Metal-Free–Catalyzed Oxidative Trimerization of Indoles Using NaNO₂ to Construct Quaternary Carbon Centers: Synthesis of 2-(1<i>H</i>-Indol-3-yl)-2,3′-biindolin-3-ones

<div><p></p><p>A simple, convenient, and efficient synthesis of 2-(1<i>H</i>-indol-3-yl)-2,3′-biindolin-3-one derivatives via a transition-metal-free-catalyzed oxidative trimeric reaction of indoles has been developed. This transformation may have occurred through a tandem oxidative homocoupling reaction by using NaNO₂ in pyridine as oxidant. This methodology provides an alternative approach for the direct generation of all-carbon quaternary centers at the C2 position of indoles.</p> </div

Table1_Potential therapeutic strategies for quercetin targeting critical pathological mechanisms associated with colon adenocarcinoma and COVID-19.XLSX

Patients with colon adenocarcinoma (COAD) are at a higher probability of infection with COVID-19 than healthy individuals. However, there is no globally accepted treatment protocol for patients with COAD/COVID-19. Quercetin has been found to have significant antitumor, antiviral and anti-inflammatory effects in several studies. Therefore, this study sought to evaluate the potential of quercetin as the agent for COAD/COVID-19 and to explore its mechanisms. We used bioinformatics algorithms to obtain COAD/COVID-19-related genes (CCRG) from COAD-related transcriptome data and COVID-related transcriptome sequencing data, and used these genes to construct a COAD prognostic model. We intersected the CCRG with the therapeutic target genes of quercetin and obtained a total of 105 genes (potential target genes of quercetin for the treatment of COAD/COVID-19). By constructing a protein-protein interaction (PPI) network, we ascertained FOS, NFKB1, NFKB1A, JUNB, and JUN as possible core target genes of quercetin for the treatment of COAD/COVID-19. Bioinformatic analysis of these 105 genes revealed that the mechanisms for quercetin the treatment of COAD/COVID-19 may be associated with oxidative stress, apoptosis, anti-inflammatory, immune, anti-viral and multiple pathways containing IL-17, TNF, HIF-1. In this study, we constructed a prognostic model of COAD/COVID19 patients by using CCRG and elucidated for the first time the potential target genes and molecular mechanisms of quercetin for the treatment of COAD/COVID-19, which may benefit the clinical treatment of COAD/COVID-19 patients. However, no clinical trials have yet been conducted to further validate the findings, but this will be the future direction of our research.</p

Characterization of Cancer Associated Mucin Type O-Glycans Using the Exchange Sialylation Properties of Mammalian Sialyltransferase ST3Gal-II

Our previous studies suggest that the α2,3sialylated T-antigen (NeuAcα2,3Galβ1,3GalNac-) and associated glycan structures are likely to be elevated during cancer. An easy and reliable strategy to label mucinous glycans that contain such carbohydrates can enable the identification of novel glycoproteins that are cancer associated. To this end, the present study demonstrates that the exchange sialylation property of mammalian ST3Gal-II can facilitate the labeling of mucin glycoproteins in cancer cells, tumor specimens, and glycoproteins in cancer sera. Results show that (i) the radiolabeled mucin glycoproteins of each of the cancer cell lines studied (T47D, MCF7, LS180, LNCaP, SKOV₃, HL60, DU4475, and HepG₂) is distinct either in terms of the specific glycans presented or their relative distribution. While some cell lines like T47D had only one single sialylated O-glycan, others like LS180 and DU4475 contained a complex mixture of mucinous carbohydrates. (ii) [¹⁴C]­sialyl labeling of primary tumor cells identified a 25–35 kDa mucin glycoprotein unique to pancreatic tumor. Labeled glycoproteins for other cancers had higher molecular weight. (iii) Studies of [¹⁴C] sialylated human sera showed larger mucin glycopeptides and >2-fold larger mucin-type chains in human serum compared to [¹⁴C]­sialyl labeled glycans of fetuin. Overall, the exchange sialylation property of ST3Gal-II provides an efficient avenue to identify mucinous proteins for applications in glycoproteomics and cancer research

Blocking of VEGF-VEGFR2 pathway abolished the radiosensitization effect of miR-200c.

<p>(A) Elisa assay was used to detect VEGF secretion changes after transfection of miR-200c mimics into A549 cells. Bevacizumab (B) and su1498 (C) were applied to block VEGF-VEGFR2 pathway. Then clonogenic assays were carried out to examine the radiosensitization effect of miR-200c after VEGF-VEGFR2 blockage. Each experiment was repeated three times. Standard errors of the mean are shown by error bars.</p

miR-200c inhibited angiogenesis of endothelial cells.

<p>HUVECs were transfected with miR-200c mimics, miR-200c inhibitors or si-VEGFR2. (A) HUVECs were cultured on Matrigel 48 h after transfection. Representative images of capillary-like structures formed and (B) the length of capillary structure were quantified. (C) The transfected HUVECs were also seeded onto the upper chamber of 8.0-mm pore size 24-well transwell plates to investigate cell migration ability. (D) The migratory cells were counted and statistically analyzed. Each experiment was repeated three times. Standard errors of the mean are shown by error bars. *indicates p<0.05 compared to the control.</p

Western blot analysis of VEGFR2 downstream signaling transduction.

<p>Ectopic expression of miR-200c inhibited phosphorylation of Akt and ERK1/2, inhibition of miR-200c increased activation of Akt and ERK1/2 pathway. Each experiment was repeated three times.</p

Ectopic expression of miR-200c increased the radiosensitivity of A549 cells by inhibiting VEGFR2 expression.

<p>Overexpression of miR-200c (A) enhanced the radiosensitivity of A549 cells to IR treatment, while miR-200c inhibition (B) showed the opposite effect. The si-VEGFR2 construct inhibited VEGFR2 protein expression 48 h post-transfection (C) resulting in the radiosensitization of A549 cells (D). Mimics control, inhibitors control and siRNA control were transfected into A549 cells respectively as negative control. The clonogenic survival assays were repeated three times with similar results. Standard errors of the mean are shown by error bars.</p

Associations between Ionomic Profile and Metabolic Abnormalities in Human Population

<div><h3>Background</h3><p>Few studies assessed effects of individual and multiple ions simultaneously on metabolic outcomes, due to methodological limitation.</p> <h3>Methodology/Principal Findings</h3><p>By combining advanced ionomics and mutual information, a quantifying measurement for mutual dependence between two random variables, we investigated associations of ion modules/networks with overweight/obesity, metabolic syndrome (MetS) and type 2 diabetes (T2DM) in 976 middle-aged Chinese men and women. Fasting plasma ions were measured by inductively coupled plasma mass spectroscopy. Significant ion modules were selected by mutual information to construct disease related ion networks. Plasma copper and phosphorus always ranked the first two among three specific ion networks associated with overweight/obesity, MetS and T2DM. Comparing the ranking of ion individually and in networks, three patterns were observed (1) “Individual ion,” such as potassium and chrome, which tends to work alone; (2) “Module ion,” such as iron in T2DM, which tends to act in modules/network; and (3) “Module-individual ion,” such as copper in overweight/obesity, which seems to work equivalently in either way.</p> <h3>Conclusions</h3><p>In conclusion, by using the novel approach of the ionomics strategy and the information theory, we observed potential associations of ions individually or as modules/networks with metabolic disorders. Certainly, these findings need to be confirmed in future biological studies.</p> </div

Partial spearman correlation coefficients between ions and metabolic features and inflammatory markers (n = 976).

<p>All correlation coefficients were calculated after adjustment for age and sex.</p>*<p>Data not adjusted for itself.</p>†<p><i>P</i><0.001,</p>‡<p><i>P</i><0.01,</p>§<p><i>P</i><0.05.</p

Characteristics of ion concentrations in study participants.

<p>Data are arithmetic mean (SD).</p>*<p>Data not adjusted for itself.</p>†<p>Data are geometric mean (95% CI).</p>‡<p><i>P</i> value<0.05 between 2 groups after adjustment for age and sex. Percentages may not sum to 100 because of rounding.</p