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.

Tumor angiogenesis is a core pathological driver of malignant growth, invasion, and metastasis, and represents a major obstacle to effective anticancer therapy. Conventional antiangiogenic agents, including neutralizing monoclonal antibodies and small-molecule tyrosine kinase inhibitors, are constrained by drug resistance, on-target toxicity, and the compensatory activation of alternative pro-angiogenic pathways. Targeted protein degradation (TPD) has emerged as a promising strategy that may overcome these limitations. Unlike traditional inhibitors that operate through an occupancy-driven mechanism, degraders function through an event-driven catalytic mechanism in which a single degrader molecule can catalytically promote the ubiquitination and subsequent proteasomal or lysosomal degradation of multiple molecules of the same target protein, thereby eliminating the target protein together with all of its functions rather than merely blocking a single active site. This review systematically delineates the pathophysiological basis of tumor angiogenesis, encompassing the angiogenic switch driven by hypoxia-inducible factor-1α (HIF-1α), the aberrant structural and functional features of the tumor vasculature, and the self-reinforcing vicious cycles that sustain malignant progression. We then categorize the principal TPD modalities, with particular emphasis on proteolysis-targeting chimeras (PROTACs) and lysosome-targeting chimeras (LYTACs), and describe their design principles and mechanisms of action. PROTACs recruit E3 ubiquitin ligases to direct intracellular targets to the ubiquitin-proteasome system for degradation, whereas LYTACs engage lysosome-targeting receptors to route extracellular and membrane proteins to the lysosome, thereby expanding the degradable target space beyond the intracellular proteome. We further summarize recent advances in the application of TPD to antiangiogenic intervention at four distinct levels. First, at the signaling initiation level, degradation of vascular endothelial growth factor (VEGF) and its receptor vascular endothelial growth factor receptor 2 (VEGFR2) by aptamer-engineered PROTACs, antibody-based LYTACs, and small-molecule VEGFR2 degraders blocks the upstream trigger of the angiogenic cascade. Second, at the signal transduction level, degradation of focal adhesion kinase (FAK), B-Raf proto-oncogene serine/threonine kinase (BRAF), phosphodiesterase 4 (PDE4), and bromodomain-containing protein 4 (BRD4) interrupts intracellular signaling cascades and transcriptional responses. Third, at the microenvironment level, degradation of proviral integration site for Moloney murine leukemia virus (PIM) kinases curtails the pro-angiogenic signals secreted by tumor-associated macrophages. Fourth, multi-target synergistic strategies, exemplified by bispecific degraders that simultaneously target human epidermal growth factor receptor 2 (HER2) and VEGF-A, represent a preliminary exploration of cooperative intervention. Representative degraders reviewed herein elicit diverse antiangiogenic phenotypes, ranging from the direct inhibition of endothelial cell proliferation, migration, and tube formation to reductions in microvessel density and the suppression of vasculogenic mimicry. Finally, we discuss the major challenges that remain, including the precise matching of degradation kinetics with the vascular normalization window, target selectivity and tissue specificity, and the activation of compensatory networks and the emergence of resistance. Since the application of TPD in this setting remains at an early stage, the clinical translation of these approaches will require careful optimization of degradation efficiency, spatiotemporal control, and delivery strategies. We also envision future directions toward immunotherapy-based combination regimens and precision-degradation approaches guided by single-cell and spatial transcriptomics. In our view, TPD should not be regarded merely as a substitute for conventional antiangiogenic drugs, but rather as a molecular tool capable of systematically remodeling the tumor vascular microenvironment. When precise control of degradation efficiency and spatiotemporal regulation are integrated with a thorough understanding of the heterogeneity and compensatory capacity of tumor vessels, the full clinical potential of this strategy can be realized.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Background and purpose:With the progressive development of breast cancer surgery toward more individualized and minimally invasive approaches,sentinel lymph node biopsy(SLNB)has replaced axillary lymph node dissection(ALND)as the standard method for axillary management in certain early-stage breast cancer patients.However,there is ongoing debate in clinical practice regarding whether regional lymph node irradiation(RNI)is necessary for patients with sentinel lymph node(SLN)positive status who have not undergone ALND.This study aimed to analyze the clinicopathological features and survival prognosis of patients with SLN-positive status who did not undergo ALND,evaluate the clinical application value of RNI,and provide evidence to support clinical treatment decisions for this group of patients.Methods:This single-center retrospective study screened breast cancer patients who underwent SLNB at Shandong Cancer Hospital from September 1,2014,to August 31,2023.All patients signed informed consent for treatment.Based on whether postoperative radiotherapy included regional lymph node irradiation(internal mammary and/or axillary and/or supra-/infra-clavicular fields),patients were divided into the RNI group and the no-RNI group for follow-up.Additionally,patients were further divided into multiple subgroups based on factors such as the type of breast surgery,tumor molecular subtype,and histological grade,to compare the clinical value of RNI among subgroups.The primary endpoint was locoregional recurrence-free survival(LRRFS),and the secondary endpoints included invasive disease-free survival(iDFS)and overall survival(OS).The Strengthening the Reporting of Observational Studies in Epidemiology(STROBE)checklist was followed for this study.Results:Clinical data of 8 328 breast cancer patients'were screened for this study,and after applying inclusion and exclusion criteria,356 patients were included in the analysis,with 186 in the RNI group and 170 in the no-RNI group.There were no significant differences between the two groups in terms of age,body mass index(BMI),menopausal status,tumor location,pathological type,histological grade,vascular invasion,estrogen receptor(ER)and progesterone receptor(PR)status,and human epidermal growth factor receptor 2(HER-2)expression(P＞0.05).However,the number of positive SLNs,T stage,and the proportion of patients undergoing total mastectomy(TM)were significantly higher in the RNI group than in the no-RNI group(P=0.006,P=0.043,P＜0.001).After a median follow-up of 38 months,no recurrence or metastasis was observed in the RNI group,while the recurrence and metastasis rate in the no-RNI group was 3.5%(6/170).Of these,4 cases had local regional recurrence,and 2 had distant metastasis.The RNI group showed superior iDFS compared to the no-RNI group(P=0.017),however there was no statistically significant difference in LRRFS and OS(P=0.051 and P=0.356).Exploratory subgroup analysis indicated that patients with tumor diameter＞2 cm(P=0.033)and triple-negative molecular(TNBC)(P=0.020)might benefit from RNI treatment in terms of LRRFS.Conclusion:For certain high-risk patients,such as those with larger tumor diameter,TNBC,or high non-SLN metastatic risk,RNI still plays an important role in reducing the risk of recurrence and metastasis in breast cancer.In clinical practice,an individualized RNI strategy should be developed based on the patient's residual lymph node tumor load,biological behavior of the tumor,and surgical method.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

Objective To investigate the efficacy and safety of the Corheart 6 left ventricular assist system in patients with end-stage heart failure. Methods A retrospective study was conducted on patients with end-stage heart failure who were treated with Corheart 6 left ventricular assist system from March 2022 to June 2024 in 4 hospitals in Jiangsu Province. The efficacy of the device was evaluated by comparing changes in clinical indicators at preoperative, discharge, 3-month postoperative, and 6-month postoperative timepoints, including the New York Heart Association (NYHA) functional classification, left ventricular ejection fraction (LVEF), and left ventricular end-diastolic diameter (LVEDD). The safety of the device was assessed by analyzing the intraoperative position and orientation of the blood pump inlet cannula, as well as the incidence of adverse events. Results In this study, 39 patients were collected, including 34 males and 5 females with a mean age of (56.4±12.5) years, ranging from 20 to 75 years. There was no operative death. There was no death in postoperative 3 months with a survival rate of 100.0%. There were 3 deaths in 6 months postoperatively, with a survival rate of 92.3%. All patients had a preoperative NYHA cardiac function classification of class Ⅳ. The NYHA cardiac function class of the patients improved (P<0.05) at discharge, 3 and 6 months after surgery when compared to the preoperative period. LVEF was significantly higher at 3 months after surgery than that during the preoperative period (P<0.05). LVEDD was significantly smaller at discharge, 3 and 6 months after surgery than that during the preoperative period (P<0.05). The safety evaluation's findings demonstrated that all 39 patients' intraoperative blood pump inlet tubes were oriented correctly, the artificial blood vessel suture sites were appropriate, there were no instances of device malfunction or pump thrombosis, or instances of bleeding or hemolysis, and the rate of the remaining adverse events was low. Conclusion With a low rate of adverse events and an excellent safety profile, the Corheart 6 left ventricular assist system can efficiently enhance cardiac function in patients with end-stage heart failure. It also has considerable clinical uses.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

As an indispensable trace element in the human body,copper plays an important role in various physiological and biochemical reactions.The dyshomeostasis of copper leads to the disorder of copper metabolism and the occurrence of related diseases.Cuproptosis,a newly proposed regulatory cell death mode,is different from the known apoptosis,pyroptosis,necroptosis,and ferroptosis.Recent studies have found that the dyshomeostasis of copper has been observed in a variety of cancers.Therefore,targeting copper for disease treatment may become a new strategy and a new idea.This article systematically summarizes the fundamental properties of copper,copper dyshomeostasis-related diseases (Menkes syndrome,Wilson's disease,and cancer) and their treatment,and reviews the research progress in cuproptosis.
Humans ; Copper/metabolism* ; Homeostasis ; Neoplasms/metabolism* ; Hepatolenticular Degeneration/metabolism* ; Menkes Kinky Hair Syndrome/metabolism*