Delta-radiomics models based on multi-phase contrast-enhanced magnetic resonance imaging can preoperatively predict glypican-3-positive hepatocellular carcinoma

Objectives: The aim of this study is to investigate the value of multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) based on the delta radiomics model for identifying glypican-3 (GPC3)-positive hepatocellular carcinoma (HCC).Methods: One hundred and twenty-six patients with pathologically confirmed HCC (training cohort: n = 88 and validation cohort: n = 38) were retrospectively recruited. Basic information was obtained from medical records. Preoperative multi-phase CE-MRI images were reviewed, and the 3D volumes of interest (VOIs) of the whole tumor were delineated on non-contrast T1-weighted imaging (T1), arterial phase (AP), portal venous phase (PVP), delayed phase (DP), and hepatobiliary phase (HBP). One hundred and seven original radiomics features were extracted from each phase, and delta-radiomics features were calculated. After a two-step feature selection strategy, radiomics models were built using two classification algorithms. A nomogram was constructed by combining the best radiomics model and clinical risk factors.Results: Serum alpha-fetoprotein (AFP) (p = 0.013) was significantly related to GPC3-positive HCC. The optimal radiomics model is composed of eight delta-radiomics features with the AUC of 0.805 and 0.857 in the training and validation cohorts, respectively. The nomogram integrated the radiomics score, and AFP performed excellently (training cohort: AUC = 0.844 and validation cohort: AUC = 0.862). The calibration curve showed good agreement between the nomogram-predicted probabilities and GPC3 actual expression in both training and validation cohorts. Decision curve analysis further demonstrates the clinical practicality of the nomogram.Conclusion: Multi-phase CE-MRI based on the delta-radiomics model can non-invasively predict GPC3-positive HCC and can be a useful method for individualized diagnosis and treatment

Niclosamide Induces Cell Cycle Arrest in G1 Phase in Head and Neck Squamous Cell Carcinoma Through Let-7d/CDC34 Axis

Niclosamide is a traditional anti-tapeworm drug that exhibits potent anti-cancer activity. Our previous study showed that niclosamide induces cell cycle arrest in G1 phase. Nevertheless, the underlying mechanism remains unknown. The following study investigated the molecular mechanism through which niclosamide induced G1 arrest in head and neck squamous cell carcinoma (HNSCC) cell lines. The effect of niclosamide on human HNSCC cell line WSU-HN6 and CNE-2Z were analyzed using IncuCyte ZOOMTM assay, flow cytometry (FCM), real-time PCR and western blot. Luciferase assay was conducted to demonstrate the interaction between let-7d (a let-7 family member which functions as a tumor suppressor by regulating cell cycle) and 3′UTR of CDC34 mRNA. Xenografts tumor model was established to evaluate the niclosamide treatment efficacy in vivo. Briefly, an exposure to niclosamide treatment led to an increased let-7d expression and a decreased expression of cell cycle regulator CDC34, finally leading to G1 phase arrest. Moreover, an overexpression of let-7d induced G1 phase arrest and downregulated CDC34, while the knockdown of let-7d partially rescued the niclosamide-induced G1 phase arrest. Luciferase assay confirmed the direct inhibition of CDC34 through the targeting of let-7d. Furthermore, niclosamide markedly inhibited the xenografts growth through up-regulation of let-7d and down-regulation of CDC34. To sum up, our findings suggest that niclosamide induces cell cycle arrest in G1 phase in HNSCC through let-7d/CDC34 axis, which enriches the anti-cancer mechanism of niclosamide

Influence of Parent Concrete Properties on Compressive Strength and Chloride Diffusion Coefficient of Concrete with Strengthened Recycled Aggregates

Parent concrete coming from a wide range of sources can result in considerable differences in the properties of recycled coarse aggregate (RCA). In this study, the RCAs were obtained by crushing the parent concrete with water-to-cement ratios (W/Cparent) of 0.4, 0.5 and 0.6, respectively, and were strengthened by carbonation and nano-silica slurry wrapping methods. It was found that when W/Cparen was 0.3, 0.4 and 0.5, respectively, compared with the mortar in the untreated RCA, the capillary porosity of the mortar in the carbonated RCA decreased by 19%, 16% and 30%, respectively; the compressive strength of concrete containing the carbonated RCA increased by 13%, 11% and 13%, respectively; the chloride diffusion coefficient of RAC (DRAC) containing the nano-SiO2 slurry-treated RCA decreased by 17%, 16% and 11%; and that of RAC containing the carbonated RCA decreased by 21%, 25% and 26%, respectively. Regardless of being strengthened or not, both DRAC and porosity of old mortar in RCAs increased with increasing W/Cparent. For different types of RCAs, DRAC increased obviously with increasing water absorption of RCA. Finally, a theoretical model of DRAC considering the water absorption of RCA was established and verified by experiments, which can be used to predict the DRAC under the influence of different factors, especially the water absorption of RCA

Application value of CT radiomic nomogram in predicting T790M mutation of lung adenocarcinoma

Abstract Background The purpose of this study was to develop a radiomic nomogram to predict T790M mutation of lung adenocarcinoma base on non-enhanced CT lung images. Methods This retrospective study reviewed demographic data and lung CT images of 215 lung adenocarcinoma patients with T790M gene test results. 215 patients (including 52 positive) were divided into a training set (n = 150, 36 positive) and an independent test set (n = 65, 16 positive). Multivariate logistic regression was used to select demographic data and CT semantic features to build clinical model. We extracted quantitative features from the volume of interest (VOI) of the lesion, and developed the radiomic model with different feature selection algorithms and classifiers. The models were trained by a 5-fold cross validation strategy on the training set and assessed on the test set. ROC was used to estimate the performance of the clinical model, radiomic model, and merged nomogram. Results Three demographic features (gender, smoking, emphysema) and ten radiomic features (Kruskal-Wallis as selection algorithm, LASSO Logistic Regression as classifier) were determined to build the models. The AUC of the clinical model, radiomic model, and nomogram in the test set were 0.742(95%CI, 0.619–0.843), 0.810(95%CI, 0.696–0.907), 0.841(95%CI, 0.743–0.938), respectively. The predictive efficacy of the nomogram was better than the clinical model (p = 0.042). The nomogram predicted T790M mutation with cutoff value was 0.69 and the score was above 130. Conclusion The nomogram developed in this study is a non-invasive, convenient, and economical method for predicting T790M mutation of lung adenocarcinoma, which has a good prospect for clinical application

Goose Nephritic Astrovirus Infection of Goslings Induces Lymphocyte Apoptosis, Reticular Fiber Destruction, and CD8 T-Cell Depletion in Spleen Tissue

The emergence of a novel goose nephritic astrovirus (GNAstV) has caused economic losses to the Chinese goose industry. High viral load is found in the spleen of goslings infected with GNAstV, but pathological injuries to the spleen due to GNAstV are largely unknown. In this study, 50 two-day-old goslings were infected orally with GNAstV, and 50 goslings were treated with PBS as control. Spleens were collected at different times following infection to assess damage. GNAstV infection caused visceral gout and urate deposition in joints, and resulted in 16% mortality. GNAstV was found in the lymphocytes and macrophages within the spleen. Lymphocyte loss, especially around the white pulp, and destruction and decline in the number of reticular fibers was observed in GNAstV-infected goslings. Moreover, in GNAstV-infected goslings, ultrahistopathological examination found that splenic lymphocytes exhibited condensed chromatin and apoptotic bodies, and reticular cells displayed damage to plasma membrane integrity and swollen mitochondria. Furthermore, TUNEL staining confirmed apoptosis of lymphocytes, and the mRNA levels of Fas and FasL were significantly increased in the GNAstV-infected goslings. In addition, GNAstV infection reduced the number and protein expression of CD8. In conclusion, GNAstV infection causes lymphocyte depletion, reticular cell necrosis, reticular fiber destruction, lymphocyte apoptosis, and reduction in CD8 levels, which contribute to spleen injury

Investigation on the Continuous Wave Mode and the ms Pulse Mode Fiber Laser Drilling Mechanisms of the Carbon Fiber Reinforced Composite

The near infrared (NIR) laser drilling of a carbon fiber reinforced polymer (CFRP) composite in the continuous wave (CW) mode and the ms pulse mode was investigated by an experiment and a numerical simulation. The relationships between the laser penetrating time, entrance hole diameter, surface heat affected zone (HAZ) width, and material ablation rate and the laser irradiation time and laser peak power densities were obtained from the experiment. For the same average power density of the laser output, 3.5 kW/cm2, it was found that the ms pulse laser mode, which had a higher peak power density, had a higher drilling efficiency. When drilling the same holes, the pulse laser mode, which had the highest peak power density of 49.8 kW/cm2, had the lowest drilling time of 0.23 s and had the smallest surface HAZ width of 0.54 mm. In addition, it was found that the laser penetrating time decreased sharply when the peak power density was higher than 23.4 kW/cm2. After analyzing the internal gas pressure by the numerical simulation, it was considered that a large internal gas pressure appeared, which resulted from polymer pyrolysis, causing a large amount of the mechanical erosion of the composite material to improve the drilling efficiency. Therefore, the ms pulse laser showed its potential and advantage in laser drilling the CFRP composite

Resistance monitoring and cross-resistance role of CYP6CW1 between buprofezin and pymetrozine in field populations of Laodelphax striatellus (Fallén)

Abstract Monitoring resistance and investigating insecticide resistance mechanisms are necessary for controlling the small brown planthopper, Laodelphax striatellus. The susceptibility to four common insecticides of L. striatellus collected from Jiangsu, Anhui, Zhejiang and Jilin provinces of China in 2015 was monitored. The results showed that all field populations remained susceptible to chlorpyrifos and thiamethoxam with resistance ratios (RRs) of 2.3- to 9.5 and 1.6- to 3.3, respectively, while the insects had developed moderate pymetrozine resistance with RRs of 18.7 to 34.5. Resistance against buprofezin had developed to an alarmingly high level in three southeastern provinces of China with RRs of 108.8 to 156.1, but in Jilin it had an RR of only 26.6. Moreover, in line with both the buprofezin and pymetrozine resistance levels, we found LsCYP6CW1 to be over-expressed in all field L. striatellus populations, which indicated that it might be important for cross-resistance between buprofezin and pymetrozine. RNA interference (RNAi) ingestion resulted in the effective suppression of LsCYP6CW1 expression, and significantly increased susceptibility to both buprofezin and pymetrozine compared with the control, which further confirmed that overexpression of LsCYP6CW1 was involved in the cross-resistance to buprofezin and pymetrozine in field L. Striatellus populations

Data from: Generation of a monoclonal antibody recognizing the heavily glycosylated CD45 Protein and its application on identifying circulating tumor cells

Here, we provide direct evidence that using recombinant proteins expressed in eukaryotic cells as antigen is a practical way to generate monoclonal antibodies (mAbs) against heavily glycosylated proteins. Heavily glycosylated proteins are typically difficult targets for mAb generation, being limited by unsatisfactory affinity and low specificity. Using the heavily glycosylated CD45 protein as an example, we demonstrate the entire process of expressing the protein in eukaryotic cells and using it as an antigen to generate CD45-targeting mAbs in mice. The mAbs generated showed robust affinity and specificity, which are crucial factors for differentiate circulating tumor cells from white blood cells in human breast cancer patient samples. Only 1 cell fusion and 2 cyclic sub-cloning steps were necessary before mAbs with satisfactory performance were obtained

Traceable machine learning real-time quality control based on patient data

Objectives Patient-based real-time quality control (PBRTQC) has gained attention as an alternative/integrative tool for internal quality control (iQC). However, it is still doubted for its performance and its application in real clinical settings. We aim to generate a newly and easy-to-access patient-based real-time QC by machine learning (ML) traceable to standard reference data with assigned values by National Institute of Metrology of China (NIM), and to compare it with PBRTQC for clinical validity evaluation. Methods For five representative biochemistry analytes, 1,195 000 patient testing results each were collected. After data processing, independent training and test sets were divided. Machine learning internal quality control (MLiQC) was set up by Random Forest in ML and was validated by way of both metrology algorithm traceability and 4 PBRTQC methods recommended by IFCC analytical working group. Results MLiQC were established. As an example of albumin (ALB) at the critical bias, the uncertainty of MLiQC was 0.14%, which was evaluated by standard reference data produced by NIM. Compared with four optimal PBRTQC methods at critical bias, the average of the number of patient samples from a bias introduced until detected (ANPed) of MLiQC averagely decreased from 600 to 20. The median and 95 quantiles of NPeds (MNPed and 95NPed) of MLiQC were superior to all optimal PBRTQCs above 90% for all test items. Conclusions MLiQC is highly superior to PBRTQC and well-suited in real settings. The validation of the model from two aspects of algorithm traceability and clinical effectiveness confirms its satisfactory performance