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Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) generates genome-wide chromatin accessibility profiles, providing valuable insights into epigenetic gene regulation at both pooled-cell and single-cell population levels. Comprehensive analysis of ATAC-seq data involves the use of various interdependent programs. Learning the correct sequence of steps needed to process the data can represent a major hurdle. Selecting appropriate parameters at each stage, including pre-analysis, core analysis, and advanced downstream analysis, is important to ensure accurate analysis and interpretation of ATAC-seq data. Additionally, obtaining and working within a limited computational environment presents a significant challenge to non-bioinformatic researchers. Therefore, we present Cloud ATAC, an open-source, cloud-based interactive framework with a scalable, flexible, and streamlined analysis framework based on the best practices approach for pooled-cell and single-cell ATAC-seq data. These frameworks use on-demand computational power and memory, scalability, and a secure and compliant environment provided by the Google Cloud. Additionally, we leverage Jupyter Notebook's interactive computing platform that combines live code, tutorials, narrative text, flashcards, quizzes, and custom visualizations to enhance learning and analysis. Further, leveraging GPU instances has significantly improved the run-time of the single-cell framework. The source codes and data are publicly available through NIH Cloud lab https://github.com/NIGMS/ATAC-Seq-and-Single-Cell-ATAC-Seq-Analysis. This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
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Nube Computacional , Secuenciación de Nucleótidos de Alto Rendimiento , Programas Informáticos , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Biología Computacional/métodos , Secuenciación de Inmunoprecipitación de Cromatina/métodos , Análisis de la Célula Individual/métodos , Cromatina/genética , Cromatina/metabolismoRESUMEN
PURPOSE: Post-operative hyperglycemia is a known risk factor for post-surgical complications. The predictive value of pre-operative blood glucose levels, however, is less understood. This study aimed to determine if pre-operative screening blood glucose levels affect the rate of post-operative infection or wound complications. We also investigated if case urgency or anatomic location alters this relationship. METHODS: A single-institution retrospective chart review was performed to evaluate patients treated between 2018 and 2021. Subjects ≥ 18 years with closed, non-infected orthopaedic diagnoses requiring surgery were included. Case urgency, demographics, comorbidities, blood glucose level within twelve h prior to surgery, and hemoglobin A1c level within 3 months of surgery, were collected. Infections and wound complications were recorded as outcomes. RESULTS: A total of 775 subjects with a mean age of 61 (range 18-96) were identified, including 543 elective and 232 trauma patients, with a mean pre-operative fasting glucose value of 127.7 mg/dL (range, 49-388 mg/dL) and average HbA1c of 6.9%. The odds of infectious complications were increased by a factor of 1.01 for every 1-point increase in blood glucose (95% CI 1.01-1.02; p < 0.01). CONCLUSIONS: Pre-operative blood glucose levels greater than 137 mg/dL were associated with an increase in wound complications, but not deep infections. Infection rates stratified by anatomic site and case urgency were not impacted by pre-operative glucose levels. The increased risk of poor wound healing in patients with pre-operative hyperglycemia demonstrates that day of surgery point-of-care blood glucose screening can be a useful risk stratification tool.
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Glucemia , Hemoglobina Glucada , Hiperglucemia , Procedimientos Ortopédicos , Complicaciones Posoperatorias , Periodo Preoperatorio , Infección de la Herida Quirúrgica , Humanos , Glucemia/análisis , Glucemia/metabolismo , Persona de Mediana Edad , Estudios Retrospectivos , Anciano , Masculino , Femenino , Adulto , Procedimientos Ortopédicos/efectos adversos , Anciano de 80 o más Años , Factores de Riesgo , Infección de la Herida Quirúrgica/etiología , Infección de la Herida Quirúrgica/epidemiología , Infección de la Herida Quirúrgica/diagnóstico , Complicaciones Posoperatorias/etiología , Complicaciones Posoperatorias/diagnóstico , Complicaciones Posoperatorias/sangre , Hiperglucemia/diagnóstico , Hiperglucemia/etiología , Hiperglucemia/sangre , Hemoglobina Glucada/análisis , Adolescente , Adulto Joven , Valor Predictivo de las Pruebas , Medición de Riesgo/métodosRESUMEN
The risk of exposure of the general public or military personnel to high levels of ionizing radiation from nuclear weapons or radiological accidents is a dire national security matter. The development of advanced molecular biodosimetry methods, those that measure biological response, such as transcriptomics, to screen large populations of radiation-exposed victims is key to improving survival outcomes during radiological mass casualty scenarios. In this study, nonhuman primates were exposed to either 12.0 Gy cobalt-60 gamma (total-body irradiation, TBI) or X-ray (partial-body irradiation, PBI) 24 h after administration of a potential radiation medical countermeasure, gamma-tocotrienol (GT3). Changes in the jejunal transcriptomic profiles in GT3-treated and irradiated animals were compared to healthy controls to assess the extent of radiation damage. No major effect of GT3 on radiation-induced transcriptome at this radiation dose was identified. About 80% of the pathways with a known activation or repression state were commonly observed between both exposures. Several common pathways activated due to irradiation include FAK signaling, CREB signaling in the neurons, phagosome formation, and G-protein coupled signaling pathway. Sex-specific differences associated with excessive mortality among irradiated females were identified in this study, including Estrogen receptor signaling. Differential pathway activation was also identified across PBI and TBI, pointing towards altered molecular response for different degrees of bone marrow sparing and radiation doses. This study provides insight into radiation-induced changes in jejunal transcriptional profiles, supporting the investigation for the identification of biomarkers for radiation injury and countermeasure efficacy.
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Síndrome de Radiación Aguda , Transcriptoma , Masculino , Animales , Femenino , Síndrome de Radiación Aguda/tratamiento farmacológico , Yeyuno , Radiación Ionizante , PrimatesRESUMEN
The premise for this study emanated from the need to understand SARS-CoV-2 infections at the molecular level and to develop predictive tools for managing COVID-19 severity. With the varied clinical outcomes observed among infected individuals, creating a reliable machine learning (ML) model for predicting the severity of COVID-19 became paramount. Despite the availability of large-scale genomic and clinical data, previous studies have not effectively utilized multi-modality data for disease severity prediction using data-driven approaches. Our primary goal is to predict COVID-19 severity using a machine-learning model trained on a combination of patients' gene expression, clinical features, and co-morbidity data. Employing various ML algorithms, including Logistic Regression (LR), XGBoost (XG), Naïve Bayes (NB), and Support Vector Machine (SVM), alongside feature selection methods, we sought to identify the best-performing model for disease severity prediction. The results highlighted XG as the superior classifier, with 95% accuracy and a 0.99 AUC (Area Under the Curve), for distinguishing severity groups. Additionally, the SHAP analysis revealed vital features contributing to prediction, including several genes such as COX14, LAMB2, DOLK, SDCBP2, RHBDL1, and IER3-AS1. Notably, two clinical features, the absolute neutrophil count and Viremia Categories, emerged as top contributors. Integrating multiple data modalities has significantly improved the accuracy of disease severity prediction compared to using any single modality. The identified features could serve as biomarkers for COVID-19 prognosis and patient care, allowing clinicians to optimize treatment strategies and refine clinical decision-making processes for enhanced patient outcomes.
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BACKGROUND: Human trafficking (HT) is a serious public health issue. Survivors of HT seek medical care. Health care professionals may be inadequately trained to identify and support survivors. This study evaluated improvements in nurses' knowledge after a professional development workshop on HT. METHOD: Pre- and postevaluation surveys assessed nurses' self-reported changes in perceived knowledge of HT and its vulnerability factors, the health impact of HT, strategies for identification and assessment of HT, and response to and follow-up of HT. RESULTS: After the workshop, participants showed significant improvement in perceived knowledge of all measures, regardless of hours of previous training and years of practice. CONCLUSION: Perceived knowledge of HT identification and response can be improved through training of nurses, regardless of hours of previous training and years of practice. [J Contin Educ Nurs. 2024;55(1):26-32.].
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Trata de Personas , Enfermeras y Enfermeros , Personal de Enfermería en Hospital , Humanos , Personal de Enfermería en Hospital/educación , Competencia Clínica , Trata de Personas/prevención & control , Educación Continua en Enfermería , Conocimientos, Actitudes y Práctica en Salud , Encuestas y CuestionariosRESUMEN
Syphilis is caused by a spirochete, Treponema pallidum. Diagnosis of syphilis is made with a venereal disease research laboratory test. Treatment of choice is intramuscular injection benzathine Penicillin. The JarischâHerxheimer reaction (JHR) is a transient immunological phenomenon that can occur in patients during treatment for syphilis with penicillin. It is a rare phenomenon but can be a potentially severe one. It manifests clinically with short-term constitutional symptoms such as fever, chills, headache, and myalgia, besides exacerbation of existing cutaneous lesions. We report the case of a 24-year-old man presenting with JHR posttreatment with benzathine penicillin.
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mRNA localization and local translation enable exquisite spatial and temporal control of gene expression, particularly in polarized, elongated cells. These features are especially prominent in radial glial cells (RGCs), which are neural and glial precursors of the developing cerebral cortex and scaffolds for migrating neurons. Yet the mechanisms by which subcellular RGC compartments accomplish their diverse functions are poorly understood. Here, we demonstrate that mRNA localization and local translation of the RhoGAP ARHGAP11A in the basal endfeet of RGCs control their morphology and mediate neuronal positioning. Arhgap11a transcript and protein exhibit conserved localization to RGC basal structures in mice and humans, conferred by the 5' UTR. Proper RGC morphology relies upon active Arhgap11a mRNA transport and localization to the basal endfeet, where ARHGAP11A is locally synthesized. This translation is essential for positioning interneurons at the basement membrane. Thus, local translation spatially and acutely activates Rho signaling in RGCs to compartmentalize neural progenitor functions.
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Células Ependimogliales , Neuroglía , Humanos , Ratones , Animales , Células Ependimogliales/metabolismo , ARN Mensajero/metabolismo , Neuroglía/metabolismo , Neurogénesis , Corteza Cerebral , Proteínas Activadoras de GTPasa/genética , Proteínas Activadoras de GTPasa/metabolismoRESUMEN
The focus of radiation biodosimetry has changed recently, and a paradigm shift for using molecular technologies of omic platforms in addition to cytogenetic techniques has been observed. In our study, we have used a nonhuman primate model to investigate the impact of a supralethal dose of 12 Gy radiation on alterations in the lung transcriptome. We used 6 healthy and 32 irradiated animal samples to delineate radiation-induced changes. We also used a medical countermeasure, γ-tocotrienol (GT3), to observe any changes. We demonstrate significant radiation-induced changes in the lung transcriptome for total-body irradiation (TBI) and partial-body irradiation (PBI). However, no major influence of GT3 on radiation was noted in either comparison. Several common signaling pathways, including PI3K/AKT, GADD45, and p53, were upregulated in both exposures. TBI activated DNA-damage-related pathways in the lungs, whereas PTEN signaling was activated after PBI. Our study highlights the various transcriptional profiles associated with γ- and X-ray exposures, and the associated pathways include LXR/RXR activation in TBI, whereas pulmonary wound-healing and pulmonary fibrosis signaling was repressed in PBI. Our study provides important insights into the molecular pathways associated with irradiation that can be further investigated for biomarker discovery.
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Previous studies and our findings suggest upregulated expression of proinflammatory chemokines CCL3/4 in germinal center (GC) centrocytes. However, the role of CCL3/4 for centrocyte interactions with follicular T cells and regulation of humoral immunity is poorly understood. We found that CCL3 promotes chemotaxis of Tfr cells ex vivo. Two-photon imaging revealed that B cells-intrinsic production of CCL3 promotes their probing by follicular regulatory T cells (Tfr) within GCs of murine lymph nodes. Overall this study suggests that CCL3 facilitates direct interactions of foreign antigen-specific GC B cells and their negative regulation with Tfr cells in vivo.