Proceedings of the National Academy of Sciences

Cyanobacteria are leading biomass producers of the ocean whose ecological success relies on their ability to respond to dynamic availability of nutrients like CO2 and nitrogen, which require distinct adaptive mechanisms. To survive nitrogen deprivation, cyanobacteria undergo a reversible transition to a dormant mode. Under low CO2 levels, a CO2 concentrating mechanism (CCM) supports their CO2 fixation. While the CCM and nitrogen assimilation have been shown to share some regulatory pathways, how the CCM impacts the response to nitrogen deprivation remains underexplored. In this study, by using mutants of the coastal cyanobacteria Synechococcus sp. PCC 7002 lacking a CCM component, we show that the high rate of carbon fixation mediated by the CCM tunes the speed of the nitrogen deprivation response in {beta}-cyanobacteria. We first show that CCM mutants are deficient in inducing their typical nitrogen deprivation response under atmospheric CO2. However, at higher CO2 concentrations, the CCM mutants induce the nitrogen deprivation response. By combining Rubisco kinetics modeling with measurement of the response speed to nitrogen in various CO2 concentrations, we show that the speed of the nitrogen deprivation response increases linearly with Rubiscos carboxylation rate. We further reveal that the regulation of nitrogen response by the CCM is also present in the distantly related freshwater cyanobacteria Synechococcus elongatus PCC 7942, suggesting a widespread role of this regulation across {beta}-cyanobacteria. This study demonstrates that CO2 fixation by the cyanobacterial CCM is a key regulator of the nitrogen deprivation response, favoring a rapid response to dynamic environments.

Individual differences in cognitive abilities have been linked to variability in cortical folding, a stable neuroanatomical scaffold largely established in utero. In the domain of reading, recent findings in small groups of typical readers suggest that a sulcal interruption (superficial annectant gyrus, gyral gap) in the left posterior occipital temporal sulcus (lhpOTS) predicts better reading skills, posing the lhpOTS as a potential early biomarker of reading difficulties. However, it remains unknown whether this relationship found in typical readers generalizes to the dyslexic population and whether the lhpOTS can serve as a biomarker for dyslexia or predict response to targeted instruction.To fill these gaps, we examine the patterns of the lhpOTS in 209 children, including children with dyslexia, from four independently-collected samples. In typical readers, we find that the relationship between the lhpOTS and reading skills is robust, replicating across binary and continuous quantifications of the sulcal interruption. However, lhpOTS patterns neither distinguish dyslexic children from typical readers nor do they predict response to intervention. Instead, targeted reading intervention drives long-term gains in reading skills that are equivalent irrespective of VOTC anatomy. Together, these findings distinguish neuroanatomical correlates of skilled reading from determinants of reading impairment and learning capacity and emphasize the importance of the educational environment in supporting reading acquisition for children with dyslexia. SIGNIFICANCE STATEMENTEarly predictors of dyslexia are important for understanding the etiology of reading difficulties and informing early intervention. One candidate biomarker for dyslexia is the left posterior occipital temporal sulcus (lhpOTS), a neuroanatomical feature established before birth. In typical readers, the presence of an interruption in the lhpOTS has been linked to better reading skills. Here, we examine this neuroanatomical feature in 209 children with and without dyslexia. While the lhpOTS reliably relates to reading skill in typical readers, it neither differentiates dyslexic from typical readers nor predicts response to intensive reading intervention. These results show that brain anatomy reflects reading proficiency but does not constrain learning and highlights the power of targeted intervention to support reading development.

Aging is characterized by progressive functional decline, yet why such decline is observed broadly across living systems remains unclear. While molecular and cellular mechanisms describe how aging progresses, they do not explain why functional decline should arise as a natural consequence of living organization. Here, we show that aging naturally emerges from three general features of life: unavoidable damage, turnover-mediated maintenance, and the energetic constraint of turnover. We develop a hierarchical damage-turnover model in which component-level damage and energetically constrained turnover jointly determine whole-system performance. In the model, damage stochastically converts functional components into non-functional components, whereas turnover restores component performance at a rate coupled to whole-system performance. Analytical and Monte Carlo analyses reveal two regimes: a non-aging regime, in which performance remains finite, and an aging regime, in which performance progressively collapses toward zero. Performance-independent turnover always maintains a positive steady state, whereas performance-dependent turnover generates irreversible decline when reduced performance weakens maintenance capacity. Stochastic fluctuations further promote collapse near the transition boundary, even when deterministic analysis predicts a nonzero steady state. These results indicate that unavoidable damage and energetically constrained turnover are sufficient to generate aging-like decline, providing a minimal theoretical explanation for long-term irreversibility in biological systems.

Methyl-coenzyme M reductase (MCR) is the primary source of biogenic methane on Earth. In the active site of MCR, a nickel (Ni)-containing porphyrin (F430) must be in the Ni1+ oxidation state to initiate catalysis. The reductive activation of MCR, i.e., reduction of F430 to its Ni1+ state, is an ATP-dependent process, but the underlying ATPase and its precise role remain unknown. Component A2 is an ATP-binding protein that associates with MCR but, since it was reported to lack ATPase activity, its putative function was designated as an ATP-carrier protein. In contrast, recent structural insights into the MCR activation complex suggest that component A2 might hydrolyze ATP to drive conformational changes required for enzyme activation. Here, we provide direct biochemical evidence that component A2 is a bona fide ATPase that hydrolyzes ATP under strictly anaerobic conditions and only upon interaction with MCR. Mutational analyses reveal that component A2 must be bound to ATP prior to association with MCR and that residues involved in ATP hydrolysis do not impact protein-protein interaction. The two nucleotide-binding domains of A2 act cooperatively but display asymmetric contributions to ATP hydrolysis and MCR engagement. In addition, a distinctive N-terminal zinc-binding motif (ZBM) is required for maximal ATPase activity but is dispensable for MCR binding. Phylogenetic analyses reveal that this ZBM distinguishes component A2 from related ABC-type ATPases. Together, these findings identify component A2 as a distinct class of remodeling ATPases that powers conformational changes underlying the reductive activation of MCR. Significance StatementA large fraction of methane on Earth is generated by methanogenic archaea using the enzyme methyl coenzyme-M reductase (MCR). The maturation of MCR is a multi-step ATP-dependent process but the role of ATP and the corresponding ATPase(s) have remained unclear. Here, we show that component A2, a protein that is universally conserved in archaea that encode MCR and related enzymes, hydrolyzes ATP only upon interaction with MCR under anaerobic conditions. Our findings, together with recent structural studies, indicate that component A2-mediated ATP hydrolysis facilitates the reductive activation of MCR during the final step of its maturation. These results clarify a key step in the biogenesis of a central enzyme involved in biological methane production.

A novel class of protein misfolding, involving changes in entanglement status, occurs across the cytosolic proteome of a bacterium and likely occurs in many other organisms. Here, we examine if this class of misfolding has measurable downstream consequences for protein homeostasis. Specifically, we test the hypothesis that proteins that misfold in this way are more likely to be degraded by the ubiquitin-proteosome system immediately after synthesis. We do this by cross-referencing protein structural information with ubiquitin mass spectrometry (Ubq-MS) data from human fibroblast cells. Ubq-MS identifies proteins that have been covalently modified with ubiquitin in a particular pattern and is a cellular signal for that protein to be degraded by the proteosome. We find that nascent proteins with native entanglements, which were previously shown to be twice as likely to misfold, are 93% (95% Confidence Interval: [44%, 160%]) more likely to be tagged with ubiquitin and targeted to the proteasome compared to proteins that do not contain such entanglements. Simulating the folding of these proteins using a coarse-grained model, we find that the ubiquitin-tagged proteins containing native entanglements are four times more likely to misfold than the non-ubiquitinated proteins that are devoid of entanglements. These results indicate that entanglement misfolding, primarily involving a failure to form native entanglements, leads to an increased likelihood that those proteins will be degraded in human cells. Finally, we estimate that approximately one-third of the globular proteome likely misfolds in this way but bypasses proteasomal degradation because their misfolded states are structurally similar to their native ensemble. These consequences for protein degradation are likely common across organisms as entanglement misfolding is inherent to the polymeric nature of proteins.

1.Space weather exerts profound effects on Earths technological systems, yet its influence on the terrestrial biosphere remains largely unexplored at the global scale. Despite decades of research on solar-terrestrial interactions, most studies have focused on technological and atmospheric effects, while potential influences on biological regulation remain largely unexplored. While local experiments suggest magnetic sensitivity in plants (Galland and Pazur 2005; Belyavskaya 2004), observational evidence for a planetary-scale vegetative response to geomagnetic disturbances is lacking. In particular, it is unclear whether weak and intermittent geomagnetic disturbances can leave detectable signatures in ecosystem-scale physiological processes. Here, we analyze a decade of satellite-derived solar-induced chlorophyll fluorescence (SIF) data alongside geomagnetic indices to isolate non-seasonal physiological anomalies. Using temperature-stratified cumulative correlation analysis and multivariate models controlling for radiative and hydrological drivers, we identify a robust, cumulative, and thermally gated association between geomagnetic activity and vegetation fluorescence. We report a global-scale coherent modulation of photosystem balance, potentially inferred from the SIF757/SIF771 ratio, with recurrent geomagnetic disturbances, exhibiting maximal coherence under cold and moderate thermal conditions and weakening under Optimum and Warm Stress regimes. This response intensifies with increasing integration window length, indicating progressive physiological integration of repeated perturbations. Comparative analyses demonstrate that geomagnetic forcing is frequently comparable to or exceeds major climatic drivers in explaining fluorescence variability within biologically active regimes. We propose a mechanism consistent with magnetic modulation of radical pair spin dynamics in iron-sulfur clusters and cryptochromes, potentially influencing reactive oxygen species generation and redox-regulatory adaptation. Our findings suggest that plants have evolutionarily co-opted geomagnetic variability as an informational signal, integrating it into existing redox-regulatory networks. Rather than a passive mechanical perturbation, the observed response reflects an evolved sensitivity that operates near physiological criticality--a hypothesis that opens new frontiers in understanding magnetosphere-biosphere coupling.

Membrane association of intrinsically disordered proteins (IDPs) mediates various cellular functions including membrane remodeling and signal transduction. Whereas membrane association through amphipathic helices and polybasic motifs is well understood, sequence determinants for deep membrane insertion of aromatic residues are still poorly characterized. Here, we decipher the sequence code for membrane insertion of aromatic-centered motifs. For an initial set of 10 9-residue aromatic-centered sequences, all-atom molecular dynamics simulations and the positioning of proteins in membranes (PPM) method produced very similar membrane insertion propensities. Applying PPM to a full library of 1.2 x 106 sequences with an F, W, or Y residue flanked by L, R, G, N, or E at four positions on either side, we found that aliphatic (L) and basic (R) residues favor membrane insertion, whereas acidic (E) and polar (N) residues disfavor it. Guided by these rules, we developed a mathematical model dubbed AroMIP to predict the membrane insertion propensities of aromatic-centered motifs. AroMIP achieves 91.2%, 92.0%, and 99.7% accuracies for F-, W-, and Y-centered motifs, respectively, in disordered regions of the human proteome and is available as a web server at https://zhougroup-uic.github.io/AroMIP/. The present work provides the sequence basis and a mechanistic understanding of how IDPs employ aromatic-centered motifs to drive membrane insertion, and enriches the tools for the study of IDP-membrane association. Significance StatementMembrane insertion of short motifs, along with membrane tethering of amphipathic helices and membrane binding of polybasic motifs, is a major mode of membrane association and mediates diverse functions including membrane remodeling and signal transduction. Here we used three complementary approaches to decipher the sequence code of membrane insertion, culminating in a sequence-based method, AroMIP, for predicting membrane-insertion propensities. Aromatic sidechains have the intrinsic ability to insert deeply into the acyl chain region of membranes; at flanking positions, they strongly stabilize the inserted state. Aliphatic and basic residues are medium to modest promoters of membrane insertion. AroMIP has >90% accuracy and identifies important motifs for regulating functions of intrinsically disordered proteins via membrane insertion.

The ATP molecule is the universal energy currency across all living organisms. There are two fundamental pathways of ATP synthesis: substrate-level and oxidative phosphorylation. While substrate-level phosphorylation generates ATP directly, in oxidative phosphorylation, proton motive force (PMF) is required to power ATP synthesis via the F1Fo ATP synthase. Using Escherichia coli, we show that due to simultaneous use of both pathways, the strength of coupling between ATP and PMF strongly depends on growth conditions: coupling is weak when requirements for independent generation of ATP and PMF are met, and becomes essential when not. We determine the conditions, under which PMF-ATP coupling becomes essential and show that PMF is required for bacterial growth irrespective of its ATP synthesis function. We propose that the main role of F1Fo in Escherichia coli, contrary to the canonical view, is not to generate ATP but to provide an auxiliary pathway that allows both, ATP and PMF, to be produced.

How the human brain organizes complex cognitive functions remains unresolved, particularly regarding the debate between localized and distributed architectures. Here, we show that the language network undergoes a non-linear developmental reorganization that reconciles these views. Using multimodal neuroimaging and behavioral measures, we identify a three-stage trajectory: early localization, a transiently distributed state during adolescence marked by a connectivity dip, and a return to refined localization in adulthood. This adolescent dip is behaviorally meaningful and contributes to integrative network architecture. Convergent shifts in functional connectivity and brain-behavior relationships identify adolescence as a critical window for large-scale network remodeling. Our findings provide a unifying framework for language network development and suggest that transient redistribution may represent a general principle of human brain maturation.

Epistasis makes the fitness effect of a mutation depend on the genetic background in which it occurs, thereby shaping the accessibility and reversibility of evolutionary trajectories. Along adaptive walks, this path-dependent epistasis can take distinct forms: contingency, when a mutation requires prior substitutions to be beneficial; entrenchment, when later substitutions make its reversion increasingly deleterious; and diminishing returns, when successive beneficial mutations reduce one anothers effects. Although these regimes have been documented experimentally, the conditions under which each predominates remain poorly understood. Here we use Fishers geometric model to derive a general framework for path-dependent epistasis under stabilizing selection on a multidimensional phenotype. We show that epistasis between substitutions has a simple geometric interpretation: contingency and entrenchment arise when the collateral effects of mutations, orthogonal to the direction of the optimum, are compensated by the preceding or subsequent adaptive path, whereas diminishing returns arise when successive substitutions remain strongly aligned with the same direction of selection. Analytical results and simulations reveal a transition controlled by a single composite parameter combining phenotypic complexity, mutation size, and distance to the optimum. Far from the optimum, adaptive walks are dominated by diminishing returns epistasis. As populations approach the optimum, or as phenotypic complexity increases, antagonistic pleiotropy generates systematic contingency and entrenchment. At mutation-selection-drift equilibrium, these effects become strong, rapidly established, and increase with phenotypic complexity. These results show that contingency and entrenchment do not require specific molecular interactions between residues: they emerge generically from nonspecific epistasis produced by stabilizing selection on pleiotropic traits. Fishers geometric model thus unifies diminishing returns, contingency, and entrenchment as distinct regimes of the same underlying geometry of adaptation.

A recently discovered class of protein misfolding involving native entanglements could be a widespread mechanism by which loss-of-function diseases arise. Here, we test that hypothesis by examining if there is any statistical association between proteins predisposed to misfold in this way and a database of gene-disease relationships. We find that globular proteins containing non-covalent lasso entanglements (NCLEs) in their native structure, which are more prone to misfolding, are 61% more likely to be associated with disease, 68% more likely to harbor pathogenic missense mutations, and their misfolding-prone entangled regions are 64% more likely to harbor pathogenic missense mutations. Protein refolding simulations indicate that these disease associated, natively entangled proteins are 2.5-times more likely to misfold than comparable non-disease proteins that lack native NCLEs. These results indicate that native entanglement misfolding, especially in the presence of missense mutations, have the potential to contribute to a wide variety of diseases. More broadly, these findings open an entirely new space of therapeutic targets in which drugs are designed to avoid these misfolded states and increase the amount of folded, functional protein.

Cetacean dorsal fins are traditionally regarded as vertical stabilizers for yaw and roll, yet marked variation in fin area and position suggests that this function is not universal. We combined computational fluid dynamics simulations of five cetacean species with comparative analyses of dorsal fin and flipper morphology across 81 species to test whether variation in dorsal fin morphology reflects the evolution of hydrodynamic stabilization. Yaw-destabilizing moments were dominated by the trunk regardless of flipper posture, whereas dorsal fins were generally too small and too close to the center of rotation to provide substantial static yaw restoration. In contrast, dorsal fins influenced roll stability in concert with extended anhedral flippers. Although dorsal fins were likely present in the common ancestor of extant cetaceans, strong dorsal fin-mediated roll stabilization was largely restricted to oceanic bite-feeding delphinids, in which rapid evolutionary enlargement of the dorsal fin and persistently extended anhedral flippers likely enhanced roll stability. In most other lineages, roll stability could be maintained by flipper posture alone despite small dorsal fins. These results recast the cetacean dorsal fin not as a universal stabilizer, but as a lineage-specific roll stabilizing structure whose function emerges through mechanical coupling with the flippers.

Cancer progression is increasingly understood as an evolutionary process shaped not only by competition but also by cooperative interactions including those mediated through diffusible "public goods" (PGs). Classical evolutionary game theory predicts that PG-producing (altruistic) subclones cannot invade well-mixed populations of non-producers, creating a paradox given their observed emergence in tumors. Here, we resolve this contradiction by combining stochastic spatial simulations with an analytically tractable Moran model to study the invasion dynamics of PG-producing cells in structured populations. Starting from a single producer cell, we explicitly model stochastic PG secretion, diffusion, binding/unbinding, and cell proliferation across biologically relevant parameter ranges. We demonstrate that spatial structure fundamentally alters invasion dynamics, enabling PG producers to invade and establish even when production incurs a fitness cost. Both numerical and analytical approaches converge on a key unifying parameter, a characteristic length scale{delta} , that captures the combined effects of diffusivity, binding kinetics, and degradation. This length scale determines the spatial extent of PG availability and thus the selective advantage of producers. We identify distinct regimes: when PGs are localized (small{delta} ), producers preferentially benefit and invasion is likely; when PGs are widely dispersed (large{delta} ), benefits are shared and invasion approaches neutrality or is suppressed by costs. Our results highlight that invasion of cooperative traits is governed by spatially mediated resource localization rather than intrinsic fitness alone. This framework provides a mechanistic basis for understanding the emergence of cooperative subclones in tumors and suggests that modulating biophysical transport properties of signaling molecules could influence tumor evolution, metastasis, and therapeutic resistance.

Conversation requires speakers to plan their responses while still listening to their partner, yet the neural dynamics supporting this overlap remain unclear. In particular, competing accounts differ on whether behaviourally relevant preparation emerges early during comprehension or only close to speech onset. Here, we recorded EEG from pairs of participants engaged in natural, face-to-face conversation and tested whether neural activity during listening predicts both when speakers begin their response (latency) and how long they speak (duration). Using event-related potentials, oscillatory analyses, and multivariate decoding, we show that pre-speech neural activity carries robust information about upcoming behaviour more than one second before articulation. The strongest and earliest effects tracked response duration, with sustained ERP components and alpha/beta power modulations predicting how long participants would speak, even after controlling for behavioural variables. In contrast, neural predictors of response latency were more temporally restricted and partly aligned with partner turn boundaries. Temporal generalisation analyses further revealed stable neural patterns linking early and late stages of preparation. Together, these findings indicate that conversational planning unfolds during listening and that early neural activity reflects the maintained specification of response extent, followed by later processes related to commitment and initiation. This supports a temporally structured account of turn taking in which preparation involves both early maintenance and late motor engagement.

It was long believed early mammals were nocturnal to avoid interactions with day-active dinosaurs. However, recent evidence indicates many dinosaurs were likely nocturnal, suggesting more complex coevolutionary dynamics prevailed. We simulated coevolution of sleep in a general predator/prey system, using a physiological model. We discovered temporal niche pursuit cycles across evolutionary timescales: prey repeatedly escaping into a novel temporal niche, with predators subsequently invading that niche. We characterized multiple oscillatory patterns for pursuit, involving distinct genetic and phenotypic mechanisms. A low-dimensional model recapitulated the dynamics of the physiological model. These findings reveal rich dynamical processes underlying selection of temporal niche.

Biological phase changes provoked by stress, such as vitrification or gel-sol transitions, enable many organisms, including extremotolerant tardigrades, to enter quiescent states and survive extreme environmental conditions. Protein-driven phase transitions are hypothesized to produce large-scale changes in intracellular viscosity, allowing tardigrades to survive extreme stresses such as desiccation. We report that the tardigrade Hypsibius exemplaris undergoes both large-scale and local increases in intracellular viscosity following exposure to anoxic and hyperosmotic stress. Such dramatic shifts in cellular viscosity would be expected to enhance cellular resilience to physical force. Indeed, we found that tardigrades can survive, behave normally, and reproduce after exposure to the highest simulated hypergravity (HG) achievable in an ultracentrifuge (one million times Earths gravity). In contrast, Caenorhabditis elegans, a similarly sized animal, does not survive these extreme forces owing to loss of cellular integrity. Remarkably, tardigrades frozen during exposure to extreme hypergravitational force show minimal disruption of fine cellular ultrastructure and little evidence of stratification of cellular components whose density varies by nearly a factor of two. Further, exposure to anoxia, hyperosmotic stress, and HG all result in a large increase in reactive oxygen species (ROS), which is required for survival under these extreme environments. Inhibition of NADPH oxidase (NOX) suppresses survival both to HG and hyperosmotic stress. Our findings suggest that intracellular viscosity changes in response to multiple extreme stresses may underlie the resilience of these animals to extraordinary physical stress, and that survival in or recovery from these states relies on ROS signaling via NADPH oxidase. Significance StatementTardigrades are renowned for surviving conditions that are lethal to nearly all other life forms. We reveal two mechanisms that support this resilience: intracellular viscosity changes and NADPH oxidase-mediated ROS signaling. Through direct assessment of the effects of altered cellular material properties, found that tardigrades are resilient to forces up to one million times Earths gravity, establishing them as the most hypergravity-resistant animal currently known.

Cytochrome bc1 is one of the key enzymes of biological energy-conserving systems. In its catalytic Q cycle, the central reaction is the oxidation of quinol (QH2), upon which electrons are directed to two separate cofactor chains. The molecular mechanism of this reaction remains elusive. The canonical model, assuming a sequence of reactions dictated by the equilibrium redox midpoint potentials of cofactors (the 2Fe2S cluster and heme bL), has recently been challenged by a new model of EB derived from quantum mechanical (QM) calculations - EMET (EMergent Electron Transfer) (https://doi.org/10.1021/acsomega.5c13233). These two models predict fundamentally different microstates of the enzyme in which semiquinone (SQ) is formed in the catalytic site (Q o) and also predict different lowest-energy configurations. Here, we test these predictions using EPR spectroscopy on highly concentrated preparations of isolated bacterial cytochrome bc1. We detect SQ spin-coupled to the reduced 2Fe2S cluster (2Fe2Sred), whose population markedly exceeds that of reduced heme bL and forms exclusively in sites containing oxidized heme. We also identify that the lowest-energy configuration corresponds to the state with reduced heme bH (adjacent to heme bL), oxidized heme bL and SQ-2Fe2Sred. These two features are precluded by the canonical model but are consistent with EMET. We conclude that EMET, unlike the canonical EB model, satisfactorily describes the occurrence of stochastic, spin-selective processes that result in electron stoichiometry among hemes b, the 2Fe2S cluster, and SQ at Qo that are observed spectroscopically.

Shenhar et al. (2026) report 50% "intrinsic" lifespan heritability after calibrating a one-component correlated-frailty survival model to Scandinavian twin lifespans. Their framework is mathematically coherent, but the intrinsic component is not identified if heritable, mortality-relevant extrinsic susceptibility is omitted at calibration. We show that one-component calibration absorbs omitted familial extrinsic structure into the intrinsic frailty scale parameter{sigma}{theta} , and that this variance absorption is visible through separate diagnostics (1) Variance absorption. Under misspecification,{sigma}{theta} is inflated by +22.1% (95% CI: 21.5-22.7%), corresponding to +49% inflation in [Formula]. Falconer h2 is downstream of calibration and inherits a +9.2 pp bias (95% CI: 8.7-9.7). The{sigma}{theta} inflation is model-general: +22% (GM), +18% (MGG), +14% (SR); any dependence summary that is strictly increasing in{sigma}{theta} inherits this inflation, so Falconer h2 is one affected downstream quantity among many (Corollary B3). (2) Structural fingerprint. In the joint twin survival surface S(t1, t2), misspecification produces systematic dependence errors (ISE 48x that of the recovery model). Conditional twin dependence is inflated at all ages, peaking at age 80 ({Delta}r = 0.048). (3) Specificity. The bias requires an omitted component that is both heritable and mortality-relevant. Three negative controls, a boundary check ({rho} = 0), and a two-component recovery refit ({sigma}{theta} restored to within -3.2%) establish specificity. ACE decomposition yields C {approx} 0 throughout: the omitted extrinsic component loads onto A (because it is shared 1.0/0.5 in MZ/DZ), so switching summary statistics does not restore identification. (4) Sensitivity and falsifiability. Over an empirically anchored regime ({sigma}{gamma} [isin] [0.30, 0.65],{rho} [isin] [0.20, 0.50]), Falconer bias ranges from +2.8 to +18.9 pp (mean 9 pp). If{rho} is sufficiently negative, the bias reverses sign in all three model families (Corollary B4). A full-likelihood robustness check shows that this upward pull is partly structural and partly estimator-specific: in the same misspecified one-component model, ML still inflates{sigma}{theta} (+3%), whereas matching only rMZ inflates it much more (+21%). These results do not resolve true intrinsic heritability but establish that Shenhars 50% estimate carries a structured, model-general upward bias originating in the fitted latent variance{sigma}{theta} .

Plant photosynthesis operates under naturally fluctuating light, yet its dynamic responses across timescales remain incompletely understood. Here, we apply sinusoidal light modulation as a controlled periodic input and analyze the response in the frequency domain, enabling quantitative system identification of photosynthetic dynamics. Using a minimal biochemical model of photosynthetic electron transport and regulation, we show that the system exhibits distinct dynamic regimes separated by a characteristic timescale of approximately 10 s. In the high-frequency domain, the response is governed by constitutive processes and reflects steady-state properties such as the plastoquinone redox state. In the low-frequency domain, regulatory feedback dominates, particularly non-photochemical quenching (NPQ), which modulates both the amplitude and phase of the response. For small-amplitude perturbations, the system behaves linearly and can be characterized using transfer functions and Bode plots. We show that key physiological parameters, including relaxation times and regulatory gains, can be extracted directly from frequency-response features such as phase maxima and gain transitions. In the nonlinear regime, large-amplitude oscillations generate higher-harmonic structure and alter time-averaged photosynthetic performance relative to constant illumination. We further introduce the concept of regulation fingerprints, defined as ratios of transfer functions between regulated and unregulated systems. These fingerprints reveal distinct spectral signatures of fast (PsbS-mediated) and slow (zeaxanthin-dependent) NPQ processes, enabling their quantitative separation. Together, these results establish frequency-domain analysis as a framework for probing and identifying the dynamic regulation of photosynthesis under fluctuating light, with direct applicability to non-invasive measurements in laboratory and field conditions.

The emergence of amino acids (AAs) and nucleobases (NBs) across meteorites, interstellar ices, and laboratory shock experiments presents a paradox: why do these specific molecular motifs--a minuscule subset of organic chemistrys combinatorial space--appear repeatedly across diverse environments, in the absence of biological selection? We identify a physical mechanism, prebiotic selection, which biases driven chemical systems toward configurations with high stationary probability p*(x) under sustained entropy flux. The bias is quantified by an information quasi-potential {Phi}I (x) = - ln p*(x), entering the overdamped Langevin dynamics O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD where {Sigma} is the local entropy production rate (Schnakenberg 1976). {Phi}I is defined self-consistently via the full non-equilibrium stationary density, avoiding the circularity of identifying it with a scalar potential. Two central theorems underlie the framework. Theorem 1 establishes that {nabla}{Sigma} and {nabla}{Phi}I are generically linearly independent off equilibrium, so the dynamics is genuinely two-field. Theorem 2 (structural constraints on single-field gradient dynamics) shows that single-field models on compact manifolds (i) produce yield curves that are at most unimodal under linear driving, and (ii) combine disjoint perturbations additively, giving superlinearity factor S = 1 + O(||{delta} V ||2). The observed superlinear synergy of Ferris et al. (1996) lies far outside this perturbative bound and therefore requires the two-field structure of EOM-IFF; the non-monotonic peak of Blank et al. (2001) is consistent with two-field dynamics and also with single-field dynamics in the unimodal-with-peak case of Theorem 2 part 1, so it does not by itself discriminate. From these results, we: (i) define a formal substrate-minimal criterion for prebiotic selection; (ii) show consistency with the non-monotonic shock-synthesis yield of Blank et al. (2001) (R2 = 0.885, peak at P* = 28.4 {+/-} 1.4 GPa); (iii) show consistency with the superlinear clay-catalysed RNA polymerisation of Ferris et al. (1996) (synergy factor S {approx} 5.75, robust under {+/-}1-nucleotide measurement uncertainty); and (iv) state two further falsifiable predictions awaiting dedicated experimental tests. Every lemma and theorem is accompanied by explicit assumptions, regime of validity, and regime of failure; the frameworks scope is what it claims, not more. Prebiotic selection is identified as a physical process distinct from and prior to biological selection, offering a unified account of chemical convergence in carbon-nitrogen chemistry under sustained entropy flux.