Botulinum toxin blocks mast cells and prevents rosacea like inflammation

Background

Rosacea is a chronic inflammatory skin condition whose etiology has been linked to mast cells and the antimicrobial peptide cathelicidin LL-37. Individuals with refractory disease have demonstrated clinical benefit with periodic injections of onabotulinum toxin, but the mechanism of action is unknown.

Pinealectomy interferes with the circadian clock genes expression in white adipose tissue

Melatonin, the main hormone produced by the pineal gland, is secreted in a circadian manner (24‐hr period), and its oscillation influences several circadian biological rhythms, such as the regulation of clock genes expression (chronobiotic effect) and the modulation of several endocrine functions in peripheral tissues. Assuming that the circadian synchronization of clock genes can play a role in the regulation of energy metabolism and it is influenced by melatonin, our study was designed to assess possible alterations as a consequence of melatonin absence on the circadian expression of clock genes in the epididymal adipose tissue of male Wistar rats and the possible metabolic repercussions to this tissue. Our data show that pinealectomy indeed has impacts on molecular events: it abolishes the daily pattern of the expression of Clock, Per2, and Cry1 clock genes and Pparγ expression, significantly increases the amplitude of daily expression of Rev‐erbα, and affects the pattern of and impairs adipokine production, leading to a decrease in leptin levels. However, regarding some metabolic aspects of adipocyte functions, such as its ability to synthesize triacylglycerols from glucose along 24 hr, was not compromised by pinealectomy, although the daily profile of the lipogenic enzymes expression (ATP‐citrate lyase, malic enzyme, fatty acid synthase, and glucose‐6‐phosphate dehydrogenase) was abolished in pinealectomized animals.     

Ospemifene plus fractional CO2 laser: a powerful strategy to treat postmenopausal vulvar pain

Abstract

This study is a single-center, retrospective analysis of postmenopausal women presenting with dyspareunia and vulvar pain, aiming to evaluate relative effectiveness of vestibular CO₂ laser therapy as a treatment. Three monthly sessions of laser were performed to each patient and thereafter a three-months follow-up was stablished. A total number of 72 patients undergoing vestibular laser treatment were recruited from patient files in the period between 2016 and 2018. Among these, 39 women also received a concomitant treatment with ospemifene (60?mg/day) during the study period. There was a statistically significant reduction of all the symptoms in both groups up to the three month follow-up. Regarding dryness and dyspareunia, the relief tent to be more prominent in the ospemifene?+?laser group at all follow-ups and remained statistically significant at three-month follow-up. Specifically, vestibular dryness was significantly lower in the ospemifene?+?laser group compared with the laser treatment group (?87% vs???34%, respectively), and the vestibular health score started declining faster in the ospemifene?+?laser group. Although, additional research is needed to understand the mechanism of action, our data shows that a combination regimen of laser and ospemifene may improve clinical effectiveness for long-term treatment of symptoms associated with the under-recognized genitourinary syndrome of menopause.     

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.