Objective To understand the changing trend of Internet outpatient visits in public hospitals,and provide support for the development planning of Internet hospitals.Methods Using the data of Internet outpatient visits in a public hos-pital from January 2021 to June 2023,the ARIMA model and GM(1,1)model were constructed respectively.The mean absolute error(MAE)and root mean square error(RMSE)were used to evaluate the fitting effect,and the Internet outpatient visits from July to December 2023 were predicted based on the dominance model.Results ARIMA(1,2,1)model and GM(1,1)model were used to predict the number of return visits of Internet outpatient service.The average absolute errors were 369.86 and 978.84,and the root-mean-square errors were 479.49 and 1444.83,respectively.The ARIMA(0,1,0)model and GM(1,1)model were used to predict the number of Internet outpatient consultations.The average absolute errors were 297.23 and 369.62,and the root-mean-square errors were 413.61 and 496.30,respectively,indicating that the ARIMA model has a good prediction effect.The forecast results show that the predicted value of Internet outpatient visits in December 2023 is 14,831 cases,and the predicted value of consultation visits is 7461 cases.Conclusion The number of Internet outpatient visits in a public hospital will continue to rise from 2021 to 2023.Therefore,hospitals should fully realize the importance of Internet medical services,take ac-tive measures to continuously optimize the medical service model,and provide patients with high-quality,efficient and convenient Internet medical services.

Objective:To develop and evaluate metal artifact removal systems (MARSs) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images.Methods:A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05).Results:Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0 mm, 1.5 mm, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively ( F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively ( F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 ( F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 ( F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 ( F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 ( F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARSs. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions:Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.

Objective:To develop and evaluate metal artifact removal systems (MARS) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images.Methods:A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05).Results:Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0, 1.5, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively ( F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively ( F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 ( F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 ( F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 ( F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 ( F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARS. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions:Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.

Objective:To evaluate the value of 99Tc m-methoxyisobutylisonitrile(MIBI) SPECT/CT imaging for the identification of dystonic muscles in patients with primary cervical dystonia (PCD). Methods:A total of 10 patients with PCD (3 males, 7 females, age (47.3±9.9) years) and 10 healthy subjects (4 males, 6 females, age (43.5±9.4) years; control group) between August 2019 and October 2021 in China-Japan Friendship Hospital were enrolled prospectively. All subjects underwent 99Tc m-MIBI SPECT/CT scan. The SUV max of 8 bilateral representative muscles, including rectus capitis posterior major, obliquus capitis inferior, splenius capitis, semispinalis, sternocleidomastoid, trapezius, musculus scalenus muscle and levator scapulae were evaluated in control group. In PCD group, muscles with abnormal uptake were determined. ROI was drawn and SUV max was measured. Independent-sample t test was used to analyze the differences of SUV max between normal and abnormal muscles. The detecting rates of neck MRI and SPECT/CT for abnormal muscles were analyzed by χ2 test. Results:Normal muscles of healthy subjects showed mild symmetrical radioactivity distribution, with the SUV max of 1.10±0.19. A total of 60 muscles with abnormal uptake in 10 patients were found, including 7 rectus capitis posterior major, 10 obliquus capitis inferior, 8 splenius capitis, 8 semispinalis, 10 sternocleidomastoid, 5 trapezius, 3 musculus scalenus muscle and 9 levator scapulae. The SUV max of muscles with abnormal uptake was 1.81±0.43, which was higher than that of normal muscles ( t=17.05, P<0.001). Only 30 pieces abnormal hypertrophy muscle were found by neck MRI, and the detecting rate was much lower than that of SPECT/CT (18.75%(30/160) vs 37.50%(60/160); χ2=28.03, P<0.001). Conclusion:99Tc m-MIBI SPECT/CT may be a useful method for identifying dystonic muscles and a guide to precision therapy in patients with PCD.

The potential medicinal value of Ma bamboo (Dendrocalamus latiflorus), one of the most popular and economically important bamboo species in China, has been underestimated. In the present study, we found that D. latiflorus leaf extract (DLE) reduced fasting blood glucose levels, body weight, and low-density lipoprotein cholesterol with low liver toxicity in db/db mice. In addition, gene expression profiling was performed and pathway enrichment analysis showed that DLE affected metabolic pathways. Importantly, DLE activated the AKT signaling pathway and reduced glucose production by downregulating glucose-6-phosphatase (G6PC) and phosphoenolpyruvate carboxykinase 1 (PCK1) expression. Moreover, network pharmacology analysis identified rutin as an active component in DLE through targeting insulin growth factor 1 receptor (IGF1R), an upstream signaling transducer of AKT. Due to its hypoglycemic effects and low toxicity, DLE may be considered an adjuvant treatment option for type 2 diabetes patients.

Objective:To analyze the progress and promotion effect of the national multidisciplinary team(MDT) pilot project of digestive system tumor diagnosis and treatment, for the reference in promoting the popularition of tumor MDT model.Methods:The data of MDT project evaluation forms of 231 digestive system tumor MDT pilot hospitals in 2018(July 2017 to June 2018), 2019(July 2018 to June 2019)and 2020(July 2018 to June 2019)were obtained. The MDT of digestive system tumors, the development of outpatient and inpatient MDT, the distribution of cases, and the management, charging and regional radiation of MDT in the pilot hospital were analyzed. Descriptive analysis and frequency analysis were used for all the data.Results:With pilot hospitals of missing data excluded, the number of pilot hospitals included in the analysis from 2018 to 2020 was 227, 224 and 224, respectively.The number of pilot hospitals carrying out digestive system tumor MDT increased from 174 in 2018 to 222 in 2020, the number of outpatient and inpatient MDT cases increased from 48 332 and 61 823 to 72 493 and 106 899 respectively, and the proportion of pilot hospitals implementing the MDT management system increased from 159 to 214. In 2020, the average expenses of outpatient and inpatient MDT were mainly 200-500 yuan, and 135(60.3%) pilot hospitals became the leading MDT hospitals in the region.Conclusions:The MDT pilot project of digestive system tumors in China has achieved remarkable results.For example, the number of pilot hospitals carrying out MDT keeps increasing year by year, and the pilot hospitals have played a leading role in the region. In order to accelerate the coverage of the tumor MDT model, the authors suggested that the hospitals should optimize MDT in terms of patient accessibility, optimize management mode, promote the medical insurance reimbursement, and strengthen regional influence.

After decades of development,protein and peptide drugs have now grown into a major drug class in the marketplace.Target identification and validation are crucial for the discovery of protein and peptide drugs,and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection.However,owing to the developmental history in the pharmaceutical industry,previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs,while studies related to protein and peptide drugs are lacking.Here,we systematically explore the target spaces in the human genome specifically for protein and peptide drugs.Compared with other proteins,both suc-cessful protein and peptide drug targets have many special characteristics,and are also significantly different from those of small-molecule drugs in many aspects.Based on these features,we develop separate effective genome-wide target prediction models for protein and peptide drugs.Finally,a user-friendly web server,Predictor Of Protein and Peptide drugs'therapeutic Targets(POPPIT)(http://poppit.ncpsb.org.cn/),is established,which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.

Objective:To evaluate the clinical value of 18F-fluorodexoyglucose (FDG) PET/CT in distinguishing benign from malignant tumors in patients with cardiac tumors. Methods:Between January 2015 and September 2018, 18F-FDG PET/CT was performed in 3 678 patents in Beijing Anzhen Hospital, and 51 of them (51/3 678, 1.39%) were diagnosed as cardiac tumors. Finally, 28 patients (10 males, 18 females; mean age (52±14) years, age range: 18-84 years) with pathological results were included. According to pathological results, patients were divided into 4 groups: group 1 with primary benign cardiac tumor ( n=9), group 2 with primary malignant cardiac tumor ( n=9), group 3 with lymphoma ( n=6) and group 4 with secondary malignant cardiac tumor ( n=4). All patients underwent early (60 min) 18F-FDG PET/CT imaging and 22 patients (6, 7, 6, 3 patients in group 1, group 2, group 3, group 4 respectively) underwent delayed (120 min) imaging. The maximum standardized uptake value (SUV max) and target/backgroud ratio (TBR) of 4 groups in early imaging and delayed imaging were calculated and compared with one-way analysis of viariace and Scheffe Post-hoc test. TBR were calcualted as SUV max/mean standardized uptake value (SUV mean) in the liver. Receiver operating characteristic (ROC) curve analysis was also performed. Results:SUV max during early imaging, defined SUV max(early), was 2.6±1.5, 9.9±4.0, 20.5±6.1, 9.2±5.8 in group 1-4 respectively ( F=21.39, P<0.01), the value of group 1 was lower than that of group 2 and 3, and the value of group 3 was the highest (all P<0.005). TBR early was 1.1±0.6, 4.1±1.6, 9.4±2.6, 3.7±2.0 in the 4 groups ( F=29.15, P<0.01), the value of group 1 was lower than that of group 2 and 3, and the value of group 3 was the highest (all P<0.005). SUV max in delayed imaging (SUV max(delay)) was 2.4±1.2, 11.0±5.9, 25.8±7.7, 13.7±7.7 respectively in the 4 groups ( F=16.01, P<0.01). TBR delay was also significantly different among the 4 groups (1.3±0.7, 5.5±2.9, 14.4±4.9, 7.9±5.0; F=14.78, P<0.01), the value of group 3 was higher than that of group 1 and 2 (all P<0.05). ROC curve analysis showed optimal cut-off values for indicating malignancy were: SUV max(early)=4.2, TBR early=1.6, SUV max(delay)=4.6, TBR delay=1.9. The corresponding sensitivities, specificities, accuracies were 19/19, 8/9, 96.4%(27/28); 19/19, 7/9, 92.9%(26/28); 16/16, 6/6, 100%(22/22); 16/16, 5/6, 95.5%(21/22), respectively. Conclusions:18F-FDG PET/CT imaging can accurately diagnose malignant cardiac tumors. Delayed imaging can further improve the accuracy for diagnosis of malignant cardiac tumors.

Objective: To investigate the clinical outcome of modified thoracic umbilical flap, spanning chest and abdomen, in repairing large soft-tissue defect of limbs. Methods: From April 2012 to March 2017, 7 patients with large soft-tissue defects of limbs were admitted in the Department of Traumatic Osteopathic, Yidu Central Hospital of Weifang. The patients include 5 males and 2 females, aged from 29 to 51 years, with the mean age of 43 years. Four patients had upper limb soft-tissue defect and 3 patients were lower limb. All limbs large soft-tissue defects were treated by ultra-long thoracic umbilical flaps, spanning chest and abdomen. Epigastric artery and intercostal arteries or lateral thoracic artery were included in the flap to provide double blood supply with only one vascular anastomosis. Results: All 7 flaps(30 cm×9 cm-45 cm×13 cm) survived. The followed-up period was 3 months to 1 years. There was no necrosis or infection in tendon and bone observed. The texture of flaps in 5 patients were similar to surrounding skin, or slightly thickened by 2-3 mm. One patient had slightly bloated flap due to obesity, but had no effect on limb function. All patients were satisfied with the outcome. Conclusions Modified thoracic umbilical flap is an reasonable design for the repairment of large soft-tissue defect of limbs, and easily to carry out.

Objective: To investigate the effects of three-dimensional digital technology (3D-CTA) in repairing wounds of the limb with anterolateral thigh perforator flap. Methods: From April 2014 to June 2017, 12 patients with extensive skin and soft tissue defects on extremities were selected from the Yidu Central Hospital of Weifang. Twelve patients were performed anterior femoral perforator flaps. There were 9 males and 3 females, aged from 23 to 52 years old, with the mean age of 32 years. The defects were 8 cm×3 cm to 25 cm×9 cm in size, and all of them were accompanied by bone and/or muscle exposure. Preoperative CT scan of the donor site of the free flap used to achieve the three-dimensional images of arterial blood area, in order to determine the origin, direction, classification, length, diameter and the position of pedicle perforator of the anterolateral thigh perforator flap by 3D-CTA.According to the preoperative condition of lateral circumflex femoral artery, the perforator flaps of anterolateral femoral artery on the contralateral or ipsilateral side were designed to repair the wound. Results: Twelve anterolateral thigh perforator flaps have been transferred using above methods. All the flaps survived well and the donor site was directly closed.All patients were followed up for 1-6 months (mean 3 months). The appearance of flaps was satisfactory. The diameter and location of the perforator artery were measured using pre-operative digital angiography, as well as the actual value of perforator artery. Preoperative digital examination was consistent with the type of perforator found during the operation, with an accuracy of 100%. Conclusions For the soft tissue reconstruction by anterolateral thigh perforator flaps, preoperative digitization technology can identify the diameter, the type and origin of vessels, optimize the operation plan, reduce the difficulty of flap design, and reduce the risk of operation.