An investigation of pesticide and microbial interactions on coffee as a means of developing an IPM strategy for economically important coffee pests in small-holder farming systems in Malawi

The results in this report highlight the importance of coffee in the rural communities of northern Malawi, the recent changes that have occurred in the system and smallholder's desire to continue with the production of the crop. Economic analysis also indicates that coffee should remain an important element of the farming system, but that there are key production and marketing issues which need to be addressed if coffee cultivation is to be successful in this sector. These include: a) reducing the economic impact of coffee plant diseases and insect pests under the smallholder low input/output system b) development of a new sustainable credit system c) creating an enabling environment for the effective development of a competitive domestic marketing system including access to rural pulperies (wet factories) for private buyers. Whilst this project is principally concerned with the first issue, as the others fall outside its direct remit, they remain important for the successful uptake of the project's scientific outputs

Channelling the force of audit and feedback : averting the dark side

Funding EMD is funded through a personal fellowship from the Healthcare Improvement Studies Institute, supported by the Health Foundation’s grant to the University of Cambridge. JMG holds a Canada Research Chair in Health Knowledge Transfer and Uptake. NMI holds a Canada Research Chair in Implementation of Evidence-based PracticePeer reviewedPostprin

Cardiolipin, and not monolysocardiolipin, preferentially binds to the interface of complexes III and IV

The mitochondrial electron transport chain comprises a series of protein complexes embedded in the inner mitochondrial membrane that generate a proton motive force via oxidative phosphorylation, ultimately generating ATP. These protein complexes can oligomerize to form larger structures called supercomplexes. Cardiolipin (CL), a conical lipid, unique within eukaryotes to the inner mitochondrial membrane, has proven essential in maintaining the stability and function of supercomplexes. Monolysocardiolipin (MLCL) is a CL variant that accumulates in people with Barth syndrome (BTHS). BTHS is caused by defects in CL biosynthesis and characterised by abnormal mitochondrial bioenergetics and destabilised supercomplexes. However, the mechanisms by which MLCL causes pathogenesis remain unclear. Here, multiscale molecular dynamics characterise the interactions of CL and MLCL with yeast and mammalian mitochondrial supercomplexes containing complex III (CIII) and complex IV (CIV). Coarse-grained simulations reveal that both CL and MLCL bind to sites at the interface between CIII and CIV of the supercomplex. Free energy perturbation calculations show that MLCL interaction is weaker than that of CL and suggest that interaction with CIV drives this difference. Atomistic contact analyses show that, although interaction with CIII is similar for CL and MLCL, CIV makes more contacts with CL than MLCL, demonstrating that CL is a more successful “glue” between the two complexes. Simulations of the human CIII2CIV supercomplex show that this interface site is maintained between species. Our study suggests that MLCL accumulation in people with BTHS disrupts supercomplex stability by formation of relatively weak interactions at the interface lipid binding site

ACE: A fast, skillful learned global atmospheric model for climate prediction

Existing ML-based atmospheric models are not suitable for climate prediction, which requires long-term stability and physical consistency. We present ACE (AI2 Climate Emulator), a 200M-parameter, autoregressive machine learning emulator of an existing comprehensive 100-km resolution global atmospheric model. The formulation of ACE allows evaluation of physical laws such as the conservation of mass and moisture. The emulator is stable for 100 years, nearly conserves column moisture without explicit constraints and faithfully reproduces the reference model's climate, outperforming a challenging baseline on over 90% of tracked variables. ACE requires nearly 100x less wall clock time and is 100x more energy efficient than the reference model using typically available resources. Without fine-tuning, ACE can stably generalize to a previously unseen historical sea surface temperature dataset.Comment: Accepted at Tackling Climate Change with Machine Learning: workshop at NeurIPS 202

Enhancer Remodeling during Adaptive Bypass to MEK Inhibition Is Attenuated by Pharmacologic Targeting of the P-TEFb Complex

Targeting the dysregulated BRaf-MEK-ERK pathway in cancer has increasingly emerged in clinical trial design. Despite clinical responses in specific cancers using inhibitors targeting BRaf and MEK, resistance develops often involving non-genomic adaptive bypass mechanisms. Inhibition of MEK1/2 by trametinib in triple negative breast cancer (TNBC) patients induced dramatic transcriptional responses, including upregulation of receptor tyrosine kinases (RTKs) comparing tumor samples before and after one week of treatment. In preclinical models MEK inhibition induced genome-wide enhancer formation involving the seeding of BRD4, MED1, H3K27 acetylation and p300 that drives transcriptional adaptation. Inhibition of P-TEFb associated proteins BRD4 and CBP/p300 arrested enhancer seeding and RTK upregulation. BRD4 bromodomain inhibitors overcame trametinib resistance, producing sustained growth inhibition in cells, xenografts and syngeneic mouse TNBC models. Pharmacological targeting of P-TEFb members in conjunction with MEK inhibition by trametinib is an effective strategy to durably inhibit epigenomic remodeling required for adaptive resistance

A guide to using the Theoretical Domains Framework of behaviour change to investigate implementation problems

Background: Implementing new practices requires changes in the behaviour of relevant actors, and this is facilitated by understanding of the determinants of current and desired behaviours. The Theoretical Domains Framework (TDF) was developed by a collaboration of behavioural scientists and implementation researchers who identified theories relevant to implementation and grouped constructs from these theories into domains. The collaboration aimed to provide a comprehensive, theory-informed approach to identify determinants of behaviour. The first version was published in 2005, and a subsequent version following a validation exercise was published in 2012. This guide offers practical guidance for those who wish to apply the TDF to assess implementation problems and support intervention design. It presents a brief rationale for using a theoretical approach to investigate and address implementation problems, summarises the TDF and its development, and describes how to apply the TDF to achieve implementation objectives. Examples from the implementation research literature are presented to illustrate relevant methods and practical considerations. Methods: Researchers from Canada, the UK and Australia attended a 3-day meeting in December 2012 to build an international collaboration among researchers and decision-makers interested in the advancing use of the TDF. The participants were experienced in using the TDF to assess implementation problems, design interventions, and/or understand change processes. This guide is an output of the meeting and also draws on the a uthors' collective experience. Examples from the implementation research literature judged by authors to be representative of specific applications of the TDF are included in this guide. Results: We explain and illustrate methods, with a focus on qualitative approaches, for selecting and specifying target behaviours key to implementation, selecting the study design, deciding the sampling strategy, developing study materials, collecting and analysing data, and reporting findings of TDF-based studies. Areas for development include methods for triangulating data, e.g. from interviews, questionnaires and observation and methods for designing interventions based on TDF-based problem analysis. Conclusions: We offer this guide to the implementation community to assist in the application of the TDF to achieve implementation objectives. Benefits of using the TDF include the provision of a theoretical basis for implementation studies, good coverage of potential reasons for slow diffusion of evidence into practice and a method for progressing from theory-based investigation to intervention