A CONSTRAINED CONSTRUCTIVE OPTIMIZATION MODEL OF BRANCHING ARTERIOLAR NETWORKS IN RAT SKELETAL MUSCLE.

Blood flow regulation within the microvasculature reflects a complex interaction of regulatory mechanisms and varies spatially and temporally according to conditions such as metabolism, growth, injury, and disease. Understanding the role of microvascular flow distributions across conditions is of interest to investigators spanning multiple disciplines; however, data collection within networks can be labour-intensive and challenging due to limited resolution. To overcome these experimental challenges, computational network models which can accurately simulate vascular behavior are highly beneficial. Constrained Constructive Optimization (CCO) is a commonly used algorithm for vascular simulation, particularly well known for its adaptability towards vascular modelling across tissues. The present work demonstrates an implementation of CCO aimed to simulate a branching arteriolar microvasculature in healthy skeletal muscle, validated against literature including comprehensive rat gluteus maximus vasculature datasets, and reviews a list of user-specified adjustable model parameters to understand how their variability affects the simulated networks. Network geometric properties, including mean element diameters, lengths, and numbers of bifurcations per order, Horton's Law ratios, and fractal dimension, demonstrate good validation once model parameters are adjusted to experimental data. This model successfully demonstrates hemodynamic properties such as Murray's Law and the network Fahraeus effect. Application of centrifugal and Strahler ordering schemes results in divergent descriptions of identical simulated networks. This work introduces a novel CCO-based model focused on generating branching skeletal muscle microvascular arteriolar networks based on adjustable model parameters, thus making it a valuable tool for investigations into skeletal muscle microvascular structure and tissue perfusion.

Probing Hydrodynamic Fluctuation-Induced Forces with an Oscillating Robot.

We study the dynamics of an oscillating, free-floating robot that generates radially expanding gravity-capillary waves at a fluid surface. In open water, the device does not self-propel; near a rigid boundary, it can be attracted or repelled. Visualization of the wave field dynamics reveals that when near a boundary, a complex interference of generated and reflected waves induces a wave amplitude fluctuation asymmetry. Attraction increases as wave frequency increases or robot-boundary separation decreases. Theory on confined gravity-capillary wave radiation dynamics developed by Hocking in the 1980s captures the observed parameter dependence due to these "Hocking fields." The flexibility of the robophysical system allows detailed characterization and analysis of locally generated nonequilibrium fluctuation-induced forces [M. Kardar and R. Golestanian, Rev. Mod. Phys. 71, 1233 (1999)RMPHAT0034-686110.1103/RevModPhys.71.1233].

Xist ribonucleoproteins promote female sex-biased autoimmunity.

Autoimmune diseases disproportionately affect females more than males. The XX sex chromosome complement is strongly associated with susceptibility to autoimmunity. Xist long non-coding RNA (lncRNA) is expressed only in females to randomly inactivate one of the two X chromosomes to achieve gene dosage compensation. Here, we show that the Xist ribonucleoprotein (RNP) complex comprising numerous autoantigenic components is an important driver of sex-biased autoimmunity. Inducible transgenic expression of a non-silencing form of Xist in male mice introduced Xist RNP complexes and sufficed to produce autoantibodies. Male SJL/J mice expressing transgenic Xist developed more severe multi-organ pathology in a pristane-induced lupus model than wild-type males. Xist expression in males reprogrammed T and B cell populations and chromatin states to more resemble wild-type females. Human patients with autoimmune diseases displayed significant autoantibodies to multiple components of XIST RNP. Thus, a sex-specific lncRNA scaffolds ubiquitous RNP components to drive sex-biased immunity.

Capillary oxygen regulates demand-supply coupling by triggering connexin40-mediated conduction: Rethinking the metabolic hypothesis.

Coupling red blood cell (RBC) supply to O2 demand is an intricate process requiring O2 sensing, generation of a stimulus, and signal transduction that alters upstream arteriolar tone. Although actively debated, this process has been theorized to be induced by hypoxia and to involve activation of endothelial inwardly rectifying K+ channels (KIR) 2.1 by elevated extracellular K+ to trigger conducted hyperpolarization via connexin40 (Cx40) gap junctions to upstream resistors. This concept was tested in resting healthy skeletal muscle of Cx40-/- and endothelial KIR2.1-/- mice using state-of-the-art live animal imaging where the local tissue O2 environment was manipulated using a custom gas chamber. Second-by-second capillary RBC flow responses were recorded as O2 was altered. A stepwise drop in PO2 at the muscle surface increased RBC supply in capillaries of control animals while elevated O2 elicited the opposite response; capillaries were confirmed to express Cx40. The RBC flow responses were rapid and tightly coupled to O2; computer simulations did not support hypoxia as a driving factor. In contrast, RBC flow responses were significantly diminished in Cx40-/- mice. Endothelial KIR2.1-/- mice, on the other hand, reacted normally to O2 changes, even when the O2 challenge was targeted to a smaller area of tissue with fewer capillaries. Conclusively, microvascular O2 responses depend on coordinated electrical signaling via Cx40 gap junctions, and endothelial KIR2.1 channels do not initiate the event. These findings reconceptualize the paradigm of blood flow regulation in skeletal muscle and how O2 triggers this process in capillaries independent of extracellular K+.

Urine proteomic signatures of histological class, activity, chronicity, and treatment response in lupus nephritis.

Lupus nephritis (LN) is a pathologically heterogenous autoimmune disease linked to end-stage kidney disease and mortality. Better therapeutic strategies are needed as only 30%-40% of patients completely respond to treatment. Noninvasive biomarkers of intrarenal inflammation may guide more precise approaches. Because urine collects the byproducts of kidney inflammation, we studied the urine proteomic profiles of 225 patients with LN (573 samples) in the longitudinal Accelerating Medicines Partnership in RA/SLE cohort. Urinary biomarkers of monocyte/neutrophil degranulation (i.e., PR3, S100A8, azurocidin, catalase, cathepsins, MMP8), macrophage activation (i.e., CD163, CD206, galectin-1), wound healing/matrix degradation (i.e., nidogen-1, decorin), and IL-16 characterized the aggressive proliferative LN classes and significantly correlated with histological activity. A decline of these biomarkers after 3 months of treatment predicted the 1-year response more robustly than proteinuria, the standard of care (AUC: CD206 0.91, EGFR 0.9, CD163 0.89, proteinuria 0.8). Candidate biomarkers were validated and provide potentially treatable targets. We propose these biomarkers of intrarenal immunological activity as noninvasive tools to diagnose LN and guide treatment and as surrogate endpoints for clinical trials. These findings provide insights into the processes involved in LN activity. This data set is a public resource to generate and test hypotheses and validate biomarkers.

Immune and molecular landscape behind non-response to Mycophenolate Mofetil and Azathioprine in lupus nephritis therapy.

Lupus nephritis (LN) represents one of the most severe complications of systemic lupus erythematosus, leading to end-stage kidney disease in worst cases. Current first-line therapies for LN, including mycophenolate mofetil (MMF) and azathioprine (AZA), fail to induce long-term remission in 60-70% of the patients, evidencing the urgent need to delve into the molecular knowledge-gap behind the non-response to these therapies. A longitudinal cohort of treated LN patients including clinical, cellular and transcriptomic data, was analyzed. Gene-expression signatures behind non-response to different drugs were revealed by differential expression analysis. Drug-specific non-response mechanisms and cell proportion differences were identified. Blood cell subsets mediating non-response were described using single-cell RNASeq data. We show that AZA and MMF non-response implicates different cells and regulatory functions. Mechanistic models were used to suggest add-on therapies to improve their current performance. Our results provide new insights into the molecular mechanisms associated with treatment failures in LN.

Robot swarms meet soft matter physics.

Principles of soft matter physics can be leveraged to develop swarms of active robots with unique properties.

Thromboxane-induced cerebral microvascular rarefaction predicts depressive symptom emergence in metabolic disease.

Previous studies have suggested that the loss of microvessel density in the peripheral circulation with evolving metabolic disease severity represents a significant contributor to impaired skeletal muscle oxygenation and fatigue-resistance. Based on this and our recent work, we hypothesized that cerebral microvascular rarefaction was initiated from the increased prooxidant and proinflammatory environment with metabolic disease and is predictive of the severity of the emergence of depressive symptoms in obese Zucker rats (OZRs). In male OZR, cerebrovascular rarefaction followed the emergence of elevated oxidant and inflammatory environments characterized by increased vascular production of thromboxane A2 (TxA2). The subsequent emergence of depressive symptoms in OZR was associated with the timing and severity of the rarefaction. Chronic intervention with antioxidant (TEMPOL) or anti-inflammation (pentoxifylline) therapy blunted the severity of rarefaction and depressive symptoms, although the effectiveness was limited. Blockade of TxA2 production (dazmegrel) or action (SQ-29548) resulted in a stronger therapeutic effect, suggesting that vascular production and action represent a significant contributor to rarefaction and the emergence of depressive symptoms with chronic metabolic disease (although other pathways clearly contribute as well). A de novo biosimulation of cerebrovascular oxygenation in the face of progressive rarefaction demonstrates the increased probability of generating hypoxic regions within the microvascular networks, which could contribute to impaired neuronal metabolism and the emergence of depressive symptoms. The results of the present study also implicate the potential importance of aggressive prodromic intervention in reducing the severity of chronic complications arising from metabolic disease.NEW & NOTEWORTHY With clinical studies linking vascular disease risk to depressive symptom emergence, we used obese Zucker rats, a model of chronic metabolic disease, to identify potential mechanistic links between these two negative outcomes. Depressive symptom severity correlated with the extent of cerebrovascular rarefaction, after increased vascular oxidant stress/inflammation and TxA2 production. Anti-TxA2 interventions prevasculopathy blunted rarefaction and depressive symptoms, while biosimulation indicated that cerebrovascular rarefaction increased hypoxia within capillary networks as a potential contributing mechanism.

A robophysical model of spacetime dynamics.

Systems consisting of spheres rolling on elastic membranes have been used to introduce a core conceptual idea of General Relativity: how curvature guides the movement of matter. However, such schemes cannot accurately represent relativistic dynamics in the laboratory because of the dominance of dissipation and external gravitational fields. Here we demonstrate that an "active" object (a wheeled robot), which moves in a straight line on level ground and can alter its speed depending on the curvature of the deformable terrain it moves on, can exactly capture dynamics in curved relativistic spacetimes. Via the systematic study of the robot's dynamics in the radial and orbital directions, we develop a mapping of the emergent trajectories of a wheeled vehicle on a spandex membrane to the motion in a curved spacetime. Our mapping demonstrates how the driven robot's dynamics mix space and time in a metric, and shows how active particles do not necessarily follow geodesics in the real space but instead follow geodesics in a fiducial spacetime. The mapping further reveals how parameters such as the membrane elasticity and instantaneous speed allow the programming of a desired spacetime, such as the Schwarzschild metric near a non-rotating blackhole. Our mapping and framework facilitate creation of a robophysical analog to a general relativistic system in the laboratory at low cost that can provide insights into active matter in deformable environments and robot exploration in complex landscapes.

Mechanical intelligence simplifies control in terrestrial limbless locomotion.

Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (those involving "mechanical intelligence"), they fail to reproduce the performance of even the simplest organisms. To uncover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We used a model biological system, the highly studied nematode worm Caenorhabditis elegans, and a robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot's kinematics quantitatively reproduced the performance of the nematodes with purely open-loop control; mechanical intelligence simplified control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans, undulatory wave reversal upon head collisions, robustified locomotion via exploitation of the systems' mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.

The rhizodynamics robot: Automated imaging system for studying long-term dynamic root growth.

The study of plant root growth in real time has been difficult to achieve in an automated, high-throughput, and systematic fashion. Dynamic imaging of plant roots is important in order to discover novel root growth behaviors and to deepen our understanding of how roots interact with their environments. We designed and implemented the Generating Rhizodynamic Observations Over Time (GROOT) robot, an automated, high-throughput imaging system that enables time-lapse imaging of 90 containers of plants and their roots growing in a clear gel medium over the duration of weeks to months. The system uses low-cost, widely available materials. As a proof of concept, we employed GROOT to collect images of root growth of Oryza sativa, Hudsonia montana, and multiple species of orchids including Platanthera integrilabia over six months. Beyond imaging plant roots, our system is highly customizable and can be used to collect time- lapse image data of different container sizes and configurations regardless of what is being imaged, making it applicable to many fields that require longitudinal time-lapse recording.

East-Asian lupus nephritis in the Hopkins Lupus Cohort.

Background and Objective: East Asian systemic lupus erythematosus (SLE) is under represented in lupus cohorts outside of East Asia. We asked whether lupus nephritis was more common and more severe in East Asians than in other ethnicities in a large United States SLE cohort. Methods: The Hopkins Lupus Cohort, a longitudinal cohort of 2802 patients (53.5% Caucasian, 39.2% African-American, 3.2% East Asian) was studied. The SLICC/ACR Damage Index was used to assess renal outcomes. Results: East Asian patients had the same prevalence of lupus nephritis as African-Americans and both were higher than Caucasians. East Asians were not significantly different in frequency of end stage kidney disease compared with African-Americans. East Asians were more likely than Caucasians to have anti-Sm, low C3 and low C4. East Asians were more likely than African-Americans to have low C3 and low C4. Conclusion: East Asians living in the United States were more likely to have lupus nephritis than Caucasians. Poor outcomes such as end stage kidney disease occurred at an equal frequency in East Asians as in African-Americans. Lupus nephritis was both more frequent and more severe in East Asians than in African-Americans.

Does the use of corticosteroids and immunosuppressants increase the risk of COVID-19 infection among people with systemic lupus erythematosus?

OBJECTIVE: An important clinical question is whether the use of immunosuppressants or corticosteroids increases the risk of incident COVID-19 disease among patients with SLE. To address this question, we examined the incidence of COVID-19 infection in a large SLE cohort. METHODS: This study was based on a single-centre cohort of patients with SLE seen quarterly from March 2020 to August 2022. Clinical information from these visits was augmented with information on COVID-19 infections and vaccinations obtained from the electronic medical records and by patient self-report. We compared treated and untreated patients with respect to the incidence of COVID-19 infection per person month. Statistical significance was assessed based on logistic regression models. RESULTS: We observed 339 incident cases of COVID-19 experienced over 24 614 person-months of follow-up from 1052 different patients. The risk of infection per person-month of follow-up was similar among those not on prednisone (1.37%), on moderate doses of prednisone (<7 mg/day) (1.44%) and those on higher doses (1.52%) (p=0.87 for difference). We observed an elevated risk among those taking belimumab, however, after adjustment for potential confounding variables, the increased risk was not statistically significant (rate ratio 1.4, 95% CI 0.88 to 2.24, p=0.16) There was no evidence of an increased risk among those taking mycophenolate, methotrexate or azathioprine. CONCLUSION: It is reassuring that there was not strong evidence of an increased risk of infection among those taking prednisone or other immunosuppressants. However, given the range of our CIs, moderate effects of these medications on COVID-19 risk cannot be completely ruled out.

The XIST lncRNA is a sex-specific reservoir of TLR7 ligands in SLE.

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a dramatic sex bias, affecting 9 times more women than men. Activation of Toll-like receptor 7 (TLR7) by self-RNA is a central pathogenic process leading to aberrant production of type I interferon (IFN) in SLE, but the specific RNA molecules that serve as TLR7 ligands have not been defined. By leveraging gene expression data and the known sequence specificity of TLR7, we identified the female-specific X-inactive specific transcript (XIST) long noncoding RNA as a uniquely rich source of TLR7 ligands in SLE. XIST RNA stimulated IFN-α production by plasmacytoid DCs in a TLR7-dependent manner, and deletion of XIST diminished the ability of whole cellular RNA to activate TLR7. XIST levels were elevated in blood leukocytes from women with SLE compared with controls, correlated positively with disease activity and the IFN signature, and were enriched in extracellular vesicles released from dying cells in vitro. Importantly, XIST was not IFN inducible, suggesting that XIST is a driver, rather than a consequence, of IFN in SLE. Overall, our work elucidated a role for XIST RNA as a female sex-specific danger signal underlying the sex bias in SLE.

Uncoupling interferons and the interferon signature explain clinical and transcriptional subsets in SLE.

Interferons (IFN) are thought to be key players in systemic lupus erythematosus (SLE). The unique and interactive roles of the different IFN families in SLE pathogenesis, however, remain poorly understood. Using reporter cells engineered to precisely quantify IFN-I, IFN-II and IFN-III activity levels in serum/plasma, we found that while IFNs play essential role in SLE pathogenesis and disease activity, they are only significant in specific subsets of patients. Interestingly, whereas IFN-I is the main IFN that governs disease activity in SLE, clinical subsets are defined by the co-elevation of IFN-II and IFN-III. Thus, increased IFN-I alone was only associated with cutaneous lupus. In contrast, systemic features, such as nephritis, were linked to co-elevation of IFN-I plus IFN-II and IFN-III, implying a synergistic effect of IFNs in severe SLE. Intriguingly, while increased IFN-I levels were strongly associated with IFN-induced gene expression (93.5%), in up to 64% of cases, the IFN signature was not associated with IFN-I. Importantly, neither IFN-II nor IFN-III explained IFN-induced gene expression in patients with normal IFN-I levels, and not every feature in SLE was associated with elevated IFNs, suggesting IFN-independent subsets in SLE. Together, the data suggest that, unlike the IFN signature, direct quantification of bioactive IFNs can identify pathogenic and clinically relevant SLE subsets amenable for precise anti-IFN therapies. Since IFN-I is only elevated in a subset of SLE patients expressing the IFN signature, this study explains the heterogeneous response in clinical trials targeting IFN-I, where patients were selected based on IFN-induced gene expression rather than IFN-I levels.

Regulation of Skeletal Muscle Resistance Arteriolar Tone: Integration of Multiple Mechanisms.

INTRODUCTION: Physiological system complexity represents an imposing challenge to gaining insight into how arteriolar behavior emerges. Further, mechanistic complexity in arteriolar tone regulation requires that a systematic determination of how these processes interact to alter vascular diameter be undertaken. METHODS: The present study evaluated the reactivity of ex vivo proximal and in situ distal resistance arterioles in skeletal muscle with challenges across the full range of multiple physiologically relevant stimuli and determined the stability of responses over progressive alterations to each other parameter. The five parameters chosen for examination were (1) metabolism (adenosine concentration), (2) adrenergic activation (norepinephrine concentration), (3) myogenic activation (intravascular pressure), (4) oxygen (superfusate PO2), and (5) wall shear rate (altered intraluminal flow). Vasomotor tone of both arteriole groups following challenge with individual parameters was determined; subsequently, responses were determined following all two- and three-parameter combinations to gain deeper insight into how stimuli integrate to change arteriolar tone. A hierarchical ranking of stimulus significance for establishing arteriolar tone was performed using mathematical and statistical analyses in conjunction with machine learning methods. RESULTS: Results were consistent across methods and indicated that metabolic and adrenergic influences were most robust and stable across all conditions. While the other parameters individually impact arteriolar tone, their impact can be readily overridden by the two dominant contributors. CONCLUSION: These data suggest that mechanisms regulating arteriolar tone are strongly affected by acute changes to the local environment and that ongoing investigation into how microvessels integrate stimuli regulating tone will provide a more thorough understanding of arteriolar behavior emergence across physiological and pathological states.

Toward a 3D physical model of diffusive polymer chains.

Recent studies in polymer physics have created macro-scale analogs to solute microscopic polymer chains like DNA by inducing diffusive motion on a chain of beads. These bead chains have persistence lengths of O(10) links and undergo diffusive motion under random fluctuations like vibration. We present a bead chain model within a new stochastic forcing system: an air fluidizing bed of granular media. A chain of spherical 6 mm resin beads crimped onto silk thread are buffeted randomly by the multiphase flow of grains and low density rising air "bubbles". We "thermalize" bead chains of various lengths at different fluidizing airflow rates, while X-ray imaging captures a projection of the chains' dynamics within the media. With modern 3D printing techniques, we can better represent complex polymers by geometrically varying bead connections and their relative strength, e.g., mimicking the variable stiffness between adjacent nucleotide pairs of DNA. We also develop Discrete Element Method (DEM) simulations to study the 3D motion of the bead chain, where the bead chain is represented by simulated spherical particles connected by linear and angular spring-like bonds. In experiment, we find that the velocity distributions of the beads follow exponential distributions rather than the Gaussian distributions expected from polymers in solution. Through use of the DEM simulation, we find that this difference can likely be attributed to the distributions of the forces imparted onto the chain from the fluidized bed environment. We anticipate expanding this study in the future to explore a wide range of chain composition and confinement geometry, which will provide insights into the physics of large biopolymers.

Colloidal robotics.

Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100 µm, that are small enough that they do not settle out of solution. Colloidal robots are particles capable of functions such as sensing, computation, communication, locomotion and energy management that are all controlled by the particle itself. Their design and synthesis is an emerging area of interdisciplinary research drawing from materials science, colloid science, self-assembly, robophysics and control theory. Many colloidal robot systems approach synthetic versions of biological cells in autonomy and may find ultimate utility in bringing these specialized functions to previously inaccessible locations. This Perspective examines the emerging literature and highlights certain design principles and strategies towards the realization of colloidal robots.