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DTSTART;TZID=America/New_York:20220117T120000
DTEND;TZID=America/New_York:20220117T130000
DTSTAMP:20260406T091321
CREATED:20220106T145241Z
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SUMMARY:BE Seminar: "Self-Assembling Nanotechnologies for Precision Biomaterials" (Santiago Correa\, Stanford)
DESCRIPTION:Self-assembled materials with defined nanoscale architectures can engage with biological systems in fundamentally new ways\, providing unprecedented biomedical opportunities. In particular\, the ability to more precisely control both the location and timing of drug release makes these biomaterials especially useful for delivering potent or sensitive cargo\, which has major implications for cancer therapy and immuno-engineering. Whether it is drug delivery\, gene therapy\, or tissue regeneration\, these materials are pushing the boundaries for engineering our own biology. \nIn this seminar\, I will discuss how self-assembled biomaterials are used to manipulate the tumor microenvironment to achieve gene silencing\, non-invasive tumor detection\, and localized immunostimulation in vivo. By leveraging non-covalent interactions to build composite nanomaterials\, we constructed multi-functional biomaterials capable of dynamic stimuli-responsive behaviors. I will detail the development of nanoparticle coatings that target ovarian tumors and preferentially traffic to specific subcellular compartments. These coatings enabled the development of both theranostic and immunostimulatory nanomedicines that required specific subcellular trafficking to carry out their functions. I will also discuss the development of nanoparticle-based\, supramolecular hydrogels\, which provide injectable\, clinically relevant strategies for localized cancer immunotherapy. Together\, these applications demonstrate the ability for self-assembled biomaterials to accomplish complex goals in vivo and mediate highly specific biomedical functions.
URL:https://seasevents.nmsdev7.com/event/be-seminar-self-assembling-nanotechnologies-for-precision-biomaterials-santiago-correa-stanford/
LOCATION:PA
CATEGORIES:Seminar,Postdoctoral
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220118T100000
DTEND;TZID=America/New_York:20220118T113000
DTSTAMP:20260406T091321
CREATED:20220113T173331Z
LAST-MODIFIED:20220113T173331Z
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SUMMARY:MEAM Seminar: "Assembly Engineering of Patchy Particles into Complex Structures\, and Beyond"
DESCRIPTION:The ability to predict\, design and make the perfect material with just the right properties to do what we want\, how we want\, and when we want is the holy grail of materials research. Such “materials on demand” require control over thermodynamics\, kinetics\, nonequilibrium behavior\, and structure across many length and time scales. With continuing advances in computer simulation capabilities\, we have never been closer to the goal\, but many challenges – and opportunities – remain. Many of those are at the boundaries of the subfields of materials research\, where ideas from one area spur advances in others\, and where computational tools and concepts are transferable across domains and scales. At the same time\, foundational understanding at one scale can help understand new discoveries at different scales\, regardless of the nature of the material and the forces holding it together. In this seminar\, we show how atomic and molecular crystal structures – made possible by chemical bonds – can be realized for nanoparticles and colloids via enthalpic and entropic bonds. We show how these bonds can be designed and engineered for self-assembly.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-assembly-engineering-of-patchy-particles-into-complex-structures-and-beyond/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220119T110000
DTEND;TZID=America/New_York:20220119T120000
DTSTAMP:20260406T091321
CREATED:20220110T152406Z
LAST-MODIFIED:20220110T152406Z
UID:10007001-1642590000-1642593600@seasevents.nmsdev7.com
SUMMARY:CEMB Future Leaders: "The place of plant chromatin in sensing mechanical stress"
DESCRIPTION:Launched in May 2021\, the Future Leaders in Mechanobiology is a monthly seminar series featuring up-and-coming leaders in mechanobiology–PhD students and postdocs from a wide range of fields\, backgrounds\, and institutions. By providing an international stage to share one’s work and opportunities to interact with researchers at all career stages\, we aim to create an inclusive and valuable series for early-stage researchers and the mechanobiology community as a whole. \nRegister HERE for access to the Zoom link and visit the CEMB website for more information.
URL:https://seasevents.nmsdev7.com/event/cemb-future-leaders-the-place-of-plant-chromatin-in-sensing-mechanical-stress/
LOCATION:https://upenn.zoom.us/j/96715197752
ORGANIZER;CN="Center for Engineering MechanoBiology (CEMB)":MAILTO:annjeong@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220119T153000
DTEND;TZID=America/New_York:20220119T163000
DTSTAMP:20260406T091321
CREATED:20220107T215630Z
LAST-MODIFIED:20220107T215630Z
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SUMMARY:CBE Seminar: "Tackling Disease-Associated Biomolecules: From RNA Therapeutics to Single-Molecule Detection"
DESCRIPTION:Abstract\nThe functionality versatility of polymeric and nucleic acid materials provides diverse engineering opportunities for the detection and therapeutic targeting of disease-associated biomolecules. My work has encompassed nanoscale and microscale technologies to address challenges in cancer therapeutics and diagnostics\, from targeting the expression of dysregulated genes to probing rare protein biomarkers. I will first describe the design of a highly potent small interfering RNA nanoparticle delivery system that leverages approaches in nucleic acid engineering and polymer chemistry. Towards overcoming analytical barriers in clinical diagnostics\, I will then describe the development of ultrasensitive single-molecule detection technologies to measure low abundance proteins. By utilizing powerful molecular amplification methods and simple signal readouts\, these digital enzyme-linked immunosorbent assay (ELISA) platforms enable the detection of low attomolar (10-18 M) protein concentrations\, with over four orders-of-magnitude improvements in sensitivity over conventional protein detection methods. Importantly\, these methods democratize ultrasensitive protein detection\, enabling high-throughput\, high-multiplex digital measurements to be carried out with common laboratory instrumentation. \nFinally\, I will highlight the application of digital ELISA technology towards the development of an ultrasensitive blood test for a retrotransposon-encoded protein as a highly specific multi-cancer biomarker. Overall\, the development of these technologies can pave the way towards the future integration of materials and biomolecular engineering approaches with ultrasensitive bioanalytical tools for accelerating biomarker signature discovery and precision medicine.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-tackling-disease-associated-biomolecules-from-rna-therapeutics-to-single-molecule-detection/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220120T100000
DTEND;TZID=America/New_York:20220120T120000
DTSTAMP:20260406T091321
CREATED:20220114T165505Z
LAST-MODIFIED:20220114T165505Z
UID:10007016-1642672800-1642680000@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense: "Statistical Learning for System Identification\, Prediction\, and Control"
DESCRIPTION:Despite the recent widespread success of machine learning\, we still do not fully understand its fundamental limitations. Going forward\, it is crucial to better understand learning complexity\, especially in critical decision making applications\, where a wrong decision can lead to catastrophic consequences. In this thesis\, we focus on the statistical complexity of learning unknown linear dynamical systems\, with focus on the tasks of system identification\, prediction\, and control. We are interested in sample complexity\, i.e. the minimum number of samples required to achieve satisfactory learning performance. Our goal is to provide finite-sample learning guarantees\, explicitly highlighting how the learning objective depends on the number of samples. A fundamental question we are trying to answer is how system theoretic properties of the underlying process can affect sample complexity. \nUsing recent advances in statistical learning\, high-dimensional statistics\, and mini-max theory\, we provide finite-sample guarantees in the following settings. i) System Identification. We provide the first finite-sample guarantees for identifying a stochastic partially-observed system; this problem is also known as the stochastic system identification problem. ii) Prediction. We provide the first end-to-end guarantees for learning the Kalman Filter\, i.e. for learning to predict\, in an offline learning architecture. We also provide the first logarithmic regret guarantees for the problem of learning the Kalman Filter in an online learning architecture\, where the data are revealed sequentially. iii) Difficulty of System Identification and Control. Focusing on fully-observed systems\, we investigate when learning linear systems is statistically easy or hard\, in the finite sample regime. Statistically easy to learn linear system classes have sample complexity that is polynomial with the system dimension. Statistically hard to learn linear system classes have worst-case sample complexity that is at least exponential with the system dimension. We show that there actually exist classes of linear systems which are hard to learn. Such classes include indirectly excited systems with a large degree of indirect excitation. Similar conclusions hold for both the problem of system identification and the problem of learning to control.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-statistical-learning-for-system-identification-prediction-and-control/
LOCATION:Zoom – Meeting ID 949 5950 4530
CATEGORIES:Seminar,Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220120T103000
DTEND;TZID=America/New_York:20220120T113000
DTSTAMP:20260406T091321
CREATED:20220107T165309Z
LAST-MODIFIED:20220107T165309Z
UID:10006999-1642674600-1642678200@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "How do tissues fracture and repair across length scales?"
DESCRIPTION:In structural materials engineering\, we often aim to create materials that are simultaneously strong\, tough and lightweight- a combination classically considered mutually exclusive. Biogenic composite materials such as bone exhibit a combination of these properties exceeding that of their constituents\, a feat generally credited to their hierarchal structure\, down to the nanoscale. In this talk\, we will demonstrate the use of micro and nanoscales site-specific microstructural characterization and mechanical experiments to probe the strength\, deformation\, and fracture of human bone. We will demonstrate an in situ SEM/nanoindentor methodology\, that enables 3-point bending fracture experiments with observation and measurement of crack growth and toughening behavior at nano and micrometer scales. We will discuss how expanding these nanoscale tissue experiments can enable future efforts in fundamental understanding of tissue regeneration. We will use generalized lessons learned about biogenic materials to discuss additive manufacturing of metals and explore how to leverage the unique tunability of nanoparticle functionalization and nanostructuring feedstock in metal additive manufacturing to expand the library of currently “printable” materials for potential applications ranging from biomedical to thermal.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-how-do-tissues-fracture-and-repair-across-length-scales/
LOCATION:https://upenn.zoom.us/j/96715197752
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220120T153000
DTEND;TZID=America/New_York:20220120T163000
DTSTAMP:20260406T091321
CREATED:20211210T164259Z
LAST-MODIFIED:20211210T164259Z
UID:10006994-1642692600-1642696200@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Engineering New Tools to Understand Airway Mucosal Barrier Function" (Gregg Duncan)
DESCRIPTION:This seminar will be held in person and on zoom (the link will be sent out via email). \nMucus is a biological gel within the lung designed to behave like an “escalator” with the ability to capture potentially harmful inhaled materials (e.g. pathogens\, particulates) and carry these materials via mucociliary clearance up to the throat to be swallowed and sterilized. MUC5B and MUC5AC are large\, gel-forming mucins that assemble to form airway mucus gels. In individuals with asthma\, biochemical analysis of mucus produced by cough revealed mucin composition is altered as a function of disease severity\, with a shift from MUC5B to MUC5AC as the predominant secreted mucin. However due to the lack of appropriate models\, it is not yet fully understood how imbalance in ratio of MUC5B to MUC5AC contributes to the biological function of mucus. Recently\, we have engineered a mucin-based biomaterial with native-like viscoelasticity\, here termed ‘synthetic mucus’. To understand mucus dysfunction in asthma\, we customized synthetic mucus to mimic the biochemical and biophysical properties of airway mucus in health and in asthma. In addition\, we characterized the rheological properties and transport function of mucus in differentiated human airway tissue cultures genetically engineered to secrete either MUC5B or MUC5AC. These bioengineered models provide new key insights on how MUC5B and MUC5AC work in concert to enable host mucosal barrier function providing a highly valuable means to understand their roles in health and disease.
URL:https://seasevents.nmsdev7.com/event/be-seminar-engineering-new-tools-to-understand-airway-mucosal-barrier-function-gregg-duncan/
LOCATION:Moore 216\, 200 S. 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
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