When multiple LOINC parts map to the same SNOMED CT concept, it indicates that those LOINC parts are semantically equivalent according to SNOMED CT. Even though they are represented separately in LOINC, SNOMED CT provides the integration by grouping them under a single concept. This enriches the representation and allows for more complete reasoning and quality assurance across terminologies.
Analysis of High-Order Residual-Based Dissipation for Unsteady Compressible F...kgrimich
A comprehensive study of the numerical properties of high-order residual-based dissipation terms for unsteady compressible flows leads to the design of well-behaved, low dissipative schemes of third-, fifth- and seventh-order accuracy. The dissipation and dispersion properties of the schemes are then evaluated theoreticaly, through Fourier space analysis, and numerically, through selected test cases including the inviscid Taylor-Green Vortex flow.
This document describes a proposed social networking website that would understand users' tastes and preferences using an ontology and machine learning. The website would allow users to create profiles, post articles and comments. A Java program would query an ontology defined in Protege using classes like tastes and wines. It would retrieve user preferences using SPARQL and update a database with clusters of similar users. The system aims to continuously learn from user interactions to improve its understanding of customers.
Comparison of Reasoners for large Ontologies in the OWL 2 EL ProfileKathrin Dentler
This document compares several reasoners for classifying large ontologies in the OWL 2 EL profile. It introduces the author's PhD project on semantic interoperability for clinical data using SNOMED CT. It outlines dimensions for comparing reasoners, including reasoning characteristics, usability, and performance. Results show how reasoners differ in methodology, features, and performance when classifying SNOMED CT, with some reasoners proving more sound and complete.
This document provides instructions for installing and running Jena, a Java framework for building semantic web and linked data applications. It discusses RDF, the resource description framework, and describes how to download the necessary tools, create a Java project in Eclipse, add the Jena libraries to the project's build path, and import example source code to get started with the Jena API.
This document provides an introduction to working with triples and datasets using the Jena API in Java. It discusses how to [1] create a dataset and named model, [2] create resources, properties, and literals that compose a triple, and [3] connect the triple components by adding them to a model. It also briefly covers serializing the model contents to file in different RDF formats like RDF/XML, TTL, and N-Triple. The goal is to demonstrate the basic steps for building, querying, and persisting RDF triples with Jena.
The document introduces Jena, a Java framework for building Semantic Web applications. It discusses key Semantic Web technologies like RDF, RDFS, OWL and SPARQL. It also provides an overview of Jena's features for manipulating RDF graphs and querying them using SPARQL. Examples are given of how to use Jena's RDF and SPARQL APIs.
Yang Yu is proposing research on improving machine learning based ontology mapping by automatically obtaining training samples from the web. The proposed system would parse two input ontologies to generate queries to search engines and collect documents to use as samples for each ontology class. These samples would then be used to train text classifiers, which would produce probabilistic mappings between classes in the two ontologies. The results would be evaluated by comparing to mappings from human experts. Current work involves exploring alternative text classification tools and ways to utilize the probabilistic mapping values generated by the classifiers.
The document discusses processing OWL ontologies using the Jena ontology API in Java. It describes how to create an ontology model, read an existing ontology, retrieve classes and properties, and examine class and property hierarchies. Key points include getting ontology classes and iterating over them, examining class relationships and restrictions, retrieving object and datatype properties, and getting property domains and ranges. The document provides examples of working with ontologies using the Jena API in Java.
Analysis of High-Order Residual-Based Dissipation for Unsteady Compressible F...kgrimich
A comprehensive study of the numerical properties of high-order residual-based dissipation terms for unsteady compressible flows leads to the design of well-behaved, low dissipative schemes of third-, fifth- and seventh-order accuracy. The dissipation and dispersion properties of the schemes are then evaluated theoreticaly, through Fourier space analysis, and numerically, through selected test cases including the inviscid Taylor-Green Vortex flow.
This document describes a proposed social networking website that would understand users' tastes and preferences using an ontology and machine learning. The website would allow users to create profiles, post articles and comments. A Java program would query an ontology defined in Protege using classes like tastes and wines. It would retrieve user preferences using SPARQL and update a database with clusters of similar users. The system aims to continuously learn from user interactions to improve its understanding of customers.
Comparison of Reasoners for large Ontologies in the OWL 2 EL ProfileKathrin Dentler
This document compares several reasoners for classifying large ontologies in the OWL 2 EL profile. It introduces the author's PhD project on semantic interoperability for clinical data using SNOMED CT. It outlines dimensions for comparing reasoners, including reasoning characteristics, usability, and performance. Results show how reasoners differ in methodology, features, and performance when classifying SNOMED CT, with some reasoners proving more sound and complete.
This document provides instructions for installing and running Jena, a Java framework for building semantic web and linked data applications. It discusses RDF, the resource description framework, and describes how to download the necessary tools, create a Java project in Eclipse, add the Jena libraries to the project's build path, and import example source code to get started with the Jena API.
This document provides an introduction to working with triples and datasets using the Jena API in Java. It discusses how to [1] create a dataset and named model, [2] create resources, properties, and literals that compose a triple, and [3] connect the triple components by adding them to a model. It also briefly covers serializing the model contents to file in different RDF formats like RDF/XML, TTL, and N-Triple. The goal is to demonstrate the basic steps for building, querying, and persisting RDF triples with Jena.
The document introduces Jena, a Java framework for building Semantic Web applications. It discusses key Semantic Web technologies like RDF, RDFS, OWL and SPARQL. It also provides an overview of Jena's features for manipulating RDF graphs and querying them using SPARQL. Examples are given of how to use Jena's RDF and SPARQL APIs.
Yang Yu is proposing research on improving machine learning based ontology mapping by automatically obtaining training samples from the web. The proposed system would parse two input ontologies to generate queries to search engines and collect documents to use as samples for each ontology class. These samples would then be used to train text classifiers, which would produce probabilistic mappings between classes in the two ontologies. The results would be evaluated by comparing to mappings from human experts. Current work involves exploring alternative text classification tools and ways to utilize the probabilistic mapping values generated by the classifiers.
The document discusses processing OWL ontologies using the Jena ontology API in Java. It describes how to create an ontology model, read an existing ontology, retrieve classes and properties, and examine class and property hierarchies. Key points include getting ontology classes and iterating over them, examining class relationships and restrictions, retrieving object and datatype properties, and getting property domains and ranges. The document provides examples of working with ontologies using the Jena API in Java.
ElogPoct: A Tool for Lipophilicity Determination in Drug DiscoveryBrian Bissett
This document presents a new RP-HPLC method for determining logPoct values, a measure of lipophilicity important for drug discovery. The key advantages of the method are that it is rapid (determinations in 20 minutes on average), uses small amounts of compound (1 mL of a 30-50 μg/mL solution), has a wide dynamic range of 6 log units, and shows good accuracy and reproducibility when tested on 36 drug molecules. A comparison to experimentally determined logPoct values indicates the new RP-HPLC method performs comparably to traditional shake-flask methods.
The Challenges of Analytical Method Validation for Hallucinogens and Designer...NMS Labs
The Challenges of Analytical Method Validation for Hallucinogens and Designer Stimulants in Biological Samples Using LC-TOF
Hosted by Agilent Technologies on October 8, 2012
Presented by Barry K Logan, Ph.D., NMS Labs National Director, Forensic Services
This document discusses quantitative structure-activity relationship (QSAR) modeling and 3D-QSAR techniques. It explains that QSAR aims to find consistent relationships between biological activity and molecular properties in order to predict activity of new compounds. It also describes several common 3D-QSAR software programs and techniques, including CoMFA, VolSurf, Catalyst, and DOCK, and provides examples of their applications to modeling various cytochrome P450 enzymes.
This document discusses polymeric nanoparticles for encapsulation and controlled release of bioactive compounds. Section 1 discusses polysaccharide-based nanocomplexes of chitosan and alginic acid for co-encapsulation and sustained release of 5-fluorouracil and temozolomide. The nanoparticles had sizes around 100-200 nm, encapsulation efficiencies between 20-80%, and provided sustained release over one week. Section 2 explores chitosan grafted with low molecular weight polylactic acid for protein encapsulation and reducing initial burst release. The grafted polylactic acid prolonged release in acidic media and reduced initial burst. Section 3 examines amphiphilic nanoparticles using chitosan grafted with polyl
The document provides information on charged aerosol detection (CAD) technology. It discusses the evolution of CAD products, how CAD works, comparisons to other detection methods like ELSD, and example applications. Key points covered include how CAD provides a uniform response for analytes independent of chemical structure, its wide dynamic range of up to four orders of magnitude, and how it can detect both non-volatile and semi-volatile compounds on HPLC and UHPLC systems without the need for reference standards.
Quantitative structure-activity relationships (QSAR) use mathematical models to predict biological activity based on molecular properties. QSAR models are developed using statistical methods like partial least squares on datasets of compounds with known activities. Three-dimensional (3D) QSAR extends this approach by incorporating 3D structural descriptors and molecular fields derived from programs like CoMFA, VolSurf, and Catalyst to model activity based on interactions at binding sites. These 3D-QSAR models can be used to predict activity and design new compounds with improved properties.
ElogDoct: A Tool for Lipophilicity Determination in Drug Discovery. 2. Basic ...Brian Bissett
I received a nice acknowledgement in this paper.
ElogDoct: A Tool for Lipophilicity Determination in Drug Discovery. 2. Basic and Neutral Compounds
Franco Lombardo, Marina Y. Shalaeva, Karl A. Tupper, and Feng Gao
Molecular Properties Group and Mathematical and Statistical Sciences Group, Pfizer Global Research and Development
Hyphenated Techniques - coupling of a separation technique and an on-line spectroscopic detection technology.
Advantages of hyphenated techniques;
1. Fast and accurate analysis.
2. Higher degree of automation.
3. Higher sample throughput.
4. Better reproducibility.
5. Reduction of contamination due to its closed system.
6. Separation and quantification achieved at same time.
Quantitative Analysis of Oligonucleotides in Human Muscle Tissue Using Liquid...Covance
APA 2019 -- Duchenne muscular dystrophy (DMD) is a rare X-linked recessive neuromuscular disease characterized by progressive severe muscle wasting and weakness. DMD is ultimately fatal, with patients typically dying from respiratory or cardiac complications in their mid- to late-20s. Exon skipping by phosphorodiamidate morpholino oligomer (PMO) is considered a promising, disease-modifying approach to treat the underlying cause of DMD. PMO was conjugated to a proprietary peptide to enhance tissue uptake, providing a PPMO. This poster describes the development and validation of a sensitive, selective and high-throughput liquid chromatography-tandem high resolution-accurate mass (LC/HR-AM) method for the quantitation of the PPMO in human muscle tissue using an analogue as the internal standard (ISTD). A key modification to the PMO is the addition of a proprietary peptide that provides specificity to binding and due to the metabolism of the peptide several entities of the PMO will be present in the muscle tissue, in order to quantitate the total amount of the PPMO in the muscle. The extraction undergoes a peptide digestion step to form an end product of PMO-A prior to the analysis.
This presentation discusses the transformation of pharmacokinetic (PK) data from its original source to the standard SDTM submission format. PK data comes from various clinical trial sources and needs to populate the SDTM PC and PP domains with linked records in RELREC. Challenges include mapping variables, relating records across domains, and deriving parameters in PP from concentrations in PC. Intermediate ADaM datasets like ADPC are often needed to perform analyses and populate PP. Care is required to represent timing criteria, flags, and other analysis-related attributes correctly between the domains.
This presentation describes the operation and application of the Waters APGC (Atmospheric Pressure Gas Chromatography) ion source which provides a highly sensitive GC-MS, MS/MS capability for tandem quadrupole and time of flight MS systems. It is very easy to swap between APGC, Electrospray (for UPLC) and other ion sources without instrument venting in minutes.
APGC provides significant performance advantages over traditional GC/MS ionisation methods, giving high sensitivity and less fragmented spectra.
Synthetic Biology——Medicilon Peptide Drug Discovery Service Platformmedicilonz
Peptides as a therapeutic method attract much attention due to the synthetic accessibility, high degree of specific binding, and the ability to target protein surfaces traditionally considered "undruggable". Macrocyclic peptides possess a lot of pharmacological characteristics distinct from other well-established therapeutic
molecular classes, resulting in a versatile drug modality with a unique profile of advantages. https://www.medicilon.com/services/biology-services/
This study investigated the phosphorylation of α-synuclein (α-Syn), a protein implicated in Parkinson's disease, using NMR spectroscopy. α-Syn has three domains and adopts different structural assemblies during its aggregation process. Phosphorylation may contribute to α-Syn aggregation, though the mechanisms are unclear. The study used NMR to monitor the activity of CK2α, a kinase known to phosphorylate α-Syn at Ser129. Preliminary results found CK2α phosphorylated α-Syn as observed by biochemical analysis and minor chemical shift changes in NMR spectra. Future work will further characterize the effects of phosphorylation on α-Syn aggregation in both buffer and cell lysates using techniques like NMR, fluorescence,
This document discusses various chromatography techniques including high-performance liquid chromatography (HPLC), fast protein liquid chromatography (FPLC), ultra-performance liquid chromatography (UPLC), and rapid resolution liquid chromatography (RRLC). HPLC uses pumps to pass a pressurized liquid through a column to separate sample components. FPLC is a modified HPLC used for protein separations using aqueous buffers and resins. UPLC uses smaller particle columns (<2μm) than HPLC to improve resolution, speed, and sensitivity. RRLC also uses sub-2μm particles and high flow rates to achieve faster analysis times than HPLC while maintaining resolution.
This document summarizes a study using perturbed angular correlation (PAC) spectroscopy to analyze the stability of polymersomes containing the radionuclide 111In. PAC measurements were taken for 111In in different forms: as a crystal, complexed with DTPA and tropolone, and loaded into polymersomes of varying sizes. The results showed the perturbation was higher for polymersomes in HEPES buffer than PBS buffer, but size did not influence stability. No clear conclusions could be drawn due to technical issues with the detectors and data analysis software. Future work proposed investigating other factors affecting stability and performing in vivo and in vitro studies to analyze polymersome lifetime upon administration.
The document describes the Shimadzu LCMS-2020 liquid chromatograph mass spectrometer. It has ultra-fast capabilities like UFswitching that allows rapid switching between positive and negative ionization modes in just 15 ms. It also features UFscanning that enables ultra-fast scan measurements up to 15,000 u/sec to detect sharp peaks from ultra-fast liquid chromatography. The instrument's hardware and software are designed to support these ultra-fast functions and provide sensitive, high-resolution analysis of samples using various ionization methods like ESI, APCI, and DUIS.
This presentation describes development of a routine tandem quadrupole LC/MS/MS method for milk and egg allergens based on proteomic studies to identify the allergenic peptide markers. Initial studies are done using a proteomic workflow and quadrupole time of flight mass spectrometry.
Accelerate AI | Knowledge Graphs in Financial Technology - Future or HypeTomasz Adamusiak
The document discusses knowledge graphs in financial technology and their potential uses and challenges. It provides an overview of Thomson Reuters' knowledge graph, which connects content, entities, and relationships. Knowledge graphs could help answer questions about regulatory exposure and risk by tracing connections between entities up to several degrees of separation. However, knowledge graphs also face challenges in accurately modeling complex, evolving relationships within financial data.
Presented at Cambridge Semantic Web Monthly Meetup on September 8, 2015
http://www.meetup.com/The-Cambridge-Semantic-Web-Meetup-Group/events/223161012/
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ElogPoct: A Tool for Lipophilicity Determination in Drug DiscoveryBrian Bissett
This document presents a new RP-HPLC method for determining logPoct values, a measure of lipophilicity important for drug discovery. The key advantages of the method are that it is rapid (determinations in 20 minutes on average), uses small amounts of compound (1 mL of a 30-50 μg/mL solution), has a wide dynamic range of 6 log units, and shows good accuracy and reproducibility when tested on 36 drug molecules. A comparison to experimentally determined logPoct values indicates the new RP-HPLC method performs comparably to traditional shake-flask methods.
The Challenges of Analytical Method Validation for Hallucinogens and Designer...NMS Labs
The Challenges of Analytical Method Validation for Hallucinogens and Designer Stimulants in Biological Samples Using LC-TOF
Hosted by Agilent Technologies on October 8, 2012
Presented by Barry K Logan, Ph.D., NMS Labs National Director, Forensic Services
This document discusses quantitative structure-activity relationship (QSAR) modeling and 3D-QSAR techniques. It explains that QSAR aims to find consistent relationships between biological activity and molecular properties in order to predict activity of new compounds. It also describes several common 3D-QSAR software programs and techniques, including CoMFA, VolSurf, Catalyst, and DOCK, and provides examples of their applications to modeling various cytochrome P450 enzymes.
This document discusses polymeric nanoparticles for encapsulation and controlled release of bioactive compounds. Section 1 discusses polysaccharide-based nanocomplexes of chitosan and alginic acid for co-encapsulation and sustained release of 5-fluorouracil and temozolomide. The nanoparticles had sizes around 100-200 nm, encapsulation efficiencies between 20-80%, and provided sustained release over one week. Section 2 explores chitosan grafted with low molecular weight polylactic acid for protein encapsulation and reducing initial burst release. The grafted polylactic acid prolonged release in acidic media and reduced initial burst. Section 3 examines amphiphilic nanoparticles using chitosan grafted with polyl
The document provides information on charged aerosol detection (CAD) technology. It discusses the evolution of CAD products, how CAD works, comparisons to other detection methods like ELSD, and example applications. Key points covered include how CAD provides a uniform response for analytes independent of chemical structure, its wide dynamic range of up to four orders of magnitude, and how it can detect both non-volatile and semi-volatile compounds on HPLC and UHPLC systems without the need for reference standards.
Quantitative structure-activity relationships (QSAR) use mathematical models to predict biological activity based on molecular properties. QSAR models are developed using statistical methods like partial least squares on datasets of compounds with known activities. Three-dimensional (3D) QSAR extends this approach by incorporating 3D structural descriptors and molecular fields derived from programs like CoMFA, VolSurf, and Catalyst to model activity based on interactions at binding sites. These 3D-QSAR models can be used to predict activity and design new compounds with improved properties.
ElogDoct: A Tool for Lipophilicity Determination in Drug Discovery. 2. Basic ...Brian Bissett
I received a nice acknowledgement in this paper.
ElogDoct: A Tool for Lipophilicity Determination in Drug Discovery. 2. Basic and Neutral Compounds
Franco Lombardo, Marina Y. Shalaeva, Karl A. Tupper, and Feng Gao
Molecular Properties Group and Mathematical and Statistical Sciences Group, Pfizer Global Research and Development
Hyphenated Techniques - coupling of a separation technique and an on-line spectroscopic detection technology.
Advantages of hyphenated techniques;
1. Fast and accurate analysis.
2. Higher degree of automation.
3. Higher sample throughput.
4. Better reproducibility.
5. Reduction of contamination due to its closed system.
6. Separation and quantification achieved at same time.
Quantitative Analysis of Oligonucleotides in Human Muscle Tissue Using Liquid...Covance
APA 2019 -- Duchenne muscular dystrophy (DMD) is a rare X-linked recessive neuromuscular disease characterized by progressive severe muscle wasting and weakness. DMD is ultimately fatal, with patients typically dying from respiratory or cardiac complications in their mid- to late-20s. Exon skipping by phosphorodiamidate morpholino oligomer (PMO) is considered a promising, disease-modifying approach to treat the underlying cause of DMD. PMO was conjugated to a proprietary peptide to enhance tissue uptake, providing a PPMO. This poster describes the development and validation of a sensitive, selective and high-throughput liquid chromatography-tandem high resolution-accurate mass (LC/HR-AM) method for the quantitation of the PPMO in human muscle tissue using an analogue as the internal standard (ISTD). A key modification to the PMO is the addition of a proprietary peptide that provides specificity to binding and due to the metabolism of the peptide several entities of the PMO will be present in the muscle tissue, in order to quantitate the total amount of the PPMO in the muscle. The extraction undergoes a peptide digestion step to form an end product of PMO-A prior to the analysis.
This presentation discusses the transformation of pharmacokinetic (PK) data from its original source to the standard SDTM submission format. PK data comes from various clinical trial sources and needs to populate the SDTM PC and PP domains with linked records in RELREC. Challenges include mapping variables, relating records across domains, and deriving parameters in PP from concentrations in PC. Intermediate ADaM datasets like ADPC are often needed to perform analyses and populate PP. Care is required to represent timing criteria, flags, and other analysis-related attributes correctly between the domains.
This presentation describes the operation and application of the Waters APGC (Atmospheric Pressure Gas Chromatography) ion source which provides a highly sensitive GC-MS, MS/MS capability for tandem quadrupole and time of flight MS systems. It is very easy to swap between APGC, Electrospray (for UPLC) and other ion sources without instrument venting in minutes.
APGC provides significant performance advantages over traditional GC/MS ionisation methods, giving high sensitivity and less fragmented spectra.
Synthetic Biology——Medicilon Peptide Drug Discovery Service Platformmedicilonz
Peptides as a therapeutic method attract much attention due to the synthetic accessibility, high degree of specific binding, and the ability to target protein surfaces traditionally considered "undruggable". Macrocyclic peptides possess a lot of pharmacological characteristics distinct from other well-established therapeutic
molecular classes, resulting in a versatile drug modality with a unique profile of advantages. https://www.medicilon.com/services/biology-services/
This study investigated the phosphorylation of α-synuclein (α-Syn), a protein implicated in Parkinson's disease, using NMR spectroscopy. α-Syn has three domains and adopts different structural assemblies during its aggregation process. Phosphorylation may contribute to α-Syn aggregation, though the mechanisms are unclear. The study used NMR to monitor the activity of CK2α, a kinase known to phosphorylate α-Syn at Ser129. Preliminary results found CK2α phosphorylated α-Syn as observed by biochemical analysis and minor chemical shift changes in NMR spectra. Future work will further characterize the effects of phosphorylation on α-Syn aggregation in both buffer and cell lysates using techniques like NMR, fluorescence,
This document discusses various chromatography techniques including high-performance liquid chromatography (HPLC), fast protein liquid chromatography (FPLC), ultra-performance liquid chromatography (UPLC), and rapid resolution liquid chromatography (RRLC). HPLC uses pumps to pass a pressurized liquid through a column to separate sample components. FPLC is a modified HPLC used for protein separations using aqueous buffers and resins. UPLC uses smaller particle columns (<2μm) than HPLC to improve resolution, speed, and sensitivity. RRLC also uses sub-2μm particles and high flow rates to achieve faster analysis times than HPLC while maintaining resolution.
This document summarizes a study using perturbed angular correlation (PAC) spectroscopy to analyze the stability of polymersomes containing the radionuclide 111In. PAC measurements were taken for 111In in different forms: as a crystal, complexed with DTPA and tropolone, and loaded into polymersomes of varying sizes. The results showed the perturbation was higher for polymersomes in HEPES buffer than PBS buffer, but size did not influence stability. No clear conclusions could be drawn due to technical issues with the detectors and data analysis software. Future work proposed investigating other factors affecting stability and performing in vivo and in vitro studies to analyze polymersome lifetime upon administration.
The document describes the Shimadzu LCMS-2020 liquid chromatograph mass spectrometer. It has ultra-fast capabilities like UFswitching that allows rapid switching between positive and negative ionization modes in just 15 ms. It also features UFscanning that enables ultra-fast scan measurements up to 15,000 u/sec to detect sharp peaks from ultra-fast liquid chromatography. The instrument's hardware and software are designed to support these ultra-fast functions and provide sensitive, high-resolution analysis of samples using various ionization methods like ESI, APCI, and DUIS.
This presentation describes development of a routine tandem quadrupole LC/MS/MS method for milk and egg allergens based on proteomic studies to identify the allergenic peptide markers. Initial studies are done using a proteomic workflow and quadrupole time of flight mass spectrometry.
Similar to Quality Assurance in LOINC® using Description Logic (20)
Accelerate AI | Knowledge Graphs in Financial Technology - Future or HypeTomasz Adamusiak
The document discusses knowledge graphs in financial technology and their potential uses and challenges. It provides an overview of Thomson Reuters' knowledge graph, which connects content, entities, and relationships. Knowledge graphs could help answer questions about regulatory exposure and risk by tracing connections between entities up to several degrees of separation. However, knowledge graphs also face challenges in accurately modeling complex, evolving relationships within financial data.
Presented at Cambridge Semantic Web Monthly Meetup on September 8, 2015
http://www.meetup.com/The-Cambridge-Semantic-Web-Meetup-Group/events/223161012/
Connecting the dots: drug information and Linked DataTomasz Adamusiak
This document discusses connecting drug information to linked open data. It provides an overview of linked data and semantic technologies for integrating data. Several existing linked data resources for drugs, clinical trials, pathways and more are described. Challenges with URI reconciliation and data locality are noted. The potential benefits of representing clinical trial and FDA data in RDF format to improve interoperability are also covered.
EHR-based Phenome Wide Association Study in Pancreatic CancerTomasz Adamusiak
Presented at 2014 AMIA Joint Summits, April 9, 2014, San Francisco, CA
BACKGROUND. Pancreatic cancer is one of the most common causes of cancer-related deaths in the United States, it is difficult to detect early and typically has a very poor prognosis. We present a novel method of large-scale clinical hypothesis generation based on phenome wide association study performed using Electronic Health Records (EHR) in a pancreatic cancer cohort. METHODS. The study population consisted of 1,154 patients diagnosed with malignant neoplasm of pancreas seen at The Froedtert & The Medical College of Wisconsin academic medical center between the years 2004 and 2013. We evaluated death of a patient as the primary clinical outcome and tested its association with the phenome, which consisted of over 2.5 million structured clinical observations extracted out of the EHR including labs, medications, phenotypes, diseases and procedures. The individual observations were encoded in the EHR using 6,617 unique ICD-9, CPT-4, LOINC, and RxNorm codes. We remapped this initial code set into UMLS concepts and then hierarchically expanded to support generalization into the final set of 10,164 clinical concepts, which formed the final phenome. We then tested all possible pairwise associations between any of the original 10,164 concepts and death as the primary outcome. RESULTS. After correcting for multiple testing and folding back (generalizing) child concepts were appropriate, we found 231 concepts to be significantly associated with death in the study population.
CONCLUSIONS. With the abundance of structured EHR data, phenome wide association studies combined with
knowledge engineering can be a viable method of rapid hypothesis generation.
Creating Dynamic Groupers Using Overrepresentation of Clinical TermsTomasz Adamusiak
Presented at Epic's Research Advisory Council, April 3, 2014, Verona, WI
See a novel approach to query expansion based on pre-existing structured information within the EHR. Presenters adopted over-representation analysis to find statistically significant associations among the clinical terms extracted from Clarity reports. The study population consisted of over 7,000 patients and their 12 million observations - including labs, medications, phenotypes, diseases, and procedures. See the detailed findings and discuss computational and terminology challenges.
Semantic Interoperability in Health Information ExchangeTomasz Adamusiak
Presented at HIMSS14 Annual Conference & Exhibition, February 26, 2014, Orlando, FL.
http://www.himssconference.org/Education/EventDetail.aspx?ItemNumber=25331
Meaningful Use certification requires several large vocabulary standards for representing clinical facts in health information exchange. This presents unique challenges for semantic interoperability such as information loss in translating from and to internal data dictionaries, semantic drift, dealing with legacy content (e.g., ICD-9) and clinical information reconciliation.
Re-identification of de-identified PHI date elementsTomasz Adamusiak
This document discusses the risks of inadvertently re-identifying patients when de-identifying health data sets through random date shifting. It notes that with multiple releases of data using random shifting, there is a high probability that some patients' dates could be re-identified. It provides an example of how two extremes of a randomly shifted birth date across two data sets could be used to guess the original birth date. The document recommends stopping the use of random shifts and instead using a non-random value for shifting to avoid this re-identification risk, especially as more data sets are released.
Integrating SNOMED CT with other Meaningful Use vocabulary standards (LOINC, ...Tomasz Adamusiak
This document discusses integrating SNOMED CT and other clinical terminology standards like LOINC, RxNorm, HCPCS, and CPT-4 with billing codes like ICD-9, ICD-10, and NDC using the Unified Medical Language System (UMLS). It describes challenges with mapping terms between different clinical terminologies and standards, and demonstrates a UMLS-based terminology server that can reconcile medications using RxNorm and NDC codes. The server allows integrated querying of real EHR data from Froedtert hospital through Epic Clarity reports.
Next-generation phenotyping using UMLS and Meaningful Use ontologies: SNOMED ...Tomasz Adamusiak
SNOMED CT, LOINC, and RxNorm, fuelled by the Meaningful Use legislation, are poised to become the cornerstone of U.S. health information interchange. SNOMED CT is one of the most comprehensive, multilingual medical terminologies in the world. LOINC is a universal standard for identifying laboratory observations. RxNorm is a standardized nomenclature for generic and branded drugs. All three are integrated within the Unified Medical Language System (UMLS) maintained by the U.S. National Library of Medicine.
While physicians rarely have to deal with clinical terminologies directly, these are indispensable for data querying, validation and reconciliation. The Clinical Informatics team at the Medical College of Wisconsin has developed ClinMiner (https://clinminer.hmgc.mcw.edu), a clinical research portal for clinical and diagnostic information on patients in genetics clinics and clinical sequencing programs, as well as other clinical research projects. ClinMiner is a larger system that incorporates data entry forms, patient reports, advanced querying, export and data visualization. Data for the system consists of many clinical and referral documents the patients have accumulated throughout their clinic and diagnostic histories, and are standardized through the three Meaningful Use ontologies: SNOMED CT, RxNorm and LOINC; integrated into a single UMLS perspective that allows for seamless and dynamic translation between the annotating sources, as well as provides a consolidated view of the underlying patient data.
This approach is unique in integrating all three terminologies into a single workflow of a clinical application, and in fact is not limited to Meaningful Use, as any terminology integrated within the UMLS can be used to annotate, visualize, and query data. This is of particular significance for reintegrating legacy clinical information, for example, billing data annotated with ICD-9 codes in the process of transitioning to ICD-10. Most importantly, as large resources such as SNOMED CT and the UMLS often remain underused due to their sheer size and complexity, ClinMiner demonstrates that the additional effort is well worth it.
Unifying ontology services for functional genomic annotationsTomasz Adamusiak
The document provides information about the Experimental Factor Ontology (EFO). EFO models experimental factors from genomic studies stored in the ArrayExpress archive, including species, diseases, and cell lines. It captures about 30% of terms not already in the UMLS. EFO uses reference ontologies and automatic mapping to import synonyms and definitions. Regression testing verifies ontology changes. EFO has a web interface and content negotiation support, and defines experimental factor hierarchies used in the Gene Expression Atlas to aggregate experiments.
The document discusses different tools used for the Experimental Factor Ontology (EFO), including those used to assign definitions and cross-references from external ontologies, as well as tools used for quality control and string matching. It notes that n-gram matching is an effective but relatively unknown method for string approximation and ontology development. The document acknowledges contributions from various groups and individuals in supporting the development of EFO.
OntoCAT - integrated programming toolkit for common ontology application task...Tomasz Adamusiak
This document discusses several ontology tools and services including the Ontology Lookup Service (OLS), NCBO BioPortal, and OWL API. It focuses on OntoCAT, an integrated programming toolkit that can be used to build ontology-based applications and services by utilizing these existing tools and libraries. OntoCAT provides database storage and browsing capabilities for ontologies as well as RESTful web services and integrations with other tools and libraries like Bioconductor.
- Video recording of this lecture in English language: https://youtu.be/Pt1nA32sdHQ
- Video recording of this lecture in Arabic language: https://youtu.be/uFdc9F0rlP0
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
These lecture slides, by Dr Sidra Arshad, offer a simplified look into the mechanisms involved in the regulation of respiration:
Learning objectives:
1. Describe the organisation of respiratory center
2. Describe the nervous control of inspiration and respiratory rhythm
3. Describe the functions of the dorsal and respiratory groups of neurons
4. Describe the influences of the Pneumotaxic and Apneustic centers
5. Explain the role of Hering-Breur inflation reflex in regulation of inspiration
6. Explain the role of central chemoreceptors in regulation of respiration
7. Explain the role of peripheral chemoreceptors in regulation of respiration
8. Explain the regulation of respiration during exercise
9. Integrate the respiratory regulatory mechanisms
10. Describe the Cheyne-Stokes breathing
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1. Chapter 42, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 36, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 13, Human Physiology by Lauralee Sherwood, 9th edition
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Quality Assurance in LOINC® using Description Logic
1. Quality Assurance in LOINC®
using Description Logic
Tomasz Adamusiak MD PhD
Postdoc at NIH NLM LHC CgSB
10/11 – 03/12
2. Objective
Identify areas for improvement in LOINC by
changing its representation to OWL DL and
comparing its classification to that of
SNOMED CT
2
3. Why do it the hard way?
Rector, A. L., & Brandt, S. Why do it the hard
way? (2008) The case for an expressive
description logic for SNOMED.
More flexibility in a more expressive language
A uniform, clear, and understandable schema
Modularisation
Access to standard tooling developed by the
wider Semantic Web and OWL communities
Protégé, OWL API
3
6. Web Ontology Language (OWL)
Manchester Syntax
Class: VegetarianPizza
EquivalentTo:
Pizza and
not (hasTopping some FishTopping) and
not (hasTopping some MeatTopping)
DisjointWith:
NonVegetarianPizza
6
7. A number of papers explored LOINC
SNOMED CT integration and DL
Dolin, R. H., Huff, S. M., Rocha, R. A., Spackman, K. A.,
& Campbell, K. E. (1998). Evaluation of a “lexically
assign, logically refine” strategy for semi-automated
integration of overlapping terminologies.
Spackman, K. A. (1998). Integrating sources for a
clinical reference terminology: experience linking
SNOMED to LOINC and drug vocabularies.
Srinivasan A. et al. (2006). Semantic web
representation of LOINC: an ontological perspective.
Bodenreider, O. (2008). Issues in mapping LOINC
laboratory tests to SNOMED CT.
7
8. Quality Assurance in literature
Geller et al. (2009). Special issue on auditing of terminologies.
Journal of biomedical informatics
Bodenreider, O., & Peters, L. B. (2009). A graph-based approach to
auditing RxNorm.
Wei, D., & Bodenreider, O. (2010). Using the abstraction network in
complement to description logics for quality assurance in
biomedical terminologies - a case study in SNOMED CT.
Rector, A., & Iannone, L. (2011). Lexically suggest, logically define:
Quality assurance of the use of qualifiers and expected results of
post-coordination in SNOMED CT.
Lin, M. C., Vreeman, D. J., McDonald, C. J., & Huff, S. M. (2012).
Auditing consistency and usefulness of LOINC use among three
large institutions - Using version spaces for grouping LOINC codes.
8
9. A universal code system for identifying
laboratory and clinical observations
9
10. LOINC codes consist of parts
Code:
2160-0 Creatinine [Mass/volume] in Serum or Plasma
Parts:
Part Type Part No. Part Name
Component LP14355-9 Creatinine
Property LP6827-2 MCnc [Mass Concentration]
Time LP6960-1 Pt [Point in time (spot)]
System LP7576-4 Ser/Plas [Serum or Plasma]
Scale LP7753-9 Qn
10
12. We used part links to create logical
definitions for codes
Code:
2160-0 Creatinine [Mass/volume] in Serum or Plasma
Parts:
Part Type Part Name DL definition:
Component Creatinine (has_component some Creatinine) and
Property MCnc (has_property some MCnc) and
Time Pt (has_time_aspect some Pt ) and
System Ser/Plas (has_system some Ser/Plas) and
Scale Qn (has_scale some Qn)
12
13. Component 2nd subpart: challenge
Code:
1558-6 Fasting glucose [Mass/volume] in Serum or Plasma
Parts:
Part Type Part No. Part Name
Component LP14635-4 Glucose
Challenge LP20355-1 post CFst
Property LP6827-2 MCnc [Mass Concentration]
Time LP6960-1 Pt [Point in time (spot)]
System LP7576-4 Ser/Plas [Serum or Plasma]
Scale LP7753-9 Qn
13
14. Component 3rd subpart: adjustment
Code:
23811-3 Alpha-1-Fetoprotein [Multiple of the median]
adjusted in Serum or Plasma
Parts:
Part Type Part No. Part Name
Component LP14331-0 Alpha-1-Fetoprotein
Adjustment LP20174-6 adjusted
Property LP71590-1 MoM [Multiple of the median]
Time LP6960-1 Pt [Point in time (spot)]
System LP7576-4 Ser/Plas [Serum or Plasma]
Scale LP7753-9 Qn
14
15. LOINC parts are not available in the
public release (2.36)
Part
Codes Parts
Links
Multiaxial
hierarchy
15
17. Multiaxial hierarchy in LOINC could be
vastly improved with DL
Type
Screenshot from the Regenstrief LOINC Mapping Assistant (RELMA)
17
18. Type
Multiaxial hierarchy in LOINC could be
vastly improved with DL
18
19. Separated codes and parts and defined
corresponding observations
OBS
Glucose
Glucose
Glucose |
OBS Glucose|
Urine
Urine
Urine
Glucose in 10
hour Urine
Glucose in Protein & Glucose
Urine by Test panel in Urine by
Test strip
strip
Multiaxial
19
20. Separated codes and parts and defined
corresponding observations
Glucose
OBS ≡
Glucose
Glucose |
Urine
OBS Glucose| ≡
Urine Urine
Glucose in 10 ≡
hour Urine
Glucose in ≡
Urine by Test
Protein & Glucose
panel in Urine by
≡
Test strip
strip
Multiaxial Inferred
20
21. SNOMED CT compensates for missing
parts relations in LOINC
Body fluid owl:EquivalentTo Body fluid
LP30504-2 32457005
Body Fluids C0005889
ISA
Urine owl:EquivalentTo Urine
LP7681-2 78014005
Urine C0042036
21
22. SNOMED CT compensates for missing
parts relations in LOINC
Body fluid
LP30504-2
32457005
Body Fluids C0005889
ISA
Urine
LP7681-2
78014005
Urine C0042036
22
23. We can identify semantically
equivalent LOINC parts via UMLS
Erythrocyte Erythrocytes
LP16699-8 LP14304-7
RBC
LP7536-8
Erythrocytes C0014792
23
24. We can identify semantically
equivalent LOINC parts via UMLS
Erythrocytes
RBC
Erythrocyte
LP14304-7
LP7536-8
LP16699-8
Erythrocytes C0014792
24
25. Reasoner infers logical consequences
from a set of asserted facts or axioms
≡
OBS Glucose has_component some Glucose and
| Urine has_system some Urine
DL definition
Inferred
≡
Glucose in 10
has_component some Glucose and
has_property some Arbitrary Concentration and
has_time_aspect some Point in time (spot) and
hour Urine has_system some Urine and
has_scale some Ord and
has_method some Test strip
DL definition
25
29. a) LOINC codes
CD3-CD56+
cells/100 cells in
Cerebral spinal b) Linked parts
fluid (56897-2) LP19037-8:Cells.CD3+CD56+
CD3+CD56+ LP35646-6:Cells.CD3-CD56+
cells/100 cells in
Cerebral spinal
fluid (51279-8) LOINC
c) DL definition
…
and (has_component some Cells.CD3+CD56+)
and (has_component some Cells.CD3-CD56+)
29
30. Also visible in LOINC browser/RELMA
http://s.details.loinc.org/LOINC/56897-2.html?sections=Comprehensive
30
31. Inconsistencies in part hierarchy result
in incorrect inference
Monocytes+Macrophages
LP14312-0
Monocytes+Macrophages Macrophages
/100 leukocytes in Peritoneal /100 leukocytes in Peritoneal
fluid by Manual count
ISA fluid by Manual count
(32029-1) (40517-5)
Macrophages
LP14314-6
31
32. Pop quiz: removing which has_component
relation changes equivalence to subsumption?
Monocytes+Macrophages
LP14312-0
Monocytes+Macrophages Macrophages
/100 leukocytes in Peritoneal /100 leukocytes in Peritoneal
fluid by Manual count
ISA fluid by Manual count
(32029-1) (40517-5)
Macrophages
LP14314-6
32
33. Issues with referential integrity
*
LP28805-7
Type of Enema device Type of Enema device
(8950-8) (8932-6)
Enema device
LP7209-2
33
35. a) LOINC codes b) Linked parts
Helmet cells [Presence] LP14570-3:Helmet cells
in Blood by Light LP14738-6:Cells
microscopy (10374-7)
Schistocytes [Presence]
in Blood by Light LP29945-0:Schistocytes
microscopy (800-3)
LOINC
c) DL definitions
(has_component some 'Helmet cells') (has_component some Schistocytes)
and (has_component some Cells)
d) Mappings
SCT_70310009: Helmet cell
is_a SCT_362837007:Entire cell SNOMED CT
35
37. Inferred nodes are better connected
locally
1000
LOINC
Inferred
Logarithm of average connectivity
100
10
1
1 10 100 1000 10000
Logarithm of number of neighbours
37
39. ¡¿Find all carbohydrate observations?!
Everything
else
Gene tests
Here Be Dragons
HPA tests
HLA tests Patient
information
Skin tests
Evaluation and
management
40. It is not easy
Here Be
Everything
Dragons
else
Gene tests
Here Be Dragons
HPA tests
HLA tests Patient
information
Skin tests
Evaluation and
management
45. No direct path between Carbohydrates
| Urine and Glucose | Urine originally
45
46. 239 LOINC codes were found to be
inconsistenly asserted in the hierarchy
183 concepts of scale type Document
28626-0:History and physical
note:Find:Pt:Setting:Doc:Physician
Asserted History and physical note
Inferred Note
Mostly insufficient modelling
46
48. LOINC curators are doing a splendid
job and the terminology is consistent
Significance of DL
1. Error detection
a) Duplicates
b) Missing hierarchical relations
c) Inconsistencies in hierarchy
2. Enhanced navigation
3. Enhanced subsumption
4. Maintenance
48
49. Recommendations
1. Create logical definitions for codes
2. Have an inferred hierarchy
3. Parts vs. codes
4. Alignment with SNOMED CT
49
50. What does it mean to have several
parts in LOINC map to SNOMED CT?
SCT_3711007:Structure of great blood vessel
(organ)
SYSTEM LP7303-3:Heart.great vessels
SYSTEM LP33690-6:Great vessel
SYSTEM LP30622-2:Great vessels
SCT_66019005:Limb structure
COMPONENT LP121777-9:Extremity
SYSTEM LP7216-7:Extremities
SYSTEM LP7395-9:Limbs
SYSTEM LP29945-0:Extremity
50
51. Limitations
Relying on UMLS to provide mappings
Imposing a specific ontological commitment
Modelling with conjunctions likely suboptimal
for more complex observations
51
53. Acknowledgments
Olivier Bodenreider MD PhD (mentor)
Bastien Rance PhD
Rainer Winnenburg PhD
Clement McDonald MD
Daniel J. Vreeman PT DPT MSc
(Regenstrief Institute)
This work was supported by the Intramural Research Program of the National Institutes of Health
(NIH), National Library of Medicine (NLM) and the Oak Ridge Institute for Science and Education (ORISE)
Training Program in Clinical Informatics managed for the U.S. Department of Energy (DOE) by Oak Ridge
Associated Universities (ORAU).
53