INCIDENTAL FINDING OF INTERRUPTED AORTIC ARCH IN AN ADULT PATIENT UNDERGOING URGENT PERCUTANEOUS CORONARY INTERVENTION

Interrupted Aortic Arch (IAA) is a rare congenital abnormality characterized by a complete discontinuity of the aortic lumen, usually located after the origin of the left subclavian artery. IAA is mainly diagnosed during childhood and has an extremely high mortality rate if left untreated. Therefore, only a few cases have been diagnosed in adulthood. We report the case of a patient with Non-ST Segment Elevation Myocardial Infarction (NSTEMI) and unknown IAA abnormality, who underwent urgent percutaneous coronary angioplasty (PCI). It was not possible to reach ascending aorta from the right radial artery because of the presence of tangled arteries connecting the prevertebral subclavian segment to the descending aorta. PCI was completed successfully through the left radial artery. A post-procedural Angio-CT scan confirmed the Aortic Arch interruption. The presented case highlights the crucial role of a multi-imaging modality approach for those patients with such congenital abnormalities before undergoing PCI

Dietary Regimens Modify Early Onset of Obesity in Mice Haploinsufficient for Rai1

Smith-Magenis syndrome is a complex genomic disorder in which a majority of individuals are obese by adolescence. While an interstitial deletion of chromosome 17p11.2 is the leading cause, mutation or deletion of the RAI1 gene alone results in most features of the disorder. Previous studies have shown that heterozygous knockout of Rai1 results in an obese phenotype in mice and that Smith-Magenis syndrome mouse models have a significantly reduced fecundity and an altered transmission pattern of the mutant Rai1 allele, complicating large, extended studies in these models. In this study, we show that breeding C57Bl/6J Rai1+/−mice with FVB/NJ to create F1 Rai1+/− offspring in a mixed genetic background ameliorates both fecundity and Rai1 allele transmission phenotypes. These findings suggest that the mixed background provides a more robust platform for breeding and larger phenotypic studies. We also characterized the effect of dietary intake on Rai1+/− mouse growth during adolescent and early adulthood developmental stages. Animals fed a high carbohydrate or a high fat diet gained weight at a significantly faster rate than their wild type littermates. Both high fat and high carbohydrate fed Rai1+/− mice also had an increase in body fat and altered fat distribution patterns. Interestingly, Rai1+/− mice fed different diets did not display altered fasting blood glucose levels. These results suggest that dietary regimens are extremely important for individuals with Smith- Magenis syndrome and that food high in fat and carbohydrates may exacerbate obesity outcomes

Fuzzy clustering with entropy regularization for interval-valued data with an application to scientific journal citations

In recent years, the research of statistical methods to analyze complex structures of data has increased. In particular, a lot of attention has been focused on the interval-valued data. In a classical cluster analysis framework, an interesting line of research has focused on the clustering of interval-valued data based on fuzzy approaches. Following the partitioning around medoids fuzzy approach research line, a new fuzzy clustering model for interval-valued data is suggested. In particular, we propose a new model based on the use of the entropy as a regularization function in the fuzzy clustering criterion. The model uses a robust weighted dissimilarity measure to smooth noisy data and weigh the center and radius components of the interval-valued data, respectively. To show the good performances of the proposed clustering model, we provide a simulation study and an application to the clustering of scientific journals in research evaluation

Feed particle size evaluation: conventional approach versus digital holography based image analysis

The aim of this study was to evaluate the application of image analysis approach based on digital holography in defining particle size in comparison with the sieve shaker method (sieving method) as reference method. For this purpose ground corn meal was analyzed by a sieve shaker Retsch VS 1000 and by image analysis approach based on digital holography. Particle size from digital holography were compared with results obtained by screen (sieving) analysis for each of size classes by a cumulative distribution plot. Comparison between particle size values obtained by sieving method and image analysis indicated that values were comparable in term of particle size information, introducing a potential application for digital holography and image analysis in feed industry

Cancer pain management in an oncological ward in a comprehensive cancer center with an established palliative care unit.

Abstract BACKGROUND: This survey was performed to draw information on pain prevalence, intensity, and management from a sample of patients who were admitted to an oncologic center where a palliative care unit (PCU) has been established for 13 years. METHODS: Cross-sectional survey in an oncological department performed 1 day per month for six consecutive months. RESULTS: Of the 385 patients, 69.1, 19.2, 8.6, and 3.1 % had no pain, mild, moderate, and severe pain, respectively. Inpatients and patients with a low Karnofsky score showed higher levels of pain intensity (p < 0.0005). One hundred twenty-eight patients with pain or receiving analgesics were analyzed for pain management index (PMI). Only a minority of patients had negative PMI score, which was statistically associated with inpatient admission (p = 0.011). Fifty of these 128 patients had breakthrough pain (BTP), and all of them were receiving some medication for BTP. CONCLUSION: It is likely that the presence of PCU team providing consultation, advices, and cultural pressure, other than offering admissions for difficult cases had a positive impact on the use of analgesics, as compared with previous similar surveys performed in oncological setting, where a PCU was unavailable. This information confirms the need of the presence of a PCU in a high volume oncological department

Screening and Management of Coronary Artery Disease in Kidney Transplant Candidates

Cardiovascular disease (CVD) is a major cause of morbidity and mortality in patients with chronic kidney disease (CKD), especially in end-stage renal disease (ESRD) patients and during the first year after transplantation. For these reasons, and due to the shortage of organs available for transplant, it is of utmost importance to identify patients with a good life expectancy after transplant and minimize the transplant peri-operative risk. Various conditions, such as severe pulmonary diseases, recent myocardial infarction or stroke, and severe aorto-iliac atherosclerosis, need to be ruled out before adding a patient to the transplant waiting list. The effectiveness of systematic coronary artery disease (CAD) treatment before kidney transplant is still debated, and there is no universal screening protocol, not to mention that a nontailored screening could lead to unnecessary invasive procedures and delay or exclude some patients from transplantation. Despite the different clinical guidelines on CAD screening in kidney transplant candidates that exist, up to today, there is no worldwide universal protocol. This review summarizes the key points of cardiovascular risk assessment in renal transplant candidates and faces the role of noninvasive cardiovascular imaging tools and the impact of coronary revascularization versus best medical therapy before kidney transplant on a patient’s cardiovascular outcome

Network analysis of synovial RNA sequencing identifies gene-gene interactions predictive of response in rheumatoid arthritis

Abstract Background To determine whether gene-gene interaction network analysis of RNA sequencing (RNA-Seq) of synovial biopsies in early rheumatoid arthritis (RA) can inform our understanding of RA pathogenesis and yield improved treatment response prediction models. Methods We utilized four well curated pathway repositories obtaining 10,537 experimentally evaluated gene-gene interactions. We extracted specific gene-gene interaction networks in synovial RNA-Seq to characterize histologically defined pathotypes in early RA and leverage these synovial specific gene-gene networks to predict response to methotrexate-based disease-modifying anti-rheumatic drug (DMARD) therapy in the Pathobiology of Early Arthritis Cohort (PEAC). Differential interactions identified within each network were statistically evaluated through robust linear regression models. Ability to predict response to DMARD treatment was evaluated by receiver operating characteristic (ROC) curve analysis. Results Analysis comparing different histological pathotypes showed a coherent molecular signature matching the histological changes and highlighting novel pathotype-specific gene interactions and mechanisms. Analysis of responders vs non-responders revealed higher expression of apoptosis regulating gene-gene interactions in patients with good response to conventional synthetic DMARD. Detailed analysis of interactions between pairs of network-linked genes identified the SOCS2/STAT2 ratio as predictive of treatment success, improving ROC area under curve (AUC) from 0.62 to 0.78. We identified a key role for angiogenesis, observing significant statistical interactions between NOS3 (eNOS) and both CAMK1 and eNOS activator AKT3 when comparing responders and non-responders. The ratio of CAMKD2/NOS3 enhanced a prediction model of response improving ROC AUC from 0.63 to 0.73. Conclusions We demonstrate a novel, powerful method which harnesses gene interaction networks for leveraging biologically relevant gene-gene interactions leading to improved models for predicting treatment response

Performance of two different artificial intelligence (AI) methods for assessing carpal bone age compared to the standard Greulich and Pyle method

Purpose: Evaluate the agreement between bone age assessments conducted by two distinct machine learning system and standard Greulich and Pyle method. Materials and methods: Carpal radiographs of 225 patients (mean age 8&nbsp;years and 10&nbsp;months, SD = 3 years and 1&nbsp;month) were retrospectively analysed at two separate institutions (October 2018 and May 2022) by both expert radiologists and radiologists in training as well as by two distinct AI software programmes, 16-bit AItm and BoneXpert® in a blinded manner. Results: The bone age range estimated by the 16-bit AItm system in our sample varied between 1&nbsp;year and 1&nbsp;month and 15&nbsp;years and 8 months (mean bone age 9&nbsp;years and 5&nbsp;months SD = 3&nbsp;years and 3 months). BoneXpert® estimated bone age ranged between 8&nbsp;months and 15&nbsp;years and 7&nbsp;months (mean bone age 8&nbsp;years and 11&nbsp;months SD = 3&nbsp;years and 3&nbsp;months). The average bone age estimated by the Greulich and Pyle method was between 11&nbsp;months and 14&nbsp;years, 9&nbsp;months (mean bone age 8&nbsp;years and 4 months SD = 3&nbsp;years and 3 months). Radiologists’ assessments using the Greulich and Pyle method were significantly correlated (Pearson’s r &gt; 0.80, p &lt; 0.001). There was no statistical difference between BoneXpert® and 16-bit AItm (mean difference = − 0.19, 95%CI = (− 0.45; 0.08)), and the agreement between two measurements varies between − 3.45 (95%CI = (− 3.95; − 3.03) and 3.07 (95%CI − 3.03; 3.57). Conclusions: Both AI methods and GP provide correlated results, although the measurements made by AI were closer to each other compared to the GP method