Effect of modification methods on the physical properties and immunomodulatory activity of particulate ß-glucan.

ß-Glucan is an immunoenhancing agent whose biological activities are linked to molecular structure. On that basis, the polysaccharide can be physiochemically modified to produce valuable functional materials. This study investigated the physical properties and immunostimulatory activity of modified ß-glucan. Alkali-treated ß-glucan had a distinct shape and smaller particle size than untreated ß-glucan. The reduced particle size was conducive to the stability of the suspension because the ß-glucan appeared to be completely dissolved by this treatment, forming an amorphous mass. Furthermore, alkali treatment improved the immunostimulating activity of ß-glucan, whereas exposure of macrophages to heat-treated ß-glucan decreased their immune activity. ß-Glucan with reduced particle size by wet-grinding also displayed immunomodulatory activities. These results suggested that the particle size of ß-glucan is a key factor in ß-glucan-induced immune responses of macrophages. Thus, the modification of the ß-glucan particle size provides new opportunities for developing immunoenhancing nutraceuticals or pharmacological therapies in the future.

Fasting GLP-1 Levels and Albuminuria Are Negatively Associated in Patients with Type 2 Diabetes Mellitus.

Glucagon-like peptide-1 (GLP-1) is an incretin hormone known for its pivotal role in enhancing insulin secretion and reducing glucagon release from the pancreas. Diabetic nephropathy, which is characterized by albuminuria, represents a significant microvascular complication of diabetes. Most of the previous studies mainly focused on the therapeutic renal protective effect in clinical trials after the administration of GLP-1 receptor agonists (GLP-1 RAs), rather than before administration. Hence, this study aimed to investigate the association between fasting plasma GLP-1 levels and albuminuria before GLP-1 RA administration. A cross-sectional study was designed to evaluate the association between fasting plasma GLP-1 levels and albuminuria in patients with type 2 diabetes mellitus (T2DM). A cohort of 68 participants with T2DM was analyzed using data collected at Wonkwang University Hospital in Iksan, Korea. Logistic regression analysis was employed to determine the odds ratio (OR) and 95% confidence interval (CI) of the incidence of albuminuria between two groups categorized by fasting GLP-1 levels, low (Group L) and high GLP-1 (Group H). The OR (95% CI) for the incidence of albuminuria comparing Group L with Group H of fasting plasma GLP-1 levels was 3.41 (1.16-10.02), p = 0.03 after adjustment for relevant variables including age, gender, fasting plasma glucose, HbA1c, C-peptide, creatinine, and medication use [angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs), sodium-glucose cotransporter-2 (SGLT-2) inhibitors, and dipeptidyl peptidase-4 (DPP-4) inhibitors]. When analyzed as a continuous variable, each 1 pmol/L reduction in fasting plasma GLP-1 levels was associated with an OR (95% CI) of 1.67 (1.17-1.87), p = 0.02, following full adjustment. These results highlight a negative association between fasting plasma GLP-1 levels and the incidence of albuminuria in Korean patients with T2DM, before GLP-1 RA administration. These findings suggest that endogenous GLP-1 may have a beneficial impact in mitigating albuminuria.

Current technologies for heavy metal removal from food and environmental resources.

Exposure to heavy metals in water and food poses a significant threat to human well-being, necessitating the efficient removal of these contaminants. The process of urban development exacerbates heavy metal pollution, thereby increasing risks to both human health and ecosystems. Heavy metals have the capacity to enter the food chain, undergo bioaccumulation and magnify, ultimately resulting in adverse effects on human health. Therefore, implementing effective pollution control measures and adopting sustainable practices are crucial for mitigating exposure and associated health risks. Various innovative approaches, including adsorption, ion exchange, and electrochemical technology, are currently being actively investigated to cope with the issue of heavy metal contamination. These innovative methods offer benefits such as efficient recycling, cost-effectiveness and environmental friendliness. In this review, we summarize recent advances for removing heavy metals from water, soil and food, providing valuable guidance for environmental engineers and researchers seeking to address contamination challenges.

Effects of Icariin and Its Metabolites on GPCR Regulation and MK-801-Induced Schizophrenia-Like Behaviors in Mice.

Icariin, a major bioactive compound found in the Epimedium genus, has been reported to exert protective effects against neurodegenerative disorders. In the current study, we aimed to investigate the regulatory effect of icariin and its active metabolites (icariside II and icaritin) against prime G-protein-coupled receptor targets, considering their association with neuronal disorders. Icariside II exhibited selective agonist activity towards the dopamine D3 receptor (D3R), with half-maximal effective concentrations of 13.29 µM. Additionally, they effectively inhibited the specific binding of radioligands to D3R. Molecular docking analysis revealed that icariside II potentially exerts its agonistic effect through hydrogen-bonding interaction with Asp110 of the D3R, accompanied by negative binding energy. Conversely, icaritin demonstrated selective antagonist effects on the muscarinic acetylcholine M2 receptor (M2R). Radioligand binding assay and molecular docking analysis identified icaritin as an orthosteric ligand for M2R. Furthermore, all three compounds, icariin and its two metabolites, successfully mitigated MK-801-induced schizophrenia-like symptoms, including deficits in prepulse inhibition and social interaction, in mice. In summary, these findings highlight the potential of icariin and its metabolites as promising lead structures for the discovery of new drugs targeting cognitive and neurodegenerative disorders.

NFAT1 and NFκB regulates expression of the common γ-chain cytokine receptor in activated T cells.

INTRODUCTION: Cytokines of the common γ chain (γc) family are critical for the development, differentiation, and survival of T lineage cells. Cytokines play key roles in immunodeficiencies, autoimmune diseases, allergies, and cancer. Although γc is considered an assistant receptor to transmit cytokine signals and is an indispensable receptor in the immune system, its regulatory mechanism is not yet well understood. OBJECTIVE: This study focused on the molecular mechanisms that γc expression in T cells is regulated under T cell receptor (TCR) stimulation. METHODS: The γc expression in TCR-stimulated T cells was determined by flow cytometry, western blot and quantitative RT-PCR. The regulatory mechanism of γc expression in activated T cells was examined by promoter-luciferase assay and chromatin immunoprecipitation assays. NFAT1 and NFκB deficient cells generated using CRISPR-Cas9 and specific inhibitors were used to examine their role in regulation of γc expression. Specific binding motif was confirmed by γc promotor mutant cells generated using CRISPR-Cas9. IL-7TgγcTg mice were used to examine regulatory role of γc in cytokine signaling. RESULTS: We found that activated T cells significantly upregulated γc expression, wherein NFAT1 and NFκB were key in transcriptional upregulation via T cell receptor stimulation. Also, we identified the functional binding site of the γc promoter and the synergistic effect of NFAT1 and NFκB in the regulation of γc expression. Increased γc expression inhibited IL-7 signaling and rescued lymphoproliferative disorder in an IL-7Tg animal model, providing novel insights into T cell homeostasis. CONCLUSION: Our results indicate functional cooperation between NFAT1 and NFκB in upregulating γc expression in activated T cells. As γc expression also regulates γc cytokine responsiveness, our study suggests that γc expression should be considered as one of the regulators in γc cytokine signaling and the development of T cell immunotherapies. Video Abstract.

Effects of Interfacial Electron Transport on Field Electron Emission from Carbon Nanotube Paste Emitters.

Field electron emission from carbon nanotubes (CNT) is preceded by the transport of electrons from the cathode metal to emission sites. Specifically, a supporting layer indispensable for adhesion of CNT paste emitters onto the cathode metal would impose a potential barrier, depending on its work function and interfacial electron transport behaviors. In this paper, we investigated the supporting layer of silicon carbide and nickel nanoparticles reacted onto a Kovar alloy (Fe-Ni-Co) cathode substrate, which has been adopted for reliable CNT paste emitters. The X-ray diffraction, X-ray photoelectron spectroscopy, ultraviolet photoelectron spectroscopy, and electrical conductivity measurements showed that the reaction of silicon carbide and nickel nanoparticles on the Kovar metal strongly depends upon the post-vacuum-annealing conditions and can be classified into two procedures of a diffusion-induced reaction (DIR) and a diffusion-limited reaction (DLR). The prolonged annealing at 750 °C for 5 h before the main annealing of the CNT paste emitters at 800 °C for 5 min led to the DIR that has enhanced the Ni silicide phase and a lower potential barrier for the interfacial electron transport, resulting in increased and weakly temperature-dependent field electron emission from the CNT paste emitters. On the other hand, the DLR with only the main anneal of the CNT paste emitters at 800 °C for 5 min gave rise to a higher potential barrier for the electron transport and so lower and strongly temperature-dependent field electron emission. From the results of the interfacial electron transport for the DIR and DLR mechanisms in the CNT paste emitters, we concluded that the ambient temperature dependency of field electron emission from CNT tips in the moderate range of up to 400 °C, still controversial, is mainly attributed to the supporting layer of the CNT emitter rather than its intrinsic electron emission.

Neuromodulatory feasibility of a current limiter-based tDCS device: a resting-state electroencephalography study.

Recently, we introduced a current limiter-based novel transcranial direct-current stimulation (tDCS) device that does not generate significant tDCS-induced electrical artifacts, thereby facilitating simultaneous electroencephalography (EEG) measurement during tDCS application. In this study, we investigated the neuromodulatory effect of the tDCS device using resting-state EEG data measured during tDCS application in terms of EEG power spectral densities (PSD) and brain network indices (clustering coefficient and path length). Resting-state EEG data were recorded from 10 healthy subjects during both eyes-open (EO) and eyes-closed (EC) states for each of five different conditions (baseline, sham, post-sham, tDCS, and post-tDCS). In the tDCS condition, tDCS was applied for 12 min with a current intensity of 1.5 mA, whereas tDCS was applied only for the first 30 s in the sham condition. EEG PSD and brain network indices were computed for the alpha frequency band most closely associated with resting-state EEG. Both alpha PSD and network indices were found to significantly increase during and after tDCS application compared to those of the baseline condition in the EO state, but not in the EC state owing to the ceiling effect. Our results demonstrate the neuromodulatory effect of the tDCS device that does not generate significant tDCS-induced electrical artifacts, thereby allowing simultaneous measurement of electrical brain activity. We expect our novel tDCS device to be practically useful in exploring the impact of tDCS on neuromodulation more precisely using ongoing EEG data simultaneously measured during tDCS application.

Phytochemical profiling of Symplocos tanakana Nakai and S. sawafutagi Nagam. leaf and identification of their antioxidant and anti-diabetic potential.

Symplocos sp. contains various phytochemicals and is used as a folk remedy for treatment of diseases such as enteritis, malaria, and leprosy. In this study, we discovered that 70% ethanol extracts of Symplocos sawafutagi Nagam. and S. tanakana Nakai leaves have antioxidant and anti-diabetic effects. The components in the extracts were profiled using high-performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry; quercetin-3-O-(6''-O-galloyl)-ß-d-galactopyranoside (6) and tellimagrandin II (7) were the main phenolic compounds. They acted as strong antioxidants with excellent radical scavenging activity and as inhibitors of non-enzymatic advanced glycation end-products (AGEs) formation. Mass fragmentation analysis demonstrated that compounds 6 and 7 could form mono- or di-methylglyoxal adducts via reaction with methylglyoxal, which is a reactive carbonyl intermediate and an important precursor of AGEs. In addition, compound 7 effectively inhibited the binding between AGE2 and receptor for AGEs as well as the activity of α-glucosidase. Enzyme kinetic study revealed that compound 7 acts as a competitive inhibitor of α-glucosidase, through interaction with the active site of the enzyme. Therefore, compounds 6 and 7, the major constituents of S. sawafutagi and S. tanakana leaves, are promising for developing drugs for preventing or treating diseases caused by aging and excessive sugar consumption.

Light-FER: A Lightweight Facial Emotion Recognition System on Edge Devices.

Facial emotion recognition (FER) systems are imperative in recent advanced artificial intelligence (AI) applications to realize better human-computer interactions. Most deep learning-based FER systems have issues with low accuracy and high resource requirements, especially when deployed on edge devices with limited computing resources and memory. To tackle these problems, a lightweight FER system, called Light-FER, is proposed in this paper, which is obtained from the Xception model through model compression. First, pruning is performed during the network training to remove the less important connections within the architecture of Xception. Second, the model is quantized to half-precision format, which could significantly reduce its memory consumption. Third, different deep learning compilers performing several advanced optimization techniques are benchmarked to further accelerate the inference speed of the FER system. Lastly, to experimentally demonstrate the objectives of the proposed system on edge devices, Light-FER is deployed on NVIDIA Jetson Nano.

Phytoestrogen Coumestrol Selectively Inhibits Monoamine Oxidase-A and Amyloid ß Self-Aggregation.

Pueraria lobata leaves contain a variety of phytoestrogens, including flavonoids, isoflavonoids, and coumestan derivatives. In this study, we aimed to identify the active ingredients of P. lobata leaves and to elucidate their function in monoamine oxidase (MAO) activation and Aß self-aggregation using in vitro and in silico approaches. To the best of our knowledge, this is the first study to elucidate coumestrol as a selective and competitive MAO-A inhibitor. We identified that coumestrol, a coumestan-derivative, exhibited a selective inhibitory effect against MAO-A (IC50 = 1.99 ± 0.68 µM), a key target protein for depression. In a kinetics analysis with 0.5 µg MAO-A, 40-160 µM substrate, and 25 °C reaction conditions, coumestrol acts as a competitive MAO-A inhibitor with an inhibition constant of 1.32 µM. During an in silico molecular docking analysis, coumestrol formed hydrogen bonds with FAD and pi-pi bonds with hydrophobic residues at the active site of the enzyme. Moreover, based on thioflavin-T-based fluorometric assays, we elucidated that coumestrol effectively prevented self-aggregation of amyloid beta (Aß), which induces an inflammatory response in the central nervous system (CNS) and is a major cause of Alzheimer's disease (AD). Therefore, coumestrol could be used as a CNS drug to prevent diseases such as depression and AD by the inhibition of MAO-A and Aß self-aggregation.

Induction of apoptosis through inactivation of ROS-dependent PI3K/Akt signaling pathway by platycodin D in human bladder urothelial carcinoma cells.

Platycodin D (PD) is a triterpenoid saponin, a major bioactive constituent of the roots of Platycodon grandiflorum, which is well known for possessing various pharmacological properties. However, the anti-cancer mechanism of PD in bladder cancer cells remains poorly understood. In the current study, we investigated the effect of PD on the growth of human bladder urothelial carcinoma cells. PD treatment significantly reduced the cell survival of bladder cancer cells associated with induction of apoptosis and DNA damage. PD inhibited the expression of inhibitor of apoptosis family members, activated caspases, and induced cleavage of poly (ADP-ribose) polymerase. PD also increased the release of cytochrome c into the cytoplasm by disrupting the mitochondrial membrane potential while upregulating the expression ratio of Bax to Bcl-2. The PD-mediated anti-proliferative effect was significantly inhibited by pre-treatment with a pancaspase inhibitor, but not by an inhibitor of necroptosis. Moreover, PD suppressed the phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway, and the apoptosis-inducing effect of PD was further enhanced by a PI3K inhibitor. In addition, PD increased the accumulation of reactive oxygen species (ROS), whereas N-acetyl cysteine (NAC), an ROS inhibitor, significantly attenuated the growth inhibition and inactivation of the PI3K/Akt/mTOR signaling caused by PD. Furthermore, NAC significantly suppressed apoptosis, DNA damage, and decreased cell viability induced by PD treatment. Collectively, our findings indicated that PD blocked the growth of bladder urothelial carcinoma cells by inducing ROS-mediated inactivation of the PI3K/Akt/mTOR signaling.

Induction of apoptotic cell death in human bladder cancer cells by ethanol extract of Zanthoxylum schinifolium leaf, through ROS-dependent inactivation of the PI3K/Akt signaling pathway.

BACKGROUND/OBJECTIVES: Zanthoxylum schinifolium is traditionally used as a spice for cooking in East Asian countries. This study was undertaken to evaluate the anti-proliferative potential of ethanol extracts of Z. schinifolium leaves (EEZS) against human bladder cancer T24 cells. MATERIALS/METHODS: Subsequent to measuring the cytotoxicity of EEZS, the anti-cancer activity was measured by assessing apoptosis induction, reactive oxygen species (ROS) generation, and mitochondrial membrane potential (MMP). In addition, we determined the underlying mechanism of EEZS-induced apoptosis through various assays, including Western blot analysis. RESULTS: EEZS treatment concentration-dependently inhibited T24 cell survival, which is associated with apoptosis induction. Exposure to EEZS induced the expression of Fas and Fas-ligand, activated caspases, and subsequently resulted to cleavage of poly (ADP-ribose) polymerase. EEZS also enhanced the expression of cytochrome c in the cytoplasm by suppressing MMP, following increase in the ratio of Bax:Bcl-2 expression and truncation of Bid. However, EEZS-mediated growth inhibition and apoptosis were significantly diminished by a pan-caspase inhibitor. Moreover, EEZS inhibited activation of the phosphoinositide 3-kinase (PI3K)/Akt pathway, and the apoptosis-inducing potential of EEZS was promoted in the presence of PI3K/Akt inhibitor. In addition, EEZS enhanced the production of ROS, whereas N-acetyl cysteine (NAC), a ROS scavenger, markedly suppressed growth inhibition and inactivation of the PI3K/Akt signaling pathway induced by EEZS. Furthermore, NAC significantly attenuated the EEZS-induced apoptosis and reduction of cell viability. CONCLUSIONS: Taken together, our results indicate that exposure to EEZS exhibits anti-cancer activity in T24 bladder cancer cells through ROS-dependent induction of apoptosis and inactivation of the PI3K/Akt signaling pathway.

The preventive effect of loganin on oxidative stress-induced cellular damage in human keratinocyte HaCaT cells.

Loganin is a type of iridoid glycosides isolated from Corni fructus and is known to have various pharmacological properties, but studies on its antioxidant activity are still lacking. Therefore, in this study, the preventive effect of loganin on oxidative stress-mediated cellular damage in human keratinocyte HaCaT cells was investigated. Our results show that loganin pretreatment in a non-toxic concentration range significantly improved cell survival in hydrogen peroxide (H2O2)-treated HaCaT cells, which was associated with inhibition of cell cycle arrest at the G2/M phase and induction of apoptosis. H2O2-induced DNA damage and reactive oxygen species (ROS) generation were also greatly reduced in the presence of loganin. Moreover, H2O2 treatment enhanced the cytoplasmic release of cytochrome c, upregulation of the Bax/Bcl-2 ratio and degradation of cleavage of poly (ADP-ribose) polymerase, whereas loganin remarkably suppressed these changes. In addition, loganin obviously attenuated H2O2-induced autophagy while inhibiting the increased accumulation of autophagosome proteins, including as microtubule-associated protein 1 light chain 3-II and Beclin-1, and p62, an autophagy substrate protein, in H2O2-treated cells. In conclusion, our current results suggests that loganin could protect HaCaT keratinocytes from H2O2-induced cellular injury by inhibiting mitochondrial dysfunction, autophagy and apoptosis. This finding indicates the applicability of loganin in the prevention and treatment of skin diseases caused by oxidative damage.

Automatic Cancer Cell Taxonomy Using an Ensemble of Deep Neural Networks.

Microscopic image-based analysis has been intensively performed for pathological studies and diagnosis of diseases. However, mis-authentication of cell lines due to misjudgments by pathologists has been recognized as a serious problem. To address this problem, we propose a deep-learning-based approach for the automatic taxonomy of cancer cell types. A total of 889 bright-field microscopic images of four cancer cell lines were acquired using a benchtop microscope. Individual cells were further segmented and augmented to increase the image dataset. Afterward, deep transfer learning was adopted to accelerate the classification of cancer types. Experiments revealed that the deep-learning-based methods outperformed traditional machine-learning-based methods. Moreover, the Wilcoxon signed-rank test showed that deep ensemble approaches outperformed individual deep-learning-based models (p < 0.001) and were in effect to achieve the classification accuracy up to 97.735%. Additional investigation with the Wilcoxon signed-rank test was conducted to consider various network design choices, such as the type of optimizer, type of learning rate scheduler, degree of fine-tuning, and use of data augmentation. Finally, it was found that the using data augmentation and updating all the weights of a network during fine-tuning improve the overall performance of individual convolutional neural network models.

Classification of the Sidewalk Condition Using Self-Supervised Transfer Learning for Wheelchair Safety Driving.

The demand for wheelchairs has increased recently as the population of the elderly and patients with disorders increases. However, society still pays less attention to infrastructure that can threaten the wheelchair user, such as sidewalks with cracks/potholes. Although various studies have been proposed to recognize such challenges, they mainly depend on RGB images or IMU sensors, which are sensitive to outdoor conditions such as low illumination, bad weather, and unavoidable vibrations, resulting in unsatisfactory and unstable performance. In this paper, we introduce a novel system based on various convolutional neural networks (CNNs) to automatically classify the condition of sidewalks using images captured with depth and infrared modalities. Moreover, we compare the performance of training CNNs from scratch and the transfer learning approach, where the weights learned from the natural image domain (e.g., ImageNet) are fine-tuned to the depth and infrared image domain. In particular, we propose applying the ResNet-152 model pre-trained with self-supervised learning during transfer learning to leverage better image representations. Performance evaluation on the classification of the sidewalk condition was conducted with 100% and 10% of training data. The experimental results validate the effectiveness and feasibility of the proposed approach and bring future research directions.

A Novel Multistage Transfer Learning for Ultrasound Breast Cancer Image Classification.

Breast cancer diagnosis is one of the many areas that has taken advantage of artificial intelligence to achieve better performance, despite the fact that the availability of a large medical image dataset remains a challenge. Transfer learning (TL) is a phenomenon that enables deep learning algorithms to overcome the issue of shortage of training data in constructing an efficient model by transferring knowledge from a given source task to a target task. However, in most cases, ImageNet (natural images) pre-trained models that do not include medical images, are utilized for transfer learning to medical images. Considering the utilization of microscopic cancer cell line images that can be acquired in large amount, we argue that learning from both natural and medical datasets improves performance in ultrasound breast cancer image classification. The proposed multistage transfer learning (MSTL) algorithm was implemented using three pre-trained models: EfficientNetB2, InceptionV3, and ResNet50 with three optimizers: Adam, Adagrad, and stochastic gradient de-scent (SGD). Dataset sizes of 20,400 cancer cell images, 200 ultrasound images from Mendeley and 400 ultrasound images from the MT-Small-Dataset were used. ResNet50-Adagrad-based MSTL achieved a test accuracy of 99 ± 0.612% on the Mendeley dataset and 98.7 ± 1.1% on the MT-Small-Dataset, averaging over 5-fold cross validation. A p-value of 0.01191 was achieved when comparing MSTL against ImageNet based TL for the Mendeley dataset. The result is a significant improvement in the performance of artificial intelligence methods for ultrasound breast cancer classification compared to state-of-the-art methods and could remarkably improve the early diagnosis of breast cancer in young women.

Schisandrae Fructus ethanol extract attenuates particulate matter 2.5-induced inflammatory and oxidative responses by blocking the activation of the ROS-dependent NF-κB signaling pathway.

BACKGROUND/OBJECTIVES: Schisandrae Fructus, the fruit of Schisandra chinensis Baill., has traditionally been used as a medicinal herb for the treatment of various diseases, and has proven its various pharmacological effects, including anti-inflammatory and antioxidant activities. In this study, we investigated the inhibitory effect of Schisandrae Fructus ethanol extract (SF) on inflammatory and oxidative stress in particulate matter 2.5 (PM2.5)-treated RAW 264.7 macrophages. MATERIALS/METHODS: To investigate the anti-inflammatory and antioxidant effects of SF in PM2.5-stimulated RAW 264.7 cells, the levels of pro-inflammatory mediator such as nitric oxide (NO) and prostaglandin E2 (PGE2), cytokines including interleukin (IL)-6 and IL-1ß, and reactive oxygen species (ROS) were measured. To elucidate the mechanism underlying the effect of SF, the expression of genes involved in the generation of inflammatory factors was also investigated. We further evaluated the anti-inflammatory and antioxidant efficacy of SF against PM2.5 in the zebrafish model. RESULTS: The results indicated that SF treatment significantly inhibited the PM2.5-induced release of NO and PGE2, which was associated with decreased inducible NO synthase and cyclooxygenase-2 expression. SF also attenuated the PM2.5-induced expression of IL-6 and IL-1ß, reducing their extracellular secretion. Moreover, SF suppressed the PM2.5-mediated translocation of nuclear factor-kappa B (NF-κB) from the cytosol into nuclei and the degradation of inhibitor IκB-α, indicating that SF exhibited anti-inflammatory effects by inhibiting the NF-κB signaling pathway. In addition, SF abolished PM2.5-induced generation of ROS, similar to the pretreatment of a ROS scavenger, but not by an inhibitor of NF-κB activity. Furthermore, SF showed strong protective effects against NO and ROS production in PM2.5-treated zebrafish larvae. CONCLUSIONS: Our findings suggest that SF exerts anti-inflammatory and antioxidant effects against PM2.5 through ROS-dependent down-regulating the NF-κB signaling pathway, and that SF can be a potential functional substance to prevent PM2.5-mediated inflammatory and oxidative damage.

Gamma-Aminobutyric Acid (GABA) Inhibits α-Melanocyte-Stimulating Hormone-Induced Melanogenesis through GABAA and GABAB Receptors.

Gamma-aminobutyric acid (GABA) is considered the primary inhibitory neurotransmitter in the human cortex. However, whether GABA regulates melanogenesis has not been comprehensively elucidated. In this study, we reveal that GABA (20 mM) significantly inhibited α-melanocyte-stimulating hormone (α-MSH)-induced extracellular (from 354.9% ± 28.4% to 126.5% ± 16.0%) and intracellular melanin contents (from 236.7% ± 11.1% to 102.7% ± 23.1%) in B16F10 melanoma cells, without inducing cytotoxicity. In addition, α-MSH-induced hyperpigmentation in zebrafish larvae was inhibited from 246.3% ± 5.4% to 116.3% ± 3.1% at 40 mM GABA, displaying no apparent cardiotoxicity. We also clarify that the GABA-mediated antimelanogenic properties were related to the direct inhibition of microphthalmia-associated transcription factor (MITF) and tyrosinase expression by inhibiting cyclic adenosine monophosphate (cAMP) and cAMP response element-binding protein (CREB). Furthermore, under α-MSH stimulation, GABA-related antimelanogenic effects were mediated through the GABAA and GABAB receptors, with subsequent inhibition of Ca2+ accumulation. In B16F10 melanoma cells and zebrafish larvae, pretreatment with bicuculline, a GABAA receptor antagonist, and CGP 46381, a GABAB receptor antagonist, reversed the antimelanogenic effect of GABA following α-MSH treatment by upregulating Ca2+ accumulation. In conclusion, our results indicate that GABA inhibits α-MSH-induced melanogenesis. Hence, in addition to the health benefits of GABA in the central nervous system, it could ameliorate hyperpigmentation disorders.