Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model.

Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.

The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases.

Neuroscientists employ a range of methods and generate increasing amounts of data describing brain structure and function. The anatomical locations from which observations or measurements originate represent a common context for data interpretation, and a starting point for identifying data of interest. However, the multimodality and abundance of brain data pose a challenge for efforts to organize, integrate, and analyze data based on anatomical locations. While structured metadata allow faceted data queries, different types of data are not easily represented in a standardized and machine-readable way that allow comparison, analysis, and queries related to anatomical relevance. To this end, three-dimensional (3D) digital brain atlases provide frameworks in which disparate multimodal and multilevel neuroscience data can be spatially represented. We propose to represent the locations of different neuroscience data as geometric objects in 3D brain atlases. Such geometric objects can be specified in a standardized file format and stored as location metadata for use with different computational tools. We here present the Locare workflow developed for defining the anatomical location of data elements from rodent brains as geometric objects. We demonstrate how the workflow can be used to define geometric objects representing multimodal and multilevel experimental neuroscience in rat or mouse brain atlases. We further propose a collection of JSON schemas (LocareJSON) for specifying geometric objects by atlas coordinates, suitable as a starting point for co-visualization of different data in an anatomical context and for enabling spatial data queries.

Scaling up cell-counting efforts in neuroscience through semi-automated methods.

Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.

Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model.

Alzheimer's disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell and pathology composition of 6- and 14-month-old AD-BXD mouse brains using the semi-automated workflow (QUINT); which we expanded to allow for nonlinear refinement of brain atlas-registration, and quality control assessment of atlas-registration and brain section integrity. Near global age-related increases in microglia, astrocyte, and amyloid-beta accumulation were measured, while regional variation in neuron load existed among strains. Furthermore, hippocampal immunohistochemistry analyses were combined with bulk RNA-sequencing results to demonstrate the relationship between cell composition and gene expression. Overall, the additional functionality of the QUINT workflow delivers a highly effective method for registering and quantifying cell and pathology changes in diverse disease models.

How good is end of life care for patients dying with cystic fibrosis?

BACKGROUND: Cystic Fibrosis (CF) is a life-limiting illness. Audit of the care of patients dying of CF has not been published to date. METHODS: Newcastle and Oxford teams adapted the National Audit of Care at the End of Life and agreed additional questions that were particularly pertinent for patients dying as a consequence of their CF. Data were extracted and analysed for 15 patients. RESULTS: On recognition that the patient was dying, the CF teams were less good at reviewing the need for physiological observations (50% vs national 70%) but better at reviewing the need for capillary blood glucose monitoring, oxygen support and intravenous antibiotics compared with the national average for all patients.On recognition that the patient was dying, the CF teams were better at assessing pain (87% vs national 80%) and breathlessness (93% vs national 73%), but less good at assessing nausea and vomiting (47% vs national 74%).There was documented evidence that 100% of families and 64% of patients were aware that the patient was at risk of dying. CONCLUSION: Comparing care of this sample of patients dying with CF against the national data is a useful first step in understanding that many aspects of care are of high quality. This audit identifies the need to offer earlier conversations to patients as their voices may be missing from the conversation. Undertaking a national audit would provide a more reliable and a fuller picture.

Densities and numbers of calbindin and parvalbumin positive neurons across the rat and mouse brain.

The calcium-binding proteins parvalbumin and calbindin are expressed in neuronal populations regulating brain networks involved in spatial navigation, memory processes, and social interactions. Information about the numbers of these neurons across brain regions is required to understand their functional roles but is scarcely available. Employing semi-automated image analysis, we performed brain-wide analysis of immunohistochemically stained parvalbumin and calbindin sections and show that these neurons distribute in complementary patterns across the mouse brain. Parvalbumin neurons dominate in areas related to sensorimotor processing and navigation, whereas calbindin neurons prevail in regions reflecting behavioral states. We also find that parvalbumin neurons distribute according to similar principles in the hippocampal region of the rat and mouse brain. We validated our results against manual counts and evaluated variability of results among researchers. Comparison of our results to previous reports showed that neuron numbers vary, whereas patterns of relative densities and numbers are consistent.

Nutil: A Pre- and Post-processing Toolbox for Histological Rodent Brain Section Images.

With recent technological advances in microscopy and image acquisition of tissue sections, further developments of tools are required for viewing, transforming, and analyzing the ever-increasing amounts of high-resolution data produced. In the field of neuroscience, histological images of whole rodent brain sections are commonly used for investigating brain connections as well as cellular and molecular organization in the normal and diseased brain, but present a problem for the typical neuroscientist with no or limited programming experience in terms of the pre- and post-processing steps needed for analysis. To meet this need we have designed Nutil, an open access and stand-alone executable software that enables automated transformations, post-processing, and analyses of 2D section images using multi-core processing (OpenMP). The software is written in C++ for efficiency, and provides the user with a clean and easy graphical user interface for specifying the input and output parameters. Nutil currently contains four separate tools: (1) A transformation toolchain named "Transform" that allows for rotation, mirroring and scaling, resizing, and renaming of very large tiled tiff images. (2) "TiffCreator" enables the generation of tiled TIFF images from other image formats such as PNG and JPEG. (3) A "Resize" tool completes the preprocessing toolset and allows downscaling of PNG and JPEG images with output in PNG format. (4) The fourth tool is a post-processing method called "Quantifier" that enables the quantification of segmented objects in the context of regions defined by brain atlas maps generated with the QuickNII software based on a 3D reference atlas (mouse or rat). The output consists of a set of report files, point cloud coordinate files for visualization in reference atlas space, and reference atlas images superimposed with color-coded objects. The Nutil software is made available by the Human Brain Project (https://www.humanbrainproject.eu) at https://www.nitrc.org/projects/nutil/.

Palliative Care During COVID-19: Data and Visits From Loved Ones.

OBJECTIVES: A vital component of the coronavirus response is care of the dying COVID-19 patient. We document the demographics, symptoms experienced, medications required, effectiveness observed, and challenges to high-quality holistic palliative care in 31 patients. This will aid colleagues in primary and secondary care settings anticipate common symptoms and formulate management plans. METHODS: A retrospective survey was conducted of patients referred to the hospital palliative care service in a tertiary hospital, south east of England between March 21 and April 26, 2020. Patients included had a confirmed laboratory diagnosis of COVID-19 via reverse transcription polymerase chain reaction nasopharyngeal swab for SARS-Cov-2 or radiological evidence of COVID-19. RESULTS: The thirty-one patients included were predominantly male (77%), elderly (median [interquartile range]: 84 [76-89]), and had multiple (4 [3-5]) comorbidities. Referral was made in the last 2 [1-3] days of life. Common symptoms were breathlessness (84%) and delirium (77%). Fifty-eight percent of patients received at least 1 "as required" dose of an opioid or midazolam in the 24 hours before death. Sixty percent of patients needed a continuous subcutaneous infusion and the median morphine dose was 10 mg S/C per 24 hours and midazolam 10 mg S/C per 24 hours. Nineteen percent of our cohort had a loved one or relative present when dying. CONCLUSION: We provide additional data to the internationally reported pool examining death arising from infection with SARS-CoV-19. The majority of patients had symptoms controlled with low doses of morphine and midazolam, and death was rapid. The impact of low visitation during dying needs exploring.

QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain.

Transgenic animal models are invaluable research tools for elucidating the pathways and mechanisms involved in the development of neurodegenerative diseases. Mechanistic clues can be revealed by applying labelling techniques such as immunohistochemistry or in situ hybridisation to brain tissue sections. Precision in both assigning anatomical location to the sections and quantifying labelled features is crucial for output validity, with a stereological approach or image-based feature extraction typically used. However, both approaches are restricted by the need to manually delineate anatomical regions. To circumvent this limitation, we present the QUINT workflow for quantification and spatial analysis of labelling in series of rodent brain section images based on available 3D reference atlases. The workflow is semi-automated, combining three open source software that can be operated without scripting knowledge, making it accessible to most researchers. As an example, a brain region-specific quantification of amyloid plaques across whole transgenic Tg2576 mouse brain series, immunohistochemically labelled for three amyloid-related antigens is demonstrated. First, the whole brain image series were registered to the Allen Mouse Brain Atlas to produce customised atlas maps adapted to match the cutting plan and proportions of the sections (QuickNII software). Second, the labelling was segmented from the original images by the Random Forest Algorithm for supervised classification (ilastik software). Finally, the segmented images and atlas maps were used to generate plaque quantifications for each region in the reference atlas (Nutil software). The method yielded comparable results to manual delineations and to the output of a stereological method. While the use case demonstrates the QUINT workflow for quantification of amyloid plaques only, the workflow is suited to all mouse or rat brain series with labelling that is visually distinct from the background, for example for the quantification of cells or labelled proteins.

Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies.

In experimental neuroscientific research, anatomical location is a key attribute of experimental observations and critical for interpretation of results, replication of findings, and comparison of data across studies. With steadily rising numbers of publications reporting basic experimental results, there is an increasing need for integration and synthesis of data. Since comparison of data relies on consistently defined anatomical locations, it is a major concern that practices and precision in the reporting of location of observations from different types of experimental studies seem to vary considerably. To elucidate and possibly meet this challenge, we have evaluated and compared current practices for interpreting and documenting the anatomical location of measurements acquired from murine brains with different experimental methods. Our observations show substantial differences in approach, interpretation and reproducibility of anatomical locations among reports of different categories of experimental research, and strongly indicate that ambiguous reports of anatomical location can be attributed to missing descriptions. Based on these findings, we suggest a set of minimum requirements for documentation of anatomical location in experimental murine brain research. We furthermore demonstrate how these requirements have been applied in the EU Human Brain Project to optimize workflows for integration of heterogeneous data in common reference atlases. We propose broad adoption of some straightforward steps for improving the precision of location metadata and thereby facilitating interpretation, reuse and integration of data.

Data integration through brain atlasing: Human Brain Project tools and strategies.

The Human Brain Project (HBP), an EU Flagship Initiative, is currently building an infrastructure that will allow integration of large amounts of heterogeneous neuroscience data. The ultimate goal of the project is to develop a unified multi-level understanding of the brain and its diseases, and beyond this to emulate the computational capabilities of the brain. Reference atlases of the brain are one of the key components in this infrastructure. Based on a new generation of three-dimensional (3D) reference atlases, new solutions for analyzing and integrating brain data are being developed. HBP will build services for spatial query and analysis of brain data comparable to current online services for geospatial data. The services will provide interactive access to a wide range of data types that have information about anatomical location tied to them. The 3D volumetric nature of the brain, however, introduces a new level of complexity that requires a range of tools for making use of and interacting with the atlases. With such new tools, neuroscience research groups will be able to connect their data to atlas space, share their data through online data systems, and search and find other relevant data through the same systems. This new approach partly replaces earlier attempts to organize research data based only on a set of semantic terminologies describing the brain and its subdivisions.

The effects of two polymorphisms on p21cip1 function and their association with Alzheimer's disease in a population of European descent.

With the exception of ApoE4, genome-wide association studies have failed to identify strong genetic risk factors for late-onset Alzheimer's disease, despite strong evidence of heritability, suggesting that many low penetrance genes may be involved. Additionally, the nature of the identified genetic risk factors and their relation to disease pathology is also largely obscure. Previous studies have found that a cancer-associated variant of the cell cycle inhibitor gene p21cip1 is associated with increased risk of Alzheimer's disease. The aim of this study was to confirm this association and to elucidate the effects of the variant on protein function and Alzheimer-type pathology. We examined the association of the p21cip1 variant with Alzheimer's disease and Parkinson's disease with dementia. The genotyping studies were performed on 719 participants of the Oxford Project to Investigate Memory and Ageing, 225 participants of a Parkinson's disease DNA bank, and 477 participants of the Human Random Control collection available from the European Collection of Cell Cultures. The post mortem studies were carried out on 190 participants. In the in-vitro study, human embryonic kidney cells were transfected with either the common or rare p21cip1 variant; and cytometry was used to assess cell cycle kinetics, p21cip1 protein expression and sub-cellular localisation. The variant was associated with an increased risk of Alzheimer's disease, and Parkinson's disease with dementia, relative to age matched controls. Furthermore, the variant was associated with an earlier age of onset of Alzheimer's disease, and a more severe phenotype, with a primary influence on the accumulation of tangle pathology. In the in-vitro study, we found that the SNPs reduced the cell cycle inhibitory and anti-apoptotic activity of p21cip1. The results suggest that the cancer-associated variant of p21cip1 may contribute to the loss of cell cycle control in neurons that may lead to Alzheimer-type neurodegeneration.

Dysfunction of the mTOR pathway is a risk factor for Alzheimer's disease.

BACKGROUND: The development of disease-modifying therapies for Alzheimer's disease is hampered by our lack of understanding of the early pathogenic mechanisms and the lack of early biomarkers and risk factors.We have documented the expression pattern of mTOR regulated genes in the frontal cortex of Alzheimer's disease patients. We have also examined the functional integrity of mTOR signaling in peripheral lymphocytes in Alzheimer's disease patients relative to healthy controls. RESULTS: In the brain mTOR is seen to control molecular functions related to cell cycle regulation, cell death and several metabolic pathways. These downstream elements of the mTOR signaling cascade are deregulated in the brain of Alzheimer's disease patients well before the development of pathology. This dysregulation of the mTOR downstream signaling cascade is not restricted to the brain but appears to be systemic and can be detected in peripheral lymphocytes as a reduced Rapamycin response. CONCLUSIONS: The dysfunction of the signaling pathways downstream of mTOR may represent a risk factor for Alzheimer's disease and is independent of the ApoE status of the patients.We have also identified the molecular substrates of the beneficial effects of Rapamycin on the nervous system. We believe that these results can further inform the development of clinical predictive tests for the risk of Alzheimer's disease in patients with mild cognitive impairment.