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Proteomic comparison of intact and fetoscopy-induced fetal membrane defect sites
Item type: Journal Article
Moser, Lukas; Gegenschatz-Schmid, Katharina; Avilla-Royo, Eva; et al. (2025)
Background
Iatrogenic preterm premature rupture of fetal membranes (iPPROM) following fetoscopic interventions remains a major barrier to the advancement of fetal therapies. The mechanisms underlying iPPROM are poorly understood, but the inability of fetal membrane (FM) defects to heal spontaneously likely plays a key role, contrasting with the regenerative potential of amniotic membranes in other contexts.
Methods
To assess the impact of fetoscopic procedures on FMs, tissue samples from patients who underwent laser surgery for twin-to-twin transfusion syndrome (16–27 weeks gestation, n = 8) were collected after cesarean delivery at 29–35 weeks. Samples were categorized by proximity to the trocar site and analyzed using proteomic and histological methods.
Results
While differential expression analysis in the amnion revealed no significant changes, pathway enrichment indicated increased collagen deposition at defect sites. In the chorion, seven differentially expressed proteins were identified, largely linked to enhanced intercellular contact stability. These findings suggest the amnion may respond to mechanical stress by reinforcing structural integrity through collagen deposition, while the chorion may attempt to stabilize cell junctions. However, no other signs of tissue regeneration were observed.
Conclusion
This study provides molecular and cellular evidence that FMs lack a substantial healing response post-surgery, underscoring the need for biologically informed repair strategies.
Performance evaluation of pressure sensor mountings under two-phase high-speed flows in a low-level outlet
Item type: Conference Paper
Vögele, Janine; Boes, Robert; Albayrak, Ismail (2025)
Accurate pressure measurements are essential for understanding hydraulic flow conditions and designing hydraulic structures adequately. However, pressure measurements are challenging in dynamic two-phase flow conditions, where air bubbles can interfere with the sensor depending on its mounting characteristics. To this end, we systematically investigated the effects of three different sensor mountings (flush, single recess, and double recess) on dynamic pressure measurements in a low-level outlet laboratory model. The study's overall goal was to find a suitable sensor mounting type to measure dynamic uplift pressures on an invert slab in a laboratory spillway model. An absolute pressure sensor with a range of 750-1350 mbar was tested with all three mountings at distances of x = 3.8 m and x = 16.6 m from the sluice gate of the low-level outlet at ten different flow conditions, with contraction Froude numbers ranging from 12.0 to 19.3. Sensor mounting had the most significant impact in the upstream region, where highly dynamic flow conditions, such as shockwaves and jet impingement on the flume bed, occurred. The flush-mounted sensor with a membrane diameter of 19 mm measured significantly higher mean and fluctuating pressures compared to both recessed sensors. While this effect was also observed in the downstream region, it was less pronounced. Both single and double recessed sensors dampened low-frequency and high-energy large-scale pressure fluctuations in all scenarios because of the smaller opening diameters of 4 and 2 mm, respectively, exposing the sensor membranes less to the highly turbulent flow. Additionally, recessing the sensors introduced resonance peaks in the power spectral density at higher frequencies. These peaks occurred at lower frequencies than expected for a Helmholtz resonator due to air bubbles being trapped within the recess structure. The deeper depth of the double-recessed sensor helped prevent air bubble entrapment, leading to improved measurement accuracy. The effects of pump and vibrational frequencies on the measurements were relevant only in the downstream section where the flow was gradually varied with less impact of shockwaves and pressure fluctuations were less compared to those at the upstream section. The present findings provide a comprehensive assessment of sensor mounting effects under different flow scenarios and measurement locations, highlighting the importance of selecting an appropriate sensor mounting to ensure accurate pressure measurements in complex, two-phase flows. Based on the results, the flush-mounting of sensors is chosen for the final spillway model, as measurements of dynamic pressure fluctuations are the primary focus.
A unified intelligence-augmented framework for building audits via physical and virtual inspection
Item type: Journal Article
Wu, Pei-Yu; El-Assady, Mennatallah; De Wolf, Catherine (2026)
Building audits are essential for informed decision-making in maintenance, renovation, and end-of-life planning. However, current practices remain predominantly manual and time-consuming due to fragmented data, limiting resource-efficient management of existing building stock. This paper presents a unified, intelligence-augmented framework designed to enhance the efficiency and reliability of both physical and virtual building inspection workflows. Five core design principles of adaptability, accessibility, affordability, acceleration, and alignment are derived from a multi-phase formal analysis to guide the development of the R2PIVS pipeline, which transforms the existing audit process into six modules: retrieval, reality capture, prediction, interaction, visualization, and summarization. The framework leverages human-AI collaboration in key building inventory tasks, including geometry measurement, visual assessment, and hazard estimation, through interactive annotation, model refinement, and output validation. Findings from expert elicitation studies indicate that the proposed application schema is promising for improving the efficiency and scalability of existing workflows. By aligning machine learning capabilities with domain-specific requirements, this research lays the foundation for a human-in-the-loop building audit system that enables standardized inspection and inventory information management to support circular construction practices throughout the building life cycle.
Compressed sensing expands the multiplexity of imaging mass cytometry
Item type: Journal Article
Hosogane, Tsuyoshi; Santana, Leonor Schubert; Eling, Nils; et al. (2025)
The multiplexity of current antibody-based imaging is limited by the number of reporters that can be detected simultaneously. Compressed sensing can be used to reconstruct high-dimensional information from low-dimensional measurements. Previously, compressed sensing using composite in situ imaging (CISI) of transcriptomic data leveraged gene co-regulation structure to recover spatial expression of 37 RNA species from images of 11 composite channels. Here, we extend the CISI framework to protein expression data measured by imaging mass cytometry (IMC). CISI-IMC accurately recovers spatial expression of 16 immune and stromal marker proteins from images of 8 composite channels with an average Pearson's correlation of 0.8 across protein. Training the CISI-IMC framework using data collected on multiple human tissues enables universal decompression of composite data from a wide range of tumor and healthy tissue types. The expression dictionary and barcoding matrix described here are immediately implementable for general immune and stromal cell type classification, but CISI-IMC can in principle be applied to other markers or other antibody-based imaging methods. Our work lays the foundation for much higher plex protein imaging.
Predicting dose accumulation reliability at the planning stage, with an application to adaptive proton therapy
Item type: Journal Article
Smolders, Andreas; Lomax, Antony John; Albertini, Francesca (2026)
Objective. Online adaptive proton therapy could benefit from reoptimization that considers the total dose delivered in previous fractions. However, the accumulated dose is uncertain because of deformable image registration (DIR) uncertainties. This work aims to evaluate the accuracy of a tool predicting the dose accumulation reliability of a treatment plan, allowing consideration of this reliability during treatment planning. Approach. A previously developed deep-learning-based DIR uncertainty model was extended to calculate the expected DIR uncertainty only from the planning computed tomography (CT) and the expected dose accumulation uncertainty by including the planned dose distribution. For 5 lung cancer patients, the expected dose accumulation uncertainty was compared to the uncertainty of the accumulated dose of 9 repeated CTs. The model was then applied to several alternative treatment plans for each patient to evaluate its potential for plan selection. Results. The average accumulated dose uncertainty was close to the expected dose uncertainty for a large range of expected uncertainties. For high expected uncertainties, the model slightly overestimated the uncertainty. For individual voxels, errors up to 5% of the prescribed dose were common, mainly due to the daily dose distribution deviating from the plan and not because of inaccuracies in the expected DIR uncertainty. Despite the voxel-wise inaccuracies, the method proved suitable to select and compare treatment plans with respect to their accumulation reliability. Significance. Using our tool to select reliably accumulatable treatment plans can facilitate the use of accumulated doses during online reoptimization.