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Abstract Mitochondrial oxidative phosphorylation (OXPHOS) has become an attractive target in anti-cancer studies in recent years. In this study, we found that a small molecule phenylbutenoid dimer NMac1 (Nm23-H1 activator 1), (±)-trans-3-(3,4-dimethoxyphenyl)-4-[(E)-3,4-dimethoxystyryl]cyclohex-1-ene, a previously identified anti-metastatic agent, has novel anti-proliferative effect only under glucose starvation in metastatic breast cancer cells. NMac1 causes significant activation of AMPK by decreasing ATP synthesis, lowers mitochondrial membrane potential (MMP, ΔΨm), and inhibits oxygen consumption rate (OCR) under glucose starvation. These effects of NMac1 are provoked by a consequence of OXPHOS complex I inhibition. Through the structure–activity relationship (SAR) study of NMac1 derivatives, NMac24 was identified as the most effective compound in anti-proliferation. NMac1 and NMac24 effectively suppress cancer cell proliferation in 3D-spheroid in vivo-like models only under glucose starvation. These results suggest that NMac1 and NMac24 have the potential as anti-cancer agents having cytotoxic effects selectively in glucose restricted cells.

Since building Neural Machine Translation (NMT) systems requires a large parallel corpus, various data augmentation techniques have been adopted, especially for low-resource languages. In order to achieve the best performance through data augmentation, the NMT systems should be able to evaluate the quality of augmented data. Several studies have addressed data weighting techniques to assess data quality. The basic idea of data weighting adopted in previous studies is the loss value that a system calculates when learning from training data. The weight derived from the loss value of the data, through simple heuristic rules or neural models, can adjust the loss used in the next step of the learning process. In this study, we propose EvalNet, a data evaluation network, to assess parallel data of NMT. EvalNet exploits a loss value, a cross-attention map, and a semantic similarity between parallel data as its features. The cross-attention map is an encoded representation of cross-attention layers of Transformer, which is a base architecture of an NMT system. The semantic similarity is a cosine distance between two semantic embeddings of a source sentence and a target sentence. Owing to the parallelism of data, the combination of the cross-attention map and the semantic similarity proved to be effective features for data quality evaluation, besides the loss value. EvalNet is the first NMT data evaluator network that introduces the cross-attention map and the semantic similarity as its features. Through various experiments, we conclude that EvalNet is simple yet beneficial for robust training of an NMT system and outperforms the previous studies as a data evaluator.

In large-scale testing and e-learning environments, automated essay scoring (AES) can relieve the burden upon human raters by replacing human grading with machine grading. However, building AES systems based on deep learning requires a training dataset consisting of essays that are manually rated with scores. In this study, we introduce EssayGAN, an automatic essay generator based on generative adversarial networks (GANs). To generate essays rated with scores, EssayGAN has multiple generators for each score range and one discriminator. Each generator is dedicated to a specific score and can generate an essay rated with that score. Therefore, the generators can focus only on generating a realistic-looking essay that can fool the discriminator without considering the target score. Although ordinary-text GANs generate text on a word basis, EssayGAN generates essays on a sentence basis. Therefore, EssayGAN can compose not only a long essay by predicting a sentence instead of a word at each step, but can also compose a score-rated essay by adopting multiple generators dedicated to the target score. Since EssayGAN can generate score-rated essays, the generated essays can be used in the supervised learning process for AES systems. Experimental results show that data augmentation using augmented essays helps to improve the performance of AES systems. We conclude that EssayGAN can generate essays not only consisting of multiple sentences but also maintaining coherence between sentences in essays.

Sentence compression is a natural language-processing task that produces a short paraphrase of an input sentence by deleting words from the input sentence while ensuring grammatical correctness and preserving meaningful core information. This study introduces a graph convolutional network (GCN) into a sentence compression task to encode syntactic information, such as dependency trees. As we upgrade the GCN to activate a directed edge, the compression model with the GCN layers can distinguish between parent and child nodes in a dependency tree when aggregating adjacent nodes. Furthermore, by increasing the number of GCN layers, the model can gradually collect high-order information of a dependency tree when propagating node information through the layers. We implement a sentence compression model for Korean and English, respectively. This model consists of three components: pre-trained BERT model, GCN layers, and a scoring layer. The scoring layer can determine whether a word should remain in a compressed sentence by relying on the word vector containing contextual and syntactic information encoded by BERT and GCN layers. To train and evaluate the proposed model, we used the Google sentence compression dataset for English and a Korean sentence compression corpus containing about 140,000 sentence pairs for Korean. The experimental results demonstrate that the proposed model achieves state-of-the-art performance for English. To the best of our knowledge, this sentence compression model based on the deep learning model trained with a large-scale corpus is the first attempt for Korean.

Korean and Japanese have different writing scripts but share the same Subject-Object-Verb (SOV) word order. In this study, we pre-train a language-generation model using a Masked Sequence-to-Sequence pre-training (MASS) method on Korean and Japanese monolingual corpora. When building the pre-trained generation model, we allow the smallest number of shared vocabularies between the two languages. Then, we build an unsupervised Neural Machine Translation (NMT) system between Korean and Japanese based on the pre-trained generation model. Despite the different writing scripts and few shared vocabularies, the unsupervised NMT system performs well compared to other pairs of languages. Our interest is in the common characteristics of both languages that make the unsupervised NMT perform so well. In this study, we propose a new method to analyze cross-attentions between a source and target language to estimate the language differences from the perspective of machine translation. We calculate cross-attention measurements between Korean–Japanese and Korean–English pairs and compare their performances and characteristics. The Korean–Japanese pair has little difference in word order and a morphological system, and thus the unsupervised NMT between Korean and Japanese can be trained well even without parallel sentences and shared vocabularies.

Abstract Secretagogin (SCGN), a hexa EF-hand calcium binding protein, plays key roles in insulin secretion in pancreatic β-cells. It is not yet understood how the binding of Ca2+ to human SCGN (hSCGN) promotes secretion. Here we have addressed this question, using mass spectrometry combined with a disulfide searching algorithm DBond. We found that the binding of Ca2+ to hSCGN promotes the dimerization of hSCGN via the formation of a Cys193-Cys193 disulfide bond. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) and molecular dynamics studies revealed that Ca2+ binding to the EF-hands of hSCGN induces significant structural changes that affect the solvent exposure of N-terminal region, and hence the redox sensitivity of the Cys193 residue. These redox sensitivity changes were confirmed using biotinylated methyl-3-nitro-4-(piperidin-1-ylsulfonyl) benzoate (NPSB-B), a chemical probe that specifically labels reactive cysteine sulfhydryls. Furthermore, we found that wild type hSCGN overexpression promotes insulin secretion in pancreatic β cells, while C193S-hSCGN inhibits it. These findings suggest that insulin secretion in pancreatic cells is regulated by Ca2+ and ROS signaling through Ca2+-induced structural changes promoting dimerization of hSCGN.

The chaperone Hsp70 has a dual role, promoting both protein refolding and protein degradation. Seo and Park et al. show that Hsp70 acetylation enhances protein refolding after stress, and that subsequent deacetylation progressively promotes ubiquitin ligase binding and protein degradation.

β/γ-Crystallins, the main structural protein in human lenses, have highly stable structure for keeping the lens transparent. Their mutations have been linked to cataracts. In this study, we identified 10 new mutations of β/γ-crystallins in lens proteomic dataset of cataract patients using bioinformatics tools. Of these, two double mutants, S175G/H181Q of βΒ2-crystallin and P24S/S31G of γD-crystallin, were found mutations occurred in the largest loop linking the distant β-sheets in the Greek key motif. We selected these double mutants for identifying the properties of these mutations, employing biochemical assay, the identification of protein modifications with nanoUPLC-ESI-TOF tandem MS and examining their structural dynamics with hydrogen/deuterium exchange-mass spectrometry (HDX-MS). We found that both double mutations decrease protein stability and induce the aggregation of β/γ-crystallin, possibly causing cataracts. This finding suggests that both the double mutants can serve as biomarkers of cataracts.

Clostridium oremlandii MsrA (CoMsrA) is a natively selenocysteine-containing methionine-S-sulfoxide reductase and classified into a 1-Cys type MsrA. CoMsrA exists as a monomer in solution. Herein, we report evidence that CoMsrA can undergo homodimerization during catalysis. The monomeric CoMsrA dimerizes in the presence of its substrate methionine sulfoxide via an intermolecular disulfide bond between catalytic Cys16 residues. The dimeric CoMsrA is resolved by the reductant glutaredoxin, suggesting the relevance of dimerization in catalysis. The dimerization reaction occurs in a concentration- and time-dependent manner. In addition, the occurrence of homodimer formation in the native selenoprotein CoMsrA is confirmed. We also determine the crystal structure of the dimeric CoMsrA, having the dimer interface around the two catalytic Cys16 residues. A central cone-shaped hole is present in the surface model of dimeric structure, and the two Cys16 residues constitute the base of the hole. Collectively, our biochemical and structural analyses suggest a novel dimerization-mediated mechanism for CoMsrA catalysis that is additionally involved in CoMsrA regeneration by glutaredoxin.

Beta cell death caused by endoplasmic reticulum (ER) stress is a key factor aggravating type 2 diabetes. Exenatide, a glucagon-like peptide (GLP)-1 receptor agonist, prevents beta cell death induced by thapsigargin, a selective inhibitor of ER calcium storage. Here, we report on our proteomic studies designed to elucidate the underlying mechanisms. We conducted comparative proteomic analyses of cellular protein profiles during thapsigargin-induced cell death in the absence and presence of exenatide in INS-1 rat insulinoma cells. Thapsigargin altered cellular proteins involved in metabolic processes and protein folding, whose alterations were variably modified by exenatide treatment. We categorized the proteins with thapsigargin initiated alterations into three groups: those whose alterations were 1) reversed by exenatide, 2) exaggerated by exenatide, and 3) unchanged by exenatide. The most significant effect of thapsigargin on INS-1 cells relevant to their apoptosis was the appearance of newly modified spots of heat shock proteins, thimet oligopeptidase and 14-3-3β, ε, and θ, and the prevention of their appearance by exenatide, suggesting that these proteins play major roles. We also found that various modifications in 14-3-3 isoforms, which precede their appearance and promote INS-1 cell death. This study provides insights into the mechanisms in ER stress-caused INS-1 cell death and its prevention by exenatide.

Ubiquitin C-terminal hydrolase-L1 (UCH-L1) has been proposed as one of the Parkinson's disease (PD) related genes, but the possible molecular connection between UCH-L1 and PD is not well understood. In this study, we discovered an N-terminal 11 amino acid truncated variant UCH-L1 that we called NT-UCH-L1, in mouse brain tissue as well as in NCI-H157 lung cancer and SH-SY5Y neuroblastoma cell lines. In vivo experiments and hydrogen-deuterium exchange (HDX) with tandem mass spectrometry (MS) studies showed that NT-UCH-L1 is readily aggregated and degraded, and has more flexible structure than UCH-L1. Post-translational modifications including monoubiquitination and disulfide crosslinking regulate the stability and cellular localization of NT-UCH-L1, as confirmed by mutational and proteomic studies. Stable expression of NT-UCH-L1 decreases cellular ROS levels and protects cells from H2O2, rotenone and CCCP-induced cell death. NT-UCH-L1-expressing transgenic mice are less susceptible to degeneration of nigrostriatal dopaminergic neurons seen in the MPTP mouse model of PD, in comparison to control animals. These results suggest that NT-UCH-L1 may have the potential to prevent neural damage in diseases like PD.

BACKGROUND: Agonists of glucagon-like peptide-1 receptor (GLP-1R) and glucokinase activators (GKA) act as antidiabetic agents by their ability protect beta cells, and stimulate insulin secretion. Oxidative and endoplasmic reticulum (ER) stresses aggravate type 2 diabetes by causing beta cell loss. It was shown that GLP-1R agonists protect beta cells from oxidative and ER stresses. On the other hand, little is known regarding how GKAs protect beta cells. We hypothesized that GKAs protect beta cells by mechanisms distinct from those underlying GLP-1R agonist and tested our hypothesis by comparing the molecular effects of exenatide, a GLP-1R agonist, and piragliatin, a GKA, on INS-1 cells under oxidative and ER-induced stresses. METHODS: BETA CELLS WERE TREATED WITH STREPTOZOTOCIN (STZ) TO INDUCE OXIDATIVE STRESS AND WITH PALMITATE OR THAPSIGARGIN (TG) TO INDUCE ER STRESS RESPECTIVELY, AND THE EFFECTS OF EXENATIDE AND PIRAGLIATIN ON THESE CELLS WERE INVESTIGATED BY: a) characterizing the kinases involved employing specific kinase inhibitors, and b) by identifying the differentially regulated proteins in response to stresses with proteomic analysis. RESULTS: Exenatide protected INS-1 cells from both ER and STZ-induced death. In contrast, piragliatin rescued the cells only from STZ-induced stress. Akt activation by exenatide appeared to contribute to its protective effects of beta cells while enhanced glucose utilization was the contributing factor in the case of piragliatin. Also, exenatide, not piragliatin, blocked changes in proteins 14-3-3β, ε and θ, and preserved the 14-3-3θ levels under the ER stress. Isoform-specific modifications of 14-3-3, and the reduction of 14-3-3θ, commonly associated with beta cell death were assessed. CONCLUSIONS: Exenatide and piragliatin exert distinct effects on beta cell survival and thus on type 2 diabetes. This study which confirmed our hypothesis is also the first to observe specific modulation of 14-3-3 isoform in stress-induced beta cell death associated with progressive deterioration of type 2 diabetes.

Human Fas associated factor 1 (hFAF1) is a pro-apoptotic scaffolding protein containing ubiquitin-associating (UBA), ubiquitin like 1 and 2 (UBL1, UBL2), and ubiquitin regulatory X (UBX) domains. hFAF1 interacts with polyubiquitinated proteins via its N-terminal UBA domain and with valosin containing protein (VCP) via its C-terminal UBX domain. Overexpression of hFAF1 or its N-terminal UBA domain significantly increases cell death by increasing the degradation of polyubiquitinated proteins. In this study, we investigated whether hFAF1, whose expression level is reduced in cervical cancer, plays a role in tumor formation. We found that HeLa cells overexpressing full-length hFAF1 or the hFAF1 UBA domain alone, significantly suppressed the anchorage independent tumor growth in soft agar colony formation, increased cell death, and activated JNK and caspase 3. Employing UBA-specific tandem immunoprecipitation, we identified moieties specifically interacting with UBA domain of hFAF1, and found that polyubiquitinated Hsp70s are recruited to UBA domain. We also demonstrated that hFAF1 overexpression promotes Hsp70 degradation via the proteasome. We further found that mutating the UBA domain (I41N), as well as knocking down hFAF1 with specific RNAi, abolishs its ability to increase the proteasomal degradation of Hsp70. These findings suggest that hFAF1 inhibits tumor formation by increasing the degradation of Hsp70 mediated via its UBA domain.

The molecular basis of heat shock response (HSR), a cellular defense mechanism against various stresses, is not well understood. In this, the first comprehensive analysis of gene expression changes in response to heat shock and MG132 (a proteasome inhibitor), both of which are known to induce heat shock proteins (Hsps), we compared the responses of normal mouse fibrosarcoma cell line, RIF-1, and its thermotolerant variant cell line, TR-RIF-1 (TR), to the two stresses. The cellular responses we examined included Hsp expressions, cell viability, total protein synthesis patterns, and accumulation of poly-ubiquitinated proteins. We also compared the mRNA expression profiles and kinetics, in the two cell lines exposed to the two stresses, using microarray analysis. In contrast to RIF-1 cells, TR cells resist heat shock caused changes in cell viability and whole-cell protein synthesis. The patterns of total cellular protein synthesis and accumulation of poly-ubiquitinated proteins in the two cell lines were distinct, depending on the stress and the cell line. Microarray analysis revealed that the gene expression pattern of TR cells was faster and more transient than that of RIF-1 cells, in response to heat shock, while both RIF-1 and TR cells showed similar kinetics of mRNA expression in response to MG132. We also found that 2,208 genes were up-regulated more than 2 fold and could sort them into three groups: 1) genes regulated by both heat shock and MG132, (e.g. chaperones); 2) those regulated only by heat shock (e.g. DNA binding proteins including histones); and 3) those regulated only by MG132 (e.g. innate immunity and defense related molecules). This study shows that heat shock and MG132 share some aspects of HSR signaling pathway, at the same time, inducing distinct stress response signaling pathways, triggered by distinct abnormal proteins.

Cytoplasmic presence of Hsp60, which is principally a nuclear gene-encoded mitochondrial chaperonin, has frequently been stated, but its role in intracellular signaling is largely unknown. In this study, we demonstrate that the cytosolic Hsp60 promotes the TNF-alpha-mediated activation of the IKK/NF-kappaB survival pathway via direct interaction with IKKalpha/beta in the cytoplasm. Selective loss or blockade of cytosolic Hsp60 by specific antisense oligonucleotide or neutralizing antibody diminished the IKK/NF-kappaB activation and the expression of NF-kappaB target genes, such as Bfl-1/A1 and MnSOD, which thus augmented intracellular ROS production and ASK1-dependent cell death, in response to TNF-alpha. Conversely, the ectopic expression of cytosol-targeted Hsp60 enhanced IKK/NF-kappaB activation. Mechanistically, the cytosolic Hsp60 enhanced IKK activation via upregulating the activation-dependent serine phosphorylation in a chaperone-independent manner. Furthermore, transgenic mouse study showed that the cytosolic Hsp60 suppressed hepatic cell death induced by diethylnitrosamine in vivo. The cytosolic Hsp60 is likely to be a regulatory component of IKK complex and it implicates the first mitochondrial factor that regulates cell survival via NF-kappaB pathway.

Nucleoside diphosphate kinase (NDPK, Nm23), a housekeeping enzyme, is known to be a multifunctional protein, acting as a metastasis suppressor, transactivation activity on c-myc, and regulating endocytosis. The cellular mechanisms regulating Nm23 functions are poorly understood. In this study, we identified the modifications and interacting proteins of Nm23-H1 in response to oxidative stress. We found that Cys109 in Nm23-H1 is oxidized to various oxidation states including intra- and inter-disulfide crosslinks, glutathionylation, and sulfonic acid formation in response to H(2)O(2) treatment both in vivo and in vitro. The cross-linking sites and modifications of oxidized Nm23-H1 were identified by peptide sequencing using UPLC-ESI-q-TOF tandem MS. Glutathionylation and oxidation of Cys109 inhibited the NDPK enzymatic activity of Nm23-H1. We also found that thioredoxin reductase 1 (TrxR1) is an interacting protein of Nm23-H1, and it binds specifically to oxidized Nm23-H1. Oxidized Nm23 is a substrate of NADPH-TrxR1-thioredoxin shuttle system, and the disulfide crosslinking is reversibly reduced and the enzymatic activity is recovered by this system. Oxidation of Cys109 in Nm23-H1 inhibited its metastatic suppressor activity as well as the enzymatic activities. The mutant, Nm23-H1 C109A, retained both the enzymatic and metastasis suppressor activities under oxidative stress. This suggests that key enzymatic and metastasis suppressor functions of Nm23-H1 are regulated by oxido-reduction of its Cys109.