Epigenetic memory of coronavirus infection in innate immune cells and their progenitors.

Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.

A vertebral skeletal stem cell lineage driving metastasis.

Vertebral bone is subject to a distinct set of disease processes from long bones, including a much higher rate of solid tumour metastases1-4. The basis for this distinct biology of vertebral bone has so far remained unknown. Here we identify a vertebral skeletal stem cell (vSSC) that co-expresses ZIC1 and PAX1 together with additional cell surface markers. vSSCs display formal evidence of stemness, including self-renewal, label retention and sitting at the apex of their differentiation hierarchy. vSSCs are physiologic mediators of vertebral bone formation, as genetic blockade of the ability of vSSCs to generate osteoblasts results in defects in the vertebral neural arch and body. Human counterparts of vSSCs can be identified in vertebral endplate specimens and display a conserved differentiation hierarchy and stemness features. Multiple lines of evidence indicate that vSSCs contribute to the high rates of vertebral metastatic tropism observed in breast cancer, owing in part to increased secretion of the novel metastatic trophic factor MFGE8. Together, our results indicate that vSSCs are distinct from other skeletal stem cells and mediate the unique physiology and pathology of vertebrae, including contributing to the high rate of vertebral metastasis.

An antioxidant feedforward cycle coordinated by linker histone variant H1.2 and NRF2 that drives nonsmall cell lung cancer progression.

Nonsmall cell lung cancer (NSCLC) is highly malignant with limited treatment options, platinum-based chemotherapy is a standard treatment for NSCLC with resistance commonly seen. NSCLC cells exploit enhanced antioxidant defense system to counteract excessive reactive oxygen species (ROS), which contributes largely to tumor progression and resistance to chemotherapy, yet the mechanisms are not fully understood. Recent studies have suggested the involvement of histones in tumor progression and cellular antioxidant response; however, whether a major histone variant H1.2 (H1C) plays roles in the development of NSCLC remains unclear. Herein, we demonstrated that H1.2 was increasingly expressed in NSCLC tumors, and its expression was correlated with worse survival. When crossing the H1c knockout allele with a mouse NSCLC model (KrasLSL-G12D/+), H1.2 deletion suppressed NSCLC progression and enhanced oxidative stress and significantly decreased the levels of key antioxidant glutathione (GSH) and GCLC, the catalytic subunit of rate-limiting enzyme for GSH synthesis. Moreover, high H1.2 was correlated with the IC50 of multiple chemotherapeutic drugs and with worse prognosis in NSCLC patients receiving chemotherapy; H1.2-deficient NSCLC cells presented reduced survival and increased ROS levels upon cisplatin treatment, while ROS scavenger eliminated the survival inhibition. Mechanistically, H1.2 interacted with NRF2, a master regulator of antioxidative response; H1.2 enhanced the nuclear level and stability of NRF2 and, thus, promoted NRF2 binding to GCLC promoter and the consequent transcription; while NRF2 also transcriptionally up-regulated H1.2. Collectively, these results uncovered a tumor-driving role of H1.2 in NSCLC and indicate an "H1.2-NRF2" antioxidant feedforward cycle that promotes tumor progression and chemoresistance.

Loss of renal tubular G9a benefits acute kidney injury by lowering focal lipid accumulation via CES1.

Surgery-induced renal ischemia and reperfusion (I/R) injury and nephrotoxic drugs like cisplatin can cause acute kidney injury (AKI), for which there is no effective therapy. Lipid accumulation is evident following AKI in renal tubules although the mechanisms and pathological effects are unclear. Here, we report that Ehmt2-encoded histone methyltransferase G9a is upregulated in patients and mouse kidneys after AKI. Renal tubular specific knockout of G9a (Ehmt2Ksp ) or pharmacological inhibition of G9a alleviates lipid accumulation associated with AKI. Mechanistically, G9a suppresses transcription of the lipolytic enzyme Ces1; moreover, G9a and farnesoid X receptor (FXR) competitively bind to the same promoter regions of Ces1. Ces1 is consistently observed to be downregulated in the kidney of AKI patients. Pharmacological inhibition of Ces1 increases lipid accumulation, exacerbates renal I/R-injury and eliminates the beneficial effects on AKI observed in Ehmt2Ksp mice. Furthermore, lipid-lowering atorvastatin and an FXR agonist alleviate AKI by activating Ces1 and reducing renal lipid accumulation. Together, our results reveal a G9a/FXR-Ces1 axis that affects the AKI outcome via regulating renal lipid accumulation.

tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data.

tRNA molecules contain dense, abundant modifications that affect tRNA structure, stability, mRNA decoding and tsRNA formation. tRNA modifications and related enzymes are responsive to environmental cues and are associated with a range of physiological and pathological processes. However, there is a lack of resources that can be used to mine and analyse these dynamically changing tRNA modifications. In this study, we established tModBase (https://www.tmodbase.com/) for deciphering the landscape of tRNA modification profiles from epitranscriptome data. We analysed 103 datasets generated with second- and third-generation sequencing technologies and illustrated the misincorporation and termination signals of tRNA modification sites in ten species. We thus systematically demonstrate the modification profiles across different tissues/cell lines and summarize the characteristics of tRNA-associated human diseases. By integrating transcriptome data from 32 cancers, we developed novel tools for analysing the relationships between tRNA modifications and RNA modification enzymes, the expression of 1442 tRNA-derived small RNAs (tsRNAs), and 654 DNA variations. Our database will provide new insights into the features of tRNA modifications and the biological pathways in which they participate.

LincRNA-ROR/miR-145/ZEB2 regulates liver fibrosis by modulating HERC5-mediated p53 ISGylation.

The tumor suppressor p53 has been implicated in the pathogenesis of liver fibrosis. HERC5-mediated posttranslational ISG modification of the p53 protein is critical for controlling its activity. Here, we demonstrated that the expression of HERC5 and ISG15 is highly elevated, whereas p53 is downregulated, in fibrotic liver tissues of mice and transforming growth factor-ß1 (TGF-ß1)-induced LX2 cells. HERC5 siRNA clearly increased the protein expression of p53, but the mRNA expression of p53 was not obviously changed. The inhibition of lincRNA-ROR (ROR) downregulated HERC5 expression and elevated p53 expression in TGF-ß1-stimulated LX-2 cells. Furthermore, the expression of p53 was almost unchanged after TGF-ß1-stimulated LX-2 cells were co-transfected with a ROR-expressing plasmid and HERC5 siRNA. We further confirmed that miR-145 is a target gene of ROR. In addition, we also showed that ROR regulates the HERC5-mediated ISGylation of p53 through mir-145/ZEB2. Together, we propose that ROR/miR-145/ZEB2 might be involved in the course of liver fibrosis by regulating ISGylation of the p53 protein.

Controllable Pyridine N-Oxidation-Nucleophilic Dechlorination Process for Enhanced Dechlorination of Chloropyridines: The Cooperation of HCO4- and HO2.

Dechlorination of chloropyridines can eliminate their detrimental environmental effects. However, traditional dechlorination technology cannot efficiently break the C-Cl bond of chloropyridines, which is restricted by the uncontrollable nonselective species. Hence, we propose the carbonate species-activated hydrogen peroxide (carbonate species/H2O2) process wherein the selective oxidant (peroxymonocarbonate ion, HCO4-) and selective reductant (hydroperoxide anion, HO2-) controllably coexist by manipulation of reaction pH. Taking 2-chloropyridine (Cl-Py) as an example, HCO4- first induces Cl-Py into pyridine N-oxidation intermediates, which then suffer from the nucleophilic dechlorination by HO2-. The obtained dechlorination efficiencies in the carbonate species/H2O2 process (32.5-84.5%) based on the cooperation of HCO4- and HO2- are significantly higher than those in the HO2--mediated sodium hydroxide/hydrogen peroxide process (0-43.8%). Theoretical calculations confirm that pyridine N-oxidation of Cl-Py can effectively lower the energy barrier of the dechlorination process. Moreover, the carbonate species/H2O2 process exhibits superior anti-interference performance and low electric energy consumption. Furthermore, Cl-Py is completely detoxified via the carbonate species/H2O2 process. More importantly, the carbonate species/H2O2 process is applicable for efficient dehalogenation of halogenated pyridines and pyrazines. This work offers a simple and useful strategy to enhance the dehalogenation efficiency of halogenated organics and sheds new insights into the application of the carbonate species/H2O2 process in practical environmental remediation.

Tight focusing of the vector optical field with polarization varying along complex curves of the Poincaré sphere.

Different from the scalar optical field with spatially uniform polarization, the vector optical field exhibits inhomogeneous distribution of polarization on the cross section. Manipulating the variation of polarization in a single optical beam is important to acquire a flexible and controllable focused optical field. Previous studies mainly focused on the vector optical field with its polarization varying along a circular trajectory of the Poincaré sphere. Here, we demonstrate the tight focusing behaviors of the vector optical field with the polarization varying along complex curves of the Poincaré sphere, which is generated by the joint modulation of azimuthal phase and amplitude distributions of orthogonally polarized components. The longitudinal polarization component with a multipolar pattern in rotational symmetry can be achieved with similar distribution of the total focused field. The transverse and longitudinal spin angular momentum distributions in the focal space are discussed. Approximately pure transverse spin angular momentum can be constructed and manipulated in the focal space, which provides the possibility to manipulate the 3D spin flux for the applications of nano and spin photonics.

tsRFun: a comprehensive platform for decoding human tsRNA expression, functions and prognostic value by high-throughput small RNA-Seq and CLIP-Seq data.

tRNA-derived small RNA (tsRNA), a novel type of regulatory small noncoding RNA, plays an important role in physiological and pathological processes. However, the understanding of the functional mechanism of tsRNAs in cells and their role in the occurrence and development of diseases is limited. Here, we integrated multiomics data such as transcriptome, epitranscriptome, and targetome data, and developed novel computer tools to establish tsRFun, a comprehensive platform to facilitate tsRNA research (http://rna.sysu.edu.cn/tsRFun/ or http://biomed.nscc-gz.cn/DB/tsRFun/). tsRFun evaluated tsRNA expression profiles and the prognostic value of tsRNAs across 32 types of cancers, identified tsRNA target molecules utilizing high-throughput CLASH/CLEAR or CLIP sequencing data, and constructed the interaction networks among tsRNAs, microRNAs, and mRNAs. In addition to its data presentation capabilities, tsRFun offers multiple real-time online tools for tsRNA identification, target prediction, and functional enrichment analysis. In summary, tsRFun provides a valuable data resource and multiple analysis tools for tsRNA investigation.

Targeted local anesthesia: a novel slow-release Fe3O4-lidocaine-PLGA microsphere endowed with a magnetic targeting function.

PURPOSE: Lidocaine microspheres can prolong the analgesic time to 24-48 h, which still cannot meet the need of postoperative analgesia lasting more than 3 days. Therefore, we added Fe3O4 to the lidocaine microspheres and used an applied magnetic field to attract Fe3O4 to fix the microspheres around the target nerves, reducing the diffusion of magnetic lidocaine microspheres to the surrounding tissues and prolonging the analgesic time. METHODS: Fe3O4-lidocaine-PLGA microspheres were prepared by the complex-emulsion volatilization method to characterize and study the release properties in vitro. The neural anchoring properties and in vivo morphology of the drug were obtained by magnetic resonance imaging. The nerve blocking effect and analgesic effect of magnetic lidocaine microspheres were evaluated by animal experiments. RESULTS: The mean diameter of magnetically responsive lidocaine microspheres: 9.04 ± 3.23 µm. The encapsulation and drug loading of the microspheres were 46.18 ± 3.26% and 6.02 ± 1.87%, respectively. Magnetic resonance imaging showed good imaging of Fe3O4-Lidocain-PLGA microspheres, a drug-carrying model that slowed down the diffusion of the microspheres in the presence of an applied magnetic field. Animal experiments demonstrated that this preparation had a significantly prolonged nerve block, analgesic effect, and a nerve anchoring function. CONCLUSION: Magnetically responsive lidocaine microspheres can prolong analgesia by slowly releasing lidocaine, which can be immobilized around the nerve by a magnetic field on the body surface, avoiding premature diffusion of the microspheres to surrounding tissues and improving drug targeting.

Promotion of squamous cell carcinoma tumorigenesis by oncogene-mediated THG-1/TSC22D4 phosphorylation.

Carcinoma cells possess high proliferative and invasive potentials and exhibit a resilience against stresses, metabolic disorder, and therapeutic efforts. These properties are mainly acquired by genetic alterations including driver gene mutations. However, the detailed molecular mechanisms have not been fully elucidated. Here, we provide a novel mechanism connecting oncogenic signaling and the tumorigenic properties by a transforming growth factor-ß1-stimulated clone 22 (TSC-22) family protein, THG-1 (also called as TSC22D4). THG-1 is localized at the basal layer of normal squamous epithelium and overexpressed in squamous cell carcinomas (SCCs). THG-1 knockdown suppressed SCC cell proliferation, invasiveness, and xenograft tumor formation. In contrast, THG-1 overexpression promoted the EGF-induced proliferation and stratified epithelium formation. Furthermore, THG-1 is phosphorylated by the receptor tyrosine kinase (RTK)-RAS-ERK pathway, which promoted the oncogene-mediated tumorigenesis. Moreover, THG-1 involves in the alternative splicing of CD44 variants, a regulator of invasiveness, stemness, and oxidative stress resistance under the RTK pathway. These findings highlight the pivotal roles of THG-1 as a novel effector of SCC tumorigenesis, and the detection of THG-1 phosphorylation by our established specific antibody could contribute to cancer diagnosis and therapy.

ColorCells: a database of expression, classification and functions of lncRNAs in single cells.

Although long noncoding RNAs (lncRNAs) have significant tissue specificity, their expression and variability in single cells remain unclear. Here, we developed ColorCells (http://rna.sysu.edu.cn/colorcells/), a resource for comparative analysis of lncRNAs expression, classification and functions in single-cell RNA-Seq data. ColorCells was applied to 167 913 publicly available scRNA-Seq datasets from six species, and identified a batch of cell-specific lncRNAs. These lncRNAs show surprising levels of expression variability between different cell clusters, and has the comparable cell classification ability as known marker genes. Cell-specific lncRNAs have been identified and further validated by in vitro experiments. We found that lncRNAs are typically co-expressed with the mRNAs in the same cell cluster, which can be used to uncover lncRNAs' functions. Our study emphasizes the need to uncover lncRNAs in all cell types and shows the power of lncRNAs as novel marker genes at single cell resolution.

Hybrid photonic deep convolutional residual spiking neural networks for text classification.

Spiking neural networks (SNNs) offer powerful computation capability due to its event-driven nature and temporal processing. However, it is still limited to shallow structure and simple tasks due to the training difficulty. In this work, we propose a deep convolutional residual spiking neural network (DCRSNN) for text classification tasks. In the DCRSNN, the feature extraction is achieved via a convolution SNN with residual connection, using the surrogate gradient direct training technique. Classification is performed by a fully-connected network. We also suggest a hybrid photonic DCRSNN, in which photonic SNNs are used for classification with a converted training method. The accuracy of hard and soft reset methods, as well as three different surrogate functions, were evaluated and compared across four different datasets. Results indicated a maximum accuracy of 76.36% for MR, 91.03% for AG News, 88.06% for IMDB and 93.99% for Yelp review polarity. Soft reset methods used in the deep convolutional SNN yielded slightly better accuracy than their hard reset counterparts. We also considered the effects of different pooling methods and observation time windows and found that the convergence accuracy achieved by convolutional SNNs was comparable to that of convolutional neural networks under the same conditions. Moreover, the hybrid photonic DCRSNN also shows comparable testing accuracy. This work provides new insights into extending the SNN applications in the field of text classification and natural language processing, which is interesting for the resources-restrained scenarios.

Nanopore Single-molecule Analysis of Biomarkers: Providing Possible Clues to Disease Diagnosis.

Biomarker detection has attracted increasing interest in recent years due to the minimally or non-invasive sampling process. Single entity analysis of biomarkers is expected to provide real-time and accurate biological information for early disease diagnosis and prognosis, which is critical to the effective disease treatment and is also important in personalized medicine. As an innovative single entity analysis method, nanopore sensing is a pioneering single-molecule detection technique that is widely used in analytical bioanalytical fields. In this review, we overview the recent progress of nanopore biomarker detection as new approaches to disease diagnosis. In highlighted studies, nanopore was focusing on detecting biomarkers of different categories of communicable and noncommunicable diseases, such as pandemic Covid-19, AIDS, cancers, neurologic diseases, etc. Various sensitive and selective nanopore detecting strategies for different types of biomarkers are summarized. In addition, the challenges, opportunities, and direction for future development of nanopore-based biomarker sensors are also discussed.

O-GlcNAcylation of TDP-43 suppresses proteinopathies and promotes TDP-43's mRNA splicing activity.

Pathological TDP-43 aggregation is characteristic of several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD-TDP); however, how TDP-43 aggregation and function are regulated remain poorly understood. Here, we show that O-GlcNAc transferase OGT-mediated O-GlcNAcylation of TDP-43 suppresses ALS-associated proteinopathies and promotes TDP-43's splicing function. Biochemical and cell-based assays indicate that OGT's catalytic activity suppresses TDP-43 aggregation and hyperphosphorylation, whereas abolishment of TDP-43 O-GlcNAcylation impairs its RNA splicing activity. We further show that TDP-43 mutations in the O-GlcNAcylation sites improve locomotion defects of larvae and adult flies and extend adult life spans, following TDP-43 overexpression in Drosophila motor neurons. We finally demonstrate that O-GlcNAcylation of TDP-43 promotes proper splicing of many mRNAs, including STMN2, which is required for normal axonal outgrowth and regeneration. Our findings suggest that O-GlcNAcylation might be a target for the treatment of TDP-43-linked pathogenesis.

Acceleration of high-quality Raman imaging via a locality enhanced transformer network.

Raman imaging (RI) is an outstanding technique that enables molecular-level medical diagnostics and therapy assessment by providing characteristic fingerprint and morphological information about molecules. However, obtaining high-quality Raman images generally requires a long acquisition time, up to hours, which is prohibitive for RI applications of timely cytopathology and histopathology analyses. To address this issue, image super-resolution (SR) based on deep learning, including convolutional neural networks and transformers, has been widely recognized as an effective solution to reduce the time required for achieving high-quality RI. In this study, a locality enhanced transformer network (LETNet) is proposed to perform Raman image SR. Specifically, the general architecture of the transformer is adopted with the replacement of self-attention by convolution to generate high-fidelity and detailed SR images. Additionally, the convolution in the LETNet is further optimized by utilizing depth-wise convolution to improve the computational efficiency of the model. Experiments on hyperspectral Raman images of breast cancer cells and Raman images of a few channels of brain tumor tissues demonstrate that the LETNet achieves superior 2×, 4×, and 8× SR with fewer parameters compared with other SR methods. Consequently, high-quality Raman images can be obtained with a significant reduction in time, ranging from 4 to 64 times. Overall, the proposed method provides a novel, efficient, and reliable solution to expedite high-quality RI and promote its application in real-time diagnosis and therapy.

Targeted Decomplexation of Metal Complexes for Efficient Metal Recovery by Ozone/Percarbonate.

Traditional methods cannot efficiently recover Cu from Cu(II)-EDTA wastewater and encounter the formation of secondary contaminants. In this study, an ozone/percarbonate (O3/SPC) process was proposed to efficiently decomplex Cu(II)-EDTA and simultaneously recover Cu. The results demonstrate that the O3/SPC process achieves 100% recovery of Cu with the corresponding kobs value of 0.103 min-1 compared with the typical •OH-based O3/H2O2 process (81.2%, 0.042 min-1). The carbonate radical anion (CO3•-) is generated from the O3/SPC process and carries out the targeted attack of amino groups of Cu(II)-EDTA for decarboxylation and deamination processes, resulting in successive cleavage of Cu-O and Cu-N bonds. In comparison, the •OH-based O3/H2O2 process is predominantly responsible for the breakage of Cu-O bonds via decarboxylation and formic acid removal. Moreover, the released Cu(II) can be transformed into stable copper precipitates by employing an endogenous precipitant (CO32-), accompanied by toxic-free byproducts in the O3/SPC process. More importantly, the O3/SPC process exhibits excellent metal recovery in the treatment of real copper electroplating wastewater and other metal-EDTA complexes. This study provides a promising technology and opens a new avenue for the efficient decomplexation of metal-organic complexes with simultaneous recovery of valuable metal resources.

Association between cadmium exposure and pulmonary function reduction: Potential mediating role of telomere attrition in chronic obstructive pulmonary disease patients.

BACKGROUND: Environmental cadmium (Cd) exposure is linked to pulmonary function injury in the general population. But, the association between blood Cd concentration and pulmonary function has not been investigated thoroughly in chronic obstructive pulmonary disease (COPD) patients, and the potential mechanisms are unclear. METHODS: All eligible 789 COPD patients were enrolled from Anhui COPD cohort. Blood specimens and clinical information were collected. Pulmonary function test was conducted. The subunit of telomerase, telomerase reverse transcriptase (TERT), was determined through enzyme linked immunosorbent assay (ELISA). Blood Cd was measured via inductively coupled-mass spectrometer (ICP-MS). RESULTS: Blood Cd was negatively and dose-dependently associated with pulmonary function. Each 1-unit increase of blood Cd was associated with 0.861 L decline in FVC, 0.648 L decline in FEV1, 5.938 % decline in FEV1/FVC %, and 22.098 % decline in FEV1 % among COPD patients, respectively. Age, current-smoking, self-cooking and higher smoking amount aggravated Cd-evoked pulmonary function decrease. Additionally, there was an inversely dose-response association between Cd concentration and TERT in COPD patients. Elevated TERT obviously mediated 29.53 %, 37.50 % and 19.48 % of Cd-evoked FVC, FEV1, and FEV1 % declines in COPD patients, respectively. CONCLUSION: Blood Cd concentration is strongly associated with the decline of pulmonary function and telomerase activity among COPD patients. Telomere attrition partially mediates Cd-induced pulmonary function decline, suggesting an underlying mechanistic role of telomere attrition in pulmonary function decline from Cd exposure in COPD patients.

Big knowledge visualization of the COVID-19 CIDO ontology evolution.

BACKGROUND: The extensive international research for medications and vaccines for the devastating COVID-19 pandemic requires a standard reference ontology. Among the current COVID-19 ontologies, the Coronavirus Infectious Disease Ontology (CIDO) is the largest one. Furthermore, it keeps growing very frequently. Researchers using CIDO as a reference ontology, need a quick update about the content added in a recent release to know how relevant the new concepts are to their research needs. Although CIDO is only a medium size ontology, it is still a large knowledge base posing a challenge for a user interested in obtaining the "big picture" of content changes between releases. Both a theoretical framework and a proper visualization are required to provide such a "big picture". METHODS: The child-of-based layout of the weighted aggregate partial-area taxonomy summarization network (WAT) provides a "big picture" convenient visualization of the content of an ontology. In this paper we address the "big picture" of content changes between two releases of an ontology. We introduce a new DIFF framework named Diff Weighted Aggregate Taxonomy (DWAT) to display the differences between the WATs of two releases of an ontology. We use a layered approach which consists first of a DWAT of major subjects in CIDO, and then drill down a major subject of interest in the top-level DWAT to obtain a DWAT of secondary subjects and even further refined layers. RESULTS: A visualization of the Diff Weighted Aggregate Taxonomy is demonstrated on the CIDO ontology. The evolution of CIDO between 2020 and 2022 is demonstrated in two perspectives. Drilling down for a DWAT of secondary subject networks is also demonstrated. We illustrate how the DWAT of CIDO provides insight into its evolution. CONCLUSIONS: The new Diff Weighted Aggregate Taxonomy enables a layered approach to view the "big picture" of the changes in the content between two releases of an ontology.

Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients.

BACKGROUND: Two years into the COVID-19 pandemic and with more than five million deaths worldwide, the healthcare establishment continues to struggle with every new wave of the pandemic resulting from a new coronavirus variant. Research has demonstrated that there are variations in the symptoms, and even in the order of symptom presentations, in COVID-19 patients infected by different SARS-CoV-2 variants (e.g., Alpha and Omicron). Textual data in the form of admission notes and physician notes in the Electronic Health Records (EHRs) is rich in information regarding the symptoms and their orders of presentation. Unstructured EHR data is often underutilized in research due to the lack of annotations that enable automatic extraction of useful information from the available extensive volumes of textual data. METHODS: We present the design of a COVID Interface Terminology (CIT), not just a generic COVID-19 terminology, but one serving a specific purpose of enabling automatic annotation of EHRs of COVID-19 patients. CIT was constructed by integrating existing COVID-related ontologies and mining additional fine granularity concepts from clinical notes. The iterative mining approach utilized the techniques of 'anchoring' and 'concatenation' to identify potential fine granularity concepts to be added to the CIT. We also tested the generalizability of our approach on a hold-out dataset and compared the annotation coverage to the coverage obtained for the dataset used to build the CIT. RESULTS: Our experiments demonstrate that this approach results in higher annotation coverage compared to existing ontologies such as SNOMED CT and Coronavirus Infectious Disease Ontology (CIDO). The final version of CIT achieved about 20% more coverage than SNOMED CT and 50% more coverage than CIDO. In the future, the concepts mined and added into CIT could be used as training data for machine learning models for mining even more concepts into CIT and further increasing the annotation coverage. CONCLUSION: In this paper, we demonstrated the construction of a COVID interface terminology that can be utilized for automatically annotating EHRs of COVID-19 patients. The techniques presented can identify frequently documented fine granularity concepts that are missing in other ontologies thereby increasing the annotation coverage.