Effects of pioglitazone on survival and omental adipocyte function in mice with sepsis induced by cecal ligation and puncture.

BACKGROUND: To examine the effects of pioglitazone, peroxisome proliferator-activated receptor-gamma (PPAR-γ), on mortality and omental adipocyte function in mice with cecal ligation and puncture (CLP). METHODS: Male mice were assigned to receive (1) vehicle/sham-operation, (2) pioglitazone/CLP, or (3) vehicle/CLP. Pioglitazone was injected intraperitoneally for 7 d before operation. Serum and omental tissue were collected before, 24, and 48 h after CLP. Serum levels of adiponectin, cytokine, and chemokine were measured with ELISA. mRNA expressions in omental tissues were determined by RT-PCR. Survival was monitored for 7 d after CLP. RESULTS: Survival after CLP was significantly better in the pioglitazone/CLP than in the vehicle/CLP. Serum adiponectin levels before CLP were higher in the pioglitazone/CLP than in the vehicle/CLP. Treatment with pioglitazone significantly inhibited the increases in the serum interleukin-6 and monocyte chemoattractant protein-1 (MCP-1) levels after CLP and lowered the mRNA expressions of proinflammatory cytokines, interleukin-6, and MCP-1 in omental tissue after CLP. CONCLUSION: The anti-inflammatory effects of pioglitazone on omental adipocyte function appear to be mediated in part by PPAR-γ activation, which down-regulates the production of inflammatory mediators.

Automated extraction of lymph nodes from 3-D abdominal CT images using 3-D minimum directional difference filter.

This paper presents a method for extracting lymph node regions from 3-D abdominal CT images using 3-D minimum directional difference filter. In the case of surgery of colonic cancer, resection of metastasis lesions is performed with resection of a primary lesion. Lymph nodes are main route of metastasis and are quite important for deciding resection area. Diagnosis of enlarged lymph nodes is quite important process for surgical planning. However, manual detection of enlarged lymph nodes on CT images is quite burden task. Thus, development of lymph node detection process is very helpful for assisting such surgical planning task. Although there are several report that present lymph node detection, these methods detect lymph nodes primary from PET images or detect in 2-D image processing way. There is no method that detects lymph nodes directly from 3-D images. The purpose of this paper is to show an automated method for detecting lymph nodes from 3-D abdominal CT images. This method employs a 3-D minimum directional difference filter for enhancing blob structures with suppressing line structures. After that, false positive regions caused by residua and vein are eliminated using several kinds of information such as size, blood vessels, air in the colon. We applied the proposed method to three cases of 3-D abdominal CT images. The experimental results showed that the proposed method could detect 57.0% of enlarged lymph nodes with 58 FPs per case.