Efficient Synthesis of 3-Iodoindenes via Lewis-Acid Catalyzed Friedel−Crafts Cyclization of Iodinated Allylic Alcohols

A convenient BF3·Et2O-catalyzed Friedel−Crafts cyclization of iodinated allylic alcohols is reported. The present reaction provides an efficient protocol to 3-iodo-1H-indene derivatives in good to high yields under mild conditions. Further, the iodoindene derivatives are valuable synthetic building blocks for elaboration of molecular complexity, such as in the construction of multiaryl substituted indenes by Suzuki coupling reaction

Additional file 1 of Prevalence and factors associated with smartphone addiction among nursing postgraduates during the COVID-19 pandemic: a multilevel study from China’s mainland

Additional file 1: Fig. S1. Normal P–P graph of the standardized residual regression. Fig. S2. Dispersion graph of the dependent variable ‘SAS-C’

Connected regulatory network for network 18.

<p>Connected regulatory network for network 18. Red nodes are transcription factors, blue nodes are splicing factors and gray nodes in the middle are targets. The connection between targets is from IPA and the connection between factors and targets are from our interaction strength matrix.</p

qRT-PCR and Western blot analysis to determine the effect of WNT5A on AR-signaling associated genes and proteins in androgen-resistant 22RV1 prostate cancer cells.

(A-D) The gene expression levels of FZD5, TNFSF10, BMP6 and AR at 0.5, 1, 3, 7 and 24h after treatment with WNT5A, respectively. (E-G) The effect of WNT5A on protein levels of skp2, Foxo1 and pERK, respectively.</p

Efficient Synthesis of 3-Iodoindenes via Lewis-Acid Catalyzed Friedel−Crafts Cyclization of Iodinated Allylic Alcohols

A convenient BF3·Et2O-catalyzed Friedel−Crafts cyclization of iodinated allylic alcohols is reported. The present reaction provides an efficient protocol to 3-iodo-1H-indene derivatives in good to high yields under mild conditions. Further, the iodoindene derivatives are valuable synthetic building blocks for elaboration of molecular complexity, such as in the construction of multiaryl substituted indenes by Suzuki coupling reaction

Experimental observation and <i>in silico</i> prediction of HMSM Model.

The bars with blue color are experimental-measured values, and the bars with green color are predicted values in the HMSM model. CX: Castration. Time 0 denotes pre-castration. (A) A simulation example of prostate tumor before/after castration. I) pre-castration; II) 2.5 weeks after castration; III) 5 weeks after castration. (B) A simulation example of cytokine profiles before/after castration. I) pre-castration; II) 2.5 weeks after castration; III) 5 weeks after castration. The slices are extracted when Y = 50. Y is the Y axis. (C) TAMs are elevated by ADT in prostate cancer (day 7 and day 14 castration). (D) CSF1 protein level was analyzed from castrated mice (day 2 and day 35 castration). (E) Relative gene expression of IL10 and VEGF at 48hours after ADT. (F) PLX lowered macrophage levels and VEGF expression after ADT. (G) The number of Treg cells is increased in lymph nodes at 2.5 weeks and 5 weeks post-castration. (H) Treg expansion in lymph nodes was reduced by IL-2 neutralization. (I) In silico prediction of CD8+ cells in the castrated tumor at 2.5 and 5 weeks. (J) In silico prediction of Treg cells in the castrated tumor at 2.5 and 5 weeks. (K) In silico prediction of single or combined treatment on PC growth after castration relative to pre-castration. (L-N) The predictions and experimental validations for prostate tumor growth with castration only (L) or plus CSF1R (M) or plus EGFR inhibition (N) after castration.</p

ODE modeling of WNT5A-EGF/AR signaling and experimental validation.

(A) The effect of WNT5A on 22RV1 cell viability. (B) The effect of EGF on 22RV1 cell viability. (C) The effect of WNT5A and EGF on protein levels of Skp2, pERK, pAKT and AR. (D) The network topology of androgen-independent pathways in prostate cancer cells. WNT5A or EGF regulates the cellular proliferation by activating AR-related pathway. This network was represented as a series of ODE equations shown in Eq. (1–6) in the section “Materials and methods”. (E) The predicted values of four proteins fit the observation data well. (F, G) The ODE system-predicted PC proliferation at 72 hours perturbed by WNT5A (F) or EGF (G) with different doses. (H, I) Sensitivity analysis of the ODE system was performed under two conditions: WNT5A treatment only (H), and EGF treatment only (I). Each parameter was perturbed by increasing or decreasing 5%.</p

The system modeling diagram of CRPC development.

The HMSM model includes two components: prostate cancer compartment (left) and lymph node compartment (right). The arrows represent cell-cell communications, which were inferred from our data or other public datasets.</p

Schematic representation of computational framework of HMSM model.

Schematic representation of computational framework of HMSM model.</p

Inference of TAM-PC interactions with RNA-Seq data.

(A) The left panel shows the RNA-seq data from the cocultured macrophage and PC LnCap and 22RV1 cells. Prostate cancer cells (LNCaP or 22RV1) were co-cultured with or without M2 macrophage (TAM) for 48 h and RNA samples were collected for RNA-seq analysis. All of the gene expression data (fold change value) were normalized with non-co-cultured counterpart cells. For example, LNCaP W/WO TAM shows the gene expression ratio of LNCaP cells co-cultured with TAM to LNCaP cells not co-cultured with TAM. The top-ranked overexpressed genes with FC>1.3 are presented. Five enriched ligand-receptor pairs were highlighted. (B) The inferred cell-cell interaction networks between TAM, Treg, 22RV1.</p