Sequential Ring Opening/In Situ SO2-Capture/Alkynylation of Cyclopropanols with Alkynyl Triflones Initiated by Energy Transfer.

A visible-light-triggered ring opening/in situ SO2-capture/alkynylation sequence of cyclopropyl alcohols with alkynyl triflones using 4CzIPN as a triplet energy transfer photocatalyst is herein described. This metal-free protocol provides a straightforward and atom-economical approach to alkynyl-substituted γ-keto sulfones with a broad scope of substituents. In this transformation, alkynyl triflones could be used as both radical acceptors and SO2 donors. Preliminary experimental mechanistic studies and synthetic utility are also demonstrated.

Preoperative prediction of microsatellite instability status in colorectal cancer based on a multiphasic enhanced CT radiomics nomogram model.

BACKGROUND: To investigate the value of a nomogram model based on the combination of clinical-CT features and multiphasic enhanced CT radiomics for the preoperative prediction of the microsatellite instability (MSI) status in colorectal cancer (CRC) patients. METHODS: A total of 347 patients with a pathological diagnosis of colorectal adenocarcinoma, including 276 microsatellite stabilized (MSS) patients and 71 MSI patients (243 training and 104 testing), were included. Univariate and multivariate regression analyses were used to identify the clinical-CT features of CRC patients linked with MSI status to build a clinical model. Radiomics features were extracted from arterial phase (AP), venous phase (VP), and delayed phase (DP) CT images. Different radiomics models for the single phase and multiphase (three-phase combination) were developed to determine the optimal phase. A nomogram model that combines clinical-CT features and the optimal phasic radscore was also created. RESULTS: Platelet (PLT), systemic immune inflammation index (SII), tumour location, enhancement pattern, and AP contrast ratio (ACR) were independent predictors of MSI status in CRC patients. Among the AP, VP, DP, and three-phase combination models, the three-phase combination model was selected as the best radiomics model. The best MSI prediction efficacy was demonstrated by the nomogram model built from the combination of clinical-CT features and the three-phase combination model, with AUCs of 0.894 and 0.839 in the training and testing datasets, respectively. CONCLUSION: The nomogram model based on the combination of clinical-CT features and three-phase combination radiomics features can be used as an auxiliary tool for the preoperative prediction of the MSI status in CRC patients.

Energy spectrum CT index-based machine learning model predicts the effect of intravenous thrombolysis in lower limbs.

To develop a noninvasive machine learning (ML) model based on energy spectrum computed tomography venography (CTV) indices for preoperatively predicting the effect of intravenous thrombolytic treatment in lower limbs. A total of 3492 slices containing thrombus regions from 58 veins in lower limbs in a cohort of 18 patients, divided in good and poor thrombolysis prognosis groups, were analyzed. Key indices were selected by univariate analysis and Pearson correlation coefficient test. A support vector machine classifier-based model was developed through ten-fold cross validation. Model performance was assessed in terms of discrimination, calibration, and clinical usefulness at both per-slice and per-vessel levels. Continuous variables and categorical variables were compared between good and poor thrombolysis prognosis group by Mann-Whitney U-test and chi-square test, respectively. A nomogram was built by integrating clinical factors and the energy spectrum CTV index-based score calculated by the model. Six indices selected from 192 indices were used to build the predictive model. The ML model achieved area under the curves (AUCs) of 0.838 and 0.767 [95% CI (confidence interval), 0.825-0.850, 0.752-0.781] in the training and validation datasets at the per-slice level, and the per-vessel level AUCs were 0.945 and 0.876 (95% CI, 0.852-0.988, 0.763-0.948) in the training and validation datasets, respectively. The nomogram showed better performance with the per-vessel level AUC, accuracy, sensitivity and specificity, yielding 0.901(95% CI, 0.793-0.964), 86.2%, 87.9% and 84.0% in the validation dataset, respectively. There was no significant difference in the vessel distribution between good and poor thrombolysis prognosis groups (chi-square test, p = 0.671). The energy spectrum CTV index-based ML model achieved favorable effectiveness in predicting the outcome of vessel-level intravenous thrombolysis. A nomogram integrating clinical factors, and risk score calculated by the developed model showed improved performance and had potential to be used as a noninvasive preoperative tool for clinicians.

The value of diffusion kurtosis imaging and intravoxel incoherent motion quantitative parameters in predicting synchronous distant metastasis of rectal cancer.

BACKGROUND: The incidence and mortality rate of rectal cancer are still high, the metastasis of rectal cancer are main causes of death. The control of the distant metastasis is one of the main concerns in the treatment of locally advanced rectal cancer, but there are few studies on predicting synchronous distant metastasis (SDM) of rectal cancer. METHOD: The data of patients with rectal adenocarcinoma confirmed by endoscopic biopsy or postoperative pathology from September 2015 to May 2020 in hospital A (center 1) and hospital B (center 2) were analyzed retrospectively, including age, sex, carcinoembryonic antigen, carbohydrate antigen 19-9, tumor location, tumor length, image staging and characteristics. The average age of the 169 patients consisting of 105 males and 64 females in study is 61.2 years. All patients underwent rectal routine rectal MRI, DKI and IVIM examinations on a 3.0-T scanner. Two radiologists sketched regions of interest (ROIs) on b = 1000 s/mm2 DKI and IVIM images to obtain quantitative parameters with FireVoxel manually. We evaluated the difference of histogram analysis, clinical and image data between SDM group and non-SDM group, and evaluated the efficacy of each index in predicting SDM of rectal cancer. RESULTS: The 90th percentile of f values in the SDM group is lower than that in the non-SDM group (29.4 ± 8.4% vs. 35 ± 17.8%, P = 0.005). CA19-9 in the SDM group is higher than that in the non-SDM group (P = 0.003). Low and high rectal cancer are more likely to develop SDM than middle rectal cancer (P = 0.05 and P = 0.047). The combination of these three indexes has a greater area under the curve (AUC) than any one index (0.801 vs. 0.685 (f (90th percentile)) and 0.627 (CA19-9), P = 0.0075 and 0.0058, respectively), and its specificity and sensitivity are 80.0% and 71.6%, respectively. When this combination is incorporated into the predictive nomogram model, the c-index is 0.801 (95% confidence interval (CI): 0.730-0.871). CONCLUSIONS: IVIM quantitative parameters combine with CA19-9 and tumor location can better predict the risk of SDM of rectal cancer.

Organophotoredox and Hydrogen Atom Transfer Cocatalyzed C-H Alkylation of Quinoxalin-2(1H)-ones with Aldehydes, Amides, Alcohols, Ethers, or Cycloalkanes.

Described is a mild method that merges organophotoredox catalysis with hydrogen atom transfer to enable C-H alkylation of quinoxalin-2(1H)-ones with feedstock aldehydes, amides, alcohols, ethers, or cycloalkanes. This reaction occurred under environmentally benign and external oxidant-free reaction conditions, providing a general and sustainable access to various C3-alkylated quinoxalinone derivatives with broad substituent diversity and good functional group compatibility.

Photodynamic therapy synergizes with PD-L1 checkpoint blockade for immunotherapy of CRC by multifunctional nanoparticles.

Checkpoint inhibitors, such as anti-PD-1/PD-L1 antibodies, have been shown to be extraordinarily effective, but their durable response rate remains low, especially in colorectal cancer (CRC). Recent studies have shown that photodynamic therapy (PDT) could effectively enhance PD-L1 blockade therapeutic effects, although the reason is still unclear. Here, we report the use of multifunctional nanoparticles (NPs) loaded with photosensitized mTHPC (mTHPC@VeC/T-RGD NPs)-mediated PDT treatment to potentiate the anti-tumor efficacy of PD-L1 blockade for CRC treatment and investigate the underlying mechanisms of PDT enhancing PD-L1 blockade therapeutic effect in this combination therapy. In this study, the mTHPC@VeC/T-RGD NPs under the 660-nm near infrared (NIR) laser could kill tumor cells by inducing apoptosis and/or necrosis and stimulating systemic immune response, which could be further promoted by the PD-L1 blockade to inhibit primary and distant tumor growth, as well as building long-term host immunological memory to prevent tumor recurrence. Furthermore, we detected that mTHPC@VeC/T-RGD NP-mediated PDT sensitizes tumors to PD-L1 blockade therapy mainly because PDT-mediated hypoxia could induce the hypoxia-inducible factor 1α (HIF-1α) signaling pathway that upregulates PD-L1 expression in CRC. Taken together, our work demonstrates that mTHPC@VeC/T-RGD NP-mediated PDT is a promising strategy that may potentiate the response rate of anti-PD-L1 checkpoint blockade immunotherapies in CRC.

Can the simplified magnetic resonance index of activity be used to evaluate the degree of activity in Crohn's disease?

BACKGROUND AND AIMS: A simplified magnetic resonance index of activity (MaRIAs) was recently proposed. Our aim was to verify whether MaRIAs can accurately assess the activity degree of CD. METHODS: We retrospectively analyzed the MRI, ileocolonoscopy, fecal calprotectin (FC), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) data of 93 CD patients. With the SES-CD as the gold standard, MaRIAs' accuracy, the correlation of MaRIAs and SES-CD, FC, ESR, CRP, and interevaluator reliability were assessed. RESULTS: MaRIAs ≥ 1 detected segments with active CD with 90.80% specificity and 81.37% sensitivity (area under the curve was 0.91, 95% confidence interval 0.87-0.94). MaRIAs score of 2 or more detected severe lesions with 88.89% specificity and 95.12% sensitivity (AUC was 0.96, 95% confidence interval was 0.94-0.98). The MaRIAs score showed a high correlation with the SES-CD in the terminal ileum, transverse colon, right colon, and left colon (r = 0.85, 0.91, 0.88, 0.86, P < 0.001) and a moderate correlation with the SES-CD in the rectum (r = 0.74, P < 0.001). The global MaRIAs score was highly correlated with the global SES-CD (r = 0.90, P < 0.001). The global MaRIAs score was positively correlated with the fecal calprotectin (FC), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) (r = 0.77, r = 0.64, and r = 0.68). The intragroup correlation coefficient (ICC) of the two physicians was nice in the terminal ileum, the right colon, the transverse colon, the left colon and was moderately good in the rectum. CONCLUSION: MaRIAs can accurately evaluate the disease activity level of CD and are highly correlated with SES-CD and biomarkers. The interrater reliability of the two physicians was moderately good to nice.

Expression of DUSP12 Reduces Lung Vascular Endothelial Cell Damage in a Murine Model of Lipopolysaccharide-Induced Acute Lung Injury via the Apoptosis Signal-Regulating Kinase 1 (ASK1)-Jun N-Terminal Kinase Activation (JNK) Pathway.

BACKGROUND Acute lung injury (ALI) results from damage to the alveolar capillary endothelial cells and can result in acute respiratory distress syndrome (ARDS). This study aimed to investigate murine lung vascular endothelial cells (MLECs) damage in a murine model of lipopolysaccharide (LPS)-induced ALI. MATERIAL AND METHODS Mice were injected with LPS to induce an acute lung injury model. An adenovirus transfection system was used to overexpress or knockdown DUSP12 in mice. MLECs were isolated, cultured and transfected with DUSP12-overexpressing adenovirus or with DUSP12 siRNA to knockdown DUSP12. LPS was used to establish a cell injury model. ELISA and RT-PCR were used to examine cell inflammation. LPS-induced oxidative stress was also evaluated using commercial kits. RESULTS A decreased level of DUSP12 was observed in MLECs treated with LPS. DUSP12 overexpression in mice attenuated LPS-induced lung inflammation and lung injury, as reflected by reduced levels of proinflammatory cytokines. Mice with DUSP12 knockdown exhibited worsened lung inflammation and injury. In vitro, DUSP12 overexpression in endothelial cells ameliorated LPS-induced inflammation, apoptosis, and oxidative stress. DUSP12 silencing in endothelial cells aggravated LPS-induced inflammation, apoptosis, and oxidative stress. Furthermore, we found that DUSP12 directly bound to apoptosis signal-regulating kinase 1 (ASK1) to inhibit Jun N-terminal kinase activation (JNK). A JNK1/2 inhibitor and ASK1 siRNA ameliorated the exacerbating effects of DUSP12 knockdown in vitro. CONCLUSIONS Our data demonstrated that DUSP12 suppressed MLEC injury in response to LPS insult by regulating the ASK1/JNK pathway.

Differentiation of pulmonary sclerosing pneumocytoma from solid malignant pulmonary nodules by radiomic analysis on multiphasic CT.

PURPOSE: To investigate the diagnostic value and feasibility of radiomics-based texture analysis in differentiating pulmonary sclerosing pneumocytoma (PSP) from solid malignant pulmonary nodules (SMPN) on single- and three-phase computed tomography (CT) images. MATERIALS AND METHODS: A total of 25 PSP patients and 35 SMPN patients with pathologically confirmed results were retrospectively included in this study. For each patient, the tumor regions were manually labeled in images acquired at the noncontrast phase (NCP), arterial phase (AP), and venous phase (VP). The least absolute shrinkage and selection operator (LASSO) method was used to select the most useful predictive features extracted from the CT images. The predictive models that discriminate PSP from SMPN based on single-phase CT images (NCP, AP, and VP) or three-phase CT images (Combined model) were developed and validated through fivefold cross-validation using a logistic regression classifier. Model performance was evaluated using receiver operating characteristic (ROC) analysis. The predictive performance was also compared between the Combined model and human readers. RESULTS: Four, five, and five features were selected from NCP, AP, and VP CT images for the development of radiomic models, respectively. The NCP, AP, and VP models exhibited areas under the curve (AUCs) of 0.748 (95% confidence interval [CI], 0.620-0.852), 0.749 (95% CI, 0.620-0.852), and 0.790 (95% CI, 0.665-0.884) in the validation dataset, respectively. The Combined model based on three-phase CT images outperformed the NCP, AP, and VP models (all p < 0.05), yielding an AUC of 0.882 (95% CI, 0.773-0.951) in the validation dataset. The Combined model displayed noninferior performance compared to two senior radiologists; however, it outperformed two junior radiologists (p = 0.004 and 0.001, respectively). CONCLUSION: The Combined model based on radiomic features extracted from three-phase CT images achieved radiologist-level performance and could be used as promising noninvasive tool to differentiate PSP from SMPN.

Bufalin reverses multidrug resistance by regulating stemness through the CD133/nuclear factor-κB/MDR1 pathway in colorectal cancer.

Recent studies have shown that MDR could be induced by the high stemness of cancer cells. In a previous study, we found bufalin could reverse MDR and inhibit cancer cell stemness in colorectal cancer, but the relationship between them was unclear. Here we identified overexpressing CD133 increases levels of Akt/nuclear factor-κB signaling mediators and MDR1, while increasing cell chemoresistance. Furthermore, bufalin reverses colorectal cancer MDR by regulating cancer cell stemness through the CD133/nuclear factor-κB/MDR1 pathway in vitro and in vivo. Taken together, our results suggest that bufalin could be developed as a novel 2-pronged drug that targets CD133 and MDR1 to eradicate MDR cells and could ultimately be combined with conventional chemotherapeutic agents to improve treatment outcomes for patients with colorectal cancer.