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Microbiome and Cancer Immunotherapy

Moonki Hong, Minkyu Jung
2021 Korean Journal of Medicine  
Immune checkpoint inhibitors (ICIs) have achieved promising clinical results in cancer treatment over the past decade. However, the efficacy of ICIs is less than 30% in most tumor types, and studies are underway to identify the predictive factors responsive to ICIs. More than 1,000 species of microorganisms live in the human body, and the second human genome project, The Human Microbiome Project, has been conducted to understand human diseases through interactions with microbes. As the
more » ... e project has progressed, many studies have reported on the association between microorganisms and human diseases, including preclinical and clinical studies on the relationship between ICIs and the microbiome. Therefore, in this manuscript, the relationship between the microbiome and cancer, especially the effectiveness of ICIs, is reviewed.
doi:10.3904/kjm.2021.96.4.312 fatcat:c5o2keghhvb5jnn46p6svfvety

Computing prime divisors in an interval

Minkyu Kim, Jung Hee Cheon
2014 Mathematics of Computation  
We address the problem of finding a nontrivial divisor of a composite integer when it has a prime divisor in an interval. We show that this problem can be solved in time of the square root of the interval length with a similar amount of storage, by presenting two algorithms; one is probabilistic and the other is its derandomized version. is, the square root of the interval length, even though it is a natural requirement to design such an algorithm. In this paper, we present two algorithms, one
more » ... s probabilistic and the other is its deterministic version, for achieving birthday complexity in finding a divisor in an interval. The proposed algorithms can find a nontrivial divisor of a composite integer N when it has a prime divisor in an interval, at around the time of the square root of the interval length with a similar amount of storage. As a result, using the proposed deterministic algorithm, we can check the existence of prime divisors in the interval, and if they exist, we can find all such prime divisors, by recursively applying the proposed deterministic algorithm at most log N times, in combination with a primality test such as [1] and a procedure to check that an integer belongs to the interval. Our algorithms basically work by solving the discrete logarithm problem over (Z/nZ) * , where n is an unknown divisor of the target composite integer N . To solve this problem efficiently, we adapt a multipoint evaluation method of univariate polynomials, as that of Pollard [15], who used it to give a deterministic time algorithm for finding divisors less than some integers. At the heart of the deterministic argument is the distribution of smooth numbers, that is, to take small integers to generate a large subgroup of (Z/N Z) * . We note that this approach was originally used for devising a deterministic primality test under some condition by Konyagin and Pomerance [9] . Compared to previous algorithms to find a divisor in an interval, the proposed algorithms are more efficient for some parameters. The complexity of Coppersmith's method depends on not only the interval length but also the relative size of the divisor for the target composite number N . In contrast, the proposed algorithms mainly depend on the interval length. This difference leads to a situation where our algorithms are better than Coppersmith's method. As log N becomes larger or log(β − α) gets closer to log α, our algorithms become more efficient than Coppersmith's method. For example, roughly speaking, when logN = 4 , log α = , log(β − α) = 2 /3, the proposed algorithms run in O(2 /3 ) time , whereas Coppersmith's method runs in O(2 5 /12 ) time, which is less efficient. Compared to Pollard's algorithm [15] , the proposed algorithms are better for the case that β − α is significantly smaller than β. We also note that by combining our techniques in Section 5 and Pollard's technique in [15, Section 2] one can obtain another deterministic algorithm suitable to the interval case, but it is not as efficient as our solution. The detailed explanation can be found in Section 5.5. In fact, one may consider applying Pollard's kangaroo method [17] to find a factor in an interval. Pollard's kangaroo method solves the discrete logarithm problem by finding a collision between two sequences which are generated by iteratively applying a function f to two distinct starting points. The main reason why this method works is that a collision between these two sequences is always preserved after applying f . However, this method as well as Pollard's rho method for the discrete logarithm [17] uses an iteration function f which does not satisfy that f (x mod p) = f (x) mod p. Such an iteration function does not preserve a collision modulo p after its applications, and so cannot be used for integer factorization. The remainder of this paper is organized as follows. In Section 2, we introduce notation and a theorem about smooth integers necessary for devising our deterministic algorithm. We start to present our algorithms by giving Lemma 3.1 in Licensed to AMS. License or copyright restrictions may apply to redistribution; see COMPUTING PRIME DIVISORS IN AN INTERVAL
doi:10.1090/s0025-5718-2014-02840-8 fatcat:sklcysszlnauhfunfq4kcajmim

Representation Learning of Resting State fMRI with Variational Autoencoder [article]

Jung-Hoon Kim, Yizhen Zhang, Kuan Han, Minkyu Choi, Zhongming Liu
2020 bioRxiv   pre-print
Resting state functional magnetic resonance imaging (rs-fMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rs-fMRI data. Here we establish a variational auto-encoder, as a generative model trainable with unsupervised learning, to disentangle the unknown sources of rs-fMRI activity. After being trained with large data from the Human Connectome Project, the model has learned to represent and generate patterns of cortical activity and
more » ... onnectivity using latent variables. Of the latent representation, its distribution reveals overlapping functional networks, and its geometry is unique to each individual. Our results support the functional opposition between the default mode network and the task-positive network, while such opposition is asymmetric and non-stationary. Correlations between latent variables, rather than cortical connectivity, can be used as a more reliable feature to accurately identify subjects from a large group, even if only a short period of data is available per subject.
doi:10.1101/2020.06.16.155937 fatcat:bnuq7hcj3bdwtphu4vcthg4l6i

Accelerating Pollard's Rho Algorithm on Finite Fields

Jung Hee Cheon, Jin Hong, Minkyu Kim
2010 Journal of Cryptology  
Most generic and memory-efficient algorithms for solving the discrete logarithm problem construct a certain random graph consisting of group element nodes and return the solution when a collision is found among the graph nodes. In this work, we develop a technique for traveling through the random graph without fully computing each node and also provide an extension to the distinguished point collision detection method that is suitable for this new situation. Concrete constructions of this
more » ... que for multiplicative subgroups of the finite fields are given. Our implementations confirm that the proposed technique provides practical speedup over existing algorithms. Keywords discrete logarithm problem · Pollard's rho · r-adding walk · distinguished point · finite field An earlier version of this work appeared in [4]. This is the accepted version of J. Cryptology 25(2) pp.195-242 (2012).
doi:10.1007/s00145-010-9093-7 fatcat:6lri46bqsveuxn3gw5mpmwreye

Testing intermediate representations for binary analysis

Soomin Kim, Markus Faerevaag, Minkyu Jung, Seungll Jung, DongYeop Oh, JongHyup Lee, Sang Kil Cha
2017 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)  
Binary lifting, which is to translate a binary executable to a high-level intermediate representation, is a primary step in binary analysis. Despite its importance, there are only few existing approaches to testing the correctness of binary lifters. Furthermore, the existing approaches suffer from low test coverage, because they largely depend on random test case generation. In this paper, we present the design and implementation of the first systematic approach to testing binary lifters. We
more » ... e evaluated the proposed system on 3 state-of-the-art binary lifters, and found 24 previously unknown semantic bugs. Our result demonstrates that writing a precise binary lifter is extremely difficult even for those heavily tested projects. FP Support SIMD Support Programming Language
doi:10.1109/ase.2017.8115648 dblp:conf/kbse/KimFJJOLC17 fatcat:k5o5neeubvbdpa3txipmydpvsm

Synthesis and Anticancer Activity of Novel Deoxoartemisinin–Glycolipid Hybrids

Dongguk Min, Minkyu Kim, Jérémy Ricci, Sora Jung, Kirim Kim, Won-Yoon Chung, Kwang-Kyun Park, Mankil Jung
2014 Chemical and pharmaceutical bulletin  
The practical synthesis and anticancer activity of novel deoxoartemisinin-glycolipid hybrids, which incorporate two drugs into a single molecule and can impact multiple targets simultaneously are presented. These hybrids exhibited potent in vitro anticancer activity against several human cancer cell lines. The deoxoartemisinin-glycolipid hybrids generally demonstrated better anticancer activity than either artemisinin or daumone alone and cisplatin.
doi:10.1248/cpb.c14-00036 pmid:24614158 fatcat:fhrq4duktzb4nbdidpj7nrkrgu

Speeding Up the Pollard Rho Method on Prime Fields [chapter]

Jung Hee Cheon, Jin Hong, Minkyu Kim
2008 Lecture Notes in Computer Science  
We propose a method to speed up the r-adding walk on multiplicative subgroups of the prime field. The r-adding walk is an iterating function used with the Pollard rho algorithm and is known to require less iterations than Pollard's original iterating function in reaching a collision. Our main idea is to follow through the r-adding walk with only partial information about the nodes reached. The trail traveled by the proposed method is a normal r-adding walk, but with significantly reduced
more » ... on time for each iteration. While a single iteration of most r-adding walks on Fp require a multiplication of two integers of log p size, the proposed method requires an operation of complexity only linear in log p, using a pre-computed table of size O((log p) r+1 · log log p). In practice, our rudimentary implementation of the proposed method increased the speed of Pollard rho with r-adding walks by a factor of more than 10 for 1024-bit random primes p.
doi:10.1007/978-3-540-89255-7_29 fatcat:45segiuulnclrhu575no7kuxti

Representation Learning of Resting State fMRI with Variational Autoencoder

Jung-Hoon Kim, Yizhen Zhang, Kuan Han, Zheyu Wen, Minkyu Choi, Zhongming Liu
2021 NeuroImage  
Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rsfMRI data. Here we establish a variational auto-encoder, as a generative model trainable with unsupervised learning, to disentangle the unknown sources of rsfMRI activity. After being trained with large data from the Human Connectome Project, the model has learned to represent and generate patterns of cortical activity and
more » ... ectivity using latent variables. The latent representation and its trajectory represent the spatiotemporal characteristics of rsfMRI activity. The latent variables reflect the principal gradients of the latent trajectory and drive activity changes in cortical networks. Representational geometry captured as covariance or correlation between latent variables, rather than cortical connectivity, can be used as a more reliable feature to accurately identify subjects from a large group, even if only a short period of data is available in each subject. Our results demonstrate that VAE is a valuable addition to existing tools, particularly suited for unsupervised representation learning of resting state fMRI activity.
doi:10.1016/j.neuroimage.2021.118423 pmid:34303794 fatcat:ctec5vqvazgsdda5jz42nhitva

Daumone fed late in life improves survival and reduces hepatic inflammation and fibrosis in mice

Jong Hee Park, Hae Young Chung, Minkyu Kim, Jung Hwa Lee, Mankil Jung, Hunjoo Ha
2014 Aging Cell  
The liver is one of the most susceptible organs to aging, and hepatic inflammation and fibrosis increase with age. Chronic inflammation has been proposed as the major molecular mechanism underlying aging and age-related diseases, whereas calorie restriction has been shown to be the most effective in extending mammalian lifespan and to have anti-aging effects through its anti-inflammatory action. Thus, it is necessary to develop effective calorie restriction mimetics. Daumone
more » ... roxy-6-methyltetrahydropyran-2-yloxy)heptanoic acid], a pheromone secreted by Caenorhabditis elegans, forces them to enter the dauer stage when facing inadequate conditions. Because Caenorhabditis elegans live longer during the dauer stage under energy deprivation, it was hypothesized that daumone may improve survival in mammals by mimicking calorie restriction. Daumone (2 mg kg À1 day À1 ) was administered orally for 5 months to 24-month-old male C57BL/6J mice. Daumone was found to reduce the risk of death by 48% compared with age-matched control mice, and the increased plasma insulin normally presented in old mice was significantly reduced by daumone. The increased hepatic hypertrophy, senescence-associated b-galactosidase activity, insulin resistance, lipid accumulation, inflammation, oxidative stress, and fibrosis in old mice were significantly attenuated by daumone. From a mechanistic view, daumone reduced the phosphorylation of the IjBa and upregulation of Rela and Nfkbia mRNA in the livers of old mice. The anti-inflammatory effect of daumone was confirmed in lipopolysaccharide-induced liver injury model. Oral administration of daumone improves survival in mice and delivers anti-aging effects to the aged liver by modulating chronic inflammation, indicating that daumone could be developed as an anti-aging compound.
doi:10.1111/acel.12224 pmid:24796965 pmcid:PMC4326938 fatcat:fq3tq5cl35g7nao2v5jh3ydybe

Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation [article]

Kyung-Min Kim, Donghyun Kwak, Hanock Kwak, Young-Jin Park, Sangkwon Sim, Jae-Han Cho, Minkyu Kim, Jihun Kwon, Nako Sung, Jung-Woo Ha
2019 arXiv   pre-print
Graph Neural Networks (GNNs) have been emerging as a promising method for relational representation including recommender systems. However, various challenging issues of social graphs hinder the practical usage of GNNs for social recommendation, such as their complex noisy connections and high heterogeneity. The oversmoothing of GNNs is an obstacle of GNN-based social recommendation as well. Here we propose a new graph embedding method Heterogeneous Graph Propagation (HGP) to tackle these
more » ... . HGP uses a group-user-item tripartite graph as input to reduce the number of edges and the complexity of paths in a social graph. To solve the oversmoothing issue, HGP embeds nodes under a personalized PageRank based propagation scheme, separately for group-user graph and user-item graph. Node embeddings from each graph are integrated using an attention mechanism. We evaluate our HGP on a large-scale real-world dataset consisting of 1,645,279 nodes and 4,711,208 edges. The experimental results show that HGP outperforms several baselines in terms of AUC and F1-score metrics.
arXiv:1908.02569v1 fatcat:br7cbjrybzat7o7sr2zuvryf5y

Diagnostic Classification and Biomarker Identification of Alzheimer's Disease with Random Forest Algorithm

Minseok Song, Hyeyoom Jung, Seungyong Lee, Donghyeon Kim, Minkyu Ahn
2021 Brain Sciences  
Random Forest (RF) is a bagging ensemble model and has many important advantages, such as robustness to noise, an effective structure for complex multimodal data and parallel computing, and also provides important features that help investigate biomarkers. Despite these benefits, RF is not used actively to predict Alzheimer's disease (AD) with brain MRIs. Recent studies have reported RF's effectiveness in predicting AD, but the test sample sizes were too small to draw any solid conclusions.
more » ... , it is timely to compare RF with other learning model methods, including deep learning, particularly with large amounts of data. In this study, we tested RF and various machine learning models with regional volumes from 2250 brain MRIs: 687 normal controls (NC), 1094 mild cognitive impairment (MCI), and 469 AD that ADNI (Alzheimer's Disease Neuroimaging Initiative database) provided. Three types of features sets (63, 29, and 22 features) were selected, and classification accuracies were computed with RF, Support vector machine (SVM), Multi-layer perceptron (MLP), and Convolutional neural network (CNN). As a result, RF, MLP, and CNN showed high performances of 90.2%, 89.6%, and 90.5% with 63 features. Interestingly, when 22 features were used, RF showed the smallest decrease in accuracy, −3.8%, and the standard deviation did not change significantly, while MLP and CNN yielded decreases in accuracy of −6.8% and −4.5% with changes in the standard deviation from 3.3% to 4.0% for MLP and 2.1% to 7.0% for CNN, indicating that RF predicts AD more reliably with fewer features. In addition, we investigated the importance of the features that RF provides, and identified the hippocampus, amygdala, and inferior lateral ventricle as the major contributors in classifying NC, MCI, and AD. On average, AD showed smaller hippocampus and amygdala volumes and a larger volume of inferior lateral ventricle than those of MCI and NC.
doi:10.3390/brainsci11040453 pmid:33918453 fatcat:d5h4vybao5aq5gz5f5kfdktc4a

Resonant-Based Capacitive Pressure Sensor Read-Out Oscillating At 1.67 Ghz In 0.18

Yong Wang, Wang Ling Goh, Jung Hyup Lee, Kevin T. C. Chai, Minkyu Je
2013 Zenodo  
Chai, Jung Hyup Lee, and Minkyu Je are with the Institute of Microelectronics, A*STAR (Agency for Science, Technology and Research), 11 Science Park Road, Singapore Science Park II, Singapore 117685 (phone  ...  Resonant-Based Capacitive Pressure SensorRead-Out Oscillating at 1.67 GHz in 0.18 µm CMOS Yong Wang, Wang Ling Goh, Jung Hyup Lee, Kevin T. C.  ... 
doi:10.5281/zenodo.1086867 fatcat:xd2p6e4hqncvthekym2lihscb4

Fine mapping of pepper trichome locus 1 controlling trichome formation in Capsicum annuum L. CM334

Hyun Jung Kim, Jung-Heon Han, Jin-Kyung Kwon, Minkyu Park, Byung-Dong Kim, Doil Choi
2009 Theoretical and Applied Genetics  
Trichomes are present on nearly all land plants and protect plants against insect herbivores, drought and UV radiation. The trichome-bearing phenotype is conferred by the dominant allele of the pepper trichome locus 1 (Ptl1) in Capsicum annuum, Mexican 'Criollo de Morelos-334' (CM334). A genetic analysis using simple sequence repeats from pepper cDNA identiWed the HpmsE031 marker as tightly linked to Ptl1 in 653 individuals of an F 2 population derived from a cross between CM334 and Chilsungcho
more » ... varieties. A bacterial artiWcial chromosome (BAC) library from CM334 covering 12£ of the genome was screened using the HpmsE031 SSR marker as a probe and three BAC clones were identiWed. The Ptl1 region was covered by one 80 kb BAC clone, TT1B7. Fluorescence in situ hybridization (FISH) conWrmed that TT1B7 localized to pepper chromosome 10. One co-dominant marker, Tco, and one dominant marker, Tsca, were successfully developed from the TT1B7 BAC sequence. Tco mapped 0.33 cM up from Ptl1 and Tsca mapped 0.75 cM down from Ptl1. Analysis of the BAC sequence predicts the presence of 14 open reading frames including 60S ribosomal protein L21-like protein (Solanum demissum), protein kinase 2 (Nicotiana tabacum), hypothetical proteins, and unnamed protein products. These results will provide not only useful information for map-based cloning of Ptl1 in Capsicum but also the starting points for analysis of R-gene cluster inked with Ptl1.
doi:10.1007/s00122-009-1237-5 pmid:20033390 fatcat:muu4fefw3bcgxffz5qtbb3qwy4

Body fluid MMP-2 as a putative biomarker in metastatic breast cancer

2012 Oncology Letters  
In the present study, we investigated the role of matrix metalloproteinase (MMP)-2 and -9 as novel biomarkers in the body fluid of patients with metastatic breast cancer. We measured the expression of MMPs in 37 samples of body fluid (10 peritoneal and 27 pleural fluids) from metastatic breast cancer patients between 2000 and 2009. Zymography and ELISA assays were used to determine the cut-off level and to quantify MMP expression from a positive control, HT-1080 conditioned media. MMP
more » ... in patient samples was measured with ELISA and compared with other clinical parameters. Ascitic carcinoembryonic antigen (CEA) and pleural CEA were measured in patient samples with a chemiluminescent enzyme immunoassay. Body fluid cytology had a positivity of 45% (9/20) for pleural fluid and 28.6% (2/7) for ascites. However, MMP-2 had a positivity of 85.2% (23/27) in 27 pleural fluid samples and 100% (10/10) in ascitic fluid with cut-off levels of 8.6 and 0.14 ng/ml for MMP-2 and -9, respectively. When body fluid CEA and MMP-2 were combined, the positivity improved to 96% in pleural fluid and 100% in ascites. MMP-2 expression in body fluid did not show any significant differences, but MMP-9 expression was lower in ascites than in pleural fluids (p<0.005). Our results suggest that MMP-2 expression in body fluid be used as an additive diagnostic marker for metastatic breast cancer patients.
doi:10.3892/ol.2012.549 pmid:22740979 pmcid:PMC3362445 fatcat:ysk3hgqllvfhvb6stlshy75odq

Subset-Restricted Random Walks for Pollard rho Method on ${\mathbf{F}_{p^m}}$ [chapter]

Minkyu Kim, Jung Hee Cheon, Jin Hong
2009 Lecture Notes in Computer Science  
In this paper, we propose a variant of the Pollard rho method. We use an iterating function whose image size is much smaller than its domain and hence reaches a collision faster than the original iterating function. We also explicitly show how this general method can be applied to multiplicative subgroups of finite fields with large extension degree. The construction for finite fields uses a distinctive feature of the normal basis representation, namely, that the p-th power of an element is
more » ... the cyclic shift of its normal basis representation, when the underlying field is of characteristic p. This makes our method appropriate for hardware implementations. On multiplicative subgroups of Fpm , our method shows time complexity advantage over the original Pollard rho method by a factor of approximately 3p−3 4p−3 √ m. Through the MOV reduction, our method can be applied to pairingbased cryptosystems over binary or ternary fields. Hence our algorithm suggests that the order of subgroups, on which the pairing-based cryptosystems rely, needs to be increased by a factor of approximately m. keywords: discrete logarithm problem, pairing, Pollard rho method, normal basis A part of this paper was made public through [1] .
doi:10.1007/978-3-642-00468-1_4 fatcat:ae33yhds3jfphijs3ogzq3zhpa
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