Sulphur mustard (SM) is an alkylating chemical warfare agent that was widely used during the World War I and in the Iran-Iraq conflict. Delayed complications of SM in different organs and their severity correlations have not previously been reported. Dermatological, ophthalmological, neurological and respiratory examinations, as well as spirometry, gasometry, high resolution computed tomography scanning of the chest, electromyography, nerve conduction velocity, cell blood counts, flow-cytometric analyses, and measurement of serum immunoglobulins and complement factors were performed on all severely SM poisoned veterans in the province of Khorasan, Iran. Haematological and immunological studies were also performed on a control group consisting of 35 healthy male subjects. The severity of dermal, ocular and respiratory complications were classified into four grades and their correlations with each other as well as with the haematological and immunological parameters were determined, using Spearman's rank correlation test. Forty male patients (aged 43.8 +/- 9.8 years) with confirmed SM poisoning 16-20 years after the exposure were studied. The most common complications were found in the lungs (95%), peripheral nerves (77.5%), skin (75%), and eyes (65%). WBC, RBC, haematocrit (HCT), IgM, C3, and the percentages of monocytes and CD3+ lymphocytes were significantly (P < 0.042) higher and the percentage of CD16 + 56 positive cells was significantly (P = 0.006) lower in the patients than in the control group. The severity of respiratory complications revealed a significant correlation with the severity of ocular complications (r = 0.322, P = 0.043), as well as with the haemoglobin (r = 0.369, P = 0.024) and HCT (r = 0.470, P =0.003). Although late complications of SM poisoning in the skin, eyes, and respiratory system are mainly due to its direct toxic effects, the neuromuscular, haematological and immunological complications are probably the result of systemic toxicity.

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Synopsis The objective of this study was to determine the influence of vehicles on the penetration of octyl methoxycinnamate (OMC), as a UV absorber, to the stratum corneum by the stripping method. The experimental formulations consisted of a conventional o/w emulsion and multilamellar and small unilamellar liposomes (MLVs and SUVs) containing OMC. MLVs containing OMC were prepared by the fusion method and then converted to SUVs by probe sonication. Various formulations were then applied onto the midvolar forearms of six volunteers at a dose of 2 mg cm‐2. After determined timepoints, the stripping method was conducted whereby 22 tape strips were applied and subsequently divided into different stripping groups. The sunscreen agent was assessed by HPLC while the SPF (sun protection factor) of the formulations was determined in human volunteers in accordance with the Australian standard. Overall the results indicate that skin accumulation of OMC in MLVs was significantly greater than in the o/w emulsion and SUVs. Furthermore, SUV's penetration into the deeper skin layers was significantly greater than MLV's and that of a conventional o/w emulsion. Also, higher amounts of OMC were recovered from the upper layers of the stratum corneum than from the deeper layers in all the formulations tested. Finally, the SPF of the liposomes containing OMC was slightly greater than that of the control lotions at a similar concentration of OMC. In conclusion, the result of this study indicates that an MLV prepared by the fusion method could be a better vehicle for OMC as a sunscreen since it has a slightly better SPF compared to a conventional formulation and more remains in the stratum corneum, reducing its penetration to the deeper layers. Address all correspondence to M. R. Jaafari.

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Background Cystic fibrosis (CF) is a genetic disorder, which is caused by the CFTR protein defects. Along with CFTR dysfunction, inflammation plays a key role in the disease outcomes. Inflammation may develop due to the internal dysfunction of the CFTR protein or external factors. Curcumin affects the CFTR protein function primarily as a corrector and potentiator and secondary as an anti-inflammatory and antimicrobial agent. The present study aims to assess the impact of nano-curcumin on clinical and inflammatory markers in children with CF. Methods This prospective, double blind control trial will be conducted at the Akbar Children’s Hospital in Mashhad, Iran. Children with CF will be enrolled based on the eligibility criteria. Placebo and curcumin with the maximum dose of 80 mg considering the body surface of the patients will be administrated for 3 months. The primary outcome is to evaluate inflammation based on serum interleukin-6, interleukin-10, and hs-CRP, stool calprotectin, and neutrophil count of nasopharyngeal swab. The secondary outcome involved clinical assessment via spirometry, anthropometrics, and quality of life. They will be assessed before and after 3 months. Discussion Due to the multifarious effects of curcumin on CF disease, it could be proposed as a nutritional strategy in the treatment of cystic fibrosis. Trial registration Iranian Registry of Clinical Trials IRCT20200705048018N1. Registered on July 10, 2020.

The Zagros forests in Western Iran are valuable ecosystems that have been seriously damaged by human interference (harvesting the wood and forest sub-products, converting the forests to the agricultural lands, and grazing) and natural events (drought events and fire). In this study, we generated accurate land cover (LC), and tree canopy cover percentage (TCC%) maps for the forests of Shirvan County, a part of Zagros forests in Western Iran using Sentinel-2, Google Earth, and field data for protective management. First, we assessed the accuracy of Google Earth data using 300 random field plots in 10 different land cover types. For land cover mapping, we evaluated the performance of four supervised classification algorithms (minimum distance (MD), Mahalanobis distance (MaD), neural network (NN), and support vector machine (SVM)). The accuracy of the land cover maps was assessed using a set of 150 stratified random plots in Google Earth. We mapped the forest canopy cover by using the normalized difference vegetation index (NDVI) map, and field plots. We calculated the Pearson correlation between the NDVI values and the TCC% (obtained from field plots). The linear regression between the NDVI values and the TCC% was used to obtain the predictive model of TCC% based on the NDVI. The results showed that Google Earth data yielded an overall accuracy of 94.4%. The SVM algorithm had the highest accuracy for the classification of Sentinel-2 data with an overall accuracy of 81.33% and a kappa index of 0.76. The results of the forest canopy cover analysis showed a Pearson correlation coefficient of 0.93 between the NDVI and TCC%, which is highly significant. The results also showed that the linear regression model is a good predictive model for TCC% estimation based on the NDVI (r2 = 0.864). The results can be used as a baseline for decision-makers to monitor land cover change in the region, whether produced by human activities or natural events and to establish measures for protective management of forests.

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