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.

Definitive chemoradiotherapy (dCRT) has become a cornerstone in the treatment of locally advanced esophageal cancer; however, local control remains suboptimal, and persistent lesions or locoregional recurrences after treatment are not uncommon. For patients without distant metastases but with local failure, whether surgical intervention can still offer curative potential remains a major clinical dilemma. Salvage esophagectomy (SE) offers potential long-term survival for selected patients, but this procedure is performed in the context of severe fibrosis, impaired local blood supply, and obscured anatomical planes following chemoradiotherapy, resulting in significantly higher perioperative risk compared to primary esophagectomy. Consequently, controversies exist regarding patient selection, preoperative restaging, choice of surgical approach, extent of lymphadenectomy, gastrointestinal reconstruction, and perioperative management. In recent years, with the refinement of restaging modalities such as PET/CT, the accumulation of experience in high-volume centers, and emerging evidence from clinical studies, the clinical role of SE has gradually shifted from a "high-risk salvage measure" to a "selective curative strategy aimed at achieving long-term survival in carefully selected patients". Nevertheless, standardized guidelines for patient selection, technical approaches, and perioperative management are still lacking. Based on current evidence and clinical experience, experts organized by the Integrated Esophageal Cancer Committee of Chinese Anti-Cancer Association systematically reviewed key issues regarding SE, including its definition, indications, preoperative evaluation, choice of surgical approach, lymphadenectomy, gastrointestinal reconstruction, and perioperative management, and formulated a Chinese expert consensus. This consensus aims to provide guidance for standardized assessment, appropriate referral, individualized surgical decision-making, and optimized perioperative management of patients with locoregional failure after dCRT. Ultimately, this will increase the likelihood of R0 resection, reduce the risk of severe complications, and promote the safer, more judicious, and standardized implementation of SE in high-risk scenarios.

Objective To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

Wilson disease is a copper metabolism disorder caused by mutations in the ATP7B gene， which encodes a copper-transporting ATPase β， and can result in multisystem damage. The kidneys are the third most commonly affected organs after the liver and brain. In recent years， numerous diagnostic and treatment guidelines for Wilson disease have emerged. However， most of these focus primarily on hepatic and neurological manifestations and their management， with limited coverage of renal involvement. The high incidence， low awareness， and lack of clinical specificity of Wilson disease-related renal damage （WDRD） have made early detection and intervention particularly challenging in clinical practice. To further optimize the treatment of patients with WDRD， improve clinical diagnosis and management， and enhance patients' quality of life， the Neurology Committee of the Chinese Association of Integrative Medicine， in April 2024， initiated a revision of the first expert consensus on the integrated diagnosis， treatment， and management of WDRD. This effort brought together experts in hepatology， encephalopathy （neurology）， and nephrology from many tertiary-level grade A hospitals and research institutions across China. Through comprehensive literature review and integration of frontline clinical experience， the expert group jointly developed Chinese Expert Consensus on Integrated Chinese and Western Medicine Management of Wilson Disease-related Renal Damage （hereinafter referred to as the "Consensus"）. This article provides a detailed interpretation of the Consensus in terms of diagnostic criteria， traditional Chinese medicine （TCM） syndrome differentiation and treatment classification， and comprehensive disease management， aiming to better guide clinical application. Regarding diagnostic criteria， the Consensus integrates the latest standards in China and abroad， highlights the importance of biochemical diagnosis， and compensates for the limitations of genetic testing. In the area of TCM syndrome differentiation and treatment， the Consensus refines four major syndrome types， introduces a newly defined syndrome， i.e.， phlegm， blood stasis， and heat accumulation， and elaborates on treatment principles， prescriptions， and clinical modification rules for each syndrome. For comprehensive disease management， the Consensus emphasizes multi-dimensional intervention strategies， including diet， exercise， emotional regulation， medication， and medical care， with the goal of maximally controlling the progression of renal dysfunction and helping patients achieve a better quality of life.

Mild cognitive impairment due to Alzheimer′s disease is an inevitable pathological stage in the early development of Alzheimer′s disease, which can be classified as "microlumps in the brain collaterals" in traditional Chinese medicine. Based on the theory of latent toxin blocking collaterals, this article discusses the etiology and pathogenesis, clinical sequelae, and traditional Chinese medicine intervention strategies for mild cognitive impairment due to Alzheimer′s disease. The onset of mild cognitive impairment due to Alzheimer′s disease is very similar to the latent pathogen theory, which states that "the latent pathogen is latent and then develops, the poison is deep and difficult to cure, and the development can be recognized but the latent pathogen cannot be detected." Combining clinical experience, our team believes that the basic nature of the disease is a slight deficiency and a slight excess of symptoms. A slight deficiency of the five zang viscera and six fu viscera as root and a latent toxin colling collaterals of qi, fire, phlegm, and blood stasis as manifestaion. These usually start from the qi depression and develop into phlegm coagulation and blood stasis, then end up in latent toxin and gradually become the healthy qi deficiency. Therefore, the deficiency of vital qi and incubation of evil, latent toxin blocking collaterals the pathogenesis of early intervention of this disease should be carried out, upholding the idea that "the upper workman treats the disease before it is diagnosed." The principle of strengthening vital qi to eliminate pathogenic factors, slowing down and promoting pathogenic factors elimination, establishing the method of supporting correctness and wisdom, simultaneously detoxifying and clearing the blood stasis, pattern differentiation as the main and the disease differentiation as the first, combining the disease and pattern, and adjusting the macroscopic and microscopic, focusing simultaneously on eliminating and replenishing, dispel phlegm and remove blood stasis, achieve a strong vital qi and the elimination of evil, and enhance intelligence, delay or even block the progression of mild cognitive impairment due to Alzheimer′s disease, improve patients′ quality of life, and provide a theoretical basis for the early clinical prevention and treatment of Alzheimer′s disease.

Objective To comprehensively assess the binocular function of college students with different glasses-wearing habits and myopic anisometropia using an eye-tracking-based,naked-eye 3D visual inspection system.Methods Between December 2023 and March 2024,a total of 137 myopic(equivalent spherical diopter per eye ≤-0.50 D)students were recruited at Sichuan University.They were divided into 2 groups,including a group of 78 participants who wore glasses continuously,and another group of 59 participants who did not wear glasses continuously.According to the degree of myopic anisometropia(the difference between the equivalent spherical diopters,ΔSE),the 2 groups were further divided into subgroups A(0 D＜ΔSE ≤ 1.00 D)and B(ΔSE＞1.00 D).Binocular function was examined using a naked-eye 3D display device based on human eye tracking,and the correlation between different glasses-wearing habits and myopic anisometropia and binocular visual function was analyzed.Results There was no statistically significant difference in the degree of myopic anisometropia between the continuous glasses-wearing group([1.15±1.15]D)and the non-continuous glasses-wearing group([1.20±1.15]D)(P=0.798).In addition,there was no statistically significant difference in refraction between the continuous glasses-wearing group and the non-continuous glasses-wearing group(P=0.158).There were statistically significant differences in the perceptual eye position of the right eye between the continuous glasses-wearing subgroups A and B(P＜0.05).There were statistically significant differences in coarse stereopsis between the non-continuous glasses-wearing subgroups A and B(P＜0.05).There were statistically significant differences in foveal suppression,fine stereopsis,and perceptual eye position between the continuous glasses-wearing group and the non-continuous glasses-wearing group(P＜0.05).Conclusion Both glasses-wearing habits and myopic anisometropia have effects on the binocular visual function of college students.

In recent years,with the constant rise in the number of infertility patients,the rapid and accurate assessment of sperm quality has become a key challenge in reproductive medicine.Currently,traditional methods for sperm classification suffer from limitations in efficiency,subjectivity,and cost-effectiveness,and hence fail to meet clinical needs.With the introduction of artificial intelligence(AI),innovative approaches have been offered to address these issues.Herein,we systematically reviewed the latest progress in AI applications in the field of male infertility,focusing on the role of AI in the assessment of sperm concentration,motility,morphology,DNA fragmentation index,and the treatment of non-obstructive azoospermia.It has been reported that AI technologies,such as convolutional neural networks,demonstrate high accuracy and efficiency in assessing sperm concentration and motility.Particularly in morphological analysis,the performance of AI has been validated in multiple studies,significantly enhancing objectivity and clinical utility.However,the assessment of DNA fragmentation index remains underexplored due to the lack of support in advanced imaging technology,with only a few models showing promise.Additionally,AI significantly improves sperm detection rates in modified testicular sperm extraction through AI-driven image recognition,offering a breakthrough in the treatment of patients with non-obstructive azoospermia.We also discussed the application of natural language processing technology in patient pre-consultation and follow-up,such as automated data collection and intelligent tracking systems,which demonstrate AI's potential to optimize medical workflows.In the future,with the accumulation of high-quality datasets,algorithm optimization,and advances in imaging technology,the application of artificial intelligence is expected to enable multi-dimensional comprehensive screening and play a greater role in the diagnosis and treatment of male infertility.

ObjectiveTo investigate the relationship between the composition of traditional Chinese medicine (TCM) and depression/anxiety/sleep disturbances (D/A/S) in patients with chronic pain.MethodsThis cross-sectional study was conducted at 13 tertiary hospitals across China, enrolling patients who experienced chronic pain between November 2023 and May 2024. The Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Pittsburgh Sleep Quality Index, and TCM constitution categories were used to assess the patients. The association between the TCM constitution and the D/A/S ratio was analyzed using multivariable logistic regression.ResultsA total of 1107 patients (63.2% women) were analyzed. Compared with those with a balanced constitution, patients who had qi-deficiency and yin-deficiency were at a higher risk of depression. Qi-deficiency and yin-deficiency were associated with anxiety. Sleep disturbances were common in patients with qi-deficiency constitution (odds ratio [OR]: 2.32, 95% confidence interval [CI]: 1.42–3.81), yang-deficiency constitution (OR: 1.94, 95% CI: 1.26–2.98), yin-deficiency constitution (OR: 2.03, 95% CI: 1.24–3.32), blood stasis constitution (OR: 2.07, 95% CI: 1.01–4.22), and qi-stagnation constitution (OR: 2.66, 95% CI: 1.35–5.25).ConclusionIn patients with chronic pain, specific TCM constitutions may be associated with D/A/S. Further longitudinal studies are needed to clarify the potential causal relationships between TCM constitution types and these conditions.

AIM To prepare anisamide-modified ursolic acid self-assembled nanoparticles,and to evaluate their anti-drug resistance effect of enzalutamide on prostate cancer.METHODS Nanoparticle precipitation method was adopted in the preparation of anisamide-modified and non-anisamide-modified self-assembled nanoparticles,respectively,after which the particle size,Zeta potential and encapsulation efficiency were determined,and the morphology was observed under transmission electron microscope.The intake of cancer-associated fibroblasts(CAFs)was investigated,after which the model for enzalutamide resistance in prostate cancer was established,CCK8 assay was applied to analyzing the sensitization effect of self-assembled nanoparticles on enzalutamide,and Western blot was used for the detection of NRG1,HER3,AKT expressions.RESULTS The anisamide-modified self-assembled nanoparticles demonstrated the average particle size,Zeta potential and encapsulation efficiency of(195.13±8.06)nm,(-29.07±0.55)mV and(94.58±0.84)％,respectively.CAFs displayed higher intake in the anisamide-modified self-assembled nanoparticles than that in the non-modified preparation and free Cy5(P＜0.05).Meanwhile,anisamide-modified self-assembled nanoparticles were able to inhibit enzalutamide resistance caused by CAFs,reduce NRG1 expression on CAFs,and anisamide-modified self-assembled nanoparticles-treated conditioned medium of CAFs could reduce HER3 and AKT expression on LNCaP cells(P＜0.05,P＜0.01).CONCLUSION Anisamide-modified ursolic acid self-assembled nanoparticles can enhance the targeting of CAFs,alleviate the drug resistance effect of enzalutamide on prostate cancer caused by CAFs,and reduce NRG1 expression in CAFs.

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.