Enhancing the use of evidence in policymaking is critical to addressing the global burden of nutrition-related disease. Whilst the public health nutrition community has embraced evidence-informed policymaking, their approach of defining relevant evidence and evaluating policy has not brought about major shifts in policymaking. This article uses a public health nutrition case study to refine a novel theory-informed framework for enhancing the use of evidence in government public health nutrition policymaking. Our aim is to contribute insights from evidence-informed policy to the emerging paradigm in public health nutrition policymaking.An enquiry framework informed by three groups of theories underpinning evidence-informed policy was used to explore the role of socially mediated processes on the use of evidence. A public health nutrition case study on food marketing to New Zealand children was conducted to refine the framework. Interview data collected from 54 individuals representing four key policy stakeholder groups, policymakers, academics, and food industry and non-government organisations were analysed using deductive and inductive thematic analysis. To enhance theoretical robustness, an alternative hypothesis of political explanations for evidence use was explored alongside the enquiry framework.We found the prevailing political climate influenced the impact of advocacy for evidence inclusive processes at the meta-policy and policymaking process levels and in policy community relationships. Low levels of awareness of the impact of these processes on evidence use and uncoordinated advocacy resulted in the perpetuation of ad hoc policymaking. These findings informed refinements to the enquiry framework.Our study highlights the role advocates can play in shifting government public health nutrition policymaking systems towards enhanced use of evidence. Our Advocacy for Evidence Use framework argues for a three-channel approach to advocacy for using evidence in the public interest. The framework provides a means for building a constituency for evidence use in public health nutrition and adds understanding about advocacy to the field of evidence-informed policy. Future research should examine the impact of coordinated advocacy on public health nutrition policymaking systems.The online version of this article (doi:10.1186/s12961-016-0154-8) contains supplementary material, which is available to authorized users. Lancet series on obesity argues for ‘new thinking’ by addressing issues at both the individual and environmental level and pursuing policy-based approaches to changing the food environment [Dietary risk factors are now the leading contributors to the global burden of disease . In partironment –10. Howeironment . We defiGovernment policymakers are confronted with a number of challenges in protecting and promoting public health nutrition (PHN). The problems for which they need to formulate policy are often complex, substantial and contested. Although evidence-informed policymaking is promoted as the ideal, it rarely takes place as a rational and linear process. Instead, advocacy has a significant influence on how and why the decision making process plays out , 13. HerAdvocacy by influential policy actors with the aim of increasing evidence use has not been systematically examined beyond three lines of enquiry: Nutley et al.’s  applicatThe Role of Advocates for Using Evidence framework argues that advocates are able to shift (1) meta-policy arrangements, (2) PHN policy community relationships, and (3) policymaking processes to enhance the use of evidence . These tMeta-policy, the highly influential written and unwritten rules about policymaking, effectively determine the use of evidence in policy processes. These ‘rules’ govern who is included and excluded, time frames for decision making and the extent and status of external input , 24. DraThis component proposes that sustained relationships between broadly based members of a policy community enable effective advocacy for evidence use. Here, the role of skilled individuals is to unite networks across PHN policy communities and across policy issues by diffusing the novel ‘idea’ that enduring relationships are critical for effective advocacy. Advocacy is for policy processes that promote the public interest through consideration of broadly based evidence.Building on Flitcroft’s argument that deliberative policymaking processes have the potential to reframe policy dilemmas and resolve policy controversies, this component proposes that the role of advocates is to pursue inclusive structures and systematic processes . Their gThis study sought to produce a robust explanatory framework through a real world policy case study. A deductive approach was used to refine an existing conceptual framework developed from a synthesis of literature relevant to evidence-informed policy. Policy case study interview data explored PHN policy actors’ views on the ability of the framework to explain advocacy for using evidence. Concurrently, a grounded theory approach was used to explore emerging explanatory themes. A rival hypothesis, political explanations for evidence use, was explored using the same approach. Food marketing to New Zealand children was chosen as an exemplary single case study. This policy area provided rich case study data as a well-established evidence base existed, a range of identifiable policy actors were involved, there was controversial meta-policy and the New Zealand Government had a clear policy position, see Additional file In-depth conversational interviews explored the role of advocates for using evidence in PHN policy on food marketing to children. Members of the New Zealand PHN policy community with an interest in food marketing to children were relatively easily identifiable by the snowballing method. The first interviewees were identified through having a senior position in an organisation affected by food marketing to children policy and by being known for having or being able to influence policy processes. Individuals without organisational affiliations or with no profile on food marketing to children policy were excluded. Over 9 consecutive weeks (July–August 2012), 54 in-depth conversational interviews, lasting 30–40 minutes, were conducted either by telephone or face-to-face. Four distinct groups emerged within this policy community: policymakers, the political and bureaucratic decision-makers; policy active academics, the sources of scientific evidence; PHN non-governmental organisation (NGO) groups, the organised civil society groups with interests in policy and evidence; and the food industry, the companies and coalitions with a high stakes involvement in policy processes. All interviewees were asked open-ended questions on their experiences of advocacy for evidence use. Questions were structured around the three components of the enquiry framework and how politics influenced the use of evidence. Additional file The interview sample comprised 16 policymakers, 13 middle to senior level food industry employees, 13 managers in non-government organisations, and 12 research-active academics interested in policy. As far as possible, interviews were conducted in blocks by category group. Interviews were transcribed within a short time frame of the interview using voice recognition software.Respondents were assigned a group identifier to identify congruent and divergent views by group: policymakers, academics, NGOs, and food industry. Group membership appeared stable at the time of the interviews, with no interviewee purporting to be a member of more than one group. To ensure anonymity, interviewees were assigned a unique code and number, e.g. PM 1, was an individual policymaker.Thematic analysis was performed on the fully transcribed interview data using the four category themes generated by the enquiry framework: meta-policy, sustained relationships, deliberative processes and the alternative explanation, political influences. Initial coding allocated comments as supporting or disagreeing with the enquiry framework components or the alternative explanation, or as a potential emerging theme. There were iterative rounds of data review to confirm the allocation of text comments to a code. Subthemes developed based on frequency of coded responses and were merged following a critical review of code allocation and examination of common conceptual links. Major category theme and subtheme descriptions were then refined. PF undertook the initial coding. This was checked by RG and ML.The results are organised around the role of advocates in the three components of the enquiry framework: meta-policy, sustained relationships and deliberative policy processes. The role of politics is also explored as an alternative explanation. Whilst food marketing to children was the entry point for the interviews, it was apparent early in each interview that issues in the wider PHN policy environment explained the current situation on food marketing to children. Consequently, data was obtained on both food marketing to children and broader PHN issues.In New Zealand, institutions inside and outside government have a government mandate to develop and implement nutrition-related policy. The key institutions are two government departments, the Ministry of Health (MoH) and the Ministry for Primary Industries, MoH Public-Private Partnerships (PPPs) with a major NGO and with the Food Industry, and the non-regulated industry-led Advertising Standards Authority.…because at the time the ministry had a vast number of advisory committees for just about any everything, it was questionable how much value they added.” Policymaker 6“In government-funded organisations, formal meta-policy structures and processes exerted a major influence on the impact of any advocacy for using evidence. For the MoH, the dis-establishment in 2009 of their Nutrition Advisory Committee represented a significant structural barrier to further evidence-informed policy development. Many aspects of PHN policy advocacy were affected by the removal of this key committee known for rigorous consideration of scientific evidence. The Nutrition Advisory Committee was not alone, as the centre right Government in their first term of office (elected in 2008) disbanded a number of expert advisory committees. A senior policymaker observed:The same Minister’s (2008–2014) well-known hands-on approach and aversion to discussing public health issues became a barrier to advocacy for creating alternative structures for providing evidence-informed policy advice. Formal channels for science-based evidence-informed policy advice were further compromised by an internal restructuring of government departments, where technical nutrition experts were replaced by politically pliable non-specialist policy analysts.These meta-policy changes, while not impacting on the type of evidence most groups were advocating, did impact on channels used by academics and smaller NGOs. The food industry and larger NGOs continued to use their own well-oiled direct advocacy channels. With the loss of their only structural channel for scientific evidence to reach policymakers, smaller NGOs and academics increased their use of ad hoc informal processes. Larger NGOs continued proactive advocacy directly to policymakers for their more broadly based scientific and contextual evidence to be considered. Similarly, the food industry continued to use direct advocacy, although with an increased emphasis on scientific evidence alongside their market-based data.Members of the food industry were also proactive with informal advocacy to shift meta-policy towards arrangements where industry had a larger role in policy development. Most academics and smaller NGOs were more reactive responding to issues as they arose, with little if any awareness of the influence of meta-policy. As newer collaborative meta-policy arrangements, PPPs were increasingly common across government and bureaucrats believed they had political support to develop partnerships with the food industry. However, the only NGO working in a MoH-funded PPP perceived a power imbalance that compromised their independence.The role of civil society groups as the ‘voice of evidence’ in formal and informal policy discussions emerged as an important issue for NGO and academic interviewees. In the prevailing political climate, civil society voices were seen as having more influence than scientific experts, particularly when a constituency was built for public health action. Some NGOs deliberately engaged in ‘sideways advocacy’ by packaging scientific evidence to enable community group voices to speak the evidence.As informal policy processes dominated nutrition policymaking, most social interactions across the policy community were based on informal relationships. Despite only a few formal committees facilitating relationships between sectors, informal mutually beneficial relationships flourished. The relationship patterns captured below Fig.  portray Advocacy for formal ongoing relationships between major groups in the policy community was distinctly limited. Formal relationships existed only where structures enabled relationships between individuals from different sectors. Only the two major nutrition NGOs had academics as long-standing members of advisory committees. These relationships were considered to have high levels of mutuality. One business industry NGO also maintained a number of advisory groups with a broad membership, and a notable absence of academics.Senior health bureaucrats reported enjoying long-standing, informal relationships with senior academics where either party would telephone the other for advice or an alternative perspective on an issue. These relationships often began as formal relationships and became sustained by mutuality arising from trust, respect and exchange of information. Most Members of Parliament (MPs) also had their own informal relationships with trusted academics. However, these relationships were short lived compared to bureaucrats’ relationships. More politically attuned NGOs also initiated and maintained relationships with elected MPs and senior bureaucrats.Who is public health, is it the Public Health Association, or is it some key academics, who is it?… Industry is easier because there are key bodies.” Policymaker 3“For the food industry, initiating and maintaining informal relationships with politicians and bureaucrats was a priority activity. Food industry members frequently coordinated their engagement with government through representative groups, including a powerful coalition, the Food Industry Group, established in 2003. In comparison, nutrition NGOs could not sustain coordinated advocacy. Competition between academics based on University affiliations combined with the disjointed NGO sector created difficulties for bureaucrats seeking external public health input on policy issues. A senior bureaucrat commented:Deliberative policymaking processes were virtually non-existent, as most policy processes used selected evidence in selected ways. For many bureaucrats, political interference and the lack of systematic internal processes for reviewing public health evidence meant they were only involved in advising on the efficacy of implementation options and had no opportunity to advocate for alternative processes.They would take all the science they could get, they know we have the science at our fingertips and will ask for it, not just science but evidence in general, sales figures.” Food industry member 4“Several major food companies initiated a type of deliberative policy process in providing scientific and other evidence directly to policymakers, believing this added credibility to industry submissions and interactions with MPs. One food industry representative understood their material provided bureaucrats with evidence that was not available from other sources:NGOs, on the other hand, provided scientific evidence to government through formal structures, committees and consultation rounds. Experienced advocates in all groups were keenly aware that their scientific evidence-based advocacy had minimal impact compared to other policy inputs.As most NGOs were dependent on government funding they pursued a politically pragmatic and conservative approach to PHN advocacy. Senior NGO interviewees attributed the high level of political involvement in PHN policy processes to New Zealand’s Mixed Member Proportional electoral system. A succession of coalition governments with small majorities over the last decade had forced MPs to be responsive to their electorates and party ideology. A NGO representative believed this political fragility enhanced the influence of civil society groups.Advocacy by some policy active academics was hindered by fear of being ‘labelled’ by politicians and bureaucrats when their views differed from Government ideology. These academics believed politicians and senior bureaucrats’ perceptions of their personal political views determined whether their advice was sought. Some expressed concern around the impact of being labelled on future competitive government research funding applications.A complex relationship between evidence and policymaking was evident in this investigation of advocates’ role in three channels that influence evidence use in PHN policymaking. Much of this complexity arose from interdependencies between the channels working to facilitate or hinder the use of evidence.Gibson’s argument for the role meta-policy plays in evidence use highlights the need for evidence use advocates to be aware of meta-policy . Our resA major consequence of low profile meta-policy is an absence of transparency. When industry groups advocate for a change in meta-policy arrangements this is seen by groups with public health values as an exercise of asymmetrical power by another group with conflicting values. In the field of evidence-informed policy, the principle of transparency is frequently applied to high quality, accessible evidence and policy processes yet rarely to meta-policy guiding how evidence is used –29. ThisIn relation to the second channel, that of sustained relationships, the findings extend the work of Flitcroft et al. , Hanney Along with transient formal structures, the pattern of long-standing networks across the policy community can help explain uncoordinated and conflicting advocacy activities. In the case study, food industry groups exhibited Sabatier’s characteristics of advocacy coalitions . Groups In contrast, NGO and academic groups failed to coordinate their activities. These groups functioned as small clusters of tightly linked individuals, more typical of social networks who do not have collective policy goals . OrganisSabatier argues that beliefs at all levels influence how coalition members respond to new information . Our anaInterestingly, although most members of outside government advisory committees fulfil Rogers’ criteria for opinion leaders they did not attempt to influence wider policymaking systems . This inIn examining deliberative processes, the third channel, two government actions undermined policymakers’ ability to systematically use broadly based evidence. Disestablishing the Nutrition Advisory Committee and side-lining MoH technical nutrition experts prepared the ground for more politically driven policymaking processes. The resulting reduction in structural capacity for addressing complex issues through on-going conversations between evidence producers and users helps explain the rise in ad hoc policy development .Compared to Lomas’ model for deliberative policymaking where skilled, transparent synthesis of evidence includes stakeholders’ values, informal politically driven processes appeared to permit only highly selected evidence to inform policy development . In the .Furthermore, without formal government-led policymaking structures and processes or rules for engagement, food industry groups have a rationale for building relationships with senior bureaucrats and politicians. As policymakers’ source of readily accessible ‘scientific advice’, industry representatives exert considerable influence over policy processes. Although the food industry meet Lomas’ criteria of a stakeholder affected by the outcome of a policy decision, their role in collaborative processes is not explicitly addressed in the deliberative processes literature . This hiDiverse explanations exist for the political influences on what, how, when and where evidence is used in policy processes. These range from the exercise of structural power and the influence of policymaking systems through to changing models of governance. The political nature of PHN policymaking has been attributed to competition between the values, beliefs and power bases of diverse stakeholders , 36, 37.In framing obesity as an individual issue, structurally powerful industry groups aligned their position with prevailing political ideology. Jenkin et al.  argues tIn addition, three policy systems level factors offer further political explanations for the role of advocates in influencing the use of evidence. Firstly, although New Zealand civil society groups are politically influential, their low profile on PHN issues prevented community groups from being a voice for evidence. Secondly, the lack of coordinated advocacy between NGO and academic members of the PHN community is partly attributable to internal politics. While this situation may arise from local conditions, Gibson observes similar patterns across the health sector. As health evidence is complex, rational evaluations are only possible when values are considered concurrently . As PHN Emerging shifts in PHN governance add another layer of complexity to the systematic and transparent use of evidence. New governance arrangements in New Zealand and Australia are similar to those in other sovereign states –43. RyanExplanations for the food industry’s high level of political influence often highlight the considerable resources devoted to a range of relationship management activities –47. LewiAs a heuristic device, the enquiry framework is subject to fallibility. Theoretical understanding of how framework components influenced each other over time was difficult to assess empirically. Whilst compelling data emerged on the political influence over PHN issues, collecting interview data over a relatively short time period created difficulty for developing a nuanced understanding of how politics influences the impact of advocacy for evidence use over time and across policy issues. A key limitation when collecting case study data was interviewees’ perceptions of evidence use. As divisions within the policy community centred on the evidence base for policy priorities, a number of interviewees struggled to separate the idea of advocacy for evidence use per se, from advocacy for consideration of their evidence.Insights from the case study produced three revisions to our ‘Role of Advocates for Using Evidence framework’  incorporPolitical theory can explain the influence of structurally powerful groups as coalitions of interests seeking common goals. Our study suggests that another political mechanism, advocacy, is a justifiable means for bringing about enhanced evidence use in policymaking. As all groups in the policy community held deep-level beliefs about the usefulness of evidence, a new frame for policymaking appears tenable. In this frame, the powerful exert their influence to change meta-policy towards structures and systems where the use of broadly based evidence is prioritised over other policy considerations. This proposition offers direction for the new approaches to PHN policymaking urged by Lang and Rayner , SwinburNew governance models where meta-policy establishes and maintains government-led structures and processes that enable broadly based evidence to be considered. As PHN policy issues are inextricably linked with food industry activities, the relationship between values and evidence requires meta-policy rules that promote explicit and transparent processes. The exertion of asymmetrical power is avoided when policy processes recognise the value base of all contributors.Deliberative policy processes that acknowledge the value of broadly based, systematically synthesised evidence. Individuals skilled in leading iterative processes will facilitate new collaborative approaches to developing understanding of and solutions to ‘wicked’ policy problems. This advocacy will address the role of government in ensuring skilled staff undertake evidence syntheses, which incorporate the values and interests of all contributors.Establishment and maintenance of relationships across the policy community as the basis for effective advocacy. Opinion leaders persuaded of the benefits of on-going trusting relationships in advocacy for evidence use have the potential to assume a key role in facilitating relationships across the policy community. Their goal is to establish structures that enable relationships to exist over time and across issues. In addition, these leaders will be cognisant of the need for advocacy to be based on shared high and medium level beliefs.The AEU framework proposes policy structure and process change become advocacy goals for the PHN policy community. Opinion leaders across the PHN community have the capacity to use their social influence skills to persuade members of their networks and the government of the benefits of deliberative, transparent use of evidence. For the ‘idea’ of using evidence to become embedded in the hearts and minds of policy communities, opinion leaders themselves may first need to be persuaded of its value. Many of these influential individuals will reframe their evidence use advocacy from calls for government to develop policies directly informed by their evidence, to advocate for policy about policymaking in the broader public interest. The AEU framework Fig.  proposesThe AEU framework Fig.  illustraThis research responded to growing pressure to better understand the PHN evidence–policymaking interface and strengthen PHN policymaking processes. Three channels were identified where advocacy will shift policymaking towards enhanced use of evidence: meta-policy, sustained relationships and deliberative policymaking processes. The principal theoretical contribution is adding understanding of the role of a politically mediated social interaction mechanism to conceptual models of evidence-informed policy. The AEU framework proposes that targeted advocacy for evidence use will build footbridges between decision makers and those who generate evidence. For policymakers and the PHN policy community the framework provides a theory-informed rationale for advocating for deliberate connections between science, society and politics. However, it also implies a central role for government in establishing evidence use promoting structures and systems. Another less obvious implication is the need for robust transparent systems for dialogue between all PHN actors where the influence of values is acknowledged. Finally, the framework provides the PHN policy community with urgently needed insights on the value of building advocacy constituencies for evidence use.


Cancer research continues to highlight the extensive genetic diversity that exists both between and within tumors. This intrinsic heterogeneity poses one of the central challenges to predicting patient clinical outcome and the personalization of treatments. Despite progress in some individual tumor types, it is not yet possible to prospectively, accurately classify patients by expected survival. One hypothesis proposed to explain this is that the prognostic classifiers developed to date are insufficiently sensitive and specific; however it is also possible that patients are not equally easy to classify by any given biomarker. We demonstrate in a cohort of 45 AJCC stage III melanoma patients that clinico-pathologic biomarkers can identify those patients that are most likely to be misclassified by a molecular biomarker. The process of modelling the classifiability of patients was then replicated in a cohort of 49 stage II breast cancer patients and 53 stage III colon cancer patients. A multi-step procedure incorporating this information not only improved classification accuracy but also indicated the specific clinical attributes that had made classification problematic in each cohort. These findings show that, even when cohorts are of moderate size, including features that explain the patient-specific performance of a prognostic biomarker in a classification framework can improve the modelling and estimation of survival. The biological complexity of most disease states limits the performance of prognostic biomarkers –3. ThereHerein we propose one such model capable of retrospectively identifying clinical and pathological features that identify and explain which patients are more likely to be successfully separated according to a good and poor prognosis by gene expression data. By including this identification step in a classification procedure we then show that we can substantially improve the accuracy of predicting prognosis in three cancer datasets; 45 AJCC stage III melanoma patients , 49 stagWe previously observed that there were subsets of AJCC stage III metastatic melanoma patients whose prognosis, death within a year of resection or survival for more than four years after resection, was more easily predicted than others for a variety of biomarkers . This inGiven that the gene expression and clinical data might be detecting different prognostic signals for different patients, two standard methods for integrating gene expression and clinical data were applied to the melanoma data and two additional cohorts in separate cancers: breast  and coloWe then took a different approach, hypothesizing that there would be clinical variables associated with the classification accuracy of the gene expression biomarker. Extranodal spread was identified as the most informative clinical variable for accurate classification of melanoma patient outcome by the biomarker constructed with gene expression data. Figure We therefore propose a new multi-step classification framework that includes modelling of gene expression biomarker performance, and which markedly improved estimation of prognosis in three different cancer types Figure . First, We further analyzed why classification performance in each of the three cancer cohorts could be improved by the multi-step approach. Specifically, we aimed to investigate whether there may simply be multiple signals in the data with one signal overpowering the others. Figure We have shown that by conceptualizing error rates as a measure of classifiablilty, we can identify clinical determinants of this classifiability and then leverage these determinants to construct superior classification models. Importantly, none of the key clinical determinants could have been selected a priori as most likely to confound classification. That is, pre-determining potential confounding variables before an experiment without sufficient evidence and using these to subset a cohort might have unnecessarily reduced power or further confounded the analysis , 11, 12.Our results imply that resources should be invested into both the measurement of gene expression and the collation of detailed clinical information to improve the accuracy of prognostic estimates for cancer patients. Both the clinical and gene expression data contain useful prognostic information, however, these two classes of information have different relevance to different patients. The pivotal message from Figure Interestingly, standard methods for integrating gene expression and clinical data did not perform competitively on these datasets. This was surprising since, in the melanoma cohort, both the gene expression and clinical data classified different patients correctly suggesting that integrating the two would be superior. Nonetheless, the question remains: why did the two integrative approaches not provide more substantial improvements to classification performance in these three datasets? To begin with, since PV is simply a linear combination of the clinical variables and a biomarker built from the gene expression, it might not be capable of capturing the inherent complexity of the data. In contrast, RF is a non-linear classification method built using decision trees making it capable of describing complex models, but despite its use of resampling methods it may still be over-fitting to the data .To conclude, we have demonstrated that by identifying clinical variables that confound gene expression biomarker performance in individual patients we were able to improve the prediction of patient clinical outcome in three cancer cohorts. The value in this finding is that it is not always clear which sources of heterogeneity might be confounding a discriminatory signal within a dataset, and this is especially true in complex diseases such as cancers. Our multi-step procedure identified the clinical variables that were most likely to obscure a potentially useful gene expression signal of interest. It therefore has strong potential to help build models of outcome that have greater translational relevance, including aiding clinicians in determining the most appropriate schedule for clinical follow up of cancer patients, through substantial improvements to their accuracy. There is also potential value in the cost-effectiveness of this approach, which begins by leveraging the clinic-pathologic information that is immediately available to the clinician in order to enhance the value of molecular biomarkers that are measured with more difficulty and at higher cost.BRAF and NRAS mutation status, as described in [Melanoma_GoodPrognosis=22), and patients who died of melanoma within 12 months of resection (nMelanoma_PoorPrognosis =23). We considered the following 11 clinico-pathologic variables in our analysis: patient age (at banking), patient sex, size of nodal metastatic tumor (mm), extranodal spread (present vs. absent), number of metastatic nodes, primary melanoma cell shape , percentage of necrosis and degree of pigmentation. BRAF and NRAS mutation status were identified via the Sequenom OncoCarta v1.0, MelaCarta v1.0 platform followed by MassARRAY25 mass spectroscopy, as previously described [We used the previously reported global mRNA expression profiles from 45 AJCC stage III metastatic melanomas (deposited in GEO Accession Number: GSE54467), and linked detailed clinico-pathologic data, including We used previously reported global mRNA expression profiles of human breast cancer samples together with clinical history   Feature selection, selecting the genes to include in a model, was performed by selecting the one thousand genes with largest fold change; 2) Using the class information, a diagonalized linear discriminant analysis (DLDA)  was traiClassifiers using the clinical data were built using logistic regression in conjunction with step-wise AIC variable selection. While logistic regression was chosen here for illustration, in further application of our multi-step framework any classifier can be used instead. Step-wise AIC was chosen as it is the default model selection choice for many logistic regression packages. Other choices are possible such as using step-wise methods with other information criteria . HoweverWe used a pre-validation approach  to integIntegration of gene expression and clinical information to predict patient clinical outcome was also performed using a random forest  classifiClassification error rates for individual patients were calculated by performing LOOCV of a classification scheme on the gene expression data. In general, such errors could alternatively be calculated using bootstrap, k-fold cross-validation or repeated k-fold cross-validation. Logistic regression was then used, treating the prediction errors as a response and using the clinical variables as explanatory variables. The clinical variable with smallest AIC was selected to divide the patients into two cohorts; those patients who could be classified with the gene expression data (referred to herein as ‘easy-to-classify’) and those who could not (‘hard-to-classify).If a clinical variable was identified as having the potential to explain the heterogeneity in the gene expression data there may me some question as to whether the samples within any of its levels contained signal on a given platform. To test if this was the case, the samples were divided by the levels of the clinical variable . Within these splits, a leave-2-out cross-validated classification scheme was independently performed.http://www.ellispatrick.com/classifiabilitycode.First, the clinical variables were used to predict which samples the gene expression data could and could not classify in the LOOCV. Using this prediction, the samples were divided into ‘easy-to-classify’ and ‘hard-to-classify’ subsets. A new classifier was built on the gene expression data for the patients in the former group while the clinical variables were used to construct a classifier for patients in the latter . This approach was implemented at the level of individual patients wherein for each case the clinical variable was first used to predict whether the gene expression data would be informative and then, depending on the result (hard or easy), the appropriate downstream classifier was then subsequently applied to predict an individual's prognosis class. This process is further illustrated in Figure


In this brief review, we identify key areas of research that inform a systematic and targeted approach for invasive brain stimulation with the goal of modulating higher cognitive functions such as memory. We outline several specific challenges that must be successfully navigated in order to achieve this goal. Specifically, using direct brain stimulation to support memory requires demonstrating that (1) there are reliable neural patterns corresponding to different events and memory states, (2) stimulation can be used to induce these target activity patterns, and (3) inducing such patterns modulates memory in the expected directions. Invasive stimulation studies typically have not taken into account intrinsic brain states and dynamics, nor have they a priori targeted specific neural patterns that have previously been identified as playing an important role in memory. Moreover, the effects of stimulation on neural activity are poorly understood and are sensitive to multiple factors including the specific stimulation parameters, the processing state of the brain at the time of stimulation, and neuroanatomy of the stimulated region. As a result, several studies have reported conflicting results regarding the use of direct stimulation for memory modulation. Here, we review the latest findings relevant to these issues and discuss how we can gain better control over the effects of direct brain stimulation for modulating human memory and cognition. Major advances have been made recently in the use of intracortical brain-computer interfaces (iBCI) to restore movements in patients with disorders such as tetraplegia  Are there reliable neural patterns corresponding to different events and memory states? (2) Can these neural activity patterns be induced in the brain via stimulation? (3) Does inducing these patterns using stimulation causally modulate memory in the expected directions?Studies using different modalities of brain imaging and electrophysiology have shown that individual items/events can be represented differently at multiple scales ranging from distributed patterns across the whole brain to highly localized spiking activity patterns and that the corresponding neural representations are reinstated when successfully remembering those items  neurons for a period of a month as mice performed a virtual-navigation task revealed that the correspondence between individual cells' activity and task features were stable over timescales of a day but underwent major reorganization across days and weeks  at 10 Hz increases parieto-occipital alpha activity and in turn modulates target detection performance in a visual oddball task (Helfrich et al., Other mechanisms like synchronization of activity in different brain regions may also have important roles in modulating cognitive performance. For example, theta synchronization between the MTL and frontal regions relates to successful memory formation (Fell et al., average controllability, capturing the ability to steer the system into different states with little effort, was greatest in default mode network hubs; modal controllability, identifying the ability to drive the system into difficult-to-reach states, was greatest in canonical cognitive-control networks such as the frontoparietal and cingulo-opercular systems; and boundary controllability, capturing the ability to integrate information across different cognitive processes, was distributed across systems but particularly in the ventral and dorsal attention systems. Utilizing such tools to select nodes in order to achieve specific control strategies may be beneficial in designing targeted stimulation studies.Finally, network control theory can be used to determine if particular nodes or sets of nodes in a brain network can be manipulated in order to drive the system into specific sequences of activity states that may be relevant for cognition. Gu et al.  employedpost-hoc analyses may help determine whether random stimulation leading to improvement in memory was accompanied by neural activity previously identified as playing an important role in successful memory processes.Here, we briefly review recent invasive stimulation studies of memory, most of which did not a priori target precise neural activity patterns. Therefore, it is difficult to make causal inferences about previously identified neural processes that accompany successful memory encoding and retrieval in the absence of stimulation. However, existing stimulation studies may provide relevant information regarding other factors such as the time of stimulation, brain state, and how these factors influence stimulation effects. Furthermore, Demonstrating the influence of time of stimulation at a coarse scale, Merkow et al.  found thInvasive brain stimulation studies have reported both positive and negative effects on memory in humans. For example, Suthana et al.  reportedLogothetis et al.  used simFurthermore, invasive brain stimulation is highly localized relative to non-invasive methods, and given the heterogeneity of neural responses at small scales, it is imperative that we understand more precisely the relationship between stimulation parameters and the response elicited from a small piece of neural tissue (e.g., Winawer and Parvizi, In this review, we identified several factors that potentially influence the effects of brain stimulation on cognition. As Braun et al.  recentlyVS drafted the manuscript. JW, TS, and KZ provided critical comments and edits.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.


Recently, Lodhi SA and colleagues have reported on a patient with choroidal neovascular membrane (CNVM) associated with tubercular granuloma, who responded to intravitreal bevacizumab injections. The available literature regarding CNVM associated with intraocular tuberculosis is briefly discussed. Choroidal neovascular membrane is a possible complication of choroidal tuberculosis and the patients should be informed about this risk. However, patients usually respond well to intravitreal anti-vascular endothelial growth factor agents as evidenced by the case reported by us and the current case reported by Lodhi et al. Dear Editor,I read with interest the report on choroidal neovascular membrane (CNVM)  in intraThe article emphasizes the paradigm that any disease which disturbs the retinal pigment epithelium and Bruch’s membrane can lead to a CNVM. The increased vascular endothelial growth factor (VEGF) levels and hypoxia within the choroidal tubercular granuloma have been reported which may play a role in CNVM formation in such cases . HoweverWe had reported the case of a 36-year-old female  with subIn indexed peer-reviewed literature, probably the earliest case of CNVM in IOTB had been reported by Chung YM and colleagues  in 1989.Thus, all patients with choroidal tuberculosis should be explained about the risk of CNVM and should be kept on follow-up. However, such patients usually respond favorably , 4] to  to 4] toThe histopathological report of the hysterectomy specimen may be relevant in this case, and it would be interesting to know the result of the same if it was available.Choroidal tuberculosis is usually bilateral in disseminated tuberculosis . Though The author declares that he has no competing interests.


Many learned behaviors are directed by complex sets of highly specific stimuli or cues. The neural mechanisms mediating learned associations in these behaviors must be capable of storing complex cue information and distinguishing among different learned associations—we call this general concept “mechanistic resolution”. For many years, our understanding of the circuitry of these learned behaviors has been based primarily on inactivation of specific cell types or whole brain areas regardless of which neurons were activated during the cue-specific behaviors. However, activation of all cells or specific cell types in a brain area do not have enough mechanistic resolution to encode or distinguish high-resolution learned associations in these behaviors. Instead, these learned associations are likely encoded within specific patterns of sparsely distributed neurons called neuronal ensembles that are selectively activated by the cues. This review article focuses on studies of neuronal ensembles in operant learned responding to obtain food or drug rewards. These studies suggest that the circuitry of operant learned behaviors may need to be re-examined using ensemble-specific manipulations that have the requisite level of mechanistic resolution. Learned associations between reinforcers and predictive stimuli are critical for survival. Unfortunately, these learned associations are also implicated in addictive behaviors. Indeed, part of what makes addictive behaviors so intractable is that craving and relapse are often triggered by exposure to closely associated stimuli Wikler, . LikewisCurrently, the majority of studies attempting to investigate the neurobiology of memory assess “global” alterations and their functions within brain regions, neurons of a specific cell-type, or afferent/efferent connections between two brain areas, regardless of the specific neural activity patterns during behavior  expression is an indirect marker used to assess neuronal activity , without accounting for differences in neuronal activity. While these technologies have provided a strong framework for our understanding of the neuroanatomy of behavior, they are not congruent with the processing, storage, or discrimination of high-resolution information in learned behaviors  the activity of specific brain areas or circuits regardless of intrinsic neural activity—in directly mediating high-resolution operant learned behaviors. As shown, the low resolution of global manipulations can obscure a brain region’s role in behavior. Since environmental information and memory storage in the brain are more likely mediated by high-resolution mechanisms such as neuronal ensembles rather than by global alterations in whole brain areas, the ensemble-specific manipulations are much more congruent with how the brain processes, stores and distinguishes among high-resolution information in learned behaviors. Indeed, data is emerging that indicate selective molecular and cellular alterations in Fos-expressing neuronal ensembles in a variety of systems and behaviors. Pavlovian conditioned behaviors also appear to share a requirement for high mechanistic resolution mediated by Fos-expressing neuronal ensembles. As the technical resolution of our manipulations continues to advance, it is likely that we will gain an even more clear perspective on the role of neuronal ensembles in a variety of behaviors. In this way, technical resolution can more closely match the mechanistic resolution of the behavioral process being studied.This is a mini review article. All authors researched and wrote 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.


With their longitudinal patient relationships, primary care physicians and their care teams are uniquely situated to promote preventive medicine, including cancer screening. A confluence of forces is driving the demand for the personalization of cancer screening recommendations. Recommendations are increasingly based on individual patient preferences, medical history, genetic and environmental risk factors, and level of interaction with the healthcare system. Current examples include choices between colonoscopy, fecal testing, and emerging tests for colorectal cancer (CRC) screening; the use of genetic information and availability of home self-testing in cervical cancer screening; the integration of multiple risk factors and patient preferences to decide the intensity and length of breast cancer screening; and the issues of smoking cessation and competing priorities when deciding whether or not to pursue lung cancer screening. These changes will inevitably increase the burden on primary care of providing high-quality cancer screening to their patients. To address, primary care physicians need access to continuously updated evidence reviews including prioritization of strongly supported recommendations, training in shared decision-making and tools for preference diagnosis, and an electronic health record (EHR) and reimbursement model that allow for population health management and team-based care. Only by reinforcing cancer screening in primary care can we ensure that personalized cancer screening is accessible and evidence-based. Mrs. J, an active 55-year-old smoker in good health, comes to your primary care office with a few days of cough and no fever or shortness of breath. Looking through her chart, you realize that it has been 3 years since you last saw her. She had followed up for fasting blood work , but not the recommended cervical cancer screening, fecal occult blood test, flu vaccine, and dedicated visit to discuss smoking cessation. After discussing her acute bronchitis, she asks whether or not she should really have a mammogram, having read that it can increase testing and treatment without any benefit. She also mentions a recent article she read about preventive mastectomies and wonders if genetic testing will help with deciding. Already 25 min behind, you do not know where to begin discussing prevention with this patient. What could make this situation easier?Primary prevention and screening of primary care patients are seen as a core part of appropriate care in the ambulatory setting . As trusFirst, an increasing number of screening recommendations encourage shared decision-making, given the growing recognition of the complex trade-offs involved in cancer screening. Strong public health messages have presented cancer screening as a panacea of early detection of aggressive cancers at treatable stages; the reality is far more complex, with frequent overdiagnosis and the treatment of “cancers” never destined to cause symptoms. Breast cancer screening recommendations, for example, now urge physicians to tailor screening based on patient preferences, especially for women outside of the 50 to 75 age range and those with dense breasts. Different women may approach the balance of marginally reduced breast cancer mortality and risks of being treated for pseudo-disease differently, making it essential that PCPs know how to “diagnose” their patients’ preferences . It is cSecond, screening recommendations increasingly require detailed patient information, often in the form of clinical risk scores or genetic testing, to determine whether screening is indicated and at what intensity . Lung caThird, individual screening tests are only one part of an increasingly long list of available tests and recommendations that are indicated for multimorbid patients. One widely cited article calculated that PCPs in the USA would need 7.4 h a day just to complete all prevention activities for an average panel of patients, in addition to the 3.5 h a day to manage ten common chronic diseases, an obviously impossible task , 9. Not Fourth, PCPs are increasingly expected to demonstrate their public health impact by improving cancer screening rates for their population of patients, particularly for strongly recommended tests like with colorectal cancer (CRC) screening . There iThough our vignette might be viewed as too familiar to PCPs, it illustrates some features of the current situation in primary care. Limited resources prevent in-depth discussions, stratification of patient populations, and contact with patients between visits. While PCPs have always used their in-depth knowledge of their patients’ personal situation to personalize care, an increasing number of complex recommendations, rising expectations, and rapidly developing technology and innovations are increasing strain . We needMost people who participate in cancer screening are unaware of the harms that need to be evaluated in perspective of potential benefits. Patient decision aids, as demonstrated in a recent randomized trial , can helPrevention recommendations need to be regularly updated and differentiate which ones should come first and receive the strongest endorsement. These recommendations need to be nuanced with clear directions on how to incorporate family history and genomic testing to present well-defined risk profiles. Following similar developments in other countries, the EviPrev programme in Switzerland attempts to assign clear priority to prevention activities with evidence of substantial benefit using an interactive online table that is linked to information resources that can be given to patients .Such work needs to be supported with computerized decision support tools and regularly updated lists showing which prevention tasks should be discussed first, to encourage PCPs to deliver difficult messages and to aid PCPs in understanding more complex information that usually accompanies genetic-risk stratification . The impKaiser Permanente Northern California provides an example of how PCPs can work in cooperation with organized screening programs to increase the use of highly recommended screening tests, such as fecal occult blood testing and colonoscopy for CRC screening . The cenprecision medicine revolution has the potential to improve the early detection of cancer while simultaneously increasing precision, furthering current trends towards personalized screening regimens. Although these challenges were noted in the current screening context, to ensure the appropriate information, education and clinical information is provided for the primary care context, PCPs will need to play a critical role in these changes to be able to successfully integrate genetic testing and patient preferences [The so-called ferences . The WISferences . Women iferences .The push for personalized cancer screening recommendations has the potential to increase workload and complexity for PCPs. An increasing number of recommendations recognize the complex trade-offs in screening and call for the incorporation of patient preferences. Detailed patient and family history-taking is required to identify patients who are most likely to benefit and for whom screening is indicated. Simultaneously, the large number of potential prevention activities makes prioritization key, and PCPs are expected to increase screening rates for their entire patient population.The PCP in the vignette is struggling to provide excellent preventive care to a patient who rarely presents for appointments and simultaneously has multiple indicated tests. Examples exist, however, of how leading organizations are making personalized cancer screening routine, even for patients who do not see their PCP regularly. Patient decision aids can provide guidance; EHR can provide real-time decision support; integrated recommendations can help prioritize what to address first; and team-based care can help contact patients so that they can get screening tests when they are ready. These interventions can be used to not only address current challenges, but also prepare PCPs to incorporate the coming precision medicine era advances into their daily practice.


Mobile and connected devices like smartphones and wearable sensors can facilitate the collection of novel naturalistic and longitudinal data relevant to psychiatry at both the personal and population level. The National Institute of Mental Health's Research Domain Criteria framework offers a useful roadmap to organize, guide and lead new digital phenotyping data towards research discoveries and clinical advances. RDoC is not simply a data collection matrix with rows representing constructs and columns representing units of analysis; it is designed as a framework to organize data such that knowledge gaps can be identified and hypothesis-driven research can move forward connecting translational domains at cell, molecular, circuit and behavioral levels. (The RDoC Matrix can be directly accessed here: https://www.nimh.nih.gov/research-priorities/rdoc/constructs/rdoc-matrix.shtml.) However, to date, linking biologically based psychiatric research to clinically observable symptoms has proven challenging.7The classification of psychiatric disorders remains unsatisfactory. Although reliability of diagnoses has improved with successive editions of the Diagnostic and Statistical Manual of Mental Disorders,9 and may reflect that NIMH's RDoC reconceptualization of illness, like others before it, is alone not sufficient. Rather, innovative models such as NIMH's RDoC need new tools and new data streams to inform the framework much like the microbiology needed its new tools for data gathering in the form of the microscope. With the increasing recognition that what we today label as psychiatric illness likely represents only one end of a continuous spectrum,10 there is a need to better understand less overt manifestations of illness. Considering psychosis as a trans-diagnostic and extended phenotype in the general population,11 what do the NIMH's RDoC constructs such as negative and positive valence systems, cognitive systems, social process, and arousal and regulatory systems look like in those with transitory and subthreshold psychotic experiences, as compared to those with clinically manifest psychotic disorders? Capturing and quantifying such patient experiences traditionally would be difficult, especially as many patients may only experience brief or transitory symptoms that are often missed in traditional infrequent assessments.12This challenge to realize a unified biological model of psychiatric illness is not new,13 Utilizing phone sensors, such as GPS, to determine temporal mobility patterns, voice recordings to detect speech and vocal markers, and call and text logs to indicate degrees of social interaction, the phone is now able to offer objective measures of behavior in a less burdensome manner than prior actigraphy efforts.14 Finally, with many smartphone and wearable sensors now able to detect pulse, galvanic skin conductance, temperature and ambient light among other capabilities, collecting real-time physiological data from subjects is practical for psychiatric research.16 Considering in situ using data from smartphones and other personal digital devices can be considered digital phenotyping.14 Although the ability to record real-time self-reported symptoms, objective measures of behavior and continuous physiology from millions of individuals was not the focus of NIMH's RDoC original conceptualization, the rapid recent expansion of smartphones and connected devices offers both a useful new tool and data streams. As portable biosensors and smartphones advance, in the near future we may soon be able to collect biological units of analysis such as genetic, molecular and electroencephalogram data in a reproducible and transparent manner.19 In practical terms, however, the use of digital devices to collect such data may be currently limited and most practical for behavior, self-reports and physiology.Connected devices such as smartphones, wearable devices and tablets now offer novel tools to capture several units of analysis of the NIMH's RDoC framework, making it possible to collect new data streams that were previously either difficult or nearly impossible to capture. Through offering real-time self-assessment surveys on the phone, it is now possible to collect time-stamped symptom surveys in a more convenient and less burdensome manner than using prior ecological momentary assessment methods.20 the field's prior difficulties in quantifying subjects' physiology, behavior and self-reported symptoms may explain why this has been a challenge. Assuming that many observable phenotypes of psychiatric illnesses are temporally dynamic, environmentally influenced and socially modulated—reliably capturing such measures without tools such as smartphones is difficult. Further, with many psychiatric illnesses impacting cognitive functioning, relying on subject self-report for data on symptoms, behavior and even physiology may be unreliable. Instead, approaching the problem with smartphone-based RDoC-like data offers a plethora of quantified information collected not only at periodic study visits but also in the subject's real-world environment, in real time, possibly over long time periods, with minimal recall bias. Digital phenotyping may offer a new lens through which the field's genetic, molecular, cellular and neural circuitry data better correlate with clinically observable psychopathology, thus elucidating translational mechanisms of illness.21 Consider a patient with clinically diagnosed agoraphobia and panic disorder. Using the construct of acute threat or fear, a smartphone in such a patient could collect self-reported data through diagnostic and assessment scales delivered as surveys on the phone, behavioral data such as avoidant behavior through GPS, facial expressions through the camera, errors/response times through cognitive assessments delivered as tap tests, and physiological data such as heart rate and skin conductance. The location of avoidance based on GPS data could indicate the source of the threat . Such observations can offer a great deal more information than is possible simply by periodic clinical assessments. Observations of such episodes during sleep may raise the question of whether another illness such as temporal lobe epilepsy may underlie the panic attacks. Such data, in individuals not yet diagnosed with an illness can potentially help identify preclinical indications of risk for the disorder. As another example, the construct of affiliation of attachment, which was previously difficult to quantify and measure proximity preferences of individuals. Now using bluetooth sensing on smartphones, which can detect proximity to similar sensors on others' smartphones, it is feasible to monitor social patterns in an unobtrusive manner that can provide data on how individuals interact with others. Utilizing tools such as the Beiwe platform that is a research grade smartphone app collecting digital phenotyping data with a supporting analytical toolset,14 clinical studies can now longitudinally collect these data streams on subjects' own personal smartphones. Although the ability to capture such data does not inherently mean that it is clinically valid or even useful, it offers new opportunities for clinical studies to field-test and validate these approaches.Although traditional research efforts studying genes, molecules, cells and neural circuits have struggled to find reproducible clinical correlates,22 It is possible to imagine how the ubiquity of smartphones will enable studies to capture rare digital phenotypes from the general population, as well as ones we today do not yet recognize; digital phenotyping may also identify which subjects to conduct more extensive genetic, molecular, cellular and neuroimaging investigations on. It is also possible to delineate the trans-diagnostic, and translational signatures of psychopathological dimensions at a preclinical level in the community and map that on to what we see in clinical populations. Such large-scale studies will be necessary to capture and quantify extended phenotypes of illness, but with the RDoC framework and population already owning23 and willing to use smartphones for clinical research,25 we already have the roadmap and tools available today.If NIMH's RDoC offers a roadmap to conceptualize psychiatric illness in a new light, smartphones and digital phenotyping offer added fuel to power new discoveries along this guided route. Unlike prior actigraphy research efforts that were hampered by inconvenient technology and high study costs, the high rates of smartphone ownership mean that large population level studies of psychiatric illness can be conducted at relatively low cost as has been recently demonstrated in major depressive disorder.The scope and scale of digital phenotyping efforts also raise considerable barriers. Privacy and confidentiality issues must be fully addressed before digital tools can be broadly applied. Likewise, transparency in data processing and analysis is needed to build trust and ensure reproducibility. The ethics associated with these digital tools require a more collaborative dialog between all stakeholders and greater subject and patient involvement. Although NIMH's RDoC may offer a way forward for digital phenotyping, the answer to the issues is less straightforward and a current struggle for many fields of healthcare even outside of psychiatry. New collaborations with data science fields, increased education about digital tools for both patients and clinicians, and emphasizing digital privacy first are all important first steps.Combining the RDoC framework with digital phenotyping offered from smartphones and other connected devices presents a unique opportunity for psychiatric research. Through incorporating the potential of these new digital technologies into RDoC framed clinical questions, psychiatry can now explore new dimensions of pathology largely inaccessible only a few years before.


For decades familial high-risk studies have informed us about genetic and environmental risk factors for schizophrenia and recently also bipolar disorder. Familial high-risk studies are important and relevant and may represent a possible shortcut to learning more about early markers of illness, mental vulnerability and resilience.The Danish High Risk and Resilience Study – VIA 7 is a prospective cohort study of 522 7-year old children, 202 of them born to at least one parent diagnosed with schizophrenia in the Danish registries, 120 of them born to a least one parent diagnosed with bipolar disorder and 200 of them born to parents without any of these diagnoses. A comprehensive battery has been used combining assessments from several domains for both parents and children.Results show that children born to parents with schizophrenia or bipolar disorder have higher frequencies of early mental problems. Further there are marked differences between the three groups concerning neuro cognition, motor functioning and living conditions including socioeconomic status, early risk factors and home environment - all factors that are known to be important with regard to healthy child development.First results from the VIA 7-study indicate that many children and families have unmet needs and problems. Perspectives are two-fold: we aim to follow the cohort and conduct a new assessment before puberty (at age 11). Simultaneously, we are evolving an early, integrated, specialized and family based intervention, called VIA Family, to prevent or ameliorate development of severe mental illness in individuals born to parents with schizophrenia or bipolar disorder.


A record of sample provenance information for a set ofparticles can play a useful role in identifying some of the sources and decreasing theextent of particle variability and the lack of reproducibility observed by manyresearchers.Nanoparticles ofvarious types are of increasing research and technological importance in biological andother applications. Difficulties in the production and delivery of nanoparticles with consistentand well defined properties appear in many forms and have a variety of causes. Amongseveral issues are those associated with incomplete information about the historyof particles involved in research studies, including the synthesis method, sample historyafter synthesis, including time and nature of storage, and the detailed nature of anysample processing or modification. In addition, the tendency of particles to change withtime or environmental condition suggests that the time between analysis and application isimportant and some type of consistency or verification process can be important. Theessential history of a set of particles can be identified as   I.Nanoparticles ormore generally nano-objectsThere has been much discussion in the literature about characterization needs fornanoparticles andother nanomaterials,Provenance is most commonly used in relation to the origin of a work of art. However, theuse of provenance is being extended to other areasIt is necessary to ask what information is needed to enable trust and reproducibility fornano-objects. To help identify an answer, it may be useful to adapt an ISO description ofprovenance information:Information thatdocuments the history of [a batch of nano-objects]: This information tells the origin orsource of the [batch of nano-objects], any changes that may have taken place since it wasoriginated, and who has had custody of it since it was originated. Examples of provenanceinformation arethe principal investigator who recorded the data, and the information concerning itsstorage, handling, and migration . The intent and objectives ofprovenance information are clear, as is the importance of origin and history. Thedescription highlights the need for both the collection and retention of relevant provenanceinformation andsome type of data record associated with a set of nano-objects. Our concern is the range ofinformation thatneeds to be included as provenance information in some type of information and data record. This perspective addresses someaspects of data completeness, but does not specifically address important issues andopportunities related to data collection and storage frameworks that allow information to be mined andproperties such as risk modeling,II.ACS Nano editorial about nanomaterialscharacterization:(1)ACS Nano,Characterization requirements vary with material and application: Consistent with thestated nanoparticle characterization needs applied for submissions to thejournal (2)Intrinsic characteristics: However, as suggested in the editorial and otherpublications,(3)Acquired or extrinsic characteristics: Characteristics of nano-objects are alsoacquired or altered during storage, handling, processing, or following suspension inexperimental biological or environmental media. These can include hydrodynamicdiameter in specific media, size changes due to dissolution, aggregation oragglomeration, surface reactivity , andcharge or zeta potential. Information about the treatments, handling, storage, and alteredproperties should be included as important components of provenance information in nano-objectdata records and may be among those most widely ignored or currently underreported.The remainder of this article explores the nature of provenance information that would be usefuland relevant to associate with a batch of nano-objects in a data record that travels with oris associated with the material. The objective is not to define a specific set of information or data requirementsbecause the requirements can depend on the material and/or application. It is useful to thinkabout a framework or context for collecting and reporting provenance information that relates tosample consistency and reproducibility. Three considerations can help guide our thinking assummarized in an We have found and reported on several issues that relate to or expand upon the abovecategories and that impact the behaviors of nanoparticles. These include details of synthesis,A.element X  nanoparticles.” In reality, thebehaviors described are usually the properties of a subset of nanoparticles from a batch ofparticles created by a specific process or sequence of processes. They have also beenstudied at some time after synthesis, handling, and some type of storage . In many cases, the properties ofthese “specific” particles should not be viewed as “generally” applicable. The followingexamples highlight differences in properties of Fe metal-core oxide-shell particles that,based on paper titles, might have been assumed to have similar properties. In addition todifferences in behaviors of particles produced by totally different processes, seeminglyminor changes in a synthesis process can produce particles with significantly alteredbehaviorsMany published papers include simple general descriptors of particles in titles such asthe “…behaviors of 4 in water produced significant differences in reactionrates and products formed. These particles were formed by (1) reduction of goethite andhematite particles with H2 at high temperatures (200–600 °C)[FeH2],3 with NaBH4 [FeBH],SP].et al.4 in water by FeBH produced more chloroform(CCl3H) than produced by reduction with FeH2, which produced moreenvironmentally benign products. The FeBH and FeH2 particles werenominally the same diameters (40–60 nm), but otherwise had some fundamentally differentcharacteristics. The metallic cores of the FeH2 particles were made up ofnearly single crystal grains essentially the size of the particles surrounded by a highlycrystalline oxide shell. In contrast, the metallic cores of the FeBH particleswere made up ≈1 nm grains with this collection of metallic grains surrounded by an oxideshell that did not appear to have high crystallinity. Although not a surprise to manyresearchers,this example affirms that more than nanoparticle size is required to identify nanoparticle properties orbehaviors.Metal-core oxide-shell Fe nanoparticles have been studied as a way to reduce contaminants inground water.BH and FeH2nanoparticles, therelatively pure FeSP particles were observed to oxidize more slowly and werealmost unreactive with the CCl4.H2 and FeSP were different insize, both contained highly crystalline metal cores and crystalline oxide shells. Wepostulated that the large difference in corrosion rate and reactivity with CCl4might be related to S retained in the nanoparticles from the salt used in part of the synthesisprocess.et al.H2 “type” particles for which the only difference was the nature of thesalt used in the synthesis process. The resulting particles had significant variations inboth reaction rate and the formation of chloroform. Although only trace residues from theanions present during synthesis remained in the particles, the reaction properties weresignificantly altered. The particles produced by this process were generally similar tothe FeH2 particles described above, but produced a wide range of reactivity andproduct formation (some similar to the FeBH particles) and all were morereactive than the FeSP particles. We have found that both major and relativelysubtle differences in nanoparticle synthesis contribute to variations in nanoparticle properties.Interestingly, in comparison to the FeSynthesis and process related provenance information: Theabove examples for relatively simple nanoparticles demonstrate that the synthesis approach andsynthesis details can have a significant impact on particle properties. Many otherexamples could be provided,(1)Record of sample synthesis: reference or details of synthesis as known (2)Characterization results: data reports including relevant dates and processing ofsamples for analysis(3)Important dates and times: synthesis, arrival in laboratory, opening of samplecontainer, primary analysis measurements, and expiry date(4)Storage time, conditions, and containers: temperature, humidity, media, lightshielded, shipping, or transport)(5)Record of additional processing: e.g., dried, washed, heated, sonicated,functionalized (including the method and number of times processed).Based on what has been observed, the range of information about particle synthesis appropriate for sampleprovenance information should include the following: It is relevant to remember that the information noted above is important and may be helpful inunderstanding differences in particle behaviors in biological systems. However,such informationmay not always be sufficient to distinguish differences in the biological effects ofparticles, especially when particles have been stored after characterization. Therefore,some type of system or biologically relevant test is often useful to verifysimilarity of particle properties for the intended purposes near the time of application.Such tests might include verifying size in media using dynamic light scattering (DLS) oranother method. The consistency of effective surface potential might be verified using azeta potential measurement just before application or use, the surface composition orconsistency might be verified by XPS, and it is often important to check for presence ofendotoxin or other biological toxicity response on known systems (positive and/ornegative control).B.Although the significance of nano-object surfaces is widely acknowledged and therelationship of surface properties to biological responses is long established,Two related issues regarding nano-object surfaces are highlighted as critical to particlereproducibility: (1) Are there unwanted surprises on the surface? (2) Does the surfacehave the composition or functionality that is intended or desired?Researchers usingsurface analysismethods frequently find elements or compounds on surfaces that are not those intended ordesired. As described in an earlier paper, F made up of Polytetrafluoroethylene (PTFE)break down products arising from a component in the synthesis system was found on thesurfaces of CuOx nanoparticles intended for toxicology studies.Bacterial endotoxin is a heat-stable common contaminant in many chemicals and glasswarethat readily attaches to nanoparticles.et al.,Surface coatings with a designed function are increasingly important to many types ofnano-object applications, including drug delivery and other types of functionality. Asdescribed in some detail by França Surface related provenance information: Therelevant question regarding nano-object surfaces concerns what analytical or functionalmeasurements have been conducted to provide researchers or others confidence that the specificnano-objects to be used for a specific purpose or a study have the expected surfaces andsurface properties?Achieving the needed confidence does not necessarily mean conducting a full set ofanalysis beforeeach application. In the work described above focusing on Fe metal-core oxide-shellnanoparticles, awide variety of analytical and other measurements were conducted on the material during initialstudies.Although other surface sensitive analysis methods are useful for specific information,Multiple approaches could be useful to directly or indirectly provide a researcher or engineer somedegree of confidence that the surfaces of a set of nano-objects have the desired orexpected properties.C.The recognition that characteristics of nano-objects are also acquired or altered duringstorage, handling, and when their environment is altered highlights the importance ofincluding information about the synthesis, processing, and handling history ofnano-objects as provenance information in a material data record. There may be multiple stagesin the lifetime of a set of particles with different types of characterization andhandling for each. They might have a set of properties or characteristics as made, aftersome storage or handling, or they might be functionalized for a particular purpose givingrise to a different set of properties. The functionalized particles might then bedispersed in biological media for cellular studies again altering the particles bychanging the environment. The handling, preparation, and any analysis results at each stageshould become elements in the material data record.(1)Material drying, heating, resuspension, or sonication: Althoughmany particle characteristics, including size, for fresh solution synthesizedsix-line ferrihydrite and dried versions of the particles are similar, the reductivedissolution rates differed significantly.(2)Handling, shipping, and storage: There are many reports that purchasedmaterials did not have the advertised/desired properties whenreceived.(3)Processing, functionalization, media exposure: Nano-objects may be processed ortreated in various ways before use or application. The history of any processing formodification, along with information related to characterization before and after theprocessing, is an important component of provenance information. It isgenerally recognized that dispersion in biological media may result in removal ofmolecules initially on the particle surface, and in many cases, new molecular layerswill form, resulting in a media modified surface. When such changes occur, abiologicalsystem will see and react with this modified surface, not the oneinitially on the particles.Several common or in some cases required process steps can induce changes innanoparticlessamples or become a source of uncontrolled variability including: invitro testing could be enhanced by including serum in the media.in vitro testing.et al.,Our experience dispersing Ag nanoparticles in biological media demonstrates how details of particleprocessing steps can make significant or subtle differences in the nature of the particlesas would be seen by a biologicalsystem. Particles often need to be dispersed in some type of media forsurface modification, delivery to biological systems, or for other types of application. Previous workdemonstrated that the dispersion of nanoparticles in cell culture media for (i)Would the serum alter the dissolution?(ii)If the serum enhanced dissolution, how sensitive would the rate of dissolution be to theamount of serum?(iii)How sensitive might the dissolution be to the way particles were added to acellculture media serum mixture?We had three questions regarding the impact of the serum on the Ag particles: To test the impact of fetal bovine serum (FBS) on dissolution [question (i)], weexamined the dissolution of particles using the procedures described in Ref. The sensitivity of the serum enhanced dissolution to serum concentration could be tested inRosewell Park Memorial Institute (RPMI) 1640 cell culture media. The procedure was to disperse an amountof particles in FBS and then add the particle serum mixture to the cell culture media to achieve adesired mixture of media and serum. The sensitivity of serum concentration for mixtureswith 1%, 10%, and 30% [vol%] FBS is shown in Fig. For the final test (iii) the Ag nanoparticles dispersed in a mixture of cell culture media with 10%serum in three different ways: (1) particles were added first to the serum and then to thecell culturemixture (FBS 10%+RMPI); (2) particles were added to the mixed solution (RPMI/FBS10%); and(3) particles were first added to the cell culture media and then the serum was added(RPMI+FBS10%). As indicated in Fig. There are three main messages from these measurements: (1) FBS significantly alters thedissolution ofAg nanoparticles;(2) the amount of FBS and order of mixing alters the rate of dissolution; (3) proceduraldetails can influence effective particle size, the rate of dissolution, and the types ofparticles that would be observed by a biological system. Therefore, it is important to report indetail the steps taken during processing and/or to conduct some type of verification stepto ensure that any small changes in processing have little consequence for themeasurements to be conducted.etal.An interlaboratory comparison conducted by Belsey Analysis preparation related provenance information: In manycases, nanoparticles are not initially in the form needed for some type ofanalysis orapplication. Powdered material may need to be dispersed in solution for DLS or zeta potentialmeasurements.D.Although preparing and delivering reproducible batches of nanoparticles for specificpurposes can be challenging, many research teams have found ways to be successful.Recognizing that reproducibility and reliability are critical issues, especially fornanomaterials, and understanding some of the physical and chemically related processesthat can cause problems helps suggest ways to improve material reliability. Ifmaterialsused in a study are not reproducible, work following from the study will likely beunreliable and not reproducible. Although the issues related to nanomaterials seem moreendemic than for most other materials, the problem materials' reproducibility is sufficiently generaland widespread that a virtual issue of the journal Chemistry of Materials was assembledto deal with matters of materials reproducibility “Best Practices for Reporting the Propertiesof Materials and Devices.”III.Relevant provenance information about batches of nanoparticles can provide a useful tool for identifying andminimizing some of the sources of different behaviors of supposedly similar nanoparticles in biologicalstudies.A wide variety of reports and editorials indicate that there are significant challenges increating and delivering well characterized nano-objects in a consistent and uniform matterfor both study and application. Issues range from differences, subtle and otherwise, innano-object synthesis, in how nano-objects are characterized, handled, stored, processed,and prepared for analysis. It is useful to recognize that in many circumstancesnano-objects are not stable in their environment. Therefore, it can be important tounderstand in detail how a set of particles were synthesized, their initial properties(intrinsic or native properties), and what has happened to the particles since the time ofsynthesis and characterization.The informationthat needs to be associated with a set of nano-objects to reliably trace their propertiesand behaviors since synthesis may be usefully identified as provenance information and this should beincluded in some type of materials associated data record. Other researchers are developing datarecording protocols to enhance the ability to extract useful information from collections ofcurated data on nano-objects.Based on our experience, the provenance information should include (1) detailed records regardingsample synthesis; (2) results of characterization, including any sample handling needed forthe characterization; (3) history of the material including important dates and times such asdate of synthesis, arrival in a laboratory, when containers were opened; (4) information about storageconditions, time, and containers; and (5) summary of any additional processing before lateruse or analysis. AnISO standard (ISO TS 20579-4)Although provenance information and an appropriate data record can assist delivery ofreproducible particles, such data only assists the process. The ultimate test for abiological application is consistent biological response. Provenance information may help in dealingwith identified issues, but positive and negative control measurements and other validationtests can help verify nano-object consistency in the environments of actual use orapplication.


The feeding of critically ill patients has recently become a controversial issue, as several studies have provided unexpected and contradictory results. Earlier beliefs regarding energy requirements in critical illness—especially during the initial phase—have been challenged. In the current review, we summarize existing evidence about fasting and the impact of early vs. late feeding on the sick organism’s responses. The most important points are the non-nutritional advantages of using the intestine, and recognition that early endogenous energy production as an important player in the response must be integrated in the nutrient prescription. There is as of yet no bedside tool to monitor dynamics in metabolism and the magnitude of the endogenous energy production. Hence, an early “full-feeding strategy” exposes patients to involuntary overfeeding, due to the absence of an objective measure enabling the adjustment of the nutritional therapy. Suggestions for future research and clinical practice are proposed. Over the last decades, nutritional interventions carried out in critically ill patients were characterized by different timings, strategies, and terminologies. Recent randomised trials have brought some new insights in this topic, challenging several earlier beliefs. Early full nutrition—which is achieved more easily with parenteral nutrition (PN)—is associated with negative clinical outcomes, whereas the route itself may be irrelevant . In the After clarifying some important definitions , the aimConsidering the question of early or late feeding implies that there is a variable period of fasting. Significant misunderstanding regarding consequences may be formed, should the metabolic tolerance and patterns of responses similar in healthy  and sickIn healthy subjects, fasting is considered to have potential beneficial effects, including spiritual benefits ,7: multiovernight fasting (defined as 14-h fasting or post-absorptive state); (2) a short term fasting up to 85 hours of starvation in which progressive alterations in lipid and glucose metabolism occur; (3) prolonged fasting beyond 3 days that causes protein catabolism.Fasting is the complete interruption of feeding for a variable duration, while nutrient restriction can be defined as the reduction of particular or total nutrient intake without causing malnutrition . In critrefeeding finally occurs, fat is processed as in the normal fed state, but the liver at first remains in a gluconeogenic mode. As the blood-glucose levels continue to rise, the liver completes the replenishment of its glycogen stores and begins to process the remaining excess glucose for fatty acid synthesis.In healthy subjects, plasma glucose levels decrease during fasting due to the slowly decreasing endogenous glucose production (EGP) from glycolysis and gluconeogenesis  and the intensity of the energy expenditure (EE) changes, causing persistent protein catabolism . The magThe neuroendocrine response to injury is a complex response that primarily stimulates protein catabolism , and is A major factor limiting optimal management is the inability to measure the dynamics of the glucose, protein, and lipid turnover at the bedside of an individual patient. Having such monitoring tools would enable targeted nutrition and metabolic therapy to control catabolism and support recovery.While all guidelines favour EN, they do not address the important dysfunctions that affect the gastrointestinal (GI) tract in response to critical illness, and make the use of this route problematic in many patients ,21. MultThe advantages of EN include the maintenance of gut integrity and function, and modulation of the stress and immune responses . Howeverp = 0.004) and protein  compared to medical patients. Whether an improper protocol implementation (as suggested by the authors) may explain this finding or if the aggressive use of prokinetics played a role remains to be demonstrated.It is not clear if the systematic and early use of prokinetic agents to stimulate GI motility is beneficial or harmful . In an oWhen feeding resumes after fasting, patients are exposed to the risk of refeeding if full feeding is provided right away. The response cannot be reduced to phosphate and potassium dynamics and plasma concentrations; refeeding also involves less well-known metabolic consequences associated with cardiac, respiratory, and liver dysfunction/failure. Progressive feeding over 3–4 days  as realised in the recent trial achieves mortality reduction . After tThe 2017 ESICM guideline recommends early EN within 48 h  based onEarly parenteral nutrition (PN) allows the provision of macro- and micro-nutrients preventing underfeeding without the potential benefits to the gut. The uncertainties come from the lack of exact determinants of the dose of nutrients required in the acute phase of critical illness. Indeed, enteral feeding intolerance in the early phase of severe illness may possibly be seen as an adaptive process, whereas the use of PN may increase the risk of overfeeding.2 and presenting acute respiratory failure requiring mechanical ventilation, did not observe any significant differences [Studies comparing early PN in adults  and chilferences . The preferences ,30. It iBased on existing weak evidence, the initiation of nutrition early via the enteral route (whilst not aiming for coverage of full energy expenditure during the first days after ICU admission) is recommended . There iImportantly, most of these studies have used different equations to calculate “full energy needs”, whereas all these equations have been shown to lead to overfeeding . The “fuEarly full nutrition, whatever the route, is harmful and associated with more hyperglycemia, infections, and organ dysfunctions;Early EN is beneficial, mainly due to its non-nutritional advantages, and possibly due to its (nearly systematic) slow progression to full feeding;Early PN does not have positive enteral effects and incurs larger risks of overfeeding, especially when equations are used to determine the energy target;Early low-dose PN may have beneficial outcome effects, particularly in malnourished patients.During the last decade, we have learned that:Available evidence and open questions are summarized in Observational trials conducted with EE measurement by indirect calorimetry ,43,44 haIt is not easy to identify the time point appropriate for advancing to full feeding. While progression over 3–4 days seems beneficial , there iSome degree of underfeeding in the early phase is probably safe and possibly beneficial;Underfeeding beyond 7 days is harmful;The limit for safe underfeeding between days 3 and 7 remains unresolved;We suggest that a cumulated extrinsic energy deficit between −50 and −100 kcal/kg could help to identify the increase in risk of malnutrition-related complications.Taken together:Based on current knowledge, energy provision should be progressive and EN should be preferred in critically ill patients who are not able to eat. The initiation of nutrition early via enteral route, not aiming at coverage of full measured EE during the first days after ICU admission, is recommended . The strFor metabolic reasons, feeding to cover full measured (or estimated) EE should not be the aim during the acute phase of illness, independent of the route. This statement is supported by the recent analysis of outcome according to the ratio of energy delivery to measured EE . It is nEarly feeding should always be below the actual energy expenditure.EN should be started within the first 48 h if an oral diet is not possible, and in the absence of contraindications.Full energy requirements should be gradually achieved by day 4 after ICU admission.The period of fasting should be limited to a maximum of 3–4 days after ICU admission.Intentional underfeeding should not be applied beyond 4 days.If EN is not covering 60% of caloric needs by day 4, PN should be considered.The effect of extrinsic energy provision significantly below EE for prolonged duration is not clear. Such underfeeding for up to 7 days may be considered in patients without underlying malnutrition.2 measurements [Clinicians should strive for determination of EE based either on indirect calorimetry or VCOurements .Based on the above studies and considerations, we suggest that:Many processes in critically ill patients go beyond normal physiology. Several recent studies were unsuccessful in improving outcome with increased energy and protein delivery. It is possible that there are narrow individual windows for optimal timing, route, and amount of nutrition. The recent data indicate that the issue also includes the composition of feeds, and particularly of the dose of proteins . AdaptivMany domains remain unexplored: e.g., little is known on the best feeding strategy in patients with very high risk of aspiration . Studies exploring metabolic patterns associated with chronic critical illness  are warranted. Finally, we suggest that future studies should use clear definitions and carefully plan sub-analyses on patient categories.Energy expenditure and substrate utilisation are deeply modified by critical illness, whereas bedside markers to assess the endogenous energy production and adapt extrinsic feeding are missing. Early EN, started at a slow rate and increased gradually over 3–4 days, should be considered as a routine feeding approach in ICU patients, due to additional non-nutritional benefits compared to PN. Compared to early full feeding by either route, late feeding may have advantages, but this effect is most likely a dose-effect.