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296 results on '"Singh, Jaiveer"'

7. PD-1 maintains CD8 T cell tolerance towards cutaneous neoantigens

Author

Damo, Martina, Hornick, Noah I., Venkat, Aarthi, William, Ivana, Clulo, Kathryn, Venkatesan, Srividhya, He, Jiaming, Fagerberg, Eric, Loza, Jennifer L., Kwok, Darwin, Tal, Aya, Buck, Jessica, Cui, Can, Singh, Jaiveer, Damsky, William E., Leventhal, Jonathan S., Krishnaswamy, Smita, and Joshi, Nikhil S.

Published
2023
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14. A robust and interpretable end-to-end deep learning model for cytometry data

Author

Hu, Zicheng, Tang, Alice, Singh, Jaiveer, Bhattacharya, Sanchita, and Butte, Atul J

Subjects
Information and Computing Sciences, Machine Learning, Infectious Diseases, Good Health and Well Being, Cytomegalovirus Infections, Deep Learning, Flow Cytometry, Humans, T-Lymphocytes, CyTOF, flow cytometry, deep learning, cytomegalovirus, model interpretation
Abstract

Cytometry technologies are essential tools for immunology research, providing high-throughput measurements of the immune cells at the single-cell level. Existing approaches in interpreting and using cytometry measurements include manual or automated gating to identify cell subsets from the cytometry data, providing highly intuitive results but may lead to significant information loss, in that additional details in measured or correlated cell signals might be missed. In this study, we propose and test a deep convolutional neural network for analyzing cytometry data in an end-to-end fashion, allowing a direct association between raw cytometry data and the clinical outcome of interest. Using nine large cytometry by time-of-flight mass spectrometry or mass cytometry (CyTOF) studies from the open-access ImmPort database, we demonstrated that the deep convolutional neural network model can accurately diagnose the latent cytomegalovirus (CMV) in healthy individuals, even when using highly heterogeneous data from different studies. In addition, we developed a permutation-based method for interpreting the deep convolutional neural network model. We were able to identify a CD27- CD94+ CD8+ T cell population significantly associated with latent CMV infection, confirming the findings in previous studies. Finally, we provide a tutorial for creating, training, and interpreting the tailored deep learning model for cytometry data using Keras and TensorFlow (https://github.com/hzc363/DeepLearningCyTOF).

Published
2020

20. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

Author

Greenwald, Noah F., Miller, Geneva, Moen, Erick, Kong, Alex, Kagel, Adam, Dougherty, Thomas, Fullaway, Christine Camacho, McIntosh, Brianna J., Leow, Ke Xuan, Schwartz, Morgan Sarah, Pavelchek, Cole, Cui, Sunny, Camplisson, Isabella, Bar-Tal, Omer, Singh, Jaiveer, Fong, Mara, Chaudhry, Gautam, Abraham, Zion, Moseley, Jackson, Warshawsky, Shiri, Soon, Erin, Greenbaum, Shirley, Risom, Tyler, Hollmann, Travis, Bendall, Sean C., Keren, Leeat, Graf, William, Angelo, Michael, and Van Valen, David

Published
2022
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30. Size-induced structural phase transition at ~6.0 nm from mixed fcc-hcp to purely fcc structure in monodispersed nickel nanoparticles

Author

Tarachand, Sharma, Vikash, Singh, Jaiveer, Nayak, Chandrani, Bhattacharyya, Dibyendu, Kaurav, Netram, Jha, Shambhu N., and Okram, Gunadhor S.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

We have investigated the core issue of atomic lattices in monodispersed Ni nanoparticles (NPs) of sizes 3.8 nm to 10.1 nm using detailed analysis of X-ray diffraction, synchrotron radiation X-ray absorption spectroscopy (XAS) and magnetization data. This has revealed the very remarkable coexistence of atomic face-centered cubic (fcc) and hexagonal closed-packed (hcp) lattices in samples with particle size less than or equal to 6.0 nm with the prevalence of only fcc phase beyond this. They are also associated with reduced coordination number, modified electronic structure, and surface atom coordination with ligands. Magnetization data furthermore reveal coexistence of ferromagnetism and superparamagnetism at 300 K. Considered to be due to dominant roles of ligands, they are likely to open up far-reaching implications to their future applications., Comment: 23 pages, 11 figures

Published
2016

31. Quantum Size Effect Exponential Heat Capacity in 4 nm Natural Nickel Nanolattice

Author

Patel, Tarachand, Singh, Jaiveer, Samatham, Satya Sanmukharao, Venkateshwarlu, Dontula, Kaurav, Netram, Ganesan, Vedachalaiyer, and Okram, Gunadhor Singh

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Quantum size effect-induced heat capacity of metal nanoparticles at low temperatures was predicted 79 years ago to be exponential. This, however, has not been reported until date. In defiance, we demonstrate here observation of exponentially decaying heat capacity, below 45.2 K, associated with quantum jumps, exceptionally in 4 nm naturally assembled hexagonal closed packed (hcp) lattice of nickel nanoparticles; high magnetic fields have negligible effect on these features. Magnetic susceptibilities in contrast reveal evolution of quantum size effects with decrease in particle size. They exhibit sharp rise below about 30 K and vestiges of saturations below 5 K. The former is explained by Curie-like characteristics of odd electrons while the latter tend towards the orthogonal even-like case. These characteristics, ascribed to the ensembles of Ni nanoparticles, will give a new direction in understanding this crucial thermodynamic phenome-non., Comment: 12 pages 9 figures

Published
2016

45. Naturally self-assembled nickel nanolattice

Author

Singh, Jaiveer, Kaurav, Netram, Lalla, Niranjan Prasad, and Okram, Gunadhor Singh

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, G.0
Abstract

This is the first report on the critical nature of nanolattice formability of different particle size (~4-10nm) of monodispersed nickel nanoparticles. They exhibit strikingly hexagonal close-packed (hcp) nanolattices without extra forces, whenever trioctylphosphine is (one of) the surfactant(s). This clearly establishes the unique role of nanolattice formability of trioctylphosphine. The c/a ratios are interestingly identical to those of atomic lattices. An attempt has also been made to explain them based on the balanced attractive and repulsive forces of the surfactant-generated cation-anion pairs on the surface of the nanoparticles. The present findings therefore will provide a far-reaching vista to fabrication of varieties of natural nanolattices and their understanding on applications in a new paradigm., Comment: 6 page article with 3 figures, one table and supporting electronic information including 4 figures, submitted for publication

Published
2014

47. Congestion Control in Vehicular Ad Hoc Network: A Review

Author

Singh, Jaiveer, Singh, Karan, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Lobiyal, Daya K., editor, Mansotra, Vibhakar, editor, and Singh, Umang, editor

Published
2018
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