Underwater Leidenfrost nanochemistry for creation of size-tailored zinc peroxide cancer nanotherapeutics

The dynamic underwater chemistry seen in nature is inspiring for the next generation of eco-friendly nanochemistry. In this context, green synthesis of size-tailored nanoparticles in a facile and scalable manner via a dynamic process is an interesting challenge. Simulating the volcano-induced dynamic chemistry of the deep ocean, here we demonstrate the Leidenfrost dynamic chemistry occurring in an underwater overheated confined zone as a new tool for customized creation of nanoclusters of zinc peroxide. The hydrodynamic nature of the phenomenon ensures eruption of the nanoclusters towards a much colder region, giving rise to growth of monodisperse, size-tailored nanoclusters. Such nanoparticles are investigated in terms of their cytotoxicity on suspension and adherent cells to prove their applicability as cancer nanotherapeutics. Our research can pave the way for employment of the dynamic green nanochemistry in facile, scalable fabrication of size-tailored nanoparticles for biomedical applications.Peer reviewe

Lifespan extension without fertility reduction following dietary addition of the autophagy activator Torin1 in Drosophila melanogaster

Autophagy is a highly conserved mechanism for cellular repair that becomes progressively down-regulated during normal ageing. Hence, manipulations that activate autophagy could increase lifespan. Previous reports show that manipulations to the autophagy pathway can result in longevity extension in yeast, flies, worms and mammals. Under standard nutrition, autophagy is inhibited by the nutrient sensing kinase Target of Rapamycin (TOR). Therefore, manipulations of TOR that increase autophagy may offer a mechanism for extending lifespan. Ideally, such manipulations should be specific and minimise off-target effects, and it is important to discover additional methods for ‘clean’ lifespan manipulation. Here we report an initial study into the effect of up-regulating autophagy on lifespan and fertility in Drosophila melanogaster by dietary addition of Torin1. Activation of autophagy using this selective TOR inhibitor was associated with significantly increased lifespan in both sexes. Torin1 induced a dose-dependent increase in lifespan in once-mated females. There was no evidence of a trade-off between longevity and fecundity or fertility. Torin1-fed females exhibited significantly elevated fecundity, but also elevated egg infertility, resulting in no net change in overall fertility. This supports the idea that lifespan can be extended without trade-offs in fertility and suggest that Torin1 may be a useful tool with which to pursue anti-ageing research

Gene Expression Profiles of Sporadic Canine Hemangiosarcoma Are Uniquely Associated with Breed

The role an individual's genetic background plays on phenotype and biological behavior of sporadic tumors remains incompletely understood. We showed previously that lymphomas from Golden Retrievers harbor defined, recurrent chromosomal aberrations that occur less frequently in lymphomas from other dog breeds, suggesting spontaneous canine tumors provide suitable models to define how heritable traits influence cancer genotypes. Here, we report a complementary approach using gene expression profiling in a naturally occurring endothelial sarcoma of dogs (hemangiosarcoma). Naturally occurring hemangiosarcomas of Golden Retrievers clustered separately from those of non-Golden Retrievers, with contributions from transcription factors, survival factors, and from pro-inflammatory and angiogenic genes, and which were exclusively present in hemangiosarcoma and not in other tumors or normal cells (i.e., they were not due simply to variation in these genes among breeds). Vascular Endothelial Growth Factor Receptor 1 (VEGFR1) was among genes preferentially enriched within known pathways derived from gene set enrichment analysis when characterizing tumors from Golden Retrievers versus other breeds. Heightened VEGFR1 expression in these tumors also was apparent at the protein level and targeted inhibition of VEGFR1 increased proliferation of hemangiosarcoma cells derived from tumors of Golden Retrievers, but not from other breeds. Our results suggest heritable factors mold gene expression phenotypes, and consequently biological behavior in sporadic, naturally occurring tumors

In Vitro Surfactant Structure-Toxicity Relationships: Implications for Surfactant Use in Sexually Transmitted Infection Prophylaxis and Contraception

Background The need for woman-controlled, cheap, safe, effective, easy-to-use and easy-to-store topical applications for prophylaxis against sexually transmitted infections (STIs) makes surfactant-containing formulations an interesting option that requires a more fundamental knowledge concerning surfactant toxicology and structure-activity relationships. Methodology/Principal Findings We report in vitro effects of surfactant concentration, exposure time and structure on the viability of mammalian cell types typically encountered in the vagina, namely, fully polarized and confluent epithelial cells, confluent but non-polarized epithelial-like cells, dendritic cells, and human sperm. Representatives of the different families of commercially available surfactants – nonionic (Triton X-100 and monolaurin), zwitterionic (DDPS), anionic (SDS), and cationic (CnTAB (n = 10 to 16), C12PB, and C12BZK) – were examined. Triton X-100, monolaurin, DDPS and SDS were toxic to all cell types at concentrations around their critical micelle concentration (CMC) suggesting a non-selective mode of action involving cell membrane destabilization and/or destruction. All cationic surfactants were toxic at concentrations far below their CMC and showed significant differences in their toxicity toward polarized as compared with non-polarized cells. Their toxicity was also dependent on the chemical nature of the polar head group. Our results suggest an intracellular locus of action for cationic surfactants and show that their structure-activity relationships could be profitably exploited for STI prophylaxis in vaginal gel formulations. The therapeutic indices comparing polarized epithelial cell toxicity to sperm toxicity for all surfactants examined, except C12PB and C12BZK, does not justify their use as contraceptive agents. C12PB and C12BZK are shown to have a narrow therapeutic index recommending caution in their use in contraceptive formulations. Conclusions/Significance Our results contribute to understanding the mechanisms involved in surfactant toxicity, have a predictive value with regard to their safety, and may be used to design more effective and less harmful surfactants for use in topical applications for STI prophylaxis.Foundation for Science and Technology of the Portuguese Ministry of Science and Higher Educatio

Assessing Computational Methods of Cis-Regulatory Module Prediction

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods

Enhancement of COPD biological networks using a web-based collaboration interface

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks