Effect of Melatonin Administration on Sleep Quality in Sulfur Mustard Exposed Patients with Sleep Disorders.

Sulfur mustard (SM) is a toxic agent that targets several tissues. It is the leading cause of persistent lung disease, progressive deterioration in lung function, and mortality among injured patients. Disturbed sleep and poor quality of sleep are common in SM-exposed patients with chronic respiratory problems. Melatonin is an alternative medication that has been widely used to treat poor sleep quality caused by several specific conditions. This study aimed to evaluate the efficacy of melatonin administration in improvement of sleep quality in SM-injured patients. In this randomized, double-blind and placebo-controlled trial study a total of 30 SM-exposed male patients were recruited. Patients received 3 mg melatonin (N = 15) or placebo (N = 15), orally in a single dose, 1 h before bedtime for 56 consecutive days. Sleep quality was evaluated by Pittsburgh Sleep Quality Index (PSQI); daytime sleepiness was measured by Epworth Sleepiness Scale (ESS), and the risk of obstructive sleep apnea was determined by STOP-Bang questionnaire. Compared with placebo, melatonin administration significantly improved global PSQI score, particularly sleep latency (P = 0.03) and subjective sleep quality (P = 0.004). Mean of global PSQI score was declined significantly (P = 0.01) from 10.13 ± 3.44 to 6.66 ± 3.08 in melatonin group. No differences in ESS and STOP-Bang scores were observed between two groups. Melatonin was effective in improving global PSQI score and sleep latency, but not daytime sleepiness and obstructive sleep apnea in SM-exposed patients. Further long-term studies involving larger number of patients are needed before melatonin can be safely recommended for the management of sleep disturbances in these patients.

Nocturnal serum melatonin levels in sulfur mustard exposed patients with sleep disorders.

BACKGROUND: Sulfur mustard (SM) exposure causes respiratory disorders, progressive deterioration in lung function and mortality in injured victims and poor sleep quality is one of the most common problems among SM-exposed patients. Since melatonin has a critical role in regulation of sleep and awareness, this study aimed to evaluate the serum melatonin levels in SM-injured subjects. METHODS: A total of 30 SM-exposed male patients and 10 controls was evaluated. Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI); daytime sleepiness was measured by the Epworth Sleepiness Scale (ESS), and the risk of obstructive sleep apnoea was determined by the STOP-Bang questionnaire. Polysomnography (PSG) and pulmonary function tests (PFTs) were also available. Nocturnal serum melatonin levels were measured using an ELISA kit. RESULTS: The mean of PSQI, ESS and STOP-Bang scores in patients (11.76±3.56, 12.6±3.03 and 5.03±1.09, respectively) were significantly (p<0.01) higher than those in the controls (2.78±0.83, 4.69±1.15 and 1.18±0.82, respectively). PFTs also showed declined respiratory quality in SM-patients. There was a significant difference regarding the PSG results between patients and controls (p<0.01). The mean of nocturnal serum melatonin levels in patients (29.78±19.31 pg/mL) was significantly (p=0.005) lower than that in the controls (78.53±34.41 pg/mL). CONCLUSIONS: Reduced nocturnal serum melatonin and respiratory disorders can be the reasons for poor sleep quality among these patients. TRIAL REGISTRATION NUMBER: IRCT2015092924267N1, Pre-results.

The cell cycle arrest and the anti-invasive effects of nitrogen-containing bisphosphonates are not mediated by DBF4 in breast cancer cells.

Recent work has shown that a DBF4 analog in yeast may be a target of nitrogen-containing bisphosphonates. DBF4 is an essential protein kinase required for DNA replication from primary eukaryotes to humans and appears to play a critical role in the S-phase checkpoint. It is also required for cell migration and cell surface adhesion. The effects of Pamidronate, risedronate, or zoledronate on cell viability and DBF4 expression were measured via MTT assays and western blotting. In addition, FACS cell cycle analyses and invasion assays were conducted in cells in the presence of nitrogen-containing bisphosphonates to identify any correlations between DBF4 expression and S-phase arrest or anti-invasive effects of the bisphosphonates. Zoledronate transiently down-regulated DBF4 expression in all three cell lines in the first 24 h of the experiment, but after 72 h, DBF4 expression returned to the control levels in all treated cells. Following treatment of the tumor cells with the bisphosphonates, the number of cells in S-phase was increased. Pamidronate and zoledronate showed anti-invasive effects in BT20 cells. The anti-invasive effects of pamidronate, risedronate and zoledronate appeared after 48 h of exposure. In MDA-MB231 cells a reduction of invasiveness was only observed after 72 h of the pamidronate exposure. We finally concluded that the anti-invasive and cell cycle arrest-inducing effects of nitrogen-containing bisphosphonates are not DBF4 mediated, and other mediators are therefore needed to explain the observed complex behaviors.

Modeling of thermodynamic and physico-chemical properties of coumarins bioactivity against Candida albicans using a Levenberg-Marquardt neural network.

In recent years, due to vital need for novel fungicidal agents, investigation on natural antifungal resources has been increased. The special features exhibited by neural network classifiers make them suitable for handling complex problems like analyzing different properties of candidate compounds in computer-aided drug design. In this study, by using a Levenberg-Marquardt (LM) neural network (the fastest of the training algorithms), the relation between some important thermodynamic and physico-chemical properties of coumarin compounds and their biological activities (tested against Candida albicans) has been evaluated. A set of already reported antifungal bioactive coumarin and some well-known physical descriptors have been selected and using LM training algorithm the best architecture of neural model has been designed for forecasting the new bioactive compounds.