2019 – Immuno Engineering Lab

IMMUNOENGINEERING LAB

01Nov

9. A composite of hyaluronic acid modified graphene oxide and iron oxide nanoparticles for targeted drug delivery and magneto-thermal therapy.

Nilkamal Pramanik, Santhalakshmi Ranganathan, Sunaina Rao, Kaushik Suneet, Shilpee Jain, Annapoorni Rangarajan, Siddharth Jhunjhunwala*. ACS Omega. 2019. 4 (5): 9284-9293. DOI: 10.1021/acsomega.9b00870.

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8. Association of mitochondria with microtubules inhibits mitochondrial fission by precluding assembly of the fission protein Dnm1.

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Kritika Mehta, Leeba A Chacko, Manjyot K Chugh, Siddharth Jhunjhunwala, Vaishnavi Ananthanarayanan*. Journal of Biological Chemistry. 2019. 294: 3385-3396. DOI: 10.1074/jbc.RA118.006799.

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7. Disparate effects of PEG or albumin based surface modification on uptake of nano-and micro-particles.

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Preeti Sharma, Devashish Sen, Varsha Neelakantan, Vinidhra Shankar, Siddharth Jhunjhunwala* Biomaterials Science. 2019. 7: 1411-1421. DOI: 10.1039/C8BM01545G.

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6. Injectable polymer-nanoparticle hydrogels for local immune cell recruitment.

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Owen S Fenton, Mark W Tibbitt, Eric A Appel, Siddharth Jhunjhunwala, Matthew J Webber, Robert Langer*. Biomacromolecules 2019; 20 (12): 4430-4436.

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Vision: To create and enable technologies
that solve clinical problems associated with
immune responses

IMMUNOENGINEERING LAB

01Nov

9. A composite of hyaluronic acid modified graphene oxide and iron oxide nanoparticles for targeted drug delivery and magneto-thermal therapy.

01Jul

8. Association of mitochondria with microtubules inhibits mitochondrial fission by precluding assembly of the fission protein Dnm1.

01Mar

7. Disparate effects of PEG or albumin based surface modification on uptake of nano-and micro-particles.

01Feb

6. Injectable polymer-nanoparticle hydrogels for local immune cell recruitment.

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29. A biomaterial implant model demonstrates that immature neutrophils drive immunopathology following acute injury.

28. Phenomenological modeling of gene transcription by approximating cooperativity of transcription factors improves prediction and reduces complexity in gene regulatory network models.

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