Objective To identify right-sided chest lead electrocardiograph (ECG) abnormalities in acute pulmonary embolismMethods Changes of routinely recorded 12-lead and right-sided chest leads V 3R, V 4R and V 5R ECGs in 98 patients with suspected pulmonary embolism hospitalized at Ninghe County Hospital during March 1999 to October 2003 were analyzed retrospectively Parameters of both right and left-sided ECGs available were measured and comparedResults Diagnosis of acute pulmonary embolism was established in only 23 (234%) of 98 suspected patients, 18 men (78%) and 5 women (22%), with mean age of (48 ? 10) ECG changes suggestive of acute right ventricular strain were found in both right and left-sided leads in 18 (78%) of 23 patients with pulmonary embolism, and their ECG changes disappeared within 24 hours after admission or onset of symptoms with pulmonary embolism in 13 (72%) of them ST segment elevation in leads V 3R, V 4R, V 5R ,and abnormalities in standard 12-lead ECGs were found in nine (39%), and five (22%) of them with a diagnosis of pulmonary embolism had normal left-sided ECGs, but elevated ST segment and qr or QS pattern (prominent q waves) in leads V 3R, V 4R and V 5R in their right-sided ECGs Thirteen (565%) of them showed ST-segment elevated in leads V 3R, V 4R and V 5R,and 20 (87%) showed qr configuration in lead V 3RConclusions Patients with acute pulmonary embolism often show characteristic ECG changes in right-sided chest leads When pulmonary embolism is suspected, especially no typical changes in routinely-recorded standard 12-lead ECGs can be found, right-sided chest lead ECG should be performed

Objective To observe the expression of inhibitor of Zeste 12(SUZ12) and matrix metalloproteinase-9(MMP-9) in retinoblastoma(RB) and their significance .Methods The paraffin embedded specimens from 56 patients with RB were studied ,10 patients belong to intraocular stage ,28 patients intraocular pressure increased stage and 18 patients outside ocular stage among them .22 ,16 ,12 ,and 6 patients with invasion degree(N) from N0-N3 differently ,while10 ,16 ,18 and 12 patients with cell differenti-ations(D) from D0-D3 differently .The expressions of SUZ12 and MMP-9 protein in 56 patient s were detected in different clinical stages ,invasion degree and cell differentiation by immunohistochemical staining and their correlations were analyzed .Results The expressions of SUZ12 and MMP-9 in RB tissues[(31 .48 ± 12 .20)% ,(34 .49 ± 13 .25)% ]were obviously higher than in para-cancer tissue[(0 .26% ± 0 .06)% ,(0 .36 ± 0 .08)% ](P<0 .01) .The expression of SUZ12 was related to clinical stages ,invasion degree and cell differentiation .The expression of SUZ12 and MMP-9 in intraocular pressure increased stage was obviously higher than in-traocular stage(t=10 .299 ,16 .253 ;P<0 .01) ,and outside ocular stage was obviously higher than intraocular stage (t= 20 .819 , 36 .417 ;P<0 .01)and intraocular pressure increased stage (t= 10 .348 ,15 .061 ;P< 0 .01) .The expression of SUZ12 and MMP-9 was increasing from N0 to N3 but decreasing from D0 to D3 .The expression of SUZ12 in RB was related to MMP-9 expression(r=0 .840 ,P=0 .000) .Conclusion The expression of SUZ12 and MMP-9 increased in RB tissue and it is helpful to predict the malig-nancy degree of RB .

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF/MS) was developed to identify the absorbed parent components and metabolites in rat bile, plasma and urine after oral administration of Radix Paeoniae Alba extract (RPAE). A total of 65 compounds were detected in rat bile, plasma and urine samples, including 11 parent compounds and 54 metabolites. The results indicated that glucuronidation, hydroxylation and methylation were the major metabolic pathways of the components of RPAE. Furthermore, the results of this work demonstrated that UPLC-Q-TOF/MS combined with MetaboLynx? software and mass defect filtering (MDF) could provide unique high throughput capabilities for drug metabolism study, with excellent MS mass accuracy and enhanced MSE data acquisition. With the MSE technique, both precursor and fragment mass spectra can be simultaneously acquired by alternating between high and low collision energy during a single chromatographic run.

Objective To investigate the CT performances and causes of misdiagnosis of parovarian cyst,to improve its diagnostic accuracy.Methods CT data of 75 patients with surgically and pathologically confirmed parovarian cyst were analyzed retrospectively. Results Among the 75 patients,there were 79 cysts,in which 48 patients (51 cysts)originated from the epoophoron and 27 patients (28 cysts) from the mesosalpinx.77 were simple serous cysts and 2 serous cystadenomas.38 were located in the right ovarian adnexa,36 in the left ovarian adnexa,3 in the anterosuperior uterus,1 in the rectouterine pouch and 1 in the right iliac fossa.The size of the cysts ranged from 10 mm × 13 mm to 174 mm × 227 mm.75 were single cysts and 4 double cysts,34 presented as ovoid cysts,25 as irregular cysts, 17 as round cysts and 3 as gourd-shaped cysts.All the 79 cysts showed clear boundaries,thin walls,non-mural nodules,cystic fluid with a homogeneous densitywith CT value of 0-31 HU.Enhanced scanning revealed curved “obvious enhancement of the fallopian tube”at the edge of 68 cysts.In addition,the ipsilateral ovary could be detected in 76 cysts.“Holding ball”was found in 1 9 cysts.Conclusion Indication in ipsilateral ovary,curved “obvious enhancement of the fallopian tube”at the edge of cysts and “holding ball”are distinctive CT performances of parovarian cysts.CT has an important diagnostic value in parovarian cyst.

To explore how to create and optimize a promotion index system of medical quality evaluation, this article focuses on the hospital visiting process from patients, using analyzing collected those index system from couples of Grade Ⅲ hospitals in Beijing, and combining the results of literal study, field study and specialist consult, according to the different situation of general hospitals and specially hospitals, with the spirit of "maintaining the patients benefits, safeguarding the patients safety,and enhancing the medical quality", introduces the framework of the promotion index system, the rules to select the indicator, and so on, and discusses several problerns related to creating the index system.

The human spine injury and various lumbar spine diseases caused by vibration have attracted extensive attention at home and abroad. To explore the biomechanical characteristics of different approaches for lumbar interbody fusion surgery combined with an interspinous internal fixator, device for intervertebral assisted motion (DIAM), finite element models of anterior lumbar interbody fusion (ALIF), transforaminal lumbar interbody fusion (TLIF) and lateral lumbar interbody fusion (LLIF) are created by simulating clinical operation based on a three-dimensional finite element model of normal human whole lumbar spine. The fusion level is at L4-L5, and the DIAM is implanted between spinous process of L4 and L5. Transient dynamic analysis is conducted on the ALIF, TLIF and LLIF models, respectively, to compute and compare their stress responses to an axial cyclic load. The results show that compared with those in ALIF and TILF models, contact forces between endplate and cage are higher in LLIF model, where the von-Mises stress in endplate and DIAM is lower. This implies that the LLIF have a better biomechanical performance under vibration. After bony fusion between vertebrae, the endplate and DIAM stresses for all the three surgical models are decreased. It is expected that this study can provide references for selection of surgical approaches in the fusion surgery and vibration protection for the postsurgical lumbar spine.
Biomechanical Phenomena ; Finite Element Analysis ; Humans ; Lumbar Vertebrae/surgery* ; Pedicle Screws ; Range of Motion, Articular ; Spinal Fusion ; Vibration

Objective To investigate the value of automatic segmentation of carotid vessel wall in multicontrast MR images using U?Net neural network. Methods Patients were retrospectively collected from 2012 to 2015 in Carotid Atherosclerosis Risk Assessment (CARE II) study. All patients who recently suffered ischemic stroke and/or transient ischemic attack underwent identical, state?of?the?art multicontrast MRI technique. A total of 17 568 carotid vessel wall MR images from 658 subjects were included in this study after inclusion criteria and exclusion criteria. All MR images were analyzed using customized analysis platform (CASCADE). Randomly, 10 592 images were assigned into training dataset, 3 488 images were assigned into validating dataset and 3 488 images were assigned into test dataset according to a ratio of 6∶2∶2. Data augmentation was performed to avoid over fitting and improve the ability of model generalization. The fine?tuned U?Net model was utilized in the segmentation of carotid vessel wall in multicontrast MR images. The U?Net model was trained in the training dataset and validated in the validating dataset. To evaluate the accuracy of carotid vessel wall segmentation, the sensitivity, specificity and Dice coefficient were used in the testing dataset. In addition, the interclass correlation and the Bland?Altman analysis of max wall thickness and wall area were obtained to demonstrate the agreement of the U?Net segmentation and the manual segmentation. Results The sensitivity, specificity and Dice coefficient of the fine?tuned U?Net model achieved 0.878,0.986 and 0.858 in the test dataset, respectively. The interclass correlation (95% confidence interval) was 0.921 (0.915-0.925) for max wall thickness and 0.929 (0.924-0.933) for wall area. In the Bland?Altman analysis, the difference of max wall thickness was (0.037±0.316) mm and the difference of wall area was (1.182±4.953) mm2. The substantial agreement was observed between U?Net segmentation method and manual segmentation method. Conclusion Automatic segmentation of carotid vessel wall in multicontrast MR images can be achieved using fine?tuned U?Net neural network, which is trained and tested in the large scale dataset labeled by professional radiologists.

Objective: To investigate the value of automatic segmentation of carotid vessel wall in multicontrast MR images using U-Net neural network. Methods: Patients were retrospectively collected from 2012 to 2015 in Carotid Atherosclerosis Risk Assessment (CARE II) study. All patients who recently suffered ischemic stroke and/or transient ischemic attack underwent identical, state-of-the-art multicontrast MRI technique. A total of 17 568 carotid vessel wall MR images from 658 subjects were included in this study after inclusion criteria and exclusion criteria. All MR images were analyzed using customized analysis platform (CASCADE). Randomly, 10 592 images were assigned into training dataset, 3 488 images were assigned into validating dataset and 3 488 images were assigned into test dataset according to a ratio of 6∶2∶2. Data augmentation was performed to avoid over fitting and improve the ability of model generalization. The fine-tuned U-Net model was utilized in the segmentation of carotid vessel wall in multicontrast MR images. The U-Net model was trained in the training dataset and validated in the validating dataset. To evaluate the accuracy of carotid vessel wall segmentation, the sensitivity, specificity and Dice coefficient were used in the testing dataset. In addition, the interclass correlation and the Bland-Altman analysis of max wall thickness and wall area were obtained to demonstrate the agreement of the U-Net segmentation and the manual segmentation. Results: The sensitivity, specificity and Dice coefficient of the fine-tuned U-Net model achieved 0.878,0.986 and 0.858 in the test dataset, respectively. The interclass correlation (95% confidence interval) was 0.921 (0.915-0.925) for max wall thickness and 0.929 (0.924-0.933) for wall area. In the Bland-Altman analysis, the difference of max wall thickness was (0.037±0.316) mm and the difference of wall area was (1.182±4.953) mm². The substantial agreement was observed between U-Net segmentation method and manual segmentation method. Conclusion Automatic segmentation of carotid vessel wall in multicontrast MR images can be achieved using fine-tuned U-Net neural network, which is trained and tested in the large scale dataset labeled by professional radiologists.

Human 5-lipoxygenase (5-LOX) is a well-validated drug target and its inhibitors are potential drugs for treating leukotriene-related disorders. Our previous work on structural optimization of the hit compound 2 from our in-house collection identified two lead compounds, 3a and 3b, exhibiting a potent inhibitory profile against 5-LOX with IC50 values less than 1 µmol/L in cell-based assays. Here, we further optimized these compounds to prepare a class of novel pyrazole derivatives by opening the fused-ring system. Several new compounds exhibited more potent inhibitory activity than the lead compounds against 5-LOX. In particular, compound 4e not only suppressed lipopolysaccharide-induced inflammation in brain inflammatory cells and protected neurons from oxidative toxicity, but also significantly decreased infarct damage in a mouse model of cerebral ischemia. Molecular docking analysis further confirmed the consistency of our theoretical results and experimental data. In conclusion, the excellent in vitro and in vivo inhibitory activities of these compounds against 5-LOX suggested that these novel chemical structures have a promising therapeutic potential to treat leukotriene-related disorders.