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10.1126/sciadv.adu9145

http://scihub22266oqcxt.onion/10.1126/sciadv.adu9145
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41337586!?!41337586

suck abstract from ncbi

pmid41337586      Sci+Adv 2025 ; 11 (49): eadu9145
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  • Maternal lipidomic signatures of preterm and small-for-gestational-age newborn infants in low- and middle-income countries #MMPMID41337586
  • Maric I; Mahzarnia A; Mujuru HA; Chimhini G; Saha SK; Shameem Hassan M; Otieno NA; Hawken S; Wilson K; Shen X; Lancaster S; Wong RJ; Reiss JD; Kerner J; Snyder MP; Hay W; Shaw GM; Stevenson DK; Ward V; Darmstadt GL
  • Sci Adv 2025[Dec]; 11 (49): eadu9145 PMID41337586show ga
  • Maternal lipid levels change dynamically during gestation to support normal fetal growth. To obtain a detailed footprint of these changes and their differences in pregnancies with preterm or small-for-gestational-age (SGA) neonates, we analyzed 641 lipids and 639 metabolites in plasma from women by 24 weeks of pregnancy from three cohorts from low- and middle-income countries: Bangladesh, Zimbabwe, and Kenya. We consistently found a significant lipid imbalance with increased lipid levels that preceded preterm birth and decreased levels that preceded SGA births. Changes were most pronounced in triglycerides, including triglycerides containing proinflammatory omega-6 polyunsaturated fatty acids (PUFAs) in pregnancies with preterm infants. A machine learning model for prediction of preterm birth had modest performance [area under the receiver operator curve (AUC) = 0.69, 95% confidence interval (CI) = (0.68, 0.70)] and lower performance for predicting SGA [AUC = 0.64, CI 95% = (0.62, 0.65)]. Increased triglycerides containing proinflammatory PUFAs provide further evidence in favor of a previously considered dietary supplementation with the long-chain fatty acids.
  • |*Infant, Premature[MESH]
  • |*Infant, Small for Gestational Age/blood[MESH]
  • |*Lipidomics/methods[MESH]
  • |*Lipids/blood[MESH]
  • |*Premature Birth/blood[MESH]
  • |Adult[MESH]
  • |Bangladesh[MESH]
  • |Developing Countries[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Infant, Newborn[MESH]
  • |Kenya[MESH]
  • |Machine Learning[MESH]


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