Noninvasive diagnostic methods are urgently required in disease stratification and monitoring in nonalcoholic fatty liver disease (NAFLD). Multiparametric magnetic resonance imaging (MRI) is a promising technique to assess hepatic steatosis, inflammation, and fibrosis, potentially enabling noninvasive identification of individuals with active and advanced stages of NAFLD.To examine the diagnostic performance of multiparametric MRI for the assessment of disease severity along the NAFLD disease spectrum with comparison to histological scores.Prospective, cohort.Thirty‐seven patients with NAFLD.Multiparametric MRI at 3.0 T consisted of magnetic resonance (MR) spectroscopy (MRS) with multi‐echo stimulated‐echo acquisition mode, magnitude‐based and three‐point Dixon using a two‐dimensional multi‐echo gradient echo, MR elastography (MRE) using a generalized multishot gradient‐recalled echo sequence and intravoxel incoherent motion (IVIM) using a multislice diffusion weighted single‐shot echo‐planar sequence.MRS), magnitude‐based MRI (PDFFMRI‐M), and three‐point Dixon (PDFFDixon), as well as FibroScan® controlled attenuation parameter (CAP). Fibrosis and disease activity were compared to IVIM and MRE. FibroScan® liver stiffness measurements were compared to fibrosis levels. Diagnostic performance of all imaging parameters was determined for distinction between simple steatosis and nonalcoholic steatohepatitis (NASH).Histological steatosis grades were compared to proton density fat fraction measured by MRS , PDFFMRI‐M , and PDFFDixon , whereas no correlation was found with CAP. MRE and IVIM diffusion and perfusion significantly correlated with disease activity  and fibrosis . MRE and IVIM diffusion had the highest area‐under‐the‐curve for distinction between simple steatosis and NASH .Histological steatosis grade correlated significantly with PDFFMultiparametric MRI is a promising method for noninvasive, accurate, and sensitive distinction between simple hepatic steatosis and NASH, as well as for the assessment of steatosis and fibrosis severity.22 Along with the global increase in obesity and type 2 diabetes mellitus (T2DM), the prevalence of nonalcoholic fatty liver disease (NAFLD) is rising; in fact, NAFLD is currently the most common cause of liver dysfunction worldwide.The overall global prevalence of NAFLD is estimated to be around 25% in the general population, while 60% of individuals with T2DM have NAFLD. Approximately 25% of individuals with simple steatosis are found to progress to NASH.Currently, liver biopsy remains the diagnostic reference standard for NAFLD, as it is the most reliable test to distinguish simple steatosis from NASH and to assess the degree of inflammation and fibrosis.Therefore, noninvasive methods that accurately assess hepatic fat content and even hepatic inflammation and fibrosis are in development for risk stratification of disease severity in NAFLD. Recently, Eddowes et al demonstrated in a biopsy‐controlled study that controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) determined with vibration‐controlled transient elastography on the FibroScan® device accurately assesses steatosis and fibrosis, respectively, in individuals with NAFLD.Multiparametric MRI is a promising technique to assess hepatic steatosis as well as inflammation and fibrosis, potentially enabling noninvasive identification of individuals with active and advanced stages of NAFLD. Thus the aim of our current proof‐of‐principle study is to assess the use of multiparametric MRI and determine the best‐performing imaging parameters for identifying the full NAFLD disease spectrum in a subgroup of the Amsterdam NAFLD‐NASH cohort.Amsterdam University Medical Centres, location Academic Medical Centre (AMC) and was registered in the Dutch Trial Register (registration number NTR7191). All participants in this study provided written informed consent. The Amsterdam NAFLD‐NASH cohort (ANCHOR) study is an observational prospective study that aims to identify and validate noninvasive diagnostic methods, both imaging and molecular markers, for the assessment of the entire NAFLD disease spectrum. To this end, participants undergo multiparametric MRI of the liver, hepatic FibroScan®, ultrasound guided liver biopsy, and urine, feces and blood sampling both at baseline and during follow‐up after 5 years. The study was begun at the end of 2018 and is still ongoing. It is conducted at the AMC, in compliance with the principles in the declaration of Helsinki and according to Good Clinical Practice guidelines.The study protocol was reviewed and approved by the institutional review board of the Amsterdam UMC outpatient clinics with hepatic steatosis on abdominal ultrasound performed for other clinical reasons were included. The other main inclusion criteria were age above 18 years, levels above the upper limit of normal for either aspartate aminotransferase and/or alanine aminotransferase and a body mass index (BMI) above 25 kg/m2. Exclusion criteria were contraindications for undergoing MRI, excessive alcohol use , known bleeding disorders, the use of anticoagulant therapy and platelet aggregation inhibitors, diagnosis of decompensated liver cirrhosis and/or hepatocellular carcinoma, the use of drugs with a potential role in aggravation of pre‐existing NAFLD, and other known causes of liver steatosis other than NAFLD .The first 37 individuals from the ANCHOR study were included in this proof‐of‐principle analysis. Individuals from M.T.) with 3 years of experience in hepatic MRI, who was blinded to the histopathology results.All individuals underwent multiparametric MRI of the liver using a clinical 3.0 T MRI unit  using a 16‐channel phased‐array anterior coil and a 10‐channel phase‐arrayed posterior coil. All data were acquired in a single approximately 45‐minute session. Participants were required to fast for a minimum of 4 hours before scanning. Images were analyzed by a single observer , magnitude‐based MRI (MRI‐M) proton density fat fraction (PDFF), and three‐point Dixon were performed. MRS data acquisition was performed using a multi‐echo stimulated‐echo acquisition mode, according to our previously described protocol.b‐values. MRE was performed using a gravitational transducer at 50 Hz and a generalized multishot gradient‐recalled echo (Ristretto MRE).Disease activity and fibrosis were quantified using intravoxel incoherent motion (IVIM) imaging and magnetic resonance elastography (MRE). The IVIM sequence consisted of a free‐breathing multislice diffusion weighted single‐shot echo‐planar imaging sequence with 18 unique All imaging sequences were assessed for performance in distinguishing simple steatosis from NASH.MRI acquisition parameters and sequence details for all included sequences are listed in Table http://www.jmrui.eu/).MRS values for each subject were calculated using the T2‐corrected water and combined fat peak amplitudes, after correcting for the amplitudes of fat peaks overlapping the water peak.MRS data analysis was performed using our previously described protocol.MRI‐M of all three ROIs was used to establish an average fat percentage of the liver.Three regions of interest (ROI) in the magnitude images of the right hepatic lobe were selected in three different slices, avoiding large vessels, bile ducts, and liver edges. Mean signal intensity per TE was determined and the PDFF calculated in Matlab R2018a  using a multi‐echo and multifrequency fat signal model to correct for T2* effects.https://github.com/maxdiefenbach/MRI_field_contributions/tree/master/fwtoolbox_v1_code). Both phase and magnitude images were used for the reconstruction. The ROI was overlaid on the reconstructed fat image to determine an average fat PDFFDixon of the entire liver in all five slices.Magnitude images were used to draw ROIs of the liver in all slices, avoiding major blood vessels, bile ducts, and liver edges. Image analysis was performed in Matlab, using a toolbox with multipoint fat‐water separation using a hierarchical field map estimationG')) and loss modulus (G") was determined from an ROI drawn in the middle of three slices, proximal to the transducer, avoiding large vessels and liver edges.Images were analyzed using ROOT softwareb‐value images, avoiding large vessels, bile ducts, and liver edges. Slices or areas with artifacts were excluded from the mask. Diffusion (D), pseudo‐diffusion (D*), and perfusion fraction (F) parameter maps of the masked regions were compiled in MATLAB using a Bayesian‐probability based fit.D, D*, and F.ROIs were drawn in all slices containing liver tissue in the reconstructed combined FibroScan® examinations were performed by a physician  who performed over 50 examinations and was blinded to the participants' histological evaluation. The device used was a FibroScan® 530 Compact  equipped with both the M‐ and XL‐probe. The type of probe used depended on the real‐time assessment of the skin‐to‐liver capsule distance for each participant. The measurement was obtained in fasting condition of at least 2 hours, with the participant in a supine position with their right arm fully abducted. Measurements were performed in the right liver lobe through a midaxillary intercostal space. FibroScan® was performed either at the moment of screening, within a month of the MRI and liver biopsy, or on the day of MRI. By using transducer‐induced vibrations, the FibroScan® captures simultaneous recordings of CAP to quantify hepatic steatosis, and transient elastography to obtain LSM as an indicator of the presence of liver fibrosis.Percutaneous ultrasound‐guided liver biopsies were performed by either an interventional radiologist or a hepatologist according to local standard procedure. All histologic specimens were scored by a liver pathologist , who was blinded to all other data. Biopsy samples were stained using a hematoxylin and eosin stain and a Sirius Red stain. The histological parameters were defined with the use of the steatosis, activity, and fibrosis (SAF) score,t test or the Mann–Whitney U test was used depending on the distribution of the data. Normality was tested according to the Shapiro–Wilk's method. Differences in median or means between the simple steatosis and NASH groups were determined for all imaging parameters, expressed as mean ± standard deviation or median with interquartile range. Spearman's rank test was used for correlation analysis, as all parameters were nonparametric. A P‐value <0.05 was considered statistically significant. Comparison of medians for analysis of multiple groups was performed using the Kruskal–Wallis test, followed by Dunn's post‐hoc test with Holm‐Bonferroni P‐value adjustment when appropriate. Correlations and comparison of medians were assessed for steatosis grade compared to PDFFMRS,MRI‐M,Dixon and FibroScan® CAP; activity grade compared to IVIM and MRE; and fibrosis grade compared to IVIM, MRE, and FibroScan® LSM. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic performance of imaging parameters, reporting the area under the ROC (AUROC) and optimal cut‐off values with sensitivity and specificity. ROC analysis was used to assess the performance of PDFFMRS,MRI‐M,Dixon and FibroScan® CAP for distinguishing between steatosis S1 and S2–3; MRE and IVIM for distinguishing between no/mild fibrosis (F0–F2) and advanced fibrosis (F3–F4). Finally, ROC analysis was reported for determining the performance of all imaging parameters for stratifying individuals in simple steatosis and NASH groups. In case of missing data, the analysis was performed for all available parameters.Statistical analysis was performed using R version 3.6.3.2 (SD ± 3.8). No adverse events were recorded during the MRI or liver biopsy. Liver biopsy was performed within 1 week of the MRI, with the exception of one participant whose biopsy was performed 2 months after the MRI. MRE data were not available for two individuals due to technical issues with the MRE hardware, one IVIM scan was not included in the analysis due to a low signal‐to‐noise ratio, and data were missing for one PDFFDixon. Clinical characteristics of the participants are shown in Table Between September 2018 and October 2020, a total of 37 individuals  with hepatic steatosis on ultrasound were included. Mean age of the participants was 49.0 years (SD ± 13.2) and mean BMI was 33.2 kg/mAll biopsies were included in the final analysis. The mean biopsy length was 18 mm (SD ± 5.5). Twenty participants fell in the S1 grade, 13 S2 and four S3. Disease activity according to the SAF score showed three individuals with no activity (A0), 12 A1, 16 A2, five A3, and one A4. According to the SAF‐score, NASH was present in 22 of the 37 participants. According to the NASH‐CRN criteria for fibrosis, two individuals exhibited no fibrosis (F0), seven F1, 20 F2, seven F3, and one cirrhosis (F4). Of the two individuals with missing MRE data, one had F2 and one F4. IVIM data were missing for an individual with F2.rs = 0.26, P = 0.12) or fibrosis stage . Fibrosis grade did correlate significantly with disease activity score .Steatosis grade did not correlate with either disease activity grade , PDFFMRI‐M , and PDFFDixon . Differences in hepatic fat fraction between grades of steatosis indicated a significant difference in the percentage of hepatic fat and steatosis grade . All three methods showed a significant difference in medians between steatosis grade 1 and grade 2, and grade 1 and grade 3 . In contrast, we found no correlation between histological steatosis grade and CAP measured by FibroScan®   0.74–0.98) with a sensitivity of 70.6% and specificity 100% at a cut‐off value of 21.98%. PDFFMRI‐M showed an AUROC of 0.87 (95% CI 0.75–0.99) with a sensitivity of 70.6% and specificity of 95.0% at a cut‐off of 22.93%. PDFFDixon had an AUROC of 0.86 (95% CI 0.74–0.99), with a sensitivity of 68.8% and specificity 95.0% at a cut‐off of 20.53%.ROC analysis for differentiating S1 from S2–S3 showed similar values for all three MRI methods. PDFFMRS, PDFFMRI‐M, and PDFFDixon strongly correlated among themselves (PDFFMRS vs. PDFFMRI‐M: r(35) = 0.99, P < 0.001; PDFFMRS vs. PDFFDixon: r(34) = 0.98, P < 0.001; PDFFMRI‐M vs. PDFFDixon: r(34) = 0.99, P < 0.001).PDFFG' showed a significantly positive correlation with activity grade , and comparison of stiffness results for individual activity grades showed a significant difference in medians between the groups  . G" did not show a correlation with activity grade (rs = 0.28) or difference in medians between groups .D  and F , we found a significant negative correlation with histological activity grade. D* had no significant correlation with activity grade. Kruskal–Wallis tests did not show a significant difference in medians between activity grades for any IVIM parameter  .For both rs = 0.43, P = 0.0077). However, comparison of medians did not show significant differences between activity grades  .Liver stiffness measured by FibroScan® showed a significant correlation with histological activity grade , IVIM D , IVIM F , and FibroScan® LSM  correlated significantly with ballooning. In contrast, none of the available imaging modalities correlated with histopathological inflammation grade. Comparison of medians revealed a significant difference between ballooning grades for MRE  and FibroScan® LSM . Inflammation grade did not show significant differences in medians for any imaging modality.Assessment of the individual components of the activity score revealed that MRE . Furthermore, we observed a significant difference between liver stiffness and fibrosis stage . Post‐hoc analysis showed a significant difference in liver stiffness between fibrosis stage F0–F3, F1–F3, and F2–F3 . G" did not provide a significant correlation with fibrosis grade  or show significant differences between the various grades .We noted a significant positive association between MRE shear stiffness and the histological fibrosis score (G" showed an AUROC of 0.74 (95% CI 0.48–1), with a sensitivity of 71.4% and specificity of 92.9% at an optimal cut‐off of 0.94 kPa.For distinguishing individuals with no/mild (F0–F2) vs. advanced  fibrosis grade, the AUROC for MRE was 0.92 (95% CI 0.83–1), with a sensitivity of 100% and a specificity of 78.6% at an optimal cut‐off of 2.30 kPa. D  and F . D* did not show a significant correlation . Differences in medians for IVIM parameters between fibrosis stages only indicated a significant difference for F , and not for D  or D* . Post‐hoc analysis only showed a significant difference between the median F values of the F0 and F3 stages .Significant correlations between IVIM parameters and fibrosis grade were found for two of the three parameters: D resulted in an AUROC of 0.79 (95% CI 0.63–0.95), with a sensitivity of 75.0% and specificity of 78.6% at an optimal cut‐off value of 0.00102 mm2/second. D* had an AUROC of 0.70 (95% CI 0.47–0.93), with a sensitivity of 62.5% and specificity of 75.0% at a cut‐off of 0.10 mm2/second. F performed best out of the IVIM parameters for distinguishing between mild and advanced fibrosis with an AUROC of 0.88 (95% CI 0.72–1), sensitivity of 75.0%, and specificity of 100% at an optimal cut‐off at 19.85%.Distinction between no/mild (F0–F2) and advanced (F3–F4) fibrosis for rs = 0.47, P = 0.0034); however, differences in liver stiffness between stages of fibrosis indicated no significant difference between liver stiffness and fibrosis stage  .There was a significant correlation between LSM by FibroScan® and histological fibrosis grade (Distinction between no/mild (F0–F2) and advanced (F3–F4) fibrosis using FibroScan® LSM resulted in an AUROC of 0.77 (95% CI 0.58–0.96), with a sensitivity of 87.5% and specificity of 69.0% at an optimal cut‐off value of 9.9 kPa.G' , IVIM D , and FibroScan® LSM  medians of the NASH group were all significantly different compared to the simple steatosis group . IVIM F, D*, and steatosis imaging parameters did not correlate with the presence of NASH.As reported under “Liver histology results,” NASH was histopathologically identified in 22 of the 37 participants using the SAF score. For MRE oup Fig. . IVIM FG' showed the highest AUROC of 0.79, followed by FibroScan LSM and IVIM D (both 0.73). Of these, specificity was highest for both MRE and Fibroscan LSM at 86.7%, while IVIM D showed the highest sensitivity at 85.7%.To determine the performance of each imaging modality for distinguishing individuals with NASH from those with simple steatosis, ROC analysis was performed. AUROC, sensitivity, and specificity values for each imaging modality are reported in Table The present proof‐of‐principle analysis shows that with the use of multiparametric MRI, NAFLD severity—particularly steatosis and fibrosis, and to a lesser extent disease activity—can be assessed. To evaluate the risk of progression toward advanced NASH and fibrosis and to determine treatment and monitoring plans, distinction between simple steatosis and NASH, and detection and staging of fibrosis are essential, yet challenging, components in the workup of an individual with NAFLD. This study presents the initial results from the Amsterdam NAFLD‐NASH cohort (ANCHOR) study, aimed at improving the noninvasive diagnosis and follow‐up of individuals with various grades and stages of NAFLD. Inclusion in the Amsterdam NAFLD cohort is still ongoing and future studies in this cohort will have to determine whether a combination of these MRI parameters can be used to predict histopathological outcomes. The current population captures the complete spectrum of NAFLD disease severity.MRS, PDFFMRI‐M, and PDFFDixon.The noninvasive assessment of hepatic steatosis has been extensively studied for all of the imaging techniques used in this study: CAP, PDFFInterestingly, FibroScan® CAP measurements did not correlate with histological steatosis grade, in contrast with previous studies.G', IVIM D, and IVIM F significantly correlated with the disease activity score, despite substantial overlap between values of the various levels. We also performed an analysis of the individual components of the activity score, comprised of inflammation and ballooning. MRE G', IVIM F, IVIM D, and FibroScan® LSM showed significant correlations with ballooning, while only IVIM D correlated with inflammation. Previous studies have shown correlations between MRE G' measurements and inflammation and/or ballooning stages,F and both inflammation and ballooning; however, those correlations did not uphold in a multivariable regression analysis.N = 32). The imaging correlations with activity score were thus chiefly driven by the contrast in ballooning grade.MRE Staging individuals with NAFLD by fibrosis severity has clear prognostic consequences: progression into the fibrotic stages of NAFLD is strongly associated with liver‐related and overall mortality,Differences in MRE hardware, MRE scan acquisition techniques, vibrational frequencies, and postprocessing techniques make it difficult to directly compare stiffness values found with MRE between studies.Diagnostic accuracy of LSM by FibroScan® for distinguishing no/mild fibrosis from advanced fibrosis was found to be inferior to MRE, as reported in previous studies.F showed a strong correlation with fibrosis stage and showed good performance for distinguishing between no/mild and advanced fibrosis, yet issues with reproducibility shown in previous studiesA recent review assessing correlations between IVIM and fibrosis grade showed substantial heterogeneity in found results.Differentiating NASH from simple steatosis enables early detection of typically asymptomatic active disease. Currently available serum biomarkers for noninvasively differentiating simple steatosis from NASH such as alanine aminotransferase (ALT)‐levels and cytokeratin‐18 fragments are suboptimal, exhibiting poor reproducibility and low accuracy.G' and IVIM D have the potential to noninvasively differentiate simple steatosis from NASH. Of these methods, sensitivity was highest for IVIM D and specificity highest for MRE G'. Noninvasive methods with a high specificity such as MRE are particularly interesting as they have the potential to reduce the amount of liver biopsies in individuals with an early disease stage.The current proof‐of‐concept study shows that the MRI parameters MRE Development of models using a combination of imaging parameters, with or without ultrasonic parameters and plasma biomarkers to distinguish between simple steatosis, are of increasing interest. In recent work an AUROC of 0.87 was found combining MRE with PDFF for distinguishing between simple steatosis and NASH,We report the initial results from the ANCHOR cohort study with promising diagnostic performance of multiparametric MRI in NAFLD; however, while the current population captures the complete spectrum of NAFLD disease severity, not all groups were evenly represented, and the cohort size is modest. Multiple imaging modalities correlated with histopathology; however, the median values found with MRI often did not significantly differ between the histopathologically determined disease severity grades due to the limited number of subjects in some groups. Furthermore, combination of outcomes in a multivariate regression analysis will only be possible when the ANCHOR cohort has advanced in size in the upcoming years. This would be of additional value as single imaging parameters have often provided promising results, but either show overlapping values between the target groups or lack sensitivity and/or specificity for providing a definite diagnosis. While power analysis for distinction between simple steatosis and NASH shows that a sample size starting from 23 participants for the best performing imaging parameter should be sufficient, theory suggests that introduction of a logistical regression model would require a minimum of 100 participants,Overall, our results indicate that multiparametric MRI is a promising noninvasive method for the accurate assessment of steatosis and fibrosis severity, as well as ballooning, with the potential to distinguish between simple hepatic steatosis and NASH.Appendix S1. Supporting InformationClick here for additional data file.Fig. S1 FibroScan® CAP values versus histological steatosis grade. Median values for grade 1, 2, and 3 were 324, 348, and 336 dB/m resp. There were no significant differences in medians between steatosis grades.Click here for additional data file.Fig. S2 FibroScan® LSM versus histological activity grade. Median stiffness values were: 6.85 kPa for grade 0, 6.93 kPa for grade 1, 10.50 kPa for grade 2, and 11.1 kPa for grade 3. There was no significant difference in medians between activity grades.Click here for additional data file.Fig. S3 FibroScan® LSM versus histological fibrosis grade. Median stiffness values were: 7.05 kPa for grade 0; 7.26 kPa for grade 1; 8.48 kPa for grade 2; 10.40 kPa for grade 3; and 23.00 kPa for grade 4. There were no significant differences in medians between fibrosis grades.Click here for additional data file.


Brassica napus L.) cultivars from 26 field sites across Europe. All seed lots harboured a high abundance and diversity of endophytes, which were dominated by six genera: Ralstonia, Serratia, Enterobacter, Pseudomonas, Pantoea, and Sphingomonas. The cultivar was the main factor explaining the variations in bacterial diversity, abundance and composition. In addition, the latter was significantly influenced by diverse biotic and abiotic factors, for example host germination rates and disease resistance against Plasmodiophora brassicae. A set of bacterial biomarkers was identified to discriminate between characteristics of the seeds, for example Sphingomonas for improved germination and Brevundimonas for disease resistance. Application of a Bayesian community approach suggested vertical transmission of seed endophytes, where the paternal parent plays a major role and might even determine the germination performance of the offspring. This study contributes to the understanding of seed microbiome assembly and underlines the potential of the microbiome to be implemented in crop breeding and biocontrol programmes.Seed microbiota influence germination and plant health and have the potential to improve crop performance, but the factors that determine their structure and functions are still not fully understood. Here, we analysed the impact of plant‐related and external factors on seed endophyte communities of 10 different oilseed rape ( Seed microbiota influence germination and plant health and have the potential to improve crop performance. Analyzing the impact of plant‐related traits and external factors on the seed microbiomes of ten oilseed rape cultivars from 26 fields across Europe, revealed the cultivar as the main driver of bacterial diversity, abundance, and composition. We identified bacterial biomarkers for pathogen resistance and germination rates and observed that the paternal parent plays a role during the vertical transmission of seed endophytes. Taxonomic assignment, however, found a high number of non‐target taxa , which were removed, resulting in 233 025 mean high‐quality reads per sample and a total of 23 543 ASVs. After normalization to 10 000 reads per samples, a mean value of 265 bacterial ASVs per sample remained. Overall, We analysed the impact of plant traits  and external factors  on the seed microbiota's diversity, abundance and composition. Fig. H′ and species richness, was only significant for the host plant‐related factors ‘cultivar’ , where microbiomes of resistant cultivars were significantly less diverse. Pairwise comparison of cultivars revealed significantly higher bacterial richness in seeds of cultivar A compared to B and C1, and higher Shannon diversity in A compared to B, C1, C2, C4, E, M and V (Table P = 0.04) and M (richness: P = 0.04).Differences in bacterial diversity, based on Shannon  V Table . ‘Seed lP = 0.003) and ‘seed lot’ (P = 0.014). However, estimations of abundance strongly varied across samples, reaching from 7.7 × 108 to 7.0 × 1011  of variations in bacterial composition, followed by ‘seed lot’   of the variations within the different cultivars. The factors ‘country of harvest’, ‘germination rate’ and ‘resistance’ explained each < 10% of dissimilarities between samples; however, the effects were significant (P ≤ 0.004).In contrast to diversity and abundance, bacterial community composition was significantly affected by all plant‐related and external factors tested, except for ‘year of harvest’. Based on Bray–Curtis distance, ‘cultivar’ explained 25.3% (01) Fig. . The effEnterobacteriales, which were predominant in cultivars B, C1, C2 and C4, accounted for only 9.2% of the bacterial community in cultivar V. Betaproteobacteriales was present in the second highest mean abundance across all samples, dominating the microbiota of cultivars A, D, M and V, but made up only 1.1% in cultivar C1. Cultivars C3 and E featured the highest abundances of Pseudomonadales and Rhizobiales, respectively. On genus level, Serratia revealed the highest mean abundance across all cultivars, which was mainly due to its prevalence (90% rel. abundance) in C1, whereas no ASV was assigned to Serratia in cultivars D and E. Overall, the microbiota of the 10 cultivars were dominated by six different genera: Ralstonia , Serratia (C1), Enterobacter (C2), Pseudomonas (C3), Panotea (C4) and Sphingomonas (E)  Fig. b.that is the oilseed rape seed core microbiome, as well as ASVs unique for each cultivar, a network was constructed based on the combined table of each cultivars' core microbiome (75% core)  Fig. . In totare) Fig. . More thn = 39) and low  germination rates, and between (ii) seeds of P. brassicae‐resistant (n = 12) and non‐resistant (n = 60) samples. After filtering features with at least 100 counts in all samples and a minimum prevalence of 10% in samples, 145 features remained to be tested. Applying LEfSe on ‘germination rate’ as discriminating parameter revealed 87 features, collated to 24 genera, that showed significant  correlation to either high or low CD levels  high  was applied to estimate the fraction of potentially inherited seed microbiota, by including both, the actual parental seed lots  and those seed lots from cultivars M and V, which were not used to produce hybrid seeds. The models estimated that both cultivars D and E obtained a large percentage of ASVs from their actual paternal line  Fig. . Since aB. napus seed microbiome. The host genotype was determined as the main factor explaining the variations in bacterial composition, diversity, richness and abundance. Besides the cultivar, only the host's resistance against P. brassicae affected bacterial diversity. In contrast, endophyte composition correlated to all factors tested, except the year of seed harvest, which had no impact on the seed microbiota on any measure  correlate to seed endophyte composition, where bacterial biomarkers were identified for both. Moreover, we estimated the contribution of parental breeding lines to seed microbiota of their hybrid offspring and found that the paternal parent might play an important role during the assembly of the seed microbiota, with potential impact on the offspring's germination performance.In this study, we disentangled the impact of plant traits  and external factors  on the structure of the ure Fig. . While set al., et al., et al., Pantoea, Pseudomonas, Rhizobium, Stenotrophomonas, and Burkholderia. Since those taxa are being reported frequently to colonize seeds, we support the idea of a symbiotic relationship and their relevance for plant health in general  were found to be significantly more abundant in asymptomatic compared to symptomatic roots of B. napus plants that were infected by P. brassicae  vigour test protocol according to the ISTA Rules, Chapter 15.8.3. CD germination rates, ranging from 13% to 96% in seed lots, were grouped into ‘high CD’ (CD rate ≥ 85%) and ‘low CD’ (CD rate < 85%). Specific seed lots of the parental lines M and V, harvested in 2013, were planted in 2017 on eight different fields to produce the hybrids D and E. In detail, cultivar D (low CD) is a hybrid of M2 (high CD) and V2 (low CD), and cultivar E (high CD) is a hybrid of M2 (high CD) and V1 (high CD); hence, both hybrids are half‐siblings sharing the same maternal line, but having different paternal lines. The fraction of the vertically transmitted microbiome from each parent was assessed for those samples.Seeds of 10 oilseed rape cultivars  harvested between 2013 and 2017, from 26 fields in four European countries, were obtained from NPZ (Norddeutsche Pflanzenzucht Hans‐Georg Lembke KG). General information and sample origins are outlined in Fig. The total DNA was extracted from all seed samples. For each sample, 20 seeds per replicate were surface sterilized by incubating them in sodium hypochloride (2%) for 5 min under agitation, following by six washing steps in sterile water. Seeds were mortared under sterile conditions and the homogenized solution was pelleted and further used for DNA extraction. Utilizing the FastDNA SPIN Kit for Soil and the FastPrep Instrument , the total DNA was extracted following the manufacturer's protocol. DNA was quality checked using a Nanodrop 2000  and stored at −20°C for PCR reactions.et al., et al., Isolated DNA was used for amplification of the 16S rRNA gene V4 hypervariable region with the 515f/806r primer pair  (Caporaso iime2 version 2018.4.0 pipeline (https://qiime2.org). Primer sequences were removed. Using the DADA2 algorithm in QIIME2 the reads were quality filtered and denoised, forward and reversed reads were joined, chimera were filtered, and feature table and representative sequences (amplicon sequences variants (ASVs)) were generated   in the package VEGAN .Bacterial genera correlating significantly to host functional parameters ‘germination rate’ and ‘resistance’ were identified by LEfSe as implemented in MicrobiomeAnalyst .Hierarchical clustering of the seed microbiome is based on Bray–Curtis dissimilarity. We used ourcetracker2 . Each sample was analysed in independent triplicates and reaction mixtures contained 5 μl KAPA SYBR Green, 0.5 μl (10 μM each) of each primer  under the project number PRJEB51924.Fig. S1. Taxonomic composition of oilseed rape seed endophytes. Barcharts in (a) and (b) represent the 18 most abundant bacterial families, and the 25 most abundant genera across the dataset, respectively; remaining genera are summarized as others.Table S1. Detailed metadata for the different seed lots.Table S2. Diversity and abundance dissimilarities between seeds for host‐related and external factors.Click here for additional data file.


In 2017, Tayside, a region in the East of Scotland, rapidly scaled‐up Hepatitis C Virus (HCV) outreach and treatment among People Who Inject Drugs (PWID) using novel community care pathways.We aimed to determine treatment outcomes for PWID during the scale‐up against pre‐determined targets; and assess re‐infection, mortality, and post‐treatment follow up.HCV treatment was delivered in community pharmacies, drug treatment centres, nurse‐led outreach clinics, prisons, and needle exchanges, alongside conventional hospital care. We retrospectively analysed clinical outcomes and compared pathways using logistic regression models.Of 800 estimated HCV‐infected PWID, 718 (90%) were diagnosed. 713 treatments commenced among 662 (92%) PWID, delivering 577 (81%) Sustained Virologic Responses (SVR). SVR was 91% among those who attended for testing. Forty‐six individuals were treated more than once. Needle exchanges and community pharmacies initiated 49% of all treatments. Regression analyses implied pharmacies had superior follow‐up, but there was no difference in likelihood of achieving SVR in community pathways relative to hospital care. Re‐infection occurred 39 times over 256.57 person years (PY), yielding a rate of 15.20 per 100 PY (95% CI 10.81‐20.78). 54 deaths occurred (29 drug related) over 1,553.04 PY, yielding a mortality rate of 3.48 per 100 PY (95% CI 2.61‐4.54). Drug‐related mortality was 1.87 per 100 PY (95% CI 1.25‐2.68).Rapid HCV treatment scale‐up to PWID in community settings, whilst maintaining high SVR, is achievable. However, other interventions are required to minimise re‐infection; reduce drug‐related deaths; and improve post‐SVR follow‐up testing regionally. Rapid regional HCV treatment scale‐up was achieved in Tayside. There were over 700 treatments across six pathways in three years, a close to two‐fold increase on previously high levels of HCV treatment among PWID. The estimated care cascade shows that 90% of the estimated HCV‐infected PWID population were diagnosed and 92% of those initiated treatment. SVR in the ITT group was over 80% and exceeded 90% in those with a documented test. Therapeutic advances led the World Health Organization, in 2016, to release its Global Health Sector Strategy, providing an implementation plan for HCV elimination.In 2017, concurrent to the WHO strategy response, National Health Service (NHS) Tayside—a health board in the East of Scotland serving approximately 416,000 people—commenced a trial of Treatment as Prevention (TasP) in HCV infection, by rapidly scaling up treatment among PWID.The programme was underpinned by novel community care pathways, and highly effective Direct Acting Antiviral (DAA) treatments.This study aims to determine if rapid regional scaleup of HCV treatment was achieved in the PWID population in line with local and WHO targets. We report critical real‐world outcomes of the scale‐up including cure rates  by treatment pathway, risks of HCV re‐infection, mortality rates, and effectiveness of post‐treatment follow‐up, both for SVR and re‐infection testing.22.1Prior to scaleup, there were an estimated 2800 PWID resident in the Tayside heath board region, of whom 800 (29%) were estimated to have chronic (6+ months infected) HCV.2.2The study is described on clinicaltrials.gov (NCT03356405) and ISCRCTN (ISRCTN72038467) and co‐sponsored by NHS Tayside and University of Dundee (2016GA08). It received NHS ethical favourable opinion (17/ES/0136). Data was obtained from HCV clinical databases; virology/microbiology records; and patient records. Caldicott Guardian approval for this was granted (IGTCAL7005).Individual parameters included: CHI; date of birth; gender; and post code of most recent residence to derive Scottish Index of Multiple Deprivation (SIMD).2.3HCV RNA testing on plasma samples was undertaken using the Hologic Panther platform with HCV Quant Dx Assay2.4Patient or public involvement groups were not involved in the design of this study. Study design was developed from prior experience of the investigators working with the stakeholders involved.2.5PWID was defined as ever injected drugs (self‐reported). Cirrhosis was defined as any of the following: Fibroscan reading >18kPa; Fib4 >3.46, or confirmation via: liver biopsy; ascites with evidence of liver disease; hepatic encephalopathy plus chronic liver disease; oesophagogastric varices with patent portal vein. SVR was undetectable HCV RNA at least 12 weeks post‐treatment. Relapse was undetectable RNA at end of treatment, but detectable prior to or at SVR; or treatment initiation and detectable RNA prior to or at SVR, if end of treatment test not conducted. Non‐response was detectable RNA above the lower limit of detection (10 IU/mL) during treatment. Re‐infection was detectable RNA following confirmed SVR, or detectable RNA at end of treatment with genotype change. Cause of death was classified as: liver related (or not); drug related 2.6There are six HCV care pathways in Tayside; five in community settings. They are named by location: conventional hospital care; drug treatment centres; needle exchanges; community pharmacies; nurse‐led outreach clinics and prisons. All community pathways are in environments accessible to PWID. In the nurse‐led outreach pathway, patients are seen in their local neighbourhood, typically in remote areas. Drug treatment clinics are in central locations. Testing, pre‐treatment assessment, and treatment are available in each . The needle exchange and community pharmacy pathways were initially experimental, implemented through pragmatic pathway trials, which became embedded to provide routine testing and treatment.2.7P of ≤0.05 was assumed to demonstrate statistical significance. Analyses were undertaken using IBM SPSS Statistics 25.Primary outcomes (treatments and SVR) were summarised using descriptive statistics, for comparison against targets. Comparison of SVR by patient and treatment characteristics were conducted in the same manner in intention‐to‐treat (ITT) and per‐protocol (PP) populations. The ITT group includes all who initiated treatment, and the PP group includes treatment completers. We hypothesised that variation in SVR in community pathways compared to specialist hospital care would be due to differences in follow‐up. Logistic regression modelling was used to assess this. Models were adjusted for patient characteristics and explored steps in the treatment journey for the ITT and PP groups, with and without SVR tests. Models were adjusted in a stepwise approach for age, gender, cirrhosis, and genotype. Where applicable, participants missing SVR were assumed treatment failures. 2.8Those who achieve SVR are offered annual follow‐up RNA testing through all pathways. We measured the efficacy of re‐infection follow‐up by calculating the proportion of cases with follow‐up RNA tests received in line with local policy . We estimated re‐infection incidence per 100 person‐years (PY), assuming a Poisson distribution. Time‐at‐risk began after SVR and ended at last negative RNA test, if not re‐infected. If re‐infected, time‐at‐risk ended at the mid‐point between last negative RNA test and re‐infection date. Where last negative RNA test indicated SVR, with no further follow‐up tests prior to the censor date, cases were excluded. Cases that did not achieve SVR or died prior to this were excluded. For cases that were re‐infected at time of SVR test, that is RNA negative at end‐of‐treatment, or missing end‐of‐treatment test, then RNA positive at SVR with different genotype, the time‐at‐risk period was from the date of end‐of‐treatment RNA test, or estimated date if test not available, and the mid‐point between then and date of SVR. Mortality was checked up to and including the censor date; rates were based on time‐at‐risk from treatment initiation for primary HCV infection to censor date or date of decease.3Annual treatments initiations among PWID in Tayside for the 3 years prior to scale‐up 2014‐16) were, 126, 138, and 130, giving a cumulative 394 treatments among 387 PWID. During treatment scaleup (January 2017 to April 2020), 713 treatments were initiated among 662 PWID . Most  were obtained in the ITT population (n = 713). Eighty‐two cases did not have an SVR test . Excluding those missing an SVR test in the ITT group, SVR was 91.4% Table . In the Of treatment completers, eight died prior to SVR testing. Of treatment non‐completers (n = 83), 41 (49.4%) obtained SVR, 30 (36.1%) did not and 12 (14.5%) were missing SVR data. Of those 12, 8 were LTFU; 3 moved and 1 died. For treatment non‐completers with documented SVR tests (n = 71), 57.7% obtained a cure.3.1During the study, 236 cases among 231 individuals were followed‐up for re‐infection. Of those who obtained SVR, 39% (227/577) had at least one follow‐up RNA test. Re‐infection occurred 39 times, 9 detected at SVR, over 256.57 PY of follow‐up, yielding a rate of 15.20 per 100 PY (95% CI 10.81‐20.78). Among those who reported recent injecting, there were 142 cases among 140 individuals over 175.43 PY, yielding a rate of 14.82 per 100 PY (95%CI 9.68‐21.72). Among re‐infections, 25 cases were re‐treated: 17 obtained SVR, four did not, and four were LTFU. Of re‐infected individuals, incidence was highest among those initially treated through needle exchanges  of 577 cases had repeat RNA testing in the first 12 months, in line with policy. Within two years of SVR, 110 (19%) of 577 had follow‐up testing. Of those, 20 (18%) reflected continued follow‐up from the previous year, in line with policy. Fifteen were tested within three years, and four within four years. The remainder either did not receive follow‐up testing or had non‐standard test intervals (eg <12 months from SVR).3.2Fifty‐four treated individuals died over a period of 1,553.04 PY, yielding an all‐cause mortality rate of 3.48 per 100 PY (95% CI 2.61‐4.54); 29 were drug related, yielding an estimated drug‐related mortality rate of 1.87 per 100 PY (95% CI 1.25‐2.68). Four (9%) deaths were liver‐related, due to: hepatocellular carcinoma (2); liver metastases and accompanying causes (2). Forty‐four (81.5%) patients died following SVR, while 10 died before SVR sample could be obtained.3.3Needle exchanges initiated the highest proportion of treatments Table . CollectResults for pathway‐denominated logistic regressions are presented in Table P ≤ 0.05). However, adjusted for patient characteristics, this became marginally non‐significant . There were no significant differences between pathways in the ITT group who attended for SVR. In the PP groups with (n = 630) and without (n = 560) SVR test, there were also no significant differences in SVR between pathways.The unadjusted model in the ITT population (n = 713) implied that those treated through community pharmacies had higher odds of achieving SVR . Of females who did not obtain SVR in this model, for 66.7% (18/27) this was due to LTFU after treatment completion. Suggesting that, following treatment completion, follow‐up for females may require attention across all pathways, as the effect fell away in the PP group with an SVR test (Data In the PP group, adjusted for age and gender, the model implied that female gender may be associated with reduced odds of SVR (OR 0.59 [.35‐1.01], Figure 4Rapid regional HCV treatment scale‐up in PWID was achieved in Tayside. There were over 700 treatments across six pathways in three years, a close to two‐fold increase on previously high levels of HCV treatment among PWID in Tayside. The estimated care cascade shows that 90% of the estimated HCV‐infected PWID population were diagnosed and 92% of those initiated treatment. SVR in the ITT group was over 80% and exceeded 90% in those with a documented test. Among treatment completers, SVR exceeded 85% and was over 95% for those with a documented test. Pharmacies and needle exchanges made substantial contributions, delivering almost half of all treatments. Our data adds strong population‐level evidence to the literature supporting HCV care in community pharmacies.Our findings suggest a high level of attrition at the post‐treatment follow‐up point among our cohort of PWID. This contrasts with data from, for example, the Icelandic national scaleup among PWID, which reported minimal attrition at each step of the HCV cascade of care.The data indicate high deprivation, in line with national estimates, and reinforces evidence that HCV disproportionately impacts the most disadvantaged.The high proportion of cure adds valuable real‐world evidence to existing literature demonstrating the efficacy of DAAs for treating HCV in PWID.Our data augments the literature suggesting re‐treatment following re‐infection should be offered without stigma or discrimination.Data reported here affirms existing evidence that completing treatment with DAAs elicits high SVR rates among PWID.4.1This study is limited by its observational nature, its reliance on routinely collected data, and the lack of a comparator cohort, which is the basis of the next phase of the study. During data collection, some assumptions were made, for example if date of infection was unavailable a surrogate was used, such as treatment initiation date, which may have affected person‐time estimates. Further, most cases that resulted in SVR were missing post‐SVR RNA testing, which limited re‐infection estimates. Finally, the NHS is free for patients: possibly limiting international transferability of the care model. However, this study's strength lies in its rich description of the PWID population and the unique investigation of TasP in the context of HCV elimination on a regional level using real‐world data.5Our analyses indicate that Tayside achieved pre‐specified local diagnosis, treatment, and SVR targets set for the TasP scale‐up programme. Further, Tayside has met WHO testing and treatment targets having diagnosed 90% of the estimated PWID population with HCV, and treated over 80% of cases.The re‐infection rate, and proportion of DRDs, suggests we reached the highest‐risk individuals for transmission of HCV and implies that harm reduction and substance misuse services in the region need strengthening. Other areas targeting PWID to achieve elimination should provide substantial‐related care in these respects alongside comprehensive testing and easy access to treatment.Guarantor of the article: Christopher J Byrne.Author Contributions: CJB co‐ordinated the study, collected data, performed statistical analyses and wrote the initial manuscript draft. LB co‐ordinated the study and collected data. SKI managed the study. ER advised on testing data. AR, DJG, MH, SH and JFD collaboratively conceived, designed, planned and executed the trial. All authors critically revised the manuscript for intellectual content and approved the final version.Supplementary MaterialClick here for additional data file.


The bone microarchitecture was assessed at appendicular and axial bones by micro‐computed tomography (μCT). Histomorphometric analysis was performed to determine cellular and dynamic bone parameters. Bone metabolism was also evaluated by biochemical markers and gene expression levels. Nacre‐based diet prevented the OVX‐induced bone loss better than that of the CaCO3 supplement, given the significant changes in trabecular bone volume fraction (BV/TV) both at the femoral distal metaphysis  and at the second lumbar spine . Trabecular osteoclast surfaces (Oc.S/BS) were also 1.5‐fold lower at the tibial proximal metaphysis in OVX Nacre group compared with OVX CaCO3 group (p = 0.02). By principal component analysis (PCA), OVX Nacre group formed a cluster away from OVX group and with a trend closest to Sham group. These data were consistent with biological measurements demonstrating a positive profile related to nacre supplementation, which blunted an increase in serum CTX level and enhanced serum P1NP secretion 14 days post‐OVX compared with CaCO3 supplementation. Bmp2 mRNA expression in OVX Nacre group was +1.76‐fold (p = 0.004) and +1.30‐fold (p = 0.20) compared with OVX and OVX CaCO3 groups, respectively. We conclude that supplementation with nacre could effectively limit bone loss induced by estrogen deficiency just after OVX in rats by modulating the negative imbalance of bone turnover. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.Nacre has emerged as a beneficial natural product for bone cells and tissues, but its effect was only studied by gavage in the ovariectomized mouse model. We sought to assess the antiosteoporotic effect of nacre through a nutritional supplementation in the ovariectomized rat model. Sixteen‐week‐old female Wistar rats were either Sham‐operated or bilateral ovariectomized (OVX) and then fed with standard diet (Sham and OVX groups) or standard diet supplemented with either 0.25% CaCO Although both men and women gradually lose bone as part of the aging process, a greater loss is observed in postmenopausal women associated with estrogen deficiency. The incidence of fracture increases with age in both sexes, but age‐adjusted rates are 49% greater in females than in males. In addition, after an initial fracture, women increase their risk of sustaining a second fracture by 36%, and from the age of 60 years, the residual lifetime risk of fracture is ~50% in women. Thus, postmenopausal osteoporosis related to its clinical consequences, including morbidity and mortality, imposes a significant health care problem to the society.Osteoporosis is a common and widespread skeletal disease that increases the risk of fragility fractures.1 It i marine animal–derived products, and fungi's metabolite, appear to be reliable sources for the development of antiosteoporotic agents due to their efficacy and safety. Nacre (mother‐of‐pearl) has been considered one of the potential candidates.Today, there is a need to develop novel approaches for osteoporosis treatment with fewer adverse effects than current therapies. It is encouraging that products from natural origin, such as plant‐derived extracts,6, 73) embedded in an organic matrix. This inorganic microstructure coupled with the organic phase contributes to the bioactivity of nacre as a novel biomaterial. Furthermore, several nacre matrix factors have been identified and known to have biological activities on bone cells. Protein PFMG1 and water/ethanol‐soluble matrix have been derived from Pinctada's pearl oyster family, which accelerate osteoblast differentiation. Beside the regulation of mineralization, protein N16 and other molecules from nacre have been demonstrated to inhibit osteoclastogenesis. These properties of nacre have directed research toward its effect on osteoporosis.Nacre is produced by mollusks and is composed of crystalline calcium carbonate  or virus injection techniques, whereas our experimental powders were integrated in dietary foods, which is considered as a classic nutritional supplementation in human.The preclinical studies revealed that nacreous factors prevent induced bone loss.14 Mos Here, we performed the ovariectomy, which mimics a condition similar to menopause, and also chose rat model, which bears a strong resemblance to human osteopenia, both in its anatomical features as well as in the transitional and steady stages of the bone dynamics.In the large variety of animal species, including rodents, non‐rodents  have been used as animal models in osteoporosis research, and no single animal species duplicates all the characteristics of human osteoporosis, and each species exhibits its own limitation.20 Her Also, the bone sites display different responses to bone loss stimulus related to their structural and metabolic characteristics. Hence, we thought that investigating the effect of nacre at both appendicular and axial bones would provide more translational insights of this novel research direction.Moreover, it is known that in osteoporotic women, the first and most severe bone changes occur in the spongy bone of the vertebral body, whereas in rats they predominantly involve the trabecular bone of the metaphyseal region of the long bones.21 AlsTo test the hypothesis that dietary nacre powder may have a protective effect against bone loss in the ovariectomized rat, we pursue two specific aims: (i) to quantify the prevention of bone loss due to estrogen deficiency at several skeletal sites and (ii) to explore the nacre action mechanisms through biomarkers involved in bone metabolism.22.1ad libitum. The animals benefited from quality attention and care by qualified personnel, both during and outside of procedures, to ensure optimal well‐being throughout the study. This study was carried out with the approval of the French Ministry of Research and Innovation . Animal procedures were performed in an accredited animal facility (authorization no. 42180801) at the PLEXAN  with the approval of the Animal Ethics Committee and in accordance with directive 2010/63/EU and the Principles of Laboratory Animal Care recommended by the National Society for Biomedical Research in France. All animal handling and experimental protocols followed the ethical standards established in the 1964 Declaration. Sixteen‐week‐old animals (mean ± SD body weight 237.6 ± 14.1 g) were assigned to one of the four groups (n = 10 per group): (i) Sham; (ii) OVX; (iii) OVX with CaCO3 (OVX CaCO3); (iv) OVX with nacre (OVX Nacre). Rats were anesthetized by 2.5% isoflurane and bilateral ovariectomy (OVX) was then performed via two ventro‐lateral incisions. The sham operation consisted of pulling the ovaries out of the abdominal cavity after skin incision, placing them back in the abdominal cavity, and suturing. No postoperative complications were observed.Eight‐week‐old female Wistar rats (mean ± SD body weight 166.8 ± 11.8 g) were housed under controlled conditions  in groups of two animals per cage with free access to water and food 3 or nacre powder. The diet was initiated on the day of surgery and was maintained for a period of 28 days after OVX. Pinctada maxima's nacre powder provided by Stansea, which is composed of 97% CaCO3  was compared with aragonite CaCO3  synthesized according to the protocol of Carteret and colleagues. Calcium content was the same for both the CaCO3 and nacre diets and 12% higher than standard diet. The composition of the diets is shown in Supplemental Table Both Sham and OVX groups received standard diet purchased by SAFE diets  and the last two groups received the standard diet mixed with 0.25% supplemental CaCOlleagues.22 CalAt the end of the study, rats were injected intraperitoneally with tetracycline (25 mg/kg body weight) at days 12 and 3 before killing to allow the bone histodynamic evaluation. Animals were weighed on arrival, before OVX, and every 2 weeks during the study. All animals were killed at the age of 20 weeks using isoflurane (4%) and cardiac puncture. The uterus was dissected and immediately weighed to check OVX efficacy.2.23 field of view (FOV)/diameter 30.7 mm). Rats were anesthetized and maintained on anesthetic isoflurane 2% for the duration of each measurement (approximately 25 minutes per rat). Tibias were scanned from the proximal growth plate and processed distally for 421 slices (6.32 mm) . The scanning system was calibrated at 70 kVp, 110 μA, and 1000 projections by 180 degrees with an integration time of 250 ms at high resolution  and then purified with a Qiagen pure tissue kit . The RNA quality was assessed by Experion automated electrophoresis station , followed by Ribogreen assay  for accurate RNA quantification. Total RNA reverse transcription was performed with iScript cDNA synthesis kit (Bio‐Rad). Quantitative real‐time (qRT) polymerase chain reaction (PCR) was conducted on CFX96 RealTime System (Bio‐Rad) with LightCycler FastStart DNA Master plus SYBRgreen I . The mRNA expression levels were normalized to the housekeeping t method.23 Pri2.5g for 2 minutes at room temperature for D0 and D14 samples or at 2000 g for 10 minutes at 4°C for D28 samples and separated in serum and plasma, then stored at −80°C. Serum levels of C‐terminal collagen cross‐linking telopeptide of type I collagen (CTX), procollagen type I N‐terminal propeptide (P1NP), and osteocalcin  were quantified by ELISA commercial kits according to manufacturer protocols . Serum calcium and inorganic phosphate levels were measured with colorimetric assays . In addition, levels of parathyroid hormone (PTH) and fibroblast growth factor 23 (FGF23) in plasma were measured by Rat Intact PTH ELISA Kit  and Mouse/Rat FGF23 Intact ELISA Kit (Immunotopics), respectively.Rats were fasted overnight before each blood collection by intravenous puncture in the tail at surgery day (D0: start point) and day 14 (D14: intermediate point), and by cardiac puncture under anesthesia at the end of the study (D28: end point). Blood was centrifuged at 13000 2.6n = 10/group.Graphical data are presented as box plots, with the central box spanning 25th to 75th percentiles and the central line representing the median. Whiskers represent the 10th and 90th percentiles and dots represent the sampling distribution. Graphs depicting body weight changes and serum/plasma biomarker levels are presented as line plots, with vertical bars depicting the mean and standard error (SE). Data were checked for normality and distribution using Quantile‐Quantile plots and Shapiro–Wilk test. Numerical tabular data are shown as the median and interquartile range (IQR) or mean and standard deviation (SD). Power analysis and calculation of sample size were performed before the initiation of the study by G*Power to define the alpha level of 0.05 and the beta level of 0.15, thereby the sample size was  Tukey's honest significant difference (HSD) post hoc test was then performed to report 95% confidence intervals (CI); (ii) biochemical marker levels in serum/plasma were analyzed by two‐way repeated measures ANOVA to determine if there were group effects (between‐subjects factor), time effects (within‐subjects factor), and interactions between them. After ANOVA, Tukey's HSD post hoc test was used for multiple comparisons between groups and between the value at time point versus that at previous time point in each group.For longitudinal data analysis, (i) comparisons between groups in μCT in vivo study at follow‐up were based on analysis of covariance (ANCOVA) general linear models using values at baseline as covariable, as a standard method.24 Tuk was then performed for pairwise comparisons.For cross‐sectional data analysis, parameters of the μCT ex vivo bone microarchitecture, histomorphometry, and relative gene expressions were compared between groups using ANOVA, followed by Tukey's HSD post hoc test. If the normal condition was not satisfied, Kruskal–Wallis test was used instead, and Mann–Whitney–Wilcoxon (MWW) unpaired test corrected by the false discovery rate adjustment method of Benjamini and Hochberg26 wasp value of 0.05 was considered statistical significance. Data analysis was conducted with R Statistical Environment and data visualization using the ggplot2 package.A nominal  by function prcomp in base R environment and the autoscale function was applied to the data set. Graphical visualization was shown using package factoextra.The μCT and histomorphometric ex vivo variables in the tibia were processed with principal component analysis (PCA), an unsupervised method of machine learning,27 by 33.1A). Beginning from 14 days post‐OVX, a weight difference of approximately 12% was observed between OVX and Sham groups . The final body weights of OVX and Sham groups at day 28 were 271.27 ± 2.25 g and 237.25 ± 9.6 g (p < 0.001), respectively. The uterus weight of OVX rats was significantly lower than that of Sham (p < 0.001) due to estrogen deficiency–induced uterine atrophy. No significant difference in uterine weight between the different OVX groups was observed (data not shown).All rats showed a gradual increase of body weight over the first 8 weeks before OVX, according to physiological growth , trabecular thickness (Tb.Th) was 22% lower , and trabecular spacing (Tb.Sp) was +67% higher  in OVX group , trabecular number (Tb.N) was 26% lower (p < 0.001), Tb.Th was 11% lower (p = 0.01), and Tb.Sp was +53% higher (p < 0.001) in OVX group compared with Sham. In the second lumbar spine , with no change in Tb.Th. (p > 0.10).In the femur Fig. , trabecuWe also assessed the cortical bone microarchitecture in the diaphysis of both tibia and femur, but no change was roughly observed at day 28 post‐OVX  compared with Sham.Representative images and parameters for histomorphometry evaluation in longitudinal sections of non‐decalcified tibias are shown in Fig. The global visualization among the μCT and histomorphometry variables in tibia and the rats was explored with PCA Fig. . Score pBgalp  and Runx2 mRNA  and both approximately 2‐fold higher NFATc1  and Rank (p < 0.001) compared with Sham group.In line with the μCT and histomorphometry results, estrogen deficiency also induced an increase of mRNA expression of gene markers involved in both osteoblastogenesis and osteoclastogenesis. As shown in Fig. In agreement with the above results, the serum levels of bone turnover biomarkers were significantly elevated in OVX rats with respect to time Fig. . There w3.23.2.1p = 0.04) , we transformed the raw data set into symmetric percent change from baseline values before conducting pairwise comparisons between OVX groups . From baseline, nacre diet significantly limited body weight gain by 44%  and 38%  compared with OVX and OVX CaCO3 group, respectively, at day 14. Both CaCO3 and nacre diet reduced by 22% of weight at the end of the study (p = 0.02).Because of the significant differences in body weight between groups observed at the beginning of study (3.2.2p > 0.10) and 20%  for OVX CaCO3 group compared with OVX Nacre group in a large effect size (ƞg2 > 0.40), with mean percent change from baseline in BV/TV of −55% (OVX), −56% (OVX CaCO3), and −48% (OVX Nacre). Supplementing with nacre also led to higher connectivity density (Conn.D), Tb.N, and Tb.Th and to lower Tb.Sp compared with those of both standard and CaCO3 diets, after accounting for baseline values  and CaCO3 (p = 0.004) diets in OVX rats, as well as other microarchitectural parameters.In the femur distal metaphysis Fig. , trabecup = 0.04) and CaCO3  diets, and trabecular number and separation were equal to standard but better than CaCO3 diet . The protective effects of nacre in trabecular bone at various bone sites are summarized in Table 3 diets in OVX rats.The OVX‐induced deterioration of microarchitecture in the second lumbar spine was also moderately prevented by nacre diet Table . In nacr3.2.33  and OVX Nacre  compared with that of OVX group. Interestingly, this decrease was 1.50‐fold greater in nacre than in CaCO3 diet (p = 0.03). Bone formation parameters in OVX CaCO3 and Nacre groups remained as increased as in the OVX group compared with Sham.In pairwise comparisons between the three OVX groups Fig. , the ost3 diet exhibited similar features to those under standard diet, whereas most of the OVX rats under nacre diet close to zero score of the first component. On the other hand, OVX Nacre rats tended to exhibit Sham's trabecular characteristics and were clearly apart from OVX rats.As illustrated in Fig. 3.2.43 and nacre) in OVX rats on osteoblastogenesis, we examined various signaling factors involved in osteoblast differentiation or reflecting its activity. Despite a global decrease in expression of the bone formation–related genes such as Col1a1, Bglap, and Runx2 in OVX CaCO3 and nacre groups compared with OVX, the mRNA amounts of these genes were more expressed in nacre than in CaCO3  and by 1.70‐fold in nacre diet (p = 0.004) compared with standard diet in OVX rats.To investigate the potential molecular mechanisms underlying the effect of experimental diets  and Acp5 by 1.45‐fold (p = 0.04) compared with the CaCO3 diet, even more than standard diet in some genes, Cathepsin K  and Spp1   than under CaCO3 diet , compared with baseline. Osteocalcin levels from baseline were similarly increased in nacre  and CaCO3 . At day 28, CaCO3 diet diminished the fluctuation of three markers related to OVX  but still more elevated than those of Sham (p < 0.05). In contrast, nacre showed more abundance of osteocalcin and CTX than CaCO3 (p = 0.02) and illustrated by approximately +1.50‐fold or more versus baseline values.At day 14, CaCOp = 0.05), whereas that of nacre was not detected.We next examined whether nacre might potentially affect the calcium – phosphate homeostasis regulated by the estrogen – PTH – FGF23 axis. As shown in Fig. p = 0.02), which were not associated with significant changes in serum FGF23 levels.Nacre supplements also had a small but significant effect on serum phosphate, with a transient about 1.50‐fold increase from baseline at day 14 and 28 . This is correlated to the gene expression analysis that reflects the cellular activities at day 28. Our outcomes support the argument that osteopenia is detected in OVX rat as soon as 14 days post‐OVX and became progressively more pronounced up to 100 days. We additionally suggest that bone formation could be maximized in the initial rapid phase at day 14, then declined at later times post‐OVX, whereas bone resorption would be sustained in the longer time, so that the increase in bone resorption exceeds the increase in bone formation.Concerning the serum markers of bone homeostasis, osteocalcin is the bone turnover marker, P1NP is a more sensitive biomarker of bone formation in osteoporosis, and CTX is a specific and sensitive biomarker of bone resorption.36 Ovated Fig. A. This 4.24.2.13 and nacre diets limited body weight gain after 28 days post‐OVX, this positive impact was detected as early as at 14 days with nacre, whereas that of CaCO3 was not  but any significant differences were detected in both young and old animals and those were not on lumbar spine BMD. Here, we used only 12% higher calcium in CaCO3 and nacre diets during 4 weeks. Thus, these recognized preventive impacts on bone sites suggest that nacre effect could be the result not only from calcium carbonate but also from organic compounds , which are known for their bioactive properties  and also meaningfully participate in the physiopathological condition in OVX rat model.In appendicular bones (tibia and femur) and lumbar spine, nacre diet partially preserved trabecular bone mass and microarchitecture parameters Figs, whereaspine BMD.41 Her3 diet .44 One or injection method used in previous studies, we gave priority to prepare the diets supplemented with CaCO3 or nacre close to the 3R principles of animal welfare. Additionally, we addressed the responses to bone loss of different skeletal sites, including appendicular and axial bones, which have a significant translational relevance. Also, by combining both longitudinal and cross‐sectional study designs, we generated an overall interpretation for estrogen deficient–induced bone loss in rats and thus tried to explain how nacre could protect bone structure in live animals.Our study has several strengths. First, instead of using the gavage7, 8 or at least of six remodeling cycles to allow relevant inference on long‐term bone efficacy and safety in humans. Although the rat has been recommended to be used as a rodent postmenopausal model, it shows a potential drawback; that is, the lack of Haversian remodeling in the intracortical bone. Lastly, the lack of control for dietary intake of the animals induced the inability of calculation about the average exposure of kg body weight to experimental powders.Our study also has limitations. The rat skeleton should be exposed to a pharmaceutical agent for a duration either equivalent to bone turnover rates in humans (100 to 200 days) and rats (40 days),47 or 3. This occurred by modulating the negative imbalance of bone turnover that led to these changes. This effect might be driven by the limitation of secondary hyperparathyroidism. However, we cannot rule out an additional uncoupling effect of nacre on bone remodeling at day 14, which could slightly stimulate bone formation. Further preclinical studies based on longer‐term evaluation and on the non‐rodent model are still needed to confirm the efficacy and safety of nacre. It remains to identify the precise mechanisms whereby the nacreous organic matrix acts on bone.In this study, we found that supplementation with nacre could effectively limit bone loss induced by estrogen deficiency after ovariectomy in rat better than CaCOMR provides scientific consultation for Megabiopharma. TT reports receiving lecture fees from Amgen, Arrow, Biogen, BMS, Chugai, Galapagos, Grunenthal, Jansen, LCA, Lilly, MSD, Nordic, Novartis, Pfizer, Sanofi, Thuasne, Theramex, and UCB and research grants or investigator's fees from Bone Therapeutics, UC. All other authors state that they have no conflicts of interest.Dung Kim Nguyen: Data curation; formal analysis; methodology; visualization; writing – original draft; writing – review and editing. Norbert Laroche: Data curation; formal analysis; investigation; methodology. Arnaud Vanden‐Bossche: Conceptualization; methodology. Marie‐Thérèse Linossier: Data curation; formal analysis; investigation; methodology. Mireille Thomas: Data curation; formal analysis; investigation; methodology. Sylvie Peyroche: Investigation; methodology. Myriam Normand: Data curation; formal analysis; methodology; software. Yacine Bertache‐Djenadi: Formal analysis; investigation. Thierry Thomas: Writing – review and editing. Hubert Marotte: Writing – review and editing. laurence vico: Conceptualization; methodology; validation; writing – review and editing. Marie‐Helene Lafage‐Proust: Methodology; writing – review and editing. Marthe Rousseau: Conceptualization; funding acquisition; investigation; methodology; project administration; resources; supervision; writing – review and editing.Study concept and design: MR, AVB, and LV. In vivo studies: MR, AVB, and NL. Micro‐CT analysis: DKN, NL, and YB. Bone histomorphometry: DKN, NL, and MHLP. Blood biomarker measurements: DKN, MTL, and SP. Gene expression analysis: DKN, MTL, and MT. Data analysis: DKN and MN. Data interpretation: DKN, MHLP, and MR. Data visualization and writing—original draft: DKN. Writing—review and editing: DKN, MHLP, and MR. Approving final version of manuscript: DKN, MHLP, TT, HM, LV, and MR.5https://publons.com/publon/10.1002/jbm4.10655.The peer review history for this article is available at Supplemental Fig. S1. OVX‐induced body weight variation in rats.Click here for additional data file.Supplemental Fig. S2. The morphological trabecular parameters in the proximal tibia in ex vivo cross‐sectional study.Click here for additional data file.Supplemental Fig. S3. Quantitative results of μCT ex vivo analysis in the distal metaphyseal femur expressed as BV/TV, Conn.D, Tb.N, Tb.Th, Tb.Sp, and SMI.Click here for additional data file.Supplemental Fig. S4. Location of skeletal sites was analyzed using μCT.Click here for additional data file.Supplemental Fig. S5. Changes in plasma PTH (A), serum calcium (B), plasma FGF23 (C), and serum phosphate (D) from baseline to follow‐up in the OVX and OVX Nacre groups.Click here for additional data file.Appendix S1. Supporting information.Click here for additional data file.Supplemental Table S1. Composition of Experimental DietsClick here for additional data file.Supplemental Table S2. The Supplemental Information Used in Bone Morphology Analysis by μCTClick here for additional data file.Supplemental Table S3. Primer Sequences Used in This StudyClick here for additional data file.Supplemental Table S4. Quantification of μCT‐Derived Cortical Bone Microarchitectural Parameters at the Tibial and Femoral Diaphysis in Ex Vivo Cross‐sectional StudyClick here for additional data file.


Whether atrial septal aneurysm (ASA) increases the risk of cerebrovascular ischemic events in patients with patent foramen ovale (PFO) remains controversial.We constructed a detailed meta‐analysis to assess the effect of ASA on risk of cerebrovascular ischemic events in patients with PFO.Randomized controlled trials (RCTs) and observational studies (cohort studies and case‐control studies) that compared PFO‐ASA against PFO alone were included. Pooled odds ratios (OR) estimates and 95% CI were calculated using the fixed‐effect and random‐effect models.p < 0.01, random‐effect model: OR = 3.63; 95% CI: 2.51–5.24; p < 0.01). However, poole results from RCTs  and cohort studies  found no evidence. Overall analysis showed that ASA increased the risk of cerebrovascular ischemic events . The sensitivity analysis confirmed the stability of all results.Four RCTs and twelve observational studies (five cohort studies and seven case‐control studies) contributed to the meta‐analysis. The pooled results of case‐control studies showed that ASA increased the risk of cerebrovascular ischemic events in patients with PFO (fixed‐effect model: OR = 3.69; 95% CI: 2.67–5.09; Although case‐control studies support ASA to increase the risk of cerebrovascular ischemic events in patients with PFO, RCTs and cohort studies challenged the credibility. Further prospective studies are needed to confirm the effect of ASA on patients with PFO. Patent foramen ovale (PFO) has been identified as one of the etiology of unexplained embolism events.This meta‐analysis was performed in accordance with the preferred reporting items for systematic reviews and meta‐analyses (PRISMA) statementWe searched electronic databases of PubMed, Embase, and MEDLINE from inception through March 2022 with no language restriction. Search terms included “patent foramen ovale”, “PFO”, “stroke”, “atrial septal aneurysm”, “antiplatelet therapy”, “anticoagulant therapy”, “medical therapy”, “transient ischemic attack (TIA)”, “TIA”, “recurrent stroke”, “recurrence of embolic events”, and cerebrovascular ischemic events. In addition, the relevant research references were also manually searched to identify potentially eligible studies.The studies enrolled in this meta‐analysis included both RCTs and observational studies (cohort studies and case–control studies) that evaluated effect of ASA on the risk of cerebrovascular ischemic events (stroke or TIA) in patients with PFO. Comparisons between patients with PFO‐ASA and those with PFO alone should be included in these studies. If all patients in one arm of a study had concomitant large shunt, the study was excluded. For RCTs and cohort studies，studies consistent with medical therapy (antiplatelet therapy and/or anticoagulant therapy) as the only preventive measure for recurrent cerebrovascular ischemic events were included in this meta‐analysis. If studies were from multiple publications of the same population, only data from the latest publications were included. Reviews, case reports, cross‐sectional studies, repeated papers, and conference abstracts were excluded in this meta‐analysis. Two reviewers (L.X. and C.Z.) abstracted the data independently according to selection criteria. Any disagreement was resolved by discussion or referral to a third author (X.P.).The quality of studies was assessed according to Cochrane Handbook for RCTsI2 test. The I2 value is between 0% and 100%, and larger values show increasing heterogeneity. If I2 was >50%, heterogeneity was considered significant; If I2 was <25%, heterogeneity was considered significant. To explore the stability of meta‐analysis results, sensitivity analysis was performed by excluding each study one by one. Funnel plots were used to test the possibility of publication bias. For all tests, p < 0.05 was considered statistically significant. Review Manager 5.3 software  was used for the statistical analyses.We conducted meta‐analyses of RCTs and observational studies (cohort studies and case–control studies) according to different study designs. For observational studies, we performed separate analyses for case–control studies and cohort studies. This was done to examine the consistency of results from different study designs. In addition, we pre‐specified subgroup analyses for the three study designs based on neurological characteristics of exposed population and age range of patients. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for each study and pooled values. If zero endpoint events occurred in 1 arm of a study, continuity correction of 1/2 was used. If zero endpoint events occurred in both arms of a study, we did not include them in the meta‐analysis. According to heterogeneity detected, we used a fixed‐effect model (Mantel–Haenszel method) or a random‐effect model (DerSimonian‐Laird method) to calculate pooled OR estimates. In the absence of heterogeneity, the results of fixed effects and random effects models are similar. In the presence of heterogeneity, both models may be biased. Therefore, we conducted interactive tests of the model against the pooled results of RCTs and observational studies. Study heterogeneity was assessed with Cochran Q test and Our initial search identified 628 records. After step‐by‐step selection and search, four RCTsp = 0.36) . The results of random‐effect model after interaction test were also not statistically significant  . Heterogeneity among studies was moderate . Sensitivity analysis showed that the pooled OR ranged from 2.36 (95% CI: 1.77–3.14) to 2.91 (95% CI: 2.22–3.83) and the overall conclusions remained unchanged.Twelve observational studies were eligible, including five cohort studies and seven case–control studies. For the cohort study, a total of 204 patients with PFO‐ASA and 583 patients with PFO alone were included in the analysis. For the case–control study, a total of 532 patients with PFO‐ASA and 471 patients with PFO alone were included in the analysis. Meta‐analysis of all observational studies showed that patients with PFO‐ASA had an increased risk of cerebrovascular ischemic events compared with patients with PFO alone . Heterogeneity among studies was not significant . Sensitivity analysis showed that the pooled OR ranged from 1.12 (95% CI: 0.62–2.07) to 1.57 (95% CI: 0.90–2.73) and the overall conclusions remained unchanged. In the analyses of case–control studies, ASA increased the risk of cerebrovascular ischemic events in patients with PFO . Heterogeneity among studies was not significant . Sensitivity analysis showed that the pooled OR ranged from 2.92 (95% CI: 2.04–4.17) to 3.80 (95% CI: 2.67–5.39) and the overall conclusions remained unchanged.We performed separate analyses of cohort and case–control studies. In the analyses of cohort studies, we found that although ASA increased the risk of cerebrovascular ischemic events in patients with PFO, the difference was not statistically significant . Heterogeneity among studies was significant . Sensitivity analysis showed that the pooled OR ranged from 1.92 (95% CI: 1.42–2.59) to 2.30 (95% CI: 1.65–3.19) after exclusion of the included studies one by one and the overall conclusions remained unchanged. The main results of meta‐analysis of RCTs and observational studies are presented in Table We performed a combined meta‐analysis of RCTs and observational studies. Combined analysis showed that ASA increased the risk of cerebrovascular ischemic events in patients with PFO . In case–control studies, ASA had a significant effect on cerebrovascular ischemic events in the subgroup ≤60 years of age . The results of subgroup analysis of RCTs and observational studies are presented in Table We pre‐specified subgroup analyses for the three study designs based on exposure population and age range of patients. In cohort studies, ASA increased the risk of cerebrovascular ischemic events in the subgroup ≤60 years of age (fixed‐effect model: OR = 2.22; 95% CI: 1.01–4.90; Funnel plots of cohort studies, case–control studies, and RCTs are shown in Figure Whether ASA can increase the risk of cerebrovascular ischemic events in patients with PFO remains controversial.Our meta‐analysis showed that the conclusions of RCTs and observational studies were different. The pooled results of observational studies showed that ASA increased the risk of cerebrovascular ischemic events in patients with PFO. However, the pooled results of RCTs showed no evidence that ASA increased the risk of cerebrovascular ischemic events in patients with PFO. Furthermore, the results of separate analysis of cohort and case–control studies were also inconsistent. For cohort studies, although patients with PFO‐ASA had an increased risk of recurrence than patients with PFO alone, the difference was not statistically significant. However，the pooled results of case–control studies showed that ASA significantly increased the risk of cerebrovascular ischemic events in patients with PFO. In our opinion, on the one hand, selection bias and event definition heterogeneity of observational studies will have a certain deviation from the research conclusion. On the other hand, most case–control studies did not use multivariable adjustment methods to adjust for confounding factors, resulting in statistical bias. Third, in RCTs and cohort studies, the low recurrence rate of cerebrovascular ischemic events led to some studies unable to find the difference after follow‐up. Prior to this study, Rigatelli et al.Subgroup analysis was performed for each of the three designs according to the factors that might influence the results. Age as influential factor plays an important role in the risk of cerebrovascular ischemic events in patients with PFO. Some studiesOur meta‐analysis had several limitations. First, observational studies included in this meta‐analysis were not adjusted for confounders. Therefore, the effect of ASA on cerebrovascular ischemic events in patients with PFO may be affected by other risk factors. Second, results of meta‐analyses and pre‐specified subgroup data can only be considered exploratory. Third, limitations of non‐randomized studies include selection bias, heterogeneity of event definition, and differences in duration and intensity of follow‐up to events. Fourth, heterogeneity in the definition of ASA was observed in several studies. In most studies, ASA was defined as an atrial septal excursion of ≥10 mm, while some studies used 11 or 15 mm as the cutoff point. The heterogeneity of these definitions cannot be ignored and may affect the results.Although case–control studies showed that ASA increased the risk of cerebrovascular ischemic events in patients with PFO, RCTs and cohort studies found no evidence. Further prospective studies are needed to confirm the effect of ASA on patients with PFO.Conceptualization: Chang Zhou and Liang Xu. Data curation: Liang Xu and Chang Zhou. Formal analysis: Xuemei Pan, Liang Xu, and Chang Zhou. Funding acquisition: Jun Zhou. Investigation: Tao Xu, Xuemei Pan, and Heng Sun. Methodology: Liang Xu, Xuemei Pan, and Jun Zhou. Software: Liang Xu and Heng Sun. Supervision: Xuemei Pan and Jun Zhou. Writing—original draft: Liang Xu and Chang Zhou. Writing—review & editing: Chang Zhou and Tao Xu.The authors have no conflicts of interest to disclose.File S1. PRISMA 2009 checklist.Click here for additional data file.File S2. Flow diagram of study selection.Click here for additional data file.Table S1. Risk of bias of included randomized trials.Table S2. Study quality of included comparative observational studies using the Newcastle‐Ottawa scale.Click here for additional data file.


Circular RNA (circRNA) myosin light chain kinase (circMYLK) has recently received increasing attention in cancer biology. Several studies have suggested that circMYLK expression is linked to prognosis and clinicopathological characteristics of various malignancies.This study was carried out to systematically review the impact of circMYLK on the progression of multiple cancers and assess the significance of circMYLK in the prognosis and clinicopathological features of the patients.PubMed, Web of Science, and Embase were systematically searched until July 2, 2021. For qualitative synthesis, the signaling pathways of circMYLK in the progression of different cancers were summarized. Regarding the meta‐analysis, overall survival (OS) and eight clinicopathological characteristics of patients with cancers were addressed. Odds ratios (ORs) and hazard ratios (HRs) were calculated to assess the association of circMYLK with prognostic and clinicopathological features.Twelve studies investigating the role of circMYLK in cancer progression met the inclusion criteria. Among these, seven studies investigated the prognostic significance of circMYLK, and nine studies ascertained the clinicopathological importance of circMYLK in patients with various malignancies. CircMYLK acts as a tumor promoter circRNA, leading to migration, proliferation, invasion, and metastasis of neoplastic cells and inhibiting their apoptosis through interaction with several miRNAs and corresponding downstream signaling pathways. Overexpression of circMYLK was correlated with poor OS  and larger tumor size , higher T stage , lymph node metastasis , and higher TNM stage .CircMYLK is involved in the progression of numerous cancers via different signaling pathways. This circRNA can serve as a promising prognostic biomarker for several types of malignancies. Furthermore, high expression of circMYLK is associated with advanced clinicopathological characteristics in various tumors. Furthermore, a manual search was conducted within the references of included studies and review articles to find further records.2.2The patient population of the study consisted of adult (age ≥ 18 years) patients diagnosed with any type of cancer.After removing the duplicate records, two investigators independently evaluated the titles and abstracts of the studies to obtain those assessing the significance of circMYLK in cancers. Studies without any description of circMYLK in malignancies were excluded. At this stage, the full texts of the remaining articles were reviewed for inclusion by the same investigators based on the following eligibility criteria:IIThe association between the expression of circMYLK and cancer progression was assessed.The non‐original studies and studies with a solely bioinformatic approach were excluded. A third investigator double‐checked the process of study selection.AND2.3The data regarding the basic study characteristics , cancer type, detection sample and method of detection, the expression pattern of circMYLK, and its downstream signaling pathway were extracted from all the included studies for qualitative synthesis of the results.For the meta‐analysis, overall survival (OS) was regarded as the primary prognostic outcome, and hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) were estimated based on the provided data and Kaplan–Meier survival curves, according to the methods described previously.p‐values comparing these groups were collected.Concerning the clinicopathological features, eight parameters were assumed: 1. Age (older vs. younger); 2. Gender ; 3. Tumor size ; 4. Tumor grade (III + IV vs. I + II); 5. T stage (III + IV vs. I + II); 6. Lymph node metastasis (yes vs. no); 7. Distant metastasis (yes vs. no); and 8. TNM stage (III + IV vs. I + II). For calculation of odds ratios (ORs) and 95% CIs, the number of patients in high‐ and low‐expression groups of the circMYLK for these endpoints and 2.4p‐value <0.05 signifying heterogeneity) and Higgins' I‐squared test (I2 > 50% indicating heterogeneity).2 > 50%), random‐effect models were employed to pool effect sizes; otherwise, fixed‐effect models were implemented. Publication bias was investigated by visual assessment of funnel plots and Begg's test for prognostic meta‐analysis. All the analyses were performed in Stata  and RevMan (version 5.4), with the p‐value <0.05 representing statistical significance.For the prognostic meta‐analysis, pooled HRs and 95% CIs were calculated to explore the association between circMYLK expression and the OS of oncologic patients. Sensitivity analysis was conducted to assess each study's contribution to the pooled HRs by excluding one study at a time from the meta‐analysis. Pooled ORs and 95% CIs were calculated for each endpoint regarding clinicopathological features. Forest plots were constructed for OS and clinicopathological features of patients with cancers. The statistical heterogeneity was explored by Cochrane's Q test . No evidence of publication bias was observed utilizing funnel plot assessment and Begg's test (p = 0.07)  with the maximum follow‐up duration ranging from 30 to 100 months Table .7, 9) Figure . Sensiti) Figure .3.3p = 0.04; heterogeneity statistics: I2 = 84%, PQ <0.01], higher T stage , lymph node metastasis , and higher TNM stage  ; p = 0.15; heterogeneity statistics: I2 = 0%, PQ = 0.47], tumor grade , and distant metastasis   population, which may influence our findings on a larger scale. Future studies are warranted to evaluate the role of circMYLK as a prognostic factor for patients with cancers of other races and ethnicities. Second, the HRs were not directly reported in any of the included studies. Thus, two experienced investigators estimated the HRs and 95% intervals based on the methods previously described by Tierney et al.5To sum up, circMYLK is involved in the progression of several cancers via different signaling pathways. This circRNA can serve as a promising prognostic biomarker for several types of malignancies, and high circMYLK expression is associated with advanced clinicopathological characteristics in various tumors. Future multicenter and high‐quality studies with patients from diverse races and ethnicities are warranted to confirm these findings.Roham Foroumadi: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; project administration ; writing – original draft (lead); writing – review and editing . Sina Rashedi: Conceptualization ; formal analysis ; methodology ; project administration; writing – original draft ; writing – review and editing. Sara Asgarian: Data curation ; formal analysis ; writing – original draft . Mahta Mardani: Data curation ; investigation ; writing – review and editing . Hossein Farrokhpour: Formal analysis; methodology ; visualization . Salar Javanshir: Investigation; writing – review and editing. Rojin Sarallah: Data curation; investigation. Nima Rezaei: Conceptualization ; project administration (lead); supervision .This study received no specific grant from funding agencies in the commercial, public, or not‐for‐profit sectors.The authors have stated explicitly that there are no conflicts of interest in connection with this article.Not applicable.Data S1. Supporting information.Click here for additional data file.