OBJECTIVETo illustrate the early alteration of plasminogen activator inhibitor-1 (PAI-1) in the recipients of hematopoietic stem cell transplantation (HSCT) and explore its clinical significance in transplantation-associated thrombotic complications.

METHODSNinety-five patients undergoing HSCT were enrolled in this study. PAI-1 level and other hemostatic parameters were measured by enzyme linked immunosorbent assay (ELISA) in platelet poor plasma samples from patients on conditioning therapy and then weekly until four weeks after HSCT.

RESULTSSignificant increase in PAI-1 was detected after conditioning treatment, followed by a diminution in the very week on transplantation (week 0), then increased with in time after transplantation. According to the occurrence of transplant-associated complications, patients were classified into four groups: thrombus group \[veno-occlusive disease (VOD) (n = 5), thrombotic microangiopathy (TMA) n = 1\], aGVHD group (n = 29), infection group (n = 19) and non-complication group (n = 41). One of 30 patients (3.3%) was diagnosed as thrombus in the auto-HSCT group, while five of 65 patients (7.7%) did in the allo-HSCT group. PAI-1 level of thrombotic patients was significantly increased compared with non-thrombotic subjects, and the patients without thrombotic complications have higher PAI-1 level in the allo-HSCT group than in auto-HSCT group. All the patients with complications presented with significantly increased PAI-1 compared with those with no complications (P < 0.05). The six patients with thrombotic complications showed extremely elevated PAI-1 \[(62.8 +/- 7.5) microg/L\] compared with that of aGVHD patients \[(45.1 +/- 9.1) microg/L\] or infection patients \[(50.0 +/- 11.2) microg/L\] post-HSCT (P < 0.05).

CONCLUSIONThe increase in plasma PAI-1 may be a specific mark for transplantation-associated thrombotic complications. Increased PAI-1 reflects the development of thrombotic complications. Extreme elevation of PAI-1 contributes to the early diagonsis of VOD and TMA after HSCT.

The objective of this study was to investigate the alterations of cytokines TNF-alpha, IL-1beta and IFN-gamma at early phase after allogeneic hematopoietic stem cell transplantation and in the course of preconditioning, and to explore the relation of these cytokines with transplant-related complications. Alterations of TNF-alpha, IL-1beta, and IFN-gamma levels in serum were detected by ELISA in 95 patients received allogeneic hematopoietic stem cell transplantation (among them 43 cases with GVHD, 5 cases with thrombosis, 31 cases with infection) and 20 in healthy adults. Alterations of the three cytokines were analyzed during the preconditioning and the early phase after transplantation. The results showed that the TNF-alpha levels in aGVHD patients underwent allo-HSCT were already higher than that in normal controls before preconditioning (p<0.01), other patients did not show significant change during this course. TNF-alpha level in all patients were higher than that at day 4 of preconditioning, then decreased at end of preconditioning (p<0.05). TNF-alpha level increased at occurrence of aGVHD, thrombosis and infection, which is most significant in patients with aGVHD, and less significant in patients with infection as compared with patients with thrombosis (p<0.05). TNF-alpha level began to increase at 2 weeks before aGVHD and thrombosis developed in patients, while TNF-alpha levels did not change in patients with infection at the same time. IL-1beta levels did not change during preconditioning, but increased at time of aGVHD, thrombosis and infection in patients, in which IL-1beta levels in patients with thrombosis increased obviously, and more obviously in patients with aGVHD than that in patients with infection (p<0.01). IL-1beta levels in patients with aGVHD began to increase at 1 week before aGHVD developed, but IL-1beta levels in patients with thrombosis began to increase at two weeks before complication developed. IFN-gamma levels did not change in all patients during the process of transplantation. It is concluded that the alterations of cytokine levels exist during the course of allo-HSCT, which reflects the vascular damage following preconditioning and occurrence of some transplant associated complications. Levels of TNF-alpha and IL-1beta are closely related to aGVHD or thrombotic complications. Monitoring changes of TNF-alpha and IL-1beta levels contributes to early discovery of aGVHD and thrombotic complications.
Adolescent ; Adult ; Child ; Female ; Graft vs Host Disease ; diagnosis ; Hematopoietic Stem Cell Transplantation ; Humans ; Interferon-gamma ; metabolism ; Interleukin-1beta ; metabolism ; Male ; Middle Aged ; Thrombosis ; diagnosis ; Transplantation Conditioning ; methods ; Transplantation, Homologous ; Tumor Necrosis Factor-alpha ; metabolism ; Young Adult

The objective of study was to compare the influences of wortmannin on platelet aggregation and platelet membrane surface glycoproteins GPIb expression after thrombin receptor activation, and to investigate the role of phosphatidylinositol 3-kinase (PI3-K) and myosin light chain kinase (MLCK) in the course of thrombin receptor activation. Peptide SFLLRN (PAR1-AP) and AYPGKF (PAR4-AP) were used for stimulating platelet, and the changes of platelet aggregation and GPIb were analyzed with 100 nmol/L wortmannin (inhibitor of PI3-K) and 10 micromol/L wortmannin (inhibitor of MLCK). The results indicated that the platelet activation was influenced by either concentration of wortmannin in response to PAR stimulation. Platelet aggregation was apparently inhibited by 10 micromol/L wortmannin through both PAR peptides, and was slightly inhibited by 100 nmol/L wortmannin only under PAR1-AP activation. In addition, GPIbalpha internalization was partly inhibited by 100 nmol/L wortmannin in response to PAR1 (p < 0.05 at 1, 2, 5 min) and PAR4 (p < 0.05 at 2, 5, 10 min) activation. Meanwhile, 10 micromol/L wortmannin induced little change for GPIbalpha centralisation in the course of PAR activation, with a delayed restoration of surface GPIbalpha observed under PAR1-AP activation, and no change of GPIbalpha redistribution existed under PAR4-AP activation. It is concluded that the different roles of PI3-K and MLCK exist in the course of thrombin receptor activation. PI3-K accelerates the short course of GPIb centralisation for two PAR signal pathways, while MLCK inhibits the restoration of GPIbalpha in PAR1 pathway.
Adult ; Androstadienes ; pharmacology ; Female ; Humans ; Male ; Myosin-Light-Chain Kinase ; metabolism ; Phosphatidylinositol 3-Kinase ; metabolism ; Platelet Activation ; drug effects ; Platelet Aggregation ; Receptors, Thrombin ; metabolism ; physiology ; Signal Transduction

OBJECTIVE: To investigate the genetic carrier rate of thalassemia and its gene mutation types as well as the distribution characteristics among the people in Lingshui Li autonomous county of Hainan province, so as to provide the basis for making the prevention programs of thalassemia in administrative departments. METHODS: Samples were collected from couples undergoing premarital and pregestational screenings, in which the positive ones in preliminary screening were further tested by genetic diagnoses and the genotypes were analyzed. RESULTS: The rate of thalassemia gene carriers was 19.41% （274/1412） of the couples of childbearing age in Lingshui Li autonomous County of Hainan Province. In these carriers,α-thalassemia accounted for 83.21%（228/274）, β-thalassemia for 8.03%（22/274）, and both α-and β-thalassemia gene accounted for 8.76% （28/274）. CONCLUSION The carrying rate of thalassemia gene in population Lingshui Li autonomous county of Hainan province is high, and its distribution has geographical characteristics,the major type is α-thalassemia. Blood screening and genetic diagnosis of thalassemia should be strengthened, and corresponding measures should be taken to reduce its gene frequency.
China ; Genetic Testing ; Genotype ; Heterozygote ; Humans ; alpha-Thalassemia ; beta-Thalassemia

Using silica gel column chromatography, gel chromatography and HPLC, we isolated secondary metabolites in fermentation broth of a rifamycin resistant mutation strain Streptomyces sp. HS-NF-1046R. Based on spectroscopic data, the chemical structures of three compounds were identified as 3-hydroxyl-2-N-propionyl- anthranilamide (1), 2,3-dihydro-8-hydroxy-2,2-dimethyl quinazolin-4-(1H)-one (2) and 2-aminobenzamide (3). Compounds 1 and 2, as new entities, were evaluated for cytotoxicity against A549, HepG2, HCT-116 and K562 cells using the SRB assay. Compounds 1 and 2 exhibited no cytotoxicity with IC₅₀ over 100 μmol·L^-1.

BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images. METHODS: Taking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR-), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists. RESULTS: The accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87-0.91, 0.89-0.92, 0.87-0.91, and 0.86-0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%). CONCLUSIONS: The CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists. TRIAL REGISTRATION Chictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.
Area Under Curve ; Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; China ; Deep Learning ; Humans ; ROC Curve ; Sensitivity and Specificity