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Background: The use of objective structured clinical examinations (OSCEs) is a well-established method of clinical assessment in the medical profession, and these are currently being integrated into advanced practice nursing curricula. Method: A program assessment was conducted at a current family nurse practitioner track within a southwestern U.S. university using the OSCE evaluative strategy. The logic model from the Centers for Disease Control and Prevention framework was incorporated. Both focus group and the de-identified faculty-scored student rubrics during the fall, spring, and summer semesters of one cohort of students (N = 73) were examined. Results: Strengths and challenges were found in the areas of student preparation, scoring/grading with variations of inter-rater reliability, and debriefing. Conclusion: Establishing a specific OSCE center with a dedicated director could support adequate attainment of formative and summative competencies for nurse practitioners and provide faculty education and standardized student preparation, while adhering to the multiple guidelines and standards related to nurse practitioner competency evaluation with simulation. [J Contin Educ Nurs. 2023;54(4):169–175.] [ABSTRACT FROM AUTHOR]

Aims: Reactive astrocytes in Alzheimer's disease (AD) have traditionally been demonstrated by increased glial fibrillary acidic protein (GFAP) immunoreactivity; however, astrocyte reaction is a complex and heterogeneous phenomenon involving multiple astrocyte functions beyond cytoskeletal remodelling. To better understand astrocyte reaction in AD, we conducted a systematic review of astrocyte immunohistochemical studies in post‐mortem AD brains followed by bioinformatics analyses on the extracted reactive astrocyte markers. Methods: NCBI PubMed, APA PsycInfo and WoS‐SCIE databases were interrogated for original English research articles with the search terms 'Alzheimer's disease' AND 'astrocytes.' Bioinformatics analyses included protein–protein interaction network analysis, pathway enrichment, and transcription factor enrichment, as well as comparison with public human ‐omics datasets. Results: A total of 306 articles meeting eligibility criteria rendered 196 proteins, most of which were reported to be upregulated in AD vs control brains. Besides cytoskeletal remodelling (e.g., GFAP), bioinformatics analyses revealed a wide range of functional alterations including neuroinflammation (e.g., IL6, MAPK1/3/8 and TNF), oxidative stress and antioxidant defence (e.g., MT1A/2A, NFE2L2, NOS1/2/3, PRDX6 and SOD1/2), lipid metabolism (e.g., APOE, CLU and LRP1), proteostasis (e.g., cathepsins, CRYAB and HSPB1/2/6/8), extracellular matrix organisation (e.g., CD44, MMP1/3 and SERPINA3), and neurotransmission (e.g., CHRNA7, GABA, GLUL, GRM5, MAOB and SLC1A2), among others. CTCF and ESR1 emerged as potential transcription factors driving these changes. Comparison with published ‐omics datasets validated our results, demonstrating a significant overlap with reported transcriptomic and proteomic changes in AD brains and/or CSF. Conclusions: Our systematic review of the neuropathological literature reveals the complexity of AD reactive astrogliosis. We have shared these findings as an online resource available at www.astrocyteatlas.org. [ABSTRACT FROM AUTHOR]

Abstract Background Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types. Results We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients. Conclusion The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications.

Background: The APOEɛ4 allele is the largest genetic risk factor for late-onset Alzheimer's disease (AD). Recent literature suggested that the contribution of APOEɛ4 to AD risk could be population-specific, with ɛ4 conferring a lower risk to Blacks or African Americans.Objective: To investigate the effect of APOE haplotypes on AD risk in individuals with European ancestry (EU) and Blacks or African Americans (AA).Methods: We selected data from 1) the National Alzheimer's Coordinating Center: a total of 3,486 AD cases and 4,511 controls (N = 7,997, 60% female) with genotypes from the Alzheimer's Disease Genetics Consortium (ADGC), and 2) the Rush University Religious Orders Study and Memory and Aging Project (ROSMAP) cohort with 578 AD and 670 controls (N = 1,248, 60% female). Using ɛ3 homozygotes as the reference, we compared the association of various APOE haplotypes with the clinical and neuropathological correlates of dementia in AA and EU.Results: In both cohorts, we find no difference in the odds or age of onset of AD among the ɛ4-linked haplotypes defined by rs769449 within either AA or EU. Additionally, while APOEɛ4 was associated with a faster rate of decline, no differences were found in rate of decline, clinical or neuropathological features among the ɛ4-linked haplotypes. Further analysis with other variants near the APOE locus failed to identify any effect modification.Conclusion: Our study finds similar effects of the ɛ4-linked haplotypes defined by rs769449 on AD as compared to ɛ3 in both AA and EU. Future studies are required to understand the heterogeneity of APOE conferred risk of AD among various genotypes and populations. [ABSTRACT FROM AUTHOR]

Background: The development of robust blood‐based biomarkers for pathological and clinical characterization of Alzheimer's disease (AD) is necessary, particularly as therapeutic approaches shift towards early intervention. Novel, ultra‐sensitive OlinkTM technology allows for high‐throughput quantification of protein signatures in biofluids. In this study, we examined the utility of this technology to identify plasma biomarkers associated with longitudinal cognitive performance in individuals presenting with mild cognitive impairment (MCI). Methods: 60 participants from the Massachusetts ADRC Longitudinal Cohort with a clinical diagnosis of MCI, baseline global CDR of 0.5, and at least five annual follow‐up evaluations were classified into two groups based on their global CDR trajectory: MCI‐decline (an increase in global CDR from 0.5 to 1) and MCI‐stable (no change in global CDR). Five OlinkTM Proximity Extension Assay (PEA) panels were assessed for technical reliability and used to quantify 460 plasma proteins at baseline visit. We built statistical models to identify proteins whose plasma levels were predictive of future cognitive decline, and used machine‐learning to evaluate the utility of these proteins for predicting conversion from MCI to dementia, relative to clinical and demographic predictors. Result: OlinkTM panels exhibited excellent technical precision and plate‐to‐plate replication. Of the 460 proteins measured, 60 did not pass quality control thresholds. A final model adjusting for age and sex identified 14 proteins with a significant fold‐change in MCI‐decline compared to MCI‐stable (p<0.05), including NfL, CX3CL1, M‐CSF, VEGF‐A, IL‐8, NOS3, TNFRSF12A, and PHOSPHO1. An additional 10 proteins approached significance (p<0.1), primarily representative of inflammatory and vascular processes. Addition of these proteins to a supervised classification model informed by baseline cognitive measured substantially improved the overall accuracy from 63% to 83.3% (AUC: 0.88, sensitivity: 0.76, specificity: 0.87). Conclusion: Our findings suggest that plasma biomarkers of neuroinflammation and vascular injury have value as predictors of MCI‐to‐dementia progression. These circulating biomarkers may reflect CNS processes, blood‐brain barrier dysfunction, and/or systemic inflammation that drive AD associated pathophysiologies, or represent comorbid vascular pathologies. Developing a plasma biomarker panel could aid in prognostic deliberations by identifying MCI individuals at higher risk of progressing to dementia in clinical practice. [ABSTRACT FROM AUTHOR]

Background: With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. Methods: To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Conclusions: Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge.

Comparisons of stem cell experiments at both molecular and semantic levels remain challenging due to inconsistencies in results, data formats, and descriptions among biomedical research discoveries. The Harvard Stem Cell Institute (HSCI) has created the Stem Cell Commons (stemcellcommons.org), an open, community-based approach to data sharing. Experimental information is integrated using the Investigation-Study-Assay tabular format (ISA-Tab) used by over 30 organizations (ISA Commons, isacommons.org). The early adoption of this format permitted the novel integration of three independent systems to facilitate stem cell data storage, exchange and analysis: the Blood Genomics Repository, the Stem Cell Discovery Engine, and the new Refinery platform that links the Galaxy analytical engine to data repositories.

Relates a nurse's experience with an elderly patient who grieved for a son who died 69 years earlier. Importance of listening; Trusting relationships between patients and nurses; Role of the nurse in emotional healing.

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Comparisons of stem cell experiments at both molecular and semantic levels remain challenging due to inconsistencies in results, data formats, and descriptions among biomedical research discoveries. The Harvard Stem Cell Institute (HSCI) has created the Stem Cell Commons (stemcellcommons.org), an open, community-based approach to data sharing. Experimental information is integrated using the Investigation-Study-Assay tabular format (ISA-Tab) used by over 30 organizations (ISA Commons, isacommons.org). The early adoption of this format permitted the novel integration of three independent systems to facilitate stem cell data storage, exchange and analysis: the Blood Genomics Repository, the Stem Cell Discovery Engine, and the new Refinery platform that links the Galaxy analytical engine to data repositories.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.