Matter Density Research Articles

Region-specific and age-related differences in astrocytes in the human brain

Astrocyte heterogeneity and its relation to aging in the normal human brain remain poorly understood. We here analyzed astrocytes in gray and white matter brain tissues obtained from donors ranging in age between the neonatal period to over 100 years. We show that astrocytes are differently distributed with higher density in the white matter. This regional difference in cellular density becomes less prominent with age. Additionally, we confirm the presence of morphologically distinct astrocytes, with gray matter astrocytes being morphologically more complex. Notably, gray matter astrocytes morphologically change with age, while white matter astrocytes remain relatively consistent in morphology. Using regional mass spectrometry-based proteomics, we did, however, identify astrocyte specific proteins with regional differences in abundance, reflecting variation in cellular density or expression level. Importantly, the expression of some astrocyte specific proteins region-dependently decreases with age. Taken together, we provide insights into region- and age-related differences in astrocytes in the human brain.

Clusternets: a deep learning approach to probe clustering dark energy

ABSTRACT Machine learning (ML) algorithms are becoming popular in cosmology for extracting valuable information from cosmological data. In this paper, we evaluate the performance of a convolutional neural network (CNN) trained on matter density snapshots to distinguish clustering dark energy (DE) from the cosmological constant scenario and to detect the speed of sound (cs) associated with clustering DE. We compare the CNN results with those from a Random Forest (RF) algorithm trained on power spectra. Varying the DE equation of state parameter wDE within the range of −0.7 to −0.99 while keeping $c_s^2 = 1$, we find that the CNN approach results in a significant improvement in accuracy over the RF algorithm. The improvement in classification accuracy can be as high as 40 per cent depending on the physical scales involved. We also investigate the ML algorithms’ ability to detect the impact of the speed of sound by choosing $c_s^2$ from the set {1, 10−2, 10−4, 10−7} while maintaining a constant wDE for three different cases: wDE ∈ {−0.7, −0.8, −0.9}. Our results suggest that distinguishing between various values of $c_s^2$ and the case where $c_s^2=1$ is challenging, particularly at small scales and when wDE ≈ −1. However, as we consider larger scales, the accuracy of $c_s^2$ detection improves. Notably, the CNN algorithm consistently outperforms the RF algorithm, leading to an approximate 20 per cent enhancement in $c_s^2$ detection accuracy in some cases.

Black holes immersed in dark matter: Energy condition and sound speed

In this work, we study the impact of the environment around a black hole in detail. We introduce nonvanishing radial pressure in a manner analogous to compact stars. We examine both isotropic and anisotropic fluid configurations with and without radial pressure respectively. Our focus extends beyond just dark matter density to the vital role of the energy condition and sound speed in the spacetime of a black hole immersed in matter. In cases of anisotropic pressure with vanishing radial pressure, all profiles violate the dominant energy condition near the BH, and the tangential sound speed exceeds light speed for all dark matter profiles. In our second approach, without assuming vanishing radial pressure, we observe similar violations and superluminal sound speeds. To rectify this, we introduce a hard cutoff for the sound speed, ensuring it remains subluminal. As a consequence, the energy condition is also satisfied. However, this results in increased density and pressure near the BH. This raises questions about the sound speed and its impact on the density structure, as well as questions about the validity of the model itself. With the matter distribution, we also compute the metric for different configurations. It reveals sensitivity to the profile structure. The metric components point toward the horizon structure. Published by the American Physical Society 2024

Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction

Predicting the course of neurodegenerative disorders early has potential to greatly improve clinical management and patient outcomes. A key challenge for early prediction in real-world clinical settings is the lack of labeled data (i.e., clinical diagnosis). In contrast to supervised classification approaches that require labeled data, we propose an unsupervised multimodal trajectory modeling (MTM) approach based on a mixture of state space models that captures changes in longitudinal data (i.e., trajectories) and stratifies individuals without using clinical diagnosis for model training. MTM learns the relationship between states comprising expensive, invasive biomarkers (β-amyloid, grey matter density) and readily obtainable cognitive observations. MTM training on trajectories stratifies individuals into clinically meaningful clusters more reliably than MTM training on baseline data alone and is robust to missing data (i.e., cognitive data alone or single assessments). Extracting an individualized cognitive health index (i.e., MTM-derived cluster membership index) allows us to predict progression to AD more precisely than standard clinical assessments (i.e., cognitive tests or MRI scans alone). Importantly, MTM generalizes successfully from research cohort to real-world clinical data from memory clinic patients with missing data, enhancing the clinical utility of our approach. Thus, our multimodal trajectory modeling approach provides a cost-effective and non-invasive tool for early dementia prediction without labeled data (i.e., clinical diagnosis) with strong potential for translation to clinical practice.

CURLING – I. The influence of point-like image approximation on the outcomes of cluster strong lens modelling

ABSTRACT Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modelling in galaxy clusters is computationally expensive, leading to the point-source approximation of strongly lensed extended images, potentially introducing systematic biases. Herein, as the first paper of the ClUsteR strong Lens modelIng for the Next-Generation observations (CURLING) program, we use lensing ray-tracing simulations to quantify the biases and uncertainties arising from the point-like image approximation for JWST-like observations. Our results indicate that the approximation works well for reconstructing the total cluster mass distribution, but can bias the magnification measurements near critical curves and the constraints on the cosmological parameters, the total matter density of the universe Ωm, and dark energy equation of state parameter w. To mitigate the biases, we propose incorporating the extended surface brightness distribution of lensed sources into the modelling. This approach reduces the bias in magnification from 46.2 per cent to 0.09 per cent for μ ∼ 1000. Furthermore, the median values of cosmological parameters align more closely with the fiducial model. In addition to the improved accuracy, we also demonstrate that the constraining power can be substantially enhanced. In conclusion, it is necessary to model cluster-scale strong lenses with pixelized multiple images, especially for estimating the intrinsic luminosity of highly magnified sources and accurate cosmography in the era of high-precision observations.

Minimal mass of thermal dark matter and the viability of millicharged particles affecting 21-cm cosmology

Thermal freeze-out offers an attractive explanation of the dark matter density free from fine-tuning of initial conditions. For dark matter with a mass below tens of MeV, photons, electrons, and neutrinos are the only available direct Standard Model annihilation products. Using a full three-sector abundance calculation, we determine the minimal mass of dark matter, allowing for an arbitrary branching into electrons/photons and neutrinos that is compatible with current cosmological observations. The analysis takes into account the heat transfer between the various sectors from annihilation elastic scattering, representing the first fully self-consistent analysis that tracks the respective sectors’ temperatures. We thereby provide accurate thermal annihilation cross sections, particularly for velocity-dependent cases, and deduce the sensitivity of current and upcoming CMB experiments to MeV thermal dark matter. In the latter context, we also establish the fine-tuned parameter region where a tiny admixture of neutrinos in the final states rules in MeV-scale p-wave annihilating DM into electrons. Finally, we show that a sub-% millicharged dark matter with an interaction strength that interferes with 21-cm cosmology is still allowed when freeze-out is supplemented with annihilation into neutrinos. For all cases considered, we provide concrete particle physics models and supplement our findings with a discussion of other relevant experimental results. Published by the American Physical Society 2024

Cosmological transition epoch from gamma-ray burst correlations

The redshift zt and the jerk parameter jt of the transition epoch are constrained by using two model-independent approaches involving the direct expansion of the Hubble rate and the expansion of the deceleration parameter around z=zt. To extend our analysis to high-redshifts, we employ the Amati, Combo, Yonetoku and Dainotti gamma-ray burst correlations. The circularity problem is prevented by calibrating these correlations through the Bézier interpolation of the updated observational Hubble data. Each gamma-ray burst data set is jointly fit with type Ia supernovae and baryonic acoustic oscillations through a Monte Carlo analysis, based on the Metropolis-Hastings algorithm, to obtain zt, jt and the correlation parameters. The overall results are compatible with the concordance model with some exceptions. We also focus on the behaviors of the dark energy, verifying its compatibility with a cosmological constant, and the matter density Ωm and compare them with the expectations of the concordance paradigm.

‘rO:Om’

Architecture’s relation to landscape is often only recognised in its response to topography, views, access, orientation and apprehension of the built work’s own exterior. As an object placed in an environment architecture is an artefact externally enhanced by vegetation as well as a container adorned by an interior. Such architecture relies on the subservience of its surrounding physical landscape and its internal hollows to define what is ‘in’ and what is ‘out’, ‘here’ and ‘there’. Negotiation of these realms is determined by elements other than the dwelling body as a living, experiencing, cultural organism capable of navigating across formal spatial boundaries. This paper explores the architectural envelope as a porous medium informed by spatial and material transmissions between body and environment. This aqueous notion of inhabitation and material repositions architecture as the concurrence of interior and landscape whereby their localities are distinguishable within a continuum of particularised densities of matter accumulating and disintegrating over time. This theoretical and physical site is explored via the construction of a room.

Quantum model of galactic halos with an Navarro-Frenk-White dark matter profile

A quantum model of a cold dark matter galactic halo is developed. The model requires specifying the mass and radius of the halo as well as its density profile. The structure of the halo resulting from the theory is predicted and its physical properties are determined. Verification of these theoretical predictions by observations is proposed and discussed. The model is constructed by analytically solving the governing equation and using its time-independent solutions to determine the internal structure of a galactic halo with an Navarro-Frenk-White cold dark matter density profile. The governing equation that is the basis of the developed theory is derived from the irreducible representations of the extended Galilean group. The method of finding the solutions is analytical, even though an Navarro-Frenk-White density profile is used in the calculations. The theory predicts a halo with a core composed of free dark matter particles that move randomly with frequent collisions. It also predicts an envelope in which the particles are confined to their orbits, which are quantized. Except in the close vicinity of the core, the population of the orbits remains fixed, and physical reasons for the nonexistence of quantum jumps between these orbits are presented. A quantum model of a galactic cold dark matter halo with a given Navarro-Frenk-White density profile is constructed. It predicts a quantum structure of the halo that is significantly different than any previously known dark matter model. The quantum model naturally accounts for dark matter being collisionless, and it predicts that dark matter can only emit radiation of one fixed frequency. The values of this frequency are computed for dark matter particles of different masses. A potential observational verification of the theory is also discussed.

ΛCDM is alive and well

Despite its successes, the ΛCDM model faces several tensions with recent cosmological data and their increased accuracy. The mismatch between the values of the Hubble constant H0 obtained from {some} direct distance ladder measurements and from the cosmic microwave background (CMB) is the most statistically significant, but the amplitude of the matter fluctuations is also regarded as a serious concern, leading to the investigation of a plethora of {alternative} models. Here, we examine the situation from a different perspective. We first show that the combination of several recent measurements from local probes leads to a tight constraint on the present-day matter density Ωm as well as on the amplitude of the matter fluctuations, both acceptably consistent with the values inferred from the CMB. Secondly, we address the Hubble tension by assuming that some determinations of the value of H0 are possibly biased. We treat such a bias as a nuisance parameter within ΛCDM and we examine such `` ΛCDM + H0 bias’’ models on the same statistical grounds as alternative cosmological models. A bias in Planck or in SH0ES produces similar improvements. However we show that a bias in the Cepheids calibration produces improvements in terms of ΔAIC that supersede existing extended models proposed up to now. In a third step, we show that the value of Ωm we obtained from our RSD, Pantheon+ and 3×2pt from DES, combined with SH0ES determination of H0, leads to a precise determination of the density parameter of the Universe ωm=0.1753±0.0069. This measurement provides an additional low-redshift test for cosmological models by comparing it to the preferred value derived from the CMB. From this test, most ΛCDM extensions seem to be confronted with a new tension as many of them cluster around ωm=0.14, while there is no tension with a local $H_0 67 $ km/s/Mpc. We conclude that a standard ΛCDM model with an unknown bias in the Cepheids distance calibration represents a model that reaches a remarkable agreement, statistically better than previously proposed extensions without bias for which such a comparison can be performed.

Holographic massive plasma state in Friedman universe: cosmological fine-tuning and coincidence problems

Massive particle and antiparticle pair production andoscillation on the horizon form a holographic and massive pair plasma state in the Friedman Universe. Via this state, the Einsteincosmology term (dark energy) interacts with matter and radiation and is time-varying Λ̃ in the Universe's evolution.It is determined by a close set of ordinary differential equations for dark energy, matter, and radiation energy densities. The solutions are unique, provided the initial conditions given by observations.In inflation and reheating, dark energy density decreases from the inflation scale, converting to matter and radiation energy densities.In standard cosmology, matter and radiation energy densities convert to dark energy density, reaching the present Universe. By comparing with ΛCDM, quintessence and dark energy interacting models, we show thatthese results can be the possible solutions for cosmological fine-tuning and coincidence problems.

Suppression of matter density growth at scales exceeding the cosmic screening length

One of the main objectives of modern cosmology is to explain the origin and evolution of cosmic structures at different scales. The principal force responsible for the formation of such structures is gravity. In a general relativistic framework, we have shown that matter density contrasts do not grow over time at scales exceeding the cosmic screening length, which corresponds to a cosmological scale of the order of two to three gigaparsecs at the present time, at which gravitational interactions exhibit an exponential cut-off. This is a purely relativistic effect.To demonstrate the suppression of density growth, we have performed N-body simulations in a box with a comoving size of 5.632 Gpc/h and obtained the power spectrum of the mass density contrast. We have shown that it becomes independent of time for scales beyond the screening length as a clear manifestation of the cosmic screening effect.

No-go theorem for static spherically symmetric configurations composed of two charged pressureless fluid species

We present a no-go theorem for spherically symmetric configurations of two charged fluid species in equilibrium. The fluid species are assumed to be dusts, that is, perfect fluids without pressure, and the equilibrium can be attained for a single dust from the balance of electrostatic repulsion and gravitational attraction. We show that this is impossible for two dust species unless both of them are indistinguishable in terms of their electric charge density to matter density ratio. The result is obtained in the main three theories of mechanics, that is, in Newtonian Mechanics, in Special Relativity and in General Relativity. In particular, as charged dust solutions have been used to study the possibility of black hole mimickers, this result shows that such mimickers can not be constructed unless the underlying charged particle has the correct charge to mass ratio.

Using axion miniclusters to disentangle the axion-photon coupling and the dark matter density

Dark matter direct (and indirect) detection experiments usually can only determine a specific combination of a power of the coupling and the dark matter density. This is also true for axion haloscopes which are sensitive to the product g 2 aγγρ DM, the combination of axion-photon coupling squared and the dark matter density. In this note we show, that in the lucky case when we intersect with a so-called axion minicluster of a suitable size, we can utilize the spectral information available in haloscopes to determine the gravitational potential of the minicluster. We can then use this to measure separately the coupling and the density of the minicluster.

Cosmological implications of inflaton-mediated dark and visible matter scatterings after reheating

The initial density of dark matter (DM) particles, otherwise secluded from the standard model (SM), may be generated at reheating, with an initial temperature ratio for internal thermalizations, ξi=TDM,i/TSM,i. This scenario necessarily implies inflaton-mediated scatterings between DM and SM after reheating, with a rate fixed by the relic abundance of DM and the reheat temperature. These scatterings can be important for an inflaton mass and reheat temperature as high as O(107 GeV) and O(109 GeV), respectively, since the thermally averaged collision terms become approximately independent of the inflaton mass when the bath temperature is larger than the mass. The impact of these scatterings on DM cosmology is studied modeling the perturbative reheating physics by a gauge-invariant set of inflaton interactions up to dimension 5 with the SM gauge bosons, fermions, and the Higgs fields. It is observed that an initially lower (higher) DM temperature will rapidly increase (decrease), even with very small couplings to the inflaton. There is a sharp lower bound on the DM mass below which the relic abundance cannot be satisfied due to faster backscatterings depleting DM quanta to SM particles. For low DM masses, the cosmic microwave background constraints become stronger due to the collisions for ξi<1, probing values as small as O(10−4), and weaker for ξi>1. The big-bang nucleosynthesis constraints become stronger due to the collisions for lower DM masses, probing ξi as small as O(0.1), and weaker for higher DM mass. Thus inflaton-mediated collisions with predictable rates, relevant even for high-scale inflation models, can significantly impact the cosmology of light DM. Published by the American Physical Society 2024

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

Estimation of the mass density of biological matter from refractive index measurements

The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms. One of the basic biophysical properties is the mass density (MD). It affects the dynamics in sub-cellular compartments and plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge, as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for assumptions about the biochemical composition of the sample and respective RI measurements. To this aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations and Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well-characterized complex mixtures given by bovine milk and intralipid emulsion and employ it to estimate the MD of living zebrafish (Danio rerio) larvae trunk tissue. Our results illustrate the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

Flattened Galaxy Rotation Curves in the Exochronous Metric

We examine some of the consequences of the Exochronous (timeless) metric and the associated ΣGR cosmological model for the formation of galaxies, and, in particular, their characteristic rotation curves. We show how the cumulative curvature from the multiple spatial hypersurfaces in this model leads to a modified version of the Poisson equation, in which the gravitational potential is computed over 4D space. Using this new form of the Poisson equation, we derive an analytic expression for gravitational potential as a function of radial distance for a uniform gas cloud undergoing gravitational collapse. We show that this results in a radial velocity profile that provides an excellent fit with commonly observed galaxy rotation curves, and hence fully accounts for the effects previously ascribed to dark matter. An expression can be derived for the equivalent matter density profile corresponding to the ΣGR gravitational potential, from which it is evident that this is very similar in form to the well-known Navarro–Frenk–White profile. As a further illustration of the consequences of adopting the Exochronous metric, we show how the principle can readily be incorporated into particle-mesh N-body simulations of large-scale structure evolution, using a relaxation solver for the solution to the Poisson equation and the evolution of the gravitational potential. Examples of the use of this simulation model are shown for the following cases: (a) the initial evolution of a large-scale structure, and (b) galaxy formation from a gravitationally collapsing gas cloud. In both cases, it is possible to directly visualise the build-up of the gravitational potential in 3D space as the simulation evolves and note how this corresponds to what is currently assumed to be dark matter.

Fuzzy bounces

We observe that the energy and the enthalpy densities can be smeared by two fudge factors that are constrained by the contracted Bianchi identities. Depending on the analytic properties of the smearing functions the underlying cosmological solutions belong to two physically different classes, namely the bounces of the scale factor and the curvature bounces. While the curvature bounces are naturally compatible with a stage of accelerated expansion, the bounces of the scale factor demand an early phase of accelerated contraction even if a short inflationary stage may arise prior to the decelerated regime. Despite the regularity of the underlying solutions, gradient instabilities and singularities do occasionally appear in the evolution of curvature inhomogeneities. After deducing the specific criteria behind these occurrences, the background-independent conclusions are corroborated by a series of concrete examples associated with different forms of the smearing functions. The evolution of the curvature inhomogeneities restricts the ranges of the solutions that turn out to be unsuitable even for a limited description of the pre-inflationary initial data. The same observation holds in the case of the gauge-invariant evolution of the matter density contrast. It is however not excluded that a class of scenarios (mainly associated with the curvature bounces) could indeed avoid the potential instabilities. All in all the present analysis explore a general approach whose results are relevant in all the contexts where bouncing solutions are invoked either as complementary or as alternative to the conventional inflationary scenarios.

Localized Changes in Dentate Nucleus Shape and Magnetic Susceptibility in Friedreich Ataxia.

The dentate nuclei of the cerebellum are key sites of neuropathology in Friedreich ataxia (FRDA). Reduced dentate nucleus volume and increased mean magnetic susceptibility, a proxy of iron concentration, have been reported by magnetic resonance imaging studies in people with FRDA. Here, we investigate whether these changes are regionally heterogeneous. Quantitative susceptibility mapping data were acquired from 49 people with FRDA and 46 healthy controls. The dentate nuclei were manually segmented and analyzed using three dimensional vertex-based shape modeling and voxel-based assessments to identify regional changes in morphometry and susceptibility, respectively. Individuals with FRDA, relative to healthy controls, showed significant bilateral surface contraction most strongly at the rostral and caudal boundaries of the dentate nuclei. The magnitude of this surface contraction correlated with disease duration, and to a lesser extent, ataxia severity. Significantly greater susceptibility was also evident in the FRDA cohort relative to controls, but was instead localized to bilateral dorsomedial areas, and also correlated with disease duration and ataxia severity. Changes in the structure of the dentate nuclei in FRDA are not spatially uniform. Atrophy is greatest in areas with high gray matter density, whereas increases in susceptibility-reflecting iron concentration, demyelination, and/or gliosis-predominate in the medial white matter. These findings converge with established histological reports and indicate that regional measures of dentate nucleus substructure are more sensitive measures of disease expression than full-structure averages. Biomarker development and therapeutic strategies that directly target the dentate nuclei, such as gene therapies, may be optimized by targeting these areas of maximal pathology. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.