Disparate Outcomes, Biologic and Therapeutic Differences in Pediatric versus Adult Patients with Ewing Sarcoma.

INTRODUCTION: Ewing sarcoma (ES) is a small blue round cell sarcoma affecting a wide age spectrum. Clinical advances predominately stem from pediatric research consortia clinical trials. In most series, adults have poorer outcomes when compared to children. The aim of this study was to perform a detailed evaluation of factors potentially accounting for this difference. METHODS: A single institution retrospective chart review was conducted on patients with ES diagnosed from 2005 to 2015, identified using a free-text search engine with the keywords "Ewing sarcoma" as well as a corresponding pathologic database. Data were analyzed based on age, pediatric (age <18) and adult (age >18 years), using a multivariate analysis model. RESULTS: Eighty-eight ES patients (34 pediatric, 54 adult) were identified with a median age of 13 (range 3-18) and 31 (range 19-70) in their respective cohorts. Five-year overall survival (OS) was higher in pediatric patients (73.5% vs. 48.1%, p = 0.0213). By stage, 5-year OS in pediatric versus adult patients was 65% versus 20% (p = 0.0530) in metastatic (n = 32) and 68.1% versus 58.8% (p = 0.278) in localized (n = 56) patients. Lung-only metastases were present in 83% of metastatic pediatric patients versus 35% of adult metastatic patients. Pediatric patients received more cycles of first-line chemotherapy (13.8 vs. 11.4, p = 0.001), independent of stage. More cycles of chemotherapy correlated with improved OS (HR: 0.864, CI: 0.773-0.967) and progression-free survival (HR: 0.897, CI: 0.808-0.996). CONCLUSIONS: Outcome differences were most notable in patients with metastatic disease, although not statistically significant. Our series found differences in presentation between pediatric and adult populations with adult patients receiving fewer cycles of chemotherapy. This may suggest that both variations in underlying disease biology and potentially differences in treatment may account for outcome disparities.

Association between early childhood lower respiratory tract infections and subsequent asthma.

OBJECTIVE: We examined the relationship between recurrent lower respiratory tract infections (LRTI) in young children and subsequent childhood asthma outcomes. METHODS: Retrospective cohort study using 2009-2017 Colorado All Payer Claims Database to assess 0- to 2-year-old children with visits due to LRTI and acute gastroenteritis (AGE). The primary exposure was number of LRTI visits prior to 2 years of age. Children with AGE served as the no LRTI comparator group. The primary outcome was incident asthma, defined by ICD-9 (490.XX) or ICD-10 (J45.9XX) codes, in the same children between 3 and 9 years of age. Multivariable accelerated failure time (AFT) models were used to estimate the effect of LRTI visits on median time to asthma diagnosis. Sensitivity analyses were performed using more conservative asthma diagnostic criteria and with hospitalized children only. RESULTS: Of 38,441 eligible subjects, 32,729 had ≥1 LRTI and 5,712 had AGE (no LRTI) between 0 and 2 years of age. Children with ≥3 LRTI visits had an 80% decrease in median time to asthma diagnosis relative to those with AGE visits only (time ratio [TR] 0.2; 95% CI 0.16, 0.24). Children with ≥3 LRTI hospitalizations had a 98% reduction in median time to asthma diagnosis relative to those with AGE hospitalizations only (TR 0.02; 95% CI 0.01, 0.07). History of atopy, wheezing, and family history of asthma documented prior to 2 years of age were also associated with earlier asthma diagnosis. CONCLUSIONS: Recurrent LRTIs, especially LRTI hospitalizations, before 2 years of age are associated with earlier diagnosis of pediatric asthma.

Bacterial xylan utilization regulons: systems for coupling depolymerization of methylglucuronoxylans with assimilation and metabolism.

Bioconversion of lignocellulosic resources offers an economically promising path to renewable energy. Technological challenges to achieving bioconversion include the development of cost-effective processes that render the cellulose and hemicellulose components of these resources to fermentable hexoses and pentoses. Natural bioprocessing of the hemicellulose fraction of lignocellulosic biomass requires depolymerization of methylglucuronoxylans. This requires secretion of endoxylanases that release xylooligosaccharides and aldouronates. Physiological, biochemical, and genetic studies with selected bacteria support a process in which a cell-anchored multimodular GH10 endoxylanase catalyzes release of the hydrolysis products, aldotetrauronate, xylotriose, and xylobiose, which are directly assimilated and metabolized. Gene clusters encoding intracellular enzymes, including α-glucuronidase, endoxylanase, ß-xylosidase, ABC transporter proteins, and transcriptional regulators, are coordinately responsive to substrate induction or repression. The rapid rates of glucuronoxylan utilization and microbial growth, along with the absence of detectable products of depolymerization in the medium, indicate that assimilation and depolymerization are coupled processes. Genomic comparisons provide evidence that such systems occur in xylanolytic species in several genera, including Clostridium, Geobacillus, Paenibacillus, and Thermotoga. These systems offer promise, either in their native configurations or through gene transfer to other organisms, to develop biocatalysts for efficient production of fuels and chemicals from the hemicellulose fractions of lignocellulosic resources.

A flexible mixed-data model applied to claims data for post-market surveillance of prescription drug safety behavior.

We develop a new modeling framework for jointly modeling first prescription times and the presence of risk-mitigating behavior for prescription drugs using real-world data. We are interested in active surveillance of clinical quality improvement programs, especially for drugs which enter the market under an FDA-mandated Risk Evaluation and Mitigation Strategy (REMS). Our modeling framework attempts to jointly model two important aspects of prescribing, the time between a drug's initial marketing and a patient's first prescription of that drug, and the presence of risk-mitigating behavior at the first prescription. First prescription times can be flexibly modeled as a mixture of component distributions to accommodate different subpopulations and allow the proportion of prescriptions that exhibit risk-mitigating behavior to change for each component. Risk-mitigating behavior is defined in the context of each drug. We develop a joint model using a mixture of positive unimodal distributions to model first prescription times, and a logistic regression model conditioned on component membership to model the presence of risk-mitigating behavior. We apply our model to two recently approved extended release/long-acting (ER/LA) opioids, which have an FDA-approved blueprint for best prescribing practices to inform our definition of risk-mitigating behavior. We also apply our methods to simulated data to evaluate their performance under various conditions such as clustering.

Application of gap time analysis with flexible hazards to pulmonary exacerbations in the EPIC observational study.

Cystic fibrosis and other chronic lung disease clinical trials often use time to first pulmonary exacerbation (PEx) or total PEx count as endpoints. The use of these outcomes may fail to capture patterns or timing of multiple exacerbations and how covariates influence the risk of future exacerbations. Analysis of gap times between PEx provides a useful framework to understand risks of subsequent events, particularly to assess if there is a temporary increase in a hazard of a subsequent PEx following the occurrence of a PEx. This may be useful for estimating the amount of time needed to follow patients after a PEx and predicting which patients are more likely to have multiple PEx. We propose a smoothed hazard for gap times to account for elevated hazards after exacerbations. A simulation study was conducted to explore model performance and was able to appropriately estimate parameters in all situations with an underlying change point with independent or correlated recurrent events. Models with different change-point structures and trends are compared using Early Pseudomonas Infection Control (EPIC) observational study data, using a quasi-likelihood modification of the Akaike information criterion; a model with a change-point provided a better fit than a model without one. The analysis suggests that the change point may be 1.8 years (SE 0.09) after the end of a PEx. Models including covariates in the hazard function revealed that having one or two copies of the Δ$\Delta$ F508 mutation, female sex, and higher numbers of previous PEx were significantly associated with increased risk of another PEx.

Analysis of Stroke Care Among 2019-2020 National Emergency Medical Services Information System Encounters.

OBJECTIVES: Emergency Medicine Service (EMS) providers play a pivotal role in early identification and initiation of treatment for stroke. The objective of this study is to characterize nationwide EMS practices for suspected stroke and assess for gender-based differences in compliance with American Stroke Association (ASA) guidelines. MATERIALS AND METHODS: Using the 2019-2020 National Emergency Medical Services Information System (NEMSIS) Datasets, we identified encounters with an EMS designated primary impression of stroke. We characterized patient characteristics and EMS practices and assessed compliance with eight metrics for "guideline-concordant" care. Multivariable logistic regression modeled the association between gender and the primary outcome (guideline-concordant care), adjusted for age, EMS level of service, EMS geographical region, region type (i.e. urban or rural), and year. RESULTS: Of 693,177 encounters with a primary impression of stroke, overall compliance with each performance metric ranged from 18% (providing supplemental oxygen when the pulse oximetry is less than 94%) to 76% (less than 90sec from incoming call to EMS dispatch). 2,382 (0.39%) encounters were fully guideline-concordant. Women were significantly less likely than men to receive guideline-concordant care (adjusted OR 0.82, 95% CI 0.75-0.89; 0.36% women, 0.43% men with guideline-concordant care). CONCLUSIONS: A minority of patients received prehospital stroke care that was documented to be compliant with ASA guidelines. Women were less likely to receive fully guideline-compliant care compared to men, after controlling for confounders, although the difference was small and of uncertain climical importance. Further studies are needed to evaluate the underlying reasons for this disparity, its impact on patient outcomes, and to identify potential targeted interventions to improve prehospital stroke care.

Screening for chronic diseases: optimizing lead time through balancing prescribed frequency and individual adherence.

Screening for chronic diseases, such as cancer, is an important public health priority, but traditionally only the frequency or rate of screening has received attention. In this work, we study the importance of adhering to recommended screening policies and develop new methodology to better optimize screening policies when adherence is imperfect. We consider a progressive disease model with four states (healthy, undetectable preclinical, detectable preclinical, clinical), and overlay this with a stochastic screening-behavior model using the theory of renewal processes that allows us to capture imperfect adherence to screening programs in a transparent way. We show that decreased adherence leads to reduced efficacy of screening programs, quantified here using elements of the lead time distribution (i.e., the time between screening diagnosis and when diagnosis would have occurred clinically in the absence of screening). Under the assumption of an inverse relationship between prescribed screening frequency and individual adherence, we show that the optimal screening frequency generally decreases with increasing levels of non-adherence. We apply this model to an example in breast cancer screening, demonstrating how accounting for imperfect adherence affects the recommended screening frequency.

High-fat diet induces an ovulatory defect associated with dysregulated endothelin-2 in mice.

High-fat diet (HFD) consumption in female rodents causes impaired estrous cyclicity, fewer pups per litter, and dysregulation of key ovulatory genes suggesting that HFD-induced subfertility may be due to ovulatory dysfunction. To test this hypothesis female mice were fed chow or HFD for 10 weeks at which point ovulation and ovarian gene expression of endothelin-2 (Edn2), a gene critical for ovulation, were assessed. After 10 weeks of HFD, both mice that remained lean and those that became obese had fewer ovulated oocytes than chow controls (P = 0.041, P = 0.0030, respectively). In chow controls, Edn2 was expressed as expected with basal levels during diestrus and proestrus, increased 11.6-fold during estrus, and decreased to basal levels during metestrus. In HFD mice, Edn2 was dysregulated across the entire estrous cycle as were other Edn2 system components (endothelin converting enzyme 1 (Ece-1), and the endothelin receptors (Ednra, Ednrb)). Interestingly, we found dysregulation of key ovarian steroidogenic genes after HFD. We also found that estradiol treatment in prepubertal mice increased Edn2 expression in the ovary (P = 0.030), suggesting that impaired steroidogenesis may be involved in the HFD-induced dysregulation of ovarian Edn2. In conclusion, HFD leads to ovulatory dysfunction regardless of the development of obesity, which appears to be mediated through dysregulation of ovarian Edn2 expression.

Association Between Chronic Inflammatory Diseases and Stroke-Associated Pneumonia - An Epidemiological Study.

BACKGROUND: Pneumonia, the most common post-acute ischemic stroke (AIS) infection, accounts for up to 30% of deaths after a stroke. Multiple chronic inflammatory diseases, such as rheumatoid arthritis, psoriasis, and inflammatory bowel disease, are associated with increased risk of stroke and stroke morbidity. This study assessed the relationship between chronic inflammatory diseases and stroke-associated pneumonia (SAP). METHODS: Using data from the 2015-2017 National Inpatient Sample, we classified hospital discharges with a diagnosis of AIS as having ulcerative colitis, Crohn's disease, rheumatoid arthritis, psoriasis, systemic lupus erythematosus, other chronic inflammatory diseases, multiple chronic inflammatory diseases, or none. With multivariable logistic regression, we assessed for associations between chronic inflammatory disease and in-hospital SAP or death. RESULTS: Among AIS discharges, there was a decreased risk of SAP among those with psoriasis or other chronic inflammatory diseases (adjusted odds ratio (aOR) 0.70, 95%CI 0.63-0.99; aOR 0.64, 95%CI, 0.46-0.89, respectively), compared to those without psoriasis and without other chronic inflammatory disease, respectively. Rheumatoid arthritis, psoriasis, and other chronic inflammatory diseases were associated with reduced in-hospital mortality (aOR 0.89, 95%CI 0.78-1.00; aOR 0.77, 95%CI 0.59-1.00; aOR 0.69, 95%CI 0.50-0.94, respectively). CONCLUSIONS: The risk of SAP and in-hospital mortality varies by chronic inflammatory disease - psoriasis and other chronic inflammatory diseases are associate with reduced rates of SAP, whereas rheumatoid arthritis, psoriasis and other chronic inflammatory disease were associated with reduced in-hospital mortality. Further investigations are needed to determine a relationship between the potential role of immunomodulation and the reduction in SAP and mortality in chronic inflammatory diseases.

Modeling the rate of HIV testing from repeated binary data amidst potential never-testers.

Many longitudinal studies with a binary outcome measure involve a fraction of subjects with a homogeneous response profile. In our motivating data set, a study on the rate of human immunodeficiency virus (HIV) self-testing in a population of men who have sex with men (MSM), a substantial proportion of the subjects did not self-test during the follow-up study. The observed data in this context consist of a binary sequence for each subject indicating whether or not that subject experienced any events between consecutive observation time points, so subjects who never self-tested were observed to have a response vector consisting entirely of zeros. Conventional longitudinal analysis is not equipped to handle questions regarding the rate of events (as opposed to the odds, as in the classical logistic regression model). With the exception of discrete mixture models, such methods are also not equipped to handle settings in which there may exist a group of subjects for whom no events will ever occur, i.e. a so-called "never-responder" group. In this article, we model the observed data assuming that events occur according to some unobserved continuous-time stochastic process. In particular, we consider the underlying subject-specific processes to be Poisson conditional on some unobserved frailty, leading to a natural focus on modeling event rates. Specifically, we propose to use the power variance function (PVF) family of frailty distributions, which contains both the gamma and inverse Gaussian distributions as special cases and allows for the existence of a class of subjects having zero frailty. We generalize a computational algorithm developed for a log-gamma random intercept model (Conaway, 1990. A random effects model for binary data. Biometrics46, 317-328) to compute the exact marginal likelihood, which is then maximized to obtain estimates of model parameters. We conduct simulation studies, exploring the performance of the proposed method in comparison with competitors. Applying the PVF as well as a Gaussian random intercept model and a corresponding discrete mixture model to our motivating data set, we conclude that the group assigned to receive follow-up messages via SMS was self-testing at a significantly lower rate than the control group, but that there is no evidence to support the existence of a group of never-testers.

Regularity of a renewal process estimated from binary data.

Assessment of the regularity of a sequence of events over time is important for clinical decision-making as well as informing public health policy. Our motivating example involves determining the effect of an intervention on the regularity of HIV self-testing behavior among high-risk individuals when exact self-testing times are not recorded. Assuming that these unobserved testing times follow a renewal process, the goals of this work are to develop suitable methods for estimating its distributional parameters when only the presence or absence of at least one event per subject in each of several observation windows is recorded. We propose two approaches to estimation and inference: a likelihood-based discrete survival model using only time to first event; and a potentially more efficient quasi-likelihood approach based on the forward recurrence time distribution using all available data. Regularity is quantified and estimated by the coefficient of variation (CV) of the interevent time distribution. Focusing on the gamma renewal process, where the shape parameter of the corresponding interevent time distribution has a monotone relationship with its CV, we conduct simulation studies to evaluate the performance of the proposed methods. We then apply them to our motivating example, concluding that the use of text message reminders significantly improves the regularity of self-testing, but not its frequency. A discussion on interesting directions for further research is provided.

In planta production and characterization of a hyperthermostable GH10 xylanase in transgenic sugarcane.

Sugarcane (Saccharum sp. hybrids) is one of the most efficient and sustainable feedstocks for commercial production of fuel ethanol. Recent efforts focus on the integration of first and second generation bioethanol conversion technologies for sugarcane to increase biofuel yields. This integrated process will utilize both the cell wall bound sugars of the abundant lignocellulosic sugarcane residues in addition to the sucrose from stem internodes. Enzymatic hydrolysis of lignocellulosic biomass into its component sugars requires significant amounts of cell wall degrading enzymes. In planta production of xylanases has the potential to reduce costs associated with enzymatic hydrolysis but has been reported to compromise plant growth and development. To address this problem, we expressed a hyperthermostable GH10 xylanase, xyl10B in transgenic sugarcane which displays optimal catalytic activity at 105 °C and only residual catalytic activity at temperatures below 70 °C. Transgene integration and expression in sugarcane were confirmed by Southern blot, RT-PCR, ELISA and western blot following biolistic co-transfer of minimal expression cassettes of xyl10B and the selectable neomycin phosphotransferase II. Xylanase activity was detected in 17 transgenic lines with a fluorogenic xylanase activity assay. Up to 1.2% of the total soluble protein fraction of vegetative progenies with integration of chloroplast targeted expression represented the recombinant Xyl10B protein. Xyl10B activity was stable in vegetative progenies. Tissues retained 75% of the xylanase activity after drying of leaves at 35 °C and a 2 month storage period. Transgenic sugarcane plants producing Xyl10B did not differ from non-transgenic sugarcane in growth and development under greenhouse conditions. Sugarcane xylan and bagasse were used as substrate for enzymatic hydrolysis with the in planta produced Xyl10B. TLC and HPLC analysis of hydrolysis products confirmed the superior catalytic activity and stability of the in planta produced Xyl10B with xylobiose as a prominent degradation product. These findings will contribute to advancing consolidated processing of lignocellulosic sugarcane biomass.

Semiparametric time-to-event modeling in the presence of a latent progression event.

In cancer research, interest frequently centers on factors influencing a latent event that must precede a terminal event. In practice it is often impossible to observe the latent event precisely, making inference about this process difficult. To address this problem, we propose a joint model for the unobserved time to the latent and terminal events, with the two events linked by the baseline hazard. Covariates enter the model parametrically as linear combinations that multiply, respectively, the hazard for the latent event and the hazard for the terminal event conditional on the latent one. We derive the partial likelihood estimators for this problem assuming the latent event is observed, and propose a profile likelihood-based method for estimation when the latent event is unobserved. The baseline hazard in this case is estimated nonparametrically using the EM algorithm, which allows for closed-form Breslow-type estimators at each iteration, bringing improved computational efficiency and stability compared with maximizing the marginal likelihood directly. We present simulation studies to illustrate the finite-sample properties of the method; its use in practice is demonstrated in the analysis of a prostate cancer data set.

Semiparametric profile likelihood estimation for continuous outcomes with excess zeros in a random-threshold damage-resistance model.

Continuous outcome data with a proportion of observations equal to zero (often referred to as semicontinuous data) arise frequently in biomedical studies. Typical approaches involve two-part models, with one part a logistic model for the probability of observing a zero and some parametric continuous distribution for modeling the positive part of the data. We propose a semiparametric model based on a biological system with competing damage manifestation and resistance processes. This allows us to derive a closed-form profile likelihood based on the retro-hazard function, leading to a flexible procedure for modeling continuous data with a point mass at zero. A simulation study is presented to examine the properties of the method in finite samples. We apply the method to a data set consisting of pulmonary capillary hemorrhage area in lab rats subjected to diagnostic ultrasound. Copyright © 2017 John Wiley & Sons, Ltd.

Meta-analysis of gene-environment interaction exploiting gene-environment independence across multiple case-control studies.

Multiple papers have studied the use of gene-environment (G-E) independence to enhance power for testing gene-environment interaction in case-control studies. However, studies that evaluate the role of G-E independence in a meta-analysis framework are limited. In this paper, we extend the single-study empirical Bayes type shrinkage estimators proposed by Mukherjee and Chatterjee (2008) to a meta-analysis setting that adjusts for uncertainty regarding the assumption of G-E independence across studies. We use the retrospective likelihood framework to derive an adaptive combination of estimators obtained under the constrained model (assuming G-E independence) and unconstrained model (without assumptions of G-E independence) with weights determined by measures of G-E association derived from multiple studies. Our simulation studies indicate that this newly proposed estimator has improved average performance across different simulation scenarios than the standard alternative of using inverse variance (covariance) weighted estimators that combines study-specific constrained, unconstrained, or empirical Bayes estimators. The results are illustrated by meta-analyzing 6 different studies of type 2 diabetes investigating interactions between genetic markers on the obesity related FTO gene and environmental factors body mass index and age.

GH115 α-glucuronidase and GH11 xylanase from Paenibacillus sp. JDR-2: potential roles in processing glucuronoxylans.

Paenibacillus sp. JDR-2 (Pjdr2) has been studied as a model for development of bacterial biocatalysts for efficient processing of xylans, methylglucuronoxylan, and methylglucuronoarabinoxylan, the predominant hemicellulosic polysaccharides found in dicots and monocots, respectively. Pjdr2 produces a cell-associated GH10 endoxylanase (Xyn10A1) that catalyzes depolymerization of xylans to xylobiose, xylotriose, and methylglucuronoxylotriose with methylglucuronate-linked α-1,2 to the nonreducing terminal xylose. A GH10/GH67 xylan utilization regulon includes genes encoding an extracellular cell-associated Xyn10A1 endoxylanase and an intracellular GH67 α-glucuronidase active on methylglucuronoxylotriose generated by Xyn10A1 but without activity on methylglucuronoxylotetraose generated by a GH11 endoxylanase. The sequenced genome of Pjdr2 contains three paralogous genes potentially encoding GH115 α-glucuronidases found in certain bacteria and fungi. One of these, Pjdr2_5977, shows enhanced expression during growth on xylans along with Pjdr2_4664 encoding a GH11 endoxylanase. Here, we show that Pjdr2_5977 encodes a GH115 α-glucuronidase, Agu115A, with maximal activity on the aldouronate methylglucuronoxylotetraose selectively generated by a GH11 endoxylanase Xyn11 encoded by Pjdr2_4664. Growth of Pjdr2 on this methylglucuronoxylotetraose supports a process for Xyn11-mediated extracellular depolymerization of methylglucuronoxylan and Agu115A-mediated intracellular deglycosylation as an alternative to the GH10/GH67 system previously defined in this bacterium. A recombinantly expressed enzyme encoded by the Pjdr2 agu115A gene catalyzes removal of 4-O-methylglucuronate residues α-1,2 linked to internal xylose residues in oligoxylosides generated by GH11 and GH30 xylanases and releases methylglucuronate from polymeric methylglucuronoxylan. The GH115 α-glucuronidase from Pjdr2 extends the discovery of this activity to members of the phylum Firmicutes and contributes to a novel system for bioprocessing hemicelluloses.

A 1,3-1,4-ß-Glucan Utilization Regulon in Paenibacillus sp. Strain JDR-2.

Paenibacillus sp. strain JDR-2 (Paenibacillus JDR-2) secretes a multimodular cell-associated glycoside hydrolase family 10 (GH10) endoxylanase (XynA10A1) that catalyzes the depolymerization of methylglucuronoxylan (MeGXn) and rapidly assimilates the products of depolymerization. Efficient utilization of MeGXn has been postulated to result from the coupling of the processes of exocellular depolymerization and assimilation of oligosaccharide products, followed by intracellular metabolism. Growth and substrate utilization patterns with barley glucan and laminarin similar to those observed with MeGXn as a substrate suggest similar processes for 1,3-1,4-ß-glucan and 1,3-ß-glucan depolymerization and product assimilation. The Paenibacillus JDR-2 genome includes a cluster of genes encoding a secreted multimodular GH16 ß-glucanase (Bgl16A1) containing surface layer homology (SLH) domains, a secreted GH16 ß-glucanase with only a catalytic domain (Bgl16A2), transporter proteins, and transcriptional regulators. Recombinant Bgl16A1 and Bgl16A2 catalyze the formation of trisaccharides, tetrasaccharides, and larger oligosaccharides from barley glucan and of mono-, di-, tri-, and tetrasaccharides and larger oligosaccharides from laminarin. The lack of accumulation of depolymerization products during growth and a marked preference for polymeric glucan over depolymerization products support a process coupling extracellular depolymerization, assimilation, and intracellular metabolism for ß-glucans similar to that ascribed to the GH10/GH67 xylan utilization system in Paenibacillus JDR-2. Coordinate expression of genes encoding GH16 ß-glucanases, transporters, and transcriptional regulators supports their role as a regulon for the utilization of soluble ß-glucans. As in the case of the xylan utilization regulons, this soluble ß-glucan regulon provides advantages in the growth rate and yields on polymeric substrates and may be exploited for the efficient conversion of plant-derived polysaccharides to targeted products.

Metabolic potential of Bacillus subtilis 168 for the direct conversion of xylans to fermentation products.

Methylglucuronoxylans (MeGXn) and methylglucuronoarabinoxylans (MeGAXn) respectively comprise most of the hemicellulose fractions in dicots and monocots and, next to cellulose, are the major resources for the production of fuels and chemicals from lignocellulosics. With either MeGXn or MeGAXn as a substrate, Bacillus subtilis 168 accumulates acidic methylglucuronoxylotriose as a limit product following the uptake and metabolism of neutral xylooligosaccharides. Secreted GH11 endoxylanase (Xyn11A), GH30 endoxylanase (Xyn30C), and GH43 arabinoxylan arabinofuranohydrolase (Axh43) respectively encoded by the xynA, xynC, and xynD genes collectively contribute to the depolymerization of MeGAXn. Studies here demonstrate the complementary roles of these enzymes in the digestion of MeGAXn. Coordinate expression of the xynD and xynC genes defines an operon accounting for the Axh43-catalyzed release of arabinose followed by Xyn30C and Xyn11A-catalyzed depolymerization of MeGAXn. Both sources generate acetate and lactate as the principal fermentation products, with yields of 26 % acetate and 32 % lactate from MeGXn compared to 22 % acetate and 21 % lactate from MeGAXn. These studies of the GH43/GH30/GH11 system in B. subtilis 168 provide a basis for the further development of B. subtilis and related species as biocatalysts for direct conversion of hemicellulose derived from energy crops as well as agricultural and forest residues to chemical feedstocks.

The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-regression, for the interaction parameter. The AWE retains full efficiency of the joint analysis using individual level data under certain natural assumptions. Lin and Zeng (2010a, b) showed that a multivariate inverse-variance weighted estimator retains full efficiency as joint analysis using individual level data, if the estimates with full covariance matrices for all the common parameters are pooled across all studies. We show consistency of our work with Lin and Zeng (2010a, b). Without sacrificing much efficiency, the AWE uses only univariate summary statistics from each study, and bypasses issues with sharing individual level data or full covariance matrices across studies. We compare the performance of the methods both analytically and numerically. The methods are illustrated through meta-analysis of interaction between Single Nucleotide Polymorphisms in FTO gene and body mass index on high-density lipoprotein cholesterol data from a set of eight studies of type 2 diabetes.

Engineering the xylan utilization system in Bacillus subtilis for production of acidic Xylooligosaccharides.

Xylans are the predominant polysaccharides in hemicelluloses and an important potential source of biofuels and chemicals. The ability of Bacillus subtilis subsp. subtilis strain 168 to utilize xylans has been ascribed to secreted glycoside hydrolase family 11 (GH11) and GH30 endoxylanases, encoded by the xynA and xynC genes, respectively. Both of these enzymes have been defined with respect to structure and function. In this study, the effects of deletion of the xynA and xynC genes, individually and in combination, were evaluated for xylan utilization and formation of acidic xylooligosaccharides. Parent strain 168 depolymerizes methylglucuronoxylans (MeGXn), releasing the xylobiose and xylotriose utilized for growth and accumulating the aldouronate methylglucuronoxylotriose (MeGX3) with some methylglucuronoxylotetraose (MeGX4). The combined GH11 and GH30 activities process the products generated by their respective actions on MeGXn to release a maximal amount of neutral xylooligosaccharides for assimilation and growth, at the same time forming MeGX3 in which the internal xylose is substituted with methylglucuronate (MeG). Deletion of xynA results in the accumulation of ß-1,4-xylooligosaccharides with degrees of polymerization ranging from 4 to 18 and an average degree of substitution of 1 in 7.2, each with a single MeG linked α-1,2 to the xylose penultimate to the xylose at the reducing terminus. Deletion of the xynC gene results in the accumulation of aldouronates comprised of 4 or more xylose residues in which the MeG may be linked α-1,2 to the xylose penultimate to the nonreducing xylose. These B. subtilis lines may be used for the production of acidic xylooligosaccharides with applications in human and veterinary medicine.