Objective We aimed to identify obstructive sleep apnea syndrome (OSAS) severity indices reflecting the anthropometric and metabolic characteristics of patients with OSAS. Methods A total of 76 patients with OSAS underwent nasal continuous positive airway pressure (nCPAP). We also investigated the effects of nCPAP on OSAS-associated muscle sympathetic nerve activity (MSNA), risk for cardiovascular diseases, and insulin secretion and sensitivity. Results Among the OSAS severity indices, HbA1c was significantly correlated with the apnea-hypopnea index, whereas HOMA-beta, HOMA-IR, and hepatic insulin resistance were significantly correlated with % SpO<90%, independent of age, gender, and body mass index (BMI). Burst incidence of MSNA was independently associated with only a 3% oxygen desaturation index. nCPAP therapy significantly lowered the OSAS severity indices and reduced the burst rate, burst incidence, and heart rate. Conclusion The OSAS severity indices reflecting apnea/hypopnea are associated with glycemic control, whereas those reflecting hypoxia, particularly % SpO<90%, are associated with hepatic insulin resistance independent of obesity. Both types of OSAS severity indices, especially the 3% oxygen desaturation index (reflecting intermittent hypoxia), are independently associated with MSNA, which is dramatically lowered with the use of nCPAP therapy. These findings may aid in interpreting each OSAS severity index and understanding the pathophysiology of OSAS in clinical settings.
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http://dx.doi.org/10.2169/internalmedicine.3005-19 | DOI Listing |
Viruses
December 2024
Department of Experimental and Clinical Medicine, University of Florence, Viale Morgagni 48, I-50134 Florence, Italy.
Background: Understanding the interference patterns of respiratory viruses could be important for shedding light on potential strategies to combat these human infectious agents.
Objective: To investigate the possible interactions between adenovirus type 2 (AdV2), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A/H1N1 pandemic (H1N1pdm09) using the A549 cell line.
Methods: Single infections, co-infections, and superinfections (at 3 and 24 h after the first virus infection) were performed by varying the multiplicity of infection (MOI).
Viruses
December 2024
Infectious Diseases Laboratory, Centro de Investigación en Ciencias de la Salud y Biomedicina, Universidad Autónoma de San Luis Potosí, San Luis Potosi 78210, Mexico.
Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections in young children. During the COVID-19 pandemic, a significant change in the epidemiology of RSV and other viruses occurred worldwide, leading to a reduction in the circulation of these infectious agents. After the pandemic, the resurgence of seasonal respiratory viruses occurred, but some features of these infections contrast to those registered prior to the pandemic.
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December 2024
1st Department of Critical Care and Pulmonary Medicine, School of Medicine, National and Kapodistrian University of Athens, "Evangelismos" General Hospital, 10676 Athens, Greece.
Hypercoagulation is central to the pathogenesis of acute and post-acute COVID-19. This prospective observational study explored whether rotational thromboelastometry (ROTEM), a method that unveils coagulation status, predicts outcomes of hospitalized patients with COVID-19 pneumonia. We investigated 62 patients using ROTEM that was conducted at enrollment, clinical deterioration, discharge and follow-up visits 1 and 3 months post-discharge.
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December 2024
Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, USA.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in multiple animal species, including white-tailed deer (WTD), raising concerns about zoonotic transmission, particularly in environments with frequent human interactions. To understand how human exposure influences SARS-CoV-2 infection in WTD, we compared infection and exposure prevalence between farmed and free-ranging deer populations in Florida. We also examined the timing and viral variants in WTD relative to those in Florida's human population.
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November 2024
Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
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