Polycaprolactone-based shape memory foams as self-fitting vaginal stents

Hicks, A. J.; Roberts, C.; Robinson, A.; Wilson, K.; Kotamreddy, V.; LaRue, T.; Veyssi, A.; Beltran, F.; Hakim, J.; Rausch, M. K.; Grunlan, M.; Cosgriff-Hernandez, E.

doi:10.1101/2024.01.26.577474

bioRxiv · 10.1101/2024.01.26.577474

Polycaprolactone-based shape memory foams as self-fitting vaginal stents

Hicks, A. J.·Roberts, C.·Robinson, A.·Wilson, K.·Kotamreddy, V.·LaRue, T.·Veyssi, A.·Beltran, F.·Hakim, J.·Rausch, M. K.·Grunlan, M.·Cosgriff-Hernandez, E.

View original source ↗Export metadata ↓

Abstract

There is an urgent critical need for a patient-forward vaginal stent that can prevent debilitating vaginal stenosis that occurs in up to 75% of patients who undergo pelvic radiation treatments and adolescent patients after vaginal reconstruction. To this end, we developed a self-fitting vaginal stent based on a shape-memory polymer (SMP) foam that can assume a secondary, compressed shape for ease of deployment. Upon insertion, the change in temperature and hydration initiates foam expansion to shape fit to the individual patient and restore the lumen of the stent to allow egress of vaginal secretions. To achieve rapid actuation at physiological temperature, we investigated the effect of architecture of two photocurable, polycaprolactone (PCL) macromers. Star-PCL-tetraacrylate displayed reduced melting temperature in the target range as compared to the linear-PCL-diacrylate. Emulsion-templating was then used to fabricate foams from 75:25 water-in-oil (W/O) emulsions that were subsequently annealed to yield high-porosity SMP foams. Upon axial shape memory testing, both foams displayed excellent shape fixity (90%); however, only the PCL star-foams displayed shape recovery ([~]84%) at 37{degrees}C to its permanent shape. A custom mold and curing system was then used to fabricate PCL star- foams into hollow, cylindrical stents. The stent was crimped to its temporary insertion shape (50% reduction in diameter, OD [~] 11 mm) with a custom radial crimper and displayed excellent shape fixity for deployment (> 95%) and shape recovery ([~] 100%). To screen vaginal stents, we developed a custom benchtop pelvic model that simulated vaginal anatomy, temperatures, and pressures with an associated computational model. A hysteroscope was used to visualize stent expansion and deformation via a scope port near the cervix of the benchtop model. A crimped SMP vaginal stent was deployed in the model and expanded to walls of the canal ([~]70% increase in cross-sectional area) in less than 5 minutes after irrigation with warm water. The vaginal stent demonstrated retention of vaginal caliber with less than 1% decrease in cross-sectional area under physiological pressure. Collectively, this work demonstrates the potential for SMP foams as self-fitting vaginal stents to prevent stenosis. Additionally, this work provides new open-source tools for the iterative design of other gynecological devices. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/577474v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1bc3162org.highwire.dtl.DTLVardef@4e5657org.highwire.dtl.DTLVardef@1069d33org.highwire.dtl.DTLVardef@13aa9da_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender

Source connections

Published article ↗

Explore related subjects

bioengineering Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Hicks, A. J., Roberts, C., Robinson, A., Wilson, K., Kotamreddy, V., LaRue, T., Veyssi, A., Beltran, F., Hakim, J., Rausch, M. K., Grunlan, M., Cosgriff-Hernandez, E.. 2024-01-30. Polycaprolactone-based shape memory foams as self-fitting vaginal stents. https://doi.org/10.1101/2024.01.26.577474

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Synergy-informed bilevel optimization reveals joint-specific benefits for realistic exoskeleton torque prediction

Simulation-driven optimization can guide exoskeleton control design, but its utility is limited by the accuracy with which muscle coordination is predicted. Strict effort-minimization formulations predict non-physiological muscle shutdown under high exoskeleton assistance, leading to peak assistive torques that exceed values reported in human-in-the-loop experiments. We evaluated the accuracy of synergy-informed simulations at predicting assistance across four single-joint exoskeleton configurations: ankle plantarflexion, knee extension, hip flexion, and hip abduction. We implemented a bilevel optimization to predict a parameterized assistive torque that minimizes metabolic cost, with assisted muscle dynamics estimated via either effort-minimization simulations (minimizing muscle effort only) or synergy-informed simulations (minimizing muscle effort constrained to a synergy structure). We used experimental data from five unimpaired adults walking at their preferred speed and compared results descriptively between the two formulations within each subject. Assistance based on effort-minimization simulations shut down agonist muscle activations and overestimated peak assistive torque compared with experimental values. In contrast, constraining muscle controls to a synergy structure prevented non-physiological muscle shutdown and yielded assistive torques closer to those measured in human-in-the-loop experiments. This benefit was not observed equally across all assisted degrees of freedom or subjects, emerging only where no single synergy could be suppressed to unload the assisted muscles. Synergy weights can therefore be interpreted as joint-specific predictors of when simulations can reliably inform wearable robot design.

bioengineering↗

bioRxiv2026

Engineered microvessel networks -- Longitudinal transcriptomic profiling validates chip-grown tissues as a robust model for studying vasculature

Vascularised Organ-on-Chip (OoC) models are promising New Approach Methodologies (NAMs), but their translation requires validation for defined Contexts of Use (CoU). Here, we combine microfluidic microvessel networks (MVNs) with longitudinal bulk and single-cell RNA sequencing to determine how cell provenance influences engineered vascular phenotype. Stromal cell identity produced distinct network architectures and transcriptional trajectories, demonstrating that support cells, commonly treated as interchangeable, represent an important CoU variable. Primary human pancreatic microvascular endothelial cells failed to form stable perfusable networks, but supplementation with 10% Human Umbilical Vein Endothelial Cells (HUVECs) or Blood Outgrowth Endothelial Cells (BOECs) rescued self-assembly. Single-cell transcriptomics identified specialised endothelial populations associated with vascular morphogenesis, including tip, stalk, phalanx, endothelial to mesenchymal transition (EndMT) and pericyte-like endothelial cells. Failed networks lacked coherent endothelial specialisation, whereas rescued networks restored stabilising cell states and revealed FLRT2--UNC5B signalling within pericyte-like HUVECs, recapitulating a pathway implicated in angiogenic development in vivo. These findings establish cell provenance as a critical determinant of microvascular NAM performance and demonstrate how transcriptomic validation can define and strengthen the biological relevance of microvessel-on-chip models for specific CoUs.

bioengineering↗

bioRxiv2026

Benchmarking foundation models for resting-state functional magnetic resonance imaging time series in cognitive aging research

Foundation models trained on large neuroimaging datasets could help smaller studies investigate cognition from brain recordings. However, whether the foundation model-derived representations improve assessment of current cognition, prediction of follow-up cognition, or characterization of cognitive change remains unclear. We evaluated nine configurations from five model families that process regional resting-state functional magnetic resonance imaging time series, using 3,103 scans from 1,653 participants across two observational and five intervention aging cohorts. Primary frozen representations showed no consistent superiority over conventional functional connectivity for concurrent cognitive associations or diagnostic classification. Changing the readout improved selected concurrent cognitive associations without updating model weights, indicating that performance depended partly on how representations were extracted. Additional post-training and embedding alignment yielded gains in selected settings but did not consistently improve performance across outcomes. In the primary longitudinal analyses, imaging representations did not establish added value beyond baseline clinical measures. These findings show that readout choice influences concurrent cognitive associations, while the added value of these representations for longitudinal outcomes remains unestablished.

bioengineering↗