Blood serum lipid profiling may improve the management of recurrent miscarriage: a combination of machine learning of mid-infrared spectra and biochemical assays
Analytical and Bioanalytical Chemistry, cilt.414, sa.29-30, ss.8341-8352, 2022 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 414 Sayı: 29-30
- Basım Tarihi: 2022
- Doi Numarası: 10.1007/s00216-022-04370-3
- Dergi Adı: Analytical and Bioanalytical Chemistry
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, EMBASE, Food Science & Technology Abstracts, MEDLINE, Metadex, Pollution Abstracts, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
- Sayfa Sayıları: ss.8341-8352
- Anahtar Kelimeler: Recurrent miscarriage, Fourier transform infrared, Lipid profile, Total protein, Oxidative load, Machine learning
- Sağlık Bilimleri Üniversitesi Adresli: Evet
Özet
The present article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood samples of women with recurrent miscarriage vs. those of healthy individuals who were followed in the Department of Obstetrics and Gynecology for 2 years. For this purpose, blood samples from a total of 120 participants, including healthy women (n=60) and women with diagnosed recurrent miscarriage (n=60), were obtained. The lipid profile (high-density lipoprotein, low-density lipoprotein, triglyceride, and total cholesterol levels) and lipid peroxidation (malondialdehyde and glutathione levels) were evaluated with a Beckman Coulter analyzer system for chemical analysis. Biomolecular structure and composition were determined using an attenuated total reflectance sampling methodology with Fourier transform infrared spectroscopy alongside machine learning technology to advance toward clinical translation. Here, we developed and validated instrumentation for the analysis of recurrent miscarriage patient serum that was able to differentiate recurrent miscarriage and control patients with an accuracy of 100% using a Fourier transform infrared region corresponding to lipids. We found that predictors of lipid profile abnormalities in maternal serum could significantly improve this patient pathway. The study also presents preliminary results from the first prospective clinical validation study of its kind. Graphical abstract: [Figure not available: see fulltext.]