Calcium Regulation of Myosin-I Tension Sensing

AbstractMyo1b is a myosin that is exquisitely sensitive to tension. Its actin-attachment lifetime increases > 50-fold when its working stroke is opposed by 1 pN of force. The long attachment lifetime of myo1b under load raises the question: how are actin attachments that last >50 s in the presence of force regulated? Like most myosins, forces are transmitted to the myo1b motor through a light-chain binding domain that is structurally stabilized by calmodulin, a calcium-binding protein. Thus, we examined the effect of calcium on myo1b motility using ensemble and single-molecule techniques. Calcium accelerates key biochemical transitions on the ATPase pathway, decreases the working-stroke displacement, and greatly reduces the ability of myo1b to sense tension. Thus, calcium provides an effective mechanism for inhibiting motility and terminating long-duration attachments

Electromyography Data Processing Impacts Muscle Synergies during Gait for Unimpaired Children and Children with Cerebral Palsy

Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpretation is important. The aim of this study was to evaluate how EMG signal processing impacts synergy outputs during gait. We evaluated the impacts of two common processing steps for synergy analyses: low pass (LP) filtering and unit variance scaling. We evaluated EMG data collected during barefoot walking from five muscles of 113 children with cerebral palsy (CP) and 73 typically-developing (TD) children. We applied LP filters to the EMG data with cutoff frequencies ranging from 4 to 40 Hz (reflecting the range reported in prior synergy research). We also evaluated the impact of normalizing EMG amplitude by unit variance. We found that the total variance accounted for (tVAF) by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency (e.g., 9.3 percentage points change for one synergy between 4 and 40 Hz). This change in tVAF can alter the number of synergies selected for further analyses. Normalizing tVAF to a z-score (e.g., dynamic motor control index during walking, walk-DMC) reduced sensitivity to LP cutoff. Unit variance scaling caused comparatively small changes in tVAF. Synergy weights and activations were impacted less than tVAF by LP filter choice and unit variance normalization. These results demonstrate that EMG signal processing methods impact outputs of synergy analysis and z-score based measures can assist in reporting and comparing results across studies and clinical centers

Ribose 2′-O-methylation provides a molecular signature for the distinction of self and non-self mRNA dependent on the RNA sensor Mda5

The 5'-cap-structures of higher eukaryote mRNAs are ribose 2'-O-methylated. Likewise, a number of viruses replicating in the cytoplasm of eukayotes have evolved 2'-O-methyltransferases to modify autonomously their mRNAs. However, a defined biological role of mRNA 2'-O-methylation remains elusive. Here we show that viral mRNA 2'-O-methylation is critically involved in subversion of type-I-interferon (IFN-I) induction. We demonstrate that human and murine coronavirus 2'-O-methyltransferase mutants induce increased IFN-I expression, and are highly IFN-I sensitive. Importantly, IFN-I induction by 2'-O-methyltransferase-deficient viruses is dependent on the cytoplasmic RNA sensor melanoma differentiation-associated gene 5 (MDA5). This link between MDA5-mediated sensing of viral RNA and mRNA 2'-O-methylation suggests that RNA modifications, such as 2'-O-methylation, provide a molecular signature for the discrimination of self and non-self mRNA

Is season of birth related to disordered eating and personality in women with eating disorders?

We assessed the relation between season of birth and eating disorder symptoms and personality characteristics in a sample of 880 women with eating disorders and 580 controls from two Price Foundation Studies. Eating disorder symptoms were assessed using the Structured Interview of Anorexic and Bulimic Disorders and the Structured Clinical Interview for DSM-IV. Personality traits were assessed using the Temperament and Character Inventory and the Frost Multidimensional Perfectionism Scale. Date of birth was obtained from a sociodemographic questionnaire. No significant differences were observed 1) in season of birth across eating disorder subtypes and controls; nor 2) for any clinical or personality variables and season of birth. We found no evidence of season of birth variation in eating disorders symptoms or personality traits. Contributing to previous conflicting findings, the present results do not support a season of birth hypothesis for eating disorders

Alternative N-terminal regions of Drosophila myosin heavy chain II regulate communication of the purine binding loop with the essential light chain

We investigated the biochemical and biophysical properties of one of the four alternative exon-encoded regions within the Drosophila myosin catalytic domain. This region is encoded by alternative exons 3a and 3b and includes part of the N-terminal β–barrel. Chimeric myosin constructs (IFI-3a and EMB-3b) were generated by exchanging the exon 3-encoded areas between native slow embryonic body wall (EMB) and fast indirect flight muscle myosin isoforms (IFI). We found that this exchange alters the kinetic properties of the myosin S1 head. The ADP release rate (k-D) in the absence of actin is completely reversed for each chimera compared to the native isoforms. Steady-state data also suggest a reciprocal shift, with basal and actin-activated ATPase activity of IFI-3a showing reduced values compared to wild-type IFI, whereas for EMB-3b these values are increased compared to wild-type EMB. In the presence of actin, ADP affinity (KAD) is unchanged for IFI-3a, compared to IFI, but ADP-affinity for EMB-3b is increased, compared to EMB, and shifted towards IFI values. ATP-induced dissociation of acto-S1 (K1k+2) is reduced for both exon 3 chimeras. Homology modeling, combined with a recently reported crystal structure for Drosophila EMB, indicate that the exon 3 encoded region in the myosin head is part of the communication pathway between the nucleotide binding pocket (purine-binding loop) and the essential light chain, emphasizing an important role for this variable N-terminal domain in regulating acto-myosin cross-bridge kinetics, in particular with respect to the force-sensing properties of myosin isoforms

Rescue therapy for vasospasm following aneurysmal subarachnoid hemorrhage:a propensity score-matched analysis with machine learning

OBJECTIVE Rescue therapies have been recommended for patients with angiographic vasospasm (aVSP) and delayed cerebral ischemia (DCI) following subarachnoid hemorrhage (SAH). However, there is little evidence from randomized clinical trials that these therapies are safe and effective. The primary aim of this study was to apply game theory-based methods in explainable machine learning (ML) and propensity score matching to determine if rescue therapy was associated with better 3-month outcomes following post-SAH aVSP and DCI. The authors also sought to use these explainable ML methods to identify patient populations that were more likely to receive rescue therapy and factors associated with better outcomes after rescue therapy. METHODS Data for patients with aVSP or DCI after SAH were obtained from 8 clinical trials and 1 observational study in the Subarachnoid Hemorrhage International Trialists repository. Gradient boosting ML models were constructed for each patient to predict the probability of receiving rescue therapy and the 3-month Glasgow Outcome Scale (GOS) score. Favorable outcome was defined as a 3-month GOS score of 4 or 5. Shapley Additive Explanation (SNAP) values were calculated for each patient-derived model to quantify feature importance and interaction effects. Variables with high S HAP importance in predicting rescue therapy administration were used in a propensity score-matched analysis of rescue therapy and 3-month GOS scores. RESULTS The authors identified 1532 patients with aVSP or DCI. Predictive, explainable ML models revealed that aneurysm characteristics and neurological complications, but not admission neurological scores, carried the highest relative importance rankings in predicting whether rescue therapy was administered. Younger age and absence of cerebral ischemia/ infarction were invariably linked to better rescue outcomes, whereas the other important predictors of outcome varied by rescue type (interventional or noninterventional). In a propensity score-matched analysis guided by SHAP-based variable selection, rescue therapy was associated with higher odds of 3-month GOS scores of 4-5 (OR 1.63, 95% CI 1.22-2.17). CONCLUSIONS Rescue therapy may increase the odds of good outcome in patients with aVSP or DCI after SAH. Given the strong association between cerebral ischemia/infarction and poor outcome, trials focusing on preventative or therapeutic interventions in these patients may be most able to demonstrate improvements in clinical outcomes. Insights developed from these models may be helpful for improving patient selection and trial design

Integrating plant physiology into simulation of fire behavior and effects

Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine-scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process-based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future

Brain correlates of non-symbolic numerosity estimation in low and high mathematical ability children

Previous studies have implicated several brain areas as subserving numerical approximation. Most studies have examined brain correlates of adult numerical approximation and have not considered individual differences in mathematical ability. The present study examined non-symbolic numerical approximation in two groups of 10-year-olds: Children with low and high mathematical ability. The aims of this study were to investigate the brain mechanisms associated with approximate numerosity in children and to assess whether individual differences in mathematical ability are associated with differential brain correlates during the approximation task. The results suggest that, similarly to adults, multiple and distributed brain areas are involved in approximation in children. Despite equal behavioral performance, there were differences in the brain activation patterns between low and high mathematical ability groups during the approximation task. This suggests that individual differences in mathematical ability are reflected in differential brain response during approximation