Salivary proteomic profile of young healthy subjects.

Background: The incidence of noncommunicable diseases (NCDs) has been rapidly ramped up worldwide. Hence, there is an urgent need to non-invasively detect NCDs possibly by exploiting saliva as a 'liquid biopsy' to identify biomarkers of the health status. Since, the absence of standardized procedures of collection/analysis and the lack of normal ranges makes the use of saliva still tricky, our purpose was to outline a salivary proteomic profile which features healthy individuals. Methods: We collected saliva samples from 19 young blood donors as reference population and the proteomic profile was investigated through mass-spectrometry. Results: We identified 1,004 proteins of whose 243 proteins were shared by all subjects. By applying a data clustering approach, we found a set of six most representative proteins across all subjects including Coronin-1A, F-actin-capping protein subunit alpha, Immunoglobulin J chain, Prosaposin, 78 kDa glucose-regulated protein and Heat shock 70 kDa protein 1A and 1B. Conclusion: All of these proteins are involved in immune system activation, cellular stress responses, proliferation, and invasion thus suggesting their use as biomarkers in patients with NCDs.

Posterior pelvic tilt is a risk factor for rectal prolapse: a propensity score matching analysis.

BACKGROUND: There is little evidence about possible effects of pelvic anatomical characteristics on proctological complications. The aim of our study was to investigate the potential correlation between sagittal pelvic position and rectal prolapse. METHODS: A study was conducted on a proctology patients and patients without any specific history of proctological disorders who were divided into two groups according to the presence or the absence of rectal prolapse. In all cases, the pelvic angle was measured with a pelvic goniometer and categorized as posterior (< 10°), neutral (10°-15°), and anterior (> 15°). To minimize effects of potential confounders in the analysis, 3:1 nearest neighbor propensity score matching (PSM) method was implemented using age, sex, and diagnose of rectal disorders as confounding variables. RESULTS: Among the 143 screened patients, posterior tilt was more frequent in the 19 patients with rectal prolapse than in those without prolapse (42 vs. 18%; p = 0.027). This result was also confirmed in the post-PSM analysis (42 vs. 14%; p = 0.036) using 35 propensity score (PS)-matched controls compared with the rectal prolapse group. Posterior tilt was associated with an increased risk of prolapse in both the unmatched population (odds ratio = 3.37; p = 0.020) and PS-matched subset (odds ratio = 4.36; p = 0.028). CONCLUSIONS: A posterior pelvic angle was more frequently associated with the diagnosis of rectal prolapse. In both the entire population and in the PS-matched subset, posterior tilt was a significant risk factor for rectal prolapse. The easy-to-do investigation of the pelvic angle can provide several benefits in terms of rectal prolapse prevention and more precise management of post-surgical prolapse recurrence.

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) without lymph node involvement, multiple or extensive lesions, for patients refusing surgery, for patients with a poor general medical status, as adjuvant for incompletely excised lesions and/or as a palliative treatment. To date, prognostic risk factors in scalp cSCC patients are poorly characterized. OBJECTIVE: To identify patterns of patients with higher risk of postradiotherapy recurrence. METHODS: A retrospective observational study was performed on scalp cSCC patients with histological diagnosis who underwent conventional radiotherapy (50-120 kV) (between 1996 and 2008, follow-up from 1 to 140 months, median 14 months). Out of the 79 enrolled patients, 22 (27.8%) had previously undergone a surgery. Two months after radiotherapy, 66 (83.5%) patients achieved a complete remission, 6 (7.6%) a partial remission, whereas 2 (2.5%) proved non-responsive to the treatment and 5 cases were lost to follow-up. Demographical and clinical data were preliminarily analysed with classical descriptive statistics and with principal component analysis. All data were then re-evaluated with a machine learning-based approach using a 4th generation artificial neural networks (ANNs)-based algorithm. RESULTS: Artificial neural networks analysis revealed four scalp cSCC profiles among radiotherapy responsive patients, not previously described: namely, (i) stage T2 cSCC type, aged 70-80 years; (ii) frontal cSCC type, aged <70 years; (iii) non-recurrent nodular or nodulo-ulcerated, stage T3 cSCC type, of the vertex and treated with >60 Grays (Gy); and (iv) flat, occipital, stage T1 cSCC type, treated with 50-59 Gy. The model uncovering these four predictive profiles displayed 85.7% sensitivity, 97.6% specificity and 91.7% overall accuracy. CONCLUSIONS: Patient profiling/phenotyping with machine learning may be a new, helpful method to stratify patients with scalp cSCCs who may benefit from a RT-treatment.

Maternal estradiol and progesterone concentrations among singleton spontaneous pregnancies during the first trimester.

BACKGROUND: Pregnancy hormonal milieu represents a crucial determinant of fetal outcome. We aim to determine 17ß-estradiol (E2) and progesterone (PGT) concentrations in spontaneous pregnancies during the first trimester. In addition, we aim to determine E2 concentrations as a function of gestational age (GA) and PGT. METHODS: Between November 2015 and March 2017, 104 healthy women of at least 18 years undergoing medical consultation for voluntary interruption of pregnancy were enrolled in an observational study at University Hospital ASST Fatebenefratelli Sacco, Milan, Italy. Only singleton pregnancies between 5+0 and 13+6 weeks of gestation were eligible. First trimester ultrasound scans were performed for dating and one fasting venous blood sample was collected for E2 and PGT determinations. RESULTS: E2 and PGT concentrations steadily increased according to GA. The correlation between E2 on a logarithmic scale and PGT concentrations was expressed by the following equation, explaining 12.6% of E2 variance: logE2 = 2.57 + 0.1 × PGT, (r = 0.34, p < 0.001). By performing a multivariable linear regression analysis adjusted for variables significantly correlated with E2 concentrations, we obtained a model explaining the 53.5% of E2 variance. The final equation to determine E2 concentrations among Caucasian women was: logE2 = 1.96 + 0.01 × GA + 0.004 × PGT. CONCLUSIONS: Gestational week-specific reference intervals are reported for maternal E2 and PGT concentrations during early pregnancy, further providing a model for E2 assessment in this period. This will represent a starting point for further evaluations between twin and ART pregnancies, as well as to potentially improve pregnancy outcome and future health of the offspring.

Plasma fatty acid profile as biomarker of coronary artery disease: a pilot study using fourth generation artificial neural networks.

Many studies, focused on identifying new biomarkers for coronary artery disease (CAD) risk computation and monitoring, suggested a potential diagnostic role for fatty acids (FA). In the present study, we explored the potential diagnostic role of FA by using a data mining approach based on fourth generation artificial neural networks (ANN). Forty-one male subjects were enrolled. According to coronary angiography, 31 displayed CAD and 10 did not (non-CAD, control group). FA analysis was performed on plasma samples using a gas chromatography-mass spectrometry system and analyses were performed by an ANN method. The variables most closely related to CAD were low levels of alpha-linolenic acid, eicosapentaenoic acid, eicosatetraenoic and docosahexaenoic acids. High levels of 1,1-dimethoxyhexadecane, total dimethyl acetals and docosatetraenoic acid were related to non-CAD condition. This subset of variables, which were most closely correlated to the target diagnosis, achieved a consistent predictive rate. The average accuracy obtained was 76.5%, with 93% of sensitivity and 60% of specificity. The area under the ROC curve was equal to 0.79. In conclusion, our study highlighted the association between different plasma FA species, CAD and non-CAD conditions. The specific subset of variables could be of interest as a new diagnostic tool for CAD management.

Pregnancy risk factors related to autism: an Italian case-control study in mothers of children with autism spectrum disorders (ASD), their siblings and of typically developing children.

This study, carried out in two Italian Institutions, assesses the frequency of 27 potential autism risk factors related to pregnancy and peri- and postnatal periods by interviewing mothers who had children with autism, children with autism and one or two typically developing siblings, or only typically developing children. The clinical sample included three case groups: 73 children and adolescents with autism (Group A), 35 children and adolescents with autism (Group A1) having 45 siblings (Group B) and 96 typically developing children (Group C) matched for gender and age. Twenty-five out of 27 of risk factors presented a higher frequency in Group A in comparison with Group C and for nine of them a statistically significant difference was found. Twenty-one out of 27 of risk factors presented a higher frequency in Group A in comparison with Group B. A higher prevalence of environmental risk factors was observed in 11 risk factors in the Group A1 in comparison with Group B and for nine of them an odds ratio higher than 1.5 was found. For 13 factors there was a progressive increase in frequency going from Group C, B and A and a statistically higher prevalence of the mean number of stressful events per pregnancy was recorded in Group A when compared with Groups B and C. The results suggest that environmental, incidental phenomena and stressful life events can influence pregnancy outcome in predisposed subjects, pointing out a possible threshold effect in women who are predisposed to have suboptimal pregnancies.

Association between coffee or tea drinking and Barrett's esophagus or esophagitis: an Italian study.

BACKGROUND/OBJECTIVES: Only a few papers have treated of the relationship between Barrett's esophagus (BE) or erosive esophagitis (E) and coffee or tea intake. We evaluated the role of these beverages in BE and E occurrence. SUBJECTS/METHODS: Patients with BE (339), E (462) and controls (619) were recruited. Data on coffee and tea and other individual characteristics were collected using a structured questionnaire. RESULTS: BE risk was higher in former coffee drinkers, irrespective of levels of exposure (cup per day; ⩽1: OR=3.76, 95% CI 1.33-10.6; >1: OR=3.79, 95% CI 1.31-11.0; test for linear trend (TLT) P=0.006) and was higher with duration (>30 years: OR=4.18, 95% CI 1.43-12.3; TLT P=0.004) and for late quitters, respectively (⩽3 years from cessation: OR=5.95, 95% CI 2.19-16.2; TLT P<0.001). The risk of BE was also higher in subjects who started drinking coffee later (age >18 years: OR=6.10, 95% CI 2.15-17.3). No association was found in current drinkers, but for an increased risk of E in light drinkers (<1 cup per day OR =1.85, 95% CI 1.00-3.43).A discernible risk reduction of E (about 20%, not significant) and BE (about 30%, P<0.05) was observed in tea drinkers. CONCLUSIONS: Our data were suggestive of a reduced risk of BE and E with tea intake. An adverse effect of coffee was found among BE patients who had stopped drinking coffee. Coffee or tea intakes could be indicative of other lifestyle habits with protective or adverse impact on esophageal mucosa.

Prediction of high on-treatment platelet reactivity in clopidogrel-treated patients with acute coronary syndromes.

BACKGROUND: About 40% of clopidogrel-treated patients display high platelet reactivity (HPR). Alternative treatments of HPR patients, identified by platelet function tests, failed to improve their clinical outcomes in large randomized clinical trials. A more appealing alternative would be to identify HPR patients a priori, based on the presence/absence of demographic, clinical and genetic factors that affect PR. Due to the complexity and multiplicity of these factors, traditional statistical methods (TSMs) fail to identify a priori HPR patients accurately. The objective was to test whether Artificial Neural Networks (ANNs) or other Machine Learning Systems (MLSs), which use algorithms to extract model-like 'structure' information from a given set of data, accurately predict platelet reactivity (PR) in clopidogrel-treated patients. METHODS: A complete set of fifty-nine demographic, clinical, genetic data was available of 603 patients with acute coronary syndromes enrolled in the prospective GEPRESS study, which showed that HPR after 1month of clopidogrel treatment independently predicted adverse cardiovascular events in patients with Syntax Score >14. Data were analysed by MLSs and TSMs. ANNs identified more variables associated PR at 1month, compared to TSMs. RESULTS: ANNs overall accuracy in predicting PR, although superior to other MLSs was 63% (95% CI 59-66). PR phenotype changed in both directions in 35% of patients across the 3 time points tested (before PCI, at hospital discharge and at 1month). CONCLUSIONS: Despite their ability to analyse very complex non-linear phenomena, ANNs or MLS were unable to predict PR accurately, likely because PR is a highly unstable phenotype.

Inequalities in access to biological treatments for psoriasis: results from the Italian Psocare registry.

BACKGROUND: Limited evidence is available on the impact of socioeconomic factors on drug prescriptions for psoriasis. OBJECTIVES: To investigate factors influencing prescription of conventional vs. biological treatment for patients with psoriasis, based on the Italian Psocare registry, with a special focus on socioeconomic factors. METHODS: This was a cross-sectional study evaluating the baseline data of patients included in the Psocare registry. All of the consecutive adult patients with a diagnosis of chronic plaque psoriasis or psoriatic arthritis who were prescribed a systemic treatment for psoriasis at participating centres were included in this study. Univariate and multivariate analyses of the baseline factors associated with a biologics prescription were performed. RESULTS: From September 2005 to September 2009, 12 838 patients were identified. A multivariate analysis revealed that, among other factors, completing a level of education higher than lower secondary school and being employed as a manager or a professional were independent factors associated with a biologics prescription at entry in the registry. Additional analyses on the association between these two variables and a severe psoriasis condition [Psoriasis Area Severity Index (PASI) score > 20] revealed a significantly increasing trend of severe disease towards lower educational attainment, while unemployed patients were more likely to have a more severe condition compared with the other categories of workers. CONCLUSIONS: We documented inequalities of drug prescriptions for psoriasis in Italy, with a trend towards a higher frequency of prescription for more expensive biologics in higher socioeconomic sectors of the population.

The constellation of dietary factors in adolescent acne: a semantic connectivity map approach.

BACKGROUND: Different lifestyle and dietetic factors have been linked with the onset and severity of acne. OBJECTIVE: To assess the complex interconnection between dietetic variables and acne. METHODS: This was a reanalysis of data from a case-control study by using a semantic connectivity map approach. 563 subjects, aged 10-24 years, involved in a case-control study of acne between March 2009 and February 2010, were considered in this study. The analysis evaluated the link between a moderate to severe acne and anthropometric variables, family history and dietetic factors. Analyses were conducted by relying on an artificial adaptive system, the Auto Semantic Connectivity Map (AutoCM). RESULTS: The AutoCM map showed that moderate-severe acne was closely associated with family history of acne in first degree relatives, obesity (BMI ≥ 30), and high consumption of milk, in particular skim milk, cheese/yogurt, sweets/cakes, chocolate, and a low consumption of fish, and limited intake of fruits/vegetables. CONCLUSION: Our analyses confirm the link between several dietetic items and acne. When providing care, dermatologists should also be aware of the complex interconnection between dietetic factors and acne.

Mindfulness trait, eating behaviours and body uneasiness: a case-control study of binge eating disorder.

BACKGROUND: Binge eating disorder (BED) is a complex and multifaceted eating disorder, and the literature indicates that BED patients show greater difficulty in identifying and making sense of emotional states, and that they have limited access to emotion regulation strategies. Findings show many links between mindfulness and emotional regulation, however there has been no previous research on mindfulness traits in BED patients. METHOD: One hundred fifty BED patients (N=150: women=98, men=52; age 49.3±4.1) were matched for gender, age, marital status and educational level with 150 non-bingeing obese and 150 normal-weight subjects. All were assessed with the Five Facet Mindfulness Questionnaire (FFMQ), Binge Eating Scale (BES), Objective bulimic episodes (EDE-OBEs) and Body Uneasiness Test (BUT). For all the participants past or current meditation experience was an exclusion criteria. RESULTS: Findings showed that Mindfulness-global, Non reactivity to experience, Acting with awareness, Describing with words and Observation of experience scores were significantly lower in BED than control groups (p<0.05). However, on the mindfulness measures, the obese control group did not differ from the normal weight control group. Moreover, correlations showed that mindfulness was more widely negatively correlated with the BED's OBEs, BES and BUT-GSI scores. Meanwhile, binge eating behaviours, frequency and severity (OBEs and BES) were more negatively correlated with action (Nonreactivity- to-experience and Acting-with-awareness scores). Body Uneasiness was more negatively correlated with mental processes (Describing-with-words and Observation-ofexperience) and mindfulness features. CONCLUSION: Implications on understanding of the mechanisms underlying the development and maintenance of problematic eating in BED were considered. Moreover, clinical considerations on treatment targets of mindfulnessbased eating awareness training were discussed.

LDL oxidative modification and carotid atherosclerosis: results of a multicenter study.

OBJECTIVE: Serum LDL conjugated diene concentration is a marker of oxidative modification of LDL. We investigated the relationship between LDL conjugated dienes and cross-sectional subclinical atherosclerosis assessed by carotid IMT in high-risk subjects of a multicenter study. METHODS: Serum LDL conjugated dienes and ultrasonographically assessed carotid intima-media thickness (IMT(mean), IMT(max) and IMT(mean-max)) were available for 553 subjects from Finland, France, Italy, the Netherlands, and Sweden. RESULTS: In multivariate regression analysis, gender (p < 0.001), age (p < 0.001), systolic blood pressure (IMT(mean), p = 0.01; IMT(mean-max), p = 0.05) and serum LDL conjugated dienes (p = 0.02 for both IMT(mean) and IMT(mean-max)) were the strongest determinants of IMT variation, adjusted for study center, ultrasound videotape reader and serum LDL cholesterol. Pack-years of smoking, added into the regression model, did not destroy the significant association between increased serum LDL conjugated dienes and IMT. Ratio of LDL conjugated dienes to LDL particle cholesterol was higher in subjects of Northern recruiting centers than of Southern centers (r = 0.39, p < 0.0001). CONCLUSIONS: There was a cross-sectional association between in vivo increased LDL oxidative modification and subclinical atherosclerosis after adjustment for traditional risk factors. The subjects in Northern countries of Europe had more oxidatively modified lipids per cholesterol in LDL particle than subjects in Southern countries.

Ten years survival of FIGO stage IIIC epithelial ovarian cancer cases due to lymph node metastases only.

PURPOSE OF INVESTIGATION: In this paper the authors have analyzed the long-term survival of women with Stage III ovarian cancer due to lymph node metastasis. MATERIALS AND METHODS: This retrospective study included 27 patients with FIGO Stage IIIC epithelial ovarian carcinoma due to lymph node metastases observed consecutively at the Mangiagalli Clinic of Milan from 1982 to 2008. RESULTS: Two cases had Fallopian tube carcinoma. A total of ten recurrences were observed. Median time to recurrence was 158 months. The five-year disease-free survival (DFS) was 57.7%. The ten-year corresponding value was 53.2%. Median survival time was 158 months, with median follow-up time of 169 months. The five-year (overall survival) OS rate was 77.1%; the ten-year rate was 55.4%. CONCLUSION: Women with ovarian cancer Stage IIIC due to nodal involvement have a five-year OS of about 80% and a ten-year OS of about 50%.

A systems biology approach: new insights into fetal growth restriction using Bayesian Networks.

IL-6, IGF-II and IGFBP-2 concentrations in placental lysates were previously shown to be associated with foetal growth. This study aimed to apply a Bayesian Network (BN) model in order to investigate complex dependencies among biochemical and clinical factors and fetal growth outcome. Twenty-one Intra-Uterine Growth Restricted (IUGR) and 25 Appropriate for Gestational Age (AGA) pregnancies were followed throughout pregnancy. Information was collected on maternal and gestational age, neonatal gender, previous gynaecological history. Total protein content, IGF-II, IGFBP-1, IGFBP-2, IL-6, and TNF-alpha concentrations in placental lysates were measured, and IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IL-6 relative gene expression in placenta assessed. A BN and a hybrid forecasting system were implemented: BN revealed a key role of maternal age and TNF-alpha on IUGR and confirmed a close relationship among IGF-II, IL-6 and foetal growth. A relationship between duration of gestation, appropriateness for gestational age, and placental IL-6 concentration was also confirmed. Compared with other techniques, BN showed a better accuracy. Findings confirmed a major role of maternal age in addition to IGF-II, IL-6 and TNF-alpha in IUGR. A direct role of IGFBP-2 was not shown. BN confirmed to be useful in understanding the system's biology and graphically representing variable relationships and hierarchy, particularly where, as in IUGR, many interactions among predictors exist.

Gene-gene and gene - clinical factors interaction in acute myocardial infarction: a new detailed risk chart.

AIMS: The complex pathogenesis of acute myocardial infarction (AMI) implicates phenotypic and genetic heterogeneity. In this pilot case-control study single nucleotide polymorphism (SNP) in several inflammatory genes, such as interleukin (IL)-1beta, IL-6, IL-10, alpha-1-antichymotrypsin (ACT), tumor necrosis factor alpha (TNF)-alpha and interferon gamma (IFN)-gamma genes along with SNPs of genes regulating vascular functions (vascular endothelial growth factor; VEGF) and cholesterol synthesis (hydroxy-methyl-glutaryl CoA reductase; HMGCR) were investigated. METHODS: Patients were genotyped with RT-PCR technique and data were analyzed with a new mathematical algorithm named Auto Contractive Map. RESULTS: The Auto Contractive Map (AutoCM), was applied in AMI patients with the aim to detect and evaluate the relationships among genetic factors, clinical variables and classical risk factors. Genes were selected because their strong regulatory effect on inflammation and SNP in these gene were located in the promoter region. In the connectivity map generated by AutoCM a group of variables was directly linked with the AMI status; these were: gender (male), early age at onset (50-65 years), HMGCR gene (CC wild type genotype), IL-1betaCT, IL-6 GG and VEGF CC genotypes. This direct link suggested a possible pathogenetic association with AMI. Other genetic, clinical and phenotypic variables were associated to the disease under a statistically defined hierarchy showed in the new connectivity map generated by AutoCM. CONCLUSION: These analyses suggested that genotypes of few inflammatory genes, a SNP in HMGCR gene, middle age, gender, low HDL and diabetes were very informative variables to predict the risk of AMI.

How to predict a high rate of inappropriateness for upper endoscopy in an endoscopic centre?

BACKGROUND: Inappropriateness of upper endoscopy (EGD) indication causes decreased diagnostic yield. Our aim of was to identify predictors of appropriateness rate for EGD among endoscopic centres. METHODS: A post-hoc analysis of two multicentre cross-sectional studies, including 6270 and 8252 patients consecutively referred to EGD in 44 (group A) and 55 (group B) endoscopic Italian centres in 2003 and 2007, respectively, was performed. A multiple forward stepwise regression was applied to group A, and independently validated in group B. A <70% threshold was adopted to define inadequate appropriateness rate clustered by centre. RESULTS: discrete variability of clustered appropriateness rates among the 44 group A centres was observed (median: 77%; range: 41-97%), and a <70% appropriateness rate was detected in 11 (25%). Independent predictors of centre appropriateness rate were: percentage of patients referred by general practitioners (GP), rate of urgent examinations, prevalence of relevant diseases, and academic status. For group B, sensitivity, specificity and area under receiver operating characteristic curve of the model in detecting centres with a <70% appropriateness rate were 54%, 93% and 0.72, respectively. CONCLUSIONS: A simple predictive rule, based on rate of patients referred by GPs, rate of urgent examinations, prevalence of relevant diseases and academic status, identified a small subset of centres characterised by a high rate of inappropriateness. These centres may be presumed to obtain the largest benefit from targeted educational programs.

The I.F.A.S.T. model allows the prediction of conversion to Alzheimer disease in patients with mild cognitive impairment with high degree of accuracy.

This paper presents the results obtained with the innovative use of special types of artificial neural networks (ANNs) assembled in a novel methodology named IFAST (implicit function as squashing time) capable of compressing the temporal sequence of electroencephalographic (EEG) data into spatial invariants. The aim of this study is to test the potential of this parallel and nonlinear EEG analysis technique in providing an automatic classification of mild cognitive impairment (MCI) subjects who will convert to Alzheimer's disease (AD) with a high degree of accuracy. Eyes-closed resting EEG data (10-20 electrode montage) were recorded in 143 amnesic MCI subjects. Based on 1-year follow up, the subjects were retrospectively classified to MCI converted to AD and MCI stable. The EEG tracks were successively filtered according to four different frequency ranges, in order to evaluate the hypotheses that a specific range, corresponding to specific brain wave type, could provide a better classification (0.12 Hz, 12.2 - 29.8 Hz; 30.2 - 40 Hz, and finally Notch Filter 48 - 50 Hz). The spatial content of the EEG voltage was extracted by IFAST step-wise procedure using ANNs. The data input for the classification operated by ANNs were not the EEG data, but the connections weights of a nonlinear auto-associative ANN trained to reproduce the recorded EEG tracks. These weights represented a good model of the peculiar spatial features of the EEG patterns at scalp surface. The classification based on these parameters was binary and performed by a supervised ANN. The best results distinguishing between MCI stable and MCI/AD reached to 85.98%.(012 Hz band). And confirmed the working hypothesis that a correct automatic classification can be obtained extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG. These results suggest that this low-cost procedure can reliably distinguish eyes-closed resting EEG data in individual MCI subjects who will have different prognosis at 1-year follow up, and is promising for a large-scale periodic screening of large populations at amnesic MCI subjects at risk of AD.

The effect of a new symbiotic formulation on plasma levels and peripheral blood mononuclear cell expression of some pro-inflammatory cytokines in patients with ulcerative colitis: a pilot study.

BACKGROUND: During intestinal inflammation white blood cells are recruited from the blood, and they represent the major contributors to tissue perpetuation of inflammation via their production of chemokines and proinflammatory cytokines. OBJECTIVES: Investigate the effect of a symbiotic formulation containing Lactobacillus Paracasei B 20160 versus placebo, on serum levels of interleukin (IL)-6, tumor necrosis factor (TNF)alpha, IL-8, IL-1beta and IL-10 and on mRNA lymphomonocyte expression of TNFalpha, IL-8 and IL-1beta in patients with ulcerative colitis. MATERIALS AND METHODS: Eighteen patients entered the study with histologically proven not complicated ulcerative colitis, treated with mesalazine. Patients were treated for 8 weeks (9 with symbiotic and 9 with placebo). Serum levels of IL-6, TNFalpha, IL-8, IL-1beta and IL-10 were measured using a commercially available sandwich ELISA kit. RT-PCR analysis was performed on total RNA isolated from peripheral lymphomonocytes. RESULTS: In basal condition, there was an increase of serum levels of TNFalpha, IL-6, and IL-8. The treatment with symbiotic significantly decreased serum levels of the last two cytokines (IL-6 and IL-8). In lymphocytes, the treatment with the symbiotic don't significantly reduced the mRNA expression of TNFalpha and IL-1beta, while that of IL-8 was strongly and significantly decreased. CONCLUSION: Our preliminary results suggest that a symbiotic formulation containing Lactobacillus paracasei significantly improves the plasma and lymphocyte content of some proinflammatory cytokines.

Auto-Contractive Maps: an artificial adaptive system for data mining. An application to Alzheimer disease.

This article presents a new paradigm of Artificial Neural Networks (ANNs): the Auto-Contractive Maps (Auto-CM). The Auto-CM differ from the traditional ANNs under many viewpoints: the Auto-CM start their learning task without a random initialization of their weights, they meet their convergence criterion when all their output nodes become null, their weights matrix develops a data driven warping of the original Euclidean space, they show suitable topological properties, etc. Further two new algorithms, theoretically linked to Auto-CM are presented: the first one is useful to evaluate the complexity and the topological information of any kind of connected graph: the H Function is the index to measure the global hubness of the graph generated by the Auto-CM weights matrix. The second one is named Maximally Regular Graph (MRG) and it is an development of the traditionally Minimum Spanning Tree (MST). Finally, Auto-CM and MRG, with the support of the H Function, are applied to a real complex dataset about Alzheimer disease: this data come from the very known Nuns Study, where variables measuring the abilities of normal and Alzheimer subject during their lifespan and variables measuring the number of the plaques and of the tangles in their brain after their death. The example of the Alzheimer data base is extremely useful to figure out how this new approach can help to re design bottom-up the overall structure of factors related to a complex disease like this.

International experience on the use of artificial neural networks in gastroenterology.

In this paper, we reconsider the scientific background for the use of artificial intelligence tools in medicine. A review of some recent significant papers shows that artificial neural networks, the more advanced and effective artificial intelligence technique, can improve the classification accuracy and survival prediction of a number of gastrointestinal diseases. We discuss the 'added value' the use of artificial neural networks-based tools can bring in the field of gastroenterology, both at research and clinical application level, when compared with traditional statistical or clinical-pathological methods.