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21.
Dalton Luiz Schiessel Ricardo K. Yamazaki Marcelo Kryczyk Isabela Coelho de Castro Adriana A. Yamaguchi Danielle C. T. Pequito 《Nutrition and cancer》2016,68(8):1369-1380
Objective: Polyunsaturated fatty acids n-3 (PUFA n-3) have shown effects in reducing tumor growth, in particular eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) abundantly present in fish oil (FO). When these fatty acids are provided in the diet, they alter the functions of the cells, particularly in tumor and immune cells. However, the effects of α-linolenic fatty acid (ALA), which is the precursor of EPA and DHA, are controversial. Thus, our objective was to test the effect of this parental fatty acid. Methods: Non-tumor-bearing and tumor-bearing Wistar rats (70 days) were supplemented with 1 g/kg body weight of FO or Oro Inca® (OI) oil (rich in ALA). Immune cells function, proliferation, cytokine production, and subpopulation profile were evaluated. Results: We have shown that innate immune cells enhanced phagocytosis capacity, and increased processing and elimination of antigens. Moreover, there was a decrease in production of pro-inflammatory cytokines (tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6)) by macrophages. Lymphocytes showed decreased proliferation capacity, increased cluster of differentiation 8 (CD8+) subpopulation, and increased TNF-α production. Conclusions: Oil rich in ALA caused similar immune modulation in cancer when compared with FO. 相似文献
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F. Fruzzetti G. Palla A. Sbrana T. Simoncini M. R. Sessa 《Gynecological endocrinology》2020,36(10):938-940
AbstractObjective: To understand the origin of extremely high gonadotropin levels in a perimenopausal woman.Methods: A 52-year-old woman with a 2?months of amenorrhea followed spontaneous menstrual cycles recovery was referred to our outpatient clinic with elevated follicle-stimulating hormone (FSH, 483 mUI/ml), luteinizing hormone (LH, 475 mUI/ml) and prolactin (PRL, 173?ng/ml). She was known to take levosulpiride. The gonadotropin levels did not fit with the clinical features.Results: A gonadotroph tumor was ruled out. Further analysis confirmed constantly high FSH, LH and PRL levels. The measurements were repeated using different analytical platforms with different results. After serial dilutions, nonlinearity was present suggesting an immunoassay interference. After post-polyethylene glycol recovery, hormone levels appeared in the normal range. Anti-goat antibodies were recognized in the serum of the patient.Conclusions: This case report shows a case of falsely abnormal high gonadotropin and PRL levels in a woman during menopause transition. In the clinical practice the evaluation of gonadotropin profile is not recommended at this age, but the abnormal levels stimulated further evaluation. An interference in the assay due to anti-goat antibodies resulted in abnormally high level of FSH and LH. A strict collaboration between clinicians and the laboratory is needed, when laboratory findings do not correspond to clinical findings. 相似文献
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T. Wu L. G. Trahair M. J. Bound C. F. Deacon M. Horowitz C. K. Rayner K. L. Jones 《Diabetic medicine》2015,32(5):595-600
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Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases. 相似文献