Infection efficiency of <i>piggyBac</i> Transposon system.

<p>(A). Schematic diagram of pMPH86, the <i>piggyBac</i> Transposon-mediated reversible vector for immortalization, that includes SV40 T-Ag and hygromycin B expression cassette. (B). Cell transducted by AdpBase or AdFLP for 24 hours. (a). DFCs transducted efficiently by adenoviral vectors AdpBase to establish immortalized dental follicle cells (iDFCs) (b). Efficient transduction of iDFCs by adenoviral vectors AdFLP to get deimmortalized dental follicle cells (dDFCs). (C). Hygromycin B selection. (a). Survival rate of cells infected with pMPH86 is 30%. (b). Survival rate of cells infected with <i>SSR#69</i> is 10%. (D). Expression of SV40T-Ag in cells infected with pMPH86 or <i>SSR#69</i>. (E). Integration of SV40T-Ag gene in cells infected with pMPH86 or <i>SSR#69</i>.</p

Establishment of single-colony-derived DFCs.

<p>(A). Clone forming of DFCs. Limiting dilution was used for single clone selection. One single cell was observed after the procedure (a), several days later the cells formed a clone in which more than 50 cells were observed (d). (B). Morphological change of DFCs after several passages. (a). At passage 3, DFCs were fibroblast-like cells. (b). Cells became flat after more than 5 passages.</p

Adipogenic differentiation of DFCs, iDFCs and dDFCs.

<p>(A) DFCs, iDFCs and dDFCs can be induced to form adipocyte-like cells. Subconfluent DFCs, iDFCs and dDFCs were infected by adenovirus Ad PPARγ2 (a). or AdRFP (data unshown). 5 days after adipogenic induction, lipid droplets can be seen clearly under phase contrast microscope (b). Lipid droplets can be stain by oil red as compared to the control groups infected by AdRFP(c). (B) The expression of PPARγ2 after adipogenic differentiation of DFCs, iDFCs and dDFCs. Subconfluent cells were transducted by AdPPARγ2 or AdRFP as negative control. On day 5, western blotting was performed using anti- PPARγ2 antibody. Anti-GAPDH Western blotting ensures the same amount of samples loaded. Samples infected by AdRFP didn’t express PPARγ2. (D) Expression of adipogenic lineage-specific genes in DFCs, iDFCs and dDFCs stimulated by PPARγ2. The assays were done in three experiments. Note: *<i>p</i> < 0.05.</p

Morphology and cell proliferation of three types of DFCs.

<p>(A) Morphology of primary dental follicle cells (DFCs), immortalized dental follicle cells (iDFCs) and deimmortalized dental follicle cells (dDFCs). Primary DFCs and deimmortalized DFCs were seeded at 20% confluence and cultured for three passages (<i>P3</i>)(a and c). iDFCs were seeded at 20% confluence and cultured for 60 passages (<i>P60</i>) (b). (B) Cell proliferation assessed with CCK8 assay. (C) Cell growth curve.</p

Telomerase activity of three types of DFCs.

<p>iDFCs maintain high telomerase activity while the telomerase activity of dDFCs is similar to primary DFCs. Telomerase activity of primary DFCs and dDFCs was tested at <i>p1</i>, <i>p3</i>, <i>p5</i> and <i>p7</i>. Telomerase activity of iDFCs was tested at <i>p1</i>, <i>p5</i>, <i>p10</i>, <i>p30</i>, and <i>p60</i>. The telomerase activity of cells was measured by telomeric repeat amplification protocol.</p

The DFCs, iDFCs and dDFCs express mesenchymal stem cell surface markers.

<p>(A) iDFCs and dDFCs possess DFCs properties. iDFCs and dDFCs are both vimentin positive and ck14 negative just the same as DFCs. (B) DFCs, iDFCs and dDFCs express mesenchymal stem cell surface markers, i.e. CD73 (a) and CD105 (b), but lack the expression of CD34(c). The percentage of strol-1 positive cells is about 13%(d).</p

Osteogenic differentiation of DFCs, iDFCs and dDFCs.

<p>(A) Induction of alkaline phosphatase (ALP), the early stage of osteogenic differentiation marker and alizarin red, the late matrix mineralization marker in DFCs, iDFCs and dDFCs after osteogenic differentiation. Subconfluent DFCs, iDFCs and dDFCs were infected by adenovirus AdBMP9 (a) or AdGFP (data unshown). ALP activity of cells was stained on day 7 and measured quantitatively at days 3, 5 and 7 (c). (B) The expression of osteopontin after osteogenic Induction of DFCs, iDFCs and dDFCs. Cells were transducted by AdBMP9 (a) or AdGFP. Anti-GAPDH Western blotting ensures the same amount of samples loaded. Samples infected by AdGFP didn’t express osteopontin. (D) Expression of osteogenic lineage-specific genes in DFCs, iDFCs and dDFCs after being induced by BMP9. Cells were transducted with AdBMP9 or AdGFP as negative control. The assays were done in three experiments. Note: *<i>p</i> < 0.05.</p

Image_1_Deep analysis of skin molecular heterogeneities and their significance on the precise treatment of patients with psoriasis.jpeg

BackgroundPsoriasis is a highly heterogeneous autoinflammatory disease. At present, heterogeneity in disease has not been adequately translated into concrete treatment options. Our aim was to develop and verify a new stratification scheme that identifies the heterogeneity of psoriasis by the integration of large-scale transcriptomic profiles, thereby identifying patient subtypes and providing personalized treatment options whenever possible.MethodsWe performed functional enrichment and network analysis of upregulated differentially expressed genes using microarray datasets of lesional and non-lesional skin samples from 250 psoriatic patients. Unsupervised clustering methods were used to identify the skin subtypes. Finally, an Xgboost classifier was utilized to predict the effects of methotrexate and commonly prescribed biologics on skin subtypes.ResultsBased on the 163 upregulated differentially expressed genes, psoriasis patients were categorized into three subtypes (subtypes A–C). Immune cells and proinflammatory-related pathways were markedly activated in subtype A, named immune activation. Contrastingly, subtype C, named stroma proliferation, was enriched in integrated stroma cells and tissue proliferation-related signaling pathways. Subtype B was modestly activated in all the signaling pathways. Notably, subtypes A and B presented good responses to methotrexate and interleukin-12/23 inhibitors (ustekinumab) but inadequate responses to tumor necrosis factor-α inhibitors and interleukin-17A receptor inhibitors. Contrastly, subtype C exhibited excellent responses to tumor necrosis factor-α inhibitors (etanercept) and interleukin-17A receptor inhibitors (brodalumab) but not methotrexate and interleukin-12/23 inhibitors.ConclusionsPsoriasis patients can be assorted into three subtypes with different molecular and cellular characteristics based on the heterogeneity of the skin's immune cells and the stroma, determining the clinical responses of conventional therapies.</p

Table_1_Deep analysis of skin molecular heterogeneities and their significance on the precise treatment of patients with psoriasis.docx

BackgroundPsoriasis is a highly heterogeneous autoinflammatory disease. At present, heterogeneity in disease has not been adequately translated into concrete treatment options. Our aim was to develop and verify a new stratification scheme that identifies the heterogeneity of psoriasis by the integration of large-scale transcriptomic profiles, thereby identifying patient subtypes and providing personalized treatment options whenever possible.MethodsWe performed functional enrichment and network analysis of upregulated differentially expressed genes using microarray datasets of lesional and non-lesional skin samples from 250 psoriatic patients. Unsupervised clustering methods were used to identify the skin subtypes. Finally, an Xgboost classifier was utilized to predict the effects of methotrexate and commonly prescribed biologics on skin subtypes.ResultsBased on the 163 upregulated differentially expressed genes, psoriasis patients were categorized into three subtypes (subtypes A–C). Immune cells and proinflammatory-related pathways were markedly activated in subtype A, named immune activation. Contrastingly, subtype C, named stroma proliferation, was enriched in integrated stroma cells and tissue proliferation-related signaling pathways. Subtype B was modestly activated in all the signaling pathways. Notably, subtypes A and B presented good responses to methotrexate and interleukin-12/23 inhibitors (ustekinumab) but inadequate responses to tumor necrosis factor-α inhibitors and interleukin-17A receptor inhibitors. Contrastly, subtype C exhibited excellent responses to tumor necrosis factor-α inhibitors (etanercept) and interleukin-17A receptor inhibitors (brodalumab) but not methotrexate and interleukin-12/23 inhibitors.ConclusionsPsoriasis patients can be assorted into three subtypes with different molecular and cellular characteristics based on the heterogeneity of the skin's immune cells and the stroma, determining the clinical responses of conventional therapies.</p

Additional file 1: Table S1. of Event-related potentials elicited by the Deutsch “high-low” word illusion in the patients with first-episode schizophrenia with auditory hallucinations

Pearson correlations between ERP latencies and amplitudes and PANSS scores in schizophrenia (n = 16). (DOCX 26 kb