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.

This study aims to determine the therapeutic effect and then elucidate the molecular mechanism of Dietary Yangrong Decoction(DYRT)on blood deficiency syndrome based on net-work pharmacology and study its active compounds.The molecular mechanism of DYRT in the treatment of blood deficiency syndrome was predicted by network pharmacology.The blood defi-ciency of rats was established using cyclophosphamide and acetophenohydrazine jointly,which was divided into a blank control group,a model group,a Men's Yangrong Decoction group(MYRT)(positive control group),a medicinal group and food-based Yangrong Decoction group.The active components were analyzed by liquid chromatography-mass spectrometry(HPLC-MS),the periph-eral hemogram was detected by an automatic biochemical analyzer,the levels of hematopoietic regulatory factors in serum were determined by ELISA,and the relative expression of EPO in kid-ney and PI3K,AKT,GM-CSF in bone marrow were measured by RT-PCR.The results showed that DYRT had 57 active ingredients and 128 potential targets for the treatment of spleen deficien-cy syndrome.1 835 items were obtained by GO enrichment analysis,and 20 pathways were ob-tained by KEGG enrichment analysis;DYRT and MYRT were identified by HPLC-MS to contain 12 same blood active compounds.Animal experiments showed that,compared with the model group,the number of red blood cells,the number of platelets and the content of hemoglobin in the DYRT group were significantly increased,and the number of white blood cells was significantly decreased(P＜0.05).The contents of EPO,IL-3,IL-6 and GM-CSF in serum were significantly in-creased,and the content of TNF-α was significantly decreased(P＜0.05).The relative expression levels of EPO in kidney and PI3K,AKT and GM-CSF mRNA in bone marrow were significantly increased(P＜0.05).Compared with the MYRT group,the number of white blood cells in the DYRT group was significantly reduced,the content of GM-CSF in serum was significantly in-creased,and the content of EPO and GM-CSF mRNA was significantly increased(P＜0.05).In conclusion,DYRT contains the same active compounds as MYRT,which can regulate hematopoi-etic factors,thereby activating the PI3K/AKT pathway to restore hematopoietic function and im-prove the blood deficiency state of the body.

This study aims to determine the therapeutic effect and then elucidate the molecular mechanism of Dietary Yangrong Decoction(DYRT)on blood deficiency syndrome based on net-work pharmacology and study its active compounds.The molecular mechanism of DYRT in the treatment of blood deficiency syndrome was predicted by network pharmacology.The blood defi-ciency of rats was established using cyclophosphamide and acetophenohydrazine jointly,which was divided into a blank control group,a model group,a Men's Yangrong Decoction group(MYRT)(positive control group),a medicinal group and food-based Yangrong Decoction group.The active components were analyzed by liquid chromatography-mass spectrometry(HPLC-MS),the periph-eral hemogram was detected by an automatic biochemical analyzer,the levels of hematopoietic regulatory factors in serum were determined by ELISA,and the relative expression of EPO in kid-ney and PI3K,AKT,GM-CSF in bone marrow were measured by RT-PCR.The results showed that DYRT had 57 active ingredients and 128 potential targets for the treatment of spleen deficien-cy syndrome.1 835 items were obtained by GO enrichment analysis,and 20 pathways were ob-tained by KEGG enrichment analysis;DYRT and MYRT were identified by HPLC-MS to contain 12 same blood active compounds.Animal experiments showed that,compared with the model group,the number of red blood cells,the number of platelets and the content of hemoglobin in the DYRT group were significantly increased,and the number of white blood cells was significantly decreased(P＜0.05).The contents of EPO,IL-3,IL-6 and GM-CSF in serum were significantly in-creased,and the content of TNF-α was significantly decreased(P＜0.05).The relative expression levels of EPO in kidney and PI3K,AKT and GM-CSF mRNA in bone marrow were significantly increased(P＜0.05).Compared with the MYRT group,the number of white blood cells in the DYRT group was significantly reduced,the content of GM-CSF in serum was significantly in-creased,and the content of EPO and GM-CSF mRNA was significantly increased(P＜0.05).In conclusion,DYRT contains the same active compounds as MYRT,which can regulate hematopoi-etic factors,thereby activating the PI3K/AKT pathway to restore hematopoietic function and im-prove the blood deficiency state of the body.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

Objective To investigate the effects and mechanism of Ferrostatin-1(Fer-1),a ferroptosis inhibitor,on myocardial ischemia-reperfusion injury(MIRI).Methods Rat H9c2 cardiomyocytes were ran-domly divided into five groups:Control group,H/R medium group,H/R medium+Fer-1 group,H/R medium+Nec-1 group,and H/R medium+emricasan group.Cell morphology was observed using electron mi-croscopy.Cell proliferation activity was assessed via CCK-8 assay and lactate dehydrogenase(LDH)release.I-ron ion levels were measured using an iron detection kit.Reactive oxygen species(ROS)and mitochondrial su-peroxide levels were detected by flow cytometry and MitoSOXTM fluorescence staining,respectively.Western blot was employed to analyze the expression of glutathione peroxidase 4(GPX4),acyl-CoA synthetase long-chain family member 4(ACSL4),nicotinamide adenine dinucleotide phosphate oxidase(NOX1),and cycloox-ygenase 2(COX2).Results Compared to the Control group,the H/R medium group exhibited significantly increased cytotoxicity(LDH levels)and reduced cell viability,with statistically significant differences(P<0.05).Treatment with Fer-1,Nec-1,or emricasan in the H/R medium group increased cell adherence,reduced vacuolization,enhanced cell viability,and decreased cytotoxicity(LDH relative releasing rate)compared to the H/R medium group.Intracellular ferrous iron and total iron levels were elevated in the H/R medium group compared to the Control group,with statistically significant differences(P<0.05),while Fer-1 treatment sig-nificantly reduced these levels(P<0.05).ROS levels were higher in the H/R medium group than in the Con-trol group,and Fer-1 treatment attenuated this increase(P<0.05).Western blot analysis revealed elevated ACSL4,NOX1,and COX2 levels,alongside reduced GPX4 levels,in the H/R medium group compared to the Control group,with statistically significant differences(P<0.05).Fer-1 treatment reversed these trends,de-creasing ACSL4,NOX1,and COX2 levels while increasing GPX4 expression,with statistically significant differences(P<0.05).Conclusion Ferroptosis plays a critical role in MIRI.Fer-1 mitigates oxidative stress injury and alleviates MIRI by inhibiting ferroptosis.

BACKGROUND: The atherogenic index of plasma (AIP) has been shown to be positively correlated with cardiovascular disease in previous studies. However, it is unclear whether elderly people with long-term high AIP levels are more likely to develop coronary heart disease (CHD). Therefore, the aim of this study was to investigate the relationship between AIP trajectory and CHD incidence in elderly people. METHODS: 19,194 participants aged ≥ 60 years who had three AIP measurements between 2018 and 2020 were included in this study. AIP was defined as log₁₀ (triglyceride/high-density lipoprotein cholesterol). The group-based trajectory model was used to identify different trajectory patterns of AIP from 2018 to 2020. Cox proportional hazards models were used to estimate the hazard ratio (HR) with 95% CI of CHD events between different trajectory groups from 2020 to 2023. RESULTS: Three different trajectory patterns were identified through group-based trajectory model: the low-level group (n = 7410, mean AIP: -0.25 to -0.17), the medium-level group (n = 9981, mean AIP: 0.02-0.08), and the high-level group (n = 1803, mean AIP: 0.38-0.42). During a mean follow-up of 2.65 years, a total of 1391 participants developed CHD. After adjusting for potential confounders, compared with the participants in the low-level group, the HR with 95% CI of the medium-level group and the high-level group were estimated to be 1.24 (1.10-1.40) and 1.43 (1.19-1.73), respectively. These findings remained consistent in subgroup analyses and sensitivity analyses. CONCLUSIONS There was a significant correlation between persistent high AIP level and increased CHD risk in the elderly. This suggests that monitoring the long-term changes in AIP is helpful to identify individuals at high CHD risk in elderly people.

Peptide-based radiopharmaceuticals targeting integrin α5β1 show promise for precise tumor diagnosis and treatment. However, current peptide-based radioligands that target α5β1 demonstrate inadequate in vivo performance owing to limited tumor retention. The use of PEGylation to enhance the tumor retention of radiopharmaceuticals by prolonging blood circulation time poses a risk of increased blood toxicity. Therefore, a PEGylation strategy that boosts tumor retention while minimizing blood circulation time is urgently needed. Here, we developed a PEGylation-enabled peptide multidisplay platform (PEGibody) for PR_b, an α5β1 targeting peptide. PEGibody generation involved PEGylation and self-assembly. [⁶⁴Cu]QM-2303 PEGibodies displayed spherical nanoparticles ranging from 100 to 200 nm in diameter. Compared with non-PEGylated radioligands, [⁶⁴Cu]QM-2303 demonstrated enhanced tumor retention time due to increased binding affinity and stability. Importantly, the biodistribution analysis confirmed rapid clearance of [⁶⁴Cu]QM-2303 from the bloodstream. Administration of a single dose of [¹⁷⁷Lu]QM-2303 led to robust antitumor efficacy. Furthermore, [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 exhibited low hematological and organ toxicity in both healthy and tumor-bearing mice. Therefore, this study presents a PEGibody-based radiotheranostic approach that enhances tumor retention time and provides long-lasting antitumor effects without prolonging blood circulation lifetime. The PEGibody-based radiopharmaceutical [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 shows great potential for positron emission tomography imaging-guided targeted radionuclide therapy for α5β1-overexpressing tumors.