Objective:To analyze the learning curve of TiRobot-assisted lumbar pedicle screw fixation (LPSF) by cumulative sum (CUSUM) test method.Methods:The clinical data of 50 patients who underwent TiRobot-assisted LPSF from January 2020 to December 2022 in Beijing Friendship Hospital, Capital Medical University were retrospectively analyzed. CUSUM analysis and learning curve fitting were performed with robot usage time as the main indicator with the time for each step refined (robot registration time, path planning time and guide wire placement time), to select the best learning curve fitting model with the R2 value closest to 1. Using the turning point of the learning curve as the boundary, the learning curve was divided into two stages as learning stage and maturity stage, and then the observation indexes were compared between the two stages. Results:All 50 patients successfully completed the surgery without perioperative complications, with a total of 244 pedicle screws implanted. The total robot usage time and robot registration time showed a gradually decreasing trend with the increase of case number, and the learning curves were successfully fitted and reached their peaks at the seventeenth and thirteenth cases respectively. The entire learning process was divided into learning stage (17 cases) and maturity stage (33 cases) based on the turning point of the learning curve of total robot usage time. The path planning time and guide wire placement time did not show significant changes with the increase in the case number. The total robot usage time, robot registration time and the intraoperative blood loss in the learning stage were significantly higher than those in the maturity stage: (35.35 ± 1.58) min vs. (30.61 ± 0.43) min, (20.83 ± 1.56) min vs. (14.94 ± 0.29) min and 400 (150, 500) ml vs. 200 (110, 300) ml, the guide wire placement time of per screw was significantly lower than that in the maturity stage: 2.00 (1.83, 2.34) min/screw vs. 2.33 (2.13, 2.69) min/screw, and there were statistical differences ( P<0.05 or <0.01). There were no statistical difference in the path planning time, path planning time of per screw, guide wire placement time and the accuracy of screw placement between two stages ( P>0.05). Conclusions:TiRobot-assisted LPSF is a new technology with safety and effectiveness, and it has a relatively short learning curve. To achieve technological maturity, at least 17 surgeries are required with accumulated experience, and the robot registration is the main step of the learning process. After reaching maturity stage, the robot usage time is significantly shortened and intraoperative trauma is significantly reduced while the relatively high screw placement accuracy is ensured.

Objective:To analyze the learning curve of TiRobot-assisted lumbar pedicle screw fixation (LPSF) by cumulative sum (CUSUM) test method.Methods:The clinical data of 50 patients who underwent TiRobot-assisted LPSF from January 2020 to December 2022 in Beijing Friendship Hospital, Capital Medical University were retrospectively analyzed. CUSUM analysis and learning curve fitting were performed with robot usage time as the main indicator with the time for each step refined (robot registration time, path planning time and guide wire placement time), to select the best learning curve fitting model with the R2 value closest to 1. Using the turning point of the learning curve as the boundary, the learning curve was divided into two stages as learning stage and maturity stage, and then the observation indexes were compared between the two stages. Results:All 50 patients successfully completed the surgery without perioperative complications, with a total of 244 pedicle screws implanted. The total robot usage time and robot registration time showed a gradually decreasing trend with the increase of case number, and the learning curves were successfully fitted and reached their peaks at the seventeenth and thirteenth cases respectively. The entire learning process was divided into learning stage (17 cases) and maturity stage (33 cases) based on the turning point of the learning curve of total robot usage time. The path planning time and guide wire placement time did not show significant changes with the increase in the case number. The total robot usage time, robot registration time and the intraoperative blood loss in the learning stage were significantly higher than those in the maturity stage: (35.35 ± 1.58) min vs. (30.61 ± 0.43) min, (20.83 ± 1.56) min vs. (14.94 ± 0.29) min and 400 (150, 500) ml vs. 200 (110, 300) ml, the guide wire placement time of per screw was significantly lower than that in the maturity stage: 2.00 (1.83, 2.34) min/screw vs. 2.33 (2.13, 2.69) min/screw, and there were statistical differences ( P<0.05 or <0.01). There were no statistical difference in the path planning time, path planning time of per screw, guide wire placement time and the accuracy of screw placement between two stages ( P>0.05). Conclusions:TiRobot-assisted LPSF is a new technology with safety and effectiveness, and it has a relatively short learning curve. To achieve technological maturity, at least 17 surgeries are required with accumulated experience, and the robot registration is the main step of the learning process. After reaching maturity stage, the robot usage time is significantly shortened and intraoperative trauma is significantly reduced while the relatively high screw placement accuracy is ensured.

OBJECTIVE To test and compare the median effective dose(ED50) of ciprofol for gastroscope in patients of different genders and ages. METHODS Patients who planed to undergo gastroscope examination and treatment from March 2023 to April 2023 were selected, and divided into four groups according to stratified random method: N1 group(non-elderly male patients), N2 group(non-elderly female patients), N3 group(elderly male patients), and N4 group(elderly female patients). All patients received intravenous injection of 0.1 μg·kg−1 sufentanil followed by injection of the test dose of ciprofol according to Dixon’s modified sequential method. Gastroscope was performed after the disappearance of the eyelash reflex. The initial dose of ciprofol in all four groups was 0.4 mg·kg−1, and the ratio of adjacent doses was 1∶1.1. The next patient would receive a 10% increase in the dose of ciprofol if the patient experienced positive reactions such as coughing, frowning, and body movements during the endoscopy process. Otherwise, it would be judged as a negative reaction, and the next patient would receive a 10% decrease in the dose of ciprofol. The transition from a positive reaction to a negative reaction was defined as a turning point, and the study was terminated when seven turning points occurred. Hemodynamic parameters, oxygen saturation and adverse reactions were recorded at different time points. The Probit regression analysis method was used to calculate the ED50 of ciprofol for four groups. RESULTS The ED50 of ciprofol combined with 0.1 μg·kg−1 sufentanil for gastroscope in the non-elderly men, non-elderly women, elderly men, and elderly women were 0.409, 0.373, 0.356, 0.327 mg·kg−1, respectively. The ED50 of ciprofol in the N1 group was significantly higher compared with the N2 group and N3 group(P<0.05). The ED50 of ciprofol in the N4 group was significantly lower compared with the N2 group and N3 group(P<0.05). CONCLUSION The ED50 of ciprofol is significantly different among gastroscope patients of different genders and ages, which is lower in female patients than in male patients, and is lower in older patients than in non-elderly patients.

OBJECTIVE: To investigate the clinical efficacy of Huang'e Capsules in the treatment of type ⅢA chronic prostatitis, and its effects on the levels of the inflammatory cytokines neutrophil elastase (NE), IL-8 and TGF-β1 in the expressed prostatic secretion (EPS) of the patients. METHODS: We selected 120 patients with type ⅢA chronic prostatitis and randomly assigned them to medication with Huang'e Capsules (the trial group, n = 60) or Levofloxacin and Tamsulosin (the control group, n = 60), both for a course of 4 weeks. We obtained the NIH-CPSI scores and the levels of NE, IL-8 and TGF-β1 in the EPS, and compared them between the two groups before and after treatment. RESULTS: Totally, 116 of the patients completed the study, 59 in the trial and 57 in the control group. The overall clinical effectiveness was significantly higher in the trial group than in the control (89.8% vs 77.2%, P<0.05). Compared with the baseline, the patients of the trial group showed significant decreases after treatment in the total NIH-CPSI scores (32.5±7.4 vs 13.2±5.1), pain symptom scores (13.7±3.9 vs 4.2±2.3), urination symptom scores (6.9±2.4 vs 5.1±3.2) and quality of life (QOL) scores (8.3±2.7 vs 3.7±1.5) (all P< 0.05), and so did the controls in the total NIH-CPSI scores (30.8±7.8 vs 13.7±3.9), pain symptom scores (14.2±4.1 vs 7.8±2.9), urination symptom scores (7.1±2.7 vs 4.9±3.4) and quality of life (QOL) scores (8.1±2.4 vs 5.6±1.9) (all P< 0.05), and the decreases were even more significant in the trial than in the control group in the pain symptom and QOL scores ( P< 0.05). The patients of the trial group also exhibited a marked reduction after treatment in the contents of NE (［1135.4±321.5］ vs ［347.6±207.3］ ng/L, P< 0.05) and IL-8 (［974.9±231.6］ vs ［ 431.3±207.2］ ng/L, P< 0.05) but an elevation in that of TGF-β1 (［591.0±172.1］ vs ［1 402.1 ± 221.5］ ng/L, P< 0.05) in the EPS, and so did the controls in the levels of NE (［1052.8±280.3］ vs ［761.1±225.1］ ng/L, P<0.05), (［1007.5±287.7］ vs ［775.7±182.5］ ng/L, P< 0.05), (［607.8±201.3］ vs ［871.3±192.5］ ng/L, P< 0.05), with even more significant improvement in the trial than in the control group (P< 0.05). CONCLUSION Huang'e Capsules has a significant clinical efficacy and safety in the treatment of type IIIA prostatitis, which can effectively relieve the pain and urination symptoms and improve the levels of the inflammatory cytokines NE, IL-8 and TGF-β1 in the patients.
Humans ; Male ; Prostatitis/metabolism* ; Interleukin-8/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Transforming Growth Factor beta1/metabolism* ; Prostate/metabolism* ; Leukocyte Elastase/metabolism* ; Tamsulosin ; Treatment Outcome ; Capsules ; Middle Aged ; Phytotherapy ; Cytokines/metabolism* ; Adult ; Levofloxacin

[This corrects the article DOI: 10.1016/j.apsb.2022.10.016.].

Sepsis-induced liver injury (SILI) is an important cause of septicemia deaths. BaWeiBaiDuSan (BWBDS) was extracted from a formula of Panax ginseng C. A. Meyer, Lilium brownie F. E. Brown ex Miellez var. viridulum Baker, Polygonatum sibiricum Delar. ex Redoute, Lonicera japonica Thunb., Hippophae rhamnoides Linn., Amygdalus Communis Vas, Platycodon grandiflorus (Jacq.) A. DC., and Cortex Phelloderdri. Herein, we investigated whether the BWBDS treatment could reverse SILI by the mechanism of modulating gut microbiota. BWBDS protected mice against SILI, which was associated with promoting macrophage anti-inflammatory activity and enhancing intestinal integrity. BWBDS selectively promoted the growth of Lactobacillus johnsonii (L. johnsonii) in cecal ligation and puncture treated mice. Fecal microbiota transplantation treatment indicated that gut bacteria correlated with sepsis and was required for BWBDS anti-sepsis effects. Notably, L. johnsonii significantly reduced SILI by promoting macrophage anti-inflammatory activity, increasing interleukin-10⁺ M2 macrophage production and enhancing intestinal integrity. Furthermore, heat inactivation L. johnsonii (HI-L. johnsonii) treatment promoted macrophage anti-inflammatory activity and alleviated SILI. Our findings revealed BWBDS and gut microbiota L. johnsonii as novel prebiotic and probiotic that may be used to treat SILI. The potential underlying mechanism was at least in part, via L. johnsonii-dependent immune regulation and interleukin-10⁺ M2 macrophage production.

Objective: To establish a comprehensive diagnostic classification model of lateral cephalograms based on artificial intelligence (AI) to provide reference for orthodontic diagnosis. Methods: A total of 2 894 lateral cephalograms were collected in Department of Orthodontics, Capital Medical University School of Stomatology from January 2015 to December 2021 to construct a data set, including 1 351 males and 1 543 females with a mean age of (26.4± 7.4) years. Firstly, 2 orthodontists (with 5 and 8 years of orthodontic experience, respectively) performed manual annotation and calculated measurement for primary classification, and then 2 senior orthodontists (with more than 20 years of orthodontic experience) verified the 8 diagnostic classifications including skeletal and dental indices. The data were randomly divided into training, validation, and test sets in the ratio of 7∶2∶1. The open source DenseNet121 was used to construct the model. The performance of the model was evaluated by classification accuracy, precision rate, sensitivity, specificity and area under the curve (AUC). Visualization of model regions of interest through class activation heatmaps. Results: The automatic classification model of lateral cephalograms was successfully established. It took 0.012 s on average to make 8 diagnoses on a lateral cephalogram. The accuracy of 5 classifications was 80%-90%, including sagittal and vertical skeletal facial pattern, mandibular growth, inclination of upper incisors, and protrusion of lower incisors. The acuracy rate of 3 classifications was 70%-80%, including maxillary growth, inclination of lower incisors and protrusion of upper incisors. The average AUC of each classification was ≥0.90. The class activation heat map of successfully classified lateral cephalograms showed that the AI model activation regions were distributed in the relevant structural regions. Conclusions: In this study, an automatic classification model for lateral cephalograms was established based on the DenseNet121 to achieve rapid classification of eight commonly used clinical diagnostic items.
Male ; Female ; Humans ; Young Adult ; Adult ; Artificial Intelligence ; Deep Learning ; Cephalometry ; Maxilla ; Mandible/diagnostic imaging*

In the fifth scientific and technological revolution， information technology is the first productivity， which has a great impact on the supply and demand of medical services. Generally， internet medicine is equivalent to the combination between health industry and information technology. "Healthy China" strategy is China's "priority development strategy"， which adheres to the principle of health equity， emphasizes the integration of health into all policies， and takes co-construction and sharing as the basic path. With implementing internet medicine， "Healthy China" strategy promotes the mobility of medical service with three tools： interconnection， data and artificial intelligence. This enhances the operation efficiency of overall medical and health system， and optimizes the allocation of medical resources. The future development of internet medicine follows the double helix mode driven by technology and policy， and the policy determines the development boundary of the industry. On the basis to ensure medical safety， we should explore the possibility of internet diagnosis and treatment further， and pay attention to the fairness of resource allocation while improving efficiency， so as to realize the co-construction and sharing of health services.

Internet medicine is not a concept of jurisprudence. China's current medical law system mainly focuses on main qualifications of the participants who conduct diagnosis and treatment. This paper focuses on several business models of the core element （diagnosis and treatment） in internet medicine， namely： online health consultation provided by internet medical platform， online diagnosis and treatment by internet hospital， and certain artificial intelligence（AI） medicine products that are specialized for diagnosis and treatment. This paper summarizes the development of these three business models， and analyzes the main problems in their development， including the legitimacy identification of online consultation， the dilemma of the development of internet hospitals， the impact of insufficient sample data on the development of medical AI， and the reverse restriction of regulatory difficulties to the development of internet medicine. The next step of developing internet medicine is to broaden the scope of internet diagnosis and treatment on the premise of medical safety， which will be based on the improvement of current regulatory system. It is urgent to build early risk warning system and supervision/ management mechanism for internet medicine.

The penetration and integration of internet with medical industry is apparently falling behind its interaction with other industries in terms of speed and scale. The main reason is due to the high risk and difficult supervision of internet medicine. Based on the regulatory context， this paper analyzes the endogenous and exogenous risk of internet medicine. The inherent characteristics of the internet （such as openness， diversity， multi subjectivity， virtuality， transparency， and high aggregation） lead to endogenous risks， including jurisdiction disputes， uncertainty of rights and obligations， security of personal information and medical information， monopoly. The lag of specific law in internet medicine， the lack of extensibility and synergy of traditional hierarchical regulatory system， the uncertainty of internet hospital regulatory policy details， the lack of technical specifications/operating procedures and other external system coverage in internet diagnosis and treatment lead to regulatory blind areas and exogenous risks. Based on the risk analysis， this paper discusses further construction of the mechanisms of risk assessment and regulation for internet medicine.