Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease.

BACKGROUND: Non-invasive renal fibrosis assessment is critical for tailoring personalized decision-making and managing follow-up in patients with chronic kidney disease (CKD). We aimed to exploit machine learning algorithms using clinical and elastosonographic features to distinguish moderate-severe fibrosis from mild fibrosis among CKD patients. METHODS: A total of 162 patients with CKD who underwent shear wave elastography examinations and renal biopsies at our institution were prospectively enrolled. Four classifiers using machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and K-Nearest Neighbor (KNN), which integrated elastosonographic features and clinical characteristics, were established to differentiate moderate-severe renal fibrosis from mild forms. The area under the receiver operating characteristic curve (AUC) and average precision were employed to compare the performance of constructed models, and the SHapley Additive exPlanations (SHAP) strategy was used to visualize and interpret the model output. RESULTS: The XGBoost model outperformed the other developed machine learning models, demonstrating optimal diagnostic performance in both the primary (AUC = 0.97, 95% confidence level (CI) 0.94-0.99; average precision = 0.97, 95% CI 0.97-0.98) and five-fold cross-validation (AUC = 0.85, 95% CI 0.73-0.98; average precision = 0.90, 95% CI 0.86-0.93) datasets. The SHAP approach provided visual interpretation for XGBoost, highlighting the features' impact on the diagnostic process, wherein the estimated glomerular filtration rate provided the largest contribution to the model output, followed by the elastic modulus, then renal length, renal resistive index, and hypertension. CONCLUSION: This study proposed an XGBoost model for distinguishing moderate-severe renal fibrosis from mild forms in CKD patients, which could be used to assist clinicians in decision-making and follow-up strategies. Moreover, the SHAP algorithm makes it feasible to visualize and interpret the feature processing and diagnostic processes of the model output.

Artificial cavernosa-like tissue based on multibubble Matrigel and a human corpus cavernous fibroblast scaffold.

Ex vivo tissue culture of the human corpus cavernosum (CC) can be used to explore the tissue structural changes and complex signaling networks. At present, artificial CC-like tissues based on acellular or three-dimensional (3D)-printed scaffolds are used to solve the scarcity of primary penis tissue samples. However, inconvenience and high costs limit the wide application of such methods. Here, we describe a simple, fast, and economical method of constructing artificial CC-like tissue. Human CC fibroblasts (FBs), endothelial cells (ECs), and smooth muscle cells (SMCs) were expanded in vitro and mixed with Matrigel in specific proportions. A large number of bubbles were formed in the mixture by vortexing combined with pipette blowing, creating a porous, spongy, and spatial structure. The CC FBs produced a variety of signaling factors, showed multidirectional differentiation potential, and grew in a 3D grid in Matrigel, which is necessary for CC-like tissue to maintain a porous structure as a cell scaffold. Within the CC-like tissue, ECs covered the surface of the lumen, and SMCs were located inside the trabeculae, similar to the structure of the primary CC. Various cell components remained stable for 3 days in vitro, but the EC content decreased on the 7th day. Wingless/integrated (WNT) signaling activation led to lumen atrophy and increased tissue fibrosis in CC-like tissue, inducing the same changes in characteristics as in the primary CC. This study describes a preparation method for human artificial CC-like tissue that may provide an improved experimental platform for exploring the function and structure of the CC and conducting drug screening for erectile dysfunction therapy.

Integrating shear wave elastography and estimated glomerular filtration rate to enhance diagnostic strategy for renal fibrosis assessment in chronic kidney disease.

Background: Assessing renal fibrosis non-invasively in patients with chronic kidney disease (CKD) remains a considerable clinical challenge. This study aimed to investigate the diagnostic efficacy of different approaches that combine shear wave elastography (SWE) and estimated glomerular filtration rate (eGFR) in distinguishing between mild fibrosis and moderate-to-severe fibrosis in CKD patients. Methods: In this prospective study, 162 patients underwent renal SWE examinations and renal biopsies. Using SWE, the right renal cortex stiffness was measured, and the corresponding SWE value was recorded. Four diagnostic patterns were used to combine eGFR and SWE value: in isolation, in series, in parallel, and in integration. The receiver operating characteristic (ROC) curve was established, and the area under the ROC curve (AUC) was calculated to quantify diagnostic performance. Sensitivity, specificity, and accuracy were computed. Results: The eGFR demonstrated sensitivity of 68.2% and specificity of 83.8%, whereas the SWE value displayed sensitivity of 84.1% and specificity of 62.2%, yielding a similar AUC (78.2% and 77.8%, respectively). Combining in series improved specificity to 97.3%, superior to other diagnostic patterns (all P values <0.01), but compromised sensitivity to 58.0%. When combined in parallel, the sensitivity increased to 94.3%, exceeding any other strategies (all P values <0.05), but the specificity dropped to 48.7%. The integrated strategy, incorporating eGFR with SWE value via the logistic regression algorithm, exhibited an AUC of 85.8%, outperforming all existing approaches (all P values <0.01), with balanced sensitivity, specificity, and accuracy of 86.4%, 74.3%, and 80.9%, respectively. Conclusions: Using an integrated strategy to combine eGFR and SWE value could improve diagnostic performance in distinguishing between mild renal fibrosis and moderate-to-severe renal fibrosis in patients with CKD, thereby helping clinicians perform a more accurate clinical diagnosis.

Association of renal elasticity evaluated by real-time shear wave elastography with renal fibrosis in patients with chronic kidney disease.

OBJECTIVE: Renal fibrosis is a final common pathological hallmark in the progression of chronic kidney disease (CKD). Non-invasive evaluation of renal fibrosis by mapping renal stiffness obtained by shear wave elastography (SWE) may facilitate the clinical therapeutic regimen for CKD patients. METHODS: A cohort of 162 patients diagnosed with CKD, who underwent renal biopsy, was prospectively and consecutively recruited between April 2019 and December 2021. The assessment of renal cortex stiffness was performed using SWE imaging. The patients were classified into different groups based on pathological renal fibrosis (mild group: n = 74; moderate-to-severe group: n = 88). Binary logistic regression model and generalized additive model were conducted to investigate the association of renal elasticity with renal fibrosis. RESULTS: Compared with the mildly impaired group, the moderate-to-severe group showed a significant decline in renal elasticity (P < .001). In the fully adjusted model, each 10 kPa drop in renal elasticity was associated with a 3.5-fold increment in the risk of moderate-to-severe renal fibrosis (fully adjusted odds ratio, 4.54; 95% CI, 2.41-8.57). Particularly, participants in the lowest elasticity group (≤29.92 kPa) had a 20-fold increased chance of moderate-to-severe renal fibrosis than those in the group with highest elasticity (≥37.93 kPa). An inverse linear association was observed between renal elasticity increment and moderate-to-severe renal fibrosis risk. CONCLUSION: There is a negative linear association between increased renal elasticity and moderate-to-severe renal fibrosis risk among CKD patients. Patients with diminished renal stiffness have a higher risk of moderate-to-severe renal fibrosis. ADVANCES IN KNOWLEDGE: CKD patients with reduced renal stiffness have a higher likelihood of moderate-to-severe renal fibrosis.

Autophagy-amplifying nanoparticles evoke immunogenic cell death combined with anti-PD-1/PD-L1 for residual tumors immunotherapy after RFA.

Incomplete radiofrequency ablation (IRFA) triggers mild protective autophagy in residual tumor cells and results in an immunosuppressive microenvironment. This accelerates the recurrence of residual tumors and causes resistance to anti-PD-1/PDL1 therapy, which bringing a great clinical challenge in residual tumors immunotherapy. Mild autophagy activation can promote cancer cell survival while further amplification of autophagy contributes to immunogenic cell death (ICD). To this regard, we constructed active targeting zeolitic imidazolate framework-8 (ZIF-8) nanoparticles (NPs) loaded with STF62247 or both STF62247 and BMS202, namely STF62247@ZIF-8/PEG-FA (SZP) or STF62247-BMS202@ZIF-8/PEG-FA (SBZP) NPs. We found that SZP NPs inhibited proliferation and stimulated apoptosis of residual tumor cells exposed to sublethal heat stress in an autophagy-dependent manner. Further results discovered that SZP NPs could amplify autophagy in residual tumor cells and evoke their ICD, which dramatically boosted the maturation of dendritic cells (DCs). Through vaccination experiments, we found for the first time that vaccination with heat + SZP treatment could efficiently suppress the growth of new tumors and establish long-term immunological memory. Furthermore, SBZP NPs could remarkably promote the ICD of residual tumor cells, obviously activate the anti-tumor immune microenvironment, and significantly inhibit the growth of residual tumors. Thus, amplified autophagy coupled with anti-PD-1/PDL1 therapy is potentially a novel strategy for treating residual tumors after IRFA.

Precise localization of microvascular invasion in hepatocellular carcinoma based on three-dimensional histology-MR image fusion: an ex vivo experimental study.

Background: Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). However, MVI cannot be detected by conventional imaging. To localize MVI precisely on magnetic resonance (MR) images, we evaluated the feasibility and accuracy of 3-dimensional (3D) histology-MR image fusion of the liver. Methods: Animal models of VX2 liver tumors were established in 10 New Zealand white rabbits under ultrasonographic guidance. The whole liver lobe containing the VX2 tumor was extracted and divided into 4 specimens, for a total of 40 specimens. MR images were obtained with a T2-weighted sequence for each specimen, and then histological images were obtained by intermittent, serial pathological sections. 3D histology-MR image fusion was performed via landmark registration in 3D Slicer software. We calculated the success rate and registration errors of image fusion, and then we located the MVI on MR images. Regarding influencing factors, we evaluated the uniformity of tissue thickness after sampling and the uniformity of tissue shrinkage after dehydration. Results: The VX2 liver tumor model was successfully established in the 10 rabbits. The incidence of MVI was 80% (8/10). 3D histology-MR image fusion was successfully performed in the 39 specimens, and the success rate was 97.5% (39/40). The average registration error was 0.44±0.15 mm. MVI was detected in 20 of the 39 successfully registered specimens, resulting in a total of 166 MVI lesions. The specific location of all MVI lesions was accurately identified on MR images using 3D histology-MR image fusion. All MVI lesions showed as slightly hyperintense on the high-resolution MR T2-weighted images. The results of the influencing factor assessment showed that the tissue thickness was uniform after sampling (P=0.38), but the rates of the tissue shrinkage was inconsistent after dehydration (P<0.001). Conclusions: 3D histology-MR image fusion of the isolated liver tumor model is feasible and accurate and allows for the successful identification of the specific location of MVI on MR images.

Contrast-enhanced US with Sulfur Hexafluoride and Perfluorobutane: LI-RADS for Diagnosing Hepatocellular Carcinoma.

Background Liver Imaging Reporting and Data System (LI-RADS) was designed for contrast-enhanced US (CEUS) with pure blood pool agents to diagnose hepatocellularfcarcinoma (HCC), such as sulfur hexafluoride (SHF), but Kupffer-cell agents, such as perfluorobutane (PFB), allow additional lesion characterization in the Kupffer phase yet remain unaddressed. Purpose To compare the diagnostic performance of three algorithms for HCC diagnosis: two algorithms based on CEUS LI-RADS version 2017 for both SHF and PFB and a modified algorithm incorporating Kupffer-phase findings for PFB. Materials and Methods This multicenter prospective study enrolled high-risk patients for HCC from June 2021 to December 2021. Each participant underwent same-day SHF-enhanced US followed by PFB-enhanced US. Each liver observation was assigned three LI-RADS categories according to each algorithm: LI-RADS SHF, LI-RADS PFB, and modified PFB. For modified PFB, observations at least 10 mm with nonrim arterial phase hyperenhancement were upgraded LR-4 to LR-5 if there was no washout with a Kupffer defect and were reassigned LR-M to LR-5 if there was early washout with mild Kupffer defect. The reference standard was pathologic confirmation or composite (typical CT or MRI features, or 1-year size stability and/or reduction). Diagnostic metrics of LR-5 for HCC using the three algorithms were calculated and compared using the McNemar test. Results Overall, 375 patients (mean age, 56 years ± 11 [SD]; 318 male patients, 57 female patients) with 424 observations (345 HCCs, 40 non-HCC malignancies, 39 benign lesions) were enrolled. PFB and SHF both using LI-RADS showed no significant difference in sensitivity (60% vs 58%; P = .41) and specificity (96% vs 95%; P > .99). The modified algorithm with PFB had increased sensitivity (80% vs 58%; P < .001) and a nonsignificant decrease in specificity (92% vs 95%; P = .73) compared with LI-RADS SHF. Conclusion Based on CEUS LI-RADS version 2017, both SHF and PFB achieved high specificity and relatively low sensitivity for HCC diagnosis. When incorporating Kupffer-phase findings, PFB had higher sensitivity without loss of specificity. Chinese Clinical Trial Registry no. ChiCTR2100047035 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kim in this issue.

Nomogram Analysis Based on Clinical and Sonographic Characteristics for the Assessment of Postpartum Stress Urinary Incontinence.

OBJECTIVES: We aimed to develop and validate a nomogram integrating clinical and sonographic characteristics for the individualized SUI risk evaluation in the early postpartum stage. METHODS: This was a prospective cross-sectional study. From June 2020 to September 2022, singleton primiparas who underwent TPUS examination at 6-8 weeks postpartum were recruited. They were divided into the training and validation cohorts at a ratio of 8:2 according to the temporal split. All subjects were interviewed before TPUS examination. Univariate and multivariate logistic analyses were performed to develop three models: the clinical, sonographic, and combined models. The ROC curve was plotted to evaluate model discrimination ability. Finally, the combined model was selected to establish the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were evaluated in the training and validation cohorts. RESULTS: The performance of the combined model was better than that of the clinical and sonographic models. Six predictors (BMI, delivery mode, lateral episiotomy, SUI during pregnancy, cystocele, and bladder neck funneling) remained in the combined model. The nomogram based on the combined model had good discrimination with AUCs of 0.848 (95% CI: 0.796-0.900) and 0.872 (95% CI: 0.789-0.955) in the training and validation cohorts, respectively, and the calibration curve showed good efficiency in assessing postpartum SUI. Decision curve analysis showed that the nomogram was clinically useful. CONCLUSIONS: The nomogram based on clinical and sonographic characteristics showed good efficiency in assessing postpartum SUI risk and can be a convenient and reliable tool for individual SUI risk assessment.

Ultrasound-based radiomics analysis in the assessment of renal fibrosis in patients with chronic kidney disease.

PURPOSE: Assessment of renal fibrosis non-invasively in chronic kidney disease (CKD) patients is still a clinical challenge. In this study, we aimed to establish a radiomics model integrating radiomics features derived from ultrasound (US) images with clinical characteristics for the assessment of renal fibrosis severity in CKD patients. METHODS: A total of 160 patients with CKD who underwent kidney biopsy and renal US examination were prospectively enrolled. Patients were classified into the mild or moderate-severe fibrosis group based on pathology results. Radiomics features were extracted from the US images, and a radiomics signature was constructed using the maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) regression algorithms. Multivariable logistic regression was employed to construct the radiomics model, which incorporated the radiomics signature and the selected clinical variables. The established model was evaluated for discrimination, calibration, and clinical utility in the derivation cohort and internal cross-validation (CV) analysis, respectively. RESULTS: The radiomics signature, consisting of nine identified fibrosis-related features, achieved moderate discriminatory ability with an area under the receiver operating characteristic curve (AUC) of 0.72 (95% confidence interval (CI) 0.64-0.79). By combining the radiomics signature with significant clinical risk factors, the radiomics model showed satisfactory discrimination performance, yielding an AUC of 0.85 (95% CI 0.79-0.91) in the derivation cohort and a mean AUC of 0.84 (95% CI 0.77-0.92) in the internal CV analysis. It also demonstrated fine accuracy via the calibration curve. Furthermore, the decision curve analysis indicated that the model was clinically useful. CONCLUSION: The proposed radiomics model showed favorable performance in determining the individualized risk of moderate-severe renal fibrosis in patients with CKD, which may facilitate more effective clinical decision-making.

Using elastography-based multilayer perceptron model to evaluate renal fibrosis in chronic kidney disease.

BACKGROUND: Given its progressive deterioration in the clinical course, noninvasive assessment and risk stratification for the severity of renal fibrosis in chronic kidney disease (CKD) are required. We aimed to develop and validate an end-to-end multilayer perceptron (MLP) model for assessing renal fibrosis in CKD patients based on real-time two-dimensional shear wave elastography (2D-SWE) and clinical variables. METHODS: From April 2019 to December 2021, a total of 162 patients with CKD who underwent a kidney biopsy and 2D-SWE examination were included in this single-center, cross-sectional, and prospective clinical study. 2D-SWE was performed to measure the right renal cortex stiffness, and the corresponding elastic values were recorded. Patients were categorized into two groups according to their histopathological results: mild and moderate-severe renal fibrosis. The patients were randomly divided into a training cohort (n = 114) or a test cohort (n = 48). The MLP classifier using a machine learning algorithm was used to construct a diagnostic model incorporating elastic values with clinical features. Discrimination, calibration, and clinical utility were used to appraise the performance of the established MLP model in the training and test sets, respectively. RESULTS: The developed MLP model demonstrated good calibration and discrimination in both the training [area under the receiver operating characteristic curve (AUC) = 0.93; 95% confidence interval (CI) = 0.88 to 0.98] and test cohorts [AUC = 0.86; 95% CI = 0.75 to 0.97]. A decision curve analysis and a clinical impact curve also showed that the MLP model had a positive clinical impact and relatively few negative effects. CONCLUSIONS: The proposed MLP model exhibited the satisfactory performance in identifying the individualized risk of moderate-severe renal fibrosis in patients with CKD, which is potentially helpful for clinical management and treatment decision-making.

Assessment of Renal Fibrosis in Patients With Chronic Kidney Disease Using Shear Wave Elastography and Clinical Features: A Random Forest Approach.

OBJECTIVE: Renal fibrosis is the common pathological hallmark of chronic kidney disease (CKD) progression. In this study, a random forest (RF) classifier based on 2-D shear wave elastography (SWE) and clinical features for the differential severity of renal fibrosis in patients with CKD is proposed. METHODS: A total of 162 patients diagnosed with CKD who underwent 2-D SWE and renal biopsy were prospectively enrolled from April 2019 to December 2021 and then randomized into training (n = 114) and validation (n = 48) cohorts at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression and recursive feature elimination for support vector machines (SVM-RFE) algorithm were employed to select renal fibrosis-related features from clinical information and elastosonographic findings. An RF model was subsequently constructed using the aforementioned informative parameters in the training cohort and evaluated in terms of discrimination, calibration and clinical utility in both cohorts. RESULTS: The LASSO and SVM-RFE analyses revealed that age, sex, blood urea nitrogen, renal resistive index, hypertension and the 2D-SWE value were independent risk variables associated with renal fibrosis severity. The established RF model incorporating these six variables exhibited fine discrimination in both the derivation (area under the curve [AUC]: 0.84, 95% confidence interval [CI]: 0.76-0.91) and validation (AUC: 0.88, 95% CI: 0.77-0.98) cohorts. Moreover, the calibration curve revealed satisfactory predictive accuracy, and the decision curve analysis revealed a significant clinical net benefit. CONCLUSION: The developed RF model, via a combination of the 2-D SWE value and clinical information, indicated satisfactory diagnostic performance and clinical practicality toward differentiating moderate-severe from mild renal fibrosis, which may provide critical insight into risk stratification for patients with CKD.

Development and Deployment of a Novel Diagnostic Tool Based on Conventional Ultrasound for Fibrosis Assessment in Chronic Kidney Disease.

RATIONALE AND OBJECTIVES: Accurate identification of risk information about fibrosis severity is crucial for clinical decision-making and clinical management of patients with chronic kidney disease (CKD). This study aimed to develop an ultrasound (US)-derived computer-aided diagnosis tool for identifying CKD patients at high risk of developing moderate-severe renal fibrosis, in order to optimize treatment regimens and follow-up strategies. MATERIALS AND METHODS: A total of 162 CKD patients undergoing renal biopsies and US examinations were prospectively enrolled and randomly divided into training (n = 114) and validation (n = 48) cohorts. A multivariate logistic regression approach was employed to develop the diagnostic tool named S-CKD for differentiating moderate-severe renal fibrosis from mild one in the training cohort by integrating the significant variables, which were screened out from demographic characteristics and conventional US features via the least absolute shrinkage and selection operator regression algorithm. The S-CKD was then deployed as both an online web-based and an offline document-based, easy-to-use auxiliary device. In both the training and validation cohorts, the S-CKD's diagnostic performance was evaluated through discrimination and calibration. The clinical benefit of using S-CKD was revealed by decision curve analysis (DCA) and clinical impact curves. RESULTS: The proposed S-CKD achieved an area under the receiver operating characteristic curve of 0.84 (95% confidence interval (CI): 0.77-0.91) and 0.81 (95% CI: 0.68-0.94) in the training and validation cohorts, respectively, indicating satisfactory diagnosis performance. Results of the calibration curves showed that S-CKD has excellent predictive accuracy (Hosmer-Lemeshow test: training cohort, p = 0.497; validation cohort, p = 0.205). The DCA and clinical impact curves exhibited a high clinical application value of the S-CKD at a wide range of risk probabilities. CONCLUSION: The S-CKD tool developed in this study is capable of discriminating between mild and moderate-severe renal fibrosis in patients with CKD and achieving promising clinical benefits, which may aid clinicians in personalizing medical decision-making and follow-up arrangement.

A methodological study of 2D shear wave elastography for noninvasive quantitative assessment of renal fibrosis in patients with chronic kidney disease.

PURPOSE: To determine the optimal measurement method of 2D shear wave elastography (2D-SWE) for noninvasive quantitative assessment of renal fibrosis in chronic kidney disease (CKD) patients. METHODS: A total of 190 CKD patients were enrolled for 2D-SWE of right kidney. The success rates, coefficients of variation (CV), and pathological correlation of different measurement sites, body positions, and depths were compared. RESULTS: (1) Measurement sites: Success rate in the middle part (100%) was higher than that in the lower pole (97.3%, P > 0.05). CV in the middle part (10.2%) was lower than that in the lower pole (16.4%, P < 0.05). Pathological correlation of the middle part (r = - 0.452, P < 0.05) was higher than that of the lower pole (r = 0.097, P > 0.05). (2) Body positions: Success rate in left lateral decubitus position (100%) was higher than that in supine (99.4%, P > 0.05) and prone position (99.4%, P > 0.05). CV was lowest (11.9%) and pathological correlation was highest (r = -0.256, P < 0.05) in prone position. (3) Measurement depths: Success rate at depth < 4 cm (100%) was higher than that at depth ≥ 4 cm (98.8%, P > 0.05). CV at depth < 4 cm (11.1%) was lower than that at depth ≥ 4 cm (14.4%, P < 0.05). Pathological correlation at depth < 4 cm (r = - 0.303, P < 0.05) was higher than that at depth ≥ 4 cm (r = - 0.156, P > 0.05). CONCLUSION: The optimal measurement method of 2D-SWE for renal fibrosis assessment was prone position, renal middle part, and measurement depth < 4 cm.

A nomogram based on shear wave elastography for assessment of renal fibrosis in patients with chronic kidney disease.

BACKGROUND: Non-invasive evaluation of renal fibrosis is still challenging. This study aimed to establish a nomogram based on shear wave elastography (SWE) and clinical features for the assessment of the severity of renal fibrosis in patients with chronic kidney disease (CKD). METHODS: One hundred and sixty-two patients with CKD who underwent kidney biopsy and SWE examination were prospectively enrolled between April 2019 and December 2021. Patients were classified into mildly or moderately-severely impaired group based on pathology results. All patients were randomly divided into a training (n = 113) or validation cohort (n = 49). Least absolute shrinkage and selection operator (LASSO) algorithm was used for data dimensionality reduction and feature selection. Then, a diagnostic nomogram incorporating the selected features was constructed using multivariable logistic regression analysis. Nomogram performance was evaluated for discrimination, calibration, and clinical utility in training and validation cohorts. RESULTS: The established SWE nomogram, which integrated SWE value, hypertension, and estimated glomerular filtration rate, showed fine calibration and discrimination in both training (area under the receiver operator characteristic curve (AUC) = 0.94; 95% confidence interval (CI) 0.89-0.98) and validation cohorts (AUC = 0.84; 95% CI 0.71-0.96). Significant improvement in net reclassification and integrated discrimination indicated that the SWE value is a valuable biomarker to assess moderate-severe renal impairment. Furthermore, decision curve analysis revealed that the SWE nomogram has clinical value. CONCLUSION: The proposed SWE nomogram showed favorable performance in determining individualized risk of moderate-severe renal pathological impairment in patients with CKD, which will help to facilitate clinical decision-making.

Benign thyroid nodules classified as ACR TI-RADS 4 or 5: Imaging and histological features.

BACKGROUND: American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) being most widely applied in clinical practice, there is an overlap in US imaging manifestations between benign and malignant thyroid nodules. OBJECTIVES: To analyze the imaging and histological characteristics of pathological benign thyroid nodules categorized as American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 4 or 5, and to explore the correlation between the suspicious sonographic signs resulting in the misdiagnoses and the histopathological features. MATERIALS AND METHODS: Overall, 227 benign thyroid nodules (215 patients) in ACR TI-RADS 4 or 5 sampled through surgical excision were analyzed between December 2020 and August 2022. We retrospectively reread the ultrasound (US) images of the pathological discordant cases, after which we performed a systematic analysis focusing on the histopathological characteristics of thyroid lesions and recorded the findings. Qualitative US features and pathological significance of the thyroid nodules were analyzed using the chi-square and Fisher's exact tests. RESULTS: The pathological type of 227 thyroid nodules (n = 103 in ACR TI-RADS 4 and n = 124 in ACR TI-RADS 5) was nodular goiter together with other histopathological features, namely, fibrosis (n = 103, 45.4 %), calcification (n = 70, 30.8 %), adenomatous hyperplasia (n = 31, 13.7 %), follicular epithelial hyperplasia (n = 23, 10.1 %), Hashimoto's thyroiditis (n = 18, 7.9 %), and cystic degeneration (n = 16, 7.1 %). Fibrosis was the most common histopathological feature in both ACR TI-RADS 4 (n = 42, 40.8 %) and 5 (n = 61, 49.2 %) categories of benign thyroid nodules. Thyroid nodules with fibrosis demonstrated sonographic features of "taller than wide" (p < 0.05), while lesions with follicular epithelial hyperplasia were likely to be detected with irregular and/or lobulated margins and very hypoechoic on US (p < 0.05 for both). CONCLUSION: Benign thyroid nodules with histopathological findings such as fibrosis are associated with suspicious US features, which may give inappropriately higher TIRADS stratification.

Low-Intensity Pulsed Ultrasound Counteracts Advanced Glycation End Products-Induced Corpus Cavernosal Endothelial Cell Dysfunction via Activating Mitophagy.

Injury to corpus cavernosal endothelial cells (CCECs) is an important pathological basis of diabetes mellitus-induced erectile dysfunction (DMED), while low-intensity pulsed ultrasound (LIPUS) has been shown to improve erectile function in DMED. To further understand its therapeutic mechanism of action, in this study, we first demonstrated increased apoptosis and shedding in the CCECs of DMED patients, accompanied by significant mitochondrial injury by immunohistochemistry and electron microscopy of corpus cavernosum tissue. Next, we used advanced glycation end products (AGEs) to simulate the diabetic environment in vitro and found that AGES damaged mitochondria and inhibited angiogenesis in CCECs in a dose-dependent manner, while LIPUS treatment significantly reversed its effects. Mechanistic studies based on transcriptome sequencing showed that LIPUS significantly up-regulated LC3 and PARKIN protein levels in mitochondria, promoted mitophagy, and affected mitochondrial dynamics and reactive oxygen species (ROS) production. In addition, the protective effects of LIPUS were abrogated when mitophagy was inhibited by 3-methyladenine. In summary, LIPUS exerted potent inhibitory effects on AGES-induced CCEC failure via mitophagy, providing a theoretical basis for DMED treatment that encompasses the protection of endothelial structure and function.

A Positron Emission Tomography Tracer Targeting the S2 Subunit of SARS-CoV-2 in Extrapulmonary Infections.

Tracking the pathogen of coronavirus disease 2019 (COVID-19) in live subjects may help estimate the spatiotemporal distribution of SARS-CoV-2 infection in vivo. This study developed a positron emission tomography (PET) tracer of the S2 subunit of spike (S) protein for imaging SARS-CoV-2. A pan-coronavirus inhibitor, EK1 peptide, was synthesized and radiolabeled with copper-64 after being conjugated with 1,4,7-triazacyclononane-1,4,7-triyl-triacetic acid (NOTA). The in vitro stability tests indicated that [64Cu]Cu-NOTA-EK1 was stable up to 24 h both in saline and in human serum. The binding assay showed that [64Cu]Cu-NOTA-EK1 has a nanomolar affinity (Ki = 3.94 ± 0.51 nM) with the S-protein of SARS-CoV-2. The cell uptake evaluation used HEK293T/S+ and HEK293T/S- cell lines that showed that the tracer has a high affinity with the S-protein on the cellular level. For the in vivo study, we tested [64Cu]Cu-NOTA-EK1 in HEK293T/S+ cell xenograft-bearing mice (n = 3) and pseudovirus of SARS-CoV-2-infected HEK293T/ACE2 cell bearing mice (n = 3). The best radioactive xenograft-to-muscle ratio (X/Nxenograft 8.04 ± 0.99, X/Npseudovirus 6.47 ± 0.71) was most evident 4 h postinjection. Finally, PET imaging in the surrogate mouse model of beta-coronavirus, mouse hepatic virus-A59 infection in C57BL/6 J mice showed significantly enhanced accumulation in the liver than in the uninfected mice (1.626 ± 0.136 vs 0.871 ± 0.086 %ID/g, n = 3, P < 0.05) at 4 h postinjection. In conclusion, our experimental results demonstrate that [64Cu]Cu-NOTA-EK1 is a potential molecular imaging probe for tracking SARS-CoV-2 in extrapulmonary infections in living subjects.

Increased thromboxane/prostaglandin receptors contribute to high glucose-induced podocyte injury and mitochondrial fission through ROCK1-Drp1 signaling.

Excessive mitochondrial fission in podocytes serves as a central hub for the pathogenesis of diabetic nephropathy (DN), and the thromboxane/prostaglandin receptor (TP receptor) plays a potential role in DN. However, regulation of the TP receptor during mitochondrial dynamics disorder in podocytes remains unknown. Here, we firstly reported novel mechanistic details of TP receptor effects on mitochondrial dynamics in podocytes under diabetic conditions. Expression of the TP receptor was significantly upregulated in podocytes under diabetic conditions both in vivo and in vitro. S18886 attenuated podocyte mitochondrial fission, glomerular injury and renal dysfunction in diabetic mice. Furthermore, inhibition of the TP receptor by both genetic and pharmacological methods dramatically reduced mitochondrial fission and attenuated podocyte injury induced by high glucose through regulating dynamin-related protein 1 (Drp1) phosphorylation and its subsequent translocation to mitochondria. In contrast, TP receptor overexpression and application of TP receptor agonist U46619 in these podocytes showed the opposite effect on mitochondrial fission and podocyte injury. Furthermore, treatment with Y27632, an inhibitor of Rho-associated kinase1 (ROCK1), significantly blunted more fragmented mitochondria and reduced podocyte injuries in podocytes with TP receptor overexpression or after U46619 treatment. Finally, pharmacological inhibition of Drp1 alleviated excessive mitochondrial fragmentation and podocyte damage in TP receptor overexpressing podocytes. Our data suggests that increased expression of the TP receptor can occur in a human cultured podocyte cell line and in podocytes derived from streptozotocin (STZ)-induced diabetic mice, which contributes to mitochondrial excessive fission and podocyte injury via ROCK1-Drp1 signaling.

Nanodrugs Incorporating LDHA siRNA Inhibit M2-like Polarization of TAMs and Amplify Autophagy to Assist Oxaliplatin Chemotherapy against Colorectal Cancer.

Oxaliplatin (OXA) is a first-line chemotherapeutic agent for treating colorectal cancer (CC). However, the chemotherapeutic effect of OXA on CC is limited by the M2-like polarization of tumor-associated macrophages (TAMs) in the tumor microenvironment (TME) and protective autophagy of tumor cells. Here, a cationic polymer APEG-PAsp(PEI) (PAPEI) was prepared to deliver small-interfering RNA (siRNA) to silence the lactate dehydrogenase A (LDHA) gene (LDHA-siRNA) to enhance the chemotherapeutic effect of OXA on CC. The PAPEI/LDHA-siRNA nanocomplex effectively silenced the LDHA gene to inhibit the secretion of lactic acid from tumor cells, resulting in inhibition of the M2-like polarization of TAMs. In addition, the nanocomplex also amplified OXA-induced autophagy and transformed protective autophagy into autophagic death. Consequently, the combination treatment of OXA and PAPEI/LDHA-siRNA showed a dramatically increased chemotherapeutic effect on CC compared with the OXA-alone treatment, which also suggested its attractive potential for treating CC-like immune "cold" tumors.