Background: Benzodiazepines (BZDs), the most commonly prescribed psychotropic drugs with anxiolytic action, may cause hyposalivation. It has been previously shown that BZDs can cause hypertrophy and decrease the acini cell number. In this study, we investigated the effects of BZDs and pilocarpine on rat parotid glands, specifically on acinar, ductal, and myoepithelial cells.Methods: Ninety male Wistar rats were divided into nine groups. Control groups received a saline solution for 30 days (C30) and 60 days (C60), and pilocarpine (PILO) for 60 days. Experimental groups received lorazepam (L30) and midazolam (M30) for 30 days. Another group (LS60 or MS60) received lorazepam or midazolam for 30 days, respectively, and saline for additional 30 days. Finally, other groups (LP60 or MP60) received either lorazepam or midazolam for 30 days, respectively, and pilocarpine for additional 30 days. The expression of calponin in myoepithelial cells and the proliferating cell nuclear antigen (PCNA) in acinar and ductal cells were evaluated.Results: Animals treated with lorazepam showed an increase in the number of positive staining cells for calponin as compared to control animals (p < 0.05). Midazolam administered with pilocarpine (MP60) induced an increase in the proliferation of acinar and ductal cells and a decrease in the positive staining cells for calponin as compared to midazolam administered with saline (MS60).Conclusion: We found that myoepithelial cells might be more sensitive to the effects of BZD than acinar and ductal cells in rat parotid glands.

Benzodiazepines (BZDs), the most commonly prescribed psychotropic drugs with anxiolytic action, may cause hyposalivation. Therefore, this study sought to quantify the acini (N) in parotid glands of Wistar rats treated chronically with two BZDs (Lorazepam and Midazolan) and to verify the action of the pilocarpine when administered with these drugs. Ninety male Wistar rats were distributed in 9 groups according to the administration of: a) S30 - saline solution for 30 days; b) S60 - saline solution for 60 days; c) P60 - pilocarpine for 60 days; d) L30 - Lorazepam for 30 days; e) M30 - Midozolam for 30 days; f) LS60 - Lorazepam for 60 days and, after this period, 30 more days of saline solution; g) MS60 - Midazolam for 30 days and, after this period, 30 more days of saline solution; h) LP60 - Lorazepam and Pilocarpine for 60 days; i) MP60 - Midazolam and Pilocarpine for 60 days. A surgery was performed on the animals to remove the glands. After this, histological cuts were stained by hematoxylin and eosin, from which the N was quantified. The ANOVA and Games-Howell tests were used for statistical analysis. The L30 and M30 groups presented less N than did the S30 group (p<0.05). The LS60, MS60, and LP60 groups presented less N than did the S60 and P60 groups (p<0.05). No differences could be observed between the MP60 and S60 groups. The chronic administration of Midazolam and Lorazepam reduced acini, which may well have collaborated in the reduction of salivary flow previously verified. The association of Midazolam with Pilocarpine led to the reestablishment of acinar cells, which may have favored the restoration of the salivary flow formerly shown.

Background: The gerontoism, a neologism adopted here, is a form of discrimination regarding age and can occur in rational, emotional, and behavioral contexts, and could be influenced by many factors. This study aimed to identify if the social support and the family functionality interfere in the self-perception of gerontoism. Methods: Participants were 376 elderly in good physical and mental condition. They participated in the Group Living organization in the Municipality of Curitiba, State of Paraná, Brazil, in 2012.  Information was collected about sociodemographic profile using a structured questionnaire. The social support, the family functionality, and the self-perception of gerontoism were defined by the Medical Outcomes Study, the Family APGAR index, and Ageism Survey, respectively. The variables were analyzed by Pearson’s correlation coefficient, One Way ANOVA, Tukey’s HSD test, and the Student’s t-test. Results: Most of the participants came from small cities from the interior (48.7%), were female (94.4%), with age ranging 60-69 yr-old (45.5%), whites (76.1%), widowers (47.1%), with children (93.9%), with low schooling (55.3%), with family income from 1-2 minimum wage (31.4%), and retirees not working (44.1%). It was not observed correlation between sociodemographic variables and self-perception of gerontoism. Statistical significance was observed between self-perception of gerontoism and social support (r= -0.26, P=0.00), and between the self-perception and family functionality (r = -0.28, P=0.00). Once the scores of self-perception of gerontoism increased, the ones from social support and family functionality, decreased. Conclusion: Lower self-perception of gerontoism was observed in elderly with higher social support and family functionality.

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Smoking is a leading cause of preventable death. The effect of tobacco is even more contundent in people with mental illness and, in general, cigarette smoking addiction is influenced by genetic factors. The opioid system is involved in the mesolimbic reward system, which is of great importance in addictive behaviors, such as smoking and is influenced by genes such as the OPRM1 . The aim of this study was to evaluate if selecting a comparison group that include light smokers versus people that never smoked impacts the results of genetic association studies. In addition, to evaluate the genetic association in different groups of smokers by analyzing independent covariates such as mental illness and clinical dental data. All subjects were participants of the Dental Registry and DNA Repository project. Genotyping was carried out using TaqMan chemistry for two markers in OPRM1 (rs553202 and rs7755635). Logistic regression analyses were performed as implemented in PLINK. The established value for alpha was 5%, and the Hardy-Weinberg equilibrium was evaluated by the chi-square test with one degree of freedom for each marker. 1,897 patients were included, which were allocated to eight distinct groups, according to the frequency and quantity of cigarettes smoked and mental illness status. There was no significant association between the two markers in OPRM1 and smoking. When mental illness and dental clinical data (tooth loss, dental caries, and periodontitis) were used as covariates, there were associations between heavy smoking and OPRM1 , when non-smokers were used as comparison. We did not have diet or microbiome data to consider for these dental analyses and suggest that these kinds of data should be always incorporated in the future. Significant results were found only when the covariables mental illness and oral clinical data were added to the analysis.