FEASIBILITY OF BREWING MAKGEOLLI (TURBID RICE WINE) USING PARTIALLY GELATINIZED WHEAT FLOUR AND TAPIOCA FLOUR

Makgeolli is made from cooked rice or wheat, then brewed with nuruk (Korean fermentation starter) for several days. But, nowadays, attempts have been made to use various raw materials and process innovations to make makgeolli for particular purposes.  This study aimed to evaluate the quality of makgeolly made from partially gelatinized wheat flour and tapioca flour. Five different combination of wheat flour and tapioca flour were used to manufacture makgeolli. The results showed that different combination of partially gelatinized wheat flour and tapioca flour significantly affected the chemical and sensorial characteristics of makgeolli. Increasing proportion of wheat flour produced higher level of total acid, amino acidity, reducing sugar and total solid of makgeolli. Inversely, alcohol content was higher when higher level of tapioca flour was used. In general, sensorial characteristics of makgeolli made from partially gelatinized wheat flour and tapioca flour didn’t acceptable by panelists. Thus, brewing makgeolli by using partially gelatinized wheat flour and tapioca flour isn’t acceptable in term of sensorial characteristics

Importance of remission and residual somatic symptoms in health-related quality of life among outpatients with major depressive disorder: a cross-sectional study

Background: Major depressive disorder (MDD) is strongly associated with an impaired quality of life (QoL), which is itself affected by various factors. Symptom-oriented ratings poorly reflect the impact of disease on the QoL and level of functioning of the mental health of subjects. The purpose of this study was to assess health-related QoL (HRQoL) using preference-based measures in outpatients with MDD with regard to their remission achievement and clinical factors affecting the HRQoL. Methods: This was a cross-sectional observational study. We recruited 811 patients with MDD from 14 psychiatric outpatient clinics in Korea. They were divided into three groups as follows: a new visit group (n = 287), a remitted group (n = 235), and a non-remitted group (n = 289). The 17-item Hamilton Depression Rating Scale was used to assign patients to the remitted or non-remitted group. The general HRQoL was assessed with the EuroQol 5D (EQ-5D), using both the EQ-5D index score and the EuroQol Visual Analog Scale (EQ-VAS). The disease-specific HRQoL was assessed with the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Results: The non-remitted group showed a significant impairment of HRQoL in view of the subscales of EQ-5D index scores, EQ-VAS, and Q-LES-Q-SF. The EQ-5D index score in the remitted group was 0.77 ± 0.10, while it was 0.57 ± 0.23 in the non-remitted group and 0.58 ± 0.24 in the new visit group (p < 0.0001). The EQ-VAS scores for the remitted and non-remitted groups were 72.5 ± 16.6 and 50.9 ± 20.3, respectively (p < 0.0001). Likewise, patients with remission had the Q-LES-Q-SF total score of 46.5 ± 8.8, whereas those with non-remission reported 36.7 ± 7.7 (p < 0.0001). The symptom severity measured by the Depression and Somatic Symptoms Scale was significantly correlated with the HRQoL. Furthermore, patients with severe somatic symptoms showed a significantly lower EQ-5D index score (0.54 ± 0.24) than those with mild/moderate somatic symptoms (0.75 ± 0.12; p = 0.002). Conclusion: Non-remitted MDD patients, especially those with more severe somatic symptoms, show a distinct impairment of HRQoL and more clinical symptoms, suggesting the importance of achieving remission in the treatment of MDD

Characterization for Binding Complex Formation with Site-Directly Immobilized Antibodies Enhancing Detection Capability of Cardiac Troponin I

The enhanced analytical performances of immunoassays that employed site-directly immobilized antibodies as the capture binders have been functionally characterized in terms of antigen-antibody complex formation on solid surfaces. Three antibody species specific to cardiac troponin I, immunoglobulin G (IgG), Fab, and F(ab′)2 were site-directly biotinylated within the hinge region and then immobilized via a streptavidin-biotin linkage. The new binders were more efficient capture antibodies in the immunoassays compared to randomly bound IgG, particularly, in the low antibody density range. The observed improvements could have resulted from controlled molecular orientation and also from flexibility, offering conditions suitable for binding complex formations

PG-RCNN: Semantic Surface Point Generation for 3D Object Detection

One of the main challenges in LiDAR-based 3D object detection is that the sensors often fail to capture the complete spatial information about the objects due to long distance and occlusion. Two-stage detectors with point cloud completion approaches tackle this problem by adding more points to the regions of interest (RoIs) with a pre-trained network. However, these methods generate dense point clouds of objects for all region proposals, assuming that objects always exist in the RoIs. This leads to the indiscriminate point generation for incorrect proposals as well. Motivated by this, we propose Point Generation R-CNN (PG-RCNN), a novel end-to-end detector that generates semantic surface points of foreground objects for accurate detection. Our method uses a jointly trained RoI point generation module to process the contextual information of RoIs and estimate the complete shape and displacement of foreground objects. For every generated point, PG-RCNN assigns a semantic feature that indicates the estimated foreground probability. Extensive experiments show that the point clouds generated by our method provide geometrically and semantically rich information for refining false positive and misaligned proposals. PG-RCNN achieves competitive performance on the KITTI benchmark, with significantly fewer parameters than state-of-the-art models. The code is available at https://github.com/quotation2520/PG-RCNN.Comment: Accepted by ICCV 202

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

ABSTRACT:Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique

Excess cost of non-remission among outpatients with major depressive disorder

Background: The purpose of this study was to assess the economic benefit of achieving remission among outpatients with major depressive disorder (MDD) who are currently employed in Korea. Methods: Cross-sectional observational study. A total of 337 outpatients with MDD with paid jobs were recruited from 14 psychiatric clinics in Korea and were then divided into three groups as follows: new visit group (n = 128), remitted group (n = 100) and non-remitted group (n = 109). The 17-item Hamilton Depression Rating Scale (HAM-D) was used to decide whether a patient should be assigned to the remitted or non-remitted group. Direct medical and non-medical costs were measured via interview with the subjects. The World Health Organization Health and Work Performance Questionnaire (HPQ) were applied in order to measure the lost productive time (LPT) and related productivity costs. Results: The three groups did not show a significant difference in direct medical cost. However, the difference between the remitted group and non-remitted group was statistically significant (25.49 ± 52.99 vs. 44.79 ± 126.55, χ2 = 12.99, p = 0.0015). The remitted group demonstrated a significant improvement in productivity (particularly presenteeism) when compared with the new visit group (Z = −3.29, p = 0.001). Although the non-remitted group received treatment at psychiatric clinics similar to the remitted group, it lost 33 more working hours per month, which is compatible to $332 per month. Conclusion: These results suggest the economic importance of achieving remission in treating depression

Differential microRNA expression signatures and cell type-specific association with Taxol resistance in ovarian cancer cells

Paclitaxel (Taxol) resistance remains a major obstacle for the successful treatment of ovarian cancer. MicroRNAs (miRNAs) have oncogenic and tumor suppressor activity and are associated with poor prognosis phenotypes. miRNA screenings for this drug resistance are needed to estimate the prognosis of the disease and find better drug targets. miRNAs that were differentially expressed in Taxol-resistant ovarian cancer cells, compared with Taxol-sensitive cells, were screened by Illumina Human MicroRNA Expression BeadChips. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to identify target genes of selected miRNAs. Kaplan–Meier survival analysis was applied to identify dysregulated miRNAs in ovarian cancer patients using data from The Cancer Genome Atlas. A total of 82 miRNAs were identified in ovarian carcinoma cells compared to normal ovarian cells. miR-141, miR-106a, miR-200c, miR-96, and miR-378 were overexpressed, and miR-411, miR-432, miR-494, miR-409-3p, and miR-655 were underexpressed in ovarian cancer cells. Seventeen miRNAs were overexpressed in Taxol-resistant cells, including miR-663, miR-622, and HS_188. Underexpressed miRNAs in Taxol-sensitive cells included miR-497, miR-187, miR-195, and miR-107. We further showed miR-663 and miR-622 as significant prognosis markers of the chemo-resistant patient group. In particular, the downregulation of the two miRNAs was associated with better survival, perhaps increasing the sensitivity of cancer cells to Taxol. In the chemo-sensitive patient group, only miR-647 could be a prognosis marker. These miRNAs inhibit several interacting genes of p53 networks, especially in TUOS-3 and TUOS-4, and showed cell line-specific inhibition effects. Taken together, the data indicate that the three miRNAs are closely associated with Taxol resistance and potentially better prognosis factors. Our results suggest that these miRNAs were successfully and reliably identified and would be used in the development of miRNA therapies in treating ovarian cancer