Assessment of chemotherapy resistance changes in human colorectal cancer xenografts in rats based on MRI histogram features.

Purpose: We investigated the value of magnetic resonance imaging (MRI) histogram features, a non-invasive method, in assessing the changes in chemoresistance of colorectal cancer xenografts in rats. Methods: A total of 50 tumor-bearing mice with colorectal cancer were randomly divided into two groups: control group and 5-fluorouracil (5-FU) group. The MRI histogram characteristics and the expression levels of p53 protein and MRP1 were obtained at 24 h, 48 h, 72 h, 120 h, and 168 h after treatment. Results: Sixty highly repeatable MRI histogram features were obtained. There were 16 MRI histogram parameters and MRP1 resistance protein differences between groups. At 24 h after treatment, the MRI histogram texture parameters of T2-weighted imaging (T2WI) images (10%, 90%, median, energy, and RootMeanSquared) and D images (10% and Range) were positively correlated with MRP1 (r = 0.925, p = 0.005). At 48 h after treatment, histogram texture parameters of apparent diffusion coefficient (ADC) images (Energy) were positively correlated with the presence of MRP1 resistance protein (r = 0.900, p = 0.037). There was no statistically significant difference between MRI histogram features and p53 protein expression level. Conclusions: MRI histogram texture parameters based on T2WI, D, and ADC maps can help to predict the change of 5-FU resistance in colorectal cancer in the early stage and provide important reference significance for clinical treatment.

Revisiting R&D intensity and CO2 emissions link in the USA using time varying granger causality test: 1870∼2020.

R&D intensity, per capita GDP, and per capita CO2 emissions links in the USA over the period of 1870-2020 reflects the evolution of the economic development and technology for the environment benefit. Using Time varying Granger causality, the empirical results indicate both causal links between R&D intensity and per capita CO2 emissions and between per capita GDP and per capita CO2 emissions are time varying. In addition, R&D intensity significantly affects per capita CO2 emissions since 1975, and the per capita GDP significantly influences per capita CO2 emissions since 1978. That is, these findings not only in supportive of the EKC theory, but further disentangle the subtly linkages for the R&D intensity and CO2 emissions and the per capita GDP and CO2 emissions. Finally, the policy implication is that launch the new technical innovation and increase in R&D investment to maintain its sustainable economic growth are the best government strategy to reduce CO2 emissions in the USA.

Learning more from the inter-rater reliability of interstitial fibrosis assessment beyond just a statistic.

Interstitial fibrosis assessment by renal pathologists lacks good agreement, and we aimed to investigate its hidden properties and infer possible clinical impact. Fifty kidney biopsies were assessed by 9 renal pathologists and evaluated by intraclass correlation coefficients (ICCs) and kappa statistics. Probabilities of pathologists' assessments that would deviate far from true values were derived from quadratic regression and multilayer perceptron nonlinear regression. Likely causes of variation in interstitial fibrosis assessment were investigated. Possible misclassification rates were inferred on reported large cohorts. We found inter-rater reliabilities ranged from poor to good (ICCs 0.48 to 0.90), and pathologists' assessments had the worst agreements when the extent of interstitial fibrosis was moderate. 33.5% of pathologists' assessments were expected to deviate far from the true values. Variation in interstitial fibrosis assessment was found to be correlated with variation in interstitial inflammation assessment (r2 = 32.1%). Taking IgA nephropathy as an example, the Oxford T scores for interstitial fibrosis were expected to be misclassified in 21.9% of patients. This study demonstrated the complexity of the inter-rater reliability of interstitial fibrosis assessment, and our proposed approaches discovered previously unknown properties in pathologists' practice and inferred a possible clinical impact on patients.

Interobserver and intraobserver variability of RECIST assessment in ovarian cancer.

OBJECTIVES: Measurement of Response Evaluation Criteria In Solid Tumors (RECIST) relies on reproducible unidimensional tumor measurements. This study assessed intraobserver and interobserver variability of target lesion selection and measurement, according to RECIST version 1.1 in patients with ovarian cancer. METHODS: Eight international radiologists independently viewed 47 images demonstrating malignant lesions in patients with ovarian cancer and selected and measured lesions according to RECIST V.1.1 criteria. Thirteen images were viewed twice. Interobserver variability of selection and measurement were calculated for all images. Intraobserver variability of selection and measurement were calculated for images viewed twice. Lesions were classified according to their anatomical site as pulmonary, hepatic, pelvic mass, peritoneal, lymph nodal, or other. Lesion selection variability was assessed by calculating the reproducibility rate. Lesion measurement variability was assessed with the intra-class correlation coefficient. RESULTS: From 47 images, 82 distinct lesions were identified. For lesion selection, the interobserver and intraobserver reproducibility rates were high, at 0.91 and 0.93, respectively. Interobserver selection reproducibility was highest (reproducibility rate 1) for pelvic mass and other lesions. Intraobserver selection reproducibility was highest (reproducibility rate 1) for pelvic mass, hepatic, nodal, and other lesions. Selection reproducibility was lowest for peritoneal lesions (interobserver reproducibility rate 0.76 and intraobserver reproducibility rate 0.69). For lesion measurement, the overall interobserver and intraobserver intraclass correlation coefficients showed very good concordance of 0.84 and 0.94, respectively. Interobserver intraclass correlation coefficient showed very good concordance for hepatic, pulmonary, peritoneal, and other lesions, and ranged from 0.84 to 0.97, but only moderate concordance for lymph node lesions (0.58). Intraobserver intraclass correlation coefficient showed very good concordance for all lesions, ranging from 0.82 to 0.99. In total, 85% of total measurement variability resulted from interobserver measurement difference. CONCLUSIONS: Our study showed that while selection and measurement concordance were high, there was significant interobserver and intraobserver variability. Most resulted from interobserver variability. Compared with other lesions, peritoneal lesions had the lowest selection reproducibility, and lymph node lesions had the lowest measurement concordance. These factors need consideration to improve response assessment, especially as progression free survival remains the most common endpoint in phase III trials.

Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment.

OBJECTIVE: This study aimed to explore the potential of magnetic resonance imaging (MRI) radiomics-based machine learning to improve assessment and diagnosis of contralateral Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions in women with primary breast cancer. MATERIALS AND METHODS: A total of 178 contralateral BI-RADS 4 lesions (97 malignant and 81 benign) collected from 178 breast cancer patients were involved in our retrospective dataset. T1 + C and T2 weighted images were used for radiomics analysis. These lesions were randomly assigned to the training (n = 124) dataset and an independent testing dataset (n = 54). A three-dimensional semi-automatic segmentation method was performed to segment lesions depicted on T2 and T1 + C images, 1,046 radiomic features were extracted from each segmented region, and a least absolute shrinkage and operator feature selection method reduced feature dimensionality. Three support vector machine (SVM) classifiers were trained to build classification models based on the T2, T1 + C, and fusion image features, respectively. The diagnostic performance of each model was evaluated and tested using the independent testing dataset. The area under the receiver operating characteristic curve (AUC) was used as a performance metric. RESULTS: The T1+C image feature-based model and T2 image feature-based model yielded AUCs of 0.71 ± 0.07 and 0.69 ± 0.07 respectively, and the difference between them was not significant (P > 0.05). After fusing T1 + C and T2 imaging features, the proposed model's AUC significantly improved to 0.77 ± 0.06 (P < 0.001). The fusion model yielded an accuracy of 74.1%, which was higher than that of the T1 + C (66.7%) and T2 (59.3%) image feature-based models. CONCLUSION: The MRI radiomics-based machine learning model is a feasible method to assess contralateral BI-RADS 4 lesions. T2 and T1 + C image features provide complementary information in discriminating benign and malignant contralateral BI-RADS 4 lesions.

Fe(III)-Catalyzed Bicyclization of Yne-Allenones With Indoles for the Atom-Economic Synthesis of 3-Indolyl Cyclobutarenes.

A new Fe(III)-catalyzed bicyclization reaction of yne-allenones with indoles has been established, enabling the direct construction of cyclobuta[a]naphthalen-4-ols with an all-carbon quaternary center in good to excellent yields. This reaction was performed by using low-cost FeCl3 as the catalyst and EtOH as the environmentally benign solvent, providing a green protocol for constructing the cyclobutarene framework with a high degree of atom economy and functional group compatibility. The reaction mechanism was proposed to proceed through a [2 + 2] cycloaddition/1,6-conjugate addition cascade.

Atom-economic synthesis of cyclobuta[a]naphthalen-4-ols via a base-promoted [2 + 2] cycloaddition/1,6-nucleophilic addition cascade.

A first atom-economic [2 + 2] cycloaddition/1,6-conjugate addition cascade of yne-allenones with C-nucleophiles including 1,3-dicarbonyls and α,α-dicyanoolefins under base-promoted conditions has been established, enabling the direct construction of C(sp3)-C(sp3) bonds to generate cyclobuta[a]naphthalen-1-ols with generally good yields. These resulting products have a cyclobutene unit that contains both an aryl and alkyl group.

Prognostic factors in Chinese patients with prostate cancer receiving primary androgen deprivation therapy: validation of Japan Cancer of the Prostate Risk Assessment (J-CAPRA) score and impacts of pre-existing obesity and diabetes mellitus.

PURPOSE: Our aim was to determine the prognostic factors in Chinese patients with prostate cancer receiving primary androgen deprivation therapy (PADT), validate the Japan Cancer of the Prostate Risk Assessment (J-CAPRA) score, and investigate the impacts of pre-existing obesity and diabetes mellitus (DM). METHODS: The study enrolled Chinese patients diagnosed with prostatic adenocarcinoma and treated with bilateral orchiectomy as PADT at Huashan Hospital, Fudan University (Shanghai, China), from January 2003 to December 2015. The overall survival (OS) and prognostic value of J-CAPRA score, pre-existing obesity, DM, and various clinicopathological variables were analyzed. RESULTS: Of the 435 patients enrolled, 174 (40.0%) deaths occurred during follow-up; 3- and 5-year OS were 74.0 and 58.9%, respectively. Multivariate analysis identified that higher Gleason score and metastasis were both correlated with worse OS and that higher J-CAPRA score was correlated with worse OS [hazard ratio (HR) 1.110, 95% confidence interval (CI) 1.035-1.190, P = 0.003). Different risk categories based on J-CAPRA score showed good stratification in OS (log-rank P = 0.015). In subgroup analysis, pre-existing obesity as a protective factor in younger patients (age ≤ 65, HR 0.271, 95% CI 0.075-0.980, P = 0.046) and pre-existing DM as a risk factor in older patients (> 75, HR 1.854, 95% CI 1.026-3.351, P = 0.041) for OS were recognized, and the prediction accuracy of J-CAPRA was elevated after incorporating pre-existing obesity and DM. CONCLUSIONS: The J-CAPRA score presented with good OS differentiation among Chinese patients under PADT. Younger patients (age ≤ 65) had better OS with pre-existing obesity, while older patients (age > 75) had worse OS with pre-existing DM.

Assessment of tibial and common peroneal nerves in diabetic peripheral neuropathy by diffusion tensor imaging: a case control study.

OBJECTIVES: To determine the diagnostic accuracy and interobserver performance of diffusion tensor imaging (DTI) in diabetic peripheral neuropathy (DPN) and detect correlations with electrophysiology. METHODS: Twelve healthy volunteers (controls) and ten DPN patients were enrolled to undergo MR examinations. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of tibial nerve (TN) and common peroneal nerve (CPN) were measured. Unpaired t test and Levene tests were performed to assess differences between the two groups. Receiver operating characteristic (ROC) analysis was performed for FA and ADC values. Pearson correlation coefficient was used to assess the correlation between DTI and electrophysiology parameters in the patient group. RESULTS: The FA values of TN and CPN in the DPN group were significantly lower and ADC were higher than the control group (p < 0.05). Interobserver agreement was excellent. FA positively correlated and ADC negatively correlated with motor nerve conduction velocity (MCV) (p < 0.05). There were no significant differences between motor nerve conduction amplitude and DTI parameters (p > 0.05). Moderate diagnostic accuracy of DTI was seen in the diagnosis of DPN. CONCLUSIONS: DTI demonstrates moderate diagnostic accuracy and excellent interobserver performance in the detection of DPN involving the TN and CPN. There is moderate correlation with MCV. KEY POINTS: • FA values of TN and CPN are significantly lower in DPN. • ADC values of TN and CPN are significantly higher in DPN. • DTI demonstrates moderate diagnostic accuracy in detection of DPN. • There is excellent interobserver performance in DTI measurements. • Moderate correlation is seen between DTI parameters and MCV.

Assessment of iron overload in very young children with limited thalassemia care resources in South China.

Southern China has one of the world's largest population of patients needing transfusions. Transfusion and chelation are not uniformly available and no magnetic resonance imaging (MRI) assessment data exists to date. A total of 153 young ß-thalassemia major (ß-TM) patients were assessed using a validated 1.5T scanner in Hong Kong, People's Republic of China (PRC). Their median age was 13 (range 7 to 30), and most patients were young (22.0% age <10, 73.0% age <15, 88.0% age <18). Erratic health care made estimation of total transfusion and chelation exposure impossible. Despite their early age, 24.0% had severe cardiac hemosiderosis [T2*<10 milliseconds (ms)], at ages as early as 8 years old. Median heart iron was 1.68 mg/g dry weight (range 0.19-7.66) and increased with age (p = 0.017), while liver iron was 22.2 mg/g dry weight (range 3.15 to 39.2). Serum ferritin levels were poor predictors of heart and liver, or pancreatic R* and pituitary R* values. Magnetic resonance imaging scans are needed to screen very young ß-TM patients with immediate risk of premature cardiac death in developing nations and triage them to more intensive treatment. This is particularly important in countries with a large number of patients and limited resources. Our data suggests that in developing countries, there is no lower limit for thalassemia MRI scanning programs.

Synthesis of isoxazolo[5,4-b]pyridines by microwave-assisted multi-component reactions in water.

A series of new polycyclic-fused isoxazolo[5,4-b]pyridines were obtained by a one-pot tandem reaction under microwave irradiation in water. Without any use of additional reagent or catalyst, the synthetic protocol represents a green one and makes this methodology suitable for library synthesis in drug discovery efforts.