Genetic diversity of Streptococcus suis clinical isolates from pigs and humans in Italy (2003-2007)

n/

Automatic diagnosis of newly emerged heart failure from serial electrocardiography by repeated structuring & learning procedure

Heart failure (HF) diagnosis, typically visually performed by serial electrocardiography, may be supported by machine-learning approaches. Repeated structuring & learning procedure (RS & LP) is a constructive algorithm able to automatically create artificial neural networks (ANN); it relies on three parameters, namely maximal number of hidden layers (MNL), initializations (MNI) and confirmations (MNC), arbitrarily set by the user. The aim of this study is to evaluate RS & LP robustness to varying values of parameters and to identify an optimized combination of parameter values for HF diagnosis. To this aim, the Leiden University Medical Center HF data-base was used. The database is constituted by 129 serial ECG pairs acquired in patients who experienced myocardial infarction; 48 patients developed HF at follow-up (cases), while 81 remained clinically stable (controls). Overall, 15 ANNs were created by considering 13 serial ECG features as inputs (extracted from each serial ECG pair), 2 classes as outputs (cases/controls), and varying values of MNL (1, 2, 3, 4 and 10), MNI (50, 250, 500, 1000 and 1500) and MNC (2, 5, 10, 20 and 50). The area under the curve (AUC) of the receiver operating characteristic did not significantly vary with varying parameter values (P >= 0.09). The optimized combination of parameter values, identified as the one showing the highest AUC, was obtained for MNL = 3, MNI = 500 and MNC = 50 (AUC = 86 %; ANN structure: 3 hidden layers of 14, 14 and 13 neurons, respectively). Thus, RS & LP is robust, and the optimized ANN represents a potentially useful clinical tool for a reliable auto-matic HF diagnosis.Cardiolog

Switching to dual/monotherapy determines an increase in CD8+ in HIV-infected individuals: An observational cohort study

Background: The CD4/CD8 ratio has been associated with the risk of AIDS and non-AIDS events. We describe trends in immunological parameters in people who underwent a switch to monotherapy or dual therapy, compared to a control group remaining on triple antiretroviral therapy (ART). Methods: We included patients in Icona who started a three-drug combination ART regimen from an ART-naïve status and achieved a viral load ≤ 50 copies/mL; they were subsequently switched to another triple or to a mono or double regimen. Standard linear regression at fixed points in time (12-24 months after the switch) and linear mixed model analysis with random intercepts and slopes were used to compare CD4 and CD8 counts and their ratio over time according to regimen types (triple vs. dual and vs. mono). Results: A total of 1241 patients were included; 1073 switched to triple regimens, 104 to dual (72 with 1 nucleoside reverse transcriptase inhibitor (NRTI), 32 NRTI-sparing), and 64 to monotherapy. At 12 months after the switch, for the multivariable linear regression the mean change in the log10 CD4/CD8 ratio for patients on dual therapy was -0.03 (95% confidence interval (CI) -0.05, -0.0002), and the mean change in CD8 count was +99 (95% CI +12.1, +186.3), taking those on triple therapy as reference. In contrast, there was no evidence for a difference in CD4 count change. When using all counts, there was evidence for a significant difference in the slope of the ratio and CD8 count between people who were switched to triple (points/year change ratio = +0.056, CD8 = -25.7) and those to dual regimen (ratio = -0.029, CD8 = +110.4). Conclusions: We found an increase in CD8 lymphocytes in people who were switched to dual regimens compared to those who were switched to triple. Patients on monotherapy did not show significant differences. The long-term implications of this difference should be ascertained

Gender differences in the use of cardiovascular interventions in HIV-positive persons; the D:A:D Study

Peer reviewe

Introduzione alla statistica.

Decrizione tratta dalla prefazione del volume. - La perdurante fase di \u201csviluppo inflazionario\u201d del settore informatico, se da un lato ha consentito l\u2019approccio verso forme di analisi sino ad un recente passato difficilmente praticabili, al contempo ha esteso l\u2019accessibilit\ue0 alle analisi stesse, sempre pi\uf9 raramente confinate nella sfera dei soli statistici professionisti. In particolare, nel campo della biostatistica la delega ai microprocessori ed agli applicativi software della fase computazionale ha indotto un progressivo spostamento di attenzione sul come gestire e rappresentare adeguatamente i dati disponibili, nonch\ue9 sulla scelta dei test pi\uf9 appropriati da selezionare in relazione alla natura del campione ed alle ipotesi da verificare. Tale scenario, nel creare un\u2019eterogenea platea di potenziali gestori di dati ed utilizzatori/fruitori di metodologie statistiche, ha reso ancora pi\uf9 pressante l\u2019obiettivo di pervenire ad una piattaforma minima di conoscenze in grado di assicurare un consapevole e produttivo "statistical thinking". Obiettivo indirettamente confermato dalla semplice constatazione dell\u2019impossibilit\ue0 di pubblicare in ambito internazionale i risultati di ricerche biomediche non adeguatamente supportate a livello statistico, o dall\u2019esigenza per strutture quali il laboratorio d\u2019analisi di un personale con appropriata compliance verso il data management e le tecniche statistiche di controllo e confronto delle procedure analitiche. Il presente volume di introduzione alla statistica, nel pieno rispetto della titolazione, si propone quindi come un\u2019esperienza assolutamente preliminare per una personale esplorazione di un territorio affascinante ma altres\uec ricco di insidie, ambiguit\ue0 e complessit\ue0 irriducibili. Il lettore che trover\ue0 crescente interesse per i contenuti della statistica non potr\ue0 evitare di acquisire la progressiva consapevolezza di come tale disciplina, nel proporsi di raccogliere, analizzare e interpretare informazioni direttamente espresse o convertibili in forma numerica, di fatto rappresenti un potente strumento di \u201cdecriptazione\u201d di realt\ue0 o fenomeni ignorati o latenti, quando non anche armamentario decisivo per la destrutturazione di valutazioni od opinioni costruite sul pregiudizio di aspettative o categorie morali, su dogmi antiscientifici in luogo di un\u2019analisi asettica ed oggettiva delle evidenze disponibili. Il manuale \ue8 completato da due Appendici di interesse generale, dedicate rispettivamente ad una breve rassegna delle principali risorse statistiche disponibili in Internet e ad un ampio e variegato glossario statistico. Quest\u2019ultimo \ue8 inteso sia come supporto ed in alcuni casi approfondimento al testo, sia come \u201carea di scoperta\u201d, all\u2019interno del quale si collocano voci e concetti non trattati nel testo, che idealmente vorrebbero contribuire a quell\u2019\u201cinnesco motivazionale\u201d, a quella inaugurazione di un personale e durevole percorso di approfondimento della disciplina che costituisce il principale obiettivo di una \u201cIntroduzione alla Statica\u201d realisticamente costruttiva

Assenza di correlazione statistica tra eterodimeri diabetogeni HLA-DQ e diabete di tipo 2: Analisi familiare.

Type 2 diabetes is a multifactorial disease with a polygenic inheritance and environmental factors contributing to its clinical expression. The search for the genetic determinants of type 2 diabetes has become possible by comparing in groups of patients and healthy controls from various populations the frequency of the different alleles of polymorphic markers of various candidate genes. Among them, unlike in type 1 diabetes, the role of specific HLA class II genes is not clear. We studied 8 families with high incidence of type 2 diabetes in which at least two probands were affected by the disease. The therapy consisted in a specific diet and the intake of hypoglicemic drugs. Amongst the 8 families 40 subjects were selected. Of these, 5 males and 19 females were affected by type 2 diabetes with no prevalence of type 1 diabetes. HLA-DQA1 and DQB1 alleles were determined with 52 healthy controls by PCRSSO and PCR-SSP techniques respectively. None of their alleles was associated to either susceptibility or protection. In conclusion, unlike in type 1 diabetes there was no statistically significant correlation between susceptible a- f DQ eterodimers and the type 2 diabetes status