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Background: Slowed balance and mobility after stroke have been well-characterized. Yet the effects of unilateral cortical lesions on whole-body neuromechanical control is poorly understood, despite increased reliance on cortical resources for balance and mobility with aging. Objective. We tested whether individuals post stroke show impaired cortical responses evoked during reactive balance, and the effect of asymmetrical interlimb contributions to balance recovery and the evoked cortical response., Methods: Using electroencephalography, we assessed cortical N1 responses evoked over fronto-midline regions (Cz) during backward support-surface perturbations loading both legs and posterior-lateral directions that preferentially load the paretic or nonparetic leg in individuals' post-stroke and age-matched controls. We tested relationships between cortical responses and clinical balance/mobility function, as well as to center of pressure (CoP) rate of rise (RoR) during balance recovery., Results: Cortical N1 responses were smaller and delayed after stroke ( P  < .047), regardless of perturbation condition. In contrast to controls, slower cortical response latencies associated with lower clinical function in stroke (Mini Balance Evaluation Systems Test: r  = -.61, P  = .007; Timed-Up-and-Go: r  = .53, P  = .024; walking speed: r  = -.46, P  = .055). Paretic-loaded balance recovery revealed slower CoP RoR ( P  = .012) that was associated with delayed cortical response latencies ( r  = -.70, P  = .003); these relationships were not present during bilateral and nonparetic-loaded conditions, nor in the older adults control group., Conclusions: Individuals after stroke may be limited in their balance ability by the slowed speed of their cortical responses to destabilization. In particular, paretic leg loading may reveal cortical response impairments that reflect reduced paretic motor capacity., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The development of reliable and extensible molecular mechanics (MM) force fields-fast, empirical models characterizing the potential energy surface of molecular systems-is indispensable for biomolecular simulation and computer-aided drug design. Here, we introduce a generalized and extensible machine-learned MM force field, espaloma-0.3, and an end-to-end differentiable framework using graph neural networks to overcome the limitations of traditional rule-based methods. Trained in a single GPU-day to fit a large and diverse quantum chemical dataset of over 1.1 M energy and force calculations, espaloma-0.3 reproduces quantum chemical energetic properties of chemical domains highly relevant to drug discovery, including small molecules, peptides, and nucleic acids. Moreover, this force field maintains the quantum chemical energy-minimized geometries of small molecules and preserves the condensed phase properties of peptides and folded proteins, self-consistently parametrizing proteins and ligands to produce stable simulations leading to highly accurate predictions of binding free energies. This methodology demonstrates significant promise as a path forward for systematically building more accurate force fields that are easily extensible to new chemical domains of interest., Competing Interests: J. D. C. is a current member of the Scientific Advisory Board of OpenEye Scientific Software, Redesign Science, Ventus Therapeutics, and Interline Therapeutics, and has equity interests in Redesign Science and Interline Therapeutics. The Chodera laboratory receives or has received funding from multiple sources, including the National Institutes of Health, the National Science Foundation, the Parker Institute for Cancer Immunotherapy, Relay Therapeutics, Entasis Therapeutics, Silicon Therapeutics, EMD Serono (Merck KGaA), AstraZeneca, Vir Biotechnology, Bayer, XtalPi, Interline Therapeutics, the Molecular Sciences Software Institute, the Starr Cancer Consortium, the Open Force Field Consortium, Cycle for Survival, a Louis V. Gerstner Young Investigator Award, and the Sloan Kettering Institute. A complete funding history for the Chodera lab can be found at http://choderalab.org/funding. Y. W. has limited financial interests in Flagship Pioneering, Inc. and its subsidiaries. M. R. S. is an Open Science Fellow with Psivant Sciences and consults for Relay Therapeutics. D. L. M. serves on the scientific advisory boards of Anagenex and OpenEye Scientific Software, Cadence Molecular Sciences, and is an Open Science Fellow with Psivant., (This journal is © The Royal Society of Chemistry.)

Obtaining accurate enthalpies of formation of chemical species, Δ H f , often requires empirical corrections that connect the results of quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state. One approach is to use atomization energy corrections followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) as shown by Buerger et al. We implement both approaches in Arkane, an open-source software that can calculate species thermochemistry using results from various QM software packages. In this work, we collect 421 reference species from the literature to derive Δ H f corrections and fit atomization energy corrections and BACs for 15 commonly used model chemistries. We find that both types of BACs yield similar accuracy, although Anantharaman- and Melius-type BACs appear to generalize better. Furthermore, BACs tend to achieve better accuracy than IDRs for commonly used model chemistries, and IDRs can be less robust because of the sensitivity to the chosen reference species and reactions. Overall, Anantharaman- and Melius-type BACs are our recommended approach for achieving accurate QM corrections for enthalpies.

Background and Purpose: Aerobic exercise can elicit positive effects on neuroplasticity and cognitive executive function but is poorly understood after stroke. We tested the effect of 4 weeks of aerobic exercise training on inhibitory and facilitatory elements of cognitive executive function and electroencephalography markers of cortical inhibition and facilitation. We investigated relationships between stimulus-evoked cortical responses, blood lactate levels during training, and aerobic fitness postintervention., Methods: Twelve individuals with chronic (>6 months) stroke completed an aerobic exercise intervention (40 minutes, 3×/wk). Electroencephalography and motor response times were assessed during congruent (response facilitation) and incongruent (response inhibition) stimuli of a Flanker task. Aerobic fitness capacity was assessed as o2peak during a treadmill test pre- and postintervention. Blood lactate was assessed acutely (<1 minute) after exercise each week. Cortical inhibition (N2) and facilitation (frontal P3) were quantified as peak amplitudes and latencies of stimulus-evoked electroencephalographic activity over the frontal cortical region., Results: Following exercise training, the response inhibition speed increased while response facilitation remained unchanged. A relationship between earlier cortical N2 response and faster response inhibition emerged postintervention. Individuals who produced higher lactate during exercise training achieved faster response inhibition and tended to show earlier cortical N2 responses postintervention. There were no associations between o2peak and metrics of behavioral or neurophysiologic function., Discussion and Conclusions: These preliminary findings provide novel evidence for selective benefits of aerobic exercise on inhibitory control during the initial 4-week period after initiation of exercise training and implicate a potential therapeutic effect of lactate on poststroke inhibitory control., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Academy of Neurologic Physical Therapy, APTA.)

We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property-free knowledge base for future anticoronavirus drug discovery.

The error-related negativity (ERN) is a neural correlate of error monitoring often used to investigate individual differences in developmental, mental health, and adaptive contexts. However, limited experimental control over errors presents several confounds to its measurement. An experimentally controlled disturbance to standing balance evokes the balance N1, which we previously suggested may share underlying mechanisms with the ERN based on a number of shared features and factors. We now measure whether the balance N1 and ERN are correlated across individuals within two small groups (N = 21 young adults and N = 20 older adults). ERNs were measured in arrow flanker tasks using hand and foot response modalities (ERN-hand and ERN-foot). The balance N1 was evoked by sudden slip-like movements of the floor while standing. The ERNs and the balance N1 showed good and excellent internal consistency, respectively, and were correlated in amplitude in both groups. One principal component strongly loaded on all three evoked potentials, suggesting that the majority of individual differences are shared across the three ERPs. However, there remains a significant component of variance shared between the ERN-hand and ERN-foot beyond what they share with the balance N1. It is unclear whether this component of variance is specific to the arrow flanker task, or something fundamentally related to error processing that is not evoked by a sudden balance disturbance. If the balance N1 were to reflect error processing mechanisms indexed by the ERN, balance paradigms offer several advantages in terms of experimental control over errors., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of &gt;130 000 DFT calculations to 10 000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

Mechanisms underlying associations between balance and cognitive impairments in older adults with and without Parkinson's disease are poorly understood. Balance disturbances evoke a cortical N1 response that is associated with both balance and cognitive abilities in unimpaired populations. We hypothesized that the N1 response reflects neural mechanisms that are shared between balance and cognitive function, and would therefore be associated with both balance and cognitive impairments in Parkinson's disease. Although N1 responses did not differ at the group level, they showed different associations with balance and cognitive function in the Parkinson's disease vs. control groups. In the control group, higher N1 amplitudes were correlated with lower cognitive set shifting ability and lower balance confidence. However, in Parkinson's disease, narrower N1 widths (i.e., shorter durations) were associated with greater parkinsonian motor symptom severity, lower balance ability and confidence, lower mobility, and lower overall cognitive function. Despite different relationships across populations, the present results suggest the N1 response reflects neural processes related to both balance and cognitive function. A better understanding of neural mechanisms linking balance and cognitive function could provide insight into associations between balance and cognitive decline in aging populations., (© The Author(s) 2022. Published by Oxford University Press.)

The mechanisms underlying associations between cognitive set shifting impairments and balance dysfunction are unclear. Cognitive set shifting refers to the ability to flexibly adjust behavior to changes in task rules or contexts, which could be involved in flexibly adjusting balance recovery behavior to different contexts, such as the direction the body is falling. Prior studies found associations between cognitive set shifting impairments and severe balance dysfunction in populations experiencing frequent falls. The objective of this study was to test whether cognitive set shifting ability is expressed in successful balance recovery behavior in older adults with high clinical balance ability ( N = 19, 71 ± 7 years, 6 female). We measured cognitive set shifting ability using the Trail Making Test and clinical balance ability using the miniBESTest. For most participants, cognitive set shifting performance (Trail Making Test B-A = 37 ± 20 s) was faster than normative averages (46 s for comparable age and education levels), and balance ability scores (miniBESTest = 25 ± 2/28) were above the threshold for fall risk (23 for people between 70 and 80 years). Reactive balance recovery in response to support-surface translations in anterior and posterior directions was assessed in terms of body motion, muscle activity, and brain activity. Across participants, lower cognitive set shifting ability was associated with smaller peak center of mass displacement during balance recovery, lower directional specificity of late phase balance-correcting muscle activity (i.e., greater antagonist muscle activity 200-300 ms after perturbation onset), and larger cortical N1 responses (100-200 ms). None of these measures were associated with clinical balance ability. Our results suggest that cognitive set shifting ability is expressed in balance recovery behavior even in the absence of profound clinical balance disability. Specifically, our results suggest that lower flexibility in cognitive task performance is associated with lower ability to incorporate the directional context into the cortically mediated later phase of the motor response. The resulting antagonist activity and stiffer balance behavior may help explain associations between cognitive set shifting impairments and frequent falls., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Payne, Palmer, McKay and Ting.)

Dengue virus (DENV) is a worldwide health burden, and a safe vaccine is needed. Neutralizing antibodies bind to quaternary epitopes on DENV envelope (E) protein homodimers. However, recombinantly expressed soluble E proteins are monomers under vaccination conditions and do not present these quaternary epitopes, partly explaining their limited success as vaccine antigens. Using molecular modeling, we found DENV2 E protein mutations that induce dimerization at low concentrations (<100 pM) and enhance production yield by more than 50-fold. Cross-dimer epitope antibodies bind to the stabilized dimers, and a crystal structure resembles the wild-type (WT) E protein bound to a dimer epitope antibody. Mice immunized with the stabilized dimers developed antibodies that bind to E dimers and not monomers and elicited higher levels of DENV2-neutralizing antibodies compared to mice immunized with WT E antigen. Our findings demonstrate the feasibility of using structure-based design to produce subunit vaccines for dengue and other flaviviruses.

Objectives: In this study we wished to determine the rank order of risk factors for endometrial cancer and calculate a pooled risk and percentage risk for each factor using a statistical meta-analysis approach. The next step was to design a neural network computer model to predict the overall increase or decreased risk of cancer for individual patients. This would help to determine whether this prediction could be used as a tool to decide if a patient should be considered for testing and to predict diagnosis, as well as to suggest prevention measures to patients., Design: A meta-analysis of existing data was carried out to calculate relative risk, followed by design and implementation of a risk prediction computational model based on a neural network algorithm., Setting: Meta-analysis data were collated from various settings from around the world. Primary data to test the model were collected from a hospital clinic setting., Participants: Data from 40 patients notes currently suspected of having endometrial cancer and undergoing investigations and treatment were collected to test the software with their cancer diagnosis not revealed to the software developers., Main Outcome Measures: The forest plots allowed an overall relative risk and percentage risk to be calculated from all the risk data gathered from the studies. A neural network computational model to determine percentage risk for individual patients was developed, implemented, and evaluated., Results: The results show that the greatest percentage increased risk was due to BMI being above 25, with the risk increasing as BMI increases. A BMI of 25 or over gave an increased risk of 2.01%, a BMI of 30 or over gave an increase of 5.24%, and a BMI of 40 or over led to an increase of 6.9%. PCOS was the second highest increased risk at 4.2%. Diabetes, which is incidentally also linked to an increased BMI, gave a significant increased risk along with null parity and noncontinuous HRT of 1.54%, 1.2%, and 0.56% respectively. Decreased risk due to contraception was greatest with IUD (intrauterine device) and IUPD (intrauterine progesterone device) at -1.34% compared to -0.9% with oral. Continuous HRT at -0.75% and parity at -0.9% also decreased the risk. Using open-source patient data to test our computational model to determine risk, our results showed that the model is 98.6% accurate with an algorithm sensitivity 75% on average., Conclusions: In this study, we successfully determined the rank order of risk factors for endometrial cancer and calculated a pooled risk and risk percentage for each factor using a statistical meta-analysis approach. Then, using a computer neural network model system, we were able to model the overall increase or decreased risk of cancer and predict the cancer diagnosis for particular patients to an accuracy of over 98%. The neural network model developed in this study was shown to be a potentially useful tool in determining the percentage risk and predicting the possibility of a given patient developing endometrial cancer. As such, it could be a useful tool for clinicians to use in conjunction with other biomarkers in determining which patients warrant further preventative interventions to avert progressing to endometrial cancer. This result would allow for a reduction in the number of unnecessary invasive tests on patients. The model may also be used to suggest interventions to decrease the risk for a particular patient. The sensitivity of the model limits it at this stage due to the small percentage of positive cases in the datasets; however, since this model utilizes a neural network machine learning algorithm, it can be further improved by providing the system with more and larger datasets to allow further refinement of the neural network.

Heightened reliance on the cerebral cortex for postural stability with aging is well-known, yet the cortical mechanisms for balance control, particularly in relation to balance function, remain unclear. Here we aimed to investigate motor cortical activity in relation to the level of balance challenge presented during reactive balance recovery and identify circuit-specific interactions between motor cortex and prefrontal or somatosensory regions in relation to metrics of balance function that predict fall risk. Using electroencephalography, we assessed motor cortical beta power, and beta coherence during balance reactions to perturbations in older adults. We found that individuals with greater motor cortical beta power evoked following standing balance perturbations demonstrated lower general clinical balance function. Individual older adults demonstrated a wide range of cortical responses during balance reactions at the same perturbation magnitude, showing no group-level change in prefrontal- or somatosensory-motor coherence in response to perturbations. However, older adults with the highest prefrontal-motor coherence during the post-perturbation, but not pre-perturbation, period showed greater cognitive dual-task interference (DTI) and elicited stepping reactions at lower perturbation magnitudes. Our results support motor cortical beta activity as a potential biomarker for individual level of balance challenge and implicate prefrontal-motor cortical networks in distinct aspects of balance control involving response inhibition of reactive stepping in older adults. Cortical network activity during balance may provide a neural target for precision-medicine efforts aimed at fall prevention with aging., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Palmer, Payne, Ting and Borich.)

Objective: To evaluate the efficacy of a pediatric headache infusion center (HIC) in alleviating the symptoms and preventing future visits to the emergency department (ED)., Background: Headache is a common reason for visits to the pediatric ED. ED visits are associated with inordinate costs of care and are conceived by parents to be avoidable if adequate alternatives are available. An infusion center for acute treatment of intractable headache in children with chronic migraine may be an effective alternative to an ED visit., Methods: This was a retrospective analysis of data from a single-center cohort of patients with a known history of chronic migraine, presenting to Dayton Children's HIC with an acute migraine from June 1, 2017 to June 1, 2020. Patients were treated according to established protocols divided into two pathways. Patient demographics, clinical characteristics, pre- and postinfusion pain scores, ED visits and inpatient admissions within 2 weeks of HIC visit, and ED visits 1 year prior and 1 year after the HIC visit were noted., Results: A total of 297 HIC visits were analyzed from 201 patients. The HIC was effective in controlling symptoms with a significant reduction in pain score (median [interquartile range; IQR] 7.0 [2.0] preinfusion vs. 1.0 [2.0] postinfusion, p < 0.001). Only 25/297 (8.4%) patients came to the ED within 2 weeks of the HIC visit, and an even smaller number of patients (20/297, 6.7%) were admitted as inpatients within 2 weeks of the HIC visit. The number of ED visits was significantly reduced in the year after the HIC visit compared with the year prior (median [IQR] 1.0 [2.0] before vs. 0.0 [1.0] after, p < 0.001)., Conclusion: A pediatric HIC is effective in alleviating the symptoms and preventing ED visits. These centers should be considered as standard of care at children's hospitals., (© 2021 American Headache Society.)

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

Mutations in the G protein-coupled receptor (GPCR) rhodopsin are a common cause of autosomal dominant retinitis pigmentosa, a blinding disease. Rhodopsin self-associates in the membrane, and the purified monomeric apo-protein opsin dimerizes in vitro as it transitions from detergent micelles to reconstitute into a lipid bilayer. We previously reported that the retinitis pigmentosa-linked F220C opsin mutant fails to dimerize in vitro, reconstituting as a monomer. Using fluorescence-based assays and molecular dynamics simulations we now report that whereas wild-type and F220C opsin display distinct dimerization propensities in vitro as previously shown, they both dimerize in the plasma membrane of HEK293 cells. Unexpectedly, molecular dynamics simulations show that F220C opsin forms an energetically favored dimer in the membrane when compared with the wild-type protein. The conformation of the F220C dimer is unique, with transmembrane helices 5 and 6 splayed apart, promoting widening of the intracellular vestibule of each protomer and influx of water into the protein interior. FRET experiments with SNAP-tagged wild-type and F220C opsin expressed in HEK293 cells are consistent with this conformational difference. We speculate that the unusual mode of dimerization of F220C opsin in the membrane may have physiological consequences.

The cortical N1 response to balance perturbation is observed in electroencephalography recordings simultaneous to automatic balance-correcting muscle activity. We recently observed larger cortical N1s in individuals who had greater difficulty resisting compensatory steps, suggesting the N1 may be influenced by stepping or changes in response strategy. Here, we test whether the cortical N1 response is influenced by stepping (planned steps versus feet-in-place) or prior planning (planned vs. unplanned steps). We hypothesized that prior planning of a step would reduce the amplitude of the cortical N1 response to balance perturbations. In 19 healthy young adults (ages 19-38; 8 men and 11 women), we measured the cortical N1 amplitude evoked by 48 backward translational support-surface perturbations of unpredictable timing and amplitude in a single experimental session. Participants were asked to plan a stepping reaction on half of perturbations, but to resist stepping otherwise. Perturbations included an easy (8 cm, 16 cm/s) perturbation that was identical across participants and did not naturally elicit compensatory steps, and a height-adjusted difficult (18-22 cm, 38-42 cm/s) perturbation that frequently elicited compensatory steps despite instructions to resist stepping. In contrast to our hypothesis, cortical N1 response amplitudes did not differ between planned and unplanned stepping reactions, but cortical responses were 11% larger with the execution of planned compensatory steps compared with nonstepping responses to difficult perturbations. These results suggest a possible role for the cortical N1 in the execution of compensatory steps for balance recovery, and this role is not influenced by whether the compensatory step was planned before the perturbation. NEW & NOTEWORTHY The cortical N1 response to balance perturbation is larger when executing compensatory steps, suggesting a relationship between the cortical N1 and subsequent motor behavior. Additionally, the cortical N1 response is not impacted by prior planning of the stepping reaction, suggesting that predictability of the motor outcome does not impact the N1 in the same way as predictability of the perturbation stimulus.

Cortical beta oscillations (13-30 Hz) reflect sensorimotor processing, but are not well understood in balance recovery. We hypothesized that sensorimotor cortical activity would increase under challenging balance conditions. We predicted greater beta power when balance was challenged, either by more difficult perturbations or by lower balance ability. In 19 young adults, we measured beta power over motor cortical areas (electroencephalography, Cz electrode) during three magnitudes of backward support -surface translations. Peak beta power was measured during early (50-150 ms), late (150-250 ms), and overall (0-400 ms) time bins, and wavelet-based analyses quantified the time course of evoked beta power. An ANOVA was used to compare peak beta power across perturbation magnitudes in each time bin. We further tested the association between perturbation-evoked beta power and individual balance ability measured in a challenging beam walking task. Beta power increased ~50 ms after perturbation, and to a greater extent in larger perturbations. Lower individual balance ability was associated with greater beta power in only the late (150-250 ms) time bin. These findings demonstrate greater sensorimotor cortical engagement under more challenging balance conditions, which may provide a biomarker for reduced automaticity in balance control that could be used in populations with neurological impairments.

Task-level goals such as maintaining standing balance are achieved through coordinated muscle activity. Consistent and individualized groupings of synchronously activated muscles can be estimated from muscle recordings in terms of motor modules or muscle synergies, independent of their temporal activation. The structure of motor modules can change with motor training, neurological disorders, and rehabilitation, but the central and peripheral mechanisms underlying motor module structure remain unclear. To assess the role of peripheral somatosensory input on motor module structure, we evaluated changes in the structure of motor modules for reactive balance recovery following pyridoxine-induced large-fiber peripheral somatosensory neuropathy in previously collected data in four adult cats. Somatosensory fiber loss, quantified by postmortem histology, varied from mild to severe across cats. Reactive balance recovery was assessed using multidirectional translational support-surface perturbations over days to weeks throughout initial impairment and subsequent recovery of balance ability. Motor modules within each cat were quantified by non-negative matrix factorization and compared in structure over time. All cats exhibited changes in the structure of motor modules for reactive balance recovery after somatosensory loss, providing evidence that somatosensory inputs influence motor module structure. The impact of the somatosensory disturbance on the structure of motor modules in well-trained adult cats indicates that somatosensory mechanisms contribute to motor module structure, and therefore may contribute to some of the pathological changes in motor module structure in neurological disorders. These results further suggest that somatosensory nerves could be targeted during rehabilitation to influence pathological motor modules for rehabilitation. NEW & NOTEWORTHY Stable motor modules for reactive balance recovery in well-trained adult cats were disrupted following pyridoxine-induced peripheral somatosensory neuropathy, suggesting somatosensory inputs contribute to motor module structure. Furthermore, the motor module structure continued to change as the animals regained the ability to maintain standing balance, but the modules generally did not recover pre-pyridoxine patterns. These results suggest changes in somatosensory input and subsequent learning may contribute to changes in motor module structure in pathological conditions.

Background: Reactive balance recovery evokes a negative peak of cortical electroencephalography (EEG) activity (N1) that is simultaneous to brainstem-mediated automatic balance-correcting muscle activity. This study follows up on an observation from a previous study, in which N1 responses were larger in individuals who seemed to have greater difficulty responding to support-surface perturbations., Research Question: We hypothesized that people engage more cortical activity when balance recovery is more challenging. We predicted that people with lower balance ability would exhibit larger cortical N1 responses during balance perturbations., Methods: In 20 healthy young adults (11 female, ages 19-38) we measured the amplitude of the cortical N1 response evoked by 48 backward translational support-surface perturbations of unpredictable timing and amplitude. Perturbations included a Small (8 cm) perturbation that was identical across participants, as well as Medium (13-15 cm) and Large (18-22 cm) perturbations scaled to participant height to control for height-related differences in perturbation difficulty. To assess individual differences in balance ability, we measured the distance traversed on a narrow (0.5-inch wide) 12-foot beam across 6 trials. We tested whether the cortical N1 response amplitude was correlated to balance ability across participants., Results: Cortical N1 amplitudes in response to standing balance perturbations (54 ± 18 μV) were inversely correlated to the distance traveled in the difficult beam-walking task (R 2 = 0.20, p = 0.029). Further, there was a significant interaction between performance on the beam-walking task and the effect of perturbation magnitude on the cortical N1 response amplitude, whereby individuals who performed worse on the beam-walking task had greater increases in N1 amplitudes with increases in perturbation magnitude., Significance: Cortical N1 response amplitudes may reflect greater cortical involvement in balance recovery when challenged. This increased cortical involvement may reflect cognitive processes such as greater perceived threat or attention to balance, which have the potential to influence subsequent motor control., Competing Interests: Declaration of Competing Interest No authors have any financial or personal relationship with other people or organizations that could inappropriately influence or bias this work., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Many health professional schools may be investing time and resources on dedicated educational spaces intended to promote collaborative learning. Alone, innovative physical space or technologies are not sufficient to ensure success in this. Lesson plans informed by collaborative praxis, individual motivation, faculty development, learner feedback, and team interactions also play a necessary and substantial role. We have used faculty observations, quantitative and qualitative student evaluation data, and the existing educational literature to provide twelve tips on leveraging curricular content, activity setup, physical space, learner behavior, and faculty facilitation to make the most of collaborative learning spaces.

Catalases are among the main scavengers of reactive oxygen species (ROS) present in the peroxisome, thereby preventing oxidative cellular and tissular damage. In human, multiple diseases are associated with malfunction of these organelles, which causes accumulation of ROS species and consequently the inefficient detoxification of cells. Despite intense research, much remains to be clarified about the precise molecular role of catalase in cellular homeostasis. Yeast peroxisomes and their peroxisomal catalases have been used as eukaryotic models for oxidative metabolism, ROS generation and detoxification, and associated pathologies. In order to provide reliable models for oxidative metabolism research, we have determined the high-resolution crystal structures of peroxisomal catalase from two important biotechnology and basic biology yeast models, Pichia pastoris and Kluyveromyces lactis. We have performed an extensive functional, biochemical and stability characterization of both enzymes in order to establish their differential activity profiles. Furthermore, we have analyzed the role of the peroxisomal catalase under study in the survival of yeast to oxidative burst challenges combining methanol, water peroxide, and sodium chloride. Interestingly, whereas catalase activity was induced 200-fold upon challenging the methylotrophic P. pastoris cells with methanol, the increase in catalase activity in the non-methylotrophic K. lactis was only moderate. The inhibitory effect of sodium azide and β-mercaptoethanol over both catalases was analyzed, establishing IC50 values for both compounds that are consistent with an elevated resistance of both enzymes toward these inhibitors. Structural comparison of these two novel catalase structures allows us to rationalize the differential susceptibility to inhibitors and oxidative bursts. The inherent worth and validity of the P. pastoris and K. lactis yeast models for oxidative damage will be strengthened by the availability of reliable structural-functional information on these enzymes, which are central to our understanding of peroxisomal response toward oxidative stress., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Detecting and correcting errors is essential to successful action. Studies on response monitoring have examined scalp ERPs following the commission of motor slips in speeded-response tasks, focusing on a frontocentral negativity (i.e., error-related negativity or ERN). Sensorimotor neurophysiologists investigating cortical monitoring of reactive balance recovery behavior observe a strikingly similar pattern of scalp ERPs following externally imposed postural errors, including a brief frontocentral negativity that has been referred to as the balance N1. We integrate and review relevant literature from these discrepant fields to suggest shared underlying mechanisms and potential benefits of collaboration across fields. Unlike the cognitive tasks leveraged to study the ERN, balance perturbations afford precise experimental control of postural errors to elicit balance N1s that are an order of magnitude larger than the ERN and drive robust and well-characterized adaptation of behavior within an experimental session. Many factors that modulate the ERN, including motivation, perceived consequences, perceptual salience, expectation, development, and aging, are likewise known to modulate the balance N1. We propose that the ERN and balance N1 reflect common neural activity for detecting errors. Collaboration across fields could help clarify the functional significance of the ERN and poorly understood interactions between motor and cognitive impairments., (© 2019 Society for Psychophysiological Research.)

The role of cortical activity in standing balance is unclear. Here we tested whether perturbation-evoked cortical responses share sensory input with simultaneous balance-correcting muscle responses. We hypothesized that the acceleration-dependent somatosensory signals that drive the initial burst of the muscle automatic postural response also drive the simultaneous perturbation-evoked cortical N1 response. We measured in healthy young adults ( n = 16) the initial burst of the muscle automatic postural response (100-200 ms), startle-related muscle responses (100-200 ms), and the perturbation-evoked cortical N1 potential, i.e., a negative peak in cortical EEG activity (100-200 ms) over the supplementary motor area. Forward and backward translational support-surface balance perturbations were applied at four levels of acceleration and were unpredictable in timing, direction, and acceleration. Our results from averaged and single-trial analyses suggest that although cortical and muscle responses are evoked by the same perturbation stimulus, their amplitudes are independently modulated. Although both muscle and cortical responses increase with acceleration, correlations between single-trial muscle and cortical responses were very weak. Furthermore, across subjects, the scaling of muscle responses to acceleration did not correspond to scaling of cortical responses to acceleration. Moreover, we observed a reduction in cortical response amplitude across trials that was related to a reduction in startle-related-but not balance-correcting-muscle activity. Therefore, cortical response attenuation may be related to a reduction in perceived threat rather than motor adaptation or changes in sensory inflow. We conclude that the cortical N1 reflects integrated sensory inputs simultaneously related to brain stem-mediated balance-correcting muscle responses and startle reflexes. NEW & NOTEWORTHY Reactive balance recovery requires sensory inputs to be transformed into appropriate balance-correcting motor responses via brain stem circuits; these are accompanied by simultaneous and poorly understood cortical responses. We used single-trial analyses to dissociate muscle and cortical response modulation with perturbation acceleration. Although muscle and cortical responses share sensory inputs, they have independent scaling mechanisms. Attenuation of cortical responses with experience reflected attenuation of brain stem-mediated startle responses rather than the amplitude of balance-correcting motor responses.

This paper examines the development and implementation of a health literacy/education station at a large free clinic in a metropolitan city in southern California. The station was made possible through a partnership between the leadership team at the clinic and senior nursing students at a large university located in southern California. This paper outlines the importance of health literacy, the partnership between the community health senior nursing students and faculty and a yearly 3-day health clinic, the Core Competencies of Public Health Nursing met by the event, student preparation prior to the event, outcomes, and recommendations for future clinics and for future collaborations., (© 2018 Wiley Periodicals, Inc.)

We present here the complete genomes of 18 phages that infect Paenibacillus larvae, the causative agent of American foulbrood in honeybees. The phages were isolated between 2014 and 2016 as part of an undergraduate phage discovery course at Brigham Young University. The phages were isolated primarily from bee debris and lysogens.