Open Access Publications - Department of Biomedical Engineering

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Open access publications by faculty, postdocs, and graduate students in the Department of Biomedical Engineering.

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Absolute substrate oxidation rates are lower in older adults with amnestic mild cognitive impairment
(Physiological Reports, 2025-04-13) Rizzi, Nicholas A.; Kramer, Mary K.; DeConne, Theodore M.; Ellison, James M.; Lanzi, Alyssa M.; Overstreet, Matthew L.; Edwards, David G.; Cohen, Matthew L.; Johnson, Curtis L.; Martens, Christopher R.
Previous studies in individuals with mild cognitive impairment suggest that they may have altered systemic metabolic function at rest; however, metabolic function during aerobic exercise is not fully understood in this population. This study sought to determine whether individuals with amnestic mild cognitive impairment (aMCI) have lower rates of baseline and peak fat oxidation (FatOx) during a graded exercise test (GXT) compared with cognitively unimpaired control participants (CU). Twenty-two (22) older adults with aMCI and 21 age- and sex-matched adults completed a GXT to assess rates of substrate oxidation and peak oxygen consumption (VO2 peak). Rates of FatOx and carbohydrate oxidation (CHOOx) were assessed using VO2 and VCO2. Resting absolute (0.10 ± 0.03 vs. 0.09 ± 0.02 g/min, p = 0.126) and relative (1.5 ± 0.43 vs. 1.4 ± 0.44 mg/kg/min, p = 0.492) rates of FatOx, as well as resting absolute (0.51 ± 0.11 vs. 0.59 ± 0.15 g/min, p = 0.093) and relative (8.0 ± 2.3 vs. 7.5 ± 2.7 mg/kg/min, p = 0.126) rates of CHOOx were similar between groups. However, peak absolute rates of FatOx (0.33 ± 0.13 vs. 0.39 ± 0.10 g/min, p = 0.033) and CHOOx (1.9 ± 0.41 vs. 2.2 ± 0.49 g/min, p = 0.046) were significantly lower in the aMCI group. Time to fatigue (7.2 ± 2.0 vs. 8.7 ± 2.3 min, p = 0.033) and absolute VO2 peak (1.3 ± 0.34 vs. 1.6 ± 0.47 L/min, p = 0.024) were also significantly lower in the aMCI group. These findings suggest that absolute peak rates of whole-body FatOx and CHOOx are reduced during aerobic exercise in older adults with aMCI.
Average Biomechanical Responses of the Human Brain Grouped by Age and Sex
(Annals of Biomedical Engineering, 2025-04-09) Alshareef, Ahmed; Carass, Aaron; Lu, Yuan-Chiao; Mojumder, Joy; Diano, Alexa M.; Bailey, Olivia M.; Okamoto, Ruth J.; Pham, Dzung L.; Prince, Jerry L.; Bayly, Philip V.; Johnson, Curtis L.
Traumatic brain injuries (TBIs) occur from rapid head motion that results in brain deformation. Computational models are typically used to estimate brain deformation to predict risk of injury and evaluate the effectiveness of safety countermeasures. The accuracy of these models relies on validation to experimental brain deformation data. In this study, we create the first group-average biomechanical responses of the brain, including structure, material properties, and deformation response, by age and sex from 157 subjects. Subjects were sorted intro three age groups—young, mid-age, and older—and by sex to create group-average neuroanatomy, material properties, and brain deformation response to non-injurious loading using structural and specialized magnetic resonance imaging data. Computational models were also built using the group-average geometry and material properties for each of the six groups. The material properties did not depend on sex, but showed a decrease in shear stiffness in the older adult group. The brain deformation response also showed differences in the distribution of strain and a decrease in the magnitude of maximum strain in the older adult group. The computational models were simulated using the same non-injurious loading conditions as the subject data. While the models’ strain response showed differences among the models, there were no clear relationships with age. Further studies, both modeling and experimental, with more data from subjects in each age group, are needed to clarify the mechanisms underlying the observed changes in strain response with age, and for computational models to better match the trends observed across the group-average responses.
Prognostic assessment of osteolytic lesions and mechanical properties of bones bearing breast cancer using neural network and finite element analysis
(Mechanobiology in Medicine, 2025-04-10) Wang, Shubo; Chu, Tiankuo; Wasi, Murtaza; Guerra, Rosa M.; Yuan, Xu; Wang, Liyun
The management of skeletal-related events (SREs), particularly the prevention of pathological fractures, is crucial for cancer patients. Current clinical assessment of fracture risk is mostly based on medical images, but incorporating sequential images in the assessment remains challenging. This study addressed this issue by leveraging a comprehensive dataset consisting of 260 longitudinal micro-computed tomography (μCT) scans acquired in normal and breast cancer bearing mice. A machine learning (ML) model based on a spatial–temporal neural network was built to forecast bone structures from previous μCT scans, which were found to have an overall similarity coefficient (Dice) of 0.814 with ground truths. Despite the predicted lesion volumes (18.5 % ± 15.3 %) being underestimated by ∼21 % than the ground truths’ (22.1 % ± 14.8 %), the time course of the lesion growth was better represented in the predicted images than the preceding scans (10.8 % ± 6.5 %). Under virtual biomechanical testing using finite element analysis (FEA), the predicted bone structures recapitulated the loading carrying behaviors of the ground truth structures with a positive correlation (y = 0.863x) and a high coefficient of determination (R2 = 0.955). Interestingly, the compliances of the predicted and ground truth structures demonstrated nearly identical linear relationships with the lesion volumes. In summary, we have demonstrated that bone deterioration could be proficiently predicted using machine learning in our preclinical dataset, suggesting the importance of large longitudinal clinical imaging datasets in fracture risk assessment for cancer bone metastasis. Graphical abstract available at: https://doi.org/10.1016/j.mbm.2025.100130 Highlights • Fracture risk assessment is critical in managing bone cancer metastasis. • Utilized 260 longitudinal μCT scans of both normal mice and cancer-bearing mice. • Bone lesion progression predicted from μCT scans using machine learning (ML). • Finite element analysis (FEA) revealed the rigidity of the predicted bone structures. • Predictive modeling of bone deterioration is a valuable tool to assess fracture risk.
A Novel Method to Assess Subject-Specific Architecture of the Achilles Tendon In Vivo in Humans
(Scandinavian Journal of Medicine & Science in Sports, 2025-03-26) Finni, Taija; Khair, Raad; Franz, Jason R.; Sukanen, Maria; Cronin, Neil; Cone, Stephanie
The Achilles tendon (AT) comprises three subtendons whose relative locations, and respective lines of action, vary individually. This study was aimed to demonstrate the efficacy of a novel method, combining Ultrasound and electrical STIMulation (USTIM), to identify the in vivo location of individual subtendons in cross-sections of the AT. We individually stimulated the triceps surae muscle heads and imaged localized tissue movement on a transverse plane 1 cm proximal to the calcaneus using B-mode ultrasonography. Movement induced by muscle stimulation was presumed to arise from movement in the respective subtendon. Frame-by-frame changes in grayscale values were analyzed to detect localized tissue movement, establishing the three subtendon locations. From 12 successfully assessed legs, we found test–retest reliability to be excellent (ICC = 0.93, N = 3), and intra- and inter-rater reliability to be good for the subtendon centroid locations (ICC > 0.77, N = 12). Reliability for identifying the subtendon area was good for test–retest (ICC = 0.77) and intra-rater assessments (ICC > 0.70) but moderate between raters (ICC = 0.53). Subtendon centroid locations assessed using USTIM showed a strong association (N = 2; r2= 0.80, p < 0.001) with those identified via the high-field MRI method established by Cone et al. Fitting with prior literature, the majority of (83%) tendons were identified as low twist type I. The novel USTIM method can identify in vivo locations of the three subtendons within a cross-section of AT with moderate to excellent reliability. This method could be used to unravel the intricacies of structure–function relationships in the AT, with potential clinical benefits for treatment of patients with AT injuries.
Effect of sulfation on a tough hybrid hydrogel network
(RSC Applied Polymers, 2025-03-17) Driesen, Sander; Atella, Valentino; Kiick, Kristi; Pitet, Louis M.; Graulus, Geert-Jan
Hybrid hydrogels can mimic the exceptional stiffness of tough native tissues (e.g., articular cartilage). However, many of these tough hybrid hydrogels currently lack bioactive moieties. Therefore, our work focuses on introducing sulfated alginate into a tough poly(acrylamide-co-acrylic acid)/alginate hybrid hydrogel network. This modification introduces the potential for effective tissue interactions and allows further diversification through chemical transformations. These hydrogels are synthesized via the radical-mediated polymerization and covalent crosslinking of acrylamide and acrylic acid. The covalent network is fortified with a second ionically crosslinked sulfated alginate network. FTIR, 13C-NMR, and elemental analysis confirmed a degree of sulfation of 42.5%. Mechanical testing showed that hydrogels with a sulfated alginate content of 2 wt% exhibit comparable compressive stiffness (up to 230 kPa) to native articular cartilage. Cyclical mechanical testing revealed the network's resilience and remarkable toughness. These results suggest the hydrogels’ potential as cartilage mimics and support their additional investigation in vitro.
Comparative analysis of rodent lens morphometrics and biomechanical properties
(Frontiers in Ophthalmology, 2025-04-03) Cheheltani, Sepideh; Islam, Sadia T.; Malino, Heather; Abera, Kalekidan; Aryal, Sandeep; Forbes, Karen; Parreno, Justin; Fowler, Velia M.
Introduction: Proper ocular lens function requires biomechanical flexibility, which is reduced during aging. As increasing lens size has been shown to correlate with lens biomechanical stiffness in aging, we tested the hypothesis that whole lens size determines gross biomechanical stiffness by comparing lenses of varying sizes from three rodent species (mice, rats, and guinea pigs). Methods: Coverslip compression assay was performed to measure whole lens biomechanics. Whole mount staining on fixed lenses, followed by confocal microscopy, was conducted to measure lens microstructures. Results: Among the three species, guinea pig lenses are the largest, rat lenses are smaller than guinea pig lenses, and mouse lenses are the smallest of the three. We found that rat and guinea pig lenses are stiffer than the much smaller mouse lenses. However, despite guinea pig lenses being larger than rat lenses, whole lens stiffness between guinea pigs and rats is not different. This refutes our hypothesis and indicates that lens size does not solely determine lens stiffness. We next compared lens microstructures, including nuclear size, capsule thickness, epithelial cell area, fiber cell widths, and suture organization between mice, rats, and guinea pigs. The lens nucleus is the largest in guinea pigs, followed by rats, and mice. However, the rat nucleus occupies a larger fraction of the lens. Both lens capsule thickness and fiber cell widths are the largest in guinea pigs, followed by mice and then rats. Epithelial cells are the largest in guinea pigs, and there are no differences between mice and rats. In addition, the lens suture shape appears similar across all three species. Discussion: Overall, our data indicates that whole lens size and microstructure morphometrics do not correlate with lens stiffness, indicating that factors contributing to lens biomechanics are complex and likely multifactorial.
Effective disc age: a statistical model for age-dependent and level-specific lumbar disc degeneration using magnetic resonance imaging (MRI)
(European Spine Journal, 2025-02-09) Newman, Harrah R.; Peloquin, John M.; Meadows, Kyle D.; Bodt, Barry A.; Vresilovic, Edward J.; Elliott, Dawn M.
Purpose Intervertebral disc degeneration progresses with normal aging; yet common disc grading schemes do not account for age. Degeneration progression also varies between spine levels and is similarly not accounted for by current grading schemes. These limitations inhibit differentiation between discs with normal and expected aging (non-pathological) and discs with accelerated degeneration (which may be pathological). We sought to develop a statistical model to quantify normal age and spine level dependent disc degeneration. Methods Eighty-four asymptomatic adult subjects ranging evenly from 18 to 83 years old underwent magnetic resonance imaging (MRI) of the lumbar spine. Subject traits, MRI-derived disc geometry, and MRI biomarkers of T2 relaxation time were evaluated and used to develop a statistical model to predict effective disc age, the age at which normal aging would produce a disc’s observed phenotype. Results After evaluating several models, a 4-predictor model utilizing 1) subject height, 2) nucleus pulposus T2 relaxation time, 3) disc mid-sagittal area and 4) disc 3D volume, optimally estimated effective disc age. The effective age closely tracked true age for spine levels L1-L5 (R2 ≈ 0.7, RMSE ≈ 10 years) and moderately tracked true age for L5-S1 (R2 = 0.4, RMSE = 14 years). The uncertainty in the effective disc age prediction was ± 3 years as assessed by fivefold cross validation. Conclusion We offer a data-driven, quantitative tool to quantify normal, expected intervertebral disc aging. This effective age model allows future research to target discs with accelerated degeneration.
Standard purification methods are not sufficient to remove micellular lipophilic dye from polymer nanoparticle solution
(RSC Pharmaceutics, 2025-03-06) Sterin, Eric H.; Weinstein, Laura A.; Chowdhury, Chitran Roy; Guzzetti, Emma C.; Day, Emily S.
Tracking nanoparticles’ location is imperative for understanding cellular interactions, pharmacokinetics, and biodistribution. DiD is a lipophilic dye commonly used to label nanoparticles for trafficking studies. Herein, we show that DiD micelles form in polymer NP solutions during synthesis and can lead to false positive results in downstream assays. Potential methods to remove these micelles are also described.
The Role of Sleep in Memory Consolidation and Reading in Dyslexia
(Journal of Cognitive Neuroscience, 2025-03-01) Solbi, Ali; Earle, F. Sayako
Dyslexia is a neurodevelopmental disorder characterized by reading difficulty, which has long been attributed to a phonological processing deficit. However, recent research suggests that general difficulties with learning and memory, but also in memory consolidation, may underlie disordered reading. This review article provides an overview of the relationship between learning and memory, memory consolidation during sleep, and reading and explores the emerging literature on consolidation during sleep in individuals with dyslexia. We consider evidence that sleep appears to be less effective for memory consolidation in children with dyslexia and how this may be related to their deficits in reading. This discussion highlights the need for further research to determine the extent to which atypical sleep patterns may contribute to learning deficits associated with disordered reading.
Osteocyte Dendrites: How Do They Grow, Mature, and Degenerate in Mineralized Bone?
(Cytoskeleton, 2024-12-09) Guerra, Rosa M.; Fowler, Velia M.; Wang, Liyun
Osteocytes, the most abundant bone cells, form an extensive cellular network via interconnecting dendrites. Like neurons in the brain, the long-lived osteocytes perceive mechanical and biological inputs and signal to other effector cells, leading to the homeostasis and turnover of bone tissues. Despite the appreciation of osteocytes' vital roles in bone biology, the initiation, growth, maintenance, and eventual degradation of osteocyte dendrites are poorly understood due to their full encasement by mineralized matrix. With the advancement of imaging modalities and genetic models, the architectural organization and molecular composition of the osteocyte dendrites, as well as their morphological changes with aging and diseases, have begun to be revealed. However, several long-standing mysteries remain unsolved, including (1) how the dendrites are initiated and elongated when a surface osteoblast becomes embedded as an osteocyte; (2) how the dendrites maintain a relatively stable morphology during their decades-long life span; (3) what biological processes control the dendrite morphology, connectivity, and stability; and (4) if these processes are influenced by age, sex, hormones, and mechanical loading. Our review of long, thin actin filament (F-actin)-containing processes extending from other cells leads to a working model that serves as a starting point to investigate the formation and maintenance of osteocyte dendrites and their degradation with aging and diseases.
Mechanical Properties of the Cortex in Older Adults and Relationships With Personality Traits
(Human Brain Mapping, 2025-02-06) Twohy, Kyra E.; Kramer, Mary K.; Diano, Alexa M.; Bailey, Olivia M.; Delgorio, Peyton L.; McIlvain, Grace; McGarry, Matthew D. J.; Martens, Christopher R.; Schwarb, Hillary; Hiscox, Lucy V.; Johnson, Curtis L.
Aging and neurodegeneration impact structural brain integrity and can result in changes to behavior and cognition. Personality, a relatively stable trait in adults as compared to behavior, in part relies on normative individual differences in cellular organization of the cerebral cortex, but links between brain structure and personality expression have been mixed. One key finding is that personality has been shown to be a risk factor in the development of Alzheimer's disease, highlighting a structure–trait relationship. Magnetic resonance elastography (MRE) has been used to noninvasively study age-related changes in tissue mechanical properties because of its high sensitivity to both the microstructural health and the structure–function relationship of the tissue. Recent advancements in MRE methodology have allowed for reliable property recovery of cortical subregions, which had previously presented challenges due to the complex geometry and overall thin structure. This study aimed to quantify age-related changes in cortical mechanical properties and the relationship of these properties to measures of personality in an older adult population (N = 57; age 60–85 years) for the first time. Mechanical properties including shear stiffness and damping ratio were calculated for 30 bilateral regions of the cortex across all four lobes, and the NEO Personality Inventory (NEO-PI) was used to measure neuroticism and conscientiousness in all participants. Shear stiffness and damping ratio were found to vary widely across regions of the cortex, upward of 1 kPa in stiffness and by 0.3 in damping ratio. Shear stiffness changed regionally with age, with some regions experiencing accelerated degradation compared to neighboring regions. Greater neuroticism (i.e., the tendency to experience negative emotions and vulnerability to stress) was associated with high damping ratio, indicative of poorer tissue integrity, in the rostral middle frontal cortex and the precentral gyrus. This study provides evidence of structure–trait correlates between physical mechanical properties and measures of personality in older adults and adds to the supporting literature that neurotic traits may impact brain health in cognitively normal aging.
MRI-based whole-brain elastography and volumetric measurements to predict brain age
(Biology Methods and Protocols, 2024-11-20) Claros-Olivares, Claudio Cesar; Clements, Rebecca G.; McIlvain, Grace; Johnson, Curtis L.; Brockmeier, Austin J.
Brain age, as a correlate of an individual’s chronological age obtained from structural and functional neuroimaging data, enables assessing developmental or neurodegenerative pathology relative to the overall population. Accurately inferring brain age from brain magnetic resonance imaging (MRI) data requires imaging methods sensitive to tissue health and sophisticated statistical models to identify the underlying age-related brain changes. Magnetic resonance elastography (MRE) is a specialized MRI technique which has emerged as a reliable, non-invasive method to measure the brain’s mechanical properties, such as the viscoelastic shear stiffness and damping ratio. These mechanical properties have been shown to change across the life span, reflect neurodegenerative diseases, and are associated with individual differences in cognitive function. Here, we aim to develop a machine learning framework to accurately predict a healthy individual’s chronological age from maps of brain mechanical properties. This framework can later be applied to understand neurostructural deviations from normal in individuals with neurodevelopmental or neurodegenerative conditions. Using 3D convolutional networks as deep learning models and more traditional statistical models, we relate chronological age as a function of multiple modalities of whole-brain measurements: stiffness, damping ratio, and volume. Evaluations on held-out subjects show that combining stiffness and volume in a multimodal approach achieves the most accurate predictions. Interpretation of the different models highlights important regions that are distinct between the modalities. The results demonstrate the complementary value of MRE measurements in brain age models, which, in future studies, could improve model sensitivity to brain integrity differences in individuals with neuropathology.
Actin Polymerization Status Regulates Tenocyte Homeostasis Through Myocardin-Related Transcription Factor-A
(Cytoskeleton, 2024-11-27) West, Valerie C.; Owen, Kaelyn E.; Inguito, Kameron L.; Ebron, Karl Matthew M.; Reiner, Tori N.; Mirack, Chloe E.; Le, Christian H.; Marqueti, Rita de Cassia; Snipes, Steven; Mousavizadeh, Rouhollah; King, Rylee E.; Elliott, Dawn M.; Parreno, Justin
The actin cytoskeleton is a potent regulator of tenocyte homeostasis. However, the mechanisms by which actin regulates tendon homeostasis are not entirely known. This study examined the regulation of tenocyte molecule expression by actin polymerization via the globular (G-) actin-binding transcription factor, myocardin-related transcription factor-a (MRTF). We determined that decreasing the proportion of G-actin in tenocytes by treatment with TGFβ1 increases nuclear MRTF. These alterations in actin polymerization and MRTF localization coincided with favorable alterations to tenocyte gene expression. In contrast, latrunculin A increases the proportion of G-actin in tenocytes and reduces nuclear MRTF, causing cells to acquire a tendinosis-like phenotype. To parse out the effects of F-actin depolymerization from regulation by MRTF, we treated tenocytes with cytochalasin D. Exposure of cells to cytochalasin D increases the proportion of G-actin in tenocytes. However, as compared to latrunculin A, cytochalasin D has a differential effect on MRTF localization by increasing nuclear MRTF. This led to an opposing effect on the regulation of a subset of genes. The differential regulation of genes by latrunculin A and cytochalasin D suggests that actin signals through MRTF to regulate a specific subset of genes. By targeting the deactivation of MRTF through the inhibitor CCG1423, we verify that MRTF regulates Type I Collagen, Tenascin C, Scleraxis, and α-smooth muscle actin in tenocytes. Actin polymerization status is a potent regulator of tenocyte homeostasis through the modulation of several downstream pathways, including MRTF. Understanding the regulation of tenocyte homeostasis by actin may lead to new therapeutic interventions against tendinopathies, such as tendinosis.
Muscular, temporal, and spatial responses to shoulder exosuit assistance during functional tasks
(Journal of Neurophysiology, 2024-11-01) Burch, Kaleb; Higginson, Jill
Shoulder exosuits are a promising new technology that could enable individuals with neuromuscular impairments to independently perform activities of daily living, however, scarce evidence exists to evaluate their ability to support such activities. Consequently, it is not understood how humans adapt motion in response to assistance from a shoulder exosuit. In this study, we developed a cable-driven shoulder exosuit and evaluated its effect on reaching and drinking tasks within a cohort of 18 healthy subjects to quantify changes to muscle activity and kinematics as well as trial-to-trial learning in duration and actuator switch timing. The exosuit successfully reduced mean muscle activity in the middle (reaching: 23.4 ± 26.3%, drinking: 20.0 ± 25.1%) and posterior (reaching: 12.8 ± 10.3%, drinking: 4.0 ± 7.2%) deltoid across both functional tasks. Likewise, the exosuit reduced integrated muscle activity in the middle deltoid (reaching: 22.2 ± 22.7%, drinking: 14.9 ± 27.0%). Exosuit assistance also altered kinematics such that individuals allowed their arms to follow forces applied by the exosuit. In terms of learning, subjects reduced movement duration by 15.6 ± 11.9% as they practiced using the exosuit. Reducing movement duration allowed subjects to reduce integrated muscle activity in the anterior (15.2 ± 10.3%), middle (14.7 ± 9.7%), and posterior (14.8 ± 9.7%) deltoids. Similarly, subjects activated the actuator switch earlier over the course of many assisted trials. The muscle activity reductions during both reaching and drinking demonstrate the promise of shoulder exosuits to enable independent function among individuals with neuromuscular impairments. The kinematic response to assistance and learning features observed in movement duration provide insight into human-exosuit interaction principles that could inform future exosuit development. NEW & NOTEWORTHY Shoulder exosuits assist arm function, but it is not understood how assistance affects motion. We evaluated spatiotemporal movement features and muscle activity during assisted and unassisted arm motions. Introducing the exosuit caused individuals to let their arms follow assistive forces. Furthermore, individuals learned to use the exosuit with practice by moving more quickly to reduce cumulative effort and by activating assistance earlier. These results demonstrate that individuals adapt exosuit-assisted motion to reduce effort.
Transforming CO2 into advanced 3D printed carbon nanocomposites
(Nature Communications, 2024-12-04) Crandall, Bradie S.; Naughton, Matthew; Park, Soyeon; Yu, Jia; Zhang, Chunyan; Mahtabian, Shima; Wang, Kaiying; Liang, Xinhua; Fu, Kelvin; Jiao, Feng
The conversion of CO2 emissions into valuable 3D printed carbon-based materials offers a transformative strategy for climate mitigation and resource utilization. Here, we 3D print carbon nanocomposites from CO2 using an integrated system that electrochemically converts CO2 into CO, followed by a thermocatalytic process that synthesizes carbon nanotubes (CNTs) which are then 3D printed into high-density carbon nanocomposites. A 200 cm2 electrolyzer stack is integrated with a thermochemical reactor for more than 45 h of operation, cumulatively synthesizing 37 grams of CNTs from CO2. A techno-economic analysis indicates a 90% cost reduction in CNT production on an industrial scale compared to current benchmarks, underscoring the commercial viability of the system. A 3D printing process is developed that achieves a high nanocomposite CNT concentration (38 wt%) while enhancing composite structural attributes via CNT alignment. With the rapidly rising demand for carbon nanocomposites, this CO2-to-nanocomposite process can make a substantial impact on global carbon emission reduction efforts.
Design and Evaluation of 3D-Printed Lattice Structures as High Flow Rate Aerosol Filters
(ACS Applied Engineering Materials, 2024-12-11) Yu, Yinkui; Zhang, Ning; Hoffman, Dominic; Rastogi, Dewansh; Woodward, Ian R.; Fromen, Catherine A.
Aerosol contamination presents significant challenges across various industries, ranging from healthcare to manufacturing. Over the past few years, open foam filters have gained prominence for their ability to efficiently capture particles while allowing reasonable airflow. In this work, we present the use of 3D-printed idealized open foam-like lattice structures as aerosol filtration media, leveraging advances in additive manufacturing to generate these highly tunable and modular filters. Using parametric design approaches, we fabricated lattice filters with four different unit cell geometries (Cubic, Kelvin, Octahedron, and Weaire–Phelan) via Digital Light Synthesis 3D printing and characterized these structures with X-ray microcomputed tomography. We compared the aerosol filtration performance of the different lattice unit cell geometries using 1 μm polystyrene latex (PSL) aerosol particles, finding the filtration performance to be positively correlated with the single-unit-cell specific surface area. We then expanded our evaluation of deposition efficiency in Kelvin cell lattice structures of varied porosities, again finding a correlation between the specific surface area and deposition performance. Experimental analysis confirmed that deposition primarily occurs through impaction and electrostatic mechanisms within the parameter space. Overall, our findings demonstrate that unit-cell-based lattices can achieve a wide range of aerosol filtration efficiencies (∼10–100%) across various operating conditions (1–4 m/s superficial velocity), offering a highly tunable in-line filtration medium capable of maintaining high efficiency even at elevated airflow rates. This work not only provides essential guidelines for designing and manufacturing 3D-printed lattices as customizable aerosol filters but also highlights the current limitations and challenges in producing these structures.
Zonal patterning of extracellular matrix and stromal cell populations along a perfusable cellular microchannel
(Lab on a Chip, 2024-10-21) Chernokal, Brea; Ferrick, Bryan J.; Gleghorn, Jason P.
The spatial organization of biophysical and biochemical cues in the extracellular matrix (ECM) in concert with reciprocal cell–cell signaling is vital to tissue patterning during development. However, elucidating the role an individual microenvironmental factor plays using existing in vivo models is difficult due to their inherent complexity. In this work, we have developed a microphysiological system to spatially pattern the biochemical, biophysical, and stromal cell composition of the ECM along an epithelialized 3D microchannel. This technique is adaptable to multiple hydrogel compositions and scalable to the number of zones patterned. We confirmed that the methodology to create distinct zones resulted in a continuous, annealed hydrogel with regional interfaces that did not hinder the transport of soluble molecules. Further, the interface between hydrogel regions did not disrupt microchannel structure, epithelial lumen formation, or media perfusion through an acellular or cellularized microchannel. Finally, we demonstrated spatially patterned tubulogenic sprouting of a continuous epithelial tube into the surrounding hydrogel confined to local regions with stromal cell populations, illustrating spatial control of cell–cell interactions and signaling gradients. This easy-to-use system has wide utility for modeling three-dimensional epithelial and endothelial tissue interactions with heterogeneous hydrogel compositions and/or stromal cell populations to investigate their mechanistic roles during development, homeostasis, or disease.
Global and local identifiability analysis of a nonlinear biphasic constitutive model in confined compression
(Journal of the Royal Society Interface, 2024-11-13) Peloquin, John M.; Elliott, Dawn M.
Application of biomechanical models relies on model parameters estimated from experimental data. Parameter non-identifiability, when the same model output can be produced by many sets of parameter values, introduces severe errors yet has received relatively little attention in biomechanics and is subtle enough to remain unnoticed in the absence of deliberate verification. The present work develops a global identifiability analysis method in which cluster analysis and singular value decomposition are applied to vectors of parameter–output variable correlation coefficients. This method provides a visual representation of which specific experimental design elements are beneficial or harmful in terms of parameter identifiability, supporting the correction of deficiencies in the test protocol prior to testing physical specimens. The method was applied to a representative nonlinear biphasic model for cartilaginous tissue, demonstrating that confined compression data does not provide identifiability for the biphasic model parameters. This result was confirmed by two independent analyses: local analysis of the Hessian of a sum-of-squares error cost function and observation of the behaviour of two optimization algorithms. Therefore, confined compression data are insufficient for the calibration of general-purpose biphasic models. Identifiability analysis by these or other methods is strongly recommended when planning future experiments.
Conjugation of Antibodies and siRNA Duplexes to Polymer Nanoparticles via Maleimide–Thiol Chemistry
(ACS Omega, 2024-11-18) Hoover, Elise C.; Chowdhury, Chitran Roy; Ruggiero, Olivia M.; Day, Emily S.
Polymeric nanoparticles (NPs) have shown great promise as highly modifiable platforms that can be applied across many different disease states. They are advantageous because they can encapsulate a range of hydrophobic and hydrophilic cargoes while having customizable surface properties. Depending on the desired biointerfacing capabilities, the surface of polymeric NPs can be modified with moieties, such as antibodies, peptides, nucleic acids, and more. The work presented here is intended to provide mechanistic insight into how different parameters influence the loading of antibodies, small interfering ribonucleic acids (siRNAs), or both on the surface of poly(lactic-co-glycolic acid) (PLGA) NPs via maleimide–thiol chemistry. Some of the conjugation parameters investigated include the buffer concentration, maleimide to protein ratio, and the addition of an excipient such as Tween-20. Through variation in the concentration of FZD7 antibodies added to the reaction mixture, we established tunable conjugation and found the upper limit of their loading density under the conditions tested. We also confirmed antibody conjugation through two different mechanisms: via a thiol-modified antibody or a thiol-modified poly(ethylene glycol) (PEG) linker. Conjugation of thiolated siRNA duplexes targeting β-catenin was also investigated through variations in both Tween-20 concentration and CaCl2 buffer concentration. Finally, the coconjugation of both antibodies and siRNA duplexes was explored. Overall, this work outlines a basis for tunable biomolecule loading on polymer NPs using maleimide–thiol chemistry and reveals the incredible versatility of polymer NP platforms.
Sequestration of gene products by decoys enhances precision in the timing of intracellular events
(Scientific Reports, 2024-11-08) Biswas, Kuheli; Dey, Supravat; Singh, Abhyudai
Expressed gene products often interact ubiquitously with binding sites at nucleic acids and macromolecular complexes, known as decoys. The binding of transcription factors (TFs) to decoys can be crucial in controlling the stochastic dynamics of gene expression. Here, we explore the impact of decoys on the timing of intracellular events, as captured by the time taken for the levels of a given TF to reach a critical threshold level, known as the first passage time (FPT). Although nonlinearity introduced by binding makes exact mathematical analysis challenging, employing suitable approximations and reformulating FPT in terms of an alternative variable, we analytically assess the impact of decoys. The stability of the decoy-bound TFs against degradation impacts FPT statistics crucially. Decoys reduce noise in FPT, and stable decoy-bound TFs offer greater timing precision with less expression cost than their unstable counterparts. Interestingly, when both bound and free TFs decay at the same rate, decoy binding does not directly alter FPT noise. We verify these results by performing exact stochastic simulations. These results have important implications for the precise temporal scheduling of events involved in the functioning of biomolecular clocks, development processes, cell-cycle control, and cell-size homeostasis.

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