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빅데이터 기반 치주질환 예측모델 개발 및 임상검증
No full textMasterI. 서론 1
가. 연구 배경 1
1. 인공지능과 빅데이터를 활용한 치의학 연구 1
2. 치주질환 진단 및 예방의 중요성 2
나. 연구의 필요성 4
1. 치주질환의 예측을 위한 임상 측정 방식의 한계 4
2. 인공지능을 활용한 치주질환의 예측 5
3. 빅데이터 기반의 치주질환 예측모델 6
다. 연구의 목적 7
II. 연구대상 및 방법 8
가. 연구계획 및 연구대상 선정 8
1. 연구 디자인 및 개요 8
2. 국민건강영양조사 자료 9
3. 경기도의료원 임상자료 9
나. 연구방법 11
1. 통계적 상관관계 분석 및 치주질환 유발인자 추출 11
2. 임상데이터 수집 13
3. 치주질환 예측모델 개발 17
4. 예측모델 성능 평가 19
5. 치주질환의 예후 예측 21
III. 결과 22
가. 기초 상관관계 분석 22
나. 데이터기반 치주질환 예측모델 평가 빅데이터를 이용한 내부검증 25
1. 모델 알고리즘별 예측 성능 비교 25
2. 모델 알고리즘별 예측 안정성 비교 27
3. 예측모델의 인자 중요도 분석 28
다. 데이터기반 치주질환 예측모델 평가 임상데이터를 이용한 외부검증 30
1. 모델 알고리즘별 예측 성능 및 재현성 비교 30
2. 기타 치주질환 임상 인자 예측 32
라. 기존 방식과 데이터기반 예측모델의 비교 분석 34
1. 치주질환 예측 성능 비교 34
2. 치주질환 예측 재현성 비교 35
IV. 고찰 36
가. 빅데이터 및 인공지능 기반 치주질환 예측모델의 효용성 36
나. 치주질환 유발인자의 위험도 분석 39
다. 치주질환 예측모델의 활용 방안 40
라. 본 연구의 중요성 및 한계점 42
V. 결론 44
참고문헌 45
부록 (APPENDIX) 51
ABSTRACT 5
한국 소아, 청소년 음료 섭취량 실태와 치아 우식 상태의 관련성
No full textMaster제 1 장 서론 1
제 2 장 이론적 배경 3
가 소아, 청소년 식이 영양 3
나 당과 치아우식증 4
다 국내와 국외 당류 섭취기준 및 실태 5
라 음료 5
마 코로나19 정의 및 전, 후의 외식 변화 6
제 3 장 연구 방법 8
가 연구 대상 8
나 연구 도구 8
1 연구 대상자의 인구, 사회학적 특성과 연구 대상자의 성별, 나이에 따른 당 섭취량 8
2 식생활 조사에서 음료의 종류와 섭취 빈도(섭취량)에 대한 조사 9
3 치아 우식 상태 9
4 연령, 성별에 따른 영양 교육 여부 & 영양표시 이용 여부 9
5 외식(배달) 횟수와 음료 섭취 빈도, 섭취량 미치는 영향 10
다 통계 분석 방법 10
제 4 장 결과 11
가 통계 분석 결과 11
1 연구 대상자의 인구, 사회학적 특성 11
2 연구 대상자의 성별, 나이에 따른 당 섭취량 평균 비교 12
3 음료별 섭취 빈도와 섭취량 13
4 음료별 섭취 빈도에 따른 성별, 나이 관련성 18
5 코로나19 ( 19년, 20년) 음료 섭취 변화 22
6 성별에 따른 영양 교육 여부와 영양표시 이용 여부 차이 24
7 나이에 따른 영양 교육 여부와 영양표시 이용 여부 차이 25
8 외식(배달) 빈도수에 따라 음료 섭취 빈도, 음료 섭취량의 영향 26
9 치아 우식과 음료 섭취 빈도의 연관성 28
제 5 장 고찰 30
제 6 장 결론 32
3
상급종합병원 Z세대 간호사의 노인간호실천에 영향을 미치는 요인
No full textMasterⅠ 서론 1
A 연구의 필요성 1
B 연구의 목적 5
C 용어의 정의 6
Ⅱ 문헌고찰 8
A Z세대 간호사의 노인간호실천 8
B 간호사의 노인간호실천 영향요인 11
Ⅲ 연구방법 14
A 연구설계 14
B 연구대상 14
C 연구도구 15
D 자료수집방법 17
E 윤리적 고려 17
F 자료분석방법 18
Ⅳ 연구결과 19
A 대상자의 일반적 특성 19
B 대상자의 노인에 대한 지식, 노인돌봄태도, 감성지능 및 노인간호실천 수준 21
C 대상자의 일반적 특성에 따른 노인간호실천 차이 23
D 대상자의 노인에 대한 지식, 태도, 감성지능, 노인간호실천 간의 관계 25
E 대상자의 노인간호실천에 영향을 미치는 요인 27
Ⅴ 논의 29
Ⅵ 결론 및 제언 35
A 결론 35
B 제언 37
참고문헌 38
부 록 47
ABSTRACT 6
Early prediction of neurally mediated syncope in head-up tilt test using machine learning
No full textMasterⅠ. INTRODUCTION 1
A. Background 1
B. Objectives 5
Ⅱ. MATERIALS AND METHODS 6
A. Overview of study process 6
B. Study population 7
C. Head-up tilt (HUT) test protocol 10
D. Signal preprocessing 11
E. Cerebral autoregulation (CA) assesments 12
F. Observation time intervals 13
G. Feature extraction 15
H. Statistical analysis 17
I. Classification models 18
J. Software 19
Ⅲ. RESULTS 20
A. Statistical analysis of signals from the HUT test 20
1. Baseline characteristics 20
2. Comparison of hemodynamic signals in the early stages of the HUT test 21
3. Comparison of CA compensation in the early stages of the HUT test 23
B. Early prediction of neurally mediated syncope (NMS) using machine learning 29
Ⅳ. DISCUSSIONS 34
A. Statistical analysis of signals from the HUT test 34
1. Comparison of hemodynamic signals in the early stages of the HUT test 34
2. CA compensation in the early stages of the HUT test 35
B. Early prediction of NMS using machine learning 36
C. Limitations 38
Ⅴ. CONCLUSIONS 39
REFERENCES 40
국문요약 4
CDK4/6 inhibitors induce breast cancer senescence with enhanced anti-tumor immunogenic properties compared with DNA-damaging agents
Get PDFSince therapy-induced senescence (TIS) can either support or inhibit cancer progression, identifying which types of chemotherapeutic agents can produce the strongest anti-tumor TIS is an important issue. Here, cyclin-dependent kinase4/6 inhibitors (CDK4/6i)-induced senescence was compared to the TIS induced by conventional DNA-damaging agents. Despite both types of agents eliciting a similar degree of senescence, we observed increased expression of the senescence-associated secretory phenotype (SASP) and ligands related to pro-tumor immunity (IL6, CXCL8, TGFβ, CD274, and CEACAM1) and angiogenesis (VEGFA) mainly in TIS induced by DNA-damaging agents rather than by CDK4/6i. Additionally, although all agents increased the expression of anti-tumor immunomodulatory proteins related to antigen presentation (MHC-I, B2M) and T cell chemokines (CXCL9, 10, 11), CDK4/6i-induced senescent cells still maintained this expression at a similar or even higher intensity than cells treated with DNA-damaging agents, despite the absence of nuclear factor-kappa-B (NF-κB) and p53 activation. These data suggest that in contrast with DNA-damaging agents, which augment the pro-tumorigenic microenvironment via pro-inflammatory SASP, CDK4/6i can generate TIS only with antitumor immunomodulatory proteins
Second-line chemoimmunotherapy with nivolumab and paclitaxel in immune-related biomarker-enriched advanced gastric cancer: a multicenter phase Ib/II study
No full textBackground: We conducted a trial to evaluate the efficacy and safety of nivolumab and paclitaxel as second-line therapy for immune-related biomarker-enriched advanced gastric cancer (AGC). Methods: This open-label, single-arm, phase Ib/II study was a part of multi-institutional, biomarker-integrated umbrella study conducted in Korea. In phase Ib, patients received nivolumab (3 mg/kg) on Days 1 and 15 and paclitaxel (dose level 1, 70 mg/m2 or dose level 2, 80 mg/m2) on Days 1, 8, 15 every four weeks. In phase II, patients with Epstein–Barr virus-related, deficient mismatch repair or programmed cell death-ligand-1-positive AGC were enrolled. The primary endpoints were recommended phase II dose (RP2D, phase Ib) and progression-free survival (PFS, phase II). Secondary endpoints included objective response rate (ORR), overall survival (OS), safety, and exploratory biomarker analysis. Results: Dose level 2 was selected as RP2D. In phase II, 48 patients were enrolled. The median PFS and OS were 3.9 and 11.2 months, respectively. The ORR was 23.3%, and the median response duration was 16.7 months. Grade 3 or higher treatment-related adverse events, mainly neutropenia, occurred in 20 patients (41.7%). Targeted sequencing revealed that patients with RTK/RAS pathway alterations or the HLA-A02 supertype had better survival. Patients with elevated baseline interleukin-1 receptor antagonist levels had worse survival. Conclusions: Although the study did not meet its primary end point, nivolumab and paclitaxel for AGC demonstrated a durable response with manageable toxicity profiles. Genomic analysis or plasma cytokine analysis may provide information for the selection of patients who would benefit more from immunotherapy combined with chemotherapy
Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses
No full textBackground: Amyotrophic lateral sclerosis (ALS) is a serious neurodegenerative disorder affecting nerve cells in the brain and spinal cord that is caused by mutations in the superoxide dismutase 1 (SOD1) enzyme. ALS-related mutations cause misfolding, dimerisation instability, and increased formation of aggregates. The underlying allosteric mechanisms, however, remain obscure as far as details of their fundamental atomistic structure are concerned. Hence, this gap in knowledge limits the development of novel SOD1 inhibitors and the understanding of how disease-associated mutations in distal sites affect enzyme activity. Methods: We combined microsecond-scale based unbiased molecular dynamics (MD) simulation with network analysis to elucidate the local and global conformational changes and allosteric communications in SOD1 Apo (unmetallated form), Holo, Apo_CallA (mutant and unmetallated form), and Holo_CallA (mutant form) systems. To identify hotspot residues involved in SOD1 signalling and allosteric communications, we performed network centrality, community network, and path analyses. Results: Structural analyses showed that unmetallated SOD1 systems and cysteine mutations displayed large structural variations in the catalytic sites, affecting structural stability. Inter- and intra H-bond analyses identified several important residues crucial for maintaining interfacial stability, structural stability, and enzyme catalysis. Dynamic motion analysis demonstrated more balanced atomic displacement and highly correlated motions in the Holo system. The rationale for structural disparity observed in the disulfide bond formation and R143 configuration in Apo and Holo systems were elucidated using distance and dihedral probability distribution analyses. Conclusion: Our study highlights the efficiency of combining extensive MD simulations with network analyses to unravel the features of protein allostery
Deep learning–radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients
Get PDFThis study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT). A total of 1280 patients with NSCLC who underwent contrast-enhanced CT scans and EGFR mutation testing before treatment were selected for the final study. Regions of interest were segmented from the CT images to extract radiomics features and obtain tumor images. These tumor images were input into a convolutional neural network model to extract 512 image features, which were combined with radiographic features and clinical data to predict the EGFR mutation. The generalization performance of the model was evaluated using external institutional data. The internal and external datasets contained 324 and 130 EGFR mutants, respectively. Sex, height, weight, smoking history, and clinical stage were significantly different between the EGFR-mutant patient groups. The EGFR mutations were predicted by combining the radiomics and clinical features, and an external validation dataset yielded an area under the curve (AUC) value of 0.7038. The model utilized 1280 tumor images, radiomics features, and clinical characteristics as input data and exhibited an AUC of approximately 0.81 and 0.78 during the primary cohort and external validation, respectively. These results indicate the feasibility of integrating radiomics analysis with deep learning for predicting EGFR mutations. CT-image-based genetic testing is a simple EGFR mutation prediction method, which can improve the prognosis of NSCLC patients and help establish personalized treatment strategies
Persicaria senticosa extract mitigates ultraviolet B-induced photoaging by suppressing the mitogen-activated protein kinase/activator protein 1/matrix metalloproteinase 1 pathway in human keratinocytes and hairless mice
Get PDFUltraviolet (UV) irradiation has been identified as a key trigger for skin photoaging, characterized by the overproduction of matrix metalloproteinases (MMPs) and reactive oxygen species (ROS), along with the accelerated decomposition of extracellular matrix (ECM) proteins, ultimately contributing to the development of wrinkles. Persicaria senticosa (PS) extracts are recognized for their antioxidative properties and their importance in skin health. Nevertheless, there is a paucity of studies investigating the potential of PS in protecting the skin against photoaging. The present study aimed to assess the effectiveness of PS extracts in preventing photoaging and elucidating the molecular mechanisms involved in using immortalized human keratinocytes (HaCaT) and hairless mice. The major bioactive constituents of PS were identified as p-coumaric acid, isoquercitrin, quercetin-3-O-glucuronide, and quercetin. Aqueous extracts of PS exhibited the ability to mitigate UVB-induced cellular damage and diminished ROS generation in HaCaT cells. Moreover, treatment with PS effectively attenuated the upregulated expression of matrix metalloproteinase-1 (MMP-1) and collagen degradation induced by UVB exposure. The property of PS to counteract photoaging was related to its capacity to inhibit the UVB-induced phosphorylation of mitogen-activated protein kinase (MAPK) and suppress the subsequent activation of activator protein 1 (AP-1) signaling pathways. Moreover, in hairless mice exposed to UVB radiation, the application of PS significantly alleviated the development of skin wrinkles, diminished epidermal thickening, and mitigated collagen degradation. Notably, PS treatment resulted in the downregulation of the UVB-activated MAPK/AP-1/MMP-1 pathway in mouse skin tissues. These findings suggest that PS has the potential to serve as a therapeutic agent for treating photoaging, holding promises in both cosmeceutical and pharmaceutical applications
Relationship between Electronic Health Literacy and Self-Management in People with Type 2 Diabetes Using a Structural Equation Modeling Approach
No full textBackground: Electronic health (eHealth) literacy is a relatively new concept used to determine health outcomes. However, it is not well known how eHealth literacy relates to health outcomes such as diabetes self-management.
Purpose: This study was designed to examine the relationships among eHealth literacy, self-efficacy, social support, and self-management in people with Type 2 diabetes.
Methods: A cross-sectional design was used to examine secondary data from a field survey of people with Type 2 diabetes recruited from outpatient clinics from August to December 2021 ( N = 453). A structural equation model was used that first analyzed the measurement model using confirmatory factor analysis and then tested the hypothesized structural model to estimate the expected relationships among the study variables. The significance of the statistical estimates for the model was assessed based on the 95% bias-corrected bootstrap confidence interval from 5,000 bootstrap resamples.
Results: Significant, indirect relationships were found between eHealth literacy and self-management via self-efficacy (β = 0.26, B = 0.17, 95% CI [0.10, 0.24]) and via social support and, in turn, self-efficacy (β = 0.08, B = 0.05, 95% CI [0.04, 0.08]). eHealth literacy, social support, and self-efficacy together explained 58.1% of the variance in self-management.
Conclusion/implications for practice: This study provides new evidence regarding how eHealth literacy relates to self-management in people with Type 2 diabetes via two indirect pathways, including self-efficacy alone and social support and self-efficacy in series. An eHealth literacy program for self-management should be developed in clinical practice that includes strategies for inducing synergistic effects from self-efficacy and social support on self-management in people with Type 2 diabetes