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Abstract Bone marrow ablation prompts transient bone formation in nearly the entire medullary cavity before marrow regeneration occurs. Here, we establish a procedure to direct bone formation in a desired particular site within the medullary cavity for support of biomedical devices. Local intramedullary injury was performed in the tibiae of rats and parathyroid hormone (PTH), alendronate, or saline was administered. Newly generated bone in the medulla was assessed by micro-CT and histology. To evaluate the function of newly generated bone, animals received intramedullary injury in tibiae followed by daily PTH. At day-14, implants were placed in the endocortical bone and the bone response to the implants was assessed. The fate of newly generated bone was compared with and without implants. We found that neither intramedullary injury nor medication alone resulted in bone formation. However, when combined, substantial bone was generated locally inside the diaphyseal medulla. Newly formed bone disappeared without implant placement but was retained with implants. Bone was especially retained around and between the implants. This study found that local bone marrow disruption followed by PTH or alendronate generated substantial cancellous bone locally in the diaphyseal medulla. This approach offers promise as a tissue engineering tool in medicine and dentistry.

Long-latency reflexes (LLRs) are critical precursors to intricate postural coordination of muscular adaptations that sustain equilibrium following abrupt disturbances. Both disturbances and adaptive responses reflect excursions of postural control from quiescent Gaussian stability under a narrow bell curve, excursions beyond Gaussianity unfolding at many timescales. LLRs slow with age, accentuating the risk of falls and undermining dexterity, particularly in settings with concurrent additional tasks. We investigated whether the wobble board could cultivate the engagement of LLRs selectively in healthy young participants executing a suprapostural Trail Making Task (TMT). A concurrent additional-task demand constituted visual precision predominantly along the anteroposterior (AP) axis and mechanical instability mainly along the mediolateral (ML) axis. We scrutinized planar center-of-pressure (CoP) trajectories to quantify postural non-Gaussianity across various temporal scales. Wobble board increased engagement of LLRs and decreased engagement of compensatory postural adjustments (CPAs), indicated by the peak in non-Gaussianity of CoP planar displacements over LLR-specific timescales (50-100 ms) and non-Gaussianity of CoP planar displacements progressively diminishing over CPA-specific timescales ([Formula: see text] ms). Engagement with TMT did not show any noticeable influence on non-Gaussian postural sway patterns. Despite aligning the unstable axis of the wobble board with participants' ML axis, thus rendering posture more unstable along the ML axis, the wobble board increased engagement of LLRs significantly more along the AP axis and reduced engagement of CPAs significantly more along the ML axis. These findings offer initial mechanistic insights into how wobble boards may bolster balance and potentially reduce the occurrence of falls by catalyzing the engagement of LLRs selectively., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)

A rich and complex temporal structure of variability in postural sway characterizes healthy and adaptable postural control. However, neurodegenerative disorders such as Parkinson's disease, which often manifest as tremors, rigidity, and bradykinesia, disrupt this healthy variability. This study examined postural sway in young and older adults, including individuals with Parkinson's disease, under different upright standing conditions to investigate the potential connection between the temporal structure of variability in postural sway and Parkinsonism. A novel and innovative method called oriented fractal scaling component analysis was employed. This method involves decomposing the two-dimensional center of pressure (CoP) planar trajectories to pinpoint the directions associated with minimal and maximal temporal correlations in postural sway. As a result, it facilitates a comprehensive assessment of the directional characteristics within the temporal structure of sway variability. The results demonstrated that healthy young adults control posture along two orthogonal directions closely aligned with the traditional anatomical anteroposterior (AP) and mediolateral (ML) axes. In contrast, older adults and individuals with Parkinson's disease controlled posture along suborthogonal directions that significantly deviate from the AP and ML axes. These findings suggest that the altered temporal structure of sway variability is evident in individuals with Parkinson's disease and underlies postural deficits, surpassing what can be explained solely by the natural aging process., (© 2024. The Author(s).)

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard cut-off points and risk scores across populations hinges upon the assumption of such generalizability. Such generalizability, in turn, hinges upon this condition that the phenomenon investigated by current statistical methods is ergodic, i.e., its statistical measures converge over individuals and time within the finite limit of observations. However, emerging evidence indicates that biological processes abound with nonergodicity, threatening this generalizability. Here, we present a solution for how to make generalizable inferences by deriving ergodic descriptions of nonergodic phenomena. For this aim, we proposed capturing the origin of ergodicity-breaking in many biological processes: cascade dynamics. To assess our hypotheses, we embraced the challenge of identifying reliable biomarkers for heart disease and stroke, which, despite being the leading cause of death worldwide and decades of research, lacks reliable biomarkers and risk stratification tools. We showed that raw R-R interval data and its common descriptors based on mean and variance are nonergodic and non-specific. On the other hand, the cascade-dynamical descriptors, the Hurst exponent encoding linear temporal correlations, and multifractal nonlinearity encoding nonlinear interactions across scales described the nonergodic heart rate variability more ergodically and were specific. This study inaugurates applying the critical concept of ergodicity in discovering and applying digital biomarkers of health and disease., (© 2023. Springer Nature Limited.)

Contrast-associated acute kidney injury (CA-AKI) is a complication of percutaneous coronary intervention (PCI). Because proteinuria is a sentinel marker of renal dysfunction, we assessed its role in predicting CA-AKI in patients undergoing PCI. A total of 1,254 patients undergoing PCI were randomly assigned to a derivation (n = 840) and validation (n = 414) dataset. We identified the independent predictors of CA-AKI where CA-AKI was defined by the new criteria issued in 2020, by a multivariate logistic regression in the derivation dataset. We created a risk score from the remaining predictors. The discrimination and calibration of the risk score in the validation dataset were assessed by the area under the receiver-operating characteristic curves (AUC) and Hosmer-Lemeshow test, respectively. A total of 64 (5.1%) patients developed CA-AKI. The 3 variables of the risk score were emergency procedures, serum creatinine, and proteinuria, which were assigned 1 point each based on the correlation coefficient. The risk score demonstrated a good discriminative power (AUC 0.789, 95% CI 0.766-0.912) and significant calibration. It was strongly associated with the onset of CA-AKI (Cochran-Armitage test, p < 0.0001). Our risk score that included proteinuria was simple to obtain and calculate, and may be useful in assessing the CA-AKI risk before PCI., (© 2022. The Author(s).)

Fractal scaling in animal behavioral activity, where similar temporal patterns appear repeatedly over a series of magnifications among time scales, governs the complex behavior of various animal species and, in humans, can be altered by neurodegenerative diseases and aging. However, the mechanism underlying fractal scaling remains unknown. Here, we cultured C. elegans in a microfluidic device for 3 days and analyzed temporal patterns of C. elegans activity by fractal analyses. The residence-time distribution of C. elegans behaviors shared a common feature with those of human and mice. Specifically, the residence-time power-law distribution of the active state changed to an exponential-like decline at a longer time scale, whereas the inactive state followed a power-law distribution. An exponential-like decline appeared with nutrient supply in wild-type animals, whereas this decline disappeared in insulin-signaling-defective daf-2 and daf-16 mutants. The absolute value of the power-law exponent of the inactive state distribution increased with nutrient supply in wild-type animals, whereas the value decreased in daf-2 and daf-16 mutants. We conclude that insulin signaling differentially affects mechanisms that determine the residence time in active and inactive states in C. elegans behavior. In humans, diabetes mellitus, which is caused by defects in insulin signaling, is associated with mood disorders that affect daily behavioral activities. We hypothesize that comorbid behavioral defects in patients with diabetes may be attributed to altered fractal scaling of human behavior., (© 2022. The Author(s).)

We propose a novel class of mixed fluctuations with different orientations and fractal scaling features as a model for anisotropic two-dimensional (2D) trajectories hypothesized to appear in complex systems. Furthermore, we develop the oriented fractal scaling component analysis (OFSCA) to decompose such mixed fluctuations into the original orientation components. In the OFSCA, the original orientations are detected based on the principle that the original angles are orthogonal to the angles with the minimum and maximum scaling exponents of the mixed fluctuations. In our approach, the angle-dependent scaling properties are estimated using the Savitzky-Golay-filter-based detrended moving-average analysis (DMA), which has a higher detrending order than the conventional moving-average-filter-based DMA. To illustrate the OFSCA, we demonstrate that the numerically generated time-series of mixed fractional Gaussian noise (fGn) processes with non-orthogonal orientations and different scaling exponents is successfully decomposed into the original fGn components. We demonstrate the existence of oriented components in the 2D trajectories by applying OFSCA to real-world time-series, such as human postural fluctuations during standing and seismic ground acceleration during the great 2011 Tohoku-oki earthquake.

Fractal scaling is a common property of temporal change in various modes of animal behavior. The molecular mechanisms of fractal scaling in animal behaviors remain largely unexplored. The nematode C. elegans alternates between swimming and resting states in a liquid solution. Here, we report that C. elegans episodic swimming is characterized by scale-free kinetics with long-range temporal correlation and local temporal clusterization, namely consistent with multifractal kinetics. Residence times in actively-moving and inactive states were distributed in a power law-based scale-free manner. Multifractal analysis showed that temporal correlation and temporal clusterization were distinct between the actively-moving state and the inactive state. These results indicate that C. elegans episodic swimming is driven by transition between two behavioral states, in which each of two transition kinetics follows distinct multifractal kinetics. We found that a conserved behavioral modulator, cyclic GMP dependent kinase (PKG) may regulate the multifractal kinetics underlying an animal behavior. Our combinatorial analysis approach involving molecular genetics and kinetics provides a platform for the molecular dissection of the fractal nature of physiological and behavioral phenomena.

Many flatworms can alternate between asexual and sexual reproduction. This is a powerful reproductive strategy enabling them to benefit from the features of the two reproductive modes, namely, rapid multiplication and genetic shuffling. The two reproductive modes are enabled by the presence of pluripotent adult stem cells (neoblasts), by generating any type of tissue in the asexual mode, and producing and maintaining germ cells in the sexual mode. In the current study, RNA sequencing (RNA-seq) was used to compare the transcriptomes of two phenotypes of the planarian Dugesia ryukyuensis: an asexual OH strain and an experimentally sexualized OH strain. Pathway enrichment analysis revealed striking differences in amino acid metabolism in the two worm types. Further, the analysis identified serotonin as a new bioactive substance that induced the planarian ovary de novo in a postembryonic manner. These findings suggest that different metabolic states and physiological conditions evoked by sex-inducing substances likely modulate stem cell behavior, depending on their different function in the asexual and sexual reproductive modes. The combination of RNA-seq and a feeding assay in D. ryukyuensis is a powerful tool for studying the alternation of reproductive modes, disentangling the relationship between gene expression and chemical signaling molecules.