Membranes最新文献

Interrelations between the plasma membrane and cytoskeleton are of crucial importance for essential cellular processes such as endocytosis, formation of intercellular junctions, cell morphology, etc. Many studies validate the beneficial effects of polyphenols as antioxidant and protective agents, but a molecular mechanism of their interaction and transition through the plasma membranes of different cell lines is still missing. In this study, we examined the affinity of fractions enriched in flavonoid glycosides (FGs) and caffeoylquinic acids (CQAs), obtained from the methanol extract of the medicinal plant Inula oculus-christi L., to reorganize the plasma membrane structure and actin cytoskeleton by using confocal microscopy. Assessment of the degree of membrane ordering aiming to distinguish the ordered from disordered regions of the cellular membranes was performed using the fluorescent dye Di-4-ANEPPDHQ, and visualization of F-actin was by TRITC-phalloidin. Two epithelial cell lines with clear differences in their origin and plasma membrane organization were chosen: the non-malignant MDCK II and the cancerous A549. Our results showed that flavonoid glycosides exhibited an ordering effect on plasma membranes of cancerous cells and fluidized one on non-malignant cells. Different patterns of actin reorganization were observed for both cell lines after treatment. Our results indicate the potential of plant-derived polyphenols as modulators of the membrane's structural organization, offering valuable insights for the development of membrane-targeted therapeutic strategies.

Optimizing the MEA structure is crucial for enhancing the performance of open-cathode PEMFCs under water shortage conditions. By investigating the impact of gradient ambient temperature on performance, it is highlighted that cathode catalyst layer hydration deeply affects proton conduction in the membrane and three-phase boundary formation. These issues consequently increase ohmic resistance and cathode activation resistance as seen via polarization curve comparison and the electrochemical impedance spectroscopy analysis method, ultimately degrading overall stack voltage output under the same current density. Under indoor temperature and humidity conditions, an orthogonal experiment was designed to validate the sensitivity analysis on the cathode I/C ratio (0.74-0.9) and catalyst layer thickness (8, 12 μm) by controlling the catalyst-coated membrane manufacture process; GDL thickness (185-324 μm) and pore structure were also investigated, combining parameter characterization techniques like MIP and BET. It is shown that with an I/C ratio of 0.86, a medium GDL pore structure and a higher catalyst layer thickness of 12 μm bring better performance output, especially when the OC PEMFC is 700 mA/cm² @ 0.62 V.

Pervaporation is a compelling alternative to azeotrope-breaking and solvent dehydration due to lower energy demand and strong selectivity compared with distillation. FAU-type zeolite membranes combine large pore openings and hydrophilic frameworks with robust chemical stability, enabling water-selective separations from alcohols such as isopropanol and ethanol. Despite numerous synthesis routes, the role of seed crystal size in secondary growth, controlling nucleation density, intergrowth, and defect formation remains insufficiently quantified for FAU membranes under identical growth conditions. Here, FAU layers were fabricated on α-Al₂O₃ supports via secondary growth with varying seed sizes in the nanometer-to-micrometer range (72 nm to 6 μm). Zeolite crystal phase purity and morphology of membranes were assessed by XRD and SEM, with pervaporation of IPA/water 80 wt% at 75 °C quantified flux, separation factor, and permeance. We show that smaller seeds (95.51 nm) increase nucleation density, yielding thinner, more intergrown FAU layers with a higher separation factor but a modest trade-off in flux.

Carbon membranes have emerged as a promising class of inorganic membranes for desalination due to their tunable pore structures, superior chemical and thermal stability, and molecular-sieving properties. In pursuit of sustainability, recent research has shifted focus towards replacing petrochemical-based precursors with renewable natural polymers. This review provides a comprehensive examination of the fundamentals, developments, and prospects of carbon membranes derived from natural polymer precursors-such as cellulose, chitosan, lignin, starch, and sugars-specifically for pervaporation desalination. It begins by summarizing the fundamentals of membrane separation and the mechanisms of carbon membrane formation, emphasizing the critical relationships between precursor structure, carbonization conditions, and the resulting membrane performance. The core of the review is dedicated to a detailed analysis of various natural polymer precursors, discussing their unique chemistries, carbonization behaviors, and the characteristics of the derived carbon membranes. Particular attention is given to their application in pervaporation desalination, where they demonstrate competitive water flux and high salt rejection (>99%) under moderate operating conditions, highlighting their potential for treating hypersaline brines. Finally, the challenges of large-scale fabrication, structural durability, and data-driven optimization are discussed, along with future directions toward scalable and sustainable membrane technologies.

Cholesterol (Chol) plays a crucial role in regulating membrane properties and biological processes such as membrane fusion, yet the molecular mechanisms underlying its function remain incompletely understood. In order to elucidate how sterol structure influences phospholipid organization relevant to membrane fusion, we compared the effects of Chol and its biosynthetic precursor lanosterol (Lan) on hydrated phosphatidylethanolamine (PE) assemblies using X-ray diffraction, the neutral flotation method, and osmotic stress measurements. Volumetric analyses revealed that Lan has a larger occupied molecular volume than Chol in the bilayers. These values were largely independent of differences between phospholipids (phosphatidylcholine and PE), indicating that sterols are deeply embedded within the bilayer. In palmitoyl-oleoyl-PE lamellar membranes, both sterols increased bilayer thickness. They both enhanced short-range repulsive hydration forces, but Chol suppressed fluctuation-induced repulsion more effectively, reflecting its greater stiffening effect. In bacterial PE systems forming the inverted hexagonal (H_II) phase, increasing sterol concentration decreased the lattice constant, with a more substantial effect for Lan, which also induced greater curvature of the water columns. These results suggest that while Chol enhances mechanical rigidity and membrane cohesion, Lan promotes molecular flexibility and curvature, properties associated with fusion intermediates.

Membrane technologies play a vital role in sustainable development due to their efficiency in separation, purification, and chemical processing applications. However, the discovery and optimization of new membrane materials remain largely reliant on trial-and-error experimentation, limiting the pace of innovation. Artificial intelligence (AI) and machine learning (ML) are increasingly being applied to overcome these limitations by enabling data-driven insights, predictive modeling, and rapid material design. These computational approaches have shown significant promise in accelerating membrane fabrication, improving process simulation, detecting and mitigating fouling, and enhancing membrane characterization. This review provides a comprehensive overview of the recent advancements in the integration of AI and ML within membrane and material science. Fundamental AI and ML concepts relevant to membrane science are discussed, together with their applications in membrane fabrication, performance prediction, process modeling, fouling control, and membrane design. Challenges related to data quality, model interpretability, and the integration of domain-specific knowledge are also highlighted, along with potential future research directions. Compared with conventional empirical approaches, the advantages of AI and ML in handling complex, multivariate datasets and accelerating innovation are demonstrated. Overall, this review underscores the transformative potential of AI and ML in developing next-generation membranes with improved efficiency, selectivity, and sustainability across various industrial applications. Although several reviews have explored ML applications in membrane processes, comprehensive integration across material design, fabrication, fouling control, optimization, and process modeling remains limited.

The conventional linear life cycle of membrane materials, spanning fabrication, use, and disposal through landfilling or incineration poses serious sustainability challenges. The environmental burden associated with both the production of new membranes and the disposal of end-of-life (EoL) modules is considerable, further intensified by the reliance on fossil fuel-derived polymers, toxic solvents, and resource-intensive manufacturing processes. These challenges underscore the urgent need to integrate sustainability principles across the entire membrane life cycle, from raw material selection to reuse and regeneration. Emerging approaches such as membrane regeneration using recyclable polymers based on covalent adaptable networks (CANs) have introduced a new paradigm of closed-loop design, enabling complete depolymerization and reformation. In parallel, more conventional strategies, including the valorization of recycled plastic waste and the upcycling or downcycling of EoL membranes, offer practical routes toward a circular membrane economy. In this review, we consolidate current advances in membrane recycling, critically evaluate their practical constraints, and delineate the technical and environmental challenges that must be addressed for broader implementation. The insights presented here aim to guide the development of next-generation circular membrane technologies that harmonize sustainability with performance.

Lipid vesicles and related nanocarriers often contain two compartments, such as the inner and outer leaflets of a bilayer membrane between which amphipathic molecules can migrate. We develop a stochastic model for describing the transfer kinetics of cargo between the two compartments in an ensemble of carriers, neglecting inter-carrier exchange to focus exclusively on intra-carrier redistribution. Starting from a set of rate equations, we examine the Gaussian regime in the limit of low cargo occupation where Gaussian and Poissonian statistics overlap. We derive a Fokker-Planck equation that we solve analytically for any initial cargo distribution among the carriers. Moments of the predicted distributions and examples, including a comparison between numerical solutions of the rate equations and analytic solutions of the Fokker-Planck equation, are presented and discussed, thereby establishing a theoretical foundation to study coupled intra- and inter-carrier transport processes in mobile nanocarrier systems.

The subfamily ENA of the P-ATPases family transports Na⁺ and H⁺ in opposite directions and, for this reason, they are called Na⁺-ATPases. They are physiologically important at high pH and high salt conditions in which other Na⁺ transporters cannot operate. This is the case, for example, of Aspergilus and Arabidopsis, respectively. Since, during their lifecycle, the parasitic protozoa face alkaline and/or high-saline environments, we postulated that the ENA subfamily could be a target for the treatment of serious and common illnesses driven by parasitic protozoa, as in the case of Chagas disease. The subgroup ATP4 ATPases, which is found in Plasmodium falciparum and Toxoplasma gondii, can be compared -through phylogenetic analysis-with the classic IID P-type ENA subfamily. Thus, some drugs that target PfATP4 ATPase and affect Na⁺ homeostasis are undergoing clinical trial, including spiroindolones. ENA-type ATPases (P-type ATPase IID) and ATP-type ATPase do not have structural homologs in mammals, appearing only in plants, fungi, and protozoan parasites, such as Trypanosoma cruzi, Leishmania sp., T. gondii, and P. falciparum. Therefore, this exclusivity points to Na⁺-ATPases as promising targets for medical projects aiming at new treatments contributing to the academic community.

Ammonia recovery from synthetic thermophilic anaerobic digestate was achieved through Direct Contact Membrane Distillation (DCMD) using hydrophobic flat-sheet membranes under different operating conditions. The influence of temperature gradients (0 °C, 20 °C, 35 °C, and 45 °C) and pH levels of the thermophilic anaerobic sludge (7.8, 8.2, 9, and 12) was investigated. The process utilized a DCMD setup with hydrophobic PTFE membranes of 0.22 µm nominal pore radius, and receiving solutions consisting of deionized water and 1 M H₂SO₄. The best results were obtained with isothermal distillation and high pH levels in the feed. Isothermal distillation at 65 °C (a temperature gradient of 0 °C), with 1 M H₂SO₄ as the receiving solution, and at pH levels 8.2 and 12, yielded NH₃ recoveries of 36.4 ± 1.6% and 100.0 ± 0.1%, respectively. Under the same conditions, the molar fluxes were 0.63 ± 0.01 mol TAN m^-2 h^-1 and 1.84 ± 0.01 mol TAN m^-2 h^-1, respectively. It is worth noting that some very low depositions on the membrane were detected, leading to changes in the surface morphology, as confirmed by atomic force microscopy.