ObjectiveThe development trend and knowledge structure of the research on human use experience （HUE） of traditional Chinese medicine （TCM） were systematically reviewed， and the core challenges and future directions were identified. This study aims to provide reference for the construction of a scientific and feasible research and development framework and evidence transformation system. MethodsLiterature related to "human use experience" published from January 1， 2019 to July 31， 2025 was retrieved from the China National Knowledge Infrastructure （CNKI）， Wanfang， China Science and Technology Journal Database （VIP）， and PubMed databases. Bibliometric visualization was conducted using Excel， VOSviewer， and CiteSpace， followed by in-depth reading and thematic summarization of core literature. ResultsA total of 181 papers were included for bibliometric analysis， with 45 articles used for in-depth thematic mining. The analysis showed that the number of publications on HUE research has increased in a stepwise manner over the past five years. Yang Zhongqi （24 times） was the core of the author network， the journal with the highest number of publications was China Journal of Chinese Materia Medica， the institutions publishing the most articles were mainly research institutions， regulatory agencies， hospitals， and universities， high-frequency keywords included "new TCM drugs"， "real-world studies"， and "clinical comprehensive evaluation"， keyword clustering analysis formed three major clusters： Policy orientation， application fields， and methodological approaches. Thematic analysis reveals that HUE-based evaluation should be integrated throughout the research and development process， encompassing three dimensions： TCM theory， clinical value， and pharmaceutical fundamentals， with toxic herbs and compatibility contraindications being key foci. Data collection primarily relies on empirical data， while real-world data constitute the primary source for clinical research， with efficacy and safety as the shared core. Data management emphasizes quality control and statistical analysis； however， the management of bias and confounding remains a critical bottleneck in evidence transformation. In practice， HUE-based approaches have successfully supported the registration and evaluation of multiple categories of new TCM drugs. ConclusionThe research on HUE of TCM has formed a policy-driven pattern characterized by， rapid development and close link with regulatory practice. A technical framework covering the whole chain of research and development has been constructed with clinical value as the core， which provides methodological basis and strategy reference for the scientific transformation of HUE of TCM from "experience" to "evidence".

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.

AIM: To investigate the effect of interleukin-8(IL-8)on the regulation of monocyte chemotactic protein-1(MCP-1)secreted by lens epithelial cells(LEC)during cell migration in the development of posterior capsule opacification(PCO).METHODS: A rat lens capsule model was established and cultured in medium supplemented with 10% fetal bovine serum. Upon migration of LEC to 30%-50% of the posterior capsule, serum was removed. The capsule was subsequently divided into two groups: a control group and an IL-8(15 ng/mL)treatment group. LEC migration was captured at multiple time points. The secretion and mRNA expression of MCP-1 were quantified using ELISA and RT-qPCR, respectively. Immunofluorescence was used to assess MCP-1 expression in the different experimental groups. SRA01/04 cells were divided into three groups: control, IL-8(15 ng/mL), and IL-8(15 ng/mL)+200 μmol/L Bindarit(BND)groups, with migration measured by the Transwell assay. Additionally, SRA01/04 cells were divided into negative control(NC), NC+15 ng/mL IL-8, and 15 ng/mL IL-8+p65 siRNA groups, and MCP-1 secretion and mRNA expression were further analyzed by ELISA and RT-qPCR.RESULTS:LEC migration in the rat lens capsule cultured in vitro showed that the cells migration of the 15 ng/mL IL-8 group significantly increased at 48, 72 and 96 h(all P<0.05). ELISA results revealed that MCP-1 levels in SRA01/04 cells from the 15 ng/mL IL-8-treated group were markedly higher than those in the control group at both 12 and 24 h(all P<0.05). RT-qPCR analysis also demonstrated a significant increase in MCP-1 mRNA expression in the 15 ng/mL IL-8 group at both time points(all P<0.05). Immunofluorescence staining indicated greater MCP-1 expression in capsular epithelial cells of the 15 ng/mL IL-8 group at 24 h(P=0.007). Transwell assays further confirmed increased cell migration in the 15 ng/mL IL-8 group compared to the control group(P=0.001), while the migration reduced in the 15 ng/mL IL-8+200 μmol/L BND group compared to the 15 ng/mL IL-8 group(P=0.003). Moreover, ELISA and RT-qPCR results demonstrated a significant increase in MCP-1 secretion and mRNA expression in the NC+15 ng/mL IL-8 group at both 12 and 24 h compared to the NC group(all P<0.01). In contrast, MCP-1 secretion and mRNA expression were reduced in the 15 ng/mL IL-8+p65 siRNA group compared to the NC+15 ng/mL IL-8 group at both time points(all P<0.01).CONCLUSION: IL-8 promotes the migration of residual epithelial cells and regulates the secretion and expression of MCP-1 in LEC. The mechanism underlying IL-8's effects appears to be mediated through the activation of the NF-κB/p65 signaling pathway.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Objective:To explore the characteristics of the brain functional networks in children with spastic cerebral palsy (SCP) while at rest and to correlate them with motor functioning.Methods:Thirty-six children with SCP were enrolled as the SCP group, while thirty-four age-matched healthy children were recruited as the control group (the HC group). Functional near-infrared spectroscopy was used to detect changes in the concentration of oxygenated hemoglobin in the children′s cerebral cortex while at rest. The left prefrontal cortex (LPFC), right prefrontal cortex (RPFC), left motor cortex (LMC), and right motor cortex (RMC) were selected as regions of interest. Phase locking values (PLVs) were used to evaluate the strength of functional connectivity (FC) among these brain regions, and graph theory methods were applied to analyze the topological properties of the brain networks. Motor functioning was assessed using the gross motor function measure (GMFM).Results:The analyses of FC strength revealed that the SCP group had significantly weaker FC among all of the regions of interest while at rest compared to the HC group. Their PLVs for LPFC-RPFC, LPFC-RMC, RPFC-RMC and LMC-RMC connectivity were all significantly smaller. Graph theory analysis showed that the SCP group had significantly lower global efficiency (GE) and smaller clustering coefficients (CCs) and network density (D), while their characteristic path lengths were significantly longer. According to the correlation analysis, the PLVs for LMC-RMC connections in the SCP group were positively correlated with their scores on dimensions D and E of the GMFM ( r=0.496 and r=0.579 respectively). GE ( r=0.587 and r=0.642) and CC ( r=0.318 and r=0.759) showed similar significant positive correlations with GMFM dimensions D and E. Conclusions:At rest, the functional networks in the brains of children with SCP exhibit abnormalities closely associated with their motor dysfunction.

Peptide receptor radionuclide therapy (PRRT) with radiolabeled SSTR2 agonists is a treatment option that is highly effective in controlling metastatic and progressive neuroendocrine tumors (NETs). Previous studies have shown that an SSTR2 agonist combined with albumin binding moiety Evans blue (denoted as ¹⁷⁷Lu-EB-TATE) is characterized by a higher tumor uptake and residence time in preclinical models and in patients with metastatic NETs. This study aimed to enhance the in vivo stability, pharmacokinetics, and pharmacodynamics of ¹⁷⁷Lu-EB-TATE by replacing the maleimide-thiol group with a polyethylene glycol chain, resulting in a novel EB conjugated SSTR2-targeting radiopharmaceutical, ¹⁷⁷Lu-LNC1010, for PRRT. In preclinical studies, ¹⁷⁷Lu-LNC1010 exhibited good stability and SSTR2-binding affinity in AR42J tumor cells and enhanced uptake and prolonged retention in AR42J tumor xenografts. Thereafter, we presented the first-in-human dose escalation study of ¹⁷⁷Lu-LNC1010 in patients with advanced/metastatic NETs. ¹⁷⁷Lu-LNC1010 was well-tolerated by all patients, with minor adverse effects, and exhibited significant uptake and prolonged retention in tumor lesions, with higher tumor radiation doses than those of ¹⁷⁷Lu-EB-TATE. Preliminary PRRT efficacy results showed an 83% disease control rate and a 42% overall response rate after two ¹⁷⁷Lu-LNC1010 treatment cycles. These encouraging findings warrant further investigations through multicenter, prospective, and randomized controlled trials.

Objective:To explore the characteristics of the brain functional networks in children with spastic cerebral palsy (SCP) while at rest and to correlate them with motor functioning.Methods:Thirty-six children with SCP were enrolled as the SCP group, while thirty-four age-matched healthy children were recruited as the control group (the HC group). Functional near-infrared spectroscopy was used to detect changes in the concentration of oxygenated hemoglobin in the children′s cerebral cortex while at rest. The left prefrontal cortex (LPFC), right prefrontal cortex (RPFC), left motor cortex (LMC), and right motor cortex (RMC) were selected as regions of interest. Phase locking values (PLVs) were used to evaluate the strength of functional connectivity (FC) among these brain regions, and graph theory methods were applied to analyze the topological properties of the brain networks. Motor functioning was assessed using the gross motor function measure (GMFM).Results:The analyses of FC strength revealed that the SCP group had significantly weaker FC among all of the regions of interest while at rest compared to the HC group. Their PLVs for LPFC-RPFC, LPFC-RMC, RPFC-RMC and LMC-RMC connectivity were all significantly smaller. Graph theory analysis showed that the SCP group had significantly lower global efficiency (GE) and smaller clustering coefficients (CCs) and network density (D), while their characteristic path lengths were significantly longer. According to the correlation analysis, the PLVs for LMC-RMC connections in the SCP group were positively correlated with their scores on dimensions D and E of the GMFM ( r=0.496 and r=0.579 respectively). GE ( r=0.587 and r=0.642) and CC ( r=0.318 and r=0.759) showed similar significant positive correlations with GMFM dimensions D and E. Conclusions:At rest, the functional networks in the brains of children with SCP exhibit abnormalities closely associated with their motor dysfunction.

Objective:To mine the risk signals of adverse events of limaprost and provide reference for safe use of the drug.Methods:US FDA Public Data Open Project (OpenFDA) platform was searched, and the adverse event (AE) reports on limaprost from January 1, 2004 to October 1, 2023 were collected. AEs were classified and standardized according to the system organ class (SOC) and preferred terms (PT) of Medical Dictionary for Regulatory Activities version 25.1. The reporting odds ratio (ROR) method was used to mine the risk signal of limaprost. An AE with reports ≥3, ROR ≥2 and the lower limit of the 95% confidence interval ( CI)>1 was defined as a risk signal, which was analyzed descriptively. Results:A total of 1 618 AE reports with limaprost as the primary suspect drug were collected, 69 risk signals were identified, involving 17 SOCs. Of the 69 PTs, 10 were recorded in the drug instructions including hepatic function abnormal, red blood cell count decreased, drug eruption, blood pressure decreased, liver disorder, platelet count decreased, anaemia, haemoglobin decreased, pyrexia, and decreased appetite. The other 59 risk signals were not recorded in the drug instructions. The top 10 PTs in signal intensity were scleroderma, tumour haemorrhage, brain natriuretic peptide increased, inappropriate antidiuretic hormone secretion, colitis microscopic, large intestine perforation, cardiac failure acute, depressive symptom, cardiac failure chronic, pulmonary alveolar haemorrhage. The risk signals with more than 10 reports were inappropriate antidiuretic hormone secretion, interstitial lung disease, renal impairment, cardiac failure, pneumonia, fall, etc.Conclusion:In addition to the AEs recorded in the instructions, limaprost may also cause serious adverse reactions such as tumour haemorrhage, brain natriuretic peptide increased, and inappropriate antidiuretic hormone secretion, which are not recorded in the instructions and have a poor prognosis.

Significant research progress has been made in the development of antibody-drug conjugates (ADCs) for the treatment of ad-vanced breast cancer (ABC),ushering new hope for patients with this refractory disease. Through the conjugation of specific antibodies with highly potent cytotoxic drugs,tumor cells can be precisely targeted and killed while minimizing damage to normal tissues. ADCs such as trastuzumab-emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd),have shown excellent efficacy in the treatment of HER2-positive ABC,significantly prolonging patient survival. Furthermore,ADCs targeting triple-negative breast cancer (TNBC),such as sacituzumab govitecan (SG),have also achieved positive results in clinical trials. With the continuous research,development,and optimization of ADCs,as well as the exploration of combination treatment strategies,ADCs are expected to play an increasingly important role in the treatment of ABC in the future. This article provides an overview of the research progress of ADCs in the treatment of ABC,exploring their efficacy and safety. We aim to offer more treatment options and renewed hope for patients with ABC.

Objective Based on the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database,data mining was conducted on hematological adverse events related to antibody drug conjugates(ADC),providing reference for the safe use of ADC drugs in clinical practice.Methods The report data from the third quarter of 2011 to the fourth quarter of 2022 were retrieved from the FAERS database.After data cleaning such as deduplication and name standardization,extract hematological adverse events related to ADC,and use report odds ratio method and the information component method for signal detection.Results A total of 101 610 adverse event reports were extracted,with 8 ADC drugs as the primary suspected drugs,and 5 768 ADC related hematological adverse event reports.Among them,3 423 cases of agranulocytosis were involved,and the signal intensity from strong to weak were sacituzumab govitecan(SG),gemtuzumab ozogamicin(GO),brentuximab vedotin(BV),polatuzumab vedotin(PV),enfortumab vedotin(EV),trastuzumab deruxtecan(TD),inotuzumab ozogamicin(IO)and ado-trastuzumab emtansine(TDM-1).There were 2 327 cases hematopoietic cell deficiency,with signals ranging from strong to weak were IO,SG,BV,EV,PV,TD,TDM-1,and GO.Report with clinical outcome of death of ADC drug related hematological adverse events included BV 179(16.84％),TDM-1 102(13.01％),TD 88(27.08％),GO 12(16.90％),IO 8(11.59％),EV 54(24.32％),PV 22(27.16％),and SG 84(21.05％).Adverse event time analysis showed that the number of events on the first day of TD,IO,and SG medication accounts for ≥ 40％of the total number of cases.The median time of hematological adverse events in TD,GO,IO,EV,PV,and SG was within one treatment course(21 days).Conclusion Attention should be paid to the risk of ADC drug-related hematological adverse event,during the clinical medication process,blood cell count changes should be closely monitored,and any abnormalities should be promptly diagnosed and treated.