Molecular imprinting-based Ru@SiO2-embedded covalent organic frameworks composite for electrochemiluminescence detection of cyanidin-3-O-glucoside

Cyanidin-3-O-glucoside (C3G), a natural antioxidant, plays multiple physiological or pathological roles in maintaining human health; thereby, designing advanced sensors to achieve specific recognition and high-sensitivity detection of C3G is significant. Herein, an imprinted-type electrochemiluminescence (ECL) sensing platform was developed using core-shell Ru@SiO2-CMIPs, which were prepared by covalent organic framework (COF)-based molecularly imprinted polymers (CMIPs) embedded in luminescent Ru@SiO2 cores. The C3G-imprinted COF shell not only helps generate a steady-enhanced ECL signal, but also enables specific recognition of C3G. When C3G is bound to Ru@SiO2-CMIPs with abundant imprinted cavities, resonance energy transfer (RET) behavior is triggered, resulting in a quenched ECL response. The constructed Ru@SiO2-CMIPs nanoprobes exhibit ultra-high sensitivity, absolute specificity, and an ultra-low detection limit (0.15 pg mL-1) for analyzing C3G in food matrices. This study provides a means to construct an efficient and reliable molecular imprinting-based ECL sensor for food analysis.

Diagnostic Performance of Deep Learning in Video-Based Ultrasonography for Breast Cancer: A Retrospective Multicentre Study

OBJECTIVE

Although ultrasound is a common tool for breast cancer screening, its accuracy is often operator-dependent. In this study, we proposed a new automated deep-learning framework that extracts video-based ultrasound data for breast cancer screening.

METHODS

Our framework incorporates DenseNet121, MobileNet, and Xception as backbones for both video- and image-based models. We used data from 3907 patients to train and evaluate the models, which were tested using video- and image-based methods, as well as reader studies with human experts.

RESULTS

This study evaluated 3907 female patients aged 22 to 86 years. The results indicated that the MobileNet video model achieved an AUROC of 0.961 in prospective data testing, surpassing the DenseNet121 video model. In real-world data testing, it demonstrated an accuracy of 92.59%, outperforming both the DenseNet121 and Xception video models, and exceeding the 76.00% to 85.60% accuracy range of human experts. Additionally, the MobileNet video model exceeded the performance of image models and other video models across all evaluation metrics, including accuracy, sensitivity, specificity, F1 score, and AUC. Its exceptional performance, particularly suitable for resource-limited clinical settings, demonstrates its potential for clinical application in breast cancer screening.

CONCLUSIONS

The level of expertise reached by the video models was greater than that achieved by image-based models. We have developed an artificial intelligence framework based on videos that may be able to aid breast cancer diagnosis and alleviate the shortage of experienced experts.

A deep learning-based calculation system for plaque stenosis severity on common carotid artery of ultrasound images

OBJECTIVES

Assessment of plaque stenosis severity allows better management of carotid source of stroke. Our objective is to create a deep learning (DL) model to segment carotid intima-media thickness and plaque and further automatically calculate plaque stenosis severity on common carotid artery (CCA) transverse section ultrasound images.

METHODS

Three hundred and ninety images from 376 individuals were used to train (235/390, 60%), validate (39/390, 10%), and test (116/390, 30%) on a newly proposed CANet model. We also evaluated the model on an external test set of 115 individuals with 122 images acquired from another hospital. Comparative studies were conducted between our CANet model with four state-of-the-art DL models and two experienced sonographers to re-evaluate the present model's performance.

RESULTS

On the internal test set, our CANet model outperformed the four comparative models with Dice values of 95.22% versus 90.15%, 87.48%, 90.22%, and 91.56% on lumen-intima (LI) borders and 96.27% versus 91.40%, 88.94%, 91.19%, and 92.88% on media-adventitia (MA) borders. On the external test set, our model still produced excellent results with a Dice value of 92.41%. Good consistency of stenosis severity calculation was observed between CANet model and experienced sonographers, with Intraclass Correlation Coefficient (ICC) of 0.927 and 0.702, Pearson's Correlation Coefficient of 0.928 and 0.704 on internal and external test set, respectively.

CONCLUSIONS

Our CANet model achieved excellent performance in the segmentation of carotid IMT and plaques as well as automated calculation of stenosis severity.

Multi-modality deep learning model reaches high prediction accuracy in the diagnosis of ovarian cancer

We evaluated the diagnostic performance of a multimodal deep-learning (DL) model for ovarian mass differential diagnosis. This single-center retrospective study included 1,054 ultrasound (US)-detected ovarian tumors (699 benign and 355 malignant). Patients were randomly divided into training (n = 675), validation (n = 169), and testing (n = 210) sets. The model was developed using ResNet-50. Three DL-based models were proposed for benign-malignant classification of these lesions: single-modality model that only utilized US images; dual-modality model that used US images and menopausal status as inputs; and multi-modality model that integrated US images, menopausal status, and serum indicators. After 5-fold cross-validation, 210 lesions were tested. We evaluated the three models using the area under the curve (AUC), accuracy, sensitivity, and specificity. The multimodal model outperformed the single- and dual-modality models with 93.80% accuracy and 0.983 AUC. The Multimodal ResNet-50 DL model outperformed the single- and dual-modality models in identifying benign and malignant ovarian tumors.

A Video-based Automated Tracking and Analysis System of Plaque Burden in Carotid Artery Using Deep Learning: A Comparison with Senior Sonographers

BACKGROUND AND OBJECTIVE

The incidence of stroke is rising, and it is the second major cause of mortality and the third leading cause of disability around the globe. The goal of this study was to rapidly and accurately identify carotid plaques and automatically quantify plaque burden using our automated tracking and segmentation US-video system.

METHODS

We collected 88 common carotid artery transection videos (11048 frames) with a history of atherosclerosis or risk factors for atherosclerosis, which were randomly divided into training, test, and validation sets using a 6:3:1 ratio. We first trained different segmentation models to segment the carotid intima and adventitia, and calculate the maximum plaque burden automatically. Finally, we statistically analyzed the plaque burden calculated automatically by the best model and the results of manual labeling by senior sonographers.

RESULTS

Of the three Artificial Intelligence (AI) models, the Robust Video Matting (RVM) segmentation model's carotid intima and adventitia Dice Coefficients (DC) were the highest, reaching 0.93 and 0.95, respectively. Moreover, the RVM model has shown the strongest correlation coefficient (0.61±0.28) with senior sonographers, and the diagnostic effectiveness between the RVM model and experts was comparable with paired-t test and Bland-Altman analysis [P= 0.632 and ICC 0.01 (95% CI: -0.24~0.27), respectively].

CONCLUSION

Our findings have indicated that the RVM model can be used in ultrasound carotid video. The RVM model can automatically segment and quantify atherosclerotic plaque burden at the same diagnostic level as senior sonographers. The application of AI to carotid videos offers more precise and effective methods to evaluate carotid atherosclerosis in clinical practice.

Worm-Based Diagnosis Combining Microfluidics toward Early Cancer Screening

Early cancer diagnosis increases therapy efficiency and saves huge medical costs. Traditional blood-based cancer markers and endoscopy procedures demonstrate limited capability in the diagnosis. Reliable, non-invasive, and cost-effective methods are in high demand across the world. Worm-based diagnosis, utilizing the chemosensory neuronal system of C. elegans, emerges as a non-invasive approach for early cancer diagnosis with high sensitivity. It facilitates effectiveness in large-scale cancer screening for the foreseeable future. Here, we review the progress of a unique route of early cancer diagnosis based on the chemosensory neuronal system of C. elegans. We first introduce the basic procedures of the chemotaxis assay of C. elegans: synchronization, behavior assay, immobilization, and counting. Then, we review the progress of each procedure and the various cancer types for which this method has achieved early diagnosis. For each procedure, we list examples of microfluidics technologies that have improved the automation, throughput, and efficiency of each step or module. Finally, we envision that microfluidics technologies combined with the chemotaxis assay of C. elegans can lead to an automated, cost-effective, non-invasive early cancer screening technology, with the development of more mature microfluidic modules as well as systematic integration of functional modules.

An artificial intelligence model based on transrectal ultrasound images of biopsy needle tract tissues to differentiate prostate cancer

PURPOSE

We aimed to develop an artificial intelligence (AI) model based on transrectal ultrasonography (TRUS) images of biopsy needle tract (BNT) tissues for predicting prostate cancer (PCa) and to compare the PCa diagnostic performance of the radiologist model and clinical model.

METHODS

A total of 1696 2D prostate TRUS images were involved from 142 patients between July 2021 and May 2022. The ResNet50 network model was utilized to train classification models with different input methods: original image (Whole model), BNT (Needle model), and combined image [Feature Pyramid Networks (FPN) model]. The training set, validation set, and test set were randomly assigned, then randomized 5-fold cross-validation between the training set and validation set was performed. The diagnostic effectiveness of AI models and image combination was accessed by an independent testing set. Then, the optimal AI model and image combination were selected to compare the diagnostic efficacy with that of senior radiologists and the clinical model.

RESULTS

In the test set, the area under the curve, specificity, and sensitivity of the FPN model were 0.934, 0.966, and 0.829, respectively; the diagnostic efficacy was improved compared with the Whole and Needle models, with statistically significant differences (P < 0.05), and was better than that of senior radiologists (area under the curve: 0.667). The FPN model detected more PCa compared with senior physicians (82.9% vs. 55.8%), with a 61.3% decrease in the false-positive rate and a 23.2% increase in overall accuracy (0.887 vs. 0.655).

CONCLUSION

The proposed FPN model can offer a new method for prostate tissue classification, improve the diagnostic performance, and may be a helpful tool to guide prostate biopsy.

Carbon dots as multifunctional fluorescent probe for Fe3+ sensing in ubiquitous water environments and living cells as well as lysine detection via "on-off-on" mechanism

Iron and amino acids are essential nutrients for living organisms, and their deficiency or excess can cause a range of diseases. Therefore, there is considerable interest in developing sensing assays capable of detecting these nutrients with sensitivity, selectivity, and multifunctionality even in complex environments. In this report, hydrothermally synthesized blue fluorescent carbon dots (C-dots) from zinc gluconate were utilized for the detection of Fe3+ and lysine via "on-off" and "on-off-on" mechanisms, respectively. Specifically, the Fe3+ sensing assay achieved a broad linear range of 0-200 μM and a low limit of detection (LOD) of 1.9 μM. It is worth mentioning that the assay was also well adapted to natural aqueous environments (e.g., lake water), and its linear detection range could be extended to 0-1000 μM with a LOD of 3.3 μM. Furthermore, the assay was also effective for intracellular Fe3+ tracking. Most importantly, the assay could also be applied for the quantitative detection of lysine with a linear range of 0-1200 μM and LOD of 8.6 μM. Systematic mechanistic studies revealed that Fe3+ sensing was based on a static quenching process between C-dots and Fe3+, whereas a stronger complexation might have formed between Fe3+ and Lys, leading to the release of C-dots and thus the recovery of fluorescence.

Sonography-based multimodal information platform for identifying the surgical pathology of ductal carcinoma in situ

BACKGROUND

The risk of ductal carcinoma in situ (DCIS) identified by biopsy often increases during surgery. Therefore, confirming the DCIS grade preoperatively is necessary for clinical decision-making.

PURPOSE

To train a three-classification deep learning (DL) model based on ultrasound (US), combining clinical data, mammography (MG), US, and core needle biopsy (CNB) pathology to predict low-grade DCIS, intermediate-to-high-grade DCIS, and upstaged DCIS.

MATERIALS AND METHODS

Data of 733 patients with 754 DCIS cases confirmed by biopsy were retrospectively collected from May 2013 to June 2022 (N1), and other data (N2) were confirmed by biopsy as low-grade DCIS. The lesions were randomly divided into training (n=471), validation (n=142), and test (n = 141) sets to establish the DCIS-Net. Information on the DCIS-Net, clinical (age and sign), US (size, calcifications, type, breast imaging reporting and data system [BI-RADS]), MG (microcalcifications, BI-RADS), and CNB pathology (nuclear grade, architectural features, and immunohistochemistry) were collected. Logistic regression and random forest analyses were conducted to develop Multimodal DCIS-Net to calculate the specificity, sensitivity, accuracy, receiver operating characteristic curve, and area under the curve (AUC).

RESULTS

In the test set of N1, the accuracy and AUC of the multimodal DCIS-Net were 0.752-0.766 and 0.859-0.907 in the three-classification task, respectively. The accuracy and AUC for discriminating DCIS from upstaged DCIS were 0.751-0.780 and 0.829-0.861, respectively. In the test set of N2, the accuracy and AUC of discriminating low-grade DCIS from upstaged low-grade DCIS were 0.769-0.987 and 0.818-0.939, respectively. DL was ranked from one to five in the importance of features in the multimodal-DCIS-Net.

CONCLUSION

By developing the DCIS-Net and integrating it with multimodal information, diagnosing low-grade DCIS, intermediate-to high-grade DCIS, and upstaged DCIS is possible. It can also be used to distinguish DCIS from upstaged DCIS and low-grade DCIS from upstaged low-grade DCIS, which could pave the way for the DCIS clinical workflow.

High Performance Thermoelectric Power of Bi0.5Sb1.5Te3 Through Synergistic Cu2GeSe3 and Se Incorporations

Bi2Te3-based alloys are the benchmark for commercial thermoelectric (TE) materials, the widespread demand for low-grade waste heat recovery and solid-state refrigeration makes it imperative to enhance the figure-of-merits. In this study, high-performance Bi0.5Sb1.5Te3 (BST) is realized by incorporating Cu2GeSe3 and Se. Concretely, the diffusion of Cu and Ge atoms optimizes the hole concentration and raises the density-of-states effective mass (md *), compensating for the loss of "donor-like effect" exacerbated by ball milling. The subsequent Se addition further increases md *, enabling a total 28% improvement of room-temperature power factor (S2σ), reaching 43.6 µW cm-1 K-2 compared to the matrix. Simultaneously, the lattice thermal conductivity is also significantly suppressed by multiscale scattering sources represented by Cu-rich nanoparticles and dislocation arrays. The synergistic effects yield a peak ZT of 1.41 at 350 K and an average ZT of 1.23 (300-500 K) in the Bi0.5Sb1.5Te2.94Se0.06 + 0.11 wt.% Cu2GeSe3 sample. More importantly, the integrated 17-pair TE module achieves a conversion efficiency of 6.4%, 80% higher than the commercial one at ΔT = 200 K. These results validate that the facile composition optimization of the BST/Cu2GeSe3/Se is a promising strategy to improve the application of BST-based TE modules.

Developing and evaluating a chronic ischemic cardiomyopathy in swine model by rest and stress CMR

A large animal model of chronic coronary artery disease (CAD) is crucial for the understanding the underlying pathophysiological processes of chronic CAD and consequences for cardiac structure and function. The goal of this study was to develop a chronic model of CAD in a swine model and to evaluate the changes of myocardial structure, myocardial motility, and myocardial viability during coronary stenosis. A total of 30 swine (including 24 experimental animals and 6 controls) were enrolled. The chronic ischemia model was constructed by using Ameroid constrictor in experimental group. The 24 experimental animals were further divided into 4 groups (6 animals in each group) and were sacrificed at 1, 2, 3 and 4 weeks after operation for pathological examination, respectively. Cardiac magnetic resonance (CMR) was performed preoperatively and weekly postoperatively until sacrificed both in experimental and control group. CMR cine images, rest/adenosine triphosphate (ATP) stress myocardial contrast perfusion and LGE were performed and analyzed. The rest wall thickening (WT) score was calculated from rest cine images. The MPRI (myocardial perfusion reserve index) and MPR (myocardial perfusion reserve) were calculated based on rest and stress perfusion images. Pathology staining including triphenyltetrazolium chloride, HE and picrosirus red staining were performed after swine were sacrificed and collagen volume fraction (CVF) was calculated. The time to formation of ischemic, hibernating, and infarcted myocardium was recorded. In experimental group, from 1w to 4w after surgery, the rest WT score decreased gradually from 35.2 ± 2.0%, 32.0 ± 2.9% to 30.5 ± 3.0% and finally 29.06 ± 1.78%, p < 0.001. Left ventricular ejection fraction was gradually impaired after modeling (58.9 ± 12.6%, 56.3 ± 10.1%, 55.3 ± 9.0%, 53.8 ± 9.9%, respectively). And the MPR and MPRI also decreased stepwise with extent of surgery time (MPRI dropped from 2.1 ± 0.4, 2.0 ± 0.2 to 1.8 ± 0.3 and finally 1.7 ± 0.1, p = 0.004; MPR dropped from 2.3 ± 0.4, 2.1 ± 0.2 to 1.9 ± 0.4 and finally 1.8 ± 0.1, p < 0.001). Stronger associations between MPR, MPRI and CVF were paralleled lower wall thickening scores in fibrosis-affected areas. The ischemic myocardium was first appeared in the first week after surgery (involving ten segments), hibernated myocardium was first appeared in the second week after surgery (involving seventeen segments). LGE was first appeared in eight swine in the third weeks after surgery (16 segments). At 4w after surgery, average 9.6 g scar tissue was found among 6 swine. At the same time, histological analysis established the presence of fibrosis and ongoing apoptosis in the infarcted area. In conclusion, our study provided valuable insights into the pathophysiological processes of chronic CAD and its consequences for cardiac structure and function in a large animal model through combining myocardial motion and stress perfusion.

Association between left atrial myopathy and sarcomere mutation in patients with hypertrophic cardiomyopathy: insights into left atrial strain by MRI feature tracking

OBJECTIVES

Left atrial (LA) myopathy, characterized by LA enlargement and mechanical dysfunction, is associated with worse prognosis in hypertrophic cardiomyopathy (HCM) while the impact of sarcomere mutation on LA myopathy remains unclear. We aimed to assess the association between LA myopathy and sarcomere mutation and to explore the incremental utility of LA strain in mutation prediction.

METHODS

A total of 105 consecutive HCM patients (mean age 47.8 ± 11.9 years, 71% male) who underwent HCM-related gene screening and cardiac MRI were retrospectively enrolled. LA volume, ejection fraction and strain indices in reservoir, conduit, and booster-pump phases were investigated respectively.

RESULTS

Fifty mutation-positive patients showed higher LA maximal volume index (59.4 ± 28.2 vs 43.8 ± 18.1 mL/m2, p = 0.001), lower reservoir (21.3 ± 7.9 vs 26.2 ± 6.6%, p < 0.001), and booster-pump strain (12.1 ± 5.4 vs 17.1 ± 5.0%, p < 0.001) but similar conduit strain (9.2 ± 4.5 vs 9.1 ± 4.5%, p = 0.909) compared with mutation-negative patients. In multivariate logistic regression, LA booster-pump strain was associated with sarcomere mutation (odds ratio = 0.86, 95% confidence interval: 0.77-0.96, p = 0.010) independent of maximal wall thickness, late gadolinium enhancement, and LA volume. Furthermore, LA booster-pump strain showed incremental value for mutation prediction added to Mayo II score (AUC 0.798 vs 0.709, p = 0.024).

CONCLUSIONS

In HCM, mutation-positive patients suffered worse LA enlargement and worse reservoir and booster-pump functions. LA booster-pump strain was a strong factor for sarcomere mutation prediction added to Mayo II score.

CLINICAL RELEVANCE STATEMENT

The independent association between sarcomere mutation and left atrial mechanical dysfunction provide new insights into the pathogenesis of atrial myopathy and is helpful to understand the adverse prognosis regarding atrial fibrillation and stroke in mutation-positive patients.

KEY POINTS

• In patients with hypertrophic cardiomyopathy, left atrial (LA) reservoir and booster-pump function, but not conduit function, were significantly impaired in mutation-positive patients compared with mutation-negative patients. • LA booster-pump strain measured by MRI-derived feature tracking is feasible to predict sarcomere mutation with high incremental value added to Mayo II score.

Phase II clinical trial of neoadjuvant anti-PD-1 (toripalimab) combined with axitinib in resectable mucosal melanoma

BACKGROUND

The outcome of patients with resectable mucosal melanoma is poor. Toripalimab combined with axitinib has shown impressive results in metastatic mucosal melanoma with an objective response rate of 48.3% and a median progression-free survival of 7.5 months in a phase Ib trial. It was hypothesized that this combination administered in the neoadjuvant setting might induce a pathologic response in resectable mucosal melanoma, so we conducted this trial.

PATIENTS AND METHODS

This single-arm phase II trial enrolled patients with resectable mucosal melanoma. Patients received toripalimab 3 mg/kg once every 2 weeks (Q2W) plus axitinib 5 mg two times a day (b.i.d.) for 8 weeks as neoadjuvant therapy, then surgery and adjuvant toripalimab 3 mg/kg Q2W starting 2 ± 1weeks after surgery for 44 weeks. The primary endpoint was the pathologic response rate according to the International Neoadjuvant Melanoma Consortium recommendations.

RESULTS

Between August 2019 and October 2021, 29 patients were enrolled and received treatment, of whom 24 underwent resection. The median follow-up time was 34.2 months (95% confidence interval 20.4-48.0 months). The pathologic response rate was 33.3% (8/24; 4 pathological complete responses and 4 pathological partial responses). The median event-free survival for all patients was 11.1 months (95% confidence interval 5.3-16.9 months). The median overall survival was not reached. Neoadjuvant therapy was tolerable with 8 (27.5%) grade 3-4 treatment-related adverse events and no treatment-related deaths. Tissue samples of 17 patients at baseline and after surgery were collected (5 responders and 12 nonresponders). Multiplex immunohistochemistry demonstrated a significant increase in CD3+ (P = 0.0032) and CD3+CD8+ (P = 0.0038) tumor-infiltrating lymphocytes after neoadjuvant therapy, particularly in pathological responders.

CONCLUSIONS

Neoadjuvant toripalimab combined with axitinib in resectable mucosal melanoma demonstrated a promising pathologic response rate with significantly increased infiltrating CD3+ and CD3+CD8+ T cells after therapy.

Application of ensemble learning for predicting GABAA receptor agonists

BACKGROUND

Over the past few decades, agonists binding to the benzodiazepine site of the GABAA receptor have been successfully developed as clinical drugs. Different modulators (agonist, antagonist, and reverse agonist) bound to benzodiazepine sites exhibit different or even opposite pharmacological effects, however, their structures are so similar that it is difficult to distinguish them based solely on molecular skeleton. This study aims to develop classification models for predicting the agonists.

METHODS

306 agonists or non-agonists were collected from literature. Six machine learning algorithms including RF, XGBoost, AdaBoost, GBoost, SVM, and ANN algorithms were employed for model development. Using six descriptors including 1D/2D Descriptors, ECFP4, 2D-Pharmacophore, MACCS, PubChem, and Estate fingerprint to characterize chemical structures. The model interpretability was explored by SHAP method.

RESULTS

The best model demonstrated an AUC value of 0.905 and an MCC value of 0.808 for the test set. The PubMac-based model (PubMac-GB) achieved best AUC values of 0.935 for test set. The SHAP analysis results emphasized that MaccsFP62, ECFP_624, ECFP_724, and PubchemFP213 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. The PubMac-GB model was applied to virtual screening for potential GABAA agonists and the top 100 compounds were given.

CONCLUSION

Overall, our ensemble learning-based model (PubMac-GB) achieved comparable performance and would be helpful in effectively identifying agonists of GABAA receptors.

Didymin protects pancreatic beta cells by enhancing mitochondrial function in high-fat diet-induced impaired glucose tolerance

PURPOSE

Prolonged exposure to plasma free fatty acids (FFAs) leads to impaired glucose tolerance (IGT) which can progress to type 2 diabetes (T2D) in the absence of timely and effective interventions. High-fat diet (HFD) leads to chronic inflammation and oxidative stress, impairing pancreatic beta cell (PBC) function. While Didymin, a flavonoid glycoside derived from citrus fruits, has beneficial effects on inflammation dysfunction, its specific role in HFD-induced IGT remains yet to be elucidated. Hence, this study aims to investigate the protective effects of Didymin on PBCs.

METHODS

HFD-induced IGT mice and INS-1 cells were used to explore the effect and mechanism of Didymin in alleviating IGT. Serum glucose and insulin levels were measured during the glucose tolerance and insulin tolerance tests to evaluate PBC function and insulin resistance. Next, RNA-seq analysis was performed to identify the pathways potentially influenced by Didymin in PBCs. Furthermore, we validated the effects of Didymin both in vitro and in vivo. Mitochondrial electron transport inhibitor (Rotenone) was used to further confirm that Didymin exerts its ameliorative effect by enhancing mitochondria function.

RESULTS

Didymin reduces postprandial glycemia and enhances 30-minute postprandial insulin levels in IGT mice. Moreover, Didymin was found to enhance mitochondria biogenesis and function, regulate insulin secretion, and alleviate inflammation and apoptosis. However, these effects were abrogated with the treatment of Rotenone, indicating that Didymin exerts its ameliorative effect by enhancing mitochondria function.

CONCLUSIONS

Didymin exhibits therapeutic potential in the treatment of HFD-induced IGT. This beneficial effect is attributed to the amelioration of PBC dysfunction through improved mitochondrial function.

A validation of an entropy-based artificial intelligence for ultrasound data in breast tumors

BACKGROUND

The application of artificial intelligence (AI) in the ultrasound (US) diagnosis of breast cancer (BCa) is increasingly prevalent. However, the impact of US-probe frequencies on the diagnostic efficacy of AI models has not been clearly established.

OBJECTIVES

To explore the impact of using US-video of variable frequencies on the diagnostic efficacy of AI in breast US screening.

METHODS

This study utilized different frequency US-probes (L14: frequency range: 3.0-14.0 MHz, central frequency 9 MHz, L9: frequency range: 2.5-9.0 MHz, central frequency 6.5 MHz and L13: frequency range: 3.6-13.5 MHz, central frequency 8 MHz, L7: frequency range: 3-7 MHz, central frequency 4.0 MHz, linear arrays) to collect breast-video and applied an entropy-based deep learning approach for evaluation. We analyzed the average two-dimensional image entropy (2-DIE) of these videos and the performance of AI models in processing videos from these different frequencies to assess how probe frequency affects AI diagnostic performance.

RESULTS

The study found that in testing set 1, L9 was higher than L14 in average 2-DIE; in testing set 2, L13 was higher in average 2-DIE than L7. The diagnostic efficacy of US-data, utilized in AI model analysis, varied across different frequencies (AUC: L9 > L14: 0.849 vs. 0.784; L13 > L7: 0.920 vs. 0.887).

CONCLUSION

This study indicate that US-data acquired using probes with varying frequencies exhibit diverse average 2-DIE values, and datasets characterized by higher average 2-DIE demonstrate enhanced diagnostic outcomes in AI-driven BCa diagnosis. Unlike other studies, our research emphasizes the importance of US-probe frequency selection on AI model diagnostic performance, rather than focusing solely on the AI algorithms themselves. These insights offer a new perspective for early BCa screening and diagnosis and are of significant for future choices of US equipment and optimization of AI algorithms.

Adenosine Triphosphate Stress Myocardial Strain in Ischemic Heart Disease: An Animal Study with Histological Validation

RATIONALE AND OBJECTIVES

It is still challenging for cardiac magnetic resonance (CMR) to detect ischemic heart disease (IHD) without the use of gadolinium contrast. We aimed to evaluate the potential value of adenosine triphosphate (ATP) stress myocardial strain derived from feature tracking (FT) as a novel method for detecting IHD in a swine model.

MATERIALS AND METHODS

CMR cines, myocardial perfusion imaging at rest and during ATP stress, and late gadolinium enhancement were obtained in both control and IHD swine. Normal, remote, ischemic, and infarcted myocardium were analyzed. The diagnostic accuracy of myocardial strain for infarction and ischemia was assessed using coronary angiography and pathology as reference.

RESULTS

Eleven IHD swine and five healthy control swine were enrolled in this study. Strain parameters, even at rest, were associated with myocardial ischemia and infarction(all p < 0.05). The area under receiver operating characteristic curve (AUC) values of all strain parameters for detecting infarcted myocardium exceeded 0.900 (all p < 0.05). The AUC values for detecting ischemic myocardium were as follows: 0.906 and 0.847 for stress and rest radial strain, 0.763 and 0.716 for stress and rest circumferential strain, 0.758 and 0.663 for stress and rest longitudinal strain (all p < 0.001). Heat maps demonstrated that all strain parameters showed mild to moderate correlations with the stress myocardial blood flow and myocardial perfusion reserve (all p < 0.05).

CONCLUSION

CMR-FT-derived ATP stress myocardial strain shows promise as a noninvasive method for detecting myocardial ischemia and infarction in an IHD swine model, with rest strain parameters offering potential as a needle-free diagnostic option.

Single-cell sequencing reveals SATB2/NOTCH1 signaling promotes the progression of malignancy of epithelial cells from papillary thyroid cancer

Although most papillary thyroid cancers (PTCs) are deemed to have a favorable clinical course and outcome, some develop an aggressive biological behavior at diagnosis or during treatment. Single-cell RNA sequencing (scRNA-seq), which is based on quantifying the features of individual cells to resolve tumor tissue heterogeneity, was used to uncover gene regulatory relationships and trace the transcriptional trajectories underlying the malignant transformation. In this study, we performed single-cell sequencing on samples from four PTC patients and one benign thyroid tumor patient. These included two papillary thyroid microcarcinoma cancers (PTMC) patients, two age-matched advanced PTC patients with invading surrounding tissues, and one patient undergoing surgical treatment due to a benign thyroid tumor. We constructed a new PTC RNA spectrum using single-cell sequencing. Single-cell sequencing analysis indicated that there was a highly invasive subgroup in the PTC epithelial cells, the expression of SATB2 (special AT-rich binding protein-2) was related to the prognosis and clinical progress of PTC, and SATB2 could promote the proliferation, migration, and invasion of PTC cells. We found that NOTCH1 was the key target gene of SATB2, and the activation of the SATB2/NOTCH1 pathway was one of the reasons for the high carcinogenicity of this subgroup.

Didymin alleviates metabolic dysfunction-associated fatty liver disease (MAFLD) via the stimulation of Sirt1-mediated lipophagy and mitochondrial biogenesis

BACKGROUND

Metabolic dysfunction-associated fatty liver disease (MAFLD) is one of the most prevalent metabolic syndromes worldwide. However, no approved pharmacological treatments are available for MAFLD. Chenpi, one kind of dried peel of citrus fruits, has traditionally been utilized as a medicinal herb for liver diseases. Didymin is a newly identified oral bioactive dietary flavonoid glycoside derived from Chenpi. In this study, we investigated the therapeutic potential of Didymin as an anti-MAFLD drug and elucidated its underlying mechanisms.

METHODS

High-fat diet (HFD)-induced MAFLD mice and alpha mouse liver 12 (AML12) cells were utilized to evaluate the effects and mechanisms of Didymin in the treatment of MAFLD. Liver weight, serum biochemical parameters, and liver morphology were examined to demonstrate the therapeutic efficacy of Didymin in MAFLD treatment. RNA-seq analysis was performed to identify potential pathways that could be affected by Didymin. The impact of Didymin on Sirt1 was corroborated through western blot, molecular docking analysis, microscale thermophoresis (MST), and deacetylase activity assay. Then, a Sirt1 inhibitor (EX-527) was utilized to confirm that Didymin alleviates MAFLD via Sirt1. Western blot and additional assays were used to investigate the underlying mechanisms.

RESULTS

Our results suggested that Didymin may possess therapeutic potential against MAFLD in vitro and in vivo. By promoting Sirt1 expression as well as directly binding to and activating Sirt1, Didymin triggers downstream pathways that enhance mitochondrial biogenesis and function while reducing apoptosis and enhancing lipophagy.

CONCLUSIONS

These suggest that Didymin could be a promising medication for MAFLD treatment. Furthermore, its therapeutic effects are mediated by Sirt1.

Assessment of late gadolinium enhancement in hypertrophic cardiomyopathy improves risk stratification based on current guidelines

BACKGROUND AND AIMS

Identifying patients with hypertrophic cardiomyopathy (HCM) who are candidates for implantable cardioverter defibrillator (ICD) implantation in primary prevention for sudden cardiac death (SCD) is crucial. The aim of this study was to externally validate the 2022 European Society of Cardiology (ESC) model and other guideline-based ICD class of recommendation (ICD-COR) models and explore the utility of late gadolinium enhancement (LGE) in further risk stratification.

METHODS

Seven hundred and seventy-four consecutive patients who underwent cardiac magnetic resonance imaging were retrospectively enrolled.

RESULTS

Forty-six (5.9%) patients reached the SCD-related endpoint during 7.4 ± 2.5 years of follow-up. Patients suffering from SCD had higher ESC Risk-SCD score (4.3 ± 2.4% vs. 2.8 ± 2.1%, P < .001) and LGE extent (13.7 ± 9.4% vs. 4.9 ± 6.6%, P < .001). Compared with the 2014 ESC model, the 2022 ESC model showed increased area under the curve (.76 vs. .63), sensitivity (76.1% vs. 43.5%), positive predictive value (16.8% vs. 13.6%), and negative predictive value (98.1% vs. 95.9%). The C-statistics for SCD prediction of 2011 American College of Cardiology (ACC)/American Heart Association (AHA), 2014 ESC, 2020 AHA/ACC, and 2022 ESC models were .68, .64, .76 and .78, respectively. Furthermore, in patients without extensive LGE, LGE ≥5% was responsible for seven-fold SCD risk after multivariable adjustment. Whether in ICD-COR II or ICD-COR III, patients with LGE ≥5% and <15% showed significantly worse prognosis than those with LGE <5% (all P < .001).

CONCLUSIONS

The 2022 ESC model performed better than the 2014 ESC model with especially improved sensitivity. LGE enabled further risk stratification based on current guidelines.

Naringenin improves muscle endurance via activation of the Sp1-ERRγ transcriptional axis

Skeletal muscle function declines in the aging process or disease; however, until now, skeletal muscle has remained one of the organs most undertreated with medication. In this study, naringenin (NAR) was found to build muscle endurance in wild-type mice of different ages by increasing oxidative myofiber numbers and aerobic metabolism, and it ameliorates muscle dysfunction in mdx mice. The transcription factor Sp1 was identified as a direct target of NAR and was shown to mediate the function of NAR on muscle. Moreover, the binding site of NAR on Sp1 was further validated as GLN-110. NAR enhances the binding of Sp1 to the CCCTGCCCTC sequence of the Esrrg promoter by promoting Sp1 phosphorylation, thus upregulating Esrrg expression. The identification of the Sp1-ERRγ transcriptional axis is of great significance in basic muscle research, and this function of NAR has potential implications for the improvement of muscle function and the prevention of muscle atrophy.

Effect of GO content on microstructure and mechanical properties of Ti6Al4V coating reinforced artificial joint

In this study, we have innovatively proposed a method of in-situ synthesized TiC hard phase to improve the surface mechanical properties of artificial joint materials (Ti6Al4V). In order to explore the optimum graphene oxide (GO) addition, GO/Ti6Al4V composite powders with different proportions (0, 0.5, 1.0, and 1.5 wt.%) were prepared. The homogeneously dispersed GO/Ti6Al4V composite powder was prepared on Ti6Al4V substrate by laser cladding technology. The microstructure, phase composition, and mechanical behavior of GO/Ti6Al4V composite coatings were studied by scanning electron microscope (SEM), optical microscope (OM), energy dispersive spectrometer (EDS), tribometer, hardness tester, and surface profiler. The results showed that the addition of GO could significantly improve the mechanical properties of TC4 substrate. During the preparation of the coating, the grain size of in-situ TiC phase was nanoscale and was distributed between acicular martensite, which played a critical role in enhancing the mechanical properties of the coating. The TiC phase distributed between acicular martensite refine the grain size of α ' phase and improve the cutting resistance of the coating. Nevertheless, excessive GO decreased the fluidity of the molten pool, and micro holes tended to generate in the coating, which had a negative impact on the mechanical properties of the coating. At the GO content of 0.5 wt.%, the microhardness of the GO/Ti6Al4V coating was 1.325 times that of pure Ti6Al4V. Under the friction environment of simulated body fluid solution, the average friction coefficient was approximately 0.307 and the wear rate decreased to 3.5 × 10-7 mm3/N · m.

Cardiac MRI-derived Myocardial Fibrosis and Ventricular Dyssynchrony Predict Response to Cardiac Resynchronization Therapy in Patients with Nonischemic Dilated Cardiomyopathy

Purpose

To determine the association of myocardial fibrosis and left ventricular (LV) dyssynchrony measured using cardiac MRI with late gadolinium enhancement (LGE) and feature tracking (FT), respectively, with response to cardiac resynchronization therapy (CRT) for nonischemic dilated cardiomyopathy (DCM).

Materials and Methods

This retrospective study included 98 patients (mean age, 59 years ± 10 [SD]; 54 men) who had nonischemic DCM, as assessed with LGE cardiac MRI before CRT. Cardiac MRI FT-derived dyssynchrony was defined as the SD of the time-to-peak strain (TTP-SD) of the LV segments in three directions (longitudinal, radial, and circumferential). CRT response was defined as a 15% increase in LV ejection fraction (LVEF) at echocardiography at 6-month follow-up, and then, long-term cardiovascular events were assessed. The likelihood ratio test was used to evaluate the incremental prognostic value of LGE and dyssynchrony parameters.

Results

Seventy-one (72%) patients showed a favorable LVEF response following CRT. LGE presence (odds ratio: 0.14 [95% CI: 0.04, 0.47], P = .002; and hazard ratio: 3.52 [95% CI: 1.37, 9.07], P = .01) and lower circumferential TTP-SD (odds ratio: 1.04 [95% CI: 1.02, 1.07], P = .002; and hazard ratio: 0.98 [95% CI: 0.96, 1.00], P = .03) were independently associated with LVEF nonresponse and long-term outcomes. Combined LGE and circumferential TTP-SD provided the highest discrimination for LVEF nonresponse (area under the receiver operating characteristic curve [AUC]: 0.89 [95% CI: 0.81, 0.94], sensitivity: 84.5% [95% CI: 74.0%, 92.0%], specificity: 85.2% [95% CI: 66.3%, 95.8%]) and long-term outcomes (AUC: 0.84 [95% CI: 0.75, 0.91], sensitivity: 76.9% [95% CI: 56.4%, 91.0%], specificity: 87.0% [95% CI: 76.7%, 93.9%]).

Conclusion

Myocardial fibrosis and lower circumferential dyssynchrony assessed with pretherapy cardiac MRI were independently associated with unfavorable LVEF response and long-term events following CRT in patients with nonischemic DCM and may provide incremental value in predicting prognosis.Keywords: MR Imaging, Cardiac, Outcomes Analysis Supplemental material is available for this article. © RSNA, 2023.

Heterologous Isomorphic Substitution Induces Optical Property Enhancement for Deep-UV Crystals: a Case in Rb[B3O3F2(OH)2]

Optical anisotropy is pivotal for optical crystals, and it can be characterized by the maximum algebraic difference in refractive indices. Improving the optical anisotropy, especially for deep-ultraviolet (UV) crystals, is still a challenge and of interest. Herein, a new hydroxyfluorooxoborate, Rb[B3O3F2(OH)2], was obtained by the heterologous isomorphic substitution strategy. Dual enhancement for the band gap and birefringence compared with the parent A[B3O3F2(OH)2] (A = [Ph4P]/[Ph3MeP]) compounds was achieved in Rb[B3O3F2(OH)2]. This considerable enhancement originates from the removal of organic components and the retention of a birefringence-active anionic framework. This enhancement pushes the application region from UV to deep-UV. This discovery not only expands the structural chemistry of borates but also demonstrates the viability of heterologous isomorphic substitution to design deep-UV crystals with enhanced optical property.

Artificial intelligence for non-mass breast lesions detection and classification on ultrasound images: a comparative study

BACKGROUND

This retrospective study aims to validate the effectiveness of artificial intelligence (AI) to detect and classify non-mass breast lesions (NMLs) on ultrasound (US) images.

METHODS

A total of 228 patients with NMLs and 596 volunteers without breast lesions on US images were enrolled in the study from January 2020 to December 2022. The pathological results served as the gold standard for NMLs. Two AI models were developed to accurately detect and classify NMLs on US images, including DenseNet121_448 and MobileNet_448. To evaluate and compare the diagnostic performance of AI models, the area under the curve (AUC), accuracy, specificity and sensitivity was employed.

RESULTS

A total of 228 NMLs patients confirmed by postoperative pathology with 870 US images and 596 volunteers with 1003 US images were enrolled. In the detection experiment, the MobileNet_448 achieved the good performance in the testing set, with the AUC, accuracy, sensitivity, and specificity were 0.999 (95%CI: 0.997-1.000),96.5%,96.9% and 96.1%, respectively. It was no statistically significant compared to DenseNet121_448. In the classification experiment, the MobileNet_448 model achieved the highest diagnostic performance in the testing set, with the AUC, accuracy, sensitivity, and specificity were 0.837 (95%CI: 0.990-1.000), 70.5%, 80.3% and 74.6%, respectively.

CONCLUSIONS

This study suggests that the AI models, particularly MobileNet_448, can effectively detect and classify NMLs in US images. This technique has the potential to improve early diagnostic accuracy for NMLs.

The effect of image resolution on convolutional neural networks in breast ultrasound

Purpose

The objective of this research was to investigate the efficacy of various parameter combinations of Convolutional Neural Networks (CNNs) models, namely MobileNet and DenseNet121, and different input image resolutions (REZs) ranging from 64×64 to 512×512 pixels, for diagnosing breast cancer.

Materials and methods

During the period of June 2015 to November 2020, two hospitals were involved in the collection of two-dimensional ultrasound breast images for this retrospective multicenter study. The diagnostic performance of the computer models MobileNet and DenseNet 121 was compared at different resolutions.

Results

The results showed that MobileNet had the best breast cancer diagnosis performance at 320×320pixel REZ and DenseNet121 had the best breast cancer diagnosis performance at 448×448pixel REZ.

Conclusion

Our study reveals a significant correlation between image resolution and breast cancer diagnosis accuracy. Through the comparison of MobileNet and DenseNet121, it is highlighted that lightweight neural networks (LW-CNNs) can achieve model performance similar to or even slightly better than large neural networks models (HW-CNNs) in ultrasound images, and LW-CNNs' prediction time per image is lower.

Signal-amplified electrochemiluminescence aptasensor for mucin 1 determination using CdS QDs/g-C3N4 and Au NPs@TEOA

A novel electrochemiluminescence (ECL) aptasensor, using graphite carbonitride (g-C₃N₄) capped CdS quantum dots (CdS QDs@g-C₃N₄) and Au nanoparticles decorated triethanolamine (AuNPs@TEOA) as dual coreactants, was proposed for the determination of mucin 1 (MUC1). Higher ECL efficiency was acquired due to the double enhancement contribution of CdS QDs and TEOA to Ru (bpy)₃²⁺ ECL. Additionally, AuNPs@TEOA also acted as nanocarrier for MUC1 aptamer immobilization. After the aptasensor was incubated in target MUC1, the decreased ECL emission was obtained because of the poor conductivity of MUC1. The ECL aptasensor displayed a good linear correlation for MUC1 in the range 0.1 pg mL^-1 -1000 ng mL^-1, and the detection limit was 33 fg mL^-1. MUC1 spiked into human serum samples was quantified to assess the practicability of the ECL aptasensor.

Generation of Hypoparathyroid Rats via Carbon-Nanoparticle-Assisted Parathyroidectomy

Hypoparathyroidism (HypoPT) is a rare disease involving the parathyroid glands that is characterized by a reduced secretion or potency of the parathyroid hormone (PTH), which leads to high serum phosphorus levels and low serum calcium levels. HypoPT most commonly results from accidental damage to the glands or their removal during thyroid or other anterior neck surgery. Parathyroid/thyroid surgery has become more common in recent years, with a corresponding rise in the occurrence of HypoPT as a postoperative complication. There is a critical need for a HypoPT animal model to better understand the mechanisms underlying the effects of HypoPT on mineral ion homeostasis and to verify the therapeutic effectiveness of novel treatments. Here, a technique is reported to create acquired HypoPT in male rats by performing parathyroidectomy (PTX) using carbon nanoparticles. The rat model shows great promise over the mouse models of hypoparathyroidism. Importantly, the human PTH receptor binding region has an 84.2% sequence similarity with that of the rat, which is higher than the 73.7% similarity shared with mice. Moreover, the effects of estrogen, which can affect the PTH/PTHrP receptor signaling pathway, have not been fully investigated in male rats. Carbon nanoparticles are lymphatic tracers that stain the thyroid lymph nodes black without affecting their function, but they do not stain the parathyroid glands, which makes them easy to identify and remove. In this study, serum PTH levels were undetectable after PTX, and this resulted in significant hypocalcemia and hyperphosphatemia. Thus, the clinical state of postoperative HypoPT can be remarkably represented in the rat model. Carbon-nanoparticle-assisted PTX can, therefore, serve as an extraordinarily effective and readily implementable model for studying the pathogenesis, treatment, and prognosis of HypoPT.

[The value of cardiac MRI in the risk stratification in patients with hypertrophic cardiomyopathy]

Objective: To explore the value of cardiac magnetic resonance imaging (CMR) in the risk stratification of hypertrophic cardiomyopathy (HCM). Methods: HCM patients who underwent CMR examination in Fuwai Hospital between March 2012 and May 2013 were retrospectively enrolled. Baseline clinical and CMR data were collected and patient follow-up was performed using telephone contact and medical record. The primary composite endpoint was sudden cardiac death (SCD) or and equivalent event. The secondary composite endpoint was all-cause death and heart transplant. Patients were divided into SCD and non-SCD groups. Cox regression was used to explore risk factors of adverse events. Receiver operating characteristic (ROC) curve analysis was used to assess the performance and the optimal cut-off of late gadolinium enhancement percentage (LGE%) for the prediction of endpoints. Kaplan-Meier and log-rank tests were used to compare survival differences between groups. Results: A total of 442 patients were enrolled. Mean age was (48.5±12.4) years and 143(32.4%) were female. At (7.6±2.5) years of follow-up, 30 (6.8%) patients met the primary endpoint including 23 SCD and 7 SCD equivalent events, and 36 (8.1%) patients met the secondary endpoint including 33 all-cause death and 3 heart transplant. In multivariate Cox regression, syncope(HR=4.531, 95%CI 2.033-10.099, P<0.001), LGE% (HR=1.075, 95%CI 1.032-1.120, P=0.001) and left ventricular ejection fraction (LVEF) (HR=0.956, 95%CI 0.923-0.991, P=0.013) were independent risk factors for primary endpoint; Age (HR=1.032, 95%CI 1.001-1.064, P=0.046), atrial fibrillation (HR=2.977, 95%CI 1.446-6.131, P=0.003),LGE% (HR=1.075, 95%CI 1.035-1.116, P<0.001) and LVEF (HR=0.968, 95%CI 0.937-1.000, P=0.047) were independent risk factors for secondary endpoint. ROC curve showed the optimal LGE% cut-offs were 5.1% and 5.8% for the prediction of primary and secondary endpoint, respectively. Patients were further divided into LGE%=0, 0<LGE%<5%, 5%≤LGE%<15% and LGE%≥15% groups. There were significant survival differences between these 4 groups whether for primary endpoint or secondary endpoint (all P<0.001) and the accumulated incidence of primary endpoint was 1.2% (2/161), 2.2% (2/89), 10.5% (16/152) and 25.0% (10/40), respectively. Conclusion: LGE is an independent risk factor for SCD events as well as all-cause death and heart transplant. LGE is of important value in the risk stratification in patients with HCM.

Detection of Myocardial Ischemia Using Cardiovascular MRI Stress T1 Mapping: A Miniature-Swine Validation Study

Purpose

To assess the efficacy of cardiac MRI stress T1 mapping in detecting ischemic and infarcted myocardium in a miniature-swine model, using pathologic findings as the reference standard.

Materials and Methods

Ten adult male Chinese miniature swine, with coronary artery stenosis induced by an ameroid constrictor, and two healthy control swine were studied. Cardiac 3-T MRI rest and adenosine triphosphate stress T1 mapping and perfusion images, along with resting and late gadolinium enhancement images, were acquired at baseline and weekly up to 4 weeks after surgery or until humanely killed. A receiver operating characteristic analysis was used to analyze the performance of T1 mapping in the detection of myocardial ischemia.

Results

In the experimental group, both the infarcted myocardium (ΔT1 = 10 msec ± 2 [SD]; ΔT1 percentage = 0.7% ± 0.1) and ischemic myocardium (ΔT1 = 10 msec ± 2; ΔT1 percentage = 0.9% ± 0.2) exhibited reduced T1 reactivity compared with the remote myocardium (ΔT1 = 53 msec ± 7; ΔT1 percentage = 4.7% ± 0.6) and normal myocardium (ΔT1 = 56 msec ± 11; ΔT1 percentage = 4.9% ± 1.1). Receiver operating characteristic analysis demonstrated high diagnostic performance of ΔT1 in detecting ischemic myocardium, with an area under the curve (AUC) of 0.84 (P < .001). Rest T1 displayed high diagnostic performance in detecting infarcted myocardium (AUC = 0.95; P < .001). When rest T1 and ΔT1 were combined, the diagnostic performance for both ischemic and infarcted myocardium were improved (AUCs, 0.89 and 0.97, respectively; all P < .001). The collagen volume fraction correlated with ΔT1, ΔT1 percentage, and Δ extracellular volume percentage (r = -0.70, -0.70, and -0.50, respectively; P = .001, .001, and .03, respectively).

Conclusion

Using histopathologic validation in a swine model, noninvasive cardiac MRI stress T1 mapping demonstrated high performance in detecting ischemic and infarcted myocardium without the need for contrast agents.Keywords: Coronary Artery Disease, MRI, Myocardial Ischemia, Rest T1 Mapping, Stress T1 Mapping, Swine Model Supplemental material is available for this article. © RSNA, 2023See also commentary by Burrage and Ferreira in this issue.

[Repeated stellate ganglion blockade for the treatment of ventricular tachycardia storm in patients with nonischemic cardiomyopathy: a new therapeutic option for patients with malignant arrhythmias]

Objectives: This study sought to describe our institutional experience of repeated percutaneous stellate ganglion blockade (R-SGB) as a treatment option for drug-refractory electrical storm in patients with nonischemic cardiomyopathy (NICM). Methods: This prospective observational study included 8 consecutive NICM patients who had drug-refractory electrical storm and underwent R-SGB between June 1, 2021 and January 31, 2022. Lidocaine (5 ml, 1%) was injected in the vicinity of the left stellate ganglion under the guidance of ultrasound, once per day for 7 days. Data including clinical characteristics, immediate and long-term outcomes, and procedure related complications were collected. Results: The mean age was (51.5±13.6) years. All patients were male. 5 patients were diagnosed as dilated cardiomyopathy, 2 patients as arrhythmogenic right ventricular cardiomyopathy and 1 patient as hypertrophic cardiomyopathy. The left ventricular ejection fraction was 37.8%±6.6%. After the treatment of R-SGB, 6 (75%) patients were free of electrical storm. 24 hours Holter monitoring showed significant reduction in ventricular tachycardia (VT) episodes from 43.0 (13.3, 276.3) to 1.0 (0.3, 34.0) on the first day following R-SGB (P<0.05) and 0.5 (0.0, 19.3) after whole R-SGB process (P<0.05). There were no procedure-related major complications. The mean follow-up was (4.8±1.1) months, and the median time of recurrent VT was 2 months. Conclusion: Minimally invasive R-SGB is a safe and effective method to treat electrical storm in patients with NICM.

Electrochemiluminescence resonance energy transfer between Ru(bpy)32+@Cu3(HHTP)2 and GO-Au composites for C-reactive protein detection

Designing innovative electrochemiluminescence (ECL) immunosensors is critical for the detection of biomarkers with a low concentration and the precise evaluation of clinical diseases. Herein, a Cu₃(hexahydroxytriphenylene)₂ (Cu₃(HHTP)₂) nanoflake-based sandwich-type ECL immunosensor was constructed for C-Reactive Protein (CRP) detection. The Cu₃(HHTP)₂ nanoflake, an electronically conductive metal-organic framework (MOF), has a periodically arranged porous structure with a cavity size of 2 nm, which not only accommodates a large amount of Ru(bpy)₃²⁺ but also confines the spatial diffusion of active species. Therefore, the Ru(bpy)₃²⁺-loaded Cu₃(HHTP)₂ nanocomplex (Ru@CuMOF) as an ECL emitter exhibits an enhanced ECL efficiency. The ECL resonance energy transfer (ECL-RET) was accomplished by combining Ru@CuMOF used as a donor with gold nanoparticles-functionalized graphene oxide nanosheets (GO-Au) utilized as an acceptor. This should be ascribed to the fact that the ECL emission spectrum of Ru@CuMOF shows the strongest signal intensity at 615 nm, overlapping with the absorption spectrum of GO-Au at 580-680 nm. Targeted detection of CRP in human serum samples was achieved by the sandwich-type immunosensor based on the ECL-RET mechanism with a 0.26 pg mL^-1 detection limit. The electro-activated hybrids of Cu₃(HHTP)₂ and ECL emitters provide a new sensing strategy for the high-sensitivity detection of disease markers.

CIB2 Is a Novel Endogenous Repressor of Atrial Remodeling

BACKGROUND

Atrial fibrillation (AF) is a highly prevalent condition that can cause or exacerbate heart failure, is an important risk factor for stroke, and is associated with pronounced morbidity and mortality. Genes uniquely expressed in the atria are known to be essential for maintaining atrial structure and function. Atrial tissue remodeling contributes to arrhythmia recurrence and maintenance. However, the mechanism underlying atrial remodeling remains poorly understood. This study was designed to investigate whether other uncharacterized atrial specific genes play important roles in atrial physiology and arrhythmogenesis.

METHODS

RNA-sequencing analysis was used to identify atrial myocyte specific and angiotensin II-responsive genes. Genetically modified, cardiomyocyte-specific mouse models (knockout and overexpression) were generated. In vivo and in vitro electrophysiological, histology, and biochemical analyses were performed to determine the consequences of CIB2 (calcium and integrin binding family member 2 protein) gain and loss of function in the atrium.

RESULTS

Using RNA-sequencing analysis, we identified CIB2 as an atrial-enriched protein that is significantly downregulated in the left atria of patients with AF and mouse models of AF from angiotensin II infusion or pressure overload. Using cardiomyocyte-specific Cib2 knockout (Cib2^-/-) and atrial myocyte-specific Cib2-overexpressing mouse models, we found that loss of Cib2 enhances AF occurrence, prolongs AF duration, and correlates with a significant increase in atrial fibrosis under stress. Conversely, Cib2 overexpression mitigates AF occurrence and atrial fibrosis triggered by angiotensin II stress. Mechanistically, we revealed that CIB2 competes with and inhibits CIB1-mediated calcineurin activation, thereby negating stress-induced structural remodeling and AF.

CONCLUSIONS

Our data suggest that CIB2 represents a novel endogenous and atrial-enriched regulator that protects against atrial remodeling and AF under stress conditions. Therefore, CIB2 may represent a new potential target for treating AF.

Biomimetic Gradient Bouligand Structure Enhances Impact Resistance of Ceramic-Polymer Composites

Biological materials relied on multiple synergistic structural design elements typically exhibit excellent comprehensive mechanical properties. Hierarchical incorporation of different biostructural elements into a single artificial material is a promising approach to enhance mechanical properties, but remains challenging. Herein, a biomimetic structural design strategy is proposed by coupling gradient structure with twisted plywood Bouligand structure, attempting to improve the impact resistance of ceramic-polymer composites. Via robocasting and sintering, kaolin ceramic filaments reinforced by coaxially aligned alumina nanoplatelets are arranged into Bouligand structure with a gradual transition in filament spacing along the thickness direction. After the following polymer infiltration, biomimetic ceramic-polymer composites with a gradient Bouligand (GB) structure are eventually fabricated. Experimental investigations reveal that the incorporation of gradient structure into Bouligand structure improves both the peak force and total energy absorption of the obtained ceramic-polymer composites. Computational modeling further suggests the substantial improvement in impact resistance by adopting GB structure, and clarifies the underlying deformation behavior of the biomimetic GB structured composites under impact. This biomimetic design strategy may provide valuable insights for developing lightweight and impact-resistant structural materials in the future.

A new xAI framework with feature explainability for tumors decision-making in Ultrasound data: comparing with Grad-CAM

BACKGROUND AND OBJECTIVE

The value of implementing artificial intelligence (AI) on ultrasound screening for thyroid cancer has been acknowledged, with numerous early studies confirming AI might help physicians acquire more accurate diagnoses. However, the black box nature of AI's decision-making process makes it difficult for users to grasp the foundation of AI's predictions. Furthermore, explainability is not only related to AI performance, but also responsibility and risk in medical diagnosis. In this paper, we offer Explainer, an intrinsically explainable framework that can categorize images and create heatmaps highlighting the regions on which its prediction is based.

METHODS

A dataset of 19341 thyroid ultrasound images with pathological results and physician-annotated TI-RADS features is used to train and test the robustness of the proposed framework. Then we conducted a benign-malignant classification study to determine whether physicians perform better with the assistance of an explainer than they do alone or with Gradient-weighted Class Activation Mapping (Grad-CAM).

RESULTS

Reader studies show that the Explainer can achieve a more accurate diagnosis while explaining heatmaps, and that physicians' performances are improved when assisted by the Explainer. Case study results confirm that the Explainer is capable of locating more reasonable and feature-related regions than the Grad-CAM.

CONCLUSIONS

The Explainer offers physicians a tool to understand the basis of AI predictions and evaluate their reliability, which has the potential to unbox the "black box" of medical imaging AI.

Scalable Manufacturing of Mechanical Robust Bioinspired Ceramic-Resin Composites with Locally Tunable Heterogeneous Structures

Lightweight structural materials with a unique combination of high stiffness, strength, toughness, and hardness, are highly desired yet challenging to be artificially fabricated. Biological structural materials, on the other hand, ingeniously integrate multiple mutually exclusive mechanical properties together relying on their hierarchically heterogeneous structures bonded with gradient interfaces. Here, a scalable bottom-up approach combining continuous nanofiber-assisted evaporation-induced self-assembly with laminating, pressure-less sintering and resin infiltration is reported to fabricate bioinspired heterogeneous ceramic-resin composites with locally tunable microstructure to fulfill specific properties. A gradient interlayer is introduced to provide a gradual transition between adjacent heterogeneous layers, effectively alleviating their property mismatch. The optimized heterogeneous nacre-like composite, as a demonstration, exhibits an attractive combination of low density (≈2.8 g cm^-3 ), high strength (≈292 MPa), toughness (≈6.4 MPa m^1/2 ), surface hardness (≈1144 kgf mm^-2 ) and impact-resistance, surpassing the overall performance of engineering alumina. This material-independent approach paves the way for designing advanced bioinspired heterogeneous materials for diverse structural and functional applications.

Detection of haemodynamic obstruction in hypertrophic cardiomyopathy using the sub-aortic complex: a cardiac MRI and Doppler study

AIM

To investigate the "sub-aortic complex (SAC)", a new cardiac magnetic resonance imaging (CMRI)-derived parameter, for the evaluation of left ventricular (LV) outflow tract (LVOT) obstruction in patients with hypertrophic cardiomyopathy (HCM), compared with conventional CMRI parameters and Doppler echocardiography.

MATERIALS AND METHODS

A total of 157 consecutive patients with HCM were recruited retrospectively. The patients were divided into two groups, 87 with LVOT obstruction and 70 without obstruction. The SAC was defined as a specific anatomical SAC affecting the LVOT, which were measured on the LV three-chamber steady-state free precession (SSFP) cine image at the end-systolic phase. The relations between the existence and severity of obstruction and SAC index (SACi) were evaluated using Pearson's correlation coefficient, receiver operating characteristic (ROC) curves, and logistic regression.

RESULTS

The SACs were significantly different between the obstructive and non-obstructive groups. The ROC curves indicated that the SACi was able to discriminate obstructive and non-obstructive patients with the best predictive accuracy (AUC = 0.949, p<0.001). The SACi was an independent predictor of LVOT obstruction and there was a significant negative correlation between resting LVOT pressure gradient and SACi (r=0.72 p<0.001). In the subgroup of patients with or without severe basal septal hypertrophy, the SACi was still able to predict LVOT obstruction with excellent diagnostic accuracy (AUC = 0.944 and 0.948, p<0.001, respectively).

CONCLUSION

The SAC is a reliable and straightforward CMRI marker for assessing LVOT obstruction. It is more effective than CMRI two-dimensional flow in diagnosing the severity of obstruction in patients with HCM.

Controlled Desiccation of Preprinted Hydrogel Scaffolds Toward Complex 3D Microarchitectures

Additive manufacturing (AM) is the key to creating a wide variety of 3D structures with unique and programmable functionalities. Direct ink writing is one of the widely used AM technologies with numerous printable materials. However, the extrude-based method is limited by low fabrication resolution, which is confined to printing macrostructures. Herein, a new AM strategy is reported, using a low-cost extrusion 3D printer, to create 3D microarchitectures at the macroscopic level through controlled desiccation of preprinted hydrogel scaffolds followed by infilling objective components. A printable hydrogel with a high-water content ensures maximum shrinkage (≈99.5% in volume) of the printed scaffolds to achieve high resolution. Stable covalent cross-linking and a suitable drying rate enable uniform shrinkage of the scaffolds to retain their original architectures. Particularly, this method can be adapted to produce liquid-metal-based 3D circuits and nanocomposite-based microrobots, indicating its capability to fabricate functional and complex 3D architectures with micron-level resolution from different material systems.

Creating an atlas of the bone microenvironment during oral inflammatory-related bone disease using single-cell profiling

Oral inflammatory diseases such as apical periodontitis are common bacterial infectious diseases that may affect the periapical alveolar bone tissues. A protective process occurs simultaneously with the inflammatory tissue destruction, in which mesenchymal stem cells (MSCs) play a primary role. However, a systematic and precise description of the cellular and molecular composition of the microenvironment of bone affected by inflammation is lacking. In this study, we created a single-cell atlas of cell populations that compose alveolar bone in healthy and inflammatory disease states. We investigated changes in expression frequency and patterns related to apical periodontitis, as well as the interactions between MSCs and immunocytes. Our results highlight an enhanced self-supporting network and osteogenic potential within MSCs during apical periodontitis-associated inflammation. MSCs not only differentiated toward osteoblast lineage cells but also expressed higher levels of osteogenic-related markers, including Sparc and Col1a1. This was confirmed by lineage tracing in transgenic mouse models and human samples from oral inflammatory-related alveolar bone lesions. In summary, the current study provides an in-depth description of the microenvironment of MSCs and immunocytes in both healthy and disease states. We also identified key apical periodontitis-associated MSC subclusters and their biomarkers, which could further our understanding of the protective process and the underlying mechanisms of oral inflammatory-related bone disease. Taken together, these results enhance our understanding of heterogeneity and cellular interactions of alveolar bone cells under pathogenic and inflammatory conditions. We provide these data as a tool for investigators not only to better appreciate the repertoire of progenitors that are stress responsive but importantly to help design new therapeutic targets to restore bone lesions caused by apical periodontitis and other inflammatory-related bone diseases.

Mesenchymal stromal cells ameliorate diabetes-induced muscle atrophy through exosomes by enhancing AMPK/ULK1-mediated autophagy

BACKGROUND

Diabetes and obesity are associated with muscle atrophy that reduces life quality and lacks effective treatment. Mesenchymal stromal cell (MSC)-based therapy can ameliorate high fat-diet (HFD) and immobilization (IM)-induced muscle atrophy in mice. However, the effect of MSCs on muscle atrophy in type 2 diabetes mellitus (T2DM) and the potential mechanism is unclear. Here, we evaluated the efficacy and explored molecular mechanisms of human umbilical cord MSCs (hucMSCs) and hucMSC-derived exosomes (MSC-EXO) on diabetes- and obesity-induced muscle atrophy.

METHODS

Diabetic db/db mice, mice fed with high-fat diet (HFD), mice with hindlimb immobilization (IM), and C2C12 myotubes were used to explore the effect of hucMSCs or MSC-EXO in alleviating muscle atrophy. Grip strength test and treadmill running were used to measure skeletal muscle strength and performance. Body composition, muscle weight, and muscle fibre cross-sectional area (CSA) was used to evaluate muscle mass. RNA-seq analysis of tibialis anterior (TA) muscle and Western blot analysis of muscle atrophy signalling, including MuRF1 and Atrogin 1, were performed to investigate the underlying mechanisms.

RESULTS

hucMSCs increased grip strength (P = 0.0256 in db/db mice, P = 0.012 in HFD mice, P = 0.0097 in IM mice), running endurance (P = 0.0154 in HFD mice, P = 0.0006 in IM mice), and muscle mass (P = 0.0004 in db/db mice, P = 0.0076 in HFD mice, P = 0.0144 in IM mice) in all models tested, with elevated CSA of muscle fibres (P < 0.0001 in db/db mice and HFD mice, P = 0.0088 in IM mice) and reduced Atrogin1 (P = 0.0459 in db/db mice, P = 0.0088 in HFD mice, P = 0.0016 in IM mice) and MuRF1 expression (P = 0.0004 in db/db mice, P = 0.0077 in HFD mice, P = 0.0451 in IM mice). MSC-EXO replicated all these hucMSC-mediated changes (P = 0.0103 for grip strength, P = 0.013 for muscle mass, P < 0.0001 for CSA of muscle fibres, P = 0.0171 for Atrogin1 expression, and P = 0.006 for MuRF1 expression). RNA-seq revealed that hucMSCs activated the AMPK/ULK1 signalling and enhanced autophagy. Knockdown of AMPK or inhibition of autophagy with 3-methyladenine (3-MA) diminished the beneficial anti-atrophy effects of hucMSCs or MSC-EXO.

CONCLUSIONS

Our results suggest that human umbilical cord mesenchymal stromal cells mitigate diabetes- and obesity-induced muscle atrophy via enhancing AMPK/ULK1-mediated autophagy through exosomes, with implications of applying hucMSCs or hucMSC-derived exosomes to treat muscle atrophy.

Apical aneurysm formation in apical hypertrophic cardiomyopathy: Pilot study with cardiac magnetic resonance

BACKGROUND

The dynamic changes and apical aneurysm formation in apical hypertrophic cardiomyopathy (HCM) have not been specifically described. This study aimed to describe these changes to better understand the progression of apical HCM.

METHODS AND RESULTS

Seventy-two patients with apical HCM who underwent at least two cardiac magnetic resonance (CMR) examinations were retrospectively included in this study. The mean interval between the first and last CMR examinations was 50.1 ± 26.8 months (ranging from 4 to 118 months). Compared with the initial values, the left atrial diameter, maximum left ventricular wall thickness and late gadolinium enhancement extent significantly increased (all P < 0.05), while the left ventricular ejection fraction significantly decreased (P < 0.05), at the latest CMR examination. More importantly, the dynamic process of apical aneurysm formation in apical HCM was observed in a subset of patients, which may follow these four stages: starting with systolic apical cavity obliteration, then broadening of the apical slit in systole, further developing into an apical outpouching, and finally forming an apical aneurysm. Eleven patients experienced adverse cardiovascular events, including new-onset or progressive atrial fibrillation (n = 7), hospitalization with heart failure (n = 3) and implantable cardioverter defibrillator intervention (n = 1), at the time of the latest CMR examination.

CONCLUSIONS

In the progression of apical HCM, cardiac structure and function will change accordingly. Apical aneurysm formation in apical HCM is a chronic and continuous dynamic process that may follow a 4-step pathway of disease progression.

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

Background

With the increasing interest of academics in the application of artificial intelligence to sepsis, thousands of papers on this field had been published in the past few decades. It is difficult for researchers to understand the themes and latest research frontiers in this field from a multi-dimensional perspective. Consequently, the purpose of this study is to analyze the relevant literature in the application of artificial intelligence to sepsis through bibliometrics software, so as to better understand the development status, study the core hotspots and future development trends of this field.

Methods

We collected relevant publications in the application of artificial intelligence to sepsis from the Web of Science Core Collection in 2000 to 2021. The type of publication was limited to articles and reviews, and language was limited to English. Research cooperation network, journals, cited references, keywords in this field were visually analyzed by using CiteSpace, VOSviewer, and COOC software.

Results

A total of 8,481 publications in the application of artificial intelligence to sepsis between 2000 and 2021 were included, involving 8,132 articles and 349 reviews. Over the past 22 years, the annual number of publications had gradually increased exponentially. The USA was the most productive country, followed by China. Harvard University, Schuetz, Philipp, and Intensive Care Medicine were the most productive institution, author, and journal, respectively. Vincent, Jl and Critical Care Medicine were the most cited author and cited journal, respectively. Several conclusions can be drawn from the analysis of the cited references, including the following: screening and identification of sepsis biomarkers, treatment and related complications of sepsis, and precise treatment of sepsis. Moreover, there were a spike in searches relating to machine learning, antibiotic resistance and accuracy based on burst detection analysis.

Conclusion

This study conducted a comprehensive and objective analysis of the publications on the application of artificial intelligence in sepsis. It can be predicted that precise treatment of sepsis through machine learning technology is still research hotspot in this field.

The Influence of Cryogenic Treatment on the Microstructure and Mechanical Characteristics of Aluminum Silicon Carbide Matrix Composites

Aluminum matrix composites have been widely used in aerospace and automotive fields due to their excellent physical properties. Cryogenic treatment was successfully adopted to improve the performance of aluminum alloy components, while its effect and mechanism on the aluminum matrix composite remained unclear. In this work, the effects of cryogenic treatment on the microstructure evolution and mechanical properties of 15%SiCp/2009 aluminum matrix composites were systematically investigated by means of Thermoelectric Power (TEP), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The results showed that TEP measurement can be an effective method for evaluating the precipitation characteristics of 15%SiCp/2009 aluminum matrix composites during aging. The addition of cryogenic treatment after solution and before aging treatment promoted the precipitation from the beginning stage of aging. Furthermore, the aging time for the maximum precipitation of the θ″ phase was about 4 h advanced, as the conduction of cryogenic treatment accelerates the aging kinetics. This was attributed to the great difference in the linear expansion coefficient between the aluminum alloy matrix and SiC-reinforced particles, which could induce high internal stress in their boundaries for precipitation. Moreover, the lattice contraction of the aluminum alloy matrix during cryogenic treatment led to the increase in dislocation density and micro defects near the boundaries, thus providing more nucleation sites for precipitation during the aging treatment. After undergoing artificial aging treatment for 20 h, the increase in dispersive, distributed precipitates after cryogenic treatment improved the hardness and yield strength by 4% and 16 MPa, respectively.

Gender Disparities in Academic Pain Medicine: A Retrospective, Cross-Sectional Bibliometric Analysis

PURPOSE

This study was conducted to characterize the gender disparities within academic pain management departments in the United States, specifically focusing on its relation to research and academic leadership. This will allow for targeted improvements in efforts made to reduce gender gaps within academic pain medicine.

METHODS

This is a retrospective, cross-sectional analysis study evaluating pain management faculty of various positions at academic institutions across the United States. We utilized publicly available data on faculty positions and sex to analyze research impact, H-index, number of publications and citations through bibliometric and linear regression analysis.

RESULTS

Our analysis found that female faculty had significantly less research output to male faculty. The three research measurement indices used in this study including H-index, number of publications, and number of citations were significantly lower in females than in males among associate and full professor faculty ranking. Multivariable analysis did not display any significant disparities of research output at the division director and department chair level.

DISCUSSION

As in many areas of medicine, there continues to be a significant gender disparity in academic pain management departments, particularly with regard to leadership positions and research impact within the field. Our study found that female pain physicians had a significantly less research output based on the three variables of H indices, number of publications, and number of citations compared to their male counterparts. This has been shown to have the impact on discrepancies in female faculty ranking. Interestingly, these variables were not significantly different between male and female faculty members of the same level of leadership except for program director. There are various contributory reasons for these disparities, including implicit biases, lack of mentorship, and familial obligations. Addressing some of these factors can help narrow the schism and promote greater gender equality within academic pain management.

An "off-on" electrochemiluminescence aptasensor for determination of lincomycin based on CdS QDs/carboxylated g-C3N4

A novel electrochemiluminescence (ECL) aptasensor for the determination of lincomycin (LIN) was developed based on CdS QDs/carboxylated g-C₃N₄ (CdS QDs/C-g-C₃N₄). CdS QDs/C-g-C₃N₄ served as the substrate of the aptasensor, and then CdS QDs/C-g-C₃N₄-modified electrode was incubated with aptamer DNA (Apt-DNA). When the non-specific sites of the electrode surface was blocked by 6-mercaptohexanol, the ferrocene-labeled probe (Fer-DNA) was assembled onto the electrode surface through base complementation with Apt-DNA. In the absence of LIN, the ECL signal was quenched effectively by Fer-DNA and a decreased ECL emission (off state) was acquired. On the contrary, LIN was specifically bond with Apt-DNA, and Fer-DNA was detached from the aptasensor surface because of the deformation of Apt-DNA, resulting in an effectively enhanced ECL signal (on state). The constructed ECL aptasensor exhibited a wide detection range for LIN determination (0.05 ng mL^-1-100 μg mL^-1) with a low detection limit (0.02 ng mL^-1). Importantly, the proposed ECL aptasensor showed outstanding accuracy and specificity for LIN determination, and also provided a potential strategy for other antibiotic determinations.

Analysis of a machine learning-based risk stratification scheme for acute kidney injury in vancomycin

Vancomycin-associated acute kidney injury (AKI) continues to pose a major challenge to both patients and healthcare providers. The purpose of this study is to construct a machine learning framework for stratified predicting and interpreting vancomycin-associated AKI. Our study is a retrospective analysis of medical records of 724 patients who have received vancomycin therapy from 1 January 2015 through 30 September 2020. The basic clinical information, vancomycin dosage and days, comorbidities and medication, laboratory indicators of the patients were recorded. Machine learning algorithm of XGBoost was used to construct a series risk prediction model for vancomycin-associated AKI in different underlying diseases. The vast majority of sub-model performed best on the corresponding sub-dataset. Additionally, the aim of this study was to explain each model and to explore the influence of clinical variables on prediction. As the results of the analysis showed that in addition to the common indicators (serum creatinine and creatinine clearance rate), some other underappreciated indicators such as serum cystatin and cumulative days of vancomycin administration, weight and age, neutrophils and hemoglobin were the risk factors for cancer, diabetes mellitus, heptic insufficiency respectively. Stratified analysis of the comorbidities in patients with vancomycin-associated AKI further confirmed the necessity for different patient populations to be studied.