Theophylline attenuates bleomycin-induced oxidative stress in rats: The role of IL-6, NF-κB, and antioxidant enzymes

Abstract The purpose of this study was to evaluate the antifibrotic and antioxidant roles of theophylline (Theo), a bioactive compound, in bleomycin (BLM)-induced pulmonary fibrosis in Wistar albino rats. Assigned into 4 groups were 32 Wistar albino rats, comprising the control group (administered 0.9% isotonic saline), BLM group (treated with BLM at a dose of 2.5 mg/kg), BLM+Theo group (treated with Theo at a dose of 75 mg/kg + BLM at a dose of 2.5 mg/kg), and Theo group (treated with Theo at a dose of 75 mg/kg). In the BLM group, a significant decrease was observed in the catalase and glutathione peroxidase enzyme activities, and reduced glutathione (GSH) (p < 0.05, p< 0.05, p< 0.001, respectively), while the malondialdehyde (MDA) levels (p< 0.001) were significantly elevated when compared to the control group. However, the MDA levels in the BLM+Theo group were also significantly higher than in the control group (p< 0.01). Similarly, the GSH levels were significantly higher in the BLM+Theo group than in the BLM group (p< 0.05). The results indicated that Theo reduced the BLM-induced activation of nuclear factor-kappaB (NF-κB) and decreased interleukin-6 (IL-6) levels, together with significant amelioration of the immunohistochemical and histopathological architecture in the lung tissues. It was concluded that the administration of Theo had a positive effect on the GSH level, and activation of NF-κB and IL-6 expression, which were significant proinflammatory markers in the BLM-treated rats.

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the overall accuracy of existing systems, the effects of DL model properties and parameters on the performance are hard to interpret. This makes comparative analysis a necessary tool towards interpretable studies and systems. Moreover, the performance of DL for emerging learning approaches such as cross-modality and multi-modal semantic segmentation tasks has been rarely discussed. In order to expand the knowledge on these topics, the CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation challenge was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI), 2019, in Venice, Italy. Abdominal organ segmentation from routine acquisitions plays an important role in several clinical applications, such as pre-surgical planning or morphological and volumetric follow-ups for various diseases. These applications require a certain level of performance on a diverse set of metrics such as maximum symmetric surface distance (MSSD) to determine surgical error-margin or overlap errors for tracking size and shape differences. Previous abdomen related challenges are mainly focused on tumor/lesion detection and/or classification with a single modality. Conversely, CHAOS provides both abdominal CT and MR data from healthy subjects for single and multiple abdominal organ segmentation. Five different but complementary tasks were designed to analyze the capabilities of participating approaches from multiple perspectives. The results were investigated thoroughly, compared with manual annotations and interactive methods. The analysis shows that the performance of DL models for single modality (CT / MR) can show reliable volumetric analysis performance (DICE: 0.98 ± 0.00 / 0.95 ± 0.01), but the best MSSD performance remains limited (21.89 ± 13.94 / 20.85 ± 10.63 mm). The performances of participating models decrease dramatically for cross-modality tasks both for the liver (DICE: 0.88 ± 0.15 MSSD: 36.33 ± 21.97 mm). Despite contrary examples on different applications, multi-tasking DL models designed to segment all organs are observed to perform worse compared to organ-specific ones (performance drop around 5%). Nevertheless, some of the successful models show better performance with their multi-organ versions. We conclude that the exploration of those pros and cons in both single vs multi-organ and cross-modality segmentations is poised to have an impact on further research for developing effective algorithms that would support real-world clinical applications. Finally, having more than 1500 participants and receiving more than 550 submissions, another important contribution of this study is the analysis on shortcomings of challenge organizations such as the effects of multiple submissions and peeking phenomenon.

Variations in fatty acid compositions of the seed oil of Eruca sativa Mill. caused by different sowing periods and nitrogen forms.

BACKGROUND: Eruca is a native plant genus of the South Europe and central Asia where it has been cultivated since centuries. As the genus name implies, the oil is high in erucic acid. MATERIALS AND METHODS: In this study, our aim was to investigate the effect of sowing periods (autumn and spring) and three forms of the nitrogen-containing fertilizers (manure, calcium nitrate [Ca(NO(3))(2), 15.5% N], and ammonium sulphate [(NH(4))(2)SO(4), 21% N]) on fatty acid compositions of the oils obtained from Eruca sativa Mill. seeds cultivated. All oils were obtained by maceration of the seeds with n-hexane at room temperature and converted to their methyl ester derivatives by trans-methylesterification reaction using boron-trifluorur (BF(3)). The fatty acid methyl esters (FAMEs) in the oils were detected by capillary gas chromatography-mass spectrometry (GC-MS). RESULTS: All the samples analyzed were found to contain quite high amounts of erucic acid ranging between 46.64-54.79%, followed by oleic (17.86-19.95%), palmitic (7.25-10.97%), linoleic (4.23-9.72%), and linolenic (1.98-3.01%) acids. CONCLUSION: Our data pointed out that there is a statistically important alteration caused by these applications on the contents of only C12:0 and C14:0 found as the minor fatty acids, whereas no other fatty acids in the samples seemed to be affected by those criteria.

Fatty acid composition of seed oil of different Sorghum bicolor varieties.

In order to find out new sources of premium quality edible oil in the country, seeds of ten varieties of Sorghum bicolor were initially analyzed for their total oil contents. The seed oil was later fractionated into eight fatty acids including two new saturated fatty acids. The oil contents were determined by Soxhlet method and compared with the results obtained by NMR analysis. The total oil contents in the seeds of sorghum ranged from 5.0 to 8.2 % (w/w), indicating non significant difference obtained by two different techniques. The results revealed that oleic acid (31.12-48.99%), Palmitoleic acid (0.43-0.56%), linoleic acids (27.59-50.73%), linolenic acid (1.71-3.89%), stearic acid (1.09-2.59%) and palmitic acid (11.73-20.18%) was present in the seed oil of different sorghum varieties when analyzed by GC-MS. It was observed that in most of the varieties polyunsaturated fatty acids (PUFA) were higher than monounsaturated fatty acids (MUFA). The two atypical SFAs, octanedioic (C8:0) and azelaic acid (C9:0) were found in some varieties. These results suggest that these S. bicolor varieties could be additional sources of edible oil due to presence of clinically important saturated and high concentration of unsaturated fatty acids. A large scale production of the seed oil after refining process can contribute towards alleviation of edible oil shortage in the country with increased use of premium quality oil.