N Context.-The Coulter DxH 800 hematology analyzer can determine leukocyte numerical parameters (total leukocyte counts and differentials). It also measures intrinsic biophysical properties of these cells in their near-native state. These morphologic measurements are known as cell population data (CPD).Objective.-To study, for the first time, the biological variations of morphologic parameters or CPD and reinvestigate numerical parameters using the newest Coulter hematology analyzer.Design.-Forty adult volunteers (21 women, 19 men) were included. All participants maintained their normal lifestyles. Blood samples were drawn in duplicate by a single experienced phlebotomist and analyzed within 2 hours using a single analyzer. Before each batch analysis, the instrument quality controls were performed using the same lots of reagents.Results.-Within-subject (CV I ) and between-subjects (CV G ) biological variations for numerical parameters are smaller than previously reported. Cell population data have much smaller overall CV I and CV G compared to numerical parameters, suggesting that these parameters are less variable around the homeostatic set point intraindividually and interindividually. Index of individuality (ratio of CV I /CV G ) for CPD was low. In addition, intraday and interday biological variations of all parameters are fairly constant.Conclusions.-These observations are clinically valuable. Data on CV I and analytical precision may be used to generate objective delta-check values for use in quality management. Comparing CV I and CV G on CPD may allow us to decide the utility of traditional population-based reference ranges. Documentation of CPD on biological variations is an essential prerequisite in the development of any new application clinically.

Background: Poorly differentiated gastric adenocarcinoma (PDGA) is a common adenocarcinoma with less glandular structure in gastric cancer. To date, the factors affecting its prognosis remain unclear. In this study, we establish a novel prognostic nomogram for PDGA. Methods:We screened the Surveillance, Epidemiology, and End Results (SEER) database and downloaded data from PDGA patients who underwent surgery between 2010 and 2015. We explored their clinicopathological characteristics and important prognostic factors such as overall survival (OS), using univariate and multivariate Cox proportional hazards regression analyses, then constructed a prognostic nomogram using the resulting significant variables to predict the OS. We verified performance of the nomogram externally using a separate Chinese set, and further compared its ability as well as the 8 th edition of the American Joint Committee on Cancer (AJCC) staging system to predict prognosis.Results: A total of 3,887 patients in the SEER database met our inclusion criteria and were therefore included in the analysis. Multivariate analysis showed that age, sex, tumor size, prime site of tumor, T stage, N stage, and M stage were all independent prognostic factors for PDGA. These factors allowed successful establishment of a nomogram model with high predictive power, based on external verification using a Chinese set comprising 632 PDGA patients. The nomogram showed a better discrimination advantage than the 8 th edition of the AJCC staging system in predicting OS (C-index of nomogram vs. AJCC staging for SEER set: 0.707 vs. 0.663; Chinese set: 0.788 vs. 0.713). Conclusions:The nomogram, established herein, was more accurate in predicting the 1-, 3-, and 5-year OS of PDGA patients than the traditional AJCC TNA staging system. Successful establishment of a PDGA prognostic nomogram is a further step towards individualized and precise treatment of gastric cancer.

BackgroundDue to the limited diagnostic ability, the low detection rate of early gastric cancer (EGC) is a serious health threat. The establishment of the mapping between endoscopic images and pathological images can rapidly improve the diagnostic ability to detect EGC. To expedite the learning process of EGC diagnosis, a mucosal recovery map for the mapping between ESD mucosa specimen and pathological images should be performed in collaboration with endoscopists and pathologists, which is a time-consuming and laborious work.Methods20 patients at the Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital of Hangzhou Medical College from March 2020 to July 2020 were enrolled in this study. We proposed the improved U-Net to obtain WSI-level segmentation results, and the WSI-level results can be mapped to the macroscopic image of the specimen. For the convenient use, a software pipeline named as “Pathology Helper” for integration the workflow of the construction of mucosal recovery maps was developed.ResultsThe MIoU and Dice of our model can achieve 0.955 ± 0.0936 and 0.961 ± 0.0874 for WSI-level segmentation, respectively. With the help of “Pathology Helper”, we can construct the high-quality mucosal recovery maps to reduce the workload of endoscopists and pathologists.Conclusion“Pathology Helper” will accelerate the learning of endoscopists and pathologists, and rapidly improve their abilities to detect EGC. Our work can also improve the detection rate of early gastric cancer, so that more patients with gastric cancer will be treated in a timely manner.

Background Gastric cancer (GC) is a serious digestive tract disease that threatens human life worldwide, and the prognosis of gastric cancer accompanied by distant lymph node or the distant metastasis organs is worse. The purpose of this study was to investigate the role of circular RNA COL6A3_030 (circBase ID: hsa_circ_0006401; circRNADb ID: hsa_circ_28198; circBank ID: hsa_circCOL6A3_030) in GC metastasis. Methods qRT-PCR analysis using back-splicing primers and Sanger sequencing of PCR products were performed to identify circCOL6A3_030 in GC tissues and cell lines; RNA-FISH assay was performed to validate the subcellular localization of circCOL6A3_030. Transwell and wound-healing assays were carried out to evaluate the migration ability of GC cells. Western blot was conducted to detect the polypeptide encoded by circCOL6A3_030 in cells. Results circCOL6A3_030 was down-regulated in GC tissues and cell lines, while circCOL6A3_030 was up-regulated in GC with distant lymph node metastasis. The migration of circCOL6A3_030 silenced GC cells was significantly inhibited in both SGC-7901 and BGC-823 cell lines. Importantly, in vivo assay, silencing circCOL6A3_030 could reduce liver metastases from gastric cancer cells. Meanwhile, further studies suggested that circCOL6A3_030 encoded a small peptide that had a function as a tumor-promoting metastasis factor and immunohistochemistry confirmed the presence of this polypeptide. Conclusions To sum up, our study showed that circCOL6A3_030 promoted GC cell migration by encoding a small peptide called circCOL6A3_030_198aa. Therefore, our results highlight the potential role of circCOL6A3_030 for clinical diagnosis and treatment of GC with distant lymph node metastasis.