Mentha spicata, also called Mentha viridis, is a medicinal plant of the Lamiaceae family characterized by its potency to synthesize and secret secondary metabolites, essentially essential oils. Different populations use the aerial parts of this plant for tea preparation, and this tisane has shown several effects, according to ethnopharmacological surveys carried out in different areas around the world. These effects are attributed to different compounds of M. spicata, in which their biological effects were recently proved experimentally. Pharmacological properties of M. spicata extracts and essential oils were investigated for different health benefits such as antioxidant, anticancer, antiparasitic, antimicrobial, and antidiabetic effects. In vitro and in vivo studies showed positives effects that could be certainly related to different bioactive compounds identified in M. spicata. Indeed, volatile compounds seem to be efficient in inhibiting different microbial agents such as bacteria, fungi, and parasites through several mechanisms. Moreover, M. spicata exhibited, according to some studies, promising antioxidant, antidiabetic, anti-inflammatory, and anticancer effects, which show its potential to be used as a source for identifying natural drugs against cellular oxidative stress and its related diseases. Importantly, toxicological investigations of M. spicata show the safety of this species at different doses and several periods of use which justify its use in traditional medicines as tisane with tea. Here, we report, explore, and highlight the data published on M. spicata concerning its botanical description and geographical distribution, its phytochemical compounds, its pharmacological properties, and its toxicological investigations of M. spicata.

Objectives: Exposure to air pollution has destructive health consequences and a potential role in ovarian cancer etiology. We conducted a systematic review of the studies assessing the associations between ovarian malignancy and exposure to air pollutants. Content: The included studies were categorized based on types of measured ambient air pollutants, including particulate matter (five studies), gases (two studies), air pollutant mixtures (eight studies), and traffic indicators for air pollution (only one study). Because of the heterogeneity of quantitative data of the reviewed studies, we qualitatively reviewed the air pollution role in ovarian cancer risk with representing incidence and/or the mortality rate of ovarian cancer in related with air pollution. Nine studies were ecological study design. Except for one, all studies confirmed a positive correlation between exposure to ambient air pollution (AAP) and increased ovarian cancer risks. Summary: We concluded that prolonged air pollution exposure through possible mechanisms, estrogen-like effects, and genetic mutations might affect ovarian tumorigenesis. This research surveyed the limitations of the previous studies, including issues with ambient air pollution surveillance and assessing the exposure, determining the air pollution sources, data analysis approaches, and study designs. Outlook: Finally, the authors provide suggestions for future environmental epidemiological inquiries on the impact of exposure to ambient air pollution on ovarian malignancy.

Objective: This study aimed to identify candidate gene biomarkers associated with immune infiltration in idiopathic pulmonary fibrosis (IPF) based on machine learning algorithms.Methods: Microarray datasets of IPF were extracted from the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs). The DEGs were subjected to enrichment analysis, and two machine learning algorithms were used to identify candidate genes associated with IPF. These genes were verified in a validation cohort from the GEO database. Receiver operating characteristic (ROC) curves were plotted to assess the predictive value of the IPF-associated genes. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to evaluate the proportion of immune cells in IPF and normal tissues. Additionally, the correlation between the expression of IPF-associated genes and the infiltration levels of immune cells was examined.Results: A total of 302 upregulated and 192 downregulated genes were identified. Functional annotation, pathway enrichment, Disease Ontology and gene set enrichment analyses revealed that the DEGs were related to the extracellular matrix and immune responses. COL3A1, CDH3, CEBPD, and GPIHBP1 were identified as candidate biomarkers using machine learning algorithms, and their predictive value was verified in a validation cohort. Additionally, ROC analysis revealed that the four genes had high predictive accuracy. The infiltration levels of plasma cells, M0 macrophages and resting dendritic cells were higher and those of resting natural killer (NK) cells, M1 macrophages and eosinophils were lower in the lung tissues of patients with IPF than in those of healthy individuals. The expression of the abovementioned genes was correlated with the infiltration levels of plasma cells, M0 macrophages and eosinophils.Conclusion: COL3A1, CDH3, CEBPD, and GPIHBP1 are candidate biomarkers of IPF. Plasma cells, M0 macrophages and eosinophils may be involved in the development of IPF and may serve as immunotherapeutic targets in IPF.

Global threat resulting in heavy metal contamination of medicinal plants is considered a serious concern. The quantitative evaluation of four heavy metals, lead (Pb), cadmium (Cd), zinc (Zn), and copper (Cu), was investigated frequently sold medicinal plants in the markets of Iran. Two medicinal plants, Mentha piperita L., and Zataria multiflora Boiss. were selected from six different herbalists of six districts of Shiraz, Iran. The dissolution of the sample was performed by a conventional wet acid digestion method, and heavy metal levels were determined using Polarograph. Statistical Analysis was used by SPSS.21. According to the achieved results in M.piperita the levels of Zn, Cd, Pb, and Cu were in the range of 2.66 ± 0.76 mg/kg, 0.017 ± 0.009 mg/kg, 0.092 ± 0.069 mg/kg, and 0.237 ± 0.080 mg/kg, respectively. The concentrations of Zn, Cd, Pb, and Cu in Z. multiflora samples were 1.46 ± 0.74 mg/kg, 0.019 ± 0.004 mg/kg, 0.11 ± 0.05 mg/kg, and 0.41 ± 0.17 mg/kg, respectively. There was a correlation between Zn with Cu in our finding (r = 0.9). Based on these results, we found that the concentration of heavy metals in these two medicinal plants was not more than the standard concentration reported for similar plants. It appears that these plants are generally safe in usual doses. The finding of this study can be used to determine standard heavy metals limits in M.piperita and Z.multiflora in future studies.