Deprescribing intervention activities mapped to guiding principles for use in general practice: a scoping review

Objective: To identify and characterise activities for deprescribing used in general practice and to map the identified activities to pioneering principles of deprescribing. Setting: Primary care. Data sources: Medline, EMBASE (Ovid), CINAHL, Australian New Zealand Clinical Trials Registry (ANZCTR), Clinicaltrials.gov, ISRCTN registry, OpenGrey, Annals of Family Medicine, BMC Family Practice, Family Practice and British Journal of General Practice (BJGP) from inception to the end of June 2021. Study: selection Included studies were original research (randomised controlled trial, quasi-experimental, cohort study, qualitative and case studies), protocol papers and protocol registrations. Data extraction: Screening and data extraction was completed by one reviewer; 10% of the studies were independently reviewed by a second reviewer. Coding of full-text articles in NVivo was conducted and mapped to five deprescribing principles. Results: Fifty studies were included. The most frequently used activities were identification of appropriate patients for deprescribing (76%), patient education (50%), general practitioners (GP) education (48%), and development and use of a tapering schedule (38%). Six activities did not align with the five deprescribing principles. As such, two principles (engage practice staff in education and appropriate identification of patients, and provide feedback to staff about deprescribing occurrences within the practice) were added. Conclusion: Activities and guiding principles for deprescribing should be paired together to provide an accessible and comprehensive guide to deprescribing by GPs. The addition of two principles suggests that practice staff and practice management teams may play an instrumental role in sustaining deprescribing processes within clinical practice. Future research is required to determine the most of effective activities to use within each principle and by whom

Salivary gland structure of \u3ci\u3eCtenarytaina eucalypti\u3c/i\u3e (MASKELL, 1890) (Hemiptera) and phloem exudate in \u3ci\u3eEucalyptus globulus\u3c/i\u3e LABILLARDIÈRE, 1799 (Myrtaceae)

The structure of the salivary glands of the free-living aphalarid Ctenarytaina eucalypti, which infests multiple species of Eucalyptus in Australasia and has been introduced into many other regions of the world, is described and illustrated. The principal salivary gland is multilobed whereas the accessory gland is tubular. 1-D electrophoresis revealed proteins of approximately 58 and 64 kDa in the salivary gland extracts and proteins of similar molecular weights in the extracted plant exudates, including phloem, from infested leaves and tender shoots of E. globulus. Proteins that could fall within this range include, but are not limited to, glucosemethanol- choline-oxidoreductase (53-66 kDa), Zn-binding dehydrogenase (67 kDa) and esterase (65-96 kDa), in addition to cytochrome P-450 (50-55 kDa), trehalase (56 kDa), amylase (50-75 kDa) and lipase (48-52 kDa). Previous studies indicate that glucose-methanol-cholineoxidoreductase, Zn-binding dehydrogenase, cytochrome P-450 and trehalase suppress plantdefence mechanisms, whereas the cell-degrading enzymes such as amylase, lipase and esterase have a possible role in enabling C. eucalypti to insert its stylet into leaf and shoot tissues of E. globulus

An integrative computational model for intestinal tissue renewal

Objectives\ud \ud The luminal surface of the gut is lined with a monolayer of epithelial cells that acts as a nutrient absorptive engine and protective barrier. To maintain its integrity and functionality, the epithelium is renewed every few days. Theoretical models are powerful tools that can be used to test hypotheses concerning the regulation of this renewal process, to investigate how its dysfunction can lead to loss of homeostasis and neoplasia, and to identify potential therapeutic interventions. Here we propose a new multiscale model for crypt dynamics that links phenomena occurring at the subcellular, cellular and tissue levels of organisation.\ud \ud Methods\ud \ud At the subcellular level, deterministic models characterise molecular networks, such as cell-cycle control and Wnt signalling. The output of these models determines the behaviour of each epithelial cell in response to intra-, inter- and extracellular cues. The modular nature of the model enables us to easily modify individual assumptions and analyse their effects on the system as a whole.\ud \ud Results\ud \ud We perform virtual microdissection and labelling-index experiments, evaluate the impact of various model extensions, obtain new insight into clonal expansion in the crypt, and compare our predictions with recent mitochondrial DNA mutation data. \ud \ud Conclusions\ud \ud We demonstrate that relaxing the assumption that stem-cell positions are fixed enables clonal expansion and niche succession to occur. We also predict that the presence of extracellular factors near the base of the crypt alone suffices to explain the observed spatial variation in nuclear beta-catenin levels along the crypt axis

Chaste: a test-driven approach to software development for biological modelling

Chaste (‘Cancer, heart and soft-tissue environment’) is a software library and a set of test suites for computational simulations in the domain of biology. Current functionality has arisen from modelling in the fields of cancer, cardiac physiology and soft-tissue mechanics. It is released under the LGPL 2.1 licence.\ud \ud Chaste has been developed using agile programming methods. The project began in 2005 when it was reasoned that the modelling of a variety of physiological phenomena required both a generic mathematical modelling framework, and a generic computational/simulation framework. The Chaste project evolved from the Integrative Biology (IB) e-Science Project, an inter-institutional project aimed at developing a suitable IT infrastructure to support physiome-level computational modelling, with a primary focus on cardiac and cancer modelling

O- vs. N-protonation of 1-dimethylaminonaphthalene-8-ketones: formation of a peri N–C bond or a hydrogen bond to the pi-electron density of a carbonyl group

X-ray crystallography and solid-state NMR measurements show that protonation of a series of 1-dimethylaminonaphthalene-8-ketones leads either to O protonation with formation of a long N–C bond (1.637–1.669 Å) between peri groups, or to N protonation and formation of a hydrogen bond to the π surface of the carbonyl group, the latter occurring for the larger ketone groups (C(O)R, R = t-butyl and phenyl). Solid state 15N MAS NMR studies clearly differentiate the two series, with the former yielding significantly more deshielded resonances. This is accurately corroborated by DFT calculation of the relevant chemical shift parameters. In the parent ketones X-ray crystallography shows that the nitrogen lone pair is directed towards the carbonyl group in all cases

Generalized Wishart processes for interpolation over diffusion tensor fields

Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive tool for watching the microstructure of fibrous nerve and muscle tissue. From dMRI, it is possible to estimate 2-rank diffusion tensors imaging (DTI) fields, that are widely used in clinical applications: tissue segmentation, fiber tractography, brain atlas construction, brain conductivity models, among others. Due to hardware limitations of MRI scanners, DTI has the difficult compromise between spatial resolution and signal noise ratio (SNR) during acquisition. For this reason, the data are often acquired with very low resolution. To enhance DTI data resolution, interpolation provides an interesting software solution. The aim of this work is to develop a methodology for DTI interpolation that enhance the spatial resolution of DTI fields. We assume that a DTI field follows a recently introduced stochastic process known as a generalized Wishart process (GWP), which we use as a prior over the diffusion tensor field. For posterior inference, we use Markov Chain Monte Carlo methods. We perform experiments in toy and real data. Results of GWP outperform other methods in the literature, when compared in different validation protocols

CCI52 sensitizes tumors to 6-mercaptopurine and inhibits MYCN-amplified tumor growth

The antimetabolite 6-mercaptopurine (6-MP) is an important component in the treatment of specific cancer subtypes, however, the development of drug resistance and dose-limiting toxicities can limit its effectiveness. The therapeutic activity of 6-MP requires cellular uptake, enzymatic conversion to thio-GMP and incorporation of thio-GTP into RNA and DNA, as well as inhibition of de novo purine synthesis by methyl-thio-IMP. Mechanisms that prevent 6-MP entry into the cell, prevent 6-MP metabolism or deplete thiopurine intermediates, can all lead to 6-MP resistance. We previously conducted a high-throughput screen for inhibitors of the multidrug transporter MRP4 using 6-MP sensitivity as the readout. In addition to MRP4-specific inhibitors, we identified a compound, CCI52, that sensitized cell lines to 6-MP independent of this transporter. CCI52 and its more stable analogue CCI52-14 also function as effective chemosensitizers in vivo, substantially extending survival in a transgenic mouse cancer model treated with 6-MP. Chemosensitization was associated with an increase in thio-IMP, suggesting that CCI52 functions directly on 6-MP uptake or metabolism. In addition to its chemosensitizing effects, CCI52 and CCI52-14 inhibited the growth of MYCN-amplified high-risk neuroblastoma cell lines and delayed tumor progression in a MYCN-driven, transgenic mouse model of neuroblastoma. These multifunctional inhibitors may be useful for the further development of anticancer agents and as tools to better understand 6-MP metabolism

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study

The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation, and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.Comment: Submitted to 'Systems Medicine' as a book chapte