A model-based approach to stabilizing crutch supported paraplegic standing by artifical hip joint stiffness

The prerequisites for stable crutch supported standing were analyzed in this paper. For this purpose, a biomechanical model of crutch supported paraplegic stance was developed assuming the patient was standing with extended knees. When using crutches during stance, the crutches will put a position constraint on the shoulder, thus reducing the number of degrees of freedom. Additional hip-joint stiffness was applied to stabilize the hip joint and, therefore, to stabilize stance. The required hip-joint stiffness for changing crutch placement and hip-joint offset angle was studied under static and dynamic conditions. Modeling results indicate that, by using additional hip-joint stiffness, stable crutch supported paraplegic standing can be achieved, both under static as well as dynamic situations. The static equilibrium postures and the stability under perturbations were calculated to be dependent on crutch placement and stiffness applied. However, postures in which the hip joint was in extension (C postures) appeared to the most stable postures. Applying at least 60 N /spl middot/ m/rad hip-joint stiffness gave stable equilibrium postures in all cases. Choosing appropriate hip-joint offset angles, the static equilibrium postures changed to more erect postures, without causing instability or excessive arm forces to occur

Association between postoperative muscle wasting and survival in older patients undergoing surgery for non-metastatic colorectal cancer

BACKGROUND: Preoperative sarcopenia in older patients is a risk factor for adverse outcomes after colorectal cancer (CRC) surgery. Longitudinal changes in muscle mass in this group have not been studied previously although muscle wasting may have prognostic significance regarding survival. We aimed to determine the association between muscle wasting and overall survival (OS) in older patients who underwent surgery for CRC.METHODS: Patients ≥70 years who underwent surgery for non-metastatic CRC in Gelre hospitals, The Netherlands, between 2011 and 2015 were included. Cross-sectional area of skeletal muscle was measured at the level of the 3rd lumbar vertebra on preoperative and postoperative abdominal CT-scans. Patients who had &gt;1 standard deviation decrease in muscle mass were considered to have muscle wasting. Cox regression analysis was used to evaluate associations between muscle wasting and OS.RESULTS: 233 patients were included (40% female, median age 76 years). Thirty-four patients had muscle wasting. After a median follow-up of 4.7 years, 53 (23%) patients died. The 3-year mortality rate was higher in patients with muscle wasting (27% vs 14%, p = .05). In multivariable analysis adjusted for age, recurrent disease and preoperative muscle mass, muscle wasting was associated with reduced OS (HR 2.8, 95% CI 1.5-5.4, p = .002).CONCLUSION: Muscle wasting predicted poorer survival in older patients who underwent CRC surgery. Measuring changes in muscle mass may improve risk prediction in this patient group. Future studies should address the etiology of muscle wasting in older patients with CRC. Whether perioperative exercise interventions can prevent muscle wasting also warrants further study.</p

Functional Gene-Expression Analysis Shows Involvement of Schizophrenia-Relevant Pathways in Patients with 22q11 Deletion Syndrome

22q11 Deletion Syndrome (22q11DS) is associated with dysmorphology and a high prevalence of schizophrenia-like symptoms. Several genes located on chromosome 22q11 have been linked to schizophrenia. The deletion is thought to disrupt the expression of multiple genes involved in maturation and development of neurons and neuronal circuits, and neurotransmission. We investigated whole-genome gene expression of Peripheral Blood Mononuclear Cells (PBMC's) of 8 22q11DS patients and 8 age- and gender-matched controls, to (1) investigate the expression levels of 22q11 genes and (2) to investigate whether 22q11 genes participate in functional genetic networks relevant to schizophrenia. Functional relationships between genes differentially expressed in patients (as identified by Locally Adaptive Statistical procedure (LAP) or satisfying p<0.05 and fold-change >1.5) were investigated with the Ingenuity Pathways Analysis (IPA). 14 samples (7 patients, 7 controls) passed quality controls. LAP identified 29 deregulated genes. Pathway analysis showed 262 transcripts differentially expressed between patients and controls. Functional pathways most disturbed were cell death, cell morphology, cellular assembly and organization, and cell-to-cell signaling. In addition, 10 canonical pathways were identified, among which the signal pathways for Natural Killer-cells, neurotrophin/Trk, neuregulin, axonal guidance, and Huntington's disease. Our findings support the use of 22q11DS as a research model for schizophrenia. We identified decreased expression of several genes (among which COMT, Ufd1L, PCQAP, and GNB1L) previously linked to schizophrenia as well as involvement of signaling pathways relevant to schizophrenia, of which Neurotrophin/Trk and neuregulin signaling seems to be especially notable

SNPExpress: integrated visualization of genome-wide genotypes, copy numbers and gene expression levels

Background: Accurate analyses of comprehensive genome-wide SNP genotyping and gene expression data sets is challenging for many researchers. In fact, obtaining an integrated view of both large scale SNP genotyping and gene expression is currently complicated since only a limited number of appropriate software tools are available. Results: We present SNPExpress, a software tool to accurately analyze Affymetrix and Illumina SNP genotype calls, copy numbers, polymorphic copy number variations (CNVs) and Affymetrix gene expression in a combinatorial and efficient way. In addition, SNPExpress allows concurrent interpretation of these items with Hidden-Markov Model (HMM) inferred Loss-of-Heterozygosity (LOH)- and copy number regions. Conclusion: The combined analyses with the easily accessible software tool SNPExpress will not only facilitate the recognition of recurrent genetic lesions, but also the identification of critical pathogenic genes

TF Target Mapper: A BLAST search tool for the identification of Transcription Factor target genes

BACKGROUND: In the current era of high throughput genomics a major challenge is the genome-wide identification of target genes for specific transcription factors. Chromatin immunoprecipitation (ChIP) allows the isolation of in vivo binding sites of transcription factors and provides a powerful tool for examining gene regulation. Crosslinked chromatin is immunoprecipitated with antibodies against specific transcription factors, thus enriching for sequences bound in vivo by these factors in the immunoprecipitated DNA. Cloning and sequencing the immunoprecipitated sequences allows identification of transcription factor target genes. Routinely, thousands of such sequenced clones are used in BLAST searches to map their exact location in the genome and the genes located in the vicinity. These genes represent potential targets of the transcription factor of interest. Such bioinformatics analysis is very laborious if performed manually and for this reason there is a need for developing bioinformatic tools to automate and facilitate it. RESULTS: In order to facilitate this analysis we generated TF Target Mapper (Transcription Factor Target Mapper). TF Target Mapper is a BLAST search tool allowing rapid extraction of annotated information on genes around each hit. It combines sequence cleaning/filtering, pattern searching and BLAST searches with extraction of information on genes located around each BLAST hit and comparisons of the output list of genes or gene ontology IDs with user-implemented lists. We successfully applied and tested TF Target Mapper to analyse sequences bound in vivo by the transcription factor GATA-1. We show that TF Target Mapper efficiently extracted information on genes around ChIPed sequences, thus identifying known (e.g. α-globin and ζ-globin) and potentially novel GATA-1 gene targets. CONCLUSION: TF Target Mapper is a very efficient BLAST search tool that allows the rapid extraction of annotated information on the genes around each hit. It can contribute to the comprehensive bioinformatic transcriptome/regulome analysis, by providing insight into the mechanisms of action of specific transcription factors, thus helping to elucidate the pathways these factors regulate

Чергове засідання Ради Міжнародної асоціації академій наук

7 червня 2012 року в Національному дослідницькому центрі «Курчатовський інститут» відбулося чергове засідання Ради Міжнародної асоціації академій наук (МААН). Під час урочистої церемонії закриття засідання президенту МААН, президенту НАН України академіку НАН України і РАН Борису Євгеновичу Патону було присвоєно звання Почесного доктора НДЦ «Курчатовський інститут»

Fatigue in Sjögren's Syndrome: A Search for Biomarkers and Treatment Targets

Background: Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease, where patients often suffer from fatigue. Biological pathways underlying fatigue are unknown. In this study aptamer-based SOMAscan technology is used to identify potential biomarkers and treatment targets for fatigue in pSS.Methods: SOMAscan® Assay 1.3k was performed on serum samples of healthy controls (HCs) and pSS patients characterized for interferon upregulation and fatigue. Differentially expressed proteins (DEPs) between pSS patients and HC or fatigued and non-fatigued pSS patients were validated and discriminatory capacity of markers was tested using independent technology.Results: Serum concentrations of over 1,300 proteins were compared between 63 pSS patients and 20 HCs resulting in 58 upregulated and 46 downregulated proteins. Additionally, serum concentrations of 30 interferon positive (IFNpos) and 30 interferon negative (IFNneg) pSS patients were compared resulting in 25 upregulated and 13 downregulated proteins. ELISAs were performed for several DEPs between pSS patients and HCs or IFNpos and IFNneg all showing a good correlation between protein levels measured by ELISA and relative fluorescence units (RFU) measured by the SOMAscan. Comparing 22 fatigued and 23 non-fatigued pSS patients, 16 serum proteins were differentially expressed, of which 14 were upregulated and 2 were downregulated. Top upregulated DEPs included neuroactive synaptosomal-associated protein 25 (SNAP-25), alpha-enolase (ENO1) and ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1). Furthermore, the proinflammatory mediator IL36a and several complement factors were upregulated in fatigued compared to non-fatigued pSS patients. ROC analysis indicated that DEPs showed good capacity to discriminate fatigued and non-fatigued pSS patients.Conclusion: In this study we validated the use of aptamer-based proteomics and identified a novel set of proteins which were able to distinguish fatigued from non-fatigued pSS patients and identified a so-called “fatigue signature.

A novel nicastrin mutation in a three-generation Dutch family with hidradenitis suppurativa: a search for functional significance

Background: Mutations in the γ-secretase enzyme subunits have been described in multiple kindreds with familial hidradenitis suppurativa (HS). Objective: In this study, we report a novel nicastrin (NCSTN) mutation causing HS in a Dutch family. We sought to explore the immunobiological function of NCSTN mutations using data of the Immunological Genome Project. Methods: Blood samples of three affected and two unaffected family members were collected. Whole-genome sequencing was performed using genomic DNA isolated from peripheral blood leucocytes. Sanger sequencing was done to confirm the causative NCSTN variant and the familial segregation. The microarray data set of the Immunological Genome Project was used for thorough dissection of the expression and function of wildtype NCSTN in the immune system. Results: In a family consisting of 23 members, we found an autosomal dominant inheritance pattern of HS and detected a novel splice site mutation (c.1912_1915delCAGT) in the NCSTN gene resulting in a frameshift and subsequent premature stop. All affected individuals had HS lesions on non-flexural and atypical locations. Wildtype NCSTN appears to be upregulated in myeloid cells like monocytes and macrophages, and in mesenchymal cells such as fibroblastic reticular cells and fibroblasts. In addition, within the 25 highest co-expressed genes with NCSTN we identified CAPNS1, ARNT and PPARD. Conclusion: This study reports the identification a novel NCSTN gene splice site mutation which causes familial HS. The associated immunobiological functions of NCSTN and its co-expressed genes ARNT and PPARD link genetics to the most common environmental and metabolic HS risk factors which are smoking and obesity

Gene expression-based classification of non-small cell lung carcinomas and survival prediction

Background: Current clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy. Methodology and Principal Findings:A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts. Conclusions:The gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome