Mechanical ventilation in a conscious male during exercise: A case report.

We recently explored the cardiopulmonary interactions during partial unloading of the respiratory muscles during exercise. Expanding upon this work, we present a noteworthy case study whereby we eliminated the influence of respiration on cardiac function in a conscious but mechanically ventilated human during exercise. This human was a young healthy endurance-trained male who was mechanically ventilated during semi-recumbent cycle exercise at 75 Watts (W) (~30% Wmax). During mechanically ventilated exercise, esophageal pressure was reduced to levels indistinguishable from the cardiac artefact which led to a 94% reduction in the work of breathing. The reduction in respiratory pressures and respiratory muscle work led to a decrease in cardiac output (-6%), which was due to a reduction in stroke volume (-13%), left ventricular end-diastolic volume (-15%) and left-ventricular end-systolic volume (-17%) that was not compensated for by heart rate. Our case highlights the influence of extreme mechanical ventilation on cardiac function while noting the possible presence of a maximal physiological limit to which respiration (and its associated pressures) impacts cardiac function when the work of breathing is maximally reduced.

Perpetual step-like restructuring of hippocampal circuit dynamics.

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we found that CA1 population vectors decorrelated gradually within a session. In contrast, individual neurons exhibited predominantly step-like emergence and disappearance of place fields or sustained change in within-field firing. The changes were not restricted to particular parts of the maze or trials and did not require apparent behavioral changes. The same place fields emerged, disappeared, and reappeared across days, suggesting that the hippocampus reuses pre-existing assemblies, rather than forming new fields de novo. Our results suggest an internally-driven perpetual step-like reorganization of the neuronal assemblies.

Plant-microbe interactions through a lens: tales from the mycorrhizosphere.

BACKGROUND: The soil microbiome plays a pivotal role in maintaining ecological balance, supporting food production, preserving water quality and safeguarding human health. Understanding the intricate dynamics within the soil microbiome necessitates unravelling complex bacterial-fungal interactions (BFIs). BFIs occur in diverse habitats, such as the phyllosphere, rhizosphere and bulk soil, where they exert substantial influence on plant-microbe associations, nutrient cycling and overall ecosystem functions. In various symbiotic associations, fungi form mycorrhizal connections with plant roots, enhancing nutrient uptake through the root and mycorrhizal pathways. Concurrently, specific soil bacteria, including mycorrhiza helper bacteria, play a pivotal role in nutrient acquisition and promoting plant growth. Chemical communication and biofilm formation further shape plant-microbial interactions, affecting plant growth, disease resistance and nutrient acquisition processes. SCOPE: Promoting synergistic interactions between mycorrhizal fungi and soil microbes holds immense potential for advancing ecological knowledge and conservation. However, despite the significant progress, gaps remain in our understanding of the evolutionary significance, perception, functional traits and ecological relevance of BFIs. Here we review recent findings obtained with respect to complex microbial communities - particularly in the mycorrhizosphere - and include the latest advances in the field, outlining their profound impacts on our understanding of ecosystem dynamics and plant physiology and function. CONCLUSIONS: Deepening our understanding of plant BFIs can help assess their capabilities with regard to ecological and agricultural safe-guarding, in particular buffering soil stresses, and ensuring sustainable land management practices. Preserving and enhancing soil biodiversity emerge as critical imperatives in sustaining life on Earth amidst pressures of anthropogenic climate change. A holistic approach integrates scientific knowledge on bacteria and fungi, which includes their potential to foster resilient soil ecosystems for present and future generations.

Mucoromycotina 'fine root endophytes': a new molecular model for plant-fungal mutualisms?

The most studied plant-fungal symbioses to date are the interactions between plants and arbuscular mycorrhizal (AM) fungi of the Glomeromycotina clade. Advancements in phylogenetics and microbial community profiling have distinguished a group of symbiosis-forming fungi that resemble AM fungi as belonging instead to the Mucoromycotina. These enigmatic fungi are now known as Mucoromycotina 'fine root endophytes' and could provide a means to understand the origins of plant-fungal symbioses. Most of our knowledge of the mechanisms of fungal symbiosis comes from investigations using AM fungi. Here, we argue that inclusion of Mucoromycotina fine root endophytes in future studies will expand our understanding of the mechanisms, evolution, and ecology of plant-fungal symbioses.

Large-scale manufacturing of base-edited chimeric antigen receptor T cells.

Base editing is a revolutionary gene-editing technique enabling the introduction of point mutations into the genome without generating detrimental DNA double-stranded breaks. Base-editing enzymes are commonly delivered in the form of modified linear messenger RNA (mRNA) that is costly to produce. Here, we address this problem by developing a simple protocol for manufacturing base-edited cells using circular RNA (circRNA), which is less expensive to synthesize. Compared with linear mRNA, higher editing efficiencies were achieved with circRNA, enabling an 8-fold reduction in the amount of RNA required. We used this protocol to manufacture a clinical dose (1 × 108 cells) of base-edited chimeric antigen receptor (CAR) T cells lacking expression of the inhibitory receptor, PD-1. Editing efficiencies of up to 86% were obtained using 0.25 µg circRNA/1 × 106 cells. Increased editing efficiencies with circRNA were attributed to more efficient translation. These results suggest that circRNA, which is less expensive to produce than linear mRNA, is a viable option for reducing the cost of manufacturing base-edited cells at scale.

Remapping in a recurrent neural network model of navigation and context inference.

Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ('remap') in response to changing contextual factors such as environmental cues, task conditions, and behavioral states, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.

Genome-wide association study of chronic sputum production implicates loci involved in mucus production and infection.

BACKGROUND: Chronic sputum production impacts on quality of life and is a feature of many respiratory diseases. Identification of the genetic variants associated with chronic sputum production in a disease agnostic sample could improve understanding of its causes and identify new molecular targets for treatment. METHODS: We conducted a genome-wide association study (GWAS) of chronic sputum production in UK Biobank. Signals meeting genome-wide significance (p<5×10-8) were investigated in additional independent studies, were fine-mapped and putative causal genes identified by gene expression analysis. GWASs of respiratory traits were interrogated to identify whether the signals were driven by existing respiratory disease among the cases and variants were further investigated for wider pleiotropic effects using phenome-wide association studies (PheWASs). RESULTS: From a GWAS of 9714 cases and 48 471 controls, we identified six novel genome-wide significant signals for chronic sputum production including signals in the human leukocyte antigen (HLA) locus, chromosome 11 mucin locus (containing MUC2, MUC5AC and MUC5B) and FUT2 locus. The four common variant associations were supported by independent studies with a combined sample size of up to 2203 cases and 17 627 controls. The mucin locus signal had previously been reported for association with moderate-to-severe asthma. The HLA signal was fine-mapped to an amino acid change of threonine to arginine (frequency 36.8%) in HLA-DRB1 (HLA-DRB1*03:147). The signal near FUT2 was associated with expression of several genes including FUT2, for which the direction of effect was tissue dependent. Our PheWAS identified a wide range of associations including blood cell traits, liver biomarkers, infections, gastrointestinal and thyroid-associated diseases, and respiratory disease. CONCLUSIONS: Novel signals at the FUT2 and mucin loci suggest that mucin fucosylation may be a driver of chronic sputum production even in the absence of diagnosed respiratory disease and provide genetic support for this pathway as a target for therapeutic intervention.

REFINE-Lung implements a novel multi-arm randomised trial design to address possible immunotherapy overtreatment.

Increasing evidence suggests that some immunotherapy dosing regimens for patients with advanced cancer could result in overtreatment. Given the high costs of these agents, and important implications for quality of life and toxicity, new approaches are needed to identify and reduce unnecessary treatment. Conventional two-arm non-inferiority designs are inefficient in this context because they require large numbers of patients to explore a single alternative to the standard of care. Here, we discuss the potential problem of overtreatment with anti-PD-1 directed agents in general and introduce REFINE-Lung (NCT05085028), a UK multicentre phase 3 study of reduced frequency pembrolizumab in advanced non-small-cell lung cancer. REFINE-Lung uses a novel multi-arm multi-stage response over continuous interventions (MAMS-ROCI) design to determine the optimal dose frequency of pembrolizumab. Along with a similarly designed basket study of patients with renal cancer and melanoma, REFINE-Lung and the MAMS-ROCI design could contribute to practice-changing advances in patient care and form a template for future immunotherapy optimisation studies across cancer types and indications. This new trial design is applicable to many new or existing agents for which optimisation of dose, frequency, or duration of therapy is desirable.

Equity Lens Protocol: Reflecting on Harms From the COVID-19 Response and Mitigation Strategies Implemented in a Local Public Health System.

This report describes an Equity Lens Protocol and its use to guide partners' systematic reflection on harms and mitigation strategies of the COVID-19 response in a local public health system. This process evaluation tool is based on the Guidance document for assuring an equitable response to COVID-19 prepared by the Pan American Health Organization. We used a participatory approach to engage public health partners in systematically reflecting on harms, mitigation strategies, and lessons learned and implications for practice. Outputs from using this tool included identified: (a) specific harms (e.g., loss of income and challenges to learning) related to particular COVID-19 response measures (e.g., home confinement and school closure) and (b) mitigation strategies implemented to reduce harms. In response to the protocol's guiding questions, partners also identified lessons learned and practice recommendations for strengthening equity work in public health responses (e.g., an equitable response requires an investment in people, structures, and relationships before a crisis). This report-and accompanying protocol-illustrates use of a practical method for systematic reflection on public health responses through an equity lens.

Does a change in end-tidal carbon dioxide level predict high altitude mountain sickness?

Background: It is postulated that lack of hypoxic ventilatory response is a predictor for AMS. End-tidal carbon dioxide (ETCO2) is an accurate, noninvasive surrogate measure of ventilation. Objectives: We sought to determine if changes in baseline ETCO2 predicts the development of AMS. Methods: This prospective cohort study took place in three separate high-altitude hiking treks. Subjects included a convenience sample of hikers. Predictor variable was change in ETCO2 levels and outcome variable was AMS. Measurements of ETCO2 levels were obtained at the base and repeated daily at various elevations and the summit of each hike. Concurrently, hikers were scored for AMS by a trained investigator. We utilized correlation coefficients and developed a linear regression model for analysis. Results: 21 subjects in 3 separate hikes participated: 10 ascended to 19,341 ft over 7 days, 6 ascended to 8900 ft in 1 day, and 4 ascended to 11,006 ft in 1 day. Mean age was 40 years, 67% were males, mean daily elevation gain was 2150 ft, and 5 hikers developed AMS. The correlation coefficients for ETCO2 and development of AMS were -0.46 (95%CI -0.33 to -0.57), and -0.77 (95%CI -0.71 to -0.83) for ETCO2 and altitude. ETCO2 predicted the development of symptoms better than the elevation with AUCs of 0.90 (95%CI 0.81-0.99) versus 0.64 (95%CI 0.45-0.83). An ETCO2 measurement of ≤22 mmHg was 100% sensitive and 60% specific for predicting AMS. Conclusions: ETCO2 was strongly correlated with altitude and moderately correlated with AMS and it was a better predictor than altitude.

Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools.

Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chromatography (LC), but choosing the 'correct' pipeline isn't straight-forward. This tutorial, in conjunction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide exploratory analysis in order to inform decision-making regarding costly and time-consuming downstream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software.

Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness.

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Remapping in a recurrent neural network model of navigation and context inference.

Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ("remap") in response to changing contextual factors such as environmental cues, task conditions, and behavioral state, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.

DeepPheWAS: an R package for phenotype generation and association analysis for phenome-wide association studies.

SUMMARY: DeepPheWAS is an R package for phenome-wide association studies that creates clinically curated composite phenotypes and integrates quantitative phenotypes from primary care data, longitudinal trajectories of quantitative measures, disease progression and drug response phenotypes. Tools are provided for efficient analysis of association with any genetic input, under any genetic model, with optional sex-stratified analysis, and for developing novel phenotypes. AVAILABILITY AND IMPLEMENTATION: The DeepPheWAS R package is freely available under GNU general public licence v3.0 from at https://github.com/Richard-Packer/DeepPheWAS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Machine learning dissection of human accelerated regions in primate neurodevelopment.

Using machine learning (ML), we interrogated the function of all human-chimpanzee variants in 2,645 human accelerated regions (HARs), finding 43% of HARs have variants with large opposing effects on chromatin state and 14% on neurodevelopmental enhancer activity. This pattern, consistent with compensatory evolution, was confirmed using massively parallel reporter assays in chimpanzee and human neural progenitor cells. The species-specific enhancer activity of HARs was accurately predicted from the presence and absence of transcription factor footprints in each species. Despite these striking cis effects, activity of a given HAR sequence was nearly identical in human and chimpanzee cells. This suggests that HARs did not evolve to compensate for changes in the trans environment but instead altered their ability to bind factors present in both species. Thus, ML prioritized variants with functional effects on human neurodevelopment and revealed an unexpected reason why HARs may have evolved so rapidly.

How do States Inform Nurses of Their Policies for Mandatory Reporting of Child Maltreatment?

Every state includes nurses as mandated reporters of suspected child maltreatment, and each state has its own law and policy regarding what is reportable and reporting requirements. These differences mean that generic training on child abuse and reporting needs to be augmented by practical state-specific information. In nearly every study of nurses, participants report having inadequate child abuse training. This paper presents an analysis of the information states post on their websites to educate nurses to appropriately identify and report suspected child abuse or neglect. Specifically, this study aims to answer the following questions: (1) how do mandated reporting laws that apply to nurses vary by state, (2) what information do states provide on their child protection and Board of Nursing websites about child maltreatment and mandatory reporting, and (3) what training resources do states make available on their websites to educate nurse mandatory reporters to ably fulfill their obligation? Data on state-by-state practices regarding mandated reporting of child abuse were gathered from the Rape, Abuse, & Incest National Network (RAINN) database, review of state statutes, Child Welfare Information Gateway, Board of Nursing sites, and the Nursing Licensure Compact (NLC) website. This analysis found that states provide little guidance or education about their child maltreatment laws, and few have resources targeted for nurses. Given rising membership in the NLC it is critical for nurses to have education about state specific mandated reporting requirements. States should consider adding mandatory reporting training as a requirement for licensure and for continuing education.

Statistical neuroscience in the single trial limit.

Individual neurons often produce highly variable responses over nominally identical trials, reflecting a mixture of intrinsic 'noise' and systematic changes in the animal's cognitive and behavioral state. Disentangling these sources of variability is of great scientific interest in its own right, but it is also increasingly inescapable as neuroscientists aspire to study more complex and naturalistic animal behaviors. In these settings, behavioral actions never repeat themselves exactly and may rarely do so even approximately. Thus, new statistical methods that extract reliable features of neural activity using few, if any, repeated trials are needed. Accurate statistical modeling in this severely trial-limited regime is challenging, but still possible if simplifying structure in neural data can be exploited. We review recent works that have identified different forms of simplifying structure - including shared gain modulations across neural subpopulations, temporal smoothness in neural firing rates, and correlations in responses across behavioral conditions - and exploited them to reveal novel insights into the trial-by-trial operation of neural circuits.

Comparing root exudate collection techniques: An improved hybrid method.

1. Plant-microbe interactions are critical for ecosystem functioning and drive rhizosphere processes. Root exudates are an important soil carbon (C) input, as well as a mechanism for communication between plants and rhizosphere microbes, but are notoriously difficult to extract and characterise. Common methods produce either substantial noise from the soil or do not mimic natural systems. Optimising methods for root exudate collection in soil is crucial for advancing our understanding of root-microbe interactions under changing environmental conditions. 2. Hybrid root exudate collection methods, where plants are grown in soil and transferred to hydroponics for exudate collection after root washing, might offer an ecologically relevant alternative to existing approaches. However, this method causes potential root damage as well as osmosis and subsequent leaking of cell contents. Here, we assessed different 'root recovery' periods after root washing and before hybrid root exudate collection, by comparing root exudate quantity and quality with both damaged root extracts and with leachates collected from the intact root-soil system. This was done across three common grassland species representing three functional groups. 3. We found that root exudate profiles of the shortest recovery period (0 days) were similar to damaged root extracts and were very high in C. With an increasing period of root recovery, profiles were more similar to leachates collected from the intact root-soil system, and C concentrations decreased. While both hybrid and leachate collection methods separated species by their root exudate profiles, the hybrid method was less variable in terms of the amount of C measured and provided a more diverse and abundant metabolome with better identification of metabolites. 4. Our results show that a recovery period after root washing of at least 3 days is critical to prevent root damage bias in hybrid collection methods, and that our hybrid method yields exudates that discriminate between species. Our data also suggest that exudates collected with this hybrid method are ecologically valid, which is vital for gaining a mechanistic understanding of their role in ecosystem functioning.