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Genetic, dietary, and inflammatory factors contribute to the etiology of major mood disorders (MMD), thus impeding the identification of specific biomarkers to assist in diagnosis and treatment. We tested association of vitamin D and inflammatory markers in 36 adolescents with bipolar disorder (BD) and major depressive disorder (MDD) forms of MMD and without MMD (non-mood control). We also assessed the overall level of inflammation using a cell-based reporter assay for nuclear factor kappa-B (NFκB) activation and measuring antibodies to oxidized LDL. We found that these factors were similar between non-mood and MMD youth. To identify potential biomarkers, we developed a screening immunoprecipitation-sequencing approach based on inflammatory brain glia maturation factor beta (GMFβ). We discovered that a homolog of GMFβ in human plasma is vitamin D-binding protein (DBP) and validated this finding using immunoprecipitation with anti-DBP antibodies and mass spectrometry/sequencing analysis. We quantified DBP levels in participants by western blot. DBP levels in BD participants were significantly higher (136%) than in participants without MMD (100%). The increase in DBP levels in MDD participants (121.1%) was not statistically different from these groups. The DBP responds early to cellular damage by binding of structural proteins and activating inflammatory cells. A product of enzymatic cleavage of DBP has been described as macrophage-activating factor. Circulating DBP is comprised of heterogenous high and low molecular fractions that are only partially recognized by mono- and polyclonal ELISA and are not suitable for the quantitative comparison of DBP in non-mood and MDD participants. Our data suggest DBP as a marker candidate of BD warranting its validation in a larger cohort of adolescent and adult MMD patients.

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Hardware neural networks with mechanical flexibility are promising next‐generation computing systems for smart wearable electronics. Several studies have been conducted on flexible neural networks for practical applications; however, developing systems with complete synaptic plasticity for combinatorial optimization remains challenging. In this study, the metal‐ion injection density is explored as a diffusive parameter of the conductive filament in organic memristors. Additionally, a flexible artificial synapse with bio‐realistic synaptic plasticity is developed using organic memristors that have systematically engineered metal‐ion injections, for the first time. In the proposed artificial synapse, short‐term plasticity (STP), long‐term plasticity, and homeostatic plasticity are independently achieved and are analogous to their biological counterparts. The time windows of the STP and homeostatic plasticity are controlled by the ion‐injection density and electric‐signal conditions, respectively. Moreover, stable capabilities for complex combinatorial optimization in the developed synapse arrays are demonstrated under spike‐dependent operations. This effective concept for realizing flexible neuromorphic systems for complex combinatorial optimization is an essential building block for achieving a new paradigm of wearable smart electronics associated with artificial intelligent systems.

No abstract