Titlebook: Host-Pathogen Interactions in Streptococcal Diseases; G. Singh Chhatwal Book 2013 The Editor(s) (if applicable) and The Author(s), under e

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ce (AI) models limit their reliability for critical decisions. This paper proposes a paradigm shift from conventional data-driven to causal model-driven decision-making, leveraging advancements in causal inference and large language models (LLMs). By applying the capabilities of generative AI, this

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Immunopathogenesis of Streptococcal Deep Tissue Infections,assive bacterial load at the tissue site, as well as virulence factors contributing to a local hyperinflammatory response are highlighted. A particular focus is on in vivo findings in patients that provide insight into host and bacterial factors that are expressed at the infected tissue site, and the mechanisms underlying tissue pathology.

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,Clinical Management of the Most Common Group A β-Hemolytic Streptococcal Infections,ikely that the current streptococcal problems will remain difficult to manage and will remain essentially unchanged until the broad implementation of a cost-effective group A streptococcal vaccine, likely some years in the future.

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Book 2013ck syndrome, as well as rheumatic fever and rheumatic heart disease as sequelae. Antibiotics alone have not been able to control the disease and in spite of many efforts an effective vaccine is not yet available. A prerequisite for novel and successful strategies for combating these bacteria is a co

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