Surveys on helminthic fauna of the nutria, Myocastor coypus, have seldom been performed in the Republic of Korea. In the present study, we describe Strongyloides myopotami (Secernentea: Strongyloididae) recovered from the small intestine of feral nutrias. Total 10 adult nutrias were captured in a wetland area in Gimhae-si (City), Gyeongsangnam-do (Province) in April 2013. They were transported to our laboratory, euthanized with ether, and necropsied. About 1,300 nematode specimens were recovered from 10 nutrias, and some of them were morphologically observed by light and scanning electron microscopies. They were 3.7-4.7 (4.0+/-0.36) mm in length, 0.03-0.04 (0.033) mm in width. The worm dimension and other morphological characters, including prominent lips of the vulva, blunted conical tail, straight type of the ovary, and 8-chambered stoma, were all consistent with S. myopotami. This nematode fauna is reported for the first time in Korea.
Animals ; Republic of Korea/epidemiology ; Rodent Diseases/epidemiology/*parasitology ; Rodentia ; Strongyloides/*isolation & purification ; Strongyloidiasis/epidemiology/parasitology/*veterinary

Three echinostome species, i.e., Patagifer bilobus, Petasiger neocomense, and Saakotrema metatestis, are newly recorded in the trematode fauna of the Republic of Korea. They were recovered from 3 species of migratory birds (Platalea minor, Podiceps cristatus, and Egretta garzetta), which were donated by the Wildlife Center of Chungbuk (WCC) and the Conservation Genome Resource Bank for Korean Wildlife (CGRB). Only 1 P. bilobus specimen was recovered from the intestine of a black-faced spoonbill (P. minor), and characterized by the bilobed head crown with a deep dorsal incision and 54 collar spines. Twenty P. neocomense were recovered from the intestine of a great crested grebe (P. cristatus), and they had a well-developed head crown with 19 spines and 2 testes obliquely located at the posterior middle of the body. Total 70 S. metatestis were collected from the bursa of Fabricius of 1 little egret (E. garzetta). It is characterized by stout tegumental spines covered in the entire leaf-shaped body, posterior extension of the uterus, presence of the uroproct and a well-developed head crown with 12 pairs of collar spines on each side. By the present study, these 3 echinostome species are newly added to the trematode fauna in Korea.
Animals ; Bird Diseases/epidemiology/*parasitology ; Birds ; Echinostoma/anatomy & histology/*classification/*isolation & purification ; Echinostomiasis/epidemiology/parasitology/*veterinary ; Female ; Male ; Republic of Korea/epidemiology ; Species Specificity

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.