Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy.

Heart failure encompasses a heterogeneous set of clinical features that converge on impaired cardiac contractile function1,2 and presents a growing public health concern. Previous work has highlighted changes in both transcription and protein expression in failing hearts3,4, but may overlook molecular changes in less prevalent cell types. Here we identify extensive molecular alterations in failing hearts at single-cell resolution by performing single-nucleus RNA sequencing of nearly 600,000 nuclei in left ventricle samples from 11 hearts with dilated cardiomyopathy and 15 hearts with hypertrophic cardiomyopathy as well as 16 non-failing hearts. The transcriptional profiles of dilated or hypertrophic cardiomyopathy hearts broadly converged at the tissue and cell-type level. Further, a subset of hearts from patients with cardiomyopathy harbour a unique population of activated fibroblasts that is almost entirely absent from non-failing samples. We performed a CRISPR-knockout screen in primary human cardiac fibroblasts to evaluate this fibrotic cell state transition; knockout of genes associated with fibroblast transition resulted in a reduction of myofibroblast cell-state transition upon TGFß1 stimulation for a subset of genes. Our results provide insights into the transcriptional diversity of the human heart in health and disease as well as new potential therapeutic targets and biomarkers for heart failure.

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets.

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.

Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender.

Droplet-based single-cell assays, including single-cell RNA sequencing (scRNA-seq), single-nucleus RNA sequencing (snRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), generate considerable background noise counts, the hallmark of which is nonzero counts in cell-free droplets and off-target gene expression in unexpected cell types. Such systematic background noise can lead to batch effects and spurious differential gene expression results. Here we develop a deep generative model based on the phenomenology of noise generation in droplet-based assays. The proposed model accurately distinguishes cell-containing droplets from cell-free droplets, learns the background noise profile and provides noise-free quantification in an end-to-end fashion. We implement this approach in the scalable and robust open-source software package CellBender. Analysis of simulated data demonstrates that CellBender operates near the theoretically optimal denoising limit. Extensive evaluations using real datasets and experimental benchmarks highlight enhanced concordance between droplet-based single-cell data and established gene expression patterns, while the learned background noise profile provides evidence of degraded or uncaptured cell types.

Predictions and rewards affect decision-making but not subjective experience.

To survive, organisms constantly make decisions to avoid danger and maximize rewards in information-rich environments. As a result, decisions about sensory input are not only driven by sensory information but also by other factors, such as the expected rewards of a decision (known as the payoff matrix) or by information about temporal regularities in the environment (known as cognitive priors or predictions). However, it is unknown to what extent these different types of information affect subjective experience or whether they merely result in nonperceptual response criterion shifts. To investigate this question, we used three carefully matched manipulations that typically result in behavioral shifts in decision criteria: a visual illusion (Müller-Lyer condition), a punishment scheme (payoff condition), and a change in the ratio of relevant stimuli (base rate condition). To gauge shifts in subjective experience, we introduce a task in which participants not only make decisions about what they have just seen but are also asked to reproduce their experience of a target stimulus. Using Bayesian ordinal modeling, we show that each of these three manipulations affects the decision criterion as intended but that the visual illusion uniquely affects sensory experience as measured by reproduction. In a series of follow-up experiments, we use computational modeling to show that although the visual illusion results in a distinct drift-diffusion (DDM) parameter profile relative to nonsensory manipulations, reliance on DDM parameter estimates alone is not sufficient to ascertain whether a given manipulation is perceptual or nonperceptual.

Metacognition and Confidence: A Review and Synthesis.

Determining the psychological, computational, and neural bases of confidence and uncertainty holds promise for understanding foundational aspects of human metacognition. While a neuroscience of confidence has focused on the mechanisms underpinning subpersonal phenomena such as representations of uncertainty in the visual or motor system, metacognition research has been concerned with personal-level beliefs and knowledge about self-performance. I provide a road map for bridging this divide by focusing on a particular class of confidence computation: propositional confidence in one's own (hypothetical) decisions or actions. Propositional confidence is informed by the observer's models of the world and their cognitive system, which may be more or less accurate-thus explaining why metacognitive judgments are inferential and sometimes diverge from task performance. Disparate findings on the neural basis of uncertainty and performance monitoring are integrated into a common framework, and a new understanding of the locus of action of metacognitive interventions is developed.

Confidence ratings do not distinguish imagination from reality.

Perceptual reality monitoring refers to the ability to distinguish internally triggered imagination from externally triggered reality. Such monitoring can take place at perceptual or cognitive levels-for example, in lucid dreaming, perceptual experience feels real but is accompanied by a cognitive insight that it is not real. We recently developed a paradigm to reveal perceptual reality monitoring errors during wakefulness in the general population, showing that imagined signals can be erroneously attributed to perception during a perceptual detection task. In the current study, we set out to investigate whether people have insight into perceptual reality monitoring errors by additionally measuring perceptual confidence. We used hierarchical Bayesian modeling of confidence criteria to characterize metacognitive insight into the effects of imagery on detection. Over two experiments, we found that confidence criteria moved in tandem with the decision criterion shift, indicating a failure of reality monitoring not only at a perceptual but also at a metacognitive level. These results further show that such failures have a perceptual rather than a decisional origin. Interestingly, offline queries at the end of the experiment revealed global, task-level insight, which was uncorrelated with local, trial-level insight as measured with confidence ratings. Taken together, our results demonstrate that confidence ratings do not distinguish imagination from reality during perceptual detection. Future research should further explore the different cognitive dimensions of insight into reality judgments and how they are related.

Dissociating the Neural Correlates of Subjective Visibility from Those of Decision Confidence.

A key goal of consciousness science is identifying neural signatures of being aware versus unaware of simple stimuli. This is often investigated in the context of near-threshold detection, with reports of stimulus awareness being linked to heightened activation in a frontoparietal network. However, because of reports of stimulus presence typically being associated with higher confidence than reports of stimulus absence, these results could be explained by frontoparietal regions encoding stimulus visibility, decision confidence, or both. In an exploratory analysis, we leverage fMRI data from 35 human participants (20 females) to disentangle these possibilities. We first show that, whereas stimulus identity was best decoded from the visual cortex, stimulus visibility (presence vs absence) was best decoded from prefrontal regions. To control for effects of confidence, we then selectively sampled trials before decoding to equalize confidence distributions between absence and presence responses. This analysis revealed striking differences in the neural correlates of subjective visibility in PFC ROIs, depending on whether or not differences in confidence were controlled for. We interpret our findings as highlighting the importance of controlling for metacognitive aspects of the decision process in the search for neural correlates of visual awareness.SIGNIFICANCE STATEMENT While much has been learned over the past two decades about the neural basis of visual awareness, the role of the PFC remains a topic of debate. By applying decoding analyses to functional brain imaging data, we show that prefrontal representations of subjective visibility are contaminated by neural correlates of decision confidence. We propose a new analysis method to control for these metacognitive aspects of awareness reports, and use it to reveal confidence-independent correlates of perceptual judgments in a subset of prefrontal areas.

Interoceptive and metacognitive facets of fatigue in multiple sclerosis.

Numerous disorders are characterised by fatigue as a highly disabling symptom. Fatigue plays a particularly important clinical role in multiple sclerosis (MS) where it exerts a profound impact on quality of life. Recent concepts of fatigue grounded in computational theories of brain-body interactions emphasise the role of interoception and metacognition in the pathogenesis of fatigue. So far, however, for MS, empirical data on interoception and metacognition are scarce. This study examined interoception and (exteroceptive) metacognition in a sample of 71 persons with a diagnosis of MS. Interoception was assessed by prespecified subscales of a standard questionnaire (Multidimensional Assessment of Interoceptive Awareness [MAIA]), while metacognition was investigated with computational models of choice and confidence data from a visual discrimination paradigm. Additionally, autonomic function was examined by several physiological measurements. Several hypotheses were tested based on a preregistered analysis plan. In brief, we found the predicted association of interoceptive awareness with fatigue (but not with exteroceptive metacognition) and an association of autonomic function with exteroceptive metacognition (but not with fatigue). Furthermore, machine learning (elastic net regression) showed that individual fatigue scores could be predicted out-of-sample from our measurements, with questionnaire-based measures of interoceptive awareness and sleep quality as key predictors. Our results support theoretical concepts of interoception as an important factor for fatigue and demonstrate the general feasibility of predicting individual levels of fatigue from simple questionnaire-based measures of interoception and sleep.

The parapoxvirus Orf virus inhibits dsDNA-mediated type I IFN expression via STING-dependent and STING-independent signalling pathways.

Type I interferons (IFNs) are critical in the host defence against viruses. They induce hundreds of interferon-stimulated genes (ISGs) many of which have an antiviral role. Poxviruses induce IFNs via their pathogen-associated molecular patterns, in particular, their genomic DNA. In a majority of cell types, dsDNA is detected by a range of cytoplasmic DNA sensors that mediate type I IFN expression via stimulator of interferon genes (STING). Orf virus (ORFV) induces cutaneous pustular skin lesions and is the type species of the Parapoxvirus genus within the Poxviridae family. The aim of this study was to investigate whether ORFV modulates dsDNA-induced type I IFN expression via STING-dependent signalling pathways in human dermal fibroblasts (hNDF) and THP-1 cells. We showed that ORFV infection of these cell types treated with poly(dA:dT) resulted in strong inhibition of expression of IFN-ß. In hNDFs, we showed using siRNA knock-down that STING was essential for type I IFN induction. IFN-ß expression was further reduced when both STING and RIG-I were knocked down. In addition, HEK293 cells that do not express STING or Toll-like receptors also produce IFN-ß following stimulation with poly(dA:dT). The 5' triphosphate dsRNA produced by RNA polymerase III specifically results in the induction of type I IFNs through the RIG-I receptor. We showed that ORFV infection resulted in strong inhibition of IFN-ß expression in HEK293 cells stimulated with poly(dA:dT). Overall, this study shows that ORFV potently counteracts the STING-dependent and STING-independent IFN response by antagonizing dsDNA-activated IFN signalling pathways.

Combining genomics and epidemiology to track mumps virus transmission in the United States.

Unusually large outbreaks of mumps across the United States in 2016 and 2017 raised questions about the extent of mumps circulation and the relationship between these and prior outbreaks. We paired epidemiological data from public health investigations with analysis of mumps virus whole genome sequences from 201 infected individuals, focusing on Massachusetts university communities. Our analysis suggests continuous, undetected circulation of mumps locally and nationally, including multiple independent introductions into Massachusetts and into individual communities. Despite the presence of these multiple mumps virus lineages, the genomic data show that one lineage has dominated in the US since at least 2006. Widespread transmission was surprising given high vaccination rates, but we found no genetic evidence that variants arising during this outbreak contributed to vaccine escape. Viral genomic data allowed us to reconstruct mumps transmission links not evident from epidemiological data or standard single-gene surveillance efforts and also revealed connections between apparently unrelated mumps outbreaks.

Dietary consumption of beef and red meat: a scoping review and evidence map on cognitive outcomes across the lifespan.

OBJECTIVE: Mixed evidence exists on the impact of beef consumption on cognition. The goal was to create an evidence map capturing studies assessing beef consumption and cognition to reveal gaps and opportunities in the body of literature. DESIGN: A scoping review was conducted to locate studies up to March 2022 using PubMed and backwards citation screening. Data were extracted by two independent reviewers with conflict resolution, and a database was created and made publicly available. SETTING: Intervention and observational studies. PARTICIPANTS: Humans of any age, sex and/or health status, without moderate to severe cognitive impairment and/or abnormalities. RESULTS: Twenty-two studies were identified that quantified beef or red meat intake and assessed cognition. Six studies assessed beef intake, with the remaining studies describing intake of red meat that may or may not include beef. Nine articles described randomised controlled trials (RCT), mostly conducted in children. Thirteen described observational studies, primarily conducted on adults and seniors. The most common cognitive domains measured included intelligence and general cognition, and memory. The majority of controlled studies were rated with high risk of bias, with the majority of observational trials rated with serious or greater risk of bias. CONCLUSIONS: Red meat and beef intake and cognition is largely understudied. There is a significant lack of replication across study designs, populations, exposures and outcomes measured. The quality of the research would be considerably enhanced by focused assessments of beef intake (and not red meat in general) and specific cognitive domains, along with improved adherence to reporting standards.

Formation of global self-beliefs in the human brain.

Humans create metacognitive beliefs about their performance across many levels of abstraction-from local confidence in individual decisions to global estimates of our skills and abilities. Despite a rich literature on the neural basis of local confidence judgements, how global self-performance estimates (SPEs) are constructed remains unknown. Using functional magnetic resonance imaging, we scanned human subjects while they performed several short blocks of tasks and reported on which task they think they performed best, providing a behavioral proxy for global SPEs. In a frontoparietal network sensitive to fluctuations in local confidence, we found that activity within ventromedial prefrontal cortex and precuneus was additionally modulated by global SPEs. In contrast, activity in ventral striatum was associated with subjects' global SPEs irrespective of fluctuations in local confidence, and predicted the extent to which global SPEs tracked objective task difficulty across individuals. Our findings reveal neural representations of global SPEs that go beyond the tracking of local confidence, and lay the groundwork for understanding how a formation of global self-beliefs may go awry in conditions characterized by distorted self-evaluation.

Dogmatism manifests in lowered information search under uncertainty.

When knowledge is scarce, it is adaptive to seek further information to resolve uncertainty and obtain a more accurate worldview. Biases in such information-seeking behavior can contribute to the maintenance of inaccurate views. Here, we investigate whether predispositions for uncertainty-guided information seeking relate to individual differences in dogmatism, a phenomenon linked to entrenched beliefs in political, scientific, and religious discourse. We addressed this question in a perceptual decision-making task, allowing us to rule out motivational factors and isolate the role of uncertainty. In two independent general population samples (n = 370 and n = 364), we show that more dogmatic participants are less likely to seek out new information to refine an initial perceptual decision, leading to a reduction in overall belief accuracy despite similar initial decision performance. Trial-by-trial modeling revealed that dogmatic participants placed less reliance on internal signals of uncertainty (confidence) to guide information search, rendering them less likely to seek additional information to update beliefs derived from weak or uncertain initial evidence. Together, our results highlight a cognitive mechanism that may contribute to the formation of dogmatic worldviews.

The Cognition/Metacognition Trade-Off.

Integration to boundary is an optimal decision algorithm that accumulates evidence until the posterior reaches a decision boundary, resulting in the fastest decisions for a target accuracy. Here, we demonstrated that this advantage incurs a cost in metacognitive accuracy (confidence), generating a cognition/metacognition trade-off. Using computational modeling, we found that integration to a fixed boundary results in less variability in evidence integration and thus reduces metacognitive accuracy, compared with a collapsing-boundary or a random-timer strategy. We examined how decision strategy affects metacognitive accuracy in three cross-domain experiments, in which 102 university students completed a free-response session (evidence terminated by the participant's response) and an interrogation session (fixed number of evidence samples controlled by the experimenter). In both sessions, participants observed a sequence of evidence and reported their choice and confidence. As predicted, the interrogation protocol (preventing integration to boundary) enhanced metacognitive accuracy. We also found that in the free-response sessions, participants integrated evidence to a collapsing boundary-a strategy that achieves an efficient compromise between optimizing choice and metacognitive accuracy.

Consuming a Protein and Fiber-Based Supplement Preload Promotes Weight Loss and Alters Metabolic Markers in Overweight Adults in a 12-Week, Randomized, Double-Blind, Placebo-Controlled Trial.

BACKGROUND: Higher protein and fiber diets promote weight management and metabolic health. OBJECTIVES: This study aimed to determine if greater weight loss and positive changes in metabolic outcomes could be achieved with twice-daily consumption of a high-protein and fiber-based multi-ingredient nutritional shake (HPF) compared with an isocaloric low-protein, lower fiber-based placebo (LPF). METHODS: Study procedures were conducted by an independent research organization under clinicaltrials.gov registration NCT03057873. Healthy overweight and obese adults [n = 206; BMI (kg/m2): 27-35; 70% female] were randomly assigned to HPF or LPF. All participants were prescribed an energy-restricted diet (500 kcal/d less than energy needs) and consumed a HPF (17 g protein, 6 g fiber) or LPF (1 g protein, 3 g fiber) shake 30 min before breakfast and lunch for 12 wk. Primary outcomes included body weight and total body fat percentage. Blood samples were collected at days (D) 0, 28, 56, and 84 for secondary analyses related to metabolic markers of health. RESULTS: Although weight loss occurred in both groups, HPF had greater weight loss at D84 compared with LPF (-3.3 kg vs. -1.8 kg, P < 0.05). Percentage body fat decreased in both groups (HPF: -1.33%, LPF: -1.09%; P < 0.001) with no differences between groups. Serum total cholesterol, LDL cholesterol, and oxidized LDL decreased between -5.1% to -8.3%, whereas adiponectin increased over time in both groups; these changes occurred to a greater extent in HPF compared with LPF (all P < 0.05). CONCLUSIONS: A multi-ingredient HPF nutritional supplement shake consumed as a preload before breakfast and lunch positively influenced weight management and metabolic outcomes in overweight adults compared with an LPF placebo. These findings suggest that specific nutrient factors (i.e., potentially including protein, fiber, and bioactive content) other than calorie reduction alone influence the success of a weight-loss regimen. This trial was registered at www.clinicaltrials.gov as NCT03057873.

Explaining distortions in metacognition with an attractor network model of decision uncertainty.

Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the model's uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. Notably, we are able to account for empirical confidence judgements by fitting the parameters of our biophysical model to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible.

Dietary sialylated oligosaccharides in early-life may promote cognitive flexibility during development in context of obesogenic dietary intake.

Introduction: Oligosaccharides found in mammalian milk have shown the potential to alter brain development across multiple species. The diversity and concentration of these oligosaccharides is species-specific and varies greatly between individuals, thus understanding their role in cognitive development is warranted. We investigated the impact of early life dietary fucosylated/neutral or sialylated human milk oligosaccharides (HMO) on behaviours in tasks assessing anxiety, motivation, appetite, learning, and memory.Methods: Sixty-four female Göttingen minipigs were artificially reared from 2 weeks postnatal and provided milk replacers. The study used four groups: no additional oligosaccharides (Con), fucosylated and neutral oligosaccharides (FN, 4 g/L), sialylated oligosaccharides (SL, 0.68 g/L), or both FN and SL (FN + SL, 4 g/L) from 2 to 11 weeks postnatal. One reference group was sow-reared. Weaning occurred between 10 and 11 weeks postnatal, and thereafter an obesogenic diet was provided. Behavioral tasks were conducted over three periods: 1) 0-11 weeks; 2) 16-29 weeks; 3) 39-45 weeks. Tasks included a spatial holeboard task, open field task, exposure to a novel object, runway task, single-feed task, and home pen behaviour observation.Results: In the holeboard, the SL group demonstrated improved reference memory during reversal trials between 16-29 weeks. All groups demonstrated equivalent behavior in open field, novel object, runway, and single-feed tasks, as well as in their home pens (Ps > 0.05).Discussion: These results suggest that early life dietary intake of sialylated oligosaccharides may provide an improvement to cognition during the equivalent developmental stage of adolescence.

Imagery adds stimulus-specific sensory evidence to perceptual detection.

Internally generated imagery and externally triggered perception rely on overlapping sensory processes. This overlap poses a challenge for perceptual reality monitoring: determining whether sensory signals reflect reality or imagination. In this study, we used psychophysics to investigate how imagery and perception interact to determine visual experience. Participants were instructed to detect oriented gratings that gradually appeared in noise while simultaneously either imagining the same grating, a grating perpendicular to the to-be-detected grating, or nothing. We found that, compared to both incongruent imagery and no imagery, congruent imagery caused a leftward shift of the psychometric function relating stimulus contrast to perceptual threshold. We discuss how this effect can best be explained by a model in which imagery adds sensory signal to the perceptual input, thereby increasing the visibility of perceived stimuli. These results suggest that, in contrast to changes in sensory signals caused by self-generated movement, the brain does not discount the influence of self-generated sensory signals on perception.

Mortality Awareness: New Directions.

Thinking about our own death and its salience in relation to decision making has become a fruitful area of multidisciplinary research across the breadth of psychological science. By bringing together experts from philosophy, cognitive and affective neuroscience, clinical and computational psychiatry we have attempted to set out the current state of the art and point to areas of further enquiry. One stimulus for doing this is the need to engage with policy makers who are now having to consider guidelines on suicide and assisted suicide so that they may be aware of their own as well as the wider populations' cognitive processes when confronted with the ultimate truth of mortality.

Transcriptional and Cellular Diversity of the Human Heart.

BACKGROUND: The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge of the intricate cellular milieu of the heart is critical to increase our understanding of cardiac homeostasis and pathology. As recent advances in low-input RNA sequencing have allowed definitions of cellular transcriptomes at single-cell resolution at scale, we have applied these approaches to assess the cellular and transcriptional diversity of the nonfailing human heart. METHODS: Microfluidic encapsulation and barcoding was used to perform single nuclear RNA sequencing with samples from 7 human donors, selected for their absence of overt cardiac disease. Individual nuclear transcriptomes were then clustered based on transcriptional profiles of highly variable genes. These clusters were used as the basis for between-chamber and between-sex differential gene expression analyses and intersection with genetic and pharmacologic data. RESULTS: We sequenced the transcriptomes of 287 269 single cardiac nuclei, revealing 9 major cell types and 20 subclusters of cell types within the human heart. Cellular subclasses include 2 distinct groups of resident macrophages, 4 endothelial subtypes, and 2 fibroblast subsets. Comparisons of cellular transcriptomes by cardiac chamber or sex reveal diversity not only in cardiomyocyte transcriptional programs but also in subtypes involved in extracellular matrix remodeling and vascularization. Using genetic association data, we identified strong enrichment for the role of cell subtypes in cardiac traits and diseases. Intersection of our data set with genes on cardiac clinical testing panels and the druggable genome reveals striking patterns of cellular specificity. CONCLUSIONS: Using large-scale single nuclei RNA sequencing, we defined the transcriptional and cellular diversity in the normal human heart. Our identification of discrete cell subtypes and differentially expressed genes within the heart will ultimately facilitate the development of new therapeutics for cardiovascular diseases.