Individual and simultaneous treatment with antipsychotic aripiprazole and antidepressant trazodone inhibit sterol biosynthesis in the adult brain

Polypharmacy, or the simultaneous use of multiple drugs to treat a single patient, is a common practice in psychiatry. Unfortunately, data on the health effects of commonly used combinations of medications are very limited. In this study, we therefore investigated the effects and interactions between two commonly prescribed psychotropic medications with sterol inhibiting side effects, trazodone (TRZ), an antidepressant, and aripiprazole (ARI), an antipsychotic. In vitro cell culture experiments revealed that both medications alone disrupted neuronal and astroglial sterol biosynthesis in dose-dependent manners. Furthermore, when ARI and TRZ were combined, exposure resulted in an additive 7-dehydrocholesterol (7-DHC) increase, as well as desmosterol (DES) and cholesterol decreases in both cell types. In adult mice, at baseline, we found that the three investigated sterols showed significant differences in distribution across the eight assessed brain regions. Furthermore, experimental mice treated with ARI or TRZ, or a combination of both medications for 8 days, showed strong sterol disruption across all brain regions. We show ARI or TRZ alone elevated 7-DHC and decreased DES levels in all brain regions, but with regional differences. However, the combined utilization of these two medications for 8 days did not lead to additive changes in sterol disturbances. Based on the complex roles of 7-DHC derived oxysterols, we conclude that individual and potentially simultaneous use of medications with sterol biosynthesis-inhibiting properties might have undesired side effects on the adult brain, with as yet unknown long-term consequences on mental or physical health.     

Identification of a four-gene metabolic signature predicting overall survival for hepatocellular carcinoma

While hundreds of consistently altered metabolic genes had been identified in hepatocellular carcinoma (HCC), the prognostic role of them remains to be further elucidated. Messenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas—Liver Hepatocellular Carcinoma and GSE14520 data set from the Gene Expression Omnibus database. Univariate Cox regression analysis and lasso Cox regression model established a novel four-gene metabolic signature (including acetyl-CoA acetyltransferase 1, glutamic-oxaloacetic transaminase 2, phosphatidylserine synthase 2, and uridine-cytidine kinase 2) for HCC prognosis prediction. Patients in the high-risk group shown significantly poorer survival than patients in the low-risk group. The signature was significantly correlated with other negative prognostic factors such as higher α-fetoprotein. The signature was found to be an independent prognostic factor for HCC survival. Nomogram including the signature shown some clinical net benefit for overall survival prediction. Furthermore, gene set enrichment analyses revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust four-gene metabolic signature for HCC prognosis prediction. The signature might reflect the dysregulated metabolic microenvironment and provided potential biomarkers for metabolic therapy and treatment response prediction in HCC.     

Sinks and sources of methylmercury in a boreal catchment

A simple, catchment-scale, cascade model was used toassess the importance of sinks and sources ofmethylmercury (MeHg) in a boreal catchment thatcontains a forested upland, a lowland peatland and asmall lake. The three compartment model was run usingrealistic flow rates and atmospheric loading of MeHg,and the model was constrained by observedconcentrations of MeHg in each compartment. Assumingno internal sinks and sources of MeHg, modelledcatchment yields showed reasonable agreement withfield observation, but the predicted internal MeHgconcentrations in each compartment were implausible. Only when sources and sinks of MeHg are added to thethree compartments do MeHg-pool concentrations fallinto the range of those measured in the field. Tomaintain both catchment-scale and compartment-scalecontinuity, the upland and peatland were net sourcesof MeHg (0.0007 and 0.1065 mg ha^-1 d^-1respectively), and the lake a net sink (-0.2215 mgha^-1 d^-1). These source/sink rates are 1.73,259 and -539 times the input of MeHg via wetprecipitation input for the modelled ice-free season. Sensitivity analysis revealed that the volume ofrunoff delivered to the peatland by the upland area,peatland size and porewater MeHg concentration in thepeatland are important controls on catchment MeHgyield, and that contemporary atmospheric deposition ofMeHg is insignificant compared to the sources of MeHgwithin the catchment.     

Origins of regioselectivity in 1,3-dipolar cycloadditions of nitrile oxides with alkynylboronates

Density functional theory (M06-2X) studies of the regioselectivity of 1,3-dipolar cycloaddition reactions of benzo and mesitonitrile oxides with alkynyl pinacol and MIDA boronates are reported. Calculated relative free energies of activation reproduce the experimentally observed product ratios. The electronic energies of activation are found to be mainly controlled by distortion energies required to achieve the transition states. Both electronic and steric effects influence regioselectivities.     

Using phylogeny to investigate the origins of the Cape flora: the importance of taxonomic, gene and genome sampling strategies

Phylogenetic methods hold great promise for the reconstruction of the transition from precursor to modern flora and the identification of underlying factors which drive the process. The phylogenetic methods presently used to address the question of the origin of the Cape flora of South Africa are considered here. The sampling requirements of each of these methods, which include dating of diversifications using calibrated molecular trees, sister pair comparisons, lineage through time plots and biogeographical optimizations, are reviewed. Sampling of genes, genomes and species are considered. Although increased higher-level studies and increased sampling are required for robust interpretation, it is clear that much progress is already made. It is argued that despite the remarkable richness of the flora, the Cape flora is a valuable model system to demonstrate the utility of phylogenetic methods in determining the history of a modern flora.     

Stimulator of interferon genes (STING): A “new chapter” in virus-associated cancer research. Lessons from wild-derived mouse models of innate immunity

Thanks to the numerous studies that have been carried out recently in the field of cytosolic DNA sensing, STING (Stimulator of Interferon Genes) is now recognized as a key mediator of innate immune signaling. A substantial body of evidence derived from in vivo mouse models demonstrates that STING-regulated pathways underlie the pathogenesis of many diseases including infectious diseases and cancers. It has also become evident from these studies that STING is a promising therapeutic target for the treatment of cancer. However, mouse strains commonly used for modelling innate immune response against infections or tumors do not allow investigators to accurately reproduce certain specific characteristics of immune response observed in human cells. In this review, we will discuss recent data demonstrating that the use of wild-derived genetically distinct inbred mice as a model for investigation into the innate immunity signaling networks may provide valuable insight into the STING-regulated pathways specific for human cells. The maximum complexity of STING-mediated mechanisms can probably be seen in case of DNA virus-induced carcinogenesis in which STING may perform unexpected biological activities. Therefore, in another part of this review we will summarize emerging data on the role of STING in human DNA virus-related oncopathologies, with particular attention to HPV-associated cervical cancer, aiming to demonstrate that STING indeed “starts a new chapter” in research on this issue and that wild-derived mouse models of STING-mediated response to infections will probably be helpful in finding out molecular basis for clinical observations.     

Density-dependent population regulation detected in short time series of saproxylic beetles

Understanding the regulation of natural populations has been a long-standing problem in ecology. Here we analyze the population dynamics of 17 species of saproxylic beetles in Shizuoka Prefecture, Japan collected over 11–12 years using autoregressive integrated moving average (ARIMA) models. We first examined the dynamics for indications of the order of the ARIMA models and evaluated the time series to determine that it was not simply a random, white noise sequence. All species dynamics were not mere random noise, and ARIMA models up to lag 3 were considered. The best model was selected from the possible ones using several criteria: model convergence, weak residual autocorrelation, the small sample AIC must be among the smallest that were not significantly different, and the lag indicated by the cutoff values in the detrended partial autocorrelation function. We found significant and nearly significant direct density-dependence for 14 of the 17 species, varying from −0.709 and stronger. The characteristic return rates were strong and only one species had a weak return rate (>0.9), implying that these species were strongly regulated by density-dependent factors. We found that populations with higher order ARIMA models (lag 2 and 3) had weaker return rates than populations with ARIMA models with only one lag, suggesting that species with more complex dynamics were more weakly regulated. These results contrast with previous suggestions that 20+ years are needed to detect density dependence from population time series and that most populations are weakly regulated.