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Online ISSN 2653-4983
Volume 4 Issue 4 (December 2025)
ORIGINAL RESEARCH
Thermodynamic compensation indicates binding promiscuity of dystrophin in the nervous system
Madison E. Fountain, Sarah F. Cuneio, Jonghoon Kang
Dystrophin plays a key role in neuronal structure and synaptic signaling, yet its full range of binding partners in the nervous system remains incompletely understood. Here, we examined dystrophin–dystrobrevin interactions using a combined thermodynamic and bioinformatic approach. Analysis of published calorimetric data revealed that binding is driven primarily by favorable electrostatic and polar interactions and displays strong enthalpy–entropy compensation (EEC), with a notably low compensation temperature, suggesting that dystrophin may accommodate diverse partners through compensatory energetics. Bioinformatic profiling and principal component analysis (PCA) distinguished dystrobrevin isoforms and indicated that the C-terminal flanking region and overall charge (pI) are key determinants of binding affinity. Multiple linear regression further showed that DG° can be predicted from sequence-derived variables, particularly pI and intrinsic disorder. Together, these findings provide a thermodynamic rationale for the broad interaction capacity of dystrophin and establish a sequence-based framework for identifying potential dystrophin-binding proteins in the nervous system.
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BRIEF REPORT
Arturo Salazar Chon and Dhay Amer Kadhim
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Epileptic pathology is commonly interpreted as a state of increased neural disorder or high entropy. We challenge this interpretation and propose that such conclusions arise from incomplete or unidimensional metric approaches. Using a Unified Neurotopological Framework, we characterize brain dynamics by integrating both informational content and network geometric structure. We quantify neural coherence through a multimodal metric set including Permutation Entropy, Persistent Homology, and Ricci Curvature. The framework is validated using EEG data by comparing status epilepticus with healthy resting-state activity (isostasis). Our results (p < 0.001) show that epileptic seizures do not reflect heightened disorder but instead constitute a catastrophic collapse of network geometry, resulting in disordered low-complexity coherence. Furthermore, we identify a paradox in which the resting healthy brain demonstrates low-ordered complexity, yet remains functionally coherent. These findings suggest that the critical biomarker differentiating health from pathology is not entropy magnitude but the dynamic geometry of neural coherence.
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PERSPECTIVE
The interdisciplinary ontology of consciousness in multiscale neuroscience
Alfredo Pereira Júnior
​According to the Interdisciplinary Ontology called "Triple Aspect Monism" (TAM), consciousness has three necessary - and conjointly sufficient - aspects: Matter, Information and Sentience. All three equally derive from a 'neutral' basis - one that is neither physical nor mental - called Energy. Matter is particle-condensed Energy; Information is the differential distribution of Energy in Space, and Sentience (defined as "the capacity of feeling") is a special type of distribution of Energy in Time. Although the three aspects are potentially present in Energy, their conjunction, generating conscious experiences, occurs only - as far as we know - in living systems. In these systems, the three aspects are integrated during the evolutionary process; they develop the “first-person perspective” proper to each singular conscious being, arising from a self-organization process (the "endogenous feedback"; Carrara-Augustenborg and Pereira Jr., 2012), which, in humans, allows the emergence of self-referential meaningful language. While Matter and Information are well treated by natural and computational sciences, the understanding of Sentience, with its special temporal waveforms, poses challenges, for which a new science - called Sentiomics (Pereira Jr. and Aguiar, 2022) - was formulated. Two compatible explanations are provided here, for the emergence of Sentience: 1) As a Fibonacci-like pattern of amplitude modulation of multi-ionic waves in time, proposed by myself with colleagues, and 2) As a quantum geometric constraint operating in dynamic organic systems and projecting conscious contents (Poznanski, 2025).
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BRIEF REPORT
Sentience in the animal kingdom based on radical emergence
Eda Alemdar
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Phenomenal consciousness, under the QPG/SIP framework, is understood as emerging from a deep, multilayered, and ontologically distinct stratum that cannot be reduced to neural computation, synaptic integration, nor behavioral response patterns alone. In this view, phenomenality does not arise from classical information processing within neuron–synapse architectures, but from threshold conditions that enable sentience to manifest as quasipolaritonic resonance modes. These threshold conditions are radically emergent requiring: (1) Sufficient density and spatial organization of neuropil microcavities, (2) Minimally separated cavity topologies capable of phase interaction, (3) High morphodynamic (non-rigid) plasticity supporting reconfigurable geometry. In this view, they replace microtubules as the key physical locus for phase-coupled quasipolaritonic modes, thereby serving as the mesoscopic bridge through which QPG/SIP dynamics can instantiate sentience. Accordingly, phenomenal consciousness is framed not as a computational output, functional representation, or emergent symbol-processing property, but as a radical phase-transition event occurring when microcavity organization reaches a coherence-supporting critical regime. In this interpretation, phenomenality is the self-organizing instantiation of functional holonomy expressed through the functional geometry of the neuropil, and sentience precedes phenomenality and grounds the possibility of consciousness itself.
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