Deep Policy Dynamic Programming for Vehicle Routing Problems

Routing problems are a class of combinatorial problems with many practical applications. Recently, end-to-end deep learning methods have been proposed to learn approximate solution heuristics for such problems. In contrast, classical dynamic programming (DP) algorithms guarantee optimal solutions, but scale badly with the problem size. We propose Deep Policy Dynamic Programming (DPDP), which aims to combine the strengths of learned neural heuristics with those of DP algorithms. DPDP prioritizes and restricts the DP state space using a policy derived from a deep neural network, which is trained to predict edges from example solutions. We evaluate our framework on the travelling salesman problem (TSP), the vehicle routing problem (VRP) and TSP with time windows (TSPTW) and show that the neural policy improves the performance of (restricted) DP algorithms, making them competitive to strong alternatives such as LKH, while also outperforming most other 'neural approaches' for solving TSPs, VRPs and TSPTWs with 100 nodes.Comment: 21 page

LSF small molecule inhibitors phenocopy LSF-targeted siRNAs causing mitotic defects and senescence in cancer cells

The oncogene LSF has been proposed as a novel target with therapeutic potential for multiple cancers. LSF overexpression correlates with poor prognosis for both liver and colorectal cancers, for which there are currently limited therapeutic treatment options. In particular, molecularly targeted therapies for hepatocellular carcinoma targeting cellular receptors and kinases have yielded disappointing clinical results, providing an urgency for targeting distinct mechanisms. LSF small molecule inhibitors, Factor Quinolinone Inhibitors (FQIs), have exhibited robust anti-tumor activity in multiple pre-clinical models of hepatocellular carcinoma, with no observable toxicity. To understand how the inhibitors impact cancer cell proliferation, we characterized the cellular phenotypes that result from loss of LSF activity. Phenotypically, inhibition of LSF activity induced a mitotic delay with condensed, but unaligned, chromosomes. This mitotic disruption resulted in improper cellular division leading to multiple outcomes: multi-nucleation, apoptosis, and cellular senescence. The cellular phenotypes observed upon FQI1 treatment were due specifically to the loss of LSF activity, as siRNA specifically targeting LSF produced nearly identical phenotypes. Taken together, these findings confirm that LSF is a promising therapeutic target for cancer treatment.First author draf

Failure detection for the Bin-Packing Constraint

Abstract In addition to a filtering algorithm, the Pack constraint introduced by Shaw uses a failure detection algorithm. This test is based on a reduction of the partial solution to a standard bin-packing problem and the computation of a bin-packing lower bound (BPLB) on the reduced problem. A first possible improvement on Shaw's test is to use a stronger BPLB. In particular, Labbé's lower bound was recently proved to dominate Martello's lower bound used by Shaw. A second possible improvement is to use a reduction different from the one introduced by Shaw. We propose two new reduction algorithms and prove that one of them theoretically dominates the others. All the proposed improvements on the failure test are evaluated using the COMET System

Quality Metrics for Stem Cell-Derived Cardiac Myocytes

Summary Advances in stem cell manufacturing methods have made it possible to produce stem cell-derived cardiac myocytes at industrial scales for in vitro muscle physiology research purposes. Although FDA-mandated quality assurance metrics address safety issues in the manufacture of stem cell-based products, no standardized guidelines currently exist for the evaluation of stem cell-derived myocyte functionality. As a result, it is unclear whether the various stem cell-derived myocyte cell lines on the market perform similarly, or whether any of them accurately recapitulate the characteristics of native cardiac myocytes. We propose a multiparametric quality assessment rubric in which genetic, structural, electrophysiological, and contractile measurements are coupled with comparison against values for these measurements that are representative of the ventricular myocyte phenotype. We demonstrated this procedure using commercially available, mass-produced murine embryonic stem cell- and induced pluripotent stem cell-derived myocytes compared with a neonatal mouse ventricular myocyte target phenotype in coupled in vitro assays

Constraint Programming for Multi-criteria Conceptual Clustering

International audienceA conceptual clustering is a set of formal concepts (i.e., closed itemsets) that defines a partition of a set of transactions. Finding a conceptual clustering is an N P-complete problem for which Constraint Programming (CP) and Integer Linear Programming (ILP) approaches have been recently proposed. We introduce new CP models to solve this problem: a pure CP model that uses set constraints, and an hybrid model that uses a data mining tool to extract formal concepts in a preprocessing step and then uses CP to select a subset of formal concepts that defines a partition. We compare our new models with recent CP and ILP approaches on classical machine learning instances. We also introduce a new set of instances coming from a real application case, which aims at extracting setting concepts from an Enterprise Resource Planning (ERP) software. We consider two classic criteria to optimize, i.e., the frequency and the size. We show that these criteria lead to extreme solutions with either very few small formal concepts or many large formal concepts, and that compromise clusterings may be obtained by computing the Pareto front of non dominated clusterings

Targeting the oncogene LSF with either the small molecule inhibitor FQI1 or siRNA causes mitotic delays with unaligned chromosomes, resulting in cell death or senescence

BACKGROUND: The oncogene LSF (encoded by TFCP2) has been proposed as a novel therapeutic target for multiple cancers. LSF overexpression in patient tumors correlates with poor prognosis in particular for both hepatocellular carcinoma and colorectal cancer. The limited treatment outcomes for these diseases and disappointing clinical results, in particular, for hepatocellular carcinoma in molecularly targeted therapies targeting cellular receptors and kinases, underscore the need for molecularly targeting novel mechanisms. LSF small molecule inhibitors, Factor Quinolinone Inhibitors (FQIs), have exhibited robust anti-tumor activity in multiple pre-clinical models, with no observable toxicity. METHODS: To understand how the LSF inhibitors impact cancer cell proliferation, we characterized the cellular phenotypes that result from loss of LSF activity. Cell proliferation and cell cycle progression were analyzed, using HeLa cells as a model cancer cell line responsive to FQI1. Cell cycle progression was studied either by time lapse microscopy or by bulk synchronization of cell populations to ensure accuracy in interpretation of the outcomes. In order to test for biological specificity of targeting LSF by FQI1, results were compared after treatment with either FQI1 or siRNA targeting LSF. RESULTS: Highly similar cellular phenotypes are observed upon treatments with FQI1 and siRNA targeting LSF. Along with similar effects on two cellular biomarkers, inhibition of LSF activity by either mechanism induced a strong delay or arrest prior to metaphase as cells progressed through mitosis, with condensed, but unaligned, chromosomes. This mitotic disruption in both cases resulted in improper cellular division leading to multiple outcomes: multi-nucleation, apoptosis, and cellular senescence. CONCLUSIONS: These data strongly support that cellular phenotypes observed upon FQI1 treatment are due specifically to the loss of LSF activity. Specific inhibition of LSF by either small molecules or siRNA results in severe mitotic defects, leading to cell death or senescence - consequences that are desirable in combating cancer. Taken together, these findings confirm that LSF is a promising target for cancer treatment. Furthermore, this study provides further support for developing FQIs or other LSF inhibitory strategies as treatment for LSF-related cancers with high unmet medical needs.R01 GM078240 - NIH HHSPublished versio

Correlation of Pain Scores, Analgesic Use, and Beck Anxiety Inventory Scores During Hospitalization in Lower Extremity Amputees

Post amputation pain can be debilitating for patients and families. Chronic pain is a common phenomenon after lower extremity amputation, occurring in up to 80% of this population. The purpose of this pilot study was to correlate post amputation pain scores to opioid analgesic consumption and Beck Anxiety Inventory (BAI) scores. Twenty-three patients with lower extremity amputation at an 827-bed acute care inner-city hospital were surveyed pre-operatively and post-operatively to determine if there was a significant correlation between anxiety and pain. A numeric scale was utilized by patients to rate their pain level, while the BAI was utilized to measure their anxiety levels