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.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective To modify YC-1,an inhibitor of hypoxia-inducible factor-1α(HIF-1α)into nanoparticles and explore its effect on reversing chemoresistance of colorectal cancer cells.Methods Nano-inhibitor mPEG350-YC-1(MYC-1)was prepared by the carboxyl condensation reaction of the active functional group hydroxyl(-OH)in the YC-1 molecule with methoxy polyethylene glycol carboxylic acid,and was verified by 1H nuclear magnetic resonance(1H-NMR).Its morphology was analyzed by transmission electron microscope(TEM),and its particle size distribution was analyzed by dynamic light scattering(DLS).By interacting FITC-labeled MYC-1(FYC-1)with HCT15 cells,the uptake ability of FYC-1 by the cells was observed using laser confocal microscopy.The cytotoxicity of MYC-1 was measured with CCK-8 assay.The sensitization effect of MYC-1 on the chemotherapy drug 5-Fu was detected through toxicity tests of resistant HCT15 cells(resistant HCT15,R-HCT15)and live/dead cell staining.The mechanism of MYC-1 reversing drug resistance was determined with immunofluorescence staining of HIF-1α and western blotting.Finally,a subcutaneous transplanted tumor model of R-HCT15 cells was constructed.The tumor bearing mice were randomly divided into PBS,5-Fu,MYC-1,and MYF groups,with 3 mice in each group.The tumor volume and weight were observed after treatment in each group to evaluate the ability of MYC-1 to reverse 5-Fu resistance in colorectal cancer.Results The nano-inhibitor MYC-1 was successfully prepared.TEM and DLS showed that MYC-1 could self-assemble into nanoparticles with a diameter of approximately 19.96±2.97 nm in aqueous solution.FYC-1 was also successfully prepared.When FYC-1 was interacted with HCT15 cells,FYC-1 could be better taken up by the cells,indicating that the amphiphilic MYC-1 could be better endocytosed into the cells to exert its function.When MYC-1 and 5-Fu acted in combination in colon cancer R-HCT15 cells,the resistance index(RI)was decreased from 7.99 to 1.55,and the relative reversal rate(RRR)of RI was 80.6%.Live(green)/dead(red)cell staining revealed that MYC-1 increased the toxicity of 5-Fu to R-HCT15 cells.Immunofluorescence staining(P<0.01)and Western blotting indicated that MYC-1 effectively inhibited the intracellular expression of HIF-1α.The combined action of MYC-1 and 5-Fu on mice with R-HCT15 subcutaneous transplanted tumors had the best therapeutic effect when compared with PBS(P<0.001),5-Fu(P<0.01),and MYC-1(P<0.01).Immunofluorescence staining of HIF-1α in tumor tissues displayed that the expression of HIF-1α was decreased in the MYC-1 and MYF groups.HE staining showed that there was no obvious damage to the important organs in each treatment group.Conclusion Nano-inhibitor MYC-1 can reverse the drug resistance of colorectal cancer to 5-Fu chemotherapy by reducing the expression of HIF-1α protein in colorectal cancer cells,thereby effectively improving the therapeutic effect of 5-Fu.

Objective The aim of this study was to characterize the basic molecular and biochemical parameters for a cyclophilin protein in Cryptosporidium parvum called CpCyP1.Methods CpCyP1 expression patterns during the parasite life cycle were evaluated using qRT-PCR with total RNA isolated from different developmental stages of C.parvum.Native CpCyP1 protein in sporozoites was detected using western blot.The localization of CpCyP1 was performed using the immunofluorescence assay,with an affinity-purified rabbit polyclonal antibody against a synthetic peptide.The peptidyl-prolyl cis-trans isomerase(PPIase)activity of His-tagged recombinant CpCyP1 was evaluated using absorbance colorimetry,and the effect of cyclosporin A(CsA)on the activity of CpCyP1 was determined.Results CpCyP1 was expressed in all parasite developmental stages,whereas CpCyP1 was present mainly in the cytosol of sporozoites,meronts,and gamonts.CpCyP1 displayed Michaelis-Menten kinetics towards N-succinyl-Ala-Ala-Pro-Phe-p-nitroanilide for its PPIase activity(Km=456.4 μmol/L;Vmax=1.981 U).CsA inhibited PPIase activity,showing lower micromolar inhibitory activity and binding affinity(Kd=5.122 μmol/L;IC50=1.004 μmol/L).Conclusions These results imply that CpCyP1 in the parasite may be the target for the previously reported anti-cryptosporidial efficacy of CsA and suggest that C.parvum cyclophilins could be evaluated as candidate drug targets.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Aim To investigate the effect of hypobaric hypoxia on macrophage necroptosis and atherosclerotic plaque instability and explore the underlying mechanisms.Methods Mouse bone marrow-derived macrophages were i-solated and cultured,and divided into control group(21％oxygen concentration)and hypoxia group(3％oxygen concen-tration).After 48 hours,cell necroptosis was detected,and the expression of cell necroptosis related proteins was deter-mined by Western blot.Healthy male ApoE-/-mice were randomly divided into control group and hypobaric hypoxia group.After the intervention for 16 weeks,the plasma lipids and inflammatory cytokines were measured,the areas of ath-erosclerotic plaque and necrotic core were evaluated by HE staining.The content of plaque collagen was detected by Mas-son staining.The number of macrophages in the plaque and the expression of necrotic apoptosis related proteins were de-tected by immunohistochemical staining and Western blot.Results Hypoxia induced increased necrotic apoptosis of macrophages(P＜0.01),while necroptotic inhibitor necrostatin-1(Nec-1)reduced hypoxia induced cell death(P＜0.05);hypoxia leads to a decrease in the expression of adenosine deaminase acting on RNA 1(ADAR1)in macrophages(P＜0.01),and an increase in the expression of Z-DNA binding protein 1(ZBP1),phosphorylated receptor-interacting serine/threonine-protein kinase(p-RIPK3),and phosphorylated mixed lineage kinase domain-like protein(p-MLKL)(all P＜0.01).Compared with the control group,the plasma lipid levels of ApoE-/-mice in the hypobaric hypoxia group did not change significantly(P＞0.05),the plasma inflammatory cytokines(TNF-α,IL-1β,IL-6 and MCP-1)increased(all P＜0.05),the area of atherosclerotic plaque increased(P＜0.05),the area of plaque necrotic core increased,the content of plaque collagen decreased,the number of macrophages increased,the expression of ADAR1 decreased,and the expres-sion of ZBP1 and p-MLKL increased(all P＜0.01).Conclusion Hypobaric hypoxia causes the imbalance of A-DAR1/ZBP1 expression in macrophages,activates RIPK3/MLKL signaling pathway,promotes macrophage necroptosis,in-creases the area of plaque necrosis core,and leads to increase instability of atherosclerotic plaque.

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.