Diagnosis of pregnancy based classification of embryo culture medium samples by infrared spectrometry and chemometrics

Zandbaaf, Shima; Khorrami, Mohammad Reza Khanmohammadi; Garmarudi, Amir Bagheri; Rashidi, Batool Hossein

doi:10.1016/j.infrared.2019.103069

Cited by 6 publications

(3 citation statements)

References 49 publications

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“…FT‐IR spectrometer (Bruker ALPHA II, Germany) equipped with a diamond ATR module was employed to acquire infrared spectra from serum samples of 77 E. granulosus s.s .‐infected sheep and 121 healthy control sheep. FT‐IR spectra were acquired using OPUS software (version 8.5) in transmission mode [25]. The spectra were measured in the range of 600–4000 cm −1 with 32 scans and a spectral resolution of 4 cm −1 .…”

Section: Methodsmentioning

confidence: 99%

Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier‐transform infrared spectroscopy combined with machine learning algorithms

Dawuti

Dou

Zheng

et al. 2023

Journal of Biophotonics

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Cystic echinococcosis (CE) in sheep is a serious zoonotic parasitic disease caused by Echinococcus granulosus sensu stricto (s.s.). Presently, the screening technology for CE in sheep is time-consuming and inaccurate, and novel screening technology is urgently needed. In this work, we combined machine-learning algorithms with Fourier transform infrared (FT-IR) spectroscopy of serum to establish a quick and accurate screening approach for CE in sheep. Serum samples from 77 E. granulosus s.s.-infected sheep to 121 healthy control sheep were measured by FT-IR spectrometer. To optimize the classification accuracy of the serum FI-TR method for the E. granulosus s.s.-infected sheep and healthy control sheep, principal component analysis (PCA), linear discriminant analysis, and support vector machine (SVM) algorithms were used to analyze the data.Among all the bands, 1500-1700 cm À1 band has the best classification effect; its diagnostic sensitivity, specificity, and accuracy of PCA-SVM were 100%, 95.74%, and 96.66%, respectively. The study showed that serum FT-IR spectroscopy combined with machine learning algorithms has great potential for rapid and accurate screening methods for the CE in sheep.

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Section: Methodsmentioning

confidence: 99%

Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier‐transform infrared spectroscopy combined with machine learning algorithms

Dawuti

Dou

Zheng

et al. 2023

Journal of Biophotonics

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“…Figure 4 displays the characteristic spectrum of the samples, revealing the presence of bands related to functional groups, such as C=O (1630 cm −1 ), associated with proteins and lipids, characteristic of components of the hCG hormone. Additionally, a band of around 2348 cm −1 corresponding to the O=C=O bond was identified, along with bands linked to CH 2 and CH 3 groups at approximately 2850 and 2910 cm −1 , respectively [33], indicating the presence of lipids. Furthermore, an intense band at around 3362 cm −1 , corresponding to a combination of OH and NH bonds related to amino acids, was detected.…”

Section: Characterization Of the Hcg Hormonementioning

confidence: 97%

Quantification of hCG Hormone Using Tapered Optical Fiber Decorated with Gold Nanoparticles

Villegas-Cantoran,

Gómez,

Gómez-Pavón

et al. 2023

Sensors

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In this study, a novel technique for the quantification of the human chorionic gonadotropin (hCG) hormone using localized surface plasmons and a tapered optical fiber decorated with gold nanoparticles (Au-NPs) is reported. The tapered optical fiber fabrication process involves stretching a single-mode optical fiber using the flame-brushing system. The waist of the tapered optical fiber reaches a diameter of 3 μm. Decoration of the taper is achieved through the photodeposition of 100 nm Au-NPs using the drop-casting technique and a radiation source emitting at 1550 nm. The presence of the hCG hormone in the sample solutions is verified by Fourier-transform infrared spectroscopy (FTIR), revealing the presence of bands related to functional groups, such as C=O (1630 cm−1), which are associated with proteins and lipids, components of the hCG hormone. Quantification tests for hormone concentrations were carried out by measuring the optical power response of the tapered optical fiber with Au-NPs under the influence of hCG hormone concentrations, ranging from 1 mIU/mL to 100,000 mIU/mL. In the waist of the tapered optical fiber, the evanescent field is amplified because of localized surface plasmons generated by the nanoparticles and the laser radiation through the optical fiber. Experimental results demonstrated a proportional relationship between measured radiation power and hCG concentration, with the optical power response decreasing from 4.45 mW down to 2.5 mW, as the hCG hormone concentration increased from 1 mIU/mL up to 100,000 mIU/mL. Furthermore, the spectral analysis demonstrated a spectral shift of 14.2 nm with the increment of the hCG hormone concentration. The measurement system exhibits promising potential as a sensor for applications in the biomedical and industrial fields.

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“…Profiling embryo culture media following implantation allowed prediction of embryo viability which later correlated to pregnancy outcomes ( 69 , 70 ). FTIR has been similarly investigated attaining sensitivity and specificities of over 90% in determining a viable pregnancy ( 71 ). Raman spectroscopy has been used to detect changes in cervix composition in vivo in mice during normal pregnancy and delayed parturition ( 72 , 73 ).…”

Section: Vibrational Spectroscopy and Pregnancymentioning

confidence: 99%

Vibrational Spectroscopy: A Valuable Screening and Diagnostic Tool for Obstetric Disorders?

Richards

Jenkins

Griffiths

et al. 2021

Front. Glob. Womens Health

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Preeclampsia (PE) is a common obstetric disorder typically affecting 2–8% of all pregnancies and can lead to several adverse obstetric outcomes for both mother and fetus with the greatest burden of severe outcomes in low middle-income countries (LMICs), therefore, screening for PE is vital. Globally, screening is based on maternal characteristics and medical history which are nonspecific for the disorder. In 2004, the World Health Organization acknowledged that no clinically useful test was able to predict the onset of PE, which prompted a universal search for alternative means of screening. Over the past decade or so, emphasis has been placed on the use of maternal characteristics in conjunction with biomarkers of disease combined into predictive algorithms, however these are yet to transition into the clinic and are cost prohibitive in LMICs. As a result, the screening paradigm for PE remains unchanged. It is evident that novel approaches are needed. Vibrational spectroscopy, specifically Raman spectroscopy and Fourier-transform infrared spectroscopy (FTIR), could provide better alternatives suited for implementation in low resource settings as no specialized reagents are required for conventional approaches and there is a drive to portable platforms usable in both urban and rual community settings. These techniques are based on light scattering and absorption, respectively, allowing detailed molecular analysis of samples to produce a unique molecular fingerprint of diseased states. The specificity of vibrational spectroscopy might well make it suited for application in other obstetric disorders such as gestational diabetes mellitus and obstetric cholestasis. In this review, we summarize current approaches sought as alternatives to current screening methodologies and introduce how vibrational spectroscopy could offer superior screening and diagnostic paradigms in obstetric care. Additionally, we propose a real benefit of such tools in LMICs where limited resources battle the higher prevalence of obstetric disorders.

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Diagnosis of pregnancy based classification of embryo culture medium samples by infrared spectrometry and chemometrics

Cited by 6 publications

References 49 publications

Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier‐transform infrared spectroscopy combined with machine learning algorithms

Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier‐transform infrared spectroscopy combined with machine learning algorithms

Quantification of hCG Hormone Using Tapered Optical Fiber Decorated with Gold Nanoparticles

Vibrational Spectroscopy: A Valuable Screening and Diagnostic Tool for Obstetric Disorders?

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