Neuromodulation effect of temporal interference stimulation based on network computational model.

Deep brain stimulation (DBS) has long been the conventional method for targeting deep brain structures, but noninvasive alternatives like transcranial Temporal Interference Stimulation (tTIS) are gaining traction. Research has shown that alternating current influences brain oscillations through neural modulation. Understanding how neurons respond to the stimulus envelope, particularly considering tTIS's high-frequency carrier, is vital for elucidating its mechanism of neuronal engagement. This study aims to explore the focal effects of tTIS across varying amplitudes and modulation depths in different brain regions. An excitatory-inhibitory network using the Izhikevich neuron model was employed to investigate responses to tTIS and compare them with transcranial Alternating Current Stimulation (tACS). We utilized a multi-scale model that integrates brain tissue modeling and network computational modeling to gain insights into the neuromodulatory effects of tTIS on the human brain. By analyzing the parametric space, we delved into phase, amplitude, and frequency entrainment to elucidate how tTIS modulates endogenous alpha oscillations. Our findings highlight a significant difference in current intensity requirements between tTIS and tACS, with tTIS requiring notably higher intensity. We observed distinct network entrainment patterns, primarily due to tTIS's high-frequency component, whereas tACS exhibited harmonic entrainment that tTIS lacked. Spatial resolution analysis of tTIS, conducted via computational modeling and brain field distribution at a 13 Hz stimulation frequency, revealed modulation in deep brain areas, with minimal effects on the surface. Notably, we observed increased power within intrinsic and stimulation bands beneath the electrodes, attributed to the high stimulus signal amplitude. Additionally, Phase Locking Value (PLV) showed slight increments in non-deep areas. Our analysis indicates focal stimulation using tTIS, prompting further investigation into the necessity of high amplitudes to significantly affect deep brain regions, which warrants validation through clinical experiments.

Nightmares in the elderly: Associations with self-reported executive functions.

STUDY OBJECTIVES: To describe nightmare phenomenology among community dwelling elderly and to test the hypothesis that reduction in cognitive control is associated with nightmare-related phenomenology including nightmare frequency and severity, greater emotional reactivity, imagery immersion, and dream enactment behaviors (DEBs). METHODS: Study 1: Survey with multiple regression and ANOVAs on N = 56 people with frequent nightmares plus N = 62 age- and gender-matched controls to quantify the strength of the association between cognitive control variables and nightmare phenomenology. Study 2: Computational simulation of nightmare phenomenology in relation to cognitive control to simulate the empirical findings and to assess the underlying causal theory through computationally supported causal inference. RESULTS: Study 1: Regressions demonstrated a strong association between reduction in cognitive control and more extreme nightmare phenomenology, including severity, frequency, daytime effects, and DEBs. Study 2: The computational simulation of nightmare phenomenology in relation to cognitive control is validated relative to regressions from study 1 and offers computational support for the causal theory explaining the associations in study 1. CONCLUSIONS: In aging people, decline in executive cognitive functions, cognitive control, and inhibitory processes reduce cognitive control over emotions, thus contributing to unusual nightmare activity, including more extreme nightmare phenomenology such as more severe nightmares, greater emotional reactivity, deeper imagery immersion, and DEBs.

A global mathematical model of climatic suitability for Plasmodium falciparum malaria.

Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control. Previous work has developed mathematical models and global maps for the suitability of temperature for malaria transmission. In this paper, existing temperature-based models are extended to include two other important bioclimatic factors: humidity and rainfall. This model is combined with fine spatial resolution climatic data to produce a more biologically-realistic global map of climatic suitability for Plasmodium falciparum malaria. The climatic suitability index developed corresponds more closely than previous temperature suitability indices with the global distribution of P. falciparum malaria. There is weak agreement between the Malaria Atlas Project estimates of P. falciparum prevalence in Africa and the estimates of suitability solely based on temperature (Spearman Correlation coefficient of ρ = 0.24 ). The addition of humidity and then rainfall improves the comparison ( ρ = 0.62 when humidity added; ρ = 0.70 when both humidity and rainfall added). By incorporating the impacts of humidity and rainfall, this model identifies arid regions that are not climatically suitable for transmission of P. falciparum malaria. Incorporation of this improved index of climatic suitability into geospatial models can improve global estimates of malaria prevalence and transmission intensity.

Ribosomal computing: implementation of the computational method.

BACKGROUND: Several computational and mathematical models of protein synthesis have been explored to accomplish the quantitative analysis of protein synthesis components and polysome structure. The effect of gene sequence (coding and non-coding region) in protein synthesis, mutation in gene sequence, and functional model of ribosome needs to be explored to investigate the relationship among protein synthesis components further. Ribosomal computing is implemented by imitating the functional property of protein synthesis. RESULT: In the proposed work, a general framework of ribosomal computing is demonstrated by developing a computational model to present the relationship between biological details of protein synthesis and computing principles. Here, mathematical abstractions are chosen carefully without probing into intricate chemical details of the micro-operations of protein synthesis for ease of understanding. This model demonstrates the cause and effect of ribosome stalling during protein synthesis and the relationship between functional protein and gene sequence. Moreover, it also reveals the computing nature of ribosome molecules and other protein synthesis components. The effect of gene mutation on protein synthesis is also explored in this model. CONCLUSION: The computational model for ribosomal computing is implemented in this work. The proposed model demonstrates the relationship among gene sequences and protein synthesis components. This model also helps to implement a simulation environment (a simulator) for generating protein chains from gene sequences and can spot the problem during protein synthesis. Thus, this simulator can identify a disease that can happen due to a protein synthesis problem and suggest precautions for it.

Late Acute Stress Effects on Decision-Making: The Magnified Attraction to Immediate Gains in the Iowa Gambling Task.

Previous literature indicates that the later phases of the acute stress response may promote poor decision-making, characterized by riskier choices and a likely inclination towards immediate reward-seeking. However, all studies addressing the effect of this phase have treated decisional capacity as a singular dimension, without analyzing the underlying processes under decision making. Employing the Value-Plus-Perseveration (VPP) RL model, based on Bayesian logic, this study aims to gain specific insights into how late phase of acute stress impacts the cognitive processes underpinning decision-making in the Iowa Gambling Task (IGT), deciphering whether, as expected, gains are processed in a magnified manner. Seventy-three participants were randomly assigned to two groups, stress (N = 35) and control (N = 38). A virtual version of The Trier Social Stress Test (TSST-VR) was employed as a laboratory stressor. Decision-making was evaluated 35minutes after the stressor onset, by means of the IGT. Results showed that stressed participants, in comparison to control group, displayed more perseverant and consistent decision-making, enhanced memory, and reinforcement learning capabilities, yet were guided by a greater attraction to decks offering immediate high gains. These results are analyzed with the understanding that in the IGT, short-term decisions focused on instant rewards are seen as counterproductive. This suggests that stress could limit the ability to switch to strategies that are more cautious and offer greater long-term benefits.

Synaptic weight dynamics underlying memory consolidation: Implications for learning rules, circuit organization, and circuit function.

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We provide two biologically plausible implementations for this reset that propose functional roles in stabilizing consolidation for core elements of the cerebellar circuit.

In silico data-based comparison of the accuracy and error source of various methods for noninvasively estimating central aortic blood pressure.

BACKGROUND AND OBJECTIVES: The higher clinical significance of central aortic blood pressure (CABP) compared to peripheral blood pressures has been extensively demonstrated. Accordingly, many methods for noninvasively estimating CABP have been proposed. However, there still lacks a systematic comparison of existing methods, especially in terms of how they differ in the ability to tolerate individual differences or measurement errors. The present study was designed to address this gap. METHODS: A large-scale 'virtual subject' dataset (n = 600) was created using a computational model of the cardiovascular system, and applied to examine several classical CABP estimation methods, including the direct method, generalized transfer function (GTF) method, n-point moving average (NPMA) method, second systolic pressure of periphery (SBP2) method, physical model-based wave analysis (MBWA) method, and suprasystolic cuff-based waveform reconstruction (SCWR) method. The errors of CABP estimation were analyzed and compared among methods with respect to the magnitude/distribution, correlations with physiological/hemodynamic factors, and sensitivities to noninvasive measurement errors. RESULTS: The errors of CABP estimation exhibited evident inter-method differences in terms of the mean and standard deviation (SD). Relatively, the estimation errors of the methods adopting pre-trained algorithms (i.e., the GTF and SCWR methods) were overall smaller and less sensitive to variations in physiological/hemodynamic conditions and random errors in noninvasive measurement of brachial arterial blood pressure (used for calibrating peripheral pulse wave). The performances of all the methods worsened following the introduction of random errors to peripheral pulse wave (used for deriving CABP), as characterized by the enlarged SD and/or increased mean of the estimation errors. Notably, the GTF and SCWR methods did not exhibit a better capability of tolerating pulse wave errors in comparison with other methods. CONCLUSIONS: Classical noninvasive methods for estimating CABP were found to differ considerably in both the accuracy and error source, which provided theoretical evidence for understanding the specific advantages and disadvantages of each method. Knowledge about the method-specific error source and sensitivities of errors to different physiological/hemodynamic factors may contribute as theoretical references for interpreting clinical observations and exploring factors underlying large estimation errors, or provide guidance for optimizing existing methods or developing new methods.

Improving glioma drug delivery: A multifaceted approach for glioma drug development.

Glioma is one of the most common central nervous system (CNS) cancers that can be found within the brain and the spinal cord. One of the pressing issues plaguing the development of therapeutics for glioma originates from the selective and semipermeable CNS membranes: the blood-brain barrier (BBB) and blood-spinal cord barrier (BSCB). It is difficult to bypass these membranes and target the desired cancerous tissue because the purpose of the BBB and BSCB is to filter toxins and foreign material from invading CNS spaces. There are currently four varieties of Food and Drug Administration (FDA)-approved drug treatment for glioma; yet these therapies have limitations including, but not limited to, relatively low transmission through the BBB/BSCB, despite pharmacokinetic characteristics that allow them to cross the barriers. Steps must be taken to improve the development of novel and repurposed glioma treatments through the consideration of pharmacological profiles and innovative drug delivery techniques. This review addresses current FDA-approved glioma treatments' gaps, shortcomings, and challenges. We then outline how incorporating computational BBB/BSCB models and innovative drug delivery mechanisms will help motivate clinical advancements in glioma drug delivery. Ultimately, considering these attributes will improve the process of novel and repurposed drug development in glioma and the efficacy of glioma treatment.

A multi-network model of Parkinson's disease tremor: exploring the finger-dimmer-switch theory and role of dopamine in thalamic self-inhibition.

Background. Tremor is a cardinal symptom of Parkinson's disease (PD) that manifests itself through complex oscillatory activity across multiple neuronal populations. According to the finger-dimmer-switch (FDS) theory, tremor is triggered by transient pathological activity in the basal ganglia-thalamo-cortical (BTC) network (the finger) and transitions into an oscillatory form within the inner circuitry of the thalamus (the switch). The cerebello-thalamo-cortical (CTC) network (the dimmer) is then involved in sustaining and amplifying tremor amplitude. In this study, we aimed to investigate the generation and progression dynamics of PD tremor oscillations by developing a comprehensive and interacting FDS model that transitions sequentially from healthy to PD to tremor and then to tremor-off state.Methods.We constructed a computational model consisting of 700 neurons in 11 regions of BTC, CTC, and thalamic networks. Transition from healthy to PD state was simulated through modulating dopaminergic synaptic connections; and further from PD to tremor and tremor-off by modulating projections between the thalamic reticular nucleus (TRN), anterior ventrolateral nucleus (VLa), and posterior ventrolateral nucleus (VLp).Results.Sustained oscillations in the frequency range of PD tremor emerged in thalamic VLp (5 Hz) and cerebellar dentate nucleus (3 Hz). Increasing self-inhibition in the thalamus through dopaminergic modulation significantly decreased tremor amplitude.Conclusion/Significance.Our results confirm the mechanistic power of the FDS theory in describing the PD tremor phenomenon and emphasize the role of dopaminergic modulation on thalamic self-inhibition. These insights pave the way for novel therapeutic strategies aimed at reducing the tremor by strengthening thalamic self-inhibition, particularly in dopamine-resistant patients.

Operation of spinal sensorimotor circuits controlling phase durations during tied-belt and split-belt locomotion after a lateral thoracic hemisection.

Locomotion is controlled by spinal circuits that interact with supraspinal drives and sensory feedback from the limbs. These sensorimotor interactions are disrupted following spinal cord injury. The thoracic lateral hemisection represents an experimental model of an incomplete spinal cord injury, where connections between the brain and spinal cord are abolished on one side of the cord. To investigate the effects of such an injury on the operation of the spinal locomotor network, we used our computational model of cat locomotion recently published in eLife (Rybak et al., 2024) to investigate and predict changes in cycle and phase durations following a thoracic lateral hemisection during treadmill locomotion in tied-belt (equal left-right speeds) and split-belt (unequal left-right speeds) conditions. In our simulations, the "hemisection" was always applied to the right side. Based on our model, we hypothesized that following hemisection, the contralesional ("intact", left) side of the spinal network is mostly controlled by supraspinal drives, whereas the ipsilesional ("hemisected", right) side is mostly controlled by somatosensory feedback. We then compared the simulated results with those obtained during experiments in adult cats before and after a mid-thoracic lateral hemisection on the right side in the same locomotor conditions. Our experimental results confirmed many effects of hemisection on cat locomotion predicted by our simulations. We show that having the ipsilesional hindlimb step on the slow belt, but not the fast belt, during split-belt locomotion substantially reduces the effects of lateral hemisection. The model provides explanations for changes in temporal characteristics of hindlimb locomotion following hemisection based on altered interactions between spinal circuits, supraspinal drives, and somatosensory feedback.

Computational account for the naturalness perception of others' jumping motion based on a vertical projectile motion model.

The visual naturalness of a rendered character's motion is an important factor in computer graphics work, and the rendering of jumping motions is no exception to this. However, the computational mechanism that underlies the observer's judgement of the naturalness of a jumping motion has not yet been fully elucidated. We hypothesized that observers would perceive a jumping motion as more natural when the jump trajectory was consistent with the trajectory of a vertical projectile motion based on Earth's gravity. We asked human participants to evaluate the naturalness of point-light jumping motions whose height and duration were modulated. The results showed that the observers' naturalness rating varied with the modulation ratios of the jump height and duration. Interestingly, the ratings were high even when the height and duration differed from the actual jump. To explain this tendency, we constructed computational models that predicted the theoretical trajectory of a jump based on the projectile motion formula and calculated the errors between the theoretical and observed trajectories. The pattern of the errors correlated closely with the participants' ratings. Our results suggest that observers judge the naturalness of observed jumping motion based on the error between observed and predicted jump trajectories.

A Subcortical Model for Auditory Forward Masking with Efferent Control of Cochlear Gain.

Previous physiological and psychophysical studies have explored whether feedback to the cochlea from the efferent system influences forward masking. The present work proposes that the limited growth-of-masking (GOM) observed in auditory nerve (AN) fibers may have been misunderstood; namely, that this limitation may be due to the influence of anesthesia on the efferent system. Building on the premise that the unanesthetized AN may exhibit GOM similar to more central nuclei, the present computational modeling study demonstrates that feedback from the medial olivocochlear (MOC) efferents may contribute to GOM observed physiologically in onset-type neurons in both the cochlear nucleus and inferior colliculus (IC). Additionally, the computational model of MOC efferents used here generates a decrease in masking with longer masker-signal delays similar to that observed in IC physiology and in psychophysical studies. An advantage of this explanation over alternative physiological explanations (e.g., that forward masking requires inhibition from the superior paraolivary nucleus) is that this theory can explain forward masking observed in the brainstem, early in the ascending pathway. For explaining psychoacoustic results, one strength of this model is that it can account for the lack of elevation in thresholds observed when masker level is randomly varied from interval-to-interval, a result that is difficult to explain using the conventional temporal window model of psychophysical forward masking. Future directions for evaluating the efferent mechanism as a contributing mechanism for psychoacoustic results are discussed.

A microscopic oxygen transport model for ultra-high dose rate radiotherapy in vivo: The impact of physiological conditions on FLASH effect.

BACKGROUND: Ultra-high dose rate irradiation (≥40 Gy/s, FLASH) has been shown to reduce normal tissue toxicity, while maintaining tumor control compared to conventional dose-rate radiotherapy. The radiolytic oxygen (O2) depletion (ROD) resulting from FLASH has been proposed to explain the normal tissue protection effect; however, in vivo experiments have not confirmed that FLASH induced global tissue hypoxia. Nonetheless, the experiments reported are based on volume-averaged measurement, which have inherent limitations in detecting microscopic phenomena, including the potential preservation of stem cells niches due to local FLASH-induced O2 depletion. Computational modeling offers a complementary approach to understand the ROD caused by FLASH at the microscopic level. PURPOSE: We developed a comprehensive model to describe the spatial and temporal dynamics of O2 consumption and transport in response to irradiation in vivo. The change of oxygen enhancement ratio (OER) was used to quantify and investigate the FLASH effect as a function of physiological and radiation parameters at microscopic scale. METHODS: We considered time-dependent O2 supply and consumption in a 3D cylindrical geometry, incorporating blood flow linking the O2 concentration ([O2]) in the capillary to that within the tissue through the Hill equation, radial and axial diffusion of O2, metabolic and zero-order radiolytic O2 consumption, and a pulsed radiation structure. Time-evolved distributions of [O2] were obtained by numerically solving perfusion-diffusion equations. The model enables the computation of dynamic O2 distribution and the relative change of OER (δROD) under various physiological and radiation conditions in vivo. RESULTS: Initial [O2] level and the subsequent changes during irradiation determined δROD distribution, which strongly depends on physiological parameters, i.e., intercapillary spacing, ultimately determining the tissue area with enhanced radioresistance. We observed that the δROD/FLASH effect is affected by and sensitive to the interplay effect among physiological and radiation parameters. It renders that the FLASH effect can be tissue environment dependent. The saturation of FLASH normal tissue protection upon dose and dose rate was shown. Beyond ∼60 Gy/s, no significant decrease in radiosensitivity within tissue region was observed. In turn, for a given dose rate, the change of radiosensitivity became saturated after a certain dose level. Pulse structures with the same dose and instantaneous dose rate but with different delivery times were shown to have distinguishable δROD thus tissue sparing, suggesting the average dose rate could be a metric assessing the FLASH effect and demonstrating the capability of our model to support experimental findings. CONCLUSION: On a macroscopic scale, the modeling results align with the experimental findings in terms of dose and dose rate thresholds, and it also indicates that pulse structure can vary the FLASH effect. At the microscopic level, this model enables us to examine the spatially resolved FLASH effect based on physiological and irradiation parameters. Our model thus provides a complementary approach to experimental methods for understanding the underlying mechanism of FLASH radiotherapy. Our results show that physiological conditions can potentially determine the FLASH efficacy in tissue protection. The FLASH effect may be observed under optimal combination of physiological parameters, not limited to radiation conditions alone.

Simulating combined monoaminergic depletions in a PD animal model through a bio-constrained differential equations system.

Introduction: Historically, Parkinson's Disease (PD) research has focused on the dysfunction of dopamine-producing cells in the substantia nigra pars compacta, which is linked to motor regulation in the basal ganglia. Therapies have mainly aimed at restoring dopamine (DA) levels, showing effectiveness but variable outcomes and side effects. Recent evidence indicates that PD complexity implicates disruptions in DA, noradrenaline (NA), and serotonin (5-HT) systems, which may underlie the variations in therapy effects. Methods: We present a system-level bio-constrained computational model that comprehensively investigates the dynamic interactions between these neurotransmitter systems. The model was designed to replicate experimental data demonstrating the impact of NA and 5-HT depletion in a PD animal model, providing insights into the causal relationships between basal ganglia regions and neuromodulator release areas. Results: The model successfully replicates experimental data and generates predictions regarding changes in unexplored brain regions, suggesting avenues for further investigation. It highlights the potential efficacy of alternative treatments targeting the locus coeruleus and dorsal raphe nucleus, though these preliminary findings require further validation. Sensitivity analysis identifies critical model parameters, offering insights into key factors influencing brain area activity. A stability analysis underscores the robustness of our mathematical formulation, bolstering the model validity. Discussion: Our holistic approach emphasizes that PD is a multifactorial disorder and opens promising avenues for early diagnostic tools that harness the intricate interactions among monoaminergic systems. Investigating NA and 5-HT systems alongside the DA system may yield more effective, subtype-specific therapies. The exploration of multisystem dysregulation in PD is poised to revolutionize our understanding and management of this complex neurodegenerative disorder.

(Mal)adaptive Mentalizing in the Cognitive Hierarchy, and Its Link to Paranoia.

Humans need to be on their toes when interacting with competitive others to avoid being taken advantage of. Too much caution out of context can, however, be detrimental and produce false beliefs of intended harm. Here, we offer a formal account of this phenomenon through the lens of Theory of Mind. We simulate agents of different depths of mentalizing within a simple game theoretic paradigm and show how, if aligned well, deep recursive mentalization gives rise to both successful deception as well as reasonable skepticism. However, we also show that if a self is mentalizing too deeply - hyper-mentalizing - false beliefs arise that a partner is trying to trick them maliciously, resulting in a material loss to the self. Importantly, we show that this is only true when hypermentalizing agents believe observed actions are generated intentionally. This theory offers a potential cognitive mechanism for suspiciousness, paranoia, and conspiratorial ideation. Rather than a deficit in Theory of Mind, paranoia may arise from the application of overly strategic thinking to ingenuous behaviour. Author Summary: Interacting competitively requires vigilance to avoid deception. However, excessive caution can have adverse effects, stemming from false beliefs of intentional harm. So far there is no formal cognitive account of what may cause this suspiciousness. Here we present an examination of this phenomenon through the lens of Theory of Mind - the cognitive ability to consider the beliefs, intentions, and desires of others. By simulating interacting computer agents we illustrate how well-aligned agents can give rise to successful deception and justified skepticism. Crucially, we also reveal that overly cautious agents develop false beliefs that an ingenuous partner is attempting malicious trickery, leading to tangible losses. As well as formally defining a plausible mechanism for suspiciousness, paranoia, and conspiratorial thinking, our theory indicates that rather than a deficit in Theory of Mind, paranoia may involve an over-application of strategy to genuine behaviour.

Numerical and computational analysis on a dissipative dynamical system: Slow invariant manifold for complex chemical mechanism.

This article presents the notion about Slow Invariant Manifold (SIM) and their fundamental role in model reduction techniques (MRTs) for challenges encountered in mechanical engineering within dissipative systems of chemical kinetics. Focusing on the reaction routes of complex mechanisms, we construct and compare primary approximations of the SIM through MRTs, including the Spectral Quasi Equilibrium Manifold (SQEM) and Intrinsic Low Dimensional Manifold (ILDM). These methods effectively transform high-dimensional complex problems into lower dimensions, solving them without compromising crucial information about the complex systems modified for homogeneous reactive systems. Employing the sensitivity analysis by using the MATLAB's toolbox, we present the numerical findings in a tabular format obtained through MRTs. This study provides the understanding about the accessible exploration of numerical solutions, improving insights of the complex variation within the system.

Understanding the effects of mineralization and structure on the mechanical properties of tendon-bone insertion using mesoscale computational modeling.

Tendon-bone fibrocartilaginous insertion, or enthesis, is a specialized interfacial region that connects tendon and bone, effectively transferring forces while minimizing stress concentrations. Previous studies have shown that insertion features gradient mineralization and branching fiber structure, which are believed to play critical roles in its excellent function. However, the specific structure-function relationship, particularly the effects of mineralization and structure at the mesoscale fiber level on the properties and function of insertion, remains poorly understood. In this study, we develop mesoscale computational models of the distinct fiber organization at tendon-bone insertions, capturing the branching network from tendon to interface fibers and the different mineralization scales. We specifically analyze three key descriptors: the mineralization scale of interface fibers, the mean, and relative standard deviation of the local branching angles of interface fibers. Tensile test simulations on insertion models with varying mineralization scales of interface fibers and structures are performed to mimic the primary loading condition applied to the insertion. We measure and analyze five representative mechanical properties: Young's modulus, strength, toughness, resilience, and failure strain. Our results reveal that mechanical properties are significantly influenced by the three key descriptors, with tradeoffs observed between mutually exclusive properties. For instance, strength and resilience plateau beyond a certain mineralization scale, while failure strain and Young's modulus exhibit monotonic decreasing and increasing trends, respectively. Consequently, there exists an optimal mineralization scale for toughness due to these tradeoffs. By analyzing the mesoscale deformation and failure mechanisms from simulation trajectories, we identify three fracture regimes closely related to the trends in mechanical properties, supporting the observed tradeoffs. Additionally, we examine in detail the effects of the mean and relative standard deviation of local branching angles on mechanical properties and deformation mechanisms. Overall, our study enhances the fundamental understanding of the composition-structure-function relationships at the tendon-bone insertion, complementing recent experimental studies. The mechanical insights from our work have the potential to guide the future biomimetic design of fibrillar adhesives and interfaces for joining soft and hard materials.

Systematic transcriptomic analysis and temporal modelling of human fibroblast senescence.

Cellular senescence is a diverse phenotype characterised by permanent cell cycle arrest and an associated secretory phenotype (SASP) which includes inflammatory cytokines. Typically, senescent cells are removed by the immune system, but this process becomes dysregulated with age causing senescent cells to accumulate and induce chronic inflammatory signalling. Identifying senescent cells is challenging due to senescence phenotype heterogeneity, and senotherapy often requires a combinatorial approach. Here we systematically collected 119 transcriptomic datasets related to human fibroblasts, forming an online database describing the relevant variables for each study allowing users to filter for variables and genes of interest. Our own analysis of the database identified 28 genes significantly up- or downregulated across four senescence types (DNA damage induced senescence (DDIS), oncogene induced senescence (OIS), replicative senescence, and bystander induced senescence) compared to proliferating controls. We also found gene expression patterns of conventional senescence markers were highly specific and reliable for different senescence inducers, cell lines, and timepoints. Our comprehensive data supported several observations made in existing studies using single datasets, including stronger p53 signalling in DDIS compared to OIS. However, contrary to some early observations, both p16 and p21 mRNA levels rise quickly, depending on senescence type, and persist for at least 8-11 days. Additionally, little evidence was found to support an initial TGFß-centric SASP. To support our transcriptomic analysis, we computationally modelled temporal protein changes of select core senescence proteins during DDIS and OIS, as well as perform knockdown interventions. We conclude that while universal biomarkers of senescence are difficult to identify, conventional senescence markers follow predictable profiles and construction of a framework for studying senescence could lead to more reproducible data and understanding of senescence heterogeneity.

Neural pathways associated with reduced rigidity during pallidal deep brain stimulation for Parkinson's disease.

Deep brain stimulation (DBS) of the internal segment of the globus pallidus (GPi) can markedly reduce muscle rigidity in people with Parkinson's disease (PD); however, the mechanisms mediating this effect are poorly understood. Computational modeling of DBS provides a method to estimate the relative contributions of neural pathway activations to changes in outcomes. In this study, we generated subject-specific biophysical models of GPi DBS (derived from individual 7-T MRI), including pallidal efferent, putamenal efferent, and internal capsule pathways, to investigate how activation of neural pathways contributed to changes in forearm rigidity in PD. Ten individuals (17 arms) were tested off medication under four conditions: off stimulation, on clinically optimized stimulation, and on stimulation specifically targeting the dorsal GPi or ventral GPi. Quantitative measures of forearm rigidity, with and without a contralateral activation maneuver, were obtained with a robotic manipulandum. Clinically optimized GPi DBS settings significantly reduced forearm rigidity (P < 0.001), which aligned with GPi efferent fiber activation. The model demonstrated that GPi efferent axons could be activated at any location along the GPi dorsal-ventral axis. These results provide evidence that rigidity reduction produced by GPi DBS is mediated by preferential activation of GPi efferents to the thalamus, likely leading to a reduction in excitability of the muscle stretch reflex via overdriving pallidofugal output.NEW & NOTEWORTHY Subject-specific computational models of pallidal deep brain stimulation, in conjunction with quantitative measures of forearm rigidity, were used to examine the neural pathways mediating stimulation-induced changes in rigidity in people with Parkinson's disease. The model uniquely included internal, efferent and adjacent pathways of the basal ganglia. The results demonstrate that reductions in rigidity evoked by deep brain stimulation were principally mediated by the activation of globus pallidus internus efferent pathways.

Evaluating the role of sex-related structure-function differences on airway aerosol transport and deposition.

Several experimental studies have found that females have higher deposition of particles in the airways compared with males. This has implications for the delivery of aerosolized therapeutics and for understanding sex differences in respiratory system response to environmental exposures. This study evaluates several factors that potentially contribute to sex differences in particle deposition, using scale-specific structure-function models of 1D ventilation distribution, particle transport, and deposition. The impact of gravity, inhalation flow rate, and dead space are evaluated in 12 structure-based models (seven female; five male). Females were found to have significantly higher total, bronchial, and alveolar deposition than males across a particle size range from 0.01 to 10 . Results suggest that higher deposition fraction in females is due to higher alveolar deposition for smaller particle sizes, and higher bronchial deposition for larger particles. Females had higher alveolar deposition in the lower lobes, and slightly lower particle concentration in the left upper lobe. Males were found to be more sensitive to changes due to gravity, showing greater reduction in bronchial deposition fraction. Males were also more sensitive to change in inhalation flow rate, and to scaling of dead space due to the larger male baseline airway size. Predictions of sex differences in particle deposition - that are consistent with the literature - suggest that sex-based characteristics of lung and airway size interacting with particle size gives rise to differences in regional deposition.