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step decrease » sizes decrease (Expand Search), teer decrease (Expand Search)
we decrease » _ decrease (Expand Search), mean decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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1201
The decrease in lactate induced by pyruvate is blocked by inhibition of MAS and of the TCA cycle in HKI/HKII double KD cells.
Published 2023“…Following the decrease in lactate evoked by pyruvate, addition of AOA reversed this effect, causing a rapid increase in lactate. …”
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1202
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1203
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1204
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1205
NbVO<sub>5</sub> Mesoporous Thin Films by Evaporation Induced Micelles Packing: Pore Size Dependence of the Mechanical Stability upon Thermal Treatment and Li Insertion/Extraction
Published 2011“…In order to investigate the potentialities and limits of the soft-templating approach in the case of complex transition metal oxide networks, we deliberately selected a “difficult” compound: NbVO<sub>5</sub> was chosen because it combines a challenging synthesis with reported severe structural distortions during the first lithium insertion in the bulk material. …”
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1206
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1207
Loss of epithelial markers is an early event in oral dysplasia and is observed within the safety margin of dysplastic and T1 OSCC biopsies
Published 2017“…<div><p>Oral squamous cell carcinoma (OSCC) is a highly aggressive cancer that is associated with poor 5-year patient survival. …”
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1208
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1209
Image_1_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif
Published 2022“…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
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1210
Image_4_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif
Published 2022“…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
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1211
Image_7_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif
Published 2022“…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
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1212
Image_3_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif
Published 2022“…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
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1213
Image_6_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif
Published 2022“…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
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1214
Image_2_TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1.tif
Published 2022“…T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. …”
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1215
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1216
Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter
Published 2023“…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
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1217
Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter
Published 2023“…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
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1218
Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter
Published 2023“…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
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1219
Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter
Published 2023“…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”
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1220
Deciphering Nonbioavailable Substructures Improves the Bioavailability of Antidepressants by Serotonin Transporter
Published 2023“…A machine learning model was developed to identify nonbioavailable substructures based on their molecular properties and shows the accuracy of 83.5%. …”