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Article: ITGB1 Suppresses Autophagy Through Inhibiting The mTORC2/AKT Signaling Pathway In H9C2 Cells.

Zhou, Weiwei / Liu, Weizhe / Zhou, Dingyan / Li, Aiying

2022 Volume 77, Issue 5, Page(s) 137–140

Abstract: Cardiomyocyte autophagy is closely related to myocardial infarction and hypertrophy. To study the molecular mechanism of autophagy is helpful for the prevention and treatment of these diseases. As a cell surface receptor, the function of ITGB1 gene in ... ...

Abstract	Cardiomyocyte autophagy is closely related to myocardial infarction and hypertrophy. To study the molecular mechanism of autophagy is helpful for the prevention and treatment of these diseases. As a cell surface receptor, the function of ITGB1 gene in cardiomyocyte autophagy is not clear. The purpose of this research was to investigate the function and molecular mechanism of ITGB1 on autophagy. The autophagy-related marker proteins and signaling molecules were detected using western blot with knockdown and overexpression of ITGB1 in H9C2 cells. The results suggested that ITGB1 could inhibit autophagy and the mTORC2/Akt pathway molecules. To further investigate whether the effect of ITGB1 on autophagy might affect myocardial hypertrophy, we constructed AngII induced H9C2 cells and TAC induced rats models. The results showed that ITGB1 inhibited myocardial hypertrophy in both H9C2 cells and heart tissues of disease model. These data highlight the regulation mechanism on autophagy by ITGB1 and the potential usefulness of the gene as a potential target for preventing heart disease.
MeSH term(s)	Animals ; Autophagy ; Cardiomegaly/metabolism ; Mechanistic Target of Rapamycin Complex 2/metabolism ; Proto-Oncogene Proteins c-akt/metabolism ; Rats ; Signal Transduction
Chemical Substances	Mechanistic Target of Rapamycin Complex 2 (EC 2.7.11.1) ; Proto-Oncogene Proteins c-akt (EC 2.7.11.1)
Language	English
Publishing date	2022-06-02
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	208793-5
ISSN	0031-7144
ISSN	0031-7144
DOI	10.1691/ph.2022.2351
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Counting People by Estimating People Flows.

Liu, Weizhe / Salzmann, Mathieu / Fua, Pascal

IEEE transactions on pattern analysis and machine intelligence

2022 Volume 44, Issue 11, Page(s) 8151–8166

Abstract: Modern methods for counting people in crowded scenes rely on deep networks to estimate people densities in individual images. As such, only very few take advantage of temporal consistency in video sequences, and those that do only impose weak smoothness ... ...

Abstract	Modern methods for counting people in crowded scenes rely on deep networks to estimate people densities in individual images. As such, only very few take advantage of temporal consistency in video sequences, and those that do only impose weak smoothness constraints across consecutive frames. In this paper, we advocate estimating people flows across image locations between consecutive images and inferring the people densities from these flows instead of directly regressing them. This enables us to impose much stronger constraints encoding the conservation of the number of people. As a result, it significantly boosts performance without requiring a more complex architecture. Furthermore, it allows us to exploit the correlation between people flow and optical flow to further improve the results. We also show that leveraging people conservation constraints in both a spatial and temporal manner makes it possible to train a deep crowd counting model in an active learning setting with much fewer annotations. This significantly reduces the annotation cost while still leading to similar performance to the full supervision case.
MeSH term(s)	Algorithms ; Crowding ; Humans
Language	English
Publishing date	2022-10-04
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2021.3102690
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Comprehensive pan-cancer analysis of expression profiles and prognostic significance for NUMB and NUMBL in human tumors.

Zhang, Yue / Yang, Hongxia / Liu, Weizhe / Song, Qiuhang / Li, Yunfeng / Zhang, Juanjuan / Zhou, Dingyan / Li, Aiying

Medicine

2023 Volume 102, Issue 35, Page(s) e34717

Abstract: NUMB has been initially identified as a critical cell fate determinant that modulates cell differentiation via asymmetrical partitioning during mitosis, including tumor cells. However, it remains absent that a systematic assessment of the mechanisms ... ...

Abstract	NUMB has been initially identified as a critical cell fate determinant that modulates cell differentiation via asymmetrical partitioning during mitosis, including tumor cells. However, it remains absent that a systematic assessment of the mechanisms underlying NUMB and its homologous protein NUMBLIKE (NUMBL) involvement in cancer. This study aimed to investigate the prognostic significance for NUMB and NUMBL in pan-cancer. In this study, using the online databases TIMER2.0, gene expression profiling interactive analysis, cBioPortal, the University of ALabama at Birmingham CANcer data analysis Portal, SearchTool for the Retrieval of Interacting Genes/Proteins, and R software, we focused on the relevance between NUMB/NUMBL and oncogenesis, progression, mutation, phosphorylation, function and prognosis. This study demonstrated that abnormal expression of NUMB and NUMBL were found to be significantly associated with clinicopathologic stages and the prognosis of survival. Besides, genetic alternations of NUMB and NUMBL focused on uterine corpus endometrial carcinoma, and higher genetic mutations of NUMBL were correlated with more prolonged overall survival and disease-free survival in different cancers. Moreover, S438 locus of NUMB peptide fragment was frequently phosphorylated in 4 cancer types and relevant to its phosphorylation sites. Furthermore, endocytosis processing and neurogenesis regulation were involved in the functional mechanisms of NUMB and NUMBL separately. Additionally, the pathway enrichment suggested that NUMB was implicated in Hippo, Neurotrophin, Thyroid hormone, and FoxO pathways, while MAPK, Hippo, Rap1, mTOR, and Notch pathways were related to the functions of NUMBL. This study highlights the predictive roles of NUMB and NUMBL in pan-cancer, suggesting NUMB and NUMBL might be served as potential biomarkers for diagnosis and prognosis in various malignant tumors.
MeSH term(s)	Humans ; Female ; Prognosis ; Carcinogenesis ; Carcinoma, Endometrioid ; Cell Differentiation ; Cell Nucleus Division ; Intracellular Signaling Peptides and Proteins
Chemical Substances	NUMBL protein, human ; Intracellular Signaling Peptides and Proteins
Language	English
Publishing date	2023-09-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	80184-7
ISSN	1536-5964 ; 0025-7974
ISSN (online)	1536-5964
ISSN	0025-7974
DOI	10.1097/MD.0000000000034717
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Variational Approach for Impurity Dynamics at Finite Temperature.

Liu, Weizhe Edward / Levinsen, Jesper / Parish, Meera M

Physical review letters

2019 Volume 122, Issue 20, Page(s) 205301

Abstract: We present a general variational principle for the dynamics of impurity particles immersed in a quantum-mechanical medium. By working within the Heisenberg picture and constructing approximate time-dependent impurity operators, we can take the medium to ... ...

Abstract	We present a general variational principle for the dynamics of impurity particles immersed in a quantum-mechanical medium. By working within the Heisenberg picture and constructing approximate time-dependent impurity operators, we can take the medium to be in any mixed state, such as a thermal state. Our variational method is consistent with all conservation laws and, in certain cases, it is equivalent to a finite-temperature Green's function approach. As a demonstration of our method, we consider the dynamics of heavy impurities that have suddenly been introduced into a Fermi gas at finite temperature. Using approximate time-dependent impurity operators involving only one particle-hole excitation of the Fermi sea, we find that we can successfully model the results of recent Ramsey interference experiments on ^{40}K atoms in a ^{6}Li Fermi gas. We also show that our approximation agrees well with the exact solution for the Ramsey response of a fixed impurity at finite temperature. Our approach paves the way for the investigation of impurities with dynamical degrees of freedom in arbitrary quantum-mechanical mediums.
Language	English
Publishing date	2019-06-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.122.205301
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Leveraging Self-Supervision for Cross-Domain Crowd Counting

Liu, Weizhe / Durasov, Nikita / Fua, Pascal

2021

Abstract: State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. While effective, these data-driven approaches rely on large amount of data annotation to achieve good performance, which stops these models ... ...

Abstract	State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. While effective, these data-driven approaches rely on large amount of data annotation to achieve good performance, which stops these models from being deployed in emergencies during which data annotation is either too costly or cannot be obtained fast enough. One popular solution is to use synthetic data for training. Unfortunately, due to domain shift, the resulting models generalize poorly on real imagery. We remedy this shortcoming by training with both synthetic images, along with their associated labels, and unlabeled real images. To this end, we force our network to learn perspective-aware features by training it to recognize upside-down real images from regular ones and incorporate into it the ability to predict its own uncertainty so that it can generate useful pseudo labels for fine-tuning purposes. This yields an algorithm that consistently outperforms state-of-the-art cross-domain crowd counting ones without any extra computation at inference time.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2021-03-30
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: RGB-based Category-level Object Pose Estimation via Decoupled Metric Scale Recovery

Wei, Jiaxin / Song, Xibin / Liu, Weizhe / Kneip, Laurent / Li, Hongdong / Ji, Pan

2023

Abstract: While showing promising results, recent RGB-D camera-based category-level object pose estimation methods have restricted applications due to the heavy reliance on depth sensors. RGB-only methods provide an alternative to this problem yet suffer from ... ...

Abstract	While showing promising results, recent RGB-D camera-based category-level object pose estimation methods have restricted applications due to the heavy reliance on depth sensors. RGB-only methods provide an alternative to this problem yet suffer from inherent scale ambiguity stemming from monocular observations. In this paper, we propose a novel pipeline that decouples the 6D pose and size estimation to mitigate the influence of imperfect scales on rigid transformations. Specifically, we leverage a pre-trained monocular estimator to extract local geometric information, mainly facilitating the search for inlier 2D-3D correspondence. Meanwhile, a separate branch is designed to directly recover the metric scale of the object based on category-level statistics. Finally, we advocate using the RANSAC-P$n$P algorithm to robustly solve for 6D object pose. Extensive experiments have been conducted on both synthetic and real datasets, demonstrating the superior performance of our method over previous state-of-the-art RGB-based approaches, especially in terms of rotation accuracy. Code: https://github.com/goldoak/DMSR.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	004
Publishing date	2023-09-18
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Radio-Frequency Response and Contact of Impurities in a Quantum Gas.

Liu, Weizhe Edward / Shi, Zhe-Yu / Levinsen, Jesper / Parish, Meera M

Physical review letters

2020 Volume 125, Issue 6, Page(s) 65301

Abstract: We investigate the radio-frequency spectroscopy of impurities interacting with a quantum gas at finite temperature. In the limit of a single impurity, we show using Fermi's golden rule that introducing (or injecting) an impurity into the medium is ... ...

Abstract	We investigate the radio-frequency spectroscopy of impurities interacting with a quantum gas at finite temperature. In the limit of a single impurity, we show using Fermi's golden rule that introducing (or injecting) an impurity into the medium is equivalent to ejecting an impurity that is initially interacting with the medium, since the "injection" and "ejection" spectral responses are simply related to each other by an exponential function of frequency. Thus, the full spectral information for the quantum impurity is contained in the injection spectral response, which can be determined using a range of theoretical methods, including variational approaches. We use this property to compute the finite-temperature equation of state and Tan contact of the Fermi polaron. Our results for the contact of a mobile impurity are in excellent agreement with recent experiments and we find that the finite-temperature behavior is qualitatively different compared to the case of infinite impurity mass.
Language	English
Publishing date	2020-08-26
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.125.065301
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Forty cases of insomnia treated by multi-output electric pulsation and auricular plaster therapy.

Liu, Weizhe

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan

2007 Volume 27, Issue 2, Page(s) 106–107

MeSH term(s)	Acupuncture Points ; Acupuncture, Ear ; Adult ; Electroacupuncture ; Female ; Humans ; Male ; Middle Aged ; Sleep Initiation and Maintenance Disorders/therapy ; Young Adult
Language	English
Publishing date	2007-06
Publishing country	China
Document type	Clinical Trial ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	603186-9
ISSN	0254-6272 ; 0255-2922
ISSN (online)	0254-6272
ISSN	0255-2922
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Counting People by Estimating People Flows

Liu, Weizhe / Salzmann, Mathieu / Fua, Pascal

2020

Abstract	Modern methods for counting people in crowded scenes rely on deep networks to estimate people densities in individual images. As such, only very few take advantage of temporal consistency in video sequences, and those that do only impose weak smoothness constraints across consecutive frames. In this paper, we advocate estimating people flows across image locations between consecutive images and inferring the people densities from these flows instead of directly regressing them. This enables us to impose much stronger constraints encoding the conservation of the number of people. As a result, it significantly boosts performance without requiring a more complex architecture. Furthermore, it allows us to exploit the correlation between people flow and optical flow to further improve the results. We also show that leveraging people conservation constraints in both a spatial and temporal manner makes it possible to train a deep crowd counting model in an active learning setting with much fewer annotations. This significantly reduces the annotation cost while still leading to similar performance to the full supervision case. Comment: Accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence. Extension of Our ECCV 2020 Paper: arXiv:1911.10782
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning
Subject code	006
Publishing date	2020-12-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Action Mode of the Mycotoxin Patulin as a Novel Natural Photosystem II Inhibitor

Guo, Yanjing / Liu, Weizhe / Wang, He / Wang, Xiaoxiong / Qiang, Sheng / Kalaji, Hazem M. / Strasser, Reto Jörg / Chen, Shiguo

Journal of agricultural and food chemistry. 2021 June 24, v. 69, no. 26

2021

Abstract: A biocontrol method plays an important role in weed management. In this study, we aimed to clarify the phytotoxicity of the mycotoxin patulin (PAT) and reveal its mode of action as a new natural photosystem II (PSII) inhibitor. Phytotoxicity test showed ... ...

Abstract	A biocontrol method plays an important role in weed management. In this study, we aimed to clarify the phytotoxicity of the mycotoxin patulin (PAT) and reveal its mode of action as a new natural photosystem II (PSII) inhibitor. Phytotoxicity test showed that PAT has herbicidal activity and causes significant leaf lesions on Ageratina adenophora. Under a half-inhibition concentration I₅₀ (2.24 μM), the observed significant decrease in oxygen evolution rate and the increase in the J-step of the chlorophyll fluorescence rise OJIP curve indicated that PAT strongly reduces photosynthetic efficiency by blocking electron transport from the primary to secondary plastoquinone acceptors (QA to QB) of PSII. Molecular modeling of PAT docking to the A. adenophora D1 protein suggested that PAT bounds to the QB site by forming hydrogen bonds to histidine 252 in the D1 protein. It is proposed that PAT is a new natural PSII inhibitor and has the potential to be developed into a bioherbicide or used as a template scaffold for discovering novel derivatives with more potent herbicidal activity.
Keywords	Ageratina adenophora ; D1 protein ; biological control ; biopesticides ; chlorophyll ; electron transfer ; food chemistry ; herbicidal properties ; histidine ; hydrogen ; leaves ; mechanism of action ; oxygen production ; patulin ; photosystem II ; phytotoxicity ; plastoquinones ; weed control
Language	English
Dates of publication	2021-0624
Size	p. 7313-7323.
Publishing place	American Chemical Society
Document type	Article
ZDB-ID	241619-0
ISSN	1520-5118 ; 0021-8561
ISSN (online)	1520-5118
ISSN	0021-8561
DOI	10.1021/acs.jafc.1c01811
Database	NAL-Catalogue (AGRICOLA)

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