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.

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.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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.

With the rapid development of competitive sports, the incidence of anterior cruciate ligament (ACL) injury is on the rise. Such injuries may shorten athletes′ career and lead to other long-term adverse consequences. Although athletes generally recover well after ACL reconstruction, many still struggle to return to their pre-injury performance levels. Advances in the understanding of ACL anatomy and injury mechanisms, along with the evolution of surgical techniques and rehabilitation methods, have provided more individualized and tailored options for athletes following ACL injuries. However, there is currently no consensus in China regarding surgical and rehabilitation strategies for competitive athletes aiming to return to sports after ACL injuries. To this end, the Sports Medicine Committee of the Chinese Research Hospital Association and the Editorial Board of the Chinese Journal of Trauma jointly formulated the Expert consensus on surgical treatment and rehabilitation for competitive sports athletes returning to sports after anterior cruciate ligament injury ( version 2025), and presented 14 recommendations covering surgical indications, preoperative rehabilitation, surgical timing, surgical strategies and postoperative rehabilitation strategies, aiming to improve the surgical treatment and rehabilitation system for ACL injuries in competitive athletes and facilitate their return to high-level sports performance after injury.

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.

Objective:To investigate lymph node metastasis(LNM)in the prostatic anterior fat pad(PAFP)of PCa patients after robot-assisted radical prostatectomy(RARP),and analyze the clinicopathological features and prognosis of LNM in the PAFP.Methods:We retrospectively analyzed the clinicopathological data on 1 003 cases of PCa treated by RARP in the Department of Urolo-gy of PLA General Hospital from January 2017 to December 2022.All the patients underwent routine removal of the PAFP during RARP and pathological examination,with the results of all the specimens examined and reported by pathologists.Based on the pres-ence and locations of LNM,we grouped the patients for statistical analysis,compared the clinicopathological features between different groups using the Student's t,Mann-Whitney U and Chi-square tests,and conducted survival analyses using the Kaplan-Meier and Log-rank methods and survival curves generated by Rstudio.Results:Lymph nodes were detected in 77(7.7％)of the 1 003 PAFP samples,and LNM in 11(14.3％)of the 77 cases,with a positive rate of 1.1％(11/1 003).Of the 11 positive cases,9 were found in the upgraded pathological N stage,and the other 2 complicated by pelvic LNM.The patients with postoperative pathological stage≥T3 constituted a significantly higher proportion in the PAFP LNM than in the non-PAFP LNM group(81.8％[9/11]vs 36.2％[359/992],P=0.005),and so did the cases with Gleason score ≥8(87.5％[7/8]vs 35.5％[279/786],P=0.009).No statisti-cally significant differences were observed in the clinicopathological features and biochemical recurrence-free survival between the pa-tients with PAFP LNM only and those with pelvic LNM only.Conclusion:The PAFP is a potential route to LNM,and patients with LNM in the PAFP are characterized by poor pathological features.There is no statistically significant difference in biochemical recur-rence-free survival between the patients with PAFP LNM only and those with pelvic LNM only.Routine removal of the PAFP and inde-pendent pathological examination of the specimen during RARP is of great clinical significance.

Objective:To experimentally validate clinical samples, analyze the mRNA expression of the FYVE domain containing phosphatidylinositol 3-phosphate 5 kinase ( PIKFYVE) gene, and its clinical significance based on the Cancer Genome Atlas (TCGA) database in hepatocellular carcinoma (HCC). Methods:Data information on 424 clinical samples (including 374 cases of HCC tissues and 50 cases of non-tumorous liver tissues) were collected based on the TCGA database. Cox regression analysis and the Kaplan-Meier method were used to analyze the relationship between mRNA expression of the PIKFYVE gene and the clinical characteristics as well as survival prognosis in patients with HCC. The relationship between the PIKFYVE gene and immune cell infiltration was examined by correlation analysis with 24 kinds of immune cells. In addition, the mRNA expression level of the PIKFYVE gene and RAC-alpha serine/threonine-protein kinase ( AKT1), phosphatase and tensin homolog ( PTEN), protein kinase C alpha ( PRKCA), inositol polyphosphate-5-phosphatase ( INPP5D), phosphoinositide-3-kinase regulatory subunit 1 ( PIK3R1), inositol polyphosphate 4-phosphatase type II ( INPP4B) and phospholipase C beta 4 ( PLCB4) gene correlations were analyzed in HCC tissues. At the same time, paraffin sections of highly differentiated, moderately differentiated, poorly differentiated, and non-tumor liver tissues from patients with HCC were collected from the Department of Pathology of the First Affiliated Hospital of Xinjiang Medical University. The histopathological observation was performed by HE staining. Immunohistochemistry was used to verify the expression levels of the PIKFYVE and Ki67 proteins in each clinical sample. The t-test was used for intergroup comparison of continuous data. The χ2 test and Wilcoxon rank sum test were used for intergroup comparison of enumeration data. The Kaplan-Meier method was used for survival analysis. Results:The expression level of the PIKFYVE gene was higher in the HCC tumor than that in normal liver tissue ( P<0.01). The overall survival time of patients was significantly longer in the low expression group than that in the high expression group ( HR=1.57, 95% CI: 1.10～2.25, P=0.014). The results of univariate Cox regression analysis showed that tumor stage, pathological grade, tumor status, residual tumor, and PIKFYVE expression level all had an effect on OS ( P<0.05). The PIKFYVE prognostic risk model had a proportionate score of HR=1.533 (95% CI: 1.077～2.181, P=0.018). Multivariate Cox risk regression analysis showed that the PIKFYVE prognostic risk model had a proportionate score of HR=1.481 (95% CI: 0.886～2.476, P=0.134) and an area under the receiver operating characteristic curve of 0.559, indicating that it had predictive value for survival prediction. The results of the correlation analysis showed that the expression level of PIKFYVE was strongly correlated with immune cell infiltration and TP53 ( P<0.01). The results of immunohistochemical staining showed that the expression level of PIKFYVE was significantly higher in HCC tissue samples than that in non-tumor liver tissues ( P<0.01), and was negatively correlated with the degree of differentiation. Conclusion:PIKFYVE, as an independent risk factor, is expected to be developed into a biomarker for clinical diagnosis, offering a reference for novel therapeutic agents in HCC.