Vidyani Suryadevara

All Publications

• Thwarting Alzheimer's Disease through Healthy Lifestyle Habits: Hope for the Future. Neurology international Govindugari, V. L., Golla, S., Reddy, S. D., Chunduri, A., Nunna, L. S., Madasu, J., Shamshabad, V., Bandela, M., Suryadevara, V. 2023; 15 (1): 162-187

  Abstract

  Alzheimer's disease (AD) is a neurodegenerative disorder that slowly disintegrates memory and thinking skills. Age is known to be the major risk factor in AD, but there are several nonmodifiable and modifiable causes. The nonmodifiable risk factors such as family history, high cholesterol, head injuries, gender, pollution, and genetic aberrations are reported to expediate disease progression. The modifiable risk factors of AD that may help prevent or delay the onset of AD in liable people, which this review focuses on, includes lifestyle, diet, substance use, lack of physical and mental activity, social life, sleep, among other causes. We also discuss how mitigating underlying conditions such as hearing loss and cardiovascular complications could be beneficial in preventing cognitive decline. As the current medications can only treat the manifestations of AD and not the underlying process, healthy lifestyle choices associated with modifiable factors is the best alternative strategy to combat the disease.

  View details for DOI 10.3390/neurolint15010013

  View details for PubMedID 36810468

• MegaPro, a clinically translatable nanoparticle for in vivo tracking of stem cell implants in pig cartilage defects. Theranostics Suryadevara, V., Hajipour, M. J., Adams, L. C., Aissaoui, N. M., Rashidi, A., Kiru, L., Theruvath, A. J., Huang, C., Maruyama, M., Tsubosaka, M., Lyons, J. K., Wu, W. E., Roudi, R., Goodman, S. B., Daldrup-Link, H. E. 2023; 13 (8): 2710-2720

  Abstract

  Rationale: Efficient labeling methods for mesenchymal stem cells (MSCs) are crucial for tracking and understanding their behavior in regenerative medicine applications, particularly in cartilage defects. MegaPro nanoparticles have emerged as a potential alternative to ferumoxytol nanoparticles for this purpose. Methods: In this study, we employed mechanoporation to develop an efficient labeling method for MSCs using MegaPro nanoparticles and compared their effectiveness with ferumoxytol nanoparticles in tracking MSCs and chondrogenic pellets. Pig MSCs were labeled with both nanoparticles using a custom-made microfluidic device, and their characteristics were analyzed using various imaging and spectroscopy techniques. The viability and differentiation capacity of labeled MSCs were also assessed. Labeled MSCs and chondrogenic pellets were implanted into pig knee joints and monitored using MRI and histological analysis. Results: MegaPro-labeled MSCs demonstrated shorter T2 relaxation times, higher iron content, and greater nanoparticle uptake compared to ferumoxytol-labeled MSCs, without significantly affecting their viability and differentiation capacity. Post-implantation, MegaPro-labeled MSCs and chondrogenic pellets displayed a strong hypointense signal on MRI with considerably shorter T2* relaxation times compared to adjacent cartilage. The hypointense signal of both MegaPro- and ferumoxytol-labeled chondrogenic pellets decreased over time. Histological evaluations showed regenerated defect areas and proteoglycan formation with no significant differences between the labeled groups. Conclusion: Our study demonstrates that mechanoporation with MegaPro nanoparticles enables efficient MSC labeling without affecting viability or differentiation. MegaPro-labeled cells show enhanced MRI tracking compared to ferumoxytol-labeled cells, emphasizing their potential in clinical stem cell therapies for cartilage defects.

  View details for DOI 10.7150/thno.82620

  View details for PubMedID 37215574

• NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health NATURE AGING Lee, P. J., Benz, C. C., Blood, P., Boerner, K., Campisi, J., Chen, F., Daldrup-Link, H., De Jager, P., Ding, L., Duncan, F. E., Eickelberg, O., Fan, R., Finkel, T., Furman, D., Garovic, V., Gehlenborg, N., Glass, C., Heckenbach, I., Joseph, Z., Katiyar, P., Kim, S., Koenigshoff, M., Kuchel, G. A., Lee, H., Lee, J., Ma, J., Ma, Q., Melov, S., Metis, K., Mora, A. L., Musi, N., Neretti, N., Passos, J. F., Rahman, I., Rivera-Mulia, J., Robson, P., Rojas, M., Roy, A. L., Scheibye-Knudsen, M., Schilling, B., Shi, P., Silverstein, J. C., Suryadevara, V., Xie, J., Wang, J., Wong, A., Niedernhofer, L. J., Wang, S., Anvari, H., Balough, J., Benz, C., Bons, J., Brenerman, B., Evans, W., Gerencser, A., Gregory, H., Hansen, M., Justice, J., Kapahi, P., Murad, N., O'Broin, A., Pavone, M., Powell, M., Scott, G., Shanes, E., Shankaran, M., Verdin, E., Winer, D., Wu, F., Adams, A., Blood, P. D., Bueckle, A., Cao-Berg, I., Chen, H., Davis, M., Filus, S., Hao, Y., Hartman, A., Hasanaj, E., Helfer, J., Herr, B., Bar Joseph, Z., Molla, G., Mou, G., Puerto, J., Quardokus, E. M., Ropelewski, A. J., Ruffalo, M., Satija, R., Schwenk, M., Scibek, R., Shirey, W., Sibilla, M., Welling, J., Yuan, Z., Bonneau, R., Christiano, A., Izar, B., Menon, V., Owens, D. M., Phatnani, H., Smith, C., Suh, Y., Teich, A. F., Bekker, V., Chan, C., Coutavas, E., Hartwig, M. G., Ji, Z., Nixon, A. B., Dou, Z., Rajagopal, J., Slavov, N., Holmes, D., Jurk, D., Kirkland, J. L., Lagnado, A., Tchkonia, T., Abraham, K., Dibattista, A., Fridell, Y., Howcroft, T., Jhappan, C., Montes, V., Prabhudas, M., Resat, H., Taylor, V., Kumar, M., Cigarroa, F., Cohn, R., Cortes, T. M., Courtois, E., Chuang, J., Dave, M., Domanskyi, S., Enninga, E., Eryilmaz, G., Espinoza, S. E., Gelfond, J., Kirkland, J., Kuo, C., Lehman, J. S., Aguayo-Mazzucato, C., Meves, A., Rani, M., Sanders, S., Thibodeau, A., Tullius, S. G., Ucar, D., White, B., Wu, Q., Xu, M., Yamaguchi, S., Assarzadegan, N., Cho, C., Hwang, I., Hwang, Y., Xi, J., Adeyi, O. A., Aliferis, C. F., Bartolomucci, A., Dong, X., DuFresne-To, M. J., Ikramuddin, S., Johnson, S. G., Nelson, A. C., Revelo, X. S., Trevilla-Garcia, C., Sedivy, J. M., Thompson, E. L., Robbins, P. D., Wang, J., Aird, K. M., Alder, J. K., Beaulieu, D., Bueno, M., Calyeca, J., Chamucero-Millaris, J. A., Chan, S. Y., Chung, D., Corbett, A., Gorbunova, V., Gowdy, K. M., Gurkar, A., Horowitz, J. C., Hu, Q., Kaur, G., Khaliullin, T. O., Lafyatis, R., Lanna, S., Li, D., Ma, A., Morris, A., Muthumalage, T. M., Peters, V., Pryhuber, G. S., Reader, B. F., Rosas, L., Sembrat, J. C., Shaikh, S., Shi, H., Stacey, S. D., St Croix, C., Wang, C., Wang, Q., Watts, A., Gu, L., Lin, Y., Rabinovitch, P. S., Sweetwyne, M. T., Artyomov, M. N., Ballentine, S. J., Chheda, M. G., Davies, S. R., DiPersio, J. F., Fields, R. C., Fitzpatrick, J. J., Fulton, R. S., Imai, S., Jain, S., Ju, T., Kushnir, V. M., Link, D. C., Ben Major, M., Oh, S. T., Rapp, D., Rettig, M. P., Stewart, S. A., Veis, D. J., Vij, K. R., Wendl, M. C., Wyczalkowski, M. A., Craft, J. E., Enninful, A., Farzad, N., Gershkovich, P., Halene, S., Kluger, Y., VanOudenhove, J., Xu, M., Yang, J., Yang, M., SenNet Consortium 2022; 2 (12): 1090-1100

  View details for DOI 10.1038/s43587-022-00326-5

  View details for Web of Science ID 000916582800010