Search Results (126)

This study investigates the metabolic responses of the model diatom Phaeodactylum tricornutum under different growth conditions, comparing benthic (adherent) and planktonic states. Using a multiblock metabolomics approach combining LC-HRMS², NMR, and GC-MS techniques, we compared the metabolome of P. tricornutum cultivated on three laboratory substrates (glass, polystyrene, and polydimethylsiloxane) and under planktonic conditions. Our results revealed metabolic differences between adherent and planktonic cultures, particularly concerning the lipid and carbohydrate contents. Adherent cultures showed a metabolic profile with an increase in betaine lipids (DGTA/S), fatty acids (tetradecanoic and octadecenoic acids), and sugars (myo-inositol and ribose), suggesting modifications in membrane composition and lipid remodeling, which play a potential role in adhesion. In contrast, planktonic cultures displayed a higher content of cellobiose, specialized metabolites such as dihydroactinidiolide, quinic acid, catechol, and terpenes like phytol, confirming different membrane composition, energy storage capacity, osmoregulation, and stress adaptation. The adaptative strategies do not only concern adherent and planktonic states, but also different adherent culture conditions, with variations in lipid, amino acid, terpene, and carbohydrate contents depending on the physical properties of the support. Our results highlight the importance of metabolic adaptation in adhesion, which could explain the fouling process. Full article

Background/Objectives: The work presented herein focused on the development and characterization of a transdermal caffeine platform fabricated from ultrathin micro- and submicron fibers produced via electrospinning. Methods: The formulations incorporated caffeine encapsulated in a polyethylene oxide (PEO) matrix, combined with various permeation enhancers. A backing layer made of annealed electrospun polycaprolactone (PCL) facilitated the lamination of the two layers to form the final multilayer patch. Comprehensive characterization was conducted, utilizing scanning electron microscopy (SEM) to assess the fiber morphology, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) for chemical detection and to assess the stability of the caffeine, and differential scanning calorimetry (DSC) along with wide-angle X-ray scattering (WAXS) to analyze the physical state of the caffeine within the fibers of the active layer. Additionally, Franz cell permeation studies were performed using both synthetic membranes (Strat-M) and ex vivo human stratum corneum (SC) to evaluate and model the permeation kinetics. Results: These experiments demonstrated the significant role of enhancers in modulating the caffeine permeation rates provided by the patch, achieving permeation rates of up to 0.73 mg/cm² within 24 h. Conclusions: This work highlights the potential of using electro-hydrodynamic processing technology to develop innovative transdermal delivery systems for drugs, offering a promising strategy for enhancing efficacy and innovative therapeutic direct plasma administration. Full article

Hydrogen is an excellent clean energy, and hydrogen production by electrolyzing water has become the preferred method. Due to its high electrolysis efficiency and great potential for energy conversion and storage, water electrolysis in a proton exchange membrane (PEM) electrolyzer has attracted considerable attention. In order to explore the factors affecting the internal resistance of PEM water electrolyzers and optimize them, a three-dimensional steady-state model of PEM water electrolyzers coupled with a porous media physical field was established. First, the flow fields in multi-channel and single-channel electrolyzers were designed and comparably simulated. It was found that both flow field configuration and flow modes affected the mass transfer and current distribution. The multi-channel parallel flow field had the lowest flow pressure drop and uniform flow field, which is beneficial to efficient catalytic electrolysis. Secondly, the simulation results of mass transfer in the PEM cell were highly consistent with the reference experimental data, and the increased reference exchange current density (i₀) can improve the oxygen/hydrogen production performance of the cell. These findings are helpful in optimizing the design of the PEM water electrolyzer. Full article

Proton exchange membrane fuel cells (PEMFC), distinguished by rapid refueling capability and zero tailpipe emissions, have emerged as a transformative energy conversion technology for automotive applications. Nevertheless, their widespread commercialization remains constrained by technical limitations mainly in operational longevity. Precise prognostics of performance degradation could enable real-time optimization of operation, thereby extending service life. This investigation proposes a hybrid prognostic framework integrating steady-state modeling with dynamic condition. First, a refined semi-empirical steady-state model was developed. Model parameters’ identification was achieved using grey wolf optimizer. Subsequently, dynamic durability testing data underwent systematic preprocessing through a correlation-based screening protocol. The processed dataset, comprising model-calculated reference outputs under dynamic conditions synchronized with filtered operational parameters, served as inputs for a recurrent neural network (RNN). Comparative analysis of multiple RNN variants revealed that the hybrid methodology achieved superior prediction fidelity, demonstrating a root mean square error of 0.6228%. Notably, the integration of steady-state physics could reduce the RNN structural complexity while maintaining equivalent prediction accuracy. This model-informed data fusion approach establishes a novel paradigm for PEMFC lifetime assessment. The proposed methodology provides automakers with a computationally efficient framework for durability prediction and control optimization in vehicular fuel cell systems. Full article

Despite substantial improvement in the definitive management of primary prostate cancer, a significant number of patients experience biochemical recurrence—a clinical state in which serum prostate-specific antigen (PSA) levels rise prior to the development of physical signs or symptoms. The early detection and localization of biochemical recurrence may confer eligibility for salvage therapy; therefore, imaging techniques that provide accurate disease visualization are imperative. In this review, we discuss various imaging methods for localizing disease in the context of biochemical recurrence in prostate cancer. Particularly, we describe available or investigational positron emission tomography (PET) radiotracers, such as ¹⁸F-FDG, ¹⁸F-NaF, choline (both ¹⁸F and ¹¹C), the ¹⁸F-labeled amino acid derivative fluciclovine, prostate-specific membrane antigen (PSMA) radioligands, and the short peptide compound bombesin. Generally, PET radiotracers such as ¹⁸F-FDG, ¹⁸F-NaF, and ¹⁸F/¹¹C choline have fallen out of favor because of their inferior sensitivity and/or specificity in relation to more recently developed radiotracers. ¹⁸F-fluciclovine has addressed these shortcomings by exploiting the upregulation of amino acid transporters in tumors; however, PSMA-targeting agents have significantly advanced the management of biochemical recurrence of prostate cancer through their high sensitivity and specificity, enabling the identification of candidates for radionuclide therapy. Investigational agents, such as bombesin-based radiotracers, may address the shortcomings of treating prostate cancer with little to no PSMA expression. Full article

In the development of more electric aircraft, hydrogen powered fuel cells are one possible solution to progress towards emission reductions in aviation. Currently, there are numerous concepts for integrating fuel cells into future aircraft. The goal of this work was to develop a dynamic fuel cell model for simulations of the powertrain. The Modelica language together with the ThermoFluidStream (TFS) library from the German Aerospace Center (DLR) provided a suitable framework. The fuel cell model takes into account the electrochemical as well as thermodynamic behavior. Hence, the proposed multi-physics model allows simulating the whole fuel cell system, from the hydrogen tank to the electric grid. Under certain simplifications, this enables performing mission simulations of the complete powertrain of future aircraft. As such, polymer electrolyte membrane (PEM) fuel cells and solid oxide fuel cells (SOFC) were considered. The fuel cell models are checked for plausibility in a simple test case against data from the literature. Furthermore, two setups of possible applications are introduced: one for each fuel cell type, which come from two projects. The preliminary control systems of these architectures are presented. Afterwards, the first results of the fuel cell systems are discussed. These results show that the models ran robustly in various environments and operational states. They provided the desired accuracy to predict the behavior of a fuel cell, while maintaining low CPU times and being capable of enabling real-time simulations in the future. Full article

Background and aims: The effect of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) on left atrial pressure (LAP) in the presence of interventricular interaction and the Frank–Starling mechanism is unknown. We developed and validated a mock circulatory loop (MCL) incorporating a novel, 3D-printed biventricular heart model and Frank–Starling algorithm, and used this model to assess the determinants of LAP during VA-ECMO support. Methods: The MCL was designed to allow a separate ventricle or biventricular configuration, with or without an active Frank–Starling mechanism. The biventricular model with Frank–Starling mechanism was validated in terms of (1) the presence and degree of ventricular interactions; (2) its ability to simulate Frank–Starling physiology; and (3) its capacity to simulate normal and pathological cardiac states. In the separate ventricle and biventricular with Frank–Starling models, we assessed the effect on LAP of changes in mean aortic pressure (mAoP), ECMO pump speed, LV contractility and ECMO return flow direction. Results: In the biventricular configuration, clamping RA inflow decreased RAP, with a concurrent decrease in LAP, consistent with direct ventricular interaction. With a programmed Frank–Starling mechanism, decreasing RAP was associated with a significant reduction in both LV outflow and LV end-systolic pressure. In the biventricular model with a Frank–Starling algorithm, the MCL was able to reproduce pre-defined normal and pathological cardiac output, and arterial and ventricular pressures. Increasing aortic pressure caused a linear increase in LAP in the separate ventricle model, which was attenuated in the biventricular model with Frank–Starling mechanism. Increasing ECMO pump speed caused no change in LAP in the separate ventricle model (p = 0.75), but significantly decreased LAP in the biventricular model with Frank–Starling mechanism (p = 0.039), with stabilization of LAP at the highest pump speeds. Changing the direction of VA-ECMO return flow did not affect LAP in either the separate ventricle (p = 0.91) or biventricular model with Frank–Starling mechanism (p = 0.76). Conclusions: Interventricular interactions and the Frank–Starling mechanism can be simulated in a physical, biventricular MCL. In their presence, the effects of VA-ECMO on LAP are mitigated, with LAP reduction and stabilization at maximal VA-ECMO speeds. Full article

With the consequences of climate change becoming more urgent, there has never been a more pressing need for technologies that can help to reduce the carbon dioxide (CO₂) emissions of the most polluting sectors, such as power generation, steel, cement, and the chemical industry. This review summarizes the state-of-the-art technologies for carbon capture, for instance, post-combustion, pre-combustion, oxy-fuel combustion, chemical looping, and direct air capture. Moreover, already established carbon capture technologies, such as absorption, adsorption, and membrane-based separation, and emerging technologies like calcium looping or cryogenic separation are presented. Beyond carbon capture technologies, this review also discusses how captured CO₂ can be securely stored (CCS) physically in deep saline aquifers or depleted gas and oil reservoirs, stored chemically via mineralization, or used in enhanced oil recovery. The concept of utilizing the captured CO₂ (CCU) for producing value-added products, including formic acid, methanol, urea, or methane, towards a circular carbon economy will also be shortly discussed. Real-life applications, e.g., already pilot-scale continuous methane (CH₄) production from flue gas CO₂, are shown. Actual deployment of the most crucial technologies for the future will be explored in real-life applications. This review aims to provide a compact view of the most crucial technologies that should be considered when choosing to capture, store, or convert CO₂, informing future researchers with efforts aimed at mitigating CO₂ emissions and tackling the climate crisis. Full article

Nanoporous membranes are heterogeneous structures, with heterogeneity manifesting at the microscale. In examining particle transport through such media, it has been observed that this transport deviates from classical diffusion, as described by Fick’s second law. Moreover, the classical model is physically unsustainable, as it is non-causal and predicts an infinite speed of concentration perturbation propagation through a substantial medium. In this work, we have derived two causal models as extensions of Fick’s second law, where causality is linked to the effects of inertial memory in the nanoporous membrane. The results of the derived models have been compared with each other and with those obtained from the classical model. It has been demonstrated that both causal models, one with exponentially fading inertial memory and the other with power-law fading memory, predict that the concentration perturbation propagates as a damped wave, leading to an increased time required for the cumulative amount of molecules passing through the membrane to reach a steady state compared to the classical model. The power-law fading memory model predicts a longer time required to achieve a stationary state. These findings have significant implications for understanding cell physiology, developing drug delivery systems, and designing nanoporous membranes for various applications. Full article

We investigated whether the elimination of two major enzymes responsible for triacylglycerol synthesis altered the structure and physical state of organelle membranes under mild heat shock conditions in the fission yeast, Schizosaccharomyces pombe. Our study revealed that key intracellular membrane structures, lipid droplets, vacuoles, the mitochondrial network, and the cortical endoplasmic reticulum were all affected in mutant fission yeast cells under mild heat shock but not under normal growth conditions. We also obtained direct evidence that triacylglycerol-deficient cells were less capable than wild-type cells of adjusting their membrane physical properties during thermal stress. The production of thermoprotective molecules, such as HSP16 and trehalose, was reduced in the mutant strain. These findings suggest that an intact system of triacylglycerol metabolism significantly contributes to membrane protection during heat stress. Full article

Cortical neurons integrate upstream signals and random electrical noise to gate signaling outcomes, leading to statistically random patterns of activity. Yet classically, the neuron is modeled as a binary computational unit, encoding Shannon entropy. Here, the neuronal membrane potential is modeled as a function of inherently probabilistic ion behavior. In this new model, each neuron computes the probability of transitioning from an off-state to an on-state, thereby encoding von Neumann entropy. Component pure states are integrated into a physical quantity of information, and the derivative of this high-dimensional probability distribution yields eigenvalues across the multi-scale quantum system. In accordance with the Hellman–Feynman theorem, the resolution of the system state is paired with a spontaneous shift in charge distribution, so this defined system state instantly becomes the past as a new probability distribution emerges. This mechanistic model produces testable predictions regarding the wavelength of free energy released upon information compression and the temporal relationship of these events to physiological outcomes. Overall, this model demonstrates how cortical neurons might achieve non-deterministic signaling outcomes through a computational process of noisy coincidence detection. Full article

Many fundamental physical problems are modeled using differential equations, describing time- and space-dependent variables from conservation laws. Practical problems, such as surface morphology, particle interactions, and memory effects, reveal the limitations of traditional tools. Fractional calculus is a valuable tool for these issues, with applications ranging from membrane diffusion to electrical response of complex fluids, particularly electrolytic cells like liquid crystal cells. This paper presents the main fractional tools to formulate a diffusive model regarding time-fractional derivatives and modify the continuity equations stating the conservation laws. We explore two possible ways to introduce time-fractional derivatives to extend the continuity equations to the field of arbitrary-order derivatives. This investigation is essential, because while the mathematical description of neutral particle diffusion has been extensively covered by various authors, a comprehensive treatment of the problem for electrically charged particles remains in its early stages. For this reason, after presenting the appropriate mathematical tools based on fractional calculus, we demonstrate that generalizing the diffusion equation leads to a generalized definition of the displacement current. This modification has strong implications in defining the electrical impedance of electrolytic cells but, more importantly, in the formulation of the Maxwell equations in material systems. Full article

The state of well-being and health of our body is regulated by the fine osmotic and biochemical balance established between the cells of the different tissues, organs, and systems. Specific districts of the human body are defined, kept in the correct state of functioning, and, therefore, protected from exogenous or endogenous insults of both mechanical, physical, and biological nature by the presence of different barrier systems. In addition to the placental barrier, which even acts as a linker between two different organisms, the mother and the fetus, all human body barriers, including the blood–brain barrier (BBB), blood–retinal barrier, blood–nerve barrier, blood–lymph barrier, and blood–cerebrospinal fluid barrier, operate to maintain the physiological homeostasis within tissues and organs. From a pharmaceutical point of view, the most challenging is undoubtedly the BBB, since its presence notably complicates the treatment of brain disorders. BBB action can impair the delivery of chemical drugs and biopharmaceuticals into the brain, reducing their therapeutic efficacy and/or increasing their unwanted bioaccumulation in the surrounding healthy tissues. Recent nanotechnological innovation provides advanced biomaterials and ad hoc customized engineering and functionalization methods able to assist in brain-targeted drug delivery. In this context, lipid nanocarriers, including both synthetic (liposomes, solid lipid nanoparticles, nanoemulsions, nanostructured lipid carriers, niosomes, proniosomes, and cubosomes) and cell-derived ones (extracellular vesicles and cell membrane-derived nanocarriers), are considered one of the most successful brain delivery systems due to their reasonable biocompatibility and ability to cross the BBB. This review aims to provide a complete and up-to-date point of view on the efficacy of the most varied lipid carriers, whether FDA-approved, involved in clinical trials, or used in in vitro or in vivo studies, for the treatment of inflammatory, cancerous, or infectious brain diseases. Full article

This review discusses the recent advancements in cost-effective fermentation methods for producing bacterial nanocellulose (BC) from food and agro-industrial waste. Achieving economical cell culture media is crucial for large-scale BC production, requiring nutrient-rich media at low cost to maximize cellulose yield. Various pretreatment methods, including chemical, physical, and biological approaches, are stated to break down waste into accessible molecules for cellulose-producing bacteria. Additionally, strategies such as dynamic bioreactors and genetic engineering methods are investigated to enhance BC production. This review also focuses on the environmental impact assessment and updated application challenges of BC such as medical applications, energy storage/electronics, filtration membranes, and food packaging. By providing insights from the recent literature findings, this review highlights the innovative potential and challenges in economically and efficiently producing BC from waste streams. Full article

Growing high-quality crystals with ideal properties is of great importance. The morphology of crystal is one key factor reflecting product quality, as it can affect the performance of products and downstream operations. In this work, the current state of crystal morphology modification is reviewed from different perspectives. First, the most widely used crystal growth models are discussed. Then, a variety of crystal morphology control methods, which include adjustment of crystallization operation parameters, addition of foreign molecules, change of different solvents, membrane assistance, the addition of external physical fields and the use of ball milling are summarized. As for applications, the control of crystal morphology has application potential in pharmaceutical and material fields, for example, energetic materials and semiconductor materials. Finally, the future development direction of crystal morphology regulation is discussed. Full article