Modulation of molecular mobility in sucrose-based amorphous solids detected by phosphorescence of erythrosin B

This project studied the temperature and composition dependence of molecular mobility in amorphous sucrose. Phosphorescence of erythrosin B provided parameters sensitive to localized molecular mobility in the glass and to more global modes of mobility activated at the glass transition and provided evidence of dynamic site heterogeneity in amorphous sucrose solids. In sucrose-based binary matrices, plasticizer (glycerol), salts (NaCl, CaCl2, MgCl2, Na-citrate, Na-acetate, Na-phosphates), maltodextrins (DE 5 to 18), protein (gelatin), and polysaccharides (xanthan and high amylose starch) were selected to investigate how variations in nature and content of each additive influence the molecular mobility as well as dynamic site heterogeneity in amorphous sucrose matrix. Measurements of phosphorescence intensity, lifetime, and emission energy were made in amorphous sucrose-additive films containing the probe erythrosin B. Results showed the complex effects of additives on the mobility in a hydrogen-bonded sugar matrix. Glycerol exhibited an antiplasticization effect shown as decreased mobility at glycerol/sucrose mole ratio ≤ 0.27 and at temperature ≤ 45° C. On the contrary, all the polymers studied, including gelatin, xanthan and high amylose starch, displayed a ‘plasticization’ effect (increasing mobility) at very low while a rigidification effect (decreasing mobility) at higher concentration without significant change in Tg. Maltodextrins, mixtures of molecules with a variety of molecular weights, increase the mobility in spite of their high Tg. Sodium chloride showed a strong rigidification effect on the sucrose matrix; however, this effect was weakened at mole ratio NaCl/sucrose above 0.5. Other salts showed effects resulting from a compromise between two opposite actions (decreasing mobility due to salt itself and increasing mobility due to absorbed moisture). All above behaviors are difficult to interpret using Tg alone. Molecular mobility appears to be more accurate to evaluate the physical stability of the matrix. Phosphorescence of erythrosin B was also able to report dynamic site heterogeneity that is an intrinsic property of the amorphous solid state. The heterogeneity was be evaluated by the variation of lifetime and lifetime heterogeneity across the excitation and emission band and the temperature dependence of bandwidth and lifetime heterogeneity. The composition influence on the dynamic site heterogeneity was discussed as well.Ph.D.Includes bibliographical references

Erythrosin B Phosphorescence Monitors Molecular Mobility and Dynamic Site Heterogeneity in Amorphous Sucrose

Molecular mobility modulates the chemical and physical stability of amorphous biomaterials. This study used steady-state and time-resolved phosphorescence of erythrosin B to monitor mobility in thin films of amorphous solid sucrose as a function of temperature. The phosphorescence intensity (lifetime), emission energy, and red-edge excitation effect were all sensitive to localized molecular mobility on the microsecond timescale in the glass and to more global modes of mobility activated at the glass transition. Blue shifts in the emission spectrum with time after excitation and systematic variations in the phosphorescence lifetime with wavelength indicated that emission originates from multiple sites ranging from short lifetime species with red-shifted emission spectrum to long lifetime species with blue-shifted emission spectrum; the activation energy for nonradiative decay of the triplet state was considerably larger for the blue-emitting species in both the glass and the melt. This study illustrates that phosphorescence from erythrosin B is sensitive both to local dipolar relaxations in the glass as well as more global relaxations in the sucrose melt and provides evidence of the value of phosphorescence as a probe of dynamic site heterogeneity as well as overall molecular mobility in amorphous biomaterials

Table_3_DPP6 and MFAP5 are associated with immune infiltration as diagnostic biomarkers in distinguishing uterine leiomyosarcoma from leiomyoma.xlsx

ObjectiveUterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM.MethodsTwo public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS.ResultIn total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non−small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (PConclusionThese findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.</p

Table_1_DPP6 and MFAP5 are associated with immune infiltration as diagnostic biomarkers in distinguishing uterine leiomyosarcoma from leiomyoma.docx

ObjectiveUterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM.MethodsTwo public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS.ResultIn total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non−small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (PConclusionThese findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.</p

Table_4_DPP6 and MFAP5 are associated with immune infiltration as diagnostic biomarkers in distinguishing uterine leiomyosarcoma from leiomyoma.xlsx

ObjectiveUterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM.MethodsTwo public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS.ResultIn total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non−small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (PConclusionThese findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.</p

Table_2_DPP6 and MFAP5 are associated with immune infiltration as diagnostic biomarkers in distinguishing uterine leiomyosarcoma from leiomyoma.docx

ObjectiveUterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM.MethodsTwo public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS.ResultIn total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non−small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (PConclusionThese findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.</p

Metabolic reprogramming and redox adaptation in sorafenib-resistant leukemia cells: detected by untargeted metabolomics and stable isotope tracing analysis

Abstract Background Internal tandem duplications (ITD) within the juxtamembrane domain of FMS-like tyrosine kinase 3 (FLT3) represent a poor prognostic indicator in acute myeloid leukemia (AML). Therapeutic benefits of tyrosine kinase inhibitors, such as sorafenib, are limited due to the emergence of drug resistance. While investigations have been conducted to improve the understanding of the molecular mechanisms underlying the resistance to this FLT3 inhibitor, a profile of cell functioning at the metabolite level and crosstalk between metabolic pathways has yet to be created. This study aimed to elucidate the alteration of metabolomic profile of leukemia cells resistant to the FLT3 inhibitor. Methods We established two sorafenib-resistant cell lines carrying FLT3/ITD mutations, namely the murine BaF3/ITD-R and the human MV4-11-R cell lines. We performed a global untargeted metabolomics and stable isotope-labeling mass spectrometry analysis to identify the metabolic alterations relevant to the therapeutic resistance. Results The resistant cells displayed fundamentally rewired metabolic profiles, characterized by a higher demand for glucose, accompanied by a reduction in glucose flux into the pentose phosphate pathway (PPP); and by an increase in oxidative stress, accompanied by an enhanced glutathione synthesis. We demonstrated that the highest scoring network of altered metabolites in resistant cells was related to nucleotide degradation. A stable isotope tracing experiment was performed and the results indicated a decrease in the quantity of glucose entering the PPP in resistant cells. Further experiment suggested that the inhibition of major enzymes in the PPP consist of glucose-6-phosphate dehydrogenase deficiency (G6PD) in the oxidative arm and transketolase (TKT) in the non-oxidative arm. In addition, we observed that chronic treatment with sorafenib resulted in an increased oxidative stress in FLT3/ITD-positive leukemia cells, which was accompanied by decreased cell proliferation and an enhanced antioxidant response. Conclusions Our data regarding comparative metabolomics characterized a distinct metabolic and redox adaptation that may contribute to sorafenib resistance in FLT3/ITD-mutated leukemia cells

Lysine methylation of FOXO3 regulates oxidative stress-induced neuronal cell death

FOXO transcription factors have a critical role in oxidative stress-induced neuronal cell death. A variety of post-translational modifications of FOXO family proteins have been reported, including phosphorylation, acetylation, ubiqutination and recently arginine methylation. Here, we demonstrate that the methyltransferase Set9 methylates FOXO3 at lysine 270. Methylation of FOXO3 leads to the inhibition of its DNA-binding activity and transactivation. Accordingly, lysine methylation reduces oxidative stress-induced and FOXO3-mediated Bim expression and neuronal apoptosis in neurons. Collectively, these findings define a novel modification of FOXO3 and show that lysine methylation negatively regulates FOXO3-mediated transcription and neuronal apoptosis.National Science Foundation of China [30870792, 81030025, 81125010]; Ministry of Science and Technology of China [973-2009CB918704, 2012CB910701