Implications of Artificial Intelligence in Addressing Antimicrobial Resistance: Innovations, Global Challenges, and Healthcare's Future.

Antibiotic resistance poses a significant threat to global public health due to complex interactions between bacterial genetic factors and external influences such as antibiotic misuse. Artificial intelligence (AI) offers innovative strategies to address this crisis. For example, AI can analyze genomic data to detect resistance markers early on, enabling early interventions. In addition, AI-powered decision support systems can optimize antibiotic use by recommending the most effective treatments based on patient data and local resistance patterns. AI can accelerate drug discovery by predicting the efficacy of new compounds and identifying potential antibacterial agents. Although progress has been made, challenges persist, including data quality, model interpretability, and real-world implementation. A multidisciplinary approach that integrates AI with other emerging technologies, such as synthetic biology and nanomedicine, could pave the way for effective prevention and mitigation of antimicrobial resistance, preserving the efficacy of antibiotics for future generations.

Persistence of SARS-CoV-2 infection and viral intra- and inter-host evolution in COVID-19 hospitalized patients.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) persistence in COVID-19 patients could play a key role in the emergence of variants of concern. The rapid intra-host evolution of SARS-CoV-2 may result in an increased transmissibility, immune and therapeutic escape which could be a direct consequence of COVID-19 epidemic currents. In this context, a longitudinal retrospective study on eight consecutive COVID-19 patients with persistent SARS-CoV-2 infection, from January 2022 to March 2023, was conducted. To characterize the intra- and inter-host viral evolution, whole genome sequencing and phylogenetic analysis were performed on nasopharyngeal samples collected at different time points. Phylogenetic reconstruction revealed an accelerated SARS-CoV-2 intra-host evolution and emergence of antigenically divergent variants. The Bayesian inference and principal coordinate analysis analysis showed a host-based genomic structuring among antigenically divergent variants, that might reflect the positive effect of containment practices, within the critical hospital area. All longitudinal antigenically divergent isolates shared a wide range of amino acidic (aa) changes, particularly in the Spike (S) glycoprotein, that increased viral transmissibility (K417N, S477N, N501Y and Q498R), enhanced infectivity (R346T, S373P, R408S, T478K, Q498R, Y505H, D614G, H655Y, N679K and P681H), caused host immune escape (S371L, S375F, T376A, K417N, and K444T/R) and displayed partial or complete resistance to treatments (G339D, R346K/T, S371F/L, S375F, T376A, D405N, N440K, G446S, N460K, E484A, F486V, Q493R, G496S and Q498R). These results suggest that multiple novel variants which emerge in the patient during persistent infection, might spread to another individual and continue to evolve. A pro-active genomic surveillance of persistent SARS-CoV-2 infected patients is recommended to identify genetically divergent lineages before their diffusion.

Phylodynamic and Evolution of the Hemagglutinin (HA) and Neuraminidase (NA) Genes of Influenza A(H1N1) pdm09 Viruses Circulating in the 2009 and 2023 Seasons in Italy.

The influenza A(H1N1) pdm09 virus, which emerged in 2009, has been circulating seasonally since then. In this study, we conducted a comprehensive genome-based investigation to gain a detailed understanding of the genetic and evolutionary characteristics of the hemagglutinin (HA) and neuraminidase (NA) surface proteins of A/H1N1pdm09 strains circulating in Italy over a fourteen-year period from 2009 to 2023 in relation to global strains. Phylogenetic analysis revealed rapid transmission and diversification of viral variants during the early pandemic that clustered in clade 6B.1. In contrast, limited genetic diversity was observed during the 2023 season, probably due to the genetic drift, which provides the virus with a constant adaptability to the host; furthermore, all isolates were split into two main groups representing two clades, i.e., 6B.1A.5a.2a and its descendant 6B.1A.5a.2a.1. The HA gene showed a faster rate of evolution compared to the NA gene. Using FUBAR, we identified positively selected sites 41 and 177 for HA and 248, 286, and 455 for NA in 2009, as well as sites 22, 123, and 513 for HA and 339 for NA in 2023, all of which may be important sites related to the host immune response. Changes in glycosylation acquisition/loss at prominent sites, i.e., 177 in HA and 248 in NA, should be considered as a predictive tool for early warning signs of emerging pandemics, and for vaccine and drug development.

Mpox: An Overview of Pathogenesis, Diagnosis, and Public Health Implications.

Mpox, caused by viruses of the genus Orthopoxvirus, is an emerging threat to human and animal health. With increasing urbanization and more frequent interaction between humans and wild animals, the risk of Mpox transmission to humans has increased significantly. This review aims to examine in depth the epidemiology, pathogenesis, and diagnosis of Mpox, with a special focus on recent discoveries and advances in understanding the disease. Molecular mechanisms involved in viral replication will be examined, as well as risk factors associated with interspecific transmission and spread of the disease in human populations. Currently available diagnostic methods will also be discussed, with a critical analysis of their limitations and possible future directions for improving the accuracy and timeliness of diagnosis. Finally, this review will explore the public health implications associated with Mpox, emphasizing the importance of epidemiological surveillance, vaccination, and emergency preparedness to prevent and manage possible outbreaks. Understanding the epidemiology and control strategies for Mpox is critical to protecting the health of human and animal communities and mitigating the risk of interspecific transmission and spread of the disease.

The Genetic Landscape of Systemic Rheumatic Diseases: A Comprehensive Multigene-Panel Study Identifying Key Gene Polymorphisms.

Systemic rheumatic diseases, including conditions such as rheumatoid arthritis, Sjögren's syndrome, systemic sclerosis, and systemic lupus erythematosus, represent a complex array of autoimmune disorders characterized by chronic inflammation and diverse clinical manifestations. This study focuses on unraveling the genetic underpinnings of these diseases by examining polymorphisms in key genes related to their pathology. Utilizing a comprehensive genetic analysis, we have documented the involvement of these genetic variations in the pathogenesis of rheumatic diseases. Our study has identified several key polymorphisms with notable implications in rheumatic diseases. Polymorphism at chr11_112020916 within the IL-18 gene was prevalent across various conditions with a potential protective effect. Concurrently, the same IL18R1 gene polymorphism located at chr2_103010912, coding for the IL-18 receptor, was observed in most rheumatic conditions, reinforcing its potential protective role. Additionally, a further polymorphism in IL18R1 at chr2_103013408 seems to have a protective influence against the rheumatic diseases under investigation. In the context of emerging genes involved in rheumatic diseases, like PARK2, a significant polymorphism at chr6_161990516 was consistently identified across different conditions, exhibiting protective characteristics in these pathological contexts. The findings underscore the complexity of the genetic landscape in rheumatic autoimmune disorders and pave the way for a deeper understanding of their etiology and the possible development of more targeted and effective therapeutic strategies.

Global Measles Surveillance: Trends, Challenges, and Implications for Public Health Interventions.

Measles, a highly contagious disease primarily affecting children, carries serious health risks, including complications and mortality. Vaccination remains the most effective preventive measure against measles transmission. The COVID-19 pandemic has exacerbated challenges in surveillance and immunization efforts, leaving millions of people exposed to preventable diseases such as measles. Globally accelerated immunization campaigns are critical for achieving regional elimination goals and mitigating the risk of outbreaks. Our team has developed an open-access database for global measles monitoring, facilitating standardized data collection and analysis. The analysis of measles cases from 2011 to 2023 reveals fluctuating trends, with notable increases in Africa in 2019 and 2023, indicating potential gaps in control strategies. Using an automated signal detection tool developed by the European Centre for Disease Prevention and Control (ECDC) team, we identified significant variations between World Health Organization (WHO) regions, underscoring the importance of continuous monitoring to detect epidemiological changes early. These results underscore the need for robust surveillance systems and accelerated vaccination efforts to safeguard public health.

On the SARS-CoV-2 Variants.

The evolutionary dynamics of viruses, particularly exemplified by SARS-CoV-2 during the ongoing COVID-19 pandemic, underscore the intricate interplay between genetics, host adaptation, and viral spread. This paper delves into the genetic evolution of SARS-CoV-2, emphasizing the implications of viral variants on global health. Initially emerging from the Wuhan-Hu-1 lineage, SARS-CoV-2 rapidly diversified into numerous variants, each characterized by distinct mutations in the spike protein and other genomic regions. Notable variants such as B.1.1.7 (α), B.1.351 (ß), P.1 (γ), B.1.617.2 (δ), and the Omicron variant have garnered significant attention due to their heightened transmissibility and immune evasion capabilities. In particular, the Omicron variant has presented a myriad of subvariants, raising concerns about its potential impact on public health. Despite the emergence of numerous variants, the vast majority have exhibited limited expansion capabilities and have not posed significant threats akin to early pandemic strains. Continued genomic surveillance is imperative to identify emerging variants of concern promptly. While genetic adaptation is intrinsic to viral evolution, effective public health responses must be grounded in empirical evidence to navigate the evolving landscape of the pandemic with resilience and precision.