Targeting anoikis resistance as a strategy for cancer therapy.

Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. Uncovering the mechanisms of anoikis resistance will provide details about cancer metastasis, and potential strategies against cancer cell dissemination and metastasis. Here, we summarize the principal elements and core molecular mechanisms of anoikis and anoikis resistance. We discuss the latest progress of how anoikis and anoikis resistance are regulated in cancers. Furthermore, we summarize emerging data on selective compounds and nanomedicines, explaining how inhibiting anoikis resistance can serve as a meaningful treatment modality against cancers. Finally, we discuss the key limitations of this therapeutic paradigm and possible strategies to overcome them. In this review, we suggest that pharmacological modulation of anoikis and anoikis resistance by bioactive compounds could surmount anoikis resistance, highlighting a promising therapeutic regimen that could be used to overcome anoikis resistance in cancers.

Epigenetic modification of ferroptosis by non-coding RNAs in cancer drug resistance.

The development of drug resistance remains a major challenge in cancer treatment. Ferroptosis, a unique type of regulated cell death, plays a pivotal role in inhibiting tumour growth, presenting new opportunities in treating chemotherapeutic resistance. Accumulating studies indicate that epigenetic modifications by non-coding RNAs (ncRNA) can determine cancer cell vulnerability to ferroptosis. In this review, we first summarize the role of chemotherapeutic resistance in cancer growth/development. Then, we summarize the core molecular mechanisms of ferroptosis, its upstream epigenetic regulation, and its downstream effects on chemotherapeutic resistance. Finally, we review recent advances in understanding how ncRNAs regulate ferroptosis and from such modulate chemotherapeutic resistance. This review aims to enhance general understanding of the ncRNA-mediated epigenetic regulatory mechanisms which modulate ferroptosis, highlighting the ncRNA-ferroptosis axis as a key druggable target in overcoming chemotherapeutic resistance.

In Situ Synthesis and Visualization of Membrane SNAP25 Nano-Organization.

Cryo-electron tomography (cryo-ET) can provide insights into the structure and states of natural membrane environments to explore the role of SNARE proteins at membrane fusion and understand the relationship between their subcellular localization/formation and action mechanism. Nevertheless, the identification of individual molecules in crowded and low signal-to-noise ratio membrane environments remains a significant challenge. In this study, cryo-ET is employed to image near-physiological state 293T cell membranes, specifically utilizing in situ synthesized gold nanoparticles (AuNPs) bound with cysteine-rich protein tags to single-molecularly labeled synaptosomal-associated protein 25 (SNAP25) on the membrane surface. The high-resolution images reveal that SNAP25 is predominantly located in regions of high molecular density within the cell membrane and aggregates into smaller clusters, which may increase the fusion efficiency. Remarkably, a zigzag arrangement of SNAP25 is observed on the cell membrane. These findings provide valuable insights into the functional mechanisms of SNARE proteins.

CdWO4 Sub-1 nm Nanowires for Visible-light CO2 Photoreduction.

Quantum size effect usually causes energy level splitting and band broadening as material size decreases. However, this may change again by the surface adsorbents, doping and defects, which rarely attracts much attention. Herein, CdWO4 sub-1 nm nanowires (SNWs) with oleylamine adsorption, PO43--doping and oxygen defects are synthesized by combining Cd(CH3COO)2, H3PW12O40 (PW12) and oleylamine (abbreviated as PO43--CdWO4-X SNWs). Compared with bulk CdWO4, they exhibit unexpected absorption spectra (extended from 292 nm to 453 nm) and bandgap (reduced from 4.25 eV to 2.74 eV), thus bringing remarkable visible-light CO2 photoreduction activity. Under 410 nm LED light irradiation, PO43--CdWO4-40 SNWs exhibit the highest photocatalytic performance with a CO2-to-CO generation rate of 1685 µmol g-1 h-1. Density functional theory (DFT) calculations demonstrate the adsorbed oleylamine raises the valence band and enhances the adsorption of reaction substrate and intermediates, thus decreasing their reduction energy barriers. Furthermore, PO43--doping and oxygen defects will generate defect energy band below the conduction band of PO43--CdWO4-40 SNWs, resulting in remarkable visible light absorption and superior photocatalytic CO2 reduction performance. This work highlights the significant impacts of surface adsorbents, doping and defects on the physicochemical and catalytic properties of sub-nano materials.

CT-based radiomics nomogram for prediction of survival after transarterial chemoembolization with drug-eluting beads in patients with hepatocellular carcinoma and portal vein tumor thrombus.

OBJECTIVES: To develop and validate a CT-based radiomics model for the prediction of the overall survival (OS) of patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT) treated with drug-eluting beads transarterial chemoembolization (DEB-TACE). METHODS: Patients were retrospectively enrolled from two institutions for the constitution of training (n = 69) and validation (n = 31) cohorts with a median follow-up of 15 months. A total of 396 radiomics features were extracted from each baseline CT image. Features selected by variable importance and minimal depth were used for random survival forest model construction. The performance of the model was assessed using the concordance index (C-index), calibration curves, integrated discrimination index (IDI), net reclassification index (NRI), and decision curve analysis. RESULTS: Type of PVTT and tumor number were proved to be significant clinical indicators for OS. Arterial phase images were used to extract radiomics features. Three radiomics features were selected for model construction. The C-index for the radiomics model was 0.759 in the training cohort and 0.730 in the validation cohort. To improve the predictive performance, clinical indicators were integrated into the radiomics model to form a combined model with a C-index of 0.814 in the training cohort and 0.792 in the validation cohort. The IDI was significant in both cohorts for the combined model versus the radiomics model in predicting 12-month OS. CONCLUSIONS: Type of PVTT and tumor number affected the OS of HCC patients with PVTT treated with DEB-TACE. Moreover, the combined clinical-radiomics model had a satisfactory performance. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics nomogram, which consisted of 3 radiomics features and 2 clinical indicators, was recommended to predict 12-month overall survival of patients with hepatocellular carcinoma and portal vein tumor thrombus initially treated with drug-eluting beads transarterial chemoembolization. KEY POINTS: • Type of portal vein tumor thrombus and tumor number were significant predictors of the OS. • Integrated discrimination index and net reclassification index provided a quantitative evaluation of the incremental impact added by new indicators for the radiomics model. • A nomogram based on a radiomics signature and clinical indicators showed satisfactory performance in predicting OS after DEB-TACE.

A systematic review of prognosis predictive role of radiomics in pancreatic cancer: heterogeneity markers or statistical tricks?

OBJECTIVES: We aimed to systematically evaluate the prognostic prediction accuracy of radiomics features extracted from pre-treatment imaging in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Radiomics literature on overall survival (OS) prediction of PDAC were all included in this systematic review. A further meta-analysis was performed on the effect size of first-order entropy. Methodological quality and risk of bias of the included studies were assessed by the radiomics quality score (RQS) and prediction model risk of bias assessment tool (PROBAST). RESULTS: Twenty-three studies were finally identified in this review. Two (8.7%) studies compared prognosis prediction ability between radiomics model and TNM staging model by C-index, and both showed a better performance of the radiomics. Twenty-one (91.3%) studies reported significant predictive values of radiomics features. Nine (39.1%) studies were included in the meta-analysis, and it showed a significant correlation between first-order entropy and OS (HR 1.66, 95%CI 1.18-2.34). RQS assessment revealed validation was only performed in 5 (21.7%) studies on internal datasets and 2 (8.7%) studies on external datasets. PROBAST showed that 22 (95.7%) studies have a high risk of bias in participants because of the retrospective study design. CONCLUSION: First-order entropy was significantly associated with OS and might improve the accuracy of PDAC prognosis prediction. Existing studies were poorly validated, and it should be noted in future studies. Modification of PROBAST for radiomics studies is necessary since the strict requirements of prospective study design may not be applicable to the demand for a large sample size in the model construction stage. KEY POINTS: • Radiomics based on the primary lesion holds great potential for prognosis prediction. First-order entropy was significantly associated with the overall survival of PDAC and might improve the accuracy of current PDAC prognosis prediction. • We strongly recommend that at least an internal validation should be conducted in any radiomics study. Attention should be paid to the complex relationships between radiomics features. • Due to the close relationship between radiomics and big data, the strict requirement of prospective study design in PROABST may not be appropriate for radiomics studies. A balance between study types and sample sizes for radiomics studies needs to be found in the model construction stage.

Management of Advanced Pancreatic Cancer through Stromal Depletion and Immune Modulation.

Pancreatic cancer is one of the leading causes of cancer-related deaths worldwide. Unfortunately, therapeutic gains in the treatment of other cancers have not successfully translated to pancreatic cancer treatments. Management of pancreatic cancer is difficult due to the lack of effective therapies and the rapid development of drug resistance. The cytotoxic agent gemcitabine has historically been the first-line treatment, but combinations of other immunomodulating and stroma-depleting drugs are currently undergoing clinical testing. Moreover, the treatment of pancreatic cancer is complicated by its heterogeneity: analysis of genomic alterations and expression patterns has led to the definition of multiple subtypes, but their usefulness in the clinical setting is limited by inter-tumoral and inter-personal variability. In addition, various cell types in the tumor microenvironment exert immunosuppressive effects that worsen prognosis. In this review, we discuss current perceptions of molecular features and the tumor microenvironment in pancreatic cancer, and we summarize emerging drug options that can complement traditional chemotherapies.

Cylindrical vector beam multiplexing for radio-over-fiber communication with dielectric metasurfaces.

Radio-over-fiber (ROF) technology, loading microwave signal on light beams, has attracted considerable attention in wireless access network for its superiority in processing high-frequency microwave signals. Multiplexing for achieving high-capacity density, however, remains elusive in ROF communication because the optical microwave occupies large bandwidth. Here, we introduce a cylindrical vector beam (CVB) multiplexing for ROF communication with dielectric Pancharatnam-Berry phase-based metasurfaces (PBMs). CVBs, a structured light beam possessing spatially nonuniform polarization distribution and carrying vector mode, provide an additional multiplexing dimension for optical communication with the advantages of weak scintillation in free-space and low mode injure in few-mode-fiber. Exploiting the spin-orbit interaction of the PB phase, we construct PBMs to manipulate CVBs, which show broadband working wavelengths ranging from C- to L-band. After 3 m free-space propagation, two multiplexed CVBs carrying 100 GHz microwave are successfully demultiplexed, and the 100 GHz ROF communication with 12 Gbit/s QPSK-OFDM signals is realized. The crosstalk of the multiplexed CVBs is less than -15.13 dB, and the bit-error-rates (BERs) are below 3.26 × 10-5. With 5 km few-mode-fiber transmission, the CVBs are also demultiplexed with the BERs of 6.51 × 10-5. These results indicate that CVB is not only capable of free-space transmission but also available for few-mode-fiber transmission, which might pave new avenues for the multiplexing of ROF communications.

[Circumcision with no-flip Shang Ring technique for adult males: analysis of 168 cases].

OBJECTIVE: To observe the clinical effects of the no-flip procedure with the Chinese Shang Ring when circumcising adult males with redundant prepuce or phimosis, and to discuss its advantages and disadvantages. METHODS: Using the no-flip Shang Ring technique, we performed circumcision for 167 adult males aged 18 -72 (mean 27.8) years with redundant prepuce or phimosis, and analyzed the clinical data, including the operation time, postoperative complications, ring-removal time, and postoperative appearance of the penis. RESULTS: Complete follow-up data of 94 cases (56.29%) were obtained. The mean operation time was (5.03 +/- 0.71) minutes and the average ring-removal time was (18.83 +/- 6.70) days. The primary postoperative complications were edema (35 cases [37.23%] at 2 weeks and 9 cases [9.57%] at 4 weeks), including 2 severe cases (2.13%), and infection (3 cases [3.19%]). The pain scores were 2.01 +/- 2.46 during the procedure and 4.52 +/- 2.53 at 24 hours postoperatively. Slipping of the outer ring occurred in 1 case, and delayed removal of the ring in 30 cases (31.91%). CONCLUSION: Adult male circumcision with the no-flip Shang Ring technique is recommended for its short operation time, simple procedure, fewer postoperative complications, less pain, and better incision appearance.

Clinical Characteristics of Adrenal Hemangioma.

Objective: Adrenal hemangioma (AH) is a rare, benign adrenal tumor often detected incidentally by imaging. This retrospective study aimed to investigate the clinical characteristics of AH, including clinical and diagnostic imaging features, to improve the recognition and understanding of AH. Methods: We retrospectively analyzed the medical records of patients diagnosed with AH at Peking Union Medical College Hospital between 2008 and 2022. Clinical manifestations, adrenal hormone levels, imaging findings, treatment approaches, and pathological results were collected and analyzed. Results: Of the 7140 adrenal tumor patients, 40 (0.56%) had AH confirmed postoperatively. The mean age at diagnosis was 53.9 years, with a female predominance. Most (70%) were asymptomatic and diagnosed incidentally. Misdiagnosis before surgery was common, most frequently as pheochromocytoma. Imaging characteristics, especially enhanced computed tomography, revealed distinct features based on tumor size. Surgery was the main treatment, with laparoscopic adrenalectomy preferred. Conclusion: This study elucidates the clinical characteristics of AH, including demographics, diagnostic challenges, and imaging features. AH often presents incidentally and is frequently misdiagnosed preoperatively. Recognizing distinct imaging characteristics and appropriate surgical management can enable accurate diagnosis and optimal treatment.

Prediction of Hepatic Encephalopathy After Transjugular Intrahepatic Portosystemic Shunt Based on CT Radiomic Features of Visceral Adipose Tissue.

RATIONALE AND OBJECTIVES: To evaluate the performance and clinical utility of CT radiomic features of visceral adipose tissue (VAT) in the prediction of hepatic encephalopathy (HE) after transjugular intrahepatic portosystemic shunt (TIPS). MATERIALS AND METHODS: This multi-center study was retrospectively designed. Patients with cirrhosis who underwent TIPS were recruited from January 2015 to December 2020. Pre-TIPS contrast-enhanced CT images were collected for VAT segmentation and radiomic feature extraction. Least absolute shrinkage and selection operator regression with ten-fold cross-validation was performed to reduce dimension. Logistic regression with regularization, support vector machine, and random forest were used for model construction. RESULTS: A total of 130 patients (90 men; mean age, 54 ± 11 years) were finally enrolled. The cohort was split into 85 patients for the training set (58 men; mean age, 53 ± 12 years) with 19 HE, 21 patients for the internal test set (17 men; mean age, 53 ± 11 years) with 5 HE, and 24 patients for the external test set (15 men; mean age, 55 ± 11 years). Ten radiomic features and C-reactive protein constituted radiomic-clinical models with the best performance. The average area under the receiver operating characteristic curve is 0.97 in the training set and 0.84 in the test sets. For a fixed sensitivity of 0.90, the specificity and negative predictive value of the model is 0.63 and 1.00, respectively; while for a fixed specificity of 0.90, the sensitivity and positive predictive value is 0.60 and 0.75, respectively. CONCLUSION: Machine learning models based on CT radiomic features extracted from VAT can predict post-TIPS HE with satisfactory performance. CLINICAL RELEVANCE STATEMENT: Our machine learning models based on CT radiomic features of visceral adipose tissue in patients with cirrhosis may assist in predicting hepatic encephalopathy after transjugular intrahepatic portosystemic shunt, indicating its potential in patient selection and clinical decision-making. KEY POINTS: Radiomics of visceral adipose tissue provide great help in predicting hepatic encephalopathy after transjugular intrahepatic portosystemic shunt. The clinical-radiomic models showed satisfactory performance with an average area under the receiver operating characteristic curve of 0.84. The model can hypothetically provide 90% sensitivity and 100% negative predictive value for guiding patients who are considering transjugular intrahepatic portosystemic shunt.

Selective Nanoblocker of Cellular Stress Response for Improved Drug-Free Tumor Therapy.

Nanotechnology-based drug-free therapeutic systems using external stimuli can avoid the inherent side effects of drugs and become an attractive therapeutic strategy. However, the cellular stress responses (CSR) are activated encounter with external stimuli, which greatly weaken the efficacy of the drug-free antitumor. Thus, this work proposes a CSR regulation strategy and synthesizes the glucose oxidase (GOx)-modified Cu3 BiS3 nanosheets (CBSG NSs) encapsulated by calcium carbonate (CBSG@CaCO3 ) as the novel drug-free nanoagent. The CBSG@CaCO3 not only cause external stimuli such as energy consumption and oxidative stress damage, but also can destroy the CSR mechanism to guarantee optimal efficacy of starvation-chemodynamic therapy (ST-CDT). In tumor cells, the CaCO3 shell layer of CBSG@CaCO3 is rapidly degraded, releasing the slowly degradable CBSG NSs with NIR-II photothermal properties that accelerate the production of external stimuli under laser irradiation. Meanwhile, CaCO3 can block CSR to disrupt the adaptive viability of cancer cells by inhibiting expression of P27 and NRF2. Importantly, the CSR regulation achieves selective treatment on tumor cells based on the difference in physiological conditions between cancer cells and normal cells. This drug-free cancer therapy with selectivity improves the problem of poor efficacy under the action of CSR, which offers a new avenue in the cancer-related disease treatment.

CT-based radiomics model for preoperative prediction of hepatic encephalopathy after transjugular intrahepatic portosystemic shunt.

OBJECTIVE: To develop and evaluate a machine learning-based CT radiomics model for the prediction of hepatic encephalopathy (HE) after transjugular intrahepatic portosystemic shunt (TIPS). METHODS: A total of 106 patients who underwent TIPS placement were consecutively enrolled in this retrospective study. Regions of interest (ROIs) were drawn on unenhanced, arterial phase, and portal venous phase CT images, and radiomics features were extracted, respectively. A radiomics model was established to predict the occurrence of HE after TIPS by using random forest algorithm and 10-fold cross-validation. Receiver operating characteristic (ROC) curves were performed to validate the capability of the radiomics model and clinical model on the training, test and original data sets, respectively. RESULTS: The radiomics model showed favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.899 (95% CI, 0.848 to 0.951), while in the test cohort, it was confirmed with an AUC of 0.887 (95% CI, 0.760 to 1.00). After applying this model to original data set, it had an AUC of 0.955 (95% CI, 0.896 to 1.00). A clinical model was also built with an AUC of 0.649 (95% CI, 0.530 to 0.767) in the original data set, and a Delong test demonstrated its relative lower efficiency when compared with the radiomics model (p < 0.05). CONCLUSION: Machine learning-based CT radiomics model performed better than traditional clinical parameter-based models in the prediction of post-TIPS HE. ADVANCES IN KNOWLEDGE: Radiomics model for the prediction of post-TIPS HE was built based on feature extraction from routine acquired pre-operative CT images and feature selection by random forest algorithm, which showed satisfied performance and proved the advantages of machine learning in this field.

A deep learning algorithm to improve readers' interpretation and speed of pancreatic cystic lesions on dual-phase enhanced CT.

PURPOSE: To develop a deep learning model (DLM) to improve readers' interpretation and speed in the differentiation of pancreatic cystic lesions (PCLs) on dual-phase enhanced CT, and a low contrast media dose, external testing set validated the model. MATERIALS AND METHODS: Dual-phase enhanced CT images of 363 patients with 368 PCLs obtained from two centers were retrospectively assessed. Based on the examination date, a training and validation set of 266 PCLs, an internal testing set of 52 PCLs were designated from center 1. An external testing set included 50 PCLs from center 2. Clinical and radiological characteristics were compared. The DLM was developed using 3D specially designed densely connected convolutional networks for PCL differentiation. Radiomic features were extracted to build a traditional radiomics model (RM). Performance of the DLM, traditional RM, and three readers was compared. RESULTS: The accuracy for differential diagnosis was 0.904 with DLM, which was the highest in the internal testing set. Accuracy differences between the DLM and senior radiologist were not significant both in the internal and external testing set (both p > 0.05). With the help of the DLM, the accuracy and specificity of the junior radiologist were significantly improved (all p < 0.05), and all readers' diagnostic time was shortened (all p < 0.05). CONCLUSION: The DLM achieved senior radiologist-level performance in differentiating benign and malignant PCLs which could improve the junior radiologist's interpretation and speed of PCLs on CT.

Assessment of Response to Chemotherapy in Pancreatic Cancer with Liver Metastasis: CT Texture as a Predictive Biomarker.

In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response (p < 0.05 vs. p = 0.398, p = 0.142, and p = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP (p = 0.016) and confirmed in the validation cohort (p = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.

Development of a Prognostic Nomogram in Hepatocellular Carcinoma with Portal Vein Tumor Thrombus Following Trans-Arterial Chemoembolization with Drug-Eluting Beads.

OBJECTIVE: To develop and validate a prognostic nomogram in eastern patients with hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT) receiving trans-arterial chemoembolization with drug-eluting beads (DEB-TACE). METHODS: This retrospective study included 200 patients with training cohort (n = 118) from institution 1 and test cohort (n = 82) from institution 2. All these patients received first-line DEB-TACE between October 2016 and October 2018. Multivariate Cox proportional hazard regression analysis was performed on the training cohort to reveal the independent prognostic factors, and then prognostic nomograms were developed. In order to evaluate the performance of the nomogram comprehensively in both the training and test cohorts, C-index, Kaplan-Meier curve with Log rank test, receiver operating characteristic curve (ROC), calibration plot, and decision curve analysis (DCA) were performed. RESULTS: Tumor number, serum γ-glutamyl transferase (GGT) level, and level of PVTT were independent risk factors of prognosis. A nomogram was constructed to predict 6-, 12- and 18-month overall survival (OS) based on these identified prognostic factors. C-indexes of the nomogram were 0.88 (95% confidence interval [CI], 0.79-0.97) in the training cohort and 0.87 (95% CI, 0.75-0.99) in the test cohort. The Kaplan-Meier curve analysis showed that the nomogram was able to separate patients into low- and high-risk subgroups. ROC curves for the nomogram at 6-, 12- and 18-month showed satisfied discrimination, with an AUC of 0.765, 0.803 and 0.809 in the training cohort, respectively, and 0.772, 0.724 and 0.746 in the test cohort, respectively. The calibration curve demonstrated good agreement between predicted and actual survival rates in the training and test cohorts. The decision curve showed good performance of the nomogram in terms of clinical application. CONCLUSION: We developed and validated a nomogram that was accurate and clinically useful in eastern patients with HBV-associated HCC with PVTT who underwent DEB-TACE.

PET-MR Imaging and MR Texture Analysis in the Diagnosis of Pancreatic Cysts: A Prospective Preliminary Study.

RATIONALE AND OBJECTIVES: Our aim was to evaluate the capability of textural and metabolic parameters measured at pretreatment 18F-fluorodeoxyglucose Positron emission tomography (PET)-MR in differentiating malignant from benign pancreatic cystic lesions. MATERIALS AND METHOD: Forty consecutive patients were prospectively enrolled in this study. They underwent simultaneous PET-MR for the diagnosis of pancreatic cysts. Thirty texture parameters were extracted from manually contoured axial T2-weighted imaging with fat suppression (T2FS) and apparent diffusion coefficient images, respectively. Maximal and mean standardized uptake values (SUVmax and SUVmean, respectively) of pancreatic cysts were measured at PET-MR imaging. The Mann-Whitney test was used to compare both textural and metabolic parameters between benign and malignant group. RESULTS: FDG uptake was significantly higher in patients with malignant pancreatic cysts (SUVmaxp = 0.002, SUVmeanp < 0.001). Malignant cysts showed significantly lower standard deviation for spatial scaling factor at 3-6mm on T2FS images and lower skewness for spatial scaling factor at 2-4mm on apparent diffusion coefficient images (p < 0.01). SUVmean had the highest Area under the curve of 0.892 on receiver-operating characteristic analysis with a sensitivity, specificity, and accuracy of 88.9%, 87.1%, and 87.6%, respectively. When metabolic and textural features were combined into a single diagnostic model, the AUC increased to 0.961, with a sensitivity, specificity, and accuracy of 88.9%, 96.8%, and 95.0%, respectively. CONCLUSION: Our study implied that PET-MR showed no obvious advantages over traditional PET-related imaging in differentiating malignant from benign pancreatic cystic lesions. Diagnostic model based on the combination of metabolic and textural parameters showed satisfactory performance.

Unresectable pancreatic ductal adenocarcinoma: Role of CT quantitative imaging biomarkers for predicting outcomes of patients treated with chemotherapy.

OBJECTIVES: The primary aim of this study was to determine if computed tomographic (CT) texture analysis measurements of the tumor are independently associated with progression-free survival (PFS) and overall survival (OS) in patients with unresectable pancreatic ductal adenocarcinoma (PDAC), including both unresectable locally advanced and metastatic PDAC, who were treated with chemotherapy. METHODS: After an institutional review board waiver was obtained, contrast material-enhanced CT studies in 41 patients with unresectable PDAC who underwent contrast-enhanced CT before chemotherapy between 2014 and 2017 were analyzed in terms of tumor texture, with quantification of mean gray-level intensity (Mean), entropy, mean of positive pixels (MPP), kurtosis, standard deviation (SD), and skewness for fine to coarse textures (spatial scaling factor (SSF) 0-6, respectively). The association between pretreatment and posttreatment texture parameters, as well as Δ value (difference between posttreatment and pretreatment texture parameters), and survival time was assessed by using Cox proportional hazards models and Kaplan-Meier analysis. RESULTS: Findings from the multivariate Cox model indicated that tumor size, tumor SD (HR, 0.942; 95% CI: 0.898, 0.988) and skewness (HR, 0.407; 95% CI: 0.172, 0.962) measurements with SSF = 3, and tumor SD (HR, 0.958; 95% CI: 0.92, 0.997) measurements with SSF = 4 were significantly and independently associated with PFS, while tumor size and tumor SD (HR, 0.928; 95% CI: 0.882, 0.976) measurements with SSF = 3 were significantly and independently associated with OS. None of the post-therapy texture parameters or Δ value had a significant association with OS or PFS in multivariate Cox regression models. Medium SD (SSF = 3) of more than 38.38 and coarse SD (SSF = 4) of more than 40.67 were associated with longer PFS after chemotherapy (for SSF = 3, median PFS was 10.0 vs 6.0 months [P = 0.024], and for SSF = 4, median PFS was 12.0 vs 6.0 months [P = 0.003]). SD of 38.38 or greater (SSF = 3) as a dichotomized variable was a significant positive prognostic factor for OS (median OS, 20.0 vs 9.0 months [P = 0.04]). Survival models that included a combination of pretreatment SD (SSF = 3) with tumor size, had the potential to perform better than SD alone, while having no statistical significance in this study (area under the ROC curve, 0.756 vs 0.715 [P = 0.066]). CONCLUSIONS: Pretreatment CT quantitative imaging biomarkers from texture analysis are associated with PFS and OS in patients with unresectable PDAC who were treated with chemotherapy, and the combination of pretreatment texture parameters and tumor size have the potential to perform better in survival models than imaging biomarker alone.

Superfine CoNi alloy embedded in Al2O3 nanosheets for efficient tandem catalytic reduction of nitroaromatic compounds by ammonia borane.

Aromatic amino compounds are important and universally used chemical intermediates in a wide range of industrial fields. Thus, their production with high efficiency and selectivity under ambient conditions is expected and demanded in modern industry. Herein, a series of superfine CoNi alloy nanoparticles embedded in Al2O3 nanosheet (CoxNi1-x/Al2O3, where x represents the content of Co in the precursor) catalysts was fabricated from CoNiAl-LDH and used to catalyze the tandem dehydrogenation of ammonia borane (AB) and hydrogenation of nitroaromatics to the corresponding amines. Systematic experiments indicate that the composition, size, morphology and catalytic performance of the CoxNi1-x/Al2O3 catalysts can be easily controlled by changing the content of Ni in the CoNiAl-LDH precursor. Particularly, Co0.67Ni0.33/Al2O3 exhibited the best tandem catalytic performance among the six samples. This as-prepared catalyst not only showed a moderate turn-over-frequency value (TOF: 34.5 molH2 molCo0.67Ni0.33-1 min-1 at 298 K without base or additives) and relatively low activation energy (32.4 kJ mol-1) for the dehydrogenation of AB, but also superior catalytic activity (conversion yield reaching up to 100%) and selectivity (>99%) for the tandem reductive transformation of in excess of sixteen types of nitroaromatics to aromatic amines. Density functional theory (DFT) calculations suggest that the construction of the CoNi alloy optimized the electronic structure with respect to the pure component, promoting its activity for AB hydrolysis and nitroaromatics hydrogenation. Finally, the catalyst could be easily recycled using a magnet due to the magnetic properties of the Co0.67Ni0.33 alloy.

Superaerophobic P-doped Ni(OH)2/NiMoO4 hierarchical nanosheet arrays grown on Ni foam for electrocatalytic overall water splitting.

Transition metal (TM) oxides and hydroxides are one of the important candidates for the development of durable and low-cost electrocatalysts towards water splitting. The key issue is exploring effective methods to improve their electrocatalytic activity. Herein, we report a new type of P-doped Ni(OH)2/NiMoO4 hierarchical nanosheet array (abbr. P-Ni(OH)2/NiMoO4) grown on Ni foam (NF), which can act as a highly efficient electrocatalyst towards overall water splitting. Such a composite was obtained by a three-step preparation process. In the first two hydrothermal reactions, the crystalline Ni(OH)2 hierarchical nanosheet arrays were grown on NF and then the low crystallinity NiMoO4 was grafted on the Ni(OH)2 nanosheets. In the third phosphorization step, P element was doped into the composite Ni(OH)2/NiMoO4. Electrocatalytic experiments show that P-Ni(OH)2/NiMoO4 possesses a smaller overpotential (60 mV) and lower Tafel slope (130 mV dec-1) toward HER in 1 M KOH. When it was employed as an integrated water splitting catalyst, only a potential of 1.55 V was required to achieve a current density of 10 mA cm-2. This catalytic activity is even better than those of electrolyzers constructed with noble metals Pt/C∥IrO2. The superior electrocatalytic performance of P-Ni(OH)2/NiMoO4 can be attributed to the high quality of crystalline Ni(OH)2 nanosheet arrays grown on NF, which dramatically improve the conductivity. Furthermore, the hierarchical structure not only increases the surface area and exposes more catalytically active sites, but also provides a superaerophobic surface, which helps to accelerate the release of generated bubbles. Moreover, the synergistic effects between P-Ni(OH)2 and P-NiMoO4 efficiently promote the HER and OER processes also. This work may suggest new a way to explore TM oxide/hydroxide-based durable electrocatalysts with highly efficient electrocatalytic activities towards overall water splitting.