Putting a Price on Prisoner Release: The History of Bail and the Future of Parole

In this article, we argue that the history of bail foretells the future of parole. Under a plancalled the Conditional Post-Conviction Release Bond Act (recently passed into law inthree states), US prisoners can secure early release only after posting ‘post-convictionbail’. As with pre-trial bail, the fledgling model would require prisoners to pay a percent-age of the bail amount to secure their release under the contractual responsibility of acommercial bail agency. If release conditions are breached, bounty hunters are legallyempowered to seize and return the parolee to prison. Our inquiry outlines the origins of this post-conviction bond plan and the research upon which it is based. Drawing on the‘new penology’ framework, we identify several underlying factors that make for a ripeadvocacy environment and set the stage for widespread state-level adoption of this planin the near future. Post-conviction bail fits squarely within the growing policy trendstoward privatization, managerialism, and actuarial justice. Most importantly, though,advocates have the benefit of precedent on their side, as most US states have longrelied on a system of commercial bail bonding and private bounty hunting to manageconditional pretrial release.

Pax7-expressing satellite cells are indispensable for adult skeletal muscle regeneration

Distinct cell populations with regenerative capacity have been reported to contribute to myofibres after skeletal muscle injury, including non-satellite cells as well as myogenic satellite cells. However, the relative contribution of these distinct cell types to skeletal muscle repair and homeostasis and the identity of adult muscle stem cells remain unknown. We generated a model for the conditional depletion of satellite cells by expressing a human diphtheria toxin receptor under control of the murine Pax7 locus. Intramuscular injection of diphtheria toxin during muscle homeostasis, or combined with muscle injury caused by myotoxins or exercise, led to a marked loss of muscle tissue and failure to regenerate skeletal muscle. Moreover, the muscle tissue became infiltrated by inflammatory cells and adipocytes. This localised loss of satellite cells was not compensated for endogenously by other cell types, but muscle regeneration was rescued after transplantation of adult Pax7(+) satellite cells alone. These findings indicate that other cell types with regenerative potential depend on the presence of the satellite cell population, and these observations have important implications for myopathic conditions and stem cell-based therapeutic approaches.

Proton pump inhibitors and histamine-2-receptor antagonists and pancreatic cancer risk: a nested case-control study

Background: The relationship between use of proton pump inhibitors (PPIs) and histamine-2-receptor antagonists (H₂RAs) and pancreatic cancer risk has yet to be examined. Data from a range of studies suggest biologically plausible mechanisms, whereby these drugs (or the conditions for which they are prescribed) may affect pancreatic cancer risk. The objective of this study was to investigate the relationship between use of PPIs/H₂RAs and pancreatic cancer risk.

Methods: A nested case – control study was conducted within the UK general practice research database (GPRD). Cases had a diagnosis of exocrine pancreatic cancer and controls were matched to cases on general practice site, sex and year of birth. Exposure to PPIs and to H₂RAs since entry into GPRD until 2 years before the diagnosis date (corresponding date in controls) and in the 5 years before the diagnosis date were separately assessed. Conditional logistic regression analyses were used to generate odds ratios (ORs) and 95% confidence intervals (CIs) associated with PPI or H₂RA use compared with nonuse.

Results: Ever use of PPIs since entry into the GPRD (excluding the 2 years prior to diagnosis) was not associated with risk of pancreatic cancer; OR (95% CI) 1.02 (0.85 – 1.22). Neither the dose nor the duration of PPI or H₂RA use was associated with pancreatic cancer risk. No consistent patterns of association were seen when cumulative exposure (dose and duration) to these drugs was examined separately or together.

Conclusion: PPI/H₂RA use, in a UK population, was not associated with pancreatic cancer risk.

Luminescent Photoinduced Electron Transfer (PET) Molecules for Sensing and Logic Operations

Chemical species can serve as inputs to supramolecular devices so that a luminescence output is created in a conditional manner. Conditionality is built into these devices by employing the classical photochemical process of photoinduced electron transfer (PET) to compete with luminescence emission. The response of these devices in the analogue regime leads to sensors that can operate in nanometric, micrometric, and millimetric spaces. Some of these devices serve in membrane science, cell physiology, and medical diagnostics. The response in the digital regime leads to Boolean logic gates. Some of these find application in improving aspects of medical diagnostics and in identifying small objects in large populations.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

A model for radiation-induced bystander effects, with allowance for spatial position and the effects of cell turnover

Bystander effects, whereby cells that are not directly exposed to ionizing radiation exhibit adverse biological effects, have been observed in a number of experimental systems. A novel stochastic model of the radiation-induced bystander effect is developed that takes account of spatial location, cell killing and repopulation. The ionizing radiation dose- and time-responses of this model are explored, and it is shown to exhibit pronounced downward curvature in the high dose-rate region, similar to that observed in many experimental systems, reviewed in the paper. It is also shown to predict the augmentation of effect after fractionated delivery of dose that has been observed in certain experimental systems. It is shown that the generally intractable solution of the full stochastic system can be considerably simplified by assumption of pairwise conditional dependence that varies exponentially over time. (C) 2004 Elsevier Ltd. All rights reserved.

Speculative Return Address Stack Management Revisited

Branch prediction feeds a speculative execution processor core with instructions. Branch mispredictions are inevitable and have negative effects on performance and energy consumption. With the advent of highly accurate conditional branch predictors, nonconditional branch instructions are gaining importance.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

Assessing length of stay and associated characteristics of geriatric patients in Northern Ireland

The effective provision of care for the elderly is becoming increasingly more difficult. This is due to the rising proportion of elderly in the population, increasing demands placed on the health services and the financial strain placed on an already stretched economy. The research presented in this paper uses three different models to represent the length of stay distribution of geriatric patients admitted to one of the six key acute hospitals in Northern Ireland and various patient characteristics associated with their respective length of stay. The accurate modelling of bed usage within wards would enable hospital managers to prepare patient discharge packages and rehabilitation services in advance. The models presented within the paper include a Cox proportional hazards model, a Bayesian network with a discrete variable to represent length of stay and a special conditional phase-type model (C-Ph) with a connecting outcome node. This research demonstrates the new efficient fitting algorithm employed for Coxian phase-type distributions while updating C-Ph models for recent elderly patient data.

Population-based study reveals new risk-stratification biomarker panel for Barrett's esophagus

BACKGROUND & AIMS: The risk of progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) is low and difficult to calculate. Accurate tools to determine risk are needed to optimize surveillance and intervention. We assessed the ability of candidate biomarkers to predict which cases of BE will progress to EAC or high-grade dysplasia and identified those that can be measured in formalin-fixed tissues. METHODS: We analyzed data from a nested case-control study performed using the population-based Northern Ireland BE Register (1993-2005). Cases who progressed to EAC (n = 89) or high-grade dysplasia =6 months after diagnosis with BE were matched to controls (nonprogressors, n = 291), for age, sex, and year of BE diagnosis. Established biomarkers (abnormal DNA content, p53, and cyclin A expression) and new biomarkers (levels of sialyl Lewis(a), Lewis(x), and Aspergillus oryzae lectin [AOL] and binding of wheat germ agglutinin) were assessed in paraffin-embedded tissue samples from patients with a first diagnosis of BE. Conditional logistic regression analysis was applied to assess odds of progression for patients with dysplastic and nondysplastic BE, based on biomarker status. RESULTS: Low-grade dysplasia and all biomarkers tested, other than Lewis(x), were associated with risk of EAC or high-grade dysplasia. In backward selection, a panel comprising low-grade dysplasia, abnormal DNA ploidy, and AOL most accurately identified progressors and nonprogressors. The adjusted odds ratio for progression of patients with BE with low-grade dysplasia was 3.74 (95% confidence interval, 2.43-5.79) for each additional biomarker and the risk increased by 2.99 for each additional factor (95% confidence interval, 1.72-5.20) in patients without dysplasia. CONCLUSIONS: Low-grade dysplasia, abnormal DNA ploidy, and AOL can be used to identify patients with BE most likely to develop EAC or high-grade dysplasia.

Contributions of two UDP-glucose dehydrogenases to viability and polymyxin B resistance of Burkholderia cenocepacia

Burkholderia cenocepacia is highly resistant to antimicrobial peptides and we hypothesized that the conversion of UDP-glucose to UDP-glucuronic acid, a reaction catalysed by the enzyme UDP-glucose dehydrogenase (Ugd) would be important for this resistance. The genome of B. cenocepacia contains three predicted ugd genes: ugd(BCAL2946), ugd(BCAM0855) and ugd(BCAM2034), all of which were individually inactivated. Only inactivation of ugd(BCAL2946) resulted in increased sensitivity to polymyxin B and this sensitivity could be overcome when either ugd(BCAL2946) or ugd(BCAM0855) but not ugd(BCAM2034) was expressed from plasmids. The growth of a conditional ugd(BCAL2946) mutant, created in the Deltaugd(BCAM0855) background, was significantly impaired under non-permissive conditions. Growth could be rescued by either ugd(BCAL2946) or ugd(BCAM0855) expressed in trans, but not by ugd(BCAM2034). Biochemical analysis of the purified, recombinant forms of Ugd(BCAL2946) and Ugd(BCAM0855) revealed that they are soluble homodimers with similar in vitro Ugd activity and comparable kinetic constants for their substrates UDP-glucose and NAD(+). Purified Ugd(BCAM2034) showed no in vitro Ugd activity. Real-time PCR analysis showed that the expression of ugd(BCAL2946) was 5.4- and 135-fold greater than that of ugd(BCAM0855) and ugd(BCAM2034), respectively. Together, these data indicate that the combined activity of Ugd(BCAL2946) and Ugd(BCAM0855) is essential for the survival of B. cenocepacia but only the most highly expressed ugd gene, ugd(BCAL2946), is required for polymyxin B resistance.

A putative gene cluster for aminoarabinose biosynthesis is essential for Burkholderia cenocepacia viability

Using a conditional mutagenesis strategy we demonstrate here that a gene cluster encoding putative aminoarabinose (Ara4N) biosynthesis enzymes is essential for the viability of Burkholderia cenocepacia. Loss of viability is associated with dramatic changes in bacterial cell morphology and ultrastructure, increased permeability to propidium iodide, and sensitivity to sodium dodecyl sulfate, suggesting a general cell envelope defect caused by the lack of Ara4N.

Regression analysis of spatial data

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

A test for psychometric function shift

A nonparametric, small-sample-size test for the homogeneity of two psychometric functions against the left- and right-shift alternatives has been developed. The test is designed to determine whether it is safe to amalgamate psychometric functions obtained in different experimental sessions. The sum of the lower and upper p-values of the exact (conditional) Fisher test for several 2 × 2 contingency tables (one for each point of the psychometric function) is employed as the test statistic. The probability distribution of the statistic under the null (homogeneity) hypothesis is evaluated to obtain corresponding p-values. Power functions of the test have been computed by randomly generating samples from Weibull psychometric functions. The test is free of any assumptions about the shape of the psychometric function; it requires only that all observations are statistically independent. © 2011 Psychonomic Society, Inc.

Breast Cancer Risk in Relation to Occupations with Exposure to Carcinogens and Endocrine Disruptors:a Canadian Case-Control Study

Background

Endocrine disrupting chemicals and carcinogens, some of which may not yet have been classified as such, are present in many occupational environments and could increase breast cancer risk. Prior research has identified associations with breast cancer and work in agricultural and industrial settings. The purpose of this study was to further characterize possible links between breast cancer risk and occupation, particularly in farming and manufacturing, as well as to examine the impacts of early agricultural exposures, and exposure effects that are specific to the endocrine receptor status of tumours.

Methods

1005 breast cancer cases referred by a regional cancer center and 1147 randomly-selected community controls provided detailed data including occupational and reproductive histories. All reported jobs were industry- and occupation-coded for the construction of cumulative exposure metrics representing likely exposure to carcinogens and endocrine disruptors. In a frequency-matched case?control design, exposure effects were estimated using conditional logistic regression.

Results

Across all sectors, women in jobs with potentially high exposures to carcinogens and endocrine disruptors had elevated breast cancer risk (OR = 1.42; 95% CI, 1.18-1.73, for 10 years exposure duration). Specific sectors with elevated risk included: agriculture (OR = 1.36; 95% CI, 1.01-1.82); bars-gambling (OR = 2.28; 95% CI, 0.94-5.53); automotive plastics manufacturing (OR = 2.68; 95% CI, 1.47-4.88), food canning (OR = 2.35; 95% CI, 1.00-5.53), and metalworking (OR = 1.73; 95% CI, 1.02-2.92). Estrogen receptor status of tumors with elevated risk differed by occupational grouping. Premenopausal breast cancer risk was highest for automotive plastics (OR = 4.76; 95% CI, 1.58-14.4) and food canning (OR = 5.70; 95% CI, 1.03-31.5).

Conclusions

These observations support hypotheses linking breast cancer risk and exposures likely to include carcinogens and endocrine disruptors, and demonstrate the value of detailed work histories in environmental and occupational epidemiology.