HIV treatment programmes globally has resulted in children with perinatally acquired HIV reaching adolescence in large numbers. The number of adolescents living with HIV is growing further due to persisting high HIV incidence rates among adolescents in low‐ and middle‐income settings, particularly in sub‐Saharan Africa. Although expanding access to HIV viral load monitoring is necessary to achieve the 90‐90‐90 targets across the HIV care continuum, implementation is incomplete. We discuss the rationale for prioritizing viral load monitoring among adolescents and the associated challenges.The success of HIV are a complex group to treat successfully due to extensive exposure to antiretroviral therapy for those with perinatally acquired HIV and the challenges in sustained medication adherence in this age group. Given the high risk of treatment failure among adolescents and the limited drug regimens available in limited resource settings, HIV viral load monitoring in adolescents could prevent unnecessary and costly switches to second‐line therapy in virologically suppressed adolescents. Because adolescents living with HIV may be heavily treatment experienced, have suboptimal treatment adherence, or may be on second or even third‐line therapy, viral load testing would allow clinicians to make informed decisions about increased counselling and support for adolescents together with the need to maintain or switch therapeutic regimens.Adolescents with Given scarce resources, prioritization of viral load testing among groups with a high risk of virological failure may be required. Adolescents have disproportionately high rates of virological failure, and targeting this age group for viral load monitoring may provide valuable lessons to inform broader scale‐up. The numbers of adolescents living with HIV has increased globally by 30% since 2005 HIV viral load (VL) testing allows accurate monitoring of antiretroviral treatment and detection of virological failure. Expanding access to VL monitoring is necessary to achieve the ambitious UNAIDS treatment target that stipulates that 90% that those on ART should have durable viral suppression. Universal access to HIV VL testing has yet to be achieved however. We discuss the rationale for prioritizing VL monitoring among adolescents.An estimated 1.8 million adolescents between 10 and 19 years old were living with HIV in 2015, an increase of 28 per cent since 2005 Children with perinatally acquired HIV who would otherwise have died in infancy and early childhood are now reaching adolescence in large numbers due to earlier diagnosis, treatment initiation and the global scale‐up of antiretroviral therapy (ART) While the rate of new infections among adults has stabilized in many countries, the decline in the incidence of infection among adolescents and young people has been slower. A third of new infections occur in the 15–24 year age group, with an estimated 670,000 young people in this age group newly infected with HIV in 2015, representing over 40% of new HIV infections globally This growing cohort of adolescents presents a challenge to resource‐limited health services not used to effectively managing adolescents, a subset of whom have complex treatment histories and chronic illness Adolescence is a period of physiological and psychological growth characterized by biological, sexual and identity development and increasing social autonomy Both adolescents with perinatally acquired and non‐perinatally acquired HIV have varied and overlapping risk factors for treatment failure and subsequent development of drug resistance. Adolescents in both groups face the complexities of living with an oft‐stigmatized condition throughout adolescence and into adulthood with the attendant risks on adherence and retention in care.Adolescents with perinatally acquired HIV are at high risk for treatment failure and multiclass drug resistance for several reasons. Those who have reached adolescence are likely to have had exposure to ART to prevent perinatal HIV infection or started ART early in life, and may be heavily treatment experienced Adolescents with recently acquired HIV infection are also at substantial risk of treatment failure and drug resistance Viral load testing is recommended by the WHO as the gold standard for monitoring HIV treatment and failure in all patients VL monitoring is not available in most resource‐limited settings Adolescence is also a period of increased sexual risk taking with subsequent risk of both HIV acquisition and transmission and of unplanned pregnancy As adolescents with perinatally acquired HIV may be heavily treatment experienced and on second or even third‐line therapy, and both those with perinatally acquired HIV and newly infected adolescents may have suboptimal treatment adherence, VL testing in this age group would allow clinicians to make informed decisions about increased counselling and support for adolescents together with the need to maintain or switch therapeutic regimens. VL monitoring accompanied by appropriate regimen change will reduce the time spent on a failing regimen avoiding the selection of resistant viral mutations In low‐ and middle‐income countries where limited VL testing is available, measuring VL six months after treatment initiation gives healthcare professionals the opportunity to intervene with targeted adherence and support interventions Adolescents are a mobile group, with migration linked to key transitions into adulthood, for example from rural to urban areas for employment or educational opportunities Phased implementation of VL testing would allow logistical and technical capacity‐building for universal access in a context where introduction of routine VL monitoring for the general population living with HIV is not feasible. Initial implementation of VL assays in LMICs could prioritize groups such as adolescents who are at higher risk of treatment failure and constitute a smaller group compared to adults with HIV. Initiating VL testing in adolescents as a sub‐section of the population living with HIV could provide a platform for investigating the feasibility, cost‐effectiveness, and acceptability of VL testing in these settings, with the potential to inform wider scale implementation.The impact of global ART programme scale‐up has produced astounding gains in mortality, turning an inevitably fatal condition into a chronic disease requiring lifelong treatment with sustained adherence. The Global Plan for the eradication of vertical transmission of HIV has significantly reduced the number of children born with HIV. Early diagnosis and treatment has resulted in most of these children reaching adolescence. The global community set the goal of ending the HIV epidemic by 2030, with ambitious targets to get 90% of people with HIV tested, 90% of those tested on treatment and 90% of those on treatment virally suppressed. Yet in 2016, we saw almost 2 million new HIV infections, most of those in adolescents and young people. As universal ‘test‐and‐treat’ becomes reality, the numbers initiating ART will rise. One group who will continue to pose significant treatment challenges are adolescents either graduating from paediatric care or newly established on ART treatment who may encounter treatment fatigue with an associated risk of failure. Unlike in the early days of ART where saving lives was the primary objective, we are entering a phase where VL testing is essential in order to successfully maintain people on long‐term ART to ensure the promise of universal treatment scale‐up. VL testing scale‐up is critical in all groups, yet, focusing on adolescents for initial operational research and scale‐up will allow targeted investigation into optimum ways of integrating VL monitoring into differentiated models of care, cost‐effectiveness and evaluating how this cost can be weighed against other HIV prevention and care programme priorities for this vulnerable group.The authors do not have any competing interests to declare.All authors contributed to writing and review, and all approved the final version.


The affiliation for the second author is incorrect. Melania Scarpa is not affiliated with #1 but with Veneto Institute of Oncology IOV–IRCCS, Padova, Italy.


Tetrax tetrax) and the great bustard (Otis tarda) using a multidimensional niche approach with habitat distribution data. We explored whether the degree of niche overlap between the species was a density‐dependent function of interspecific competition. We then looked for evidences of ecological release by comparing measures of niche breadth and position of the little bustard between allopatric and sympatric situations. Furthermore, we evaluated whether niche shifts could depend not only on the presence of great bustard but also on the density of little and great bustards. The habitat niches of these bustard species partially overlapped when co‐occurring, but we found no relationship between degree of overlap and great bustard density. In the presence of the competitor, little bustard's niche was displaced toward increased use of the species' primary habitat. Little bustard's niche breadth decreased proportionally with great bustard density in sympatric sites, in consistence with theory. Overall, our results suggest that density‐dependent variation in little bustard's niche is the outcome of interspecific competition with the great bustard. The use of computational tools like kernel density estimators to obtain multidimensional niches should bring novel insights on how species' ecological niches behave under the effects of interspecific competition in ecological communities.Interspecific competition is a dominant force in animal communities that induces niche shifts in ecological and evolutionary time. If competition occurs, niche expansion can be expected when the competitor disappears because resources previously inaccessible due to competitive constraints can then be exploited . Here, we aimed to determine the potential effects of interspecific competition between the little bustard ( Legume crops  are also cultivated although not in all the study sites or years. Other minor land uses are vineyards Vitis vinifera, olive groves Olea europaea, almond orchards Prunus dulcis, pastures, and urbanized areas. The little bustard was present in all study sites whereas the great bustard was absent in La Solana, Bellmunt, and Belianes. This fact allows for the evaluation of differences in niche breadth and position between allopatric and sympatric situations.This study was conducted in nine different sites across Spain between 2006 and 2012. Seven sites were located in central Spain and two in the northeast  cereal; (2) ploughed field; (3) leguminous crop; (4) 1‐year fallow ; (5) fallow older than 2 years and short shrubland ; (6) dry woody culture, including olive groves, vineyards, and almond tree orchards; and (7) others, which encompasses minority substrates avoided by the species like urban areas, or forests.2.3We generated the multidimensional niche hyperspace of these bustard species using information on habitat cover. Study sites are often arbitrarily delimitated, and areas falling outside the local distribution of the species may be included within the study site boundaries. This fact can bias measurements of habitat composition or estimates of species density . We similarly built KDEs only with random points creating “environmental niches” in order to control for the effects of habitat availability on little bustard habitat niche (n = 26). We built two‐dimensional KDEs for possible combinations of pairs of PC axes with ecological meaning for the species, instead of the one‐dimensional KDEs used in other studies  where little and great bustard co‐occurred and the number of bird observations allowed for KDE calculation . The calculation of niche overlap required that the two‐dimensional habitat niches of little and great bustard were estimated inside a common niche space and the probability density functions evaluated in the same points in order to be comparable. Therefore, we set the coordinates  of the two‐dimensional niche in which the probability density functions would be evaluated . Great bustard density for each study site and year was the number of all individuals observed, divided by the corresponding MCP area. We included study site as random factor in order to account for potential dependent effects between regions surveyed on several years.The effect of great bustard density on the degree of niche overlap between the species was analyzed using generalized linear mixed models (GLMMs) with Gaussian error distribution (n = 26 sites × year). In order to test the hypothesis of niche release, we used niche breadth and niche position  as the response variables, and the presence/absence of great bustard as the explanatory variable. We further analyzed whether intra‐ and interspecific density‐dependent effects caused niche variation, in order to evaluate the potential effects of density‐dependent competition using GLMMs. Niche breadth and position were used as response variables, and the explanatory variables were the density of little and great bustards inside the MCP. GLMMs testing potential density‐dependent competition only included those study sites and years where little and great bustards co‐occurred (n = 16 sites × year). In order to test for the functional response in habitat use, that is, the relative use depending on habitat availability  whereas Bellmunt showed the highest density . Great bustard density varied more than little bustard density within the MCP from 0.38 birds/km2 in Calatrava South to 20.85 birds/km2 in Valdetorres  being positively correlated with cereal cover, while the second axis PC2) was positively correlated with the cover of ploughed fields but negatively correlated with the surface of young fallows, indicating a gradient of management of annual fallow .The habitat niches of the little and the great bustard partially overlapped for the two‐dimensional niche spaces  may be small to clearly separate the effects of intra‐ and interspecific competition. These results should encourage future studies that tease apart the relative importance of intra‐ and interspecific competition.Contrary to theoretical predictions stating that intraspecific competition should expand the species niche because of a diversification of resource use (Svanbäck & Bolnick, The little bustard habitat niche also depends on the particular landscape composition. More precisely, the availability of cereals and young fallows within the landscape affects little bustard niche breadth and position Tables  and 4. TOur findings add new empirical evidence to the effects of competition on these bustard species. However, we acknowledge that this study has exclusively centered on the potential effects of competition on the habitat niche of little bustard males. Although results do not allow us to clarify whether great bustards also affect the habitat niche of little bustard females, this possibility should be borne in mind. Shared preferences between males and females of little bustard for particular habitats like fallows have been documented at landscape scale (e.g., Morales, Traba, Delgado, & García de la Morena, Under the current disappearance of nonproductive agrarian substrates and the recovery of the superior great bustard competitor (whose numbers have recently increased in many areas of Spain (Alonso & Palacín, This is the first study addressing interspecific density‐dependent competition, habitat use, and species niche adjustments using a multidimensional niche method. Overall, our findings suggest that these bustard species are currently competing, perhaps induced by the recent changes in the dynamics of agricultural landscapes due to agricultural intensification. Most importantly, our study reveals density‐dependent effects of intra‐ and interspecific competition on a species' habitat niche, a fact that is still poorly understood. Our two‐dimensional habitat niche approach highlights relevant aspects of the quantification of species niche using kernel density estimators. The selection of niche dimensions is an important step in evaluating the role of interspecific competition in niche shifts and must rely on detailed knowledge of the species' ecological requirements. Empirical studies using computational tools which allow to easily obtain multidimensional niches should give more realistic insights on evolutionary and ecological processes shaping communities (Blonder et al., None declared.R.T., M.M, and J.T conceived and designed the study and the statistical analysis. All authors contributed to fieldwork. R.T. analyzed the data and wrote the article. All authors reviewed the manuscript at different stages, and their wise comments greatly improved the scientific quality of the article. Click here for additional data file.


Hum Brain Mapp 37:4597–4614, 2016. © The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.This article describes the first application of a generic  Bayesian analysis of between‐subject effects in the dynamic causal modeling (DCM) of electrophysiological (MEG) data. It shows that (i) non‐invasive (MEG) data can be used to characterize subject‐specific differences in cortical microcircuitry and (ii) presents a validation of DCM with neural fields that exploits intersubject variability in gamma oscillations. We find that intersubject variability in visually induced gamma responses reflects changes in the excitation‐inhibition balance in a canonical cortical circuit. Crucially, this variability can be explained by subject‐specific differences in intrinsic connections to and from inhibitory interneurons that form a pyramidal‐interneuron gamma network. Our approach uses Bayesian model reduction to evaluate the evidence for (large sets of) nested models—and optimize the corresponding connectivity estimates at the within and between‐subject level. We also consider Bayesian cross‐validation to obtain predictive estimates for gamma‐response phenotypes, using a leave‐one‐out procedure.  The functional significance of cortical gamma band activity speaks to several important issues: including its ability to coordinate communication among neural populations, for example, those involved in attending to a particular stimulus Fries, , bindingOur focus here is on explaining intersubject variability in visual gamma responses in terms of cortical structure and function. In particular, we address the following question: which neurobiological mechanisms might explain differences in visually induced gamma oscillations recorded in different individuals and what is the role of intrinsic connections? This is the first application of empirical Bayes for dynamic causal modeling (DCM)  is a vector of coefficients that weights the contributions of each neuronal population to the observed MEG signal. Here, gu(ω) is a spatiotemporal representation of fluctuations or inputs driving induced responses, which we assume to be spatially white and a mixture of white and pink temporal components. These contributions are based on differences in anatomical properties and the lead field configuration of each population , where each electrode or sensor has its own sensitivity profile, reflecting the topographic structure of the underlying cortical source.Here, gu(ω) and transfer functions T) that depend on model parameters at the first or within‐subject level: θ(1). The transfer functions T) are the Fourier transform of the impulse response or first‐order Volterra kernel associated with (ordinary or integro) differential equations in Eq. φ⊂θ(1) and the spectra of the inputs and channel noise, {αn,αu,βn,βu}⊂θ(1). In this (single source ‐ single sensor) setup, Eq. Equation s Tk,ω,θ that dep T that deg(ω) as a mixture of predictions and sampling errors ɛ(1) with covariance Σ. Gaussian assumptions about these sampling errors provide the likelihood model at the first (within‐subject) level: p(g(ω)|θ(1)). The predictions are themselves a mixture of predicted cross spectra g⌢(ω) and channel noise gn(ω). This concludes the description of the likelihood model. We next consider how this likelihood model is placed within a hierarchical model of responses from multiple subjectsIn summary, Eq. empirical Bayesian models. Common examples are PEB models, in which random effects are assumed to be Gaussian (as above). Effectively, hierarchical models equip subject‐specific or first‐level models with empirical priors that optimally shrink parameter estimates to a group mean. This approach distinguishes between (first‐level) models that generate subject‐specific data and (second‐level) linear models that contain explanatory variables at the between‐subject level.In a Bayesian context, hierarchical models are known as Equation In our case, the first (subject‐specific) level Eq.  is givenX is a design matrix describing between‐subject effects and ɛ(2),ɛ(3) represent random effects at higher levels . To model differences among subjects, we have to specify phenotypic differences among subjects . Here, we will characterize subjects in terms of their characteristic gamma responses using three proxies (see below). These explanatory variables or phenotypes constitute the design matrix X. The Kronecker tensor product with the identity matrix X⊗I means that we have a second level parameter for every second level (phenotypic) variable and every first level (connectivity) parameter. This means one can identify the combination of connectivity parameters and phenotypic variables that best explains intersubject variability. This is addressed using Bayesian model reduction (or comparison) over (second level) models (after inverting a DCM for each subject). We perform an exhaustive search over all possible (reduced) models where one or more second level parameters have been removed. In other words, we create a large model space that includes all reduced models; in which every combination of effects is suppressed, using precise shrinkage priors.Here, The data modeled below were taken from a previous study  was present continuously and participants were instructed to maintain fixation on the square throughout. Stimuli were positioned so that their top right‐hand corner always coincided with fixation. This ensured that the stimuli were presented in the lower‐left visual quadrant, thereby precluding source cancellation across primary visual cortex representing different visual quadrants.Each trial comprised a 1,500 ms baseline period, in which only the fixation square was present. This was followed by a stimulus for a random duration between 1,000 and 1,500 ms, followed by a 1,000 ms response period; resulting in a total trial time of 3,500–4,000 ms. Gratings were presented at one of three different sizes—2°, 4°, and 8°—and participants were instructed to indicate which of the three different sizes had been presented by pressing one of three buttons using their right hand during the response period . Participants viewed 100 trials per condition , and trials were presented in random order.Whole‐head MEG recordings were acquired using a 275‐channel CTF radial gradiometer system sampled at 1,200 Hz. An additional 29 reference channels were recorded for noise cancellation purposes, and the primary sensors were analyzed as synthetic third‐order gradiometers [Vrba and Robinson, Several studies have concluded that gamma responses depend crucially on various input features, for example, orientation [Frien et al., F = 0.034, P = 0.72). Next the authors asked whether the amplitude of the gamma‐band response was affected by the size of the stimulus. To test this, they identified the peak frequency of response independent of condition  and measured the change in source amplitude (relative to baseline) at this frequency for each condition (only data from 0.5 to 1 s were included). Figure F = 18.1, P = 0.00002), where, quantitatively, average gamma‐band response rose approximately linearly with log stimulus size.This article focuses on individual differences in gamma responses elicited by vertically oriented gratings of different sizes. Here, we use visually induced V1 responses in the 30–80 Hz range reported in [Perry et al., F,22 = 0.0Figure In summary, Figure In what follows, we tested this hypothesis, with a special focus on identifying the particular connections and neuronal populations responsible for intersubject differences. We inverted the hierarchical model in Eq. Our goal was to identify which (connectivity) parameters—in particular, intrinsic connections—subtend intersubject variability in observed gamma responses. To make inferences about intersubject differences, it is necessary to use a hierarchical model that accommodates within and between subject effects, such as Eq. Our hierarchical model treated intrinsic connectivity as a random (between‐subject) effect, which was modeled by adding random Gaussian effects to subject‐specific parameters as is standard in DCM models for Cross Spectral Densities [Moran et al., The synaptic or connectivity parameters describing cortical microcircuitry are considered to mediate systematic group differences  we will use to characterize subject‐specific differences. In this application, we used three proxies to describe phenotypic variations between subjects; namely, the change in amplitude of gamma responses with increasing stimulus size, the peak frequency over all stimuli and the amplitude of gamma responses (based on the maximum amplitude across stimuli): These are the proxies used in [Perry et al., spm_dcm_bmc_peb.m).3 = 8 plausible hypotheses or models: see bottom left of Figure spm_dcm_peb_fit.m). Crucially, this empirical Bayesian approach is implemented so that one can compare different second level models without having to repeat the inversion of each subject's DCM. This can be thought of as a generalization of the standard summary statistic approach.To ensure that one or more of the between‐subject explanatory variables were necessary to explain observed responses, we first compared all combinations of the three explanatory variables and assessed the model evidence, pooled over subjects . In other words, we considered all possible hypotheses: each assuming a different combination of the connectivity parameters (see Table This Bayesian model comparison assesses the importance of different (combinations of) explanatory variables; however, this does not tell us which intrinsic connections are important for mediating individual differences. To address this, we then performed an exhaustive search over models examining all combinations of second level parameters. The second level parameters include the effects of the three explanatory variables on each of the (10) intrinsic connections , all the connections—that have been identified as mediating between subject effects—involve II. For example, intrinsic connections three, six and nine correspond to intrinsic connections from II to SS populations, deep pyramidal cells to II, and II to deep pyramidal cells respectively. Interestingly, the intrinsic connectivity from deep pyramidal cells to II  where all possible combinations of these parameters might explain group differences and evaluated the evidence for these hypotheses using data from multiple subjects. Our results suggest that group variability emerges from differences in intrinsic connections that reflect individual differences in the excitation to inhibition balance.In the above analysis, we used empirical Bayes to equip the (first level) DCM parameters with optimal shrinkage priors to explain group effects in gamma response variability. In brief, we found that individual differences are mediated primarily by connections to and from the II. In the last analysis, we consider an alternative use of these (shrinkage) priors; namely, we treat empirical priors obtained by inverting a group of (training) subjects as full priors when inverting a new (test) subject that belongs to the same group. In other words, we evaluate the posterior belief about a model parameter in an unknown (test) subject  and parameter estimates from the remaining subjects. In other words, we used all but one subject to estimate the model parameters (changes in effective connectivity) that best explained intersubject variations in spectral response to stimulus sizes. These estimates allowed us to use the parameter estimate from the “left out” subject to predict their spectral responses ; based on, and only on, effective connectivity changes. By comparing the predicted and actual spectral responses for every “left out” subject, we can therefore establish an unbiased (out‐of‐sample') correlation between the effective connectivity and spectral phenotype.In contrast to the analyses above, this approach reverses the roles of explanatory variables and model parameters in the design matrix—and can be used to establish the predictive validity of DCMs. This approach also allows us to quantify the extent to which connectivity from deep pyramidal cells to II  explains intersubject differences in gamma responses. We used a leave one out scheme to provide a posterior predictive density over a range of gamma response changes. This provides an out‐of‐sample estimate of the intersubject variance that can be explained by just knowing a single (DCM estimate of) intrinsic connection strength. This analysis also serves as a cross validation because the posterior predictive density is based on independent data (in the leave one out scheme).spm_dcm_loo.m). The left panel shows the true and (out‐of‐sample) predicted gamma response change . The shaded area represents the 90% Bayesian confidence intervals. These estimates are predictive in the sense that they are based on data that did not include the subject being predicted. In other words, these represent out‐of‐sample estimates that reflect what would happen if we were just given the estimate of intrinsic connectivity from a new subject. The correlation between the expected and the observed response change was 0.46, which means one could explain over 20% of intersubject variability in stimulus size selective gamma responses, given the posterior estimate of intrinsic connectivity from deep pyramidal cells to II. The significance of this correlation was trend significant (P = 0.06) and can be regarded as a cross‐validation accuracy verification of the Bayesian model reduction. Note that although the significance of this correlation is only trend significant (P < 0.06) it reflects a conservative out‐of‐sample correlation. In other words, this is the correlation we would expect with a new cohort of independent subjects based on the parameters estimates from the current subjects.Figure In addition to predicting phenotypic traits using cross validation, one can also use the optimized model to generate physiological responses (at the single subject or group level). This can be useful for examining how various connectivity (or condition‐specific changes) contribute to observable spectral responses. Indeed, generating predicted responses from optimized DCM can also be used to ask which data features are important for informing estimates of specific model parameters.Biophysical modeling of brain activity has a long history Coombes,  and has Here, we used an important class of biophysical models called ‘neural fields’ in the DCM framework to characterize individual differences in induced responses in the gamma band during a visual perception experiment. In this analysis, neural fields constitute the first level of a hierarchical Bayesian model, acting like a filter that receives spatially uncorrelated  noise as temporal input and produces output spectra; notably in the gamma band. Modulations of these responses across individuals reveal differences in subject‐specific anatomy and physiology captured by the neural field parameters. In particular, we asked whether variability in stimulus size, tuning, and gamma responses can be explained by intersubject differences in intrinsic connections forming a PING network. We found strong evidence in non‐invasive  data for this hypothesis. Furthermore, Bayesian model comparison (at the between‐subject level) identified the connections accounting for intersubject variability and these were exclusively to and from II. This finding is supported by a number of theoretical and empirical lines of argument: we focus on three perspectives that explain why inhibitory connections are implicated in visually induced gamma responses:First, from a theoretical perspective, one can appeal to a predictive coding explanation for individual differences in gamma band activity: in this setting, size effects may be mediated by changes in cortical excitability and, ultimately, the gain of pyramidal cell populations [Adesnik et al., Physiologically, the changes in the post‐synaptic gain of neuronal populations are most likely due to changes in local inhibition in a manner reminiscent of PING models [Traub et al., These gain control mechanisms may also mediate surround suppression—through changes in spatial integration properties. In the primary visual cortex, excitatory and inhibitory pools of neurons are proximally located and connected through elongated axonal collaterals. This implies that the boundary between the effective extent of excitation and inhibition—the relative densities of neurons of different types that are activated for various stimuli—is flexible. This can also reveal the functional specificity of gamma rhythms for different stimulus sizes and suggest an approximate distance over which local generators might show synchronization [Leopold et al., Our findings are also in accord with recent computational work modeling the emergence of gamma power peaks in the visual cortex based on an inhibition‐stabilized network [Jadi and Sejnowski, The neurobiological mechanisms considered above highlight the central role of inhibitory connectivity in generating gamma response variability [Cardin et al., This article serves to introduce hierarchical modeling for DCM studies of electromagnetic responses. Our example focused on the underlying connectivity generating responses to visual stimuli (of the same size)—trying to explain intersubject variability in (intrinsic) connectivity, in terms of subject specific differences in gamma responses to stimuli (of different sizes). More refined analyses of intersubject variability could consider the effect of stimulus size on intrinsic connectivity. In other words, one can apply the same procedures not just to connectivity but to context‐sensitive changes in connectivity elicited at the within subject level. In the present example, this would involve fitting responses to all three stimulus sizes and parameterizing the effect of stimulus size on intrinsic connectivity: see Pinotsis et al  for an eThe analysis showcased in this work uses a general empirical Bayesian framework for model comparison at the group level: see [Friston et al.,


Two types of immune checkpoint inhibitors, both antibodies that target cytotoxic T‐lymphocyte antigen‐4 and those that target programmed cell death‐protein 1, have been approved for use in melanoma, non‐small‐cell lung cancer, and renal cell carcinoma as first‐line or second‐line therapy. Their adverse events are primarily regarded as immune‐related adverse events. We felt it was important to pinpoint and discuss certain preconceptions or misconceptions regarding thyroid dysfunction, hypophysitis, and diabetes induced by immune checkpoint inhibitors. We have identified areas of uncertainty and unmet requirements, including essential interaction between endocrinologists and oncologists. Five issues have been identified for discussion: (1) diagnosis of endocrine toxicity, (2) assessment of toxicity severity, (3) treatment of toxicity, (4) withdrawal or continuation of immunotherapy, (5) preventive action. Cancer immunotherapy using anticytotoxic anti‐T‐cell antigen‐4 (CTLA4) antibodies (anti‐CTLA4) or anti‐programmed cell death‐protein1 (PD1) antibodies (anti‐PD1) have been approved for melanoma, non‐small‐cell lung cancer, and renal cell carcinoma and are also under investigation with respect to various other cancer types. These antibodies are directed against inhibitory and costimulatory molecules and result in activation of the immune system, in order to enhance tumor immunity. Cancer immunotherapy has improved progression‐free survival and overall survival in these tumors Oncologists have started to address these new irAEs over the past 10 years, and much has been learnt in certain situations such as intestinal irAEs. Frequent toxicities directed against the endocrine glands target the pituitary gland, the thyroid, and the pancreas A review of randomized studies shows that ICPI may induce “endocrine toxicity” such as thyroid dysfunction, hypophysitis, or diabetes. However, information relating to these endocrine toxicities is often scarce and imprecise The laboratory tests used to monitor thyroid function raise significant concerns. TSH measurement is the routine basal test used to evaluate thyroid status. However, ICPI‐related hypophysitis has been reported, especially in ipilimumab therapy The second example refers to “adrenal insufficiency”. This toxicity was reported in 1% to 3% of patients. The use of CTCAE is recommended when grading the severity of adverse events resulting from all types of therapy, including cancer therapy. Endocrine adverse events, including severe events (≥grade 3), are described in ICPI treatment It is difficult to discern whether hypophysitis constitutes a severe event. Unrecognized pituitary insufficiency can be life‐threatening due to corticotropic deficiency, whereas hormone replacement in acknowledged pituitary failure is uncomplicated. Only pituitary stalk enlargement associated with compression of the optic chiasm should, in our opinion, be considered a severe adverse event. For this reason pituitary MRI should be performed in the event of suspected hypophysitis Diabetes mellitus is now reported as an adverse event in various types of anti‐PD1 β‐blockers seem adequate in managing the thyrotoxic phase of thyroiditis Because ICPI modulate immune responses, high‐dose corticosteroid treatment is proposed. This strategy is proposed in gastrointestinal or liver toxicity High‐dose corticosteroids are recommended in the treatment of hypophysitis This question is of importance when ICPI treatment is effective. Surprisingly, the discontinuation or continuation of ICPI has not been systematically debated in recent reviews To avoid severe endocrine adverse events, the most effective strategy is necessarily a preventive one. In view of the scarcity of systematic prospective data on ICPI endocrine adverse events, in our opinion, no objective recommendations can be made. Either we can use current guidelines of package inserts of molecules or we can propose a new algorithm based on clinical experience and limited data. In our systematic hormonal blood test evaluation (data as yet unpublished), we observe highly precocious thyroid disorders after the first or second injection of ICPI. Central glucocorticoid insufficiency (due to hypophysitis) may also occur. Currently, ipilimumab package inserts merely recommend thyroid function test and ACTH evaluation before initial and each subsequent ipilimumab injection Objective recommendations for follow‐up are problematic because information on the timing of adverse event onset is often absent from large trials Although certain endocrine adverse events are frequent during cancer immunotherapy, their management is relatively uncomplicated. A concerted approach by endocrinologists and oncologists is essential in order to determine the degree of severity of adverse events, establish the best course of treatment, and opt whether to continue or interrupt immunotherapy. In our view, clinical and biochemical screening of endocrine toxicity would improve our knowledge of physiopathological mechanisms as well as help modify our management and in preventing severe events, as is currently the case in toxicity induced by tyrosine kinase inhibitors. Our primary objective must remain the treatment of aggressive forms of cancer and the preservation of an acceptable quality of life for patients None declared.


To assess the efficacy of vaginal progesterone for the prevention of preterm birth and neonatal morbidity and mortality in asymptomatic women with a twin gestation and a sonographic short cervix  in the mid‐trimester.This was an updated systematic review and meta‐analysis of individual patient data (IPD) from randomized controlled trials comparing vaginal progesterone with placebo/no treatment in women with a twin gestation and a mid‐trimester sonographic cervical length ≤ 25 mm. MEDLINE, EMBASE, POPLINE, CINAHL and LILACS , the Cochrane Central Register of Controlled Trials, Research Registers of ongoing trials, Google Scholar, conference proceedings and reference lists of identified studies were searched. The primary outcome measure was preterm birth < 33 weeks' gestation. Two reviewers independently selected studies, assessed the risk of bias and extracted the data. Pooled relative risks (RRs) with 95% confidence intervals (CI) were calculated.vs 43.1%; RR, 0.69 ; moderate‐quality evidence). Moreover, vaginal progesterone administration was associated with a significant decrease in the risk of preterm birth < 35, < 34, < 32 and < 30 weeks' gestation (RRs ranging from 0.47 to 0.83), neonatal death ), respiratory distress syndrome ), composite neonatal morbidity and mortality ), use of mechanical ventilation ) and birth weight < 1500 g ) . There were no significant differences in neurodevelopmental outcomes at 4–5 years of age between the vaginal progesterone and placebo groups.IPD were available for 303 women  and their 606 fetuses/infants from six randomized controlled trials. One study, which included women with a cervical length between 20 and 25 mm, provided 74% of the total sample size of the IPD meta‐analysis. Vaginal progesterone, compared with placebo/no treatment, was associated with a statistically significant reduction in the risk of preterm birth < 33 weeks' gestation (31.4% Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.Administration of vaginal progesterone to asymptomatic women with a twin gestation and a sonographic short cervix in the mid‐trimester reduces the risk of preterm birth occurring at < 30 to < 35 gestational weeks, neonatal mortality and some measures of neonatal morbidity, without any demonstrable deleterious effects on childhood neurodevelopment. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.  Twin births have become more prevalent in developed countries over the last decadesPreterm birth is the most important factor determining neonatal morbidity and mortality among twins. The risk of preterm birth < 37 and < 32 weeks' gestation is eight‐ to ninefold higher in twin than in singleton gestationsA short cervix, traditionally defined as a transvaginal sonographic cervical length (CL) ≤ 25 mm in the mid‐trimester of pregnancy, is an important risk factor for spontaneous preterm birth and has emerged as one of the strongest and most consistent predictors of preterm birth in asymptomatic women with singletonA meta‐analysis of individual patient data (IPD) published in 2012 reported on the efficacy of vaginal progesterone in preventing preterm birth and neonatal morbidity and mortality in asymptomatic women with a twin gestation and a CL ≤ 25 mm in the mid‐trimesterThe objective of this study was to update the previous IPD meta‐analysis on the efficacy of vaginal progesterone in asymptomatic women with a twin gestation and a sonographic CL ≤ 25 mm in the mid‐trimester for the prevention of preterm birth and neonatal morbidity and mortality.The study was conducted according to a prospectively prepared protocol and reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta‐Analyses statementprogesterone’, ‘preterm birth’, ‘randomized controlled trial’ and ‘twin gestation’. Google Scholar, proceedings of congresses on obstetrics, maternal‐fetal medicine and ultrasound in obstetrics, reference lists of identified studies, previously published systematic reviews and review articles were also searched. Experts in the field were contacted to identify further studies. No language restrictions were applied.We searched MEDLINE, EMBASE, POPLINE, CINAHL and LILACS , the Cochrane Central Register of Controlled Trials and Research Registers of ongoing trials using a combination of keywords and text words related to ‘RCTs in which asymptomatic women with a twin gestation and a sonographic short cervix (CL ≤ 25 mm) in the mid‐trimester were allocated randomly to receive vaginal progesterone or placebo/no treatment for the prevention of preterm birth and/or adverse perinatal outcomes were eligible for inclusion in the review. Trials were included if the primary aim of the study was to prevent preterm birth in women with a twin gestation and a short cervix, or to prevent preterm birth in women with an unselected twin gestation but for whom outcomes were available in those with a prerandomization CL ≤ 25 mm. We excluded quasirandomized trials, trials that evaluated vaginal progesterone in women with preterm labor, arrested preterm labor (as maintenance tocolysis), preterm rupture of membranes or second‐trimester bleeding, trials that assessed vaginal progesterone in the first trimester only to prevent miscarriage and studies that did not report clinical outcomes. Studies published only as abstracts were excluded if additional information on methodological issues and results could not be obtained.All of the potentially relevant studies were retrieved and reviewed independently by two authors to determine inclusion. Disagreements were resolved by discussion amongst the reviewers.The corresponding author of each eligible trial was contacted and asked to provide anonymized data (without identifiers) about baseline characteristics and outcomes for every randomly assigned patient, as well as data on study characteristics and details of interventions and co‐interventions. All initial communications with authors were based on a template explaining the study and the data required. Data provided by the investigators were merged into a master database specifically constructed for the review. Data were checked for missing information, errors and inconsistencies by cross‐referencing with the publications of the original trials. Quality and integrity of the randomization processes were assessed by reviewing the chronological randomization sequence and pattern of assignment, as well as the balance of baseline characteristics across treatment groups. Inconsistencies or missing data were discussed with the authors and corrections were made when deemed necessary.Informed consent was provided by the patients upon enrollment in each of the original trials. In the present study, the data were not used for any purposes other than those of the original trial and no new data were collected. Therefore, informed consent specifically for this project was not considered necessary. This study was exempted from review by the Human Investigation Committee Administration Office of Wayne State University.The primary outcome measure was preterm birth < 33 weeks' gestation. Secondary outcome measures included: preterm birth < 37, < 36, < 35, < 34, < 32, < 30 and < 28 weeks' gestation; spontaneous preterm birth < 33 and < 34 weeks' gestation; respiratory distress syndrome (RDS); necrotizing enterocolitis; intraventricular hemorrhage; proven neonatal sepsis; retinopathy of prematurity; fetal death; neonatal death; perinatal death; a composite outcome of neonatal morbidity and mortality ; birth weight < 1500 g and < 2500 g; admission to the neonatal intensive care unit; use of mechanical ventilation; and long‐term neurodevelopmental outcomes .Cochrane Handbook for Systematic Reviews of InterventionsThe risk of bias in each included trial was assessed independently by two authors using the criteria outlined in the I2. We pooled results from individual studies using a fixed‐effect model if substantial statistical heterogeneity was not present (< 50%). If I2 values were ≥ 50%, a random‐effects model was used to pool data across studies. For adverse perinatal outcomes, we estimated pooled RRs using analytical methods that assumed independence between neonates. However, to avoid incorrect conclusions due to the non‐independence of newborns from twin gestations, we also used a generalized linear model with generalized estimating equations to estimate parameters while controlling for cluster correlationsWe included all randomized women and their fetuses/infants and performed all analyses on an intention‐to‐treat basis. For outcomes dealing with gestational age at delivery, the unit of analysis was the pregnancy, whereas for perinatal outcomes, the unit of analysis was the fetus/neonate. IPD were combined in a two‐stage approach in which outcomes were analyzed in the original trial and then summary statistics were generated using standard summary data meta‐analysis techniques to give an overall measure of effect (pooled RR with 95% CI)P‐value ≥ 0.05 was considered to indicate that the effect of treatment did not differ significantly among subgroups. We planned to carry out sensitivity analyses to explore the effect of trial quality assessed by allocation concealment and random sequence generation (considering selection bias) and blinding (considering performance and detection biases), with studies rated as ‘high risk of bias’ or ‘unclear risk of bias’ for these domains being excluded from the analyses in order to assess whether this made any difference to the overall result. Subgroup and sensitivity analyses were only performed for the primary outcome of preterm birth < 33 weeks' gestation and for the secondary outcome of neonatal death. We also planned to explore potential sources of heterogeneity and to assess publication and related biases if at least 10 studies were included in a meta‐analysis, but these analyses were not undertaken due to the limited number of trials included in the review.Subgroup analyses were performed to evaluate the effect of vaginal progesterone according to CL , daily dose of vaginal progesterone  and obstetric history (no previous spontaneous preterm birth < 37 weeks' gestation and at least one previous spontaneous preterm birth < 37 weeks' gestation). A test for interaction between the treatment and subgroups was performed to examine whether treatment effects differed among subgroupsGRADE HandbookWe used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, as outlined in the We performed all statistical analyses using Review Manager  and SAS version 9.2  software.in‐vitro fertilization or intracytoplasmic sperm injectionFigure The individual characteristics of the studies included in the meta‐analysis are shown in Table et al.Three studies used vaginal progesterone 200 mg/day capsule, one useet al.The risk of bias in each included study is summarized in Figure vs 43.1%; RR, 0.69 ; P = 0.01; I2 = 0%; six studies, 303 women; moderate‐quality evidence) compared with those allocated to placebo/no treatment ; moderate‐quality evidence), perinatal death ; moderate‐quality evidence), RDS ; moderate‐quality evidence), composite neonatal morbidity and mortality ; moderate‐quality evidence), birth weight < 1500 g ; moderate‐quality evidence) and use of mechanical ventilation ; moderate‐quality evidence) . Nonetheless, vaginal progesterone was associated with a statistically significant reduction in the risk of preterm birth < 33 weeks' gestation and neonatal death in women with a CL between 10 and 20 mm  and 0.20 , respectively) and women who were administered 400 mg of daily vaginal progesterone  and 0.42 , respectively). Moreover, vaginal progesterone significantly decreased the risk of neonatal death in women with a CL between 21 and 25 mm ) and women with no previous spontaneous preterm birth ).Subgroup analyses of the effect of vaginal progesterone on preterm birth < 33 weeks' gestation and neonatal death, according to CL, daily dose of vaginal progesterone and obstetric history, are shown in Table When the sensitivity analysis was restricted to the five trials with adequate blinding of patients, clinical staff and outcome assessorsn = 225) or placebo (n = 212), at a mean age of 57 monthsP = 0.03), although there was no statistically significant difference in the risk of low ASQ score (< 10th percentile) between the study groups ). A subgroup analysis showed that dichorionic twins who were exposed prenatally to vaginal progesterone had a significantly lower risk of having a low total ASQ score than those who were exposed to placebo ).No study has reported the effects of vaginal progesterone on long‐term neurodevelopmental outcomes in twin gestations with a short cervix. Thus far, two trials have reported the effects of prenatal exposure to vaginal progesterone on long‐term neurodevelopmental outcomes in unselected twin gestationsThe main finding in this updated IPD meta‐analysis is that the administration of vaginal progesterone to asymptomatic women with a twin gestation and a mid‐trimester sonographic short cervix significantly reduces the risk of preterm birth < 33 weeks' gestation (primary outcome) by 31% and neonatal death by 47%. In addition, patients who received vaginal progesterone had a significantly decreased risk of preterm birth < 35, < 34, < 32 and < 30 weeks, spontaneous preterm birth < 33 and < 34 weeks, perinatal death, composite neonatal morbidity and mortality, RDS, birth weight < 1500 g and use of mechanical ventilation. Moreover, evidence from two trials that assessed vaginal progesterone in unselected twin gestations showed that there were no significant differences in the risk of neurodevelopmental disability at 4–5 years of age between children exposed prenatally to vaginal progesterone and those exposed to placebo.Evidence for most critical outcomes assessed with GRADE methodology was considered to be of moderate quality (Table S1). We downgraded the evidence from high quality to moderate quality because most of the pooled effect was provided by one study with moderate risk of bias. A judgment of moderate quality means that we have some confidence that our results approach the true impact of vaginal progesterone on preterm birth and adverse neonatal outcomes in twin gestations with a short cervix; at the same time, we acknowledge that future trials may change these results.We evaluated several clinically important subgroups based on CL, daily dose of vaginal progesterone and history of spontaneous preterm birth. Overall, subgroup analyses indicated that the beneficial effects of vaginal progesterone did not differ significantly across patient groups, as the interaction tests for subgroup differences were non‐significant. Patients with a CL between 10 and 20 mm or those who received vaginal progesterone 400 mg/day seemed to have a greater‐than‐average reduction in the risk of preterm birth < 33 weeks' gestation and neonatal death. However, analyses of categories such as CL < 10 mm, daily dose of vaginal progesterone of 100 or 200 mg and history of spontaneous preterm birth were based on small numbers of women, reflecting the pattern of recruitment to the original trials, in which most women had a CL between 10 and 25 mm, used vaginal progesterone 400 mg/day and did not have a history of spontaneous preterm birth. As a result, our analysis was limited in its power to estimate effects within those groups of patients. Thus, although prespecified and clinically interesting, these subgroup analyses should be interpreted with caution.in‐utero exposure to vaginal progesterone, administered in twin gestations for the prevention of preterm birth, has no detrimental effects on long‐term neurodevelopmental outcomes. A total of 761 surviving children who participated in two placebo‐controlled trials of vaginal progesterone to prevent preterm birth in unselected twin gestationsCurrent evidence suggests that et al.et al.With regard to the effects of the prenatal exposure to vaginal progesterone on childhood health outcomes in twins, the follow‐up study by McNamara et al.et al.In our previous IPD meta‐analysisI2 = 0%), whereas the majority of meta‐analyses regarding adverse perinatal outcomes had low heterogeneity or no heterogeneity; and (iv) the sensitivity analyses restricted to trials at low risk of bias that were consistent with (and thus supportive of) the overall findings.The main strengths of our meta‐analysis include: (i) the use of patient‐level data, which offer several advantages over study‐level analysis, including the ability to use more appropriate statistical methods not always feasible using study‐level analysis, define outcome measures consistently across studies, investigate subgroups in which treatment may be either more or less effective, address questions that have not been satisfactorily resolved by individual trials, minimize publication and reporting biases and adjust for prognostic variables that may have confounded the original treatment comparisons; (ii) the baseline balance in prognostic factors between the two study groups, which reduces the possibility of causing bias in the intervention effect estimates; (iii) the absence of substantial heterogeneity in most of the meta‐analyses performed; indeed, all meta‐analyses on the effect of vaginal progesterone on preterm birth had no observed heterogeneity  or no treatment (NCT02329535) in ∼750 women with a twin gestation and a sonographic short cervix will help to determine whether vaginal progesterone can be recommended to these patients with the aim of preventing preterm birth and improving perinatal outcomes.Table S1 Summary of findings of the quality of evidence for each outcome measureClick here for additional data file.


Fetal cardiovascular magnetic resonance imaging (MRI) offers a potential alternative to echocardiography, although in practice, its use has been limited. We sought to explore the need for additional imaging in a tertiary fetal cardiology unit and the usefulness of standard MRI sequences.Cases where the diagnosis was not fully resolved using echocardiography were referred for MRI. Following a three‐plane localiser, fetal movement was assessed with a balanced steady‐state free precession (bSSFP) cine. Single‐shot fast spin echo and bSSFP sequences were used for diagnostic imaging.n = 10) and pulmonary vessels (n = 4). Single‐shot fast spin echo sequences produced ‘black‐blood’ images, useful for examining the extracardiac vasculature in these cases. BSSFP sequences were more useful for intracardiac structures. Real‐time SSFP allowed for dynamic assessment of structures such as cardiac masses, with enhancement patterns also allowing for tissue characterisation in these cases.Twenty‐two fetal cardiac MRIs were performed over 12 months, at mean gestation of 32 weeks (26–38 weeks). The majority of referrals were for suspected vascular abnormalities (17/22), particularly involving the aortic arch (Prenatal Diagnosis published by John Wiley & Sons, Ltd.Fetal vascular abnormalities such as coarctation can be difficult to diagnose by using ultrasound. Fetal MRI may have an adjunctive role in the evaluation of the extracardiac vascular anatomy and tissue characterisation. © 2016 The Authors.  What's Already Known About This Topic?Fetal cardiac MRI offers the potential to be a safe adjunct to echocardiography; however, there is no consensus on routine fetal indications or technical protocols for cardiovascular MRI in clinical practice. Previous studies have focused mainly on its utility for intracardiac imaging.What Does This Study Add?Abnormalities involving the extracardiac vasculature were the most common group of referrals for additional imaging in clinical practice. Fast spin echo MRI sequences offer the potential for better visualisation of these structures than ultrasound alone. Additional MRI benefits such as tissue characterisation can add further value in selected cases. Conventional fetal echocardiography is the mainstay for prenatal diagnosis of congenital cardiac lesions, based on its ease of use, availability and high diagnostic accuracy.Magnetic resonance imaging (MRI) has been an established adjunct for postnatal assessment of the cardiovascular system since the 1980s,The first report of attempted fetal cardiac MRI was in 2005, using real‐time sequences with an attempt to quantify ventricular volumes.The increasing use of MRI for prenatal evaluation of the fetal brainOver a one‐year period, fetal MRI was requested on clinical grounds by the fetal cardiology service, reserved for any difficult fetal cases where the diagnosis was in doubt or could benefit from additional imaging. We present an analysis of the pattern of referrals we subsequently observed and the diagnostic utility of standard MRI sequences in this context.Referrals were based on the judgement of the attending fetal cardiologists . All examinations took place between June 2014 and May 2015. Pre‐existing ethical approval was in place for a long‐standing project examining brain growth in fetuses with CHD, which also permitted the use of cardiac sequences (REC: 07/H0707/105). All participants provided written consent and received concomitant fetal brain imaging. The timing of the MRI was determined by the clinical teams, taking into account the gestational age at diagnosis, the potential impact of new information on fetal counselling and management, and the timeframe for optimal imaging quality . A paediatric cardiologist with expertise in cardiac MR was present at every study (RR or KP). Each mother's tympanic temperature was taken before and after the MRI or if they became uncomfortable during the study. Conservative limits of a rise in temperature of ≥1 °C and/or an absolute estimated temperature in the fetus of greater than 38 °C A large field of view (covering the whole fetus) bSSFP cine  scan with low spatial resolution but higher temporal resolution (303 ms) was used following the initial localiser sequence to demonstrate the degree of gross fetal movement.+4 weeks  and the average age at MRI was 31+3 weeks . Two twin pregnancies were included, each with one healthy and one affected twin.Twenty‐two fetal cardiac MRI examinations were performed over the referral period. The average gestational age at diagnosis 23The most common indications were for possible coarctation of the aorta in six patients, other arch abnormalities in four patients  and assessment of pulmonary vessels in four patients Table . In totaThree examinations failed to provide any useful cardiovascular information. In two cases, this was due to excessive fetal movement (at 29 and 33 weeks). In one case, assessment of the pulmonary veins in a 26‐week fetus was impossible due to severe lung compression from a large diaphragmatic hernia; however, this important prognostic information was used to help counsel the parents prior to the demise of the fetus at 29 weeks. No postnatal data were available in two cases . Autopsy was not performed in either case. In all remaining patients, the MRI diagnosis was confirmed postnatally. A comprehensive summary of all studies performed is shown in Table Single‐shot fast spin echo sequences produced T2‐weighted images with black‐blood‐like contrast with excellent contrast between the vasculature and higher signal intensity of the thymus, lung and myocardium. These sequences were the most useful for assessment of extra‐cardiac vascular anatomy as these structures are less mobile throughout the cardiac cycle Figures , 2, 3, 4Balanced SSFP images produced bright blood images with good contrast between the blood pool and surrounding tissue, particularly intracardiac structures Figures , 7, 8; hWe instituted an open referral process for fetal MRI in a tertiary UK fetal cardiac centre. Whilst previous explorations of the clinical utility of fetal cardiac MRI have focused predominantly on intracardiac anatomy,The single most frequent single referral indication in our series was for suspected coarctation of the aorta, a notoriously challenging condition to predict prenatally due to both the technical difficulty of imaging this region and the obligatory patency of the arterial duct in fetal life, the postnatal closure of which can only then reveal life‐threatening aortic constriction.In addition to vascular imaging, in three cases the combined use of SSFSE sequences provided the unique ability to characterise cardiac tumours before birth, a potential use of prenatal MRI with a high prognostic impact.Finally, it should also be noted that several of the MRI studies reported in our series concomitantly provided important complementary imaging that could directly or indirectly impact the cardiac prognosis, for example describing the devastating extent of pulmonary compression from a very large diaphragmatic hernia in a fetus that did not survive to term. Fetal MRI can also be used to assess lung parenchymal lesions and airway compromise in CHDAs we observed, even small fetal movements can disrupt the spatial relationship of multi‐slice sequences, making post‐hoc analysis extremely challenging. The application of novel motion‐corrected slice‐volume registration algorithms to multiple MRI image stacks has been used to generate accurate 3D volumes of the fetal thorax.Other advanced MRI techniques can offer novel means of evaluation of physiological parameters of the fetal heart and circulation. The application of retrospective ‘metric‐optimised’ gating to phase contrast sequences can be used to quantify vascular flows and is currently being explored in a wide variety of settings.These innovations will not only help to bring prenatal cardiovascular MRI closer to its postnatal counterpart but could also offer the potential to enhance our fundamental understanding of the nature and aetiology of congenital heart defects – including challenging prenatal diagnoses such as coarctation of the aorta – and their interactions with other organ systems such as the placentaAbnormalities of the fetal vasculature such as coarctation of the aorta can be challenging to diagnose with ultrasound, even in experienced hands. Standard sequence MRI may have an adjunctive role in the assessment of the extracardiac vascular anatomy and tissue characterisation. Developments such as motion‐corrected slice‐volume registration and metric‐optimised gated phase contrast flow quantification and real‐time techniques, alongside increasingly accessible infrastructure, may further develop the role of MRI as an adjunct to echocardiography in the investigation and diagnosis of congenital heart disease in the fetus.Fetal cardiac MRI offers the potential to be a safe adjunct to echocardiography; however, there is no consensus on routine fetal indications or technical protocols for cardiovascular MRI in clinical practice. Previous studies have focused mainly on its utility for intracardiac imaging.Abnormalities involving the extracardiac vasculature were the most common group of referrals for additional imaging in clinical practice. Fast spin echo MRI sequences offer the potential for better visualisation of these structures than ultrasound alone. Additional MRI benefits such as tissue characterisation can add further value in selected cases.We have described 22 cases that were selected for additional imaging from a single institution. Due to the increased likelihood of image corruption from uncontrolled fetal movement, we tended to perform additional imaging in the third trimester. Whilst our median gestational age of 33 weeks is comparable to other published series, this does represent a current limitation of the modality. As imaging was performed for clinical evaluation, the acquisition and interpretation of MRI images was not blinded to previous assessments. In two fetuses that did not survive to term, no autopsy information was available due to lack of parental consent.


Odocoileus virginianus) have been expanding their range into the North American boreal forest over the last half of the 20th century. This has already altered predator–prey dynamics in Alberta, Canada, where the distribution likely reaches the northern extent of its continuous range. Although current white‐tailed deer distribution is explained by both climate and human land use, the influence each factor had on the observed range expansion would depend on the spatial and temporal pattern of these changes. Our objective was to quantify the relative importance of land use and climate change as drivers of white‐tailed deer range expansion and to predict decadal changes in white‐tailed deer distribution in northern Alberta for the first half of the 21st century. An existing species distribution model was used to predict past decadal distributions of white‐tailed deer which were validated using independent data. The effects of climate and land use change were isolated by comparing predictions under theoretical “no‐change between decades” scenarios, for each factor, to predictions under observed climate and land use change. Climate changes led to more than 88%, by area, of the increases in probability of white‐tailed deer presence across all decades. The distribution is predicted to extend 100 km further north across the northeastern Alberta boreal forest as climate continues to change over the first half of the 21st century.Quantifying the relative influence of multiple mechanisms driving recent range expansion of non‐native species is essential for predicting future changes and for informing adaptation and management plans to protect native species. White‐tailed deer ( However, 19% of changes at the poleward and upper elevational range boundaries studied shifted in a direction that was inconsistent with changing climate  have been expanding their range into the North American boreal forest over the last half of the 20th century  abundance and elevated predation on threatened woodland caribou  from Dawe  predicting the presence of deer through that time period (hindcasting); and (4) testing the model predictions using independent data and standard validation metrics. The relative influence of climate change and land use factors was then investigated, using the time validated model and temporal manipulation of model covariates. Finally, covariates were extrapolated to facilitate future distribution predictions.The overall workflow for this analysis involved: (1) selecting an appropriate model to describe white‐tailed deer distribution; (2) 2 , jack pine (Pinus banksiana), trembling aspen (Populus tremuloides), and balsam poplar , and peatland complexes composed of shrub and fen wetlands, and black spruce (Picea mariana) and tamarack (Larix larcina) bogs. Mean temperatures from the warmest and coldest month are 15.7 and −19.2°C, respectively, and mean annual precipitation is 469 mm  (Anderson N = 127), the Integrated Landscape Management laboratory at the University of Alberta (N = 151) or a combined effort between these groups (N = 21). Two methods were used to collect the data: a 9‐km triangular‐shaped transect sampled on foot, and a 10‐km linear transect sampled on snowmobile . Long‐term averaged climate variables have been found to have higher predictive power than shorter term climate variables in ecological models and models containing long‐term averaged WSIswe variables outcompeted models containing WSIswe from the 2 years prior to sampling , which is the number of occurrences divided by the number of observations, is directly related to the model probabilities in a logistic regression model  is currently the most widely used metric to test the predictions of SDMs because it summarizes performance over a range of threshold values , were then subtracted from the correctly calculated 1980s probabilities. Conversely, to determine where climate was responsible for a change in probability between the 1970 and 1980 decades, we calculated the predicted probabilities for the 1980s using the land use footprint from 1980 and the climate data from the 1970s. The new probability grids, which assume no change in climate between 1970 and 1980 , were subtracted from the correctly calculated 1980s probabilities. Where subtracted values equaled zero in both cases, there was no change in probability between decades. Where the absolute value of the difference in probabilities was greatest for climate, climate was the driver of change for that grid cell, and where the absolute value of the difference in probabilities was greatest for land use, land use was the driver of change for that grid cell. This series of calculations was repeated for the changes between 1980 and 1990, and 1990 and 2000. We also identified where changes resulted in the predicted probability of presence crossing the prevalence threshold, theoretically, signifying a change from absence to presence.4th assessment report  and a range of likely outcomes developed in the 5th assessment report (RCP4.5 being most similar to the B1 scenario) suggest that linear changes in temperature and growing season length are likely  are based on general climate models (GCMs) developed at grid cell sizes ranging from 125 to 400 km and over monthly time periods  indicating the SDM model overestimates the proportion of occupied cells at high probabilities and underestimates the proportion of occupied cells at low probabilities. There is also a significant negative intercept  which indicates a tendency toward overestimating occurrence over all . This is consistent with the error found in the discrimination statistics.The calibration model had a significant positive slope , increasing land use intensity could also lead to white‐tailed deer spread. Northward expansion of the industrial footprint in Alberta is not currently expected Hamley ; howeverIt would be expected that as climate becomes more favorable, the distribution change should also follow the pattern of natural favorable habitat. Some studies have found that white‐tailed deer disperse along river corridors, although others have not found any association (Sparrowe and Springer The relative influence of climate change and land use on abundance may be different than that delineated here for presence. There is some expectation that the probability of detecting a species should increase as its abundance increases; however, it may be that climate change is a stronger facilitator of spread, through increased survival further northward, while land use, via provision of resources of varying quality and quantity, is a larger driver of abundance. A broad suite of factors are known to influence abundance, such as life history, competition, habitat quality, and site history, of which presence–absence models may be less influenced (Pearce and Ferrier The quality of resources for white‐tailed deer resulting from different land use footprints is likely patchy across the study area. Land use footprint was included in models as the cumulative total footprint; however, the individual industry contributions varied substantially over space and time (Dawe et al. The SDM predictions for past decades matched closely with the observed presences and absences from independent validation data; however, predictive power decreased as predictions were made further from the decade in which the model was built. This loss of predictive power appears to be related to the model's ability to predict absences. In 1970, only 38% of absences in validation data were predicted to be absences. This means 62% of absences in the data were predicted to have white‐tailed deer present. Araújo et al.  suggesteA trade‐off exists when including mechanistically informed climate variables in SDMs because the variables may not be included in GCM projections under future climate scenarios. Although projections from GCMs are based on varying parameterizations and complexity of atmospheric and ocean circulation systems, several authors have modeled change in climate variables over past decades using linear relationships (Stone et al. None declared.


In the early studies, human or porcine embryonic neural cells were grafted in the striatum of animals or patients in an attempt to replace lost neurons. Although the immune‐privileged status of the brain as a recipient organ was widely accepted, it rapidly became evident that CNS‐grafted allogeneic and xenogeneic cells could be recognized and rejected by the immune system, resulting in poor neural graft survival and limited functional recovery. Since then, the CNS transplantation field has witnessed a sharp rise in the number of studies in which allogeneic and xenogeneic neural or mesenchymal stem cells  are transplanted, predominantly aiming at providing trophic stimulation and promoting endogenous repair of the brain. Interestingly, in many recent NSC and MSC‐based publications functional improvement was used as the principal measure to evaluate the success of cell transplantation, while the fate of transplanted cells remained largely unreported. In this review, we first attempt to understand why primary neural cell isolates were largely substituted for NSCs and MSCs in cell grafting studies. Next, we review the current knowledge on the immune mechanisms involved in the recognition and rejection of allogeneic and xenogeneic cellular grafts in the CNS. Finally, we propose strategies to reduce graft immunogenicity and to improve graft survival in order to design improved cell‐based CNS therapies. S Recognition and understanding of the innate and adaptive immune mechanisms involved in immunological rejection of allogeneic/xenogeneic cellular grafts in the central nervous system is a major prerequisite for the design of improved off‐the‐shelf cellular therapies for brain disorders and traumata.Before the turn of the century, embryonic neural cells and/or dissociated neural tissue were the main sources of donor material used in central nervous system (CNS) transplantation studies, which predominantly focused on Parkinson's disease and Huntington's disease Direct cellular grafting into the CNS is a process that never goes unnoticed by the host's immune system, regardless of the origin of the transplanted cells The brain has long been considered an immunologically privileged site for transplantation owing to its distinctive architecture: while the (presumed) absence of conventional lymphatics was thought to prevent antigen drainage from CNS tissue to secondary lymphoid organs, the presence of a blood‐brain barrier (BBB) was believed to block immune cell entry into the CNS. Nevertheless, functional lymphatic vessels connecting the meninges to deep cervical lymph nodes were recently discovered, and activated T cells—but not naive T cells or antibodies—can readily cross the BBB in search of their cognate antigen Having been our laboratory's research focus for many years, we recently proposed a model of the sequential cellular events taking place shortly after intracerebral transplantation of syngeneic mesenchymal cell grafts, reviewed in detail in Le Blon et al. 3CR1‐eGFP x CCR2‐RFP transgenic mouse model), clearly demonstrated that the expression of typical M2 markers, like Arginase1, Ym1 and Fizz1, was specifically induced in MSC graft‐infiltrating macrophages, but not (or to a lesser extent) in MSC‐graft recognizing microglia Along with neutrophils, CNS‐resident microglia and blood‐borne macrophages are the first cells to be recruited to sites of CNS transplantation + and CD8+ T lymphocytes are found in rejecting and recently rejected grafts whereas long‐term surviving grafts are (nearly) devoid of T cells + T lymphocytes are the principal mediators. This is reflected by the preferential recruitment of CD4+ T cells to the graft site and a coinciding accumulation of Th1 cytokine‐encoding transcripts  in the CNS +—but not CD8+—T lymphocyte depletion + T cells to xenograft rejection was observed + T cell‐mediated rejection mainly serves as a redundancy mechanism, which becomes increasingly important when preceding immunological events fail to mediate graft rejection. The prolonged survival of neural xenografts in CD1d1 knockout mice additionally demonstrates a role for NKT cells in CNS graft recognition/rejection Considerable experimental evidence points to the involvement of T lymphocytes in the rejection of allogeneic/xenogeneic neural—but not mesenchymal—cell grafts in the CNS: (a) porcine embryonic brain cells induce an in vitro proliferative response in human T cells While intracerebral cell graft recognition seems to be mediated by microglia, macrophages and T cells, host humoral responses should not be overlooked. Although the intact BBB is impermeable to antibodies, the transplantation procedure temporarily compromises its integrity  + lymphocyte depletion or immunoglobulin deficiency) is often sufficient to achieve excellent cell graft survival in rodents Despite the multitude of immune recognition mechanisms in play, interference with a single pathway  immunological rejection of the grafted cells. Pharmacological suppression of the host immune system is the most commonly used method, with a multitude of immunosuppressants already having been approved for human use Thirty years following the first allotransplantation and xenotransplantation studies in rodents and humans, it is clear that many open questions remain regarding the immunological processes involved in cell graft recognition and, more importantly, the clinical benefit of  cellular therapies. The lack of scientific support for the latter may not be so unexpected as cell integration/replacement strategies for CNS therapy have been approached with too simplified—even naive—thoughts which are not supported by current knowledge in developmental biology and regeneration. Therefore, future clinical attempts should take into account the multitude of immunological mechanisms that may interfere with graft survival and differentiation Fig. . FurtherC.J.H.: conception and design, literature interpretation and discussion, manuscript writing; D.L.B., A.Q., J.D., H.G., and Z.B.: literature interpretation and discussion; P.P.: conception and design, literature interpretation and discussion, final approval of manuscript.The authors indicated no potential conflicts of interest.