A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Serum Metabolomic Signature Predicts Ovarian Response to Controlled Stimulation. | LitMetric

AI Article Synopsis

  • The study focused on identifying serum metabolites as potential biomarkers to predict ovarian response during in vitro fertilization (IVF) after controlled ovarian stimulation (COS).
  • Utilizing blood samples analyzed through liquid chromatography-tandem mass spectrometry (LC-MS/MS), researchers found 50 significant differences in metabolite levels before and after COS, with specific amino acids showing notable changes.
  • The findings suggested that combination levels of glycine, acetylglycine, and certain lipids could effectively predict ovarian response to COS, indicating the importance of serum metabolism in IVF treatments.

Article Abstract

In in vitro fertilization (IVF), it is meaningful to find novel biomarkers predicting ovarian response in advance. The aim of the study was to identify serum metabolomics predicting ovarian response after controlled ovarian stimulation (COS). Blood samples collected at the start of pituitary downregulation and on the fifth day after COS using Liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods were analyzed to quantify metabolites. Demographic data were calculated with SPSS version 22.0 software. Multivariate statistics were used to analyze metabolomics dataset. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic model. Analyses revealed 50 different metabolomics between the pre- and post-COS groups. Compared with baseline, amino acids increased significantly following COS. At baseline, acetylglycine was more abundant in FOI<1 group, while glycine and lipids increased in FOI≥1 group. After COS, glycine, N-acetyl-L-alanine, D-alanine, and 2-aminomuconic acid were higher in those with FOI≥1, but L-glutamine was abundant in FOI<1. ROC curves indicated that combination of glycine, acetylglycine, and lipids predicts different responses to COS (AUC=0.866). Serum metabolism might reflect the response to ovarian stimulation. Higher glycine and PC may be a good predictor for response to COS.

Download full-text PDF

Source
http://dx.doi.org/10.1055/a-1882-3967DOI Listing

Publication Analysis

Top Keywords

ovarian response
12
response controlled
8
predicting ovarian
8
serum metabolomic
4
metabolomic signature
4
signature predicts
4
ovarian
4
predicts ovarian
4
controlled stimulation
4
stimulation vitro
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!