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.

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.

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.

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.

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.

Proteomic analysis of the palmitate-induced myotube secretome reveals involvement of the annexin A1-formyl peptide receptor 2 (FPR2) pathway in insulin resistance.

Elevated levels of the free fatty acid palmitate are found in the plasma of obese patients and induce insulin resistance. Skeletal muscle secretes myokines as extracellular signaling mediators in response to pathophysiological conditions. Here, we identified and characterized the skeletal muscle secretome in response to palmitate-induced insulin resistance. Using a quantitative proteomic approach, we identified 36 secretory proteins modulated by palmitate-induced insulin resistance. Bioinformatics analysis revealed that palmitate-induced insulin resistance induced cellular stress and modulated secretory events. We found that the decrease in the level of annexin A1, a secretory protein, depended on palmitate, and that annexin A1 and its receptor, formyl peptide receptor 2 agonist, played a protective role in the palmitate-induced insulin resistance of L6 myotubes through PKC-θ modulation. In mice fed with a high-fat diet, treatment with the formyl peptide receptor 2 agonist improved systemic insulin sensitivity. Thus, we identified myokine candidates modulated by palmitate-induced insulin resistance and found that the annexin A1- formyl peptide receptor 2 pathway mediated the insulin resistance of skeletal muscle, as well as systemic insulin sensitivity.

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.

TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information.

MOTIVATION: Time-evolving differential protein-protein interaction (PPI) networks are essential to understand serial activation of differentially regulated (up- or downregulated) cellular processes (DRPs) and their interplays over time. Despite developments in the network inference, current methods are still limited in identifying temporal transition of structures of PPI networks, DRPs associated with the structural transition and the interplays among the DRPs over time. RESULTS: Here, we present a probabilistic model for estimating Time-Evolving differential PPI networks with MultiPle Information (TEMPI). This model describes probabilistic relationships among network structures, time-course gene expression data and Gene Ontology biological processes (GOBPs). By maximizing the likelihood of the probabilistic model, TEMPI estimates jointly the time-evolving differential PPI networks (TDNs) describing temporal transition of PPI network structures together with serial activation of DRPs associated with transiting networks. This joint estimation enables us to interpret the TDNs in terms of temporal transition of the DRPs. To demonstrate the utility of TEMPI, we applied it to two time-course datasets. TEMPI identified the TDNs that correctly delineated temporal transition of DRPs and time-dependent associations between the DRPs. These TDNs provide hypotheses for mechanisms underlying serial activation of key DRPs and their temporal associations. AVAILABILITY AND IMPLEMENTATION: Source code and sample data files are available at http://sbm.postech.ac.kr/tempi/sources.zip. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Endothelial deletion of phospholipase D2 reduces hypoxic response and pathological angiogenesis.

OBJECTIVE: Aberrant regulation of the proliferation, survival, and migration of endothelial cells (ECs) is closely related to the abnormal angiogenesis that occurs in hypoxia-induced pathological situations, such as cancer and vascular retinopathy. Hypoxic conditions and the subsequent upregulation of hypoxia-inducible factor-1α and target genes are important for the angiogenic functions of ECs. Phospholipase D2 (PLD2) is a crucial signaling mediator that stimulates the production of the second messenger phosphatidic acid. PLD2 is involved in various cellular functions; however, its specific roles in ECs under hypoxia and in vivo angiogenesis remain unclear. In the present study, we investigated the potential roles of PLD2 in ECs under hypoxia and in hypoxia-induced pathological angiogenesis in vivo. APPROACH AND RESULTS: Pld2 knockout ECs exhibited decreased hypoxia-induced cellular responses in survival, migration, and thus vessel sprouting. Analysis of hypoxia-induced gene expression revealed that PLD2 deficiency disrupted the upregulation of hypoxia-inducible factor-1α target genes, including VEGF, PFKFB3, HMOX-1, and NTRK2. Consistent with this, PLD2 contributed to hypoxia-induced hypoxia-inducible factor-1α expression at the translational level. The roles of PLD2 in hypoxia-induced in vivo pathological angiogenesis were assessed using oxygen-induced retinopathy and tumor implantation models in endothelial-specific Pld2 knockout mice. Pld2 endothelial-specific knockout retinae showed decreased neovascular tuft formation, despite a larger avascular region. Tumor growth and tumor blood vessel formation were also reduced in Pld2 endothelial-specific knockout mice. CONCLUSIONS: Our findings demonstrate a novel role for endothelial PLD2 in the survival and migration of ECs under hypoxia via the expression of hypoxia-inducible factor-1α and in pathological retinal angiogenesis and tumor angiogenesis in vivo.

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.

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.

Osmotic stress regulates mammalian target of rapamycin (mTOR) complex 1 via c-Jun N-terminal Kinase (JNK)-mediated Raptor protein phosphorylation.

mTOR complex 1 (mTORC1) is a multiprotein complex that integrates diverse signals including growth factors, nutrients, and stress to control cell growth. Raptor is an essential component of mTORC1 that functions to recruit specific substrates. Recently, Raptor was suggested to be a key target of regulation of mTORC1. Here, we show that Raptor is phosphorylated by JNK upon osmotic stress. We identified that osmotic stress induces the phosphorylation of Raptor at Ser-696, Thr-706, and Ser-863 using liquid chromatography-tandem mass spectrometry. We found that JNK is responsible for the phosphorylation. The inhibition of JNK abolishes the phosphorylation of Raptor induced by osmotic stress in cells. Furthermore, JNK physically associates with Raptor and phosphorylates Raptor in vitro, implying that JNK is responsible for the phosphorylation of Raptor. Finally, we found that osmotic stress activates mTORC1 kinase activity in a JNK-dependent manner. Our findings suggest that the molecular link between JNK and Raptor is a potential mechanism by which stress regulates the mTORC1 signaling pathway.

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.

Proteomic analysis of tumor necrosis factor-alpha (TNF-α)-induced L6 myotube secretome reveals novel TNF-α-dependent myokines in diabetic skeletal muscle.

There is a strong possibility that skeletal muscle can respond to irregular metabolic states by secreting specific cytokines. Obesity-related chronic inflammation, mediated by pro-inflammatory cytokines, is believed to be one of the causes of insulin resistance that results in type 2 diabetes. Here, we attempted to identify and characterize the members of the skeletal muscle secretome in response to tumor necrosis factor-alpha (TNF-α)-induced insulin resistance. To conduct this study, we comparatively analyzed the media levels of proteins released from L6 skeletal muscle cells. We found 28 TNF-α modulated secretory proteins by using separate filtering methods: Gene Ontology, SignalP, and SecretomeP, as well as the normalized Spectral Index for label-free quantification. Ten of these secretory proteins were increased and 18 secretory proteins were decreased by TNF-α treatment. Using microarray analysis of Zuker diabetic rat skeletal muscle combined with bioinformatics and Q-PCR, we found a correlation between TNF-α-mediated insulin resistance and type 2 diabetes. This novel approach combining analysis of the conditioned secretome and transcriptome has identified several previously unknown, TNF-α-dependent secretory proteins, which establish a foothold for research on the different causes of insulin resistance and their relationships with each other.

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.

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.