The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research

Introduction: Treatment of severe mental illness (SMI) symptoms, especially negative symptoms and cognitive dysfunction in schizophrenia, remains a major unmet need. There is good evidence that SMIs have a strong genetic background and are characterized by multiple biological alterations, including disturbed brain circuits and connectivity, dysregulated neuronal excitation-inhibition, disturbed dopaminergic and glutamatergic pathways, and partially dysregulated inflammatory processes. The ways in which the dysregulated signaling pathways are interconnected remains largely unknown, in part because well-characterized clinical studies on comprehensive biomaterial are lacking. Furthermore, the development of drugs to treat SMIs such as schizophrenia is limited by the use of operationalized symptom-based clusters for diagnosis. Methods: In line with the Research Domain Criteria initiative, the Clinical Deep Phenotyping (CDP) study is using a multimodal approach to reveal the neurobiological underpinnings of clinically relevant schizophrenia subgroups by performing broad transdiagnostic clinical characterization with standardized neurocognitive assessments, multimodal neuroimaging, electrophysiological assessments, retinal investigations, and omics-based analyzes of blood and cerebrospinal fluid. Moreover, to bridge the translational gap in biological psychiatry the study includes in vitro investigations on human-induced pluripotent stem cells, which are available from a subset of participants. Results: Here, we report on the feasibility of this multimodal approach, which has been successfully initiated in the first participants in the CDP cohort; to date, the cohort comprises over 194 individuals with SMI and 187 age and gender matched healthy controls. In addition, we describe the applied research modalities and study objectives. Discussion: The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive dysfunction, and treatment-resistant symptoms in general are still difficult to treat

Directional control of weakly localized Raman from a random network of fractal nanowires

Disordered optical media are an emerging class of materials capable of strongly scattering light. Their study is relevant to investigate transport phenomena and for applications in imaging, sensing and energy storage. While such materials can be used to generate coherent light, their directional emission is typically hampered by their very multiple scattering nature. Here, we tune the out-of-plane directionality of coherent Raman light scattered by a fractal network of silicon nanowires. By visualizing Rayleigh scattering, photoluminescence and weakly localized Raman light from the random network of nanowires via real-space microscopy and Fourier imaging, we gain insight on the light transport mechanisms responsible for the material's inelastic coherent signal and for its directionality. The possibility of visualizing and manipulating directional coherent light in such networks of nanowires opens venues for fundamental studies of light propagation in disordered media as well as for the development of next generation optical devices based on disordered structures, inclusive of sensors, light sources and optical switches

Clear directions for random lasers

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firedrakeproject/petsc4py: The Python interface to PETSc

This release is specifically created to document the version of petsc4py used in a particular set of experiments using Firedrake. Please do not cite this as a general source for Firedrake or any of its dependencies. Instead, refer to https://www.firedrakeproject.org/citing.htmlThis release is specifically created to document the version of petsc4py used in a particular set of experiments using Firedrake. Please do not cite this as a general source for Firedrake or any of its dependencies. Instead, refer to https://www.firedrakeproject.org/citing.html20181204.

Regulation Theories in Retrospect and Prospect.

This chapter critically assesses the regulation approach to the critique of political economy. It starts with the theoretical background to regulation theories; moves on to compare the main approaches and their various fields of application; and then offers some methodological and epistemological criticisms of the leading schools. Then come some more general methodological remarks on the object and subject of regulation and some specific comments on one of the weakest areas of regulation theory - its account of the state. Thus this chapter focuses on methodology and general theory rather than empirical analysis