Metabolic Regulation of mTOR Activation and Endoplasmic Reticulum Stress in the Heart

When subjected to increased workload, the heart responds metabolically by increasing its reliance on glucose and structurally by increasing the size of myocytes. Whether changes in metabolism regulate the structural remodeling process is unknown. A likely candidate for a link between metabolism and growth in the heart is the mammalian target of rapamycin (mTOR), which couples energy and nutrient metabolism to cell growth. Recently, sustained mTOR activation has also been implicated in the development of endoplasmic reticulum (ER) stress. We explored possible mechanisms by which acute metabolic changes in the hemodynamically stressed heart regulate mTOR activation, ER stress and cardiac function in the ex vivo isolated working rat heart. Doubling the heart’s workload acutely increased rates of glucose uptake beyond rates of glucose oxidation. The concomitant increase in glucose 6-phosphate (G6P) was associated with mTOR activation, endoplasmic reticulum (ER) stress and impaired contractile function. Both rapamycin and metformin restored glycolytic homeostasis, relieved ER stress and rescued contractile function. G6P and ER stress were also downregulated with mechanical unloading of failing human hearts. Taken together, the data support the hypothesis that metabolic remodeling precedes, triggers, and sustains structural remodeling of the heart and implicate a critical role for G6P in load-induced contractile dysfunction, mTOR activation and ER stress. In general terms, the intermediary metabolism of energy providing substrates provides signals for the onset and progression of hypertrophy and heart failure

Uncertainty-aware Perception Models for Off-road Autonomous Unmanned Ground Vehicles

Off-road autonomous unmanned ground vehicles (UGVs) are being developed for military and commercial use to deliver crucial supplies in remote locations, help with mapping and surveillance, and to assist war-fighters in contested environments. Due to complexity of the off-road environments and variability in terrain, lighting conditions, diurnal and seasonal changes, the models used to perceive the environment must handle a lot of input variability. Current datasets used to train perception models for off-road autonomous navigation lack of diversity in seasons, locations, semantic classes, as well as time of day. We test the hypothesis that model trained on a single dataset may not generalize to other off-road navigation datasets and new locations due to the input distribution drift. Additionally, we investigate how to combine multiple datasets to train a semantic segmentation-based environment perception model and we show that training the model to capture uncertainty could improve the model performance by a significant margin. We extend the Masksembles approach for uncertainty quantification to the semantic segmentation task and compare it with Monte Carlo Dropout and standard baselines. Finally, we test the approach against data collected from a UGV platform in a new testing environment. We show that the developed perception model with uncertainty quantification can be feasibly deployed on an UGV to support online perception and navigation tasks

Phase I study of nab-paclitaxel, gemcitabine, and bevacizumab in patients with advanced cancers.

BackgroundWe performed a phase I modified 3 + 3 dose escalation study to evaluate the safety and activity of bevacizumab plus gemcitabine and nab-paclitaxel in patients with advanced solid tumours.MethodsPatients were given fixed dose gemcitabine plus increasing doses of nab-paclitaxel and bevacizumab. Toxicity, response, and association with VEGF polymorphism was analysed.ResultsThe study enrolled 110 patients who had undergone a median of 3 prior lines of therapy. The median age was 60 years (range, 17-85 years), and 55 patients (50%) had gemcitabine-refractory disease. We observed 3 dose-limiting toxicities during dose escalation and 3 DLTs in expansion cohorts. Dose escalation to 150 mg/m2 nab-paclitaxel and 15 mg/kg bevacizumab with 1000 mg/m2 of gemcitabine was well tolerated with no MTD. One patient with gemcitabine-refractory peritoneal papillary carcinoma had a complete response, 13 patients (13%) had partial responses, and 54 patients (52%) had stable disease ≥12 weeks. Exploratory VEGF single nucleotide polymorphism (SNP) analysis was performed on 13 patients.ConclusionsThe combination of gemcitabine, nab-paclitaxel, and bevacizumab is safe, well-tolerated, and has activity in advanced malignancies, including gemcitabine-refractory tumours. Based on this study, the recommended phase 2 dose is gemcitabine 1000 mg/m2, nab-paclitaxel 125 mg/m2, and bevacizumab 15 mg/kg. VEGF polymorphism data should be evaluated in future bevacizumab-based trials

Molecular Profiling of Hepatocellular Carcinoma Using Circulating Cell-Free DNA.

PurposeMolecular profiling has been used to select patients for targeted therapy and determine prognosis. Noninvasive strategies are critical to hepatocellular carcinoma (HCC) given the challenge of obtaining liver tissue biopsies.Experimental designWe analyzed blood samples from 206 patients with HCC using comprehensive genomic testing (Guardant Health) of circulating tumor DNA (ctDNA).ResultsA total of 153/206 (74.3%) were men; median age, 62 years (range, 18-91 years). A total of 181/206 patients had ≥1 alteration. The total number of alterations was 680 (nonunique); median number of alterations/patient was three (range, 1-13); median mutant allele frequency (% cfDNA), 0.49% (range, 0.06%-55.03%). TP53 was the common altered gene [>120 alterations (non-unique)] followed by EGFR, MET, ARID1A, MYC, NF1, BRAF, and ERBB2 [20-38 alterations (nonunique)/gene]. Of the patients with alterations, 56.9% (103/181) had ≥1 actionable alterations, most commonly in MYC, EGFR, ERBB2, BRAF, CCNE1, MET, PIK3CA, ARID1A, CDK6, and KRAS. In these genes, amplifications occurred more frequently than mutations. Hepatitis B (HBV)-positive patients were more likely to have ERBB2 alterations, 35.7% (5/14) versus 8.8% HBV-negative (P = 0.04).ConclusionsThis study represents the first large-scale analysis of blood-derived ctDNA in HCC in United States. The genomic distinction based on HCC risk factors and the high percentage of potentially actionable genomic alterations suggests potential clinical utility for this technology

Bridging the gap between autonomous skill learning and task-specific planning

Skill acquisition and task specific planning are essential components of any robot system, yet they have long been studied in isolation. This, I contend, is due to the lack of a common representational framework. I present a holistic approach to planning robot behavior, using previously acquired skills to represent control knowledge (and objects) directly, and to use this background knowledge to build plans in the space of control actions. Actions in this framework are closed-loop controllers constructed from combinations of sensors, effectors, and potential functions. I will show how robots can use reinforcement learning techniques to acquire sensorimotor programs. The agent then builds a functional model of its interactions with the world as distributions over the acquired skills. In addition, I present two planning algorithms that can reason about a task using the functional models. These algorithms are then applied to a variety of tasks such as object recognition and object manipulation to achieve its objective on two different robot platforms

CMPSCI 691BB Project Report: A Framework for Intrinsically Motivated Agents

We propose a framework for creating intrinsically motivated autonomous agents that is based on the principle of homeostasis. The fundamental idea here is that organisms tend to pursue curious activity only when the basic needs such as food, drink, regulation of temperature or chemical balance etc have been taken care of, and the animal has achieve

Drug Development in Soft Tissue Sarcomas: Novel Targets and Recent Early Phase Trial Results

Soft tissue sarcomas are a heterogeneous group of rare malignancies with few effective standard therapies. Our understanding of the underlying biology driving tumorigenesis in these mesenchymal tumors have led to a growth in drug development for soft tissue sarcomas. This review focuses on novel targets in soft tissue sarcomas, describes early clinical trial results of drugs directed at these targets, and discusses the data surrounding the use of these compounds in clinical practice and rationale for possible future US Food and Drug Administration approvals

Generalization and transfer in robot control

We address the generalization and transfer of sensorimotor programs in robot systems. We use a factorable control-based approach that provides a natural, discrete abstraction of the underlying continuous state/action space and thus allows for the application of learning algorithms that converge in practical amounts of time. We argue that our approach provides an efficient means for the adaptation of skills to new situations. We show the performance gains for our framework in simulation, and demonstrate results from on-line learning on a bimanual robot. 1