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.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

ObjectiveTo establish a rat model of osteoarthritis and study the anti-inflammatory effects and mechanisms of fraxetin. MethodsEighteen 8-week-old male SPF-grade SD rats were randomly divided into three groups: Rats in the blank group received a right articular cavity injection of 50 μL of normal saline for 1 week; the model and intervention groups were injected with monosodium iodoacetate (MIA) into the right joint cavity to induce osteoarthritis, while the intervention group subsequently received fraxetin (5 mg·kg^-1·d^-1) for 1 week. Four weeks after drug intervention, abdominal aortic blood was collected. The animals were then euthanized, and knee joint cartilage were collected. The cartilage samples were stained with hematoxylin-eosin, safranin O-fast green, and toluidine blue for histopathological examination and scoring using the Mankin and OARSI scoring systems. The trabecular bone volume/total volume (Tb.BV/TV), trabecular bone surface density/total volume (Tb.BS/TV), and trabecular number (Tb.N) of each group were compared and analyzed using a micro-CT scanning system. The expression levels of various inflammatory factors [tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6)], and cartilage oligomeric matrix protein (COMP) were measured using enzyme-linked immunosorbent assay (ELISA). The expression levels of mitogen-activated protein kinase p38 (p38 MAPK), phosphorylation-p38 MAPK (p-p38 MAPK), c-Jun N-terminal kinase (JNK), and phosphorylation-JNK (p-JNK) were measured by western blotting. ResultsThe staining of cartilage sections of rat knee joints showed that the articular surface defects in the model group were severe, while the cartilage destruction in the intervention group was relatively reduced. Micro-CT results showed that Tb.BV/TV, Tb.BS/TV and Tb.N in the intervention group were significantly higher than those in the model group (P < 0.05); the Mankin score in the model group was significantly higher than that in the blank group (P < 0.05), the Mankin score in the intervention group was significantly lower than that in the model group (P < 0.05); while the OARSI score in the intervention group was significantly lower than that in the model group (P < 0.05). The results of the enzyme-linked immunosorbent assay showed that the serum levels of TNF-α, IL-1β, IL-6, and COMP in the model group were significantly higher than those in the blank group (all P < 0.05), while those in the intervention group were significantly lower than in the model group (P < 0.05). Western blot results showed that the expression levels of p-p38 MAPK and p-JNK in the knee cartilage tissue were significantly lower in the intervention group than in the model group (both P < 0.05), and significantly higher in the model group than in the blank group (both P < 0.05). ConclusionFraxetin may play a therapeutic role in a monosodium iodoacetate-induced rat model of osteoarthritis through the p38 MAPK pathway.

ObjectiveTo establish a rat model of osteoarthritis and study the anti-inflammatory effects and mechanisms of fraxetin. MethodsEighteen 8-week-old male SPF-grade SD rats were randomly divided into three groups: Rats in the blank group received a right articular cavity injection of 50 μL of normal saline for 1 week; the model and intervention groups were injected with monosodium iodoacetate (MIA) into the right joint cavity to induce osteoarthritis, while the intervention group subsequently received fraxetin (5 mg·kg^-1·d^-1) for 1 week. Four weeks after drug intervention, abdominal aortic blood was collected. The animals were then euthanized, and knee joint cartilage were collected. The cartilage samples were stained with hematoxylin-eosin, safranin O-fast green, and toluidine blue for histopathological examination and scoring using the Mankin and OARSI scoring systems. The trabecular bone volume/total volume (Tb.BV/TV), trabecular bone surface density/total volume (Tb.BS/TV), and trabecular number (Tb.N) of each group were compared and analyzed using a micro-CT scanning system. The expression levels of various inflammatory factors [tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6)], and cartilage oligomeric matrix protein (COMP) were measured using enzyme-linked immunosorbent assay (ELISA). The expression levels of mitogen-activated protein kinase p38 (p38 MAPK), phosphorylation-p38 MAPK (p-p38 MAPK), c-Jun N-terminal kinase (JNK), and phosphorylation-JNK (p-JNK) were measured by western blotting. ResultsThe staining of cartilage sections of rat knee joints showed that the articular surface defects in the model group were severe, while the cartilage destruction in the intervention group was relatively reduced. Micro-CT results showed that Tb.BV/TV, Tb.BS/TV and Tb.N in the intervention group were significantly higher than those in the model group (P < 0.05); the Mankin score in the model group was significantly higher than that in the blank group (P < 0.05), the Mankin score in the intervention group was significantly lower than that in the model group (P < 0.05); while the OARSI score in the intervention group was significantly lower than that in the model group (P < 0.05). The results of the enzyme-linked immunosorbent assay showed that the serum levels of TNF-α, IL-1β, IL-6, and COMP in the model group were significantly higher than those in the blank group (all P < 0.05), while those in the intervention group were significantly lower than in the model group (P < 0.05). Western blot results showed that the expression levels of p-p38 MAPK and p-JNK in the knee cartilage tissue were significantly lower in the intervention group than in the model group (both P < 0.05), and significantly higher in the model group than in the blank group (both P < 0.05). ConclusionFraxetin may play a therapeutic role in a monosodium iodoacetate-induced rat model of osteoarthritis through the p38 MAPK pathway.

Objective:To investigate and assess the situation of popularization and promotion of domestically innovative medical devices in Liaoning Province,so as to provide a basis for promoting the allocation policy of domestically innovation medical devices.Methods:Self-made questionnaire and on-site filling survey were conducted to implement investigation and analysis for the allocation situation of newly medical equipment of 188 medical institutions in 9 demonstration regions of the Project on Regional Application and Demonstration of Innovative Medical Equipment in Liaoning Province from 2015 to 2020.The allocation data of medical equipment between before(from 2015 to 2017)and after the demonstration projects were implemented(from 2018 to 2020)were compared.The occupancy rate of domestically medical devices(referred as"occupancy ratio of domestic device")was used as an evaluation indicator to assess the status of equipment allocation and application before and after the projects of application and demonstration were implemented in the region of innovative equipment for diagnosis and treatment.Results:In the 9 demonstrational regions of Liaoning province,the number of newly added domestic medical devices during the period from 2018 to 2020 increased from 1,608 units between 2015 and 2017 to 1,703 units.The occupancy ratio of newly added domestic devices increased from 72.7%to 84.9%.The occupancy ratio of domestic devices of newly added key equipment increased from 63.0%to 83.4%,and the growth rate reached 20.4%.In different districts and different grades of medical institution,the increase and application of domestically medical devices appeared difference.Conclusion:The occupancy rate of newly added domestically medical devices in 9 demonstration regions in Liaoning province has generally increased.However,there are still imbalances between different regions and different grades of medical institutions.The manufacturers of domestically medical devices still need strengthen brand building and marketing promotion,so as to further enhance market competitiveness of domestically medical devices.

This study aimed to investigate the correlation between changes in intestinal toxicity and compositional alterations of Euphorbiae Ebracteolatae Radix(commonly known as Langdu) before and after milk processing, and to explore the detoxification mechanism of milk processing. Mice were intragastrically administered the 95% ethanol extract of raw Euphorbiae Ebracteolatae Radix, milk-decocted(milk-processed), and water-decocted(water-processed) Euphorbiae Ebracteolatae Radix. Fecal morphology, fecal water content, and the release levels of inflammatory cytokines tumor necrosis factor-α(TNF-α) and interleukin-1β(IL-1β) in different intestinal segments were used as indicators to evaluate the effects of different processing methods on the cathartic effect and intestinal inflammatory toxicity of Euphorbiae Ebracteolatae Radix. LC-MS/MS was employed to analyze the small-molecule components in the raw product, the 95% ethanol extract of the milk-processed product, and the milky waste(precipitate) formed during milk processing, to assess the impact of milk processing on the chemical composition of Euphorbiae Ebracteolatae Radix. The results showed that compared with the blank group, both the raw and water-processed Euphorbiae Ebracteolatae Radix significantly increased the fecal morphology score, fecal water content, and the release levels of TNF-α and IL-1β in various intestinal segments(P<0.05). Compared with the raw group, all indicators in the milk-processed group significantly decreased(P<0.05), while no significant differences were observed in the water-processed group, indicating that milk, as an adjuvant in processing, plays a key role in reducing the intestinal toxicity of Euphorbiae Ebracteolatae Radix. Mass spectrometry results revealed that 29 components were identified in the raw product, including 28 terpenoids and 1 acetophenone. The content of these components decreased to varying extents after milk processing. A total of 28 components derived from Euphorbiae Ebracteolatae Radix were identified in the milky precipitate, of which 27 were terpenoids, suggesting that milk processing promotes the transfer of toxic components from Euphorbiae Ebracteolatae Radix into milk. To further investigate the effect of milk adjuvant processing on the toxic terpenoid components of Euphorbiae Ebracteolatae Radix, transmission electron microscopy(TEM) was used to observe the morphology of self-assembled casein micelles(the main protein in milk) in the milky precipitate. The micelles formed in casein-terpenoid solutions were characterized using particle size analysis, fluorescence spectroscopy, ultraviolet spectroscopy, and Fourier-transform infrared(FTIR) spectroscopy. TEM observations confirmed the presence of casein micelles in the milky precipitate. Characterization results showed that with increasing concentrations of toxic terpenoids, the average particle size of casein micelles increased, fluorescence intensity of the solution decreased, the maximum absorption wavelength in the UV spectrum shifted, and significant changes occurred in the infrared spectrum, indicating that interactions occurred between casein micelles and toxic terpenoid components. These findings indicate that the cathartic effect of Euphorbiae Ebracteolatae Radix becomes milder and its intestinal inflammatory toxicity is reduced after milk processing. The detoxification mechanism is that terpenoid components in Euphorbiae Ebracteolatae Radix reassemble with casein in milk to form micelles, promoting the transfer of some terpenoids into the milky precipitate.
Animals ; Mice ; Milk/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Male ; Tumor Necrosis Factor-alpha/immunology* ; Intestines/drug effects* ; Interleukin-1beta/immunology* ; Tandem Mass Spectrometry ; Female

This paper aimed to explore the intestinal toxicity of Euphoriae Ebracteolata Radix(EER) before and after being processed with Mongolian medicine Hezi Decoction(HZD) and the toxicity-reducing mechanism of this processing method. The intestinal toxicity in rats treated with unprocessed EER and HZD-processed EER extracts via 95% ethanol was compared. The comparison was based on several indicators, including fecal volume, serum diamine oxidase(DAO) and D-lactate(D-LA) levels, the water content of various intestinal segments and their contents, and inflammatory factor levels in intestinal segments. Tandem mass tag(TMT) quantitative proteomics technology was employed to analyze the key proteins associated with changes in intestinal toxicity between unprocessed EER and HZD-processed EER. The results indicated that compared with the blank group, unprocessed EER significantly increased the fecal volume, serum DAO and D-LA levels, water content of the ileal segment and its contents, as well as the release levels of inflammatory factors, including tumor necrosis factor(TNF-α) and interleukin-1 beta(IL-1β) in the ileal segment of rats(P<0.05), indicating that EER can cause diarrhea, increase intestinal permeability, and induce intestinal inflammation. Compared with those in the unprocessed EER group, all indicators in the HZD-processed EER group were significantly reduced(P<0.05). The TMT quantitative proteomics analysis revealed that a total of 6 487 proteins were identified in the rat ileum tissue. Compared to the blank group, 182 proteins exhibited significant changes in the unprocessed EER group, while 907 proteins in the HZD-processed EER group showed significant changes. The intersection of the differential proteins between the two groups identified 38 common proteins. Among them, the protein levels of intestinal barrier tight junction protein claudin3, squalene monooxidase(Sqle), clusterin, Na~+/H~+ exchange regulatory cofactor NHE-RF3(Pdzk1), and Y+L amino acid transporter 1(Slc7a7) exhibited significant changes before and after processing, and these changes were closely related to intestinal barrier function. Compared with the blank group, the expression of claudin3, Pdzk1, and Slc7a7 in the raw product group was significantly down-regulated(P<0.05),while the expression of Sqle and clusterin was significantly up-regulated(P<0.05).Compared with the raw product group, the expression of claudin3, Pdzk1, and Slc7a7 in the processed product group of HZD was significantly up-regulated(P<0.05), while the expression of Sqle and clusterin was significantly down-regulated(P<0.05). Western blot was used to detect the expression level of claudin 3 in the ileum of rats in each group. The results show that compared to that in the blank group, the expression level of claudin 3 in the unprocessed EER group was significantly reduced(P<0.01); compared to that in the unprocessed EER group, the expression level of claudin 3 in the HZD-processed EER group was significantly increased(P<0.01). This finding aligned with the proteomic outcomes, indicating that claudin 3 protein levels could serve as a crucial indicator for intestinal damage caused by EER. In summary, HZD-processed EER can reduce EER's intestinal toxicity, and the primary mechanism for its alleviation of intestinal barrier damage is the regulation of the intestinal barrier tight junction protein claudin 3 and other intestinal-related proteins.
Animals ; Drugs, Chinese Herbal/adverse effects* ; Proteomics ; Rats ; Male ; Rats, Sprague-Dawley ; Intestines/drug effects* ; Intestinal Mucosa/drug effects* ; Tumor Necrosis Factor-alpha/metabolism*

OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models

OBJECTIVE: To explore a predictive model that can better predict the prognosis of patients with diffuse large B-cell lymphoma (DLBCL), and validate its clinical value. METHODS: Clinical data of 134 newly treated DLBCL patients were collected from Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2015 to January 2020. Several risk factors of the patients were screened and analyzed, a novel prognostic model were then established based on this, and its clinical application potential was validated. RESULTS: In the novel model, predicting progression-free survival (PFS) based on the age at initial treatment, albumin level, Hans classification, Ann Arbor stage, and BCL2 expression showed better predictive performance than International Prognostic Index (IPI) score (AUC: 0.788 vs 0.620，P <0.001). Predicting overall survival (OS) based on the age at initial treatment, albumin level, lactate dehydrogenase (LDH) level, and expressions of BCL2 and MUM1 proteins also showed better predictive performance for mortality risk than IPI score (AUC: 0.817 vs 0.624，P <0.001). CONCLUSION This novel prognostic model can better predict the survival prognosis of DLBCL patients compared to the IPI scoring system.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Prognosis ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Risk Factors ; Male ; Female ; Middle Aged