A strategy of "adding fuel to the flames" enables a self-accelerating cycle of ferroptosis-cuproptosis for potent antitumor therapy.

Cuproptosis in antitumor therapy faces challenges from copper homeostasis efflux mechanisms and high glutathione (GSH) levels in tumor cells, hindering copper accumulation and treatment efficacy. Herein, we propose a strategy of "adding fuel to the flames" for potent antitumor therapy through a self-accelerating cycle of ferroptosis-cuproptosis. Disulfiram (DSF) loaded hollow mesoporous copper-iron sulfide (HMCIS) nanoparticle with conjugation of polyethylene glycol (PEG) and folic acid (FA) (i.e., DSF@HMCIS-PEG-FA) was developed to swiftly release DSF, H2S, Cu2+, and Fe2+ in the acidic tumor microenvironment (TME). The hydrogen peroxide (H2O2) levels and acidity within tumor cells enhanced by the released H2S induce acceleration of Fenton (Fe2+) and Fenton-like (Cu2+) reactions, enabling the powerful tumor ferroptosis efficacy. The released DSF acts as a role of "fuel", intensifying catalytic effect ("flame") in tumor cells through the sustainable Fenton chemistry (i.e., "add fuel to the flames"). Robust ferroptosis in tumor cells is characterized by serious mitochondrial damage and GSH depletion, leading to excess intracellular copper that triggers cuproptosis. Cuproptosis disrupts mitochondria, compromises iron-sulfur (Fe-S) proteins, and elevates intracellular oxidative stress by releasing free Fe3+. These interconnected processes form a self-accelerating cycle of ferroptosis-cuproptosis with potent antitumor capabilities, as validated in both cancer cells and tumor-bearing mice.

Hepatic-associated vascular morphological assessment to predict overt hepatic encephalopathy before TIPS: a multicenter study.

BACKGROUND: To provide patients the chance of accepting curative transjugular intrahepatic portosystemic shunt (TIPS) rather than palliative treatments for portal hypertension-related variceal bleeding and ascites, we aimed to assess hepatic-associated vascular morphological change to improve the predictive accuracy of overt hepatic encephalopathy (HE) risks. METHODS: In this multicenter study, 621 patients undergoing TIPS were subdivided into training (413 cases from 3 hospitals) and external validation datasets (208 cases from another 3 hospitals). In addition to traditional clinical factors, we assessed hepatic-associated vascular morphological changes using maximum diameter (including absolute and ratio values). Three predictive models (clinical, hepatic-associated vascular, and combined) were constructed using logistic regression. Their discrimination and calibration were compared to test the necessity of hepatic-associated vascular assessment and identify the optimal model. Furthermore, to verify the improved performance of ModelC-V, we compared it with four previous models, both in discrimination and calibration. RESULTS: The combined model outperformed the clinical and hepatic-associated vascular models (training: 0.814, 0.754, 0.727; validation: 0.781, 0.679, 0.776; p < 0.050) and had the best calibration. Compared to previous models, ModelC-V showed superior performance in discrimination. The high-, middle-, and low-risk populations displayed significantly different overt HE incidence (p < 0.001). Despite the limited ability of pre-TIPS ammonia to predict overt HE risks, the combined model displayed a satisfactory ability to predict overt HE risks, both in the low- and high-ammonia subgroups. CONCLUSION: Hepatic-associated vascular assessment improved the predictive accuracy of overt HE, ensuring curative chances by TIPS for suitable patients and providing insights for cirrhosis-related studies.

High Intensity Focused Ultrasound-Driven Nanomotor for Effective Ferroptosis-Immunotherapy of TNBC.

The heterogeneity of triple-negative breast cancers (TNBC) remains challenging for various treatments. Ferroptosis, a recently identified form of cell death resulting from the unrestrained peroxidation of phospholipids, represents a potential vulnerability in TNBC. In this study, a high intensity focused ultrasound (HIFU)-driven nanomotor is developed for effective therapy of TNBC through induction of ferroptosis. Through bioinformatics analysis of typical ferroptosis-associated genes in the FUSCCTNBC dataset, gambogic acid is identified as a promising ferroptosis drug and loaded it into the nanomotor. It is found that the rapid motion of nanomotors propelled by HIFU significantly enhanced tumor accumulation and penetration. More importantly, HIFU not only actuated nanomotors to trigger effective ferroptosis of TNBC cells, but also drove nanomotors to activate ferroptosis-mediated antitumor immunity in primary and metastatic TNBC models, resulting in effective tumor regression and prevention of metastases. Overall, HIFU-driven nanomotors show great potential for ferroptosis-immunotherapy of TNBC.

A modified model for predicting mortality after transjugular intrahepatic portosystemic shunt: A multicentre study.

BACKGROUND AND AIMS: The transjugular intrahepatic portosystemic shunt has controversial survival benefits; thus, patient screening should be performed preoperatively. In this study, we aimed to develop a model to predict post-transjugular intrahepatic portosystemic shunt mortality to aid clinical decision making. METHODS: A total of 811 patients undergoing transjugular intrahepatic portosystemic shunt from five hospitals were divided into the training and external validation data sets. A modified prediction model of post-transjugular intrahepatic portosystemic shunt mortality (ModelMT ) was built after performing logistic regression. To verify the improved performance of ModelMT , we compared it with seven previous models, both in discrimination and calibration. Furthermore, patients were stratified into low-, medium-, high- and extremely high-risk subgroups. RESULTS: ModelMT demonstrated a satisfying predictive efficiency in both discrimination and calibration, with an area under the curve of .875 in the training set and .852 in the validation set. Compared to previous models (ALBI, BILI-PLT, MELD-Na, MOTS, FIPS, MELD, CLIF-C AD), ModelMT showed superior performance in discrimination by statistical difference in the Delong test, net reclassification improvement and integrated discrimination improvement (all p < .050). Similar results were observed in calibration. Low-, medium-, high- and extremely high-risk groups were defined by scores of ≤160, 160-180, 180-200 and >200, respectively. To facilitate future clinical application, we also built an applet for ModelMT . CONCLUSIONS: We successfully developed a predictive model with improved performance to assist in decision making for transjugular intrahepatic portosystemic shunt according to survival benefits.

Low-temperature photothermal-induced alkyl radical release facilitates dihydroartemisinin-triggered "valve-off" starvation therapy.

The high nutrient and energy demand of tumor cells compared to normal cells to sustain rapid proliferation offer a potentially auspicious avenue for implementing starvation therapy. However, conventional starvation therapy, such as glucose exhaustion and vascular thrombosis, can lead to systemic toxicity and exacerbate tumor hypoxia. Herein, we developed a new "valve-off" starvation tactic, which was accomplished by closing the valve of glucose transporter protein 1 (GLUT1). Specifically, dihydroartemisinin (DHA), 2,20-azobis [2-(2-imidazolin-2-yl) propane] dihydrochloride (AI), and Ink were co-encapsulated in a sodium alginate (ALG) hydrogel. Upon irradiation with the 1064 nm laser, AI rapidly disintegrated into alkyl radicals (R•), which exacerbated the DHA-induced mitochondrial damage through the generation of reactive oxygen species and further reduced the synthesis of adenosine triphosphate (ATP). Simultaneously, the production of R• facilitated DHA-induced starvation therapy by suppressing GLUT1, which in turn reduced glucose uptake. Systematic in vivo and in vitro results suggested that this radical-enhanced "valve-off" strategy for inducing tumor cell starvation was effective in reducing glucose uptake and ATP levels. This integrated strategy induces tumor starvation with efficient tumor suppression, creating a new avenue for controlled, precise, and concerted tumor therapy.

Circ_0005015 upregulates BACH1 to promote aggressive behaviors in glioblastoma by sponging microRNA-382-5p.

To investigate the potential role and molecular mechanism of circ_0005015 in GBM progression. Circ_0005015, microRNA-382-5p (miR-382-5p), and BTB domain and CNC homolog 1 (BACH1) levels were measured by real-time quantitative polymerase chain reaction (RT-qPCR). Cell proliferation was determined by MTT, colony formation, and EdU assays. Cell apoptosis was analyzed using flow cytometry. Cell migration and invasion were assessed using wound healing and transwell assays. Glucose accumulation and lactate levels were examined by the corresponding kit. RNA pull-down and dual-luciferase reporter assays were performed to confirm the interaction between miR-382-5p and circ_0005015 or BACH1. Protein levels of MMP9, PCNA, and BACH1 were examined using western blot assay. Role of circ_0005015 on tumor growth in vivo was analyzed using a xenograft tumor model. Circ_0005015 content was up-regulated in GBM patients and cells, its knockdown restrained GBM cell proliferation, migration, invasion, glycolysis, and triggered apoptosis. Mechanistically, we found that circ_0005015 could directly interact with miR-382-5p and serve as a miRNA sponge to regulate BACH1 expression. In addition, circ_0005015 knockdown might repress tumor growth in vivo. Circ_0005015 boosted GBM progression via binding to miR-382-5p to up-regulate BACH1, which may offer new effective targets for GBM treatment.

Model containing sarcopenia and visceral adiposity can better predict the prognosis of hepatocellular carcinoma: a multicenter study.

AIM: This study aimed to explore whether the addition of sarcopenia and visceral adiposity could improve the accuracy of model predicting progression-free survival (PFS) in hepatocellular carcinoma (HCC). METHODS: In total, 394 patients with HCC from five hospitals were divided into the training and external validation datasets. Patients were initially treated by liver resection or transarterial chemoembolization. We evaluated adipose and skeletal muscle using preoperative computed tomography imaging and then constructed three predictive models, including metabolic (ModelMA), clinical-imaging (ModelCI), and combined (ModelMA-CI) models. Their discrimination, calibration, and decision curves were compared, to identify the best model. Nomogram and subgroup analysis was performed for the best model. RESULTS: ModelMA-CI containing sarcopenia and visceral adiposity had good discrimination and calibrations (integrate area under the curve for PFS was 0.708 in the training dataset and 0.706 in the validation dataset). ModelMA-CI had better accuracy than ModelCI and ModelMA. The performance of ModelMA-CI was not affected by treatments or disease stages. The high-risk subgroup (scored > 198) had a significantly shorter PFS (p < 0.001) and poorer OS (p < 0.001). CONCLUSIONS: The addition of sarcopenia and visceral adiposity improved accuracy in predicting PFS in HCC, which may provide additional insights in prognosis for HCC in subsequent studies.

CT Findings of Undifferentiated Pancreatic Cancer With Osteoclast-Like Giant Cells: A Case Series from a Single Center's Experience With 10 Cases.

Little is known about the imaging features of undifferentiated carcinoma with osteoclast-like giant cells of the pancreas (UCOGCP) because of its extremely low incidence. To improve the diagnostic accuracy of this tumor, 10 UCOGCP cases with confirmed histopathology were collected and their clinical and image data features were analyzed. We found that the median age of our study was 61 years (50-76 years in range) and the main clinical manifestations were nonspecific abdominal pain. There were some differences in the degree of enhancement and computed tomography (CT) features between the tumor located at the head and body or tail of the pancreas. Perhaps these subtle imaging findings can provide valuable diagnostic information.

3D automatic liver and spleen assessment in predicting overt hepatic encephalopathy before TIPS: a multi-center study.

BACKGROUND: Overt hepatic encephalopathy (HE) should be predicted preoperatively to identify suitable candidates for transjugular intrahepatic portosystemic shunt (TIPS) instead of first-line treatment. This study aimed to construct a 3D assessment-based model to predict post-TIPS overt HE. METHODS: In this multi-center cohort study, 487 patients who underwent TIPS were subdivided into a training dataset (390 cases from three hospitals) and an external validation dataset (97 cases from another two hospitals). Candidate factors included clinical, vascular, and 2D and 3D data. Combining the least absolute shrinkage and operator method, support vector machine, and probability calibration by isotonic regression, we constructed four predictive models: clinical, 2D, 3D, and combined models. Their discrimination and calibration were compared to identify the optimal model, with subgroup analysis performed. RESULTS: The 3D model showed better discrimination than did the 2D model (training: 0.719 vs. 0.691; validation: 0.730 vs. 0.622). The model combining clinical and 3D factors outperformed the clinical and 3D models (training: 0.802 vs. 0.735 vs. 0.719; validation: 0.816 vs. 0.723 vs. 0.730; all p < 0.050). Moreover, the combined model had the best calibration. The performance of the best model was not affected by the total bilirubin level, Child-Pugh score, ammonia level, or the indication for TIPS. CONCLUSION: 3D assessment of the liver and the spleen provided additional information to predict overt HE, improving the chance of TIPS for suitable patients. 3D assessment could also be used in similar studies related to cirrhosis.

Comparison Between the Stereoscopic Virtual Reality Display System and Conventional Computed Tomography Workstation in the Diagnosis and Characterization of Cerebral Arteriovenous Malformations.

It is difficult to accurately understand the angioarchitecture of cerebral arteriovenous malformations (CAVMs) before surgery using existing imaging methods. This study aimed to evaluate the ability of the stereoscopic virtual reality display system (SVRDS) to display the angioarchitecture of CAVMs by comparing its accuracy with that of the conventional computed tomography workstation (CCTW). Nineteen patients with CAVM confirmed on digital subtraction angiography (DSA) or during surgery were studied. Computed tomography angiography images in the SVRDS and CCTW were retrospectively analyzed by two experienced neuroradiologists using a double-blind method. Angioarchitectural parameters, such as the location and size of the nidus, type and number of the arterial feeders and draining veins, and draining pattern of the vessels, were recorded and compared. The diameter of the nidus ranged from 1.1 to 9 cm. Both CCTW and SVRDS correctly diagnosed the location of the nidus in 19 patients with CAVM. Among the 19 patients, 35 arterial feeders and 25 draining veins were confirmed on DSA and during surgery. With the DSA and intraoperative results as the gold standard bases, the CCTW misjudged one arterial feeder and one draining vein and missed three arterial feeders and two draining veins; meanwhile, the SVRDS missed only two arterial feeders. SVRDS had some advantages in displaying nidus, arterial branches, and draining veins of the CAVM compared with CCTW, as well as SVRDS could more intuitively display the overall angio-architectural spatial picture of CAVM.

Diagnostic value of multiple b-value diffusion-weighted imaging in discriminating the malignant from benign breast lesions.

OBJECTIVE: The conventional breast Diffusion-weighted imaging (DWI) was subtly influenced by microcirculation owing to the insufficient selection of the b values. However, the multiparameter derived from multiple b-value exhibits more reliable image quality and maximize the diagnostic accuracy. We aim to evaluate the diagnostic performance of stand-alone parameter or in combination with multiparameter derived from multiple b-value DWI in differentiating malignant from benign breast lesions. METHODS: A total of forty-one patients diagnosed with benign breast tumor and thirty-eight patients with malignant breast tumor underwent DWI using thirteen b values and other MRI functional sequence at 3.0 T magnetic resonance. Data were accepted mono-exponential, bi-exponential, stretched-exponential, aquaporins (AQP) model analysis. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of quantitative parameter or multiparametric combination. The Youden index, sensitivity and specificity were used to assess the optimal diagnostic model. T-test, logistic regression analysis, and Z-test were used. P value < 0.05 was considered statistically significant. RESULT: The ADCavg, ADCmax, f, and α value of the malignant group were lower than the benign group, while the ADCfast value was higher instead. The ADCmin, ADCslow, DDC and ADCAQP showed no statistical significance. The combination (ADCavg-ADCfast) yielded the largest area under curve (AUC = 0.807) with sensitivity (68.42%), specificity (87.8%) and highest Youden index, indicating that multiparametric combination (ADCavg-ADCfast) was validated to be a useful model in differentiating the benign from breast malignant lesion. CONCLUSION: The current study based on the multiple b-value diffusion model demonstrated quantitatively multiparametric combination (ADCavg-ADCfast) exhibited the optimal diagnostic efficacy to differentiate malignant from benign breast lesions, suggesting that multiparameter would be a promising non-invasiveness to diagnose breast lesions.

Deep Learning for Detection of Intracranial Aneurysms from Computed Tomography Angiography Images.

The accuracy of computed tomography angiography (CTA) image interpretation depends on the radiologist. This study aims to develop a new method for automatically detecting intracranial aneurysms from CTA images using deep learning, based on a convolutional neural network (CNN) implemented on the DeepMedic platform. Ninety CTA scans of patients with intracranial aneurysms are collected and divided into two datasets: training (80 subjects) and test (10 subjects) datasets. Subsequently, a deep learning architecture with a three-dimensional (3D) CNN model is implemented on the DeepMedic platform for the automatic segmentation and detection of intracranial aneurysms from the CTA images. The samples in the training dataset are used to train the CNN model, and those in the test dataset are used to assess the performance of the established system. Sensitivity, positive predictive value (PPV), and false positives are evaluated. The overall sensitivity and PPV of this system for detecting intracranial aneurysms from CTA images are 92.3% and 100%, respectively, and the segmentation sensitivity is 92.3%. The performance of the system in the detection of intracranial aneurysms is closely related to their size. The detection sensitivity for small intracranial aneurysms (≤ 3 mm) is 66.7%, whereas the sensitivity of detection for large (> 10 mm) and medium-sized (3-10 mm) intracranial aneurysms is 100%. The deep learning architecture with a 3D CNN model on the DeepMedic platform can reliably segment and detect intracranial aneurysms from CTA images with high sensitivity.

Prediction of outcomes by diffusion kurtosis imaging in patients with large (≥5 cm) hepatocellular carcinoma after liver resection: A retrospective study.

Purpose: To evaluate preoperative diffusion kurtosis imaging (DKI) in predicting the outcomes of large hepatocellular carcinoma (HCC) after liver resection (LR). Materials and methods: From January 2015 to December 2017, patients with a large (≥5cm) HCC who underwent preoperative DKI were retrospectively reviewed. The correlations of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) with microvascular invasion (MVI) or histological grade were analyzed. Cox regression analyses were performed to identify the predictors of recurrence-free survival (RFS) and overall survival (OS). A nomogram to predict RFS was established. P<0.05 was considered as statistically significant. Results: A total of 97 patients (59 males and 38 females, 56.0 ± 10.9 years) were included in this study. The MK, MD, and ADC values were correlated with MVI or histological grade (P<0.01). With a median follow-up time of 41.2 months (range 12-69 months), 67 patients (69.1%) experienced recurrence and 41 patients (42.3%) were still alive. The median RFS and OS periods after LR were 29 and 45 months, respectively. The 1-, 3-, and 5-year RFS and OS rates were 88.7%, 41.2%, and 21.7% and 99.0%, 68.3%, and 25.6%, respectively. MK (P<0.001), PVT (P<0.001), and ADC (P=0.033) were identified as independent predictor factors for RFS. A nomogram including the MK value for RFS showed the best performance, and the C-index was 0.895. Conclusion: The MK value obtained from DKI is a potential predictive factor for recurrence and poor survival, which could provide valuable information for guiding the efficacy of LR in patients with large HCC.

Magnetic resonance imaging features of a solitary fibrous tumor of the vulva: a case report.

Solitary fibrous tumors (SFTs) are commonly seen in the pleura. SFT involvement of the vulva is rare, and clinical diagnosis is mainly based on histopathological and immunohistochemical analyses. We herein describe the imaging features of a 69-year-old woman with an SFT of the vulva. The SFT was hypointense on T1-weighted images, similar to muscle; however, it showed inhomogeneous hyperintensity predominantly on fat-suppressed T2-weighted images. An area of low signal intensity was evident on T2-weighted images, and the tumor showed progressive enhancement in delayed phases. The tumor also displayed heterogeneous and prolonged, persistent enhancement, and serpentine vessels were present in the peritumoral area as signal voids. Pathological examination confirmed that the lesion was an atypical SFT originating from the vulva, and it was composed of spindle cells and perivascular and stromal hyalinization. This case reveals the characteristic imaging findings of vulvar SFT and their association with the relevant pathological findings, thus contributing to the primary diagnosis and preoperative evaluation of this potentially aggressive tumor.

Functional Connectivity Underlying Symptoms in Preschool Boys With Autism: A Resting-State Functional Magnetic Resonance Imaging Study.

Background: Single-sex children have been regarded as one of the best subjects to understand the abnormal development patterns of autism spectrum disorders (ASDs). However, the functional connectivity (FC) behind their symptoms is still unknown. Methods: Based on FC analysis, the acquired resting-state functional magnetic resonance imaging (rs-fMRI) data sets, including 86 boys with ASD and 54 normal controls (NC), were used to detect the neural synchronous activity between brain regions. Pearson correlation analysis was used to evaluate the relationship between the abnormal FC value and clinical features. Results: Individuals with ASD showed enhanced FC between the right calcarine and the right lingual gyrus (LG). The right medial orbital frontal cortex also showed increased FC with bilateral inferior temporal gyrus (ITG) [two-tailed, voxel-level p < 0.001, gaussian random field (GRF) correction, cluster-level p < 0.05]. We did not find a correlation between the abnormal FC value and clinical scales. Conclusion: Our study reveals a possible relationship between atypical visual attention and poor learning ability in subjects with ASD, and delayed social language development may be a secondary symptom to ASD.

Acid-Responsive Aggregated Gold Nanoparticles for Radiosensitization and Synergistic Chemoradiotherapy in the Treatment of Esophageal Cancer.

Radiotherapy and chemotherapy are limited by insufficient therapeutic efficacy of low-dose radiation and nonspecific drug biodistribution. Herein, an acid-responsive aggregated nanosystem (AuNPs-D-P-DA) loaded with doxorubicin (DOX) is designed for radiosensitization and synergistic chemoradiotherapy. In response to the acid microenvironment of esophageal cancer (EC), small-sized AuNPs-D-P-DA forms large-sized gold nanoparticle (AuNPs) aggregates in tumor tissues to hinder the backflow of AuNPs to the circulation, resulting in enhanced tumor accumulation and retention. Simultaneously, the AuNPs-based radiosensitization is significantly improved because of the high concentration and large size of intratumoral AuNPs, while DOX are delivered and released specifically into tumor cells triggered by the acid microenvironment for chemo-radio synergistic therapy. Acid-responsive AuNPs exacerbate radiation-induced DNA damage, cell apoptosis, cell cycle arrest, and low colony formation ability in vitro and enhance anti-tumor efficacy in vivo compared to un-responsive control. When combined with acid-responsive DOX, the therapeutic efficacy of the formulation is further improved by their synergistic effect. After the treatment of acid-responsive AuNPs plus radiotherapy, fatty acid metabolism is reprogrammed in xenograft models, which provides potential targets for further improvement of radiosensitization. In summary, the acid-responsive AuNPs-D-P-DA nanosystem leverages the radio- and chemotherapeutic synergies of AuNPs-sensitized X-ray irradiation and acid-responsive DOX in the treatment of EC.

Extracellular matrix-degrading STING nanoagonists for mild NIR-II photothermal-augmented chemodynamic-immunotherapy.

Regulation of stimulator of interferon genes (STING) pathway using agonists can boost antitumor immunity for cancer treatment, while the rapid plasma clearance, limited membrane permeability, and inefficient cytosolic transport of STING agonists greatly compromise their therapeutic efficacy. In this study, we describe an extracellular matrix (ECM)-degrading nanoagonist (dNAc) with second near-infrared (NIR-II) light controlled activation of intracellular STING pathway for mild photothermal-augmented chemodynamic-immunotherapy of breast cancer. The dNAc consists of a thermal-responsive liposome inside loading with ferrous sulfide (FeS2) nanoparticles as both NIR-II photothermal converters and Fenton catalysts, 2'3'-cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) as the STING agonist, and an ECM-degrading enzyme (bromelain) on the liposome surface. Mild heat generated by dNAc upon NIR-II photoirradiation improves Fenton reaction efficacy to kill tumor cells and cause immunogenic cell death (ICD). Meanwhile, the generated heat triggers a controlled release of cGAMP from thermal-responsive liposomes to active STING pathway. The mild photothermal activation of STING pathway combined with ICD promotes anti-tumor immune responses, which leads to improved infiltration of effector T cells into tumor tissues after bromelain-mediated ECM degradation. As a result, after treatment with dNAc upon NIR-II photoactivation, both primary and distant tumors in a murine mouse model are inhibited and the liver and lung metastasis are effectively suppressed. This work presents a photoactivatable system for STING pathway and combinational immunotherapy with improved therapeutic outcome.