IF 14.1

MedComm Pub Date : 2026-10-11 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71054

Bin Feng, Dingyi Yang, Xin Yang, Huanli Luo, Tian Wang, Liyuan Chen, Liang Tan, Liang Du, Yongzhong Wu, Wei Zhou, Ying Wang, Fu Jin

{"title":"Optimizing Lung-molGPA-Directed Therapy for EGFR/ALK/ROS1-Wildtype Non-Small Cell Lung Cancer Brain Metastases: Survival Outcomes Analysis.","authors":"Bin Feng, Dingyi Yang, Xin Yang, Huanli Luo, Tian Wang, Liyuan Chen, Liang Tan, Liang Du, Yongzhong Wu, Wei Zhou, Ying Wang, Fu Jin","doi":"10.1002/mco2.71054","DOIUrl":"https://doi.org/10.1002/mco2.71054","url":null,"abstract":"Patients with non-small cell lung cancer (NSCLC) and brain metastases whose tumors lack EGFR, ALK, or ROS1 alterations have heterogeneous outcomes and limited evidence to guide treatment intensity. We assessed whether Lung-molGPA could stratify prognosis and inform treatment selection in this population. This retrospective two-center cohort included 811 patients with EGFR/ALK/ROS1-wild-type NSCLC treated between September 2013 and August 2022. Overall survival (OS) was evaluated using Kaplan-Meier methods and center-stratified multivariable Cox regression across three Lung-molGPA strata and treatment modalities. Median OS was 6.9 months (95% confidence interval [CI], 6.4-7.4) overall and 4.81 (4.20-5.30), 7.65 (6.73-8.40), and 16.00 (13.40-22.90) months in the Lung-molGPA 0-1.0, 1.5-2.0, and 2.5-3.0 groups, respectively (p < 0.001). Compared with the 0-1.0 group, adjusted mortality was lower in the 1.5-2.0 (hazard ratio [HR], 0.68; 95% CI, 0.58-0.80) and 2.5-3.0 groups (HR, 0.39; 95% CI, 0.30-0.50). Chemotherapy, immunotherapy, antiangiogenic therapy, and brain- and chest-directed local therapy were independently associated with lower mortality, although their associations varied across prognostic strata and treatment contexts. Lung-molGPA provides clinically meaningful prognostic separation and may help tailor treatment intensity for EGFR/ALK/ROS1-wild-type NSCLC with brain metastases.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71054"},"PeriodicalIF":14.1,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13655364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149187117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Super-Resolution MRI-Derived Tumor-Stroma Ratio Phenotyping for Prognostic and Therapeutic Stratification in Pancreatic Ductal Adenocarcinoma. 胰腺导管腺癌预后和治疗分层的超分辨率mri衍生肿瘤-间质比率表型分析。

IF 14.1

MedComm Pub Date : 2026-10-09 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71039

Xingxing Wang, Zongyu Xie, Hanxiao Li, Qiying Tang, Jianjun Zhou, Jingcheng Huang, Shiwu Fang, Dalong Li, Lei Li, Mengsu Zeng, Minping Hong, Qiuyang Zhu, Yaolin Xu, Haitao Sun

{"title":"Super-Resolution MRI-Derived Tumor-Stroma Ratio Phenotyping for Prognostic and Therapeutic Stratification in Pancreatic Ductal Adenocarcinoma.","authors":"Xingxing Wang, Zongyu Xie, Hanxiao Li, Qiying Tang, Jianjun Zhou, Jingcheng Huang, Shiwu Fang, Dalong Li, Lei Li, Mengsu Zeng, Minping Hong, Qiuyang Zhu, Yaolin Xu, Haitao Sun","doi":"10.1002/mco2.71039","DOIUrl":"https://doi.org/10.1002/mco2.71039","url":null,"abstract":"Pancreatic ductal adenocarcinoma (PDAC) exhibits profound stromal heterogeneity that influences tumor progression, recurrence risk, and therapeutic response; however, stromal phenotypes are currently assessed by postoperative histopathology. Here, we developed a super-resolution MRI (srMRI)-based radiomics model to enable noninvasive tumor-stroma ratio (TSR) phenotyping in PDAC. Using multicenter cohorts comprising 737 patients, we constructed a srMRI-derived TSR-radscore capable of predicting pathological TSR with high accuracy (AUC = 0.870 and 0.791 in training and external validation cohorts). The TSR-radscore independently stratified recurrence-free survival and, when integrated with clinicopathological variables, improved early recurrence prediction in an independent surgical cohort. In a locally advanced PDAC cohort, srMRI-derived TSR was associated with distinct therapeutic outcomes, with H-TSR tumors showing improved survival under systemic therapy and an association with outcomes following immune checkpoint inhibitor-based combination therapy. Transcriptomic analyses revealed that L-TSR tumors were enriched in extracellular matrix remodeling and TGF-β-related signaling pathways. Single-cell profiling further uncovered distinct cancer-associated fibroblast and T-cell states across TSR phenotypes, linking imaging-derived TSR patterns to underlying stromal and immune microenvironmental programs. Collectively, srMRI-derived TSR phenotyping provides a noninvasive and biologically interpretable biomarker for stromal characterization in PDAC, enabling improved recurrence-risk stratification and pre-treatment clinical assessment.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71039"},"PeriodicalIF":14.1,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13650606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning-Based Prediction of Mortality in Patients With Mitral Regurgitation: Results From Two Nationwide, Prospective Studies. 基于机器学习的二尖瓣返流患者死亡率预测：两项全国性前瞻性研究的结果。

IF 14.1

MedComm Pub Date : 2026-10-09 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71005

Yuzhe Yin, Junxing Lv, Qinghao Zhao, Yunqing Ye, Weiwei Wang, Haitong Zhang, Zhenyan Zhao, Qingrong Liu, Zikai Yu, Bin Zhang, Shuai Guo, Zhenya Duan, Bincheng Wang, Yanyan Zhao, Runlin Gao, Zhe Li, Haiyan Xu, Yongjian Wu, Junbo Ge

{"title":"Machine Learning-Based Prediction of Mortality in Patients With Mitral Regurgitation: Results From Two Nationwide, Prospective Studies.","authors":"Yuzhe Yin, Junxing Lv, Qinghao Zhao, Yunqing Ye, Weiwei Wang, Haitong Zhang, Zhenyan Zhao, Qingrong Liu, Zikai Yu, Bin Zhang, Shuai Guo, Zhenya Duan, Bincheng Wang, Yanyan Zhao, Runlin Gao, Zhe Li, Haiyan Xu, Yongjian Wu, Junbo Ge","doi":"10.1002/mco2.71005","DOIUrl":"https://doi.org/10.1002/mco2.71005","url":null,"abstract":"Mitral regurgitation (MR) is among the most prevalent valvular heart diseases. We developed and externally validated a machine learning (ML)-based mortality prediction model for patients with significant MR. From the ChinaValvular Heart Disease (China-VHD) registry, 6323 patients with moderate or greater MR were randomly split 7:3 into training and internal validation sets. Variables selected concordantly by Cox stepwise regression, Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression, and Boruta were retained. Seventeen ML and traditional models were compared. The final model was tested in the internal set and an external cohort of 4658 patients from the China Elderly Valve Disease (China-DVD) study. SHapley Additive exPlanations (SHAP) analysis assessed interpretability. Fifteen predictors were identified. CatBoost performed best, with AUCs of 0.783 (95% confidence interval [CI] 0.751-0.815) internally and 0.703 (0.678-0.728) externally, outperforming Cox (0.699), MitraScore (0.620), and EuroSCORE II (0.679). Age, NYHA class, and left ventricular ejection fraction were the top predictors. The model effectively distinguished high-risk from low-risk patients internally (adjusted hazard ratio [HR] 5.49, p < 0.001) and externally (adjusted HR 3.05, p < 0.001). In conclusion, we developed and externally validated an ML-based mortality prediction model for MR irrespective of etiology or treatment strategy, with potential to improve risk stratification and clinical decision-making.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71005"},"PeriodicalIF":14.1,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13650608/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149169229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ischemic Stroke and Traumatic Brain Injury: Epidemiology, Molecular Pathways, and Emerging Therapies. 缺血性中风和创伤性脑损伤：流行病学、分子途径和新兴疗法。

IF 14.1

MedComm Pub Date : 2026-10-09 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71053

Mengzhao Feng, Qi Qin, Fang Wang, Kaiyuan Zhang, Zhihua Li, Junlei Chang, Min Yu, Fuyou Guo

{"title":"Ischemic Stroke and Traumatic Brain Injury: Epidemiology, Molecular Pathways, and Emerging Therapies.","authors":"Mengzhao Feng, Qi Qin, Fang Wang, Kaiyuan Zhang, Zhihua Li, Junlei Chang, Min Yu, Fuyou Guo","doi":"10.1002/mco2.71053","DOIUrl":"https://doi.org/10.1002/mco2.71053","url":null,"abstract":"Ischemic stroke and traumatic brain injury are two leading causes of death and long-term disability worldwide. Despite their different primary insults, both conditions trigger a complex cascade of secondary brain injury that largely determines neurological outcome. This review systematically compares the epidemiology, shared molecular pathways, and emerging therapeutic strategies for secondary brain injury after ischemic stroke and traumatic brain injury. We focus on three interconnected pathological cascades spanning blood-brain barrier disruption, neuroinflammation, and neuronal death driven by excitotoxicity, oxidative stress, and multiple forms of programmed cell death. For each pathway, we highlight convergent and divergent mechanisms between the two disorders. We then summarize emerging preclinical interventions ranging from small molecule inhibitors and repurposed drugs to nanomedicine, extracellular vesicles, and neuromodulation techniques. In parallel, we review recent and ongoing clinical trials targeting these pathways, emphasizing mechanism-based strategies. Finally, we discuss current challenges and offer future perspectives on biomarker-driven patient stratification, innovative drug delivery systems bypassing the blood-brain barrier, and multitarget combination regimens. By providing a unified framework that compares ischemic stroke and traumatic brain injury side by side, this review aims to guide the development of more effective, personalized treatments for secondary brain injury.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71053"},"PeriodicalIF":14.1,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13650598/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149169303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correction to "Therapeutic potential of nicotinamide and ABT263 inalcohol-associated liver disease through targeting cellular senescence". 修正“烟酰胺和ABT263通过靶向细胞衰老治疗酒精相关肝病的潜力”。

IF 14.1

MedComm Pub Date : 2026-10-06 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.70969

引用次数: 0

Profiling Gut Microbiome and Metabolites Aids Diagnosis and Prediction of Progression in Mild Cognitive Impairment. 分析肠道微生物组和代谢物有助于轻度认知障碍的诊断和预测进展。

IF 14.1

MedComm Pub Date : 2026-10-06 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71045

Birong Zhang, Richard Brown, Antony Bayer, Joanna Waring, B Paul Morgan, Julian R Marchesi, You Zhou

{"title":"Profiling Gut Microbiome and Metabolites Aids Diagnosis and Prediction of Progression in Mild Cognitive Impairment.","authors":"Birong Zhang, Richard Brown, Antony Bayer, Joanna Waring, B Paul Morgan, Julian R Marchesi, You Zhou","doi":"10.1002/mco2.71045","DOIUrl":"10.1002/mco2.71045","url":null,"abstract":"Accumulating evidence suggests a link between the gut microbiota and metabolome and mild cognitive impairment (MCI); however, it remains largely unknown whether these parameters can aid MCI diagnosis and predict disease progression. We comprehensively characterized gut microbiota and metabolomic profiles in fecal samples from 35 individuals, including 16 spousal pairs in which one partner had MCI. Compared with controls, MCI cases exhibited significantly elevated levels of Izemoplasmatales spp. in the fecal microbiome and proline in the metabolome, along with decreased levels of Ruminococcus spp., Lachnospira spp., and fumaric acid. Among MCI cases, rapid progressors showed significantly increased Bilophila spp. in the microbiome, accompanied by higher arginine, aspartic acid, and hypoxanthine in the metabolome, and reduced Coprococcus spp., compared with slow progressors. Machine learning models integrating microbiota and metabolite features identified marker sets that accurately distinguished MCI cases from matched cognitively healthy controls (AUC: 0.944) and predicted rapid disease progression, with the integrated model outperforming single-modality models for diagnosis. These findings identify distinct gut microbiota and metabolite signatures associated with MCI, highlighting their potential as candidate biomarkers for early diagnosis and risk stratification, thereby addressing the unmet need for simple tests for early detection.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71045"},"PeriodicalIF":14.1,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13639709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149121097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intratumoral Microbiota in Fueling Cancer and Steering Treatment Response. 肿瘤内微生物群促进癌症和指导治疗反应。

IF 14.1

MedComm Pub Date : 2026-10-06 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71052

Minhui Xu, Jie Yu, Ying Chen, Shengfang Ge, Lin Ye, Yefei Wang, Yixiong Zhou, Renbing Jia

{"title":"Intratumoral Microbiota in Fueling Cancer and Steering Treatment Response.","authors":"Minhui Xu, Jie Yu, Ying Chen, Shengfang Ge, Lin Ye, Yefei Wang, Yixiong Zhou, Renbing Jia","doi":"10.1002/mco2.71052","DOIUrl":"10.1002/mco2.71052","url":null,"abstract":"Microorganisms within tumors, also known as intratumoral microbiota, actively shape the tumor microenvironment (TME), influencing cancer progression and treatment response. Research has therefore expanded beyond the gut microbiota to intratumoral bacterial and fungal communities. Advances in low-biomass sequencing, contamination control, and spatial profiling have made it possible to detect these low-abundance microbes within the TME and map their marked heterogeneity across cancer types and tissue compartments. However, their origins, causal functions, and clinical relevance remain debated. Here, we summarize contamination-sensitive workflows and high-resolution techniques required for low-biomass tissues, and compare representative taxa in major cancer settings. We further explore microbial origins, taxonomic diversity, and localized interactions with malignant, immune, and stromal cells. We synthesize mechanistic evidence linking intratumoral microbes to genomic instability, epigenetic regulation, oncogenic signaling, metabolic reprogramming, and metastasis. Based on these insights, we evaluate their impact on cancer therapies, alongside emerging microbial interventions and barriers to clinical translation. Ultimately, this review provides a framework for assessing intratumoral microbiota as biomarkers, treatment-response modifiers, and therapeutic targets, while highlighting the key evidence needed to translate these findings into the clinic.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71052"},"PeriodicalIF":14.1,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13639541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

KRAS Mutations in Cancers: From Undruggable Dilemma to Precision Medicine. 癌症中的KRAS突变：从无法治愈的困境到精准医学。

IF 14.1

MedComm Pub Date : 2026-10-06 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71050

Jiaying Cai, Yimin Wu, Xing Jia, Li Yang, Wenjun Yang, Weishan Lu, Zhiye Huang, Yang Pan, Zixuan Fei, Junnan Ru, Jiazheng Zhao, Jue Shen, Taobo Luo, Da Chen, Haihong Yu, Haihan Deng, Jian Zeng, Wenmei Jiang, Leilei Wu

{"title":"KRAS Mutations in Cancers: From Undruggable Dilemma to Precision Medicine.","authors":"Jiaying Cai, Yimin Wu, Xing Jia, Li Yang, Wenjun Yang, Weishan Lu, Zhiye Huang, Yang Pan, Zixuan Fei, Junnan Ru, Jiazheng Zhao, Jue Shen, Taobo Luo, Da Chen, Haihong Yu, Haihan Deng, Jian Zeng, Wenmei Jiang, Leilei Wu","doi":"10.1002/mco2.71050","DOIUrl":"10.1002/mco2.71050","url":null,"abstract":"KRAS is one of the most frequently altered oncogenic drivers across human solid tumors and has long represented a central challenge in precision oncology. The clinical success of covalent KRAS G12C inhibitors has transformed a historically \"undruggable\" target into a tractable therapeutic class, but durable benefit remains limited by adaptive feedback, acquired resistance, co-mutation context, and tumor-lineage-specific barriers. A major unresolved question is how to extend this success across diverse KRAS alleles and cancer types. This review summarizes the molecular epidemiology and therapeutic landscape of KRAS-mutant cancers, with emphasis on non-small cell lung cancer, colorectal cancer, and pancreatic ductal adenocarcinoma. We compare G12C-directed therapy with emerging G12D-, G12V-, and pan-KRAS strategies and dissect resistance architectures involving EGFR feedback, RTK/MAPK/PI3K pathway reactivation, phenotypic plasticity, stromal constraints, and immune or metabolic adaptation. We further discuss resistance-informed combination therapy, targeted protein degraders, immune-based approaches, antibody-drug conjugates, biomarker-guided sequencing, and strategies for rare KRAS variants. Particular attention is given to how allele identity, tumor lineage, and adaptive signaling jointly shape therapeutic vulnerability. By framing KRAS therapy through the \"same mutation, different outcomes\" paradigm, this review provides a context-informed roadmap for extending KRAS-directed precision oncology beyond G12C monotherapy.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71050"},"PeriodicalIF":14.1,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13639538/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correction to "Type 2 Diabetes Mellitus: Molecular Pathogenesis and Therapeutic Interventions". 更正“2型糖尿病：分子发病机制和治疗干预”。

IF 14.1

MedComm Pub Date : 2026-10-06 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.70968

引用次数: 0

Multifunctional Hydrogels: Rational Design and Application in Regenerative Medicine. 多功能水凝胶：合理设计及其在再生医学中的应用。

IF 14.1

MedComm Pub Date : 2026-10-06 eCollection Date: 2026-10-01 DOI: 10.1002/mco2.71046

Linyang Song, Epiphane K Silli, Yazhen Xu, Huixia Lv, Ruoxian Song

{"title":"Multifunctional Hydrogels: Rational Design and Application in Regenerative Medicine.","authors":"Linyang Song, Epiphane K Silli, Yazhen Xu, Huixia Lv, Ruoxian Song","doi":"10.1002/mco2.71046","DOIUrl":"10.1002/mco2.71046","url":null,"abstract":"Multifunctional hydrogels have emerged as advanced biomaterial platforms capable of integrating structural support, therapeutic delivery, and biological regulation to address the complex requirements of regenerative medicine. Their unique ability to mimic native extracellular matrix environments through tunable biochemical and biophysical properties has enabled broad applications in tissue repair and regeneration. This review provides a comprehensive overview of the rational design principles, fabrication strategies, and biomedical applications of multifunctional hydrogels. The fundamental relationships between polymer composition, crosslinking mechanisms, network architecture, and biological performance were firstly discussed, highlighting how these parameters regulate mechanical properties, degradation behavior, and cellular interactions. Subsequently, representative hydrogel systems, including natural polymers, synthetic polymers, and hybrid composites, are critically compared regarding their advantages, limitations, and suitability for different regenerative scenarios. We further examine functional strategies such as controlled therapeutic delivery, immunomodulation, cell encapsulation, and stimuli-responsive regulation, with emphasis on their mechanisms and translational potential. Applications in wound healing, bone and cartilage regeneration, neural repair, and cardiovascular tissue engineering are discussed alongside current clinical challenges. Finally, we highlight key barriers including scalability, standardization, regulatory considerations, and future opportunities toward clinically translatable multifunctional hydrogel technologies.","PeriodicalId":94133,"journal":{"name":"MedComm","volume":"7 10","pages":"e71046"},"PeriodicalIF":14.1,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13639544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149120964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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