Pan-Cancer Analysis Identifies MNX1 and Associated Antisense Transcripts as Biomarkers for Cancer

The identification of diagnostic and prognostic biomarkers is a major objective in improving clinical outcomes in cancer, which has been facilitated by the availability of high-throughput gene expression data. A growing interest in non-coding genomic regions has identified dysregulation of long non-coding RNAs (lncRNAs) in several malignancies, suggesting a potential use as biomarkers. In this study, we leveraged data from large-scale sequencing projects to uncover the expression patterns of the MNX1 gene and its associated lncRNAs MNX1-AS1 and MNX1-AS2 in solid tumours. Despite many reports describing MNX1 overexpression in several cancers, limited studies exist on MNX1-AS1 and MNX1-AS2 and their potential as biomarkers. By employing clustering methods to visualise multi-gene relationships, we identified a discriminative power of the three genes in distinguishing tumour vs. normal samples in several cancers of the gastrointestinal tract and reproductive systems, as well as in discerning oesophageal and testicular cancer histological subtypes. Notably, the expressions of MNX1 and its antisenses also correlated with clinical features and endpoints, uncovering previously unreported associations. This work highlights the advantages of using combinatory expression patterns of non-coding transcripts of differentially expressed genes as clinical evaluators and identifies MNX1, MNX1-AS1, and MNX1-AS2 expressions as robust candidate biomarkers for clinical applicationsD.R. is the recipient of a Kidscan funded PhD studentship and partly supported by Brunel University Londo

Identification of DC thermal steady-state differential inductance of ferrite power inductors

In this paper, we propose a method for the identification of the differential inductance of saturable ferrite inductors adopted in DC–DC converters, considering the influence of the operating temperature. The inductor temperature rise is caused mainly by its losses, neglecting the heating contribution by the other components forming the converter layout. When the ohmic losses caused by the average current represent the principal portion of the inductor power losses, the steady-state temperature of the component can be related to the average current value. Under this assumption, usual for saturable inductors in DC–DC converters, the presented experimental setup and characterization method allow identifying a DC thermal steady-state differential inductance profile of a ferrite inductor. The curve is obtained from experimental measurements of the inductor voltage and current waveforms, at different average current values, that lead the component to operate from the linear region of the magnetization curve up to the saturation. The obtained inductance profile can be adopted to simulate the current waveform of a saturable inductor in a DC–DC converter, providing accurate results under a wide range of switching frequency, input voltage, duty cycle, and out-put current values

Data-Driven Constraint Handling in Multi-Objective Inductor Design

This paper analyses the multi-objective design of an inductor for a DC-DC buck converter. The core volume and total losses are the two competing objectives, which should be minimised while satisfying the design constraints on the required differential inductance profile and the maximum overheating. The multi-objective optimisation problem is solved by means of a population-based metaheuristic algorithm based on Artificial Immune Systems (AIS). Despite its effectiveness in finding the Pareto front, the algorithm requires the evaluation of many candidate solutions before converging. In the case of the inductor design problem, the evaluation of a configuration is time-consuming. In fact, a non-linear iterative technique (fixed point) is needed to obtain the differential inductance profile of the configuration, as it may operate in conditions of partial saturation. However, many configurations evaluated during an optimisation do not comply with the design constraint, resulting in expensive and unnecessary calculations. Therefore, this paper proposes the adoption of a data-driven surrogate model in a pre-selection phase of the optimisation. The adopted model should classify newly generated configurations as compliant or not with the design constraint. Configurations classified as unfeasible are disregarded, thus avoiding the computational burden of their complete evaluation. Interesting results have been obtained, both in terms of avoided configuration evaluations and the quality of the Pareto front found by the optimisation procedure

One-loop calculations of hyperon polarizabilities under the large N_c consistency condition

The spin-averaged electromagnetic polarizabilities of the hyperons $\Lambda$ and $\Sigma$ are calculated within the one-loop approximation by use of the dispersion theory. The photon and meson couplings to hyperons are determined so as to satisfy the large N_c consistency condition. It is shown that in order for the large N_c consistency condition to hold exotic hyperon states such as $\Sigma^{**}$ with I=2 and J=3/2 are required in the calculation of the magnetic polarizability of the $\Sigma$ state.Comment: 17 pages, REVTeX, no figure

Neonatal screening for congenital hypothyroidism in an Italian Centre: a 5-years real-life retrospective study

Introduction: Congenital hypothyroidism is an endocrine disease with a significant incidence in the general population (1:2000–1:3000 newborns in Italy) and a different geographical distribution, partially explained by endemic iodine deficiency, genetic traits and autoimmune thyroid diseases. Objectives: Aims of this study are: to evaluate the incidence of positive neonatal blood spot screening for CH in western Sicily, identified by the screening centre of the Children Hospital “G. Di Cristina”, ARNAS, Palermo; to evaluate the impact of a lower TSH cutoff in the neonatal blood spot screening for CH. Materials and methods: The TSH threshold of the neonatal screening was established as ≥6 mU/L of whole blood. We analysed the screening centre data in the period January 2013–April 2018, for a total number of 85.373 babies (45.7% males; 54.3% females). Results: 4.082 Babies (4.8%) required a second screening. Among these, 372 (0.44%) were out of range. The diagnosis of congenital hypothyroidism (CH) was confirmed in 182 babies (0.21%). 77/372 newborns (20.7%) with confirmed high TSH levels showed whole blood TSH levels ≥6 - < 7 mU/L. In synthesis, 48.9% of the out of range re-testing had a confirmed diagnosis of CH. Conclusion: The reduction of TSH cutoff to 6 mU/L allowed to identify 77/372 neonates (20.7%) with confirmed out of range TSH, otherwise not recruited by the previously employed TSH cutoff

Preliminary investigation of the antioxidant, anti-diabetic, and anti-inflammatory activity of Enteromorpha intestinalis extracts

Marine algae are a promising source of potent bioactive agents against oxidative stress, diabetes, and inflammation. However, the possible therapeutic effects of many algal metabolites have not been exploited yet. In this regard, we explored the therapeutic potential of Enteromorpha intestinalis extracts obtained from methanol, ethanol, and hexane, in contrasting oxidative stress. The total phenolic (TPC) and flavonoids (TFC) content were quantified in all extracts, with ethanol yielding the best values (about 60 and 625 mg of gallic acid and rutin equivalents per gram of extract, respectively). Their antioxidant potential was also assessed through DPPH•, hydroxyl radical, hydrogen peroxide, and superoxide anion scavenging assays, showing a concentration-dependent activity which was greater in the extracts from protic and more polar solvents. The α-amylase and α-glucosidase activities were estimated for checking the antidiabetic capacity, with IC50 values of about 3.8 μg/mL for the methanolic extract, almost as low as those obtained with acarbose (about 2.8 and 3.3 μg/mL, respectively). The same extract also showed remarkable anti-inflammatory effect, as determined by hemolysis, protein denaturation, proteinase and lipoxygenase activity assays, with respectable IC50 values (about 11, 4, 6, and 5 μg/mL, respectively), also in comparison to commercially used drugs, such as acetylsalicylic acid

Uterine mesenchymal tumors: development and preliminary results of a magnetic resonance imaging (MRI) diagnostic algorithm

Purpose: The aim of our study is to propose a diagnostic algorithm to guide MRI findings interpretation and malignancy risk stratification of uterine mesenchymal masses with a multiparametric step-by-step approach. Methods: A non-interventional retrospective multicenter study was performed: Preoperative MRI of 54 uterine masses was retrospectively evaluated. Firstly, the performance of MRI with monoparametric and multiparametric approach was assessed. Reference standard for final diagnosis was surgical pathologic result (n = 53 patients) or at least 1-year MR imaging follow-up (n = 1 patient). Subsequently, a diagnostic algorithm was developed for MR interpretation, resulting in a Likert score from 1 to 5 predicting risk of malignancy of the uterine lesion. The accuracy and reproducibility of the MRI scoring system were then tested: 26 preoperative pelvic MRI were double-blind evaluated by a senior (SR) and junior radiologist (JR). Diagnostic performances and the agreement between the two readers with and without the application of the proposed algorithm were compared, using histological results as standard reference. Results: Multiparametric approach showed the best diagnostic performance in terms of accuracy (94.44%,) and specificity (97.56%). DWI was confirmed as the most sensible parameter with a relative high specificity: low ADC values (mean 0.66) significantly correlated to uterine sarcomas diagnosis (p < 0.01). Proposed algorithm allowed to improve both JR and SR performance (algorithm-aided accuracy 88.46% and 96%, respectively) and determined a significant increase in inter-observer agreement, helping even the less-experienced radiologist in this difficult differential diagnosis. Conclusions: Uterine leiomyomas and sarcomas often show an overlap of clinical and imaging features. The application of a diagnostic algorithm can help radiologists to standardize their approach to a complex myometrial mass and to easily identify suspicious MRI features favoring malignancy

High-order Spatio-temporal Schemes for Coupled, Multi-physics Reactor Simulations

This report summarizes the work done in the summer of 08 by the Ph.D. student Vijay Mahadevan. The main focus of the work was to coupled 3-D neutron difusion to 3-D heat conduction in parallel with accuracy greater than or equal to 2nd order in space and time. Results show that the goal was attained