Biology subjects

Seok, J.

Publications and source records attributed to Seok, J..

4 recordsLinked to original sources

bioRxiv2026

Microfluidic Mechanical Reactivation of Aged Stem Cells

Stem cell aging significantly impairs therapeutic efficacy, requiring innovative strategies to restore potency. We present a microfluidic cell-compressing platform for reactivation (-CPR) designed to apply controlled hydrodynamic deformation to late-passage stem cells. This mechanical stimulation facilitates functional reactivation without external chemical cues. Within a defined window, -CPR effectively reduces oxidative stress, SA-{beta}-Gal activity, and {gamma}H2AX foci, while simultaneously restoring proliferation and canonical stemness markers (OCT4, SOX2, and KLF4). Mechanical stimulation via -CPR induces coordinated structural remodeling: nuclei become more compact, actin cortex organization is restored, -actinin redistributes to focal adhesions, and microtubule networks are restructured, suggesting a rebalanced intracellular tension. Transcriptomic and proteomic analyses reveal that this process reprograms extracellular matrix remodeling and DNA repair pathways while attenuating pro-fibrotic and senescence-associated secretory phenotype (SASP)-associated pathways. Crucially, this reactivation occurs without compromising fundamental MSC hallmarks, preserving intrinsic immunophenotypes and multilineage differentiation potential. Functionally, -CPR-processed stem cells demonstrate restored in vitro wound closure and enhanced tissue repair in vivo, with efficacy appearing dependent on mechanical dosage. This platform establishes a non-genetic, mechanobiological approach to restoring stem cell function, offering a scalable strategy for functional reactivation and potentially paving the way toward comprehensive cellular rejuvenation.

bioengineering↗

bioRxiv2023

Periodontitis promotes bacterial extracellular vesicle-induced neuroinflammation in the brain and trigeminal ganglion

Gram-negative bacteria derived extracellular vesicles (EVs), also known as outer membrane vesicles, have attracted significant attention due to their pathogenic roles in various inflammatory diseases. We recently demonstrated that EVs secreted by the periodontopathogen Aggregatibacter actinomycetemcomitans (Aa) can cross the blood-brain barrier (BBB) and that their extracellular RNA cargo can promote the secretion of proinflammatory cytokines, such as IL-6 and TNF-, in the brain. To gain more insight into the relationship between periodontal disease (PD) and neuroinflammatory diseases, we investigated the effect of Aa EVs in a mouse model of ligature-induced PD. When EVs were administered through intragingival injection or EV-soaked gel, proinflammatory cytokines were strongly induced in the brains of PD mice. The use of TLR (Toll-like receptor)-reporter cell lines and MyD88 knockout mice confirmed that the increased release of cytokines was triggered by Aa EVs via TLR4 and TLR8 signaling pathways and their downstream MyD88 pathway. Furthermore, the injection of EVs through the epidermis and gingiva resulted in the direct retrograde transfer of Aa EVs from axon terminals to the cell bodies of trigeminal ganglion (TG) neurons and the subsequent activation of TG neurons. We also found that the Aa EVs changed the action potential of TG neurons. These findings suggest that EVs derived from periodontopathogens such as Aa might be involved in pathogenic pathways for neuroinflammatory diseases, neuropathic pain, and other systemic inflammatory symptoms as a comorbidity of periodontitis. Author summaryExtracellular vesicles (EVs) secreted from bacterial cells play a key role in microbe-host cell communication. Bacterial EVs (bEVs) may be closely linked to the pathogenesis underlying neuroinflammatory diseases. In the current experiments, bEVs caused the brain to release proinflammatory cytokines by activating the host TLR signaling pathway. This induction of neuroinflammation was significantly more prominent in the periodontitis disease model, implying a substantial link between periodontal and neuroinflammatory diseases through bEVs. We also show that bEVs are translocated to the neuronal cell body via retrograde axonal transport, where they directly activate neuronal proinflammatory signals (Fig 8). Our findings reveal that bEVs are a pathogenic pathway for neurological conditions potentially linked to periodontitis, such as Alzheimers disease and trigeminal neuropathic pain. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/548287v1_fig8.gif" ALT="Figure 8"> View larger version (32K): org.highwire.dtl.DTLVardef@ff2928org.highwire.dtl.DTLVardef@1e72688org.highwire.dtl.DTLVardef@92e002org.highwire.dtl.DTLVardef@b0e125_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig 8.C_FLOATNO Graphic summary. Model of bacterial EV (bEVs) function in the brain and trigeminal neuron. bEVs have the ability to enter host brain cells through the bloodstream and to enter the trigeminal ganglion neuronal cell body through retrograde axonal transport, where they directly trigger proinflammatory neuronal signals. Through the TLR4/TLR8-MyD88 and NF-{kappa}B signaling pathways, bEVs and their RNA cargo can stimulate the production of TNF- and IL-6 in the host cells. The production of neuroinflammation is noticeably more pronounced in the periodontitis disease model, suggesting a strong association between periodontal and neuroinflammatory diseases via bEVs. C_FIG

pathology↗

bioRxiv2019

The semantic segmentation approach for normal and pathologic tympanic membrane using deep learning

ObjectivesThe purpose of this study was to create a deep learning model for the detection and segmentation of major structures of the tympanic membrane.\n\nMethodsTotal 920 tympanic endoscopic images had been stored were obtained, retrospectively. We constructed a detection and segmentation model using Mask R-CNN with ResNet-50 backbone targeting three clinically meaningful structures: (1) tympanic membrane (TM); (2) malleus with side of tympanic membrane; and (3) suspected perforation area. The images were randomly divided into three sets - taining set, validation set, and test set - at a ratio of 0.6:0.2:0.2, resulting in 548, 187, and 185 images, respectively. After assignment, 548 tympanic membrane images were augmented 50 times each, reaching 27,400 images.\n\nResultsAt the most optimized point of the model, it achieved a mean average precision of 92.9% on test set. When an intersection over Union (IoU) score of greater than 0.5 was used as the reference point, the tympanic membrane was 100% detectable, the accuracy of side of the tympanic membrane based on the malleus segmentation was 88.6% and detection accuracy of suspicious perforation was 91.4%.\n\nConclusionsAnatomical segmentation may allow the inclusion of an explanation provided by deep learning as part of the results. This method is applicable not only to tympanic endoscope, but also to sinus endoscope, laryngoscope, and stroboscope. Finally, it will be the starting point for the development of automated medical records descriptor of endoscope images.

bioinformatics↗

bioRxiv2018

Alteration of Vascular Endothelial Cadherin in Alzheimer’s Disease Patient and Mouse Model

Alzheimers disease (AD) is characterized by amyloid plaques and pathologic cerebrovascular remodeling. Cerebrovascular abnormalities may contribute to the pathology of AD, but the molecular mechanisms are not fully understood. In this study, we evaluated blood-brain barrier (BBB) disruption and the role of VE-cadherin in the progression of amyloid pathology. Here, we determined that levels of VE-cadherin are decreased in brain vessels of AD patients and mouse model of AD. In vitro experiments showed that the disappearance of VE-cadherin by beta-amyloid at the endothelial cell surface was due to cleavage of VE-cadherin. VE-cadherin cleavage was inhibited by a {gamma}-secretase and ADAM10 inhibitor. The disappearance of VE-cadherin in brain vessels was also seen in amyloid precursor protein transgenic mice. In the postmortem brain of individuals with AD, furthermore, levels of VE-cadherin were significantly reduced in vessels. Dementia patients showed a distinct blood biochemical profile characterized by high soluble VE-cadherin (sVEC). There was a strong association between plasma sVEC (adjusted odds ratio = 3.41, P < 0.001) and dementia. These results suggest that measurements of plasma VE-cadherin could have the potential for predicting the risk of progressive AD.

neuroscience↗