Translating Hanja Historical Documents to Contemporary Korean and English

The Annals of Joseon Dynasty (AJD) contain the daily records of the Kings of Joseon, the 500-year kingdom preceding the modern nation of Korea. The Annals were originally written in an archaic Korean writing system, `Hanja', and were translated into Korean from 1968 to 1993. The resulting translation was however too literal and contained many archaic Korean words; thus, a new expert translation effort began in 2012. Since then, the records of only one king have been completed in a decade. In parallel, expert translators are working on English translation, also at a slow pace and produced only one king's records in English so far. Thus, we propose H2KE, a neural machine translation model, that translates historical documents in Hanja to more easily understandable Korean and to English. Built on top of multilingual neural machine translation, H2KE learns to translate a historical document written in Hanja, from both a full dataset of outdated Korean translation and a small dataset of more recently translated contemporary Korean and English. We compare our method against two baselines: a recent model that simultaneously learns to restore and translate Hanja historical document and a Transformer based model trained only on newly translated corpora. The experiments reveal that our method significantly outperforms the baselines in terms of BLEU scores for both contemporary Korean and English translations. We further conduct extensive human evaluation which shows that our translation is preferred over the original expert translations by both experts and non-expert Korean speakers.Comment: 2022 EMNLP Finding

Full Reference Video Quality Assessment for Machine Learning-Based Video Codecs

Machine learning-based video codecs have made significant progress in the past few years. A critical area in the development of ML-based video codecs is an accurate evaluation metric that does not require an expensive and slow subjective test. We show that existing evaluation metrics that were designed and trained on DSP-based video codecs are not highly correlated to subjective opinion when used with ML video codecs due to the video artifacts being quite different between ML and video codecs. We provide a new dataset of ML video codec videos that have been accurately labeled for quality. We also propose a new full reference video quality assessment (FRVQA) model that achieves a Pearson Correlation Coefficient (PCC) of 0.99 and a Spearman's Rank Correlation Coefficient (SRCC) of 0.99 at the model level. We make the dataset and FRVQA model open source to help accelerate research in ML video codecs, and so that others can further improve the FRVQA model

A lab-on-a-disc platform enables serial monitoring of individual CTCs associated with tumor progression during EGFR-targeted therapy for patients with NSCLC

Rationale: Unlike traditional biopsy, liquid biopsy, which is a largely non-invasive diagnostic and monitoring tool, can be performed more frequently to better track tumors and mutations over time and to validate the efficiency of a cancer treatment. Circulating tumor cells (CTCs) are considered promising liquid biopsy biomarkers; however, their use in clinical settings is limited by high costs and a low throughput of standard platforms for CTC enumeration and analysis. In this study, we used a label-free, high-throughput method for CTC isolation directly from whole blood of patients using a standalone, clinical setting-friendly platform. Methods: A CTC-based liquid biopsy approach was used to examine the efficacy of therapy and emergent drug resistance via longitudinal monitoring of CTC counts, DNA mutations, and single-cell-level gene expression in a prospective cohort of 40 patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Results: The change ratio of the CTC counts was associated with tumor response, detected by CT scan, while the baseline CTC counts did not show association with progression-free survival or overall survival. We achieved a 100% concordance rate for the detection of EGFR mutation, including emergence of T790M, between tumor tissue and CTCs. More importantly, our data revealed the importance of the analysis of the epithelial/mesenchymal signature of individual pretreatment CTCs to predict drug responsiveness in patients. Conclusion: The fluid-assisted separation technology disc platform enables serial monitoring of CTC counts, DNA mutations, as well as unbiased molecular characterization of individual CTCs associated with tumor progression during targeted therapy

A microfluidic chip for screening individual cancer cells via eavesdropping on autophagyinducing crosstalk in the stroma niche

Autophagy is a cellular homeostatic mechanism where proteins and organelles are digested and recycled to provide an alternative source of building blocks and energy to cells. The role of autophagy in cancer microenvironment is still poorly understood. Here, we present a microfluidic system allowing monitoring of the crosstalk between single cells. We used this system to study how tumor cells induced autophagy in the stromal niche. Firstly, we could confirm that transforming growth factor beta 1 (TGF beta 1) secreted from breast tumor cells is a paracrine mediator of tumor-stroma interaction leading to the activation of autophagy in the stroma component fibroblasts. Through proof of concept experiments using TGF beta 1 as a model factor, we could demonstrate real time monitoring of autophagy induction in fibroblasts by single tumor cells. Retrieval of individual tumor cells from the microfluidic system and their subsequent genomic analysis was possible, allowing us to determine the nature of the factor mediating tumor-stroma interactions. Therefore, our microfluidic platform might be used as a promising tool for quantitative investigation of tumor-stroma interactions, especially for and high-throughput screening of paracrine factors that are secreted from heterogeneous tumor cell populations

Dehydrated aqueous two-phase system micro-domains retain their shape upon rehydration to allow patterned reagent delivery to cells

Aqueous reagent solution micro-domains with sharp boundaries and defined shapes are created over cell monolayers within an immiscible bulk aqueous phase through rehydration of freestanding and portable dried reagent patches of the corresponding shape. This is in contrast to typical dissolution of reagent tablets or lyophilized biopolymer patches in aqueous solutions where no discernible reagent solution patterns are formed upon their full hydration. The key to enable the engineering of such stable reagent solution micro-domains is to formulate the reagent patches with polymers that form an aqueous two-phase system (ATPS) upon hydration by the bulk aqueous phase. This paper demonstrates this concept using dried reagent patches that incorporate dextran (DEX) and a bulk aqueous phase comprised of cell culture medium containing poly(ethylene) glycol (PEG). For reagents that prefer to partition in the DEX phase of the resulting ATPS, this procedure results in micro-patterned localization of reagent solution only to regions of the cell monolayer covered with the rehydrated DEX patch. The types of aqueous reagent solution micro-domain shapes that can be formed by the rehydration of such freestanding DEX-reagent patches are surprisingly broad and can be readily controlled by use of different templates for dehydrating the DEX solutions or even by cutting flat patches. The utility of the method is demonstrated through localized delivery of fluorescent molecules and enzymes for cell detachment. The patterned enzymatic detachment of cells enables convenient wound healing assays where cell monolayers can be wounded in different shapes dictated by the silhouette of the original DEX-reagent patchesclose1

Racial differences in long-term social, physical, and psychological health among adolescent and young adult cancer survivors

Background The current guidelines for survivorship in adolescents and young adults (AYA) cancer are based on studies conducted in the United States and European AYA survivors. However, previous studies have shown that the health-related quality of life in cancer survivors can vary depending on race, yet the long-term health differences among AYA survivors by race/ethnicity have not been fully explored. Therefore, our aim is to compare the psychosocial and physical health of AYA survivors and their matched controls across different racial and ethnic groups. Methods We conducted a cross-sectional study using US National Health and Nutrition Examination Survey (NHANES) and the Korea NHANES from 2007 to 2018. We included AYA cancer survivors who were diagnosed with any type of cancer aged between 15 and 39 years, and who were adult with aged over 18 years old at survey year. We then stratified the study population by race/ethnicity with Non-Hispanic White (NHW, n = 310), African American (AA, n = 42), Hispanic (n = 81) from NHANES, and Asian (n = 389) from the Korea NHANES. We also selected 5 times age-, sex-, race-, and survey year-matched general population among participants who had never been diagnosed with cancer (N = 4110). Variables were defined using questionnaire data, physical exams, and laboratory tests. Results Compared to NHW, Hispanics (aOR 1.15, 95% CI 1.00–1.32) had poor or fair general health, lower education (aOR 1.23, 95% CI 1.07–1.40), and lower household income (aOR 1.16, 95% CI 1.01–1.33). AA survivors were more likely to be non-coupled (aOR 1.35, 95% 1.15–1.60) and have hypertension (aOR 1.18, 95% CI 1.03–1.36). Asians were more former/current drinkers (aOR 1.21, 95% CI 1.05–1.40). NHW are more likely to experience psychological limitation. Compared to matched general, NHW and Asian survivors had poor general health and psychological health. Conclusions This study provides evidence for future studies concerning long-term health after AYA cancer survivorship that may vary according to race.This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2022R1A2C1013119