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http://dx.doi.org/10.25673/120610
Titel: | Early Diagnosis of Fetal Sex and its Relationship to Some Biochemical and Physiological Variables in Pregnant Women in Salah Al-Din Governorate |
Autor(en): | Omer, Noor Lateef Tayawi, Hussien Mohammed |
Erscheinungsdatum: | 2025 |
Umfang: | 1 Online-Ressource (5 Seiten) |
Sprache: | Englisch |
Zusammenfassung: | Genes for sex determination are widely analyzed and used to predict fetal sex during different trimesters of pregnancy. However, their correlation with sex prediction based on ultrasound results, as well as with testosterone and estrogen levels in the first trimester, is quite limited. Therefore, the present study aimed to assess the degree of agreement between several sex-determining genes (SRY, DYS14, and DAZ) analyzed in the first trimester and Doppler-predicted sex, and to evaluate their correlation with hormone levels. Whole blood samples (5 mL) were collected from 110 Iraqi pregnant women between the 1st and 12th weeks of pregnancy. DNA was extracted from all samples, and the presence of the selected genes was confirmed using real-time PCR. The detection of amplification was considered a positive result for each gene, indicating male sex. The concentrations of testosterone and estrogen were measured using the ELISA technique. All pregnancies were monitored to confirm the Doppler results postnatally. The results of the present study showed no significant correlations between sex predicted by the SRY, DYS14, and DAZ genes and sex predicted by Doppler. Furthermore, the levels of both hormones did not significantly correlate with sex predicted by either molecular or Doppler methods. In conclusion, sex prediction in the first trimester of pregnancy frequently yields inaccurate results. |
URI: | https://opendata.uni-halle.de//handle/1981185920/122565 http://dx.doi.org/10.25673/120610 |
Open-Access: | ![]() |
Nutzungslizenz: | ![]() |
Enthalten in den Sammlungen: | International Conference on Applied Innovations in IT (ICAIIT) |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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5-16-ICAIIT_2025_13(2).pdf | 681.31 kB | Adobe PDF | ![]() Öffnen/Anzeigen |