Long-Term Impact of Community-Based Information,Education and Communication Activities on Food Hygiene and Food Safety Behaviors in Vietnam: A Longitudinal Study

Background

Ingestion of contaminated water or food is a major contributor to childhood diarrhea in developing countries. In Vietnam, the use of community-based information, education and communication (IEC) activities could be a sustainable strategy to improve food hygiene and food safety behaviors. This study thus examined the long-term impact of community-based IEC activities on food hygiene and food safety behaviors.

Methods

In this longitudinal study, we interviewed caregivers of children aged between six months and four years in suburban Hanoi. Baseline data were collected in January 2006 (n = 125). After conducting IEC interventions, we collected a 1^st set of evaluation data in January 2007 (n = 132). To examine the long-term impact of the interventions, we then collected a 2^nd set of evaluation data in January 2008 (n = 185). Changes in childhood diarrhea prevalence, IEC coverage, and food hygiene and food safety behaviors were assessed over a two-year period using bivariate and logistic regression analyses. Effective IEC channels were determined through multiple linear regression analysis.

Results

Childhood diarrhea was significantly reduced from 21.6% at baseline to 7.6% at the 1^st post-intervention evaluation (P = 0.002), and to 5.9% at the 2^nd evaluation. Among 17 food hygiene and food safety behaviors measured, a total of 11 behaviors were improved or maintained by the 2^nd evaluation. Handwashing after toilet use was significantly improved at both evaluation points. Overall, 3 food safety behaviors and 7 food hygiene behaviors were found to have significantly improved at the 1^st and at the 2^nd evaluations, respectively. Flip chart communication administered by community groups was identified to be the most effective IEC channel for effecting behavior change (P = 0.018).

Conclusions

Flip chart communication administered by community groups is effective for improving multiple food hygiene and food safety behaviors in sustainable ways, and should be included in water and health promotion programs.     

Scale-up of the fermentation and purification of the recombinant heavy chain fragment C of botulinum neurotoxin serotype F, expressed in Pichia pastoris

A recombinant heavy chain fragment C of botulinum neurotoxin serotype F (BoNTF(Hc)) has been expressed in Pichia pastoris for use as an antigen in a proposed human vaccine. P. pastoris cells were grown using glycerol batch, glycerol fed-batch, and methanol fed-batch methods to achieve high cell densities. The total cellular protein recovered after homogenization was 72 mg/g of cell paste. BoNTF(Hc) was purified from soluble Pichia cell lysate employing ion-exchange chromatographic (IEC) and hydrophobic interaction chromatographic (HIC) methods developed at the bench scale using 10-100 mL columns. The process was performed at the pilot scale using 1-4L columns for evaluation of scale up. The purification process resulted in greater than 98% pure product consisting of at least three forms of BoNTF(Hc) based on mass spectrometry and yielded up to 205 mg/kg cells at the bench scale and 170 mg/kg cells at the pilot scale. Full-length BoNTF(Hc) is present based on mass spectrometry and SDS-PAGE, however is postulated to be N-terminally blocked by acetylation. N-terminal sequencing showed that two of the three forms are missing the first 11 (80%) and 14 (20%) amino acids of the N-terminus from the full-length form. The ratios of the two clipped forms were consistent from the bench to pilot scales. Purified BoNTF(Hc) at the pilot scale was found to sufficiently protect mice against a high dose of BoNTF neurotoxin.     

A Novel Approach to Estimating Heterozygosity from Low-Coverage Genome Sequence

High-throughput shotgun sequence data make it possible in principle to accurately estimate population genetic parameters without confounding by SNP ascertainment bias. One such statistic of interest is the proportion of heterozygous sites within an individual’s genome, which is informative about inbreeding and effective population size. However, in many cases, the available sequence data of an individual are limited to low coverage, preventing the confident calling of genotypes necessary to directly count the proportion of heterozygous sites. Here, we present a method for estimating an individual’s genome-wide rate of heterozygosity from low-coverage sequence data, without an intermediate step that calls genotypes. Our method jointly learns the shared allele distribution between the individual and a panel of other individuals, together with the sequencing error distributions and the reference bias. We show our method works well, first, by its performance on simulated sequence data and, second, on real sequence data where we obtain estimates using low-coverage data consistent with those from higher coverage. We apply our method to obtain estimates of the rate of heterozygosity for 11 humans from diverse worldwide populations and through this analysis reveal the complex dependency of local sequencing coverage on the true underlying heterozygosity, which complicates the estimation of heterozygosity from sequence data. We show how we can use filters to correct for the confounding arising from sequencing depth. We find in practice that ratios of heterozygosity are more interpretable than absolute estimates and show that we obtain excellent conformity of ratios of heterozygosity with previous estimates from higher-coverage data.     

Noninvasive Transcranial Electrostimulation of the Brain Endophrinergic Structures: Effects on Human Fatigue and Related Psychophysiological Indices

A randomized single-blind passive placebo-controlled study using a set of seven subjective and objective psychophysiological tests that evaluated the background state and changes in 26 psychophysiological indices (including the physical, cognitive, and affective components of fatigue) showed that transcranial electrostimulation (TES) of endorphinergic structures of the human brain facilitates the normalization of most indices. The positive effects of TES were more pronounced in subjects with strong negative shifts of the initial indices, which suggests a homeostatic character of the effects of activation of the brain endorphin-mediated mechanisms. Special attention was paid to the use of an analog scale for rapid evaluation of fatigue whose validity, reliability, and applicability were proved experimentally by the method of correlation matrices.     

The assessment of back muscle capacity using intermittent static contractions. Part I – Validity and reliability of electromyographic indices of fatigue

IntroductionBack muscle capacity is impaired in chronic low back pain patients but no motivation-free test exists to measure it. The aims of this study were to assess the reliability and criterion validity of electromyographic indices of muscle fatigue during an intermittent absolute endurance test.MethodsHealthy subjects (44 males and 29 females; age: 20–55 yrs) performed three maximal voluntary contractions (MVC) and a fatigue test while standing in a static dynamometer. Surface EMG signals were collected from four pairs of back muscles (multifidus at the L5 level, iliocostalis lumborum at L3, and longissimus at L1 and T10). The fatigue test, assessing absolute endurance (90-Nm torque), consisted in performing an intermittent extension task to exhaustion. Strength was defined as the peak MVC whereas our endurance criterion was defined as the time to reach exhaustion (Tend) during the fatigue test. From the first five min (females) or ten min (males) of EMG data, frequency and time-frequency domain analyses were applied to compute various spectral indices of muscle fatigue.ResultsThe EMG indices were more reliable when computed from the time-frequency domain than when computed from the frequency domain, but showed comparable correlation results (criterion validity) with Tend and Strength. Some EMG indices reached moderate to good correlation (range: 0.64–0.69) with Tend, lower correlations (range: 0.39–0.55) with Strength, and good to excellent between-day test-retest reliability results (intra-class correlation range: 0.75–0.83). The quantification of the spectral content more locally in different frequency bands of the power spectrum was less valid and reliable than the indices computed from the entire power spectrum. Differences observed among muscles were interpreted in light of specific neuromuscular activation levels that were observed during the endurance test. These findings supported the use of an intermittent and time-limited (5–10 min) absolute endurance test, that is a practical way to assess the back capacity of chronic low back pain subjects, to assess absolute endurance as well as strength with the use of electromyographic indices of muscle fatigue.     

Absolute binding free energy calculations using molecular dynamics simulations with restraining potentials

The absolute (standard) binding free energy of eight FK506-related ligands to FKBP12 is calculated using free energy perturbation molecular dynamics (FEP/MD) simulations with explicit solvent. A number of features are implemented to improve the accuracy and enhance the convergence of the calculations. First, the absolute binding free energy is decomposed into sequential steps during which the ligand-surrounding interactions as well as various biasing potentials restraining the translation, orientation, and conformation of the ligand are turned "on" and "off." Second, sampling of the ligand conformation is enforced by a restraining potential based on the root mean-square deviation relative to the bound state conformation. The effect of all the restraining potentials is rigorously unbiased, and it is shown explicitly that the final results are independent of all artificial restraints. Third, the repulsive and dispersive free energy contribution arising from the Lennard-Jones interactions of the ligand with its surrounding (protein and solvent) is calculated using the Weeks-Chandler-Andersen separation. This separation also improves convergence of the FEP/MD calculations. Fourth, to decrease the computational cost, only a small number of atoms in the vicinity of the binding site are simulated explicitly, while all the influence of the remaining atoms is incorporated implicitly using the generalized solvent boundary potential (GSBP) method. With GSBP, the size of the simulated FKBP12/ligand systems is significantly reduced, from approximately 25,000 to 2500. The computations are very efficient and the statistical error is small ( approximately 1 kcal/mol). The calculated binding free energies are generally in good agreement with available experimental data and previous calculations (within approximately 2 kcal/mol). The present results indicate that a strategy based on FEP/MD simulations of a reduced GSBP atomic model sampled with conformational, translational, and orientational restraining potentials can be computationally inexpensive and accurate.     

Gap Junctional Communication between Murine Macrophages and Intestinal Epithelial Cell Lines

In intestinal inflammation, inflammatory cells infiltrate the submucosa and are found juxtaposed to intestinal epithelial cell (IEC) basolateral membranes and may directly regulate IEC function. In this study we determined whether macrophage (M), P388D1 and J774A.1, are coupled by gap junctions to IEC lines, Mode-K and IEC6. Using flow cytometric analysis, we show bi-directional transfer of the fluorescent dye, calcein (700 Da) between IEC and M resulting in a 3.5–20-fold increase in recipient cell fluorescence. Homocellular and heterocellular dye transfer between M and/or IEC was detected in cocultures of P388D1, J774A.1, Mode-K, IEC6 and CMT93. However, transfer between P388D1 and Mode-K was asymmetrical in that transfer from P388D1 to Mode-K was always more efficient than transfer from Mode-K to P388D1. Dye transfer was strictly dependent on IEC-M? adhesion which in turn was dependent on the polarity of IEC adhesion molecule expression. Both calcein dye transfer and adhesion were inhibited by the addition of heptanol to cocultures. Furthermore we demonstrate both IEC homocellular, and M?-IEC heterocellular propagation of calcium waves in response to mechanical stimulation, typical of gap junctional communication. Finally, areas of close membrane apposition were seen in electron micrographs of IEC-M? cocultures, suggestive of gap junction formation. These data indicate that IEC and MM? are coupled by gap junctions suggesting that gap junctional communication may provide a means by which inflammatory cells might regulate IEC function.     

Use of periodic abstinence in Bangladesh: do they really understand?

Data from a nationally representative study in Bangladesh (BDHS 1996-97) were analysed to identify significant predictors of use of periodic abstinence, in comparison with other modern contraceptive methods. The study found that women in Bangladesh mostly use modern methods during their peak reproductive years, after which some of them switch to periodic abstinence. These women tend to be more from educated and from higher socioeconomic backgrounds and with at least one living son. Another set of data from the Matlab DSS was analysed and the results were in the same direction. Focus group discussions found that women were using the periodic abstinence method incorrectly, abstaining for more days than is necessary. For Bangladeshi contraceptive users to reach a higher degree of use-effectiveness for period abstinence, more IEC materials need to be developed.     

The Influence of Data Resolution on Predicted Distribution and Estimates of Extent of Current Protection of Three ‘Listed’ Deep-Sea Habitats

Modelling approaches have the potential to significantly contribute to the spatial management of the deep-sea ecosystem in a cost effective manner. However, we currently have little understanding of the accuracy of such models, developed using limited data, of varying resolution. The aim of this study was to investigate the performance of predictive models constructed using non-simulated (real world) data of different resolution. Predicted distribution maps for three deep-sea habitats were constructed using MaxEnt modelling methods using high resolution multibeam bathymetric data and associated terrain derived variables as predictors. Model performance was evaluated using repeated 75/25 training/test data partitions using AUC and threshold-dependent assessment methods. The overall extent and distribution of each habitat, and the percentage contained within an existing MPA network were quantified and compared to results from low resolution GEBCO models. Predicted spatial extent for scleractinian coral reef and Syringammina fragilissima aggregations decreased with an increase in model resolution, whereas Pheronema carpenteri total suitable area increased. Distinct differences in predicted habitat distribution were observed for all three habitats. Estimates of habitat extent contained within the MPA network all increased when modelled at fine scale. High resolution models performed better than low resolution models according to threshold-dependent evaluation. We recommend the use of high resolution multibeam bathymetry data over low resolution bathymetry data for use in modelling approaches. We do not recommend the use of predictive models to produce absolute values of habitat extent, but likely areas of suitable habitat. Assessments of MPA network effectiveness based on calculations of percentage area protection (policy driven conservation targets) from low resolution models are likely to be fit for purpose.     

Semi-Supervised Multi-View Learning for Gene Network Reconstruction

The task of gene regulatory network reconstruction from high-throughput data is receiving increasing attention in recent years. As a consequence, many inference methods for solving this task have been proposed in the literature. It has been recently observed, however, that no single inference method performs optimally across all datasets. It has also been shown that the integration of predictions from multiple inference methods is more robust and shows high performance across diverse datasets. Inspired by this research, in this paper, we propose a machine learning solution which learns to combine predictions from multiple inference methods. While this approach adds additional complexity to the inference process, we expect it would also carry substantial benefits. These would come from the automatic adaptation to patterns on the outputs of individual inference methods, so that it is possible to identify regulatory interactions more reliably when these patterns occur. This article demonstrates the benefits (in terms of accuracy of the reconstructed networks) of the proposed method, which exploits an iterative, semi-supervised ensemble-based algorithm. The algorithm learns to combine the interactions predicted by many different inference methods in the multi-view learning setting. The empirical evaluation of the proposed algorithm on a prokaryotic model organism (E. coli) and on a eukaryotic model organism (S. cerevisiae) clearly shows improved performance over the state of the art methods. The results indicate that gene regulatory network reconstruction for the real datasets is more difficult for S. cerevisiae than for E. coli. The software, all the datasets used in the experiments and all the results are available for download at the following link: http://figshare.com/articles/Semi_supervised_Multi_View_Learning_for_Gene_Network_Reconstruction/1604827.     

A neural model of the dynamic activation of memory

We study an Attractor Neural Network that stores natural concepts, organized in semantic classes. The concepts are represented by distributed patterns over a space of attributes, and are related by both semantic and episodic associations. While semantic relations are expressed through an hierarchical coding over the attribute space, episodic links are realized via specific synaptic projections. Due to dynamic thresholds expressing neuronal fatigue, the network's behavior is characterized by convergence toward the concept patterns on a short time scale, and by transitions between the various patterns on a longer time scale. In its baseline, undamaged state, the network manifests semantic, episodic, and random transitions, and demonstrates the phenomen of priming. Modeling possible pathological changes, we have found that increasing the noise level or the rate of neuronal fatigue decreases the frequency of semantic transitions. When neurons characterized by large synaptic connectivity are deleted, semantic transitions decay before the episodic ones, in accordance with the findings in patients with Alzheimer's disease.     

3D TOF-PET image reconstruction using total variation regularization

In this paper we introduce a semi-analytic algorithm for 3-dimensional image reconstruction for positron emission tomography (PET). The method consists of the back-projection of the acquired data into the most likely image voxel according to time-of-flight (TOF) information, followed by the filtering step in the image space using an iterative optimization algorithm with a total variation (TV) regularization. TV regularization in image space is more computationally efficient than usual iterative optimization methods for PET reconstruction with full system matrix that use TV regularization. The efficiency comes from the one-time TOF back-projection step that might also be described as a reformatting of the acquired data. An important aspect of our work concerns the evaluation of the filter operator of the linear transform mapping an original radioactive tracer distribution into the TOF back-projected image. We obtain concise, closed-form analytical formula for the filter operator. The proposed method is validated with the Monte Carlo simulations of the NEMA IEC phantom using a one-layer, 50 cm-long cylindrical device called Jagiellonian PET scanner. The results show a better image quality compared with the reference TOF maximum likelihood expectation maximization algorithm.     

A LABELED AFFECTIVE MAGNITUDE (LAM) SCALE FOR ASSESSING FOOD LIKING/DISLIKING1

The most widely used scale for assessing food liking or disliking is the 9‐pt hedonic scale. Unfortunately, this affective scale suffers from problems related to unequal scale intervals and the underuse of end categories, which results in a reduced ability to differentiate among extremely well liked or extremely disliked foods. Magnitude estimation avoids these problems while enabling ratio statements to be made about the data. However, it does not provide absolute ratings of liking/disliking and can be difficult for some consumers to use. We report here on the development of a labeled affective magnitude scale (LAM) scale that has advantages over both the 9‐pt hedonic scale and magnitude estimation. Forty‐four semantic labels were scaled for their affective meaning by subjects using modulus‐free magnitude estimation. The geometric mean magnitude estimates obtained for each semantic label were used to construct a series of labeled affective magnitude scales by spacing the labels along a visual analogue scale according to their obtained semantic values. Reliability and sensitivity studies were conducted to assess the effects of alternative semantic and numeric labels. The results of these studies led to the choice of a scale format that uses verbal labels that are consistent with the 9‐pt hedonic scale. The labeled affective magnitude (LAM) scale was compared to the hedonic scale and magnitude estimation in several food preference and acceptability tests. The LAM was shown to have equal reliability and sensitivity to the hedonic scale, provided somewhat greater discrimination among highly liked foods, and resulted in data that were similar to magnitude estimation in terms of the obtained ratios among rated stimuli. The LAM scale was also judged by consumers to be as easy to use as the 9‐pt hedonic scale and significantly less difficult than magnitude estimation.     

Generation of renewable mouse intestinal epithelial cell monolayers and organoids for functional analyses

Background

Conditional reprogramming has enabled the development of long-lived, normal epithelial cell lines from mice and humans by in vitro culture with ROCK inhibitor on a feeder layer. We applied this technology to mouse small intestine to create 2D mouse intestinal epithelial monolayers (IEC monolayers) from genetic mouse models for functional analysis.

Results

IEC monolayers form epithelial colonies that proliferate on a feeder cell layer and are able to maintain their genotype over long-term passage. IEC monolayers form 3D spheroids in matrigel culture and monolayers on transwell inserts making them useful for functional analyses. IEC monolayers derived from the Cystic Fibrosis (CF) mouse model CFTR ?F508 fail to respond to CFTR activator forskolin in 3D matrigel culture as measured by spheroid swelling and transwell monolayer culture via Ussing chamber electrophysiology. Tumor IEC monolayers generated from the Apc^Min/+ mouse intestinal cancer model grow more quickly than wild-type (WT) IEC monolayers both on feeders and as spheroids in matrigel culture.

Conclusions

These results indicate that generation of IEC monolayers is a useful model system for growing large numbers of genotype-specific mouse intestinal epithelial cells that may be used in functional studies to examine molecular mechanisms of disease and to identify and assess novel therapeutic compounds.

     

The Neural Substrates of Self-Evaluation of Mental Fatigue: A Magnetoencephalography Study

There have been several studies of the neural mechanisms underlying sensation of fatigue. However, little is known about the neural mechanisms underlying self-evaluation of the level of fatigue. The aim of this study was to identify the neural substrates involved in self-evaluation of the level of mental fatigue. We used magnetoencephalography (MEG) with high temporal resolution on 14 healthy participants. During MEG recordings, participants were asked to evaluate their level of mental fatigue in time with execution cues (evaluation trials) or to do nothing in time with execution cues (control trials). The MEG data were analyzed with equivalent current dipole (ECD) and spatial filtering methods to localize the neural activity related to the evaluation of mental fatigue. The daily level of fatigue sensation was assessed using the Checklist Individual Strength questionnaire. In evaluation trials, ECDs were observed in the posterior cingulate cortex (PCC) in seven of 14 participants, with a mean latency of 366.0 ms. The proportion of the participants with ECDs in the PCC was higher in evaluation trials than in control trials (P<0.05, McNemar test). The extent of the decreased delta band power in the PCC (Brodmann’s area 31) 600–700 ms after the onset of the execution cue and that in the dorsolateral prefrontal cortex (DLPFC; Brodmann’s area 9) 800–900 ms after the onset of the execution cue were greater in the evaluation trials than in the control trials. The decrease in delta band power in the DLPFC was positively related to that in the PCC and to the daily level of fatigue sensation. These data suggest that the PCC and DLPFC are involved in the self-evaluation of mental fatigue.     

Stroke rehabilitation reaches a threshold

Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is "in vain": there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train-wait-train paradigm: if spontaneous arm use has increased in the "wait" period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided.     

Caution is needed when applying Margalef diversity index

The use of diversity indices has increased due to the necessity of testing different methodologies to develop the ecological status classification of water bodies within the water framework directive implementation. The Margalef diversity index is one of the indices applied within these aims. Several software packages calculate various diversity indices. However, these packages do not give any warning that for the Margalef index the data must be organized as absolute numbers and not as a density data matrix. In data expressed as number of individuals per square meter, if the sample size is lower than a square meter this index is sub estimated. With other diversity indices commonly used in ecological evaluation it is indifferent to use density data or absolute numbers since these indices only consider relative proportions in their calculus.     

Disease activity and cognition in rheumatoid arthritis: an open label pilot study

Introduction

We hypothesised that fatigue in rheumatoid arthritis (RA) is related to TNF-alpha induced dysregulation of cerebral blood flow. Our objectives were to assess fatigue, cognitive function and cerebral blood flow before and after initiation of anti-TNF treatment.

Methods

In a pilot study, 15 patients initiating treatment with adalimumab were assessed for fatigue using a visual analogue scale (FACIT-F), cognitive function using a panel of psychometric tests and regional cerebral blood flow using MR perfusion imaging.

Results

Patients improved clinically after anti-TNF therapy in terms of DAS28 and FACIT-F. Furthermore significant improvements were documented in full scale, verbal and performance IQ following therapy. There was a non-significant trend towards reduced cerebral perfusion in both grey and white matter, and fatigue at 3 months correlated with cerebral blood flow in white (p = 0.014) and grey (p = 0.005) matter.

Conclusions

We demonstrate for the first time a significant improvement in cognitive function following effective treatment of RA. Although we observed minor reductions in cerebral blood flow, and a correlation between cerebral blood flow and fatigue, a larger, controlled study would be required to affirm a causal relationship.