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Abstract Purpose Prostate cancer (PCa) is a common malignancy in men, with an escalating mortality rate attributed to Recurrence and metastasis. Recent studies have illuminated collagen’s critical regulatory role within the tumor microenvironment, significantly influencing tumor progression. Accordingly, this investigation is dedicated to examining the relationship between genes linked to collagen and the prognosis of PCa, with the objective of uncovering any possible associations between them. Methods Gene expression data for individuals with prostate cancer were obtained from the TCGA repository. Collagen-related genes were identified, leading to the development of a risk score model associated with biochemical recurrence-free survival (BRFS). A prognostic nomogram integrating the risk score with essential clinical factors was crafted and evaluated for efficacy. The influence of key collagen-related genes on cellular behavior was confirmed through various assays, including CCK8, invasion, migration, cell cloning, and wound healing. Immunohistochemical detection was used to evaluate PLOD3 expression in prostate cancer tissue samples. Results Our study identified four key collagen-associated genes (PLOD3, COL1A1, MMP11, FMOD) as significant. Survival analysis revealed that low-risk groups, based on the risk scoring model, had significantly improved prognoses. The risk score was strongly associated with prostate cancer prognosis. Researchers then created a nomogram, which demonstrated robust predictive efficacy and substantial clinical applicability.Remarkably, the suppression of PLOD3 expression notably impeded the proliferation, invasion, migration, and colony formation capabilities of PCa cells. Conclusion The risk score, derived from four collagen-associated genes, could potentially act as a precise prognostic indicator for BRFS of patients. Simultaneously, our research has identified potential therapeutic targets related to collagen. Notably, PLOD3 was differentially expressed in cancer and para-cancer tissues in clinical specimens and it also was validated through in vitro studies and shown to suppress PCa tumorigenesis following its silencing.

Abstract Background Studies have indicated a close association between genes linked to liquid–liquid phase separation (LLPS) and the progression of prostate cancer (PCa). However, the interplay among long non-coding RNAs (lncRNAs) linked to LLPS in PCa remains elusive. Therefore, we constructed a prediction model based on LLPS-related LncRNA in PCa to explore its relationship with the prognosis and drug treatment of PCa. Methods We obtained clinical and sequencing data from TCGA and LLPS genes from the Phase Separation Protein Database. By analyzing the differential expression of LLPS-related genes and lncRNAs in prostate cancer, and using Poisson correlation, we identified LLPS-related lncRNAs. Prognostic LLPS-lncRNAs were found through prognostic correlation analysis and included in a Cox model to compute regression coefficients. Patients were scored and divided into high- and low-risk groups. Independent prognostic factors were integrated into a prognostic nomogram with risk and Gleason scores. We also conducted drug sensitivity analyses, GSEA, and validated the impact of key lncRNAs through functional experiments. Results Our study identified five LLPS-associated lncRNAs that are of prognostic importance. And found notable disparities in biochemical recurrence rates and survival outcomes between these risk groups, with the low-risk cohort exhibiting superior prognostic indicators. Moreover, our prediction nomogram demonstrated robust predictive accuracy and significant clinical utility. Furthermore, our model exhibited promising capabilities in forecasting patient sensitivity to various conventional therapeutic drugs, thereby highlighting its potential in personalized treatment strategies. GSEA showed that these lncRNAs may influence PCa prognosis and sensitivity to therapeutic agents by affecting pathways such as cell cycle. Knockdown of AC009812.4 could inhibit the ability of PCa cells to proliferate, migrate and invade, and compare to paracancerous tissue, AC009812.4 in PCa tissue has significantly higher expression. Conclusion Our research uncovers the prognostic significance of lncRNAs associated with LLPS in PCa and established a model exhibiting excellent predictive accuracy for prognosis. Those lncRNAs may influence progress of PCa as well as sensitivity to therapy drugs through pathways such as cell cycle.

Freeze-thaw cycles (FTC) cause significant changes in the physical and mechanical properties of soil, leading to structural alterations that can seriously threaten the safety and longevity of engineering structures. To investigate the consolidation characteristics of soils subjected to FTC, 18 sets of consolidation compression tests were carried out with saturated clay. Using a modified consolidation apparatus, the changes in pore-water pressure (PWP) and strain during consolidation were measured, with a focus on the effects of dry density and the number of FTC. The results show that although the overall patterns of PWP and strain during consolidation are similar before and after FTC, variations in dry density and the number of FTC lead to significant differences in the measured values. Specifically, PWP decreases while soil deformation increases with an increasing number of FTC cycles, even across different dry density conditions. The most pronounced changes in PWP and strain occur during the first 1–3 FTC cycles, with some samples showing continued significant changes up to 3–5 cycles. However, beyond five FTC, the increments in PWP and strain become considerably smaller. Meanwhile, an approximate linear relationship was observed between the peak PWP and steady-state strain values during graded loading, with this linearity decreasing as dry density increases. In addition, the Burgers model was modified based on the measured dissipation pattern of PWP to overcome the shortcomings of the traditional Burgers model. The modified Burgers model provides a more accurate representation of the soil's deformation process following FTC compared to the traditional model. This study can provide theoretical guidance for predicting the deformation of soils after freeze-thaw cycles.

Purpose To assess whether gray-scale ultrasound (US) based radiomic features can help distinguish HER2 expressions (ie, HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing) in breast cancer. Materials and Methods This retrospective study encompassed female breast cancer patients who underwent US examinations at two distinct centers from February 2021 to July 2023. Tumor segmentation and radiomic feature extraction were performed on grayscale US images. Decision Tree analysis was employed to simultaneously evaluate feature importance, and the Least Absolute Shrinkage and Selection Operator technique was utilized for feature selection to construct the radiomic signature. The Area Under the Curve (AUC) of the Receiver Operating Characteristic curve was employed to assess the performance of the radiomic features. Multivariate logistic regression was used to identify independent predictors for distinguishing HER2 expression in the dataset. Results The training set comprised 292 patients from Center 1 (median, 51 years; interquartile range [IQR]: 45-61), while the external validation set included 131 patients from Center 2 (median, 51 years; IQR: 45-62). In the external validation dataset, the radiomic features achieved AUC of 0.76 for distinguishing between HER2-low and positive tumors versus HER2-zero tumors. The AUC for differentiating HER2-low (1+) from HER2-zero tumors was 0.74, and for distinguishing HER2-low (2+) from HER2-zero tumors, the AUC was 0.77. In the multivariate analysis assessing HER2-low and HER2-positive versus HER2-zero tumors, internal echoes (P = .029) and margins (P

ABSTRACT Background Early detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels. Methods A mixed‐cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set. Results The BCaS3miR model, utilizing only three serum miRNAs (miR‐6087, miR‐1343‐3p, and miR‐5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984–0.991), 0.964 (95% CI: 0.936–0.984), and 0.917 (95% CI: 0.836–0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR‐1343‐3p/miR‐6087 and miR‐5100/miR‐6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages. Conclusions Using a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.

Abstract A high‐temperature superconducting (HTS) dynamo flux pump can inject DC currents into closed‐loop HTS magnets without contact. It enables the realisation of current‐lead‐free or even through‐wall charging systems for high‐field applications such as nuclear magnetic resonance/magnetic resonance imaging (MRI) magnets, fusion reactors and accelerators. Researchers have proposed many simulation models to understand the working principle of HTS dynamos, few of which are in 3D because of converging problems. Therefore, the influences of many key 3D parameters in the HTS dynamo are scarcely reported. The authors propose an efficient 3D modelling method of the HTS dynamo based on the T‐A formulation. The rotating magnets are modelled by a ring‐shaped permanent magnet with space‐time‐variant remanent flux density to avoid moving meshes. This, together with the T‐A formulation, makes the 3D model efficient and universal. The accuracy of the model is verified by the experimental instantaneous and time‐integrated dynamic voltages. Using this model, the authors present systematic case studies to thoroughly explore the influences of the key parameters of a dynamo flux pump on the dynamic voltage and losses. The proposed modelling method and results could significantly benefit the design and optimisation of HTS dynamos for high‐field magnets.

Abstract Purpose Prostate cancer (PCa) is one of the major tumor diseases that threaten men’s health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two. Methods Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted. Results The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue. Conclusions A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.

Abstract Objective The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization. Methods Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat‐sen Memorial Hospital of Sun Yat‐sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c‐index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model. Results A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c‐index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system. Conclusion Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision‐making processes.

Abstract Objective Buccal mucosa cancer (BMC) is one of the most common oral cancers and has poor prognosis. The study aimed to develop and validate nomograms for predicting the 1‐, 3‐, and 5‐year overall survival (OS) and cancer‐specific survival (CSS) of BMC patients. Methods We collected and reviewed information on BMC patients diagnosed between 2004 and 2019 from the Surveillance Epidemiology and End Results database. Two nomograms were developed and validated to predict the OS and CSS based on predictors identified by univariate and multivariate Cox regression. An extra external validation was further performed using data from Sun Yat‐sen Memorial Hospital (SYSMH). Results A total of 3154 BMC patients included in this study were randomly assigned to training and validation groups in a 2:1 ratio. Independent prognostic predictors were identified, confirmed, and fitted into nomograms for OS and CSS, respectively. The C‐indices are 0.767 (Training group OS), 0.801 (Training group CSS), 0.763 (Validation group OS), and 0.781 (Validation group OS), respectively. Moreover, the nomograms exhibited remarkable precision in forecasting and significant clinical significance, as evidenced by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA). The final validation using our data from SYSMH also showed high accuracy and substantial clinical benefits within the nomograms. The C‐indices are 0.849 (SYSMH group OS) and 0.916 (SYSMH group CSS). These indexes are better than tumor, node, and metastasis stage based on prediction results. Conclusions The nomograms developed with great performance predicted 1‐, 3‐, and 5‐year OS and CSS of BMC patients. Use of the nomograms in clinical practices shall bring significant benefits to BMC patients.

The fibroblast growth factor receptor (FGFR) is a crucial receptor tyrosine kinase involved in essential biological processes, including growth, development, and tissue repair. However, FGFR gene mutations, including amplification, fusion, and mutation, can disrupt epigenetics, transcriptional regulation, and tumor microenvironment interactions, leading to cancer development. Targeting these kinase mutations with small molecule drugs or antibodies has shown clinical benefits. For example, erdafitinib is approved for treating locally advanced or metastatic urothelial cancer patients with FGFR2/FGFR3 mutations, and pemigatinib is approved for treating cholangiocarcinoma with FGFR2 fusion/rearrangement. Effective screening of FGFR variant patients is crucial for the clinical application of FGFR inhibitors. Various detection methods, such as polymerase chain reaction, next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry, are available, and their selection should be based on diagnostic and treatment decision-making needs. Our developed expert consensus aims to standardize the diagnosis and treatment process for FGFR gene mutations and facilitate the practical application of FGFR inhibitors in clinical practice.

Abstract In order to strengthen the overall planning and coordination of urban construction and ecological space in Baishan City, we should formulate a scientific land type planning of Production-Living-Ecological Space (PLES). In this paper, land use dynamic attitude model, land use transfer matrix, land use function center of gravity transfer model, eco-environmental quality index(EEQI) and geographic detector model are used to discuss the spatio-temporal evolution of PLES in Baishan City from 2000 to 2020. Spatio-temporal evolution of EEQI and its influencing factors. The results show that: (1) During the study period, Baishan City showed the characteristics that the production space first increased and then decreased, the ecological space decreased, and the living space continued to increase. Among them, the ecological space is the dominant space of Baishan City, covering an area of more than 80%. From the perspective of the transformation of PLES, from 2000 to 2020, Baishan City is mainly characterized by the transformation of ecological space into production space and living space. In the second type of space, green ecological space, forestry ecological space and other ecological space have decreased, while other types of space have increased in varying degrees. (2) During the study period, the overall EEQI of Baishan City remained in good condition, and the ecological environment quality(EEQ) of the three periods were 0.6571, 0.6412 and 0.6562 respectively. The higher EEQI is distributed in Changbai County and Linjiang City, while the areas with lower EEQI are concentrated in the north-central part of Hunjiang City, the middle part of Jiangyuan District and the northwest of Fusong County. (3) According to the analysis of the influencing factors of EEQ, the influence of the factors of spatial differentiation of EEQI in Baishan City changed significantly from 2000 to 2020, and the average annual rainfall was the core factor affecting the spatial differentiation of EEQ in Baishan City, the second is the urbanization rate and the distance from the county government, and the interaction between the average annual rainfall and the distance from the county government has a strong influence on the spatial differentiation of EEQ in Baishan City. This study reveals the evolution of spatial types and EEQ of PLES in Baishan City, and provides a scientific reference for the effective management and utilization of land resources in Baishan City.

Abstract Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Transarterial radioembolization (TARE) is a well-established clinical therapy for the treatment of patients with intermediate to advanced hepatocellular carcinoma (HCC) or those who are ineligible for radical treatment. However, commercialized radioactive microspheres still have some issues, such as high density, complicated preparation, non-biodegradability. Furthermore, the use of different radioactive microspheres during TARE and lung shunt fraction assessment has led to inconsistencies in biodistribution in certain cases. This study employed biodegradable hyaluronic acid (HA) as the backbone and modified with bisphosphonate and methacrylic acid to prepare biodegradable gel microspheres (HAMS) using the water-in-oil emulsification and photo-crosslinking for labeling the diagnostic radionuclide of 99mTc and therapeutic radionuclide of 90Y. Both 99mTc radiolabeled HAMS (99mTc-HAMS) and radiolabeled 90Y-HAMS (90Y-HAMS) were highly efficient in radiolabeling and exhibited excellent radiostability in vitro and in vivo. 99mTc-HAMS are highly effective in assessing the LSF, while 90Y-HAMS, administered though TARE, are effective in inhibiting the growth of in situ HCC without any side effects. Both 99mTc-HAMS and 90Y-HAMS have promising clinical applications in HCC theranostics.

Meningioma is a benign tumor with slow growth and long course. However, patients with recurrent malignant meningioma still face a lack of effective treatment. Here, we report a rare case of primary mediastinal malignant meningioma with lung and bone metastases, who benefited from the treatment of apatinib (≥33 months) and anlotinib (until the publication date). Retrospective molecular analysis revealed the frequent amplification of FGF6 in primary and metastatic lesions. Then we constructed the FGF6 over-expressed IOMM-LEE and CH157MN malignant meningioma cell lines, and in vitro and vivo experiments showed that overexpression of FGF6 can promote the proliferation, migration and invasion of malignant meningioma cells. Based on the Western analysis, we revealed that FGF6 can promote the phosphorylation of FGFR, AKT, and ERK1/2, which can be inhibited by anlotinib. Together, we were the first to verify that overexpression of FGF6 promotes the progression of malignant meningiomas by activating FGFR/AKT/ERK1/2 pathway and pointed out that anlotinib may effectively inhibit the disease progression of patients with FGF6 amplification.

The fusion genes NRG1 and NRG2, members of the epidermal growth factor (EGF) receptor family, have emerged as key drivers in cancer. Upon fusion, NRG1 retains its EGF-like active domain, binds to the ERBB ligand family, and triggers intracellular signaling cascades, promoting uncontrolled cell proliferation. The incidence of NRG1 gene fusion varies across cancer types, with lung cancer being the most prevalent at 0.19 to 0.27%. CD74 and SLC3A2 are the most frequently observed fusion partners. RNA-based next-generation sequencing is the primary method for detecting NRG1 and NRG2 gene fusions, whereas pERBB3 immunohistochemistry can serve as a rapid prescreening tool for identifying NRG1-positive patients. Currently, there are no approved targeted drugs for NRG1 and NRG2. Common treatment approaches involve pan-ERBB inhibitors, small molecule inhibitors targeting ERBB2 or ERBB3, and monoclonal antibodies. Given the current landscape of NRG1 and NRG2 in solid tumors, a consensus among diagnostic and treatment experts is proposed, and clinical trials hold promise for benefiting more patients with NRG1 and NRG2 gene fusion solid tumors.

Microwave ablation is a highly efficacious method of treating cancer that employs electromagnetic radiation falling within the microwave spectrum. While it is highly effective in managing small to medium sized tumors, it demonstrates certain restrictions when applied to larger tumors. A network partition structure has been constructed to partition the tumor and its neighboring regions. A dynamic simulation has been facilitated through the establishment of a bidirectional coupling model between temperature and electromagnetic fields within the tissue, which was achieved through the design of dependency functions for tissue characteristics and temperature. A strategy for regulating the output of electromagnetic wave energy is presented: segmented microwave power control. The work, utilizing COMSOL Multiphysics simulation software, investigates the characteristics of electromagnetic propagation in the context of tissue properties and electromagnetic energy. Approaches to augment the efficiency of tissue energy absorption, broaden the scope of ablation, and diminish carbonization regions are delineated, thereby providing a theoretical foundation for large-area microwave ablation treatment with a single antenna.

BackgroundOsteosarcoma is a leading subtype of bone tumor affecting adolescents and adults. Comparative molecular characterization among different age groups, especially in pediatric, adolescents and adults, is scarce.MethodsWe collected samples from 194 osteosarcoma patients, encompassing pediatric, adolescent, and adult cohorts. Genomic analyses were conducted to reveal prevalent mutations and compare molecular features in pediatric, adolescent, and adult patients.ResultsSamples from 194 osteosarcoma patients across pediatric to adult ages were analyzed, revealing key mutations such as TP53, FLCN, NCOR1, and others. Children and adolescents showed more gene amplifications and HRD mutations, while adults had a greater Tumor Mutational Burden (TMB). Mutations in those over 15 were mainly in cell cycle and PI3K/mTOR pathways, while under 15s had more in cell cycle and angiogenesis with higher VEGFA, CCND3, TFEB mutations. CNV patterns varied with age: VEGFA and XPO5 amplifications more in under 25s, and CDKN2A/B deletions in over 25s. Genetic alterations in genes like MCL1 and MYC were associated with poor prognosis, with VEGFA mutations also indicating worse outcomes. 58% of patients had actionable mutations, suggesting opportunities for targeted therapies. Age-specific patterns were observed, with Multi-TKI mutations more common in younger patients and CDK4/6 inhibitor mutations in adults, highlighting the need for personalized treatment approaches in osteosarcoma. In a small group of patients with VEGFR amplification, postoperative treatment with multi-kinase inhibitors resulted in a PR in 3 of 13 cases, especially in patients under 15. A significant case involved a 13-year-old with a notable tumor size reduction achieving PR, even with other genetic alterations present in some patients with PD.ConclusionThis study delineates the molecular differences among pediatric, adolescent, and adult osteosarcoma patients at the genomic level, emphasizing the necessity for precision diagnostics and treatment strategies, and may offer novel prognostic biomarkers for patients with osteosarcoma. These findings provide a significant scientific foundation for the development of individualized treatment approaches tailored to patients of different age groups.

The coupling control of multi-physics fields has become a focal issue in the engineering domain, especially for achieving a more precise simulation and prediction of physical phenomena. This approach plays a crucial role in enhancing design efficiency and optimizing material selection. Focusing primarily on the controllability between microwave and temperature fields, the Emission Area Extension Structure (EAES) is a novel structure in response to the demand for high circularity in microwave ablation. Finite element analysis was employed to examine the distribution characteristics of electromagnetic and temperature fields in liver tissue under varying power and time conditions. Comparative analyses were conducted to evaluate the impact and performance of the EAES vs traditional structures in ablation. Incorporating the EAES into conventional ablation needles allows for a more concentrated distribution of the electromagnetic field without altering the needle diameter. In the simulation of tissue ablation, the circularity of ablation increased by 10%, while water-cooling efficiency increased by 11%. The introduction of EAES, while maintaining its minimally invasive characteristics, effectively enhanced the controllability of conformal ablation. Furthermore, a mathematical model was developed to serve as a theoretical basis for selecting optimal preoperative parameters, incorporating conditions such as ablation time, power, range, and circularity. Overall, by conducting a multi-physics field coupling analysis on microwave ablation needles and proposing the EAES solution, this study aims to enhance the predictability, controllability, and safety of conformal ablation.