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Revisiting collagen:A breaching point in tumor immunotherapy
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作者 Yi-Da Wang Hai-Yue You +3 位作者 Feng Zhang Xin Ning Jie Mei Yan Zhang 《Life Research》 2026年第1期1-4,共4页
Immunotherapy has brought unprecedented breakthroughs to advanced malignant tumors,yet the immune microenvironment shaped by the tumor stroma has often been underestimated in the traditional focus on the“immune check... Immunotherapy has brought unprecedented breakthroughs to advanced malignant tumors,yet the immune microenvironment shaped by the tumor stroma has often been underestimated in the traditional focus on the“immune checkpoint-T cell”axis.Collagen not only constitutes a mechanical barrier that distinguishes between the periphery and core of solid tumors but also systematically remodels the orientation of metabolism,vasculature,and immune cell phenotypic plasticity through its spatial density,fiber arrangement,and crosslinking patterns(F igure 1)[1,2].Abundant evidence suggests that over-accumulated types I and III collagen drive CD8+T cell exhaustion,NK cell functional inhibition,and tumor-associated macrophage polarization through ligand-receptor networks involving LAIR-1,DDR2,andβ1/β3 integrins[3-6].Mechanistically,collagen engagement of LAIR-1 delivers inhibitory signals in effector lymphocytes,promoting dysfunctional or exhausted states[7-9].In parallel,collagen-β1/β3 integrin signaling activates mechanotransduction pathways(e.g.,FAK/SRC),reducing T-cell motility and immune-tumor contact,while DDR2 activation supports matrix-remodeling programs that limit lymphocyte trafficking. 展开更多
关键词 immune microenvironment advanced malignant tumorsyet tumor immunotherapy immune cell phenotypic plasticity COLLAGEN tumor stroma collagen I solid tumors
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Deep Learning for Brain Tumor Segmentation and Classification: A Systematic Review of Methods and Trends
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作者 Ameer Hamza Robertas Damaševicius 《Computers, Materials & Continua》 2026年第1期132-172,共41页
This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 20... This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers. 展开更多
关键词 Brain tumor segmentation brain tumor classification deep learning vision transformers hybrid models
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Circulating Tumor DNA in Cervical Cancer:Clinical Utility and Medico-Legal Perspectives
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作者 Abdulrahman K.Sinno Aisha Mustapha +6 位作者 Navya Nair Simona Zaami Lina De Paola Valentina Billone Eleonora Conti Giuseppe Gullo Pasquale Patrizio 《Oncology Research》 2026年第1期71-88,共18页
Cervical cancer related to human papillomavirus(HPV)is a leading cause of cancer-related mortality among women worldwide.Cancer cells release fragments of their DNA,known as circulating tumor DNA(ctDNA),which can be d... Cervical cancer related to human papillomavirus(HPV)is a leading cause of cancer-related mortality among women worldwide.Cancer cells release fragments of their DNA,known as circulating tumor DNA(ctDNA),which can be detected in bodily fluids.A PubMed search using the terms“ctHPV”or“circulating tumor DNA”and“cervical cancer”,limited to the past ten years,identified 104 articles,complemented by hand-searching for literature addressing medico-legal implications.Studies were evaluated for relevance and methodological quality.Detection and characterization of circulating tumor HPV DNA(ctHPV DNA)have emerged as promising tools for assessing prognosis and disease recurrence in cervical cancer.Detection techniques include polymerase chain reaction(PCR),digital droplet PCR(ddPCR),and next-generation sequencing(NGS).This review summarizes current knowledge on ctHPV DNA in cervical cancer and explores its clinical and medico-legal implications,including management of discordant results,diagnostic errors,liability,and data protection compliance. 展开更多
关键词 Circulating tumor DNA circulating tumor human papillomavirus cervical cancer medico-legal implications
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Gut microbiota and the colorectal cancer tumor microenvironment:From carcinogenic mechanisms to therapeutic opportunities
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作者 Zi-Ke Chen Jia-Wei Zhao +2 位作者 Yu-Gang Wang Chen Wang Min Shi 《World Journal of Gastrointestinal Oncology》 2026年第1期114-121,共8页
Colorectal cancer(CRC)is ranked as the third most common tumor globally,representing approximately 10%of all cancer cases,and is the second primary cause of cancer-associated mortality.Existing therapeutic approaches ... Colorectal cancer(CRC)is ranked as the third most common tumor globally,representing approximately 10%of all cancer cases,and is the second primary cause of cancer-associated mortality.Existing therapeutic approaches demonstrate limited efficacy against CRC,partially due to the immunosuppressive tumor microenvironment(TME).In recent years,substantial evidence indicates that dysbiosis of the gut microbiota and its metabolic products is closely associated with the initiation,progression,and prognostic outcomes of CRC.In this minireview,we systematically elaborate on how these microbes and their metabolites directly impair intestinal epithelial integrity,activate cancer-associated fibroblasts,remodel tumor vasculature,and critically,sculpt an immunosuppressive landscape by modulating T cells,dendritic cells,and tumor-associated macrophages.We highlight the translational potential of targeting the gut microbiota,including fecal microbiota transplantation,probiotics,and engineered microbial systems,to reprogram the TME and overcome resistance to immunotherapy and chemotherapy.A deeper understanding of the microbiota-TME axis is essential for developing novel diagnostic and therapeutic paradigms for CRC. 展开更多
关键词 Gut microbiota tumor immune microenvironment Colorectal cancer tumor stromal cells Immune cells
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Synergistic Ferroptosis-Immunotherapy Nanoplatforms:Multidimensional Engineering for Tumor Microenvironment Remodeling and Therapeutic Optimization
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作者 Xiao Wei Yanqiu Jiang +6 位作者 Feiyang Chenwu Zhi Li Jie Wan Zhengxi Li Lele Zhang Jing Wang Mingzhu Song 《Nano-Micro Letters》 2026年第2期471-538,共68页
Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent... Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent,and metastatic malignancies.Mechanistically,ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death(ICD),eliciting damage-associated molecular patterns(DAMPs)release to activate partial antitumor immunity.However,standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations:low tumor immunogenicity,immunosuppressive microenvironment constraints,and tumor microenvironment(TME)-associated physiological barriers(e.g.,hypoxia,dense extracellular matrix).To address these challenges,synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance,encompassing(1)direct amplification of antitumor immunity,(2)disruption of immunosuppressive tumor niches,and(3)biophysical hallmark remodeling in TME.Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy.Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy,this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis-immunotherapy strategies.It advances multidimensional nanoplatform design principles for material selection,structural configuration,physicochemical modulation,multifunctional integration,and artificial intelligence-enabled design,providing a scientific basis for efficacy optimization.Moreover,it examines translational challenges of ferroptosis-immunotherapy nanoplatforms across preclinical and clinical stages,proposing actionable solutions while envisioning future onco-immunotherapy directions.Collectively,it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies,offering a roadmap for accelerating clinical translation in onco-immunotherapy research. 展开更多
关键词 Ferroptosis-immunotherapy Nanoplatforms tumor microenvironment Synergistic strategies Nanocarrier design
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Right patient approach to experimental stromal cell therapies for gastrointestinal tumors
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作者 Francesca Vescio Silvia Curcio +2 位作者 Isabella Aquila Michele Ammendola Alessandro Pasquale Tarallo 《World Journal of Gastrointestinal Oncology》 2026年第1期282-286,共5页
Experimental therapies targeting immune and stromal cells,such as mast cells,cancer-associated fibroblasts,dendritic cells,and tumor endothelial cells,in the treatment of gastrointestinal solid tumors pose new and com... Experimental therapies targeting immune and stromal cells,such as mast cells,cancer-associated fibroblasts,dendritic cells,and tumor endothelial cells,in the treatment of gastrointestinal solid tumors pose new and complex surgical and medico-legal challenges.These innovative treatments require that informed consent not be limited to simple acceptance of the medical procedure,but instead reflect a true relational and cognitive process grounded in understanding,free choice,and the ability to revoke consent at any time.In particular,it is essential that the patient understands the experimental nature of the therapy,its development stage,potential benefits and risks,as well as the implications for their health and personal dignity.In the case of stromal cell-based treatments,which may exert complex immunomodulatory effects or activate angiogenic pathways that are not yet fully understood,patients must be made fully aware that they are participating in a non-standardized therapy whose outcomes,whether beneficial or harmful,cannot yet be predicted with certainty.This requires particularly careful medical communication,using simple yet scientifically accurate explanations delivered in appropriate language,along with a final verification of the patient’s actual understanding. 展开更多
关键词 Experimental therapies SURGERY Non-standardized treatment Gastrointestinal tumor Informed consent
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Tumor microenvironment-driven microRNA dysregulation:Key interactions in colorectal cancer progression
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作者 Adriana G Quiroz-Reyes Paulina Delgado-Gonzalez +6 位作者 Jose Francisco Islas Veronica L Loaiza-Gutierrez Michelle G Santoyo-Suarez Juan A Garcia-Loredo Carlos A Gonzalez-Villarreal Fernanda Ramirez-Fernandez Elsa N Garza-Treviño 《World Journal of Gastrointestinal Oncology》 2026年第1期28-46,共19页
Colorectal cancer remains one of the leading causes of morbidity and mortality worldwide.Despite notable advances in early detection and therapeutic strategies,the molecular mechanisms underlying tumor survival,chemot... Colorectal cancer remains one of the leading causes of morbidity and mortality worldwide.Despite notable advances in early detection and therapeutic strategies,the molecular mechanisms underlying tumor survival,chemotherapy resistance,and metastasis are not yet fully understood.MicroRNAs(miRNAs)have emerged as pivotal regulators of cancer development,as they modulate gene expression and orchestrate key signaling pathways.However,the epigenetic mechanisms that control miRNA expression and their downstream gene targets remain largely unclear.In this review,we highlight the critical role of the colorectal cancer microenvironment in influencing miRNA expression and discuss how this regulation contributes to tumorigenesis.A better understanding of these processes may lead to the identification of novel therapeutic targets and strategies to prevent recurrence. 展开更多
关键词 Cancer progression MICRORNAS Colorectal cancer tumor microenvironment Therapeutic response
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Integrating artificial intelligence in the diagnostic pathway of duodenal gastrointestinal stromal tumors:A case report
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作者 Himanshu Agrawal Garima Dwivedi +3 位作者 Rahul Rohitaj Himanshu Tanwar Shailender Maurya Nikhil Gupta 《Artificial Intelligence in Gastroenterology》 2026年第1期36-43,共8页
BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of ... BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of GIST cases.These tumors often present with nonspecific symptoms,making early detection challenging.This case discusses a duodenal GIST misdiagnosed as pancreatic cancer due to obstructive jaundice.CASE SUMMARY A 40-year-old male with jaundice and abdominal symptoms underwent imaging,which suggested a malignant periampullary tumor.Preoperative misdiagnosis of pancreatic cancer was made,and surgery was performed.Postoperative histopathology confirmed a duodenal GIST.The role of artificial intelligence in the diagnostic pathway is explored,emphasizing its potential to differentiate between duodenal GISTs and other similar conditions using advanced imaging analysis.CONCLUSION Artificial intelligence in radiomic imaging holds significant promise in enhancing the diagnostic process for rare cancers like duodenal GISTs,ensuring timely and accurate treatment. 展开更多
关键词 Gastrointestinal stromal tumor DUODENUM Artificial intelligence Radiomics Preoperative diagnosis
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Astragali Radix(Huangqi)inhibits bone tumor cell migration and survival by targeting GPC2
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作者 Shu-Biao Wu Di Li +1 位作者 Yu-Tian Ma Cheng-Hai Wang 《Traditional Medicine Research》 2026年第4期64-74,共11页
Background:Bone tumors represent a significant clinical challenge characterized by high morbidity and complex therapeutic requirements.Although Astragali Radix(Huangqi)is recognized for its potential pharmacological b... Background:Bone tumors represent a significant clinical challenge characterized by high morbidity and complex therapeutic requirements.Although Astragali Radix(Huangqi)is recognized for its potential pharmacological benefits in cancer therapy,the specific molecular mechanisms and their influence on vitamin metabolism pathways in bone malignancies are not well defined.Methods:We conducted an integrated analysis of prognostic genes and survival outcomes in osteosarcoma,focusing on the expression of GPC2 and its correlation with tumor progression and patient survival rates.In order to explore the therapeutic relevance of 20 bioactive compounds extracted from Huangqi,molecular docking was performed to quantify their binding free energies to the GPC2 receptor,shedding light on their potential affinity and biological activity.Furthermore,the expression levels of GPC2 in tumor cells compared to normal cells were analyzed using qRT-PCR.Additionally,the effects of GPC2 overexpression and silencing on cellular viability,apoptotic response,and migratory capacity were systematically investigated.Results:In our study,GPC2 emerged as a significant prognostic gene,where high expression levels correlated with reduced overall survival.The molecular interactions between Astragalus components and the GPC2 receptor reveal compounds with strong affinity,suggesting their potential as effective targets.Furthermore,the overexpression of GPC2 enhanced tumor cell viability and migration,while its knockdown resulted in decreased cell viability and expanded apoptosis.Conclusion:This study demonstrates that Huangqi-derived components may exert anticancer effects by regulating the expression of the GPC2 gene within the vitamin metabolism pathway.These findings offer new insights into the therapeutic potential of traditional herbal medicine for improving bone tumor prognosis and provide a scientific foundation for future translational research. 展开更多
关键词 Huangqi GPC2 bone tumors vitamin metabolism system molecular docking OSTEOSARCOMA
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Enhanced recovery after surgery-based recovery room nursing improves perioperative safety in gastrointestinal tumor surgery
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作者 Wan-Qi Zhong Su Wu +6 位作者 Ru-Xin Jiang Shao-Ru Chen Dan-Yang Li Jun Zhou Jiang-Xia Wu Ruo-Jing Zeng Hui Zhi 《World Journal of Gastrointestinal Oncology》 2026年第1期211-220,共10页
BACKGROUND Gastrointestinal(GI)tumors are among the most prevalent malignancies,and surgical intervention remains a primary treatment modality.However,the complexity of GI surgery often leads to prolonged recovery and... BACKGROUND Gastrointestinal(GI)tumors are among the most prevalent malignancies,and surgical intervention remains a primary treatment modality.However,the complexity of GI surgery often leads to prolonged recovery and high postoperative complication rates,which threaten patient safety and functional outcomes.Enhanced recovery after surgery(ERAS)principles have been shown to improve perioperative outcomes through evidence-based,multidisciplinary care pathways.Despite its widespread adoption,there is a paucity of research focusing specifically on optimizing ERAS-guided nursing processes in the post-anesthesia care unit(PACU)and evaluating its impact on perioperative safety in patients undergoing GI tumor surgery.This study aimed to investigate whether an ERASbased PACU nursing protocol could enhance recovery,reduce complications,and improve patient safety in this surgical population.AIM To explore the impact of optimizing the recovery room nursing process based on ERAS on the perioperative safety of patients with GI tumors.METHODS A total of 260 patients with GI tumors who underwent elective surgeries under general anesthesia in our hospital from August 2023 to August 2025 and were then observed in the recovery unit(PACU)were selected.They were randomly divided into the observation group(the PACU nursing process was optimized based on ERAS)and the control group(the conventional PACU nursing process was adopted)by the random number grouping method,with 130 cases in each group.The time of gastric tube removal,urinary catheter removal,defecation time,hospital stay,time of leaving the room after tube removal,retention time in the recovery room,occurrence of complications,satisfaction and readmission rate were compared between the two groups after entering the room.Compare the occurrence of adverse events in the PACU nursing process between the two groups.RESULTS The time of gastric tube removal,urinary catheter removal,defecation time,hospital stay,retention time in the recovery room,total incidence of complications and readmission rate in the observation group were significantly lower than those in the control group,and the satisfaction rate was higher than that in the control group(P<0.05).The occurrence of adverse events in the PACU nursing process in the observation group was lower than that in the control group(P<0.05).CONCLUSION Optimizing the PACU nursing process based on ERAS can effectively accelerate the recovery process of patients undergoing GI tumor surgery,reduce adverse events,improve nursing satisfaction,and at the same time,lower the incidence of adverse events in the PACU nursing process,providing a more refined management basis for clinical practice. 展开更多
关键词 Enhanced recovery after surgery Recovery room NURSING Gastrointestinal tumors Perioperative period
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STC2+Malignant Cell State Associated with EMT,Tumor Microenvironment Remodeling,and Poor Prognosis Revealed by Single-Cell and Spatial Transcriptomics in Colorectal Cancer
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作者 Kai Gui Tianyi Yang +4 位作者 Chengying Xiong Yue Wang Zhiqiang He Wuxian Li Min Tang 《Oncology Research》 2026年第1期521-546,共26页
Objectives:The mechanism by which specific tumor subsets in colorectal cancer(CRC)use alternative metabolic pathways,particularly those modulated by hypoxia and fructose,to alter the tumor microenvironment(TME)remains... Objectives:The mechanism by which specific tumor subsets in colorectal cancer(CRC)use alternative metabolic pathways,particularly those modulated by hypoxia and fructose,to alter the tumor microenvironment(TME)remains unclear.This study aimed to identify these malignant subpopulations and characterize their intercellular signaling networks and spatial organization through an integrative multi-omics approach.Methods:Leveraging bulk datasets,single-cell RNA sequencing,and integrative spatial transcriptomics,we developed a prognostic model based on hypoxia-and fructose metabolism-related genes(HFGs)to delineate tumor cell subpopulations and their intercellular signaling networks.Results:We identified a specific subset of stanniocalcin-2 positive(STC2+)malignant cells spatially enriched within tumor regions and strongly associated with poor prognosis.This subset served as a key signaling hub in the TME,exhibiting increased epithelial–mesenchymal transition activity.STC2+cells engage in two spatially organized ligand–receptor interactions:the growth differentiation factor 15(GDF15)—transforming growth factor beta receptor 2(TGFBR2)pathway targeting endothelial cells and the migration inhibitory factor(MIF)—(cluster of differentiation 74[CD74]+C-X-C motif chemokine receptor 4[CXCR4])pathway targeting macrophages.Conclusion:This study identified a malignant cell state in CRC that is metabolically defined and spatially limited,including liver metastases,and is characterized by elevated STC2 expression and active immune-stromal interactions.Given the interplay between metabolic reprogramming and TME remodeling,STC2+malignant cells are a functionally significant subpopulation and a potential therapeutic target. 展开更多
关键词 Colorectal cancer(CRC) machine learning fructose metabolism tumor microenvironment(TME) prognosis
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SwinHCAD: A Robust Multi-Modality Segmentation Model for Brain Tumors Using Transformer and Channel-Wise Attention
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作者 Seyong Jin Muhammad Fayaz +2 位作者 L.Minh Dang Hyoung-Kyu Song Hyeonjoon Moon 《Computers, Materials & Continua》 2026年第1期511-533,共23页
Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the b... Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the burden on medical staff and provides quantitative information,existing methodologies and recent models still struggle to accurately capture and classify the fine boundaries and diverse morphologies of tumors.In order to address these challenges and maximize the performance of brain tumor segmentation,this research introduces a novel SwinUNETR-based model by integrating a new decoder block,the Hierarchical Channel-wise Attention Decoder(HCAD),into a powerful SwinUNETR encoder.The HCAD decoder block utilizes hierarchical features and channelspecific attention mechanisms to further fuse information at different scales transmitted from the encoder and preserve spatial details throughout the reconstruction phase.Rigorous evaluations on the recent BraTS GLI datasets demonstrate that the proposed SwinHCAD model achieved superior and improved segmentation accuracy on both the Dice score and HD95 metrics across all tumor subregions(WT,TC,and ET)compared to baseline models.In particular,the rationale and contribution of the model design were clarified through ablation studies to verify the effectiveness of the proposed HCAD decoder block.The results of this study are expected to greatly contribute to enhancing the efficiency of clinical diagnosis and treatment planning by increasing the precision of automated brain tumor segmentation. 展开更多
关键词 Attention mechanism brain tumor segmentation channel-wise attention decoder deep learning medical imaging MRI TRANSFORMER U-Net
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NIR-IIb-triggered microbial upconversion photosynthesis enables hypoxia-resistant tumor lactate catabolism
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作者 Bingzhu Zheng Feiyu Li +5 位作者 Jiafei Chen Qilong Yan Renren Deng Zhi Li Jian Ruan Xiang Li 《Nano Research》 2026年第1期903-915,共13页
Elevated lactate levels in solid tumors contribute to immunosuppression,metabolic reprogramming,and resistance to therapy.Although lactate oxidase(LOX)offers a viable strategy for in situ lactate depletion,its therape... Elevated lactate levels in solid tumors contribute to immunosuppression,metabolic reprogramming,and resistance to therapy.Although lactate oxidase(LOX)offers a viable strategy for in situ lactate depletion,its therapeutic efficacy is fundamentally limited by tumor hypoxia due to the oxygen dependence of LOX.Here,we report a hybrid nanomaterial-microbial system that enables hypoxiaresistant lactate catabolism through near-infrared(NIR)-IIb-triggered upconverson photosynthesis.This system integrates LOX-producing Escherichia coli(E.coli)with Chlorella(Chl)and lanthanide-doped upconversion nanoparticles(UCNPs),which convert deeply penetrating 1550 nm light into visible emission to drive oxygenic photosynthesis.Unlike conventional photosynthetic oxygenation approaches limited by shallow visible light penetration,this system enables spatiotemporally controlled oxygen generation deep within tumors,sustaining LOX activity under hypoxia.In murine tumor models,the hybrid symbionts significantly inhibited tumor growth,promoted T cell infiltration,and induced durable immune memory.This work establishes a versatile optogeneticmetabolic platform for overcoming oxygen-limited metabolism in cancer therapy via deep-tissue-activatable microbial photosynthesis. 展开更多
关键词 lactate consumption engineered E.coli near-infrared(NIR)photosynthesis tumor therapy
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Retraction: MicroRNA-148a Acts as a Tumor Suppressor in Osteosarcoma via Targeting Rho-Associated Coiled-Coil Kinase
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作者 Oncology Research Editorial Office 《Oncology Research》 2026年第1期622-622,共1页
The published article titled“MicroRNA-148a Acts as a Tumor Suppressor in Osteosarcoma via Targeting Rho-Associated Coiled-Coil Kinase”has been retracted from Oncology Research,Vol.25,No.8,2017,pp.1231–1243.DOI:10.3... The published article titled“MicroRNA-148a Acts as a Tumor Suppressor in Osteosarcoma via Targeting Rho-Associated Coiled-Coil Kinase”has been retracted from Oncology Research,Vol.25,No.8,2017,pp.1231–1243.DOI:10.3727/096504017X14850134190255 URL:https://www.techscience.com/or/v25n8/56908 Following the publication,concerns have been raised about a number of figures in this article.An unexpected area of similarity was identified in terms of the cellular data,where the results from differently performed experiments were intended to have been shown,although the areas immediately surrounding this area featured comparatively different distributions of cells.In addition,the western blots in this article were presented with atypical,unusually shaped and possibly anomalous protein bands in many cases. 展开更多
关键词 cellular datawhere tumor suppressor western blots rho associated coiled coil kinase microrna cellular data OSTEOSARCOMA figures
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Multimodal artificial intelligence integrates imaging,endoscopic,and omics data for intelligent decision-making in individualized gastrointestinal tumor treatment
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作者 Hui Nian Yi-Bin Wu +5 位作者 Yu Bai Zhi-Long Zhang Xiao-Huang Tu Qi-Zhi Liu De-Hua Zhou Qian-Cheng Du 《Artificial Intelligence in Gastroenterology》 2026年第1期1-19,共19页
Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including ... Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies. 展开更多
关键词 Multimodal artificial intelligence Gastrointestinal tumors Individualized therapy Intelligent diagnosis Treatment optimization Prognostic prediction Data fusion Deep learning Precision medicine
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基于改进P2PNet的猪只计数方法
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作者 陈韬 徐爱俊 +1 位作者 周素茵 叶俊华 《农业工程学报》 北大核心 2025年第11期209-218,共10页
猪只计数是现代养猪业的重要任务,对于评估养殖规模、优化饲养策略和提升经济效益具有关键作用。然而,复杂的猪场环境中,猪群密度高、遮挡多等因素使得计数准确性面临挑战。为此,该研究提出了一种基于人群计数模型P2PNet改进的猪只计数... 猪只计数是现代养猪业的重要任务,对于评估养殖规模、优化饲养策略和提升经济效益具有关键作用。然而,复杂的猪场环境中,猪群密度高、遮挡多等因素使得计数准确性面临挑战。为此,该研究提出了一种基于人群计数模型P2PNet改进的猪只计数模型PIG-P2PNet。首先,通过在P2PNet主干网络中引入高效通道注意力机制,有效捕捉通道间的依赖关系,增强了模型对重叠猪只的识别能力。其次,在P2PNet特征金字塔中集成坐标通道混洗注意力模块,强化了空间位置信息和通道特征的提取与交互能力,提升了模型在不同密度场景下的适应性;此外,设计了一种基于情景感知的匈牙利匹配算法,通过引入加权距离惩罚、不确定性成本和自适应密度惩罚,提高了匹配精度。最后,为应对背景与目标样本不平衡的问题,使用Focal Loss替换交叉熵损失,进一步提升了模型的分类准确性。PIG-P2PNet在自建的包含多种场景、视角和密度级别的猪只点标注数据集上的测试结果表明,其平均绝对误差(mean absolute error,MAE)、均方根误差(root mean square error,RMSE)和归一化绝对误差(normalized absolute error,NAE)分别为0.873、1.502和0.040,比改进前分别降低了33.9%、22.1%和39.4%。相较于经典计数模型CSRNet、CANNet和CLTR,PIGP2PNet在MAE上分别降低了63.3%、54.5%和26.7%,在RMSE上降低了49.7%、47.1%和13.7%,在NAE上降低了73.5%、56.5%和35.5%。因此,该研究提出的PIG-P2PNet猪只计数模型准确性高、鲁棒性强,为猪只计数提供了一种创新性的技术方案。 展开更多
关键词 猪只计数 注意力机制 深度学习 匈牙利匹配算法 P2pnet
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Clinical value of combining epirubicin with mindfulness intervention in patients with urinary system tumors and depression 被引量:1
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作者 Juan Liu Yan-Ping Guo +1 位作者 Yan-Mei Lu Bei-Lin Wang 《World Journal of Psychiatry》 SCIE 2025年第1期54-62,共9页
BACKGROUND Urinary system tumors often cause negative psychological symptoms,such as depression and dysphoria which significantly impact immune function and indirectly affect cancer prognosis.While epirubicin(EPI)is r... BACKGROUND Urinary system tumors often cause negative psychological symptoms,such as depression and dysphoria which significantly impact immune function and indirectly affect cancer prognosis.While epirubicin(EPI)is recommended by the European Association of Urology and can improve prognosis,its long-term use can cause toxic side effects,reduce treatment compliance,and increase psycho-logical burden.Therefore,an appropriate intervention mode is necessary.METHODS This was a retrospective study including 110 patients with urinary system tumors and depression admitted to Zhumadian Central Hospital between March 2021 and July 2023.Patients were divided into conventional(n=55)and joint inter-vention(n=55)groups.The conventional group received mitomycin and routine nursing,while the joint intervention group received EPI and mindfulness intervention.Both groups underwent three cycles of chemotherapy.Immune function(CD4+cells,CD8+cells,CD4+/CD8+ratio),tumor marker levels[urinary bladder cancer antigen(UBC),bladder tumor antigen(BTA)and nuclear matrix protein 22(NMP22)],quality of life questionnaire-core 30(QLQ-C30),17-item Hamilton depression scale(HAMD-17),and cancer-related fatigue[cancer fatigue scale(CFS)]were assessed.Adverse reactions and nursing satisfaction were recorded and evaluated.RESULTS Post-intervention,CD4+,CD8+,and CD4+/CD8+levels increased in both groups,with the joint intervention group showing more significant improvement(P<0.05).Tumor marker levels(NMP22,BTA,and UBC)were lower in the joint intervention group compared to the conventional group(P<0.05).The joint intervention group also showed a greater reduction in HAMD-17 scores(9.38±3.12 vs 15.45±4.86,P<0.05),higher QLQ-C30 scores,and lower CFS scores(both P<0.05).Additionally,the joint intervention group had a lower incidence of adverse reactions and higher nursing satisfaction(P<0.05).CONCLUSION EPI combined with mindfulness intervention significantly improved clinical outcomes in patients with urinary system tumors and depression and is worthy of clinical application. 展开更多
关键词 Urinary system tumor Bladder cancer Prostate cancer DEPRESSION EPIRUBICIN
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Correlation between gut microbiota and tumor immune microenvironment:A bibliometric and visualized study 被引量:1
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作者 Zheng-Jun Hu Hui-Rong Zhu +3 位作者 Yong-Jie Jin Pan Liu Xiao-Wei Yu Yu-Ren Zhang 《World Journal of Clinical Oncology》 2025年第2期110-129,共20页
BACKGROUND In recent years,numerous reports have been published regarding the relationship between the gut microbiota and the tumor immune microenvironment(TIME).However,to date,no systematic study has been conducted ... BACKGROUND In recent years,numerous reports have been published regarding the relationship between the gut microbiota and the tumor immune microenvironment(TIME).However,to date,no systematic study has been conducted on the relationship between gut microbiota and the TIME using bibliometric methods.AIM To describe the current global research status on the correlation between gut microbiota and the TIME,and to identify the most influential countries,research institutions,researchers,and research hotspots related to this topic.METHODS We searched for all literature related to gut microbiota and TIME published from January 1,2014,to May 28,2024,in the Web of Science Core Collection database.We then conducted a bibliometric analysis and created visual maps of the published literature on countries,institutions,authors,keywords,references,etc.,using CiteSpace(6.2R6),VOSviewer(1.6.20),and bibliometrics(based on R 4.3.2).RESULTS In total,491 documents were included,with a rapid increase in the number of publications starting in 2019.The country with the highest number of publications was China,followed by the United States.Germany has the highest number of citations in literature.From a centrality perspective,the United States has the highest influence in this field.The institutions with the highest number of publications were Shanghai Jiao Tong University and Zhejiang University.However,the institution with the most citations was the United States National Cancer Institute.Among authors,Professor Giorgio Trinchieri from the National Institutes of Health has the most local impact in this field.The most cited author was Fan XZ.The results of journal publications showed that the top three journals with the highest number of published papers were Frontiers in Immunology,Cancers,and Frontiers in Oncology.The three most frequently used keywords were gut microbiota,tumor microenvironment,and immunotherapy.CONCLUSION This study systematically elaborates on the research progress related to gut microbiota and TIME over the past decade.Research results indicate that the number of publications has rapidly increased since 2019,with research hotspots including“gut microbiota”,“tumor microenvironment”and“immunotherapy”.Exploring the effects of specific gut microbiota or derived metabolites on the behavior of immune cells in the TIME,regulating the secretion of immune molecules,and influencing immunotherapy are research hotspots and future research directions. 展开更多
关键词 Gut microbiota tumor immune microenvironment BIBLIOMETRIC CITESPACE VOSviewer R-bibliometrics
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Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models
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作者 Shanmugasundaram Hariharan D.Anandan +3 位作者 Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第1期91-122,共32页
Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present wi... Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and challenging.This review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and resilience.Performance metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical contexts.The review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging conditions.It suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular methods.This paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges. 展开更多
关键词 Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning
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基于改进P2PNet的铁路车站人群数量估计算法
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作者 万成凯 安高云 崔岚 《计算机与现代化》 2025年第11期58-64,共7页
本文针对铁路车站等场景下人群数量估计问题,提出一种基于改进P2PNet的铁路车站人群数量估计算法。该算法对传统的P2PNet算法进行较大的改动和优化。首先,算法模型采用BiFPN的路径聚合来增强网络对不同尺度特征图的融合能力,解决图像中... 本文针对铁路车站等场景下人群数量估计问题,提出一种基于改进P2PNet的铁路车站人群数量估计算法。该算法对传统的P2PNet算法进行较大的改动和优化。首先,算法模型采用BiFPN的路径聚合来增强网络对不同尺度特征图的融合能力,解决图像中人员大小尺度相差较大的情况;其次,网络在低层特征图引入A-SPP结构以提高网络的感受野范围,增强网络提取多尺度特征的能力;再次,网络中的OutLayer之前采用了CSAM注意力动态地调整特征图中各个通道和空间位置的重要性,更有效地回归图像中人的位置和分类;最后,在损失函数中,Focal Loss代替了传统的交叉熵,来解决正负样本不均衡和难易样本不均衡的问题。在公开数据集和自有数据集上进行对比实验的结果表明,该算法在平均绝对误差上优于当前同类先进算法。在实际的车站视频场景下,该算法能够准确估计人群数量。 展开更多
关键词 人群数量估计 P2pnet 多尺度特征 注意力机制 特征融合
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