IL-6 and TNF-alpha proinflammatory cytokine gene polymorphisms could change individual susceptibility to IBS and might have a role in pathophysiology of disease.

Inflammation and mucosal immune system activation have an important role in irritable bowel syndrome (IBS), whereas genetic factors can control some immunological mediators. In this study, a number of polymorphic genes coding for T-helper 1, T-helper 2, and T-regulatory cytokines were genotyped in 71 patients with IBS, and the results were compared with controls. IL-4 CC genotype at position -590, IL-4 TT genotype at position -33, and IL-10 GA genotype at position -1082 were significantly overrepresented in the patients with IBS in comparison with controls (P < 0.001). The frequencies of the following haplotypes in the patient group were significantly higher than in the control group: IL-2 (-330, +160) GT haplotype (P = 0.002), IL-4 (-1098, -590, -33) TCC haplotype (P < 0.001), and TCT haplotype (P < 0.001). While production of cytokines could be affected by genetic polymorphisms within coding and promoter regions of cytokine genes, IL-4 and IL-10 gene polymorphisms could affect individual susceptibility to IBS.

Silymarin, a mixture of flavonolignans, is extracted from milk thistle (Silybum marianum) and has a strong antioxidant activity and exhibits anticarcinogenic, anti-inflammatory, and cytoprotective effects. In this study we attempted to determine whether silymarin and the glutathione modifiers, buthionine sulfoxamine (BSO) and N-acetylcysteine (NAC), are involved in regulation of cyclooxygenase (COX)-2 and inducible nitric oxide synthase (iNOS) in proliferating mesenchymal stem cells (MSCs). Cellular glutathione was manipulated during a 14-day culture using BSO, NAC and silymarin. At intervals of 2, 7 and 14 days, cells were collected and COX-2 and iNOS levels were measured. In parallel, generation of cellular H(2)O(2) and glutathione were measured. Supplementation of the culture media with BSO caused a dose-dependent decrease in MSC proliferation, whereas NAC or silymarin elevated the proliferation (p < 0.05). Treatment of MSC with NAC or silymarin caused a significant decrease in COX-2 levels. However, COX-2 levels in cells treated with high levels of NAC (1.0 mM) were significantly lower than those in MSCs treated with high levels of silymarin (100 μM). BSO (1.0 and 5.0 μM) caused a significant increase in COX-2 on days 2, 7 and 14. BSO caused a significant increase in iNOS, whereas NAC or silymarin decreased cellular iNOS. Overall result show that glutathione, iNOS and COX-2 in proliferating MSCs are affected by silymarin treatment. It appears that glutathione is the main target of silymarin, and in consequence iNOS and COX-2 are affected in response to silymarin treatment.

The aim of the current study was the development of nanosuspension stability in nanoprecipitation using microfluidic devices. Also, it is desirable to understand how the microfluidic preparation parameters influenced the stability of the stable-iodine ( 127 I) nanosuspension. In optimization process through artificial neural networks (ANNs), the relations between input and output variables were investigated for 37 samples obtained by microfluidic nanoprecipitation process. Solvent temperature, antisolvent flow rate, and solvent flow rate were used as input variables, and the sedimentation time and polydispersity index (PDI) were considered as output parameters. Sedimentation time as an indicator of physical stability of nanosuspension was evaluated by observation of a densely packed sediment. Also, size and PDI of different samples were determined by dynamic light scattering. The size of the optimized sample was confirmed by transmission electron microscopy. The result obtained from modeling showed that increasing solvent temperature and antisolvent flow rate led to a decrease in PDI and an increase in the sedimentation time. The antisolvent flow rate was determined as the most important factor that affected the sedimentation time and PDI. Increasing the solvent flow rate was identified as an adverse factor which increased PDI or decreased formulation's sedimentation time. Optimization using ANN showed that microfluidic preparation parameters of nanosuspension as input variables had potential impacts on output parameters.