Search Results (132)

Carbonate reservoirs exhibit complex combinations of pores, fractures, and vugs, and their strong heterogeneity makes pore-scale displacement mechanisms and recovery enhancement difficult to predict. In this study, six microfluidic glass-etched models representative of pore-type, vuggy, and fracture-pore carbonate reservoirs were designed from cast thin sections of the S oilfield. Experiments were conducted to investigate the effects of different factors on microscopic displacement behavior and residual-oil distribution. The results show that microscopic residual oil in carbonate reservoirs mainly occurs as film flow, droplet flow, columnar flow, multi-pore flow, and cluster flow, with cluster flow dominating the late stage of development in all model types. Under waterflooding, pore-type reservoirs exhibit the most uniform sweep and the highest recovery factor (44.26%), whereas vuggy reservoirs readily develop preferential flow channels and show the lowest recovery factor (41.58%). For fracture-pore reservoirs, injection perpendicular to the fracture provides the best performance, and wider or denser fractures improve displacement efficiency. Compared with gas flooding, waterflooding increases recovery by 10.48% in pore-type reservoirs and by 16.44% in fracture-type reservoirs. High-rate waterflooding and mid-stage flow diversion further improve recovery by 9.05–10.87% and 17.12–19.63%, respectively. These results provide pore-scale evidence for optimizing development strategies for carbonate reservoirs. Full article

Intramuscular fat (IMF) marbling is a key determinant of beef quality, yet predicting how breed-specific gene expression translates into tissue-scale fat patterning remains a major challenge. Using a small public transcriptomic dataset (n = 3 per breed), this study presents a proof-of-concept omics-to-tissue modeling framework that converts RNA-seq data into biophysically interpretable parameters governing intramuscular adipogenesis. Using transcriptomic profiles from GSE161967 (Japanese Black Wagyu versus Chinese Red Steppes), we derived composite indices capturing the adipogenic commitment (φ) and lipid droplet capacity (ψ) from curated gene modules. These indices were mapped via calibrated linear functions to a Cellular Potts Model (CPM), parameterizing the fibro-adipogenic progenitor (FAP) differentiation probability, lipogenesis rate, adipocyte cohesion, and progenitor abundance. The gene-derived parameters placed Wagyu in a high-adipogenic regime ($p_{F\to A}^{\mathrm{base}}$ = 0.65; $k_{lipogenesis}$ = 0.12), while Chinese Red Steppes resided in a low-adipogenic regime (0.25; 0.04). The CPM simulations revealed a sharp, predictive threshold at $p_{F\to A}^{\mathrm{base}}$ ≈ 0.55, below which IMF remained negligible and above which stable adipocyte clusters and 8–9% IMF emerged. Without post hoc tuning, the gene-derived parameters correctly predicted robust marbling in Wagyu and a lean phenotype in Chinese Red Steppes. A sensitivity analysis identified the adipogenic commitment as the primary control parameter, with lipogenesis acting as an amplifier. Together, these results demonstrate that transcriptomic measurements can quantitatively predict emergent marbling phenotypes through a small set of interpretable biophysical parameters, establishing a generalizable framework for forecasting complex tissue traits from omics data. Full article

Background/Objectives: Milk somatic cells reflect the cellular composition and functional state of the lactating mammary gland and represent a valuable, non-invasive source for transcriptomic studies. Single-cell RNA sequencing (scRNA-seq) enables cell-type-resolved analysis of bovine milk; however, sequencing depth strongly influences the detection of lowly expressed genes and the resolution of transcriptional cell states. The aim of this study was to further characterise the single-cell transcriptome of bovine milk somatic cells, with particular emphasis on high-resolution gene expression profiling and cellular heterogeneity. Methods: Milk somatic cells were isolated from two healthy Holstein Friesian cows in mid-lactation and profiled using a droplet-based scRNA-seq platform. Newly generated high-depth datasets were integrated with two previously published bovine milk scRNA-seq datasets using an identical bioinformatics pipeline. Data integration, clustering and cell-type annotation were performed using the Seurat framework, and transcription factor expression was evaluated across datasets with different sequencing depths. Results: Single-cell transcriptomic analysis revealed a diverse cellular landscape in bovine milk, comprising epithelial, progenitor, and immune cell populations. Unsupervised clustering identified 21 transcriptionally distinct clusters, including multiple CD8⁺ T-cell subpopulations, monocytes, neutrophils, mast cells, and B cells, as well as luminal epithelial and luminal progenitor cells. While overall cell-type composition was comparable across datasets, deeply sequenced samples exhibited higher transcriptomic complexity and enabled refined resolution of immune and epithelial subpopulations. Deeper sequencing facilitated the detection of low-abundance transcription factors that were not observed in lower-depth datasets. Among these, NANOG was detected exclusively in deeply sequenced samples, suggesting the presence of rare transcriptional states associated with cellular plasticity. Conclusions: This study expands the single-cell transcriptomic landscape of bovine milk somatic cells and demonstrates the importance of sequencing depth for resolving functional cellular heterogeneity. The results highlight milk as a powerful, non-invasive source for investigating mammary gland biology and cellular plasticity during lactation. Full article

Despite extensive pore-scale studies on oil–water displacement, quantitative understanding of the dynamic evolution of residual oil morphology and waterflooding efficiency in geologically heterogeneous sandstones remains limited, particularly under large water-injection multiples. To better understand pore-scale oil–water distribution and its influence on enhanced oil recovery, this study utilized Micro-CT combined with SEM-EDS to examine the 3D pore structure and oil–water phase evolution in a heterogeneous sandstone sample from the Xiayang Formation, Wushi Sag, Zhanjiang. Mineralogical analyses reveal that dolomite cementation and vermicular kaolinite infilling introduce strong pore-scale heterogeneity by selectively reducing pore connectivity and permeability, posing challenges for uniform fluid displacement. A 30% KI solution was used to enhance X-ray attenuation of the aqueous phase, enabling clear discrimination between oil and water. Micro-CT reconstructions reveal a relatively uniform pore network dominated by medium-to-large intergranular pores. As the water-injection multiple increases, water progressively invades larger pores, while residual oil is immobilized by capillary forces within micro-throats, forming isolated clusters. The oil-droplet size distribution broadens from a narrow range (50–100 µm) to a wider one (200–300 µm), indicating interfacial destabilization and droplet coalescence. Quantitative analysis indicates that oil saturation decreases from approximately 90% to 36%, while waterflooding efficiency increases rapidly to ~45% at 1 PV and gradually approaches a plateau of ~60% beyond 500–1000 PV. This waterflooding plateau is attributed to capillary trapping and pore-scale connectivity limitations imposed by mineral-induced heterogeneity, which prevent further mobilization of residual oil despite continued water injection. This study advances pore-scale waterflooding research by combining mineralogical heterogeneity with long-term micro-CT imaging, revealing the pore-scale mechanisms controlling residual oil evolution and ultimate waterflooding limits in realistic sandstone. Full article

The accurate assessment of tailings dam operational status and timely risk warnings are critical for ensuring their safe operation. To address the limitations of existing models in managing complex environments and multidimensional risk factors, this study proposes an early warning model for tailings dam operational status based on a two-dimensional cloud model. First, a comprehensive early warning system is developed to assess the probability and consequences of dam failure, using risk probability and consequences as two-dimensional coordinates, incorporating the randomness and fuzziness of uncertainty described by cloud theory, and transforming qualitative data into quantitative conclusions. Next, a genetic algorithm optimizes the projection pursuit model to determine weights, and weighted numerical features are utilized to enhance the classification of early warning levels. Furthermore, the two-dimensional cloud model is enhanced by introducing a proximity coefficient to replace the membership function, with the resulting cloud map visualized using a forward cloud generator. Finally, the early warning level of the tailings dam’s operational status is determined based on the clustering of cloud droplets and the proximity coefficient. Empirical application to five tailings dams in Hubei Province confirms the model’s effectiveness and practicality. The results demonstrate that the model effectively addresses the complexity and uncertainty of tailings dam operational status, delivers accurate warnings, and provides robust decision support for emergency response. Full article

Tick-borne pathogens pose a significant threat to human health. In this study, a multiple droplet digital PCR (ddPCR) assay was developed to detect four tick-borne pathogens: Borrelia burgdorferi sensu lato (Bbsl), Coxiella burnetii (C. burnetii), spotted fever group Rickettsia (SFGR), and Borrelia miyamotoi (B. miyamotoi). Based on the singleplex ddPCR reaction system of Bbsl, the primer probes of the other three species were incorporated to develop a multiplex ddPCR reaction system. The annealing temperature and the final concentration of the primer probes were then optimized for multiplex ddPCR. The multiplex ddPCR assay was assessed for its sensitivity, specificity, repeatability, and ability to detect simulated and actual samples. The developed multiplex ddPCR approach enables the simultaneous detection of Bbsl, C. burnetii, SFGR, and B. miyamotoi. The positive target microtitre clusters are closely grouped and distinctly separated from each other, with the multiplex ddPCR assay demonstrating a dynamic range of five orders of magnitude. The limits of detection (LOD) for the multiplex ddPCR assay were 4 copies/20 µL for Bbsl, 3 copies/20 µL for C. burnetii, 3 copies/20 µL for SFGR, and 2 copies/20 µL for B. miyamotoi. The assay demonstrated high specificity, with no observed cross-reactivity against non-target pathogens. Performance was validated using both spiked samples and field-collected clinical specimens. In the evaluation of 30 ticks and 30 serum samples, the ddPCR method (in both singleplex and multiplex formats) achieved higher positive detection rates for all four target pathogens compared to quantitative real-time PCR (qPCR). In addition, the detection proportions of multiplex and singleplex ddPCR were consistent. Multiplex ddPCR can detect low DNA concentrations in samples and enables the absolute quantification of Bbsl, C. burnetii, SFGR, and B. miyamotoi, providing a novel detection approach for the clinical diagnosis of tick-borne diseases. Full article

Parvovirus B19 is a DNA virus. Most parvoviruses infect animals; Parvovirus B19 infects humans. Parvovirus B19 is mainly transmitted through respiratory droplets during close contact, but additional routes such as transmission through contaminated blood products and vertical transmission from mother to fetus have also been documented. Infections occur throughout the year, with a seasonal increase between late winter and early summer. Clinical symptoms depend on age, and on patients’ immune status. Healthy, immunocompetent individuals experience asymptomatic or mild infections including a febrile rash; serious complications rarely appear, such as rheumatoid-like arthritis or acute myocarditis. Clusters of myocarditis cases following Parvovirus B19 infections appeared in a daycare in Thessaloniki in 2024. To molecularly and phylogenetically characterize Parvovirus B19 strains detected during a pediatric outbreak associated with elevated troponin levels and myocarditis in Northern Greece, and to compare these strains with isolates from adult cases with mild symptoms in order to explore potential associations between viral genetic variability and cardiac involvement. MinION sequencing protocol was performed for nine whole blood samples, seven belonging to children with myocarditis, and two to adults presenting mild symptoms. Statistical analysis was performed with QualiMap 2.3 and relevant tools. Phylogenetic analysis identified distinct viral groups originating from the samples investigated. A distinct branch was formed by the reference genome and the ones of the adults’ samples, while samples from children with myocarditis provided discrete branches differing from the reference one. The findings demonstrate a clear association between Parvovirus B19 infection and myocarditis in the pediatric cases analyzed. The detected viral strains, including variants identified in several samples, support the role of Parvovirus B19 as a contributing factor in post-infectious cardiac involvement. Although these results reinforce the clinical relevance of Parvovirus B19 in childhood myocarditis, expanding the sample size would allow for a more robust characterization of circulating strains and confirmation of the observed patterns. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is now recognized as the leading cause of chronic liver disease worldwide. MASLD spans a spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH) and is linked to progressive fibrosis and ultimately hepatocellular carcinoma (HCC). Growing evidence implicates cellular senescence (CS) and lipid droplets (LDs) as key drivers of disease progression, although their interaction remains poorly characterized. This review provides an integrative and stage-dependent synthesis of current mechanistic insights into how bidirectional crosstalk between CS and LD regulation shapes the transition from steatosis to MASH. Senescent hepatocytes display altered lipid metabolism, including upregulation of receptors such as cluster of differentiation (CD) 36, enhancing lipid uptake to meet increased energy demands. Initially, elevated free fatty acid influx can activate peroxisome-proliferator-activated receptor alpha (PPARα), promoting fatty acid oxidation (FAO) as a compensatory response. Over time, persistent CS under steatotic conditions leads to mitochondrial dysfunction and suppression of fatty acid oxidation (FAO), while the senescence-associated secretory phenotype (SASP), largely driven by nuclear factor—kappa B (NF-κB) signaling, promotes chronic hepatic inflammation. By framing LDs as active modulators of senescence-associated signaling rather than passive lipid stores, this review highlights how disruption of senescence–lipid feedback loops may represent a disease-modifying opportunity in MASLD progression. Full article

This work presents results on laser-induced fabrication of metal and oxide structures on glass substrates. The Laser-Induced Reverse Transfer (LIRT) technique is applied using Zn and Sn, sintered ZnO and SnO₂, and oxide composite targets. The processing is performed by nanosecond pulses of a Nd:YAG laser system operated at wavelength of 1064 nm. Detailed analyses of the deposited material morphology, composition and structure are presented, as the role of the processing conditions is revealed. It is found that at the applied conditions of using up to five laser pulses, the deposited material is composed of a nanostructured film covered in microsized nanoparticle clusters or droplets. The use of metal targets leads to formation of structures composed of metal and oxide phases. The adhesion test shows that part of the deposited material is stably adhered to the substrate surface. It is demonstrated that the deposited materials can be used as resistive gas sensors with sensitivity to NH₃, CO, ethanol, acetone and N₂O, at concentrations of 30 ppm. The ability of the method to deposit composite structures that consist of a mixture of both investigated oxides is also demonstrated. Full article

Catalytic coacervates, or droplet reactors, represent a forefront research area in chemistry and materials science. Despite advancements in this field, challenges persist in achieving liquid–liquid phase separation (LLPS) droplet compartmentalization and site-specific reactant recruitment/localization for reaction catalysis, similar to those within biological systems. Herein, we describe the catalytic coacervates for aqueous photo-RAFT in dilution, focusing on the site-specific recruitment/localization of ionized monomer with the aid of macromolecular crowding and confinement. Cooperative hydrogen-bonded interpolymer complexation (IPC) of imidazolium-copolymers initiates the ion-cluster formation. Further hierarchical inter-cluster complexation (ICC) leads to the LLPS droplet compartmentalization into charged dense-phase and neutral dilute-phase compartments. Site-specific recruitment and localization of the oppositely charged monomer into dense-phase compartments are achieved by salt-bridging molecular recognition. “Substantial DMA-dilution” (that is, macromolecular crowding) results in sustainable dense-phase catalytic sites within dilute-phase crowding surroundings, enabling reaction catalysis in dilution (<2% w/w monomer) to 97% conversion in 12 min. These findings underscore the key roles of macromolecular crowding and confinement in the tailorable LLPS droplet compartmentalization and also the site-specific reactant recruitment/localization essential for enzyme reaction catalysis, and provide practical guidelines for creating catalytic coacervates towards lifelike reaction functions. Full article

Low-salinity water flooding is a commonly used method to enhance oil recovery. At the microscopic scale, changes in pore structure and the distribution of remaining oil are critical to the effectiveness of water flooding. However, current research on the relationship between pore structure and remaining oil distribution is relatively limited. Therefore, this study employed micro-CT technology to analyze changes in pore structure and the distribution characteristics of remaining oil in sandstone cores during the water flooding process. Micron CT technology provides non-destructive, high-resolution three-dimensional imaging, clearly revealing the dynamic changes in the oil-water interface and remaining oil. The experiments included water saturation, oil saturation, and multi-stage water displacement processes in sandstone cores with different permeability values. The results show that the oil saturation in the rock core decreases during water flooding, and the morphology of remaining oil changes with increasing water flooding volume: cluster-like remaining oil decreases rapidly, while porous and membrane-like remaining oil gradually transforms, and columnar and droplet-like remaining oil increases under specific conditions. The study results indicate that at 1 PV flooding volume, the crude oil recovery rate reaches 57.56%; at 5 PV, the recovery rate increases to 64.00%; and at 100 PV, the recovery rate reaches 75.53%. This indicates that water flooding significantly improves recovery rates by enhancing wettability and capillary forces. Meanwhile, pore connectivity decreases, and particle migration becomes prominent, especially for particles smaller than 20 μm. These changes have significant impacts on remaining oil distribution and recovery rates. This study provides microscopic evidence for optimizing reservoir development strategies and holds important implications for enhancing recovery rates in mature oilfields. Full article

Icing on aircraft surfaces during operation poses a threat to flight safety. As a passive anti-icing technology, hydrophobic microstructure can achieve long-term anti-icing. In this work, a composite process combining hot-embossing of PVD-coated punches with a low surface energy fluoride-modification scheme is proposed to generate nanoscale cluster structures on hundreds of microns array channels to construct a superhydrophobic micro-nano composite structure. The droplet freezing and frosting behavior of the hydrophobic microstructures was analyzed, and it was found that the anti-icing and anti-frost properties of the microstructure surface improved with an increase in the microstructure period size (T). Compared with the original surface, the freezing time of the microstructure at T = 500 μm was delayed by 214.3% (7 s → 22 s), and the frost layer coverage time was delayed by 75.7% (70 s → 123 s). The maximum water contact angle of the superhydrophobic micro-nano composite structure was 153.3°, and the droplet freezing time was delayed to 95 s, which is a 1166.67% difference, indicating that the multi-stage micro-nano composite structure can significantly improve surface anti-icing performance. The main reason for this result is that the bottom of the microstructure can store air pockets, preventing droplet wetting and heat exchange. Full article

Elucidating amyloid formation inside biomolecular condensates requires models that resolve (i) local, chemistry specific contacts controlling β registry and (ii) mesoscale phase behavior and cluster coalescence on microsecond timescales—capabilities beyond single resolution models. We present a hybrid united atom/coarse-grained (UA–CG) force field coupling a PACE UA peptide model with the MARTINI CG framework. Cross-resolution nonbonded parameters are first optimized against all-atom side chain potentials of mean force to balance the relative strength between different types of interactions and then refined through universal parameter scaling by matching radius of gyration distributions for specific systems. We applied this approach to simulate a recently reported model system comprising the LVFFAR₉ peptide that can co-assemble into amyloid fibrils via liquid–liquid phase separation. Our ten-microsecond simulations reveal rapid droplet formation populated by micelle-like nanostructures with its inner core composed of LVFF clusters. The nanostructures can further fuse but the fusion is reaction-limited due to an electrostatic coalescence barrier. β structures emerge once clusters exceed ~10 peptides, and the LVFFAR₉ fraction modulates amyloid polymorphism, reversing parallel versus antiparallel registry at lower LVFFAR₉. These detailed insights generated from long simulations highlight the promise of our hybrid UA–CG strategy in investigating the molecular mechanisms of condensate aging. Full article

Droplet-based microlens fabrication using Ultra Violet (UV) curable polymers demands the precise measurement of three-dimensional geometries, especially for non-axisymmetric shapes influenced by electric field deformation. In this work, we present a polar coordinate-based contour fitting method combined with Hermite interpolation to reconstruct 3D droplet geometries from two orthogonal shadowgraphy images. The image segmentation process integrates superpixel clustering with active contours to extract the droplet boundary, which is then approximated using a spline-based polar fitting approach. The two resulting contours are merged using a polar Hermite interpolation algorithm, enabling the reconstruction of freeform droplet shapes. We validate the method against both synthetic Computer-Aided Design (CAD) data and precision-machined reference objects, achieving volume deviations below 1% for axisymmetric shapes and approximately 3.5% for non-axisymmetric cases. The influence of focus, calibration, and alignment errors is quantitatively assessed through Monte Carlo simulations and empirical tests. Finally, the method is applied to real electrically deformed droplets, with volume deviations remaining within the experimental uncertainty range. This demonstrates the method’s robustness and suitability for metrology tasks involving complex droplet geometries. Full article

The multiscale interactive system composed of wind, leaves, and droplets serves as a critical dynamic unit in precision orchard spraying. Its coupling mechanisms fundamentally influence pesticide transport pathways, deposition patterns, and drift behavior within crop canopies, forming the foundational basis for achieving intelligent and site-specific spraying operations. This review systematically examines the synergistic dynamics across three hierarchical scales: Droplet–leaf surface wetting and adhesion at the microscale; leaf cluster motion responses at the mesoscale; and the modulation of airflow and spray plume diffusion by canopy architecture at the macroscale. Key variables affecting spray performance—such as wind speed and turbulence structure, leaf biomechanical properties, droplet size and electrostatic characteristics, and spatial canopy heterogeneity—are identified and analyzed. Furthermore, current advances in multiscale modeling approaches and their corresponding experimental validation techniques are critically evaluated, along with their practical boundaries of applicability. Results indicate that while substantial progress has been made at individual scales, significant bottlenecks remain in the integration of cross-scale models, real-time acquisition of critical parameters, and the establishment of high-fidelity experimental platforms. Future research should prioritize the development of unified coupling frameworks, the integration of physics-based and data-driven modeling strategies, and the deployment of multimodal sensing technologies for real-time intelligent spray decision-making. These efforts are expected to provide both theoretical foundations and technological support for advancing precision and intelligent orchard spraying systems. Full article