80 research outputs found
기체μμμμ μμΈνΈμλ―Έλ Ένμ λν μ°κ΅¬μ AFM μ μ΄μ©ν μλΆμ μ°κ΅¬
νμλ
Όλ¬Έ(μμ¬) --μμΈλνκ΅ λνμ :ννλΆ,2008. 2.Maste
Effects of arsenic on platelet activation through the induction of platelet shape change
νμλ
Όλ¬Έ (μμ¬)-- μμΈλνκ΅ λνμ : μ½νκ³Ό, 2015. 2. μ μ§νΈ.μ€κΈμ λΉμλ νκ²½ μ€μ λ리 μ‘΄μ¬νλ μμλ‘μ, μ£Όλ‘ μμ©μλ₯Ό ν΅νμ¬ μΈμ²΄μ λ
ΈμΆλλ€. λ§μ±μ μΈ λΉμ λ
ΈμΆμ΄ λ€μν μ¬νκ΄κ³ μ§νμ μ λ°νλ€λ μ¬μ€μ μνμ μΌλ‘ λ³΄κ³ λμ΄ μμΌλ©° μ΄λ¬ν μμΈ μ€μ νλλ‘ λΉμμ μν νμ μμ± μμ©μ λν΄ μ°κ΅¬κ° νλ°ν μ§ν μ€μ μμ§λ§ μμ§ μ νν κΈ°μ μ λ°νμ§μ§ μμλ€. ννΈ νμν μμ§μ μν νμ μμ± κΈ°μ μ μ¬λ¬ λ¨κ³μ κ±Έμ³μ μ§νλλλ° μΌλ°μ μΌλ‘ λ€μν μκ·Ήμ μν΄ νμ±νλ νμνμ κ·Έ ννκ° λ°λλ shape change κ³Όμ μ μλ°νλ©΄μ μμ§μ΄ νμ±λλ€. Shape change κ³Όμ μ νμ±νλ νμν λ΄ cytoskeletal proteinμ integrityκ° λ³ννλ©΄μ λ°μνλλ° μ΄λ¬ν shape change κ³Όμ μμ νμν λ΄ κ³Όλ¦½λ€μ΄ λΆλΉλκ³ integrinμ΄ νμ±νλλ©΄μ νμνμ μμ§μ΄ μ΄μ§λλ€.
λ³Έ μ°κ΅¬μμλ νμ μμ± λ° λ€μν μ¬νκ΄ μ§νμ κΈ°μ¬νλ νμνμ λμμΌλ‘ νμ¬ λΉμκ° νμνμ νμ±νμ shape change λ° νμ μμ±μ μμ©νλ κΈ°μ μ μ μνκ³ μ νμλ€. μ¬λμ νμ‘μΌλ‘λΆν° λΆλ¦¬ν Platelet rich plasmaμ Sodium Arseniteλ₯Ό κ°νμ¬ νμνμ νμ±νλ₯Ό μ λνμλ€. λΉμμ μν νμνμ νμ±ν ν¨κ³Όλ νμνμ ννμ μΈ λ³νλ₯Ό ν΅ν΄ νμΈνμλ€. λΉμμ μν νμνμ νμ±νμ κ΄μ¬νλ key proteinμ μ°ΎκΈ° μν΄ proteomic analysisλ₯Ό νμμΌλ©° μ΄λ₯Ό ν΅ν΄ λΉμμ μν΄ νμν λ΄ filamin A proteinμ μΈμ°νκ° μ μμ μΌλ‘ μ¦κ°νλ€λ κ²°κ³Όλ₯Ό μ»μλ€. Western blotμ ν΅ν΄ λΉμκ° filamin Aμ μΈμ°ν μ¦κ°νλ©° μ΄κ²μ΄ filamin Aμ μμ νμ κ΄μ¬νλ κ²μ νμΈνμκ³ μ΄λ¬ν filamin Aμ μμ νλ Glycoprotein(GP)IbΞ± unitκ³Όμ interaction μ ν΅ν΄ νμν λͺ¨μ λ³νμ μν₯μ μ£Όμλ€. GPIbΞ±λ λΉμ λλ μμ‘΄μ μΌλ‘ surface expressionμ΄ κ°μνμμΌλ©° Filamin Aμ ν¨κ» μΈν¬ μμͺ½μΌλ‘ μ΄λνμλ€.
Confocal microscopyλ₯Ό μ΄μ©νμ¬ λΉμκ° μ€μ λ‘ actin μ assemblyλ₯Ό μ‘°μ νλμ§ νμΈν κ²°κ³Ό λΉμμ μν΄ actin μ assemblyκ° λ³ννλ κ²μ νμΈν μ μμμΌλ©° actinμ assemblyμ κ΄μ¬νλ μμ μ‘°μ λ¨λ°±μ§μΈ small GTPase proteinμ νμ±μ μΈ‘μ ν κ²°κ³Ό λΉμμ μν΄ κ·Έ νμ±μ΄ κ°μνλ κ²μ νμΈνμλ€. Small GTPase proteinμ νμ λ¨κ³μμ actin polymerizationμ μ‘°μ νλ actin capping proteinμΈ cofilinμ κ²½μ°μλ κ·Έ νμ±μ΄ μκ°μ λ°λΌ λ³νλ©΄μ actin dynamicμ μν₯μ λ―ΈμΉλ κ²μΌλ‘ λνλ¬λ€. Actin dynamicμ΄ λ³νν¨μ λ°λΌ νμν Ξ±-granuleμ λΆλΉκ° μ¦κ°νλμ§ νμΈνκΈ° μν΄ p-selectinμ λ°νμ μΈ‘μ ν κ²°κ³Ό λΉμ λλ μμ‘΄μ μΌλ‘ p-selectinμ λ°νμ΄ μ¦κ°νμλ€. λΉμμ μν μ체μ μΈ νμν μμ§ ν¨κ³Όλ λνλμ§ μμμΌλ©° νμν agonistμΈ thrombinκ³Ό ADPμ μν νμν μμ§ ν¨κ³Όλ₯Ό λΉμκ° λλ μμ‘΄μ μΌλ‘ μ΄μ§μμΌ°λ€.
μ΄μμ κ²°κ³Όλ₯Ό μ’
ν©νλ©΄, λΉμλ νμνμ νμ±νμμΌ κ·Έ ννλ₯Ό λ³νμν€λ©° μ΄λ¬ν ννλ³νλ νμνμ Glycoprotein IbΞ± - Filamin Aμ relocalization λ° actin assemblyμ λ³νλ₯Ό ν΅ν΄ λνλλ κ²°κ³Όμμ μ μ μλ€. λΉμμ μν΄ ννμ μΈ λ³νλ₯Ό λνλ΄λ νμνμμ λΆμ°©λ¨λ°±μ§μΈ P-selectinμ λ°νμ΄ μ¦κ°νμμΌλ©° agonistμ μν νμ‘ μκ³ μμ©μ΄ μ΄μ§λμλ€. λ°λΌμ λ³Έ μ°κ΅¬κ²°κ³Όλ λΉμ λ
ΈμΆμ μν μ¬νκ΄κ³ μ§νμ λ°λ³ μμΈ μ€ νλλ‘ μ§λͺ©λκ³ μλ νμ μμ±μ μ€λͺ
νλ ν κ°μ§ κΈ°μ μΌλ‘ μ μλ μ μμ κ²μ΄λ€.μ΄ λ‘ β
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List of Figures β
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List of Abbreviations β
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μ λ‘ 1
μ€ ν λ°© λ² 5
μμ½ λ° antibodies 5
Platelet rich plasmaμ μ‘°μ 5
μ£Όμ¬μ μνλ―Έκ²½ (SEM)μ μ΄μ©ν νμν λͺ¨μ λ³ν κ΄μ°° 6
Proteomic analysis 6
Filamin A μ λ°ν λ° μΈμ°ν μΈ‘μ 6
GPIbΞ± λ° P-selectin λ°ν μΈ‘μ 7
GPIba λ° Filamin A redistribution κ΄μ°° 8
Confocal microscopyλ₯Ό μ΄μ©ν Actin assembly κ΄μ°° 8
Small GTPase protein activity μΈ‘μ 9
Platelet aggregation μΈ‘μ 10
ν΅κ³ μ²λ¦¬ 10
μ€ ν κ²° κ³Ό 11
κ³ μ°° 23
μ°Έ κ³ λ¬Έ ν 28
보 μΆ© μ λ£ 34
Abstract 36Maste
μ μ μμ λ° μ²μλ μ μ’ κ³¨ 골λ λΆν¬ λ° κ΄λ ¨ μμΈ
νμλ
Όλ¬Έ(μμ¬)--μμΈλνκ΅ λνμ :보건νκ³Ό 보건νμ 곡,2004.Maste
A Multilevel Analysis on the Factors Associated with Cancer Screening of Korea
μ°κ΅¬λͺ©μ : νκ΅μΈμ μ μκ²λ₯ μ κ΅κ°, μβ€λ, μβ€κ΅°β€κ΅¬ μμ€μμ μ°μΆνκ³ , νκ΅μΈμ μ μκ²κ³Ό κ΄λ ¨ μλ κ°μΈ λ° μ§μμμ€ μμΈμ νμ
νλ€. μ μκ²μ μν₯μ μ£Όλ κ°μΈ λ° μ§μμμΈμ ν¨κ³Όλ₯Ό νμΈνκ³ κ°μΈ λ° μ§μμμΈμ΄ νκ΅μΈμ μ μκ²λ₯ μ§μ κ° μ°¨μ΄μ μ£Όλ μν₯μ νμ
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μ°κ΅¬λ°©λ²: 2008λ
μ μνν μ§μμ¬ν건κ°μ‘°μ¬μμ ν보ν λ§ 30μΈ μ΄μ μ κ΅ λν νλ³Έ 152,558λͺ
μ μλ£λ₯Ό λΆμνμλ€. μ’
μλ³μμΈ μ μκ²λ₯ μ μ΅κ·Ό 2λ
κ° μ κ²μ§ κ²½νμΌλ‘ νμκ³ , λ
립λ³μ μ€ κ°μΈμμ€ λ³μλ μ€λμ¨μ μλ£μ΄μ© λͺ¨νμ λ°λΌ λ³μλ₯Ό μ μ νμλ€. λ
립λ³μ μ€ μβ€λμ μ§μμμ€ λ³μλ μ¬νλ°νμ§μ, μΈκ΅¬ 1μΈλΉ μ§μλ΄ μ΄μμ°, λ΄κ΅μΈ 100λͺ
λΉ μΈκ΅μΈ μ, μΈκ΅¬ λλΉ μμλ΄μ¬μ λΉμ¨, μΈκ΅¬ 1,000λͺ
λΉ μμ¬ μ, μΈκ΅¬ 10λ§ λͺ
λΉ λ³΄κ±΄κΈ°κ΄ μμ 6κ°λ₯Ό μ μ νμκ³ , λ
립λ³μ μ€ μβ€κ΅°β€κ΅¬μ μ§μμμ€ λ³μλ μ¬νλ°νμ§μ, μ£Όλ―Όλ±λ‘μΈκ΅¬ 1μΈλΉ μ§λ°©μΈλΆλ΄μ‘, λ΄κ΅μΈ 100λͺ
λΉ μΈκ΅μΈ μ, μΈκ΅¬ 1,000λͺ
λΉ μμ¬ μ, μΈκ΅¬ 10λ§ λͺ
λΉ λ³΄κ±΄κΈ°κ΄μμ 5κ°λ₯Ό μ μ νμλ€. λΉλλΆμ, μΉ΄μ΄μ κ³± κ²μ , μΈ΅ν μΉ΄μ΄μ κ³± κ²μ , μ§μ λ²μ μν μ°λ Ήνμ€ν, λ€μ€νκ·λΆμ, λ€μμ€ λ‘μ§μ€ν± νκ·λΆμμΌλ‘ νκ΅μΈμ μ μκ²λ₯ μ μ°μΆνκ³ μ μκ²λ₯ μ μ§μ κ° μ°¨μ΄μ κ΄λ ¨ μλ κ°μΈμμ€κ³Ό μ§μμμ€μ μμΈμ ν¨κ³Όλ₯Ό νμΈνμλ€.
μ°κ΅¬κ²°κ³Ό : νκ΅μΈμ μ΅κ·Ό 2λ
κ° μ μκ²λ₯ μ 43%μ΄μκ³ μ μκ²λ₯ μ μ§μ κ° μ°¨μ΄λ μ‘΄μ¬νλ€. μβ€λ μμ€μμ μ΅κ³ λ° μ΅μ μ μκ²λ₯ μ 보μ΄λ μ λΌλ¨λ(49.58%)μ μΈμ°κ΄μμ(38.8%) κ°μ μ°¨μ΄λ 10.78%pμκ³ , μβ€κ΅°β€κ΅¬ μμ€μμ μ΅κ³ λ° μ΅μ μ μκ²λ₯ μ 보μ΄λ κ²½λΆ μ²μ‘κ΅°(68.33%)μ κ²½λΆ μΈμ§κ΅°(20.87%) κ°μ μ°¨μ΄λ 47.46%pμλ€. μ°λ Ήνμ€ν μΈκ΅¬ 10λ§ λͺ
λΉ μμκ²μ μλ μ μ¬ν κ²°κ³Όλ₯Ό 보μλ€. λ€μ€νκ·λΆμκ³Ό λ€μμ€ λΆμ κ²°κ³Ό μ°κ΅¬μμ μ¬μ©λ κ°μΈλ³μλ€μ λͺ¨λ μ μκ²κ³Ό κ΄λ ¨μ΄ μμλλ° κ°μ₯ μ€λͺ
λ ₯μ΄ λμ λ³μλ 건κ°κ²μ§ κ²½νμ΄μλ€.
λ¨μ±μ μ μκ²λ₯ κ³Ό κ΄λ ¨ μλ μ§μ μμ€ λ³μλ 3κ°(μ¬νλ°νμ§μ, μΈκ΅¬ λλΉ μμλ΄μ¬μ λΉμ¨, λ΄κ΅μΈ 100λͺ
λΉ μΈκ΅μΈ μ), μ¬μ± λ° μ°κ΅¬λμμ μ 체μ μ μκ²λ₯ κ³Ό κ΄λ ¨ μλ μ§μμμ€ λ³μλ 1κ°(μ¬νλ°νμ§μ)λ‘ μμ΄νκ³ , λ³μλ€μ΄ λ¨μ±κ³Ό μ¬μ±μ μ μκ²λ₯ μ μ£Όλ μν₯μ κ°λλ μμ΄νλ€. μΒ·λ ꡬμ±μμ μ§μμ¬ν μ°Έμ¬λλ₯Ό λ리νλμΈκ΅¬ λλΉ μμλ΄μ¬μ λΉμ¨μ λ¨μ±μ μ μκ²λ₯ κ³Ό κ΄λ ¨μ΄ μμλ€. μΈκ΅¬ λλΉ μμλ΄μ¬μ λΉμ¨μ΄ 1% μ¦κ°νλ κ²½μ° ν΄λΉ μΒ·λ λ¨μ±μ μ μκ²λ₯ μ 32.1% μ¦κ°νκ³ μΈκ΅¬ λλΉ μμλ΄μ¬μ λΉμ¨μ μβ€λ κ° λ¨μ±μ μ μκ²λ₯ μ°¨μ΄λ₯Ό 33.8% μ λ μ€λͺ
νκ³ μμλ€. μβ€κ΅°β€κ΅¬μ κ΄λ ¨λ μ§μλ³μ μ€ μ§μμ μ¬νκ²½μ μ μμ€μ λ리νλ μ¬νλ°νμ§μλ λ¨μ±κ³Ό μ¬μ±μ μ μκ²κ³Ό κ΄λ ¨μ΄ μμκ³ μ§μμ¬νμ μμ μ±μ λ리νλ λ΄κ΅μΈ 100λͺ
λΉ μΈκ΅μΈ μλ λ¨μ±μ μ μκ²κ³Ό μ μν κ΄κ³μ μμλ€. μ¬νλ°νμ§μκ° ν λ¨μ μ¦κ°νλ κ²½μ°, μ¦ μ¬νλ°νμμ€μ΄ μ¦κ°νλ κ²½μ°, ν΄λΉ μβ€κ΅°β€κ΅¬ λ¨μ±μ μ μκ²μ 33.9% μ¦κ°νκ³ , λ΄κ΅μΈ 100λͺ
λΉ μΈκ΅μΈ μκ° 1λͺ
μ¦κ°νλ κ²½μ° ν΄λΉ μβ€κ΅°β€κ΅¬ λ¨μ±μ μ μκ²μ 8.4% κ°μνλ€. μ§λ¨ κ° λΆμ°λΉμ¨λΆμμ λ°λ₯΄λ©΄ λ λ³μλ λ¨μ±μ μ·ꡰ·ꡬ κ° μ μκ²λ₯ μ μ°¨μ΄λ₯Ό 10.19% λ§νΌ μ€λͺ
νκ³ μλ€. ννΈ, μ¬μ±μ μ μκ²κ³Ό κ΄λ ¨λ μΒ·λ μμ€ μ§μλ³μλ μμμΌλ©°, μ·ꡰ·ꡬ μμ€μμ μ¬νλ°νμ§μλ§ κ΄λ ¨μ΄ μμλ€. μ¬νλ°νμ§μκ° ν λ¨μ μ¦κ°νλ κ²½μ° μ¬μ±μ μ μκ²μ 17.8% μ¦κ°νκ³ μ¬νλ°νμ§μλ μ¬μ±μ μ·ꡰ·ꡬ κ° μ μκ²λ₯ μ μ°¨μ΄λ₯Ό 3.29%λ§νΌ μ€λͺ
νκ³ μμλ€. μ’
ν©νλ©΄ μ§μλ³μλ λ¨μ±κ³Ό μ¬μ±μκ² λ€λ₯Έ κ°λλ‘ μν₯μ μ£Όμλλ° λ¨μ±μ΄ μ¬μ±λ³΄λ€ μλμ μΌλ‘ μ§μμμΈμ μν₯μ λ§μ΄ λ°κ³ μμλ€.
κ²°λ‘ : νκ΅μΈμ μ μκ²μλ κ°μΈ λ° μ§μμμΈμ΄ λμμ μμ©νκ³ μμκ³ κ°μΈμ μ κ²μ§ μ΄νκ³Ό κ΄λ ¨λ λ³μλ€μ μ€λͺ
λ ₯μ λμμμ μ±λ³μ λ°λΌ μμ΄νκ² λνλκ³ μμλ€. μ μ±
λ΄λΉμλ€μ μ κ²μ§μ κ΄ν μλ‘μ΄ μ μ±
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μ κ²ν νλ κ²½μ° κ°μΈ λ° μ§μλ³μλ₯Ό μ’
ν©μ μΌλ‘ κ³ λ €ν μ κ·Όμ ν΄μΌ νλ€.Objectives: To calculate regular, two-year, cancer screening attendance rate of Korean in the level of nation, city/province, and county level. To identify the factors associated with regular cancer screening-attendance rate of Korean. To identify the community level factors associated with the gap in regular, two-year, cancer screening-attendance rate among counties in the same city/province.
Methods: The nationwide representative sample 152 558 adults thirty years of age and older with derived from 2008 Community Health Survey of Korea. The dependent variable of cancer screening was defined as cancer screening experience in recent two years. Explanatory variables of individual level are selected by Anderson Model. Six explanatory variables such as Social deprivation index, the number of foreigners per 100, gloss regional domestic product, the number of physician per 1 000, the number of public clinic per 100 000, and the rate of volunteers among citizen were selected in city/province level. Five explanatory variables including variables such as Social deprivation index, the number of foreigners per 100, the number of physician per 1 000, the number of public clinic per 100 000, and local tax per citizen were selected in the county level. Regular cancer screening attendance rate of Korean was calculated by frequency analysis, chi-square test, Cochran-Mantel-Haenzsel analysis, multiple regression analysis, and multilevel logistic regression analysis.
Results: Regular cancer screening-attendance rate of Korean was 43%. The gap in regular cancer screening-attendance rate existed among cities, provinces, and counties in the same city/province. Jeolla southern province (49.58%) has the highest regular cancer screening-attendance rate among 15 cities and provinces while Woolsan City (38.8%) the lowest. Chungsonggun (68.36%) has the highest regular cancer screening-attendance rate among 230 counties while Wooljingun (20.8%) the lowest.
All statistical analysis has been done by three group of all, male, and female. All of the individual factors dealt with this paper were associated with regular cancer screening attendance in those three groups. To be specific, the highly educated social position and high family income were significantly associated with regular cancer screening attendance. The strongest explanatory variable was whether regular checkup-attendance was taken or not.
Some of the community factors dealt with this paper were associated with regular cancer screening attendance. However, the significance of each variable was quite different between male and female. For male, the rate of volunteers among citizen was the only community factor associated with regular cancer screening attendance in city/province level and explains 33.8% of disparity of regular cancer screening attendance rate between city and province. Social deprivation index and the number of foreigners per 100 were associated with regular cancer screening attendance of male in county level and explain 10.19% of disparity of regular cancer screening attendance rate among counties. For female, there was no community factor associated with regular cancer screening attendance in city/province level. Social deprivation index was the only factor associated with regular cancer screening attendance of female in county level and explains 3.29% of disparity of regular cancer screening attendance rate among counties.
Conclusion: According to the result, regular cancer screening attendance is associated with both individual and community factors. Although every individual factor is significantly associated regular cancer screening attendance, the way they act is quite different among male/female and the young/the old. According to this study, the rate regular cancer screening attendance of male are more strongly associated with community factors than that of female. Individual and community factors should be considered synthetically when the policy-makers try to introduce new policy on cancer screening.κ΅λ¬Έμ΄λ‘ β
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Abstract 116Maste
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