Journal of Innovative Optical Health Sciences, Volume. 18, Issue 1, 2550003(2025)
Machine learning-enhanced SERS for accurate azoospermia diagnosis via seminal plasma exosome analysis
[1] P. Njagi et al. Financial costs of assisted reproductive technology for patients in low- and middle-income countries: A systematic review. Hum. Reprod. Open, 2023, hoad007(2023).
[2] A. Agarwal et al. Male infertility. Lancet, 397, 319-333(2021).
[3] J. Chen et al. Microbiology and immune mechanisms associated with male infertility. Front. Immunol., 14, 1139450(2023).
[4] F. Ghieh et al. Genetic defects in human azoospermia. Basic Clin. Androl., 29, 1-16(2019).
[5] L. Björndahl, J. Kirkman Brown. The sixth edition of the WHO laboratory manual for the examination and processing of human semen: Ensuring quality and standardization in basic examination of human ejaculates. Fertil. Steril., 117, 246-251(2022).
[6] R. K. Sharma et al. Role of cytocentrifugation combined with nuclear fast picroindigocarmine staining in detecting cryptozoospermia in men diagnosed with azoospermia. World J. Mens Health, 40, 627(2022).
[7] J. A. Marinaro et al. Successful cryptozoospermia management with multiple semen specimen collection. Fertil. Steril., 120, 996-1003(2023).
[8] M. Jeseta et al. Non-invasive diagnostics of male spermatogenesis from seminal plasma: Seminal proteins. Diagnostics (Basel), 13, 2468(2023).
[9] D. M. Pegtel, S. J. Gould. Exosomes. Annu. Rev. Biochem., 88, 487-514(2019).
[10] N. Wang et al. Exosomes: New insights into the pathogenesis of metabolic syndrome. Biology (Basel), 12, 1480(2023).
[11] M. Ghafourian et al. The implications of exosomes in pregnancy: Emerging as new diagnostic markers and therapeutics targets. Cell Commun. Signal., 20, 51(2022).
[12] M. Dimik et al. The exosome: A review of current therapeutic roles and capabilities in human reproduction. Drug Deliv. Transl. Res., 13, 473-502(2023).
[13] Y. Daneshmandpour et al. Micrornas association with azoospermia, oligospermia, asthenozoospermia, and teratozoospermia: A systematic review. J. Assist. Reprod. Genet., 37, 763-775(2020).
[14] D. Fietz et al. Proteomic biomarkers in seminal plasma as predictors of reproductive potential in azoospermic men. Front. Endocrinol. (Lausanne), 15, 1327800(2024).
[15] K. Yu et al. Comparative proteomic analysis of seminal plasma exosomes in buffalo with high and low sperm motility. BMC Genomics, 24, 8(2023).
[16] A. S. Neyroud et al. Extra-cellular vesicles of the male genital tract: New actors in male fertility?. Basic Clin. Androl., 31, 1-9(2021).
[17] Z. Wang et al. Early diagnosis of thyroid-associated ophthalmopathy using label-free raman spectroscopy and multivariate analysis. Spectrochim. Acta A: Mol. Biomol. Spectrosc., 310, 123905(2024).
[18] Y. Qian et al. Label-free and raman dyes-free surface-enhanced raman spectroscopy for detection of DNA. Sens. Actuators B: Chem., 254, 483-489(2018).
[19] I. W. Schie et al. High-throughput screening raman spectroscopy platform for label-free cellomics. Anal. Chem., 90, 2023-2030(2018).
[20] S. He et al. Label-free identification of trace microcystin-lr with surface-enhanced raman scattering spectra. Talanta, 195, 401-406(2019).
[21] A. Downes, A. Elfick. Raman spectroscopy and related techniques in biomedicine. Sensors (Basel), 10, 1871-1889(2010).
[22] S. Sloan-Dennison et al. From raman to sesorrs: Moving deeper into cancer detection and treatment monitoring. Chem. Commun., 57, 12436-12451(2021).
[23] M. Moskovits. Surface-enhanced spectroscopy. Rev. Mod. Phys., 57, 783-826(1985).
[24] W. Lin et al. An integrated sample-to-answer sers platform for multiplex phenotyping of extracellular vesicles. Sens. Actuators B: Chem., 394, 134355(2023).
[25] L. Guerrini et al. Surface-enhanced raman scattering (sers) spectroscopy for sensing and characterization of exosomes in cancer diagnosis. Cancers, 13, 2179(2021).
[26] C. Fan et al. Ultrasensitive exosome detection by modularized sers labeling for postoperative recurrence surveillance. ACS Sens., 6, 3234-3241(2021).
[27] Q. Zhang et al. Dual-aptamer-assisted ratiometric sers biosensor for ultrasensitive and precise identification of breast cancer exosomes. ACS Sens., 8, 875-883(2023).
[28] U. Parlatan et al. Label-free identification of exosomes using raman spectroscopy and machine learning. Small, 19, 2205519(2023).
[29] Y. Xie et al. Artificial intelligent label-free sers profiling of serum exosomes for breast cancer diagnosis and postoperative assessment. Nano Lett., 22, 7910-7918(2022).
[30] E. A. Jensen et al. Label-free blood typing by raman spectroscopy and artificial intelligence. Adv. Mater. Technol., 9, 2301462(2024).
[31] G. Frens. Controlled nucleation for the regulation of the particle size in monodisperse gold suspensions. Nature Phys. Sci., 241, 20-22(1973).
[32] A. Vashisht, P. K. Ahluwalia, G. K. Gahlay. A comparative analysis of the altered levels of human seminal plasma constituents as contributing factors in different types of male infertility. Curr. Issues Mol. Biol., 43, 1307-1324(2021).
[33] Z. Movasaghi, S. Rehman, I. U. Rehman. Raman spectroscopy of biological tissues. Appl. Spectrosc. Rev., 42, 493-541(2007).
[34] V. A. Binson et al. A review of machine learning algorithms for biomedical applications. Ann. Biomed. Eng., 52, 1159-1183(2024).
[35] I. H. Sarker. Machine learning: Algorithms, real-world applications and research directions. SN Comput. Sci., 2, 160(2021).
[36] R. Ratra, P. Gulia. Experimental evaluation of open source data mining tools (weka and orange). Int. J. Eng. Trends Technol., 68, 30-35(2020).
[37] A. I. Adekitan, J. Abolade, O. Shobayo. Data mining approach for predicting the daily internet data traffic of a smart university. J. Big Data, 6, 11(2019).
[38] C. A. Yen, S. P. Curran. Incomplete proline catabolism drives premature sperm aging. Aging Cell, 20, e13308(2021).
[39] F. Benko et al. Signaling roleplay between ion channels during mammalian sperm capacitation. Biomedicines, 11, 2519(2023).
[40] X. Cheng et al. Lipidomics profiles of human spermatozoa: Insights into capacitation and acrosome reaction using uplc-ms-based approach. Front. Endocrinol., 14, 1273878(2023).
[41] F. Antonucci et al. Snap-25, a known presynaptic protein with emerging postsynaptic functions. Front. Synaptic Neurosci., 8, 7(2016).
[42] J. Zhao et al. Specific depletion of the motor protein kif5b leads to deficits in dendritic transport, synaptic plasticity and memory. eLife, 9, e53456(2020).
[43] T. Skotland, K. Sandvig, A. Llorente. Lipids in exosomes: Current knowledge and the way forward. Prog. Lipid Res., 66, 30-41(2017).
[44] J. Huang et al. Rapid azoospermia classification by stimulated raman scattering and second harmonic generation microscopy. Biomed. Opt. Express, 14, 5569-5582(2023).
Get Citation
Copy Citation Text
Jiarui Wang, Shiyan Jiang, Jiaxin Shi, Jing Wang, Shengrong Du, Zufang Huang. Machine learning-enhanced SERS for accurate azoospermia diagnosis via seminal plasma exosome analysis[J]. Journal of Innovative Optical Health Sciences, 2025, 18(1): 2550003
Category: Research Articles
Received: Aug. 6, 2024
Accepted: Oct. 20, 2024
Published Online: Feb. 21, 2025
The Author Email: Du Shengrong (dushengrong2001@126.com), Huang Zufang (zfhuang@fjnu.edu.cn)