Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Objective To explore the effects of electromagnetic field(EMF)on thechange of Ca2+ in osteolbast from the qualitative and quantitative perspectives,and try to identify the role of Ca2+in EMF regulation on osteoblast proliferation and differentiation.Methods A platform was established for generating sine EMF with a frequency of 38.7 Hz and a strength of 1.5 mT.The MC3T3-E1 osteoblasts were randomly divided into control group and experimental group(EMF intervention for 8 h per day).CCK8 was used to detect osteoblast proliferation,ALP staining to detect osteoblast differentiation,and Ca2+fluorescence probes and flow cytometer to detect the Ca2+concentration in osteoblasts.Results CCK8 result showed that EMF intervention for 48,72,96 and 120 h could significantly promote osteoblast proliferation.After 14 days of EMF intervention,the positive expression of ALP was significantly higher in EMF group than in control group.Ca2+fluorescent staining and flow cytometry results revealed that EMF intervention could increase the Ca2+in osteoblasts.Conclusion The EMF-induced upregulation of Ca2+ signal in osteoblasts may be closely related to the promotions of osteoblast proliferation and differentiation by EMF,but which Ca2+-related biosignaling pathways are involved in the EMF promoting osteoblast proliferation and differentiation remains to be further investigated.

Objective:To design a fall detection system for elderly patients to solve the problem of elderly patients failing to detect accidental falls in time and to improve the efficiency of medical care.Methods:Based on real-time stream transmission protocol(RTSP),combined with YOLOv5 and Kalman algorithms,a fall detection system for elderly patients was designed by using Vue and Flask technologies.A visual background system management was established,and a unified management platform was provided for medical staff through comprehensive processing of multiple video streams to realize the autonomous detection and alarm of human fall behavior.30 healthy volunteers who underwent fall testing at Xijing Hospital of Air Force Medical University in 2020 to 2022 were selected and divided into normal walking group,squatting group and falling group according to the simulated behavioural categories,with 10 in each group.The fall detection performance was evaluated using two evaluation indicators:detection accuracy and detection speed to verify and determine whether the fall detection system for elderly patients can meet the requirements of timely and accurate fall detection and alarm.Results:The overall fall detection rate of the normal walking group,the squatting group and the falling group can reach 29 frames per second,and the accuracy rate can reach 95.24%.and the system can respond to the fall alarm in time.Conclusion:The fall detection system for elderly patients can assist medical staff to promptly detect and deal with the occurrence of falls,improve the efficiency of fall detection for elderly patients,and meet the real-time detection and alarm of fall behavior for elderly patients.

Objective To investigate the effect of 810 nm low-level laser on neuronal axonal regeneration of mice with spinal cord injury and its related mechanism.Methods In vivo experiment:20 Balb/c mice were randomly divided into the spinal cord injury group(SCI group)and the 810 nm low-level laser irradiation group(low-level laser group)after spinal cord injury according to the random number table method,with each group containing ten mice.A mice SCI model was established through clamp injury and the low-level laser group continuously irradiated the damaged area with weak 810 nm low-level laser with selected parameters(continuous wave with wave length 810 nm,power density 2 mW/cm2,spot are 4.5 cm2,irradiation time 50 minutes,energy 6000J/cm2).Then immunofluorescence staining was used to observe the M1 macrophage marker-inducible nitric oxide synthase(iNOS),the M2 macrophage marker arginase 1(Arg-1)and the universal marker F4/80 of macrophages after 14 days.Furthermore,in the in vitro experiment,standardized low-level laser-macrophage irradiation model was established.Another 20 Balb/c mice were used to obtain primary bone marrow-derived macrophages which were induced into M1 macrophages using lipopolysaccharide(LPS)and interferon-gamma(INF-γ).The M1 macrophages were randomly divided into the M1 macrophage group(M1 group)and the low-level laser therapy group(M1 + low-level laser group)equally according to the random number table method.The M1 group was not treated,and the M1 + low-level laser group was treated with low-level laser of selected parameters.RT-qPCR and ELISA were used to detect the expression of interleukin-1 receptor antagonist(IL-1RA)and interleukin-10(IL-10)in M1 macrophages 24 hours after irradiation.Western blot was used to analyze the expression of iNOS,Arg-1,differentiation antigen cluster 206(CD206),protein kinase B(AKT),phosphorylated protein kinase B(p-AKT),cyclic adenosine response element binding protein(CREB)and phosphorylated cyclic adenosine response element binding protein(p-CREB)in M1 macrophages 48 hours after irradiation.Dorsal root gangtion neurons(DRG)were cultured in two groups of macrophage conditioned medium,and the length of DRG axon growth was measured 48 h later to evaluate the effect of low-level laser on neuronal axon growth.Results In the in vivo experiment,compared with mice with spinal cord injury alone,the fluorescence intensity of F4/80+ iNOS+ in the spinal cord injury area decreased(1.00±0.08vs. 0.06±0.04)(P＜ 0.05)and the fluorescence intensity of F4/80 + Arg-1 + increased after low-level laser(1.00±0.07vs.2.15±0.12)(P＜0.01).In the in vitro experiment,compared with the M1 group,the expression of the M1 macrophage marker iNOS in the M1 + low-level laser group decreased(1.00±0.11 vs.0.08±0.01)(P＜ 0.01);the M2 macrophage marker Arg-1(1.00±0.14vs.2.44±0.16)(P＜0.01),and the expression of CD206(1.00±0.12 vs.1.83±0.05)(P＜0.01)increased.In addition,IL-1RA expression was increased in the M1 + low-level laser group compared with the M1 group(RT-qPCR:1.00±0.00vs.2.27±0.22)(P＜0.01)(ELISA:1435.58±100.48vs.2006.12±123.91(P＜0.05);IL-10 expression was also increased in the M1 +low-level laser group compared with the M1 group(RT-qPCR:1.00±0.00 vs. 3.45±0,56)(P＜0.05)(ELISA:137.13±4.20 vs.188.29±8.49)(P＜ 0,01);compared with the M1 group,the macrophage polarization pathway protein in the M1 + low-level laser group increased,AKT(1.07±0.12vs.1.74±0.04)(P＜0.01),p-AKT(1.00±0.12 vs.1.64±0.15)(P＜0.05),p-CREB(1.00±0.10vs.2.12±0.18)(P＜0.01).Compared with the M1 group,the conditioned medium of the M1 + low-level laser group significantly promoted DRG axon growth(567.66±63.59 vs.1068.95±130.14)(P＜ 0,05).Conclusions The 810 nm low-level laser irradiation can promote neuronal axon regeneration of mice with spinal cord injury,which may be related to the regulation of macrophage polarization phenotype by low-level laser through AKT/CREB pathway.