Generation of large scale digital evaluation models via synthetic aperture radar interferometry

We investigate the possibility to generate a large-scale Digital Elevation Model by applying the Synthetic Aperture Radar interferometry technique and using tandem data acquired by the ERS-1/ERS-2 sensors. The presented study is mainly focused on the phase unwrapping step that represents the most critical point of the overall processing chain. In particular, we concentrate on the unwrapping problems related to the use of a large ERS tandem data set that, in order to be unwrapped, must be partitioned. The paper discusses the inclusion of external information (even rough) of the scene topography, the application of a region growing unwrapping technique and the insertion of possible constraints on the phase to be retrieved in order to minimize the global unwrapping errors. Our goal is the generation of a digital elevation model relative to an area of 300 km by 100km located in the southern part of Italy. Comparisons between the achieved result and a precise digital terrain model, relative to a smaller area, are also included

Problematizing the Relationship Between Cultural, Social, and Political Capital and Graduate Student Participation in a Community Engagement Professional Association

The Graduate Student Network (GradSN) brings together emerging scholars who have an interest in research on service-learning and community engagement (SLCE). In this reflective essay, we problematize the relationship between social, cultural, and economic capital and graduate student participation in the GradSN, specifically the GradSN chair role. To begin, we share the origins, process, and initial findings of a collaborative autoethnographic study that involved a group of seven past, present, and incoming chairs. Participation in this study led us to question what barriers exist for graduate student participation in the GradSN, resulting in this reflective essay. Second, we share the critically reflexive practice the three of us engaged in to interrogate our identities in relation to our chair role. Finally, we discuss the concept of full participation as a way to disrupt current structures in the GradSN, concluding with ideas for future inquiry and action

<b><i>Topoisomerase 1</i></b> Promoter Variants and Benefit from Irinotecan in Metastatic Colorectal Cancer Patients

Objective: Topoisomerase 1 (topo-1) is an important target for the treatment of metastatic colorectal cancer (CRC). The aim of the present study was to evaluate the correlation between topo-1 single-nucleotide polymorphisms (SNPs) and clinical outcome in metastatic CRC (mCRC) patients. Methods: With the use of specific software (PROMO 3.0), we performed an in silico analysis of topo-1 promoter SNPs; the rs6072249 and rs34282819 SNPs were included in the study. DNA was extracted from 105 mCRC patients treated with FOLFIRI ± bevacizumab in the first line. SNP genotyping was performed by real-time PCR. Genotypes were correlated with clinical parameters (objective response rate, progression-free survival, and overall survival). Results: No single genotype was significantly associated with clinical variables. The G allelic variant of rs6072249 topo-1 SNP is responsible for GC factor and X-box-binding protein transcription factor binding. The same allelic variant showed a nonsignificant trend toward a shorter progression-free survival (GG, 7.5 months; other genotypes, 9.3 months; HR 1.823, 95% CI 0.8904-3.734; p = 0.1). Conclusion: Further analyses are needed to confirm that the topo-1 SNP rs6072249 and transcription factor interaction could be a part of tools to predict clinical outcome in mCRC patients treated with irinotecan-based regimens

Systematic analysis of SNR in bipartite Ghost Imaging with classical and quantum light

We present a complete and exhaustive theory of signal-to-noise-ratio in bipartite ghost imaging with classical (thermal) and quantum (twin beams) light. The theory is compared with experiment for both twin beams and thermal light in a certain regime of interest

Next Generation Practitioner-Scholars Navigating Community Engagement Professional Development: A Collaborative Autoethnography

This collaborative autoethnographic research study examines the motivations, experiences, and professional outcomes of seven community engagement practitioner-scholars who served in a high-level elected position in a community engagement research association and its affiliated graduate student network. The findings highlight the role of professional associations and graduate student networks in facilitating professional development for next generation community engagement practitioner-scholars, such as supporting them in creating connections, expanding networks, developing professional identities, and cultivating cultural capital

Optimising whole body computed tomography doses for paediatric trauma patients: a Swiss retrospective analysis

We aimed to evaluate the impact of a low-dose whole-body computed tomography (WBCT) protocol on radiation doses in paediatric major trauma patients. Retrospective cohort study of paediatric trauma patients (<16 years) at a national level 1 paediatric trauma centre (PTC) over a 6 year period prior and post introduction of a low-dose WBCT protocol (2014-2019). Demographic data, patient characteristics, CT device, and exposure information including scan range, dose-length product, and volume CT dose index were collected. Effective dose (ED) and exposure parameters were compared before and after protocol introduction. Forty-eight patients underwent WBCT during the study period. Prior to introduction of the low-dose protocol (n= 18), the ED was 20.6 mSv (median 20.1 ± 5.3 mSv [range 12.5-30.7]). After introduction of the low-dose WBCT protocol (n= 30), mean ED was 4.8 mSv (median 2.6 ± 5.0 [range: 0.8-19.1]). This resulted in a reduction of 77% in mean ED (pvalue <0.001). Significant radiation dose reduction of 77% can be achieved with low-dose WBCT protocols in PTCs

Metabolomics Fingerprint Predicts Risk of Death in Dilated Cardiomyopathy and Heart Failure

BACKGROUND: Heart failure (HF) is a leading cause of morbidity and mortality worldwide. Metabolomics may help refine risk assessment and potentially guide HF management, but dedicated studies are few. This study aims at stratifying the long-term risk of death in a cohort of patients affected by HF due to dilated cardiomyopathy (DCM) using serum metabolomics via nuclear magnetic resonance (NMR) spectroscopy. METHODS: A cohort of 106 patients with HF due to DCM, diagnosed and monitored between 1982 and 2011, were consecutively enrolled between 2010 and 2012, and a serum sample was collected from each participant. Each patient underwent half-yearly clinical assessments, and survival status at the last follow-up visit in 2019 was recorded. The NMR serum metabolomic profiles were retrospectively analyzed to evaluate the patient's risk of death. Overall, 26 patients died during the 8-years of the study. RESULTS: The metabolomic fingerprint at enrollment was powerful in discriminating patients who died (HR 5.71, p = 0.00002), even when adjusted for potential covariates. The outcome prediction of metabolomics surpassed that of N-terminal pro b-type natriuretic peptide (NT-proBNP) (HR 2.97, p = 0.005). Metabolomic fingerprinting was able to sub-stratify the risk of death in patients with both preserved/mid-range and reduced ejection fraction [hazard ratio (HR) 3.46, p = 0.03; HR 6.01, p = 0.004, respectively]. Metabolomics and left ventricular ejection fraction (LVEF), combined in a score, proved to be synergistic in predicting survival (HR 8.09, p = 0.0000004). CONCLUSIONS: Metabolomic analysis via NMR enables fast and reproducible characterization of the serum metabolic fingerprint associated with poor prognosis in the HF setting. Our data suggest the importance of integrating several risk parameters to early identify HF patients at high-risk of poor outcomes