Quantum privacy and quantum coherence

We derive a simple relation between a quantum channel's capacity to convey coherent (quantum) information and its usefulness for quantum cryptography.Comment: 6 pages RevTex; two short comments added 7 October 199

Agent-based and continuous models of hopper bands for the Australian plague locust: How resource consumption mediates pulse formation and geometry

Locusts are significant agricultural pests. Under favorable environmental conditions flightless juveniles may aggregate into coherent, aligned swarms referred to as hopper bands. These bands are often observed as a propagating wave having a dense front with rapidly decreasing density in the wake. A tantalizing and common observation is that these fronts slow and steepen in the presence of green vegetation. This suggests the collective motion of the band is mediated by resource consumption. Our goal is to model and quantify this effect. We focus on the Australian plague locust, for which excellent field and experimental data is available. Exploiting the alignment of locusts in hopper bands, we concentrate solely on the density variation perpendicular to the front. We develop two models in tandem; an agent-based model that tracks the position of individuals and a partial differential equation model that describes locust density. In both these models, locust are either stationary (and feeding) or moving. Resources decrease with feeding. The rate at which locusts transition between moving and stationary (and vice versa) is enhanced (diminished) by resource abundance. This effect proves essential to the formation, shape, and speed of locust hopper bands in our models. From the biological literature we estimate ranges for the ten input parameters of our models. Sobol sensitivity analysis yields insight into how the band's collective characteristics vary with changes in the input parameters. By examining 4.4 million parameter combinations, we identify biologically consistent parameters that reproduce field observations. We thus demonstrate that resource-dependent behavior can explain the density distribution observed in locust hopper bands. This work suggests that feeding behaviors should be an intrinsic part of future modeling efforts.Comment: 26 pages, 11 figures, 3 tables, 3 appendices with 1 figure; revised Introduction, Sec 1.1, and Discussion; cosmetic changes to figures; fixed typos and made clarifications throughout; results unchange

Impact of Bayesian penalized likelihood reconstruction on quantitative and qualitative aspects for pulmonary nodule detection in digital 2-[18F]FDG-PET/CT

To evaluate the impact of block sequential regularized expectation maximization (BSREM) reconstruction on quantitative and qualitative aspects of 2-[18F]FDG-avid pulmonary nodules compared to conventional ordered subset expectation maximization (OSEM) reconstruction method. Ninety-one patients with 144 2-[18F]FDG-avid pulmonary nodules (all ≤ 20 mm) undergoing PET/CT for oncological (re-)staging were retrospectively included. Quantitative parameters in BSREM and OSEM (including point spread function modelling) were measured, including maximum standardized uptake value (SUVmax). Nodule conspicuity in BSREM and OSEM images was evaluated by two readers. Wilcoxon matched pairs signed-rank test was used to compare quantitative and qualitative parameters in BSREM and OSEM. Pulmonary nodule SUVmax was significantly higher in BSREM images compared to OSEM images [BSREM 5.4 (1.2–20.7), OSEM 3.6 (0.7–17.4); p = 0.0001]. In a size-based analysis, the relative increase in SUVmax was more pronounced in smaller nodules (≤ 7 mm) as compared to larger nodules (8–10 mm, or > 10 mm). Lesion conspicuity was higher in BSREM than in OSEM (p < 0.0001). BSREM reconstruction results in a significant increase in SUVmax and a significantly improved conspicuity of small 2-[18F]FDG-avid pulmonary nodules compared to OSEM reconstruction. Digital 2-[18F]FDG-PET/CT reading may be enhanced with BSREM as small lesion conspicuity is improved

Optimization of Drug Prescription and Medication Management in Older Adults with Cardiovascular Disease

Cardiovascular disease increases incrementally with age and elderly patients concomitantly sustain multimorbidities, with resultant prescription of multiple medications. Despite conforming with disease-specific cardiovascular clinical practice guidelines, this polypharmacy predisposes many elderly individuals with cardiovascular disease to adverse drug events and non-adherence. Patient-centered care requires that the clinician explore with each patient his or her goals of care and that this shared decision-making constitutes the basis for optimization of medication management. This approach to aligning therapies with patient preferences is likely to promote patient satisfaction, to limit morbidity, and to favorably affect healthcare costs

Immune-inflammatory proteome of elite ice hockey players before and after SARS-CoV-2 infection

Lette

Racial and Ethnic Differences in Serum Cotinine Levels of Cigarette Smokers Third National Health and Nutrition Examination Survey, 1988-1991

Context.— Cotinine, a metabolite of nicotine, is a marker of exposure to tobacco smoke. Previous studies suggest that non-Hispanic blacks have higher levels of serum cotinine than non-Hispanic whites who report similar levels of cigarette smoking. Objective.— To investigate differences in levels of serum cotinine in black, white, and Mexican American cigarette smokers in the US adult population. Design.— Third National Health and Nutrition Examination Survey, 1988-1991. Participants.— A nationally representative sample of persons aged 17 years or older who participated in the survey. Outcome Measures.— Serum cotinine levels by reported number of cigarettes smoked per day and by race and ethnicity. Results.— A total of 7182 subjects were involved in the study; 2136 subjects reported smoking at least 1 cigarette in the last 5 days. Black smokers had cotinine concentrations substantially higher at all levels of cigarette smoking than did white or Mexican American smokers (P\u3c.001). Serum cotinine levels for blacks were 125 nmol/L (22 ng/mL) (95% confidence interval [CI], 79-176 nmol/L [14-31 ng/mL]) to 539 nmol/L (95 ng/mL) (95% CI, 289-630 nmol/L [51-111 ng/mL]) higher than for whites and 136 nmol/L (24 ng/mL) (95% CI, 85-182 nmol/L [15-32 ng/mL]) to 641 nmol/L (113 ng/mL) (95% CI, 386-897 nmol/L [68-158 ng/mL]) higher than for Mexican Americans. These differences do not appear to be attributable to differences in environmental tobacco smoke exposure or in number of cigarettes smoked. Conclusions.— To our knowledge, this study provides the first evidence from a national study that serum cotinine levels are higher among black smokers than among white or Mexican American smokers. If higher cotinine levels among blacks indicate higher nicotine intake or differential pharmacokinetics and possibly serve as a marker of higher exposure to cigarette carcinogenic components, they may help explain why blacks find it harder to quit and are more likely to experience higher rates of lung cancer than white smokers

Can We Predict Skeletal Lesion on Bone Scan Based on Quantitative PSMA PET/CT Features?

Objective: The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS). Methods: In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times. Results: A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation. Conclusions: These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection

Low-dose CT from myocardial perfusion SPECT/CT allows the detection of anemia in preoperative patients

BACKGROUND To assess whether low-dose CT for attenuation correction of myocardial perfusion single-photon emission computed tomography (SPECT) allows for identification of anemic patients and grading anemia severity. METHODS AND RESULTS Patients who underwent a preoperative blood-test and low-dose CT scan, as a part of a cardiac SPECT exam, between 01 January 2015 and 31 December 2017 were enrolled in this retrospective study. Hemoglobin (Hb) levels and hematocrit were derived from clinical records. CT images were visually assessed (qualitative analysis) for the detection of inter-ventricular septum sign (IVSS) and aortic rim sign (ARS) and quantitative analysis were performed. The diagnostic accuracy for detecting anemia was compared using Hb values as the standard of reference. A total of 229 patients were included (110 with anemia; 57 mild; 46 moderate; 7 severe). The AUC of IVSS and ARS were 0.830 and 0.669, respectively (p<0.0001). The quantitative analysis outperformed ARS and IVSS; (AUC of 0.893, p=0.29). The optimal anemia cut-off using Youden index was 4.5 HU. CONCLUSION Quantitative analysis derived from low-dose CT images, as a part of cardiac SPECT exams, have a diagnostic accuracy similar to that of hematocrit for the detection of anemia and may allow discriminating different anemia severities

Frequency and intensity of [18F]-PSMA-1007 uptake after COVID-19 vaccination in clinical PET

Objectives: To assess the frequency and intensity of [18F]-prostate-specific membrane antigen (PSMA)-1007 axillary uptake in lymph nodes ipsilateral to COVID-19 vaccination with BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) in patients with prostate cancer referred for oncological [18F]-PSMA positron emission tomography (PET)/CT or PET/MR imaging. Methods: 126 patients undergoing [18F]-PSMA PET/CT or PET/MR imaging were retrospectively included. [18F]-PSMA activity (maximum standardized uptake value) of ipsilateral axillary lymph nodes was measured and compared with the non-vaccinated contralateral side and with a non-vaccinated negative control group. [18F]-PSMA active lymph node metastases were measured to serve as quantitative reference. Results: There was a significant difference in maximum standardized uptake value in ipsilateral and compared to contralateral axillary lymph nodes in the vaccination group (n = 63, p < 0.001) and no such difference in the non-vaccinated control group (n = 63, p = 0.379). Vaccinated patients showed mildly increased axillary lymph node [18F]-PSMA uptake as compared to non-vaccinated patients (p = 0.03). [18F]-PSMA activity of of lymph node metastases was significantly higher (p < 0.001) compared to axillary lymph nodes of vaccinated patients. Conclusion: Our data suggest mildly increased [18F]-PSMA uptake after COVID-19 vaccination in ipsilateral axillary lymph nodes. However, given the significantly higher [18F]-PSMA uptake of prostatic lymph node metastases compared to "reactive" nodes after COVID-19 vaccination, no therapeutic and diagnostic dilemma is to be expected. Advances in knowledge: No specific preparations or precautions (e.g. adaption of vaccination scheduling) need to be undertaken in patients undergoing [18F]-PSMA PET imaging after COVID-19 vaccination

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification

BACKGROUND Deep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative reconstruction (IR) algorithms for computed tomography (CT) image reconstruction. The aim of this study was to evaluate the effect of DLIR on image quality and quantification of coronary artery calcium (CAC) in comparison to FBP. METHODS One hundred patients were consecutively enrolled. Image quality-associated variables (noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)) as well as CAC-derived parameters (Agatston score, mass, and volume) were calculated from images reconstructed by using FBP and three different strengths of DLIR (low (DLIR_L), medium (DLIR_M), and high (DLIR_H)). Patients were stratified into 4 risk categories according to the Coronary Artery Calcium - Data and Reporting System (CAC-DRS) classification: 0 Agatston score (very low risk), 1-99 Agatston score (mildly increased risk), Agatston 100-299 (moderately increased risk), and ≥ 300 Agatston score (moderately-to-severely increased risk). RESULTS In comparison to standard FBP, increasing strength of DLIR was associated with a significant and progressive decrease of image noise (p < 0.001) alongside a significant and progressive increase of both SNR and CNR (p < 0.001). The use of incremental levels of DLIR was associated with a significant decrease of Agatston CAC score and CAC volume (p < 0.001), while mass score remained unchanged when compared to FBP (p = 0.232). The underestimation of Agatston CAC led to a CAC-DRS misclassification rate of 8%. CONCLUSION DLIR systematically underestimates Agatston CAC score. Therefore, DLIR should be used cautiously for cardiovascular risk assessment. KEY POINTS • In coronary artery calcium imaging, the implementation of deep learning image reconstructions improves image quality, by decreasing the level of image noise. • Deep learning image reconstructions systematically underestimate Agatston coronary artery calcium score. • Deep learning image reconstructions should be used cautiously in clinical routine to measure Agatston coronary artery calcium score for cardiovascular risk assessment