Epizootic pneumonia of bighorn sheep is a devastating disease of uncertain etiology. To help clarify the etiology, we used culture and culture-independent methods to compare the prevalence of the bacterial respiratory pathogens Mannheimia haemolytica, Bibersteinia trehalosi, Pasteurella multocida, and Mycoplasma ovipneumoniae in lung tissue from 44 bighorn sheep from herds affected by 8 outbreaks in the western United States. M. ovipneumoniae, the only agent detected at significantly higher prevalence in animals from outbreaks (95%) than in animals from unaffected healthy populations (0%), was the most consistently detected agent and the only agent that exhibited single strain types within each outbreak. The other respiratory pathogens were frequently but inconsistently detected, as were several obligate anaerobic bacterial species, all of which might represent secondary or opportunistic infections that could contribute to disease severity. These data provide evidence that M. ovipneumoniae plays a primary role in the etiology of epizootic pneumonia of bighorn sheep.

The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.

Genetically encoded voltage indicators (GEVIs) enable monitoring of neuronal activity at high spatial and temporal resolution. However, the utility of existing GEVIs has been limited by the brightness and photostability of fluorescent proteins and rhodopsins. We engineered a GEVI, called Voltron, that uses bright and photostable synthetic dyes instead of protein-based fluorophores, thereby extending the number of neurons imaged simultaneously in vivo by a factor of 10 and enabling imaging for significantly longer durations relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In the mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously over a 15-minute period of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.

Background: Human challenge studies involve the deliberate exposure of healthy volunteers to an infectious micro-organism in a highly controlled and monitored way. They are used to understand infectious diseases and have contributed to the development of vaccines. In early 2020, the UK started exploring the feasibility of establishing a human challenge study with SARS-CoV-2. Given the significant public interest and the complexity of the potential risks and benefits, it is vital that public views are considered in the design and approval of any such study and that investigators and ethics boards remain accountable to the public. Methods: Mixed methods study comprising online surveys conducted with 2,441 UK adults and in-depth virtual focus groups with 57 UK adults during October 2020 to explore the public's attitudes to a human challenge study with SARS-CoV-2 taking place in the UK. Results: There was overall agreement across the surveys and focus groups that a human challenge study with SARS-CoV-2 should take place in the UK. Transparency of information, trust and the necessity to provide clear information on potential risks to study human challenge study participants were important. The perceived risks of taking part included the risk of developing long-term effects from COVID, impact on personal commitments and mental health implications of isolation. There were a number of practical realities to taking part that would influence a volunteer's ability to participate (e.g. Wi-Fi, access to exercise, outside space and work, family and pet commitments). Conclusions: The results identified practical considerations for teams designing human challenge studies. Recommendations were grouped: 1) messaging to potential study participants, 2) review of the protocol and organisation of the study, and 3) more broadly, making the study more inclusive and relevant. This study highlights the value of public consultation in research, particularly in fields attracting public interest and scrutiny .

Human cortex transcriptomic studies have revealed a hierarchical organization of γ-aminobutyric acid-producing (GABAergic) neurons from subclasses to a high diversity of more granular types. Rapid GABAergic neuron viral genetic labeling plus Patch-seq (patch-clamp electrophysiology plus single-cell RNA sequencing) sampling in human brain slices was used to reliably target and analyze GABAergic neuron subclasses and individual transcriptomic types. This characterization elucidated transitions between PVALB and SST subclasses, revealed morphological heterogeneity within an abundant transcriptomic type, identified multiple spatially distinct types of the primate-specialized double bouquet cells (DBCs), and shed light on cellular differences between homologous mouse and human neocortical GABAergic neuron types. These results highlight the importance of multimodal phenotypic characterization for refinement of emerging transcriptomic cell type taxonomies and for understanding conserved and specialized cellular properties of human brain cell types.

Understanding cortical microcircuits requires thorough measurement of physiological properties of synaptic connections formed within and between diverse subclasses of neurons. Towards this goal, we combined spatially precise optogenetic stimulation with multicellular recording to deeply characterize intralaminar and translaminar monosynaptic connections to supragranular (L2/3) neurons in the mouse visual cortex. The reliability and specificity of multiphoton optogenetic stimulation were measured across multiple Cre lines, and measurements of connectivity were verified by comparison to paired recordings and targeted patching of optically identified presynaptic cells. With a focus on translaminar pathways, excitatory and inhibitory synaptic connections from genetically defined presynaptic populations were characterized by their relative abundance, spatial profiles, strength, and short-term dynamics. Consistent with the canonical cortical microcircuit, layer 4 excitatory neurons and interneurons within L2/3 represented the most common sources of input to L2/3 pyramidal cells. More surprisingly, we also observed strong excitatory connections from layer 5 intratelencephalic neurons and potent translaminar inhibition from multiple interneuron subclasses. The hybrid approach revealed convergence to and divergence from excitatory and inhibitory neurons within and across cortical layers. Divergent excitatory connections often spanned hundreds of microns of horizontal space. In contrast, divergent inhibitory connections were more frequently measured from postsynaptic targets near each other.

Fluorescent calcium indicators are often used to investigate neural dynamics, but the relationship between fluorescence and action potentials (APs) remains unclear. Most APs can be detected when the soma almost fills the microscope's field of view, but calcium indicators are used to image populations of neurons, necessitating a large field of view, generating fewer photons per neuron, and compromising AP detection. Here, we characterized the AP-fluorescence transfer function in vivo for 48 layer 2/3 pyramidal neurons in primary visual cortex, with simultaneous calcium imaging and cell-attached recordings from transgenic mice expressing GCaMP6s or GCaMP6f. While most APs were detected under optimal conditions, under conditions typical of population imaging studies, only a minority of 1 AP and 2 AP events were detected (often <10% and ~20-30%, respectively), emphasizing the limits of AP detection under more realistic imaging conditions.

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably obtaining healthy tissue, conducting multiple patch-clamp recordings on inhibitory cell types, and identifying those cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), machine learning-based cell type classification and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- vs. SST-positive interneurons. We find that there are robust molecular differences in synapse-associated genes between these neuron types, and that individual presynaptic pyramidal neurons evoke postsynaptic responses with heterogeneous synaptic dynamics in different postsynaptic cell types. Using molecular identification with FISH and classifiers based on transcriptomically identified PVALB neurons analyzed by Patch-seq, we find that PVALB neurons typically show depressing synaptic characteristics, whereas other interneuron types including SST-positive neurons show facilitating characteristics. Together, these data support the existence of target cell-specific synaptic properties in human cortex that are similar to rodent, thereby indicating evolutionary conservation of local circuit connectivity motifs from excitatory to inhibitory neurons and their synaptic dynamics.

Neocortical layer 1 (L1) is a site of convergence between pyramidal-neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neurons with extensive L1 branching, but whether L1 interneurons are similarly diverse is underexplored. Using Patch-seq recordings from human neurosurgical tissue, we identified four transcriptomic subclasses with mouse L1 homologs, along with distinct subtypes and types unmatched in mouse L1. Subclass and subtype comparisons showed stronger transcriptomic differences in human L1 and were correlated with strong morphoelectric variability along dimensions distinct from mouse L1 variability. Accompanied by greater layer thickness and other cytoarchitecture changes, these findings suggest that L1 has diverged in evolution, reflecting the demands of regulating the expanded human neocortical circuit.

A scoping review will be undertaken to examine and map the available evidence that has been produced in relation to pain management in Parkinson's, with a focus on behavioural interventions, resources and/or how professionals support people with Parkinson's self-management of pain.

Consumer nutrition environments are defined as places in which consumers interact with the food they eat; these food choices can impact human and planetary health. Assessment measures for consumer nutrition environments are numerous, and vary widely on what, and how, they assess the food environment. The objective of this scoping review was to synthesize existing evidence on nutrition environment measurements and their capacity to assess nutrient-dense food access and food sustainability capacity. Eligibility criteria were developed to capture relevant peer-reviewed literature about auditing measures designed to assess nutrient-dense foods and food sustainability capacity in the consumer nutrition environment. A search strategy was conducted to collect articles published between January 1, 2002-June 4, 2022, using PubMed, Web of Science, Scopus, PsycINFO and the Cochrane library electronic databases. After screening 2457 manuscripts, 58 met inclusion criteria. Study aims, funding source(s), types of retailers assessed, assessment format and name, constructs measured, food categories measured, assessment of validity and/or reliability, and other relevant data were extracted from each manuscript. Results showed that most measures use checklists, surveys, questionnaires or similar methods to assess availability, quality, and price of select food items as assessment constructs. Most do not assess nutrient-dense food availability, and even fewer assess food sustainability. Development of comprehensive, reliable, and valid consumer nutrition environment measures that assess nutrient-dense food availability and food sustainability is important for research, planning, evaluation and advocacy aimed at improving consumer food environments for human and planetary health.

Higher-order thalamic nuclei, such as the visual pulvinar, play essential roles in cortical function by connecting functionally related cortical and subcortical brain regions. A coherent framework describing pulvinar function remains elusive because of its anatomical complexity and involvement in diverse cognitive processes. We combined large-scale anatomical circuit mapping with high-density electrophysiological recordings to dissect a homolog of the pulvinar in mice, the lateral posterior thalamic nucleus (LP). We define three broad LP subregions based on correspondence between connectivity and functional properties. These subregions form corticothalamic loops biased toward ventral or dorsal stream cortical areas and contain separate representations of visual space. Silencing the visual cortex or superior colliculus revealed that they drive visual tuning properties in separate LP subregions. Thus, by specifying the driving input sources, functional properties, and downstream targets of LP circuits, our data provide a roadmap for understanding the mechanisms of higher-order thalamic function in vision.

Abundant evidence supports the presence of at least three distinct types of thalamocortical (TC) neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex (V1). Different types of TC neurons in mice, humans, and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of TC neurons in the primate dLGN: magnocellular (M) neurons, parvocellular (P) neurons, and two types of koniocellular (K) neurons. Despite extensively documented morphological and physiological differences between M and P neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. Likewise, the dominant feature of TC neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to the observed differences in morphology and cortical projection targets. Finally, alignment of transcriptome profiles across species highlights expanded diversity of GABAergic neurons in primate versus mouse dLGN and homologous types of TC neurons in primates that are distinct from TC neurons in mouse.

To examine the association between self-reported activity pacing (a strategy to manage fatigue symptoms) and objectively-measured physical activity behaviours in adults with multiple sclerosis.

The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties1-3. Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present an online platform, Allen Brain Cell Atlas, to visualize the mouse whole-brain cell-type atlas along with the single-cell RNA-sequencing and MERFISH datasets. We systematically analysed the neuronal and non-neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell-type organization in different brain regions-in particular, a dichotomy between the dorsal and ventral parts of the brain. The dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. Our study also uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types. Finally, we found that transcription factors are major determinants of cell-type classification and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole mouse brain transcriptomic and spatial cell-type atlas establishes a benchmark reference atlas and a foundational resource for integrative investigations of cellular and circuit function, development and evolution of the mammalian brain.

To assess the clustering properties of residential urban food environment indicators across neighbourhoods and to determine if clustering profiles are associated with diet outcomes among adults in Brooklyn, New York.

The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success. The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. The protocol, analysis and acquisition software are compiled at https://githubcom/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets.

Modern genetic approaches are powerful in providing access to diverse cell types in the brain and facilitating the study of their function. Here, we report a large set of driver and reporter transgenic mouse lines, including 23 new driver lines targeting a variety of cortical and subcortical cell populations and 26 new reporter lines expressing an array of molecular tools. In particular, we describe the TIGRE2.0 transgenic platform and introduce Cre-dependent reporter lines that enable optical physiology, optogenetics, and sparse labeling of genetically defined cell populations. TIGRE2.0 reporters broke the barrier in transgene expression level of single-copy targeted-insertion transgenesis in a wide range of neuronal types, along with additional advantage of a simplified breeding strategy compared to our first-generation TIGRE lines. These novel transgenic lines greatly expand the repertoire of high-precision genetic tools available to effectively identify, monitor, and manipulate distinct cell types in the mouse brain.

The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer's disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease.

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities.