Biomarkers and OLGIM Stage for Prospective Preneoplastic Risk Stratification

serum pepsinogen (PG) tests correlate with the occurrence of gastric atrophy and intestinal metaplasia. However, because of its low sensitivity, Huang et al report that in North America, where Helicobacter pylori prevalence is low (8%) and the use of proton pump inhibitors is frequent, the discrimination value for gastric preneoplastic lesions, atrophic gastritis, and intestinal metaplasia of gastropanel biomarkers is too low to obtain good results

Family's History Based on the CDH1 Germline Variant (c.360delG) and a Suspected Hereditary Gastric Cancer Form

Hereditary diffuse gastric cancer (HDGC) is a cancer susceptibility syndrome caused by germline pathogenic variant in CDH1, the gene encoding E-cadherin. The germline loss-of-function variants are the only proven cause of the cancer syndrome HDGC, occurring in approximately 10-18% of cases and representing a helpful tool in genetic counseling. The current case reports the family history based on a CDH1 gene variant, c.360delG, p.His121Thr in a suspected family for hereditary gastric cancer form. This frameshift deletion generates a premature stop codon at the amino acid 214, which leads to a truncated E-cadherin protein detecting it as a deleterious variant. The present study expands the mutational spectra of the family with the CDH1 variant. Our results highlight the clinical impact of the reported CDH1 variant running in gastric cancer families

A Behavior-Based Intrusion Detection System Using Ensemble Learning Techniques

Intrusion Detection Systems (IDSs) play a key role in modern ICT security. Attacks detected and reported by IDSs are often analyzed by administrators who are tasked with countering the attack and minimizing its damage. Consequently, it is important that the alerts generated by the IDS are as detailed as possible. In this paper, we present a multi-layered behavior-based IDS using ensemble learning techniques for the classification of network attacks. Three widely adopted and appreciated models, i.e., Decision Trees, Random Forests, and Artificial Neural Networks, have been chosen to build the ensemble. To reduce the system response time, our solution is designed to immediately filter out traffic detected as benign without further analysis, while suspicious events are investigated to achieve a more fine-grained classification. Experimental evaluation performed on the CIC-IDS2017 public dataset shows that the system is able to detect nine categories of attacks with high performances, according to all the considered metrics

Sequential Deliberation for Social Choice

In large scale collective decision making, social choice is a normative study of how one ought to design a protocol for reaching consensus. However, in instances where the underlying decision space is too large or complex for ordinal voting, standard voting methods of social choice may be impractical. How then can we design a mechanism - preferably decentralized, simple, scalable, and not requiring any special knowledge of the decision space - to reach consensus? We propose sequential deliberation as a natural solution to this problem. In this iterative method, successive pairs of agents bargain over the decision space using the previous decision as a disagreement alternative. We describe the general method and analyze the quality of its outcome when the space of preferences define a median graph. We show that sequential deliberation finds a 1.208- approximation to the optimal social cost on such graphs, coming very close to this value with only a small constant number of agents sampled from the population. We also show lower bounds on simpler classes of mechanisms to justify our design choices. We further show that sequential deliberation is ex-post Pareto efficient and has truthful reporting as an equilibrium of the induced extensive form game. We finally show that for general metric spaces, the second moment of of the distribution of social cost of the outcomes produced by sequential deliberation is also bounded

Atypical lymphoproliferation progressing into B-cell lymphoma in rheumatoid arthritis treated with different biological agents: clinical course and molecular characterization.

10noA patient with rheumatoid arthritis (RA) developed an atypical lymphoproliferative disorder (LPD) after methotrexate and cyclosporine A, which regressed after suspension of both drugs. After subsequent treatment with rituximab, the LPD was still undetectable. Anti-tumor necrosis factor a therapy was used when the arthritis relapsed, but an aggressive B-cell non Hodgkin's lymphoma developed. Molecular analyses showed an oligoclonal B-cell expansion at the LPD step. A minor clone with significant sequence homology to B-cell lymphomas arising in Sjogren's syndrome and mixed cryoglobulinemia syndrome, given rise to the non-Hodgkin's lymphoma. Treatment of rheumatoid arthritis associated with lymphoproliferation represents a clinical challenge, and common pathogenetic pathways to lymphoma may occur in different autoimmune diseases.openopenQuartuccio, Luca; De Re, V.; Fabris, M; Marzotto, A.; Franzolini, N; Gasparotto, D.; Caggiari, L.; Ferraccioli, G.; Scott, Cathryn Anne; DE VITA, SalvatoreQuartuccio, Luca; De Re, V.; Fabris, M; Marzotto, A.; Franzolini, N; Gasparotto, D.; Caggiari, L.; Ferraccioli, G.; Scott, Cathryn Anne; DE VITA, Salvator

Polymorphisms in Pepsinogen C and miRNA Genes Associate with High Serum Pepsinogen II in Gastric Cancer Patients

Background: Pepsinogen (PG) II (PGII) is a serological marker used to estimate the risk of gastric cancer but how PGII expression is regulated is largely unknown. It has been suggested that PGII expression, from the PGC (Progastricsin) gene, is regulated by microRNAs (miRNA), but how PGII levels vary with Helicobacter pylori (H. pylori) infection and miRNAs genotype remains unclear. Methods: Serum levels of PGI and PGII were determined in 80 patients with gastric cancer and persons at risk for gastric cancer (74 first-degree relatives of patients, 62 patients with autoimmune chronic atrophic gastritis, and 2 patients with dysplasia), with and without H. pylori infection. As control from the general population, 52 blood donors were added to the analyses. Associations between PGII levels and genetic variants in PGC and miRNA genes in these groups were explored based on H. pylori seropositivity and the risk for gastric cancer. The two-dimensional difference in gel electrophoresis (2D-DIGE) and the NanoString analysis of messenger RNA (mRNAs) from gastric cancer tissue were used to determine the pathways associated with increased PGII levels. Results: PGII levels were significantly higher in patients with gastric cancer, and in those with H. pylori infection, than in other patients or controls. A PGI/PGII ratio 3 was found better than PGI < 25 ng/mL to identify patients with gastric cancer (15.0% vs. 8.8%). For two genetic variants, namely rs8111742 in miR-Let-7e and rs121224 in miR-365b, there were significant differences in PGII levels between genotype groups among patients with gastric cancer (p = 0.02 and p = 0.01, respectively), but not among other study subjects. Moreover, a strict relation between rs9471643 C-allele with H. pylori infection and gastric cancer was underlined. Fold change in gene expression of mRNA isolated from gastric cancer tissue correlated well with polymorphism, H. pylori infection, increased PGII level, and pathway for bacteria cell entry into the host. Conclusions: Serum PGII levels depend in part on an interaction between H. pylori and host miRNA genotypes, which may interfere with the cut-off of PGI/PGII ratio used to identify persons at risk of gastric cancer. Results reported new findings regarding the relation among H. pylori, PGII-related host polymorphism, and genes involved in this interaction in the gastric cancer setting

Response of microchannel plates in ionization mode to single particles and electromagnetic showers

Hundreds of concurrent collisions per bunch crossing are expected at future hadron colliders. Precision timing calorimetry has been advocated as a way to mitigate the pileup effects and, thanks to their excellent time resolution, microchannel plates (MCPs) are good candidate detectors for this goal. We report on the response of MCPs, used as secondary emission detectors, to single relativistic particles and to electromagnetic showers. Several prototypes, with different geometries and characteristics, were exposed to particle beams at the INFN-LNF Beam Test Facility and at CERN. Their time resolution and efficiency are measured for single particles and as a function of the multiplicity of particles. Efficiencies between 50% and 90% to single relativistic particles are reached, and up to 100% in presence of a large number of particles. Time resolutions between 20ps and 30ps are obtained.Comment: 20 pages, 9 figures. Paper submitted to NIM

Chaos and Quantum Thermalization

We show that a bounded, isolated quantum system of many particles in a specific initial state will approach thermal equilibrium if the energy eigenfunctions which are superposed to form that state obey {\it Berry's conjecture}. Berry's conjecture is expected to hold only if the corresponding classical system is chaotic, and essentially states that the energy eigenfunctions behave as if they were gaussian random variables. We review the existing evidence, and show that previously neglected effects substantially strengthen the case for Berry's conjecture. We study a rarefied hard-sphere gas as an explicit example of a many-body system which is known to be classically chaotic, and show that an energy eigenstate which obeys Berry's conjecture predicts a Maxwell--Boltzmann, Bose--Einstein, or Fermi--Dirac distribution for the momentum of each constituent particle, depending on whether the wave functions are taken to be nonsymmetric, completely symmetric, or completely antisymmetric functions of the positions of the particles. We call this phenomenon {\it eigenstate thermalization}. We show that a generic initial state will approach thermal equilibrium at least as fast as $O(\hbar/\Delta)t^{-1}$, where $\Delta$ is the uncertainty in the total energy of the gas. This result holds for an individual initial state; in contrast to the classical theory, no averaging over an ensemble of initial states is needed. We argue that these results constitute a new foundation for quantum statistical mechanics.Comment: 28 pages in Plain TeX plus 2 uuencoded PS figures (included); minor corrections only, this version will be published in Phys. Rev. E; UCSB-TH-94-1

Proteomics signature of autoimmune atrophic gastritis: towards a link with gastric cancer

Background: Autoimmune atrophic gastritis (AAG) is a chronic disease that can progress to gastric cancer (GC). To better understand AAG pathology, this proteomics study investigated gastric proteins whose expression levels are altered in this disease and also in GC. Methods: Using two-dimensional difference gel electrophoresis (2D-DIGE), we compared protein maps of gastric corpus biopsies from AAG patients and controls. Differentially abundant spots (|fold change|≥ 1.5, P < 0.01) were selected and identified by LC-MS/MS. The spots were further assessed in gastric antrum biopsies from AAG patients (without and with Helicobacter pylori infection) and from GC patients and unaffected first-degree relatives of GC patients. Results: 2D-DIGE identified 67 differentially abundant spots, with 28 more and 39 less abundant in AAG-corpus than controls. LC-MS/MS identified these as 53 distinct proteins. The most significant (adjusted P < 0.01) biological process associated with the less abundant proteins was "tricarboxylic acid cycle". Of the 67 spots, 57 were similarly differentially abundant in AAG-antrum biopsies irrespective of H. pylori infection status. The differential abundance was also observed in GC biopsies for 14 of 28 more abundant and 35 of 39 less abundant spots, and in normal gastric biopsies of relatives of GC patients for 6 and 25 spots, respectively. Immunoblotting confirmed the different expression levels of two more abundant proteins (PDIA3, GSTP gene products) and four less abundant proteins (ATP5F1A, PGA3, SDHB, PGC). Conclusion: This study identified a proteomics signature of AAG. Many differential proteins were shared by GC and may be involved in the progression of AAG to GC