Active Learning Pipeline to Identify Candidate Terms for a CDSS Ontology.

Ontology is essential for achieving health information and information technology application interoperability in the biomedical fields and beyond. Traditionally, ontology construction is carried out manually by human domain experts (HDE). Here, we explore an active learning approach to automatically identify candidate terms from publications, with manual verification later as a part of a deep learning model training and learning process. We introduce the overall architecture of the active learning pipeline and present some preliminary results. This work is a critical and complementary component in addition to manually building the ontology, especially during the long-term maintenance stage.

Challenges and Opportunities of Artificial Intelligence in CDSS and Patient Safety.

Ensuring patient safety in healthcare involves training professionals and implementing clinical decision support systems (CDSS) and health IT solutions to reduce errors and adverse events. The integration of artificial intelligence (AI) into health IT has revolutionized clinical settings by enabling real-time insights and personalized recommendations. However, the use of health IT can lead to unintended consequences that are not adequately addressed during training and implementation. These consequences can hinder the maximization of benefits and limit equitable access to healthcare. In this paper, we explore the impact of AI on CDSS and health IT, discuss the challenges in educating clinical informaticians, and aim to promote patient safety through collaboration with practitioners, researchers, and educators.

A Data Pipeline for Enhancing Quality of MAUDE-Based Studies.

The increasing use of MAUDE reports in patient safety research highlights the importance of understanding the processing and dissemination of open-access MAUDE data. However, the absence of a structured data pipeline undermines the reproducibility and transparency of studies relying on MAUDE data. In response, we conducted a comprehensive analysis of a recent study on endoscopic clips, assessing methodologies and results. We advocate for implementing an extract, transform, and load (ETL) pipeline, utilizing openFDA and integrating keyword search strategies and data visualization techniques. This approach aims to enhance the quality of MAUDE-based studies, ensuring their reproducibility and transparency. Moreover, ETL serves as a cornerstone in data engineering, enabling real-time data management and quality assurance, thus promoting the sustainability and collaboration of MAUDE-based patient safety research.

Developing a Generative AI-Powered Chatbot for Analyzing MAUDE Database.

This paper presents a chatbot that simplifies accessing and understanding the open-access records of adverse events related to medical devices in the MAUDE database. The chatbot is powered by generative AI technology, enabling count and search queries. The chatbot uses the openFDA API and GPT-4 model to interpret users' natural language queries, generate appropriate API calls, and summarize adverse event reports. The chatbot also provides a downloadable link to the original reports. The model's performance in generating accurate API calls was assessed and improved by training it with few-shot examples of query-URL pairs. Additionally, the quality of content-based summaries was evaluated by human expert ratings. This initiative is a significant step towards making patient safety data accessible, replicable, and easily manageable by a broader range of researchers.

Occurrence and emission characteristics of microplastics in agricultural surface runoff under different natural rainfall and short-term fertilizer application.

Land-based microplastics (MPs) are considered the primary source of MPs in aquatic environments, with runoff being a major pathway for their transfer from soil to surface water. However, the transportation characteristics of MPs via agricultural surface runoff remain unclear. In this study, we investigated the occurrence and emission characteristics of MPs in agricultural surface runoff under various short-term fertilizer applications and natural rainfall events using laser direct infrared imaging analysis (LDIR). MPs from fertilizers and soils co-migrated with the agricultural runoff. The abundance and concentration of MPs in runoff were 145.90 ± 22.48-2043.38 ± 89.51 items·L-1 and 39.17 ± 21.94-523.04 ± 47.85 µg·L-1, respectively. Small and low-density MPs, such as polyethylene (PE), chlorinated polyethylene (CPE), and polyurethane (PU) in film/fragment form with 20-50 µm exhibited a higher mobility. No statistical differences were observed in the distribution of runoff MPs with the application of different fertilizers. There was a significant positive relationship between runoff MP abundance and rainfall intensity. The annual emission load in this study area was 116.73 g·hm-2, indicating that the transportation of MPs via agricultural surface runoff cannot be ignored. This study is conducive to understanding the migration behavior of MPs in soil-water environments in a better manner.

α-Ketoglutarate plays an inflammatory inhibitory role by regulating scavenger receptor class a expression through N6-methyladenine methylation during sepsis.

Sepsis arises from an uncontrolled inflammatory response triggered by infection or stress, accompanied by alteration in cellular energy metabolism, and a strong correlation exists between these factors. Alpha-ketoglutarate (α-KG), an intermediate product of the TCA cycle, has the potential to modulate the inflammatory response and is considered a crucial link between energy metabolism and inflammation. The scavenger receptor (SR-A5), a significant pattern recognition receptor, assumes a vital function in anti-inflammatory reactions. In the current investigation, we have successfully illustrated the ability of α-KG to mitigate inflammatory factors in the serum of septic mice and ameliorate tissue damage. Additionally, α-KG has been shown to modulate metabolic reprogramming and macrophage polarization. Moreover, our findings indicate that the regulatory influence of α-KG on sepsis is mediated through SR-A5. We also elucidated the mechanism by which α-KG regulates SR-A5 expression and found that α-KG reduced the N6-methyladenosine level of macrophages by up-regulating the m6A demethylase ALKBH5. α-KG plays a crucial role in inhibiting inflammation by regulating SR-A5 expression through m6A demethylation during sepsis. The outcomes of this research provide valuable insights into the relationship between energy metabolism and inflammation regulation, as well as the underlying molecular regulatory mechanism.

Intuitive Data Visualization for Enhanced Patient Comprehension.

The pilot study explores how data visualization influences patient comprehension and engagement in understanding hyperlipidemia test results across diverse patient groups. Employing Gestalt theory and the Relational Information Display (RID) framework, intuitive visual tools were developed using Google Sheets, QlikView®, and Microsoft® Excel®. The survey conducted with patients used a Likert scale to evaluate six different line and bar graphs, each presenting the same LDL cholesterol data. The study emphasized the creation of graphs that were easily interpretable. The survey aimed to assess preferences for various data visualization formats. The survey results indicated that patients preferred stacked area charts, while healthcare providers favored line charts. The results highlight the importance of user-centric design and the effective application of theoretical frameworks in creating visualizations that enhance patient engagement and comprehension. The study highlights the role of tailored data visualizations in healthcare, emphasizing the need for such tools in user-centered health technology.

A User-Centered Data Visualization of Atherosclerotic Heart Disease Risk Factors.

High cholesterol levels significantly contribute to the risk of atherosclerotic cardiovascular disease (ACVD), with a notable portion of ischemic heart disease cases linked to elevated cholesterol levels. Effective graphical displays of lipid panel tests and other cardiac risk factors are crucial for quick and accurate data interpretation, enabling early intervention for individuals with hyperlipidemia. Applying design theories such as Gestalt and distributed cognitive theories is essential for creating user-centered graphical data displays in the context of cardiovascular (CV) risk factors. The proposed dashboard informed by these theories is expected to help healthcare providers better address cardiovascular disease (CVD), enhancing diagnosis, treatment, and prevention. Moreover, this approach may help alleviate clinical provider burnout, improve patient outcomes, and reduce provider stress, thus contributing to safer and more effective healthcare systems.

Enhancing MAUDE Database Utility by GPT-4 and Cause-Effect Visualization.

The MAUDE database is a valuable public resource for understanding malfunctions and adverse events related to medical devices and health IT. However, its extensive data and complex structure pose challenges. To overcome this, we have developed an automated analytical pipeline using GPT-4, a cutting-edge large language model. This pipeline is intended to efficiently extract, categorize, and visualize safety events with minimal human annotation. In our analysis of 4,459 colonoscopy reports from MAUDE (2011-2021), the events were categorized into operational, human factor, and device-related. Ishikawa diagrams visualized a subset stored in a vector database for easy retrieval and comparison through a similarity search. This innovative approach streamlines access to vital safety insights, reducing the workload on human annotators, and holds promise to enhance the utility of the MAUDE database.

Patients' Perceptions of Using Technology for Self-Reporting Cancer Medication Safety Events from Home.

Frequent transitions of care among patients with cancer increase their risks for medication safety events (MSEs). Patients and families need to become "vigilant partners" in MSE self-reporting when transitioning back home. However, limited evidence is available to guide patient and family engagement in preventing and managing MSEs. This study explored patients' perceptions of using technology for MSE self-reporting by interviewing 41 patients with breast, prostate, lung, or colorectal cancer. The findings revealed that patients with cancer perceived technology as convenient and easy to use to address urgent MSE concerns. However, the lack of access to technology and being unconfident in using technology can be barriers to using technology for MSE reporting. Personalized support is needed to facilitate patients' engagement in MSE self-reporting. Factors identified in the study will further support the user-centered design and development of technology systems that can support patients' needs and expectations for medication safety.

The role of ATP-binding cassette subfamily G member 1 in tumor progression.

BACKGROUND: ATP-binding cassette subfamily G member 1 is mostly known as a transporter for intracellular cholesterol efflux, and a number of studies indicate that ABCG1 also functions actively in tumor initiation and progression. This review aimed to provide an overall review of how ABCG1 acts in tumor progression. METHOD: A comprehensive searching about ABCG1 and tumor was conducted up to November 2023 using proper keywords through databases including PubMed and Web of Science. RESULT: Overall, ABCG1 plays a crucial role in the development of multiple tumorigenesis. ABCG1 enhances tumor-promoting ability through conferring stem-like properties to cancer cells and mediates chemoresistance in multiple cancers. Additionally, ABCG1 may act as a kinase to phosphorylate downstream molecules and induces tumor growth. In tumor microenvironment, ABCG1 plays a substantial role in immunity response through macrophages to create a tumor-favoring circumstance. CONCLUSION: High expression of ABCG1 is usually associated with poor prognosis, which means ABCG1 may be a potential biomarker for early diagnosis and prognosis of various cancers. ABCG1-targeted therapy may provide a novel treatment for cancer patients.

The relationship between medication beliefs, patient activation, and self-rated health in patients taking oral anticancer agents.

PURPOSE: Patients on oral anticancer agent (OAA) therapies have the autonomy to manage their cancer treatments in home settings. However, patients may not have adequate knowledge, confidence, or ability to effectively manage OAA-related consequences, which can significantly impact their treatment and health outcomes. This study aims to identify the associations between medication beliefs, patient activation, and self-rated health (SRH) among oncology patients taking OAAs and explore the potential mediation effects of patient activation on the relationship between medication beliefs and SRH. METHODS: A secondary data analysis was conducted on cross-sectional data from 114 patients who were diagnosed with breast, colorectal, lung, or prostate cancer. Patients completed a self-reported survey including items of SRH, Beliefs about Medicines Questionnaire (BMQ), and Patient Activation Measure (PAM-13). Descriptive statistics, bivariate correlation, hierarchical multiple linear regression, and mediation analysis were conducted. RESULTS: The results indicate that patients taking OAAs have ambivalent attitudes toward medication. Both medication necessity (r = - 0.27) and concerns (r = - 0.21) were negatively associated with SRH, while patient activation was positively associated with SRH (r = 0.38). Patient activation had a negative association with medication concerns (r = - 0.36) and fully mediated the relationship between medication concerns and SRH in patients taking OAAs (indirect effect = - 0.154, 95% confidence interval, - 0.276 to - 0.060). CONCLUSION: The findings highlight the significance of activating patients to better understand and manage their OAAs. It is crucial for oncology professionals to provide multifaceted interventions to promote patient activation with an effort to mitigate the negative impact of medication beliefs on patient-perceived health outcomes.

Linking artificial sweetener intake with kidney function: insights from NHANES 2003-2006 and findings from Mendelian randomization research.

Background: The current investigation examines the association between artificial sweetener (AS) consumption and the likelihood of developing chronic kidney disease (CKD), along with its impact on kidney function. Methods: We utilized data from the National Health and Nutrition Examination Survey from 2003-2006 to conduct covariance analysis and weighted adjusted logistic regression, aiming to assess the association between artificial sweetener intake and CKD risk, as well as kidney function indicators. Subsequently, we employed Mendelian randomization methods to validate the causal relationship between the intake of artificial sweeteners, CKD risk, and kidney function indicators. Instrumental variable analysis using inverse-variance weighting and Robust adjusted profile score were the primary analytical methods employed. Results: A total of 20,470 participants were included in the study, with 1,257 participants ultimately included in the analysis. In all adjusted logistic regression models, no significant association was found between the intake of artificial sweeteners and CKD risk. Similarly, the summary odds ratios (OR) for each unit change in genetically predicted CKD risk were 2.14 (95% CI: 0.83, 5.21, p = 0.092), 1.41 (95% CI: 0.54, 3.63, p = 0.482), and 1.50 (95% CI: 0.50, 4.52, p = 0.468) for the impact of artificial sweeteners added to cereals, tea, and coffee, respectively. It was only observed that adding artificial sweeteners to coffee was associated with a modest reduction in urinary albumin-to-creatinine ratio (OR = 0.94, 95% CI: -0.108, -0.022, p = 0.003), the effect appeared to be relatively small and may not directly impact the individual level. Conclusion: Our study does not support a causal relationship between artificial sweetener intake and the risk of CKD. However, due to the limitations and potential confounding factors, these findings need to be further validated through larger sample sizes in observational studies and Mendelian randomization analyses.

High-density genetic map construction and QTL mapping of a zigzag-shaped stem trait in tea plant (Camellia sinensis).

The highly unique zigzag-shaped stem phenotype in tea plants boasts significant ornamental value and is exceptionally rare. To investigate the genetic mechanism behind this trait, we developed BC1 artificial hybrid populations. Our genetic analysis revealed the zigzag-shaped trait as a qualitative trait. Utilizing whole-genome resequencing, we constructed a high-density genetic map from the BC1 population, incorporating 5,250 SNP markers across 15 linkage groups, covering 3,328.51 cM with an average marker interval distance of 0.68 cM. A quantitative trait locus (QTL) for the zigzag-shaped trait was identified on chromosome 4, within a 61.2 to 97.2 Mb range, accounting for a phenotypic variation explained (PVE) value of 13.62%. Within this QTL, six candidate genes were pinpointed. To better understand their roles, we analyzed gene expression in various tissues and individuals with erect and zigzag-shaped stems. The results implicated CsXTH (CSS0035625) and CsCIPK14 (CSS0044366) as potential key contributors to the zigzag-shaped stem formation. These discoveries lay a robust foundation for future functional genetic mapping and tea plant genetic enhancement.

Oncology patients' willingness to report their medication safety concerns from home: a qualitative study.

PURPOSE: Oncology patients often struggle to manage their medications and related adverse events during transitions of care. They are expected to take an active role in self-monitoring and timely reporting of their medication safety events or concerns to clinicians. The purpose of this study was to explore the factors influencing oncology patients' willingness to report adverse events or concerns related to their medication after their transitions back home. METHODS: A qualitative interview study was conducted with adult patients with breast, prostate, lung, or colorectal cancer who experienced care transitions within the previous year. A semi-structured interview guide was developed to understand patients' perceptions of reporting mediation-related safety events or concerns from home. All interviews were conducted via phone calls, recorded, and transcribed for thematic data analysis. RESULTS: A total of 41 individuals participated in the interviews. Three main themes and six subthemes emerged, including patients' perceived relationship with clinicians (the quality of communication and trust in clinicians), perceived severity of adverse medication events (perceived severe vs. non-severe events), and patient activation in self-management (self-efficacy in self-management and engagement in monitoring health outcomes). CONCLUSION: The patient-clinician relationship significantly affects patients' reporting behaviors, which can potentially interact with other factors, including the severity of adverse events. It is important to engage oncology patients in medication safety self-reporting from home by enhancing health communication, understanding patients' perceptions of severe events, and promoting patient activation. By addressing these efforts, healthcare providers should adopt a more patient-centered approach to enhance the overall quality and safety of oncological care.

Bulked Segregant RNA-Seq Reveals Different Gene Expression Patterns and Mutant Genes Associated with the Zigzag Pattern of Tea Plants (Camellia sinensis).

The unique zigzag-patterned tea plant is a rare germplasm resource. However, the molecular mechanism behind the formation of zigzag stems remains unclear. To address this, a BC1 genetic population of tea plants with zigzag stems was studied using histological observation and bulked segregant RNA-seq. The analysis revealed 1494 differentially expressed genes (DEGs) between the upright and zigzag stem groups. These DEGs may regulate the transduction and biosynthesis of plant hormones, and the effects on the phenylpropane biosynthesis pathways may cause the accumulation of lignin. Tissue sections further supported this finding, showing differences in cell wall thickness between upright and curved stems, potentially due to lignin accumulation. Additionally, 262 single-nucleotide polymorphisms (SNPs) across 38 genes were identified as key SNPs, and 5 genes related to zigzag stems were identified through homologous gene function annotation. Mutations in these genes may impact auxin distribution and content, resulting in the asymmetric development of vascular bundles in curved stems. In summary, we identified the key genes associated with the tortuous phenotype by using BSR-seq on a BC1 population to minimize genetic background noise.

Assessing the Reproducibility of Research Based on the Food and Drug Administration Manufacturer and User Facility Device Experience Data.

OBJECTIVE: This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes. METHODS: Studies using MAUDE data were sourced from PubMed by searching for "MAUDE" or "Manufacturer and User Facility Device Experience" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow. RESULTS: As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107). CONCLUSIONS: Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.

The Acceptance and Use of Digital Technologies for Self-Reporting Medication Safety Events After Care Transitions to Home in Patients With Cancer: Survey Study.

BACKGROUND: Actively engaging patients with cancer and their families in monitoring and reporting medication safety events during care transitions is indispensable for achieving optimal patient safety outcomes. However, existing patient self-reporting systems often cannot address patients' various experiences and concerns regarding medication safety over time. In addition, these systems are usually not designed for patients' just-in-time reporting. There is a significant knowledge gap in understanding the nature, scope, and causes of medication safety events after patients' transition back home because of a lack of patient engagement in self-monitoring and reporting of safety events. The challenges for patients with cancer in adopting digital technologies and engaging in self-reporting medication safety events during transitions of care have not been fully understood. OBJECTIVE: We aim to assess oncology patients' perceptions of medication and communication safety during care transitions and their willingness to use digital technologies for self-reporting medication safety events and to identify factors associated with their technology acceptance. METHODS: A cross-sectional survey study was conducted with adult patients with breast, prostate, lung, or colorectal cancer (N=204) who had experienced care transitions from hospitals or clinics to home in the past 1 year. Surveys were conducted via phone, the internet, or email between December 2021 and August 2022. Participants' perceptions of medication and communication safety and perceived usefulness, ease of use, attitude toward use, and intention to use a technology system to report their medication safety events from home were assessed as outcomes. Potential personal, clinical, and psychosocial factors were analyzed for their associations with participants' technology acceptance through bivariate correlation analyses and multiple logistic regressions. RESULTS: Participants reported strong perceptions of medication and communication safety, positively correlated with medication self-management ability and patient activation. Although most participants perceived a medication safety self-reporting system as useful (158/204, 77.5%) and easy to use (157/204, 77%), had a positive attitude toward use (162/204, 79.4%), and were willing to use such a system (129/204, 63.2%), their technology acceptance was associated with their activation levels (odds ratio [OR] 1.83, 95% CI 1.12-2.98), their perceptions of communication safety (OR 1.64, 95% CI 1.08-2.47), and whether they could receive feedback after self-reporting (OR 3.27, 95% CI 1.37-7.78). CONCLUSIONS: In general, oncology patients were willing to use digital technologies to report their medication events after care transitions back home because of their high concerns regarding medication safety. As informed and activated patients are more likely to have the knowledge and capability to initiate and engage in self-reporting, developing a patient-centered reporting system to empower patients and their families and facilitate safety health communications will help oncology patients in addressing their medication safety concerns, meeting their care needs, and holding promise to improve the quality of cancer care.

User-Centered Data Display for Clinicians to Diagnose and Manage Hypertension.

The accurate diagnosis and effective treatment of hypertension are hindered by challenges stemming from limited access to comprehensive blood pressure (BP) data and the need for clinical context surrounding BP readings. Using handwritten tables for home-monitored BP exacerbates issues related to integration of electronic health records (EHRs) and trend analysis. This study employs user-centered design principles to develop prototypes for BP data visualization, with the primary goal of harmonizing disparate BP data sources to empower clinicians in precise hypertension diagnosis and management.