Objective: This study aimed to investigate the inhibitory effects of Brucea javanica oil oral emulsion (BJOOE) on primary liver cancer induced by diethylnitrosamine (DEN). Methods:Rats were randomly divided into the control group, model group, and BJOOE group. Rats were given free access to water. DEN was administered intragastrically to induce liver cancer in rats. Five weeks later, rats were intragastrically administered with BJOOE for five times per week. The rats were killed after 14 weeks. Abdominal aortic blood samples were collected. The contents of ALT, AST, ALP, γ-GT, and AFP of serum were detected by an automatic biochemical analyzer. The liver index, spleen index, thymus index, and changes in liver cancer nodules of the surface were observed in rats. Changes in the number of liver cancer nodules of the surface were detected by imaging. Results:Compared with the control group, the liver index, spleen index, and number of nodules of the model group significantly increased, whereas the thymus index significantly decreased (P<0.01). The levels of ALT, AFP, AST, ALP, andγ-GT of serum in the model group were significantly higher than those in the control group (P<0.01). Compared with the model group, BJOOE significantly reduced the liver index, spleen index, and number of cancer nodules, but increased the thymus index in the liver of rats with cancer (P<0.01). The levels of ALT, AFP, AST, ALP, andγ-GT of serum in rats with hepatic carcinoma significantly improved (P<0.01 or P<0.05). Conclusion:BJOOE could inhibit primary liver cancer, and the underlying mechanisms are complex.

Objective Based on the Kabat-Zinn's mindfulness decompression therapy and Teasdale's mindfulness cognitive therapy,and using the solution-focused approach as the frame structure,we establish comprehensive,standard mindfulness interventions scheme of domiciliary patients with chronic obstructive pulmonary disease,which can provide the basis for the development of the community and residential care.Methods Twenty-six experts were selected as the target of the study and two rounds of correspondence were used to establish the final mindfulness intervention plan of the domiciliary patients with chronic obstructive pulmonary disease.Meanwhile,the reliability and representativeness of the consultation are tested by using the coordination degree,positive coefficient and authoritative coefficient of expert opinions.Results The positive coefficient of the two round correspondence experts were 88.46%(23/26)and 100.00%(23/23),and the expert authority coefficient was 0.90 and 0.91.The variation coefficient of the indicators after two rounds of expert consultation was 0.04-0.14,the coordination coefficient of experts was 0.32(P＜0.01)and 0.59(P＜0.01)respectively.The final construct of domiciliary patients of chronic obstructive pulmonary disease with the intervention programme consists of 5 steps,25 entries,which was suitable for the positive reading intervention scheme.Conclusions The results show that experts enquiry for representative and high credibility,and the mindfulness intervention plan of domiciliary patients with chronic obstructive pulmonary disease is scientific and practical.

Objective:To evaluate the performance of an artificial intelligent (AI)-based automated digital cell morphology analyzer (hereinafter referred as AI morphology analyzer) in detecting peripheral white blood cells (WBCs).Methods:A multi-center study. 1. A total of 3010 venous blood samples were collected from 11 tertiary hospitals nationwide, and 14 types of WBCs were analyzed with the AI morphology analyzers. The pre-classification results were compared with the post-classification results reviewed by senior morphological experts in evaluate the accuracy, sensitivity, specificity, and agreement of the AI morphology analyzers on the WBC pre-classification. 2. 400 blood samples (no less than 50% of the samples with abnormal WBCs after pre-classification and manual review) were selected from 3 010 samples, and the morphologists conducted manual microscopic examinations to differentiate different types of WBCs. The correlation between the post-classification and the manual microscopic examination results was analyzed. 3. Blood samples of patients diagnosed with lymphoma, acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndrome, or myeloproliferative neoplasms were selected from the 3 010 blood samples. The performance of the AI morphology analyzers in these five hematological malignancies was evaluated by comparing the pre-classification and post-classification results. Cohen′s kappa test was used to analyze the consistency of WBC pre-classification and expert audit results, and Passing-Bablock regression analysis was used for comparison test, and accuracy, sensitivity, specificity, and agreement were calculated according to the formula.Results:1. AI morphology analyzers can pre-classify 14 types of WBCs and nucleated red blood cells. Compared with the post-classification results reviewed by senior morphological experts, the pre-classification accuracy of total WBCs reached 97.97%, of which the pre-classification accuracies of normal WBCs and abnormal WBCs were more than 96% and 87%, respectively. 2. The post-classification results reviewed by senior morphological experts correlated well with the manual differential results for all types of WBCs and nucleated red blood cells (neutrophils, lymphocytes, monocytes, eosinophils, basophils, immature granulocytes, blast cells, nucleated erythrocytes and malignant cells r>0.90 respectively, reactive lymphocytes r=0.85). With reference, the positive smear of abnormal cell types defined by The International Consensus Group for Hematology, the AI morphology analyzer has the similar screening ability for abnormal WBC samples as the manual microscopic examination. 3. For the blood samples with malignant hematologic diseases, the AI morphology analyzers showed accuracies higher than 84% on blast cells pre-classification, and the sensitivities were higher than 94%. In acute myeloid leukemia, the sensitivity of abnormal promyelocytes pre-classification exceeded 95%. Conclusion:The AI morphology analyzer showed high pre-classification accuracies and sensitivities on all types of leukocytes in peripheral blood when comparing with the post-classification results reviewed by experts. The post-classification results also showed a good correlation with the manual differential results. The AI morphology analyzer provides an efficient adjunctive white blood cell detection method for screening malignant hematological diseases.

Objective:To establish autoverification rules for coagulation tests in multicenter cooperative units, in order to reduce workload for manual review of suspected results and shorten turnaround time (TAT) of test reports, while ensure the accuracy of results.Methods:A total of 14 394 blood samples were collected from fourteen hospitals during December 2019 to March 2020. These samples included: Rules Establishment Group 11 230 cases, including 1 182 cases for Delta check rules; Rules Validation Group 3 164 cases, including 487cases for Delta check; Clinical Application Trial Group 77 269 cases. Samples were analyzed for coagulation tests using Sysmex CS series automatic coagulation analyzers, and the clinical information, instrument parameters, test results, clinical diagnosis, medication history of anticoagulant and other relative results such as HCT, TG, TBIL, DBIL were summarized; on the basis of historical data, the 2.5 and 97.5 percentile of all data arranged from low to high were initially accumulated; on the basis of clinical suggestions, critical values and specific drug use as well as relative guidelines, autoverification rules and limits were established.The rules were then input into middleware, in which Stage I/Stage II validation was done. Positive coincidence, negative coincidence, false negative, false positive, autoverification pass rate, passing accuracy (coincidence of autoverification and manual verification) were calculated. Autoverification rules underwent trial application in coagulation results reports.Results:(1) The autoverification algorisms involve 33 rules regarding PT/INR, APTT, FBG, D-dimer, FDP,Delta check, reaction curve and sample abnormalities; (2)Autoverification Establishment Group showed autoverification pass rate was 68.42% (7 684/11 230), the false negative rate was 0%(0/11230), coincidence of autoverification and manual verification was 98.51%(11 063/11 230), in which positive coincidence and negative coincidence were respectively 30.09% (3 379/11 230) and 68.42%(7 684/11 230); Autoverification Validation Group showed autoverification pass rate was 60.37%(1 910/3 164), the false negative rate was 0%(0/11 230), coincidence of autoverification and manual verification was 97.79%(3 094/3 164), in which positive coincidence and negative coincidence were respectively 37.42%(1 184/3 164) and 60.37%(1 910/3 164); (3) Trialed implementation of these autoverification rules on 77 269 coagulation samples showed that the average TAT shortened by 8.5 min-83.1 min.Conclusions:This study established 33 autoverification rules in coagulation tests. Validation showedthese rules could ensure test quality while shortening TAT and lighten manual workload.