A recently developed machine learning algorithm referred to as Extreme Learning Machine (ELM) was used to classify machine control commands out of time series of spike trains of ensembles of CA1 hippocampus neurons (n=34) of a rat, which was performing a target-to-goal task on a two-dimensional space through a brain-machine interface system. Performance of ELM was analyzed in terms of training time and classification accuracy. The results showed that some processes such as class code prefix, redundancy code suffix and smoothing effect of the classifiers' outputs could improve the accuracy of classification of robot control commands for a brain-machine interface system.
Aniline Compounds ; Animals ; Brain-Computer Interfaces ; Hippocampus ; Learning ; Neural Prostheses ; Neurons ; Rats ; Machine Learning

BACKGROUND/OBJECTIVES: The aim of this study was to examine the validity and reproducibility of a food frequency questionnaire (FFQ) developed in Korea for breast cancer survivors. SUBJECTS/METHODS: Ninety-nine breast cancer survivors who completed an FFQ twice and three 3-day dietary records (DRs) between 2016–2017 were included. Energy and 14 nutrient intakes were calculated from FFQs and DRs. To determine the validity of the FFQ, energyadjusted de-attenuated Pearson correlations between two FFQ assessments and the average of the three 3-day DRs were calculated, and to determine reproducibility, energy-adjusted Pearson correlations and degrees of agreement were calculated between the first and second FFQ assessments. RESULTS: Correlation coefficients of validity ranged from 0.29 (protein) to 0.47 (fat) (median value = 0.36) for the FFQ assessment and from 0.20 (riboflavin) to 0.53 (calcium) (median value = 0.37) for the second. Correlation coefficients of reproducibility ranged from 0.22 (sodium) to 0.62 (carbohydrate) (median value = 0.36). Regarding FFQ reproducibilities, percentage classifications of exact agreements for energy-adjusted nutrients ranged from 27.3% (sodium) and 45.5% (fat). A median 76.8% of participants were classified into the same or adjacent quartiles, while a median of 5.6% of participants were classified in extreme quartiles. Bland–Atman plots for the majority of data points of three macronutrients, calcium and vitamins A and C fell within limits of agreement. CONCLUSIONS These results indicated that the newly developed FFQ for Korean breast cancer survivors has acceptable validity and reproducibility as compared with three 3-day DRs collected over a one-year period.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

Purpose: In this trial, we investigated the efficacy and safety of adjuvant letrozole for hormone receptor (HR)-positive breast cancer. Here, we report the clinical outcome in postmenopausal women with HR-positive breast cancer treated with adjuvant letrozole according to estrogen receptor (ER) expression levels. Methods: In this multi-institutional, open-label, observational study, postmenopausal patients with HR-positive breast cancer received adjuvant letrozole (2.5 mg/daily) for 5 years unless they experienced disease progression or unacceptable toxicity or withdrew their consent. The patients were stratified into the following 3 groups according to ER expression levels using a modified Allred score (AS): low, intermediate, and high (AS 3–4, 5–6, and 7–8, respectively). ER expression was centrally reviewed. The primary objective was the 5-year disease-free survival (DFS) rate. Results: Between April 25, 2010, and February 5, 2014, 440 patients were enrolled. With a median follow-up of 62.0 months, the 5-year DFS rate in all patients was 94.2% (95% confidence interval [CI], 91.8–96.6). The 5-year DFS and recurrence-free survival (RFS) rates did not differ according to ER expression; the 5-year DFS rates were 94.3% and 94.1%in the low-to-intermediate and high expression groups, respectively (p = 0.6), and the corresponding 5-year RFS rates were 95.7% and 95.4%, respectively (p = 0.7). Furthermore, 25 patients discontinued letrozole because of drug toxicity. Conclusion Treatment with adjuvant letrozole showed very favorable treatment outcomes and good tolerability among Korean postmenopausal women with ER-positive breast cancer, independent of ER expression.

Purpose: In this trial, we investigated the efficacy and safety of adjuvant letrozole for hormone receptor (HR)-positive breast cancer. Here, we report the clinical outcome in postmenopausal women with HR-positive breast cancer treated with adjuvant letrozole according to estrogen receptor (ER) expression levels. Methods: In this multi-institutional, open-label, observational study, postmenopausal patients with HR-positive breast cancer received adjuvant letrozole (2.5 mg/daily) for 5 years unless they experienced disease progression or unacceptable toxicity or withdrew their consent. The patients were stratified into the following 3 groups according to ER expression levels using a modified Allred score (AS): low, intermediate, and high (AS 3–4, 5–6, and 7–8, respectively). ER expression was centrally reviewed. The primary objective was the 5-year disease-free survival (DFS) rate. Results: Between April 25, 2010, and February 5, 2014, 440 patients were enrolled. With a median follow-up of 62.0 months, the 5-year DFS rate in all patients was 94.2% (95% confidence interval [CI], 91.8–96.6). The 5-year DFS and recurrence-free survival (RFS) rates did not differ according to ER expression; the 5-year DFS rates were 94.3% and 94.1%in the low-to-intermediate and high expression groups, respectively (p = 0.6), and the corresponding 5-year RFS rates were 95.7% and 95.4%, respectively (p = 0.7). Furthermore, 25 patients discontinued letrozole because of drug toxicity. Conclusion Treatment with adjuvant letrozole showed very favorable treatment outcomes and good tolerability among Korean postmenopausal women with ER-positive breast cancer, independent of ER expression.