{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T18:18:02Z","timestamp":1767205082774,"version":"build-2238731810"},"reference-count":59,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["SKLTCM202313"],"award-info":[{"award-number":["SKLTCM202313"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["SKLTCM2022028"],"award-info":[{"award-number":["SKLTCM2022028"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["82074129"],"award-info":[{"award-number":["82074129"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["82204666"],"award-info":[{"award-number":["82204666"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["82374073"],"award-info":[{"award-number":["82374073"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["2023NSFSC0691"],"award-info":[{"award-number":["2023NSFSC0691"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["2022YFS0635"],"award-info":[{"award-number":["2022YFS0635"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["2022YFS0635-B1"],"award-info":[{"award-number":["2022YFS0635-B1"]}]},{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources","award":["2022JDJQ0061"],"award-info":[{"award-number":["2022JDJQ0061"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["SKLTCM202313"],"award-info":[{"award-number":["SKLTCM202313"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["SKLTCM2022028"],"award-info":[{"award-number":["SKLTCM2022028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82074129"],"award-info":[{"award-number":["82074129"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82204666"],"award-info":[{"award-number":["82204666"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82374073"],"award-info":[{"award-number":["82374073"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["2023NSFSC0691"],"award-info":[{"award-number":["2023NSFSC0691"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["2022YFS0635"],"award-info":[{"award-number":["2022YFS0635"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["2022YFS0635-B1"],"award-info":[{"award-number":["2022YFS0635-B1"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["2022JDJQ0061"],"award-info":[{"award-number":["2022JDJQ0061"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Sichuan Science and Technology Program","award":["SKLTCM202313"],"award-info":[{"award-number":["SKLTCM202313"]}]},{"name":"Sichuan Science and Technology Program","award":["SKLTCM2022028"],"award-info":[{"award-number":["SKLTCM2022028"]}]},{"name":"Sichuan Science and Technology Program","award":["82074129"],"award-info":[{"award-number":["82074129"]}]},{"name":"Sichuan Science and Technology Program","award":["82204666"],"award-info":[{"award-number":["82204666"]}]},{"name":"Sichuan Science and Technology Program","award":["82374073"],"award-info":[{"award-number":["82374073"]}]},{"name":"Sichuan Science and Technology Program","award":["2023NSFSC0691"],"award-info":[{"award-number":["2023NSFSC0691"]}]},{"name":"Sichuan Science and Technology Program","award":["2022YFS0635"],"award-info":[{"award-number":["2022YFS0635"]}]},{"name":"Sichuan Science and Technology Program","award":["2022YFS0635-B1"],"award-info":[{"award-number":["2022YFS0635-B1"]}]},{"name":"Sichuan Science and Technology Program","award":["2022JDJQ0061"],"award-info":[{"award-number":["2022JDJQ0061"]}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Biomolecules"],"abstract":"<jats:p>(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing radiation therapy, which can result in morbidity and even death. However, a notable deficiency exists in the availability of specific drugs designed for the treatment of RIT. (2) Methods: In our pursuit of new drugs for RIT treatment, we employed three deep learning (DL) algorithms: convolutional neural network (CNN), deep neural network (DNN), and a hybrid neural network that combines the computational characteristics of the two. These algorithms construct computational models that can screen compounds for drug activity by utilizing the distinct physicochemical properties of the molecules. The best model underwent testing using a set of 10 drugs endorsed by the US Food and Drug Administration (FDA) specifically for the treatment of thrombocytopenia. (3) Results: The Hybrid CNN+DNN (HCD) model demonstrated the most effective predictive performance on the test dataset, achieving an accuracy of 98.3% and a precision of 97.0%. Both metrics surpassed the performance of the other models, and the model predicted that seven FDA drugs would exhibit activity. Isochlorogenic acid A, identified through screening the Chinese Pharmacopoeia Natural Product Library, was subsequently subjected to experimental verification. The results indicated a substantial enhancement in the differentiation and maturation of megakaryocytes (MKs), along with a notable increase in platelet production. (4) Conclusions: This underscores the potential therapeutic efficacy of isochlorogenic acid A in addressing RIT.<\/jats:p>","DOI":"10.3390\/biom14030267","type":"journal-article","created":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T04:31:23Z","timestamp":1708662683000},"page":"267","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks"],"prefix":"10.3390","volume":"14","author":[{"given":"Taian","family":"Yi","sequence":"first","affiliation":[{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1199-7024","authenticated-orcid":false,"given":"Jiesi","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Chemistry, School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruixue","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9850-7576","authenticated-orcid":false,"given":"Anguo","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueyue","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengyang","family":"Ni","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoqin","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2358-4575","authenticated-orcid":false,"given":"Wenjun","family":"Zou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6136-7469","authenticated-orcid":false,"given":"Jianming","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Chemistry, School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China"},{"name":"Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China"},{"name":"The Institute of Cardiovascular Research, Key Laboratory of Medical Electrophysiology of Ministry of Education, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"15593258211056196","DOI":"10.1177\/15593258211056196","article-title":"Hematological Changes Following Low Dose Radiation Therapy and Comparison to Current Standard of Care Cancer Treatments","volume":"19","author":"Jameus","year":"2021","journal-title":"Dose Response"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"20503121211034366","DOI":"10.1177\/20503121211034366","article-title":"New approaches and procedures for cancer treatment: Current perspectives","volume":"9","author":"Debela","year":"2021","journal-title":"SAGE Open Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1038\/s41416-018-0201-z","article-title":"Practice-changing radiation therapy trials for the treatment of cancer: Where are we 150 years after the birth of Marie Curie?","volume":"119","author":"Thompson","year":"2018","journal-title":"Br. J. Cancer"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.1182\/blood.V89.7.2303","article-title":"Radiotherapy-Associated Neutropenia and Thrombocytopenia: Analysis of Risk Factors and Development of a Predictive Model","volume":"89","author":"Lamborn","year":"1997","journal-title":"Blood"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"271","DOI":"10.2174\/157339406777934717","article-title":"Cancer therapy-induced residual bone marrow injury-Mechanisms of induction and implication for therapy","volume":"2","author":"Wang","year":"2006","journal-title":"Curr. Cancer Ther. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.3324\/haematol.2021.279512","article-title":"Treatment of chemotherapy-induced thrombocytopenia in patients with non-hematologic malignancies","volume":"107","author":"Kuter","year":"2022","journal-title":"Haematologica"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1680","DOI":"10.1182\/blood-2004-10-4080","article-title":"HLAMatchmaker-driven analysis of responses to HLA-typed platelet transfusions in alloimmunized thrombocytopenic patients","volume":"107","author":"Nambiar","year":"2006","journal-title":"Blood"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5451","DOI":"10.1182\/blood-2023-191091","article-title":"Recombinant Human Thrombopoietin Combined with Thrombopoietin Receptor Agonists Can Facilitate the Recovery of Platelet after Allogeneic HSCT","volume":"142","author":"Cheng","year":"2023","journal-title":"Blood"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.3324\/haematol.2018.212845","article-title":"Thrombopoietin receptor agonists: Ten years later","volume":"104","author":"Ghanima","year":"2019","journal-title":"Haematologica"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1021\/ar500432k","article-title":"The Chemical Space Project","volume":"48","author":"Reymond","year":"2015","journal-title":"Acc. Chem. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1007\/s00210-022-02250-2","article-title":"A year in pharmacology: New drugs approved by the US Food and Drug Administration in 2021","volume":"395","author":"Aksoyalp","year":"2022","journal-title":"Naunyn-Schmiedeberg\u2019s Arch. Pharmacol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1016\/j.tips.2019.06.004","article-title":"Advancing Drug Discovery via Artificial Intelligence","volume":"40","author":"Chan","year":"2019","journal-title":"Trends Pharmacol. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/s41586-023-05905-z","article-title":"Computational approaches streamlining drug discovery","volume":"616","author":"Sadybekov","year":"2023","journal-title":"Nature"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"998245","DOI":"10.3389\/fphar.2022.998245","article-title":"Virtual screening and activity evaluation of multitargeting inhibitors for idiopathic pulmonary fibrosis","volume":"13","author":"Wang","year":"2022","journal-title":"Front. Pharmacol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"768747","DOI":"10.3389\/fgene.2021.768747","article-title":"Hypertension-Related Drug Activity Identification Based on Novel Ensemble Method","volume":"12","author":"Yang","year":"2021","journal-title":"Front. Genet."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sun, Y.Y., Lin, T.T., Cheng, W.C., Lu, I.H., Lin, C.Y., and Chen, S.H. (2022). Peptide-Based Drug Predictions for Cancer Therapy Using Deep Learning. Pharmaceuticals, 15.","DOI":"10.1101\/2022.02.01.478580"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"175604","DOI":"10.1016\/j.ejphar.2023.175604","article-title":"The combination of machine learning and transcriptomics reveals a novel megakaryopoiesis inducer, MO-A, that promotes thrombopoiesis by activating FGF1\/FGFR1\/PI3K\/Akt\/NF-\u03baB signaling","volume":"944","author":"Zhang","year":"2023","journal-title":"Eur. J. Pharmacol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.thromres.2023.04.011","article-title":"Identification of thrombopoiesis inducer based on a hybrid deep neural network model","volume":"226","author":"Mo","year":"2023","journal-title":"Thromb. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1007\/s42979-021-00815-1","article-title":"Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions","volume":"2","author":"Sarker","year":"2021","journal-title":"SN Comput. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3755","DOI":"10.1021\/acs.jcim.0c00409","article-title":"autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences","volume":"60","author":"Jing","year":"2020","journal-title":"J. Chem. Inf. Model."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wu, C.K., Zhang, X.C., Yang, Z.J., Lu, A.P., Hou, T.J., and Cao, D.S. (2021). Learning to SMILES: BAN-based strategies to improve latent representation learning from molecules. Briefings Bioinform., 22.","DOI":"10.1093\/bib\/bbab327"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1600131","DOI":"10.1002\/minf.201600131","article-title":"Modeling Tanimoto Similarity Value Distributions and Predicting Search Results","volume":"36","author":"Vogt","year":"2017","journal-title":"Mol. Informatics"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1002\/qsar.200290002","article-title":"Identification of Diverse Database Subsets using Property-Based and Fragment-Based Molecular Descriptions","volume":"21","author":"Ashton","year":"2002","journal-title":"Int. J. Quant. Struct. Prop. Relatsh."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1021\/ci010132r","article-title":"Reoptimization of MDL Keys for Use in Drug Discovery","volume":"42","author":"Durant","year":"2002","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1021\/ci100050t","article-title":"Extended-Connectivity Fingerprints","volume":"50","author":"Rogers","year":"2010","journal-title":"J. Chem. Inf. Model."},{"key":"ref_26","first-page":"8464452","article-title":"A Novel Molecular Representation Learning for Molecular Property Prediction with a Multiple SMILES-Based Augmentation","volume":"2022","author":"Li","year":"2022","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"106096","DOI":"10.1016\/j.phrs.2022.106096","article-title":"Discovery of a novel megakaryopoiesis enhancer, ingenol, promoting thrombopoiesis through PI3K-Akt signaling independent of thrombopoietin","volume":"177","author":"Wang","year":"2022","journal-title":"Pharmacol. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3239","DOI":"10.1074\/jbc.M116.751693","article-title":"The Plant Hormone Abscisic Acid Is a Prosurvival Factor in Human and Murine Megakaryocytes","volume":"292","author":"Malara","year":"2017","journal-title":"J. Biol. Chem."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1821","DOI":"10.1016\/j.biocel.2006.03.011","article-title":"Biological characteristics of megakaryocytes: Specific lineage commitment and associated disorders","volume":"38","author":"Sun","year":"2006","journal-title":"Int. J. Biochem. Cell Biol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1055\/s-2004-833474","article-title":"Molecular mechanisms of megakaryocyte differentiation","volume":"30","author":"Schulze","year":"2004","journal-title":"Semin. Thromb. Hemost."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Noh, J.Y. (2021). Megakaryopoiesis and Platelet Biology: Roles of Transcription Factors and Emerging Clinical Implications. Int. J. Mol. Sci., 22.","DOI":"10.3390\/ijms22179615"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s13566-015-0201-z","article-title":"Role of thrombocytopenia in radiation-induced mortality and review of therapeutic approaches targeting platelet regeneration after radiation exposure","volume":"5","author":"DiCarlo","year":"2016","journal-title":"J. Radiat. Oncol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"754624","DOI":"10.3389\/fonc.2021.754624","article-title":"Risk Analysis of Severe Thrombocytopenia in Nasopharyngeal Carcinoma During Concurrent Radio-Chemotherapy","volume":"11","author":"Hu","year":"2021","journal-title":"Front. Oncol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"101022","DOI":"10.1016\/j.tranon.2021.101022","article-title":"Platelet transfusion for cancer secondary thrombocytopenia: Platelet and cancer cell interaction","volume":"14","author":"Wang","year":"2021","journal-title":"Transl. Oncol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1182\/blood-2016-06-722686","article-title":"TPO-RAs multitask in ITP","volume":"128","author":"Yazdanbakhsh","year":"2016","journal-title":"Blood"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"20406207211001139","DOI":"10.1177\/20406207211001139","article-title":"Thrombopoietin receptor agonist for treatment of immune thrombocytopenia in pregnancy: A narrative review","volume":"12","author":"Agarwal","year":"2021","journal-title":"Ther. Adv. Hematol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3049","DOI":"10.1016\/j.apsb.2022.02.002","article-title":"Why 90% of clinical drug development fails and how to improve it?","volume":"12","author":"Sun","year":"2022","journal-title":"Acta Pharm. Sin. B"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1007\/s10822-013-9672-4","article-title":"Estimation of the size of drug-like chemical space based on GDB-17 data","volume":"27","author":"Polishchuk","year":"2013","journal-title":"J. Comput. Aided Mol. Des."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.ymeth.2023.01.004","article-title":"Explore drug-like space with deep generative models","volume":"210","author":"Wang","year":"2023","journal-title":"Methods"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-1-60327-258-2_1","article-title":"Design and implementation of high-throughput screening assays","volume":"Volume 565","author":"Hertzberg","year":"2009","journal-title":"High Throughput Screening. Methods in Molecular Biology"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.drudis.2020.10.010","article-title":"Artificial intelligence in drug discovery and development","volume":"26","author":"Paul","year":"2021","journal-title":"Drug Discov. Today"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.1007\/s10462-021-10058-4","article-title":"Machine Learning in Drug Discovery: A Review","volume":"55","author":"Dara","year":"2022","journal-title":"Artif. Intell. Rev."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/s41524-022-00734-6","article-title":"Recent advances and applications of deep learning methods in materials science","volume":"8","author":"Choudhary","year":"2022","journal-title":"NPJ Comput. Mater."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.ymeth.2019.04.008","article-title":"Deep learning in bioinformatics: Introduction, application, and perspective in the big data era","volume":"166","author":"Li","year":"2019","journal-title":"Methods"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1007\/s11030-021-10225-3","article-title":"Convolutional neural networks (CNNs): Concepts and applications in pharmacogenomics","volume":"25","author":"Vaz","year":"2021","journal-title":"Mol. Divers."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1186\/s40537-023-00727-2","article-title":"A survey on deep learning tools dealing with data scarcity: Definitions, challenges, solutions, tips, and applications","volume":"10","author":"Alzubaidi","year":"2023","journal-title":"J. Big Data"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.jep.2012.09.003","article-title":"Hepatoprotective and antiviral properties of isochlorogenic acid A from Laggera alata against hepatitis B virus infection","volume":"144","author":"Hao","year":"2012","journal-title":"J. Ethnopharmacol."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Liu, H., Zhu, S., Liu, Q., and Zhang, Y. (2019). Spectrum-effect relationship study between HPLC fingerprints and antioxidant of honeysuckle extract. Biomed. Chromatogr., 33.","DOI":"10.1002\/bmc.4583"},{"key":"ref_49","first-page":"860","article-title":"Isochlorogenic acid (ICGA): Natural medicine with potentials in pharmaceutical developments","volume":"18","author":"Wang","year":"2020","journal-title":"Chin. J. Nat. Med."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"109989","DOI":"10.1016\/j.intimp.2023.109989","article-title":"Isochlorogenic acid A alleviates dextran sulfate sodium-induced ulcerative colitis in mice through STAT3\/NF-\u043aB pathway","volume":"118","author":"Tang","year":"2023","journal-title":"Int. Immunopharmacol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3109\/01913123.2016.1170744","article-title":"Platelet production of megakaryocyte: A review with original observations on human in vivo cells and bone marrow","volume":"40","author":"Ru","year":"2016","journal-title":"Ultrastruct. Pathol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"3348","DOI":"10.1172\/JCI26891","article-title":"The biogenesis of platelets from megakaryocyte proplatelets","volume":"115","author":"Patel","year":"2005","journal-title":"J. Clin. Investig."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1080\/01926230600939856","article-title":"Normal structure, function, and histology of the bone marrow","volume":"34","author":"Travlos","year":"2006","journal-title":"Toxicol. Pathol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1288","DOI":"10.1161\/ATVBAHA.119.312129","article-title":"New Insights Into the Differentiation of Megakaryocytes From Hematopoietic Progenitors","volume":"39","author":"Noetzli","year":"2019","journal-title":"Arter. Thromb. Vasc. Biol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1002\/ajh.2830340302","article-title":"Properties of the exchangeable splenic platelets released into the circulation during exercise-induced thrombocytosis","volume":"34","author":"Chamberlain","year":"1990","journal-title":"Am. J. Hematol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1080\/09537104.2020.1732322","article-title":"Platelet phenotype and function in the absence of splenic sequestration (Review)","volume":"32","author":"Luu","year":"2021","journal-title":"Platelets"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1636","DOI":"10.1038\/s41417-022-00476-z","article-title":"Global characterization of megakaryocytes in bone marrow, peripheral blood, and cord blood by single-cell RNA sequencing","volume":"29","author":"Zhang","year":"2022","journal-title":"Cancer Gene Ther."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Short, C., Lim, H.K., Tan, J., and O\u2019Neill, H.C. (2019). Targeting the Spleen as an Alternative Site for Hematopoiesis. BioEssays, 41.","DOI":"10.1002\/bies.201800234"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1182\/blood.2021012827","article-title":"The bone marrow niche from the inside out: How megakaryocytes are shaped by and shape hematopoiesis","volume":"139","author":"Stone","year":"2022","journal-title":"Blood"}],"updated-by":[{"DOI":"10.3390\/biom14060655","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000}}],"container-title":["Biomolecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-273X\/14\/3\/267\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T15:06:53Z","timestamp":1754233613000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-273X\/14\/3\/267"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,23]]},"references-count":59,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["biom14030267"],"URL":"https:\/\/doi.org\/10.3390\/biom14030267","relation":{},"ISSN":["2218-273X"],"issn-type":[{"value":"2218-273X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,23]]}}}