Expert Opinion on Drug Discovery最新文献

The design of multi-target ligands and their role in schizophrenia therapy: an update. 多靶点配体的设计及其在精神分裂症治疗中的作用：最新进展。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-08 DOI: 10.1080/17460441.2026.2669617

Zarko Gagic, Marija Popovic-Nikolic, Marija Carapic, Selma Zukic, Slavica Oljacic, Katarina Nikolic

{"title":"The design of multi-target ligands and their role in schizophrenia therapy: an update.","authors":"Zarko Gagic, Marija Popovic-Nikolic, Marija Carapic, Selma Zukic, Slavica Oljacic, Katarina Nikolic","doi":"10.1080/17460441.2026.2669617","DOIUrl":"https://doi.org/10.1080/17460441.2026.2669617","url":null,"abstract":"Introduction: Schizophrenia is a complex psychiatric disorder with a partially understood pathophysiology involving multiple neurotransmitter systems and receptor families in its onset and progression. Modern therapeutic approaches for effective schizophrenia treatment require multi-target drug actions that exert therapeutic effects through interactions with various neurotransmitter systems.Areas covered: This review provides an updated overview of schizophrenia pathophysiology, focusing on current dopaminergic, serotonergic, and glutamatergic hypotheses, with particular attention to multi-target antipsychotics and the rationale for their development. The literature was searched using relevant online scientific journal databases. For the overview of recent advances and novel multi-target ligands, studies published primarily between 2020 and 2026 were included. State-of-the-art strategies for designing multi-target ligands, including molecular modeling and computer-aided drug design approaches, are discussed, along with the opportunities and limitations associated with multifunctional compounds.Expert opinion: Advancing schizophrenia treatment depends on the ongoing development of well-balanced multi-target ligands, which require careful adjustment of affinities across multiple neurotransmitter systems and receptor families while avoiding off-target interactions and maintaining optimal physicochemical and pharmacokinetic properties. Nevertheless, multi-target antipsychotics offer substantial advantages in therapy, positioning them as a transformative direction in antipsychotic drug discovery.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-16"},"PeriodicalIF":4.9,"publicationDate":"2026-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147835386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The application of fluorinated α-amino acids to drug discovery techniques. 氟化α-氨基酸在药物发现技术中的应用。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-06 DOI: 10.1080/17460441.2026.2667920

Paul Richardson

{"title":"The application of fluorinated α-amino acids to drug discovery techniques.","authors":"Paul Richardson","doi":"10.1080/17460441.2026.2667920","DOIUrl":"https://doi.org/10.1080/17460441.2026.2667920","url":null,"abstract":"Introduction: While fluorinated amino acids (FAAs) have been utilized for the discovery and development of both small molecules and therapeutic peptides, it is important to also recognize the stand-alone value of these entities. The ability of fluorine to replace hydrogen in naturally occurring amino acids (or indeed be incorporated in unnatural/novel amino acids) without a significant perturbation in the steric properties of the molecule allows direct substitutions to seamlessly occur, while the 'unique' nature of the fluorine atom itself allows these 'analogues' to be utilized in biological systems.Areas covered: This review discusses several areas where fluorinated amino acids (FAAs) have been directly employed within drug discovery. While by no means comprehensive, the examples and case studies described are intended not only to demonstrate current applications but also to illustrate both the vast potential and the array of challenges that still arise in these areas.Expert opinion: While progress has been made, there is substantial room for growth and innovation in each field. For example, a better understanding of the factors critical in defining the selectivity and kinetics of irreversible enzyme inhibition should enable better FAA-based derivatives to be designed to further probe these entities as therapeutics. While the examples presented here utilize the fluorine in both the design and imaging element of a single theranostic agent, complementing techniques, such as 19F-NMR with cryo-EM for fragment-based drug discovery, provide a compelling path for more efficient drug discovery.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-21"},"PeriodicalIF":4.9,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147835788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In vitro prediction of the immunogenicity of therapeutic proteins: state of the art and current challenges and perspectives. 治疗性蛋白免疫原性的体外预测：现状和当前的挑战和观点。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-04 DOI: 10.1080/17460441.2026.2665791

Olivier Fardel, Emna Mahfoudhi, Laurence Launay, Amélie Moreau, Claire Denizot, David Malnoë, Yannick Parmentier

{"title":"In vitro prediction of the immunogenicity of therapeutic proteins: state of the art and current challenges and perspectives.","authors":"Olivier Fardel, Emna Mahfoudhi, Laurence Launay, Amélie Moreau, Claire Denizot, David Malnoë, Yannick Parmentier","doi":"10.1080/17460441.2026.2665791","DOIUrl":"10.1080/17460441.2026.2665791","url":null,"abstract":"Introduction: Immunogenicity of therapeutic proteins is a major concern because it may compromise their clinical use and efficacy. Preclinical prediction of anti-drug antibody development using in vitro assays is therefore a challenge for candidate biologics.Areas covered: This review, based on a thorough literature search of the PubMed database up to December 2025, provides an overview of in vitro assays predicting biologic immunogenicity, including antigen internalization assay, dendritic cell activation assay, peptide-MHC II affinity measurement, MHC‑associated peptide proteomics (MAPPs) assay, and T cell activation/proliferation assays. The main features and applications of these assays are summarized, with special emphasis on their advantages and limitations.Expert opinion: Although in vitro immunogenicity assays are proposed to discriminate between low- and high-immunogenic biologics, they face numerous challenges. These include selecting the most appropriate test(s), lack of standardization in methods and technical parameters, defining positivity thresholds, high costs, the need for specialized equipment and trained personnel, the complexity and labor-intensive nature of assays, and the difficulty of translating in vitro results into clinical immunogenicity outcomes. Additional assay validation studies are undoubtedly required to better define the implementation and robustness of in vitro immunogenicity prediction for biologics, which could be advantageously combined with in silico approaches.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-19"},"PeriodicalIF":4.9,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing drug discovery for inflammatory bowel diseases through human intestinal organoid-based models. 通过人类肠道类器官模型推进炎症性肠病药物的发现。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-04-02 DOI: 10.1080/17460441.2026.2650549

Manuel B Braga-Neto, Samreen Jatana, Florian Rieder, Andrei I Ivanov

{"title":"Advancing drug discovery for inflammatory bowel diseases through human intestinal organoid-based models.","authors":"Manuel B Braga-Neto, Samreen Jatana, Florian Rieder, Andrei I Ivanov","doi":"10.1080/17460441.2026.2650549","DOIUrl":"10.1080/17460441.2026.2650549","url":null,"abstract":"Introduction: Inflammatory bowel diseases (IBD), including Crohn's disease and ulcerative colitis, are chronic inflammatory conditions that affect millions of patients worldwide. Despite recent advances, available IBD drugs targeting the immune system have limited efficacy, and disease recurrence is common.Areas covered: The authors describe reported applications of human intestinal organoids to understand the mechanisms of action and predict patient response to current IBD therapies. Furthermore, they also outline the potential of human intestinal organoid-based technologies to accelerate drug discovery in IBD and propose a framework to bridge discoveries from bench to bedside.Expert opinion: The lag in development of novel IBD therapies reflects the complex nature of the disease and our poor understanding of its pathogenesis. The future breakthrough in understanding IBD and developing novel IBD drugs requires development and adaptation of novel disease-relevant experimental models, including organoid-based models, to evaluate the efficiency and accurately predict response to therapy. Indeed, presently the utilization of intestinal organoids in the IBD field has been limited and was not used in the development of any of the currently available therapies, including biologics (anti-TNF, anti-12/IL23, anti-α4β7) and small molecules. The authors affirm that a stepwise approach would help accelerate future organoid-based drug discovery efforts.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"491-506"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147497863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent advances in purpose-built 3D bioprinted cancer models for drug development. 用于药物开发的生物3D打印癌症模型的最新进展。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-03-30 DOI: 10.1080/17460441.2026.2642320

Louise Ramos, Meghan Robinson, Nada Lallous, Ryan Flannigan, Mads Daugaard

{"title":"Recent advances in purpose-built 3D bioprinted cancer models for drug development.","authors":"Louise Ramos, Meghan Robinson, Nada Lallous, Ryan Flannigan, Mads Daugaard","doi":"10.1080/17460441.2026.2642320","DOIUrl":"10.1080/17460441.2026.2642320","url":null,"abstract":"Introduction: There is an ongoing effort to develop novel therapies for cancer; however, there is often a failure in current preclinical models to translate clinical therapeutic outcomes. This disconnect could be remedied with more physiologically accurate preclinical models. We highlight a selection of recent studies that demonstrate how innovative 3-dimensional (3D) techniques enable more realistic in vitro modeling and accurate evaluation of anti-cancer drug responses.Areas covered: Papers discussed were selected with the aim of highlighting recent significant advances towards more translationally relevant models. 75 articles were initially compiled through online journal database searches dating from 2018 to the present, and refined to include only works which illustrated significant improvements towards clinical relevance, leaving 11 articles. We cover advances including use of tissue fragmentation and spatial mapping to replicate tumor-stroma interactions, and manipulation of bioink chemistry to mimic native tissue stiffness. We describe novel technologies for generating 3D biochemical and hypoxic gradients and integration of sacrificial bioinks to generate perfusable microvasculature. We cover the applicability of these innovative models for testing various anti-cancer therapeutics and predicting patient-specific drug sensitivities.Expert opinion: We discuss the potential of 3D bioprinted models for predicting patient-specific responses in developing tailored therapies towards precision oncology.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"475-490"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Marine metabolomics for bioactive material discovery: current trends, challenges, and future perspectives. 生物活性物质发现的海洋代谢组学：当前趋势、挑战和未来展望。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-04-27 DOI: 10.1080/17460441.2026.2662416

Jia-Hui Ma, Fazlurrahman Khan, Young-Mog Kim, Tae-Hee Kim, Won-Kyo Jung

{"title":"Marine metabolomics for bioactive material discovery: current trends, challenges, and future perspectives.","authors":"Jia-Hui Ma, Fazlurrahman Khan, Young-Mog Kim, Tae-Hee Kim, Won-Kyo Jung","doi":"10.1080/17460441.2026.2662416","DOIUrl":"10.1080/17460441.2026.2662416","url":null,"abstract":"Introduction: Marine metabolomics has emerged as a powerful approach for elucidating the chemical basis of marine biodiversity, ecological interactions, and organismal responses to environmental change. By profiling low-molecular-weight metabolites, it provides a functional link between genotype, phenotype, and environment.Areas covered: This review is based on a structured survey of literature published from 2015 to 2025, retrieved from major scientific databases including Web of Science, Scopus, and PubMed, using keywords related to marine metabolomics, mass spectrometry, and chemical ecology, and focusing on peer-reviewed studies. This review synthesizes recent advances and core challenges in marine metabolomics. Specifically, the authors emphasize the strong context dependence of metabolite expression spatial, temporal, and ecological scales, driven by environmental heterogeneity, biological interactions, and exposure history.Expert opinion: Despite significant methodological progress, the field continues to face persistent bottlenecks across the research pipeline, including preservation of in situ metabolic states during sampling, severe matrix interference, limited structural annotation of marine-specific metabolites, challenges in ecologically relevant functional validation, and difficulties in translating laboratory findings into real-world applications. Emerging integrated strategies, including multidimensional mass spectrometry, advanced data analytics, stable isotope tracing, spatial metabolomics, and ecologically realistic experimental systems, are highlighted as key pathways to improve structural resolution, functional interpretation, causal inference, and translational robustness.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"533-552"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Therapeutic aptamers in drug discovery: future elements of the pharmaceutical arsenal? 药物发现中的治疗适体：药物武器库的未来元素？

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-04-02 DOI: 10.1080/17460441.2026.2652406

Krushna P Dhorde, Ipsita Roy

引用次数: 0

Leveraging molecular dynamics simulations to study psychedelics and their receptors in future drug development. 利用分子动力学模拟研究致幻剂及其受体在未来药物开发中的应用。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-03-23 DOI: 10.1080/17460441.2026.2649897

Cong Zhang, Pu Jiang, Yibo Wang, Xiaohui Wang

{"title":"Leveraging molecular dynamics simulations to study psychedelics and their receptors in future drug development.","authors":"Cong Zhang, Pu Jiang, Yibo Wang, Xiaohui Wang","doi":"10.1080/17460441.2026.2649897","DOIUrl":"10.1080/17460441.2026.2649897","url":null,"abstract":"Introduction: Psychedelics show great promise for treating Central Nervous System (CNS) disorders but are limited by side effects like hallucinations. Molecular dynamics (MD) simulations offer atomic-level insights into receptor interactions, helping to overcome these challenges and guide the development of safer, more effective psychedelic-based therapies.Areas covered: This perspective reviews how MD simulations provide atomic-level insights into key psychedelic-receptor mechanisms: biased signaling, receptor multimerization, and lipid modulation. We also discuss MD's role in validating cryo-EM binding sites, alongside challenges in force fields, structural data, and system complexity that must be overcome to advance rational CNS drug design.Expert opinion: MD simulations are transforming psychedelic drug discovery from serendipity to precision design. While immediate impact lies in accelerating lead optimization through in silico screening of biased signaling and multimer-selective compounds, broader adoption requires closing the translational gap between simulation predictions and in vivo outcomes. Key advancements will come from AI-refined force fields, integrative structural modeling of receptor complexes, and coupling MD with kinetic pharmacology. The ultimate goal is a predictive 'digital pharmacology' platform. Within five years, cloud-based MD screening is expected to become standard, delivering safer, mechanism-based clinical candidates and paving the way for personalized neurotherapeutics.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"465-473"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147485276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Therapeutic targeting of adhesion GPCRs: a status update and future potential. 粘附gpcr的治疗靶向：现状更新和未来潜力。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-04-24 DOI: 10.1080/17460441.2026.2662413

Jesse D Stillwell, Maryam Ahmadian Elmi, Rashed R Parag, Erwin G Van Meir

{"title":"Therapeutic targeting of adhesion GPCRs: a status update and future potential.","authors":"Jesse D Stillwell, Maryam Ahmadian Elmi, Rashed R Parag, Erwin G Van Meir","doi":"10.1080/17460441.2026.2662413","DOIUrl":"10.1080/17460441.2026.2662413","url":null,"abstract":"Introduction: Adhesion G-Protein Coupled Receptors (aGPCRs) represent the second largest GPCR family and consist of 32 members in humans, of which 19 are orphan receptors. Despite making up a substantial portion of GPCRs, there are no clinically approved therapeutics targeting them or using them in clinical applications. aGPCRs have functional roles in numerous tissues and their dysregulation through mutations or expression is associated with a variety of diseases, including cancer. Therefore, there is strong interest in therapeutic targeting aGPCRs or their controlled pathways.Areas covered: The authors showcase the currently available approaches (small molecules, antibodies, knockouts/downs, peptides, nanoparticles, and cell-based therapies) that modulate aGPCR function or pathways. Furthermore, the authors discuss aGPCRs with potential for future therapeutic targeting. Of all aGPCRs, 14 are being exploited as targets and 7 have potential. For the remaining 11, a brief description of their function and any known involvement in disease were included.Expert opinion: The field is currently hampered by lack of knowledge about endogenous ligands and downstream signaling for aGPCRs. Once this knowledge gap is overcome, a clear library of agonists and antagonists can be developed, unleashing successful and widespread aGPCR exploitation and modulation. In the coming years, ligand identification will accelerate, allowing more aGPCR therapeutic advances.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"447-463"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging machine learning for selective cannabinoid ligand discovery: methods, challenges, and opportunities. 利用机器学习进行选择性大麻素配体发现：方法、挑战和机遇。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-04-21 DOI: 10.1080/17460441.2026.2661209

Bailang Liu, Jie Liu, Wenjing Guo, Ann Varghese, Menghang Xia, Ruili Huang, Tucker A Patterson, Huixiao Hong

{"title":"Leveraging machine learning for selective cannabinoid ligand discovery: methods, challenges, and opportunities.","authors":"Bailang Liu, Jie Liu, Wenjing Guo, Ann Varghese, Menghang Xia, Ruili Huang, Tucker A Patterson, Huixiao Hong","doi":"10.1080/17460441.2026.2661209","DOIUrl":"10.1080/17460441.2026.2661209","url":null,"abstract":"Introduction: Selective modulation of cannabinoid receptors, particularly achieving CB2 selectivity over CB1, represents a promising strategy for developing safer therapeutics with reduced psychotropic effects. This review examines how machine learning (ML) approaches can address persistent challenges in cannabinoid receptors selectivity and accelerate drug discovery.Areas covered: The authors summarize current ML-based methodologies applied to cannabinoid ligand discovery, focusing on strategies for predicting receptor affinity and selectivity. The literature covered was identified through a PubMed search followed by manual screening to retain studies directly relevant to cannabinoid-focused AI-driven ligand discovery. The review discusses feature engineering approaches, including molecular fingerprints, physicochemical descriptors, and SMILES-based representations, as well as classification and regression algorithms for selectivity prediction. The authors evaluate model performance metrics, dataset limitations, and interpretability challenges. Recent advances in deep learning and generative models for de novo molecular design are also highlighted, with emphasis on their potential to expand chemical space and improve selective ligand identification.Expert opinion: ML has significantly advanced the prediction of cannabinoid receptor selectivity, yet progress remains constrained by data quality, endpoint inconsistency, and limited interpretability. Future efforts integrating curated datasets, mechanistically informed modeling, and generative AI frameworks are expected to substantially enhance the discovery of selective cannabinoid therapeutics.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"517-532"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0