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The popularity of sample surveys in evaluation and research makes it necessary for consumers to tell a good survey from a poor one. Several sources were identified that gave advice on how to evaluate a sample design used in a survey study. The sources are either too limited or too extensive to be useful practically. The purpose of this paper is to recommend six important yet practical guidelines for evaluating the quality of a sample design in a survey study. The six guidelines are: (1) a clearly specified population; (2) an explicitly stated unit of analysis; (3) a specification of determining a desired sample size; (4) an informative description of the sample selection procedures; (5) a description of response rate and nonresponse treatment; and (6) demonstration of appropriate estimation procedures. For each guideline, discussion is focused on definitions, problems found in the literature, and the consequences of the problems. (Contains 30 references.) (Author/SLD)

Recent longitudinal studies of glioblastoma (GBM) have demonstrated a lack of apparent selection pressure for specific DNA mutations in recurrent disease. Single-cell lineage tracing has shown that GBM cells possess a high degree of plasticity. Together this suggests that phenotype switching, as opposed to genetic evolution, may be the escape mechanism that explains the failure of precision therapies to date. We profiled 86 primary-recurrent patient-matched paired GBM specimens with single-nucleus RNA, single-cell open-chromatin, DNA and spatial transcriptomic/proteomic assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype. We show that the mesenchymal state is mediated by activator protein 1. Increased T-cell abundance at recurrence was prognostic and correlated with hypermutation status. We identified tumor-supportive networks of paracrine and autocrine signals between GBM cells, nonmalignant neuroglia and immune cells. We present cell-intrinsic and cell-extrinsic targets and a single-cell multiomics atlas of GBM under therapy.

BackgroundAlternative splicing is a rich source of tumor-specific neoantigen targets for immunotherapy. This holds promise for glioblastomas (GBMs), the most common primary tumors of the adult brain, which are resistant to standard-of-care therapy. Although most clinical trials enroll patients at recurrence, most preclinical studies have been done with specimens from primary disease. There are limited expression data from GBMs at recurrence and surprisingly little is known about the evolution of splicing patterns under therapy.ResultWe profile 37 primary-recurrent paired human GBM specimens via RNA sequencing. We describe the landscape of alternative splicing in GBM at recurrence and contrast that to primary and non-malignant brain-tissue specimens. By screening single-cell atlases, we identify cell-type-specific splicing patterns and novel splicing events in cell-surface proteins that are suitable targets for engineered T cell therapies. We identify recurrent-specific isoforms of mitogen-activated kinase pathway genes that enhance invasiveness and are preferentially expressed by stem-like cells.ConclusionThese studies shed light on gene expression in recurrent GBM and identify novel targets for therapeutic development.

SummarySingle-cell data are being generated at an accelerating pace. How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types. By comparing novel and published data from distinct scRNA-seq modalities that were acquired from the same tissues, we show that this approach preserves cell-type labels when mapping across diverse platforms.Availability and implementationhttps://github.com/diazlab/ELSA.Contactaaron.diaz@ucsf.edu.Supplementary informationSupplementary data are available at Bioinformatics online.

Although tumor-propagating cells can be derived from glioblastomas (GBM) of the proneural and mesenchymal subtypes, a glioma stem-like cell (GSC) of the classic subtype has not been identified. It is unclear whether mesenchymal GSCs (mGSC) and/or proneural GSCs (pGSC) alone are sufficient to generate the heterogeneity observed in GBM. We performed single-cell/single-nucleus RNA sequencing of 28 gliomas, and single-cell ATAC sequencing for 8 cases. We found that GBM GSCs reside on a single axis of variation, ranging from proneural to mesenchymal. In silico lineage tracing using both transcriptomics and genetics supports mGSCs as the progenitors of pGSCs. Dual inhibition of pGSC-enriched and mGSC-enriched growth and survival pathways provides a more complete treatment than combinations targeting one GSC phenotype alone. This study sheds light on a long-standing debate regarding lineage relationships among GSCs and presents a paradigm by which personalized combination therapies can be derived from single-cell RNA signatures, to overcome intratumor heterogeneity. SIGNIFICANCE: Tumor-propagating cells can be derived from mesenchymal and proneural glioblastomas. However, a stem cell of the classic subtype has yet to be demonstrated. We show that classic-subtype gliomas are comprised of proneural and mesenchymal cells. This study sheds light on a long-standing debate regarding lineage relationships between glioma cell types.See related commentary by Fine, p. 1650.This article is highlighted in the In This Issue feature, p. 1631.

Space-filling designs are commonly used in computer experiments and other scenarios for investigating complex systems, but the construction of such designs is challenging. In this thesis, we construct a series of maximin-distance Latin hypercube designs via Williams transformations of good lattice point designs. Some constructed designs are optimal under the maximin L1-distance criterion, while others are asymptotically optimal. Moreover, these designs are also shown to have small pairwise correlations between columns. The procedure is further extended to the construction of multi-level nonregular fractional factorial designs which have better properties than regular designs. Existing research on the construction of nonregular designs focuses on two-level designs. We construct a novel class of multilevel nonregular designs by permuting levels of regular designs via the Williams transformation. The constructed designs can reduce aliasing among effects without increasing the run size. They are more efficient than regular designs for studying quantitative factors. In addition, we explore the application of experimental design strategies to data-driven problems and develop a subsampling framework for big data linear regression. The subsampling procedure inherits optimality from the design matrices and therefore minimizes the mean squared error of coefficient estimations for sufficiently large data. It works especially well for the problem of label-constrained regression where a large covariate dataset is available but only a small set of labels are observable. The subsampling procedure can also be used for big data reduction where computation and storage issues are the primary concern.

Environmental contamination by 99Tc(VII) from radioactive wastewater streams is of particular concern due to the long half-life of 99Tc and high mobility of pertechnetate. Herein, we report a novel MXene-polyelectrolyte nanocomposite with three-dimensional networks for enhanced removal of perrhenate, which is pertechnetate simulant. The introduction of poly(diallyldimethylammonium chloride) (PDDA) regulates the surface charge and improves the stability of Ti2CT x nanosheet, resulting in Re(VII) removal capacity of up to 363 mg g-1, and fast sorption kinetics. The Ti2CT x/PDDA nanocomposite furthermore exhibits good selectivity for ReO4- when competing anions (such as Cl- and SO42-) coexist at a concentration of 1800 times. The immobilization mechanism was confirmed as a sorption-reduction process by batch sorption experiments and X-ray photoelectron spectroscopy. The pH-dependent reducing activity of Ti2CT x/PDDA nanocomposite toward Re(VII) was clarified by X-ray absorption spectroscopy. As the pH increases, the local environment gradually changes from octahedral-coordinated Re(IV) to tetrahedral-coordinated Re(VII). The overall results suggest that Ti2CT x/PDDA nanocomposite may be a promising candidate for efficient elimination of Tc contamination. The reported surface modification strategy might result in applications of MXene-based materials in environmental remediation of other oxidized anion pollutants.

The book is a study on intensifiers and reflexive pronouns between two languages (English and Mandarin Chinese) and the first one drawing a complete picture in this domain. It provides the full uses of self, zìji and benrén. In the case of benrén, here for the first time the full use of this pronoun in Mandarin Chinese is analysed. It is also the first book that uses contrastive study to talk about intensifiers and reflexive pronouns, which reveals many hidden characteristics of the intensifiers and reflexive pronouns that otherwise cannot be seen. It is based on the most distinctive research of the latest 30 years in the linguistic field.

Background The objective of this study is to identify the critical formulation parameters controlling distribution and function for the rectal administration of microbicides in humans. Four placebo formulations were designed with a wide range of hydrophilic characteristics (aqueous to lipid) and rheological properties (Newtonian, shear thinning, thermal sensitive and thixotropic). Aqueous formulations using typical polymers to control viscosity were iso-osmotic and buffered to pH 7. Lipid formulations were developed from lipid solvent/lipid gelling agent binary mixtures. Testing included pharmaceutical function and stability as well as in vitro and in vivo toxicity. Results The aqueous fluid placebo, based on poloxamer, was fluid at room temperature, thickened and became shear thinning at 37°C. The aqueous gel placebo used carbopol as the gelling agent, was shear thinning at room temperature and showed a typical decrease in viscosity with an increase in temperature. The lipid fluid placebo, myristyl myristate in isopropyl myristate, was relatively thin and temperature independent. The lipid gel placebo, glyceryl stearate and PEG-75 stearate in caprylic/capric triglycerides, was also shear thinning at both room temperature and 37°C but with significant time dependency or thixotropy. All formulations showed no rectal irritation in rabbits and were non-toxic using an ex vivo rectal explant model. Conclusions Four placebo formulations ranging from fluid to gel in aqueous and lipid formats with a range of rheological properties were developed, tested, scaled-up, manufactured under cGMP conditions and enrolled in a formal stability program. Clinical testing of these formulations as placebos will serve as the basis for further microbicide formulation development with drug-containing products.

We present a novel linear scaling ab initio total energy electronic structure calculation method, which is simple to implement, easily to parallelize, and produces essentially the same results as the direct ab initio method, while it could be thousands of times faster. Using this method, we have studied the dipole moments of CdSe quantum dots, and found both significant bulk and surface contributions. The bulk dipole contribution cannot simply be estimated from the bulk spontaneous polarization value by a proportional volume factor. Instead it has a geometry dependent screening effect. The dipole moment also produces a strong internal electric field which induces a strong electron hole separation.

We present a new linearly scaling three-dimensional fragment (LS3DF) method for large scale ab initio electronic structure calculations. LS3DF is based on a divide-and-conquer approach, which incorporates a novel patching scheme that effectively cancels out the artificial boundary effects due to the subdivision of the system. As a consequence, the LS3DF program yields essentially the same results as direct density functional theory (DFT) calculations. The fragments of the LS3DF algorithm can be calculated separately with different groups of processors. This leads to almost perfect parallelization on tens of thousands of processors. After code optimization, we were able to achieve 35.1 Tflop/s, which is 39percent of the theoretical speed on 17,280 Cray XT4 processor cores. Our 13,824-atom ZnTeO alloy calculation runs 400 times faster than a direct DFT calculation, even presuming that the direct DFT calculation can scale well up to 17,280 processor cores. These results demonstrate the applicability of the LS3DF method to material simulations, the advantage of using linearly scaling algorithms over conventional O(N3) methods, and the potential for petascale computation using the LS3DF method.

We present a novel linear scaling ab initio total energy electronic structure calculation method, which is simple to implement, easily to parallelize, and produces essentially the same results as the direct ab initio method, while it could be thousands of times faster.

We present a linear scaling 3 dimensional fragment (LS3DF) method that uses a novel decomposition and patching scheme to do ab initio density functional theory (DFT) calculations for large systems. This method cancels out the artificial boundary effects that arise from the spatial decomposition. As a result, the LS3DF results are essentially the same as the original full-system DFT results with errors smaller than the errors introduced by other sources of numerical approximations. In addition, the resulting computational times are thousands of times smaller than conventional DFT methods, making calculations with 100,000 atom systems possible. The LS3DF method is applicable to insulator and semiconductor systems, which covers a current gap in the DOE's materials science code portfolio for large-scale ab initio simulations.

We have carried out a survey of codes and algorithms used on NERSC computers within the science category of material science. This is part of the effort to track the usage of different algorithms in NERSC community. This survey is based on the data provided in the ERCAP application of FY06. To figure out the usage of each code in one account, we have multiplied the total high performance computer (HPC) time allocation (MPP hours) of this account with the percentage usage of this code as estimated by the users in the ERCAP application. This is not the actual usage time, but should be a good estimation of it, and it represents the intention of the users.

An efficient new method is presented to calculate the quantum transports using periodic boundary conditions. This method allows the use of conventional ground state ab initio programs without big changes. The computational effort is only a few times of a normal ground state calculations, thus is makes accurate quantum transport calculations for large systems possible.

Isoelectronic impurity states are localized states induced by stoichiometric single atom substitution in bulk semiconductor. Photoluminescence spectra indicate deep impurity levels of 0.5 to 0.9eV above the top of valence band for systems like: GaN:As, GaN:P, CdS:Te, ZnS:Te. Previous calculations based on small supercells seemingly confirmed these experimental results. However, the current ab initio calculations based on thousand atom supercells indicate that the impurity levels of the above systems are actually much shallower(0.04 to 0.23 eV), and these impurity levels should be compared with photoluminescence excitation spectra, not photoluminescence spectra.