Whole-cycle management of women with epilepsy of child-bearing age: ontology construction and application.

BACKGROUND: The effective management of epilepsy in women of child-bearing age necessitates a concerted effort from multidisciplinary teams. Nevertheless, there exists an inadequacy in the seamless exchange of knowledge among healthcare providers within this context. Consequently, it is imperative to enhance the availability of informatics resources and the development of decision support tools to address this issue comprehensively. MATERIALS AND METHODS: The development of the Women with Epilepsy of Child-Bearing Age Ontology (WWECA) adhered to established ontology construction principles. The ontology's scope and universal terminology were initially established by the development team and subsequently subjected to external evaluation through a rapid Delphi consensus exercise involving domain experts. Additional entities and attribute annotation data were sourced from authoritative guideline documents and specialized terminology databases within the respective field. Furthermore, the ontology has played a pivotal role in steering the creation of an online question-and-answer system, which is actively employed and assessed by a diverse group of multidisciplinary healthcare providers. RESULTS: WWECA successfully integrated a total of 609 entities encompassing various facets related to the diagnosis and medication for women of child-bearing age afflicted with epilepsy. The ontology exhibited a maximum depth of 8 within its hierarchical structure. Each of these entities featured three fundamental attributes, namely Chinese labels, definitions, and synonyms. The evaluation of WWECA involved 35 experts from 10 different hospitals across China, resulting in a favorable consensus among the experts. Furthermore, the ontology-driven online question and answer system underwent evaluation by a panel of 10 experts, including neurologists, obstetricians, and gynecologists. This evaluation yielded an average rating of 4.2, signifying a positive reception and endorsement of the system's utility and effectiveness. CONCLUSIONS: Our ontology and the associated online question and answer system hold the potential to serve as a scalable assistant for healthcare providers engaged in the management of women with epilepsy (WWE). In the future, this developmental framework has the potential for broader application in the context of long-term management of more intricate chronic health conditions.

Perspectives on the role of industry in informatics research and authorship.

OBJECTIVES: Advances in informatics research come from academic, nonprofit, and for-profit industry organizations, and from academic-industry partnerships. While scientific studies of commercial products may offer critical lessons for the field, manuscripts authored by industry scientists are sometimes categorically rejected. We review historical context, community perceptions, and guidelines on informatics authorship. PROCESS: We convened an expert panel at the American Medical Informatics Association 2022 Annual Symposium to explore the role of industry in informatics research and authorship with community input. The panel summarized session themes and prepared recommendations. CONCLUSIONS: Authorship for informatics research, regardless of affiliation, should be determined by International Committee of Medical Journal Editors uniform requirements for authorship. All authors meeting criteria should be included, and categorical rejection based on author affiliation is unethical. Informatics research should be evaluated based on its scientific rigor; all sources of bias and conflicts of interest should be addressed through disclosure and, when possible, methodological mitigation.

Characterization and genome-informatic analysis of a novel lytic mendocina phage vB_PmeS_STP12 suitable for phage therapy pseudomonas or biocontrol.

BACKGROUND: A novel lytic bacteriophage (phage) was isolated with Pseudomonas mendocina strain STP12 (P. mendocina) from the untreated site of Sewage Treatment Plant of Lovely Professional University, India. P. mendocina is a Gram-negative, rod-shaped, aerobic bacterium belonging to the family Pseudomonadaceae and has been reported in fifteen (15) cases of economically important diseases worldwide. METHODS AND RESULTS: Here, a novel phage specifically infecting and killing P. mendocina strain STP12 was isolated from sewage sample using enrichment, spot test and double agar overlay (DAOL) method and was designated as vB_PmeS_STP12. The phage vB-PmeS-STP12 was viable at wide range of pH and temperature ranging from 4 to10 and - 20 to 70 °C respectively. Host range and efficiency of plating (EOP) analysis indicated that phage vB-PmeS-STP12 was capable of infecting and killing P. mendocina strain STP6 with EOP of 0.34. Phage vB_PmeS_STP12 was found to have a significant bacterial reduction (p < 0.005) at all the doses administered, particularly at optimal MOI of 1 PFU/CFU, compared to the control. Morphological analysis using high resolution transmission electron microscopy (HR-TEM) revealed an icosahedral capsid of ~ 55 nm in diameter on average with a short, non-contractile tail. The genome of vB_PmeS_STP12 is a linear, dsDNA containing 36,212 bp in size with a GC content of 58.87% harbouring 46 open reading frames (ORFs). The 46 predicted ORFs encode proteins with functional information categorized as lysis, replication, packaging, regulation, assembly, infection, immune, and hypothetical. However, the genome of vB_PmeS_STP12 appeared to be devoid of tRNAs, integrase gene, toxins genes, virulence factors, antimicrobial resistance genes (ARGs) and CRISPR arrays. The blast analysis with phylogeny revealed that vB_PmeS_STP12 is genetically similar to Pseudomonas phage PMBT14, Pseudomonas phage Almagne and Serratia phage Serbin with a highest identity of 74.00%, 74.93% and 59.48% respectively. CONCLUSIONS: Taken together, characterization, morphological analysis and genome-informatics indicated that vB_PmeS_STP12 is podovirus morphotype belonging to the class Caudoviticetes, family Zobellviridae which appeared to be devoid of integrase gene, ARGs, CRISPR arrays, virulence factors and toxins genes, exhibiting stability and infectivity at wide range of pH (4 to10) and temperature (-20 to 70 °C), thereby making vB_PmeS_STP12 suitable for phage therapy or biocontrol. Based on the bibliometric analysis and data availability with respect to sequences deposited in GenBank, this is the first report of a phage infecting Pseudomonas mendocina.

Integrative Research of Neuropharmacology and Informatics Pharmacology for Mental Disorder.

Mental illness poses a huge social burden, accounting for approximately 14% of all deaths. Depression, a major component of mental illness, affects approximately 300 million people worldwide, mainly in developed countries, and is not only a major social burden but also a cause of suicide. The social burden of depression is estimated to increase further in developing countries, and overcoming it is a pressing issue for all countries, including Japan. Although clinical evidence has demonstrated the efficacy of serotonergic neurotransmission enhancers in the treatment of depression, the full picture of their therapeutic effects has not yet been fully elucidated. In this review, we show that the hyperactivity of serotonin neurons, especially those in the dorsal raphe nucleus, is commonly induced by various antidepressants within a period corresponding to the onset of their clinical efficacy. We established quantitative prediction methods for pharmacological activity using only chemical structures to translate the biological understanding of mental disorders, including major depressive disorders, into clinically effective therapeutics. Our method exhibited better performance than the previously reported methods of quantitative prediction, while targeting a larger number of proteins. Our article suggests the importance of integrative neuropharmacology and informatics-based pharmacology studies to understand the biological basis of mental disorders and facilitate drug development for these disorders.

Validating core therapeutic targets for osteoporosis treatment based on integrating network pharmacology and informatics.

OBJECTIVE: Our goal was to find metabolism-related lncRNAs that were associated with osteoporosis (OP) and construct a model for predicting OP progression using these lncRNAs. METHODS: The GEO database was employed to obtain gene expression profiles. The WGCNA technique and differential expression analysis were used to identify hypoxia-related lncRNAs. A Lasso regression model was applied to select 25 hypoxia-related genes, from which a classification model was created. Its robust classification performance was confirmed with an area under the ROC curve close to 1, as verified on the validation set. Concurrently, we constructed a ceRNA network based on these genes to unveil potential regulatory processes. Biologically active compounds of STZYD were identified using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP) database. BATMAN was used to identify its targets, and we obtained OP-related genes from Malacards and DisGeNET, followed by identifying intersection genes with metabolism-related genes. A pharmacological network was then constructed based on the intersecting genes. The pharmacological network was further integrated with the ceRNA network, resulting in the creation of a comprehensive network that encompasses herb-active components, pathways, lncRNAs, miRNAs, and targets. Expression levels of hypoxia-related lncRNAs in mononuclear cells isolated from peripheral blood of OP and normal patients were subsequently validated using quantitative real-time PCR (qRT-PCR). Protein levels of RUNX2 were determined through a western blot assay. RESULTS: CBFB, GLO1, NFKB2 and PIK3CA were identified as central therapeutic targets, and ADD3-AS1, DTX2P1-UPK3BP1-PMS2P11, TTTY1B, ZNNT1 and LINC00623 were identified as core lncRNAs. CONCLUSIONS: Our work uncovers a possible therapeutic mechanism for STZYD, providing a potential therapeutic target for OP. In addition, a prediction model of metabolism-related lncRNAs of OP progression was constructed to provide a reference for the diagnosis of OP patients.

Improving Vaccine Equity: How Community Engagement and Informatics Facilitate Health System Outreach to Underrepresented Groups.

BACKGROUND: Given the inequities in access to health care resources like COVID-19 vaccination, health systems should carefully consider how to reach underrepresented groups. Reflecting on vaccine rollout efforts holds insight on the role of community engagement and informatics support in promoting health equity. OBJECTIVES: This study aimed to assess the effectiveness of four outreach strategies deployed by University of Washington (UW) Medicine in improving vaccine equity over traditional vaccine scheduling online or by phone, we report on appointment scheduling and completion of appointments (i.e., vaccine administration) through (1) automated outreach to individuals from underrepresented groups, (2) temporary "pop-up" clinics in neighborhoods highly impacted by COVID-19, (3) vulnerable population clinics, and (4) mobile vaccine vans. METHODS: We conducted a 6-month retrospective analysis of electronic health records (EHR) to describe the sociodemographic characteristics of individuals who scheduled appointments using the outreach strategies and characteristics associated with a greater likelihood of vaccine administration based on appointment completion. To help explain trends in the EHR data, we engaged 10 health system leaders and staff who spearheaded the outreach strategies in follow-up conversations to identify qualitative insights into what worked and why. RESULTS: Compared with traditional scheduling, all outreach strategies except vulnerable population clinics had higher vaccine appointment completion rates, including automated outreach (N = 3,734 [94.7%], p < 0.001), pop-up clinics (N = 4,391 [96.0%], p < 0.001), and mobile vans (N = 4,198 [99.1%], p < 0.001); and lower cancellation rates, including automated outreach (N = 166 [1.1%], p < 0.001), pop-up clinics (N = 155 [0.6%], p < 0.001), and mobile vans (N = 0 [0%], p < 0.001). Qualitative insights emphasized ongoing community partnerships and information resources in successful outreach. CONCLUSION: Vaccine equity outreach strategies improved the proportion of patients who scheduled and completed vaccination appointments among populations disproportionately impacted by COVID-19. Engaging community partners and equity-focused informatics tools can facilitate outreach. Lessons from these outreach strategies carry practical implications for health systems to amplify their health equity efforts.

Public Health Informatics and the Perioperative Physician: Looking to the Future.

The role of informatics in public health has increased over the past few decades, and the coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of aggregated, multicenter, high-quality, near-real-time data to inform decision-making by physicians, hospital systems, and governments. Given the impact of the pandemic on perioperative and critical care services (eg, elective procedure delays; information sharing related to interventions in critically ill patients; regional bed-management under crisis conditions), anesthesiologists must recognize and advocate for improved informatic frameworks in their local environments. Most anesthesiologists receive little formal training in public health informatics (PHI) during clinical residency or through continuing medical education. The COVID-19 pandemic demonstrated that this knowledge gap represents a missed opportunity for our specialty to participate in informatics-related, public health-oriented clinical care and policy decision-making. This article briefly outlines the background of PHI, its relevance to perioperative care, and conceives intersections with PHI that could evolve over the next quarter century.

A Pragmatic Informatics Approach to Develop Knowledge Tools for Supporting Cardiac Surgical Patients' Mental Health Needs.

A pragmatic informatics approach was developed to create knowledge tools for co-design of a new model of mental healthcare in cardiac surgery The real-world evidence generation leverages existing technological platforms and routine data collections plus tailored brief tools, surveys and qualitative data.

A FHIR Native Radiology Informatics Platform.

FHIR is a new standard that is rapidly being adopted in healthcare. We describe and implement a Radiology informatics platform (RIS) that is FHIR native and incorporates the ability to execute AI algorithms to aid with the interpretation of scans. Our design utilises the FHIR workflow pattern as an application programming interface with functionality provided by independent micro services thus granting flexibility and expandability.

Evaluating Informatics Competencies Requirements for Hospital Nurse Managers in Japan.

This study classifies the nursing informatics competency requirements for nurses and healthcare leaders in the United States according to each of the four levels listed in the "Management Ladder for Hospital Nurse Managers (JNA version)" published by the Japanese Nursing Association. Computer skills were included in Level I. Fifteen informatics knowledge items and four informatic competency items that could not be classified for the levels of the management ladder for nurse managers in Japan. This list of nursing informatics competencies, categorized according to the management levels of hospital nurse managers, can be used to provide nursing informatics training to them.

Designing an Informatics Infrastructure for a National Aged Care Medication Roundtable.

In the residential aged care sector medication management has been identified as a major area of concern contributing to poor outcomes and quality of life for residents. Monitoring medication management in residential aged care in Australia has been highly reliant on small, internal audits. The introduction of electronic medication administration systems provides new opportunities to establish improved methods for ongoing, timely and efficient monitoring of a range of medication indicators, made more meaningful by linking medication data with resident characteristics and outcomes. Benchmarking contemporary medication indicators provides a further opportunity for improvement and is most effective when indicator data are adjusted to take account of confounding factors, such as residents' characteristics and health conditions. Roundtables provide a structure for sharing and discussing indicator data in a trusted and supportive environment and encourage the identification of strategies which may be effective in improving medication management. This paper describes a new project to establish, implement and evaluate a National Aged Care Medication Roundtable.

Resilience Informatics for Public Health.

Resilience research is attracting increasing attention as stressors such as pandemics and climate change impact normal life worldwide. Informatics tools can play an important role in enhancing resilience of people, communities, and organizations. We present Resilience Informatics as a sub-discipline of resilience research and propose a conceptual framework for Resilience Informatics to aid in the development and effective deployment of informatics systems for resilience.

An Informatics Platform for the Management of Data for Australian Dementia Network (ADNeT) Initiative.

Alzheimer's disease and other dementias are becoming more prevalent and placing increasing burdens on the community. The ADNeT Screening and Trials initiative aims to improve research outcomes by identifying people with an increased risk of developing these diseases and directing them to suitable clinical trials. To support the initiative, we have developed a modular informatics platform utilizing private cloud deployment to securely manage operational and research data across six clinical sites.

Overview of the Knowledge Management Center for Illuminating the Druggable Genome.

The Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) project aims to aggregate, update, and articulate protein-centric data knowledge for the entire human proteome, with emphasis on the understudied proteins from the three IDG protein families. KMC collates and analyzes data from over 70 resources to compile the Target Central Resource Database (TCRD), which is the web-based informatics platform (Pharos). These data include experimental, computational, and text-mined information on protein structures, compound interactions, and disease and phenotype associations. Based on this knowledge, proteins are classified into different Target Development Levels (TDLs) for identification of understudied targets. Additional work by the KMC focuses on enriching target knowledge and producing DrugCentral and other data visualization tools for expanding investigation of understudied targets.

Informatics and Computational Approaches for the Discovery and Optimization of Natural Product-Inspired Inhibitors of the SARS-CoV-2 2'-O-Methyltransferase.

The urgent need for new classes of orally available, safe, and effective antivirals─covering a breadth of emerging viruses─is evidenced by the loss of life and economic challenges created by the HIV-1 and SARS-CoV-2 pandemics. As frontline interventions, small-molecule antivirals can be deployed prophylactically or postinfection to control the initial spread of outbreaks by reducing transmissibility and symptom severity. Natural products have an impressive track record of success as prototypic antivirals and continue to provide new drugs through synthesis, medicinal chemistry, and optimization decades after discovery. Here, we demonstrate an approach using computational analysis typically used for rational drug design to identify and develop natural product-inspired antivirals. This was done with the goal of identifying natural product prototypes to aid the effort of progressing toward safe, effective, and affordable broad-spectrum inhibitors of Betacoronavirus replication by targeting the highly conserved RNA 2'-O-methyltransferase (2'-O-MTase). Machaeriols RS-1 (7) and RS-2 (8) were identified using a previously outlined informatics approach to first screen for natural product prototypes, followed by in silico-guided synthesis. Both molecules are based on a rare natural product group. The machaeriols (3-6), isolated from the genus Machaerium, endemic to Amazonia, inhibited the SARS-CoV-2 2'-O-MTase more potently than the positive control, Sinefungin (2), and in silico modeling suggests distinct molecular interactions. This report highlights the potential of computationally driven screening to leverage natural product libraries and improve the efficiency of isolation or synthetic analog development.

Informatic challenges and advances in illuminating the druggable proteome.

The understudied members of the druggable proteomes offer promising prospects for drug discovery efforts. While large-scale initiatives have generated valuable functional information on understudied members of the druggable gene families, translating this information into actionable knowledge for drug discovery requires specialized informatics tools and resources. Here, we review the unique informatics challenges and advances in annotating understudied members of the druggable proteome. We demonstrate the application of statistical evolutionary inference tools, knowledge graph mining approaches, and protein language models in illuminating understudied protein kinases, pseudokinases, and ion channels.

Informatics guided FE design of bioactive titanium alloy/composite multi-layered dental implants.

A dental implant with three distinct layers, of titanium alloy at core, porous titanium alloy at the intermediate layer and titanium alloy hydroxyapatite composite at the outer layer, is designed to achieve low elastic modulus and adequate strength with bioactive surface. Artificial Neural Network (ANN) along with Rule of Mixture (ROM) is used to generate the objective functions for the Genetic Algorithm (GA) based multi-objective optimization for achieving the optimal designs, which are validated using Finite Element Analysis (FEA) simulations. The composition and processing parameters are correlated with the yield strength and elastic modulus of titanium alloy using ANN. The ANN models are generated to express the strength and effective modulus of the implant using ROM. To determine the optimal composition of titanium alloys, porous layers, and composite layers for a three-layer dental implant, multi-objective genetic algorithm is employed. The Pareto optimal solutions provide the guidelines for designing the implant. A few selected non-dominated solutions are used for studying the actual stress distribution at the bone-implant interface using FEA, and showed significant improvements compared to conventional implants.