請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95053完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 楊孝友 | zh_TW |
| dc.contributor.advisor | Hsiao-Yu Yang | en |
| dc.contributor.author | 許巍泓 | zh_TW |
| dc.contributor.author | Wei-Hung Hsu | en |
| dc.date.accessioned | 2024-08-26T16:27:42Z | - |
| dc.date.available | 2024-08-27 | - |
| dc.date.copyright | 2024-08-26 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2024-08-06 | - |
| dc.identifier.citation | 1. Hayhoe, K., et al., Our Changing Climate, in Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II, D.R. Reidmiller, et al., Editors. 2018, U.S. Global Change Research Program: Washington, DC, USA. p. 72-144.
2. Johnson, R.J., C. Wesseling, and L.S. Newman, Chronic Kidney Disease of Unknown Cause in Agricultural Communities. N Engl J Med, 2019. 380(19): p. 1843-1852. 3. Chapman, C.L., et al., Occupational heat exposure and the risk of chronic kidney disease of nontraditional origin in the United States. Am J Physiol Regul Integr Comp Physiol, 2021. 321(2): p. R141-R151. 4. Group, K.D.I.G.O.K.C.W., KDIGO 2012 Clinical Practice Guideline for the evaluation and management of chronic kidney disease. Kidney International, January 2013. 3(1): p. 136-150. 5. Lv, J.C. and L.X. Zhang, Prevalence and disease burden of chronic kidney disease. Advances in Experimental Medicine and Biology, 2019. 1165: p. 3-15. 6. Butler-Dawson, J., et al., Evaluation of heat stress and cumulative incidence of acute kidney injury in sugarcane workers in Guatemala. Int Arch Occup Environ Health, 2019. 92(7): p. 977-990. 7. Moyce, S., et al., Hydration Choices, Sugary Beverages, and Kidney Injury in Agricultural Workers in California. J Nurs Scholarsh, 2020. 52(4): p. 369-378. 8. Chapman, C.L.J., B. D.; Vargas, N. T.; Hostler, D.; Parker, M. D.; Schlader, Z. J., Both hyperthermia and dehydration during physical work in the heat contribute to the risk of acute kidney injury. J Appl Physiol, 2020. 128(4): p. 715-728. 9. Moyce, S., et al., Acute kidney injury and workload in a sample of California agricultural workers. Am J Ind Med, 2020. 63(3): p. 258-268. 10. Glaser, J., et al., Preventing kidney injury among sugarcane workers: promising evidence from enhanced workplace interventions. Occup Environ Med, 2020. 77(8): p. 527-534. 11. Singh, A., et al., Heat and PAHs Emissions in Indoor Kitchen Air and Its Impact on Kidney Dysfunctions among Kitchen Workers in Lucknow, North India. PLoS One, 2016. 11(2): p. e0148641. 12. Wegman, D.H., et al., Intervention to diminish dehydration and kidney damage among sugarcane workers. Scand J Work Environ Health, 2018. 44(1): p. 16-24. 13. Ghiyasi, S., et al., The effect of personal protective equipment on thermalstress: An experimental study on firefighters. Work, 2020. 67(1): p. 141-147. 14. Chang, T.H., et al., Mobile COVID-19 Screening Units: Heat Stress and Kidney Function Among Health Care Workers. Am J Kidney Dis, 2022. 80(3): p. 426-428. 15. Waikar, S.S., R.A. Betensky, and J.V. Bonventre, Creatinine as the gold standard for kidney injury biomarker studies? Nephrol Dial Transplant, 2009. 24(11): p. 3263-5. 16. Ostermann, M., et al., Recommendations on Acute Kidney Injury Biomarkers From the Acute Disease Quality Initiative Consensus Conference: A Consensus Statement. JAMA Netw Open, 2020. 3(10): p. e2019209. 17. Ali, R.J., F.H. Al-Obaidi, and H.S. Arif, The Role of Urinary N-acetyl Beta-D-glucosaminidase in Children with Urological Problems. Oman Med J, 2014. 29(4): p. 285-8. 18. Moriguchi, J., et al., N-acetyl-beta-D-glucosaminidase (NAG) as the most sensitive marker of tubular dysfunction for monitoring residents in non-polluted areas. Toxicol Lett, 2009. 190(1): p. 1-8. 19. Han, W.K., et al., Urinary biomarkers in the early diagnosis of acute kidney injury. Kidney Int, 2008. 73(7): p. 863-9. 20. Çuhadar, S. and T. Semerci, Renal Biomarkers N-Acetyl-Beta-D-Glucosaminidase (NAG), Endothelin, and Their Application, in Biomarkers in Kidney Disease. Biomarkers in Disease: Methods, Discoveries and Applications, V. Patel and V. Preedy, Editors. 2016, Springer: Dordrecht. 21. Sheridan, A.M. and J.V. Bonventre, Cell biology and molecular mechanisms of injury in ischemic acute renal failure. Current Opinion in Nephrology and Hypertension, 2000. 9(4): p. 427-434. 22. Vaidya, V.S., et al., Kidney injury molecule-1 outperforms traditional biomarkers of kidney injury in preclinical biomarker qualification studies. Nat Biotechnol, 2010. 28(5): p. 478-85. 23. Wen, Y. and C.R. Parikh, Current concepts and advances in biomarkers of acute kidney injury. Crit Rev Clin Lab Sci, 2021. 58(5): p. 354-368. 24. Thomas, J.M., et al., IL-18 (Interleukin-18) Produced by Renal Tubular Epithelial Cells Promotes Renal Inflammation and Injury During Deoxycorticosterone/Salt-Induced Hypertension in Mice. Hypertension, 2021. 78(5): p. 1296-1309. 25. Hirooka, Y. and Y. Nozaki, Interleukin-18 in Inflammatory Kidney Disease. Front Med (Lausanne), 2021. 8: p. 639103. 26. Parikh, C.R., et al., Urinary interleukin-18 is a marker of human acute tubular necrosis. Am J Kidney Dis, 2004. 43(3): p. 405-14. 27. Shigenaga, M.K., Gimeno, C. J., & Ames, B. N., Urinary 8-hydroxy-2’-deoxyguanosine as a biological marker of in vivo oxidative DNA damage. Proceedings of the National Academy of Sciences of the United States of America, 1989. 86(24): p. 9697-9701. 28. Graille, M., et al., Urinary 8-OHdG as a Biomarker for Oxidative Stress: A Systematic Literature Review and Meta-Analysis. Int J Mol Sci, 2020. 21(11). 29. Goto, H., et al., Heat acclimation ameliorated heat stress-induced acute kidney injury and prevented changes in kidney macrophages and fibrosis. Am J Physiol Renal Physiol, 2022. 323(3): p. F243-F254. 30. Garcia-Trabanino, R., et al., Heat stress, dehydration, and kidney function in sugarcane cutters in El Salvador--A cross-shift study of workers at risk of Mesoamerican nephropathy. Environ Res, 2015. 142: p. 746-55. 31. Moyce, S., et al., Heat strain, volume depletion and kidney function in California agricultural workers. Occup Environ Med, 2017. 74(6): p. 402-409. 32. Paula Santos, U., et al., Burnt sugarcane harvesting is associated with acute renal dysfunction. Kidney Int, 2015. 87(4): p. 792-9. 33. Nerbass, F.B., et al., Occupational Heat Stress and Kidney Health: From Farms to Factories. Kidney Int Rep, 2017. 2(6): p. 998-1008. 34. Bankir, L., N. Bouby, and E. Ritz, Vasopressin: a novel target for the prevention and retardation of kidney disease? Nat Rev Nephrol, 2013. 9(4): p. 223-39. 35. Schrier, R.W., et al., Tubular hypermetabolism as a factor in the progression of chronic renal failure. Am J Kidney Dis, 1988. 12(3): p. 243-9. 36. Diggle, C.P., et al., Ketohexokinase: expression and localization of the principal fructose-metabolizing enzyme. J Histochem Cytochem, 2009. 57(8): p. 763-74. 37. Cirillo, P., et al., Ketohexokinase-dependent metabolism of fructose induces proinflammatory mediators in proximal tubular cells. J Am Soc Nephrol, 2009. 20(3): p. 545-53. 38. Roncal Jimenez, C.A., et al., Fructokinase activity mediates dehydration-induced renal injury. Kidney Int, 2014. 86(2): p. 294-302. 39. Krleza, J.L., et al., Capillary blood sampling: national recommendations on behalf of the croatian Society of medical biochemistry and laboratory medicine. Biochemia Medica (Zagreb), 2015. 25(3): p. 335-358. 40. Matsushita K, M.B., Woodward M, Emberson JR, Jafar TH, Jee SH, Polkinghorne KR, Shankar A, Smith DH, Tonelli M, Warnock DG, Wen CP, Coresh J, Gansevoort RT, Hemmelgarn BR, Levey AS; Chronic Kidney Disease Prognosis Consortium., Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate. JAMA, 2012. 307(18): p. 1941-51. 41. Drijvers, J.M., et al., The enzyme-linked immunosorbent assay: The application of ELISA in clinical research, in Basic Science Methods for Clinical Researchers, M.S. Jalali, Francesca Y.L.; Jalali, Mehdi, Editor. 2017, Academic Press. p. 119-133. 42. Biolab, A. News: Product News. n.d. [cited 2024 July 27]; Available from: https://www.acebiolab.com/TW/news/40. 43. CUSABIO, Human N-acetyl-β-D-glucosaminidase NAG ) ELISA Kit: For the quantitative determination of human NAG concentrations in serum, urine China. 44. FineTest, Human KIM-1(Kidney Injury Molecule 1) ELISA Kit. China. 45. Corp, C.-C., SEA064Hu 96 Tests: Enzyme-linked immunosorbent assay kit for Interleukin 18 (IL-18). Houston, TX, USA. 46. abbexa, 8-Hydroxy-2-Deoxyguanosine (8-OHdG) ELISA Kit. 27 Aug 2021: Cambridge, UK. 47. Croghan, C. and P.P. Egeghy, Methods of dealing with values below the limit of detection using SAS, in Southeastern SAS User Group. 2003: St. Petersburg, FL. 48. Team, R.C., R: A language and environment for statistical computing. 2022, Vienna, Austria: R Foundation for Statistical Computing. 49. VJ, C., gee: Generalized Estimation Equation Solver. 2022. 50. Dustin Tingley, T.Y., Kentaro Hirose, Luke Keele, Kosuke Imai, mediation: R Package for Causal Mediation Analysis. Journal of Statistical Software, 2014. 59(5): p. 1-38. 51. Hsu, Y.C., et al., The association between duration of postnatal weight loss and neurodevelopment outcomes in very low birth weight infants. Pediatr Neonatol, 2022. 63(1): p. 33-40. 52. MacKinnon, D.P., A.J. Fairchild, and M.S. Fritz, Mediation process. Annual Review of Psychology, 2007. 58: p. 593-614. 53. Zhou, M., et al., Cross-sectional and longitudinal associations between urinary zinc and lung function among urban adults in China. Thorax, 2020. 75(9): p. 771-779. 54. Mackinnon, D.P. and J.H. Dwyer, Estimating Mediated Effects in Prevention Studies. Evaluation Review, 2016. 17(2): p. 144-158. 55. Zhang, Y., M. Liu, and R. Xie, Associations between cadmium exposure and whole-body aging: mediation analysis in the NHANES. BMC Public Health, 2023. 23(1): p. 1675. 56. Lu, S., et al., Lipid metabolism, BMI and the risk of nonalcoholic fatty liver disease in the general population: evidence from a mediation analysis. J Transl Med, 2023. 21(1): p. 192. 57. Preacher, K.J. and A.F. Hayes, Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods, 2008. 40(3): p. 879-91. 58. Hayes, A.F., PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. 2012. 59. You, Y., et al., The association between sedentary behavior, exercise, and sleep disturbance: A mediation analysis of inflammatory biomarkers. Front Immunol, 2022. 13: p. 1080782. 60. Shadish, W.C., TD; Campbell, DT, Experimental and quasi-experimental designs for generalized causal inference. 2001: Cengage Learning. 61. Nanayakkara, S., et al., Tubulointerstitial damage as the major pathological lesion in endemic chronic kidney disease among farmers in North Central Province of Sri Lanka. Environ Health Prev Med, 2012. 17(3): p. 213-21. 62. Wijkstrom, J., et al., Morphological and clinical findings in Sri Lankan patients with chronic kidney disease of unknown cause (CKDu): Similarities and differences with Mesoamerican Nephropathy. PLoS One, 2018. 13(3): p. e0193056. 63. Goto, H., et al., Early biomarkers for kidney injury in heat-related illness patients: a prospective observational study at Japanese Self-Defense Force Fuji Hospital. Nephrol Dial Transplant, 2023. 38(3): p. 644-654. 64. Junglee, N.A., et al., Exercising in a hot environment with muscle damage: effects on acute kidney injury biomarkers and kidney function. Am J Physiol Renal Physiol, 2013. 305(6): p. F813-20. 65. Han, W.K., et al., Kidney Injury Molecule-1 (KIM-1): a novel biomarker for human renal proximal tubule injury. Kidney Int, 2002. 62(1): p. 237-44. 66. Zhou, Y., et al., Comparison of kidney injury molecule-1 and other nephrotoxicity biomarkers in urine and kidney following acute exposure to gentamicin, mercury, and chromium. Toxicol Sci, 2008. 101(1): p. 159-70. 67. Krawczeski, C.D., et al., Temporal relationship and predictive value of urinary acute kidney injury biomarkers after pediatric cardiopulmonary bypass. J Am Coll Cardiol, 2011. 58(22): p. 2301-9. 68. James, M.T., et al., Long-term outcomes of acute kidney injury and strategies for improved care. Nat Rev Nephrol, 2020. 16(4): p. 193-205. 69. Coca, S.G., S. Singanamala, and C.R. Parikh, Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis. Kidney Int, 2012. 81(5): p. 442-8. 70. Neugarten, J. and L. Golestaneh, Female sex reduces the risk of hospital-associated acute kidney injury: a meta-analysis. BMC Nephrol, 2018. 19(1): p.314. 71. Curtis, L.M., Sex and Gender Differences in AKI. Kidney360, 2024. 5(1): p. 160-167. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95053 | - |
| dc.description.abstract | 序論
全球暖化與極端高溫氣候增加熱負荷,自1970年代,於熱帶國家中出現新興「非傳統原因之慢性腎病變」,增加健康及社會負擔。過去文獻發現高溫、脫水、高勞動力、休息不足等危險因子。目前假說提出熱暴露導致重複性脫水,並因脫水進一步引起發炎、氧化壓力增加,造成腎臟實質小管損傷。另外,許多研究也發現新型生物指標(N-乙醯-β-D-葡萄糖胺酶、腎損傷分子)可早期發現腎臟結構損傷。 目前,熱暴露導致急性腎損傷機轉仍不清楚。因此,本研究的目的為:(1)評估篩檢站護理人員在熱暴露前後,生理指標與新型腎臟損傷生物指標的變化;(2)評估早期腎臟損傷的可能危險因子;(3)藉由新型腎臟損傷生物指標,探討「早期腎臟受傷位置」,以中介效應分析,釐清熱危害致腎臟損傷的因果關係路徑。 研究方法 以事前事後比較研究設計,於2021年9–10月一處台北新冠肺炎篩檢站,18歲以上、至少工作三個月、無糖尿病、高血壓、腎結石病史、無使用非類固醇止痛藥之篩檢護理人員納入收案。分別在受試者班別的工作前後,進行核心體溫、體重的量測、全血肌酸酐即時檢驗、及後續於實驗室以酵素結合免疫吸附分析法,檢驗工作前後尿液中新型腎臟損傷(N-乙醯-β-D-葡萄糖胺酶、腎損傷分子)、發炎(白細胞介素)及氧化壓力(8-羥基去氧鳥苷)生物指標。收案人員皆經過標準化訓練,各量測儀器於收案前皆經有效校正,檢驗試劑符合品質檢驗。採用成對樣本t檢定分析熱暴露前後體溫、體重(脫水程度)、全血肌酸酐、腎臟損傷、發炎及氧化壓力生物指標變化。以廣義估計方程式(GEE)分析熱暴露影響早期腎臟損傷之相關因素。藉中介效應分析評估熱致腎損傷的因果關係路徑。 結果 共36位護理師納入結果分析,多數為20-30歲女性。在工作熱暴露後,核心體溫、脫水程度、全血肌酸酐顯著上升,且腎臟損傷(N-乙醯-β-D-葡萄糖胺酶)及氧化壓力(8-羥基去氧鳥苷)指標也顯著上升。顯著影響早期腎臟損傷之相關因素包含核心體溫上升、嚴重脫水、氧化壓力指數等變項。中介效應分析,熱壓力可藉由氧化壓力上升,導致腎臟損傷(提供48.55%解釋力),而脫水為獨立腎臟損傷影響因子。 結論: 氧化壓力作為「熱壓力致腎損傷」的中介因素,而脫水為獨立影響因子。根據結果,建議未來介入研究可採取補充水分、降溫、抗氧化等措施,評估對熱壓力造成腎損傷預防的成效。 | zh_TW |
| dc.description.abstract | Introduction
Global warming and increasing extreme heat weather have raised heat stress, leading to the emergence of "chronic kidney disease of nontraditional cause" in tropical countries since the 1970s. Previous studies have identified risk factors such as high temperatures, dehydration, heavy loading work, and insufficient rest. Current hypotheses suggest that heat exposure causes repeated dehydration, which further leads to inflammation and increased oxidative stress, resulting in renal tubular injury. Additionally, many studies have found that novel biomarkers (N-acetyl-β-D-glucosaminidase, kidney injury molecule) can detect early renal structural damage. The mechanisms by which heat exposure leads to acute kidney injury are still unclear. Therefore, the objectives of this study are: (1) evaluate the changes in physical parameters and novel kidney injury biomarkers in screening station nurses before and after heat exposure; (2) assess potential risk factors for early kidney injury; and (3) investigate the "location of early kidney injury" using novel kidney injury biomarkers, and clarify the causal pathways through mediation analysis. Study methods Pre- and post-study design, this research was conducted from September to October 2021 at a COVID-19 screening station in Taipei. The study included screening nurses who were 18 years or older, had been working for at least three months, and had no medical history of diabetes, hypertension, kidney stones, or chronic use of non-steroidal anti-inflammatory drugs. Core body temperature, body weight, and whole blood creatinine were measured before and after the participants' shifts. Additionally, urine samples collected before and after work were analyzed in the laboratory using enzyme-linked immunosorbent assay (ELISA) to test for novel kidney injury biomarkers (N-acetyl-β-D-glucosaminidase, kidney injury molecule), inflammation markers (interleukins), and oxidative stress markers (8-hydroxydeoxyguanosine). All procedures were standardized, with instruments calibrated for accuracy, and test reagents met quality control standards. Paired T tests were used to analyze changes in body temperature, body weight (dehydration), whole blood creatinine, kidney injury biomarkers, inflammation, and oxidative stress biomarkers before and after heat exposure. Generalized estimating equations (GEE) were used to analyze factors related to early kidney injury due to heat exposure. Mediation analysis was conducted to clarify the causal pathways leading to heat-induced kidney injury. Result A total of 36 nurses were included in the analysis, most of whom were women aged 20-30. After heat exposure at work, core body temperature, dehydration percentage, and whole blood creatinine significantly increased. Additionally, markers for kidney injury (N-acetyl-β-D-glucosaminidase) and oxidative stress (8-hydroxydeoxyguanosine) also showed significant increases. Factors significantly affecting early kidney injury included increased core body temperature, severe dehydration, and oxidative stress. Mediation analysis indicated that heat stress could lead to kidney injury through an increase in oxidative stress, explaining 48.55% of the effect, while dehydration was an independent factor influencing kidney injury. Conclusion Oxidative stress acts as a mediator in "heat stress-induced kidney injury", while dehydration is an independent influencing factor. Based on the results, we suggest further intervention study using hydration, cooling, antioxidant supplementation to evaluate their effectiveness in preventing heat-stress induced kidney injury. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-26T16:27:42Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-08-26T16:27:42Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 序言 1
摘要 2 Abstract 4 圖次 8 表次 9 附圖次 10 附表次 11 第一章、序論 12 第二章、研究方法 18 2.1 研究設計 18 2.2 研究對象 18 2.3 資料收集 19 2.4 問卷調查 19 2.5 非侵入性生理量測(體重、核心體溫、血壓) 20 2.6 傳統腎功能指數量測(血、尿液肌酸酐、腎絲球過濾率) 21 2.7 酵素結合免疫吸附分析法 22 2.8 新型腎臟損傷生物指標 26 2.9 處理低於檢測極限值的方法 27 2.10 研究檢定力計算 28 2.11 統計分析 28 2.12 廣義估計方程式 29 2.13 中介效應分析 29 第三章、結果 32 3.1 基本資料描述性統計 32 3.2 受試族群工作前、後生理指標比較 32 3.3 受試族群工作前、後腎臟損傷生物指標比較 32 3.4 腎臟損傷生物指標影響變項分析 33 3.5 中介因素分析 33 3.6 研究檢定力計算 34 第四章、討論 35 第五章、結論 39 第六章、文獻 40 附錄一、NAG檢驗實驗步驟,及蛋白質濃度與吸光度之標準曲線 52 附錄二、KIM-1檢驗實驗步驟,及蛋白質濃度與吸光度之標準曲線 57 附錄三、IL-18檢驗實驗步驟,及蛋白質濃度與吸光度之標準曲線 62 附錄四、8-OHDG檢驗實驗步驟,及蛋白質濃度與吸光度之標準曲線 67 附錄五、成對樣本T檢定、廣義估計方程式、中介分析的R語法 70 附錄六、序列中介分析評估熱暴露致腎臟損傷機轉 75 附錄七、平行中介分析評估熱暴露致腎臟損傷機轉 76 附錄八、經肌酸酐校正後腎臟損傷、氧化壓力蛋白結果 77 附錄九、熱暴露致腎損傷研究問卷 80 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 腎小管損傷 | zh_TW |
| dc.subject | 熱壓力 | zh_TW |
| dc.subject | 中介分析 | zh_TW |
| dc.subject | 氧化壓力 | zh_TW |
| dc.subject | 脫水 | zh_TW |
| dc.subject | dehydration | en |
| dc.subject | oxidative stress | en |
| dc.subject | mediation analysis | en |
| dc.subject | proximal tubular injury | en |
| dc.subject | heat stress | en |
| dc.title | 藉新型腎臟損傷生物標記探討熱壓力致腎損傷機轉 | zh_TW |
| dc.title | Evaluation of the Mechanisms of Heat Stress Induced Kidney Injury by Novel Kidney Injury Biomarkers | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 林靖愉;唐德成 | zh_TW |
| dc.contributor.oralexamcommittee | Ching-Yu Lin;Der-Cherng Tarng | en |
| dc.subject.keyword | 熱壓力,腎小管損傷,脫水,氧化壓力,中介分析, | zh_TW |
| dc.subject.keyword | heat stress,proximal tubular injury,dehydration,oxidative stress,mediation analysis, | en |
| dc.relation.page | 89 | - |
| dc.identifier.doi | 10.6342/NTU202403283 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2024-08-06 | - |
| dc.contributor.author-college | 公共衛生學院 | - |
| dc.contributor.author-dept | 環境與職業健康科學研究所 | - |
| 顯示於系所單位: | 環境與職業健康科學研究所 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-112-2.pdf 未授權公開取用 | 2.28 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
