• Biomolecules & Therapeutics
• /
• 제23권4호
• /
• pp.320-326
• /
• 2015

The clinical benefits of oncogenic BRAF inhibitor therapies are limited by the emergence of drug resistance. In this study, we investigated the role of a negative regulator of the MAPK pathway, Spry2, in acquired resistance using BRAF inhibitor-resistant derivatives of the BRAF-V600E melanoma (A375P/Mdr). Real-time RT-PCR analysis indicated that the expression of Spry2 was higher in A375P cells harboring the BRAF V600E mutation compared with wild-type BRAF-bearing cells (SK-MEL-2) that are resistant to BRAF inhibitors. This result suggests the ability of BRAF V600E to evade feedback suppression in cell lines with BRAF V600E mutations despite high Spry2 expression. Most interestingly, Spry2 exhibited strongly reduced expression in A375P/Mdr cells with acquired resistance to BRAF inhibitors. Furthermore, the overexpression of Spry2 partially restored sensitivity to the BRAF inhibitor PLX4720 in two BRAF inhibitor-resistant cells, indicating a positive role for Spry2 in the growth inhibition induced by BRAF inhibitors. On the other hand, long-term treatment with PLX4720 induced pERK reactivation following BRAF inhibition in A375P cells, indicating that negative feedback including Spry2 may be bypassed in BRAF mutant melanoma cells. In addition, the siRNA-mediated knockdown of Raf-1 attenuated the rebound activation of ERK stimulated by PLX4720 in A375P cells, strongly suggesting the positive role of Raf-1 kinase in ERK activation in response to BRAF inhibition. Taken together, these data suggest that RAF signaling may be released from negative feedback inhibition through interacting with Spry2, leading to ERK rebound and, consequently, the induction of acquired resistance to BRAF inhibitors.

• 생약학회지
• /
• 제36권3호통권142호
• /
• pp.201-204
• /
• 2005

The rhizome extract of Atractylodes japonica Koidzumi(Compositae) exhibited a particular inhibition on the proliferation of cultured human tumor cell lines, in vitro. Thus, the intensive phytichemical investigation of the MeOH extract of Atractylodes japonica have been conducted by the way of activity-guided purification. The repeated column chromatographic separation of the n-hexane soluble part of extract resulted in the isolation of four sesquiterpenes (1-4) and a polyacetylene component (5). Chemical structures of them were identified as atractylon (1), atractylenolide Ⅰ(2), atractylenolide Ⅲ(3), eudesma-4(15),7(11)-dien-8-one (4) and 1,3-diacetyl-atractylodiol (5) by spectroscopic means. Among the isolates, compound 2-4 were shown to give moderate inhibitory effect in a dose dependent manner on the proliferation of cultured human tumor cell lines such as A549 (non small cell lung), SK-OV-3 (ovary), SK-MEL-2 (melanoma), XF498 (central nerve system) and HCT 15(colon), respectively.

• 생약학회지
• /
• 제36권3호통권142호
• /
• pp.240-244
• /
• 2005

The methanol extract of the seed of Myristica fragrans (myristicaceae) demonstrated a potent inhibition on the proliferation of cultured human tumor cells such as A549 (non small cell lung), SK-OV-3 (ovary), SK-MEL-2(melanoma), XF498 (central nerve system) and HCT-15(colon). The MeOH extract was fractionated into three portions by serial solvent partition i,e., EtOAc soluble part, BuOH soluble part and remaining water layer. Among them, the EtOAc soluble part of the extract demonstrated a potent inhibition on the proliferation of cultured human tumor cells, Bioassay-guided fractionation of the EtOAc soluble part led to the isolation of six lignan constituents, i.e., safrole(1), machilin A (2), licarin B (3), macelignan (4), mesodihydroguaiaretic acid (5) and myristargenol A (6) as well as a large amount of myristic acid as active ingredients. Structures of the isolated active components (1-6) were established by chemical and spectroscopic means.

• 한국전자통신학회논문지
• /
• 제16권3호
• /
• pp.401-406
• /
• 2021

최근 들어, 음향 이벤트 검출을 위하여 CRNN(: Convolutional Recurrent Neural Network) 구조에 기반 한 평균-교사 모델이 대표적으로 사용되고 있다. 평균-교사 모델은 두 개의 병렬 형태의 CRNN을 가진 구조이며, 이들의 출력들의 일치성을 학습 기준으로 사용함으로서 약-전사 레이블(label)과 비-전사 레이블 음향 데이터에 대해서도 효과적인 학습이 가능하다. 본 연구에서는 최신의 평균-교사 모델에 로그-멜 스펙트럼에 대한 차분 특징을 추가적으로 사용함으로서 보다 나은 성능을 이루고자 하였다. DCASE 2018/2019 Challenge Task 4용 학습 및 테스트 데이터를 이용한 음향 이벤트 검출 실험에서 제안된 차분특징을 이용한 평균-교사모델은 기존의 방식에 비해서 최대 8.1%의 상대적 ER(: Error Rate)의 향상을 얻을 수 있었다.

• 융합신호처리학회논문지
• /
• 제19권4호
• /
• pp.147-152
• /
• 2018

수중에서의 일시적인 신호는 복잡하고, 변화가 심하며, 비선형적이므로 신호의 패턴을 정확히 모델링하기 어렵다. 본 논문에서는 수중 신호 중 하나인 고래 소리를 선택하여 음성분석 기법에 많이 사용하는 Cepstral 분석에 의한 MFCC 추출법을 이용하여 분석하였고, MFCC와 $L_2$-norm 최소화 기법을 이용하여 고래소리를 재생하였다 실험 분석에 사용된 고래의 종류는 혹등고래(Humpback whale), 참고래(Right whale), 대왕고래(Blue whale), 귀신고래(Gray whale), 밍크고래(Minke whale) 등 5종으로서 과거 한반도 동해안에 출몰한 적이 있는 고래들이다. 원본 고래소리에서 MATLAB프로그래밍을 이용하여 20차 MFCC계수들을 추출한 후 이를 가중 $L_2$-norm 최소화를 이용한 MFCC역변환을 통해 재생한다. 최종적으로 가중치가 3~4의 값에서 고래소리 재생이 가장 적합함을 알 수 있었다.

• Biomolecules & Therapeutics
• /
• 제27권3호
• /
• pp.302-310
• /
• 2019

Melanoma cells have been shown to respond to BRAF inhibitors; however, intrinsic and acquired resistance limits their clinical application. In this study, we performed RNA-Seq analysis with BRAF inhibitor-sensitive (A375P) and -resistant (A375P/Mdr with acquired resistance and SK-MEL-2 with intrinsic resistance) melanoma cell lines, to reveal the genes and pathways potentially involved in intrinsic and acquired resistance to BRAF inhibitors. A total of 546 differentially expressed genes (DEGs), including 239 up-regulated and 307 down-regulated genes, were identified in both intrinsic and acquired resistant cells. Gene ontology (GO) analysis revealed that the top 10 biological processes associated with these genes included angiogenesis, immune response, cell adhesion, antigen processing and presentation, extracellular matrix organization, osteoblast differentiation, collagen catabolic process, viral entry into host cell, cell migration, and positive regulation of protein kinase B signaling. In addition, using the PAN-THER GO classification system, we showed that the highest enriched GOs targeted by the 546 DEGs were responses to cellular processes (ontology: biological process), binding (ontology: molecular function), and cell subcellular localization (ontology: cellular component). Ingenuity pathway analysis (IPA) network analysis showed a network that was common to two BRAF inhibitorresistant cells. Taken together, the present study may provide a useful platform to further reveal biological processes associated with BRAF inhibitor resistance, and present areas for therapeutic tool development to overcome BRAF inhibitor resistance.

• 한국음향학회지
• /
• 제38권4호
• /
• pp.433-441
• /
• 2019

본 논문에서는 입 주변에 방사한 초음파 신호가 반사되어 돌아올 때 발생하는 초음파 도플러 신호를 LSTM(Long Short Term Memory) 순환 신경망 (Recurrent Neural Networks, RNN)을 이용해 음성 패러미터를 추정하는 방법을 소개하고 다층 퍼셉트론 (Multi-Layer Perceptrons, MLP) 신경망을 이용한 방법과 성능 비교를 하였다. 본 논문에서는 LSTM 순환 신경망을 이용해 초음파 도플러 신호로부터 음성 신호의 푸리에 변환 계수를 추정하였다. LSTM 순환 신경망을 학습하기 위한 입력 및 기준값으로 초음파 도플러 신호와 음성 신호로부터 각각 추출된 멜 주파수 대역별 에너지 로그값과 푸리에 변환 계수가 사용되었다. 테스트 데이터를 이용한 실험을 통해 LSTM 순환 신경망과 MLP의 성능을 평가, 비교하였고 척도로는 평균 제곱근 오차(Root Mean Squared Error, RMSE)가 사용되었다.각 실험의 RMSE는 각각 0.5810, 0.7380로 나타났다. 약 0.1570 차이로 LSTM 순환 신경망을 이용한 방법의 성능 우세한 것으로 확인되었다.

• Advances in nano research
• /
• 제13권1호
• /
• pp.87-96
• /
• 2022

Drug self-delivery systems can easily realize combination drug therapy and avoid carrier-induced toxicity and immunogenicity because they do not need non-therapeutic carrier materials. So, designing appropriate drug self-delivery systems for specific diseases can settle most of the problems existing in traditional drug delivery systems. Retinal pigment epithelium is very important for the homeostasis of retina. However, it is vulnerable to oxidative damage and difficult to repair. Worse still, the antioxidants can hardly reach the retina by non-invasive administration routes due to the ocular barriers. Herein, the targeted group (folic acid) and antioxidant (melatonin) have been grafted on the surface of ZnO quantum dots to fabricate a new kind of drug self-delivery systems as a protectant via eyedrops. In this study, the negative nanoparticles with size ranging in 4~6 nm were successfully synthesized. They could easily and precisely deliver drugs to retinal pigment epithelium via eyedrops. And they realized acid degradation to controlled release of melatonin and zinc in retinal pigment epithelium cells. Consequently, the structure of retinal pigment epithelium cells were stabilized according to the expression of ZO-1 and β-catenin. Moreover, the antioxidant capacity of retinal pigment epithelium were enhanced both in health mice and photic injury mice. Therefore, such new drug self-delivery systems have great potential both in prevention and treatment of oxidative damage induced retinal diseases.

• 사상체질의학회지
• /
• 제33권4호
• /
• pp.1-9
• /
• 2021

Objectives The purpose of this study was to check whether the classification of the individual's Body Mass Index (BMI) could be predicted by analyzing the voice data constructed at the Korean medicine data center (KDC) using machine learning. Methods In this study, we proposed a convolutional neural network (CNN)-based BMI classification model. The subjects of this study were Korean adults who had completed voice recording and BMI measurement in 2006-2015 among the data established at the Korean Medicine Data Center. Among them, 2,825 data were used for training to build the model, and 566 data were used to assess the performance of the model. As an input feature of CNN, Mel-frequency cepstral coefficient (MFCC) extracted from vowel utterances was used. A model was constructed to predict a total of four groups according to gender and BMI criteria: overweight male, normal male, overweight female, and normal female. Results & Conclusions Performance evaluation was conducted using F1-score and Accuracy. As a result of the prediction for four groups, The average accuracy was 0.6016, and the average F1-score was 0.5922. Although it showed good performance in gender discrimination, it is judged that performance improvement through follow-up studies is necessary for distinguishing BMI within gender. As research on deep learning is active, performance improvement is expected through future research.

• 한국지진공학회논문집
• /
• 제25권2호
• /
• pp.71-81
• /
• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.