Pancreatic cancer-derived S-100A8 N-terminal peptide: a diabetes cause?

BACKGROUND: Our aim was to identify the pancreatic cancer diabetogenic peptide. METHODS: Pancreatic tumor samples from patients with (n=15) or without (n=7) diabetes were compared with 6 non-neoplastic pancreas samples using SDS-PAGE. RESULTS: A band measuring approximately 1500 Da was detected in tumors from diabetics, but not in neoplastic samples from non-diabetics or samples from non-neoplastic subjects. Sequence analysis revealed a 14 amino acid peptide (1589.88 Da), corresponding to the N-terminal of the S100A8. At 50 nmol/L and 2 mmol/L, this peptide significantly reduced glucose consumption and lactate production by cultured C(2)C(12) myoblasts. The 14 amino acid peptide caused a lack of myotubular differentiation, the presence of polynucleated cells and caspase-3 activation. CONCLUSIONS: The 14 amino acid peptide from S100A8 impairs the catabolism of glucose by myoblasts in vitro and may cause hyperglycemia in vivo. Its identification in biological fluids might be helpful in diagnosing pancreatic cancer in patients with recent onset diabetes mellitus

Pancreatic cancer-associated diabetes mellitus: an open field for proteomic applications.

Background: Diabetes mellitus is associated with pancreatic cancer in more than 80% of the cases. Clinical, epidemiological, and experimental data indicate that pancreatic cancer causes diabetes mellitus by releasing soluble mediators which interfere with both beta-cell function and liver and muscle glucose metabolism. Methods: We analysed, by matrix-assisted laser desorption ionization time of flight (MALDI-TOF), a series of pancreatic cancer cell lines conditioned media, pancreatic cancer patients' peripheral and portal sera, comparing them with controls and chronic pancreatitis patients' sera. Results: MALDI-TOF analysis of pancreatic cancer cells conditioned media and patients' sera indicated a low molecular weight peptide to be the putative pancreatic cancer-associated diabetogenic factor. The sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis of tumor samples from diabetic and non-diabetic patients revealed the presence of a 1500 Da peptide only in diabetic patients. The amino acid sequence of this peptide corresponded to the N-terminal of an S-100 calcium binding protein, which was therefore suggested to be the pancreatic cancer-associated diabetogenic factor. Conclusions: We identified a tumor-derived peptide of 14 amino acids sharing a 100% homology with an S-100 calcium binding protein, which is probably the pancreatic cancer-associated diabetogenic facto

Statistical analysis driven optimized deep learning system for intrusion detection

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially catastrophic scenario can be envisaged where a nation-state intercepting encrypted financial data gets hacked. Thus, intelligent cybersecurity systems have become inevitably important for improved protection against malicious threats. However, as malware attacks continue to dramatically increase in volume and complexity, it has become ever more challenging for traditional analytic tools to detect and mitigate threat. Furthermore, a huge amount of data produced by large networks has made the recognition task even more complicated and challenging. In this work, we propose an innovative statistical analysis driven optimized deep learning system for intrusion detection. The proposed intrusion detection system (IDS) extracts optimized and more correlated features using big data visualization and statistical analysis methods (human-in-the-loop), followed by a deep autoencoder for potential threat detection. Specifically, a pre-processing module eliminates the outliers and converts categorical variables into one-hot-encoded vectors. The feature extraction module discard features with null values and selects the most significant features as input to the deep autoencoder model (trained in a greedy-wise manner). The NSL-KDD dataset from the Canadian Institute for Cybersecurity is used as a benchmark to evaluate the feasibility and effectiveness of the proposed architecture. Simulation results demonstrate the potential of our proposed system and its outperformance as compared to existing state-of-the-art methods and recently published novel approaches. Ongoing work includes further optimization and real-time evaluation of our proposed IDS.Comment: To appear in the 9th International Conference on Brain Inspired Cognitive Systems (BICS 2018

Potentiality in Biology

We take the potentialities that are studied in the biological sciences (e.g., totipotency) to be an important subtype of biological dispositions. The goal of this paper is twofold: first, we want to provide a detailed understanding of what biological dispositions are. We claim that two features are essential for dispositions in biology: the importance of the manifestation process and the diversity of conditions that need to be satisfied for the disposition to be manifest. Second, we demonstrate that the concept of a disposition (or potentiality) is a very useful tool for the analysis of the explanatory practice in the biological sciences. On the one hand it allows an in-depth analysis of the nature and diversity of the conditions under which biological systems display specific behaviors. On the other hand the concept of a disposition may serve a unificatory role in the philosophy of the natural sciences since it captures not only the explanatory practice of biology, but of all natural sciences. Towards the end we will briefly come back to the notion of a potentiality in biology

A model for orientation effects in electron‐transfer reactions

A method for solving the single‐particle Schrödinger equation with an oblate spheroidal potential of finite depth is presented. The wave functions are then used to calculate the matrix element T_BA which appears in theories of nonadiabatic electron transfer. The results illustrate the effects of mutual orientation and separation of the two centers on TBA. Trends in these results are discussed in terms of geometrical and nodal structure effects. Analytical expressions related to T_BA for states of spherical wells are presented and used to analyze the nodal structure effects for T_BA for the spheroidal wells

Instantaneous Shape Sampling - a model for the γ\gamma-absorption cross section of transitional nuclei

The influence of the quadrupole shape fluctuations on the dipole vibrations in transitional nuclei is investigated in the framework of the Instantaneous Shape Sampling Model, which combines the Interacting Boson Model for the slow collective quadrupole motion with the Random Phase Approximation for the rapid dipole vibrations. Coupling to the complex background configurations is taken into account by folding the results with a Lorentzian with an energy dependent width. The low-energy energy portion of the $\gamma$- absorption cross section, which is important for photo-nuclear processes, is studied for the isotopic series of Kr, Xe, Ba, and Sm. The experimental cross sections are well reproduced. The low-energy cross section is determined by the Landau fragmentation of the dipole strength and its redistribution caused by the shape fluctuations. Collisional damping only wipes out fluctuations of the absorption cross section, generating the smooth energy dependence observed in experiment. In the case of semi-magic nuclei, shallow pygmy resonances are found in agreement with experiment

A visual guide for lower limb prothetic alignment

A novel method to provide an objective visual guide during lower limb prosthetic alignment is proposed. A customized ambulatory device was built to collect kinematic and temporal gait data from 3 subjects walking in four different experiment setups. Multiple gait events within a gait cycle and stride time were derived as feature variables and were pre-processed using Principle Component Analysis (PCA). Distinctive clusters due to different walking setups were noticed in a PCA plot in two dimensions. Dispersion of each clusters and distances amongst each other explains the walking variability and differences under different setups

Elevated expression of artemis in human fibroblast cells is associated with cellular radiosensitivity and increased apoptosis

Copyright @ 2012 Nature Publishing GroupThis article has been made available through the Brunel Open Access Publishing Fund.Background: The objective of this study was to determine the molecular mechanism(s) responsible for cellular radiosensitivity in two human fibroblast cell lines 84BR and 175BR derived from two cancer patients. Methods: Clonogenic assays were performed following exposure to increasing doses of gamma radiation to confirm radiosensitivity. γ-H2AX foci assays were used to determine the efficiency of DNA double strand break (DSB) repair in cells. Quantitative-PCR (Q-PCR) established the expression levels of key DNA DSB repair proteins. Imaging flow cytometry using Annexin V-FITC was used to compare artemis expression and apoptosis in cells. Results: Clonogenic cellular hypersensitivity in the 84BR and 175BR cell lines was associated with a defect in DNA DSB repair measured by the γ-H2AX foci assay. Q-PCR analysis and imaging flow cytometry revealed a two-fold overexpression of the artemis DNA repair gene which was associated with an increased level of apoptosis in the cells before and after radiation exposure. Over-expression of normal artemis protein in a normal immortalised fibroblast cell line NB1-Tert resulted in increased radiosensitivity and apoptosis. Conclusion: We conclude elevated expression of artemis is associated with higher levels of DNA DSB, radiosensitivity and elevated apoptosis in two radio-hypersensitive cell lines. These data reveal a potentially novel mechanism responsible for radiosensitivity and show that increased artemis expression in cells can result in either radiation resistance or enhanced sensitivity.This work was supported in part by The Vidal Sassoon Foundation USA. This article is made available through the Brunel Open Access Publishing Fund

A Tree-Loop Duality Relation at Two Loops and Beyond

The duality relation between one-loop integrals and phase-space integrals, developed in a previous work, is extended to higher-order loops. The duality relation is realized by a modification of the customary +i0 prescription of the Feynman propagators, which compensates for the absence of the multiple-cut contributions that appear in the Feynman tree theorem. We rederive the duality theorem at one-loop order in a form that is more suitable for its iterative extension to higher-loop orders. We explicitly show its application to two- and three-loop scalar master integrals, and we discuss the structure of the occurring cuts and the ensuing results in detail.Comment: 20 pages. Few typos corrected, some additional comments included, Appendix B and one reference added. Final version as published in JHE