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.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

Iron is an indispensable trace element for the human body to maintain normal physiological functions， widely participating in key processes such as oxygen transport， energy metabolism， and cell signal transduction. The homeostasis of iron is crucial for maintaining the structural integrity and functional stability of the cardiovascular system. Recent studies have shown that iron homeostasis imbalance， especially iron overload， has become a major risk factor for the occurrence and development of atherosclerosis （AS）. The downstream-induced ferroptosis can form a "iron overload-lipid peroxidation-inflammation" vicious triangle through multiple pathways such as promoting oxidative stress， lipid peroxidation， and inflammatory response， and the three mutually reinforce each other to accelerate plaque formation and progression. Traditional Chinese medicine （TCM） has demonstrated unique advantages in the prevention and treatment of AS， with definite clinical efficacy. Its mechanism of action， in addition to improving lipid metabolism and protecting vascular endothelium， is closely related to the regulation of iron homeostasis in the body. From the new perspectives of systemic iron homeostasis imbalance and the "iron overload-lipid peroxidation-inflammation" vicious triangle， this article reviews the research progress in the association between iron homeostasis imbalance and AS in recent years， and integrate the mechanism of iron homeostasis imbalance in modern medicine with the TCM theory of stasis and toxin interconnection. It focuses on exploring the potential molecular mechanisms of TCM in regulating iron homeostasis through intervention in key pathways of iron overload and inhibition of ferroptosis， summarizes the "iron reduction-antioxidation-anti-inflammation" network constructed by TCM compound prescriptions， and the characteristics of TCM active components in synergistically resisting systemic iron homeostasis imbalance through sharing key targets such as nuclear factor erythroid 2-related factor 2 （Nrf2） and nuclear factor （NF）-κB. This article provides ideas and a theoretical basis that combine the characteristics of TCM theory with modern scientific evidence for the prevention and treatment of AS.

[Objective] To evaluate the efficacy and safety of sacral neuromodulation (SNM) in the treatment of patients with benign prostatic hyperplasia (BPH) complicated with underactive bladder (UAB) who respond poorly to transurethral resection of the prostate (TURP). [Methods] A retrospective analysis was performed on 10 patients with BPH and UAB treated with TURP by the same surgeon in Zhongda Hospital Southeast University during Jan.2018 and Jan.2023.The residual urine volume was not significantly relieved after operation, and the maximum urine flow rate and urine volume per discharge were not significantly improved.All patients underwent phase I SNM, and urinary diaries were recorded before and after surgery to observe the average daily frequency of urination, volume per urination, maximum urine flow rate, and residual urine volume. [Results] The operation time was (97.6±11.2) min.During the postoperative test of 2-4 weeks, if the residual urine volume reduction by more than 50% was deemed as effective, SNM was effective in 6 patients (60.0%). Compared with preoperative results, the daily frequency of urination [(20.2±3.8) times vs. (13.2±3.2) times], volume per urination [(119.2±56.7) mL vs. (246.5±59.2) mL], maximum urine flow rate [(8.7±1.5) mL/s vs. (16.5±2.6) mL/s], and residual urine volume [(222.5±55.0) mL vs. (80.8±16.0) mL] were significantly improved, with statistical significance (P<0.05). There were no complications such as bleeding, infection, fever or pain.The 6 patients who had effective outcomes successfully completed phase II surgery, and the fistula was removed.During the follow-up of 1 year, the curative effect was stable, and there were no complications such as electrode displacement, incision infection, or pain in the irritation sites.The residual urine volume of the other 4 unsuccessful patients did not improve significantly, and the electrodes were removed and the vesicostomy tube was retained. [Conclusion] SNM is safe and effective in the treatment of BPH with UAB patients with poor curative effects after TURP.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To explore the independent risk factors for long-term adverse prognosis after percutaneous renal artery angioplasty in patients with transplant renal artery stenosis(TRAS).Methods We retrospectively collected medical records and surgery details of TRAS patients who underwent renal artery angioplasty at the Department of Peripheral Vascular Diseases,The First Affiliated Hospital of Xi'an Jiaotong University,from January 2017 to June 2021.All patients were followed up for 3 years post-operation.Multivariate Cox regression analyses were performed to find the independent predictive factors for long-term adverse prognosis after renal artery angioplasty in the TRAS patients.Results A total of 45 TRAS patients who underwent percutaneous renal artery angioplasty were included in this study.During the five-year follow-up period,10 patients(22.2％)experienced long-term adverse events.These consisted of 3 patients(6.7％)who died from any cause,1 patient(2.2％)who developed transplant renal artery dissection,6 patients(13.3％)who had restenosis of the transplant renal artery,and 1 patient(2.2％)who lost the transplant kidney and received dialysis again.Multivariate Cox regression analysis showed that male gender(HR=4.915,95％CI:1.036-23.328,P=0.045)and balloon angioplasty alone(HR=8.594,95％CI:2.191-33.710,P=0.002)were independent risk factors for long-term adverse prognosis after renal artery angioplasty in TRAS patients.Conclusion Male gender and balloon angioplasty alone are independent risk factors for long-term adverse prognosis after renal artery angioplasty in TRAS patients.

Objective To explore the predictive value of serum high-mobility group box protein B1(HMGB1)and soluble receptor for advanced glycation end-products(sRAGE)in the occurrence and short-term prognosis of sepsis-associated encephalopathy(SAE).Methods Clinical data of 228 patients with sepsis were retrospectively analyzed.According to the presence of SAE,patients were divided into the SAE group(96 cases)and the non-SAE group(132 cases).General clinical data,laboratory test results,Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores,Sequential Organ Failure Assessment(SOFA)scores and serum HMGB1 and sRAGE levels were compared between the two groups.Multivariate Logistic regression analysis was performed to determine factors influencing SAE occurrence.Receiver operating characteristic(ROC)curves were plotted to evaluate the predictive ability of HMGB1,sRAGE and the HMGB1/sRAGE ratio to predict the occurrence and short-term prognosis of SAE.Kaplan-Meier survival curves were used to compare the 28-day mortality rates of SAE patients with different HMGB1 and sRAGE expression levels.Results Compared to the non-SAE group,patients in the SAE group exhibited elevated serum HMGB1 levels,decreased sRAGE levels and an increased HMGB1/sRAGE ratio(P＜0.05).The areas under the curve(AUC)for predicting SAE using HMGB1,sRAGE and the HMGB1/sRAGE ratio were 0.826(95%CI:0.770-0.872),0.682(95%CI:0.617-0.742)and 0.895(95%CI:0.848-0.932),respectively,indicating predictive value.Among the 96 SAE patients,52(54.2%)died within 28 days.There were no statistically significant differences in HMGB1,sRAGE and the HMGB1/sRAGE ratio between surviving and deceased patients(P＞0.05).Similarly,there were no significant differences in 28-day mortality rates between SAE patients with different HMGB1 or sRAGE expression levels.Conclusion Elevated serum HMGB1 and reduced sRAGE are of significant value in the auxiliary diagnosis of SAE,but have limited clinical predictive value for short-term prognosis.

Objective:To construct a training program for nurses in shared-decision making of breast cancer surgery based on core competence, and to provide reference for clinical training.Methods:From February to May 2023, through literature review, qualitative interview, group discussion, Delphi and analytic hierarchy process, the training program were determined.Results:Among 18 experts, there were 3 males and 15 females, aged (44.67±9.24) years old. The final training program included 6 first-level indicators(admission criteria, training content (theory + practice), training format, training hours, training instructors, training evaluation), 17 second-level indicators, and 57 third-level indicators. The effective response rates of 2 rounds of expert consultations were both 18/18, and the expert authority coefficients were both 0.933. The Kendall coordination coefficients of the first and second round were 0.160, 0.213 (both P<0.05). Conclusions:The training program of decision aid nurses in breast cancer surgery is scientific, practical and clinically valuable, and can provide reference for the development of standardized training for nurses.

Objective:To construct a recommended list of high-alert medication (HAM) based on big data from medication error (ME) reports in China, providing reference for preventing and reducing HAM-related risks.Methods:The drugs involved in the serious ME reports of the National Monitoring Network for Clinical Safe Medication (Monitoring Network) were collected (as of December 31, 2023), and the candidate drugs were preliminarily determined referring to the HAM list of China 2023 (Chinese list) and the latest three lists of American Institute for Safe Medication Practices (ISMP). Candidate drugs that were included in both the Chinese list and ISMP lists, as well as those existed in the Chinese list but had never been included in the ISMP lists were included in the current list, and their risk levels followed the original risks in the Chinese list. Candidate drugs that existed in the Chinese list but had been excluded from the ISMP lists, and those existed in the ISMP lists but had not been included in the Chinese list were listed as suspected drugs. For the other candidate drugs, those did not meet the definition of HAM were excluded firstly, and those related to ME that had caused serious harm were listed as suspected drugs, according to the judicial cases on ME of China Judgements Online and PKULAW database. Two methods, including Delphi expert consultation and questionnaire survey, were used to determine whether the above suspected drugs were included in the HAM list and their risk levels.Results:A total of 138 drugs were obtained through the initial screening, 106 of which were directly included in the current list, and 32 of which were listed as drugs requiring further assessment. After 2 rounds of Delphi expert consultation by 18 experts and surveys with 136 valid questionnaires, 32 suspected drugs did not meet the inclusion criteria. Finally, a total of 106 drugs were included in the current list, including 51 A-class drugs in 9 categories, 33 B-class drugs in 9 categories, and 22 C-class drugs in 5 categories.Conclusion:Based on the big data of the ME reports in China, a HAM list is constructed, which is accurate and concise and better fits the actual clinical drug risks in China, helping to improve the drug safety management.