BackgroundLung cancer remains the leading cause of cancer-related mortality despite continuous efforts to find effective treatments. Data from the American Cancer Society indicate that while the overall incidence of lung cancer is declining, it continues to rise in women. Stem cell-based therapy has been an emerging strategy to treat various diseases. The purpose of this paper is to determine the efficacy of an intrinsic anti-cancer effect of rat umbilical cord matrix stem cells (UCMSCs) on lung cancer.MethodsA mouse syngeneic lung carcinoma model was used to test the basic ability of UCMSCs to control the growth of lung cancer. Lung tumors were experimentally induced by tail vein administration of Lewis lung carcinoma (LLC) cells derived from the lung of C57BL/6 mouse. Rat UCMSCs were then administered intratracheally five days later or intravenously on days 5 and 7. The tumor burdens were determined by measuring lung weight three weeks after the treatment.ResultsCo-culture of rat UCMSCs with LLC significantly attenuated the proliferation of LLC cells as monitored by MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide), a tetrazole cell proliferation assay, thymidine uptake, and direct cell counts. In vitro colony assays with rat UCMSCs as feeder layers markedly reduced LLC colony size and number. Co-culture of rat UCMSCs with LLCs causes G0/G1 arrest of cancer cells. This is evident in the decrease of cyclin A and CDK2 expression. The in vivo studies showed that rat UCMSC treatment significantly decreased tumor weight and the total tumor mass. Histological study revealed that intratracheally or systemically administered rat UCMSCs homed to tumor areas and survived for at least 3 weeks without any evidence of differentiation or adverse effects.ConclusionsThese results indicate that rat UCMSCs alone remarkably attenuate the growth of lung carcinoma cells in vitro and in a mouse syngeneic lung carcinoma graft model and could be used for targeted cytotherapy for lung cancer.
The diterpene geranylgeraniol (all trans-3,7,11,15-tetramethyl-2,6,10,14-hexadecatetraen-1-ol) suppresses the growth of human liver, lung, ovary, pancreas, colon, stomach and blood tumors with undefined mechanisms. We evaluated the growth-suppressive activity of geranylgeraniol in murine B16 melanoma cells. Geranylgeraniol induced dose-dependent suppression of B16 cell growth (IC(50) = 55 ± 13 µmol/L) following a 48-h incubation in 96-well plates. Cell cycle arrest at the G1 phase, manifested by a geranylgeraniol-induced increase in the G1/S ratio and decreased expression of cyclin D1 and cyclin-dependent kinase 4, apoptosis detected by Guava Nexin™ assay and fluorescence microscopy following acridine orange and ethidium bromide dual staining, and cell differentiation shown by increased alkaline phosphatase activity, contributed to the growth suppression. Murine 3T3-L1 fibroblasts were 10-fold more resistant than B16 cells to geranylgeraniol-mediated growth suppression. Geranylgeraniol at near IC(50) concentration (60 µmol/L) suppressed the mRNA level of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase by 50%. The impact of geranylgeraniol on B16 cell growth, cell cycle arrest and apoptosis were attenuated by supplemental mevalonate, the product of HMG-CoA reductase that is essential for cell growth. Geranylgeraniol and d-δ-tocotrienol, a down-regulator of HMG-CoA reductase, additively suppressed the growth of B16 cells. These results support our hypothesis that mevalonate depletion mediates the tumor-specific growth-suppressive impact of geranylgeraniol. Geranylgeraniol may have potential in cancer chemoprevention and/or therapy.
The effects of climate change on tropical forests may have global consequences due to the forests’ high biodiversity and major role in the global carbon cycle. In this study, we document the effects of experimental warming on the abundance and composition of a tropical forest floor herbaceous plant community in the Luquillo Experimental Forest, Puerto Rico. This study was conducted within Tropical Responses to Altered Climate Experiment (TRACE) plots, which use infrared heaters under free‐air, open‐field conditions, to warm understory vegetation and soils + 4°C above nearby control plots. Hurricanes Irma and María damaged the heating infrastructure in the second year of warming, therefore, the study included one pretreatment year, one year of warming, and one year of hurricane response with no warming. We measured percent leaf cover of individual herbaceous species, fern population dynamics, and species richness and diversity within three warmed and three control plots. Results showed that one year of experimental warming did not significantly affect the cover of individual herbaceous species, fern population dynamics, species richness, or species diversity. In contrast, herbaceous cover increased from 20% to 70%, bare ground decreased from 70% to 6%, and species composition shifted pre to posthurricane. The negligible effects of warming may have been due to the short duration of the warming treatment or an understory that is somewhat resistant to higher temperatures. Our results suggest that climate extremes that are predicted to increase with climate change, such as hurricanes and droughts, may cause more abrupt changes in tropical forest understories than longer‐term sustained warming.
Quantile regression (QR) allows one to model the effect of covariates across the entire response distribution, rather than only at the mean, but QR methods have been almost exclusively applied to continuous response variables produced by a single data-generating process. Of the few studies that have performed QR on count data, none have accounted for excess zeros from a Bayesian perspective, as does the hurdle model that we propose. In this article, we propose a Bayesian two-part QR model for count data with excess zeros. The proposed model is compared to a frequentist approach via simulation, and its usefulness is displayed on two real datasets. In each application, multiple covariates are found to have differing effects across the response distribution, with special attention given to the nature of those effects in the outermost response distribution quantiles.
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