Delta said it is making the move to protect employees amid the coronavirus pandemic, but planes have been flying near empty

Some Buckeyes are not comfortable being told by a "woman in power" to quarantine, one expert said.

China says it will improve public health systems after criticism of its early response to the virus.

Kurtis Shuler, Marilou Sison-Mangus, Juhee Lee.

Source: Bayesian Analysis, Volume 15, Number 2, 559--578.

Abstract:
We propose a Bayesian sparse multivariate regression method to model the relationship between microbe abundance and environmental factors for microbiome data. We model abundance counts of operational taxonomic units (OTUs) with a negative binomial distribution and relate covariates to the counts through regression. Extending conventional nonlocal priors, we construct asymmetric nonlocal priors for regression coefficients to efficiently identify relevant covariates and their effect directions. We build a hierarchical model to facilitate pooling of information across OTUs that produces parsimonious results with improved accuracy. We present simulation studies that compare variable selection performance under the proposed model to those under Bayesian sparse regression models with asymmetric and symmetric local priors and two frequentist models. The simulations show the proposed model identifies important covariates and yields coefficient estimates with favorable accuracy compared with the alternatives. The proposed model is applied to analyze an ocean microbiome dataset collected over time to study the association of harmful algal bloom conditions with microbial communities.

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.

Antony Overstall, James McGree.

Source: Bayesian Analysis, Volume 15, Number 1, 103--131.

Abstract:
A Bayesian design is given by maximising an expected utility over a design space. The utility is chosen to represent the aim of the experiment and its expectation is taken with respect to all unknowns: responses, parameters and/or models. Although straightforward in principle, there are several challenges to finding Bayesian designs in practice. Firstly, the utility and expected utility are rarely available in closed form and require approximation. Secondly, the design space can be of high-dimensionality. In the case of intractable likelihood models, these problems are compounded by the fact that the likelihood function, whose evaluation is required to approximate the expected utility, is not available in closed form. A strategy is proposed to find Bayesian designs for intractable likelihood models. It relies on the development of an automatic, auxiliary modelling approach, using multivariate Gaussian process emulators, to approximate the likelihood function. This is then combined with a copula-based approach to approximate the marginal likelihood (a quantity commonly required to evaluate many utility functions). These approximations are demonstrated on examples of stochastic process models involving experimental aims of both parameter estimation and model comparison.

Stefano Peluso, Siddhartha Chib, Antonietta Mira.

Source: Bayesian Analysis, Volume 14, Number 3, 727--751.

Abstract:
We develop a general Bayesian semiparametric change-point model in which separate groups of structural parameters (for example, location and dispersion parameters) can each follow a separate multiple change-point process, driven by time-dependent transition matrices among the latent regimes. The distribution of the observations within regimes is unknown and given by a Dirichlet process mixture prior. The properties of the proposed model are studied theoretically through the analysis of inter-arrival times and of the number of change-points in a given time interval. The prior-posterior analysis by Markov chain Monte Carlo techniques is developed on a forward-backward algorithm for sampling the various regime indicators. Analysis with simulated data under various scenarios and an application to short-term interest rates are used to show the generality and usefulness of the proposed model.

Luis Gutiérrez, Andrés F. Barrientos, Jorge González, Daniel Taylor-Rodríguez.

Source: Bayesian Analysis, Volume 14, Number 2, 649--675.

Abstract:
We propose a Bayesian nonparametric strategy to test for differences between a control group and several treatment regimes. Most of the existing tests for this type of comparison are based on the differences between location parameters. In contrast, our approach identifies differences across the entire distribution, avoids strong modeling assumptions over the distributions for each treatment, and accounts for multiple testing through the prior distribution on the space of hypotheses. The proposal is compared to other commonly used hypothesis testing procedures under simulated scenarios. Two real applications are also analyzed with the proposed methodology.

Joris Mulder, Jean-Paul Fox.

Source: Bayesian Analysis, Volume 14, Number 2, 521--552.

Abstract:
The intraclass correlation plays a central role in modeling hierarchically structured data, such as educational data, panel data, or group-randomized trial data. It represents relevant information concerning the between-group and within-group variation. Methods for Bayesian hypothesis tests concerning the intraclass correlation are proposed to improve decision making in hierarchical data analysis and to assess the grouping effect across different group categories. Estimation and testing methods for the intraclass correlation coefficient are proposed under a marginal modeling framework where the random effects are integrated out. A class of stretched beta priors is proposed on the intraclass correlations, which is equivalent to shifted $F$ priors for the between groups variances. Through a parameter expansion it is shown that this prior is conditionally conjugate under the marginal model yielding efficient posterior computation. A special improper case results in accurate coverage rates of the credible intervals even for minimal sample size and when the true intraclass correlation equals zero. Bayes factor tests are proposed for testing multiple precise and order hypotheses on intraclass correlations. These tests can be used when prior information about the intraclass correlations is available or absent. For the noninformative case, a generalized fractional Bayes approach is developed. The method enables testing the presence and strength of grouped data structures without introducing random effects. The methodology is applied to a large-scale survey study on international mathematics achievement at fourth grade to test the heterogeneity in the clustering of students in schools across countries and assessment cycles.

Peter D. Hoff

Source: Bayesian Anal., Volume 6, Number 2, 179--196.

Abstract:
Modern datasets are often in the form of matrices or arrays, potentially having correlations along each set of data indices. For example, data involving repeated measurements of several variables over time may exhibit temporal correlation as well as correlation among the variables. A possible model for matrix-valued data is the class of matrix normal distributions, which is parametrized by two covariance matrices, one for each index set of the data. In this article we discuss an extension of the matrix normal model to accommodate multidimensional data arrays, or tensors. We show how a particular array-matrix product can be used to generate the class of array normal distributions having separable covariance structure. We derive some properties of these covariance structures and the corresponding array normal distributions, and show how the array-matrix product can be used to define a semi-conjugate prior distribution and calculate the corresponding posterior distribution. We illustrate the methodology in an analysis of multivariate longitudinal network data which take the form of a four-way array.

Nathan B. Cruze, Andreea L. Erciulescu, Balgobin Nandram, Wendy J. Barboza, Linda J. Young.

Source: Statistical Science, Volume 34, Number 2, 301--316.

Abstract:
In the United States, county-level estimates of crop yield, production, and acreage published by the United States Department of Agriculture’s National Agricultural Statistics Service (USDA NASS) play an important role in determining the value of payments allotted to farmers and ranchers enrolled in several federal programs. Given the importance of these official county-level crop estimates, NASS continually strives to improve its crops county estimates program in terms of accuracy, reliability and coverage. In 2015, NASS engaged a panel of experts convened under the auspices of the National Academies of Sciences, Engineering, and Medicine Committee on National Statistics (CNSTAT) for guidance on implementing models that may synthesize multiple sources of information into a single estimate, provide defensible measures of uncertainty, and potentially increase the number of publishable county estimates. The final report titled Improving Crop Estimates by Integrating Multiple Data Sources was released in 2017. This paper discusses several needs and requirements for NASS county-level crop estimates that were illuminated during the activities of the CNSTAT panel. A motivating example of planted acreage estimation in Illinois illustrates several challenges that NASS faces as it considers adopting any explicit model for official crops county estimates.

Víctor Elvira, Luca Martino, David Luengo, Mónica F. Bugallo.

Source: Statistical Science, Volume 34, Number 1, 129--155.

Abstract:
Importance sampling (IS) methods are broadly used to approximate posterior distributions or their moments. In the standard IS approach, samples are drawn from a single proposal distribution and weighted adequately. However, since the performance in IS depends on the mismatch between the targeted and the proposal distributions, several proposal densities are often employed for the generation of samples. Under this multiple importance sampling (MIS) scenario, extensive literature has addressed the selection and adaptation of the proposal distributions, interpreting the sampling and weighting steps in different ways. In this paper, we establish a novel general framework with sampling and weighting procedures when more than one proposal is available. The new framework encompasses most relevant MIS schemes in the literature, and novel valid schemes appear naturally. All the MIS schemes are compared and ranked in terms of the variance of the associated estimators. Finally, we provide illustrative examples revealing that, even with a good choice of the proposal densities, a careful interpretation of the sampling and weighting procedures can make a significant difference in the performance of the method.

Treat the babe in your life to one (or two or three) of these indulgent gifts.

And they’re available in 19 fun prints.

Barry E. Stein
Jan 2, 2020; 40:3-11
Viewpoints

Subhash Kulkarni
Oct 31, 2018; 38:9346-9354
Symposium and Mini-Symposium

Irune Diaz-Aparicio
Feb 12, 2020; 40:1453-1482
Development Plasticity Repair

Peter M. Zygmunt
Jun 1, 2002; 22:4720-4727
Behavioral

Barbara J. Weiland
Jan 28, 2015; 35:1505-1512
Neurobiology of Disease

RJ Wenthold
Mar 15, 1996; 16:1982-1989
Articles

Tatiana Stepanova
Apr 1, 2003; 23:2655-2664
Cellular

KM Harris
Jul 1, 1992; 12:2685-2705
Articles

Fiona Doetsch
Jul 1, 1997; 17:5046-5061
Articles

M Niethammer
Apr 1, 1996; 16:2157-2163
Articles

Thomas Schikorski
Aug 1, 1997; 17:5858-5867
Articles

Christelle Peyron
Dec 1, 1998; 18:9996-10015
Articles

HG Kuhn
Mar 15, 1996; 16:2027-2033
Articles

M Steriade
Aug 1, 1993; 13:3252-3265
Articles

Guo-qiang Bi
Dec 15, 1998; 18:10464-10472
Articles

CG Dotti
Apr 1, 1988; 8:1454-1468
Articles

Italian translation of the speech delivered by Mr Jaime Caruana, General Manager of the BIS, on the occasion of the Bank's Annual General Meeting, Basel, 25 June 2017.

To view more press releases, please visit http://www.snl.com/irweblinkx/news.aspx?iid=1024452.

To view more press releases, please visit http://www.snl.com/irweblinkx/news.aspx?iid=1024452.

The U.S. Postal Service recently has been battered by a decline in the number of packages it delivers, partly caused by the coronavirus situation. It reportedly is losing $2 billion each month and will be "illiquid" by Sept. 30. The USPS is chartered to do the hard and often unprofitable work no one else wants to do, but the White House has rejected talk of a bailout for the service.

You can reduce the story of CRM to a lot of things, especially its many component parts. Social networking, cloud computing and analytics are mentioned often. We don't need an exhaustive list, but if we stop there I think we miss a lot. To me CRM isn't about the parts, although like most people following the industry, I get a modicum of joy when a vendor adds something new to the toolbox.

Human ventral temporal cortex (VTC) is critical for visual recognition. It is thought that this ability is supported by large-scale patterns of activity across VTC that contain information about visual categories. However, it is unknown how category representations in VTC are organized at the submillimeter scale and across cortical depths. To fill this gap in knowledge, we measured BOLD responses in medial and lateral VTC to images spanning 10 categories from five domains (written characters, bodies, faces, places, and objects) at an ultra-high spatial resolution of 0.8 mm using 7 Tesla fMRI in both male and female participants. Representations in lateral VTC were organized most strongly at the general level of domains (e.g., places), whereas medial VTC was also organized at the level of specific categories (e.g., corridors and houses within the domain of places). In both lateral and medial VTC, domain-level and category-level structure decreased with cortical depth, and downsampling our data to standard resolution (2.4 mm) did not reverse differences in representations between lateral and medial VTC. The functional diversity of representations across VTC partitions may allow downstream regions to read out information in a flexible manner according to task demands. These results bridge an important gap between electrophysiological recordings in single neurons at the micron scale in nonhuman primates and standard-resolution fMRI in humans by elucidating distributed responses at the submillimeter scale with ultra-high-resolution fMRI in humans.

SIGNIFICANCE STATEMENT Visual recognition is a fundamental ability supported by human ventral temporal cortex (VTC). However, the nature of fine-scale, submillimeter distributed representations in VTC is unknown. Using ultra-high-resolution fMRI of human VTC, we found differential distributed visual representations across lateral and medial VTC. Domain representations (e.g., faces, bodies, places, characters) were most salient in lateral VTC, whereas category representations (e.g., corridors/houses within the domain of places) were equally salient in medial VTC. These results bridge an important gap between electrophysiological recordings in single neurons at a micron scale and fMRI measurements at a millimeter scale.

Prohibitin (PHB) is a critical protein involved in many cellular activities. In brain, PHB resides in mitochondria, where it forms a large protein complex with PHB2 in the inner TFmembrane, which serves as a scaffolding platform for proteins involved in mitochondrial structural and functional integrity. PHB overexpression at moderate levels provides neuroprotection in experimental brain injury models. In addition, PHB expression is involved in ischemic preconditioning, as its expression is enhanced in preconditioning paradigms. However, the mechanisms of PHB functional regulation are still unknown. Observations that nitric oxide (NO) plays a key role in ischemia preconditioning compelled us to postulate that the neuroprotective effect of PHB could be regulated by NO. Here, we test this hypothesis in a neuronal model of ischemia–reperfusion injury and show that NO and PHB are mutually required for neuronal resilience against oxygen and glucose deprivation stress. Further, we demonstrate that NO post-translationally modifies PHB through protein S-nitrosylation and regulates PHB neuroprotective function, in a nitric oxide synthase-dependent manner. These results uncover the mechanisms of a previously unrecognized form of molecular regulation of PHB that underlies its neuroprotective function.

SIGNIFICANCE STATEMENT Prohibitin (PHB) is a critical mitochondrial protein that exerts a potent neuroprotective effect when mildly upregulated in mice. However, how the neuroprotective function of PHB is regulated is still unknown. Here, we demonstrate a novel regulatory mechanism for PHB that involves nitric oxide (NO) and shows that PHB and NO interact directly, resulting in protein S-nitrosylation on residue Cys⁶⁹ of PHB. We further show that nitrosylation of PHB may be essential for its ability to preserve neuronal viability under hypoxic stress. Thus, our study reveals a previously unknown mechanism of functional regulation of PHB that has potential therapeutic implications for neurologic disorders.

To determine whether Cav1.2 voltage-gated Ca²⁺ channels contribute to astrocyte activation, we generated an inducible conditional knock-out mouse in which the Cav1.2 α subunit was deleted in GFAP-positive astrocytes. This astrocytic Cav1.2 knock-out mouse was tested in the cuprizone model of myelin injury and repair which causes astrocyte and microglia activation in the absence of a lymphocytic response. Deletion of Cav1.2 channels in GFAP-positive astrocytes during cuprizone-induced demyelination leads to a significant reduction in the degree of astrocyte and microglia activation and proliferation in mice of either sex. Concomitantly, the production of proinflammatory factors such as TNFα, IL1β and TGFβ1 was significantly decreased in the corpus callosum and cortex of Cav1.2 knock-out mice through demyelination. Furthermore, this mild inflammatory environment promotes oligodendrocyte progenitor cells maturation and myelin regeneration across the remyelination phase of the cuprizone model. Similar results were found in animals treated with nimodipine, a Cav1.2 Ca²⁺ channel inhibitor with high affinity to the CNS. Mice of either sex injected with nimodipine during the demyelination stage of the cuprizone treatment displayed a reduced number of reactive astrocytes and showed a faster and more efficient brain remyelination. Together, these results indicate that Cav1.2 Ca²⁺ channels play a crucial role in the induction and proliferation of reactive astrocytes during demyelination; and that attenuation of astrocytic voltage-gated Ca²⁺ influx may be an effective therapy to reduce brain inflammation and promote myelin recovery in demyelinating diseases.

SIGNIFICANCE STATEMENT Reducing voltage-gated Ca²⁺ influx in astrocytes during brain demyelination significantly attenuates brain inflammation and astrocyte reactivity. Furthermore, these changes promote myelin restoration and oligodendrocyte maturation throughout remyelination.

Reward has a remarkable ability to invigorate motor behavior, enabling individuals to select and execute actions with greater precision and speed. However, if reward is to be exploited in applied settings, such as rehabilitation, a thorough understanding of its underlying mechanisms is required. In a series of experiments, we first demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Specifically, reward promoted the selection of the correct action in the presence of distractors, while also improving execution through increased speed and maintenance of accuracy. These results led to a shift in the speed-accuracy functions for both selection and execution. In addition, punishment had a similar impact on action selection and execution, although it enhanced execution performance across all trials within a block, that is, its impact was noncontingent to trial value. Although the reward-driven enhancement of movement execution has been proposed to occur through enhanced feedback control, an untested possibility is that it is also driven by increased arm stiffness, an energy-consuming process that enhances limb stability. Computational analysis revealed that reward led to both an increase in feedback correction in the middle of the movement and a reduction in motor noise near the target. In line with our hypothesis, we provide novel evidence that this noise reduction is driven by a reward-dependent increase in arm stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate motor performance without compromising accuracy.

SIGNIFICANCE STATEMENT While reward is well-known for enhancing motor performance, how the nervous system generates these improvements is unclear. Despite recent work indicating that reward leads to enhanced feedback control, an untested possibility is that it also increases arm stiffness. We demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Furthermore, we show that punishment has a similar positive impact on performance. Importantly, by combining computational and biomechanical approaches, we show that reward leads to both improved feedback correction and an increase in stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate performance without compromising accuracy. This work suggests that stiffness control plays a vital, and underappreciated, role in the reward-based imporvemenets in motor control.

Calcineurin inhibitors, such as tacrolimus (FK506) and cyclosporine, are widely used as standard immunosuppressants in organ transplantation recipients. However, these drugs can cause severe pain in patients, commonly referred to as calcineurin inhibitor-induced pain syndrome (CIPS). Although calcineurin inhibition increases NMDAR activity in the spinal cord, the underlying mechanism remains enigmatic. Using an animal model of CIPS, we found that systemic administration of FK506 in male and female mice significantly increased the amount of α2-1–GluN1 complexes in the spinal cord and the level of α2-1–bound GluN1 proteins in spinal synaptosomes. Treatment with FK506 significantly increased the frequency of mEPSCs and the amplitudes of monosynaptic EPSCs evoked from the dorsal root and puff NMDAR currents in spinal dorsal horn neurons. Inhibiting α2-1 with gabapentin or disrupting the α2-1–NMDAR interaction with α2-1Tat peptide completely reversed the effects of FK506. In α2-1 gene KO mice, treatment with FK506 failed to increase the frequency of NMDAR-mediated mEPSCs and the amplitudes of evoked EPSCs and puff NMDAR currents in spinal dorsal horn neurons. Furthermore, systemic administration of gabapentin or intrathecal injection of α2-1Tat peptide reversed thermal and mechanical hypersensitivity in FK506-treated mice. In addition, genetically deleting GluN1 in dorsal root ganglion neurons or α2-1 genetic KO similarly attenuated FK506-induced thermal and mechanical hypersensitivity. Together, our findings indicate that α2-1–bound NMDARs mediate calcineurin inhibitor-induced tonic activation of presynaptic and postsynaptic NMDARs at the spinal cord level and that presynaptic NMDARs play a prominent role in the development of CIPS.

SIGNIFICANCE STATEMENT Calcineurin inhibitors are immunosuppressants used to prevent rejection of transplanted organs and tissues. However, these drugs can cause severe, unexplained pain. We showed that calcineurin inhibition enhances physical interaction between α2-1 and NMDARs and their synaptic trafficking in the spinal cord. α2-1 is essential for calcineurin inhibitor-induced aberrant activation of presynaptic and postsynaptic NMDARs in the spinal cord. Furthermore, inhibiting α2-1 or disrupting α2-1–NMDAR interaction reduces calcineurin inhibitor-induced pain hypersensitivity. Eliminating NMDARs in primary sensory neurons or α2-1 KO also attenuates calcineurin inhibitor-induced pain hypersensitivity. This new information extends our mechanistic understanding of the role of endogenous calcineurin in regulating synaptic plasticity and nociceptive transmission and suggests new strategies for treating this painful condition.

FAO will use World Food Day this year to promote one of the five pillars of Zero Hunger Challenge. The theme of the campaign will be “Sustainable Food Systems for Food Security and Nutrition.” Events in more than 120 countries – supported by videos, an issues paper, posters, media interviews and more – will communicate the message that our food systems [...]

Have you ever wondered if you are getting adequate nutrients from the food you eat? It is a common misconception that malnutrition means not getting enough food. This is, however, incorrect! People who take in insufficient food can be malnourished, but also those who consume too much face the same risks. Malnutrition is defined as “An abnormal physiological condition caused by [...]

The challenge is to maintain and develop the socioeconomic benefits from forests while safeguarding the resource. FAO’s State of the World’s Forests (SOFO) 2014 argues that if the focus of data collection and policy is shifted from trees to people, forests can be sustainably managed to meet society’s growing demands. Read the most important findings: The formal forestry sector employs some 13.2 [...]

In the face of changing weather driven by climate change and the increasing demand for food, Conservation Agriculture (CA) aims to achieve sustainable and profitable agriculture and improve farmers’ livelihoods. Here are five things you need to know. 1. CA observes three main principles that you should remember Direct seeding involves growing crops without mechanical seedbed preparation and with minimal soil disturbance [...]