Harnessing computational tools of the digital era for enhanced infection control.

This paper explores the potential of artificial intelligence, machine learning, and big data analytics in revolutionizing infection control. It addresses the challenges and innovative approaches in combating infectious diseases and antimicrobial resistance, emphasizing the critical role of interdisciplinary collaboration, ethical data practices, and integration of advanced computational tools in modern healthcare.

Integrating Digital Health Solutions with Immunization Strategies: Improving Immunization Coverage and Monitoring in the Post-COVID-19 Era.

The COVID-19 pandemic underscored the critical importance of vaccination to global health security and highlighted the potential of digital health solutions to improve immunization strategies. This article explores integrating digital health technologies with immunization programs to improve coverage, monitoring, and public health outcomes. It examines the current landscape of digital tools used in immunization initiatives, such as mobile health apps, electronic health records, and data analytics platforms. Case studies from different regions demonstrate the effectiveness of these technologies in addressing challenges such as vaccine hesitancy, logistics, and real-time monitoring of vaccine distribution and adverse events. The paper also examines ethical considerations, data privacy issues, and the need for a robust digital infrastructure to support these innovations. By analyzing the successes and limitations of digital health interventions in immunization campaigns during and after the COVID-19 pandemic, we provide recommendations for future integration strategies to ensure resilient and responsive immunization systems. This research aims to guide policymakers, health professionals, and technologists in leveraging digital health to strengthen immunization efforts and prepare for future public health emergencies.

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.

The Efficacy of CO2 Vaginal Laser in the Treatment of Recurrent, Post-Coital and Interstitial Cystitis: A Multicentric Prospective Study.

Background: This multicentric prospective study was carried out at Fondazione Policlinico Universitario Campus Bio Medico and Ospedale di Stato of St. Marino Republic. Between 1 January 2019, and 31 December 2022, all pre- and post-menopausal women diagnosed with recurrent, post-coital, and interstitial cystitis at both centers were included in the study. The main aim of the study was to assess the effectiveness of vaginal CO2 laser treatment, alone or combined with intravesical hyaluronic acid instillations, in managing cystitis symptoms, such as dysuria, pollakiuria, and urgency, across the entire patient cohort. The secondary objective was to investigate the reduction in number of annual cystitis episodes post-treatment. Methods: Each woman underwent three to four sessions of micro-ablative CO2 vaginal laser treatment. A follow-up examination was conducted 12 months after the final laser session (up to December 2023), during which a post-treatment VAS assessment evaluated dysuria, daily pollakiuria, and urgency. The enrolled patients recorded the number of cystitis episodes experienced during the 12-month pre- and post-treatment period. Results: Results indicated the laser's efficacy in reducing the total number of cystitis episodes per year and an improvement in symptoms up to one year post-treatment. Greater efficacy of the CO2 laser treatment, particularly when combined with intravesical hyaluronic acid instillation, was observed in both pre- and post- menopausal women. Conclusions: Fractional CO2 laser therapy represents a safe and efficacious, non-hormonal approach for pre- and post-menopausal women diagnosed with recurrent, post-coital, and interstitial cystitis.

Transmission dynamics, complications and mitigation strategies of the current mpox outbreak: A comprehensive review with bibliometric study.

As the mankind counters the ongoing COVID-19 pandemic by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), it simultaneously witnesses the emergence of mpox virus (MPXV) that signals at global spread and could potentially lead to another pandemic. Although MPXV has existed for more than 50 years now with most of the human cases being reported from the endemic West and Central African regions, the disease is recently being reported in non-endemic regions too that affect more than 50 countries. Controlling the spread of MPXV is important due to its potential danger of a global spread, causing severe morbidity and mortality. The article highlights the transmission dynamics, zoonosis potential, complication and mitigation strategies for MPXV infection, and concludes with suggested 'one health' approach for better management, control and prevention. Bibliometric analyses of the data extend the understanding and provide leads on the research trends, the global spread, and the need to revamp the critical research and healthcare interventions. Globally published mpox-related literature does not align well with endemic areas/regions of occurrence which should ideally have been the scenario. Such demographic and geographic gaps between the location of the research work and the endemic epicentres of the disease need to be bridged for greater and effective translation of the research outputs to pubic healthcare systems, it is suggested.

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.