Vanderbilt University

About: Vanderbilt University is a education organization based out in Nashville, Tennessee, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 45066 authors who have published 106528 publications receiving 5435039 citations. The organization is also known as: Vandy.

Food Web Complexity and Community Dynamics

Abstract: Food webs in nature have multiple, reticulate connections between a diversity of consumers and resources. Such complexity affects web dynamics: it first spreads the direct effects of consumption and productivity throughout the web rather than focusing them at particular "trophic levels." Second, consumer densities are often donor controlled with food from across the trophic spectrum, the herbivore and detrital channels, other habitats, life-history omnivory, and even trophic mutualism. Although consumers usually do not affect these resources, increased numbers often allow consumers to depress other resources to levels lower than if donor-controlled resources were absent. We propose that such donor-controlled and "multichannel" omnivory is a general feature of consumer control and central to food web dynamics. This observation is contrary to the normal practice of inferring dynamics by simplifying webs into a few linear "trophic levels," as per "green world" theories. Such theories do not accommodate commo...

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

Abstract: Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Survival in BRAF V600–Mutant Advanced Melanoma Treated with Vemurafenib

Abstract: Approximately 50% of melanomas harbor activating (V600) mutations in the serine– threonine protein kinase B-RAF (BRAF). The oral BRAF inhibitor vemurafenib (PLX4032) frequently produced tumor regressions in patients with BRAF V600– mutant metastatic melanoma in a phase 1 trial and improved overall survival in a phase 3 trial. METHODS We designed a multicenter phase 2 trial of vemurafenib in patients with previously treated BRAF V600–mutant metastatic melanoma to investigate the efficacy of vem urafenib with respect to overall response rate (percentage of treated patients with a tumor response), duration of response, and overall survival. The primary end point was the overall response rate as ascertained by the independent review committee; overall survival was a secondary end point. RESULTS A total of 132 patients had a median follow-up of 12.9 months (range, 0.6 to 20.1). The confirmed overall response rate was 53% (95% confidence interval [CI], 44 to 62; 6% with a complete response and 47% with a partial response), the median duration of response was 6.7 months (95% CI, 5.6 to 8.6), and the median progression-free survival was 6.8 months (95% CI, 5.6 to 8.1). Primary progression was observed in only 14% of patients. Some patients had a response after receiving vemurafenib for more than 6 months. The median overall survival was 15.9 months (95% CI, 11.6 to 18.3). The most common adverse events were grade 1 or 2 arthralgia, rash, photosensitivity, fatigue, and alopecia. Cutaneous squamous-cell carcinomas (the majority, keratoacanthoma type) were diagnosed in 26% of patients. CONCLUSIONS Vemurafenib induces clinical responses in more than half of patients with previously treated BRAF V600–mutant metastatic melanoma. In this study with a long follow-up, the median overall survival was approximately 16 months. (Funded by Hoffmann–La Roche; ClinicalTrials.gov number, NCT00949702.)

Phase 3 Trial of 177Lu-Dotatate for Midgut Neuroendocrine Tumors

Abstract: BackgroundPatients with advanced midgut neuroendocrine tumors who have had disease progression during first-line somatostatin analogue therapy have limited therapeutic options. This randomized, controlled trial evaluated the efficacy and safety of lutetium-177 (177Lu)–Dotatate in patients with advanced, progressive, somatostatin-receptor–positive midgut neuroendocrine tumors. MethodsWe randomly assigned 229 patients who had well-differentiated, metastatic midgut neuroendocrine tumors to receive either 177Lu-Dotatate (116 patients) at a dose of 7.4 GBq every 8 weeks (four intravenous infusions, plus best supportive care including octreotide long-acting repeatable [LAR] administered intramuscularly at a dose of 30 mg) (177Lu-Dotatate group) or octreotide LAR alone (113 patients) administered intramuscularly at a dose of 60 mg every 4 weeks (control group). The primary end point was progression-free survival. Secondary end points included the objective response rate, overall survival, safety, and the side-ef...

Probabilistic Programming in Python using PyMC3

Abstract: Probabilistic Programming allows for automatic Bayesian inference on user-defined probabilistic models. Recent advances in Markov chain Monte Carlo (MCMC) sampling allow inference on increasingly complex models. This class of MCMC, known as Hamiltonian Monte Carlo, requires gradient information which is often not readily available. PyMC3 is a new open source Probabilistic Programming framework written in Python that uses Theano to compute gradients via automatic dierentiation as well as compile probabilistic programs on-the-fly to C for increased speed. Contrary to other Probabilistic Programming languages, PyMC3 allows model specification directly in Python code. The lack of a domain specific language allows for great flexibility and direct interaction with the model. This paper is a tutorial-style introduction to this software package.