BACKGROUND:Facet joint osteoarthritis is acknowledged as a significant contributor to lower back pain in the geriatric population.The advent of an innovative spinal facet joint fusion device presents a therapeutic option for intervening during the initial stages of facet joint osteoarthritis,and significantly reduces the incidence of a series of complications caused by poor early conservative treatment and late surgical treatment.However,its effect on the biomechanics of the lumbar spine is unknown.OBJECTIVE:To investigate the biomechanical disparities between the novel lumbar zygapophyseal joint fusion device and traditional fusion devices.METHODS:A comprehensive three-dimensional finite element model of the L3-S1 lumbar spine was established and validated.Based on this intact model,three groups of surgical models were constructed:a bilateral pedicle screw fixation model,a bilateral novel facet joint fusion fixation model,and a bilateral facet screw fixation model,with the surgical segment designated as L4-5.Under a load of 500 N,a torque of 7.5 Nm was applied to all lumbar models to calculate the range of motion,displacement values,and intervertebral disc stress values at the L4-5 segment;stress values at the L3-4 and L5-S1 segments were also measured.RESULTS AND CONCLUSION:(1)Compared with the intact model,the range of motion at the L4-5 segment was reduced in all surgical models.(2)The novel device exhibited the smallest range of motion at the L4-5 segment under left and right rotational conditions;the greatest range of motion at the L4-5 segment under extension conditions;and a greater range of motion under other conditions than the bilateral pedicle screw fixation model.(3)The novel device demonstrated the smallest displacement values at the L4-5 segment under left and right rotational conditions;under other conditions,the displacement values at the L4-5 segment were greater than those in the bilateral pedicle screw fixation model.(4)In terms of stress distribution at the L4-5 segment,the novel device consistently exhibited the smallest values across all conditions.(5)For the L3-4 segment,the novel device showed the greatest stress values under extension and left and right rotational conditions,while under other conditions,the values were lower than those in the bilateral pedicle screw fixation model.(6)Compared with pedicle screw fixation,the novel device produced smaller stress values at the L5-S1 segment.(7)This study indicates that,compared with pedicle screw fixation,the novel device impacts the biomechanics of the lumbar spine by fusing the facet joints.It provides stability while preserving the range of motion at the surgical segment and reduces stress on the intervertebral discs of the surgical and adjacent segments,thereby potentially delaying disc degeneration.This suggests that the novel device can achieve biomechanical effects similar to those of pedicle screw fixation in theory.

Objective To develop a virtual reality rehabilitation support system and evaluate its effects on improving discharge readiness in caregivers of laryngectomy patients.Methods The system is equipped with a virtual reality-based home nursing skills guidance module for post-laryngectomy patients and an evidence-based artificial intelligence Q&A module.A convenience sampling method was adopted to select 64 caregivers of patients who underwent laryngectomy for the first time in the otorhinolaryngology head and neck surgery department of a tertiary A hospital in Beijing from July 2024 to January 2025 for a systematic study on application effects.To avoid cross-contamination between an experimental group and a control group,ward-based grouping was applied.A coin toss was used to assign Ward 1 to an experimental group and Ward 2 to a control group,with 32 cases in each group.The experimental group received discharge guidance based on the virtual reality technology,while the control group was provided with conventional verbal and written discharge instructions.The readiness for hospital discharge and the quality of discharge teaching scores of caregivers were compared between the 2 groups after the intervention.Results No sample detachment.After the intervention,the patient caregivers in the experimental group scored significantly higher than those in the control group in terms of discharge readiness and quality of discharge guidance,with a statistically significant difference(P＜0.001).Conclusion This study developed the virtual reality rehabilitation system for laryngeal cancer patients demonstrated good feasibility and effectiveness.The application of this system for discharge education significantly improved discharge readiness of caregivers and quality of discharge guidance for post-laryngectomy patients.It also helped with the optimization of health education models,enhancement of nursing resource utilization efficiency,and improvement of transitional care.

Objective To establish a human monocytic THP-1 macrophage-derived foam cell model and analyze the role of the α subunit of coatomer protein Ⅰ(α-COP)in apolipoprotein A-1(apoA-1)-mediated cholesterol efflux from foam cells.Methods THP-1 cells were induced to adhere using PMA(PMA group),followed by treatment with acetylated low-density lipoprotein(Ac-LDL)to generate macrophage-derived foam cells(Ac-LDL group).Subsequent incubation with apoA-1 formed the apoA-1 group.Cholesterol efflux rates mediated by apoA-1 and intracellular lipid accumulation were quantified through liquid scintillation counting and oil red O staining.The expression patterns of α-COP were systematically analyzed using quantitative real-time PCR(qPCR),Western blotting,and laser scanning confocal microscopy.THP-1 macrophage-derived foam cells mediated by apoA-1 were transduced with scrambled shRNA(Scr group)or α-COP-specific shRNA lentivirus(α-COP shRNA group)to assess the effects of α-COP knockdown on cholesterol efflux efficiency and total cellular cholesterol content.Subcellular localization of adipopoilin(ADFP)and cholesterol probe Fil-ipin Ⅲ staining patterns were visualized via laser scanning confocal microscopy.Bioinformatics analysis of α-COP expression profiles in carotid atherosclerotic plaques was performed using datasets from the GEO data-base.Results Compared with the Ac-LDL group,the cholesterol efflux rate in the apoA-1 group was signifi-cantly increased[(9.77±0.79)%vs.(2.74±0.37)%,P＜0.001].Oil red O staining demonstrated reduced lipid accumulation in foam cells of the apoA-1 group compared with the Ac-LDL group.The relative mRNA expression level of α-COP in the apoA-1 group was significantly higher than that in the Ac-LDL group(P＜0.001),with corresponding elevation in protein expression(P＜0.001).Fluorescence intensity analysis re-vealed increased mean fluorescence intensity of α-COP in the apoA-1 group compared with the Ac-LDL group.Following α-COP knockdown by shRNA,the apoA-1-mediated cholesterol efflux rate was significantly de-creased(P＜0.05)and total intracellular cholesterol levels were increased(P＜0.001)in the α-COP shRNA group compared with the Scr group.The α-COP shRNA group exhibited enhanced red fluorescence intensity of ADFP(P＜0.05)and increased blue fluorescence intensity of Filipin Ⅲ(P＜0.01)compared with the Scr group.Database analysis indicated that α-COP mRNA expression was lower in carotid atherosclerotic plaques than in normal arterial tissues,with reduced expression in advanced-stage plaques compared with early-stage plaques(P＜0.05).Conclusion α-COP participates in apoA-1-mediated cholesterol efflux from foam cells,and interference with α-COP expression results in reduced cholesterol efflux and increased intracellular lipid accumulation.

Objective To verify the accuracy of a Non-Contact Sleep Monitoring Mattress(NCSMM)based on body movement during sleep in assessing sleep quality of patients before neurosurgery in order to provide a more portable and efficient assessment tool for clinical staff.Methods A single-arm trial was conducted on 114 inpatients admitted in our department selected with convenience sampling.Sleep quality data of 1 night were collected through 5 sleep quality assessment tools,including NCSMM,polysomnography(PSG),Patient-Reported Outcome Measurement Information System(PROMIS)Sleep Disturbance scale,Richards-Campbell Sleep Scale(RCSQ),and a wearable device(smart watch for body movements and sleep quality monitoring).The sleep efficiency(≤85%)obtained by PSG was used as the diagnostic standard for sleep disorders.The area under the receiver operating characteristic curve(AUC),sensitivity,specificity,positive predictive value,negative predictive value,and Youden index were calculated for the other 4 tools to evaluate and compare their diagnostic effectiveness.Results The AUC value for NCSMM,PROMIS,RCSQ and smart watch was 0.788(95%CI:0.687～0.888,P<0.001),0.664(95%CI:0.543～0.784,P=0.02),0.723(95%CI:0.600～0.846,P=0.001)and 0.750(95%CI:0.654～0.846,P<0.001),respectively.The diagnostic accuracy rate was 0.774,0.559,0.742 and 0.602,with corresponding Youden index value of 0.488,0.321,0.456,and 0.459.NCSMM demonstrated the best AUC value,sensitivity and Youden index when compared with the other 3 tools.Conclusion NCSMM shows high accuracy in assessing sleep quality in pre-neurosurgery inpatients,and it is a viable portable and efficient assessment tool in clinical practice.

Objective:To explore and model risk factors in patients with major adverse cardiovascular events (MACEs) after acute type A aortic dissection (ATAAD), and to develop and validate a personalized machine learning model to assess risk factors and predict MACEs in these patients.Methods:Clinical data of patients who attended Beijing Anzhen Hospital and underwent surgical treatment for ATAAD from January 2018 to October 2022 were retrospectively analyzed. Using MACEs as the endpoint, 70% of these patients were randomly divided into the training set and the remaining 30% into the validation set. LASSO regression was applied to explore key clinical variables in the training set. The optimal predictive model was selected from nine machine learning algorithms based on area under the curve. And Shapley Additive explanations was used to elucidate the predictive model. Results:Of the 481 patients included in this study, 135 (35.6%) patients experienced an endpoint event. By combining the results of the training and validation sets, when assessing the validity of the single model with the highest predictive accuracy for the outcome, it was shown that the logistic model (0.774, 95% CI: 0.717-0.830) was the most effective in the combined effect and had a high model accuracy (0.743, 95% CI: 0.720-0.766). According to the results of the LASSO, the factors most associated with postoperative MACEs were history of cerebrovascular disease, coronary artery involvement, shock status on admission to the operating room, FDP, PLT, CPB, ascending aortic clamping, and age. Conclusion:In this study, nine machine learning models were developed to predict the occurrence of postoperative MACEs in patients with acute type A aortic dissection. The logistic model performed significantly better compared to other algorithms. Our study successfully predicted postoperative MACES and identified the factors most associated with MACEs.

Objective To develop a virtual reality rehabilitation support system and evaluate its effects on improving discharge readiness in caregivers of laryngectomy patients.Methods The system is equipped with a virtual reality-based home nursing skills guidance module for post-laryngectomy patients and an evidence-based artificial intelligence Q&A module.A convenience sampling method was adopted to select 64 caregivers of patients who underwent laryngectomy for the first time in the otorhinolaryngology head and neck surgery department of a tertiary A hospital in Beijing from July 2024 to January 2025 for a systematic study on application effects.To avoid cross-contamination between an experimental group and a control group,ward-based grouping was applied.A coin toss was used to assign Ward 1 to an experimental group and Ward 2 to a control group,with 32 cases in each group.The experimental group received discharge guidance based on the virtual reality technology,while the control group was provided with conventional verbal and written discharge instructions.The readiness for hospital discharge and the quality of discharge teaching scores of caregivers were compared between the 2 groups after the intervention.Results No sample detachment.After the intervention,the patient caregivers in the experimental group scored significantly higher than those in the control group in terms of discharge readiness and quality of discharge guidance,with a statistically significant difference(P＜0.001).Conclusion This study developed the virtual reality rehabilitation system for laryngeal cancer patients demonstrated good feasibility and effectiveness.The application of this system for discharge education significantly improved discharge readiness of caregivers and quality of discharge guidance for post-laryngectomy patients.It also helped with the optimization of health education models,enhancement of nursing resource utilization efficiency,and improvement of transitional care.

BACKGROUND:Facet joint osteoarthritis is acknowledged as a significant contributor to lower back pain in the geriatric population.The advent of an innovative spinal facet joint fusion device presents a therapeutic option for intervening during the initial stages of facet joint osteoarthritis,and significantly reduces the incidence of a series of complications caused by poor early conservative treatment and late surgical treatment.However,its effect on the biomechanics of the lumbar spine is unknown.OBJECTIVE:To investigate the biomechanical disparities between the novel lumbar zygapophyseal joint fusion device and traditional fusion devices.METHODS:A comprehensive three-dimensional finite element model of the L3-S1 lumbar spine was established and validated.Based on this intact model,three groups of surgical models were constructed:a bilateral pedicle screw fixation model,a bilateral novel facet joint fusion fixation model,and a bilateral facet screw fixation model,with the surgical segment designated as L4-5.Under a load of 500 N,a torque of 7.5 Nm was applied to all lumbar models to calculate the range of motion,displacement values,and intervertebral disc stress values at the L4-5 segment;stress values at the L3-4 and L5-S1 segments were also measured.RESULTS AND CONCLUSION:(1)Compared with the intact model,the range of motion at the L4-5 segment was reduced in all surgical models.(2)The novel device exhibited the smallest range of motion at the L4-5 segment under left and right rotational conditions;the greatest range of motion at the L4-5 segment under extension conditions;and a greater range of motion under other conditions than the bilateral pedicle screw fixation model.(3)The novel device demonstrated the smallest displacement values at the L4-5 segment under left and right rotational conditions;under other conditions,the displacement values at the L4-5 segment were greater than those in the bilateral pedicle screw fixation model.(4)In terms of stress distribution at the L4-5 segment,the novel device consistently exhibited the smallest values across all conditions.(5)For the L3-4 segment,the novel device showed the greatest stress values under extension and left and right rotational conditions,while under other conditions,the values were lower than those in the bilateral pedicle screw fixation model.(6)Compared with pedicle screw fixation,the novel device produced smaller stress values at the L5-S1 segment.(7)This study indicates that,compared with pedicle screw fixation,the novel device impacts the biomechanics of the lumbar spine by fusing the facet joints.It provides stability while preserving the range of motion at the surgical segment and reduces stress on the intervertebral discs of the surgical and adjacent segments,thereby potentially delaying disc degeneration.This suggests that the novel device can achieve biomechanical effects similar to those of pedicle screw fixation in theory.

Objective:To explore and model risk factors in patients with major adverse cardiovascular events (MACEs) after acute type A aortic dissection (ATAAD), and to develop and validate a personalized machine learning model to assess risk factors and predict MACEs in these patients.Methods:Clinical data of patients who attended Beijing Anzhen Hospital and underwent surgical treatment for ATAAD from January 2018 to October 2022 were retrospectively analyzed. Using MACEs as the endpoint, 70% of these patients were randomly divided into the training set and the remaining 30% into the validation set. LASSO regression was applied to explore key clinical variables in the training set. The optimal predictive model was selected from nine machine learning algorithms based on area under the curve. And Shapley Additive explanations was used to elucidate the predictive model. Results:Of the 481 patients included in this study, 135 (35.6%) patients experienced an endpoint event. By combining the results of the training and validation sets, when assessing the validity of the single model with the highest predictive accuracy for the outcome, it was shown that the logistic model (0.774, 95% CI: 0.717-0.830) was the most effective in the combined effect and had a high model accuracy (0.743, 95% CI: 0.720-0.766). According to the results of the LASSO, the factors most associated with postoperative MACEs were history of cerebrovascular disease, coronary artery involvement, shock status on admission to the operating room, FDP, PLT, CPB, ascending aortic clamping, and age. Conclusion:In this study, nine machine learning models were developed to predict the occurrence of postoperative MACEs in patients with acute type A aortic dissection. The logistic model performed significantly better compared to other algorithms. Our study successfully predicted postoperative MACES and identified the factors most associated with MACEs.

Purpose/Significance To sort out the literature in the field of traditional Chinese medicine(TCM)in China in the past decade,and to expound the hot topics and development trends in this field.Method/Process Literature in the field of TCM in Wanfang Data from 2013 to 2022 is searched.The abstracts are taken as the research objects,the topics are extracted by BERTopic model,and CiteSpace is used for visualization and analysis.Result/Conclusion 12 683 papers in Chinese are included,and the 5 topics are found:clinical trials and efficacy,research on pathogenesis and pharmacology,the development of the field of TCM,treatment of chronic dis-ease,drug analysis and literature research.The paper makes an in-depth analysis of the topic of the development of traditional Chinese medicine,which continues to grow in popularity,and puts forward that the deep integration of artificial intelligence(AI)and TCM is the future trend.

Purpose/Significance The paper discusses the construction of the current elderly health policy system by using policy text min-ing and quantitative evaluation,and provides references for future policy adjustment and optimization.Method/Process Policies on elderly health issued by the relative departments from 2019 to 2023 are analyzed.The ROST text data mining tool is used to extract high-frequency words and build semantic networks.Gephi is utilized to visualize social network relationships for text analysis.Quantitative analysis of these policies is conducted using the PMC index model.Results/Conclusion The high-frequency words such as"national","society","knowl-edge","resources",and"guarantee"are identified as key areas in elderly health policies,which are interconnected within the social network.The overall trend of the elderly health policy formulation is positive.It is suggested to improve the accuracy and adaptability of the policy,clari-fy the time node and core elements of the policy,and enhance the strategic analysis of the function and content of the policy.