{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T18:33:46Z","timestamp":1792002826399,"version":"4.4.0"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T00:00:00Z","timestamp":1744761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T00:00:00Z","timestamp":1744761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["22204117"],"award-info":[{"award-number":["22204117"]}],"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":["T2321005"],"award-info":[{"award-number":["T2321005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Special Project for Clinical Key Diseases in Diagnosis and Treatment Technology of Suzhou","award":["LCZX202104"],"award-info":[{"award-number":["LCZX202104"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Nanobiotechnol"],"DOI":"10.1186\/s12951-025-03339-5","type":"journal-article","created":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T04:43:21Z","timestamp":1744778601000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma"],"prefix":"10.1186","volume":"23","author":[{"given":"Haiting","family":"Cao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofeng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huayi","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binbin","family":"Chu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yao","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Houyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fenglin","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,16]]},"reference":[{"key":"3339_CR1","doi-asserted-by":"publisher","first-page":"e111657","DOI":"10.1371\/journal.pone.0111657","volume":"9","author":"H Tokue","year":"2014","unstructured":"Tokue H, Hirasawa S, Morita H, Koyma Y, Miyazaki M, Shibuya K, et al. Percutaneous image-guided biopsy for non-mass-forming isolated splenomegaly and suspected malignant lymphoma. PLoS ONE. 2014;9:e111657.","journal-title":"PLoS ONE"},{"key":"3339_CR2","doi-asserted-by":"publisher","first-page":"3733","DOI":"10.1200\/JCO.2004.02.171","volume":"22","author":"M Picardi","year":"2004","unstructured":"Picardi M, Gennarelli N, Ciancia R, De Renzo A, Gargiulo G, Ciancia G, et al. Randomized comparison of power Doppler ultrasound-directed excisional biopsy with standard excisional biopsy for the characterization of lymphadenopathies in patients with suspected lymphoma. JCO. 2004;22:3733\u201340.","journal-title":"JCO"},{"key":"3339_CR3","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1259\/bjr\/60580076","volume":"84","author":"C Burke","year":"2011","unstructured":"Burke C, Thomas R, Inglis C, Baldwin A, Ramesar K, Grace R, et al. Ultrasound-guided core biopsy in the diagnosis of lymphoma of the head and neck. A 9 year experience. BJR. 2011;84:727\u201332.","journal-title":"BJR"},{"key":"3339_CR4","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1002\/cam4.224","volume":"3","author":"I Shimizu","year":"2014","unstructured":"Shimizu I, Okazaki Y, Takeda W, Kirihara T, Sato K, Fujikawa Y, et al. Use of percutaneous image-guided coaxial core-needle biopsy for diagnosis of intraabdominal lymphoma. Cancer Med. 2014;3:1336\u201341.","journal-title":"Cancer Med"},{"key":"3339_CR5","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1038\/bjc.1991.107","volume":"63","author":"JS Whelan","year":"1991","unstructured":"Whelan JS, Reznek RH, Daniell SJ, Norton AJ, Lister TA, Rohatiner AZ. Computed tomography (CT) and ultrasound (US) guided core biopsy in the management of non-Hodgkin\u2019s lymphoma. Br J Cancer. 1991;63:460\u20132.","journal-title":"Br J Cancer"},{"key":"3339_CR6","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1136\/jclinpath-2017-204644","volume":"70","author":"BJ Williams","year":"2017","unstructured":"Williams BJ, Bottoms D, Treanor D. Future-proofing pathology: the case for clinical adoption of digital pathology. J Clin Pathol. 2017;70:1010\u20138.","journal-title":"J Clin Pathol"},{"key":"3339_CR7","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.1038\/s41591-019-0575-3","volume":"25","author":"K Rockwood","year":"2019","unstructured":"Rockwood K, Wallace LMK, Davis DH. Genetic predisposition and modifiable risks for late-life dementia. Nat Med. 2019;25:1331\u20132.","journal-title":"Nat Med"},{"key":"3339_CR8","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.juro.2010.03.021","volume":"184","author":"F Brimo","year":"2010","unstructured":"Brimo F, Schultz L, Epstein JI. The value of mandatory second opinion pathology review of prostate needle biopsy interpretation before radical prostatectomy. J Urol. 2010;184:126\u201330.","journal-title":"J Urol"},{"key":"3339_CR9","doi-asserted-by":"publisher","first-page":"2637","DOI":"10.1002\/anie.202011903","volume":"60","author":"Y Zhan","year":"2021","unstructured":"Zhan Y, Ling S, Huang H, Zhang Y, Chen G, Huang S, et al. Rapid unperturbed- tissue analysis for intraoperative cancer diagnosis using an enzyme-activated NIR-II nanoprobe. Angew Chem Int Ed. 2021;60:2637\u201342.","journal-title":"Angew Chem Int Ed"},{"key":"3339_CR10","doi-asserted-by":"publisher","first-page":"9081","DOI":"10.1021\/acsnano.8b03029","volume":"12","author":"J Min","year":"2018","unstructured":"Min J, Im H, Allen M, McFarland PJ, Degani I, Yu H, et al. Computational optics enables breast cancer profiling in point-of-care settings. ACS Nano. 2018;12:9081\u201390.","journal-title":"ACS Nano"},{"key":"3339_CR11","doi-asserted-by":"publisher","first-page":"3561","DOI":"10.1038\/s41467-023-39085-1","volume":"14","author":"C Stashko","year":"2023","unstructured":"Stashko C, Hayward M-K, Northey JJ, Pearson N, Ironside AJ, Lakins JN, et al. A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer. Nat Commun. 2023;14:3561.","journal-title":"Nat Commun"},{"key":"3339_CR12","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1038\/s42256-020-0173-6","volume":"2","author":"P Mukherjee","year":"2020","unstructured":"Mukherjee P, Zhou M, Lee E, Schicht A, Balagurunathan Y, Napel S, et al. A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets. Nat Mach Intell. 2020;2:274\u201382.","journal-title":"Nat Mach Intell"},{"key":"3339_CR13","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1038\/s43018-021-00236-2","volume":"2","author":"O Morin","year":"2021","unstructured":"Morin O, Valli\u00e8res M, Braunstein S, Ginart JB, Upadhaya T, Woodruff HC, et al. An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication. Nat Cancer. 2021;2:709\u201322.","journal-title":"Nat Cancer"},{"key":"3339_CR14","doi-asserted-by":"publisher","first-page":"1453","DOI":"10.1038\/s41591-019-0539-7","volume":"25","author":"P-HC Chen","year":"2019","unstructured":"Chen P-HC, Gadepalli K, MacDonald R, Liu Y, Kadowaki S, Nagpal K, et al. An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis. Nat Med. 2019;25:1453\u20137.","journal-title":"Nat Med"},{"key":"3339_CR15","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1038\/s41571-019-0252-y","volume":"16","author":"K Bera","year":"2019","unstructured":"Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A. Artificial intelligence in digital pathology-new tools for diagnosis and precision oncology. Nat Rev Clin Oncol. 2019;16:703\u201315.","journal-title":"Nat Rev Clin Oncol"},{"key":"3339_CR16","doi-asserted-by":"publisher","first-page":"1026","DOI":"10.1038\/s43018-022-00436-4","volume":"3","author":"A Shmatko","year":"2022","unstructured":"Shmatko A, Ghaffari LN, Gerstung M, Kather JN. Artificial intelligence in histopathology: enhancing cancer research and clinical oncology. Nat Cancer. 2022;3:1026\u201338.","journal-title":"Nat Cancer"},{"key":"3339_CR17","doi-asserted-by":"publisher","first-page":"1559","DOI":"10.1038\/s41591-018-0177-5","volume":"24","author":"N Coudray","year":"2018","unstructured":"Coudray N, Ocampo PS, Sakellaropoulos T, Narula N, Snuderl M, Feny\u00f6 D, et al. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning. Nat Med. 2018;24:1559\u201367.","journal-title":"Nat Med"},{"key":"3339_CR18","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1038\/s41591-019-0508-1","volume":"25","author":"G Campanella","year":"2019","unstructured":"Campanella G, Hanna MG, Geneslaw L, Miraflor A, Werneck Krauss Silva V, Busam KJ, et al. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nat Med. 2019;25:1301\u20139.","journal-title":"Nat Med"},{"key":"3339_CR19","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436\u201344.","journal-title":"Nature"},{"key":"3339_CR20","doi-asserted-by":"publisher","first-page":"6753","DOI":"10.1038\/s41467-022-34275-9","volume":"13","author":"G Shamai","year":"2022","unstructured":"Shamai G, Livne A, Pol\u00f3nia A, Sabo E, Cretu A, Bar-Sela G, et al. Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer. Nat Commun. 2022;13:6753.","journal-title":"Nat Commun"},{"key":"3339_CR21","doi-asserted-by":"publisher","first-page":"23777","DOI":"10.1002\/anie.202109170","volume":"60","author":"Y Xue","year":"2021","unstructured":"Xue Y, Ji W, Jiang Y, Yu P, Mao L. Deep learning for voltammetric sensing in a living animal brain. Angew Chem Int Ed. 2021;60:23777\u201383.","journal-title":"Angew Chem Int Ed"},{"key":"3339_CR22","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1186\/s12951-024-02881-y","volume":"22","author":"J Yuan","year":"2024","unstructured":"Yuan J, Zhu H, Li S, Thierry B, Yang C-T, Zhang C, et al. Truncated M13 phage for smart detection of E. coli under dark field. J Nanobiotechnol. 2024;22:599.","journal-title":"J Nanobiotechnol"},{"key":"3339_CR23","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1038\/s42256-024-00966-9","volume":"7","author":"Z Nie","year":"2025","unstructured":"Nie Z, Liu X, Chen J, Wang Z, Liu Y, Si H, et al. A unified evolution-driven deep learning framework for virus variation driver prediction. Nat Mach Intell. 2025;7:131\u201344.","journal-title":"Nat Mach Intell"},{"key":"3339_CR24","doi-asserted-by":"publisher","first-page":"6268","DOI":"10.1038\/s41598-025-90423-3","volume":"15","author":"A Halder","year":"2025","unstructured":"Halder A, Dalal A, Gharami S, Wozniak M, Ijaz MF, Singh PK, et al. A fuzzy rank-based deep ensemble methodology for multi-class skin cancer classification. Sci Rep. 2025;15:6268.","journal-title":"Sci Rep"},{"key":"3339_CR25","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1038\/s41467-025-55825-x","volume":"16","author":"Y Ding","year":"2025","unstructured":"Ding Y, Li J-T, Zhang J, Li P, Bai H, Fang B, et al. Mitochondrial segmentation and function prediction in live-cell images with deep learning. Nat Commun. 2025;16:743.","journal-title":"Nat Commun"},{"key":"3339_CR26","doi-asserted-by":"publisher","first-page":"3463","DOI":"10.1038\/s41598-024-53733-6","volume":"14","author":"AM El-Assy","year":"2024","unstructured":"El-Assy AM, Amer HM, Ibrahim HM, Mohamed MA. A novel CNN architecture for accurate early detection and classification of Alzheimer\u2019s disease using MRI data. Sci Rep. 2024;14:3463.","journal-title":"Sci Rep"},{"key":"3339_CR27","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-03408-6","author":"N Eisemann","year":"2025","unstructured":"Eisemann N, Bunk S, Mukama T, Baltus H, Elsner SA, Gomille T, et al. Nationwide real-world implementation of AI for cancer detection in population-based mammography screening. Nat Med. 2025;31:917\u201324.","journal-title":"Nat Med"},{"key":"3339_CR28","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1038\/s41591-024-03329-4","volume":"31","author":"F Christiansen","year":"2025","unstructured":"Christiansen F, Konuk E, Ganeshan AR, Welch R, Pal\u00e9s Huix J, Czekierdowski A, et al. International multicenter validation of AI-driven ultrasound detection of ovarian cancer. Nat Med. 2025;31:189.","journal-title":"Nat Med"},{"key":"3339_CR29","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1038\/s41591-019-0715-9","volume":"26","author":"TC Hollon","year":"2020","unstructured":"Hollon TC, Pandian B, Adapa AR, Urias E, Save AV, Khalsa SSS, et al. Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nat Med. 2020;26:52\u20138.","journal-title":"Nat Med"},{"key":"3339_CR30","doi-asserted-by":"publisher","first-page":"0027","DOI":"10.1038\/s41551-016-0027","volume":"1","author":"DA Orringer","year":"2017","unstructured":"Orringer DA, Pandian B, Niknafs YS, Hollon TC, Boyle J, Lewis S, et al. Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat Biomed Eng. 2017;1:0027.","journal-title":"Nat Biomed Eng"},{"key":"3339_CR31","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1038\/s41570-018-0031-9","volume":"2","author":"C Zhan","year":"2018","unstructured":"Zhan C, Chen X, Yi J, Li J, Wu D, Tian Z. From plasmon-enhanced molecular spectroscopy to plasmon-mediated chemical reactions. Nat Rev Chem. 2018;2:216\u201330.","journal-title":"Nat Rev Chem"},{"key":"3339_CR32","doi-asserted-by":"publisher","first-page":"16021","DOI":"10.1038\/natrevmats.2016.21","volume":"1","author":"S Ding","year":"2016","unstructured":"Ding S, Yi J, Li J, Ren B, Wu D, Panneerselvam R, et al. Nanostructure-based plasmon-enhanced Raman spectroscopy for surface analysis of materials. Nat Rev Mater. 2016;1:16021.","journal-title":"Nat Rev Mater"},{"key":"3339_CR33","doi-asserted-by":"publisher","first-page":"0060","DOI":"10.1038\/s41570-017-0060","volume":"1","author":"S Laing","year":"2017","unstructured":"Laing S, Jamieson LE, Faulds K, Graham D. Surface-enhanced Raman spectroscopy for in vivo biosensing. Nat Rev Chem. 2017;1:0060.","journal-title":"Nat Rev Chem"},{"key":"3339_CR34","doi-asserted-by":"publisher","first-page":"4946","DOI":"10.1021\/acs.chemrev.7b00668","volume":"118","author":"C Zong","year":"2018","unstructured":"Zong C, Xu M, Xu L, Wei T, Ma X, Zheng X, et al. Surface-enhanced Raman spectroscopy for bioanalysis: reliability and challenges. Chem Rev. 2018;118:4946\u201380.","journal-title":"Chem Rev"},{"key":"3339_CR35","doi-asserted-by":"publisher","first-page":"5454","DOI":"10.1002\/anie.201908154","volume":"59","author":"SEJ Bell","year":"2020","unstructured":"Bell SEJ, Charron G, Cort\u00e9s E, Kneipp J, De La Chapelle ML, Langer J, et al. Towards reliable and quantitative surface-enhanced Raman scattering (SERS): from key parameters to good analytical practice. Angew Chem Int Ed. 2020;59:5454\u201362.","journal-title":"Angew Chem Int Ed"},{"key":"3339_CR36","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1186\/1476-4598-12-48","volume":"12","author":"J Surmacki","year":"2013","unstructured":"Surmacki J, Musial J, Kordek R, Abramczyk H. Raman imaging at biological interfaces: applications in breast cancer diagnosis. Mol Cancer. 2013;12:48.","journal-title":"Mol Cancer"},{"key":"3339_CR37","doi-asserted-by":"publisher","first-page":"4506","DOI":"10.1158\/0008-5472.CAN-17-0709","volume":"77","author":"Y Wang","year":"2017","unstructured":"Wang Y, Reder NP, Kang S, Glaser AK, Yang Q, Wall MA, et al. Raman-encoded molecular imaging with topically applied SERS nanoparticles for intraoperative guidance of lumpectomy. Cancer Res. 2017;77:4506\u201316.","journal-title":"Cancer Res"},{"key":"3339_CR38","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1186\/s12951-024-02600-7","volume":"22","author":"S Spaziani","year":"2024","unstructured":"Spaziani S, Esposito A, Barisciano G, Quero G, Elumalai S, Leo M, et al. Combined SERS-Raman screening of HER2-overexpressing or silenced breast cancer cell lines. J Nanobiotechnol. 2024;22:350.","journal-title":"J Nanobiotechnol"},{"key":"3339_CR39","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1186\/s12951-022-01327-7","volume":"20","author":"S Bock","year":"2022","unstructured":"Bock S. Highly sensitive near-infrared SERS nanoprobes for in vivo imaging using gold-assembled silica nanoparticles with controllable nanogaps. J Nanobiotechnol. 2022;20:130.","journal-title":"J Nanobiotechnol"},{"key":"3339_CR40","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1186\/s12951-024-02339-1","volume":"22","author":"Y Xiao","year":"2024","unstructured":"Xiao Y, Luo S, Qiu J, Zhang Y, Liu W, Zhao Y, et al. Highly sensitive SERS platform for pathogen analysis by cyclic DNA nanostructure@AuNP tags and cascade primer exchange reaction. J Nanobiotechnol. 2024;22:75.","journal-title":"J Nanobiotechnol"},{"key":"3339_CR41","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1186\/s12951-022-01756-4","volume":"21","author":"Z Wu","year":"2023","unstructured":"Wu Z, Zhao D, Han X, Liu J, Sun Y, Li Y, et al. Deposition of hydrophilic Ti3C2Tx on a superhydrophobic ZnO nanorod array for improved surface-enhanced Raman scattering performance. J Nanobiotechnol. 2023;21:17.","journal-title":"J Nanobiotechnol"},{"key":"3339_CR42","doi-asserted-by":"publisher","first-page":"14216","DOI":"10.1021\/acs.analchem.8b03080","volume":"90","author":"H Shi","year":"2018","unstructured":"Shi H, Wang H, Meng X, Chen R, Zhang Y, Su Y, et al. Setting up a surface-enhanced Raman scattering database for artificial-intelligence-based label-free discrimination of tumor suppressor genes. Anal Chem. 2018;90:14216\u201321.","journal-title":"Anal Chem"},{"key":"3339_CR43","doi-asserted-by":"publisher","first-page":"3597","DOI":"10.1021\/acs.analchem.8b05595","volume":"91","author":"R Chen","year":"2019","unstructured":"Chen R, Shi H, Meng X, Su Y, Wang H, He Y. Dual-amplification strategy-based SERS chip for sensitive and reproducible detection of DNA methyltransferase activity in human serum. Anal Chem. 2019;91:3597\u2013603.","journal-title":"Anal Chem"},{"key":"3339_CR44","doi-asserted-by":"publisher","first-page":"5132","DOI":"10.1002\/anie.201412294","volume":"54","author":"H Wang","year":"2015","unstructured":"Wang H, Zhou Y, Jiang X, Sun B, Zhu Y, Wang H, et al. Simultaneous capture, detection, and inactivation of bacteria as enabled by a surface-enhanced Raman scattering multifunctional chip. Angew Chem Int Ed. 2015;54:5132\u20136.","journal-title":"Angew Chem Int Ed"},{"key":"3339_CR45","doi-asserted-by":"publisher","first-page":"5646","DOI":"10.1021\/acs.analchem.7b05139","volume":"90","author":"X Meng","year":"2018","unstructured":"Meng X, Wang H, Chen N, Ding P, Shi H, Zhai X, et al. A graphene-silver nanoparticle-silicon sandwich SERS chip for quantitative detection of molecules and capture, discrimination, and inactivation of bacteria. Anal Chem. 2018;90:5646\u201353.","journal-title":"Anal Chem"},{"key":"3339_CR46","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1002\/anie.201307271","volume":"53","author":"E Lipiec","year":"2014","unstructured":"Lipiec E, Sekine R, Bielecki J, Kwiatek WM, Wood BR. Molecular characterization of DNA double strand breaks with tip-enhanced Raman scattering. Angew Chem Int Ed. 2014;53:169\u201372.","journal-title":"Angew Chem Int Ed"},{"key":"3339_CR47","doi-asserted-by":"publisher","first-page":"4883","DOI":"10.1021\/nn500840x","volume":"8","author":"B Kang","year":"2014","unstructured":"Kang B, Austin LA, El-Sayed MA. Observing real-time molecular event dynamics of apoptosis in living cancer cells using nuclear-targeted plasmonically enhanced Raman nanoprobes. ACS Nano. 2014;8:4883\u201392.","journal-title":"ACS Nano"},{"key":"3339_CR48","doi-asserted-by":"publisher","first-page":"12158","DOI":"10.1038\/s41598-022-15313-4","volume":"12","author":"S Seweryn","year":"2022","unstructured":"Seweryn S, Skirli\u0144ska-Nosek K, Wilkosz N, Sofi\u0144ska K, Perez-Guaita D, O\u0107wieja M, et al. Plasmonic hot spots reveal local conformational transitions induced by DNA double-strand breaks. Sci Rep. 2022;12:12158.","journal-title":"Sci Rep"},{"key":"3339_CR49","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1038\/sj.cr.7290049","volume":"10","author":"J Zhang","year":"2000","unstructured":"Zhang J, Xu M. DNA fragmentation in apoptosis. Cell Res. 2000;10:205\u201311.","journal-title":"Cell Res"},{"key":"3339_CR50","doi-asserted-by":"publisher","first-page":"1809","DOI":"10.1016\/j.theriogenology.2005.04.010","volume":"64","author":"GJ Dietrich","year":"2005","unstructured":"Dietrich GJ, Szpyrka A, Wojtczak M, Dobosz S, Goryczko K, \u017bakowski \u0141, et al. Effects of UV irradiation and hydrogen peroxide on DNA fragmentation, motility and fertilizing ability of rainbow trout (Oncorhynchus mykiss) spermatozoa. Theriogenology. 2005;64:1809\u201322.","journal-title":"Theriogenology"},{"key":"3339_CR51","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1016\/j.mito.2007.07.003","volume":"7","author":"M Singh","year":"2007","unstructured":"Singh M, Sharma H, Singh N. Hydrogen peroxide induces apoptosis in HeLa cells through mitochondrial pathway. Mitochondrion. 2007;7:367\u201373.","journal-title":"Mitochondrion"},{"key":"3339_CR52","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.radonc.2016.12.004","volume":"122","author":"F Qvarnstr\u00f6m","year":"2017","unstructured":"Qvarnstr\u00f6m F, Simonsson M, Nyman J, Hermansson I, Book M, Johansson KA, et al. Double strand break induction and kinetics indicate preserved hypersensitivity in keratinocytes to subtherapeutic doses for 7weeks of radiotherapy. Radiother Oncol. 2017;122:163\u20139.","journal-title":"Radiother Oncol"},{"key":"3339_CR53","doi-asserted-by":"publisher","DOI":"10.1002\/jrs.6764","author":"LA Bratchenko","year":"2024","unstructured":"Bratchenko LA, Bratchenko IA. Avoiding overestimation and the \u2018black box\u2019 problem in biofluids multivariate analysis by Raman spectroscopy: interpretation and transparency with the SP-LIME algorithm. J Raman Spectrosc. 2024;21:10097.","journal-title":"J Raman Spectrosc"},{"key":"3339_CR54","doi-asserted-by":"publisher","first-page":"102252","DOI":"10.1016\/j.artmed.2022.102252","volume":"125","author":"IA Bratchenko","year":"2022","unstructured":"Bratchenko IA, Bratchenko LA. Comment on \u201cFinding reduced Raman spectroscopy fingerprint of skin samples for melanoma diagnosis through machine learning.\u201d Artif Intell Med. 2022;125:102252.","journal-title":"Artif Intell Med"},{"key":"3339_CR55","doi-asserted-by":"publisher","first-page":"e202300016","DOI":"10.1002\/jbio.202300016","volume":"16","author":"YA Khristoforova","year":"2023","unstructured":"Khristoforova YA, Bratchenko LA, Skuratova MA, Lebedeva EA, Lebedev PA, Bratchenko IA. Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis. J Biophotonics. 2023;16:e202300016.","journal-title":"J Biophotonics"}],"container-title":["Journal of Nanobiotechnology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12951-025-03339-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12951-025-03339-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12951-025-03339-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T07:02:20Z","timestamp":1744786940000},"score":1,"resource":{"primary":{"URL":"https:\/\/jnanobiotechnology.biomedcentral.com\/articles\/10.1186\/s12951-025-03339-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,16]]},"references-count":55,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["3339"],"URL":"https:\/\/doi.org\/10.1186\/s12951-025-03339-5","relation":{},"ISSN":["1477-3155"],"issn-type":[{"value":"1477-3155","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,16]]},"assertion":[{"value":"17 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The non-interventional research protocols of clinical pathological samples (including normal lymphoma and non-Hodgkin's lymphoma (NHL) from healthy donors and lymphoma patients) used in the present study were approved by the Ethics Committee of the First Affiliated Hospital of Soochow University [Audit Number: (2023) LUN Research Batch No. 314 approvals].","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"295"}}