Front Med (Lausanne). 2023 Mar 15;10:1073313. doi: 10.3389/fmed.2023.1073313. eCollection 2023.

ABSTRACT

This paper provides an overview of current linguistic and ontological challenges which have to be met in order to provide full support to the transformation of health ecosystems in order to meet precision medicine (5 PM) standards. It highlights both standardization and interoperability aspects regarding formal, controlled representations of clinical and research data, requirements for smart support to produce and encode content in a way that humans and machines can understand and process it. Starting from the current text-centered communication practices in healthcare and biomedical research, it addresses the state of the art in information extraction using natural language processing (NLP). An important aspect of the language-centered perspective of managing health data is the integration of heterogeneous data sources, employing different natural languages and different terminologies. This is where biomedical ontologies, in the sense of formal, interchangeable representations of types of domain entities come into play. The paper discusses the state of the art of biomedical ontologies, addresses their importance for standardization and interoperability and sheds light to current misconceptions and shortcomings. Finally, the paper points out next steps and possible synergies of both the field of NLP and the area of Applied Ontology and Semantic Web to foster data interoperability for 5 PM.

PMID:37007792 | PMC:PMC10050682 | DOI:10.3389/fmed.2023.1073313

BMC Health Serv Res. 2023 Apr 1;23(1):328. doi: 10.1186/s12913-023-09325-7.

ABSTRACT

BACKGROUND: Low and lower middle-income countries suffer lack of healthcare providers and proper workforce education programs, a greater spread of illnesses, poor surveillance, efficient management, etc., which are addressable by a central policy framework implementation. Accordingly, an eHealth policy framework is required specifically for these countries to successfully implement eHealth solutions. This study explores existing frameworks and fills the gap by proposing an eHealth policy framework in the context of developing countries.

METHODS: This PRISMA-based (PRISMA Preferred Reporting Items For Systematic Reviews and Meta-Analyses) systematic review used Google Scholar, IEEE, Web of Science, and PubMed latest on 23rd May 2022, explored 83 publications regarding eHealth policy frameworks, and extracted 11 publications scrutinizing eHealth policy frameworks in their title, abstract, or keywords. These publications were analyzed by using both expert opinion and Rstudio programming tools. They were explored based on their developing/developed countries' context, research approach, main contribution, constructs/dimensions of the framework, and related categories. In addition, by using cloudword and latent semantic space techniques, the most discussed concepts and targeted keywords were explored and a correlation test was conducted to depict the important concepts mentioned in the related literature and extract their relation with the targeted keywords in the interest of this study.

RESULTS: Most of these publications do not develop or synthesize new frameworks for eHealth policy implementation, but rather introduce eHealth implementation frameworks, explain policy dimensions, identify and extract relevant components of existing frameworks or point out legal or other relevant eHealth implementation issues.

CONCLUSION: After a thorough exploration of related literature, this study identified the main factors affecting an effective eHealth policy framework, found a gap in the context of developing countries, and proposed a four-step eHealth policy implementation guideline for successful implementation of eHealth in the context of developing. The limitation of this study is the lack of a proper amount of practically implemented eHealth policy framework cases in developing countries published in the literature for the review. Ultimately, this study is part of the BETTEReHEALTH (More information about the BETTEReHEALTH project at https://betterehealth.eu ) project funded by the European Union Horizon's 2020 under agreement number 101017450.

PMID:37005588 | DOI:10.1186/s12913-023-09325-7

Int Urogynecol J. 2023 Apr 1. doi: 10.1007/s00192-023-05511-7. Online ahead of print.

ABSTRACT

INTRODUCTION AND HYPOTHESIS: Toileting behaviors are related to lower urinary tract symptoms and bladder dysfunction and are an important factor affecting bladder health. The aim of this study was to translate the Toileting Behaviors-Women's Elimination Behaviors (TB-WEB) Scale into Turkish and to validate its internal consistency, test-retest reliability, and construct and criterion validity for use in Turkish pregnant women.

METHOD: The research was conducted with 226 pregnant women who presented to the antenatal outpatient clinics of a university hospital in Türkiye for antenatal follow-up. Data were collected using a sociodemographic questionnaire prepared by the researchers and the TB-WEB Scale. Descriptive data were analyzed using numbers, percentage and mean values, whereas psychometric analysis of the scale was performed using semantic equivalence, content validity, explanatory and confirmatory factor analysis, Cronbach's α, item-total correlation, and test-retest analysis.

RESULTS: The scale consisted of 20 items and five subscales. The content validity index of the items was found to be 93%. Cronbach's α coefficient was found to be 0.77 for the whole scale; 0.60 for the place preference for voiding subscale; 0.73 for the premature voiding subscale; 0.84 for the delayed voiding subscale; 0.83 for the straining voiding subscale; and 0.88 for the position preference for voiding subscale. The scale mediates 62% of the total variance. Confirmatory factor analysis found that item factor loadings varied between 0.31 and 0.99 and root mean square error of approximation (RMSEA) value was found 0.078.

CONCLUSION: The Turkish version of the TB-WEB Scale is a valid and reliable instrument in evaluating women's toileting behaviors during pregnancy.

PMID:37004519 | DOI:10.1007/s00192-023-05511-7

PeerJ. 2023 Mar 24;11:e15076. doi: 10.7717/peerj.15076. eCollection 2023.

ABSTRACT

BACKGROUND: Considering that adolescents spend considerable time on the Internet and social media and experience high levels of stress, it is difficult to find a study that investigates adolescent stress through a big data-based network analysis of social media. Hence, this study was designed to provide basic data to establish desirable stress coping strategies for adolescents based on a big data-based network analysis of social media for Korean adolescent stress. The purpose of this study was to (1) identify social media words that express stress in adolescents and (2) investigate the associations between those words and their types.

METHODS: To analyse adolescent stress, we used social media data collected from online news and blog websites and performed semantic network analysis to understand the relationships among keywords extracted in the collected data.

RESULTS: The top five words used by Korean adolescents were counselling, school, suicide, depression, and activity in online news, and diet, exercise, eat, health, and obesity in blogs. As the top keywords of the blog are mainly related to diet and obesity, it reflects adolescents' high degree of interest in their bodies; the body is also a primary source of adolescent stress. In addition, blogs contained more content about the causes and symptoms of stress than online news, which focused more on stress resolution and coping. This highlights the trend that social blogging is a new channel for sharing personal information.

CONCLUSIONS: The results of this study are valuable as they were derived through a social big data analysis of data obtained from online news and blogs, providing a wide range of implications related to adolescent stress. Hence this study can contribute basic data for the stress management of adolescents and their mental health management in the future.

PMID:36992939 | PMC:PMC10042152 | DOI:10.7717/peerj.15076

Sci Data. 2023 Mar 27;10(1):171. doi: 10.1038/s41597-023-01993-8.

ABSTRACT

The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in the healthy human body. It is compiled by an international team of experts who develop standard terminologies that they link to 3D reference objects, describing anatomical structures. The third HRA release (v1.2) covers spatial reference data and ontology annotations for 26 organs. Experts access the HRA annotations via spreadsheets and view reference object models in 3D editing tools. This paper introduces the Common Coordinate Framework (CCF) Ontology v2.0.1 that interlinks specimen, biological structure, and spatial data, together with the CCF API that makes the HRA programmatically accessible and interoperable with Linked Open Data (LOD). We detail how real-world user needs and experimental data guide CCF Ontology design and implementation, present CCF Ontology classes and properties together with exemplary usage, and report on validation methods. The CCF Ontology graph database and API are used in the HuBMAP portal, HRA Organ Gallery, and other applications that support data queries across multiple, heterogeneous sources.

PMID:36973309 | PMC:PMC10043028 | DOI:10.1038/s41597-023-01993-8

Prim Care Companion CNS Disord. 2023 Mar 14;25(2):22m03348. doi: 10.4088/PCC.22m03348.

ABSTRACT

Objective: To assess the humanistic and economic burden of attention-deficit/hyperactivity disorder (ADHD) among adult patients treated with immediate-release (IR) only or extended-release (ER) only stimulants and those unmedicated versus treated with ER + IR stimulants.

Methods: This study analyzed linked data from National Health and Wellness Survey and claims to assess the differences in patient characteristics and outcomes, including health-related quality of life (HRQoL), work productivity and activity impairment, and health care resource utilization (HRU) and associated costs by comparing ADHD patients treated with either IR or ER and those unmedicated for ADHD versus ER + IR.

Results: The burden of ADHD was compared among adults on stimulant medications with different duration of effect (DoE) (ER + IR: n = 34, ER: n = 184, IR: n = 149) and the unmedicated group (n = 114). Bivariate analysis showed the IR (P = .047) and unmedicated groups (P = .01) had significantly lower Medical Outcomes Study 36-item Short Form physical component summary scores versus ER + IR. The unmedicated group had higher HRU and associated costs versus other groups. Multivariable analysis revealed that the unmedicated group had twice as many outpatient visits (P = .001) and higher total annual direct costs than those on ER + IR (risk ratio = 2.20, P = .016). Patients with mental health comorbidities had significantly poorer HRQoL mental component summary scores and higher activity impairment versus those without mental health comorbidities (P = .001 and P < .001, respectively).

Conclusions: Patients with ADHD treated with longer DoE formulations had substantially better economic outcomes versus shorter DoE formulation or unmedicated groups, offering potential cost savings to the health care system and the patient. Furthermore, it is important to consider the effect of mental health comorbidities in the overall management of ADHD.

PMID:36946563 | DOI:10.4088/PCC.22m03348

Schizophr Bull. 2023 Mar 22;49(Supplement_2):S142-S152. doi: 10.1093/schbul/sbac056.

ABSTRACT

BACKGROUND AND HYPOTHESIS: Mapping a patient's speech as a network has proved to be a useful way of understanding formal thought disorder in psychosis. However, to date, graph theory tools have not explicitly modelled the semantic content of speech, which is altered in psychosis.

STUDY DESIGN: We developed an algorithm, "netts," to map the semantic content of speech as a network, then applied netts to construct semantic speech networks for a general population sample (N = 436), and a clinical sample comprising patients with first episode psychosis (FEP), people at clinical high risk of psychosis (CHR-P), and healthy controls (total N = 53).

STUDY RESULTS: Semantic speech networks from the general population were more connected than size-matched randomized networks, with fewer and larger connected components, reflecting the nonrandom nature of speech. Networks from FEP patients were smaller than from healthy participants, for a picture description task but not a story recall task. For the former task, FEP networks were also more fragmented than those from controls; showing more connected components, which tended to include fewer nodes on average. CHR-P networks showed fragmentation values in-between FEP patients and controls. A clustering analysis suggested that semantic speech networks captured novel signals not already described by existing NLP measures. Network features were also related to negative symptom scores and scores on the Thought and Language Index, although these relationships did not survive correcting for multiple comparisons.

CONCLUSIONS: Overall, these data suggest that semantic networks can enable deeper phenotyping of formal thought disorder in psychosis. Whilst here we focus on network fragmentation, the semantic speech networks created by Netts also contain other, rich information which could be extracted to shed further light on formal thought disorder. We are releasing Netts as an open Python package alongside this manuscript.

PMID:36946531 | DOI:10.1093/schbul/sbac056

Cogn Process. 2023 Mar 21. doi: 10.1007/s10339-023-01131-7. Online ahead of print.

ABSTRACT

During the epidemic, online advertising became more important, and several studies have suggested that internet users tend to avoid viewing online ads, such as banner ads. Previous studies have shown that product items that use animation lead to increased visual attention to all items on a webpage at the expense of attention to nonanimated items on the same webpage. However, few studies have compared the impact of the picture and text forms taken by static banners on the effectiveness of banner ads. At the same time, whether semantic factors (theme consistency) moderate the influence of structural factors (picture and text forms) on banner advertising remains unknown. The aim of this paper is to examine the influence of structural factors and semantic factors of ads on participants' visual attention to and memory of banner ads. The participants (twenty-seven males and forty females aged 18-26 years) were divided into two groups, one for consistent ad-web content themes and the other for inconsistent ad-web content themes. Then, the participants were asked to browse 16 complete pages (4 pages each of text-type web content and text-type banner ads, picture-type web content and picture-type banner ads, text-type web content and picture-type banner ads, and picture-type web content and text-type banner ads), and their eye movements were recorded to measure the participants' level of attention to the banner ads. A recognition task was used to measure the participants' memories of the banner ads. The results showed that the text-type banner ad had a lower blindness rate and exerted better attention and memory effects than the picture-type banner ad, and the text-type banner ad had a lower blindness rate and better attention and memory effects when positioned in the background of picture-type web content than when positioned in the background of text-type web content. A significant interaction effect among banner ad type, web content type and theme consistency showed that ad-web content theme consistency moderated the effect of web content type and banner ad type on ad effectiveness. Taken together, the results of these tasks demonstrate that theme consistency moderates the effect of web content type and banner ad type on ad effectiveness in a top-down manner. To reduce the negative effect of banner blindness, placing text-type banner ads in picture-type web content and setting a consistent theme between the banner ad and the web content is the more effective choice. The findings from this study can be used to assist advertising agencies in designing more effective and efficient banner ads from the perspective of basic psychology.

PMID:36943584 | DOI:10.1007/s10339-023-01131-7

Public Health. 2023 May;218:12-20. doi: 10.1016/j.puhe.2023.02.008. Epub 2023 Feb 15.

ABSTRACT

INTRODUCTION: The UK shielding policy intended to protect people at the highest risk of harm from COVID-19 infection. We aimed to describe intervention effects in Wales at 1 year.

METHODS: Retrospective comparison of linked demographic and clinical data for cohorts comprising people identified for shielding from 23 March to 21 May 2020; and the rest of the population. Health records were extracted with event dates between 23 March 2020 and 22 March 2021 for the comparator cohort and from the date of inclusion until 1 year later for the shielded cohort.

RESULTS: The shielded cohort included 117,415 people, with 3,086,385 in the comparator cohort. The largest clinical categories in the shielded cohort were severe respiratory condition (35.5%), immunosuppressive therapy (25.9%) and cancer (18.6%). People in the shielded cohort were more likely to be female, aged ≥50 years, living in relatively deprived areas, care home residents and frail. The proportion of people tested for COVID-19 was higher in the shielded cohort (odds ratio [OR] 1.616; 95% confidence interval [CI] 1.597-1.637), with lower positivity rate incident rate ratios 0.716 (95% CI 0.697-0.736). The known infection rate was higher in the shielded cohort (5.9% vs 5.7%). People in the shielded cohort were more likely to die (OR 3.683; 95% CI: 3.583-3.786), have a critical care admission (OR 3.339; 95% CI: 3.111-3.583), hospital emergency admission (OR 2.883; 95% CI: 2.837-2.930), emergency department attendance (OR 1.893; 95% CI: 1.867-1.919) and common mental disorder (OR 1.762; 95% CI: 1.735-1.789).

CONCLUSION: Deaths and healthcare utilisation were higher amongst shielded people than the general population, as would be expected in the sicker population. Differences in testing rates, deprivation and pre-existing health are potential confounders; however, lack of clear impact on infection rates raises questions about the success of shielding and indicates that further research is required to fully evaluate this national policy intervention.

PMID:36933354 | PMC:PMC9928733 | DOI:10.1016/j.puhe.2023.02.008

Lancet. 2022 Nov;400 Suppl 1:S29. doi: 10.1016/S0140-6736(22)02239-5. Epub 2022 Nov 24.

ABSTRACT

BACKGROUND: The Family Nurse Partnership (FNP) is an early home visiting service supporting young mothers. A randomised controlled trial of FNP in England found no effect on short-term primary outcomes or maltreatment in children up to age 7 years, but positive impacts on some educational outcomes. We report preliminary results of a national evaluation of FNP using linked administrative data.

METHODS: We constructed a cohort of all mothers in England aged 13-19 years who gave birth between April 1, 2010, and March 31, 2019, to their firstborn child or children, using linked administrative data from hospital admissions (Hospital Episode Statistics) and education and social care (National Pupil Database). We evaluated differences in a range of policy relevant child and maternal outcomes, comparing mothers who were enrolled in FNP with those who were not, using propensity score matching.

FINDINGS: Of 110 960 mothers in our linked cohort, 26 290 (24%) were enrolled in FNP. FNP mothers were younger, more deprived, and more likely to have adversity or social care histories than mothers not enrolled. Compared with mothers not enrolled in FNP, those in FNP did not have fewer unplanned hospital admissions for injury or maltreatment in children by age 2 years, lower rates of children looked after in out-of-home care by age 7 years, or improved maternal outcomes, but were more likely to achieve a good level of development at school entry. We present findings among subgroups of younger maternal age (13-15 years), increased deprivation according to quintile of Index of Multiple Deprivation, and adversity and social care history. We also present sensitivity analyses that aim to minimise confounding.

INTERPRETATION: Our study supports findings from previous trials of FNP showing little benefit for measured child maltreatment and maternal outcomes, but some evidence of benefit for school readiness. Interpretation of results needs careful consideration of the impact of residual confounding due to unmeasured or undisclosed factors (eg, family violence) linked to targeting of FNP to higher risk mothers, and surveillance bias.

FUNDING: National Institute for Health and Care Research.

PMID:36929972 | DOI:10.1016/S0140-6736(22)02239-5

Brain. 2023 Mar 16:awad013. doi: 10.1093/brain/awad013. Online ahead of print.

ABSTRACT

Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need to better predict long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnection-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace of white matter disconnections (disconnectome) to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights that are available as the first comprehensive atlas of disconnectome-deficit relations across 86 scores-a Neuropsychological White Matter Atlas. Our novel predictive framework, the Disconnectome Symptoms Discoverer, achieved better predictivity performances than six other models, including functional disconnection, lesion topology and volume modelling. Out-of-sample prediction derived from this atlas presented a mean absolute error below 20% and allowed personalize neuropsychological predictions. Prediction on an external cohort achieved an R2 = 0.201 for semantic fluency. In addition, training and testing were replicated on two external cohorts achieving an R2 = 0.18 for visuospatial performance. This framework is available as an interactive web application (http://disconnectomestudio.bcblab.com) to provide the foundations for a new and practical approach to modelling cognition in stroke. We hope our atlas and web application will help to reduce the burden of cognitive deficits on patients, their families and wider society while also helping to tailor future personalized treatment programmes and discover new targets for treatments. We expect our framework's range of assessments and predictive power to increase even further through future crowdsourcing.

PMID:36928757 | DOI:10.1093/brain/awad013

J Dent Educ. 2023 Mar 16. doi: 10.1002/jdd.13193. Online ahead of print.

ABSTRACT

PURPOSE: The aim of this study is to investigate the literature to evaluate dental students' attitudes regarding the treatment of older adults.

METHODS: A scoping review was performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses/PRISMA guidelines to identify articles from four electronic databases: MEDLINE via the PubMed interface, Embase, Cumulative Index to Nursing and Allied Health Literature, and AgeLine. Gray literature searches were also performed in Scopus, Web of Science, and ProQuest Dissertations and Theses-Health and Medicine.

RESULTS: Eleven articles were assessed. The majority (72, 72%) were published between 2011 and 2020, evidencing various contexts of dental students, such as different countries and cultures, and levels of education. The most commonly used tool/instrument to survey dental students' attitudes was the Aging Semantic Differential Scale. Student age, race, and marital status did not seem to interfere with dental students' attitudes regarding the treatment of older adults.

CONCLUSIONS: Dental students tend to have a positive attitude toward older people. In this context, female students, students who interact with older people, and clinical students have more positive attitudes than male and nonclinical students.

PMID:36928643 | DOI:10.1002/jdd.13193

PLoS One. 2023 Mar 14;18(3):e0282712. doi: 10.1371/journal.pone.0282712. eCollection 2023.

ABSTRACT

In the visual design of a portal website, color is the first intuitive factor for users. It is relatively difficult for the designer of a city portal website to choose a color system that represents a city's unique color from among the many available options. Therefore, this study extracted a decision-making model of the urban color system, which can help decision-makers and designers choose among color systems, and then effectively design a portal website that conforms to local cultural attributes. The proposed method to solve the problem involved obtaining optimal color matching by performing weight analysis of colors through 123 sample color semantics, factor analysis, and a fuzzy analytic hierarchy process. Semantic analysis was used to classify colors into four categories of fashion, technology, calm, and dazzling. The fashion color matching scheme scored relatively high. Web page color matching schemes with a white background were popular, among which a white and green color matching scheme scored relatively high. At the same time, there are differences in color preferences between genders and cultures. This study is significant because it proposes a color decision model for portal websites, which provides a reference value that can also be applied to the selection of color schemes for other types of web pages in the future.

PMID:36917586 | DOI:10.1371/journal.pone.0282712

JMIR Public Health Surveill. 2023 Mar 14;9:e38868. doi: 10.2196/38868.

ABSTRACT

BACKGROUND: Chlamydia and gonorrhea cases continue to rise in Illinois, increasing by 16.4% and 70.9% in 2019, respectively, compared with 2015. Providers are required to report both chlamydia and gonorrhea, as mandated by public health laws. Manual reporting remains a huge burden; 90%-93% of cases were reported to Illinois Department of Public Health (IDPH) via electronic laboratory reporting (ELR), and the remaining were reported through web-based data entry platforms, faxes, and phone calls. However, cases reported via ELRs only contain information available to a laboratory facility and do not contain additional data needed for public health. Such data are typically found in an electronic health record (EHR). Electronic case reports (eCRs) were developed and automated the generation of case reports from EHRs to be reported to public health agencies.

OBJECTIVE: Prior studies consolidated trigger criteria for eCRs, and compared with manual reporting, found it to be more complete. The goal of this project is to pilot standards-based eCR for chlamydia and gonorrhea. We evaluated the throughput, completeness, and timeliness of eCR compared to ELR, as well as the implementation experience at a large health center-controlled network in Illinois.

METHODS: For this study, we selected 8 clinics located on the north, west, and south sides of Chicago to implement the eCRs; these cases were reported to IDPH. The study period was 52 days. The centralized EHR used by these clinics leveraged 2 of the 3 case detection scenarios, which were previously defined as the trigger, to generate an eCR. These messages were successfully transmitted via Health Level 7 electronic initial case report standard. Upon receipt by IDPH, these eCRs were parsed and housed in a staging database.

RESULTS: During the study period, 183 eCRs representing 135 unique patients were received by IDPH. eCR reported 95% (n=113 cases) of all the chlamydia cases and 97% (n=70 cases) of all the gonorrhea cases reported from the participating clinical sites. eCR found an additional 14 (19%) cases of gonorrhea that were not reported via ELR. However, ELR reported an additional 6 cases of chlamydia and 2 cases of gonorrhea, which were not reported via eCR. ELR reported 100% of chlamydia cases but only 81% of gonorrhea cases. While key elements such as patient and provider names were complete in both eCR and ELR, eCR was found to report additional clinical data, including history of present illness, reason for visit, symptoms, diagnosis, and medications.

CONCLUSIONS: eCR successfully identified and created automated reports for chlamydia and gonorrhea cases in the implementing clinics in Illinois. eCR demonstrated a more complete case report and represents a promising future of reducing provider burden for reporting cases while achieving greater semantic interoperability between health care systems and public health.

PMID:36917153 | DOI:10.2196/38868

Sci Data. 2023 Mar 10;10(1):127. doi: 10.1038/s41597-023-02028-y.

ABSTRACT

The Swiss Personalized Health Network (SPHN) is a government-funded initiative developing federated infrastructures for a responsible and efficient secondary use of health data for research purposes in compliance with the FAIR principles (Findable, Accessible, Interoperable and Reusable). We built a common standard infrastructure with a fit-for-purpose strategy to bring together health-related data and ease the work of both data providers to supply data in a standard manner and researchers by enhancing the quality of the collected data. As a result, the SPHN Resource Description Framework (RDF) schema was implemented together with a data ecosystem that encompasses data integration, validation tools, analysis helpers, training and documentation for representing health metadata and data in a consistent manner and reaching nationwide data interoperability goals. Data providers can now efficiently deliver several types of health data in a standardised and interoperable way while a high degree of flexibility is granted for the various demands of individual research projects. Researchers in Switzerland have access to FAIR health data for further use in RDF triplestores.

PMID:36899064 | DOI:10.1038/s41597-023-02028-y

Brief Bioinform. 2023 Mar 9:bbad077. doi: 10.1093/bib/bbad077. Online ahead of print.

ABSTRACT

Neuropeptides are a diverse and complex class of signaling molecules that regulate a variety of biological processes. Neuropeptides provide many opportunities for the discovery of new drugs and targets for the treatment of a wide range of diseases, and thus, computational tools for the rapid and accurate large-scale identification of neuropeptides are of great significance for peptide research and drug development. Although several machine learning-based prediction tools have been developed, there is room for improvement in the performance and interpretability of the proposed methods. In this work, we developed an interpretable and robust neuropeptide prediction model, named NeuroPred-PLM. First, we employed a language model (ESM) of proteins to obtain semantic representations of neuropeptides, which could reduce the complexity of feature engineering. Next, we adopted a multi-scale convolutional neural network to enhance the local feature representation of neuropeptide embeddings. To make the model interpretable, we proposed a global multi-head attention network that could be used to capture the position-wise contribution to neuropeptide prediction via the attention scores. In addition, NeuroPred-PLM was developed based on our newly constructed NeuroPep 2.0 database. Benchmarks based on the independent test set show that NeuroPred-PLM achieves superior predictive performance compared with other state-of-the-art predictors. For the convenience of researchers, we provide an easy-to-install PyPi package (https://pypi.org/project/NeuroPredPLM/) and a web server (https://huggingface.co/spaces/isyslab/NeuroPred-PLM).

PMID:36892166 | DOI:10.1093/bib/bbad077

Child Abuse Negl. 2023 May;139:106126. doi: 10.1016/j.chiabu.2023.106126. Epub 2023 Mar 6.

ABSTRACT

BACKGROUND: Women prisoners are a growing portion of the prison population. Health and social outcomes of their children have been studied and found to be poor, but little is known about child protection outcomes.

OBJECTIVES: Ascertain child protection system contact of children exposed to maternal incarceration.

PARTICIPANTS AND SETTING: All children born between 1985 and 2011 exposed to the incarceration of their mothers in a Western Australian correctional facility and a matched comparison group.

METHODS: A matched cohort study using linked administrative data on 2637 mothers entering prison between 1985 and 2015 and their 6680 children. We estimated hazard ratios (HRs) and incidence rate ratios (IRRs) of child protection service (CPS) contact post maternal incarceration (four concern levels), comparing rates for children exposed to maternal incarceration with a matched non-exposed group, adjusting for maternal and child factors.

FINDINGS: Exposure to maternal incarceration increased risk of CPS contact. Unadjusted HRs exposed vs unexposed children were 7.06 (95%CI = 6.49-7.69) for substantiated child maltreatment and 12.89 (95%CI = 11.42-14.55) for out-of-home care (OOHC). Unadjusted IRRs were 6.04 (95%CI = 5.57-6.55) for number of substantiations and 12.47 (95%CI = 10.65-14.59) for number of removals to OOHC. HRs and IRRs were only slightly attenuated in adjusted models.

CONCLUSIONS: Maternal incarceration is a warning flag for a child at high risk of serious child protection concerns. Family-friendly rehabilitative women's prisons, incorporating support for more nurturing mother-child relationships could provide a placed-based public health opportunity for disrupting distressing life trajectories and intergenerational pathways of disadvantage of these vulnerable children and their mothers. This population should be a priority for trauma-informed family support services.

PMID:36889149 | DOI:10.1016/j.chiabu.2023.106126

Gigascience. 2022 Dec 28;12:giad014. doi: 10.1093/gigascience/giad014.

ABSTRACT

BACKGROUND: The life sciences are one of the biggest suppliers of scientific data. Reusing and connecting these data can uncover hidden insights and lead to new concepts. Efficient reuse of these datasets is strongly promoted when they are interlinked with a sufficient amount of machine-actionable metadata. While the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles have been accepted by all stakeholders, in practice, there are only a limited number of easy-to-adopt implementations available that fulfill the needs of data producers.

FINDINGS: We developed the FAIR Data Station, a lightweight application written in Java, that aims to support researchers in managing research metadata according to the FAIR principles. It implements the ISA metadata framework and uses minimal information metadata standards to capture experiment metadata. The FAIR Data Station consists of 3 modules. Based on the minimal information model(s) selected by the user, the "form generation module" creates a metadata template Excel workbook with a header row of machine-actionable attribute names. The Excel workbook is subsequently used by the data producer(s) as a familiar environment for sample metadata registration. At any point during this process, the format of the recorded values can be checked using the "validation module." Finally, the "resource module" can be used to convert the set of metadata recorded in the Excel workbook in RDF format, enabling (cross-project) (meta)data searches and, for publishing of sequence data, in an European Nucleotide Archive-compatible XML metadata file.

CONCLUSIONS: Turning FAIR into reality requires the availability of easy-to-adopt data FAIRification workflows that are also of direct use for data producers. As such, the FAIR Data Station provides, in addition to the means to correctly FAIRify (omics) data, the means to build searchable metadata databases of similar projects and can assist in ENA metadata submission of sequence data. The FAIR Data Station is available at https://fairbydesign.nl.

PMID:36879493 | DOI:10.1093/gigascience/giad014

Age Ageing. 2023 Mar 1;52(3):afac332. doi: 10.1093/ageing/afac332.

ABSTRACT

BACKGROUND: emergency department (ED) visits have inherent risks for people with dementia yet increase towards the end-of-life. Although some individual-level determinants of ED visits have been identified, little is known about service-level determinants.

OBJECTIVE: to examine individual- and service-level factors associated with ED visits by people with dementia in the last year of life.

METHODS: retrospective cohort study using hospital administrative and mortality data at the individual-level, linked to health and social care service data at the area-level across England. The primary outcome was number of ED visits in the last year of life. Subjects were decedents with dementia recorded on the death certificate, with at least one hospital contact in the last 3 years of life.

RESULTS: of 74,486 decedents (60.5% women; mean age 87.1 years (standard deviation: 7.1)), 82.6% had at least one ED visit in their last year of life. Factors associated with more ED visits included: South Asian ethnicity (incidence rate ratio (IRR) 1.07, 95% confidence interval (CI) 1.02-1.13), chronic respiratory disease as the underlying cause of death (IRR 1.17, 95% CI 1.14-1.20) and urban residence (IRR 1.06, 95% CI 1.04-1.08). Higher socioeconomic position (IRR 0.92, 95% CI 0.90-0.94) and areas with higher numbers of nursing home beds (IRR 0.85, 95% CI 0.78-0.93)-but not residential home beds-were associated with fewer ED visits at the end-of-life.

CONCLUSIONS: the value of nursing home care in supporting people dying with dementia to stay in their preferred place of care must be recognised, and investment in nursing home bed capacity prioritised.

PMID:36861183 | DOI:10.1093/ageing/afac332

BMC Bioinformatics. 2023 Feb 27;24(1):69. doi: 10.1186/s12859-023-05190-7.

ABSTRACT

BACKGROUND: Information provided by high-throughput sequencing platforms allows the collection of content-rich data about biological sequences and their context. Sequence alignment is a bioinformatics approach to identifying regions of similarity in DNA, RNA, or protein sequences. However, there is no consensus about the specific common terminology and representation for sequence alignments. Thus, automatically linking the wide existing knowledge about the sequences with the alignments is challenging.

RESULTS: The Sequence Alignment Ontology (SALON) defines a helpful vocabulary for representing and semantically annotating pairwise and multiple sequence alignments. SALON is an OWL 2 ontology that supports automated reasoning for alignments validation and retrieving complementary information from public databases under the Open Linked Data approach. This will reduce the effort needed by scientists to interpret the sequence alignment results.

CONCLUSIONS: SALON defines a full range of controlled terminology in the domain of sequence alignments. It can be used as a mediated schema to integrate data from different sources and validate acquired knowledge.

PMID:36849882 | DOI:10.1186/s12859-023-05190-7