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Our work investigates the polycrystalline composite deformation behavior through multiscale simulations with experimental data at hand. Since deformation mechanisms on the micro-level link the ones on the macro-level and the nanoscale, it is preferable to perform micromechanical finite element simulations based on real microstructures. The image segmentation is a necessary step for the meshing. Our 2D EBSD images contain at least a few hundred grains. Machine learning (ML) was adopted to automatically identify subregions, i.e., individual grains, to improve local feature extraction efficiency and accuracy. Denoising in preprocessing and postprocessing before and after ML, respectively, is beneficial in high quality feature identification. The ML algorithms used were self-developed with the usage of inherent code packages (Python). The performances of the three supervised ML models—decision tree, random forest, and support vector machine—are compared herein; the latter two achieved accuracies of up to 99.8%. Calculations took about 0.5 h from the original input dataset (EBSD image) to the final output (segmented image) running on a personal computer (CPU: 3.6 GHz). For a realizable manual pixel sortation, the original image was firstly scaled from the initial resolution 10802 pixels down to 3002. After ML, some manual work was necessary due to the remaining noises to achieve the final image status ready for meshing. The ML process, including this manual work time, improved efficiency by a factor of about 24 compared to a purely manual process. Simultaneously, ML minimized the geometrical deviation between the identified and original features, since it used the original resolution. For serial work, the time efficiency would be enhanced multiplicatively.

Background Circulating genetically abnormal cells (CACs) with specific chromosome variations have been confirmed to be present in non‐small cell lung cancer (NSCLC). However, the diagnostic performance of CAC detection remains unclear. This study aimed to evaluate the potential clinical application of the CAC test for the early diagnosis of NSCLC. Methods In this prospective study, a total of 339 participants (261 lung cancer patients and 78 healthy volunteers) were enrolled. An antigen‐independent fluorescence in situ hybridization was used to enumerate the number of CACs in peripheral blood. Results Patients with early‐stage NSCLC were found to have a significantly higher number of CACs than those of healthy participants (1.34 vs. 0.19; P, Workflow of circulating genetically abnormal cells enumeration. Circulating genetically abnormal cell detection in early stage non‐small‐cell lung cancer was feasible. Circulating genetically abnormal cell test has good stability and adaptability for different patient populations. Circulating genetically abnormal cells could be used as a promising noninvasive biomarker for the early diagnosis of NSCLC.

The present study aimed to compare prostate cancer (PCa) and clinically significant PCa (csPCa) detection sensitivity between magnetic resonance imaging guided-biopsy (MRI-GB) and transrectal ultrasound-guided biopsy (TRUS-GB) in patients with ≥ 1 negative TRUS-GB, and to explore the additive value of TRUS-GB to MRI-GB. The meta-analysis of 18 studies demonstrated that MRI-GB had a similar sensitivity for PCa detection but a higher sensitivity for csPCa than TRUS-GB. In conclusion, there was limited value in combining TRUS-GB with MRI-GB compared with MRI-GB alone for csPCa detection in patients with one or more negative TRUS-GBs that were suspicious of having PCa.

Objective: This paper sets out to investigate the miR-205 and HMGB1 expressions in chronic periodontitis (PO) patients and their associations with the inflammatory factors. Methods: From February 2016 to May 2018, 68 PO patients treated in our hospital were recruited for the study and placed in a patient group (PG), and 60 healthy volunteers were also recruited and placed in a healthy group (HG). Serum samples were collected from both groups for the identification of miR-205 using qPCR, as well as to determine the HMGB1 and inflammatory factor (IL-1β, IL-6, TNF-α) expression levels using ELISA. The correlations of the miR-205 and HMGB1 expression levels with the periodontal clinical indicators and the inflammatory factors were analyzed using a correlation analysis. Results: In comparison with the HG expression, the serum miR-205 expression was lower, and the HMGB1 was elevated in PG (P < 0.05). An ROC curve analysis showed that the areas under the curve (AUCs) of the serum miR-205 and HMGB1 expressions in diagnosing PO were 0.936 and 0.955 respectively. However, the serum miR-205 expression in PG increased while the HMGB1 expression decreased post treatment (P < 0.05). A correlation analysis revealed an inverse association between the serum miR-205 expression levels and the periodontal clinical indicators [bleeding index (BI), probing depth (PD), plaque index (PLI), and attachment loss (AL)], and the inflammatory factors [interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-α (TNF-α)], but there was a positive association between the HMGB1 expression level and these parameters. Conclusions: miR-205 and HMGB1 are closely related to the progression of PO, and may be candidate biomarkers for the diagnosis and treatment of PO.

GNSS based Bistatic Forward Looking Synthetic Aperture Radar (GNSS-BFLSAR) system is particular kind of passive bistatic SAR system. In the system, GNSS is used as the transmitter, while the receiver is mounted on the airplane. The airplane travels along a straight line and the imaging target is in the front. GNSS-BFLSAR is benefited from low cost and good safety. It is widely used in self-landing, self-navigating and battle field information acquiring, etc. This paper is focusing on the investigation of point target 2-D spectrum of GNSS-BFLSAR and Point Spread Function (PSF) generation method. First, a geometric model of such system is built, followed by the generation of echo signal. Then, the analytical formula of 2-D spectrum is obtained. Next, the PSF generation is provided. In the end, the whole procedure is simulated with Matlab. The simulation result verifies the validity of theoretical analysis of this paper and makes a foundation for imaging formation research of such system in the future.

Background Most previous studies of circulating tumor cells (CTCs) are based on the CellSearch platform, but CellSearch has a number of limitations. This study aimed to use the LiquidBiopsy system and immunofluorescence to test the human epidermal growth factor receptor 2 (HER2) status of CTCs in patients with breast cancer. Materials and Methods The LiquidBiopsy system was used to detect HER2-positive (HER2 + ) cells in whole blood by microfluidic immunomagnetic bead screening and immunofluorescence assay, according to the manufacturer;s instructions. HER2 expression on CTCs was assessed using the Ariol system, calibrated through spiking experiments of 100 cells (BT474, SKBR3, A431, and MDA-MB-231) and 2.5 × 10 7 white blood cells/mL from healthy donors. Seventy-one patients with breast cancer and 107 non-cancer donors consented to provide blood. Results Based on breast cancer cell lines experiments, HER2 + CTCs were defined as CTCs with HER2 immunofluorescence intensity ≥ 3.5 times higher than the CD45 immunofluorescence intensity (100% sensitivity and 99.9% specificity). Among the 71 patients with breast cancer, 31 (43.7%) had HER2 + tumor. Among the HER2 + patients, 41.9% (13/31) were found to be HER2 + based on CTC ≥ 1, and 25.8% (8/31) were positive based on CTC ≥ 3. In HER2-negative patients by pathologic examination, 1 (2.5%) patient was found to have ≥ 3 HER2 + CTCs, whereas 15 (37.5%) patients had ≥ 1 HER2 + CTC. HER2 + CTCs were detected at all stages, even in early breast cancer, but the detection rate was higher in metastatic breast cancer. Conclusion This proof-of-concept study strongly suggests that HER2 + CTCs can be detected using the LiquidBiopsy system.