Temperature, recreational fishing and diapause egg connections : dispersal of spiny water fleas (Bythotrephes longimanus)

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License. The definitive version was published in Biological Invasions 13 (2011): 2513-2531, doi:10.1007/s10530-011-0078-8.The spiny water flea (Bythotrephes longimanus) is spreading from Great Lakes coastal waters into northern inland lakes within a northern temperature-defined latitudinal band. Colonization of Great Lakes coastal embayments is assisted by winds and seiche surges, yet rapid inland expansion across the northern states comes through an overland process. The lack of invasions at Isle Royale National Park contrasts with rapid expansion on the nearby Keweenaw Peninsula. Both regions have comparable geology, lake density, and fauna, but differ in recreational fishing boat access, visitation, and containment measures. Tail spines protect Bythotrephes against young of the year, but not larger fish, yet the unusual thick-shelled diapausing eggs can pass through fish guts in viable condition. Sediment traps illustrate how fish spread diapausing eggs across lakes in fecal pellets. Trillions of diapausing eggs are produced per year in Lake Michigan and billions per year in Lake Michigamme, a large inland lake. Dispersal by recreational fishing is linked to use of baitfish, diapausing eggs defecated into live wells and bait buckets, and Bythothephes snagged on fishing line, anchor ropes, and minnow seines. Relatively simple measures, such as on-site rinsing of live wells, restricting transfer of certain baitfish species, or holding baitfish for 24 h (defecation period), should greatly reduce dispersal.Study of Lakes Superior and Michigan was funded from NSF OCE-9726680 and OCE-9712872 to W.C.K., OCE-9712889 to J. Churchill. Geographic survey sampling and Park studies in the national parks during 2008-2010 were funded by a grant from the National Park Service Natural Resource Preservation Program GLNF CESU Task Agreement No. J6067080012

Comparison of Artificial Neural Network and Logistic Regression Models for Predicting In-Hospital Mortality after Primary Liver Cancer Surgery

BACKGROUND: Since most published articles comparing the performance of artificial neural network (ANN) models and logistic regression (LR) models for predicting hepatocellular carcinoma (HCC) outcomes used only a single dataset, the essential issue of internal validity (reproducibility) of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model. METHODOLOGY/PRINCIPAL FINDINGS: Patients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC) curves, Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive) parameter affecting in-hospital mortality followed by age and lengths of stay. CONCLUSIONS/SIGNIFICANCE: In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data

Liver Volumetry Plug and Play: Do It Yourself with ImageJ

AB - BACKGROUND: A small remnant liver volume is an important risk factor for posthepatectomy liver failure and can be predicted accurately by computed tomography (CT) volumetry using radiologic image analysis software. Unfortunately, this software is expensive and usually requires support by a radiologist. ImageJ is a freely downloadable image analysis software package developed by the National Institute of Health (NIH) and brings liver volumetry to the surgeon's desktop. We aimed to assess the accuracy of ImageJ for hepatic CT volumetry. METHODS: ImageJ was downloaded from http://www.rsb.info.nih.gov/ij/ . Preoperative CT scans of 15 patients who underwent liver resection for colorectal cancer liver metastases were retrospectively analyzed. Scans were opened in ImageJ; and the liver, all metastases, and the intended parenchymal transection line were manually outlined on each slice. The area of each selected region, metastasis, resection specimen, and remnant liver was multiplied by the slice thickness to calculate volume. Volumes of virtual liver resection specimens measured with ImageJ were compared with specimen weights and calculated volumes obtained during pathology examination after resection. RESULTS: There was an excellent correlation between the volumes calculated with ImageJ and the actual measured weights of the resection specimens (r(2) = 0.98, p < 0.0001). The weight/volume ratio amounted to 0.88 +/- 0.04 (standard error) and was in agreement with our earlier findings using CT-linked radiologic software. CONCLUSION: ImageJ can be used for accurate hepatic CT volumetry on a personal computer. This application brings CT volumetry to the surgeon's desktop at no expense and is particularly useful in cases of tertiary referred patients, who already have a proper CT scan on CD-ROM from the referring institution. Most likely the discrepancy between volume and weight results from exsanguination of the liver after resectio

Liver surgery in the presence of cirrhosis or steatosis: Is morbidity increased?

<p>Abstract</p> <p>Background data</p> <p>The prevalence of steatosis and hepatitis-related liver cirrhosis is dramatically increasing together worldwide. Cirrhosis and, more recently, steatosis are recognized as a clinically important feature that influences patient morbidity and mortality after hepatic resection when compared with patients with healthy liver.</p> <p>Objective</p> <p>To review present knowledge regarding how the presence of cirrhosis or steatosis can influence postoperative outcome after liver resection.</p> <p>Methods</p> <p>A critical review of the English literature was performed to provide data concerning postoperative outcome of patients presenting injured livers who required hepatectomy.</p> <p>Results</p> <p>In clinical studies, the presence of steatosis impaired postoperative outcome regardless the severity and quality of the hepatic fat. A great improvement in postoperative outcome has been achieved using modern and multidisciplinary preoperative workup in cirrhotic patients. Due to the lack of a proper classification for morbidity and a clear definition of hepatic failure in the literature, the comparison between different studies is very limited. Although, many surgical strategies have been developed to protect injured liver surgery, no one have gained worldwide acceptance.</p> <p>Conclusion</p> <p>Surgeons should take the presence of underlying injured livers into account when planning the extent and type of hepatic surgery. Preoperative and perioperative interventions should be considered to minimize the additional damage. Further randomized trials should focus on the evaluation of novel preoperative strategies to minimize risk in these patients. Each referral liver center should have the commitment to report all deaths related to postoperative hepatic failure and to use a common classification system for postoperative complications.</p

Plasma and cellular fibronectin: distinct and independent functions during tissue repair

Fibronectin (FN) is a ubiquitous extracellular matrix (ECM) glycoprotein that plays vital roles during tissue repair. The plasma form of FN circulates in the blood, and upon tissue injury, is incorporated into fibrin clots to exert effects on platelet function and to mediate hemostasis. Cellular FN is then synthesized and assembled by cells as they migrate into the clot to reconstitute damaged tissue. The assembly of FN into a complex three-dimensional matrix during physiological repair plays a key role not only as a structural scaffold, but also as a regulator of cell function during this stage of tissue repair. FN fibrillogenesis is a complex, stepwise process that is strictly regulated by a multitude of factors. During fibrosis, there is excessive deposition of ECM, of which FN is one of the major components. Aberrant FN-matrix assembly is a major contributing factor to the switch from normal tissue repair to misregulated fibrosis. Understanding the mechanisms involved in FN assembly and how these interplay with cellular, fibrotic and immune responses may reveal targets for the future development of therapies to regulate aberrant tissue-repair processes