OBJECTIVE To investigate the pharmacokinetics and bioavailability of naproxen choline ionic liquid in rats after intragastric administration. METHODS Naproxen choline ionic liquid was given to rats by intragastric administration. Blood samples were collected at different time points after administration. The blood samples were precipitated by methanol and then centrifuged, and then an Extend-C18 column(4.6 mm×250 mm, 5 μm) was used. Methanol(A)-0.3% phosphoric acid aqueous solution(B) (74:26) was used as the mobile phase, the flow rate was 0.8 mL·min-1, and the detection wavelength was 230 nm. Indomethacin and naproxen were used as internal standard and tested object in determination of naproxen choline ionic liquid in rat plasma. Pharmacokinetic parameters were calculated using DAS 2.0 software. RESULTS After intragastric administration of naproxen suspension to rats, its t1/2α was 5.12 h, t1/2β was 10.13 h, Tmaxwas 2 h, Cmax was 112.92 mg·L-1, and AUC(0-t) was 1 091.01 mg·L-1·h. After intragastric administration of naproxen choline, its t1/2α was 5.64 h, t1/2β was 69.32 h, Tmax was 1 h, Cmax was 135.97 mg·L-1, AUC(0-t) was 1 305.79 mg·L-1·h, and the relative bioavailability was 119.686%. CONCLUSION After intragastric administration of naproxen choline to rats, the peak concentration and bioavailability of the naproxen in vivo are higher than those of the common suspension, and the peak time is earlier.

Objective:To evaluate the use of ulthera in carotid body tumor resectionMethods:From Jun 2004 to Jun 2019 at the First Hospital of China Medical University. Forty-three shamblin grade Ⅱ or Ⅲ patients were retrospectively assigned to ulthera assisted carotid body tumor resection (26 cases) and traditional carotid body tumor resection (17 cases).Results:In ulthera assisted group, the average tumor diameter was (4.0±0.6) cm, compared to (3.9±0.9) cm in traditional carotid body tumor surgery group, P=0.875. The operation time of the two group was respectively (117.6±39.8) min and (149.4±55.0) min ( P=0.005), blood loss (145.7±70.6) ml vs. (194.1±80.7) ml ( P=0.006), hospital stay was (16.8±7.5) d vs. (22.7±13.0) d ( P=0.017), and following-up period was between 6 and 180 months. One patient relapsed in ulthera assisted group. The postoperative complications occurred in 8 and 7 cases respectively. Conclusion:Ulthera assisted carotid body tumor resection helps shorten operation time, hospital stay and decrease intraoperative blood loss.

Objective: To understand the molecular evolution characteristics of the nucleoprotein (N) genes and epidemiological feature of 118 rabies virus (RABV) strains isolated in Yunnan province, China from 2006 to 2015. Methods: The brain tissue samples from mad dogs, suspicious sick dogs, sick cow, and human brain tissue, saliva and CSF samples from rabies patients were collected in Yunnan province to detect the viral antigen by direct immunofluorescence assay (DFA). The viral RNA from positive samples was extracted. Coding region of N gene was amplified by RT-PCR and sequenced. The phylogenetic tree was constructed by Neighbor-Joining method of MEGA5.0 software. Results: The sequences of N genes of 91 RABV strains in Yunnan from 2012 to 2015 were obtained. With the sequences of N genes of 27 RABV strains in Yunnan from 2006 to 2011 and 29 RABV strains from Southeast Asian Countries, the phylogenetic analysis was performed. RABV strains in Yunnan were divided into clades YN-A (105 strains), YN-B (6 strains), YN-C (7 strains), which belonged to clades China-I, China-VI, China-II respectively. Clade YN-A was epidemic every year from 2006 to 2015, of them, 14 strains from 2006 to 2011 and 91 strains from 2012 to 2015 were distributed in 13 prefectures (cities) of Yunnan. Clades YN-B and YN-C were epidemic only from 2006 to 2010 and from 2008 to 2011 respectively. The regional distribution of clades YN-B and YN-C was limited. The strains of YN-A and YN-C were closely related to the strains of clades China-I and China-II from neighboring Sichuan, Guizhou, Guangxi and Hunan provinces. The strains of YN-B were closely related to the strains from Myanmar, Laos, Vietnam and Cambodia. Conclusions Three RABV clades with multiple transmission sources were identified in Yunnan. Clade YN-A was widely distributed in rabies endemic area in Yunnan from 2006 to 2015, and it has strong ability to spread as principal clade in Yunnan. Since 2012, clades YN-B and YN-C were not found again in Yunnan.

Objective To observe the value of 3D Res2Net deep learning model for predicting volume doubling time(VDT)of solid pulmonary nodule.Methods Chest CT data of 734 patients with solid pulmonary nodules were retrospectively analyzed.The patients were divided into progressive group(n=218)and non-progressive group(n=516)according to whether lung nodule volume increased by ≥25％during follow-up or not,also assigned into training set(n=515)and validation set(n=219)at a ratio of 7∶3.Then a clinical model was constructed based on clinical factors being significantly different between groups,CT features model was constructed based on features of nodules on 2D CT images using convolutional neural network,and 3D Res2Net model was constructed based on Res2Net network using 3D CT images as input.Receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated.Taken actual VDT as gold standard,the efficacy of the above models for predicting solid pulmonary nodule'VDT≤400 days were evaluated.Results No significant difference of predicting efficacy for solid pulmonary nodule'VDT≤400 days was found among clinical model,CT feature model and 3D Res2Net model,the AUC of which was 0.689,0.698 and 0.734 in training set,0.692,0.714 and 0.721 in validation set,respectively.3D Res2Net model needed 5-7 s to predict VDT of solid pulmonary nodules,with an average time of(5.92±1.08)s.Conclusion 3D Res2Net model could be used to predict VDT of solid pulmonary nodules,which might obviously reduce manual interpreting time.

Objective To observe the value of feature pyramid network(FPN)for automatic segmentation and semantic feature classification of spontaneous intracerebral hemorrhage(sICH)hematoma showed on non-contrast CT.Methods Non-contrast CT images of 408 sICH patients in hospital A(training set)and 103 sICH patients in hospital B(validation set)were retrospectively analyzed.Deep learning(DL)segmentation model was constructed based on FPN to segment the hematoma region,and its efficacy was assessed using intersection over union(IoU),Dice similarity coefficient(DSC)and accuracy.Then DL classification model was established to identify the semantic features of sICH hematoma.Receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the efficacy of DL classification model for recognizing semantic features of sICH hematoma.Results The IoU,DSC and accuracy of DL segmentation model for 95％sICH hematoma in training set was 0.84±0.07,0.91±0.04 and(88.78±8.04)％,respectively,which was 0.83±0.07,0.91±0.05 and(88.59±7.76)％in validation set,respectively.The AUC of DL classification model for recognizing irregular shape,uneven density,satellite sign,mixed sign and vortex sign of sICH hematoma were 0.946-0.993 and 0.714-0.833 in training set and validation set,respectively.Conclusions FPN could accurately,effectively and automatically segment hematoma of sICH,hence having high efficacy for identifying semantic features of sICH hematoma.