Retinoic acid modulation of granule cell activity and spatial discrimination in the adult hippocampus.

Retinoic acid (RA), derived from vitamin A (retinol), plays a crucial role in modulating neuroplasticity within the adult brain. Perturbations in RA signaling have been associated with memory impairments, underscoring the necessity to elucidate RA's influence on neuronal activity, particularly within the hippocampus. In this study, we investigated the cell type and sub-regional distribution of RA-responsive granule cells (GCs) in the mouse hippocampus and delineated their properties. We discovered that RA-responsive GCs tend to exhibit a muted response to environmental novelty, typically remaining inactive. Interestingly, chronic dietary depletion of RA leads to an abnormal increase in GC activation evoked by a novel environment, an effect that is replicated by the localized application of an RA receptor beta (RARß) antagonist. Furthermore, our study shows that prolonged RA deficiency impairs spatial discrimination-a cognitive function reliant on the hippocampus-with such impairments being reversible with RA replenishment. In summary, our findings significantly contribute to a better understanding of RA's role in regulating adult hippocampal neuroplasticity and cognitive functions.

Comparative Anatomy of the Dentate Mossy Cells in Nonhuman Primates: Their Spatial Distributions and Axonal Projections Compared With Mouse Mossy Cells.

Glutamatergic mossy cells (MCs) mediate associational and commissural connectivity, exhibiting significant heterogeneity along the septotemporal axis of the mouse dentate gyrus (DG). However, it remains unclear whether the neuronal features of MCs are conserved across mammals. This study compares the neuroanatomy of MCs in the DG of mice and monkeys. The MC marker, calretinin, distinguishes two subpopulations: septal and temporal. Dual-colored fluorescence labeling is utilized to compare the axonal projection patterns of these subpopulations. In both mice and monkeys, septal and temporal MCs project axons across the longitudinal axis of the ipsilateral DG, indicating conserved associational projections. However, unlike in mice, no MC subpopulations in monkeys make commissural projections to the contralateral DG. In monkeys, temporal MCs send associational fibers exclusively to the inner molecular layer, while septal MCs give rise to wide axonal projections spanning multiple molecular layers, akin to equivalent MC subpopulations in mice. Despite conserved septotemporal heterogeneity, interspecies differences are observed in the topological organization of septal MCs, particularly in the relative axonal density in each molecular layer along the septotemporal axis of the DG. In summary, this comparative analysis sheds light on both conserved and divergent features of MCs in the DG of mice and monkeys. These findings have implications for understanding functional differentiation along the septotemporal axis of the DG and contribute to our knowledge of the anatomical evolution of the DG circuit in mammals.

Maladaptation of dentate gyrus mossy cells mediates contextual discrimination deficit after traumatic stress.

Fear overgeneralization is a maladaptive response to traumatic stress that is associated with the inability to discriminate between threat and safety contexts, a hallmark feature of post-traumatic stress disorder (PTSD). However, the neural mechanisms underlying this deficit remain unclear. Here, we show that traumatic stress exposure impairs contextual discrimination between threat and safety contexts in the learned helplessness (LH) model. Mossy cells (MCs) in the dorsal hippocampus are suppressed in response to traumatic stress. Bidirectional manipulation of MC activity in the LH model reveals that MC inhibition is causally linked to impaired contextual discrimination. Mechanistically, MC inhibition increases the number of active granule cells in a given context, significantly overlapping context-specific ensembles. Our study demonstrates that maladaptive inhibition of MCs after traumatic stress is a substantial mechanism underlying fear overgeneralization with contextual discrimination deficit, suggesting a potential therapeutic target for cognitive symptoms of PTSD.

Multi-proteomic analyses of 5xFAD mice reveal new molecular signatures of early-stage Alzheimer's disease.

An early diagnosis of Alzheimer's disease is crucial as treatment efficacy is limited to the early stages. However, the current diagnostic methods are limited to mid or later stages of disease development owing to the limitations of clinical examinations and amyloid plaque imaging. Therefore, this study aimed to identify molecular signatures including blood plasma extracellular vesicle biomarker proteins associated with Alzheimer's disease to aid early-stage diagnosis. The hippocampus, cortex, and blood plasma extracellular vesicles of 3- and 6-month-old 5xFAD mice were analyzed using quantitative proteomics. Subsequent bioinformatics and biochemical analyses were performed to compare the molecular signatures between wild type and 5xFAD mice across different brain regions and age groups to elucidate disease pathology. There was a unique signature of significantly altered proteins in the hippocampal and cortical proteomes of 3- and 6-month-old mice. The plasma extracellular vesicle proteomes exhibited distinct informatic features compared with the other proteomes. Furthermore, the regulation of several canonical pathways (including phosphatidylinositol 3-kinase/protein kinase B signaling) differed between the hippocampus and cortex. Twelve potential biomarkers for the detection of early-stage Alzheimer's disease were identified and validated using plasma extracellular vesicles from stage-divided patients. Finally, integrin α-IIb, creatine kinase M-type, filamin C, glutamine γ-glutamyltransferase 2, and lysosomal α-mannosidase were selected as distinguishing biomarkers for healthy individuals and early-stage Alzheimer's disease patients using machine learning modeling with approximately 79% accuracy. Our study identified novel early-stage molecular signatures associated with the progression of Alzheimer's disease, thereby providing novel insights into its pathogenesis.

Association between initial clozapine titration and pneumonia risk among patients with schizophrenia in a Korean tertiary hospital.

Pneumonia is a significant adverse drug reaction (ADR) associated with clozapine, characterized by high mortality and potential linkage with other inflammatory responses. Despite the critical nature, research regarding the development of pneumonia during initial clozapine titration remains limited. This retrospective study included 1408 Korean inpatients with schizophrenia spectrum disorders. Data were collected from January 2000 to January 2023. Pneumonia developed in 3.5 % of patients within 8 weeks of clozapine initiation. Patients who developed pneumonia were taking a greater number and higher dose of antipsychotics at baseline (2.14 vs. 1.58, p < 0.001; 25.64 vs. 19.34, p = 0.012). The average onset occurred 17.24 days after initiation, on an average dose of 151.28 mg/day. Titration was either paused or slowed in most of these patients, with no reported fatalities. The types of pneumonia included aspiration pneumonia, mycoplasma pneumonia, bronchopneumonia, and COVID-19 pneumonia. Myocarditis, drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome, and urinary tract infections were also identified. Logistic regression analysis revealed that a greater number of concomitant antipsychotics (odds ratio [OR] = 1.59, p = 0.027) and concomitant benzodiazepine use (OR = 2.33, p = 0.005) at baseline were associated with an increased risk of pneumonia. Overall, pneumonia development during clozapine titration is linked with other inflammatory ADRs, suggesting a shared immunological mechanism. Close monitoring is recommended, especially for patients taking multiple antipsychotics and benzodiazepines. Further studies involving repeated measures of clozapine concentrations at trough and steady state, along with a more detailed description of pneumonia types, are warranted.

Association between initial pattern of clozapine titration, concentration-to-dose ratio, and incidence of fever in patients with schizophrenia spectrum disorders in a Korean tertiary hospital.

Safe and effective administration of clozapine requires careful monitoring for inflammatory reactions during the initial titration. The concentration-to-dose (C/D) ratio must be taken into account, which may vary among ethnicities. In this retrospective study, 1408 Korean schizophrenia inpatients were examined for during the first 8 weeks of clozapine titration. The average doses of clozapine administered during weeks 1, 2, 4, and 8 were 77.37, 137.73, 193.20, and 212.83 mg/day, with significantly lower doses for females than males. The average C/D ratio was significantly higher in females (1.75 ± 1.04 and 1.11 ± 0.67 ng/mL per mg/day). Patients with higher C/D ratios were more likely to experience fever and were prescribed lower doses of clozapine starting from week 4. In total, 22.1 % of patients developed a fever at an average of 15.74 days after initiating clozapine. Patients who developed a fever were younger, used more antipsychotics at baseline, had a higher C/D ratio, and had a higher incidence of an elevated C-reactive protein level. A higher C/D ratio, use of a greater number of antipsychotics at baseline, and concomitant olanzapine use were risk factors for the development of inflammatory reactions. The incidence of pneumonia, agranulocytosis, and myocarditis within 8 weeks were 3.7 %, 0.3 %, and 0.1 %. In summary, the target dose of clozapine titration is lower for Korean schizophrenia patients, with a higher C/D ratio and more frequent fever compared to Western patients; however, myocarditis occurs rarely. Our findings may contribute to the titration methods for clozapine for the East Asian population.

HDOP and VDOP Analysis in an Ideal Placement Environment for Dual GNSSs.

Increasing the number of satellites in a global navigation satellite system (GNSS) improves the positioning accuracy and increases availability. However, it reduces the positioning accuracy improvement rate and increases the calculation loads, which can cause battery usage problems in mobile devices using a GNSS. An appropriate satellite selection method is required. One current method entails the use of ideal satellite placement with respect to the minimum geometric dilution of precision (GDOP). In this study, the described ideal satellite placement with the minimum GDOP were divided in terms of the horizontal dilution of precision (HDOP) and vertical dilution of precision (VDOP). HDOP and VDOP were mathematically derived and analyzed. The derived formula was verified using simulations. The analysis was performed with actual dual GNSS satellite data. The satellites adjacent to the ideal placement were selected and the DOP was calculated. Simply selecting satellites closest to the ideal placement afforded large values for HDOP and VDOP. This issue was addressed using a satellite changing algorithm considering the dual GNSS, resulting in reduced values of the HDOP and VDOP.

Efficient architecture for deep neural networks with heterogeneous sensitivity.

In this study, we present a neural network that consists of nodes with heterogeneous sensitivity. Each node in a network is assigned a variable that determines the sensitivity with which it learns to perform a given task. The network is trained via a constrained optimization that maximizes the sparsity of the sensitivity variables while ensuring optimal network performance. As a result, the network learns to perform a given task using only a few sensitive nodes. Insensitive nodes, which are nodes with zero sensitivity, can be removed from a trained network to obtain a computationally efficient network. Removing zero-sensitivity nodes has no effect on the performance of the network because the network has already been trained to perform the task without them. The regularization parameter used to solve the optimization problem was simultaneously found during the training of the networks. To validate our approach, we designed networks with computationally efficient architectures for various tasks such as autoregression, object recognition, facial expression recognition, and object detection using various datasets. In our experiments, the networks designed by our proposed method provided the same or higher performances but with far less computational complexity.

Deep neural networks with a set of node-wise varying activation functions.

In this study, we present deep neural networks with a set of node-wise varying activation functions. The feature-learning abilities of the nodes are affected by the selected activation functions, where the nodes with smaller indices become increasingly more sensitive during training. As a result, the features learned by the nodes are sorted by the node indices in order of their importance such that more sensitive nodes are related to more important features. The proposed networks learn input features but also the importance of the features. Nodes with lower importance in the proposed networks can be pruned to reduce the complexity of the networks, and the pruned networks can be retrained without incurring performance losses. We validated the feature-sorting property of the proposed method using both shallow and deep networks as well as deep networks transferred from existing networks.

Hippocampal mossy cell involvement in behavioral and neurogenic responses to chronic antidepressant treatment.

Most antidepressants, including selective serotonin reuptake inhibitors (SSRIs), initiate their drug actions by rapid elevation of serotonin, but they take several weeks to achieve therapeutic onset. This therapeutic delay suggests slow adaptive changes in multiple neuronal subtypes and their neural circuits over prolonged periods of drug treatment. Mossy cells are excitatory neurons in the dentate hilus that regulate dentate gyrus activity and function. Here we show that neuronal activity of hippocampal mossy cells is enhanced by chronic, but not acute, SSRI administration. Behavioral and neurogenic effects of chronic treatment with the SSRI, fluoxetine, are abolished by mossy cell-specific knockout of p11 or Smarca3 or by an inhibition of the p11/AnxA2/SMARCA3 heterohexamer, an SSRI-inducible protein complex. Furthermore, simple chemogenetic activation of mossy cells using Gq-DREADD is sufficient to elevate the proliferation and survival of the neural stem cells. Conversely, acute chemogenetic inhibition of mossy cells using Gi-DREADD impairs behavioral and neurogenic responses to chronic administration of SSRI. The present data establish that mossy cells play a crucial role in mediating the effects of chronic antidepressant medication. Our results indicate that compounds that target mossy cell activity would be attractive candidates for the development of new antidepressant medications.

Obligatory roles of dopamine D1 receptors in the dentate gyrus in antidepressant actions of a selective serotonin reuptake inhibitor, fluoxetine.

Depression is a leading cause of disability. Current pharmacological treatment of depression is insufficient, and development of improved treatments especially for treatment-resistant depression is desired. Understanding the neurobiology of antidepressant actions may lead to development of improved therapeutic approaches. Here, we demonstrate that dopamine D1 receptors in the dentate gyrus act as a pivotal mediator of antidepressant actions in mice. Chronic administration of a selective serotonin reuptake inhibitor (SSRI), fluoxetine, increases D1 receptor expression in mature granule cells in the dentate gyrus. The increased D1 receptor signaling, in turn, contributes to the actions of chronic fluoxetine treatment, such as suppression of acute stress-evoked serotonin release, stimulation of adult neurogenesis and behavioral improvement. Importantly, under severely stressed conditions, chronic administration of a D1 receptor agonist in conjunction with fluoxetine restores the efficacy of fluoxetine actions on D1 receptor expression and behavioral responses. Thus, our results suggest that stimulation of D1 receptors in the dentate gyrus is a potential adjunctive approach to improve therapeutic efficacy of SSRI antidepressants.

Effects of Silibinin Against Prothrombin Kringle-2-Induced Neurotoxicity in the Nigrostriatal Dopaminergic System In Vivo.

Parkinson's disease (PD) and Alzheimer's disease exhibit common features of neurodegenerative diseases and can be caused by numerous factors. A common feature of these diseases is neurotoxic inflammation by activated microglia, indicating that regulation of microglial activation is a potential mechanism for preserving neurons in the adult brain. Recently, we reported that upregulation of prothrombin kringle-2 (pKr-2), one of the domains that make up prothrombin and which is cleaved and generated by active thrombin, induces nigral dopaminergic (DA) neuronal death through neurotoxic microglial activation in the adult brain. In this study, we show that silibinin, a flavonoid found in milk thistle, can suppress the production of inducible nitric oxide synthase and neurotoxic inflammatory cytokines, such as interleukin-1ß and tumor necrosis factor-α, after pKr-2 treatment by downregulating the extracellular signal-regulated kinase signaling pathway in the mouse substantia nigra. Moreover, as demonstrated by immunohistochemical staining, measurements of the dopamine and metabolite levels, and open-field behavioral tests, silibinin treatment protected the nigrostriatal DA system resulting from the occurrence of pKr-2-triggered neurotoxic inflammation in vivo. Thus, we conclude that silibinin may be beneficial as a natural compound with anti-inflammatory effects against pKr-2-triggered neurotoxicity to protect the nigrostriatal DA pathway and its properties, and thus, may be applicable for PD therapy.

Facial Attribute Recognition by Recurrent Learning With Visual Fixation.

This paper presents a recurrent learning-based facial attribute recognition method that mimics human observers' visual fixation. The concentrated views of a human observer while focusing and exploring parts of a facial image over time are generated and fed into a recurrent network. The network makes a decision concerning facial attributes based on the features gleaned from the observer's visual fixations. Experiments on facial expression, gender, and age datasets show that applying visual fixation to recurrent networks improves recognition rates significantly. The proposed method not only outperforms state-of-the-art recognition methods based on static facial features, but also those based on dynamic facial features.

A secretome profile indicative of oleate-induced proliferation of HepG2 hepatocellular carcinoma cells.

Increased fatty acid (FA) is often observed in highly proliferative tumors. FAs have been shown to modulate the secretion of proteins from tumor cells, contributing to tumor survival. However, the secreted factors affected by FA have not been systematically explored. Here, we found that treatment of oleate, a monounsaturated omega-9 FA, promoted the proliferation of HepG2 cells. To examine the secreted factors associated with oleate-induced cell proliferation, we performed a comprehensive secretome profiling of oleate-treated and untreated HepG2 cells. A comparison of the secretomes identified 349 differentially secreted proteins (DSPs; 145 upregulated and 192 downregulated) in oleate-treated samples, compared to untreated samples. The functional enrichment and network analyses of the DSPs revealed that the 145 upregulated secreted proteins by oleate treatment were mainly associated with cell proliferation-related processes, such as lipid metabolism, inflammatory response, and ER stress. Based on the network models of the DSPs, we selected six DSPs (MIF, THBS1, PDIA3, APOA1, FASN, and EEF2) that can represent such processes related to cell proliferation. Thus, our results provided a secretome profile indicative of an oleate-induced proliferation of HepG2 cells.

LPA-induced migration of ovarian cancer cells requires activation of ERM proteins via LPA1 and LPA2.

Lysophosphatidic acid (LPA) has been implicated in the pathology of human ovarian cancer. This phospholipid elicits a wide range of cancer cell responses, such as proliferation, trans-differentiation, migration, and invasion, via various G-protein-coupled LPA receptors (LPARs). Here, we explored the cellular signaling pathway via which LPA induces migration of ovarian cancer cells. LPA induced robust phosphorylation of ezrin/radixin/moesin (ERM) proteins, which are membrane-cytoskeleton linkers, in the ovarian cancer cell line OVCAR-3. Among the LPAR subtypes expressed in these cells, LPA1 and LPA2, but not LPA3, induced phosphorylation of ERM proteins at their C-termini. This phosphorylation was dependent on the Gα12/13/RhoA pathway, but not on the Gαq/Ca2+/PKC or Gαs/adenylate cyclase/PKA pathway. The activated ERM proteins mediated cytoskeletal reorganization and formation of membrane protrusions in OVCAR-3 cells. Importantly, LPA-induced migration of OVCAR-3 cells was completely abolished not only by gene silencing of LPA1 or LPA2, but also by overexpression of a dominant negative ezrin mutant (ezrin-T567A). Taken together, this study demonstrates that the LPA1/LPA2/ERM pathway mediates LPA-induced migration of ovarian cancer cells. These findings may provide a potential therapeutic target to prevent metastatic progression of ovarian cancer.

Redox-Triggered Coloration Mechanism of Electrically Tunable Colloidal Photonic Crystals.

Electrically tunable colloidal photonic crystals (ETPCs) have been investigated because of several merits such as easy color tunability, no discoloration, and clear color. The coloration mechanism of ETPCs has been explained in terms of only the electric field. Herein, we report on a new mechanism: electric field plus redox reaction. Specifically, the coloration behavior of ETPCs was investigated under electrically conductive or insulated conditions using current-voltage, cyclic voltammetry, and zeta potential measurements, as well as scanning electron microscopy. Electrophoretic movement of ETPC particles toward the positive electrode was caused by the electric field due to the particles' negative surface charge. At the positive electrode, ETPC particles lost their electrons and formed a colloidal crystal structure. Finally, an ETPC transparent tube device was constructed to demonstrate the coloration mechanism.

Dynamic relocalization of NHERF1 mediates chemotactic migration of ovarian cancer cells toward lysophosphatidic acid stimulation.

NHERF1/EBP50 (Na+/H+ exchanger regulating factor 1; Ezrin-binding phosphoprotein of 50 kDa) organizes stable protein complexes beneath the apical membrane of polar epithelial cells. By contrast, in cancer cells without any fixed polarity, NHERF1 often localizes in the cytoplasm. The regulation of cytoplasmic NHERF1 and its role in cancer progression remain unclear. In this study, we found that, upon lysophosphatidic acid (LPA) stimulation, cytoplasmic NHERF1 rapidly translocated to the plasma membrane, and subsequently to cortical protrusion structures, of ovarian cancer cells. This movement depended on direct binding of NHERF1 to C-terminally phosphorylated ERM proteins (cpERMs). Moreover, NHERF1 depletion downregulated cpERMs and further impaired cpERM-dependent remodeling of the cell cortex, suggesting reciprocal regulation between these proteins. The LPA-induced protein complex was highly enriched in migratory pseudopodia, whose formation was impaired by overexpression of NHERF1 truncation mutants. Consistent with this, NHERF1 depletion in various types of cancer cells abolished chemotactic cell migration toward a LPA gradient. Taken together, our findings suggest that the high dynamics of cytosolic NHERF1 provide cancer cells with a means of controlling chemotactic migration. This capacity is likely to be essential for ovarian cancer progression in tumor microenvironments containing LPA.

A predictive model of the tensile strength of twisted carbon nanotube yarns.

Due to the outstanding mechanical properties of individual carbon nanotubes (CNTs) at the nanoscale, CNT yarns are expected to demonstrate high strength at the macroscale. In this study, a predictable model was developed to predict the tensile strength of twisted CNT yarns. First, the failure mechanism of twisted CNT yarns was investigated using in situ tensile tests and ex situ observations. It was revealed that CNT bundles, which are groups of CNTs that are tightly bound together, formed during tensile loading, leaving some voids around the bundles. Failure of the CNT yarns occurred as the CNT bundles were pulled out of the yarns. Two stresses that determined the tensile strength of the CNT yarns were identified: interfacial shear and frictional stresses originating from van der Waals interactions, and the lateral pressure generated by the twisted yarn structure. Molecular dynamics and yarn mechanics were used to calculate these two stresses. Finally, the tensile strength of CNT yarns was predicted and compared with experimental data, showing reasonable agreement.

Ambivalent Effect of Thermal Reduction in Mass Rejection through Graphene Oxide Membrane.

We report ambivalent rejection behavior of a graphene oxide membrane (GOM) having a reduced interlayer spacing. Ultrathin GOMs having a thickness of 50 nm were fabricated using a vacuum filtration method followed by subjecting the samples to thermal reduction at 162 °C. The interlayer spacing of GOMs was reduced by 1 Å on thermal reduction as compared with that of the natural GOMs. The rejection rate with dye molecules was tested using dyes having three different types of charges in a dead-end filtration instrument. Rejection rate of the reduced GOM with the dyes having an opposite charge was improved up to 99.7%, indicating the dominant effect of the physical sieving diameter. In contrast, in the case of ion permeation of natural GOM, a higher rejection rate for several metal ions was observed as compared with that of GOMs having 1 Å smaller interlayer spacing, indicating the dominant effect of surface charges on the GOM samples.

Modeling Non-Stationary Asymmetric Lens Blur by Normal Sinh-Arcsinh Model.

Images acquired by a camera show lens blur due to imperfection in the optical system even when images are properly focused. Lens blur is non-stationary in a sense that the amount of blur depends on pixel locations in a sensor. Lens blur is also asymmetric in a sense that the amount of blur is different in the radial and tangential directions, and also in the inward and outward radial directions. This paper presents parametric blur kernel models based on the normal sinh-arcsinh distribution function. The proposed models can provide flexible shapes of blur kernels with a different symmetry and skewness to model complicated lens blur due to optical aberration in a properly focused images accurately. Blur of single focal length lenses is estimated, and the accuracy of the models is compared with the existing parametric blur models. An advantage of the proposed models is demonstrated through deblurring experiments.