Image1_High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.TIF

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.</p

Table1_High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.DOCX

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.</p

Table2_High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.DOCX

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.</p

Image3_High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.TIF

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.</p

Image2_High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.TIF

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.</p

Image4_High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.TIF

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.</p

Image_1_Serum proteomic biomarker investigation of vascular depression using data-independent acquisition: a pilot study.TIF

BackgroundVascular depression (VaD) is a depressive disorder closely associated with cerebrovascular disease and vascular risk factors. It remains underestimated owing to challenging diagnostics and limited information regarding the pathophysiological mechanisms of VaD. The purpose of this study was to analyze the proteomic signatures and identify the potential biomarkers with diagnostic significance in VaD.MethodsDeep profiling of the serum proteome of 35 patients with VaD and 36 controls was performed using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Functional enrichment analysis of the quantified proteins was based on Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Reactome databases. Machine learning algorithms were used to screen candidate proteins and develop a protein-based model to effectively distinguish patients with VaD.ResultsThere were 29 up-regulated and 31 down-regulated proteins in the VaD group compared to the controls (|log2FC| ≥ 0.26, p ≤ 0.05). Enrichment pathways analyses showed that neurobiological processes related to synaptic vesicle cycle and axon guidance may be dysregulated in VaD. Extrinsic component of synaptic vesicle membrane was the most enriched term in the cellular components (CC) terms. 19 candidate proteins were filtered for further modeling. A nomogram was developed with the combination of HECT domain E3 ubiquitin protein ligase 3 (HECTD3), Nidogen-2 (NID2), FTO alpha-ketoglutarate-dependent dioxygenase (FTO), Golgi membrane protein 1 (GOLM1), and N-acetylneuraminate lyase (NPL), which could be used to predict VaD risk with favorable efficacy.ConclusionThis study offers a comprehensive and integrated view of serum proteomics and contributes to a valuable proteomics-based diagnostic model for VaD.</p

Image_2_Serum proteomic biomarker investigation of vascular depression using data-independent acquisition: a pilot study.TIF

BackgroundVascular depression (VaD) is a depressive disorder closely associated with cerebrovascular disease and vascular risk factors. It remains underestimated owing to challenging diagnostics and limited information regarding the pathophysiological mechanisms of VaD. The purpose of this study was to analyze the proteomic signatures and identify the potential biomarkers with diagnostic significance in VaD.MethodsDeep profiling of the serum proteome of 35 patients with VaD and 36 controls was performed using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Functional enrichment analysis of the quantified proteins was based on Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Reactome databases. Machine learning algorithms were used to screen candidate proteins and develop a protein-based model to effectively distinguish patients with VaD.ResultsThere were 29 up-regulated and 31 down-regulated proteins in the VaD group compared to the controls (|log2FC| ≥ 0.26, p ≤ 0.05). Enrichment pathways analyses showed that neurobiological processes related to synaptic vesicle cycle and axon guidance may be dysregulated in VaD. Extrinsic component of synaptic vesicle membrane was the most enriched term in the cellular components (CC) terms. 19 candidate proteins were filtered for further modeling. A nomogram was developed with the combination of HECT domain E3 ubiquitin protein ligase 3 (HECTD3), Nidogen-2 (NID2), FTO alpha-ketoglutarate-dependent dioxygenase (FTO), Golgi membrane protein 1 (GOLM1), and N-acetylneuraminate lyase (NPL), which could be used to predict VaD risk with favorable efficacy.ConclusionThis study offers a comprehensive and integrated view of serum proteomics and contributes to a valuable proteomics-based diagnostic model for VaD.</p

Data_Sheet_2_Serum proteomic biomarker investigation of vascular depression using data-independent acquisition: a pilot study.docx

BackgroundVascular depression (VaD) is a depressive disorder closely associated with cerebrovascular disease and vascular risk factors. It remains underestimated owing to challenging diagnostics and limited information regarding the pathophysiological mechanisms of VaD. The purpose of this study was to analyze the proteomic signatures and identify the potential biomarkers with diagnostic significance in VaD.MethodsDeep profiling of the serum proteome of 35 patients with VaD and 36 controls was performed using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Functional enrichment analysis of the quantified proteins was based on Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Reactome databases. Machine learning algorithms were used to screen candidate proteins and develop a protein-based model to effectively distinguish patients with VaD.ResultsThere were 29 up-regulated and 31 down-regulated proteins in the VaD group compared to the controls (|log2FC| ≥ 0.26, p ≤ 0.05). Enrichment pathways analyses showed that neurobiological processes related to synaptic vesicle cycle and axon guidance may be dysregulated in VaD. Extrinsic component of synaptic vesicle membrane was the most enriched term in the cellular components (CC) terms. 19 candidate proteins were filtered for further modeling. A nomogram was developed with the combination of HECT domain E3 ubiquitin protein ligase 3 (HECTD3), Nidogen-2 (NID2), FTO alpha-ketoglutarate-dependent dioxygenase (FTO), Golgi membrane protein 1 (GOLM1), and N-acetylneuraminate lyase (NPL), which could be used to predict VaD risk with favorable efficacy.ConclusionThis study offers a comprehensive and integrated view of serum proteomics and contributes to a valuable proteomics-based diagnostic model for VaD.</p

Data_Sheet_1_Serum proteomic biomarker investigation of vascular depression using data-independent acquisition: a pilot study.xlsx

BackgroundVascular depression (VaD) is a depressive disorder closely associated with cerebrovascular disease and vascular risk factors. It remains underestimated owing to challenging diagnostics and limited information regarding the pathophysiological mechanisms of VaD. The purpose of this study was to analyze the proteomic signatures and identify the potential biomarkers with diagnostic significance in VaD.MethodsDeep profiling of the serum proteome of 35 patients with VaD and 36 controls was performed using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Functional enrichment analysis of the quantified proteins was based on Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Reactome databases. Machine learning algorithms were used to screen candidate proteins and develop a protein-based model to effectively distinguish patients with VaD.ResultsThere were 29 up-regulated and 31 down-regulated proteins in the VaD group compared to the controls (|log2FC| ≥ 0.26, p ≤ 0.05). Enrichment pathways analyses showed that neurobiological processes related to synaptic vesicle cycle and axon guidance may be dysregulated in VaD. Extrinsic component of synaptic vesicle membrane was the most enriched term in the cellular components (CC) terms. 19 candidate proteins were filtered for further modeling. A nomogram was developed with the combination of HECT domain E3 ubiquitin protein ligase 3 (HECTD3), Nidogen-2 (NID2), FTO alpha-ketoglutarate-dependent dioxygenase (FTO), Golgi membrane protein 1 (GOLM1), and N-acetylneuraminate lyase (NPL), which could be used to predict VaD risk with favorable efficacy.ConclusionThis study offers a comprehensive and integrated view of serum proteomics and contributes to a valuable proteomics-based diagnostic model for VaD.</p