Qiuyi Wang
Apr 1, 2020; 61:570-579
Methods

Invitation Only Research Event

Event participants

Ryhor Astapenia, Robert Bosch Stiftung Academy Fellow, Russia and Eurasia Programme, Chatham House
Chair: James Nixey, Programme Director, Russia and Eurasia, Chatham House

Steroids that contain a 3-hydroxyl group (3-OH steroids) are widely distributed in nature. During analysis with ESI-MS, they easily become dehydrated while in the protonated form, resulting in the production of several precursor ions and leading to low sensitivity of detection. To address this analytical challenge, here, we developed a method for the quantitation of 3-OH steroids by LC-MS/MS coupled with post-column addition of lithium (Li) ions to the mobile phase. The Li ion has a high affinity for the keto group of steroids, stabilizing their structures during ionization and permitting detection of analytes exclusively as the lithiated form. This not only improved the intensities of the precursor ions, but also promoted the formation of typical lithiated fragment ions. This improvement made the quantitation by multiple reaction monitoring more sensitive and reliable, as evidenced by 1.53–188 times enhanced detection sensitivity of 13 steroids that contained at least one keto and two hydroxyl groups or one keto and one 5-olefinic double bond, among 16 different 3-OH steroids. We deployed our newly developed method for profiling steroids in mouse brain tissue and identified six steroids in one tissue sample. Among these, 16-hydroxyestrone, tetrahydrocorticosterone, and 17α-hydroxypregnenolone were detected for the first time in the mouse brain. In summary, the method described here enables the detection of lithiated steroids by LC-MS/MS, including three 3-OH steroids not previously reported in the mouse brain. We anticipate that this new method may allow the determination of 3-OH steroids in different brain regions.

Invitation Only Research Event

Invitation Only Research Event

Event participants

Ryhor Astapenia, Robert Bosch Stiftung Academy Fellow, Russia and Eurasia Programme, Chatham House
Chair: James Nixey, Programme Director, Russia and Eurasia, Chatham House

We’ve been banging the drum about transparency of payment to doctors for years - we’ve even put a moratorium on financial conflicts of interest in the authors of any of our education articles. Not because we think that all doctors who receive money from industry are being influenced to push their agenda - but because we have no way of telling when...

No sooner than the Government’s announced its intention to restart the economy, private sector groups are advocating for longer working hours to fast-track recovery during the COVID-19 pandemic. In a collaborative move, the Jamaica Manufacturers...

Research Event

For generations, migrants have emigrated from Senegal, particularly from in and around the Senegal River Valley. With France a key destination, French policy changes have had significant impact on Senegalese migrants and the hometown associations through which they support development in Senegal. This article explores how these policy shifts influence development and quality of life in the Senegal River Valley.

Elizabeth R. Seaquist
May 1, 2013; 36:1384-1395
Scientific Statement

Khalid A. Jadoon
Oct 1, 2016; 39:1777-1786
Emerging Technologies and Therapeutics

As governments seek to push their borders out by amassing ever more data on travelers and migrants, their creation of increasingly complex border surveillance systems and use of risk-assessment technologies could ease mobility for some while rendering other groups immobile based on hypothetical risk profiles and decisions that are not publicly known and cannot be challenged, as this article explores.

The Organized Dentistry Coalition is asking the U.S. Department of Health and Human Services to “extend federal authorization for licensed dentists to conduct Food and Drug Administration-authorized, point-of-care testing” during the COVID-19 pandemic.

Some 30 companies including Dow, Total and other big makers of plastic raised $1 billion to contribute to cleaner ocean waters.

States publish a wealth of data about their English Learner students’ academic achievement and other outcomes such as graduation rates. But the answer to the question “Who is an EL?” is not always the same. This brief explains how the EL subgroup varies across states and types of data, and why it is important to understand these differences when making decisions about how ELs and schools are faring.

Andrew M. Davis
Apr 1, 2008; 26:58-62
Feature Articles

Even before the pandemic, this age group were reporting record levels of levels.

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The state's last superintendent resigned under pressure after he attempted to take over Montgomery's school system and figure out a way to grade the state's schools.

Parents Unified for Local School Education New Jersey is calling for community-driven schools and opposes the One Newark reorganization plan.

"This report is the final report for the Orange-bellied Parrot Habitat Management and Restoration Project carried out on King Island. The report relates to the activity period starting 30th of June 2007 and finishing on the 25th of May 2008."--Introduction.

An introduction to the group that was established by Dina Davis, with only six members who email examples of their current work to the rest of the group for review and feedback. Includes biographical details and examples of the work of each author.

A plan to end a years-long court battle over school funding in Kansas is under threat after an influential group of school districts withdrew its support.

A $59 million investment in software developer Social Solutions aims to ease the flow of data among schools and social service providers.

State lawmakers have made it illegal for school districts to spend any public money on the Mississippi Association of School Superintendents, saying district leaders personally attacked state officials while they were seeking votes for a school funding initiative last year.

François Bachoc, Baptiste Broto, Fabrice Gamboa, Jean-Michel Loubes.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 503--546.

Abstract:
In the framework of the supervised learning of a real function defined on an abstract space $mathcal{X}$, Gaussian processes are widely used. The Euclidean case for $mathcal{X}$ is well known and has been widely studied. In this paper, we explore the less classical case where $mathcal{X}$ is the non commutative finite group of permutations (namely the so-called symmetric group $S_{N}$). We provide an application to Gaussian process based optimization of Latin Hypercube Designs. We also extend our results to the case of partial rankings.

A new strategy for probabilistic graphical modeling is developed that draws parallels to community detection analysis. The method jointly estimates an undirected graph and homogeneous communities of nodes. The structure of the communities is taken into account when estimating the graph and at the same time, the structure of the graph is accounted for when estimating communities of nodes. The procedure uses a joint group graphical lasso approach with community detection-based grouping, such that some groups of edges co-occur in the estimated graph. The grouping structure is unknown and is estimated based on community detection algorithms. Theoretical derivations regarding graph convergence and sparsistency, as well as accuracy of community recovery are included, while the method's empirical performance is illustrated in an fMRI context, as well as with simulated examples.

Pierre Lafaye de Micheaux, Benoît Liquet, Matthew Sutton.

Source: Statistics Surveys, Volume 13, 119--149.

Abstract:
Partial Least Squares (PLS) methods have been heavily exploited to analyse the association between two blocks of data. These powerful approaches can be applied to data sets where the number of variables is greater than the number of observations and in the presence of high collinearity between variables. Different sparse versions of PLS have been developed to integrate multiple data sets while simultaneously selecting the contributing variables. Sparse modeling is a key factor in obtaining better estimators and identifying associations between multiple data sets. The cornerstone of the sparse PLS methods is the link between the singular value decomposition (SVD) of a matrix (constructed from deflated versions of the original data) and least squares minimization in linear regression. We review four popular PLS methods for two blocks of data. A unified algorithm is proposed to perform all four types of PLS including their regularised versions. We present various approaches to decrease the computation time and show how the whole procedure can be scalable to big data sets. The bigsgPLS R package implements our unified algorithm and is available at https://github.com/matt-sutton/bigsgPLS .

An important component of every country's COVID-19 response is fast and efficient testing -- to identify and isolate cases, as well as for early detection of local hotspots. For many countries, producing a sufficient number of tests has been a serious limiting factor in their efforts to control COVID-19 infections. Group testing is a well-established mathematical tool, which can provide a serious and rapid improvement to this situation. In this note, we compare several well-established group testing schemes in the context of qPCR testing for COVID-19. We include example calculations, where we indicate which testing architectures yield the greatest efficiency gains in various settings. We find that for identification of individuals with COVID-19, array testing is usually the best choice, while for estimation of COVID-19 prevalence rates in the total population, Gibbs-Gower testing usually provides the most accurate estimates given a fixed and relatively small number of tests. This note is intended as a helpful handbook for labs implementing group testing methods.

Hays County announced it has joined the Texas Purchasing Group and will be publishing and distributing upcoming bid opportunities on the system along with their current platform in these unprecedented...

(PRWeb April 09, 2020)

Read the full story at https://www.prweb.com/releases/hays_county_joins_the_texas_purchasing_group_by_bidnet_direct/prweb17021429.htm

Li Zhu, Zhiguang Huo, Tianzhou Ma, Steffi Oesterreich, George C. Tseng.

Source: The Annals of Applied Statistics, Volume 13, Number 4, 2611--2636.

Abstract:
Variable selection is a pervasive problem in modern high-dimensional data analysis where the number of features often exceeds the sample size (a.k.a. small-n-large-p problem). Incorporation of group structure knowledge to improve variable selection has been widely studied. Here, we consider prior knowledge of a hierarchical overlapping group structure to improve variable selection in regression setting. In genomics applications, for instance, a biological pathway contains tens to hundreds of genes and a gene can be mapped to multiple experimentally measured features (such as its mRNA expression, copy number variation and methylation levels of possibly multiple sites). In addition to the hierarchical structure, the groups at the same level may overlap (e.g., two pathways can share common genes). Incorporating such hierarchical overlapping groups in traditional penalized regression setting remains a difficult optimization problem. Alternatively, we propose a Bayesian indicator model that can elegantly serve the purpose. We evaluate the model in simulations and two breast cancer examples, and demonstrate its superior performance over existing models. The result not only enhances prediction accuracy but also improves variable selection and model interpretation that lead to deeper biological insight of the disease.

Bo Ning, Seonghyun Jeong, Subhashis Ghosal.

Source: Bernoulli, Volume 26, Number 3, 2353--2382.

Abstract:
We study frequentist properties of a Bayesian high-dimensional multivariate linear regression model with correlated responses. The predictors are separated into many groups and the group structure is pre-determined. Two features of the model are unique: (i) group sparsity is imposed on the predictors; (ii) the covariance matrix is unknown and its dimensions can also be high. We choose a product of independent spike-and-slab priors on the regression coefficients and a new prior on the covariance matrix based on its eigendecomposition. Each spike-and-slab prior is a mixture of a point mass at zero and a multivariate density involving the $ell_{2,1}$-norm. We first obtain the posterior contraction rate, the bounds on the effective dimension of the model with high posterior probabilities. We then show that the multivariate regression coefficients can be recovered under certain compatibility conditions. Finally, we quantify the uncertainty for the regression coefficients with frequentist validity through a Bernstein–von Mises type theorem. The result leads to selection consistency for the Bayesian method. We derive the posterior contraction rate using the general theory by constructing a suitable test from the first principle using moment bounds for certain likelihood ratios. This leads to posterior concentration around the truth with respect to the average Rényi divergence of order $1/2$. This technique of obtaining the required tests for posterior contraction rate could be useful in many other problems.

South East Family History Group (S.A.) -- Periodicals.

But will that keep susceptible populations safe?

The new service will join others at the existing 811 HealthLine, helping connect people with their local food services and offering answers for those without access to online services.

The Bank of Canada, the Bank of England, the Bank of Japan, the European Central Bank, the Sveriges Riksbank and the Swiss National Bank, together with the Bank for International Settlements (BIS), have created a group to share experiences as they assess the potential case for central bank digital currency (CBDC) in their home jurisdictions. (Press release, 21 January 2020)

A group of Winnipeg-born hockey players connected with a sexist group chat are being either let go from their teams or investigated, after screenshots from the private chat were made public earlier this week.

Seventy-three homeless shelters and other community organizations are getting extra funding to help pay for basics like extra food, cleaning and staff during the COVID-19 pandemic.

The Ottawa Senators have named Anthony LeBlanc as their president of business operations. LeBlanc was most recently a founding partner of Schooner Sports and Entertainment, a group trying to bring a CFL team to Halifax.