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At least 19 recordsLinked to original sources
PubMed2026

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan® for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans↗
PubMed1992

DeoR repression at-a-distance only weakly responds to changes in interoperator separation and DNA topology.

The interoperator distance between a synthetic operator Os and the deoP2O2-galK fusion was varied between 46 and 176 bp. The repression of the deoP2 directed galK expression as a function of the interoperator distance (center-to-center) was measured in vivo in a single-copy system. The results show that the DeoR repressor efficiently can repress transcription at all the interoperator distances tested. The degree of repression depends very little on the spacing between the operators, however, a weak periodic dependency of 8-11 bp may exist.

Bacterial Proteins↗
PubMed2025

PMkbase (version 1.0): an interactive web-based tool for tracking bacterial metabolic traits using phenotype microarrays made interoperable with sequence information and visualizing/processing PM data.

Bacteria showcase remarkable metabolic diversity and traits, even among strains of the same species. In recent years, a large number of bacterial genomes have been sequenced, leading to the elucidation and documentation of genomic differences and commonalities across and within species. Genome-scale metabolic reconstructions, which are often defined and curated using data from phenotype microarrays, elucidate the differences in metabolic traits resulting from genomic diversity. These microarrays measure cellular respiration on a variety of carbon, nitrogen, phosphorus, and sulfur sources and various stressors and inhibitors over a period of time to determine the metabolic activity of a given strain. Despite their popularity in measuring bacterial metabolic activity and traits, no public databases that allow researchers to warehouse, access, and analyze this information currently exist. Additionally, there are no publicly available tools that allow researchers to view the variance of these metabolic traits across bacterial strains. To address this need, we present Phenotype Microarray Knowledgebase (PMkbase [version 1.0], https://pmkbase.com/), an interactive database that acts as a repository of phenotype microarray (PM) data with integrated sequence information. Binarized activity calls, along with associated kinetic parameters, are made for all metabolic substrates and inhibitors. Users can upload their own data for analysis and visualization and to perform quality checks on their experiments. PMkbase will address an unmet need to track and view bacterial metabolic traits and provide researchers with valuable information to develop metabolic models, enrich pangenomic analyses, and design new experiments.IMPORTANCEBacterial species can be differentiated by their metabolic profiles or the type of nutrients they consume. Interestingly, strains within the same species also display differences in nutrient consumption. Phenotype microarrays are a high-throughput, widely used technology to measure which substrates can be metabolized by various microbial strains and the extent to which inhibitors can affect it. Despite their widespread use, public databases to parse and access this data type at scale do not exist. PMkbase, which contains 9,024 data points for nitrogen substrate utilization, 41,664 data points for carbon substrate utilization, 8,448 data points for phosphorus/sulfur substrate utilization, and 27,264 data points on various antibiotics across three species (Escherichia coli, Pseudomonas putida, and Staphylococcus aureus), has been developed to allow researchers to freely access PM data, along with enriching the data with sequence information.

Bacteria↗
PubMed2025

Privacy-preserving framework for genomic computations via multi-key homomorphic encryption.

MOTIVATION: The affordability of genome sequencing and the widespread availability of genomic data have opened up new medical possibilities. Nevertheless, they also raise significant concerns regarding privacy due to the sensitive information they encompass. These privacy implications act as barriers to medical research and data availability. Researchers have proposed privacy-preserving techniques to address this, with cryptography-based methods showing the most promise. However, existing cryptography-based designs lack (i) interoperability, (ii) scalability, (iii) a high degree of privacy (i.e. compromise one to have the other), or (iv) multiparty analyses support (as most existing schemes process genomic information of each party individually). Overcoming these limitations is essential to unlocking the full potential of genomic data while ensuring privacy and data utility. Further research and development are needed to advance privacy-preserving techniques in genomics, focusing on achieving interoperability and scalability, preserving data utility, and enabling secure multiparty computation. RESULTS: This study aims to overcome the limitations of current cryptography-based techniques by employing a multi-key homomorphic encryption scheme. By utilizing this scheme, we have developed a comprehensive protocol capable of conducting diverse genomic analyses. Our protocol facilitates interoperability among individual genome processing and enables multiparty tests, analyses of genomic databases, and operations involving multiple databases. Consequently, our approach represents an innovative advancement in secure genomic data processing, offering enhanced protection and privacy measures. AVAILABILITY AND IMPLEMENTATION: All associated code and documentation are available at https://github.com/farahpoor/smkhe.

Computer Security↗
PubMed2026

The European Health Data Space and the Secondary Use of Sensitive Health Data.

INTRODUCTION: The European Health Data Space (EHDS) is one of the European Union's most ambitious data-governance projects. It aims to create a common framework through which electronic health data can be accessed and reused across Member States for care, research, innovation, policy, and public-interest purposes. Its practical viability depends not only on digital infrastructure, but also on legal, ethical, and organisational harmonisation, particularly for genetic and genomic data. METHODS: This paper examines the EHDS with emphasis on the secondary use of health data. It reviews the EHDS institutional architecture, discusses Finland's Findata as a national model for structured access, and analyses challenges for data holders and data donors, including interoperability, governance burdens, privacy protection, residual re-identification risk, and genomic-data sensitivity. RESULTS: A cross-border cancer-genomics case study shows that the EHDS can streamline data discovery and the routing of access requests, but does not by itself eliminate legal fragmentation, heterogeneous ethics review, and consent-related barriers. DISCUSSION: Effective implementation will require harmonisation beyond infrastructure, including clearer consent standards, more consistent ethics procedures, interoperable metadata, and proportionate safeguards for genomic data.

Electronic Health Records↗
PubMed2026

Programmatic access to ICTV virus taxonomy through a public ontology API.

BACKGROUND: The International Committee on Taxonomy of Viruses (ICTV) is responsible for developing and maintaining a universal virus taxonomy. As the reference framework for organising the viral world, it is essential for virology and related fields. Despite its widespread use in research and public health, programmatic access to ICTV taxonomy has remained limited, posing challenges for integration, versioning, and interoperability across databases and bioinformatics resources requiring up-to-date virus taxonomy. FINDINGS: To address this, we developed a public and sustainable solution leveraging ontology-based APIs. All available ICTV Master Species List (MSL) releases, from MSL1 to MSL41, were transformed into a unified, semantically structured ontology comprising more than 195,000 current and historical entities and deployed through the Ontology Lookup Service (OLS). The ontology is automatically rebuilt and republished whenever a new MSL release becomes available. Complementary ICTV-NCBI mappings and helper libraries support integration into downstream systems. CONCLUSIONS: Together, these resources enable, for the first time, public programmatic retrieval of current and historical ICTV taxon names, taxonomic relationships, metadata, and persistent identifiers through stable endpoints, including resolution of former taxonomic terms to their current accepted taxon or taxa and retrieval of taxon histories across releases. More broadly, this work illustrates a general strategy for transforming structured biological datasets into semantically enriched graph resources exposed through scalable public APIs. These developments enhance interoperability, reduce manual curation, and support FAIR-aligned taxonomic data management in virology and pandemic preparedness.

API↗
PubMed2026

Programmatic access to ICTV virus taxonomy through a public ontology API.

The International Committee on Taxonomy of Viruses (ICTV) is responsible for developing and maintaining a universal virus taxonomy. As the reference framework for organising the viral world, it is essential for virology and related fields. Despite its widespread use in research and public health, programmatic access to ICTV taxonomy has remained limited, posing challenges for integration, versioning, and interoperability across databases and bioinformatics resources requiring up-to-date virus taxonomy. To address this, we developed a public and sustainable solution leveraging ontology-based APIs. Successive ICTV Master Species List (MSL) releases were transformed into a structured ontology and deployed as a unified representation through the Ontology Lookup Service (OLS). The framework also provides ICTV-NCBI mappings and helper libraries for integration into downstream systems. This enables, for the first time, public programmatic retrieval of current and historical virological taxon names, taxonomic relationships, metadata, and persistent identifiers through stable endpoints. More broadly, this work illustrates a general strategy for transforming structured biological datasets into semantically enriched graph resources exposed through scalable public APIs. These developments enhance interoperability, reduce manual curation, and support FAIR-aligned taxonomic data management in virology and pandemic preparedness.

API↗
PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗
PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗
PubMed2026

The need for standardization and improved open (meta)data practices in metaproteomics.

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices. Video Abstract.

Proteomics↗
PubMed1992

Blinded evaluation of planar technetium-99m-sestamibi myocardial perfusion studies.

Sestamibi planar myocardial perfusion studies were performed at Hotel-Dieu de Montreal on 28 patients with documented coronary artery disease and 16 normal subjects. Stress and rest studies were performed on separate days. These studies were sent to Virginia for interpretation while blinded as to age, sex, and other clinical information. Studies were quantitated independently by two operators (using a computer program modified for Sestamibi), and interpreted independently by two experienced interpreters. Computer quantitation of 2816 segments gave an average interoperator deviation of 2.2%. Pure quantitative criteria were applied for computer interpretation. By varying the detection threshold, we produced the entire ROC curve relating sensitivity and specificity as a function of detection threshold. Using only computer criteria for normal or abnormal, interoperator agreement by patient was 98% and 93% by view. The computer could achieve equal positive and negative predictive accuracy of 87%. Interpreters, allowed both quantitative and subjective judgment, agreed on 91% of 44 patients, 90% of 132 views, and 92% of 660 segments. Interpreters averaged 94% positive and 86% negative predictive accuracy.

Adult↗
PubMed1979

Cine-densitometric measurement of coronary arterial stenoses.

Computer-aided operator-interactive densitometry has been developed and applied to determine the percent stenosis for obstructive lesions in the coronary arterial tree. Phantom experiments performed to assess system linearity, accuracy of densitometric measurements, nonuniformity in image amplified response, and the interference of structure noise in measuring precision have been described. Three observers assessed the reproducibility of the method by repeating analyses on 20 stenoses in man recorded on 35-mm cine angiograms. Calculation of the intra- and interobserver errors found that their values significantly decrease with increasing percent stenosis. The reproducibility of the technique was also tested on stenoses that were exposed at multiple angles. The results agreed with those found for the intra- and interoperator errors. Limitations of the densitometric approach and desirability of further automation of the measurements are also discussed.

Cineangiography↗
PubMed1992

Determination of bone mineral density by dual x-ray absorptiometry in patients with uncemented total hip arthroplasty.

Bone remodeling is an expected sequela with total hip arthroplasty (THA). Although there are several methods of estimating bone response in THA patients from radiographs, there are no accurate and generally accepted methods for quantitative determinations in vivo. In this study, we describe an application of dual x-ray absorptiometry (DXA) for measuring bone mineral content and bone mineral density in the proximal femur following THA. DXA is a noninvasive technique with minimal radiation exposure (< 5 mrem). Various aspects of measurement error (accuracy and reliability) of this application of DXA were determined in a series of studies reported here. Accuracy error (how similar are the measured and actual values) was < 1% determined in bone phantoms of four densities. Precision error (how reproducible are the measurements) was also < 1% at all four densities in the phantoms and was only slightly elevated (0.9-1.5%) in repeated measurements of implanted cadaver femora. Precision error in vivo, determined both from multiple replicates on five patients and from duplicate scans on 30 patients, was further elevated but remained < 5%. Contributions to precision error, rotation of the leg, and interoperator variability were assessed; none was found to elevate precision error appreciably. We suggest that DXA is a feasible method for quantifying bone response following THA, and will allow discrimination of small changes (> 5%) not previously measurable.

Absorptiometry, Photon↗
PubMed1992

Reproducibility of lateral spine scans using dual energy X-ray absorptiometry.

Reproducibility of lateral spine dual energy X-ray absorptiometry (LAT DEXA) scans using a Lunar DPX-L scanner was assessed in a cadaveric phantom and in patients. One hundred phantom measurements over 7 months demonstrated a longitudinal stability of 1.7% (coefficient of variation, CV). Additional scans were performed with the phantom rotated by up to 20 degrees in each of the three orthogonal planes to assess the effects of variable patient positioning. Horizontal and vertical rotation of the spine had little effect on the estimated bone mineral density (BMD), however, axial rotation of greater than 8 degrees led to errors in the BMD measurement. One hundred consecutive patients had two lateral scans performed within 1 month. BMD (range 0.10-1.6 g/cm2) was determined for each scan by one operator. Significant overlap from ribs and pelvis was often seen with L2 and L4 vertebrae but one vertebra (L3) could be measured in every case. Intraoperator and interoperator variability was assessed by three experienced operators, each analyzing 10 patients' scans on five separate occasions, and was found to be less than 1.1% for a single vertebra. BMD estimation of vertebral bodies and midslices by lateral DEXA scans (CV% of 3.8% and 4.6%) have a 95% confidence interval of 0.074 g/cm2 and 0.096 g/cm2, respectively for two vertebrae. This variability is due mainly to axial rotation, with operator variability, horizontal rotation, and vertical rotation having little effect on BMD estimation.

Absorptiometry, Photon↗
PubMed2026

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗
PubMed1992

Change in occlusal height resulting from placement of pit and fissure sealants.

This in-vitro study was done to identify the amount of change in occlusal height resulting from standard sealant application technique and to determine whether this change was uniform for both a filled and an unfilled sealant material. Twelve dental hygienists experienced in sealant technique each applied 10 filled sealants and 10 unfilled sealants in standardized artificial teeth mounted in a dentiform and mannikin setup in a dental unit. The teeth were measured with a digital caliper before and after sealant placement. Measurements were from a predetermined point at the apical area of the teeth to the depth of the central fossa. For the sample of 240 teeth, the mean sealant thickness was 0.43 +/- 0.20 mm. When the data for the filled and unfilled sealants were examined separately, the means were 0.47 +/- 0.23 mm and 0.38 +/- 0.16 mm, respectively. A t-test indicated a significant difference at p < 0.001. Analysis of variance revealed significant interoperator differences in sealant thickness (p < 0.01).

Analysis of Variance↗
PubMed2023

The phenotype-genotype reference map: Improving biobank data science through replication.

Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.

Humans↗