Deep learning model based on endoscopic images predicting treatment response in locally advanced rectal cancer undergo neoadjuvant chemoradiotherapy: a multicenter study.

PURPOSE: Neoadjuvant chemoradiotherapy has been the standard practice for patients with locally advanced rectal cancer. However, the treatment response varies greatly among individuals, how to select the optimal candidates for neoadjuvant chemoradiotherapy is crucial. This study aimed to develop an endoscopic image-based deep learning model for predicting the response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. METHODS: In this multicenter observational study, pre-treatment endoscopic images of patients from two Chinese medical centers were retrospectively obtained and a deep learning-based tumor regression model was constructed. Treatment response was evaluated based on the tumor regression grade and was defined as good response and non-good response. The prediction performance of the deep learning model was evaluated in the internal and external test sets. The main outcome was the accuracy of the treatment prediction model, measured by the AUC and accuracy. RESULTS: This deep learning model achieved favorable prediction performance. In the internal test set, the AUC and accuracy were 0.867 (95% CI: 0.847-0.941) and 0.836 (95% CI: 0.818-0.896), respectively. The prediction performance was fully validated in the external test set, and the model had an AUC of 0.758 (95% CI: 0.724-0.834) and an accuracy of 0.807 (95% CI: 0.774-0.843). CONCLUSION: The deep learning model based on endoscopic images demonstrated exceptional predictive power for neoadjuvant treatment response, highlighting its potential for guiding personalized therapy.

Tong-Xie-Yao-Fang induces mitophagy in colonic epithelial cells to inhibit colitis-associated colorectal cancer.

ETHNOPHARMACOLOGICAL RELEVANCE: Based on the core pathogenesis of hepatosplenic disorder and qi transformation disorder in ulcerative colitis, Tong-Xie-Yao-Fang (TXYF) is a classical traditional Chinese medicine commonly used to treat ulcerative colitis. Our study revealed that it has the potential to prevent colitis-associated colorectal cancer, which embodies the academic concept in traditional Chinese medicine of treating the disease before it develops. AIM OF THE STUDY: This study was aimed at evaluating the therapeutic role of TXYF in treating colitis-associated colorectal cancer and exploring its possible underlying mechanisms. MATERIALS AND METHODS: A colitis-associated colorectal cancer model was established in mice using azoxymethane and dextran sulfate sodium salt to examine the therapeutic effect of TXYF. The mouse body weights were observed. Hematoxylin-eosin staining was used to evaluate mouse colon histopathology. Colon cancer cells and colon epithelial cells were used to explore the potential molecular mechanisms. The proliferation and apoptosis of cells were detected by CCK8 and cell colony assays, flow cytometry and western blotting. The epithelial-mesenchymal transition (EMT) and mitophagy markers were examined by immunohistochemistry, western blotting, quantitative real-time PCR and immunofluorescence staining. RESULTS: TXYF inhibited the tumorigenesis of mice with colitis-associated colorectal cancer and the growth of inflammatory colon cells. TXYF induced mitophagy in colon cancer cells through the PTEN-induced putative kinase 1 (PINK1)/Parkin pathway to reverse EMT, which was consistent with the results in mice with colitis-associated colorectal cancer. CONCLUSIONS: The results of the present study demonstrated that TXYF effectively inhibited the progression of colitis-associated colorectal cancer through the PINK1/Parkin pathway, which provides new evidence for prevention strategies for this disease.

Integrating Tumor and Nodal Radiomics to Predict the Response to Neoadjuvant Chemotherapy and Recurrence Risk for Locally Advanced Gastric Cancer.

AIMS: To develop and evaluate machine learning models using tumor and nodal radiomics features for predicting the response to neoadjuvant chemotherapy (NAC) and recurrence risk in locally advanced gastric cancer (LAGC). BACKGROUND: Early and accurate response prediction is vital to stratify LAGC patients and select proper candidates for NAC. OBJECTIVE: A total of 218 patients with LAGC undergoing NAC followed by gastrectomy were enrolled in our study and were randomly divided into a training cohort (n = 153) and a validation cohort (n = 65). METHODS: We extracted 1316 radiomics features from the volume of interest of the primary lesion and maximal lymph node on venous phase CT images. We built 3 radiomics signatures for distinguishing good responders and poor responders based on tumor radiomics (TR), nodal radiomics (NR), and a combination of the two (TNR), respectively. A nomogram was then developed by integrating the radiomics signature and clinical factors. Kaplan- Meier survival curves were used to evaluate the prognostic value of the nomogram. RESULTS: The TNR signature achieved improved predictive value, with AUCs of 0.755 and 0.744 in the training and validation cohorts. Our proposed nomogram model (TNRN) showed a good performance for GR prediction in the prediction efficacy, calibration ability, and clinical benefit, with AUCs of 0.779 and 0.732 in the training and validation cohorts, superior to the clinical model. Moreover, the TNRN could accurately classify the patients into high-risk and low-risk groups in both training and validation cohorts with regard to postoperative recurrence and metastasis. CONCLUSION: The TNRN performed well in identifying good responders and provided valuable information for predicting progression-free survival time (PFS) in patients with LAGC who underwent NAC.

Adverse events and efficacy of second-round CAR-T cell therapy in relapsed pediatric B-ALL.

OBJECTIVE: Chimeric antigen receptor (CAR) T-cell therapy has transformed the treatment approach for pediatric patients suffering from relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL). However, there was a paucity of data on the challenges associated with second-round CAR-T therapy in this population. METHODS: Medical records of nine pediatric patients who received second-round CAR-T therapy in a single center from June 2019 to May 2023 were analyzed. Throughout the course of the clinical trial, we evaluated adverse events including CRS, CRES, infections, hematologic toxicity, and organ injury, as well as CAR-T responses. RESULTS: Except for one patient who chose CART therapy due to testicular relapse, the remaining patients had indications for CAR-T therapy due to relapse with bone marrow alone or combined with other site. There were no difference between the transfusion dose of CART1 and CART2. No differences of incidence and grade of CRS was found between the first-round CAR-T therapy (CART1) and second-round CAR-T therapy (CART2). Additionally, we found that the incidence of CRES was higher for CART1(3/9,33.3%) than CART2(1/9,11.1%). Our findings revealed that there were no differences of IL-2, IL-4, IL-6, IL-10, IFN-γ, and TNF-α between CART1 and CART2, but the peak level of IL-17A was significantly higher in patients receiving CART1 compared to those receiving CART2 (p = .011). Early and late infection rates after CART1 were higher than CART2. Based on the dynamic changes of ANC, hemoglobin and platelet, ANC, and platelet were reduced obviously post CART. It seems that the incidences of severe thrombocytopenia and severe anemia were higher in the CART1 group compared to CART2. The MRD-negative CR rates for CART1 and CART2 are 100% and 44.4%, respectively (p = .029). All patients experienced events (relapse, chemotherapy, transplantation, or death) after receiving CART2, including one died, three discharged automatically, and the remaining five patients survived. CONCLUSION: Although the remission rate of CART2 is not as high as the CART1 due to the severity of the disease, its safety regarding CRS, CRES, infections, and organ injury is still excellent. Therefore, CART2 remains a viable option for treating pediatric relapsed B-ALL.

Development and validation of multiparametric models based on computed tomography enterography to determine endoscopic activity and surgical risk in patients with Crohn's disease: A multi-center study.

Objective: To develop novel multiparametric models based on computed tomography enterography (CTE) scores to identify endoscopic activity and surgical risk in patients with Crohn's disease (CD). Methods: We analyzed 171 patients from 3 hospitals. Correlations between CTE outcomes and endoscopic scores were assessed using Spearman's rank correlation analysis. Predictive models for moderate to severe CD were developed, and receiver operating characteristic (ROC) curves were constructed to determine the area under the ROC curve (AUC). A combined nomogram based on CTE scores and clinical variables was also developed for predicting moderate to severe CD and surgery. Results: CTE scores were significantly correlated with endoscopy scores at the segment level. The global CTE score was an independent predictor of severe (HR = 1.231, 95% CI: 1.048-1.446, p = 0.012) and moderate-to-severe Simplified Endoscopic Scores for Crohn's Disease (SES-CD) (HR = 1.202, 95% CI: 1.090-1.325, p < 0.001). The nomogram integrating CTE and clinical data predicted moderate to severe SES-CD and severe SES-CD scores in the validation cohort with AUCs of 0.837 and 0.807, respectively. The CTE score (HR = 1.18; 95% CI: 1.103-1.262; p = 0.001) and SES-CD score (HR = 3.125, 95% CI: 1.542-6.33; p = 0.001) were independent prognostic factors for surgery-free survival. A prognostic nomogram incorporating CTE scores, SES-CD and C-reactive protein (CRP) accurately predicted the risk of surgery in patients with CD. Conclusion: The newly developed CTE score and multiparametric models displayed high accuracy in predicting moderate to severe CD and surgical risk for CD patients.

Synthesis of Polyether Carboxylate and the Effect of Different Electrical Properties on Its Viscosity Reduction and Emulsification of Heavy Oil.

Heavy oil exploitation needs efficient viscosity reducers to reduce viscosity, and polyether carboxylate viscosity reducers have a significant viscosity reduction effect on heavy oil. Previous work has studied the effect of different side chain lengths on this viscosity reducer, and now a series of polyether carboxylate viscosity reducers, including APAD, APASD, APAS, APA, and AP5AD (the name of the viscosity reducer is determined by the name of the desired monomer), with different electrical properties have been synthesized to investigate the effect of their different electrical properties on viscosity reduction performance. Through the performance tests of surface tension, contact angle, emulsification, viscosity reduction, and foaming, it was found that APAD viscosity reducers had the best viscosity reduction performance, reducing the viscosity of heavy oil to 81 mPa·s with a viscosity reduction rate of 98.34%, and the worst viscosity reduction rate of other viscosity reducers also reached 97%. Additionally, APAD viscosity reducers have the highest emulsification rate, and the emulsion formed with heavy oil is also the most stable. The net charge of APAD was calculated from the molar ratio of the monomers and the total mass to minimize the net charge. While the net charge of other surfactants was higher. It shows that the amount of the surfactant's net charge affects the surfactant's viscosity reduction effect, and the smaller the net charge of the surfactant itself, the better the viscosity reduction effect.

Study on Contrast-Enhanced Ultrasound Imaging and Anti-Tumor Effects of Drug-Loaded Nanodroplets with Tumor Targeting and Ultrasound Sensitivity.

BACKGROUND: Ultrasound-responsive nanodroplets (NDs) targeting tumors have shown great potential in ultrasound imaging and tumor therapy, but most of these studies are based NDs with lipid shells that cannot overcome the uptake by cells of the reticulo-endothelial system (RES). NDs with shells comprised of polyethylene glycol (PEG)-based polymers could effectively suppressed the uptake of RES, but the phase transition, contrast-enhanced imaging and drug release about these NDs have not been well illuminated. METHODS: Folate receptor targeted NDs with shells of polymers and loaded with DOX (FA-NDs/DOX) were prepared. The particle size distribution and morphology of NDs was characterized with dynamic light scattering (DLS) and microscope. Phase transition and contrast-enhanced ultrasound imaging under different mechanical indices (MIs) was studied, and the intensity of contrast enhancement were quantitatively analyzed. The targeting property of FA-NDs/DOX to MDA-MB-231 cells and cellular uptake were observed using a fluorescence microscope. The anti-tumor effects of FA-NDs/DOX combined with low-intensity focused ultrasound (LIFU) was studied through cytotoxicity tests. Flow cytometry assays were used to detect cell apoptosis. RESULTS: The average particle size of the FA-NDs/DOX was 448.0 ± 8.9 nm, and the zeta potential was 30.4 ± 0.3 mV. When exposed to ultrasound at 37 °C, ultrasound contrast enhancement of FA-NDs/DOX was observed when MI ≥0.19. A stronger acoustic signal was observed under higher MIs and concentrations. The results of quantitative analysis showed that the contrast enhancement intensity of FA-NDs/DOX (1.5 mg/mL) at MI of 0.19, 0.29 and 0.48 was 26.6 ± 0.9 dB, 97.0 ± 3.8 dB and 153.1 ± 5.7 dB, respectively. The contrast enhancement of the FA-NDs/DOX lasted for more than 30 minutes at an MI of 0.48. In targeting experiments, FA-NDs could be recognized by MDA-MB-231 cells, and significant cellular uptake was observed. The blank FA-NDs showed good biocompatibility, while the FA-NDs/DOX induced apoptosis of MDA-MB-231 and MCF-7 cells. By combining LIFU irradiation and FA-NDs/DOX treatment, the best cell-killing effect was achieved. CONCLUSIONS: The FA-NDs/DOX prepared in this study has excellent performance in contrast-enhanced ultrasound imaging, tumor targeting and enhanced chemotherapy. This FA-NDs/DOX with polymer shells provides a novel platform for ultrasound molecular imaging and tumor therapy.

New scoring system combining computed tomography body composition analysis and inflammatory-nutritional indicators to predict postoperative complications in stage II-III colon cancer.

BACKGROUND AND AIM: Postoperative complications are important clinical outcomes for colon cancer patients. This study aimed to investigate the predictive value of inflammatory-nutritional indicators combined with computed tomography body composition on postoperative complications in patients with stage II-III colon cancer. METHODS: We retrospectively collected data from patients with stage II-III colon cancer admitted to our hospital from 2017 to 2021, including 198 patients in the training cohort and 50 patients in the validation cohort. Inflammatory-nutritional indicators and body composition were included in the univariate and multivariate analyses. Binary regression was used to develop a nomogram and evaluate its predictive value. RESULTS: In the multivariate analysis, the monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), nutritional risk score (NRS), skeletal muscle index (SMI), and visceral fat index (VFI) were independent risk factors for postoperative complications of stage II-III colon cancer. In the training cohort, the area under the receiver operating characteristic curve of the predictive model was 0.825 (95% confidence interval [CI] 0.764-0.886). In the validation cohort, it was 0.901 (95% CI 0.816-0.986). The calibration curve showed that the prediction results were in good agreement with the observational results. Decision curve analysis showed that colon cancer patients could benefit from the predictive model. CONCLUSIONS: A nomogram combining MLR, SII, NRS, SMI, and VFI with good accuracy and reliability in predicting postoperative complications in patients with stage II-III colon cancer was established, which can help guide treatment decisions.

GSDME-dependent pyroptosis signaling pathway in diabetic nephropathy.

Diabetic nephropathy (DN) is one of the serious chronic microvascular complications of diabetes, and leads to the increased morbidity and mortality in diabetic patients. Gasdermin E (GSDME)-dependent pyroptosis signaling pathway plays important roles in a variety of physiological and pathological processes. However, its role and mechanism in DN are still unclear. In this study, we established a rat DN model by intraperitoneal injection of streptozotocin (STZ) successfully. Structural and functional disorders in the kidney were exhibited on the 12th week after STZ injection; the expressions of caspase-3 and GSDME at protein level in renal cortex were significantly up-regulated. At the 20th week, GSDME-N increased significantly, accompanied by the upregulation of caspase-1 in renal cortex and the release of mature IL-1ß (mIL-1ß) in serum. Furthermore, we found the protein levels of GSDME, caspase-3, caspase-1 and IL-1ß were all increased in HK2 and HBZY-1 cells under high-glucose conditions. We also found that the expression of GSDME-N significantly decreased when caspase-3 was knockdown. In contrast, knockdown of GSDME has no effect on caspase-3. Interestingly, either caspase-3, caspase-1 or GSDME knockdown reduced the release of mIL-1ß. Finally, injection of adeno-associated virus (AAV) 9-shGSDME into the rat kidney reduced kidney damage and renal cell pyroptosis in comparison with wild-type diabetic rats. These results indicated that the activation of caspase-1 induced IL-1ß maturation, and the activation of caspase-3 mediated cleavage of GSDME responsible for the formation of plasma membrane pore, followed by cytoplasmic release of mIL-1ß. Overall, we identified a pro-pyroptosis role for GSDME in DN, which does provide an important basis for clinical therapeutic studies.

The Predictive Value of a New Inflammatory-Nutritional Score for Quality of Life after Laparoscopic Distal Gastrectomy for Gastric Cancer.

We explored the predictive value of various inflammatory-nutritional indicators for postoperative quality of life (QoL) in gastric cancer (GC) patients undergoing laparoscopic distal gastrectomy (LDG) and developed a novel inflammatory-nutritional score (INS). In this study, 156 GC patients who underwent LDG were included. We used multiple linear regression to analyze the correlation between postoperative QoL and inflammatory-nutritional indicators. Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to construct INS. Hemoglobin was positively correlated with physical functioning (ß =8.5; p = 0.003) and cognitive functioning (ß = 3.5; p = 0.038) 3 mo, after surgery. Prognostic nutritional index (PNI) was positively associated with global health status (ß =5.8; p = 0.043). Albumin-alkaline phosphatase ratio (AAPR) was negatively correlated with emotional functioning 12 mo, after surgery (ß = -5.7; p = 0.024). Neutrophil-lymphocyte ratio (NLR), Lymphocyte- monocyte ratio (LMR), AAPR, hemoglobin and PNI were selected using LASSO regression analysis to construct INS. The C-index values of the model in the training group and the validation group were 0.806 (95% CI, 0.719-0.893) and 0.758 (95% CI: 0.591-0.925), respectively. INS had particular predictive value for postoperative QoL in patients undergoing LDG and provided a reference for risk stratification and clinical practice.

ALK-JNK signaling promotes NLRP3 inflammasome activation and pyroptosis via NEK7 during Streptococcus pneumoniae infection.

Streptococcus pneumoniae (S. pneumoniae), a clinically important pathogen worldwide, causes serious invasive diseases, such as pneumonia, otitis media, and meningitis. The NLR family pyrin domain-containing 3 (NLRP3) inflammasome, an important component of the innate immune system, plays a key role in defense against pathogen infection; however the specific activation mechanism induced by S. pneumoniae infection is not fully understood. Here, primary mouse macrophages were selected as the in vitro cell model, and the effect of kinases on S. pneumoniae infection-induced NLRP3 inflammasome activation was investigated in vivo and in vitro using the western blot/RT-PCR/Co-IP/immunofluorescence staining/ELISA with or without kinase inhibitor or siRNA pretreatment. In this study, we found that the formation of the NEK7-NLRP3 complex significantly increased during S. pneumoniae infection and that anaplastic lymphoma kinase (ALK) and Jun N-terminal kinase (JNK) were phosphorylated rapidly. ALK and JNK inhibitors significantly reduced the ability of bacterial killing, the gene expression of NLRP3 inflammasome, the formation of apoptosis-associated speck-like protein containing caspase-recruitment domain (ASC) specks and the NEK7-NLRP3 complex, which in turn decreased the activation level of NLRP3 inflammasome-associated molecules and the maturation of interleukin-1ß (IL-1ß). In addition, ALK regulated the phosphorylation of JNK. Interestingly, the ALK/JNK/NEK7-NLRP3 signaling pathway is also involved in regulating pyroptosis and IL-1ß secretion triggered by S. pneumoniae infection. In conclusion, our data suggest, for the first time, that the ALK/JNK/NEK7-NLRP3 signaling pathway may play an important role in NLRP3 inflammasome activation and pyroptosis and consequently regulate the host immune response upon S. pneumoniae infection.

CT-based radiomics for the identification of colorectal cancer liver metastases sensitive to first-line irinotecan-based chemotherapy.

BACKGROUND: Chemosensitivity prediction in colorectal cancer patients with liver metastases has remained a research hotspot. Radiomics can extract features from patient imaging, and deep learning or machine learning can be used to build models to predict patient outcomes prior to chemotherapy. PURPOSE: In this study, the radiomics features and clinical data of colorectal cancer patients with liver metastases were used to predict their sensitivity to irinotecan-based chemotherapy. METHODS: A total of 116 patients with unresectable colorectal cancer liver metastases who received first-line irinotecan-based chemotherapy from January 2015 to January 2020 in our institution were retrospectively collected. Overall, 116 liver metastases were randomly divided into training (n = 81) and validation (n = 35) cohorts in a 7:3 ratio. The effect of chemotherapy was determined based on Response Evaluation Criteria in Solid Tumors. The lesions were divided into response and nonresponse groups. Regions of interest (ROIs) were manually segmented, and sample sizes of 1×1×1, 3×3×3, 5×5×5 mm3 were used to extract radiomics features. The relevant features were identified through Pearson correlation analysis and the MRMR algorithm, and the clinical data were merged into the artificial neural network. Finally, the p-model was obtained after repeated learning and testing. RESULTS: The p-model could distinguish responders in the training (area under the curve [AUC] 0.754, 95% CI 0.650-0.858) and validation cohorts (AUC 0.752 95% CI 0.581-0.904). AUC values of the pure image group model are 0.720 (95% CI 0.609-0.827) and 0.684 (95% CI 0.529-0.890) for the training and validation cohorts respectively. As for the clinical data model, AUC values of the training and validation cohorts are 0.638 (95% CI 0.500-0.757) and 0.545 (95% CI 0.360-0.785), respectively. The performances of the latter two are less than that of the former. CONCLUSION: The p-model has the potential to discriminate colorectal cancer patients sensitive to chemotherapy. This model holds promise as a noninvasive tool to predict the response of colorectal liver metastases to chemotherapy, allowing for personalized treatment planning.

Noninvasive Prediction of Ki-67 Expression in Hepatocellular Carcinoma Using Machine Learning-Based Ultrasomics: A Multicenter Study.

OBJECTIVES: To investigate the ability of ultrasomics to predict Ki-67 expression in hepatocellular carcinoma (HCC). METHODS: A total of 244 patients from three hospitals were retrospectively recruited (training dataset, n = 168; test dataset, n = 43; and validation dataset, n = 33). Lesion segmentation of the ultrasound images was performed manually by two radiologists. In total, 1409 ultrasomics features were extracted. Feature selection was conducted using the intra-class correlation coefficient, variance threshold, mutual information, and recursive feature elimination plus eXtreme Gradient Boosting. The support vector machine was combined with the learning curve and grid search parameter tuning to construct the clinical, ultrasomics, and combined models. The predictive performance of the models was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and accuracy. RESULTS: The ultrasomics model performed well on the training, test, and validation datasets. The AUC (95% confidence interval [CI]) for these datasets were 0.955 (0.912-0.981), 0.861 (0.721-0.947), and 0.665 (0.480-0.819), respectively. The combination of ultrasomics and clinical features significantly improved model performance on all three datasets. The AUC (95% CI), sensitivity, specificity, and accuracy were 0.986 (0.955-0.998), 0.973, 0.840, and 0.869 on the training dataset; 0.871 (0.734-0.954), 0.750, 0.829, and 0.814 on the test dataset; and 0.742 (0.560-0.878), 0.714, 0.808, and 0.788 on the validation dataset, respectively. CONCLUSIONS: Ultrasomics was proved to be a potential noninvasive method to predict Ki-67 expression in HCC.

Quantitative Radiological Features and Deep Learning for the Non-Invasive Evaluation of Programmed Death Ligand 1 Expression Levels in Gastric Cancer Patients: A Digital Biopsy Study.

RATIONALE AND OBJECTIVES: Programmed Death-Ligand 1 (PD-L1) is an important biomarker for patient selection of immunotherapy in gastric cancer (GC). This study aimed to construct and validate a non-invasive virtual biopsy system based on radiological features and clinical factors to predict the PD-L1 expression level in GC. MATERIALS AND METHODS: 217 patients who received gastrectomy for GC were consecutively enrolled in this study, with 157 patients from center 1 as the training cohort and 60 patients from center 2 as the external validation cohort. 1205 quantitative radiomics features were extracted from preprocessed pre-operative contrast-enhanced CT images of enrolled patients. A radiological signature was computed using a regression random forest model and was integrated with clinical factors in a multilayer perceptron. The performance of the digital biopsy system was evaluated by the receiver operating characteristic (ROC) curve and calibration curve in both the training and validation cohort. RESULTS: 15 features were selected for the construction of radiological signature, which was significantly associated with expression levels of PD-L1 in both the training cohort (p<0.0001) and the external validation cohort (p<0.01). The hybrid deep learning model integrating the radiological signature and clinical factor could accurately distinguish GCs with high PD-L1 expression levels in both the training cohort (AUC = 0.806, 95%CI: 0.736-0.875) and the validation cohort (AUC = 0.784, 95%CI: 0.668-0.901). CONCLUSIONS: Our results indicate that the combination of deep learning and quantitative radiological features are potential approaches for the non-invasive evaluation of PD-L1 expression levels in GC. The digital biopsy system could provide valuable suggestive information for clinical decision-making of immunotherapy in GC.

Synthesis of Polycarboxylate Viscosity Reducer and the Effect of Different Chain Lengths of Polyether on Viscosity Reduction of Heavy Oil.

Since there are not many studies on the application of polymeric surfactants in viscosity reduction emulsification of heavy oil, a series of polyether carboxylic acid-sulfonate polymeric surfactants were synthesized. The viscosity reduction performance and the effect of different chain lengths on the viscosity reduction effect were also investigated. The viscosity reduction, emulsification, wetting, and foaming performance tests showed that the viscosity reduction performance of this series of polymeric surfactants was excellent, with the viscosity reduction rate exceeding 95%, and the viscosity was reduced to 97 mPa·s by the polymeric surfactant with a molecular weight of 600 polyethers. It was also concluded that among the three surfactants with different side chains, the polymeric surfactant with a polyether molecular weight of 600, which is the medium side-chain length, had the best viscosity reduction performance. The study showed that the polyether carboxylic acid-sulfonate polymer surfactant had a promising application in the viscosity reduction of heavy oil.

Perforating and nonperforating indications in repeated surgeries for Crohn's disease.

BACKGROUND: Despite advances in medical therapy for Crohn's disease (CD), most patients with CD require repeated resection surgeries. AIM: To analyze the perforating and nonperforating indications of repeated CD operations and identify the anastomosis characteristics for postoperative CD. METHODS: We retrospectively reviewed 386 patients who underwent at least one resection for CD between 2003 and 2013.Clinical characteristics of each surgery were collected. Univariate and multivariate analyses were performed to determine risk factors for recurrence. RESULTS: The indication for reoperation in CD tends to be the same as that for primary operation, i.e., perforating disease tends to represent as perforating disease and nonperforating as nonperforating. Concordance was found between the first surgery and second surgery in terms of the indication for the operation (P = 0.006), and the indication for the third surgery was also correlated with that for the second surgery (P = 0.033). Even if the correlation of surgical indications between repeated operations, the rate of perforating indication for the second and third surgeries was significantly higher than that of the first surgery. In addition, the presence of perforating CD was a predictor of recurrence for both the first and second surgeries. Moreover, anastomotic lesions were the most common sites of recurrence after the operation. Based on the importance of anastomosis, anastomosis might be a new type of disease location for the classification of postoperative CD. CONCLUSION: CD not only has stable characteristics but also progresses chronically. Perforation is a progressive surgical indication for Crohn's disease. For CD after surgery, anastomosis may be a new classification of disease location.

A Comparison of Adverse Events Among Radiofrequency Ablation, Conventional Transarterial Chemoembolization (TACE) and Drug-Eluting Bead TACE in Treating Hepatocellular Carcinoma Patients.

BACKGROUND: There has been very limited investigation regarding the comparison of adverse events (AEs) among radiofrequency ablation (RFA), conventional transarterial chemoembolization (cTACE), and drug-eluting bead TACE (DEB-TACE) in treating HCC patients; therefore, the present study aimed to resolve this issue. METHODS: Two-hundred and forty-six HCC patients (with a total of 267 procedures [treatment times]) treated with RFA (73 patients with 79 procedures), cTACE (86 patients with 94 procedures), or DEB-TACE (87 patients with 94 procedures) were included. Demographic and clinical data were collected. The information on AEs was also retrieved and analyzed. RESULTS: Total AEs incidence was notably different among the RFA group, cTACE group, and DEB-TACE group and was the highest in cTACE group (86.2%), then in DEB-TACE group (76.6%), and the lowest in RFA group (63.3%). Regarding specific AEs incidence, the incidences of fever, fatigue, and nausea were distinctive among the three groups, while no distinctiveness was found in incidence of other AEs. Furthermore, multivariate logistic regression revealed that cTACE (versus RFA) was independently correlated with increased risk of total AEs, fatigue, and nausea/vomiting; however, the interventional therapies were not independently correlated with the risk of pain, fever or constipation. Other independent predictive factors for total AEs risk were male gender, bronchial asthma, and disease duration. CONCLUSION: cTACE resulted in the highest AEs incidence compared with RFA and DEB-TACE in treating HCC patients.

ZSCAN16-AS1 expedites hepatocellular carcinoma progression via modulating the miR-181c-5p/SPAG9 axis to activate the JNK pathway.

Hepatocellular carcinoma (HCC) is generally known as one of the most common cancers in the world. Nowadays, interventional therapies such as transcatheter arterial chemoembolization (TACE) have emerged as an efficient therapy for HCC patients. Accumulating evidence has unveiled that long non-coding RNAs (lncRNAs) are crucial regulators in HCC progression. Nonetheless, the biological function of lncRNA zinc finger and SCAN domain containing 16 antisense RNA 1 (ZSCAN16-AS1) in HCC has not been systematically clarified. RT-qPCR was used to test ZSCAN16-AS1 expression in HCC cells. The biological functions of RP11-757 G1.5 on HCC cell proliferation, migration, invasion and apoptosis were investigated by colony formation, EdU, CCK-8 and transwell assays, as well as flow cytometry analysis. RNA immunoprecipitation (RIP), RNA pull-down and luciferase reporter assays were utilized to explore the specific mechanism of ZSCAN16-AS1. ZSCAN16-AS1 was significantly up-regulated in HCC cells. ZSCAN16-AS1 silence inhibited HCC cell proliferation, migration and invasion, while it accelerated HCC cell apoptosis. ZSCAN16-AS1 worked as a competing endogenous RNA (ceRNA) to regulate sperm associated antigen 9 (SPAG9) expression through sponging miR-181 c-5p. Moreover, SPAG9 could activate the c-Jun-N-terminal kinase (JNK) pathway. Taken together, our study elucidated that ZSCAN16-AS1 expedited HCC progression via modulating the miR-181 c-5p/SPAG9 axis to activate the JNK pathway, which might be a highly potential HCC therapy and treatment target.