Aims
To investigate the morphological and molecular characteristics of Leydig cell tumours (LCTs) of the testis for the identification of cases that may metastasise.
Methods and results
Six ...parameters for a predictive model of the metastatic risk were evaluated in 37 benign and 14 malignant LCTs of the testis LCT Scaled Score (LeSS). The tumour size (benign LCTs, mean 13.3 mm; malignant LCTs, mean 44 mm) (P < 0.001) and five other parameters (infiltrative margins, necrosis, vascular invasion, mitotic count, and nuclear atypia) showed significant differences (Wilcoxon's test, P < 0.001). Eight metastatic LCTs and one benign LCT had infiltrative margins. Foci of coagulative necrosis occurred in 10 metastatic LCTs, whereas vascular invasion was identified in nine of 14 metastatic LCTs and none of 37 benign LCTs. Benign LCTs showed <2 mitoses/10 high‐power fields (HPFs), whereas a high mitotic count (range, 3–50 mitoses/10 HPFs) was a feature of malignant LCTs. These parameters were selected by use of an inferential analysis based on univariate logistic regression models to develop a score. A LeSS of <4 correctly identified all histologically and clinically benign LCTs. A LeSS of ≥4 correctly identified all malignant LCTs. MDM2 and CDK4 immunostains were applied in all 51 cases: benign LCTs were negative; three of 11 malignant LCTs (27%) showed strong and diffuse immunopositivity and high levels of MDM2 and CDK4 amplification as determined with fluorescence in‐situ hybridisation analysis and next‐generation sequencing.
Conclusion
We provide a new tool, the LeSS, for the prediction of malignant behaviour in LCTs.
In this article, we address the problem of mining and analyzing multivariate functional data. That is, data where each observation is a set of possibly correlated functions. Complex data of this kind ...is more and more common in many research fields, particularly in the biomedical context. In this work, we propose and apply a new concept of depth measure for multivariate functional data. With this new depth measure it is possible to generalize robust statistics, such as the median, to the multivariate functional framework, which in turn allows the application of outlier detection, boxplots construction, and nonparametric tests also in this more general framework. We present an application to Electrocardiographic (ECG) signals.
Cardiovascular ischaemic diseases are one of the main causes of death all over the world. In this class of pathologies, a quick diagnosis is essential for a good prognosis in reperfusive treatment. ...In particular, an automatic classification procedure based on statistical analysis of teletransmitted electrocardiograph ('ECG') traces would be very helpful for an early diagnosis. This work presents an analysis of ECG traces, either physiological or pathological, of patients whose 12-lead prehospital ECG has been sent to the 118 Dispatch Center in Milan by life-support personnel. The statistical analysis starts with a preprocessing step, where functional data are reconstructed from noisy observations and biological variability is removed by a non-linear registration procedure. Then, a multivariate functional k-means clustering procedure is carried out on reconstructed and registered ECGs and their first derivatives. Hence, a new semi-automatic diagnostic procedure, based solely on the ECG morphology, is proposed to classify ECG traces; finally, the performance of this classification method is evaluated.
The CMS electromagnetic calorimeter aims at providing high precision calorimetry at the large madron collider (LHC). It consists of about 75.000 lead tungstate (PbWO 4 ) crystals that have to operate ...reliably for at least 10 years, in a high radiation environment. In order to profit fully from the very good intrinsic energy resolution of the crystals, severe requirements on their temperature stability must be satisfied. Another challenge is given by the high data rates to be sustained by the readout electronics. With more than a half of the barrel modules produced, the calorimeter is well into its production phase. A large effort was devoted to optimize the integration between mechanics, cooling and readout electronics. The performance of the first modules has been tested in an electron beam, to validate the monitoring system and the calibration strategy. Very satisfactory results were achieved, in complete agreement with the goals of ECAL. An overview of the calorimeter design and of its construction status will be given, as well as the results from the testbeam measurements and the predicted performance at the LHC.
In this paper, we propose a generalized functional linear regression model for a binary outcome indicating the presence/absence of a cardiac disease with multivariate functional data among the ...relevant predictors. In particular, the motivating aim is the analysis of electrocardiographic traces of patients whose pre-hospital electrocardiogram (ECG) has been sent to 118 Dispatch Center of Milan (the Italian free-toll number for emergencies) by life support personnel of the basic rescue units. The statistical analysis starts with a preprocessing of ECGs treated as multivariate functional data. The signals are reconstructed from noisy observations. The biological variability is then removed by a nonlinear registration procedure based on landmarks. Thus, in order to perform a data-driven dimensional reduction, a multivariate functional principal component analysis is carried out on the variance-covariance matrix of the reconstructed and registered ECGs and their first derivatives. We use the scores of the Principal Components decomposition as covariates in a generalized linear model to predict the presence of the disease in a new patient. Hence, a new semi-automatic diagnostic procedure is proposed to estimate the risk of infarction (in the case of interest, the probability of being affected by Left Bundle Brunch Block). The performance of this classification method is evaluated and compared with other methods proposed in literature. Finally, the robustness of the procedure is checked via leave-j-out techniques.
Abstract Background The relative risk of developing idiopathic PD is 1.5 times greater in men than in women, but an increased female prevalence in LRRK2-carriers has been described in the Ashkenazi ...Jewish population. We report an update about the frequency of major LRRK2 mutations in a large series of consecutive patients with Parkinson's disease (PD), including extensive characterization of clinical features. In particular, we investigated gender-related differences in motor and non-motor symptoms in the LRRK2 population. Methods 2976 unrelated consecutive Italian patients with degenerative Parkinsonism were screened for mutations on exon 41 (G2019S, I2020T) and a subgroup of 1190 patients for mutations on exon 31 (R1441C/G/H). Demographic and clinical features were compared between LRRK2-carriers and non-carriers, and between male and female LRRK2 mutation carriers. Results LRRK2 mutations were identified in 40 of 2523 PD patients (1.6%) and not in other primary parkinsonian syndromes. No major clinical differences were found between LRRK2-carriers and non-carriers. We found a novel I2020L missense variant, predicted to be pathogenic. Female gender was more common amongst carriers than non-carriers (57% vs. 40%; p = 0.01), without any gender-related difference in clinical features. Family history of PD was more common in women in the whole PD group, regardless of their LRRK2 status. Conclusions PD patients with LRRK2 mutations are more likely to be women, suggesting a stronger genetic load compared to idiopathic PD. Further studies are needed to elucidate whether there is a different effect of gender on the balance between genetic and environmental factors in the pathogenesis of PD.
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