Search Results (114)

Effective evaluation of building fabric is essential to understanding building performance. Traditional methods, such as ISO 9869-1, provide point U-values but do not always capture the complete picture, and new measurement-led approaches are needed to support building retrofit. Heat3D is a novel iOS application that performs rapid U-value measurements of building elements by mapping thermographic images from a mobile infrared camera onto an augmented reality (AR) model of a room, from which heat flux across the element is calculated. A field trial of 22 UK properties during the 2019–2020 winter heating season assessed Heat3D’s heat flux measurements against traditional heat flux plates, with 90% of 295 Heat3D surveys falling within the combined uncertainty of the reference method. A second field trial, conducted over the 2020–2021 winter heating period, evaluated a new timelapse iteration of the method capable of measuring wall U-value within approximately 60 min; 90% of 42 Heat3D surveys fell within the combined confidence interval of the ISO 9869-1-measured U-value. These results indicate that Heat3D offers a viable, rapid alternative to traditional methods for both heat flux and U-value measurement. Full article

Tissue engineering is widely used in research for investigating cellular proliferation, behavior, and responses to various stimuli. However, the predictive value of preclinical studies using cell culture plates is limited by the inability to recapitulate the complexity of the physiological microenvironment. Synthetic three-dimensional (3D) scaffolds can be engineered to mimic the complex morphology of the extracellular matrix of native tissues and can serve as physiologically relevant platforms for preclinical studies. In this study, 3D electrospun scaffolds were characterized to aid in breast cancer research. Unlike previous studies that focused primarily on scaffold fabrication or cell viability, this work systematically evaluates how scaffold morphology influences breast epithelial and breast cancer cell behavior within three-dimensional microenvironments. Breast cancer cell lines and normal breast epithelial cells were seeded on scaffolds of different morphologies, on commercially available mesh scaffolds, and on standard tissue culture plates. Cells were treated with a fluorescent fructose mimic (ManCou-H) that targets the fructose-specific transporter GLUT5 to assess metabolic activity on different scaffolds. The study evaluated cell–cell and cell–matrix interactions through time-lapse experiments, cell metabolism, and variations in the expression of cytoskeletal protein (CK18) and GLUT5. Statistically relevant differences were observed between cells cultured on scaffolds and plates, and different scaffolds morphologies. Results from this study demonstrate that scaffold topology alone can significantly alter cellular phenotype and metabolic responses, highlighting the importance of scaffold selection in the development of predictive non-animal in vitro models and studies of the tumor microenvironment. Full article

Neurodegenerative diseases feature diverse pathological protein aggregates, including Lewy bodies in Alzheimer’s disease (AD) and skein-like filaments in amyotrophic lateral sclerosis (ALS). The physical mechanisms underlying this morphological diversity remain unclear. Here, we demonstrate that aggregation of the prion-like domain of hnRNPA1 (A1PrD), implicated in AD and ALS, is driven by solution composition and phase transition dynamics. Utilizing 3D timelapse and fluorescence lifetime imaging microscopy, we show that solution conditions modulate phase separation, gelation, and fibrillation, resulting in distinct structures such as fibril, gel, and starburst morphologies. Homotypic and heterotypic interactions between A1PrD and RNA were observed to shift the balance between pathological and physiological condensates. Importantly, amyloid-rich starbursts displayed prion-like infection capabilities toward amyloid-poor condensates. Our findings highlight how the interplay between solution composition and kinetic balances of liquid-liquid phase separation, gelation, and fibrillation shapes the diverse pathological aggregate morphologies characteristic of neurodegenerative diseases. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its consequences represent a growing global health burden that urgently requires physiologically relevant in vitro models beyond conventional 2D culture systems. In this study, we report the successful establishment of 45 patient-derived liver organoid lines. These organoids were generated from healthy, steatotic and cirrhotic tissues collected from 207 liver surgeries at RWTH University Hospital Aachen, with an initiation success rate of 82%. The organoids were propagated for at least six passages using an optimized protocol. Multiplex immunofluorescence analysis revealed highly proliferative structures with approximately 40% Ki-67-positive cells expressing hepatocyte (Albumin and HNF4α) and cholangiocyte (CK19) markers. Intermittent LGR5 staining suggested the presence of liver progenitor cell features. Quantitative PCR results confirmed variable HNF4α expression, indicating inter-patient heterogeneity in differentiation status. Time-lapse imaging combined with mathematical modeling uncovered a biphasic growth dynamic with an initial linear expansion in the first 15 h, followed by exponential growth (doubling time ≈ 20.6 h) between 30 and 72 h. Overall, our workflow produced genetically and phenotypically stable liver organoids that recapitulate essential features of various hepatic conditions. This provides a solid foundation for disease modeling, potential drug testing, and quantitative systems biology. Full article

Background: Embryoid bodies (EBs) play a central role in organoid engineering, where their formation fidelity and size critically influence downstream differentiation outcomes. Current EB production workflows primarily rely on retrospective quality assessment, which limits reproducibility in high-throughput culture systems. Objective: This study aimed to develop a prospective, non-invasive framework that integrates early-phase bright-field time-lapse imaging with a three-dimensional convolutional neural network to predict EB formation outcomes and final EB diameter within the microwell platform. Methods: Time-lapse image sequences collected during the first hours after cell seeding on the microwell array were used to train 3D-CNN models for classification (formation vs. non-formation) and regression (final diameter). A balanced dataset was constructed through under-sampling, and five-fold cross-validation with data augmentation was applied to evaluate model performance. Results: The classification model achieved an accuracy of 96.5%, reliably distinguishing between successful and failed EB formation using short-duration image sequences. The regression model predicted the final EB diameter with a mean absolute error of ±7.1 µm, reflecting strong agreement with measured values and capturing seeding-density-dependent size variations. Conclusions: Early aggregation dynamics captured by bright-field time-lapse imaging contain sufficient spatiotemporal information to enable accurate, prospective EB quality prediction. The proposed framework provides a label-free and automation-compatible strategy for improving reproducibility in large-scale EB manufacturing and supports the future development of adaptive and closed-loop organoid culture systems for clinical applications. Full article

Accurate classification of precipitation phase (liquid, mixed, or solid) is essential in high mountain environments, where rapid changes in elevation can lead to abrupt phase transitions over short distances, significantly affecting hydro-meteorological, ecological, and socio-economic activities. However, most existing classification schemes have not been evaluated over long periods using real observational data, but mainly through simulations. This study addresses this gap by introducing a new methodology based on X-band polarimetric radar and by validating it against real precipitation events over an extended time period. The machine learning model is trained and tested using a four-year dataset including X-band radar, Micro Rain Radar, disdrometer, and temperature profile data from the Grenoble region (French Alps). To improve the classification accuracy, three temperature profile sources were tested: lapse rates obtained from automatic weather stations, interpolation of the temperature profile from the freezing level detected by the Micro Rain Radar, and temperature profiles from the operational AROME model forecast. Three different phase classification schemes were tested: two existing schemes based on fuzzy-logic, and the new method based on random forest. Results show that the random forest method, trained with radar polarimetric variables, AROME temperature profiles, and target labels derived from Micro Rain Radar observations, achieves the highest accuracy. Despite the overall good classification results, limitations persist in identifying mixed-phase precipitation due to its transitional nature and vertical variability. Feature importance analysis indicates that temperature is the most influential variable in the classification scheme, followed by reflectivity factor measured in the horizontal plane ($Z_e)$ and differential reflectivity ($Z_{dr})$. This methodology demonstrates the potential of combining machine learning techniques with multi-instrument observations to improve hydrometeor classification in complex terrain. The approach offers valuable insights for operational forecasting, water resource management, and climate impact assessments in mountainous regions. Full article

In the context of reservoir monitoring, time-lapse (4D) full-waveform inversion (FWI) of seismic data can potentially estimate reservoir changes with high resolution. However, most existing field-data applications are carried out with isotropic, and often acoustic, FWI algorithms. Here, we apply a time-lapse FWI methodology for transversely isotropic (TI) media with a vertical symmetry axis (VTI) to offshore streamer data acquired at Pyrenees field in Australia. We explore different objective functions, including those based on global correlation (GC) and designed to mitigate errors in the source signature (SI, or source-independent). The GC objective function, which utilizes mostly phase information, produces the most accurate inversion results by mitigating the difficulties associated with amplitude matching of the synthetic and field data. The SI FWI algorithm is generally more robust in the presence of distortions in the source wavelet than the other two methods, but its application to field data is hampered by reliance on amplitude matching. Taking anisotropy into account provides a better fit to the recorded data, especially at far offsets. In addition, the application of the anisotropic FWI improves the flatness of the major reflection events in the common-image gathers (CIGs). The 4D response obtained by FWI reveals time-lapse parameter variations likely caused by the reservoir gas coming out of solution and by the replacement of gas with oil. Full article

Macrophages are critical to the formation of infection- and non-infection-associated immune structures such as cancer spheroids, pathogen-, and non-pathogen-associated granulomas, contributing to the spatiotemporal and chemical immune response and eventual outcome of disease. While well established in cancer immunology, the prevalence of using three-dimensional (3D) cultures to characterize later-stage structural immune response in pathogen-associated granulomas continues to increase, generating valuable insights for empirical and computational analysis. To enable integration of data from 3D in vitro studies with the vast bibliome of standard two-dimensional (2D) tissue culture data, methods that determine concordance between 2D and 3D immune response need to be established. Focusing on macrophage migration and oxidative species production, we develop experimental and computational methods to enable concurrent spatiotemporal and biochemical characterization of 2D versus 3D macrophage–mycobacterium interaction. We integrate standard biological sampling methods, time-lapse confocal imaging, and 4D quantitative image analysis to develop a 3D ex vivo model of Mycobacterium smegmatis infection using bone-marrow-derived macrophages (BMDMs) embedded in reconstituted basement membrane (RBM). Comparing features of 2D to 3D macrophage response that contribute to control and resolution of bacteria infection, we determined that macrophages in 3D environments increased production of reactive species, motility, and differed in cellular volume. Results demonstrate a viable and extensible approach for comparison of 2D and 3D datasets and concurrent biochemical plus spatiotemporal characterization of initial macrophage structural response during infection. Full article

Cell observation is crucial in life science research, and advancements in microscopy are essential for deciphering biological phenomena. These technological developments have significantly enhanced our understanding of cellular mechanisms and processes. Light, characterized by its wave-like properties, is fundamental to scientific observation. Recently, new technologies have been developed to detect changes in light wavelengths upon illumination, using them as signals for visualization. Three-dimensional optical wave field microscopy (3D-OWFM), a recent innovation in optimal imaging, leverages the wave properties of light to capture objects without labels, invasive procedures, or direct contact, thus facilitating non-invasive observation. In this study, we observed and analyzed mammalian cell structure and behaviors using 3D-OWFM. The 3D-OWFM revealed the intrinsic structure of the cells, including the cytoplasm and nucleus, with high clarity. The optical path difference (OPD) intensity effectively highlighted nuclear complexity. Furthermore, time-lapse imaging captured cell division process through variations in OPD signal intensity. These findings indicate that 3D-OWFM has significant potential for cell observation, offering insights not attainable with conventional microscopes. Full article

Murine microglia exhibit rapid self-renewal upon removal from the postnatal brain. However, the signaling pathways that regulate microglial repopulation remain largely unclear. To address this knowledge gap, we depleted microglia from mixed glial cultures using anti-CD11b magnetic particles and cultured them for 4 weeks to monitor their repopulation ability in vitro. Flow cytometry and immunocytochemistry revealed that anti-CD11b bead treatment effectively eliminated >95% of microglia in mixed glial cultures. Following removal, the number of CX3CR1-positive microglia gradually increased; when a specific threshold was reached, repopulation ceased without any discernable rise in cell death. Cell cycle and 5-ethynyl-2′-deoxyuridine incorporation assays suggested the active proliferation of repopulating microglia at d7. Time-lapse imaging demonstrated post-removal division of microglia. Colony-stimulating factor 1 receptor-phosphoinositide 3-kinase-protein kinase B signaling was identified as crucial for microglial repopulation, as pharmacological inhibition or neutralization of the pathway significantly abrogated repopulation. Transwell cocultures revealed that resident microglia competitively inhibited microglial proliferation probably through contact inhibition. This in vitro microglial removal system provides valuable insights into the mechanisms underlying microglial proliferation. Full article

Background: Sperm selection is critical in assisted reproduction, typically relying on swim-up and centrifugation density gradients. New methods, such as PICSI (physiological intracytoplasmic sperm selection), aim to enhance outcomes by selecting mature sperm based on hyaluronic acid (HA) binding and have generated interest due to their potential impact on the clinical outcomes of patients who undergo assisted reproductive treatments. Methods: A single-center, prospective, and triple-blinded study was conducted with 277 couples in the egg donation program. The oocytes of each recipient patient were randomly microinjected using the ICSI or PICSI technique and maintained in culture in time-lapse incubators until blastocyst formation. Biological and clinical outcomes were analyzed, including fertilization and blastocyst formation rates, embryo morphokinetics, pregnancy, miscarriage, and live birth rates, and artificial intelligence-assigned embryo quality scores. Results: Clinical outcomes were comparable between the two groups, but a higher pregnancy rate was observed in the PICSI group than in the ICSI group (74.04% vs. 70.87%). Although blastocyst formation rates were similar on both day 5 (D5) and day 6 of development, the proportion of good-quality embryos on D5 was higher in the PICSI group (68.27%) than in the ICSI group (63.47%) (p > 0.05). Finally, the cumulative pregnancy rate was significantly higher in the experimental group than in the control group (88% vs. 72%) after four embryo transfers (p < 0.05). Conclusions: Utilizing HA to perform sperm selection during ICSI procedures does not increase live birth rates. However, it may enhance the quality of the selected sperm. This could be beneficial for patients in egg donation programs, particularly for those who have experienced repeated pregnancy loss. Full article

Time-lapse imaging has made possible the detailed observation of all stages of embryonic development, including also from the extrusion of the second polar body up to the first cleavage. By extensive observation, we achieved detection of a variety of behaviors of PBIIs such as (a) morphologically static behavior, (b) amoeboid movement, (c) shrinking, (d) fragmenting, and (e) ruffling. Retrospective analysis was performed on 282 ICSI zygotes derived from 69 ART treatment cycles from January to August 2019. Zygotes with morphologically static PBIIs (a) and PBIIs showing various behaviors (b)~(e) were classified into Group 1 (n = 70) and Group 2 (n = 212), respectively. Based on the rates of irregular division, good quality embryos, and the time from the PBII extrusion, pronuclear breakdown to the first cleavage was compared between groups (Study 1). Furthermore, the relationship between the type of PBII behaviors and ploidy in 94 biopsied blastocysts from 15 cycles was examined, in which one or more euploid embryos were obtained between August 2021 and July 2024 (Study 2). The results showed that good quality embryos tended to have morphologically static PBIIs, and that euploid embryos were absent in embryos with fragmenting and ruffling PBIIs. The behavior of PBIIs may be a new predictor of embryonic developmental potential, and, in the future, morphokinetic behaviors of PBIIs may be a useful parameter for AI-assisted embryo evaluation systems. Full article

In this study, we used machine learning (ML) to estimate time-lapse velocity variations in a reservoir region using seismic data. To accomplish this task, we needed an adequate training set that could map seismic data to velocity perturbation. We generated a synthetic seismic database by simulating reservoirs of varying velocities using a 2D velocity model typical of the Brazilian pre-salt ocean bottom node (OBN) acquisition, located in the Santos basin, Brazil. The largest velocity change in the injector well was around 3% of the empirical velocity model, which mimicked a realistic scenario. The acquisition geometry was formed by the geometry of 1 shot and 49 receivers. For each synthetic reservoir, the corresponding seismic data were obtained by estimating a one-shot forward-wave propagation using acoustic approximation. We studied the reservoir illumination to optimize the input data of the ML inversion. We split the set of synthetic reservoirs into two subsets: training (80%) and testing (20%) sets. We point out that the ML inversion was restricted to the reservoir zone, which means that it was inversion-oriented to a target. We obtained a good similarity between true and ML-inverted reservoir anomalies. The similarity diminished for a situation with non-repeatability noise. Full article

Shear stress plays a crucial role in modulating cell adhesion and signaling. We present a microfluidic shear stress generator used to investigate the adhesion dynamics of Dictyostelium discoideum, an amoeba cell model organism with well-characterized adhesion properties. We applied shear stress and tracked cell adhesion, motility, and detachment using time-lapse videomicroscopy. In the precise shear conditions generated on-chip, our results show cell migration patterns are influenced by shear stress, with cells displaying an adaptive response to shear forces as they alter their adhesion and motility behavior. Additionally, we observed that DH1-10 wild-type D. discoideum cells exhibit stronger adhesion and resistance to shear-induced detachment compared to phg2 adhesion-defective mutant cells. We also highlight the influence of cell density on detachment kinetics. Full article

Time-lapse ground-penetrating radar (GPR) surveys, combined with automated infiltration experiments, provide a non-invasive approach for investigating the distribution of infiltrated water within the soil medium and creating three-dimensional images of the wetting bulb. This study developed and validated an experimental protocol aimed at quantifying and visualizing water distribution fluxes in layered soils under both unsaturated and saturated conditions. The 3D images of the wetting bulb significantly enhanced the interpretation of infiltration data, enabling a detailed analysis of water movement through the layered system. We used the infiltrometer data and the Beerkan Estimation of Soil Transfer parameters (BEST) method to determine soil capacitive indicators and evaluate the physical quality of the upper soil layer. The field survey involved conducting time-lapse GPR surveys alongside infiltration experiments between GPR repetitions. These experiments included both tension and ponding tests, designed to sequentially activate the soil matrix and the full pore network. The results showed that the soil under study exhibited significant soil aeration and macroporosity (represented by AC and p_MAC), while indicators related to microporosity (such as PAWC and RFC) were notably low. The RFC value of 0.55 m³ m⁻³ indicated the soil’s limited capacity to retain water relative to its total pore volume. The PAWC value of 0.10 m³ m⁻³ indicated a scarcity of micropores ranging from 0.2 to 30 μm in diameter, which typically hold water accessible to plant roots within the total porosity. The saturated soil hydraulic conductivity, K_s, values ranged from 192.2 to 1031.0 mm h⁻¹, with a mean of 424.4 mm h⁻¹, which was 7.9 times higher than the corresponding unsaturated hydraulic conductivity measured at a pressure head of h = −30 mm (K₋₃₀). The results indicated that the upper soil layer supports root proliferation and effectively drains excess water to the underlying limestone layer. However, this layer has limited capacity to store and supply water to plant roots and acts as a restrictive barrier, promoting non-uniform downward water movement, as revealed by the 3D GPR images. The observed difference in hydraulic conductivity between the two layers suggests that surface ponding and overland flow are generated through a saturation excess mechanism. Water percolating through the soil can accumulate above the limestone layer, creating a shallow perched water table. During extreme rainfall events, this water table may rise, leading to the complete saturation of the soil profile. Full article