Probing the hair detectability of prohibited substances in sports: an in vivo-in silico-clinical approach and analytical implications compared with plasma, urine, and faeces.

Hair analysis is a crucial method in forensic toxicology with potential applications in revealing doping histories in sports. Despite its widespread use, knowledge about detectable substances in hair is limited. This study systematically assessed the detectability of prohibited substances in sports using a multifaceted approach. Initially, an animal model received a subset of 17 model drugs to compare dose dependencies and detection windows across different matrices. Subsequently, hair incorporation data from the animal experiment were extrapolated to all substances on the World Anti-Doping Agency's List through in-silico prediction. The detectability of substances in hair was further validated in a proof-of-concept human study involving the consumption of diuretics and masking agents. Semi-quantitative analysis of substances in specimens was performed using ultra-performance liquid chromatography-tandem mass spectrometry. Results showed plasma had optimal dose dependencies with limited detection windows, while urine, faeces, and hair exhibited a reasonable relationship with the administered dose. Notably, hair displayed the highest detection probability (14 out of 17) for compounds, including anabolic agents, hormones, and diuretics, with beta-2 agonists undetected. Diuretics such as furosemide, canrenone, and hydrochlorothiazide showed the highest hair incorporation. Authentic human hair confirmed diuretic detectability, and their use duration was determined via segmental analysis. Noteworthy is the first-time reporting of canrenone in human hair. Anabolic agents were expected in hair, whereas undetectable compounds, such as peptide hormones and beta-2 agonists, were likely due to large molecular mass or high polarity. This study enhances understanding of hair analysis in doping investigations, providing insights into substance detectability.

In silico prediction of parkinsonian motor deficits-related neurotoxicants based on the adverse outcome pathway concept.

Exposure to neurotoxicants has been associated with Parkinson's disease (PD). Limited by the clinical variation in the signs and symptoms as well as the slow disease progression, the identification of parkinsonian neurotoxicants relies on animal models. Here, we propose an innovative in silico model for the prediction of parkinsonian neurotoxicants. The model was designed based on a validated adverse outcome pathway (AOP) for parkinsonian motor deficits initiated from the inhibition of mitochondrial complex I. The model consists of a molecular docking model for mitochondrial complex I protein to predict the molecular initiating event and a neuronal cytotoxicity Quantitative Structure-Activity Relationships (QSAR) model to predict the cellular outcome of the AOP. Four known PD-related complex I inhibitors and four non-neurotoxic chemicals were utilized to develop the threshold of the models and to validate the model, respectively. The integrated model showed 100% specificity in ruling out the non-neurotoxic chemicals. The screening of 41 neurotoxicants and complex I inhibitors with the model resulted in 16 chemicals predicted to induce parkinsonian disorder through the molecular initiating event of mitochondrial complex I inhibition. Five of them, namely cyhalothrin, deguelin, deltamethrin, diazepam, and permethrin, are cases with direct evidence linking them to parkinsonian motor deficit-related signs and symptoms. The neurotoxicant prediction model for parkinsonian motor deficits based on the AOP concept may be useful in prioritizing chemicals for further evaluations on PD potential.

Discovery of Spoilage Markers for Chicken Eggs Using Liquid Chromatography-High Resolution Mass Spectrometry-Based Untargeted and Targeted Foodomics.

The current approaches remain insufficient for measuring chicken egg spoilage or present analytical limitations. This study aimed to complement the existing analyses and identify novel markers using liquid chromatography-high resolution mass spectrometry-based foodomics strategies. In the discovery set, comparative untargeted metabolomics was utilized to identify marker candidates in microbially inoculated chicken eggs. Markers were annotated by spectral matching with authentic standards, experimental libraries, or in silico fragmentation. In the validation set, targeted metabolomics was employed to verify the markers in stored chicken eggs from five farms. Statistical differences at a p-value < 0.001 revealed increases in lactic and 3-hydroxybutyric acids and decreases in phosphocholine, LPE(O-18:1), LPC(16:0), and LPC(18:0) in stored eggs. Receiver operating characteristic curve analysis of the six combined markers yielded an AUC of 0.956 and a sensitivity and specificity of ∼90%. Four phospholipids were highlighted as a novel class of spoilage markers. Our findings may contribute to further industrial implementation, benefiting the quality assurance and food safety of poultry egg production.

Computational identification of preservatives with potential neuronal cytotoxicity.

Preservatives play a vital role in cosmetics by preventing microbiological contamination for keeping products safe to use. However, a few commonly used preservatives have been suggested to be neurotoxic. Cytotoxicity to neuronal cells is commonly used as the first-tier assay for assessing chemical-induced neurotoxicity. Given the time and resources required for chemical screening, computational methods are attractive alternatives over experimental approaches in prioritizing chemicals prior to further experimental evaluations. In this study, we developed a Quantitative Structure-Activity Relationships (QSAR) model for the identification of potential neurotoxicants. A set of 681 chemicals was utilized to construct a robust prediction model using oversampling and Random Forest algorithms. Within a defined applicability domain, the independent test on 452 chemicals showed a high accuracy of 87.7%. The application of the model to 157 preservatives identified 15 chemicals potentially toxic to neuronal cells. Three of them were further validated by in vitro experiments. The results suggested that further experiments are desirable for assessing the neurotoxicity of the identified preservatives with potential neuronal cytotoxicity.

Anti-Inflammatory and Antibacterial Activity Constituents from the Stem of Cinnamomum validinerve.

One new dibenzocycloheptene, validinol (1), and one butanolide firstly isolated from the natural source, validinolide (2), together with 17 known compounds were isolated from the stem of Cinnamomum validinerve. Among the isolates, lincomolide A (3), secosubamolide (7), and cinnamtannin B1 (19) exhibited potent inhibition on both superoxide anion generation (IC50 values of 2.98 ± 0.3 µM, 4.37 ± 0.38 µM, and 2.20 ± 0.3 µM, respectively) and elastase release (IC50 values of 3.96 ± 0.31 µM, 3.04 ± 0.23 µM, and 4.64 ± 0.71 µM, respectively) by human neutrophils. In addition, isophilippinolide A (6), secosubamolide (7), and cinnamtannin B1 (19) showed bacteriostatic effects against Propionibacterium acnes in in vitro study, with minimal inhibitory concentration (MIC) values at 16 µg/mL, 16 µg/mL, and 500 µg/mL, respectively. Further investigations using the in vivo ear P. acnes infection model showed that the intraperitoneal administration of the major component cinnamtannin B1 (19) reduced immune cell infiltration and pro-inflammatory cytokines TNF-α and IL-6 at the infection sites. The results demonstrated the potential of cinnamtannin B1 (19) for acne therapy. In summary, these results demonstrated the anti-inflammatory potentials of Formosan C. validinerve during bacterial infections.

Cinnamtannin B1 attenuates rosacea-like signs via inhibition of pro-inflammatory cytokine production and down-regulation of the MAPK pathway.

BACKGROUND: Rosacea is a common inflammatory disease of facial skin. Dysregulation of innate immunity with enhanced inflammation and increased abundance of LL-37 at the epidermal site is a characteristic feature of rosacea. Cinnamtannin B1 (CB1) is a condensed tannin with anti-inflammatory and anti-microbial activities. The aims of the study were to evaluate the potential of CB1 as a therapy for rosacea and to characterize the potential mechanisms of action. METHODS: We intraperitoneally administered 20 mg/kg CB1 once daily for 2 days into the LL-37-induced mouse model of rosacea. The effects of CB1 in vivo were evaluated by the observations of lesions, histology, immunohistochemistry, and the transcription and translation of pro-inflammatory cytokines and chemokines. Human keratinocyte HaCaT and monocyte THP-1 were used to characterize the effects of CB1 on LL-37-induced inflammation in vitro. The changes in pro-inflammatory chemokine interleukin-8 (IL-8) were quantitated by enzyme-linked immunosorbent assay (ELISA), and the expressions of genes involved were determined by Western blotting. RESULTS: CB1 attenuated local redness, inflammation, and neutrophil recruitment in the mouse model of rosacea in vivo. CB1 suppressed myeloperoxidase (MPO) and macrophage inflammatory protein 2 (MIP-2) production, a functional homolog of interleukin-8 (IL-8), at the lesions. In vitro experiments confirmed that CB1 reversed the LL-37-induced IL-8 production in human keratinocytes HaCaT and monocyte THP-1 cells. CB1 inhibited IL-8 production through downregulating the phosphorylation of extracellular signal-regulated kinase (ERK) in the mitogen-activated protein kinase (MAPK) pathway. CONCLUSION: CB1 attenuated LL-37-induced inflammation, specifically IL-8 production, through inhibiting the phosphorylation of ERK. CB1 has potential as a treatment for rosacea.