With this 100% online Postgraduate diploma, you will master the most advanced and personalized therapeutic strategies to address infections caused by Multidrug-Resistant Bacteria”

According to a recent report by the European Center for Disease Prevention and Control, the prevalence of multidrug-resistant bacteria in hospital settings has increased significantly in the last decade. This phenomenon underscores the urgent need for nursing professionals to implement innovative strategies to address this growing threat. One example of these is Artificial Intelligence, which enables experts to analyze large volumes of data to identify patterns that indicate antibiotic resistance. This enables nurses to make a faster and more accurate diagnosis.

In response to this, TECHis implementing a cutting-edge Postgraduate diploma in Advanced Multidrug-Resistant Bacteria Strategies for Nursing. The academic itinerary will analyze innovative clinical methods such as High Throughput Sequencing, Nanoparticles or Antibacterial Vaccines. In this way, graduates will be able to quickly initiate the most effective treatments to reduce the spread of infections in healthcare environments. Likewise, the syllabus will delve into the most sophisticated techniques for the rational design of drugs, among which the new penicillins stand out. In line with this, the program will delve into how Artificial Intelligence can be used to combat bacterial resistance to antibiotics.

In terms of methodology, this university program has a 100% online format, easily accessible from any device with an Internet connection and without predetermined schedules. In this sense, TECHuses its disruptive Relearning teaching method, so that nurses can deepen their knowledge of the contents without resorting to techniques that involve extra effort, such as memorization.  The only thing that professionals will require is to have an electronic device with Internet access (such as a cell phone, tablet or computer) to access the most complete teaching materials on the market and enjoy a first class experience.

You will have the full support of the world's largest online academic institution, TECHwith the latest educational technology at your fingertips”

This Postgraduate diploma in Advanced Multidrug-Resistant Bacteria Strategies for Nursing contains the most complete and updated scientific program on the market. Its most notable features are:

• The development of practical cases presented by experts in Microbiology, Medicine and Parasitology
• The graphic, schematic and eminently practical contents with which it is conceived gather scientific and practical information on those disciplines that are indispensable for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

You will delve into how Antibacterial Vaccines prevent a wide variety of diseases caused by specific pathogenic bacteria” 

The program’s teaching staff includes professionals from the field who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities. 

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations. 

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the course. For this purpose, students will be assisted by an innovative interactive video system created by renowned and experienced experts.

Do you want to delve into the application of Artificial Intelligence in Microbiology? Achieve it with this complete program in only 540 hours” 

TECH's Relearning method will allow you to learn with less effort and more performance, involving you more in your professional specialization”   

Through this Postgraduate diploma, nurses will have a comprehensive understanding of the mechanisms by which bacteria develop resistance to antibiotics. The syllabus will address emerging strategies to deal with Multidrug-Resistant Bacteria, including Temporary Collateral Sensitization, Bacteriophages or Phage Therapy. Therefore, professionals will implement proactive measures in clinical settings to reduce the transmission of resistant bacteria. Likewise, the syllabus will delve into New Antimicrobial Molecules, which will allow nurses to considerably reduce the incidence of nosocomial infections.

You will incorporate the most advanced infection control strategies into your clinical practice and prevent the spread of Multidrug-Resistant Bacteria” 

Module 1. Emerging Strategies for Multidrug-Resistant Bacteria

1.1. CRISPR-Cas9 Gene Editing

1.1.1. Molecular Mechanism of Action
1.1.2. Applications

1.1.2.1. CRISPR-Cas9 as a Therapeutic Tool
1.1.2.2. Engineering of Probiotic Bacteria
1.1.2.3. Rapid Detection of Resistance
1.1.2.4. Elimination of Resistance Plasmids
1.1.2.5. Development of New Antibiotics
1.1.2.6. Safety and Stability

1.1.3. Limitations and Challenges

1.2. Temporary Collateral Sensitization (SCT)

1.2.1. Molecular Mechanism
1.2.2. Advantages and Applications of SCT
1.2.3. Limitations and Challenges

1.3. Gene Silencing

1.3.1. Molecular Mechanism
1.3.2. RNA Interference
1.3.3. Antisense Oligonucleotides
1.3.4. Benefits and Applications of Gene Silencing
1.3.5. Limitations

1.4. High-Throughput Sequencing

1.4.1. Stages of High-Throughput Sequencing
1.4.2. Bioinformatics Tools for Combating Multidrug-Resistant Bacteria
1.4.3. Challenges

1.5. Nanoparticles

1.5.1. Mechanisms of Action against Bacteria
1.5.2. Clinical Applications
1.5.3. Limitations and Challenges

1.6. Engineering of Probiotic Bacteria

1.6.1. Production of Antimicrobial Molecules
1.6.2. Bacterial Antagonism
1.6.3. Modulation of the Immune System
1.6.4. Clinical Applications

1.6.4.1. Prevention of Nosocomial Infections
1.6.4.2. Reducing the Incidence of Respiratory Infections
1.6.4.3. Adjunctive Therapy in the Treatment of Urinary Tract Infections
1.6.4.4. Prevention of Resistant Skin Infections

1.6.5. Limitations and Challenges

1.7. Antibacterial Vaccines

1.7.1. Types of Vaccines against Diseases Caused by Bacteria
1.7.2. Vaccines in Development against Major Multidrug-Resistant Bacteria
1.7.3. Challenges and Considerations

1.8. Bacteriophages

1.8.1. Mechanism of Action
1.8.2. Lytic Cycle of Bacteriophages
1.8.3. Lysogenic Cycle of Bacteriophages

1.9. Phage Therapy

1.9.1. Isolation and Transport of Bacteriophages
1.9.2. Purification and Handling of Bacteriophages in the Laboratory
1.9.3. Phenotypic and Genetic Characterization of Bacteriophages
1.9.4. Preclinical and Clinical Trials
1.9.5. Compassionate Use of Phages and Success Stories

1.10. Antibiotic Combination Therapy

1.10.1. Mechanisms of Action
1.10.2. Efficacy and Risks
1.10.3. Challenges and Constraints
1.10.4. Combined Antibiotic and Phage Therapy

Module 2. New Antimicrobial Molecules

2.1. New Antimicrobial Molecules

2.1.1. The Need for New Antimicrobial Molecules
2.1.2. Impact of New Molecules on Antimicrobial Resistance
2.1.3. Challenges and Opportunities in the Development of New Antimicrobial Molecules

2.2. Methods of Discovery of New Antimicrobial Molecules

2.2.1. Traditional Discovery Approaches
2.2.2. Advances in Screening Technology
2.2.3. Rational Drug Design Strategies
2.2.4. Biotechnology and Functional Genomics
2.2.5. Other Innovative Approaches

2.3. New Penicillins: New Drugs, their Future Role in Anti-Infective Therapeutics

2.3.1. Classification
2.3.2. Mechanism of Action
2.3.3. Antimicrobial Spectrum
2.3.4. Therapeutic Uses
2.3.5. Adverse Effects
2.3.6. Presentation and Dosage

2.4. Cephalosporins

2.4.1. Classification
2.4.2. Mechanism of Action
2.4.3. Antimicrobial Spectrum
2.4.4. Therapeutic Uses
2.4.5. Adverse Effects
2.4.6. Presentation and Dosage

2.5. Carbapenemics and Monobactams

2.5.1. Classification
2.5.2. Mechanism of Action
2.5.3. Antimicrobial Spectrum
2.5.4. Therapeutic Uses
2.5.5. Adverse Effects
2.5.6. Presentation and Dosage

2.6. Cyclic Glycopeptides and Lipopeptides

2.6.1. Classification
2.6.2. Mechanism of Action
2.6.3. Antimicrobial Spectrum
2.6.4. Therapeutic Uses
2.6.5. Adverse Effects
2.6.6. Presentation and Dosage

2.7. Macrolides, Ketolides and Tetracyclines

2.7.1. Classification
2.7.2. Mechanism of Action
2.7.3. Antimicrobial Spectrum
2.7.4. Therapeutic Uses
2.7.5. Adverse Effects
2.7.6. Presentation and Dosage

2.8. Aminoglycosides and Quinolones

2.8.1. Classification
2.8.2. Mechanism of Action
2.8.3. Antimicrobial Spectrum
2.8.4. Therapeutic Uses
2.8.5. Adverse Effects
2.8.6. Presentation and Dosage

2.9. Lincosamides, Streptogramins and Oxazolidinones

2.9.1. Classification
2.9.2. Mechanism of Action
2.9.3. Antimicrobial Spectrum
2.9.4. Therapeutic Uses
2.9.5. Adverse Effects
2.9.6. Presentation and Dosage

2.10. Rifamycins and other Developmental Antimicrobial Molecules

2.10.1. Rifamycins: Classification

2.10.1.2. Mechanism of Action
2.10.1.3. Antimicrobial Spectrum
2.10.1.4. Therapeutic Uses
2.10.1.5. Adverse Effects
2.10.1.6. Presentation and Dosage

2.10.2. Antibiotics of Natural Origin
2.10.3. Synthetic Antimicrobial Agents
2.10.4. Antimicrobial Peptides
2.10.5. Antimicrobial Nanoparticles

Module 3. Artificial Intelligence in Clinical Microbiology and Infectious Diseases

3.1. Artificial Intelligence (AI) in Clinical Microbiology and Infectious Diseases

3.1.1. Current Expectation of AI in Clinical Microbiology
3.1.2. Emerging Areas Interrelated to AI
3.1.3. Transversality of AI

3.2. Artificial Intelligence (AI) Techniques and other Complementary Technologies applied to Clinical Microbiology and Infectious Diseases

3.2.1. AI Logic and Models
3.2.2. Technologies for AI

3.2.2.1. Machine Learning
3.2.2.2. Deep Learning
3.2.2.3. Data Science and Big Data

3.3. Artificial Intelligence (AI) in Microbiology

3.3.1. AI in Microbiology: History and Evolution
3.3.2. AI Technologies that can be Used in Microbiology
3.3.3. Research Objectives of AI in Microbiology

3.3.3.1. Understanding Bacterial Diversity
3.3.3.2. Exploring Bacterial Physiology
3.3.3.3. Investigation of Bacterial Pathogenicity
3.3.3.4. Epidemiological Surveillance
3.3.3.5. Development of Antimicrobial Therapies
3.3.3.6. Microbiology in Industry and Biotechnology

3.4. Classification and Identification of Bacteria using Artificial Intelligence (AI)

3.4.1. Machine Learning Techniques for Bacterial Identification
3.4.2. Taxonomy of Multi-Resistant Bacteria using AI
3.4.3. Practical Implementation of AI in Clinical and Research Laboratories in Microbiology

3.5. Bacterial Protein Decoding

3.5.1. AI Algorithms and Models for Protein Structure Prediction
3.5.2. Applications in the Identification and Understanding of Resistance Mechanisms
3.5.3. Practical Application AlphaFold and Rosetta

3.6. Decoding the Genome of Multi-Resistant Bacteria

3.6.1. Identification of Resistance Genes
3.6.2. Genomic Big Data Analysis: AI-Assisted Sequencing of Bacterial Genomes
3.6.3. Practical Application Identification of Resistance Genes

3.7. Artificial Intelligence (AI) Strategies in Microbiology and Public Health

3.7.1. Infectious Outbreak Management
3.7.2. Epidemiological Surveillance
3.7.3. AI for Personalized Treatments

3.8. Artificial Intelligence (AI) to Combat Antibiotic Resistance in Bacteria

3.8.1. Optimizing Antibiotic Use
3.8.2. Predictive Models for the Evolution of Antimicrobial Resistance
3.8.3. Targeted Therapy Based on Development of New Antibiotics by AI

3.9. Future of Artificial Intelligence in Microbiology

3.9.1. Synergies between Microbiology and AI
3.9.2. Lines of AI Implementation in Microbiology
3.9.3. Long-Term Vision of the Impact of AI in the Fight against Multi-Drug Resistant Bacteria

3.10. Technical and Ethical Challenges in the Implementation of Artificial Intelligence (AI) in Microbiology

3.10.1. Legal Considerations
3.10.2. Ethical and Liability Considerations
3.10.3. Barriers to AI Implementation

3.10.3.1. Technical Barriers
3.10.3.2. Social Barriers
3.10.3.3. Economic Barriers
3.10.3.4. Cybersecurity

If you have set yourself the goal of renewing your knowledge, TECH gives you the opportunity to achieve this while combining it with your work responsibilities as a nurse. Enroll now!"