Cob Property Analysis

The goal of this project was to research the material properties of the green building material COB in order to better understand how to apply COB in real world applications. The research portion included soil analysis, compression, modulus of rupture and elasticity tests, hydrometer analysis, and atterberg limits tests. Additionally, through a partnership with the professionals of the COB Research Institute team and another COB-centric senior design group, this team was able to produce the first full-scale wall tests for COB. Four 7-foot walls were constructed and in-plane lateral cyclic loading was applied to create the effects of a COB structure under lateral loading. The results of the full-scale tests are in the process of being incorporated in the entry for COB into the California Residential Code, with a recommendation given for the reinforcing design that performed the best, through allowable load and deflection calculations. Finally, the team used a sample footprint for a simple house to develop structural house components for a COB structure that could benefit COB application in the real world. The simulated application of COB is helping the COB Research Institute formulate their submittal and ultimately provide a jumping off point for further research of this nature. The ultimate goal was to spread awareness of sustainable building practices and make them more accessible to the general public

Predicting Board-Foot Tree Volume from Stump Diameter for Eight Hard-wood Species in Ohio

Author Institution: School of Natural Resources, The Ohio State University ; Indiana Deaprtment of Natural Resources, Division of Forestry ; Northeastern Forest Experiment Station, Forestry Sciences LaboratoryRegression equations were developed to predict volume table values for merchantable gross volume from stump diameter for eight species of hardwood trees in south-central Ohio. Mesavage and Girard's volume tables were used to develop equations for both the Doyle and International lA log rules. Data for the study were collected in Scioto Co., Ohio. Regression equations were weighted by the inverse of estimated variances. The range in R2 was from 0.82 to 0.96. Both equations and tables are presented for each species and for combined equations

Illustrating Neuroaesthetics

This body of art attempts to bridge two subjects, visual art and neuroscience. It does so by illustrating five topics in neuroaesthetics, the study of how we see and perceive art. I believe beautiful things can happen at the intersections of interdisciplinary subjects and wanted to explore this one further. The first piece begins with a straightforward introduction to the structure of the human eye. The drawings following increase in complexity, working further up the visual process. For instance, the second depicts intermediate pathways in the brain using Op art techniques. The third illustrates how memory influences how we see the world in addition to art. The fourth exhibits the six basic emotions, which can be evoked by art depending on one’s episodic memories and empathy toward the artist. Finally, the fifth exemplifies how lack of familiar imagery in abstract art leaves much of work to the individual’s top-down functioning in the brain. If any of these words or ideas are unfamiliar, good. While each piece has its own summary of the science the work is illustrating, I hope for some it is just a jumping off point for learning about a new subject, whether that be art, neuroscience, or something in between

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies.

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Recent strategies targeting the kinome with combination therapies have shown promise, such as trametinib and dabrafenib in advanced melanoma, but empirical design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico filtering prior to experimental testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generated combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with transcriptomics from CCLE to build machine learning models with elastic-net feature selection to predict cell line sensitivity across nine cancer types, with accuracy R2 ∼ 0.75-0.9. We then validated the model by using a PDX-derived TNBC cell line and saw good global accuracy (R2 ∼ 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 ∼ 0.9). Additionally, the model was able to predict a highly synergistic combination of trametinib and omipalisib for TNBC treatment, which incidentally was recently in phase I clinical trials. Our choice of tree-based models for greater interpretability allowed interrogation of highly predictive kinases in each cancer type, such as the MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes

Kinome inhibition states and multiomics data enable prediction of cell viability in diverse cancer types

Protein kinases play a vital role in a wide range of cellular processes, and compounds that inhibit kinase activity emerging as a primary focus for targeted therapy development, especially in cancer. Consequently, efforts to characterize the behavior of kinases in response to inhibitor treatment, as well as downstream cellular responses, have been performed at increasingly large scales. Previous work with smaller datasets have used baseline profiling of cell lines and limited kinome profiling data to attempt to predict small molecule effects on cell viability, but these efforts did not use multi-dose kinase profiles and achieved low accuracy with very limited external validation. This work focuses on two large-scale primary data types, kinase inhibitor profiles and gene expression, to predict the results of cell viability screening. We describe the process by which we combined these data sets, examined their properties in relation to cell viability and finally developed a set of computational models that achieve a reasonably high prediction accuracy (R2 of 0.78 and RMSE of 0.154). Using these models, we identified a set of kinases, several of which are understudied, that are strongly influential in the cell viability prediction models. In addition, we also tested to see if a wider range of multiomics data sets could improve the model results and found that proteomic kinase inhibitor profiles were the single most informative data type. Finally, we validated a small subset of the model predictions in several triple-negative and HER2 positive breast cancer cell lines demonstrating that the model performs well with compounds and cell lines that were not included in the training data set. Overall, this result demonstrates that generic knowledge of the kinome is predictive of very specific cell phenotypes, and has the potential to be integrated into targeted therapy development pipelines

Parental Smoking in the Vicinity of Children and Tobacco Control Policies in the European Region

Objective: To ascertain patterns of parental smoking in the vicinity of children in Eastern and Western Europe and their relation to Tobacco Control Scale (TCS) scores. Methods: Data on parental smoking patterns were obtained from the School Child Mental Health Europe (SCMHE), a 2010 cross-sectional survey of 5141 school children aged 6 to 11 years and their parents in six countries: Germany, Netherlands, Lithuania, Romania, Bulgaria and Turkey ranked by TCS into three level categories toward tobacco control policies. Results: A slightly higher proportion of Eastern compared to Western European mothers (42.4 vs. 35.1%) were currently smoking in but the difference was not statistically significant after adjusting for maternal age and maternal educational attainment. About a fifth (19.3%) and a tenth (10.0%) of Eastern and Western European mothers, respectively, smoked in the vicinity of their children, and the difference was significant even after adjustment for potential confounders (p less than 0.001). Parents with the highest educational attainment were significantly less likely to smoke in the vicinity of their children than those with the lowest attainment. After control of these covariates lax tobacco control policies, compared to intermediate policies, were associated with a 50% increase in the likelihood of maternal smoking in the vicinity of children adjusted odds ratio (AOR) = 1.52 and 1.64. Among fathers, however, the relationship with paternal smoking and TCS seems more complex since strict policy increases the risk as well AOR = 1,40. Only one country, however belongs to the strict group. Significance: Tobacco control policies seem to have influenced maternal smoking behaviors overall to a limited degree and smoking in the vicinity of children to a much greater degree. Children living in European countries with lax tobacco control policies are more likely to be exposed to second hand smoking from maternal and paternal smoking

Combined kinase inhibitors of MEK1/2 and either PI3K or PDGFR are efficacious in intracranial triple-negative breast cancer

Background: Triple-negative breast cancer (TNBC), lacking expression of hormone and human epidermal growth factor receptor 2 receptors, is an aggressive subtype that frequently metastasizes to the brain and has no FDA-approved systemic therapies. Previous literature demonstrates mitogen-Activated protein kinase kinase (MEK) pathway activation in TNBC brain metastases. Thus, we aimed to discover rational combinatorial therapies with MEK inhibition, hypothesizing that co-inhibition using clinically available brain-penetrant inhibitors would improve survival in preclinical models of TNBC brain metastases. Methods: Using human-derived TNBC cell lines, synthetic lethal small interfering RNA kinase screens were evaluated with brain-penetrant inhibitors against MEK1/2 (selumetinib, AZD6244) or phosphatidylinositol-3 kinase (PI3K; buparlisib, BKM120). Mice bearing intracranial TNBC tumors (SUM149, MDA-MB-231Br, MDA-MB-468, or MDA-MB-436) were treated with MEK, PI3K, or platelet derived growth factor receptor (PDGFR; pazopanib) inhibitors alone or in combination. Tumors were analyzed by western blot and multiplexed kinase inhibitor beads/mass spectrometry to assess treatment effects. Results: Screens identified MEK+PI3K and MEK+PDGFR inhibitors as tractable, rational combinations. Dual treatment of selumetinib with buparlisib or pazopanib was synergistic in TNBC cells in vitro. Both combinations improved survival in intracranial SUM149 and MDA-MB-231Br, but not MDA-MB-468 or MDA-MB-436. Treatments decreased mitogen-Activated protein kinase (MAPK) and PI3K (Akt) signaling in sensitive (SUM149 and 231Br) but not resistant models (MDA-MB-468). Exploratory analysis of kinome reprogramming in SUM149 intracranial tumors after MEK PI3K inhibition demonstrates extensive kinome changes with treatment, especially in MAPK pathway members. Conclusions: Results demonstrate that rational combinations of the clinically available inhibitors selumetinib with buparlisib or pazopanib may prove to be promising therapeutic strategies for the treatment of some TNBC brain metastases. Additionally, effective combination treatments cause widespread alterations in kinase pathways, including targetable potential resistance drivers

MicroRNA 9-3p Targets 1 Integrin To Sensitize Claudin-Low Breast Cancer Cells to MEK Inhibition

MEK1/2 inhibitors such as AZD6244 are in clinical trials for the treatment of multiple cancers, including breast cancer. Targeted kinase inhibition can induce compensatory kinome changes, rendering single therapeutic agents ineffective. To identify target proteins to be used in a combinatorial approach to inhibit tumor cell growth, we used a novel strategy that identified microRNAs (miRNAs) that synergized with AZD6244 to inhibit the viability of the claudin-low breast cancer cell line MDA-MB-231. Screening of a miRNA mimic library revealed the ability of miR-9-3p to significantly enhance AZD6244-induced extracellular signal-regulated kinase inhibition and growth arrest, while miR-9-3p had little effect on growth alone. Promoter methylation of mir-9 genes correlated with low expression of miR-9-3p in different breast cancer cell lines. Consistent with miR-9-3p having synthetic enhancer tumor suppressor characteristics, miR-9-3p expression in combination with MEK inhibitor caused a sustained loss of c-MYC expression and growth inhibition. The β1 integrin gene (ITGB1) was identified as a new miR-9-3p target, and the growth inhibition seen with small interfering RNA knockdown or antibody blocking of ITGB1 in combination with MEK inhibitor phenocopied the growth inhibition seen with miR-9-3p plus AZD6244. The miRNA screen led to identification of a druggable protein, ITGB1, whose functional inhibition synergizes with MEK inhibitor

Irreversible JNK1-JUN inhibition by JNK-IN-8 sensitizes pancreatic cancer to 5-FU/FOLFOX chemotherapy

Over 55,000 people in the United States are diagnosed with pancreatic ductal adenocarcinoma (PDAC) yearly, and fewer than 20% of these patients survive a year beyond diagnosis. Chemotherapies are considered or used in nearly every PDAC case, but there is limited understanding of the complex signaling responses underlying resistance to these common treatments. Here, we take an unbiased approach to study protein kinase network changes following chemotherapies in patient-derived xenograft (PDX) models of PDAC to facilitate design of rational drug combinations. Proteomics profiling following chemotherapy regimens reveals that activation of JNK-JUN signaling occurs after 5-fluorouracil plus leucovorin (5-FU + LEU) and FOLFOX (5-FU + LEU plus oxaliplatin [OX]), but not after OX alone or gemcitabine. Cell and tumor growth assays with the irreversible inhibitor JNK-IN-8 and genetic manipulations demonstrate that JNK and JUN each contribute to chemoresistance and cancer cell survival after FOLFOX. Active JNK1 and JUN are specifically implicated in these effects, and synergy with JNK-IN-8 is linked to FOLFOX-mediated JUN activation, cell cycle dysregulation, and DNA damage response. This study highlights the potential for JNK-IN-8 as a biological tool and potential combination therapy with FOLFOX in PDAC and reinforces the need to tailor treatment to functional characteristics of individual tumors

Neratinib, a pan ERBB/HER inhibitor, restores sensitivity of PTEN-null, BRAFV600E melanoma to BRAF/MEK inhibition

Introduction Approximately 50% of melanomas harbor an activating BRAFV600E mutation. Standard of care involves a combination of inhibitors targeting mutant BRAF and MEK1/2, the substrate for BRAF in the MAPK pathway. PTEN loss-of-function mutations occur in ~40% of BRAFV600E melanomas, resulting in increased PI3K/AKT activity that enhances resistance to BRAF/MEK combination inhibitor therapy. Methods To compare the response of PTEN null to PTEN wild-type cells in an isogenic background, CRISPR/Cas9 was used to knock out PTEN in a melanoma cell line that harbors a BRAFV600E mutation. RNA sequencing, functional kinome analysis, and drug synergy screening were employed in the context of BRAF/MEK inhibition. Results RNA sequencing and functional kinome analysis revealed that the loss of PTEN led to an induction of FOXD3 and an increase in expression of the FOXD3 target gene, ERBB3/HER3. Inhibition of BRAF and MEK1/2 in PTEN null, BRAFV600E cells dramatically induced the expression of ERBB3/HER3 relative to wild-type cells. A synergy screen of epigenetic modifiers and kinase inhibitors in combination with BRAFi/MEKi revealed that the pan ERBB/HER inhibitor, neratinib, could reverse the resistance observed in PTEN null, BRAFV600E cells. Conclusions The findings indicate that PTEN null BRAFV600E melanoma exhibits increased reliance on ERBB/HER signaling when treated with clinically approved BRAFi/MEKi combinations. Future studies are warranted to test neratinib reversal of BRAFi/MEKi resistance in patient melanomas expressing ERBB3/HER3 in combination with its dimerization partner ERBB2/HER2