ObjectiveTo investigate the mechanisms by which Renshentang treats atherosclerosis （AS） in mice， focusing on the regulation of endothelial inflammatory responses mediated by transient receptor potential vanilloid subtype 1 （TRPV1）. MethodsAn AS model was established in apolipoprotein E knockout （ApoE^-/-） mice fed a high-fat diet. The mice were randomly divided into a simvastatin group （0.02 g·kg^-1·d^-1） and low-， medium-， and high-dose Renshentang groups （1.77， 3.54， 7.08 g·kg^-1·d^-1）， with 12 mice in each group. ApoE^-/- mice were fed a high-fat diet and treated simultaneously. C57BL/6J mice fed a normal diet served as the normal group （n=9）. After continuous administration for 12 weeks， mice were anesthetized and the aortas were collected. Oil Red O staining was used to observe lipid plaque formation in the aorta. Hematoxylin-eosin （HE） staining was performed to examine pathological changes in the aortic root. Immunohistochemistry was used to analyze the levels of pro-inflammatory factors tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）， as well as the expression of TRPV1， phosphorylated phosphoinositide 3-kinase （p-PI3K）， and phosphorylated protein kinase B （p-Akt） in the aortic root. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect endothelial nitric oxide synthase （eNOS） mRNA expression in the aorta， and Western blot was used to detect TRPV1 protein expression. ResultsCompared with the normal group， the model group showed a significant increase in aortic plaque formation （P<0.01） and significantly elevated levels of TNF-α and IL-1β in the aortic root （P<0.01）. The expression levels of TRPV1， p-PI3K， and p-Akt were decreased （P<0.05， P<0.01）， and eNOS mRNA expression was reduced （P<0.05， P<0.01）. Compared with the model group， all Renshentang groups significantly reduced aortic plaque formation （P<0.01）， significantly decreased TNF-α and IL-1β levels （P<0.01）， and markedly increased the expression levels of TRPV1， p-PI3K， p-Akt， and eNOS mRNA （P<0.05， P<0.01）. ConclusionRenshentang may inhibit endothelial inflammation and suppress the formation of AS by increasing TRPV1 protein expression and up-regulating the PI3K/Akt/eNOS signaling pathway， which may be one of the molecular mechanisms underlying its therapeutic effect against AS.

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To evaluate the application value of nucleic acid mass spectrometry in detecting ERG11 gene mutations associated with azole resistance in Candida tropicalis(C.tropicalis),thereby providing a scientific basis for the rational clinical use of azole antifungal agents.Methods Clinical isolates of C.tropicalis were obtained from the Affiliated Hospital of Xuzhou Medical University between July 2023 and November 2024.For each isolate,specific ERG11 mutations(A395T and C461T)were analyzed using Sanger sequencing and nucleic acid mass spectrometry.Sanger sequencing was used as the reference standard to evaluate the performance of mass spectrometry in mutation detection.Results The established nucleic acid mass spectrometry method effectively identified four genotypes of ERG11(A395T and C461T),with distinct spectral peaks for each mutation and no cross-interference observed.Among 88 clinical isolates,the sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NPV)for the A395T mutation were 86.7%,100%,100%,and 97.3%,respectively.For the C461T mutation,the corresponding values were 81.3%,100%,100%,and 96.0%,respectively.Kappa statistics demonstrated a high level of agreement between mass spectrometry and sequencing results.Conclusions Nucleic acid mass spectrometry exhibits high sensitivity and specificity in the detection of ERG11 mutations,enabling rapid,accurate,and adaptable high-throughput analysis.This makes it a highly effective method for identifying mutations associated with fungal resistance.

Objective:To investigate the association between different types of lung nodules and the risk of lung cancer in a population at high risk of lung cancer and to provide an epidemiologic basis for the comprehensive management of lung nodules.Methods:Using the free lung cancer screening program of low-dose CT (LDCT) in Wenling, Zhejiang Province, we collected baseline and imaging information of high-risk groups for lung cancer who underwent LDCT screening from April 2019 to October 2021 and patients with previous history of lung cancer, tuberculosis, pneumoconiosis, and silicosis were excluded. A total of 28 539 study subjects were included in the analysis, and the follow-up ended on 31 December 2023. Based on the characteristics of the detected pulmonary nodules, the study subjects were classified with no nodules, with solid nodules, with pure ground glass nodules, and with part solid nodules groups. The association between different characteristics of lung nodules and the risk of lung cancer development was analyzed using the Cox proportional hazard regression model with a new diagnosis of lung cancer during the follow-up period as the outcome.Results:The overall detection rate of lung nodules with a mean diameter of ≥3 mm was 76.5%, of which 53.7%, 18.2%, and 4.6% were detected in the solid nodule, pure ground glass nodule, and partially solid nodule groups, respectively. There were statistically significant differences between the different nodule groups in terms of age, gender, BMI, history of toxic exposure education level, smoking status, history of lung disease, and family history of lung cancer (all P<0.05). The median follow-up time of the study population was 3.4 years, and 485 new lung cancer cases were diagnosed during the follow-up period. After adjusting for covariates, the results of multifactorial Cox proportional hazard regression model analysis showed that the risk of lung cancer was higher in pure ground glass nodules and part solid nodules compared with solid nodules, with HR values (95% CI) of 1.89 (1.52-2.35) and 6.49 (5.18-8.14), respectively. The results of subgroup analysis showed that patients in the group of part solid nodules had the highest risk of lung cancer in all strata of the population, followed by patients with pure ground glass nodules. Patients in the solid nodule group who were older or had previous lung disease had a higher risk of lung cancer, and the risk of lung cancer in the part solid nodule group differed between genders. Conclusions:The proportion of lung nodules detected is high in the high-risk group of lung cancer, and among them, patients with pure ground glass and part solid nodules have a higher risk of developing lung cancer. Attention should be paid to the annual follow-up management for patients with solid nodules who are older or who have had lung diseases, as well as for female patients with part solid nodules.

Objective:To investigate the effectiveness of the crisis management theory of reduction, readiness, response and recovery (4R) in the prevention of postoperative complications in patients with lower extremity varices.Methods:Convenience sampling was used to select 172 patients who underwent surgical treatment for lower extremity varices in the Hefei First People's Hospital from October 2022 to November 2023 as study subjects. Patients admitted from October 2022 to June 2023 were recruited in control group ( n=88) with routine nursing. Patients admitted from July to November 2023 were included in observation group ( n=84) , and nursing interventions based on the 4R crisis management theory were implemented on the basis of control group. Postoperative ulcer surface healing time, time for calf numbness to subside, pain scores and postoperative complications were compared between the two groups. Results:The time for disappearance of ulcer surface and the time for calf numbness to subside of the patients in observation group were shorter than those in control group, and the differences were statistically significant ( P<0.05) . Before the intervention, the pain score was (3.58±0.61) in observation group and (3.72±0.57) in control group, and the difference was not statistically significant ( P>0.05) . After the intervention, the pain score was (2.33±0.55) in observation group and (2.50±0.50) in control group, and the difference was statistically significant ( P<0.05) . The incidence of postoperative complications was 4.76% (4/84) in observation group and 19.32% (17/88) in control group, and the difference was statistically significant ( P<0.05) . Conclusions:Nursing interventions based on the 4R crisis management theory can effectively alleviate the pain of patients undergoing lower extremity varicose vein surgery, shorten the time of ulcer healing and calf numbness, and reduce the incidence of postoperative complications.

Objective To develop and validate a deep learning-based segmentation model for low-dose cervical spine X-ray,aiming to address the insufficient segmentation accuracy in low-dose protocols while balancing radiation protection and diagnostic accuracy.Methods A total of 1 363 patients cervical spine X-ray images data were collected.A dose-attenuation mathematical simulation sys-tem was constructed to generate 14 122 dynamic low-dose cervical spine images incorporating quantum noise,contrast degradation,and blur artifacts.A neural network model was developed for automated segmentation of low-dose cervical spine X-ray using this dataset.Results Within the dose range of 50%to 7.5%,the average reults of automatic segmentation by the neural network model and manual segmentation for each group were as follows:50%dose group,intersection over union(IoU)=0.98 vs 0.93(P=0.707)and Dice coefficient(Dice)=0.99 vs 0.96(P=0.749);10%dose group,IoU=0.97 vs 0.87(P=0.201)and Dice=0.99 vs 0.93(P=0.219);7.5%dose group,IoU=0.97 vs 0.67(P<0.01)and Dice=0.98 vs 0.80(P<0.01).Conclusion The developed deep learning model achieved robust cervical spine segmentation(IoU>0.96,Dice>0.98)below diagnostic dose thresholds[peak signal-to-noise ratio(PSNR)<38 dB,structural similarity index(SSIM)<0.65].Under ultra-low-dose conditions(PSNR=27.710 dB,SSIM=0.274),it demonstrated a 44.78%IoU improvement and 22.5%Dice improvement over manual segmentation.This model enables minimal radia-tion exposure while preserving diagnostic performance,confirming its theoretical feasibility for low-dose X-ray image analysis and clinical research potential.

Objective:To investigate the current status of clinical leadership among Interventional Operating Room nurses in Shandong Province and to analyze its influencing factors.Methods:In December 2024, 220 Interventional Operating Room nurses from 46 ClassⅢ Grade A general hospitals in Shandong Province were selected for a cross-sectional survey using convenience sampling. General Information Questionnaire, Clinical Leadership Survey, Chinese version of Wong and Law Emotional Intelligence Scale (WLEIS-C) , and Jefferson Scale of Empathy-Health Professionals (JSE-HP) were used as survey instruments. Multiple linear regression was used to analyze the factors influencing clinical leadership among Interventional Operating Room nurses. Pearson correlation analysis was used to explore the relationship between emotional intelligence, empathy, and clinical leadership.Results:A total of 220 questionnaires were distributed and 204 valid questionnaires were recovered, with a valid recovery rate of 92.73% (204/220) . The clinical leadership scores of the 204 Interventional Operating Room nurses were (66.35±8.74) , and the dimensions scored, in descending order, as encouraging the heart, enabling others to act, modeling the way, inspiring a shared vision, and challenging the process. The mean scores of WLEIS-C and JSE-HP items were (5.88±0.90) and (4.61±0.63) , respectively. Multiple linear regression analysis showed that the nature of employment and whether or not they participated in leadership training were influencing factors for clinical leadership among Interventional Operating Room nurses (partial regression coefficients of -2.831 and -2.999, respectively; P<0.05) . Emotional intelligence and empathy ability among Interventional Operating Room nurses were positively correlated with clinical leadership ( P<0.05) . Conclusions:Clinical leadership of nurses in the Interventional Operating Room of ClassⅢ Grade A general hospitals in Shandong Province is at a moderate to high level. Nurses who participate in leadership training, have staffing, have greater empathy, and have higher emotional intelligence have greater clinical leadership. It is recommended that nursing administrators add leadership-related courses to the training of nurses in the Interventional Operating Room, and take steps to improve nurses' emotional intelligence and empathy ability, thereby promoting clinical leadership among Interventional Operating Room nurses.

As the use of nursing information systems (NIS) in clinical nursing practice has proliferated, NIS education has received increased attention. This paper introduces the background and research form of NIS in nursing education at home and abroad, and summarizes the deficiencies in the application and puts forward suggestions, in order to provide references for the subsequent development of a high-quality system and the development of courses that fit the actual situation of nursing students in China.

Cancer stands as a significant global public health challenge,and cancer screening serves as a pivotal strategy for reducing its mortality.Presently,only a limited number of cancer types have appropriate screening methods available.Traditional single-cancer screen-ing approaches are fraught with limitations,including invasiveness,low accuracy,and poor patient compliance.Multi-cancer early detection(MCED)leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA,cell-free RNA,proteins,and metabolites in blood and other bodily fluids.This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage,showcasing immense potential for improving existing can-cer screening strategies.This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED,biomarker selection and detection technologies,the criteria for cancer type selection,research design and clinical utility evaluation,as well as implementation path-ways.The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED,thereby facilitating the continuous optimization of cancer screening strategies.