Search Results (411)

This study investigates the synergistic effects of compaction pressure and vapor-induced phase separation (VIPS) on the morphological, mechanical, and initial filtration properties of activated carbon/polyethersulfone composite block membranes. Membranes were fabricated using varying compaction pressures (5 and 10 kg/cm²) and VIPS exposure times (0 and 10 min) prior to direct non-solvent-induced phase separation (NIPS). Surface wettability analysis revealed that the optimized 50 wt.% activated carbon configurations were superhydrophilic (0° water contact angle), exhibiting instantaneous fluid absorption driven by strong capillary forces within the highly hygroscopic matrix. Morphological and gravimetric evaluations demonstrated that minimizing compaction (5 kg/cm²) and bypassing VIPS generated large macrovoids, resulting in the highest bulk internal porosity (61.05%) and maximum continuous gravity-driven water flux. Conversely, incorporating a 10-min VIPS exposure shifted the internal structure toward an interconnected sponge-like network. This structural transformation yielded the highest bovine serum albumin (BSA) rejection rate (12.97%) when paired with low pressure, as the network extended fluid residence time and maximized exposure to the activated carbon adsorption sites. Applying high compaction pressure (10 kg/cm²) to VIPS-treated membranes induced excessive polymer encapsulation of the active particles, significantly reducing separation efficiency while concurrently maximizing initial uniaxial tensile strength. Ultimately, these findings establish a foundational and highly tunable framework, demonstrating that calibrating mechanical compression alongside phase inversion dynamics balances permeability, adsorptive selectivity, and inter-particle binding cohesion for composite block membranes. Full article

Tight dolomite gas reservoirs are promising exploration targets, yet their evaluation is complicated by multiscale pore-throat heterogeneity and poor seepage connectivity. Here, high-pressure mercury intrusion (HPMI), nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), and deep-learning-assisted pore extraction were integrated to characterize the pore-throat structure and fractal features of the Middle Ordovician Majiagou Formation in the Ordos Basin. The reservoir is dominated by diagenetic-origin pores, mainly intercrystalline and intragranular dissolution pores, together with microfractures, and can be classified into three types with progressively poorer connectivity and flow capacity. Type I reservoirs contain more regular pores, larger pore-throat systems, and better storage and seepage capacity; Type II reservoirs are intermediate, whereas Type III reservoirs exhibit complex pore morphology, isolated pore networks, poor petrophysical properties, and limited gas-flow potential. The corresponding fractal dimensions are weakly correlated but complementary: D_SEM captures pore-boundary complexity, D_HPMI reflects pore-throat architecture and capillary-pressure-controlled seepage pathways, and D_NMR reflects multiscale movable-fluid distribution. Clay minerals, especially illite-rich mixed layers, further intensify pore-throat heterogeneity. Increasing fractal dimension is generally associated with higher displacement and median pressures, but poorer connectivity, porosity, permeability, movable-fluid content, and gas deliverability. These results provide a basis for the quantitative evaluation of multiscale pore systems and reservoir quality in tight dolomite gas reservoirs. Full article

Beginning with a general understanding of catastrophic obstetric collapse (COC), it has been established that a catastrophic obstetric collapse is typically the result of sudden massive bleeding requiring emergency peripartum hysterectomy (EPH); this is different from historical views of what constitutes a catastrophic obstetric collapse. Current studies have found evidence that a catastrophic obstetric collapse can be the result of a longer-duration process involving gradual maternal physiological destabilization, the culmination of which creates a “maternal point of no return” for the mother. As a result of disrupting the maternal–fetal interface in placenta accreta spectrum disorders (PASDs), there are many abnormalities present in the decidua, such as: defective decidualization, fragmentation of the extracellular matrix, aberrant angiogenesis, continued hypoxic signals, and the persistence of invasive trophoblastic phenotypes. These structurally fragile vascular interfaces will eventually undergo endothelial dysfunction, oscillatory shear stress, glycocalyx injury, oxidative damage and progressive depletion of the maternal vascular adaptive reserve. Chronic inflammation will also continue to amplify immune thrombosis, alter complement function, facilitate NETosis, and cause widespread instability in diffuse microvasculature, leading to a reduced ability of the maternal system to tolerate physiological stress while maintaining macrocirculatory stability. Additionally, invasive placentation may lead to mitochondrial dysfunction, decreased oxidative phosphorylation, disrupted intracellular calcium homeostasis, ferroptotic lipid peroxidation, and redox-mediated endothelial injury, leading to a progressive limitation in the mother’s bioenergetic adaptability to hemorrhage. Ultimately, these events seem to culminate in a threshold condition where endothelial disorganization exists along with capillary transit time heterogeneity, impaired oxygen diffusion, metabolic instability, and progressive desynchrony of vascular, inflammatory, coagulative and mitochondrial networks before eventual hemodynamic collapse. Therefore, based on these findings, we propose the concept of the “Maternal Point of No Return” as a transitional state in which physiological adaptations begin to fail and irreversibly destabilize at a systems level. Lastly, we review potential applications of current technological advancements, including artificial intelligence (AI), radiomic-based placental phenotyping, exosomal biology, physiological variability analysis, spatial multi-omics, and digital twin physiology, to enable future precision-obstetrics strategies to identify a decline in maternal resilience prior to irreversible decompensation. Full article

Automated and accurate segmentation of retinal vessels in fundus images provides pivotal evidence for ophthalmologists to effectively and non-invasively diagnose prevalent ocular and systemic diseases. However, existing methods often struggle to maintain the topological continuity of fine-diameter capillaries, leading to severe vascular discontinuity and fragmented segmentation results in challenging scenarios such as complex, irregular microvascular branches, pathological lesions, and high-noise conditions. To address these limitations, we developed a novel symmetric dual-branch network with frequency-aware decomposition and prototype refinement (FDPR-DBNet). Specifically, the network initially utilizes the discrete wavelet transform (DWT) to decompose input retinal images into high-frequency and low-frequency components, which are then processed by a structurally symmetric dual-branch encoder. In the high-frequency branch, the parallel atrous convolution activation (PACA) module is designed to explore fine-grained contour and edge patterns related to vessel terminals and microvessels. Concurrently, within the low-frequency branch, the spatial-frequency characteristic activation (SFCA) unit is constructed by introducing the selective state-space model ($S6$) and Fourier transform to extract salient structural backbones. Moreover, the spatial attention residual fusion (SARF) module and cross-frequency fusion (CFF) block are designed to establish a symmetric guidance mechanism, effectively reinforcing bidirectional feature interaction and alignment across different frequency spectra to eliminate vascular fragmentation. Furthermore, by embedding global and local window self-attention into the Transformer, we formulated the cross-scale enhancement (CSE) module, comprising global semantic enhancement (GSE) and local detail enhancement (LDE), to model multi-scale contextual semantic correlations and enhance the adaptive recognition of vessel structures. Ultimately, we embedded the multi-wise prototype characteristic refinement (MPCR) component into the decoder to correct cross-scale semantic features through a dynamic calibration mechanism, while introducing a new connectivity loss to strictly enforce topological continuity. Experimental results on four publicly available retinal image datasets (DRIVE, CHASE_DB1, STARE, and IOSTAR) demonstrate that the proposed model achieves competitive performance and effectively preserves vascular integrity even in the presence of fundus lesions and noise. Full article

The dewatering of cyanobacteria-laden sludge remains a challenge. Extracellular polymeric substances (EPS) mainly consist of polysaccharides and proteins, which form a stable gel network with water through hydrogen bonding and other interactions. To address this bottleneck, a low-voltage (5 V) electrochlorination system was constructed, employing a Ti/IrO₂/RuO₂ electrode as the anode, iron as the cathode, and calcium chloride dihydrate (CaCl₂·2H₂O) as the electrolyte. The results showed that the active chlorine generated during electrolysis degraded the highly water-retentive loosely bound EPS (LB-EPS) and tightly bound EPS (TB-EPS), converting them into low-viscosity, easily removable soluble EPS (S-EPS). Moreover, the total contents of polysaccharides and proteins in EPS decreased. Three-dimensional excitation-emission matrix fluorescence spectroscopy revealed that in the EPS of the algal sludge, the relative proportion of humic-like substances increased, while that of protein-like products decreased. At a CaCl₂·2H₂O dosage of 1 g/L, the dewatering performance of the algal sludge was significantly improved: the capillary suction time (CST) of the algal suspension decreased from 10.30 ± 0.1 s to 4.1 ± 0.05 s, the proportion of bound water decreased from 43.5% to 9.8%, and the cake solids content increased to 9.48%. The residual water quality of this process was also favorable, with total phosphorus (TP) and total nitrogen (TN) concentrations stabilized at 0.166 ± 0.040 mg/L and 9.0 ± 1.1 mg/L, respectively. Therefore, this study provides an efficient, low-energy electrochemical pretreatment strategy to overcome the dewatering bottleneck in cyanobacteria-laden sludge, thereby reducing the treatment load and cost of downstream mechanical dewatering. Full article

Background/Objectives: Cancer metastasis is responsible for most cancer-related deaths, yet the precise anatomical and physiological routes by which cancer cells disseminate remain incompletely defined. This review aims to present an integrated model of lymphatic and hematogenous dissemination that provides a unified framework for understanding metastatic progression. Methods: The published literature on lymphatic biology, microvascular physiology, tumor immunology, and cancer metastasis was critically reviewed and integrated to develop a comprehensive anatomical and physiological model of cancer dissemination. Results: The proposed model identifies lymphatic dissemination as the predominant metastatic route in many solid tumors. Cancer cells enter structurally permissive initial lymphatic capillaries and are transported to the sentinel lymph node (SLN), where interactions with the tumor microenvironment may eliminate disseminated cells, maintain dormancy, or facilitate immune escape and further dissemination. Cancer cells that survive within or escape beyond the SLN subsequently travel through collecting lymphatics and the thoracic or right lymphatic duct to enter the systemic venous circulation. Following cardiopulmonary transit, surviving cells may be redistributed through the systemic arterial circulation to distant organs. A secondary pathway involves direct hematogenous intravasation through post-capillary venules, where reduced shear stress, increased endothelial permeability, and permissive endothelial biology facilitate entry into the venous circulation. Thus, lymphatic and direct venular pathways ultimately converge in the venous circulation before systemic arterial dissemination. Conclusions: This unified model integrates lymphatic and hematogenous dissemination into a coherent anatomical and physiological framework. By emphasizing the SLN as an early immunologic checkpoint and the arterial circulation as the final distribution network for disseminated cancer cells, this review provides a conceptual basis for understanding metastatic patterns and identifying biomarkers and therapeutic vulnerabilities. Full article

Radiofrequency ablation (RFA) is commonly modeled using classical heat diffusion equations; however, growing evidence suggests that heat transport in biological tissues exhibits nonlocal and scale-dependent behavior driven by capillary perfusion. In this work, we develop a fractional diffusion framework for the computational modeling of hepatic tumor ablation based on the fractional Laplacian operator. A characteristic length scale is introduced to bridge microscale capillary effects and macroscale heat propagation, enabling the model to capture the superdiffusive thermal transport associated with hepatic vascular networks. Owing to its nonlocal nature, the fractional formulation entails significantly higher computational costs than classical diffusion models. To address this challenge, we investigate the complexity of two temporal discretization strategies: the backward Euler method with uniform time stepping and an adaptive backward–forward Euler scheme. Numerical experiments involving single- and double-probe ablation configurations demonstrate the robustness of the proposed framework and illustrate its applicability to realistic ablation scenarios. Overall, the results indicate that fractional diffusion provides a flexible and physiologically meaningful framework for modeling heat transfer during RFA. Full article

Objective: This study aimed to evaluate the predictability of baseline optical coherence tomography angiography (OCTA) metrics utilizing a specialized capillary–large vessel segmentation analysis framework in patients with diabetic macular edema (DME) undergoing anti-vascular endothelial growth factor (anti-VEGF) therapy. Methods: Forty-two treatment-naïve eyes with DME receiving three monthly loading anti-VEGF injections were included. Superficial capillary plexus (SCP) images from 3 × 3 mm OCTA scans were processed to isolate the capillary network from the large vessels via image processing. Vessel density and skeleton density were extracted for the total, large-vessel, and capillary components. Multiple linear and logistic regression models were used to identify independent predictors of post-treatment best-corrected visual acuity (BCVA) and “good visual outcome” (≥3-line improvement or final BCVA of 20/40 or better). Results: Following three monthly anti-VEGF injections, the mean BCVA significantly improved from 0.57 ± 0.36 to 0.37 ± 0.30 LogMAR (p < 0.0001), and the mean central retinal thickness decreased from 424.3 ± 117.7 μm to 316.9 ± 84.7 μm (p < 0.0001). The proportion of patients who achieved a good visual outcome was 73.8%. Baseline central retinal thickness was associated with baseline BCVA (p = 0.049) but not predictive of post-treatment BCVA (p = 0.38) or good visual outcomes (p = 0.79). Baseline capillary vessel density was identified as a significant independent predictor of post-treatment BCVA (p = 0.024), whereas total and large-vessel metrics were not. Capillary vessel density was also the only significant predictor of good visual outcomes (p = 0.044). Conclusions: Baseline capillary vessel density is a robust predictor of visual prognosis after anti-VEGF therapy in patients with DME, underscoring the importance of capillary network integrity in functional recovery. Full article

The fractal characteristics of coal pore–fracture networks and their evolution under compression are essential for predicting rock mass failure and fluid transport. This study combines micro-CT scanning with fractal theory and seepage mechanics to investigate the structural evolution of coal under uniaxial compression and its impact on fluid transport. CT scans were performed at four characteristic stages (initial, elastic, plastic, and failure) to reconstruct three-dimensional fracture networks. Quantitative analysis reveals that fracture porosity increases sequentially from 0.44% to 5.01%, with the failure stage reaching 11.4 times the initial value. Fracture length and aperture distributions follow power-law scaling, and their fractal dimensions exhibit distinct evolution patterns: length dimension increases from 2.43 to a peak of 2.56 in the plastic stage and then drops to 2.47 at failure, while aperture dimension decreases from 2.29 to a trough of 2.12 before rebounding to 2.26. These patterns reflect a dynamic adjustment of network complexity, transitioning from primary fractures to micro-fracture dominance and finally to main fracture coalescence. Based on the Knudsen number, three diffusion regimes of Fick, transition and Knudsen are identified. A fractal permeability model is developed by idealizing the pore space as tortuous capillaries, showing that permeability scales with the fourth power of the maximum pore diameter and is positively influenced by the fractal dimension and the number of large pores. Furthermore, a coupled seepage–stress model is derived, incorporating pressure transmission, shear transmission, and crack opening coefficients. The damage variable is expressed as a function of stress level and fractal dimension. These findings provide theoretical support for predicting gas transport and failure behavior in coal under coupled hydro-mechanical conditions. Full article

The myocardium possesses one of the highest vascular densities in the body. The outermost wall layer of large and medium-sized vessels, the adventitia, forms a critical interface between the vasculature and the myocardium and serves as a reservoir for stem and progenitor cells capable of differentiating into all vascular wall lineages as well as innate immune cells, including macrophages. Current cardiac organoid models intrinsically develop networks of endothelial cords and small capillary-like structures that resemble cardiac microvessels. However, these microvessels mostly lack an adventitial compartment in vivo. Here, we present a potential alternative assembloid strategy that combines vascular segments from mouse and human origin with either cardiomyocytes or cardiac spheroids derived from human induced pluripotent stem cells, thereby incorporating large diameter vessels and the vascular adventitia into a cardiac tissue model. Within the assembloids, the myocardial component remained contractile and connected to the vascular adventitia, which displayed cellular sprouting toward the hiPSC-derived cardiac tissue. Immunostaining for vascular and immune markers revealed that the adventitia gave rise to endothelial sprouts and macrophage-like cells which integrated into the myocardial tissue. In summary, we present proof of concept for complex assembloids composed of vessel segments and human iPSC-derived cardiomyocytes which contain and maintain an in vivo-like adventitial compartment. We suggest this model may serve as a platform for investigating myocardial–stromal interactions, cardiac tissue repair, and functional remodeling under both physiological and pathological conditions. Furthermore, the incorporation of large-lumen vessel segments may enable future experimental perfusion, rendering the model particularly suitable for drug testing via intravascular delivery. Full article

High-permeability reservoirs at the extra-high water-cut stage commonly exhibit preferential flow, limited sweep expansion, and complex remaining-oil occurrence. To clarify the pore-scale mechanisms controlling waterflood sweep and remaining-oil retention, this study integrates CT-assisted core flooding and microfluidic chip visualization using a high-permeability sandstone core from the Guantao Formation in the Bohai Bay Basin. The CT-assisted core flooding experiment was used to quantify the stage-wise evolution of pores swept by the water phase, while the microfluidic experiment was used to visualize displacement pathways, local bypassing, and remaining-oil morphology under controlled pore-network conditions. The results show that waterflood sweep exhibits clear stage-wise evolution. During the low water-cut stage, injected water preferentially advances through large pore channels, resulting in limited sweep efficiency. With increasing water cut, pores newly swept by the water phase gradually shift from large pores to medium and small pores, accompanied by increasing displacement pressure. Under the present experimental conditions, the lower radius limit of pores newly swept by the water phase is approximately 7.54 μm, corresponding to a capillary force of about 0.9 MPa. When the injected volume exceeds approximately 2.5 PV, the sweep efficiency approaches a plateau and increases only from 0.72 to 0.75 at 5.0 PV, indicating that approximately 25% of the pore space remains difficult to be effectively swept. Image-based classification indicates that remaining oil can be divided into six occurrence types: clustered, porous, columnar, dead-end, film-like, and granular. Clustered and porous are the dominant occurrence types, accounting for a combined 59.7% of the total remaining oil. Pore-structure heterogeneity controls the microscopic sweep boundary through the combined effects of intra-unit structural dispersion and cross-unit structural contrast, which together regulate capillary resistance, seepage resistance, preferential flow, local bypassing, and remaining-oil retention. Microfluidic observations further show that permeability contrast and displacement velocity affect pore-scale displacement pathways and remaining-oil morphology. These findings provide experimental evidence for understanding the lower sweep-radius limit and remaining-oil occurrence mechanisms in high-permeability heterogeneous reservoirs at the extra-high water-cut stage, while the chip-scale velocity effects should be interpreted as pore-scale mechanistic evidence and require further validation before field-scale application. Full article

Low-salinity waterflooding (LSWF) represents a cost-effective enhanced oil recovery (EOR) strategy for mature sandstone reservoirs. However, its success strongly depends on pore-scale transport and wettability mechanisms that conventional reservoir simulators cannot accurately capture. This study implements a pore-network modeling (PNM) framework to evaluate and optimize LSWF performance in sandstone systems. A representative pore network was calibrated to match core-scale petrophysical properties—porosity, permeability, and pore-throat size distributions. The LSWF process was simulated using a coupled advective–diffusive salinity transport model integrated with salinity-dependent wettability alteration, expressed through variations in contact angle and interfacial tension. From the multiphase invasion and flow simulations, macroscopic constitutive relationships were derived, including capillary pressure, relative permeability, and fractional flow curves for different injection salinities. Sensitivity analyses indicate that wettability alteration induced by salinity reduction is the dominant mechanism enhancing oil recovery, as reflected in measurable shifts in the relative permeability endpoints and capillary pressure curves. The model predicts an optimal injection salinity window between 2000 and 4500 ppm, yielding up to 7.2% incremental oil recovery, while extremely low salinities produce non-monotonic trends due to competing interfacial tension effects. Overall, the proposed PNM workflow demonstrates a robust approach for (i) translating pore-scale phenomena into reservoir-scale constitutive laws, (ii) identifying salinity ranges for pilot testing, and (iii) reducing uncertainty in field-scale LSWF simulations. Full article

The efficient adsorption and storage of gases within nanoporous materials are critical for technologies such as adsorbed natural gas systems and energy storage. A paramount goal is to maximize the adsorbent’s gas uptake capacity. However, the fundamental relationship between pore structure and adsorption performance in disordered aerogels remains unclear, hindering rational material design—specifically, where within the complex pore network adsorption predominantly occurs and how the pore size distribution (PSD) should be engineered to enhance capacity. To address this, we conduct molecular dynamics simulations investigating nitrogen adsorption in silica aerogels with tunable PSDs (achieved via tensile deformation) and varied gas–solid interaction strengths (ε). Our results reveal a kinetic-capacity trade-off: microporous-dominated structures saturate rapidly but have limited total uptake, whereas structures with developed mesoporosity (2–10 nm) achieve higher equilibrium capacity via capillary condensation, despite slower kinetics. The interaction strength ε is identified as a key factor governing both capacity and selectivity. Synthesizing these insights, we establish dual design guidelines: to maximize storage capacity, a hierarchical network combining micropores and interconnected mesopores is essential; for optimal reversible performance in cyclic applications like adsorbed natural gas, prioritizing open mesopores with moderately tuned surface chemistry is key. This work clarifies key aspects of the structure–performance relationships and provides evidence-based design guidelines for designing advanced aerogel adsorbents tailored for efficient, low-pressure gas storage. Full article

Background: Precise decoding of brain states is essential for closed-loop neuromodulation, but current electrodes and recording strategies are inadequate. Multi-region recording offers network-level advantages over single-region approaches, yet remains underdeveloped due to the lack of low-cost, flexible multi-region electrodes and standardized workflows. Methods: We developed a low-cost, modular, silica capillary tube-based 16-channel electrode for multi-region local field potential (LFP) recording in small animals, along with an integrated workflow for spectral analysis, functional connectivity assessment, and machine learning-based brain state decoding. Results: Our electrode design enables flexible customization of target regions and low-cost (~19.43 USD/unit) assembly without specialized equipment. In vivo validation in rats targeting eight emotional network nuclei achieved 79.2% implantation accuracy, with stable LFP recordings maintained for over 3 months. In a reserpine-induced depression model, spectral analysis revealed state-specific oscillatory changes including reduced alpha power in the infralimbic cortex. Inter-regional functional connectivity analysis further captured drug-induced network-level synchronization changes. We also developed a machine learning pipeline with random forest classifier that achieved ~96.4% accuracy in decoding brain states from the multi-region signals. Conclusions: This modular multi-region electrode provides a practical, adaptable, and low-cost platform for long-term distributed network recording, supporting quantitative LFP analysis, functional connectivity assessment, and high-accuracy brain state decoding, laying a technical foundation for preclinical closed-loop neuromodulation research. Full article

The persistence of petrochemical plastics necessitates high-performance and recyclable alternatives, yet balancing mechanical robustness with component-level closed-loop recovery remains challenging for biomass-based plastic-replacement films. Here, a high-performance, thermo-malleable, and closed-loop recyclable composite film is constructed by integrating a highly crystalline enzyme-treated mulberry paper (Enzyme-MP) fiber network with an in situ formed polyimine (PI) vitrimer network via capillary-assisted infiltration. This process induces densification and extensive interfacial hydrogen bonding, forming a confined interpenetrating architecture that enhances stress transfer and restricts chain mobility. As a result, the composite film achieves a tensile strength of 70.3 MPa and a Young’s modulus of 2.37 GPa, together with excellent thermomechanical stability over a broad temperature range. The dynamic imine exchange enables thermo-malleability, allowing seamless self-welding and thickness-scalable lamination at 120 °C. The dense structure also acts as an effective barrier, reducing water uptake to 14.3% and providing resistance to various organic solvents. Furthermore, full-component closed-loop recycling is realized via room-temperature transimination, enabling selective depolymerization of the matrix while preserving the crystalline cellulose fiber network. This work demonstrates a viable strategy to integrate high-strength film performance, processability, and chemical recyclability in biomass-based composite films, while providing a basis for future cradle-to-cradle material circulation in recyclable plastic-replacement films. Full article