The optimal starting time of postoperative intraperitoneal mitomycin-C therapy with preserved intestinal wound healing

BACKGROUND: There is controversy about the effect of the timing of intraperitoneal administration of chemotherapeutic agents on the healing of intestinal anastomosis. We have investigated the effect on intestinal wound healing of mitomycin-C administered at different times post-operatively. METHODS: Eighty-four Wistar-Albino female rats underwent ileal resection and end-to-end anastomosis. The rats were randomly selected for intraperitoneal administration of mitomycin-C or saline as follows: mitomycin-C group (n = 65), 2 mg/kg mitomycin-C; control group (n = 13), 10 ml saline. The former was sub-divided into 5 equal groups (A 1–5) and mitomycin-C was administered postoperatively as follows: day 0 (A1), day 3 (A2), day 5 (A3), day 7 (A4) and day 10 (A5). All the rats were sacrificed on the 14th postoperative day and anastomotic bursting pressures and tissue hydroxyproline levels were determined. RESULTS: Five of the animals died postoperatively: 2 (15.4%) in group A1, 2 (15.4%) in group A2 and 1(7.7%) in group A3. Non-lethal anastomotic leakage was observed in a further five animals: 1 in group A1, 2 in group A2, 1 in group A5 and 1 in the control group. Groups A1 and A2 had significantly lower anastomotic bursting pressures than the other groups (P was <0.05 for each comparison). The anastomotic bursting pressures of group A3, A4 and A5 were comparable with those of the controls (P was >0.05 for each comparison). Tissue hydroxyproline levels in group A1 and A2 were significantly lower than in the controls (P values were <0.05 for each comparison) or the other mitomycin-C sub-groups (P was <0.05 for each comparison). CONCLUSIONS: Intraperitoneal chemotherapy impairs intestinal wound healing when applied before the 5th postoperative day. Additional therapeutic approaches are needed to prevent this potentially lethal side effect of early intraperitoneal mitomycin-C administration

Gene selection for classification of microarray data based on the Bayes error

<p>Abstract</p> <p>Background</p> <p>With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, e.g., disease diagnosis. Several widely used gene selection methods often select top-ranked genes according to their individual discriminative power in classifying samples into distinct categories, without considering correlations among genes. A limitation of these gene selection methods is that they may result in gene sets with some redundancy and yield an unnecessary large number of candidate genes for classification analyses. Some latest studies show that incorporating gene to gene correlations into gene selection can remove redundant genes and improve classification accuracy.</p> <p>Results</p> <p>In this study, we propose a new method, Based Bayes error Filter (BBF), to select relevant genes and remove redundant genes in classification analyses of microarray data. The effectiveness and accuracy of this method is demonstrated through analyses of five publicly available microarray datasets. The results show that our gene selection method is capable of achieving better accuracies than previous studies, while being able to effectively select relevant genes, remove redundant genes and obtain efficient and small gene sets for sample classification purposes.</p> <p>Conclusion</p> <p>The proposed method can effectively identify a compact set of genes with high classification accuracy. This study also indicates that application of the Bayes error is a feasible and effective wayfor removing redundant genes in gene selection.</p

Ameliorative potential of Lavandula stoechas in metabolic syndrome via multitarget interactions.

ETHNOPHARMACOLOGICAL IMPORTANCE: Decoction and infusion prepared from aerial parts of Lavandula stoechas L. (L. stoechas) have been traditionally used as remedy against several components of metabolic syndrome (MetS) and associated disorders including type II diabetes and cardiovascular diseases by Anatolian people. AIM OF THE STUDY: The aim is to elucidate the potential ameliorative effects of L. stoechas aqueous extracts on insulin resistance and inflammation models through multitarget in vitro approaches and also to elucidate mechanism of action by analyzing transcriptional and metabolic responses. MATERIALS AND METHODS: An aqueous extract was prepared and fractionated to give rise to ethyl acetate (EE) and butanol (BE) extracts. The anti-insulin resistance effects of BE and EE were evaluated on palmitate induced insulin resistance model of H4IIE, C2C12 and 3T3L1 cells by using several metabolic parameters. Specifically, whole genome transcriptome analysis was performed by using microarray over 55.000 genes in control, insulin resistant and EE (25 µg/mL) treated insulin resistant H4IIE cells. Anti-inflammatory effects of both extracts were analyzed in LPS-stimulated RAW264.7 macrophages. RESULTS: Both EE and BE at low doses (25-50 µg/mL) significantly decreased hepatic gluconeogenesis in H4IIE cell line by suppressing the expression of PEPCK and G6Pase. In C2C12 myotubes, both extracts increased the insulin stimulated glucose uptake more effectively than metformin. Both extracts decreased the isoproterenol induced lipolysis in 3T3L1 cell line. Moreover, they also effectively increased the expression of lipoprotein lipase protein level in insulin resistant myotubes at low doses. EE increased the protein level of PPARγ and stimulated the activation AKT in insulin resistant H4IIE and C2C12 cell lines. The results obtained from biochemical assays, mRNA/protein studies and whole genome transcriptome analyses were found to be complementary and provided support for the hypothesis that EE might be biologically active against insulin resistance and act through the inhibition of liver gluconeogenesis and AKT activation. Besides, LPS induced inflammation in RAW264.7 macrophages was mainly inhibited by EE through suppression of iNOS/NO signaling, IL1β and COX-2 genes. HPLC-TOF/MS analysis of EE of L. stoechas mainly resulted in caffeic acid, apigenin, luteolin, rosmarinic acid and its methyl ester, 4-hydroxybenzoic acid, vanillic acid, ferrulic acid and salicylic acid. CONCLUSION: Data suggest that EE of L. stoechas contains phytochemicals that can be effective in the treatment/prevention of insulin resistance and inflammation. These results validate the traditional use of L. stoechas in Anatolia against several metabolic disorders including metabolic syndrome