Junghwa Park

Dr. Junghwa Park


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 June 2024 in Pathogens
Verified
Journal Article
Open access
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SKSi Yeong Kim
Si Yeong Kim
MSMinkee Son
Minkee Son
JPJunghwa Park
Junghwa Park
HNHee Sam Na
Hee Sam Na
JCJin Chung
Jin Chung
(1) Background: Peptides are appealing as pharmacological materials because they are easily produced, safe, and tolerable. Despite increasing gum-care awareness, periodontitis is still prevalent and is influenced by factors like high sugar consumption, smoking, and aging. Porphyromonas gingivalis is considered a major etiologic agent of periodontitis and activates the NLR family pyrin domain containing 3 (NLRP3) but is absent in melanoma 2 (AIM2) inflammasomes, resulting in pro-inflammatory cytokine release. (2) Methods: We examined the anti-inflammatory effects of 18 peptides derived from human stromal cell-derived factor-1 (SDF-1) on THP-1 macrophages. Inflammation was induced by P. gingivalis, and the anti-inflammatory effects were analyzed using molecular biological techniques. In a mouse periodontitis model, alveolar bone resorption was assessed using micro-CT. (3) Results: Of the 18 SDF-1-derived peptides, S10 notably reduced IL-1β and TNF-α secretion. S10 also diminished the P. gingivalis-induced expression of NLRP3, AIM2, ASC (apoptosis-associated speck-like protein), caspase-1, and IL-1β. Furthermore, S10 attenuated the enhanced TLR (toll-like receptor) signaling pathway and decreased the phosphorylation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinases (MAPKs). In addition, S10 mitigated alveolar bone loss in our P. gingivalis-induced mouse model of periodontitis. (4) Conclusions: S10 suppressed TLR/NF-κB/NLRP3 inflammasome signaling and the AIM2 inflammasome in our P. gingivalis-induced murine periodontitis model, which suggests that it has potential use as a therapeutic treatment for periodontitis.

Verified
Journal Article
Open access
PDF file
SOSoo-min Ok
Soo-min Ok
HJHYEMIN JU
HYEMIN JU
SJSun-Hee Jeong
Sun-Hee Jeong
YAYong-Woo Ahn
Yong-Woo Ahn
JJJi-Young Joo
Ji-Young Joo
HNHee Sam Na
Hee Sam Na
Background/Objective: Oral lichen planus (OLP) is a chronic inflammatory disorder of the oral mucosa with unclear etiology. Increasing evidence implicates oral microbial dysbiosis in its pathogenesis, but little is known about supragingival plaque communities in relation to clinical subtypes. This cross-sectional case–control study aimed to characterize the supragingival plaque microbiota and microbial interaction networks in erosive OLP (E-OLP), non-erosive OLP (NE-OLP), and healthy controls (HCs), to elucidate microbial patterns associated with disease severity. Methods: Supragingival plaque samples were collected from 90 participants (30 per group) and analyzed using 16S rRNA gene sequencing. Alpha and beta diversity metrics, differential abundance, and co-occurrence network analyses were performed. Results: E-OLP exhibited pronounced dysbiosis, including the enrichment of pro-inflammatory taxa (e.g., Prevotella, Parvimonas) and depletion of health-associated commensals (e.g., Rothia, Capnocytophaga). Network analysis revealed the stepwise disintegration of microbial community structure from HC to NE-OLP to E-OLP, with reduced connectivity and increased dominance of pathogenic clusters in E-OLP. These microbial alterations aligned with clinical findings, as E-OLP patients showed significantly higher Reticulation/keratosis, Erythema, and Ulceration (REU) scores for erythema and ulceration compared to NE-OLP. Conclusions: Supragingival plaque dysbiosis and ecological disruption are strongly associated with OLP severity and subtype. This study highlights the utility of plaque-based microbial profiling in capturing lesion-proximal dysbiotic signals, which may complement mucosal and salivary analyses in future diagnostic frameworks. Multi-omics approaches incorporating fungal, viral, and metabolic profiling are warranted to fully elucidate host–microbe interactions in OLP.