Search alternatives:
marked decrease » marked increase (Expand Search)
maps decrease » small decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
marked decrease » marked increase (Expand Search)
maps decrease » small decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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The heart rate was similar among the groups.
Published 2025“…Following the overexpression of miRNA 221 in myocardium, there was a marked alleviation of myocardial injury and cardiomyocyte apoptosis and necrosis, significant enhancement of left ventricular systolic function, and marked decrease in the levels of PLB, p-PLB (Ser16), p-PLB (Thr17), caspase 3 and Cyt C, as well as a significant decrease in total calcium levels in myocardium.…”
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S1 File -
Published 2025“…Following the overexpression of miRNA 221 in myocardium, there was a marked alleviation of myocardial injury and cardiomyocyte apoptosis and necrosis, significant enhancement of left ventricular systolic function, and marked decrease in the levels of PLB, p-PLB (Ser16), p-PLB (Thr17), caspase 3 and Cyt C, as well as a significant decrease in total calcium levels in myocardium.…”
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Primer sequences for RT-qPCR.
Published 2025“…Following the overexpression of miRNA 221 in myocardium, there was a marked alleviation of myocardial injury and cardiomyocyte apoptosis and necrosis, significant enhancement of left ventricular systolic function, and marked decrease in the levels of PLB, p-PLB (Ser16), p-PLB (Thr17), caspase 3 and Cyt C, as well as a significant decrease in total calcium levels in myocardium.…”
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Heat maps for different models.
Published 2025“…First, an efficient channel attention mechanism (ECA) is inserted in the layer before the SPPF in the backbone network, which realizes efficient computation of channel attention and reduces redundant computation while decreasing the model complication. Second, using the Content-Aware ReAssembly of Features (CARAFE) module instead of the original nearest-neighbor up-sampling module achieves light weighting while allowing for better aggregation of contextual information within a larger sensory field, which effectively improves the diversity and effectiveness of the model. …”
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