Maxillofacial fractures are common and frequently occurring diseases in Oral and Maxillofacial Surgery.The traditional clinical diagnosis and treatment process is easily affected by complex maxillofacial anatomy and differences in doctors' experience in reading X-rays and making diagnoses.In recent years,artificial intelligence technology has provided new solutions for the accurate diag-nosis and treatment planning of maxillofacial fractures.Automating image analysis through computer vision methods improves diagnostic accuracy and efficiency and assists in formulating treatment plans,showing broad application prospects and value.This article reviews and summarizes the research on the application of artificial intelligence in the auxiliary diagnosis and treatment of maxillofacial fractures at home and abroad,analyzes its advantages and disadvantages,and looks forward to future research trends.

Objective:To investigate the longitudinal stability of the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and the Activity of Daily Living Scale (ADL).Methods:The longitudinal cognitive assessment results of 68 dementia patients admitted to the Dementia and Leukoencephalopathy Outpatient Clinic, Department of Neurology, Peking Union Medical College Hospital, from January 2021 to January 2024, were retrospectively analyzed, including the total and sub-items scores of the MMSE, MoCA, and ADL. Two different rules were applied to analyze the abnormality rates: rule 1, where the current test result being better than the previous one was considered an abnormality; rule 2, where the current test result being better than the previous average score was considered an abnormality (If a patient had only 2 cognitive assessments, rule 2 was considered the same as rule 1). Two rules were used to analyze the abnormality rates of the scales. The statistical analyses were repeated after excluding patients with possible anxiety and depression status.Results:In assessing the total score stability, MMSE showed the lowest abnormality rates [27.2% (31/114) under rule 1 and 29.8% (34/114) under rule 2], while MoCA had the highest abnormality rates [41.3% (26/63) and 46.0% (29/63), respectively]. The ADL abnormality rates were 27.7% (23/83) and 33.7% (28/83), respectively. Among MoCA sub-items, category cue, multiple choice cue, second memory trial, orientation, and clock showed higher abnormality rates [31.7%(20/63), 30.2%(19/63), 23.8%(15/63), 22.2%(14/63), 22.2%(14/63), respectively]. After excluding population with possible anxiety and depression status, the relative abnormality rates of MMSE and ADL sub-items did not significantly change, while the abnormality rate of orientation in MoCA sub-items decreased relatively.Conclusion:The MMSE and ADL exhibit good stability in long-term monitoring of dementia patients, serving as essential tools for assessing and following up cognitive changes.

OBJECTIVE To observe the changes of serum proteins in the mice with carbapenem-resistant hyperviru-lent Klebsiella pneumoniae(CR-hvKP)bloodstream infection by using liquid chromatogram-mass spectrometer(LC-MS),find out the differentially expressed proteins and carry out corresponding biological function analysis.METHODS The models of ICR mice with CR-hvKP and classical Klebsiella pneumoniae(cKP)bloodstream infec-tions were established,the serum specimens were collected from the mice at 12 hours of establishment of the in-fection models and were detected by using LC-MS.The result of LC-MS was identified by using Maxquant soft-ware.The corresponding bioinformatics analysis was performed for the differentially expressed proteins.RESULTS As compared with the normal control group,there were 24 upregulated proteins and 20 downregulated proteins in CR-hvKP group.As compared with cKP group,there were 107 upregulated proteins in the CR-hvKP group.The 134 differentially expressed proteins were retrieved one by one from Uniprot database,it was found that the pro-teins were involved in biological regulation,immune process,biological interaction,movement,metabolic process,response to stimulation,signal transduction,inflammatory response,oxidative stress and angiogenesis.The signal pathway analysis involved multiple metabolism-related pathways,including complement and coagula-tion cascades,cholesterol metabolism,bacterial infection,heme clearance,and assembly,remodeling and clear-ance of plasma lipoprotein.In terms of the proteins being attached great importance,the expression levels of kal-likrein B1(KLKB1)and serpin family A(Serpina)1b were downregulated as compared with the normal control group and were upregulated as compared with the cKP group;the expression levels of serum amyloid A protein(SAA)1,SAA2,Vanin-3(VNN3)and hemoglobinβpolypeptide chain b2(HBB-b2)were upregulated as com-pared with both the cKP group and the normal control group.CONCLUSIONS The CR-hvKP bloodstream infection involves the activation and action of multiple proteins.The rise of SAA1,SAA2,VNN3 and HBB-b2 or the de-cline of KLKB1 and Serpina1b may indicate the CR-hvKP bloodstream infection.

Maxillofacial fractures are common and frequently occurring diseases in Oral and Maxillofacial Surgery.The traditional clinical diagnosis and treatment process is easily affected by complex maxillofacial anatomy and differences in doctors' experience in reading X-rays and making diagnoses.In recent years,artificial intelligence technology has provided new solutions for the accurate diag-nosis and treatment planning of maxillofacial fractures.Automating image analysis through computer vision methods improves diagnostic accuracy and efficiency and assists in formulating treatment plans,showing broad application prospects and value.This article reviews and summarizes the research on the application of artificial intelligence in the auxiliary diagnosis and treatment of maxillofacial fractures at home and abroad,analyzes its advantages and disadvantages,and looks forward to future research trends.

OBJECTIVE To observe the changes of serum proteins in the mice with carbapenem-resistant hyperviru-lent Klebsiella pneumoniae(CR-hvKP)bloodstream infection by using liquid chromatogram-mass spectrometer(LC-MS),find out the differentially expressed proteins and carry out corresponding biological function analysis.METHODS The models of ICR mice with CR-hvKP and classical Klebsiella pneumoniae(cKP)bloodstream infec-tions were established,the serum specimens were collected from the mice at 12 hours of establishment of the in-fection models and were detected by using LC-MS.The result of LC-MS was identified by using Maxquant soft-ware.The corresponding bioinformatics analysis was performed for the differentially expressed proteins.RESULTS As compared with the normal control group,there were 24 upregulated proteins and 20 downregulated proteins in CR-hvKP group.As compared with cKP group,there were 107 upregulated proteins in the CR-hvKP group.The 134 differentially expressed proteins were retrieved one by one from Uniprot database,it was found that the pro-teins were involved in biological regulation,immune process,biological interaction,movement,metabolic process,response to stimulation,signal transduction,inflammatory response,oxidative stress and angiogenesis.The signal pathway analysis involved multiple metabolism-related pathways,including complement and coagula-tion cascades,cholesterol metabolism,bacterial infection,heme clearance,and assembly,remodeling and clear-ance of plasma lipoprotein.In terms of the proteins being attached great importance,the expression levels of kal-likrein B1(KLKB1)and serpin family A(Serpina)1b were downregulated as compared with the normal control group and were upregulated as compared with the cKP group;the expression levels of serum amyloid A protein(SAA)1,SAA2,Vanin-3(VNN3)and hemoglobinβpolypeptide chain b2(HBB-b2)were upregulated as com-pared with both the cKP group and the normal control group.CONCLUSIONS The CR-hvKP bloodstream infection involves the activation and action of multiple proteins.The rise of SAA1,SAA2,VNN3 and HBB-b2 or the de-cline of KLKB1 and Serpina1b may indicate the CR-hvKP bloodstream infection.

Objective:To investigate the longitudinal stability of the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and the Activity of Daily Living Scale (ADL).Methods:The longitudinal cognitive assessment results of 68 dementia patients admitted to the Dementia and Leukoencephalopathy Outpatient Clinic, Department of Neurology, Peking Union Medical College Hospital, from January 2021 to January 2024, were retrospectively analyzed, including the total and sub-items scores of the MMSE, MoCA, and ADL. Two different rules were applied to analyze the abnormality rates: rule 1, where the current test result being better than the previous one was considered an abnormality; rule 2, where the current test result being better than the previous average score was considered an abnormality (If a patient had only 2 cognitive assessments, rule 2 was considered the same as rule 1). Two rules were used to analyze the abnormality rates of the scales. The statistical analyses were repeated after excluding patients with possible anxiety and depression status.Results:In assessing the total score stability, MMSE showed the lowest abnormality rates [27.2% (31/114) under rule 1 and 29.8% (34/114) under rule 2], while MoCA had the highest abnormality rates [41.3% (26/63) and 46.0% (29/63), respectively]. The ADL abnormality rates were 27.7% (23/83) and 33.7% (28/83), respectively. Among MoCA sub-items, category cue, multiple choice cue, second memory trial, orientation, and clock showed higher abnormality rates [31.7%(20/63), 30.2%(19/63), 23.8%(15/63), 22.2%(14/63), 22.2%(14/63), respectively]. After excluding population with possible anxiety and depression status, the relative abnormality rates of MMSE and ADL sub-items did not significantly change, while the abnormality rate of orientation in MoCA sub-items decreased relatively.Conclusion:The MMSE and ADL exhibit good stability in long-term monitoring of dementia patients, serving as essential tools for assessing and following up cognitive changes.

In response to the current situation and teaching status of the medical image processing course on the background of"new medical science",a teaching software which is highly compatible with the teaching process of medical image processing is developed.The teaching software allows for linear grayscale transformation,windowing display,scaling,rotation,mirroring,median filtering,differential sharpening,edge detection,histogram acquisition,and histogram equalization of medical images.Additionally,it enables parameter adjustments within a certain range for linear grayscale transformation,windowing display,scaling,rotation,median filtering,differential sharpening,and edge detection.Meanwhile,it employs different algorithms to achieve the scaling of medical images.The teaching software is used in the theoretical and experimental teaching of medical image processing courses at Baotou Medical College.It can improve students'initiative and enthusiasm in learning,strengthen their understanding of the examination points for radiology technicians,lay a solid foundation for subsequent courses,and ultimately achieve the goal of in-depth integration of"Medical Engineering"and"Medical Science"in the medical image technology major at Baotou Medical College under the background of"new medical science".

Objective To investigate the feasibility of the autoregressive integrated moving average model (ARIMA) in analyzing foodborne diseases in Hubei Province and predicting the future trend of foodborne diseases in Hubei Province. Methods Based on the number of reported cases of foodborne diseases in Hubei Province for eight consecutive years (2014-2021), an ARIMA model was constructed using Python software to fit the data. The model was validated and parameters were optimized with data from January 2022 to December 2022. The optimal fitting model was used to predict the incidence and trends of foodborne diseases in 2023. Results The incidence of foodborne diseases in Hubei Province showed seasonal periodicity, and the peak of epidemic was usually in July every year. SARIMA (0,1,0) (2,2,1)₁₂ was determined as the best fitting model. The model extrapolation effect was verified with 2022 data, and MAPE was 23.90 %, indicating that the model extrapolation effect was effective. Conclusion The SARIMA model is effective for short-term prediction of foodborne disease incidence trends in Hubei Province, and can provide a scientific basis for the formulation of foodborne disease prevention and control policies in the coming year.

Objective:To analyze the clinical and imaging features of patients with COVID-19-related osmotic demyelination syndrome (ODS).Methods:COVID-19-related ODS cases diagnosed in the Department of Neurology, Peking Union Medical College Hospital from January 2020 to September 2023 were retrospectively reviewed. And their past medical history, possible triggers, clinical manifestations, imaging manifestations, treatment and prognosis were summarized.Results:A total of 5 patients with COVID-19-related ODS were included. Electrolyte disturbances acted as an inducement of ODS in all patients (5/5),4 of whom with hyponatremia. Four of 5 patients first presented with disturbance of consciousness, followed by predominant dystonia. Imaging of all patients (5/5) showed isolated extrapontine myelinolysis (EPM). With the prolongation of the course of disease, such signal intensity could return to normal, and lesions showed atrophic changes in some patients. The patients′ clinical symptoms were partly relieved within a few days to a few months after treatment.Conclusions:COVID-19-related ODS is mostly associated with hyponatremia, and EPM is more common. COVID-19 should be considered as a risk factor for ODS.

Objective:To explore the efficacy of subcutaneous injection of granulocyte-macrophage colony-stimulating factor (GM-CSF) in preventing invasive fungal disease (IFD) in patients with multiple myeloma (MM).Methods:The clinical data of 222 patients who were admitted to the Second Hospital of Harbin Medical University from January 2015 to June 2021 were retrospectively analyzed. The patients was given GM-CSF (3-5 μg·kg -1·d -1, GM-CSF group) or granulocyte colony-stimulating factor (G-CSF, 2-5 μg·kg -1·d -1, G-CSF group) when neutrophils (ANC) ≤1.5×10 9/L after induction chemotherapy. Patients were discontinued when white blood cell count (WBC) ≥10.0×10 9/L. The incidence of IFD (including confirmed, clinical and proposed diagnosis) and breakthrough invasive fungal infections was compared between the two groups. Results:The incidence of IFD was 8.1% (18/222) in all patients. The incidence of IFD was 3.5% (3/85) and 10.9% (15/137) in the GM-CSF and G-CSF groups, respectively, and the difference between the two groups was statistically significant ( χ2 = 3.88, P = 0.049). In 9 patients of GM-CSF group receiving fungal infection prophylaxis and in 15 patients of G-CSF group receiving fungal infection prophylaxis, the incidence of breakthrough invasive fungal infections was 0 and 7 cases, respectively, and the difference between the two groups was statistically significant ( P = 0.022). Conclusions:GM-CSF application in MM patients can reduce the incidence of IFD and breakthrough invasive fungal infections.