OBJECTIVETo construct a 3D finite-element model of the craniofacial complex with the original DICOM data of CT and to investigate the preliminary biomechanical characteristics with different directions and magnitudes of retractive forces to the maxilla of rhesus monkeys.

METHODSA male rhesus monkey with mixed dentition was used. Spiral CT was performed to establish a 3D finite-element model of the craniofacial complex. The ANSYS 12.1 software was used to analyze craniofacial complex displacement.

RESULTSEach landmark showed larger displacement with increasing force value. The displacement values and force size exhibited a linear relationship. In the x-axis direction, all displacements were small. In the y-axis direction, all displacements showed significantly higher changes with increasing force value displacement. In the z-axis direction, the A-point and ANS point moved downward, but PNS moved upward.

CONCLUSIONLoading retractive force resultes in an apparent backward and clockwise rotation on the maxilla with no obvious effects on the width of the upper jaw.

Objective To investigate the impact of mind wandering in sustained attention response task, and offer interventions to cope with mind wandering. Methods In December, 2016, a total of 37 athletes were tested with sustained attention response task. Their technical index, reaction time variation and accurate rate were calculated. Results The statistics of 25 athletes showed that, the technical index was lower in complex task than in simple task (t(35)=-8.019, P<0.001). No significant difference was found in the reaction time variation between two tasks (t(23)=-1.575, P=0.129), the main effect of mind wandering was not significant (F(1,23)=0.488, P=0.492), as well as the interaction of mind wandering and task difficulty (F(1,23)=0.054, P=0.262). No significant difference was found in the accurate rate between two tasks (t(23)=-1.046, P=0.307), the main effect of mind wandering was not significant (F(1,23)=0.119, P=0.733), and the interaction of mind wander-ing and task difficulty was marginal significance (F(1,23)=3.608, P=0.070). Conclusion Athlete's mind wandering with awareness would influ-ence the performance in complex sustained attention response task. Mindfulness training and tasks engagement could effectively cope with mind wandering.

Objective To explore the effect of liposomal transfection of cyclin D1 antisense oligodeoxynucleotide (ASON) on A549 cell proliferation and apoptosis. Methods By liposomal transfection technique, cyclin D1 ASON was co-cultured with A549 cells. The cell growth curve was determined by MTT assay. The protein and mRNA of cyclin D1 were measured by FACS and RT-PCR. Results In the cyclin D1 ASON liposomal transfection group, the proliferation of A549 cells was significantly inhibited as compared to that in cyclin D1 ASON group (P

Objective To analyze the etiology of pseudoachalasia.Methods Patients who were diagnosed as having pseudoachalasia in Endoscopy Center of The Affiliated Zhongshan Hospital of Fudan University from September 2010 to June 2015 were retrospectively analysed.Results A total of 12 patients were enrolled in this study,6 males and 6 females.The median age,median disease duration and median Eckcardt score was 54.5(24.0～71.0) years old,2.5(0.2～ 10.0) years and 4(3～9),respectively.Seven cases were caused by malignant tumors,2 had benign tumors,and 3 peptic stricture.Conclusion The most common cause of pseudoachalasia is malignant tumors.Accurate diagnosis relies on the comprehensive medical history and complete examinations.

Logistic regression is a kind of multiple regression method to analyze the relationship between a binary outcome or categorical outcome and multiple influencing factors, including multiple logistic regression, conditional logistic regression, polytomous logistic regression, ordinal logistic regression and adjacent categorical logistic regression. This paper illustrates the basic principle, independent variable selection and assignment, applied condition, model evaluation and diagnosis for multiple logistic regression model. Moreover, the principle and application for polytomous logistic regression and ordinal logistic regression models were also introduced. By providing SAS codes and detailed explanations of the result for an example of obesity, readers could be able to better understand logistic regression model, and apply this method correctly to their research and daily work, so as to improve their capacity of the data analysis.

Logistic regression is a kind of multiple regression method to analyze the relationship between a binary outcome or categorical outcome and multiple influencing factors, including multiple logistic regression, conditional logistic regression, polytomous logistic regression, ordinal logistic regression and adjacent categorical logistic regression. This paper illustrates the basic principle, independent variable selection and assignment, applied condition, model evaluation and diagnosis for multiple logistic regression model. Moreover, the principle and application for polytomous logistic regression and ordinal logistic regression models were also introduced. By providing SAS codes and detailed explanations of the result for an example of obesity, readers could be able to better understand logistic regression model, and apply this method correctly to their research and daily work, so as to improve their capacity of the data analysis.

BACKGROUNDTo determine the inhibitory effect of antisense peptide nucleic acids (PNA) of telomerase on the growth of lung cancer cell lines.

METHODSThe synthesized modified antisense PNAs of telomerase were transfected into the lung cancer cell lines A549 and NCI-H446 respectively by lipofectamine transfection. Telomerase activity was detected by RT-PCR-ELLISA, and the cell counts were determined by MTT.

RESULTSSeventy two hours after transfection with antisense PNAs of telomerase, telomerase activity (A450 value) of A549 and NCI-H446 were down regulated from 0.582 ±0.039, 0.571±0.043 to 0.294±0.048 ( P < 0.01), 0.276±0.051 ( P < 0.01) respectively, and alive cell counts (A580 value) of them from 0.485± 0.009 , 0.513±0.015 to 0.191±0.027 ( P < 0.01), 0.138±0.046 ( P < 0.01) respectively. The growth of two lung cancer cell lines were significantly inhibited.

CONCLUSIONSAntisense PNA of telomerase might inhibit not only the telomerase activity, but also the growth of lung cancer cell lines in vitro.

BACKGROUNDTo evaluate the clinical significance of telomerase activity in lung cancer and to investigate the possibility of telomerase as cancer marker for lung cancer.

METHODSThe activity of telomerase was investigated by TRAP-PCR-ELISA in lung cancer tissues and corresponding adjacent noncancerous tissues obtained from resected specimens of 48 patients with lung cancer and 42 specimens of benign pulmonary lesions were examined simultaneously.

RESULTSTelomerase activity was detected in 42 (87.5%) of the 48 tumors and only 4 (8.3%) of the 48 adjacent noncancerous lung tissue samples (Chi-Square=13.029, P < 0.01), but in none of 42 specimens of benign pulmonary lesions (Chi-Square=14.016, P < 0.01). Correlation with pathological parameters showed that the expression of telomerase activity was associated with lymph node metastasis (93.5% vs 76.4% , Chi-Square=63.511, P < 0.01), but not with histological type, location and differenciated grade of tumor.

CONCLUSIONSTelomerase activation correlates with the carcinogenesis and aggressiveness of lung cancer. Telomerase might be one of the important diagnostic and prognostic factors in patients with lung cancer.

Objective To investigate the variations of mtDNA from high and low metastatic mouse hepatocarcinoma cell sublines Hca-F and Hca-P, and the relationship between mutations of mtDNA and carcinogenesis. Methods The variations of D-loop, ND3 and tRNA Met+Glu+Ile gene fragments of mtDNA from Hca-F and Hca-P cells were analyzed by PCR-RFLP and sequencing techniques. Results No amplification fragment length polymorphism and restriction fragment length polymorphism were observed in tRNA Met+Glu+Ile , ND3 and D-loop of mtDNA from the 2 cell sublines. Sequence difference between these 2 cell sublines were found in mtDNA D-loop region by sequencing. Conclusions Genetic alteration of mtDNA non-coding region in tumors, which may reflect the environmental and genetic influences operative during tumor progression, can be linked to their tumorigenic phenotype.