Randomized Phase III Trial of Paclitaxel and Carboplatin Versus Paclitaxel and Ifosfamide in Patients With Carcinosarcoma of the Uterus or Ovary: An NRG Oncology Trial

PURPOSE This phase III randomized trial ( NCT00954174 ) tested the null hypothesis that paclitaxel and carboplatin (PC) is inferior to paclitaxel and ifosfamide (PI) for treating uterine carcinosarcoma (UCS). PATIENTS AND METHODS Adults with chemotherapy-naïve UCS or ovarian carcinosarcoma (OCS) were randomly assigned to PC or PI with 3-week cycles for 6-10 cycles. With 264 events in patients with UCS, the power for an overall survival (OS) hybrid noninferiority design was 80% for a null hazard ratio (HR) of 1.2 against a 13% greater death rate on PI with a type I error of 5% for a one-tailed test. RESULTS The study enrolled 536 patients with UCS and 101 patients with OCS, with 449 and 90 eligible, respectively. Primary analysis was on patients with UCS, distributed as follows: 40% stage I, 6% stage II, 31% stage III, 15% stage IV, and 8% recurrent. Among eligible patients with UCS, PC was assigned to 228 and PI to 221. PC was not inferior to PI. The median OS was 37 versus 29 months (HR = 0.87; 90% CI, 0.70 to 1.075; P < .01 for noninferiority, P > .1 for superiority). The median progression-free survival was 16 versus 12 months (HR = 0.73; P = < 0.01 for noninferiority, P < .01 for superiority). Toxicities were similar, except that more patients in the PC arm had hematologic toxicity and more patients in the PI arm had confusion and genitourinary hemorrhage. Among 90 eligible patients with OCS, those in the PC arm had longer OS (30 v 25 months) and progression-free survival (15 v 10 months) than those in the PI arm, but with limited precision, these differences were not statistically significant. CONCLUSION PC was not inferior to the active regimen PI and should be standard treatment for UCS.

Multi-objective dynamic programming with limited precision

This paper addresses the problem of approximating the set of all solutions for Multi-objective Markov Decision Processes. We show that in the vast majority of interesting cases, the number of solutions is exponential or even infinite. In order to overcome this difficulty we propose to approximate the set of all solutions by means of a limited precision approach based on White’s multi-objective value-iteration dynamic programming algorithm. We prove that the number of calculated solutions is tractable and show experimentally that the solutions obtained are a good approximation of the true Pareto front.

Meta-Material Enhanced Spatial Mode Decomposition

Acquiring precise information about the mode content of a laser is critical for multiplexed optical communications, optical imaging with active wave-front control, and quantum-limited interferometric measurements. Hologram-based mode decomposition devices allow a fast, direct measurement of the mode content, but they have limited precision due to cross-coupling between modes. Here we report the first proof-of-principle demonstration of mode decomposition with a meta-surface, resulting in significantly enhanced precision. A mode-weight fluctuation of 0.6ppm (-62 dB) can be measured with 1 second of averaging at a Fourier frequency of 80 Hz, an improvement on the state-of-the-art by more than three orders of magnitude. The improvement is attributable to the reduction in cross-coupling enabled by the exceptional phase accuracy of the meta-surface. We show a systematic study of the limiting sources of noise, and we show that there is a promising path towards complete mode decomposition with similar precision.

The role of epistasis in determining the fitness landscape of HIV proteins

The rapid evolution of HIV is constrained by interactions between mutations which affect viral fitness. In this work, we explore the role of epistasis in determining the fitness landscape of HIV for multiple drug target proteins, including Protease, Reverse Transcriptase, and Integrase. Epistatic interactions between residues modulate the mutation patterns involved in drug resistance with unambiguous signatures of epistasis best seen in the comparison of a maximum entropy sequence co-variation (Potts) model predicted and experimental HIV sequence ``prevalences" when expressed as higher-order marginals (beyond triplets) of the sequence probability distribution. In contrast, the evidence for epistasis based on experimental measures of fitness such as replicative capacity is weak; the correspondence with Potts model ``prevalence"-based predictions is obscured by site conservation and limited precision. Double mutant cycles provide in principle one of the best ways to probe epistatic interactions experimentally without reference to a particular background, and we find they reveal that the most strongly interacting mutations in HIV involve correlated sets of drug-resistance-associated residues, however the analysis is complicated by the small dynamic range of measurements. The use of correlated models for the design of experiments to probe viral fitness can help identify the epistatic interactions involved in mutational escape, and lead to better inhibitor therapies.

Neurons with dendrites can perform linearly separable computations with low resolution synaptic weights

In theory, neurons modelled as single layer perceptrons can implement all linearly separable computations. In practice, however, these computations may require arbitrarily precise synaptic weights. This is a strong constraint since both biological neurons and their artificial counterparts have to cope with limited precision. Here, we explore how non-linear processing in dendrites helps overcome this constraint. We start by finding a class of computations which requires increasing precision with the number of inputs in a perceptron and show that it can be implemented without this constraint in a neuron with sub-linear dendritic subunits. Then, we complement this analytical study by a simulation of a biophysical neuron model with two passive dendrites and a soma, and show that it can implement this computation. This work demonstrates a new role of dendrites in neural computation: by distributing the computation across independent subunits, the same computation can be performed more efficiently with less precise tuning of the synaptic weights. This work not only offers new insight into the importance of dendrites for biological neurons, but also paves the way for new, more efficient architectures of artificial neuromorphic chips.

Automatic Cohort Determination from Twitter for HIV Prevention amongst Ethnic Minorities

Recruiting people from diverse backgrounds to participate in health research requires intentional and culture-driven strategic efforts. In this study, we utilize publicly available Twitter posts to identify targeted populations to recruit for our HIV prevention study. Natural language processing methods were used to find self-declarations of ethnicity, gender, and age group, and advanced classification methods to find sexually-explicit language. Using the official Twitter API and the available tools, Demographer and M3, we identified 4800 users who were likely young Black or Hispanic men living in Los Angeles from an initial collection of 47.4 million tweets posted over 8 months. Despite a limited precision, our results suggest that it is possible to automatically identify users based on their demographic attributes and characterize their language on Twitter for enrollment into epidemiological studies.

Risk Factors Associated With Readmission After Pancreatectomy: A Single-Institution Retrospective Cohort Study

Background Pancreatectomy has a significant rate of procedure-specific morbidity which can result in readmission. Readmission has been proposed as a measure of quality. The goal of this study is to determine what factors are associated with readmission after pancreatectomy and whether readmission can be prevented. Methods A retrospective review of a single institution’s pancreatectomies between January 2011 and April 2015 was performed. Demographic, perioperative, and outpatient data were collected from the medical record. Primary outcome was 90-day readmission. Univariate and multivariable analyses were performed to determine which factors were associated with increased risk for readmission. Results A total of 257 patients met inclusion criteria; the 90-day readmission rate was 32.7%. The median time to readmission was 13 days. Readmitted patients were more likely to have a postoperative pancreatic fistula (POPF) on univariate analysis. Surgical site infections were more common in readmitted patients (18% vs 6.4%, P = .0138). Upon multivariable adjustment, only POPF ( P = .0005) remained significant. A positive dose-response relationship was noted between POPF grade and the odds of readmission with odds ratios (ORs) ranging from 1.6 (95% Confidence Interval (CI): .6-4.1) for grade A to 16.7 (95% CI: 1.8-156.8) for grade C, albeit with limited precision. Conclusions Readmission after pancreatectomy is a common occurrence despite the many advancements in perioperative care. Our data suggest that POPF is a risk factor for readmission after pancreatectomy. Presently, this factor is not clearly preventable. This suggests that readmission may not be the best measure of quality to utilize in the evaluation of pancreatic surgery.