BACKGROUND:Maxillofacial bone three-dimensional(3D)printing technology has been widely used in clinical diagnosis and treatment,but the data source before performing maxillofacial bone 3D printing mainly comes from the CT scanning data.The lens,thyroid and other parts of the human body are extremely sensitive to X-rays;therefore,it is particularly important to effectively reduce the dose of CT radiation when acquiring the data source.OBJECTIVE:To explore the feasibility of low-dose CT technology in optimizing radiation dose for maxillofacial bone 3D printing.METHODS:The medical records of 65 patients who underwent maxillofacial bone 3D printing in the Department of Stomatology at the General Hospital of Northern Theater Command from March 2021 to December 2023 were retrospectively collected and categorized into a conventional CT-dose 3D printing group(conventional CT-dose,120 kVp,automated tube current modulation,n=32)and a low-CT-dose 3D printing group(low-CT-dose group,80 kVp,automated tube current modulation,n=33).The effective dose of radiation was calculated and compared between the two groups.A Likert scale was used to evaluate the quality of 3D printing in the two groups,and the measurement bias and consistency between evaluators were measured using the Bland-Altman method.RESULTS AND CONCLUSION:(1)There was no significant difference in the general demographic characteristics(age,height,weight,body mass,sex,and body mass index)between the two groups(all P＞0.05).(2)The effective dose value of the low CT-dose 3D printing group was(0.3±0.1)mSv,which was about 62.5％lower than that in the conventional CT-dose 3D printing group[(0.8±0.1)mSv].(3)There was no significant difference in the subjective scoring of 3D printing quality between the two groups(all P＞0.05).The subjective consistency among evaluators was good,with Kappa values of 0.85,0.80,and 0.76.The scatter points in the Bland-Altman for both protocols were uniformly distributed within the standard deviation line,indicating good consistency between the two groups.To conclude,low-dose CT technology can be effectively applied in maxillofacial bone 3D printing,reducing radiation dose without affecting the quality of 3D printing.

BACKGROUND:Maxillofacial bone three-dimensional(3D)printing technology has been widely used in clinical diagnosis and treatment,but the data source before performing maxillofacial bone 3D printing mainly comes from the CT scanning data.The lens,thyroid and other parts of the human body are extremely sensitive to X-rays;therefore,it is particularly important to effectively reduce the dose of CT radiation when acquiring the data source.OBJECTIVE:To explore the feasibility of low-dose CT technology in optimizing radiation dose for maxillofacial bone 3D printing.METHODS:The medical records of 65 patients who underwent maxillofacial bone 3D printing in the Department of Stomatology at the General Hospital of Northern Theater Command from March 2021 to December 2023 were retrospectively collected and categorized into a conventional CT-dose 3D printing group(conventional CT-dose,120 kVp,automated tube current modulation,n=32)and a low-CT-dose 3D printing group(low-CT-dose group,80 kVp,automated tube current modulation,n=33).The effective dose of radiation was calculated and compared between the two groups.A Likert scale was used to evaluate the quality of 3D printing in the two groups,and the measurement bias and consistency between evaluators were measured using the Bland-Altman method.RESULTS AND CONCLUSION:(1)There was no significant difference in the general demographic characteristics(age,height,weight,body mass,sex,and body mass index)between the two groups(all P＞0.05).(2)The effective dose value of the low CT-dose 3D printing group was(0.3±0.1)mSv,which was about 62.5％lower than that in the conventional CT-dose 3D printing group[(0.8±0.1)mSv].(3)There was no significant difference in the subjective scoring of 3D printing quality between the two groups(all P＞0.05).The subjective consistency among evaluators was good,with Kappa values of 0.85,0.80,and 0.76.The scatter points in the Bland-Altman for both protocols were uniformly distributed within the standard deviation line,indicating good consistency between the two groups.To conclude,low-dose CT technology can be effectively applied in maxillofacial bone 3D printing,reducing radiation dose without affecting the quality of 3D printing.

Metabolic dysfunction-associated fatty liver disease (MAFLD), characterized by fatty acid overload, secondary chronic inflammation, and fibrosis, has become the most prevalent chronic liver disease globally. While no effective pharmacotherapy exists for MAFLD, mitigating inflammatory responses represents a promising approach to preventing the progression from steatosis to severe steatohepatitis. The NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, which detects endogenous danger and stress signals, has emerged as a significant target for inflammatory disease treatment, as transcriptional inactivation of its components demonstrates the therapeutic potential for MAFLD. Natural products targeting NLRP3 inflammasome activation have shown promising efficacy in MAFLD therapy. This review synthesizes the current understanding of NLRP3 inflammasome activation and therapeutic targets for NLRP3 homeostasis. Additionally, natural products reported to inhibit NLRP3 inflammasome for MAFLD improvement are categorized according to their mechanisms of action. The review also addresses limitations and future directions regarding natural products targeting NLRP3 inflammasome in MAFLD treatment. Enhanced understanding of NLRP3 inflammasome activation mechanisms in MAFLD and the identification of novel natural products supported by mechanistic research will significantly advance MAFLD treatment.
Humans ; NLR Family, Pyrin Domain-Containing 3 Protein/immunology* ; Inflammasomes/metabolism* ; Biological Products/therapeutic use* ; Animals ; Fatty Liver/immunology*

Objective To construct a distance self-attention(DSA)and long short-term memory(LSTM)model and observe its value for predicting X-ray tube arcing in CT equipment.Methods CT equipment status data of internet of medical things were collected and preprocessed,then DSA-LSTM model based on model attention(MA)module and nonlinear attenuation distance factor was constructed,and its value for predicting X-ray tube arcing in CT equipment was analyzed compared with other models.Results Compared with other models,DSA-LSTM model had better comprehensive efficiency for predicting X-ray tube arcing in CT equipment.MA module and nonlinear attenuation distance factor could improve the predictive efficiency of DSA-LSTM model,and all included features contributed to the performance of DSA-LSTM model in a certain extent.Conclusion DSA-LSTM model could effectively predict X-ray tube arcing in CT equipment.

Objective To investigate and analyze the current situation of the construction of Smart Hospital in the dis-trict-level hospital of Beijing,and to provide reference for thedistrict-level hospitals to promote the construction of Smart Hospitals.Methods A questionnaire survey was conducted in Beijing district-level hospitals,and the construc-tion of Smart Hospital was analyzed by descriptive statistical analysis.Results The overall construction rate of Beijing district-level hospitals smart service business function was 50.98％,and the overall average construction rate of hos-pital smart management business function was 46.72％.93.75％hospitals thought that the investment in Smart Hos-pital construction was insufficient.The functions of smart service and management in different grades and categories of hospitals were different.Conclusion In order to promote the construction of Smart Hospital in Beijingdistrict-level hospitals,we should improve the top-level system such as strategic planning for the construction of smart hospi-tals,increase the investment in hospital informatization and talent teams,strengthen the standardization of intercon-nection between different hospitals,enhance the sharing and utilization of medical data and information,and strengthen the application of new hospital technologies and hospital information security.

Objective To investigate and analyze the current situation of the construction of Smart Hospital in the dis-trict-level hospital of Beijing,and to provide reference for thedistrict-level hospitals to promote the construction of Smart Hospitals.Methods A questionnaire survey was conducted in Beijing district-level hospitals,and the construc-tion of Smart Hospital was analyzed by descriptive statistical analysis.Results The overall construction rate of Beijing district-level hospitals smart service business function was 50.98％,and the overall average construction rate of hos-pital smart management business function was 46.72％.93.75％hospitals thought that the investment in Smart Hos-pital construction was insufficient.The functions of smart service and management in different grades and categories of hospitals were different.Conclusion In order to promote the construction of Smart Hospital in Beijingdistrict-level hospitals,we should improve the top-level system such as strategic planning for the construction of smart hospi-tals,increase the investment in hospital informatization and talent teams,strengthen the standardization of intercon-nection between different hospitals,enhance the sharing and utilization of medical data and information,and strengthen the application of new hospital technologies and hospital information security.

Objective To satisfy the normalized disinfection in the orthopedic ward,an air sterilizer based on low-temperature plasma has been developed to investigate its sterilization results in a dynamic environment of hospitalization where patients,companions and medical workers are involved.Methods This study took an orthopedics ward in the Secondary Affiliated Hospital of Xi'an Jiaotong University,as the research object,where a home-made low-temperature plasma air sterilizer was utilized.A six-stage viable Andersen cascade impactor was used to sample the natural bacteria in the ward before and after machine operation for three hours.The species and quantity of bacteria in the ward were analyzed.Results The ozone concentration in the indoor dynamic environment decreased to below 5 ppbv.After three-hour disinfection,the elimination rate of natural bacteria reached 92.35％.The final colony forming unit decreased to～150 CFU/m3;the extinction rates of Staphylococcus hominis,Bacillus cereus,molds,and Micrococcus luteus were 90.48％,80.90％,87.50％,and 92.82％respectively.Even all Haemophilus massiliensis disappeared after two-hour treatment.Conclusion Intermittent disinfection of the dynamic environment in the ward using low-temperature plasma synergistic catalyst has enabled the indoor ozone concentration to reach the first-level national standard line,effectively suppressing secondary pollution caused by ozone leakage while efficiently killing suspended microorganisms in the air,which is close to the disinfection level Ⅰenvironment specified in Hygienic Standard for Disinfection in Hospitals(GB 15982-2012).The results also show that the plasma catalytic synergistic disinfection and sterilization has the technical advantages of efficient disinfection and human-machine coexistence,which can ensure indoor air quality safety,reduce the workload of nursing staff,and thus is an effective method to assist or even replace the existing physical and chemical means.

Objective To satisfy the normalized disinfection in the orthopedic ward,an air sterilizer based on low-temperature plasma has been developed to investigate its sterilization results in a dynamic environment of hospitalization where patients,companions and medical workers are involved.Methods This study took an orthopedics ward in the Secondary Affiliated Hospital of Xi'an Jiaotong University,as the research object,where a home-made low-temperature plasma air sterilizer was utilized.A six-stage viable Andersen cascade impactor was used to sample the natural bacteria in the ward before and after machine operation for three hours.The species and quantity of bacteria in the ward were analyzed.Results The ozone concentration in the indoor dynamic environment decreased to below 5 ppbv.After three-hour disinfection,the elimination rate of natural bacteria reached 92.35％.The final colony forming unit decreased to～150 CFU/m3;the extinction rates of Staphylococcus hominis,Bacillus cereus,molds,and Micrococcus luteus were 90.48％,80.90％,87.50％,and 92.82％respectively.Even all Haemophilus massiliensis disappeared after two-hour treatment.Conclusion Intermittent disinfection of the dynamic environment in the ward using low-temperature plasma synergistic catalyst has enabled the indoor ozone concentration to reach the first-level national standard line,effectively suppressing secondary pollution caused by ozone leakage while efficiently killing suspended microorganisms in the air,which is close to the disinfection level Ⅰenvironment specified in Hygienic Standard for Disinfection in Hospitals(GB 15982-2012).The results also show that the plasma catalytic synergistic disinfection and sterilization has the technical advantages of efficient disinfection and human-machine coexistence,which can ensure indoor air quality safety,reduce the workload of nursing staff,and thus is an effective method to assist or even replace the existing physical and chemical means.

Objective To construct a distance self-attention(DSA)and long short-term memory(LSTM)model and observe its value for predicting X-ray tube arcing in CT equipment.Methods CT equipment status data of internet of medical things were collected and preprocessed,then DSA-LSTM model based on model attention(MA)module and nonlinear attenuation distance factor was constructed,and its value for predicting X-ray tube arcing in CT equipment was analyzed compared with other models.Results Compared with other models,DSA-LSTM model had better comprehensive efficiency for predicting X-ray tube arcing in CT equipment.MA module and nonlinear attenuation distance factor could improve the predictive efficiency of DSA-LSTM model,and all included features contributed to the performance of DSA-LSTM model in a certain extent.Conclusion DSA-LSTM model could effectively predict X-ray tube arcing in CT equipment.

BACKGROUND:MRI is important for the diagnosis of early knee osteoarthritis.MRI image recognition and intelligent segmentation of knee osteoarthritis using deep learning method is a hot topic in image diagnosis of artificial intelligence. OBJECTIVE:Through deep learning of MRI images of knee osteoarthritis,the segmentation of femur,tibia,patella,cartilage,meniscus,ligaments,muscles and effusion of knee can be automatically divided,and then volume of knee fluid and muscle content were measured. METHODS:100 normal knee joints and 100 knee osteoarthritis patients were selected and randomly divided into training dataset(n=160),validation dataset(n=20),and test dataset(n=20)according to the ratio of 8:1:1.The Coarse-to-Fine sequential training method was used to train the 3D-UNET network deep learning model.A Coarse MRI segmentation model of the knee sagittal plane was trained first,and the rough segmentation results were used as a mask,and then the fine segmentation model was trained.The T1WI and T2WI images of the sagittal surface of the knee joint and the marking files of each structure were input,and DeepLab v3 was used to segment bone,cartilage,ligament,meniscus,muscle,and effusion of knee,and 3D reconstruction was finally displayed and automatic measurement results(muscle content and volume of knee fluid)were displayed to complete the deep learning application program.The MRI data of 26 normal subjects and 38 patients with knee osteoarthritis were screened for validation. RESULTS AND CONCLUSION:(1)The 26 normal subjects were selected,including 13 females and 13 males,with a mean age of(34.88±11.75)years old.The mean muscle content of the knee joint was(1 051 322.94±2 007 249.00)mL,the mean median was 631 165.21 mL,and the mean volume of effusion was(291.85±559.59)mL.The mean median was 0 mL.(2)There were 38 patients with knee osteoarthritis,including 30 females and 8 males.The mean age was(68.53±9.87)years old.The mean muscle content was(782 409.18±331 392.56)mL,the mean median was 689 105.66 mL,and the mean volume of effusion was(1 625.23±5 014.03)mL.The mean median was 178.72 mL.(3)There was no significant difference in muscle content between normal people and knee osteoarthritis patients.The volume of effusion in patients with knee osteoarthritis was higher than that in normal subjects,and the difference was significant(P<0.05).(4)It is indicated that the intelligent segmentation of MRI images by deep learning can discard the defects of manual segmentation in the past.The more accuracy evaluation of knee osteoarthritis was necessary,and the image segmentation was processed more precisely in the future to improve the accuracy of the results.