<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jagadeeshaprasad, Mashanipalya G.</style></author><author><style face="normal" font="default" size="100%">Batkulwar, Kedar B.</style></author><author><style face="normal" font="default" size="100%">Meshram, Nishita N.</style></author><author><style face="normal" font="default" size="100%">Tiwari, Shalbha</style></author><author><style face="normal" font="default" size="100%">Korwar, Arvind M.</style></author><author><style face="normal" font="default" size="100%">Unnikrishnan, Ambika G.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Mahesh J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Targeted quantification of N-1-(carboxymethyl) valine and N-1-(carboxyethyl) valine peptides of beta-hemoglobin for better diagnostics in diabetes</style></title><secondary-title><style face="normal" font="default" size="100%">Clinical Proteomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Diabetes</style></keyword><keyword><style  face="normal" font="default" size="100%">Diagnosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Glycation</style></keyword><keyword><style  face="normal" font="default" size="100%">Glycemic control</style></keyword><keyword><style  face="normal" font="default" size="100%">HbA1c</style></keyword><keyword><style  face="normal" font="default" size="100%">Mass spectrometry</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAR</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">BIOMED CENTRAL LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND</style></pub-location><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">Article Number: 7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Background: N-1-(Deoxyfructosyl) valine (DFV) beta-hemoglobin (beta-Hb), commonly referred as HbA1c, is widely used diagnostic marker in diabetes, believed to provide glycemic status of preceding 90-120 days. However, the turnover of hemoglobin is about 120 days, the DFV-beta-Hb, an early and reversible glycation product eventually may undergo irreversible advanced glycation modifications such as carboxymethylation or carboxyethylation. Hence quantification of N-1-(carboxymethyl) valine (CMV) and N-1-(carboxyethyl) valine (CEV) peptides of beta-Hb would be useful in assessing actual glycemic status. Results: Fragment ion library for synthetically glycated peptides of hemoglobin was generated by using high resolution-accurate mass spectrometry (HR/AM). Using parallel reaction monitoring, deoxyfructosylated, carboxymethylated and carboxyethylated peptides of hemoglobin were quantified in clinical samples from healthy control, pre-diabetes, diabetes and poorly controlled diabetes. For the first time, we report N-1-beta-valine undergoes carboxyethylation and mass spectrometric quantification of CMV and CEV peptides of beta-hemoglobin. Carboxymethylation was found to be the most abundant modification of N-1-beta-valine. Both CMV-beta-Hb and CEV-beta-Hb peptides showed better correlation with severity of diabetes in terms of fasting glucose, postprandial glucose and microalbuminuria. Conclusions: This study reports carboxymethylation as a predominant modification of N-1-beta-valine of Hb, and quantification of CMV-beta-Hb and CEV-beta-Hb could be useful parameter for assessing the severity of diabetes.&lt;/p&gt;</style></abstract><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">3.476</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Patil, Yugendra R.</style></author><author><style face="normal" font="default" size="100%">Tiwari, Shalbha</style></author><author><style face="normal" font="default" size="100%">Momin, Abdulrahaman A.</style></author><author><style face="normal" font="default" size="100%">Unnikrishnan, A. G.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Mahesh J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Autoantibodies against Nε-carboxymethyl lysine and methylglyoxal modified albumin are associated with cardiovascular risk in type 2 diabetes</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Diabetes in Developing Countries</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">AGE</style></keyword><keyword><style  face="normal" font="default" size="100%">Atherosclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes</style></keyword><keyword><style  face="normal" font="default" size="100%">Glycation</style></keyword><keyword><style  face="normal" font="default" size="100%">Immune response</style></keyword><keyword><style  face="normal" font="default" size="100%">ROC</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">45</style></volume><pages><style face="normal" font="default" size="100%">1104-1110</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	{Background Albumin is an abundant plasma protein which gets modified with advanced glycation end products (AGEs) predominantly in diabetic condition. AGE modification induces immune response and autoantibodies are generated which play an important role in disease pathology. Objective This study aimed to illustrate the role of autoantibodies against N epsilon-carboxymethyl lysine (CML) and methylglyoxal (MG) modified albumin in diabetic cardiovascular complications. MethodsType-2 diabetes subjects were enrolled and further grouped into stress test positive or stress test negative based on treadmill stress test (TMT). Autoantibody titer was quantified by ELISA assay for CML-modified albumin (stress test positive&lt;/p&gt;
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	0.8&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Patil, Yugendra R.</style></author><author><style face="normal" font="default" size="100%">Tiwari, Shalbha</style></author><author><style face="normal" font="default" size="100%">Unnikrishnan, A. G.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Mahesh J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Proteome profile of stress test assessed cardiovascular disease risk-prone diabetic subjects</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Cardiovascular Translational Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">cardiovascular disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes</style></keyword><keyword><style  face="normal" font="default" size="100%">Multiple reaction monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Plasma markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteome profile</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative mass spectrometry</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">960-969</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Cardiovascular disease (CVD) is the leading cause of death in the diabetic population. There is a need for specific predictive markers to assess CVD risk. The present study explored the plasma proteome profile of treadmill test (TMT) assessed diabetic stress test positive (DSTP) and diabetic stress test negative (DSTN) subjects by performing a SWATH-MS-based label-free quantitative mass spectrometry approach to identify differentially expressed proteins (DEPs). CVD-relevant DEPs were further validated using a targeted mass spectrometry approach (MRM-HR). It was observed that CO4B, PON1 and LUM exhibited considerable differential expression in both the MS approaches, and ROC analysis showed significant AUC (0.97, 0.79 and 0.77, respectively). Overall, the present study reports these proteins as potential alternative markers for TMT in assessing CVD risk. These markers can possibly overcome the limitations of TMT with further validation in the large cohort.Graphical AbstractAn overview of experimental approaches used in the current study. The study design depicts diabetic subjects assessed for cardiovascular risk by TMT or stress test. The experimental design shows the use of the SWATH-MS approach to identify differentially expressed proteins and validate CVD-related proteins with targeted MS approaches such as MRM-HR. Finally, CO4B, PON1 and LUM exhibited significant AUC in ROC analysis, indicating their potential marker capabilities to predict CVD in diabetic subjects.&lt;/p&gt;
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	2.9&lt;/p&gt;
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