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Multi-physics modeling and finite-element formulation of neuronal dendrite growth with electrical polarization

Brain Multiphysics 2023年 4卷

作者： Wang, Shuolun Wang, Xincheng Holland, Maria A. Department of Aerospace and Mechanical Engineering University of Notre Dame Notre Dame 46556 IN United States Bioengineering Graduate Program University of Notre Dame Notre Dame 46556 IN United States

The neuron serves as the basic computational unit for the brain. Altered neuronal morphologies are usually found in various neurological diseases, such as Down syndrome, Williams syndrome, and idiopathic autism. Compelling biological evidence demonstrates that neuronal morphology can be dynamically regulated by neuronal activity through the mediation of calcium signaling pathways. Moreover, studies have revealed that exposure to an applied electric field can induce directional migration of neurites toward the cathode. In this study, we developed a coupled system that combines an advective Gray–Scott model with Gauss's law to gain a better understanding of dendrite growth and response to electrical polarization. Our simulation results successfully capture key features such as dendrite branching, space-filling, self-avoidance, and electrical polarization. With the help of the convolutional neural network, we inversely identified model parameters of real dendrite morphologies from an online open source. Finally, we calibrated our model using experimental data on growing neurons under applied electric fields. © 2023

关键词： Convolutional neural network Finite element modeling Neuronal dendrites Turing patterns

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Resistive-pulse sensing tumor-derived exosome detection device for resrouce-limited settings 21

Resistive-pulse sensing tumor-derived exosome detection devi...

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21st International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2017

作者： Carey, Thomas R. Yu, Connie W. Sohn, Lydia L. UC Berkeley-UCSF Graduate Program in Bioengineering United States UC Berkeley Bioengineering United States UC Berkeley Mechanical Engineering United States

ISBN: (纸本)9780692941836

We present the theory, design, and initial characterization of a tumor-derived exosome detection platform based on resistive-pulse sensing to enable cost-effective, point-of-care cancer screening. Our platform detects exosomes displaying a specific surface antigen by electronically measuring the effective size increase that occurs when exosomes bind to colloids functionalized with a specific antibody. We have demonstrated that our device can distinguish antibody-functionalized colloids from similar colloids incubated with SKBR3-derived exosomes. © 17CBMS-0001.

关键词： Colloids

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Fast non-iterative algorithm for 3D point-cloud holography

arXiv

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arXiv 2023年

作者： Ersaro, Nathan Tessema Yalcin, Cem Murray, Liz Kabuli, Leyla Waller, Laura Muller, Rikky Graduate Program in Bioengineering University of California Berkeley University of California San Francisco BerkeleyCA94720 United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States

Recently developed iterative and deep learning-based approaches to computer-generated holography (CGH) have been shown to achieve high-quality photorealistic 3D images with spatial light modulators. However, such approaches remain overly cumbersome for patterning sparse collections of target points across a photoresponsive volume in applications including biological microscopy and material processing. Specifically, in addition to requiring heavy computation that cannot accommodate real-time operation in mobile or hardware-light settings, existing sampling-dependent 3D CGH methods preclude the ability to place target points with arbitrary precision, limiting accessible depths to a handful of planes. Accordingly, we present a non-iterative point cloud holography algorithm that employs fast deterministic calculations in order to efficiently allocate patches of SLM pixels to different target points in the 3D volume and spread the patterning of all points across multiple time frames. Compared to a matched-performance implementation of the iterative Gerchberg-Saxton algorithm, our algorithm's relative computation speed advantage was found to increase with SLM pixel count, reaching >100,000x at 512x512 array format. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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MULTIPLEXED DNA-DIRECTED PATTERNING OF ANTIBODIES FOR SINGLE-CELL SURFACE MARKER ANALYSIS 25

MULTIPLEXED DNA-DIRECTED PATTERNING OF ANTIBODIES FOR SINGLE...

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25th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2021

作者： Kozminsky, Molly Scheideler, Olivia J. Li, Brian Liu, Nathaniel K. Sohn, Lydia L. California Institute of Quantitative Biosciences Berkeley United States UC Berkeley-UCSF Graduate Program in Bioengineering Berkeley and San Francisco United States UC Berkeley Department of Mechanical Engineering Berkeley United States

ISBN: (纸本)9781733419031

Cell surface marker expression is a ubiquitously measured property of single-cell phenotypes. However, measuring several markers with exogenous labels can be costly and complex. We applied a novel bioconjugation chemistry known as DNA-directed patterning to functionalize glass substrates with great specificity and flexibility. Combined with a newly-designed node-pore sensing device, we have developed a flexible and label-free platform for multiplexed surface-marker screening of single cells. In this work, we present our design and demonstrate our platform's capability to screen two example cell types for surface-marker expression. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： DNA

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GranatumX:A Community-engaging, Modularized, and Flexible Webtool for Single-cell Data Analysis

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Genomics, Proteomics & Bioinformatics 2021年第3期19卷 452-460页

作者： David G.Garmire Xun Zhu Aravind Mantravadi Qianhui Huang Breck Yunits Yu Liu Thomas Wolfgruber Olivier Poirion Tianying Zhao Cédric Arisdakessian Stefan Stanojevic Lana X.Garmire Department of Electrical Engineering&Computer Science University of MichiganAnn ArborMI 48109USA Epidemiology Program University of Hawaii Cancer CenterHonoluluHI 96813USA Department of Biostatistics University of MichiganAnn ArborMI 48109USA Department of Computational Medicine and Bioinformatics University of MichiganAnn ArborMI 48105USA Molecular Biosciences and Bioengineering Graduate Program University of Hawaii at ManoaHonoluluHI 96822USA

We present GranatumX,a next-generation software environment for single-cell RNA sequencing(scRNA-seq)data *** is inspired by the interactive webtool *** enables biologists to access the latest scRNA-seq bioinformatics methods in a web-based graphical *** also offers software developers the opportunity to rapidly promote their own tools with others in customizable *** architecture of GranatumX allows for easy inclusion of plugin modules,named Gboxes,which wrap around bioinformatics tools written in various programming languages and on various *** can be run on the cloud or private servers and generate reproducible *** is a community-engaging,flexible,and evolving software ecosystem for scRNA-seq analysis,connecting developers with bench *** is freely accessible at http://***/granatumx/app.

关键词： Single-cell RNA sequencing Analysis Pipeline Webtool Module

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LoraMap: Harnessing the Power of LoRA Connections

arXiv

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arXiv 2024年

作者： Park, Hyeryun Kwak, Jeongwon Jang, Dongsuk Park, Sumin Choi, Jinwook Interdisciplinary Program for Bioengineering Graduate School Seoul National University Korea Republic of Integrated Major in Innovative Medical Science Graduate School Seoul National University Korea Republic of Department of Biomedical Engineering College of Medicine Seoul National University Korea Republic of Medical Research Center Institute of Medical and Biological Engineering Seoul National University Korea Republic of

Fact-checking techniques can mitigate hallucinations in Large Language Models (LLMs), a prominent issue in specialized domains. As parameter-efficient techniques such as Low-Rank Adaptation (LoRA) can overcome substantial computational overhead, some studies have explored the integration of multiple LoRAs. While previous studies focus on parallel integration, this paper investigates methods to establish connections among multiple LoRAs. We create three reasoning datasets tailored to fact-checking and fine-tune individual LoRAs, allowing them to view and reason from diverse perspectives. Then, we explore strategies for allocating these reasoning LoRAs and introduce LoraMap, an approach to map connections between them. The results of the fact-checking task demonstrate that the performance of LoraMap is superior to LoraHub, an existing method for integrating LoRAs. LoraMap also outperforms with significantly fewer trainable parameters than LoraConcat, which concatenates LoRAs and further fine-tunes them. Copyright © 2024, The Authors. All rights reserved.

关键词： Problem oriented languages

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Comparative assessment of alveolar bone loss in experimental periodontitis: a 2D and 3D microtomographic study in a rat model

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Periodontal and Implant Research 2024年第1期8卷 1-14页

作者： Fernandes, P. G. da Silva, A. M. H. Stocco, T. D. Magalhães, D. S. F. Vanderlei, J. M. T. M. M. de Almeida, A. L. G. Oliveira, F. A Taba, M. Department of Oral Surgery and Periodontology University of São Paulo Ribeirão Preto School of Dentistry Ribeirão Preto Brazil Dentistry Department UNORTE- University Center of Northern São Paulo São José do Rio Preto Brazil Bioengineering Graduate Program Scientific and Technological Institute Brazil University São Paulo Brazil

Periodontitis is a chronic inflammatory condition characterized by soft and hard tissue breakdown due to attachment and alveolar bone loss. The objective of this investigation was to quantify the alveolar bone loss and recovery in a rat model subjected to ligature-induced periodontitis (PD) using both two-dimensional (2D) and three-dimensional (3D) microtomographic examinations. A cohort of 40 rats was distributed into control (C) and PD groups. Bone loss assessments were undertaken on the 10th day post-ligature insertion for bone loss and again 11 days after ligature extraction on the 21st day for bone recovery. In the 2D analysis, bone loss was evaluated in furcation regions, interproximal areas, and buccal and lingual aspects and for the 3D, the region of interest were the interproximal and furcation areas. Except for the CEJ-Lingual region, a disparity was observed between the C and PD groups on the 10th and 21st days (p < 0.05). In 3D evaluations “bone volume” (BV) and “bone volume to total volume ratio” (BV/TV) were measured. Both parameters demonstrated disease progression and bone recovery with detectable variations on the 10th and 21st days (p < 0.05). The outcomes confirm microtomographic examinations as a robust technique for bone change monitoring. Notably, the linear and volumetric measurements obtained from the same sample showed different perspectives of bone loss percentages. The selection of the anatomical area of interest and the analytical technique wield potential influence on results and must be considered based on their importance in studies targeting bone loss or bone recovery evaluations.

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DROPLET DIGITAL IMMUNO-PCR FOR PROFILING PROTEIN-SPECIFIC EXTRACELLULAR VESICLES 26

DROPLET DIGITAL IMMUNO-PCR FOR PROFILING PROTEIN-SPECIFIC EX...

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Lix, Chxnchen Lin, Hxixian Yao, Shxhxai Department of Laboratory Medicine Nanfang Hospital Southern Medical University Guangzhou China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Bioengineering Graduate Program Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781733419048

We construct a versatile droplet digital immuno-PCR ddiPCR assay which integrates immuno-PCR and droplet digital PCR ddPCR for quantifying protein-specific extracellular vesicle EV subpopulations at the single-vesicle level. We applied the ddiPCR assays for profiling the EV proteins of CD/CD63/CD81, HER2, EpCAM in a breast cancer cohort. The results demonstrated that the counting of multi-subpopulation EVs could significantly distinguish patients with breast tumor at different stages or hepatocellular carcinoma from healthy controls. This study provides a promising strategy to count multi-subpopulation EVs at the single-vesicle level for cancer diagnosis. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Drops

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Customizable Automated High Content Image Acquisition and Analysis for Tissue Biopsies

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Microscopy Today 2022年第2期30卷 30-38页

作者： Neal, Christopher A Hodge, Jacob G Zamierowski, David S Mellott, Adam J KIDDRC Imaging Core Facility University of Kansas Medical Center Kansas City KS Bioengineering Graduate Program University of Kansas Lawrence KS Department of Plastic Surgery University of Kansas Medical Center Kansas City KS

Advancements in high content image analysis have led to an increase in the adoption of these techniques in basic science and clinical research. High-throughput approaches to imaging and image analysis require minimal user interventions, circumventing the often prohibitively time-consuming and unreliable standard manual analysis. In this study, we demonstrate how high content imaging (HCI) techniques, in combination with high content analysis (HCA), can be paired with more traditional manual analysis to quantify both micro- and macro-level features of biopsied tissue sections. High-resolution, full-color images of stained tissue were acquired and stitched together to reconstruct the entire tissue section, which enabled analyses that required accurate identification of a given region's location within the tissue section. A custom region of interest grid was generated that followed the curvature of the tissue. The composite images were used in two separate analyses: tissue layer thickness as a macro-level approach, and nuclei density as a micro-level approach. Ultimately, the flexibility of the HCI and HCA methodologies used in this study allowed for complex analysis of tissue that would not have been otherwise feasible.

关键词： high content analysis analytical imaging automated analysis microscopy tissue microanalysis

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Generation of multi-tracer PET attenuation maps using zero-shot learning

Generation of multi-tracer PET attenuation maps using zero-s...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： M. J. Cho H. S. Shim J. S. Lee Interdisciplinary Program of Bioengineering Seoul National University Seoul Republic of Korea Graduate School Integrated Major in Innovative Medical Science Seoul National University Seoul Republic of Korea Department of Nuclear Medicine Seoul National University Seoul Republic of Korea

Attenuation correction is crucial for achieving high accuracy in PET images. Unfortunately, attenuation correction cannot be performed on PET images when transmission or CT data is unavailable. In such cases, an attenuation map is obtained by utilizing additional anatomical or morphological images. In previous studies, specific models for each tracer in PET images were trained to generate attenuation maps. However, this approach is associated with two major limitations. First, computational resources are greatly increased as each tracer requires a separate network for training. Second, PET images with less commonly used tracers usually have a shortage of data, making it challenging to train a network. To address these limitations, we propose a zero-shot learning method for generating CT-derived attenuation maps (µ-CT) from MLAA-derived attenuation maps (µ-MLAA) using only 18 F-FDG images. Unlike tracer-specific methods which require a separate network for each tracer, this method utilizes a single generator network that encodes the structural features of the input image and the style of the reference µCT to generate the attenuation map. We evaluated our method using clinical brain PET/CT scan datasets of three different tracers, which are 18 F-FDG, 18 F-Florbetaben, and 18 F-FP-CIT. The proposed method which was exclusively trained on 18 F-FDG performs better than tracer-specific networks trained on the same tracer across all evaluation metrics. Moreover, the proposed method generates predictions for the tracers 18 F-Florbetaben and 18 F-FP-CIT, which were not included in the training data, that are either highly comparable or not significantly different from those produced by the tracer-specific networks trained on the corresponding tracer data. The results demonstrate the effectiveness of our zero-shot learning approach in generating multi-tracer PET attenuation maps with only 18 F-FDG.

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