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Chen AM, Palacci A, Vélez N, Hawkins RD, Gershman SJ. A Hierarchical Bayesian Model of Adaptive Teaching. Cogn Sci 2024; 48:e13477. [PMID: 38980989 DOI: 10.1111/cogs.13477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 06/05/2024] [Accepted: 06/08/2024] [Indexed: 07/11/2024]
Abstract
How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N = 312 adults). In Experiment 1, we show that teachers select examples that account for learners' background knowledge, and adjust their examples based on learners' feedback. In Experiment 2, we show that learners strategically provide more feedback when teachers' examples deviate from their background knowledge. These findings provide a foundation for extending computational accounts of pedagogy to richer interactive settings.
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Affiliation(s)
- Alicia M Chen
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
| | | | | | | | - Samuel J Gershman
- Department of Psychology, Harvard University
- Center for Brains, Minds, and Machines, Massachusetts Institute of Technology
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2
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Bock F, Dong X, Li S, Viquez OM, Sha E, Tantengco M, Hennen EM, Plosa E, Ramezani A, Brown KL, Whang YM, Terker AS, Arroyo JP, Harrison DG, Fogo A, Brakebusch CH, Pozzi A, Zent R. Rac1 promotes kidney collecting duct repair by mechanically coupling cell morphology to mitotic entry. SCIENCE ADVANCES 2024; 10:eadi7840. [PMID: 38324689 PMCID: PMC10849615 DOI: 10.1126/sciadv.adi7840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 01/03/2024] [Indexed: 02/09/2024]
Abstract
Prolonged obstruction of the ureter, which leads to injury of the kidney collecting ducts, results in permanent structural damage, while early reversal allows for repair. Cell structure is defined by the actin cytoskeleton, which is dynamically organized by small Rho guanosine triphosphatases (GTPases). In this study, we identified the Rho GTPase, Rac1, as a driver of postobstructive kidney collecting duct repair. After the relief of ureteric obstruction, Rac1 promoted actin cytoskeletal reconstitution, which was required to maintain normal mitotic morphology allowing for successful cell division. Mechanistically, Rac1 restricted excessive actomyosin activity that stabilized the negative mitotic entry kinase Wee1. This mechanism ensured mechanical G2-M checkpoint stability and prevented premature mitotic entry. The repair defects following injury could be rescued by direct myosin inhibition. Thus, Rac1-dependent control of the actin cytoskeleton integrates with the cell cycle to mediate kidney tubular repair by preventing dysmorphic cells from entering cell division.
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Affiliation(s)
- Fabian Bock
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xinyu Dong
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shensen Li
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Olga M. Viquez
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric Sha
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew Tantengco
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Elizabeth M. Hennen
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Erin Plosa
- Division of Neonatology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alireza Ramezani
- Interdisciplinary Center for Quantitative Modeling in Biology, University of California, Riverside, CA, USA
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | - Kyle L. Brown
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Young Mi Whang
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew S. Terker
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Juan Pablo Arroyo
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
| | - David G. Harrison
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Agnes Fogo
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Cord H. Brakebusch
- Biotech Research Center, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Ambra Pozzi
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Physiology and Molecular Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Roy Zent
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
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DeSanto M, Strait R, Zopp J, Brown K, Deem S. Metastatic melanoma to the proximal ureter. Urol Case Rep 2023; 50:102543. [PMID: 37664533 PMCID: PMC10474140 DOI: 10.1016/j.eucr.2023.102543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023] Open
Abstract
We present an exceptionally rare scenario of obstructive uropathy secondary to a ureteral mass. This case details a 68-year-old female with metastatic stage IIID melanoma of the right heel found to have a two cm right proximal ureteral mass with associated hydronephrosis. Pathology from ureteroscopic biopsy revealed metastatic melanoma to the ureter, creating a unique treatment quandary.
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Affiliation(s)
- Matthew DeSanto
- Charleston Area Medical Center, Charleston, West Virgina, USA
| | - Robert Strait
- Charleston Area Medical Center, Charleston, West Virgina, USA
| | - Jared Zopp
- Charleston Area Medical Center, Charleston, West Virgina, USA
| | - Kevin Brown
- Charleston Area Medical Center, Charleston, West Virgina, USA
| | - Samuel Deem
- Charleston Area Medical Center, Charleston, West Virgina, USA
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Bo S, Stabinska J, Wu Y, Pavuluri K, Singh A, Mohanta Z, Choudhry R, Kates M, Sedaghat F, Bhujwalla Z, Pomper MG, McMahon MT. Exploring the potential of the novel imidazole-4,5-dicarboxyamide chemical exchange saturation transfer scaffold for pH and perfusion imaging. NMR IN BIOMEDICINE 2023; 36:e4894. [PMID: 36543742 PMCID: PMC10200726 DOI: 10.1002/nbm.4894] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 12/12/2022] [Accepted: 12/20/2022] [Indexed: 05/23/2023]
Abstract
Here, we describe and assess the potential of 14 newly synthesized imidazole-4,5-dicarboxyamides (I45DCs) for pH and perfusion imaging. A number of these aromatic compounds possess large labile proton chemical shifts (up to 7.7 ppm from water) because of their intramolecular hydrogen bonds and a second labile proton to allow for chemical exchange saturation transfer (CEST) signal ratio-based pH measurements. We have found that the contrast produced is strong for a wide range of substitutions and that the inflection points in the CEST signal ratio versus pH plots used to generate concentration-independent pH maps can be adjusted based on these subsitutions to tune the pH range that can be measured. These I45DC CEST agents have advantages over the triiodobenzenes currently employed for tumor and kidney pH mapping, both preclinically and in initial human studies. Finally, as CEST MRI combined with exogenous contrast has the potential to detect functional changes in the kidneys, we evaluated our highest performing anionic compound (I45DC-diGlu) on a unilateral urinary obstruction mouse model and observed lower contrast uptake in the obstructed kidney compared with the unobstructed kidney and that the unobstructed kidney displayed a pH of ~ 6.5 while the obstructed kidney had elevated pH and an increased range in pH values. Based on this, we conclude that the I45DCs have excellent imaging properties and hold promise for a variety of medical imaging applications, particularly renal imaging.
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Affiliation(s)
- Shaowei Bo
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Julia Stabinska
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Yunkou Wu
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - KowsalyaDevi Pavuluri
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Aruna Singh
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Zinia Mohanta
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Rehan Choudhry
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Max Kates
- The James Buchanan Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Farzad Sedaghat
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Zaver Bhujwalla
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Martin G. Pomper
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- The James Buchanan Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Michael T. McMahon
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
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5
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Yang SCH, Folke T, Shafto P. The Inner Loop of Collective Human-Machine Intelligence. Top Cogn Sci 2023. [PMID: 36807872 DOI: 10.1111/tops.12642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 02/02/2023] [Accepted: 02/02/2023] [Indexed: 02/22/2023]
Abstract
With the rise of artificial intelligence (AI) and the desire to ensure that such machines work well with humans, it is essential for AI systems to actively model their human teammates, a capability referred to as Machine Theory of Mind (MToM). In this paper, we introduce the inner loop of human-machine teaming expressed as communication with MToM capability. We present three different approaches to MToM: (1) constructing models of human inference with well-validated psychological theories and empirical measurements; (2) modeling human as a copy of the AI; and (3) incorporating well-documented domain knowledge about human behavior into the above two approaches. We offer a formal language for machine communication and MToM, where each term has a clear mechanistic interpretation. We exemplify the overarching formalism and the specific approaches in two concrete example scenarios. Related work that demonstrates these approaches is highlighted along the way. The formalism, examples, and empirical support provide a holistic picture of the inner loop of human-machine teaming as a foundational building block of collective human-machine intelligence.
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Affiliation(s)
| | - Tomas Folke
- Department of Mathematics and Computer Science, Rutgers University
| | - Patrick Shafto
- Department of Mathematics and Computer Science, Rutgers University
- School of Mathematics, Institute for Advanced Studies
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