Oxygen-defect bismuth oxychloride nanosheets for ultrasonic cavitation effect enhanced sonodynamic and second near-infrared photo-induced therapy of breast cancer.

Sonodynamic therapy (SDT) relies heavily on the presence of oxygen to induce cell death. Its effectiveness is thus diminished in the hypoxic regions of tumor tissue. To address this issue, the exploration of ultrasound-based synergistic treatment modalities has become a significant research focus. Here, we report an ultrasonic cavitation effect enhanced sonodynamic and 1208 nm photo-induced cancer treatment strategy based on thermoelectric/piezoelectric oxygen-defect bismuth oxychloride nanosheets (BNs) to realize the high-performance eradication of tumors. Upon ultrasonic irradiation, the local high temperature and high pressure generated by the ultrasonic cavitation effect combined with the thermoelectric and piezoelectric effects of BNs create a built-in electric field. This facilitates the separation of carriers, increasing their mobility and extending their lifetimes, thereby greatly improving the effectiveness of SDT and NIR-Ⅱ phototherapy on hypoxia. The Tween-20 modified BNs (TBNs) demonstrate ∼88.6 % elimination rate against deep-seated tumor cells under hypoxic conditions. In vivo experiments confirm the excellent antitumor efficacy of TBNs, achieving complete tumor elimination within 10 days with no recurrences. Furthermore, due to the high X-ray attenuation of Bi and excellent NIR-Ⅱ absorption, TBNs enable precise cancer diagnosis through photoacoustic (PA) imaging and computed tomography (CT).

Prediction of acute coronary syndrome in patients with myeloproliferative neoplasms.

Background: Patients with myeloproliferative neoplasms (MPN) are exposed to a higher risk of cardiovascular disease, especially cardiovascular calcification. The present research aimed to analyze the clinical features and coronary artery calcium score (CACS) in MPN patients, and construct an effective model to predict acute coronary syndrome (ACS) in MPN patients. Materials and methods: A total of 175 MPN patients and 175 controls were recruited from the First Affiliated Hospital of Ningbo University. Based on cardiovascular events, the MPN patients were divided into the ACS group and the non-ACS group. Multivariate Cox analysis was completed to explore ACS-related factors. Furthermore, ROC curves were plotted to assess the predictive effect of CACS combined with white blood cells (WBC) and platelet for ACS in MPN patients. Results: The MPN group exhibited a higher CACS than the control group (133 vs. 55, P < 0.001). A total of 16 patients developed ACS in 175 MPN patients. Compared with non-ACS groups, significant differences in age, diabetes, smoking history, WBC, percentage of neutrophil, percentage of lymphocyte, neutrophil count, hemoglobin, hematocrit, platelet, lactate dehydrogenase, ß 2-microglobulin, and JAK2V617F mutation were observed in the ACS groups. In addition, the CACS in the ACS group was also significantly higher than that in the non-ACS group (374.5 vs. 121, P < 0.001). The multivariable Cox regression analysis identified WBC, platelet, and CACS as independent risk factors for ACS in MPN patients. Finally, ROC curves indicated that WBC, platelet, and CACS have a high predictive value for ACS in MPN patients (AUC = 0.890). Conclusion: CACS combined with WBC and platelet might be a promising model for predicting ACS occurrence in MPN patients.

Predicting Emission Wavelengths in Benzobisoxazole-Based OLEDs with Gradient Boosted Ensemble Models.

We demonstrate the use of gradient-boosted ensemble models that accurately predict emission wavelengths in benzobis[1,2-d:4,5-d']oxazole (BBO) based fluorescent emitters. We have curated a database of 50 molecules from previously published data by the Jeffries-EL group using density functional theory (DFT) computed ground and excited state features. We consider two machine learning (ML) models based on (i) whole cruciform molecules and (ii) their constituent fragment molecules. Both ML models provide accurate predictions with root-mean-square errors between 30 and 36 nm, competitive with state-of-the-art deep learning models trained on orders of magnitude more molecules, and this accuracy holds even when tested on four new BBO emitters unseen by the models. We also provide an interpretable feature importance analysis and discuss the relevant relationships between DFT and changes in predicted emission wavelength.

Coronary computed tomographic angiography-derived anatomic and hemodynamic plaque characteristics in prediction of cardiovascular events.

This study investigated the association of anatomic and hemodynamic plaque characteristics based on deep learning coronary computed tomography angiography (CCTA) with high-risk plaques that caused subsequent major adverse cardiovascular events (MACE). A retrospective analysis was conducted on patients who underwent CCTA between 1 month and 3 years prior to the occurrence of a MACE. Deep learning and computational fluid dynamics algorithms based on CCTA were applied to extract adverse plaque characteristics (low-attenuation plaque, positive remodeling, napkin-ring sign, and spotty calcification), and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFRCT], change in FFRCT across the lesion [△FFRCT], wall shear stress [WSS], and axial plaque stress [APS]). Correlation analysis, logistic regression, and Cox proportional risk analysis were conducted to understand the relationship between these measures and the occurrence of MACE and assess the value of hemodynamic parameters in predicting the incidence of MACE events and their prognosis. Our study included 86 patients with a total of 134 vessels exhibiting plaque formation and 83 culprit vessels with a subsequent coronary event. Culprit vessels had percent diameter stenosis [%DS] (0.54 ± 0.16 vs. 0.62 ± 0.13, P = 0.003), larger non-calcified plaque volume (45.8 vs. 101.7, P < 0.001), larger low-attenuation plaque volume (3.6 vs. 14.5, P < 0.001), more lesions with ≥ 3 adverse plaque characteristics (APC) (4 vs.26, P = 0.002), and worse hemodynamic features of adverse plaque. FFRCT demonstrated better visualization of maximum achievable flow in the presence of coronary stenosis and better correlation with the stenosis severity, while maximum of wall shear stress (WSSmax) was highly correlated with low-attenuation plaques and APC. The inclusion of hemodynamic parameters improved the efficacy of the predictive model, and a high WSS suggested a higher probability of MACE. Hemodynamic parameters based on CCTA are significantly correlated with plaque morphology. Importantly, integrating CCTA-derived parameters can refine the predictive performance of MACE occurrence.

Value of perfusion parameters from golden-angle radial sparse parallel dynamic contrast-enhanced magnetic resonance imaging in predicting pathological complete response after neoadjuvant chemoradiotherapy for locally advanced rectal cancer

PURPOSE: Non-invasive methods for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) can provide distinct leverage in the management of patients with locally advanced rectal cancer (LARC). This study aimed to investigate whether including the golden-angle radial sparse parallel (GRASP) dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameter (Ktrans), in addition to tumor regression grading (TRG) and apparent diffusion coefficient (ADC) values, can improve the predictive ability for pCR. METHODS: Patients with LARC who underwent nCRT and subsequent surgery were included. The imaging parameters were compared between patients with and without pCR. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive ability of these parameters for pCR. RESULTS: A total of 111 patients were included in the study. A pCR was obtained in 32 patients (28.8%). MRI-based TRG (mrTRG) showed a negative correlation with pCR (r = -0.61, P < 0.001), and the average ADC value showed a positive correlation with pCR (r = 0.62, P < 0.001). Before nCRT, Ktrans in the pCR group was significantly higher than in the non-pCR group (1.30 ± 0.24 vs. 0.88 ± 0.34, P < 0.001), but no difference was identified after nCRT. Following ROC curve analysis, the area under the curve (AUC) of mrTRG (level 1-2), average ADC value, and Ktrans value for predicting pCR were 0.738 [95% confidence interval (CI): 0.65-0.82], 0.78 (95% CI: 0.69-0.86), and 0.84 (95% CI: 0.77-0.92), respectively. The model combining the three parameters had significantly higher predictive ability for pCR (AUC: 0.94, 95% CI: 0.88-0.98). CONCLUSION: The use of a combination of the GRASP DCE-MRI Ktrans with mrTRG and ADC can lead to a better pCR predictive performance.

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study.

BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performance, and validate its application in real-world clinical implementation. METHODS: We developed a deep-learning model using 16 546 head and neck CTA examination images from 14 517 patients at eight Chinese hospitals. Using an adapted, stepwise implementation and evaluation, 120 certified clinicians from 15 geographically different hospitals were recruited. Initially, the AI model was externally validated with images of 900 digital subtraction angiography-verified CTA cases (examinations) and compared with the performance of 24 clinicians who each viewed 300 of these cases (stage 1). Next, as a further external validation a multi-reader multi-case study enrolled 48 clinicians to individually review 298 digital subtraction angiography-verified CTA cases (stage 2). The clinicians reviewed each CTA examination twice (ie, with and without the AI model), separated by a 4-week washout period. Then, a randomised open-label comparison study enrolled 48 clinicians to assess the acceptance and performance of this AI model (stage 3). Finally, the model was prospectively deployed and validated in 1562 real-world clinical CTA cases. FINDINGS: The AI model in the internal dataset achieved a patient-level diagnostic sensitivity of 0·957 (95% CI 0·939-0·971) and a higher patient-level diagnostic sensitivity than clinicians (0·943 [0·921-0·961] vs 0·658 [0·644-0·672]; p<0·0001) in the external dataset. In the multi-reader multi-case study, the AI-assisted strategy improved clinicians' diagnostic performance both on a per-patient basis (the area under the receiver operating characteristic curves [AUCs]; 0·795 [0·761-0·830] without AI vs 0·878 [0·850-0·906] with AI; p<0·0001) and a per-aneurysm basis (the area under the weighted alternative free-response receiver operating characteristic curves; 0·765 [0·732-0·799] vs 0·865 [0·839-0·891]; p<0·0001). Reading time decreased with the aid of the AI model (87·5 s vs 82·7 s, p<0·0001). In the randomised open-label comparison study, clinicians in the AI-assisted group had a high acceptance of the AI model (92·6% adoption rate), and a higher AUC when compared with the control group (0·858 [95% CI 0·850-0·866] vs 0·789 [0·780-0·799]; p<0·0001). In the prospective study, the AI model had a 0·51% (8/1570) error rate due to poor-quality CTA images and recognition failure. The model had a high negative predictive value of 0·998 (0·994-1·000) and significantly improved the diagnostic performance of clinicians; AUC improved from 0·787 (95% CI 0·766-0·808) to 0·909 (0·894-0·923; p<0·0001) and patient-level sensitivity improved from 0·590 (0·511-0·666) to 0·825 (0·759-0·880; p<0·0001). INTERPRETATION: This AI model demonstrated strong clinical potential for intracranial aneurysm detection with improved clinician diagnostic performance, high acceptance, and practical implementation in real-world clinical cases. FUNDING: National Natural Science Foundation of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

A Contrast-Enhanced Tri-Modal MRI Technique for High-Performance Hypoxia Imaging of Breast Cancer.

Personalized radiotherapy strategies enabled by the construction of hypoxia-guided biological target volumes (BTVs) can overcome hypoxia-induced radioresistance by delivering high-dose radiotherapy to targeted hypoxic areas of the tumor. However, the construction of hypoxia-guided BTVs is difficult owing to lack of precise visualization of hypoxic areas. This study synthesizes a hypoxia-responsive T1, T2, T2 mapping tri-modal MRI molecular nanoprobe (SPION@ND) and provides precise imaging of hypoxic tumor areas by utilizing the advantageous features of tri-modal magnetic resonance imaging (MRI). SPION@ND exhibits hypoxia-triggered dispersion-aggregation structural transformation. Dispersed SPION@ND can be used for routine clinical BTV construction using T1-contrast MRI. Conversely, aggregated SPION@ND can be used for tumor hypoxia imaging assessment using T2-contrast MRI. Moreover, by introducing T2 mapping, this work designs a novel method (adjustable threshold-based hypoxia assessment) for the precise assessment of tumor hypoxia confidence area and hypoxia level. Eventually this work successfully obtains hypoxia tumor target and accurates hypoxia tumor target, and achieves a one-stop hypoxia-guided BTV construction. Compared to the positron emission tomography-based hypoxia assessment, SPION@ND provides a new method that allows safe and convenient imaging of hypoxic tumor areas in clinical settings.

Oxygen Vacancy Defect Enhanced NIR-II Photothermal Performance of BiOxCl Nanosheets for Combined Phototherapy of Cancer Guided by Multimodal Imaging.

Narrow photo-absorption range and low carrier utilization are significant barriers that restrict the antitumor efficiency of 2D bismuth oxyhalide (BiOX, X = Cl, Br, I) nanosheets (NSs). Introducing oxygen vacancy (OV) defects can expand the absorption range and improve carrier utilization, which are crucial but also challenging. In this study, a series of BiOxCl NSs with different OV defect concentrations (x = 1, 0.7, 0.5) is developed, which shows full spectrum absorption and strong absorption in the second near-infrared region (NIR-II). Density functional theory calculations are utilized to calculate the crystal structure and density states of BiOxCl, which confirm that part of the carriers is separated by OV enhanced internal electric field to improve carrier utilization. The carriers without redox reaction can be trapped in the OV, leading to great majority of photo-generated carriers promoting the photothermal performance. Triggered by single NIR-II (1064 nm), BiOxCl NSs' bidirectional efficient utilization of carriers achieves synchronously combined phototherapy, leading to enhanced tumor ablation and multimodal diagnostic in vitro and vivo. It is thus believed that this work provides an innovative strategy to design and construct nanoplatforms of indirect band gap semiconductors for clinical phototheranostics.

The Clinical Value of Apparent Diffusion Coefficient of Readout Segmentation of Long Variable Echo Trains and Correlation With Ki-67 Expression in Distal Rectal Cancer.

OBJECTIVE: The aim of the study is to explore the clinical value of the apparent diffusion coefficient (ADC) derived from the readout segmentation of long variable echo trains (RESOLVE) technique for identifying clinicopathologic features of distal rectal cancer and correlations between ADC and Ki-67 expression. METHODS: The data of 112 patients with a proven pathology of distal rectal cancer who underwent preoperative magnetic resonance imaging were retrospectively analyzed. The mean ADC value was measured using the "full-layer and center" method. Differences in ADC values and Ki-67 expression in different clinical stages, pathological types, and tumor differentiation were compared using analysis of variance. Correlations between ADC value and clinicopathologic features were assessed using Spearman correlation analysis. RESULTS: Interobserver agreement of confidence levels from 2 radiologists was excellent for ADC measurement ( k =  0.85). Patients with a lower clinical stage, well-differentiated adenocarcinomas, and a higher possibility of mucinous adenocarcinoma exhibited a positive correlation with higher ADC values, but these factors were negatively correlated with Ki-67 expression (all P < 0.05). We found that ADC value was negatively correlated with Ki-67 expression ( r = -0.62, P < 0.001). CONCLUSIONS: The ADC value generated by RESOLVE sequences was significantly associated with clinicopathologic features and Ki-67 expression in patients with distal rectal cancer in this study. Thus, the ADC value could be considered a new noninvasive imaging biomarker that could be helpful in predicting the biological properties of distal rectal cancer.

Quantitative assessment of collateral time on perfusion computed tomography in acute ischemic stroke patients.

Background and aim: Good collateral circulation is recognized to maintain perfusion and contribute to favorable clinical outcomes in acute ischemic stroke. This study aimed to derive and validate an optimal collateral time measurement on perfusion computed tomography imaging for patients with acute ischemic stroke. Methods: This study included 106 acute ischemic stroke patients with complete large vessel occlusions. In deriving cohort of 23 patients, the parasagittal region of the ischemic hemisphere was divided into six pial arterial zones according to pial branches of the middle cerebral artery. Within the 85 arterial zones with collateral vessels, the receiver operating characteristic analysis was performed to derive the optimal collateral time threshold for fast collateral flow on perfusion computed tomography. The reference for fast collateral flow was the peak contrast delay on the collateral vessels within each ischemic arterial zone compared to its contralateral normal arterial zone on dynamic computed tomography angiography. The optimal perfusion collateral time threshold was then tested in predicting poor clinical outcomes (modified Rankin score of 5-6) and final infarct volume in the validation cohort of 83 patients. Results: For the derivation cohort of 85 arterial zones, the optimal collateral time threshold for fast collateral flow on perfusion computed tomography was a delay time of 4.04 s [area under the curve = 0.78 (0.67, 0.89), sensitivity = 73%, and specificity = 77%]. Therefore, the delay time of 4 s was used to define the perfusion collateral time. In the validation cohort, the perfusion collateral time showed a slightly higher predicting power than dynamic computed tomography angiography collateral time in poor clinical outcomes (area under the curve = 0.72 vs. 0.67; P < 0.001). Compared to dynamic computed tomography angiography collateral time, the perfusion collateral time also had better performance in predicting final infarct volume (R-squared values = 0.55 vs. 0.23; P < 0.001). Conclusion: Our results indicate that perfusion computed tomography can accurately quantify the collateral time after acute ischemic stroke.

Inhibitory effects of Ganoderma lucidum triterpenoid on the growth and metastasis of hepatocellular carcinoma.

OBJECTIVE: To investigate the inhibitory effects and mechanisms of triterpenoids from Ganoderma lucidum (G. lucidum triterpenoids) on the growth and metastasis of hepatocellular carcinoma (HCC) both in vitro and in vivo. METHODS: In in-vitro experiments, the inhibitory effects of G. lucidum triterpenoids on human HCC SMMC-7721 cell lines were investigated by observing the proliferation, apoptosis, migration and invasion phenotypes of the cell line and assessing the cell cycles as well as the cell apoptosis and proliferation. In in-vivo experiments, nude mouse SMMC-7721 tumor models were established and divided into control group, treatment group A (low concentration group) and treatment group B (high concentration group) according to the treatment models received. Magnetic resonance imaging (MRI) was performed 3 times on each mouse model to calculate their tumor volumes. The liver and kidney functions of the models were evaluated. Tissues harvested from their solid organs were subjected to HE staining, and the tumor tissues were subjected to HE staining and immunohistochemical staining (E-cad, Ki-67, and Tunel), respectively. RESULTS: i. In in-vitro experiments, G. lucidum triterpenoids could inhibit the growth of human HCC SMMC-7721 cell lines via regulating their proliferation and apoptosis phenotype. ii. In in-vivo experiments, the comparison of tumor volumes of mouse models obtained from the second and third MIR scanning was found to be statistically significant between the control group and treatment group A (P<0.05); and statistically significant differences were also found in the tumor volumes from the second and third MRI scanning between the control group and treatment group B (P<0.05). iii. No significant acute injuries or adverse effects were observed in the liver or kidney of the nude mice. CONCLUSION: G. lucidum triterpenoids could inhibit the growth of tumor cells via blocking their proliferation, accelerating apoptosis, and inhibiting migration and invasion, without marked toxic effects on normal organs and tissues in the body.

Clinical characteristics and high-resolution computed tomography findings of 805 patients with mild or moderate infection from SARS-CoV-2 Omicron subvariant BA.2.

BACKGROUND: COVID-19 is a global pandemic. Currently, the predominant strain is SARS-CoV-2 Omicron subvariant BA.2 in many countries. Understanding its infection characteristics can facilitate clinical management. OBJECTIVES: This study aimed to characterize the clinical, laboratory, and high-resolution computed tomography (HRCT) findings in patients with mild or moderate infection from SARS-CoV-2 Omicron subvariant BA.2. METHODS: We performed a retrospective study on patients infected with SARS-CoV-2 Omicron subvariant BA.2 between April 4th and April 17th, 2022. The clinical characteristics, laboratory features, and HRCT images were reviewed. RESULTS: A total of 805 patients were included (411 males and 394 females, median age 33 years old). The infection was mild, moderate, severe, and asymptomatic in 490 (60.9%), 37 (4.6%), 0 (0.0%), and 278 (34.5%) patients, respectively. Notably, 186 (23.1%), 96 (11.9%), 265 (32.9%), 11 (3.4%), 7 (0.9%), and 398 (49.4%) patients had fever, cough, throat discomfort, stuffy or runny nose, fatigue, and no complaint, respectively. Furthermore, 162 (20.1%), 332 (41.2%), and 289 (35.9%) patients had decreased white blood cell counts, reduced lymphocytes, and elevated C-reactive protein levels, respectively. HRCT revealed pneumonia in 53 (6.6%) patients. The majority of the lung involvements were ground-glass opacity (50, 94.3%) mostly in the subpleural area. The grade of lung injury was mainly mild (90.6%). Short-term follow-ups showed that most patients with pneumonia recovered. CONCLUSION: Most patients with mild or moderate infection from SARS-CoV-2 Omicron subvariant BA.2 were adults, with fever and upper respiratory symptoms as the main clinical presentations. Lower respiratory infection was mild, with ground-glass opacity in the subpleural area as the main finding.

Sequential targeting biomimetic nano platform for enhanced mild photothermal therapy and chemotherapy of tumor.

Tumor targeting drug delivery is of significant importance for the treatment of triple negative breast cancer (TNBC) considering the presence of appreciable amount of tumor matrix and the absence of effective targets on the tumor cells. Hence in this study, a new therapeutic multifunctional nanoplatform with improved TNBC targeting ability and efficacy was constructed and used for therapy of TNBC. Specifically, curcumin loaded mesoporous polydopamine (mPDA/Cur) nanoparticles were synthesized. Thereafter, manganese dioxide (MnO2) and a hybrid of cancer-associated fibroblasts (CAFs) membranes as well as cancer cell membranes were sequentially coated on the surface of mPDA/Cur to obtain mPDA/Cur@M/CM. It was found that two distinct kinds of cell membranes were able to endow the nano platform with homologous targeting ability, thereby achieving accurate delivery of drugs. Nanoparticles gathered in the tumor matrix can loosen the tumor matrix via the photothermal effect mediated by mPDA to rupture the physical barrier of tumor, which is conducive to the penetration and targeting of drugs to tumor cells in the deep tissues. Moreover, the existence of curcumin, MnO2 and mPDA was able to promote the apoptosis of cancer cells by promoting increased cytotoxicity, enhanced Fenton-like reaction, and thermal damage, respectively. Overall, both in vitro and in vivo results showed that the designed biomimetic nanoplatform could significantly inhibit the tumor growth and thus provide an efficient novel therapeutic strategy for TNBC.

Evaluation of Coronary Artery Diffuse Calcification Stenosis by Corrected Coronary Opacification Difference.

OBJECTIVES: The artifacts produced by calcification on coronary computed tomographic angiography (CCTA) have a great influence on the diagnosis of coronary stenosis. The purpose of this study is to investigate the value of corrected coronary opacification (CCO) difference in the diagnosis of stenosis in diffusely calcified coronary arteries (DCCAs). METHODS: A total of 84 patients were enrolled. The CCO difference across the diffuse calcification was measured through CCTA. Coronary arteries were grouped according to the extent of stenosis obtained by invasive coronary angiography (ICA). The Kruskal-Wallis H test was used to compare the CCO differences between different groups and a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the CCO difference. RESULTS: Among the 84 patients, 58 patients had one DCCA, 14 patients had 2 DCCAs, and 12 patients had 3 DCCAs. A total of 122 coronary arteries were examined, 16 showed no significant stenosis, 42 had <70% stenosis, and 64 had 70-99% stenosis. The median CCO differences among the 3 groups were 0.064, 0.117, and 0.176, respectively. There were significant differences between the group without stenosis and the group with 70-99% stenosis (H = -3.581, P = 0.001), and between the group with <70% stenosis and the group with 70-99% stenosis (H = -2.430, P = 0.045). The area under the ROC curve was 0.681 and the optimal cut-off point was 0.292. Taking the ICA results as the gold standard, the sensitivity and specificity for the diagnosis of ≥70% coronary stenosis with a cut-off point of 0.292 were 84.4% and 44.8%, respectively. CONCLUSION: CCO difference could be useful in the diagnosis of ≥70% severe coronary stenosis in DCCA. Through this non-invasive examination, the CCO difference could be a reference for clinical treatment.

Perirenal fat thickness and liver fat fraction are independent predictors of MetS in adults with overweight and obesity suspected with NAFLD: a retrospective study.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) has a multidirectional relationship with metabolic syndrome (MetS) and used to be considered a hepatic manifestation of MetS. Perirenal fat, as a part of visceral adipose tissue (VAT), was reported to be correlated with MetS components, but data for intraorgan fat are lacking. This study was undertaken to assess the value of peripheral and intraorgan fat to predict MetS in adults with overweight and obesity with suspected NAFLD. METHODS: We studied 134 sequential adults (mean age, 31.5 years; 47% female) with overweight and obesity with suspected NAFLD. All participants underwent abdominal magnetic resonance imaging (MRI) examination. Anthropometric and metabolic parameters and perirenal fat thickness (PRFT), subcutaneous adipose tissue thickness (SATT), liver fat fraction (LFF), pancreas fat fraction (PFF), and lumbar spine fat fraction (LSFF) were collected. MetS was defined according to the International Diabetes Federation (IDF) criteria. Statistical analyses included basic statistics, linear correlation and logistic regression analysis. RESULTS: A total of 63 adults with MetS and 71 adults with advanced liver steatosis (grades 2 and 3) were included in our study. Patients with MetS had greater PRFT (p = 0.026) and LFF (p < 0.001), as well as greater homeostasis model assessment of insulin resistance (HOMA-IR), alanine transaminase (ALT), aspartate transaminase (AST), and decreased SATT. MetS patients had a higher proportion of advanced steatosis than those without MetS (P < 0.001). The MetS score was associated with PRFT and LFF. Logistic regression analysis showed that the PRFT and LFF were independent predictors of MetS after adjusting for age and sex. A cutoff of 9.15 mm for PRFT and 14.68% for LFF could be predictive of MetS. CONCLUSIONS: This study shows that the absolute cutoff level of 9.15 mm for PRFT and 14.68% for LFF may be clinically important markers for identifying patients who are at high risk of MetS among adults with overweight and obesity with suspected NAFLD, irrespective of sex and age. Moreover, ectopic fat levels in pancreas and lumbar spine are positively associated with PRFT. TRIAL REGISTRATION: Not applicable.

Detection of Intracranial Aneurysms Using Multiphase CT Angiography with a Deep Learning Model.

RATIONALE AND OBJECTIVES: Determine the effect of a multiphase fusion deep-learning model with automatic phase selection in detection of intracranial aneurysm (IA) from computed tomography angiography (CTA) images. MATERIALS AND METHODS: CTA images of intracranial arteries from patients at Ningbo First Hospital were retrospectively analyzed. Images were randomly classified as training data, internal validation data, or test data. CTA images from cases examined by digital subtraction angiography (DSA) were examined for independent validation. A deep-learning model was constructed by automatic phase selection of multiphase fusion, and compared to the single-phase algorithm to evaluate algorithm sensitivity. RESULTS: We analyzed 1110 patients (1493 aneurysms) as training data, 139 patients (174 aneurysms) as internal validation data, and 134 patients (175 aneurysms) as test data. The sensitivity of the multiphase analysis of the internal validation data, test data, and independent validation data were greater than from the single-phase analysis. The recall of the multiphase selection was greater or equal to that of single-phase selection in the aneurysm position, shape, size, and rupture status. Use of the test data to determine the presence and absence of aneurysm rupture led to a recall from multiphase selection of 94.8% and 87.6% respectively; both of these values were greater than those from single-phase selection (89.6% and 79.4%). CONCLUSION: A multiphase fusion deep learning model with automatic phase selection provided automated detection of IAs with high sensitivity.

Delayed pericardial effusion or tamponade following left atrial appendage closure: A single-center experience.

BACKGROUND: Pericardial effusion or pericardial tamponade (PE/PT) is a relatively common complication of left atrial appendage closure (LAAC). However, delayed PE/PT is rare with limited data. The aim of the study was to analyze the incidence and clinical consequences of delayed PE/PT following LAAC. METHODS: Patients with nonvalvular AF who were successfully implanted with LAAC devices from October 2014 to April 2021 were consecutively screened. Subjects experiencing delayed PE/PT after LAAC were included. All treatment sessions of the subjects were recorded in detail. After discharge, the patients were followed up for clinical outcomes. RESULTS: A total of 748 patients with successful LAAC [nitinol cage device (475 Watchman 2.5), nitinol plug device (131 ACP and 142 LAmbre)] were screened. Six patients experienced delayed PE/PT (1 Watchman, 2 ACP, 3 LAmbre). The incidence of delayed PE/PT was higher in patients with a nitinol plug device (1.8% vs. 0.2%, P = 0.027). Bloody PE only occurred in patients with a nitinol plug device (5/273, 1.8%). All the patients accepted pericardiocentesis and discontinuing antithrombotic medication, and none of the patients died or needed cardiac surgery. All patients were followed up for 810 (598, 1174) days after discharge. None of them developed constrictive pericarditis or thromboembolic or major bleeding events. CONCLUSION: Delayed PE/PT is rare but can occur, and the incidence of delayed bloody PE/PT for the nitinol plug device was higher than that for the nitinol cage device. The strategy of emergency pericardiocentesis combined with discontinuing antithrombotic medication may be effective for delayed bloody PE/PT.

Residue screening and analysis of enrofloxacin and its metabolites in real aquatic products based on ultrahigh-performance liquid chromatography coupled with high resolution mass spectrometry.

The abuse of enrofloxacin (ENR) in aquaculture and the lack of monitoring of other metabolites except ciprofloxacin (CIP) may lead to unknown harmful effects on human health. In this study, ENR metabolites were screened in real fish samples based on ultrahigh-performance liquid chromatography coupled with Q-Orbitrap mass spectrometry combined with Compound Discoverer software, and another metabolite deethylene-ENR besides CIP was detected and identified for the first time. Correspondingly, a method for the determination of ENR and CIP and the semi-quantitative analysis of deethylene-ENR in aquatic products was established. Method validation illustrated that excellent linearity and satisfactory recoveries of analytes were obtained. Limits of detection of ENR and CIP were both 0.1 µg kg-1, and their limits of quantification both 1 µg kg-1. CIP and deethylene-ENR were detected in 12 of 14 ENR-positive fish samples, so deethylene-ENR should be of concern as a possible risk candidate in aquatic products.

Determination of chlorpromazine and its metabolites in animal-derived foods using QuEChERS-based extraction, EMR-Lipid cleanup, and UHPLC-Q-Orbitrap MS analysis.

Chlorpromazine (CPZ) is abused in animal husbandry and can be extensively metabolized in humans and animals. However, the actual monitoring mainly focuses on the parent compound but lacks attention to its metabolites. A method was developed and validated firstly for identification and determination of CPZ and its four major metabolites in animal-derived foods using ultrahigh-performance liquid chromatography coupled with quadrupole-Orbitrap mass spectrometry in combination with QuEChERS preparation method. Satisfactory recoveries of analytes spiked in fish and pork samples ranged from 72 to 117 %, and limits of quantification were 2.0 and 1.0 µg kg-1 for fish and pork samples respectively. Moreover, through the hydrolysis experiments of CPZ, its hydrolysates, such as CPZ-sulfoxide, CPZ-N-oxide and CPZ-sulfoxide-N-oxide, were identified as potential risk compounds. The developed method has been successfully applied to the determination of CPZ and its metabolites in actual commercial samples, as well as to the screening of other CPZ-related risk compounds.

Quantitative collateral score for the prediction of clinical outcomes in stroke patients: Better than visual grading.

Objectives: To identify preoperative prognostic factors for acute ischemic stroke (AIS) patients receiving mechanical thrombectomy (MT) and compare the performance of quantitative collateral score (qCS) and visual collateral score (vCS) in outcome prediction. Methods: Fifty-five patients with AIS receiving MT were retrospectively enrolled. qCS was defined as the percentage of the volume of collaterals of both hemispheres. Based on the dichotomous outcome assessed using a 90-day modified Rankin Scale (mRS), we compared qCS, vCS, age, sex, National Institute of Health stroke scale score, etiological subtype, platelet count, international normalized ratio, glucose levels, and low-density lipoprotein cholesterol (LDL-C) levels between favorable and unfavorable outcome groups. Logistic regression analysis was performed to determine the effect on the clinical outcome. The discriminatory power of qCS, vCS, and their combination with cofounders for determining favorable outcomes was tested with the area under the receiver-operating characteristic curve (AUC). Results: vCS, qCS, LDL-C, and age could all predict clinical outcomes. qCS is superior over vCS in predicting favorable outcomes with a relatively higher AUC value (qCS vs. vCS: 0.81 vs. 0.74) and a higher sensitivity rate (qCS vs. vCS: 72.7% vs. 40.9%). The prediction power of qCS + LDL-C + age was best with an AUC value of 0.91, but the accuracy was just increased slightly compared to that of qCS alone. Conclusion: Collateral scores, LDL-C and age were independent prognostic predictors for patients with AIS receiving MT; qCS was a better predictor than vCS. Furthermore, qCS + LDL-C + age offers a strong prognostic prediction power and qCS alone was another good choice for predicting clinical outcome.