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Your search keyword '"Kulkarni, Ameya S"' showing total 29 results
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29 results on '"Kulkarni, Ameya S"'

5. Functional characterization of a single nucleotide polymorphism associated with Alzheimer’s disease in a hiPSC-based neuron model

Author

Stolzenburg, Lindsay R., primary, Esmaeeli, Sahar, additional, Kulkarni, Ameya S., additional, Murphy, Erin, additional, Kwon, Taekyung, additional, Preiss, Christina, additional, Bahnassawy, Lamiaa, additional, Stender, Joshua D., additional, Manos, Justine D., additional, Reinhardt, Peter, additional, Rahimov, Fedik, additional, Waring, Jeffrey F., additional, and Ramathal, Cyril Y., additional

Published
2023
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10. Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer

Author

Ren, Zuen, primary, Liang, Huizhi, additional, Galbo, Phillip M., additional, Dharmaratne, Malindrie, additional, Kulkarni, Ameya S., additional, Fard, Atefeh Taherian, additional, Aoun, Marie Louise, additional, Martinez-Lopez, Nuria, additional, Suyama, Kimita, additional, Benard, Outhiriaradjou, additional, Zheng, Wei, additional, Liu, Yang, additional, Albanese, Joseph, additional, Zheng, Deyou, additional, Mar, Jessica C., additional, Singh, Rajat, additional, Prystowsky, Michael B., additional, Norton, Larry, additional, and Hazan, Rachel B., additional

Published
2022
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11. scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data.

Author

Dharmaratne, Malindrie, Kulkarni, Ameya S, Taherian Fard, Atefeh, and Mar, Jessica C

Subjects
*GENE expression, *RNA sequencing, *PHENOTYPES, *GENETIC transcription regulation, *OPEN-ended questions
Abstract

Background Single-cell RNA sequencing (scRNA-seq) methods have been advantageous for quantifying cell-to-cell variation by profiling the transcriptomes of individual cells. For scRNA-seq data, variability in gene expression reflects the degree of variation in gene expression from one cell to another. Analyses that focus on cell–cell variability therefore are useful for going beyond changes based on average expression and, instead, identifying genes with homogeneous expression versus those that vary widely from cell to cell. Results We present a novel statistical framework, scShapes , for identifying differential distributions in single-cell RNA-sequencing data using generalized linear models. Most approaches for differential gene expression detect shifts in the mean value. However, as single-cell data are driven by overdispersion and dropouts, moving beyond means and using distributions that can handle excess zeros is critical. scShapes quantifies gene-specific cell-to-cell variability by testing for differences in the expression distribution while flexibly adjusting for covariates if required. We demonstrate that scShapes identifies subtle variations that are independent of altered mean expression and detects biologically relevant genes that were not discovered through standard approaches. Conclusions This analysis also draws attention to genes that switch distribution shapes from a unimodal distribution to a zero-inflated distribution and raises open questions about the plausible biological mechanisms that may give rise to this, such as transcriptional bursting. Overall, the results from scShapes help to expand our understanding of the role that gene expression plays in the transcriptional regulation of a specific perturbation or cellular phenotype. Our framework scShapes is incorporated into a Bioconductor R package (https://www.bioconductor.org/packages/release/bioc/html/scShapes.html). [ABSTRACT FROM AUTHOR]

Published
2023
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12. Muscle fibrosis and maladaptation occur progressively in CKD and are rescued by dialysis

Author

Brightwell, Camille R., primary, Kulkarni, Ameya S., additional, Paredes, William, additional, Zhang, Kehao, additional, Perkins, Jaclyn B., additional, Gatlin, Knubian J., additional, Custodio, Matthew, additional, Farooq, Hina, additional, Zaidi, Bushra, additional, Pai, Rima, additional, Buttar, Rupinder S., additional, Tang, Yan, additional, Melamed, Michal L., additional, Hostetter, Thomas H., additional, Pessin, Jeffrey E., additional, Hawkins, Meredith, additional, Fry, Christopher S., additional, and Abramowitz, Matthew K., additional

Published
2021
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15. Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer.

Author

Zuen Ren, Huizhi Liang, Galbo, Phillip M., Dharmaratne, Malindrie, Kulkarni, Ameya S., Fard, Atefeh Taherian, Aoune, Marie Louise, Martinez-Lopez, Nuria, Suyama, Kimita, Benard, Outhiriaradjou, Wei Zheng, Yang Liu, Albanese, Joseph, Deyou Zheng, Mar, Jessica C., Singh, Rajat, Prystowsky, Michael B., Norton, Larry, and Hazan, Rachel B.

Subjects
GLUTATHIONE peroxidase, BREAST cancer, VASCULAR endothelial growth factors, OXIDATION-reduction reaction, CURCUMIN, REACTIVE oxygen species
Abstract

In search of redox mechanisms in breast cancer, we uncovered a striking role for glutathione peroxidase 2 (GPx2) in oncogenic signaling and patient survival. GPx2 loss stimulates malignant progression due to reactive oxygen species/hypoxia inducible factor-α (HIF1α)/ VEGFA (vascular endothelial growth factor A) signaling, causing poor perfusion and hypoxia, which were reversed by GPx2 reexpression or HIF1α inhibition. Ingenuity Pathway Analysis revealed a link between GPx2 loss, tumor angiogenesis, metabolic modulation, and HIF1α signaling. Single-cell RNA analysis and bioenergetic profiling revealed that GPx2 loss stimulated the Warburg effect in most tumor cell subpopulations, except for one cluster, which was capable of oxidative phosphorylation and glycolysis, as confirmed by coexpression of phosphorylated-AMPK and GLUT1. These findings underscore a unique role for redox signaling by GPx2 dysregulation in breast cancer, underlying tumor heterogeneity, leading to metabolic plasticity and malignant progression. [ABSTRACT FROM AUTHOR]

Published
2022
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29. Amine-boranes: green hypergolic fuels with consistently low ignition delays.

Author

Ramachandran PV, Kulkarni AS, Pfeil MA, Dennis JD, Willits JD, Heister SD, Son SF, and Pourpoint TL

Abstract

Complexation of amines with borane converts them to hypergols or decreases their ignition delays (IDs) multifold (with white fuming nitric acid as the oxidant). With consistently low IDs, amine-boranes represent a class of compounds that can be promising alternatives to toxic hydrazine and its derivatives as propellants. A structure-hypergolicity relationship study reveals the necessary features for the low ID., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Published
2014
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