ABSTRACT
The fast development of today's healthcare and the need to extract new medical knowledge from exponentially-growing volumes of standardized Electronic Health Records data, as required by studies in Precision Medicine, brings up a challenge that may probably only be addressed using NoSQL DBMSs, due to the non-optimal performance of traditional relational DBMSs on standardized data; and these database systems operated by semantic archetype-based query languages, because of the expected generalized extension of standardized EHR systems. An AQL into MongoDB interpreter has been developed to its first version. It translates system-independent AQL queries posed on ISO/EN 13606 standardized EHR extracts into the NoSQL MongoDB query language. The new interpreter has the advantages of both the archetype-based system-independent AQL queries and the dual-model-based standardized EHR extracts stored on document-centric NoSQL DBMSs, such as MongoDB. AQL queries are independent of applications, programming languages and system environments due to the use of the dual model, but EHR extracts featuring this model are best persisted on document-based NoSQL databases. Consequently, the interpreter allows us to query standardized EHR extracts semantically, and also affording optimal performance.
Subject(s)
Database Management Systems , Electronic Health Records , Information Storage and Retrieval , Programming Languages , SoftwareABSTRACT
BACKGROUND: The use of wearable tools for health self-quantification (SQ) introduces new ways of thinking about one's body and about how to achieve desired health outcomes. Measurements from individuals, such as heart rate, respiratory volume, skin temperature, sleep, mood, blood pressure, food consumed, and quality of surrounding air can be acquired, quantified, and aggregated in a holistic way that has never been possible before. However, health SQ still lacks a formal common language or taxonomy for describing these kinds of measurements. Establishing such taxonomy is important because it would enable systematic investigations that are needed to advance in the use of wearable tools in health self-care. For a start, a taxonomy would help to improve the accuracy of database searching when doing systematic reviews and meta-analyses in this field. Overall, more systematic research would contribute to build evidence of sufficient quality to determine whether and how health SQ is a worthwhile health care paradigm. OBJECTIVE: The aim of this study was to investigate a sample of SQ tools and services to build and test a taxonomy of measurements in health SQ, titled: the classification of data and activity in self-quantification systems (CDA-SQS). METHODS: Eight health SQ tools and services were selected to be examined: Zeo Sleep Manager, Fitbit Ultra, Fitlinxx Actipressure, MoodPanda, iBGStar, Sensaris Senspod, 23andMe, and uBiome. An open coding analytical approach was used to find all the themes related to the research aim. RESULTS: This study distinguished three types of measurements in health SQ: body structures and functions, body actions and activities, and around the body. CONCLUSIONS: The CDA-SQS classification should be applicable to align health SQ measurement data from people with many different health objectives, health states, and health conditions. CDA-SQS is a critical contribution to a much more consistent way of studying health SQ.
Subject(s)
Classification/methods , Delivery of Health Care/methods , Humans , Self CareABSTRACT
BACKGROUND: Self-quantification (SQ) is a way of working in which, by using tracking tools, people aim to collect, manage, and reflect on personal health data to gain a better understanding of their own body, health behavior, and interaction with the world around them. However, health SQ lacks a formal framework for describing the self-quantifiers' activities and their contextual components or constructs to pursue these health related goals. Establishing such framework is important because it is the first step to operationalize health SQ fully. This may in turn help to achieve the aims of health professionals and researchers who seek to make or study changes in the self-quantifiers' health systematically. OBJECTIVE: The aim of this study was to review studies on health SQ in order to answer the following questions: What are the general features of the work and the particular activities that self-quantifiers perform to achieve their health objectives? What constructs of health SQ have been identified in the scientific literature? How have these studies described such constructs? How would it be possible to model these constructs theoretically to characterize the work of health SQ? METHODS: A systematic review of peer-reviewed literature was conducted. A total of 26 empirical studies were included. The content of these studies was thematically analyzed using Activity Theory as an organizing framework. RESULTS: The literature provided varying descriptions of health SQ as data-driven and objective-oriented work mediated by SQ tools. From the literature, we identified two types of SQ work: work on data (ie, data management activities) and work with data (ie, health management activities). Using Activity Theory, these activities could be characterized into 6 constructs: users, tracking tools, health objectives, division of work, community or group setting, and SQ plan and rules. We could not find a reference to any single study that accounted for all these activities and constructs of health SQ activity. CONCLUSIONS: A Health Self-Quantification Activity Framework is presented, which shows SQ tool use in context, in relation to the goals, plans, and competence of the user. This makes it easier to analyze issues affecting SQ activity, and thereby makes it more feasible to address them. This review makes two significant contributions to research in this field: it explores health SQ work and its constructs thoroughly and it adapts Activity Theory to describe health SQ activity systematically.
Subject(s)
Activities of Daily Living/classification , Health Behavior , Female , Humans , Male , Models, TheoreticalABSTRACT
BACKGROUND: Patient-reported outcomes (PROs) from social media use in chronic disease management continue to emerge. While many published articles suggest the potential for social media is positive, there is a lack of robust examination into mediating mechanisms that might help explain social media's therapeutic value. This study presents findings from a global online survey of people with chronic pain (PWCP) to better understand how they use social media as part of self-management. OBJECTIVE: Our aim is to improve understanding of the various health outcomes reported by PWCP by paying close attention to therapeutic affordances of social media. We wish to examine if demographics of participants underpin health outcomes and whether the concept of therapeutic affordances explains links between social media use and PROs. The goal is for this to help tailor future recommendations for use of social media to meet individuals' health needs and improve clinical practice of social media use. METHODS: A total of 231 PWCP took part in a global online survey investigating PROs from social media use. Recruited through various chronic disease entities and social networks, participants provided information on demographics, health/pain status, social media use, therapeutic affordances, and PROs from use. Quantitative analysis was performed on the data using descriptive statistics, cross-tabulation, and cluster analysis. RESULTS: The total dataset represented 218 completed surveys. The majority of participants were university educated (67.0%, 146/218) and female (83.9%, 183/218). More than half (58.7%, 128/218) were married/partnered and not working for pay (75.9%, 88/116 of these due to ill health). Fibromyalgia (46.6%, 55/118) and arthritis (27.1%, 32/118) were the most commonly reported conditions causing pain. Participants showed a clear affinity for social network site use (90.0%, 189/210), followed by discussion forums and blogs. PROs were consistent, suggesting that social media positively impact psychological, social, and cognitive health. Analysis also highlighted two strong correlations linking platform used and health outcomes (particularly psychological, social, and cognitive) to (1) the narrative affordance of social media and (2) frequency of use of the platforms. CONCLUSIONS: Results did not uncover definitive demographics or characteristics of PWCP for which health outcomes are impacted. However, findings corroborate literature within this domain suggesting that there is a typical profile of people who use social media for health and that social media are more suited to particular health outcomes. Exploration of the relationship between social media's therapeutic affordances and health outcomes, in particular the narration affordance, warrants further attention by patients and clinicians.
Subject(s)
Attitude to Health , Chronic Pain/therapy , Health Status , Social Media , Adult , Blogging , Disease Management , Female , Humans , Internet , Male , Patient Outcome Assessment , Self Care/methods , Social NetworkingABSTRACT
BACKGROUND: Research continues to present tenuous suggestions that social media is well suited to enhance management of chronic disease and improve health outcomes. Various studies have presented qualitative reports of health outcomes from social media use and have examined discourse and communication themes occurring through different social media. However, there is an absence of published studies examining and unpacking the underlying therapeutic mechanisms driving social media's effects. OBJECTIVE: This paper presents a qualitative analysis thoroughly describing what social media therapeutically affords people living with chronic pain who are self-managing their condition. From this therapeutic affordance perspective, we aim to formulate a preliminary conceptual model aimed at better understanding "how" social media can influence patient outcomes. METHODS: In total, 218 people with chronic pain (PWCP) completed an online survey, investigating patient-reported outcomes (PROs) from social media use. Supplementary to quantitative data collected, participants were also given the opportunity to provide further open commentary regarding their use of social media as part of chronic pain management; 68/218 unique users (31.2%) chose to provide these free-text responses. Through thematic content analysis, 117 free-text responses regarding 10 types of social media were coded. Quotes were extracted and tabulated based on therapeutic affordances that we had previously identified. Inductive analysis was then performed to code defining language and emergent themes central to describing each affordance. Three investigators examined the responses, developed the coding scheme, and applied the coding to the data. RESULTS: We extracted 155 quotes from 117 free-text responses. The largest source of quotes came from social network site users (78/155, 50.3%). Analysis of component language used to describe the aforementioned affordances and emergent themes resulted in a final revision and renaming of therapeutic affordances: "exploration" (52/155, 33.5% of quotes), "connection" (50/155, 32.3% of quotes), "narration" (33/155, 21.3% of quotes), "adaptation" (13/155, 8.4% of quotes), and "self-presentation" (7/155, 4.5% of quotes). Of the most described affordances, "exploration" was based on a propensity for participants to explain their social media use for information seeking purposes. "Connection" placed greater emphasis on interaction, highlighting themes of "exchanging information" and "mitigating isolation". Responses regarding "narration" highlighted the value of shared experiences and the emotionally cathartic role this plays. CONCLUSIONS: Much of the efficacy of social media may be explicable via a closer examination of therapeutic affordances. Particular areas that warrant attention include social media's ability to filter and guide people to useful information, connect individuals, and share experiences. Further research into a variety of chronic conditions is warranted. Coupled with the results of the present study, a greater theoretical basis detailing how social media may foster health outcomes may lead to an improved evidence base for conducting research and may inform recommendations for social media use in chronic disease management.
Subject(s)
Chronic Pain/therapy , Social Media , Adolescent , Adult , Chronic Disease , Data Collection , Disease Management , Female , Humans , Internet , Male , Middle Aged , Self Care , Young AdultABSTRACT
The application of digital interventions in healthcare beyond research has been translated in the development of software as a medical device. Along with corresponding regulations for medical devices, there is a need for assessing adverse events to conduct post-market surveillance and to appropriately label digital health interventions to ensure proper use and patient safety. To date unexpected consequences of digital health interventions are neglected or ignored, or at least remain undescribed in literature. This paper is intended to raise awareness across the research community about these upcoming challenges. We recommend that - together with developing a new research field of digitalovigilance - a systematic assessment and monitoring of adverse events and unexpected interactions be included in clinical trials, along with the reporting of such events and the conduct of meta-analyses on critical aspects.
Subject(s)
Digital Health , Health Facilities , Humans , Patient Safety , SoftwareABSTRACT
Whilst the future for social media in chronic disease management appears to be optimistic, there is limited concrete evidence indicating whether and how social media use significantly improves patient outcomes. This review examines the health outcomes and related effects of using social media, while also exploring the unique affordances underpinning these effects. Few studies have investigated social media's potential in chronic disease, but those we found indicate impact on health status and other effects are positive, with none indicating adverse events. Benefits have been reported for psychosocial management via the ability to foster support and share information; however, there is less evidence of benefits for physical condition management. We found that studies covered a very limited range of social media platforms and that there is an ongoing propensity towards reporting investigations of earlier social platforms, such as online support groups (OSG), discussion forums and message boards. Finally, it is hypothesized that for social media to form a more meaningful part of effective chronic disease management, interventions need to be tailored to the individualized needs of sufferers. The particular affordances of social media that appear salient in this regard from analysis of the literature include: identity, flexibility, structure, narration and adaptation. This review suggests further research of high methodological quality is required to investigate the affordances of social media and how these can best serve chronic disease sufferers. Evidence-based practice (EBP) using social media may then be considered.
Subject(s)
Disease Management , Social Media , Chronic Disease , Humans , InternetABSTRACT
OBJECTIVE: The European Health Data Space (EHDS) aims to provide better exchange and expand access to health data across Europe. In this way, the EHDS will support healthcare delivery (known as the "primary use of data") and facilitate access to health data for research and policy-making purposes (known as the "secondary use of data"). To achieve this goal, we need to build the required ecosystem of the EHDS with all healthcare stakeholders. MATERIALS AND METHODS: We conducted a survey research study to explore the health informaticians' recommendations on future health data scenarios shaping the EHDS ecosystem. We created an anonymous- online questionnaire and disseminated it through wide international networks of health informaticians. In addition, we conducted a workshop during the Medical Informatics Europe Conference (MIE2022) and invited the attendees to complete the questionnaire during the workshop. RESULTS: We received 43 responses to our questionnaire from 15 European Union (EU) countries and 7 non-EU countries. Most respondents described the current health data scenario in their countries as a traditional healthcare system with moderate growth (25.6 %, n = 11). The second selected scenario was the reinventing healthcare scenario in a data-driven one-world framework (23.3 %, n = 10). DISCUSSION: The results of this work are matched with the findings of the recently published study on digital health implementation in the EU (conducted by the French government in April 2022). This also reflects the current ongoing efforts in the EU countries to deploy national infrastructure for health data management, exchange, and sharing. CONCLUSIONS: Upon the respondents' recommendations, there is a strong need to support the health democratization scenarios in Europe, as the main driver for building the EHDS ecosystem.
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Delivery of Health Care , Ecosystem , Humans , European Union , Europe , Policy MakingABSTRACT
[This corrects the article DOI: 10.2196/43656.].
ABSTRACT
BACKGROUND: Personalized precision medicine represents a paradigm shift and a new reality for the health care system in Spain, with training being fundamental for its full implementation and application in clinical practice. In this sense, health care professionals face educational challenges related to the acquisition of competencies to perform their professional practice optimally and efficiently in this new environment. The definition of competencies for health care professionals provides a clear guide on the level of knowledge, skills, and attitudes required to adequately carry out their professional practice. In this context, this acquisition of competencies by health care professionals can be defined as a dynamic and longitudinal process by which they use knowledge, skills, attitudes, and good judgment associated with their profession to develop it effectively in all situations corresponding to their field of practice. OBJECTIVE: This report aims to define a proposal of essential knowledge domains and common competencies for all health care professionals, which are necessary to optimally develop their professional practice within the field of personalized precision medicine as a fundamental part of the medicine of the future. METHODS: Based on a benchmark analysis and the input and expertise provided by a multidisciplinary group of experts through interviews and workshops, a new competency framework that would guarantee the optimal performance of health care professionals was defined. As a basis for the development of this report, the most relevant national and international competency frameworks and training programs were analyzed to identify aspects that are having an impact on the application of personalized precision medicine and will be considered when developing professional competencies in the future. RESULTS: This report defines a framework made up of 58 competencies structured into 5 essential domains: determinants of health, biomedical informatics, practical applications, participatory health, and bioethics, along with a cross-cutting domain that impacts the overall performance of the competencies linked to each of the above domains. Likewise, 6 professional profiles to which this proposal of a competency framework is addressed were identified according to the area where they carry out their professional activity: health care, laboratory, digital health, community health, research, and management and planning. In addition, a classification is proposed by progressive levels of training that would be advisable to acquire for each competency according to the professional profile. CONCLUSIONS: This competency framework characterizes the knowledge, skills, and attitudes required by health care professionals for the practice of personalized precision medicine. Additionally, a classification by progressive levels of training is proposed for the 6 professional profiles identified according to their professional roles.
ABSTRACT
BACKGROUND: Health care has evolved to support the involvement of individuals in decision making by, for example, using mobile apps and wearables that may help empower people to actively participate in their treatment and health monitoring. While the term "participatory health informatics" (PHI) has emerged in literature to describe these activities, along with the use of social media for health purposes, the scope of the research field of PHI is not yet well defined. OBJECTIVE: This article proposes a preliminary definition of PHI and defines the scope of the field. METHODS: We used an adapted Delphi study design to gain consensus from participants on a definition developed from a previous review of literature. From the literature we derived a set of attributes describing PHI as comprising 18 characteristics, 14 aims, and 4 relations. We invited researchers, health professionals, and health informaticians to score these characteristics and aims of PHI and their relations to other fields over three survey rounds. In the first round participants were able to offer additional attributes for voting. RESULTS: The first round had 44 participants, with 28 participants participating in all three rounds. These 28 participants were gender-balanced and comprised participants from industry, academia, and health sectors from all continents. Consensus was reached on 16 characteristics, 9 aims, and 6 related fields. DISCUSSION: The consensus reached on attributes of PHI describe PHI as a multidisciplinary field that uses information technology and delivers tools with a focus on individual-centered care. It studies various effects of the use of such tools and technology. Its aims address the individuals in the role of patients, but also the health of a society as a whole. There are relationships to the fields of health informatics, digital health, medical informatics, and consumer health informatics. CONCLUSION: We have proposed a preliminary definition, aims, and relationships of PHI based on literature and expert consensus. These can begin to be used to support development of research priorities and outcomes measurements.
Subject(s)
Delivery of Health Care , Medical Informatics , Humans , Delphi Technique , Consensus , Surveys and QuestionnairesABSTRACT
BACKGROUND: The purpose of educational recommendations is to assist in establishing courses and programs in a discipline, to further develop existing educational activities in the various nations, and to support international initiatives for collaboration and sharing of courseware. The International Medical Informatics Association (IMIA) has published two versions of its international recommendations in biomedical and health informatics (BMHI) education, initially in 2000 and revised in 2010. Given the recent changes to the science, technology, the needs of the healthcare systems, and the workforce of BMHI, a revision of the recommendations is necessary. OBJECTIVE: The aim of these updated recommendations is to support educators in developing BMHI curricula at different education levels, to identify essential skills and competencies for certification of healthcare professionals and those working in the field of BMHI, to provide a tool for evaluators of academic BMHI programs to compare and accredit the quality of delivered programs, and to motivate universities, organizations, and health authorities to recognize the need for establishing and further developing BMHI educational programs. METHOD: An IMIA taskforce, established in 2017, updated the recommendations. The taskforce included representatives from all IMIA regions, with several having been involved in the development of the previous version. Workshops were held at different IMIA conferences, and an international Delphi study was performed to collect expert input on new and revised competencies. RESULTS: Recommendations are provided for courses/course tracks in BMHI as part of educational programs in biomedical and health sciences, health information management, and informatics/computer science, as well as for dedicated programs in BMHI (leading to bachelor's, master's, or doctoral degree). The educational needs are described for the roles of BMHI user, BMHI generalist, and BMHI specialist across six domain areas - BMHI core principles; health sciences and services; computer, data and information sciences; social and behavioral sciences; management science; and BMHI specialization. Furthermore, recommendations are provided for dedicated educational programs in BMHI at the level of bachelor's, master's, and doctoral degrees. These are the mainstream academic programs in BMHI. In addition, recommendations for continuing education, certification, and accreditation procedures are provided. CONCLUSION: The IMIA recommendations reflect societal changes related to globalization, digitalization, and digital transformation in general and in healthcare specifically, and center on educational needs for the healthcare workforce, computer scientists, and decision makers to acquire BMHI knowledge and skills at various levels. To support education in BMHI, IMIA offers accreditation of quality BMHI education programs. It supports information exchange on programs and courses in BMHI through its Working Group on Health and Medical Informatics Education.
Subject(s)
Education, Medical , Medical Informatics , Humans , Curriculum , Educational Status , Health EducationABSTRACT
BACKGROUND: Colon cancer patients with the same stage show diverse clinical behavior due to tumor heterogeneity. We aimed to discover distinct classes of tumors based on microarray expression patterns, to analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters and to study differences in the survival. METHODS: Hierarchical clustering was performed for class discovery in 88 colon tumors (stages I to IV). Pathways analysis and correlations between clinical parameters and our classification were analyzed. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the main subtype was generated using the 3-Nearest-Neighbor method. Coincidences with other prognostic predictors were assesed. RESULTS: Hierarchical clustering identified four robust tumor subtypes with biologically and clinically distinct behavior. Stromal components (p < 0.001), nuclear ß-catenin (p = 0.021), mucinous histology (p = 0.001), microsatellite-instability (p = 0.039) and BRAF mutations (p < 0.001) were associated to this classification but it was independent of Dukes stages (p = 0.646). Molecular subtypes were established from stage I. High-stroma-subtype showed increased levels of genes and altered pathways distinctive of tumour-associated-stroma and components of the extracellular matrix in contrast to Low-stroma-subtype. Mucinous-subtype was reflected by the increased expression of trefoil factors and mucins as well as by a higher proportion of MSI and BRAF mutations. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the Low-stroma-subtype distinguished low risk patients from high risk patients in the external cohort (Dukes B and C:HR = 8.56(2.53-29.01); Dukes B,C and D:HR = 1.87(1.07-3.25)). Eight different reported survival gene signatures segregated our tumors into two groups the Low-stroma-subtype and the other tumor subtypes. CONCLUSIONS: We have identified novel molecular subtypes in colon cancer with distinct biological and clinical behavior that are established from the initiation of the tumor. Tumor microenvironment is important for the classification and for the malignant power of the tumor. Differential gene sets and biological pathways characterize each tumor subtype reflecting underlying mechanisms of carcinogenesis that may be used for the selection of targeted therapeutic procedures. This classification may contribute to an improvement in the management of the patients with CRC and to a more comprehensive prognosis.
Subject(s)
Adenocarcinoma, Mucinous/metabolism , Colonic Neoplasms/metabolism , Stromal Cells/metabolism , Adenocarcinoma, Mucinous/classification , Adenocarcinoma, Mucinous/pathology , Adult , Aged , Aged, 80 and over , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Colonic Neoplasms/classification , Colonic Neoplasms/pathology , Female , Gene Expression Profiling , Humans , Immunohistochemistry , Kaplan-Meier Estimate , Male , Middle Aged , Mucins/metabolism , Protein Array Analysis , Tumor Microenvironment/physiologyABSTRACT
BACKGROUND: Severe disease caused by 2009 pandemic influenza A/H1N1virus is characterized by the presence of hypercytokinemia. The origin of the exacerbated cytokine response is unclear. As observed previously, uncontrolled influenza virus replication could strongly influence cytokine production. The objective of the present study was to evaluate the relationship between host cytokine responses and viral levels in pandemic influenza critically ill patients. METHODS: Twenty three patients admitted to the ICU with primary viral pneumonia were included in this study. A quantitative PCR based method targeting the M1 influenza gene was developed to quantify pharyngeal viral load. In addition, by using a multiplex based assay, we systematically evaluated host cytokine responses to the viral infection at admission to the ICU. Correlation studies between cytokine levels and viral load were done by calculating the Spearman correlation coefficient. RESULTS: Fifteen patients needed of intubation and ventilation, while eight did not need of mechanical ventilation during ICU hospitalization. Viral load in pharyngeal swabs was 300 fold higher in the group of patients with the worst respiratory condition at admission to the ICU. Pharyngeal viral load directly correlated with plasma levels of the pro-inflammatory cytokines IL-6, IL-12p70, IFN-γ, the chemotactic factors MIP-1ß, GM-CSF, the angiogenic mediator VEGF and also of the immuno-modulatory cytokine IL-1ra (p < 0.05). Correlation studies demonstrated also the existence of a significant positive association between the levels of these mediators, evidencing that they are simultaneously regulated in response to the virus. CONCLUSIONS: Severe respiratory disease caused by the 2009 pandemic influenza virus is characterized by the existence of a direct association between viral replication and host cytokine response, revealing a potential pathogenic link with the severe disease caused by other influenza subtypes such as H5N1.
Subject(s)
Cytokines/metabolism , Influenza A Virus, H1N1 Subtype/immunology , Influenza A Virus, H1N1 Subtype/isolation & purification , Influenza, Human/immunology , Influenza, Human/virology , Nasopharynx/virology , Adult , Critical Illness , Female , Humans , Influenza, Human/pathology , Male , Middle Aged , Polymerase Chain Reaction/methods , Viral Load/methodsABSTRACT
OBJECTIVES: To summarize the major activities of the International Academy of Health Sciences Informatics (IAHSI) in the 2020 time period and to welcome its 2020 Class of Fellows. METHOD: Report from the members of the Academy's Board. RESULTS: Due to the SARS-CoV-2 pandemic, both Plenary meetings in 2020 had to be organized as virtual meetings. Scientific discussions, focusing on mobilizing computable biomedical knowledge and on data standards and interoperability formed major parts of these meetings. A statement on the use of informatics in pandemic situations was elaborated and sent to the World Health Organization. A panel on data standards and interoperability started its work. 34 Fellows were welcomed in the 2020 Class of Fellows so that the Academy now consists of 179 members. CONCLUSIONS: There was a shift from supporting to strategic activities in the Academy's work. After having achieved organizational stability, the Academy can now focus on its strategic work and so on its main objective.
Subject(s)
Academies and Institutes/organization & administration , Medical Informatics , Global Health , National Academy of Sciences, U.S. , United StatesABSTRACT
Autism spectrum disorder (ASD) is a complex set of neurodevelopmental pathologies characterized by impoverished social and communicative abilities and stereotyped behaviors. Although its genetic basis is unquestionable, the involvement of environmental factors such as exposure to pesticides has also been proposed. Despite the systematic analyses of this relationship in humans, there are no specific reviews including both human and preclinical models. The present systematic review summarizes, analyzes, and discusses recent advances in preclinical and epidemiological studies. We included 45 human and 16 preclinical studies. These studies focused on Organophosphates (OP), Organochlorine (OC), Pyrethroid (PT), Neonicotinoid (NN), Carbamate (CM), and mixed exposures. Preclinical studies, where the OP Chlorpyrifos (CPF) compound is the one most studied, pointed to an association between gestational exposure and increased ASD-like behaviors, although the data are inconclusive with regard to other ages or pesticides. Studies in humans focused on prenatal exposure to OP and OC agents, and report cognitive and behavioral alterations related to ASD symptomatology. The results of both suggest that gestational exposure to certain OP agents could be linked to the clinical signs of ASD. Future experimental studies should focus on extending the analysis of ASD-like behaviors in preclinical models and include exposure patterns similar to those observed in human studies.
Subject(s)
Autism Spectrum Disorder , Chlorpyrifos , Pesticides , Prenatal Exposure Delayed Effects , Pyrethrins , Autism Spectrum Disorder/chemically induced , Autism Spectrum Disorder/epidemiology , Female , Humans , Pesticides/toxicity , Pregnancy , Prenatal Exposure Delayed Effects/chemically inducedABSTRACT
In recent years, the worldwide prevalence of overweight and obesity among adults and children has dramatically increased. The conventional model regarding the onset of obesity is based on an imbalance between energy intake and expenditure. However, other possible environmental factors involved, such as the exposure to chemicals like pesticides, cannot be discarded. These compounds could act as endocrine-disrupting chemicals (EDC) that may interfere with hormone activity related to several mechanisms involved in body weight control. The main objective of this study was to systematically review the data provided in the scientific literature for a possible association between prenatal and postnatal exposure to pesticides and obesity in offspring. A total of 25 human and 9 animal studies were analyzed. The prenatal, perinatal, and postnatal exposure to organophosphate, organochlorine, pyrethroid, neonicotinoid, and carbamate, as well as a combined pesticide exposure was reviewed. This systematic review reveals that the effects of pesticide exposure on body weight are mostly inconclusive, finding conflicting results in both humans and experimental animals. The outcomes reviewed are dependent on many factors, including dosage and route of administration, species, sex, and treatment duration. More research is needed to effectively evaluate the impact of the combined effects of different pesticides on human health.
Subject(s)
Pesticides , Pyrethrins , Adult , Child , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Female , Humans , Neonicotinoids , Obesity/chemically induced , Obesity/epidemiology , Organophosphates , Pesticides/toxicity , PregnancyABSTRACT
BACKGROUND: Primer and probe sequences are the main components of nucleic acid-based detection systems. Biologists use primers and probes for different tasks, some related to the diagnosis and prescription of infectious diseases. The biological literature is the main information source for empirically validated primer and probe sequences. Therefore, it is becoming increasingly important for researchers to navigate this important information. In this paper, we present a four-phase method for extracting and annotating primer/probe sequences from the literature. These phases are: (1) convert each document into a tree of paper sections, (2) detect the candidate sequences using a set of finite state machine-based recognizers, (3) refine problem sequences using a rule-based expert system, and (4) annotate the extracted sequences with their related organism/gene information. RESULTS: We tested our approach using a test set composed of 297 manuscripts. The extracted sequences and their organism/gene annotations were manually evaluated by a panel of molecular biologists. The results of the evaluation show that our approach is suitable for automatically extracting DNA sequences, achieving precision/recall rates of 97.98% and 95.77%, respectively. In addition, 76.66% of the detected sequences were correctly annotated with their organism name. The system also provided correct gene-related information for 46.18% of the sequences assigned a correct organism name. CONCLUSIONS: We believe that the proposed method can facilitate routine tasks for biomedical researchers using molecular methods to diagnose and prescribe different infectious diseases. In addition, the proposed method can be expanded to detect and extract other biological sequences from the literature. The extracted information can also be used to readily update available primer/probe databases or to create new databases from scratch.
Subject(s)
DNA Primers/genetics , DNA Probes/genetics , Data Mining , Databases, Genetic , Base Sequence , DNA Primers/chemistry , DNA Probes/chemistry , Periodicals as TopicABSTRACT
BACKGROUND: Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH) experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms. RESULTS: The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of >or= 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258) have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections. CONCLUSIONS: In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae.