Allometric scaling of metabolic rate from molecules and mitochondria to cells and mammals

Metabolic scaling: exploring the relation between metabolic rate and body size

We present an alternative to the traditional classroom lecture on the topics of metabolic scaling, allometric relationships between metabolic rate (MR) and body size, and reasons for rejecting Rubner's surface "law," concepts that students have described as challenging, counterintuitive, and/or mathematical. In groups, students work with published data on MR and body size for species representing all five vertebrate groups. To support the exercise, we developed a worksheet that has students define the concept in their own words, compare different measures of MR, and evaluate plots of MR and mass-specific MR vs. body mass for both homeotherms and poikilotherms. Students also attempt to explain why selected species have exceptionally high or low MR values for their body sizes. Student feedback indicated that active learning is an effective way to learn the concepts of metabolic scaling and allometric relationships and that the opportunity to work in groups with real data stimulates interest and an appreciation for the importance of metabolic scaling to the understanding of animal physiology.NEW & NOTEWORTHY Here we describe a worksheet that we designed for a group exercise in which students study real data to learn about metabolic scaling in different groups of vertebrates, understand that metabolic rates are allometric functions of body size, and consider why physiologists now reject Rubner's surface "law." We used this exercise in a course in animal physiology in place of the traditional lecture approach to teaching the concept of metabolic scaling.

Does death drive the scaling of life?

The magnitude of many kinds of biological structures and processes scale with organismal size, often in regular ways that can be described by power functions. Traditionally, many of these "biological scaling" relationships have been explained based on internal geometric, physical, and energetic constraints according to universal natural laws, such as the "surface law" and "3/4-power law". However, during the last three decades it has become increasingly apparent that biological scaling relationships vary greatly in response to various external (environmental) factors. In this review, I propose and provide several lines of evidence supporting a new ecological perspective that I call the "mortality theory of ecology" (MorTE). According to this viewpoint, mortality imposes time limits on the growth, development, and reproduction of organisms. Accordingly, small, vulnerable organisms subject to high mortality due to predation and other environmental hazards have evolved faster, shorter lives than larger, more protected organisms. A MorTE also includes various corollary, size-related internal and external causative factors (e.g. intraspecific resource competition, geometric surface area to volume effects on resource supply/transport and the protection of internal tissues from environmental hazards, internal homeostatic regulatory systems, incidence of pathogens and parasites, etc.) that impact the scaling of life. A mortality-centred approach successfully predicts the ranges of body-mass scaling slopes observed for many kinds of biological and ecological traits. Furthermore, I argue that mortality rate should be considered the ultimate (evolutionary) driver of the scaling of life, that is expressed in the context of other proximate (functional) drivers such as information-based biological regulation and spatial (geometric) and energetic (metabolic) constraints.

The determination of leaf size on the basis of developmental traits

Mature leaf area (LA) is a showcase of diversity - varying enormously within and across species, and associated with the productivity and distribution of plants and ecosystems. Yet, it remains unclear how developmental processes determine variation in LA. We introduce a mathematical framework pinpointing the origin of variation in LA by quantifying six epidermal 'developmental traits': initial mean cell size and number (approximating values within the leaf primordium), and the maximum relative rates and durations of cell proliferation and expansion until leaf maturity. We analyzed a novel database of developmental trajectories of LA and epidermal anatomy, representing 12 eudicotyledonous species and 52 Arabidopsis experiments. Within and across species, mean primordium cell number and maximum relative cell proliferation rate were the strongest developmental determinants of LA. Trade-offs between developmental traits, consistent with evolutionary and metabolic scaling theory, strongly constrain LA variation. These include trade-offs between primordium cell number vs cell proliferation, primordium mean cell size vs cell expansion, and the durations vs maximum relative rates of cell proliferation and expansion. Mutant and wild-type comparisons showed these trade-offs have a genetic basis in Arabidopsis. Analyses of developmental traits underlying LA and its diversification highlight mechanisms for leaf evolution, and opportunities for breeding trait shifts.

All You Need to Know About Allometric Scaling: An Integrative Review on the Theoretical Basis, Empirical Evidence, and Application in Human Pharmacology

Scaling approaches are used to describe or predict clearance for paediatric or obese populations from normal-weight adult values. Theoretical allometry assumes the existence of a universal bodyweight-based scaling relationship. Although theoretical allometry is highly disputed, it is commonly applied in pharmacological data analyses and clinical practice. The aim of the current review is to (1) increase pharmacologists' understanding of theoretical allometry to better understand the (implicit) assumptions and (dis)advantages and (2) highlight important methodological considerations with the application of this methodology. Theoretical allometry originated in an empirical, and later debated, observation by Kleiber of a scaling exponent of 0.75 between basal metabolic rate and body mass of mammals. The mathematical framework of West, Brown, and Enquist provides one possible explanation for this value. To date, multiple key assumptions of this framework have been disputed or disproven, and an increasing body of evidence is emerging against the existence of one universal allometric exponent. The promise of ease and universality of use that comes with theoretical approaches may be the reason they are so strongly sought after and defended. However, ecologists have suggested that the theory should move from a 'Newtonian approach', in which physical explanations are sought for a universal law and variability is of minor importance, to a 'Darwinian approach', in which variability is considered of primary importance for which evolutionary explanations can be found. No scientific support was found for the application of allometry for within-species scaling, so the application of basal metabolic rate-based scaling principles to clearance scaling remains unsubstantiated. Recent insights from physiologically based modelling approaches emphasise the interplay between drugs with different properties and physiological variables that underlie drug clearance, which drives the variability in the allometric scaling exponent in the field of pharmacology. To deal with this variability, drug-specific or patient-specific adaptations to theoretical allometric scaling are proposed, that introduce empiric elements and reduce the universality of the theory. The use of allometric scaling with an exponent of 0.75 may hold empirical merit for paediatric populations, except for the youngest individuals (aged ≤ 5 years). Nevertheless, biological interpretations and extrapolation potential attributed to models based on 0.75 allometric scaling are theoretically unfounded, and merits of the empirical application of this function should, as for all models, always be supported by appropriate model validation procedures. In this respect, it is not the value of the allometric exponent but the description and prediction of individual clearance values and drug concentrations that are of primary interest.

Responses of juvenile blacklegged ticks (Acari: Ixodidae) to hosts of varying quality

Blacklegged ticks (Ixodes scapularis) are the most medically and economically important vectors in North America. Each of their 3 life stages requires a blood meal from one of many potential host species, during which they can acquire or transmit pathogens. Host species, however, vary tremendously in their quality for ticks, as measured by differences in feeding and molting success. There should be clear fitness benefits for ticks that preferentially feed upon high-quality hosts (e.g., white-footed mice, Peromyscus leucopus), or at least avoid feeding on very low-quality hosts (e.g., Virginia opossums, Didelphis virginiana). Indeed, laboratory experiments have found some evidence of host preferences in I. scapularis; but these involve presenting ticks with hosts simultaneously and measuring movement towards hosts on a horizontal plane. In nature, however, host-seeking ticks encounter hosts sequentially and their movements are principally in a vertical plane. Here, we present the results of a study in which we measured the vertical movements of host-seeking juvenile blacklegged ticks before and after a host (P. leucopus, Tamias striatus, Sciurus carolinensis, or D. virginiana) was present, and whether the strength of their responses varies with host quality. We found ticks did not measurably alter the speed of their vertical movement in the presence of any hosts, regardless of host quality. Both larvae and nymphs quested slightly higher in the presence of hosts, but this did not vary by host species. These results call into question the existence of active host preferences, at least in this stage of the host-seeking process.

Quantitative Systems Pharmacology Modeling in Immuno-Oncology: Hypothesis Testing, Dose Optimization, and Efficacy Prediction

Despite an increasing number of clinical trials, cancer is one of the leading causes of death worldwide in the past decade. Among all complex diseases, clinical trials in oncology have among the lowest success rates, in part due to the high intra- and inter-tumoral heterogeneity. There are more than a thousand cancer drugs and treatment combinations being investigated in ongoing clinical trials for various cancer subtypes, germline mutations, metastasis, etc. Particularly, treatments relying on the (re)activation of the immune system have become increasingly present in the clinical trial pipeline. However, the complexities of the immune response and cancer-immune interactions pose a challenge to the development of these therapies. Quantitative systems pharmacology (QSP), as a computational approach to predict tumor response to treatments of interest, can be used to conduct in silico clinical trials with virtual patients (and emergent use of digital twins) in place of real patients, thus lowering the time and cost of clinical trials. In line with improved mechanistic understanding of the human immune system and promising results from recent cancer immunotherapy, QSP models can play critical roles in model-informed drug development in immuno-oncology. In this chapter, we discuss how QSP models were designed to serve different study objectives, including hypothesis testing, dose optimization, and efficacy prediction, via case studies in immuno-oncology.

Inferring the metabolic rate of bone

The bone organ is poorly represented in comparative research on mammalian mass-specific metabolic rates. As a first order attempt to remedy this, from the literature we collected mass-specific metabolic rates for all major organs except for the bone organ, and by subtraction infer the rate for the bone organ. The scaling relationships are given of each whole-organ mass-specific metabolic rate and of the relationship between whole-organ metabolic rate and body mass. Scaling of the lung, adipose depot and bone organ with body mass is higher than would be expected by ¾ power scaling. We interpret the similar scalings of bone and the adipose depot in light of their evolved regulation of whole-body metabolism. We also briefly examine the supra-¾ power scaling of the lung as well as the independence of the mass-specific metabolic rate of the heart from body mass. The bone organ exhibits relatively high energy expenditure with increasing body size. The bone marrow and its medullary adipocyte store may be responsible for engendering the greater share of the bone organ's energetic cost.

Genotype × environment × management analysis to define allometric rules between leaves and stems in wheat

Allometric rules provide insights into structure-function relationships across species and scales and are commonly used in ecology. The fields of agronomy, plant phenotyping, and modeling also need simplifications such as those provided by allometric rules to reconcile data at different temporal and spatial levels (organs/canopy). This study explores the variations in relationships for wheat in terms of the distribution of crop green area between leaves and stems, and the allocation of above-ground biomass between leaves and stems during the vegetative period, using a large dataset covering different years, countries, genotypes, and management practices. The results showed that the relationship between leaf and stem area was linear, genotype-specific, and sensitive to radiation. The relationship between leaf and stem biomass depended on genotype and nitrogen fertilization. The mass per area, associating area and biomass for both leaf and stem, varied strongly by developmental stage and was significantly affected by environment and genotype. These allometric rules were evaluated and shown to have satisfactory performance, and their potential use is discussed with regard to current phenotyping techniques and plant/crop models. Our results enable the definition of models and minimum datasets required for characterizing diversity panels and making predictions in various genotype × environment × management contexts.

Constructing stability: optimal learning in noisy ecological niches

Organisms can learn in response to environmental inputs as well as actively modify their environments through niche construction on slower evolutionary time scales. How quickly should an organism respond to a changing environment, and when possible, should organisms adjust the time scale of environmental change? We formulate these questions using a model of learning costs that considers optimal time scales of both memory and environment. We derive a general, sublinear scaling law for optimal memory as a function of environmental persistence. This encapsulates a trade-off between remembering and forgetting. We place learning strategies within a niche construction dynamics in a game theoretic setting. Niche construction is found to reduce or stabilize environmental volatility when learned environmental resources can be monopolized. When learned resources are shared, niche destructors evolve to degrade the shared environment. We integrate these results into a metabolic scaling framework in order to derive learning strategies as a function of body size.

Endocrine gland size is proportional to its target tissue size

Endocrine glands secrete hormones into the circulation to target distant tissues and regulate their functions. The qualitative relationship between hormone-secreting organs and their target tissues is well established, but a quantitative approach is currently limited. Quantification is important, as it could allow us to study the endocrine system using engineering concepts of optimality and tradeoffs. In this study, we collected literature data on 24 human hormones secreted from dedicated endocrine cells. We find that the number of endocrine cells secreting a hormone is proportional to the number of its target cells. A single endocrine cell serves approximately 2,000 target cells, a relationship that spans 6 orders of magnitude of cell numbers. This suggests an economic principle of cells working near their maximal capacity, and glands that are no bigger than they need to be.

On the Dynamics of Mortality and the Ephemeral Nature of Mammalian Megafauna

AbstractEnergy flow through consumer-resource interactions is largely determined by body size. Allometric relationships govern the dynamics of populations by impacting rates of reproduction as well as alternative sources of mortality, which have differential impacts on smaller to larger organisms. Here we derive and investigate the timescales associated with four alternative sources of mortality for terrestrial mammals: mortality from starvation, mortality associated with aging, mortality from consumption by predators, and mortality introduced by anthropogenic subsidized harvest. The incorporation of these allometric relationships into a minimal consumer-resource model illuminates central constraints that may contribute to the structure of mammalian communities. Our framework reveals that while starvation largely impacts smaller-bodied species, the allometry of senescence is expected to be more difficult to observe. In contrast, external predation and subsidized harvest have greater impacts on the populations of larger-bodied species. Moreover, the inclusion of predation mortality reveals mass thresholds for mammalian herbivores, where dynamic instabilities may limit the feasibility of megafaunal populations. We show how these thresholds vary with alternative predator-prey mass relationships, which are not well understood within terrestrial systems. Finally, we use our framework to predict the harvest pressure required to induce mass-specific extinctions, which closely align with previous estimates of anthropogenic megafaunal exploitation in both paleontological and historical contexts. Together our results underscore the tenuous nature of megafaunal populations and how different sources of mortality may contribute to their ephemeral nature over evolutionary time.

Multi-scaling allometry in human development, mammalian morphology, and tree growth

Various animal and plant species exhibit allometric relationships among their respective traits, wherein one trait undergoes expansion as a power-law function of another due to constraints acting on growth processes. For instance, the acknowledged consensus posits that tree height scales with the two-thirds power of stem diameter. In the context of human development, it is posited that body weight scales with the second power of height. This prevalent allometric relationship derives its nomenclature from fitting two variables linearly within a logarithmic framework, thus giving rise to the term "power-law relationship." Here, we challenge the conventional assumption that a singular power-law equation adequately encapsulates the allometric relationship between any two traits. We strategically leverage quantile regression analysis to demonstrate that the scaling exponent characterizing this power-law relationship is contingent upon the centile within these traits' distributions. This observation fundamentally underscores the proposition that individuals occupying disparate segments of the distribution may employ distinct growth strategies, as indicated by distinct power-law exponents. We introduce the innovative concept of "multi-scale allometry" to encapsulate this newfound insight. Through a comprehensive reevaluation of (i) the height-weight relationship within a cohort comprising 7, 863, 520 Japanese children aged 5-17 years for which the age, sex, height, and weight were recorded as part of a national study, (ii) the stem-diameter-height and crown-radius-height relationships within an expansive sample of 498, 838 georeferenced and taxonomically standardized records of individual trees spanning diverse geographical locations, and (iii) the brain-size-body-size relationship within an extensive dataset encompassing 1, 552 mammalian species, we resolutely substantiate the viability of multi-scale allometric analysis. This empirical substantiation advocates a paradigm shift from uni-scaling to multi-scaling allometric modeling, thereby affording greater prominence to the inherent growth processes that underlie the morphological diversity evident throughout the living world.

Size matters in metabolic scaling: Critical role of the thermodynamic efficiency of ATP synthesis and its dependence on mitochondrial H+ leak across mammalian species

In this last article of the trilogy, the unified biothermokinetic theory of ATP synthesis developed in the previous two papers is applied to a major problem in comparative physiology, biochemistry, and ecology-that of metabolic scaling as a function of body mass across species. A clear distinction is made between intraspecific and interspecific relationships in energy metabolism, clearing up confusion that had existed from the very beginning since Kleiber first proposed his mouse-to-elephant rule almost a century ago. It is shown that the overall mass exponent of basal/standard metabolic rate in the allometric relationship [Formula: see text] is composed of two parts, one emerging from the relative intraspecific constancy of the slope (b), and the other (b') arising from the interspecific variation of the mass coefficient, a(M) with body size. Quantitative analysis is shown to reveal the hidden underlying relationship followed by the interspecific mass coefficient, a(M)=P0M0.10, and a universal value of P0=3.23 watts, W is derived from empirical data on mammals from mouse to cattle. The above relationship is shown to be understood only within an evolutionary biological context, and provides a physiological explanation for Cope's rule. The analysis also helps in fundamentally understanding how variability and a diversity of scaling exponents arises in allometric relations in biology and ecology. Next, a molecular-level understanding of the scaling of metabolism across mammalian species is shown to be obtained by consideration of the thermodynamic efficiency of ATP synthesis η, taking mitochondrial proton leak as a major determinant of basal metabolic rate in biosystems. An iterative solution is obtained by solving the mathematical equations of the biothermokinetic ATP theory, and the key thermodynamic parameters, e.g. the degree of coupling q, the operative P/O ratio, and the metabolic efficiency of ATP synthesis η are quantitatively evaluated for mammals from rat to cattle. Increases in η (by ∼15%) over a 2000-fold body size range from rat to cattle, primarily arising from an ∼3-fold decrease in the mitochondrial H+ leak rate are quantified by the unified ATP theory. Biochemical and mechanistic consequences for the interpretation of basal metabolism, and the various molecular implications arising are discussed in detail. The results are extended to maximum metabolic rate, and interpreted mathematically as a limiting case of the general ATP theory. The limitations of the analysis are pointed out. In sum, a comprehensive quantitative analysis based on the unified biothermokinetic theory of ATP synthesis is shown to solve a central problem in biology, physiology, and ecology on the scaling of energy metabolism with body size.

Thermodynamic analysis of energy coupling by determination of the Onsager phenomenological coefficients for a 3×3 system of coupled chemical reactions and transport in ATP synthesis and its mechanistic implications

The nonequilibrium coupled processes of oxidation and ATP synthesis in the fundamental process of oxidative phosphorylation (OXPHOS) are of vital importance in biosystems. These coupled chemical reaction and transport bioenergetic processes using the OXPHOS pathway meet >90% of the ATP demand in aerobic systems. On the basis of experimentally determined thermodynamic OXPHOS flux-force relationships and biochemical data for the ternary system of oxidation, ion transport, and ATP synthesis, the Onsager phenomenological coefficients have been computed, including an estimate of error. A new biothermokinetic theory of energy coupling has been formulated and on its basis the thermodynamic parameters, such as the overall degree of coupling, q and the phenomenological stoichiometry, Z of the coupled system have been evaluated. The amount of ATP produced per oxygen consumed, i.e. the actual, operating P/O ratio in the biosystem, the thermodynamic efficiency of the coupled reactions, η, and the Gibbs free energy dissipation, Φ have been calculated and shown to be in agreement with experimental data. At the concentration gradients of ADP and ATP prevailing under state 3 physiological conditions of OXPHOS that yield Vmax rates of ATP synthesis, a maximum in Φ of ∼0.5J(hmgprotein)-1, corresponding to a thermodynamic efficiency of ∼60% for oxidation on succinate, has been obtained. Novel mechanistic insights arising from the above have been discussed. This is the first report of a 3 × 3 system of coupled chemical reactions with transport in a biological context in which the phenomenological coefficients have been evaluated from experimental data.

Why animals can outrun robots

Animals are much better at running than robots. The difference in performance arises in the important dimensions of agility, range, and robustness. To understand the underlying causes for this performance gap, we compare natural and artificial technologies in the five subsystems critical for running: power, frame, actuation, sensing, and control. With few exceptions, engineering technologies meet or exceed the performance of their biological counterparts. We conclude that biology's advantage over engineering arises from better integration of subsystems, and we identify four fundamental obstacles that roboticists must overcome. Toward this goal, we highlight promising research directions that have outsized potential to help future running robots achieve animal-level performance.

Quantifying maternal investment in mammals using allometry

Maternal investment influences the survival and reproduction of both mothers and their progeny and plays a crucial role in understanding individuals' life-history and population ecology. To reveal the complex mechanisms associated with reproduction and investment, it is necessary to examine variations in maternal investment across species. Comparisons across species call for a standardised method to quantify maternal investment, which remained to be developed. This paper addresses this limitation by introducing the maternal investment metric - MI - for mammalian species, established through the allometric scaling of the litter mass at weaning age by the adult mass and investment duration (i.e. gestation + lactation duration) of a species. Using a database encompassing hundreds of mammalian species, we show that the metric is not highly sensitive to the regression method used to fit the allometric relationship or to the proxy used for adult body mass. The comparison of the maternal investment metric between mammalian subclasses and orders reveals strong differences across taxa. For example, our metric confirms that Eutheria have a higher maternal investment than Metatheria. We discuss how further research could use the maternal investment metric as a valuable tool to understand variation in reproductive strategies.

Unraveling power-law scaling through exponential cell division dynamics

A primary objective of biology is the development of universal laws that define how organic form develops and how it evolves as a function of size, both ontogenetically and across evolutionary time. Scaling theory has been essential in reaching this goal by giving a complete perspective point, particularly in illuminating the fundamental biological features produced within scaling exponents defining families of equations. Nonetheless, the theoretical basis of the allometric equation within scaling theory are inadequately explained, particularly when it comes to establishing links between micro-level processes at the cellular level and macro-level phenomena. We proposed an unlimited cell bipartition, resulting in an exponential growth in cell numbers during an individual's lifespan, to bridge this conceptual gap between cellular processes and allometric scaling. The power-law scaling between body mass and organ weight was produced by the synchronous exponential increments and the allometric exponent is rate of logarithmic cell proliferation rate. Substituting organ weight for erythrocyte weight aided in the development of a power-law scaling relationship between body mass and metabolic rate. Furthermore, it is critical to understand how cell size affects the exponent in power-law scaling. We find that a bigger exponent will result from an increase in the average weight of organ cells or a decrease in the average weight of all cells. Furthermore, cell proliferation dynamics showed a complex exponential scaling between body mass and longevity, defying the previously reported power-law scaling. We discovered a quadratic link between longevity and logarithmic body mass. Notably, all of the parameters included in these relationships are explained by indices linked to cell division and embryonic development. This research adds to our understanding of the complex interaction between cellular processes and overarching scaling phenomena in biology.

Pulmonary vasculature development in congenital diaphragmatic hernia: a novel automated quantitative imaging analysis

PURPOSE

Impaired fetal lung vasculature determines the degree of pulmonary hypertension in the congenital diaphragmatic hernia (CDH). This study aims to demonstrate the morphometric measurements that differ in pulmonary vessels of fetuses with CDH.

METHODS

Nitrofen-induced CDH Sprague-Dawley rat fetuses were scanned with microcomputed tomography. The analysis of the pulmonary vascular tree was performed with artificial intelligence.

RESULTS

The number of segments in CDH was significantly lower than that in the control group on the left (U = 2.5, p = 0.004) and right (U = 0, p = 0.001) sides for order 1(O1), whereas there was a significant difference only on the right side for O2 and O3. The pooled element numbers in the control group obeyed Horton's law (R2 = 0.996 left and R2 = 0.811 right lungs), while the CDH group broke it. Connectivity matrices showed that the average number of elements of O1 springing from elements of O1 on the left side and the number of elements of O1 springing from elements of O3 on the right side were significantly lower in CDH samples.

CONCLUSION

According to these findings, CDH not only reduced the amount of small order elements, but also destroyed the fractal structure of the pulmonary arterial trees.

Metabolic scaling as an emergent outcome of variation in metabolic rate

The allometric scaling of metabolic rate and what drives it are major questions in biology with a long history. Since the metabolic rate at any level of biological organization is an emergent property of its lower-level constituents, it is an outcome of the intrinsic heterogeneity among these units and the interactions among them. However, the influence of lower-level heterogeneity on system-level metabolic rate is difficult to investigate, given the tightly integrated body plan of unitary organisms. In this context, social insects such as honeybees can serve as important model systems because unlike unitary organisms, these superorganisms can be taken apart and reassembled in different configurations to study metabolic rate and its various drivers at different levels of organization. This commentary discusses the background of such an approach and how combining it with artificial selection to generate heterogeneity in metabolic rate with an analytical framework to parse out the different mechanisms that contribute to the effects of heterogeneity can contribute to the various models of metabolic scaling. Finally, the absence of the typical allometric scaling relationship among different species of honeybees is discussed as an important prospect for deciphering the role of top-down ecological factors on metabolic scaling. This article is part of the theme issue 'The evolutionary significance of variation in metabolic rates'.

Coupling and biological free-energy transduction processes as a bridge between physics and life: Molecular-level instantiation of Ervin Bauer's pioneering concepts in biological thermodynamics

The nonequilibrium coupled processes of oxidation and ATP synthesis in the biological process of oxidative phosphorylation (OXPHOS) are fundamental to all life on our planet. These steady-state energy transduction processes ‒ coupled by proton and anion/counter-cation concentration gradients in the OXPHOS pathway ‒ generate ∼95 % of the ATP requirement of aerobic systems for cellular function. The rapid energy cycling and homeostasis of metabolites involved in this coupling are shown to be responsible for maintenance and regulation of stable nonequilibrium states, the latter first postulated in pioneering biothermodynamics work by Ervin Bauer between 1920 and 1935. How exactly does this occur? This is shown to be answered by molecular considerations arising from Nath's torsional mechanism of ATP synthesis and two-ion theory of energy coupling developed in 25 years of research work on the subject. A fresh analysis of the biological thermodynamics of coupling that goes beyond the previous work of Stucki and others and shows how the system functions at the molecular level has been carried out. Thermodynamic parameters, such as the overall degree of coupling, q of the coupled system are evaluated for the state 4 to state 3 transition in animal mitochondria with succinate as substrate. The actual or operative P to O ratio, the efficiency of the coupled reactions, η, and the Gibbs energy dissipation, Φ have been calculated and shown to be in good agreement with experimental data. Novel mechanistic insights arising from the above have been discussed. A fourth law/principle of thermodynamics is formulated for a sub-class of physical and biological systems. The critical importance of constraints and time-varying boundary conditions for function and regulation is discussed in detail. Dynamic internal structural changes essential for torsional energy storage within the γ-subunit in a single molecule of the FOF1-ATP synthase and its transduction have been highlighted. These results provide a molecular-level instantiation of Ervin Bauer's pioneering concepts in biological thermodynamics.

DNA methylation rates scale with maximum lifespan across mammals

DNA methylation rates have previously been found to broadly correlate with maximum lifespan in mammals, yet no precise relationship has been observed. We developed a statistically robust framework to compare methylation rates at conserved age-related sites across mammals. We found that methylation rates negatively scale with maximum lifespan in both blood and skin. The emergence of explicit scaling suggests that methylation rates are, or are linked to, an evolutionary constraint on maximum lifespan acting across diverse mammalian lineages.

A Nonlinear Dynamical View of Kleiber's Law on the Metabolism of Plants and Animals

Kleiber's empirical law, which describes that metabolism increases as the mass to the power 3/4, has arguably remained life sciences' enigma since its formal uncovering in 1930. Why is this behavior sustained over many orders of magnitude? There have been quantitative rationalizations put forward for both plants and animals based on realistic mechanisms. However, universality in scaling laws of this kind, like in critical phenomena, has not yet received substantiation. Here, we provide an account, with quantitative reproduction of the available data, of the metabolism for these two biology kingdoms by means of broad arguments based on statistical mechanics and nonlinear dynamics. We consider iterated renormalization group (RG) fixed-point maps that are associated with an extensive generalized (Tsallis) entropy. We find two unique universality classes that satisfy the 3/4 power law. One corresponds to preferential attachment processes-rich gets richer-and the other to critical processes that suppress the effort for motion. We discuss and generalize our findings to other empirical laws that exhibit similar situations, using data based on general but different concepts that form a conjugate pair that gives rise to the same power-law exponents.

An energy costly architecture of neuromodulators for human brain evolution and cognition

In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

The Clockwork Embryo: Mechanisms Regulating Developmental Rate

Organismal development requires the reproducible unfolding of an ordered sequence of discrete steps (cell fate determination, migration, tissue folding, etc.) in both time and space. Here, we review the mechanisms that grant temporal specificity to developmental steps, including molecular clocks and timers. Individual timing mechanisms must be coordinated with each other to maintain the overall developmental sequence. However, phenotypic novelties can also arise through the modification of temporal patterns over the course of evolution. Two main types of variation in temporal patterning characterize interspecies differences in developmental time: allochrony, where the overall developmental sequence is either accelerated or slowed down while maintaining the relative duration of individual steps, and heterochrony, where the duration of specific developmental steps is altered relative to the rest. New advances in in vitro modeling of mammalian development using stem cells have recently enabled the revival of mechanistic studies of allochrony and heterochrony. In both cases, differences in the rate of basic cellular functions such as splicing, translation, protein degradation, and metabolism seem to underlie differences in developmental time. In the coming years, these studies should identify the genetic differences that drive divergence in developmental time between species.

How and Why Does Metabolism Scale with Body Mass?

Most explanations for the relationship between body size and metabolism invoke physical constraints; such explanations are evolutionarily inert, limiting their predictive capacity. Contemporary approaches to metabolic rate and life history lack the pluralism of foundational work. Here, we call for reforging of the lost links between optimization approaches and physiology.

Derived faunivores are the forerunners of major synapsid radiations

Evolutionary radiations generate most of Earth's biodiversity, but are there common ecomorphological traits among the progenitors of radiations? In Synapsida (the mammalian total group), 'small-bodied faunivore' has been hypothesized as the ancestral state of most major radiating clades, but this has not been quantitatively assessed across multiple radiations. To examine macroevolutionary patterns in a phylogenetic context, we generated a time-calibrated metaphylogeny ('metatree') comprising 1,888 synapsid species from the Carboniferous through the Eocene (305-34 Ma) based on 269 published character matrices. We used comparative methods to investigate body size and dietary evolution during successive synapsid radiations. Faunivory is the ancestral dietary regime of each major synapsid radiation, but relatively small body size is only established as the common ancestral state of radiations near the origin of Mammaliaformes in the Late Triassic. The faunivorous ancestors of synapsid radiations typically have numerous novel characters compared with their contemporaries, and these derived traits may have helped them to survive faunal turnover events and subsequently radiate.

Interspecies Scaling of Transgene Products for Viral Vector Gene Therapies: Method Assessment Using Data from Eleven Viral Vectors

The prediction of transgene product expression in human is important to guide first-in-human (FIH) dose selection for viral vector-based gene replacement therapies. Recently, allometric scaling from preclinical data and interspecies normalization of dose-response (D-R) relationship have been used to predict human transgene product expression of adeno-associated virus (AAV) vectors. In this study, we assessed two interspecies allometric scaling methods and two dose-response methods in predicting human transgene product expression of nine intravenously administered AAV vectors, one intramuscularly administered AAV vector, and one intravesical administered adenoviral vector. Among the four methods, normalized D-R method generated the highest prediction accuracy, with geometric mean fold error (GMFE) of 2.9 folds and 75% predictions within fivefold deviations of observed human transgene product levels. The vg/kg-based D-R method worked well for locally delivered vectors but substantially overpredicted human transgene product levels of some hemophilia A and B vectors. For both intravenously and locally administered vectors, the prediction accuracy of allometric scaling using body weight^-0.25 (AS by W^-0.25) was superior to allometric scaling using log(body weight) (AS by logW). This study successfully extended the use of allometric scaling and interspecies D-R normalization methods for human transgene product prediction from intravenous viral vectors to locally delivered viral vectors.

Single-nucleus transcriptome inventory of giant panda reveals cellular basis for fitness optimization under low metabolism

BACKGROUND

Energy homeostasis is essential for the adaptation of animals to their environment and some wild animals keep low metabolism adaptive to their low-nutrient dietary supply. Giant panda is such a typical low-metabolic mammal exhibiting species specialization of extremely low daily energy expenditure. It has low levels of basal metabolic rate, thyroid hormone, and physical activities, whereas the cellular bases of its low metabolic adaptation remain rarely explored.

RESULTS

In this study, we generate a single-nucleus transcriptome atlas of 21 organs/tissues from a female giant panda. We focused on the central metabolic organ (liver) and dissected cellular metabolic status by cross-species comparison. Adaptive expression mode (i.e., AMPK related) was prominently displayed in the hepatocyte of giant panda. In the highest energy-consuming organ, the heart, we found a possibly optimized utilization of fatty acid. Detailed cell subtype annotation of endothelial cells showed the uterine-specific deficiency of blood vascular subclasses, indicating a potential adaptation for a low reproductive energy expenditure.

CONCLUSIONS

Our findings shed light on the possible cellular basis and transcriptomic regulatory clues for the low metabolism in giant pandas and helped to understand physiological adaptation response to nutrient stress.

Chigger mite (Eutrombicula alfreddugesi) ectoparasitism does not contribute to sex differences in growth rate in eastern fence lizards (Sceloporus undulatus)

Parasitism is nearly ubiquitous in animals and is frequently associated with fitness costs in host organisms, including reduced growth, foraging, and reproduction. In many species, males tend to be more heavily parasitized than females and thus may bear greater costs of parasitism. Sceloporus undulatus is a female-larger, sexually size dimorphic lizard species that is heavily parasitized by chigger mites (Eutrombicula alfreddugesi). In particular, the intensity of mite parasitism is higher in male than in female juveniles during the period of time when sex differences in growth rate lead to the development of sexual size dimorphism (SSD). Sex-biased differences in fitness costs of parasitism have been documented in other species. We investigated whether there are growth costs of mite ectoparasitism, at a time coinciding with sex differences in growth rate and the onset of SSD. If there are sex-biased growth costs of parasitism, then this could suggest a contribution to the development of SSD in S. undulatus. We measured growth and mite loads in two cohorts of unmanipulated, field-active yearlings by conducting descriptive mark-recapture studies during the activity seasons of 2016 and 2019. Yearling males had consistently higher mid-summer mite loads and consistently lower growth rates than females. However, we found that growth rate and body condition were independent of mite load in both sexes. Furthermore, growth rates and mite loads were higher in 2019 than in 2016. Our findings suggest that juveniles of S. undulatus are highly tolerant of chigger mites and that any costs imposed by mites may be at the expense of functions other than growth. We conclude that sex-biased mite ectoparasitism does not contribute to sex differences in growth rate and, therefore, does not contribute to the development of SSD.

Scale in Language

A central concern of the cognitive science of language since its origins has been the concept of the linguistic system. Recent approaches to the system concept in language point to the exceedingly complex relations that hold between many kinds of interdependent systems, but it can be difficult to know how to proceed when "everything is connected." This paper offers a framework for tackling that challenge by identifying *scale* as a conceptual mooring for the interdisciplinary study of language systems. The paper begins by defining the scale concept-simply, the possibility for a measure to be larger or smaller in different instances of a system, such as a phonemic inventory, a word's frequency value in a corpus, or a speaker population. We review sites of scale difference in and across linguistic subsystems, drawing on findings from linguistic typology, grammatical description, morphosyntactic theory, psycholinguistics, computational corpus work, and social network demography. We consider possible explanations for scaling differences and constraints in language. We then turn to the question of *dependencies between* sites of scale difference in language, reviewing four sample domains of scale dependency: in phonological systems, across levels of grammatical structure (Menzerath's Law), in corpora (Zipf's Law and related issues), and in speaker population size. Finally, we consider the implications of the review, including the utility of a scale framework for generating new questions and inspiring methodological innovations and interdisciplinary collaborations in cognitive-scientific research on language.

Are size and mitochondrial power of cells inter-determined?

Mitochondria are the central hub of ATP production in most eukaryotic cells. Cellular power (energy per unit time), which is primarily generated in these organelles, is crucial to our understanding of cell function in health and disease. We investigated the relation between a mitochondrion's power (metabolic rate) and host cell size by combining metabolic theory with the analysis of two recent databases, one covering 109 protists and the other 63 species including protists, metazoans, microalgae, and vascular plants. We uncovered an interesting statistical regularity: in well-fed protists, relatively elevated values of mitochondrion power cluster around the smallest cell sizes and the medium-large cell sizes. In contrast, in starved protists and metazoans, the relation between mitochondrion power and cell size is inconclusive, and in microalgae and plants, mitochondrion power seems to increase from smaller cells to larger ones (where this investigation includes plant cells of volume up to ca. 2.18 × 105 μm3). Using these results, estimates are provided of the number of active ATP synthase molecules and basal uncouplers.

A sense of proximity: Cell packing modulates oxygen consumption

Accurately modeling oxygen transport and consumption is crucial to predict metabolic dynamics in cell cultures and optimize the design of tissue and organ models. We present a methodology to characterize the Michaelis-Menten oxygen consumption parameters in vitro, integrating novel experimental techniques and computational tools. The parameters were derived for hepatic cell cultures with different dimensionality (i.e., 2D and 3D) and with different surface and volumetric densities. To quantify cell packing regardless of the dimensionality of cultures, we devised an image-based metric, referred to as the proximity index. The Michaelis-Menten parameters were related to the proximity index through an uptake coefficient, analogous to a diffusion constant, enabling the quantitative analysis of oxygen dynamics across dimensions. Our results show that Michaelis-Menten parameters are not constant for a given cell type but change with dimensionality and cell density. The maximum consumption rate per cell decreases significantly with cell surface and volumetric density, while the Michaelis-Menten constant tends to increase. In addition, the dependency of the uptake coefficient on the proximity index suggests that the oxygen consumption rate of hepatic cells is superadaptive, as they modulate their oxygen utilization according to its local availability and to the proximity of other cells. We describe, for the first time, how cells consume oxygen as a function of cell proximity, through a quantitative index, which combines cell density and dimensionality. This study enhances our understanding of how cell-cell interaction affects oxygen dynamics and enables better prediction of aerobic metabolism in tissue models, improving their translational value.

Reservoir host immunology and life history shape virulence evolution in zoonotic viruses

The management of future pandemic risk requires a better understanding of the mechanisms that determine the virulence of emerging zoonotic viruses. Meta-analyses suggest that the virulence of emerging zoonoses is correlated with but not completely predictable from reservoir host phylogeny, indicating that specific characteristics of reservoir host immunology and life history may drive the evolution of viral traits responsible for cross-species virulence. In particular, bats host viruses that cause higher case fatality rates upon spillover to humans than those derived from any other mammal, a phenomenon that cannot be explained by phylogenetic distance alone. In order to disentangle the fundamental drivers of these patterns, we develop a nested modeling framework that highlights mechanisms that underpin the evolution of viral traits in reservoir hosts that cause virulence following cross-species emergence. We apply this framework to generate virulence predictions for viral zoonoses derived from diverse mammalian reservoirs, recapturing trends in virus-induced human mortality rates reported in the literature. Notably, our work offers a mechanistic hypothesis to explain the extreme virulence of bat-borne zoonoses and, more generally, demonstrates how key differences in reservoir host longevity, viral tolerance, and constitutive immunity impact the evolution of viral traits that cause virulence following spillover to humans. Our theoretical framework offers a series of testable questions and predictions designed to stimulate future work comparing cross-species virulence evolution in zoonotic viruses derived from diverse mammalian hosts.

Cellular allostatic load is linked to increased energy expenditure and accelerated biological aging

Stress triggers anticipatory physiological responses that promote survival, a phenomenon termed allostasis. However, the chronic activation of energy-dependent allostatic responses results in allostatic load, a dysregulated state that predicts functional decline, accelerates aging, and increases mortality in humans. The energetic cost and cellular basis for the damaging effects of allostatic load have not been defined. Here, by longitudinally profiling three unrelated primary human fibroblast lines across their lifespan, we find that chronic glucocorticoid exposure increases cellular energy expenditure by ∼60%, along with a metabolic shift from glycolysis to mitochondrial oxidative phosphorylation (OxPhos). This state of stress-induced hypermetabolism is linked to mtDNA instability, non-linearly affects age-related cytokines secretion, and accelerates cellular aging based on DNA methylation clocks, telomere shortening rate, and reduced lifespan. Pharmacologically normalizing OxPhos activity while further increasing energy expenditure exacerbates the accelerated aging phenotype, pointing to total energy expenditure as a potential driver of aging dynamics. Together, our findings define bioenergetic and multi-omic recalibrations of stress adaptation, underscoring increased energy expenditure and accelerated cellular aging as interrelated features of cellular allostatic load.

Knowledge-based mechanistic modeling accurately predicts disease progression with gefitinib in EGFR-mutant lung adenocarcinoma

Lung adenocarcinoma (LUAD) is associated with a low survival rate at advanced stages. Although the development of targeted therapies has improved outcomes in LUAD patients with identified and specific genetic alterations, such as activating mutations on the epidermal growth factor receptor gene (EGFR), the emergence of tumor resistance eventually occurs in all patients and this is driving the development of new therapies. In this paper, we present the In Silico EGFR-mutant LUAD (ISELA) model that links LUAD patients' individual characteristics, including tumor genetic heterogeneity, to tumor size evolution and tumor progression over time under first generation EGFR tyrosine kinase inhibitor gefitinib. This translational mechanistic model gathers extensive knowledge on LUAD and was calibrated on multiple scales, including in vitro, human tumor xenograft mouse and human, reproducing more than 90% of the experimental data identified. Moreover, with 98.5% coverage and 99.4% negative logrank tests, the model accurately reproduced the time to progression from the Lux-Lung 7 clinical trial, which was unused in calibration, thus supporting the model high predictive value. This knowledge-based mechanistic model could be a valuable tool in the development of new therapies targeting EGFR-mutant LUAD as a foundation for the generation of synthetic control arms.

Allometric scaling of metabolic rate and cardiorespiratory variables in aquatic and terrestrial mammals

While basal metabolic rate (BMR) scales proportionally with body mass (Mb ), it remains unclear whether the relationship differs between mammals from aquatic and terrestrial habitats. We hypothesized that differences in BMR allometry would be reflected in similar differences in scaling of O2 delivery pathways through the cardiorespiratory system. We performed a comparative analysis of BMR across 63 mammalian species (20 aquatic, 43 terrestrial) with a Mb range from 10 kg to 5318 kg. Our results revealed elevated BMRs in small (>10 kg and <100 kg) aquatic mammals compared to small terrestrial mammals. The results demonstrated that minute ventilation, that is, tidal volume (VT )·breathing frequency (fR ), as well as cardiac output, that is, stroke volume·heart rate, do not differ between the two habitats. We found that the "aquatic breathing strategy", characterized by higher VT and lower fR resulting in a more effective gas exchange, and by elevated blood hemoglobin concentrations resulting in a higher volume of O2 for the same volume of blood, supported elevated metabolic requirements in aquatic mammals. The results from this study provide a possible explanation of how differences in gas exchange may serve energy demands in aquatic versus terrestrial mammals.

Keep your cool: Overwintering physiology in response to urbanization in the acorn ant, Temnothorax curvispinosus

Winter presents a challenge for survival, yet temperate ectotherms have remarkable physiological adaptations to cope with low-temperature conditions. Under recent climate change, rather than strictly relaxing pressure on overwintering survival, warmer winters can instead disrupt these low-temperature trait-environment associations, with negative consequences for populations. While there is increasing evidence of physiological adaptation to contemporary warming during the growing season, the effects of winter warming on physiological traits are less clear. To address this knowledge gap, we performed a common garden experiment using relatively warm-adapted versus cold-adapted populations of the acorn ant, Temnothorax curvispinosus, sampled across an urban heat island gradient, to explore the effects of winter conditions on plasticity and evolution of physiological traits. We found no evidence of evolutionary divergence in chill coma recovery nor in metabolic rate at either of two test temperatures (4 and 10 °C). Although we found the expected plastic response of increased metabolic rate under the 10 °C acute test temperature as compared with the 4 °C test temperature, this plastic response, (i.e., the acute thermal sensitivity of metabolic rate), was not different across populations. Surprisingly, we found that winter-acclimated urban ant populations exhibited higher heat tolerance compared with rural ant populations, and that the magnitude of divergence was comparable to that observed among growing-season acclimated ants. Finally, we found no evidence of differences between populations with respect to changes in colony size from the beginning to the end of the overwintering experiment. Together, these findings indicate that despite the evolution of higher heat tolerance that is often accompanied by losses in low-temperature tolerance, urban acorn ants have retained several components of low-temperature physiological performance when assessed under ecologically relevant overwintering conditions. Our study suggests the importance of measuring physiological traits under seasonally-relevant conditions to understand the causes and consequences of evolutionary responses to contemporary warming.

Gene and protein expression and metabolic flux analysis reveals metabolic scaling in liver ex vivo and in vivo

Metabolic scaling, the inverse correlation of metabolic rates to body mass, has been appreciated for more than 80 years. Studies of metabolic scaling have largely been restricted to mathematical modeling of caloric intake and oxygen consumption, and mostly rely on computational modeling. The possibility that other metabolic processes scale with body size has not been comprehensively studied. To address this gap in knowledge, we employed a systems approach including transcriptomics, proteomics, and measurement of in vitro and in vivo metabolic fluxes. Gene expression in livers of five species spanning a 30,000-fold range in mass revealed differential expression according to body mass of genes related to cytosolic and mitochondrial metabolic processes, and to detoxication of oxidative damage. To determine whether flux through key metabolic pathways is ordered inversely to body size, we applied stable isotope tracer methodology to study multiple cellular compartments, tissues, and species. Comparing C57BL/6 J mice with Sprague-Dawley rats, we demonstrate that while ordering of metabolic fluxes is not observed in in vitro cell-autonomous settings, it is present in liver slices and in vivo. Together, these data reveal that metabolic scaling extends beyond oxygen consumption to other aspects of metabolism, and is regulated at the level of gene and protein expression, enzyme activity, and substrate supply.

Interspecies normalization of dose-response relationship for adeno-associated virus-mediated haemophilia gene therapy-Application to human dose prediction

AIMS

The aim of this study is to develop an approach to predict human dose-response relationship and first-in-human (FIH) dose for adeno-associated virus (AAV)-mediated haemophilia gene therapy.

METHODS

Preclinical dose-response relationships of 7 AAV vectors were normalized to a species-invariant scale using an exponent of 0.25, and the normalized dose-response relationship was then used for FIH dose prediction. The performance of this dose-response normalization approach for FIH dose prediction was compared to that of direct body weight-based dose (vg/kg) conversion and allometric scaling approaches.

RESULTS

A power regression analysis of normalized factor VIII (FVIII) or factor IX (FIX) showed a moderate-to-strong correlation between FVIII or FIX and vector dose across 3 species (R² ranged 0.59 to 0.89), indicating it was feasible to normalize dose-response in multiple species to a species-invariant scale. When the mean values of normalized FVIII or FIX at each dose level were used for regression, the R² values of the 7 vectors were improved to be >0.84. The FIH doses predicted by the 3 approaches were ranked as allometric scaling > dose-response normalization > direct vg/kg conversion for all vectors except for rAAV2-hAAT-FIX and scAAV2/8-LP1-hFIXco. Among the 7 vectors, dose-response normalization, direct vg/kg conversion and allometric scaling generated accurate FIH dose predictions for 2, 2 and 3 vectors, respectively.

CONCLUSION

This study first demonstrated that it is feasible to normalize dose-response relationship of AAV-mediated haemophilia gene therapy in multiple species to a species-invariant scale. The normalized dose-response relationship from preclinical species was successfully extrapolated to patients for FIH dose prediction.

Short- and long-term consequences of heat exposure on mitochondrial metabolism in zebra finches (Taeniopygia castanotis)

Understanding the consequences of heat exposure on mitochondrial function is crucial as mitochondria lie at the core of metabolic processes, also affecting population dynamics. In adults, mitochondrial metabolism varies with temperature but can also depend on thermal conditions experienced during development. We exposed zebra finches to two alternative heat treatments during early development: "constant", maintained birds at ambient 35 °C from parental pair formation to fledglings' independence, while "periodic" heated broods at 40 °C, 6 h daily at nestling stage. Two years later, we acclimated birds from both experiments at 25 °C for 21 days, before exposing them to artificial heat (40 °C, 5 h daily for 10 days). After both conditions, we measured red blood cells' mitochondrial metabolism using a high-resolution respirometer. We found significantly decreased mitochondrial metabolism for Routine, Oxidative Phosphorylation (OxPhos) and Electron Transport System maximum capacity (ETS) after the heat treatments. In addition, the birds exposed to "constant" heat in early life showed lower oxygen consumption at the Proton Leak (Leak) stage after the heat treatment as adults. Females showed higher mitochondrial respiration for Routine, ETS and Leak independent of the treatments, while this pattern was reversed for OxPhos coupling efficiency (OxCE). Our results show that short-term acclimation involved reduced mitochondrial respiration, and that the reaction of adult birds to heat depends on the intensity, pattern and duration of temperature conditions experienced at early-life stages. Our study provides insight into the complexity underlying variation in mitochondrial metabolism and raises questions on the adaptive value of long-lasting physiological adjustments triggered by the early-life thermal environment.

One-stop patient-specific myocardial blood flow quantification technique based on allometric scaling law

Establishing a patient-specific and non-invasive technique to derive blood flow as well as coronary structural information from one single cardiac CT imaging modality. 336 patients with chest pain or ST segment depression on electrocardiogram were retrospectively enrolled. All patients underwent adenosine-stressed dynamic CT myocardial perfusion imaging (CT-MPI) and coronary computed tomography angiography (CCTA) in sequence. Relationship between myocardial mass (M) and blood flow (Q), defined as log(Q) = b · log(M) + log(Q₀), was explored based on the general allometric scaling law. We used 267 patients to obtain the regression results and found strong linear relationship between M (gram) and Q (mL/min) (b = 0.786, log(Q₀) = 0.546, r = 0.704; p < 0.001). We Also found this correlation was applicable for patients with either normal or abnormal myocardial perfusion (p < 0.001). Datasets from the other 69 patients were used to validate this M-Q correlation and found the patient-specific blood flow could be accurately estimated from CCTA compared to that measured from CT-MPI (146.480 ± 39.607 vs 137.967 ± 36.227, r = 0.816, and 146.480 ± 39.607 vs 137.967 ± 36.227, r = 0.817, for the left ventricle region and LAD-subtended region, respectively, all unit in mL/min). In conclusion, we established a technique to provide general and patient-specific myocardial mass-blood flow correlation obeyed to allometric scaling law. Blood flow information could be directly derived from structural information acquired from CCTA.

First-in-Patient Dose Prediction for Adeno-Associated Virus-Mediated Hemophilia Gene Therapy Using Allometric Scaling

In this study, the author compared the performance of two allometric scaling approaches and body-weight-based dose conversion approach for first-in-patient (FIP) dose prediction for adeno-associated virus (AAV)-mediated hemophilia gene therapy using preclinical and clinical efficacy data of nine AAV vectors. In general, body-weight-based direct conversion of effective doses in monkeys or dogs was more likely to underestimate FIP dose but worked for one bioengineered vector with a high transduction efficiency specifically in humans. In contrast, allometric scaling between gene efficiency factor (log GEF) and body weight (log W) was likely to overestimate FIP dose but worked for two vectors with capsid-specific T-cell responses in patients. The third approach, allometric scaling between log GEF and W^-0.25 was appropriate for FIP dose prediction in the absence of T-cell responses to AAV vectors or a dramatic difference in vector transduction efficiency between animals and humans.

Systems biology of human aging: A Fibonacci time series model

Fractals are everywhere in nature, particularly at the interfaces where matter or energy must be transferred, since they maximize surface area while minimizing energy losses. Temporal fractals have been well studied at micro scales in human biology, but have received comparatively little attention at broader macro scales. In this paper, we describe a fractal time series model of human aging from a systems biology perspective. This model examines how intrinsic aging rates are shaped by entropy and Fibonacci fractal dynamics, with implications for the emergence of key life cycle traits. This proposition is supported by research findings. The finding of an intrinsic aging rate rooted in Fibonacci fractal dynamics represents a new predictive paradigm in evolutionary biology.

Evolutionary scaling of maximum growth rate with organism size

Data from nearly 1000 species reveal the upper bound to rates of biomass production achievable by natural selection across the Tree of Life. For heterotrophs, maximum growth rates scale positively with organism size in bacteria but negatively in eukaryotes, whereas for phototrophs, the scaling is negligible for cyanobacteria and weakly negative for eukaryotes. These results have significant implications for understanding the bioenergetic consequences of the transition from prokaryotes to eukaryotes, and of the expansion of some groups of the latter into multicellularity. The magnitudes of the scaling coefficients for eukaryotes are significantly lower than expected under any proposed physical-constraint model. Supported by genomic, bioenergetic, and population-genetic data and theory, an alternative hypothesis for the observed negative scaling in eukaryotes postulates that growth-diminishing mutations with small effects passively accumulate with increasing organism size as a consequence of associated increases in the power of random genetic drift. In contrast, conditional on the structural and functional features of ribosomes, natural selection has been able to promote bacteria with the fastest possible growth rates, implying minimal conflicts with both bioenergetic constraints and random genetic drift. If this extension of the drift-barrier hypothesis is correct, the interpretations of comparative studies of biological traits that have traditionally ignored differences in population-genetic environments will require revisiting.

Interspecies and in vitro-in vivo scaling for quantitative modeling of whole-body drug pharmacokinetics in patients: Application to the anticancer drug oxaliplatin

Quantitative systems pharmacology holds the promises of integrating results from laboratory animals or in vitro human systems into the design of human pharmacokinetic/pharmacodynamic (PK/PD) models allowing for precision and personalized medicine. However, reliable and general in vitro-to-in vivo extrapolation and interspecies scaling methods are still lacking. Here, we developed a translational strategy for the anticancer drug oxaliplatin. Using ex vivo PK data in the whole blood of the mouse, rat, and human, a model representing the amount of platinum (Pt) in the plasma and in the red blood cells was designed and could faithfully fit each dataset independently. A "purely physiologically-based (PB)" scaling approach solely based on preclinical data failed to reproduce human observations, which were then included in the calibration. Investigating approaches in which one parameter was set as species-specific, whereas the others were computed by PB scaling laws, we concluded that allowing the Pt binding rate to plasma proteins to be species-specific permitted to closely fit all data, and guaranteed parameter identifiability. Such a strategy presenting the drawback of including all clinical datasets, we further identified a minimal subset of human data ensuring accurate model calibration. Next, a "whole body" model of oxaliplatin human PK was inferred from the ex vivo study. Its three remaining parameters were estimated, using one third of the available patient data. Remarkably, the model achieved a good fit to the training dataset and successfully reproduced the unseen observations. Such validation endorsed the legitimacy of our scaling methodology calling for its testing with other drugs.

The energetic cost of allostasis and allostatic load

Chronic psychosocial stress increases disease risk and mortality, but the underlying mechanisms remain largely unclear. Here we outline an energy-based model for the transduction of chronic stress into disease over time. The energetic model of allostatic load (EMAL) emphasizes the energetic cost of allostasis and allostatic load, where the "load" is the additional energetic burden required to support allostasis and stress-induced energy needs. Living organisms have a limited capacity to consume energy. Overconsumption of energy by allostatic brain-body processes leads to hypermetabolism, defined as excess energy expenditure above the organism's optimum. In turn, hypermetabolism accelerates physiological decline in cells, laboratory animals, and humans, and may drive biological aging. Therefore, we propose that the transition from adaptive allostasis to maladaptive allostatic states, allostatic load, and allostatic overload arises when the added energetic cost of stress competes with longevity-promoting growth, maintenance, and repair. Mechanistically, the energetic restriction of growth, maintenance and repair processes leads to the progressive wear-and-tear of molecular and organ systems. The proposed model makes testable predictions around the physiological, cellular, and sub-cellular energetic mechanisms that transduce chronic stress into disease risk and mortality. We also highlight new avenues to quantify allostatic load and its link to health across the lifespan, via the integration of systemic and cellular energy expenditure measurements together with classic allostatic load biomarkers.

Sublinear scaling of the cellular proteome with ploidy

Ploidy changes are frequent in nature and contribute to evolution, functional specialization and tumorigenesis. Analysis of model organisms of different ploidies revealed that increased ploidy leads to an increase in cell and nuclear volume, reduced proliferation, metabolic changes, lower fitness, and increased genomic instability, but the underlying mechanisms remain poorly understood. To investigate how gene expression changes with cellular ploidy, we analyzed isogenic series of budding yeasts from 1N to 4N. We show that mRNA and protein abundance scales allometrically with ploidy, with tetraploid cells showing only threefold increase in protein abundance compared to haploids. This ploidy-dependent sublinear scaling occurs via decreased rRNA and ribosomal protein abundance and reduced translation. We demonstrate that the activity of Tor1 is reduced with increasing ploidy, which leads to diminished rRNA gene repression via a Tor1-Sch9-Tup1 signaling pathway. mTORC1 and S6K activity are also reduced in human tetraploid cells and the concomitant increase of the Tup1 homolog Tle1 downregulates the rDNA transcription. Our results suggest that the mTORC1-Sch9/S6K-Tup1/TLE1 pathway ensures proteome remodeling in response to increased ploidy.

Why isn’t each cell its own cell type? Diminishing returns of increasing cell type diversity can explain cell type allometry

Since the discovery of cells by Robert Hooke and Antoni van Leeuwenhoek in the 17th century, thousands of different cell types have been identified, most recently by sequencing-based single-cell profiling techniques. Yet, for many organisms we still do not know, how many different cell types they are precisely composed of. A recent survey of experimental data, using mostly morphology as a proxy for cell type, revealed allometric scaling of cell type diversity with organism size. Here, I argue from an evolutionary fitness perspective and suggest that three simple assumptions can explain the observed scaling: Evolving a new cell type has, 1. a fitness cost that increases with organism size, 2. a fitness benefit that also increases with organism size but 3. diminishes exponentially with the number of existing cell types. I will show that these assumptions result in a quantitative model that fits the observed cell type numbers across organisms of all size and explains why we should not expect isometric scaling.