Expert Review of Proteomics最新文献

Advances and applications of clinical proteomics in precision medicine. 临床蛋白质组学在精准医学中的研究进展及应用。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-09-21 DOI: 10.1080/14789450.2025.2560919

Salwa Alshehri, Rui Vitorino, Ohud Saleh, Samah Al-Harthi, Alaa Alahmadi, Reem Alotibi, Simone C da Silva Rosa, Aya Osama, Sameh Magedeldin, Dana Alhattab, Abdul-Hamid Emwas, Mariusz Jaremko

{"title":"Advances and applications of clinical proteomics in precision medicine.","authors":"Salwa Alshehri, Rui Vitorino, Ohud Saleh, Samah Al-Harthi, Alaa Alahmadi, Reem Alotibi, Simone C da Silva Rosa, Aya Osama, Sameh Magedeldin, Dana Alhattab, Abdul-Hamid Emwas, Mariusz Jaremko","doi":"10.1080/14789450.2025.2560919","DOIUrl":"10.1080/14789450.2025.2560919","url":null,"abstract":"Introduction: Clinical proteomics has become a pivotal component of precision medicine, significantly advancing the understanding of disease mechanisms and informing therapeutic strategies. This review explores how clinical proteomics is transforming diagnostic and therapeutic approaches across multiple fields.Areas covered: This review highlights recent developments and applications of clinical proteomics in cardiovascular and neurological disorders, as well as its impact on drug development. Technologies such as mass spectrometry and protein microarrays have enhanced diagnostic precision, facilitated the discovery of novel biomarkers, and uncovered new therapeutic targets. In cardiovascular medicine, proteomics supports early disease detection and patient risk stratification, while in neurology, it helps identify disease-specific protein signatures that guide targeted interventions. The integration of proteomics with databases like Universal Protein Resource (UniProt) and the Human Protein Atlas, alongside the use of advanced bioinformatics tools, has streamlined data analysis and accelerated the design of personalized therapies.Expert opinion: Clinical proteomics is rapidly evolving, offering unprecedented opportunities to refine diagnostics, personalize therapies, and improve patient outcomes. Overcoming current challenges in standardization and validation will be essential for its full integration into clinical practice.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"1-20"},"PeriodicalIF":2.8,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MRMAssayDB: a comprehensive integrated resource for targeted proteomics assays. MRMAssayDB：一个综合性的靶向蛋白质组学分析资源。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-09-18 DOI: 10.1080/14789450.2025.2557023

Yassene Mohammed, Pallab Bhowmick, Christoph H Borchers

{"title":"MRMAssayDB: a comprehensive integrated resource for targeted proteomics assays.","authors":"Yassene Mohammed, Pallab Bhowmick, Christoph H Borchers","doi":"10.1080/14789450.2025.2557023","DOIUrl":"10.1080/14789450.2025.2557023","url":null,"abstract":"Introduction: Targeted quantitative proteomics is vital for accurate protein measurement in biological samples. Techniques like Multiple Reaction Monitoring (MRM or SRM) and Parallel Reaction Monitoring (PRM), often used with isotopically labeled internal standards, provide absolute quantification, and represent the current gold standard. However, developing and validating assays for individual proteins remains labor-intensive. Several repositories, such as CPTAC, SRMAtlas, PanoramaWeb, and PeptideTracker host targeted assay data with varying levels of detail. MRMAssayDB is an integrated platform that hosts and annotates the curated targeted proteomics assays from these resources.Areas covered: First launched in 2018 and updated in 2021, the latest release of MRMAssayDB includes over 1.1 million assays for 939,000 peptides, enabling quantification of 61,000 proteins from 146 organisms. The database also maps proteins to 19,000 Gene Ontology terms and 4,000 biological pathways. A newly integrated visualization module projects peptide assays onto Alphafold-predicted 3D protein structures, allowing users to examine peptide locations, post-translational modifications, and disease mutations while also supporting mapping to structures in the Protein Data Bank (PDB).Expert opinion: MRMAssayDB significantly improves access to validated proteotypic peptides and transition data, facilitating efficient assay selection and quantitative panel building for researchers in targeted proteomics. Availability: http://mrmassaydb2.proteomicscentre.com.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"1-12"},"PeriodicalIF":2.8,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144977018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proteomic profiling of cerebrospinal fluid reveals pathophysiology changes and diversity of treatment response in pediatric Streptococcus pneumoniae meningitis. 脑脊液蛋白质组学分析揭示了儿童肺炎链球菌脑膜炎的病理生理变化和治疗反应的多样性。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-09-01 Epub Date: 2025-08-03 DOI: 10.1080/14789450.2025.2538654

Jing Wei, Binglin Jian, Liang Zhu, Linyun Guo, Jidong Du, Yuncui Yu, Xixi Zhang, Yunyan Wu, Wei Sun, Zhengguang Guo, Kui Zhu, Peng Guo, Lulu Jia, Gang Liu

{"title":"Proteomic profiling of cerebrospinal fluid reveals pathophysiology changes and diversity of treatment response in pediatric Streptococcus pneumoniae meningitis.","authors":"Jing Wei, Binglin Jian, Liang Zhu, Linyun Guo, Jidong Du, Yuncui Yu, Xixi Zhang, Yunyan Wu, Wei Sun, Zhengguang Guo, Kui Zhu, Peng Guo, Lulu Jia, Gang Liu","doi":"10.1080/14789450.2025.2538654","DOIUrl":"10.1080/14789450.2025.2538654","url":null,"abstract":"Background: Streptococcus pneumoniae meningitis (SPM) is a critical pediatric infection with a high mortality rate. This study aimed to investigate changes in the cerebrospinal fluid (CSF) proteome in SPM patients and identify biomarkers for SPM diagnosis and treatment monitoring.Research design and methods: Here, we retrospectively collected and evaluated CSF proteomes of 47 SPM and 116 non-CNS-infected patients (Control), including longitudinal samples from 11 SPM patients. Candidate biomarkers were validated by parallel reaction monitoring (PRM) in 146 samples (36 longitudinal/12 SPM, 110 Control) and evaluated via receiver operating characteristic (ROC) analysis.Results: We identified 648 differentially expressed proteins (DEPs) associated with complement activation and oxidative stress. SPM patients with abnormal CSF white blood cells (SPMAN) exhibited dysregulation in coagulation and fibrinolysis, while those with normal counts (SPMN) displayed redox homeostasis alterations. The ELANE and H4C1 panel achieved a superior diagnostic accuracy (AUC = 0.967), and the combination of IGKV1-17, IGKC, and IGKV4-1 effectively tracked therapy response (AUC = 0.872).Conclusion: This study establishes CSF proteomic signatures of pediatric SPM, providing dual-purpose biomarker panels for clinical diagnosis and treatment monitoring, with implications for targeted interventions.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"345-361"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144700167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sample preparation and cleanup methods for clinical top-down proteomics. 临床自上而下蛋白质组学的样品制备和清理方法。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-09-01 Epub Date: 2025-07-29 DOI: 10.1080/14789450.2025.2539913

Amal Mohamed Kamal, Amy Carfagno, Cynthia Nagy, Luca Fornelli

{"title":"Sample preparation and cleanup methods for clinical top-down proteomics.","authors":"Amal Mohamed Kamal, Amy Carfagno, Cynthia Nagy, Luca Fornelli","doi":"10.1080/14789450.2025.2539913","DOIUrl":"10.1080/14789450.2025.2539913","url":null,"abstract":"Introduction: The investigation of different proteoforms in clinical samples is a promising approach to elucidate the molecular mechanisms of diseases. Furthermore, proteoform analysis holds great potential for identifying disease-specific biomarkers and targets for personalized medicine. Despite advances in top-down proteomics (TDP) instrumentation, sample preparation and cleanup remain challenging. Work in this area has focused on developing rapid, cost-effective, and less-labor-intensive protocols aimed at minimizing the introduction of artefactual modifications to endogenous proteoforms or bias in proteoform recovery during sample processing.Area covered: To inform the selection of sample processing approaches in clinical TDP, this review summarizes state-of-the-art targeted (i.e. affinity and non-affinity-based enrichment) and untargeted (i.e. gel-based fractionation) sample preparation protocols. In addition, currently available offline and online sample cleanup procedures (e.g. dialysis, solid-phase extraction, filter-aided sample preparation, precipitation, and solid-phase protein preparation) are reviewed, highlighting their effectiveness for desalting and/or detergent removal.Expert opinion: TDP demonstrates great potential in the clinical setting due to its ability to capture disease-specific proteoforms commonly overlooked in traditional diagnostic assays. The establishment of standardized guidelines for reproducible clinical TDP workflows is essential to leverage advances in sample preparation techniques and analytical instrumentation to facilitate wider adoption of TDP for clinical applications.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"329-343"},"PeriodicalIF":2.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12433189/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent developments in spatial proteomics with MALDI mass spectrometry imaging: a journey toward clinical adoption. 空间蛋白质组学与MALDI质谱成像的最新进展：走向临床应用的旅程。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-09-01 Epub Date: 2025-07-22 DOI: 10.1080/14789450.2025.2537212

Andrew Smith

引用次数: 0

A 2025 perspective on the role of machine learning for biomarker discovery in clinical proteomics. 展望2025年机器学习在临床蛋白质组学中发现生物标志物的作用。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-08-09 DOI: 10.1080/14789450.2025.2545828

Charlotte Adams, Wout Bittremieux

{"title":"A 2025 perspective on the role of machine learning for biomarker discovery in clinical proteomics.","authors":"Charlotte Adams, Wout Bittremieux","doi":"10.1080/14789450.2025.2545828","DOIUrl":"10.1080/14789450.2025.2545828","url":null,"abstract":"Introduction: Machine learning holds significant promise for accelerating biomarker discovery in clinical proteomics, yet its real-world impact remains limited by widespread methodological pitfalls and unrealistic expectations.Areas covered: In this perspective, we critically examine the application of machine learning for biomarker discovery in clinical proteomics, emphasizing that algorithmic novelty alone cannot compensate for issues such as small sample sizes, batch effects, overfitting, data leakage, and poor model generalization.Expert opinion: We caution against the uncritical application of complex models, such as deep learning architectures, that often exacerbate these problems, offering limited interpretability and negligible performance gains in typical clinical proteomics datasets. Instead, we advocate for the realistic and responsible use of machine learning, grounded in rigorous study design, appropriate validation strategies, and transparent, reproducible modeling practices. Emphasizing simplicity, interpretability, and domain awareness over hype-driven complexity is essential if machine learning is to fulfill its translational potential in the clinic.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"1-12"},"PeriodicalIF":2.8,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144796023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Repurposing proteomic nanoLC-MS platforms for untargeted metabolomics: evaluating DIA and polarity switching performance in human plasma. 重新利用蛋白质组学纳米质谱平台进行非靶向代谢组学：评估人血浆中的介质和极性切换性能。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-08-01 Epub Date: 2025-07-24 DOI: 10.1080/14789450.2025.2537210

Frederico G Pinto, Alexander D Giddey, Nesrin Mohamed, Rauda S B Almarri, Munazza Murtaza, Nasna Nassir, Omer S Alkhnbashi, Mohammed J Uddin, Nelson C Soares

{"title":"Repurposing proteomic nanoLC-MS platforms for untargeted metabolomics: evaluating DIA and polarity switching performance in human plasma.","authors":"Frederico G Pinto, Alexander D Giddey, Nesrin Mohamed, Rauda S B Almarri, Munazza Murtaza, Nasna Nassir, Omer S Alkhnbashi, Mohammed J Uddin, Nelson C Soares","doi":"10.1080/14789450.2025.2537210","DOIUrl":"10.1080/14789450.2025.2537210","url":null,"abstract":"Background: Many of the advanced MS methods applied in proteomics such as nanoflow LC-MS with data-independent acquisition have yet to be verified and/or optimized on metabolomics applications.Research design and methods: This study evaluates the feasibility of repurposing a proteomics-optimized nanoLC-MS platform for untargeted metabolomics. Using NIST SRM 1950 reference human plasma, we compared the performance of polarity switching and separate polarity modes under DIA conditions, focusing on metabolite coverage, annotation, and response linearity.Results: We observed, in the separate polarity and switching polarity runs 669 and 353 features in (+) mode and 558 and 446 features in (-) mode, respectively. A total of 233 metabolites were annotated using the (±) separate polarities and 179 using the (±) switching polarity based on MassBank of North America (MoNA) public MS library and filtered with the Human Metabolome Database (HMDB). Both switching and separate polarity methods performed well regarding response linearities which were investigated by spiking some amino acid compounds into plasma matrix.Conclusions: The polarity switching DIA approach for metabolomics reduced sample consumption and analysis time, but led to fewer detected features and annotations compared to separate polarity runs. These findings support the use of unified nanoLC-MS platforms for integrated multi-omics analysis.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"307-314"},"PeriodicalIF":2.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proteomic technologies for profiling cell-membrane/secretome interactions in brain metastatic cancer progression. 分析脑转移癌进展中细胞膜/分泌组相互作用的蛋白质组学技术。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-08-01 Epub Date: 2025-07-23 DOI: 10.1080/14789450.2025.2536061

Iulia M Lazar

{"title":"Proteomic technologies for profiling cell-membrane/secretome interactions in brain metastatic cancer progression.","authors":"Iulia M Lazar","doi":"10.1080/14789450.2025.2536061","DOIUrl":"10.1080/14789450.2025.2536061","url":null,"abstract":"Introduction: The ability of cancer cells to disseminate from the primary tumor and form metastatic lesions frequently leads to fatal outcomes. Recently, however, it has been recognized that this process is driven by complex interactions between the cancer and the neighboring cells, and, overall, made possible by a supportive tumor microenvironment. The emergence of high-throughput technologies is expected to bring much-needed clarity to unraveling the players and intricate communication pathways that promote metastatic progression.Areas covered: In this report, the impact of mass spectrometry and proteomic technologies on deciphering the cross-talk between cancer and tumor microenvironment cells is discussed. Focus is placed on the role of cell-membrane and secretome proteins as the main enablers of this cross-talk, and on the challenges presented by metastatic tumors that evolve in the brain. Future prospects are assessed in the context of recent biology, technology, and data analysis breakthroughs.Expert opinion: Advancements in high-throughput proteomic technologies, complemented by the exciting potential of new disease model systems and data processing abilities of artificial intelligence, are expected to bring groundbreaking progress in deciphering the fundamental biological mechanisms that support cancer behavior and metastatic development, revealing novel therapeutic targets, and guiding innovative intervention approaches.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"297-306"},"PeriodicalIF":2.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144651031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping of volatile organic compounds in children's saliva using headspace sorbent extraction coupled to TD-GC-MS. 顶空吸附剂萃取联用TD-GC-MS测定儿童唾液中挥发性有机化合物。

IF 2.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-08-01 Epub Date: 2025-07-24 DOI: 10.1080/14789450.2025.2537254

Efstathios A Elia, Anna Zissimou, Photini Papaioakeim, Agapios Agapiou

{"title":"Mapping of volatile organic compounds in children's saliva using headspace sorbent extraction coupled to TD-GC-MS.","authors":"Efstathios A Elia, Anna Zissimou, Photini Papaioakeim, Agapios Agapiou","doi":"10.1080/14789450.2025.2537254","DOIUrl":"10.1080/14789450.2025.2537254","url":null,"abstract":"Objectives: Saliva, an easily accessible biofluid, has emerged as a promising source of biomarkers for noninvasive disease diagnostics. Human saliva comprises a complex mixture of volatile organic compounds (VOCs) originating from various sources, including exhaled breath, diet, environmental factors, and the body's metabolic activity. Their presence in saliva can be influenced by several factors, including age, gender, diet, lifestyle, health status, and the oral microbiome.Methods: Qualitative analysis of salivary VOCs as potential indicators of specific lifestyles and early environmental exposure in children was performed. Saliva samples from 40 children were analyzed using a headspace high-capacity sorptive extraction (HS-HiSorb) technique coupled with thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). The method was developed and conditions such as the choice of sorbent material and sample preparation steps were optimized.Results: A range of VOCs in the saliva samples, including alcohols, aldehydes, ketones, nitrogen and sulfur containing compounds, organic acids, esters and hydrocarbons were identified and a selection of them were quantified. The influence of the HiSorb coating composition and the extraction parameters on the observed chromatographic areas of each analyte were also evaluated.Conclusion: A green sample preparation method for the qualitative analysis of VOCs in the saliva of children was developed.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"315-324"},"PeriodicalIF":2.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proteomic blood-biomarkers for personalized risk stratification of diabetic retinopathy patients. 糖尿病视网膜病变患者个性化风险分层的蛋白质组学血液生物标志物。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2025-07-01 Epub Date: 2025-07-20 DOI: 10.1080/14789450.2025.2534399

Bent Honoré, Lasse Jørgensen Cehofski, Steffen Heegaard, Ivan Brandslund, Henrik Vorum, Carina Slidsborg

{"title":"Proteomic blood-biomarkers for personalized risk stratification of diabetic retinopathy patients.","authors":"Bent Honoré, Lasse Jørgensen Cehofski, Steffen Heegaard, Ivan Brandslund, Henrik Vorum, Carina Slidsborg","doi":"10.1080/14789450.2025.2534399","DOIUrl":"10.1080/14789450.2025.2534399","url":null,"abstract":"Introduction: Diabetes mellitus (DM) is a challenging chronic disease worldwide. The incidence is expected to rise dramatically by 2030 due to smoking, obesity, and aging population, increasing the public health burden in coming years. Diabetic retinopathy (DR) is a common microvascular complication and a leading cause of blindness among working-age individuals. Understanding the proteomic mechanisms driving disease progression and visual loss is of paramount importance when laying novel strategies for managing patients in clinical practice.Areas covered: We summarize proteomic studies addressing molecular biomarkers in human blood for DR. We discuss methodological advantages and challenges. Proteomic technology advancement has reached a level where even low-abundance proteins related to disease can be detected in blood. The pooled results of these studies suggest that the biomarkers are specific to the disease stage and hold promise for personalized risk stratification in DR.Expert opinion: With the development of advanced mass spectrometry technology for the investigation of biomarkers in blood, this research area is expected to advance in the future. Similarly, it is expected that novel blood-based biomarkers for DR will be validated in international studies and implemented in clinical practice. Therefore, future perspectives hold promises of personalized risk profiling for diagnosis, disease progression, and optimal choice of treatment.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"287-295"},"PeriodicalIF":3.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144627613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0