Embryos assist morphogenesis of others through calcium and ATP signaling mechanisms in collective teratogen resistance

Information for organismal patterning can come from a variety of sources. We investigate the possibility that instructive influences for normal embryonic development are provided not only at the level of cells within the embryo, but also via interactions between embryos. To explore this, we challenge groups of embryos with disruptors of normal development while varying group size. Here, we show that Xenopus laevis embryos are much more sensitive to a diverse set of chemical and molecular-biological perturbations when allowed to develop alone or in small groups, than in large groups. Keeping per-embryo exposure constant, we find that increasing the number of exposed embryos in a cohort increases the rate of survival while incidence of defects decreases. This inter-embryo assistance effect is mediated by short-range diffusible signals and involves the P2 ATP receptor. Our data and computational model emphasize that morphogenesis is a collective phenomenon not only at the level of cells, but also of whole bodies, and that cohort size is a crucial variable in studies of ecotoxicology, teratogenesis, and developmental plasticity.

Target-agnostic drug prediction integrated with medical record analysis uncovers differential associations of statins with increased survival in COVID-19 patients

Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.

Enhancers of Host Immune Tolerance to Bacterial Infection Discovered Using Linked Computational and Experimental Approaches

Current therapeutic strategies against bacterial infections focus on reduction of pathogen load using antibiotics; however, stimulation of host tolerance to infection in the presence of pathogens might offer an alternative approach. Computational transcriptomics and Xenopus laevis embryos are used to discover infection response pathways, identify potential tolerance inducer drugs, and validate their ability to induce broad tolerance. Xenopus exhibits natural tolerance to Acinetobacter baumanii, Klebsiella pneumoniae, Staphylococcus aureus, and Streptococcus pneumoniae bacteria, whereas Aeromonas hydrophila and Pseudomonas aeruginosa produce lethal infections. Transcriptional profiling leads to definition of a 20-gene signature that discriminates between tolerant and susceptible states, as well as identification of a more active tolerance response to gram negative compared to gram positive bacteria. Gene pathways associated with active tolerance in Xenopus, including some involved in metal ion binding and hypoxia, are found to be conserved across species, including mammals, and administration of a metal chelator (deferoxamine) or a HIF-1α agonist (1,4-DPCA) in embryos infected with lethal A. hydrophila increased survival despite high pathogen load. These data demonstrate the value of combining the Xenopus embryo infection model with computational multiomics analyses for mechanistic discovery and drug repurposing to induce host tolerance to bacterial infections.

Target-agnostic drug prediction integrated with medical record analysis uncovers differential associations of statins with increased survival in COVID-19 patients

Importance

Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit.

Objectives

To test if different statins differ in their ability to exert protective effects based on molecular computational predictions and electronic medical record analysis.

Main Outcomes and Measures

A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2, with a total of 2,436 drugs investigated. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus.

Results

Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells.

Conclusions and Relevance

Different statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.

Acute multidrug delivery via a wearable bioreactor facilitates long-term limb regeneration and functional recovery in adult Xenopus laevis

Limb regeneration is a frontier in biomedical science. Identifying triggers of innate morphogenetic responses in vivo to induce the growth of healthy patterned tissue would address the needs of millions of patients, from diabetics to victims of trauma. Organisms such as Xenopus laevis-whose limited regenerative capacities in adulthood mirror those of humans-are important models with which to test interventions that can restore form and function. Here, we demonstrate long-term (18 months) regrowth, marked tissue repatterning, and functional restoration of an amputated X. laevis hindlimb following a 24-hour exposure to a multidrug, pro-regenerative treatment delivered by a wearable bioreactor. Regenerated tissues composed of skin, bone, vasculature, and nerves significantly exceeded the complexity and sensorimotor capacities of untreated and control animals' hypomorphic spikes. RNA sequencing of early tissue buds revealed activation of developmental pathways such as Wnt/β-catenin, TGF-β, hedgehog, and Notch. These data demonstrate the successful "kickstarting" of endogenous regenerative pathways in a vertebrate model.

Studying Protista WBR and Repair Using Physarum polycephalum

Physarum polycephalum is a protist slime mould that exhibits a high degree of responsiveness to its environment through a complex network of tubes and cytoskeletal components that coordinate behavior across its unicellular, multinucleated body. Physarum has been used to study decision making, problem solving, and mechanosensation in aneural biological systems. The robust generative and repair capacities of Physarum also enable the study of whole-body regeneration within a relatively simple model system. Here we describe methods for growing, imaging, quantifying, and sampling Physarum that are adapted for investigating regeneration and repair.

Intra-articular etanercept attenuates pain and hypoxia from TMJ loading in the rat

Mechanical overloading of the temporomandibular joint (TMJ) and biochemical changes, like inflammation and hypoxia, contribute to cartilage degeneration and pain associated with osteoarthritis (OA). Yet, how overloading contributes to early dysregulation of chondrocytes is not understood, limiting the development of diagnostics and treatments for TMJ OA. Hypoxia-inducible factors (HIF)-1α/2α in chondrocytes were evaluated at Days 8 and 15 in a rat TMJ pain model induced by jaw loading (1 h/day for 7 days) using immunohistochemistry and compared between cases that induce persistent (3.5 N), acute (2 N), or no (0 N) sensitivity. Hypoxia was measured on Day 8 by immunolabeling of the tracer EF5 and 18 F-EF5 PET imaging. To assess the role of tumor necrosis factor (TNF) in painful TMJ loading, intra-articular etanercept was given before loading. Orofacial sensitivity was evaluated during and after loading. Facial grimace, TNF-α, HIF-2α, and hypoxia levels in the TMJ were measured after loading. HIF-2α was elevated (P = .03) after 3.5 N loading at Day 8, but HIF-1α was unchanged. EF5 uptake increased on Day 8 in the 3.5 N group (P < .048) by tissue assay and 18 F-EF5 PET. At Day 8, both HIF-2α (P = .01) and EF5 uptake (P = .005) were correlated with loading magnitude. Etanercept attenuated sensitivity (P < .01) and the facial grimace on Day 7 (P = .01). It also reduced (P < .01) HIF-2α and EF5 uptake on Day 8; but TNF-α levels were not different from controls at that time. Findings suggest that TMJ loading that induces persistent sensitivity upregulates the catabolic factor HIF-2α and reduces oxygen levels in the cartilage, which may be TNF-driven.

Lower back pain and healthy subjects exhibit distinct lower limb perturbation response strategies: A preliminary study

BACKGROUND

It is hypothesized that inherent differences in movement strategies exist between control subjects and those with a history of lower back pain (LBP). Previous motion analysis studies focus primarily on tracking spinal movements, neglecting the connection between the lower limbs and spinal function. Lack of knowledge surrounding the functional implications of LBP may explain the diversity in success from general treatments currently offered to LBP patients.

OBJECTIVE

This pilot study evaluated the response of healthy controls and individuals with a history of LBP (hLBP) to a postural disturbance.

METHODS

Volunteers (n= 26) were asked to maintain standing balance in response to repeated balance disturbances delivered via a perturbation platform while both kinematic and electromyographic data were recorded from the trunk, pelvis, and lower limb.

RESULTS

The healthy cohort utilized an upper body-focused strategy for balance control, with substantial activation of the external oblique muscles. The hLBP cohort implemented a lower limb-focused strategy, relying on activation of the semitendinosus and soleus muscles. No significant differences in joint range of motion were identified.

CONCLUSIONS

These findings suggest that particular reactive movement patterns may indicate muscular deficits in subjects with hLBP. Identification of these deficits may aid in developing specific rehabilitation programs to prevent future LBP recurrence.

Experimental Methods to Inform Diagnostic Approaches for Painful TMJ Osteoarthritis

Temporomandibular joint (TMJ) osteoarthritis (OA) is a degenerative disease of the joint that can produce persistent orofacial pain as well as functional and structural changes to its bone, cartilage, and ligaments. Despite advances in the clinical utility and reliability of the Diagnostic Criteria for Temporomandibular Disorders, clinical tools inadequately predict which patients will develop chronic TMJ pain and degeneration, limiting clinical management. The challenges of managing and treating TMJ OA are due, in part, to a limited understanding of the mechanisms contributing to the development and maintenance of TMJ pain. OA is initiated by multiple factors, including injury, aging, abnormal joint mechanics, and atypical joint shape, which can produce microtrauma, remodeling of joint tissues, and synovial inflammation. TMJ microtrauma and remodeling can increase expression of cytokines, chemokines, and catabolic factors that damage synovial tissues and can activate free nerve endings in the joint. Although studies have separately investigated inflammation-driven orofacial pain, acute activity of the trigeminal nerve, or TMJ tissue degeneration and/or damage, the temporal mechanistic factors leading to chronic TMJ pain are undefined. Limited understanding of the interaction between degeneration, intra-articular chemical factors, and pain has further restricted the development of targeted, disease-modifying drugs to help patients avoid long-term pain and invasive procedures, like TMJ replacement. A range of animal models captures features of intra-articular inflammation, joint overloading, and tissue damage. Although those models traditionally measure peripheral sensitivity as a surrogate for pain, recent studies recognize the brain's role in integrating, modulating, and interpreting nociceptive inputs in the TMJ, particularly in light of psychosocial influences on TMJ pain. The articular and neural contributors to TMJ pain, imaging modalities with clinical potential to identify TMJ OA early, and future directions for clinical management of TMJ OA are reviewed in the context of evidence in the field.

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

The Interface of Mechanics and Nociception in Joint Pathophysiology: Insights From the Facet and Temporomandibular Joints

Chronic joint pain is a widespread problem that frequently occurs with aging and trauma. Pain occurs most often in synovial joints, the body's load bearing joints. The mechanical and molecular mechanisms contributing to synovial joint pain are reviewed using two examples, the cervical spinal facet joints and the temporomandibular joint (TMJ). Although much work has focused on the macroscale mechanics of joints in health and disease, the combined influence of tissue mechanics, molecular processes, and nociception in joint pain has only recently become a focus. Trauma and repeated loading can induce structural and biochemical changes in joints, altering their microenvironment and modifying the biomechanics of their constitutive tissues, which themselves are innervated. Peripheral pain sensors can become activated in response to changes in the joint microenvironment and relay pain signals to the spinal cord and brain where pain is processed and perceived. In some cases, pain circuitry is permanently changed, which may be a potential mechanism for sustained joint pain. However, it is most likely that alterations in both the joint microenvironment and the central nervous system (CNS) contribute to chronic pain. As such, the challenge of treating joint pain and degeneration is temporally and spatially complicated. This review summarizes anatomy, physiology, and pathophysiology of these joints and the sensory pain relays. Pain pathways are postulated to be sensitized by many factors, including degeneration and biochemical priming, with effects on thresholds for mechanical injury and/or dysfunction. Initiators of joint pain are discussed in the context of clinical challenges including the diagnosis and treatment of pain.

Mapping of pain circuitry in early post-natal development using manganese-enhanced MRI in rats

Premature or ill full-term infants are subject to a number of noxious procedures as part of their necessary medical care. Although we know that human infants show neural changes in response to such procedures, we know little of the sensory or affective brain circuitry activated by pain. In rodent models, the focus has been on spinal cord and, more recently, midbrain and medulla. The present study assesses activation of brain circuits using manganese-enhanced magnetic resonance imaging (MEMRI). Uptake of manganese, a paramagnetic contrast agent that is transported across active synapses and along axons, was measured in response to a hindpaw injection of dilute formalin in 12-day-old rat pups, the age at which rats begin to show aversion learning and which is roughly the equivalent of full-term human infants. Formalin induced the oft-reported biphasic response at this age and induced a conditioned aversion to cues associated with its injection, thus demonstrating the aversiveness of the stimulation. Morphometric analyses, structural equation modeling and co-expression analysis showed that limbic and sensory paths were activated, the most prominent of which were the prefrontal and anterior cingulate cortices, nucleus accumbens, amygdala, hypothalamus, several brainstem structures, and the cerebellum. Therefore, both sensory and affective circuits, which are activated by pain in the adult, can also be activated by noxious stimulation in 12-day-old rat pups.

Rentian scaling for the measurement of optimal embedding of complex networks into physical space

The London Underground is one of the largest, oldest and most widely used systems of public transit in the world. Transportation in London is constantly challenged to expand and adapt its system to meet the changing requirements of London's populace while maintaining a cost-effective and efficient network. Previous studies have described this system using concepts from graph theory, reporting network diagnostics and core-periphery architecture. These studies provide information about the basic structure and efficiency of this network; however, the question of system optimization in the context of evolving demands is seldom investigated. In this paper we examined the cost effectiveness of the topological-physical embedding of the Tube using estimations of the topological dimension, wiring length and Rentian scaling, an isometric scaling relationship between the number of elements and connections in a system. We measured these properties in both two- and three-dimensional embeddings of the networks into Euclidean space, as well as between two time points, and across the densely interconnected core and sparsely interconnected periphery. While the two- and three-dimensional representations of the present-day Tube exhibit Rentian scaling relationships between nodes and edges of the system, the overall network is approximately cost-efficiently embedded into its physical environment in two dimensions, but not in three. We further investigated a notable disparity in the topology of the network's local core versus its more extended periphery, suggesting an underlying relationship between meso-scale structure and physical embedding. The collective findings from this study, including changes in Rentian scaling over time, provide evidence for differential embedding efficiency in planned versus self-organized networks. These findings suggest that concepts of optimal physical embedding can be applied more broadly to other physical systems whose links are embedded in a well-defined space, and whose topology is constrained by a cost function that minimizes link lengths within that space.