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.

Large language models (LLMs) offer a modern approach to help inherit traditional Chinese medicine (TCM). This article discussed the progress of LLM applications in TCM and proposed future development directions by reviewing the existing research. We have found that LLMs and related technologies have excellent applications and performance in the management of TCM knowledge and data. They are often applied in information extraction, knowledge graph construction, and data standardization processing. However, data quality and security issues need to be given more attention. In clinical diagnosis and treatment, LLMs can imitate the thinking of TCM by disassembling and reconstructing its diagnostic process and can achieve functions such as prescription recommendation and question and answer (Q&A). However, this approach involves LLMs making inferences and predictions based on existing corpora and thus may not flexibly handle complex environments and tasks. Moreover, the current evaluation criteria for TCM LLMs can be summarized into 3 categories: general evaluation metrics, technical framework evaluation, and evaluation criteria for the characteristics of TCM (such as consistency rates of prescriptions and diagnostic suggestions). However, the lack of a unified and standardized evaluation system hinders the clinical application of TCM LLMs. The future progress of TCM LLMs should focus on the 3 aforementioned critical aspects to achieve technological breakthroughs. In addition, we are promoting the research on vertical TCM LLMs and application terminals. We believe this will bring new ideas to the research on TCM LLMs.

[Objective] To compare the clinical efficacy of super pulse thulium laser enucleation of the prostate (SPThuLEP) with "open tunnel" and transurethral holmium laser enucleation of the prostate (HoLEP) in the treatment of benign prostatic hyperplasia (BPH), in order to provide reference for the treatment options of BPH. [Methods] The clinical data of 112 BPH patients treated in our hospital during Jan.2023 and Jul.2023 were retrospectively analyzed, including 65 treated with SPThuLEP with "open tunnel" and 57 with HoLEP.The operation time, postoperative hemoglobin decrease, postoperative bladder irrigation, catheter indwelling time, hospitalization time and complications were compared between the two groups.The changes of maximum urine flow rate (Qmax), international prostate symptom score (IPSS), quality of life score (QoL), postvoid residual (PVR) and prostate-specific antigen (PSA) were compared between the two groups before operation and one month after operation. [Results] All operations were successful without conversion to open or transurethral plasmakinetic resection.The postoperative decrease of hemoglobin in SPThuLEP group was lower than that in HoLEP group [(13.12±6.72) g/L vs. (21.02±6.51) g/L], with statistical difference (P<0.05). There were no significant differences in the operation time [(63.35±15.73) min vs.(61.02±17.55) min], postoperative bladder irrigation time [(1.07±0.45) d vs. (1.06±0.36) d], catheter indwelling time [(2.98±0.56) d vs. (3.01±0.63) d] and hospitalization time [(3.63±0.61) d vs.(3.79±0.76) d] between the two groups (P>0.05). No blood transfusion, secondary bleeding or unplanned hospitalization occurred, and there were no serious complications such as transurethral electroresection syndrome (TURS), urethral stricture and urinary incontinence.One month after operation, the Qmax, IPSS, QoL, PVR and PSA of the two groups were significantly improved compared with those before operation (P<0.05), but with no statistical difference between the two groups (P>0.05). [Conclusion] SPThuLEP with "open tunnel" has comparable efficacy as HoLEP in the treatment of BPH.With advantages of small amount of bleeding and high safety, this minimally invasive technique can be widely popularized in clinical practice.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To observe the value of contrast-enhanced ultrasound(CEUS)for diagnosing malignant adnexal tumors.Methods Totally 112 patients with single adnexal masse were retrospectively enrolled and divided into benign adnexal tumor group(benign group,n=73)and malignant adnexal tumor group(malignant group,n=39).Clinical data,laboratory indicators,ovarian-adnexal ultrasound reporting and data system(O-RADS)classification based on conventional ultrasound(US),CEUS manifestations and CEUS classification of benign and malignant tumors were compared between groups.Multivariable logistic regression analysis of clinical and laboratory indicators being statistically different between groups,as well as US O-RADS classification and CEUS classification was performed to screen the independent predictors of malignant adnexal tumors,and combined models were constructed using forward stepwise regression method.The efficacy of each independent predictor and combined model for diagnosing malignant adnexal tumors was analyzed.Results Statistical differences of carbohydrate antigen 125(CA125),US O-RADS classification,enhancement time and level of CEUS,as well as CEUS classification were found between groups(all P＜0.05).CA125,US O-RADS classification and CEUS classification were all independent predictors of malignant adnexal tumors(all P＜0.05).Combined model Ⅰ,Ⅱ and Ⅲ were constructed based on CA125+CEUS classification,US O-RADS classification+CEUS classification and CA125+US O-RADS classification+CEUS classification,respectively.The area under the curve(AUC)of single CA125 level,US O-RADS classification,CEUS classification and combined model Ⅰ,Ⅱ and Ⅲ for diagnosing malignant adnexal tumor was 0.708,0.809,0.908,0.918,0.945 and 0.954,respectively.AUC of combined model Ⅲ was higher than that of combined model Ⅰ(Z=-2.142,P=0.032),while no significant difference of AUC was found between combined model Ⅱ and Ⅰ nor Ⅱ and Ⅲ(both P＞0.05).Conclusion CEUS could be used to effectively diagnose malignant adnexal tumor.Combining with CA125 level and US O-RADS classification could significantly improve its diagnostic efficacy.

Objective We aimed to evaluate the efficacy and safety of Shengxuebao Mixture in the treatment of cancer-related anemia(CRA)presenting with syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood.Methods A randomized,double-blind,placebo-controlled,multicenter clinical trial was conducted.Eligible patients with malignant tumors meeting the inclusion and exclusion criteria were enrolled from 26 hospitals,including Dongzhimen Hospital,Beijing University of Chinese Medicine,Xiaogan Central Hospital,and Yangzhou Hospital of Traditional Chinese Medicine,from June 1,2022,to September 30,2024.Patients were allocated 1:1 to either the experimental group receiving Shengxuebao Mixture or the control group receiving its simulator(placebo)using a block randomization method under double-blind conditions.Both groups received 15 mL orally three times daily for 28 consecutive days.The primary efficacy indicators included the hemoglobin(Hb)improvement rate(RHb)and the traditional Chinese medicine(TCM)syndrome improvement rate(RTCM)at week 4 of treatment.The secondary efficacy indicators encompassed Hb and red blood cell(RBC)count,Karnofsky Performance Status(KPS)score,TCM syndrome score,individual TCM symptom scores,and changes in each of these indicators compared to the baseline period at weeks 2,4,and 6 of treatment.Safety evaluations were conducted at week 4 of treatment.Results A total of 239 patients were enrolled,with 225 cases included in the Full Analysis Set(FAS)(109 in the experimental group vs.116 control group),163 in the Per Protocol Set(PPS)(77 vs.86),and 225 in the Safety Set(SS)(109 vs.116).Baseline characteristics between groups showed no significant differences.Significant differences were observed between the experimental and control groups in RHb at week 4(FAS:49.51%vs.35.24%,P<0.05;PPS:53.25%vs.36.05%,P<0.05)and RTCM at week 4(FAS:61.54%vs.39.62%,P<0.01;PPS:64.94%vs.40.70%,P<0.01).At weeks 2,4,and 6,the experimental group showed greater improvements in Hb and RBC counts than the control group.Additionally,the TCM syndrome scores were lower in the experimental group than in the control group at these time points.Except for week 2 in PPS,the KPS improvement was better in the experimental group than in the control group(P<0.05).The experimental group also demonstrated a greater reduction in scores for individual TCM symptoms such as spiritlessness and weakness,poor appetite and reduced food intake at weeks 4 and 6 compared to the control group(P<0.05,P<0.01).Furthermore,the reduction in vertigo score was more pronounced in the experimental group at week 6(P<0.01).For the score of pale and lusterless complexion,only in the PPS was the reduction from baseline more significant in the experimental group than in the control group at weeks 4 and 6(P<0.05).No significant differences were observed between the experimental and control groups in the incidence of all adverse events or drug-related adverse reactions.Conclusion Shengxuebao Mixture demonstrates significant efficacy in patients with CRA presenting syndrome of deficiency of liver and kidney combined with syndrome of deficiency of both qi and blood,effectively increasing Hb levels,ameliorating TCM syndromes,alleviating clinical symptoms,and enhancing functional status,with no significant difference in adverse drug reactions compared to the placebo.

Objective:To evaluate the efficacy and safety of endoscopic submucosal dissection (ESD) for the treatment of ileocecal valve lipoma.Methods:A retrospective cohort study was performed on data of ileocecal lipoma patients who underwent ESD at the Endoscopy Center of Zhongshan Hospital, Fudan University from December 2013 to June 2023. According to the lesion location, the patients were divided into ileocecal valve group and cecum group. The operation time, operation speed, en bloc resection rate, complications, and follow-up outcomes between the two groups were compared.Results:A total of 59 patients with ileocecal lipoma were enrolled, including 31 patients in the ileocecal valve group and 28 patients in the cecum group.There were no significant differences in gender, age, specimen size, or lesion size between the two groups ( P>0.05). Lipomas in both the ileocecal valve group and the cecum group were successfully resected by ESD. The en bloc resection rates were 100.0% (31/31) and 92.9% (26/28) respectively, and the difference was not statistically significant ( χ2=0.033, P=0.133). Median operative duration significantly differed between the two groups ( ileocecal valve group 26 min VS cecum group 20 min, Z=-0.136, P=0.027), as did resection speed (ileocecal valve group 0.14 cm2/min VS cecum group 0.24 cm2/min, Z=-0.223, P=0.022). Adverse events included one postoperative fever in the ileocecal valve group and one delayed bleeding in the cecum group. During the median follow-up of 38 months (7-106 months), there was no case of residual tumor or recurrence. Conclusion:Despite technical challenges in ESD of ileocecal valve lipoma, it is still a safe, feasible and effective treatment method.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the sample preparation proficiency and storage proficiency of 11 clinical biobanks in Beijing through simulated experiments, and to establish an assessment method for the quality comparability of biological samples.Methods:An exploratory research design was adopted. In November 2023, artificial composite serum quality control materials containing six recombinant human protein markers—recombinant human alanine aminotransferase (rhALT), recombinant human aspartate aminotransferase (rhAST), recombinant human creatine kinase (rhCK), recombinant human creatine kinase-MB (rhCK-MB), recombinant human B-type natriuretic peptide (rhBNP), and recombinant human troponin I (rhTNI)—were distributed to 11 clinical biobanks in Beijing City. Sample preparation and storage followed the standardized operating procedures. Proficiency differences were assessed through statistical analysis.Results:Three-way repeated measures ANOVA revealed all six protein markers showed a declining trend over storage time in ultra-low-temperature environments ( F values 11.68-4 179.66, all P<0.01). However, neither long-term/temporary refrigerator types ( F values 0.01-1.23, all P>0.05)nor placement locations within refrigerators significantly affected the stability of these six proteins ( F valus 0.03-1.47, all P>0.05). The biases in detection results for rhALT, rhAST, rhTNI, and rhBNP at different storage time points were within the allowable bias limits for each item, supporting their use as markers for protein stability in biobank samples. All 11 institutions passed the storage proficiency assessment. In the preparation proficiency assessment, deviations were observed in post-preparation sample results, with a notably high out-of-control rate for rhCK (36.36%). Conclusion:Sample preparation proficiency can serve as a quality control metric for clinical biobanks. Future external quality assessment systems for biobanks should focus on sample preparation rather than storage processes.