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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Azadeh Yazdan-Shahmorad Daniel B. Silversmith Philip N. Sabes University of California San Francisco San Francisco CA US UC Berkeley – UCSF Graduate Program in Bioengineering San Francisco CA 94158 USA

Optogenetics is a powerful tool that enables millisecond-level control of the activity of specific groups of neurons. Furthermore, it has the great advantage of artifact free recordings. These characteristics make this technique ideal for relating brain function to behavior in animals with great behavioral capabilities such as non-human primates (NHPs). We recently introduced a practical, stable interface for optogenetic stimulation and recording of large-scale cortical circuits in NHPs. Here we present the various potentials of this interface for studying circuits and connectivity at a large-scale and for relating it to behavior.

关键词： Frequency modulation Oscillators Time series analysis Couplings Electrical stimulation

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Deep learning-guided design of dynamic proteins

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Science (New York, N.Y.) 2025年第6749期388卷 eadr7094页

作者： Amy B Guo Deniz Akpinaroglu Christina A Stephens Michael Grabe Colin A Smith Mark J S Kelly Tanja Kortemme The UC Berkeley-UCSF Graduate Program in Bioengineering University of California San Francisco San Francisco CA USA. Department of Bioengineering and Therapeutic Sciences University of California San Francisco San Francisco CA USA. Department of Pharmaceutical Chemistry University of California San Francisco San Francisco CA USA. Cardiovascular Research Institute University of California San Francisco San Francisco CA USA. Department of Chemistry Wesleyan University Middletown CT USA. Quantitative Biosciences Institute University of California San Francisco San Francisco CA USA. Chan Zuckerberg Biohub San Francisco CA USA.

Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-guided approach for de novo design of dynamic changes between intradomain geometries of proteins, similar to switch mechanisms prevalent in nature, with atomic-level precision. We solve four structures that validate the designed conformations, demonstrate modulation of the conformational landscape by orthosteric ligands and allosteric mutations, and show that physics-based simulations are in agreement with deep-learning predictions and experimental data. Our approach demonstrates that new modes of motion can now be realized through de novo design and provides a framework for constructing biology-inspired, tunable, and controllable protein signaling behavior de novo.

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Open-top selective plane illumination microscope compatible with standard sample holders

Open-top selective plane illumination microscope compatible ...

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Novel Techniques in Microscopy, NTM 2015

作者： McGorty, Ryan Liu, Harrison Kamiyama, Daichi Huang, Bo Deparment of Pharmaceutical Chemistry University of California San Francisco San FranciscoCA94158 United States UC Berkeley - UCSF Graduate Program in Bioengineering University of California San Francisco San FranciscoCA94158 United States Department of Biochemistry and Biophysics University of California San Francisco San FranciscoCA94158 United States

Selective plane illumination microscopy (SPIM) has emerged recently as a powerful tool in optically sectioning tissue samples. We have designed a new SPIM that allows samples to be mounted in a variety of common metho... 详细信息

ISBN: (纸本)9781557529541

关键词： Aberration correction Cylindrical lenses Laser beams Light sheet microscopy Selective plane illumination microscopy Spatial resolution

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Fourier diffuserscope: Single-shot 3d fourier light field microscopy with a diffuser

arXiv

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arXiv 2020年

作者： Liu, Fanglin Linda Grace, K.U.O. Antipa, Nick Yanny, Kyrollos Waller, Laura Electrical Engineering and Computer Sciences University of California Berkeley94709 United States UCB/UCSF Joint Graduate Program in Bioengineering University of California BerkeleyCA94709 United States

Light field microscopy (LFM) uses a microlens array (MLA) near the sensor plane of a microscope to achieve single-shot 3D imaging of a sample, without any moving parts. Unfortunately, the 3D capability of LFM comes with a significant loss of lateral resolution at the focal plane, which is highly undesirable in microscopy. Placing the MLA near the pupil plane of the microscope, rather than the image plane, can mitigate the artifacts near focus and provide an efficient shift-invariant model at the expense of field-of-view. Here, we show that our Fourier DiffuserScope achieves significantly better performance than Fourier LFM. Fourier DiffuserScope uses a diffuser in the pupil plane to encode depth information, then reconstructs volumetric information computationally by solving a sparsity-constrained inverse problem. Our diffuser consists of randomly placed microlenses with varying focal lengths. We show that by randomizing the microlens positions, a larger lateral field-of-view can be achieved compared to a conventional MLA;furthermore, by adding diversity to the focal lengths, the axial depth range is increased. To predict system performance based on diffuser parameters, we for the first time establish a theoretical framework as a design guideline, followed by numerical simulations to verify. Under both theoretical and numerical analysis, we demonstrate that our diffuser design provides more uniform resolution over a larger volume, both laterally and axially, outperforming the MLA used in LFM. We build an experiment system with an optimized lens set and achieve 3 volume. Copyright © 2020, The Authors. All rights reserved.

关键词： Microlenses

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Nature Versus Nurture: Developing Enzymes That Function Under Extreme Conditions

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Chemical and Biomolecular Engineering 1000年第1期3卷 77-102页

作者： Michael J. Liszka Melinda E. Clark Elizabeth Schneider Douglas S. Clark 1Department of Chemical and Biomolecular Engineering 2Energy Biosciences Institute 3UC Berkeley and UCSF Graduate Program in Bioengineering University of California Berkeley California 94720 email: mliszka@berkeley.edu melinda_clark@berkeley.edu ebeth@berkeley.edu clark@berkeley.edu

Many industrial processes used to produce chemicals and pharmaceuticals would benefit from enzymes that function under extreme conditions. Enzymes from extremophilic microorganisms have evolved to function in a variety of extreme environments, and bioprospecting for these microorganisms has led to the discovery of new enzymes with high tolerance to nonnatural conditions. However, bioprospecting is inherently limited by the diversity of enzymes evolved by nature. Protein engineering has also been successful in generating extremophilic enzymes by both rational mutagenesis and directed evolution, but screening for activity under extreme conditions can be difficult. This review examines the emerging synergy between bioprospecting and protein engineering in developing extremophilic enzymes. Specific topics include unnatural industrial conditions relevant to biocatalysis, biophysical properties of extremophilic enzymes, and industrially relevant extremophilic enzymes found either in nature or through protein engineering.

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Scan-specific Self-supervised Bayesian Deep Non-linear Inversion for Undersampled MRI Reconstruction

arXiv

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arXiv 2022年

作者： Leynes, Andrew P. Deveshwar, Nikhil Nagarajan, Srikantan S. Larson, Peder E.Z. The Department of Radiology and Biomedical Imaging University of California San Francisco San FranciscoCA94158 United States The UC Berkeley UC San Francisco Joint Graduate Program in Bioengineering Berkeley San FranciscoCA United States

Magnetic resonance imaging is subject to slow acquisition times due to the inherent limitations in data sampling. Recently, supervised deep learning has emerged as a promising technique for reconstructing sub-sampled MRI. However, supervised deep learning requires a large dataset of fully-sampled data. Although unsupervised or self-supervised deep learning methods have emerged to address the limitations of supervised deep learning approaches, they still require a database of images. In contrast, scan-specific deep learning methods learn and reconstruct using only the sub-sampled data from a single scan. Here, we introduce Scan-Specific Self-Supervised Bayesian Deep Non-Linear Inversion (DNLINV) that does not require an auto calibration scan region. DNLINV utilizes a Deep Image Prior-type generative modeling approach and relies on approximate Bayesian inference to regularize the deep convolutional neural network. We demonstrate our approach on several anatomies, contrasts, and sampling patterns and show improved performance over existing approaches in scan-specific calibrationless parallel imaging and compressed sensing. © 2022, CC BY.

关键词： Magnetic resonance imaging

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Calibrationless parallel imaging reconstruction based on structured low-rank matrix completion

Calibrationless parallel imaging reconstruction based on str...

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作者： Shin, Peter J. Larson, Peder E. Z. Ohliger, Michael A. Elad, Michael Pauly, John M. Vigneron, Daniel B. Lustig, Michael Department of Radiology and Biomedical Imaging University of California at San Francisco San FranciscoCA United States UC Berkeley-UCSF Graduate Program in Bioengineering CA United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA United States Department of Computer Science Technion'Israel Institute of Technology Haifa Israel Magnetic Resonance Systems Research Laboratory Department of Electrical Engineering Stanford University StanfordCA United States

Purpose: A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k-space estimation (SAKE), is presented. It is a data-driven, coil-by-coil reconstruction method that does not require a separate calibration step for estimating coil sensitivity information. Methods: In SAKE, an undersampled, multichannel dataset is structured into a single data matrix. The reconstruction is then formulated as a structured low-rank matrix completion problem. An iterative solution that implements a projection-ontosets algorithm with singular value thresholding is described. Results: Reconstruction results are demonstrated for retrospectively and prospectively undersampled, multichannel Cartesian data having no calibration signals. Additionally, non-Cartesian data reconstruction is presented. Finally, improved image quality is demonstrated by combining SAKE with wavelet-based compressed sensing. Conclusion: Because estimation of coil sensitivity information is not needed, the proposed method could potentially benefit MR applications where acquiring accurate calibration data is limiting or not possible at all. © 2013 Wiley Periodicals, Inc.

关键词： Compressed sensing

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Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array

arXiv

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arXiv 2020年

作者： Monakhova, Kristina Yanny, Kyrollos Aggarwal, Neerja Waller, Laura Department of Electrical Engineering & Computer Sciences University of California BerkeleyCA94720 United States UCB/UCSF Joint Graduate Program in Bioengineering University of California BerkeleyCA94720 United States

Hyperspectral imaging is useful for applications ranging from medical diagnostics to crop monitoring;however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot techniques exist but are often confined to bulky bench-top setups or have low spatio-spectral resolution. In this paper, we propose a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging. Our system consists of a repeated spectral filter array placed directly on the image sensor and a diffuser placed close to the sensor. Each point in the world maps to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. A sparsity-constrained inverse problem solver then recovers the hyperspectral volume with good spatio-spectral resolution. By using a spectral filter array, our hyperspectral imaging framework is flexible and can be designed with contiguous or non-contiguous spectral filters that can be chosen for a given application. We provide theory for system design, demonstrate a prototype device, and present experimental results with high spatio-spectral resolution. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Copyright © 2020, The Authors. All rights reserved.

关键词： Spectroscopy

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Hybrid dedicated and distributed coding in PMd/M1 provides separation and interaction of bilateral arm signals

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PLoS Computational Biology 2021年第11期17卷 e1009615-e1009615页

作者： Dixon, Tanner C. Merrick, Christina M. Wallis, Joni D. Ivry, Richard B. Carmena, Jose M. UC Berkeley-UCSF Graduate Program in Bioengineering University of California-Berkeley BerkeleyCA United States Department of Psychology University of California-Berkeley BerkeleyCA United States Helen Wills Neuroscience Institute University of California-Berkeley BerkeleyCA United States Department of Electrical Engineering and Computer Sciences University of California-Berkeley BerkeleyCA United States

Pronounced activity is observed in both hemispheres of the motor cortex during preparation and execution of unimanual movements. The organizational principles of bi-hemispheric signals and the functions they serve throughout motor planning remain unclear. Using an instructed-delay reaching task in monkeys, we identified two components in population responses spanning PMd and M1. A "dedicated"component, which segregated activity at the level of individual units, emerged in PMd during preparation. It was most prominent following movement when M1 became strongly engaged, and principally involved the contralateral hemisphere. In contrast to recent reports, these dedicated signals solely accounted for divergence of arm-specific neural subspaces. The other "distributed"component mixed signals for each arm within units, and the subspace containing it did not discriminate between arms at any stage. The statistics of the population response suggest two functional aspects of the cortical network: One that spans both hemispheres for supporting preparatory and ongoing processes, and another that is predominantly housed in the contralateral hemisphere and specifies unilateral output. © 2021 Dixon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Population statistics

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Performance evaluation and comparison of two triple-nuclear RF resonators for 1H/19F/31PMR imaging at 9.4T

Performance evaluation and comparison of two triple-nuclear ...

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2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019

作者： Du, Feng Liu, Shengping Li, Nan Liu, Congcong Chen, Qiaoyan Zhang, Shuai Wang, Haifeng Zhang, Xiaoliang Li, Ye Research Center for Biomedical Imaging Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guang Dong China Chongqing University of Technology Department of Biomedical Engineering Chongqing China Department of Radiology and Biomedical Imaging University of California San Francisco San FranciscoCA94158 United States UCSF/UC Berkeley Joint Graduate Group in Bioengineering San FranciscoCA94158 United States

ISBN: (纸本)9781728137261

Radio frequency (RF) coils are critical devices in magnetic resonance (MR) systems for transmitting and receiving magnetic resonance signals. However, the required high operating frequency at ultrahigh magnetic fields makes the design of highly efficient radio frequency (RF) transmit or receive coils technically challenging. This is particularly true in the double-tuned or triple-tuned RF coils usually required in heteronuclear MRI and MRS where multiple nuclei, such as 1H, 19F, and 31P, are involved. The performance of RF coils is a critically important factor for realizing the high sensitivity provided by ultrahigh magnetic fields to contribute towards the advancement of a novel human in vivo application at 9.4T. In this work, two different configurations of novel triple-nuclear (1H/19F/31P) RF resonators were proposed for the ultrahigh field 9.4T applications. We also reported on the design and construction, and a field-circuit co-simulation was used to obtain the S-parameters, B1+ field and specific absorption rate (SAR) distributions to evaluate and compare their performance. And the characteristics and advantages of the proposed two different configurations of triple-nuclear RF resonators in the applications of 1H/19F/31P at ultrahigh magnetic field were investigated. © 2019 IEEE.

关键词： Magnetic resonance

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