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DTSTART;TZID=America/Los_Angeles:20251106T114000
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SUMMARY:BME 280B Seminar: Anne Nakamoto\, Alan Zhang\, Shelbi Russell
DESCRIPTION:Presenter 1: Anne Nakamoto\, BME PhD Candidate\, Corbett-Detig Lab\, UC Santa Cruz \nTalk: Investigating deleterious mutation burden across populations and landscapes in the California Conservation Genomics Project \nDescription: Biodiversity is being lost at an accelerated rate due in part to anthropogenic forces\, posing a threat to the sustainability of Earth’s ecosystems as well as to human health. A major goal of conservation genomics is to use genomic data to understand population health\, which can inform management decisions for the preservation of biodiversity. The California Conservation Genomics Project (CCGP) is an extensive dataset containing species of conservation interest sampled across California\, allowing a landscape genomics approach to conservation. Among the many metrics that can be used to assess population health is genetic load\, which refers to the reduction in fitness imposed by deleterious mutations. In this work\, we construct a bioinformatic analysis framework to identify deleterious genomic variants in CCGP species based on evolutionary constraint. This allows us to investigate patterns in genetic burden across populations and the landscape of California. \nPresenter 2: Alan Zhang\, BME PhD Candidate\, Corbett-Detig Lab\, UC Santa Cruz \nTalk: Scalable Strain-Level Metagenomic Deconvolution and Assembly Using Pangenome Mutation-Annotated Networks \nDescription: Strain-level deconvolution of metagenomic samples is essential for pathogen surveillance\, mixed infection diagnosis\, and evolutionary genomics\, yet remains computationally challenging as genomic databases expand. Existing methods scale poorly with database size or rely exclusively on single nucleotide polymorphism (SNP) information. SNP-based approaches rely on mutation-annotated trees and thus require well-established reference genomes\, limiting their applicability to divergent species that lack alignable root references. We present panMAMA (panMAN Metagenomic Assignment and Metagenomic Assembly)\, a method that leverages the pangenome Mutation-Annotated Network (panMAN) data structure to enable accurate strain-level quantification across both closely related and divergent genomes. By employing k-min-mer-based pseudo-chaining with a seed-annotated tree index\, panMAMA achieves substantial computational speedup compared to existing k-mer-based tools while maintaining high accuracy. We demonstrate that panMAMA accurately deconvolves both closely related SARS-CoV-2 genomes and divergent HIV and respiratory syncytial virus (RSV) genomes\, outperforming existing tools including Freyja on simulated wastewater samples. Through a hybrid heuristic and maximum likelihood approach for read assignment and consensus calling\, panMAMA effectively recovers variant genomes from low-heterogeneity samples of divergent species. These results establish panMAMA as a scalable and accurate platform that extends strain-level metagenomic analysis to previously intractable highly divergent species. \nPresenter 3: Shelbi Russell\, PhD\, UC Santa Cruz\, Ph.D.\, Organismic & Evol Bio\, Harvard\, PostDoc MCDB\, UC Santa Cruz \nDescription: Many animals harbor bacterial symbionts that manipulate host reproduction to enhance bacterial survival and transmission. Obligate intracellular symbionts\, such as Wolbachia pipientis\, are particularly adept at host manipulation\, influencing reproductive biology and even blocking viral replication. These bacterially induced traits have been harnessed in field studies to control mosquito populations and limit the spread of human pathogens like Dengue and Zika viruses. Despite these promising applications\, the molecular mechanisms underlying Wolbachia’s interactions with host cells remain poorly understood. Furthermore\, even less is known about the implications of these symbionts spreading to non-target hosts in the ecosystem. Previous work from my lab tackled these questions in vivo: we discovered that the wMel strain of Wolbachia can enhance host fertility and we discovered that even extremely low rates of horizontal symbiont transmission among hosts can influence bacterial genome evolution. However\, in vivo systems offer limited resolution to identify the precise cellular mechanisms of fertility enhancement and the real-time genomic impacts of horizontal transmission. Here\, we use an in vitro Drosophila system to 1) identify the cell type-specific impacts of Wolbachia infection on host-microbe interactions and 2) characterize how strains interact within host tissues during mixed infections. This simplified\, easy to sample system enabled us to concentrate the effects of host cell type on Wolbachia gene expression and to control de novo strain infections and mixtures. Through these experiments\, we discovered that different host cell types induce differential Wolbachia gene expression that feeds back to alter host gene expression and epigenetic silencing. These findings have motivated on-going single cell RNAseq work to resolve the process at the single cell level\, during de novo infections. Results from the experimental mixed infections revealed highly reproducible strain and cell type-specific dynamics. We will leverage these discoveries to understand strain-specific tissue tropisms and how multiple strains can co-exist as superinfections in nature\, which will inform future biocontrol strategies. \nBio: Shelbi is an Assistant Professor in the Department of Biomolecular Engineering at UCSC. She started her lab in 2022\, after completing her PhD at Harvard University in 2016 and performing her postdoctoral work at UCSC. Her passion for studying symbiotic systems began as an undergraduate researcher at the University of Kansas describing new tapeworm species. She transitioned to studying the evolutionary genomics of bacterial-animal mutualisms in her PhD and was awarded the UC Chancellor’s Postdoctoral Fellowship and the NIH Career Development Award (K99) to test genomic hypotheses in the Wolbachia-Drosophila model system during her postdoc. As faculty\, she is working to learn how hosts and microbes function and evolve so we can engineer associations for biological control. She has authored 24 papers and obtained $2.75 million in funding. Her interdisciplinary training makes her uniquely qualified to lead these investigations and has enabled novel breakthroughs in our understanding of symbiont evolution and microbe-induced host phenotypes. \nHosted by: Professor Josh Stuart\, BME Department \nRoom: PSB-240
URL:https://events.ucsc.edu/event/bme-280b-seminar-anne-nakamoto-alan-zhang-shelbi-russell/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20251030T134000
DTEND;TZID=America/Los_Angeles:20251030T150000
DTSTAMP:20260429T212441
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SUMMARY:Applied Microeconomics and Trade Seminar Series presents: Shanjun Li
DESCRIPTION:Applied Microeconomics and Trade Seminar\nDate: Thursday\, October 30th\, 2025\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Shanjun Li\nPersonal Webpage \nTitle: Steven and Roberta Denning Professor of Global Sustainability \nAffiliation: Stanford University \nHost: Peter Christensen \n \nSeminar title: Range Anxiety\n \nABSTRACT:   Range anxiety\, the fear of depleting battery before reaching a charging station\, is often cited as a major barrier to electric vehicle (EV) adoption\, yet there has been limited formal economic analysis to quantify its importance and understand the policy implications. We develop a continuous-time dynamic model of EV usage and charging decisions to quantify range anxiety as the utility loss from feasible yet unrealized trips due to perceived range constraints. Using high-frequency data of 188\,000 EV trips and 30\,000 charging events among 8\,000 EVs in Shanghai\, we recover model parameters governing consumer driving and charging decisions. The estimates imply that\, across EV models with varying driving ranges\, average range anxiety was about $1\,900 in 2021 but declined to $1\,200 in 2024\, driven by improvements in charging infrastructure and\, especially\, in creases in driving range. Policy simulations underscore the importance of coordinating investments in battery capacity and charging infrastructure to address range anxiety: relative to socially optimal levels\, Shanghai’s EV market has under-invested in driving range while over-investing in charging infrastructure.
URL:https://events.ucsc.edu/event/applied-microeconomics-and-trade-seminar-series-presents-shanjun-li/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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DTSTART;TZID=America/Los_Angeles:20251030T114000
DTEND;TZID=America/Los_Angeles:20251030T131500
DTSTAMP:20260429T212441
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SUMMARY:BME 280B Seminar: Preconfigured neuronal firing sequences in human brain organoids
DESCRIPTION:Presenter: Tjitse (TJ) van der Molen\, Ph.D. (Postdoc\, Sharf Lab\, UC Santa Cruz and PhD Kosik Lab\, UC Santa Barbara) \nDescription: Neuronal firing sequences are thought to be the building blocks of information and broadcasting within the brain. Yet\, it remains unclear when these sequences emerge during neurodevelopment. Here we demonstrate that structured firing sequences appear in spontaneous activity of human and murine brain organoids\, both unguided and forebrain identity directed\, as well as ex vivo neonatal murine cortical slices. We observed temporally rigid and flexible firing patterns in human and murine brain organoids and early postnatal murine somatosensory cortex\, but not in dissociated primary cortical cultures. These results suggest that temporal sequences do not arise in an experience-dependent manner\, but are rather constrained by a preconfigured architecture established during neurodevelopment. By demonstrating the developmental recapitulation of neural firing patterns\, these findings highlight the potential of brain organoids as a model for neuronal circuit assembly. \nBio: Tjitse van der Molen studies spontaneous and evoked neural circuit activity in human and mouse stem cell derived brain organoids using dense multi electrode arrays. His main goal is to gain a better understanding of how healthy neural circuits process information and how possible malfunctions in neural circuit activity may result in disease\, in order to develop appropriate treatments. Tjitse recently completed his PhD in the Kosik lab at UC Santa Barbara and is now continuing his research as a postdoc in the Sharf lab at UC Santa Cruz. \nIn this talk\, Tjitse will present his latest manuscript that is currently in press with Nature Neuroscience\, focused on spontaneously occurring repeated sequential firing patterns that are present in the intrinsic activity of both brain organoids and neonatal mouse brain slices but not in 2D primary cultures. Similar sequential firing patterns have recently been shown to be important for information encoding and learning in the human cortex. The presence of these sequential firing patterns in the spontaneous activity of brain organoids that have never received external stimuli supports the notion that they develop in an experience-independent manner. \nHosted by: Professor Josh Stuart\, BME Department \nZoom Link: https://ucsc.zoom.us/j/99970819390?pwd=8sl5pd5TTBA5f6nqyCzo5mFpaqcEJG.1 \nFull Schedule: https://docs.google.com/document/d/1xD09vITwd_Pj9Ge6hHEuBFa5zBUYu2O-bjpSibt7VHE/edit?tab=t.0 \nRoom: PSB-240
URL:https://events.ucsc.edu/event/bme-280b-seminar-preconfigured-neuronal-firing-sequences-in-human-brain-organoids/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20251028T134000
DTEND;TZID=America/Los_Angeles:20251028T150000
DTSTAMP:20260429T212441
CREATED:20251022T210813Z
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SUMMARY:Macroeconomics & International Finance Seminar Series Presents: Zhiguo He
DESCRIPTION:Macroeconomics and International Finance Seminar\nDate: Tuesday\, October 28\, 2025\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Zhiguo He\nTitle: James Irvin Miller Professor of Finance\nAffiliation: Stanford University \nHost: Michael Leung \n \nSeminar title: Household Migration and Collateral Constraint: Cash-based Housing Resettlement in China\n \nABSTRACT:   Collateral constraints reduce household migration to expensive locations by restricting financing for home purchases. This endogenous location choice can amplify the impact of relaxing borrowing constraints. Using China’s cash-based shantytown renovation program (2015-2018) as a natural experiment\, we provide evidence that cash resettlement– by converting illiquid shanty houses into cash– facilitated household location upgrading and raised house prices in more expensive locations. A dynamic spatial model with collateral constraints confirms that endogenous location upgrading amplified the effect of cash transfer\, raising lifetime housing expenditures by nearly 50%\, and house price growth in low-tier cities by 9% in 2016-2020.
URL:https://events.ucsc.edu/event/macroeconomics-international-finance-seminar-series-presents-zhiguo-he/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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DTSTART;TZID=America/Los_Angeles:20251023T134000
DTEND;TZID=America/Los_Angeles:20251023T150000
DTSTAMP:20260429T212441
CREATED:20251022T204629Z
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SUMMARY:Behavioral\, Econometrics and Theory Seminar Series Presents: Kevin Chen
DESCRIPTION:Economics Behavioral\, Econometrics\, & Theory Seminar\nDate: Thursday\, October 23\, 2025\nTime: 1:40-3:00 p.m.\nLocation: Engineering 2\, Rm 499\n\n \n\nSpeaker: Kevin Chen \nTitle:  Assistant Professor of Economics \nAffiliation: Stanford University\nHost: Michael Leung\n \nSeminar title: Compound Selection Decisions: An Almost SURE Approach \n \nABSTRACT:  This paper proposes methods for producing compound selection decisions in a Gaussian sequence model. Given unknown\, fixed parameters µ_{1:n} and known σ_{1:n} with observations Yᵢ ∼ 𝒩(μᵢ\, σᵢ²)\, the aim is to select a subset of units S to maximize utility Σ_{i∈S}(μᵢ − Kᵢ) for known costs Kᵢ. Inspired by Stein’s unbiased risk estimate (SURE)\, we introduce an almost unbiased estimator\, ASSURE\, for the expected utility of a proposed decision rule. ASSURE allows a user to choose a welfare-maximizing rule from a pre-specified class by optimizing the estimated welfare\, thereby producing selection decisions that borrow strength across noisy estimates. We show that ASSURE yields decision rules that are asymptotically no worse than the optimal but infeasible rule in the pre-specified class. We apply ASSURE to p-value decision procedures in A/B testing\, selecting Census tracts for economic opportunity\, and identifying discriminating firms.
URL:https://events.ucsc.edu/event/behavioral-econometrics-and-theory-seminar-series-presents-kevin-chen/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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