An Automated Approach for Identifying Erroneous IS-A Relations in SNOMED CT.

SNOMED CT is the most comprehensive clinical terminology employed worldwide and enhancing its accuracy is of utmost importance. In this work, we introduce an automated approach to identifying erroneous IS-A relations in SNOMED CT. We first extract linked concept-pairs from which we generate Term Difference Pairs (TDPs) that contain differences between the concepts. Given a TDP, if the reversed TDP also exists and the number of linked-pairs generating this TDP is less than those generating the reversed TDP, then we suggest the former linked-pairs as potentially erroneous IS-A relations. We applied this approach to the Clinical finding and Procedure subhierarchies of the 2022 March US Edition of SNOMED CT, and obtained 52 potentially erroneous IS-A relations and a candidate list of 48 linked-pairs. A domain expert confirmed 41 out of 52 (78.8%) are valid and identified 26 erroneous IS-A relations out of 48 linked-pairs demonstrating the effectiveness of the approach.

Leveraging logical definitions and lexical features to detect missing IS-A relations in biomedical terminologies.

Biomedical terminologies play a vital role in managing biomedical data. Missing IS-A relations in a biomedical terminology could be detrimental to its downstream usages. In this paper, we investigate an approach combining logical definitions and lexical features to discover missing IS-A relations in two biomedical terminologies: SNOMED CT and the National Cancer Institute (NCI) thesaurus. The method is applied to unrelated concept-pairs within non-lattice subgraphs: graph fragments within a terminology likely to contain various inconsistencies. Our approach first compares whether the logical definition of a concept is more general than  that of the other concept. Then, we check whether the lexical features of the concept are contained in those of the other concept. If both constraints are satisfied, we suggest a potentially missing IS-A relation between the two concepts. The method identified 982 potential missing IS-A relations for SNOMED CT and 100 for NCI thesaurus. In order to assess the efficacy of our approach, a random sample of results belonging to the "Clinical Findings" and "Procedure" subhierarchies of SNOMED CT and results belonging to the "Drug, Food, Chemical or Biomedical Material" subhierarchy of the NCI thesaurus were evaluated by domain experts. The evaluation results revealed that 118 out of 150 suggestions are valid for SNOMED CT and 17 out of 20 are valid for NCI thesaurus.

A deep learning approach to identify missing is-a relations in SNOMED CT.

OBJECTIVE: SNOMED CT is the largest clinical terminology worldwide. Quality assurance of SNOMED CT is of utmost importance to ensure that it provides accurate domain knowledge to various SNOMED CT-based applications. In this work, we introduce a deep learning-based approach to uncover missing is-a relations in SNOMED CT. MATERIALS AND METHODS: Our focus is to identify missing is-a relations between concept-pairs exhibiting a containment pattern (ie, the set of words of one concept being a proper subset of that of the other concept). We use hierarchically related containment concept-pairs as positive instances and hierarchically unrelated containment concept-pairs as negative instances to train a model predicting whether an is-a relation exists between 2 concepts with containment pattern. The model is a binary classifier leveraging concept name features, hierarchical features, enriched lexical attribute features, and logical definition features. We introduce a cross-validation inspired approach to identify missing is-a relations among all hierarchically unrelated containment concept-pairs. RESULTS: We trained and applied our model on the Clinical finding subhierarchy of SNOMED CT (September 2019 US edition). Our model (based on the validation sets) achieved a precision of 0.8164, recall of 0.8397, and F1 score of 0.8279. Applying the model to predict actual missing is-a relations, we obtained a total of 1661 potential candidates. Domain experts performed evaluation on randomly selected 230 samples and verified that 192 (83.48%) are valid. CONCLUSIONS: The results showed that our deep learning approach is effective in uncovering missing is-a relations between containment concept-pairs in SNOMED CT.

A GCN-based approach to uncover misaligned synonymous terms in the UMLS Metathesaurus.

The Unified Medical Language System (UMLS), a large repository of biomedical vocabularies, has been used for supporting various biomedical applications. Ensuring the quality of the UMLS is critical to maintain both the accuracy of its content and the reliability of downstream applications. In this work, we present a Graph Convolutional Network (GCN)-based approach to identify misaligned synonymous terms organized under different UMLS concepts. We used synonymous terms grouped under the same concept as positive samples and top lexically similar terms as negative samples to train the GCN model. We applied the model to a test set and suggested those negative samples predicted to be synonymous as potentially misaligned synonymous terms. A total of 147,625 suggestions were made. A human expert evaluated 100 randomly selected suggestions and agreed with 60 of them. The results indicate that our GCN-based approach shows promise to help improve the synonymy grouping in the UMLS.

A substring replacement approach for identifying missing IS-A relations in SNOMED CT.

Biomedical ontologies provide formalized information and knowledge in the biomedical domain. Over the years, biomedical ontologies have played an important role in facilitating biomedical research and applications. Common quality issues of biomedical ontologies include inconsistent naming of concepts, redundant concepts, redundant relations, incomplete/incorrect concept definitions, and incomplete/incorrect class hierarchies. In this work, we focus on addressing the incompleteness of the class hierarchy in SNOMED CT. We develop a substring replacement approach, leveraging concepts' lexical features and existing IS-A relations to identify potential missing IS-A relations in SNOMED CT. To evaluate the effectiveness of our approach, we performed both automated and manual validation. For the automated evaluation, we leverage relations from external terminologies in the Unified Medical Language System (UMLS) to validate the identified missing IS-A relations. For the manual validation, a randomly selected 100 samples from the results are reviewed by a domain expert. Applying our approach to the March 2022 release of SNOMED CT US Edition, we identified 3,228 potential missing IS-A relations, among which 63 were validated through the UMLS. The evaluation by the domain expert revealed that 89 out of 100 (a precision of 89%) missing IS-A relations are valid cases, showing the effectiveness of this substring replacement approach to facilitate the quality assurance of IS-A relations in SNOMED CT.

Toll receptors remodel epithelia by directing planar-polarized Src and PI3K activity.

Toll-like receptors are essential for animal development and survival, with conserved roles in innate immunity, tissue patterning, and cell behavior. The mechanisms by which Toll receptors signal to the nucleus are well characterized, but how Toll receptors generate rapid, localized signals at the cell membrane to produce acute changes in cell polarity and behavior is not known. We show that Drosophila Toll receptors direct epithelial convergent extension by inducing planar-polarized patterns of Src and PI3-kinase (PI3K) activity. Toll receptors target Src activity to specific sites at the membrane, and Src recruits PI3K to the Toll-2 complex through tyrosine phosphorylation of the Toll-2 cytoplasmic domain. Reducing Src or PI3K activity disrupts planar-polarized myosin assembly, cell intercalation, and convergent extension, whereas constitutive Src activity promotes ectopic PI3K and myosin cortical localization. These results demonstrate that Toll receptors direct cell polarity and behavior by locally mobilizing Src and PI3K activity.

A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.

OBJECTIVE: The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical information systems. In this article, we introduce a novel transformation-based auditing method that leverages the UMLS knowledge to systematically identify missing hierarchical IS-A relations in the source terminologies. MATERIALS AND METHODS: Given a concept name in the UMLS, we first identify its base and secondary noun chunks. For each identified noun chunk, we generate replacement candidates that are more general than the noun chunk. Then, we replace the noun chunks with their replacement candidates to generate new potential concept names that may serve as supertypes of the original concept. If a newly generated name is an existing concept name in the same source terminology with the original concept, then a potentially missing IS-A relation between the original and the new concept is identified. RESULTS: Applying our transformation-based method to English-language concept names in the UMLS (2019AB release), a total of 39 359 potentially missing IS-A relations were detected in 13 source terminologies. Domain experts evaluated a random sample of 200 potentially missing IS-A relations identified in the SNOMED CT (U.S. edition) and 100 in Gene Ontology. A total of 173 of 200 and 63 of 100 potentially missing IS-A relations were confirmed by domain experts, indicating that our method achieved a precision of 86.5% and 63% for the SNOMED CT and Gene Ontology, respectively. CONCLUSIONS: Our results showed that our transformation-based method is effective in identifying missing IS-A relations in the UMLS source terminologies.

A lexical-based approach for exhaustive detection of missing hierarchical IS-A relations in SNOMED CT.

Incompleteness of ontologies affects the quality of downstream ontology-based applications. In this paper, we introduce a novel lexical-based approach to automatically detect potentially missing hierarchical IS-A relations in SNOMED CT. We model each concept with an enriched set of lexical features, by leveraging words and noun phrases in the name of the concept itself and the concept's ancestors. Then we perform subset inclusion checking to suggest potentially missing IS-A relations between concepts. We applied our approach to the September 2017 release of SNOMED CT (US edition) which suggested a total of 38,615 potentially missing IS-A relations. For evaluation, a domain expert reviewed a random sample of 100 missing IS-A relations selected from the "Clinical finding" sub-hierarchy, and confirmed 90 are valid (a precision of 90%). Additional review of invalid suggestions further revealed incorrect existing IS-A relations. Our results demonstrate that systematic analysis of the enriched lexical features of concepts is an effective approach to identify potentially missing hierarchical IS-A relations in SNOMED CT.

An LRR Receptor-Teneurin System Directs Planar Polarity at Compartment Boundaries.

Epithelial cells dynamically self-organize in response to extracellular spatial cues relayed by cell-surface receptors. During convergent extension in Drosophila, Toll-related receptors direct planar polarized cell rearrangements that elongate the head-to-tail axis. However, many cells establish polarity in the absence of Toll receptor activity, indicating the presence of additional spatial cues. Here we demonstrate that the leucine-rich-repeat receptor Tartan and the teneurin Ten-m provide critical polarity signals at epithelial compartment boundaries. The Tartan and Ten-m extracellular domains interact in vitro, and Tartan promotes Ten-m localization to compartment boundaries in vivo. We show that Tartan and Ten-m are necessary for the planar polarity and organization of compartment boundary cells. Moreover, ectopic stripes of Tartan and Ten-m are sufficient to induce myosin accumulation at stripe boundaries. These results demonstrate that the Tartan/Ten-m and Toll receptor systems together create a high-resolution network of spatial cues that guides cell behavior during convergent extension.

Toward the Development and Application of an Environmental Risk Assessment Framework for Microplastic.

Emissions of plastic waste to the environment and the subsequent degradation into microplastic particles that have the potential to interact with biological organisms represent a concern for global society. Current understanding of the potential impacts on aquatic and terrestrial population stability and ecosystem structure and function associated with emissions of microplastic particles is limited and insufficient to fully assess environmental risks. Multistakeholder discussions can provide an important element in helping to identify and prioritize key knowledge gaps in assessing potential risks. In the present review, we summarize multistakeholder discussions from a 1-d International Council of Chemical Associations-sponsored symposium, which involved 39 scientists from 8 countries with representatives from academia, industry, and government. Participants were asked to consider the following: discuss the scientific merits and limitations of applying a proposed conceptual environmental risk assessment (ERA) framework for microplastic particles and identify and prioritize major research needs in applying ERA tools for microplastic particles. Multistakeholder consensus was obtained with respect to the interpretation of the current state of the science related to effects and exposure to microplastic particles, which implies that it is unlikely that the presence of microplastic in the environment currently represents a risk. However, the quality and quantity of existing data require substantial improvement before conclusions regarding the potential risks and impacts of microplastic particles can be fully assessed. Research that directly addresses the development and application of methods that strengthen the quality of data should thus be given the highest priority. Activities aimed at supporting the development of and access to standardized reference material were identified as a key research need. Environ Toxicol Chem 2019;38:2087-2100. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Auditing SNOMED CT hierarchical relations based on lexical features of concepts in non-lattice subgraphs.

OBJECTIVE: We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. METHODS: Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT's IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor concepts within the non-lattice subgraph. In stage 3, subset inclusion relations between the lexical attribute sets of each pair of concepts in each non-lattice subgraph are compared to existing IS-A relations in SNOMED CT. For concept pairs within each non-lattice subgraph, if a subset relation is identified but an IS-A relation is not present in SNOMED CT IS-A transitive closure, then a missing IS-A relation is reported. The September 2017 release of SNOMED CT (US edition) was used in this investigation. RESULTS: A total of 14,380 non-lattice subgraphs were extracted, from which we suggested a total of 41,357 missing IS-A relations. For evaluation purposes, 200 non-lattice subgraphs were randomly selected from 996 smaller subgraphs (of size 4, 5, or 6) within the "Clinical Finding" and "Procedure" sub-hierarchies. Two domain experts confirmed 185 (among 223) suggested missing IS-A relations, a precision of 82.96%. CONCLUSIONS: Our results demonstrate that analyzing the lexical features of concepts in non-lattice subgraphs is an effective approach for auditing SNOMED CT.

A Rapid Induction Mechanism for Lin28a in Trophic Responses.

Environmental cues provoke rapid transitions in gene expression to support growth and cellular plasticity through incompletely understood mechanisms. Lin28 RNA-binding proteins have evolutionarily conserved roles in post-transcriptional coordination of pro-growth gene expression, but signaling pathways allowing trophic stimuli to induce Lin28 have remained uncharacterized. We find that Lin28a protein exhibits rapid basal turnover in neurons and that mitogen-activated protein kinase (MAPK)-dependent phosphorylation of the RNA-silencing factor HIV TAR-RNA-binding protein (TRBP) promotes binding and stabilization of Lin28a, but not Lin28b, with an accompanying reduction in Lin28-regulated miRNAs, downstream of brain-derived neurotrophic factor (BDNF). Binding of Lin28a to TRBP in vitro is also enhanced by phospho-mimic TRBP. Further, phospho-TRBP recapitulates BDNF-induced neuronal dendritic spine growth in a Lin28a-dependent manner. Finally, we demonstrate MAPK-dependent TRBP and Lin28a induction, with physiological function in growth and survival, downstream of diverse growth factors in multiple primary cell types, supporting a broad role for this pathway in trophic responses.

Transcript specificity in BDNF-regulated protein synthesis.

Brain-derived neurotrophic factor (BDNF) is a critical activity-dependent modulator of gene expression, which can regulate both transcription and translation. Several functions of BDNF, including the induction of dendrite outgrowth and long-term synaptic plasticity, are known to depend, in particular, upon the ability of BDNF to regulate protein synthesis. Although BDNF modestly increases total neuronal protein synthesis, substantial evidence indicates that BDNF induces the translation of only a small subset of expressed mRNAs and demonstrates an extraordinary degree of transcript specificity. The mechanism by which BDNF selectively upregulates the translation of only a discrete group of mRNAs is of intrinsic importance to its trophic function in promoting neuronal growth and plasticity, and is the focus of this review. This article is part of the Special Issue entitled 'BDNF Regulation of Synaptic Structure, Function, and Plasticity'.

Hydroxynaphthyridine-derived group III metal chelates: wide band gap and deep blue analogues of green Alq3 (tris(8-hydroxyquinolate)aluminum) and their versatile applications for organic light-emitting diodes.

A series of group III metal chelates have been synthesized and characterized for the versatile application of organic light-emitting diodes (OLEDs). These metal chelates are based on 4-hydroxy-1,5-naphthyridine derivates as chelating ligands, and they are the blue version analogues of well-known green fluorophore Alq(3) (tris(8-hydroxyquinolinato)aluminum). These chelating ligands and their metal chelates were easily prepared with an improved synthetic method, and they were facially purified by a sublimation process, which enables the materials to be readily available in bulk quantity and facilitates their usage in OLEDs. Unlike most currently known blue analogues of Alq(3) or other deep blue materials, metal chelates of 4-hydroxy-1,5-naphthyridine exhibit very deep blue fluorescence, wide band gap energy, high charge carrier mobility, and superior thermal stability. Using a vacuum-thermal-deposition process in the fabrication of OLEDs, we have successfully demonstrated that the application of these unusual hydroxynaphthyridine metal chelates can be very versatile and effective. First, we have solved or alleviated the problem of exciplex formation that took place between the hole-transporting layer and hydroxynaphthyridine metal chelates, of which OLED application has been prohibited to date. Second, these deep blue materials can play various roles in OLED application. They can be a highly efficient nondopant deep blue emitter: maximum external quantum efficiency eta(ext) of 4.2%; Commision Internationale de L'Eclairage x, y coordinates, CIE(x,y) = 0.15, 0.07. Compared with Alq(3), Bebq(2) (beryllium bis(benzoquinolin-10-olate)), or TPBI (2,2',2''-(1,3,5-phenylene)tris(1-phenyl-1H-benzimidazole), they are a good electron-transporting material: low HOMO energy level of 6.4-6.5 eV and not so high LUMO energy level of 3.0-3.3 eV. They can be ambipolar and possess a high electron mobility of 10(-4) cm(2)/V s at an electric field of 6.4 x 10(5) V/cm. They are a qualified wide band gap host material for efficient blue perylene (CIE(x,y) = 0.14, 0.17 and maximum eta(ext) 3.8%) or deep blue 9,10-diphenylanthracene (CIE(x,y) = 0.15, 0.06 and maximum eta(ext) 2.8%). For solid state lighting application, they are desirable as a host material for yellow dopant (rubrene) in achieving high efficiency (eta(ext) 4.3% and eta(P) 8.7 lm/W at an electroluminance of 100 cd/m(2) or eta(ext) 3.9% and eta(P) 5.1 lm/W at an electroluminance of 1000 cd/m(2)) white electroluminescence (CIE(x,y) = 0.30, 0.35).

The acute and chronic toxicity of hexadecyl and heptadecyl sulfate to aquatic organisms.

HSAS (high-solubility alkyl sulfate) is a new anionic surfactant composed predominantly of methyl and ethyl branched hexadecyl and heptadecyl sulfate. Effects of HSAS on a wide range of fish, algae, and invertebrates were investigated in conventional laboratory toxicity tests as well as in exposures conducted as part of an experimental stream model ecosystem study. For invertebrates and fish, C(16.7)HSAS (average alkyl chain length 16.7) acute LC(50) values ranged from 0.23 (channel catfish) to 2.9 (Asiatic clam, Corbicula) mg/L in well and river waters. LC(50) values for those species tested in both waters were typically within a factor of 1.5 and all were within a factor of 2 of each other, suggesting bioavailability is similar in these waters. Chronic toxicity values ranged from 0.070 (fathead minnow) to 0.42 (amphipod, Hyalella) mg/L across fish and invertebrates with algal chronic toxicity values ranging from 0.5 (blue-green algae, Anabaena flos-aquae) to 7.8 (green algae, Scenedesmus) mg/L. The order of sensitivity to HSAS acute and chronic toxicity was fish = invertebrate > algae. Based on the chronic single species sensitivity distribution, the concentrations protective of 90 and 95% of species were estimated to be 0.058 and 0.036 mg/L, respectively. These compare well with the model ecosystem NOEC of 0.064 mg/L.

Synthesis, characterization, and photophysical properties of Os(II) diimine complexes [Os(N(wedge)N)(CO)(2)I(2)] (N(wedge)N = bipyridine, phenanthroline, and pyridyl benzoxazole).

A new series of Os(II) diimine complexes with the general formula [Os(N(wedge)N)(CO)(2)I(2)], N(wedge)N = 2,2'-bipyridine (bpy) (1), 4,4'-di-tert-butyl-2,2'-bipyridine (dbubpy) (2), 4,7-diphenyl-1,10-phenanthroline (dpphen) (3), 2-(2'-pyridyl)benzoxazole (pboz) (4), and 5-tert-butyl-2-(2'-pyridyl)benzoxazole (bupboz) (5), were synthesized and characterized by spectroscopic methods and by a single-crystal X-ray diffraction study on the dpphen complex 3. The corresponding photophysical properties were studied using UV-vis and emission spectrometry. The resulting phosphorescence features both in solution and as a solid film, in combination with the MO calculation, lead us to conclude that the emissions originate from mixed halide-to-ligand (XLCT approximately 70%) and metal-to-ligand (MLCT approximately 30%) transitions instead of the typical MLCT transition. Using complexes 4 and 5 as the dopant emitters, we evaluated their potential to serve as a phosphor for organic light emitting diodes by examining their electroluminescent performances. Reddish orange electroluminescence centered around 600 nm was observed for organic light emitting diodes (OLEDs) fabricated using complex 5 as the emitter; the device efficiency was shown to be as high as 2.8% (and 5.0 cd/A or 2.7 lm/W), and the peak luminance was shown to be 5600 cd/m(2) at a driving voltage of approximately 15 V.

Readily synthesised arylamino fumaronitrile for non-doped red organic light-emitting diodes.

Bright (maximum 10034 cd m(-2), 455 cd m(-2) at 20 mA cm(-2)) and efficient (maximum 2.4% at 4 mA cm(-2)) red (lambda(max)el 634-636 nm) organic light-emitting diodes employ arylamino-substituted fumaronitrile as the novel host emitter, which is readily prepared and easily purified.

Modeling nonsteady-state conditions and kinetics of mass transport for hydrophobic compounds in activated-sludge treatment.

A new model that describes the fate of hydrophobic and volatile organic compounds in activated-sludge treatment includes two novel features. First, all of the mass balances are nonsteady state, which allows the model to describe the effects of transients in loading, temperature, or operation. Second, the model describes the mass transfer of hydrophobic compounds with kinetics, not equilibrium. A series of examples demonstrate the new features of the model and how they can be important. When the kinetics of mass transfer are not fast, hydrophobic compounds remain significantly out of equilibrium, even when the system is operating at steady state. When the loading of a hydrophobic compound increases, its aqueous-phase concentration approaches (but does not quite reach) its steady-state concentration much more rapidly than does the density of the adsorbed hydrophobic compound. Finally, the importance of mass-transport kinetics between the aqueous and sorbed phases suggests that research should be focused on this poorly understood mechanism in activated sludge.