Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

Classification of protein domain movements using Dynamic Contact Graphs

A new method for the classification of domain movements in proteins is described and applied to 1822 pairs of structures from the Protein Data Bank that represent a domain movement in two-domain proteins. The method is based on changes in contacts between residues from the two domains in moving from one conformation to the other. We argue that there are five types of elemental contact changes and that these relate to five model domain movements called: ‘‘free’’, ‘‘openclosed’’, ‘‘anchored’’, ‘‘sliding-twist’’, and ‘‘see-saw.’’ A directed graph is introduced called the ‘‘Dynamic Contact Graph’’ which represents the contact changes in a domain movement. In many cases a graph, or part of a graph, provides a clear visual metaphor for the movement it represents and is a motif that can be easily recognised. The Dynamic Contact Graphs are often comprised of disconnected subgraphs indicating independent regions which may play different roles in the domain movement. The Dynamic Contact Graph for each domain movement is decomposed into elemental Dynamic Contact Graphs, those that represent elemental contact changes, allowing us to count the number of instances of each type of elemental contact change in the domain movement. This naturally leads to sixteen classes into which the 1822 domain movements are classified

The liver is a common non-exocrine target in primary Sjögren's syndrome: A retrospective review

BACKGROUND: The autoimmune destruction of exocrine glands that defines primary Sjögren's syndrome (1°SS) often extends to non-exocrine organs including the liver. We aimed to determine the prevalence of liver disease in patients with 1°SS and to evaluate the association of this complication with other non-exocrine features and serologic markers of autoimmunity and systemic inflammation. METHODS: We reviewed 115 charts of patients with 1°SS and further analyzed the 73 cases that fulfilled the European Epidemiology Center Criteria, seeking evidence for clinical and subclinical liver disease. RESULTS: Liver function tests had been determined in 59 of the 73 patients. Of those, 29 patients (49.1%) had abnormal liver function tests including 20.3% with clinically overt hepatic disease. Liver disease was the most common non-exocrine feature in this cohort. Risk factors for abnormal liver function tests were distributed similarly between the patients with and without liver disease. In 60% of patients with abnormal liver function tests no explanation for this complication was found except for 1°SS. Liver involvement was significantly more common in 1°SS patients who also had evidence of lung, kidney and hematological abnormalities. Patients with abnormal liver function tests were also more likely to have an elevated sedimentation rate and a positive anti-ENA during the course of their disease. CONCLUSION: Liver involvement is a common complication in 1°SS. Its presence correlates with systemic disease. We consider that this complication should be routinely sought in patients with 1°SS, especially when a positive anti-ENA or evidence of systemic inflammation is found

Potential diagnostic and prognostic values of detecting promoter hypermethylation in the serum of patients with gastric cancer

While there is no reliable serum biomarker for the diagnosis and monitoring of patients with gastric cancer, we tested the potential diagnostic and prognostic values of detecting methylation changes in the serum of gastric cancer patients. DNA was extracted from the pretherapeutic serum of 60 patients with confirmed gastric adenocarcinoma and 22 age-matched noncancer controls. Promoter hypermethylation in 10 tumour-related genes (APC, E-cadherin, GSTP1, hMLH1, MGMT, p15, p16, SOCS1, TIMP3 and TGF-beta RII) was determined by quantitative methylation-specific PCR (MethyLight). Preferential methylation in the serum DNA of gastric cancer patients was noted in APC (17%), E-cadherin (13%), hMLH1 (41%) and TIMP3 (17%) genes. Moreover, patients with stages III/IV diseases tended to have higher concentrations of methylated APC (P=0.08), TIMP3 (P=0.005) and hMLH1 (P=0.03) in the serum. In all, 33 cancers (55%) had methylation detected in the serum in at least one of these four markers, while three normal subjects had methylation detected in the serum (specificity 86%). The combined use of APC and E-cadherin methylation markers identified a subgroup of cancer patients with worse prognosis (median survival 3.3 vs 16.1 months, P=0.006). These results suggest that the detection of DNA methylation in the serum may carry both diagnostic and therapeutic values in gastric cancer patients

Using structural motif descriptors for sequence-based binding site prediction

All authors are with the Biotechnological Center, TU Dresden, Tatzberg 47-51, 01307 Dresden, Germany and -- Wan Kyu Kim is with the Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USABackground: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, we aim to predict protein-protein interactions (PPI) and protein-ligand interactions (PLI) on sequence level using 3D information. To this end, we use machine learning to compile sequential segments that constitute structural features of an interaction site into one profile Hidden Markov Model descriptor. The resulting collection of descriptors can be used to screen sequence databases in order to predict functional sites. -- Results: We generate descriptors for 740 classified types of protein-protein binding sites and for more than 3,000 protein-ligand binding sites. Cross validation reveals that two thirds of the PPI descriptors are sufficiently conserved and significant enough to be used for binding site recognition. We further validate 230 PPIs that were extracted from the literature, where we additionally identify the interface residues. Finally we test ligand-binding descriptors for the case of ATP. From sequences with Swiss-Prot annotation "ATP-binding", we achieve a recall of 25% with a precision of 89%, whereas Prosite's P-loop motif recognizes an equal amount of hits at the expense of a much higher number of false positives (precision: 57%). Our method yields 771 hits with a precision of 96% that were not previously picked up by any Prosite-pattern. -- Conclusion: The automatically generated descriptors are a useful complement to known Prosite/InterPro motifs. They serve to predict protein-protein as well as protein-ligand interactions along with their binding site residues for proteins where merely sequence information is available.Institute for Cellular and Molecular [email protected]

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Hypoxia Due to Cardiac Arrest Induces a Time-Dependent Increase in Serum Amyloid β Levels in Humans

Amyloid β (Aβ) peptides are proteolytic products from amyloid precursor protein (APP) and are thought to play a role in Alzheimer disease (AD) pathogenesis. While much is known about molecular mechanisms underlying cerebral Aβ accumulation in familial AD, less is known about the cause(s) of brain amyloidosis in sporadic disease. Animal and postmortem studies suggest that Aβ secretion can be up-regulated in response to hypoxia. We employed a new technology (Single Molecule Arrays, SiMoA) capable of ultrasensitive protein measurements and developed a novel assay to look for changes in serum Aβ42 concentration in 25 resuscitated patients with severe hypoxia due to cardiac arrest. After a lag period of 10 or more hours, very clear serum Aβ42 elevations were observed in all patients. Elevations ranged from approximately 80% to over 70-fold, with most elevations in the range of 3–10-fold (average approximately 7-fold). The magnitude of the increase correlated with clinical outcome. These data provide the first direct evidence in living humans that ischemia acutely increases Aβ levels in blood. The results point to the possibility that hypoxia may play a role in the amyloidogenic process of AD

Lysosomal protease deficiency or substrate overload induces an oxidative-stress mediated STAT3-dependent pathway of lysosomal homeostasis

How cells regulate their lysosomal proteolytic capacity is only partly understood. Here, the authors show that lysosomal protease deficiency or substrate overload induces lysosomal stress leading to activation of a STAT3-dependent, TFEB-independent pathway of lysosomal hydrolase expression

Disruption of the Autophagy-Lysosome Pathway Is Involved in Neuropathology of the nclf Mouse Model of Neuronal Ceroid Lipofuscinosis

Variant late-infantile neuronal ceroid lipofuscinosis, a fatal lysosomal storage disorder accompanied by regional atrophy and pronounced neuron loss in the brain, is caused by mutations in the CLN6 gene. CLN6 is a non-glycosylated endoplasmic reticulum (ER)-resident membrane protein of unknown function. To investigate mechanisms contributing to neurodegeneration in CLN6 disease we examined the nclf mouse, a naturally occurring model of the human CLN6 disease. Prominent autofluorescent and electron-dense lysosomal storage material was found in cerebellar Purkinje cells, thalamus, hippocampus, olfactory bulb and in cortical layer II to V. Another prominent early feature of nclf pathogenesis was the localized astrocytosis that was evident in many brain regions and the more widespread microgliosis. Expression analysis of mutant Cln6 found in nclf mice demonstrated synthesis of a truncated protein with a reduced half-life. Whereas the rapid degradation of the mutant Cln6 protein can be inhibited by proteasomal inhibitors, there was no evidence for ER stress or activation of the unfolded protein response in various brain areas during postnatal development. Age-dependent increases in LC3-II, ubiquitinated proteins, and neuronal p62-positive aggregates were observed, indicating a disruption of the autophagy-lysosome degradation pathway of proteins in brains of nclf mice, most likely due to defective fusion between autophagosomes and lysosomes. These data suggest that proteasomal degradation of mutant Cln6 is sufficient to prevent the accumulation of misfolded Cln6 protein, whereas lysosomal dysfunction impairs constitutive autophagy promoting neurodegeneration