Analysis of data collected from behavioral paradigms has provided important information for understanding the etiology and progression of diseases that involve neural regions mediating abnormal behavior. The trace eyeblink conditioning (EBC) paradigm is particularly suited to examine cerebro-cerebellar interactions since the paradigm requires the cerebellum, forebrain, and awareness of the stimulus contingencies. Impairments in acquiring EBC have been noted in several neuropsychiatric conditions, including schizophrenia, Alzheimer’s disease (AD), progressive supranuclear palsy, and post-traumatic stress disorder. Although several species have been used to examine EBC, the rabbit is unique in its tolerance for restraint, which facilitates imaging, its relatively large skull that facilitates chronic neuronal recordings, a genetic sequence for amyloid that is identical to humans which makes it a valuable model to study AD, and in contrast to rodents, it has a striatum that is differentiated into a caudate and a putamen that facilitates analysis of diseases involving the striatum. This review focuses on EBC during schizophrenia and AD since impairments in cerebro-cerebellar connections have been hypothesized to lead to a cognitive dysmetria. We also relate EBC to conditioned avoidance responses that are more often examined for effects of antipsychotic medications, and we propose that an analysis of novel object recognition (NOR) may add to our understanding of how the underlying neural circuitry has changed during disease states. We propose that the EBC and NOR paradigms will help to determine which therapeutics are effective for treating the cognitive aspects of schizophrenia and AD, and that neuroimaging may reveal biomarkers of the diseases and help to evaluate potential therapeutics. The rabbit, thus, provides an important translational system for studying neural mechanisms mediating maladaptive behaviors that underlie some psychiatric diseases, especially cognitive impairments associated with schizophrenia and AD, and object recognition provides a simple test of memory that can corroborate the results of EBC. Neuropsychiatric diseases are a significant worldwide health issue. Analysis of data collected from behavioral paradigms has provided important information for understanding the etiology, and progression of diseases that involve neural regions mediating abnormal behavior. Behavioral paradigms also provide systems for testing potential treatments and therapeutics. Eyeblink conditioning (EBC) is one such behavioral paradigm. This paradigm pairs a neutral conditioning stimulus (CS), e.g., a brief tone, flash of light, or vibration of whiskers with a mildly aversive stimulus to the eye or surrounding area in order to evoke a conditioned blink response. Subjects become conditioned after several pairings of the stimuli such that a blink is evoked in response to the CS and prior to the onset of the aversive unconditioned stimulus (US). Importantly, control experiments indicate that the learning is associative in nature, i.e., blinks do not tend to occur to the CS when it is presented in a random unpaired schedule with the US.Learning occurs most quickly when onset of the US is delayed from the onset of the CS by approximately 250 ms, and when the CS and US overlap and coterminate in time [longer interstimulus intervals (ISIs) are optimal for human subjects]. The 250 ms ISI is the shortest interval tested in the rabbit by Schneiderman and Gormezano . SeveralThe distinction between the neural requirements for the delay and trace versions of the EBC paradigm allows behavioral testing to dissociate forebrain-dependent cognitive effects from a more basic sensorimotor integration mediated by the brainstem/cerebellar/thalamic systems. Although EBC has been used most often to study neural mechanisms mediating learning and memory in healthy adults, the dissociation between forebrain and cerebellar/brainstem effects is useful in helping to characterize the effects of a disease state, and the effects of a potential treatment.in vivo recordings from single neurons and multiunit activity in different brain regions during the task , which is highly expressed in cerebellum, or mutations of the glutamate receptor mGluR1  or subunIn terms of AD, the insertion of genes related to AD have been shown to accelerate impairments in mice acquiring EBC , 53 and A circuit diagram of relevant brain regions involved in trace and delay EBC is shown in Figure The cerebellum is a necessary component for acquisition and expression of conditioned blink responses , 57. It Although most recording and lesion techniques are invasive and not appropriate to study in humans, functional magnetic resonance imaging can be done in both human and non-human animal subjects during and after learning –70. BlinOther neuropsychiatric diseases have also been examined with EBC, e.g., AD, PSP, PD, and PTSD. Briefly, AD significantly impairs acquisition relative to age-matched control subjects , acquisiSchizophrenia, a neuropsychiatric syndrome that includes symptoms of hallucinations, delusions, and extremely disordered thinking affects approximately 1% of the population. Behavioral abnormalities related to schizophrenia usually appear in the late teens and causes a life-long disability. Much evidence suggests that schizophrenia is a neuro-developmental disorder affecting connections between the cerebellum and PFC, which leads to a cognitive dysmetria , 71. MorSchizophrenia should affect both trace and delay conditioning since the cerebellum is required for both the delay and trace versions of the paradigm , even thWe have also used fMRI to measure the blood oxygen level-dependent (BOLD) response from the cerebellum in rabbits conditioned to evoke eyeblinks. We demonstrated learning-related decreases in the cerebellar cortex and learning-related increases in the deep cerebellar nuclei . We haveA receptors are upregulated. These deficits in the PFC could account for the disturbances in working memory , and is dependent on the proper functioning of the neurons and interneurons within the region. Abnormalities in GABAergic neurons have been proposed to contribute to the symptoms of schizophrenia. Changes in the inhibitory neurons of the PFC, especially of the dorsolateral PFC, have been reviewed by Lewis et al. . They prg memory , possiblg memory .Myelination defects in the cerebellar–prefrontal tracts are also thought to be involved in schizophrenia and have been hypothesized to lead to a functional disconnection between the two regions and a cognitive dysmetria . This diper se, or due to interactions with medications. Those types of studies have been done (with delay conditioning) since the review by Lubow  was one of the first neurotransmitters examined for effects on EBC. Given the involvement of the hippocampus in EBC , and theHaloperidol was the next major drug examined for effects on EBC. This antipsychotic medication blocks dopamine (D2), alpha 1, and 5-HT2 (serotonin) receptors, among others, and has been shown to impair the acquisition rate for EBC . The impThe effects of serotonergic receptors on cognition, psychoses, and EBC deserve further review. An analysis of their effects on EBC has been investigated by John Harvey . He and N-methyl-d-aspartate (NMDA) receptor is the major excitatory receptor in the brain and is altered during learning and memory to facilitate ionic flow through its channel. Antagonists of the NMDA receptor  are known to induce psychosis and have been found to impair EBC significantly in a dose-dependent manner in rabbits , the type of response that has classically been observed to evaluate the effectiveness of antipsychotic medications, i.e., suppression of the CAR . HoweverAs alluded to earlier, EBC works so well with rabbits because it requires minimal behavioral output from the rabbit, and rabbits do not express much spontaneous behavior that might otherwise interfere with the behavior of interest. In terms of being able to use the rabbit to examine the neurobiology of schizophrenia in more detail, additional behaviors would be beneficial, both to add support to the results from EBC and to compare the rabbit to other established behavioral tests that are done in rodents. The novel object recognition (NOR) test is a popular test for declarative memory in rodents, especially for tests of schizophrenic-like impairments , 98, 99.The NOR paradigm has been used in rabbits by Hoffmann , 101 andTrace EBC is uniquely suited to examine cerebro-cerebellar interactions since the paradigm has been shown to require both the cerebellum and the forebrain. The additional requirement for awareness of the stimulus contingencies when a stimulus-free trace interval separates the two stimuli during a trial gives the paradigm good face validity. Although the paradigm has been used most often to study neural mechanisms mediating learning and memory in healthy adults, the paradigm can be used to detect impairments in neuropsychiatric diseases, especially schizophrenia. The paradigm is also quite translational in nature and animal models of schizophrenia can be examined with EBC in several species to allow an analysis from genes to molecules to behavior. The paradigm is frequently used in rabbits, rats, mice, and humans, but the rabbit model is particularly appealing given its tolerance for restraint and the ease of using it without the need for anesthetics or sedatives during functional imaging experiments. An animal model of schizophrenia is particularly suited to answer two important questions: (1) what therapeutics are best for treating both the cognitive and psychotic aspects of schizophrenia and (2) can neuroimaging reveal biomarkers of the disease and a determination of appropriate therapeutics? Forebrain-dependent trace EBC in the rabbit is positioned to answer these questions, and the relatively new demonstration of NOR in the rabbit  providesThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Nanoscale particles are known to exhibit novel and unprecedented properties that make them quite different from their corresponding bulk-scale materials. The key differences are (i) an increased relative surface area and (ii) quantum size effects. Since the growth, catalytic activity and the various interactions with molecules (including biomolecules) occur at the surface of nanoparticles, a given mass of material in nanoparticle form will be much more reactive than the same mass of bulk material. As the properties of nanoscale materials become better understood and our ability to control these properties is further advanced, an enormous potential to create materials with novel properties and applications emerges. Nanoscience and nanotechnology are set to revolutionize many fields of science.Although the technological, economic and perhaps even societal benefits of nanomaterials are indisputable, concerns have also been raised that the very same properties that make them interesting might also have negative health effects. Unfortunately, these potentially negative effects cannot easily be predicted or derived from the known toxicity of the corresponding macroscopic material. Hence, major gaps in the knowledge necessary for assessing their risk to human health currently exist. There is also a lack of existing methodologies to improve techniques for nanoparticle characterization, the detection and localization of nanoparticles in biological systems, as well as the biological activity, fate and persistence of such systems. The complexity of this problem is amplified by the huge variety of nanoscale materials and objects as well as the enormous number of potential biomolecules and cells, thus creating a large parameter space to be examined.With these shortcomings in mind, we initiated a national Priority Program (Schwerpunktprogramm SPP1313) in Germany in 2007 at the Deutsche Forschungsgemeinschaft (DFG) entitled, “Biological Responses to Nanoscale Particles (Bio-Nano-Responses)”. In this research network, a fundamental understanding of interactions between nanoparticles and biological systems at the molecular and cellular level are to be investigated. The major objective has been to elucidate the physical, chemical and biological elementary processes by which manufactured nanoparticles enter a biological environment, interact with its components and interfere with its functions.In this program, the bio–nano response beginning at an exposure entry port such as the lung, the GI tract or the skin has been studied as a sequence of interactions, namely,the interactions with proteins and cellular constituents,the transfer across boundaries and biological membranes,the intercellular trafficking, andthe impact on important biological functions and cell constituents.It was agreed that proper synthesis, thorough purification and full characterization of nanoparticles using state-of-the-art technologies were paramount in order to assess their biological action. Moreover, the aim was to correlate detailed material properties with their biological effects in order to elucidate the biological response to the material challenge. The nanoparticles used in this study were those of current, wide-spread technological importance, such as metals , oxides , polymers  and quantum dots (II/VI semiconductors). Naturally occurring and industrially available nanoparticles have generally not been considered.The work of this project primarily addressed the behavior of purposely-designed, highly-engineered nanoparticles under conditions of non-intended, accidental exposure to biological environments. Although it is known  that the surface area seems to be one of the properties that causes a severe biological response, other properties such as solubility, hydrophobicity, surface functionalization, surface charge, colloidal stability and nanoparticle morphology have been suggested to be of equal relevance. Since it is these properties that are frequently modified in engineered nanoparticles to improve their applicability, the investigation of the interdependence of the bio–nano activity has been of primary importance. Therefore, questions concerning the mechanism of interaction at the molecular and subcellular levels (as well as their consequences for cell integrity and function) constituted the priorities for this research.In addition to “simple” nanoparticles, some groups in the SPP1313 have also focused on the synthesis of multifunctional particles, in which parameters such as fluorescence, surface conjugates of biomolecules, magnetism, radioactivity, Janus particles and core–shell particles were combined. In particular, the use of fluorescently labeled particles has become one of the preferred tools to track nanoparticles inside cells and tissue.When nanoparticles are exposed to biological fluids, their surface-active components  will adhere to the nanoparticles and form a so-called “protein corona”. As a result, biological systems never come into contact with bare nanoparticles, but rather with their protein-coated analogues. Since this discovery, a large variety of experimental techniques have been developed to unravel the chemical and molecular mechanistic details, as well as their biological consequences.Depending on whether a given cell spends energy during the uptake of nanoparticles or not, such uptake through the cell membrane is considered to be active or passive. While small molecules or nanoparticles can cross membranes with the mediation of specialized proteins, larger nanoparticles exhibit more complex entry mechanisms that are jointly described as endocytosis.The entry mechanism of nanoparticles into living cells and their subsequent trafficking within the cell and translocation between cells are important processes which affect not only nanotoxicology but also nano-biomedicine. In the SPP1313, several projects presented experimental strategies to study and dissect nanoparticle uptake. The employed approaches comprised not only technical advancements such as novel imaging techniques and particle tracking algorithms, but also generic molecular ways to interfere with uptake mechanisms by using si-RNAs and chemical inhibitors. However, a solid conclusion on whether or not nanoparticle-specific entry routes exist and/or which of the established routes are preferred as a function of shape, size, and most importantly, surface functionalization and protein corona, could thus far not be established.The SPP1313 research network resulted from an open national call after an intensive evaluation of proposals by an international group of experts. It operated for a total of 6 years with an intermediate reevaluation after 3 years. An important condition for participation was clustering. The approximately 40 projects in this network were requested to form cooperative and interdisciplinary clusters with 3–4 projects in each cluster, led by a cluster leader. In fact, the successful participation in SPP1313 was not only based on the evaluation of the individual projects but also on the prospective, added value expected from the formation of such clusters.The idea of clustering was born on the basis of the expectation that “horizontal” cooperation between chemists/material scientists on the one side and biologists/toxicologists on the other side would foster the cooperation and enhance its effectiveness. Hence, clustering largely prevented pure disciplinary work but rather promoted cooperative science. After six years of participation, it was clear that such a structural organization of the network was the key to its success. To date, a total of approximately 250 peer-reviewed papers have been published.This special issue in the Beilstein Journal of Nanotechnology reflects some of this work. This issue was motivated by the idea that a comprehensive overview over the science conducted in SPP1313 was the most appropriate way to make the results from this network known to a wider group of experts both in material science and the sciences of related biological effects. Because most of the original work from the individual research groups or clusters has already been published, this special issue mostly contains mini-reviews, which summarize the current and previous work of the contributing groups.The successful operation of a large research network requires the commitment of many people. As a coordinator of the SPP1313 network, I would like to express my sincere gratitude first of all to the Deutsche Forschungsgemeinschaft for funding this network and in particular to Dr. Torsten Hotopp for his favorable and encouraging administration. Additionally, I wish to thank members of the international evaluation board as well as the members of the Scientific Steering Committee of SPP1313, who provided substantial guidance and facilitation in coordinating this network. I would also like to acknowledge the substantial support I have received from the Rector of the University of Duisburg-Essen and the Dean of the Faculty of Chemistry during the course of this program. Finally, it is necessary to mention that without the enormous commitment of my resident colleagues, Dr. Oliver Locker-Grütjen and Dr. Michael Eisinger from ZWU, as well as of my secretaries, Iris Marissen and Natascha Seyock, the coordination of the program would not have been as effective and enjoyable. Lastly, it is my pleasure to acknowledge the excellent cooperation with the Beilstein editorial office for the preparation of this special issue.Reinhard ZellnerEssen, December 2014


Training interventions for older adults are designed to remediate performance on trained tasks and to generalize, or transfer, to untrained tasks. Evidence for transfer is typically based on the trained group showing greater improvement than controls on untrained tasks, or on a correlation between gains in training and in transfer tasks. However, this ignores potential correlational relationships between trained and untrained tasks that exist before training. By accounting for crossed (trained and untrained) and lagged (pre-training and post-training) and cross-lagged relationships between trained and untrained scores in structural equation models, the training-transfer gain relationship can be independently estimated. Transfer is confirmed if only the trained but not control participants' gain correlation is significant. Modeling data from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study (Smith et al.,  Longitudinal declines in many cognitive processes, including memory, attention, working memory, and speed of processing, are normative in aging  study , and remembering facts from stories. It was possible that the primary training measure of sound sweep discrimination might be differentially associated with outcome changes than another measure that had also been collected, syllable span. By assessing relationships of change in the two trained tasks in the IMPACT study, the issue of what changes are measured comes to the forefront. Most multimodal training studies do not include pre and post training measures of all aspects of the training, so it is difficult to determine what aspects of training gain are associated with transfer gains. In the present analysis, the transfer measures were not only different from the training tasks in terms of the specific materials used  but tested recall where only recognition had been trained, using subtests from widely used clinical neuropsychological tests. They involved episodic memory recall or reorganization of material in working memory. That is, transfer tasks were not closely related to training tasks. The training tasks also differed substantially in terms of overlap with transfer tasks.The training program was multimodal in that multiple processes involving rapid auditory discrimination were trained. For example, the training tasks included discriminating easily confused phonemes, remembering them in order, remembering their locations in a matrix, remembering and following increasingly complex sets of instructions to move objects in particular sequences  or active control (N = 245) conditions and given computers to use at home for the trial. Trained participants completed a series of six exercises focused on improving speed and accuracy of auditory memory. Exercises used computer-adaptive algorithms to maintain challenge. The specific exercises were:The IMPACT study had tested the efficacy of a commercially available computerized cognitive training program on the speeded auditory discrimination task and on untrained clinical neuropsychological measures of memory and attention  or downward (from high to more low pitched).Tell Us Apart: pairs of confusable syllables, such as bō and dō, are presented on the screen. One syllable was spoken and participants indicated which they heard.Match it: a matrix of buttons was presented on the screen. Clicking a button revealed a written syllable that was spoken aloud. There were two buttons with the identical syllables in the matrix. Participants found the matched pairs; as they identified them correctly, the buttons disappeared until all were gone.Sound Replay: Sequences of two, three, or more confusable syllables were presented auditorily. Participants listened to the syllables, then clicked buttons identifying the syllables in the order in which they were presented. There were more buttons on the screen than there were syllables, so the task involved recognition of the syllables as well as memory for their ordering.Listen and Do: A set of spoken instructions was presented. Participants saw a scene with various characters and structures on it, with instructions to click particular characters or structures or to move the characters. Participants followed the instructions in the order given.Story Teller: Participants listened to segments of stories and answered multiple-choice questions about them.Active controls watched educational television program series on their computers and answered questions about the content afterwards. Both groups completed their activities 1 h a day, 5 days a week for 8 week, totaling 40 h of exposure. Computers were removed from participants' homes after they completed their training. The top panel of Table Performance was evaluated at baseline before randomization, within 3 weeks of training completion, and 3 months later. The primary outcome was a composite index score of performance on the auditory tests of the Repeatable Battery for the Assessment of Neuropsychological Status  an age-sensitive and more difficult test than the RBANS Schmidt, , story mData from the pretest and immediate post-training assessments of the IMPACT study were analyzed. The published analyses included primary and secondary experimenter-determined outcome measures that had not been evaluated empirically for their psychometric characteristics. Initial analyses of all subtests administered were conducted to confirm the structure of the two outcomes of the IMPACT study as latent variables so that transfer to the common construct they represented rather than to specific test scores could be appropriately assessed . To identify the model that best characterized the structure of the data, exploratory maximum likelihood factor analyses , extracted 2, 3, 4, and 5 factors, with each indicator (test score) constrained to load only on one factor. A Promax rotation was used to allow factors to correlate, and no equality constraints were imposed on factor loadings. Each model was compared to an independence null model, in which covariances among all observed variables were constrained to zero. For this analysis, four fit indices to determine goodness of fit were used: RMSEA . Fit indices for the 5-factor model were acceptable, and this model produced the lowest BIC value out of all the models examined.Measurement models of the outcome variables were next assessed using R: lavaan, version 0.5–15) on both the 4- and 5-factor models was next conducted. Each indicator was constrained to load only on the factor it measured and factor covariances were freely estimated. All available data were included in the maximum likelihood estimation. Four fit indices were used to determine goodness of fit: RMSEA, SRMR, TLI, and CFI : configural, metric, scalar, and structural invariance. Configural invariance indicates that the variables load on the same factors across groups, but the value of the factor loadings may vary. Metric invariance indicates that the factor loadings are identical across groups. Scalar invariance indicates that the item intercepts are identical across groups, and structural invariance indicates that the factor means are identical across groups  but the structural model resulted in a smaller RMSEA of 0.06 compared to the 0.07 of all other models. The χ 2/df ratio for the structural model (1.96) also indicated the best fit relative to metric (2.06), scalar (2.06), and configural (2.26) models.Results from the invariance analyses of the 5-factor model across the experimental and control groups supported the strictest measurement invariance and structural invariance, as fit did not worsen with increasing stringency of invariance tests. The models did not vary in This indicated that any observed differences between experimental and control groups on the factors could be interpreted as representing differences in the same constructs. Table The five between-group invariant factors identified in the measurement model seen in Table speed and the recognition of sequences of confusable syllables, referred to as syllable span. Analyses were conducted separately for each training effect indicator and for each of the five outcome factor scores.Multigroup structural equation models were used to test the hypothesis that latent change in each trained task was associated with latent change in each untrained variable after controlling for crossed, lagged, and cross-lagged relationships between the trained and untrained scores assessed at pre and at posttest in the experimental but not in the active control group. The model is shown in Figure The modeling approach involved estimating the maximum likelihood parameters for the illustrated bivariate change score model and testing whether selected parameters differed between the experimental and control groups. Analyses were conducted separately for each of the five outcomes and the two trained indicators in an intent-to-treat design, so that all available data, including those of the dropouts, were included. For all models, it was assumed that random assignment to groups eliminated baseline differences in test scores so that baseline intercepts for the trained and untrained variables were set to be equal for both groups. Model 1 was set to be completely invariant over groups, with all parameters constrained to be equal. Model 2 freed the intercepts for the latent change of the training and the outcome indicators across groups with all other parameters constrained to be equal. This tested the hypothesis that training affected the means of the trained and untrained outcomes. Model 3 included the freed intercepts and the regression parameters of the crossed and lagged relationships between pretest and latent change of trained and untrained outcomes across groups. Model 4 additionally freed the variances of the latent changes for trained and untrained outcomes.Table 2 Log Likelihood (-2LL)/number of df test, which subtracts the value of -2LL and df from each successive model, with the Δ -2LL/Δdf tested using the χ 2 distribution to determine a significant improvement in fit from the prior model, with a significant Δχ 2/Δdf indicating improvement in fit. This, together with the smallest AIC, and smallest RMSEA, was used to select the best fitting model to characterize the trained and control groups.Table -2LL. The critical regression parameter for this study was the path from the latent change in the speed training measure to the latent change in each outcome.Results for sound sweep discrimination training are seen in Table Table Intercepts for latent changes on all of the outcomes (1→ ΔOutcome) differed significantly from zero for the experimental and control groups, suggesting that practice effects were observed in both groups. Pretest speed and pretest outcome performance were negatively associated with their respective latent changes , indicating greater change in those with lower baseline scores and possibly regression to the mean. This was the case for both the experimental and control groups. Crossed and lagged relationships between speed and outcome measures were significant, confirming the need to control for them in assessing training effects.Most critically, the test of transfer as the independent relationship between latent speed and latent outcome change was significant only for the experimental group on the RBANS List Memory factor score. Transfer was not observed in the RBANS Story Memory, RAVLT List Memory, RBMT Story Memory, or WMS Working Memory factor scores.Δ2LL/Δ df test was significant for Models 3 and 4, indicating no fit improvements beyond those of Model 2. However, AIC was smaller for Model 3 than for Model 2 for RAVLT List memory, RBMT Story Memory and WMS Working Memory, and smaller than for Model 4 for all of those outcomes. RMSEA was generally smaller for Model 3 than Model 2, but it was decided that Model 2 would be considered best fitting if it had the lowest AIC and an RMSEA 90% CI that did not differ from that of Model 3. Otherwise, Model 3 was selected as the best-fitting. Thus Model 2 was considered the best-fitting model for the two RBANS factor scores. Model 3 was considered best-fitting for RAVLT List Memory, RBMT Story Memory, and WMS Working memory.The next series of analyses evaluated model fit with syllable span as the training measure with results seen in the lower panel of Table The pretest standardized covariances, shown in Table The differences in parameters for the two RBANS factor scores in Model 2 suggested that the trained group only differed from the control group in the amount of improvement in the model intercepts but not the regression parameters. These did differ for the remaining outcome factor scores for which Model 3 was the best fit. The critical test of the relationship between latent change in the trained and in the untrained scores was significant for RAVLT List Memory, RBMT Story Memory, and WMS Working Memory for the experimental but not the control group, indicating evidence of transfer. In addition, the relationship between the two latent change variables was significant for syllable span and RBANS Story Memory but because the path was constrained to be equal for experimental and control groups in that model, it did not demonstrate transfer of training as defined in the analysis.The final set of analyses tested whether transfer was associated with individual differences. They included the covariates of age, sex, and education, all of which were associated with baseline training task performance. Bivariate change models tested the baseline and latent change trained and outcome variables regressed on the covariates, with covariate effects fixed across experimental and control groups, because of random assignment. The critical relationships of latent changes in training and outcomes were free to vary. Table For Speed, the pretest scores only were associated with the covariates. Being younger and male were associated with lower (faster) speed. Paradoxically, having more years of education was associated with slower performance. No correlations were observed for the latent change of speed. Age was negatively associated with syllable span at baseline, with worse performance, and more education was associated with higher scores. For latent change in syllable span, being older was associated with less gain and more highly educated with more gain. There were no sex differences in associations with baseline or latent change syllable span.The covariates, as expected, had significant relationships with the baseline outcome factor scores, as seen in Table Despite the relationships of covariates with the outcomes at pretest and for their latent changes, all of the significant latent change training-latent change outcome relationships observed in the main bivariate analyses for the experimental but not the control group remained significant after accounting for covariates. Transfer was therefore independent of the covariates.The goal of cognitive training of older adults is to support them in either maintaining or improving their functioning. Critical to this is the effectiveness of training in producing transfer. It has been suggested that multimodal cognitive training will produce transfer to multiple outcomes  was analyzed to compute the median Bayes Factor, which, for all reported outcomes, was 0.79, thus in favor of modest transfer effects.Suggestions have also been made that biases in interpretation of training effects exist because, in effect, competing hypotheses rather than the null hypothesis, are being evaluated. In the working memory training literature, the hypothesis that training transfers to abilities like intelligence assumes that the null is simply the absence of transfer. However, an alternative hypothesis is implied by the intelligence literature, which suggests that the abilities cannot be improved by training (see Tidwell et al., d = 0.32, equivalent to r = 0.16, associated with transfer in older adults (Hindin and Zelinski, r = 0.02 for the effect of aspirin and reduced risk of death by heart attack (Meyer et al., r = 0.11 or d = 0.23 in young adults (Hindin and Zelinski, Hindin and Zelinski  assessedTidwell et al.  suggest Concerns raised in the literature include the observation that training is adaptive whereas active control conditions generally are not, and this was true of the present study. Though this could bias findings because adaptive training promotes performance improvements to a greater extent than standardized training, and because there may be different levels of motivation and strategy use that may affect outcomes in experimental and control groups, the evidence for this potential source of spurious training and transfer effects is quite weak (see Redick et al., In the present study, there was a trained group and an active control condition with double blinding. A concern in clinical trials, even with double blinding, is whether the trained group gets more attention from study staff and whether there is an implicit message because of unchallenging sham material that control participants are not getting the experimental treatment, so that they experience less social interaction and expect less improvement, both of which dampen performance. In the present study, there were no differences in the amount of interaction with trainers for the two treatment groups. Participants had been told that after the study was completed, they would receive upon request copies of the training materials that produced better outcomes on the untrained tasks. Some of the control participants requested copies of the DVDs they had watched. This suggests that expectancies of cognitive benefits, which could affect performance, were present in some control participants (see Boot et al., The study was not informative regarding change in underlying processes compared to overlap in similarities in task characteristics. This could not be evaluated for three reasons. First, the neural basis of overlap was not tested. Second, the multimodal training design could not rule out complex sources of transfer. Third, the speeded auditory discrimination and syllable span tasks differed with respect to whether they were non-verbal or verbal, as well as on their measurement characteristics. Though the findings would suggest that syllable span was more effective for transfer to recall memory than time-ordered sound sweep discrimination, we note that training effects from the four other trained tasks in the program used in the IMPACT study could not be assessed. We also note that all training tasks involved adaptive speeded processing and difficult auditory discrimination training, and that with the extant design, the specific benefits to transfer within the training program could not be isolated.We note that what constitutes near and far transfer has not yet been objectively defined, and varies from study to study, so prediction of the amount of transfer that should be observed for a given outcome is difficult. In the present study, the most parsimonious explanation for performance improvements on untrained tasks in older adults is that of overlap in task demands, because training was multimodal. This is an important limitation. However, improvement in untrained tasks rather than broad abilities in older adults may have important implications for public health. The ACTIVE trial showed that training of reasoning and of speed was associated with reductions in risk of dependency 10 years after the study was initiated (Rebok et al., Other limitations to this study are those of the IMPACT study inclusion and exclusion criteria. This resulted in a convenience sample of very healthy participants, with high fluency in English, and low participation rates by members of ethnic minorities. Participants had committed to engage in the study for a minimum of 6 months. These characteristics suggest that the findings may not be generalizable to the population of older adults.The findings have positive implications for the cognitive training of older adults who are healthy and willing to engage in challenging and extensive multimodal training such as that provided in the IMPACT study. The current set of findings suggest that even when individual differences including age are incorporated into models that test transfer independent of other possible within-study influences, the relationship between latent changes in trained and untrained tasks generally remains significant.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Essential proteins/genes are indispensable to the survival or reproduction of an organism, and the deletion of such essential proteins will result in lethality or infertility. The identification of essential genes is very important not only for understanding the minimal requirements for survival of an organism, but also for finding human disease genes and new drug targets. Experimental methods for identifying essential genes are costly, time-consuming, and laborious. With the accumulation of sequenced genomes data and high-throughput experimental data, many computational methods for identifying essential proteins are proposed, which are useful complements to experimental methods. In this review, we show the state-of-the-art methods for identifying essential genes and proteins based on machine learning and network topological features, point out the progress and limitations of current methods, and discuss the challenges and directions for further research. Genome-wide gene deletion studies have shown that a small fraction of genes in a genome are indispensable to the survival or reproduction of an organism ]. These data have enabled researchers to explore the features of essential genes and proteins and, through this exploration, reveal which features are associated with essentiality and, finally, develop computational methods proposed to identify essential genes and proteins.In fact, computational approaches for the prediction of essential genes have already been developed and used for a long time. In 1996, Mushegian and Koonin were the first to develop a computational method to predict essential genes based on comparative genomics , functional annotation  and network topology  the computational methods used were those based on machine learning, a method in which computers make and improve predictions based on some data through learning algorithms (see next sections for details). On the other hand, of the 14 articles reporting the utilization of machine learning for the prediction of essential genes and proteins, 12 (86%) report the utilization of network topological features as learning attributes . Therefore, this brief analysis of these 34 papers suggests a strong link between machine learning and network topological features regarding the prediction of essential genes and proteins.Given the potential importance of this link, we sought in this review to go through the related works reporting the utilization of machine learning and network topological features for the prediction of essential genes and proteins and show the current developments, as well as pointing out the benefits, limitations, and further research directions. To this end, we firstly provide some fundamentals on machine learning, biological networks and network topological features and then present studies on prediction of essential genes and proteins using machine learning and network topological features from three different points of view: from the viewpoint of the biological networks and topological features, from the viewpoint of sources of training and testing data sets, i.e., training and testing in the same or different organisms, and from the viewpoint of machine learning algorithms.Machine learning algorithms build models from example inputs in order to make data-driven predictions or decisions. Machine learning tasks are typically classified into three broad categories: supervised learning, unsupervised learning and reinforcement learning, depending on the nature of the learning signal or feedback available to a learning system. Supervised learning aims to infer a function from labeled training data in which each example/instance is a pair consisting of an input object  and a desired output value. The inferred function can be used for mapping new examples. Depending on the outputs, machine learning tasks can be categorized into classification, clustering, regression, density estimation, and dimensionality reduction. For the task of identifying essential proteins/genes, supervised classification algorithms are often used.N training examples of the form {, …, } such that xi is the feature vector—set of learning features (or attributes) that are descriptive of the training example —of the ith example and yi is its label , a learning algorithm seeks a function g: X→Y, where X is the input space and Y is the output space. The function g is an element of hypothesis space of possible functions G. It is sometimes convenient to represent g using a scoring function f: X×Y→R such that g is defined as returning the y value that gives the highest score: g(x) = argmaxyf. Let F denote the space of scoring functions. Many learning algorithms are probabilistic models where g takes the form of a conditional probability model g(x) = P(y|x) , or f takes the form of a joint probability model f  = P .In supervised classification, given a set of There are many ways of measuring classification performance. Accuracy, confusion matrix, log-loss, area under the receiver operating characteristic (ROC) curve (AUC), and precision-recall are all popular metrics. Accuracy simply measures how often the prediction model makes the correct prediction. It is the ratio between the number of correct predictions and the total number of predictions. Although accuracy is simple to calculate, it is unable to make distinction between classes. If the cost of classification for each class is different, or if the test data are imbalanced between classes, we might want to look at how many examples failed for one class vs. another class. In this case accuracy is not enough. A confusion matrix or confusion table shows a more detailed breakdown of correct and incorrect classifications for each class. The rows of the matrix correspond to ground truth labels, and the columns represent the prediction.A variation of accuracy is the average per-class accuracy, the average of the accuracy for each class. Accuracy is an example of a micro-average, and average per-class accuracy is a macro-average. Log-loss or logarithmic loss can be used if the raw output of the prediction model is a numeric probability. The probability essentially serves as a gauge of confidence. AUC is the area under the ROC curve and shows the sensitivity of the prediction model for plotting the rate of true positives to the rate of false positives. In pattern recognition and information retrieval with binary classification, precision is the fraction of retrieved instances that are relevant, while recall  is the fraction of relevant instances that are retrieved. Precision and recall are often not discussed in isolation, instead either values for one measure are compared for a fixed level at the other measure , or both are combined into a single measure, e.g., F-measure.Various machine learning algorithms have been used for identifying essential genes and proteins. The most commonly used algorithms are support vector machine (SVM) and ensemble learning-based methods Table . In the Gp(P) = , where Vp = {pi|pi ∈ P} is vertex set that represent biological entities , and Ep = {|for pi, pj ∈ P and i≠j} is edge set that present their interactions. Let N denote the number of nodes in the network and matrix A its adjacency matrix whose element Au, v is 1 if there is an edge between node u and node v, and 0 otherwise.A biological network can be represented as weighted or unweighted nondirected or directed graph There are various types of biological networks, such as protein-protein interaction (PPI) networks (PINs), transcriptional regulatory networks (TRNs), gene co-expression networks (GCNs), metabolic networks (MNs) and integrated networks  in a network in relation to all other elements. While there exist many different types of network topological features  that is defined as the total number of edges incident upon a node in the unweighted network Figure , or the s Figure . Local cGenerally, the development of predictive models in a machine learning approach is accomplished by the following steps: selection of learning attributes , construction of the training and testing data sets , selection of learning algorithms, design of the machine learning approach and evaluation of the predictive performance of models. We structured this section according to these steps: first we discuss the studies from the perspective of the learning attributes , then we discuss the studies from the perspective of the construction of training and testing data sets (in the same or different organisms) and finally we discuss the studies from the perspective of machine learning algorithms and approaches. The discussions are based on the papers shown in Table As previously mentioned in the Section “Biological Networks and Network Topological Features”, PINs are the most frequently utilized network among all other different types of biological networks from which topological features used as learning attributes are calculated. As shown in Table We hypothesized that there are two main reasons for which PINs have been the most used biological network for the prediction of essential proteins. The first reason is the pioneering study by Jeong et al.  showing A cellular network, however, is not composed only of PPIs. Instead, other interactions are intertwined with PPIs, i.e., metabolic and transcriptional regulatory interactions. Although PINs may provide a global view of cellular signaling, essential genes and proteins are also involved in metabolic processes and direct regulation of gene transcription, that is, essential genes can be present only in non-PINs (MNs or TRNs). Hence, by using only PPIs, researchers are unable to predict essential genes in MNs or TRNs. However, in some cases  or the enzymes p1 and p2 share metabolites. Moreover, other authors  counts the total number of closed walks in which a given protein/gene takes part in the network and gives more weights to closed walks of short lengths. Closed walks are related to the network subgraph, thus SC accounts for the number of subgraphs in which a protein/gene participates, giving more weights to smaller subgraphs. Eigenvector centrality (EC) is also a pure network topological features that measures the influence of a node in a network. It assigns relative scores to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connection to low-scoring nodes. EC is defined as the principal eigenvector of the adjacency matrix A defining the network  to network topological features improves the prediction of essential genes and proteins. As an example, we cite the studies by Hwang et al.  and AcenThus, it seems that only network topological features are not enough to distinguish essential from non-essential genes and proteins. This raises the following question: is the positive correlation between essentiality and network topological features only an artifact of a possible bias  present in the networks mainly derived from small scale experiments? If so, this could explain the moderate predictability of essentiality by network topological features. While Coulomb et al.  showed tPrediction methods for essential genes and proteins often use supervised classification methods to build a model based on a variety of features related to gene and protein essentiality. Usually, most of the known essential and nonessential genes and proteins in an organism are used as training data, and some genes and proteins are left out as testing data. Cross-validation has often been used to evaluate the model. In this type of method, prediction models can only be constructed based on those organisms that most of their essential genes and proteins are experimentally determined.However, to predict essential genes and proteins across related organisms, especially distantly related organisms, would be more useful since it can enable us to quickly find out the essential genes and proteins for unstudied organisms. Until now, only relatively few researches have been used machine learning to predict essential genes and proteins across related organisms in comparison with those using machine learning to predict essential genes and proteins within an organism. And often, homology mapping has been used to predict essential genes in newly sequenced organisms taking in consideration known essential genes and proteins  can be distinguished by certain learning features, ensemble learning algorithms—combination of multiple learning algorithms—are also powerful learning algorithms but, in their case, the prediction power is related to the improvement of the prediction performance in comparison to individual algorithms. Many studies have showed that by using ensemble algorithms is possible to obtain better predictive performance than could be obtained from any of the constituent individual learning algorithms (Leblanc and Tibshirane, Still regarding comparison among machine learning algorithms, it would be also interesting to discuss the comparison of the prediction performances among individual learning algorithms applied to the same training and testing set. This is useful since each type of machine learning algorithm is adapted to a certain type of data Mena,  and, theFinally, it is important to discuss the impact of the correlation among the network topological features on the prediction performance of models created by training of the machine learning algorithms. Some network topological features have shown to be highly correlated, such as DC and BC, for example (Valente et al., in silico. The accumulation of various omics data for a large number of organisms and the collections of essential genes for some model organisms have enabled researchers to explore the characteristics of essential genes and the factors that make essential genes different from nonessential genes. Many computational methods have been proposed to predict essential genes, and at the same time, many features have been found to be related with gene essentiality. In this review, we showed some recent progress in predicting essential genes by using machine learning and network topological features. In the following, we will discuss some main challenges in this research field.The importance of identifying essential genes and the limitations of experimental methods has stimulated researchers to predict essential genes S. cerevisiae and E. coli, due to the relatively more complete interactome data for these organisms. It may be more useful to construct reliable interacting networks for more organisms by using the currently proposed methods of predicting protein-protein interactions (for a review on this subject, please see Rao et al., Most studies using network topological features using machine learning have focused on very few model organisms, for example, S. cerevisiae and E. coli; however, small proteins in E. coli tend to be essential while small proteins tend to be nonessential in S. cerevisiae. Investigating the relationship between the variation of correlation level and predictive power for gene essentiality of features and the evolution direction of organisms should be more useful and interesting. Prediction methods are expected to be more powerful if they consider such relationship. At the same time, few studies have been performed to investigate whether network features also show similar variation across different organisms. If not, network features would be superior to those derived from sequence data for building useful models to predict essential genes and proteins across distantly related organisms.In addition, while many features have been found to be associated with gene essentiality, both correlation level and predictive power may vary in different organisms. For example, protein length is correlated with gene essentiality in both The currently proposed machine learning-based prediction methods often utilize supervised learning. In supervised learning, the training and testing data are assumed to be drawn from the same distribution. So it is suitable for them to be used for the task of training and testing in the same organisms. However, predicting essential genes across related organisms are more interesting and practical. As the correlation between features and essentiality and the prediction power of these features for discriminating essential from non-essential genes and proteins vary in different organisms, the training data and the testing data are likely to have different distributions for the task of predicting essential genes across organisms. The difference in general increases with the evolutionary distance of the training and testing organisms (Cheng et al., To conclude, despite the great progress that has been made in the machine learning-based prediction of essential genes using network topological features since the publication of the pioneering study in the field (Chen and Xu, XZ, MLA, and NL drafted, revised, and finalized the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Diet-related noncommunicable diseases represent a major global public health challenge, and require a multisectoral policy response. However, the use of trade policy in this context has met with varied success in the face of strong global trade liberalization agendas. The Government of Ghana has implemented an innovative food standards policy to limit the amount of fat in meat and meat cuts, in response to rising imports of low quality fatty meat cuts. This paper presents an analysis of the policy process and outcomes, as well as contextual factors in policy development, to enable policy learning in other jurisdictions.We conducted 28 semi-structured policy analysis interviews with 37 stakeholders at the national and regional level in Ghana, and collated relevant documents. We analysed the data using the health policy analysis triangle and policy theories related to lesson drawing.The standards were developed in response to health concerns related to fatty meat (particularly turkey tails), in a context of rising meat imports and a generalised concern about the low quality and high fat content of imported meats. The standards were the result of collaboration between the trade and health sectors. The standards apply to both imported and domestic meat, and were designed to be compliant with Ghana’s multilateral trade commitments. The overall effect of the ban has been to reduce availability of specific ‘low quality’ high-fat meats in the Ghanaian food supply, namely turkey tails and chicken feet.This study indicates that the use of standards can reduce availability of high-fat meat in a national food supply. The main strength of a standards approach to reducing fatty meat (mainly imported) in the food supply is compliance with global trade law, while the main challenge is effective enforcement. However, the Government of Ghana appears to have developed a functional and flexible application of the policy. Features of this policy approach useful for policy learning include: collaboration at every stage between ministries of trade and health; considerations relating to compliance with international trade law; strategic enforcement of the policy; and the importance of public awareness efforts. Diet-related noncommunicable diseases (NCDs) represent a major global public health challenge . Even inAs part of this multisectoral approach, international institutions, non-government agencies and academics have recommended trade policies designed to improve the healthfulness of the food supply and prevent NCDs -7. TradePolicies in the Pacific banning imported fatty meat products have met with varied success in the face of strong global trade liberalization agendas . RequireGhana implemented an innovative food standards policy to limit the amount of fat in beef, mutton, pork and poultry in response to rising imports of low quality meat with liberalization of trade in the early 1990s. This appears to be the only policy of its kind globally, but the development, implementation and effect of this policy has not yet been assessed. This paper presents an analysis of the policy process and outcomes of this innovative trade policy intervention to improve diets. It also identifies contextual factors in policy development, to enable policy learning in other jurisdictions.process , context, content and actors  for the policy, as well as the policy outcomes, guided by research questions based on the policy process :We used case study research and policy analysis methodologies to evaluate the policy, which enabled in-depth assessment of the policy process and outcomes in Ghana, while maximising usefulness of the case study for policy learning in other contexts ,15,16. W– What was the nature of the policy intervention? (content)– Why was it proposed? – How did it get onto the political agenda? – Who is responsible for implementing the policy, and how has it been implemented? – What was the outcome of the policy initiative?We drew on both qualitative and quantitative sources to answer these questions, including interviews , trade data , food availability and production data , information on trade policy change  and information on food supply policies . We also triangulated interview data through analysis of documents relevant to the case study policy, identified through interviews, internet searches, and hard-copy searches of major newspapers for the year 1999 . These iWe identified stakeholders for interview by sending letters of invitation to the heads of the key policy and implementing agencies with relevance to the fatty meat restriction, as well as to the CEOs of several leading meat importers and agricultural producers. All government agencies contacted agreed to allow a representative(s) to participate, as did the majority of companies contacted. Further relevant stakeholders within Government agencies were also identified via snowball sampling during interviews, but interviewees did not indicate that we should contact further agencies.We conducted 28 semi-structured interviews with 37 stakeholders in Accra and Kumasi in August 2013 , from the following groups: Policy makers in Trade (4), Health (4) and Agriculture (4); Implementers in Ghana Standards Authority (2), Ghana Food and Drugs Authority (2), Animal Extension (1) and Customs Excise and Preventive Service (2); and Agricultural producers, Traders and importers (8). As outlined above, we asked specifically about the process and outcome of the restrictions on fatty meat, and also asked broad contextual questions regarding the historical trade policy context, changes in food prices and agricultural production, and the perceived effect of food imports on agricultural production. We used iterative analysis throughout the interviewing to identify and pursue themes based on the research framework. Detailed notes from all interviews were recorded by two interviewers. Within one day of all interviews, they were transcribed and sent to the interviewee for checking and amendment.We present our analysis using the health policy analysis triangle. The themes identified were also informed by policy theories related to lesson drawing, in order to inform the capacity for policy learning in other contexts -21. ThesThis study was approved by the Committee on Human Research, Publications and Ethics, Kwame Nkrumah University of Science and Technology, School of Medical Sciences and Komfo Anokye Teaching Hospital, Kumasi, Ghana.The percentages for fat content of pork, beef, mutton and poultry meat and meat cuts are found in standards that have been published by the Ghana Standards Authority  These specify that carcasses and cuts of pork and beef shall contain no more than 25% fat, poultry no more than 15% fat and lamb no more than 30% fat  that these standards regarding fat content also appeared in the first edition of the standards, which are no longer available (due to being superseded by the second edition). The original standards were implemented in the early 1990s. There is a discrepancy between the percentages of fat given in the GSA documents, and those in the 2001 and 2008 WTO Trade Policy Reviews, which cite the figures as 25% for beef, 42% for pork, 35% for mutton, and 15% for poultry ,27. For The key contextual factors that appear to have influenced the development of the standards were health concerns related to fatty meat, rising meat imports, and the status of Ghana as a member state of the General Agreement on Tariffs and Trade .NCDs began to rise in Ghana during the 1980s. By 1991 cardiovascular disease was the leading cause of death, and the diabetes prevalence in urban areas was 2–3% . Ghana iPer capita meat availability in Ghana has increased from around 11 kg in 1990 to 14 kg in 2009 ) that lThe standards were developed by the GSA, then the Ghana Standards Board. Interviewees reported that the standards were the result of collaboration between the Ministries of Trade, Health and Agriculture, and that the Ministry of Trade issued the directive for their development (GSA is an implementing agency of the Ministry of Trade). The technical committees that developed the standards included representatives from GSA, FDA, Ministries of Health, Trade and Agriculture, the Council for Scientific and Industrial Research, universities, and other agricultural research institutes.Percentages of fat given in the standards were based on the association of high-fat meat consumption with NCDs, particularly cardiovascular disease, and the cut-offs for what constitutes 'high-fat' were derived from analysis of the fat content of local and imported meats. Interviewees reported that they represent a ‘reasonable’ expectation of the amount of fat in meat and meat cuts. The standards apply to both imported and domestic meat, and are thus non-discriminatory. Interviewees from the Ministry of Trade reported that membership of the GATT/WTO influenced the choice of a non-discriminatory and evidence based standard for reducing fatty meat imports.The implementation and enforcement of the standards are currently the responsibility of the Ghana Food and Drugs Authority , which was established in 1992. Meat is on the ‘high risk imports’ list, which means that the GSA takes a sample of any meat entering the country for testing in relation to a wide number of different quality standards. The focus of this testing is on quality from a micro-biological perspective. However, the implementing officers also consider standards compliance more broadly. The GSA notifies the FDA where there is a need for enforcement. The FDA also conducts spot checks locally, at cold stores (mainly frozen imported meat) and butchers . All local meat sold must be killed in an abattoir, and these are also subject to inspection. Prior to importation, meat traders must have FDA approval of their facilities and obtain a permit from Veterinary Services (Ministry of Agriculture). However, the application for the permit does not require a declaration of the percentage of fat in the intended import.All importers interviewed were aware of the restrictions on meat imports related to fat. One industry interviewee related how, when applying for a loan for his importing business, he was told that importing turkey tails was not allowed. The butchers that we interviewed were not aware of the standards, but reported that consumers requested that the fat be trimmed from the meat before weighing and purchase. There was no public awareness campaign to accompany the ban.The initial focus of the ban was on turkey tails, but in the late 1990s medical specialists noticed a high availability of chicken feet in Ghana, which they were concerned about because of the lack of bioavailable protein and presence of high amounts of fat in this ‘cut’. They lobbied the Ministry of Trade to use the standard to restrict their import. In response, the Ministry of Trade issued a press release in September 1999 stating that chicken feet were not permitted to be imported under the standard. This press release also contained a reminder to importers of the restrictions on fat in meat, and stated that these standards would be enforced . While tImports of turkey tails rose again in the late 2000s, generating public commentary regarding the low quality of the meat and the need for enforcement in 2009–2010 and again in 2012 ,39. In rAlmost all interviewees reported that it is still possible to obtain turkey tails in the market, generally imported over the land border with Togo, but that the amount available was very low compared to what it was before the standards were implemented.A notable aspect of the actors involved was the interplay between health and trade at all stages: agenda setting, development, implementation, and enforcement all involved collaboration between the Ministries of Health and Trade and their agencies (FDA and GSA at latter phases).There was, however, a dearth of actors at the international level. Two interviewees reported that the USA had suggested removal of the standard, and one additional interviewee attributed this to the World Bank, but there was no evidence of contest through formal channels (a search of the WTO and GATT notifications and complaints). Similarly, there was no mention of international agencies influencing the agenda setting process, other than the contextual effect of WTO membership in informing the choice of a non-discriminatory and justifiable tool.The overall effect of the ban has been to reduce availability of specific ‘low quality’ high-fat meats in the Ghanaian food supply, namely turkey tails and chicken feet. Detailed data for chicken imports from the USA (the main source of chicken imports until the mid-2000s) show that unspecified turkey cuts other than wings and legs (i.e. likely to be turkey tails) declined in the early 1990s with the initiation of the food standards Figure . They suOverall poultry import data from the US show that the major import is now chicken leg quarters Figure . AccordiInterviewees from both the Department of Agriculture and from industry reported that the standards have had little effect on local agriculture. Meat production in Ghana has increased steadily  but suppNutritionists reported that the food environment in Ghana remains less than ideal. While there is much less turkey tail available, other sources of saturated fat include fried pork (‘domedo’) and chicken, instant noodles and sausages. Soft drinks are also heavily advertised. Diet-related NCDs continue to increase, but at the same time maternal and child undernutrition remains an issue.This study indicates that the use of standards can reduce fatty meat availability in a national food supply. In Ghana, standards have been used to substantially reduce imports of turkey tails and chicken feet; products that have also been identified as a health concern in other countries. The main strength of a standards approach to reducing fatty meat (mainly imported) in the food supply is that it is generally compliant with global trade law and much more likely than product-specific bans to be justifiable in this context. In an era of liberalized trade, global, regional and bilateral trade agreements affect all countries, and food supply-focused NCD prevention interventions must be consistent with these agreements to limit the potential for contest in these forums.First, the standards do not discriminate between imports and domestically produced meats, and apply to the main types of meat available . They are thus compliant with the core trade liberalization principle of ‘non-discrimination’, which prevents countries from discriminating between goods on the basis of their country of origin, or between ‘like’ products . This isFinally, the standards are likely to be justifiable from a technical perspective because the maximum fat percentages were based on public health concerns and applied uniformly to cuts of meat containing high levels of fats. However, a difficulty in this respect arises from the lack of an international standard regarding high-fat meats in the context of diet-related NCD prevention, as both the SPS and TBT Agreements recommend that measures be based on relevant international standards . It is aThis distinction has implications regarding the requirements for justifying the measure under international trade law from a technical perspective. The Agreement on TBT (Article 2) requires that measures be non-discriminatory and not more trade restrictive than necessary . In relaOur findings indicate that the main challenge in using a standards-based approach to reducing fatty meat in the food supply is effective enforcement. The maximum-fat standards in Ghana are currently not incorporated into pre-import checks, and enforcement has focussed on two specific meat cuts. This may reflect a concern that has been raised about the use of such standards in low and middle income countries: the expense of full enforcement . However, in Ghana, the application of the standards only to cuts of meat identified as exceeding the stated percentage of fat seems to be functionally effective while maintaining low enforcement costs. This method of application still allows for adaptation to changes in food environment (e.g. using the standard to stop imports of chicken feet after they began to be imported in the mid-1990s), which makes it preferable to product-specific bans. In addition, the lack of industry complaint about the standards might be due to a possibility that such complaints could lead to broader application or more rigorous testing of imports.It is not clear what the overall effect of the standards have been in improving diets and preventing NCDs. Ghana continues to battle a dual burden of under- and over- nutrition, and it is likely that low quality fatty meats contribute to both aspects due to their low protein content and high fat content. In a 2013 consumption survey (n = 60) conducted in Kumasi, Ghana , 85% participants reported avoiding fatty meat, stating that it leads to disease, and only 5% reported consuming turkey tails. Although only 15% saw the standards as reducing consumption of fatty meat, the majority (52%) had a positive outlook of the long-term effect of the restriction and supported the policy as a means to improve health and prevent disease.Our analysis suggests two ways to strengthen the implementation and enforcement of the standards. First, Ghana could require importation report from country of origin to state fat content. Currently this is not an enforceable requirement, although in 2011 the USDA issued a new requirement for exporters to Ghana that required the labelling of poultry exports with the percentage of fat . Second,This case study offers four key opportunities for policy learning for other countries facing a rising burden of diet-related NCDs and considering the inclusion of food-supply-oriented policy approaches as part of a package of interventions . First, the successful initiation, development and implementation of the policy required collaboration at every stage between Ministries of trade and health. Second, it is important to carefully consider and justify the policy instrument used in relation to applicable international trade law. In this case, the policy appears justifiable, but further consideration could be given to public health evidence and calculation of the requirements, keeping in mind the requirements that technical measures and standards be non-discriminatory and not more trade restrictive than necessary. Third, enforcement of the policy was enabled at a low cost by the targeting of specific commonly consumed non-compliant products. Fourth, the fluctuations in imports suggest that public awareness efforts can be an important corollary to such a policy, reflecting findings in the Pacific . RegularNCDs: Non-communicable diseases; ECOWAS: Economic Community Of West African States; EU: European Union; FAO: United Nations Food and Agriculture Organization; USA: United States of America; WTO: World Trade Organization.The authors declare that they have no competing interests.AMT & RA developed the study concept and protocol, and all authors were involved in data collection and analysis. AMT drafted the paper, and all authors reviewed and approved the final version.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/14/249/prepub


Throughout the past century NBS/NIST supported a great variety of research studies in crystallography where the aim was the highest attainable accuracy in measurements. While avoiding overlap with other papers in this volume, this article summarizes results from: 1) early work on crystallization as a method of purification, in contributions to sugar chemistry, and in solution growth of large crystals; 2) the NBS/ARPA Program of research on crystal growth and characterization; 3) the NBS Free-Radical Research Program; 4) the XRCD method as a direct path to relative atomic mass data and the fundamental physical constants; 5) the dynamical theory of x-ray diffraction; and 6) symmetry considerations such as are involved in the influence on crystals of mechanical stress or fields, and of point defect motion. During the latter half of the 19th century, the study of matter in the nearly perfect molecular disorder of the gaseous state led to the kinetic theory and thermodynamic concepts that prominently shaped progress in chemistry and physics into the next century. Since its inauguration, the National Bureau of Standards (NBS) contributed to that progress by its careful critical measurements at the highest attainable sensitivity, as is well documented in Refs. .In the 20th century, the study of the nearly perfect molecular order of the solid state and its interactions with photons—that is the study of crystallography—has prominently shaped spectacular further progress in physics and chemistry. Crystallography today is at the center of all materials science and engineering, including solid-state physics, geology, metallurgy, ceramics, biophysics, and biochemistry. Thus crystallography has become a prominent key to a widening scientific understanding of our material universe, and even the life within it. NBS, now renamed the National Institute of Standards and Technology, has again contributed by its predilection to careful experimentation and critical measurements at the highest attainable sensitivity. In choosing my illustrative examples of NBS/NIST achievements in crystallography, I have avoided overlap with contributions otherwise covered in either this Special Issue or in Refs.  and [2],The theory of atomic scale order in crystals had long been established based on morphological and optical studies. This order could not be directly observed in the 19th century. Besides, many solids do not exhibit long- range order; they are not crystalline, but amorphous. Many crystals were long known to shatter at characteristic temperatures when cooled below their melting points. Melt growth, especially of metal crystals, had been extensively studied. Vapor growth had been observed, such as in ice crystals, since the Renaissance. Solution growth of crystals had been most widely studied, variabilities of their solubilities carefully measured, and the growth of macroscopic crystals had been demonstrated for many substances.The resistance to being crystallized, particularly of certain sugars, was known when the problem of reliable cane sugar assay was brought to the NBS in the face of controversy between suppliers, refiners, and distributors. The Federal Government was involved by virtue of its import duties on sugar. Frederick Bates and his colleagues  transforIt had also long been known in science and exploited by the manufacturing industry that many substances can be successfully purified from contamination by crystallization from melt and from solution. Chemists knew how to exploit the phase rule, a widely applicable development from the study of gases. They also observed that large crystals tend to be purer than small crystals of the same substance because the latter have larger ratios of surface area to crystal volume. Impurities are preferentially held at crystal grain boundaries. The selectivity of the growing crystal for incorporating molecules of only a specific type and chirality in sugars was found at NBS to depend not only on crystal phase, but also on crystal habit and temperature , 5.11Before the implications of dislocations had been widely understood, Charles Saylor at NBS stood out among our colleagues with a deep understanding of the processes of purification by crystallization. In Ref.  he refinJohn Torgesen, supported by his technician, Avery Horton, was widely regarded at NBS as the most successful experimenter in crystal growth. His work is exemplified by his large ammonium dihydrogen phosphate crystals and their habit modifications by ion additions, as well as by his purification of “ultrapure” reagent-grade benzene by melt recrystallization. He has left few direct traces of his influence in the literature except for two items, one on crystallography in chemical research , and anoSo numerous were the NBS contributions to such investigations that, in 1962, C. F. Yost of the Advanced Research Projects Agency (ARPA) of the U.S. Department of Defense agreed with I. C. Schoonover of NBS to fund jointly a 3 year program of unclassified research at NBS on crystal growth and characterization. At that time it had become clear that progress in science and technology often depended on breaking down barriers to cooperation between specialists in different disciplines or organizational divisions. Thus, Schoonover was anxious to experiment with “matrix management” across lines of organizational responsibilities without loss of the established NBS management structure. ARPA agreed to give the NBS program manager complete freedom of choice of tasks; while Schoonover gave instructions for many innovative tasks to be so supported, each with very little “seed” money. An important selection criterion was that each task had to be strongly supported also within the division from which it was proposed. In the event, in excess of a hundred separate tasks were so funded from 11—that is most—NBS research divisions. It is clearly impossible to describe here the individual summaries given in Refs. . By a gld-electrons . They investigated the band structure of reduced strontium titanate (0.1 % to 0.01 % oxygen deficiency). It is cubic (perovskite structure) down to liquid helium temperatures. From knowledge of the density of states [From among the many ARPA studies, let me first single out research by Hans Frederikse’s group on semiconductors based on f states  and calcf states , they wePhysical properties of crystals can be measured for characterizing the chemical and physical perfection of crystals. Among these properties the most important has probably been that of density. Its impact is described in Ref.   could be trapped in solid matrices at the melting point of helium . With eaA series of papers with Jack Watchman, such as , had theTheoretical work on point defects and dislocations has produced an enormous literature to which NBS/NIST has contributed significantly. Justice is not done to that by here citing just two examples. Using a relaxation mode analysis, A. D. Franklin investigated the step-wise diffusion of atoms or ions into crystals  and rece


In Japan, there is a unique clinical department, “Psychosomatic Medicine”, while there is not a department of behavioral science or behavioral medicine in medical schools. Although only eight medical schools have the department, psychosomatic physicians in the department have been involved with behavioral medicine. In the present manuscript, the author would like to introduce the contribution to behavioral medicine made by psychosomatic physicians in three aspects, education, clinical settings, and research, and propose some strategy for psychosomatic physicians to get more involved with behavioral medicine. In Japan, there is not a department of behavioral science or behavioral medicine in medical schools. Instead, there is a unique clinical department, The Department of Psychosomatic Medicine. However, only eight medical schools have the department.Medical doctors in the department are basically internists who treat patients with stress-related diseases. They can use both pharmacology and psychotherapy, which means that they are familiar with behavior modification.Therefore, psychosomatic medicine in Japan is very closely associated with behavioral medicine. In fact, all of the board members of the clinical section of the Japanese Society of Behavioral Medicine are psychosomatic physicians, and medical doctors in the department (psychosomatic physicians) also play an important role in the medical education for behavioral medicine in the eight medical schools. I would like to introduce three aspects in behavioral medicine that are closely associated with psychosomatic physicians in Japan.First, I would like to introduce the current status of education for behavioral medicine in medical schools by departments of psychosomatic medicine . In JapaIn addition, they are involved with clinical clerkship for the 5th-year medical students for one week or two weeks. In some medical schools, half of the students experience the department of psychosomatic medicine during their clinical clerkship, while all of the students experience the department of psychosomatic medicine in the other medical schools. Psychosomatic physicians in the eight medical schools also teach the 5th-year or 6th-year medical students for their elective clinical clerkship for four weeks.Table Some departments of psychosomatic medicine in the eight medical schools also hold an open seminar for medical students, young doctors, clinical psychologists, and nurses. The seminars also include many themes in behavioral medicine.In Japan, department of psychosomatic medicine was originally established in order to see patients with “psychosomatic diseases”. “Psychosomatic diseases” are defined by the Japanese Society of Psychosomatic Medicine as physical diseases that are closely influenced by psychosocial factors in terms of their onset/course and that are not merely physical symptoms caused by psychiatric disorders . The JapIn addition, behavioral medicine is included in the curriculum for becoming Board Certified Psychosomatic Internists. Psychosomatic physicians in Japan are required to be able to apply non-pharmacological intervention such as psychotherapies and behavioral modification as well as pharmacological intervention. Cognitive behavioral therapy, transactional analysis, and autogenic training are considered the three essential psychotherapies for psychosomatic physicians in Japan . TherefoMany studies in behavioral medicine have been conducted by psychosomatic physicians in Japan. For example, I and my colleagues have been involved in research using the ecological momentary assessment (EMA) method, which was originally developed by Stone and Shiffman in behavioral medicine. We first demonstrated that traditional assessment of headache intensity based on patient recall was not reliable using EMA . Then, wPsychosomatic physicians in Japan have been involved with and contributed to the field of behavioral medicine. However, these activities have not been acknowledged by medical doctors in other areas and general people. Therefore, psychosomatic physicians should interact with doctors in other areas and get involved with publicity activities for spreading the role of psychosomatic physicians in behavioral medicine.