Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation

Background: The use of knowledge models facilitates information retrieval, knowledge base development, and therefore supports new knowledge discovery that ultimately enables decision support applications. Most existing works have employed machine learning techniques to construct a knowledge base. However, they often suffer from low precision in extracting entity and relationships. In this paper, we described a data-driven sublanguage pattern mining method that can be used to create a knowledge model. We combined natural language processing (NLP) and semantic network analysis in our model generation pipeline. Methods: As a use case of our pipeline, we utilized data from an open source imaging case repository, Radiopaedia.org, to generate a knowledge model that represents the contents of medical imaging reports. We extracted entities and relationships using the Stanford part-of-speech parser and the “Subject:Relationship:Object” syntactic data schema. The identified noun phrases were tagged with the Unified Medical Language System (UMLS) semantic types. An evaluation was done on a dataset comprised of 83 image notes from four data sources. Results: A semantic type network was built based on the co-occurrence of 135 UMLS semantic types in 23,410 medical image reports. By regrouping the semantic types and generalizing the semantic network, we created a knowledge model that contains 14 semantic categories. Our knowledge model was able to cover 98% of the content in the evaluation corpus and revealed 97% of the relationships. Machine annotation achieved a precision of 87%, recall of 79%, and F-score of 82%. Conclusion: The results indicated that our pipeline was able to produce a comprehensive content-based knowledge model that could represent context from various sources in the same domain

Characteristic cytokine profile of the aqueous humor in eyes with congenital cataract and pre-existing posterior capsule dysfunction

ObjectivesTo investigate the characteristic cytokine profile of the aqueous humor in eyes with congenital cataract and pre-existing posterior capsule dysfunction (PCD).MethodsIn this cross-sectional study, the enrolled eyes with congenital cataract and PCD were included in the PCD group, while those with an intact posterior capsule were included in the control group. Demographic data and biometric parameters were recorded. The levels of 17 inflammatory factors in the aqueous humor collected from the enrolled eyes were detected using Luminex xMAP technology, and intergroup differences in the collected data were analyzed.ResultsThe PCD group comprised 41 eyes from 31 patients with congenital cataract and PCD, whereas the control group comprised 42 eyes from 27 patients with congenital cataract and an intact posterior capsule. Lens thickness was significantly thinner in the PCD group than in the control group. However, the levels of monocyte chemoattractant protein-1 (MCP-1), transforming growth factor-β2 (TGF-β2), and vascular endothelial growth factor (VEGF) were significantly higher in the PCD group than in the control group. Multivariate logistic regression confirmed that lens thickness and TGF-β2 level were independent risk factors for PCD.ConclusionA thinner lens thickness in eyes with congenital cataract and PCD could serve as a biometric feature of these eyes. The higher levels of MCP-1, TGF-β2, and VEGF in eyes with PCD indicated a change in their intraocular inflammatory microenvironment, which possibly led to cataract progression. Lens thickness and TGF-β2 level are independent risk factors for PCD

A global North-South division line for portraying urban development

Rapid urbanization has tremendously changed the global landscape with profound impacts on our society. Nighttime light (NTL) data can provide valuable information about human activities and socioeconomic conditions thus has become an effective proxy to measure urban development. By using NTL-derived urban measures from 1992 to 2018, we analyzed the spatiotemporal patterns of global urban development from country to region to city scales, which presented a distinct North-South divergence characterized by the rising and declining patterns. A global North-South division line was identified to partition the globe into the Line-North and the Line-South geographically, which accorded with the socioeconomic difference from the aspects of urban population and economy. This line may keep a certain degree of stability deriving from the trends of population and economic information but also bears uncertainties in the long term

PCAT1 is a poor prognostic factor in endometrial carcinoma and associated with cancer cell proliferation, migration and invasion

Long non-coding RNAs (lncRNAs) are emerging as important modulators of cancer progression, among which prostate cancer-associated transcript 1 (PCAT1) has been shown to be an oncogene in several tumors. However, the clinical significance and biological function of PCAT1 in endometrial carcinoma (EC) remain unclear. In this study, we used 89 EC tissues and HEC-1B, Ishikawa, RL95-2 and AN3CA EC cell lines. We found elevated expression levels of PCAT1 in EC tissues and cell lines using reverse transcription qPCR (RT-qPCR). The prognostic value of PCAT1 was determined using Kaplan–Meier survival and Cox regression analysis. The results showed that higher PCAT1 expression was positively correlated with FIGO stage, myometrial invasion, lymph node metastasis, and a shorter overall survival. A series of functional assays showed that the knockdown of PCAT1 by small interfering RNA (siRNA) targeting PCAT1 (siPCAT1) suppressed cell proliferation, migration and invasion, but promoted apoptosis. Western blot analysis further showed that B-cell lymphoma 2 (Bcl-2), vimentin and N-cadherin were downregulated, but E-cadherin and Bcl-2-associated death promoter (Bad) were upregulated in PCAT1-silenced EC cells. Taken together, our results underscore the oncogenic role of PCAT1 in EC and show that PCAT1 may be a potential therapeutic target in EC treatment

Greenhouse gas emissions from U.S. crude oil pipeline accidents:1968 to 2020

Abstract Crude oil pipelines are considered as the lifelines of energy industry. However, accidents of the pipelines can lead to severe public health and environmental concerns, in which greenhouse gas (GHG) emissions, primarily methane, are frequently overlooked. While previous studies examined fugitive emissions in normal operation of crude oil pipelines, emissions resulting from accidents were typically managed separately and were therefore not included in the emission account of oil systems. To bridge this knowledge gap, we employed a bottom-up approach to conducted the first-ever inventory of GHG emissions resulting from crude oil pipeline accidents in the United States at the state level from 1968 to 2020, and leveraged Monte Carlo simulation to estimate the associated uncertainties. Our results reveal that GHG emissions from accidents in gathering pipelines (~720,000 tCO2e) exceed those from transmission pipelines (~290,000 tCO2e), although significantly more accidents have occurred in transmission pipelines (6883 cases) than gathering pipelines (773 cases). Texas accounted for over 40% of total accident-related GHG emissions nationwide. Our study contributes to enhanced accuracy of the GHG account associated with crude oil transport and implementing the data-driven climate mitigation strategies

Extensive beam test study of prototype MRPCs for the T0 detector at the CSR external-target experiment

The CSR External-target Experiment (CEE) will be the first large-scale nuclear physics experiment device at the Cooling Storage Ring (CSR) of the Heavy-Ion Research Facility in Lanzhou (HIRFL) in China. A new T0 detector has been proposed to measure the multiplicity, angular distribution and timing information of charged particles produced in heavy-ion collisions at the target region. Multi-gap resistive plate chamber (MRPC) technology was chosen as part of the construction of the T0 detector, which provides precision event collision times (T0) and collision geometry information. The prototype was tested with hadron and heavy-ion beams to study its performance. By comparing the experimental results with a Monte Carlo simulation, the time resolution of the MRPCs are found to be $\sim$ 50 ps or better. The timing performance of the T0 detector, including both detector and readout electronics, we found to fulfil the requirements of the CEE.Comment: 12 pages, 36 figure