你看見的世界其實是媒體資訊建構的論文書籍站
國立臺灣大學 護理學研究所 李芸湘所指導 蘇育蓁的 探討非何杰金氏淋巴癌存活者之化療相關周邊神經病變的症狀困擾與因應策略 （2020），提出Barg bar關鍵因素是什麼，來自於非何杰金氏淋巴癌、化療相關周邊神經病變、因應策略。
而第二篇論文臺北醫學大學 公共衛生學系碩士班 謝芳宜所指導 龔琪瑪的 An association study of genetic polymorphisms of PPAR delta and cardiovascular diseases in an arseniasis-endemic area in Lanyang Basin of Taiwan （2020），提出因為有 基因多形的重點而找出了 Barg bar的解答。
探討非何杰金氏淋巴癌存活者之化療相關周邊神經病變的症狀困擾與因應策略
為了解決Barg bar 的問題，作者蘇育蓁 這樣論述：
化學治療(R)-CHOP為非何杰金氏淋巴癌主要治療處方，但其中化學藥物Vincristine相關周邊神經病變是造成病人生活極大困擾的長期副作用。然而，化療相關周邊神經病變仍缺乏具體有效的預防與治療策略，臨床上，多數患者會自行發展出個人因應策略克服症狀造成的生活困擾，但在因應策略選擇與其有效性為何目前仍尚無相關研究，因此，本研究將針對此部分進行深入探討。 本研究為橫斷式之描述性相關性研究，於中部某醫學中心血液腫瘤科門診、門診化療室及病房，以立意取樣針對123位非何杰金氏淋巴癌的患者進行收案。研究工具包含：歐洲癌症治療與研究組織生活品質核心問卷-周邊神經病變、特定於VIPN相關因應策略有效
性量表，並使用整體神經病變（臨床版）進行化療相關周邊神經病變的評估，最後以描述性及推論性統計進行分析。 研究結果顯示 (1)以歐洲癌症治療與研究組織生活品質核心問卷-周邊神經病變進行症狀嚴重度評估，共102位患者自覺有症狀，其中以手麻木、腳抽筋和腳麻木最嚴重，而施測者以整體神經病變（臨床版）向每位患者進行測試，共61位患者出現神經受損症狀，尤其以肌腱反射最為明顯 (2)化療相關周邊神經病變的自我評估與理學檢查嚴重度，皆與年齡呈現顯著正相關 (3)具Vincristine相關周邊神經病變的患者於症狀因應的整體有效性平均為5.17分，心理因應的整體有效性平均為6.15分，而心理因應有效性和自
我評估症狀嚴重度呈現顯著負相關，尤其與感覺神經症狀呈現顯著低度負相關，症狀因應有效性則未見顯著差異。 結論：臨床評估建議仍以病人自我評估的化療相關周邊神經病變症狀為主，讓病人定期自我檢視症狀的變化，以回歸病人為中心的照護，必要時，再配合整體神經病變（臨床版）評估，以提供最適當的時機轉介病人進一步復健科神經學相關檢測，並可提供本研究之VIPN的因應策略做為臨床照護之建議。
An association study of genetic polymorphisms of PPAR delta and cardiovascular diseases in an arseniasis-endemic area in Lanyang Basin of Taiwan
為了解決Barg bar 的問題，作者龔琪瑪 這樣論述：
Background: Oxidative stress, inflammation and endothelial dysfunction are important factors involved in the development of cardiovascular disease. Arsenic exposure is associated with increased inflammation and oxidative stress. Elevated PPARδ is related to the downregulation of oxidative stress an
d inflammation. However, the potential genetic contribution of PPARδ alone and under arsenic exposure to the risk of cardiovascular disease (CVD) remains unclear.Objective: We aim to investigate the relationship between PPARδ genetic polymorphisms and the CVD risk in residents who participated in a
cohort from arseniasis-endemic area of northeastern Taiwan during 1991 to 1994 as well as the gene-environment interaction on CVD risk.Methods: A community-based case- control study was used in this study. A total of 863 subjects, including 420 CVD cases and 842 controls were included in the study.
Controls were randomly selected and frequency matched with cases by age±5 years and sex under the case: control ratio of 1:2. The data of demographic characteristics, lifestyle behaviors, disease histories and well water consumption history were collected by a questionnaire. Household water samples
were collected from wells to determine arsenic contamination by flame atomic absorption spectrometry. Six PPARδ SNPs, rs1053049, rs2016520, rs3734254, rs3798343, rs9470015 were genotyped using iPLEX Gold and MassARRAY Sequenom platform. The associations of CVD and PPARδ gene variants were analyzed b
y multivariate logistic regression after adjusting for CVD risk factors. An interaction effect was determined by the indexes of relative excess risk due to interaction (RERI), attributable proportion (AP), and Rothman’s synergy index (S).Results: Our results showed that higher arsenic concentration,
cumulative arsenic levels, diabetes, and hypertension were significantly associated with CVD. Under the dominant model, PPARδ rs1053049, rs2016520, rs3734254 were shown to be significantly associated with the risk of CVD after adjustment of age, gender, diabetes, hypertension, and arsenic exposure.
In Haplotype analysis, PPARδ haplotype H4 were associated with increased risk of CVD but not reach statistical significance. However, in diplotype analysis, PPARδ diplotype (H1, H4) was significantly associated with CVD (OR=1.412, 95% CI:1.054-1.892). In subgroup analysis, the associations between
PPARδ rs3734254 C allele carriers (OR=1.762, 95% CI: 1.150-2.700) or rs9470015 A allele carriers (OR=1.637, 95% CI:1.072-2.500) and the risk of CVD were only significant in the groups exposed to arsenic at >50 μg/L in drinking water, but these associations were not seen in the group with arsenic exp
osure ≤50 μg/L. In addition, subjects with H4 haplotype also had significantly higher CVD risk compared to those with non-H4 haplotype in the group with high arsenic exposure, but the association was not observed in arsenic exposure ≤50 μg/L. Diplotype (H1, H4) was significantly associated with CVD
especially in subjects with diabetes. In effect modification analysis of PPARδ on the association between nongenetic risk factors and CVD risk, PPARδ rs3734254 C allele or rs9470015 A allele or haplotype H4 might modify the association between arsenic exposure and risk of CVD; PPARδ diplotype (H1, H
4) might modify the association between diabetes and risk of CVD. In the interaction analysis, we found a significant positive interaction between the rs9470015 risk genotype (AA+GA) and arsenic exposure on risk of CVD (AP=0.355, 95% CI: 0.031-0.679). The significant positive interaction was also se
en between PPARδ haplotype H4 and arsenic exposure on CVD risk (AP=0.304, 95% CI: 0.039-0.569). There was a significant positive interaction between PPARδ diplotype (H1, H4) and diabetes on CVD risk. The joint effect analysis showed that the CVD risk increased with the increasing number of the three
risk factors of arsenic exposure, hypertension, and PPARδ gene (risk genotype/risk haplotype/risk dipotype).Conclusion: In conclusion, we found a significant positive association between PPARδ rs2016520 CT+CC genotype, rs1053049 CT+CC genotype, rs3734254 CT+CC genotype, rs9470015 CC+CT genotype, ha
plotype H4 and risk of CVD risk, especially among the study subjects with arsenic exposure > 50 μg/L. PPARδ diplotype (H1, H4) significantly increased the risk of CVD as compared to the reference diplotype (H1, H1). There is a significant gene-environment interaction between PPARδ rs9470015 risk gen
otypes (CC+CT) and arsenic exposure on the risk of CVD. Finally, with the accumulation of non-genetic and genetic risk factors, the risk for CVD increases accordingly.