Objective To predict the lymphovascular invasion(LVI)status of breast cancer patients based on digital breast tomo-synthesis(DBT)intratumoral and peritumoral radiomics nomogram.Methods A total of 192 breast cancer patients from 2 institu-tions were retrospectively selected,in which institution 1 was used for train(n=113)and test(n=49),while institution 2 was used for external validation(n=30).Radiomics features were extracted and selected based on intratumoral and peritumoral 1 mm regions from DBT images.Different machine learning algorithms were used to construct intratumoral,peritumoral,and combined intratumoral and peritumoral models,respectively.Patient clinical data were analyzed by both univariate and multivariate logistic regression analy-ses to identify independent risk factors for the clinical imaging model.The performance of the models was evaluated using the receiver operating characteristic(ROC)curve.The radiomics features with the optimal diagnostic performance and the selected clinical imaging features were combined to construct a comprehensive clinical-radiomics model,and a nomogram was drawn.Results The combined intratumoral and peritumoral model was the optimal radiomics model.Maximum tumor diameter[odds ratio(OR)=1.486,P=0.014],suspicious malignant calcifications(OR=2.898,P=0.015),and axillary lymph node(ALN)metastasis(OR=3.615,P<0.001)were independent risk factors for LVI positive.Furthermore,the area under the curve(AUC)of the comprehensive clinical-radiomics model in the training set,test set and external valida-tion set was 0.889,0.916,and 0.862,respectively,which was higher than those of the combined intratumoral and peritumoral model(0.858,0.849,0.844)and the clinical imaging model(0.743,0.759,0.732).Conclusion The predictive nomogram,derived from both radiomics and clinical imaging features,is relatively accurate in identifying future LVI occurrence in breast cancer,demonstra-ting its potential as an assistive tool for clinicians to devise individualized treatment regimes.

Objective To predict the lymphovascular invasion(LVI)status of breast cancer patients based on digital breast tomo-synthesis(DBT)intratumoral and peritumoral radiomics nomogram.Methods A total of 192 breast cancer patients from 2 institu-tions were retrospectively selected,in which institution 1 was used for train(n=113)and test(n=49),while institution 2 was used for external validation(n=30).Radiomics features were extracted and selected based on intratumoral and peritumoral 1 mm regions from DBT images.Different machine learning algorithms were used to construct intratumoral,peritumoral,and combined intratumoral and peritumoral models,respectively.Patient clinical data were analyzed by both univariate and multivariate logistic regression analy-ses to identify independent risk factors for the clinical imaging model.The performance of the models was evaluated using the receiver operating characteristic(ROC)curve.The radiomics features with the optimal diagnostic performance and the selected clinical imaging features were combined to construct a comprehensive clinical-radiomics model,and a nomogram was drawn.Results The combined intratumoral and peritumoral model was the optimal radiomics model.Maximum tumor diameter[odds ratio(OR)=1.486,P=0.014],suspicious malignant calcifications(OR=2.898,P=0.015),and axillary lymph node(ALN)metastasis(OR=3.615,P<0.001)were independent risk factors for LVI positive.Furthermore,the area under the curve(AUC)of the comprehensive clinical-radiomics model in the training set,test set and external valida-tion set was 0.889,0.916,and 0.862,respectively,which was higher than those of the combined intratumoral and peritumoral model(0.858,0.849,0.844)and the clinical imaging model(0.743,0.759,0.732).Conclusion The predictive nomogram,derived from both radiomics and clinical imaging features,is relatively accurate in identifying future LVI occurrence in breast cancer,demonstra-ting its potential as an assistive tool for clinicians to devise individualized treatment regimes.

Background Gastric carcinogenesis is a multifactorial and complex process, in which long non-coding RNAs (lncRNAs) play important roles as oncogenes or antioncogenes. Research has found that the expression of lncRNA LINC02859 is down-regulated in gastric cancer tissues and correlated with the degree of tumor differentiation and TNM stage, and also plays an important role in the development of malignant transformation of cells induced by environmental carcinogen N-methyl-N'-nitro-N-nitrosoguanidine (MNNG), but its mechanism of action is still unclear. Objective To explore the role and potential regulatory mechanism of gastric cancer-associated lncRNA LINC02859 in MNNG-induced malignant transformation of human normal gastric mucosal cells (GES-1). Methods A total of 110 gastric cancer patients from a high incidence area of gastric cancer in Gansu Province were selected, and their cancer tissues and normal gastric mucosa tissues adjacent to the cancer were collected to detect the expression level of LINC02859 by real-time quantitative PCR (RT-qPCR). High-throughput sequencing and bioinformatics analysis of the tissues were used to identify the potential signaling pathways regulated by the genes co-expressed with LINC02859. GES-1 cells at 70%-80% cell fusion with low cell passage number and normal morphology were incubated with 0, 0.25 and 0.5 μmol·L⁻¹ MNNG solution for 48 h and the LINC02859 expression level was detected. Cell proliferation activity was detected by Cell Counting Kit-8 (CCK-8), clone formation was detected by plate clone formation assay, and cell migration ability was detected by scratch assay to evaluate the effects of MNNG on cell morphology and function. The expression levels of key proteins of Wnt signaling pathway were detected by RT-qPCR and Western blotting. Results The RT-qPCR results showed that LINC02859 was lowly expressed in the gastric cancer tissues compared with the paracancerous tissues, and the difference was statistically significant (P < 0.05). The pathway enrichment analysis showed that LINC02859 potentially regulated the Wnt pathway. The in vitro malignant transformation assay suggested that after the MNNG exposure, the malignant cells of passage 5 (MC-5) had altered morphology, increased number of colony formation, and higher proliferation and migration ability than the control cells; compared with the normal GES-1 cells, LINC02859 gene expression levels were reduced in the 0.25 μmol·L⁻¹ and the 0.5 μmol·L⁻¹ MNNG-exposed GES-1 cells; the expression levels of key proteins of the Wnt pathway, transcription factor 7 (TCF7), Axis inhibitor (Axin1), phosphorylation of glycogen synthase kinase-3 beta (p-GSK-3β), casein kinase 1 (CK1), and β-catenin, were elevated in the cells after 0.5 μmol·L⁻¹ MNNG exposure (P < 0.05); whereas, overexpression of LINC02859 suppressed the activating effect of MNNG on the Wnt pathway. Conclusion LINC02859 is lowly expressed in the cancer tissues of gastric cancer patients. MNNG exposure induces morphological and functional changes in GES-1 cells, down-regulated expression of LINC02859, and activation of the Wnt signaling pathway; overexpression of LINC02859 inhibits the activation of the Wnt signaling pathway in the gastric carcinogenesis induced by MNNG exposure.

Objective: To evaluate the effectiveness of deep learning model trained on routine CT scans when identity the malignant and benign lung nodule on target CT scans dataset. Methods: This retrospective study enrolled 923 patients with lung nodules found by chest CT scan in Shanghai Chest Hospital from January 2016 to December 2018. A total of 969 nodules with pathological report were analyzed. The deep learning based pulmonary malignant prediction method in a fine-grained classification manner was used to make the prediction, and the AUC (the area under the curve), accuracy, sensitivity and specificity of routine CT scans and target CT scans were compared, and Delong test and IDI (Integrated Discrimination Improvement) were employed to provide statistical results. Furthermore, statistical methods were used to investigate the differences between the benign and malignant classification of nodules on routine CT and on target CT. Results: In the benign and malignant discrimination task, AUC, accuracy, sensitivity and specificity on the routine scans were 0.81, 82.0%, 86.0% and 56.6% respectively, while the AUC, accuracy, sensitivity and specificity on the target scans were 0.84, 85.0%, 88.8% and 60.5% respectively. The IDI was 0.056 (Z test, P<0.05), and there was statistically significant difference in ROC (Delong test, P=0.01). Conclusions The deep learning model trained on the data set of routine CT scans can achieve better diagnostic efficiency in target CT scans data.

Gastrointestinal stromal tumors (GISTs) are derived from non-directed differentiation of gastrointestinal mesenchymal tissue, which lack of typical clinical symptoms, and many asymptomatic GISTs are often found on physical examination. The tumor is primarily through implantation metastasis and blood metastasis. Currently, conventional medical imaging methods, such as X-ray barium meal, US, CT, MRI, PET/CT and ES, are still the main means of diagnosis of GISTs. Early diagnosis and early treatment are key factors of the prognosis in GISTs. Therefore, we need to be proficient in various medical imaging methods, then apply them to the diagnosis of GISTs, and to provide comprehensive and valuable information for clinical practice. Through retrieving and consulting literature of medical imaging associated with GISTs, this paper reviews the current status and progress of medical imaging in diagnosis of GISTs.
Gastrointestinal Neoplasms ; Gastrointestinal Stromal Tumors ; Humans ; Magnetic Resonance Imaging ; Prognosis

Gastrointestinal stromal tumors (GISTs) are derived from non -directed differentiation of gastrointestinal mesenchymal tissue, which lack of typical clinical symptoms, and many asymptomatic GISTs are often found on physical examination. The tumor is primarily through implantation metastasis and blood metastasis. Currently, conventional medical imaging methods, such as X-ray barium meal, US, CT, MRI, PET/CT and ES, are still the main means of diagnosis of GISTs. Early diagnosis and early treatment are key factors of the prognosis in GISTs. Therefore, we need to be proficient in various medical imaging methods, then apply them to the diagnosis of GISTs, and to provide comprehensive and valuable information for clinical practice. Through retrieving and consulting literature of medical imaging associated with GISTs, this paper reviews the current status and progress of medical imaging in diagnosis of GISTs.

Gastrointestinal stromal tumors (GISTs) are derived from non -directed differentiation of gastrointestinal mesenchymal tissue, which lack of typical clinical symptoms, and many asymptomatic GISTs are often found on physical examination. The tumor is primarily through implantation metastasis and blood metastasis. Currently, conventional medical imaging methods, such as X-ray barium meal, US, CT, MRI, PET/CT and ES, are still the main means of diagnosis of GISTs. Early diagnosis and early treatment are key factors of the prognosis in GISTs. Therefore, we need to be proficient in various medical imaging methods, then apply them to the diagnosis of GISTs, and to provide comprehensive and valuable information for clinical practice. Through retrieving and consulting literature of medical imaging associated with GISTs, this paper reviews the current status and progress of medical imaging in diagnosis of GISTs.

Objective To study the CT characteristics of rare renal malignant tumors.Methods 7 cases with rare renal malignant tumors confirmed by operation and pathology were reviewed and their CT manifestations were analyzed retrospectively.In clinical, all cases had abdomen pain,6 cases had macroscopic haematuria,and 1 case had asymptomatic by chance.Results Of 7 cases,3 ca-ses were sarcomatoid carcinoma,1 case was carcinosarcoma,1 case was malignant mesenchymal tumor,1 case was lymphoma,and 1 case was neuroendocrine carcinoma.The diameter was about 4.0-12.3 cm.1 case had uniform density,6 cases uneven,and the boundary was not clear.Conclusion The rare renal malignant tumors are misdiagnosed easily.Combined clinical data with imaging performance are helpful to make comprehensive analysis,and to improve accuracy rate for diagnosis,definite diagnosis still depends on pathological examination.

Objective To investigate the numbers, sizes and types distribution of diatoms in drowned and postmortem immersed rabbits’ lungs. Methods Sixty-two rabbits were randomly divided into drowning group (n=30), postmortem immersion group (n=30) and land death group (n=2), and the diatoms in each lung lobe were analyzed quantitatively and qualitatively by microwave digestion and scanning electron microscopy. Results In the drowning group, the diatoms were detected in each lung lobe with Cyclotella and Melosira in the majority. In the postmortem immersion group, Cyclotella was in the majority. And the diatoms weren’t detected in some lung lobes in postmortem immersion. There were significant dif-ferences in the detection rates of upper lobe of left lung, middle lobe and cardiac lobe of right lung in two groups (P<0.05). Conclusion Based on the microwave digestion and scanning electron microscopy, the numbers, sizes and types distribution of diatoms in drowned and postmortem immersed rabbits ’ lungs can be analyzed and used as references for testing theory.

Objective To analyze the variations of glycerol-3-phosphate dehydrogenase 1 like gene (GPD1-L) and address the association with sudden m anhood death syndrom e (SMDS). Methods The genom ic DNA was extracted from blood sam ples of the SMDS group and the norm alcontrolgroup.The exons, exon-in-tron boundaries and 3′-U TRs of coding region of GPD1-L w ere PCRam plified and DNAsequenced di-rectly to confirm the types of variations. The genotype frequency and allele frequency w ere analyzed statistically. Results There w ere tw ovariants in the SMDS group, c.465C>Tand c.*18G>T, the latter existed certain degree difference of genotype distribution and allele frequency betw een the SMDS group and the control group, but there was no statistically significant (P>0.05). Conclusion The relation be-tw een gene m utation of GPD1-L and the occurrence of Chinese SMDS deserves a further research.