Broad-coverage biomedical relation extraction with SemRep.

BACKGROUND: In the era of information overload, natural language processing (NLP) techniques are increasingly needed to support advanced biomedical information management and discovery applications. In this paper, we present an in-depth description of SemRep, an NLP system that extracts semantic relations from PubMed abstracts using linguistic principles and UMLS domain knowledge. We also evaluate SemRep on two datasets. In one evaluation, we use a manually annotated test collection and perform a comprehensive error analysis. In another evaluation, we assess SemRep's performance on the CDR dataset, a standard benchmark corpus annotated with causal chemical-disease relationships. RESULTS: A strict evaluation of SemRep on our manually annotated dataset yields 0.55 precision, 0.34 recall, and 0.42 F 1 score. A relaxed evaluation, which more accurately characterizes SemRep performance, yields 0.69 precision, 0.42 recall, and 0.52 F 1 score. An error analysis reveals named entity recognition/normalization as the largest source of errors (26.9%), followed by argument identification (14%) and trigger detection errors (12.5%). The evaluation on the CDR corpus yields 0.90 precision, 0.24 recall, and 0.38 F 1 score. The recall and the F 1 score increase to 0.35 and 0.50, respectively, when the evaluation on this corpus is limited to sentence-bound relationships, which represents a fairer evaluation, as SemRep operates at the sentence level. CONCLUSIONS: SemRep is a broad-coverage, interpretable, strong baseline system for extracting semantic relations from biomedical text. It also underpins SemMedDB, a literature-scale knowledge graph based on semantic relations. Through SemMedDB, SemRep has had significant impact in the scientific community, supporting a variety of clinical and translational applications, including clinical decision making, medical diagnosis, drug repurposing, literature-based discovery and hypothesis generation, and contributing to improved health outcomes. In ongoing development, we are redesigning SemRep to increase its modularity and flexibility, and addressing weaknesses identified in the error analysis.

National cancer screening program for gastric cancer in Korea: Nationwide treatment benefit and cost.

BACKGROUND: The purpose of this study was to evaluate the nationwide benefit and cost of the national cancer screening program (NCSP) for gastric cancer treatment. METHODS: For this nationwide, population-based study, the Korean National Health Insurance Big Data Base, which included gastric cancer-related treatment information and the costs for all patients with gastric cancer who were 40 years old or older between 2004 and 2013, was restructured. Patients with gastric cancer who participated in the NCSP at least once (the screening group) were compared with those who did not participate in the NCSP (the nonscreening group). RESULTS: The screening group (n = 116,775) spent significantly less on medical care expenses than the nonscreening group (n = 74,927) during the 5 years since the initial treatment (P < .0001). The screening group presented a significantly better prognosis for 5 and 9 years than the nonscreening group (P < .0001). The screening group revealed a 41% decreased hazard ratio (P < .0001) for death in comparison with the nonscreening group; the prognostic benefit became more obvious when treatment was started within the first 4 months after screening. The age-standardized mortality rate ratio of the screening group versus the nonscreening group was 0.62 (P < .0001). The NCSP for gastric cancer required an average of 22,169,769 Korean Republic won (US $20,309) for 1 life-year saved, which was less than the average gross domestic product (GDP) per capita in Korea. CONCLUSIONS: The screening group had significantly lower medical care expenses and showed a significantly better prognosis than the nonscreening group. On the basis of the GDP per capita, the NCSP for gastric cancer was cost-effective for treatment prognosis.

Prevalence and incidence of neuromyelitis optica spectrum disorder and multiple sclerosis in Korea.

BACKGROUND: The epidemiology of neuromyelitis optica spectrum disorder and multiple sclerosis varies depending on the region and ethnicity. OBJECTIVE: To estimate the prevalence and incidence of neuromyelitis optica spectrum disorder and multiple sclerosis in Korea during 2010-2016. METHODS: We analyzed the National Health Insurance research database, which contains single-payer health insurance data collected in Korea. Neuromyelitis optica spectrum disorder was defined based on the 2006 Wingerchuk criteria (for 2010-2015), and the 2015 International Panel for Neuromyelitis Optica Diagnosis criteria (for 2016). Multiple sclerosis was defined by the 2005 International Panel criteria for multiple sclerosis. RESULTS: In 2016, the age-standardized prevalence per 100,000 persons was 2.56 (95% confidence interval: 2.43-2.7) for neuromyelitis optica spectrum disorder and 3.23 (95% confidence interval: 3.08-3.39) for multiple sclerosis. The age-standardized incidence of neuromyelitis optica spectrum disorder and multiple sclerosis were 0.73 (95% confidence interval: 0.66-0.8) and 0.50 (95% confidence interval: 0.44-0.56) per 100,000 persons in 2016. The prevalence of neuromyelitis optica spectrum disorder and multiple sclerosis have increased over time during 2010-2016 (18.5% and 5.4% annually; both p-trend < 0.001). The incidence of neuromyelitis optica spectrum disorder increased annually (10.0%, p-trend < 0.001), while the incidence of multiple sclerosis remained stable. CONCLUSION: While the prevalence of neuromyelitis optica spectrum disorder and multiple sclerosis are comparable in Korea, the incidence of neuromyelitis optica spectrum disorder is higher than that of multiple sclerosis. Both the prevalence and incidence of neuromyelitis optica spectrum disorder are rapidly increasing in Korea.

Towards a characterization of apparent contradictions in the biomedical literature using context analysis.

BACKGROUND: With the substantial growth in the biomedical research literature, a larger number of claims are published daily, some of which seemingly disagree with or contradict prior claims on the same topics. Resolving such contradictions is critical to advancing our understanding of human disease and developing effective treatments. Automated text analysis techniques can facilitate such analysis by extracting claims from the literature, flagging those that are potentially contradictory, and identifying any study characteristics that may explain such contradictions. METHODS: Using SemMedDB, our own PubMed-scale repository of semantic predications (subject-relation-object triples), we identified apparent contradictions in the biomedical research literature and developed a categorization of contextual characteristics that explain such contradictions. Clinically relevant semantic predications relating to 20 diseases and involving opposing predicate pairs (e.g., an intervention treats or causes a disease) were retrieved from SemMedDB. After addressing inference, uncertainty, generic concepts, and NLP errors through automatic and manual filtering steps, a set of apparent contradictions were identified and characterized. RESULTS: We retrieved 117,676 predication instances from 62,360 PubMed abstracts (Jan 1980-Dec 2016). From these instances, automatic filtering steps generated 2236 candidate contradictory pairs. Through manual analysis, we determined that 58 of these pairs (2.6%) were apparent contradictions. We identified five main categories of contextual characteristics that explain these contradictions: (a) internal to the patient, (b) external to the patient, (c) endogenous/exogenous, (d) known controversy, and (e) contradictions in literature. Categories (a) and (b) were subcategorized further (e.g., species, dosage) and accounted for the bulk of the contradictory information. CONCLUSIONS: Semantic predications, by accounting for lexical variability, and SemMedDB, owing to its literature scale, can support identification and elucidation of potentially contradictory claims across the biomedical domain. Further filtering and classification steps are needed to distinguish among them the true contradictory claims. The ability to detect contradictions automatically can facilitate important biomedical knowledge management tasks, such as tracking and verifying scientific claims, summarizing research on a given topic, identifying knowledge gaps, and assessing evidence for systematic reviews, with potential benefits to the scientific community. Future work will focus on automating these steps for fully automatic recognition of contradictions from the biomedical research literature.

Observation of partial reduction of manganese in the lithium rich layered oxides, 0.4Li2MnO3-0.6LiNi1/3Co1/3Mn1/3O2, during the first charge.

Lithium-rich layered oxides show promise as high-energy harvesting materials due to their large capacities. However, questions remain regarding the large irreversible loss in capacities for the first charge-discharge cycle due to oxygen removal in lattices related to layered Li2MnO3. Herein we present detailed studies on Li-rich Mn-based layered oxides of 0.4Li2MnO3-0.6LiNi1/3Co1/3Mn1/3O2 (Li-rich NCM) electrochemically activated between 2.5 V and 4.3 or 4.7 V vs. Li+/Li. Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) revealed unusual manganese reduction after the first charge up to a high voltage of 4.7 V. Moreover, the electronic structure did not fully recover to the original pristine of Mn4+ state after discharge. Interestingly, these phenomena were not limited to a single particle, but were observed across the entire electrode. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) images and electron dispersive spectra (EDS) also showed a dramatic decline in oxygen content with highly porous morphologies, associated with oxygen vacancy formation following oxidation of O2- ions to O2. Our analysis suggests that an unstable manganese valence state with severe defects due to oxygen vacancies may lead to large irreversible capacity loss during the first charge-discharge cycle of Li-rich layered oxides.

Awareness about past diagnosis and treatment history: nationwide survey of childhood cancer survivors and their parents.

OBJECTIVE: To assess the awareness of past medical history and long-term care issues of childhood cancer survivors (CCS) in Korea. METHODS: A nationwide survey was conducted on CCS and their parents in 10 regional cancer centers in Korea. Answers regarding cancer diagnosis and treatment history were compared with the treatment summary and categorized into three ('specific,' 'general,' and 'no') or two ('yes' and 'no') groups. RESULTS: Out of 343 contacts, 293 dyads completed the survey, and 281 dyads were analyzed. Awareness of cancer diagnosis was mostly specific for parents (76.5%) and CCS (35.2%). Awareness of anti-cancer treatment exposure was mostly general (84.6% for surgery, 67.9% for chemotherapy, and 53.9% for hematopoietic stem cell transplantation) rather than specific. In particular, more than half of the parents were not aware of the exposure to cardiotoxic agents (72.9%) or radiation therapy (56.3%). Providing information about long-term side effects and prevention of secondary cancer was significantly correlated only with more concern and more follow-up visits (P ≤ 0.001, respectively), without correlation with more specific awareness of exposure to cardiotoxic agents or radiation. CONCLUSION(S): Most of the parents of CCS were not aware of treatment-related risk factors necessary for long-term care. Providing information was significantly correlated with more concern and more follow-up visits, without improving corresponding knowledge about their past medical history. Effort aimed towards improving awareness about risk factors, the manner of providing information, and the patient referral system within which we use this information is warranted.

Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.

Influence of citric acid molar ratio on the sintering behavior of nanocrystalline BaCe0.8Sm0.2O(3-delta).

The samarium-doped barium cerate (BaCe0.8Sm0.2O(3-delta), BCS) nano crystalline powders were synthesized via citric-nitrate method. The BCS nanopowders were prepared with various molar ratio of citric acid to metal nitrate. The pure perovskite structure was obtained from the BCS calcinated at 1200 degrees C and its crystalline size was increased with increase of the molar ratio citric acid to metal nitrate, while the aggregated particle size was significantly decreased as increasing the molar ratio. Also, excellent densification behavior was observed when high molar ratio of citric acid to metal nitrate was used. It was clarified that the molar ratio of citric acid determines the aggregated particle size and, in turn, finial microstructure after sintering.

Analysis of Self-Assembled Low- and High-Molecular-Weight Poly-L-Lysine-Ce6 Conjugate-Based Nanoparticles.

In cancer therapy, photodynamic therapy (PDT) has attracted significant attention due to its high potential for tumor-selective treatment. However, PDT agents often exhibit poor physicochemical properties, including solubility, necessitating the development of nanoformulations. In this study, we developed two cationic peptide-based self-assembled nanomaterials by using a PDT agent, chlorin e6 (Ce6). To manufacture biocompatible nanoparticles based on peptides, we used the cationic poly-L-lysine peptide, which is rich in primary amines. We prepared low- and high-molecular-weight poly-L-lysine, and then evaluated the formation and performance of nanoparticles after chemical conjugation with Ce6. The results showed that both molecules formed self-assembled nanoparticles by themselves in saline. Interestingly, the high-molecular-weight poly-L-lysine and Ce6 conjugates (HPLCe6) exhibited better self-assembly and PDT performance than low-molecular-weight poly-L-lysine and Ce6 conjugates (LPLCe6). Moreover, the HPLCe6 conjugates showed superior cellular uptake and exhibited stronger cytotoxicity in cell toxicity experiments. Therefore, it is functionally beneficial to use high-molecular-weight poly-L-lysine in the manufacturing of poly-L-lysine-based self-assembling biocompatible PDT nanoconjugates.

Clustering cliques for graph-based summarization of the biomedical research literature.

BACKGROUND: Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts). RESULTS: SemRep is used to extract semantic predications from the citations returned by a PubMed search. Cliques were identified from frequently occurring predications with highly connected arguments filtered by degree centrality. Themes contained in the summary were identified with a hierarchical clustering algorithm based on common arguments shared among cliques. The validity of the clusters in the summaries produced was compared to the Silhouette-generated baseline for cohesion, separation and overall validity. The theme labels were also compared to a reference standard produced with major MeSH headings. CONCLUSIONS: For 11 topics in the testing data set, the overall validity of clusters from the system summary was 10% better than the baseline (43% versus 33%). While compared to the reference standard from MeSH headings, the results for recall, precision and F-score were 0.64, 0.65, and 0.65 respectively.

SemMedDB: a PubMed-scale repository of biomedical semantic predications.

SUMMARY: Effective access to the vast biomedical knowledge present in the scientific literature is challenging. Semantic relations are increasingly used in knowledge management applications supporting biomedical research to help address this challenge. We describe SemMedDB, a repository of semantic predications (subject-predicate-object triples) extracted from the entire set of PubMed citations. We propose the repository as a knowledge resource that can assist in hypothesis generation and literature-based discovery in biomedicine as well as in clinical decision-making support. AVAILABILITY AND IMPLEMENTATION: The SemMedDB repository is available as a MySQL database for non-commercial use at http://skr3.nlm.nih.gov/SemMedDB. An UMLS Metathesaurus license is required. CONTACT: kilicogluh@mail.nih.gov.

A methodology for extending domain coverage in SemRep.

We describe a domain-independent methodology to extend SemRep coverage beyond the biomedical domain. SemRep, a natural language processing application originally designed for biomedical texts, uses the knowledge sources provided by the Unified Medical Language System (UMLS©). Ontological and terminological extensions to the system are needed in order to support other areas of knowledge. We extended SemRep's application by developing a semantic representation of a previously unsupported domain. This was achieved by adapting well-known ontology engineering phases and integrating them with the UMLS knowledge sources on which SemRep crucially depends. While the process to extend SemRep coverage has been successfully applied in earlier projects, this paper presents in detail the step-wise approach we followed and the mechanisms implemented. A case study in the field of medical informatics illustrates how the ontology engineering phases have been adapted for optimal integration with the UMLS. We provide qualitative and quantitative results, which indicate the validity and usefulness of our methodology.

The association between perceived social support and continued smoking in cancer survivors.

OBJECTIVE: With the increased survival rate of cancer patients, positive changes in health behaviors, including smoking cessation, are becoming progressively more important. While studies in the general population have demonstrated the beneficial effects of high perceived support of smoking cessation and continuing abstinence, few studies have addressed such issues in cancer survivors. We examined the factors related to continued smoking among cancer survivors with specific attention given to the role of perceived social support. METHODS: A nationwide, multicenter survey was conducted with 1956 cancer patients. Smoking status at the time of diagnosis and at the time of survey, and perceived social support, as measured by the Duke-UNC Functional Social Support Questionnaire, were collected by self-reported questionnaire. RESULTS: Among 493 participants who were smoking at the time of cancer diagnosis, 131 (26.6%) were continued smokers at the time of survey. In a multivariate logistic regression analysis, current alcohol consumption (odds ratio, 3.29; 95% confidence interval, 1.91-5.65), early cancer stage (P(for trend)< 0.01), lung cancer diagnosis (odds ratio, 0.41; 95% confidence interval, 0.19-0.88), and high perceived social support (odds ratio, 0.59; 95% confidence interval, 0.37-0.96) showed significant associations with continued smoking. CONCLUSIONS: Cancer survivors with low perceived social support were more likely to continue smoking. Our study suggests that perceived social support may be an important factor for smoking cessation and maintenance of smoking cessation in this population.

Improved chemical stability and conductivity of barium cerate nanopowders by Lanthanum doping.

Despite of the highest proton conductivity, barium cerate electrolytes are well known for the deficiency of chemical stability at elevated temperature under CO2 atmosphere. This work is focused on improving chemical stability of lanthanum doped barium cerate (BCL) powder for electrolyte. Although lanthanum doping causes distortion of perovskite structure lattice, immoderate doping could stabilize structure due to increasing symmetry of structure lattices. The thermogravimetric analysis and AC impedance measurements revealed that the lanthanum doping suppresses the reaction between barium and carbonate and this effect results in sufficient improvement in ionic conductivity in operating temperatures range. It was confirmed that BaCe0.7La0.3O3-delta (BCL30) was the most stable composition and the conductivity of BCL30 is high as 3.8 S x cm(-1) x K at 700 degrees C.

Morphological and structural properties of electrospun Sm0.5Sr0.5CoO3-delta nanofibers.

Strontium-doped samarium cobaltite (Sm0.5Sr0.5CoO3-delta, SSC) fibers were successfully fabricated by electrospinning of a precursor gel derived from polyvinyl alcohol (PVA) and aqueous metal nitrate. After calcination of the as-spun SSC fibers in microwave furnace at above 500 degrees C, SSC fibers of 100 +/- 20 nm in diameter with well-developed cubic-perovskite structure were successfully obtained. The crystal structure morphology, and grain structure of the fibers were influenced by the calcination temperature and the grain structure was evolved to "bamboo" structured polycrystalline SSC at above 700 degrees C.

Effect of interlayer spacing on the electrochemical properties of alkali titanate nanotubes.

Multilayered titanate nanotubes (TNTs) has been considered as a candidate for lithium ion battery anode material. However, it has a problem of high irreversible capacity due to trapped lithium ions in the interlayer space. To solve this problem, an attempt to enlarge the interlayer spacing has been made in this work to improve intercalation characteristics of TNTs. Monoatomic ions in hydrothermally heat-treated TNTs were substituted to one of Li, Na and K alkali ions via ion-exchange process. The TNTs (200) interlayer spacing peak in XRD patterns showed a shift to a lower angle, indicating an enlarged interlayer spacing of TNTs. The Li-, Na- and K-ion exchanged TNTs exhibited an initial capacity of 214, 230 and 248 mA h/g at 0.1 C, respectively, in the TNTs // LiPF6 electrolyte // Li metal coin type cell test. It was found that the enlarged interlayer spacing resulted in an increment in the specific capacity and rate capability. This increase was attributed to both the enhanced lithium ion diffusion and the increased number of lithium ion intercalation sites in the TNTs interlayers.

Regional factors associated with participation in the national health screening program: a multilevel analysis using national data.

High participation rates are important for maximizing the effects of a health screening program. Previous studies have suggested that individual or regional characteristics have effects on health behaviors. In this study, we investigated the determinants of participation in the National Screening Program for Transitional Ages by simultaneously analyzing individual and area-level factors by multilevel analysis. A total of 1,081,216 subjects, aged 40 and 66 yr and nested in 254 areas, were included. There was a significant variation in participation rates across the areas even after adjusting for individual and area-level variables. Among the individual-level variables, increasing age, sex, higher income, and mild disability grade were associated with a higher participation rate. In urban areas, the 40-yr-old group had higher participation rates than the 66-yr-old group. Deprived areas had significantly high participation rates for both age groups. The number of screening centers per 1,000 inhabitants had no significant effect on participation in the screening program. In conclusion, regional characteristics are associated with participation rates independent of personal features and regional factors have differential effects with respect to age. A multi-dimensional approach is recommended to promote participation in health screening programs.

Determinants of family satisfaction with inpatient palliative care in Korea.

OBJECTIVE: We aimed to identify which structures and processes of care are key determinants of overall satisfaction with palliative care. METHODS: A nationwide, multicentre, cross-sectional questionnaire survey was conducted with 501 bereaved family members of terminal cancer patients (effective response rate: 20.9 percent). Structures and processes were evaluated using the Care Evaluation Scale (CES). RESULTS: In univariate analyses, all domains of the CES were significantly associated with overall satisfaction with care. In multivariate analyses, the domains of physical care by physician, physical care by nurse, environment, and coordination positively influenced overall satisfaction. After case-mix adjustment, physical care by nurse, age of patient, and lower education level of bereaved family member remained as significant determinants. CONCLUSION: Our finding that nursing is the most critical determinant of overall satisfaction within many structure and process domains has an important implication for clinical quality improvement and resource allocation.

Comparison of the Smoking Cessation of Heated Tobacco Product Users and Conventional Cigarette Smokers in Korea.

BACKGROUND: Since the introduction of heated tobacco products (HTPs) in Korea in 2017, their annual sales have increased. Several studies have investigated the perceptions of HTPs and smoking cessation behaviors. For the first time, In 2019, questions focused on HTP use were introduced in the Korea National Health and Nutrition Examination Survey (KNHNES). This study aimed to compare smoking cessation behaviors between HTP users and conventional cigarette smokers using KNHANES data. METHODS: Data of 947 current adult smokers from the 8th KNHNES (2019) were analyzed. Current smokers were divided into conventional cigarette (CC)-only, HTP-only, and dual-use groups. The general characteristics of the three groups were investigated. Differences in current intention to quit smoking and past attempts to quit smoking among the three groups were analyzed using multivariate logistic regression analysis by IBM SPSS ver. 25.0. RESULTS: HTP-only users demonstrated fewer future smoking cessation plans (adjusted odds ratio [AOR], 0.398; 95% confidence interval [CI], 0.195-0.813; P=0.012) and fewer smoking cessation attempts in the past year (AOR, 0.533; 95% CI, 0.298-0.954; P=0.034) than CC-only smokers. However, there was no significant difference between dual-use (CC+HTP) and CC-only smokers. CONCLUSION: While dual-use and CC-only smokers showed similar smoking cessation behaviors, HTP-only users had fewer previous attempts to quit smoking and were less likely to be currently ready to quit smoking. These findings can be explained by a decrease in the need to quit smoking due to the convenience of HTP and the perception that HTPs are less harmful than CC.

Psychometric Testing of a New Instrument for Assessing Cancer Patient Preparedness for the Survivorship Transition.

Purpose: This study aims to develop and examine the psychometric properties of the "Preparedness for Transition to Survivorship Care Instrument" (PTSCI) for cancer survivors. Methods: A cross-sectional study of cancer survivors in Korea was conducted to test the reliability and validity of the PTSCI. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and concurrent validity tests were conducted. Results: The EFA showed that the 7-factor structure of a 34-item PTSCI accounted for 61.5% of the total observed variance. In CFA, three competing models were created and compared to a seven-factor solution model. A 6-factor 31-item model showed the best fit and was chosen as the final PTSCI model. PTSCI is significantly associated with quality of life, psychological distress, and health promotion. Conclusions: PTSCI can be helpful in preparing for diverse psychosocial and behavioral issues faced by cancer survivors in the survivorship phase.