پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 646 |
| تعداد مقالات | 9,458 |
| تعداد مشاهده مقاله | 68,235,751 |
| تعداد دریافت فایل اصل مقاله | 47,769,400 |
Enhanced Quantification of Co-eluting Amino Acids Using TLC based Image Analysis and Multivariate Calibration | ||
| شیمى کاربردى روز | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 04 شهریور 1404 | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/chem.2025.37549.2365 | ||
| نویسندگان | ||
| مهردخت سادات حسینی حقیقی1؛ مریم رجبی* 2؛ مریم خوشکام3؛ تکتم محمدی مقدم4 | ||
| 1دانشکده شیمی، دانشگاه سمنان، سمنان، ایران | ||
| 2گروه شیمی تجزیه، دانشکده شیمی، دانشگاه سمنان، سمنان، ایران | ||
| 3گروه آموزشی شیمی، دانشکده علوم، دانشگاه زنجان، زنجان، ایران | ||
| 4مرکز تحقیقات سلامت محیط کار، دانشگاه علوم پزشکی نیشابور، نیشابور، ایران | ||
| تاریخ دریافت: 08 اردیبهشت 1404، تاریخ بازنگری: 21 مرداد 1404، تاریخ پذیرش: 04 شهریور 1404 | ||
| چکیده | ||
| L-Glutamine (Gln) and Glycine (Gly) are two amino acids with overlapping retention times in thin-layer chromatography (TLC). This overlap presents a significant analytical challenge, particularly when both compounds are present in the same mixture, as their spots on the TLC plate may not be fully resolved. Here, we used smartphone-based image analysis combined with PLS regression for semi-separated Gln/Gly quantification in TLC. A smartphone captured TLC plates images under consistent lighting conditions, and custom software processed them to generate chromatographic profiles. Calibration curves showed linear responses, with detection limits of 0.007 M and 0.008 M for Gln and Gly, respectively. Despite mobile-phase optimization, complete spot resolution was unachievable. To address this, partial least squares (PLS) regression deconvoluted the merged signals, enabling accurate quantification. The method was validated using a pharmaceutical product, yielding recovery rates of 100.4 ± 1.4% for Gln and 100.6 ± 1.0% for Gly, demonstrating its reliability for complex samples. | ||
| کلیدواژه‌ها | ||
| TLC based image analysis؛ Multivariate calibration؛ Co-eluting components؛ Amino acids | ||
| عنوان مقاله [English] | ||
| Enhanced Quantification of Co-eluting Amino Acids Using TLC based Image Analysis and Multivariate Calibration | ||
| نویسندگان [English] | ||
| Mehrdokht Hosseini Haghighi1؛ Maryam Rajabi2؛ Maryam Khoshkam3؛ Toktam Mohammadi Moghaddam4 | ||
| 1Department of Analytical Chemistry, Faculty of Chemistry, Semnan University, Semnan, Iran | ||
| 2Department of Analytical Chemistry, Faculty of Chemistry, Semnan University, Semnan, Iran | ||
| 3Department of Chemistry, Faculty of Science, University of Zanjan, Zanjan, Iran | ||
| 4Workplace Health Research Center, Neyshabour University of Medical Sciences, Neyshabour, Iran | ||
| چکیده [English] | ||
| L-Glutamine (Gln) and Glycine (Gly) are two amino acids with overlapping retention times in thin-layer chromatography (TLC). This overlap presents a significant analytical challenge, particularly when both compounds are present in the same mixture, as their spots on the TLC plate may not be fully resolved. Here, we used smartphone-based image analysis combined with PLS regression for semi-separated Gln/Gly quantification in TLC. A smartphone captured TLC plates images under consistent lighting conditions, and custom software processed them to generate chromatographic profiles. Calibration curves showed linear responses, with detection limits of 0.007 M and 0.008 M for Gln and Gly, respectively. Despite mobile-phase optimization, complete spot resolution was unachievable. To address this, partial least squares (PLS) regression deconvoluted the merged signals, enabling accurate quantification. The method was validated using a pharmaceutical product, yielding recovery rates of 100.4 ± 1.4% for Gln and 100.6 ± 1.0% for Gly, demonstrating its reliability for complex samples. | ||
| کلیدواژه‌ها [English] | ||
| TLC based image analysis, Multivariate calibration, Co-eluting components, Amino acids | ||
| مراجع | ||
|
| ||
|
آمار تعداد مشاهده مقاله: 21 |
||