Prognostic value of neutrophil/lymphocyte ratio and mean platelet volume/platelet ratio for 1-year mortality in critically ill patients

Several studies have reported that the neutrophil to lymphocyte ratio (NLR) and mean platelet volume (MPV) are associated with poor prognosis. This study investigated whether NLR and/or the MPV/platelet ratio could function as predictive markers of mortality in critically ill patients. We retrospectively reviewed 1,154 patients admitted to the intensive care unit (ICU) between January 2017 and December 2017. Patients were divided into 2 groups according to 1-year mortality. We compared the NLR and MPV/platelet ratio on each day of ICU admission. Patients were classified into tertiles based on their NLR and MPV/platelet ratios, and the incidence of 1-year mortality was compared. Kaplan-Meier survival curves were plotted to evaluate their potential as prognostic factors for 1-year mortality. The NLR and MPV/platelet ratio were higher in the non-survivor group than in the survivor group. The incidence of 1-year mortality was the highest in the third tertile for both the NLR and MPV/platelet ratio. The MPV/platelet ratio was an independent predictor for 1-year mortality based on the Kaplan-Meier survival analysis. Our data showed that the MPV/platelet ratio is a predictive factor for 1-year mortality in critically ill patients.11Nsciescopu

Cytokine-Related Effect of Buccal-Delivered Collagen Peptide Incorporated in Mucoadhesive Films to Improve Female Skin Conditions

Recently, interest in collagen products has increased in the industries However, collagen products that are taken orally have the problem of being degraded by digestive enzymes. Therefore, a collagen peptide buccal delivery film (C-BDF) was developed to enhance the absorption without destruction and a clinical trial was conducted. A C-BDF was developed as a double layer and the permeation of collagen peptide (CP) through swine mucosa was investigated. This clinical study was performed on 43 healthy women, who were divided into either a control (n = 21) or test group (n = 22), over the course of 4 weeks. Skin assessments analyzed the hydration, elasticity, and roughness. In addition, the production of peroxynitrite and IL-1α in RAW 264.7 cells in supernatant media was conducted. A total of 1 kDa of CP in BDF showed significantly stronger permeation through swine mucosa compared to 3 kDa of CP in BDF. The C-BDF significantly enhanced skin hydration, elasticity, and roughness, and it removed wrinkles with no side effects after 2 weeks of intake. In addition, the production of peroxynitrite and IL-1α after the treatment with CP was significantly increased. Therefore, this study showed that collagen peptides could be completely absorbed into mucosa via a buccal delivery system and homeopathic effects might occur

Extracellular vesicle-derived protein from Bifidobacterium longum alleviates food allergy through mast cell suppression

Background: The incidence of food allergies has increased dramatically during the last decade. Recently, probiotics have been studied for the prevention and treatment of allergic disease. Objective: We examined whether Bifidobacterium longum KACC 91563 and Enterococcus faecalis KACC 91532 have the capacity to suppress food allergies. Methods: B longum KACC 91563 and E faecalis KACC 91532 were administered to BALB/c wild-type mice, in which food allergy was induced by using ovalbumin and alum. Food allergy symptoms and various immune responses were assessed. Results: B longum KACC 91563, but not E faecalis KACC 91532, alleviated food allergy symptoms. Extracellular vesicles of B longum KACC 91563 bound specifically tomast cells and induced apoptosis without affecting T-cell immune responses. Furthermore, injection of family 5 extracellular solute-binding protein, a main component of extracellular vesicles, into micemarkedly reduced the occurrence of diarrhea in a mouse food allergy model. Conclusion: B longum KACC 91563 induces apoptosis of mast cells specifically and alleviates food allergy symptoms. Accordingly, B longum KACC 91563 and family 5 extracellular solute-binding protein exhibit potential as therapeutic approaches for food allergies.111414Nsciescopu

Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019

Background: The Korean Society of Thoracic Radiology (KSTR) recently constructed a nation-wide coronavirus disease 2019 (COVID-19) database and imaging repository, referred to the Korean imaging cohort of COVID-19 (KICC-19) based on the collaborative efforts of its members. The purpose of this study was to provide a summary of the clinico-epidemiological data and imaging data of the KICC-19. Methods: The KSTR members at 17 COVID-19 referral centers retrospectively collected imaging data and clinical information of consecutive patients with reverse transcription polymerase chain reaction-proven COVID-19 in respiratory specimens from February 2020 through May 2020 who underwent diagnostic chest computed tomography (CT) or radiograph in each participating hospital. Results: The cohort consisted of 239 men and 283 women (mean age, 52.3 years; age range, 11-97 years). Of the 522 subjects, 201 (38.5%) had an underlying disease. The most common symptoms were fever (n = 292) and cough (n = 245). The 151 patients (28.9%) had lymphocytopenia, 86 had (16.5%) thrombocytopenia, and 227 patients (43.5%) had an elevated CRP at admission. The 121 (23.4%) needed nasal oxygen therapy or mechanical ventilation (n = 38; 7.3%), and 49 patients (9.4%) were admitted to an intensive care unit. Although most patients had cured, 21 patients (4.0%) died. The 465 (89.1%) subjects underwent a low to standard-dose chest CT scan at least once during hospitalization, resulting in a total of 658 CT scans. The 497 subjects (95.2%) underwent chest radiography at least once during hospitalization, which resulted in a total of 1,475 chest radiographs. Conclusion: The KICC-19 was successfully established and comprised of 658 CT scans and 1,475 chest radiographs of 522 hospitalized Korean COVID-19 patients. The KICC-19 will provide a more comprehensive understanding of the clinical, epidemiological, and radiologic characteristics of patients with COVID-19.Y

Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study

BACKGROUND: An artificial intelligence (AI) model using chest radiography (CXR) may provide good performance in making prognoses for COVID-19. OBJECTIVE: We aimed to develop and validate a prediction model using CXR based on an AI model and clinical variables to predict clinical outcomes in patients with COVID-19. METHODS: This retrospective longitudinal study included patients hospitalized for COVID-19 at multiple COVID-19 medical centers between February 2020 and October 2020. Patients at Boramae Medical Center were randomly classified into training, validation, and internal testing sets (at a ratio of 8:1:1, respectively). An AI model using initial CXR images as input, a logistic regression model using clinical information, and a combined model using the output of the AI model (as CXR score) and clinical information were developed and trained to predict hospital length of stay (LOS) ≤2 weeks, need for oxygen supplementation, and acute respiratory distress syndrome (ARDS). The models were externally validated in the Korean Imaging Cohort of COVID-19 data set for discrimination and calibration. RESULTS: The AI model using CXR and the logistic regression model using clinical variables were suboptimal to predict hospital LOS ≤2 weeks or the need for oxygen supplementation but performed acceptably in the prediction of ARDS (AI model area under the curve [AUC] 0.782, 95% CI 0.720-0.845; logistic regression model AUC 0.878, 95% CI 0.838-0.919). The combined model performed better in predicting the need for oxygen supplementation (AUC 0.704, 95% CI 0.646-0.762) and ARDS (AUC 0.890, 95% CI 0.853-0.928) compared to the CXR score alone. Both the AI and combined models showed good calibration for predicting ARDS (P=.079 and P=.859). CONCLUSIONS: The combined prediction model, comprising the CXR score and clinical information, was externally validated as having acceptable performance in predicting severe illness and excellent performance in predicting ARDS in patients with COVID-19.Y