Correlation of pretreatment drug induced apoptosis in ovarian cancer cells with patient survival and clinical response

Background This study was performed to determine if a chemotherapy-induced apoptosis assay (MiCK) could predict the best therapy for patients with ovarian cancer. Methods A prospective, multi-institutional and blinded trial of the assay was conducted in 104 evaluable ovarian cancer patients treated with chemotherapy. The MiCK assay was performed prior to therapy, but treating physicians were not told of the results and selected treatment only on clinical criteria. Outcomes (response, time to relapse, and survival) were compared to the drug-induced apoptosis observed in the assay. Results Overall survival in primary therapy, chemotherapy naïve patients with Stage III or IV disease was longer if patients received a chemotherapy which was best in the MiCK assay, compared to shorter survival in patients who received a chemotherapy that was not the best. (p < 0.01, hazard ratio HR 0.23). Multivariate model risk ratio showed use of the best chemotherapy in the MiCK assay was the strongest predictor of overall survival (p < 0.01) in stage III or IV patients. Standard therapy with carboplatin plus paclitaxel (C + P) was not the best chemotherapy in the MiCK assay in 44% of patients. If patients received C + P and it was the best chemotherapy in the MiCK assay, they had longer survival than those patients receiving C + P when it was not the best chemotherapy in the assay (p = 0.03). Relapse-free interval in primary therapy patients was longer if patients received the best chemotherapy from the MiCK assay (p = 0.03, HR 0.52). Response rates (CR + PR) were higher if physicians used an active chemotherapy based on the MiCK assay (p = 0.03). Conclusion The MiCK assay can predict the chemotherapy associated with better outcomes in ovarian cancer patients. This study quantifies outcome benefits on which a prospective randomized trial can be developed

Bootstrap Methods: A Guide for Practitioners and Researchers

Includes bibliographical references (p. 188-329) and indexes.1. What is bootstrapping? -- 1.1. Background -- 1.2. Introduction -- 1.3. Wide range of applications -- 1.4. Historical notes -- 1.5. Summary -- 2. Estimation -- 2.1. Estimating bias -- 2.1.1. How to do it by bootstrapping -- 2.1.2. Error rate estimation in discrimination -- 2.1.3. Error rate estimation: an illustrative problem -- 2.1.4. Efron's patch data example -- 2.2. Estimating location and dispersion -- 2.2.1. Means and medians -- 2.2.2. Standard errors and quartiles -- 2.3. Historical notes -- 3. Confidence sets and hypothesis testing -- 3.1. Confidence sets -- 3.1.1. Typical value theorems for M-estimates -- 3.1.2. Percentile method -- 3.1.3. Bias Correction and the Acceleration Constant -- 3.1.4. Iterated Bootstrap -- 3.1.5. Bootstrap Percentile t Confidence Intervals -- 3.2. Relationship Between Confidence Intervals and Tests of Hypotheses -- 3.3. Hypothesis Testing Problems -- 3.3.1. Tendril DX Lead Clinical Trial Analysis --^3.4. Application of bootstrap confidence Intervals to Binary Dose-Response Modeling -- 3.5. Historical Notes -- 4. Regression analysis -- 4.1. Linear Models -- 4.1.1. Gauss-Markov Theory -- 4.1.2. Why Not Just Use Least Squares? -- 4.1.3. Should I Bootstrap the Residuals from the Fit? -- 4.2. Nonlinear Models -- 4.2.1. Examples of Nonlinear Models -- 4.2.2. Quasi-optical Experiment -- 4.3. Nonparametric Models -- 4.4. Historical Notes -- 5. Forecasting and Time Series Analysis -- 5.1. Methods of Forecasting -- 5.2. Time Series Models -- 5.3. When Does Bootstrapping Help with Prediction Intervals? -- 5.4. Model-Based Versus Block Resampling -- 5.5. Explosive Autoregressive Processes -- 5.6. Bootstrapping-Stationary Arma Models -- 5.7. Frequency-Based Approaches -- 5.8. Sieve Bootstrap -- 5.9. Historical notes -- 6. Which resampling Method Should You Use? -- 6.1. Related Methods -- 6.1.1. Jackknife -- 6.1.2. Delta Method, Infinitesimal Jackknife, and Influence Functions --^6.1.3. Cross-Validation -- 6.1.4. Subsampling -- 6.2. Bootstrap variants -- 6.2.1. Bayesian bootstrap -- 6.2.2. Smoothed bootstrap -- 6.2.3. Parametric Bootstrap -- 6.2.4. Double bootstrap -- 6.2.5. m-out-of-n Bootstrap -- 7. Efficient and Effective Simulation -- 7.1. How Many Replications? -- 7.2. Variance Reduction Methods -- 7.2.1. Linear Approximation -- 7.2.2. Balanced Resampling -- 7.2.3. Antithetic Variates -- 7.2.4. Importance Sampling -- 7.2.5. Centering -- 7.3. When Can Monte Carlo Be Avoided? -- 7.4. Historical Notes -- 8. Special Topics -- 8.1. Spatial Data -- 8.1.1. Kriging -- 8.1.2. Block Bootstrap on Regular Grids -- 8.1.3. Block Bootstrap on Irregular Grids -- 8.2. Subset Selection -- 8.3. Determining the Number of Distributions in a Mixture Model -- 8.4. Censored Data -- 8.5. p-Value Adjustment -- 8.5.1. Description of Westfall-Young Approach -- 8.5.2. Passive Plus OX Example -- 8.5.3. Consulting Example -- 8.6. Bioequivalence Applications --^8.6.1. Individual Bioequivalence -- 8.6.2. Population Bioequivalence -- 8.7. Process Capability Indices -- 8.8. Missing Data -- 8.9. Point Processes -- 8.10. Lattice Variables -- 8.11. Historical Notes -- 9. When Bootstrapping Fails Along with Remedies for Failures -- 9.1. Too Small of a Sample Size -- 9.2. Distributions with Infinite Moments -- 9.2.1. Introduction -- 9.2.2. Example of Inconsistency -- 9.2.3. Remedies -- 9.3. Estimating Extreme Values -- 9.3.1. Introduction -- 9.3.2. Example of Inconsistency -- 9.3.3. Remedies -- 9.4. Survey Sampling -- 9.4.1. Introduction -- 9.4.2. Example of Inconsistency -- 9.4.3. Remedies -- 9.5. Data Sequences that Are M-Dependent -- 9.5.1. Introduction -- 9.5.2. Example of Inconsistency When Independence Is Assumed -- 9.5.3. Remedies -- 9.6. Unstable Autoregressive Processes -- 9.6.1. Introduction -- 9.6.2. Example of Inconsistency -- 9.6.3. Remedies -- 9.7. Long-Range Dependence -- 9.7.1. Introduction -- 9.7.2. Example of Inconsistency --^9.7.3. Remedies -- 9.8. Bootstrap Diagnostics -- 9.9. Historical Notes

Maternal Alcohol Consumption During Pregnancy and Physical Outcomes up to 5 Years of Age: A Longitudinal Study

Aim To examine whether alcohol exposure in pregnancy affects weight and head circumference (HC) at birth and 5 years, and whether these effects are independent of cigarette exposure in pregnancy and social disadvantage. Study design The Mater-University Study of Pregnancy (MUSP) involves a prospective cohort of 8556 mothers who were enrolled at first antenatal visit. The quantity and frequency of alcohol consumption in early and late pregnancy and a measure of binge drinking in early pregnancy were recorded. Weight and HC were measured on children seen at birth and at 5 years. Level of cigarette use in early pregnancy and maternal age and level of education and family income were also measured. Results Light and moderate alcohol consumption in early or later pregnancy had no independent effects on weight or HC at birth or 5 years. Binge drinking in early pregnancy was not associated with restricted HC, and there was no effect modification by concurrent cigarette use in early pregnancy. An apparent effect of alcohol in late pregnancy on birth weight was due to confounding by cigarette use, with social risk being an independent predictor. Conclusion Alcohol ingestion up to moderate levels in pregnancy was not associated with deficits in either weight or HC at birth or at 5 years

Varespladib and cardiovascular events in patients with an acute coronary syndrome: the VISTA-16 randomized clinical trial

IMPORTANCE: Secretory phospholipase A2(sPLA2) generates bioactive phospholipid products implicated in atherosclerosis. The sPLA2inhibitor varespladib has favorable effects on lipid and inflammatory markers; however, its effect on cardiovascular outcomes is unknown. OBJECTIVE: To determine the effects of sPLA2inhibition with varespladib on cardiovascular outcomes. DESIGN, SETTING, AND PARTICIPANTS: A double-blind, randomized, multicenter trial at 362 academic and community hospitals in Europe, Australia, New Zealand, India, and North America of 5145 patients randomized within 96 hours of presentation of an acute coronary syndrome (ACS) to either varespladib (n = 2572) or placebo (n = 2573) with enrollment between June 1, 2010, and March 7, 2012 (study termination on March 9, 2012). INTERVENTIONS: Participants were randomized to receive varespladib (500 mg) or placebo daily for 16 weeks, in addition to atorvastatin and other established therapies. MAIN OUTCOMES AND MEASURES: The primary efficacy measurewas a composite of cardiovascular mortality, nonfatal myocardial infarction (MI), nonfatal stroke, or unstable angina with evidence of ischemia requiring hospitalization at 16 weeks. Six-month survival status was also evaluated. RESULTS: At a prespecified interim analysis, including 212 primary end point events, the independent data and safety monitoring board recommended termination of the trial for futility and possible harm. The primary end point occurred in 136 patients (6.1%) treated with varespladib compared with 109 patients (5.1%) treated with placebo (hazard ratio [HR], 1.25; 95%CI, 0.97-1.61; log-rank P = .08). Varespladib was associated with a greater risk of MI (78 [3.4%] vs 47 [2.2%]; HR, 1.66; 95%CI, 1.16-2.39; log-rank P = .005). The composite secondary end point of cardiovascular mortality, MI, and stroke was observed in 107 patients (4.6%) in the varespladib group and 79 patients (3.8%) in the placebo group (HR, 1.36; 95% CI, 1.02-1.82; P = .04). CONCLUSIONS AND RELEVANCE: In patients with recent ACS, varespladib did not reduce the risk of recurrent cardiovascular events and significantly increased the risk of MI. The sPLA2inhibition with varespladib may be harmful and is not a useful strategy to reduce adverse cardiovascular outcomes after ACS. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01130246. Copyright 2014 American Medical Association. All rights reserved

Solution-based intramolecular singlet fission in cross-conjugated pentacene dimers

We show unambiguous and compelling evidence by means of pump–probe experiments, which are complemented by calculations using ab initio multireference perturbation theory, for intramolecular singlet fission (SF) within two synthetically tailored pentacene dimers with cross-conjugation, namely XC1 and XC2. The two pentacene dimers differ in terms of electronic interactions as evidenced by perturbation of the ground state absorption spectra stemming from stronger through-bond contributions in XC1 as confirmed by theory. Multiwavelength analysis, on one hand, and global analysis, on the other hand, confirm that the rapid singlet excited state decay and triplet excited state growth relate to SF. SF rate constants and quantum yields increase with solvent polarity. For example, XC2 reveals triplet quantum yields and rate constants as high as 162 ± 10% and (0.7 ± 0.1) × 1012 s−1, respectively, in room temperature solutions

Project: Evaluation of Speech Intelligibility in Wireless Communication via Speech Recognition Metrics

ardized as FS-1016 CELP. Using FS-1016 the bandwidth requirements for speech have been reduced to 4.8Kbps with only marginal reduction in the quality of speech recognition. With this great reduction in bandwidth requirements comes a greater sensitivity to noise in signal transmission. Consider that each bit represents a greater portion of the signal than in the uncompressed environment. In a &quot;wired&quot; environment (e.g., copper or fiber), noise is usually sufficiently small enough to be ignored. However, in the quickly growing field of wireless communication (e.g., cellular and cordless phones) noise is a much more serious problem. 3 In examining the effects of noise in the digital transmission of noise signals, researchers have examined the effects of the wireless channel in terms of signal-to-noise ratio (SNR) and segmental SNR (SEGSNR). SNR and SEGSNR are traditional metrics used in electrical engineering and related applications. SNR is usually expressed as the ave

Developments in the Syntax and Logic of the Talmudic Hermeneutic Kelal Uferaṭ Ukelal

The purpose of this study is to show that the logical content of a Tann’ayitic hermeneutic changed and developed as it passed into the hands of the ’Amor’ayim, the Tann’ayim’s successors, and then into the anonymous stratum of the Babylonian Talmud. This hermeneutic was based on a very specific syntactical order in a biblical verse, which was formed by an initial inclusive clause, followed by a list of specifics, and then followed by a second inclusive clause. This hermeneutic is called in Hebrew kelal uferaṭ ukelal. In the Tann’ayitic period the hermeneutic required that the second inclusive clause had to be more extensive than the first one. It appears that this new degree of extensiveness suggested that the list of specifics was not definitive of the initial inclusive clause and that other things might be implied by the second one. The way that the rabbinic interpreter determined what these things might be was by seeking the common characteristics that the items in the specifics clause shared. By the time of the late Tann’ayim and early ’Amor’ayim the requirement for the two inclusive clauses had changed. The formal syntax of the hermeneutic remained, but inclusive clauses had to be equal in their degree of inclusivity. The change in logic seems to be the result of viewing a second, more inclusive clause as a distinct element that could be disconnected from the first inclusive clause and the specifics that follow it. If the two inclusive clauses were, however, the same or similar, the rabbinic interpreter could argue that they belonged to the same categories and thus formed a legitimate kelal uferaṭ ukelal. In the final period of the Talmud’s creation neither the syntactic nor logical requirements were any longer needed to form a kelal uferaṭ ukelal. Two artificially constructed inclusive clauses and some specifics could appear in almost any order within a biblical verse and be considered a kelal uferaṭ ukelal. It appears that the desire of the rabbinic interpreters of each era to connect their halakot to the Torah was the force behind the changes we have described