Pharmacokinetic interactions between fexuprazan, a potassium-competitive acid blocker, and nonsteroidal anti-inflammatory drugs in healthy males.

Fexuprazan, a novel potassium-competitive acid blocker, is expected to be used for the prevention of nonsteroidal anti-inflammatory drugs (NSAIDs) induced ulcer. This study aimed to evaluate pharmacokinetic (PK) interactions between fexuprazan and NSAIDs in healthy subjects. A randomized, open-label, multicenter, six-sequence, one-way crossover study was conducted in healthy male subjects. Subjects randomly received one of the study drugs (fexuprazan 40 mg BID, celecoxib 200 mg BID, naproxen 500 mg BID, or meloxicam 15 mg QD) for 5 or 7 days in the first period followed by the combination of fexuprazan and one of NSAIDs for the same days and the perpetrator additionally administered for 1-2 days in the second period. Serial blood samples for PK analysis were collected until 48- or 72-h post-dose at steady state. PK parameters including maximum plasma concentration at steady state (Cmax,ss) and area under plasma concentration-time curve over dosing interval at steady state (AUCτ,ss) were compared between monotherapy and combination therapy. The PKs of NSAIDs were not significantly altered by fexuprazan. For fexuprazan, differences in PK parameters (22% in Cmax, 19% in AUCτ,ss) were observed when co-administered with naproxen, but not clinically significant. The geometric mean ratio (90% confidence interval) of combination therapy to monotherapy for Cmax,ss and AUCτ,ss was 1.22 (1.02-1.46) and 1.19 (1.00-1.43), respectively. There were no significant changes in the systemic exposure of fexuprazan by celecoxib and meloxicam. Fexuprazan and NSAIDs did not show clinically meaningful PK interactions.

Mitigating Search Interference With Task-Aware Nested Search.

Neural Architecture Search (NAS) has emerged as a promising tool in the field of AutoML for designing more accurate and efficient architectures. The majority of NAS works employ a weight-sharing technique to reduce the search cost by sharing the weights of a supernet, which is a composite of all architectures produced from the search space. Nonetheless, this method has a significant drawback in that negative interference may arise when candidate architectures share the same weights. This issue becomes even more severe in multi-task searches, where a supernet is shared across tasks. To address this problem, we propose a task-aware nested search for multiple tasks that generates task-specific search spaces and architectures using a search-in-search approach consisting of space-search and architecture-search phases. In the space-search phase, we discover an optimal subspace in a task-aware manner by utilizing the proposed search space generator based on the global search space. On top of each subspace, we search for a promising architecture in the architecture-search phase. This method can mitigate search interference by adaptively sharing weights of the supernet by the generated subspace. The experimental results on various vision benchmarks (CityScapes, NYUv2, and Tiny-Taskonomy) show that the proposed method achieves outstanding performance over existing methods in terms of task accuracy, model parameters, and latency.

The pharmacokinetic, safety, and tolerability profiles of eslicarbazepine acetate are comparable between Korean and White subjects.

Eslicarbazepine acetate (ESL) is a prodrug antiseizure medication for the treatment of focal seizures. ESL shows a well-established pharmacokinetic (PK)-pharmacodynamic relationship and has similar extrinsic epilepsy-related factors across ethnicities. This study evaluated and compared ESL safety, tolerability, and PK characteristics between Korean and White subjects. A randomized, double-blind, placebo-controlled, single- and multiple-dose escalation study was conducted in healthy Korean and White adults. Participants randomly received a single dose and multiple oral doses of ESL (400-1600 mg) or placebo once daily for 11 days at a ratio of 8:2. Serial blood samples were collected to determine the plasma concentration of ESL and its metabolites (eslicarbazepine, [R-licarbazepine and oxcarbazepine). Safety and tolerability were assessed throughout the study. A total of 29 Korean and 20 White subjects completed the study. The PK profiles of the metabolites of ESL were similar between Korean and White subjects. The geometric mean ratio (90% confidence interval) of Korean to White subjects for the area under the concentration-time curve within a dosing interval of eslicarbazepine was 1.06 (0.97-1.17) and 0.96 (0.87-1.06) after multiple oral doses of 400 and 1600 mg ESL, respectively. Other PK parameters were also similar between the two ethnic groups. ESL was well-tolerated in healthy Korean and White subjects, and its PK characteristics were similar between the two ethnic groups. The results of this study support to use the same dosage regimen of ESL in both White and Korean patients with seizures.

Changes in the gut microbiome influence the hypoglycemic effect of metformin through the altered metabolism of branched-chain and nonessential amino acids.

AIMS: Although metformin has been reported to affect the gut microbiome, the mechanism has not been fully determined. We explained the potential underlying mechanisms of metformin through a multiomics approach. METHODS: An open-label and single-arm clinical trial involving 20 healthy Korean was conducted. Serum glucose and insulin concentrations were measured, and stool samples were collected to analyze the microbiome. Untargeted metabolomic profiling of plasma, urine, and stool samples was performed by GC-TOF-MS. Network analysis was applied to infer the mechanism of the hypoglycemic effect of metformin. RESULTS: The relative abundances of Escherichia, Romboutsia, Intestinibacter, and Clostridium were changed by metformin treatment. Additionally, the relative abundances of metabolites, including carbohydrates, amino acids, and fatty acids, were changed. These changes were correlated with energy metabolism, gluconeogenesis, and branched-chain amino acid metabolism, which are major metabolic pathways related to the hypoglycemic effect. CONCLUSIONS: We observed that specific changes in metabolites may affect hypoglycemic effects through both pathways related to AMPK activation and microbial changes. Energy metabolism was mainly related to hypoglycemic effects. In particular, branched-chain amino acid metabolism and gluconeogenesis were related to microbial metabolites. Our results will help uncover the potential underlying mechanisms of metformin through AMPK and the microbiome.

Assessment of Oral Vancomycin-Induced Alterations in Gut Bacterial Microbiota and Metabolome of Healthy Men.

Several classes of antibiotics have reduced the mortality caused by infectious diseases; however, orally administered antibiotics alter the composition of gut microbiota, leading to dysbiosis-related disease. Therefore, in this study, we used 16S rRNA gene sequencing- and metabolomics-based approaches to investigate the effects of oral vancomycin on gut bacterial microbiota and the metabolome in biospecimens collected from healthy men. Samples collected from 11 healthy men were analyzed using 16S rRNA gene sequencing and metabolomics. 16S rRNA gene sequencing was performed to analyze the gut bacterial microbiota, and GC-TOFMS-based untargeted metabolomics was performed to analyze fecal, urine, and plasma metabolomics. Spearman's rank correlation was utilized to explore the associations between gut bacterial microbiota and metabolome. Fecal 16S rRNA gene sequencing analysis showed decreased relative abundance of genera belonging to the phyla Bacteroidetes and Firmicutes, and increased relative abundance of genera of the phyla Proteobacteria and Fusobacteria. Fecal metabolomics analysis showed that levels of uracil, L-aspartic acid, lithocholic acid, and deoxycholic acid were significantly higher at baseline, whereas that of dihydrouracil was significantly higher after vancomycin administration. No significant metabolic markers were selected from urine and plasma metabolomics analysis. This study demonstrates that oral vancomycin administration induces alterations in gut bacterial microbiota and metabolome. Correlation analysis between our two datasets shows that alteration of the gut bacterial microbiota, induced by oral vancomycin, potentially affected the systemic activity of dihydropyrimidine dehydrogenase. This correlation should be further examined in future studies to define the effects of gut bacterial microbiota on drug-metabolizing enzymes, thereby contributing to the development of personalized therapy.

Current Bioequivalence Study Designs in South Korea: A Comprehensive Analysis of Bioequivalence Study Reports Between 2013 and 2019.

Demonstration of bioequivalence (BE) is mandatory while developing generic drugs. The scientific concept of BE applies equally to different regulatory agencies. However, the application of the concept may differ for each agency, which can affect the design of BE studies. To evaluate the study practices in terms of the BE concept in South Korea, we retrospectively analyzed BE study reports available from Ministry of Food and Drug Safety between 2013 and 2019. Statistical estimation of the pharmacokinetic parameters, including peak concentration and area under the concentration-time curve to the last measurable concentration, as well as study design, number of subjects in a study, study duration, fasting status, and formulation of specific drugs were obtained. The drugs were classified per World Health Organization Anatomical Therapeutic Chemical Classification and Biopharmaceutics Classification System. Post-hoc intrasubject coefficient of variation and corresponding sample sizes were calculated from the 90% confidence intervals of pharmacokinetic parameters. A total of 143 generic drugs in 588 BE studies were analyzed. The largest number of studies were performed in the area of Cardiovascular system (172 studies), followed by Nervous system (143 studies) and Alimentary tract and metabolism (92 studies). Overall, BE studies in South Korea were conducted in accordance with the global guideline despite the differences in details. BE studies were focused on the several therapeutic areas and conducted in a similar manner. The number of subjects was generally larger than that estimated with 90% power.

Effects of vancomycin-induced gut microbiome alteration on the pharmacodynamics of metformin in healthy male subjects.

Metformin is a major treatment for type 2 diabetes. This study was conducted to investigate the impact of gut microbiome dysbiosis on the pharmacokinetics and antihyperglycemic effects of metformin. Healthy adult males aged 19-45 years with no defecation abnormalities were recruited for this 4-period clinical study: baseline; post-metformin (i.e., multiple oral doses of 1000 mg metformin on days 1-4); post-vancomycin (i.e., multiple oral doses of 500 mg vancomycin on days 11-17 inducing gut microbiome changes); and post-metformin + vancomycin (i.e., multiple oral doses of 1000 mg metformin on days 16-19). In each period, serum glucose and insulin concentrations following an oral glucose tolerance test, fecal samples for gut microbiome composition, and safety data were obtained. Following metformin dosing, plasma and urine samples for pharmacokinetics were collected. Nine subjects completed the study. The pharmacokinetics of metformin remained unchanged, and the antihyperglycemic effect was significantly decreased after vancomycin administration (p value = 0.039), demonstrating the weak relationship between the pharmacokinetics and pharmacodynamics of metformin. Relative abundances of some genus were changed after vancomycin administration, and tended to correlate with the antihyperglycemic effects of metformin (p value = 0.062 for Erysipelatoclostridium; p value = 0.039 for Enterobacter; and p value = 0.086 for Faecalibacterium). Adverse events occurred in all subjects and were resolved without sequelae. In conclusion, a decrease in the antihyperglycemic effect of metformin was observed after concomitant administration with vancomycin, without changes in metformin pharmacokinetics. The antihyperglycemic effect was tended to correlate with the relative abundance of several genus, suggesting that the effect of metformin is partly attributable to the gut microbiome (ClinicalTrials.gov, NCT03809260).

Comparative pharmacokinetics between tenofovir disoproxil phosphate and tenofovir disoproxil fumarate in healthy subjects.

Tenofovir is the representative treatment for human immunodeficiency virus and hepatitis B virus infection. This study was conducted to assess the pharmacokinetics (PKs) and safety characteristics after a single administration of tenofovir disoproxil phosphate compared to tenofovir disoproxil fumarate in healthy male subjects. An open-label, randomized, single administration, two-treatment, two-sequence crossover study was conducted in 37 healthy volunteers. Serial blood samples were collected up to 72 hours. Non-compartmental analysis was used to calculate the PK parameters. The 90% confidence intervals (90% CIs) of the geometric mean ratio (GMR) were calculated for comparing tenofovir disoproxil phosphate to tenofovir disoproxil fumarate. Safety assessments were performed including clinical laboratory tests, adverse events, etc. during the study. The GMR and 90% CIs were 1.0514 (0.9527-1.1603) for Cmax and 1.0375 (0.9516-1.1311) for AUClast, respectively, and both fell within the conventional bioequivalence range of 0.8-1.25. Both tenofovir salt forms were tolerable. This study demonstrated that tenofovir disoproxil phosphate (292 mg) was bioequivalent to tenofovir disoproxil fumarate (300 mg).

Pharmacokinetic comparison between tablet of varenicline tartrate and orally disintegrating film of varenicline salicylate in healthy subjects.

OBJECTIVE: Varenicline is an efficacious aid for smoking cessation. In this study, the pharmacokinetics and safety were compared between film-coated tablets of varenicline tartrate (reference drug) and the newly developed orally disintegrating films of varenicline salicylate (test drug), both of them contained 1 mg of varenicline. MATERIALS AND METHODS: A randomized, open-label, single-dose, two-sequence, two-period crossover study was conducted in healthy male subjects. Serial blood samples were obtained for up to 72 hours in each period, with a washout period of 7 days or more. The pharmacokinetic parameters were calculated using the noncompartmental method. Safety profiles were assessed throughout the study. RESULTS: A total of 28 subjects completed the study. The plasma varenicline concentration-time profiles were similar for the two study drugs. The maximum plasma varenicline concentration (Cmax) was 5,768.95 ng/L (mean) and 5,780.55 ng/L for the test drug and reference drug, respectively. The areas under the concentration-time curve from time 0 to the last measurable time point (AUC0-t) were 94,086.30 h×ng/L and 89,958.55 h×ng/L for the test drug and reference drug, respectively. The geometric mean ratios (90% confidence intervals) of the test drug to the reference drug for Cmax and AUC0-t were 0.9955 (0.9488 - 1.0444) and 1.0449 (0.9848 - 1.1088), respectively, which fell within the bioequivalence range of 0.8 - 1.25. There was no difference in safety between the study drugs. CONCLUSION: The pharmacokinetics and safety profiles were similar between the two study drugs. The orally disintegrating film of varenicline salicylate can be an alternative to varenicline tartrate tablets.

Comparison of the Pharmacokinetics of a Fixed-Dose Combination of Rosuvastatin/Metformin Sustained-Release (10/1000 mg) and Separate Tablets in Healthy Male Subjects.

Fixed-dose combination (FDC) drugs with various dose combinations for the treatment of type 2 diabetes mellitus and dyslipidemia are currently in demand. We compared the pharmacokinetic (PK) profiles of the rosuvastatin/metformin sustained-release (10/1000 mg) FDC and separate tablets and evaluated the effect of food by randomized, open-label, 3-period, 6-sequence crossover studies conducted in healthy male subjects. Subjects were randomly assigned to one of the following treatments: separate tablets of 10 mg rosuvastatin and 1000 mg metformin sustained release in the fed state and the FDC in the fasted and fed states. PK samples were collected up to 72 hours postdose for rosuvastatin, N-desmethyl rosuvastatin, and metformin. The PK parameters were determined using a noncompartmental method, and the geometric mean ratio (GMR) and the 90% confidence interval (CI) of the treatments were calculated. A total of 35 subjects completed the study. The GMR and 90%CI of the peak concentration (Cmax ) and area under the plasma concentration-time curve from time zero to the last measurable concentration (AUClast ) of the FDC and the separate tablets were within the bioequivalence criteria (0.8-1.25) for both rosuvastatin and metformin. The effect of food was statistically significant for both rosuvastatin and metformin but not expected to be of clinical significance.

Pharmacokinetics and Tolerability of LC28-0126, a Novel Necrosis Inhibitor, After Multiple Ascending Doses: A Phase I Randomized, Double-blind, Placebo-controlled Study in Healthy Male Subjects.

PURPOSE: LC28-0126 is a reactive oxygen species scavenger being developed for the treatment of various conditions caused by oxidative stress, such as oral mucositis, graft-versus-host disease, and lethal reperfusion injury in acute myocardial infarction. The aim of this study was to assess the tolerability and pharmacokinetic properties of LC28-0126 with multiple IV administrations in healthy male subjects. METHODS: A dose-block-randomized, double-blind, placebo-controlled, multiple ascending-dose study was conducted. Subjects received 3-, 10-, 20-, or 30-mg doses of LC28-0126 or inactive control vehicle, infused over 30 min, once daily for 7 days. Blood and urine samples were collected for pharmacokinetics assessment. Tolerability was assessed by the documentation of adverse events, including abnormal findings on physical examination, vital sign measurements, blood oxygen saturation monitoring, 12-lead ECG, continuous ECG monitoring, and clinical laboratory testing. FINDINGS: A total of 32 subjects completed the study. After multiple dosing, the plasma concentration of LC28-0126 showed a steep decrease after infusion, followed by slow elimination. Systemic exposure of LC28-0126 was increased proportionally to doses ranging from 3 to 30 mg. The accumulation ratios were 2.58-2.79 on multiple dosing. The fractions excreted unchanged in urine were found to be <5%. All reported drug-related adverse events were injection-site reactions, and no serious adverse events were reported. IMPLICATIONS: Multiple administrations of LC28-0126 exhibited a dose-proportional pharmacokinetic profile and were well tolerated at a dose range of 3-30 mg. ClinicalTrials.gov identifier: NCT03196804.

Pharmacokinetics and pharmacodynamics of a fixed-dose combination of gemigliptin/metformin sustained release 25/500 mg compared to the loose combination in healthy male subjects.

A fixed-dose combination (FDC) of gemigliptin/metformin can improve the medication adherence in patients with type 2 diabetes mellitus (T2DM). In this study, the pharmacokinetic (PK) and pharmacodynamic (PD) profiles of gemigliptin and metformin were compared between FDC and the corresponding loose combination under fasted and fed states. A two-part, randomized, open label, single-dose, two-way crossover study was conducted in healthy male subjects. Under fasted (part 1) or fed (part 2) state, 2 FDC tablets of gemigliptin/metformin sustained release (SR) 25/500 mg or loose combination with one tablet of gemigliptin 50 mg and two tablets of metformin extended release (XR) 500 mg were orally administered in each period with a 7-day washout. Serial blood samples were collected up to 48 hours to determine the drug concentration and the dipeptidyl peptidase 4 (DPP-4) activity. The concentration-time profiles of gemigliptin and metformin were similar between FDC and loose combination in both the fasted and fed states. Geometric mean ratios and 90% confidence intervals of FDC to loose combination for area under the concentration-time curve and maximum plasma concentration of gemigliptin and metformin were within the bioequivalence range (0.8-1.25) in both states. DPP-4 activity-time profiles of FDC were comparable to that of the loose combination, showing similar area under the DPP-4 inhibition-time curve and maximum DPP-4 inhibition between FDC and loose combination, regardless of the fasted or fed state. In conclusion, the PK/PD characteristics of gemigliptin and metformin were similar in FDC tablets and loose combination both in fasted and fed states. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03355014.

A Fixed-Dose Combination Of Gemigliptin And Rosuvastatin Exhibits Similar Pharmacokinetics, Pharmacodynamics, And Safety Compared To That Of A Loose Combination In Healthy Subjects.

PURPOSE: Fixed-dose combination (FDC) of gemigliptin and rosuvastatin may improve medication compliance of patients with comorbid type 2 diabetes and dyslipidemia. Pharmacokinetics (PK), pharmacodynamics (PD), and safety of gemigliptin/rosuvastatin 50/20 mg FDC was compared with a loose combination of individual tablets in healthy subjects. PATIENTS AND METHODS: A randomized, open-label, single-dose, two-period, two-sequence, two-treatment crossover study was conducted. Subjects received FDC or a loose combination of gemigliptin (50 mg) and rosuvastatin (20 mg) during each period, with a 14-day washout. Serial blood samples were collected up to 72 hrs after dosing to measure plasma concentrations of gemigliptin, its active metabolite LC15-0636, and rosuvastatin for PK assessment, and DPP-4 activity for PD assessment. PK and PD parameters were calculated using a non-compartmental method. Safety profiles were evaluated throughout the study. RESULTS: Thirty-seven subjects completed the study. The concentration-time profiles of gemigliptin, LC15-0636, and rosuvastatin were similar between FDC and loose combination, respectively. For each of the three compounds, the geometric mean ratios (90% confidence interval) of FDC to loose combination for Cmax and AUClast fell within the bioequivalence range of 0.8-1.25. Inhibition of DPP-4 activity-time profiles after administration of FDC and loose combination was overlapping, and Imax and AUEClast were similar. Both FDC and the loose combination were well tolerated. CONCLUSION: PK, PD, and safety profiles of gemigliptin, its metabolite, and rosuvastatin were similar between FDC and loose combination. The FDC of gemigliptin (50 mg) and rosuvastatin (20 mg) can be used as an alternative to a loose combination, which is expected to improve patient compliance.

Physiologically Based Pharmacokinetic Modeling of Fimasartan, Amlodipine, and Hydrochlorothiazide for the Investigation of Drug-Drug Interaction Potentials.

PURPOSE: To build a physiologically based pharmacokinetic (PBPK) model for fimasartan, amlodipine, and hydrochlorothiazide, and to investigate the drug-drug interaction (DDI) potentials. METHODS: The PBPK model of each drug was developed using Simcyp software (Version 15.0), based on the information obtained from literature sources and in vitro studies. The predictive performance of the model was assessed by comparing the predicted PK profiles and parameters with the observed data collected from healthy subjects after multiple oral doses of fimasartan, amlodipine, and hydrochlorothiazide. The DDI potentials after co-administration of three drugs were simulated using the final model. RESULTS: The predicted-to-observed ratios of all the pharmacokinetic parameters met the acceptance criterion. The PBPK model predicted no significant DDI when fimasartan was co-administered with amlodipine or hydrochlorothiazide, which is consistent with the observed clinical data. In the simulation of DDI at steady-state after co-administration of three drugs, the model predicted that fimasartan exposure would be increased by ~24.5%, while no changes were expected for the exposures of amlodipine and hydrochlorothiazide. CONCLUSIONS: The developed PBPK model adequately predicted the pharmacokinetics of fimasartan, amlodipine, and hydrochlorothiazide, suggesting that the model can be used to further investigate the DDI potential of each drug.

Effect of food on the pharmacokinetics of YH4808, a potassium-competitive acid blocker, after single- and multiple-oral dosing in healthy subjects.

PURPOSE: YH4808 is a potassium-competitive acid blocker, developed for the treatment of acid-related disorders. Two clinical studies in healthy male subjects were conducted to evaluate the effect of food on the pharmacokinetics of YH4808. METHODS: The first study, a randomized, three-treatment, three-period, crossover study, compared pharmacokinetics of YH4808 (300 mg) after a single dose at fed state with a standard or a high-fat meal to those at fasted state. The second study, a randomized, two-treatment, two-period, crossover study, investigated pharmacokinetics at fasted or fed state with a standard meal after twice daily dose of YH4808 (100 mg) for 7 days. Bloods for pharmacokinetic evaluation were sampled up to 48 h post-dose and 24 h post-dose at steady state, respectively. The pharmacokinetic parameters were estimated by non-compartmental method. RESULTS: After single dosing, the geometric means of maximum plasma concentration increased by 1.2 and 2.1 times in the fed states with a standard meal and a high-fat meal, respectively, of that in fasted state. Corresponding values of area under the plasma concentration-time curve (AUC) from time 0 to the last measurable time point increased by 1.8 and 2.8 times, respectively. After multiple dosing, the geometric mean for 24-h AUC at steady state slightly increased in fed state by 1.1 times of that in fasted state. CONCLUSIONS: As fat content of the food increased, the systemic exposure of YH4808 after single dosing increased. However, systemic exposures at steady state after multiple dosing between fasted and fed states were similar. TRIAL REGISTRATION: ClinicalTrials.gov registry no.: NCT01520012.

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

Pattern-based Granger causality mapping in FMRI.

Since its development, the multivoxel pattern analysis (MVPA) method has been widely used to study high-level cognitive function in the brain. The results of the MVPA indicate that the spatial pattern of functional MRI data contains useful information. In addition to the spatial pattern analysis of the brain functions, effective connectivity can also be analyzed between the spatial pattern-based information. In this article, we propose a multivoxel pattern-based causality mapping method to explore influences between the spatial pattern-based information in the brain. The method applies the Granger causality to interested regions of the brain in terms of spatiotemporal pattern-based data, which are known to play an important role in dealing with high-level functions of the brain. The method can compose a causality map throughout the entire brain for any specified region of interest. Both simulations and experiments were performed to show the performance of the proposed method, and the existence and analyzability of the connectivity between pattern-based information in the brain were verified.