Finding hidden semantics of text tables

Combining data from different sources for further automatic processing is often hindered by differences in the underlying semantics and representation. Therefore when linking information presented in documents in tabular form with data held in databases, it is important to determine as much information about the table and its content. Important information about the table data is often given in the text surrounding the table in that document. The table's creators cannot clarify all the semantics in the table itself therefore they use the table context or the text around it to give further information. These semantics are very useful when integrating and using this data, but are often difficult to detect automatically. We propose a solution to part of this problem based on a domain ontology. The input to our system is a document that contains tabular data and the system aims to find semantics in the document that are related to the tabular data. The output of our system is a set of detected semantics linked to the corresponding table. The system uses elements of semantic detection, semantic representation, and data integration. Semantic detection uses a domain ontology, in which we store concepts of that domain. This allows us to analyse the content of the document (text) and detect context information about the tables present in a document containing tabular data. Our approach consists of two components: (1) extract, from the domain ontology, concepts, synonyms, and relations that correspond to the table data. (2) Build a tree for the paragraphs and use this tree to detect the hidden semantics by searching for words matching the extracted concepts. Semantic representation techniques then allow representation of the detected semantics of the table data. Our system represents the detected semantics, as either 'semantic units' or 'enhanced metadata'. Semantic units are a flexible set of meta-attributes that describe the meaning of the data item along with the detected semantics. In addition, each semantic unit has a concept label associated with it that specifies the relationship between the unit and the real world aspects it describes. In the enhanced metadata, table metadata is enhanced with the semantics and representation context found in the text. Integrating data in our proposed system takes place in two steps. First, the semantic units are converted to a common context, reflecting the application. This is achieved by using appropriate conversion functions. Secondly, the semantically identical semantic units, will be identified and integrated into a common representation. This latter is the subject of future work. Thus the research has shown that semantics about a table are in the text and how it is possible to locate and use these semantics by transforming them into an appropriate form to enhance the basic table metadata

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Adefovir Dipivoxil as a Therapeutic Candidate for Medullary Thyroid Carcinoma: Targeting RET and STAT3 Proto-Oncogenes

Aberrant gene expression is often linked to the progression of various cancers, making the targeting of oncogene transcriptional activation a potential strategy to control tumor growth and development. The RET proto-oncogene’s gain-of-function mutation is a major cause of medullary thyroid carcinoma (MTC), which is part of multiple endocrine neoplasia type 2 (MEN2) syndrome. In this study, we used a cell-based bioluminescence reporter system driven by the RET promoter to screen for small molecules that potentially suppress the RET gene transcription. We identified adefovir dipivoxil as a transcriptional inhibitor of the RET gene, which suppressed endogenous RET protein expression in MTC TT cells. Adefovir dipivoxil also interfered with STAT3 phosphorylation and showed high affinity to bind to STAT3. Additionally, it inhibited RET-dependent TT cell proliferation and increased apoptosis. These results demonstrate the potential of cell-based screening assays in identifying transcriptional inhibitors for other oncogenes

Healthcare Providers’ knowledge, attitudes and practice in relation to drug hypersensitivity reactions at King Abdulaziz Medical City in Riyadh

Background: Drug hypersensitivity reactions (DHRs) are immune-mediated responses triggered by exposure to a drug. DHRs are responsible for serious adverse drug reactions (ADRs) and are considered the fifth leading cause of death. This study aims to assess and evaluate the knowledge, practice, and attitudes of healthcare providers (HCPs) towards DHRs. Methods: A cross-sectional survey was conducted at King Abdulaziz Medical City (KAMC) in Riyadh, Saudi Arabia. Healthcare providers, including pharmacists, physicians, and nurses, were recruited using a convenience sampling method to complete the survey. The survey comprised three domains: knowledge (14 items), attitudes (5 items), and practices (6 items), utilizing a standardized self-administered questionnaire. Results: The survey was completed by 373 healthcare providers. The respondents were predominantly female (72.1 %) with a mean age of 33.8 ± 7.8 years. Of the respondents, 64 % were nurses, 25 % pharmacists, and 11.3 % physicians. Educational levels varied, with 53 % holding a bachelor's degree, 22 % an associate degree, and 25 % a master's degree or higher. The median knowledge score was 48. Female healthcare providers, those with advanced levels of education, and physicians had higher knowledge scores compared to male and nurse participants (p < 0.05). One-third of the respondents (33 %) were satisfied with their knowledge of DHRs, and 42 % believed HCPs should receive more advanced training in DHR management. Less than a quarter of HCPs reported inquiring about patients' histories of hypersensitivity reactions. Conclusions: The study revealed that healthcare workers had a relatively low level of knowledge about drug hypersensitivity reactions and lacked a consensus on DHR management. While displaying a positive attitude towards DHRs, they often did not translate this attitude into consistent clinical practice

Exploring the Impact of COVID-19 Response on Population Health in Saudi Arabia: Results from the “Sharik” Health Indicators Surveillance System during 2020

Background: Although some studies have explored the effects of responses to COVID-19 on mortality, there are limited data on their effects on more immediate health risk factors and the trends of chronic diseases. Objective: To explore the prevalence of some behavioral health risk factors, intermediate risk factors, and chronic diseases at different timepoints during 2020 using the data available from a currently used surveillance system in Saudi Arabia. Methods: This study undertook a secondary analysis of data from the Sharik Health Indicators Surveillance System (SHISS). The SHISS employs short cross-sectional phone interviews, conducted in all 13 administrative regions of Saudi Arabia on a quarterly basis. Each interview lasts approximately 4 min and is conducted by a trained data collector. The SHISS collects demographic data, as well as data on the major behavioral and intermediate chronic disease risk factors and the major chronic diseases, including diabetes, heart disease, stroke, cancer, and chronic respiratory diseases. Results: Of the 44,782 potential participants contacted in 2020, 30,134 completed the interview, with a response rate of 67.29%. Out of the total participants, 51.2% were female. The mean age was 36.5. The behavioral risk factors in this period exhibited significant changes compared to those in the first quarter (Q1) of 2020, when there were no significant restrictions on daily activities. These significant changes are related to reductions in fruit and vegetable intake (adjusted odds ratio (AOR), 0.23) and physical activity (AOR, 0.483), and a significant increase in e-cigarette use (AOR 1.531). In terms of the intermediate risk factors observed in the SHISS, significant increases in hypercholesterolemia (AOR, 1.225) and hypertension (AOR, 1.190) were observed. Finally, heart disease (AOR, 1.279) and diabetes (AOR, 1.138) displayed significant increases compared to Q1. Conclusions: This study shows some evidence of the impact of responses to COVID-19 on the health of the population in Saudi Arabia. Significant reductions in fruit and vegetable intake and physical activity, and significant increases in e-cigarette use, hypertension, and hypercholesterolemia may increase the burden of chronic diseases in Saudi Arabia in the near future. Thus, continuous monitoring of the health risk factors within the population, and early interventions, are recommended to prevent future increases in chronic diseases

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

Abstract Introduction Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI’s role in clinical practice is crucial for successful implementation by equipping healthcare providers with essential knowledge and tools. Research Significance This review article provides a comprehensive and up-to-date overview of the current state of AI in clinical practice, including its potential applications in disease diagnosis, treatment recommendations, and patient engagement. It also discusses the associated challenges, covering ethical and legal considerations and the need for human expertise. By doing so, it enhances understanding of AI’s significance in healthcare and supports healthcare organizations in effectively adopting AI technologies. Materials and Methods The current investigation analyzed the use of AI in the healthcare system with a comprehensive review of relevant indexed literature, such as PubMed/Medline, Scopus, and EMBASE, with no time constraints but limited to articles published in English. The focused question explores the impact of applying AI in healthcare settings and the potential outcomes of this application. Results Integrating AI into healthcare holds excellent potential for improving disease diagnosis, treatment selection, and clinical laboratory testing. AI tools can leverage large datasets and identify patterns to surpass human performance in several healthcare aspects. AI offers increased accuracy, reduced costs, and time savings while minimizing human errors. It can revolutionize personalized medicine, optimize medication dosages, enhance population health management, establish guidelines, provide virtual health assistants, support mental health care, improve patient education, and influence patient-physician trust. Conclusion AI can be used to diagnose diseases, develop personalized treatment plans, and assist clinicians with decision-making. Rather than simply automating tasks, AI is about developing technologies that can enhance patient care across healthcare settings. However, challenges related to data privacy, bias, and the need for human expertise must be addressed for the responsible and effective implementation of AI in healthcare

Drug shortages in Saudi Arabia: Root causes and recommendations

Drug shortages are a multifaceted problem that has been recurring in Saudi Arabia over the past decade with its significant negative impact on patient care. However, there is a dearth of evidence about possible domestic reasons, if any, behind this recurring problem. Recently, the Pharmacy Education Unit at King Saud University College of Pharmacy has called for a meeting with multiple stakeholders from academia, pharmaceutical care, pharmaceutical industry, purchasing and planning, and regulatory bodies to unveil the root domestic causes of the drug shortages in the Kingdom. Four major topics were used to guide the discussion in this meeting, including: current situation of drug shortages in Saudi Arabia, major factors contributing to drug shortages, challenges and obstacles to improve drug supply, and stakeholders’ recommendations to manage drug shortages. The meeting was audio-recorded and transcribed into verbatim by five authors. The text was then reviewed and analyzed to identify different themes by the first and third authors. Multiple causes were identified and several recommendations were proposed. The main domestic causes of drug shortages that were explored in this study included poor medication supply chain management, lack of government regulation that mandates early notification of drug shortages, a government procurement policy that does not keep pace with the changes in the pharmaceutical market, low profit margins of some essential drugs, weak and ineffective law-violation penalties against pharmaceutical companies and licensed drug importers and distributors, and overdependence on drug imports. The participants have also proposed multiple recommendations to address drug shortages. Policy makers should consider these factors that contribute to drug shortages in Saudi Arabia as well as the recommendations when designing future initiatives and interventions to prevent drug shortages. Keywords: Shortage, Drugs, Patient safet

Impact of the COVID-19 pandemic on patients with paediatric cancer in low-income, middle-income and high-income countries: a multicentre, international, observational cohort study

OBJECTIVES: Paediatric cancer is a leading cause of death for children. Children in low-income and middle-income countries (LMICs) were four times more likely to die than children in high-income countries (HICs). This study aimed to test the hypothesis that the COVID-19 pandemic had affected the delivery of healthcare services worldwide, and exacerbated the disparity in paediatric cancer outcomes between LMICs and HICs. DESIGN: A multicentre, international, collaborative cohort study. SETTING: 91 hospitals and cancer centres in 39 countries providing cancer treatment to paediatric patients between March and December 2020. PARTICIPANTS: Patients were included if they were under the age of 18 years, and newly diagnosed with or undergoing active cancer treatment for Acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, Wilms' tumour, sarcoma, retinoblastoma, gliomas, medulloblastomas or neuroblastomas, in keeping with the WHO Global Initiative for Childhood Cancer. MAIN OUTCOME MEASURE: All-cause mortality at 30 days and 90 days. RESULTS: 1660 patients were recruited. 219 children had changes to their treatment due to the pandemic. Patients in LMICs were primarily affected (n=182/219, 83.1%). Relative to patients with paediatric cancer in HICs, patients with paediatric cancer in LMICs had 12.1 (95% CI 2.93 to 50.3) and 7.9 (95% CI 3.2 to 19.7) times the odds of death at 30 days and 90 days, respectively, after presentation during the COVID-19 pandemic (p<0.001). After adjusting for confounders, patients with paediatric cancer in LMICs had 15.6 (95% CI 3.7 to 65.8) times the odds of death at 30 days (p<0.001). CONCLUSIONS: The COVID-19 pandemic has affected paediatric oncology service provision. It has disproportionately affected patients in LMICs, highlighting and compounding existing disparities in healthcare systems globally that need addressing urgently. However, many patients with paediatric cancer continued to receive their normal standard of care. This speaks to the adaptability and resilience of healthcare systems and healthcare workers globally

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p