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Tuo, X.

Publications and source records attributed to Tuo, X..

2 recordsLinked to original sources

Deep learning-based adaptive detection of fetal nucleated red blood cells

Aimthis study, we established an artificial intelligence system for rapid identification of fetal nucleated red blood cells (fNRBCs). MethodDensity gradient centrifugation and magnetic-activated cell sorting were used for the separation of fNRBCs from umbilical cord blood. The cell block technique was used for fixation. We proposed a novel preprocessing method based on imaging characteristics of fNRBCs for region of interest (ROI) extraction, which automatically segmented individual cells in peripheral blood cell smears. The discriminant information from ROIs was encoded into a feature vector and pathological diagnosis were provided by the prediction network. ResultsFour umbilical cord blood samples were collected and validated based on a large dataset containing 260 samples. Finally, the dataset was classified into 3,720 and 1,040 slides for training and testing, respectively. In the test set, classifier obtained 98.5% accuracy and 96.5% sensitivity. ConclusionTherefore, this study offers an effective and accurate method for fNRBCs preservation and identification.

pathology↗

The differential distribution of bacteria between cancerous and noncancerous ovarian tissues in situ

The female upper reproductive tract, including the uterus, fallopian tubes and ovaries, is believed to be a sterile environment. With the improvement of bacterial detection, the theory of the sterile female upper reproductive tract has been frequently challenged in recent years. However, thus far, no researchers have used ovaries as study targets. Six women who were diagnosed with ovarian cancer were included in the cancer group, and ten women who were diagnosed with a noncancerous ovarian condition (including three patients with uterine myoma and seven patients with uterine adenomyosis) were included in the control group. Immunohistochemistry staining using an antibacterial lipopolysaccharide (LPS) antibody was used to confirm the presence of bacteria in the ovarian tissues. In addition, 16S rRNA sequencing was used to compare the differences in the bacteria between ovarian cancer tissues and noncancerous ovarian tissues. BugBase and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) were used to predict the functional composition of the bacteria. Bacterial LPS was present in ovarian cancer tissue and noncancerous ovarian tissue, which implied the presence of bacteria in ovarian tissue. When compared to the noncancerous ovarian bacteria at the phylum level, the cancerous ovarian bacteria were composed of increased Aquificae and Planctomycetes and decreased Crenarchaeota. When predicting metagenomes, gene functions associated with the potentially pathogenic and the oxidative stress-tolerant phenotype were enriched in the ovaries of the cancer group. Forty-six significantly different KEGG pathways existed in the ovarian bacteria of the cancer group compared to that of the control group. Different bacteria compositions were present in cancerous and noncancerous ovarian tissues. Author summaryAbdominal solid viscera have always been believed to be absolutely sterile. With the improvement of bacterial detection, this concept is being challenged. Researchers found some bacteria existed in endometrial diseases, the question of whether the ovaries are sterile is still unclear. Therefore, we assume that the bacteria in ovarian tissue are associated with ovarian cancer. When compared to the noncancerous ovarian bacteria at the phylum level, the cancerous ovarian bacteria were composed of increased Aquificae and Planctomycetes and decreased Crenarchaeota. When predicting metagenomes, gene functions associated with the potentially pathogenic and the oxidative stress-tolerant phenotype were enriched in the ovaries of the cancer group. Forty-six significantly different KEGG pathways existed in the ovarian bacteria of the cancer group compared to that of the control group. Different bacteria compositions were present in cancerous and noncancerous ovarian tissues.

microbiology↗