Micro-pillar tunnel stamp for enhanced transdermal delivery of topical drug formulations.

Dissolving microneedles (DMNs), despite their minimally invasive drug administration, face challenges in skin insertion and drug-loading capacity, which lead to less effective drug delivery. The micro-pillar tunnel stamp (MPTS) was designed to enhance the transdermal delivery efficacy of externally provided topical formulations via the creation of microchannels. The tunnel and canal of the MPTS enable the simultaneous application of DMNs and topical drugs. The application of micro-pillar-polycaprolactone (MP-PCL), which is a DMN made of a slowly dissolving polymer, exhibited a drug permeation rate 1.3-fold and 2.6-fold higher than that of micro-pillar-hyaluronic acid (MP-HA), a DMN made of a rapidly dissolving polymer, and the topical group, respectively. The base diameter of MP-PCL was set to 700 µm for maximized delivery efficacy, achieving 2.8-fold higher L-ascorbic acid accumulation than that of the topical group. In vivo analysis showed that, compared to topical administration, MPTS-delivered lidocaine had 5-fold greater permeation and the MPTS-delivered group showed 1.25-fold higher skin residual amount, confirming enhanced delivery. Thus, the optimized MPTS system can be presented as an attractive alternative to overcome the limitations of the existing MN systems such as incomplete insertion and limited drug-loading capacity, enhancing the delivery of topical formulations in the transdermal market. STATEMENT OF SIGNIFICANCE: We developed a micro-pillar tunnel stamp (MPTS) to enhance the delivery of externally provided topical formulations. The functional tunnel and canal of the MPTS enabled the simultaneous application of a dissolving microneedle (DMN) array insertion and administration of external topical drugs. Upon insertion, the DMNs created skin microchannels that allowed the externally administered drug to diffuse. DMNs were fabricated using polycaprolactone (PCL), a slowly dissolving polymer, to maintain their structure inside the skin and prolong the opening duration of the microchannels. This system achieved significantly improved delivery of topically administered external drugs via integration with slowly dissolving DMNs, while offering the possibility of its development as a universal delivery system for various topical pharmaceuticals.

Light-FER: A Lightweight Facial Emotion Recognition System on Edge Devices.

Facial emotion recognition (FER) systems are imperative in recent advanced artificial intelligence (AI) applications to realize better human-computer interactions. Most deep learning-based FER systems have issues with low accuracy and high resource requirements, especially when deployed on edge devices with limited computing resources and memory. To tackle these problems, a lightweight FER system, called Light-FER, is proposed in this paper, which is obtained from the Xception model through model compression. First, pruning is performed during the network training to remove the less important connections within the architecture of Xception. Second, the model is quantized to half-precision format, which could significantly reduce its memory consumption. Third, different deep learning compilers performing several advanced optimization techniques are benchmarked to further accelerate the inference speed of the FER system. Lastly, to experimentally demonstrate the objectives of the proposed system on edge devices, Light-FER is deployed on NVIDIA Jetson Nano.

Optimizing Face Recognition Inference with a Collaborative Edge-Cloud Network.

The rapid development of deep-learning-based edge artificial intelligence applications and their data-driven nature has led to several research issues. One key issue is the collaboration of the edge and cloud to optimize such applications by increasing inference speed and reducing latency. Some researchers have focused on simulations that verify that a collaborative edge-cloud network would be optimal, but the real-world implementation is not considered. Most researchers focus on the accuracy of the detection and recognition algorithm but not the inference speed in actual deployment. Others have implemented such networks with minimal pressure on the cloud node, thus defeating the purpose of an edge-cloud collaboration. In this study, we propose a method to increase inference speed and reduce latency by implementing a real-time face recognition system in which all face detection tasks are handled on the edge device and by forwarding cropped face images that are significantly smaller than the whole video frame, while face recognition tasks are processed at the cloud. In this system, both devices communicate using the TCP/IP protocol of wireless communication. Our experiment is executed using a Jetson Nano GPU board and a PC as the cloud. This framework is studied in terms of the frame-per-second (FPS) rate. We further compare our framework using two scenarios in which face detection and recognition tasks are deployed on the (1) edge and (2) cloud. The experimental results show that combining the edge and cloud is an effective way to accelerate the inferencing process because the maximum FPS achieved by the edge-cloud deployment was 1.91× more than the cloud deployment and 8.5× more than the edge deployment.

Functional improvement of collagen-based bioscaffold to enhance periodontal-defect healing via combination with dietary antioxidant and COMP-angiopoietin 1.

Scaffolds combined with bioactive agents can enhance bone regeneration at therapeutic sites. We explore whether combined supplementation with coumaric acid and recombinant human-cartilage oligomeric matrix protein-angiopoietin 1 (rhCOMP-Ang1) is an ideal approach for bone tissue engineering. We developed coumaric acid-conjugated absorbable collagen scaffold (CA-ACS) and investigated whether implanting CA-ACS in combination with rhCOMP-Ang1 facilitates ACS- or CA-ACS-mediated bone formation using a rat model of critically sized mandible defects. We examined the mechanisms by which coumaric acid and rhCOMP-Ang1 regulate behaviors of human periodontal ligament fibroblasts (hPLFs). The CA-ACS exhibits greater anti-degradation and mechanical strength properties than does ACS alone. Implanting CA-ACS loaded with rhCOMP-Ang1 greatly enhances bone regeneration at the defect via the activation of angiogenic, osteogenic, and anti-osteoclastic responses compared with other rat groups implanted with an ACS alone or CA-ACS. Treatment with both rhCOMP-Ang1 and coumaric acid increases proliferation, mineralization, and migration of cultured hPLFs via activation of the Ang1/Tie2 signaling axis at a greater rate than treatment with either of them alone. Collectively, this study demonstrates that CA-ACS impregnated with rhCOMP-Ang1 enhances bone regeneration at therapeutic sites, and this enhancement is associated with a synergistic interaction between rhCOMP-Ang1-mediated angiogenesis and coumaric acid-related antioxidant responses.

No Association between Metabolic Syndrome and Periodontitis in Korean Postmenopausal Women.

This study aimed to determine the association between metabolic syndrome (MetS) and periodontitis in Korean postmenopausal women. The study selected 3320 menopause women (40-79-year-old) from those who participated in the seventh Korea National Health and Nutrition Survey (2016-2018). This association was determined using frequency and multiple logistic regression analyses. The prevalence of MetS in postmenopausal women was 33.2%, and among the MetS components, abdominal obesity showed a higher odds ratio of periodontitis by 1.36 (95% confidence interval (CI): 1.12-1.65; p < 0.05). The odds ratio for periodontitis was 1.34 times higher (95% CI: 1.12-1.60) in the MetS prevalence group with three or more MetS components (p < 0.05); however, after adjusting for demographic characteristics and health behavior variables, it was not statistically significant. Therefore, our results indicated that MetS has no association with periodontitis in postmenopausal women after adjusting for confounding variables.

Association between Metabolic Syndrome and the Number of Remaining Teeth in Postmenopausal Women: A Cross-Sectional Analysis Using the Korean National Health and Nutritional Examination Survey.

There are very few studies on metabolic syndrome (MetS) and oral health in postmenopausal women. The purpose of this cross-sectional study was to determine the association between MetS and its components and the number of remaining teeth in postmenopausal women in Korea. The study selected 3320 menopausal women (40-79 years old) from those who participated in the seventh Korea National Health and Nutrition Survey (2016-2018). Multiple regression and multiple logistic regression analyses were performed to determine the association between MetS and its components and the number of remaining teeth. According to the multiple regression analysis, the regression coefficient (B) values were -1.62 (p < 0.05), -1.31 (p < 0.05), -1.60 (p < 0.05), and -2.28 (p < 0.05) in the hypertension group, hyperglycemia group, low high-density lipoprotein (HDL) cholesterol group, and MetS prevalence group, respectively. This indicates that the number of remaining teeth was lower in the MetS prevalence group as compared to the non-prevalence groups. As observed in the multiple logistic regression analysis, the odds ratio of the number of remaining teeth (less than 20) was higher in the MetS prevalence group (1.82 (p < 0.05)) as compared to the non-prevalence groups (1.25 (p < 0.05) in the abdominal obesity group, 1.50 (p < 0.05) in the hypertension group, 1.36 (p <0.05) in the hyperglycemia group, and 1.72 (p < 0.05) in the low HDL cholesterol group). Therefore, our results indicate that abdominal obesity, hypertension, diabetes, dyslipidemia, and prevalence of MetS are associated with tooth loss in postmenopausal women.

Calcium bridging drives polysaccharide co-adsorption to a proxy sea surface microlayer.

Saccharides comprise a significant mass fraction of organic carbon in sea spray aerosol (SSA), but the mechanisms through which saccharides are transferred from seawater to the ocean surface and eventually into SSA are unclear. It is hypothesized that saccharides cooperatively adsorb to other insoluble organic matter at the air/sea interface, known as the sea surface microlayer (SSML). Using a combination of surface-sensitive infrared reflection-absorption spectroscopy and all-atom molecular dynamics simulations, we demonstrate that the marine-relevant, anionic polysaccharide alginate co-adsorbs to an insoluble palmitic acid monolayer via divalent cationic bridging interactions. Ca2+ induces the greatest extent of alginate co-adsorption to the monolayer, evidenced by the ∼30% increase in surface coverage, whereas Mg2+ only facilitates one-third the extent of co-adsorption at seawater-relevant cation concentrations due to its strong hydration propensity. Na+ cations alone do not facilitate alginate co-adsorption, and palmitic acid protonation hinders the formation of divalent cationic bridges between the palmitate and alginate carboxylate moieties. Alginate co-adsorption is largely confined to the interfacial region beneath the monolayer headgroups, so surface pressure, and thus monolayer surface coverage, only changes the amount of alginate co-adsorption by less than 5%. Our results provide physical and molecular characterization of a potentially significant polysaccharide enrichment mechanism within the SSML.

Determining Average Linear Dimension and Volume of Korean Lungs for Lung Phantom Construction.

ABSTRACT: The purpose of this study was to determine the average size and volume of lungs and to simulate the morphology of internal organs for the development of a Korean adult lung phantom. The body-size data of 2,195 males and 2,293 females aged between 20 and 60 y were included to calculate the average physical dimensions. Two hundred datasets of computed tomography corresponding to the average physique range were collected to measure the average linear dimensions (the length of x, y, and z-axis) of lungs. One set of lung CT images was finally obtained and converted to three-dimensional (3D) format. To confirm the validity of the new lung model, physical lung phantoms were constructed using International Commission on Radiation Units and Measurements (ICRU) density and similar density to what was obtained from the human CT image and then compared with the Lawrence Livermore National Laboratory (LLNL) phantom. The mean size of the chest width and thickness was 31.8 ± 2.8 and 21.4 ± 1.9 cm for males and 28.0 ± 1.6 cm and 19.4 ± 2.0 cm for females, respectively. The standard deviation of the lung dimension in this group was ± 3.0 cm in length, ± 0.8 cm in width, and ± 2.27 cm in depth. The two modified lung phantoms showed highly accurate geometry and linear attenuation coefficient vs. those of the LLNL phantom. The difference in CT number was ± 2% HU for the LLNL phantom and ± 4% HU for the human CT image based on a CT examination conducted using the chest CT protocol. Moreover, both lungs weighed 734 g to 1,246 g, within the range of the reference value of the ICRU report. These results demonstrate that a new lung model based on average linear dimension measurement in a group with average physique simulated the features and physical properties of real human lungs and facilitated further studies for phantom construction.

Application of machine learning approaches for osteoporosis risk prediction in postmenopausal women.

Many predictive tools have been reported for assessing osteoporosis risk. The development and validation of osteoporosis risk prediction models were supported by machine learning. INTRODUCTION: Osteoporosis is a silent disease until it results in fragility fractures. However, early diagnosis of osteoporosis provides an opportunity to detect and prevent fractures. We aimed to develop machine learning approaches to achieve high predictive ability for osteoporosis risk that could help primary care providers identify which women are at increased risk of osteoporosis and should therefore undergo further testing with bone densitometry. METHODS: We included all postmenopausal Korean women from the Korea National Health and Nutrition Examination Surveys (KNHANES V-1, V-2) conducted in 2010 and 2011. Machine learning models using methods such as the k-nearest neighbors (KNN), decision tree (DT), random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), artificial neural networks (ANN), and logistic regression (LR) were developed to predict osteoporosis risk. We analyzed the effect of applying the machine learning algorithms to the raw data and featuring the selected data only where the statistically significant variables were included as model inputs. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were used to evaluate performance among the seven models. RESULTS: A total of 1792 patients were included in this study, of which 613 had osteoporosis. The raw data consisted of 19 variables and achieved performances (in terms of AUROCs) of 0.712, 0.684, 0.727, 0.652, 0.724, 0.741, and 0.726 for KNN, DT, RF, GBM, SVM, ANN, and LR with fivefold cross-validation, respectively. The feature selected data consisted of nine variables and achieved performances (in terms of AUROCs) of 0.713, 0.685, 0.734, 0.728, 0.728, 0.743, and 0.727 for KNN, DT, RF, GBM, SVM, ANN, and LR with fivefold cross-validation, respectively. CONCLUSION: In this study, we developed and compared seven machine learning models to accurately predict osteoporosis risk. The ANN model performed best when compared to the other models, having the highest AUROC value. Applying the ANN model in the clinical environment could help primary care providers stratify osteoporosis patients and improve the prevention, detection, and early treatment of osteoporosis.

Effect of saphenous vein diameter and reflux time on stump length after cyanoacrylate closure.

Cyanoacrylate closure (CAC) has recently been introduced for the treatment of incompetent saphenous veins. The purpose of the present study is to investigate the correlation of the saphenous vein diameter and reflux time (RT) with the stump length after CAC. A retrospective review was performed using prospectively collected data of CAC patients. The pre-operative saphenous vein diameter and RT were measured. The stump length was measured immediately after the procedure and at 1 week. Pearson's correlation analysis was applied to determine the correlation between the saphenous vein diameter or RT and stump length. A total of 32 saphenous veins were closed in 21 patients, 15 of whom were female. The mean age was 56.9±12.6 years (range, 31-73 years). Complete closure was achieved in all patients. The pre-operative mean diameter was 7.0±2.2 mm. The mean stump lengths were 26.1±10.2 and 28.1±13.6 mm on post-operative days 0 and 7, respectively (P=0.002). The Pearson coefficients for the correlation between the saphenous vein diameter and stump length on post-operative days 0 and 7 were 0.528 (P=0.005) and 0.177 (P=0.430), respectively. Furthermore, the Pearson coefficients for the correlation between the RT and stump length on post-operative days 0 and 7 were -0.215 (P=0.282) and 0.019 (P=0.938), respectively. In conclusion, CAC is effective modality for the treatment of saphenous vein insufficiency. The stump length increased with the diameter of the saphenous veins, while the RT had no marked effect on the stump length. Therefore, the glue injection should be initiated from the instructed position to avoid glue extension into deep veins and to prevent elongating the stump length.

Low-dose ionizing radiation attenuates mast cell migration through suppression of monocyte chemoattractant protein-1 (MCP-1) expression by Nr4a2.

Purpose: The aim of this study was to investigate whether low-dose ionizing radiation attenuates mast cell migration by modulating migration-associated signaling pathways and the expression of chemotactic cytokines.Materials and methods: IgE-sensitized RBL-2H3 mast cells were exposed with ionizing radiation at 0.01, 0.05, 0.1, or 0.5 Gy using a 137Cs γ-irradiator and stimulated with 2,4-dinitrophenol-human serum albumin. Cell migration was determined using a transwell assay system, F-actin distribution using Alex Fluor 488-conjugated phalloidin, expression of various signaling proteins by Western blotting, mRNA expression by RT-PCR.Results: Low-dose ionizing radiation significantly suppressed mast cell migration induced by IgE-mediated mast cell activation. Furthermore, low-dose ionizing radiation altered cell morphology, as reflected by changes in F-actin distribution, and inhibited the activation of PI3K, Btk, Rac1, and Cdc42. These effects were mediated by Nr4a2, an immune-modulating factor. Knockdown of Nr4a2 reduced mast cell migration, inhibited the PI3K and Btk signaling pathways, and reduced expression of the chemotactic cytokine monocyte chemoattractant protein-1 (MCP-1). We further demonstrated that direct blockade of MCP-1 using neutralizing antibodies inhibits mast cell migration.Conclusion: Low-dose ionizing radiation inhibits mast cell migration through the regulation production of MCP-1 by Nr4a2 in the activated mast cell system.

Reading simple and complex facial expressions in patients with major depressive disorder and anxiety disorders.

AIM: Decoding facial expression is important for psychological well-being. This study examined facial emotion recognition of simple/complex and pleasant/unpleasant emotions in patients with major depressive disorder (MDD) and anxiety disorders (AnD). METHODS: Patients with MDD (n = 37), AnD (n = 36) and healthy controls (HC) (n = 40) participated in this study. The recognition accuracy of emotional faces was calculated. RESULTS: Patients with MDD had significantly lower recognition accuracy compared to HC. Patients with MDD exhibited lower recognition accuracy for simple emotions compared to patients with AnD and HC, and lower accuracy for complex emotions compared only to HC. Patients with AnD and HC showed comparable recognition accuracy for simple emotions, which were lower than that of patients with MDD. However, in recognition accuracy of complex emotions, AnD was not significantly different from either MDD or HC. CONCLUSIONS: Patients with MDD and AnD have a distinctive difficulty with the recognition of facial expressions. The recognition of complex emotions in patients with MDD and AnD should be studied further.

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study.

OBJECTIVE: The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses. METHODS: A 5 × 5 × 5 mm(3) uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current-time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5-7) and knowledge-based IMR (soft-tissue Levels 1-3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed. RESULTS: The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs. CONCLUSION: At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment. ADVANCES IN KNOWLEDGE: Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients.

Soluble RANKL expression in Lactococcus lactis and investigation of its potential as an oral vaccine adjuvant.

BACKGROUND: To initiate mucosal immune responses, antigens in the intestinal lumen must be transported into gut-associated lymphoid tissue through M cells. Recently, it has been increasingly recognized that receptor activator of NF-kB ligand (RANKL) controls M cell differentiation by interacting with RANK expressed on the sub-epithelium of Peyer's patches. In this study, we increased the number of M cells using soluble RANKL (sRANKL) as a potent mucosal adjuvant. RESULTS: For efficient oral delivery of sRANKL, we constructed recombinant Lactococcus lactis (L. lactis) IL1403 secreting sRANKL (sRANKL-LAB). The biological activity of recombinant sRANKL was confirmed by observing RANK-RANKL signaling in vitro. M cell development in response to oral administration of recombinant L. lactis was determined by 1.51-fold higher immunohistochemical expression of M cell marker GP-2, compared to that of non-treatment group. In addition, an adjuvant effect of sRANKL was examined by immunization of mice with M-BmpB as a model antigen after treatment with sRANKL-LAB. Compared with the wild-type L. lactis group, the sRANKL-LAB group showed significantly increased systemic and mucosal immune responses specific to M-BmpB. CONCLUSIONS: Our results show that the M cell development by sRANKL-LAB can increase the antigen transcytotic capability of follicle-associated epithelium, and thereby enhance the mucosal immune response, which implies that oral administration of sRANKL is a promising adjuvant strategy for efficient oral vaccination.

Improvement of Chemical Stability of BaCe0.9Y0.1O3/BaCe0.6Zr0.3Y0.1O3 Bi-Layer Electrolyte.

Doped-BaCeO3 has high protonic conductivity at intermediate temperature, but poor chemical stability. In contrast, doped-BaZrO3 is rather stable, but has poor protonic conductivity. In this study, the BCY-BCZY bi-layer system was investigated in the hope of the synergetic improvement of high conductivity and good chemical stability. Nano-sized the BCY and modified-BCZY powders were prepared by the citric-nitrate route and bi-layer electrolyte made of BCY covered with a thin film BCY-BCZY deposited by the electrostatic slurry spray deposition. The improvement of chemical stability, measured in CO2 atmosphere, is turned out to be resulted from the substitution of Zr4+ cation. Overall, the BCY-BCZY bi-layer electrolyte shows promising improvement in chemical stability against produced water on the cathode side during the cell operation.

An amperometric nanobiosensor for the selective detection of K⁺-induced dopamine released from living cells.

A highly sensitive amperometric sensor has been studied for selective monitoring of K(+)-induced dopamine released from dopaminergic cells (PC12) which is based on an EDTA immobilized-poly(1,5-diaminonaphthalne) (poly-DAN) layer comprising graphene oxide (GO) and gold nanoparticles (GO/AuNPs). The integration of a negatively charged probe molecule on the poly-DAN/GO/AuNPs nanohybrid attained the signal enhancement to discriminate dopamine (DA) molecules from foreign species by catalytic effect and surface charge, and hydrogen bonding-based interactions with a probe molecule. The sensor performance and morphology were investigated using voltammetry, impedance spectrometry, SEM, and XPS. Experimental variables affecting the analytical performance of the sensor probe were optimized, and linear response was observed in the range of 10 nM-1 µM with a detection limit of 5.0 nM (±0.01) for DA. Then, the sensor was applied to monitor dopamine released from PC12 cells upon extracellular stimulation of K(+) ions. It was also confirmed that K(+)-induced dopamine release was inhibited by a calcium channel inhibitor (Nifidipine). The results demonstrated that the presented biosensor could be used as an excellent tool for monitoring the effect of exogenous agents on living cells and drug efficacy tests.

Exploring codon optimization and response surface methodology to express biologically active transmembrane RANKL in E. coli.

Receptor activator of nuclear factor (NF)-κB ligand (RANKL), a master cytokine that drives osteoclast differentiation, activation and survival, exists in both transmembrane and extracellular forms. To date, studies on physiological role of RANKL have been mainly carried out with extracellular RANKL probably due to difficulties in achieving high level expression of functional transmembrane RANKL (mRANKL). In the present study, we took advantage of codon optimization and response surface methodology to optimize the soluble expression of mRANKL in E. coli. We optimized the codon usage of mRANKL sequence to a preferred set of codons for E. coli changing its codon adaptation index from 0.64 to 0.76, tending to increase its expression level in E. coli. Further, we utilized central composite design to predict the optimum combination of variables (cell density before induction, lactose concentration, post-induction temperature and post-induction time) for the expression of mRANKL. Finally, we investigated the effects of various experimental parameters using response surface methodology. The best combination of response variables was 0.6 OD600, 7.5 mM lactose, 26°C post-induction temperature and 5 h post-induction time that produced 52.4 mg/L of fusion mRANKL. Prior to functional analysis of the protein, we purified mRANKL to homogeneity and confirmed the existence of trimeric form of mRANKL by native gel electrophoresis and gel filtration chromatography. Further, the biological activity of mRANKL to induce osteoclast formation on RAW264.7 cells was confirmed by tartrate resistant acid phosphatase assay and quantitative real-time polymerase chain reaction assays. Importantly, a new finding from this study was that the biological activity of mRANKL is higher than its extracellular counterpart. To the best of our knowledge, this is the first time to report heterologous expression of mRANKL in soluble form and to perform a comparative study of functional properties of both forms of RANKL.

Clinical implications of loudness dependence of auditory evoked potentials in patients with atypical depression.

OBJECTIVES: The loudness dependence of auditory evoked potentials (LDAEP) has been proposed as a useful biomarker of serotonin activity, and the LDAEP value is low in patients with melancholic depression. In this study, we evaluated LDAEP levels in patients with atypical depression. METHODS: We recruited 53 patients with atypical depression and 68 patients with non-atypical depression. Subjects were evaluated by the Atypical Depression Diagnostic Scale (ADDS), Hamilton Rating Scale for Depression (HAMD), Hamilton Rating Scale for Anxiety (HAMA), Beck Scale for Suicidal Ideation (BSI), Behavioral Inhibition System and Behavioral Activation System (BIS/BAS) scales, and Hypomanic Personality Scale (HPS). To determine LDAEP, the peak-to-peak N1/P2 was measured at five stimulus intensities and the LDAEP was calculated as the linear-regression slope. RESULTS: Patients with atypical depression had stronger LDAEP values and higher BAS and HPS scores than those with non-atypical depression. LDAEP showed a pattern of gradual decrease according to ADDS score hierarchy in patients with major depressive disorder. In the atypical depression group, LDAEP showed significant negative correlation with the BSI score and significant positive correlation with BAS score. In the non-atypical depression group, LDAEP did not show any significant correlations with the scores of psychological scales. CONCLUSIONS: Our results suggest that there is a relatively deficient serotonergic activity in patients with atypical depression and that LDAEP reflects mood reactivity. The transient drop of serotonergic activity induced by mood vulnerability might contribute to suicidal tendencies in patients with atypical depression.

Influence of citric acid molar ratio on the sintering behavior of nanocrystalline BaCe0.8Sm0.2O(3-delta).

The samarium-doped barium cerate (BaCe0.8Sm0.2O(3-delta), BCS) nano crystalline powders were synthesized via citric-nitrate method. The BCS nanopowders were prepared with various molar ratio of citric acid to metal nitrate. The pure perovskite structure was obtained from the BCS calcinated at 1200 degrees C and its crystalline size was increased with increase of the molar ratio citric acid to metal nitrate, while the aggregated particle size was significantly decreased as increasing the molar ratio. Also, excellent densification behavior was observed when high molar ratio of citric acid to metal nitrate was used. It was clarified that the molar ratio of citric acid determines the aggregated particle size and, in turn, finial microstructure after sintering.

Functional connectivity of resting state EEG and symptom severity in patients with post-traumatic stress disorder.

OBJECTIVES: Post-traumatic stress disorder (PTSD) is thought to be a brain network disorder. This study aimed to examine the resting-state functional connectivity (FC) in patients with PTSD. METHODS: Thirty-three PTSD patients and 30 age- and gender-matched healthy controls were recruited. Symptom severity of the PTSD patients was assessed, and 62-channel EEG was measured. EEGs were recorded during the resting state, with the eyes closed. Three nodal network measures to assess nodal centrality [nodal degree (Dnodal; connection strength), nodal efficiency (Enodal; communication efficiency), and betweenness centrality (BC; connection centrality)] were calculated in the delta, theta, alpha, beta, and gamma bands. RESULTS: Dnodal and Enodal of the beta and gamma bands were decreased in PTSD patients compared to healthy controls. These decreased nodal centrality values were observed primarily at the frontocentral electrodes. In addition, Dnodal of the beta and gamma bands was significantly correlated with depressive symptoms and increased arousal symptoms, respectively. Enodal of the beta and gamma bands was significantly correlated with re-experience, increased arousal, and the severity and frequency of general PTSD symptoms. CONCLUSION: Compared to controls, patients with PTSD were found to have decreased resting-state FC, and these FC measures were significantly correlated with PTSD symptom severity. Our results suggest that resting-state FC could be a useful biomarker for PTSD.