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BackgroundCommon data models (CDMs) help standardize electronic health record data and facilitate outcome analysis for observational and longitudinal research. An analysis of pathology reports is required to establish fundamental information infrastructure for data-driven colon cancer research. The Observational Medical Outcomes Partnership (OMOP) CDM is used in distributed research networks for clinical data; however, it requires conversion of free text–based pathology reports into the CDM’s format. There are few use cases of representing cancer data in CDM. ObjectiveIn this study, we aimed to construct a CDM database of colon cancer–related pathology with natural language processing (NLP) for a research platform that can utilize both clinical and omics data. The essential text entities from the pathology reports are extracted, standardized, and converted to the OMOP CDM format in order to utilize the pathology data in cancer research. MethodsWe extracted clinical text entities, mapped them to the standard concepts in the Observational Health Data Sciences and Informatics vocabularies, and built databases and defined relations for the CDM tables. Major clinical entities were extracted through NLP on pathology reports of surgical specimens, immunohistochemical studies, and molecular studies of colon cancer patients at a tertiary general hospital in South Korea. Items were extracted from each report using regular expressions in Python. Unstructured data, such as text that does not have a pattern, were handled with expert advice by adding regular expression rules. Our own dictionary was used for normalization and standardization to deal with biomarker and gene names and other ungrammatical expressions. The extracted clinical and genetic information was mapped to the Logical Observation Identifiers Names and Codes databases and the Systematized Nomenclature of Medicine (SNOMED) standard terminologies recommended by the OMOP CDM. The database-table relationships were newly defined through SNOMED standard terminology concepts. The standardized data were inserted into the CDM tables. For evaluation, 100 reports were randomly selected and independently annotated by a medical informatics expert and a nurse. ResultsWe examined and standardized 1848 immunohistochemical study reports, 3890 molecular study reports, and 12,352 pathology reports of surgical specimens (from 2017 to 2018). The constructed and updated database contained the following extracted colorectal entities: (1) NOTE_NLP, (2) MEASUREMENT, (3) CONDITION_OCCURRENCE, (4) SPECIMEN, and (5) FACT_RELATIONSHIP of specimen with condition and measurement. ConclusionsThis study aimed to prepare CDM data for a research platform to take advantage of all omics clinical and patient data at Seoul National University Bundang Hospital for colon cancer pathology. A more sophisticated preparation of the pathology data is needed for further research on cancer genomics, and various types of text narratives are the next target for additional research on the use of data in the CDM.

Previous studies have emphasized the significance of a strong El Niño preceding La Niña (LN) in the formation of multi-year LN events due to the slow recharge-discharge ocean heat content process. However, observational analyses from 1900 to 2022 reveal that the majority (64%) of multi-year LN events did not necessitate a preceding strong El Niño to generate their second LN, suggesting an overemphasis on traditional views. Instead, here we show that a negative phase of the North Pacific Meridional Mode (PMM) during spring, when the first LN begins to decay, activates the mechanism responsible for triggering another LN and producing a multi-year event. The westward extension of the first LNs cold anomalies, which interact directly with the eastern edge of the western Pacific warm pool, is highlighted as a crucial factor in the occurrence of a negative PMM. Additionally, the PMM mechanism can create a third LN, leading to triple-dip events.

Inactivation of Capicua (CIC) or upregulation of yes-associated protein 1, YAP1, leads to broad RAS-RAF-MEK-ERK inhibitor resistance and tumor progression in multiple human cancers. Despite these shared malignant phenotypes, it remains unclear whether CIC and YAP1 are mechanistically linked. Here, we show that the ERK-regulated transcription factor CIC can directly repress YAP1 expression through non-consensus GGAAGGAA DNA-binding motifs in a proximal YAP1 regulatory element. Through binding at GGAA repeats, CIC regulates YAP1 transcriptional output in both normal and human cancer cells. Silencing YAP1 in CIC-deficient cells restores MAPK inhibitor sensitivity and suppresses tumor growth. Thus, we uncover a molecular link between the MAPK-ERK effector CIC and YAP1 in human cells and established YAP inhibition as a strategy to target CIC-deficient cancers.

Objectives: This study aimed to examine the joint effect of two core message elements -- authoritative source and argument strength -- in correction tweets to counter conspiratorial misinformation about the measles, mumps and rubella (MMR) vaccine. Design/Method: An online experiment with US residents (N = 404) was conducted in a 2 (authoritative correction sources: layperson vs US Centres for Disease Prevention and Control [CDC]) × 2 (correction argument strength: weak vs strong) design. Results: The results indicate that the correction employing strong arguments and a correction provided by the CDC heightened heuristic processing of the corrective information, which in turn increased the perceived credibility of the conspiratorial misinformation. The effect of the CDC correction on heuristic processing was heightened when it contained weak arguments. Notably, user-generated corrections with weak arguments reduced heuristic processing of the information and contributed to reducing the perceived credibility of the misinformation. Conclusion: Based on the findings, we argue that both communicator- and content-related cues jointly influence how audiences process corrective information. The current study discusses the potency of user-generated social media corrections to counter vaccine misinformation and provides practical implications for how user-generated social media correction can be utilised by health practitioners. Public health organisations should prioritise presenting corrective information in an easily understandable manner, using user-generated content that fosters a sense of connection and engagement with individuals.

Human prostate cancer can result from chromosomal rearrangements that lead to aberrant ETS gene expression. The mechanisms that lead to fusion-independent ETS factor upregulation and prostate oncogenesis remain relatively unknown. Here, we show that two neighboring transcription factors, Capicua (CIC) and ETS2 repressor factor (ERF), which are co-deleted in human prostate tumors can drive prostate oncogenesis. Concurrent CIC and ERF loss commonly occur through focal genomic deletions at chromosome 19q13.2. Mechanistically, CIC and ERF co-bind the proximal regulatory element and mutually repress the ETS transcription factor, ETV1. Targeting ETV1 in CIC and ERF-deficient prostate cancer limits tumor growth. Thus, we have uncovered a fusion-independent mode of ETS transcriptional activation defined by concurrent loss of CIC and ERF.

Using observational data and model hindcasts produced by a coupled climate model, we examine the response of the East Asian winter monsoon (EAWM) to three types of El Niño: eastern Pacific (EP) and central Pacific I (CP-I) and II (CP-II) El Niños. The observational analysis shows that all three El Niño types weaken the EAWM with varying degrees of impact. The EP El Niño has the largest weakening effect, while the CP-II El Niño has the second largest, and the CP-I El Niño has the smallest. We find that diverse El Niño types impact the EAWM by altering the responses of two anomalous anticyclones during El Niño mature winter: the western North Pacific anticyclone (WNPAC) and Kuroshio anticyclone (KAC). The WNPAC responses are controlled by the Gill response and Indian Ocean warming processes that both respond to the eastern-to-central tropical Pacific precipitation anomalies. The KAC responses are controlled by a poleward wave propagation responding to the northwestern tropical Pacific precipitation anomalies. We find that the model hindcasts significantly underestimate the weakening effect during the EP and CP-II El Niños. These underestimations are related to a model deficiency in which it produces a too-weak WNPAC response during the EP El Niño and completely misses the KAC response during both types of El Niño. The too-weak WNPAC response is caused by the model deficiency of simulating too-weak eastern-to-central tropical Pacific precipitation anomalies. The lack of KAC response arises from the unrealistic response of the model’s extratropical atmosphere to the northwestern tropical Pacific precipitation anomalies.

In the observations, El Niño events initiated by a subtropical Pacific mechanism (SP-onset El Niños) show larger uncertainty in their decay evolution patterns than those initiated by a tropical Pacific mechanism. A 2,200-year simulation of Community Earth System Model reproduces this observed feature and its SP-onset El Niños are analyzed to understand the cause of the large uncertainty. Results show that the onset location of SP-onset El Niño, which interacts with the eastern edge of the western Pacific warm pool, is a key factor controlling its decay evolution. When the onset is located east (west) of 155°E, the event has a strong tendency to reverse (maintain) its phase, leading to cyclic (multiyear) evolution. These two onset locations respectively activate Indo-Pacific and tropical-subtropical Pacific interactions to give rise to the different evolution patterns. The findings offer a potential way to predict the evolution of SP-onset El Niños using their onset locations.