Towards an integrated understanding of dietary phenotypes.

Diet and nutrition comprise a complex, multi-faceted interface between animal biology and food environments. With accumulating information on the many facets of this association arises a need for systems-based approaches that integrate dietary components and their links with ecology, feeding, post-ingestive processes and the functional and ecological consequences of these interactions. We briefly show how a modelling approach, nutritional geometry, has used the experimental control afforded in laboratory studies to begin to unravel these links. Laboratory studies, however, have limited ability to establish whether and how the feeding and physiological mechanisms interface with realistic ecological environments. We next provide an overview of observational field studies of free-ranging primates that have examined this, producing largely correlative data suggesting that similar feeding mechanisms operate in the wild as in the laboratory. Significant challenges remain, however, in establishing causal links between feeding, resource variation and physiological processes in the wild. We end with a more detailed account of two studies of temperate primates that have capitalized on the discrete variation provided by seasonal environments to strengthen causal inference in field studies and link patterns of intake to dynamics of nutrient processing. This article is part of the theme issue 'Food processing and nutritional assimilation in animals'.

Integrative Bayesian models using Post-selective inference: A case study in radiogenomics.

Integrative analyses based on statistically relevant associations between genomics and a wealth of intermediary phenotypes (such as imaging) provide vital insights into their clinical relevance in terms of the disease mechanisms. Estimates for uncertainty in the resulting integrative models are however unreliable unless inference accounts for the selection of these associations with accuracy. In this paper, we develop selection-aware Bayesian methods, which (1) counteract the impact of model selection bias through a "selection-aware posterior" in a flexible class of integrative Bayesian models post a selection of promising variables via ℓ1 -regularized algorithms; (2) strike an inevitable trade-off between the quality of model selection and inferential power when the same data set is used for both selection and uncertainty estimation. Central to our methodological development, a carefully constructed conditional likelihood function deployed with a reparameterization mapping provides tractable updates when gradient-based Markov chain Monte Carlo (MCMC) sampling is used for estimating uncertainties from the selection-aware posterior. Applying our methods to a radiogenomic analysis, we successfully recover several important gene pathways and estimate uncertainties for their associations with patient survival times.

Palliative and Critical Care: Their Convergence in the Pediatric Intensive Care Unit.

Palliative care (PC) is an integral component of optimal critical care (CC) practice for pediatric patients facing life-threatening illness. PC acts as an additional resource for patients and families as they navigate through critical illness. Although PC encompasses end of life care, it is most effective when integrated early alongside disease-directed and curative therapies. PC primarily focuses on improving quality of life for patients and families by anticipating, preventing and treating suffering throughout the continuum of illness. This includes addressing symptom distress and facilitating communication. Effective communication is vital to elicit value-based goals of care, and to guide parents through patient-focused and potentially difficult decision-making process which includes advanced care planning. A multidisciplinary approach is most favorable when providing support to both patient and family, whether it is from the psychosocial, practical, emotional, spiritual or cultural aspects. PC also ensures coordination and continuity of care across different care settings. Support for family carries on after death with grief and bereavement support. This narrative review aims to appraise the current evidence of integration of PC into pediatric CC and its impact on patient- and family-centered outcomes. We will also summarize the impact of integration of good PC into pediatric CC, including effective communication with families, advanced care planning, withholding or withdrawal of life sustaining measures and bereavement support. Finally, we will provide a framework on how best to integrate PC in PICU. These findings will provide insights on how PC can improve the quality of care of a critically ill child.

Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi-phased study of prostate cancer.

BACKGROUND: DNA methylation and gene expression are known to play important roles in the etiology of human diseases such as prostate cancer (PCa). However, it has not yet been possible to incorporate information of DNA methylation and gene expression into polygenic risk scores (PRSs). Here, we aimed to develop and validate an improved PRS for PCa risk by incorporating genetically predicted gene expression and DNA methylation, and other genomic information using an integrative method. METHODS: Using data from the PRACTICAL consortium, we derived multiple sets of genetic scores, including those based on available single-nucleotide polymorphisms through widely used methods of pruning and thresholding, LDpred, LDpred-funt, AnnoPred, and EBPRS, as well as PRS constructed using the genetically predicted gene expression and DNA methylation through a revised pruning and thresholding strategy. In the tuning step, using the UK Biobank data (1458 prevalent cases and 1467 controls), we selected PRSs with the best performance. Using an independent set of data from the UK Biobank, we developed an integrative PRS combining information from individual scores. Furthermore, in the testing step, we tested the performance of the integrative PRS in another independent set of UK Biobank data of incident cases and controls. RESULTS: Our constructed PRS had improved performance (C statistics: 76.1%) over PRSs constructed by individual benchmark methods (from 69.6% to 74.7%). Furthermore, our new PRS had much higher risk assessment power than family history. The overall net reclassification improvement was 69.0% by adding PRS to the baseline model compared with 12.5% by adding family history. CONCLUSIONS: We developed and validated a new PRS which may improve the utility in predicting the risk of developing PCa. Our innovative method can also be applied to other human diseases to improve risk prediction across multiple outcomes.

Intensity patterns at the peaks of brain activity in fMRI and PET are highly correlated with neural models of spatial integration.

Spatial integration during the brain's cognitive activity prompts changes in energy used by different neuroglial populations. Nevertheless, the organisation of such integration in 3D -brain activity remains undescribed from a quantitative standpoint. In response, we applied a cross-correlation between brain activity and integrative models, which yielded a deeper understanding of information integration in functional brain mapping. We analysed four datasets obtained via fundamentally different neuroimaging techniques (functional magnetic resonance imaging [fMRI] and positron emission tomography [PET]) and found that models of spatial integration with an increasing input to each step of integration were significantly more correlated with brain activity than models with a constant input to each step of integration. In addition, marking the voxels with the maximal correlation, we found exceptionally high intersubject consistency with the initial brain activity at the peaks. Our method demonstrated for the first time that the network of peaks of brain activity is organised strictly according to the models of spatial integration independent of neuroimaging techniques. The highest correlation with models integrating an increasing at each step input suggests that brain activity reflects a network of integrative processes where the results of integration in some neuroglial populations serve as an input to other neuroglial populations.

Identifying biomarkers for predicting successful embryo implantation: applying single to multi-OMICs to improve reproductive outcomes.

BACKGROUND: Successful embryo implantation is a complex process that requires the coordination of a series of events, involving both the embryo and the maternal endometrium. Key to this process is the intricate cascade of molecular mechanisms regulated by endocrine, paracrine and autocrine modulators of embryonic and maternal origin. Despite significant progress in ART, implantation failure still affects numerous infertile couples worldwide and fewer than 10% of embryos successfully implant. Improved selection of both the viable embryos and the optimal endometrial phenotype for transfer remains crucial to enhancing implantation chances. However, both classical morphological embryo selection and new strategies incorporated into clinical practice, such as embryonic genetic analysis, morphokinetics or ultrasound endometrial dating, remain insufficient to predict successful implantation. Additionally, no techniques are widely applied to analyse molecular signals involved in the embryo-uterine interaction. More reliable biological markers to predict embryo and uterine reproductive competence are needed to improve pregnancy outcomes. Recent years have seen a trend towards 'omics' methods, which enable the assessment of complete endometrial and embryonic molecular profiles during implantation. Omics have advanced our knowledge of the implantation process, identifying potential but rarely implemented biomarkers of successful implantation. OBJECTIVE AND RATIONALE: Differences between the findings of published omics studies, and perhaps because embryonic and endometrial molecular signatures were often not investigated jointly, have prevented firm conclusions being reached. A timely review summarizing omics studies on the molecular determinants of human implantation in both the embryo and the endometrium will help facilitate integrative and reliable omics approaches to enhance ART outcomes. SEARCH METHODS: In order to provide a comprehensive review of the literature published up to September 2019, Medline databases were searched using keywords pertaining to omics, including 'transcriptome', 'proteome', 'secretome', 'metabolome' and 'expression profiles', combined with terms related to implantation, such as 'endometrial receptivity', 'embryo viability' and 'embryo implantation'. No language restrictions were imposed. References from articles were also used for additional literature. OUTCOMES: Here we provide a complete summary of the major achievements in human implantation research supplied by omics approaches, highlighting their potential to improve reproductive outcomes while fully elucidating the implantation mechanism. The review highlights the existence of discrepancies among the postulated biomarkers from studies on embryo viability or endometrial receptivity, even using the same omic analysis. WIDER IMPLICATIONS: Despite the huge amount of biomarker information provided by omics, we still do not have enough evidence to link data from all omics with an implantation outcome. However, in the foreseeable future, application of minimally or non-invasive omics tools, together with a more integrative interpretation of uniformly collected data, will help to overcome the difficulties for clinical implementation of omics tools. Omics assays of the embryo and endometrium are being proposed or already being used as diagnostic tools for personalised single-embryo transfer in the most favourable endometrial environment, avoiding the risk of multiple pregnancies and ensuring better pregnancy rates.

Part II: using an integrated case model for delivering mental health services in general practice for Pacific people.

OBJECTIVE: To discuss an alternative model for delivering mental health services to Pacific people in general practice. METHODS: Review of primary healthcare models which attempt to integrate behavioural healthcare with general practice. RESULTS: There is some evidence that relationship-based collaborative models may improve both mental and physical health. Such a model has been implemented successfully by Alaskan Native Americans. CONCLUSION: An integrated model of healthcare incorporating Pacific cultural values may reduce stigma and improve engagement and efficacy in delivering mental health treatment to Pacific people, their families and communities.

Factor analysis for survival time prediction with informative censoring and diverse covariates.

Fulfilling the promise of precision medicine requires accurately and precisely classifying disease states. For cancer, this includes prediction of survival time from a surfeit of covariates. Such data presents an opportunity for improved prediction, but also a challenge due to high dimensionality. Furthermore, disease populations can be heterogeneous. Integrative modeling is sensible, as the underlying hypothesis is that joint analysis of multiple covariates provides greater explanatory power than separate analyses. We propose an integrative latent variable model that combines factor analysis for various data types and an exponential proportional hazards (EPH) model for continuous survival time with informative censoring. The factor and EPH models are connected through low-dimensional latent variables that can be interpreted and visualized to identify subpopulations. We use this model to predict survival time. We demonstrate this model's utility in simulation and on four Cancer Genome Atlas datasets: diffuse lower-grade glioma, glioblastoma multiforme, lung adenocarcinoma, and lung squamous cell carcinoma. These datasets have small sample sizes, high-dimensional diverse covariates, and high censorship rates. We compare the predictions from our model to three alternative models. Our model outperforms in simulation and is competitive on real datasets. Furthermore, the low-dimensional visualization for diffuse lower-grade glioma displays known subpopulations.

Psychotherapy Integration: a main Obstacle and Challenge / La Integración en Psicoterapia: un Obstáculo y Desafío Principal

Abstract Psychotherapy integration is a key trend in psychotherapy nowadays. This paper offers a critical perspective on a main obstacle and challenge for psychotherapy integration. Psychotherapy integration should be treated more as a process than as a product. For psychotherapy integration to contribute to the future of psychotherapy, it should not forget its original Exploratory spirit, avoiding and being cautious about Established approaches, and being, therefore, more a process than a product. This assumption should be related first with the core spirit of psychotherapy integration, an ongoing process of respect for different psychotherapeutic models, and an attitude of work in progress. It should, secondly, be related with the stance or perspective that ought to be taken toward the ongoing appearance of new integrative models.

Resumen La tendencia actual a la integración en psicoterapia es importante. Este trabajo plantea una perspectiva crítica sobre un obstáculo y desafío principal para dicha tendencia. La integración en psicoterapia debe tratarse más como un proceso que como un producto. Para que la integración en psicoterapia contribuya al futuro de la psicoterapia no debería olvidar su espíritu inicial de Exploración, evitando y tomando precauciones frente a los enfoques Establecidos, convirtiéndose, por tanto, más en un proceso que en un producto. Este supuesto se puede relacionar, en primer lugar, con el espíritu central de la integración en psicoterapia, es decir, con un proceso continuo de respeto de los distintos enfoques psicoterapéuticos, y una actitud de trabajo en progreso. En segundo lugar, se puede relacionar con la perspectiva que se debe asumir en relación a la aparición continua de nuevos modelos integradores.

Expanding co-payment for methadone maintenance services in Vietnam: the importance of addressing health and socioeconomic inequalities.

BACKGROUND: Ensuring high enrollment while mobilizing resources through co-payment services is critical to the success of the methadone maintenance treatment (MMT) program in Vietnam. This study assessed the willingness of patients to pay (WTP) for different MMT services delivery models and determined its associated factors. METHODS: A facility based survey was conducted among 1016 MMT patients (98.7% male, 42% aged 35 or less, and 67% living with spouse) in five MMT clinics in Hanoi and Nam Dinh province in 2013. Socioeconomic, HIV and health status, history of drug use and rehabilitation, and MMT experience were interviewed. WTP was assessed using contingent valuation method, including a set of double-bounded binary questions and a follow-up open-ended question. Point and interval data models were used to estimate maximum willingness to pay. RESULTS: 95.5% patients were willing to pay for MMT at the monthly mean price of US$ 32 (95%CI = 28-35). Higher WTP was associated with higher level of educational attainment, higher income, male sex, and had high expenses on opiates prior to MMT. Patients who reported having any problem in Pain/ Discomfort, and who did not have outpatient care last year were willing to pay less for MMT than others. CONCLUSION: High level of WTP supports the co-payment policies as a strategy to mobilize resources for the MMT program in Vietnam. However, it is necessary to ensure equalities across patient groups by acknowledging socioeconomic status of different settings and providing financial supports for disadvantaged patients with severe health status.

Reorganization of the Connectivity between Elementary Functions - A Model Relating Conscious States to Neural Connections.

In the present paper it is argued that the "neural correlate of consciousness" (NCC) does not appear to be a separate "module" - but an aspect of information processing within the neural substrate of various cognitive processes. Consequently, NCC can only be addressed adequately within frameworks that model the general relationship between neural processes and mental states - and take into account the dynamic connectivity of the brain. We presently offer the REFGEN (general reorganization of elementary functions) model as such a framework. This model builds upon and expands the REF (reorganization of elementary functions) and REFCON (of elementary functions and consciousness) models. All three models integrate the relationship between the neural and mental layers of description via the construction of an intermediate level dealing with computational states. The importance of experience based organization of neural and cognitive processes is stressed. The models assume that the mechanisms of consciousness are in principle the same as the basic mechanisms of all aspects of cognition - when information is processed to a sufficiently "high level" it becomes available to conscious experience. The NCC is within the REFGEN model seen as aspects of the dynamic and experience driven reorganizations of the synaptic connectivity between the neurocognitive "building blocks" of the model - the elementary functions.

Probabilistic models of eukaryotic evolution: time for integration.

In spite of substantial work and recent progress, a global and fully resolved picture of the macroevolutionary history of eukaryotes is still under construction. This concerns not only the phylogenetic relations among major groups, but also the general characteristics of the underlying macroevolutionary processes, including the patterns of gene family evolution associated with endosymbioses, as well as their impact on the sequence evolutionary process. All these questions raise formidable methodological challenges, calling for a more powerful statistical paradigm. In this direction, model-based probabilistic approaches have played an increasingly important role. In particular, improved models of sequence evolution accounting for heterogeneities across sites and across lineages have led to significant, although insufficient, improvement in phylogenetic accuracy. More recently, one main trend has been to move away from simple parametric models and stepwise approaches, towards integrative models explicitly considering the intricate interplay between multiple levels of macroevolutionary processes. Such integrative models are in their infancy, and their application to the phylogeny of eukaryotes still requires substantial improvement of the underlying models, as well as additional computational developments.

Eschewing certainties: the creation of family therapists in the 21st century.

I reflect here on Family Therapy's origins, our present dilemmas, and future possibilities. Using the lens of training new Family Therapists for current public sector domains, I examine our field's strengths, vulnerabilities, and contradictions. I critique the current vogue of model certainty and branding. Our responsibilities to trainees, young practitioners, and the families we serve are highlighted.

Anorexia nervosa during adolescence and young adulthood: towards a developmental and integrative approach sensitive to time course.

Anorexia nervosa is situated at the junction between two time scales, the time scale of adolescence, in which intense physiological and psychological upheavals are occurring over a relatively short period of time, and the time scale of the potentially chronic evolution of the disease over the course of the patient's lifespan. This second time scale links the critical period of adolescence with the pre-morbid period, during which a complex state of vulnerability, often unseen and unheard, combines with different risk factors, which may be isolated, associated, dissociated or concomitant, to produce the emergence of anorexia; it ushers also adolescence into the period of adulthood, flagged with the reorganization that occurs in the course of the healing process (in case of recovery), or pervaded by somatic and mental distress (in cases where the condition becomes chronic). Given the lifespan nature of the disease, it is difficult to differentiate premorbid pathogenic factors from changes resulting from the acute or chronic phases of the illness. It is also difficult to establish straightforward correlations between physiological disturbances and their clinical consequences, or conversely to assume that the restoration of physiological parameters means the disappearance of the underlying mental disorder. Taken together, these observations support an approach to anorexia nervosa that is both developmental and integrative, taking into account both the complexity of the pathways involved and the developmental timescales of these pathways. This type of approach can help to adjust therapeutic strategies and thus enhance prognosis, in particular by integrating the temporal parameter into the dynamics of care plans.

Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur.