Showing of 1 reviews. There was a problem filtering reviews right now. Please try again later. Format: Kindle Edition Verified Purchase. This book is a good read with no real surprises as far as the plot goes, Sam Colton is a stuntman who also takes cases as a private investigator. A young girl vanishes without a trace!
But it looks like a cover up by a man who has high hopes of becoming president of the U. The cops have been slapdash in searching the girls room for evidence, Sam is approached by the parents and asked if he could look into what has happened to their daughter, as the police have no body or any idea what has happened to her? Sam is given the run around following false clues to various town and cities and even down into Mexico, along the way he is shot at various times, but survives these attempts on his life.
The author deals with things relevant to the case in hand and has not tried to bulk out the story with inane babbling, like giving long drawn out descriptions of journey's or the clothes worn ETC. A good book, but could be bettered by throwing in some curve balls to make the reader work a little harder to discover what really happened. Worth a read if you don't want anything to heavy.
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Need customer service? Click here. Unlimited One-Day Delivery and more. There's a problem loading this menu at the moment. Learn more about Amazon Prime. Back to top. Exclusion criteria were pre-existing diabetes mellitus or impaired glucose tolerance, or prior partial pancreatectomy with IAT. The patient was mailed the informed consent in advance, and the investigator obtained informed consent subsequently by telephone.
This study was a retrospective assessment of outcomes which included medical records review and a telephone questionnaire. Because patients did not have any onsite study visit, and the study risk was minimal, the UMN-IRB approved obtaining consent by telephone as described. TP-IAT was performed as described previously [ 17 ]. Briefly, TP was done to preserve the blood supply to the pancreas until immediately before resection to minimize warm ischemia time. Following TP, the pancreas was surface-cooled and transported to the islet isolation laboratory.
The basic method for islet isolation and purification has been described previously [ 17 ]. After digestion, the islet preparation may have been additionally purified by density gradient centrifugation.
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A visual estimate of purity was performed by estimating the percent of insulin-producing cells stained by DTZ [ 19 ]. Furthermore, ISI a dimensionless quantity was calculated by dividing the total number of IEs in a preparation by the total number of IPs. ISI provides a simple metric that reflects the average size of an IP in a preparation [ 20 , 21 ]. IE dose was converted to an amount of DNA after multiplying by the conversion factor of The typical autoislet product preparation time ranged from 3. During the infusion, the portal pressures were continuously monitored and if they exceeded 25 cm H 2 O the remainder of the islet preparation was infused into the peritoneal cavity.
Target BGLs have been summarized elsewhere [ 24 ]. The AUC was calculated from ROC curves generated for each islet product characteristic and these values were evaluated. We analyzed several multivariate models and additionally included age, BMI, and purity to the model. In addition, we compared the models using the Akaike information criterion AIC values with a smaller AIC value standing for a better model. All statistical analyses were performed using SAS statistical software package, version 9. For the different multivariate models, none of the additional variables reached any measurable impact.
Age seems to have a slight impact as there was a significant negative correlation between IE dose , OCR dose and age. Note that the width of the gray region is much narrower with the OCR dose. The black dotted line represents the calculated cut-off point for clinical outcome IE dose : 5, and OCR dose : 6. The second column of graphs represents receiver operating characteristic ROC curves for each of the five islet product characteristics from this data set.
The area-under-the-curve AUC has been calculated for each islet product characteristic and these values are shown above each ROC curve. As islet transplantation moves closer to becoming standard-of-care, in vitro islet quality assessment assays that can be performed routinely and prospectively to predict CTOs are needed.
The IE dose in our cohort of patients was more predictive of CTO than a past cohort presented by Anazawa et al [ 10 ].
Therefore, it is possible that in a larger cohort OCR dose would be significantly more predictive than IE dose especially in those patients who receive a marginal IE dose as illustrated in Table 2. The concept of transplanting an adequate IE dose to achieve II is intuitive, and it has been proven to be important in clinical practice [ 1 , 2 , 4 , 7 — 9 , 25 — 28 ].
Published results demonstrate that when used together these parameters can predict diabetes reversal in mice with high specificity and sensitivity. A reason may be in the difference in the transplant site renal subcapsule in mice vs. It may be that transplanting large quantities of dead or dying tissue into a confined space, such as under the renal capsule, may more greatly impact the engraftment of the viable tissue by sequestering an inflammatory response directly into the site of transplant and or by increasing the diffusional distance for oxygen.
This same phenomenon may not occur following intraportal transplant since the tissue is not confined to a small space, but rather distributed throughout a large organ. Interestingly the data showed recipients that achieved II had a significantly higher purity than those who were dependent 6—12 months post-IAT Table 1 suggesting that low purity may be associated with worse transplant outcomes. Initial observations at the University of Minnesota suggest that a larger transplanted TV typically due to lower purity may itself be associated with worse CTOs.
Our group has found that large TVs result in increased post-IAT portal pressures, which are directly associated with higher complication rates portal venous thrombosis and bleeding. Islet size has also been implicated as predictive, with smaller islets expected to result in better CTO, especially at a marginal IE dose. We do not have a clear explanation for this difference, but it is conceivable that the effect of islet size is marginalized when very high IE doses are transplanted. There are some limitations of this study. Calculation of the OCR dose is based on the IE dose and thus the values have some inherent uncertainty since they are based on operator-dependent manual counts.
In addition, rather than correlating OCR dose only with categorical CTOs, it may also be appropriate to quantify the reduction in exogenous insulin requirements and also account for recipient factors, such as varying insulin sensitivity between individuals. These improvements will aid in the case of islet allotransplant, as we predict that this model will be more difficult to correlate CTO with characterization assays due to confounding factors such as the need for immunosuppression therapy, potential rejection, and the high possibility of multiple preparations being transplanted into a single recipient.
Future studies will involve optimizing the predictive capability of OCR dose in the IAT model and examining the utility of these islet product characteristics, specifically OCR dose , on the more challenging case of islet allotransplant.
We thank Dr. Julia Goldstein, Dr. Guillermo Arreaza-Rubin and Dr. Thomas Eggermann on helpful discussions on data analysis and presentation.
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The authors would like to thank the Schulze Diabetes Institute islet isolation team and all of our clinical nurses. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. National Center for Biotechnology Information , U. PLoS One. Published online Aug Klearchos K. Bellin , 2 , 3 David E.
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Sutherland , 2 , 3 Thomas M. Suszynski , 2 , 3 Jennifer P. Kitzmann , 1 , 2 , 3 Efstathios S. Avgoustiniatos , 2 , 3 Angelika C. Gruessner , 1 Kathryn R.
Mueller , 1 , 2 , 3 Gregory J. Beilman , 2 Appakalai N. Balamurugan , 2 , 3 Gopalakrishnan Loganathan , 2 , 3 Clark K. Colton , 4 Maria Koulmanda , 5 Gordon C. Weir , 6 Josh J. Wilhelm , 2 , 3 Dajun Qian , 7 Joyce C. Niland , 7 and Bernhard J. Hering 2 , 3. Melena D. David E. Thomas M. Jennifer P. Efstathios S. Angelika C. Kathryn R. Gregory J. Appakalai N. Clark K. Gordon C.
Josh J. Joyce C. Bernhard J. Matthias G von Herrath, Editor. Author information Article notes Copyright and License information Disclaimer. Competing Interests: The authors have declared that no competing interests exist.