Background : The therapeutic effects of surfactants on acute lung injury derive not only from their recruiting action on collapsed alveoli but also from their anti-inflammatory action in the alveolar sapce. This study evaluated the anti-inflammatory action of a surfactant in an acute lung injury model of rats by neutrophils were recollected from the BAL fluid and the NF-
These experiments were conducted to investigate the :actors influencing the systemic action of Dimethoate (O,O-dimethyl-S-(N-methylcarhamoylmethyl) photphorodithioate) to rice seeds and the phytotoxic effects on the seed germination. Dimethoate
This experiment was conducted to investigate the effects of varying levels of metabolizable energy (ME) and crude protein (CP) on growth performance and carcass characteristics in layer-type growing male chicks. Nine hundred 1-d-old Hy-Line Brown male chicks were randomly allocated to 30 pens in a
Background : Pleural effusion is one of the most common clinical manifestations associated with a variety of pulmonary diseases such as malignancy, tuberculosis, and pneumonia. However, there are no useful laboratory tests to determine the specific cause of pleural effusion. Therefore, an attempt was made to analyze the various types of pleural effusion and search for useful laboratory tests for pleural effusion in order to differentiate between the diseases, especially between a malignant pleural effusion and a non-malignant pleural effusion. Methods : 93 patients with a pleural effusion, who visited the Severance hospital from January 1998 to August 1999, were enrolled in this study. Ultrasound-guided thoracentesis was done and a confirmational diagnosis was made by a gram stain, bacterial culture, Ziehl-Neelsen stain, a mycobacterial culture, a pleural biopsy and cytology. Results : The male to female ratio was 56 : 37 and the average age was
Sesquiterpenoids are defined as
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (