Analysis of Fiber Network Architecture in Blood Vessels and Blood Clots

Fibrous networks, including collagen and fibrin, provide strength and support, and are critical for maintaining homeostasis. In this study, we have developed algorithms to define the structural properties of collagen and fibrin networks from microscopic images of these networks in abdominal aortic aneurysms (AAA) and blood clots, respectively. AAA is a biomechanical disease characterized by significant changes in the structure and strength of the arterial wall due to differential changes in the composition of fibrillar collagen in adventitial and medial layers. Using bright-field and polarized microscopic images of histological sections of mouse aorta stained with Picrosirius red (PSR) stain, we developed MATLAB code to locally quantify collagen content within the vessel wall. The method was benchmarked against manual quantification, and the superiority of the automated analysis was established by statistical analyses of accuracy and reproducibility. Fibrin networks form the structural and functional basis of blood clots. We developed an algorithm using a combination of ImageJ plugins and a custom MATLAB code to analyze the ultrastructure of blood clots from the scanning electron microscopic images of fibrin networks. This morphometric profile was used to correlate clot structure to mechanics, which has implications for our understanding of hemostasis and thrombosis

Physics and Phenomenology of Galactic Starburst Winds

Mathematical and Physical Sciences: 1st Place (The Ohio State University Edward F. Hayes Graduate Research Forum)Cool clouds are expected to be destroyed and incorporated into hot supernova-driven galactic winds. The mass-loading of a wind by the cool medium modifies the bulk velocity, temperature, density, entropy, and abundance profiles of the hot phase relative to an unmass-loaded outflow. We provide general equations and limits for this physics that can be used to infer the rate of cool gas entrainment from X-ray observations, accounting for non-spherical expansion. In general, mass-loading flattens the density and temperature profiles, decreases the velocity and increases the entropy if the Mach number is above a critical value. We first apply this model to a recent high- resolution galactic outflow simulation where the mass-loading can be directly inferred. We show that the temperature, entropy, and composition profiles are well matched, providing evidence that this physics sets the bulk hot gas profiles. We then model the diffuse X-ray emission from the local starburst M82. The non-spherical (more cylindrical) outflow geometry is directly taken from the observed X-ray surface brightness profile. These models predict an asymptotic hot wind velocity of ∼ 1000 km s−1 , which is ∼1.5–2 times smaller than previous predictions. We also show how the observed entropy profile can be used to constrain the outflow velocity, making predictions for future missions like XRISM. We then test the models with 3D hydrodynamic simulations and find that the 1D analytics agree well, and that they are generically stable. As the flow transitions to the subsonic regime, we see the assumptions of a steady-state flow break down, and a multi-phase and multi-dynamical flow is generated through non-linear instabilities.No embarg

Patient-held logbooks for cancer care treatment : the users’ evaluative perspective

The quality and usefulness of patient held logbooks as a record to improve communication between healthcare professionals providing cancer care was evaluated. Its aim was to facilitate greater coordination and information sharing between patients, carers, clinicians and other health professionals. A mixed-method exploratory study conducted 12-week post distribution of logbooks to patients undertaking cancer care. Data was gathered through questionnaires returned by 66 participants (response rate of 57.4%) and interviews with five clinical oncology nurses at a Tasmanian hospital. The logbook quality was evaluated against two sets of indicators, including content and layout. The general effectiveness of the patient logbook was also assessed based on its usefulness, usability, efficiency and satisfaction. The logbook was considered useful among 63 (95.1%) participants. They acknowledged the logbook enabled them to be better informed, created a feeling of empowerment and greater control over their medical condition. The logbook was observed to improve communication between clinicians, their patients and families. The evaluation generated rich, in-depth information and provided useful insights into the general quality and usefulness of the logbook for cancer care. The strengths and weaknesses of the logbook were highlighted and how to better utilise its functions in the current medical system

Highly-mass-loaded hot galactic winds are unstable to cool filament formation

When cool clouds are ram-pressure accelerated by a hot supersonic galactic wind, some of the clouds may be shredded by hydrodynamical instabilities and incorporated into the hot flow. Recent one-dimensional steady-state calculations show how cool cloud entrainment directly affects the bulk thermodynamics, kinematics, and observational characteristics of the hot gas. In particular, mass-loading decelerates the hot flow and changes its entropy. Here, we investigate the stability of planar and spherical mass-loaded hot supersonic flows using both perturbation analysis and three-dimensional time-dependent radiative hydrodynamical simulations. We show that mass-loading is stable over a broad range of parameters and that the 1D time-steady analytic solutions exactly reproduce the 3D time-dependent calculations, provided that the flow does not decelerate sufficiently to become subsonic. For higher values of the mass-loading, the flow develops a sonic point and becomes thermally unstable, rapidly cooling and forming elongated dense cometary filaments. We explore the mass-loading parameters required to reach a sonic point and the radiative formation of these filaments. For certain approximations, we can derive simple analytic criteria. In general a mass-loading rate similar to the initial mass outflow rate is required. In this sense, the destruction of small cool clouds by a hot flow may ultimately spontaneously generate fast cool filaments, as observed in starburst superwinds. Lastly, we find that the kinematics of filaments is sensitive to the slope of the mass-loading function. Filaments move faster than the surrounding wind if mass-loading is over long distances whereas filaments move slower than their surroundings if mass-loading is abrupt.Comment: 12 pages, 15 figures, submitted to MNRAS (21 July 2023

Temperature and Metallicity Gradients in the Hot Gas Outflows of M82

We utilize deep Chandra X-ray Observatory imaging and spectra of M82, the prototype of a starbursting galaxy with a multiphase wind, to map the hot plasma properties along the minor axis of the galaxy. We extract spectra from 11 regions up to 2.5 kpc from the starbursting midplane and model the data as a multi-temperature, optically thin thermal plasma with contributions from a non-thermal (power-law) component and from charge exchange (CX). We examine the gradients in best-fit parameters, including the intrinsic column density, plasma temperature, metal abundances, and number density of the hot gas as a function of distance from the M82 nucleus. We find that the temperatures and number densities of the warm-hot and hot plasma peak at the starbursting ridge and decreases along the minor axis. The temperature and density profiles are inconsistent with spherical adiabatic expansion of a super-heated wind and suggest mass loading and mixing of the hot phase with colder material. Non-thermal emission is detected in all of the regions considered, and CX comprises 8-25% of the total absorption-corrected, broad-band (0.5-7 keV) X-ray flux. We show that the abundances of O, Ne, Mg, and Fe are roughly constant across the regions considered, while Si and S peak within 500 pc of the central starburst. These findings support a direct connection between the M82 superwind and the warm-hot, metal-rich circumgalactic medium (CGM).Comment: 15 pages, 8 figures, ApJ in pres

Neural ODEs as a discovery tool to characterize the structure of the hot galactic wind of M82

Dynamic astrophysical phenomena are predominantly described by differential equations, yet our understanding of these systems is constrained by our incomplete grasp of non-linear physics and scarcity of comprehensive datasets. As such, advancing techniques in solving non-linear inverse problems becomes pivotal to addressing numerous outstanding questions in the field. In particular, modeling hot galactic winds is difficult because of unknown structure for various physical terms, and the lack of \textit{any} kinematic observational data. Additionally, the flow equations contain singularities that lead to numerical instability, making parameter sweeps non-trivial. We leverage differentiable programming, which enables neural networks to be embedded as individual terms within the governing coupled ordinary differential equations (ODEs), and show that this method can adeptly learn hidden physics. We robustly discern the structure of a mass-loading function which captures the physical effects of cloud destruction and entrainment into the hot superwind. Within a supervised learning framework, we formulate our loss function anchored on the astrophysical entropy ($K \propto P/\rho^{5/3}$). Our results demonstrate the efficacy of this approach, even in the absence of kinematic data $v$. We then apply these models to real Chandra X-Ray observations of starburst galaxy M82, providing the first systematic description of mass-loading within the superwind. This work further highlights neural ODEs as a useful discovery tool with mechanistic interpretability in non-linear inverse problems. We make our code public at this GitHub repository (https://github.com/dustindnguyen/2023_NeurIPS_NeuralODEs_M82).Comment: 9 Pages, 2 Figures, Accepted at the NeurIPS 2023 workshop on Machine Learning and the Physical Science

Complete Genome Sequence of Strain JM503A, a Genetically Tractable Dental Abscess Clinical Isolate

Parvimonas micra is a pathobiont of humans that is often found in abundance at sites of mucosal inflammation as well as within malignant tumors. Here, we report the complete genome sequence of P. micra strain JM503A, which is a genetically tractable clinical isolate derived from a human odontogenic abscess specimen