PASSCLAIM - gut health and immunity

Background The gut and immune system form a complex integrated structure that has evolved to provide effective digestion and defence against ingested toxins and pathogenic bacteria. However, great variation exists in what is considered normal healthy gut and immune function. Thus, whilst it is possible to measure many aspects of digestion and immunity, it is more difficult to interpret the benefits to individuals of variation within what is considered to be a normal range. Nevertheless, it is important to set standards for optimal function for use both by the consumer, industry and those concerned with the public health. The digestive tract is most frequently the object of functional and health claims and a large market already exists for gut-functional foods worldwide. Aim To define normal function of the gut and immune system and describe available methods of measuring it. Results We have defined normal bowel habit and transit time, identified their role as risk factors for disease and how they may be measured. Similarly, we have tried to define what is a healthy gut flora in terms of the dominant genera and their metabolism and listed the many, varied and novel methods for determining these parameters. It has proved less easy to provide boundaries for what constitutes optimal or improved gastric emptying, gut motility, nutrient and water absorption and the function of organs such as the liver, gallbladder and pancreas. The many tests of these functions are described. We have discussed gastrointestinal well being. Sensations arising from the gut can be both pleasant and unpleasant. However, the characteristics of well being are ill defined and merge imperceptibly from acceptable to unacceptable, a state that is subjective. Nevertheless, we feel this is an important area for future work and method development. The immune system is even more difficult to make quantitative judgements about. When it is defective, then clinical problems ensure, but this is an uncommon state. The innate and adaptive immune systems work synergistically together and comprise many cellular and humoral factors. The adaptive system is extremely sophisticated and between the two arms of immunity there is great redundancy, which provides robust defences. New aspects of immune function are discovered regularly. It is not clear whether immune function can be "improved". Measuring aspects of immune function is possible but there is no one test that will define either the status or functional capacity of the immune system. Human studies are often limited by the ability to sample only blood or secretions such as saliva but it should be remembered that only 2% of lymphocytes circulate at any given time, which limits interpretation of data. We recommend assessing the functional capacity of the immune system by: measuring specific cell functions ex vivo, measuring in vivo responses to challenge, e. g. change in antibody in blood or response to antigens, determining the incidence and severity of infection in target populations during naturally occurring episodes or in response to attenuated pathogens.

A preliminary investigation of the running digit span as a test of working memory

The objective of this study was to compare performance on different versions of the running span task, and to examine the relationship between task performance and tests of episodic memory and executive function. We found that the average capacity of the running span was approximately 4 digits, and at long sequence lengths, performance was no longer affected by varying the running span window. Both episodic and executive function measures correlated with short and long running spans. suggesting that a simple dissociation between immediate memory and executive processes in short and long running digit span tasks may not be warranted.

Dissociating mere exposure and repetition priming as a function of word type

The mere exposure effect is defined as enhanced attitude toward a stimulus that has been repeatedly exposed. Repetition priming is defined as facilitated processing of a previously exposed stimulus. We conducted a direct comparison between the two phenomena to test the assumption that the mere exposure effect represents an example of repetition priming. In two experiments, having studied a set of words or nonwords, participants were given a repetition priming task (perceptual identification) or one of two mere exposure (affective liking or preference judgment) tasks. Repetition printing was obtained for both words and nonwords, but only nonwords produced a mere exposure effect. This demonstrates a key boundary for observing the mere exposure effect, one not readily accommodated by a perceptual representation systems (Tulving & Schacter, 1990) account, which assumes that both phenomena should show some sensitivity to nonwords and words.

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.

Prediction of Parkinson’s Disease tremor onset using a radial basis function neural network based on particle swarm optimization

Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.

Acute effects of elevated NEFA on vascular function: a comparison of SFA and MUFA

There is emerging evidence to show that high levels of NEFA contribute to endothelial dysfunction and impaired insulin sensitivity. However, the impact of NEFA composition remains unclear. A total of ten healthy men consumed test drinks containing 50 g of palm stearin (rich in SFA) or high-oleic sunflower oil (rich in MUFA) on separate occasions; a third day included no fat as a control. The fats were emulsified into chocolate drinks and given as a bolus (approximately 10 g fat) at baseline followed by smaller amounts (approximately 3 g fat) every 30 min throughout the 6 h study day. An intravenous heparin infusion was initiated 2 h after the bolus, which resulted in a three- to fourfold increase in circulating NEFA level from baseline. Mean arterial stiffness as measured by digital volume pulse was higher during the consumption of SFA (P,0·001) but not MUFA (P¼0·089) compared with the control. Overall insulin and gastric inhibitory peptide response was greater during the consumption of both fats compared with the control (P,0·001); there was a second insulin peak in response to MUFA unlike SFA. Consumption of SFA resulted in higher levels of soluble intercellular adhesion molecule-1 (sI-CAM) at 330 min than that of MUFA or control (P#0·048). There was no effect of the test drinks on glucose, total nitrite, plasminogen activator inhibitor-1 or endothelin-1 concentrations. The present study indicates a potential negative impact of elevated NEFA derived from the consumption of SFA on arterial stiffness and sI-CAM levels. More studies are needed to fully investigate the impact of NEFA composition on risk factors for CVD.

Dual-orthogonal radial basis function networks for nonlinear time series prediction

A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.

A review of the evidence for the effects of total dietary fat, SFA, MUFA and n-6 PUFA on vascular function, endothelial progenitor cells and microparticles

Vascular dysfunction is recognised as an integrative marker of CVD. While dietary strategies aimed at reducing CVD risk include reductions in the intake of SFA, there are currently no clear guidelines on what should replace SFA. The purpose of this review was to assess the evidence for the effects of total dietary fat and individual fatty acids (SFA, MUFA and n-6 PUFA) on vascular function, cellular microparticles and endothelial progenitor cells. Medline was systematically searched from 1966 until November 2010. A total of fifty-nine peer-reviewed publications (covering fifty-six studies), which included five epidemiological, eighteen dietary intervention and thirty-three test meal studies, were identified. The findings from the epidemiological studies were inconclusive. The limited data available from dietary intervention studies suggested a beneficial effect of low-fat diets on vascular reactivity, which was strongest when the comparator diet was high in SFA, with a modest improvement in measures of vascular reactivity when high-fat, MUFA-rich diets were compared with SFA-rich diets. There was consistent evidence from the test meal studies that high-fat meals have a detrimental effect on postprandial vascular function. However, the evidence for the comparative effects of test meals rich in MUFA or n-6 PUFA with SFA on postprandial vascular function was limited and inconclusive. The lack of studies with comparable within-study dietary fatty acid targets, a variety of different study designs and different methods for determining vascular function all confound any clear conclusions on the impact of dietary fat and individual fatty acids on vascular function.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Ethnic differences in beta-cell function, dietary intake and expression of the metabolic syndrome among UK adults of south Asian, black African-Caribbean and white-European origin at high risk of metabolic syndrome

A cross-sectional analysis of ethnic differences in dietary intake, insulin sensitivity and beta-cell function, using the intravenous glucose tolerance test (IVGTT), was conducted on 497 healthy adult participants of the ‘Reading, Imperial, Surrey, Cambridge, and Kings’ (RISCK) study. Insulin sensitivity (Si) was significantly lower in African-Caribbean (AC) and South Asian (SA) participants [IVGTT-Si; AC: 2.13 vs SA: 2.25 vs white-European (WE): 2.84 (×10−4 mL µU min)2, p < 0.001]. AC participants had a higher prevalence of anti-hypertensive therapy (AC: 19.7% vs SA: 7.5%), the most cardioprotective lipid profile [total:high-density lipoprotein (HDL); AC: 3.52 vs SA: 4.08 vs WE: 3.83, p = 0.03] and more pronounced hyperinsulinaemia [IVGTT–acute insulin response (AIR)] [AC: 575 vs SA: 428 vs WE: 344 mL/µU/min)2, p = 0.002], specifically in female participants. Intake of saturated fat and carbohydrate was lower and higher in AC (10.9% and 50.4%) and SA (11.1% and 52.3%), respectively, compared to WE (13.6% and 43.8%, p < 0.001). Insulin resistance in ACs is characterised by ‘normal’ lipid profiles but high rates of hypertension and pronounced hyperinsulinaemia.

Processing speed, executive function, and age differences in remembering and knowing

A group of young (n=52, M=23.27 years) and old (n=52, M=68.62 years) adults studied two lists of semantically unrelated nouns. For one list a time of 2 s was allowed for encoding, and for the other, 5 s. A recognition test followed where participants classified their responses according to Gardiner’s (1988) remember–know procedure. Age differences for remembering and knowing were minimal in the faster 2-s encoding condition. However, in the longer 5-s encoding condition, younger persons produced significantly more remember responses, and older adults a greater number of know responses. This dissociation suggests that in the longer encoding condition, younger adults utilized a greater level of elaborative rehearsal governed by executive processes, whereas older persons employed maintenance rehearsal involving short-term memory. Statistical control procedures, however, found that independent measures of processing speed accounted for age differences in remembering and knowing and that independent measures of executive control had little influence. The findings are discussed in the light of contrasting theoretical accounts of recollective experience in old age.

A genome-wide test of the differential susceptibility hypothesis reveals a genetic predictor of differential response to psychological treatments for child anxiety disorders

Background: The differential susceptibly hypothesis suggests that certain genetic variants moderate the effects of both negative and positive environments on mental health and may therefore be important predictors of response to psychological treatments. Nevertheless, the identification of such variants has so far been limited to preselected candidate genes. In this study we extended the differential susceptibility hypothesis from a candidate gene to a genome-wide approach to test whether a polygenic score of environmental sensitivity predicted response to Cognitive Behavioural Therapy (CBT) in children with anxiety disorders. Methods: We identified variants associated with environmental sensitivity using a novel method in which within-pair variability in emotional problems in 1026 monozygotic (MZ) twin pairs was examined as a function of the pairs’ genotype. We created a polygenic score of environmental sensitivity based on the whole-genome findings and tested the score as a moderator of parenting on emotional problems in 1,406 children and response to individual, group and brief parent-led CBT in 973 children with anxiety disorders. Results: The polygenic score significantly moderated the effects of parenting on emotional problems and the effects of treatment. Individuals with a high score responded significantly better to individual CBT than group CBT or brief parent-led CBT (remission rates: 70.9%, 55.5% and 41.6% respectively). Conclusions: Pending successful replication, our results should be considered exploratory. Nevertheless, if replicated, they suggest that individuals with the greatest environmental sensitivity may be more likely to develop emotional problems in adverse environments, but also benefit more from the most intensive types of treatment.