Institute of Physics, University of Rzeszów, Poland.
Institute of Computer Science, University of Rzeszów, Poland.
Photodiagnosis Photodyn Ther. 2022 Jun;38:102883. doi: 10.1016/j.pdpdt.2022.102883. Epub 2022 Apr 26.
By in vitro fertilization, oocytes can be removed and the embryo can be cultured, and then trans cervically replaced when they reach cleavage or at the blastocyst stage. The characterization of the follicular fluid is important for the treatment process. Women who applied to the Academic Hospital in vitro fertilization (IVF) Center diagnosed with idiopathic female infertility (IFI) were sought in the patient group. Demographics and clinical gonadotropin measurements of the study population were recorded. Of the 116 follicular fluid samples (n=58 male-induced infertility; n=58 control) were analyzed using the FTIR system. To identify FTIR spectral characteristics of follicular fluids associated with an ovarian reserve and reproductive hormone levels from control and IFI, six machine learning methods and multivariate analysis were used. To assess the quantitative information about the total biochemical composition of a follicular fluid across various diagnoses. FTIR spectra showed a higher level of vibrations corresponding to lipids and a lower level of amide vibrations in the IFI group. Furthermore, the T square plot from Partial Last Square (PLS) analysis showed, that these vibrations can be used to distinguish IFI from the control group which was obtained by principal component analysis (PCA). Proteins and lipids play an important role in the development of IFI. The absorption dynamics of FTIR spectra showed wavenumbers with around 100% discrimination probability, which means, that the presented wavenumbers can be used as a spectroscopic marker of IFI. Also, six machine learning methods showed, that classification accuracy for the original set was from 93.75% to 100% depending on the learning algorithm used. These results can inform about IFI women's follicular fluid has biomacromolecular differentiation in their follicular fluid. By using a safe and effective tool for the characterization of changes in follicular fluid during in vitro fertilization, this study builds upon a comprehensive examination of the idiopathic female infertility remodeling process in human studies. We anticipate that this technology will be a valuable adjunct for clinical studies.
通过体外受精，可以取出卵子并培养胚胎，然后在卵裂期或囊胚期经宫颈移植。卵泡液的特征对于治疗过程很重要。本研究在患者组中寻找在学术医院进行体外受精 (IVF) 中心诊断为特发性女性不孕 (IFI) 的女性。记录研究人群的人口统计学和临床促性腺激素测量值。使用 FTIR 系统分析了 116 个卵泡液样本（n=58 例男性诱导性不孕；n=58 例对照）。为了从对照和 IFI 中识别与卵巢储备和生殖激素水平相关的卵泡液的 FTIR 光谱特征，使用了六种机器学习方法和多元分析。评估了跨各种诊断的卵泡液总生化成分的定量信息。FTIR 光谱显示，IFI 组的脂质振动水平较高，酰胺振动水平较低。此外，偏最小二乘 (PLS) 分析的 T 平方图表明，这些振动可用于区分 IFI 与对照组，这是通过主成分分析 (PCA) 获得的。蛋白质和脂质在 IFI 的发展中起重要作用。FTIR 光谱的吸收动力学显示出约 100%的区分概率的波数，这意味着，所呈现的波数可以用作 IFI 的光谱标记。此外，六种机器学习方法表明，根据使用的学习算法，原始数据集的分类准确率从 93.75%到 100%不等。这些结果可以说明 IFI 女性的卵泡液在其卵泡液中有生物大分子的分化。通过使用一种安全有效的工具来描述体外受精过程中卵泡液的变化，本研究对人类研究中特发性女性不孕重塑过程进行了全面检查。我们预计，这项技术将成为临床研究的有力辅助手段。
