Physical Sciences

Abstract: Spatial self-organized patterns are ubiquitous features of vegetation ecosystems, and cyclic nontransitive competition serves as a crucial intrinsic mechanism for sustaining biodiversity. However, existing studies lack cross-scale comparative analyses of vegetation territorial competition based on multiple models. This study combines lattice models and continuous differential equation models to investigate the territorial occupation dynamics and spatial evolution of vegetation communities driven by cyclic competition. The results demonstrate that cyclic competition acts as a core mechanism maintaining vegetation biodiversity, which enables the self-organization of stable spiral wave patterns in space and supports the long-term dynamic coexistence of multiple species. Discrete and continuous models exhibit highly consistent macroscopic dynamical behaviors, which reveal the intrinsic dynamical characteristics of cyclic competitive systems. By integrating microscopic lattice simulation and macroscopic differential equation analysis, this study verifies that spiral waves represent a highly robust species coexistence mode and clarifies the coupled regulatory effects of species richness and stochasticity on system evolution. The findings further deepen the understanding of the complexity of vegetation ecosystems and provide important theoretical references for subsequent theoretical derivation and field observational research on vegetation community competition and evolution.

Abstract: Complex diseases challenge one of the oldest assumptions in medicine: that illness can be reduced to a single cause. Instead, increasing evidence suggests that many pathologies emerge from the collective dynamics of components interacting across molecular, cellular, physiological, behavioral, and ecological scales. Thus, we revisit the fundamental question of what a disease is through the lens of complex systems theory. In particular, we argue that diseases are better understood as emergent dynamical states of living systems that arise from the breakdown, reorganization, or destabilization of regulatory networks. Within this framework, mathematical models can describe health and disease as alternative attractors in a multidimensional state space, and disease onset often reflects critical transitions driven by stress, perturbation, or loss of resilience. Therefore, concepts from nonlinear dynamics, network theory, ecology, and statistical physics (such as bifurcations, hysteresis, phase transitions, and multistability) provide a unifying language to describe phenomena as diverse as patient comorbidity, psychiatric disorders, cancer progression, epidemic spreading, or neurodegeneration. We also discuss how multiscale models can bridge molecular mechanisms with organism-level behavior to reveal universal principles of complex diseases. This perspective implies that the future of medicine may depend on understanding not only the components of biological systems, but also the laws governing their collective organization, which could open new avenues for prediction, prevention, and control.

Abstract: Traumatic brain injury (TBI) triggers complex molecular responses that remain incompletely understood at the structural level, where it's highly connected to neurodegeneration and synaptic dysfunction. Growing evidence implicates intrinsically disordered proteins (IDPs), and proteins with intrinsically disordered regions (IDRs), as key regulators of stress-responsive signaling. In this study, we represent an in silico study of the 24 TBI-relevant proteins, such as MAPT, SERF2, SERBP1, BEX3, TDP43, NFL, C9orf16, C9orf58, APP, NRN1, NEFM, SYNGAP1, SNAP25, DLG4, APOC2, HCLS1, HMGB1, FUS, EPHA4, SEMA4D, S100B, PLEK, CAMK2A, and SNCA, integrating analysis of the predisposition for intrinsic disorder and liquid–liquid phase separation (LLPS) through RIDAO, FuzDrop, and AlphaFold platforms. We demonstrate that more than 90% of residues in SERF2, BEX3, MAPT, SERBP1, HMGB1, SNCA, and FUS are predicted as disordered. The amino acid sequences of NEFM, HCLS1, C9orf16, NEFL, C9orf58, SNAP25, SYNGAP1, S100B, and TDP43 contain between 50% and 90% of disordered residues, and the disorder contents of APP, APOC2, and DLG4 are 47.53%, 45.54% and 33.29%. Only five proteins (SEMA4D, PLEK, CAMK2A, EPHA4, and NRN1) have less than 30% disordered residues. The high prevalence of disorder in TBI-associated proteins correlates with their strong propensity for spontaneous liquid-liquid phase separation (LLPS). In fact, 15 proteins (FUS, SYNGAP1, MAPT, NEFM, SERBP1, HCLS1, SERF2, BEX3, C9orf16, TDP43, HMGB1, APP, NEF, DLG4, and SNCA) are expected to act as droplet drivers, and five more proteins (SEMA4D, C9orf58, SNAP25, CAMK2A, and EPHA4) can serve as droplet clients. The gene ontology analysis emphasized that the 24 TBI-related proteins (TBIome) are functionally associated with synaptic regulation, RNA metabolism, cytoskeletal dynamics, and mitochondrial stress response. We also show that human proteins interacting the members of TBIome are on average a bit more disordered than the human brain proteins in general. This extended TBI interactome is functionally connected to cytoplasmic translation, translation, synaptic vesicle cycle, modulation of chemical synaptic transmission, regulation of neurotransmitter levels, regulation of synaptic plasticity, neurotransmitter secretion, synaptic vesicle exocytosis, protein localization to synapse, and trans-synaptic signaling. Many of these proteins have strong LLPS potential as well. Therefore, high intrinsic disorder propensity and strong LLPS potential represent shared structural and functional features of proteins linked to the TBI-related pathophysiology. Collectively, these findings support a model in which disorder-based mechanisms contribute to post-traumatic molecular reprogramming, which underlie the pathological roles of TBI-related proteins.

Abstract: Aqueous two-phase systems (ATPSs) provide a versatile, fully aqueous platform for probing solute–water interactions and protein structure. This review first surveys the diversity and phase behavior of biphasic aqueous systems formed by polymers and salts. We describe how phase diagrams characterize ATPS formation and composition, and how both polymer chemistry and salt identity, more than molecular size alone, govern phase separation by modulating the solvent properties of water. Building on a modified binodal model, we show that phase separation and solute partitioning can be understood in terms of changes in aqueous solvent dipolarity/polarizability, hydrogen-bond donor/acceptor properties, hydrophobicity, and electrostatics, quantified via solvatochromic probes and homologous solute series. These measurements underpin solvent interaction analysis (SIA), in which the partition coefficients of small molecules and proteins across panels of ATPSs are used to generate “structural signatures” that sensitively report on amino acid substitutions, conformational changes, aggregation, ligand binding, osmolyte effects, and post-translational modifications, independent of protein size. We discuss how SIA can be implemented in vial-, plate-, and microfluidic formats and combined with diverse analytical readouts (HPLC, MS, colorimetric and immunoassays), and contrast this structure-focused approach with conventional concentration-only proteomic and biomarker strategies. Particular emphasis is placed on structure-based biomarker discovery, where disease-relevant shifts in proteoform distributions—especially glycosylation changes—are often more informative than bulk protein levels, and where SIA can complement or simplify complex glycomics and top-down proteomics workflows. As a case study, we describe the recently FDA approved isoPSA assay, which applies SIA principles to prostate-specific antigen by measuring cancer-associated structural alterations in circulating PSA via its partition behavior in a proprietary ATPS. IsoPSA generates a single index that discriminates high-grade prostate cancer from benign and low-grade conditions. Prospective, longitudinal, and MRI-integrated clinical studies demonstrate that IsoPSA^® improves pre-biopsy risk stratification, reduces unnecessary biopsies, and provides robust negative and positive predictive characteristics within the PSA “gray zone.” Collectively, the data support aqueous solvent interaction analysis as a broadly applicable, mechanistically grounded technology for protein characterization, drug–protein interaction studies, and structure-centric biomarker development, exemplified by the clinical translation of IsoPSA.

Abstract: We review a theoretical and experimental programme aimed at understanding two intimately related fundamental phenomena in biophysics: (i) the classical analogue of Fröhlich phonon condensation in macromolecules driven out of thermal equilibrium, and (ii) the consequent activation of long-range resonant electrodynamic intermolecular forces. Both phenomena are underpinned by explicit Hamiltonian models. The first is derived by applying the time-dependent variational principle (TDVP) to the quantum Wu--Austin model, producing a fully classical Hamiltonian in action-angle variables whose nonlinear rate equations exhibit a nonequilibrium phase transition, the channelling of supplied energy into the lowest-frequency collective mode. The second is grounded in a classical electrodynamic Hamiltonian for two coupled oscillating dipoles whose normal-mode structure predicts long-range (\( \sim 1/r^3 \)) resonant interactions, absent at thermal equilibrium but activated by out-of-equilibrium collective oscillations. We also discuss a complementary Hamiltonian approach that connects Fröhlich's rate equations directly to Hamilton's equations of motion, clarifying the role of bath-mediated nonlinear coupling and the conditions for strong condensation at room temperature. In addition, the TDVP is applied to a Davydov--Holstein--Fröhlich Hamiltonian describing electron--phonon motion along the backbone of a specific DNA sequence and its cognate restriction enzyme EcoRI: the time-domain Fourier cross-spectrum of the resulting electron currents exhibits a sharp co-resonance peak for the canonical recognition sequence that disappears upon randomisation, providing a sequence-specific electrodynamic signature of DNA--protein recognition. Experimental evidence from THz near-field spectroscopy, fluorescence correlation spectroscopy, and direct observation of protein clustering is reviewed in relation to these theoretical predictions. The results establish a coherent physical picture suggesting that metabolic energy supply can play a role in driving macromolecules into coherently oscillating states that activate selective, distance-reaching electrodynamic forces capable of contributing to the organisation of biochemical reactions in living matter.

Abstract: Low-field nuclear magnetic resonance (NMR)-based stimulation is an emerging non-invasive biophysical approach for tissue modulation. Unlike optical or mechanically mediated modalities, its magnetic-field components are less constrained by tissue depth, enabling distributed exposure of deep anatomical structures. This review examines its physical principles, focusing on cyclic adiabatic passage, longitudinal relaxation time (T1), and how field parameters and tissue relaxation properties shape the spatial and temporal distribution of the applied perturbation. Clinical studies indicate a favorable safety profile together with reported improvements in pain, physical function, quality of life and related outcomes across several musculoskeletal indications, while experimental studies demonstrate modulation of inflammatory signaling, mitochondrial function, metabolism and redox-sensitive pathways. Two major mechanistic questions are identified: how a relaxation-weighted perturbation, potentially shaped by extracellular, pericellular or matrix-associated tissue properties, is transmitted to intracellular signaling pathways, and how weak non-thermal perturbations are amplified into specific biological responses. A multi-level framework is proposed to investigate how physical perturbations are distributed in tissue, transmitted to intracellular pathways, shaped by cellular state and amplified into measurable biological responses. Low-field NMR-based stimulation represents a physically plausible but mechanistically unresolved modality whose further development will depend on integrating magnetic resonance physics with systems-level biology.

Abstract: Given that red blood cells (RBCs) are the most abundant cells in blood, their morphology and mechanics strongly affect blood rheology. Furthermore, changes in the physiological functions and health status of an organism can also affect RBC mechanics. Therefore, understanding the mechanical properties of RBCs holds substantial research value in the biomedical field. Optical tweezers (OT) technology has become a crucial method for measuring and analyzing the mechanical properties of RBCs, owing to their unique advantages such as non-contact manipulation and piconewton-level force sensitivity. This review first outlines the basic mechanical properties of RBCs, the mechanical sensing principles of optical tweezers, and their basic manipulation modes. It then focuses on the measurement and application of key mechanical parameters, such as the deformation index and shear modulus. Furthermore, the review also covers the integration of optical tweezers with Raman spectroscopy, fluorescence, and microfluidics. These combined approaches allow for the simultaneous acquisition of mechanical and molecular data, dynamic monitoring of mechanical state changes, and analysis of external stimuli and physiological mechanisms, thereby supporting disease diagnosis, drug efficacy evaluation, as well as artificial blood quality assessment.

Abstract: The pervasive allometric scaling laws in biology, most notably Kleiber’s law (B ∝ M^3/4), conflict with the predictions of classical Euclidean dimensional analysis (B ∝ M^2/3). While the West-Brown-Enquist (WBE) model resolved this paradox using hierarchical fractal networks, and Barenblatt’s incomplete similarity formalized the fractional exponents, a rigorous symmetry framework connecting the two has been lacking. In this paper, we reconstruct dimensional analysis from the perspective of Lie group theory, demonstrating that incomplete similarity corresponds to a deformed scaling Lie group parameterized by anomalous dimensions. We show that the internal fractal network breaks the isotropic Euclidean scaling symmetry. Crucially, we formulate natural selection and physical optimization as a constrained optimization problem on the Lie group parameters. Maximizing the throughput exponent subject to the physical bounds of fractal dimensions uniquely selects the anomalous parameters, rigorously yielding the 3/4-power law. Substituting these optima back into the Lie group action reveals an algebraic dimensional promotion: the broken symmetry is restored, but the effective group is isomorphic to a 4D Euclidean scaling group. This provides a rigorous algebraic foundation for the “fourth dimension of life,” establishing allometric scaling as the universal geometric invariant of optimized resource-distribution networks.

Abstract: Gastrointestinal (GI) cancers account for a quarter of all cancer cases worldwide and are responsible for a third of cancer deaths. One of the characteristic features of GI tissue is its multilayered structure, which in addition to multiple scattering, complicates optical-spectral analysis. The risk of lymph node metastasis in GI cancer is primarily related to the depth of tumor invasion. The use of spectroscopic diagnostics and photodynamic therapy for the detection and treatment of GI cancer is a rapidly developing field. The method proposed in this paper for layer-by-layer optical properties assessment, suitable for real-time clinical application to the walls of hollow organs, allows for both determining the depth of tumor invasion into the GI organ wall and calculating the absorbed dose layer-by-layer. This paper proposes a method for recording spectral data in two geometries, diffuse reflectance and transmission, using light delivery from both the external and internal surfaces of the gastrointestinal tract wall. Layer-by-layer assessment of optical properties was performed using a developed algorithm based on the inverse adding-doubling method with initial optical properties values ​​determined using the modified two-stream Kubelka-Munk model with the accuracy equal to 86±13%. The method was approbated in clinical conditions.  Based on the results of the work, the developed method for assessing the optical properties of multilayered biological tissues exhibited sufficient speed and accuracy for in vivo application to personalize laser-induced therapy by correction of the laser dose.

Abstract: We study the effects of weak magnetic fields (around 2 mT) on the growth of Staphylococcus aureus (S. aureus) in the presence of a few sweeteners (monosaccharides, disaccharides, sugar alcohols, and consumer-grade sweeteners). Bacterial growth rates were compared in various magnetic fields at room temperature. Bacterial growth was estimated using optical absorbance measurements at various wavelengths, and pH values were manually estimated using pH strips. Absorbance was measured at 492 nm and 630 nm, which are wavelengths comparable to the size of a cell of S. aureus after division. This comparability plays a vital role in the scale of measured absorbance values. The results imply that bacterial growth may be reduced due to acidic byproducts formed by metabolizing sugars or sugar alcohols, as an increasingly acidic solution is less ideal for bacterial growth. Magnetic fields were also found to have a minor effect on pH estimates. These results reveal potential effects on microorganisms in the presence of sugars and sugar alcohols in addition to weak magnetic fields, demonstrating the contribution of various environmental conditions with increasing prevalence in the modern day.

Abstract: Microtubules contain ordered aromatic amino-acid networks whose optical excitations have been proposed to support non-trivial energy-transfer dynamics. Here, we examined whether bound tryptamine ligands can perturb the excitonic structure of the tubulin tryptophan network. A virtual screen of 294 tryptamines was performed across seven known binding regions of the tubulin heterodimer using AutoDock Vina. From this screen, top-ranked tryptamine ligands were carried forward for excited-state analysis. Geometry optimization and time-dependent density functional theory (TD-DFT) calculations were used to obtain vertical excitation energies and transition dipole moments for the ligand-bound states in the ultraviolet range. These ligand properties were then incorporated into a tight-binding Hamiltonian describing the tubulin tryptophan excitation network in order to evaluate changes in exciton energies and eigenvector delocalization. The calculations indicate that tryptamine binding can modify the excitonic landscape of tubulin in a ligand-dependent manner, with the magnitude of the perturbation governed by excitation wavelength, transition dipole strength, and spatial orientation relative to the intrinsic tryptophan network. These results support the possibility that aromatic ligands may provide a chemically tunable route to altering the optical response of tubulin and motivate future experimental tests of ligand-dependent modulation of microtubule photophysics.

Abstract: Pulse wave propagation through blood vessels is affected by many biophysical parameters that change with aging. The aim of this study was to investigate both theoretically and experimentally how the pulse wave velocity changes in the vertical position and to introduce a new parameter in biophysics - pulse wave acceleration - PWA. On a biophysical model of the cardiovascular system, placed in horizontal and vertical position, pressure waveforms were measured along the arterial tree at several sites at different diastolic pressures and pump frequencies. Blood flow waveforms on the carotid and femoral arteries in the supine and standing position were measured on the subjects. The results showed that the pulse pressure wave accelerates in the direction of gravity and decelerates in the opposite direction both in the model and in humans. A new biophysical parameter - PWA - was defined, and the experimental results are in agreement with the mathematical model. Due to the acceleration of the pulse wave, the reflected wave in the standing position arrives earlier in systole and affects the increase in pressure. The novel biophysical parameter provides a more accurate assessment of the age of the cardiovascular system and a more precise diagnosis of increased blood pressure.

Abstract: FLASH radiotherapy, characterized by ultra-high dose rates, has been shown to reduce normal tissue toxicity while preserving tumor control, yet its underlying mechanism remains unresolved. Existing models based on radiolytic oxygen depletion (ROD) successfully capture dose-rate dependence but fail to explain key experimental features, including threshold-like onset, saturation of the sparing effect, and sensitivity to temporal delivery structure. Here, we propose a mechanistic framework — Memory-modulated Radiolytic Oxygen Depletion (M-ROD) — that extends classical ROD by incorporating a bounded, history-dependent internal state. The dynamical structure of this state — cooperative activation, bounded feedback, and characteristic decay — is consistent with that of cooperative biological regulatory processes, including gene regulatory networks. In this framework, dose-rate–dependent stress activates a nonlinear biological state that evolves through induction, bounded feedback, and decay, modulating radiosensitivity alongside oxygen effects. We show that the framework reproduces the defining characteristics of FLASH, including sharp threshold-like transitions, plateau behavior, and strong dependence on pulse spacing, duty cycle, and irradiation sequence, while reducing to conventional radiobiology under low dose-rate conditions. The pulse-spacing sensitivity that distinguishes M-ROD from memoryless models requires the state to relax on a characteristic timescale τ_M of approximately 10–100 ms; we show that bioelectric membrane dynamics, treated as a passive RC system using parameter values from standard electrophysiology, naturally produce relaxation in this range without parameter tuning. The model predicts that the magnitude of the FLASH effect is governed by the extent of state activation rather than dose rate alone, providing a mechanistic explanation for variability across experiments. These results support the interpretation of FLASH as an emergent state transition in a dynamical biological system and offer experimentally testable predictions that distinguish it from memoryless models.

Abstract: Forward osmosis (FO) membranes are commonly evaluated through macroscopic observables such as water flux and reverse solute flux. However, these quantities do not necessarily reveal whether water permeation and solute leakage remain governed by the same dominant transport pathways, particularly in heterogeneous nanostructured membranes where selective nanochannels and defect-mediated pores can contribute differently to solvent and solute transport. Here, we introduce a hierarchical diagnostic framework to assess transport coherence loss in heterogeneous FO membranes. The framework comprises a baseline model (BM), an extended model (EM) including chemistry–geometry coupling through accessibility loss, and a full model (FM) incorporating selective pore-size heterogeneity. The flux ratio R=J_s/J_w is used as a regime-based diagnostic descriptor of transport organization, and its normalized form is used to map coherence variations across the state-space defined by structural selectivity and nanochemical state. The results show that chemistry–geometry coupling produces the first clear reorganization of the coherence landscape, whereas pore-size heterogeneity mainly broadens the response while preserving its dominant topology. Simulations based on both Monte Carlo and experimentally derived pore-size distributions show consistent trends. Overall, the BM–EM–FM hierarchy offers an interpretable framework for describing transport coherence loss and the emergence of leakage-prone regimes in heterogeneous FO membranes.

Abstract: Ant navigation is widely explained through pheromone-mediated trail formation and reinforcement, which accounts for efficient shortest-path selection in two-dimensional environments. However, certain three-dimensional foraging behaviors—such as navigation toward suspended food sources or the rapid use of newly established material paths—raise questions about whether chemical gradients alone fully explain route detection and selection. This paper examines experimental observations that appear difficult to reconcile with purely diffusion-based pheromone models and proposes an expanded framework incorporating the concept of Intrinsic Energy Spin (IESpin) fields. According to this hypothesis, all entities possess an intrinsic spin (ISpin) that encodes their fundamental intrinsic properties. The ISpin field propagates through space and interacts with other entities in the universe, giving rise to an IESpin field. These fields are proposed to propagate preferentially through continuous matter, potentially allowing organisms to detect spatial pathways and resource signatures via field gradients. The hypothesis generates experimentally testable predictions concerning material-dependent transmission, pheromone-independent navigation, and the possible existence of non-chemical sensory mechanisms in ants.

Abstract: Many peer-reviewed studies report spatiotemporal or kinetic parameters of running gait without considering their stability, temporal structure, or relationship to typical run durations. This study investigated the stability and temporal structure of key spatiotemporal and kinetic parameters during a 30-minute easy-paced treadmill run (13 km∙h-1) while participants wore familiar and unfamiliar every day running shoes. Step-level data were analysed across the full time series and in sequential 1-minute epochs to determine how long each parameter takes to reach practical stability and whether this differs between shoe conditions. Approximately, 2,450 steps were analysed per condition. Within-participant variability was low (CV< 2.5%) for all parameters and conditions except for peak impact force (CV=6.9-7.0%) and average loading rate (CV=8.4-8.7%). DFA-α indicated persistent temporal structure for stride duration, swing time, and active peak force, whereas loading-phase kinetics showed weak long-range dependence. No significant differences were observed between shoe conditions for variability or temporal structure, although ground contact time was slightly longer in the unfamiliar shoe. Practical windows of stability relative to each participant’s 30-minute mean ranged from 11 to 17 minutes for spatiotemporal variables, 9-17 minutes for active peak force, and within the first minute for impact related parameters and impulse. These findings indicate that studies examining spatiotemporal and kinetic parameters during easy-paced treadmill running require 11-17 minutes of continuous data to obtain 1-minute epoch estimates that are practically stable relative to 30-minute averages, regardless of footwear familiarity.

Abstract: This present study adopted the Box-Behnken Design (BBD) with Response Surface Methodology (RSM) to identify the optimum input processing factors (heating temperature: 40, 50 and 60 °C, heating time: 30, 45 and 60 min and pressing height: 60, 80 and 100 mm) for estimating the oil output parameters (mass of oil, oil yield and oil expression efficiency) and deformation energy. The mechanical properties examined were the hardness and secant modulus of elasticity. Based on the full quadratic model, which includes both significant and non-significant terms, the optimal input processing factors were determined to be a heating temperature of 60 °C, a heating time of 52.5 min, and a sample pressing height of 100 mm, with coefficient of determination (R²) values ranging from 0.68 to 0.95. The linear models with the significant terms predicted the mass of oil of 33.36 g, oil yield of 21.5 %, oil expression efficiency of 65.47 % and the experimental deformation energy of 1080.82 J. The percentage error values between the experimental and theoretical deformation energies were from 1.35 to 28.31%, suggesting that the varying input processing factors affected the coefficients of the tangent curve model for fitting the experimental force-deformation curves. The hardness and secant modulus of elasticity values ranged between 3.65 and 7.09 kN/mm and 123.98 to 150.39 MPa, indicating that the varying input processing factors had a significant effect on the stiffness of the bulk hemp seeds. These findings are useful for modelling and optimising the mechanical behaviour of oilseeds using a mechanical screw press to enhance oil recovery efficiency.

Abstract: This work presents a discrete theoretical model in which basal metabolic rate B is described as a dynamic function of an organism’s ontogenetic stage n. Instead of treating B only as a static function of body mass M, we adopt the form B(n) = B₀ M^b(n), in which the effective scaling exponent b(n) varies systematically throughout development. In contrast to classical approaches, such as Kleiber’s empirical law (B ∝ M^3/4) and the continuous fractal model of West–Brown–Enquist (WBE), which assume a constant exponent, the present framework emphasizes how the metabolic scaling relationship itself can evolve over the life cycle of a single individual. The model is inspired by a Fibonacci-based description of growth in discrete stages, leading to analytic expressions for b(n) that connect ontogenetic progression to changes in the scaling between metabolism and mass. In this setting, Kleiber’s constant B₀ ≈ 70 kcal/day is reinterpreted as a metabolic anchoring point, linking the classical law B ≈ 70 M^3/4 to a developmentally explicit formulation. We show that the resulting trajectory B(n) captures, at a conceptual level, how metabolic scaling can shift from strongly sublinear behavior at early stages towards an almost linear regime as n increases, and that the predicted basal rates remain compatible, in order of magnitude, with values reported for mammals of different sizes. In this way, the work offers a unified framework that connects the evolution of B(n) across ontogeny to the recursive organization of biological growth.

Abstract: Permeation of different chemical substances across the membrane is of utmost importance to the life and health of a living cell. Depending on the nature of the permeant, the process is mediated by either the protein (e.g., membrane channels) or lipid phases of the membrane, or both. In the case of small and physiologically important gas molecules, namely O2 and CO2, the literature supports the involvement of both pathways in their transport. The extent of involvement of the lipid phase, however, is directly dependent on the nature of the lipid constituents of the membrane that determine its various structural and physicochemical properties. In this study, we use molecular dynamics simulation, as a method with sufficient spatial and temporal resolutions, to analyze these properties in heterogeneous lipid bilayers, composed of phospholipids with varied tails, sphingomyelin, and cholesterol, to different degrees. Together with the calculation of the free energy profiles, diffusion constants, and gas diffusivity, the results shed light onto the importance of the lipid phase of membranes in gas transport rate and how they can be modulated by their lipid composition.

Abstract: This paper presents the first experimental study of the physical properties of the millimeter-wave radio response of aqueous media and biological objects to external centimeter-wave electromagnetic radiation. It has been hypothesized that the spectrum of the radio response to external millimeter-wave radiation contains not only frequencies an order of magnitude or more lower than the radiation signal, but also frequencies close to the radiation signal and even frequencies higher than the external signal. This radio response property would suggest that each point in an aquatic environment exposed to electromagnetic waves could be a source of a radio response across an ultra-wide spectrum of electromagnetic frequencies. Experiments have demonstrated the presence of a radio response at frequencies of 61,2 GHz, 94 GHz, and 118 GHz when water is irradiated in the microwave range of 1,16–5,6 GHz at a power flux of 10 mW/cm2. The experimental results prompt a new examination of the comparative effects of 4G and 5G cellular electromagnetic waves on humans.