Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

A new sustained-release (SR) pregabalin tablet, YHD1119, was formulated for once-daily dosing. In the current study, we aimed to evaluate the pharmacokinetics of YHD1119 tablets in patients with reduced renal function. Subjects were grouped by creatinine clearance:> 60 mL/min/1.73m 2 (Cohort A) and 30–60 mL/min/1.73m 2 (Cohort B). Eight subjects in Cohort A received a YHD1119 75 mg tablet (Y75T) and a YHD1119 150 mg tablet (Y150T) in each period, and eight subjects in Cohort B received a Y75T. Non-compartment analysis and population pharmacokinetic analysis using a one-compartment model with first-order elimination and first-order absorption with lag time were performed. Sixteen subjects completed the study. The geometric mean ratio (GMR) (90% confidence intervals [CI]) for maximum concentration (C max ), and area under the concentration-time profile from 0 to the last measurable time (AUC last ) after Y75T of Cohort B to those of Y75T of Cohort A were 1.2273 (1.0245–1.4701), and 2.4146 (1.8142–3.2138), respectively. The GMR (90% CI) for C max , and AUC last after Y75T of Cohort B to those of Y150T of Cohort A were 0.6476 (0.5229–0.8021), and 1.1471 (0.8418–1.5632), respectively. Simulated steady-steady pregabalin concentrations after once-daily Y75T dosing in subjects with eGFR 45 mL/min/1.73 m 2 were within the range of steady-state concentrations simulated after once-daily Y150T dosing in subjects with eGFR 90 mL/min/1.73 m 2 . The total pregabalin exposure of Y75T in patients with moderate renal impairment was comparable with that of Y150T in subjects with near-normal renal function.