Particulate matter (PM10) exacerbates on MK-801-induced schizophrenia-like behaviors through the inhibition of ERK-CREB-BDNF signaling pathway.

Particulate matter (PM), released into the air by a variety of natural and human activities, is a key indicator of air pollution. Although PM is known as the extensive health hazard to affect a variety of illness, few studies have specifically investigated the effects of PM10 exposure on schizophrenic development. In the present study, we aimed to investigate the impact of PM10 on MK-801, N-methyl-D-aspartate (NMDA) receptor antagonist, induced schizophrenia-like behaviors in C57BL/6 mouse. Preadolescent mice were exposed PM10 to 3.2 mg/m3 concentration for 4 h/day for 2 weeks through a compartmentalized whole-body inhalation chamber. After PM10 exposure, we conducted behavioral tests during adolescence and adulthood to investigate longitudinal development of schizophrenia. We found that PM10 exacerbated schizophrenia-like behavior, such as psychomotor agitation, social interaction deficits and cognitive deficits at adulthood in MK-801-induced schizophrenia animal model. Furthermore, the reduced expression levels of brain-derived neurotrophic factor (BDNF) and the phosphorylation of BDNF related signaling molecules, extracellular signal-regulated kinase (ERK) and cAMP response element-binding protein (CREB), were exacerbated by PM10 exposure in the adult hippocampus of MK-801-treated mice. Thus, our present study demonstrates that exposure to PM10 in preadolescence exacerbates the cognitive impairment in animal model of schizophrenia, which are considered to be facilitated by the decreased level of BDNF through reduced ERK-CREB expression.

Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models.

This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as air fresheners, fragrances, and anti-fogging agents submitted to K-REACH using machine learning models. We manually curated inhalation toxicity data based on OECD test guideline 403 (Acute inhalation), 412 (Sub-acute inhalation), and 413 (Sub-chronic inhalation) for 1709 chemicals from the OECD eChemPortal database. Machine learning models were trained using ten algorithms, along with four molecular fingerprints (MACCS, Morgan, Topo, RDKit) and molecular descriptors, achieving F1 scores ranging from 51 % to 91 % in test dataset. Leveraging the high-performing models, we conducted a virtual screening of chemicals, initially applying them to data-rich chemicals generally used in occupational settings to determine the prediction uncertainty. Results showed high sensitivity (75 %) but low specificity (23 %), suggesting that our models can contribute to conservative screening of chemicals. Subsequently, we applied the models to consumer product chemicals, identifying 79 as of high concern. Most of the prioritized chemicals lacked GHS classifications related to inhalation toxicity, even though they were predicted to be used in many consumer products. This study highlights a potential regulatory blind spot concerning the inhalation risk of consumer product chemicals while also indicating the potential of artificial intelligence (AI) models to aid in prioritizing chemicals at the screening level.

Geraniin from the methanol extract of Pilea mongolica suppresses LPS-induced inflammatory responses by inhibiting IRAK4/MAPKs/NF-κB/AP-1 pathway in HaCaT cells.

The skin acts as a vital barrier, shielding the body from external threats that can trigger dryness, itching, and inflammation. Pilea mongolica, a traditional Chinese medicinal herb, holds promise for various ailments, yet its anti-inflammatory properties remain understudied. This study aimed to explore the potential anti-inflammatory effects of the methanol extract of P. mongolica (MEPM) and its underlying molecular mechanisms and active compounds in LPS-stimulated human keratinocytes. MEPM treatment, at concentrations without cytotoxicity, significantly decreased NO productions and the iNOS, IL-6, IL-1ß, and TNF-α levels in LPS-induced HaCaT cells. Moreover, MEPM suppressed IRAK4 expression and phosphorylation of JNK, ERK, p38, p65, and c-Jun, suggesting that the anti-inflammatory effects of MEPM result from the inhibition of IRAK4/MAPK/NF-κB/AP-1 signaling pathway. Through LC/MS/MS analysis, 30 compounds and 24 compounds were estimated in negative and positive modes, respectively, including various anti-inflammatory compounds, such as corilagin and geraniin. Through HPLC analysis, geraniin was found to be present in MEPM at a concentration of 18.87 mg/g. Similar to MEPM, geraniin reduced iNOS mRNA expression and inhibited NO synthesis. It also decreased mRNA and protein levels of inflammatory cytokines, including IL-6 and TNF-α, and inhibited IRAK4 expression and the phosphorylation of MAPKs, NF-κB, and AP-1 pathways. Therefore, it can be inferred that the anti-inflammatory effects of MEPM are attributable to geraniin. Thus, MEPM and its active compound geraniin are potential candidates for use in natural functional cosmetics.

Anti-Inflammatory Effects of the LK5 Herbal Complex on LPS- and IL-4/IL-13-Stimulated HaCaT Cells and a DNCB-Induced Animal Model of Atopic Dermatitis in BALB/c Mice.

Atopic dermatitis (AD) is a chronic inflammatory skin disease influenced by a complex interplay of genetic and environmental factors. The activation of the JAK-STAT pathway increases the expression of inflammatory cytokines such as IL-4 and IL-13, further deteriorating AD. Therefore, for the treatment of AD, the JAK-STAT pathway is emerging as a significant target, alongside inflammatory cytokines. This study investigates the potential therapeutic effects of a novel herbal complex, LK5, composed of Scutellaria baicalensis, Liriope platyphylla, Sophora flavescens, Dictammus dasycarpus, and Phellodendron schneider, known for their anti-inflammatory and immune-modulating properties. We examined the anti-inflammatory and anti-AD effects of the LK5 herbal complex in HaCaT cells stimulated by LPS and IL-4/IL-13, as well as in a mouse model of AD induced by DNCB. In HaCaT cells stimulated with LPS or IL-4/IL-13, the LK5 herbal complex demonstrated anti-inflammatory effects by inhibiting the expression of inflammatory cytokines including TNF-α, IL-6, and IL-1ß, and downregulating the phosphorylation of STAT proteins. In a murine AD-like model induced by DNCB, administration of the LK5 herbal complex significantly ameliorated clinical symptoms, including dermatitis, ear thickness, and TEWL. Histological analysis revealed a reduction in epidermal thickness and mast cell infiltration. The LK5 herbal complex also inhibited pruritus induced by compound 48/80. Furthermore, the LK5 herbal complex treatment significantly decreased the levels of inflammatory cytokines such as TSLP, IL-6, and IgE in plasma and ear tissue of AD-induced mice. These findings suggest that the LK5 herbal complex may modulate the immune response and alleviate AD symptoms by inhibiting STAT pathways.