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Abstract Multicellular spheroids embedded in 3D hydrogels are prominent in vitro models for 3D cell invasion. Yet, quantification methods for spheroid cell invasion that are high‐throughput, objective and accessible are still lacking. Variations in spheroid sizes and the shapes of the cells within render it difficult to objectively assess invasion extent. The goal of this work is to develop a high-throughput quantification method of cell invasion into 3D matrices that minimizes sensitivity to initial spheroid size and cell spreading and provides precise integrative directionally-dependent metrics of invasion. By analyzing images of fluorescent cell nuclei, invasion metrics are automatically calculated at the pixel level. The initial spheroid boundary is segmented and automated calculations of the nuclear pixel distances from the initial boundary are used to compute common invasion metrics (i.e., the change in invasion area, mean distance) for the same spheroid at a later timepoint. We also introduce the area moment of inertia as an integrative metric of cell invasion that considers the invasion area as well as the pixel distances from the initial spheroid boundary. Further, we show that principal component analysis can be used to quantify the directional influence of a stimuli to invasion (e.g., due to a chemotactic gradient or contact guidance). To demonstrate the power of the analysis for cell types with different invasive potentials and the utility of this method for a variety of biological applications, the method is used to analyze the invasiveness of five different cell types. In all, implementation of this high‐throughput quantification method results in consistent and objective analysis of 3D multicellular spheroid invasion. We provide the analysis code in both MATLAB and Python languages as well as a GUI for ease of use for researchers with a range of computer programming skills and for applications in a variety of biological research areas such as wound healing and cancer metastasis. 

This paper presents a novel approach to fall prediction for bipedal robots, specifically targeting the detection of potential falls while standing caused by abrupt, incipient, and intermittent faults. Leveraging a 1D convolutional neural network (CNN), our method aims to maximize lead time for fall prediction while minimizing false positive rates. The proposed algorithm uniquely integrates the detection of various fault types and estimates the lead time for potential falls. Our contributions include the development of an algorithm capable of detecting abrupt, incipient, and intermittent faults in full-sized robots, its implementation using both simulation and hardware data for a humanoid robot, and a method for estimating lead time. Evaluation metrics, including false positive rate, lead time, and response time, demonstrate the efficacy of our approach. Particularly, our model achieves impressive lead times and response times across different fault scenarios with a false positive rate of 0. The findings of this study hold significant implications for enhancing the safety and reliability of bipedal robotic systems. 

Abstract As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) within a fine-scale geographic area (30 m). We scaled National Agricultural Statistic Survey land management data to National Land Cover Data cropland extents to assess GWP of cropland management over time and among management units (i.e. counties and production systems). We found that cropland extent alone was not indicative of GWP emissions; rather, rates of management intensity, such as energy and fertilizer use, are greater indicators of anthropogenic GWP. We found production processes for fuel and fertilizers contributed 51.93% of GWP, where 33.58% GWP was estimated from N₂O emissions after fertilization, and only 13.31% GWP was due to energy consumption by field equipment. This demonstrates that upstream processes in LCA should be considered in NbS with the relative contribution of fertilization to GWP. Additionally, while land cover change had minimal GWP effect, urbanization will replace croplands and forests where NbS are implemented. Fine-scale landscape variations are essential for NbS to identify, as they accumulate within regional and global estimates. As such, this study demonstrates the capability to harness both LCA and fine-resolution imagery for applications in spatiotemporal and socioecological research towards identifying and monitoring NbS. 

Abstract Proximity ligation assays (PLAs) use specific antibodies to detect endogenous protein‐protein interactions. PLAs are a highly useful biochemical technique that allow two proteins within proximity to be visualized with fluorescent probes amplified by PCR. While this technique has gained prominence, the use of a PLA in mouse skeletal muscle (SkM) is novel. In this article, we discuss how the PLA method can be used in SkM to study the protein‐protein interactions within mitochondria‐endoplasmic reticulum contact sites (MERCs). © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Proximity ligation assay for skeletal muscle tissue and myoblast for MERC proteins 

Abstract OPA1 is a dynamin‐related GTPase that modulates mitochondrial dynamics and cristae integrity. Humans carry eight different isoforms of OPA1 and mice carry five, all of which are expressed as short‐ or long‐form isoforms. These isoforms contribute to OPA1's ability to control mitochondrial energetics and DNA maintenance. However, western blot isolation of all long and short isoforms of OPA1 can be difficult. To address this issue, we developed an optimized western blot protocol based on improving running time to isolate five different isoforms of OPA1 in mouse cells and tissues. This protocol can be applied to study changes in mitochondrial structure and function. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Western Blot Protocol for Isolating OPA1 Isoforms in Mouse Primary Skeletal Muscle Cells 

For legged robots to operate in complex terrains, they must be robust to the disturbances and uncertainties they encounter. This paper contributes to enhancing robustness by designing fall detection/prediction algorithms that will provide sufficient lead time for corrective motions to be taken. Falls can be caused by abrupt (fast-acting), incipient (slow-acting), or intermittent (non-continuous) faults. Early fall detection is a challenging task due to the masking effects of controllers (through their disturbance attenuation actions), the direct relationship between lead time and false positive rates, and the temporal behavior of the faults/underlying factors. In this paper, we propose a fall detection algorithm capable of detecting both incipient and abrupt faults while maximizing lead time and meeting desired thresholds on the false positive and negative rates 

Abstract While some established undergraduate summer programs are effective across many institutions, these programs may only be available to some principal investigators or may not fully address the diverse needs of incoming undergraduates. This article outlines a 10‐week science, technology, engineering, mathematics, and medicine (STEMM) education program designed to prepare undergraduate students for graduate school through a unique model incorporating mentoring dyads and triads, cultural exchanges, and diverse activities while emphasizing critical thinking, research skills, and cultural sensitivity. Specifically, we offer a straightforward and adaptable guide that we have used for mentoring undergraduate students in a laboratory focused on mitochondria and microscopy, but which may be customized for other disciplines. Key components include self‐guided projects, journal clubs, various weekly activities such as mindfulness training and laboratory techniques, and a focus on individual and cultural expression. Beyond this unique format, this 10‐week program also seeks to offer an intensive research program that emulates graduate‐level experiences, offering an immersive environment for personal and professional development, which has led to numerous achievements for past students, including publications and award‐winning posters. 

ABSTRACT Age‐related skeletal muscle atrophy, known as sarcopenia, is characterized by loss of muscle mass, strength, endurance, and oxidative capacity. Although exercise has been shown to mitigate sarcopenia, the underlying governing mechanisms are poorly understood. Mitochondrial dysfunction is implicated in aging and sarcopenia; however, few studies explore how mitochondrial structure contributes to this dysfunction. In this study, we sought to understand how aging impacts mitochondrial three‐dimensional (3D) structure and its regulators in skeletal muscle. We hypothesized that aging leads to remodeling of mitochondrial 3D architecture permissive to dysfunction and is ameliorated by exercise. Using serial block‐face scanning electron microscopy (SBF‐SEM) and Amira software, mitochondrial 3D reconstructions from patient biopsies were generated and analyzed. Across five human cohorts, we correlate differences in magnetic resonance imaging, mitochondria 3D structure, exercise parameters, and plasma immune markers between young (under 50 years) and old (over 50 years) individuals. We found that mitochondria are less spherical and more complex, indicating age‐related declines in contact site capacity. Additionally, aged samples showed a larger volume phenotype in both female and male humans, indicating potential mitochondrial swelling. Concomitantly, muscle area, exercise capacity, and mitochondrial dynamic proteins showed age‐related losses. Exercise stimulation restored mitofusin 2 (MFN2), one such of these mitochondrial dynamic proteins, which we show is required for the integrity of mitochondrial structure. Furthermore, we show that this pathway is evolutionarily conserved, as Marf, the MFN2 ortholog inDrosophila, knockdown alters mitochondrial morphology and leads to the downregulation of genes regulating mitochondrial processes. Our results define age‐related structural changes in mitochondria and further suggest that exercise may mitigate age‐related structural decline through modulation of mitofusin 2.