ACS Publications最新文献

{"title":"Double-Responsive Metallic Magnetic Nanoparticles Based on Tumor Microenvironment \"Leverage\" Rebalancing for Triple Collaborative Cancer Therapy.","authors":"Yimei Zhang, Liqun Wei, Xiaole Yin, Yiliang Xie, Hang Gao, Bing Zhang, Zhihuan Zhao, Weihong Zhao, Min Xu","doi":"10.1021/acs.bioconjchem.5c00475","DOIUrl":"https://doi.org/10.1021/acs.bioconjchem.5c00475","url":null,"abstract":"<p><p>Targeted perturbation of redox balance through concurrent elevation of reactive oxygen species (ROS) production and glutathione (GSH) depletion has emerged as a therapeutic paradigm for triggering tumor cell apoptosis. Nevertheless, the conventional single-agent system demonstrates limited therapeutic efficacy due to insufficient oxidative stress amplification within tumor cells. Herein, we designed pH- and GSH double-responsive metallic magnetic Ag-NH₂-CoFe₂O₄@C@DOX nanoparticles (ANFCD NPs), which disrupted the redox balance within the tumor microenvironment (TME) to achieve synergistic chemodynamic therapy (CDT), photothermal therapy (PTT), and chemotherapy (CT) effects. In the acidic TME, ANFCD NPs functioned as both a Fenton catalyst and GSH depletor through the reversible redox property of Fe (II/III) and Co (I/II), inducing oxidative stress and exerting a \"leverage\" rebalancing to potentiate CDT. Additionally, ANFCD NPs showed high photothermal conversion efficiency, enhancing PTT efficacy via magnetic targeting-driven tumor accumulation. Meanwhile, they could also responsively release DOX to achieve CT. More importantly, the hyperthermia generated by ANFCD NPs not only effectively eradicated tumor cells but also boosted the CDT effect and promoted DOX release, ultimately achieving the aim of combined therapy. Therefore, such a nanomaterial is a promising therapeutic agent for disrupting redox homeostasis to augment multimodal collaborative therapy, which might show further applications in nanomedical science.</p>","PeriodicalId":29,"journal":{"name":"Bioconjugate Chemistry","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preclinical Development and Comparison of [^99mTc]Tc/[¹⁷⁷Lu]Lu-Labeled Anti-Trop2 Fc-Fused Nanobodies as Pancreatic Cancer Theranostics.","authors":"Yuan Feng, Wenzhu Hu, Xingyi Wang, Yan Wang, Zaijie Wu, Biao Yang, Yonglu Chen, Teng Li, Dawei Jiang, Yaxin Shi, Xiaoli Lan, Yongkang Gai","doi":"10.1021/acs.molpharmaceut.5c01039","DOIUrl":"https://doi.org/10.1021/acs.molpharmaceut.5c01039","url":null,"abstract":"<p><p>Antibody-based radiotheranostics hold significant promise for tumor diagnosis and treatment; however, the clinical translation of radiotherapeutic agents is significantly hindered by suboptimal pharmacokinetics, particularly undesirable retention in healthy tissues. In this study, we developed novel high-affinity anti-Trop2 nanobodies using phage display technology and then generated two VHH-Fc constructs, B9 and C10, which are recombinant single-chain antibodies fused with IgG1-Fc. These were radiolabeled with [^99mTc]Tc and [¹⁷⁷Lu]Lu. A systematic comparison was then conducted against the clinically relevant monoclonal antibody hRS7 (sacituzumab). The [^99mTc]Tc-labeled-B9 exhibited high Trop2-binding affinity, rapid tumor accumulation, and substantially decreased hepatic and renal uptake in BxPC-3 xenograft models compared with [^99mTc]Tc-hRS7. Comprehensive SPECT/CT imaging and quantitative biodistribution studies further corroborated its prolonged intratumoral retention. When radiolabeled with [¹⁷⁷Lu]Lu, [¹⁷⁷Lu]Lu-B9 maintained robust tumor uptake while demonstrating faster clearance from nontarget tissues than the monoclonal antibody (hRS7). Quantitative analysis over 168 h postinjection revealed a 56.17% reduction in hepatic uptake and a 23.68% decrease in renal uptake compared to [¹⁷⁷Lu]Lu-hRS7. In a preclinical mouse model, two-cycle administration of [¹⁷⁷Lu]Lu-B9 induced significant tumor growth inhibition, prolonged survival, and minimal systemic toxicity. These findings highlight VHH-Fc-based radiotheranostics as a promising strategy to achieve favorable tumor retention while reducing off-target organ exposure.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290360","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}

{"title":"Skin Adhesive 3D-Printable BSA-Amyloid/Cellulose Hybrid Hydrogel Film for Rapid Wound Healing and Skin Regeneration with Enhanced Antioxidant and Anti-Inflammatory Properties.","authors":"Saurabh Kumar Srivastava, Shikha Tripathi, Sakshi Agarwal, Rahul Ranjan, Somesh Agrawal, Prodyut Dhar, Eugene B Postnikov, Shilpi Chaudhary, Vinod Tiwari, Avanish Singh Parmar","doi":"10.1021/acsabm.5c01216","DOIUrl":"https://doi.org/10.1021/acsabm.5c01216","url":null,"abstract":"<p><p>Natural polymer-based hydrogels closely mimic the extracellular matrix, making them ideal for supporting cell growth and tissue regeneration. Recent advancements in tuning their porosity, morphology, and size have helped overcome key challenges in tissue engineering, such as vascularization and multicellular integration. However, their clinical use is often limited by drawbacks, such as low mechanical strength, structural instability, high production costs, and limited reproducibility. In this work, we present a skin-adhesive, 3D-printable/injectable hybrid hydrogel composed of natural protein and cellulose. This hybrid hydrogel overcomes the limitations of conventional systems by enhancing mechanical strength, scaffold stability, reproducibility, cost-effectiveness, and adhesive properties while preserving high biocompatibility and biodegradability. Using the same formulation, a wound dressing material is fabricated and applied at the wound site either by suturing or as an adhesive film. Furthermore, the hydrogel exhibits inherent antibacterial, antioxidant (60% of radical scavenging), anti-inflammatory, cell viability (up to 90%), and cell migration properties that significantly promote wound healing. This multifunctional hybrid hydrogel offers a promising solution for next-generation wound dressing applications and contributes to the advancement of bioactive and customizable materials in regenerative medicine.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recurrent Neural Networks Predict Future Peptide Aggregation for Drug Development.","authors":"Prageeth R Wijewardhane, Katelyn Smith, Jonathan Fine, Jameson R Bothe, Peter Wuelfing, Yong Liu, Gaurav Chopra","doi":"10.1021/acs.molpharmaceut.5c00314","DOIUrl":"https://doi.org/10.1021/acs.molpharmaceut.5c00314","url":null,"abstract":"<p><p>Physical stability of an active pharmaceutical ingredient (API) is a key consideration in the development of a pharmaceutical drug. Solution conditions such as pH, excipient concentrations, and storage temperatures can impact the physical stability of a therapeutic peptide in formulation. Optimizing these conditions is a critical activity in achieving a higher stability of a therapeutic peptide product. A Thioflavin T (ThioT) fluorescent reporter assay is widely used to measure the aggregation of peptide products. ThioT kinetic assays are used to predict the propensity of fibril formation by using ThioT curves for a peptide stored in a solution. However, there is no analytical relationship that can be used to relate the physical stability for different formulation conditions, resulting in execution of large-scale stability assays that require significant resources for pharmaceutical companies. Therefore, there is a need to develop new artificial intelligence (AI) methods to predict future ThioT curves in a fast and cost-effective manner. Here, we combined an experimental measure of time-varying conformational states from ThioT assays with AI models to predict peptide aggregation in different formulation conditions during drug development. We formulated the peptide aggregation problem as \"language translation\" in natural language processing, wherein the sequence of aggregation states at earlier time points was used to predict (or \"translate\") the aggregation states for future time points. We developed a new sequence-to-sequence long short-term memory (LSTM)-based recurrent neural network (RNN) model to predict entire ThioT curves at future time points (6 and 12 months) using data sets from initial and 1 month ThioT curves for different conditions. We achieved an excellent average mean absolute error (MAE) of 2.04 for the model, which was used to predict and experimentally validate ThioT curves for a 6 month time point. In contrast to the LSTM, the multilayer perceptron (MLP) baseline model showed a higher MAE of 5.17. However, at the 12 month time point, with limited training data, both models achieved comparable results with average MAEs of 4.25 and 4.45 for LSTM and MLP, respectively. Therefore, we conclude that LSTM models can be used to predict future ThioT curves only using the initial and 1 month ThioT curves as input. We believe that the use of recurrent neural network models will benefit the pharmaceutical industry to predict and explore the formulation landscape for future physical stability measurements of APIs based on short-term stability data.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298007","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}

{"title":"Multiscale Simulations Elucidate the Mechanism of Polyglutamine Aggregation and the Role of Flanking Domains in Fibril Polymorphism.","authors":"Avijeet Kulshrestha, Tien Minh Phan, Azamat Rizuan, Priyesh Mohanty, Jeetain Mittal","doi":"10.1021/acs.jpcb.5c06627","DOIUrl":"https://doi.org/10.1021/acs.jpcb.5c06627","url":null,"abstract":"<p><p>Protein aggregation, which is implicated in aging and neurodegenerative diseases, typically involves a transition from soluble monomers and oligomers to insoluble fibrils. Polyglutamine (polyQ) tracts in proteins can form amyloid fibrils, which are linked to polyQ diseases, including Huntington's disease (HD), where the length of the polyQ tract inversely correlates with the age of onset. Despite significant research on the mechanisms of Httex1 aggregation, atomistic information regarding the intermediate stages of its fibrillation and the morphological characteristics of the end-state amyloid fibrils remains limited. Recently, molecular dynamics (MD) simulations based on a hybrid multistate structure-based model, Multi-eGO, have shown promise in capturing the kinetics and mechanism of amyloid fibrillation with high computational efficiency while achieving qualitative agreement with experiments. Here, we utilize the Multi-eGO simulation methodology to study the mechanism and kinetics of polyQ fibrillation and the effect of the N17 flanking domain of the huntingtin protein. Aggregation simulations of polyQ produced highly heterogeneous amyloid fibrils with variable-width branched morphologies by incorporating combinations of β-turn, β-arc, and β-strand structures, while the presence of the N17 flanking domain reduced amyloid fibril heterogeneity by favoring β-strand conformations. Our simulations reveal that the presence of the N17 domain enhanced aggregation kinetics by promoting the formation of large, structurally stable oligomers. Furthermore, the early-stage aggregation process involves two distinct mechanisms: backbone interactions driving β-sheet formation and side-chain interdigitation. Overall, our study provides detailed insights into the fibrillation kinetics, mechanisms, and end-state polymorphism associated with Httex1 amyloid aggregation.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conformational Analysis of Macrocyclic Compounds Using a Machine-Learned Interatomic Potential.","authors":"Hani M Hashim, Jeremy N Harvey","doi":"10.1021/acs.jctc.5c01072","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c01072","url":null,"abstract":"<p><p>Macrocyclic compounds play a vital role in many chemical and biological systems, yet their conformational analysis remains a significant challenge. In this work, we investigate the conformational landscape of macrocyclic compounds using a machine-learned interatomic potential (MLIP) based on a Nequip-like graph neural network. This MLIP is trained on the energy differences between ωB97XD3 and GFN1-xTB. The model not only reproduces the DFT relative conformer energies of the macrocycles with high fidelity but also yields optimized structures that are practically identical to those obtained via density functional theory. Furthermore, when integrated into a metadynamics-based conformational sampling framework (CREST), we recover structures that very closely match the structure obtained after gas-phase optimization with DFT starting from the crystal structure. These results underscore the potential of machine learning to overcome longstanding challenges in the conformational analysis of complex macrocyclic systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Polymeric Microbubble Monodispersity and Acoustic Responses through Selective Reagent Sourcing.","authors":"Beatriz José Cardoso, Mirjavad Moosavifar, Roman A Barmin, Rui Zhang, Céline Bastard, Jens Koehler, Stephan Rütten, Michael Pohl, Sven Thoröe-Boveleth, Thomas Kraus, Laura De Laporte, Fabian Kiessling, Twan Lammers, Roger M Pallares","doi":"10.1021/acs.molpharmaceut.5c01114","DOIUrl":"https://doi.org/10.1021/acs.molpharmaceut.5c01114","url":null,"abstract":"<p><p>Gas-filled microbubbles (MBs) are widely used as contrast agents for ultrasound (US) imaging and are increasingly being explored for US-mediated drug delivery. Polymeric poly(butyl cyanoacrylate) (PBCA) MBs are particularly well-suited for these applications due to their relatively narrow size distribution, strong acoustic responsiveness, and high drug-loading capacity. While past studies have focused on enhancing the performance of MBs through polymer chemistry, the impact of reagent sourcing has received little attention. The butyl cyanoacrylate monomer, being highly reactive, is commercialized in the presence of chemicals that prevent self-polymerization. As a result, monomers from different suppliers may vary in additives and polymerization characteristics. This study demonstrates that the choice of monomer source strongly affects the size distribution, acoustic response, and payload capability of PBCA MBs. Optimized reagent selection improved the monodispersity of the samples, reducing the half-width at half-maximum of their size distributions from 30 to 16% relative to their diameters. Furthermore, differences in polymer chain length and shell thickness, driven by the monomer source, lead to 180% increases in both drug loading capacity and acoustic responsiveness. These results highlight reagent sourcing as a critical (and previously underappreciated) factor in improving the characteristics and performance of polymeric MBs.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290390","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}

{"title":"Ethylene Glycol and Trehalose Cryopreservation of Cell-Laden Hydrogel Microspheres Enabled by Microfluidic Fabrication.","authors":"Jiangnan Yu, Pengfei Pan, Xiaoli Li, Jin Zhang, Xintian Dingzhang, Xia Jiang, Xiaowen Wang, Jollibekov Berdiyar, Qilong Wang, Ximing Xu, Xia Cao","doi":"10.1021/acs.biomac.5c00559","DOIUrl":"https://doi.org/10.1021/acs.biomac.5c00559","url":null,"abstract":"<p><p>Cell-laden hydrogel microspheres have gained significant attention in 3D cell culture applications, yet effective cryopreservation methods for these systems remain underexplored. This study developed a microfluidic platform for fabricating monodisperse, cell-laden microspheres and investigated a dimethyl sulfoxide (DMSO)- and fetal bovine serum (FBS)-free cryopreservation approach. The platform enabled rapid production of gelatin methacryloyl (GelMA) and calcium alginate (ALG) microspheres, demonstrating cell viability exceeding 80% for U251 cells in GelMA microspheres and 90% for both U251 cells and induced pluripotent stem cells (iPSCs) in ALG microspheres. A DMSO-/FBS-free cryoprotectant (12% ethylene glycol, 4% trehalose; E/T) was identified that maintained >90% post-thaw viability in GES, U251, HepG2, A549, and 3T6 cells, with iPSCs retaining >80% viability. Crucially, E/T effectively preserved iPSC-laden microspheres while preventing DMSO-induced apoptosis and preserving pluripotency. This work establishes a systematic protocol for cryopreserving cell-laden hydrogel microspheres without DMSO/FBS, providing a clinically translatable strategy to advance 3D cell culture technologies.</p>","PeriodicalId":30,"journal":{"name":"Biomacromolecules","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"XGBoost- and Mass Spectrometry-Based Feature Selection for Identifying Metabolic Biomarkers Associated with HBV-Related Liver Disease Progression and Hepatocellular Carcinoma Treatment.","authors":"Shao-Hua Li, Ming Song, Peng Wang, Tian-Shun Kou, Xuan-Xian Peng, Hua Ye, Hui Li","doi":"10.1021/acs.jproteome.5c00540","DOIUrl":"https://doi.org/10.1021/acs.jproteome.5c00540","url":null,"abstract":"<p><p>XGBoost, a gradient boosting algorithm, is widely recognized for its efficiency and robustness in multiclass classification tasks. Metabolomics serves as a powerful tool for biomarker discovery; however, metabolic biomarkers associated with the progression from chronic hepatitis B (CHB) to liver cirrhosis (LC) to hepatocellular carcinoma (HCC), as well as those related to treatment effects in HCC (HCCAT), remain unclear. In this study, an XGBoost-based machine learning approach combined with mass spectrometry was used to analyze the metabolic profiles of 30 healthy controls (HC), 29 CHB patients, 30 LC patients, 30 HCC patients, and 30 HCCAT patients. Biomarker screening was conducted through three comparative analyses: (1) HC, CHB, LC, HCC, and HCCAT; (2) HC, CHB, LC, and HCC; and (3) HC, HCC, and HCCAT. A total of 17 metabolic biomarkers were identified, among which nine had not been previously associated with HBV-related liver diseases. Notably, a potential biomarker panel composed of eicosenoic acid, dihydromorphine, cysteine, acetic acid, sitosterol, and hypoxanthine showed promise for disease prognosis and therapeutic evaluation. These findings highlight the great potential of integrating metabolomics with machine learning to identify novel metabolic biomarkers related to HBV-associated liver disease progression and treatment response.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion of Atoms in Glassy Mixtures of Deuterium and Lithium.","authors":"P S Krstic, A Maan, B E Koel, R Majeski","doi":"10.1021/acs.jpcb.5c04245","DOIUrl":"https://doi.org/10.1021/acs.jpcb.5c04245","url":null,"abstract":"<p><p>The diffusion coefficients of D and Li were calculated in amorphous, glassy Li+D mixtures for various concentrations of D in lithium over the temperature range 100-1000 K. The densities of the mixtures as a function of temperature were also determined. The diffusion coefficients were obtained by the analysis of the mean-squared displacement using molecular dynamics with ReaxFF, a reactive force field. The diffusion and density data obtained for Li+D mixtures were compared with the available experimental and calculated data reported in the literature.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}