Prunus mume Sieb. et Zucc.) is a famous ornamental plant and fruit crop grown in East Asian countries. Limited genetic resources, especially molecular markers, have hindered the progress of mei breeding projects. Here, we performed low-depth whole-genome sequencing of Prunus mume ‘Fenban’ and Prunus mume ‘Kouzi Yudie’ to identify high-quality polymorphic markers between the two cultivars on a large scale.Mei  cultivar, producing a set of informative diversity data. We also analyzed the frequency and distribution of detected InDels and SSRs in mei genome and validated their usefulness as DNA markers. These markers were successfully amplified in the cultivars and in their segregating progeny.A total of 1464.1 Mb and 1422.1 Mb of ‘Fenban’ and ‘Kouzi Yudie’ sequencing data were uniquely mapped to the mei reference genome with about 6-fold coverage, respectively. We detected a large number of putative polymorphic markers from the 196.9 Mb of sequencing data shared by the two cultivars, which together contained 200,627 SNPs, 4,900 InDels, and 7,063 SSRs. Among these markers, 38,773 SNPs, 174 InDels, and 418 SSRs were distributed in the 22.4 Mb CDS region, and 63.0% of these marker-containing CDS sequences were assigned to GO terms. Subsequently, 670 selected SNPs were validated using an Agilent’s SureSelect solution phase hybridization assay. A subset of 599 SNPs was used to assess the genetic similarity of a panel of mei germplasm samples and a plum (A large set of high-quality polymorphic SNPs, InDels, and SSRs were identified in parallel between ‘Fenban’ and ‘Kouzi Yudie’ using low-depth whole-genome sequencing. The study presents extensive data on these polymorphic markers, which can be useful for constructing high-resolution genetic maps, performing genome-wide association studies, and designing genomic selection strategies in mei. Prunus mume Sieb. et Zucc., 2n=2x=16) is a member of Rosaceae, sub-family Prunoideae  . These aWhole-genome sequencing allowed us to detect 200,627 candidate SNP markers in ‘Fenban’ and ‘Kouzi Yudie’. The density of these SNP markers was 847 SNPs/Mb in mei assembly sequences, which was notably lower than that in potato   and sorgTo validate the quality of identified SNPs for a genotyping system, we randomly selected a set of 670 SNPs, which were assembled into an Agilent’s SureSelect solution phase hybridization assay. The 670 SNPs contained 581 SNPs at an average spacing of about 340 Kb widely distributed across eight mei pseudo-chromosomes and 89 SNPs located in assembly sequences which were not anchored to any mei pseudo-chromosome Figure .Captured DNA was sequenced on an Illumina GA II instrument, generating 4.2 G sequencing data with 78 bp reads from the 24 libraries that had been prepared with the SureSelect method (NCBI database under accession SRA063161), and 3.4 G reads passed through the Illumina chastity filter to produce automatic allele calling for each locus. Each library was sequenced to a specific depth, providing a mean ~20-fold mapped coverage of the targeted region. Of 670 SNPs, 89.4%  produced non-ambiguous data containing 513 SNPs distributed across eight mei pseudo-chromosomes and 86 SNPs located in assembly sequences that were not anchored to mei pseudo-chromosomes ] for SNPs are low , 1.2 μl of 2.5 mM dNTP, and 0.6 U of Taq DNA polymerase . The different mixtures were as follows: 0.9 μl of 10 uM each of forward and reverse primers for SSRs, and 1 μl of these for InDels and added ddH2O to the total volume. The PCR amplifications of SSRs and InDels were performed with the following program: 5 min at 95°C; followed by 25 cycles of 40 s at 95°C, 30 s at the optimized annealing temperature for each primers , and a regular reverse primer. The PCR reactions of SSRs and InDels were respectively conducted in a 10 μl mixture. The same mixtures included 50 ng of the genomic DNA, 1 μl of 10 × buffer [20 mM Tris–HCl (pH 8.4), 20 mM KCl, 10 mM  and ‘Kouzi Yudie’ (KZYD) and their F1 hybrids (HB): (A) and (B) loci heterozygosity in the ‘Fenban’, two alleles; (C) loci heterozygosity in the ‘Kouzi Yudie’, two alleles.Click here for fileRelative frequency for mono-, di-, and trinucleotides of SSR repeat motifs.Click here for fileExamples of amplifications of SSR primers labeled with FAM fluorescent dyes. Panels indicated data from ‘Fenban’ (FB) and ‘Kouzi Yudie’ (KZYD) and their F1 hybrids (HB): (A) locus heterozygosities in the ‘Fenban’, two alleles; (B) locus heterozygosities in the ‘Kouzi Yudie’, two alleles; (C) locus heterozygosities in parental lines, two alleles; (D) locus heterozygosities in parental lines, three alleles; (E) locus heterozygosities in parental lines, four alleles; (F) locus homozygosity in parental lines.Click here for file


Quantum dots (QDs) have long promised to revolutionize fluorescence detection to include even applications requiring simultaneous multi-species detection at single molecule sensitivity. Despite the early promise, the unique optical properties of QDs have not yet been fully exploited in e. g. multiplex single molecule sensitivity applications such as single particle tracking (SPT). In order to fully optimize single molecule multiplex application with QDs, we have in this work performed a comprehensive quantitative investigation of the fluorescence intensities, fluorescence intensity fluctuations, and hydrodynamic radii of eight types of commercially available water soluble QDs. In this study, we show that the fluorescence intensity of CdSe core QDs increases as the emission of the QDs shifts towards the red but that hybrid CdSe/CdTe core QDs are less bright than the furthest red-shifted CdSe QDs. We further show that there is only a small size advantage in using blue-shifted QDs in biological applications because of the additional size of the water-stabilizing surface coat. Extending previous work, we finally also show that parallel four color multicolor (MC)-SPT with QDs is possible at an image acquisition rate of at least 25 Hz. We demonstrate the technique by measuring the lateral dynamics of a lipid, biotin-cap-DPPE, in the cellular plasma membrane of live cells using four different colors of QDs; QD565, QD605, QD655, and QD705 as labels. H≈20–25 nm) and for which the binding valency towards the target molecule is challenging to control and validate The last two decades have seen a dramatic increase in the utilization of single molecule detection methods in a variety of biological applications More recently quantum dots (QDs) have seen increased use in SPT H) of all but the QD800s. Based on these results we have designed and assembled a fluorescence microscope capable of parallel four color SPT using QD565, QD605, QD655 and QD705. Finally, we demonstrate an application of parallel four color MC-SPT by investigating the lateral dynamics of an artificial lipid, biotin-cap-DPPE in the plasma membrane of a live mouse embryo fibroblast (MEFs).The objective of this work was to extend parallel SPT with QDs from two to four colors. In order to achieve this, we have performed a comprehensive quantitative comparison of the fluorescence intensities, fluorescent intensity fluctuations and size of eight types of QDs . We have used single molecule fluorescence imaging in order to quantify the fluorescence intensity and intensity fluctuations of these QDs. We have furthermore used fluorescence correlation spectroscopy (FCS) to determine the hydrodynamic radii  of the CCD camera  and QD800 (∼85% of time in “off” state) spend a majority of their time in a dark non-fluorescent state while the remaining QDs are principally in their bright fluorescent “on” state. Again, this is likely a consequence of the changed composition of the core/shell materials of these QDs.These results also show that there is a quantitative difference in the fractional “on” time, FRepresentative examples from this analysis of the temporal fluctuations of the fluorescence intensity of thus identified single QDs for each QD color, ±1 mM DTT are shown in H≈6 nm) to a fluorescently labeled mouse IgG1 H. Targeted QDs are available as either chemical conjugates to the basic AMP coating or to the additional amino-PEG coating. In this case, we used QDs that had sAv conjugated directly to the basic AMP coating. The RH of these materials is approximately independent of the QD core-shell where sAv-QD525, sAv-QD565, sAv-QD585, and sAv-QD605 are ≈9.5 nm or ≈1.7× the size of a mouse IgG1, sAv-QD625 and sAv-QD655 are ≈11.5 nm or ≈2× the size of a mouse IgG1, and sAv-QD705 are ≈13 nm or ≈2.3× the size of a mouse IgG1 , in order to account for the observed differences in fluorescence intensity between, in particular, QD565 compared to QD655. We typically also don’t use a fluorescence emission filter in the fluorescence channel for detecting QD705, however, the fluorescence signal in all cases is pre-filtered with a 500 nm longpass fluorescence emission filter , sAv-QD605: δr≈14 nm (N = 1637), sAv-QD655: δr≈15 nm (N = 2689), and sAv-QD705: δr≈28 nm (N = 514)  . We have= 514) . The artificially loaded lipids were labeled with a four color combination of sAv-QD565, sAv-QD605, sAv-QD655, and sAv-QD705, respectively and the lateral dynamics was imaged with 105, are comparable to other similar measurements of the long range diffusion of lipids and membrane proteins in the plasma membrane of live cells, and which were acquired at similar acquisition rates (28).The resulting data analysis of all observed particle trajectories, N, longer than n >20 image frames, using classical MSD SPT analysis of the motion at short time intervals, 1≤n t≤5 corresponding to a time window of ≈40≤t≤≈200 ms is shown in 5, of the lateral dynamics of biotin-cap-DPPE that had been labeled with the various sAv-QDs show that there is a statistical difference between the lateral dynamics of the lipids that had been labeled with sAv-QD655 as compared to all other colors of QDs . But there was no statistical difference in the lateral motion of lipids that had been labeled with either sAv-QD565, sAv-QD605, or sAv-QD705 .The QDs used here were Qdot® ITK streptavidin (sAv) conjugates. These were purchased either in the form of Qdot® Strepavidin Conjugate Sampler Kits or individually from Invitrogen . The product specifications of these QDs are given in W Hg arc lamp for fluorescence excitation. The excitation power at the objective back aperture plane and with a filter cube consisting of a HQ470/40 nm fluorescence excitation filter, a Q495LP dichroic mirror  and a 500LP emission filter was measured to be ≈35 mW/cm2. Data was acquired on an Andor DV887-ECS/BV EMCCD  and using Andor IQ software. The pixel size of this camera is 16×16 µm2. This combined set-up results in that the optical sampling is optimized according to the Nyquist criterion for light microscopy with a projected pixel size of ≈108 nm2. The quantum efficiency (QE) of this camera, according to the manufacturer, exceeds 90% from 500 nm to about 670 nm, dropping to about 85% at 700 nm and 70% at 800 nm  with a 150×1.45 NA UApo TIRFM Olympus oil immersion microscope objective and by use of a 100t 800 nm . Simultaoff), and an asymmetric normal distribution, multiplied by the instrument response function (IRF) of the microscope. The rationale for this fitting model is that the QD intermittency has an inverse power law dependence such that intermittency also frequently occurs at time scales much less that the integration rate of a measurement. This implies that several measurements are of QDs that are partly on and partly off obs(5 or 10 ms in this case), isThe position of single QDs in each image set was determined as has been described before. QDon/off, the width of the mean fluorescence intensity distributions, σon/off, and the asymmetry factor r were free parameters  = 5.6±0.2 nm eff,. The diffusion coefficient, D, is inversely dependent on the molecular size, RH, and is given by the Stokes-Einstein relationThe FCS measurements reported in this paper were made on a custom built multiphoton excitation microscope that has been described previously s is the viscosity of the solvent (here taken as that of pure water at 293K (ηs = 1.002 cP)) and φ is the volume fraction occupied by BSA in the buffer. At 1% BSA (w:v) and using a RH of 3.42 nm for BSA K.QD, in ROIs of 7×7 pixels centered on each of the imported QD positions and in each image in the image sequence. We next counted all ROIs in each image, NQDon (t), for each channel for which IQD/IBkgd>1.01, where IBkgd is the mean pixel intensity of a similar sized ROI but which contained no QD. We next determined the fraction of the counted ROIs, NQDon (t), in each spectral channel relative to the total sum of all ROIs in all four spectral channels, In order to quantify the fluorescence overlap of the QDs in the QuadView microscope configuration, we acquired time-lapse image sequences of immobilized QDs of each color with 10 ms camera integration. Acquired image sequences were analyzed by a combination of ImageJ and Mathematica. To start, we used ImageJ to split the image sequences into quadrants of equal size, each corresponding to a specific spectral channel of 565/40 nm, 605/20 nm, 655/20 nm or >690 nm. Split image sequences were then concatenated into a single sequence and a maximum intensity projection image of the entire sequence was generated. We then used a Particle Tracker plug-in in ImageJ point, t .2+δx2)1/2 where δx and δy are the standard deviations of the determined mean centroids in the x- and y- direction, respectively.In order to determine the localization precision, we used the SPT analysis as described above to repeatedly determine the centroid position of single immobilized QDs. The centroids from several single QDs were then superimposed by subtraction of the mean centroid of each single QD. We next determined the spatial precision, δr, where we define δr = (δx2 and 0.1 g/L MgCl2 (D-PBS) and by bulk loading cells with biotin-cap-DPPE (Avanti Polar Lipids) by use of fatty-acid free BSA  Simultaneous four color QD labeling was done by washing cells 3× in Dulbecco’s PBS with 0.1 g/L CaCllag – (1/3) taqlag is the time interval between images, taq is the camera integration time, and N is the total number of frames in a trajectory. The MSD curves for each single trajectory, m, were curve fit at short time intervals, 1≤n t≤5 (corresponding to ∼40≤t≤∼200 ms) to a model for free diffusion with fit weights equal to the inverse variance (1/σ2)Single acquired time-lapse sequences were split into four quadrants, each corresponding to a single QD color, and analyzed independently by use of a Particle Tracker plug-in in ImageJ 2), to5> is the mean diffusion coefficient for a given molecule and label5D. The K-S test quantifies the distance between the cumulative density function of the two test populations. The null hypothesis is that the two test populations are drawn from the same distribution. The distributions are considered continuous, but are otherwise not restricted.The non-parametric Kolmogorov-Smirnov test (K-S test) was used to evaluate the differences between the different populations of the determined diffusion coefficient Figure S1Cumulative frequency histograms of fluorescence intensities of single sAv-QD525, sAv-QD585, sAv-QD625, and AMP-QD800. Cumulative frequency histograms of the background subtracted fluorescence intensities per pixel of 9×9 pixel arrays of identified single QDs in absence of DTT (left), and in presence of 1 mM DTT (right). These histograms were generated from 3 fields of view in total containing between ∼100≤n≤∼600 single QDs that were each imaged for m = 300 image frames. The total sampling points for each histogram (m n) were ∼30,000≤m n≤∼180,000. The mean fluorescence intensities, IQDon, and fractional intermittency times, FQDon, were determined by non-linear curve fitting (red dashed line) as described in the Methods section.(TIF)Click here for additional data file.Figure S2QuadView microscope filter configuration. Parallel multi-color single QD measurements were acquired using a QuadView image splitter  with dichromatic mirrors Q585LP, Q630LP and Q690LP and with D565/40 m, D605/20 m, and D655/20 m fluorescence bandpass filters from Chroma Technologies . All imaging was done on an Andor DV887-ECS/BV EMCCD . The quantum efficiency  of this camera according to the technical specifications of the manufacturer is approximately independent of the wavelength over a spectral range of ∼500–∼670 nm, with an approximate decrease of 5% at 700 nm, and about 25% at 800 nm. The emission spectra of sAv-QD565 (orange line), QD605 (red line), QD655 (dark red line), and QD705 (black line) were acquired on a NanoDrop 3300 Fluorospectrometer .(TIF)Click here for additional data file.Figure S3Representative fluorescence intensity time traces of single sAv-QD525, sAv-QD585, sAv-QD625, and AMP-QD800. Representative, background subtracted, integrated fluorescence intensities, as a function of time, of identified single QDs that had been absorbed non-specifically to a glass coverslip in the absence of DTT (left) and in the presence of 1 mM DTT (right). Images of QDs with different peak emissions were acquired under identical conditions with continuous blue illumination with 5 ms integration at a frame rate of ∼25 Hz for 300 image frames. Also shown are the fluorescence intensity fluctuations of the background (grey lines).(TIF)Click here for additional data file.Figure S4Localization precision of single sAv-QD525, sAv-QD565, sAv-QD585, sAv-QD605, sAv-QD625, sAv-QD655, QD705, and AMP-QD800: The localization precision of single QD imaging with 5 ms camera integration times was determined by time-lapse imaging and SPT analysis of QDs that had been immobilized on glass. Shown are the determined centroids from N independent single QDs (black points) and the mean centroid  of all centroids, where superpositioning in the center of a projected pixel was done by first subtracting the mean centroid of each single QD, respectively. The centroids are displayed on the projected pixel array of the EMCCD (Projected pixel size of ≈108 nm). The localization precision, δr, was found to be (a) sAv-QD525: δr≈30 nm (N = 254), (b) sAv-QD565: δr≈22 nm (N = 1441), (c) sAv-QD585: δr≈22 nm (N = 1187), (d) sAv-QD605: δr≈14 nm (N = 8598), (e) sAv-QD625: δr≈16 nm (N = 1155), (f) sAv-QD655: δr≈14 nm (N = 2979), (g) sAv-QD705: δr≈16 nm (N = 427), and (h) AMP-QD800: δr≈23 nm (N = 337). Scale bar is equal to 100 nm.(TIF)Click here for additional data file.Figure S5QDon.Localization precision of single sAv-QD525, sAv-QD565, sAv-QD585, sAv-QD605, sAv-QD625, sAv-QD655, sAv-QD705, and AMP-QD800 as a function of the mean fluorescence intensity, I The localization precision of single QD imaging at 5 ms image integration was determined by time-lapse imaging and SPT analysis of QDs that had been immobilized on glass. This plot indicates that the maximum achievable localization precision, δr = (δx2+δy2)1/2, of the described microscope configuration and analysis methodology is δx = δy≈10 nm. This corresponds to a maximum localization precision of ≈1/10 the projected pixel size along either the x- or y-axis. The thus determined precision provides an estimate of the minimum localization precision in the case of completely stationary QDs. However, the precision will always be greater for non-stationary QDs as a result of mobility during the image integration time, tAq. In this case, the precision will also depend on tAq, the particle diffusion rate, D, and the mode of diffusion, i.e. for normal diffusion the precision would be δr = (δx2+δx2+4 D tAq)1/2. It is noteworthy that the precision of SPT measurements is significantly improved in the presence of nanodomains.(TIF)Click here for additional data file.Figure S6QD fluorescence brightness in QuadView microscope configuration. Representative single image frame comparison of the fluorescence intensity of QD565, QD605, QD655, and QD705 in the QuadView microscope configuration. Time lapse images in each instance were acquired with 10 ms camera integration using a Hg arc lamp, a 470/40 nm bandpass excitation filter, a 510LP emission filter, a 150X, 1.45 NA objective, a QuadView image splitter and an Andor EMCCD BV887. All images are displayed at identical brightness and contrast ratios and are hence directly comparable.(TIF)Click here for additional data file.Figure S7Cumulative frequency histograms of fluorescence intensities of single sAv-QD565, sAv-QD605, sAv-QD655, and sAv-QD705 in QuadView configuration. Cumulative frequency histograms of the background subtracted fluorescence intensities per pixel of 9×9 pixel arrays of identified single QDs in absence of DTT. These histograms were generated from one field of view in total containing between ∼60≤n≤∼270 single QDs that were each imaged for m = 300 image frames. The total sampling points for each histogram (m n) were ∼18,000≤m n≤∼81,000. Ensemble average mean fluorescence intensities, IQDon, and fractional intermittency times, FQDon, were determined by non-linear curve fitting (red dashed line) as described in the Methods section.(TIF)Click here for additional data file.Figure S8Quantification of fluorescence overlap of sAv-QD565, sAv-QD605, sAv-QD655, and sAv-QD705 in QuadView configuration. The fraction of the number of detected fluorescent QDs, NQDon(t), in each respective color channel at each time point, t, relative to the total number of detected QDs, n all four spectral channels, (TIF)Click here for additional data file.Figure S9Localization precision of single QD565, QD605, QD655, and QD705 in the QuadView configuration. The localization precision of MC-SPT ín the QuadView configuration with 10 ms image integration was determined by time-lapse imaging and SPT analysis of QDs that had been immobilized on glass. Shown are the determined centroids of N single independent QDs (black points) and the mean centroid  of all superimposed centroids, where superpositioning in the center of a projected pixel was done by first subtracting the mean centroid of each single QD respectively. The centroids are displayed on the projected pixel array of the EMCCD (Projected pixel size of ≈108 nm). The localization precision, δr, of the MC-SPT was found to be (a) sAv-QD565: δr≈21 nm (N = 1028), (b) sAv-QD605: δr≈14 nm (N = 1637), (c) sAv-QD655: δr≈15 nm (N = 2689), and (d) sAv-QD705: δr≈28 nm (N = 514). Scale bar is equal to 100 nm.(TIF)Click here for additional data file.Figure S10Sample distributions of the number of detected QDs in each image frame in each image channel for the MC-SPT example in. The mean ±1 SD of the number of detected sAv-QDs in each image channel for the example in 2, b) sAv-QD605: 0.037±0.004 QDs/µm2, c) sAv-QD655: 0.050±0.004 QDs/µm2, and d) sAv-QD705: 0.037±0.004 QDs/µm2. The overall labeling density for all QDs in all channels was 0.200±0.009 QDs/µm2.(TIF)Click here for additional data file.Figure S11Sample distributions of the length of the detected QD trajectories in each image channel for the MC-SPT example in. A result of the QD blinking is that SPT with QDs results in many short trajectories such that the number of trajectories is much greater than the number of detected QDs in each image frame. In the given example in (TIF)Click here for additional data file.Figure S125, for biotin-cap-DPPE for each sAv-QD conjugate in each image channel for the MC-SPT example inFitted diffusion coefficients, D. The diffusion coefficient, D5, was determined by calculating the MSD curve for each trajectory that were longer than 20 steps, and by curve fitting the initial five points, t < n t <5 t, of each trajectory, as is described in the Methods section. The entire distribution of the fitted values of D5 are shown for all trajectories that were labeled with a) sAv-QD565 (N = 289), b) sAv-QD605 (N = 142), c) sAv-QD655 (N = 162), and d) sAv-QD705 (N = 131). The mean diffusion coefficient, <D5>, (± SEM) was for a) sAv-QD565: 0.047±0.002 µm2/s, b) sAv-QD605: 0.052±0.003 µm2/s, c) sAv-QD655: 0.039±0.002 µm2/s, and d) sAv-QD705: 0.049±0.003 µm2/s.(TIF)Click here for additional data file.Table S1Product specifications of investigated QDs. The reported molar extinction coefficients are those given by the manufacturer.(DOC)Click here for additional data file.Table S2QDon, and fractional intermittency times, FQDon, of single QDs with 500 LP Emission Filter Microscope Configuration.Quantification of mean intensity, I(DOC)Click here for additional data file.Table S3Hydrodynamic Radii of QDs.(DOC)Click here for additional data file.Table S4QDon, and fractional intermittency times, FQDon, of single QDs with QuadView microscope filter configuration.Quantification of fluorescence intensities, I(DOC)Click here for additional data file.Table S5Localization precision of single QD imaging.(DOC)Click here for additional data file.Table S6Summary of MC-SPT results for four color tracking of biotin-cap-DPPE labeled with each type of sAv-QD.(DOC)Click here for additional data file.Table S7p-values for non-parametric two-sided Kolmogorov-Smirnov test of the diffusion coefficient of biotin-cap-DPPE in live MEFs. White shade = Statistical significant difference at confidence level of α ≤ 0.05. Gray shade = No statistical significant difference at confidence level of α ≤ 0.05.(DOC)Click here for additional data file.Movie S1QD fluorescence intensity. Representative video comparison of the fluorescence intensities of QD525, QD565, QD585, QD605, QD625, QD655, QD705, and QD800. Time lapse images in each instance were acquired with 5 ms camera integration at an image acquisition rate of ≈25 Hz using a Hg arc lamp, a 470/40 nm bandpass excitation filter, a 500LP emission filter, a 150X, 1.45 NA objective, and an Andor EMCCD BV887. All images are displayed at identical brightness and contrast ratios and are hence directly comparable. Scale bar equals 10 µm.(AVI)Click here for additional data file.


Here, we report the case of a 55-year-old man with reactivation of old cutaneous scars associated with a febrile illness, episcleritis, polyarthralgias, erythema nodosum and hilar adenopathy. High-resolution computed tomography (HRCT) revealed right paratracheal, bilateral hilar, and subcarinal lymphadenopathy without any nodular densities in both lung fields. A scar biopsy revealed multiple noncaseating granulomas and confirmed the diagnosis of sarcoidosis. A short course of oral steroids led to regression of systemic symptoms, and the scars returned to baseline size. This patient represented a rare case of simultaneous Löfgren's syndrome and scar sarcoidosis. The diagnosis usually requires a compatible clinical picture, histologic demonstration of noncaseating granulomas, and exclusion of other diseases capable of producing similar histology or clinical features . Systemi patient . The difA 55-year-old man presented to our hospital with 6-week history of low-grade intermittent fever, malaise, fatigue, joint pains involving both knees and ankles along with painful nodules on left lower limb, and redness of both eyes of 1-week duration. He had loss of appetite and a weight loss of 3 kg over this period. He complained of increasing size of old scars present on his forehead . These sPhysical examination revealed the following: pulse rate—84/minute, blood pressure—120/80 mm Hg, and respiratory rate—18/minute. The lesions on the forehead were subcutaneous, firm, nontender, and minimally mobile, and he also tender subcutaneous nodules on left shin suggestive of erythema nodosum. Eye examination revealed bilateral episcleritis. He had tenderness in both knees and ankles without any swelling. There were no lymph nodes or hepatosplenomegaly. Chest and cardiac examination was unremarkable.9/L, serum creatinine 1.2 mg/dL, bilirubin 0.3 mg/dL, ALT 51 IU, AST 36 IU, and alkaline phosphatase 161 units. Erythrocyte sedimentation rate was 70 mm/h, and serum calcium was 10.8 mg/dL . A chest radiograph showed doubtful hilar lymph node. High-resolution computed tomography (HRCT) , lymphoma, and tuberculosis was considered. The scar on the forehead was biopsied which revealed a noncaseating epitheloid granuloma which was negative for acid-fast bacilli staining, and thus a diagnosis of sarcoidosis was confirmed .The patient responded to a short course of 10 mg prednisolone daily. His systemic features disappeared, and the enlarged scar resolved to its original size.  occurs in 9% to  34%    of  patients [  and women.  Erythema  nodosum  is  observed  predominantly  in  women, whereas  marked  ankle  periarticular  inflammation  or  arthritis  without  erythema  nodosum  is  more  common in  men [Löfgren's syndrome, an acute form of sarcoidosis characterized by erythema nodosum, bilateral hilar adenopathy, and polyarthralgia or polyarthritis,Sarcoidosis affects the skin in 20%–30% of cases. Cutaneous sarcoidosis can manifest with specific and nonspecific lesions. The specific lesions are lupus pernio and plaques associated with more severe systemic involvement and more chronic course, while nonspecific lesions include erythema nodosum, the hallmark of acute and benign disease.Scar sarcoidosis is a rare and highly specific manifestation of cutaneous sarcoidosis, with only a few case reports described. Scar sarcoid has not been reported in context of Löfgren syndrome.Scar sarcoidosis presents with redness and recurrence of activity at the site of scars due to previous wounds, intramuscular injections, tattoos, herpes zoster, ritual scarification, or allergen extracts for desensitization. Itching is conspicuously absent which helps to distinguish it from clinical mimickers like hypertrophic scar and keloid. Scar sarcoidosis may herald a relapse or be a first presentation of acute sarcoidosis as in our case.The severity of the systemic disease determines the need and modality of treatment. For patients with severe systemic involvement or disfiguring skin lesions, the mainstay of treatment is systemic corticosteroid therapy. Hydroxychloroquine and methotrexate are used as steroid sparing agents.Recognition of cutaneous lesions is important because they provide a visible clue to diagnosis and serve to avoid more invasive attempts at obtaining tissue for histologic examination as in our case.


As expected, the vast majority of gene deletions showed no strong effects on entry into/exit from senescence. However, around 200 gene deletions behaving similarly to a rad52Δest1Δ archetype (rad52Δ affects homologous recombination) accelerated entry into senescence, and such cells often could not recover growth. A smaller number of strains similar to a rif1Δest1Δ archetype (rif1Δ affects proteins that bind telomeres) accelerated entry into senescence but also accelerated recovery from senescence. Our genome-wide analysis identifies genes that affect entry into and/or exit from telomere-initiated senescence and will be of interest to those studying telomere biology, replicative senescence, cancer, and ageing. Our dataset is complementary to other high-throughput studies relevant to telomere biology, genetic stability, and DNA damage responses.In telomerase-deficient yeast cells, like equivalent mammalian cells, telomeres shorten over many generations until a period of senescence/crisis is reached. After this, a small fraction of cells can escape senescence, principally using recombination-dependent mechanisms. To investigate the pathways that affect entry into and recovery from telomere-driven senescence, we combined a gene deletion disrupting telomerase ( In most eukaryotes, including mammals and yeasts, telomerase helps maintain telomeric DNA and solve the chromosome end-replication problem .In most human somatic cells, there is insufficient telomerase to maintain telomere length indefinitely through cell divisions, and consequently, telomeres shorten and ultimately become nonfunctional. Telomere shortening is thought to be a double-edged sword in metazoan cells . On one Telomere structure and function need to be maintained in cells with unlimited proliferative potential. In the majority of cancers, structure and function are preserved via the expression of high levels of telomerase, permitting unlimited and uncontrolled cell division. However, in around 15% of cancers, telomeres are maintained by alternative lengthening of telomeres (ALT) mechanisms  was combined with the genome-wide knockout collection using SGA as previously described  using an 0.8 mm diameter pin tool.est1::natMX yfg::G418 double mutants were cherry-picked after SGA. Inoculation from solid to liquid media was performed on the Biomatrix BM3-SC robot using a 96-pin (1 mm diameter) pintool. 96-well liquid culture plates were incubated at 30°C for 22 hr without shaking. A Biomek FX robot  was used to vortex the cultures to resuspend and then inoculated into new sets of 96-well plates containing 200 µl media in each well. A 96-pin (2 mm diameter) pin tool  was used, transferring approximately 3 µl of cell culture at each passage. In a similar procedure, resuspended cell cultures were diluted in 200 µl sterile H2O and vortexed before the diluted cultures were spotted onto solid agar plates. Agar plates were incubated for 48 hr at 30°C before being photographed.Selected Solid agar plates were photographed on an spImager (S&P Robotics Inc.) and analyzed using Colonyzer .r) between strain MDPs and the MDP of each archetype, using the cor function in the R statistical package  difference between profiles. The area under each MDP  was also estimated as the sum of mean culture size across all 22 passages. Lists ranking the MDP for each strain according to its correlation coefficient were generated, with the strains having MDP shape most similar to the archetype (and the archetype itself) at the top of the list . Note that the absolute fitness of a comparator strain does not have to be similar to that of the archetype for their MDPs to correlate well. Two strains, one sick and one healthy, can have similarly shaped MDPs that correlate well. It is for this reason that some of the heat maps in The similarity of the MDP shape of each strain to that of three example archetypes was estimated using Pearson's correlation coefficient . For classes similar to each of the three archetypes, the average recovered fraction of class members was calculated.XhoI, then run overnight on a 1% agarose gel at 1 V/cm. Southern transfer and detection was performed using DIG-High Prime Labeling and Detection Kit (Roche) and visualized on a FUJI LAS4000. Telomeric Y′-TG probes  method to combine a systematic genome-wide collection of gene deletions with an lomerase . In a lilomerase . The liqyfg∆ est1∆ genotypes along with 36 independently generated his3∆ est1∆ “wild type control” strains were inoculated. Cultures in 16 such replicate plates, each with independently generated double mutants, were grown in parallel . In combination with est1∆, we tested the effects of deleting 27 genes previously reported as affecting telomere length (Table S1). The his3∆ est1∆ strains are suitable “controls” because, although HIS3 is disrupted with the KANMX marker, the cells express spHIS5 from the MATa-specific promoter and are therefore histidine prototrophs and expected to show no growth defects , the dilution ranges from 1:600 for healthy cultures to 1:7 when cells are deeply senescent.To follow growth in liquid, we used the procedure outlined in his3∆ est1∆ strains, situated in the outer two rows/columns of each 384-spot plate, entered into and recovered from senescence over 16 passages  from our supplementary data website (http://research.ncl.ac.uk/colonyzer/ChangSenescence/#images).It is clear that the majority of passages . The maje.g., rad52∆ est1∆ and upf2∆ est1∆) grew poorly in comparison with his3∆ est1∆ strains  for all genotypes. MDPs are curves showing the senescence characteristics of each genotype and are constructed after estimating yeast culture cell densities for repeat cultures of different genotypes at each passage from photographs using the image analysis tool Colonyzer  or organisms (bacteria) was observed. By passage 16, at the end of the experiment, the mean fitness of his3∆ est1∆ strains was nearly as high as that at passage 1, which was as expected because of the emergence of recombination-dependent survivors; however, a large variance in cell densities was observed . These included those that entered senescence rapidly, including mre11∆, xrs2∆, rad52∆, rad54∆, rad55∆, rad57∆, rtt101∆, rtt107∆, rtt109∆, pol32∆, upf1∆, upf2∆, upf3∆, dcc1∆, ctf8∆, ctf18∆, slx5∆, slx8∆, sgs1∆, rad27∆, mms1∆, mms22∆, cdc73∆, rtf1∆, rfm1∆, sum1∆, kem1∆, rrp8∆, asf1∆, tel1∆, elg1∆, hmo1∆, ede1∆, ydl118w∆, rho4∆, spt21∆, tsa1∆, lea1∆, and sla1∆; a large number that behaved normally, including exo1∆, chk1∆, rad9∆; and a small group of just three genes, est3∆, rif1∆, and rif2∆, consisting of mutants that appeared to enter senescence early and recover early. Table S1 summarizes the behavior of individual genes and whether the results we obtained were consistent with previously published studies. It is clear that our results largely reproduced results previously reported from detailed, high-quality, low-throughput experiments giving us confidence in our data. However, there were some interesting surprises, such as the behavior of upf1∆, upf2∆, and upf3∆ mutants that failed to recover from senescence here  but had previously been reported to delay senescence , are in our supplementary data website (http://research.ncl.ac.uk/colonyzer/ChangSenescence/#images).By pinning parallel colonies rather than growing liquid cultures, we increased throughput 36-fold. In pinning experiments, we grew a minimum of 8, sometimes 56 , and in the case of nescence . In someFigure S4). In addition many of the DNA repair mutants known to be defective in recovery from senescence did not recover from senescence in these highly parallel experiments . It is interesting to compare the solid pinning data (File S2) with that for the 60 strains also analyzed in liquid culture, 6 of which are shown in File S2. In contrast to the pattern observed in liquid cultures, in pinning experiments evidence of a period of poor growth followed by recovery for many strains was less striking .We generated MDPs of all 4299 genotypes over 22 passages, and plots of these profiles together with culture size standard deviations are available  was clearly less than the fitness of est1∆chk1∆ and est1∆his3∆ strains (2000 units). This most likely is due the low fitness induced by deletion of RAD52 itself. With time, the fitness of rad52∆est1∆ declined until, by passage 10, cultures were very small and did not really recover. The rate of entry of rad52∆est1∆ cultures into senescence was much slower than that observed in liquid cultures, consistent with cultures being diluted less on solid agar compared with liquid cultures and, therefore, having less potential to divide.upf2∆est1∆ strains on solid pins seemed to be more similar to his3∆est1∆ strains than to rad52∆est1∆ strains. Conversely, in liquid cultures, upf2∆est1∆ strains are more similar to rad52∆est1∆ strains . Disrupting the nonsense-mediated RNA decay pathway affects many different transcripts and, hence, cellular processes, including those relevant to telomere biology . We classified strains according to the similarity of their MDP to that of three archetypal gene disruptions: his3∆est1∆, a neutral control strain (File S5); rad52∆est1∆, affecting a typical gene required for recovery from senescence ; and rif1∆est1∆, showing accelerated entry into and exit from senescence (File S8). Similarity between MDPs was quantified using Pearson’s correlation coefficient (r).To help classify the behavior of the thousands of different genotypes, we generated MDPs for each of the ∼4300 gene deletion strains (his3∆est1∆ strains (r > 0.85). There was a general trend of lower density across all passages for these strains . In fact, the five strains whose MDP is least well correlated with those of his3∆est1∆  are the strongest examples of the rif1∆est1∆ archetype, which we define below.As we expected, the vast majority (more than 3000) of the double mutants can be classified in the category of “normal senescence” , defined strains ; at later > 0.85) leaves only three members of the rif1∆est1∆ class; however, we can see in EST3, RIF1, RIF2, and TEL1 are genes that are well known to affect telomere maintenance and rif1∆ and rif2∆ mutants accelerated entry into and recovery from senescence in rif1∆est2∆ and rif2∆est2∆ mutants. The effects of est3∆ on est1∆ mutants that we have observed are not consistent with previous reports . The tel1∆est1∆ results from previous studies are somewhat conflicting (Table S1). Some previous data agree with our results whereas other data do not; it is not clear whether the differences are due to strain background or some other factor, such as experimental design. Other genes in this class, notably ELG1 encoding a replication factor C (RFC)-type protein and with known telomere-related phenotypes (Using a strict correlation cut off (File S7) having an MDP that correlated well with that of rad52∆est1∆  yeast process” analysis. Interestingly, we found significant enrichment for genes involved in response to stress, chromosome organization, DNA metabolic processes, cellular membrane organization, vesicle-mediated transport, transcription DNA dependence, cell cycle, and protein modification . These results strongly suggest that replication fork progression plays an important role in replicative senescence. However, our data also suggest that there are many additional pathways/complexes affecting replicative senescence . Inevitably, the high-throughput pinning approach suffers from a lack of resolution compared with the liquid-based approach. Nevertheless, it contains a great deal of valuable quantitative information. We have constructed a high-quality dataset demonstrating senescence profiles for all 4299 gene deletions in the knockout library combined with a telomerase defect that will complement other low- and high-throughput analyses of telomere biology and the DNA damage response.We report the first genome-wide analysis of the effects of gene deletions on entry into and exit from telomere-initiated senescence in his3∆est1∆ , rad52∆est1∆ (accelerated entry into senescence and failure to recover), and rif1∆est1∆ (accelerated entry into senescence and recovery). However, other clustering or analysis approaches may also prove informative. For example, we also performed unsupervised hierarchical quality threshold (QT) clustering to identify 23 different MDP classes . The MDPs which we constructed , together with the images and raw quantifications from which they are derived, are published to allow others to analyze our dataset using different approaches, for example, by searching for strains whose deletions result in MDPs correlating strongly with those of archetypes of specific interest, which could be different to the three presented here.We chose to classify double deletion mutations based on the similarity of their MDPs to those of archetypal mutations: rad52∆ est1∆ archetype strain and mutants in this class show poor growth when generated by SGA immediately after germination. Therefore we tested whether additional information is gained from continuing to passage such poor-growing strains. To address this issue, we chose to compare our rad52∆-like cluster with genes we identified as growing poorly with est1∆ at passage 0 in our experiments, and with analogous datasets from large-scale, genome-wide synthetic lethal analysis experiments .The Figure S7C–F on plots similar to rad52∆est1∆ class  dataset. Therefore we conclude that, at the very least, our high-throughput senescence assays complement the existing datasets, identifying gene deletions with notably different properties.To compare the relative merits of each dataset, the member strains of each are highlighted in 1∆ class  and S7C RAD52 or RIF1 show very interesting effects on the senescence process in budding yeast. Although some genes in the RAD52 class, such as SLX5, SLX8, and MMS1, were previously reported to affect the processes of recovery from senescence, we have identified 200 or more genes in this class. Our data also shed new light on the functions of proteins with known roles in telomere biology, such as Elg1 or members of the Ctf18 complex.Our dataset is a rich resource for those working in telomere biology in budding yeast and other eukaryotic organisms. All our data are freely available, and there are numerous provocative and interesting observations worthy of further investigation. For example, the genes behaving like EST3 gene affects the senescence profile of est1∆ mutants in a manner analogous to rif1∆ mutants. It may also be interesting to extend this approach to S. pombe, where telomere biology is significantly different from S. cerevisiae and genome-wide knockout libraries and SGA approaches are now available (We imagine that iterations of our genome-wide approach to understand senescence, perhaps utilizing genome-wide liquid passage approaches, like


FH) gene is known to be associated with HLRCC.Hereditary leiomyomatosis and renal cell cancer (HLRCC) is a rare tumor predisposition syndrome characterized by cutaneous and uterine leiomyomas and papillary type 2 renal cell cancer. Germline mutation of the fumarate hydratase  in exon 7, was detected in the 2 cases. Functional prediction with the bioinformatics programs, SIFT and Polyphen-2, reported “damaging (SIFT score 0.00)” and “probably damaging (PSIC score 1.621)” values, respectively. In 162 healthy individuals, there were no cases of a G transition to any base. Finally, (c.1021G > A) in exon 7, was identified as a point mutation.We describe a 64-year-old father and his 39-year-old son with HLRCC who developed papillary type 2 RCCs lacking cutaneous leiomyomas at any site. A common missense mutation in the We report a family with HLRCC in which a novel missense mutation was detected. A familial papillary type 2 renal cancer should be considered HLRCC unless typical cutaneous leiomyomas do not occur. FH) gene, which is located at 1q42.3-43 [FH gene codes for fumarate hydratase, which is an enzyme that catalyzes the conversion of fumarate to malate in the Krebs cycle. Mutations of the FH gene, including missense, frameshift, and complete or partial deletions, have been detected in 90% of HLRCC families, suggesting that the FH gene has the characteristics of a tumor suppressor gene. HLRCC is comparatively rare, and so far, 180 HLRCC families have been identified worldwide [FH mutation database provides a total of 155 variants, as of the last up-date on August 17, 2011 [FH gene was detected.Hereditary leiomyomatosis and renal cell cancer (HLRCC: OMIM 605839) is an inherited autosomal dominant cancer syndrome characterized by cutaneous leiomyoma, uterine leiomyoma, and/or a single renal tumor . CutaneoA 64-year-old man had anorexia and body weight loss of 10 kg for 3 months before referral. Contrast enhanced computed tomography (CECT) revealed a huge mass arising on his left kidney  and FH gene, and the study was approved by the Medical Ethic Committee of Nara Prefectural Nara Hospital. DNA was extracted from their peripheral blood leukocytes (PBLs), and was directly sequenced to include all coding exons of VHL and FH as described previously [VHL. However, the analysis revealed a single missense mutation  in exon 7 of FH, which was common to both cases , which is defined as a minor allelic frequency of more than 1%. Both the HLRCC cases showed (c.1021G > A). There was no case of a G transition to any base among 162 healthy individuals  analysiTolerant ) provides Figure . FinallyVHL inactivation is very common in both sporadic clear cell RCC and the hereditary cancer syndrome known as von Hippel-Lindau disease [MET gene mutation occurs in both hereditary and sporadic papillary type 1 RCCs, whereas the FH gene mutation is detected only in hereditary papillary type 2 RCC as a germline mutation [Hereditary renal cell cancer comprises an estimated 3-5% of RCCs, and to date, 10 HRC syndromes have been described . Clear c disease . Papillamutation .FH gene encodes fumarate hydratase, which is an enzyme of the Krebs cycle that catalyzes the conversion of fumarate to malate. Thus, FH deficiencies are thought to result in chronic accumulation of fumarate, and lead to competitive inhibition of hypoxia induced factor (HIF) prolyl hydroxylase (HPH). Under normoxic conditions, hydroxylated HIF is recognized by the VHL complex and targeted for ubiqutin-mediated degradation. When HPH is inhibited, HIF remains unhydroxylated and avoids degradation. Then, accumulated HIF consequently upregulates HIF target genes such as VEGF, GLUT1, PDGF, and TGFα, which facilitate tumor growth [FH mutation or FH enzyme activity [The r growth . Thus, tactivity . Indeed,FH mutation is missense (57%), followed by frameshift and nonsense (27%), and diverse deletions, splice site and duplications [FH mutations. A very small number of these mutations have known changes in FH enzymatic activity, although most of them have SIFT scores of “0.00”.The most common type of ications . A totalications . From thHLRCC-associated renal cancers are early onset and very aggressive, and most reported patients died within 5 years of diagnosis . RadicalSmit et al.  advocateFH gene was confirmed by genotyping and in silico analysis. Papillary type 2 RCCs, which have a familial occurrence, should be used for HLRCC identification, if no cutaneous leiomyomas develop. When a germline mutation is identified, all family members should be offered appropriate counseling and genetic testing.To our best knowledge, a novel missense mutation of the Peripheral blood leukocytes (PBLs) from 162 healthy cohorts were used for consecutive genetic analysis. These samples were collected by following protocols that were approved by the Medical Ethics Committee of Nara Medical University. Written informed consent was obtained from all participants. DNA was extracted according to standard procedures.The impact of the (p.D341N) missense mutation on protein function was assessed with SIFT and PolyPhen-2. Both SIFT and PolyPhen-2 are online prediction tools that predict the degree of impact of an amino acid substitution on the structure and function of a human protein. SIFT provides a SIFT Score in which a value of less than 0.05 indicates that the amino acid substitution is predicted to be “Damaging”. PolyPhen-2 provides a position-specific, independent count (PSIC) score difference, which was assigned using the categories “probably damaging” (2.00 or more), “possibly damaging” (1.40-1.90), “potentially damaging” (1.20-1.50), “borderline” (1.00-1.20) and “benign” (0.00-0.90).FH by pyrosequencing (PSQ) using PyroMark Q96 (Qiagen), according to the manufacture’s protocol. To enable single-strand preparation, the reverse primer was 5′-biotinylated. Reaction volumes of 30 μl contained 5× GoTaq buffer, 1.5 units of GoTaq Hot Start Polymerase (Promega), 1 μM of primers, and 500 nM of dNTPs. PCR conditions were as follows: 95°C for 3 min; 45 cycles of 95°C for 30 s, 58°C for 30 s, and 72°C for 30 s; and a final extension step at 72°C for 4 min. PCR primer sequences were: 5′-TTCTGTTTCACTTGCTAATGGTAGA-3′ (forward), and 5′-GGACCTAGTCAAGTTTTAGCTCCA-3′ (reverse), respectively. The sequencing primer sequence was 5′-AGTCTGATGAAGATAGCAA-3′. We designed this assay so that if c.1021G > A was an unreported SNP, it could detect all nucleotide variations. Sequences to analyze were ATG/NATATTC.One hundred and sixty-two healthy control samples were Genotyped at nt 1021 on Written informed consent was obtained from these patients’ next of kin for publication of this case report and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.The authors declare that they have no competing interests.MK participated in the genetic analysis and drafted the manuscript. YC conceived the study idea, and participated in its design and coordination and in writing of the manuscript. YL participated in genetic analysis. KT and YK managed the patients. KT and TS participated in VHL mutation analysis. KF collected blood samples from healthy subjects at Nara Medical University, Kashihara, Japan and gained ethics committee approval to enroll this study. HK managed histopathological findings of the patients. SS managed the patients, gained ethics committee approval for genetic analysis of this study at Nara Prefectural Nara hospital, Nara, Japan, and participated in writing of the manuscript. All authors read and approved the final manuscript.


A number of studies have concluded that cognitive control is not fully established until late adolescence. The precise differences in brain function between adults and adolescents with respect to cognitive control, however, remain unclear. To address this issue, we conducted a study in which 185 adolescents (mean age (SD) 14.6 (0.3) years) and 28 adults (mean age (SD) 25.2 (6.3) years) performed a single task that included both a stimulus-response (S-R) interference component and a task-switching component. Behavioural responses  and brain activity during correct, error and post-error trials, detected by functional magnetic resonance imaging (fMRI), were measured. Behaviourally, RT and ER were significantly higher in incongruent than in congruent trials and in switch than in repeat trials. The two groups did not differ in RT during correct trials, but adolescents had a significantly higher ER than adults. In line with similar RTs, brain responses during correct trials did not differ between groups, indicating that adolescents and adults engage the same cognitive control network to successfully overcome S-R interference or task switches. Interestingly, adolescents with stronger brain activation in the bilateral insulae during error trials and in fronto-parietal regions of the cognitive control network during post-error trials did have lower ERs. This indicates that those mid-adolescents who commit fewer errors are better at monitoring their performance, and after detecting errors are more capable of flexibly allocating further cognitive control resources. Although we did not detect a convincing neural correlate of the observed behavioural differences between adolescents and adults, the revealed interindividual differences in adolescents might at least in part be due to brain development. Cognitive control denotes several functions within the cognitive system that are necessary for performing non-routine tasks or coping with challenging situations, e.g. for shifting flexibly between competing tasks. Flexibility is needed in adaptive self-regulation and goal-directed behaviour The conflict-monitoring hypothesis Parts of this network, especially the frontal regions, mature structurally throughout adolescence Like brain response in the cognitive control network error processing has been associated with activity in the ACC, anterior insula, parietal lobe, medial temporal lobe, basal ganglia and in the thalamus An additional limitation of studies that have addressed cognitive control as well as error monitoring is that broad age ranges for adolescent subgroups were used, although it is well known that the brain structure develops considerably throughout adolescence From recent studies As higher cognitive functions develop throughout adolescence We collected data from a large adolescent sample  and from 29 adults (mean age 25 years). We compared the two groups’ behaviour (RT and ER) and brain response (fMRI blood oxygen level-dependent (BOLD) response) during correct trials, during error trials and during correct trials after an error occurred or no response was given.Data were collected within the project “The adolescent brain”, which is funded by the German Federal Ministry of Education and Research (BMBF). A total of 260 adolescents took part in the study, of which 237  performed the interference and switch task. 29 adults (mean age 25.2 years) also performed the task.All potential participants were screened for several exclusion criteria: presence of neurological disorders, current drug treatment, surgeries on heart or head and conditions posing safety issues for the MRI scan. Subjects participated in the study after giving written informed consent and for those who were under eighteen years old, at least one parent had to additionally agree to their participation by signing the consent form. The study was approved by the local research ethics committee (Ethics Committee of the Technische Universität Dresden) and conducted in accordance with the Declaration of Helsinki. All subjects were also screened for mental disorders using DAWBA – Developmental and Well-Being assessment The imbalance in sample size between the adolescent and adult groups is due to the fact that there were limited resources for data collection from adults for a cross-sectional analysis. The main source of funding for this investigation came from the project “The adolescent brain”, which focuses on the assessment of longitudinal development during adolescence. The herein reported adolescent sample will be measured again at the ages of 16 and 18 using the same investigational tools.We used event-related fMRI and employed a task that included both an S-R interference component and a task switching component. Our task is not a classical interference task (like Stroop) as no dominant response is primed: Both components were equally frequent. But, there is a relevant and an irrelevant task dimension leading to interference by overlapping S-R-mappings. In each trial, subjects were shown an arrow consisting of two touching triangles pointing in one of four  directions and a red dot located either at the tip or the tail of the arrow see . SubjectOur task allowed us to set up a design with 2 within-subject factors of interest. The first factor represented the task transition (repetition vs. switch), and the second the congruence of the present trial (congruent vs. incongruent). Further, there were two within-subject factors of no interest, namely task (arrow vs. dot) to create the switch effect, and previous trial congruence (congruent vs. incongruent). Hence, there were four different conditions, i.e. repeat-congruent (rp_C), repeat-incongruent (rp_I), switch-congruent (sw_C), and switch-incongruent (sw_I). These were balanced with 64 trials each, meaning that 50% of all the trials were congruent and 50% incongruent, while 50% were repeat trials and 50% switch trials. Trials were presented in a randomised order. In order to avoid priming effects, there were no consecutive identical trials Outside the scanner, 35 trials of the interference and switch task were practised in a sitting position in front of a computer monitor. In addition, subjects performed another 35 practice trials in the scanner prior to scanning, to familiarize themselves with using the joystick while lying in the scanner.Subjects were free to ask questions until imaging started. A total of 273 trials were performed. We included seven 20-second breaks in order to obtain a baseline measure for event-related fMRI and to give subjects time to relax and then to re-focus on the task. During a break, subjects were instructed to look at two parallel lines in the middle of the screen.The first two trials and the last trial of the entire run were not included in the analysis. Moreover, the first two trials following a break were also discarded. Hence, there were 256 experimental trials.Behavioural data analysis included mean RT and ER. Trials in which subjects made an error or did not react within the given time window of 2.1 seconds after stimulus onset  were discarded from the RT analyses. Missing trials were very uncommon (mean omission rate for adolescents: 1.27% (SD 3.10%), and for adults: 0.25% (SD 0.85%)). Moreover, correct trials following error and missing trials were also discarded to disentangle task effects and post-error/post-missing effects, because subjects often react more slowly  and more accurately after an error Values were calculated with Matlab 7.5 . Further calculations were processed with SPSS 19.0 . Mean RT and ER served as dependent variables in repeated measures 2×2×2 ANOVAs with the factors ‘task transition’ (repeat vs. switch), ‘congruence’ (congruent vs. incongruent), and ‘group’ (adolescents vs. adults). We checked for normal distribution and equal variances.Furthermore, to examine whether there were learning or motivational effects over the course of performing the task, we analysed individuals’ cumulative ERs for the adolescent and for the adult group. We also calculated post-error slowing as RT  − RT . For this last analysis we only included participants who made at least three mistakes. This inclusion criterion was also used by Fitzgerald et al. 2 and an in-plane resolution of 64×64 pixels, resulting in a voxel size of 3×3×3 mm3. Each subject had a single run with 506 TRs, leading to a duration of 20 minutes and 24 s (506 * 2410 ms). To exclude structural abnormalities, a 3D T1-weighted magnetization-prepared rapid gradient echo (MPRAGE) image data set was acquired .Data were acquired with a 3.0 T Siemens TRIO MRI scanner. For functional imaging, a standard echo planar imaging (EPI) sequence was used (repetition time (TR): 2410 ms; echo time (TE): 25 ms; flip angle: 80°). Functional MRI scans were obtained from 42 transversal slices, orientated 30° clockwise to the anterior commissure–posterior commissure line, with a thickness of 2 mm (1 mm gap), a field of view (FOV) of 192×192 mmStimuli were presented via Nordic Neurolab goggles . The task was presented and the behavioural responses were recorded with Presentation® software . Head motion was restricted with foam inserts that were placed to the left and the right of the head.http://www.fil.ion.ucl.ac.uk/spm). During preprocessing, data were corrected for temporal differences in slice timing and inter-scan head motions. The scans were normalized to the standard EPI template  using a voxel size of 3×3×3 mm3 and smoothed with an 8 mm full-width-at-half-maximum Gaussian kernel.We analysed functional MRI data using statistical parametric mapping ×2 (task transition)×2 ×2  design. All error trials , missing trials  as well as correct trials following error and missing trials  were considered as additional regressors. To alleviate the effects of movement, we also integrated the realignment parameters (three translation and three rotation parameters) as regressors of no interest. According to the 2 (task transition)×2  design used for behavioural data analysis, all repeat and congruent trials were summed up and equally weighted irrespective of task and previous trial congruence. This was done for the other conditions analogously. Therefore, the contrasts of interest in the first level analysis were rp_C − baseline, rp_I − baseline, sw_C − baseline, sw_I − baseline, error − correct , and post-error/post-missing − correct. The resulting images were then submitted to second-level analysis.Behavioural data analysis).Second-level group analysis included three different analyses. First, a full factorial whole-brain analysis including the between-subject factor group, and within-subject factors task transition and present trial congruence was calculated in order to analyse differences in task transition and congruence between adolescents and adults during correct trials. However, correct trials following error or missing trials were excluded here. This analysis mirrored the repeated measures ANOVA for the RTs and ERs . To test whether possible group differences with regard to error processing were mainly due to differences in performance (here ER) or not, we conducted a two-sample t-test and included the individual overall ER as a covariate. Specifically, we created one additional regressor for ER in adolescents as well as one for ER in adults, which enabled us to also model the interaction of ER and group. We only included the participants who made at least three mistakes during the whole experiment (181 adolescents and 22 adults). This inclusion criterion proved to be a reasonable trade-off between the minimum number of errors per subject to obtain a more reliable mean value over those error trials and number of participants who met the criterion. In a previous study Third, using the post-error/post-missing − correct contrast we performed a further whole-brain analysis to test whether processing of correct trials following incorrect or missing trials differed between mid-adolescents and adults. This third group statistic was analogous to the second one: We also used a two-sample t-test, included overall individual ER as a covariate with separate regressors for both groups to account for interaction, and only included participants who made at least three errors during the whole experiment.p<0.05, FDR-corrected, at the voxel level and an extend threshold of at least 25 contiguous voxels. When reporting differences at this threshold we explicitly refer to significant differences. If these analyses did not yield significant group differences, we additionally ran a secondary analysis to control for false negative results (type II errors). Here we used a more lenient voxel-level threshold of p<0.01, uncorrected, and reported activations if they exceeded a cluster-level threshold of p<0.05, uncorrected. This resulted in k >88 voxels for the first group statistic concerning differences in task transition and present trial congruence between adolescents and adults, in k >67 voxels for the second group statistic concerning error processing and in k >75 voxels for the third group statistic concerning post-error/post-missing processing.To adjust statistical analyses to the unequal sample size we selected the ‘unequal variance’ option within SPM for all group statistics. In order to control for false positive results (type I errors) in our whole-brain analyses we used a threshold of Behavioural as well as functional MRI data are available upon request.k >79 voxels for the lenient threshold.To maximise performance differences between groups we reanalysed behavioural data comparing adults and 45 adolescents that made at least 20 mistakes during the whole task. The repeated measures ANOVA was calculated in order to analyse the effects of task transition and congruence in adolescents and adults. Mean RTs and ERs for adults and adolescents for the four different conditions are depicted in F = 230.503; p<0.001; ηp2 = 0.522) and incongruent trials  = 279.488; p<0.001; ηp2 = 0.570), compared to repeat and congruent trials, respectively. Additionally, there was a significant interaction of task transition * congruence  = 15.711; p<0.001; ηp2 = 0.069), indicating that the effect of incongruence was enhanced in switch compared to repeat trials. There were no significant differences in RT between adolescents and adults  = 0.976; p = 0.324; ηp2 = 0.005) as well as no significant interaction of group and task transition  = 0.261; p = 0.610; ηp2 = 0.001), of group and congruence  = 0.596; p = 0.441; ηp2 = 0.003), and of all three factors  = 0.047; p = 0.829; ηp2<0.001).Subjects reacted slower in switch  = 26.715; p<0.001; ηp2 = 0.112) with adolescents making significantly more mistakes than adults . The effect of task transition as well as the effect of congruence were enhanced in adolescents compared to adults  = 6.040; p = 0.015; ηp2 = 0.028; Δrp = 2.7%; Δsw = 4.4%; and F = 24.065; p<0.001; ηp2 = 0.102; ΔC = 1.1%; ΔI = 5.9%). Further, there was a significant three-way interaction of group, task transition and congruence  = 8.147; p = 0.005; ηp2 = 0.037), meaning that the interaction between task transition and congruence is enhanced in adolescents compared to adults. Subjects were less accurate in switch trials  = 38.899; p<0.001; ηp2 = 0.156) and in incongruent trials  = 135.944; p<0.001; ηp2 = 0.392). Again, the effect of congruence was larger in switch than in repeat trials  = 33.183; p<0.001; ηp2 = 0.136).In contrast to mean RT, ER showed a significant main effect of group (2>0.99).Since adolescents made more mistakes than adults, we examined the course of the cumulative mean error during the interference and switch task. The error frequency remained constant over the task, indicated by a nearly perfect linear growth pattern of errors for both groups , but no significant differences between adolescents and adults . There was no correlation between ER and post-error slowing .Further, we observed a significant post-error slowing effect  to reduce the type II errors, no differences in this direction could be detected. On the other hand adolescents showed a significantly weaker brain response than adults in the right cerebellum.Concerning the main effect of group brain activity during correct trials did not yield any clusters with stronger brain responses in adolescents than in adults. Even when using a very liberal threshold . No significant interactions between group and congruence or between all three factors were observed even when applying a liberal threshold. However, there was a significant interaction between task switch and incongruence in a cluster within the cerebellum and midbrain, in a frontal cluster including the right ACC (BA 24), in a cluster including the left parahippocampal gyrus, in the thalamus, in the cingulate gyrus, and in a small cluster including the right parahippocampal gyrus (BA 20).Reanalysing the subsample of adolescents (N = 45 adolescents that made at least 20 mistakes and N = 28 adults) yielded changes within the group main effect and within the interaction between group and task transition, and group and congruence respectively see . Error-pMaterials and methods). ER was included as a covariate in both statistics with two regressors to account for interaction effects. Regarding brain response during error trials, the analysis revealed a well-known network consisting of parietal and frontal cortices . When controlled for ER, brain response in adolescents and adults during error processing did not differ significantly, even at a liberal threshold.Note that only data from the 181 adolescents and 22 adults who made at least three mistakes were included in the two group statistics concerning error trials and post-error/post-missing trials  and the left cerebellum.p<0.01, uncorrected, at voxel-level, and p<0.05, uncorrected, at cluster-level, i.e. k >75 voxels) this analysis revealed a weaker brain response in adolescents in the left MFG (BA 10) , our analysis revealed a significantly stronger brain response in a network of frontal and parietal areas see . When co 10) see .We find it interesting that there was a significant negative correlation between brain response during post-error/post-missing trials and overall ER in a network of parietal and prefrontal structures see , but onlAs expected, adolescents in general made more errors than adults in the combined interference and switch task and exhibited stronger increases in ER in trials with higher cognitive demands, i.e. in switch and incongruent trials. Nevertheless, during correct trials RTs did not differ and brain responses were widely comparable for both groups and only less pronounced in the right cerebellum of adolescents compared to adults. When analysing a subsample of 45 adolescents with more than 20 errors (i.e. a 4.7-fold higher ER) brain response in adolescents in the pre-SMA and in the PPC was weaker than in adults.Regarding the neural correlate of a 2.5-fold higher ER in mid-adolescents we found that within this group ER was negatively correlated with brain response in the left and right insulae during error trials and in a network of parietal and prefrontal areas during those trials following errors or missing responses. When controlled for performance differences (ER) during error and post-error/post-missing trials brain responses did not differ between groups. We conclude that adolescents with a stronger brain response in these trials are better at monitoring their performance and after detecting errors are more capable of flexibly allocating additional cognitive control resources, and thus they make fewer errors than their peers.As we expected, RT and ER substantially increased in switch compared to repeat trials. Likewise, RT and ER were higher in incongruent compared to congruent trials, and this increase was particularly pronounced on switch trials. This is in agreement with previous studies In line with these behavioural parameters, in the fMRI data we found substantially stronger BOLD response during switch compared to repeat trials in a well-described brain network including frontal and parietal cortices In summary, the task successfully produced effects of task transition and congruence, as shown by behavioural and imaging data.Although adolescents and adults reacted equally fast, adolescents’ ER was 2.5 times larger than the adults’ ER. This is consistent with prior studies We were surprised to find that neural activation during correct trials only revealed a weaker brain response within the right cerebellum for adolescents. But, when comparing error-prone adolescents to adults the subsample analysis revealed additionally a significant weaker brain response within the pre-SMA, the PPC, the MFG, and in occipital regions in the younger group. Prior studies p<0.01, voxel-level, uncorrected, and p<0.05, cluster-level, uncorrected, i.e. k >88 voxels) we found that neural switch costs were enhanced in adolescents compared to adults in occipital and temporal regions, in the right ACC, and in the right MFG. Within the subsample analysis (N = 45 error-prone adolescents and N = 28 adults) only the differences in the occipital regions remained and additionally the neural incongruence effect was enhanced in error-prone adolescents in the right inferior frontal gyrus. Thus, we speculate that during highly demanding switch or incongruent trials adolescents’ brain activation might increase in parts of the cognitive control network resulting in the same performance for both groups. However, these differences have to be interpreted with caution as they were based on an analysis in which we applied a liberal threshold to reduce the risk of type II errors.When we applied a liberal threshold  in parietal cortices, the insula, and the dorsal ACC. Although only evident at a liberal threshold, the error processing activity is in line with previous studies Unlike some prior developmental studies What is more, we obtained a significant negative correlation in adolescents between brain response in the bilateral anterior insulae during error processing and ER, i.e., the higher the insula activation during error trials, the lower the ER. For adults, there was only a trend, which may be due to their smaller variance of ER and of error-related activity, and to their substantially smaller sample size. At a liberal threshold there was also a correlation in the positive direction for adolescents in the right cuneus, the left supramarginal gyrus, the right paracentral lobule (BA 4) and the left cerebellum. To our knowledge only three studies correlated activity during error trials with ER: Fitzgerald et al. Behaviourally, we found a significant post-error slowing effect However, there were no significant neural or behavioural differences between adolescents and adults, although a prior study It is important to note that only for adolescents was there a significant negative correlation between overall ER and brain response during post-error/post-missing trials in several regions of the cognitive control network, e.g. the bilateral inferior parietal lobe (BA 39), the bilateral MFG , the right superior frontal gyrus (BA 8) and the posterior cingulate cortex (BA 23). For adults there was a trend in the opposite direction, which is further indicated by the interaction between ER and group at the liberal threshold in the left superior frontal gyrus (BA 6). To our knowledge, no study has reported a correlation between post-error brain response and ER. Indeed, King et al. Several limitations of the present study should be mentioned. First, we used a cross-sectional study design. These designs are confounded by inter-individual cohort and variance effects, which can weaken true developmental effects Although both groups reacted equally fast during correct trials of our interference and switch task, adolescents made 2.5 times as many mistakes as adults. In line with their similar performance during correct trials, the majority of adolescents and adults engage their cognitive control network to the same extent.Regarding error processing, two mechanisms seem to be pivotal: First, error monitoring and second, the post-error adjustments during trials directly following errors. We found it interesting that during error trials overall ER correlated negatively with brain response in the anterior insulae, and during post-error/post-missing trials overall ER correlated negatively with brain response in several regions of the cognitive control network, but only for adolescents. We conclude that adolescents that commit fewer errors than their peers might be better at monitoring their performance, indicated by a stronger brain response during error trials, and might also subsequently be more capable of flexibly allocating additional cognitive control resources, as mirrored by the more pronounced activity of their cognitive control network after incorrect or missing responses. One could further speculate that, especially in adolescents making many mistakes, neural (post-)error processing is still less mature.Table S1Increase in brain response for the first group statistic concerning task effects during correct trials (N = 185 adolescents and N = 28 adults). If there were no significant differences at the corrected threshold, we additionally report results from the exploratory analysis . The following abbreviations are used: repeat (rp), switch (sw), congruent trial (C), incongruent trial (I).(DOCX)Click here for additional data file.Table S2Increase in brain response for the group statistic concerning task effects during correct trials . If there were no significant differences at the corrected threshold, we additionally report results from the exploratory analysis . The following abbreviations are used: repeat (rp), switch (sw), congruent trial (C), incongruent trial (I).(DOCX)Click here for additional data file.Table S3Increase in brain response for the second group statistic concerning error trials (N = 181 adolescents and N = 22 adults). If there were no significant differences at the corrected threshold, we additionally report results from the exploratory analysis . The following abbreviations are used: overall error rate (ER).(DOCX)Click here for additional data file.Table S4Increase in brain response for the third group statistic concerning correct trials following errors or missing trials (N = 181 adolescents and N = 22 adults). If there were no significant differences at the corrected threshold, we additionally report results from the exploratory analysis . The following abbreviations are used: overall error rate (ER), supplementary motor area (SMA).(DOCX)Click here for additional data file.


Cognitive behavioral group therapy (CBGT) is an effective, well-established,but not widely available treatment for social anxiety disorder (SAD).Internet-based cognitive behavior therapy (ICBT) has the potential toincrease availability and facilitate dissemination of therapeutic servicesfor SAD. However, ICBT for SAD has not been directly compared with in-persontreatments such as CBGT and few studies investigating ICBT have beenconducted in clinical settings. Our aim was to investigate if ICBT is atleast as effective as CBGT for SAD when treatments are delivered in apsychiatric setting.We conducted a randomized controlled non-inferiority trial with allocation toICBT (n = 64) or CBGT (n = 62)with blinded assessment immediately following treatment and six monthspost-treatment. Participants were 126 individuals with SAD who received CBGTor ICBT for a duration of 15 weeks. The Liebowitz Social Anxiety Scale(LSAS) was the main outcome measure. The following non-inferiority marginwas set: following treatment, the lower bound of the 95 % confidenceinterval (CI) of the mean difference between groups should be less than 10LSAS-points.d between group = 0.41)and −2.51–15.69 (Cohen’s d betweengroup = 0.36) favoring ICBT, which was well within thenon-inferiority margin. Mixed effects models analyses showed no significantinteraction effect for LSAS, indicating similar improvement acrosstreatments .Both groups made large improvements. At follow-up, 41 (64%)participants in the ICBT group were classified as responders . In the CBGT group, 28 participants(45%) responded to the treatment . At post-treatment and follow-up respectively,the 95 % CI of the LSAS mean difference was 0.68–17.66(Cohen’s ICBT delivered in a psychiatric setting can be as effective as CBGT in thetreatment of SAD and could be used to increase availability to CBT.NCT00564967ClinicalTrials.gov  Social anxiety disorder (SAD), or social phobia, is characterized by a persistent anddebilitating fear of being evaluated by others. SAD typically has an early onsetMore recently, guided Internet-based CBT (ICBT) has shown promising results in RCTsconducted by three independent research groups Although ICBT for SAD has demonstrated effects in line with CBGT, the currentevidence holds a number of limitations. There has been no comparison to conventionalCBT, such as CBGT, and most studies have relied solely on self-report instruments asmeasures of treatment outcome. In addition, most studies have been conducted inuniversity settings, which might have a different impact on treatment experience andoutcome compared to receiving care at a psychiatric clinic. Although one study hasindicated that the characteristics of Internet clinic patients could be similar tothose of outpatient clinics In summary, more empirical evidence is needed before ICBT can be validly employed ina psychiatric context. As CBGT is an effective gold standard treatment appropriatefor use as a benchmark The protocol for this trial and supporting CONSORT checklist are available assupporting information; see www.internetpsykiatri.se). There were no advertisements innewspapers or other media. The study protocol was approved by the RegionalEthical Review Board in Stockholm (Karolinska Institutet) and written informedconsent was obtained from all participants after a detailed description of thestudy had been given.Recruitment for the study took place between 2007 and 2009. Participants wererecruited by referral from primary care physicians and psychiatrists, and byself-referral to the psychiatric clinic at the Karolinska University Hospital inStockholm, Sweden. Information about the treatment and the study was publishedon the official web page of the clinic  fulfill the DSM-IV During the first stage of the recruitment process, potential participants wereasked to complete the Social Phobia Screening Questionnaire (SPSQ) α = .96) andhigh test-retest reliability over one week(r = .97) α = .95) as wellas a high 12-week test-retest reliability (r = .83) The primary outcome measure was the clinician administrated Liebowitz SocialAnxiety Scale (LSAS) The Beck Anxiety Inventory (BAI) Psychiatric diagnoses were established using the SCID-I-Research version (RV)A treatment credibility scale comprising five items was administered todetermine whether participants viewed the two treatments as equally credibleWe used an Internet application to administer the LSAS-SR, SIAS, SPS, BAI,MADRS-S, and the QOLI. Internet and paper-and-pencil administrations of thesemeasures have been shown to possess equivalent psychometric properties http://www.random.org) wasused to ensure randomization. The random sequence was generated afterinclusion of participants to ensure that assignment of intervention wasconcealed from assessing psychiatrists and researchers of the study.Participants were allocated to CBGT or ICBT in a 1∶1 ratio usingsimple randomization with no restrictions or matching. To ensure theintegrity of the blinding procedure, participants were instructed not tomention which treatment they had received during the post-treatment andfollow-up interviews. After completing the interviews, the assessingpsychiatrists guessed allocation status for each participant.Assessments, including diagnostic interviews, were conducted before treatment, immediately after treatment ,and six months after treatment . During treatment, theLSAS-SR and the suicide ideation item of MADRS-S were administered on aweekly basis. Participants assessed treatment credibility after one week oftreatment. The randomization procedure involved two external persons notinvolved in the study; one provided randomization data and the othermonitored that no manipulation of treatment allocation was performed by theresearch group. A true random number service  d = 0.5. Test criterion fornon-inferiority for these measures was that the lower bound of the 95% CIof between group effect sizes should fall within this range. This criterion wasjudged acceptable as it has been proposed that an effect size of 0.5 marks theborder between a mild and moderate effect Statistical analyses were conducted using PASW version 18.0 .The non-inferiority margin of the primary outcome measure LSAS was set atΔ10 points, which was based on clinical judgment and a review of theevidence of CBGT compared to credible control conditions for SAD. Meta-analyticreviews, adopting random-effects models, have estimated the lower bound of the95% confidence interval (CI) of the between group effect size to 0.39 = 0.02–1.38,p = .17–.98).Main outcome continuous variables were analyzed using a linear mixed effectsmodel because of its superior qualities regarding missing data as well as inreducing the risk of committing type I errors Loss of data is presented in d = 0.5 effect sizes. As stated above,Within group effect sizes on the primary outcome measure LSAS were large for bothtreatments. At post-treatment and six month follow-up respectively, the 95% CI of the mean difference between the groups on LSAS score was0.68–17.66 and −2.5–15.69, favoring ICBT. This was well withinthe non-inferiority margin of 10 LSAS points for the lower bound. Analysis ofthe other continuous measures showed that all lower bounds of 95% CIs forbetween group effect sizes fell well within the non-inferiority margin ofF = 179.06;df = 1,219; p<.001). There was nosignificant interaction of group and time for the primary outcome measure LSAS,indicating similar improvement across groups. As illustrated in F = 0.25; df = 2,243; p = .77). At post-treatment, 35 (55%) of the participants  in the ICBT group were classified as respondersaccording to the Jacobson and Truax criteria F = 80.95 −83.39;df = 2, p<.001). Mixed effectsmodel analysis showed no significant interaction of group and time for thesevariables .There was a significant effect of time on both the SIAS and SPS.Analysis using mixed effects model yielded no significant interaction ofgroup and time for these variables.There was a significant effect of time on MADRS-S, BAI, ASI and QOLI(p<.02), but CBGT participants were not. Mann-WhitneyU-test showed no significant difference between ICBT and CGBT atpost-treatment (p = .08.). However, atsix-month follow-up, participants receiving ICBT were significantly moreimproved on the CGI-I (p<.01). F = 0.354;df = 2, 225;p = .59).At post-treatment, 42 participants (66%) in the ICBT group wereclassified as very much improved or much improved according to the CGI-I. In the CBGT group, thecorresponding number of participants was 34 (55%) as assessed usingthe CGI-I . Wilcoxon testsshowed that participants who had received ICBT were further improved atfollow-up according to the CGI-I .Following treatment, 18 (31 %) participants who had received ICBT nolonger met diagnostic criteria for SAD (28 % if considering dropoutsas non-responders). The corresponding number for participants who underwentCBGT was 12 . At follow-up, 25 (46%) participants who had receivedICBT (41% if considering dropouts non-responders) and 21 (40%)receiving CBGT (34% if considering dropouts non-responders) no longermet diagnostic criteria for SAD. At post-treatment and six month follow-upthere was no significant difference in the prevalence of SAD between groups = 0.07,p = .95).Credibility ratings after one week of treatment showed that participants in bothgroups rated their respective treatment as credible. Out of a possible total of50, the average scores were 34.0 (SD = 9.03) and 33.8(SD = 10.6) for ICBT and CGBT, respectively. There was nosignificant difference in treatment credibility between treatment groups,indicating successful blinding.In four instances the blinding was broken. On two occasions participantsaccidentally mentioned their treatment allocation status to the assessor, and inother two occasions it was deemed necessary to break the blinding because of theneed to assess increased depressive symptoms during treatment. As shown in 2 = 0.77, df = 1,p = .38).Prior to randomization participants were asked to state their treatmentpreference. Of 126 participants, 68 (54%) preferred ICBT and 58(46%) CBGT. There was no difference between groups in terms of proportionof participants that received the preferred treatment out of a possible total of 15. Fiftyparticipants in CBGT (81%) attended at least five sessions and 17(27%) attended all sessions. The average number of completed modules inICBT was 9.33 (SD = 4.95) of 15. Fifty-one participants inICBT (80%) completed at least 5 modules and 19 (29.7%) completedall modules. Important to note is that the main components of the treatments hadbeen introduced at week 5.On average, therapists delivering ICBT spent 5.5 minutes(SD = 3.6) weekly per patient. The corresponding amount oftime in CBGT was 50 minutes (2.5 h sessions with two therapists and 6 patients).Taking nonattendance into consideration, this number would have been evenhigher. ICBT therapists sent 17.4 messages to each patient on average, i.e. 1.2weekly per patient.F = 90.52-188.67; df = 2, 188–198;p<.001). Mixed effects models analysis showed no significantinteraction effect of time and treatment group on the LSAS, nor on the SIAS and the SPS.Analysis including only those exposed to treatment (at least five sessions ormodules) yielded results equal to the intention-to-treat analysis on continuousoutcome measures of social anxiety, indicating that between group effects in thelatter were not moderated by completion status. There was a significant effectof time on all three measures  toconventional CBT that could facilitate the dissemination of CBT and improvehealthcare resource allocation. When results are interpreted it is also important tobear in mind that that the non-inferiority margin allowed for up to a moderateeffect between treatments. However, this margin was judged as clinically valid, andagain, if ICBT is to be used as a complement, the usefulness of employing verynarrow non-inferiority margins is limited.There are several limitations that warrant mention and could provide venues forfuture research. First, there was no randomization to an active placebo condition,which raises the issue of misinterpreting regression to the mean as indicative oftwo effective treatments. However, given the chronicity demonstrated by SAD In spite of these limitations, we conclude that ICBT may be at least as effective asCBGT, and that it is feasible to conduct ICBT for SAD in a psychiatric setting. AsICBT requires much less resources than conventional CBT, it could be the mostpromising means to increase the availability of CBT for persons affected by SAD.Protocol S1Trial Protocol.(DOC)Click here for additional data file.Checklist S1CONSORT Checklist.(DOC)Click here for additional data file.