Cryo-electron tomography (cryo-ET) enables the determination of high-resolution three-dimensional structures of macromolecular complexes within cells in a near-physiological state, providing crucial structural insights into fundamental life processes. Cryo-ET has achieved landmark successes in single-cell models. However, many critical biological processes do not occur in isolated cells but emerge from intercellular coordination within tissues. Furthermore, many research subjects, including neural tissues, tumor biopsies, plant tissues, and clinical pathological samples, cannot be obtained through single-cell culture and must be directly dissected from organisms or tissue blocks. Advancing cryo-ET from single-cell to tissue-level applications is therefore crucial for capturing the full complexity of biological activities in their native context. A major technical bottleneck for tissue cryo-ET lies in the preparation of sufficiently thin (<300 nm) lamellae from vitrified tissue specimens. Although high-pressure freezing can vitrify tissues up to 200 µm thick, these samples are far too thick for direct transmission electron microscopy imaging. Among the available thinning methods, cryo-focused ion beam (cryo-FIB) milling has emerged as the most promising approach, as it avoids the mechanical artifacts inherent to cryo-ultramicrotomy. However, conventional on-the-grid cryo-FIB milling is inefficient for thick tissues, requiring excessive milling time and discarding most of the sample. To overcome these limitations, cryo-lift-out has been developed—a technique in which a micromanipulator physically extracts a chunk of interest from deep within the tissue and transfers it to a dedicated grid for final thinning. This approach bypasses the thickness barrier and enables site-specific analysis of internal structures. This review systematically traces the evolution of cryo-lift-out from its origins in materials science to its adaptation for biological tissues. In room-temperature lift-out, reliable attachment is achieved by gas-injection system (GIS)-assisted metal deposition. Transferring this approach to cryogenic conditions proved challenging because precursor gases condense on all cold surfaces, leading to contamination and poor adhesion. The development of copper-assisted redeposition marked a critical turning point: instead of relying on gas deposition, this method uses ion-beam sputtering to deposit copper atoms at the needle-chunk interface, creating a strong, low-contamination bond. This innovation has enabled robust cryo-lift-out workflows and paved the way for serial lift-out, in which multiple consecutive lamellae are prepared from a single tissue chunk, substantially increasing throughput and enabling volumetric imaging. Despite these advances, several technical challenges remain. Curtaining effects caused by uneven chunk surfaces can introduce artifacts into tomograms, requiring careful optimization of milling parameters and protective coating. The cryo-adhesion step still demands precise control of beam angle, needle positioning, and milling depth, making the process highly operator-dependent. Additionally, the choice of grid geometry is critical. Custom-designed grids with double-sided attachment improves stability and offer better compatibility with cryo-ET tilt series. Automation, which has greatly improved room-temperature lift-out, has not yet been achieved for cryo-lift-out due to the complexity of handling heterogeneous biological tissues and the need for real-time adaptation. Future progress will likely focus on integrating cryo-lift-out with volume electron microscopy to correlate ultrastructure across scales, developing intelligent control systems to reduce user intervention, and extending the technology to challenging samples such as plant tissues and some material science samples for interface study. A systematic analysis of the cryo-lift-out technique clarifies the key limiting factors for its large-scale application and lays a foundation for methodological refinement and technological innovation. By consolidating recent advances and identifying remaining bottlenecks, this review aims to support the broader adoption of cryo-lift-out and accelerate the development of tissue-scale in situ structural biology.

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.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

ObjectiveTo investigate the mRNA expression profile and clinical significance of the RAB24 gene in hepatocellular carcinoma （HCC） based on multi-source database including The Cancer Genome Atlas （TCGA） and clinical cohort validation. MethodsData from TCGA （n=424） were utilized to evaluate the prognostic value of RAB24 expression via Kaplan-Meier analysis and Cox regression models. An independent clinical cohort comprising 90 HCC and 30 paracancerous tissues was established to validate protein expression and histopathological features through immunohistochemistry （IHC） and routine histological staining. The TIMER database was employed to analyze the association between RAB24 and the tumor microenvironment （TME）. Furthermore， integrated with LinkedOmics， GSEA and GSVA algorithms were used to quantitatively characterize the core molecular pathways regulated by RAB24. ResultsThe mRNA expression level of RAB24 in HCC was significantly higher than that in non-tumor liver tissues （P<0.05）. Kaplan-Meier analysis revealed that the overall survival （OS） of patients in the RAB24 low-expression group was significantly longer compared to the high-expression group （HR=1.570， Log-rank P=0.01）. Cox proportional hazards regression analysis demonstrated that RAB24 expression （HR=1.480， P=0.028）， T stage （HR=2.949， P<0.001）， M stage （HR=4.077， P=0.017）， and tumor residual status （HR=2.317， P<0.001） were independent prognostic factors for HCC. RAB24 expression was highly correlated with alpha-fetoprotein （AFP） levels and immune infiltration levels （P<0.01）， and showed a significant， low-level positive correlation with the TP53 gene （Rho=0.31， P<0.01）. Quantitative analysis of the RAB24 protein in clinical samples validated that RAB24 expression in HCC tissues was significantly elevated compared to non-tumor liver tissues （P<0.05）. TIMER analysis confirmed that RAB24 expression was highly associated with the infiltration of multiple immune cells （such as B cells and NK cells）， as well as stromal and tumor purity scores in tumor tissues （P<0.01）. GSEA/GSVA enrichment revealed that the P53， MYC， and mTORC1 signaling pathways were activated in the RAB24 high-expression group； correlation analysis confirmed that the RAB24 expression level exhibited a significant， low-level positive correlation with the ribosome pathway activity score （r=0.23， P<0.01）. ConclusionsThe RAB24 gene， as a poor prognostic factor for HCC patients， is a potential biomarker for HCC diagnosis， treatment and prognosis. The study is expected to lay a theoretical foundation for the precise diagnosis and treatment of clinical HCC.

Objective To compare postoperative major adverse events in patients with triple-vessel disease undergoing complete versus incomplete revascularization during coronary artery bypass grafting (CABG). Methods A retrospective analysis was conducted on patient data from Tianjin Chest Hospital who underwent primary isolated CABG surgery between 2019 and 2020. Patients were divided into a complete revascularization group and an incomplete revascularization group based on the revascularization status. Inverse probability of treatment weighting (IPTW) was used for risk adjustment. Results A total of 1 419 patients were included in the study, with 1 086 (76.5%) undergoing complete revascularization. IPTW analysis showed that complete revascularization could reduce the incidence of major adverse cardiovascular and cerebrovascular events [HR=0.596, 95%CI (0.404, 0.880), P=0.010] and angina [HR=0.560, 95%CI (0.377, 0.823), P=0.004]. Conclusion In patients with multivessel coronary artery disease, complete revascularization may be associated with improved patient outcomes.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

Objective To analyze the PLCβ4 gene mRNA expression and its clinical significance in hepatocellular carcinoma (HCC) based on TCGA database. Methods Based on the data on 424 clinical samples (including 374 cases of HCC tissues and 50 cases of nontumor liver tissues) in the TCGA database, Kaplan–Meier method, Cox regression analysis, and immune infiltration analysis were performed to evaluate the relationship between PLCβ4 gene and the clinical characteristics and survival prognosis of HCC patients. Correlation analysis between PLCβ4 gene and 24 types of immune cells was applied to investigate the relationship between PLCβ4 gene and immune cell infiltration and mRNA expression level of TP53 gene, a high-frequency mutation gene in HCC. In addition, paraffin sections of highly, moderately, and poorly differentiated tumor tissues and normal liver tissues from HCC patients were collected. The histopathological observation was carried out via HE staining method, and the expression levels of PLCβ4 and Ki-67 proteins in each clinical sample were verified through the immunohistochemical method. Results The expression level of PLCβ4 gene in HCC was significantly higher than that in normal tissues (P<0.01), and all patients in the PLCβ4 high-expression group had a significantly longer overall survival than those in the low-expression group (P<0.05), which suggested that PLCβ4 substantially affected the prognosis of HCC patients. Correlation analysis showed that the expression level of PLCβ4 gene was highly correlated with immune cell infiltration and the expression level of TP53 gene. As verified by clinical sample experiments, HE staining experiments and immunohistochemical results revealed that PLCβ4 gene expression in HCC tissue samples was significantly higher than that in normal tissues (P<0.001), and it was negatively correlated with the degree of differentiation. Conclusion PLCβ4 may serve as an independent prognostic factor in HCC and is expected to be a novel molecular target for HCC treatment.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

BACKGROUND:The highest incidence of spinal fracture is in the thoracolumbar segment,and its symptoms are back pain,posterior convexity deformity,activity limitation,or with spinal cord nerve injury causing lower limb pain,numbness,and even paraplegia and other complications.The finite element method is a digital computer modeling technique,which can simulate the physical model and carry out force analysis realistically.OBJECTIVE:To review the application of finite element method in thoracolumbar spine fractures.METHODS:We searched the Chinese and English literature databases PubMed,Web of Science,and CNKI for relevant literature on the application of the finite element analysis method in spinal thoracolumbar fracture published before March 2024.The search terms in Chinese and English were:finite element analysis methods,biomechanical phenomena,stress analysis,thoracolumbar fractures,spinal fractures.Finally,55 papers were included.RESULTS AND CONCLUSION:(1)The exploration of thoracolumbar fractures caused by different etiologies(osteoporotic,traumatic,and pathological)through the finite element method is conducive to a deeper understanding of the biomechanics of various types of thoracolumbar fractures,and to improve the individualized and fine-tuned treatment of thoracolumbar fractures.(2)The finite element analysis of a single sample or a small number of samples has the chance,and a larger number of samples are required for the future finite element analysis to reduce the chance caused by the sample.(3)The rigid structure of bones alone cannot meet the biomechanical working conditions of the integrity of the physical object,and future finite element models need to incorporate all the structures of the physical object(e.g.,soft tissues,such as muscles and ligaments)as far as possible.(4)The finite element method has been used in more studies on osteoporotic and traumatic thoracolumbar spine fractures,which will need to be more in-depth in the future,and less in the field of pathologic thoracolumbar fractures,which has a wider scope for future research.