Project description:Transcripional profiling of lymphocytes from patients with amyotrophic lateral sclerosis (ALS) (n=11) and healthy control subjects (n=11). The goal was to determine disease response expression signatures relevant of ALS pathogenesis that affect brain and spinal cord. The reference design was used: each Cy5-labeled cRNA sample from ALS patient or healthy control subject was cohybridized on Agilent-014850 Whole Human Genome Microarray 4x44K G4112F with the reference pool formed with equal amounts of Cy3-labeled cRNAs from each sample from the healthy control group.
Project description:Autoimmune polyendocrine syndrome type I (APS-1) is a rare and devastating organ-specific autoimmune disease characterised by mutations in the Autoimmune Regulator (AIRE) gene. As AIRE is crucial for negative selection in the thymus, increased numbers of undesirable autoreactive T cells are released into the blood with the potential to cause tissue injury, including endocrine organ failure, chronic mucocutaneous candidiasis and hepatitis. B cells are also affected and produce high amounts of neutralising autoantibodies against both cytokines and organ-specific targets. The Aire-deficient mouse model has informed to some extent about immunological aspects of APS-1, but the rarity of APS-1 and inaccessibility of thymic tissue have severely limited immunological studies in patients. Sampling of APS-I patients and controls was performed in standardized manners in PAXgene blood RNA tubes (PreAnalytix, Qiagen, Hombrectikon, Switzerland) and stored at 80ºC until use. Purification of RNA was achieved by the PAXgene blood RNA kit following the instructions from the manufacturer. Samples were quality assessed by Agilent Bioanalyzer, using the Agilent 6000 Nano kit (Agilent, Santa Clara, CA, USA), providing RNA with RNA integrity numbers (RIN) above 6.0. The samples were randomly distributed into 4 batches for RNA extraction, each with 4 patients and 4 sex- and age matched controls and was extracted by the same person on the same day. Following the procedures from Illumina, RNA was subsequently transformed to cRNA, and these constructs were labeled, amplified and quality-checked again by the Agilent Bioanalyzer. The cRNAs were then hybridized to 4 Illumina HumanRef-8 BeadChip microarrays, followed by washing and scanning according to the protocol. Quality control of the arrays was done by BeadStudio.
Project description:Background
This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure.
Results
Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way.
Conclusions
We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics
Model is encoded by Ruby and submitted and curated to BioModels by Ahmad Zyoud
Project description:We focused on the major peripheral blood lymphocyte populations that may be involved in anti-tumor responses and negatively impacted by cancer, specifically CD8 T cells, CD4 T cells, B cells and CD56dim natural killer cells. The pure cell subsets were stringently sorted by flow cytometry from PBMC samples. Gene expression profiles of these cell populations from melanoma patients were compared to healthy controls. Experiment Overall Design: The raw data set contained 48 arrays: 6 healthy and 6 melanoma arrays for each of the 4 cell types. Two of the arrays had quality issues due to background noise and were excluded, leaving us with 46 arrays. Experiment Overall Design: On each array we used Cy3 to label a pool of two RNA samples from a pair of age and gender matched stage IV (American Joint Committee on Cancer) melanoma patients or from a pair of age and gender matched healthy donors. We used Cy5 to label the Total Lymphocyte Reference (TLR) RNA. The TLR is a common reference specifically created for this study using the total peripheral lymphocyte fraction from 20 healthy donors.
Project description:Transcripional profiling of lymphocytes from patients with amyotrophic lateral sclerosis (ALS) (n=11) and healthy control subjects (n=11). The goal was to determine disease response expression signatures relevant of ALS pathogenesis that affect brain and spinal cord. The reference design was used: each Cy5-labeled cRNA sample from ALS patient or healthy control subject was cohybridized on Agilent-014850 Whole Human Genome Microarray 4x44K G4112F with the reference pool formed with equal amounts of Cy3-labeled cRNAs from each sample from the healthy control group. Eleven lymphocyte samples from definite sporadic ALS patients and eleven samples from healthy control subjects were used.
Project description:Gene expression changes in the blood was studied by RNAseq Results: Strong differences between patients groups, specific expression changes for heathy control (Hlty), uncomplicated infection (Inf1_P), sepsis (Seps_P), septic shock (Shock_P), follow-up of sepsis (Seps_FU), follow-up of septic shock (Shock_FU) groups.
Project description:PURPOSE:The aim of this multicenter trial was to generate a [123I]FP-CIT SPECT database of healthy controls from the common SPECT systems available in Japan. METHODS:This study included 510 sets of SPECT data from 256 healthy controls (116 men and 140 women; age range, 30-83 years) acquired from eight different centers. Images were reconstructed without attenuation or scatter correction (NOACNOSC), with only attenuation correction using the Chang method (ChangACNOSC) or X-ray CT (CTACNOSC), and with both scatter and attenuation correction using the Chang method (ChangACSC) or X-ray CT (CTACSC). These SPECT images were analyzed using the Southampton method. The outcome measure was the specific binding ratio (SBR) in the striatum. These striatal SBRs were calibrated from prior experiments using a striatal phantom. RESULTS:The original SBRs gradually decreased in the order of ChangACSC, CTACSC, ChangACNOSC, CTACNOSC, and NOACNOSC. The SBRs for NOACNOSC were 46% lower than those for ChangACSC. In contrast, the calibrated SBRs were almost equal under no scatter correction (NOSC) conditions. A significant effect of age was found, with an SBR decline rate of 6.3% per decade. In the 30-39 age group, SBRs were 12.2% higher in women than in men, but this increase declined with age and was absent in the 70-79 age group. CONCLUSIONS:This study provided a large-scale quantitative database of [123I]FP-CIT SPECT scans from different scanners in healthy controls across a wide age range and with balanced sex representation. The phantom calibration effectively harmonizes SPECT data from different SPECT systems under NOSC conditions. The data collected in this study may serve as a reference database.