Investigating Mechanisms of Mitotic Spindle Positioning

The direction, or orientation, of cell division is important because it determines the fate and positions of cells within a tissue. The position of the mitotic spindle, the molecular machine that separates the chromosomes during mitosis, determines the plane of cell division. Cells sometimes use intercellular signals as spatial cues to position the mitotic spindle, but how mitotic spindles are positioned within cells in response to external cues remains unclear. To approach this question, I used the EMS cell in the early C. elegans embryo, an established model for studying cell interactions and miotic spindle orientation during development. I used contemporary genome editing strategies such as CRISPR, confocal live imaging, and classic embryological techniques, to address how proteins are deployed within cells to position mitotic spindles. The second chapter of this work is an in vivo comparison of fluorescent proteins in C. elegans. This study was a valuable technical advance and revealed which fluorescent proteins to use for in vivo live imaging. In the third chapter, using fluorescent proteins, I created tools to visualize our proteins of interest, and determined whether they were cortically enriched by cell-cell signaling mechanisms to direct mitotic spindle positioning. I found surprisingly, that APC and Dishevelled are enriched asymmetrically at the EMS cortex, but NuMA and dyenin are not. These findings have implications for better understanding how signaling pathway proteins might function as positional cues for spindle orientation, independent of the asymmetric enrichment of the canonical Gα/LGN/NuMA complexDoctor of Philosoph

The Effects of Research & Development Funding on Scientific Productivity: Academic Chemistry, 1990-2009

This article examines the relationship between Research & Development (R&D) funding and the production of knowledge by academic chemists. Using articles published, either raw counts or adjusted for quality, we find a strong, positive causal effect of funding on knowledge production. This effect is similar across subsets of universities, suggesting a relatively efficient allocation of R&D funds. Finally, we document a rapid acceleration in the rate at which chemical knowledge was produced in the late 1990s and early 2000s relative to the financial and human resources devoted to its production

Academic Chemistry Inputs and Outcomes Data

The Academic Chemistry Inputs and Outcomes Data assembles panel data on academic chemistry inputs and outputs for 147 universities from 1989 through 2009. Each observation represents a single university-year and includes information on numbers of publications, citations to these publications, levels of federal and non-federal R&D funding, numbers of faculty, postdoctoral researchers, doctorates awarded and institutional characteristics. The data were compiled for the analysis of the determinants of university publication behavior and its relationship to research funding as reported in Joshua L. Rosenbloom, Donna K. Ginther, Ted Juhl and Joseph Heppert, "The Effects of Research & Development Funding on Scientific Productivity: Academic Chemistry, 1990-2009," Public Library of Science One, available in KU ScholarWorks at http://hdl.handle.net/1808/20057. As described in the Data Description and Code Book, these data were assembled by linking together information from a number of publicly available data sources and combining them with proprietary data on publications and citations provided by Thomson Reuters from their Web of Science database. These data are available to download as a text file (.csv) and as a STATA (.dta) data file. Anyone is free to use these data for scholarly purposes, but must include a citation to this user guide in any papers or published articles that employ these data

Activation of T Lymphocytes in Response to Persistent Bacterial Infection: Induction of CD11b and of Toll-Like Receptors on T Cells

T cell activation is invariably associated with virus infections, but activation of T cells is also noted, for example, in patients with persistent bacterial infections with intracellular pathogens or localised bacterial biofilms. The latter is characterised by a destructive inflammatory process. Massive infiltration of leukocytes, predominantly of polymorphonuclear neutrophils (PMNs) and of T lymphocytes, is seen. While PMN influx into sites of bacterial infection is in line with their role as “first-line defence” a role of T cells in bacterial infection has not yet been delineated. We now found evidence for activation and expansion of peripheral blood T cells and an upregulation of Toll-like receptors 1, 2, and 4 on small portions of T cells. T cells recovered from the infected site were terminally differentiated and produced interferon gamma, a cytokine known to enhance functions of phagocytic cells, leading to the conclusion that infiltrated T cells support the local immuner defence

CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objects

We present CARTO, a novel approach for reconstructing multiple articulated objects from a single stereo RGB observation. We use implicit object-centric representations and learn a single geometry and articulation decoder for multiple object categories. Despite training on multiple categories, our decoder achieves a comparable reconstruction accuracy to methods that train bespoke decoders separately for each category. Combined with our stereo image encoder we infer the 3D shape, 6D pose, size, joint type, and the joint state of multiple unknown objects in a single forward pass. Our method achieves a 20.4% absolute improvement in mAP 3D IOU50 for novel instances when compared to a two-stage pipeline. Inference time is fast and can run on a NVIDIA TITAN XP GPU at 1 HZ for eight or less objects present. While only trained on simulated data, CARTO transfers to real-world object instances. Code and evaluation data is available at: http://carto.cs.uni-freiburg.deComment: 20 pages, 11 figures, accepted at CVPR 202

AO-Grasp: Articulated Object Grasp Generation

We introduce AO-Grasp, a grasp proposal method that generates stable and actionable 6 degree-of-freedom grasps for articulated objects. Our generated grasps enable robots to interact with articulated objects, such as opening and closing cabinets and appliances. Given a segmented partial point cloud of a single articulated object, AO-Grasp predicts the best grasp points on the object with a novel Actionable Grasp Point Predictor model and then finds corresponding grasp orientations for each point by leveraging a state-of-the-art rigid object grasping method. We train AO-Grasp on our new AO-Grasp Dataset, which contains 48K actionable parallel-jaw grasps on synthetic articulated objects. In simulation, AO-Grasp achieves higher grasp success rates than existing rigid object grasping and articulated object interaction baselines on both train and test categories. Additionally, we evaluate AO-Grasp on 120 realworld scenes of objects with varied geometries, articulation axes, and joint states, where AO-Grasp produces successful grasps on 67.5% of scenes, while the baseline only produces successful grasps on 33.3% of scenes.Comment: Project website: https://stanford-iprl-lab.github.io/ao-gras

Comparative assessment of fluorescent proteins for in vivo imaging in an animal model system.

Fluorescent protein tags are fundamental tools used to visualize gene products and analyze their dynamics in vivo. Recent advances in genome editing have expedited the precise insertion of fluorescent protein tags into the genomes of diverse organisms. These advances expand the potential of in vivo imaging experiments and facilitate experimentation with new, bright, photostable fluorescent proteins. Most quantitative comparisons of the brightness and photostability of different fluorescent proteins have been made in vitro, removed from biological variables that govern their performance in cells or organisms. To address the gap, we quantitatively assessed fluorescent protein properties in vivo in an animal model system. We generated transgenic Caenorhabditis elegans strains expressing green, yellow, or red fluorescent proteins in embryos and imaged embryos expressing different fluorescent proteins under the same conditions for direct comparison. We found that mNeonGreen was not as bright in vivo as predicted based on in vitro data but is a better tag than GFP for specific kinds of experiments, and we report on optimal red fluorescent proteins. These results identify ideal fluorescent proteins for imaging in vivo in C. elegans embryos and suggest good candidate fluorescent proteins to test in other animal model systems for in vivo imaging experiments