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Daniel I. Benjamin

Researcher at University of California, Berkeley

Publications -  21
Citations -  1509

Daniel I. Benjamin is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Flux (metabolism) & Glycolysis. The author has an hindex of 13, co-authored 19 publications receiving 1166 citations. Previous affiliations of Daniel I. Benjamin include Stanford University.

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Microglia dictate the impact of saturated fat consumption on hypothalamic inflammation and neuronal function.

TL;DR: It is shown that microglia sense SFAs and orchestrate an inflammatory process in the MBH that alters neuronal function when SFA consumption is high, and in this context, microglial depletion enhances leptin signaling and reduces food intake.
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A dysregulated endocannabinoid-eicosanoid network supports pathogenesis in a mouse model of Alzheimer's disease.

TL;DR: It is found that pharmacological blockade of MAGL recapitulates the cytokine-lowering effects through reduced prostaglandin production, rather than enhanced endocannabinoid signaling, and put forth MAGL inhibitors as a potential next-generation strategy for combating AD.
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Ether lipid generating enzyme AGPS alters the balance of structural and signaling lipids to fuel cancer pathogenicity

TL;DR: It is demonstrated that ablation of AGPS in cancer cells results in reduced cell survival, cancer aggressiveness, and tumor growth through altering the balance of ether lipid, fatty acid, eicosanoid, and fatty acid–derived glycerophospholipid metabolism, resulting in an overall reduction in the levels of several oncogenic signaling lipids.
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HIF-1α Is an Essential Mediator of IFN-γ–Dependent Immunity to Mycobacterium tuberculosis

TL;DR: HIF-1α is identified as a novel regulator of IFN-γ–dependent immunity that coordinates an immunometabolic program essential for control of M. tuberculosis infection both in vitro and in vivo.
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Global Profiling Strategies for Mapping Dysregulated Metabolic Pathways in Cancer

TL;DR: This review presents several examples of how large-scale profiling platforms have yielded fundamental insights into dysregulated metabolism in cancer and questions and challenges that must be addressed to more completely describe, and eventually control, the diverse metabolic pathways that support tumorigenesis.