Anwendungsbereiche von künstlicher Intelligenz im Kontext von One Health mit Fokus auf antimikrobielle Resistenzen

Die Gesundheit der Menschen steht vor einer Reihe neuer Herausforderungen, die maßgeblich durch den fortschreitenden Klimawandel, den demografischen Wandel und die Globalisierung angetrieben werden. Der One-Health-Ansatz basiert auf dem Verständnis, dass die Gesundheit von Menschen, Tieren und Umwelt eng verknüpft ist. Bei der Umsetzung von One Health in die Praxis ergibt sich die Notwendigkeit, in der Forschung diverse und heterogene Datenströme und -typen aus den verschiedenen Sektoren zu kombinieren und zu analysieren. Verfahren der künstlichen Intelligenz (KI) bieten dabei neue Möglichkeiten zur sektorübergreifenden Beurteilung von heutigen und zukünftigen Gesundheitsgefahren. Dieser Beitrag gibt einen Überblick über verschiedene Anwendungsbereiche von KI-Verfahren im Zusammenhang mit One Health und zeigt Herausforderungen auf. Am Beispiel der Ausbreitung antimikrobieller Resistenzen (AMR), die eine zunehmende globale Gefahr im One-Health-Kontext darstellt, werden bestehende und zukünftige KI-basierte Lösungsansätze zur Eindämmung und Prävention beschrieben. Diese reichen von neuartiger Arzneientwicklung und personalisierter Therapie über gezieltes Monitoring der Antibiotikanutzung in Tierhaltung und Landwirtschaft bis hin zu einer umfassenden Umwelt-Surveillance für zukünftige AMR-Risikobewertungen.Societal health is facing a number of new challenges, largely driven by ongoing climate change, demographic ageing, and globalization. The One Health approach links human, animal, and environmental sectors with the goal of achieving a holistic understanding of health in general. To implement this approach, diverse and heterogeneous data streams and types must be combined and analyzed. To this end, artificial intelligence (AI) techniques offer new opportunities for cross-sectoral assessment of current and future health threats. Using the example of antimicrobial resistance as a global threat in the One Health context, we demonstrate potential applications and challenges of AI techniques. This article provides an overview of different applications of AI techniques in the context of One Health and highlights their challenges. Using the spread of antimicrobial resistance (AMR), an increasing global threat, as an example, existing and future AI-based approaches to AMR containment and prevention are described. These range from novel drug development and personalized therapy, to targeted monitoring of antibiotic use in livestock and agriculture, to comprehensive environmental surveillance.Peer Reviewe

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease

\ua9 2023Background: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions. Methods: MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology. Findings: MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases. Conclusions: MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO). Funding: NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04

GA4GH Phenopackets: A Practical Introduction.

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases

GA4GH Phenopackets: A Practical Introduction

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases

Detection and Verification of Mammalian Mirtrons by Northern Blotting

microRNAs (miRNAs) have vital roles in regulating gene expression—contributing to major diseases like cancer and heart disease. Over the last decade, thousands of miRNAs have been discovered through high throughput sequencing-based annotation. Different classes have been described, as well as a great dynamic range of expression levels. While sequencing approaches provide insight into biogenesis and allow confident identification, there is a need for additional methods for validation and characterization. Northern blotting was one of the first techniques used for studying miRNAs, and remains one of the most valuable as it avoids enzymatic manipulation of miRNA transcripts. Blotting can also provide insight into biogenesis by revealing RNA processing intermediates. Compared to sequencing, however, northern blotting is a relatively insensitive technology. This creates a challenge for detecting low expressed miRNAs, particularly those produced by inefficient, non-canonical pathways. In this chapter, we describe a strategy to study such miRNAs by northern blotting that involves ectopic expression of both miRNAs and miRNA-binding Argonaute (Ago) proteins. Through use of epitope tags, this strategy also provides a convenient method for verification of small RNA competency to be loaded into regulatory complexes

Determination of Odor Detection Threshold in the Göttingen Minipig

The aim of the study was to examine the ability of Göttingen minipigs to acquire an olfaction-based operant conditioning task and to determine the detection threshold for ethyl acetate and ethanol. We used an automated olfactometer developed for rodents to train and test 14 pigs. Odor sampling and reliable responding were obtained after three to fifteen 160-trial sessions. Successful transfer of the task from ethyl acetate to ethanol was achieved in 1–4 sessions. Detection threshold for ethyl acetate varied between 10−2% and 10−6% v/v and for ethanol between 0.1% and 5 × 10−6% v/v. The results provide evidence that minipigs can successfully acquire 2-odorant discrimination using a food-rewarded instrumental conditioning paradigm for testing olfactory function. This olfactory discrimination paradigm provides reliable measures of olfactory sensitivity and thereby enables detection of changes in olfaction in a porcine model of Alzheimer's disease currently being developed

Receptor-targeted liposome-peptide-siRNA nanoparticles represent a novel and efficient therapeutic approach to prevent conjunctival fibrosis.

There is increasing evidence that the Myocardin-related transcription factor/Serum response factor (MRTF/SRF) pathway plays a key role in fibroblast activation and that knocking down MRTF can lead to reduced scarring and fibrosis. Here, we have developed a receptor-targeted liposome-peptide-siRNA nanoparticle as a non-viral delivery system for MRTF-B siRNA in conjunctival fibrosis. Using 50 nM siRNA, the MRTF-B gene was efficiently silenced by 76% and 72% with LYR and LER nanoparticles, respectively. The silencing efficiency was low when non-targeting peptides or siRNA alone or liposome-siRNA alone were used. LYR and LER nanoparticles also showed higher silencing efficiency than PEGylated LYR-P and LER-P nanoparticles. The nanoparticles were not cytotoxic using different liposomes, targeting peptides, and 50 nM siRNA. Three-dimensional fibroblast-populated collagen matrices were also used as a functional assay to measure contraction in vitro, and showed that MRTF-B LYR nanoparticles completely blocked matrix contraction after a single transfection treatment. In conclusion, this is the first study to develop and show that receptor-targeted liposome-peptide-siRNA nanoparticles represent an efficient and safe non-viral siRNA delivery system that could be used to prevent fibrosis after glaucoma filtration surgery and other contractile scarring conditions in the eye

A Developmental Perspective on Community Service in Adolescence

A substantial number of U.S. adolescents currently participate in community service and there is increased national interest in service programs. This article assesses the assumption of developmental benefits to service participants by critically reviewing 44 empirical studies. It offers a theoretical framework for understanding the findings by connecting them to identity development and delineating three pertinent concepts: agency, social relatedness, and moral-political awareness. These concepts are applied to studies that investigate: ( 1) the characteristics and motivations of participants, ( 2) the effects of service, and ( 3) the process of service. The findings support the conclusion that service activities which provide opportunities for intense experiences and social interactions are often associated with prosocial development. The findings also point to the need for more studies focused on particular service programs and on relationships between service providers and those served

Expression and Function of Serotonin 2A and 2B Receptors in the Mammalian Respiratory Network

Neurons of the respiratory network in the lower brainstem express a variety of serotonin receptors (5-HTRs) that act primarily through adenylyl cyclase. However, there is one receptor family including 5-HT2A, 5-HT2B, and 5-HT2C receptors that are directed towards protein kinase C (PKC). In contrast to 5-HT2ARs, expression and function of 5-HT2BRs within the respiratory network are still unclear. 5-HT2BR utilizes a Gq-mediated signaling cascade involving calcium and leading to activation of phospholipase C and IP3/DAG pathways. Based on previous studies, this signal pathway appears to mediate excitatory actions on respiration. In the present study, we analyzed receptor expression in pontine and medullary regions of the respiratory network both at the transcriptional and translational level using quantitative RT-PCR and self-made as well as commercially available antibodies, respectively. In addition we measured effects of selective agonists and antagonists for 5-HT2ARs and 5-HT2BRs given intra-arterially on phrenic nerve discharges in juvenile rats using the perfused brainstem preparation. The drugs caused significant changes in discharge activity. Co-administration of both agonists revealed a dominance of the 5-HT2BR. Given the nature of the signaling pathways, we investigated whether intracellular calcium may explain effects observed in the respiratory network. Taken together, the results of this study suggest a significant role of both receptors in respiratory network modulation