The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-Blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID.

BACKGROUND: Individuals with long COVID lack evidence-based treatments and have difficulty participating in traditional site-based trials. Our digital, decentralized trial investigates the efficacy and safety of nirmatrelvir/ritonavir, targeting viral persistence as a potential cause of long COVID. METHODS: The PAX LC trial (NCT05668091) is a Phase 2, 1:1 randomized, double-blind, superiority, placebo-controlled trial in 100 community-dwelling, highly symptomatic adult participants with long COVID residing in the 48 contiguous US states to determine the efficacy, safety, and tolerability of 15 days of nirmatrelvir/ritonavir compared with placebo/ritonavir. Participants are recruited via patient groups, cultural ambassadors, and social media platforms. Medical records are reviewed through a platform facilitating participant-mediated data acquisition from electronic health records nationwide. During the drug treatment, participants complete daily digital diaries using a web-based application. Blood draws for eligibility and safety assessments are conducted at or near participants' homes. The study drug is shipped directly to participants' homes. The primary endpoint is the PROMIS-29 Physical Health Summary Score difference between baseline and Day 28, evaluated by a mixed model repeated measure analysis. Secondary endpoints include PROMIS-29 (Mental Health Summary Score and all items), Modified GSQ-30 with supplemental symptoms questionnaire, COVID Core Outcome Measures for Recovery, EQ-5D-5L (Utility Score and all items), PGIS 1 and 2, PGIC 1 and 2, and healthcare utilization. The trial incorporates immunophenotyping to identify long COVID biomarkers and treatment responders. CONCLUSION: The PAX LC trial uses a novel decentralized design and a participant-centric approach to test a 15-day regimen of nirmatrelvir/ritonavir for long COVID.

Evaluating the clinical benefit of brain-computer interfaces for control of a personal computer.

Brain-computer interfaces (BCIs) enabling the control of a personal computer could provide myriad benefits to individuals with disabilities including paralysis. However, to realize this potential, these BCIs must gain regulatory approval and be made clinically available beyond research participation. Therefore, a transition from engineering-oriented to clinically oriented outcome measures will be required in the evaluation of BCIs. This review examined how to assess the clinical benefit of BCIs for the control of a personal computer. We report that: (a) a variety of different patient-reported outcome measures can be used to evaluate improvements inhow a patient feels, and we offer some considerations that should guide instrument selection. (b) Activities of daily living can be assessed to demonstrate improvements inhow a patient functions, however, new instruments that are sensitive to increases in functional independence via the ability to perform digital tasks may be needed. (c) Benefits tohow a patient surviveshas not previously been evaluated but establishing patient-initiated communication channels using BCIs might facilitate quantifiable improvements in health outcomes.

Neural representation in M1 and S1 cortex of bilateral hand actions during prehension.

Bimanual movements that require coordinated actions of the two hands may be coordinated by synchronous bilateral activation of somatosensory and motor cortical areas in both hemispheres, by enhanced activation of individual neurons specialized for bimanual actions, or by both mechanisms. To investigate cortical neural mechanisms that mediate unimanual and bimanual prehension, we compared actions of the left and right hands in a reach to grasp-and-pull instructed-delay task. Spike trains were recorded with multiple electrode arrays placed in the hand area of primary motor (M1) and somatosensory (S1) cortex of the right hemisphere in macaques, allowing us to measure and compare the relative timing, amplitude, and synchronization of cortical activity in these areas as animals grasped and manipulated objects that differed in shape and location. We report that neurons in the right hemisphere show common task-related firing patterns for the two hands but actions of the ipsilateral hand elicited weaker and shorter-duration responses than those of the contralateral hand. We report significant bimanual activation of neurons in M1 but not in S1 cortex when animals have free choice of hand use in prehension tasks. Population ensemble responses in M1 thereby provide an accurate depiction of hand actions during skilled manual tasks. These studies also demonstrate that somatosensory cortical areas serve important cognitive and motor functions in skilled hand actions. Bilateral representation of hand actions may serve an important role in "motor equivalence" when the same movements are performed by either hand and in transfer of skill learning between the hands.NEW & NOTEWORTHY Humans can manipulate small objects with the right or left hand but typically select the dominant hand to handle them. We trained monkeys to grasp and manipulate objects with either hand, while recording neural activity in primary motor (M1) and somatosensory (S1) cortex. Actions of both hands activate M1 neurons, but S1 neurons respond only to the contralateral hand. Bilateral sensitivity in M1 may aid skill transfer between hands after stroke or head injury.

Developing a neurobehavioral animal model of poverty: Drawing cross-species connections between environments of scarcity-adversity, parenting quality, and infant outcome.

Children reared in impoverished environments are at risk for enduring psychological and physical health problems. Mechanisms by which poverty affects development, however, remain unclear. To explore one potential mechanism of poverty's impact on social-emotional and cognitive development, an experimental examination of a rodent model of scarcity-adversity was conducted and compared to results from a longitudinal study of human infants and families followed from birth (N = 1,292) who faced high levels of poverty-related scarcity-adversity. Cross-species results supported the hypothesis that altered caregiving is one pathway by which poverty adversely impacts development. Rodent mothers assigned to the scarcity-adversity condition exhibited decreased sensitive parenting and increased negative parenting relative to mothers assigned to the control condition. Furthermore, scarcity-adversity reared pups exhibited decreased developmental competence as indicated by disrupted nipple attachment, distress vocalization when in physical contact with an anesthetized mother, and reduced preference for maternal odor with corresponding changes in brain activation. Human results indicated that scarcity-adversity was inversely correlated with sensitive parenting and positively correlated with negative parenting, and that parenting fully mediated the association of poverty-related risk with infant indicators of developmental competence. Findings are discussed from the perspective of the usefulness of bidirectional-translational research to inform interventions for at-risk families.

Motor cortical networks for skilled movements have dynamic properties that are related to accurate reaching.

Neurons in the Primary Motor Cortex (MI) are known to form functional ensembles with one another in order to produce voluntary movement. Neural network changes during skill learning are thought to be involved in improved fluency and accuracy of motor tasks. Unforced errors during skilled tasks provide an avenue to study network connections related to motor learning. In order to investigate network activity in MI, microwires were implanted in the MI of cats trained to perform a reaching task. Spike trains from eight groups of simultaneously recorded cells (95 neurons in total) were acquired. A point process generalized linear model (GLM) was developed to assess simultaneously recorded cells for functional connectivity during reaching attempts where unforced errors or no errors were made. Whilst the same groups of neurons were often functionally connected regardless of trial success, functional connectivity between neurons was significantly different at fine time scales when the outcome of task performance changed. Furthermore, connections were shown to be significantly more robust across multiple latencies during successful trials of task performance. The results of this study indicate that reach-related neurons in MI form dynamic spiking dependencies whose temporal features are highly sensitive to unforced movement errors.

Statistical inference for assessing functional connectivity of neuronal ensembles with sparse spiking data.

The ability to accurately infer functional connectivity between ensemble neurons using experimentally acquired spike train data is currently an important research objective in computational neuroscience. Point process generalized linear models and maximum likelihood estimation have been proposed as effective methods for the identification of spiking dependency between neurons. However, unfavorable experimental conditions occasionally results in insufficient data collection due to factors such as low neuronal firing rates or brief recording periods, and in these cases, the standard maximum likelihood estimate becomes unreliable. The present studies compares the performance of different statistical inference procedures when applied to the estimation of functional connectivity in neuronal assemblies with sparse spiking data. Four inference methods were compared: maximum likelihood estimation, penalized maximum likelihood estimation, using either l(2) or l(1) regularization, and hierarchical Bayesian estimation based on a variational Bayes algorithm. Algorithmic performances were compared using well-established goodness-of-fit measures in benchmark simulation studies, and the hierarchical Bayesian approach performed favorably when compared with the other algorithms, and this approach was then successfully applied to real spiking data recorded from the cat motor cortex. The identification of spiking dependencies in physiologically acquired data was encouraging, since their sparse nature would have previously precluded them from successful analysis using traditional methods.

A regularized point process generalized linear model for assessing the functional connectivity in the cat motor cortex.

Identification of multiple simultaneously recorded neural spike train recordings is an important task in understanding neuronal dependency, functional connectivity, and temporal causality in neural systems. An assessment of the functional connectivity in a group of ensemble cells was performed using a regularized point process generalized linear model (GLM) that incorporates temporal smoothness or contiguity of the solution. An efficient convex optimization algorithm was then developed for the regularized solution. The point process model was applied to an ensemble of neurons recorded from the cat motor cortex during a skilled reaching task. The implications of this analysis to the coding of skilled movement in primary motor cortex is discussed.