• Journal of Marine Bioscience and Biotechnology
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• v.15 no.2
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• pp.41-48
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• 2023

The objective of the present study was to improve the biomass productivity of newly isolated freshwater green microalga Parachlorella sp. This was accomplished by culture conditions optimization, including CO₂ concentration, superficial gas velocity, and light intensity, in 0.5 L bubble column photobioreactors. The supplied CO₂ concentration and gas velocity varied from 0.032% (air) to 10% and 0.02 m/s - 0.11 m/s, respectively, to evaluate their effects on growth kinetics. Next, to maximize the production rate of Parachlorella sp., a lumostatic operation based on a specific light uptake rate (q_e) was applied. From these results, the optimal CO₂ concentration in the supplied gas and the gas velocity were determined to be 5% and 0.064 m/s, respectively. For the lumostatic operation at 10.2 µmol/g/s, biomass productivity and photon yield showed significant increases of 83% and 66%, respectively, relative to cultures under constant light intensity. These results indicate that the biomass productivity of Parachlorella sp. can be improved by optimizing gas properties and light control as cell concentrations vary over time.

• Korean Journal of Microbiology
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• v.55 no.2
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• pp.157-159
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• 2019

Pseudomonas fluorescens NBC275 (Pf275) isolated from soil sample collected at riverside of Nakdonggang showed antagonistic activity against fungal pathogens of plants and insects. Here we present complete genome sequence of Pf275. The genome comprises of 6,610,362 bp with GC content of 60.9%, which includes 5,869 predicted protein-coding genes, 16 rRNAs, and 65 tRNAs. Genome analysis revealed gene clusters encoding antimicrobial secondary metabolites such as pyoverdine, 2, 4-diacetylphloroglucinol, and phenazine, which are known to play essential roles in biocontrol of diseases.

• Korean journal of applied entomology
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• v.62 no.1
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• pp.29-31
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• 2023

One Eucradinae beetle, Anhedobia capucina, belong to the family Ptinidae is reported in Korea for the first time. We provide the brief diagnosis, information and the photographic images of the species.

• Korean Journal of Plant Resources
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• v.35 no.5
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• pp.565-573
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• 2022

Gingival inflammation is one of the main causes that can be related to various periodontal diseases. Human gingival fibroblast (HGF) is the major constituent in periodontal connective tissue and secretes various inflammatory mediators, such as nitric oxide (NO) and prostaglandin E₂ (PGE₂), upon lipopolysaccharide stimulation. This study is aimed at investigating the anti-inflammatory and antioxidative activities of Lotus Root extract (LRE) in Porphyromonas gingivalis derived lipopolysaccharide (LPS-PG)-stimulated HGF-1 cells. The concentration of NO and PGE₂, as well as their responsible enzymes, inducible NO synthase (iNOS), and cyclooxygenase-2 (COX-2), was analyzed by Griess reaction, ELISA, and western blot analysis. LPS-PG sharply elevated the production and protein expression of inflammatory mediators, which were significantly attenuated by LRE treatment in a dose-dependent manner. LRE treatment also suppressed activation of Toll-like receptor 4 (TLR4)/myeloid differentiation primary response gene 88 (MyD88) and nuclear factor-κB (NF-κB) in LPS-PG-stimulated HGF-1 cells. In addition, one of phase II enzyme, NAD(P)H quinone dehydrogenase (NQO)-1, and its transcription factor, Nuclear factor erythroid 2-related factor 2 (Nrf2), were significantly induced by LRE treatment. Consequently, these results suggest that LRE ameliorates LPS-PG-induced inflammatory responses by attenuating TLR4/MyD88-mediated NF-κB, and activating NQO-1/Nrf2 antioxidant response element signaling pathways in HGF-1 cells.

• Korean Journal of Plant Resources
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• v.32 no.4
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• pp.255-263
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• 2019

Glycyrrhizae radix is one of the most frequently prescribed ingredients in Oriental medicine, and Glycyrrhizae radix extract has been shown to exert anti-cancer effects. However, the cellular and molecular mechanisms of programed cell death (apoptosis) by Glycyrrhizae radix are poorly defined. In the present study, it was examined the molecular mechanisms of apoptosis by water extracts of Glycyrrhizae radix (GRW) in human bladder T24 cancer cells. It was found that GRW could inhibit the cell growth of T24 cells in a concentration-dependent manner, which was associated with the induction of apoptotic cell death, as evidenced by the formation of apoptotic bodies, DNA fragmentation and increased populations of annexin-V positive cells. The induction of apoptotic cell death by GRW was connected with an up-regulation of pro-apoptotic Bax protein expression and down-regulation of anti-apoptotic proteins (Bcl-2 and Bcl-xL), and inhibition of apoptosis family proteins (XIAP, cIAP-1 and cIAP-2). In addition, apoptosis-inducing concentrations of GRW induced the activation of caspase-9, an initiator caspase of the mitochondrial-mediated intrinsic pathway, and caspase-3, accompanied by proteolytic degradation of PARP. GRW also induced apoptosis via a death receptor-mediated extrinsic pathway by caspase-8 activation, resulting in the down-regulation of total Bid and suggesting the existence of cross-talk between the extrinsic and intrinsic pathways. Taken together, the present results suggest that GRW may be a potential chemotherapeutic agent for the control of human bladder cancer cells.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.275-278
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• 2018

An aquatic wasp, Agriotypus silvestris Konishi & Aoyagi, 1994 is newly recognized in South Korea. A diagnosis and photographs of the diagnostic characters for the species and an identification key to the South Korean Agriotypus species are provided herein.

• Korean journal of applied entomology
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• v.62 no.1
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• pp.33-37
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• 2023

An archostematan beetles, Tenomerga mucida (Chevrolat, 1829), belong to the family Cupedidae is reported in Korea for the first time. We provide the diagnostic information based on morphology with microscophic images of the species compared with Tenomerga anguliscutis.

• Korean journal of applied entomology
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• v.62 no.2
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• pp.79-81
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• 2023

This paper presents the confirmed occurrence of the reed beetle genus Sominella Jacobson, 1908 in North Korea, based on a specimen of S. macrocnemia (Fischer von Waldheim, 1824). Photographs of the habitus, main diagnostic characters, and a distribution map in Korea are provided.

• Korean Journal of Plant Resources
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• v.34 no.1
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• pp.89-97
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• 2021

Two unrecorded alien plants, Pilea microphylla (L.) Liebm. (Urticaceae) and Elsholtzia griffithii Hook. f. (Lamiaceae), were found in Korea. P. microphylla was discovered in Seoul-si and Jeju-do. This species is distinguished from other related Korean taxa by leaf characteristics such as spatulate or obovate shape and 2-7 mm long with entire margin. E. griffithii was discovered in Incheon-si. This species is defined by spikes, narrowly lanceolate bract with 3 mm long and relatively shorter corolla length as ca 2.5 mm. Here, we provide Korean name, descriptions of the morphological characteristics, photographs and a key to allied taxa.

• Journal of Korean Society on Water Environment
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• v.37 no.4
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• pp.275-285
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• 2021

Algal bloom is an important issue in maintaining the safety of the drinking water supply system. Fast detection and classification of algae images are essential for the management of algal blooms. Conventional visual identification using a microscope is a labor-intensive and time-consuming method that often requires several hours to several days in order to obtain analysis results from field water samples. In recent decades, various deep learning algorithms have been developed and widely used in object detection studies. YOLO is a state-of-the-art deep learning algorithm. In this study the third version of the YOLO algorithm, namely, YOLOv3, was used to develop an algae image detection model. YOLOv3 is one of the most representative one-stage object detection algorithms with faster inference time, which is an important benefit of YOLO. A total of 1,114 algae images for 30 genera collected by microscope were used to develop the YOLOv3 algae image detection model. The algae images were divided into four groups with five, 10, 20, and 30 genera for training and testing the model. The mean average precision (mAP) was 81, 70, 52, and 41 for data sets with five, 10, 20, and 30 genera, respectively. The precision was higher than 0.8 for all four image groups. These results show the practical applicability of the deep learning algorithm, YOLOv3, for algae image detection.