132 research outputs found

    Surgical management of mediastinal liposarcoma extending from hypopharynx to carina: Case report

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    We describe the complete resection of a giant, well-differentiated mediastinal liposarcoma extending retropharynx to envelop the aortic arch, trachea and esophagus following preoperative radiotherapy

    Making sense of ultrahigh-resolution movement data: A new algorithm for inferring sites of interest

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    Decomposing the life track of an animal into behavioral segments is a fundamental challenge for movement ecology. The proliferation of high‐resolution data, often collected many times per second, offers much opportunity for understanding animal movement. However, the sheer size of modern data sets means there is an increasing need for rapid, novel computational techniques to make sense of these data. Most existing methods were designed with smaller data sets in mind and can thus be prohibitively slow. Here, we introduce a method for segmenting high‐resolution movement trajectories into sites of interest and transitions between these sites. This builds on a previous algorithm of Benhamou and Riotte‐Lambert (2012). Adapting it for use with high‐resolution data. The data’s resolution removed the need to interpolate between successive locations, allowing us to increase the algorithm’s speed by approximately two orders of magnitude with essentially no drop in accuracy. Furthermore, we incorporate a color scheme for testing the level of confidence in the algorithm's inference (high = green, medium = amber, low = red). We demonstrate the speed and accuracy of our algorithm with application to both simulated and real data (Alpine cattle at 1 Hz resolution). On simulated data, our algorithm correctly identified the sites of interest for 99% of “high confidence” paths. For the cattle data, the algorithm identified the two known sites of interest: a watering hole and a milking station. It also identified several other sites which can be related to hypothesized environmental drivers (e.g., food). Our algorithm gives an efficient method for turning a long, high‐resolution movement path into a schematic representation of broadscale decisions, allowing a direct link to existing point‐to‐point analysis techniques such as optimal foraging theory. It is encoded into an R package called SitesInterest, so should serve as a valuable tool for making sense of these increasingly large data streams

    Why did the animal turn? Time‐varying step selection analysis for inference between observed turning‐points in high frequency data

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    1. Step selection analysis (SSA) is a fundamental technique for uncovering the drivers of animal movement decisions. Its typical use has been to view an animal as ‘selecting’ each measured location, given its current (and possibly previous) locations. Although an animal is unlikely to make decisions precisely at the times its locations are measured, if data are gathered at a relatively low frequency (every few minutes or hours) this is often the best that can be done. Nowadays, though, tracking data are increasingly gathered at very high frequencies, often ≄1 Hz, so it may be possible to exploit these data to perform more behaviourally‐meaningful step selection analysis. 2. Here, we present a technique to do this. We first use an existing algorithm to determine the turning‐points in an animal's movement path. We define a ‘step’ to be a straight‐line movement between successive turning‐points. We then construct a generalised version of integrated SSA (iSSA), called time‐varying iSSA (tiSSA), which deals with the fact that turning‐points are usually irregularly spaced in time. We demonstrate the efficacy of tiSSA by application to data on both simulated animals and free‐ranging goats Capra aegagrus hircus, comparing our results to those of regular iSSA with locations that are separated by a constant time‐interval. 3. Using (regular) iSSA with constant time‐steps can give results that are misleading compared to using tiSSA with the actual turns made by the animals. Furthermore, tiSSA can be used to infer covariates that are dependent on the time between turns, which is not possible with regular iSSA. As an example, we show that our study animals tend to spend less time between successive turns when the ground is rockier and/or the temperature is hotter. 4. By constructing a step selection technique that works between observed turning‐points of animals, we enable step selection to be used on high‐frequency movement data, which are becoming increasingly prevalent in modern biologging studies. Furthermore, since turning‐points can be viewed as decisions, our method places step selection analysis on a more behaviourally‐meaningful footing compared to previous techniques

    Postoperative Aspiration Pneumonia (PoPNA) Prevention Protocol

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    Postoperative pneumonia increases morbidity, mortality, length of stay, and hospital costs up to 12,000−12,000-40,000 per patient TJUH Center City ranked in the top 3rd - 4th quartile of pulmonary complications on the 2020 National Surgical Quality Improvement Program perioperative review ICOUGH protocol: widely accepted, standardized set of post-operative interventions to reduce pneumonia incidence Survey design: measure ICOUGH compliance before and after implementation of resident note checklist in EPI

    Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT

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    Background: Limited data are available regarding whether computer-aided diagnosis (CAD) improves assessment of malignancy risk in indeterminate pulmonary nodules (IPNs). Purpose: To evaluate the effect of an artificial intelligence-based CAD tool on clinician IPN diagnostic performance and agreement for both malignancy risk categories and management recommendations. Materials and Methods: This was a retrospective multireader multicase study performed in June and July 2020 on chest CT studies of IPNs. Readers used only CT imaging data and provided an estimate of malignancy risk and a management recommendation for each case without and with CAD. The effect of CAD on average reader diagnostic performance was assessed using the Obuchowski-Rockette and Dorfman-Berbaum-Metz method to calculate estimates of area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Multirater Fleiss Îș statistics were used to measure interobserver agreement for malignancy risk and management recommendations. Results: A total of 300 chest CT scans of IPNs with maximal diameters of 5-30 mm (50.0% malignant) were reviewed by 12 readers (six radiologists, six pulmonologists) (patient median age, 65 years; IQR, 59-71 years; 164 [55%] men). Readers\u27 average AUC improved from 0.82 to 0.89 with CAD (P \u3c .001). At malignancy risk thresholds of 5% and 65%, use of CAD improved average sensitivity from 94.1% to 97.9% (P = .01) and from 52.6% to 63.1% (P \u3c .001), respectively. Average reader specificity improved from 37.4% to 42.3% (P = .03) and from 87.3% to 89.9% (P = .05), respectively. Reader interobserver agreement improved with CAD for both the less than 5% (Fleiss Îș, 0.50 vs 0.71; P \u3c .001) and more than 65% (Fleiss Îș, 0.54 vs 0.71; P \u3c .001) malignancy risk categories. Overall reader interobserver agreement for management recommendation categories (no action, CT surveillance, diagnostic procedure) also improved with CAD (Fleiss Îș, 0.44 vs 0.52; P = .001). Conclusion: Use of computer-aided diagnosis improved estimation of indeterminate pulmonary nodule malignancy risk on chest CT scans and improved interobserver agreement for both risk stratification and management recommendations

    Human α2ÎČ1HI CD133+VE epithelial prostate stem cells express low levels of active androgen receptor

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    Stem cells are thought to be the cell of origin in malignant transformation in many tissues, but their role in human prostate carcinogenesis continues to be debated. One of the conflicts with this model is that cancer stem cells have been described to lack androgen receptor (AR) expression, which is of established importance in prostate cancer initiation and progression. We re-examined the expression patterns of AR within adult prostate epithelial differentiation using an optimised sensitive and specific approach examining transcript, protein and AR regulated gene expression. Highly enriched populations were isolated consisting of stem (α(2)ÎČ(1)(HI) CD133(+VE)), transiently amplifying (α(2)ÎČ(1)(HI) CD133(-VE)) and terminally differentiated (α(2)ÎČ(1)(LOW) CD133(-VE)) cells. AR transcript and protein expression was confirmed in α(2)ÎČ(1)(HI) CD133(+VE) and CD133(-VE) progenitor cells. Flow cytometry confirmed that median (±SD) fraction of cells expressing AR were 77% (±6%) in α(2)ÎČ(1)(HI) CD133(+VE) stem cells and 68% (±12%) in α(2)ÎČ(1)(HI) CD133(-VE) transiently amplifying cells. However, 3-fold lower levels of total AR protein expression (peak and median immunofluorescence) were present in α(2)ÎČ(1)(HI) CD133(+VE) stem cells compared with differentiated cells. This finding was confirmed with dual immunostaining of prostate sections for AR and CD133, which again demonstrated low levels of AR within basal CD133(+VE) cells. Activity of the AR was confirmed in prostate progenitor cells by the expression of low levels of the AR regulated genes PSA, KLK2 and TMPRSS2. The confirmation of AR expression in prostate progenitor cells allows integration of the cancer stem cell theory with the established models of prostate cancer initiation based on a functional AR. Further study of specific AR functions in prostate stem and differentiated cells may highlight novel mechanisms of prostate homeostasis and insights into tumourigenesis

    Distinguishing post-treatment changes from recurrent disease in cholangiocarcinoma: a case report

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    <p>Abstract</p> <p>Introduction</p> <p>Three-dimensional techniques for radiotherapy have expanded possibilities for partial volume liver radiotherapy. Characteristic, transient radiographic changes can occur in the absence of clinical radiation-induced liver disease after hepatic radiotherapy and must be distinguished from local recurrence.</p> <p>Case presentation</p> <p>In this report, we describe computed tomography changes after chemoradiotherapy for cholangiocarcinoma as an example of collaboration to determine the clinical significance of the radiographic finding.</p> <p>Conclusion</p> <p>Because of improved three-dimensional, conformal radiotherapy techniques, consultation across disciplines may be necessary to interpret post-treatment imaging findings.</p
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