• 제목/요약/키워드: Biomedical Applications

검색결과 756건 처리시간 0.035초

Carboxymethyl cellulose/polyethylene glycol superabsorbent hydrogel cross-linked with citric acid

  • Lee, Deuk Yong;Chun, Cheolbyong;Son, Siwon;Kim, Yena
    • 한국결정성장학회지
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    • 제32권3호
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    • pp.107-114
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    • 2022

  • Carboxymethyl cellulose/poly(ethylene glycol) (CMC/PEG) hydrogels crosslinked with citric acid (CA) are synthesized to evaluate the effect of CMC molecular weight (Mw), PEG and CA concentration on the optical property, swelling rate (SR), degradation rate (DR), and cytotoxicity and cell proliferation of hydrogels. For crosslinked CMC/PEG hydrogels, the FT-IR peak intensity associated with hydroxyl groups decreases due to PEG intercalation (esterification crosslinking) between CMC chains in a similar manner as the concentration of CA crosslinker increases. Crosslinked CMC (Mw = 90,000)/PEG hydrogels with 10 % CA dissolve regardless of PEG content. However, the SR of the CMC (Mw = 250,000)/PEG hydrogels decrease from 4923 % to 168 % with increasing PEG and CA concentrations from 0 to 20 % and from 0 to 25 %, respectively. As the Mw of CMC increases, the DR of the hydrogel is greatly improved. CMC (Mw = 250,000)/PEG10 hydrogels with 10 % CA exhibit the optimum properties of high absorbing capacity (3,200 %) with moderate DR (54 %), stiffness (1.39 ± 0.19 GPa), and cell viability (94.8 ± 1.3 %). CA-crosslinked CMC/PEG hydrogels are highly suitable for wound dressing or personal care applications due to their non-toxicity, good cell proliferation, SR, and mechanical properties.

  • https://doi.org/10.6111/JKCGCT.2022.32.3.107 인용 PDF KSCI

Recent advances in spatially resolved transcriptomics: challenges and opportunities

  • Lee, Jongwon;Yoo, Minsu;Choi, Jungmin
    • BMB Reports
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    • 제55권3호
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    • pp.113-124
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    • 2022

  • Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

  • https://doi.org/10.5483/BMBRep.2022.55.3.014 인용 PDF KSCI

DEMO: Deep MR Parametric Mapping with Unsupervised Multi-Tasking Framework

  • Cheng, Jing;Liu, Yuanyuan;Zhu, Yanjie;Liang, Dong
    • Investigative Magnetic Resonance Imaging
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    • 제25권4호
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    • pp.300-312
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    • 2021

  • Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

  • https://doi.org/10.13104/imri.2021.25.4.300 인용 PDF KSCI

A study on the Differences in the Accommodation Applications Selection Attributes by Lifestyles

  • Kim, Kyu-dong;Jeon, Se-hoon;Kim, Jeong-lae
    • International Journal of Advanced Culture Technology
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    • 제8권4호
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    • pp.212-219
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    • 2020

  • We conducted this study to identify the accommodation applications users' lifestyle types and the composition factors for consumers' accommodation applications selection attributes and to identify the difference in the selection attributes perception of accommodation applications between groups classified by user's lifestyle types. According to the study, 6 factors were derived as the accommodation applications users' lifestyle types and were named social/leisure-oriented type, fashion-seeking type, culture-seeking type, self-examining type, self-centered type, family-oriented type. Also 6 factors were derived as the accommodation applications selection attributes and were named convenience, interactivity, economic efficiency, transaction reliability, product reliability and informativeness. Valid clusters were divided into four groups and were named culture/tourism group, self-examining group, passive and cautious group and Social and practicality-seeking group. Most of the selection attributes perception of accommodation applications between groups had statistically significant differences(p<.05), except for some items of transaction reliability. Based on the results of this study, we should strive to establish effective marketing strategies that reflect differences in the selection attributes perception of the accommodation application between groups classified by users' lifestyle types.

  • https://doi.org/10.17703/IJACT.2020.8.4.212 인용 PDF KSCI