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BackgroundThis study investigated the prognostic effects of venous thromboembolism (VTE)-related factors in patients with metastatic pancreatic cancer receiving palliative chemotherapy. Predictive factors for VTE were also investigated.MethodsA total of 216 patients diagnosed with metastatic pancreatic cancer who received gemcitabine-based palliative chemotherapy at our institution were retrospectively evaluated.ResultsVTE occurred in 51 (23.6%) patients during treatment and did not affect survival. However, patients who were diagnosed with VTE at the beginning of chemotherapy showed poor prognosis compared with patients diagnosed with VTE during chemotherapy: all patients (hazard ratio [HR] 1.897, p = 0.008); patients diagnosed with VTE (HR = 3.768, p = 0.001). Low serum sodium (Na) (< 135 mmol/L) and high Khorana score (≥3) were strong predictive factors of early VTE (odds ratio [OR] 5.109; 95% confidence interval [95% CI] = 1.010–25.845; p = 0.049 for Khorana score, OR 10.304; 95% CI = 1.036–102.466; p = 0.047) for hyponatremia).ConclusionsOur study demonstrated that occurrence and detection of VTE in the early period of chemotherapy was the most significant VTE-related prognostic factor in patients with metastatic pancreatic cancer receiving chemotherapy. Prediction using the Khorana score and serum Na levels would be helpful in early diagnosis of VTE.

A new crack detection approach based on local binary patterns (LBP) with support vector machine (SVM) was proposed in this paper. The propsed algorithm can extract the LBP feature from each frame of the video taken from the road. Then, the dimension of the LBP feature spaces can be reduced by Principal Component Analysis(PCA). The simplified samples are trained to be decided the type of crack using Support Vector Machine(SVM). In order to reflect the directional imformation in detail, the LBP processed image is devided into nine sub-blocks. In this paper, driving tests were performed 10 times and 12,000 image data were applied to the proposed algorithm. The average accuracy of the proposed algorithm with sub-blocks is 91.91%, which is about 6.6% higher than the algorithm without sub-blocks. The LBP-PCA with SVM applying sub-blocks reflects the directional information of the crack so that it has high accuracy of 89.41% and 88.24%, especially in transverse and longitudinal cracks. In the performance analysis of different crack classifiers, the F-Measure, which considered balance between the precision and the recall, of alligator cracks classifier was the highest at 0.7601 and hence crack detection performance is higher than others.

Purpose: Bone Morphogenetic Proteins (BMPs) are members of the TGF-β superfamily and it has been demonstrated that BMPs enhance migration, invasion and metastasis. The purpose of this study was to identify the association between the serum BMP-2 level and the progression status of gastric cancer.Materials and Methods: Fifty-five patients with metastatic gastric cancer (metastatic disease group), six patients with early gastric cancer without lymph node metastasis (the EGC group), and ten healthy control subjects were enrolled in this study. The serum BMP-2 level was quantified by use of a commercially available ELISA kit. In EGC group patients and patients with metastatic disease, whole blood was obtained before endoscopic mucosal resection and before the commencement of a scheduled cycle of systemic chemotherapy, respectively.Results: No significant difference in the mean serum BM P -2 le ve ls wa s obse rve d be twe e n the control subjects and the EGC group patients (87.95 pg/ml for the control subjects and 84.50 pg/ml for the EG C group, p=1.0). However, the metastatic disease group patients had a significantly higher level of serum BMP (179.61 pg/ml) than the control subjects and EGC group patients (87.95 pg/ml for the control subjects and 84.50 pg/ml for the EGC group, p＜0.0001). Moreover, the mean serum BMP-2 level from patients with a bone metastasis was significantly higher than the mean serum BMP-2 level from patients without a bone metastasis (

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