Biology subjects

Little, S.

Publications and source records attributed to Little, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Device-embedded accelerometry complements neural signals for tracking parkinsonian motor states

Adaptive deep brain stimulation (aDBS) relies on physiological biomarkers to infer motor state and guide therapeutic stimulation in Parkinsons disease. However, neural biomarkers may themselves be altered by stimulation, potentially limiting their utility for closed-loop control. We address this limitation by testing whether DBS device-embedded accelerometers can accurately track Parkinsonian motor state across stimulation conditions. We analysed over 1,900 hours of chronic recordings of subthalamic nucleus (STN), sensorimotor cortical and device-embedded accelerometry signals acquired before and during continuous STN stimulation, alongside continuous wearable assessments of bradykinesia and dyskinesia. Across stimulation conditions, accelerometry-derived features robustly tracked motor symptom severity and outperformed neural features for symptom decoding. Mechanistically, total STN beta power - a widely used biomarker for aDBS - proved less informative because it conflates periodic and aperiodic neural processes with opposing relationships to motor state. Under active stimulation, periodic beta activity showed reduced coupling to symptom severity, whereas STN aperiodic activity, cortical periodic activity and cortico-subthalamic coherence remained comparatively stable. Together, these findings demonstrate that neural and behavioural biomarkers exhibit differential robustness during deep brain stimulation and identify device-embedded accelerometry as a robust behavioural biomarker of motor state, motivating its use in next-generation adaptive DBS systems.

bioengineering↗

bioRxiv2026

SARS-CoV-2 Spike H655Y drives protease preference but does not dictate cellular tropism

Throughout the COVID-19 pandemic, SARS-CoV-2 has undergone rapid adaptation, with the Omicron variant exhibiting an unexpected shift towards upper airway infection and preference for membrane fusion activated by endosomal cathepsins, a reversion to ancestral sarbecovirus entry mechanisms. This phenotype coincides with convergent acquisition of the spike mutation H655Y, which reduces TMPRSS2-mediated activation. Here, using a comprehensive panel of 13 spikes of SARS-CoV-2 variants, we interrogated whether H655Y-mediated protease switching explains Omicrons upper airway phenotype, challenging several existing hypotheses, from spike stability, shedding and acquired intra-molecular interactions by H655Y. Our findings reveal that protease preference and tissue tropism are mechanistically uncoupled. While spike pre-processing by furin determines protease preference in pre-Omicron variants, this relationship breaks down in H655Y-bearing viruses. Notably, mutations in the NTD and RBD of BA.2.86 can override the H655Y phenotype entirely, indicating that RBD-mediated interactions, rather than protease usage, represent the critical determinants of Omicrons upper airway adaptation. This work reframes our understanding of coronavirus spike evolution, revealing that tissue tropism operates through mechanisms fundamentally distinct from those dictating protease preference.

microbiology↗

bioRxiv2026

Evexomostat (SDX-7320), a Methionine Aminopeptidase Type 2 (METAP2) Inhibitor, Stimulates Weight Loss and Inhibits Obesity-Accelerated Tumor Growth

Obesity and diabetes are associated with worse prognosis for numerous malignancies. Both insulin resistance and altered levels of adipokines may explain the link between obesity and tumor progression. In preclinical models, METAP2 inhibitors induce weight loss and possess anti-tumor activity, but their effects on obesity-accelerated tumor growth are unknown. Here, we investigated the effects of SDX-7320, a novel polymer-conjugated METAP2 inhibitor, on obesity and obesity-accelerated tumor growth. The anti-obesity and metabolic effects of SDX-7320 were evaluated in diet-induced obese (DIO) mice. Pharmacokinetic-pharmacodynamic relationships for SDX-7320 and the active moiety SDX-7539, a fumagillin class METAP2 inhibitor, were assessed in DIO rats. Anti-tumor efficacy of SDX-7320 was assessed in syngeneic models of obesity-accelerated tumor growth. The anti-tumor efficacy of SDX-7320 and tirzepatide, a weight loss agent, were compared in DIO mice with MC38 tumors. Treatment with SDX-7320 stimulated weight loss in obese mice, increased insulin sensitivity, decreased plasma leptin, and increased plasma adiponectin. Pharmacokinetic-pharmacodynamic analysis showed greater anti-obesity efficacy in response to SDX-7320 than SDX-7539. SDX-7320 significantly attenuated obesity-accelerated tumor growth in three different models (B16F10, EO771, MC38). RNA-Seq analysis of MC38 tumors indicated that SDX-7320 suppressed expression of cell cycle genes (decreased G2M checkpoint and E2F target pathways) and increased expression of host immune response genes (elevated interferon alpha- and gamma-response pathways). In obese mice, SDX-7320 led to significantly greater MC38 tumor growth inhibition than tirzepatide, but caused less weight loss. Plasma metabolomics revealed non-overlapping effects of SDX-7320 and tirzepatide, consistent with different mechanisms of action. Taken together, we have shown for the first time that a METAP2 inhibitor attenuates obesity-accelerated tumor growth. Mechanistically, SDX-7320-mediated tumor growth inhibition likely results from both direct anti-tumor effects (given the observed intratumoral changes in the expression of cell cycle and immune response genes), and indirect effects on the host including weight loss, decreased adipose mass, improved insulin sensitivity and normalization of plasma leptin and adiponectin levels. The fact that SDX-7320 caused greater tumor growth inhibition than tirzepatide, yet caused less weight loss, suggests that direct anti-tumor effects significantly contribute to the anti-tumor activity of SDX-7320.

cancer biology↗

bioRxiv2025

Dynamic neural states underpin bradykinesia severity in Parkinsons disease

BackgroundBradykinesia in Parkinsons disease (PD) may arise due to transient, network-wide neural dynamics that extend beyond beta-band oscillatory activity within the motor cortical-subthalamic nucleus (STN) circuit. MethodsWe address this question by using Hidden Markov Models (HMMs) to identify neural states from chronic motor cortical and STN recordings in five PD patients (1,046 hours from 10 hemispheres), with concurrent measurements of bradykinesia using wearable sensors. FindingsWe identified four neural states with distinct spectral and temporal features. Two states exhibited spectral signatures--particularly STN low and high gamma, STN delta/alpha, cortical beta, and cortico-STN beta coherence--that predicted worsening bradykinesia. However, STN beta power alone was not consistently predictive, challenging traditional beta-centric views. These states also displayed compensatory features associated with bradykinesia amelioration, including cortical delta/alpha activity, cortical high gamma, and cortico-STN high gamma coherence. Two additional states affected bradykinesia through temporal rather than spectral properties. Prolonged lifetimes of one of these state worsened symptoms, whereas increased occurrences of another, marked by local beta without cortico-STN beta coherence, improved motor function. InterpretationOur findings highlight the multidimensional nature of bradykinesia and suggest that state-aware, adaptive interventions targeting state features--rather than single frequency bands--may offer new opportunities for improved deep brain stimulation in PD. FundingAO is supported by an MRC Clinician Scientist Fellowship (MR/W024810/1) and a Rosetrees Trust/Race Against Dementia Team award. BA and AO acknowledge funding support from the Oxford University Hospitals Charity and Jon Moulton Trust. TL acknowledges funding support from the China Scholarship Council. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSPrevious work has demonstrated that subthalamic nucleus oscillatory activity at beta (15-30 Hz) frequencies correlates positively with motor symptoms in Parkinsons disease. This has led to beta activity being used as a biomarker for adaptive Deep Brain Stimulation. It remains unclear however whether other oscillatory features within the broader motor cortical-subthalamic nucleus network could provide improved biomarkers for tracking symptom severity. Added value of this studyWe address this by performing chronic motor cortical and subthalamic nucleus recordings in Parkinsons disease patients during activities of daily living. Simultaneous measurements of symptom severity were captured using wearable sensors. We used Hidden Markov Models to identify transient states of neural activity and related these to symptom severity. Although cortical beta and cortico-STN beta coherence predicted worsening motor symptoms, STN beta activity alone was not a consistent predictor. Interestingly, we identified spectral features associated with motor symptom improvements, including cortical delta/alpha activity, cortical high gamma, and cortico-STN high gamma coherence. Additionally, there was a compensatory state characterised by short-lived cortical and subthalamic nucleus beta activity, whose increased occurrence was associated with symptomatic improvements. Implications of all the available evidenceOur findings highlight the importance of prolonged, high temporal resolution measurements of both neural activity and symptom severity for discovering adaptive Deep Brain Stimulation biomarkers. Crucially, we identify new target states and spectral features for improving motor symptoms in Parkinsons disease.

neuroscience↗

bioRxiv2025

Organellar data sets confirm overall angiosperm relationships if problematic RNA-edit sites are accounted for in mitochondrial genomes

PremisePlastid-based data sets continue to play a major role in our understanding of early flowering-plant relationships, although organellar genomes of major lineages outside the monocots and eudicots remain under-sampled. A tendency of mitochondrial RNA-edit sites to mislead phylogenetic analysis in mixed transcriptomic/genomic data sets needs attention in angiosperm-wide studies, which only rarely consider mitochondrial genomes. MethodsWe compared mitochondrial- vs. plastid-based phylogenomic inferences, examined the effect of removing putative RNA-edit sites from mitochondrial data, and performed combined organellar analysis (plastid plus filtered mitochondrial genomes). We expanded taxon sampling for multiple angiosperm lineages for phylogenomic analysis using both organellar genomes, representing several poorly sampled lineages (in particular Degeneriaceae, Trimeniaceae) with smaller (few-gene) data sets. ResultsPlastid-based inferences recover well-supported relationships that align with and build upon previous studies, and recover well-supported internal relationships for two ANA-grade families (Hydatellaceae, Trimeniaceae) sampled for nearly all species. By contrast, unfiltered mitochondrial inferences of angiosperm phylogeny are generally poorly supported, and recover anomalous relationships compared to plastid-based inferences. However, removing putative mitochondrial RNA-edit sites dramatically reduces inter-organellar conflict and improves overall branch support. ConclusionsWe accounted for phylogenomic discordance between the two organellar genomes regarding overall angiosperm-wide relationships and filled in taxonomic gaps (poorly sampled lineages). Removing RNA edit sites substantially improves congruence in interorganellar inferences by effectively correcting a systematic bias in mitochondrial data. Uncertain relationships persist among five major mesangiosperm lineages in plastid-based inferences, but a clade comprising Chloranthales, Ceratophyllales and eudicots is well supported by filtered mitochondrial data.

plant biology↗

bioRxiv2025

A protective role of REM sleep in the pathological basal ganglia-cortical circuit of Parkinson's disease

Sleep disturbances have been shown to be intimately and bidirectionally related to disease progression across a wide range of neurodegenerative disorders including Parkinsons disease (PD) and Alzheimers disease. However, the precise neurophysiological mechanisms relating abnormal sleep to aberrant daytime network activity that accelerates disease progression has yet to be determined. We collected chronic, multi-night (n=40), intracranial cortico-basal recordings during sleep from a cohort of patients with PD along with paired polysomnography and morning self-reports. This revealed that longer duration (and shorter latency) of rapid eye movement (REM) sleep predicted reduced daytime resting beta (13-30 Hz) activity and cortico-basal functional and effective connectivity, features established to be pathophysiological in PD. Within REM sleep, stronger cortical delta activity specifically predicted reduced pathophysiological cortico-basal neural network features. Additionally, REM delta power significantly predicted greater self-reported morning alertness. These findings highlight a potentially protective role of REM sleep in cortico-basal network health in PD and daytime subjective experience, representing a potential target for closed loop neuromodulation therapies to impact neurodegenerative disease progression.

neuroscience↗

bioRxiv2024

Beta burst characteristics and coupling within the sensorimotor cortical-subthalamic nucleus circuit in Parkinson's disease

BackgroundBursts of exaggerated subthalamic nucleus (STN) beta activity contribute to clinical impairments in Parkinsons disease (PD). Few studies have explored the characteristics and coupling of bursts across the sensorimotor cortical-STN circuit. ObjectiveWe sought to (1) establish the characteristics of sensorimotor cortical and STN bursts during naturalistic behaviours, and (2) determine the predictability of STN bursts from motor cortical recordings. MethodsWe analysed 1,478 hours of wirelessly streamed bilateral sensorimotor cortical and STN recordings from 5 PD patients. ResultsSTN bursts were longer than cortical bursts and had shorter inter-burst intervals. Long bursts (>200ms) in both structures displayed temporal overlap (>30%), with an estimated cortico-STN conduction delay of 8ms. Furthermore, approximately 27% of all STN bursts were preceded by a cortical burst. ConclusionCortical beta bursts tend to precede STN beta bursts, with short delays. However, subcortical mechanisms are also likely to contribute to STN burst initiation and propagation.

neuroscience↗

bioRxiv2024

Learning-related oscillatory dynamics in the human cortico-basal ganglia network during motor sequence initiation in Parkinson's Disease

Learning dexterous motor sequences is crucial to autonomy and quality of life but can be altered in Parkinsons Disease (PD). Learning involves optimizing pre-movement planning (preplanning) of multiple sequence elements to reduce computational overhead during active movement. However, it is unclear which brain regions mediate preplanning or how this process evolves with learning. Recording cortico-basal ganglia field potentials during a multi-day typing task in four individuals with PD, we found evidence for network-wide multi-element preplanning that improved with learning, facilitated by functional connectivity. In both cortex and basal ganglia, pre-movement gamma ({gamma}, 30-250 Hz) activity, historically linked to population spiking, distinguished between future action sequences and became increasingly predictive with learning. For motor cortex {gamma}, this increase was tied to learning-related cross-frequency coupling led by cortically-driven network delta ({delta}, 0.5-4 Hz) synchrony. More generally, coordinated network {delta} supported a complex pattern of learning-driven cross-frequency couplings within and between cortex and basal ganglia, including striatal lead of cortical beta ({beta}, 12-30 Hz) activity, reflecting the specialized roles of these brain regions in motor preparation. In contrast, impaired learning was characterized by practice-driven decreases in {gamma}s predictive value, limited cross-frequency coupling and absent network {delta} synchrony, with network dynamics possibly altered by pathologically high inter-basal ganglia {delta} synchrony. These results suggest that cortically-led {delta} phase coordination optimized cortico-basal ganglia multi-element preplanning through enhanced recruitment of higher-frequency neural activity. Neurostimulation that enhances cortico-basal ganglia {delta} synchrony may thus hold potential for improving skilled fine motor control in PD.

neuroscience↗

bioRxiv2024

β2-Adrenergic Biased Agonist Inhibits the Development of Th17 and the Response of Memory Th17 Cells in an NF-κB-Dependent Manner.

IntroductionAdrenergic receptors regulate metabolic, cardiovascular and immunological functions in response to the sympathetic nervous system. The effect of {beta}2-adrenergic receptor (AR) as a high-expression receptor on different subpopulations of T cells is complex and varies depending on the type of ligand and context. While traditional {beta}2-AR agonists generally suppress T cells, they potentially enhance IL-17A production by Th17 cells. The effects of pharmacological drugs that count as biased agonists of AR like nebivolol are not completely understood. We investigated the impact of nebivolol on human memory CD4+ T (Th1, Th2, Th17) cells and polarized naive Th17 cells highlighting its potential for IL-17A suppression via a non-canonical {beta}2AR cell-signaling pathway. MethodsThe effects of nebivolol were tested on healthy human peripheral blood mononuclear cells, purified memory Th cells, and polarized naive Th17 cells activated with antiCD3/antiCD28/antiCD2 ImmunoCult reagent. IFN-{gamma}, IL-4, and IL-17A which are primarily derived from Th1, Th2, and Th17 cells respectively, were quantified by ELISA and flow cytometry. IL-10 was measured by ELISA. Gene expression of RORC, ADRB1, ADRB2, and ADRB3 was evaluated by qPCR. The ADRB2 gene was knocked out in memory Th cells using CRISPR/Cas9. Protein expression of phosphorylated-serine133-CREB and phosphorylated-NF-{kappa}B p65 was assessed by Western blot. Proliferation was assessed by fluorescent dye loading and flow cytometry. ResultsNebivolol treatment decreased IL-17A and IFN-{gamma} secretion by activated-memory Th cells and elevated IL-4 levels. Nebivolol reduced the proportion of IL-17A+ Th cells and downregulated RORC expression. Unlike the {beta}2-AR agonist terbutaline, nebivolol inhibited the shift of naive CD4+ T cells towards the Th17 phenotype. IL-10 and proliferation index remained unchanged. Nebivolol-treated {beta}2-knockout memory Th cells showed significant inhibition of {beta}2AR-mediated signaling, evidenced by the absence of IL-17A suppression compared to controls. Phosphorylation of the NF-{kappa}B p65 subunit was inhibited by nebivolol, but CREB phosphorylation was not changed, suggesting a selective transcriptional control. ConclusionsThe findings demonstrate that nebivolol acts through a {beta}2-AR-mediated signaling pathway, as a distinctive anti-inflammatory agent capable of selectively shifting Th17 cells and suppressing phosphorylation of NF-{kappa}B. This highlights nebivolols potential for therapeutic interventions in chronic autoimmune conditions with elevated IL-17A levels.

immunology↗

bioRxiv2023

Beta and theta oscillations track effort and previous reward in human basal ganglia and prefrontal cortex during decision making

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we investigate this with chronic intracranial recordings from prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinsons disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12-20 Hz) oscillations tracking subjective effort on a single trial basis and PFC theta (4-7 Hz) signaling previous trial reward. Stimulation of PFC increased overall acceptance of offers in addition to increasing the impact of reward on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, as well as supporting a causal role of PFC for such choices.

neuroscience↗

bioRxiv2023

Predicting Long and Short Duration Beta Bursts from Subthalamic Nucleus Local Field Potential Activity in Parkinson's Disease

Neural activities within the beta frequency range (13-30 Hz) are not stationary, but occur in transient packets known as beta bursts. Parkinsons disease (PD) is characterized by the occurrence of beta bursts of increased duration and amplitude within the cortico-basal ganglia network. The pathophysiological importance of beta bursts is exemplified by the fact that they serve as a clinically useful feedback signal in beta amplitude triggered adaptive Deep Brain Stimulation (aDBS). Prolonged duration beta bursts are closely associated with motor impairments in PD, whilst bursts of shorter duration may have a physiological role. Consequently, we aimed to develop a deep learning-based pipeline capable of predicting long (> 150ms) and short (< 150ms) duration beta bursts from subthalamic nucleus local field potential (LFP) recordings. Our approach achieved promising accuracy values of 87% and 85.2% in two patients implanted with a DBS device that was capable of long-term wireless LFP sensing. Our findings highlight the feasibility of prolonged beta burst prediction and could inform the development of a new type of intelligent DBS approach with the capability of delivering stimulation only during the occurrence of prolonged bursts.

bioengineering↗

bioRxiv2023

Multi-night naturalistic cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings in Parkinson's disease

BackgroundSleep disturbance is a prevalent and highly disabling comorbidity in individuals with Parkinsons disease (PD) that leads to worsening of daytime symptoms, accelerated disease progression and reduced quality of life. ObjectivesWe aimed to investigate changes in sleep neurophysiology in PD particularly during non-rapid eye movement (NREM) sleep, both in the presence and absence of deep brain stimulation (DBS). MethodsMulti-night (n=58) intracranial recordings were performed at-home, from chronic electrocorticography and subcortical electrodes, with sensing-enabled DBS pulse generators, paired with portable polysomnography. Four people with PD and one person with cervical dystonia were evaluated to determine the neural structures, signals and connections modulated during NREM sleep and prior to spontaneous awakenings. Recordings were performed both ON and OFF DBS in the presence of conventional dopaminergic replacement medications. ResultsWe demonstrate an increase in cortico-basal slow wave activity in delta (1-4 Hz) and a decrease in beta (13-31 Hz) during NREM (N2 and N3) versus wakefulness in PD. Cortical-subcortical coherence was also found to be higher in the delta range and lower in the beta range during NREM versus wakefulness. DBS stimulation resulted in a further elevation in cortical delta and a decrease in alpha (8-13 Hz) and low beta (13-15 Hz) power compared to the OFF stimulation state. During NREM sleep, we observed a strong inverse interaction between subcortical beta and cortical slow wave activity and found that subcortical beta increases prior to spontaneous awakenings. ConclusionsChronic, multi-night recordings in PD reveal opposing sleep stage specific modulations of cortico-basal slow wave activity in delta and subcortical beta power and connectivity in NREM, effects that are enhanced in the presence of DBS. Within NREM specifically, subcortical beta and cortical delta are strongly inversely correlated and subcortical beta power is found to increase prior to and predict spontaneous awakenings. We find that DBS therapy appears to improve sleep in PD partially through direct modulation of cortico-basal beta and delta oscillations. Our findings help elucidate a contributory mechanism responsible for sleep disturbances in PD and highlight potential biomarkers for future precision neuromodulation therapies targeting sleep and spontaneous awakenings.

neuroscience↗

bioRxiv2022

High precision magnetoencephalography reveals increased right-inferior frontal gyrus beta power during response conflict

Flexibility of behavior and the ability to rapidly switch actions is critical for adaptive living in humans. It is well established that the right-inferior frontal gyrus (R-IFG) is recruited during outright action-stopping, relating to increased beta (12-30 Hz) power. Additionally, pre-supplementary motor area (pre-SMA) is plausibly recruited during response conflict/switching, relating to increased theta (4-8 Hz) power. It has been posited that inhibiting incorrect response tendencies is central to motor flexibility. However, it is not known if the commonly reported R-IFG beta signature of response inhibition in action-stopping is also recruited during response conflict, which would suggest overlapping networks for stopping and switching. In the current study, we analyzed high precision magnetoencephalography (hpMEG) data recorded with very high trial numbers (total n > 10,000) from 8 subjects during different levels of response conflict. We hypothesized that a R-IFG-triggered network for response inhibition is domain general and also involved in mediating response conflict. We therefore tested whether R-IFG showed increased beta power dependent on the level of response conflict. We also hypothesized that pre-SMA is an important node in response conflict processing, and tested whether pre-SMA theta power increased for response conflict trials. Using event-related spectral perturbations and linear mixed modeling, we found that both R-IFG beta and pre-SMA theta increased for response conflict trials, with the R-IFG beta increase specific to trials with strong response conflict. This result supports a more generalized role for R-IFG beta in response inhibition, beyond simple stopping behavior towards response switching. Significance StatementResponse inhibition is a core component of cognitive control. Neural mechanisms of response inhibition are typically studied using stopping paradigms. However, there is an unresolved debate regarding whether the response inhibition network is specific to stopping or generalizes to switching between tasks and overcoming conflict between competing response tendencies. Increased beta (12-30 Hz) in R-IFG has historically been interpreted as a marker of successful response inhibition in the stop-signal task. Here, we investigated the presence of this electrophysiological marker of response inhibition specifically during response conflict (switching). We found R-IFG beta power increased for trials with strong response conflict, and not for weak or no response conflict, thereby supporting a generalized role for R-IFG beta in response inhibition and switching.

neuroscience↗

bioRxiv2022

Sub-harmonic Entrainment of Cortical Gamma Oscillations to Deep Brain Stimulation in Parkinson's Disease: Predictions and Validation of a Patient-Specific Non-Linear Model

ObjectivesThe exact mechanisms of deep brain stimulation (DBS) are still an active area of investigation, in spite of its clinical successes. This is due in part to the lack of understanding of the effects of stimulation on neuronal rhythms. Entrainment of brain oscillations has been hypothesised as a potential mechanism of neuromodulation. A better understanding of entrainment might further inform existing methods of continuous DBS, and help refine algorithms for adaptive methods. The purpose of this study is to develop and test a theoretical framework to predict entrainment of cortical rhythms to DBS across a wide range of stimulation parameters. Materials and MethodsWe fit a model of interacting neural populations to selected features characterising PD patients off-stimulation finely-tuned gamma rhythm recorded through electrocorticography. Using the fitted models, we predict basal ganglia DBS parameters that would result in 1:2 entrainment, a special case of sub-harmonic entrainment observed in patients and predicted by theory. ResultsWe show that the neural circuit models fitted to patient data exhibit 1:2 entrainment when stimulation is provided across a range of stimulation parameters. Furthermore, we verify key features of the region of 1:2 entrainment in the stimulation frequency/amplitude space with follow-up recordings from the same patients, such as the loss of 1:2 entrainment above certain stimulation amplitudes. ConclusionOur results reveal that continuous, constant frequency DBS in patients may lead to nonlinear patterns of neuronal entrainment across stimulation parameters, and that these responses can be predicted by modelling. Should entrainment prove to be an important mechanism of therapeutic stimulation, our modelling framework may reduce the parameter space that clinicians must consider when programming devices for optimal benefit.

neuroscience↗

bioRxiv2021

Stimulation related artifacts and a multipurpose template-based offline removal solution for a novel sensing-enabled deep brain stimulation device

BackgroundThe Medtronic "Percept" is the first FDA approved deep brain stimulation (DBS) device with sensing capabilities during active stimulation. Its real-world signal recording properties have yet to be fully described. ObjectiveThis study details sources of artifact (and potential mitigations) in local field potential (LFP) signals collected by the Percept, and assesses the potential impact of artifact on the future development of adaptive DBS (aDBS) using this device. MethodsLFP signals were collected from seven subjects in both experimental and clinical settings. The presence of artifacts and their effect on the spectral content of neural signals were evaluated in both the stimulation ON and OFF states using three distinct offline artifact removal techniques. ResultsTemplate subtraction successfully removed multiple sources of artifact, including 1) electrocardiogram (ECG), 2) non-physiologic polyphasic artifacts, and 3) ramping related artifacts seen when changing stimulation amplitudes. ECG removal from stimulation ON (at 0 mA) signals recovered the spectral shape seen when OFF stimulation (averaged difference in normalized power in theta, alpha, and beta bands [≤] 3.5%). ECG removal using singular value decomposition was similarly successful, though required subjective researcher input. QRS interpolation produced similar recovery of beta-band signal, but resulted in residual low-frequency artifact. ConclusionsArtifacts present when stimulation is enabled notably affected the spectral properties of sensed signals using the Percept. Multiple discrete artifacts could be successfully removed offline using an automated template subtraction method. The presence of unrejected artifact likely influences online power estimates, with the potential to affect aDBS algorithm performance.

neuroscience↗

bioRxiv2021

SARS-CoV-2 infection studies in lung organoids identify TSPAN8 as novel mediator

SARS coronavirus-2 (SARS-CoV-2) is causing a global pandemic with large variation in COVID-19 disease spectrum. SARS-CoV-2 infection requires host receptor ACE2 on lung epithelium, but epithelial underpinnings of variation are largely unknown. We capitalized on comprehensive organoid assays to report remarkable variation in SARS-CoV-2 infection rates of lung organoids from different subjects. Tropism is highest for TUBA- and MUC5AC-positive organoid cells, but levels of TUBA-, MUC5A-, or ACE2-positive cells do not predict infection rate. We identify surface molecule Tetraspanin 8 (TSPAN8) as novel mediator of SARS-CoV-2 infection, which is not downregulated by this specific virus. TSPAN8 levels, prior to infection, strongly correlate with infection rate and TSPAN8-blocking antibodies diminish SARS-CoV-2 infection. We propose TSPAN8 as novel functional biomarker and potential therapeutic target for COVID-19.

microbiology↗

bioRxiv2021

Laminar dynamics of beta bursts in human motor cortex

Modulation of motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient bursting events rather than slowly modulating oscillations, suggesting a more rapid, information-encoding functional role than previously believed. Insight into how beta bursts are generated in sensorimotor circuits can provide important constraints to theories about their functional role for movement control. To this end, we leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings.

neuroscience↗

bioRxiv2020

Nup98-dependent transcriptional memory is established independently of transcription

Cellular ability to mount an enhanced transcriptional response upon repeated exposure to external cues has been termed transcriptional memory, which can be maintained epigenetically through cell divisions. The majority of mechanistic knowledge on transcriptional memory has been derived from bulk molecular assays, and this phenomenon has been found to depend on a nuclear pore component Nup98 in multiple species. To gain an alternative perspective on the mechanism and on the contribution of Nup98, we set out to examine single-cell population dynamics of transcriptional memory by monitoring transcriptional behavior of individual Drosophila cells upon initial and subsequent exposures to steroid hormone ecdysone. To this end, we combined single-molecule RNA FISH with mathematical modeling, and found that upon hormone exposure, cells rapidly activate a low-level transcriptional response, but simultaneously, begin a slow transitioning into a specialized memory state, characterized by a high rate of expression. Strikingly, our modeling predicted that this transition between non-memory and memory states is independent of the transcription stemming from initial activation, and we were able to confirm this prediction experimentally by showing that inhibiting transcription during initial ecdysone exposure did not interfere with memory establishment. Together, our findings reveal that Nup98s role in transcriptional memory is to stabilize the forward rate of conversion from low to high expressing state, and that induced genes engage in two separate behaviors - transcription itself and the establishment of epigenetically propagated transcriptional memory.

molecular biology↗