Neuropharmacological computational analysis of longitudinal electroencephalograms in clozapine-treated patients with schizophrenia using hierarchical dynamic causal modeling.

The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN. The medication duration mainly affects the intrinsic connectivity and NMDA time constant in DMN. Virtual perturbation analysis specified the contribution of each parameter to the cross-spectral density (CSD) of the EEG, particularly intrinsic connectivity and membrane capacitances for CSD frequency shifts and progression. It further reveals that excitatory and inhibitory connectivity complements frequency-specific CSD changes, notably the alpha frequency band in DMN. Positive and negative synergistic interactions exist between neurobiological properties primarily within the same region in patients treated with clozapine. The current study shows how computational neuropharmacology helps explore the multiscale link between neurobiological properties and clinical observations and understand the long-term mechanism of neuropharmacological intervention reflected in clinical EEG.

Small extracellular vesicles derived from patients with persistent atrial fibrillation exacerbate arrhythmogenesis via miR-30a-5p.

Small extracellular vesicles (sEVs) are nanometer-sized membranous vesicles that contribute to the pathogenesis of atrial fibrillation (AF). Here, we investigated the role of sEVs derived from patients with persistent AF in the pathophysiology of AF. First, we evaluated the pathological effects of sEVs derived from the peripheral blood of patients with persistent AF (AF-sEVs). AF-sEVs treatment reduced cell viability, caused abnormal Ca2+ handling, induced reactive oxygen species (ROS) production and led to increased CaMKII activation of non-paced and paced atrial cardiomyocytes. Next, we analyzed the miRNA profile of AF-sEVs to investigate which components of AF-sEVs promote arrhythmias, and we selected six miRNAs that correlated with CaMKII activation. qRT-PCR experiment identified that miR-30a-5p was significantly down-regulated in AF-sEVs, paced cardiomyocytes, and atrial tissues of patients with persistent AF. CaMKII was predicted by bioinformatics analysis as a miR-30a-5p target gene and validated by a dual luciferase reporter; hence, we evaluated the effects of miR-30a-5p on paced cardiomyocytes and validated miR-30a-5p as a pro-arrhythmic signature of AF-sEVs. Consequently, AF-sEVs-loaded with miR-30a-5p attenuated pacing-induced Ca2+-handling abnormalities, whereas AF-sEVs-loaded with anti-miR-30a-5p reversed the change in paced cardiomyocytes. Taken together, the regulation of CaMKII by miR-30a-5p revealed that miR-30a-5p is a major mediator for AF-sEVs-mediated AF pathogenesis. Accordingly, these findings suggest that sEVs derived from patients with persistent AF exacerbate arrhythmogenesis via miR-30a-5p.

Association Between Frailty-Related Factors and Depression among Older Adults.

OBJECTIVES: We analyzed the association between individual frailty-related factors and depression in older adults. METHODS: A total of 796 older adults who underwent geriatric assessments were included in this cross-sectional study. The frailty-related factors studied were grip strength, physical activity, walking speed, weight loss, and recurrent falls. Depression was based on the Geriatric Depression Scale. RESULTS: After adjustment for covariates, recurrent falls were associated with depression in males (OR 3.84, 95% CI 1.30-11.35). Among females, weakest grip strength, slow walking speed, and weight loss were associated with depression (OR 2.61, 95% CI 1.52-4.49; OR 1.78, 95% CI 1.02-3.11; and OR 2.52, 95% CI 1.17-5.44, respectively). Having more frailty-related factors was also associated with higher odds of depression. CONCLUSIONS: The associations between individual frailty-related factors and depression differed among males and females. Further prospective studies on depression and individual frailty-related factors by sex may help elucidate specific targets to be prioritized for clinical assessment and intervention. CLINICAL IMPLICATIONS: Older adults affected by depression and frailty may present different clinical manifestations based on sex, and require different treatment approaches. Clinicians should assess both physical and psychological needs for integrated care in frail older adults.

A computational framework for optimal control of a self-adjustive neural system with activity-dependent and homeostatic plasticity.

The control of the brain system has received increasing attention in the domain of brain science. Most brain control studies have been conducted to explore the brain network's graph-theoretic properties or to produce the desired state based on neural state dynamics, regarding the brain as a passively responding system. However, the self-adjusting nature of neural system after treatment has not been fully considered in the brain control. In the present study, we propose a computational framework for optimal control of the brain with a self-adjustment process in the effective connectivity after treatment. The neural system is modeled to adjust its outgoing effective connectivity as activity-dependent plasticity after treatment, followed by synaptic rescaling of incoming effective connectivity. To control this neural system to induce the desired function, the system's self-adjustment parameter is first estimated, based on which the treatment is optimized. Utilizing this framework, we conducted simulations of optimal control over a functional hippocampal circuitry, estimated using dynamic causal modeling of voltage-sensitive dye imaging from the wild type and mutant mice, responding to consecutive electrical stimuli. Simulation results for optimal control of the abnormal circuit toward a healthy circuit using a single node treatment, neural-type specific treatment as an analogy of medication, and combined treatments of medication and nodal treatment suggest the plausibility of the current framework in controlling the self-adjusting neural system within a restricted treatment setting. We believe the proposed computational framework of the self-adjustment system would help optimal control of the dynamic brain after treatment.

Empirical Bayes estimation of pairwise maximum entropy model for nonlinear brain state dynamics.

The pairwise maximum entropy model (pMEM) has recently gained widespread attention to exploring the nonlinear characteristics of brain state dynamics observed in resting-state functional magnetic resonance imaging (rsfMRI). Despite its unique advantageous features, the practical application of pMEM for individuals is limited as it requires a much larger sample than conventional rsfMRI scans. Thus, this study proposes an empirical Bayes estimation of individual pMEM using the variational expectation-maximization algorithm (VEM-MEM). The performance of the VEM-MEM is evaluated for several simulation setups with various sample sizes and network sizes. Unlike conventional maximum likelihood estimation procedures, the VEM-MEM can reliably estimate the individual model parameters, even with small samples, by effectively incorporating the group information as the prior. As a test case, the individual rsfMRI of children with attention deficit hyperactivity disorder (ADHD) is analyzed compared to that of typically developed children using the default mode network, executive control network, and salient network, obtained from the Healthy Brain Network database. We found that the nonlinear dynamic properties uniquely established on the pMEM differ for each group. Furthermore, pMEM parameters are more sensitive to group differences and are better associated with the behavior scores of ADHD compared to the Pearson correlation-based functional connectivity. The simulation and experimental results suggest that the proposed method can reliably estimate the individual pMEM and characterize the dynamic properties of individuals by utilizing empirical information of the group brain state dynamics.

Complex structure of cytochrome c-cytochrome c oxidase reveals a novel protein-protein interaction mode.

Mitochondrial cytochrome c oxidase (CcO) transfers electrons from cytochrome c (Cyt.c) to O2 to generate H2O, a process coupled to proton pumping. To elucidate the mechanism of electron transfer, we determined the structure of the mammalian Cyt.c-CcO complex at 2.0-Å resolution and identified an electron transfer pathway from Cyt.c to CcO. The specific interaction between Cyt.c and CcO is stabilized by a few electrostatic interactions between side chains within a small contact surface area. Between the two proteins are three water layers with a long inter-molecular span, one of which lies between the other two layers without significant direct interaction with either protein. Cyt.c undergoes large structural fluctuations, using the interacting regions with CcO as a fulcrum. These features of the protein-protein interaction at the docking interface represent the first known example of a new class of protein-protein interaction, which we term "soft and specific". This interaction is likely to contribute to the rapid association/dissociation of the Cyt.c-CcO complex, which facilitates the sequential supply of four electrons for the O2 reduction reaction.

Bayesian estimation of maximum entropy model for individualized energy landscape analysis of brain state dynamics.

The pairwise maximum entropy model (MEM) for resting state functional MRI (rsfMRI) has been used to generate energy landscape of brain states and to explore nonlinear brain state dynamics. Researches using MEM, however, has mostly been restricted to fixed-effect group-level analyses, using concatenated time series across individuals, due to the need for large samples in the parameter estimation of MEM. To mitigate the small sample problem in analyzing energy landscapes for individuals, we propose a Bayesian estimation of individual MEM using variational Bayes approximation (BMEM). We evaluated the performances of BMEM with respect to sample sizes and prior information using simulation. BMEM showed advantages over conventional maximum likelihood estimation in reliably estimating model parameters for individuals with small sample data, particularly utilizing the empirical priors derived from group data. We then analyzed individual rsfMRI of the Human Connectome Project to show the usefulness of MEM in differentiating individuals and in exploring neural correlates for human behavior. MEM and its energy landscape properties showed high subject specificity comparable to that of functional connectivity. Canonical correlation analysis identified canonical variables for MEM highly associated with cognitive scores. Inter-individual variations of cognitive scores were also reflected in energy landscape properties such as energies, occupation times, and basin sizes at local minima. We conclude that BMEM provides an efficient method to characterize dynamic properties of individuals using energy landscape analysis of individual brain states.

Effects of Chronic Low-Dose Internal Radiation on Immune-Stimulatory Responses in Mice.

The Linear-No-Threshold (LNT) model predicts a dose-dependent linear increase in cancer risk. This has been supported by biological and epidemiological studies at high-dose exposures. However, at low-doses (LDR ≤ 0.1 Gy), the effects are more elusive and demonstrate a deviation from linearity. In this study, the effects of LDR on the development and progression of mammary cancer in FVB/N-Tg(MMTVneu)202Mul/J mice were investigated. Animals were chronically exposed to total doses of 10, 100, and 2000 mGy via tritiated drinking water, and were assessed at 3.5, 6, and 8 months of age. Results indicated an increased proportion of NK cells in various organs of LDR exposed mice. LDR significantly influenced NK and T cell function and activation, despite diminishing cell proliferation. Notably, the expression of NKG2D receptor on NK cells was dramatically reduced at 3.5 months but was upregulated at later time-points, while the expression of NKG2D ligand followed the opposite trend, with an increase at 3.5 months and a decrease thereafter. No noticeable impact was observed on mammary cancer development, as measured by tumor load. Our results demonstrated that LDR significantly influenced the proportion, proliferation, activation, and function of immune cells. Importantly, to the best of our knowledge, this is the first report demonstrating that LDR modulates the cross-talk between the NKG2D receptor and its ligands.

Sequential treatment of nitrate and phosphate in groundwater using a permeable reactive barrier system.

When not properly treated, nitrate and phosphate present in groundwater can damage human health and environments. In this study, laboratory column experiments were performed for sequential treatment of nitrate and phosphate in groundwater. Two columns were set up and connected: one to treat nitrate with organic carbon materials (i.e., woodchips) and the other to treat phosphate with basic oxygen furnace (BOF) slag. The columns were operated for a total of 1.6 years. The results showed that nitrate was removed through denitrification and phosphate was removed by precipitation of the phosphate minerals (e.g., hydroxyapatite). BOF slag was effective at removing phosphate, though the high pH (11-12) of the system's effluent water raised a concern for the downgradient areas. Of the three subsequent experiments performed, pH was near neutral when the effluent of the BOF slag column was passed through local soil. Sparging with CO2 and air, in contrast, resulted in pH levels that were either too low (5 in the case of CO2) or too high (9.5 in the case of air). The study shows that sequential permeable reactive barrier (PRB) systems consisting of woodchips and BOF slag can be effective for removal of nitrate and phosphate in groundwater and they can be a long-term remedial solution for groundwater contaminated with both nitrate and phosphate.

Dynamic causal modeling of hippocampal activity measured via mesoscopic voltage-sensitive dye imaging.

The aim of this paper is to present a dynamic causal modeling (DCM) framework for hippocampal activity measured via voltage-sensitive dye imaging (VSDI). We propose a DCM model of the hippocampus that summarizes interactions between the hilus, CA3 and CA1 regions. The activity of each region is governed via a neuronal mass model with two inhibitory and one/two excitatory neuronal populations, which can be linked to measurement VSDI by scaling neuronal activity. To optimize the model structure for the hippocampus, we propose two Bayesian schemes: Bayesian hyperparameter optimization to estimate the unknown electrophysiological properties necessary for constructing a mesoscopic hippocampus model; and Bayesian model reduction to determine the parameterization of neural properties, and to test and include potential connections (morphologically inferred without direct evidence yet) in the model by evaluating group-level model evidence. The proposed method was applied to model spatiotemporal patterns of accumulative responses to consecutive stimuli in separate groups of wild-type mice and epileptic aristaless-related homeobox gene (Arx) conditional knock-out mutant mice (Arx-/+;Dlx5/6CRE-IRES-GFP) in order to identify group differences in the effective connectivity within the hippocampus. The causal role of each group-differing connectivity in generating mutant-like responses was further tested. The group-level analysis identified altered intra- and inter-regional effective connectivity, some of which are crucial for explaining mutant-like responses. The modelling results for the hippocampal activity suggest the plausibility of the proposed mesoscopic hippocampus model and the usefulness of utilizing the Bayesian framework for model construction in the mesoscale modeling of neural interactions using DCM.

Therapeutic potential of miR-21 regulation by human peripheral blood derived-small extracellular vesicles in myocardial infarction.

Small extracellular vesicles (sEVs) as natural membranous vesicles are on the frontiers of nanomedical research, due to their ability to deliver therapeutic molecules such as microRNAs (miRNAs). The miRNA-21 (miR-21) is thought to be involved in the initiation and development of myocardial infarction (MI). Here, we examined whether miR-21 regulation using human peripheral blood-derived sEVs (PB-sEVs) could serve as a potential therapeutic strategy for MI. First, we examined miR-21 levels in hypoxic conditions and validated the ability of PB-sEVs to serve as a potential delivery system for miRNAs. Further, bioinformatics analysis and luciferase assay were performed to identify target genes of miR-21 mechanistically. Among numerous target pathways, we focused on nitrogen metabolism, which remains relatively unexplored compared with other possible miR-21-mediated pathways; hence, we aimed to determine novel target genes of miR-21 related to nitrogen metabolism. In hypoxic conditions, the expression of miR-21 was significantly up-regulated and correlated with nitric oxide synthase 3 (NOS3) levels, which in turn influences cardiac function. The down-regulation of miR-21 expression by PB-sEVs loaded with anti-miR-21 significantly improved survival rates, consistent with the augmentation of cardiac function. However, the up-regulation of miR-21 expression by PB-sEVs loaded with miR-21 reversed these effects. Mechanistically, miR-21 targeted and down-regulated the mRNA and protein expression of striatin (STRN), which could regulate NOS3 expression. In conclusion, we identified a novel therapeutic strategy to improve cardiac function by regulating the expression of miR-21 with PB-sEVs as an miR-21 or anti-miR-21 delivery vehicle and confirmed the miR-21-associated nitrogen metabolic disorders in MI.

Expression of miRNAs in circulating exosomes derived from patients with persistent atrial fibrillation.

Atrial fibrillation (AF), the most common type of cardiac arrhythmia, is thought to be regulated by changes in microRNA (miRNA) expression. However, the evidence for this is inconsistent. The high stability and expression of circulating exosomal miRNAs may allow their use as candidate biomarkers. For the discovery phase, exosomes were isolated from the serum of patients with supraventricular tachycardia (SVT) as the controls (n = 5) and with paroxysmal AF (n = 4) and persistent AF (n = 5) for microarray analysis of miRNAs. Forty-five miRNAs were expressed significantly higher (>1.5-fold) in patients with persistent AF, but not in patients with paroxysmal AF, relative to the levels in patients with SVT control. Notably, expression of 5 miRNAs (miRNA-103a, -107, -320d, -486, and let-7b) was elevated by more than 4.5-fold in patients with persistent AF. For the validation phase, miRNAs were analyzed using quantitative RT-PCR analysis in exosomes from the serum of patients with SVT control (n = 20) and patients with persistent AF (n = 40). These miRNAs and their target genes were involved in atrial function and structure, oxidative stress, and fibrosis pathways. These findings suggest that serum exosomal miRNAs might be used as novel biomarkers to reflect the progression of AF.-Mun, D., Kim, H., Kang, J.-Y., Park, H., Park, H., Lee, S.-H., Yun, N., Joung, B. Expression of miRNAs in circulating exosomes derived from patients with persistent atrial fibrillation.

Structural basis for specific recognition of core fucosylation in N-glycans by Pholiota squarrosa lectin (PhoSL).

Fucosylation of the N-glycan core via the α1-6 linkage (core fucosylation) is detected in specific types of cancers and related diseases, and thereby serves for a relevant biomarker. The lectin from a mushroom Pholiota squarrosa (PhoSL) shows a clear specificity to core fucosylation, without recognizing those with other types of fucosylation, such as the H type via the α1-2 linkage or the Lewis type via the α1-3 or α1-4 linkage. Here we determined the crystal structure of the PhoSL trimer in complex with a disaccharide fucose(α1-6)N-acetylglucosamine (GlcNAc). In the three sugar-binding pockets of PhoSL, extensive hydrophobic and hydrogen-bonding contacts were formed with the fucose moiety. In contrast, the GlcNAc moiety showed only a few hydrophobic and hydrogen-bonding contacts. To elucidate the mechanism for the specificity, we performed molecular dynamics simulations on this disaccharide and a trisaccharide fucose(α1-6)[GlcNAc(ß1-4)]GlcNAc in complex with PhoSL. It was observed that the GlcNAc corresponding to the outer one of the N-glycan core entered the sugar-binding pocket with the N-acetyl group placed stably at the bottom, forming extensive hydrophobic and hydrogen-bonding interactions. In addition, these glycans adopted unstressed favorable conformations when bound to PhoSL. In contrast, H- and Lewis-types of fucosylated trisaccharides adopting favorable conformations caused inevitable steric hindrance with the steep edge of the binding pocket, when docked with PhoSL. Therefore, the specificity to core fucosylation of PhoSL was achieved by a combination of these preferential and exclusive mechanisms.

Dynamic causal modeling for calcium imaging: Exploration of differential effective connectivity for sensory processing in a barrel cortical column.

Multi-photon calcium imaging (CaI) is an important tool to assess activities of neural populations within a column in the sensory cortex. However, the complex asymmetrical interactions among neural populations, termed effective connectivity, cannot be directly assessed by measuring the activity of each neuron or neural population using CaI but calls for computational modeling. To estimate effective connectivity among neural populations, we proposed a dynamic causal model (DCM) for CaI by combining a convolution-based dynamic neural state model and a dynamic calcium ion concentration model for CaI signals. After conducting a simulation study to evaluate DCM for CaI, we applied it to an experimental CaI signals measured at the layer 2/3 of a barrel cortical column that differentially responds to hit and error whisking trials in mice. We first identified neural populations and constructed computational models with intrinsic connectivity of neural populations within the layer 2/3 of the barrel cortex and extrinsic connectivity with latent external modes. Bayesian model inversion and comparison shows that interactions with latent inhibitory and excitatory external modes explain the observed CaI signals within the barrel cortical column better than any other tested models, with a single external mode or without any latent modes. The best model also showed differential intrinsic and extrinsic effective connectivity between hit and error trials in the functional hierarchy. Both simulation and experimental results suggest the usefulness of DCM for CaI in terms of exploration of hierarchical interactions among neural populations observed in CaI.

Is it possible for short peptide composed of positively- and negatively-charged "hydrophilic" amino acid residue-clusters to form metastable "hydrophobic" packing?

We theoretically and experimentally analyzed a conformational ensemble of a small, characteristic polypeptide consisting of positively- and negatively-charged amino acid residue clusters, (Lys)9(Glu)9(Lys)9, designed based on the supercoiled DNA-recognition (SDR) domain, with the capability of preferentially binding to supercoiled DNA. Advanced molecular dynamics (MD) simulations coupled with a generalized ensemble technique revealed that substantial amounts of ordered, helical structures were present at the boundaries of the Lys and Glu segments in the obtained conformational ensemble. In fact, the helical content of the peptide calculated from our MD simulations was consistent with that estimated from our experimental analysis employing circular dichroism (CD) spectroscopy. The statistical analysis of the structural ensemble revealed the metastable hydrophobic contact clusters, which were stabilized by closely cohesive residue contacts, formed through "hybrid" hydrophobic (methylene groups) and electrostatic (salt bridges) residue contacts. Both short-range and long-range residue contacts were involved in the metastable hydrophobic clusters, constituting the aforementioned local helical conformations and the compact entire structures, respectively. A significant helical propensity was also found in the (Lys)n and (Glu)m boundaries of other conventional protein structures deposited in the Protein Data Bank (PDB), thus indicating the generality of this conformational trend that has been identified herein.

Cardiac-specific delivery by cardiac tissue-targeting peptide-expressing exosomes.

Naturally occurring RNA carriers such as exosomes might be an untapped source of effective delivery vehicles. However, if exosomes are to be exploited for therapeutic applications, they must target specific tissues or cell types to avoid off-target effects. This study evaluated whether genetic modification of exosomes could enhance exosome delivery to heart cells and heart tissue without toxicity. Exosomes expressing cardiac-targeting peptide (CTP)-Lamp2b on the exosomal membrane (CTP-Exo) were generated by introducing vectors encoding CTP-Lamp2b into HEK 293 cells. The expression of CTP-Lamp2b peptide on exosomes was stabilized by attaching glycosylation sequences. Exosomes expressing only Lamp2b on exosomal membranes (CTL-Exo) were generated as a control. The in vitro and in vivo uptake of CTL-Exo and CTP-Exo was evaluated in cell lines and mice. Both exosomes were delivered to HEK 293 and H9C2 cells. The delivery of the exosome was not different between CTP-Exo and CTL-Exo in HEK 293 cells, whereas the delivery of CTP-Exo was 16% greater than that of CTL-Exo in H9C2 cells (P = 0.047). Cell viability was maintained at almost 100% with different dosages of both CTL-Exo and CTP-Exo. Moreover, compared with CTL-Exo, the in vivo delivery of exosomes to the hearts of mice was increased by 15% with CTP-Exo (P = 0.035). The delivery to livers and spleens was not different between the two exosomes. Genetic modification of exosomes by expressing CTP-Lamp2b on the exosomal membrane enhanced exosome delivery to heart cells and the heart tissue. These results suggested that CTP-Exo might be used as a therapeutic tool for heart disease.

Impacts of Phragmites australis Invasion on Soil Enzyme Activities and Microbial Abundance of Tidal Marshes.

The rapid expansion of Phragmites australis in brackish marshes of the East Coast of the USA has drawn much attention, because it may change vegetation diversity and ecosystem functions. In particular, higher primary production of Phragmites than that of other native species such as Spartina patens and Schoenoplectus americanus has been noted, suggesting possible changes in carbon storage potential in salt marshes. To better understand the long-term effect of the invasion of Phragmites on carbon storage, however, information on decomposition rates of soil organic matter is essential. To address this issue, we compared microbial enzyme activities and microbial functional gene abundances (fungi, laccase, denitrifier, and methanogens) in three depths of soils with three different plants in a brackish marsh in Maryland, USA. Laccase and phenol oxidase activities were measured to assess the decomposition potential of recalcitrant carbon while ß-glucosidase activity was determined as proxy for cellulose decomposition rate. Microbial activities near the surface (0-15 cm) were the highest in Spartina-community sites followed by Phragmites- and Schoenoplectus-community sites. A comparison of stable isotopic signatures (δ13C and δ15N) of soils and plant leaves suggests that deep organic carbon in the soils mainly originated from Spartina, and only the surface soils may have been influenced by Phragmites litter. In contrast, fungal, laccase, and denitrifier abundances determined by real-time qPCR exhibited no discernible patterns among the surface soils of the three vegetation types. However, the abundance of methanogens was higher in the deep Phragmites-community soil. Therefore, Phragmites invasion will accelerate CH4 emission by greater CH4 production in deep soils with abundant methanogens, although enzymatic mechanisms revealed the potential for larger C accumulation by Phragmites invasion in salt marshes in the east coast of the USA.

Development and Evaluation of "Chronic Illness Care Smartphone Apps" on Nursing Students' Knowledge, Self-efficacy, and Learning Experience.

This study developed smartphone-based virtual experiential nursing applications to care for patients with chronic illness, especially patients with hypertension and diabetes, and evaluated the effect of the applications on nursing students' knowledge, self-efficacy, and learning experiences. Applications using gamification elements were developed according to the steps of assessment, design, development, implementation, and evaluation. Knowledge and self-efficacy were assessed via questionnaires, while learning experiences were assessed via six focus group interviews after the applications were used for 1 week. Quantitative data were analyzed using descriptive analysis, χ test, Fisher's exact test, t test for the homogeneity of participants (experimental, 49; control, 43), an independent t test, and a paired t test for effectiveness in each group. Qualitative data were analyzed using qualitative thematic analysis. Knowledge on hypertension (t = 4.41, P < .001) and diabetes (t = 2.45, P < .009), as well as self-efficacy for hypertension (t = 3.08, P < .002) and diabetes (t = 1.75, P < .043), significantly improved in the experimental group compared to the control group. Students may use the applications as complementary learning resources without the limitations of time and space, and students were satisfied overall with their use. The chronic illness care smartphone applications are effective learning resources that assist students in assessing patients' health problems and implementing nursing care plans to improve patient conditions.

Energy landscape analysis of the subcortical brain network unravels system properties beneath resting state dynamics.

The configuration of the human brain system at rest, which is in a transitory phase among multistable states, remains unknown. To investigate the dynamic systems properties of the human brain at rest, we constructed an energy landscape for the state dynamics of the subcortical brain network, a critical center that modulates whole brain states, using resting state fMRI. We evaluated alterations in energy landscapes following perturbation in network parameters, which revealed characteristics of the state dynamics in the subcortical brain system, such as maximal number of attractors, unequal temporal occupations, and readiness for reconfiguration of the system. Perturbation in the network parameters, even those as small as the ones in individual nodes or edges, caused a significant shift in the energy landscape of brain systems. The effect of the perturbation on the energy landscape depended on the network properties of the perturbed nodes and edges, with greater effects on hub nodes and hubs-connecting edges in the subcortical brain system. Two simultaneously perturbed nodes produced perturbation effects showing low sensitivity in the interhemispheric homologous nodes and strong dependency on the more primary node among the two. This study demonstrated that energy landscape analysis could be an important tool to investigate alterations in brain networks that may underlie certain brain diseases, or diverse brain functions that may emerge due to the reconfiguration of the default brain network at rest.

A nationwide study of the incidence rate of herb-induced liver injury in Korea.

Discrepant incidence has been reported regarding the incidence of herb-induced liver injury (HILI). To address the growing worldwide concern of HILI, we evaluated the risk of HILI in a nationwide prospective study. Between April 2013 and January 2016, 1001 inpatients (360 males and 641 females) from 10 tertiary hospitals throughout South Korea were treated with herbal drugs and had their liver enzymes periodically measured. A total of six patients met the criteria for HILI with RUCAM scores ranging from 4 to 7. All these participants were women and developed the hepatocellular type of HILI. One HILI participant met the criteria for Hy's law; however, none of six cases presented clinical symptoms related to liver injury. This is the first nationwide prospective study that estimated the extent of the incidence of HILI [total: 0.60%, 95% confidence interval (CI) 0.12-1.08; women: 0.95%, 95% CI 0.19-1.68] and described its features in hospitalized participants.