EAE is associated with inflammation and demyelination of the nervous system. Micro-array can be used to investigate gene expression and biological pathways that are altered during disease. There are few studies of the changes in gene expression in EAE, and these have mostly been done in a chronic mouse EAE model. EAE induced in the Lewis with myelin basic protein (MBP-EAE) is well characterised, making it an ideal candidate for the analysis of gene expression in this disease model.Experimental autoimmune encephalomyelitis MBP-EAE was induced in female Lewis rats by inoculation with MBP and adjuvants. Total RNA was extracted from the spinal cords and used for micro-array analysis using AffimetrixGeneChip Rat Exon 1.0 ST Arrays. Gene expression in the spinal cords was compared between healthy female rats and female rats with MBP-EAE. Gene expression in the spinal cord of rats with MBP-EAE differed from that in the spinal cord of normal rats, and there was regulation of pathways involved with immune function and nervous system function. For selected genes the change in expression was confirmed with real-time PCR.EAE leads to modulation of gene expression in the spinal cord. We have identified the genes that are most significantly regulated in MBP-EAE in the Lewis rat and produced a profile of gene expression in the spinal cord at the peak of disease. On the basis of pathological findings and genetic studies that show that the majority of genes that predispose to multiple sclerosis (MS) are associated with T cell activation EAE was first induced by inoculation of whole brain tissue In this study we have investigated MBP-EAE, which is characterized by weight loss and ascending paralysis Because of the extensive characterization of MPB-EAE in the Lewis rat, it is an excellent candidate for studies aimed at defining the gene expression profile of the disease. There have been no previous gene array studies of MBP-EAE in the Lewis rat; however, the expression profile of selected cytokines, chemokines, adhesion molecules, cell markers, matrix metalloproteinases and other genes relevant to disease etiology have been examined in this model by real-time PCR (RT-PCR) Rats were inoculated with MBP to induce EAE. The typical clinical course of this disease is shown in RNA quality analysis was carried out on the BioRad Experion automated electrophoresis system. All preparations used in both assays had values of values of >9.5 for RNA quality indicator (RQI) Of the 2,350 differentially regulated genes, 2,265 mapped to known locations in the Partek data-base and the remainder were unmapped. Of these mapped genes, 1,665 were mapped to named genes. Of the 1,665 differentially regulated genes, 998 were found to be down-regulated and 667 were up-regulated. These are listed in www.ingenuity.com ) for functional and pathway analysis. After filtering to exclude genes that were not of relevance to the nervous system, we produced an annotated set of 1,190 differentially regulated genes. These genes were used for our further analysis of functions, pathways and upstream regulators.The 2,530 genes that were differentially regulated were up-loaded into the Ingenuity Pathway analysis software package (IPA) , or have been associated with one or more of the commonly used EAE models, as shown in To produce a list of the genes that are most significantly and highly regulated in MBP-EAE, we used a False Discovery Rate (FDR) To confirm our micro-array findings, expression levels of a the genes caspase 1 (Casp1), oligodendrocyte myelin glycoprotein (OMG), alpha subunit voltage-gated sodium channel type 1 (Scn1a), Fas (TNF receptor superfamily member 6) and superoxide dismutase 2, mitochondrial (Sod2) were validated using RT-PCR in 8 rats in each group. These genes were selected as being regulated in EAE and of biological interest. Gene transcripts were amplified from cDNA preparations. These were obtained from the original total RNA samples used in the micro-array analysis and an additional 4 normal rats with MBP-EAE and an additional 4 healthy rats. The results are shown in The functional predictions that are generated from IPA are based on the direction of expression of a number of downstream genes which have been previously shown to be associated with that function. The functions that are most significantly altered in MBP-EAE are shown in A number of Canonical pathways were identified in IPA as being significantly regulated in MBP-EAE, based on the expression profile of genes in MBP treated animals compared to healthy controls. These are shown in From IPA we have identified the upstream regulators that are predicted to be activated or inactivated in MBP-EAE. These are shown in In this study, using female Lewis rats, we have investigated the expression of genes in MBP-EAE compared to controls. We have studied rats at day 13, which is the peak of clinical disease, when processes that lead to recovery are under way. The pathology of MBP-EAE involves infiltration of the CNS with macrophages and activated T lymphocytes Genes involved in the inflammatory response and in antigen processing and presentation were some of the most highly regulated genes identified. Cell-cell signalling and interaction and cell movement were also highly represented amongst the most differentially regulated gene transcripts identified. A number of chemokines and their receptors, annexin 3A and fibronectin were all up-regulated more than four-fold in the diseased spinal cords. Cellular growth factors, notably IL2-α and the common gamma chain were highly up-regulated as was the inflammatory cytokine IL1-β which is expressed in activated microglial cells The regulation of key components of the classical  and alternative  complement pathways and the complement component 3a receptor 1 (3ar1), but not molecules in the terminal pathway, is in accordance with previous studies which indicate that the common terminal pathway (culminating in the membrane attack complex) is not important for the development of fulminant demyelinating EAE Genes associated with apoptosis which were highly regulated in our data set include the apoptosis related serine peptidases (Caspases) which have all been associated with disease in various EAE models Down-regulation of gene transcripts in MBP induced EAE in the Lewis rat was much more subtle than up-regulation however almost a thousand genes were found to be significantly down-regulated in the model . EighteeOf the most highly regulated genes in the spinal cord  & 2, manhttp://rgd.mcw.edu/).EAE can only be induced in susceptible animals. In studies of different mouse and rat strains, some genetic loci have been identified as being important in the predisposition to EAE. In our study, many of the genes identified as being differentially regulated found to map to those regions , formation of amyloid fibrils, and proliferation of oligodendrocyte precursor cells. Apoptosis is known to be an important function in EAE. Apoptosis of T cells is important in the regulation of MBP-EAE The functions that are predicted to be downregulated include long term-potentiation, neurotransmission, synaptic transmission, quantity of vesicles and delay in the death of neurons. These downregulated functions presumably reflect damage to neural tissue.From IPA we also obtained a list of the canonical pathways that were regulated in MBP-EAE. There were changes in immune pathways and neural pathways. The immune related pathways include antigen presentation, T cell differentiation and complement pathways, all of which would be expected to be activated in EAE. The neural related pathways include dopamine feedback of cAMP signalling, Creb signalling in neurones, biosynthesis of steroids and ALS signalling.From IPA we have identified the upstream regulators that are predicted to be activated or inactivated in MBP-EAE. The greatest inactivation was predicted in sirtuin 2 (sirt2). Sirt 2 is is a member of the sirtuin family of histone deacetylases and has been shown to have a role in promoting longevity In conclusion, we have shown that MBP induced EAE alters gene expression in the spinal cord. We have produced a gene expression profile for this model in the Lewis rat which correlates well with the documented characteristics of the disease. Further examination of the pathways and functions regulated should pave the way for future studies into their regulation which may lead to the identification of potential drug targets for enhancement of the resolution of inflammatory disease in the CNS.This research was approved by the Animal Ethics Committee of the University of Queensland. The approval number was UQCCR/770/08/MSRA.EAE was induced in 11 wk old female Lewis rats by subcutaneous injection at the base of the tail of 50 µg recombinant MBP, using our standard methods . Healthy age-matched unimmunized rats were used as controls. Weakness of the tail, hindlimbs and forelimbs was assessed by grading the degree of weakness of each region separately on a scale of 0 (no weakness) to 4 , as described previously On day 13 after inoculation, which is the peak of clinical disease, rats were sacrificed and the spinal cord was excised from the spinal column by insufflation using a large bore blunt ended needle and a 60 ml syringe. Total RNA was extracted from tissues using QIAGEN RNeasy® Lipid tissue Midi kits as per the manufactures instructions and treated with DNase1 (QIAGEN) to remove all traces of genomic DNA prior to storage at −80°C. The RNA quality analysis was carried out using the BioRadExperion automated gel electrophoresis system (BioRad Laboratories Inc.).For each group, 4 biological replicates were used. cDNA synthesis and amplification was performed using the Applause WT-Amp Plus ST kit (NuGEN). Samples were enzymatically fragmented and biotinylated using the Encore Biotin Module labelling kit (NuGEN). Samples were hybridized to AffimetrixGeneChip Rat Exon 1.0 ST Arrays as per the manufacturer’s instructions. Briefly, 5 µg of fragmented biotinylated ssDNA was hybridised for 16 hrs at 45°C, 60 rpm to the array chip. After 16 hrs GeneChips were washed on a FS_450 Fluidics station using the washing script FS450_0001 with buffers and stains supplied with the GeneChip Hybridisation, Wash and Stain Kit from Affymetrix.Data was acquired on a 7G GeneChip Scanner 3000 and.CEL file generation performed using AGCC. Expression Console with Robust Multi-chip Average (RMA) was used initially to extract probe intensity data. This data was used to access Affimetrix supplied PolyA and Eucaryotic Hybridisation controls to confirm consistent processing of the RNA samples. Subsequent statistical analysis was performed in Partek Genomics Suite – Version 6.110801 . The Affymetrix RaEx-1_0-st-v1.r2.dt.core.mps was used to filter probe sets. RMA background correction was applied including pre-background adjustment for GC content and quantile normalization across all chips in the experiment. Probe data was log2 transformed.For gene transcript expression analysis, core probe sets were averaged for each gene. The significance of differences in gene expression between the EAE and healthy control data sets was evaluated by analysis of variance (ANOVA) that compared the controls and normal rats and investigated the effect of different batches. There was no significant batch effect in this study.Although we are aware that the data may not be distributed normally and that a reduced homogeneity of variance may exist, the alternative non-parametric tests such as the Kruskal Wallis analysis would not produce the ratio of means required to identify statistically significant functional categories and pathways and make predictions about the possible downstream functional effects of fold change for various groups of genes. As a result, the above violations to the assumptions made by this analysis were considered to be adequately compensated for by the robust nature of the analysis. We have produced a list of all the genes that are regulated in EAE, and also a smaller list of the genes that are most highly regulated in MBP-EAE.www.ingenuity.com) was used to identify biological functions, gene networks and pathways which were significantly regulated in the spinal cord in EAE compared to healthy controls. In IPA, right-tailed Fisher’s exact test was used to calculate a p-value determining the probability that each function network or pathway assigned to that data set is due to chance alone. Molecules from the data set that met the p<0.05 cut off and were associated with biological functions in the Ingenuity knowledge base were considered for the analysis.IPA . Each biological function considered is associated with a number of upstream genes based on annotations derived from the literature and stored in the Ingenuity knowledgebase. The previously observed effects on function of each gene in this set are then used to predict an increase or decrease in the function under the conditions studied. 2qPCR Primer Assay, QIAGEN). Real time PCR analysis was carried on the MyIQ™ real time PCR thermo-cycler and detection system (BioRad Laboratories Inc.) using the RT2 QPCR Primer assay according to the manufactures’ protocol. Briefly, 1 µg of total rat spinal cord RNA was treated with QIAGEN Genomic DNA Elimination mix for 5 min at 42?C prior to being reverse transcribed using the kit protocol. RT-PCR conditions were as follows: 95?C, 10 min (Hot Start Taq polymerisation activation step) followed by 40 cycles of 95?C, 15 sec, 60?C, 1 min. The reactions were monitored using SYBR Green containing fluorescein . At the end of each PCR run a melting curve analysis was carried out to verify that homogeneous products of equal size had been amplified for each primer pair. The same set of RNA samples that was used for the micro-array experiments was also analysed by RT-PCR and in addition we tested four more independent validation samples from each group, which had been collected and prepared in an identical manner, to test for sampling error. Expression was normalized to rat peptidylprolylisomerase H (rtPpih). Fold changes were calculated using the ΔΔCT method Validation of the results obtained from the micro-array experiments was carried out using real time PCR. Five genes  found to be differentially regulated in EAE in the micro-array gene expression experiments, were selected for validation by RT-PCR. Rat primer pairs were purchased from SA BioSystems Click here for additional data file.Figure S2RNA Electropherogram Profile. Tissue samples were snap frozen in liquid nitrogen and stored at −80°C prior to total RNA preparation using the QIAGEN RNeasy Lipid tissue kit. RNA quality analysis was carried out on the BioRad Experion automated electrophoresis system. This shows an example of the electropherogram profiles illustrating the high quality of samples used. All preparations had RQI values of >9.5.(DOCX)Click here for additional data file.Figure S3Regulation of the Antigen presentation pathway in MBP-EAE. This figure shows the upregulation of MHC class I and MHC class II linked pathways of antigen presentation in MBP-EAE.(TIF)Click here for additional data file.Figure S4Regulation of the T Helper Cell Differentiation in MBP-EAE. This figure shows that there is upregulation of the pathways of Th0 cell differentiation, especially into Th1 and Th17 cells in MBP-EAE.(TIF)Click here for additional data file.Figure S5Regulation of Cytotoxic T-lymphocyte mediated apoptosis of target cells in MBP-EAE. This figure shows that there is upregulation of the pathways involved in T cell cytotoxicity of target cells in MBP-EAE.(TIF)Click here for additional data file.Figure S6Regulation of Fc gamma –mediated phagocytosis in macrophages and monocytes in MBP-EAE. This shows that in rats with MBP-EAE there is up-regulation of many of the genes in the pathways leading to phagosome formation after Fc gamma binding.(TIF)Click here for additional data file.Figure S7Regulation of Interferon signalling in MBP-EAE. This shows that there is upregulation of many of the genes in the JAK/STAT pathway of interferon signalling in rats with MBP-EAE.(TIF)Click here for additional data file.Figure S8Regulation of Dendritic cell maturation in MBP-EAE. This figure shows that many of the genes in the pathway of dendritic cell maturation are upregulated in MBP-EAE, except IL-12 which is downregulated.(TIF)Click here for additional data file.Figure S9B cell development in MBP-EAE. This shows that many cell surface receptors involved in the stages of B cell maturation are up- regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S10Regulation of Trem1 Signalling in MBP-EAE. This shows that many of the intracellular signalling molecules involved in signalling by the triggering receptor expressed on myeloid cells 1 (TREM1) are upregulated in MBP-EAE. This pathway is involved in adaptive and innate immunity.(TIF)Click here for additional data file.Figure S11Regulation of Communication between innate and adaptive immune cells in MBP-EAE. This shows that many signalling molecules involved in this pathway are upregulated except for IL12 which is down regulated.(JPG)Click here for additional data file.Figure S12Regulation of the Complement pathway in MBP-EAE. This shows that the classical pathway and the alternate pathway but not the common terminal pathway are regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S13Regulation of genes in the pathway entitled Pathogenesis of Multiple Sclerosis. This is a pathway of chemokine receptors. The receptors CCR1, CCR5, CXCR3, CCL5, CXCL9 and CXCL10 are up-regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S14Regulation of Synaptic long term potentiation in MBP-EAE. This shows that this pathway of signalling in response to glutamate is down-regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S15Regulation of Dopamine-DARPP32 feedback in cAMP signalling in MBP-EAE. This shows that this pathway of signalling in response to dopamine is down-regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S16Regulation of the Amyotrophic Lateral Sclerosis pathway in MBP-EAE. This pathway of intra-cellular signalling that leads to cell death and degeneration in response to glutamate is down-regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S17Regulation of Creb signalling in neurons in MBP-EAE. This shows that this pathway of intracellular signalling leading to expression of cAMP response element-binding (Creb) is down-regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S18Regulation Endothelin-1 signalling in MBP-EAE. This shows that this pathway of intracellular signalling in response to endothelin 1 (ET1) is downregulated in MBP-EAE.(TIF)Click here for additional data file.Figure S19Regulation the Biosynthesis of steroids in MBP-EAE. This shows that the squalene pathway involved in the bio-synthesis of steroids is down-regulated in MBP-EAE.(TIF)Click here for additional data file.Figure S20Regulation Taurine/hypotaurine metabolism in MBP-EAE. This shows downregulation of elements of the pathway that leads to synthesis of taurine and hypotaurine from cysteine in MBP-EAE.(TIF)Click here for additional data file.Table S1(XLSX)Click here for additional data file.Table S2(XLSX)Click here for additional data file.


To evaluate the relationship and agreement between standard automated perimetry (SAP) and Matrix frequency doubling technology (Matrix-FDT) in subjects with ocular hypertension and healthy control subjects.Forty-four eyes of 44 ocular hypertensive subjects and 29 eyes of 29 healthy age-matched control subjects were included in this prospective study. All participants underwent complete ophthalmic examination, including slit-lamp biomicroscopy, intraocular pressure measurement, pachymetry, and dilated fundus examination, and showed reliable visual field tests. One randomly selected eye of each participant was examined with SAP (Swedish Interactive Threshold Algorithm [SITA] Standard 24-2 test) and Matrix-FDT (24-2 threshold test), in random order. Correlations between global indices , regions  and 52 single field positions were analyzed using Spearman’s rank correlation coefficient.In both groups, mean deviation values of SAP and Matrix-FDT correlated significantly . Pattern standard deviation of SAP and Matrix-FDT showed no significant correlation in healthy subjects but correlated significantly in ocular hypertensive subjects . In healthy subjects, a significant correlation between SAP and Matrix-FDT was shown in the supero-temporal and infero-temporal sectors of the disc . In OHT subjects, supero-temporal, supero-nasal and nasal sectors correlated significantly . The correlation pattern of individual visual field test locations appeared heterogeneous in both groups.In both, ocular hypertensive and healthy subjects SAP and Matrix-FDT correlate well. In ocular hypertensive subjects, both techniques showed good correlation in the supero-temporal, supero-nasal, and nasal sectors of the disc. Poor agreement was found in the temporal, infero-temporal and infero-nasal disc sectors. This missing correlation might be related to early retinal nerve fiber layer damage in these regions of the disc, recognized by one of the visual field instruments. Glaucoma is a disease in which death of retinal ganglion cells (RGCs) is associated with visual field defects and visual impairment. The evaluation of these visual field defects is essential for diagnosing and monitoring glaucoma and for recognizing progression. Until today the “gold standard” for visual field testing is standard automated perimetry (SAP) which measures light sensitivity thresholds at various locations across the visual field. Frequency doubling technology (FDT) has been suggested a test that may detect retinal ganglion cell damage earlier than standard automated perimetry. In comparison to SAP, FDT uses contrast sensitivity and a different test algorithm to detect visual field changes. The second generation of FDT perimeter, the Humphrey Matrix-FDT, was released in 2003. It utilizes additional tests to improve the spatial resolution of visual field defects by using smaller targets with a higher spatial frequency and a lower temporal frequency. The purpose of this cross sectional observational study was to evaluate the agreement between Matrix frequency doubling technology perimetry and standard automated perimetry  in subjects with ocular hypertension and healthy subjects and to determine if Matrix-FDT might be a helpful tool in detecting early visual field defects in OHT subjects that are not yet detectable with standard white-on-white perimetry.Forty-four eyes of 44 ocular hypertensive subjects and 29 eyes of 29 healthy control subjects were included in this prospective controlled study.The study protocol was approved by the Ethics Committee of Mainz University, Rhineland Palatinate, Germany. All study procedures adhered to the recommendations of the Declaration of Helsinki and all participants signed informed consent prior to any testing, clinical examination, or collection of demographic or medical information.Ocular hypertension was defined as IOP>21 mmHg on at least two occasions prior to enrolment. At the time of enrolment, subjects with OHT were allowed to be on IOP lowering treatment. All participants had normal results on Humphrey 24-2 automated perimetry tests (no clustered field defects) as well as healthy optic nerves by clinical expert exam (dilated stereoscopic fundus examination with a high power fundus lens of 78 D or 90 D). Discs were considered healthy when they had symmetric vertical cup to disc ratio in both eyes, intact neuroretinal rims without notching, no disc hemorrhages, and no nerve fiber layer defect. Age-matched control subjects had an intraocular pressure <21 mmHg, and normal disc appearance based on a dilated stereoscopic fundus examination. All measurements were performed on one day, and all participants were recruited within an eight-month period. All subjects were familiar with standard automated perimetry because each had undergone at least one visual field examination before the study. None of the participants had undergone frequency doubling perimetry testing prior to the study. A brief demonstration was performed to familiarize them with the procedure. Subjects who met the inclusion criteria and who agreed to participate were enrolled in the study.To be included in the study, participants had to have best-corrected visual acuity of at least logMAR 0.3, spherical refraction within ±5.0 D, and astigmatism of less than ±3.0 D. All subjects underwent complete ophthalmic examination, including visual acuity testing, slit-lamp biomicroscopy, intraocular pressure measurement with Goldmann applanation tonometry, central corneal thickness measurement with ultrasound pachymetry, and dilated fundus examination.Subjects with non-glaucomatous secondary causes of elevated intraocular pressure , other intraocular disease, history of other conditions that might affect visual field testing , or medications known to affect visual field sensitivity, were excluded from the investigation.Testing on all subjects was performed using the Matrix Frequency Doubling Technology perimeter  and the Humphrey Field Analyzer II  in randomized order on one day. If required, a rest of 15 minutes between each visual field exam was permitted. For both, OHT and healthy subjects, one eye was randomly selected to be included in the study, and the investigator was masked to the subject’s group classification.Participants were tested on the Humphrey Field Analyzer II, using the 24-2 standard test algorithm  which consists of 52 test locations. On FDT, the 24-2 full threshold test algorithm, consisting of 55 test locations, was used. The ZEST  algorithm was used for threshold estimation. Not included in the comparison were the two locations in the vicinity of the blind spot and the test point in the central visual field which are examined only by the FDT but not by the SAP perimeter.The statistical analysis evaluated the agreement between Humphrey-SAP and Matrix-FDT in subjects with OHT and healthy controls.Comparisons between global indices (Humphrey MD/PSD versus Matrix-FDT MD/PSD) and between groups were based on t-tests. Correlations between global indices, hemifields, quadrants, sectors and single field points were compared using Spearman’s rank correlation coefficient (r). The significance level was set to p<0.05.This study is an explorative study where no p value adjustment was performed. This strategy was chosen since adjustment for multiple testing  would have increased the risk of falsely accepting the null hypothesis (type II error). Especially Bonferroni adjustments are known to be highly conservative so that one can miss real differences. Forty-four eyes of 44 ocular hypertensive subjects and 29 eyes of 29 healthy control subjects were included in this prospective controlled study. Among the 44 OHT subjects, SAP glaucoma hemifield test result was classified as “inside normal limits” in 32 eyes, “outside normal limits” in 10 eyes, and “others” in 2 eyes (including borderline). The FDT glaucoma hemifield result was classified as “normal” in 28 eyes, “outside normal limits” in 7 eyes, and “others” in 9 eyes (including borderline). Complete concordance between SAP and FDT glaucoma hemifield test was shown in 28 (64%) eyes . SAP glaucoma hemifield test was normal in 8 cases in which FDT showed different results .Among the 29 healthy subjects, the SAP glaucoma hemifield test result was classified as “inside normal limits” in 22 eyes, “outside normal limits” in 3 eyes, and “others” in 4 eyes (including borderline). The FDT glaucoma hemifield result was classified as “normal” in 22 eyes, “outside normal limits” in 4 eyes, and “others” in 3 eyes . Complete concordance of GHT between SAP and FDT was shown in 19 (66%) eyes . SAP glaucoma hemifield test was normal in 4 cases in which FDT showed different results .Correlations between visual field global indices (mean deviation and pattern standard deviation) were analyzed using Spearman’s rank correlation coefficient (r). In the OHT group , averageIn the control subject group , only thBoth hemifields of the control group presented with significant correlation between Humphrey-SAP and Matrix-FDT . In ocular hypertensive subjects, only the inferior hemifield presented with a significant correlation . Subdivided into quadrants, the nasal-inferior quadrants were significantly correlated in both groups . The temporal-inferior quadrant was significantly correlated in OHT subjects .To specifically investigate the correlation between the two instruments in the same test location of the visual field, each of the 52 SAP visual field test locations was compared with the corresponding location of the Matrix-FDT visual field as demonstrated in It needs to be considered that high and statistically significant correlations for given visual field points do not necessarily lead to high and statistically significant overall correlations in the given area. For instance, a greater amount of highly correlated field points can be found in the supero-nasal quadrant compared with the infero-nasal quadrant of healthy control subjects. However, a statistically significant overall correlation can only be found in the infero-nasal quadrant but not in the supero-nasal quadrant.Garway-Heath et al. established an optic disc-visual field map which relates six sectors of the optic disc  to corresponding sectors of the visual field . [24] AcIn the OHT group, SAP and Matrix-FDT correlated significantly in sectors I , II , and III . In the healthy subject group, there was a significant correlation between SAP and Matrix FDT in sectors I  and V .Subjects with ocular hypertension carry an increased risk of developing glaucoma during their lifetime. It is desirable to find techniques which detect conversion from OHT to glaucoma at the earliest stage in order to avoid any significant field loss.Matrix-FDT may detect retinal ganglion cell damage earlier than standard automated perimetry. While various investigations between SAP and FDT were carried out in glaucoma patients, only few studies addressed to OHT subjects so far.This study investigated the correlation between SAP and Matrix-FDT in subjects with ocular hypertension and healthy control subjects. Global indices of subjects with ocular hypertension correlated significantly  whereas only mean deviation values showed significant correlation in the healthy subject group . This is in agreement with data published by Bozkurt et al. They compared ocular hypertensive participants and glaucoma patients with Humphrey 30-2 SITA standard test and Matrix 30-2 threshold test and found SAP MD positively correlated with Matrix-FDT MD  and SAP PSD significantly correlated with Matrix-FDT PSD . In contrast to our results, no correlation was found between SAP global indices and Matrix global indices in the OHT group. Other investigations found good correlations between SAP and Matrix-FDT in glaucoma patients. Concordance of glaucoma hemifield test between Matrix-FDT and SAP was 64% in OHT subjects and 66% in healthy subjects. In the OHT group, FDT presented with abnormal or borderline results in 18.2% where SAP showed normal results. In healthy subjects, this was seen in only 13.8%.In relation to hemifields interestingly both, the superior and inferior hemifield were significantly correlated between both techniques  in healthy subjects whereas in OHT subjects only the inferior hemifield showed a significant correlation . Subdivided into quadrants, only the nasal inferior quadrant in healthy subjects  and the temporal inferior and nasal inferior quadrants in ocular hypertensive subjects  were significantly correlated. This differs from the results reported by Zarkovic et al. The correlation of SAP and FDT in individual test locations was found to be heterogenous. This is in agreement with results published by Zarkovic et al., who describe a great variance of correlation between individual test points from a correlation of less than 0.2 for some points in the inferior temporal field up to high correlated points (r = 0.88) for some points of the supero-nasal field. As seen in our investigation, they describe no apparent trend between the degree of correlation and the position of test points in relation to eccentricity from the macula, or the vertical and horizontal meridians.Structure and function are two main pillars of glaucoma diagnosis and management. In the year 2000, Garway-Heath et al. established a structure-function map which relates sectors in the visual field to sectors on the optic nerve head. According to the structure-function map by Garway-Heath et al. we found a correlation of the two instruments in the supero-temporal, supero-nasal and nasal sectors of ocular hypertensive subjects and in the supero-temporal and infero-temporal sectors of healthy control subjects. No correlation between both techniques was found in sectors IV, V, and VI of OHT subjects. These three sectors are related to the temporal, infero-temporal and infero-nasal region of the optic nerve head. In healthy subjects, sectors without correlation  are arranged somewhat more heterogeneously. As early retinal nerve fiber layer defects often occur in the temporal/temporal-inferior regions of the optic nerve head One factor that needs to be discussed is the role of variability in the current study. Limited agreement between techniques in relatively homogenous groups like OHT subjects and normal controls might be explained by test-retest variability. In the current study, the smallest agreement was found in temporal, infero-temporal and infero-nasal sectors of the ocular hypertensive group. This limited agreement could also be explained by an increased variability as an early sign of glaucomatous damage in these connected sectors. Interesting in this context is a study by Cellini et al. Our findings are of special interest in view of recently published data where correlations between three perimetric tests  and confocal scanning laser ophthalmoscopy (cSLO) were investigated in glaucoma patients. Although performing several hypothesis tests using the same sample somewhat increases the experimentwise type I error in this study , we decided not to apply methods for correction for multiple comparisons. There is considerable controversy in the literature regarding the application of such methods. Comparing the number of observed significant test results with the number of expected significant test results can give some impression if the findings make sense above chance level. In the current study, 80 tests were undertaken . Hence, the overall number of expected significant tests results at a significance level of 0.05 is 4. Since the number of observed significant test results is much higher than 4 (14 significant correlations for the first 28 tests and 20 significant correlations for single field points), the results can be interpreted as plausible and believable.A weakness of this study might be the fact that only one of each field test was performed and that individuals were only familiarized with standard white-on-white perimetry. It is known that in the context of visual field testing changes in sensitivity can occur both within and between tests in normal individuals. For standard automated perimetry (SAP), variability was shown to be greater in patients with glaucoma and other optic neuropathies than in normal individuals. Finally, the sequence wherein test locations are tested might also be of importance. Locations which are tested later can either display lower sensitivity due to fatigue effects or higher sensitivity due to learning effects. Concentration, awareness and compliance of the patient as well as environmental influences can potentially bias the results.While a large number of studies have been published in the past comparing the first-generation FDT with standard automated perimetry, only few studies have compared the second generation Matrix-FDT with SAP. The majority of these studies included glaucoma patients. To date there do not exist sufficient data that would allow a statement about visual field defects of OHT subjects in frequency doubling technology. Further studies with a higher number of participants should investigate whether the missing correlation in some parts of the optic nerve head found in this study are signs of early glaucomatous abnormalities in OHT subjects or simply due to physiological differences.Our study found a good overall agreement between Humphrey-SAP and Matrix-FDT in ocular hypertensive and healthy control subjects. One major finding is a missing correlation between both perimeters in areas where glaucoma tends to start. As there exist only few studies comparing Matrix-FDT and SAP in ocular hypertensive subjects, our results should be confirmed by larger, prospective, longitudinal studies.Future investigations are needed in order to compare FDT- and SAP patterns of healthy and ocular hypertensive subjects who converted to glaucoma.


Galanin is expressed at low levels in the intact sensory neurons of the dorsal root ganglia with a dramatic increase after peripheral nerve injury. The neuropeptide is also expressed in primary afferent terminals in the dorsal horn, spinal inter-neurons and in a number of brain regions known to modulate nociception. Intrathecal administration of galanin modulates sensory responses in a dose-dependent manner with inhibition at high doses. To date it is unclear which of the galanin receptors mediates the anti-nociceptive effects of the neuropeptide and whether their actions are peripherally and/or centrally mediated. In the present study we investigated the effects of direct administration into the receptive field of galanin and the galanin receptor-2/3-agonist Gal2-11 on nociceptive primary afferent mechanical responses in intact rats and mice and in the partial saphenous nerve injury (PSNI) model of neuropathic pain.Exogenous galanin altered the responses of mechano-nociceptive C-fibre afferents in a dose-dependent manner in both naive and nerve injured animals, with low concentrations facilitating and high concentrations markedly inhibiting mechano-nociceptor activity. Further, use of the galanin fragment Gal2-11 confirmed that the effects of galanin were mediated by activation of galanin receptor-2 . The inhibitory effects of peripheral GalR2 activation were further supported by our demonstration that after PSNI, mechano-sensitive nociceptors in galanin over-expressing transgenic mice had significantly higher thresholds than in wild type animals, associated with a marked reduction in spontaneous neuronal firing and C-fibre barrage into the spinal cord.These findings are consistent with the hypothesis that the high level of endogenous galanin in injured primary afferents activates peripheral GalR2, which leads to an increase in C-fibre mechanical activation thresholds and a marked reduction in evoked and ongoing nociceptive responses. The neuropeptide galanin is expressed at low levels in ~5% of small diameter neurons in the intact adult rodent dorsal root ganglion (DRG) -3. HigheBehavioural studies have demonstrated that intrathecal (i.t.) administration of galanin modulates nociception in a dose-dependent manner, with facilitation of nociceptive reflexes at low concentrations of galanin ,11 and aThe observed anti-nociceptive effects of high levels of endogenous or exogenous galanin are mediated by the activation of one or more G-protein coupled galanin receptors . Studies using in-situ hybridization have shown that GalR1 and GalR2 mRNAs are expressed by 51% and 83% of adult rat DRG neurons, respectively . The levThe short half-life of galanin and Gal2-11  in pIn summary, it has not been possible to directly analyse whether the anti-nociceptive actions of galanin are principally peripherally and/or centrally mediated, nor to dissect the roles played by each galanin receptor subtype in nociceptive processing in the adult animal. The aim of the present study was to test the hypothesis that peripheral activation of GalR2 can modulate nociceptive C-fibre afferent mechanical responses in naive rats and mice and that these effects are altered in the PSNI model of neuropathic pain. Here we show that administration of low concentrations of galanin and Gal2-11 directly into the receptive field of intact but injured sensory afferents facilitates, and high concentrations markedly inhibit mechano-nociceptor activity. Further, mechano-sensitive nociceptors in Gal-OE mice had significantly higher thresholds after PSNI than in WT mice, associated with an abolition of spontaneous neuronal firing, the neural correlate of ongoing pain.These findings are consistent with the hypothesis that the high level of endogenous galanin in injured primary afferents activates peripheral GalR2, which leads to an increase in C-fibre mechanical activation thresholds and a marked reduction in evoked and ongoing nociceptive responses. This would be expected to lead to a decrease in C-fibre barrage into the spinal cord, which in turn would reduce central sensitisation and allodynia.We first studied whether administration of galanin into the peripheral receptive field modulates neuronal activity of mechanically sensitive cutaneous primary afferents. We also tested whether these effects were dose-dependent, using doses similar to those previously described to cause facilitation and suppression by i.t. administration . In adulWe then confirmed that similar responses to galanin in mechanically sensitive C-fibre afferents were also present in mice. In adult intact naive CBA/Bl6 mice 10 uM galanin was injected subcutaneously into the peripheral receptive field of C-fibre nociceptors. This increased mechanical thresholds  in rats and mice induces a robust increase in mechanical allodynia three days after saphenous nerve injury which lasts for at least 14 days ,34, and Nerve injured adult rats were used three days after PSNI when the degree of mechanical allodynia had reached its peak  and all We applied the PSNI model to the previously described Gal-OE and strain-matched WT mice. The Gal-OE mice over-express galanin in the DRG, spinal cord and brain under the control of the 20-kb galanin promoter ,35 and hTo determine whether the reversal of the mechanical allodynia after PSNI in the Gal-OE mice was attributable to altered primary afferent properties, cutaneous primary mechano-sensitive afferents were studied in Gal-OE mice seven days after PSNI  and compared to allodynic WT mice. Mechano-sensitive nociceptors (pooled C- and A delta fibres with conduction velocities (CV) of 0.33-8.5 m/s) in Gal-OE mice after PSNI had significantly higher thresholds than those from naïve Gal-OE mice  in rat and mouse, in the intact state and after the PSNI model of neuropathic pain. Our findings demonstrate that the principal effects of peripherally administered galanin are on high threshold C-fibre mechano-sensitive (HTM) primary afferents i.e. nociceptors. In intact adult animals the mechanically-evoked thresholds of nociceptive afferents is enhanced by s.c. administration of low doses of galanin or Gal2-11 directly into the receptive field, whilst at higher concentrations the mechanical thresholds of HTM afferents are greatly inhibited. This suggests that galanin has a similar dose-dependent effect on primary afferent nociceptors to those previously reported with respect to the spinal flexor reflex ,39. Of nHaving demonstrated a clear biphasic nociceptive response to peripherally administered galanin and Gal2-11 in the intact adult rodent we then used the PSNI neuropathic pain model to study the effects of peripheral administration of both ligands and transgenic over-expression of the neuropeptide on peripheral sensitisation. There is now widespread acceptance that the behavioural hypersensitivity that follows nerve injury is attributable to sensitisation of neuronal networks in the central nervous system -42. In aOur findings in the rat after PSNI demonstrate that s.c. administration of 100 nM galanin or Gal2-11 decreased, and 10 uM increased, the mechanical activation thresholds of nociceptive afferents. The magnitude of these changes was very similar to that observed in the intact rat. Previous work by Wiesenfeld-Hallin had shown that the depressive effect of i.t. galanin on the flexor reflex occurred more often and at lower doses of galanin after sciatic nerve axotomy compared to intact rats . We haveThe application of the PSNI model to the Gal-OE transgenic mice, which over express galanin in the DRG, spinal cord and brain, demonstrated a reversal in allodynia in the Gal-OE mice. These findings are paralleled by an abolition in nociceptor spontaneous activity and the calculated afferent barrage into the spinal cord, further supporting a peripheral anti-nociceptive role for galanin/GalR2. After nerve injury the raised levels of endogenous galanin in the DRG and in the nerve trunk following anterograde transport of galanin from the cell body to the site of injury , could eIn the present study we have shown that the biphasic nociceptive responses to peripherally administered galanin and the GalR2/3-specific ligand Gal2-11  in intaq/11 which leads to an increase in calcium influx and neuronal excitability [To date, the majority of published work using the GalR2/3 specific agonist Gal2-11 has shown that central GalR2 activation plays a predominantly stimulatory role with regard to nociception. Intrathecal infusion of low dose Gal2-11 in the intact rat reduces mechanosensory thresholds  and peritability . These rtability . More retability . Similartability . This cotability  and provi (inhibiting adenylyl cyclase and thus nociception) and to Gq/11  by which activation of GalR2 by low dose galanin or Gal2-11 facilitates nociceptor and spinal flexor reflex activity and inhibits these same neurons at higher doses are unclear. Studies using in-situ hybridization (there are no antisera specific for either receptor subtype that can be used for immunocytochemistry) have shown that the majority of the neurons in the DRG express both GalR1 and GalR2 mRNAs  whilst iiewed in , and thul stores . Similare kinase . Both ofOur current findings and those of Wiesenfeld-Hallin raise the issue of whether the local extra-cellular levels of galanin after nerve injury are sufficient to inhibit nociceptive responses via activation of GalR1 and/or GalR2. Previous work by Duggan et al using antibody microprobes has shown an extensive basal release of galanin in the dorsal horn of intact adult rats, with a significant rise in release in the superficial layer of the cord ipsilateral to peripheral nerve injury ,56. ThesIn summary, we have demonstrated yet another layer of complexity in the "galanin pain story". Our data supports the hypothesis that peripheral activation of GalR2 by the raised levels of endogenous galanin in injured primary afferents increases C-fibre thresholds and decreases evoked and spontaneous activity. These changes in primary afferent properties lead to a decrease in C-fibre barrage into the spinal cord which would be expected to reduce central sensitisation and allodynia. These findings will need to be further substantiated in intact rodents and the neuropathic pain models described above, once GalR2-specific drug-like agonists are identified and characterized. Of note, the previously described loss of a subset of small diameter unmyelinated neurons that are likely to be nociceptors in the DRG of Gal-KO  and GalRExperiments were performed on 8 week old male Wistar rats and 8 week old male Gal-OE and strain matched wildtype (WT) CBA/Bl6 mice ,36. Anim2 . An incision was made in the inguinal fossa of the right hind leg exposing the superficial saphenous nerve. The saphenous nerve was isolated proximal to any branch points using blunt dissection with fine forceps from the surrounding tissues. PSNI surgery prior to electrophysiogical experiments had to be positioned to allow sufficient nerve proximal to the injury site to allow recordings to be made. A size 4.0 sterile silk suture in rat (size 7.0 in mice) was used to ligate ~50% of the total nerve, with the lateral half of the nerve being ligated for consistency. The skin was sutured with a 4.0 sterile silk suture. Animals were monitored and allowed to recover thereafter for the duration of the experiments. Electrophysiological experiments were carried out three days after PSNI in rat and seven days in mice.Partial saphenous nerve ligation injury (PSNI) was performed as previously described ,34,37. AAnaesthesia was induced with sodium pentobarbital  and were then maintained deeply anaesthetised and areflexive using continuous infusion of sodium pentobarbital . Body temperature was maintained within physiological limits by means of a feedback controlled heater and rectal thermister. At the end of all experiments, rats and mice were killed by an overdose of sodium pentobarbital.An incision was made along the right inguinal fossa to expose the saphenous nerve. Using blunt dissection, skin was freed from surrounding tissue and this was used to create a pool. To keep the tissue hydrated the pool was filled with warmed mineral oil. In the mouse, the pool was lined with Xantopren XL, which set once mixed with Activator Universal . This prevented mineral oil leakage, due to the porosity of mouse skin. The saphenous nerve was exposed and the epineurium was removed to allow fine filaments to be dissected from the main trunk of the nerve. Filaments were placed on bipolar platinum recording electrodes for differential recordings of neuronal activity to identify individual afferent fibres. After nerve injury, recordings were made proximal to the site of injury. This recorded activity was amplified, filtered and captured for off-line analysis by a micro1401  and P.C interface (Viglen) using Spike 2 software .A search protocol was used to identify afferents that innervated the hindpaw (no higher than the ankle) and had identifiable receptive fields. Initial characterisation of afferents involved mechanical search stimulus (brush/glass rod/probe/pinch with blunt forceps) and monopolar electrical search stimulation. The mechanical search stimulus was used to apply pressure to discrete areas of the foot to stimulate robust responses from mechanically sensitive afferents. Electrical stimulation involved the use of a monopolar (cathode) electrode. The monopolar electrode was used to determine conduction velocity (CV) for fibres in m/s. This was applied to the receptive field on the hindpaw . The CV for afferents were defined as C-fibres <1 m/s, and A-fibres as >1 m/s ,59. ThesOnce a single primary afferent receptive field had been identified, it was further characterised. Brush, pinch with blunt forceps and the use of direct calibrated force with von Frey hairs  were all applied to the receptive field to determine mechanical response properties. Mechanical thresholds were identified by applying a range of von Frey (vF) hairs, with each vF applied no more than three times to the receptive field for 5 seconds as previously described ,60-62. UMechano-nociceptor afferent activation threshold data in intact naïve and PSNI groups after galanin or Gal2-11 injections were normalised to the respective mean baseline thresholds, allowing direct comparisons between the groups. The total primary afferent barrage was calculated as previously described , from thVehicle and drugs were administered using an insulin needle (BD micro fineTM). 30ul subcutaneous injections (s.c.) were administered just outside the identified receptive field. The initial s.c. injection involved injecting 30ul of vehicle  thirty minutes after characterisation of the afferents. Five minutes later mechanical thresholds and evoked activity were recorded. If mechanical activation thresholds and/or mechanical evoked activity were significantly diminished by the vehicle injection , the effect of the drug was not investigated. If afferent properties were unchanged by vehicle then the drug was injected at the same site thirty minutes after vehicle injection. Mechanical thresholds and evoked activity were determined at one and/or five minutes after injection. At one minute, only the activation threshold was identified due to the time constraints of the experiment. Different concentrations of galanin  and the GalR2/3 agonist Gal2-11  were administered. Repeated vehicle  injections showed no change in mechanical activation threshold (data not shown).The day prior to behavioural testing mice were placed in transparent perspex enclosures and habituated to the testing environment for a minimum of 15 minutes until they settled. Habituation occurred prior to all behavioural testing sessions. Mechanical withdrawal thresholds were recorded from both ipsilateral and contralateral hind paws. Mechanical withdrawal thresholds were determined using a series of calibrated von Frey filaments . Each von Frey hair ranging from 0.16 g to 2 g was applied to the medial plantar surface of each hindpaw 5 times for a maximum period of 5 seconds or until a withdrawal was elicited. The 50% mechanical withdrawal thresholds , were then calculated from stimulus/response curves, generated as previously described ,37,58.Data are shown as mean ± SEM. Mechanically evoked activity before and after drug along with mechanical withdrawal testing were compared using one way ANOVA with post hoc Bonferroni tests . Activation thresholds were compared using either one-way ANOVAs with post hoc Bonferroni multiple comparison test or paired T test .The authors declare that they have no competing interests.RH carried out nociceptive behaviour and teased fibre electrophysiological experiments. RH, LFD and DW were responsible for experimental design and drafting of the manuscript. All authors have read and approved this final version of the manuscript.


Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development.Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation , as well as gene-specific determinants that can fine-tune expression. We present a novel approach,  Modular regulatory network learning with per gene information. When applied to examine transcriptional responses in two distinct processes, stress response and cellular differentiation, MERLIN accurately reconstructed regulatory programs of individual genes while revealing regulatory module organization and predicted upstream signaling proteins for regulatory modules. MERLIN is applicable to different environmental, developmental and disease contexts to dissect regulatory programs and ultimately build network-based predictive models of cellular states.The state of a cell is largely determined by the genes the cell expresses. Transcriptional control of gene expression is exerted by transcription factor proteins that bind to regulatory regions of genes and affect their expression. Transcriptional programs have a modular organization enabling multiple genes to be coordinately regulated, and at the same time are fine-tuned for each gene through interactions of transcription factors with a gene's regulatory region. Transcription factors are themselves controlled by upstream signaling proteins, that in turn can be transcriptionally controlled. This complex process of gene expression control is described by a regulatory network that captures who regulates whom. A key challenge in systems biology is to reconstruct regulatory networks that capture precise gene-specific regulatory information, as well as the modular organization of transcriptional programs. We developed a novel regulatory network inference approach, MERLIN,  It then iterates over two steps , but the performance was much worse than any of the methods above.We compared the quality of networks inferred by MERLIN to those inferred from three other algorithms using several criteria defined below. The algorithms include a linear regression per-gene network inference method (LINEARREGR), GENIE3 a state-of-the-art per-gene network inference algorithm n = 100, 200, 300, 400, 500, 1000 genes using GeneNetWeaver (GNW) We used both simulated gene expression data where the ground truth of the networks generating the data were known, as well as real gene expression data where the ground truth networks are not known. Simulated data was generated for networks of different number of genes, Edge-based comparison used fold enrichment and the area under the precision-recall curve (AUPR) Figure S1A, Regulator-based comparison measured the number of regulators whose targets significantly matched between the true and inferred networks (FDRModule-based comparison measured how many regulators associated with modules in the ground truth networks matched regulators associated with these modules in the inferred networks (We defined three criteria to compare the inferred networks: (a) On simulated data MERLIN outperformed LINEARREGR and MODNET using edge-, regulator- and module-based metrics . Thus MERLIN combines the strengths of both the per-gene and per-module network inference methods, inferring high quality reconstructions of individual regulatory edges, as well as high confidence target sets localized to specific modules.We next used MERLIN results from the Gasch et al data First we asked whether MERLIN modules are indeed coherent groups of co-expressed and co-regulated genes by measuring: (a) the average Pearson's correlation for pairs of genes within a module (Table S1), targets of transcription factors based on ChIP-chip assays or genes with upstream sequence-specific binding motifs. The majority of the modules (63 of 96) were enriched either for genes of the same GO process, ChIP-chip targets of TF, or genes with sequence-specific motif instances of a TF. This enrichment together with the high Pearson's correlations between gene expression profiles assigned to each module suggests that modules inferred by MERLIN are co-expressed gene regulons that capture biological meaningful relationships among genes in a module.Next, we evaluated whether modules are biologically meaningful by testing whether the modules were enriched for genes annotated with specific Gene Ontology (GO) processes http://pages.discovery.wisc.edu/~sroy/merlin.Using the inferred regulatory network and module memberships, we derived a regulator-module relationship network if the regulator's predicted “targets” (defined here merely as the genes whose expression was predicted by the regulators expression pattern) were enriched in a given module (FDR<0.05). This network connected 175 different regulators to one or more of 96 modules  compared to the average . To systematically test these possibilities we computed the Silhouette index for each module, which measures how different a module's expression is compared to other modules. A positive Silhouette index for a module suggests that the expression of the module is distinct in expression from other modules. The Silhouette index was significantly higher than random clusters  were enriched for genes whose proteins display more genetic or physical interactions among each other than expected by random .To test our approach on another dataset, we applied MERLIN to infer transcriptional regulatory networks in a very different biological context: during differentiation of human embryonic stem cells to neural progenitor cells. Four time courses were available that represent the first seven or eleven days of differentiation from the pluripotent state (either ES or iPS cells) to states that represent early neural precursor cell types. Each cell line was treated by two different conditions to induce neural differentiation , ChIP-seTable S2). In contrast, genes in Module 7 were associated with an opposite pattern of initial repression in the earlier time points (up to day 4) and upregulation at later time points. Several lines of evidence, in addition to the opposite temporal dynamics, suggested that Module 1 is associated with the maintenance of the ES pluripotent state, whereas Module 7 is associated with neural fate specification. First, genes associated with maintenance of the ES state such as POU5F1 are represented in Module 1. Second, Module 1 is enriched for ChIP seq-based targets of several factors, obtained from the ENCODE project Third, 16 of POU5F1's 23 MERLIN predicted targets (7C), two factors critical for pluripotency Fourth, Module 7's genes are associated with neural-specific functions such as nervous system development, neurogenesis (FDR<0.05) suggesting these genes are neural lineage specific genes. Finally, using a recent set of lineage specific genes, we found Module 1 to be enriched for the ES-specific and Mesendoderm, an early differentiation time point, genes (FDR<1E-51), and Module 7 to be enriched for the neural lineage-specific genes The majority of the transcriptional changes are captured in two large modules, Module 1 with 1177 genes, and Module 7 with 974 genes . Interestingly some of the regulators associated with these modules based on ChIP-seq, DNAse1 filtered motif instances While the majority of the transcriptional response was captured by modules 1 and 7, we found several smaller modules that exhibited patterns of more complex temporal dynamics .We found that while GENIE3, a state-of-the-art per-gene method performed well using edge-based metrics, when applied to yeast, it did not perform as well on module-based measures. In contrast, MODNET, a state-of-the-art module-based method, performed poorly using edge-based measures, but performed better on module-based measures. This improvement in performance was due to the module information allowing us to restrict ourselves to targets that are co-expressed in a module and thereby exhibit coherent function. Indeed identifying co-expressed sets of genes is a pre-requisite to identifying meaningful Our application of MERLIN to the yeast stress response data and the human embryonic stem cell differentiation data reveals its ability to dissect the transcriptional regulatory programs especially in large datasets that measure diverse conditional responses. In particular, in the human embryonic stem cell differentiation data, the module with genes that are up-regulated in the later time points but not in the earlier (ES) time points had little or no enrichment in the ChIP-seq targets. Incidentally, ChIP-seq datasets were generated in the H1-ES (human embryonic stem cells) cell line, and the modules in which there was enrichment comprised genes that were most expressed in the earlier time points that reflect a more ES-like state. MERLIN therefore captures context-specific regulatory interactions. Such interactions are most enlightening for modules exhibiting induced expression in conditions or tissues that have not been studied in great detail, perhaps due to under-sampling of these biological responses. Even in the yeast stress response data, which is a very well studied dataset, we derived new insight into the role of HOG1 and the downstream modules that might be regulated through intermediate transcription factors as we discuss below.Our ability to capture these regulatory networks likely centers on the inherent feedback and feed-forward loops in eukaryotic transcriptional responses: genes encoding signaling proteins are often themselves targets of the pathways they encode. In other cases, genes encoding regulatory proteins  are augmented in anticipation of their future need; nonetheless, their expression patterns remain predictive of physiologically related genes. These features are likely to be common to many different responses across diverse organisms.An important difference between the yeast and the human dataset was the number of biological conditions the genes were measured in. In particular, in yeast we had more than a dozen environmental perturbations whereas in human we had four relatively similar kinds of perturbations. While the relatively uniform nature of expression dynamics in this dataset enables us to identify the major patterns of expression as two large modules, adding more diverse perturbations can help us identify smaller fine-grained modules as in the yeast dataset that are easier to interpret biologically and for follow-up studies with smaller functional assays.et alThere are several directions of future work associated with MERLIN. An immediate step is to more accurately model expression levels from next-generation sequencing data by considering conditional negative binomial or Poisson distributions The increasing abundance of environment-specific, tissue-specific and disease-specific transcriptional profiles, especially for poorly characterized organisms, makes our ability to infer regulatory networks especially important. Approaches such as MERLIN that identify the gene-specific regulatory information for individual genes, while revealing the global modular organization of regulatory networks can significantly advance our understanding of wiring and combinatorial regulation of transcriptional responses governing cellular states.The MERLIN approach is based on a probabilistic graphical model of network inference where the goal is to infer regulatory networks by maximizing the likelihood of observed expression data given a network structure The model that MERLIN learns has three components: Given Given a module assignment and a graph at a particular learning iteration, The likelihood Algorithm 1 in Text S1) begins with a set of modules The algorithm  2) 3) There are three parameters in MERLIN that need to be specified:  number of good-sized modules, where a good-sized module must have at least 5 genes, (b) percentage of total genes that are in the good-sized modules. Ideally we would be able to include as many genes as possible in these good sized modules without losing biological coherence.S4). This was true for both the high modularity . In general, the optimal value of We found that the most important parameter that affected F-score was Figure S6). Because the networks we infer are directed regulatory networks, standard measures of modularity which are defined for undirected graphs were not sufficient. We defined a measure of regulatory modularity (defined below) that measures the extent of shared regulators of genes in a module compared to shared regulators with genes outside a module. We find that as we increase Finally, we studied the effect of the We applied MERLIN to two transcriptomic datasets, one in yeast For the human data, we had RNA-seq read counts from four time courses, two each for two cell lines: human ES line H1 and human iPS cell line DF19.7. We assembled these reads into a per gene count using RSEM To apply MERLIN to each of these data sets we started with five random initializations. For the yeast data we split the data into five equal folds and learned models on four fifths of the data, and repeated this five times. A high confidence network was that which had an edge in three of the five random initializations. For the human data since we did not have as much data as in yeast, we used the entire data, but generated different MERLIN networks by starting with five different random initializations of clusterings We defined regulatory modularity for a set of modules, For each module with We compared the performance of MERLIN on simulated networks to the performance of three other algorithms using edge-based, regulator-based and module-based metrics. These comparisons were done on simulated ground truth networks where the true networks were known. We used GeneNetWeaver (GNW) to generate simulated expression data We first examined the agreement between the ground truth networks of different sizes to the inferred networks using standard precision-recall measures In addition to AUPR we also compute the significance of overlap of edges between true and inferred edges using a hypergeometric In addition to edge-based comparisons, we developed measures that compare the inferred networks based on each regulator's target sets. This is done by considering one regulator at a time. For each regulator, To assess regulator-module relationships in the simulated datasets we used the modules that were part of the ground truth simulation. We generated the “true” regulator-module graph by asking what regulators' targets were significantly over-represented  from MEME suite http://ftp.ebi.ac.uk/pub/databases/ensembl/encode/integration_data_jan2011/byDataType/peaks/jan2011/spp/optimal/hub/, and associated a gene to the transcription factor if its peak was within ±2000 bps of the TSS of the gene.To map ChIP-seq and DNAse1 sites in the human dataset we focussed on ±2000 bps of the transcription start site (TSS) of a gene, where the TSS coordinates were obtained from Gencode10 as used in the ENCODE project Figure S1Edge-based comparisons on simulated networks of different sizes using different per-gene and per-module methods of network inference. A. Performance measured using Area under the precision recall (AUPR) curve. B. Performance measured using fold enrichment of predicted network edges to true network edges, where fold enrichment is defined as the ratio of the observed and expected fraction of true edges.(PDF)Click here for additional data file.Figure S2Comparison of MERLIN to per-gene linear regression approach based on prediction error. Shown are the number of genes in which MERLIN is significantly better or worse than the linear regression-based per-gene approach. Prediction of expression is evaluated using Pearson's correlation between true and predicted expression of a gene using five-fold cross validation. The Pearson's correlation in the five folds are used to test whether the correlations are significantly higher or lower between two methods using a one-sided t-test.(PDF)Click here for additional data file.Figure S3Effect of MERLIN hyper-parameter values on network reconstruction performance for high modularity networks. Shown are the F-scores for networks of different sizes of high modularity for different parameter settings of sparsity ((PDF)Click here for additional data file.Figure S4Effect of MERLIN hyper-parameter values on network reconstruction performance for high modularity networks. Shown are the F-scores for networks of different sizes of low modularity for different parameter settings of sparsity ((PDF)Click here for additional data file.Figure S5Effect of different parameters on network structure recovery and module level statistics. Shown are the F-scores on two sets of three networks with 100, 300 and 500 nodes, the top set has high modularity and the bottom set has low modularity. The modularity during network generation was controlled by a parameter specifying the probability with which a target and regulator come from the same module. F-score and module statistics are shown for different values of parameter settings controlling sparsity ((PDF)Click here for additional data file.Figure S6Effect of module effect hyper-parameter on regulatory modularity of the inferred network. Shown are measured regulatory modularity of the inferred network for different values of the module effect parameter ((PDF)Click here for additional data file.Table S1Gene Ontology process enrichment for MERLIN modules on yeast stress data. This table lists the Gene Ontology process enrichment for the modules/clusters inferred using MERLIN on Gasch stress data. Each row corresponds to a GO process and the columns correspond to the Module ID, term name, (TXT)Click here for additional data file.Table S2Gene Ontology process enrichment for MERLIN modules inferred on human ES cell differentiation data. This table lists the Gene Ontology process enrichment for the modules inferred using MERLIN on the human ES cell differentiation data. The file format is as in Table S1.(TXT)Click here for additional data file.Table S3MSigDB term enrichment for MERLIN modules inferred on human ES cell differentiation data. This table lists the MSigDB term enrichment for the modules inferred using MERLIN on the human ES cell differentiation data. The file format is as in Table S1.(TXT)Click here for additional data file.Text S1Pseudo code and additional details of the MERLIN algorithm.(PDF)Click here for additional data file.


Recent advances in industrial non-contact scanners offer unprecedented opportunities for quality assessment of dental restorations. The majority of investigations published to date are limited to local two-dimensional results. A triple-scan protocol for virtual fit assessment of multi-unit screw-retained implant restorations is presented in this technical report. The advantages for application in biomechanical research include detailed three-dimensional information on internal component congruence in implant superstructures to be used in mathematical models. One inherent shortcoming is the measurement of misfit in one or two linear dimensions, lacking the important third dimension.11Protocols such as external vertical gap measurements with microscopes, torque–angle signature analysis and strain gauge measurements are routinely used to assess precision of fit for implant frameworks.13 Non-contact optical precision scanners are used to digitize objects, and best-fit registration algorithms are used for virtual alignment. The underlying principle of these techniques, which are adopted from industrial quality control applications, is that the software algorithm attempts to achieve the greatest possible contact area of selected surfaces. However, dental products are free-form objects and distortion is always 3D. Thus, results may potentially be falsified, as areas of greater misfit are virtually approximated and may not accurately represent the actual discrepancy. The objective of the technique proposed here is to describe a registration protocol ensuring correct spatial orientation of components in relation to each other. The validity and reproducibility of this approach have been previously investigated and a similar protocol is applied for the virtual registration of conventional restorations for natural teeth.14More recent studies have addressed the three-dimensional (3D) nature of the misfit.Manufacture the implant master cast and the respective screw-retained test frameworks according to a defined research protocol .Modify the surfaces and eliminate implant replica reflectivity and frameworks under investigation to accommodate for non-contact optical digitization with either spray coating (e.g. titanium oxide) or surface roughening .If surface coating is applied, utilize an airbrush system to ensure a homogenous and ultra thin coating layer.Fully digitize components using an industrial high-precision non-contact scanner . For high-accuracy surface acquisition, choose the smallest measurement area available for the system.Mount the frameworks under investigation in a special measurement frame  to allow for object digitization from both sides by integrating all measurements into a predefined coordinate system .Attach scan markers  to the implant master cast; scan the master cast solo (MS).Scan and digitize the framework solo (FS).Place the framework on the master cast, tighten framework abutment screws according to the research protocol and scan the framework–master cast (FM) object.Use commercially available software  to generate Standard Tessellation Language (STL) surfaces of the digitized objects .Open the MS-STL and the FM-STL. Select the FM-STL as reference file and pre-align (pre-register) the data sets. For subsequent best-fit registration, select surfaces on the FM-STL, excluding the framework and the implant replicas and match data sets  – Step 1Apply the same protocol in a successive step, to match the FM-STL and the FS-STL. Select the FM-STL as reference CAD and pre-align (pre-register) data sets. For best-fit registration, select the entire outer contour of the FS, excluding the intaglio surfaces in contact with the implant replicas  – Step 2In the third and final step, delete the FM-STL and maintain the aligned FS-STL and MS-STL for subsequent virtual fit assessment according to the defined research protocol  – Step 3To measure gaps between contacting surfaces, select the intaglio surfaces of the framework in contact with implant surfaces or surfaces under investigation according to the research protocol and invert the surface normal .With the implant replica of the master model defined as reference, measure distances to framework surfaces .n = 10/group). Group I conventional cast-on abutments  were used for manufacture of three-unit screw-retained high-noble alloy frameworks. The frameworks were manually adapted on the respective gypsum model, and premature contacts resulting from the casting process were eliminated.From a metal master model based on a patient situation with two implants , 20 polyether impressions  were taken with custom trays. Following established protocols for manufacture of definitive gypsum master casts, models were randomly divided into two groups (2) and frameworks were mounted in special measurement frames (Reference frame). All tests were conducted at an ambient room temperature of 20°C.In group II, implant replicas were digitized utilizing a contact-probe scanner  and screw-retained titanium frameworks were CAD/computer-aided manufacturing (CAM) produced . Following the previously described triple-scan digitization and registration protocol with an industrial non-contact scanner (ATOS SO II), superstructure fit was analysed three dimensionally on each respective master cast. For high-accuracy surface acquisition, the smallest available measurement area was chosen  to differentiate between surface areas towards the pontic site and surface area towards the non-pontic sites and resulting mean distances (millimetre) calculated. Statistical methods applied included the two-sided and exact Mann–Whitney p<0.001). Fit assessment of contacting surfaces for group I indicated shrinkage towards the pontic site, whereas for group II equal circumferential fit was observed . Currently, this is usually done with two-dimensional external vertical gap measurement techniques. However, microscopic analysis is limited to the outermost area of components and does not yield information on internal component fit of mating surfaces.7 By utilizing the external surfaces for data matching of the three scans, the transformation error during registration can be greatly reduced and established registration algorithms applied.14 This differs from other reported approaches for 3D fit assessment of components that require additional materials and highly complex alignment and registration procedures.13The presented triple-scan and registration technique may be applied for future in vitro research projects, because the methodology eliminates a number of shortcomings inherent to currently applied investigative techniques.14 A notable advantage compared to other reported techniques in dental research is that the true spatial orientation of a framework attached to the respective definitive cast is ensured. The danger of eliminating singular irregularities through a general best-fit protocol is eliminated. While the application range of 3D-assessment techniques in dentistry is broad, certain system-intrinsic and object-related factors must be taken into account when protocols are applied. If highly reflective or translucent materials are used, the surface may need to be coated, possibly introducing an additional source of measurement error secondary to system-related measurement accuracy. However, if comparative studies are performed, the absolute values are of minor importance. If high-accuracy measurements are required, high-precision contact-probe scanners could be used for verification purposes.16 Other options include scan systems with a working principle that is independent of material or surface quality or special surface-coating appliances that can deposit defined and homogeneous surface layers. Further studies are needed to investigate the intrinsic measurement system and the protocol-related effects on the measurement accuracy.This approach can be easily applied in a routine laboratory setting without the need for specific metrology expertise because no complex alignment and registration procedures are needed and established best-fit registration algorithms can be applied.17 It is important to note that the differences between manufacturing techniques were not statistically significant if overall  fit was assessed but only if surfaces were investigated separately. This finding underlines the importance of more detailed and sophisticated analytical methods, as an average of 3D distorted components does not necessarily reflect the true congruence/incongruence between two components.The pilot investigation applying the described technique showed that the applied triple-scan protocol and the 3D precision assessment is a valid protocol to obtain detailed information on true fit of components at selective regions of interest. Based on the initial results, conclusions of other scientific publications indicating the superior precision of CAD-/CAM-manufactured components compared to conventional casting techniques for implant-supported/implant-retained superstructures can be confirmed.The presented technique is an easy-to-use method facilitating the 3D internal fit and precision measurements of implant restorations. It can be used to provide valuable data on manufacturing distortion and misfit of implant-retained restorations.


The Taihang Mountain range of north-central China, the Southern region area of Fujian province, and the Chaoshan plain of Guangdong province are 3 major regions in China well known for their high incidence of esophageal cancer (EC). These areas also exhibit high incidences of gastric cardia cancer (GCC). The ancestors of the Chaoshanese, now the major inhabitants in the Chaoshan plain, were from north-central China. We hypothesized that EC and GCC patients in Chaoshan areas share a common ancestry with Taihang Mountain patients. We analyzed 16 East Asian-specific Y-chromosome biallelic markers  and 6 Y-chromosome short tandem repeat (Y-STR) loci in 72 EC and 48 GCC patients from Chaoshan and 49 EC and 63 GCC patients from the Taihang Mountain range. We also compared data for 32 Chaoshan Hakka people and 24 members of the aboriginal She minority who live near the Chaoshan area. Analysis was by frequency distribution and principal component, correlation and hierarchical cluster analysis of Y-SNP. Chaoshan patients were closely related to Taihang Mountain patients, even though they are geographically distant. Y-STR analysis revealed that the 4 patient groups were more closely related with each other than with other groups. Network analysis of the haplogroup O3a3c1-M117 showed a high degree of patient-specific substructure. We suggest that EC and GCC patients from these 2 areas share a similar patrilineal genetic background, which may play an important role in the genetic factor of EC and GCC in these populations. Esophageal cancer (EC) is one of the most common fatal cancers worldwide. China has geographical “hot spots” of high EC incidence. A well-known region with high risk of EC in China is the Taihang Mountain area between Henan, Hebei, and Shanxi provinces in north-central China, the famous “Asian EC belt” ranging from the Caucasian mountains, across northern Iran, all the way to northern China The geographic features of south-littoral Chaoshan and north-central Taihang Mountain area are distinct, but the incidence of EC and GCC is high within these 2 regions The 3 main populations in Chaoshan area include 2 Han populations – Chaoshanese with Chaoshan dialects and Hakka with Hakka dialects – and one local aboriginal She population. Since the Qing Dynasty (216∼207 BC), the Henan and Shanxi Han people of north-central China migrated into the Chaoshan area in Guangdong province via Fujian province because of war and famine. They gradually became the predominant inhabitants of the Chaoshan area and are called Chaoshanese The Hakka and Chaoshanese populations show the characteristics of their unique cultures Our previous research of Y-chromosome and mtDNA haplogroups concluded that the EC high-risk populations in Taihang Mountain, Fujian Minnan and Guangdong Chaoshan share a similar patrilineal and matrilineal genetic background Y-SNP genotyping revealed the haplogroup frequencies of the Chaoshan EC or GCC patients, Taihang Mountain EC or GCC patients, and Chaoshan Hakka and She populations. The highest haplogroup of Chaoshan patients was O3a3c1-M117, which is the characteristic haplogroup for Northern East Asians . It was Principal component analysis (PCA) involves a mathematical procedure that transforms a number of correlated variables into a  number of uncorrelated variables called principal components. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. In the principal-component plot, the smaller the distance of two populations, the closer the genetic relationship is between the two. Y-SNP haplogroup frequencies for the patient groups and high-risk population from the same area were positively correlated, and frequencies for all patient groups were positively correlated with the Fujian and Chaoshan high-risk populations . FrequenTo study the affinity among the 4 patient groups and their relationship with other Han and minority nationalities, we analyzed Y-SNP data by hierarchical cluster analysis with average linkage (between groups). We compared 17 Chinese Han populations , 3 southern minority nationalities , DYS390, DYS391, DYS392, DYS393 and DYS394. We included 6 additional Chinese populations and 3 high-risk populations: Zhejiang ST distance matrix, we constructed an unrooted neighbor-joining tree  Chaoshan patients–72 EC and 48 GCC patients; 2) Taihang Mountain patients–49 EC and 63 GCC patients; and 3) Chaoshan EC low-risk population–24 She people from Chaoshan Fenghuang Mountain and 32 Chaoshan Hakka from Chaoshan Puning county. Disease in all patients was confirmed pathologically. All participants involved in our study were given written informed consents. The study was approved by the ethical review committee of Shantou University Medical College. Genomic DNA was extracted from whole blood by the TIANamp Blood DNA kit (DP318-03) .Y-SNPs were genotyped by Sequenom MassARRAY iPLEX Gold module (Sequenom Inc.) . In the network map, individuals with the same mutations of Y-STRs were in the same node, and one node could generate other nodes due to gradual Y-STR mutation The extent of genetic differentiation of the populations was estimated by the RChaoshanese are descendants of north-central China Han people. North-central Chinese Han began to migrate into southern China beginning in the Qin Dynasty (216 BC). The Han Dynasty (206 BC–220 AD) experienced another 3 waves of large-scale migration into southern China because of the decrease in the native population in this area. Gradually, over 2,000 years, the north-central Chinese Han became the main population – Chaoshanese in the Chaoshan region, called Helao, who directly migrated from north-central China, or Fulao, who first migrated to Fujian Minnan, then to Chaoshan with well-maintained language and customs from north-central China. The Taihang Mountain people in north-central China, Fujian Minnan and Chaoshan areas are well known for their high incidence of EC With the development of diagnostic techniques and improved epidemiology, more GCC cases have been confirmed in these areas. EC and GCC are the 2 most common cancers in these 3 areas. Our previous genetic research showed that high-risk populations in these 3 areas share a common ancestry On Y-SNP principal component analysis, the paternal structure for Chaoshan patients differed from that for Chaoshan Hakka and She populations, although they are in geographic proximity and Chaoshan Hakka are also descendants of north-central Chinese Hans. Chaoshan patients clustered closely with the Fujian and Henan high-risk population and patients, although they are geographically distant. Chaoshan Hakka and She populations clustered together, which agrees with historical records. Chaoshan Hakka mainly inhabit the mountain area, for more gene flow with the She population, who also live in the mountain area. Y-SNP haplotype frequencies were positively correlated among patients, which further supports their close genetic affinity. The results of hierarchical cluster analysis also supported the close genetic affinity among patients and high-risk populations. Phylogenetically, the patient groups were more closely related to each other than with the high-risk population . NetworkRecent genome-wide association studies from China high-risk areas showed significant association of a variant at 10q23 in PLCE1 and both esophageal squamous cell carcinoma and gastric cardia adenocarcinoma, which highlights the common genetic mechanisms that may contribute to the etiology of both cancers We suggest that EC and GCC do not occur at random in high-risk populations but are closely associated with a certain patrilineal background structure and these related patients may inherit a pathogenic genetic structure from their common ancestors.In summary, the patrilineal genetic structure of Chaoshan and Taihang Mountain patients is similar, and patients have closer affinity with each other than with the high-risk populations. The EC and GCC patients share a recent common ancestor. In contrast, the Chaoshan Hakka and She populations have a relatively distant relationship with Chaoshanese people, which may explain in part the high incidence of EC and GCC in Chaoshanese people.Table S1Raw data for individual Y-SNP.(XLS)Click here for additional data file.Table S2Raw data for individual Y-STR.(XLS)Click here for additional data file.