• Title/Summary/Keyword: Computational

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Active Phytochemicals of Indian Spices Target Leading Proteins Involved in Breast Cancer: An in Silico Study

  • Ashok Kumar Krishnakumar;Jayanthi Malaiyandi;Pavatharani Muralidharan;Arvind Rehalia;Anami Ahuja;Vidhya Duraisamy;Usha Agrawal;Anjani Kumar Singh;Himanshu Narayan, Singh;Vishnu Swarup
    • Journal of the Korean Chemical Society
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    • v.68 no.3
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    • pp.151-159
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    • 2024
  • Indian spices are well known for their numerous health benefits, flavour, taste, and colour. Recent Advancements in chemical technology have led to better extraction and identification of bioactive molecules (phytochemicals) from spices. The therapeutic effects of spices against diabetes, cardiac problems, and various cancers has been well established. The present in silico study aims to investigate the binding affinity of 29 phytochemicals from 11 Indian spices with two prominent proteins, BCL3 and CXCL10 involved in invasiveness and bone metastasis of breast cancer. The three-dimensional structures of 29 phytochemicals were extracted from PubChem database. Protein Data Bank was used to retrieve the 3D structures of BCL3 and CXCL10 proteins. The drug-likeness and other properties of compounds were analysed by ADME and Lipinski rule of five (RO5). All computational simulations were carried out using Autodock 4.0 on Windows platform. The proteins were set to be rigid and compounds were kept free to rotate. In-silico study demonstrated a strong complex formation (positive binding constants and negative binding energy ΔG) between all phytochemicals and target proteins. However, piperine and sesamolin demonstrated high binding constants with BCL3 (50.681 × 103 mol-1, 137.76 × 103 mol-1) and CXCL10 (98.71 × 103 mol-1, 861.7 × 103 mol-1), respectively. The potential of these two phytochemicals as a drug candidate was highlighted by their binding energy of -6.5 kcal mol-1, -7.1 kcal mol-1 with BCL3 and -6.9 kcal mol-1, -8.2 kcal mol-1 with CXCL10, respectively coupled with their favourable drug likeliness and pharmacokinetics properties. These findings underscore the potential of piperine and sesamolin as drug candidates for inhibiting invasiveness and regulating breast cancer metastasis. However, further validation through in vitro and in vivo studies is necessary to confirm the in silico results and evaluate their clinical potential.

Blood-Brain Barrier Disruption in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Evaluation with Region-Based Quantification of Dynamic Contrast-Enhanced MR Imaging Parameters Using Automatic Whole-Brain Segmentation

  • Heera Yoen;Roh-Eul Yoo;Seung Hong Choi;Eunkyung Kim;Byung-Mo Oh;Dongjin Yang;Inpyeong Hwang;Koung Mi Kang;Tae Jin Yun;Ji-hoon Kim;Chul-Ho Sohn
    • Korean Journal of Radiology
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    • v.22 no.1
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    • pp.118-130
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    • 2021
  • Objective: This study aimed to investigate the blood-brain barrier (BBB) disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS) using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging and automatic whole brain segmentation. Materials and Methods: Forty-two consecutive mTBI patients with PCS who had undergone post-traumatic MR imaging, including DCE MR imaging, between October 2016 and April 2018, and 29 controls with DCE MR imaging were included in this retrospective study. After performing three-dimensional T1-based brain segmentation with FreeSurfer software (Laboratory for Computational Neuroimaging), the mean Ktrans and vp from DCE MR imaging (derived using the Patlak model and extended Tofts and Kermode model) were analyzed in the bilateral cerebral/cerebellar cortex, bilateral cerebral/cerebellar white matter (WM), and brainstem. Ktrans values of the mTBI patients and controls were calculated using both models to identify the model that better reflected the increased permeability owing to mTBI (tendency toward higher Ktrans values in mTBI patients than in controls). The Mann-Whitney U test and Spearman rank correlation test were performed to compare the mean Ktrans and vp between the two groups and correlate Ktrans and vp with neuropsychological tests for mTBI patients. Results: Increased permeability owing to mTBI was observed in the Patlak model but not in the extended Tofts and Kermode model. In the Patlak model, the mean Ktrans in the bilateral cerebral cortex was significantly higher in mTBI patients than in controls (p = 0.042). The mean vp values in the bilateral cerebellar WM and brainstem were significantly lower in mTBI patients than in controls (p = 0.009 and p = 0.011, respectively). The mean Ktrans of the bilateral cerebral cortex was significantly higher in patients with atypical performance in the auditory continuous performance test (commission errors) than in average or good performers (p = 0.041). Conclusion: BBB disruption, as reflected by the increased Ktrans and decreased vp values from the Patlak model, was observed throughout the bilateral cerebral cortex, bilateral cerebellar WM, and brainstem in mTBI patients with PCS.

Monte Carlo Simulation of Absorbed Energy by Gold Nano-Particles for Proton (양성자에 대한 금 나노입자의 밀도에 따른 흡수 에너지의 몬테카를로 전산모사)

  • Kwon Su Chon
    • Journal of the Korean Society of Radiology
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    • v.18 no.1
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    • pp.1-9
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    • 2024
  • Proton therapy is known for its superior treatment method due to Bragg peak. To enhance the therapeutic effects of protons, research has been conducted on distributing gold nanoparticles within tumors to increase the absorbed dose. While previous studies focused on handling gold nanoparticles at micrometer and nonometer scale, this study proposes a method to computationally estimate the effect of gold nanoparticles at the millimeter scale. The Geant4 toolkit was applied to computational modeling. Assuming a uniform distribution of water, similar to the human body, and gold nanoparticles, the concentration of gold nanoparticles was adjusted using density ratios. When the density ratio was 5%, the gain in absorbed energy due to gold nanoparticles was nearly twice that of the pure water phantom at the Bragg peak. As the density ratio increased, the gain in absorbed energy linearly increased. When gold nanoparticles were distributed in only one voxel at the Bragg peak, the energy of the protons affected only the neighboring voxels. However, in cases where gold nanoparticles were distributed over a wide area, the volume showing 95% of the maximum absorbed energy (9.46 keV) for the pure water phantom (9.95 keV) exhibited an improvement in absorbed energy over a region 16 times larger, and this region increased as the density ratio increased. Further research is needed to quantify the relationship between the density ratio of gold nanoparticles and the relative biological effect (RBE) in the millimeter scale.

Research on the Development of Distance Metrics for the Clustering of Vessel Trajectories in Korean Coastal Waters (국내 연안 해역 선박 항적 군집화를 위한 항적 간 거리 척도 개발 연구)

  • Seungju Lee;Wonhee Lee;Ji Hong Min;Deuk Jae Cho;Hyunwoo Park
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.367-375
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    • 2023
  • This study developed a new distance metric for vessel trajectories, applicable to marine traffic control services in the Korean coastal waters. The proposed metric is designed through the weighted summation of the traditional Hausdorff distance, which measures the similarity between spatiotemporal data and incorporates the differences in the average Speed Over Ground (SOG) and the variance in Course Over Ground (COG) between two trajectories. To validate the effectiveness of this new metric, a comparative analysis was conducted using the actual Automatic Identification System (AIS) trajectory data, in conjunction with an agglomerative clustering algorithm. Data visualizations were used to confirm that the results of trajectory clustering, with the new metric, reflect geographical distances and the distribution of vessel behavioral characteristics more accurately, than conventional metrics such as the Hausdorff distance and Dynamic Time Warping distance. Quantitatively, based on the Davies-Bouldin index, the clustering results were found to be superior or comparable and demonstrated exceptional efficiency in computational distance calculation.

Stem Rot of Pearl Millet Prevalence, Symptomatology, Disease Cycle, Disease Rating Scale and Pathogen Characterization in Pearl Millet-Klebsiella Pathosystem

  • Vinod Kumar Malik;Pooja Sangwan;Manjeet Singh;Pavitra Kumari;Niharika Shoeran;Navjeet Ahalawat;Mukesh Kumar;Harsh Deep;Kamla Malik;Preety Verma;Pankaj Yadav;Sheetal Kumari;Aakash;Sambandh Dhal
    • The Plant Pathology Journal
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    • v.40 no.1
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    • pp.48-58
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    • 2024
  • The oldest and most extensively cultivated form of millet, known as pearl millet (Pennisetum glaucum (L.) R. Br. Syn. Pennisetum americanum (L.) Leeke), is raised over 312.00 lakh hectares in Asian and African countries. India is regarded as the significant hotspot for pearl millet diversity. In the Indian state of Haryana, where pearl millet is grown, a new and catastrophic bacterial disease known as stem rot of pearl millet spurred by the bacterium Klebsiella aerogenes (formerly Enterobacter) was first observed during fall 2018. The disease appears in form of small to long streaks on leaves, lesions on stem, and slimy rot appearance of stem. The associated bacterium showed close resemblance to Klebsiella aerogenes that was confirmed by a molecular evaluation based on 16S rDNA and gyrA gene nucleotide sequences. The isolates were also identified to be Klebsiella aerogenes based on biochemical assays, where Klebsiella isolates differed in D-trehalose and succinate alkalisation tests. During fall 2021-2023, the disease has spread all the pearl millet-growing districts of the state, extending up to 70% disease incidence in the affected fields. The disease is causing considering grain as well as fodder losses. The proposed scale, consisting of six levels (0-5), is developed where scores 0, 1, 2, 3, 4, and 5 have been categorized as highly resistant, resistant, moderately resistant, moderately susceptible, susceptible, and highly susceptible disease reaction, respectively. The disease cycle, survival of pathogen, and possible losses have also been studied to understand other features of the disease.

Shipboard Verification Test of Onboard Carbon Dioxide Capture System (OCCS) Using Sodium Hydroxide(NaOH) Solution (가성소다(NaOH) 용액을 이용한 선상 이산화탄소 포집 장치의 선박 검증시험)

  • Gwang Hyun Lee;Hyung Ju Roh;Min woo Lee;Won Kyeong Son;Jae Yeoul Jeong;Tae-Hong Kim;Byung-Tak NAM;Jae-Ik Kim
    • Journal of the Society of Naval Architects of Korea
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    • v.61 no.1
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    • pp.51-60
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    • 2024
  • Hi Air Korea and Hanwha ocean are currently developing an Onboard Carbon dioxide Capture System (OCCS) to absorb CO2 emitted from ship's engine using a sodium hydroxide(NaOH) solution, and converting the resulting salt into a solid form through a chemical reaction with calcium oxide (CaO). The system process involves the following steps; 1)The reaction of CO2 gas absorption in water, 2)The reaction between carbonic acid (H2CO3) and NaOH solution to produce carbonate or bicarbonate, and 3)The reaction between carbonate or bicarbonate and CaO to form calcium carbonate (CaCO3). And ultimately, the solid material, CaCO3, is separated and discharged using a separator. The OCCS has been installed on an ship and the test results have confirmed significant reduction effects of CO2 in the ship's exhaust gas. A portion of the exhaust gas emitted from the engine was transferred to the OCCS using a blower. The flow rate of the transferred gas ranged from 800 to 1384 m3/hr, and the CO2 concentration in the exhaust gas was 5.1 vol% for VLSFO, 3.7 vol% for LNG and a 12 wt% NaOH solution was used. The results showed a CO2 capture efficiency of approximately 42.5 to 64.1 vol% and the CO2 capture rate approximately 48.4 to 52.2kg/hr. Additionally, to assess the impact of the discharged CaCO3on the marine ecosystem, we conducted "marine ecotoxicity test" and performed Computational Fluid Dynamics (CFD) analysis to evaluate the dispersion and dilution of the discharged effluent.

Design of Authentication Mechinism for Command Message based on Double Hash Chains (이중 해시체인 기반의 명령어 메시지 인증 메커니즘 설계)

  • Park Wang Seok;Park Chang Seop
    • Convergence Security Journal
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    • v.24 no.1
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    • pp.51-57
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    • 2024
  • Although industrial control systems (ICSs) recently keep evolving with the introduction of Industrial IoT converging information technology (IT) and operational technology (OT), it also leads to a variety of threats and vulnerabilities, which was not experienced in the past ICS with no connection to the external network. Since various control command messages are sent to field devices of the ICS for the purpose of monitoring and controlling the operational processes, it is required to guarantee the message integrity as well as control center authentication. In case of the conventional message integrity codes and signature schemes based on symmetric keys and public keys, respectively, they are not suitable considering the asymmetry between the control center and field devices. Especially, compromised node attacks can be mounted against the symmetric-key-based schemes. In this paper, we propose message authentication scheme based on double hash chains constructed from cryptographic hash function without introducing other primitives, and then propose extension scheme using Merkle tree for multiple uses of the double hash chains. It is shown that the proposed scheme is much more efficient in computational complexity than other conventional schemes.

Big Data Analytics in RNA-sequencing (RNA 시퀀싱 기법으로 생성된 빅데이터 분석)

  • Sung-Hun WOO;Byung Chul JUNG
    • Korean Journal of Clinical Laboratory Science
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    • v.55 no.4
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    • pp.235-243
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    • 2023
  • As next-generation sequencing has been developed and used widely, RNA-sequencing (RNA-seq) has rapidly emerged as the first choice of tools to validate global transcriptome profiling. With the significant advances in RNA-seq, various types of RNA-seq have evolved in conjunction with the progress in bioinformatic tools. On the other hand, it is difficult to interpret the complex data underlying the biological meaning without a general understanding of the types of RNA-seq and bioinformatic approaches. In this regard, this paper discusses the two main sections of RNA-seq. First, two major variants of RNA-seq are described and compared with the standard RNA-seq. This provides insights into which RNA-seq method is most appropriate for their research. Second, the most widely used RNA-seq data analyses are discussed: (1) exploratory data analysis and (2) pathway enrichment analysis. This paper introduces the most widely used exploratory data analysis for RNA-seq, such as principal component analysis, heatmap, and volcano plot, which can provide the overall trends in the dataset. The pathway enrichment analysis section introduces three generations of pathway enrichment analysis and how they generate enriched pathways with the RNA-seq dataset.

PASTELS project - overall progress of the project on experimental and numerical activities on passive safety systems

  • Michael Montout;Christophe Herer;Joonas Telkka
    • Nuclear Engineering and Technology
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    • v.56 no.3
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    • pp.803-811
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    • 2024
  • Nuclear accidents such as Fukushima Daiichi have highlighted the potential of passive safety systems to replace or complement active safety systems as part of the overall prevention and/or mitigation strategies. In addition, passive systems are key features of Small Modular Reactors (SMRs), for which they are becoming almost unavoidable and are part of the basic design of many reactors available in today's nuclear market. Nevertheless, their potential to significantly increase the safety of nuclear power plants still needs to be strengthened, in particular the ability of computer codes to determine their performance and reliability in industrial applications and support the safety demonstration. The PASTELS project (September 2020-February 2024), funded by the European Commission "Euratom H2020" programme, is devoted to the study of passive systems relying on natural circulation. The project focuses on two types, namely the SAfety COndenser (SACO) for the evacuation of the core residual power and the Containment Wall Condenser (CWC) for the reduction of heat and pressure in the containment vessel in case of accident. A specific design for each of these systems is being investigated in the project. Firstly, a straight vertical pool type of SACO has been implemented on the Framatome's PKL loop at Erlangen. It represents a tube bundle type heat exchanger that transfers heat from the secondary circuit to the water pool in which it is immersed by condensing the vapour generated in the steam generator. Secondly, the project relies on the CWC installed on the PASI test loop at LUT University in Finland. This facility reproduces the thermal-hydraulic behaviour of a Passive Containment Cooling System (PCCS) mainly composed of a CWC, a heat exchanger in the containment vessel connected to a water tank at atmospheric pressure outside the vessel which represents the ultimate heat sink. Several activities are carried out within the framework of the project. Different tests are conducted on these integral test facilities to produce new and relevant experimental data allowing to better characterize the physical behaviours and the performances of these systems for various thermo-hydraulic conditions. These test programmes are simulated by different codes acting at different scales, mainly system and CFD codes. New "system/CFD" coupling approaches are also considered to evaluate their potential to benefit both from the accuracy of CFD in regions where local 3D effects are dominant and system codes whose computational speed, robustness and general level of physical validation are particularly appreciated in industrial studies. In parallel, the project includes the study of single and two-phase natural circulation loops through a bibliographical study and the simulations of the PERSEO and HERO-2 experimental facilities. After a synthetic presentation of the project and its objectives, this article provides the reader with findings related to the physical analysis of the test results obtained on the PKL and PASI installations as well an overall evaluation of the capability of the different numerical tools to simulate passive systems.

Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility

  • Qing-Qing Zhou;Jiashuo Wang;Wen Tang;Zhang-Chun Hu;Zi-Yi Xia;Xue-Song Li;Rongguo Zhang;Xindao Yin;Bing Zhang;Hong Zhang
    • Korean Journal of Radiology
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    • v.21 no.7
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    • pp.869-879
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    • 2020
  • Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.