APC-β-catenin-TCF signaling silences the intestinal guanylin-GUCY2C tumor suppressor axis.

Sporadic colorectal cancer initiates with mutations in APC or its degradation target β-catenin, producing TCF-dependent nuclear transcription driving tumorigenesis. The intestinal epithelial receptor, GUCY2C, with its canonical paracrine hormone guanylin, regulates homeostatic signaling along the crypt-surface axis opposing tumorigenesis. Here, we reveal that expression of the guanylin hormone, but not the GUCY2C receptor, is lost at the earliest stages of transformation in APC-dependent tumors in humans and mice. Hormone loss, which silences GUCY2C signaling, reflects transcriptional repression mediated by mutant APC-β-catenin-TCF programs in the nucleus. These studies support a pathophysiological model of intestinal tumorigenesis in which mutant APC-β-catenin-TCF transcriptional regulation eliminates guanylin expression at tumor initiation, silencing GUCY2C signaling which, in turn, dysregulates intestinal homeostatic mechanisms contributing to tumor progression. They expand the mechanistic paradigm for colorectal cancer from a disease of irreversible mutations in APC and β-catenin to one of guanylin hormone loss whose replacement, and reconstitution of GUCY2C signaling, could prevent tumorigenesis

Institutional imaginaries of publics in stem cell banking: The cases of the UK and Spain

The UK and Spanish Stem Cell Banks hold politically controversial-but potentially therapeutically beneficial-human embryonic stem cells for distribution to research laboratories globally. The UK bank was the first of its type in the world, opening in 2004, and the Spanish bank used it as a role model in its own development. Both banks structure their operations in response to how their staffs imagine the publics in their nation make trust judgements about their work. Differences between the workings of each bank can be traced to differences in the collective imaginings operating at each bank-termed 'institutional imaginaries'-about how publics think. The UK bank sustains an imaginary in which distance lends legitimacy and disengagement signifies correct moral practice. It conjures a public that values a steady, safe and reliable institution-free from potential conflict of interest-about which the less news the better. This stands in contrast to the Spanish bank that conjures a public that retains an interest in legitimate, ethical guardianship of stem cell material, but which is less worried about conflict of interest in attaining this. Instead, for the Spanish institution, engagement with science and the media through the projection of the bank as cutting edge is deemed crucial for maintaining public support. © 2013 Copyright Process Press.The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. This work was undertaken as part of the research programme of the ESRC Genomics Network at the Centre for Economic and Social Aspects of Genomics (Cesagen), Cardiff School of Social Sciences, Cardiff University, UK

Glycoprotein IIb-IIIa Is Expressed on Avian Multilineage Hematopoietic Progenitor Cells

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Corporate Governance, Opaque Bank Activities, and Risk/Return Efficiency: Pre- and Post-Crisis Evidence from Turkey

Does better corporate governance unambiguously improve the risk/return efficiency of banks? Or does either a re-orientation of banks' revenue mix towards more opaque products, an economic downturn, or tighter supervision create off-setting or reinforcing effects? The authors relate bank efficiency to shortfalls from a stochastic risk/return frontier. They analyze how internal governance mechanisms (CEO duality, board experience, political connections, and education profile) and external governance mechanisms (discipline exerted by shareholders, depositors, or skilled employees) determine efficiency in a sample of Turkish banks. The 2000 financial crisis was a wakeup call for bank efficiency and corporate governance. As a result, better corporate governance mechanisms have been able to improve risk/return efficiency when the economic, regulatory, and supervisory environments are more stable and bank products are more complex.corporate governance;bank risk;noninterest income;crisis;frontier

Individual quality assessment of autografting by probability estimation for clinical endpoints: a prospective validation study from the European group for blood and marrow transplantation.

The aim of supportive autografting is to reduce the side effects from stem cell transplantation and avoid procedure-related health disadvantages for patients at the lowest possible cost and resource expenditure. Economic evaluation of health care is becoming increasingly important. We report clinical and laboratory data collected from 397 consecutive adult patients (173 non-Hodgkin lymphoma, 30 Hodgkin lymphoma, 160 multiple myeloma, 7 autoimmune diseases, and 28 acute leukemia) who underwent their first autologous peripheral blood stem cell transplantation (PBSCT). We considered primary endpoints evaluating health economic efficacy (eg, antibiotic administration, transfusion of blood components, and time in hospital), secondary endpoints evaluating toxicity (in accordance with Common Toxicity Criteria), and tertiary endpoints evaluating safety (ie, the risk of regimen-related death or disease progression within the first year after PBSCT). A time-dependent grading of efficacy is proposed with day 21 for multiple myeloma and day 25 for the other disease categories (depending on the length of the conditioning regimen) as the acceptable maximum time in hospital, which together with antibiotics, antifungal, or transfusion therapy delineates four groups: favorable (≤7 days on antibiotics and no transfusions; ≤21 [25] days in hospital), intermediate (from 7 to 10 days on antibiotics and 7 days on antibiotics, >3 but 30/34 days in hospital after transplantation), and very unfavorable (>10 days on antibiotics, >6 transfusions; >30 to 34 days in hospital). The multivariate analysis showed that (1) PBSC harvests of ≥4 × 106/kg CD34 + cells in 1 apheresis procedure were associated with a favorable outcome in all patient categories except acute myelogenous leukemia and acute lymphoblastic leukemia (P = .001), (2) ≥5 × 106/kg CD34 + cells infused predicted better transplantation outcome in all patient categories (P 500 mL) (P = .002), and (5) patients with a central venous catheter during both collection and infusion of PBSC had a more favorable outcome post-PBSCT than peripheral access (P = .007). The type of mobilization regimen did not affect the outcome of auto-PBSCT. The present study identified predictive variables, which may be useful in future individual pretransplantation probability evaluations with the goal to improve supportive care

Prediction of Ureteral Injury During Colorectal Surgery Using Machine Learning

Background Ureteral injury (UI) is a rare but devastating complication during colorectal surgery. Ureteral stents may reduce UI but carry risks themselves. Risk predictors for UI could help target the use of stents, but previous efforts have relied on logistic regression (LR), shown moderate accuracy, and used intraoperative variables. We sought to use an emerging approach in predictive analytics, machine learning, to create a model for UI. Methods Patients who underwent colorectal surgery were identified in the National Surgical Quality Improvement Program (NSQIP) database. Patients were split into training, validation, and test sets. The primary outcome was UI. Three machine learning approaches were tested including random forest (RF), gradient boosting (XGB), and neural networks (NN), and compared with traditional LR. Model performance was assessed using area under the curve (AUROC). Results The data set included 262,923 patients, of whom 1519 (.578%) experienced UI. Of the modeling techniques, XGB performed the best, with an AUROC score of .774 (95% CI .742-.807) compared with .698 (95% CI .664-.733) for LR. Random forest and NN performed similarly with scores of .738 and .763, respectively. Type of procedure, work RVUs, indication for surgery, and mechanical bowel prep showed the strongest influence on model predictions. Conclusions Machine learning-based models significantly outperformed LR and previous models and showed high accuracy in predicting UI during colorectal surgery. With proper validation, they could be used to support decision making regarding the placement of ureteral stents preoperatively

A Comprehensive Resource for Induced Pluripotent Stem Cells from Patients with Primary Tauopathies.

Primary tauopathies are characterized neuropathologically by inclusions containing abnormal forms of the microtubule-associated protein tau (MAPT) and clinically by diverse neuropsychiatric, cognitive, and motor impairments. Autosomal dominant mutations in the MAPT gene cause heterogeneous forms of frontotemporal lobar degeneration with tauopathy (FTLD-Tau). Common and rare variants in the MAPT gene increase the risk for sporadic FTLD-Tau, including progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). We generated a collection of fibroblasts from 140 MAPT mutation/risk variant carriers, PSP, CBD, and cognitively normal controls; 31 induced pluripotent stem cell (iPSC) lines from MAPT mutation carriers, non-carrier family members, and autopsy-confirmed PSP patients; 33 genome engineered iPSCs that were corrected or mutagenized; and forebrain neural progenitor cells (NPCs). Here, we present a resource of fibroblasts, iPSCs, and NPCs with comprehensive clinical histories that can be accessed by the scientific community for disease modeling and development of novel therapeutics for tauopathies

Instrumental variable meta-analysis of individual patient data: application to adjust for treatment non-compliance

<p>Abstract</p> <p>Background</p> <p>Intention-to-treat (ITT) is the standard data analysis method which includes all patients regardless of receiving treatment. Although the aim of ITT analysis is to prevent bias due to prognostic dissimilarity, it is also a counter-intuitive type of analysis as it counts patients who did not receive treatment, and may lead to "bias toward the null." As treated (AT) method analyzes patients according to the treatment actually received rather than intended, but is affected by the selection bias. Both ITT and AT analyses can produce biased estimates of treatment effect, so instrumental variable (IV) analysis has been proposed as a technique to control for bias when using AT data. Our objective is to correct for bias in non-experimental data from previously published individual patient data meta-analysis by applying IV methods</p> <p>Methods</p> <p>Center prescribing preference was used as an IV to assess the effects of methotrexate (MTX) in preventing debilitating complications of chronic graft-versus-host-disease (cGVHD) in patients who received peripheral blood stem cell (PBSCT) or bone marrow transplant (BMT) in nine randomized controlled trials (1107 patients). IV methods are applied using 2-stage logistic, 2-stage probit and generalized method of moments models.</p> <p>Results</p> <p>ITT analysis showed a statistically significant detrimental effect with the use of day 11 MTX, resulting in cGVHD odds ratio (OR) of 1.34 (95% CI 1.02-1.76). AT results showed no difference in the odds of cGVHD with the use of MTX [OR 1.31 (95%CI 0.99-1.73)]. IV analysis further corrected the results toward no difference in the odds of cGVHD between PBSCT vs. BMT, allowing for a possibility of beneficial effects of MTX in preventing cGVHD in PBSCT recipients (OR 1.14; 95%CI 0.83-1.56).</p> <p>Conclusion</p> <p>All instrumental variable models produce similar results. IV estimates correct for bias and do not exclude the possibility that MTX may be beneficial, contradicting the ITT analysis.</p

A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data

A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74931/1/j.1540-5915.1993.tb00508.x.pd