OBJECTIVE To investigate the effects and mechanisms of Lycium ruthenicum Murr. in improving sleep. METHODS Network pharmacology was employed to identify the active components of L. ruthenicum and their associated disease targets， followed by enrichment analysis. A caffeine‑induced zebrafish model of sleep deprivation was established ， and the zebrafish were treated with L. ruthenicum Murr. extract （LRME） at concentrations of 0.1， 0.2 and 0.4 mg/mL， respectively； 24 h later， behavioral changes of zebrafish and pathological alterations in brain neurons were subsequently observed. The levels of inflammatory factors [interleukin-6 （IL-6）， IL-1β， IL-10， tumor necrosis factor-α （TNF-α）]， oxidative stress markers [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， catalase （CAT）]， and neurotransmitters [5- hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， glutamic acid （Glu）， dopamine （DA）， and norepinephrine （NE）] were measured. The protein expression levels of protein kinase B1 （AKT1）， phosphorylated AKT1 （p-AKT1）， epidermal growth factor receptor （EGFR）， B-cell lymphoma 2 （Bcl-2）， sarcoma proto-oncogene，non-receptor tyrosine kinase （SRC）， and heat shock protein 90α family class A member 1 （HSP90AA1） in the zebrafish were also determined. RESULTS A total of 12 active components and 176 intersecting disease targets were identified through network pharmacology analysis. Among these， apigenin， naringenin and others were recognized as core active compounds， while AKT1， EGFR and others served as key targets； EGFR tyrosine kinase inhibitor resistance signaling pathway was identified as the critical pathway. The sleep improvement rates in zebrafish of LRME low-， medium-， and high-dose groups were 54.60%， 69.03% and 77.97%， 开发。E-mail：hjp_yft@163.com respectively， while the inhibition ratios of locomotor distance were 0.57， 0.83 and 0.95， respectively. Compared with the model group， the number of resting counts， resting time and resting distance were significantly increased/extended in LRME medium- and high-dose groups （P＜0.05）. Neuronal damage in the brain was alleviated. Additionally， the levels of IL-6， IL-1β， TNF-α， MDA， Glu， DA and NE， as well as the protein expression levels of AKT1， p-AKT1， EGFR， SRC and HSP90AA1， were markedly reduced （P＜0.05）， while the levels of IL-10， SOD， GSH-Px， CAT， 5-HT and GABA， as well as Bcl-2 protein expression， were significantly elevated （P＜0.05）. CONCLUSIONS L. ruthenicum Murr. demonstrates sleep-improving effects， and its specific mechanism may be related to the regulation of inflammatory responses， oxidative stress， neurotransmitter balance， and the EGFR tyrosine kinase inhibitor resistance signaling pathway.

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.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

ObjectiveTo observe the therapeutic effect of Erchentang on depression in obese mice and explore the therapeutic mechanism. MethodsC57BL/6J mice were randomized into the control， model， metformin （0.65 g·kg^-1）， and low-， medium-， and high-dose （3.35， 6.7， and 13.4 g·kg^-1， respectively） Erchentang groups. Gavage was initiated simultaneously with modeling and continued for 28 days. The therapeutic effects of Erchentang were evaluated through behavioral tests， liver and brain indices， liver function， lipid indicators， and histopathological changes in the liver and brain tissue. RNA-seq technology was used to conduct transcriptomic analysis of mouse liver tissue， and differentially expressed genes were screened and subjected to Kyoto Encyclopedia of Genes and Genomes （KEGG） analysis. Key genes were further verified by Western blot and Real-time polymerase chain reaction（Real-time PCR）. ResultsBehavioral tests， liver function， lipid indicators， and histopathological changes in the liver and brain tissue all demonstrated that Erchentang had therapeutic effects on depression in obese mice. KEGG pathway enrichment analysis of transcriptomic data indicated that Erchentang treated depression in obese mice mainly through the peroxisome proliferator-activated receptor （PPAR） signaling pathway. Western blot and Real-time PCR results showed that compared with the model group， the low-， medium-， and high-dose Erchentang groups exhibited downregulated expression of fatty acid-binding protein （FABP） 1 （P<0.01） and upregulated expression of acyl-CoA oxidase （ACOX） 1， PPARα， cholesterol 7α-hydroxylase （CYP7A） 1， and phosphoenolpyruvate carboxy kinase （PCK） 1 （P<0.05） in the liver tissue. ConclusionErchentang exerts therapeutic effects on obesity-associated depression by regulating the PPAR signaling pathway and the expression of related genes FABP1， ACOX1， PPARα， CYP7A1， and PCK1.

Objective To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

Objective:To evaluate the safety and efficacy of mild hypothermia arch-clamping technique in the surgical treatment of DeBakey Type Ⅰ aortic dissection.Methods:From December 2019 to November 2023, a total of 97 patients with DeBakey type Ⅰ aortic dissection who underwent arch-clamping technique in Beijing Anzhen Hospital were prospectively enrolled. The patients were divided into mild hypothermia group and moderate hypothermia group according to the lowest rectal temperature during the circulatory arrest period. The perioperative data of the two groups were compared, and complex adverse outcomes consisting of 30-day death, stroke, paraplegia and CRRT were used as the primary endpoint. Multivariate logistic regression was used to determine the predictors of clinical adverse outcomes. Survival analysis was evaluated by the Kaplan- Meier method. Results:The overall incidence of complex adverse outcomes was 20.6%, 13.6% in the mild hypothermia group and 22.7% in the moderate hypothermia group( P=0.535), and the incidence of stroke was 4.6% and 6.7%( P=1.000), respectively. The cardiopulmonary bypass time and aortic-clamping time in the mild hypothermia group were significantly shortened (147.5 min vs. 163.0 min, P=0.032; 89 min vs. 99 min, P=0.042). There was no significant difference in long-term survival and reintervention between the two groups(91.9% vs. 89.3%, P=0.87; 9.1% vs. 5.3%, P=0.13). Conclusion:Mild hypothermia arch-clamping technique is a safe and effective method for the treatment of DeBakey type Ⅰ aortic dissection, with satisfactory short-term and long-term efficacy.

Objective To perform a regression analysis on the predictive value of serum micro-RNAs(miR)for early neurological deterioration(END)in patients with branch atheromatous dis-ease(BAD).Methods A total of 134 BAD patients admitted in our department from February 2020 to February 2023 were enrolled,and according to the END status,they were divided into de-terioration group(28 cases)and non-deterioration group(106 cases).Serum levels of miR-130a,miR-210,miR-141-3p and miR-29a-3p were measured at admission.NIHSS score was used to eval-uate the END status at admission and at 7 d after admission.Binary logistic regression analysis was adopted to construct a model of above four miRs in predicting END in BAD patients.ROC curve was plotted to assess the predictive value of the four miRs alone or combined together for END.Results The serum levels of miR-130a and miR-210 were significantly higher,while those of miR-141-3p and miR-29a-3p were obviously lower in the deterioration group than the non-deterioration group(P＜0.01).Logistic regression analysis indicated that serum miR-130a,miR-210,miR-141-3p and miR-29a-3p were independent predictors of END in BAD patients(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of the four miRs combined together in predicting END in BAD patients was 0.977(95％CI:0.936-0.995),with a sensitivity of 96.43％and a specificity of 90.57％,and the combined detection exhibited better predictive effi-ciency than each indicator alone(P＜0.01).Conclusion Serum miR-130a,miR-210,miR-141-3p and miR-29a-3p have certain value in predicting END in BAD patients,and their combined detec-tion can enhance its predictive efficiency.

Objective To explore the application value of intravoxel incoherent motion(IVIM)imaging parameters in the differential diagnosis of benign and malignant breast nodules and their correlation with the expression of Ki-67 receptor in breast cancer.Methods The data of 41 female patients who completed 3.0 T breast magnetic resonance imaging(MRI)with complete surgical pathology results in the Second Hospital of Jiaxing City from October 2022 to January 2025 were analysed and evaluated.Conventional images and diffusion-weighted images with 11 b values were collected.The IVIM imaging parameters of real diffusion coefficient(D),perfusion related diffusion coefficient(D*)and perfusion fraction(f)were measured and calculated in the region of interest of each lesion.The receiver operating characteristic curve were plotted to quantify the differential diagnostic efficacy of each parameter of IVIM imaging in benign and malignant breast nodules.The differences of parameters between benign and malignant breast nodules and between the groups with different expression levels of Ki-67 receptor in breast cancer were analysed,and the correlation between each parameter and the expression level of Ki-67 in breast cancer was counted.Results The D value of benign breast nodules group(benign groups)was significantly higher than that of malignant breast nodules group(malignant groups),and the D*value was significantly lower than that of malignant group,and the differences between benign group and malignant group were statistically significant(t=-4.773,t=2.063,P＜0.05);Thefvalue of benign group was slightly lower than that of malignant group,and the differences between two groups were not statistically significant(t=0.035,P＞0.05).Among the parameters of IVIM imaging,D value had the best differential diagnostic efficacy for benign and malignant breast nodules,with area under the curve(AUC)of 0.870(95％CI:0.755-0.985)and a specificity of 75.0％;D*value had the second best differential diagnostic efficacy after D value,with an AUC of 0.789(95％CI:0.658-0.920),but it had the highest sensitivity of 88.2％;And the differential diagnosis efficiency off value was the worst,much less than D and D*values.The D value in the high Ki-67 expression group of breast cancer was lower than that in the low expression group,while the D* and f values in the high expression group were higher than that in the low expression group,and the differences of each imaging parameter of IVIM were not statistically significant between two groups(t=-2.617,t=2.169,t=0.647,P＞0.05).There was a significant negative correlation between the expression of the Ki-67 receptor and the D value(r=-0.615,P＜0.05),and no significant correlation was seen with either D *or f value(r=0.223,r-0.031,P＞0.05).Conclusion The D and D*values of IVIM imaging parameters have great clinical value in the differential diagnosis of benign and malignant breast nodules.

Objectives:To explore the relationship between plasma big endothelin-1(Big ET-1)level and left ventricular(LV)remodeling assessed by cardiac magnetic resonance(CMR)in patients with hypertrophic obstructive cardiomyopathy(HOCM).Methods:A total of 180 consecutive HOCM patients were enrolled from November 2013 to July 2015 in Fuwai Hospital,Chinese Academy of Medical Sciences.The baseline characteristics of the patients were collected and the plasma Big ET-1 levels were measured.According to LV remodeling index(LVRI),the patients were divided into severe remodeling group(LVRI>1.3 g/ml,n=119)and mild remodeling group(LVRI≤1.3 g/ml,n=61).The Pearson correlation analysis and multivariate logistic regression analysis were conducted to assess the correlations between plasma Big ET-1 level and indicators of LV remodeling.Results:Compared to the mild remodeling group,the plasma Big ET-1 level([0.84±0.30]pmol/L vs.[0.41±0.19]pmol/L),LVRI([1.7±0.3]g/ml vs.[1.1±0.1]g/ml),the extent of late gadolinium enhancement(LGE)([16.8±8.9]g vs.[7.0±6.6]g)were significantly higher in the severe remodeling group(all P<0.001).Pearson correlation analysis revealed that in patients with HOCM,plasma Big ET-1 level were positively correlated with left atrial anteroposterior diameter,interventricular septal thickness(IVS),LV mass(LVM),LVRI,LGE and LV outflow tract(LVOT)gradient and negatively correlated with LV ejection fraction(all P<0.05).Multivariate logistic regression analysis showed that LVM(OR=1.037,95% CI:1.019-1.056,P<0.001)and plasm Big ET-1 level(OR=11.461,95% CI:2.264-58.014,P=0.003)were the independent determinants for severe LV remodeling in HOCM patients.Conclusions:Among patients with HOCM,the plasma Big ET-1 level are markedly higher in those with severe LV remodeling and are positively associated with left atrial anteroposterior diameter,IVS,LVRI,LVM,LVOT gradient and LGE.Elevated Big ET-1 level and LVM are independent determinants of severe LV remodeling in HOCM patients.

Objective:To investigate the correlation between leucine-rich α2 glycoprotein (LRG) and endoscopic activity in patients with Crohn′s disease (CD), based on the assessment of inflammation in small intestinal lesion by double-balloon enteroscope (DBE).Methods:From 15 August 2022 to 22 August 2023, the clinical data of 139 patients with small bowel CD diagnosed by DBE at the First Affiliated Hospital of Anhui Medical University were prospectively collected, which included fecal calprotectin (FC), C-reactive protein (CRP), white blood cell count, hemoglobin, albumin, Crohn′s disease activity index (CDAI), and simple endoscopic score for Crohn′s disease (SES-CD). According to the SES-CD, endoscopic activity was classified as mucosal healing (0), endoscopic remission (0 to 2), mild activity (3 to 6), moderate activity (7 to 15), and severe activity (≥16). LRG levels were detected in all patients. Spearman rank correlation was used to analyze the correlation between LRG, clinical biochemical parameters and endoscopic scores. Receiver operating characteristic curve (ROC) was performed to determine the optimal cut-off value of LRG for evaluating endoscopic mucosal healing. Mann-Whitney U test, Kruskal-Wallis H test, and Bonferroni corrected test were used for statistical analysis. Results:Among 139 patients with small bowel CD, the LRG level was 17.3 (13.0, 25.2) mg/L, and SES-CD was 5 (1, 9); 32 patients achieved mucosal healing, 50 patients achieved endoscopic remission; 39 patients had mild activity, 40 patients had moderate activity, and 10 patients had severe activity. The SES-CD was negatively correlated with both hemoglobin and albumin ( r=-0.177 (95% confidence interval, 95% CI: -0.334 to -0.011), -0.293 (95% CI: -0.438 to -0.133)), with statistical significance ( P=0.037, <0.001). The SES-CD was positively correlated with CRP, CDAI, LRG and FC ( r=0.344 (95% CI: 0.188 to 0.482), 0.429 (95% CI: 0.282 to 0.556), 0.525 (95% CI: 0.393 to 0.636), 0.661 (95% CI: 0.556 to 0.745)), with statistical significant (all P<0.001). For the 64 small bowel CD patients with CRP in the normal reference value, SES-CD was positively correlated with CDAI, LRG and FC ( r=0.296 (95% CI: 0.054 to 0.505), 0.364 (95% CI: 0.129 to 0.559), 0.547 (95% CI: 0.348 to 0.699)), with statistical significance ( P=0.017, =0.003, <0.001). The LRG level of patients with endoscopic mucosal healing was significantly lower than that of patients with endoscopic remission (11.5 (10.1, 17.2) mg/L vs. 17.3 (13.4, 23.5) mg/L), with statistical significance ( Z=-3.25, P<0.001). ROC analysis showed that the area under the curve (AUC) of LRG in predicting endoscopic mucosal healing was 0.81 (95% CI: 0.73 to 0.89), with an optimal cut-off value of 15.27 mg/L. The sensitivity, specificity, positive predictive value and negative predictive value were 0.757, 0.718, 0.900 and 0.469, respectively. The accuracy of the combination of LRG and FC (AUC was 0.88, 95% CI: 0.82 to 0.94) in predicting endoscopic mucosal healing was higher than that of LRG alone (AUC was 0.81, 95% CI: 0.73 to 0.89), and the difference was statistically significant ( P=0.011). Conclusion:Based on the results of DBE, LRG may be a reliable biomarker for predicting endoscopic remission and mucosal healing in patients with small bowel CD.