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Objective:To explore the different coagulation state in patients with adenomyosis and its clinical significance.Methods:Clinical data of the patients admitted to the First Affiliated Hospital of Nanjing Medical University from January 2017 to December 2021 were retrospectively analyzed. (1) Differential coagulation state between 25 healthy women and 25 patients with adenomyosis were compared during menstrual and non-menstrual periods. (2) The coagulation indexes of 145 patients with adenomyosis (observation group 1) and 129 patients with cervical intraepithelial neoplasia grade Ⅲ (control group 1) who underwent hysterectomy in non-menstrual period were compared. (3) The coagulation indexes of 154 patients with adenomyosis (observation group 2) and 147 women without myometrial lesions (control group 2) who underwent endometrial curettage during uterine bleeding period were compared. (4) Correlations of coagulation index with cancer antigen 125 (CA 125), cancer antigen 19-9 (CA 19-9) and uterine volume in patients with adenomyosis were analyzed. Results:(1) The coagulation state of each health women during the menstrual and non-menstrual period showed no significant differences (all P>0.05). For the 25 patients with adenomyosis, fibrinogen [FIB; 2.61 g/L(2.50-3.10 g/L)] and D-dimer [0.60 mg/L (0.40-1.00 mg/L)] in the menstrual period were significantly higher than those in the non-menstrual period [2.25 g/L (1.90-2.70 g/L) and 0.27 mg/L (0.20-0.40 mg/L), respectively; both P<0.01], while thrombin time [TT; 16.70 s (16.10-17.40 s)] in the menstrual period was significantly lower than that in the non-menstrual period [17.95 s (17.20-18.40 s); P<0.01]. (2) In the non-bleeding period, D-dimer [0.26 mg/L (0.20-0.40 mg/L)] and platelet count [257.0×10 9/L (212.0×10 9/L-308.5×10 9/L)] of observation group 1 were significantly higher than those of control group 1 (all P<0.01). Besides, FIB ( r=0.237, P=0.004) and D-dimer ( r=0.373, P<0.001) were positively correlated with CA 125, while prothrombin time (PT; r=-0.208, P=0.012) and internationalized normalized ratio of plasma prothrombin time (PT-INR; r=-0.201, P=0.015) were negatively correlated with CA 19-9. (3) In the bleeding period, PT [10.70 s (10.10-11.20 s)] and PT-INR [0.93 (0.90-1.00)] of observation group 2 were significantly lower than those of control group 2 (all P<0.01), while D-dimer [0.41 mg/L (0.20-0.80 mg/L)] was significantly higher than that in the control group 2 ( P<0.001). Furthermore, FIB ( r=0.252, P=0.038) and D-dimer ( r=0.321, P=0.008) were positively correlated with uterine volume, while activated partial thromboplastin time (APTT; r=-0.190, P=0.018) and TT ( r=-0.304, P=0.012) were negatively correlated with uterine volume. (4) During non-menstrual period and uterine bleeding period, APTT and TT in patients of observation group 1 and 2 combined with anemia were significantly lower than those of non-anemia patients (all P<0.05). Conclusion:Patients with adenomyosis have a tendency to hypercoagulability in both the uterine bleeding and non-bleeding periods, which may be related to enlarged uterine volume, increased serum CA 125 and anemia.
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Objective:To investigate the efficacy and safety of dienogest (DNG) alone and gonadotropin-releasing hormone agonist (GnRH-a) combined with DNG sequential treatment to adenomyosis.Methods:The clinical data of 110 patients with adenomyosis attending the First Affiliated Hospital of Nanjing Medical University from December 2019 to March 2022 were retrospectively analyzed, including 40 patients treated with DNG (2 mg/day) alone (DNG group) and 70 patients treated with sequential DNG (2 mg/day) after 3-6 injections of GnRH-a (GnRH-a+DNG group). The clinical data before and after treatment were compared between the two groups.Results:(1) The dysmenorrhea visual analogue scale (VAS) scores, cancer antigen 125 (CA 125) and cancer antigen 19-9 (CA 19-9) levels at different time periods after treatment were significantly lower than before treatment in both groups (median before treatment: DNG group 70.0 mm, 68.55 kU/L, 22.45 kU/L respectively, GnRH-a+DNG group 80.0 mm, 151.50 kU/L, 20.44 kU/L respectively; all P<0.001). (2) The hemoglobin (Hb) levels of patients in both groups at different time periods after treatment were significantly higher than those before treatment (median: DNG group 102.00 g/L, GnRH-a+DNG group 94.00 g/L; all P<0.001). (3) Treatment with DNG alone did not have a significant effect on uterine volume in patients of DNG group ( P>0.05), and uterine volume decreased significantly in the 15th-24th months of GnRH-a+DNG group compared with that before treatment (median: 167.76 vs 227.77 cm 3; P<0.05). (4) There were no significant differences in hepatic and renal function and coagulation indexes between the two groups before and after treatment (all P>0.05), and no significant abnormal lesions were observed in breast tissue during the follow-up period. (5) The incidence of amenorrhea of GnRH-a+DNG group was higher than that of DNG group, and the incidences of irregular spotting bleeding and breakthrough hemorrhage were lower than those in DNG group. Conclusions:Whether DNG is used alone or in combination with GnRH-a in sequence, it could significantly relieve dysmenorrhea symptoms, improve the level of Hb, reduce the levels of CA 125 and CA 19-9 in patients with adenomyosis, with no adverse effects on coagulation and hepatic or renal function. GnRH-a sequential DNG therapy is superior to DNG alone in improving uterine bleeding patterns and controlling the growth of uterine volume in patients with adenomyosis.
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Objective:To explore the predictive value of 18F-fluorodeoxyglucose (FDG) PET/CT radiomics for the programmed death ligand-1 (PD-L1) expression level in lung adenocarcinoma patients. Methods:A total of 101 patients (43 males, 58 females; median age 60 years) with histologically confirmed lung adenocarcinoma who received pre-treatment 18F-FDG PET/CT from January 2017 to January 2019 in Peking University Cancer Hospital were included retrospectively. There were 44 patients with positive PD-L1 by immunohistochemical assays, and 57 with PD-L1 negative. Patients were assigned to a training set ( n=71) and a validation set ( n=30). Clinical data, PET/CT radiomics parameters, conventional metabolic parameters, and observed CT characteristics of these patients were included in the models. The filter method and embedded method were used in feature selection. Models based on logistic regression, random forest, XGBoost and Light Gradient Boosting Machine (LightGBM) were trained and evaluated, and the optimal parameters to predict the PD-L1 expression as well as the area under curve (AUC) were attained. Results:All models had predictive ability in the prediction of PD-L1 expression, while LightGBM was more powerful than the others, with the precision for positive and negative predictions of 0.85 and 0.76, respectively. Incorporating clinical data and data derived from thin-section CT images (clinical data+ CT) into the LightGBM, the precision, recall and F1-score for positive and negative patients were 0.71, 0.67, 0.69 and 0.69, 0.73, 0.72, respectively, with the accuracy of 0.70 and the AUC of 0.79. As for clinical data+ PET, the precision, recall and F1-score for positive and negative patients were 0.79, 0.73, 0.76 and 0.75, 0.80, 0.77, respectively, with the accuracy of 0.77 and the AUC of 0.80. As for clinical data+ CT+ PET, the precision, recall and F1-score for positive and negative patients were 0.85, 0.73, 0.79 and 0.76, 0.87, 0.81, respectively, with the accuracy of 0.80 and the AUC of 0.83. Features with significant importance in the model (clinical data+ CT+ PET) were as follows: maximum standardized uptake value (SUV max), peak of standardized uptake value (SUV peak), CT_shape_Maximum2DDiameterSlice, PET_shape_Elongation, PET_gray level co-occurrence matrix (GLCM)_Correlation, etc. Conclusions:Incorporating clinical data, PET/CT radiomics features and conventional metabolic parameters, the PD-L1 expression can be effectively predicted, which help to assist the selection of patients who may benefit from the immunotherapy.
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The adenosine triphosphate (ATP)-binding cassette transporter G1 (ABCG1),a member of the superfamily of ATP-binding cassette transporters,is involved in the efflux of cholesterol and phospholipids from cells,and it maintains the intracellular hpid homeostasis.ABCG1 deficiency results in foam cell formation,endothelial dysfunction,and inflammatory reaction,and it further leads to the development and progression of atherosclerosis.However,the role of ABCG1 in atherosclerosis in animal experiments and human studies is still a debatable matter.In this paper,the recent findings on the role of ABCG1 in atherosclerotic disease are reviewed.
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In the present investigation, we studied four methods of blind source separation/independent component analysis (BSS/ICA), AMUSE, SOBI, JADE, and FastICA. We did the feature extraction of electroencephalogram (EEG) signals of brain computer interface (BCI) for classifying spontaneous mental activities, which contained four mental tasks including imagination of left hand, right hand, foot and tongue movement. Different methods of extract physiological components were studied and achieved good performance. Then, three combined methods of SOBI and FastICA for extraction of EEG features of motor imagery were proposed. The results showed that combining of SOBI and ICA could not only reduce various artifacts and noise but also localize useful source and improve accuracy of BCI. It would improve further study of physiological mechanisms of motor imagery.
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Humans , Algorithms , Artifacts , Brain , Physiology , Brain-Computer Interfaces , Electroencephalography , Foot , Hand , Imagination , Movement , Signal Processing, Computer-Assisted , TongueABSTRACT
In the process of designing genechip probe for detecting pathogenic microorganism, the selection of single nucleotide polymorphism (SNP) combination is of great importance. At present, there is no automatic design method. This work is hard and the result is not always well. A new approach for selecting SNP combination is presented in this paper. Genetic algorithm is used to search optimal solution on the basis of classification ability of SNP combination, which is evaluated by the rough set theory. Other related experimental parameters are also incorporated. Experimental results show that the method can find out the best SNP combination pattern efficiently and accurately, thus demonstrating the reliability of this new method for designing the genechip probe.