Additional file 1 of Low-intensity pulsed ultrasound promotes mesenchymal stem cell transplantation-based articular cartilage regeneration via inhibiting the TNF signaling pathway

Additional file 1 Table S1: Lists of hUC-MSCs qPCR primers. Table S2: Lists of C28/I2 qPCR primer

Additional file 2 of Low-intensity pulsed ultrasound promotes mesenchymal stem cell transplantation-based articular cartilage regeneration via inhibiting the TNF signaling pathway

Additional file 2 Figure S1: Representative Alcian blue staining images for the chondrocyte spheres in suspension culture for LIPUS stimulation and adhered for staining. Figure S2: Western blot data of chondrogenic proteins (COL-II, ACAN, and SOX-9) and actin after different parameters of LIPUS stimulatio

Additional file 3 of Low-intensity pulsed ultrasound promotes mesenchymal stem cell transplantation-based articular cartilage regeneration via inhibiting the TNF signaling pathway

Additional file 3 Full-length blots of the data shown in Figure S2

ROC curve results for different diffusion models.

PurposeTo compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment.Materials and methodsA total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups.ResultsA total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively.ConclusionThe Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.</div

Results of ROC curve comparisons for different renal parenchymal models.

Results of ROC curve comparisons for different renal parenchymal models.</p

ROC curve results for six diffusion parameters.

PurposeTo compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment.Materials and methodsA total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups.ResultsA total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively.ConclusionThe Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.</div

The placement of ROIs.

The ROIs were placed both in the cortex and medulla of the three regions of the kidney (upper pole, real hilum and lower pole) on the b = 0 s/mm2 DW images.</p

ROC curve results of different renal parenchymal models.

ROC curve results of different renal parenchymal models.</p

Comparison of six diffusion parameters between patients with PA and HCs.

Comparison of six diffusion parameters between patients with PA and HCs.</p

ROC curves of the different renal parenchymal models for distinguishing patients with PA from HCs.

The AUC values of the Model_DKI_Cortex, Model_DKI_Medulla, Model_DKI, Model_Cortex, Model_Medulla and Model_all parameters were 0.833, 0.877, 0.966, 0.851,0.877 and 0.967, respectively.</p