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Hyperpigmentation disorders causing emotional distress require the topical use of depigmenting agents of natural origin. In this study, the anti-melanogenic effects of the Lilium lancifolium root extract (LRE) were investigated in B16F10 cells. Consequently, a non-cytotoxic concentration of the extract reduced intracellular melanin content and tyrosinase activity in a dose-dependent manner, correlating with the diminished expression of core melanogenic enzymes within cells. LRE treatment also inhibited cyclic adenosine monophosphate (cAMP) response element-binding protein (CREB)/microphthalmia-associated transcription factor signaling, which regulates the expression of tyrosinase-related genes. Upon examining these findings from a molecular mechanism perspective, LRE treatment suppressed the phosphorylation of protein kinase A (PKA), p38, and extracellular signal-related kinase (ERK), which are upstream regulators of CREB. In addition, L-phenylalanine and regaloside A, specifically identified within the LRE using liquid chromatography-mass spectrometry, exhibited inhibitory effects on melanin production. Collectively, these results imply that LRE potentially suppresses cAMP-mediated melanogenesis by downregulating PKA/CREB and mitogen-activated protein kinase (MAPK)/CREB signaling pathways. Therefore, it can be employed as a novel therapeutic ingredient of natural origin to ameliorate hyperpigmentation disorders.

Background Melatonin, a neurohormone, maybe involved in physiological processes, such as antioxidation, anti-inflammation, and hair growth. In the present study, we investigated the effects of melatonin on proliferation and intracellular signaling in DP cells using a three-dimensional (3D) spheroid culture system that mimics the in vivo hair follicle system. Methods DP cells were incubated in monolayer (2D) and 3D spheroid culture systems. The expression levels of melatonin receptors in DP cells were analyzed using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting. The effect of melatonin on the hair-inductive property of DP cells was analyzed using a WST-1-based proliferation assay, determination of DP spheroid size, expression analysis of DP signature genes, and determination of β-catenin stabilization in DP cells. The AKT/GSK3β/β-catenin signaling pathway associated with melatonin-induced β-catenin stabilization in DP cells was investigated by analyzing changes in upstream regulator proteins, including AKT, GSK3β, and their phosphorylated forms. Results The expression levels of the melatonin receptors were higher in human DP cells than in human epidermal keratinocytes and human dermal fibroblast cells. Comparing the expression level according to the human DP cell culture condition, melatonin receptor expression was upregulated in the 3D culture system compared to the traditional two-dimensional monolayer culture system. Cell viability analysis showed that melatonin concentrations up to 1 mM did not affect cell viability. Moreover, melatonin increased the diameter of DP cell 3D spheroids in a dose-dependent manner. Immunoblotting and qRT-PCR analysis revealed that melatonin upregulated the expression of hair growth-related genes, including alkaline phosphatase, bone morphogenetic protein 2, versican, and wingless-int 5A, in a melatonin receptor-dependent manner. Cell fractionation analysis showed that melatonin increased the nuclear localization of β-catenin. This result correlated with the increased transcriptional activation of T-cell factor/lymphoid enhancer factor-responsive luciferase induced by melatonin treatment. Interestingly, melatonin induced the phosphorylation of protein kinase B/AKT at serine 473 residue and GSK-3β at serine 9 residue. To determine whether AKT phosphorylation at serine 473 induced β-catenin nuclear translocation through GSK3β phosphorylation at serine 9, the PI3K/AKT inhibitor LY294002 was cotreated with melatonin. Immunoblotting showed that LY294002 inhibited melatonin-induced phosphorylation of GSK3β at serine 9 residue and β-catenin activation. Conclusion Collectively, this report suggests that melatonin promotes growth properties by activating the AKT/GSK3β/β-catenin signaling pathway through melatonin receptors.

Glucose metabolism is a key metabolic pathway that orchestrates cellular homeostasis by generating ATP, nucleotides, and amino acids. Abnormal glucose signaling has been found in many diseases including cancers and inflammatory diseases. According to recent report, glycolysis contributes to pathogenesis of psoriasis and ablation of Glut1 attenuates animal models of psoriasis. While we were screening a molecular target for atopic dermatitis, we found the levels of glucose transporters including Glut1 (SLC2a1) and Glut3 (SLC2a3) are highly expressed in skin biopsies of dermatitis patients from multiple datasets. We demonstrated that administration of 2-deoxy-d-glucose (2DG) ameliorates animal models of 12-o-tetradecanoylphorbol-13-acetate (TPA) and oxazolone induced dermatitis using morphological and histological analysis. These results suggest that inhibition of glucose metabolism ameliorates dermatitis in animal models.

BACKGROUND: Accumulating evidence indicates that reactive oxygen species (ROS) are an important etiological factor for the induction of dermal papilla cell senescence and hair loss, which is also known alopecia. Arctiin is an active lignin isolated from Arctium lappa and has anti-inflammation, anti-microbial, and anti-carcinogenic effects. In the present study, we found that arctiin exerts anti-oxidative effects on human hair dermal papilla cells (HHDPCs). RESULTS: To better understand the mechanism, we analyzed the level of hydrogen peroxide (H2O2)-induced cytotoxicity, cell death, ROS production and senescence after arctiin pretreatment of HHDPCs. The results showed that arctiin pretreatment significantly inhibited the H2O2-induced reduction in cell viability. Moreover, H2O2-induced sub-G1 phase accumulation and G2 cell cycle arrest were also downregulated by arctiin pretreatment. Interestingly, the increase in intracellular ROS mediated by H2O2 was drastically decreased in HHDPCs cultured in the presence of arctiin. This effect was confirmed by senescence associated-beta galactosidase (SA-β-gal) assay results; we found that arctiin pretreatment impaired H2O2-induced senescence in HHDPCs. Using microRNA (miRNA) microarray and bioinformatic analysis, we showed that this anti-oxidative effect of arctiin in HHDPCs was related with mitogen-activated protein kinase (MAPK) and Wnt signaling pathways. CONCLUSIONS: Taken together, our data suggest that arctiin has a protective effect on ROS-induced cell dysfunction in HHDPCs and may therefore be useful for alopecia prevention and treatment strategies.

In this study, the protective functions of bacteria-free conditioned media from Bifidobacterium and Lactobacillus species against ultraviolet radiation-induced skin ageing and associated cellular damage were investigated. The effects of ultraviolet radiation-induced reactive oxygen species production were suppressed by all conditioned media; particularly, the loss of cell viability and downregulation of collagen gene expression were significantly reversed by the conditioned media from B. longum and B. lactis. Further exa mination of potential anti-pigmentation effects revealed that the B. lactis-derived conditioned media significantly inhibited tyrosinase activity and alpha-melanocyte-stimulating hormone-induced melanin production in human epidermal melanocytes. Further, the conditioned media suppressed the phosphorylation of extracellular signal- related kinase, which functions as an upstream regulator of melanogenesis. Therefore, B. lactis-derived conditioned media can potentially protect against cellular damage involved in skin-ageing processes.

Abstract The hygroscopic property of particulate matter (PM) influencing light scattering and absorption is vital for determining visibility and accurate sensing of PM using a low-cost sensor. In this study, we examined the hygroscopic properties of coarse PM (CPM) and fine PM (FPM; PM2.5) and the effects of their interactions with weather factors on visibility. A censored regression model was built to investigate the relationships between CPM and PM2.5 concentrations and weather observations. Based on the observed and modeled visibility, we computed the optical hygroscopic growth factor, $$f\left( {RH} \right)$$ f RH , and the hygroscopic mass growth, $$GM_{VIS}$$ G M VIS , which were applied to PM2.5 field measurement using a low-cost PM sensor in two different regions. The results revealed that the CPM and PM2.5 concentrations negatively affect visibility according to the weather type, with substantial modulation of the interaction between the relative humidity (RH) and PM2.5. The modeled $$f\left( {RH} \right)$$ f RH agreed well with the observed $$f\left( {RH} \right)$$ f RH in the RH range of the haze and mist. Finally, the RH-adjusted PM2.5 concentrations based on the visibility-derived hygroscopic mass growth showed the accuracy of the low-cost PM sensor improved. These findings demonstrate that in addition to visibility prediction, relationships between PMs and meteorological variables influence light scattering PM sensing.

Autonomous driving is a complex problem that requires intelligent decision making, and it has recently garnered significant interest due to its potential advantages in convenience and safety. In autonomous driving, conventional path planning to reach a destination is a time-consuming challenge. Therefore, learning-based approaches have been successfully applied to the controller or decision-making aspects of autonomous driving. However, these methods often lack explainability, as passengers cannot discern where the vehicle is headed. Additionally, most experiments primarily focus on highway scenarios, which do not effectively represent road curvature. To address these issues, we propose a reinforcement-learning-based trajectory learning in the Frenet frame (RLTF), which involves learning trajectories in the Frenet frame. Learning trajectories enable the consideration of future states and enhance explainability. We demonstrate that RLTF achieves a 100% success rate in the simulation environment, considering future states on curvy roads with continuous obstacles while overcoming issues associated with the Frenet frame. [ABSTRACT FROM AUTHOR]

Digital public displays installed in various locations provide valuable information for the passers-by. However, the static characteristic of the digital public display limits the consumption of the displayed content to a small area. Personal mobile devices such as smartphones are now capable of interacting with digital public displays, which enables the passers-by to "take-away" the content and consume it on-the-go. This process requires device binding, content selection, and transfer between the two devices. In this paper, we propose a device binding method which utilizes the content brightness changing pattern as a unique content ID on the public display and an illuminance sensor on the mobile to bind and transfer between two devices. We conducted performance evaluations for binding algorithm robustness in different conditions. Also comparative studies among other binding interaction methods were conducted. Our results show that our proposed method performed stably across the various conditions and overall performance in interaction completion time and error rate was similar or superior to the existing methods.

Lately, pose estimation based on learning-based Visual Odometry (VO) methods, where raw image data are provided as the input of a neural network to get 6 Degrees of Freedom (DoF) information, has been intensively investigated. Despite its recent advances, learning-based VO methods still perform worse than the classical VO that consists of feature-based VO methods and direct VO methods. In this paper, a new pose estimation method with the help of a Gated Recurrent Unit (GRU) network trained by pose data acquired by an accurate sensor is proposed. The historical trajectory data of the yaw angle are provided to the GRU network to get a yaw angle at the current timestep. The proposed method can be easily combined with other VO methods to enhance the overall performance via an ensemble of predicted results. Pose estimation using the proposed method is especially advantageous in the cornering section which often introduces an estimation error. The performance is improved by reconstructing the rotation matrix using a yaw angle that is the fusion of the yaw angles estimated from the proposed GRU network and other VO methods. The KITTI dataset is utilized to train the network. On average, regarding the KITTI sequences, performance is improved as much as 1.426% in terms of translation error and 0.805 deg/100 m in terms of rotation error.