Conventional and multi-omics assessments of subacute inhalation toxicity due to propylene glycol and vegetable glycerin aerosol produced by electronic cigarettes.

Propylene glycol (PG) and vegetable glycerin (VG) are the most common solvents used in electronic cigarette liquids. No long-term inhalation toxicity assessments have been performed combining conventional and multi-omics approaches on the potential respiratory effects of the solvents in vivo. In this study, the systemic toxicity of aerosol generated from a ceramic heating coil-based e-cigarette was evaluated. First, the aerosol properties were characterized, including carbonyl emissions, the particle size distribution, and aerosol temperatures. To determine toxicological effects, rats were exposed, through their nose only, to filtered air or a propylene glycol (PG)/ glycerin (VG) (50:50, %W/W) aerosol mixture at the target concentration of 3 mg/L for six hours daily over a continuous 28-day period. Compared with the air group, female rats in the PG/VG group exhibited significantly lower body weights during both the exposure period and recovery period, and this was linked to a reduced food intake. Male rats in the PG/VG group also experienced a significant decline in body weight during the exposure period. Importantly, rats exposed to the PG/VG aerosol showed only minimal biological effects compared to those with only air exposure, with no signs of toxicity. Moreover, the transcriptomic, proteomic, and metabolomic analyses of the rat lung tissues following aerosol exposure revealed a series of candidate pathways linking aerosol inhalation to altered lung functions, especially the inflammatory response and disease. Dysregulated pathways of arachidonic acids, the neuroactive ligand-receptor interaction, and the hematopoietic cell lineage were revealed through integrated multi-omics analysis. Therefore, our integrated multi-omics approach offers novel systemic insights and early evidence of environmental-related health hazards associated with an e-cigarette aerosol using two carrier solvents in a rat model.

Pharmacokinetic differences in nicotine and nicotine salts mediate reinforcement-related behavior: an animal model study.

Since their introduction in the United States and Europe in 2007, electronic cigarettes (E-Cigs) have become increasingly popular among smokers. Nicotine, a key component in both tobacco and e-cigarettes, can exist in two forms: nicotine-freebase (FBN) and nicotine salts (NS). While nicotine salt is becoming more popular in e-cigarettes, the effect of nicotine salts on reinforcement-related behaviors remains poorly understood. This study aimed to compare the reinforcing effects of nicotine and nicotine salts in animal models of drug self-administration and explore potential mechanisms that may contribute to these differences. The results demonstrated that three nicotine salts (nicotine benzoate, nicotine lactate, and nicotine tartrate) resulted in greater reinforcement-related behaviors in rats compared to nicotine-freebase. Moreover, withdrawal-induced anxiety symptoms were lower in the three nicotine salt groups than in the nicotine-freebase group. The study suggested that differences in the pharmacokinetics of nicotine-freebase and nicotine salts in vivo may explain the observed behavioral differences. Overall, this study provides valuable insights into the reinforcing effects of nicotine as well as potential differences between nicotine-freebase and nicotine salts.

Cancer survival prediction by learning comprehensive deep feature representation for multiple types of genetic data.

BACKGROUND: Cancer is one of the leading death causes around the world. Accurate prediction of its survival time is significant, which can help clinicians make appropriate therapeutic schemes. Cancer data can be characterized by varied molecular features, clinical behaviors and morphological appearances. However, the cancer heterogeneity problem usually makes patient samples with different risks (i.e., short and long survival time) inseparable, thereby causing unsatisfactory prediction results. Clinical studies have shown that genetic data tends to contain more molecular biomarkers associated with cancer, and hence integrating multi-type genetic data may be a feasible way to deal with cancer heterogeneity. Although multi-type gene data have been used in the existing work, how to learn more effective features for cancer survival prediction has not been well studied. RESULTS: To this end, we propose a deep learning approach to reduce the negative impact of cancer heterogeneity and improve the cancer survival prediction effect. It represents each type of genetic data as the shared and specific features, which can capture the consensus and complementary information among all types of data. We collect mRNA expression, DNA methylation and microRNA expression data for four cancers to conduct experiments. CONCLUSIONS: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction. AVAILABILITY AND IMPLEMENTATION: https://github.com/githyr/ComprehensiveSurvival .

Joint learning sample similarity and correlation representation for cancer survival prediction.

BACKGROUND: As a highly aggressive disease, cancer has been becoming the leading death cause around the world. Accurate prediction of the survival expectancy for cancer patients is significant, which can help clinicians make appropriate therapeutic schemes. With the high-throughput sequencing technology becoming more and more cost-effective, integrating multi-type genome-wide data has been a promising method in cancer survival prediction. Based on these genomic data, some data-integration methods for cancer survival prediction have been proposed. However, existing methods fail to simultaneously utilize feature information and structure information of multi-type genome-wide data. RESULTS: We propose a Multi-type Data Joint Learning (MDJL) approach based on multi-type genome-wide data, which comprehensively exploits feature information and structure information. Specifically, MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned multiple correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representation matrix and fused similarity matrix, MDJL constructs graph convolutional network with Cox loss for survival prediction. CONCLUSIONS: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction.

Corrigendum: Menthol Flavor in E-Cigarette Vapor Modulates Social Behavior Correlated With Central and Peripheral Changes of Immunometabolic Signalings.

[This corrects the article DOI: 10.3389/fnmol.2022.800406.].

Menthol Flavor in E-Cigarette Vapor Modulates Social Behavior Correlated With Central and Peripheral Changes of Immunometabolic Signalings.

The use of electronic cigarette (e-cigarette) has been increasing dramatically worldwide. More than 8,000 flavors of e-cigarettes are currently marketed and menthol is one of the most popular flavor additives in the electronic nicotine delivery systems (ENDS). There is a controversy over the roles of e-cigarettes in social behavior, and little is known about the potential impacts of flavorings in the ENDS. In our study, we aimed to investigate the effects of menthol flavor in ENDS on the social behavior of long-term vapor-exposed mice with a daily intake limit, and the underlying immunometabolic changes in the central and peripheral systems. We found that the addition of menthol flavor in nicotine vapor enhanced the social activity compared with the nicotine alone. The dramatically reduced activation of cellular energy measured by adenosine 5' monophosphate-activated protein kinase (AMPK) signaling in the hippocampus were observed after the chronic exposure of menthol-flavored ENDS. Multiple sera cytokines including C5, TIMP-1, and CXCL13 were decreased accordingly as per their peripheral immunometabolic responses to menthol flavor in the nicotine vapor. The serum level of C5 was positively correlated with the alteration activity of the AMPK-ERK signaling in the hippocampus. Our current findings provide evidence for the enhancement of menthol flavor in ENDS on social functioning, which is correlated with the central and peripheral immunometabolic disruptions; this raises the vigilance of the cautious addition of various flavorings in e-cigarettes and the urgency of further investigations on the complex interplay and health effects of flavoring additives with nicotine in e-cigarettes.

In vitro and in vivo antibacterial activity of a lysine-rich scorpion peptide derivative.

Antimicrobial peptides are widely acknowledged as an alternative class of antimicrobial agents. In this study, a lysine-rich scorpion peptide derivative Pacavin-5K was designed, which showed an improved antibacterial spectrum, significantly higher antibacterial activity, and lower toxicity compared to the native peptide. It also showed an improved thermal and serum stability. Notably, Pacavin-5K significantly decreased the bacterial counts in the wounded region in the mouse cutaneous infection model caused by Staphylococcus aureus and Pseudomonas aeruginosa. Moreover, Pacavin-5K did not induce bacterial resistance associated with its antibacterial mechanism disrupting the membrane. Furthermore, Pacavin-5K could kill the S. aureus cells at the biofilm state. Overall, Pacavin-5K could be a potential alternative antibacterial agent against skin infection caused by S. aureus and P. aeruginosa.

Involvement of oxytocin and GABA in consolation behavior elicited by socially defeated individuals in mandarin voles.

Consolation, which entails comforting contact directed toward a distressed party, is a common empathetic response in humans and other species with advanced cognition. Here, using the social defeat paradigm, we provide empirical evidence that highly social and monogamous mandarin voles (Microtus mandarinus) increased grooming toward a socially defeated partner but not toward a partner who underwent only separation. This selective behavioral response existed in both males and females. Accompanied with these behavioral changes, c-Fos expression was elevated in many of the brain regions relevant for emotional processing, such as the anterior cingulate cortex (ACC), bed nucleus of the stria terminalis, paraventricular nucleus (PVN), basal/basolateral and central nucleus of the amygdala, and lateral habenular nucleus in both sexes; in the medial preoptic area, the increase in c-Fos expression was found only in females, whereas in the medial nucleus of the amygdala, this increase was found only in males. In particular, the GAD67/c-Fos and oxytocin (OT)/c-Fos colocalization rates were elevated in the ACC and PVN, indicating selective activation of GABA and OT neurons in these regions. The "stressed" pairs matched their anxiety-like behaviors in the open-field test, and their plasma corticosterone levels correlated well with each other, suggesting an empathy-based mechanism. This partner-directed grooming was blocked by pretreatment with an OT receptor antagonist or a GABAA receptor antagonist in the ACC but not by a V1a subtype vasopressin receptor antagonist. We conclude that consolation behavior can be elicited by the social defeat paradigm in mandarin voles, and this behavior may be involved in a coordinated network of emotion-related brain structures, which differs slightly between the sexes. We also found that the endogenous OT and the GABA systems within the ACC are essential for consolation behavior in mandarin voles.