Amphotericin-based channels favor cation permeability, whereas CFTR is fundamentally an anion channel. In addition, the AmB channels lose their capacity to increase the pH of the airway surface liquid in cystic fibrosis airway epithelia at high concentrations. These properties led the team to hypothesize that chemically tuning such channels to favor anion permeability would improve their capacity to restore physiology in disease-relevant model systems.

To test that hypothesis, the researchers synthesized AmB-AA, a derivative of amphotericin B bearing an added positively charged appendage. This structural change produced ion channels with an improved relative permeability to anions. In cultured cystic fibrosis airway epithelia, AmB-AA increased airway surface liquid pH more effectively than amphotericin B, and it maintained that benefit at both low and high concentrations, addressing the concentration-dependent loss of activity seen with the parent compound.

The team then pushed the design further with a second derivative, C2'epiAmB-AA. This molecule was engineered to minimize cholesterol binding, and in doing so it reduced toxicity to cultured cystic fibrosis airway epithelia. Crucially, C2'epiAmB-AA functioned as an effective surrogate for CFTR in primary cultured airway epithelia obtained from people with cystic fibrosis, the disease-relevant model tissue for this line of research.

The findings demonstrate that both the selectivity and the toxicity of a molecular prosthetic can be addressed rationally rather than accepting the properties of a naturally occurring molecule. By adding a positive charge to bias the channel toward anions and further modifying the structure to reduce cholesterol interactions, the researchers improved physiological performance and the toxicity profile in cultured epithelia simultaneously. Important caveats remain.

All results come from laboratory models: cultured airway epithelia, including primary cultures derived from people with cystic fibrosis, not from living patients. Increasing airway surface liquid pH in a culture model is a measured laboratory outcome and a step toward therapy, not a demonstrated clinical benefit. Even with those limits, the study offers a concrete demonstration that molecular prosthetics can be iteratively engineered, in much the way an engineer refines a mechanical prosthesis, to better match the biological function they are meant to replace.

Anion-selective derivatives of amphotericin B now represent a measured improvement over the natural product that started this approach in cystic fibrosis airway models.

Subject of Research: Engineering anion-selective amphotericin B derivatives as molecular prosthetics for the CFTR channel in cystic fibrosis airway epithelia

Article Title: Molecular prosthetics for CFTR designed for anion selectivity outperform amphotericin B in cystic fibrosis airway epithelia

Article References: Marin-Toledo, J. P., Greenan, D. M., Celis, N., Haske, L., Lewandowska, A., Rakowski, C. K., Shastry, S., Gworek, B., Maji, A., Green, K. J., Welsh, M. J., Thornell, I. M., Pogorelov, T. V., & Burke, M. D. (2026). Molecular prosthetics for CFTR designed for anion selectivity outperform amphotericin B in cystic fibrosis airway epithelia. Nature Communications. https://doi.org/10.1038/s41467-026-78819-9

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78819-9

Keywords: cystic fibrosis, CFTR, amphotericin B, molecular prosthetics, ion channels, anion selectivity, airway surface liquid pH, airway epithelia, drug design, cholesterol binding, Nature Communications, Molecular

Kv4.2 is the pore-forming component of A-type potassium channels expressed prominently in dendrites, where the channels constrain excitability and influence the integration of incoming signals. These channels operate within larger complexes that include regulatory proteins such as the KChIP family and the membrane-associated subunits DPP6 and DPP10. DPP6 is particularly important in hippocampal CA1 pyramidal neurons: it supports channel surface expression, alters conductance and inactivation, and helps establish the increase in Kv4.2 abundance from the cell body toward distal dendrites. The new study used wild-type mice, mice lacking maternal UBE3A expression to model Angelman syndrome, and separate DPP6 knockout mice to distinguish the effects of the two proteins.

The first set of experiments asked where the UBE3A ubiquitin ligase encounters Kv4.2. Researchers tagged Kv4.2 with a binding site for alpha-bungarotoxin, allowing them to label channels that were present on the surface of living cells. In HEK293T cells expressing the tagged channel and UBE3A, surface-labeled Kv4.2 showed little colocalization with UBE3A when membrane trafficking was restricted at 4 degrees Celsius. When the labeled cells were returned to 37 degrees Celsius, permitting internalization and intracellular movement, Kv4.2–UBE3A colocalization increased markedly. A biochemical version of the experiment produced the same pattern: recovery of UBE3A with surface-tagged Kv4.2 was barely detectable under restricted trafficking but rose after incubation allowed endocytosis, with more UBE3A recovered at 50 minutes than at 20 minutes.

These observations place UBE3A downstream of channel internalization rather than showing that it constitutively binds channels at the plasma membrane. That fits earlier work in which neuronal activity promotes phosphorylation of Kv4.2 at threonine 607, recruitment of the prolyl isomerase Pin1, dissociation from DPP6 and subsequent UBE3A-dependent degradation. The current results refine the sequence: activity-associated remodeling is followed by endocytosis, after which UBE3A preferentially processes the internalized channel pool. The study did not directly image the accumulation of such a pool in Angelman syndrome neurons, so that part of the proposed mechanism remains a model that requires further testing.

In hippocampal tissue from UBE3A-deficient “AS” mice, the amount of DPP6 and its distribution among synaptosomal, postsynaptic-density and non-postsynaptic-density fractions were unchanged relative to wild-type littermates. Co-immunoprecipitation also found no detectable association between UBE3A and DPP6 in transfected cells, arguing against a simple model in which UBE3A regulates DPP6 by binding it directly. By contrast, the amount of DPP6 associated with Kv4.2 was significantly reduced in AS mice. The interaction between Kv4.2 and KChIP proteins was unaffected, indicating that loss of UBE3A did not broadly dismantle every interaction between Kv4.2 and its auxiliary subunits.

Seizure induction with pentylenetetrazole provided an activity-dependent test of the complex. In wild-type mice, pentylenetetrazole at 60 mg/kg reduced Kv4.2–DPP6 association after 30 minutes, as expected from the established model of activity-induced channel remodeling. The same treatment did not produce a significant additional reduction in AS mice, whose association was already reduced. Basal phosphorylation of Kv4.2 at threonines 602 and 607 was normal in AS mice, and seizure-induced phosphorylation at threonine 607 remained intact. The defect therefore appears to lie after the principal phosphorylation response rather than in the basal phosphorylation signal itself, although AS mice showed an additional increase in threonine-602 phosphorylation after seizure induction that was not seen in wild-type animals.

DPP6 knockout mice displayed a different molecular phenotype, helping show that the auxiliary subunit is not merely a passive partner. Basal phosphorylation at both threonine 602 and threonine 607 was elevated in DPP6-deficient tissue, while the phosphorylation increase normally triggered by pentylenetetrazole was absent. Phosphorylation of p38 MAPK, the kinase associated with the two threonine sites, remained normal at baseline and after treatment, suggesting that upstream kinase activation was intact. The authors interpret the findings as evidence of reciprocal regulation: activity-dependent phosphorylation promotes dissociation from DPP6, while DPP6 helps organize a channel complex capable of appropriate phosphorylation dynamics. This distinction is important because the AS phenotype involves altered complex remodeling with largely preserved basal phosphorylation, whereas removing DPP6 alters the phosphorylation pattern itself.

Immunostaining then connected the biochemical changes to dendritic structure. Kv4.2 protein normally forms a proximal-to-distal gradient along both apical and basal dendrites of CA1 pyramidal neurons. The researchers quantified staining about 10 micrometers from the stratum pyramidale and at more distant sites, including 130 micrometers in stratum radiatum and 70 micrometers in stratum oriens. That gradient was significantly impaired in DPP6 knockout mice on both apical and basal dendrites, consistent with an earlier electrophysiological finding that DPP6 is required for the corresponding increase in A-type potassium current toward distal dendrites. The imaging results therefore show that the electrical gradient has a matching protein-distribution component.

UBE3A-deficient mice also had impaired Kv4.2 gradients along both sets of CA1 dendrites. Kainic-acid-induced seizures altered the distribution in wild-type mice, whereas AS mice showed a loss of the gradient in stratum oriens but a significantly smaller seizure-associated change than wild-type littermates. This reduced responsiveness suggests that UBE3A-deficient neurons have less capacity to redistribute Kv4.2 in response to increased activity. Their basal distribution resembled the remodeled pattern seen after seizure induction in wild-type animals, raising the possibility that loss of UBE3A leaves neurons in a persistently shifted trafficking state. The findings do not establish that this mechanism directly causes seizures, cognitive impairment or other features of Angelman syndrome, and the experiments were conducted in animals and cultured cells rather than patients.

Kv4.2 normally limits dendritic excitability and helps shape the propagation and integration of excitatory signals. Its disrupted organization could therefore have effects beyond the biochemical status of the channel complex, especially given the hyperexcitability and seizure susceptibility associated with Angelman syndrome. The results also reconcile, at least partly, the previously reported increase in somatic A-type current in AS mice with the impaired dendritic gradient found here: greater overall Kv4.2 abundance could raise somatic currents, while weakened DPP6 association could disturb the channel’s normal spatial distribution. The study identifies post-endocytic Kv4.2 processing as a new mechanistic link between UBE3A deficiency and dendritic ion-channel dysfunction, but whether restoring complex assembly, trafficking or distribution would improve symptoms remains untested.

Subject of Research: Kv4.2–DPP6 channel-complex dynamics and dendritic organization in an Angelman syndrome mouse model

Article Title: Impaired Kv4.2-DPP6 complex dynamics in a mouse model of Angelman syndrome

Article References: Hu, J.-H., Liu, Y., Malloy, C., & Hoffman, D. A. (2026). Impaired Kv4.2-DPP6 complex dynamics in a mouse model of Angelman syndrome. Frontiers in Cellular Neuroscience, 20, Article 1953686. https://doi.org/10.3389/fncel.2026.1953686

Image Credits: AI Generated

DOI: 10.3389/fncel.2026.1953686

Keywords: Angelman syndrome, UBE3A, Kv4.2, DPP6, dendritic excitability, hippocampus, ion channels, membrane trafficking, mouse model, neuronal hyperexcitability, Impaired, complex

The researchers examined heart cells from male mice with severe heart failure induced by transverse aortic constriction and male rabbits with chronic failure produced by combined pressure and volume overload. Healthy controls were included for both species. The mouse model produced an ejection fraction below 25%, while rabbit hearts with left ventricular end-systolic dimension above 1.4 cm and ejection fraction below 35% were classified as failing. Cells were randomly assigned to vehicle, 1 micromolar empagliflozin, or 1 micromolar cariporide, a selective inhibitor of the sodium-hydrogen exchanger NHE-1. Patch-clamp recordings were conducted at 37 degrees Celsius, and electrophysiological outcomes were compared using hierarchical analysis of variance.

Failing cardiomyocytes had prolonged action-potential duration at 90% repolarization, greater short-term variability, and, in the rabbit model, a more depolarized resting membrane potential. Mouse cells also showed a lower maximal action-potential upstroke velocity. Empagliflozin pretreatment attenuated these abnormalities in both models: it reduced action-potential prolongation and variability, improved resting potential in rabbit cells, and increased upstroke velocity in failing mouse cells. Three-hour treatment produced no significant electrophysiological changes in healthy controls, while three-minute exposure had no measurable effect in either healthy or failing cells. The delay between empagliflozin and its observed effects was a central feature of the results.

The drug also shifted the pacing threshold at which action-potential alternans appeared, a beat-to-beat oscillation linked with unstable repolarization. In failing mouse cells, alternans appeared at rates of at least 7 hertz; at 10 hertz it occurred in all 15 untreated failing cells but in only one of 10 cells after empagliflozin pretreatment. In rabbits, the alternans threshold was 3 hertz in failing cells and 5 hertz in controls. Pretreatment increased the threshold in failing rabbit cells and reduced the magnitude of alternans to control levels. These observations were made in isolated cells and therefore do not establish that the treatment prevents arrhythmias in a whole heart or in a patient.

Delayed afterdepolarizations, spontaneous depolarizations that can trigger abnormal beats, were also reduced. In failing mouse cells, empagliflozin lowered their incidence and prevented spontaneous action potentials. In failing rabbit cells, they occurred in 10 of 15 cells without pretreatment, compared with 2 of 12 after pretreatment, a statistically significant difference. Acute empagliflozin exposure did not reduce alternans or afterdepolarizations. Cariporide did not reproduce the broad effects of empagliflozin: it did not improve action-potential duration or alternans in either model and only modestly reduced afterdepolarizations in mouse cells. This comparison does not rule out NHE-1 as a contributor, because the experiments used normoxic conditions and an internal pH of 7.2, where NHE-1 activity is relatively low.

Strong buffering of intracellular calcium with 10 millimolar EGTA reproduced much of the electrical stabilization. It reduced action-potential prolongation and variability, prevented alternans in both failing models, and abolished delayed afterdepolarizations. The results identify disturbed intracellular calcium handling as a major component of the cellular phenotype, although they do not prove that every effect of empagliflozin is calcium-dependent. Calcium and sodium handling are closely coupled in failing hearts: increased late sodium current can promote intracellular sodium accumulation, alter calcium exchange, activate calcium/calmodulin-dependent protein kinase II, and reinforce abnormalities in calcium release. The study therefore supports a mechanistic link between improved sodium and calcium regulation and the observed electrical effects, without establishing a single molecular target.

Direct current measurements identified two ion currents consistent with the action-potential changes. Late sodium current was small in healthy cells but markedly increased in failing mouse and rabbit cardiomyocytes, by 126% and 93%, respectively, relative to healthy controls. Three-hour pretreatment with empagliflozin reversed this increase in both species. The inward rectifier potassium current, which supports resting membrane potential and repolarization, was reduced in failing cells. Empagliflozin increased its density in both models, including the physiologically relevant outward current in mouse cells, where it rose by 46%, compared with a 15% increase in inward current. As with the action-potential results, empagliflozin did not significantly change these currents in healthy control cells.

The time dependence is compatible with several non-acute mechanisms discussed by the authors. Empagliflozin may suppress post-translational changes that enhance late sodium current in heart failure, potentially involving altered CaMKII-dependent phosphorylation. It might also act as a pharmacological chaperone, changing the trafficking or functional membrane expression of cardiac sodium channels. Previous studies have reported both direct inhibition of Nav1.5, generally at concentrations above the 1 micromolar used here, and increased functional expression of peak sodium current after longer exposure. The present experiments did not directly distinguish these mechanisms or test whether changes in late sodium and inward rectifier currents caused the action-potential improvements.

Several boundaries constrain the findings. The study used only male animals and deliberately excluded diabetes and ischemic disease, isolating a glucose-independent effect in chronic non-ischemic failure; whether responses differ by sex or in ischemic heart failure remains unknown. The work also examined isolated cells rather than intact hearts, animals, or people. Although empagliflozin improves clinical outcomes in heart failure, these experiments do not show that the electrophysiological changes observed here explain its clinical benefits or predict reduced arrhythmias in patients. The next steps would include tissue and organ-level studies using whole-heart optical mapping and in-vivo arrhythmia testing, alongside experiments designed to identify the relevant molecular targets and determine whether the effects are specific to empagliflozin or shared by other SGLT2 inhibitors.

Subject of Research: Cellular electrophysiological effects of empagliflozin in non-ischemic HFrEF cardiomyocytes

Article Title: Complex antiarrhythmic effects of empagliflozin in non-ischemic HFrEF cardiomyocytes

Article References: Hegyi, B., & Bers, D. M. (2026). Complex antiarrhythmic effects of empagliflozin in non-ischemic HFrEF cardiomyocytes. Frontiers in Pharmacology, 17, Article 1955044. https://doi.org/10.3389/fphar.2026.1955044

Image Credits: AI Generated

DOI: 10.3389/fphar.2026.1955044

Keywords: empagliflozin, heart failure, HFrEF, cardiac arrhythmias, action potential, ion channels, intracellular calcium, late sodium current, IK1, SGLT2 inhibitors, cardiomyocytes, Complex

The story begins with green algae. Hegemann and Nagel identified channelrhodopsins, a family of light-sensitive proteins embedded in the membranes of unicellular algae, and characterized them as ion channels that open when illuminated with blue light. Their landmark papers in 2002 and 2003 showed that channelrhodopsin-1 acts as a light-gated proton channel and that channelrhodopsin-2 is a directly light-gated, cation-selective membrane channel. In other words, these proteins convert photons into electrical and ionic signals with remarkable precision, a capability that algae use to navigate toward favorable light conditions.

Deisseroth’s contribution was to transplant this algal machinery into animal neurons. By expressing channelrhodopsins in specific cells and delivering light through optical fibers, researchers gained the ability to control the activity of defined neural circuits in living animals with millisecond precision. The 2007 demonstration of in vivo control of rodent motor cortex using an integrated fiberoptic and optogenetic interface established optogenetics as a foundational technology of modern neuroscience. Light, unlike drugs or electrodes, can be switched on and off instantly, targeted spatially, and dosed with extraordinary temporal resolution.

What the editorial by Zhan-Yan Zhang, Qing-Qing Liu, B. Marambe, Barana C. Jayawardana, Ge-Fei Hao, and Wen-Chao Yang makes clear is that this light-based control of ion fluxes is not confined to neurons. Plants, too, are governed by ionic signals. Calcium influxes trigger immune responses, anion effluxes drive stomatal closure during drought, and membrane potential gradients guide the growth of pollen tubes. If a light-gated channel can be expressed in plant cells, the same logic of optogenetic control applies: shine light of the right wavelength, and a specific ionic event unfolds at a chosen time and place.

Recent work shows how powerful this can be. A study published in Nature in 2024 by Ding and colleagues examined two engineered channelrhodopsins in plant leaf cells. The cation channel XXM 2.0, activated by green light, mediates calcium influx that sets off a cascade resembling a pathogen attack: bursts of reactive oxygen species, activation of the defense hormones jasmonic acid, salicylic acid, and ethylene, and ultimately programmed cell death. These are the hallmarks of a plant immune response, produced not by a microbe but by a beam of light. The same study showed that the light-gated anion channel ACR1 2.0 triggers an entirely different program. When illuminated, it drives anion efflux that mimics drought stress, causing stomata to close and abscisic acid to accumulate.

The implications for basic plant science are considerable. Plant signaling pathways are notoriously tangled: hormones cross-regulate each other, ion fluxes feed back on gene expression, and responses to pathogens overlap with responses to drought. Optogenetic tools offer a way to isolate variables. By varying the duration and frequency of light stimulation, researchers can dial calcium influx or anion efflux up and down independently of any pathogen or water deficit, then measure exactly how reactive oxygen species, phytohormone levels, and cellular damage respond. Combined with cell-type-specific expression, transcriptomic profiling, and functional validation of candidate genes, this approach could pinpoint the key regulatory nodes that connect ion signaling to defense and stress tolerance. The editorial suggests that pathogen inoculation and drought assays could then test whether the pathways identified optogenetically actually confer resistance in the field.

Agricultural chemistry stands to benefit as well. Insect nervous systems run on ion channels, and many of the most effective insecticides work by disrupting them. Voltage-sensitive sodium channels, gamma-aminobutyric acid receptors, ryanodine receptors, nicotinic acetylcholine receptors, and glutamate-gated chloride channels are all established targets of commercial agrochemicals. Screening new compounds against these channels has traditionally required electrical recordings or indirect assays that are slow and difficult to scale. A doctoral project at the University of Bonn described in the editorial took a different approach: by co-expressing channelrhodopsin 2 with the insect voltage-sensitive sodium channel, short light pulses could precisely control channel opening, creating a light-activated, high-throughput screening platform for compounds that act on this critical target.

Complementing this screening strategy is the emerging field of photopharmacology applied to agrochemicals. Rather than using light to open a channel, photopharmacology builds photoswitches, such as azobenzene groups, directly into insecticide molecules. The resulting compounds can be toggled between active and inactive states with specific wavelengths of light, giving researchers optical control over multiple insect ion channel targets. A 2023 review in Advanced Agrochemicals catalogued how this strategy could be applied across the major insecticide target classes. Together, optogenetics-assisted screening and photopharmacological design offer two complementary routes toward novel insecticidal lead compounds and, just as importantly, toward a clearer mechanistic understanding of how they work once found.

Perhaps the most striking agricultural application involves reproduction. In 2021, Zhou and colleagues demonstrated in Nature Plants that the light-gated anion channel ACR1 2.0 could control pollen tube growth in plants. Under uniform green-light illumination, anion efflux and membrane depolarization in pollen tube cells reversibly inhibited growth. When only part of a pollen tube was illuminated, growth redirected away from the light, revealing that anion efflux and membrane potential gradients contribute to the directional guidance of pollen tube tip growth. Since pollen tube guidance determines whether fertilization succeeds, understanding and potentially manipulating this process touches directly on seed set, one of the most important agronomic traits in crop production.

The editorial sketches a research agenda built on these foundations. In crop breeding, the ACR1 2.0 result provides a starting point for dissecting the relationships among anion fluxes, membrane potential changes, pollen tube guidance, and fertilization. Genetic variation analysis and genome editing could then validate candidate regulatory factors and determine their effects on seed set and yield. None of this suggests that farmers will soon shine lasers on their fields, and the authors are careful to frame channelrhodopsins as research tools rather than products. But the trajectory is familiar: optogenetics began as a curiosity of algal photobiology, became the defining technique of circuit neuroscience, and is now generating hypotheses, screening platforms, and molecular designs relevant to plant immunity, pesticide discovery, and breeding. The 2026 Nobel Prize honors a technology that taught us to talk to neurons in the language of light. The editorial’s argument is that plants, pests, and pollen tubes are listening too.

Subject of Research: Applications of Nobel Prize-winning channelrhodopsins and optogenetics in plant signaling, pesticide discovery, and crop breeding

Article Title: From medicine to fields: what the 2026 nobel prize means for agricultural biotechnology

Article References: Zhang, Z.-Y., Liu, Q.-Q., Marambe, B., Jayawardana, B. C., Hao, G.-F., & Yang, W.-C. (2026). From medicine to fields: what the 2026 nobel prize means for agricultural biotechnology. Advanced Biotechnology, 4(4), Article 43. https://doi.org/10.1007/s44307-026-00142-7

Image Credits: AI Generated

DOI: 10.1007/s44307-026-00142-7

Keywords: optogenetics, channelrhodopsins, Nobel Prize 2026, plant signaling, agricultural biotechnology, pesticide discovery, crop breeding, ion channels, pollen tube growth, plant immunity, photopharmacology, abscisic acid

At the conceptual heart of the collection lies a review by Alvarez and colleagues surveying biological processes where quantum phenomena may play a functional role. The authors synthesize representative cases including photon capture in vision, the highly efficient energy transfer that underpins photosynthesis, and vertebrate magnetoreception with particular emphasis on the radical pair mechanism. By clarifying the types of biological systems in which quantum dynamics may become functionally relevant, the review establishes a conceptual foundation for the diverse studies that follow, helping readers distinguish between processes where quantum effects are plausibly exploited by evolution and those where they remain incidental.

Building on that foundation, Parisio and coauthors contribute a pedagogical introduction to the quantum-mechanical concepts most relevant to biology, using the avian compass as a guiding example. The article presents the radical pair mechanism didactically, showing how spin dynamics and quantum coherence can influence biochemical reactions in living organisms. The avian magnetoreception case is especially compelling: certain birds appear to navigate using Earth’s magnetic field through light-sensitive cryptochrome proteins whose radical pair intermediates may retain spin coherence long enough for magnetic-field effects to modulate reaction outcomes. By bridging fundamental quantum theory with this biologically motivated model system, the contribution situates magnetoreception within the broader landscape of quantum effects in living matter.

The origin of life emerges as one of the most important themes in the collection. Quilici and colleagues offer a mini-review on how computational quantum methods can inform prebiotic chemistry, addressing scenarios ranging from thermal reactions on early Earth to photochemical processes under astrophysical conditions. Computational simulations of electronic structure and reaction pathways allow researchers to test how life could emerge from inorganic chemistry without needing to recreate every experimental condition in the laboratory. Quantum chemical calculations of reaction energetics, transition states, and photochemical excitation provide a mechanistic window onto the molecular-scale events that may have bridged nonliving and living chemistry billions of years ago.

Neuroscience enters the quantum biology conversation through a theoretical study of ion channels. Neuronal ion channels are complex, coupled, many-body quantum systems in which electronic coherence has recently been speculated to persist for relatively long timescales despite the decohering effects of their environments, possibly assisted by noise. Da Silva Ramos and colleagues model an ion channel as a linear quantum chain using a tight-binding Hamiltonian with Lindblad source-drain dynamics, examining how correlated on-site energies act as a tunable switch between trapping and conduction. The work suggests that correlated disorder, rather than being purely detrimental, could modulate transport efficiency in biological ion channels. If quantum coherence in ion transport proves functionally relevant, the implications for neuroscience and medicine could be profound, opening new avenues for understanding neuronal signaling and designing interventions at the molecular scale.

Light-matter interactions in human tissue feature prominently in two contributions on retinal and skin photophysics. Brash and Gaillard examine the molecular mechanisms of chemiexcitation and review emerging evidence that melanin in the human retina may undergo chemiexcitation as part of a protective response against age-related macular degeneration. Chemiexcitation refers to the generation of electronically excited states through chemical reactions rather than photon absorption, and the review highlights how such excited states can influence biological function. Herrera and colleagues, meanwhile, investigate how red-light irradiation influences cellular responses, with particular attention to nitric oxide homeostasis and its implications for phototherapeutic interventions. Their work examines how photon energy interacts with biological chromophores to modulate cellular signaling and metabolic pathways, contributing to a growing body of research on photobiomodulation in living systems.

At the subtle end of the biophysical spectrum, Gallep analyzes patterns of ultraweak photon emission in seedlings that appear to follow periodicities resembling local gravimetric tidal cycles across several geographic locations. Auto-luminescence in seedlings, if genuinely coupled to gravimetric tides, would situate biophoton dynamics within a chronobiological framework and suggest that environmental physical fluctuations may leave measurable signatures on biological photon emission rhythms. The study exemplifies the field’s willingness to explore subtle physical influences on biological systems, a hallmark of quantum biology that demands rigorous statistical treatment across multiple sites and conditions.

Systems-level and translational perspectives round out the collection. Casotti and colleagues present an integrative view of cancer research combining systems biology, evolutionary thinking, and multidisciplinary synergy, emphasizing the reduction of disciplinary silos, open data sharing, and patient-centered feedback in therapeutic development. Costa and colleagues report an electrochemical aptasensor for detecting dengue NS1 protein, built on a self-assembled monolayer of DNA aptamers and thiol molecules and characterized through electrochemical capacitance spectroscopy, with optimization via aptamer-to-thiol ratio tuning. The device illustrates how molecular recognition integrated with nanoscale electrochemical sensing can translate bio-inspired physical principles into practical diagnostics. Davinack outlines how quantum computing and quantum machine learning, through algorithms for classification, clustering, and optimization, could support population-genetic inference and molecular ecology, while Martins and colleagues review the biological mechanisms and clinical evidence for photobiomodulation therapy in neuropathic pain, discussing multimodal strategies, personalized dosimetry, and wearable and transcranial technologies.

Together, the contributions reflect the diverse theoretical, computational, experimental, and translational frameworks now converging on quantum phenomena in biological systems. The editorial expresses hope that the Research Topic provides a useful overview of current research activity and supports continued dialogue and collaboration across disciplines. As quantum technologies mature and biological instrumentation grows ever more sensitive, the boundary between quantum physics and biology is likely to blur further, promising discoveries that range from the molecular origins of life to next-generation medical therapies.

Subject of Research: Quantum biology

Article Title: Editorial: Quantum biology

Article References: Pires de Sousa, M. V. (2026). Editorial: Quantum biology. Frontiers in Photonics, 7, Article 1826400. https://doi.org/10.3389/fphot.2026.1826400

Image Credits: AI Generated

DOI: 10.3389/fphot.2026.1826400

Keywords: quantum biology, biophotonics, magnetoreception, radical pair mechanism, prebiotic chemistry, ion channels, photobiomodulation, biosensors, quantum computing, retinal photochemistry, Editorial, Quantum

The discovery arose from an unexpected direction. TMEM63B belongs to a small family of recently characterized ion channels whose opening is governed by mechanical force rather than by chemical ligands or voltage. Its closest relative, TMEM63A, has been implicated in hearing and mechanical sensation, so the researchers set out to test whether TMEM63B performs a similar job in the somatosensory system. They began by mapping where the protein appears in the nervous system and found that it is broadly expressed across the neurons of the dorsal root ganglion, the cellular way station through which nearly every touch, pressure, and temperature signal from the body must pass. That broad distribution made the channel a plausible candidate for a general sensory function, but what the knockout mice revealed was not what anyone anticipated.

When the team deleted TMEM63B throughout the animal, the mice showed a marked reduction in their sensitivity to noxious heat. The same deficit appeared when the deletion was restricted to the dorsal root ganglia themselves, confirming that the channel acts within sensory neurons rather than somewhere else in the pain circuitry. Crucially, responses to other sensory modalities were largely preserved, which pointed to a specific role in thermosensation rather than a general impairment of the animals’ sensory systems. In behavioral assays, mice lacking the channel tolerated heat stimuli that wild-type animals found aversive, a phenotype reminiscent of what happens when known heat-activated TRP channels are removed, yet the effect was distinct enough to indicate that TMEM63B operates as an independent contributor rather than a mere accessory.

To understand what was happening at the level of individual cells, the researchers turned to calcium imaging and electrophysiology, the twin workhorses of sensory neuroscience. In cultured dorsal root ganglion neurons, raising the temperature triggered a surge of intracellular calcium and an accompanying ionic current, the signature of a heat-activated channel at work. In neurons from TMEM63B-deficient mice, both signals were significantly attenuated. The channel’s removal did not abolish heat responses entirely, which is consistent with the established role of TRP channels, but it measurably weakened them, revealing that TMEM63B accounts for a real share of the total heat-evoked current that sensory neurons can generate.

The most telling measurement came from the threshold experiments. Sensory neurons do not fire action potentials the instant a stimulus begins; they wait until the depolarization crosses a critical point. By recording the temperature at which heat-sensitive neurons first launched an action potential, the team found that deleting TMEM63B elevated this threshold. In practical terms, neurons without the channel required a hotter stimulus before they committed to firing, which provides a direct mechanistic explanation for the blunted heat sensitivity observed in the behaving animals. The channel is not merely a passive bystander in the heat response; it actively lowers the bar at which nociceptive neurons decide that a stimulus has become dangerous.

Having established the channel’s role in living neurons, the researchers asked whether TMEM63B could respond to heat on its own. They expressed the recombinant protein in a heterologous system and monitored its activity with calcium imaging. The result was a moderate heat-activated response, confirming that TMEM63B is intrinsically thermosensitive rather than merely modulating other heat sensors. Yet the response was noticeably weaker than what the channel appears to deliver inside neurons, and that discrepancy pointed the investigators toward a missing cofactor in the cellular environment.

The missing ingredient turned out to be a lipid. Arachidonic acid, a polyunsaturated fatty acid released from membrane phospholipids during inflammation and tissue injury, dramatically potentiated the heat response of recombinant TMEM63B. In its presence, the channel was strongly activated by temperatures that had produced only modest effects before. This lipid-dependent modulation is more than a biochemical curiosity. Arachidonic acid and its metabolites accumulate at sites of injury and inflammation, precisely the conditions under which noxious heat becomes most punishing. A channel whose heat sensitivity is amplified by inflammatory lipids would be ideally positioned to become more responsive exactly when the body needs its pain alarm to ring loudest.

The discovery carries several implications for how scientists think about temperature sensing. First, it demonstrates that the TRP channels, long considered the dominant and perhaps exclusive molecular thermometers of the somatosensory system, do not act alone. TMEM63B now joins the short list of non-TRP proteins shown to contribute to noxious thermosensation, and its membership in the mechanosensitive channel family raises the possibility that mechanical and thermal signaling share deeper molecular overlap than previously appreciated. Second, the lipid modulation of TMEM63B suggests a regulatory layer that most thermosensation research has not explored. If the sensitivity of heat-detecting channels can be tuned by the membrane’s fatty acid composition, then the same stimulus may be perceived differently depending on the biochemical state of the tissue, providing a potential mechanism for the heightened heat sensitivity that accompanies inflammation.

There are also translational questions worth asking. Chronic pain conditions often involve abnormal thermal sensitivity, and the molecular targets of current analgesics remain limited. A channel that contributes to noxious heat detection and whose activity depends on a modifiable lipid environment offers a new angle for pharmacological intervention, although the authors’ findings stop well short of any therapeutic claim. What the study does establish is a concrete mechanism: a broadly expressed dorsal root ganglion channel, activated by heat, potentiated by arachidonic acid, and required for the full behavioral and cellular response to noxious temperatures. As the field continues to inventory the molecular sensors that translate the physical world into neural signals, TMEM63B stands as a reminder that some of the most important players may have been hiding in plain sight, classified under the wrong sense all along.

Subject of Research: The role of the mechanosensitive ion channel TMEM63B in noxious heat sensation in dorsal root ganglion neurons

Article Title: The mechanosensitive channel TMEM63B contributes to noxious heat sensation in the dorsal root ganglia

Article References: Ye, C., Zang, Y.-Y., Duan, G.-F., Chen, J., Wu, D., Wang, D., Li, C., Xu, Y., Xia, T., Gu, X., & Shi, Y. S. (2026). The mechanosensitive channel TMEM63B contributes to noxious heat sensation in the dorsal root ganglia. PLOS Biology, 24(10), e3004060. https://doi.org/10.1371/journal.pbio.3004060

Image Credits: AI Generated

DOI: 10.1371/journal.pbio.3004060

Keywords: TMEM63B, dorsal root ganglion, noxious heat, thermosensation, ion channels, TRP channels, arachidonic acid, mechanosensation, pain neuroscience, calcium imaging, sensory neurons, PLOS Biology

Detailed neuronal models have become essential instruments in modern neuroscience. They allow researchers to examine the mechanisms behind observed electrical behavior and to predict how neurons respond under conditions that are difficult or impossible to study directly in experiments. They also serve as the fundamental building blocks of large-scale network models of brain regions. Yet many earlier models suffered from significant limitations: they were often fitted to a narrow set of experimental conditions, leaving little information about how they would behave outside the scope of the original study. Because multiple parameter combinations can fit limited data equally well, such underconstrained models can produce unrealistic parameter values and incorrect predictions when applied to new situations.

The motivation for the new work came in part from a sobering assessment published a few years ago. Using the HippoUnit validation tool, researchers compared several available rat CA1 pyramidal cell models against experimental data from a variety of paradigms and found that although some models captured certain aspects of the cells’ behavior—typically those they were originally built to replicate—none could simultaneously reproduce all the relevant behaviors. A thoroughly validated, accurate, general-purpose model of this crucial cell type was simply missing. The new study set out to fill that gap by leveraging the extraordinary wealth of anatomical, biophysical, and physiological data available for CA1 pyramidal cells.

The construction process was systematic and iterative. The team started with a high-quality morphological reconstruction of a real CA1 pyramidal cell, complete with detailed soma and dendrites, and added axonal compartments from a separate reconstruction. They then curated a new set of ion channel models, carefully re-evaluating each one against the latest experimental data on channel kinetics and distribution. The final model contains thirteen distinct active voltage- and calcium-gated ion channels, including sodium channels with different kinetics for the soma, axon, and dendrites; multiple types of potassium channels; and four types of calcium channels. Calcium currents were described using the Goldman-Hodgkin-Katz equation, which provides a better fit for calcium-mediated currents than the traditional conductance-based formalism.

Parameters that were not sufficiently constrained by experimental data were determined through automated optimization using the Neuroptimus tool, which employs the Covariance Matrix Adaptation Evolution Strategy algorithm. The researchers ran twenty independent optimizations simultaneously from different random starting points to avoid getting stuck in local minima. The optimization targeted electrophysiological features extracted from somatic whole-cell recordings of real rat CA1 pyramidal cells, including spike counts, interspike intervals, action potential shapes, and voltage responses to both positive and negative current injections. When a parameter consistently drifted toward the edge of its allowed range, the team expanded the boundary and re-ran the search.

Validation was equally rigorous. The team used all five built-in tests of the HippoUnit framework, which automatically simulates experimental protocols and compares model behavior against experimental data. The Somatic Features Test examined voltage responses to current injections; the Backpropagating Action Potential Test evaluated how action potentials propagate from the soma into the dendrites; the Post-synaptic Potential Attenuation Test measured how synaptic signals diminish as they travel toward the soma; the Depolarization Block Test probed the cell’s response to strong sustained stimulation; and the Oblique Integration Test assessed nonlinear synaptic integration in thin dendritic branches. The models performed well on four of the five tests, with the depolarization block test revealing an interesting discrepancy that the researchers traced to the simplified axonal morphology in their model.

One of the most consequential findings concerned the NMDA receptor, a type of glutamate receptor critical for nonlinear dendritic integration. The team systematically evaluated eight different published models of NMDA receptor voltage dependence and found that none produced fully satisfactory results in their cell model. Some showed far too much supralinear summation of synaptic inputs, others remained sublinear, and none matched the experimental observations of how clustered synaptic inputs on oblique dendrites produce dendritic spikes. By systematically tuning the parameters of a sigmoid function describing the voltage-dependent magnesium block of the receptor, they identified a voltage dependence that matched experimental data both qualitatively and quantitatively. The result suggests that the precise voltage dependence of NMDA receptors has a major impact on how CA1 pyramidal cells integrate their inputs.

A second major contribution concerned dendritic spines, the tiny protrusions that receive most excitatory synaptic input. Modeling all 29,602 spines explicitly increases computational cost by more than an order of magnitude, so the team compared three approaches: merging spine properties into the parent dendrite using a surface-correction factor, explicitly modeling only the spines that receive synaptic input, and explicitly modeling every spine. Remarkably, for somatic current responses, backpropagating action potentials, and synaptic potential attenuation, all three versions behaved almost identically. But for nonlinear synaptic integration in oblique dendrites, the version without explicit spines produced clearly different results, because the high electrical resistance of the spine neck amplifies local voltage transients and strongly activates voltage-dependent mechanisms in the spine head. The hybrid approach—explicitly modeling only spines that receive synapses—offered a practical compromise.

The researchers also systematically blocked each ion channel in the model and compared the effects against what is known from experimental pharmacology. Blocking sodium channels prevented firing entirely; blocking A-type potassium channels eliminated the distance-dependent attenuation of backpropagating action potentials; blocking the hyperpolarization-activated current abolished the voltage sag during negative current injections. These channel-by-channel validations confirmed that the model’s components behave like their biological counterparts. The team also performed gradual perturbations, shifting each parameter by small amounts to probe how sensitive the model’s behavior is to precise parameter values, finding that a few critical parameters—particularly those governing sodium channels—had dominant effects across all tests.

The new model, along with all optimization scripts and validation results, has been made publicly available, and the researchers hope it will serve as a reliable component of detailed hippocampal network models as well as a platform for studying synaptic plasticity and dendritic computation. Just as importantly, the systematic workflow they developed—combining curated biophysical mechanisms, automated parameter fitting, and multi-paradigm validation—should generalize to other cell types. As the authors note, the most critical requirement for building faithful data-driven models of any neuron is the availability of comprehensive experimental data, and their approach provides a template for how such data can be transformed into models that are accurate, reusable, and broadly applicable across the computational neuroscience community.

Subject of Research: Development and validation of a detailed biophysical model of hippocampal CA1 pyramidal neurons

Article Title: How to train your neuron: developing a detailed, up-to-date, multipurpose model of hippocampal CA1 pyramidal cells

Article References: Tar, L., Sáray, S., Mohácsi, M., Freund, T. F., & Káli, S. (2026). How to train your neuron: developing a detailed, up-to-date, multipurpose model of hippocampal CA1 pyramidal cells. Frontiers in Computational Neuroscience, 20, Article 1897214. https://doi.org/10.3389/fncom.2026.1897214

Image Credits: AI Generated

DOI: 10.3389/fncom.2026.1897214

Keywords: CA1 pyramidal cells, hippocampus, computational neuroscience, biophysical modeling, ion channels, dendritic spines, NMDA receptors, Neuroptimus, HippoUnit, parameter optimization, synaptic integration, dendritic computation

The 2011 milestone, when Kralj and colleagues imaged electrical spiking in E. coli at roughly one hertz, was field-shaping in two ways. First, the signal itself: electrical spikes in bacteria invited comparisons to neuronal action potentials, even though the underlying mechanisms and spatial scales differ profoundly. Second, the hypothesis space: the spikes coincided with rapid efflux of a small-molecule fluorophore, hinting that electrical state might couple directly to membrane transport machinery and potentially influence drug susceptibility or stress responses. That observation also seeded the field’s central controversy, which persists today: are membrane-potential transients a cause of downstream bacterial behavior, or merely an aftereffect of fluctuating metabolic conditions?

Conceptually, the review distinguishes three related but mechanistically distinct domains that are frequently conflated in the literature. Transmembrane voltage dynamics encompass fluctuations and excitability-like transients in individual cells. Ionic signaling in communities involves extracellular potassium waves that depolarize neighboring cells across millimeter scales. Electrochemical interactions at interfaces include electrode-based stimulation and impedance phenotyping. Bacterial membrane potential typically lies within a roughly seventy-millivolt range between minus seventy-five and minus one hundred forty millivolts, with strong dependence on growth medium, growth phase, and species. In neuroscience, excitability requires a stereotyped, amplified response to a threshold stimulus followed by a refractory period, and whether bacteria strictly fulfill this definition remains debated, which is why the authors deliberately use the term excitability-like.

Measurement remains the field’s principal bottleneck and driver of controversy. Many classical voltage probes and calibration assumptions were developed for eukaryotic membranes and must be re-validated for bacterial envelopes and growth conditions. Commonly used Nernstian indicators such as thioflavin T, DiBAC, and TMRM tend to report steady-state potential rather than fast transients, and their signals can be confounded by membrane permeability changes, efflux pump activity, and other variations in membrane physiology independent of voltage. Even at low concentrations, these dyes can influence bacterial growth. Genetically encoded PROPS-like indicators avoid some of these pitfalls but require genomic modification, limiting clinical applicability. Recent synthetic reviews now explicitly call for bacterial-specific standardization, including careful reporting of medium composition, growth phase, probe concentration, illumination dose, and validation by multiple experimental approaches.

Non-optical approaches play a crucial complementary role, corroborating optical results while avoiding potential biases such as phototoxicity. Krasnopeeva and colleagues developed an electric-circuit analogue linking the proton motive force, membrane electrical properties, and catabolism, using the bacterial flagellar motor as a rapid single-cell readout under dynamic stresses. Their approach could separate stressors that directly change membrane potential, as an ionophore would, from those that cause physical membrane damage. Notably, they found that shorter-wavelength light can induce electrophysiological impairment, reinforcing the need for rigorous wavelength and dose controls in photobiology-driven experiments. Other physical voltmeters have achieved millisecond resolution in membrane-potential variations, and a 2025 study pushed toward absolute membrane-potential measurements in Bacillus subtilis using fluorescence lifetime, showing that a single strain can vary between minus sixty-five and minus one hundred twenty-seven millivolts when moving from rich to minimal medium.

The second inflection point came from biofilm studies in B. subtilis, where electrical and metabolic dynamics were shown to be coupled at community scale. In 2015, Liu and colleagues described long-range metabolic codependence between peripheral and interior biofilm cells as a mechanism resolving a growth-protection conflict, producing collective oscillations. The same year, Prindle and colleagues demonstrated that ion channels can conduct long-range electrical signals through spatially propagating potassium waves: a metabolic trigger induces potassium release, the increased extracellular potassium depolarizes neighboring cells, and the depolarization wave coordinates metabolic states across the biofilm. These findings extended beyond a single community, with two oscillating biofilms shown to synchronize through electrical signaling, an ecological phenomenon described as nutrient time-sharing.

Theory has matured in parallel. A percolation-based framework linked signal propagation to community heterogeneity and spatial organization, providing a quantitative language for when long-range transmission becomes possible and how near-critical organization can facilitate it. A complementary spatial reaction-diffusion model explicitly combined metabolic and electrical components, bridging the metabolism-first and channel-first schools of thought that often appear as competing intuitions. Preliminary coincident results have emerged in Gram-negative bacteria as well: membrane-potential oscillations have been demonstrated in E. coli biofilms, and collective polarization dynamics beyond a critical biofilm size have been observed in Neisseria gonorrhoeae. Electrical signals also reach outward: potassium-channel-mediated signaling generated by a biofilm can attract distant motile cells in a species-independent manner, and voltage transients in E. coli have been shown to induce calcium influx, supporting the idea that bacteria can treat calcium as a second messenger.

The field has now entered a perturb-and-measure phase, shifting from observation to intervention. A membrane-targeted azobenzene called Ziapin2 was shown to photomodulate membrane potential in B. subtilis, positioning photopharmacology-like strategies as practical tools for bacterial electrophysiology without genetic manipulation. Structured multiscale silicon has been developed as a nongenetic optical transducer capable of modulating single bacterial cells and biofilms at high spatiotemporal resolution. Electrical platforms are advancing too: identical electrical stimuli can produce opposite polarization dynamics depending on the proliferative capacity of the cells, emphasizing that bacterial electrical responses are state-dependent. At the translational end, a drug-free bioelectronic strategy exploited the selective excitability of Staphylococcus epidermidis and demonstrated reduced colonization on a porcine skin model using an electroceutical patch, while electrical impedance spectroscopy revealed that E. coli biofilms exhibit stable negative capacitances under small DC bias, implicating a specific voltage-gated potassium channel.

Among the more provocative post-2015 directions is the possibility that bacterial communities encode persistent electrical states. Transient optical perturbations have been shown to generate a long-lasting potassium-channel-mediated change in membrane potential within a biofilm, such that exposed cells subsequently responded out of phase relative to unexposed cells during oscillations, interpreted as a type of membrane-potential-based memory within a microbial community. This behavior is consistent with bistable dynamics within the metabolic-electrical network, and for photobiology it opens a methodological opportunity: optical perturbation can write states, optical readout can track them, and spatially structured illumination can test whether writing is local, propagative, or dependent on community connectivity.

Looking forward, the review identifies several frontiers. Nongenetic optical modulators point toward bacterial all-optical electrophysiology experiments where stimulation patterns are as controllable as in modern optogenetics. Supplementing cultures with tricarboxylic acid cycle intermediates such as glutamate, fumarate, or pyruvate can boost the proton motive force, amplify membrane potential, and increase the uptake of aminoglycoside antibiotics, suggesting a relevant clinical framework that might work synergistically with chemical phototransducers like Ziapin2. Standardized interrogation protocols pairing defined stimuli with time-resolved readouts could generate reproducible response fingerprints of bacterial physiological state, enabling diagnostics for antibiotic tolerance, persister formation, and dormancy. The relation between membrane potential and antibiotic tolerance still lacks consensus on how hyperpolarization versus depolarization affects antibiotic efficacy, requiring extensive investigation across bacterium-stimulus-antibiotic combinations. Whether bacterial spikes ultimately earn the name action potentials or demand bacteria-native descriptors anchored in metabolism and transport physiology, the next fifteen years promise to transform light-driven tools into causal instruments for reading, writing, and programmatically controlling the electrical lives of microbes.

Subject of Research: bacterial bioelectricity and membrane potential dynamics

Article Title: Bacterial bioelectricity, the first 15 years: developments, tools, and remaining questions

Article References: Cianflone, E., Keller, H. R., Subramaniam, N., & Paternò, G. M. (2026). Bacterial bioelectricity, the first 15 years: developments, tools, and remaining questions. Frontiers in Photobiology, 4, Article 1834373. https://doi.org/10.3389/fphbi.2026.1834373

Image Credits: AI Generated

DOI: 10.3389/fphbi.2026.1834373

Keywords: bacterial bioelectricity, membrane potential, electrophysiology, biofilms, potassium waves, voltage imaging, optogenetics, photobiology, antimicrobial control, ion channels, Bacillus subtilis, Escherichia coli

Ion channels are the protein macromolecules that conduct electrically charged ions across neuronal membranes, and their conductance is controlled by their conformational state. Markov models of molecular kinetics sit at the very foundation of neuroscience, describing the physical components that implement the brain’s computations. They were first applied to neuroscience to describe the ion channels responsible for generating action potentials, and because brains are composed of trillions of repeated components, computational neuroscience has what the study’s author calls a voracious appetite for these models. Yet despite their biological fidelity, Markov kinetic models have remained underutilized because they are notoriously difficult to simulate efficiently.

The mathematical core of the problem is the master equation, which describes how a probability distribution over the channel’s conformational states evolves over time. This initial value problem has an analytic solution expressed through the matrix exponential function, yielding what is known as the propagator matrix. The propagator matrix advances the state of the model over each time step, but computing it exactly is prohibitively expensive for large-scale simulations. Direct evaluation of the Taylor series expansion converges slowly and is numerically unstable, while better methods such as scaling and squaring with Padé approximants still involve matrix-matrix multiplications whose time complexity scales cubically with the number of model states.

Established numerical solvers fall into two camps, each with serious drawbacks. Explicit integration methods, such as the forward Euler and Runge–Kutta–Chebyshev approaches, evaluate the derivative and run the state forward in time. They are simple and efficient, with quadratic time complexity, but they can be numerically unstable, allowing small errors to accumulate and compound exponentially into sudden catastrophic failure. Implicit methods, including the backward Euler and Crank–Nicolson schemes, evaluate the derivative at the end of the time step and offer accurate, stable integration, but they require solving a system of equations via Gaussian elimination, giving them cubic time complexity. The NEURON simulator, the state-of-the-art tool for conductance-based neuronal modeling, uses implicit methods by default.

The AME method takes a fundamentally different approach. Instead of computing the propagator matrix from scratch at every time step, it constructs a piecewise polynomial approximation of the propagator matrix function. The input space is partitioned into a regular grid of non-overlapping regions, each containing a polynomial approximation fitted to sampled data using linear least squares regression. Within each region, the input vector is transformed into a normalized range, and because the function being approximated returns a full matrix, the method builds a separate approximation for every cell of the propagator matrix, with all approximations sharing the same partitions and polynomial form for computational efficiency.

What makes the method particularly elegant is how it measures and controls its own accuracy. The integration error is defined as the maximum absolute error in any component of the state vector after integrating over one unit of time, across all possible initial states and inputs. Exploiting the Chapman–Kolmogorov equation, the method squares propagator matrices to extend sample integration periods from one time step to a full unit of time. Because Markov models are linear and probability is a conserved quantity, the maximum error occurs when the entire probability mass sits in a single state, which means the error of the standard basis vectors bounds the error of all possible state vectors. A greedy algorithm then adjusts the number of input partitions until the residual integration error falls below a user-specified error target, and a hill-climbing algorithm searches the space of polynomial forms to maximize throughput.

The method also handles a subtlety specific to neurobiology: chemical concentrations such as neurotransmitter levels span many orders of magnitude, which is difficult to approximate with fixed-size piecewise regions. The AME method preconditions concentration inputs with a base-2 logarithmic transform and a small positive offset, determined experimentally by testing 50 offsets in a geometric progression and selecting the one that minimizes the root-mean-square residual error. The base-2 logarithm is preferred because efficient algorithms and even dedicated hardware instructions, such as the lg2 instruction in Nvidia PTX assembly, can compute it quickly.

To validate the approach, the author assembled a benchmark of 99 Markov models drawn from four independent sources, covering AMPA and NMDA receptors, all nine subtypes of voltage-gated sodium channels, and 88 models of voltage-gated potassium channels built from seven kinetic schemes. The models were obtained from ModelDB and GitHub, and some numerically unstable models were detected and rejected by the tooling. Accuracy comparisons using the analytic solution as ground truth showed that the backward Euler method is only first-order accurate, with error directly proportional to the time step, whereas the AME method controls its accuracy independently of the time step, achieving an error target of 10 to the power of minus 3 for all state and input vectors tested.

The practical consequences were demonstrated in simulations of action potentials, the electrical signals that broadcast information throughout the brain, where timing errors quickly cascade. A single-compartment neuron containing eight ion channels from the benchmark was stimulated to produce trains of action potentials. With the backward Euler method, action potentials were delayed in proportion to the time step, while simulations using the exact matrix exponential and the AME method delayed action potentials only in proportion to the square of the time step, limited by NEURON’s second-order cable solver. Varying the AME error target showed convergence by 10 to the power of minus 3, while the loosest target of 10 to the power of minus 1 caused simulations to fail to produce action potentials altogether. In speed benchmarks with 1,000 single-compartment neurons, the AME method consistently ranked fastest, followed by backward Euler and then the exact matrix exponential.

The accompanying open-source program, called ame and available under the MIT license on the Python Package Index, integrates the method into the NEURON simulator, and for comparison the exact analytic solution was also added to NEURON as a new solver option. On an NVIDIA B200 GPU, the method achieved integration speeds as low as 0.059 nanoseconds per step per instance for a four-state potassium channel model, corresponding to real-time simulation of roughly 420,000 instances. The method does have limitations: it is restricted to models with one or two input variables, its time complexity scales quadratically with the number of model states, and building the approximation can take up to an hour per model on state-of-the-art hardware. Nevertheless, because most voltage-gated ion channels genuinely have only one input and most phenomena of interest can be modeled with a dozen states or less, the method’s trade-offs are well suited to its purpose. By decoupling accuracy from the time step and delivering GPU-friendly, branch-free execution, the AME method paves the way for large-scale neuronal simulations to adopt far more realistic models of the ion channels that generate the brain’s electrical activity.

Subject of Research: A fast and accurate numerical method for simulating Markov kinetic models of ion channels in large-scale neuronal simulations

Article Title: Approximate matrix exponential: a fast and accurate solver for Markov kinetic models of ion channels

Article References: McDougall, D. A. (2026). Approximate matrix exponential: a fast and accurate solver for Markov kinetic models of ion channels. Frontiers in Computational Neuroscience, 20, Article 1901593. https://doi.org/10.3389/fncom.2026.1901593

Image Credits: AI Generated

DOI: 10.3389/fncom.2026.1901593

Keywords: ion channels, Markov kinetic models, matrix exponential, NEURON simulator, GPU computing, numerical integration, computational neuroscience, propagator matrix, action potentials, conductance-based models, piecewise polynomial approximation, neuronal simulation

The biological starting point is a channel protein that vascular biologists have studied for decades. In the smooth muscle cells of cerebral arteries, calcium- and voltage-gated potassium channels of large conductance, known as BK channels, act as a built-in brake on contraction. When calcium rises inside a contracting myocyte, BK channels open and release potassium, which repolarizes the membrane, relaxes the muscle cell and keeps the artery open. Alcohol disrupts this safety mechanism. By inhibiting BK channels in cerebrovascular smooth muscle, alcohol allows the arteries to constrict, reducing blood flow to brain tissue, a response that has been proposed to contribute to the elevated stroke risk seen after heavy drinking episodes.

Over the years, the Memphis group made a series of counterintuitive observations. A high-cholesterol diet, far from worsening alcohol’s cerebrovascular effects, actually protected rats against alcohol-induced constriction of cerebral arteries. More recently, they found that oral supplementation with docosahexaenoic acid, or DHA, the omega-3 fatty acid abundant in fish oil, offered similar protection in males. That raised an obvious question: if both interventions work, do their effects stack? To find out, the researchers, led by Shiwani Thapa, Steven Mysiewicz, Alex Dopico and Anna Bukiya, combined the two protective strategies in the same animals and asked whether the combined benefit exceeded either one alone.

The in vivo experiments used Sprague-Dawley rats maintained on a high-cholesterol diet for 18 weeks, long enough to significantly raise both blood lipids and cholesterol content within the artery walls themselves. Half of the animals also received daily oral DHA at 14 milligrams per kilogram of body weight, while controls received an equivalent volume of water. The team then implanted a cranial window over branches of the middle cerebral artery, threaded a catheter into the carotid artery to deliver alcohol directly into the cerebral circulation, and filmed the pial arterioles every minute under a microscope. Alcohol was infused at 50 millimolar, a concentration corresponding to the moderate-to-heavy drinking range and roughly three times the legal driving limit in most of the United States.

The results were unambiguous. In males on the high-cholesterol diet alone, the fold-change in arteriole diameter nine minutes after alcohol infusion averaged 1.13, statistically indistinguishable from baseline fluctuations, meaning the arteries essentially refused to constrict. Adding DHA changed nothing meaningful: the fold-change was 0.95, not significantly different from the control group. Females showed the same pattern, with values of 1.12 and 1.04 respectively. If cholesterol and DHA acted on separate targets, the combination should have produced at least some additional benefit. Instead, the effect plateaued, a classic ceiling signature suggesting that both lipids converge on a shared mechanism that, once engaged, cannot be engaged further.

To rule out systemic confounders, the team repeated the logic in isolated arteries. Pressurized middle cerebral arteries from rats were stripped of their endothelium or left intact, enriched with cholesterol using a methyl-beta-cyclodextrin delivery complex, and then bathed in 3 micromolar DHA before being challenged with alcohol concentrations spanning 5 to 100 millimolar, from behaviorally relevant doses to sub-lethal levels. Cholesterol enrichment alone abolished alcohol-induced constriction across the entire range in both sexes, and DHA added nothing. Because the outcome was identical with and without a functional endothelium, the shared pathway appears to reside within the smooth muscle cell itself, independent of the circulation and of complex neuronal networks.

The search for that shared target turned to a single amino acid. Previous work from the same laboratory had shown that cholesterol’s protection hinges on tyrosine 450, residue Y450, within the slo1 alpha subunit that forms the BK channel pore. Substituting phenylalanine for tyrosine, the Y450F mutation, disables cholesterol’s protective effect. If cholesterol and DHA truly share a pathway, Y450 should also be required for DHA’s protection. To test this, the researchers turned to genetically engineered knock-in mice carrying the slo1Y450F substitution, bred on a C57BL/6J background alongside wild-type littermates, and pressurized their isolated middle cerebral arteries ex vivo at 60 millimeters of mercury to develop myogenic tone.

In males, the prediction held. In wild-type arteries, alcohol at 50 millimolar constricted vessels by about 1 percent of baseline diameter, and DHA flipped that response to a slight average dilation, a significant protective effect. In arteries from Y450F knock-in males, DHA’s protection vanished entirely: alcohol responses were statistically identical with and without the fatty acid. A two-way analysis of variance revealed a significant interaction between genotype and DHA treatment, confirming that loss of the tyrosine residue, not some background difference between the mouse groups, was responsible for eliminating the protection.

The females told a more surprising story. Wild-type female arteries showed little alcohol-induced constriction to begin with, consistent with earlier reports that vessels from female rodents are consistently less sensitive to alcohol, possibly reflecting differences in BK channel accessory beta1 subunit composition or modulation by female steroid hormones. But in Y450F knock-in females, alcohol produced a pronounced constriction of nearly 3.9 percent, and DHA fully protected against it. In other words, removing tyrosine 450 did not abolish DHA’s protection in females the way it did in males; instead, it unmasked a vulnerability that DHA could still counter through some other, Y450-independent route. The researchers conclude that slo1Y450 functions as a sexually dimorphic sensor within a shared pathway linking alcohol, cholesterol and DHA actions on cerebral artery diameter.

The physiological stakes are considerable. Because blood flow varies with the fourth power of vessel radius under Poiseuille’s law, even a 5 percent change in cerebral artery diameter can reduce perfusion by up to 20 percent, and neuronal function is acutely sensitive to such perturbations. The Tennessee team cautions that these findings come from rodent and mouse models and that the reasons for the sex differences remain unresolved, but the work narrows the molecular landscape considerably: a single tyrosine in a potassium channel emerges as a potential relay station where alcohol’s vasoconstrictive action and two dietary lipids’ protective effects meet. It also delivers a broader message for vascular pharmacology, namely that strategies to blunt alcohol’s cerebrovascular damage may need to be designed, and dosed, differently for men and women.

Subject of Research: Shared molecular pathway by which cholesterol and docosahexaenoic acid protect cerebral arteries against alcohol-induced constriction via the BK channel slo1 Y450 residue

Article Title: Cholesterol and docosahexaenoic acid likely protect against alcohol-induced constriction of cerebral arteries via a common pathway

Article References: Thapa, S., Mysiewicz, S., Dopico, A. M., & Bukiya, A. N. (2026). Cholesterol and docosahexaenoic acid likely protect against alcohol-induced constriction of cerebral arteries via a common pathway. Advances in Drug and Alcohol Research, 6, Article 16302. https://doi.org/10.3389/adar.2026.16302

Image Credits: AI Generated

DOI: 10.3389/adar.2026.16302

Keywords: binge drinking, cerebral arteries, BK channels, cholesterol, docosahexaenoic acid, omega-3, vascular smooth muscle, alcohol, sex differences, ion channels, cerebrovascular dysfunction, slo1 subunit