Cystic dystrophy in heterotopic pancreas.

Cystic dystrophy in heterotopic pancreas, or paraduodenal pancreatitis, is a rare and complicated presentation involving heterotopic pancreatic tissue in the duodenal wall. This condition is present in 5% of the general population but disease mainly affects middle-aged alcoholic-smoking men with chronic pancreatitis (CP). It may be purely duodenal or segmental (pancreatico-duodenopathy). Its pathophysiology arises from alcohol toxicity with obstruction of small ducts of heterotopic pancreatic tissue present in the duodenal wall and the pancreatic-duodenal sulcus, leading to repeated episodes of pancreatitis. The symptomatology includes episodes of acute pancreatitis, weight loss, and vomiting due to duodenal obstruction. Imaging shows thickening of the wall of the second portion of the duodenum with multiple small cysts. A stepwise therapeutic approach is preferred. Conservative medical treatment is favored in first intention (analgesics, continuous enteral feeding, somatostatin analogues), which allows complete symptomatic regression in 57% of cases associated with a 5% rate of complications (arterial thrombosis and diabetes). Endoscopic treatment may also be associated with conservative measures. Surgery achieves a complete regression of symptoms in 79% of cases but with a 20% rate of complications. Surgery is indicated in case of therapeutic failure or in case of doubt about a malignant tumor. Pancreaticoduodenectomy and duodenal resection with pancreatic preservation (PPDR) seem to be the most effective treatments. PPDR has also been proposed as a first-line treatment for purely duodenal location of paraduodenal pancreatitis, thereby preventing progression to an extended segmental form.

Reduction of patient radiation dose with a new organ based dose modulation technique for thoraco-abdominopelvic computed tomography (CT) (Liver dose right index).

PURPOSE: To evaluate the radiation dose reduction, image quality and diagnostic confidence with thoraco-abdominopelvic computed tomography (TACT) using a new organ based dose modulation system (liver dose right index [Liver DRI]), compared to TACT using a standard automatic exposure control adjusting mA according to attenuation. METHODS: A total of 37 patients who had two TACT examinations on 2 different CT scanners, one using standard automatic exposure control (combination of a DoseRight automatic current selection and Z modulation) and one using Liver DRI were included. There were 19 men and 18 women with a mean age of 67.6±11.7 (SD) years (range: 36-85 years) For each patient, volume CT dose index (CTDIvol), size-specific dose estimates (SSDE) and signal-to-noise ratio (SNR) were evaluated at each anatomic level (lung, breast, liver and pelvis area) for each protocol. Two radiologists assessed independently image quality, artifacts and diagnostic confidence. RESULTS: The radiation dose decreased significantly using Liver DRI compared to standard automatic exposure control on the total scan length, lung, breast and pelvis area, with a significant CTDIvol reduction of 27% (P=0.0001), 23% (P=0.0002), 24% (P=0.0002) and 31% (P=0.0001), respectively; and a significant SSDE reduction of 23% (P=0.0001), 28% (P=0.0001), 23% (P=0.0002) and 29% (P=0.0001), respectively. No significant SNR reductions were observed in all measured tissues at the level of the aortic arch, celiac trunk and iliac bifurcation, except in the muscle (P=0.0013) and fat tissue (P=0.0052) at the level of the ureteral meatus. No significant differences were noted between both protocols in overall image quality, artifacts and diagnostic confidence with an excellent inter observer agreement between radiologists (Kappa values of 0.83, 0.85 and 0.88, respectively). CONCLUSION: Liver DRI organ based dose modulation technique allows significant dose reduction compared to standard automatic exposure control while preserving diagnostic image quality in all thoraco-abdominopelvic areas.

Identification of putative exported/secreted proteins in prokaryotic proteomes.

The increasing number of bacterial genomes being sequenced fuels an equal demand for methods to rapidly analyze the proteomes of these organisms. One group of proteins of pressing importance is the exported/secreted proteins, given their dominant immunogenicity and role in pathogenesis. With this in mind, a weight matrix algorithm and two artificial neural networks, one based on amino acid position within the N-terminus and the other on amino acid frequency, were developed for identification of such proteins. The neural networks and a hybrid method, combining the weight matrix algorithm and the amino acid frequency neural network, were tested independently against a standard data set of secreted and cytoplasmic proteins to determine their accuracy in predicting secreted prokaryotic proteins. The results of these analyses demonstrated that the amino acid position neural network provided the highest accuracy (Mathews correlation coefficient of 0.93) in predicting secreted proteins of Gram-negative bacteria, whereas the hybrid method was best (Mathews correlation coefficient of 0.97) for prediction of Gram-positive secreted proteins. These two methods were integrated into a single program (ExProt) designed to analyze whole proteomes. In addition to protein localization, ExProt also contains a neural network trained to identify the most probable signal peptidase I cleavage site of secreted proteins. When tested against the standard protein data set ExProt correctly predicted 73.5 and 84.5% of the cleavage sites in Gram-positive and Gram-negative secreted proteins, respectively. Comparative analysis of Gram-negative, Gram-positive, Mycobacterium tuberculosis, and Archaea proteomes with ExProt revealed that the fraction of putative exported/secreted proteins encoded by bacterial genomes ranged from 8% for Methanococcus jannaschii to 37% for Mycoplasma pneumoniae.