Peculiarities of bioaccumulation and toxic effects produced by nanoparticles of molybdenum (VI) oxide under multiple oral exposure of rats: examination and comparative assessment.

INTRODUCTION: Molybdenum (VI) oxide nanoparticles (MoO3 NPs) are widely used in various economic activities. This creates elevated risks of exposure to this nanomaterial for workers and population in general and, consequently, there can be an increased number of developing pathological changes caused by exposure to MoO3 NPs. OBJECTIVE: To examine and comparatively assess peculiarities of bioaccumulation and toxic effects produced by MoO NPs under multiple oral introductions. METHODS: We evaluated sizes of analyzed particles by scanning electronic microscopy; specific surface area was calculated by the method of Brunauer, Emmett and Taylor; the total pore volume, by Barrett, Joyner and Halenda. Rats were exposed as per the scheme introduced by Lim with colleagues. We examined biochemical and hematological blood indicators, molybdenum concentrations and pathomorphological changes in tissues of various organs 24 hours after the last exposure. The study involved comparison with effects produced by MoO3 microparticles. RESULTS: The tested MoO3 sample was established to be a nanomaterial as per the whole set of its physical properties. 50% of animals in the exposed group died on the 16th day in the experiment after the total exposure dose of MoO3 NPs reached 6500 mg/kg of body weight. Having analyzed blood plasma, we determined the following. There was a growth in quantity of leukocytes and a share of segmented neutrophils and monocytes, which were by 1.76-3.50 times higher than in the control group. Activity of alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, gamma-glutamyl transpeptidase, alpha-amylase, and lactate dehydrogenase, and concentrations of urea, crude and direct bilirubin were higher by 1.61-22.86 times. Decrease in the number of platelets, plateletcrit, the relative number of lymphocytes, the number and proportion of large platelets by 1.31-2.71 times. We detected elevated molybdenum concentrations in the lungs, heart, liver, kidneys, brain and blood under exposure to MoO3 NPs in an amount exceeding the control values by 12.10-361.75 times. Rats exposed to MoO3 NPs had liver parenchymal steatosis, inflammatory changes, hemorrhagic infarctions and hyperplasia in the lungs. CONCLUSION: MoO3 NPs have a more apparent ability to bioaccumulate and produce toxic effects in comparison with their microdispersed analogue under multiple oral introductions into the body.

Profiling Secreted miRNA Biomarkers of Chemical-Induced Neurodegeneration in Human iPSC-Derived Neurons.

Elucidation of predictive fluidic biochemical markers to detect and monitor chemical-induced neurodegeneration has been a major challenge due to a lack of understanding of molecular mechanisms driving altered neuronal morphology and function, as well as poor sensitivity in methods to quantify low-level biomarkers in bodily fluids. Here, we evaluated 5 neurotoxicants (acetaminophen [negative control], bisindolylmaleimide-1, colchicine, doxorubicin, paclitaxel, and rotenone) in human-induced pluripotent stem cell-derived neurons to profile secreted microRNAs (miRNAs) at early and late stages of decline in neuronal cell morphology and viability. Based on evaluation of these morphological (neurite outgrowth parameters) and viability (adenosine triphosphate) changes, 2 concentrations of each chemical were selected for analysis in a human 754 miRNA panel: a low concentration with no/minimal effect on cell viability but a significant decrease in neurite outgrowth, and a high concentration with a significant decrease in both endpoints. A total of 39 miRNAs demonstrated significant changes (fold-change ≥ 1.5 or ≤ 0.67, p value < .01) with at least 1 exposure. Further analyses of targets modulated by these miRNAs revealed 38 key messenger RNA targets with roles in neurological dysfunctions, and identified transforming growth factor-beta (TGF-ß) signaling as a commonly enriched pathway. Of the 39 miRNAs, 5 miRNAs, 3 downregulated (miR-20a, miR-30b, and miR-30d) and 3 upregulated (miR-1243 and miR-1305), correlated well with morphological changes induced by multiple neurotoxicants and were notable based on their relationship to various neurodegenerative conditions and/or key pathways, such as TGF-ß signaling. These datasets reveal miRNA candidates that warrant further evaluation as potential safety biomarkers of chemical-induced neurodegeneration.

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib.

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug's known mechanism of action. Also, the models predict each drug's potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets.

An integrated map of HIV-human protein complexes that facilitate viral infection.

Recent proteomic and genetic studies have aimed to identify a complete network of interactions between HIV and human proteins and genes. This HIV-human interaction network provides invaluable information as to how HIV exploits the host machinery and can be used as a starting point for further functional analyses. We integrated this network with complementary datasets of protein function and interaction to nominate human protein complexes with likely roles in viral infection. Based on our approach we identified a global map of 40 HIV-human protein complexes with putative roles in HIV infection, some of which are involved in DNA replication and repair, transcription, translation, and cytoskeletal regulation. Targeted RNAi screens were used to validate several proteins and complexes for functional impact on viral infection. Thus, our HIV-human protein complex map provides a significant resource of potential HIV-host interactions for further study.

Drug target prediction and repositioning using an integrated network-based approach.

The discovery of novel drug targets is a significant challenge in drug development. Although the human genome comprises approximately 30,000 genes, proteins encoded by fewer than 400 are used as drug targets in the treatment of diseases. Therefore, novel drug targets are extremely valuable as the source for first in class drugs. On the other hand, many of the currently known drug targets are functionally pleiotropic and involved in multiple pathologies. Several of them are exploited for treating multiple diseases, which highlights the need for methods to reliably reposition drug targets to new indications. Network-based methods have been successfully applied to prioritize novel disease-associated genes. In recent years, several such algorithms have been developed, some focusing on local network properties only, and others taking the complete network topology into account. Common to all approaches is the understanding that novel disease-associated candidates are in close overall proximity to known disease genes. However, the relevance of these methods to the prediction of novel drug targets has not yet been assessed. Here, we present a network-based approach for the prediction of drug targets for a given disease. The method allows both repositioning drug targets known for other diseases to the given disease and the prediction of unexploited drug targets which are not used for treatment of any disease. Our approach takes as input a disease gene expression signature and a high-quality interaction network and outputs a prioritized list of drug targets. We demonstrate the high performance of our method and highlight the usefulness of the predictions in three case studies. We present novel drug targets for scleroderma and different types of cancer with their underlying biological processes. Furthermore, we demonstrate the ability of our method to identify non-suspected repositioning candidates using diabetes type 1 as an example.

Tissue regeneration in vivo within recombinant spidroin 1 scaffolds.

One of the major tasks of tissue engineering is to produce tissue grafts for the replacement or regeneration of damaged tissue, and natural and recombinant silk-based polymer scaffolds are promising candidates for such grafts. Here, we compared two porous scaffolds made from different silk proteins, fibroin of Bombyx mori and a recombinant analog of Nephila clavipes spidroin 1 known as rS1/9, and their biocompatibility and degradation behavior in vitro and in vivo. The vascularization and intergrowth of the connective tissue, which was penetrated with nerve fibers, at 8 weeks after subcutaneous implantation in Balb/c mice was more profound using the rS1/9 scaffolds. Implantation of both scaffolds into bone defects in Wistar rats accelerated repair compared to controls with no implanted scaffold at 4 weeks. Based on the number of macrophages and multinuclear giant cells in the subcutaneous area and the number of osteoclasts in the bone, regeneration was determined to be more effective after the rS1/9 scaffolds were implanted. Microscopic examination of the morphology of the matrices revealed differences in their internal microstructures. In contrast to fibroin-based scaffolds, the walls of the rS1/9 scaffolds were visibly thicker and contained specific micropores. We suggest that the porous inner structure of the rS1/9 scaffolds provided a better micro-environment for the regenerating tissue, which makes the matrices derived from the recombinant rS1/9 protein favorable candidates for future in vivo applications.

Widespread distribution of HLA-DR-expressing cells in macroscopically undiseased intima of the human aorta: a possible role in surveillance and maintenance of vascular homeostasis.

The architectonics and cell composition of the human large arteries are not sufficiently understood. The present study is the first to undertake an analysis of the distribution and quantities of HLA-DR-expressing cells in grossly undiseased human intima using immunohistochemical and immunofluorescent analysis, complemented by the advantages of confocal microscopy. The study revealed a widespread distribution of HLA-DR-expressing cells throughout the intimal space where the cells were integrated into continuous networks via long cell processes. Numbers of HLA-DR+ cells were found to be significantly larger in the middle third of the intima than in the superficial and deep intimal portions. We speculate that a widespread distribution of HLA-DR-expressing cells in the intima of normal human aorta might play a role in the surveillance and maintenance of vascular homeostasis.

Functional synergies yet distinct modulators affected by genetic alterations in common human cancers.

An important general concern in cancer research is how diverse genetic alterations and regulatory pathways can produce common signaling outcomes. In this study, we report the construction of cancer models that combine unique regulation and common signaling. We compared and functionally analyzed sets of genetic alterations, including somatic sequence mutations and copy number changes, in breast, colon, and pancreatic cancer and glioblastoma that had been determined previously by global exon sequencing and SNP (single nucleotide polymorphism) array analyses in multiple patients. The genes affected by the different types of alterations were mostly unique in each cancer type, affected different pathways, and were connected with different transcription factors, ligands, and receptors. In our model, we show that distinct amplifications, deletions, and sequence alterations in each cancer resulted in common signaling pathways and transcription regulation. In functional clustering, the impact of the type of alteration was more pronounced than the impact of the kind of cancer. Several pathways such as TGF-ß/SMAD signaling and PI3K (phosphoinositide 3-kinase) signaling were defined as synergistic (affected by different alterations in all four cancer types). Despite large differences at the genetic level, all data sets interacted with a common group of 65 "universal cancer genes" (UCG) comprising a concise network focused on proliferation/apoptosis balance and angiogenesis. Using unique nodal regulators ("overconnected" genes), UCGs, and synergistic pathways, the cancer models that we built could combine common signaling with unique regulation. Our findings provide a novel integrated perspective on the complex signaling and regulatory networks that underlie common human cancers.