The functional capacity and quality of life of women with advanced breast cancer

The rehabilitation needs of patients with metastatic breast cancer (MBC) are poorly studied. The primary aim of the study was to evaluate the functional capacity of women with MBC and quality of life (QoL). The present study is an open, non-randomized, prospective cross-sectional observation study. The functional capacity of 128 MBC patients with ongoing cancer treatments, were studied in Helsinki University Hospital (HUS): Peak expiratory flow (PEF), dynamic and static balance, 6 minute walking distance (6MWD), 10 meter walking, sit-to-stand test, repeated squat, grip strength, shoulder movement, pain, and QoL by Beck's depression scale (BDI), health assessment questionnaire (HAQ), RAND SF-36 and EORTC QLQ-30 items. The walking capacity was compromised in half and the strength of the lower extremities in one-third of the patients. PEF was below the normal reference in 55 %, static balance in 62 % and dynamic balance in 73 % (= 61 year olds). The grip power was lowered in 44/30 % of the patients (right/left) and the shoulder movement was restricted in 30 %. Some disability in physical functioning experienced 55 % (HAQ) and 37 % felt depressive (BDI). The QoL (RAND SF-36) was poor especially in the field of physical, role and social functioning and bodily pain (<0.001). Pain, depression, and a poor 6MWD results independently determined the physical component of QoL (p <0.001). The functional capacity of patients with MBC was significantly lowered. This, in association with distressing symptoms like pain and depression causes a vicious circle further leading to functional disabilities and impaired QoL.Peer reviewe

Identification and characterization of antibacterial compound(s) of cockroaches (Periplaneta americana)

Infectious diseases remain a significant threat to human health, contributing to more than 17 million deaths, annually. With the worsening trends of drug resistance, there is a need for newer and more powerful antimicrobial agents. We hypothesized that animals living in polluted environments are potential source of antimicrobials. Under polluted milieus, organisms such as cockroaches encounter different types of microbes, including superbugs. Such creatures survive the onslaught of superbugs and are able to ward off disease by producing antimicrobial substances. Here, we characterized antibacterial properties in extracts of various body organs of cockroaches (Periplaneta americana) and showed potent antibacterial activity in crude brain extract against methicillin-resistant Staphylococcus aureus and neuropathogenic E. coli K1. The size-exclusion spin columns revealed that the active compound(s) are less than 10 kDa in molecular mass. Using cytotoxicity assays, it was observed that pre-treatment of bacteria with lysates inhibited bacteria-mediated host cell cytotoxicity. Using spectra obtained with LC-MS on Agilent 1290 infinity liquid chromatograph, coupled with an Agilent 6460 triple quadruple mass spectrometer, tissues lysates were analyzed. Among hundreds of compounds, only a few homologous compounds were identified that contained isoquinoline group, chromene derivatives, thiazine groups, imidazoles, pyrrole containing analogs, sulfonamides, furanones, flavanones, and known to possess broad-spectrum antimicrobial properties, and possess anti-inflammatory, anti-tumour, and analgesic properties. Further identification, characterization and functional studies using individual compounds can act as a breakthrough in developing novel therapeutics against various pathogens including superbugs

A Few Bad Apples:A Model of Disease Influenced Agent Behaviour in a Heterogeneous Contact Environment

For diseases that infect humans or livestock, transmission dynamics are at least partially dependent on human activity and therefore human behaviour. However, the impact of human behaviour on disease transmission is relatively understudied, especially in the context of heterogeneous contact structures such as described by a social network. Here, we use a strategic game, coupled with a simple disease model, to investigate how strategic agent choices impact the spread of disease over a contact network. Using beliefs that are based on disease status and that build up over time, agents choose actions that stochastically determine disease spread on the network. An agent’s disease status is therefore a function of both his own and his neighbours actions. The effect of disease on agents is modelled by a heterogeneous payoff structure. We find that the combination of network shape and distribution of payoffs has a non-trivial impact on disease prevalence, even if the mean payoff remains the same. An important scenario occurs when a small percentage (called noncooperators) have little incentive to avoid disease. For diseases that are easily acquired when taking a risk, then even when good behavior can lead to disease eradication, a small increase in the percentage of noncooperators (less than 5%) can yield a large (up to 25%) increase in prevalence

The six-minute walk test in community dwelling elderly: influence of health status.

BACKGROUND: The 6 minutes walk test (6MWT) is a useful assessment instrument for the exercise capacity of elderly persons. The impact of the health status on the 6MWT-distance in elderly, however, remains unclear, reducing its value in clinical settings. The objective of this study was to investigate to what extent the 6MWT-distance in community dwelling elderly is determined by health conditions. METHODS: One hundred and fifty-six community dwelling elderly people (53 male, 103 female) were assessed for health status and performed the 6MWT. After clinical evaluation, electrocardiography and laboratory examination participants were categorized into a stratified six-level classification system according to their health status, going from A (completely healthy) to D (signs of active disease at the moment of examination). RESULTS: The mean 6MWT-distance was 603 m (SD = 178). The 6MWT-distance decreased significantly with increasing age (ANOVA p = 0.0001) and with worsening health status (ANCOVA, corrected for age p < 0.001). A multiple linear regression model with health status, age and gender as independent variables explained 31% of the 6MWT-distance variability. Anthropometrical measures (stature, weight and BMI) did not significantly improve the prediction model. A significant relationship between 6MWT-distance and stature was only present in category A (completely healthy). CONCLUSIONS: Significant differences in 6MWT-distance are observed according to health status in community-dwelling elderly persons. The proposed health categorizing system for elderly people is able to distinguish persons with lower physical exercise capacity and can be useful when advising physical trainers for seniors

Local Network Topology in Human Protein Interaction Data Predicts Functional Association

The use of high-throughput techniques to generate large volumes of protein-protein interaction (PPI) data has increased the need for methods that systematically and automatically suggest functional relationships among proteins. In a yeast PPI network, previous work has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional association. In this study we improved the prediction scheme by developing a new algorithm and applied it on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting function-associated protein pairs. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as benchmarks to compare and evaluate the function relevance. The application of our algorithms to human PPI data yielded 4,233 significant functional associations among 1,754 proteins. Further functional comparisons between them allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made functional inferences from detailed analysis on one subcluster highly enriched in the TGF-β signaling pathway (P<10−50). Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotation in this post-genomic era

A Combined Epigenetic and Non-Genetic Approach for Reprogramming Human Somatic Cells

Reprogramming of somatic cells to different extents has been reported using different methods. However, this is normally accompanied by the use of exogenous materials, and the overall reprogramming efficiency has been low. Chemicals and small molecules have been used to improve the reprogramming process during somatic cell nuclear transfer (SCNT) and induced pluripotent stem (iPS) cell generation. We report here the first application of a combined epigenetic and non-genetic approach for reprogramming somatic cells, i.e., DNA methyltransferase (DNMT) and histone deacetylase (HDAC) inhibitors, and human embryonic stem cell (hESC) extracts. When somatic cells were pretreated with these inhibitors before exposure to hESC (MEL1) extracts, morphological analysis revealed a higher rate of hESC-like colony formation than without pretreatment. Quantitative PCR (qPCR) demonstrated that pluripotency genes were upregulated when compared to those of somatic cells or treated with hESC extracts alone. Overall changes in methylation and acetylation levels of pretreated somatic cells suggests that epigenetic states of the cells have an effect on reprogramming efficiency induced by hESC extracts. KnockOutserum replacement (KOSR™) medium (KO-SR) played a positive role in inducing expression of the pluripotency genes. hESC extracts could be an alternative approach to reprogram somatic cells without introducing exogenous materials. The epigenetic pre-treatment of somatic cells could be used to improve the efficiency of reprogramming process. Under differentiation conditions, the reprogrammed cells exhibited differentiation ability into neurons suggesting that, although fully reprogramming was not achieved, the cells could be transdifferentiated after reprogramming

Upregulation of MiR-155 in Nasopharyngeal Carcinoma is Partly Driven by LMP1 and LMP2A and Downregulates a Negative Prognostic Marker JMJD1A

The role of microRNA-155 (miR-155) has been associated with oncogenesis of several human tumors. However the expression pattern of miR-155 has not been investigated in nasopharyngeal carcinoma (NPC). The present study was to assess miR-155 expression pattern and its possible function in NPC, to identify its targets and evaluate their clinical applications in NPC. MiR-155 was found to be upregulated in two Epstein-Barr virus (EBV) negative NPC derived cell lines CNE1 and TW03, as well as in NPC clinical samples by quantitative Real-time PCR and in situ hybridization detection. EBV encoded LMP1 and LMP2A could further enhance the expression of miR-155 in NPC CNE1 and TW03 cells. JMJD1A and BACH1 were identified as putative targets of miR-155 in a bioinformatics screen. Overexpression of miR-155 downregulated a luciferase transcript fused to the 3′UTR of JMJD1A and BACH1. MiR-155 mimic could downregulate the expression of JMJD1A and BACH1, while miR-155 inhibitor could upregulate JMJD1A expression in NPC cell lines. Moreover, downregulation of JMJD1A was significantly correlated with N stage in TNM classification (p = 0.023), a lower five-year survival rate (p = 0.021), and a lower five-year disease-free survival rate (p = 0.049) of NPC patients. Taken together, up-regulation of miR-155 in NPC is partly driven by LMP1 and LMP2A, and results in downregulation of JMJD1A, which is associated with N stage and poor prognosis of NPC patients. The potential of miR-155 and JMJD1A as therapeutic targets in NPC should be further investigated

Gene-Disease Network Analysis Reveals Functional Modules in Mendelian, Complex and Environmental Diseases

Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Reconstruction of the Core and Extended Regulons of Global Transcription Factors

The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across α-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual α-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 α-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the α-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks

Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

<p>Abstract</p> <p>Background</p> <p>In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme.</p> <p>Results</p> <p>The diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges.</p> <p>Conclusions</p> <p>The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.</p