raman spectroscopy
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2023 ◽  
Vol 83 ◽  
V. A. Nascimento ◽  
S. M. Malmonge ◽  
A. R. Santos Jr.

Abstract Mesenchymal stem cells (MSCs) have great potential for application in cell therapy and tissue engineering procedures because of their plasticity and capacity to differentiate into different cell types. Given the widespread use of MSCs, it is necessary to better understand some properties related to osteogenic differentiation, particularly those linked to biomaterials used in tissue engineering. The aim of this study was to develop an analysis method using FT-Raman spectroscopy for the identification and quantification of biochemical components present in conditioned culture media derived from MSCs with or without induction of osteogenic differentiation. All experiments were performed between passages 3 and 5. For this analysis, MSCs were cultured on scaffolds composed of bioresorbable poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV) and poly(ε-caprolactone) (PCL) polymers. MSCs (GIBCO®) were inoculated onto the pure polymers and 75:25 PHBV/PCL blend (dense and porous samples). The plate itself was used as control. The cells were maintained in DMEM (with low glucose) containing GlutaMAX® and 10% FBS at 37oC with 5% CO2 for 21 days. The conditioned culture media were collected and analyzed to probe for functional groups, as well as possible molecular variations associated with cell differentiation and metabolism. The method permitted to identify functional groups of specific molecules in the conditioned medium such as cholesterol, phosphatidylinositol, triglycerides, beta-subunit polypeptides, amide regions and hydrogen bonds of proteins, in addition to DNA expression. In the present study, FT-Raman spectroscopy exhibited limited resolution since different molecules can express similar or even the same stretching vibrations, a fact that makes analysis difficult. There were no variations in the readings between the samples studied. In conclusion, FT-Raman spectroscopy did not meet expectations under the conditions studied.

Fuel ◽  
2022 ◽  
Vol 312 ◽  
pp. 122811
Nannan Cheng ◽  
Jienan Pan ◽  
Mengyan Shi ◽  
Quanlin Hou ◽  
Yuzhen Han

2022 ◽  
Vol 37 ◽  
pp. 102689
Wei Wu ◽  
Shengsong Huang ◽  
Xiaodong Xie ◽  
Cheng Chen ◽  
Ziwei Yan ◽  

2022 ◽  
Vol 145 ◽  
pp. 104122
Laura J. Bonales ◽  
Nieves Rodríguez-Villagra ◽  
Iván Sánchez-García ◽  
Oscar R. Montoro

Fuel ◽  
2022 ◽  
Vol 312 ◽  
pp. 122980
Xiaojin Guo ◽  
Xiang Xu ◽  
Xiaoyong Xue ◽  
Xiquan Li

2022 ◽  
Vol 372 ◽  
pp. 131146
Huanhuan Li ◽  
Suleiman A. Haruna ◽  
Yin Wang ◽  
Md Mehedi Hassan ◽  
Wenhui Geng ◽  

César Marina-Montes ◽  
Luis V. Pérez-Arribas ◽  
Jesús Anzano ◽  
Silvia Fdez-Ortiz de Vallejuelo ◽  
Julene Aramendia ◽  

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