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  1. AU=Liang John W
  2. AU="Segura-Martínez, Patricia"
  3. AU="Cao, Xi-Ming"
  4. AU="Labaronne, Emmanuel"
  5. AU="Shimpukade, Bharat"
  6. AU="Claude, Pierre-Abel"
  7. AU="Rocha Vogel, Angus"
  8. AU="Larkin, J"
  9. AU="Gilbert, A."
  10. AU="Jérémie Bruno"
  11. AU="Barg, Alexej"
  12. AU="Niranjan, M"
  13. AU="Solomon, Hilla"
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  15. AU=Carley David W
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  1. Artikel ; Online: Structure of adenylyl cyclase 5 in complex with Gβγ offers insights into ADCY5-related dyskinesia.

    Yen, Yu-Chen / Li, Yong / Chen, Chun-Liang / Klose, Thomas / Watts, Val J / Dessauer, Carmen W / Tesmer, John J G

    Nature structural & molecular biology

    2024  

    Abstract: The nine different membrane-anchored adenylyl cyclase isoforms (AC1-9) in mammals are stimulated by the heterotrimeric G protein, ... ...

    Abstract The nine different membrane-anchored adenylyl cyclase isoforms (AC1-9) in mammals are stimulated by the heterotrimeric G protein, Gα
    Sprache Englisch
    Erscheinungsdatum 2024-04-08
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2126708-X
    ISSN 1545-9985 ; 1545-9993
    ISSN (online) 1545-9985
    ISSN 1545-9993
    DOI 10.1038/s41594-024-01263-0
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: Antioxidative Sirt1 and the Keap1-Nrf2 Signaling Pathway Impair Inflammation and Positively Regulate Autophagy in Murine Mammary Epithelial Cells or Mammary Glands Infected with

    Khan, Sohrab / Wang, Tian / Cobo, Eduardo R / Liang, Bingchun / Khan, Muhammad Asfandyar / Xu, Maolin / Qu, Weijie / Gao, Jian / Barkema, Herman W / Kastelic, John P / Liu, Gang / Han, Bo

    Antioxidants (Basel, Switzerland)

    2024  Band 13, Heft 2

    Abstract: Streptococcus ... ...

    Abstract Streptococcus uberis
    Sprache Englisch
    Erscheinungsdatum 2024-01-29
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2704216-9
    ISSN 2076-3921
    ISSN 2076-3921
    DOI 10.3390/antiox13020171
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Decoding articulatory and phonetic components of naturalistic continuous speech from the distributed language network.

    Thomas, Tessy M / Singh, Aditya / Bullock, Latané P / Liang, Daniel / Morse, Cale W / Scherschligt, Xavier / Seymour, John P / Tandon, Nitin

    Journal of neural engineering

    2023  Band 20, Heft 4

    Abstract: Objective. ...

    Abstract Objective.
    Mesh-Begriff(e) Humans ; Speech ; Phonetics ; Language ; Electroencephalography/methods ; Sensorimotor Cortex ; Brain-Computer Interfaces
    Sprache Englisch
    Erscheinungsdatum 2023-08-14
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2170901-4
    ISSN 1741-2552 ; 1741-2560
    ISSN (online) 1741-2552
    ISSN 1741-2560
    DOI 10.1088/1741-2552/ace9fb
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Linking water use efficiency with water use strategy from leaves to communities

    Liang, Jie / Krauss, Ken W. / Finnigan, John / Stuart‐Williams, Hilary / Farquhar, Graham D. / Ball, Marilyn C.

    New Phytologist. 2023 Dec., v. 240, no. 5 p.1735-1742

    2023  

    Abstract: Limitations and utility of three measures of water use characteristics were evaluated: water use efficiency (WUE), intrinsic WUE and marginal water cost of carbon gain (∂E/∂A) estimated, respectively, as ratios of assimilation (A) to transpiration (E), ... ...

    Abstract Limitations and utility of three measures of water use characteristics were evaluated: water use efficiency (WUE), intrinsic WUE and marginal water cost of carbon gain (∂E/∂A) estimated, respectively, as ratios of assimilation (A) to transpiration (E), of A to stomatal conductance (gₛ) and of sensitivities of E and A with variation in gₛ. Only the measure ∂E/∂A estimates water use strategy in a way that integrates carbon gain relative to water use under varying environmental conditions across scales from leaves to communities. This insight provides updated and simplified ways of estimating ∂E/∂A and adds depth to understanding ways that plants balance water expenditure against carbon gain, uniquely providing a mechanistic means of predicting water use characteristics under changing environmental scenarios.
    Schlagwörter carbon ; stomatal conductance ; water use efficiency
    Sprache Englisch
    Erscheinungsverlauf 2023-12
    Umfang p. 1735-1742.
    Erscheinungsort John Wiley & Sons, Ltd
    Dokumenttyp Artikel ; Online
    Anmerkung REVIEW
    ZDB-ID 208885-x
    ISSN 1469-8137 ; 0028-646X
    ISSN (online) 1469-8137
    ISSN 0028-646X
    DOI 10.1111/nph.19308
    Datenquelle NAL Katalog (AGRICOLA)

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  5. Artikel ; Online: Linking water use efficiency with water use strategy from leaves to communities.

    Liang, Jie / Krauss, Ken W / Finnigan, John / Stuart-Williams, Hilary / Farquhar, Graham D / Ball, Marilyn C

    The New phytologist

    2023  Band 240, Heft 5, Seite(n) 1735–1742

    Abstract: Limitations and utility of three measures of water use characteristics were evaluated: water use efficiency (WUE), intrinsic WUE and marginal water cost of carbon gain ( ...

    Abstract Limitations and utility of three measures of water use characteristics were evaluated: water use efficiency (WUE), intrinsic WUE and marginal water cost of carbon gain (
    Mesh-Begriff(e) Photosynthesis ; Water ; Plant Leaves ; Carbon ; Carbon Dioxide ; Plant Transpiration ; Plant Stomata
    Chemische Substanzen Water (059QF0KO0R) ; Carbon (7440-44-0) ; Carbon Dioxide (142M471B3J)
    Sprache Englisch
    Erscheinungsdatum 2023-10-12
    Erscheinungsland England
    Dokumenttyp Journal Article ; Review
    ZDB-ID 208885-x
    ISSN 1469-8137 ; 0028-646X
    ISSN (online) 1469-8137
    ISSN 0028-646X
    DOI 10.1111/nph.19308
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel: Fungal-derived selenium nanoparticles and their potential applications in electroless silver coatings for preventing pin-tract infections.

    Liang, Xinjin / Zhang, Shuai / Gadd, Geoffrey Michael / McGrath, John / Rooney, David W / Zhao, Qi

    Regenerative biomaterials

    2022  Band 9, Heft 1, Seite(n) rbac013

    Abstract: Pin-tract infections (PTIs) are a common complication of external fixation of fractures and current strategies for preventing PTIs have proven to be ineffective. Recent advances show that the use of anti-infection coatings with local antibacterial ... ...

    Abstract Pin-tract infections (PTIs) are a common complication of external fixation of fractures and current strategies for preventing PTIs have proven to be ineffective. Recent advances show that the use of anti-infection coatings with local antibacterial activity may solve this problem. Selenium has been considered as a promising anti-infection agent owing to its antibacterial and antibiofilm activities. In this study, selenium nanoparticles (SeNPs) were synthesized
    Sprache Englisch
    Erscheinungsdatum 2022-02-22
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2799042-4
    ISSN 2056-3426 ; 2056-3418
    ISSN (online) 2056-3426
    ISSN 2056-3418
    DOI 10.1093/rb/rbac013
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; Online: Hepatitis C in Injection-Drug Users - A Hidden Danger of the Opioid Epidemic.

    Liang, T Jake / Ward, John W

    The New England journal of medicine

    2018  Band 378, Heft 13, Seite(n) 1169–1171

    Mesh-Begriff(e) Analgesics, Opioid ; Drug Users ; Epidemics ; Hepatitis C/etiology ; Humans ; Opioid-Related Disorders/complications ; Opioid-Related Disorders/epidemiology ; Substance Abuse, Intravenous/complications
    Chemische Substanzen Analgesics, Opioid
    Sprache Englisch
    Erscheinungsdatum 2018-03-30
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 207154-x
    ISSN 1533-4406 ; 0028-4793
    ISSN (online) 1533-4406
    ISSN 0028-4793
    DOI 10.1056/NEJMp1716871
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Artikel: PyTorch-FEA: Autograd-enabled Finite Element Analysis Methods with Applications for Biomechanical Analysis of Human Aorta.

    Liang, Liang / Liu, Minliang / Elefteriades, John / Sun, Wei

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Motivation: Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical ... ...

    Abstract Motivation: Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed.
    Methods: In this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance.
    Results: We applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.
    Sprache Englisch
    Erscheinungsdatum 2023-03-28
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.1101/2023.03.27.533816
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel: Synergistic Integration of Deep Neural Networks and Finite Element Method with Applications for Biomechanical Analysis of Human Aorta.

    Liang, Liang / Liu, Minliang / Elefteriades, John / Sun, Wei

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Motivation: Patient-specific finite element analysis (FEA) has the potential to aid in the prognosis of cardiovascular diseases by providing accurate stress and deformation analysis in various scenarios. It is known that patient-specific FEA is time- ... ...

    Abstract Motivation: Patient-specific finite element analysis (FEA) has the potential to aid in the prognosis of cardiovascular diseases by providing accurate stress and deformation analysis in various scenarios. It is known that patient-specific FEA is time-consuming and unsuitable for time-sensitive clinical applications. To mitigate this challenge, machine learning (ML) techniques, including deep neural networks (DNNs), have been developed to construct fast FEA surrogates. However, due to the data-driven nature of these ML models, they may not generalize well on new data, leading to unacceptable errors.
    Methods: We propose a synergistic integration of DNNs and finite element method (FEM) to overcome each other’s limitations. We demonstrated this novel integrative strategy in forward and inverse problems. For the forward problem, we developed DNNs using state-of-the-art architectures, and DNN outputs were then refined by FEM to ensure accuracy. For the inverse problem of heterogeneous material parameter identification, our method employs a DNN as regularization for the inverse analysis process to avoid erroneous material parameter distribution.
    Results: We tested our methods on biomechanical analysis of the human aorta. For the forward problem, the DNN-only models yielded acceptable stress errors in majority of test cases; yet, for some test cases that could be out of the training distribution (OOD), the peak stress errors were larger than 50%. The DNN-FEM integration eliminated the large errors for these OOD cases. Moreover, the DNN-FEM integration was magnitudes faster than the FEM-only approach. For the inverse problem, the FEM-only inverse method led to errors larger than 50%, and our DNN-FEM integration significantly improved performance on the inverse problem with errors less than 1%.
    Sprache Englisch
    Erscheinungsdatum 2023-04-05
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.1101/2023.04.03.535423
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  10. Artikel ; Online: PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta.

    Liang, Liang / Liu, Minliang / Elefteriades, John / Sun, Wei

    Computer methods and programs in biomedicine

    2023  Band 238, Seite(n) 107616

    Abstract: Background and objectives: Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to ... ...

    Abstract Background and objectives: Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed.
    Methods: In this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance.
    Results: We applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.
    Conclusions: We have presented PyTorch-FEA, a new library of FEA code and methods, representing a new approach to develop FEA methods to forward and inverse problems in solid mechanics. PyTorch-FEA eases the development of new inverse methods and enables a natural integration of FEA and DNNs, which will have numerous potential applications.
    Mesh-Begriff(e) Humans ; Finite Element Analysis ; Aorta/diagnostic imaging ; Risk Assessment ; Biomechanical Phenomena
    Sprache Englisch
    Erscheinungsdatum 2023-05-18
    Erscheinungsland Ireland
    Dokumenttyp Journal Article
    ZDB-ID 632564-6
    ISSN 1872-7565 ; 0169-2607
    ISSN (online) 1872-7565
    ISSN 0169-2607
    DOI 10.1016/j.cmpb.2023.107616
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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