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 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 explore the necessity of routine chest X-ray (CXR) examination after lung surgery based on patient symptom burden. Methods A retrospective study was conducted on the patients who underwent thoracoscopic lung resection at the Department of Thoracic Surgery of Guangdong Provincial People's Hospital from March 2020 to April 2023. Routine CXR findings obtained within 24 h post-operation, after chest tube removal, and at 1-month post-discharge, as well as subsequent clinical interventions triggered by these examinations, were collected and analyzed. The Perioperative Symptom Assessment Lung (PSA-Lung) inventory was used to quantify symptom burden including pain, dyspnea, and sleep disturbance. Results A total of 2 101 patients were collected, including 986 males and 1 115 females, with a median age of 56 years. The rate of clinical interventions triggered by routine CXR examinations was very low, being 1.0%, 0.5%, and 1.3% within 24 h post-operation, within 12 h after extubation, and at 1-month post-discharge, respectively. One month after discharge, patients in the intervention group exhibited significantly higher scores for dyspnea (3 points vs. 2 points, P=0.015), pain (2 points vs. 1 point, P=0.039), and sleep disturbance (3 points vs. 2 points, P=0.036) compared with the non-intervention group. Conclusion Very few routine postoperative CXR examinations change patients’ management, and patients who need extra-intervention tended to have more severe symptom burden after surgery.

Objective To analyze the current quality of treatment for hospitalized cancer patients in Bei-jing,identify major issues in treatment practices,and propose improvements.Methods Nine hospitals in Beijing were selected for examination.Expert on-site interviews and medical record sampling were conducted.The"Bei-jing Cancer Diagnosis and Treatment Quality Control Checklist"was used to assess the hardware,management,anti-cancer drug therapy,radiation therapy,and surgical treatment during cancer treatment at these hospitals from January to October 2023.The relevant problems were analyzed.Results Among the nine hospitals,two(22.2％)were equipped with laminar flow rooms,and three(33.3％)had intravenous drug preparation centers.In terms of institutional management,seven hospitals(77.8％)had standardized anti-cancer drug prescription authority management,eight(88.9％)had complete emergency plans,and five(55.6％)had oncology specialist pharmacists.Regarding anti-cancer drug therapy,the areas with higher completion rates included pathology diag-nosis support(97.6％),routine pre-treatment examinations(96.3％),adverse reaction evaluation(92.7％),discharge summaries(95.1％),and admission records(91.5％).However,the accuracy of tumor staging before treatment(70.7％)and the evaluation of therapeutic efficacy after drug treatment(76.9％)needed improvement.The oncology specialty significantly outperformed the non-oncology specialty in terms of the accuracy rate of TNM staging(86.0％vs.46.9％,P＜0.001),the completeness of informed consent forms(100％vs.68.8％,P＜0.001),the completeness of drug indication evaluation(96.0％vs.78.1％,P=0.025),the completeness of admission medical history records(98.0％vs.81.3％,P=0.008),the rationality of drug dosage(96.0％vs.75.0％,P=0.005),the rationality of drug infusion time(100％vs.62.5％,P＜0.001),and the rationality of the order of drug infusion(100％vs.87.5％,P=0.010).Although the quality of radiation therapy was high,the subsequent evaluation of therapeutic efficacy(39.3％)requires enhancement.In surgical treatment,the preoper-ative pathology diagnosis support rate(78.1％)and the accuracy of tumor staging(37.5％)were relatively low,indicating issues with incomplete preoperative evaluation and the absence of multidisciplinary discussions.Conclusions There remains significant room for improvement in the quality of cancer treatment in China.It is recommended to standardize tumor staging assessment processes,strengthen entry assessments for non-oncology departments,promote the implementation of multidisciplinary treatment models,and establish a multi-department collaborative management model.Continuous monitoring of cancer diagnosis and treatment quality indicators is es-sential to promote ongoing improvements in cancer treatment quality.

Cross-linking mass spectrometry (XL-MS) technology has become a key tool for identifying protein-protein interactions (PPIs) and revealing the protein structures in living cells, tissues, or organelles. The XL-MS technology has demonstrated remarkable superiority compared with conventional methods for studying PPIs and protein structures. In the past few years, new cross-linker structures have been arising continuously. They have not only broadened the range of cross-linking reactions but also provided additional methods for the enrichment of cross-linking peptides. Moreover, owing to the advancement of computer software and artificial intelligence, cross - linking data search engines and visualization software have also been enhancing the speed and accuracy of cross-linking peptide identification. The evolution of cross-linkers and cross-linking peptide search engines has promoted the application of the XL-MS technology in the research on protein-protein interactions (PPIs) within organelles and even living cells and in the analysis of protein structures.

Objective To investigate the mechanism of lobetyolin's intervention in HepG2 cells abnormal cholesterol metabolism.Methods This study used oleic acid(OA)stimulation of HepG2 cells as a model.MTT assay,oil red O staining,biochemical kit assay,qRT-PCR assay,Western blot assay and NBD labeled cholesterol effection assay were used to study the effect of lobetyolin on cholesterol metabolism in HepG2 cells.Results The results showed that lobetyolin could reduce the content of lipid drops,the levels of triglyceride(TG)and total cholesterol(TC)in HepG2 cells stimulated by OA,increase cholesterol effection rate,and up-regulate cytochrome 7A1(CYP7A1),liver x receptor α(LXRα),ATP-binding cassette transporter A1(ABCA1),peroxisome proliferator-activated receptor(PPARγ)and other mRNA or protein expression levels.However,combined intervention with PPARγ antagonist Mifobate(SR-202)can significantly inhibit the promoting effect of lobetyolin on cholesterol metabolism in HepG2 cells.Conclusion This study revealed that lobetyolin can improve the cholesterol effection rate of HepG2 cells stimulated by OA and promote cholesterol catabolism,and the mechanism of action may be related to the regulation of PPARγ/CYP7A1 pathway.

Using Real-time PCR technology, a highly specific and sensitive method for detecting DNA residues of Escherichia coli host cells in levodopa was established, validated, and preliminarily applied. Escherichia coli strain MB6 16S ribosomal RNA gene was selected as the target gene to design multiple pairs of primers and the target fragment by specific amplification of PCR was obtained. The target fragment was cloned into the pLENTI-BSD-CON vector and the recombinant plasmid was constructed and named pLENTI-BSD-CON-E.coli-16S. A quantitative PCR detection method (SYBR Green method) with magnetic bead extraction and purification methods was established with the reference standard of the recombinant plasmid. Furthermore, the established method was validated, including linear and range, accuracy, precision, specificity, and quantification limit, and applied to the detection of levodopa raw materials. Meanwhile, the detection method was compared with the Taqman probe method by the commercial kit. The primer sequences of the quantitative PCR detection method (SYBR Green method) were TTCGATGCAACGCGAAGAAC (forward) and GTGTAGCCCTGGTCGTAAGG (reverse). The standard curve of DNA was in the range of 10 fg/μL to 3 ng/μL with good linearity (R2≥ 0.98). The quantitative limit was 10 fg/μL. In addition, the detection recovery rate was in the range of 59.7% to 80.7%, with RSD at less than 15%. Nine batches of levodopa were detected by this method, and the amount of E.coli DNA residue was below the limit. The developed qPCR method can be used for quantitative detection of residual DNA in biological products produced by E.coli as host cells, such as levodopa . The results indicate that the sensitivity of the detection method for recombinant plasmid construction standards is superior than the reagent kit detection method.

Objective To investigate the mechanism of lobetyolin's intervention in HepG2 cells abnormal cholesterol metabolism.Methods This study used oleic acid(OA)stimulation of HepG2 cells as a model.MTT assay,oil red O staining,biochemical kit assay,qRT-PCR assay,Western blot assay and NBD labeled cholesterol effection assay were used to study the effect of lobetyolin on cholesterol metabolism in HepG2 cells.Results The results showed that lobetyolin could reduce the content of lipid drops,the levels of triglyceride(TG)and total cholesterol(TC)in HepG2 cells stimulated by OA,increase cholesterol effection rate,and up-regulate cytochrome 7A1(CYP7A1),liver x receptor α(LXRα),ATP-binding cassette transporter A1(ABCA1),peroxisome proliferator-activated receptor(PPARγ)and other mRNA or protein expression levels.However,combined intervention with PPARγ antagonist Mifobate(SR-202)can significantly inhibit the promoting effect of lobetyolin on cholesterol metabolism in HepG2 cells.Conclusion This study revealed that lobetyolin can improve the cholesterol effection rate of HepG2 cells stimulated by OA and promote cholesterol catabolism,and the mechanism of action may be related to the regulation of PPARγ/CYP7A1 pathway.

To analyze the current quality of treatment for hospitalized cancer patients in Beijing, identify major issues in treatment practices, and propose improvements.

Surgical innovation is an important part of surgical research and practice. The evaluation of surgical innovation through the stages is similar to those for drug development, but with important differences. The Idea, Development, Exploration, Assessment, and Long-term follow-up (IDEAL) Framework and Recommendations represent a new paradigm for the evaluation of surgical intervention and devices which was developed in 2009. The IDEAL is a five-stage framework involving the nature stages of surgical innovation, together with recommendations for surgical research pathway. The Framework and Recommendations were updated and published in 2019, which added a pre-IDEAL stage if necessary. The updated IDEAL also underlines the purpose, key question and ethical issues for each stage. In the first paper of IDEAL Framework and Recommendations series, we conducted a comprehensive introduction of IDEAL (e.g. the development, updates and application of IDEAL) to promote the dissemination and application of IDEAL in China.