Pub Date : 2024-09-08DOI: 10.1101/2024.09.06.611628
Madeline Fuchs, Dillon T Seroski, Bethsymarie Soto Morales, Lucas Melgar, Giannia Scibilio, Abigail Ziegler, Renjie Liu, Benjamin G Keselowsky, Gregory A Hudalla
Enzyme therapeutics are often compromised by poor accumulation within target tissues, necessitating high doses that can exacerbate off-target effects. We report an injectable supramolecular enzyme-peptide gel platform for prolonged local enzyme retention in vivo. The gel is based on CATCH(+/-) (Co-Assembling Tags based on CHarge-complementarity), cationic and anionic peptide pairs that form β-sheet fibrils upon mixing. Enzymes recombinantly fused to CATCH(-) peptide integrate into CATCH(+/-) β-sheet fibrils during assembly, resulting in an enzyme-peptide gel. Catalytically-active gels were fabricated with four disparate enzymes: CATCH(-)-NanoLuc luciferase, CATCH(-)-cutinase, CATCH(-)-uricase, and CATCH(-)-adenosine synthase A. CATCH(-)-cutinase gels demonstrated tunability of the platform, while CATCH(-)-NanoLuc gels demonstrated prolonged tissue retention relative to soluble enzyme. CATCH(-)-uricase gels resolved localized inflammation in a gout model, while CATCH(-)-adenosine synthase A gels suppressed localized lipopolysaccharide-induced inflammation. Modular and tunable enzyme content, coupled with prolonged tissue retention, establish CATCH enzyme-peptide gels as a generalizable vehicle for effective local therapeutic biocatalysis.
酶疗法往往因在靶组织内蓄积不良而受到影响，必须使用大剂量，否则会加剧脱靶效应。我们报告了一种可注射的超分子酶肽凝胶平台，用于延长体内局部酶的保留时间。这种凝胶基于 CATCH(+/-)（Co-Assembling Tags based on CHarge-complementarity），阳离子和阴离子肽对在混合后形成 β 片状纤维。与 CATCH(-) 肽重组融合的酶在组装过程中整合到 CATCH(+/-) β 片纤维中，形成酶肽凝胶。用四种不同的酶制造了具有催化活性的凝胶：CATCH(-)-cutinase 凝胶展示了平台的可调性，而 CATCH(-)-NanoLuc 凝胶则展示了与可溶性酶相比更长的组织保留时间。CATCH（-）-尿酸酶凝胶解决了痛风模型中的局部炎症，而CATCH（-）-腺苷合成酶A凝胶抑制了脂多糖诱导的局部炎症。模块化和可调整的酶含量，加上长时间的组织保留，使 CATCH 酶肽凝胶成为一种可用于有效局部治疗生物催化的通用载体。
{"title":"Supramolecular Enzyme-Peptide Gels for Localized Therapeutic Biocatalysis","authors":"Madeline Fuchs, Dillon T Seroski, Bethsymarie Soto Morales, Lucas Melgar, Giannia Scibilio, Abigail Ziegler, Renjie Liu, Benjamin G Keselowsky, Gregory A Hudalla","doi":"10.1101/2024.09.06.611628","DOIUrl":"https://doi.org/10.1101/2024.09.06.611628","url":null,"abstract":"Enzyme therapeutics are often compromised by poor accumulation within target tissues, necessitating high doses that can exacerbate off-target effects. We report an injectable supramolecular enzyme-peptide gel platform for prolonged local enzyme retention in vivo. The gel is based on CATCH(+/-) (Co-Assembling Tags based on CHarge-complementarity), cationic and anionic peptide pairs that form β-sheet fibrils upon mixing. Enzymes recombinantly fused to CATCH(-) peptide integrate into CATCH(+/-) β-sheet fibrils during assembly, resulting in an enzyme-peptide gel. Catalytically-active gels were fabricated with four disparate enzymes: CATCH(-)-NanoLuc luciferase, CATCH(-)-cutinase, CATCH(-)-uricase, and CATCH(-)-adenosine synthase A. CATCH(-)-cutinase gels demonstrated tunability of the platform, while CATCH(-)-NanoLuc gels demonstrated prolonged tissue retention relative to soluble enzyme. CATCH(-)-uricase gels resolved localized inflammation in a gout model, while CATCH(-)-adenosine synthase A gels suppressed localized lipopolysaccharide-induced inflammation. Modular and tunable enzyme content, coupled with prolonged tissue retention, establish CATCH enzyme-peptide gels as a generalizable vehicle for effective local therapeutic biocatalysis.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.04.611159
Zhou Zhou, Xiaogai Li, Svein Kleiven
Finite element (FE) models of the human head are important injury assessment tools but developing a high-quality, hexahedral-meshed FE head model without compromising geometric accuracy is a challenging task. Important brain features, such as the cortical folds and ventricles, were captured only in a handful of FE head models that were primarily developed from two meshing techniques, i.e., surface-based meshing with conforming elements to capture the interfacial boundaries and voxel-based meshing by converting the segmented voxels into elements with and without meshing smoothing. Despite these advancements, little knowledge existed of how similar the strain responses were between surface- and voxel-based FE head models. To address this, a previously developed surface-based head model with conforming meshes to capture the cortical folds-subarachnoid cerebrospinal fluid and brain-ventricle interfaces was reused, and two voxel-based models with and without mesh smoothing were newly created here. These three models were employed to simulate head impacts. The results showed remarkable similarities in the strain responses between the surface- and the voxel-based models. When calculating commonly used injury metrics, including the percentile strains below the maximum (e.g., 95 percentile strain) and the volume of brain element with the strain over certain thresholds, the responses of the three models were virtually identical. When examining the strain distribution, the three models showed different patterns at the interfacial boundary (e.g., sulci and gyri in the cortex, regions adjacent to the falx and tentorium) with strain differences exceeding 0.1. The mesh smoothing procedure in the voxel-based models marginally reduced the strain discrepancies compared to the surface-based model. This study yielded new quantitative insights into the general similarity in the strain responses between the surface- and voxel-based FE head models and underscored that caution should be exercised when using the strain at the interface to predict injury.
人体头部有限元（FE）模型是重要的损伤评估工具，但在不影响几何精度的前提下开发高质量的六面体网格 FE 头部模型是一项具有挑战性的任务。重要的大脑特征，如皮质褶皱和脑室，只能在少数几个头部有限元模型中捕捉到，这些模型主要由两种网格划分技术开发而成，即基于曲面的网格划分技术和基于体素的网格划分技术，前者使用保形元素捕捉界面边界，后者通过将分割的体素转换为元素并进行或不进行网格平滑处理。尽管取得了这些进步，但人们对基于曲面和基于体素的 FE 头部模型之间应变响应的相似性知之甚少。为了解决这个问题，我们重新使用了之前开发的基于表面的头部模型，该模型采用了符合网格来捕捉皮质褶皱-蛛网膜下腔脑脊液和脑-脑室界面。这三个模型用于模拟头部撞击。结果显示，表面模型和基于体素的模型的应变反应非常相似。在计算常用的损伤指标时，包括低于最大值的百分位应变（如 95 百分位应变）和应变超过特定阈值的脑元素体积，这三种模型的响应几乎完全相同。在研究应变分布时，三个模型在界面边界（如皮层的沟和回旋、邻近动眼神经和触角的区域）显示出不同的模式，应变差异超过 0.1。与基于表面的模型相比，基于体素的模型中的网格平滑程序略微减少了应变差异。这项研究对基于表面和基于体素的 FE 头部模型之间应变反应的普遍相似性提出了新的定量见解，并强调在使用界面应变预测损伤时应谨慎行事。
{"title":"Surface-Based vs. Voxel-Based Finite Element Head Models: Comparative Analyses of Strain Responses","authors":"Zhou Zhou, Xiaogai Li, Svein Kleiven","doi":"10.1101/2024.09.04.611159","DOIUrl":"https://doi.org/10.1101/2024.09.04.611159","url":null,"abstract":"Finite element (FE) models of the human head are important injury assessment tools but developing a high-quality, hexahedral-meshed FE head model without compromising geometric accuracy is a challenging task. Important brain features, such as the cortical folds and ventricles, were captured only in a handful of FE head models that were primarily developed from two meshing techniques, i.e., surface-based meshing with conforming elements to capture the interfacial boundaries and voxel-based meshing by converting the segmented voxels into elements with and without meshing smoothing. Despite these advancements, little knowledge existed of how similar the strain responses were between surface- and voxel-based FE head models. To address this, a previously developed surface-based head model with conforming meshes to capture the cortical folds-subarachnoid cerebrospinal fluid and brain-ventricle interfaces was reused, and two voxel-based models with and without mesh smoothing were newly created here. These three models were employed to simulate head impacts. The results showed remarkable similarities in the strain responses between the surface- and the voxel-based models. When calculating commonly used injury metrics, including the percentile strains below the maximum (e.g., 95 percentile strain) and the volume of brain element with the strain over certain thresholds, the responses of the three models were virtually identical. When examining the strain distribution, the three models showed different patterns at the interfacial boundary (e.g., sulci and gyri in the cortex, regions adjacent to the falx and tentorium) with strain differences exceeding 0.1. The mesh smoothing procedure in the voxel-based models marginally reduced the strain discrepancies compared to the surface-based model. This study yielded new quantitative insights into the general similarity in the strain responses between the surface- and voxel-based FE head models and underscored that caution should be exercised when using the strain at the interface to predict injury.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.04.611131
Jaemyung Shin, Minseok Kang, Kinam Hyun, Zhangkang Li, Hitendra Kumar, Kangsoo Kim, Simon S. Park, Keekyoung Kim
Controlled volume microliter cell-laden droplet bioprinting is important for precise biologics deposition, reliably replicating 3D microtissue environments for building cell aggregates or organoids. To achieve this, we propose an innovative machine-learning approach to predict cell-laden droplet volumes according to input parameters. We developed a novel bioprinting platform capable of collecting high-throughput droplet images and generating an extensive dataset for training machine learning and deep learning algorithms. Our research compared the performance of three machine learning and two deep learning algorithms that predict droplet volume based on numerous bioprinting parameters. By adjusting bioink viscosity, nozzle size, printing time, printing pressure, and cell concentration as input parameters, we precisely could control droplet sizes, ranging from 0.1 to 50 microliter in volume. We utilized a hydrogel precursor composed of 5% gelatin methacrylate and a mixture of 0.5% and 1% alginate, respectively. Additionally, we optimized the cell bioprinting process using green fluorescent protein-tagged 3T3 fibroblast cells. These models demonstrated superior predictive accuracy and revealed the interrelationships among parameters while taking minimal time for training and testing. This method promises to advance the mass production of organoids and microtissues with precise volume control for various biomedical applications.
{"title":"Machine Learning Driven Optimization for High Precision Cellular Droplet Bioprinting","authors":"Jaemyung Shin, Minseok Kang, Kinam Hyun, Zhangkang Li, Hitendra Kumar, Kangsoo Kim, Simon S. Park, Keekyoung Kim","doi":"10.1101/2024.09.04.611131","DOIUrl":"https://doi.org/10.1101/2024.09.04.611131","url":null,"abstract":"Controlled volume microliter cell-laden droplet bioprinting is important for precise biologics deposition, reliably replicating 3D microtissue environments for building cell aggregates or organoids. To achieve this, we propose an innovative machine-learning approach to predict cell-laden droplet volumes according to input parameters. We developed a novel bioprinting platform capable of collecting high-throughput droplet images and generating an extensive dataset for training machine learning and deep learning algorithms. Our research compared the performance of three machine learning and two deep learning algorithms that predict droplet volume based on numerous bioprinting parameters. By adjusting bioink viscosity, nozzle size, printing time, printing pressure, and cell concentration as input parameters, we precisely could control droplet sizes, ranging from 0.1 to 50 microliter in volume. We utilized a hydrogel precursor composed of 5% gelatin methacrylate and a mixture of 0.5% and 1% alginate, respectively. Additionally, we optimized the cell bioprinting process using green fluorescent protein-tagged 3T3 fibroblast cells. These models demonstrated superior predictive accuracy and revealed the interrelationships among parameters while taking minimal time for training and testing. This method promises to advance the mass production of organoids and microtissues with precise volume control for various biomedical applications.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.04.611031
Adele S. Ricciardi, Christina Barone, Rachael Putman, Elias Quijano, Anisha Gupta, Richard Nguyen, Hanna Mandl, Alexandra S. Piotrowski-Daspit, Francesc Lopez-Giraldez, Valerie Luks, Mollie R. Freedman-Weiss, James S. Farrelly, Samantha Ahle, Peter M. Glazer, W. Mark Saltzman, David H. Stitelman, Marie E. Egan
In utero gene editing has the potential to modify disease causing genes in multiple developing tissues before birth, possibly allowing for normal organ development, disease improvement, and conceivably, cure. In cystic fibrosis (CF), a disease that arises from mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, there are signs of multiorgan disease affecting the function of the respiratory, gastrointestinal, and reproductive systems already present at birth. Thus, treating CF patients early is crucial for preventing or delaying irreversible organ damage. Here we demonstrate proof-of-concept of multiorgan mutation correction in CF using peptide nucleic acids (PNAs) encapsulated in polymeric nanoparticles and delivered systemically in utero. In utero editing was associated with sustained postnatal CFTR activity, at a level similar to that of wild-type mice, in both respiratory and gastrointestinal tissue, without detection of off-target mutations in partially homologous loci. This work suggests that systemic in utero gene editing represents a viable strategy for treating monogenic diseases before birth that impact multiple tissue types.
{"title":"Systemic in utero gene editing as a treatment for cystic fibrosis","authors":"Adele S. Ricciardi, Christina Barone, Rachael Putman, Elias Quijano, Anisha Gupta, Richard Nguyen, Hanna Mandl, Alexandra S. Piotrowski-Daspit, Francesc Lopez-Giraldez, Valerie Luks, Mollie R. Freedman-Weiss, James S. Farrelly, Samantha Ahle, Peter M. Glazer, W. Mark Saltzman, David H. Stitelman, Marie E. Egan","doi":"10.1101/2024.09.04.611031","DOIUrl":"https://doi.org/10.1101/2024.09.04.611031","url":null,"abstract":"In utero gene editing has the potential to modify disease causing genes in multiple developing tissues before birth, possibly allowing for normal organ development, disease improvement, and conceivably, cure. In cystic fibrosis (CF), a disease that arises from mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, there are signs of multiorgan disease affecting the function of the respiratory, gastrointestinal, and reproductive systems already present at birth. Thus, treating CF patients early is crucial for preventing or delaying irreversible organ damage. Here we demonstrate proof-of-concept of multiorgan mutation correction in CF using peptide nucleic acids (PNAs) encapsulated in polymeric nanoparticles and delivered systemically in utero. In utero editing was associated with sustained postnatal CFTR activity, at a level similar to that of wild-type mice, in both respiratory and gastrointestinal tissue, without detection of off-target mutations in partially homologous loci. This work suggests that systemic in utero gene editing represents a viable strategy for treating monogenic diseases before birth that impact multiple tissue types.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.03.611113
Mahmoud Alipour, Sara C. Mednick, Paola Malerba
Background: Sleep slow oscillations (SOs), characteristic of NREM sleep, are causally tied to cognitive outcomes and the health-promoting homeostatic functions of sleep. Due to these known benefits, brain stimulation techniques aiming to enhance SOs are being developed, with great potential to contribute to clinical interventions, as they hold promise for improving sleep functions in populations with identified SO deficits (e.g., mild cognitive impairment). SO-targeting closed-loop stimulation protocols currently strive to identify SO occurrences in real time, a computationally intensive step that can lead to reduced precision (compared to post-hoc detection). These approaches are also often limited to focusing on only one electrode location, thus inherently precluding targeting of SOs that is informed by the overall organization of SOs in space-time. Prediction of SO emergence across the electrode manifold would establish an alternative to online detection, thus greatly advancing the development of personalized and flexible brain stimulation paradigms. This study presents a computational model that predicts SO occurrences at multiple locations across a night of sleep. In combination with our previous study on optimizing brain stimulation protocols using the spatiotemporal properties of SOs, this model contributes to increasing the accuracy of SO targeting in brain stimulation applications. Methods: SOs were detected in a dataset of nighttime sleep of 22 subjects (9 females), acquired with polysomnography including 64 EEG channels. Modeling of SO occurrence was achieved for SOs in stage N3, or in a combination of stages N2 and N3 (N2&N3). We study SO emergence at progressively more refined time scales. First, the cumulative SO occurrences in successive sleep cycles were successfully fit with exponentials. Secondly, the SO timing in each individual was modeled with a renewal point process. Using an inverse Gaussian model, we estimated the probability density function of SO timing and its parameters μ (mean) and λ (shape, representing skewness) in successive cycles. Results: We observed a declining trend in the SO count across sleep cycles, which we modeled using a power law relationship. The decay rate per cycle was 1.473 for N3 and 1.139 for N2&N3, with variances of the decay rates across participants being 1 and 0.53, respectively. This pattern mirrors the declining trend of slow wave activity (SWA) across sleep cycles, likely due to the inherent relationship between SWA and SO. Additionally, the SO timing model for N3 showed an increasing trend in the model parameters (μ, λ) across cycles. The increase rate per cycle followed a power law relationship with a rate of 0.83 and an exponential relationship with a rate of 4.59, respectively. The variances of the increase rates were 0.02 for μ and 0.44 for λ across participants. Conclusion: This study establishes a predictive model for SO occurrence during NREM sleep, providing insights into i
背景：睡眠慢振荡（SOs）是 NREM 睡眠的特征，与认知结果和促进健康的睡眠平衡功能有着因果关系。由于这些已知的益处，目前正在开发旨在增强睡眠慢振荡的脑刺激技术，这些技术有望改善存在睡眠慢振荡缺陷（如轻度认知障碍）的人群的睡眠功能，因此具有促进临床干预的巨大潜力。以 SO 为目标的闭环刺激方案目前致力于实时识别 SO 的发生，这是一个计算密集型步骤，可能导致精度降低（与事后检测相比）。这些方法通常还局限于只关注一个电极位置，因此无法根据 SO 在时空中的整体组织情况来确定 SO 的目标。预测SO在整个电极歧管中的出现将为在线检测提供一个替代方案，从而极大地推动个性化和灵活的脑刺激范式的发展。本研究提出了一个计算模型，可预测一夜睡眠中多个位置的 SO 出现情况。结合我们之前利用SO的时空特性优化脑刺激方案的研究，该模型有助于提高脑刺激应用中SO定位的准确性：在 22 名受试者（9 名女性）的夜间睡眠数据集中检测到了 SO，这些数据是通过包括 64 个脑电图通道的多导睡眠监测仪获得的。针对 N3 阶段或 N2 和 N3 阶段组合（N2&N3）的 SO，建立了 SO 发生模型。我们以逐渐细化的时间尺度来研究 SO 的出现。首先，我们成功地用指数拟合了连续睡眠周期中的累积 SO 发生率。其次，用更新点过程来模拟每个个体的 SO 时间。利用反高斯模型，我们估算了连续周期中SO发生时间的概率密度函数及其参数μ（平均值）和λ（形状，代表偏度）：我们观察到，SO计数在各睡眠周期呈下降趋势，我们用幂律关系对其进行了建模。N3 和 N2&N3 每个周期的衰减率分别为 1.473 和 1.139，不同参与者的衰减率方差分别为 1 和 0.53。这种模式反映了慢波活动（SWA）在各个睡眠周期中的下降趋势，这可能是由于慢波活动与 SO 之间的内在联系。此外，N3的SO定时模型显示，模型参数（μ、λ）在各周期内呈上升趋势。每个周期的增长率分别为 0.83 的幂律关系和 4.59 的指数关系。不同参与者μ和λ的增加率方差分别为0.02和0.44：本研究建立了NREM睡眠中SO发生的预测模型，深入了解了SO在连续周期和不同脑电图通道中的组织情况，这与个性化刺激范式的开发息息相关。这些研究结果表明，个性化模型参数可通过纳入第一个睡眠周期中的SO信息进行估算，因此可在SO发生前通过概率分布预测其发生时间，从而更精确地定位SO。
{"title":"Predictive Modeling of Sleep Slow Oscillation Emergence on the electrode manifold: Toward Personalized Closed-Loop Brain Stimulation","authors":"Mahmoud Alipour, Sara C. Mednick, Paola Malerba","doi":"10.1101/2024.09.03.611113","DOIUrl":"https://doi.org/10.1101/2024.09.03.611113","url":null,"abstract":"Background: Sleep slow oscillations (SOs), characteristic of NREM sleep, are causally tied to cognitive outcomes and the health-promoting homeostatic functions of sleep. Due to these known benefits, brain stimulation techniques aiming to enhance SOs are being developed, with great potential to contribute to clinical interventions, as they hold promise for improving sleep functions in populations with identified SO deficits (e.g., mild cognitive impairment). SO-targeting closed-loop stimulation protocols currently strive to identify SO occurrences in real time, a computationally intensive step that can lead to reduced precision (compared to post-hoc detection). These approaches are also often limited to focusing on only one electrode location, thus inherently precluding targeting of SOs that is informed by the overall organization of SOs in space-time. Prediction of SO emergence across the electrode manifold would establish an alternative to online detection, thus greatly advancing the development of personalized and flexible brain stimulation paradigms. This study presents a computational model that predicts SO occurrences at multiple locations across a night of sleep. In combination with our previous study on optimizing brain stimulation protocols using the spatiotemporal properties of SOs, this model contributes to increasing the accuracy of SO targeting in brain stimulation applications.\u0000Methods: SOs were detected in a dataset of nighttime sleep of 22 subjects (9 females), acquired with polysomnography including 64 EEG channels. Modeling of SO occurrence was achieved for SOs in stage N3, or in a combination of stages N2 and N3 (N2&N3). We study SO emergence at progressively more refined time scales. First, the cumulative SO occurrences in successive sleep cycles were successfully fit with exponentials. Secondly, the SO timing in each individual was modeled with a renewal point process. Using an inverse Gaussian model, we estimated the probability density function of SO timing and its parameters μ (mean) and λ (shape, representing skewness) in successive cycles.\u0000Results: We observed a declining trend in the SO count across sleep cycles, which we modeled using a power law relationship. The decay rate per cycle was 1.473 for N3 and 1.139 for N2&N3, with variances of the decay rates across participants being 1 and 0.53, respectively. This pattern mirrors the declining trend of slow wave activity (SWA) across sleep cycles, likely due to the inherent relationship between SWA and SO. Additionally, the SO timing model for N3 showed an increasing trend in the model parameters (μ, λ) across cycles. The increase rate per cycle followed a power law relationship with a rate of 0.83 and an exponential relationship with a rate of 4.59, respectively. The variances of the increase rates were 0.02 for μ and 0.44 for λ across participants.\u0000Conclusion: This study establishes a predictive model for SO occurrence during NREM sleep, providing insights into i","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.03.611092
Samuel R. Little, Niloufar Rahbari, Mehri Hajiaghayi, Fatemeh Gholizadeh, Fanny-Mei Cloarec-Ung, Joel Phillips, Hugo Sinha, Alison Hirukawa, David JHF Knapp, Peter J. Darlington, Steve CC Shih
Genetically engineering human immune cells has been shown to be an effective approach for developing novel cellular therapies to treat a wide range of diseases. To expand the scope of these cellular therapies while solving persistent challenges, extensive research and development is still required. Electroporation has recently emerged as one of the most popular techniques for inserting biological payloads into human immune cells to perform genetic engineering. However, several recent studies have reported that electroporation can negatively impact cell functionality. Additionally, the requirement to use large amounts of cells and expensive payloads to achieve efficient delivery can drive up the costs of development efforts. Here we use a digital microfluidic enabled electroporation system (referred to as triDrop) and compare them against two state-of-the-art commercially available systems for the engineering of human T cells. We describe the ability to use triDrop for highly viable, highly efficient transfection while using substantially fewer cells and payload. Subsequently, we perform transcriptomic analysis on cells engineered with each of the three systems and show that electroporation with triDrop lead to less dysregulation of several functionally relevant pathways. Finally, in a direct comparison of immunotherapeutic functionality, we show that T cells engineered with triDrop have an improved ability to mount an immune response when presented with tumor cells. These results show that the triDrop platform is uniquely suited to produce functionally engineered immune cells while also reducing the costs of cell engineering compared to other commercially available systems.
人类免疫细胞基因工程已被证明是开发新型细胞疗法治疗多种疾病的有效方法。要扩大这些细胞疗法的范围，同时解决长期存在的难题，仍需要进行广泛的研究和开发。最近，电穿孔技术已成为将生物有效载荷植入人体免疫细胞以进行基因工程的最流行技术之一。然而，最近的一些研究报告指出，电穿孔会对细胞功能产生负面影响。此外，要求使用大量细胞和昂贵的有效载荷来实现高效传递，也会增加开发成本。在这里，我们使用一种数字微流控电穿孔系统（简称为 triDrop），并将其与两种最先进的商业化人 T 细胞工程系统进行比较。我们介绍了使用 triDrop 进行高活性、高效转染的能力，同时大大减少了细胞和有效载荷的使用。随后，我们对这三种系统分别设计的细胞进行了转录组分析，结果表明，使用 triDrop 进行电穿孔导致的几种功能相关通路的失调较少。最后，我们对免疫治疗功能进行了直接比较，结果表明，当肿瘤细胞出现时，使用三滴滴酶工程的 T 细胞启动免疫反应的能力更强。这些结果表明，与其他商业化系统相比，triDrop 平台非常适合生产功能工程化免疫细胞，同时还能降低细胞工程的成本。
{"title":"A Digital Microfluidic Platform for the Microscale Production of Functional Immune Cell Therapies","authors":"Samuel R. Little, Niloufar Rahbari, Mehri Hajiaghayi, Fatemeh Gholizadeh, Fanny-Mei Cloarec-Ung, Joel Phillips, Hugo Sinha, Alison Hirukawa, David JHF Knapp, Peter J. Darlington, Steve CC Shih","doi":"10.1101/2024.09.03.611092","DOIUrl":"https://doi.org/10.1101/2024.09.03.611092","url":null,"abstract":"Genetically engineering human immune cells has been shown to be an effective approach for developing novel cellular therapies to treat a wide range of diseases. To expand the scope of these cellular therapies while solving persistent challenges, extensive research and development is still required. Electroporation has recently emerged as one of the most popular techniques for inserting biological payloads into human immune cells to perform genetic engineering. However, several recent studies have reported that electroporation can negatively impact cell functionality. Additionally, the requirement to use large amounts of cells and expensive payloads to achieve efficient delivery can drive up the costs of development efforts. Here we use a digital microfluidic enabled electroporation system (referred to as triDrop) and compare them against two state-of-the-art commercially available systems for the engineering of human T cells. We describe the ability to use triDrop for highly viable, highly efficient transfection while using substantially fewer cells and payload. Subsequently, we perform transcriptomic analysis on cells engineered with each of the three systems and show that electroporation with triDrop lead to less dysregulation of several functionally relevant pathways. Finally, in a direct comparison of immunotherapeutic functionality, we show that T cells engineered with triDrop have an improved ability to mount an immune response when presented with tumor cells. These results show that the triDrop platform is uniquely suited to produce functionally engineered immune cells while also reducing the costs of cell engineering compared to other commercially available systems.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intracellular transport is driven by teams of various motor proteins. Advances in DNA nanotechnology have enabled the programmable linkage of different types of motor proteins. In this study, we developed a modular, photostable, fluorescence-labeled tiny DNA origami block (FTOB) for extended observation of collective transport by selected motor combinations. The FTOB is designed as a 4-helix bundle (~8.4 nm) with densely accumulated fluorescent dyes, minimizing blinking and photobleaching. By designing a pair of connector DNAs, FTOBs are heterodimerized following motor protein attachment using the ALFA-tag/nanobody system. Our system examined the impact of a pathogenic mutant kinesin on its collective movement with wild-type kinesin, clearly observing two distinct behaviors: the team's velocity was generally governed by the slower mutant but occasionally surged to levels comparable to that of a single wild-type motor. Our photostable, robust, modular FTOB system could serve as a versatile tool for precisely dissecting cooperative cargo transport.
{"title":"Modular photostable fluorescent DNA blocks dissect the effects of pathogenic mutant kinesin on collective transport","authors":"Tomoki Kita, Ryota Sugie, Yuki Suzuki, Shinsuke Niwa","doi":"10.1101/2024.09.06.611758","DOIUrl":"https://doi.org/10.1101/2024.09.06.611758","url":null,"abstract":"Intracellular transport is driven by teams of various motor proteins. Advances in DNA nanotechnology have enabled the programmable linkage of different types of motor proteins. In this study, we developed a modular, photostable, fluorescence-labeled tiny DNA origami block (FTOB) for extended observation of collective transport by selected motor combinations. The FTOB is designed as a 4-helix bundle (~8.4 nm) with densely accumulated fluorescent dyes, minimizing blinking and photobleaching. By designing a pair of connector DNAs, FTOBs are heterodimerized following motor protein attachment using the ALFA-tag/nanobody system. Our system examined the impact of a pathogenic mutant kinesin on its collective movement with wild-type kinesin, clearly observing two distinct behaviors: the team's velocity was generally governed by the slower mutant but occasionally surged to levels comparable to that of a single wild-type motor. Our photostable, robust, modular FTOB system could serve as a versatile tool for precisely dissecting cooperative cargo transport.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1101/2024.09.05.608688
David Jiang, Andrew J Robinson, Abbey Nkansah, Jonathan Leung, Leopold Guo, Steve A Maas, Jeffrey A Weiss, Elizabeth M Cosgriff-Hernandez, Lucas H Timmins
The failure of synthetic small-diameter vascular grafts has been attributed to a mismatch in the compliance between the graft and native artery, driving mechanisms that promote thrombosis and neointimal hyperplasia. Additionally, the buckling of grafts results in large deformations that can lead to device failure. Although design features can be added to lessen the buckling potential, the addition is detrimental to decreasing compliance (e.g., reinforcing coil). Herein, we developed a novel finite element framework to inform vascular graft design by evaluating compliance and resistance to buckling. A batch-processing scheme iterated across the multi-dimensional design parameter space, which included three parameters: coil thickness, modulus, and spacing. Three types of finite element models were created in FEBio for each unique coil-reinforced graft parameter combination to simulate pressurization, axial buckling, and bent buckling, and results were analyzed to quantify compliance, buckling load, and kink radius, respectively, from each model. Importantly, model validation demonstrated that model predictions agree qualitatively and quantitatively with experimental observations. Subsequently, data for each design parameter combination were integrated into an optimization function for which a minimum value was sought. The optimization values identified various candidate graft designs with promising mechanical properties. Our investigation successfully demonstrated the model-directed framework identified vascular graft designs with optimal mechanical properties, which can potentially improve clinical outcomes by addressing device failure. In addition, the presented computational framework promotes model-directed device design for a broad range of biomaterial and regenerative medicine strategies.
{"title":"A Computational Framework to Optimize the Mechanical Behavior of Synthetic Vascular Grafts","authors":"David Jiang, Andrew J Robinson, Abbey Nkansah, Jonathan Leung, Leopold Guo, Steve A Maas, Jeffrey A Weiss, Elizabeth M Cosgriff-Hernandez, Lucas H Timmins","doi":"10.1101/2024.09.05.608688","DOIUrl":"https://doi.org/10.1101/2024.09.05.608688","url":null,"abstract":"The failure of synthetic small-diameter vascular grafts has been attributed to a mismatch in the compliance between the graft and native artery, driving mechanisms that promote thrombosis and neointimal hyperplasia. Additionally, the buckling of grafts results in large deformations that can lead to device failure. Although design features can be added to lessen the buckling potential, the addition is detrimental to decreasing compliance (e.g., reinforcing coil). Herein, we developed a novel finite element framework to inform vascular graft design by evaluating compliance and resistance to buckling. A batch-processing scheme iterated across the multi-dimensional design parameter space, which included three parameters: coil thickness, modulus, and spacing. Three types of finite element models were created in FEBio for each unique coil-reinforced graft parameter combination to simulate pressurization, axial buckling, and bent buckling, and results were analyzed to quantify compliance, buckling load, and kink radius, respectively, from each model. Importantly, model validation demonstrated that model predictions agree qualitatively and quantitatively with experimental observations. Subsequently, data for each design parameter combination were integrated into an optimization function for which a minimum value was sought. The optimization values identified various candidate graft designs with promising mechanical properties. Our investigation successfully demonstrated the model-directed framework identified vascular graft designs with optimal mechanical properties, which can potentially improve clinical outcomes by addressing device failure. In addition, the presented computational framework promotes model-directed device design for a broad range of biomaterial and regenerative medicine strategies.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1101/2024.09.03.611088
Rachel I Taitano, Valeriya Gritsenko
Movement analysis is a critical tool in understanding and addressing various disabilities associated with movement deficits. By analyzing movement patterns, healthcare professionals can identify the root causes of these alterations, which is essential for preventing, diagnosing, and rehabilitating a broad spectrum of medical conditions, disabilities, and injuries. With the advent of affordable motion capture technologies, quantitative data on patient movement is more accessible to clinicians, enhancing the quality of care. Nonetheless, it is crucial that these technologies undergo rigorous validation to ensure their accuracy in collecting and monitoring patient movements, particularly for remote healthcare services where direct patient observation is not possible. In this study, motion capture technology was used to track upper extremity movements during a reaching task presented in virtual reality. Kinematic data was then calculated for each participant using a scaled dynamic inertial model. The goal was to evaluate the accuracy of joint angle calculations using inverse kinematics from motion capture relative to the typical movement redundancy. Shoulder, elbow, radioulnar, and wrist joint angles were calculated with models scaled using either direct measurements of each individual’s arm segment lengths or those lengths were calculated from individual height using published average proportions. The errors in joint angle trajectories calculated using the two methods of model scaling were compared to the inter-trial variability of those trajectories. The variance of this error was primarily within the normal range of variability between repetitions of the same movements. This suggests that arm joint angles can be inferred with good enough accuracy from motion capture data and individual height to be useful for the clinical assessment of motor deficits.
{"title":"Evaluating Joint Angle Data for Clinical Assessment Using Multidimensional Inverse Kinematics with Average Segment Morphometry.","authors":"Rachel I Taitano, Valeriya Gritsenko","doi":"10.1101/2024.09.03.611088","DOIUrl":"https://doi.org/10.1101/2024.09.03.611088","url":null,"abstract":"Movement analysis is a critical tool in understanding and addressing various disabilities associated with movement deficits. By analyzing movement patterns, healthcare professionals can identify the root causes of these alterations, which is essential for preventing, diagnosing, and rehabilitating a broad spectrum of medical conditions, disabilities, and injuries. With the advent of affordable motion capture technologies, quantitative data on patient movement is more accessible to clinicians, enhancing the quality of care. Nonetheless, it is crucial that these technologies undergo rigorous validation to ensure their accuracy in collecting and monitoring patient movements, particularly for remote healthcare services where direct patient observation is not possible. In this study, motion capture technology was used to track upper extremity movements during a reaching task presented in virtual reality. Kinematic data was then calculated for each participant using a scaled dynamic inertial model. The goal was to evaluate the accuracy of joint angle calculations using inverse kinematics from motion capture relative to the typical movement redundancy. Shoulder, elbow, radioulnar, and wrist joint angles were calculated with models scaled using either direct measurements of each individual’s arm segment lengths or those lengths were calculated from individual height using published average proportions. The errors in joint angle trajectories calculated using the two methods of model scaling were compared to the inter-trial variability of those trajectories. The variance of this error was primarily within the normal range of variability between repetitions of the same movements. This suggests that arm joint angles can be inferred with good enough accuracy from motion capture data and individual height to be useful for the clinical assessment of motor deficits.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1101/2024.09.04.611160
Sunni Chen, Ruiqi Wang, Youn Joong Kim, Emily Radican, Yu Lei, Yong Ku Cho, Zhenlei Xiao, Mingyu Qiao, Yangchao Luo
Microalgae are well-known for their role as sustainable bio-factories, offering a promising solution to the global food and nutrition crisis. To clarify the potential of Chlorella sorokiniana UTEX 1230 for food applications, particularly as an alternative protein source, the study employed a mixotrophic cultivation mode with sodium acetate (NaAc) as a cost-effective organic carbon (NaAc-C) source. Varying levels of NaAc-C and nitrate-sourced nitrogen were investigated, optimizing the effect of metabolic characteristics of the microalgal growth. The designed heterotrophic cultivation confirmed the ability of C. sorokiniana UTEX 1230 to grow on NaAc-C, and then the mixotrophic cultures, when supported by both NaAc-C and CO2, exhibited superior growth performance, achieving double the biomass concentration compared to the autotrophic control. The addition of nitrogen (750 mg/L NaNO₃) facilitated the thorough metabolism of NaAc-C and enhanced photosynthetic activity indicated by a 196% increase in pigment levels, which resulted in a maximum biomass concentration of 2.82 g/L in the 150 mM NaAc-C group. A detailed analysis of nitrogen and protein concentrations over time revealed that higher nitrogen availability led to greater protein accumulation which was then degraded to support essential life activities under nitrogen starvation. Therefore, it is suggested that supplementing nitrate on the 3rd day and harvesting on the 4th day could be strategically implemented to increase protein yield from 0.17 g/L/d to 0.34 g/L/d. These findings offer theoretical guidance for further refining this microalgal strain for use as an alternative protein.
{"title":"Impact of Acetate and Optimized Nitrate Levels on Mixotrophic Growth and Protein Dynamics in Chlorella Sorokiniana","authors":"Sunni Chen, Ruiqi Wang, Youn Joong Kim, Emily Radican, Yu Lei, Yong Ku Cho, Zhenlei Xiao, Mingyu Qiao, Yangchao Luo","doi":"10.1101/2024.09.04.611160","DOIUrl":"https://doi.org/10.1101/2024.09.04.611160","url":null,"abstract":"Microalgae are well-known for their role as sustainable bio-factories, offering a promising solution to the global food and nutrition crisis. To clarify the potential of Chlorella sorokiniana UTEX 1230 for food applications, particularly as an alternative protein source, the study employed a mixotrophic cultivation mode with sodium acetate (NaAc) as a cost-effective organic carbon (NaAc-C) source. Varying levels of NaAc-C and nitrate-sourced nitrogen were investigated, optimizing the effect of metabolic characteristics of the microalgal growth. The designed heterotrophic cultivation confirmed the ability of C. sorokiniana UTEX 1230 to grow on NaAc-C, and then the mixotrophic cultures, when supported by both NaAc-C and CO2, exhibited superior growth performance, achieving double the biomass concentration compared to the autotrophic control. The addition of nitrogen (750 mg/L NaNO₃) facilitated the thorough metabolism of NaAc-C and enhanced photosynthetic activity indicated by a 196% increase in pigment levels, which resulted in a maximum biomass concentration of 2.82 g/L in the 150 mM NaAc-C group. A detailed analysis of nitrogen and protein concentrations over time revealed that higher nitrogen availability led to greater protein accumulation which was then degraded to support essential life activities under nitrogen starvation. Therefore, it is suggested that supplementing nitrate on the 3rd day and harvesting on the 4th day could be strategically implemented to increase protein yield from 0.17 g/L/d to 0.34 g/L/d. These findings offer theoretical guidance for further refining this microalgal strain for use as an alternative protein.","PeriodicalId":501308,"journal":{"name":"bioRxiv - Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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