• 생명과학회지
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• 제32권8호
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• pp.589-594
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• 2022

이 연구에서 베툴린산이 STZ에 의해 유발된 고혈당 쥐에서 탄수화물 소화 효소의 활성을 억제하고 식후 고혈당을 감소시킬 수 있는지 여부를 알아보았다. 그 결과, 베툴린산이 α-글루코시다아제와 α-아밀라아제 활성에 강력한 억제 효과를 보여주었다. α-글루코시다아제와 α-아밀라아제에 대한 베툴린산의 IC₅₀는 각각 12.83± 6.81 및 18.32±3.24 μM으로, 이는 경구 혈당강하제인 acarbose의 IC₅₀ 보다 값이 낮아 베툴린산의 탄수화물 소화효소의 억제 활성이 높다는 것을 나타낸다. 당뇨쥐와 정상쥐에서 증가된 식후 혈당은 베툴린산을 투입한 고혈당군, 정상군 모두 대조군보다 유의하게 식후 혈당이 억제되었습니다. 30, 60, 120분에 각각 혈당을 측정하였을 떄, 당뇨쥐에서 베툴린산을 투여한 군의 혈당은 23.22±1.1, 24.38±1.31, and 21.05±1.36 μM 으로 대조군의 혈당인 24.64± 1.7, 27.22±1.58, and 26.36±1.40 μM 보다 유의하게 감소하였다. 당뇨쥐에서 베툴린산 투여한 군의 AUC도 대조군 쥐에 비해 유의하게 감소하였지만, acarbose를 투여한 군에 비해서는 더 많이 감소하지 않았다. 이러한 연구 결과는 베툴린산이 탄수화물 소화 효소의 강력한 억제제로의 가능성을 보여주어, 당뇨병 쥐의 식후 고혈당증을 개선할 수 있을 것이라 사료된다.

• Imaging Science in Dentistry
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• 제53권3호
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• pp.193-198
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• 2023

Purpose: Artificial intelligence (AI) is poised to play a major role in medical diagnostics. Periodontal disease is one of the most common oral diseases. The early diagnosis of periodontal disease is essential for effective treatment and a favorable prognosis. This study aimed to assess the effectiveness of AI in diagnosing periodontal bone loss through radiographic analysis. Materials and Methods: A literature search involving 5 databases (PubMed, ScienceDirect, Scopus, Health and Medical Collection, Dentistry and Oral Sciences) was carried out. A specific combination of keywords was used to obtain the articles. The PRISMA guidelines were used to filter eligible articles. The study design, sample size, type of AI software, and the results of each eligible study were analyzed. The CASP diagnostic study checklist was used to evaluate the evidence strength score. Results: Seven articles were eligible for review according to the PRISMA guidelines. Out of the 7 eligible studies, 4 had strong CASP evidence strength scores (7-8/9). The remaining studies had intermediate CASP evidence strength scores (3.5-6.5/9). The highest area under the curve among the reported studies was 94%, the highest F1 score was 91%, and the highest specificity and sensitivity were 98.1% and 94%, respectively. Conclusion: AI-based detection of periodontal bone loss using radiographs is an efficient method. However, more clinical studies need to be conducted before this method is introduced into routine dental practice.

• 대한간호학회지
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• 제53권4호
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• pp.468-479
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• 2023

Purpose: This study aimed to evaluate the use of the respiratory rate oxygenation (ROX) index, ROX-heart rate (ROX-HR) index, and saturation of percutaneous oxygen/fraction of inspired oxygen ratio (SF ratio) to predict weaning from high-flow nasal cannula (HFNC) in patients with respiratory distress in a pediatric intensive care unit. Methods: A total of 107 children admitted to the pediatric intensive care unit were enrolled in the study between January 1, 2017, and December 31, 2021. Data on clinical and personal information, ROX index, ROX-HR index, and SF ratio were collected from nursing records. The data were analyzed using an independent t-test, χ² test, Mann-Whitney U test, and area under the curve (AUC). Results: Seventy-five (70.1%) patients were successfully weaned from HFNC, while 32 (29.9%) failed. Considering specificity and sensitivity, the optimal cut off points for predicting treatment success and failure of HFNC oxygen therapy were 6.88 and 10.16 (ROX index), 5.23 and 8.61 (ROX-HR index), and 198.75 and 353.15 (SF ratio), respectively. The measurement of time showed that the most significant AUC was 1 hour before HFNC interruption. Conclusion: The ROX index, ROX-HR index, and SF ratio appear to be promising tools for the early prediction of treatment success or failure in patients initiated on HFNC for acute hypoxemic respiratory failure. Nurses caring for critically ill pediatric patients should closely observe and periodically check their breathing patterns. It is important to continuously monitor three indexes to ensure that ventilation assistance therapy is started at the right time.

• 한국산림과학회지
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• 제112권2호
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• pp.145-156
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• 2023

본 연구에서는 -18℃ 및 4℃에서 18년간 저장된 소나무 종자 963개에 대해 FT NIR 스펙트럼을 조사하여 7개 머신러닝 방법(XGBoost, Boosted Tree, Bootstrap Forest, Neural Networks, Decision Tree, Support Vector Machine, PLS-DA)을 이용한 종자발아 예측모델을 만들고, 그 성능을 비교하였다. XGBoost 및 Boosted Tree 모델의 예측성능이 가장 우수하였으며, 정확도, 오분류율 및 AUC 값은 각각 0.9722, 0.0278, 0.9735과 0.9653, 0.0347, 0.9647이었다. 2개 모델에서 종자발아 유무를 예측하는 데 있어 상대적 중요도가 높았던 54개 파수 변수들에 대한 파장대는 크게 6개(811~1,088 nm, 1,137~1,273 nm, 1,336~1,453 nm, 1,666~1,671 nm, 1,879~2,045 nm, 2,058~2,409 nm) 그룹으로 나눌 수 있었으며, 방향족 아미노산, 셀룰로스, 리그닌, 전분, 지방산 및 수분과 관련된 것으로 추정되었다. 이상의 결과를 종합할 때, 본 연구에서 얻어진 FT NIR 스펙트럼 데이터과 2개의 머신러닝 모델은 소나무 저장종자의 발아 유무를 정확도 96% 이상으로 예측할 수 있기에 장기저장 종자 유전자원의 비파괴적 활력검정에 유용하게 활용될 수 있을 것으로 생각된다.

• Journal of Chest Surgery
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• 제56권4호
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• pp.244-251
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• 2023

Background: Extracorporeal membrane oxygenation (ECMO) has been widely used in patients with cardiorespiratory failure. The serum albumin level is an important prognostic marker in critically ill patients. We evaluated the efficacy of using pre-ECMO serum albumin levels to predict 30-day mortality in patients with cardiogenic shock (CS) who underwent venoarterial (VA) ECMO. Methods: We reviewed the medical records of 114 adult patients who underwent VA-ECMO between March 2021 and September 2022. The patients were divided into survivors and non-survivors. Clinical data before and during ECMO were compared. Results: Patients' mean age was 67.8±13.6 years, and 36 (31.6%) were female. The proportion of survival to discharge was 48.6% (n=56). Cox regression analysis showed that the pre-ECMO albumin level independently predicted 30-day mortality (hazard ratio, 0.25; 95% confidence interval [CI], 0.11-0.59; p=0.002). The area under the receiver operating characteristic curve of albumin levels (pre-ECMO) was 0.73 (standard error [SE], 0.05; 95% CI, 0.63-0.81; p<0.001; cut-off value=3.4 g/dL). Kaplan-Meier survival analysis showed that the cumulative 30-day mortality was significantly higher in patients with a pre-ECMO albumin level ≤3.4 g/dL than in those with a level >3.4 g/dL (68.9% vs. 23.8%, p<0.001). As the adjusted amount of albumin infused increased, the possibility of 30-day mortality also increased (coefficient=0.140; SE, 0.037; p<0.001). Conclusion: Hypoalbuminemia during ECMO was associated with higher mortality, even with higher amounts of albumin replacement, in patients with CS who underwent VA-ECMO. Further studies are needed to predict the timing of albumin replacement during ECMO.

• Animal Bioscience
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• 제36권9호
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• pp.1336-1349
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• 2023

Objective: The study was conducted to screen differentially expressed miRNAs in sows at early pregnancy by high-throughput sequencing and explore its mechanism of action on embryo implantation. Methods: The blood serum of pregnant and non-pregnant Landrace×Yorkshire sows were collected 14 days after artificial insemination, and exosomal miRNAs were purified for high throughput miRNA sequencing. The expression patterns of 10 differentially expressed (DE) miRNAs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The qRT-PCR quantified the abundance of serum exosomal miR-192 in pregnant and control sows, and the diagnostic power was assessed by receiver operating characteristic (ROC) analysis. The target genes of DE miRNAs were predicted with bioinformatics software, and the functional and pathway enrichment analysis was performed on gene ontology and the Kyoto encyclopedia of genes and genomes terms. Furthermore, a luciferase reporter system was used to identify the target relation between miR-192 and integrin alpha 4 (ITGA4), a gene influencing embryo implantation in pigs. Finally, the expression levels of miRNAs and the target gene ITGA4 were analyzed by qRT-PCR, and western blot, with the proliferation of BeWo cells detected by cell counting kit-8 (CCK-8). Results: A total of 221 known miRNAs were detected in the libraries of the pregnant and non-pregnant sows, of which 55 were up-regulated and 67 were down-regulated in the pregnant individuals compared with the non-pregnant controls. From these, the expression patterns of 10 DE miRNAs were validated. The qRT-PCR analysis further confirmed a significantly higher expression of miR-192 in the serum exosomes extracted from pregnant sows, when compared to controls. The ROC analysis revealed that miR-192 provided excellent diagnostic accuracy for pregnancy (area under the ROC curve [AUC]=0.843; p>0.001). The dual-luciferase reporter assay indicated that miR-192 directly targeted ITGA4. The protein expression of ITGA4 was reduced in cells that overexpressed miR-192. Overexpression of miR-192 resulted in the decreased proliferation of BeWo cells and regulated the expression of cell cycle-related genes. Conclusion: Serum exosomal miR-192 could serve as a potential biomarker for early pregnancy in pigs. miR-192 targeted ITGA4 gene directly, and miR-192 can regulate cellular proliferation.

• 대한임상검사과학회지
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• 제55권2호
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• pp.113-120
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• 2023

고중성지방혈증-허리(hypertriglyceridemic-waist, HTGW) 표현형은 관상동맥질환 위험을 예측하는 것으로 알려져 있다. 본 연구는 고혈압자를 대상으로 HTGW 표현형과 대사이상 사이의 관련성을 평가하였다. 경기지역 종합병원에서 2018년 1월부터 2021년 12월까지 건강검진을 실시한 20세 이상 성인 고혈압자를 대상으로 단면연구를 시행하였다. HTGW 표현형은 중성지방 농도 ≥150 mg/dL, 허리둘레 남성 ≥90 cm, 여성 ≥85 cm로 정의되었다. 본 연구대상자의 HTGW 표현형 유병률은 17.9%였다. 연령과 성별, 체질량지수를 보정한 후 HTGW군의 위험비는 NTNW군과 비교하여 낮은 고밀도 지단백 콜레스테롤은 5.09 (95% 신뢰구간, 95% confidence interval [95% CI]: 3.545~7.309), 높은 저밀도 지단백 콜레스테롤은 1.68 (95% CI: 1.176~2.411), 높은 총콜레스테롤은 2.92 (95% CI: 2.009~4.235), 당뇨병은 3.39 (95% CI: 2.124~5.412), 고요산혈증은 1.85 (95% CI: 1.286~2.674)이었다. 대사증후군을 진단하기 위한 HTGW 표현형의 곡선하 면적값은 전체 대상자 0.849, 남성 0.858, 여성 0.890로 나타났다. 결론적으로 HTGW 표현형은 대사이상과 밀접한 관련이 있으며, 대사증후군이 있는 성인 고혈압자의 모니터링에 유용한 지표였다.

• 한국식생활문화학회지
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• 제22권1호
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• pp.157-165
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• 2007

This study was designed to evaluate the effects of fructose(F) or sucrose(S) and guar gum intake on carbohydrate and lipid metabolism in 15-week-old male Goto-Kakizaki(GK) rats. Fifty rats were randomly assigned to 5 groups which were different in carbohydrate(25% of carbohydrate) and fiber(5% w/w) sources. The carbohydrate(CHO) sources of each group were comstarch(control group, 100% of CHO), fructose with cellulose(F), fructose with guar gum(FG), sucrose with cellulose(S), and sucrose with guar gum(SG). Each group was fed exterimental diet for 4 weeks. We measured food intake, body weight gain, adipose tissues weight and organs weight. We conducted oral glucose tolerance test(OGTT) and measured plasma insulin concentration to examine carbohydrate metabolism. To evaluate lipid metabolism, we measured the lipid profile of plasma, liver and feces. Food intake and weight gain of FG or SG groups tended to be less than those of F or S groups. Perirenal and epididymal fat pad weights of SG group were significantly lower than those of S group and those of FG group tended to be lower than those of F group. In OGTT, blood glucose values of F or S groups were significantly higher than those of C group, and FG or SG groups tended to be lower than those of F or S groups during the experimental time. The area under the curve(AUC) of C group was significantly highest among the groups, AUC and plasma insulin concentration of FG or SG groups tended to be lower than those of F or S groups. Plasma and hepatic triglyceride (TG) of FG and SG groups were significantly lower than those of F and S groups, plasma and hepatic total lipid(TL) and total cholesterol(TC) of FG and SG groups tended to be lower than those of F and S groups. Fecal TL, TG and TC of FG or SG groups tended to be higher than those of F and S groups. In conclusion, intake of guar gum should improve carbohydrate and lipid metabolism in partial substitution of fructose or sucrose for cornstarch in GK rats.

• 한국환경복원기술학회지
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• 제26권5호
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• 한국시뮬레이션학회논문지
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• 제32권4호
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• pp.19-26
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• 2023

전국 대학생의 중도 탈락 비율의 증가는 학생 개인 뿐만 아니라 대학과 사회에 심각한 부정적 영향을 끼친다. 본 연구에서는 중도 탈락이 예상되는 학생을 사전에 식별하기 위하여, 각 대학의 학사관리 시스템에서 손쉽게 얻을 수 있는 학적 데이터를 기반으로 머신러닝 분야의 결정트리, 랜덤 포레스트, 로지스틱 회귀 및 딥러닝 기반의 중도 탈락 예측 모델을 구축하고, 그 성능을 비교·분석하였다. 분석 결과 로지스틱 회귀 기반 예측 모델의 재현율이 가장 높았으나 f-1 및 auc 값이 낮은 한계를 보였고, 랜덤 포레스트 기반의 예측 모델의 경우 재현율을 제외한 다른 모든 지표에서 가장 우수한 성능을 보였다. 또한 예측 기간에 따른 예측 모델의 성능을 확인하기 위하여 예측 기간을 단기(1개 학기 이내), 중기(2개 학기 이내) 및 장기(3개 학기 이내)로 나누어 분석해 본 결과, 장기 예측 시 가장 높은 예측력을 보였다. 본 연구를 통해 각 대학은 중도 탈락이 예상되는 학생들을 조기에 식별하고, 이들에 대한 집중 관리를 통해 중도 탈락 비율을 줄이며 나아가 대학 재정 안정화에 기여할 수 있을 것으로 기대된다.