Food Superstores, Food Deserts and Traffic Generation in the UK: A Semi-Parametric Regression Approach

This study contributes another route towards explaining and tackling ‘food desert’ effects. It features the estimation of a (semi-parametric) trip attraction model for food superstores in the UK using a composite dataset. The data comprises information from the UK Census of Population, the NOMIS (National Online Manpower Information System) archive and traffic and site-specific data from the TRICS (Trip Rate Information Computer System) databases. The results indicate that traffic to a given food superstore, ceteris paribus, increases with household car ownership, store parking provision, site size (floor space), and distance to the nearest competitor. Furthermore, increases in public transport provision are shown to be associated with increasing car trips. This latter effect is discussed in the light of planning policy for development control purposes and a role linked to the reinforcement of ‘food deserts’. The results also reveal activity-specific household economies of scope and scale. It is suggested how these may also further perpetuate unsustainable development and ‘food desert’ characteristics.Traffic Generation, Food Superstores, Food Deserts, Activity Based Travel, Sustainable Development, Modelling

Deleterious consequences of antioxidant supplementation on lifespan in a wild-derived mammal

Peer reviewedPublisher PD

Enhanced anticancer activity of a combination of docetaxel and Aneustat (OMN54) in a patient-derived, advanced prostate cancer tissue xenograft model.

The current first-line treatment for advanced metastatic prostate cancer, i.e. docetaxel-based therapy, is only marginally effective. The aim of the present study was to determine whether such therapy can be improved by combining docetaxel with Aneustat (OMN54), a multivalent botanical drug candidate shown to have anti-prostate cancer activity in preliminary in vitro experiments, which is currently undergoing a Phase-I Clinical Trial. Human metastatic, androgen-independent C4-2 prostate cancer cells and NOD-SCID mice bearing PTEN-deficient, metastatic and PSA-secreting, patient-derived subrenal capsule LTL-313H prostate cancer tissue xenografts were treated with docetaxel and Aneustat, alone and in combination. In vitro, Aneustat markedly inhibited C4-2 cell replication in a dose-dependent manner. When Aneustat was combined with docetaxel, the growth inhibitions of the drugs were essentially additive. In vivo, however, the combination of docetaxel and Aneustat enhanced anti-tumor activity synergistically and very markedly, without inducing major host toxicity. Complete growth inhibition and shrinkage of the xenografts could be obtained with the combined drugs as distinct from the drugs on their own. Analysis of the gene expression of the xenografts using microarray indicated that docetaxel + Aneustat led to expanded anticancer activity, in particular to targeting of cancer hallmarks that were not affected by the single drugs. Our findings, obtained with a highly clinically relevant prostate cancer model, suggest, for the first time, that docetaxel-based therapy of advanced human prostate cancer may be improved by combining docetaxel with Aneustat

MOLI: multi-omics late integration with deep neural networks for drug response prediction

Sharifi-Noghabi H, Zolotareva O, Collins CC, Ester M. MOLI: multi-omics late integration with deep neural networks for drug response prediction. Bioinformatics. 2019;35(14):I501-I509.Motivation Historically, gene expression has been shown to be the most informative data for drug response prediction. Recent evidence suggests that integrating additional omics can improve the prediction accuracy which raises the question of how to integrate the additional omics. Regardless of the integration strategy, clinical utility and translatability are crucial. Thus, we reasoned a multi-omics approach combined with clinical datasets would improve drug response prediction and clinical relevance. Results We propose MOLI, a multi-omics late integration method based on deep neural networks. MOLI takes somatic mutation, copy number aberration and gene expression data as input, and integrates them for drug response prediction. MOLI uses type-specific encoding sub-networks to learn features for each omics type, concatenates them into one representation and optimizes this representation via a combined cost function consisting of a triplet loss and a binary cross-entropy loss. The former makes the representations of responder samples more similar to each other and different from the non-responders, and the latter makes this representation predictive of the response values. We validate MOLI on in vitro and in vivo datasets for five chemotherapy agents and two targeted therapeutics. Compared to state-of-the-art single-omics and early integration multi-omics methods, MOLI achieves higher prediction accuracy in external validations. Moreover, a significant improvement in MOLI's performance is observed for targeted drugs when training on a pan-drug input, i.e. using all the drugs with the same target compared to training only on drug-specific inputs. MOLI's high predictive power suggests it may have utility in precision oncology. Availability and implementation https://github.com/hosseinshn/MOLI. Supplementary information Supplementary data are available at Bioinformatics online

Scaling up family planning in Zambia—Part 2: The cost of scaling up family planning services

This costing study is Part 2 of a broader implementation research study designed to establish the feasibility of integrating successful interventions and lessons from the Scaling Up Family Planning (SUFP) project into Zambia’s health system at the conclusion of the project, and to contribute to the global learning on scaling up family planning services. The main contribution of the costing study was to examine the cost implications in determining the scope and pace of scale up. Challenges experienced during the project reportedly included lack of equipment and limited space in some facilities, government staff shortages, and irregular access to supplies of oral contraceptives and condoms at the community level. Sustainability of interventions after the end of the project was a major concern, with doubts over the ability of the government to cover the costs of outreach, supply chain, and community-based distribution (CBD) support costs that have been covered by the project. Finally, finding solutions to high CBD attrition rates was identified as a key challenge. The report details lessons learned from this project and makes recommendations, including further research that would be beneficial both for the country and globally

Self-care coping strategies in people with diabetes: a qualitative exploratory study

<p>Abstract</p> <p>Background</p> <p>The management of diabetes self-care is largely the responsibility of the patient. With more emphasis on the prevention of complications, adherence to diabetes self-care regimens can be difficult. Diabetes self-care requires the patient to make many dietary and lifestyle changes. This study will explore patient perceptions of diabetes self-care, with particular reference to the burden of self-care and coping strategies among patients.</p> <p>Methods</p> <p>A maximum variation sample of 17 patients was selected from GP practices and diabetes clinics in Ireland to include patients with types 1 and 2 diabetes, various self-care regimens, and a range of diabetes complications. Data were collected by in-depth interviews; which were tape-recorded and transcribed. The transcripts were analysed using open and axial coding procedures to identify main categories, and were reviewed by an independent corroborator. Discussion of the results is made in the theoretical context of the health belief, health value, self-efficacy, and locus of control frameworks.</p> <p>Results</p> <p>Patients' perceptions of their self-care varied on a spectrum, displaying differences in self-care responsibilities such as competence with dietary planning, testing blood sugar and regular exercise. Three patient types could be distinguished, which were labeled: "proactive manager," a patient who independently monitors blood glucose and adjusts his/her self-care regime to maintain metabolic control; "passive follower," a patient who follows his/her prescribed self-care regime, but does not react autonomously to changes in metabolic control; and "nonconformist," a patient who does not follow most of his/her prescribed self-care regimen.</p> <p>Conclusion</p> <p>Patients have different diabetes self-care coping strategies which are influenced by their self-care health value and consequently may affect their diet and exercise choices, frequency of blood glucose monitoring, and compliance with prescribed medication regimens. Particular attention should be paid to the patient's self-care coping strategy, and self-care protocols should be tailored to complement the different patient types.</p

Increasing Engagement in the Mirboo North Community Energy Hub

The Mirboo North Community Energy Hub (MNCEH) is a community-driven initiative designed to promote sustainability solutions. Its founding business case was prepared by Primaform, a partner in the Snowy River Innovation (SRI) group. The goal of this project was to increase community engagement in the MNCEH, particularly in the dairy farming and agroforestry sectors. Based on interviews and surveys, we identified successful community engagement strategies to recommend to the MNCEH. We also found that Mirboo North and district lacked a trusted source of energy information. We created a prototype website for the MNCEH to serve as an information source and community engagement tool

Energy Efficient Catalytic Activation of Hydrogen peroxide for Green Chemical Processes: Final Report

A new, highly energy efficient approach for using catalytic oxidation chemistry in multiple fields of technology has been pursued. The new catalysts, called TAML® activators, catalyze the reactions of hydrogen peroxide and other oxidants for the exceptionally rapid decontamination of noninfectious simulants (B. atrophaeus) of anthrax spores, for the energy efficient decontamination of thiophosphate pesticides, for the facile, low temperature removal of color and organochlorines from pulp and paper mill effluent, for the bleaching of dyes from textile mill effluents, and for the removal of recalcitrant dibenzothiophene compounds from diesel and gasoline fuels. Highlights include the following: 1) A 7-log kill of Bacillus atrophaeus spores has been achieved unambiguously in water under ambient conditions within 15 minutes. 2) The rapid total degradation under ambient conditions of four thiophosphate pesticides and phosphonate degradation intermediates has been achieved on treatment with TAML/peroxide, opening up potential applications of the decontamination system for phosphonate structured chemical warfare agents, for inexpensive, easy to perform degradation of stored and aged pesticide stocks (especially in Africa and Asia), for remediation of polluted sites and water bodies, and for the destruction of chemical warfare agent stockpiles. 3) A mill trial conducted in a Pennsylvanian bleached kraft pulp mill has established that TAML catalyst injected into an alkaline peroxide bleach tower can significantly lower color from the effluent stream promising a new, more cost effective, energy-saving approach for color remediation adding further evidence of the value and diverse engineering capacity of the approach to other field trials conducted on effluent streams as they exit the bleach plant. 4) Dibenzothiophenes (DBTs), including 4,6-dimethyldibenzothiophene, the most recalcitrant sulfur compounds in diesel and gasoline, can be completely removed from model gasoline (octane or decane) at low temperature and ambient pressure via treatment with a TAML activator and hydrogen peroxide in a two-phase system consisting of the fuel as the first phase and a water/tertiary butanol second phase. The DBTs are oxidized to sulphones (or sulfoxides), which then completely extract into the water/t-butanol phase. Treatment of commercial diesel spiked with DBT under the same conditions results in compete DBT oxidation. In contrast with the octane and decane experiments, removal to the water/t-butanol phase is not yet complete and is being further optimized. Analysis by the sulfur specific GC-FPD technique suggests that >70% sulfur compounds are removed from unspiked diesel after one treatment. Further treatments are being investigated. The GC-FPD results will be checked by total sulfur analysis methodology

Real time Pattern Based Melodic Query for Music Continuation System

This paper presents a music continuation system using pattern matching to find patterns within a library of MIDI files using a realtime algorithm to build a system which can be used as interactive DJ system. This paper also looks at the influence of different kinds of pattern matching on MIDI file analysis. Many pattern-matching algorithms have been developed for text analysis, voice recognition and Bio-informatics but as the domain knowledge and nature of the problems are different these algorithms are not ideally suitable for real time MIDI processing for interactive music continuation system. By taking patterns in real-time, via MIDI keyboard, the system searches patterns within a corpus of MIDI files and continues playing from the user's musical input. Four different types of pattern matching are used in this system (i.e. exact pattern matching, reverse pattern matching, pattern matching with mismatch and combinatorial pattern matching in a single system). After computing the results of the four types of pattern matching of each MIDI file, the system compares the results and locates the highest pattern matching possibility MIDI file within the library