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Thrombospondin (Thbs) proteins are induced in sites of tissue damage or active remodeling. The endoplasmic reticulum (ER) stress response is also prominently induced with disease where it regulates protein production and resolution of misfolded proteins. Here we describe a function for Thbs as ER-resident effectors of an adaptive ER stress response. Thbs4 cardiac-specific transgenic mice were protected from myocardial injury, whereas Thbs4(-/-) mice were sensitized to cardiac maladaptation. Thbs induction produced a unique profile of adaptive ER stress response factors and expansion of the ER and downstream vesicles. Thbs bind the ER lumenal domain of activating transcription factor 6α (Atf6α) to promote its nuclear shuttling. Thbs4(-/-) mice showed blunted activation of Atf6α and other ER stress-response factors with injury, and Thbs4-mediated protection was lost upon Atf6α deletion. Hence, Thbs can function inside the cell during disease remodeling to augment ER function and protect through a mechanism involving regulation of Atf6α.
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Estrés del Retículo Endoplásmico , Transducción de Señal , Trombospondinas/metabolismo , Factor de Transcripción Activador 6/genética , Animales , Cardiomiopatías/metabolismo , Modelos Animales de Enfermedad , Humanos , Ratones , Ratones Transgénicos , Regiones Promotoras Genéticas , Trombospondinas/genéticaRESUMEN
Lineage mapping has identified both proliferative and quiescent intestinal stem cells, but the molecular circuitry controlling stem cell quiescence is incompletely understood. By lineage mapping, we show Lrig1, a pan-ErbB inhibitor, marks predominately noncycling, long-lived stem cells that are located at the crypt base and that, upon injury, proliferate and divide to replenish damaged crypts. Transcriptome profiling of Lrig1(+) colonic stem cells differs markedly from the profiling of highly proliferative, Lgr5(+) colonic stem cells; genes upregulated in the Lrig1(+) population include those involved in cell cycle repression and response to oxidative damage. Loss of Apc in Lrig1(+) cells leads to intestinal adenomas, and genetic ablation of Lrig1 results in heightened ErbB1-3 expression and duodenal adenomas. These results shed light on the relationship between proliferative and quiescent intestinal stem cells and support a model in which intestinal stem cell quiescence is maintained by calibrated ErbB signaling with loss of a negative regulator predisposing to neoplasia.
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Colon/metabolismo , Genes Supresores de Tumor , Intestino Delgado/metabolismo , Glicoproteínas de Membrana/metabolismo , Proteínas del Tejido Nervioso/metabolismo , Adenoma/patología , Proteína de la Poliposis Adenomatosa del Colon/metabolismo , Animales , Colon/citología , Receptores ErbB/metabolismo , Perfilación de la Expresión Génica , Humanos , Neoplasias Intestinales/patología , Intestino Delgado/citología , Ratones , Receptores Acoplados a Proteínas G/metabolismo , Transducción de Señal , Células Madre/citología , Células Madre/metabolismoRESUMEN
The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.
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Movimiento Celular , Rastreo Celular , Células/citología , Biología Evolutiva/métodos , Embrión de Mamíferos/citología , Feto/citología , Difusión de la Información , Organogénesis , Adulto , Animales , Atlas como Asunto , Técnicas de Cultivo de Célula , Supervivencia Celular , Visualización de Datos , Femenino , Humanos , Imagenología Tridimensional , Masculino , Modelos Animales , Organogénesis/genética , Organoides/citología , Células Madre/citologíaRESUMEN
To understand the genetic contribution to primary pediatric cardiomyopathy, we performed exome sequencing in a large cohort of 528 children with cardiomyopathy. Using clinical interpretation guidelines and targeting genes implicated in cardiomyopathy, we identified a genetic cause in 32% of affected individuals. Cardiomyopathy sub-phenotypes differed by ancestry, age at diagnosis, and family history. Infants < 1 year were less likely to have a molecular diagnosis (p < 0.001). Using a discovery set of 1,703 candidate genes and informatic tools, we identified rare and damaging variants in 56% of affected individuals. We see an excess burden of damaging variants in affected individuals as compared to two independent control sets, 1000 Genomes Project (p < 0.001) and SPARK parental controls (p < 1 × 10-16). Cardiomyopathy variant burden remained enriched when stratified by ancestry, variant type, and sub-phenotype, emphasizing the importance of understanding the contribution of these factors to genetic architecture. Enrichment in this discovery candidate gene set suggests multigenic mechanisms underlie sub-phenotype-specific causes and presentations of cardiomyopathy. These results identify important information about the genetic architecture of pediatric cardiomyopathy and support recommendations for clinical genetic testing in children while illustrating differences in genetic architecture by age, ancestry, and sub-phenotype and providing rationale for larger studies to investigate multigenic contributions.
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Cardiomiopatía Dilatada/genética , Exoma , Regulación de la Expresión Génica , Genotipo , Patrón de Herencia , Edad de Inicio , Cardiomiopatía Dilatada/metabolismo , Cardiomiopatía Dilatada/patología , Estudios de Casos y Controles , Niño , Estudios de Cohortes , Femenino , Perfilación de la Expresión Génica , Predisposición Genética a la Enfermedad , Pruebas Genéticas , Variación Genética , Humanos , Masculino , Fenotipo , Guías de Práctica Clínica como Asunto , Secuenciación del ExomaRESUMEN
In this Letter, the first name of author Virendra K. Chaudhri was incorrectly spelled 'Viren'; author Meenakshi Venkatasubramanian should also be associated with 'Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio 45221, USA'; authors Bruce J. Aronow, Nathan Salomonis, Harinder Singh and H. Leighton Grimes should also be associated with 'Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio 45229, USA'. The Letter has not been corrected online.
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BACKGROUND: In response to severe kidney injury, the kidney epithelium displays remarkable regenerative capabilities driven by adaptable resident epithelial cells. To date, it has been widely considered that the adult kidney lacks multipotent stem cells; thus, the cellular lineages responsible for repairing proximal tubule damage are incompletely understood. Leucine-rich repeats and immunoglobulin-like domains protein 1-expressing cells (Lrig1+ cells) have been identified as a long-lived cell in various tissues that can induce epithelial tissue repair. Therefore, we hypothesized that Lrig1+ cells participate in kidney development and tissue regeneration. METHODS: We investigated the role of Lrig1+ cells in kidney injury using mouse models. The localization of Lrig1+ cells in the kidney was examined throughout mouse development. The function of Lrig1+ progeny cells in acute kidney injury repair was examined in vivo using a tamoxifen-inducible Lrig1-specific Cre recombinase-based lineage tracing in three different kidney injury mouse models. Additionally, we conducted single-cell RNA-sequencing to characterize the transcriptional signature of Lrig1+ cells and to trace their progeny. RESULTS: Lrig1+ cells were present during kidney development and contributed to formation of the proximal tubule and collecting duct structures in mature mouse kidneys. In three-dimensional culture, single Lrig1+ cells demonstrated long-lasting propagation and differentiated into the proximal tubule and collecting duct lineages. These Lrig1+ proximal tubule cells highly expressed progenitor-like and quiescence-related genes, giving rise to a novel cluster of cells with regenerative potential in adult kidneys. Moreover, these long-lived Lrig1+ cells expanded and repaired damaged proximal tubules in response to three types of acute kidney injury in mice. CONCLUSIONS: These findings highlight the critical role of Lrig1+ cells in kidney regeneration.
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An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of individuals with ulcerative colitis (UC) require colectomy within 5 years of diagnosis, but polygenic risk scores (PRSs) utilizing findings from genome-wide association studies (GWASs) are unable to provide meaningful prediction of this adverse status. By contrast, in Crohn disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a transcriptional risk score (TRS). Here, we demonstrate that a measured TRS based on bulk rectal gene expression in the PROTECT inception cohort study has a positive predictive value approaching 50% for colectomy. Single-cell profiling demonstrates that the genes are active in multiple diverse cell types from both the epithelial and immune compartments. Expression quantitative trait locus (QTL) analysis identifies genes with differential effects at baseline and week 52 follow-up, but for the most part, differential expression associated with colectomy risk is independent of local genetic regulation. Nevertheless, a predicted polygenic transcriptional risk score (PPTRS) derived by summation of transcriptome-wide association study (TWAS) effects identifies UC-affected individuals at 5-fold elevated risk of colectomy with data from the UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with TWASs for stratification of risk of disease complications.
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Colectomía/estadística & datos numéricos , Colitis Ulcerosa/cirugía , Enfermedad de Crohn/cirugía , Sitios de Carácter Cuantitativo , Transcriptoma , Bancos de Muestras Biológicas , Estudios de Cohortes , Colitis Ulcerosa/complicaciones , Colitis Ulcerosa/diagnóstico , Colitis Ulcerosa/genética , Colon/metabolismo , Colon/patología , Colon/cirugía , Enfermedad de Crohn/complicaciones , Enfermedad de Crohn/diagnóstico , Enfermedad de Crohn/genética , Conjuntos de Datos como Asunto , Progresión de la Enfermedad , Perfilación de la Expresión Génica , Estudio de Asociación del Genoma Completo , Humanos , Herencia Multifactorial , Pronóstico , Medición de Riesgo , Reino UnidoRESUMEN
Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in the alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns for perturbation analyses, we developed CellDrift (https://github.com/KANG-BIOINFO/CellDrift), a generalized linear model-based functional data analysis method that is capable of identifying covarying temporal patterns of various cell types in response to perturbations. As compared to several other approaches, CellDrift demonstrated superior performance in the identification of temporally varied perturbation patterns and the ability to impute missing time points. We applied CellDrift to multiple longitudinal datasets, including COVID-19 disease progression and gastrointestinal tract development, and demonstrated its ability to identify specific gene programs associated with sequential biological processes, trajectories and outcomes.
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COVID-19 , COVID-19/genética , Humanos , Modelos LinealesRESUMEN
Recent evidence suggests that lncRNAs play an integral regulatory role in numerous functions, including determination of cellular identity. We determined global expression (RNA-seq) and genome-wide profiles (ChIP-seq) of histone post-translational modifications and p53 binding in human embryonic stem cells (hESCs) undergoing differentiation to define a high-confidence set of 40 lncRNAs, which are p53 transcriptional targets. We focused on lncRNAs highly expressed in pluripotent hESCs and repressed by p53 during differentiation to identify lncPRESS1 as a p53-regulated transcript that maintains hESC pluripotency in concert with core pluripotency factors. RNA-seq of hESCs depleted of lncPRESS1 revealed that lncPRESS1 controls a gene network that promotes pluripotency. Further, we found that lncPRESS1 physically interacts with SIRT6 and prevents SIRT6 chromatin localization, which maintains high levels of histone H3K56 and H3K9 acetylation at promoters of pluripotency genes. In summary, we describe a p53-regulated, pluripotency-specific lncRNA that safeguards the hESC state by disrupting SIRT6 activity.
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Diferenciación Celular/genética , Diferenciación Celular/fisiología , Células Madre Embrionarias/fisiología , Histonas/metabolismo , Células Madre Pluripotentes/metabolismo , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Proteína p53 Supresora de Tumor/metabolismo , Cromatina/metabolismo , Células Madre Embrionarias/citología , Histona Desacetilasas , Histonas/genética , Humanos , Células Madre Pluripotentes/citología , Procesamiento Proteico-Postraduccional/genética , Sirtuinas/genética , Sirtuinas/metabolismo , Proteína p53 Supresora de Tumor/genéticaRESUMEN
Heterozygous NRXN1 deletions constitute the most prevalent currently known single-gene mutation associated with schizophrenia, and additionally predispose to multiple other neurodevelopmental disorders. Engineered heterozygous NRXN1 deletions impaired neurotransmitter release in human neurons, suggesting a synaptic pathophysiological mechanism. Utilizing this observation for drug discovery, however, requires confidence in its robustness and validity. Here, we describe a multicenter effort to test the generality of this pivotal observation, using independent analyses at two laboratories of patient-derived and newly engineered human neurons with heterozygous NRXN1 deletions. Using neurons transdifferentiated from induced pluripotent stem cells that were derived from schizophrenia patients carrying heterozygous NRXN1 deletions, we observed the same synaptic impairment as in engineered NRXN1-deficient neurons. This impairment manifested as a large decrease in spontaneous synaptic events, in evoked synaptic responses, and in synaptic paired-pulse depression. Nrxn1-deficient mouse neurons generated from embryonic stem cells by the same method as human neurons did not exhibit impaired neurotransmitter release, suggesting a human-specific phenotype. Human NRXN1 deletions produced a reproducible increase in the levels of CASK, an intracellular NRXN1-binding protein, and were associated with characteristic gene-expression changes. Thus, heterozygous NRXN1 deletions robustly impair synaptic function in human neurons regardless of genetic background, enabling future drug discovery efforts.
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Proteínas de Unión al Calcio/genética , Mutación , Moléculas de Adhesión de Célula Nerviosa/genética , Neuronas/metabolismo , Neurotransmisores/metabolismo , Esquizofrenia/metabolismo , Estudios de Casos y Controles , Transdiferenciación Celular , Células Cultivadas , Estudios de Cohortes , Células Madre Embrionarias/citología , Expresión Génica , Guanilato-Quinasas/metabolismo , Heterocigoto , Humanos , Células Madre Pluripotentes Inducidas/citologíaRESUMEN
BACKGROUND: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ââreflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. METHODS: We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. RESULTS: With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. CONCLUSION: In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.
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COVID-19 , Registros Electrónicos de Salud , Humanos , Recolección de Datos , Registros , Análisis por ConglomeradosRESUMEN
AIM: To predict ambulatory status and Gross Motor Function Classification System (GMFCS) levels in patients with cerebral palsy (CP) by applying natural language processing (NLP) to electronic health record (EHR) clinical notes. METHOD: Individuals aged 8 to 26 years with a diagnosis of CP in the EHR between January 2009 and November 2020 (~12 years of data) were included in a cross-sectional retrospective cohort of 2483 patients. The cohort was divided into train-test and validation groups. Positive predictive value, sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated for prediction of ambulatory status and GMFCS levels. RESULTS: The median age was 15 years (interquartile range 10-20 years) for the total cohort, with 56% being male and 75% White. The validation group resulted in 70% sensitivity, 88% specificity, 81% positive predictive value, and 0.89 AUC for predicting ambulatory status. NLP applied to the EHR differentiated between GMFCS levels I-II and III (15% sensitivity, 96% specificity, 46% positive predictive value, and 0.71 AUC); and IV and V (81% sensitivity, 51% specificity, 70% positive predictive value, and 0.75 AUC). INTERPRETATION: NLP applied to the EHR demonstrated excellent differentiation between ambulatory and non-ambulatory status, and good differentiation between GMFCS levels I-II and III, and IV and V. Clinical use of NLP may help to individualize functional characterization and management. WHAT THIS PAPER ADDS: Natural language processing (NLP) applied to the electronic health record (EHR) can predict ambulatory status in children with cerebral palsy (CP). NLP provides good prediction of Gross Motor Function Classification System level in children with CP using the EHR. NLP methods described could be integrated in an EHR system to provide real-time information.
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Parálisis Cerebral , Niño , Humanos , Masculino , Adolescente , Adulto Joven , Adulto , Femenino , Parálisis Cerebral/complicaciones , Parálisis Cerebral/diagnóstico , Procesamiento de Lenguaje Natural , Estudios Retrospectivos , Estudios Transversales , Registros Electrónicos de SaludRESUMEN
Antibiotic-resistant superbug bacteria represent a global health problem with no imminent solutions. Here we demonstrate that the combination (termed AB569) of acidified nitrite (A-NO2-) and Na2-EDTA (disodium ethylenediaminetetraacetic acid) inhibited all Gram-negative and Gram-positive bacteria tested. AB569 was also efficacious at killing the model organism Pseudomonas aeruginosa in biofilms and in a murine chronic lung infection model. AB569 was not toxic to human cell lines at bactericidal concentrations using a basic viability assay. RNA-Seq analyses upon treatment of P. aeruginosa with AB569 revealed a catastrophic loss of the ability to support core pathways encompassing DNA, RNA, protein, ATP biosynthesis, and iron metabolism. Electrochemical analyses elucidated that AB569 produced more stable SNO proteins, potentially explaining one mechanism of bacterial killing. Our data implicate that AB569 is a safe and effective means to kill pathogenic bacteria, suggesting that simple strategies could be applied with highly advantageous therapeutic/toxicity index ratios to pathogens associated with a myriad of periepithelial infections and related disease scenarios.
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Antibacterianos/química , Antibacterianos/farmacología , Bacterias/efectos de los fármacos , Ácido Edético/farmacología , Nitrito de Sodio/farmacología , Animales , Antibacterianos/uso terapéutico , Biopelículas/efectos de los fármacos , Modelos Animales de Enfermedad , Regulación hacia Abajo , Farmacorresistencia Bacteriana/efectos de los fármacos , Ácido Edético/química , Enfermedades Pulmonares/tratamiento farmacológico , Enfermedades Pulmonares/microbiología , Redes y Vías Metabólicas , Ratones , Nitritos/química , Nitritos/farmacología , Pseudomonas aeruginosa/efectos de los fármacosRESUMEN
Viruses can subvert a number of cellular processes including splicing in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection, datasets from the betacoronaviruses SARS-CoV and MERS, as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification, and have a smaller number of exons as compared with differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by differential alternative splicing and gene expression in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS. The alternative splicing changes observed in betacoronaviruses infection potentially modify a broad range of cellular functions, via changes in the functions of the products of a diverse set of genes involved in different biological processes.
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COVID-19 , Gripe Humana , Infección por el Virus Zika , Virus Zika , Empalme Alternativo , COVID-19/genética , Humanos , Subtipo H3N2 del Virus de la Influenza A , SARS-CoV-2/genética , Virus Zika/genéticaRESUMEN
An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development, and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, re-analysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP and external research efforts.
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Delineating hierarchical cellular states, including rare intermediates and the networks of regulatory genes that orchestrate cell-type specification, are continuing challenges for developmental biology. Single-cell RNA sequencing is greatly accelerating such research, given its power to provide comprehensive descriptions of genomic states and their presumptive regulators. Haematopoietic multipotential progenitor cells, as well as bipotential intermediates, manifest mixed-lineage patterns of gene expression at a single-cell level. Such mixed-lineage states may reflect the molecular priming of different developmental potentials by co-expressed alternative-lineage determinants, namely transcription factors. Although a bistable gene regulatory network has been proposed to regulate the specification of either neutrophils or macrophages, the nature of the transition states manifested in vivo, and the underlying dynamics of the cell-fate determinants, have remained elusive. Here we use single-cell RNA sequencing coupled with a new analytic tool, iterative clustering and guide-gene selection, and clonogenic assays to delineate hierarchical genomic and regulatory states that culminate in neutrophil or macrophage specification in mice. We show that this analysis captured prevalent mixed-lineage intermediates that manifested concurrent expression of haematopoietic stem cell/progenitor and myeloid progenitor cell genes. It also revealed rare metastable intermediates that had collapsed the haematopoietic stem cell/progenitor gene expression programme, instead expressing low levels of the myeloid determinants, Irf8 and Gfi1 (refs 9, 10, 11, 12, 13). Genetic perturbations and chromatin immunoprecipitation followed by sequencing revealed Irf8 and Gfi1 as key components of counteracting myeloid-gene-regulatory networks. Combined loss of these two determinants 'trapped' the metastable intermediate. We propose that mixed-lineage states are obligatory during cell-fate specification, manifest differing frequencies because of their dynamic instability and are dictated by counteracting gene-regulatory networks.
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Diferenciación Celular/genética , Linaje de la Célula/genética , Perfilación de la Expresión Génica/métodos , Redes Reguladoras de Genes , Macrófagos/citología , Neutrófilos/citología , Análisis de la Célula Individual/métodos , Animales , Inmunoprecipitación de Cromatina , Proteínas de Unión al ADN/metabolismo , Femenino , Factores Reguladores del Interferón/metabolismo , Macrófagos/metabolismo , Masculino , Ratones , Ratones Endogámicos C57BL , Modelos Biológicos , Células Progenitoras Mieloides/citología , Células Progenitoras Mieloides/metabolismo , Neutrófilos/metabolismo , Análisis de Secuencia de ARN , Factores de Transcripción/genética , Factores de Transcripción/metabolismoRESUMEN
BACKGROUND: Immunofluorescent confocal microscopy uses labeled antibodies as probes against specific macromolecules to discriminate between multiple cell types. For images of the developmental mouse lung, these cells are themselves organized into densely packed higher-level anatomical structures. These types of images can be challenging to segment automatically for several reasons, including the relevance of biomedical context, dependence on the specific set of probes used, prohibitive cost of generating labeled training data, as well as the complexity and dense packing of anatomical structures in the image. The use of an application ontology helps surmount these challenges by combining image data with its metadata to provide a meaningful biological context, modeled after how a human expert would make use of contextual information to identify histological structures, that constrains and simplifies the process of segmentation and object identification. RESULTS: We propose an innovative approach for the semi-supervised analysis of complex and densely packed anatomical structures from immunofluorescent images that utilizes an application ontology to provide a simplified context for image segmentation and object identification. We describe how the logical organization of biological facts in the form of an ontology can provide useful constraints that facilitate automatic processing of complex images. We demonstrate the results of ontology-guided segmentation and object identification in mouse developmental lung images from the Bioinformatics REsource ATlas for the Healthy lung database of the Molecular Atlas of Lung Development (LungMAP1) program CONCLUSION: We describe a novel ontology-guided approach to segmentation and classification of complex immunofluorescence images of the developing mouse lung. The ontology is used to automatically generate constraints for each image based on its biomedical context, which facilitates image segmentation and classification.
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Algoritmos , Procesamiento de Imagen Asistido por Computador , Pulmón , Microscopía Confocal , Animales , Técnica del Anticuerpo Fluorescente , Pulmón/diagnóstico por imagen , RatonesRESUMEN
Generating detailed and accurate organogenesis models using single-cell RNA-seq data remains a major challenge. Current methods have relied primarily on the assumption that descendant cells are similar to their parents in terms of gene expression levels. These assumptions do not always hold for in vivo studies, which often include infrequently sampled, unsynchronized, and diverse cell populations. Thus, additional information may be needed to determine the correct ordering and branching of progenitor cells and the set of transcription factors (TFs) that are active during advancing stages of organogenesis. To enable such modeling, we have developed a method that learns a probabilistic model that integrates expression similarity with regulatory information to reconstruct the dynamic developmental cell trajectories. When applied to mouse lung developmental data, the method accurately distinguished different cell types and lineages. Existing and new experimental data validated the ability of the method to identify key regulators of cell fate.
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AIM: To characterize the patterns of care of children with cerebral palsy (CP) in a tertiary healthcare system. METHOD: Electronic health record data from 2009 to 2019 were extracted for children with CP. Machine learning hierarchical clustering was used to identify clusters of care. The ratio of in-person to care coordination visits was calculated for each specialty. RESULTS: The sample included 6369 children with CP (55.7% males, 44.3% females, 76.2% white, 94.7% non-Hispanic; with a mean age of 8y 2mo [SD 5y 10mo; range 0-21y; median 7y 1mo]) at the time of diagnosis. A total of 3.7 million in-person visits and care coordination notes were identified across 34 specialties. The duration of care averaged 5 years 5 months with five specialty interactions and 21.8 in-person visits per year per child. Seven clusters of care were identified, including: musculoskeletal and function; neurological; high-frequency/urgent care services; procedures; comorbid diagnoses; development and behavioral; and primary care. Network analysis showed shared membership among several clusters. INTERPRETATION: Coordination of care is a central element for children with CP. Medical informatics, machine learning, and big data approaches provide unique insights into care delivery to inform approaches to improve outcomes for children with CP. What this paper adds Seven primary clusters of care were identified: musculoskeletal and function; neurological; high-frequency/urgent care services; procedures; comorbid diagnoses; development and behavioral; and primary care. The in-person to care coordination visit ratio was 1:5 overall for healthcare encounters. Most interactions with care teams occur outside of in-person visits. The ratio of in-person to care coordination activities differ by specialty.
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Parálisis Cerebral/terapia , Grupo de Atención al Paciente , Adolescente , Niño , Preescolar , Registros Electrónicos de Salud , Femenino , Humanos , Lactante , Masculino , Adulto JovenRESUMEN
Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.