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2. Distinct cytoskeletal proteins define zones of enhanced cell wall synthesis in Helicobacter pylori
- Author(s):
- Taylor, Jenny A.; Bratton, Benjamin P.; Sichel, Sophie R.; Blair, Kris M.; Jacobs, Holly M.; DeMeester, Kristen E.; Kuru, Erkin; Gray, Joe; Biboy, Jacob; VanNieuwenhze, Michael S.; Vollmer, Waldemar; Grimes, Catherine L.; Shaevitz, Joshua W.; Salama, Nina R.
- Abstract:
- Helical cell shape is necessary for efficient stomach colonization by Helicobacter pylori, but the molecular mechanisms for generating helical shape remain unclear. We show that the helical centerline pitch and radius of wild-type H. pylori cells dictate surface curvatures of considerably higher positive and negative Gaussian curvatures than those present in straight- or curved-rod bacteria. Quantitative 3D microscopy analysis of short pulses with either N-acetylmuramic acid or D-alanine metabolic probes showed that cell wall growth is enhanced at both sidewall curvature extremes. Immunofluorescence revealed MreB is most abundant at negative Gaussian curvature, while the bactofilin CcmA is most abundant at positive Gaussian curvature. Strains expressing CcmA variants with altered polymerization properties lose helical shape and associated positive Gaussian curvatures. We thus propose a model where CcmA and MreB promote PG synthesis at positive and negative Gaussian curvatures, respectively, and that this patterning is one mechanism necessary for maintaining helical shape.
- Type:
- Dataset and Image
- Issue Date:
- April 2019
3. Princeton Open Ventilation Monitor
- Author(s):
- Bourrianne, Philippe; Chidzik, Stanley; Cohen, Daniel; Elmer, Peter; Hallowell, Thomas; Kilbaugh, Todd J.; Lange, David; Leifer, Andrew M.; Marlow, Daniel R.; Meyers, Peter D.; Normand, Edna; Nunes, Janine; Oh, Myungchul; Page, Lyman; Periera, Talmo; Pivarski, Jim; Schreiner, Henry; Stone, Howard A.; Tank, David W.; Thiberge, Stephan; Tully, Christopher
- Abstract:
- The detailed information on the design and construction of the Princeton Open Ventilation Monitor device and software are contained in this data repository. This information consists of the electrical design files, mechanical design files, bill of materials, human subject recording and analysis code, and a copy of the code repository for operating the patient monitors and central station.
- Type:
- Dataset, Software, and Image
- Issue Date:
- 22 November 2021
4. Three dimensional archaeocyathide and coral imagery for morphologic analysis
- Author(s):
- Manzuk, Ryan; Maloof, Adam
- Abstract:
- In our study, we compare the three dimensional (3D) morphologic characteristics of Earth's first reef-building animals (archaeocyath sponges) with those of modern, photosynthetic corals. Within this repository are the 3D image data products for both groups of animals. The archaeocyath images were produced through serial grinding and imaging with the Grinding, Imaging, and Reconstruction Instrument at Princeton University. The images in this repository are the downsampled data products used in our study, and the full resolution (>2TB) image stacks are available upon request from the author. For the coral image data, the computed tomography (CT) images of all samples are included at full resolution. Also included in this repository are the manual and automated outline coordinates of the archaeocyath and coral branches, which can be directly used for morphological study.
- Type:
- Dataset, Image, MovingImage, and StillImage
- Issue Date:
- August 2022
5. Visual Analogy Extrapolation Challenge (VAEC)
- Author(s):
- Webb, Taylor; Dulberg, Zachary; Frankland, Steven; Petrov, Alexander; O'Reilly, Randall; Cohen, Jonathan
- Abstract:
- Extrapolation -- the ability to make inferences that go beyond the scope of one's experiences -- is a hallmark of human intelligence. By contrast, the generalization exhibited by contemporary neural network algorithms is largely limited to interpolation between data points in their training corpora. In this paper, we consider the challenge of learning representations that support extrapolation. We introduce a novel visual analogy benchmark that allows the graded evaluation of extrapolation as a function of distance from the convex domain defined by the training data. We also introduce a simple technique, context normalization, that encourages representations that emphasize the relations between objects. We find that this technique enables a significant improvement in the ability to extrapolate, considerably outperforming a number of competitive techniques.
- Type:
- Dataset and Image
- Issue Date:
- 2020
