Abstract: Telmisartan (TEL) is a non-peptide, orally administered antihypertensive agent primarily known as angiotensin II type 1 (AT1) blocker. In this review, we provide a detailed overview of how TEL modulates voltage-gated Na⁺ current (I_Na) and affects action potential (AP) firing behavior. TEL exerts differential stimulatory effects on the peak and late components of I_Na when subjected to brief depolarizing pulses across a range of cell types, such as mHippoE-14 hippocampal neuron, cultured dorsal root ganglion neurons, and HL-1 atrial cardiomyocytes. TEL can augment the inactivating (persistent) I_Na elicited by ascending long ramp pulse in mHippoE-14 cells. By using a parvalbumin-expressing interneuron-based modeled cell combined with bifurcation analysis, it is possible to predict how applied current influences subthreshold oscillations and the generation of somatic spiking in the presence of TEL. According to the Hodgkin-Huxley model, mimicking the action of TEL—characterized by an increased peak amplitude of I_Na and a slowed inactivation time course—leads to the emergence of periodic oscillations in membrane potential. Using a Markovian process, a separate model can also be mathematically constructed, showing that changes in certain rate constants can simulate the effect of TEL on I_Na in cardiac cells. The molecular docking prediction between TEL and the NaV1.7 channel was made by expected formation of hydrophobic interactions as well as hydrogen bonding. Beyond its antagonistic action on AT1 receptor and agonistic activation of peroxisome proliferator-activator-γ, the direct stimulation of I_Na may also contribute to its modulation of AP firing in various excitable cells. Current evidence supports TEL’s modulatory impact on Na_V channel activity and cellular excitability, while also acknowledging that the mechanism—whether direct or indirect—remains under investigation.

Abstract: Background: Intraoperative radiotherapy with low-energy X-rays (IOXRT) is an increasingly utilized modality during breast conserving therapy (BCT). However, the molecular mechanisms by which it affects the postoperative microenvironment remain to be fully elucidated. Surgical wound fluid (WF) has been demonstrated to modulate cancer cell behavior; however, its metabolomic composition has not been previously characterized in the context of breast cancer. The objective of this study was to evaluate metabolic alterations in postoperative WF and to determine whether IOXRT induces distinct metabolic signatures compared with mastectomy (AMP).Methods: Postoperative WF was collected from 54 breast cancer patients (38 BCT IOXRT; 16 AMP) at two time points: day 1 (A) and day 5 (B) after surgery. The samples were then subjected to analysis using ¹H NMR spectroscopy, encompassing NOESY, CPMG, and JRES techniques. A total of 114 spectral signals were quantified, and 42 metabolites were identified. Multivariate analyses (PCA, PLS DA, OPLS DA) and Wilcoxon signed rank tests were applied to assess temporal and intergroup differences.Results: A clear metabolic separation between time points A and B was observed in both treatment groups. However, statistical analysis revealed no significant differences between BCT IOXRT and AMP. In BCT IOXRT, on the fifth day, WF exhibited a decline in branched chain amino acids, asparagine, lysine, methionine, and glutamate, concomitant with an increase in lactate and pyruvate. AMP-specific alterations encompassed a decrease in 2-oxoglutarate and hypoxanthine on the first day, along with an increase in glucose and creatinine on the fifth day. A decline in ketone bodies (3-hydroxybutyrate, acetoacetate, acetone) was observed in both groups.Conclusions: Postoperative WF demonstrates dynamic metabolic changes reflecting early wound healing processes and treatment-related effects. IOXRT has been found to be associated with enhanced glycolytic signatures and reduced amino acid levels, suggesting altered metabolic activity in the irradiated tumor bed. The metabolomic profiling of WF has the potential to offer a novel source of biomarkers, which could facilitate the assessment of treatment response and tumor microenvironment characteristics.

Abstract: Biological coherence arises from coordinated integration of redox chemistry, hydration dynamics, electromagnetic interactions, and bioenergetic flux. Although substantial progress has been made in characterizing these processes individually, current frameworks do not fully explain how distributed biochemical events achieve stable temporal coordination across scales. In thermally noisy, dissipative environments, energy alone cannot account for sustained biological organization. A missing element is the establishment and renewal of phase reference - the temporal alignment that enables spatially distributed processes to act in synchrony. Here we propose a physical mechanism for phase reference access and anchoring based on cyclic nanodomain dynamics at a nanoscale redox-photonic interface previously termed the Redox Photonic Coupling System (RPCS). This interface supports an additional functional modality - phase breathing - a process mediated by molecular nitrogen (N₂) through which cyclic nanodomain nucleation and collapse anchors and sustains phase reference in living systems. Nitrogen-mediated oscillatory boundary dynamics create transient coherence windows that permit local access to phase reference, enabling phase-aligned oxidative-reductive resolution and anchoring of phase onto redox-generated Photonic Activation Quanta (PAQs). Absorption of phase-conditioned PAQs by adjacent hydration shells enables generation and accumulation of centropy, defined as stored organizational capacity that supports coordinated biological work.This framework identifies phase breathing as a previously unrecognized mechanism sustaining biological coherence and assigns molecular nitrogen a structural organizational role beyond respiratory dilution. By integrating nanodomain mechanics, photonic phase conditioning, and redox dynamics within a single interface, it provides a mechanistic basis for how coherent biological function is generated and maintained.

Abstract: The relationship between the thin adsorbed water layer conventionally observed on hydrophilic surfaces and the much larger "exclusion zone" described in the literature has remained unclear. In this review, we survey the evidence for both phenomena and propose that they are intimately connected: the adsorbate constitutes a structurally distinct phase that generates a magnetic field, which in turn diamagnetically orders the surrounding water over much larger distances. This model reconciles the thin adsorbate with the much larger exclusion zone, and is consistent with available data, with broader implications for water’s magnetic properties.

Abstract: Molecular interactions underpin the functioning of the living cell. Molecules exist in distinct quaternary structural forms, associate with molecular partners in signaling cascades, form transient quinary interactions, localize in membrane domains, and cluster in membrane-less condensates. Measuring the concentration, size, and dynamics of these molecular assemblies remains an enduring biophysical challenge, particularly in cells, where heterogeneity is the rule rather than the exception. Orthogonal signals derived from fluorescence lifetime, fluorescence fluctuations, and fluorescence polarization provide valuable metrics for probing interactions and environments, concentration and size, as well as rotational dynamics, respectively. This paper combines fluorescence lifetime imaging microscopy with image correlation analysis and polarization to determine the concentrations, brightness, lifetime, and rotational correlation time of different fluorescent states. A two-population model is examined as a prototypical example of a heterogenous system. The analysis is illustrated on a simple fluorescence model system, where cluster densities, relative brightnesses, lifetimes and rotational correlation times are extracted.

Abstract: This article addresses a current point of contention in the field of single molecule/single particle tracking, as well as relevant literature, and supplements it with some published cell-based experiments to illustrate our conclusions and known theorems. We attempt to explain the controversy surrounding the differing biophysical and cell biological results of studies on the individual molecule and those “at the single-molecule level” as well as at the level of many molecules in such a way that even readers who are unfamiliar with the subject can understand it without having to read all the mathematical, physical, and biophysical references.

Abstract: A conscious moment feels instantaneous, yet its ingredients are spread out in space, so signals take time to travel and integration must occur within a window of duration θ. In Stack Theory, Occurrence means each ingredient is true at least once within the window, while CoInstantiation means all are true together at some time. The Temporal Gap is Occurrence without CoInstantiation. Here, I show that if unity requires CoInstantiation and ingredients must exchange causal influence within window under a signal speed ceiling v, then the system diameter D satisfies D ≤ κvθ, with κ = 1 for hub exchange and κ = 1/2 for all-to-all exchange. A minimal message passing model shows fragmentation at these thresholds. Primate corpus callosum data imply size lower bounds on θ. This may rule out co-instantiated consciousness for liquid brains like ant colonies, AI on contemporary hardware, and it implies size constraints for proposed human–AI hybrids.

Abstract: Red blood cell (RBC) deformability is a key determinant of microcirculatory flow and can be altered in hematological disorders such as chronic lymphocytic leukemia (CLL). This study aimed to evaluate RBC deformability under controlled microfluidic flow conditions and to assess the influence of software platform choice on deformability quantification. RBC suspensions from healthy individuals and untreated CLL patients were analyzed using a microfluidic imaging system across a range of shear rates. A dedicated image-processing algorithm was developed and implemented in two software environments (LabVIEW and Python) to automatically detect deformed cells, measure major and minor cell axes, and calculate the deformability index (DI). Both analytical approaches demonstrated a shear-dependent increase in DI in healthy controls, whereas RBCs from CLL patients exhibited reduced deformability and a blunted response to increasing shear rates, particularly at intermediate shear rates. Although LabVIEW produced consistently higher absolute DI values than Python, both platforms showed strong correlation and preserved the same relative trends and group discrimination. These findings demonstrate that microfluidic image flow analysis provides a robust approach for assessing RBC biomechanics and highlight the importance of standardized image-processing workflows for reliable deformability quantification across software platforms.

Abstract: Quantitative structure–activity/property relationship (QSAR/QSPR) is a well-established methodology widely used to model molecular properties based on structure, and is applied in fields such as drug design and environmental protection. The knowledge and procedures developed and used in QSPR modelling will be applied to the validation of protein folding rate models. Understanding the protein folding process is considered one of the most important scientific topics, and identifying the fundamental factors responsible for protein folding has been the subject of intensive research over the past 30 years [1]. Among the structural descriptors determining the protein folding rate, the length of the protein sequence, the content of regular secondary structures, and the average contact row distance between amino acids in the 3D structure are the most important. Comparative studies of different methods for predicting protein folding rates are occasionally published, and we conducted one such study. We found that the experimental data in literature databases and the data available online are inconsistent and scattered. This is partly due to differences in experimental data and protein sequence lengths, but more so due to the questionable quality of the models themselves. We observed very large deviations in the predictions of ln(kf) by some of the analysed models implemented as web servers. The root mean square errors (RMSEs) of some of the analysed models in predicting ln(kf) for a new external set of proteins are much larger than the RMSEs obtained for the same models on the training sets. External validation demonstrates that protein folding rate models available on web servers have accuracy for external protein sets comparable to that of a simple model based solely on the logarithm of protein chain length. This finding, which highlights the importance of external model validation as recommended by the OECD guidelines for QSAR validation, is fundamental and offers a new perspective for improving protein folding rate models by applying the knowledge and procedures used in the QSPR methodology.

Abstract: The emergence and persistence of life pose a profound paradox. Statistical estimates of abiogenesis under standard prebiotic models yield extremely low probabilities (10⁻⁷⁸–10⁻¹⁰⁰), although such values are strongly model‑dependent and do not constitute evidence against naturalistic origins. Rather, they highlight a gap between current physical chemistry and the observed robustness of biological organization. Here we propose that both phenomena can be explained by the action of a hitherto unobserved informational reservoir that subtly “leaks” into biological systems, biasing microstate probabilities in real time. While quantum coherence and nonlocality currently represent the most plausible physical substrates, the hypothesis deliberately remains agnostic about the ultimate origin of this reservoir. Crucially, the transfer need not be intentional; it may constitute an unintended “crosstalk” across an ontological boundary—analogous to sound leaking through a wall between apartments. This framework offers a strictly naturalistic alternative to intelligent design theories while generating falsifiable predictions distinguishable from both pure chance and directed panspermia.

Abstract: The method of X-ray Footprinting and Mass Spectrometry (XFMS) using high brightness synchrotron X-ray sources has become an established method in structural biology and is based on the radiolytic production of hydroxyl radicals which oxidatively modify protein sidechains. While other methods of producing hydroxyl radicals are available, one benefit of using high flux density sources is that hydroxyl radical scavenging reactions can be minimized, and exposure times kept short to minimize secondary reactions. Here we present an application of the XFMS method using low dose rate X-rays from a commercial instrument. We demonstrate the feasibility of the approach using short peptides, characterizing the oxidative modifications +14, +16, and +32 Da under both aerated and low-oxygen conditions, and we additionally quantify the hydrogen peroxide production for various doses using the low dose rate source. These results provide fundamental information on the oxidative damage to peptides due to hydroxyl radicals using a low dose rate X-ray source.

Abstract: Firefly luciferase exhibits a puzzling anticorrelation: its quantum yield ($\phi$) increases dramatically upon enzyme binding, yet the fluorescence lifetime ($\tau$) becomes significantly shorter. While standard biochemistry attributes this solely to non-radiative suppression, this paradox has led to speculation about quantum electrodynamical effects, specifically the Purcell enhancement in a biological nanocavity.In this work, we critically evaluate the plausibility of luciferase acting as a dielectric optical cavity. By applying fundamental limits of Mie theory and wave optics to the protein's physical dimensions and refractive index, we demonstrate that the required Purcell factors ($F_P \approx 40$) are physically unattainable in the Rayleigh scattering regime ($ka \ll 1$) defined by the protein structure. Consequently, we argue that the observed kinetic data are better explained by an intrinsic change in the emitter's electronic structure. Specifically, the active site (containing both hydrophobic residues and charged side chains like Arg218) likely enforces a rigid, planar conformation on oxyluciferin, dramatically increasing its transition dipole moment ($\mu$) and thus its intrinsic radiative rate ($\Gamma_0$). This analysis excludes the necessity of exotic photonic cavities, redirecting focus back to precise electrostatic and steric tuning by the enzyme.

Abstract: Biological redox chemistry is traditionally described in terms of oxidant and reductant abundance, redox potential, and associated measures of oxidative stress. While informative, these scalar descriptors fail to explain why systems with comparable redox activity can exhibit profoundly different functional outcomes, or why the same pathology, across different biological contexts, may display opposing redox stress phenotypes. Here, we introduce redox coherence and redox decoherence as distinct emergent biological states arising from the integrity of a Redox Photonic Coupling System (RPCS). In this framework, redox chemistry is organized along two coupled axes - oxidative excitation and reductive assimilation - whose spatiotemporal synchronization within a nanodomain Coherence Interface (CI) determines whether redox-derived excitation is resolved into organized hydration shell architecture associated with adjacent biological substrates or dissipated through unstructured pathways.We define redox resilience as the capacity of the system to restore coherent resolution following perturbation, emphasizing recovery dynamics rather than static redox balance, and identify loss of this resilience as the defining feature of redox decoherence. Within this framework, oxidative and reductive stress are not primary causes but directional expressions of an underlying decoherent state, shaped by axis dominance and CI desynchronization.Distinct photonic outcomes are associated with these organizational states: Photonic Activation Quanta (PAQ) reflect coherent resolution and propagation of excitation, tightly coupled to organized water formation, whereas Decoherent Photon Emissions (DPE) mark dissipative resolution modes. The PAQ:DPE ratio thus provides a dynamic, state-sensitive readout of redox organization and recovery capacity, rather than a measure of oxidant or antioxidant burden alone.Together, this framework reframes redox biology as a state-dependent process governed by spatiotemporal organization, structured hydration and resilience, offering a unifying principle for interpreting redox physiology and pathology beyond redox magnitude.

Abstract: Computational biology has completely changed the paradigm of drug development, moving it from random screening to a logical, predictive science. Three fundamental computational approaches Structure-Based Drug Design (SBDD), Ligand-Based Drug Design (LBDD), and Network Pharmacology are integrated in this review's potent, synergistic framework. In order to uncover important treatment targets, we show how these approaches function together as a coherent pipeline, with Network Pharmacology offering a systems-level blueprint of disease mechanisms. This realization immediately drives LBDD for intelligent screening utilizing pharmacophore and QSAR models in the absence of structural data, and SBDD for atomic-level rational design in the presence of it. Importantly, we stress that the foundation of this integrated strategy is early and iterative in silico ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling, which guarantees the development of molecules with the best possible safety and drug-likeness. A new era of effective, multifaceted pharmaceutical development is ushered in by this technique, which de-risks the discovery process and speeds up the time from target identification to viable lead candidate by combining different disciplines into a single workflow.

Abstract: LexA/signal peptidase-like superfamily proteins are serine proteases that use the Ser-Lys catalytic dyad to carry out their biological functions. Here, we investigate the two known families of LexA/signal peptidase-like superfamily proteins, the type I signal peptidase and LexA endopeptidase domain-like, and describe the structural catalytic cores that govern the catalytic residues in these proteins. We show that the structural catalytic core of these proteins is a combination of two subzones, the NucBaseOmega and Omega. While the NucBaseOmega subzone is a pattern observed in all proteins of the studied superfamily, the Omega subzone in the type I signal peptidase family differs from that of the LexA endopeptidase domain-like family. Thus, the amino acids and 3D characteristics of the Omega subzone are a structural marker of the proteins belonging to a specific family.

Abstract: Cellular dynamics rely on numerous physical processes, including phase separation, membrane remodeling, stress relaxation, transport and stochastic fluctuation control, which are commonly treated as passive consequences of thermodynamics, mechanics or statistical physics. Here we advance the hypothesis that living systems can actively regulate such processes through biologically produced, reusable agents that act analogously to enzymes, but target physical state transitions rather than chemical reactions. We introduce the concept of enzymatic-like control, defined as the localized and saturable lowering of kinetic, topological or statistical barriers in configuration space by endogenous cellular components. Among the many cellular physical phenomena to which this concept may apply, we focus on biomolecular condensate nucleation and dissolution as a concrete and analytically tractable example. Condensate dynamics are conceived as barrier-limited physical reactions whose kinetic rates can be selectively modulated by putative enzyme-like Phase-Kinetases without altering equilibrium phase behavior. Using hazard-based inference and survival analysis, we present simulations demonstrating how these putative enzyme-like agents could generate small effective free-energy shifts on the order of a few kT, resulting in orders-of-magnitude changes in nucleation rates and yielding explicit, falsification-oriented criteria.Our framework complements existing biochemical and mechanical models by providing a testable perspective on the active regulation of physical dynamics without invoking new chemistry or nonstandard physics. It reframes cellular organization as the selective control of physical state transitions, rather than their passive accommodation within fixed physical laws.

Abstract: Microplastics (MPs) have become a widespread environmental contaminant, raising concern due to their persistence, capacity to transport pollutants, and potential risks to ecosystems and human health. Their increasing global production, prolonged degra-dation, and ubiquity in aquatic environments underscore the need for improved strategies for monitoring and mitigation. This review examines the definition, sources, environmental transport mechanisms, associated risks, and current detection methods for MPs in natural and engineered water systems. The methods discussed encompass a broad range of analytical and sensing technologies used to identify, characterize, and quantify MPs across diverse environmental matrices. The review highlights that no single technique is sufficient for comprehensive MP analysis; instead, the combination of multiple methods enhances sensitivity, specificity, and reliability. Current findings indicate widespread MP contamination, including within the human body, emphasizing significant ecological and health concerns. Progress in automated sample preparation, standardized protocols, and advanced sensing platforms is key to improving detection efficiency and comparability across different studies. Overall, the evidence presented supports the need for strengthened monitoring, continued technological innovation, and coordinated mitigation policies. Reducing MP pollution will require interdisciplinary collaboration, regulatory action, and increased public awareness to protect environ-mental integrity and human health.

Abstract: Allosteric modulation has emerged as a powerful strategy for achieving superior selectivity and safety in drug discovery and protein function regulation. Unlike highly conserved orthosteric sites, allosteric pockets are structurally diverse and less evolutionarily constrained, making them particularly amenable to be modulated by designed miniproteins. Miniproteins can provide extended binding interfaces and high affinity for shallow, dynamic, or cryptic regulatory surfaces that are often inaccessible to small molecules. Recent advances in artificial intelligence (AI) are transforming this field through deep learning–based structure prediction and generative modeling. These AI-driven approaches enable the identification of allosteric hotspots, characterization of conformational ensembles, and de novo} design of structured miniprotein binders. They are rapidly expanding the landscape of designing selective modulators across diverse allosteric targets, including GPCRs, receptor tyrosine kinases, nuclear receptors, ion channels, and protein–protein interfaces. This review summarizes state-of-the-art AI-driven computational methodologies for designing miniproteins as potential allosteric modulators and discusses their current challenges and future opportunities in allosteric drug discovery.

Abstract: Enzyme performance parameters, including the turnover number and specificity constant, exhibit remarkable diversity due to biological evolution and natural selection. In some bacterial and human enzymes, catalytic efficiencies approach fundamental physical limits, underscoring the importance of physical constraints on enzymatic function. A deeper understanding of these constraints, particularly in far-from-equilibrium irreversible processes, is therefore essential for rational enzyme engineering. Such constraints are most naturally addressed within the frameworks of nanothermodynamics and stochastic thermodynamics, which remain relatively unfamiliar to much of the molecular biology community. Recent theoretical and experimental advances indicate that classical enzyme kinetic parameters are not independent, but are systematically linked to energetic dissipation. In particular, enzymes appear to occupy a characteristic dissipation plane defined by entropy production, reflecting the coupled influence of thermodynamic principles and evolutionary selection. In this review, we synthesize evidence across diverse enzyme families demonstrating correlated increases in housekeeping dissipation, evolutionary divergence, and enzymatic performance. Together, these findings support dissipation as a physically grounded parameter that connects enzyme kinetics, biological evolution, and nonequilibrium thermodynamics.

Abstract: Breast cancer (BC), affecting 2.3 million women annually, requires early detection and effective follow-up to achieve >90% survival rates. Current modalities (mammography: 1000 mm³, MRI: 4.2 mm³) struggle with micro-tumors and dense breasts. This work presents a smart bra integrating electrical impedance spectroscopy (EIS) and electrocardiography (ECG)-based heart rate variability (HRV) to detect tumors as small as 0.1–0.5 mm³ (~1–5 × 10⁴ cells) and monitor relapse and cardiotoxicity every 3 months post-diagnosis. The device uses 24 MNP-coated silver-nylon electrodes, a 3-lead ECG sensor (AD8232), a high-precision impedance analyzer (10 kHz–1 MHz), and multimodal sensing (EIS, temperature, HRV). A hybrid LSTM-XGBoost model with space-time attention and GAN augmentation achieves >90% sensitivity and >85% specificity. EIS detects electric fields of 18.9 mV/m (0.1 mm³, superficial), 50 mV/m (0.5 mm³, superficial), and 41.7 mV/m (0.5 mm³, deep). ECG-based HRV (SDNN < 50 ms, RMSSD < 20 ms) predicts relapse (AUC = 0.80 with CEA) and cardiotoxicity (OR = 2.7). Tumor location statistics (60–70% upper-outer quadrant, 10–15% superficial) inform electrode placement. A patient trial will validate performance against mammography, ultrasound, clinical ECG, and CEA, targeting FDA 510(k) clearance. This multimodal wearable promises transformative early detection and longitudinal monitoring.