Search alternatives:
linear decrease » linear increase (Expand Search)
lower decrease » larger decrease (Expand Search), teer decrease (Expand Search), showed decreased (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
linear decrease » linear increase (Expand Search)
lower decrease » larger decrease (Expand Search), teer decrease (Expand Search), showed decreased (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
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Comparison of renal tissue pathological damage grades across different groups at all time points.
Published 2024Subjects: -
406
Comparison of PCNA expression grades across different groups at various time points.
Published 2024Subjects: -
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PAS staining images of pathological changes in renal tissues among 4 groups (×400).
Published 2024Subjects: -
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Comparison of mTOR expression grading among different groups at different time points.
Published 2024Subjects: -
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Downregulation of <i>TcPiezo1</i> expression decreases Ca<sup>2+</sup> entry in <i>T. cruzi.</i>
Published 2025“…(B) Downregulation of <i>TcPiezo1</i> expression showed a significant decrease of intracellular Ca<sup>2+</sup> (+Tet). …”
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Geometric manifold comparison visualization
Published 2025“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
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419
Hyperparameter ranges
Published 2025“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
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420
Convolutional vs RNN context encoder
Published 2025“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”