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An important task in survival analysis is choosing a structure for the relationship between covariates of interest and the time-to-event outcome. For example, the accelerated failure time (AFT) model structures each covariate effect as a constant multiplicative shift in the outcome distribution across all survival quantiles. Though parsimonious, this structure cannot detect or capture effects that differ across quantiles of the distribution, a limitation that is analogous to only permitting proportional hazards in the Cox model. To address this, we propose a general framework for quantile-varying multiplicative effects under the AFT model. Specifically, we embed flexible regression structures within the AFT model and derive a novel formula for interpretable effects on the quantile scale. A regression standardization scheme based on the g-formula is proposed to enable the estimation of both covariate-conditional and marginal effects for an exposure of interest. We implement a user-friendly Bayesian approach for the estimation and quantification of uncertainty while accounting for left truncation and complex censoring. We emphasize the intuitive interpretation of this model through numerical and graphical tools and illustrate its performance through simulation and application to a study of Alzheimer's disease and dementia. [ABSTRACT FROM AUTHOR]

A series of sulfonated poly(arylene ether sulfone) block copolymers with aliphatic chains (SPAES-LA) to lend structural flexibility in the polymer backbone have been synthesized to prepare proton exchange membranes (PEMs) showing improved electrochemical performance and dimensional/oxidative stabilities. The SPAES-LAs, bearing different hydrophilic/hydrophobic segment lengths, are prepared via polycondensation and sulfonation reactions. The sulfonation reaction occurs in specific fluorenylidene units by using chlorosulfonic acid. The SPAES-LA membrane, fabricated by solvent casting method, exhibits remarkable dimensional/thermal stabilities. Moreover, proton conductivity of as-prepared SPAES-LA membranes demonstrates significant improvement with expansion of ion clusters which is due to the increased hydrophilic volume ratio. In particular, the SPAES-LA-X12Y28 membrane exhibited heightened proton conductivity of 158.4 mS cm−1 as well as suitable dimensional stability and durability towards radical oxidation, due to an effective well-defined hydrophilic-hydrophobic interface. Furthermore, H 2 /O 2 fuel cell performance using SPAES-LA-X12Y28 membrane achieves a maximum power density of 232.02 mW cm−2, a result which points out that SPAES-LA membranes show great potential for applications of polymer electrolyte membrane. Image 1 • The block copolymers are synthesized via controlling oligomer lengths. • The fabricated membranes show desirable thermo-oxidative stability. • The membranes showed high physio-chemical properties. • The as-prepared membranes exhibit high ionic conductivity and unit-cell performance. [ABSTRACT FROM AUTHOR]

Microorganisms play critical roles in human health and disease. They live in diverse communities in which they interact synergistically or antagonistically. Thus for estimating microbial associations with clinical covariates, such as treatment effects, joint (multivariate) statistical models are preferred. Multivariate models allow one to estimate and exploit complex interdependencies among multiple taxa, yielding more powerful tests of exposure or treatment effects than application of taxon-specific univariate analyses. Analysis of microbial count data also requires special attention because data commonly exhibit zero inflation, i.e., more zeros than expected from a standard count distribution. To meet these needs, we developed a Bayesian variable selection model for multivariate count data with excess zeros that incorporates information on the covariance structure of the outcomes (counts for multiple taxa), while estimating associations with the mean levels of these outcomes. Though there has been much work on zero-inflated models for longitudinal data, little attention has been given to high-dimensional multivariate zero-inflated data modeled via a general correlation structure. Through simulation, we compared performance of the proposed method to that of existing univariate approaches, for both the binary ("excess zero") and count parts of the model. When outcomes were correlated the proposed variable selection method maintained type I error while boosting the ability to identify true associations in the binary component of the model. For the count part of the model, in some scenarios the univariate method had higher power than the multivariate approach. This higher power was at a cost of a highly inflated false discovery rate not observed with the proposed multivariate method. We applied the approach to oral microbiome data from the Pediatric HIV/AIDS Cohort Oral Health Study and identified five (of 44) species associated with HIV infection. [ABSTRACT FROM AUTHOR]

Summary: Organic‐inorganic composite membranes were prepared by introducing silicon dioxide (SiO2) or functionalized SiO2 (ƒ‐SiO2) with various particle sizes into sulfonated poly (arylene ether ketone) (SPAEK) containing pendant groups, and the membrane was manufactured via directly casting which is a cost‐competitive method. The structure and morphology of the composite membranes were confirmed by 1H NMR, FT‐IR, XRD, and FE‐SEM analysis which demonstrated that inorganic nanofillers were successfully introduced. The FE‐SEM surface images showed that SiO2 and ƒ‐SiO2 particles were very well dispersed within the membrane sheets. The water uptake and swelling ratio of the composite membranes including SiO2 or ƒ‐SiO2 almost did not change when compared with the pristine SPAEK membrane. All fabricated membranes demonstrated good thermal/dimensional stabilities, robust mechanical behavior, and excellent proton conductivity. In particular, the SPAEK/ƒ‐SiO2 composite membranes exhibited improved ionic conductivity compared with the pristine membrane at 70% relative humidity (RH) due to hydrogen bonding between ─SO3H groups of functionalized inorganic filler and polymer backbone. Furthermore, the maximum power density of SPAEK/ƒ‐SiO2 reached as high as 273.11 mW cm−2 at 60°C under 70% RH. Therefore, the composite membranes with ƒ‐SiO2 testify to great potential as polymer electrolyte membrane. [ABSTRACT FROM AUTHOR]

Abstract A series of composite membranes for application as anion exchange membranes were prepared by introducing various amounts (0.1–5.0 wt%) of reduced graphene oxide (rGO) into chloromethylated poly(arylene ether ketone) (CM-PAEK), followed by quarternization and anionization. CM-PAEK/rGO composite membranes with controlled weight ratios of rGO were fabricated by cost-competitive solution casting method. The field emission scanning electron microscopy (FE-SEM) images of the composite membranes showed that the distribution of rGO was uniform, and the prepared membranes have similar thicknesses confirmed by the cross-sectional image. The composite membranes exhibited enhanced the mechanical strength due to π-π interaction between the aromatic chain of rGO and the polymer backbone, and after the quaternization, hydroxide conduction was improved by hydrogen bonding between rGO and functional ammonium groups. Among the QN-PAEK/rGO membranes with various amounts of rGO, QN-PAEK/rGO 1.0 wt% demonstrated the highest ionic conductivity of 115 mS cm−1, and other composite membranes, which were blended more than that (3 wt% and 5 wt%), showed a decrease in ionic conductivity due to aggregation of inorganic nano fillers. Furthermore, alkaline resistance, mechanical strength, and dimensional stability of composite membranes have been greatly improved due to the introduction of rGO, which demonstrate great potential application as anion exchange membrane for fuel cells. Graphical abstract Image 1 Highlights • QN-PAEK/rGO composite membranes were prepared by introducing various amount of rGO. • The QN-PAEK/rGO composite membranes demonstrated superior OH− conductivity. • The prepared membranes showed improved mechanical and dimensional stabilities. • The membranes exhibited remarkable alkaline stability in a 2 M NaOH solution for 600 h. [ABSTRACT FROM AUTHOR]

Statistical analyses that investigate risk factors for Alzheimer's disease (AD) are often subject to a number of challenges. Some of these challenges arise due to practical considerations regarding data collection such that the observation of AD events is subject to complex censoring including left-truncation and either interval or right-censoring. Additional challenges arise due to the fact that study participants under investigation are often subject to competing forces, most notably death, that may not be independent of AD. Towards resolving the latter, researchers may choose to embed the study of AD within the 'semi-competing risks' framework for which the recent statistical literature has seen a number of advances including for the so-called illness-death model. To the best of our knowledge, however, the semi-competing risks literature has not fully considered analyses in contexts with complex censoring, as in studies of AD. This is particularly the case when interest lies with the accelerated failure time (AFT) model, an alternative to the traditional multiplicative Cox model that places emphasis away from the hazard function. In this article, we outline a new Bayesian framework for estimation/inference of an AFT illness-death model for semi-competing risks data subject to complex censoring. An efficient computational algorithm that gives researchers the flexibility to adopt either a fully parametric or a semi-parametric model specification is developed and implemented. The proposed methods are motivated by and illustrated with an analysis of data from the Adult Changes in Thought study, an on-going community-based prospective study of incident AD in western Washington State. [ABSTRACT FROM AUTHOR]

The analysis of multiple outcomes is becoming increasingly common in modern biomedical studies. It is well-known that joint statistical models for multiple outcomes are more flexible and more powerful than fitting a separate model for each outcome; they yield more powerful tests of exposure or treatment effects by taking into account the dependence among outcomes and pooling evidence across outcomes. It is, however, unlikely that all outcomes are related to the same subset of covariates. Therefore, there is interest in identifying exposures or treatments associated with particular outcomes, which we term outcome-specific variable selection. In this work, we propose a variable selection approach for multivariate normal responses that incorporates not only information on the mean model, but also information on the variance-covariance structure of the outcomes. The approach effectively leverages evidence from all correlated outcomes to estimate the effect of a particular covariate on a given outcome. To implement this strategy, we develop a Bayesian method that builds a multivariate prior for the variable selection indicators based on the variance-covariance of the outcomes. We show via simulation that the proposed variable selection strategy can boost power to detect subtle effects without increasing the probability of false discoveries. We apply the approach to the Normative Aging Study (NAS) epigenetic data and identify a subset of five genes in the asthma pathway for which gene-specific DNA methylations are associated with exposures to either black carbon, a marker of traffic pollution, or sulfate, a marker of particles generated by power plants. [ABSTRACT FROM AUTHOR]

Readmission following discharge from an initial hospitalization is a key marker of quality of healthcare in the United States. For the most part, readmission has been studied among patients with “acute” health conditions, such as pneumonia and heart failure, with analyses based on a logistic-Normal generalized linear mixed model. Naïve application of this model to the study of readmission among patients with “advanced” health conditions such as pancreatic cancer, however, is problematic because it ignores death as a competing risk. A more appropriate analysis is to imbed such a study within the semicompeting risks framework. To our knowledge, however, no comprehensive statistical methods have been developed for cluster-correlated semicompeting risks data. To resolve this gap in the literature we propose a novel hierarchical modeling framework for the analysis of cluster-correlated semicompeting risks data that permits parametric or nonparametric specifications for a range of components giving analysts substantial flexibility as they consider their own analyses. Estimation and inference is performed within the Bayesian paradigm since it facilitates the straightforward characterization of (posterior) uncertainty for all model parameters, including hospital-specific random effects. Model comparison and choice is performed via the deviance information criterion and the log-pseudo marginal likelihood statistic, both of which are based on a partially marginalized likelihood. An efficient computational scheme, based on the Metropolis-Hastings-Green algorithm, is developed and had been implemented in the R package SemiCompRisks. A comprehensive simulation study shows that the proposed framework performs very well in a range of data scenarios, and outperforms competitor analysis strategies. The proposed framework is motivated by and illustrated with an ongoing study of the risk of readmission among Medicare beneficiaries diagnosed with pancreatic cancer. Using data onn= 5298 patients atJ=112 hospitals in the six New England states between 2000–2009, key scientific questions we consider include the role of patient-level risk factors on the risk of readmission and the extent of variation in risk across hospitals not explained by differences in patient case-mix. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Background: Although the prognosis for HIV-infected individuals has improved after antiretroviral therapy (ART) scale-up, limited data exist on the incidence of AIDS-defining opportunistic infections (ADIs) and mortality during ART in resource-limited settings. Methods: HIV-infected adults in two large hospitals in urban Hanoi were enrolled to the prospective cohort, from October 2007 through December 2013. Those who started ART less than one year before enrollment were assigned to the survival analysis. Data on ART history and ADIs were collected retrospectively at enrollment and followed-up prospectively until April 2014. Results: Of 2,070 cohort participants, 1,197 were eligible for analysis and provided 3,446 person-years (PYs) of being on ART. Overall, 161 ADIs episodes were noted at a median of 3.20 months after ART initiation (range 0.03–75.8) with an incidence 46.7/1,000 PYs (95% confidence interval [CI] 39.8–54.5). The most common ADI was tuberculosis with an incidence of 29.9/1,000 PYs. Mortality after ART initiation was 8.68/1,000 PYs and 45% (19/45) died of AIDS-related illnesses. Age over 50 years at ART initiation was significantly associated with shorter survival after controlling for baseline CD4 count, but neither having injection drug use (IDU) history nor previous ADIs were associated with poor survival. Semi-competing risks analysis in 951 patients without ADIs history prior to ART showed those who developed ADIs after starting ART were at higher risk of death in the first six months than after six months. Conclusion: ADIs were not rare in spite of being on effective ART. Age over 50 years, but not IDU history, was associated with shorter survival in the cohort. This study provides in-depth data on the prognosis of patients on ART in Vietnam during the first decade of ART scale-up. [ABSTRACT FROM AUTHOR]

Here, we present a series of organic-inorganic composite membranes using graphitic carbon nitride (gC 3 N 4) derivatives (porous (p-) gC 3 N 4) and F-doped porous (F-p-) gC 3 N 4) to improve the electrochemical properties and dimensional stability for anion exchange membranes (AEMs). The introduction of F-p-gC 3 N 4 onto a quaternized poly(phenylene oxide) (QPPO) matrix induced the expansion of the ion channel by promoting nanophase separation, and the composite membranes possess high ion conductivity (>142.1 mS cm−1 at 90 °C, i.e., 1.75 times as high as the pristine membrane) and suitable alkaline durability (>74% ion conductivity in 1 M KOH at 80 °C for 30 days) with enhanced dimensional change. Importantly, H 2 -O 2 fuel cell performance of QPPO/F-p-gC 3 N 4 -0.5 reached a maximum peak power density of 286.2 mW cm−2 at 60 °C. In addition, the QPPO/F-p-gC 3 N 4 -0.5-based membrane electrode assembly can be operated under 0.15 A cm−2 current density at 60 °C for 100 h. Thus, this strategy could be suitable for future work on AEM applications. [Display omitted] • The F-doped porous gC 3 N 4 (F-p-gC 3 N 4) was prepared for anion exchange composite membranes. • The composite membrane showed superior ion conductivity of 142.1 mS cm−1 with suitable dimensional stability. • The ion conductivity of composite membrane was well-retained after alkaline stability >30 days in 1 M KOH at 80 °C. • The H 2 -O 2 fuel cell performance exhibited the highest peak power density of 286.2 mW cm−2. • The prepared composite membrane exhibited long-term stability at 60 °C for 100 h. [ABSTRACT FROM AUTHOR]

The presented work is motivated by the need of reliably estimating and predicting the survival rates for individuals diagnosed with cancer, when gene expression profiles are available for identifying molecular risks factors for cancer. The regression analysis of such data is challenged by three characteristics of data: (i) time-to-event outcome, (ii) high-dimensional covariate space, and (iii) a group structure of genes. One strategy to simultaneously deal with all three of the aforementioned challenges is to build a penalized regression model using special penalty functions such as elastic net, fused lasso, and group lasso. To our knowledge, existing methods are sparse or non-existent, however, when a Bayesian estimation/inference is the goal for the penalized regression models. In this article, we propose a Bayesian semi-parametric framework for the regression analysis of gene expression data with survival outcomes. Our proposed Bayesian methods permit researchers to take advantage of numerous benefits including the ability to incorporate substantive prior information, the straightforward and automated quantification of uncertainty in prediction, and the prescriptive nature of computation. The performance of our proposed models for variable selection and prediction is thoroughly investigated through simulation studies, where we consider four scenarios based on different underlying group structures of covariates and covariate effects. The results generally show the satisfactory variable selection capability and predictability of our methods. Finally, we apply our proposed framework to three different gene expression data sets. We developed an efficient Markov chain Monte Carlo algorithm for the implementation of our proposed framework and provided an easy-to-use R package. [ABSTRACT FROM AUTHOR]

Abstract: The synthesis and properties of densely sulfonated poly(arylene biphenylsulfone ketone) block copolymer and its composite membranes including phosphotungstic acid (PWA) were investigated. The chemical structure of the block copolymers was characterized by FT-IR, 1H-NMR, and GPC. The block copolymer composite membranes were prepared by mixing the block copolymer with a commercial PWA. The composite membranes have shown not only good thermal stability (decomposition temperature in nitrogen >250°C), but also lower water uptake than the unfilled membranes. Their crystalline phases and morphologies have been confirmed by X-ray diffraction (XRD) and field-emission scanning electron microscopy (FSEM), respectively. The composite membranes displayed relevant ion exchange capacity (IEC), as well as good proton conductivity especially at elevated temperature. The proton conductivity of the Block-19/PWA-30 composite membrane (IEC 1.58meqg−1) reached the maximum of 97mScm−1 at 90°C under 100% relative humidity (RH), which is comparable to Nafion-117. The fabricated composite membrane exhibited a maximum fuel cell power density of 150mWcm−2, which was much higher that of Block-19 membrane and can be considered as a candidate for potential application in fuelcells. [Copyright &y& Elsevier]

Two new cyclopropanoic fatty acid glycosides, named parisveroside A (1) and parisveroside B (2), were isolated from a MeOH extract of the roots of Paris verticillata (Liliaceae) together with three other known compounds, salicin (3), 3-(β-d-glucopyranosyloxymethyl)-2-(4-hydroxy-3-methoxyphenyl)-5-(3-hydroxypropyl)-7-methoxy-(2R,3S)-dihydrobenzofuran (4), and allantoin (5). Their structures were elucidated on the basis of spectroscopic data, including 1D and 2D NMR, HR-FAB-MS, and chemical evidence. To investigate the antineuroinflammatory effects of the isolated compounds (1-5), nitric oxide (NO) production was evaluated in the lipopolysaccharide-activated microglia cell line, BV-2. Compounds 2 and 4 significantly inhibited NO production with IC50 values of 74.8 and 60.5 µmol/L, respectively. Utilisant comme produit de départ le mélange obtenu par extraction des racines de Paris verticillata (Liliacée) à l'aide de méthanol, on a isolé deux nouveaux glycosides dérivés de l'acide gras cyclopropanoïque, soit le parisvéroside A (1) et le parisvéroside B (2), ainsi que trois autres produits connus, la salicine (3), le 3-(β-d-glucopyranosyloxyméthyl)-2-(4-hydroxy-3-méthoxyphényl)-5-(3-hydroxypropyl)-7-méthoxy-(2R,3S)-dihydrobenzofurane (4) et l'allantoïne (5). On a élucidé les structures en se basant sur des preuves chimiques et des données spectroscopiques, dont celles des RMN 1D et 2D et de la spectrométrie de masse à haute résolution avec bombardement avec des atomes rapides (SM-HR-BAR). Pour étudier les effets anti-neuroinflammatoires des composés isolés, on a évalué la production d'oxyde d'azote (NO) dans des cellules BV-2 de la lignée cellulaire de microglie activée par un lipopolysaccharide. Les composés 2 et 4 inhibent d'une façon significative la production de NO avec des valeurs de IC50 de 74,8 et 60,5 µmol/L respectivement. [ABSTRACT FROM AUTHOR]

In this work, quaternized poly(arylene ether ketone) (QPAEK)/functionalized TiO 2 (f -TiO 2) composite membranes were fabricated with different f -TiO 2 contents (1, 3, 5, 7, and 9 wt%), and the structure of the materials was characterized by 1H NMR, ATR-FT-IR, XRD, XPS, and FE-SEM. The addition of f -TiO 2 enlarges the ion cluster in the membrane due to enhancing the interaction between the functional groups, and SAXS analysis revealed an extension of the ion domain size with an increase in the filler content (up to 5 wt%). In particular, the composite membrane with 5 wt% f -TiO 2 displayed the highest ion conductivity (74.6 mS cm−1); such a result was attributed to the formation of water traps by the deliquescence of TiO 2 and enhanced interfacial interactions between the pure organic polymers and inorganic nanomaterials. This work proves that a composite membrane with an appropriate f -TiO 2 concentration is a promising candidate for application to anion exchange membranes. [Display omitted] • Anionic organic-inorganic composite membranes are prepared by introducing various amount of f -TiO 2. • The properties of composite membranes are optimized by changing the contents of f -TiO 2. • The prepared membranes show improved mechanical and dimensional stabilities. • The QPAEK/ f -TiO 2 composite membranes demonstrate superior oxidative/alkaline stabilities. [ABSTRACT FROM AUTHOR]

A series of novel blended anion exchange membranes (AEMs) were prepared with hyperbranched brominated poly(arylene ether sulfone) (Br-HB-PAES) and linear chloromethylated poly(phenylene oxide) (CM-PPO). The as-prepared blended membranes were fabricated with different weight ratios of Br-HB-PAES to CM-PPO, and the quaternization reaction for introducing the ionic functional group was performed by triethylamine. The Q-PAES/PPO-XY (quaternized-PAES/PPO-XY) blended membranes promoted the ion channel formation as the strong hydrogen bonds interconnecting the two polymers were maintained, and showed an improved hydroxide conductivity with excellent thermal behavior. In particular, the Q-PAES/PPO-55 membrane showed a very high hydroxide ion conductivity (90.9 mS cm−1) compared to the pristine Q-HB-PAES membrane (32.8 mS cm−1), a result supported by the morphology of the membrane as determined by the AFM analysis. In addition, the rigid hyperbranched structure showed a suppressed swelling ratio of 17.9–24.9% despite an excessive water uptake of 33.2–50.3% at 90 °C, and demonstrated a remarkable alkaline stability under 2.0 M KOH conditions over 1000 h. [ABSTRACT FROM AUTHOR]

Novel anion conductive nanocomposite membranes with superb hydroxide conductivity and chemical durability in alkaline conditions were prepared by the introduction of quaternary ammonium functionalized graphene oxide (Q-GO) into quaternized poly(arylene ether) (QPAE) random copolymer. Q-GO containing amino silane units, which induce ion cluster formation in the polymer matrix, was synthesized using (3-aminopropyl)triethoxysilane (APTS) and (3-bromopropyl)trimethyl ammonium bromide (PTMA) as the main quaternization reagents. The chemical structures and morphologies of the polymers and inorganic nanofillers were characterized by 1H NMR, FT-IR, FE-SEM, XPS, and SAXS. GO-(APTS- c -PTMA), the so called Q-GO, was used to expand the ion transfer sites and improve the physicochemical stability of the membrane. The electrochemical properties, thermal/mechanical properties, and chemical stabilities of the anion exchange membranes (AEMs) were investigated in accordance with different contents of GO-(APTS- c -PTMA). The π-π bonds between the polymer matrix and the Q-GO resulted in improved dimensional stability and mechanical properties in the composite membrane. The QPAE/GO-(APTS- c -PTMA) 0.7 wt% membrane showed the highest hydroxide conductivity of 114.2 mS cm−1 at 90 °C with an ion exchange capacity of 1.45 mmol g−1, which is 2.07 times higher than the pristine membrane (55.1 mS cm−1 at 90 °C). Furthermore, the single-cell performance of the QPAE/GO-(APTS- c -PTMA) 0.7 wt% as an AEM showed an excellent maximum power density of 135.8 mW cm−2 at 70 °C. Image 1 • Cheap and easy method for crosslinked anion exchange membrane (AEM) preparation for anion exchange membrane fuel cells AEMFC. • The composite AEMs showed highest hydroxide conductivity. • The prepared composite AEMs exhibit long-term chemical stability (>20 days). • The cell was stably operated at 60 °C for 120 h. [ABSTRACT FROM AUTHOR]

Summary: In this work, sulfonated diblock copolymers (SDBCs) were prepared by polycondensation of sulfonated poly(ether‐ether‐ketone) (SPEEK) and hydrophobic oligomer, which were combined with sintered anatase titanium oxide (S‐An‐TiO2) to create a hybrid membrane for apply in proton exchange membrane fuel cells (PEMFCs) operating with low relative humidity (RH). Then, a series of composite membranes (SDBC/S‐An‐TiO2) were prepared by varying the wt% of S‐An‐TiO2 blended with SDBC. The results showed that appropriate quantity (ie, 15 wt%) of S‐An‐TiO2 can significantly improve the proton conductivity and physiochemical properties of prepared composite membrane, as well as the PEMFC performance and durability under 20% RH. The 1.5 wt% of SDBC/S‐An‐TiO2 offers high current output, power output, and durability values at 60°C under 20% RH, which are 0.207 A cm−2, 0.074 W cm−2 and over 90 hours, respectively. These results can be attributed to the good interfacial compatibility between S‐An‐TiO2 and SDBC. [ABSTRACT FROM AUTHOR]

In Bayesian semi-parametric analyses of time-to-event data, non-parametric process priors are adopted for the baseline hazard function or the cumulative baseline hazard function for a given finite partition of the time axis. However, it would be controversial to suggest a general guideline to construct an optimal time partition. While a great deal of research has been done to relax the assumption of the fixed split times for other non-parametric processes, to our knowledge, no methods have been developed for a gamma process prior, which is one of the most widely used in Bayesian survival analysis. In this paper, we propose a new Bayesian framework for proportional hazards models where the cumulative baseline hazard function is modelled a priori by a gamma process. A key feature of the proposed framework is that the number and position of interval cutpoints are treated as random and estimated based on their posterior distributions. [ABSTRACT FROM AUTHOR]

A series of anion exchange membranes composed of partially fluorinated poly(arylene ether sulfone)s (PAESs) multiblock copolymers bearing quaternary ammonium groups were synthesized with controlled lengths of the hydrophilic precursor and hydrophobic oligomer via direct polycondensation. The chloromethylation and quaternization proceeded well by optimizing the reaction conditions to improve hydroxide conductivity and physical stability, and the fabricated membranes were very flexible and transparent. Atomic force microscope images of quaternized PAES (QN-PAES) membranes showed excellent hydrophilic/hydrophobic phase separation and distinct ion transition channels. An extended architecture of phase separation was observed by increasing the hydrophilic oligomer length, which resulted in significant improvements in the water uptake, ion exchange capacity, and hydroxide conductivity. Furthermore, the open circuit voltage (OCV) of QN-PAES X10Y23 and X10Y13 was found to be above 0.9 V, and the maximum power density of QN-PAES X10Y13 was 131.7 mW cm−2 at 60 °C under 100% RH. [ABSTRACT FROM AUTHOR]

Sulfonated poly(arylene biphenylether sulfone)-poly(arylene ether) (SPABES-PAE) block copolymers by controlling the molar ratio of SPABES and PAE oligomers were successfully synthesized, and the performances of SPABES-PAE (1:2, 1:1, and 2:1) membranes were compared with Nafion 212. The prepared membranes including fluorinated hydrophobic units were stable against heat, nucleophile attack, and physio-chemical durability during the tests. Moreover, the polymers exhibited better solubility in a variety of solvents. The chemical structure of SPABES-PAEs was investigated by 1H nuclear magnetic resonance (1H NMR), Fourier transform infrared spectroscopy (FT-IR), and gel permeation chromatography (GPC). The membrane of SPABES-PAEs was fabricated by the solution casting method, and the membranes were very flexible and transparent with a thickness of 70–90 μm. The morphology of the membranes was observed using atomic force microscope and the ionic domain size was proved by small angle X-ray scattering (SAXS) measurement. The incorporation of polymers including fluorinated units allowed the membranes to provide unprecedented oxidative and dimensional stabilities, as verified from the results of ex situ durability tests and water uptake capacity, respectively. By the collective efforts, we observed an enhanced water retention capacity, reasonable dimensional stability and high proton conductivity, and the peak power density of the SPABES-PAE (2:1) was 333.29 mW·cm−2 at 60 °C under 100% relative humidity (RH). [ABSTRACT FROM AUTHOR]

The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City. [ABSTRACT FROM AUTHOR]

We designed and synthesized a series of sulfonated poly(arylene ether sulfone) (SPES) with different hydrophilic or hydrophobic oligomer ratios using poly-condensation strategy. Afterward, we fabricated the corresponding membranes via a solution-casting approach. We verified the SPES membrane chemical structure using nuclear magnetic resonance (1H NMR) and confirmed the resulting oligomer ratio. Field-emission scanning electron microscope (FE-SEM) and atomic force microscope (AFM) results revealed that we effectively attained phase separation of the SPES membrane along with an increased hydrophilic oligomer ratio. Thermal stability, glass transition temperature (Tg) and membrane elongation increased with the ratio of hydrophilic oligomers. SPES membranes with higher hydrophilic oligomer ratios exhibited superior water uptake, ion-exchange capacity, contact angle and water sorption, while retaining reasonable swelling degree. The proton conductivity results showed that SPES containing higher amounts of hydrophilic oligomers provided a 74.7 mS cm−1 proton conductivity at 90 °C, which is better than other SPES membranes, but slightly lower than that of Nafion-117 membrane. When integrating SPES membranes with proton-exchange membrane fuel cells (PEMFCs) at 60 °C and 80% relative humidity (RH), the PEMFC power density exhibited a similar increment-pattern like proton conductivity pattern. [ABSTRACT FROM AUTHOR]

Each cell comprising an intact, healthy, confluent epithelial layer ordinarily remains sedentary, firmly adherent to and caged by its neighbors, and thus defines an elemental constituent of a solid-like cellular collective [1,2]. After malignant transformation, however, the cellular collective can become fluid-like and migratory, as evidenced by collective motions that arise in characteristic swirls, strands, ducts, sheets, or clusters [3,4]. To transition from a solid-like to a fluid-like phase and thereafter to migrate collectively, it has been recently argued that cells comprising the disordered but confluent epithelial collective can undergo changes of cell shape so as to overcome geometric constraints attributable to the newly discovered phenomenon of cell jamming and the associated unjamming transition (UJT) [1,2,5–9]. Relevance of the jamming concept to carcinoma cells lines of graded degrees of invasive potential has never been investigated, however. Using classical in vitro cultures of six breast cancer model systems, here we investigate structural and dynamical signatures of cell jamming, and the relationship between them [1,2,10,11]. In order of roughly increasing invasive potential as previously reported, model systems examined included MCF10A, MCF10A.Vector; MCF10A.14-3-3ζ; MCF10.ErbB2, MCF10AT; and MCF10CA1a [12–15]. Migratory speed depended on the particular cell line. Unsurprisingly, for example, the MCF10CA1a cell line exhibited much faster migratory speed relative to the others. But unexpectedly, across different cell lines higher speeds were associated with enhanced size of cooperative cell packs in a manner reminiscent of a peloton [9]. Nevertheless, within each of the cell lines evaluated, cell shape and shape variability from cell-to-cell conformed with predicted structural signatures of cell layer unjamming [1]. Moreover, both structure and migratory dynamics were compatible with previous theoretical descriptions of the cell jamming mechanism [2,10,11,16,17]. As such, these findings demonstrate the richness of the cell jamming mechanism, which is now seen to apply across these cancer cell lines but remains poorly understood. • In each of 6 cancer cell lines, cell shape and its variability conformed with predicted structural signatures of unjamming. • Across these different cell lines, cell shape information alone was not sufficient to predict migratory dynamics. • Across cell lines, higher speeds were associated with enhanced cooperative pack sizes in a manner reminiscent of a peloton. [ABSTRACT FROM AUTHOR]

Semi-competing risks refer to the setting where primary scientific interest lies in estimation and inference with respect to a non-terminal event, the occurrence of which is subject to a terminal event. In this paper, we present the R package SemiCompRisks that provides functions to perform the analysis of independent/clustered semi-competing risks data under the illness-death multi-state model. The package allows the user to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions; parametric or non-parametric specifications for random effects distributions when the data are cluster-correlated; and, a Markov or semi-Markov specification for terminal event following non-terminal event. While estimation is mainly performed within the Bayesian paradigm, the package also provides the maximum likelihood estimation for select parametric models. The package also includes functions for univariate survival analysis as complementary analysis tools. [ABSTRACT FROM AUTHOR]

The hydrothermal synthesis behavior of ZnO nanowire (NW) on carbon nanotubes (CNTs) with respect to molar concentrations of zinc nitrate hexahydrate and hexamethylenetetramine and temperature was investigated. The ZnO NWs could be synthesized with a single-crystalline wurtzite structure and a diameter in the range of tens of nanometers. Their size does not strongly depend on the temperature, while it increases with increasing molar concentration. The NWs tend to have pyramidal shape at a growth front with increasing temperature and molar concentration probably due to enriched Zn2+ ion concentration. This demonstrates the morphological dependence of ZnO NWs on the relative rates between the decomposition of Zn precursor and subsequent oxidation of Zn to ZnO in hydrothermal synthesis. [ABSTRACT FROM AUTHOR]

The study was designed to assess the effects of local heat (LH) application on postganglionic muscle sympathetic nerve activity (MSNA) measured by microneurography in healthy men. In the first protocol, MSNA of the left peroneal nerve, blood pressure (BP), heart rate (HR), and skin temperature of the shin (TSK) were recorded in nine men. In the second protocol, leg blood flow (LBF) was measured in the same subjects by strain-gauge plethysmography. In both protocols, after 10 min of rest in the supine position, a heated hydrocollator pack was applied to the shin and anterior foot for 15 min and recovery was monitored over a period of 20 min. TSK gradually increased from 31.7 ± 0.1 to 41.9 ± 0.5°C (mean ± SEM) during LH. No subject complained of pain, and BP and HR remained constant. The MSNA burst rate (16.1 ± 2.1 beats/min) during the control period decreased significantly (P < 0.05) to 72.0 ± 2.3% during LH. Total MSNA also decreased to 59.2 ± 2.6% (P < 0.05) during LH, but both immediately returned to baseline at recovery. In contrast, LBF in the left leg significantly and immediately increased (P < 0.05) after LH application and remained significantly elevated until the end of the recovery period. These results suggest that: (1) LH application significantly attenuates MSNA without any changes in HR and BP. (2) Other factors in addition to MSNA seem to control regional blood flow in the lower extremity during LH. [ABSTRACT FROM AUTHOR]

The development of potential and novel proton exchange membranes (PEMs) is imperative for the further commercialization of PEM fuel cells (PEMFCs). In this work, phosphotungstic acid (PWA) and graphene oxide (GO) were integrated into sulfonated poly(arylene ether) (SPAE) through a solution casting approach to create a potential composite membrane for PEMFC applications. Thermal stability of membranes was observed using thermogravimetric analysis (TGA), and the SPAE/GO/PWA membranes exhibited high thermal stability compared to pristine SPAE membranes, owing to the interaction between SPAEK, GO, and PWA. By using a scanning electron microscope (SEM) and atomic force microscope (AFM), we observed that GO and PWA were evenly distributed throughout the SPAE matrix. The SPAE/GO/PWA composite membrane comprising 0.7 wt% GO and 36 wt% PWA exhibited a maximum proton conductivity of 186.3 mS cm−1 at 90 °C under 100% relative humidity (RH). As a result, SPAE/GO/PWA composite membrane exhibited 193.3 mW cm−2 of the maximum power density at 70 °C under 100% RH in PEMFCs. [ABSTRACT FROM AUTHOR]

Recent advances in CRISPR/Cas gene editing technology have significantly expanded the possibilities and accelerated the pace of creating genetically engineered animal models. However, CRISPR/Cas-based strategies designed to precisely edit the genome can often yield unintended outcomes. Here, we report the use of zygotic CRISPR/Cas9 injections to generate a knock-in GFP reporter mouse at the Gdf11 locus. Phenotypic and genomic characterization of founder animals from these injections revealed a subset that contained the correct targeting event and exhibited GFP expression that, within the hematopoietic system, was restricted predominantly to lymphoid cells. Yet, in another subset of founder mice, we detected aberrant integration events at the target site that dramatically and inaccurately shifted hematopoietic GFP expression from the lymphoid to the myeloid lineage. Additionally, we recovered multiple Gdf11 deletion alleles that modified the C-terminus of the GDF11 protein. When bred to homozygosity, most of these alleles recapitulated skeletal phenotypes reported previously for Gdf11 knockout mice, suggesting that these represent null alleles. However, we also recovered one Gdf11 deletion allele that encodes a novel GDF11 variant protein ("GDF11-WE") predicted to contain two additional amino acids (tryptophan (W) and glutamic acid (E)) at the C-terminus of the mature ligand. Unlike the other Gdf11 deletion alleles recovered in this study, homozygosity for the Gdf11WE allele did not phenocopy Gdf11 knockout skeletal phenotypes. Further investigation using in vivo and in vitro approaches demonstrated that GDF11-WE retains substantial physiological function, indicating that GDF11 can tolerate at least some modifications of its C-terminus and providing unexpected insights into its biochemical activities. Altogether, our study confirms that one-step zygotic injections of CRISPR/Cas gene editing complexes provide a quick and powerful tool to generate gene-modified mouse models. Moreover, our findings underscore the critical importance of thorough characterization and validation of any modified alleles generated by CRISPR, as unintended on-target effects that fail to be detected by simple PCR screening can produce substantially altered phenotypic readouts. [ABSTRACT FROM AUTHOR]