Development and validation of a risk calculator for major mood disorders among the offspring of bipolar parents using information collected in routine clinical practice.

Family history is a significant risk factor for bipolar disorders (BD), but the magnitude of risk varies considerably between individuals within and across families. Accurate risk estimation may increase motivation to reduce modifiable risk exposures and identify individuals appropriate for monitoring over the peak risk period. Our objective was to develop and independently replicate an individual risk calculator for bipolar spectrum disorders among the offspring of BD parents using data collected in routine clinical practice. Data from the longitudinal Canadian High-Risk Offspring cohort study collected from 1996 to 2020 informed the development of a 5 and 10-year risk calculator using parametric time-to-event models with a cure fraction and a generalized gamma distribution. The calculator was then externally validated using data from the Lausanne-Geneva High-Risk Offspring cohort study collected from 1996 to 2020. A time-varying C-index by age in years was used to estimate the probability that the model correctly classified risk. Bias corrected estimates and 95% confidence limits were derived using a jackknife resampling approach. The primary outcome was age of onset of a major mood disorder. The risk calculator was most accurate at classifying risk in mid to late adolescence in the Canadian cohort (n = 285), and a similar pattern was replicated in the Swiss cohort (n = 128). Specifically, the time-varying C-index indicated that there was approximately a 70% chance that the model would correctly predict which of two 15-year-olds would be more likely to develop the outcome in the future. External validation within a smaller Swiss cohort showed mixed results. Findings suggest that this model may be a useful clinical tool in routine practice for improved individualized risk estimation of bipolar spectrum disorders among the adolescent offspring of a BD parent; however, risk estimation in younger high-risk offspring is less accurate, perhaps reflecting the evolving nature of psychopathology in early childhood. Based on external validation with a Swiss cohort, the risk calculator may not be as predictive in more heterogenous high-risk populations. The Canadian High-Risk Study has been funded by consecutive operating grants from the Canadian Institutes for Health Research, currently CIHR PJT Grant 152796 he Lausanne-Geneva high-risk study was and is supported by five grants from the Swiss National Foundation (#3200-040,677, #32003B-105,969, #32003B-118,326, #3200-049,746 and #3200-061,974), three grants from the Swiss National Foundation for the National Centres of Competence in Research project "The Synaptic Bases of Mental Diseases" (#125,759, #158,776, and #51NF40 - 185,897), and a grant from GlaxoSmithKline Clinical Genetics

Decreased mental time travel to the past correlates with default-mode network disintegration under lysergic acid diethylamide

This paper reports on the effects of LSD on mental time travel during spontaneous mentation. Twenty healthy volunteers participated in a placebo-controlled crossover study, incorporating intravenous administration of LSD (75 μg) and placebo (saline) prior to functional magnetic resonance imaging (fMRI). Six independent, blind judges analysed mentation reports acquired during structured interviews performed shortly after the functional magnetic resonance imaging (fMRI) scans (approximately 2.5 h post-administration). Within each report, specific linguistic references to mental spaces for the past, present and future were identified. Results revealed significantly fewer mental spaces for the past under LSD and this effect correlated with the general intensity of the drug’s subjective effects. No differences in the number of mental spaces for the present or future were observed. Consistent with the previously proposed role of the default-mode network (DMN) in autobiographical memory recollection and ruminative thought, decreased resting-state functional connectivity (RSFC) within the DMN correlated with decreased mental time travel to the past. These results are discussed in relation to potential therapeutic applications of LSD and related psychedelics, e.g. in the treatment of depression, for which excessive reflection on one’s past, likely mediated by DMN functioning, is symptomatic

Clinical use of lithium salts: guide for users and prescribers

Lithium has been used clinically for 70 years, mainly to treat bipolar disorder. Competing treatments and exaggerated impressions about complexity and risks of lithium treatment have led to its declining use in some countries, encouraging this update about its safe clinical use. We conducted a nonsystematic review of recent research reports and developed consensus among international experts on the use of lithium to treat major mood disorders, aiming for a simple but authoritative guide for patients and prescribers

Enlightened or Delusional?: Differentiating Religious, Spiritual, and Transpersonal Experiences from Psychopathology

Psychological diagnosis faces unique challenges when used to differentiate nonpsychopathological religious/spiritual/transpersonal (R/S/T) experiences from those that might evidence psychopathology, particularly considering the diversity of such experiences and the value-laden assumptions inherent in most diagnostic practices. Theoretical and pragmatic problems related to the diagnostic category, Religious and Spiritual Problem, as contained in the Diagnostic and Statistical Manual of Mental Disorders are discussed. Attention is paid to identifying potential biases and errors in using, or failing to use, this diagnostic category, particularly as related to developing culturally sensitive diagnoses. Specific methods, including psychometric approaches, for evaluating R/S/T experiences that may range from healthy to psychopathological are reviewed and recommendations are presented for improving current diagnostic practices and furthering needed research.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Towards the clinical implementation of pharmacogenetics in bipolar disorder.

BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm

Coastal wetland mapping plays an essential role in monitoring climate change, the hydrological cycle, and water resources. In this study, a novel classification framework based on the gravitational optimized multilayer perceptron classifier and extended multi-attribute profiles (EMAPs) is presented for coastal wetland mapping using Sentinel-2 multispectral instrument (MSI) imagery. In the proposed method, the morphological attribute profiles (APs) are firstly extracted using four attribute filters based on the characteristics of wetlands in each band from Sentinel-2 imagery. These APs form a set of EMAPs which comprehensively represent the irregular wetland objects in multiscale and multilevel. The EMAPs and original spectral features are then classified with a new multilayer perceptron (MLP) classifier whose parameters are optimized by a stability-constrained adaptive alpha for a gravitational search algorithm. The performance of the proposed method was investigated using Sentinel-2 MSI images of two coastal wetlands, i.e., the Jiaozhou Bay and the Yellow River Delta in Shandong province of eastern China. Comparisons with four other classifiers through visual inspection and quantitative evaluation verified the superiority of the proposed method. Furthermore, the effectiveness of different APs in EMAPs were also validated. By combining the developed EMAPs features and novel MLP classifier, complicated wetland types with high within-class variability and low between-class disparity were effectively discriminated. The superior performance of the proposed framework makes it available and preferable for the mapping of complicated coastal wetlands using Sentinel-2 data and other similar optical imagery

Can we predict Λ\Lambda for the Non-SUSY sector of the Landscape ?

We propose a new selection criteria for predicting the most probable wavefunction of the universe that propagates on the string landscape background, by studying its dynamics from a quantum cosmology view. Previously we applied this proposal to the $SUSY$ sector of the landscape. In this work the dynamic selection criterion is applied to the investigation of the non-$SUSY$ sector.In the absence of detailed information about its structure, it is assumed that this sector has a stochastic distribution of vacua energies.The calculation of a distribution probability for the cosmological constants $\Lambda_{eff}$, obtained from the density of states $\rho$, indicates that the most probable wavefunction is peaked around universes with zero $\Lambda_{eff}$. In contrast to the {\it extended wavefunction} solutions found for the $SUSY$ sector with $N$-vacua and peaked around $\Lambda_{eff}\simeq \frac{1}{N^2}$, wavefunctions residing on the non-$SUSY$ sector exhibit {\it Anderson localization}.Although minisuperspace is a limited approach it presently provides a dynamical quantum selection rule for the most probable vacua solution from the landscape.Comment: 6 pages, 1 figur