<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>13</volume><submitter>Du R</submitter><pubmed_abstract>&lt;h4>Objective&lt;/h4>The objective of this study was to reveal the potential crosstalk between immune infiltration and N&lt;sup>6&lt;/sup>- methyladenosine (m&lt;sup>6&lt;/sup>A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.&lt;h4>Methods&lt;/h4>We analyzed imbalanced immune infiltration and differentially expressed m&lt;sup>6&lt;/sup>A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and vali</pubmed_abstract><journal>Frontiers in endocrinology</journal><pagination>853857</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8971567</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus.</pubmed_title><pmcid>PMC8971567</pmcid><pubmed_authors>Du R</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Li L</pubmed_authors></additional><is_claimable>false</is_claimable><name>N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus.</name><description>&lt;h4>Objective&lt;/h4>The objective of this study was to reveal the potential crosstalk between immune infiltration and N&lt;sup>6&lt;/sup>- methyladenosine (m&lt;sup>6&lt;/sup>A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.&lt;h4>Methods&lt;/h4>We analyzed imbalanced immune infiltration and differentially expressed m&lt;sup>6&lt;/sup>A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and vali</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2025-04-19T12:55:59.605Z</modification><creation>2025-04-19T12:55:59.605Z</creation></dates><accession>S-EPMC8971567</accession><cross_references><pubmed>35370940</pubmed><doi>10.3389/fendo.2022.853857</doi></cross_references></HashMap>