The potential for deprescribing in care home residents with Type 2 diabetes

Background: Type 2 diabetes is a common diagnosis in care home residents that is associated with potentially inappropriate prescribing and thus risk of additional suffering. Previous studies found that diabetes medicines can be safely withdrawn in care home residents, encouraging further investigation of the potential for deprescribing amongst these patients. Objectives: Describe comorbidities and medicine use in care home residents with Type 2 diabetes; identify number of potentially inappropriate medicines prescribed for these residents using a medicines optimisation tool; assess clinical applicability of the tool. Setting Thirty care homes for older people, East Anglia, UK. Method: Data on diagnoses and medicines were extracted from medical records of 826 residents. Potentially inappropriate medicines were identified using the tool ‘Optimising Safe and Appropriate Medicines Use’. Twenty percent of results were validated by a care home physician. Main outcome measure: Number of potentially inappropriate medicines. Results: The 106 residents with Type 2 diabetes had more comorbidities and prescriptions than those without. Over 90 % of residents with Type 2 diabetes had at least one potentially inappropriate medication. The most common was absence of valid indication. The physician unreservedly endorsed 39 % of the suggested deprescribing, and would consider discontinuing all but one of the remaining medicines following access to additional information. Conclusion: UK care home residents with Type 2 diabetes had an increased burden of comorbidities and prescriptions. The majority of these patients were prescribed potentially inappropriate medicines. Validation by a care home physician supported the clinical applicability of the medicines optimisation tool

Findings from the University of East Anglia's evaluation of the Ipswich/Suffolk multi-agency strategy on prostitution following the five murders in 2006

This paper provides a summary of the main findings of an evaluation of a new multi-agency Strategy set up to tackle on-street sex-working, after five prostitutes were murdered in the English county town of Ipswich. It focuses on the outcomes of the Strategy’s four objectives, including their cost-effectiveness. It also offers an insight into the lives of the women who were previously involved in street sex-working, the means by which the Strategy helped them to move towards exiting this work, and the ways in which younger people identified as being at risk of entering it might be prevented from doing so

Investigating calcium signalling in Marchantia polymorpha: A study of CBLs and CIPKs.

Global food security is one of the preeminent challenges facing the modern world as a rising population demands an ever increasing volume of food to feed it. However, simultaneously climate change through both drought and other extreme weather events is proceeding to destroy arable land, leaving less and less viable farming space every year. In order to help combat this, generations of more hardy crop plants could be generated to use this otherwise unusable land. But in order to do this we need to understand better just how plants respond to the stresses currently rendering the land useless. Calcium is a ubiquitous secondary messenger in plants which is involved in a variety of stress responses including physical, biotic and abiotic stresses by creating calcium signals. Plants decode these signals through a suite of decoder proteins, however years of evolution and hybridisation events have left the genome of crop plants highly convoluted and difficult to decipher. However, Marchantia polymorpha is one of the earliest diverging land plants, with a much reduced set of decoder proteins, making it an excellent tool for studying both how these stress responses evolved, and how the systems themselves operate. This work investigates a particular subset of these decoder proteins, Calcineurin B-Like proteins (CBLs) and their interacting partners, CBL-Interacting Protein Kinases (CIPKs). When compared to the tradition plant model organism Arabidopsis thaliana I have shown that both CIPKs of M. polymorpha bind CBLs non-specifically, binding to all three native CBLs as well as AtCBL4 from Arabidopsis thaliana. This total promiscuity is not shared by AtCIPK24, failing to bind CBL-C from M. polymorpha. Additionally, work has begun on identifying the stresses that CIPKs are responsible for, a phenotyping experiment utilising cipk-B KO mutants showing that CIPK-B is necessary for salt tolerance in M. polymorpha

Signatures of Bayesian inference emerge from energy efficient synapses

Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mechanisms cost energy. We examined four such mechanisms along with the associated scaling of the energetic costs. We then embedded these energetic costs for reliability in artificial neural networks (ANN) with trainable stochastic synapses, and trained these networks on standard image classification tasks. The resulting networks revealed a tradeoff between circuit performance and the energetic cost of synaptic reliability. Additionally, the optimised networks exhibited two testable predictions consistent with pre-existing experimental data. Specifically, synapses with lower variability tended to have 1) higher input firing rates and 2) lower learning rates. Surprisingly, these predictions also arise when synapse statistics are inferred through Bayesian inference. Indeed, we were able to find a formal, theoretical link between the performance-reliability cost tradeoff and Bayesian inference. This connection suggests two incompatible possibilities: evolution may have chanced upon a scheme for implementing Bayesian inference by optimising energy efficiency, or alternatively, energy efficient synapses may display signatures of Bayesian inference without actually using Bayes to reason about uncertainty.Comment: 29 pages, 11 figure

Crystallisation and crystal structure studies of some TCNQ salts

A series of salts of the radical ion TCNQ were prepared by standard organic techniques or by controlled electrocrystallisation and their three-dimensional crystal structures were determined by single crystal X-ray diffractometry. The crystallisation of the two-phase system found in 1,2-bis(1-ethyl-4-pyridinio)ethene (TCNQ)4 was studied using a.c. conductivity techniques. The results showed phase formation to be dependent upon both concentration and cooling rate, and no evidence was found for a third phase possessing a metallic d.c. solid state conductivity. The structures reported in detail are: a) 1,4-dimethylpyridinium (TCNQ)2' DMPY(TCNQ)2' Triclinic, a = 7.833, b = 13.889, c -7.171Angstrem, alpha = 106.81, beta = 112.50, gamma = 95.36°, z = 1, space group P1. TCNQ moieties stacked as discrete diads with an interplanar separation of 3.21 Angstrem within the diad. The d.c. dark conductivity was measured (sigma 300 = 1.7 x 10 (-4) ohm cm (-1)) and is consistent with the observed structure. b) 2,3-bis(1-methyl-4-pyridinio)butane (TCNQ)4' DMPB (TCNQ)4, Triclinic, a = 7.798, b = 14.248, c = 13.690 Angstrem, alpha = 109.53, beta = 103.37, gamma = 95.42°, Z = 1, space group P1. TCNQ moieties stacked as discrete tetrads with interplanar separations of 3.13 and 3.17 Angstrem within the tetrad. Anisotropic d.c. dark conductivity measurements were made and found to be consistent with the structure. c) 1,2-bis(1-hydro-4-pyridinio)ethane (TCNQ)2, DHPA (TCNQ)2, monoclinic, a = 29.481, b = 7.405, c = 13.470 grad., beta = 94.03 grad., Z = 4, space group 2/c. TCNQ moieties arranged in 4 columns of diads along c with an interplanar separation of 3.10 Angstrem within the diad. The structure exhibits hydrogen bonding (N - H--------N heavy atom separation = 2.885 Angstrem) between the cation and TCNQ moieties. d) 1,2-bis(1-hydro-4-pyridinio)ethane (TCNQ)4, DHPA (TCNQ)4, monoclinic, a = 12.894, b = 3.933, c = 27.580 grad., beta = 109.95 grad., Z = 1, space group P 21/c .TCNQ moieties in infinite stacks along b with cations in disordered positions in the channels between the stacks

Topological and simplicial features in reservoir computing networks

Reservoir computing is a framework which uses the nonlinearinternal dynamics of a recurrent neural network to perform complexnon-linear transformations of the input. This enables reservoirs tocarry out a variety of tasks involving the processing of time-dependent orsequential-based signals. Reservoirs are particularly suited for tasks thatrequire memory or the handling of temporal sequences, common in areassuch as speech recognition, time series prediction, and signal processing.Learning is restricted to the output layer and can be thought of as“reading out” or “selecting from” the states of the reservoir. With all butthe output weights fixed they do not have the costly and difficult trainingassociated with deep neural networks. However, while the reservoircomputing framework shows a lot of promise in terms of efficiency andcapability, it can be unreliable. Existing studies show that small changesin hyperparameters can markedly affect the network’s performance. Herewe studied the role of network topologies in reservoir computing in thecarrying out of three conceptually different tasks: working memory, perceptualdecision making, and chaotic time-series prediction. We implementedthree different network topologies (ring, lattice, and random)and tested reservoir network performances on the tasks. We then usedalgebraic topological tools of directed simplicial cliques to study deeperconnections between network topology and function, making comparisonsacross performance and linking with existing reservoir research

The chronic effects of dietary (poly)phenols on mitochondrial dysfunction and glucose uptake in cellular models of the liver and skeletal muscle.

Background: Type 2 diabetes is characterised by chronic hyperglycaemia, insulin resistance and associated mitochondrial dysfunction. (Poly)phenols have been shown to attenuate cellular oxidative stress and restore glucose homeostasis, but the specific mechanisms and compounds responsible remain unknown. Methods: HepG2 cells were used as an in vitro hepatic model, on which the effects of quercetin on high glucose-induced oxidative stress and mitochondrial dysfunction were investigated. Mitochondria were assessed for complex I activity, cellular redox status, mitochondrial respiration and PGC-1α expression. LHCN-M2 human skeletal myocytes were differentiated in various glucose and insulin concentrations and characterised for their use as a model to explore the effects of relevant (poly)phenol metabolites on glucose uptake and metabolism. Metabolic phenotype and the effects of metabolites derived from ferulic acid, flavonols, resveratrol and berry (poly)phenols were evaluated by Western capillary protein assays, uptake of 2-[1-14C(U)]-deoxy-D-glucose and D-[14C(U)]-glucose; respirometry and the ROS assay were also used for initial metabolic characterisation. Results: Mitochondrial function was restored by quercetin in HepG2 cells exposed to high glucose, by reversing the increased cellular NADH, enhancing mitochondrial respiration and preventing proton leak, and upregulating PGC-1α, all of which led to restored complex I activity after 24 h. The LHCN-M2 model was established and cells differentiated in a normal or high glucose/insulin environment. Glucose transport was restored, and metabolism increased, in high glucose/insulin myotubes by various metabolites. Isovanillic acid 3-O-sulfate in particular elicited this effect by upregulating GLUT1, GLUT4 and PI3K protein expression, and acutely activating the insulin signalling pathway. Conclusions: Quercetin protects against hepatic mitochondrial dysfunction through pleiotropic effects involving improved redox status and enhanced mitochondrial respiration and function. (Poly)phenol metabolites, including the gut microbiome catabolite isovanillic acid 3-O-sulfate, restore glucose uptake and metabolism in human skeletal muscle exposed to high glucose and insulin, via insulin-dependent pathways

Molecular diversity and functional composition of cellulose degrading communities in anoxic environments

The major fraction of microbial communities cannot be cultivated by artificial means in the laboratory. In order to access the full diversity of microbial life in the open environment it is necessary to employ culture independent methods. Molecular biology and now metagenomics have enabled the phylogenetic and functional investigation of microbial communities without isolation and cultivation of organisms and has led to a new appreciation of the breadth of diversity of microbes on Earth and to the discovery and characterisation of new enzymes. Here, molecular biological techniques have been applied to the study of microbial communities specifically in anaerobic environments and with an emphasis on those involved in the primary degradation of plant cellulosic biomass. Quantitative PCR was used to assess the presence of cellulolytic bacteria both in landfill leachate and specifically in association with cotton cellulose “baits” maintained in leachate microcosms. Lineages of clostridia previously associated with cellulose degrading strains were detected in all five of the landfill leachate samples, and Fibrobacter spp. were detected at low abundance (2.3% of total bacteria) in one sample. Clostridia Group III and Fibrobacter spp. were enriched on the surface of a bait (17% and 29% of total bacteria, respectively) that was rapidly degraded by the colonising community and were present in low abundance

Variational Bayesian inference for comparison Var(1) models

Suppose that we wish to determine which models in a candidate set are most likely to have given rise to a set of observed data. Then, it is well-established that, from a Bayesian viewpoint, evaluation of the marginal likelihood for each candidate is a crucial step to this end. For the purposes of model comparison, this will enable subsequent computation of both Bayes’ factors and posterior model probabilities. Given its evident significance in this area, it is thus regrettable that analytic calculation of the marginal likelihood is often not possible. To tackle this problem, one recent addition to the literature is the variational Bayesian approach. In this thesis, it is seen that variational Bayes provides efficient, accurate approximations to both the marginal likelihood and the parameter posterior distribution, conditioned on each model. In particular, the theory is applied to ranking sparse, vector autoregressive graphical models of order 1 in both the zero and non-zero mean case. That is, our primary aim is to estimate the unknown sparsity structure of the autoregressive matrix in the process. Moreover, approximate, marginal posterior information about the coefficients of this matrix is also of interest. To enable rapid exploration of higher-dimensional graphical spaces, a Metropolis-Hastings algorithm is presented so that a random walk can be made between neighbouring graphs. The scheme is then tested on both simulated and real datasets of varying dimension.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research CouncilGBUnited Kingdo