Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism

Abstract Background Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. An ontology for anti-rheumatism traditional Chinese drugs would strongly support the representation, analysis, and understanding of these drugs. Results In this study, we first systematically collected reported information about 26 traditional Chinese decoction pieces drugs, including their chemical ingredients and adverse events (AEs). By mostly reusing terms from existing ontologies (e.g., TCMDPO for traditional Chinese medicines, NCBITaxon for taxonomy, ChEBI for chemical elements, and OAE for adverse events) and making semantic axioms linking different entities, we developed the Ontology of Chinese Medicine for Rheumatism (OCMR) that includes over 3000 class terms. Our OCMR analysis found that these 26 traditional Chinese decoction pieces are made from anatomic entities (e.g., root and stem) from 3 Bilateria animals and 23 Mesangiospermae plants. Anti-inflammatory and antineoplastic roles are important for anti-rheumatism drugs. Using the total of 555 unique ChEBI chemical entities identified from these drugs, our ChEBI-based classification analysis identified 18 anti-inflammatory, 33 antineoplastic chemicals, and 9 chemicals (including 3 diterpenoids and 3 triterpenoids) having both anti-inflammatory and antineoplastic roles. Furthermore, our study detected 22 diterpenoids and 23 triterpenoids, including 16 pentacyclic triterpenoids that are likely bioactive against rheumatism. Six drugs were found to be associated with 184 unique AEs, including three AEs (i.e., dizziness, nausea and vomiting, and anorexia) each associated with 5 drugs. Several chemical entities are classified as neurotoxins (e.g., diethyl phthalate) and allergens (e.g., eugenol), which may explain the formation of some TCD AEs. The OCMR could be efficiently queried for useful information using SPARQL scripts. Conclusions The OCMR ontology was developed to systematically represent 26 traditional anti-rheumatism Chinese drugs and their related information. The OCMR analysis identified possible anti-rheumatism and AE mechanisms of these drugs. Our novel ontology-based approach can also be applied to systematic representation and analysis of other traditional Chinese drugs.https://deepblue.lib.umich.edu/bitstream/2027.42/140395/1/12918_2017_Article_510.pd

A bioinformatics potpourri

© 2018 The Author(s). The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018

Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches

Drug Safety (DS) is a domain with significant public health and social impact. Knowledge Engineering (KE) is the Computer Science discipline elaborating on methods and tools for developing “knowledge-intensive” systems, depending on a conceptual “knowledge” schema and some kind of “reasoning” process. The present systematic and mapping review aims to investigate KE-based approaches employed for DS and highlight the introduced added value as well as trends and possible gaps in the domain. Journal articles published between 2006 and 2017 were retrieved from PubMed/MEDLINE and Web of Science® (873 in total) and filtered based on a comprehensive set of inclusion/exclusion criteria. The 80 finally selected articles were reviewed on full-text, while the mapping process relied on a set of concrete criteria (concerning specific KE and DS core activities, special DS topics, employed data sources, reference ontologies/terminologies, and computational methods, etc.). The analysis results are publicly available as online interactive analytics graphs. The review clearly depicted increased use of KE approaches for DS. The collected data illustrate the use of KE for various DS aspects, such as Adverse Drug Event (ADE) information collection, detection, and assessment. Moreover, the quantified analysis of using KE for the respective DS core activities highlighted room for intensifying research on KE for ADE monitoring, prevention and reporting. Finally, the assessed use of the various data sources for DS special topics demonstrated extensive use of dominant data sources for DS surveillance, i.e., Spontaneous Reporting Systems, but also increasing interest in the use of emerging data sources, e.g., observational healthcare databases, biochemical/genetic databases, and social media. Various exemplar applications were identified with promising results, e.g., improvement in Adverse Drug Reaction (ADR) prediction, detection of drug interactions, and novel ADE profiles related with specific mechanisms of action, etc. Nevertheless, since the reviewed studies mostly concerned proof-of-concept implementations, more intense research is required to increase the maturity level that is necessary for KE approaches to reach routine DS practice. In conclusion, we argue that efficiently addressing DS data analytics and management challenges requires the introduction of high-throughput KE-based methods for effective knowledge discovery and management, resulting ultimately, in the establishment of a continuous learning DS system

Intelligent technologies for real-time monitoring and decision support systems

MPhilAutomation of data processing and control of operations involving intelligent technologies that is considered the next generation technology requires error-free data capture systems in both clinical research and healthcare. The presented research constitutes a step in the development of intelligent technologies in healthcare. The proposed improvement is by automation that includes the elements of intelligence and prediction. In particular automatic data acquisition systems for several devices are developed including pervasive computing technologies for mobility. The key feature of the system is the minimisation/near eradication of erroneous data input along with a number of other security measures ensuring completeness, accuracy and reliability of the patients‟ data. The development is based on utilising existing devices to keep the cost of Data Acquisition Systems down. However, with existing technology and devices one can be limited to features required to perform more refined analysis. Research of existing and development of a new device for assessment of neurological diseases, such as MS (Multiple Sclerosis) using Stroop test is performed. The software can also be customized for use in other diseases affecting Central Nervous System such as Parkinson‟s disease. The introduction of intelligent functions into the majority of operations enables quality checks and provides on-line user assistance. It could become a key tool in the first step of patient diagnosis before referring to more advanced tests for further investigation. Although the software cannot fully ensure the diagnosis of MS or PD but can make significant contribution in the process of diagnosis and monitorin

FAIR and bias-free network modules for mechanism-based disease redefinitions

Even though chronic diseases are the cause of 60% of all deaths around the world, the underlying causes for most of them are not fully understood. Hence, diseases are defined based on organs and symptoms, and therapies largely focus on mitigating symptoms rather than cure. This is also reflected in the most commonly used disease classifications. The complex nature of diseases, however, can be better defined in terms of networks of molecular interactions. This research applies the approaches of network medicine – a field that uses network science for identifying and treating diseases – to multiple diseases with highly unmet medical need such as stroke and hypertension. The results show the success of this approach to analyse complex disease networks and predict drug targets for different conditions, which are validated through preclinical experiments and are currently in human clinical trials

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

A mixed methods sequential explanatory study of the utilisation and practice of traditional Chinese medicine by Chinese people in Hong Kong and Guangzhou

Little is known about why traditional Chinese (TCM) continues to be used and practised by Chinese people despite the existence of evidence-based Western medicine (WM). This study aims to explore Chinese patients and TCM practitioners’ attitudes and beliefs towards the utilisation and practice of TCM and to determine if there are any differences in the way in which Chinese people use and practice TCM in different regions of China, in this study, Hong Kong and Guangzhou. A mixed-method, sequential explanatory study was undertaken that involved two phases. In the first phase, a structured questionnaire translated into Chinese was used to collect data from a convenience sample of Chinese patients attending outpatient clinics in Hong Kong and Guangzhou. A Chinese research assistant who could speak Cantonese and Mandarin distributed the questionnaires to patients attending the TCM outpatient clinics in Hong Kong and Guangzhou. Also, a random sample of Chinese medicine practitioners in Hong Kong was sent a questionnaire by post, as a list of Chinese medicine practitioners names, and clinic addresses in Hong Kong are available on the Chinese Medical Council’s Internet website. For TCM practitioners in Guangzhou, a Chinese research assistant distributed the questionnaire in-person to a random sample of TCM doctors working at the Guangzhou University of Traditional Chinese medicine in Guangzhou. In the second phase of the study, semi-structured interviews were conducted with patients and Chinese medicine practitioners in Hong Kong and patients and TCM practitioners in Guangzhou. Patients and TCM practitioners who took part in an interview were randomly selected from a list of patients and TCM practitioners who had previously filled out a questionnaire in the first phase of the study. A total of 1,200 patients and 400 TCM practitioners took part in the study, which comprised of 600 patients attending an out-patient TCM clinic in Hong Kong and 600 attending an out-patient TCM clinic in Guangzhou. The response rate for patients who took part was 81.4% (n= 505) and for Guangzhou 91.6% (n=550). For TCM practitioners, the response rate was 55% (n=110) for practitioners in Hong Kong and 61.5% (n= 123) for practitioners in Guangzhou. Patients’ mean age was 44.6 years, and the sample consisted of 41.2% males and 58.8% females. For TCM practitioners, the mean age was 45.4 years and the sample consisting of 66.1% males and 33.9% females. In the second phase of the study, semi-structured interviews were conducted with 16 patients and 16 TCM practitioners in Hong Kong and Guangzhou, respectively. The results showed that for patients in Hong Kong and Guangzhou the most common use of TCM was for the treatment of acute medical conditions, such as colds and flu and also for chronic medical conditions, such as rheumatism and diabetes. Also, patients in Guangzhou were found to use TCM to “recuperate” the body after taking Western medicines prescribed by WM doctors, or after suffering a chronic illness. Concurrent use of TCM and WM was found to be more common in patients in Guangzhou, than in patients in Hong Kong. The integration of TCM services in hospitals in Hong Kong is notably different from that of China. Unlike China, where TCM practitioners are permitted to treat in-patients inside state-run hospitals, in Hong Kong, TCM practitioners are only permitted to treat patients on an outpatient basis and not as in-patients. The results of this study contribute to the existing body of literature about the utilisation and practice of TCM by Chinese people in Hong Kong and Guangzhou. The study also provides unique information about the practice of TCM in Hong Kong since the implementation of the Chinese medicine Ordinance and the establishment of the Chinese Medicine Council of Hong Kong. Although the study contributes to the existing body of literature concerning the utilisation and practice of TCM by Chinese people and TCM practitioners ‘respectively, it does have several inherent limitations. Among the significant limitations is the fact that, as a cross-sectional survey design was used, therefore no “cause and effect” relationships can be drawn from the results. Furthermore, because statistical tests, in general, require a large sample size to ensure a representative distribution of the population being studied, the total number of patients and TCM practitioners who participated in the study is relatively small