Fibroma of tendon sheath located within the ankle joint capsule

We report a very rare case of fibroma of the tendon sheath arising from the anteromedial ankle joint capsule, with no apparent connection to any tendon in the area, found in a 58-year-old patient complaining of progressive local swelling. This uncommon tumor has its usual localization in tendon sheaths, is extremely rare in joint capsules, and has never been described in this location previously. MRI showed nonuniform low signal intensity in T1- and T2-weighted images and high intensity in STIR images. The mass was completely excised by open surgery. Histopathological analysis later confirmed the diagnosis of a fibroma of the tendon sheath

Are genetic risk factors for psychosis also associated with dimension-specific psychotic experiences in adolescence?

Psychosis has been hypothesised to be a continuously distributed quantitative phenotype and disorders such as schizophrenia and bipolar disorder represent its extreme manifestations. Evidence suggests that common genetic variants play an important role in liability to both schizophrenia and bipolar disorder. Here we tested the hypothesis that these common variants would also influence psychotic experiences measured dimensionally in adolescents in the general population. Our aim was to test whether schizophrenia and bipolar disorder polygenic risk scores (PRS), as well as specific single nucleotide polymorphisms (SNPs) previously identified as risk variants for schizophrenia, were associated with adolescent dimension-specific psychotic experiences. Self-reported Paranoia, Hallucinations, Cognitive Disorganisation, Grandiosity, Anhedonia, and Parent-rated Negative Symptoms, as measured by the Specific Psychotic Experiences Questionnaire (SPEQ), were assessed in a community sample of 2,152 16-year-olds. Polygenic risk scores were calculated using estimates of the log of odds ratios from the Psychiatric Genomics Consortium GWAS stage-1 mega-analysis of schizophrenia and bipolar disorder. The polygenic risk analyses yielded no significant associations between schizophrenia and bipolar disorder PRS and the SPEQ measures. The analyses on the 28 individual SNPs previously associated with schizophrenia found that two SNPs in TCF4 returned a significant association with the SPEQ Paranoia dimension, rs17512836 (p-value=2.57x10-4) and rs9960767 (p-value=6.23x10-4). Replication in an independent sample of 16-year-olds (N=3,427) assessed using the Psychotic-Like Symptoms Questionnaire (PLIKS-Q), a composite measure of multiple positive psychotic experiences, failed to yield significant results. Future research with PRS derived from larger samples, as well as larger adolescent validation samples, would improve the predictive power to test these hypotheses further. The challenges of relating adult clinical diagnostic constructs such as schizophrenia to adolescent psychotic experiences at a genetic level are discussed

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information.AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins.AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains

PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries

BACKGROUND: Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation. RESULTS: To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer. CONCLUSIONS: PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

Background: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual aminoacids are systematically mutated to alanine and changes in free energy of binding (Delta Delta G) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition.Results: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which Delta Delta G >= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%.Conclusion: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration

Mechanism of Action of Cyclophilin A Explored by Metadynamics Simulations

Trans/cis prolyl isomerisation is involved in several biological processes, including the development of numerous diseases. In the HIV-1 capsid protein (CA), such a process takes place in the uncoating and recruitment of the virion and is catalyzed by cyclophilin A (CypA). Here, we use metadynamics simulations to investigate the isomerization of CA's model substrate HAGPIA in water and in its target protein CypA. Our results allow us to propose a novel mechanistic hypothesis, which is finally consistent with all of the available molecular biology data

A randomized two arm phase III study in patients post radical resection of liver metastases of colorectal cancer to investigate bevacizumab in combination with capecitabine plus oxaliplatin (CAPOX) vs CAPOX alone as adjuvant treatment

<p>Abstract</p> <p>Background</p> <p>About 50% of patients with colorectal cancer are destined to develop hepatic metastases. Radical resection is the most effective treatment for patients with colorectal liver metastases offering five year survival rates between 36-60%. Unfortunately only 20% of patients are resectable at time of presentation. Radiofrequency ablation is an alternative treatment option for irresectable colorectal liver metastases with reported 5 year survival rates of 18-30%. Most patients will develop local or distant recurrences after surgery, possibly due to the outgrowth of micrometastases present at the time of liver surgery. This study aims to achieve an improved disease free survival for patients after resection or resection combined with RFA of colorectal liver metastases by adding the angiogenesis inhibitor bevacizumab to an adjuvant regimen of CAPOX.</p> <p>Methods/design</p> <p>The Hepatica study is a two-arm, multicenter, randomized, comparative efficacy and safety study. Patients are assessed no more than 8 weeks before surgery with CEA measurement and CT scanning of the chest and abdomen. Patients will be randomized after resection or resection combined with RFA to receive CAPOX and Bevacizumab or CAPOX alone. Adjuvant treatment will be initiated between 4 and 8 weeks after metastasectomy or resection in combination with RFA. In both arms patients will be assessed for recurrence/new occurrence of colorectal cancer by chest CT, abdominal CT and CEA measurement. Patients will be assessed after surgery but before randomization, thereafter every three months after surgery in the first two years and every 6 months until 5 years after surgery. In case of a confirmed recurrence/appearance of new colorectal cancer, patients can be treated with surgery or any subsequent line of chemotherapy and will be followed for survival until the end of study follow up period as well. The primary endpoint is disease free survival. Secondary endpoints are overall survival, safety and quality of life.</p> <p>Conclusion</p> <p>The HEPATICA study is designed to demonstrate a disease free survival benefit by adding bevacizumab to an adjuvant regime of CAPOX in patients with colorectal liver metastases undergoing a radical resection or resection in combination with RFA.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier NCT00394992</p

Human embryonic stem cells: preclinical perspectives

Human embryonic stem cells (hESCs) have been extensively discussed in public and scientific communities for their potential in treating diseases and injuries. However, not much has been achieved in turning them into safe therapeutic agents. The hurdles in transforming hESCs to therapies start right with the way these cells are derived and maintained in the laboratory, and goes up-to clinical complications related to need for patient specific cell lines, gender specific aspects, age of the cells, and several post transplantation uncertainties. The different types of cells derived through directed differentiation of hESC and used successfully in animal disease and injury models are described briefly. This review gives a brief outlook on the present and the future of hESC based therapies, and talks about the technological advances required for a safe transition from laboratory to clinic

Endothelial progenitor cells and integrins: adhesive needs

In the last decade there have been multiple studies concerning the contribution of endothelial progenitor cells (EPCs) to new vessel formation in different physiological and pathological settings. The process by which EPCs contribute to new vessel formation in adults is termed postnatal vasculogenesis and occurs via four inter-related steps. They must respond to chemoattractant signals and mobilize from the bone marrow to the peripheral blood; home in on sites of new vessel formation; invade and migrate at the same sites; and differentiate into mature endothelial cells (ECs) and/or regulate pre-existing ECs via paracrine or juxtacrine signals. During these four steps, EPCs interact with different physiological compartments, namely bone marrow, peripheral blood, blood vessels and homing tissues. The success of each step depends on the ability of EPCs to interact, adapt and respond to multiple molecular cues. The present review summarizes the interactions between integrins expressed by EPCs and their ligands: extracellular matrix components and cell surface proteins present at sites of postnatal vasculogenesis. The data summarized here indicate that integrins represent a major molecular determinant of EPC function, with different integrin subunits regulating different steps of EPC biology. Specifically, integrin α4β1 is a key regulator of EPC retention and/or mobilization from the bone marrow, while integrins α5β1, α6β1, αvβ3 and αvβ5 are major determinants of EPC homing, invasion, differentiation and paracrine factor production. β2 integrins are the major regulators of EPC transendothelial migration. The relevance of integrins in EPC biology is also demonstrated by many studies that use extracellular matrix-based scaffolds as a clinical tool to improve the vasculogenic functions of EPCs. We propose that targeted and tissue-specific manipulation of EPC integrin-mediated interactions may be crucial to further improve the usage of this cell population as a relevant clinical agent