Biology and Life Sciences

Abstract: Background/Objectives: Gamma-aminobutyric acid (GABA) is increasingly recognized as an important modulator of pancreatic beta-cell function, but the mechanisms by which it regulates intracellular Ca²⁺ oscillations and coordinated beta-cell activity remain insufficiently understood. The aim of this study was to investigate how GABA influences the amplitude, frequency, phase adjustment, entrainment, and synchronization of beta-cell Ca²⁺ oscillations. Methods: We developed an extended mathematical model based on our previously established Dual Anaplerotic Model of the GABA shunt. The model incorporates explicit dynamics of cytosolic Ca²⁺, endoplasmic reticulum Ca²⁺, ATP, and a regulatory variable controlling Ca2+ influx, while extracellular GABA is represented as a delayed interstitial signal feeding back on cellular excitability. Single-cell and two-cell simulations were performed to analyze GABA-dependent oscillatory regulation and intercellular coupling. Results: The model reproduced key experimental observations under both control and GABA-deficient conditions, including reduced Ca²⁺-oscillation amplitude and prolonged oscillation period when GABA production was suppressed. Mechanistically, GABA affected single-cell oscillations through two complementary pathways: metabolically, by modulating ATP production through PEP-related and TCA-related contributions linked to the GABA shunt; and extracellularly, by adjusting the phase of Ca²⁺ influx through fast and delayed inhibitory feedback. In the two-cell model, delayed interstitial GABA signaling was sufficient to entrain and synchronize non-identical oscillators over finite ranges of parameter mismatch, and weak effective electrical coupling further broadened these synchronization ranges. Conclusions: GABA acts as a dual regulator of beta-cell dynamics, linking intracellular metabolism to Ca²⁺-oscillation patterning and promoting coordinated activity through intercellular phase adjustment. The model provides a mechanistic framework connecting GABA metabolism, ATP dynamics, Ca²⁺ signaling, and beta-cell synchronization in pancreatic islets.

Abstract: Circadian disruption resulting from factors such as jet lag, shift work, or aging leads to exaggerated inflammatory responses and increased disease susceptibility. However, the core dynamical mechanism by which circadian disruption exacerbates innate immune responses remains poorly understood. Here, we develop an integrated mathematical model coupling the mammalian circadian clock with antigen-induced innate immune responses, incorporating key regulatory interactions including glucocorticoid modulation and pro-inflammatory positive feedback loops. The model successfully recapitulates experimental data regarding homeostatic immune circadian oscillations and time-dependent gating of acute inflammatory responses. Dynamic analyses reveal that the circadian clock exerts its gating function by modulating the bistable characteristics within pro-inflammatory positive feedback loops. Circadian disruption, simulated as jet lag or age-related reduction in clock gene amplitude, reshapes this bistable landscape and prolongs residence duration in the pathological hyperinflammatory state. This shift not only amplifies acute cytokine bursts but also sustains exaggerated inflammatory activity, providing a unifying mechanistic explanation for acute tissue injury and chronic low-grade inflammation (inflammaging) under circadian disruption.

Abstract: Protein-based biosensors require controlled and site-selective functionalization strategies to enable stable immobilization and signal transduction without compromising protein structure and activity. Here, we evaluate a chemoselective linchpin-directed modification (LDM) approach targeting Lys–His pairs as a tool for site-specific labeling of the model fluorescent biosensor green fluorescent protein (GFPmut2). A panel of LDM molecules with variable spacer lengths was prepared, and a structure-guided computational workflow was implemented to map Lys–His distances on the protein and predict potential modification sites. Experimental validation by UV–Vis spectroscopy and mass spectrometry demonstrated efficient conjugation and a final degree of labeling close to unity, consistent with single-site modification, with all LDM molecules selectively targeted the same histidine residue (His181), independently of spacer length. Structural analysis revealed that this residue is located within an accessible internal cavity, enabling a funneling effect that enhances local reactivity. Importantly, the modification preserves the fluorescence and pH response of GFP, confirming retention of sensing functionality. These results demonstrate that LDM enables selective modification not only of surface residues, but also of structurally guided, non-surface residues. This approach provides a novel strategy for the controlled functionalization and immobilization of protein-based biosensors, improving their stability and performance.

Abstract: The kinetic-bystander framework of McMahon et al. (2013) remains the most rigorous formal model of signalling between irradiated and unirradiated cells, but three residual gaps remain. First, the intracellular response of recipient cells is compressed into a single hazard parameter μ, leaving unspecified the molecular processes linking signal reception to altered behaviour. Second, the framework contains no explicit mechanism for persistent recipient-cell state through which prior signalling exposure modifies future response across fractions. Third, recent structural identifiability analysis showed the model to be intrinsically non-identifiable under conventional surviving-fraction observation, limiting recoverability of internal dynamics from observable response. Subsequent extensions broadened biological scope through immune-mediated cohort and abscopal effects (Asur et al., 2015; Moghaddasi et al., 2022; Jenkins et al., 2024) and improved phenomenological fit through dose–distance interaction terms (Arous et al., 2025), but did not address these residual intracellular and observational limitations. We propose, as a hypothesis, that the AP-1 / CBP-p300-mediated cis-epigenetic memory mechanism recently demonstrated by Li et al. (2026) provides one candidate intracellular implementation addressing the first two gaps while partially enriching the third through additional observables. We support the proposal through three analyses requiring neither numerical simulation nor new data: a timescale-reconciliation argument with explicit treatment of pulsed versus continuous exposure, structural propositions yielding parameter-independent predictions, and literature-derived order-of-magnitude analysis. We further connect the proposal to existing phenomenological extensions by predicting how the empirical interaction parameter of Arous et al. (2025) should vary with AP-1 / CBP-p300 status and fraction number. We position the mechanism as complementary to organism-level immune-memory processes, operating at a different biological scale through distinct machinery. The framework generates experimentally testable pharmacological predictions while remaining explicitly hypothetical and awaiting direct validation.

Abstract: Time-resolved neutron scattering has been used to study dynamically polarised protons in tyrosyl doped bovine liver catalase. Both dynamic nuclear polarisation and the efficiency of the reversal of the proton polarisation change significantly with the occupancy of the tyrosyl radical inside the catalase molecule. A sample rich in tyrosyl (0.78 per heme) is compared with earlier data from a sample with much lower occupancy of 0.58. An extremely localized proton polarisation of unprecedented height near each of the tyrosyl radicals is maintained by an efficient magnetic nuclear spin diffusion barrier. The proton polarisation remains low further away from the tyrosyl radical sites.

Abstract: This study aimed to characterize metabolomic changes in the eye lens of senescence-accelerated OXYS rats in comparison with control Wistar rats, and to identify biochemical shifts associated with genotype, age, and cataract progression. Cataract severity was clinically graded. Rats' lenses were analyzed using quantitative ¹H NMR spectroscopy at 3.6 and approximately 4.5 months of age. A total of 43 metabolites were quantified. We found that at 3.6 months of age, OXYS lenses exhibited a significant accumulation of 17 metabolites, primarily amino acids, compared to Wistar rats, suggesting an imbalance between amino acid uptake and crystallin biosynthesis. However, by 4.5 months, OXYS lenses exhibited rapid metabolic changes characterized by significant decreases in amino acid, glucose, and key energy/antioxidant markers, including NAD, adenylate energy charge, and hypotaurine. Clinical cataract grade (Grade 2 vs. 3) had a negligible impact on the overall metabolomic profile. Our results indicate that profound metabolic reorganization, including an initial amino acid excess followed by energy and antioxidant depletion, precedes the morphological manifestation of cataracts in OXYS rats. We suggest that a biochemical "point of no return" occurs early in cataractogenesis, while subsequent increase in lens opacification is a secondary consequence of preexisting metabolic disturbances.

Abstract: The association of small molecules with lipid membranes plays a central role in drug delivery, pharmacokinetics, toxicity, and membrane biophysics, also being of fundamental importance in drug pharmacodynamics given that most drug targets are membrane-associated proteins. Accurate determination of solute–membrane association affinities, however, remains challenging due to the diversity of experimental systems, the complexity of membrane environments, and the intrinsic limitations of individual methodologies. This review provides a comprehensive overview of the experimental and computational approaches currently used to quantify small molecules association with lipid membranes. Standard experimental techniques, including spectroscopy-based methods, calorimetry, electrophoretic measurements, and surface-sensitive approaches, are discussed alongside established computational strategies ranging from continuum models to atomistic molecular dynamics simulations. Particular emphasis is placed on the formalisms required for data analysis, including partitioning models and thermodynamic frameworks, as well as on the assumptions underlying each method. The validity limits, sources of uncertainty, and common experimental and interpretative pitfalls are critically examined. By providing a unified and comparative perspective, this work establishes a structured framework for the quantitative study of solute–membrane interactions, guiding new researchers in the selection of appropriate methodologies and in the rigorous analysis of experimental and computational results. Moreover, it enables the consistent and quantitative rationalization of affinity parameters reported across the literature, supporting the development of curated datasets and predictive relationships that can inform the design of new and more effective drugs.

Abstract: Rel/SpoT family enzymes participate in controlling the cellular levels of the alarmone (p)ppGpp, thereby activating the stringent response and promoting survival under stress conditions. These proteins contain an N-terminal catalytic domain and a C-terminal regulatory domain. They catalyze both the synthesis of ppGpp/pppGpp from ATP and GDP/GTP and their hydrolysis to GDP/GTP and pyrophosphate. Here, we report the crystal structure of the N-terminal domain of Rel from Streptococcus equisimilis (Rel_Seq385) in complex with pppGpp at 3.2 Å resolution. The asymmetric unit contains a dimer with asymmetric ligation, in which pppGpp occupies only the synthetase site in one monomer, whereas it is observed in both the hydrolase and synthetase sites in the other. Molecular dynamics simulations supported this binding arrangement for the monomer with both sites occupied and revealed additional probable transient binding sites that may contribute to alarmone binding.

Abstract: Mechanistic models in radiobiology have proliferated across FLASH ultra-high dose-rate radiotherapy, spatially fractionated radiation therapy (SFRT), and stereotactic body radiotherapy (SBRT), yet the field has not converged on unified mechanistic explanations despite decades of model development. We propose that this proliferation partly reflects a structural property of the model-observation pairing itself: clinically accessible measurements may be insufficient to uniquely recover the parameters governing the underlying biological dynamics. Using generating-series structural identifiability analysis, we examine four representative models spanning the temporal, spatial, magnitude, and adaptive-state dimensions of radiobiological response: the Pratx-Kapp radiolytic oxygen depletion model (FLASH), the McMahon kinetic-bystander model (SFRT), the LQ-L extension (SBRT), and the Gupta phenotypic-plasticity model of adaptive resistance. The Pratx-Kapp and McMahon models exhibit intrinsic non-identifiability under conventional surviving-fraction observation, while the LQ-L and Gupta models exhibit observation-dependent identifiability conditional on dose-range coverage and marker-panel richness. These findings suggest that increasing radiobiological complexity progressively exposes the limitations of fixed-parameter mechanistic descriptions under partial observability. As a constructive response, we propose, as a hypothesis, that adaptive latent-state inference frameworks operating over a coupled multi-layer organizational state may provide a complementary operational paradigm for radiobiology under uncertainty.

Abstract: Osmosis has lacked a satisfactory mechanistic explanation for over a century. Pollack and colleagues showed that hydrophilic surfaces release protons into adjacent water, and that the resulting pH and potential gradients across a membrane can account for the direction of osmotic flow. That account, however, is incomplete: a pure proton flux across a membrane would acidify one side indefinitely, and would not by itself constitute the transfer of water. The missing step is redox. Osmosis is the same chemistry as in the demonstrated acid–base battery with oxygen electrodes, in which water is broken down on the alkaline side (4 OH⁻ → O₂ + 2 H₂O + 4 e⁻), electrons cross to the acidic side, and water is reconstituted there (4 H⁺ + O₂ + 4 e⁻ → 2 H₂O). Dioxygen is consumed and produced in the cycle and is therefore required. This redox interpretation has a direct anatomical consequence: any biological system sustaining osmosis at scale must continuously supply dioxygen to the acidic side. The loop of Henle in the mammalian kidney is shown to be precisely such a recirculation system, with the vasa recta returning dioxygen released in the descending limb back to where it is needed. The anatomy of the nephron is what the redox mechanism predicts.

Abstract: Heme-containing enzymes play vital functions in living organisms, including humans. Here we demonstrate two indirect effects of (electric discharge)-treated stainless steel on a model enzyme — horseradish peroxidase (HRP). The first effect is the complete loss of the enzyme’s adsorption after its incubation in grounded stainless steel chamber, which has been preliminarily subjected to electric discharge in air at atmospheric pressure. The second one is the formation of enzyme aggregates in the sample incubated in another grounded chamber two meters away from the discharge-treated one. At that, the HRP’s enzymatic activity is found to be unaffected in the both cases. These effects may be explained by the occurrence of knotted electromagnetic fields (KEMF). By using high-speed atomic force microscopy (HS-AFM), we reveal the relatively high surface mobility of cytochromes P450cam and P450 102A1 (BM3), whose isoelectric point (pI) values are acidic; at that, thymidylate synthase (TYMS) with near-neutral pI adsorbs strongly. Thus, HRP is the best model object, since its basic pI provides quite strong adsorption on mica. Since (electric discharge)-processed materials have found applications in medicine, we expect that the effects discovered will be considered in future biomedical applications of (electric discharge)-based technologies.

Abstract: Actin, a highly conserved and ubiquitous eukaryotic protein, underlies essential cellular processes including motility, shape maintenance and muscle contraction. Its dynamic transition between monomeric and filamentous states is powered by ATP hydrolysis, which undergoes structural rearrangements that accelerate turnover in filaments and serve as a measure of filament aging. A wide range of actin binding proteins (ABPs) regulate polymerization, depolymerization, and network organization. Recent high resolution cryo-EM and cryo-ET studies have revealed detailed structures of actin, its isoforms, and ABP complexes, including their organization in cells, deepening our understanding of actin function in health and disease.

Abstract: The mechanosensitive ion channel Piezo1 acts as a crucial molecule for cellular mechanical signal sensing and transduction. It transforms physical mechanical cues in the microenvironment, including matrix stiffness, fluid shear stress, and tissue tension, into intracellular biochemical signals through Ca2⁺ influx-mediated mechanisms. Consequently, it regulates the activation, proliferation, differentiation, migration, and effector functions of blood cells. Herein, we review the research progress of Piezo1 in various white blood cells, with a particular emphasis on its functional regulatory mechanisms in neutrophils, macrophages, platelets, and T and B lymphocytes. We briefly summarize its current functional status in natural killer cells, dendritic cells, plasma cells, platelets, and other cell types. We analyze the integrated effects and multi-cellular cooperative interactions of Piezo1-mediated blood cell mechanotransduction across physiological and pathological contexts. We discuss the potential value of Piezo1 as a mechano-immunotherapeutic target, therapeutic strategies, and challenges facing clinical translation. Finally, we provide perspectives on future research directions, offering theoretical references for deepening the understanding of the molecular mechanisms by which mechanical microenvironments regulate white blood cell function and disease progression and for developing novel therapeutic strategies.

Abstract: The axonal membrane is not the seat of nerve conduction: it is the boundary between two osmotic reservoirs whose asymmetry is the thermodynamic engine of the action potential. Voltage-gated ion channels are not the generators of the nerve signal: they are its osmotic amplifiers, and their spatial distribution along the axon is a geometric necessity, not an arbitrary anatomical feature. The Ionic-Mechano-Hydraulic (IMH) model formalises this principle: intracellular K⁺ adsorbed on the cytoplasmic polyelectrolyte gel triggers an ionic phase transition; extracellular Na⁺ amplifies the resulting hydraulic wave through Nav channels; Kv channels close the osmotic cycle and enforce the refractory period. The conduction velocity is predicted from the elastic modulus of myelin, not from the density of the sodium channel. The model resolves a 75-year-old anomaly that Huxley and Stämpfli themselves described as impossible in a purely electrical system: a positive current enters a node before the membrane potential at the preceding node has reached its maximum. Ten falsifi-able predictions are presented that cover myelin mechanics, mechanoreceptor adaptation, terminal arborisation geometry, velocity-diameter scaling, and axon diameter limits derived from first physical principles. The Hodgkin-Huxley model is not discarded: it is explained.

Abstract: A neural model for the formation of visual engrams is proposed, operating according to a non-Hebbian principle — specifically, through the enhancement of inhibitory synapses, up to and including the formation of veto synapses. The model relies on two hypothetical mechanisms: (1) rapid, repetitive reactivation ("ripple-reverberation") and (2) high-frequency synchronization enabling the activation of inhibitory synapses, which consequently become veto synapses. Through such learning, "neural locks" for familiar patterns are formed in memory. This model constitutes a component of a more general top-down model of visual recognition described previously (Levashov & Safiulina, 2025). The problem of processing activity patterns in living neural networks is discussed, as these patterns are not holistic but rather manifest as a mosaic of activated and non-activated neurons.

Abstract: Background: Lung cancer causes more deaths than any other malignancy worldwide, accounting for 2.2 million new cases and 1.8 million deaths in 2020. Extracting structured clinical knowledge from unstructured French-language oncology records remains methodologically unresolved in Tunisian and Francophone healthcare systems, where validated natural language processing tools do not yet exist. This study examined the effectiveness of transformer-based named entity recognition for automated clinical annotation of Tunisian lung cancer reports. Aim: The study aimed to (i) benchmark four transformer-based models on a publicly available thoracic radiology dataset, (ii) evaluate five models, including a French biomedical specialist, on a newly constructed Tunisian clinical corpus, and (iii) demonstrate prototype deployment feasibility for structured clinical decision support. Methods: A benchmarking study evaluated BERT, RoBERTa, BioClinicalBERT, and CamemBERT on the RadGraph dataset (600 annotated thoracic radiology reports). Five models were subsequently fine-tuned on 200 manually annotated initial diagnostic reports from Mami Pneumo-Phthisiology Hospital, Tunis. All models were trained for a maximum of 10 epochs, with a learning rate of 5x10-5, a batch size of 16, and an 80/10/10 train-validation-test split, and evaluated using precision, recall, and F1-score. Results: On RadGraph, RoBERTa achieved the highest F1-score of 0.873 (precision: 0.869, recall: 0.877), followed by BioClinicalBERT (F1: 0.868) and BERT (F1: 0.857). CamemBERT achieved an F1 score of 0.682 on this English dataset. On the Tunisian corpus, DrBERT outperformed all models with an F1-score of 0.811, compared to RoBERTa at 0.79. A prototype interface generated structured clinical summaries encompassing prior conditions, imaging modalities, and TNM staging. Conclusion: Language- and domain-adapted transformer models effectively extract structured clinical entities from French-language Tunisian lung cancer reports. DrBERT's precision advantage confirms that biomedical pretraining in the target language is the primary driver of performance in specialized French oncology text. This work establishes foundational infrastructure for NLP-driven oncology data management in Tunisia and comparable Francophone settings.

Abstract: In hepatocellular carcinoma (HCC), aberrant histone modifications are linked to the dysregulation of long non-coding RNA (lncRNA) expression. Although existing computational models can accurately predict some associations, they lack deep physical interpretability. We constructed an energy model based on the physical principle that energy determines molecular structure. Total DNA segment energy was calculated by summing adjacent trinucleotide interaction energies and applied to analyze 11 key histone modifications in HCC, specifically within lncRNA promoter regions where modification signals were increased or decreased. Finally, ten-fold cross-validation revealed that significant energy differences between sequences with increased and decreased histone signals enable excellent classification performance. These results indicted a strong correlation between the total energy of local DNA structures and histone modification signal. Furthermore, introducing longer k-mers led to computational redundancy without a consistent improvement, confirming that the trinucleotide model most effectively acquires the local DNA structural changes associated with histone modification levels. Our model can effectively distinguish DNA sequences associated with different histone modification levels from a physical energy perspective. This model serves as an interpretable tool for epigenetic research while providing a new understanding a new perspective for understanding the dysregulation of lncRNA expression in HCC.

Abstract: Pressure-powered spore-launching strategy is a unique feature for many fungal species. Fungal species have evolved this dispersal method to project spores into the surrounding environment, thereby increasing reproductive success and completing their life cycle. Sporangia squirters (like Pilobolus), ballistospore catapulters (like Agaricus), and ascospore launchers (like Neurospora) are prominent fungal cannons. Osmotic pressure and surface tension are responsible for propelling spores at extreme acceleration exceeding 20,000g and velocities reaching 94 km/h, thus enabling spores to travel distances of up to several meters. Thanks to advances in biophysical modeling and high-speed imaging, the century-old mystery of fungal launching strategies has been understood to involve principles of fluid mechanics, optics, and projectile dynamics, by investigating many fungal models. With a focus on the underlying biophysical principles and their broader implications for fungal ecology, this review summarizes current knowledge of morphology and biomechanics. Additionally, it discusses how each step of spore launching relates to fundamental physical principles of energy and motion.

Abstract: Lineages are conceived as corridors through time of two-sigma exclusion of uncertainty by Bayesian analysis of numbers of morphological traits and species. Methods of structural monophyly constructed evolutionary dendrograms of a family and of a tribe of bryophytes. Shannon informational bits known for speciation events in these groups allow projections of changes into the past. Sampling and relationships in the present imply kinds and rates of origination and extinction of species. Vopson’s estimates of the mass of one informational bit is used to spacelike calculate total mass of information of two bryophyte lineages from total bits associated with speciation over time. Three levels of observational sampling yield similar information masses for the two lineages. Numbers of observations of calculated events over time are expressed in “Reals” as fundamental units of historical reification. Observation is postulated as a source of historical reification based on a functional equivalence of switching of light-speed-mediated Then and Now for estimation of spacelike events. This Common Now concept is quite like that of a many worlds theory of entangled events. Dark matter, Schrödinger’s cat, aliens, the Big Bang, the Matrix, and dragons make an appearance. Best fit to average axion depth is observational sampling at 2 cm size of a mathematically spherical moss. Scientific reality is identified with calculated information extending experience in both directions of time.

Abstract: The trajectories of complex biological systems are commonly inferred from long-term observations of recovery or deviation after perturbation. We suggest that early-time state-space geometry could contain information enough to anticipate system trajectories before recovery. This hypothesis is informed by extensions of the quantum adiabatic theorem suggesting that under fast, nonadiabatic perturbations, a system prepared in its ground state within the same phase retains the largest overlap with the post-perturbation ground state. Translating to biological systems, we consider cellular functional identity as a stable attractor in a high-dimensional state space where abrupt perturbations like brief inflammatory pulses do not induce regime transitions. Our simulations suggest that post-perturbation states distribution is biased toward the original attractor, reflecting persistence of structural alignment rather than uniform exploration of accessible configurations. Early-time overlap with the baseline attractor, attractor dominance and state-space entropy could stand for operational metrics for inferring system fate. Higher initial overlap should correspond to increased return probability and reduced dispersion, whereas reduced overlap may indicate proximity to regime boundaries. We predict that system fate can be inferred from initial post-perturbation configurations without requiring long-term observation. Potential applications of our framework include fast assessment of cellular resilience, early identification of instability preceding disease transitions and optimization of intervention strategies based on early system responses.