Objective To evaluate the clinical effect of a novel computer-assisted navigation technique for intraoperative correction of femoral rotation deformity in diaphyseal fractures.Methods From November 2015 to November 2016,a navigation system (BrainLAB,Germany) was used in antegrade intramedullary nailing for 13 patients with femoral shaft fracture to intraoperatively restore the normal length and rotation of the fractured femur.They were 11 men and 2 women,with an average age of 38.2 years.The iujury affected the left side in 5 cases and the right side in 8.According to the Winquist Classification,there were 6 cases of type Ⅰ,3 ones of type Ⅱ,3 ones of type m,and one of type Ⅳ.This navigation system allowed the surgeons to detect and set the femoral anteversion (FAV) and length of the injured leg at the desired angle and length of the healthy contralateral femur,precisely matching the contralateral limb and restoring the normal length and rotation of the fractured femur.All the patients underwent postoperative CT scan of bilateral femora for measurement of the lengths and rotations which were conpared with the intraoperative values obtained with the navigation system.Results Additional operative time required for computerized navigation averaged 42.8 min (from 35 to 55 min).The mean length difference between the treated and untreated femora was 4.2 nnn (from 2 to 9 mm).The FAVs obtained from intraoperative navigation and postoperative CT scan were 34.0° ± 8.4° and 33.5° ± 8.3° in the healthy side and 31.2° ± 8.5° and 32.8° ± 9.0° in the injured side,showing no significant differences either between the 2 sides or between intraoperation and postoperation (P ＞ 0.05).The mean rotational difference between the 2 extremities were 4.8° ± 1.6° for the navigation and 3.8° ± 1.9° for the CT scan,showing an insignificant difference (P ＞ 0.05).All the incisions healed well with no intraoperative or postoperative complications.Conclusions This novel navigation technique may serve as a reliable tool to accurately correct the rotational malalignment of femoral shaft fractures intraoperatively,but care should be taken in every step of the navigation procedure to reduce complications.

Objective To explore the influencing factor of duration of untreated psychosis(DUP) and the relationship between duration of untreated psychosis and treatment outcome in epidemiological first-episode schizophrenia. Methods 912 medical records of the first episode schizophrenia patients were recruited in the study for epidemiological survey . The general medical data, clinical diagnosis, and treatment outcome were collected. DUP was determined refer to symptom onset for schizophrenia (SOS) scale. Patients were divided into short DUP and long DUP groups according to the median values of DUP values. Results Between short DUP and long DUP groups, the difference in marriage was significant ( P < 0. 05). The unmarried patients in the short DUP group (63.7% ) was higher than the long DUP group (52.6% ), the variance was significant (λ2 =5.990, P<0.05). The divorce in the short DUP group (0.6% ) was lower than the long DUP group (4.4% ) , the variance was significant (λ2 =5.079, P<0.01).The simple schizophrenia in the short DUP group (1.5%) was lower than the long DUP group (4. 1% ) , the variance was significant (λ2 =5.868, P<0.05). The treatment outcomes between the two groups had a significant variance ( λ2 =36.093, P < 0.01) , and the Ridit analysis of treatment outcomes between the two groups showed significant difference ( u = 5.183, P<0.01). The marriage,age of onset and clinical diagnosis were significantly correlated with DUP in multiple factor Logistic regression analysis. Conclusion The marriage,age of onset and clinical diagnosis are significantly correlated with DUP in the first episode schizophrenia patients,the longer of DUP and the worse of treatment outcome.

Objective To elucidate the roles of high mobility group box-1 protein (HMGB1) and myeloperoxidase (MPO) deficiency in evaluating coronary stenosis and the vulnerability of atherosclerotic plaques in patients with coronary heart disease.Methods Totally 50 patients with acute myocardial infarction (AMI),50 patients with unstable angina pectoris (UAP),50 patients with stable angina pectoris (SAP) and 30 patients without coronary heart disease underwent the study.Coronary arteriography (CAG) and intravascular ultrasound (IVUS) were performed to analyze coronary stenosis and plaque characteristics and then gensini score was calculated.Concentrations of HMGB1,MPO and hypersensitive C reactive protein (hsC-RP) were measured by means of enzymelinked-immonosorbent assay (ELISA).Results Concentrations of HMGB1,MPO and hsC-RP were significantly higher in AMI and UAP patients than in SAP paticnts (all P＜ 0.01).IVUS showed that 51.3 ％ (20/39) AMI patients,46.7％ (43/92) UAP patients had soft lipid-rich plaqucs,while 52.9％(46/87) SAP patients had fibrous plaques,only 17.2％(15/87) had soft plaques.AMI and UAP patients had larger plaque burden and vascular remodeling index than did the SAP patients (both P＜0.01).In AMI group,HMGB1 and MPO levels were correlated well with gensini score and remodeling index measured by IVUS,respectively(r=0.54,0.48,allP＜0.05),while in UAP group,HMGB1 and MPO levels were correlated well with gensini score and plaque burden measured by IVUS,respectively(r=0.43,0.56,all P＜0.05).Conclusions HMGB1 and MPO are positively correlated with coronary stenosis,which can be used to predict the severity of ACS.HMGB1 and MPO are associated closely with plaque vulnerability and rupture.

Objective:To propose a method of cervical cytology screening based on deep convolutional neural network and compare it with the diagnosis of cytologists.Method:The deep segmentation network was used to extract 618 333 regions of interest (ROI) from 5, 516 cytological pathological images. Combined with the experience of physicians, the deep classification network with the ability to analyze ROI was trained. The classification results were used to construct features, and the decision model was used to complete the classification of cytopathological images.Results:The sensitivity and specificity were 89.72%, 58.48%, 33.95% and 95.94% respectively. Among the smears derived from four different preparation methods, this algorithm had the best effect on natural fallout with a sensitivity of 91.10%, specificity of 69.32%, positive predictive rate of 41.41%, and negative predictive rate of 97.03%.Conclusion:Deep convolutional neural network image recognition technology can be applied to cervical cytology screening.