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Melatonin has emerged as an anti-inflammatory agent, potent direct free-radical scavenger, and an indirect antioxidant in preventing ischemia-reperfusion injury. This study aimed to evaluate melatonin's effect on cardiac biomarkers after coronary artery bypass grafting (CABG).A double-blind, randomized placebo-controlled pilot clinical study.Booali Sina Hospital, Qazvin University of Medical Sciences, Qazvin, Iran.One hundred patients undergoing elective CABG. The patients were divided randomly into control (C) and melatonin (M) groups (50 patients per group).The M group received 3 mg of melatonin the night before surgery, 3 mg in the morning, and routine cardiac surgery medications. The C group received 1 placebo tablet rather than melatonin. After surgery, the patients in the M group received 3 mg of melatonin, and the C group received 1 placebo tablet at bedtime until the third day after CABG.In both groups, creatine kinase-MB (CPK-MB), cardiac troponin I, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) were measured before surgery and on the first, second, and third postoperative days. Serum CPK-MB levels on the second and third day after CABG were significantly lower in the M group than in the C group (p0.05). Regarding cardiac troponin I, CRP, and ESR markers, there were no significant changes in serum concentration before surgery and on the first, second, and third days after surgery between the 2 groups (p0.05). The mean length of hospitalization in the ICU was lower in the M group (3.4 ± 1.05) compared with the C group (3.96 ± 1.06, p = 0.01).Melatonin reduced the postoperative level of CPK-MB and the length of hospitalization in the ICU in patients who underwent cardiac surgery.

The aim of current study is to tailor chitosan derivate which is water-soluble while presents original biological features of chitosan. For this purpose, the 6-O chitosan sulfate (CS) with naked amine groups was synthesized via regioselective modification of chitosan (C) during which both crosslinking capacity and antibacterial properties of the C were remained intact. This was achieved by sulfation the C under controlled acidic conditions using chlorosulfonic acid/sulfuric acid mixture. Subsequently, a chemically crosslinked hydrogel of the CS was used as a wound dressing substrate. The modified sulfate groups retained the biocompatibility of C and showed antibacterial effects against gram-positive and gram-negative bacteria. In addition, the presence of sulfate groups in the CS chemical structure improved its anticoagulant activity compared to the unmodified C. Both in vitro and in vivo enzyme-linked immunosorbent assay (ELISA) measurements showed that CS had a higher potential to bind and scavenger anti-inflammatory cytokines, including IL-6 and transforming growth factor-β (TGF-β), both of which play critical roles in the early stage of the wound healing process. After treatment of full-thickness wounds with CS hydrogels, the macrophage cells (c.a. 6 × 10

Background: Colorectal cancer (CRC) is among the most common and preventable cancers, the incidence and risk factors of which are different in various populations. Objectives: The present study aims at assessing incidence rate, risk factors, and symptoms of CRC among the populations aged 50 to 70 years old covered by the health centers in Arak, as well as evaluating participation rate in the CRC screening program. Methods: The present cross-sectional study was conducted from 2016 to 2019 among all of the individuals aged 50 to 70 years old, who were referred to rural, urban, and suburban health centers in Arak for CRC screening, and their data were recorded in the Sib system. The participation rate, risk factors (family and individual history of CRC, colorectal adenoma, and inflammatory bowel disease), symptoms (lower gastrointestinal bleeding, constipation with or without diarrhea, and weight loss), and crude incidence rate of CRC were calculated in the age range. Results: The mean (SD) age of the CRC was 59.72 (5.56) years. In addition, the individuals’ participation rate in the program was about 44.2%, which was more among women (55.5%) and villagers (93.7%). Most subjects complained of constipation in the last month and CRC family history. The CRC crude incidence rates were 35.93 (95% CI: 25.55 - 50.54), 40.96 (95% CI: 29.81 - 56.29), 43.76 (95% CI: 32.22 - 59.43), and 52.84 (95% CI: 40.05 - 69.71) per 100000 individuals during 2016, 2017, 2018, and 2019, respectively. Conclusions: The participation rate in the CRC screening program was low, and the trend of the cancer crude incidence rate increased among the populations aged 50 to 70 years. Finally, informing about the recognition of the risk factors and symptoms of cancer, as well as the timely referral for screening was considered essential.

Alginate as a naturally-derived biomaterial with marine algae sources has gained much attention in both laboratorial and industrial applications due to its structural and chemical resemblance to extracellular matrix (ECM) as well as desirable properties like biocompatibility, biodegradability, processability and low cost. Electrospun alginate nanofibrous scaffolds have found wide applications in biomedical field such as tissue engineering, biomedicine and drug delivery systems. However, electrospinning of alginate is challenging due to the low solubility and high viscosity of high molecular weight alginate, high density of intra- and intermolecular hydrogen bonding, polyelectrolyte nature of aqueous solution and lack of appropriate organic solvent. The aim of this review is to summarize the challenges and obstacles in alginate electrospinning reported in the literature as well as the introduced solutions for them, in order to open new opportunities for more intended and successful investigations in the field.

In this study a method for hand gesture recognition using dynamic Bayesian networks was presented. This study includes two main subdivisions namely: hand posture recognition and dynamic hand gesture recognition (without hand posture recognition). In the first session, after hand segmentation using a method based on histogram of direction and fuzzy SVM classifier, we train the posture recognition system. In the second session, after skin detection and face and hands segmentation, their tracing were carried out by means of Kalman filter. Then, by tracing the obtained data, the positions of hand was achieved. For combining the achieved data and output of hand posture recognition unit we utilize Bayesian dynamic network. For recognition of 12 hand gestures in this study, 12 Bayesian dynamic networks with two distinct designs were used. The difference between these two models is in the utilizing features and their relations with each other. Therefore, one of these models was used based on each gesture feature. The results of implementation show the about 90% average accuracy for all gestures.