Nowadays, the field of microbiology is undergoing a revolutionary change due to the emergence of Artificial Intelligence (AI). AI is being used to analyze massive data in a predictable form, about the behavior of microorganisms, to solve microbial classification-related problems, exploring the interaction between microorganisms and the surrounding environment. It also helps to extract novel microbial metabolites which have been used in various fields like medical, food and agricultural industries. As the pace of innovation in Microbiology is accelerating, the use of AI in these industries will be beneficial. AI will not only show its extraordinary potential in expanding the market of antibiotics, food, and agriculture but also offer an eco-friendly, safer, and profitable solution to the respective industries. It would be challenging to search out specific features and discuss future research on AI in microbiology with a wide perspective. - Uncovering extended functions of AI in Microbiology. - Production and development of novel drug targets through AI. - Challenges for using and selecting appropriate AI tools in health, agriculture and food sector

Immunological Methods in Microbiology, Volume 47 in the Methods in Microbiology series, highlights new advances in the field, with this new volume presenting interesting chapters on Immunological Techniques in the Clinical laboratory, Immunologic Diagnosis of HIV and Opportunistic Infections, Combining Antigen Detection and Serology for the Diagnosis of Selected Infectious Diseases, Immunologic Detection of Lyme Disease and Related Borrelioses, Immunodetection of Bacteria Causing Brucellosis, Immunological Diagnostic Techniques Used to Identify and Type Pasteurella, Immunological Tests for Diarrhea caused by Diarrheagenic Escherichia coli Targeting Their Main Virulence Factors, and much more.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

The book Methods in Silkworm Microbiology is the first ever publication that provides in-depth reviews on the latest progresses about silkworm -pathogen interactions, diseases and management practices for sustainable development of sericulture. Different molecular and immunodiagnostic methods for the detection of pathogens have been comprehensively addressed. Most recent advancements on the role of Micro RNAs in silkworm and pathogen interactions are provided with suitable illustrations. Recent technological advances and emerging trends in exploring silkworm gut microbial communities towards translation research, particularly to understand microbiome functions have been highlighted. Information on various immune mechanisms of silkworm against invading pathogens is summarized. The book further highlights the silkworm gut microbiota as a potential source for biotechnological applications. Provide comprehensive reviews and valuable methods from the selected experts on the topic "Methods in silkworm microbiology/pathology" Provides latest information on application of genomics and transcriptomics to decipher silkworm gut microbial communities. Different molecular and immunodiagnostic methods for the detection of pathogens have been comprehensively addressed Provides up to date information on silkworm-pathogen interactions, different silkworm diseases and immune mechanisms

This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."

Skincare Anarchy, the beauty podcast that has taken the cosmetic industry by storm, with a collection of over 400 full-length interviews spotlighting the brains behind the beauty, is taking their features to the next level. YŪGEN, a hybrid publication of beauty editorial, interview features, and a peer-reviewed medical journal, is a fully interactive, magazine-like e-pub. Best of all, volume 1 is fully open access! “This is our testament to the brains behind the beauty” (Dr. Ekta). Sign up for first access via the Skincare Anarchy Email 📧 List (https://linktr.ee/Skincareanarchy (https://linktr.ee/Skincareanarchy))! Accepting PR pitches for future volumes, and to inquire about coming on our podcast Skincare Anarchy! Email: [email protected]

Nowadays, the field of microbiology is undergoing a revolutionary change due to the emergence of Artificial Intelligence (AI). AI is being used to analyze massive data in a predictable form, about the behavior of microorganisms, to solve microbial classification-related problems, exploring the interaction between microorganisms and the surrounding environment. It also helps to extract novel microbial metabolites which have been used in various fields like medical, food and agricultural industries. As the pace of innovation in Microbiology is accelerating, the use of AI in these industries will be beneficial. AI will not only show its extraordinary potential in expanding the market of antibiotics, food, and agriculture but also offer an eco-friendly, safer, and profitable solution to the respective industries. It would be challenging to search out specific features and discuss future research on AI in microbiology with a wide perspective.

Type IV secretion systems (T4SSs) are highly versatile membrane-associated transporter machines used by Gram-negative and Gram-positive bacteria to deliver substrate molecules to a large variety of target cells. This volume summarizes our current knowledge of the large variety and structural diversity of T4SSs in pathogenic Escherichia, Agrobacterium, Legionella, Coxiella, Bartonella, Helicobacter, Enterococcus and other species. Divided into 13 chapters contributed by leading experts, it presents findings that significantly enhance our understanding of how various pathogens manipulate host cell functions to trigger bacterial uptake, promote intracellular growth, suppress defense mechanisms and of how bacteria spread antibiotic resistances, thus facilitating bacterial colonization and disease development. The book is an invaluable source of information for researchers and clinicians.