[Ag(PcL)]-Catalysed Domino Approach to 6-Substituted Benzoxazino Isoquinolines

In this paper, we describe a new silver catalysed domino approach to 6-substituted benzoxazino isoquinolines starting from 2-alkynylbenzaldehydes and 1-substituted-(2-aminophenyl)methanols. The strategy is characterized by good reaction yields, and can be performed at room temperature as well as under heating (conventional or dielectric) in different reaction times. Best results have been obtained by using silver complexes of macrocyclic pyridine-containing ligands (PcL) as catalysts. The stereoselectivity of the transformation has been investigated by using chiral reaction partners and chiral catalyst, but unfortunately, modest stereoselectivities has been achieved. On the other hand, this approach represents an alternative synthetic strategy for the preparation of 6-substituted benzoxazino isoquinolines, which are the key scaffold of some compounds endowed of biological activity

Autoimmune polyendocrine syndromes in the pediatric age

Autoimmune polyendocrine syndromes (APSs) encompass a heterogeneous group of rare diseases characterized by autoimmune activity against two or more endocrine or non-endocrine organs. Three types of APSs are reported, including both monogenic and multifactorial, heterogeneous disorders. The aim of this manuscript is to present the main clinical and epidemiological characteristics of APS-1, APS-2, and IPEX syndrome in the pediatric age, describing the mechanisms of autoimmunity and the currently available treatments for these rare conditions

Sexual developmental disorders in pediatrics

Disorders of sex development (DSD) are a heterogeneous group of pathologies that result in an alteration in sex determination or differentiation. DSD are estimated to affect 1: 4,500 newborns and according to the 2006 Chicago Consensus classification, DSD can be divided into three categories: those with a 46 XX karyotype, those with a 46 XY karyotype and those relating to sex chromosomes. It is crucial to correctly identify the pathology already in the first days of life to direct the patient and his family to the best path of care. For this reason, the role of the pediatrician is fundamental in the correct identification of the clinical picture and in supporting the family during the long process that involves the management of these patients. To make a diagnosis, it is necessary to follow a path led by a multidisciplinary team that includes several steps such as the execution of the genetic analysis, the evaluation with diagnostic imaging methods and laboratory evaluations. The therapeutic management, on the other hand, is still very complex even if in recent years we have moved from an attitude of early gender reassignment to an approach of watchful waiting to let the patient choose when she/he is mature enough to do so, which gender she/he feels to belong. It should not be forgotten that throughout this process the pediatrician must be both supportive and clinically active in the management of the child and his family

The potential role of MR based radiomic biomarkers in the characterization of focal testicular lesions

How to differentiate with MRI-based techniques testicular germ (TGCTs) and testicular non-germ cell tumors (TNGCTs) is still under debate and Radiomics may be the turning key. Our purpose is to investigate the performance of MRI-based Radiomics signatures for the preoperative prediction of testicular neoplasm histology. The aim is twofold: (i), differentiating TGCTs and TNGCTs status and (ii) differentiating seminomas (SGCTs) from non-seminomatous (NSGCTs). Forty-two patients with pathology-proven testicular neoplasms and referred for pre-treatment MRI, were retrospectively enrolled. Thirty-two out of 44 lesions were TGCTs. Twelve out of 44 were TNGCTs or other histologies. Two radiologists segmented the volume of interest on T2-weighted images. Approximately 500 imaging features were extracted. Least Absolute Shrinkage and Selection Operator (LASSO) was applied as method for variable selection. A linear model and a linear support vector machine (SVM) were trained with selected features to assess discrimination scores for the two endpoints. LASSO identified 3 features that were employed to build fivefold validated linear discriminant and linear SVM classifiers for the TGCT-TNGCT endpoint giving an overall accuracy of 89%. Four features were employed to build another SVM for the SGCT-SNGCT endpoint with an overall accuracy of 86%. The data obtained proved that T2-weighted-based Radiomics is a promising tool in the diagnostic workup of testicular neoplasms by discriminating germ cell from non-gem cell tumors, and seminomas from non-seminomas

Radiomics in the characterization of lipid-poor adrenal adenomas at unenhanced CT: time to look beyond usual density metrics

Objectives: In this study, we developed a radiomic signature for the classification of benign lipid-poor adenomas, which may potentially help clinicians limit the number of unnecessary investigations in clinical practice. Indeterminate adrenal lesions of benign and malignant nature may exhibit different values of key radiomics features. Methods: Patients who had available histopathology reports and a non-contrast-enhanced CT scan were included in the study. Radiomics feature extraction was done after the adrenal lesions were contoured. The primary feature selection and prediction performance scores were calculated using the least absolute shrinkage and selection operator (LASSO). To eliminate redundancy, the best-performing features were further examined using the Pearson correlation coefficient, and new predictive models were created. Results: This investigation covered 50 lesions in 48 patients. After LASSO-based radiomics feature selection, the test dataset’s 30 iterations of logistic regression models produced an average performance of 0.72. The model with the best performance, made up of 13 radiomics features, had an AUC of 0.99 in the training phase and 1.00 in the test phase. The number of features was lowered to 5 after performing Pearson’s correlation to prevent overfitting. The final radiomic signature trained a number of machine learning classifiers, with an average AUC of 0.93. Conclusions: Including more radiomics features in the identification of adenomas may improve the accuracy of NECT and reduce the need for additional imaging procedures and clinical workup, according to this and other recent radiomics studies that have clear points of contact with current clinical practice. Clinical relevance statement: The study developed a radiomic signature using unenhanced CT scans for classifying lipid-poor adenomas, potentially reducing unnecessary investigations that scored a final accuracy of 93%. Key Points: • Radiomics has potential for differentiating lipid-poor adenomas and avoiding unnecessary further investigations. • Quadratic mean, strength, maximum 3D diameter, volume density, and area density are promising predictors for adenomas. • Radiomics models reach high performance with average AUC of 0.95 in the training phase and 0.72 in the test phase