Purinergic P2Y Receptor Antagonists ; Consensus ; Cardiovascular System ; Cardiology ; Asia

Humans ; Sarcoma ; NFATC Transcription Factors ; RNA-Binding Protein EWS

Humans ; Colon, Descending ; Dendritic Cell Sarcoma, Follicular

Humans ; Glomerulonephritis, Membranoproliferative/pathology* ; Fibronectins

Objective: To investigate the clinicopathological features, molecular genetic features, differential diagnosis and prognosis of ELOC mutated renal cell carcinoma. Methods: From January 2015 to June 2022, 11 cases of renal cell carcinoma with clear-cell morphology, expression of CAⅨ and CK7 and no 3p deletion were collected. Two cases of ELOC mutant renal cell carcinoma were diagnosed using whole exome sequencing (WES). The clinical features, morphology, immunophenotype, FISH and WES results were analyzed. The relevant literature was reviewed. Results: The two patients were both male, aged 29 and 51 years, respectively. They were both found to have a renal mass by physical examination. The maximum diameters of the tumors were 3.5 cm and 2.0 cm, respectively. At the low magnification, the tumors were well-defined. The tumor cells showed a pushing border and were separated by thick fibrous bands, forming nodules. The tumor cells were arranged in a variety of patterns, including tubular, papillary, solid nest or alveolar. At high magnification, the tumor cells were large, with well-defined cell borders and clear cytoplasm or fine eosinophilic granules. CAⅨ was diffusely box-like positive in both cases. Case 1 was partially and moderately positive for CK7, strongly positive for CD10, diffusely and moderately positive for P504S, and weakly positive for 34βE12. In case 2, CK7 and CD10 were both partially, moderately positive and P504s were diffusely positive, but 34βE12 was negative. FISH results showed that both cases had no 3p deletion. ELOC c.235T>A (p.Y79N) mutation was identified using WES in case 1, while ELOC c.236_237inv (p.Y79C) mutation was identified in case 2. Conclusions: As a new clinical entity, ELOC mutated renal cell carcinoma may be underdiagnosed due to its overlap with clear cell renal cell carcinoma in morphology and immunophenotype. The diagnosis of renal cell carcinoma with ELOC mutation should be confirmed by morphology, immunohistochemistry, FISH and gene mutation detection. However, more additional cases are needed to explain its biological behavior and prognosis.
Humans ; Male ; Biomarkers, Tumor/genetics* ; Carcinoma, Renal Cell/pathology* ; Chromosome Aberrations ; Kidney Neoplasms/pathology* ; Molecular Biology ; Mutation ; Prognosis

Objective: To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfoliative cytology and its clinical values. Methods: A total of 3 033 urine exfoliated cytology samples were collected at the Henan People's Hospital, Capital Medical University, Beijing, China. Liquid-based thin-layer cytology was prepared. The slides were manually read under the microscope and digitally presented using a scanner. The intelligent identification and analysis were carried out using an artificial intelligence TPS assisted screening system. The Paris Report Classification System of Urinary Exfoliated Cytology 2022 was used as the evaluation standard. Atypical urothelial cells and even higher grade lesions were considered as positive when evaluating the recognition sensitivity, specificity, and diagnostic accuracy of artificial intelligence-assisted screening systems and human-machine collaborative cytologic screening methods in urine exfoliative cytology. Among the collected cases, there were also 1 100 pathological tissue controls. Results: The accuracy, sensitivity and specificity of the AI-assisted cytologic screening system were 77.18%, 90.79% and 69.49%; those of human-machine coordination method were 92.89%, 99.63% and 89.09%, respectively. Compared with the histopathological results, the accuracy, sensitivity and specificity of manual reading were 79.82%, 74.20% and 95.80%, respectively, while those of AI-assisted cytologic screening system were 93.45%, 93.73% and 92.66%, respectively. The accuracy, sensitivity and specificity of human-machine coordination method were 95.36%, 95.21% and 95.80%, respectively. Both cytological and histological controls showed that human-machine coordination review method had higher diagnostic accuracy and sensitivity, and lower false negative rates. Conclusions: The artificial intelligence TPS assisted cytologic screening system has achieved acceptable accuracy in urine exfoliation cytologic screening. The combination of manual screening and artificial intelligence TPS assisted screening system can effectively improve the sensitivity and accuracy of cytologic screening and reduce the risk of misdiagnosis.
Humans ; Artificial Intelligence ; Urothelium/pathology* ; Cytodiagnosis ; Epithelial Cells/pathology* ; Sensitivity and Specificity ; Urologic Neoplasms/urine*

Humans ; Castleman Disease/surgery* ; Liver

Objective: To examine a predictive model that incorporating high risk pathological factors for the prognosis of stage Ⅰ to Ⅲ colon cancer. Methods: This study retrospectively collected clinicopathological information and survival outcomes of stage Ⅰ~Ⅲ colon cancer patients who underwent curative surgery in 7 tertiary hospitals in China from January 1, 2016 to December 31, 2017. A total of 1 650 patients were enrolled, aged (M(IQR)) 62 (18) years (range: 14 to 100). There were 963 males and 687 females. The median follow-up period was 51 months. The Cox proportional hazardous regression model was utilized to select high-risk pathological factors, establish the nomogram and scoring system. The Bootstrap resampling method was utilized for internal validation of the model, the concordance index (C-index) was used to assess discrimination and calibration curves were presented to assess model calibration. The Kaplan-Meier method was used to plot survival curves after risk grouping, and Cox regression was used to compare disease-free survival between subgroups. Results: Age (HR=1.020, 95%CI: 1.008 to 1.033, P=0.001), T stage (T3:HR=1.995,95%CI:1.062 to 3.750,P=0.032;T4:HR=4.196, 95%CI: 2.188 to 8.045, P<0.01), N stage (N1: HR=1.834, 95%CI: 1.307 to 2.574, P<0.01; N2: HR=3.970, 95%CI: 2.724 to 5.787, P<0.01) and number of lymph nodes examined (≥36: HR=0.438, 95%CI: 0.242 to 0.790, P=0.006) were independently associated with disease-free survival. The C-index of the scoring model (model 1) based on age, T stage, N stage, and dichotomous variables of the lymph nodes examined (<12 and ≥12) was 0.723, and the C-index of the scoring model (model 2) based on age, T stage, N stage, and multi-categorical variables of the lymph nodes examined (<12, 12 to <24, 24 to <36, and ≥36) was 0.726. A scoring system was established based on age, T stage, N stage, and multi-categorical variables of lymph nodes examined, the 3-year DFS of the low-risk (≤1), middle-risk (2 to 4) and high-risk (≥5) group were 96.3% (n=711), 89.0% (n=626) and 71.4% (n=313), respectively. Statistically significant difference was observed among groups (P<0.01). Conclusions: The number of lymph nodes examined was an independent prognostic factor for disease-free survival after curative surgery in patients with stage Ⅰ to Ⅲ colon cancer. Incorporating the number of lymph nodes examined as a multi-categorical variable into the T and N staging system could improve prognostic predictive validity.
Male ; Female ; Humans ; Prognosis ; Neoplasm Staging ; Retrospective Studies ; Nomograms ; Lymph Nodes/pathology* ; Risk Factors ; Colonic Neoplasms/surgery*

OBJECTIVE: To construct a schistosomiasis transmission risk assessment system in Wuhan City and preliminary evaluate its application effect, so as to promote the rational allocation of schistosomiasis control resources and accelerate the progress towards schistosomiasis elimination. METHODS: The schistosomiasis risk assessment indicators were collected through referring schistosomiasis surveillance data of Wuhan City from 2014 to 2020, literature review and expert interviews. Indicators within each criterion and sub-criterion were screened using the Delphi method, and a hierarchical structure model was created based on analytic hierarchy process. Quantitative assignment of each indicator was conducted according to relative importance, and the weight and combination weight of each criterion were calculated in each analytic hierarchy framework to create a schistosomiasis transmission risk assessment system, which was used for the schistosomiasis transmission risk assessment in 12 national schistosomiasis surveillance sites in Wuhan City. RESULTS: A three-level schistosomiasis transmission risk assessment system was preliminarily constructed, which included a target layer, 5 criterion layers and 21 sub-criterion layers. Of all indicators in the criterion layer, transmission route had the highest weight (0.433), followed by source of Schistosoma japonicum infection (0.294); and among all indicators in the sub-criterion layer, S. japonicum infection in Oncomelania hupensis and sentinel mice had the highest combination weight (0.125), followed by prevalence of S. japonicum infection in humans (0.091) and bovines (0.053), snail control by chemical treatment (0.049), positive rate of inquiry examinations (0.048), allocation of schistosomiasis control professionals (0.045), and areas of submerged snail-infested settings (0.041). Of the 12 national schistosomiasis surveillance sites in Wuhan City, there were 5 sites with weights of > 0.8, 4 sites with weights of 0.6 to 0.8, and 3 sites with weights of < 0.6 in 2020. CONCLUSIONS A schistosomiasis transmission risk assessment system has been constructed based on analytic hierarchy process in Wuhan City, which may provide a evidence-based basis for health resource allocation and decision-making for schistosomiasis control.
Animals ; Humans ; Cattle ; Mice ; Analytic Hierarchy Process ; Schistosomiasis/prevention & control* ; Schistosomiasis japonica/epidemiology* ; Snails ; Risk Assessment

OBJECTIVE: To investigate the spatial distribution characteristics of the prevalence of advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody, and to examine the correlation between the prevalence of advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody in Hunan Province in 2020, so as to provide insights into advanced schistosomiais control in the province. METHODS: The epidemiological data of schistosomiasis in Hunan Province in 2020 were collected, including number of permanent residents in survey villages, number of advanced schistosomiasis patients, number of residents receiving serological tests and number of residents seropositive for anti-Schistosoma antibody, and the prevalence advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody were descriptively analyzed. Village-based spatial distribution characteristics of prevalence advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody were identified in Hunan Province in 2020, and the correlation between the revalence advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody was examined using Spearman correlation analysis. RESULTS: The prevalence of advanced schistosomiasis was 0 to 2.72% and the seroprevalence of anti-Schistosoma antibody was 0 to 20.25% in 1 153 schistosomiasis-endemic villages in Hunan Province in 2020. Spatial clusters were identified in both the prevalence of advanced schistosomiasis (global Moran's I = 0.416, P < 0.01) and the seroprevalence of anti-Schistosoma antibody (global Moran's I = 0.711, P < 0.01) in Hunan Province. Local spatial autocorrelation analysis identified 98 schistosomiasis-endemic villages with high-high clusters of the prevalence of advanced schistosomiasis, 134 endemic villages with high-high clusters of the seroprevalence of anti-Schistosoma antibody and 36 endemic villages with high-high clusters of both the prevalence of advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody in Hunan Province. In addition, spearman correlation analysis showed a positive correlation between the prevalence of advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody (r_s = 0.235, P < 0.05). CONCLUSIONS There were spatial clusters of the prevalence of advanced schistosomiasis and seroprevalence of anti-Schistosoma antibody in Hunan Province in 2020, which were predominantly located in areas neighboring the Dongting Lake. These clusters should be given a high priority in the schistosomiasis control programs.
Animals ; Humans ; Prevalence ; Seroepidemiologic Studies ; Schistosomiasis/epidemiology* ; Schistosoma ; Spatial Analysis ; Antibodies, Helminth ; China/epidemiology*