GAMLSS framework as well as their censored or truncated counterparts. To illustrate these novel approaches in practice, they are employed to obtain probabilistic precipitation forecasts at numerous sites in a mountainous region (Tyrol, Austria) based on a large number of numerical weather prediction quantities. It is shown that the novel distributional regression forests automatically select variables and interactions, performing on par or often even better than GAMLSS specified either through prior meteorological knowledge or a computationally more demanding boosting approach.

Yanjun Qian, Jianhua Z. Huang, Chiwoo Park, Yu Ding.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1537--1563.

Abstract:
In situ transmission electron microscope (TEM) adds a promising instrument to the exploration of the nanoscale world, allowing motion pictures to be taken while nano objects are initiating, crystalizing and morphing into different sizes and shapes. To enable in-process control of nanocrystal production, this technology innovation hinges upon a solution addressing a statistical problem, which is the capability of online tracking a dynamic, time-varying probability distribution reflecting the nanocrystal growth. Because no known parametric density functions can adequately describe the evolving distribution, a nonparametric approach is inevitable. Towards this objective, we propose to incorporate the dynamic evolution of the normalized particle size distribution into a state space model, in which the density function is represented by a linear combination of B-splines and the spline coefficients are treated as states. The closed-form algorithm runs online updates faster than the frame rate of the in situ TEM video, making it suitable for in-process control purpose. Imposing the constraints of curve smoothness and temporal continuity improves the accuracy and robustness while tracking the probability distribution. We test our method on three published TEM videos. For all of them, the proposed method is able to outperform several alternative approaches.

Kamran Kalbasi, Thomas Mountford.

Source: Bernoulli, Volume 26, Number 2, 1504--1534.

Abstract:
In this paper, we study the local times of vector-valued Gaussian fields that are ‘diagonally operator-self-similar’ and whose increments are stationary. Denoting the local time of such a Gaussian field around the spatial origin and over the temporal unit hypercube by $Z$, we show that there exists $lambdain(0,1)$ such that under some quite weak conditions, $lim_{n ightarrow+infty}frac{sqrt[n]{mathbb{E}(Z^{n})}}{n^{lambda}}$ and $lim_{x ightarrow+infty}frac{-logmathbb{P}(Z>x)}{x^{frac{1}{lambda}}}$ both exist and are strictly positive (possibly $+infty$). Moreover, we show that if the underlying Gaussian field is ‘strongly locally nondeterministic’, the above limits will be finite as well. These results are then applied to establish similar statements for the intersection local times of diagonally operator-self-similar Gaussian fields with stationary increments.

Yating Liu, Gilles Pagès.

Source: Bernoulli, Volume 26, Number 2, 1171--1204.

Abstract:
We establish conditions to characterize probability measures by their $L^{p}$-quantization error functions in both $mathbb{R}^{d}$ and Hilbert settings. This characterization is two-fold: static (identity of two distributions) and dynamic (convergence for the $L^{p}$-Wasserstein distance). We first propose a criterion on the quantization level $N$, valid for any norm on $mathbb{R}^{d}$ and any order $p$ based on a geometrical approach involving the Voronoï diagram. Then, we prove that in the $L^{2}$-case on a (separable) Hilbert space, the condition on the level $N$ can be reduced to $N=2$, which is optimal. More quantization based characterization cases in dimension 1 and a discussion of the completeness of a distance defined by the quantization error function can be found at the end of this paper.

Jarno Vanhatalo, Marcelo Hartmann, Lari Veneranta.

Source: Bayesian Analysis, Volume 15, Number 2, 415--447.

Abstract:
Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description for species distribution response along environmental covariates and the spatial random effect that captures deviations from the distribution patterns explained by environmental covariates. Joint species distribution models (JSDMs) additionally include interspecific correlations which have been shown to improve their descriptive and predictive performance compared to single species models. However, current JSDMs are restricted to hierarchical generalized linear modeling framework. Their limitation is that parametric models have trouble in explaining changes in abundance due, for example, highly non-linear physical tolerance limits which is particularly important when predicting species distribution in new areas or under scenarios of environmental change. On the other hand, semi-parametric response functions have been shown to improve the predictive performance of SDMs in these tasks in single species models. Here, we propose JSDMs where the responses to environmental covariates are modeled with additive multivariate Gaussian processes coded as linear models of coregionalization. These allow inference for wide range of functional forms and interspecific correlations between the responses. We propose also an efficient approach for inference with Laplace approximation and parameterization of the interspecific covariance matrices on the Euclidean space. We demonstrate the benefits of our model with two small scale examples and one real world case study. We use cross-validation to compare the proposed model to analogous semi-parametric single species models and parametric single and joint species models in interpolation and extrapolation tasks. The proposed model outperforms the alternative models in all cases. We also show that the proposed model can be seen as an extension of the current state-of-the-art JSDMs to semi-parametric models.

Luis Gutiérrez, Eduardo Gutiérrez-Peña, Ramsés H. Mena.

Source: Bayesian Analysis, Volume 14, Number 2, 427--447.

Abstract:
This work presents a Bayesian predictive approach to statistical shape analysis. A modeling strategy that starts with a Gaussian distribution on the configuration space, and then removes the effects of location, rotation and scale, is studied. This boils down to an application of the projected normal distribution to model the configurations in the shape space, which together with certain identifiability constraints, facilitates parameter interpretation. Having better control over the parameters allows us to generalize the model to a regression setting where the effect of predictors on shapes can be considered. The methodology is illustrated and tested using both simulated scenarios and a real data set concerning eight anatomical landmarks on a sagittal plane of the corpus callosum in patients with autism and in a group of controls.

Yuan Ke, Stanislav Minsker, Zhao Ren, Qiang Sun, Wen-Xin Zhou.

Source: Statistical Science, Volume 34, Number 3, 454--471.

Abstract:
We provide a survey of recent results on covariance estimation for heavy-tailed distributions. By unifying ideas scattered in the literature, we propose user-friendly methods that facilitate practical implementation. Specifically, we introduce elementwise and spectrumwise truncation operators, as well as their $M$-estimator counterparts, to robustify the sample covariance matrix. Different from the classical notion of robustness that is characterized by the breakdown property, we focus on the tail robustness which is evidenced by the connection between nonasymptotic deviation and confidence level. The key insight is that estimators should adapt to the sample size, dimensionality and noise level to achieve optimal tradeoff between bias and robustness. Furthermore, to facilitate practical implementation, we propose data-driven procedures that automatically calibrate the tuning parameters. We demonstrate their applications to a series of structured models in high dimensions, including the bandable and low-rank covariance matrices and sparse precision matrices. Numerical studies lend strong support to the proposed methods.

Georg Lindgren.

Source: Statistical Science, Volume 34, Number 1, 100--128.

Abstract:
We describe and compare how methods based on the classical Rice’s formula for the expected number, and higher moments, of level crossings by a Gaussian process stand up to contemporary numerical methods to accurately deal with crossing related characteristics of the sample paths. We illustrate the relative merits in accuracy and computing time of the Rice moment methods and the exact numerical method, developed since the late 1990s, on three groups of distribution problems, the maximum over a finite interval and the waiting time to first crossing, the length of excursions over a level, and the joint period/amplitude of oscillations. We also treat the notoriously difficult problem of dependence between successive zero crossing distances. The exact solution has been known since at least 2000, but it has remained largely unnoticed outside the ocean science community. Extensive simulation studies illustrate the accuracy of the numerical methods. As a historical introduction an attempt is made to illustrate the relation between Rice’s original formulation and arguments and the exact numerical methods.

P Seguela
Feb 1, 1993; 13:596-604
Articles

Bank of Italy Working Papers by Giorgio Albareto, Andrea Cardillo, Andrea Hamaui and Giuseppe Marinelli

Bank of England Working Papers by Cristiano Cantore and Lukas Freund

The Education Department wants states to re-submit "equity plans" to ensure that effective teachers are matched with disadvantaged and minority students.

There have been no previous large studies of congenital heart disease in very low birth weight infants.

This study characterized the frequency, mortality rate, and lesion distribution of serious congenital heart disease in very low birth weight infants by using a large international multicenter database. (Read the full article)

New, effective approaches to obesity prevention are urgently needed. Social network interventions warrant our attention. Social networks play a significant role in adult and adolescent obesity. The role of social networks in pediatric obesity has not been examined.

Afterschool friendship ties play a critical role in setting physical activity patterns in children as young as 5 to 12 years. Children’s activity levels can be changed by the activity level of their social network during a 12-week afterschool program. (Read the full article)

Aspergillus niger, the third species responsible for invasive aspergillosis has been considered as a homogeneous species until DNA-based identification uncovered many cryptic species. These species have been recently reclassified into the Aspergillus section Nigri. However little is yet known among the section Nigri about the species distribution and the antifungal susceptibility pattern of each cryptic species. A total of 112 clinical isolates collected from 5 teaching hospitals in France and phenotypically identified as A. niger were analyzed. Identification to the species level was carried out by nucleotide sequence analysis. The Minimum Inhibitory Concentrations (MICs) of itraconazole, voriconazole, posaconazole, isavuconazole and amphotericin B were determined by both the EUCAST and gradient concentration strips methods. Aspergillus tubingensis (n=51, 45.5%) and A. welwitschiae (n=50, 44.6%) were the most common species while A. niger accounted for only 6.3% (n=7). The MICs of azoles drugs were higher for A. tubingensis than for A. welwitschiae. The MIC of amphotericin B was 2 mg/L or less for all isolates. Importantly, MICs determined by EUCAST showed no correlation with those determined by gradient concentration strips methods, these latter being lower than the former (Spearman's rank correlation tests ranging - depending on the antifungal agent - from 0.01 to 0.25; p>0.4). In conclusion, A. niger should be considered as a minority species in the section Nigri. The differences in MICs between species for different azoles underline the importance of accurate identification. Significant divergences in the determination of MIC between EUCAST and gradient concentration strips methods require further investigation.

Linezolid has strong antimicrobial activity against the multidrug-resistant (MDR) strains of Mycobacterium tuberculosis. Little is known about the distribution of linezolid in tuberculosis (TB) lesions in patients with MDR-TB. The aim of this study is to evaluate the distribution of linezolid in TB lesions in patients with spinal MDR-TB. Nine patients with spinal MDR-TB were enrolled prospectively from August 2019 to February 2020. The patients received a linezolid-containing anti-TB treatment regimen and needed surgery for the removal of TB lesions. During the operation, nine blood samples, eight diseased bone tissue samples, seven pus samples and four granulation tissue samples were collected simultaneously and 2 h after the oral administration of 600 mg of linezolid. Linezolid concentrations in plasma, diseased bone tissue, pus, and granulation tissue samples were subjected to high-performance liquid chromatography–tandem mass spectrometry. At sample collection, the mean concentrations of linezolid in plasma, diseased bone tissue, pus, and granulation tissue samples of the nine patients were 11.14 ± 5.82, 5.94 ± 4.27, 11.09 ± 4.58, 14.08 ± 10.61 mg/L, respectively. The mean ratios of linezolid concentration in diseased bone/plasma, pus/plasma, and granulation/plasma were 53.84%, 91.69%, and 103.57%, respectively. The mean ratios of linezolid concentration in pus/plasma and granulation/plasma were higher than those in diseased bone/plasma, and the difference was statistically significant (t =-2.810, p = 0.015; t =-4.901, p = 0.001). In conclusion, linezolid had different concentration distributions in different types of TB infected tissues in patients with spinal MDR-TB.

Lima, Peru, Apr 23, 2020 / 10:02 am (CNA).- As the ongoing coronavirus lockdown in Peru leaves the working poor in a vulnerable situation, one priest has been working to ensure that thousands in need have access to food.

Fr. Omar Sánchez Portillo is the secretary general of Caritas Lurín, on metro Lima’s south side.

Sánchez has distributed more than 15,000 food baskets, with the help of donors and volunteers at the Beatitudes Association, which he founded, since the nationwide quarantine was declared March 15. Peru’s Ministry of Health has confirmed 19,000 cases of coronavirus with 530 deaths.

Recently, Sánchez also received a donation of 5,000 live chickens from a poultry farm. He found himself needing to quickly process the chickens for distribution.

Sánchez turned to his fellow priests in the diocese of Lurín with an appeal on Whatsapp. To his surprise, almost 30 priests showed up to volunteer, including Bishop-elect Cristobal Mejía, who was recently named bishop of Chulucanas.

The priests and other volunteers worked all day, plucking, cleaning and preparing the birds for distribution.

“Today has been a long day,” Sánchez commented on his Facebook page. “Thank you dear priests! Thank you for your example, your work, and your joy. I feel proud to belong to a such an active, alive diocese so full of God, and to be part of a presbyterate full of holiness and enthusiasm for our priestly mission.”

In a statement to ACI Prensa, CNA’s Spanish language news partner, Sánchez noted that in the Diocese of Lurín, which is comprised of 55 parishes, there are many poor people who do not have access to electricity or running water.

The priest estimates about 60% of the people in the diocese live in extreme poverty. Southern Lima, where his diocese is located, contains the third and fourth most COVID-infected areas in the country.

Sánchez also pointed out that most Peruvians lack the ability to save money, which leaves vulnerable populations even more at risk during the quarantine.

“A lot of people are out of work and out on the street, a lot of them are temporary workers, many of them earn a living day-to-day,” he said.

So far, volunteers have distributed 75,000 food baskets throughout the South Lima area. However, the needs remain great.

“Every day in the parishes there are people out looking, knocking on doors, that haven’t gotten any food, or what they have gotten isn’t enough and has already run out,” he explained.

 

NEW CASTLE (March 28, 2019) – As part of its Community Naloxone Distribution initiative, the Division of Public Health (DPH) will hold two additional community naloxone distribution events in New Castle County next week. This initiative is part of a multi-pronged approach to address the opioid crisis and reduce the number of individuals dying from […]

I have written several articles about how to work with continuous probability distributions in SAS. I always emphasize that it is important to be able to compute the four essential functions for working with a statistical distribution. Namely, you need to know how to generate random values, how to compute [...]

The post The geometric distribution in SAS appeared first on The DO Loop.

…FG Urged To Involve Civil Society Groups  Minister of Humanitarian Affairs, Disaster Management and Social Development, Hajia Sadiya Umar Farouq, has been applauded for the successes recorded in providing palliatives for Nigerians to cushion the socio-economic effects of the lockdown and COVID-19 pandemic. This is coming as the Federal Government has been urged to involve […]

The post Palliatives Distribution:  Minister of Humanitarian receives accolades appeared first on Nigerian Pilot News.

Seven people were killed when protesters angry over what they see as unfair food aid distribution during the coronavirus pandemic clashed with police in Afghanistan's western Ghor province.

Seven people were killed when protesters angry over what they see as unfair food aid distribution during the coronavirus pandemic clashed with police in Afghanistan's western Ghor province on Saturday, according to a local member of parliament. Fourteen more were wounded during the protest - sparked by growing unhappiness at the distribution...

Our client briefing, “The final AIFMD cross-border fund distribution package: mapping the changes” published on 22 July 2019, provided a summary of the main changes introduced by Regulation (EU) 2019/1156 on facilitating cross-border d...

Fourteen more were wounded during the protest - sparked by growing unhappiness at the distribution allegedly favouring people with political connections, said Gulzaman Nayeb, a local lawmaker.

Approved project 50193-003 in India.

BACKGROUND:Electrical impedance tomography (EIT) is a noninvasive, portable lung imaging technique that provides functional distribution of ventilation. We aimed to describe the relationship between the distribution of ventilation by mode of ventilation and level of oxygenation impairment in children who are critically ill. We also aimed to describe the safety of EIT application.METHODS:A prospective observational study of EIT images obtained from subjects in the pediatric ICU. Images were categorized by whether the subjects were on intermittent mandatory ventilation (IMV), continuous spontaneous ventilation, or no positive-pressure ventilation. Images were categorized by the level of oxygenation impairment when using SpO2/FIO2. Distribution of ventilation is described by the center of ventilation.RESULTS:Sixty-four images were obtained from 25 subjects. Forty-two images obtained during IMV with a mean ± SD center of ventilation of 55 ± 6%, 14 images during continuous spontaneous ventilation with a mean ± SD center of ventilation of 48.1 ± 11%, and 8 images during no positive-pressure ventilation with a mean ± SD center of ventilation of 47.5 ± 10%. Seventeen images obtained from subjects with moderate oxygenation impairment with a mean ± SD center of ventilation of 59.3 ± 1.9%, 12 with mild oxygenation impairment with a mean ± SD center of ventilation of 52.6 ± 2.3%, and 4 without oxygenation impairment with a mean ± SD center of ventilation of 48.3 ± 4%. There was more ventral distribution of ventilation with IMV versus continuous spontaneous ventilation (P = .009), with IMV versus no positive-pressure ventilation (P = .01) cohorts, and with moderate oxygenation impairment versus cohorts without oxygenation impairment (P = .009). There were no adverse events related to the placement and use of EIT in our study.CONCLUSIONS:Children who had worse oxygen impairment or who received controlled modes of ventilation had more ventral distribution of ventilation than those without oxygen impairment or the subjects who were spontaneously breathing. The ability of EIT to detect changes in the distribution of ventilation in real time may allow for distribution-targeted mechanical ventilation strategies to be deployed proactively; however, future studies are needed to determine the effectiveness of such a strategy.

The kidneys play an important role in many processes, including urine formation, water conservation, acid-base equilibrium, and elimination of waste. The anatomic and functional development of the kidney has different maturation time points in humans versus animals, with critical differences between species in maturation before and after birth. Absorption, distribution, metabolism, and excretion (ADME) of drugs vary depending on age and maturation, which will lead to differences in toxicity and efficacy. When neonate/juvenile laboratory animal studies are designed, a thorough knowledge of the differences in kidney development between newborns/children and laboratory animals is essential. The human and laboratory animal data must be combined to obtain a more complete picture of the development in the kidneys around the neonatal period and the complexity of ADME in newborns and children. This review examines the ontogeny and cross-species differences in ADME processes in the developing kidney in preterm and term laboratory animals and children. It provides an overview of insights into ADME functionality in the kidney by identifying what is currently known and which gaps still exist. Currently important renal function properties such as glomerular filtration rate, renal blood flow, and ability to concentrate are generally well known, while detailed knowledge about transporter and metabolism maturation is growing but is still lacking. Preclinical data in those properties is limited to rodents and generally covers only the expression levels of transporter or enzyme-encoding genes. More knowledge on a functional level is needed to predict the kinetics and toxicity in neonate/juvenile toxicity and efficacy studies.

Radiohybrid PSMA (rhPSMA) ligands, a new class of theranostic prostate-specific membrane antigen (PSMA)–targeting agents, feature fast ¹⁸F synthesis and utility for labeling with radiometals. Here, we assessed the biodistribution and image quality of ¹⁸F-rhPSMA-7 to determine the best imaging time point for patients with prostate cancer. Methods: In total, 202 prostate cancer patients who underwent a clinically indicated ¹⁸F-rhPSMA-7 PET/CT were retrospectively analyzed, and 12 groups based on the administered activity and uptake time of PET scanning were created: 3 administered activities (low, 222–296 MBq; moderate, 297–370 MBq; and high, 371–444 MBq) and 4 uptake time points (short, 50–70 min; intermediate, 71–90 min; long, 91–110 min; and extra long, ≥111 min). For quantitative analyses, SUV_mean and organ- or tumor-to-background ratio were determined for background, healthy organs, and 3 representative tumor lesions. Qualitative analyses assessed overall image quality, nonspecific blood-pool activity, and background uptake in bone or marrow using 3- or 4-point scales. Results: In quantitative analyses, SUV_mean showed a significant decrease in the blood pool and lungs and an increase in the kidneys, bladder, and bones as the uptake time increased. SUV_mean showed a trend to increase in the blood pool and bones as the administered activity increased. However, no significant differences were found in 377 tumor lesions with respect to the administered activity or uptake time. In qualitative analyses, the overall image quality was stable along with the uptake time, but the proportion rated to have good image quality decreased as the administered activity increased. All other qualitative image parameters showed no significant differences for the administered activities, but they showed significant trends with increasing uptake time: less nonspecific blood activity, more frequent background uptake in the bone marrow, and increased negative impact on clinical decision making. Conclusion: The biodistribution of ¹⁸F-rhPSMA-7 was similar to that of established PSMA ligands, and tumor uptake of ¹⁸F-rhPSMA-7 was stable across the administered activities and uptake times. An early imaging time point (50–70 min) is recommended for ¹⁸F-rhPSMA-7 PET/CT to achieve the highest overall image quality.

Approximately 40% of patients with diabetic macular edema (DME) are resistant to anti–vascular endothelial growth factor (VEGF) therapy (rDME). Here, we demonstrate that significant correlations between inflammatory cytokines and VEGF, as observed in naive DME, are lost in patients with rDME. VEGF overexpression in the mouse retina caused delayed inflammatory cytokine upregulation, monocyte/macrophage infiltration (CD11b⁺ Ly6C⁺ CCR2⁺ cells), macrophage/microglia activation (CD11b⁺ CD80⁺ cells), and blood-retinal barrier disruption due to claudin-5 redistribution, which did not recover with VEGF blockade alone. Phosphorylated protein analysis of VEGF-overexpressed retinas revealed rho-associated coiled-coil–containing protein kinase (ROCK) activation. Administration of ripasudil, a selective ROCK inhibitor, attenuated retinal inflammation and claudin-5 redistribution. Ripasudil also contributed to the stability of claudin-5 expression by both transcriptional enhancement and degradation suppression in inflammatory cytokine–stimulated endothelium. Notably, the anti-VEGF agent and the ROCK inhibitor were synergic in suppressing cytokine upregulation, monocyte/macrophage infiltration, macrophage/microglia activation, and claudin-5 redistribution. Furthermore, in vitro analysis confirmed that claudin-5 redistribution depends on ROCK2 but not on ROCK1. This synergistic effect was also confirmed in human rDME cases. Our results suggest that ROCK-mediated claudin-5 redistribution by inflammation is a key mechanism in the anti-VEGF resistance of DME.

Manoella Gemaque Cavalcante, Cleusa Yoshiko Nagamachi, Julio Cesar Pieczarka, and Renata Coelho Rodrigues Noronha

Eukaryotic genomes exhibit substantial accumulation of repetitive DNA sequences. These sequences can participate in chromosomal reorganization events and undergo molecular cooption to interfere with the function and evolution of genomes. In turtles, repetitive DNA sequences appear to be accumulated at probable break points and may participate in events such as non-homologous recombination and chromosomal rearrangements. In this study, repeated sequences of 5S rDNA, U2 snRNA and Tc1/Mariner transposons were amplified from the genomes of the turtles, Podocnemis expansa and Podocnemis unifilis, and mapped by fluorescence in situ hybridization. Our data confirm the 2n=28 chromosomes for these species (the second lowest 2n in the order Testudines). We observe high conservation of the co-located 5S rDNA and U2 snRNA genes on a small chromosome pair (pair 13), and surmise that this represents the ancestral condition. Our analysis reveals a wide distribution of the Tc1/Mariner transposons and we discuss how the mobility of these transposons can act on karyotypic reorganization events (contributing to the 2n decrease of those species). Our data add new information for the order Testudines and provide important insights into the dynamics and organization of these sequences in the chelonian genomes.

Bacteria accumulate small, organic compounds called compatible solutes via uptake from the environment or biosynthesis from available precursors to maintain the turgor pressure of the cell in response to osmotic stress. The halophile Vibrio parahaemolyticus has biosynthesis pathways for the compatible solutes ectoine (encoded by ectABC-asp_ect) and glycine betaine (encoded by betIBA-proXWV), four betaine-carnitine-choline transporters (encoded by bccT1 to bccT4), and a second ProU transporter (encoded by proVWX). All of these systems are osmotically inducible with the exception of bccT2. Previously, it was shown that CosR, a MarR-type regulator, was a direct repressor of ectABC-asp_ect in Vibrio species. In this study, we investigated whether CosR has a broader role in the osmotic stress response. Expression analyses demonstrated that betIBA-proXWV, bccT1, bccT3, bccT4, and proVWX are repressed in low salinity. Examination of an in-frame cosR deletion mutant showed that expression of these systems is derepressed in the mutant at low salinity compared with the wild type. DNA binding assays demonstrated that purified CosR binds directly to the regulatory region of both biosynthesis systems and four transporters. In Escherichia coli green fluorescent protein (GFP) reporter assays, we demonstrated that CosR directly represses transcription of betIBA-proXWV, bccT3, and proVWX. Similar to Vibrio harveyi, we showed betIBA-proXWV was directly activated by the quorum-sensing LuxR homolog OpaR, suggesting a conserved mechanism of regulation among Vibrio species. Phylogenetic analysis demonstrated that CosR is ancestral to the Vibrionaceae family, and bioinformatics analysis showed widespread distribution among Gammaproteobacteria in general. Incidentally, in Aliivibrio fischeri, Aliivibrio finisterrensis, Aliivibrio sifiae, and Aliivibrio wodanis, an unrelated MarR-type regulator gene named ectR was clustered with ectABC-asp, which suggests the presence of another novel ectoine biosynthesis regulator. Overall, these data show that CosR is a global regulator of osmotic stress response that is widespread among bacteria.

IMPORTANCE Vibrio parahaemolyticus can accumulate compatible solutes via biosynthesis and transport, which allow the cell to survive in high salinity conditions. There is little need for compatible solutes under low salinity conditions, and biosynthesis and transporter systems need to be repressed. However, the mechanism(s) of this repression is not known. In this study, we showed that CosR played a major role in the regulation of multiple compatible solute systems. Phylogenetic analysis showed that CosR is present in all members of the Vibrionaceae family as well as numerous Gammaproteobacteria. Collectively, these data establish CosR as a global regulator of the osmotic stress response that is widespread in bacteria, controlling many more systems than previously demonstrated.

Doxycycline, an FDA-approved tetracycline, is used in tuberculosis in vivo models for the temporal control of mycobacterial gene expression. In these models, animals are infected with recombinant Mycobacterium tuberculosis carrying genes of interest under transcriptional control of the doxycycline-responsive TetR-tetO unit. To minimize fluctuations of plasma levels, doxycycline is usually administered in the diet. However, tissue penetration studies to identify the minimum doxycycline content in food achieving complete repression of TetR-controlled genes in tuberculosis (TB)-infected organs and lesions have not been conducted. Here, we first determined the tetracycline concentrations required to achieve silencing of M. tuberculosis target genes in vitro. Next, we measured doxycycline concentrations in plasma, major organs, and lung lesions in TB-infected mice and rabbits and compared these values to silencing concentrations measured in vitro. We found that 2,000 ppm doxycycline supplemented in mouse and rabbit feed is sufficient to reach target concentrations in TB lesions. In rabbit chow, the calcium content had to be reduced 5-fold to minimize chelation of doxycycline and deliver adequate oral bioavailability. Clearance kinetics from major organs and lung lesions revealed that doxycycline levels fall below concentrations that repress tet promoters within 7 to 14 days after doxycycline is removed from the diet. In summary, we have shown that 2,000 ppm doxycycline supplemented in standard mouse diet and in low-calcium rabbit diet delivers concentrations adequate to achieve full repression of tet promoters in infected tissues of mice and rabbits.

Although they are usually not considered to be diabetes complications, musculoskeletal disorders (MSKDs) are common in individuals with type 1 or type 2 diabetes and can strongly interfere with daily diabetes care, especially in people using diabetes technologies. The authors of this retrospective study in a population of 140 patients with type 1 diabetes report the distribution of subtypes of MSKDs and speculate about the mechanisms involved. The authors emphasize the need for multidisciplinary care involving not only the diabetes care team but also orthopedic surgeons. This report should lead to large, prospective studies to increase knowledge about these under-studied complications.