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Sofía Jaurrieta-Largo, José Pablo Miramontes-González, Luis Corral-Gudino, Miriam Gabella-Martín, Sofía Pérez-Arroyo, Ana M. Torres, Jorge Mateo, José Luis Pérez-Castrillón and Ricardo Usategui-Martín
Int. J. Mol. Sci.2025, 26(16), 7975; https://doi.org/10.3390/ijms26167975 (registering DOI) - 18 Aug 2025
The genetic background influences the outcomes of COVID-19. This study aimed to evaluate the incidence of polymorphisms in genes linked to the RAAS system, cytokine production, and vitamin D on COVID-19 severity, with the goal of gaining a deeper understanding of the genetic
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The genetic background influences the outcomes of COVID-19. This study aimed to evaluate the incidence of polymorphisms in genes linked to the RAAS system, cytokine production, and vitamin D on COVID-19 severity, with the goal of gaining a deeper understanding of the genetic etiology related to COVID-19. This study involved 338 COVID-19 patients and employed machine learning methods to identify the genetic variants that most significantly affect COVID-19 severity. The results revealed that polymorphisms in the IL6, IL6R, IL1α, IL1R, IFNγ, TNFα, CRP, VDR, VDBP, and ACE2 genes are the most significant genetic factors influencing COVID-19 prognosis, particularly in terms of the risks of COVID-19 pneumonia, mortality, rehospitalization, and associated mortality. The machine learning methods achieved an AUC of 0.86 for predicting COVID-19 pneumonia, mortality, and mortality related to rehospitalization, as well as an AUC of 0.85 for rehospitalization within the first year. These results confirm the crucial role of genetic background in COVID-19 prognosis, facilitating the identification of patients at increased risk. In summary, this research demonstrates that genetics-driven machine learning models can pinpoint patients at heightened risk by primarily focusing on genetic variants associated with ACE2, inflammation, and vitamin D.
Full article
Air pollution poses a significant threat to public health, particularly in urban and industrialized regions. This study investigates the relationship between air quality and the frequency of Emergency Medical Service (EMS) calls in the Małopolska Voivodeship of Poland between 2020 and 2023. Data
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Air pollution poses a significant threat to public health, particularly in urban and industrialized regions. This study investigates the relationship between air quality and the frequency of Emergency Medical Service (EMS) calls in the Małopolska Voivodeship of Poland between 2020 and 2023. Data from over 190 air quality sensors (PM10) were spatially aggregated using both hexagonal grids and administrative boundaries, while EMS call records were filtered to focus on cardiovascular and respiratory incidents. During 2020–2023, a total of 305,142 EMS calls were analyzed, and months with PM10 exceedances showed an average of 1.50 respiratory calls per 1000 residents compared to 1.19 in months without exceedances. Statistical analyses, including Kolmogorov-Smirnov tests and Pearson correlation, were applied to explore temporal and spatial associations. Results indicate a statistically significant increase in EMS calls during periods of elevated air pollution, with the strongest correlation observed for respiratory-related incidents. Comparative analyses between high- and low-pollution municipalities supported the observed relationships. Further analysis indicated that the COVID-19 pandemic may have partially confounded these associations, particularly for respiratory cases, though significant patterns remained even after accounting for pandemic peaks. While limitations related to data gaps and seasonal biases exist, the findings suggest that real-time air pollution data could inform better EMS resource allocation. This research highlights the potential of integrating environmental data into public health strategies to improve emergency response and reduce health risks in polluted regions.
Full article
Background/Objectives: Obesity is a major modifier of COVID-19 outcomes, contributing to increased disease severity and complications. This study aimed to assess the impact of obesity on clinical severity, pulmonary involvement, and in-hospital mortality among COVID-19 patients and to identify independent predictors of
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Background/Objectives: Obesity is a major modifier of COVID-19 outcomes, contributing to increased disease severity and complications. This study aimed to assess the impact of obesity on clinical severity, pulmonary involvement, and in-hospital mortality among COVID-19 patients and to identify independent predictors of severe disease. Methods: We conducted a retrospective cohort study of 3005 hospitalized adults with RT-PCR-confirmed COVID-19 between 1 January 2020 and 1 March 2023. Patients were stratified by obesity status (body mass index (BMI) ≥ 30 kg/m2). Clinical, comorbidity, imaging, and laboratory data, as well as vaccination status (vaccinated or unvaccinated), were collected. Multivariate regression and gradient boosting models were used to identify predictors of severe outcomes. Effect estimates are expressed as relative risks (RRs) with 95% confidence intervals (CIs). Results: Obese patients (n = 894) showed significantly higher rates of severe COVID-19 (31.7% vs. 22.4%, p < 0.001) and more extensive lung damage (>50% involvement: 27.9% vs. 22.0%, p < 0.001), with lower admission SpO2 (92.1 ± 4.0% vs. 94.2 ± 3.2%, p < 0.001). Hypoxemia (SpO2 < 90%) was more frequent in obese individuals. The relative risk (RR) for severe disease was 1.41 (95% CI 1.25–1.60), and for >50% lung involvement, it was 1.27 (95% CI 1.11–1.45). Age > 65 years was the strongest predictor of mortality, particularly in non-obese patients. Gradient boosting models outperformed logistic regression (AUC = 0.92 vs. 0.87). Conclusions: Obesity independently predicts severe COVID-19 and pulmonary impairment. These findings support obesity-based risk stratification for clinical management and public health interventions.
Full article
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Charity A. Nassuna, Fahim Yiga, Joweria Nakaseegu, Esther Amwine, Bridget Nakamoga, Noel Ayuro, Nicholas Owor, David Odongo, Jocelyn Kiconco, Thomas Nsibambi, Samuel Wasike, Ben Andagalu, Chelsea Harrington, Adam W. Crawley, Julius Ssempiira, Ray Ransom, Amy L. Boore, Barnabas Bakamutumaho, John T. Kayiwa and Julius J. Lutwama
Limited surveillance and laboratory testing for non-influenza viruses remains a challenge in Uganda. The World Health Organization (WHO) designated National Influenza Center (NIC) tested samples from patients with influenza-like illness (ILI) and severe acute respiratory infections (SARIs) during August 2022–February 2023. We leveraged
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Limited surveillance and laboratory testing for non-influenza viruses remains a challenge in Uganda. The World Health Organization (WHO) designated National Influenza Center (NIC) tested samples from patients with influenza-like illness (ILI) and severe acute respiratory infections (SARIs) during August 2022–February 2023. We leveraged the influenza sentinel surveillance system to detect other respiratory viruses (ORVs). Samples were tested using the US Centers for Disease Control and Prevention (CDC) influenza and SARS-CoV-2 multiplex and the FTDTM Respiratory Pathogens 21 assays using real-time reverse transcription polymerase chain reaction (RT-qPCR). A total of 687 (ILI = 471 (68.6%) and SARI = 216 (31.4%) samples were tested. The median age was 2 years (IQR: 1–25) for ILI and 6 years (IQR: 1–18) for SARI case definitions (p-value = 0.045). One or more respiratory pathogens were detected in 38.7% (n = 266) of all samples; 33 (12.4%) were selected for metagenomics sequencing and 8 (3%) for SARS-CoV-2 targeted sequencing. Respiratory pathogens were detected by sequencing in 23 of 33 (69.7%) samples. Our study provides insight into the usefulness of this surveillance system in conducting virological testing for other viruses and provides tools and evidence to monitor patterns and characteristics of viruses causing ILI/SARI, which will guide public health decisions and interventions in Uganda.
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Francesca Roncaglia, Lucia Mangone, Francesco Marinelli, Isabella Bisceglia, Maria Barbara Braghiroli, Valentina Mastrofilippo, Fortunato Morabito, Antonia Magnani, Antonino Neri, Lorenzo Aguzzoli and Vincenzo Dario Mandato
Background/Objectives: The COVID-19 pandemic has impacted cancer diagnosis and treatment. This study assessed the effects of the pandemic on the stage and delays between diagnosis and treatment in endometrial cancer. Methods: The study included 543 cases diagnosed between 2017 and 2023
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Background/Objectives: The COVID-19 pandemic has impacted cancer diagnosis and treatment. This study assessed the effects of the pandemic on the stage and delays between diagnosis and treatment in endometrial cancer. Methods: The study included 543 cases diagnosed between 2017 and 2023 in a population-based cancer registry. Data on stage, diagnostic procedures, treatments, and time to surgery (TTS) were compared across the pre-COVID (2017—2019), COVID (2020—2022), and post-COVID (2023) periods. Multiple regression analysis was used to identify factors influencing TTS. Results: During the three periods, stages I and II showed no variation, whereas a significant increase was recorded in stage III (7.5%, 9.5%, and 17.8%, respectively; p < 0.05), as well as a slight increase in grade 3 (15.4%, 13.6%, and 19.2%, respectively). A significant decrease in laparotomies (30.3%, 11.6%, and 11.0%, respectively; p < 0.01) and an increase in laparoscopies (60.1%, 78.1%, and 80.8%, respectively; p < 0.05) were observed. TTS decreased for interventions performed within 30 days (10.1%, 3.7%, and 1.4%, respectively; p < 0.01) and within 60 days (38.6%, 19.4%, and 6.9%, respectively; p < 0.01), while a significant increase was observed for >60 days (22.8%, 29.8%, and 37.0%, respectively; p < 0.05) and >90 days (7.5%, 23.1%, and 20.5%, respectively; p < 0.01). Multivariable analysis confirmed a reduction in TTS in the pre-COVID period (β −19.63; CI 95% −31.31; −7.95) and an increase in the post-COVID period (β 31.60; CI 95% 13.68; 49.53); while an increase was confirmed only for stage IV (β 48.80; CI 95% 23.15; 74.45). Conclusions: The COVID-19 pandemic has led to an increase in more advanced cancers and delays in surgery.
Full article
Despite the widespread use of vaccines against SARS-CoV-2, COVID-19 continues to pose global health challenges, requiring efficient drug screening and repurposing strategies. This study presents a novel hybrid framework that integrates deep learning (DL) with molecular docking to accelerate the identification of potential
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Despite the widespread use of vaccines against SARS-CoV-2, COVID-19 continues to pose global health challenges, requiring efficient drug screening and repurposing strategies. This study presents a novel hybrid framework that integrates deep learning (DL) with molecular docking to accelerate the identification of potential therapeutics. The framework comprises three crucial steps: (1) a previously developed DL model is employed to rapidly screen candidate compounds, selecting those with predicted interaction scores above a cut-off value of 0.8; (2) AutoDock Vina version 1.5.6 and LeDock version 1.0 are used to evaluate binding affinities, with a threshold of <−7.0 kcal·mol−1; and (3) predicted drug–protein binding sites are evaluated to determine their overlap with known active residues of the target protein. We first validated the framework using four experimentally confirmed COVID-19 drug–target pairs and then applied it to identify potential inhibitors of the SARS-CoV-2 main protease (MPro). Among 29 drug candidates selected based on antiviral, anti-inflammatory, or anti-cancer properties, only Enasidenib met all three selection criteria, showing promise as an MPro inhibitor. However, further experimental and clinical studies are required to confirm its efficacy against SARS-CoV-2. This work provides an interpretable strategy for virtual screening and drug repurposing, which can be readily adapted to other DL models and docking tools.
Full article
submission deadline 30 Aug 2025
| 3 articles
| Viewed by 2648
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Submission Open
Keywords: COVID-19; performance of health systems; healthcare delivery; performance indicators; health policy; decision making; healthcare management; crisis management; operations research; systems research
(This special issue belongs to the Section Health Policy)
submission deadline 31 Aug 2025
| 4 articles
| Viewed by 4868
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Submission Open
Keywords: antiviral design and discovery; natural product screening; natural products as a scaffold for semisynthetic antivirals; repurposing drugs; high-throughput screening; antiviral resistance; biophysical characterization of the interaction between antivirals and targets; combination of light and photosensitizers in antiviral discovery; cell-based and in vivo assays; in silico calculations
submission deadline 31 Aug 2025
| 7 articles
| Viewed by 22116
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Submission Open
Keywords: SARS-CoV-2 complications; SARS-CoV2 prognostic and predictive biomarkers; long COVID-19 and autoimmune disease; COVID-19 and microbiome; artificial intelligence
submission deadline 31 Aug 2025
| 15 articles
| Viewed by 37779
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Submission Open
Keywords: individual and social attitudes and awareness toward COVID-19; literacy (scientific; medical; vaccine; health); vaccine hesitancy; compliance with screening and mitigation rules; pandemic community resilience; multifaceted responses to the enduring COVID-19 pandemic
The first webinar in the series, held on 17 April 2020, saw both Prof. Dr. Antoine Flahault, Director of the Institute of Global Health, University of Geneva, Switzerland, and Prof. Dr. Evelyne Bischof, Associate Professor, Shanghai University of Medicine and Health Sciences, Shanghai, China and Research physician, University Hospital of Basel, Basel, Switzerland speak on this topic.
The second webinar in the series, entitled “Coronaviruses: history, replication, innate immune antagonism”, saw Prof. Dr. Susan R. Weiss, Professor of Microbiology, Perelman School of Medicine, University of Pennsylvania speak on this topic.
WEBINAR 3: Could the COVID-19 Crisis be the Opportunity to Make Cities Carbon Neutral, Liveable and Healthy
The third webinar in this series was presented by Prof. Dr. Mark Nieuwenhuijsen, a world leading expert in environmental exposure assessment, epidemiology, and health risk/impact assessment with a strong focus and interest on healthy urban living.
WEBINAR 4: COVID-19 - Global Supply Chains and the SDGs
For the fourth webinar of this series, Prof. Dr. Max Bergman, Dr. Dorothea Schostok and Prof. Dr. Patrick Paul Walsh gave a presentation on Global Supply Chains and the SDGs.
WEBINAR 5: The New Role of Family Physicians in Times of COVID-19
The fifth webinar of the COVID-19 Series saw Prof. Dr. Christos Lionis discuss the new role of family physicians that emerged during the COVID-19 pandemic.
WEBINAR 6: Survey on Symptoms/Signs, Protective Measures, Level of Awareness and Perception Regarding COVID-19 Outbreak among Dentists
In the sixth webinar of this series, Prof. Dr. Guglielmo Campus and Prof. Dr. Maria Grazia present and discuss the risk and the preventions that can and should be taken by dentists during this pandemic.
WEBINAR 7: Living with COVID-19: An Early Intervention Therapeutic Strategy to Control the Pandemic
The seventh webinar of the COVID-19 series, Dr. Hamid Merchant discussed the different therapeutic strategies that can be adopted in the early stages of the infection.
WEBINAR 8: Impact of COVID-19 on Routine Immunization, Reproduction and Pregnancy Outcome
For the eighth COVID-19 webinar, Prof. Dr. Jon Øyvind Odland discussed the effect that COVID-19 seems to have on pregnant women; whereas Prof. Dr. Giovanni Gabutti discussed the role of routine immunization as a way of fighting COVID-19.
