Discovering High-Utility Itemsets at Multiple Abstraction Levels

High-Utility Itemset Mining (HUIM) is a relevant data mining task. The goal is to discover recurrent combinations of items characterized by high prot from transactional datasets. HUIM has a wide range of applications among which market basket analysis and service proling. Based on the observation that items can be clustered into domain-specic categories, a parallel research issue is generalized itemset mining. It entails generating correlations among data items at multiple abstraction levels. The extraction of multiple-level patterns affords new insights into the analyzed data from dierent viewpoints. This paper aims at discovering a novel pattern that combines the expressiveness of generalized and High-Utility itemsets. According to a user-defined taxonomy items are rst aggregated into semantically related categories. Then, a new type of pattern,namely the Generalized High-utility Itemset (GHUI), is extracted. It represents a combinations of items at different granularity levels characterized by high prot (utility). While protable combinations of item categories provide interesting high-level information, GHUIs at lower abstraction levels represent more specic correlationsamong protable items. A single-phase algorithm is proposed to efficiently discover utility itemsets at multiple abstraction levels. The experiments, which were performed on both real and synthetic data, demonstrate the effectiveness and usefulness of the proposed approach

Automated detection of left ventricle in arterial input function images for inline perfusion mapping using deep learning: A study of 15,000 patients

Purpose: Quantification of myocardial perfusion has the potential to improve the detection of regional and global flow reduction. Significant effort has been made to automate the workflow, where one essential step is the arterial input function (AIF) extraction. Failure to accurately identify the left ventricle (LV) prevents AIF estimation required for quantification, therefore high detection accuracy is required. This study presents a robust LV detection method using the convolutional neural network (CNN). Methods: CNN models were trained by assembling 25,027 scans (N = 12,984 patients) from three hospitals, seven scanners. Performance was evaluated using a hold‐out test set of 5721 scans (N = 2805 patients). Model inputs were a time series of AIF images (2D+T). Two variations were investigated: (1) two classes (2CS) for background and foreground (LV mask), and (2) three classes (3CS) for background, LV, and RV. The final model was deployed on MRI scanners using the Gadgetron reconstruction software framework. Results: Model loading on the MRI scanner took ~340 ms and applying the model took ~180 ms. The 3CS model successfully detected the LV in 99.98% of all test cases (1 failure out of 5721). The mean Dice ratio for 3CS was 0.87 ± 0.08 with 92.0% of all cases having Dice >0.75. The 2CS model gave a lower Dice ratio of 0.82 ± 0.22 (P .2) comparing automatically extracted AIF signals with signals from manually drawn contours. Conclusions: A CNN‐based solution to detect the LV blood pool from the arterial input function image series was developed, validated, and deployed. A high LV detection accuracy of 99.98% was achieved

Biochemical properties of Paracoccus denitrificans FnrP:Reactions with molecular oxygen and nitric oxide

In Paracoccus denitrificans, three CRP/FNR family regulatory proteins, NarR, NnrR and FnrP, control the switch between aerobic and anaerobic (denitrification) respiration. FnrP is a [4Fe-4S] cluster containing homologue of the archetypal O2 sensor FNR from E. coli and accordingly regulates genes encoding aerobic and anaerobic respiratory enzymes in response to O2, and also NO, availability. Here we show that FnrP undergoes O2-driven [4Fe-4S] to [2Fe-2S] cluster conversion that involves up to 2 O2 per cluster, with significant oxidation of released cluster sulfide to sulfane observed at higher O2 concentrations. The rate of the cluster reaction was found to be ~6-fold lower than that of E. coli FNR, suggesting that FnrP can remain transcriptionally active under microaerobic conditions. This is consistent with a role for FnrP in activating expression of the high O2 affinity cytochrome c oxidase under microaerobic conditions. Cluster conversion resulted in dissociation of the transcriptionally active FnrP dimer into monomers. Therefore, along with E. coli FNR, FnrP belongs to the subset of FNR proteins in which cluster type is correlated with association state. Interestingly, two key charged residues, Arg140 and Asp154, that have been shown to play key roles in the monomer-dimer equilibrium in E. coli FNR are not conserved in FnrP, indicating that different protomer interactions are important for this equilibrium. Finally, the FnrP [4Fe-4S] cluster is shown to undergo reaction with multiple NO molecules, resulting in iron nitrosyl species and dissociation into monomers

Activation of Cytotoxic and Regulatory Functions of NK Cells by Sindbis Viral Vectors

Oncolytic viruses (OVs) represent a relatively novel anti-cancer modality. Like other new cancer treatments, effective OV therapy will likely require combination with conventional treatments. In order to design combinatorial treatments that work well together, a greater scrutiny of the mechanisms behind the individual treatments is needed. Sindbis virus (SV) based vectors have previously been shown to target and kill tumors in xenograft, syngeneic, and spontaneous mouse models. However, the effect of SV treatment on the immune system has not yet been studied. Here we used a variety of methods, including FACS analysis, cytotoxicity assays, cell depletion, imaging of tumor growth, cytokine blockade, and survival experiments, to study how SV therapy affects Natural Killer (NK) cell function in SCID mice bearing human ovarian carcinoma tumors. Surprisingly, we found that SV anti-cancer efficacy is largely NK cell-dependent. Furthermore, the enhanced therapeutic effect previously observed from Sin/IL12 vectors, which carry the gene for interleukin 12, is also NK cell dependent, but works through a separate IFNγ-dependent mechanism, which also induces the activation of peritoneal macrophages. These results demonstrate the multimodular nature of SV therapy, and open up new possibilities for potential synergistic or additive combinatorial therapies with other treatments

Engineered swift equilibration of a Brownian particle

A fundamental and intrinsic property of any device or natural system is its relaxation time relax, which is the time it takes to return to equilibrium after the sudden change of a control parameter [1]. Reducing $tau$ relax , is frequently necessary, and is often obtained by a complex feedback process. To overcome the limitations of such an approach, alternative methods based on driving have been recently demonstrated [2, 3], for isolated quantum and classical systems [4--9]. Their extension to open systems in contact with a thermostat is a stumbling block for applications. Here, we design a protocol,named Engineered Swift Equilibration (ESE), that shortcuts time-consuming relaxations, and we apply it to a Brownian particle trapped in an optical potential whose properties can be controlled in time. We implement the process experimentally, showing that it allows the system to reach equilibrium times faster than the natural equilibration rate. We also estimate the increase of the dissipated energy needed to get such a time reduction. The method paves the way for applications in micro and nano devices, where the reduction of operation time represents as substantial a challenge as miniaturization [10]. The concepts of equilibrium and of transformations from an equilibrium state to another, are cornerstones of thermodynamics. A textbook illustration is provided by the expansion of a gas, starting at equilibrium and expanding to reach a new equilibrium in a larger vessel. This operation can be performed either very slowly by a piston, without dissipating energy into the environment, or alternatively quickly, letting the piston freely move to reach the new volume

Gadolinium oxide nanocrystal nonvolatile memory with HfO2/Al2O3 nanostructure tunneling layers

In this study, Gd2O3 nanocrystal (Gd2O3-NC) memories with nanostructure tunneling layers are fabricated to examine their performance. A higher programming speed for Gd2O3-NC memories with nanostructure tunneling layers is obtained when compared with that of memories using a single tunneling layer. A longer data retention (< 15% charge loss after 104 s) is also observed. This is due to the increased physical thickness of the nanostructure tunneling layer. The activation energy of charge loss at different temperatures is estimated. The higher activation energy value (0.13 to 0.17 eV) observed at the initial charge loss stage is attributed to the thermionic emission mechanism, while the lower one (0.07 to 0.08 eV) observed at the later charge loss stage is attributed to the direct tunneling mechanism. Gd2O3-NC memories with nanostructure tunneling layers can be operated without degradation over several operation cycles. Such NC structures could potentially be used in future nonvolatile memory applications

Entering and Exiting the Medicare Part D Coverage Gap: Role of Comorbidities and Demographics

Background: Some Medicare Part D enrollees whose drug expenditures exceed a threshold enter a coverage gap with full cost-sharing, increasing their risk for reduced adherence and adverse outcomes. Objective: To examine comorbidities and demographic characteristics associated with gap entry and exit. Design: We linked 2005-2006 pharmacy, outpatient, and inpatient claims to enrollment and Census data. We used logistic regression to estimate associations of 2006 gap entry and exit with 2005 medical comorbidities, demographics, and Census block characteristics. We expressed all results as predicted percentages. PATIENTS: 287,713 patients without gap coverage, continuously enrolled in a Medicare Advantage Part D (MAPD) plan serving eight states. Patients who received a low-income subsidy, could not be geocoded, or had no 2006 drug fills were excluded. Results: Of enrollees, 15.9% entered the gap, 2.6% within the first 180 days; among gap enterers, only 6.7% exited again. Gap entry was significantly associated with female gender and all comorbidities, particularly dementia (39.5% gap entry rate) and diabetes (28.0%). Among dementia patients entering the gap, anti-dementia drugs (donepezil, memantine, rivastigmine, and galantamine) and atypical antipsychoticmedications (risperidone, quetiapine, and olanzapine) together accounted for 40% of pre-gap expenditures. Among diabetic patients, rosiglitazone accounted for 7.2% of pre-gap expenditures. Having dementia was associated with twice the risk of gap exit. Conclusions: Certain chronically ill MAPD enrollees are at high risk of gap entry and exposure to unsubsidized medication costs. Clinically vulnerable populations should be counseled on how to best manage costs through drug substitution or discontinuation of specific, non-essential medications. © 2010 Society of General Internal Medicine

An Innovative Option for Venous Reconstruction After Pancreaticoduodenectomy: the Left Renal Vein

INTRODUCTION: Pancreatic ductal adenocarcinoma has a high mortality rate with limited treatment options. One option is pancreaticoduodenectomy, although complete resection may require venous resection. Pancreaticoduodenectomy with venous resection and reconstruction is becoming a more common practice with many choices for venous reconstruction. We describe the technique of using the left renal vein as a conduit for venous reconstruction during pancreaticoduodenectomy. METHODS: The technique for use of the left renal vein as an interposition graft for venous reconstruction during pancreaticoduodenectomy is described as well as outcomes for nine patients that have undergone the procedure. RESULTS: Nine patients, seven men, with a mean age of 57 years, have undergone the operation. There were eight interposition grafts and one patch graft. Mean operating time was 7.8 hours, and mean tumor size was 3.4 cm. Eight patients had node-positive disease, and six had involvement of the vein. Mean hospital stay was 14 days and perioperative morbidity included a superficial wound infection, delayed gastric emptying, ascites, and gastrointestinal bleeding in one patient each. Creatinine ranged from 0.8–1.1 mg/dl preoperatively and from 0.7–1.3 mg/dl at discharge. Mean follow-up was 6.8 months with normal creatinine values noted through the follow-up period. Two patients had died during follow-up from recurrent disease at 8.3 and 18.2 months after the operation. CONCLUSIONS: The left renal vein provides an additional choice for an autologous graft during pancreaticoduodenectomy with venous resection. The ease of harvesting the graft and maintenance of renal function distinguish its use

The Impact of Medical Interpretation Method on Time and Errors

Background: Twenty-two million Americans have limited English proficiency. Interpreting for limited English proficient patients is intended to enhance communication and delivery of quality medical care. Objective: Little is known about the impact of various interpreting methods on interpreting speed and errors. This investigation addresses this important gap. Design: Four scripted clinical encounters were used to enable the comparison of equivalent clinical content. These scripts were run across four interpreting methods, including remote simultaneous, remote consecutive, proximate consecutive, and proximate ad hoc interpreting. The first 3 methods utilized professional, trained interpreters, whereas the ad hoc method utilized untrained staff. Measurements: Audiotaped transcripts of the encounters were coded, using a prespecified algorithm to determine medical error and linguistic error, by coders blinded to the interpreting method. Encounters were also timed. Results: Remote simultaneous medical interpreting (RSMI) encounters averaged 12.72 vs 18.24 minutes for the next fastest mode (proximate ad hoc) (p = 0.002). There were 12 times more medical errors of moderate or greater clinical significance among utterances in non-RSMI encounters compared to RSMI encounters (p = 0.0002). Conclusions: Whereas limited by the small number of interpreters involved, our study found that RSMI resulted in fewer medical errors and was faster than non-RSMI methods of interpreting