Investigating the Brain Mechanisms of Externally Cued Sit-to-Stand Movement in Parkinson's Disease.

BACKGROUND: One of the more challenging daily-life actions for Parkinson's disease patients is starting to stand from a sitting position. Parkinson's disease patients are known to have difficulty with self-initiated movements and benefit from external cues. However, the brain processes underlying external cueing as an aid remain unknown. The advent of mobile electroencephalography (EEG) now enables the investigation of these processes in dynamic sit-to-stand movements. OBJECTIVE: To identify cortical correlates of the mechanisms underlying auditory cued sit-to-stand movement in Parkinson's disease. METHODS: Twenty-two Parkinson's disease patients and 24 healthy age-matched participants performed self-initiated and externally cued sit-to-stand movements while cortical activity was recorded through 32-channel mobile EEG. RESULTS: Overall impaired integration of sensory and motor information can be seen in the Parkinson's disease patients exhibiting less modulation in the θ band during movement compared to healthy age-matched controls. How Parkinson's disease patients use external cueing of sit-to-stand movements can be seen in larger high ß power over sensorimotor brain areas compared to healthy controls, signaling sensory integration supporting the maintenance of motor output. This appears to require changes in cognitive processing to update the motor plan, reflected in frontal θ power increases in Parkinson's disease patients when cued. CONCLUSION: These findings provide the first neural evidence for why and how cueing improves motor function in sit-to-stand movement in Parkinson's disease. The Parkinson's disease patients' neural correlates indicate that cueing induces greater activation of motor cortical areas supporting the maintenance of a more stable motor output, but involves the use of cognitive resources to update the motor plan. © 2024 International Parkinson and Movement Disorder Society.

Neural correlates of motor imagery and execution in real-world dynamic behavior: evidence for similarities and differences.

A large body of evidence shows that motor imagery and action execution behaviors result from overlapping neural substrates, even in the absence of overt movement during motor imagery. To date it is unclear how neural activations in motor imagery and execution compare for naturalistic whole-body movements, such as walking. Neuroimaging studies have not directly compared imagery and execution during dynamic walking movements. Here we recorded brain activation with mobile EEG during walking compared to during imagery of walking, with mental counting as a control condition. We asked 24 healthy participants to either walk six steps on a path, imagine taking six steps, or mentally count from one to six. We found beta and alpha power modulation during motor imagery resembling action execution patterns; a correspondence not found performing the control task of mental counting. Neural overlap occurred early in the execution and imagery walking actions, suggesting activation of shared action representations. Remarkably, a distinctive walking-related beta rebound occurred both during action execution and imagery at the end of the action suggesting that, like actual walking, motor imagery involves resetting or inhibition of motor processes. However, we also found that motor imagery elicits a distinct pattern of more distributed beta activity, especially at the beginning of the task. These results indicate that motor imagery and execution of naturalistic walking involve shared motor-cognitive activations, but that motor imagery requires additional cortical resources.

Identifying the impact of non-pharmaceutical interventions on RSV transmission in a single-centre observational study.

During the COVID-19 pandemic, the introduction of non-pharmaceutical interventions (NPIs) resulted in an unprecedented reduction in the transmission of the respiratory syncytial virus (RSV), the predominant cause of bronchiolitis. As NPIs were eased, it was speculated that RSV transmission would return with an increase in the severity of bronchiolitis. In a large tertiary hospital, a dramatic reduction in the incidence of bronchiolitis was seen during the COVID-19 pandemic. The easing of NPIs correlated with an increase in RSV transmission particularly in the community; however, there was no evidence of an increase in the severity of bronchiolitis.

An update on lipophilic efficiency as an important metric in drug design.

INTRODUCTION: Lipophilic efficiency (LipE) and lipophilic metabolic efficiency (LipMetE) are valuable tools that can be utilized as part of a multiparameter optimization process to advance a hit to a clinical quality compound. AREAS COVERED: This review covers recent, effective use cases of LipE and LipMetE that have been published in the literature over the past 5 years. These use cases resulted in the delivery of high-quality molecules that were brought forward to in vivo work and/or to clinical studies. The authors discuss best-practices for using LipE and LipMetE analysis, combined with lipophilicity-focused compound design strategies, to increase the speed and effectiveness of the hit to clinical quality compound optimization process. EXPERT OPINION: It has become well established that increasing LipE and LipMetE within a series of analogs facilitates the improvement of broad selectivity, clearance, solubility, and permeability and, through this optimization, also facilitates the achievement of desired pharmacokinetic properties, efficacy, and tolerability. Within this article, we discuss lipophilic efficiency-focused optimization as a tool to yield high-quality potential clinical candidates. It is suggested that LipE/LipMetE-focused optimization can facilitate and accelerate the drug-discovery process.

Extended reality to assess post-stroke manual dexterity: contrasts between the classic box and block test, immersive virtual reality with controllers, with hand-tracking, and mixed-reality tests.

BACKGROUND: Recent technological advancements present promising opportunities to enhance the frequency and objectivity of functional assessments, aligning with recent stroke rehabilitation guidelines. Within this framework, we designed and adapted different manual dexterity tests in extended reality (XR), using immersive virtual reality (VR) with controllers (BBT-VR-C), immersive VR with hand-tracking (BBT-VR-HT), and mixed-reality (MD-MR). OBJECTIVE: This study primarily aimed to assess and compare the validity of the BBT-VR-C, BBT-VR-HT and MD-MR to assess post-stroke manual dexterity. Secondary objectives were to evaluate reliability, usability and to define arm kinematics measures. METHODS: A sample of 21 healthy control participants (HCP) and 21 stroke individuals with hemiparesis (IHP) completed three trials of the traditional BBT, the BBT-VR-C, BBT-VR-HT and MD-MR. Content validity of the different tests were evaluated by asking five healthcare professionals to rate the difficulty of performing each test in comparison to the traditional BBT. Convergent validity was evaluated through correlations between the scores of the traditional BBT and the XR tests. Test-retest reliability was assessed through correlations between the second and third trial and usability was assessed using the System Usability Scale (SUS). Lastly, upper limb movement smoothness (SPARC) was compared between IHP and HCP for both BBT-VR test versions. RESULTS: For content validity, healthcare professionals rated the BBT-VR-HT (0[0-1]) and BBT-MR (0[0-1]) as equally difficult to the traditional BBT, whereas they rated BBT-VR-C as more difficult than the traditional BBT (1[0-2]). For IHP convergent validity, the Pearson tests demonstrated larger correlations between the scores of BBT and BBT-VR-HT (r = 0.94;p < 0.001), and BBT and MD-MR (r = 0.95;p < 0.001) than BBT and BBT-VR-C (r = 0.65;p = 0.001). BBT-VR-HT and MD-MR usability were both rated as excellent, with median SUS scores of 83[57.5-91.3] and 83[53.8-92.5] respectively. Excellent reliability was found for the BBT-VR-C (ICC = 0.96;p < 0.001), BBT-VR-HT (ICC = 0.96;p < 0.001) and BBT-MR (ICC = 0.99;p < 0.001). The usability of the BBT-VR-C was rated as good with a median SUS of 70[43.8-83.8]. Upper limb movements of HCP were significantly smoother than for IHP when completing either the BBT-VR-C (t = 2.05;p = 0.043) and the BBT-VR-HT (t = 5.21;p < 0.001). CONCLUSION: The different XR manual tests are valid, short-term reliable and usable tools to assess post-stroke manual dexterity. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT04694833 ; Unique identifier: NCT04694833, Date of registration: 11/24/2020.

Ocean climate and hydrodynamics drive decadal shifts in Northeast Atlantic dinoflagellates.

The abundance of large marine dinoflagellates has declined in the North Sea since 1958. Although hypotheses have been proposed to explain this diminution (increasing temperature and wind), the mechanisms behind this pattern have thus far remained elusive. In this article, we study the long-term changes in dinoflagellate biomass and biodiversity in relation to hydro-climatic conditions and circulation within the North Atlantic. Our results show that the decline in biomass has paralleled an increase in biodiversity caused by a temperature-induced northward movement of subtropical taxa along the European shelf-edge, and facilitated by changes in oceanic circulation (subpolar gyre contraction). However, major changes in North Atlantic hydrodynamics in the 2010s (subpolar gyre expansion and low-salinity anomaly) stopped this movement, which triggered a biodiversity collapse in the North Sea. Further, North Sea dinoflagellate biomass remained low because of warming. Our results, therefore, reveal that regional climate warming and changes in oceanic circulation strongly influenced shifts in dinoflagellate biomass and biodiversity.

Next-Generation Nanopore Sensors Based on Conductive Pulse Sensing for Enhanced Detection of Nanoparticles.

Nanopore sensing has been successfully used to characterize biological molecules with single-molecule resolution based on the resistive pulse sensing approach. However, its use in nanoparticle characterization has been constrained by the need to tailor the nanopore aperture size to the size of the analyte, precluding the analysis of heterogeneous samples. Additionally, nanopore sensors often require the use of high salt concentrations to improve the signal-to-noise ratio, which further limits their ability to study a wide range of nanoparticles that are unstable at high ionic strength. Here, a new paradigm in nanopore research that takes advantage of a polymer electrolyte system to comprise a conductive pulse sensing approach is presented. A finite element model is developed to explain the conductive pulse signals observed and compare these results with experiments. This system enables the analytical characterization of heterogeneous nanoparticle mixtures at low ionic strength . Furthermore, the wide applicability of the method is demonstrated by characterizing metallic nanospheres of varied sizes, plasmonic nanostars with various degrees of branching, and protein-based spherical nucleic acids with different oligonucleotide loadings. This system will complement the toolbox of nanomaterials characterization techniques to enable real-time optimization workflow for engineering a wide range of nanomaterials.

Characterizing neurocognitive impairments in Parkinson's disease with mobile EEG when walking and stepping over obstacles.

The neural correlates that help us understand the challenges that Parkinson's patients face when negotiating their environment remain under-researched. This deficit in knowledge reflects the methodological constraints of traditional neuroimaging techniques, which include the need to remain still. As a result, much of our understanding of motor disorders is still based on animal models. Daily life challenges such as tripping and falling over obstacles represent one of the main causes of hospitalization for individuals with Parkinson's disease. Here, we report the neural correlates of naturalistic ambulatory obstacle avoidance in Parkinson's disease patients using mobile EEG. We examined 14 medicated patients with Parkinson's disease and 17 neurotypical control participants. Brain activity was recorded while participants walked freely, and while they walked and adjusted their gait to step over expected obstacles (preset adjustment) or unexpected obstacles (online adjustment) displayed on the floor. EEG analysis revealed attenuated cortical activity in Parkinson's patients compared to neurotypical participants in theta (4-7 Hz) and beta (13-35 Hz) frequency bands. The theta power increase when planning an online adjustment to step over unexpected obstacles was reduced in Parkinson's patients compared to neurotypical participants, indicating impaired proactive cognitive control of walking that updates the online action plan when unexpected changes occur in the environment. Impaired action planning processes were further evident in Parkinson's disease patients' diminished beta power suppression when preparing motor adaptation to step over obstacles, regardless of the expectation manipulation, compared to when walking freely. In addition, deficits in reactive control mechanisms in Parkinson's disease compared to neurotypical participants were evident from an attenuated beta rebound signal after crossing an obstacle. Reduced modulation in the theta frequency band in the resetting phase across conditions also suggests a deficit in the evaluation of action outcomes in Parkinson's disease. Taken together, the neural markers of cognitive control of walking observed in Parkinson's disease reveal a pervasive deficit of motor-cognitive control, involving impairments in the proactive and reactive strategies used to avoid obstacles while walking. As such, this study identified neural markers of the motor deficits in Parkinson's disease and revealed patients' difficulties in adapting movements both before and after avoiding obstacles in their path.

NIMBUS study protocol: a single-centre feasibility study of non-invasive monitoring with bowel ultrasound in paediatric inflammatory bowel disease.

INTRODUCTION: Incidence of inflammatory bowel disease (IBD) is increasing in childhood and treatment increasingly targets mucosal healing. Monitoring bowel inflammation requires endoscopy or MRI enterography which are invasive, expensive and have long waiting lists.We aim to examine the feasibility of a non-invasive monitoring tool-bowel ultrasound (BUS)-in children with IBD and explore correlations with inflammatory markers and disease activity measures. Some BUS criteria have been found to correlate with these markers; however, this has not been validated in children.We aim to examine the feasibility of BUS for monitoring inflammation in this population; highlighting useful parameters for this purpose. We aim to inform a larger scale randomised controlled trial using BUS. METHODS AND ANALYSIS: This prospective observational feasibility study will be carried out over 24 months at the Noah's Ark Children's Hospital for Wales, Cardiff; with the endpoint recruitment of 50 participants. Children aged 2-18 years with a modified Porto criteria diagnosis of IBD will be included.Patients without IBD or who have previously undergone IBD-related surgery will be excluded; as will families unable to give informed consent.Ultrasound scan images and reports will be collected, as well as laboratory results and clinical outcomes.The primary aim will assess the feasibility of targeted BUS for disease monitoring; including recruitment statistics. The secondary aims will involve data collection and correlation analysis for targeted ultrasound parameters, biomarkers, disease activity scores and prediction of changes in treatment. The statistical methods will include: feasibility metrics, descriptive statistics, cross-tabulation and χ2 analysis, correlation analysis, regression analysis. ETHICS AND DISSEMINATION: Ethical approval is granted by NHS Research Ethics Committee. The sponsor is Cardiff and Vale University Health Board. We will publish the results in a peer-reviewed medical journal. TRIAL REGISTRATION NUMBER: NCT05673278.

Measuring the impact of deprivation on learning difficulties and behaviour among infants born preterm: A cohort study.

BACKGROUND: Preterm birth and social deprivation are known risk factors for learning difficulties. However there has been little work looking into the interaction between these two risks. We aimed to identify if children born preterm to families with higher levels of social deprivation are disproportionately more likely to have learning difficulties than those with lower levels of social deprivation. METHODS: Data from the RANOPS (Respiratory And Neurological Outcomes in children born Preterm Study) was used to assess prevalence of learning difficulties. The effects of preterm birth and deprivation were reviewed. Multi-level logistic regression models were used to examine if gestational age and deprivation impacts interacted after adjustment for possible confounders. Primary outcome measure was parent-reported learning difficulties. Secondary outcome measures were parent-reported behavioural problems and a statement of special educational need. RESULTS: We investigated the developmental outcomes of 6,691 infants with a median age of 5 years at time of survey (IQR 5). Deprivation decile (OR 1.08 (1.03,1.12)) and preterm birth (OR 2.67 (2.02,3.53)) were both associated with increased risk of learning difficulties. There was little evidence for any interaction between preterm birth and deprivation (p = 0.298) and the risk of learning difficulties. CONCLUSIONS: Deprivation and preterm birth have significant associations with learning difficulties. While deprivation does not appear to have potentiated the impact of preterm birth, preterm infants in the most deprived areas have the highest risk of learning difficulties with almost 1 in 3 extremely premature infants with a learning difficulty in the most deprived areas.

A feature and conjunction visual search immersive virtual reality serious game for measuring spatial and distractor inhibition attention using response time and action kinematics.

BACKGROUND: Treisman (1980) proposed that visual-spatial attention to targets presented with distractors involves parallel and serial cognition. When the target is different from distractors by a single feature, the number of distractors does not influence search speed (parallel). However, when the target is different from the distractor by a conjunction of features, increased numbers of distractors increase task difficulty (serial). Here, we developed a serious game in immersive virtual reality (IVR) for evaluating spatial and distractor inhibition attention. METHODS: We tested 60 healthy participants. They performed the serious game in which they had to find a target mole wearing a red miner's helmet. In the single feature parallel conditions, the distractor moles wore blue (miner's or horned) helmets, and in the conjunction feature serial conditions, the distractor moles wore blue miner's helmets or red horned helmets. There were 11-17-23 distractors. Responses were made with the dominant hand by hitting the target with a virtual hammer. We measured mean response time (RT), mean velocity (MV) and coefficient of variance of speed (CV). RESULTS: Participants were significantly slower (RT and MV) and showed greater CV when responding to targets in conjunction compared to single feature search tasks. Further, participants were slower (RT and MV) and showed greater CV when the number of distractors increased. A significant interaction between search tasks and distractors showed that RT and CV only increased with distractor number for the conjunction search tasks. MV decreased with distractor number for both single and conjunction tasks, with a stronger decrease for conjunction relative to single feature search. CONCLUSION: The results replicated previous findings, providing support for the use of immersive virtual reality technology for the simultaneous evaluation of spatial and distractor inhibition attention using complex 3D objects.

Evaluating Analytical Expressions for Scanning Electrochemical Cell Microscopy (SECCM).

Scanning electrochemical cell microscopy (SECCM) maps the electrochemical activity of a surface with nanoscale resolution using an electrolyte-filled nanopipette. The meniscus at the end of the pipet is sequentially placed at an array of locations across the surface, forming a series of nanometric electrochemical cells where the current-voltage response is measured. Quantitative interpretation of these responses typically employs numerical modeling to solve the coupled equations of transport and electron transfer, which require costly software or self-written code. Expertise and time are required to build and solve numerical models, which must be rerun for each new experiment. In contrast, algebraic expressions directly relate the current response to physical parameters. They are simpler to use, faster to calculate, and can provide greater insight but frequently require simplifying assumptions. In this work, we provide algebraic expressions for current and concentration distributions in SECCM experiments, which are formulated by approximating the pipet and meniscus using 1-D spherical coordinates. Expressions for the current and concentration distributions as a function of experimental parameters and in various conditions (steady state and time dependent, diffusion limited, and including migration) all show excellent agreement with numerical simulations employing a full geometry. Uses of the analytical expressions include determination of expected currents in experiments and quantifying electron-transfer rate constants in SECCM experiments.

Phytoplankton life strategies, phenological shifts and climate change in the North Atlantic Ocean from 1850 to 2100.

Significant phenological shifts induced by climate change are projected within the phytoplankton community. However, projections from current Earth System Models (ESMs) understandably rely on simplified community responses that do not consider evolutionary strategies manifested as various phenotypes and trait groups. Here, we use a species-based modelling approach, combined with large-scale plankton observations, to investigate past, contemporary and future phenological shifts in diatoms (grouped by their morphological traits) and dinoflagellates in three key areas of the North Atlantic Ocean (North Sea, North-East Atlantic and Labrador Sea) from 1850 to 2100. Our study reveals that the three phytoplanktonic groups exhibit coherent and different shifts in phenology and abundance throughout the North Atlantic Ocean. The seasonal duration of large flattened (i.e. oblate) diatoms is predicted to shrink and their abundance to decline, whereas the phenology of slow-sinking elongated (i.e. prolate) diatoms and of dinoflagellates is expected to expand and their abundance to rise, which may alter carbon export in this important sink region. The increase in prolates and dinoflagellates, two groups currently not considered in ESMs, may alleviate the negative influence of global climate change on oblates, which are responsible of massive peaks of biomass and carbon export in spring. We suggest that including prolates and dinoflagellates in models may improve our understanding of the influence of global climate change on the biological carbon cycle in the oceans.

Mechanistic Study of the Conductance and Enhanced Single-Molecule Detection in a Polymer-Electrolyte Nanopore.

Solid-state nanopores have been widely employed in the detection of biomolecules, but low signal-to-noise ratios still represent a major obstacle in the discrimination of nucleic acid and protein sequences substantially smaller than the nanopore diameter. The addition of 50% poly(ethylene) glycol (PEG) to the external solution is a simple way to enhance the detection of such biomolecules. Here, we demonstrate with finite-element modeling and experiments that the addition of PEG to the external solution introduces a strong imbalance in the transport properties of cations and anions, drastically affecting the current response of the nanopore. We further show that the strong asymmetric current response is due to a polarity-dependent ion distribution and transport at the nanopipette tip region, leading to either ion depletion or enrichment for few tens of nanometers across its aperture. We provide evidence that a combination of the decreased/increased diffusion coefficients of cations/anions in the bath outside the nanopore and the interaction between a translocating molecule and the nanopore-bath interface is responsible for the increase in the translocation signals. We expect this new mechanism to contribute to further developments in nanopore sensing by suggesting that tuning the diffusion coefficients of ions could enhance the sensitivity of the system.

Design and Synthesis of Functionally Active 5-Amino-6-Aryl Pyrrolopyrimidine Inhibitors of Hematopoietic Progenitor Kinase 1.

Immune activating agents represent a valuable class of therapeutics for the treatment of cancer. An area of active research is expanding the types of these therapeutics that are available to patients via targeting new biological mechanisms. Hematopoietic progenitor kinase 1 (HPK1) is a negative regulator of immune signaling and a target of high interest for the treatment of cancer. Herein, we present the discovery and optimization of novel amino-6-aryl pyrrolopyrimidine inhibitors of HPK1 starting from hits identified via virtual screening. Key components of this discovery effort were structure-based drug design aided by analyses of normalized B-factors and optimization of lipophilic efficiency.

Simulation of the cyclic voltammetric response of an outer-sphere redox species with inclusion of electrical double layer structure and ohmic potential drop.

A finite-element model has been developed to simulate the cyclic voltammetric (CV) response of a planar electrode for a 1e outer-sphere redox process, which fully accounts for cell electrostatics, including ohmic potential drop, ion migration, and the structure of the potential-dependent electric double layer. Both reversible and quasi-reversible redox reactions are treated. The simulations compute the time-dependent electric potential and ion distributions across the entire cell during a voltammetric scan. In this way, it is possible to obtain the interdependent faradaic and non-faradaic contributions to a CV and rigorously include all effects of the electric potential distribution on the rate of electron transfer and the local concentrations of the redox species Oz and Rz-1. Importantly, we demonstrate that the driving force for electron transfer can be different to the applied potential when electrostatic interactions are included. We also show that the concentrations of Oz and Rz-1 at the plane of electron transfer (PET) significantly depart from those predicted by the Nernst equation, even when the system is characterised by fast electron transfer/diffusion control. A mechanistic rationalisation is also presented as to why the electric double layer has a negligible effect on the CV response of such reversible systems. In contrast, for quasi-reversible electron transfer the concentrations of redox species at the PET are shown to play an important role in determining CV wave shape, an effect also dependant on the charge of the redox species and the formal electrode potential of the redox couple. Failure to consider electrostatic effects could lead to incorrect interpretation of electron-transfer kinetics from the CV response. Simulated CVs at scan rates between 0.1 and 1000 V s-1 are found to be in good agreement with experimental data for the reduction of 1.0 mM Ru(NH3)63+ at a 2 mm diameter gold disk electrode in 1.0 M potassium nitrate.

Performing a shortened version of the Action Research Arm Test in immersive virtual reality to assess post-stroke upper limb activity.

BACKGROUND: To plan treatment and measure post-stroke recovery, frequent and time-bounded functional assessments are recommended. With increasing needs for neurorehabilitation advances, new technology based methods, such as virtual reality (VR) have emerged. Here, we developed an immersive VR version of the Action Research Arm Test (ARAT-VR) to complement neurorehabilitation. OBJECTIVE: This study aimed to assess the validity, usability and test-retest reliability of the ARAT-VR among individuals with stroke, healthcare professionals and healthy control subjects (HCS). METHODS: Among the 19 items of the ARAT, 13 items were selected and developed in immersive VR. 11 healthcare professionals, 30 individuals with stroke, and 25 HCS were recruited. Content validity was assessed by asking healthcare professionals to rate the difficulty of performing each item of the ARAT-VR in comparison to the classical Action Research Arm Test (ARAT-19). Concurrent validity was first measured using correlation (Spearman tests) between the ARAT-VR and ARAT-19 scores for the individuals with stroke, and second through correlation and comparison between the scores of the ARAT-VR and the reduced version of the ARAT (ARAT-13) for both individuals with stroke and HCS (Wilcoxon signed rank tests and Bland-Altman plots). Usability was measured using the System Usability Scale. A part of individuals with stroke and HCS were re-tested following a convenient delay to measure test-retest reliability (Intra-class correlation and Wilcoxon tests). RESULTS: Regarding the content validity, median difficulty of the 13 ARAT-VR items (0[0 to - 1] to 0[0-1]) evaluated by healthcare professionals was rated as equivalent to the classical ARAT for all tasks except those involving the marbles. For these, the difficulty was rated as superior to the real tasks (1[0-1] when pinching with the thumb-index and thumb-middle fingers, and 1[0-2] when pinching with thumb-ring finger). Regarding the concurrent validity, for paretic hand scores, there were strong correlations between the ARAT-VR and ARAT-13 (r = 0.84), and between the ARAT-VR and ARAT-19 (r = 0.83). Usability (SUS = 82.5[75-90]) and test-retest reliability (ICC = 0.99; p < 0.001) were excellent. CONCLUSION: The ARAT-VR is a valid, usable and reliable tool that can be used to assess upper limb activity among individuals with stroke, providing potential to increase assessment frequency, remote evaluation, and improve neurorehabilitation. Trial registration https://clinicaltrials.gov/ct2/show/NCT04694833 ; Unique identifier: NCT04694833, Date of registration: 11/24/2020.

Probing RNA Conformations Using a Polymer-Electrolyte Solid-State Nanopore.

Nanopore systems have emerged as a leading platform for the analysis of biomolecular complexes with single-molecule resolution. The conformation of biomolecules, such as RNA, is highly dependent on the electrolyte composition, but solid-state nanopore systems often require high salt concentration to operate, precluding analysis of macromolecular conformations under physiologically relevant conditions. Here, we report the implementation of a polymer-electrolyte solid-state nanopore system based on alkali metal halide salts dissolved in 50% w/v poly(ethylene) glycol (PEG) to augment the performance of our system. We show that polymer-electrolyte bath governs the translocation dynamics of the analyte which correlates with the physical properties of the salt used in the bath. This allowed us to identify CsBr as the optimal salt to complement PEG to generate the largest signal enhancement. Harnessing the effects of the polymer-electrolyte, we probed the conformations of the Chikungunya virus (CHIKV) RNA genome fragments under physiologically relevant conditions. Our system was able to fingerprint CHIKV RNA fragments ranging from ∼300 to ∼2000 nt length and subsequently distinguish conformations between the co-transcriptionally folded and the natively refolded ∼2000 nt CHIKV RNA. We envision that the polymer-electrolyte solid-state nanopore system will further enable structural and conformational analyses of individual biomolecules under physiologically relevant conditions.

Finite Element Modeling of the Combined Faradaic and Electrostatic Contributions to the Voltammetric Response of Monolayer Redox Films.

The voltammetric response of electrodes coated with a redox-active monolayer is computed by finite element simulations based on a generalized model that couples the Butler-Volmer, Nernst-Planck, and Poisson equations. This model represents the most complete treatment of the voltammetric response of a redox film to date and is made accessible to the experimentalist via the use of finite element modeling and a COMSOL-generated report. The model yields a full description of the electric potential and charge distributions across the monolayer and bulk solution, including the potential distribution associated with ohmic resistance. In this way, it is possible to properly account for electrostatic effects at the molecular film/electrolyte interface, which are present due to the changing charge states of the redox head groups as they undergo electron transfer, under both equilibrium and nonequilibrium conditions. Specifically, our numerical simulations significantly extend previous theoretical predictions by including the effects of finite electron-transfer rates (k0) and electrolyte conductivity. Distortion of the voltammetric wave due to ohmic potential drop is shown to be a function of electrolyte concentration and scan rate, in agreement with experimental observations. The commonly used Laviron analysis for the determination of k0 fails to account for ohmic drop effects, which may be non-negligible at high scan rates. This model provides a more accurate alternative for k0 determination at all scan rates. The electric potential and charge distributions across an electrochemically inactive monolayer and electrolyte solution are also simulated as a function of applied potential and are found to agree with the Gouy-Chapman-Stern theory.

The neural response is heightened when watching a person approaching compared to walking away: Evidence for dynamic social neuroscience.

The action observation network has been proposed to play a key role in predicting the action intentions (or goals) of others, thereby facilitating social interaction. Key information when interacting with others is whether someone (an agent) is moving towards or away from us, indicating whether we are likely to interact with the person. In addition, to determine the nature of a social interaction, we also need to take into consideration the distance of the agent relative to us as the observer. How this kind of information is processed within the brain is unknown, at least in part because prior studies have not involved live whole-body motion. Consequently, here we recorded mobile EEG in 18 healthy participants, assessing the neural response to the modulation of direction (walking towards or away) and distance (near vs. far distance) during the observation of an agent walking. We evaluated whether cortical alpha and beta oscillations were modulated differently by direction and distance during action observation. We found that alpha was only modulated by distance, with a stronger decrease of power when the agent was further away from the observer, regardless of direction. Critically, by contrast, beta was found to be modulated by both distance and direction, with a stronger decrease of power when the agent was near and facing the participant (walking towards) compared to when they were near but viewed from the back (walking away). Analysis revealed differences in both the timing and distribution of alpha and beta oscillations. We argue that these data suggest a full understanding of action observation requires a new dynamic neuroscience, investigating actual interactions between real people, in real world environments.