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  1. Article: Development of fluorophores for the detection of oligomeric aggregates of amyloidogenic proteins found in neurodegenerative diseases.

    Teppang, Kristine L / Zhao, Qilin / Yang, Jerry

    Frontiers in chemistry

    2023  Volume 11, Page(s) 1343118

    Abstract: Alzheimer's disease and Parkinson's disease are the two most common neurodegenerative diseases globally. These neurodegenerative diseases have characteristic late-stage symptoms allowing for differential diagnosis; however, they both share the presence ... ...

    Abstract Alzheimer's disease and Parkinson's disease are the two most common neurodegenerative diseases globally. These neurodegenerative diseases have characteristic late-stage symptoms allowing for differential diagnosis; however, they both share the presence of misfolded protein aggregates which appear years before clinical manifestation. Historically, research has focused on the detection of higher-ordered aggregates (or amyloids); however, recent evidence has shown that the oligomeric state of these protein aggregates plays a greater role in disease pathology, resulting in increased efforts to detect oligomers to aid in disease diagnosis. In this review, we summarize some of the exciting new developments towards the development of fluorescent probes that can detect oligomeric aggregates of amyloidogenic proteins present in Alzheimer's and Parkinson's disease patients.
    Language English
    Publishing date 2023-12-22
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2711776-5
    ISSN 2296-2646
    ISSN 2296-2646
    DOI 10.3389/fchem.2023.1343118
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Differentiable Entailment for Parameter Efficient Few Shot Learning

    Kim, Ethan / Yang, Jerry

    2023  

    Abstract: Few-shot learning allows pre-trained language models to adapt to downstream tasks while using a limited number of training examples. However, practical applications are limited when all model parameters must be optimized. In this work we apply a new ... ...

    Abstract Few-shot learning allows pre-trained language models to adapt to downstream tasks while using a limited number of training examples. However, practical applications are limited when all model parameters must be optimized. In this work we apply a new technique for parameter efficient few shot learning while adopting a strict definition of parameter efficiency. Our training method combines 1) intermediate training by reformulating natural language tasks as entailment tasks \cite{wang_entailment_2021} and 2) differentiable optimization of template and label tokens \cite{zhang_differentiable_2021}. We quantify the tradeoff between parameter efficiency and performance in the few-shot regime and propose a simple model agnostic approach that can be extended to any task By achieving competitive performance while only optimizing 3\% of a model's parameters and allowing for batched inference, we allow for more efficient practical deployment of models.
    Keywords Computer Science - Computation and Language
    Subject code 006
    Publishing date 2023-01-30
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Approximate Policy Iteration With Deep Minimax Average Bellman Error Minimization.

    Kang, Lican / Liu, Yuhui / Luo, Yuan / Yang, Jerry Zhijian / Yuan, Han / Zhu, Chang

    IEEE transactions on neural networks and learning systems

    2024  Volume PP

    Abstract: In this work, we investigate the utilization of deep approximate policy iteration (DAPI) in estimating the optimal action-value function ... ...

    Abstract In this work, we investigate the utilization of deep approximate policy iteration (DAPI) in estimating the optimal action-value function Q
    Language English
    Publishing date 2024-01-09
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2023.3346992
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: A Rare Case of Traumatic Acute Pronator Syndrome in the Setting of Anticoagulation Therapy.

    Tuano, Krystle R / Fisher, Marlie H / Yang, Jerry H / Gordon, Mickey J

    Cureus

    2023  Volume 15, Issue 3, Page(s) e36931

    Abstract: Pronator syndrome (PS) is a rare type of peripheral compression neuropathy in which the median nerve becomes entrapped as it passes through the pronator teres muscle at the proximal forearm. We report an unusual case of acute PS in a 78-year-old patient ... ...

    Abstract Pronator syndrome (PS) is a rare type of peripheral compression neuropathy in which the median nerve becomes entrapped as it passes through the pronator teres muscle at the proximal forearm. We report an unusual case of acute PS in a 78-year-old patient on warfarin who presented after traumatic forearm injury with forearm swelling, pain, and paresthesias. After emergent nerve decompression and hematoma evacuation, the patient regained near complete recovery of median nerve function six months after diagnosis and treatment.
    Language English
    Publishing date 2023-03-30
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.36931
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online: Semi-Supervised Deep Sobolev Regression

    Ding, Zhao / Duan, Chenguang / Jiao, Yuling / Yang, Jerry Zhijian

    Estimation, Variable Selection and Beyond

    2024  

    Abstract: We propose SDORE, a semi-supervised deep Sobolev regressor, for the nonparametric estimation of the underlying regression function and its gradient. SDORE employs deep neural networks to minimize empirical risk with gradient norm regularization, allowing ...

    Abstract We propose SDORE, a semi-supervised deep Sobolev regressor, for the nonparametric estimation of the underlying regression function and its gradient. SDORE employs deep neural networks to minimize empirical risk with gradient norm regularization, allowing computation of the gradient norm on unlabeled data. We conduct a comprehensive analysis of the convergence rates of SDORE and establish a minimax optimal rate for the regression function. Crucially, we also derive a convergence rate for the associated plug-in gradient estimator, even in the presence of significant domain shift. These theoretical findings offer valuable prior guidance for selecting regularization parameters and determining the size of the neural network, while showcasing the provable advantage of leveraging unlabeled data in semi-supervised learning. To the best of our knowledge, SDORE is the first provable neural network-based approach that simultaneously estimates the regression function and its gradient, with diverse applications including nonparametric variable selection and inverse problems. The effectiveness of SDORE is validated through an extensive range of numerical simulations and real data analysis.
    Keywords Statistics - Machine Learning ; Computer Science - Machine Learning ; 62G05 ; 62G08 ; 65N21
    Subject code 519
    Publishing date 2024-01-09
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  6. Article: Synthesis of functionalized 2,3-diaminopropionates and their potential for directed monobactam biosynthesis.

    Lichstrahl, Michael S / Kahlert, Lukas / Li, Rongfeng / Zandi, Trevor A / Yang, Jerry / Townsend, Craig A

    Chemical science

    2023  Volume 14, Issue 14, Page(s) 3923–3931

    Abstract: ... ...

    Abstract The
    Language English
    Publishing date 2023-03-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 2559110-1
    ISSN 2041-6539 ; 2041-6520
    ISSN (online) 2041-6539
    ISSN 2041-6520
    DOI 10.1039/d2sc06893a
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Healthcare facilities should publicly report the coronavirus disease 2019 (COVID-19) vaccination coverage of healthcare personnel.

    Yang, Jerry M / Babcock, Hilary M / Baghdadi, Jonathan D

    Infection control and hospital epidemiology

    2021  Volume 43, Issue 10, Page(s) 1534–1535

    MeSH term(s) Humans ; Vaccination Coverage ; COVID-19/prevention & control ; Health Personnel ; Health Facilities ; Delivery of Health Care ; Vaccination
    Language English
    Publishing date 2021-07-13
    Publishing country United States
    Document type Journal Article
    ZDB-ID 639378-0
    ISSN 1559-6834 ; 0195-9417 ; 0899-823X
    ISSN (online) 1559-6834
    ISSN 0195-9417 ; 0899-823X
    DOI 10.1017/ice.2021.319
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1714: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Stimuli-responsive drug delivery systems.

    Yang, Jerry

    Advanced drug delivery reviews

    2012  Volume 64, Issue 11, Page(s) 965–966

    MeSH term(s) Drug Delivery Systems ; Pharmaceutical Preparations/administration & dosage
    Chemical Substances Pharmaceutical Preparations
    Language English
    Publishing date 2012-08
    Publishing country Netherlands
    Document type Editorial ; Research Support, Non-U.S. Gov't
    ZDB-ID 639113-8
    ISSN 1872-8294 ; 0169-409X
    ISSN (online) 1872-8294
    ISSN 0169-409X
    DOI 10.1016/j.addr.2012.05.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2241: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  9. Book ; Online: Current density impedance imaging with PINNs

    Duan, Chenguang / Jiao, Yuling / Lu, Xiliang / Yang, Jerry Zhijian

    2023  

    Abstract: In this paper, we introduce CDII-PINNs, a computationally efficient method for solving CDII using PINNs in the framework of Tikhonov regularization. This method constructs a physics-informed loss function by merging the regularized least-squares output ... ...

    Abstract In this paper, we introduce CDII-PINNs, a computationally efficient method for solving CDII using PINNs in the framework of Tikhonov regularization. This method constructs a physics-informed loss function by merging the regularized least-squares output functional with an underlying differential equation, which describes the relationship between the conductivity and voltage. A pair of neural networks representing the conductivity and voltage, respectively, are coupled by this loss function. Then, minimizing the loss function provides a reconstruction. A rigorous theoretical guarantee is provided. We give an error analysis for CDII-PINNs and establish a convergence rate, based on prior selected neural network parameters in terms of the number of samples. The numerical simulations demonstrate that CDII-PINNs are efficient, accurate and robust to noise levels ranging from $1\%$ to $20\%$.
    Keywords Mathematics - Numerical Analysis ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Subject code 518
    Publishing date 2023-06-24
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Translational opportunities for amyloid-targeting fluorophores.

    Cao, Kevin J / Yang, Jerry

    Chemical communications (Cambridge, England)

    2018  Volume 54, Issue 66, Page(s) 9107–9118

    Abstract: Advances in diagnostic medicine have led to an increased awareness and heightened concern for the high prevalence of amyloid-associated neurodegenerative diseases, especially in the elderly. These diseases have characteristic late stage symptoms that ... ...

    Abstract Advances in diagnostic medicine have led to an increased awareness and heightened concern for the high prevalence of amyloid-associated neurodegenerative diseases, especially in the elderly. These diseases have characteristic late stage symptoms that often make it possible to distinguish one disorder from another, though methods to diagnose neurodegeneration pre-symptomatically remain a critical challenge. At the molecular level, misfolded protein aggregates known as amyloids are ubiquitously found in many neurodegenerative diseases, and have been suggested to appear before clinical symptoms manifest. Amyloids have, thus, become a valuable potential diagnostic target for chemists, and recent work by many groups have shown that they can be selectively targeted by small molecule fluorescent probes. Here, we summarize some of the exciting work currently under investigation in the area of fluorescence-based amyloid detection and highlight recent efforts to expand the utility of amyloid-targeting fluorophores as clinical tools for disease diagnostics.
    MeSH term(s) Alzheimer Disease/diagnostic imaging ; Amyloid/metabolism ; Amyloidogenic Proteins/metabolism ; Amyloidogenic Proteins/urine ; Amyloidosis/diagnostic imaging ; Animals ; Female ; Fluorescence ; Fluorescent Dyes/metabolism ; Fluorescent Dyes/pharmacology ; Humans ; Microscopy, Atomic Force ; Microscopy, Fluorescence ; Protein Binding
    Chemical Substances Amyloid ; Amyloidogenic Proteins ; Fluorescent Dyes
    Language English
    Publishing date 2018-07-11
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 1472881-3
    ISSN 1364-548X ; 1359-7345 ; 0009-241X
    ISSN (online) 1364-548X
    ISSN 1359-7345 ; 0009-241X
    DOI 10.1039/c8cc03619e
    Database MEDical Literature Analysis and Retrieval System OnLINE

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