Assessing Houston’s Forested Habitat

The City of Houston has a total of 380 parks totaling 35,742 acres. Approximately 16,000 of those acres are forested habitat, each totaling over an acre in size. A method for prioritizing and assessing these areas was first established in 2017 to determine management needs and funding requirements. Prior to this time, the priority had been given to street trees through a comprehensive inventory to support tree ordinance mitigation requirements. Additionally, in 2015 the US Forest Service collected data on the tree canopy cover and species composition of trees within the City of Houston, including both natural and urbanized areas

Planning for Climate Change Through Riparian Restoration in Houston, Texas

The City of Houston faces a unique set of natural and developmental resiliency challenges that make it especially vulnerable to the impacts of climate change. As part of a comprehensive Climate Action Plan, the City is incorporating a suite of forestry practices. The City’s Riparian Restoration Initiative, which increases natural forest cover in riparian zones, helps address climate change, but also benefits other issues like flooding, water quality, air quality, and maintenance of natural areas. This approach provides a model for future integration of forestry practices into the City’s climate approach and other regional efforts

Novel Materials Can Radically Improve Whole-System Environmental Impacts of Additive Manufacturing

Additive manufacturing often has higher environmental impacts per part than traditional manufacturing at scale, but new materials can enable more sustainable 3D printing. This study developed and tested novel materials for paste extrusion printing, and tested materials invented by others. Testing compared their whole-system environmental impacts to standard ABS extrusion, measured by life cycle assessment (LCA); testing also assessed material strength, printability, and cost. Materials were chosen for low print energy (chemical bonding, not melting), low toxicity, and circular life cycle (biodegradable, ideally sourced from waste biomaterial). Printing energy was reduced 75% (from 160 to 40 Wh/part), and embodied impacts of materials were reduced 82% (from 6.6 to 1.2 ReCiPe Endpoint H millipoints/part). Overall impacts per part were reduced 78% (from 27 to 6 ReCiPe Endpoint H millipoints/part), including embodied impacts of the printer itself, in a maximum utilization scenario. Results were also compared to previous studies of seven different 3D printers of various types. More than ten material recipes were tested, and pecan shell flour with sodium silicate showed the best print quality. Strength and print quality did not approach ABS, but material cost was cut by 50%. Thus, while further development is required, some materials show promise for greener additive manufacturing

Identification of a selective G1-phase benzimidazolone inhibitor by a senescence-targeted virtual screen using artificial neural networks

Cellular senescence is a barrier to tumorigenesis in normal cells and tumour cells undergo senescence responses to genotoxic stimuli, which is a potential target phenotype for cancer therapy. However, in this setting, mixed-mode responses are common with apoptosis the dominant effect. Hence, more selective senescence inducers are required. Here we report a machine learning-based in silico screen to identify potential senescence agonists. We built profiles of differentially affected biological process networks from expression data obtained under induced telomere dysfunction conditions in colorectal cancer cells and matched these to a panel of 17 protein targets with confirmatory screening data in PubChem. We trained a neural network using 3517 compounds identified as active or inactive against these targets. The resulting classification model was used to screen a virtual library of ~2M lead-like compounds. 147 virtual hits were acquired for validation in growth inhibition and senescence-associated β-galactosidase (SA-β-gal) assays. Among the found hits a benzimidazolone compound, CB-20903630, had low micromolar IC50 for growth inhibition of HCT116 cells and selectively induced SA-β-gal activity in the entire treated cell population without cytotoxicity or apoptosis induction. Growth suppression was mediated by G1 blockade involving increased p21 expression and suppressed cyclin B1, CDK1 and CDC25C. Additionally, the compound inhibited growth of multicellular spheroids and caused severe retardation of population kinetics in long term treatments. Preliminary structure-activity and structure clustering analyses are reported and expression analysis of CB-20903630 against other cell cycle suppressor compounds suggested a PI3K/AKT-inhibitor-like profile in normal cells, with different pathways affected in cancer cells

A fully automated procedure for the parallel, multidimensional purification and nucleotide loading of the human GTPases KRas, Rac1 and RalB

Small GTPases regulate many key cellular processes and their role in human disease validates many proteins in this class as desirable targets for therapeutic intervention. Reliable recombinant production of GTPases, often in the active GTP loaded state, is a prerequisite for the prosecution of drug discovery efforts. The preparation of these active forms can be complex and often constricts the supply to the reagent intensive techniques used in structure base drug discovery. We have established a fully automated, multidimensional protein purification strategy for the parallel production of the catalytic G-domains of KRas, Rac1 and RalB GTPases in the active form. This method incorporates a four step chromatography purification with TEV protease-mediated affinity tag cleavage and a conditioning step that achieves the activation of the GTPase by exchanging GDP for the non-hydrolyzable GTP analogue GMPPnP. We also demonstrate that an automated method is efficient at loading of KRas with mantGDP for application in a SOS1 catalysed fluorescent nucleotide exchange assay. In comparison to more conventional manual workflows the automated method offers marked advantages in method run time and operator workload. This reduces the bottleneck in protein production while generating products that are highly purified and effectively loaded with nucleotide analogues

VLA/Realfast Detection of a Burst from FRB 180916.J0158+65 and Tests for Periodic Activity

We report on the detection of a burst from FRB 180916 by realfast/Very Large Array and present software for interpreting fast radio bursts (FRB) periodicity. We demonstrate a range of periodicity analyses with bursts from FRB 180916, FRB 121102 and FRB 180814. Our results for FRB 180916 and FRB 121102 are consistent with published results. For FRB 180814, we did not detect any significant periodic episodes. The realfast-detected and other high-frequency bursts for FRB 180916 tend to lie at the beginning of the activity window, indicating a possible phase-frequency relation. The python package frbpa can be used to reproduce and expand on this analysis to test models for repeating FRBs

VLA/Realfast Detection of a Burst from FRB180916.J0158+65 and Tests for Periodic Activity

We report on the detection of a burst from FRB180916 by realfast/VLA and present software for interpreting fast radio bursts (FRB) periodicity. We demonstrate a range of periodicity analyses with bursts from FRB180916, FRB121102 and FRB180814. Our results for FRB180916 and FRB121102 are consistent with published results. For FRB180814, we did not detect any significant periodic episodes. The realfast-detected and other high-frequency bursts for FRB180916 tend to lie at the beginning of the activity window, indicating a possible phase-frequency relation. The python package $\texttt{frbpa}$ can be used to reproduce and expand on this analysis to test models for repeating FRBs.Comment: Published in Research Notes of the AA

The development of theory-informed participant-centred interventions to maximise participant retention in randomised controlled trials

Acknowledgements We would like to thank all of the participants who volunteered their time to contribute to this study. We would also like to thank all of the teams linked to the host trials we worked with to help identify potential participants. Funding This research is funded by the Chief Scientist Office of the Scottish Government’s Health and Social Care Department [HIPS/16/46]. KG held a Medical Research Council UK Methodology Fellowship during the delivery of this project [MR/L01193X/1]. The publication was supported through a Health Research Board Trials Methodology Research Network award. MDW acknowledges support from the NIHR Newcastle Biomedical Research Centre. MW acknowledges support from the NIHR Imperial Biomedical Research Centre (BRC). The Health Services Research Unit, Institute of Applied Health Sciences (University of Aberdeen), is core-funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The funders had no involvement in study design, collection, analysis and interpretation of data, reporting or the decision to publish.Peer reviewedPublisher PD