The transition from non–muscle‐invasive bladder cancer (NMIBC) to muscle‐invasive bladder cancer (MIBC) is detrimental to bladder cancer (BLCA) patients. Here, we aimed to study the underlying mechanism of the subtype transition. Gene set variation analysis (GSVA) revealed the epithelial‐mesenchymal transition (EMT) signalling pathway with the most positive correlation in this transition. Then, we built a LASSO Cox regression model of an EMT‐related gene signature in BLCA. The patients with high risk scores had significantly worse overall survival (OS) and disease‐free survival (DFS) than those with low risk scores. The EMT‐related gene signature also performed favourably in the accuracy of prognosis and in the subtype survival analysis. Univariate and multivariate Cox regression analyses demonstrated that the EMT‐related gene signature, pathological N stage and age were independent prognostic factors for predicting survival in BLCA patients. Furthermore, the predictive nomogram model was able to effectively predict the outcome of BLCA patients by appropriately stratifying the risk score. In conclusion, we developed a novel EMT‐related gene signature that has tumour‐promoting effects, acts as a negative independent prognostic factor and might facilitate personalized counselling and treatment in BLCA. Furthermore, we integrated the least absolute shrinkage and selection operator (LASSO) Cox regression model of the EMT‐related gene signature in BLCA. The results showed that BLCA patients with high EMT risk scores were strongly associated with shorter disease‐free survival and overall survival than BLCA patients with low risk scores. Finally, we demonstrate that BLCA patients with a high EMT risk score are more likely to progress and metastasize, which is in accordance with the features of EMT. Together, our findings highlight a functional role for the EMT‐related gene signature and uncover a potential prognostic biomarker for BLCA.22.1https://tcga.xenahubs.net). Other data sets, including http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32548, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32894 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48075, were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/); detailed information is shown in Tables http://software.broadinstitute.org/gsea/index.jsp).TCGA‐BLCA pancancer‐normalized data and clinical information were downloaded from UCSC Xena , where Expri is the relative expression of the gene in the signature for patient i, and coefi is the LASSO coefficient of gene i.In our study, the ‘HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION’ genes were used as candidate biomarkers. Based on the ‘glmnet’ package in R, LASSO Cox regression analysis was applied to build an optimal prognostic signature for BLCA samples by using these candidate biomarkers.2.5The patients from different data sets were equally divided into low‐risk and high‐risk groups based on the risk score of the EMT‐related gene signature. Then, time‐dependent receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC) for 1‐year, 3‐year and 5‐year overall survival and disease‐free survival and to determine the prediction accuracy of our model by using the ‘survivalROC’ package in R.2.6http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507 and OS in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48075; DFS in TCGA‐BLCA, DFS in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, DFS in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32548 and DFS in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32894) were applied to validate our signature. Time‐dependent ROC analysis was also performed to prove the accuracy for survival prediction.To further investigate the clinical value of our signature, independent data sets , and the statistical significance between them was analysed by the t test or one‐way ANOVA. Then, cluster analysis was performed and a heat map was constructed with the 7 EMT‐related genes to better differentiate the low‐risk group and the high‐risk group according to the EMT‐related gene signature risk score by utilizing the ‘pheatmap’ package in R. The relationship between each clinicopathological characteristic and the risk level was measured by the chi‐square test. *2.8To determine whether the prognostic model was significant in other clinical characteristics, all the clinicopathological characteristics in the TCGA‐BLCA data set, including subtype transition, age, gender, pathological tumour stage, histological subtype, pathological N stage, pathological T stage, lymphovascular invasion status and number of positive lymphonodes by HE, were divided into two groups. Patients were stratified into age ≤65 years and age >65 years, female and male subgroups, pathological tumour stage I/II and stage III/IV subgroups, no papillary and papillary subgroups, pathological N0 and N+ (N1‐3) subgroups, pathological T0‐T2 and T3‐4 subgroups, lymphovascular invasion ‐ and lymphovascular invasion + subgroups, and number of positive lymph nodes by HE = 0 and number of positive lymph nodes by HE > 0 subgroups. Overall survival analysis was performed in each subgroup.2.9P value, HR and 95% CI of each variable through the ‘forestplot’ package in R. We found that the EMT‐related gene signature, pathological N stage and age were the only three independent prognostic factors that could be used to predict the survival rate in the TCGA‐BLCA data set. Therefore, the three independent prognostic factors were used to build the nomogram by utilizing the ‘rms’, ‘nomogramEx’ and ‘regplot’ packages in R. Next, we estimated whether the predicted survival outcome  was close to the actual outcome with calibration curves. Nomogram‐predicted survival and the observed outcome were plotted on the x‐axis and y‐axis, respectively, and the 45° line represents the best prediction. Furthermore, 3‐year decision curve analysis and 5‐year decision curve analysis (DCA), which can assess and compare prediction models that incorporate clinical consequences, were used to measure whether our established nomogram was suitable for clinical utility. The x‐axis indicates the percentage of threshold probability, and the y‐axis represents the net benefit.First, univariate and multivariate Cox regression analyses were performed to identify the proper terms to build the nomogram. A forest plot was used to show the 2.10Kaplan‐Meier survival analysis was used to assess the survival differences between different clinicopathological characteristics, between the high‐/low‐risk groups and between the MIBC/NMIBC groups in the data sets mentioned above. The ‘survival’ package in R was used to perform a two‐sided log‐rank test and univariate and multivariate Cox regression analyses.2.11P < .05. One‐way ANOVA or Student's t test was used to determine the significance of differences between the risk score and clinicopathological characteristics. The chi‐square test was applied to analyse the correlation between the EMT‐related gene signature risk level and clinicopathological parameters. The Kaplan‐Meier survival curves were built to analyse survival differences between the high‐risk and low‐risk groups. Univariate and multivariate Cox proportional hazard models were generated to estimate the hazard ratios of prognostic factors and to select independent prognostic factors. The ROC curves, calibration curves and DCA were compared to determine the predictive accuracy of the prognostic models.All statistical analyses were performed with R software 3.5.3. Statistical significance was set at a probability value of 33.1http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32548, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32894 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48075. The results demonstrated that the EMT signalling pathway was significantly activated during the process of the subtype transition from NMIBC to MIBC   Figure . Accordi) Figure .3.3http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48075) for OS validation and 1 internal set (TCGA‐BLCA) and 3 external data sets  for DFS validation. We found significantly higher survival rates in the low‐risk group compared with the high‐risk group in each data set. In the OS validation sets, we observed significant prognostic values in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507 (P = .0016) and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48075 (P = .015), with 1‐, 3‐ and 5‐year prognostic accuracies of 0.664, 0.679 and 0.649 and 0.703, 0.662 and 0.684, respectively  indicated the same trend in survival, with great significance , and the AUC was 0.659, 0.716, 0.784 and 0.789 at 1 year; 0.589, 0.745, 0.712 and 0.736 at 3 years; and 0.566, 0.745, 0.680 and 0.685 at 5 years, respectively  is displayed in Table 3.5As the EMT‐related gene signature was correlated with the above clinicopathological characteristics, we wanted to determine whether the prognostic value of our model was applicable to other clinical factors. All patients were divided into the indicated subgroup. Then, stratification analysis was performed according to age, gender, histological subtype, pathological T stage pathological N stage, pathological tumour stage, lymphovascular invasion status and number of positive lymphonodes by HE. The EMT‐related gene signature was quite useful in all subgroups, with clinically and statistically significant prognostic value Figure .3.6Then, we performed univariate and multivariate Cox regression analyses to investigate whether our model was a clinically independent prognostic factor for BLCA patients. The risk scores of the EMT‐related gene signature and clinicopathological characteristics, including age, gender, histological subtype, grade, pathological T stage, pathological N stage and pathological tumour stage, were used as covariates. The results revealed that the EMT‐related gene signature, pathological N stage and age were the only independent prognostic factors that could be used to predict the survival rate in BLCA patients Figure .3.7Based on the results of the univariate and multivariate Cox regression analyses, we further constructed a nomogram combining the only three independent prognostic factors, namely the EMT‐related gene signature, age and pathological N stage, to provide a quantitative method for clinicians to predict the probability of 3‐ and 5‐year OS in BLCA patients Figure A. Every 4BLCA is a disease with a high socio‐economic burden and high morbidity and mortality.Despite advances in the transurethral resection of bladder tumour (TURBT) or instillation therapy, approximately 30% of NMIBC patients will finally progress to MIBC. And about 50% of MIBC patients will suffer from local or systemic recurrence after radical cystectomy and even die from the disease.With the development of genome sequencing and bioinformatics, an increasing number of studies have focused on molecular biomarkers associated with standard pathological features to identify the risk stratification of patients, to guide treatment planning and ultimately to improve clinical outcome.In this study, we conducted GSVA to screen the most important signalling pathways by comparing MIBC with NMIBC. Surprisingly, the EMT signalling pathway ranked as the top pathway with a positive correlation in four independent data sets from the GEO database. Moreover, the results of GSEA showed that the EMT signalling pathway was positively correlated with MIBC development. All of these results indicate that the EMT signalling pathway might play a key role in the subtype transition from NMIBC to MIBC. Then, we constructed an EMT‐related gene signature associated with BLCA prognosis using the LASSO Cox regression model by utilizing the TCGA data set. Furthermore, we combined the EMT prognostic signature with other clinicopathological prognostic variables to build a predictive nomogram model, which could offer an effective way for treatment planning and improving the overall outcome of BLCA patients.Recent studies have revealed the involvement of EMT in the pathogenesis of cancers, including BLCA.A novel LASSO Cox regression model was constructed to build a prognostic EMT‐related gene signature for BLCA specimens in the TCGA database as a training set. Then, the BLCA patients were equally divided into high‐risk and low‐risk groups according to the risk score in each sample. The results showed that the risk score could successfully predict the survival of BLCA patients, in which the high‐risk group had a significantly worse OS than the low‐risk group. The ROC curves also indicated that the EMT‐related gene signature had favourable prognostic power. All of these findings were validated in several external and internal data sets. Moreover, we found that our prognostic signature risk score and risk level were positively correlated with clinicopathological data, including age, histological subtype, grade, pathological T stage, pathological N stage, pathological tumour stage, lymphovascular invasion status and number of positive lymphonodes by HE, and negatively correlated with the survival rate of BLCA patients. Furthermore, we conducted a subgroup analysis of the EMT‐related gene signature on OS by utilizing clinicopathological factors. As expected, the prediction ability of the EMT‐related gene signature was effective in all subgroups. All of these results indicate that the EMT‐related gene signature plays a pro‐oncogenic role in BLCA progression and an inducer role in subtype transition, which is consistent with the function of the EMT signalling pathway.The high recurrence rate of BLCA makes it very different from other types of cancer. NMIBC will become invasive and ultimately develop into MIBC, which recurs frequently. However, MIBC patients who receive radical cystectomy or chemotherapy sometimes will experience recurrence, resulting in an extremely shortened predicted survival time. All of these factors stress the importance of determining whether the EMT‐related gene signature is also correlated with the recurrence of BLCA. Therefore, we used the established EMT‐related gene signature to determine the disease‐free survival (DFS) rate of BLCA patients. Based on the results of four independent data sets, we found that the EMT‐related gene signature was also applicable to DFS and could successfully distinguish BLCA patients with significantly different survival times and had high predictive power. Then, we integrated the clinicopathological factors with the EMT‐related gene signature to perform univariate and multivariate Cox regression analyses. The results demonstrated that the EMT‐related gene signature, pathological N stage and age were the only three independent prognostic factors to predict the survival rate in BLCA patients.BLCA is more common in men than in women, with respective incidence and mortality rates of 9.6 and 3.2 per 100 000 in men, which are approximately 4 times higher than those in women globally.In conclusion, we identified a novel EMT‐related gene signature associated with the prognosis of BLCA patients based on the results of EMT signalling pathway enrichment. The EMT‐related gene signature has tumour‐promoting effects and is a negative independent prognostic factor in BLCA. Furthermore, by integrating the EMT‐related gene signature with age and pathological N stage, we constructed a predictive model that is available to effectively predict the outcome of BLCA patients by appropriately stratifying the risk score.The authors declare that they have no competing interests.RC and LY made substantial contributions to conception and design of the research. RC, LY and BM carried out data collection and analysis. RC, LY and YT wrote the paper. RC, LY, BM, GW, WQ and TY edited the manuscript and provided critical comments. All authors read and approved the final manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


HFpEF). We hypothesized that this could result in pericardial constraint and diastolic ventricular interaction in some patients during exercise.Exercise‐induced pulmonary hypertension is common in heart failure with preserved ejection fraction . Cardiac volumes, and normalized radius of curvature (NRC) of the interventricular septum at end‐diastole and end‐systole, were measured at rest and peak‐exercise, and compared between the groups. The septum was circular at rest in all 3 groups at end‐diastole. At peak‐exercise, end‐systolic NRC increased to 1.47±0.05 (P<0.001) in HFpEF patients, confirming development of pulmonary hypertension. End‐diastolic NRC also increased to 1.54±0.07 (P<0.001) in HFpEF patients, indicating septal flattening, and this correlated significantly with end‐systolic NRC . In hypertensive controls and healthy controls, peak‐exercise end‐systolic NRC increased, but this was significantly less than observed in HFpEF patients . There were also small, non‐significant increases in end‐diastolic NRC in both groups . In HFpEF patients, peak‐exercise end‐diastolic NRC also negatively correlated  with the change in left ventricular end‐diastolic volume with exercise , and a trend was noted towards a negative correlation with change in stroke volume .Contrast stress echocardiography was performed in 30 HFpEF, and this restriction to left ventricular filling by the right ventricle exacerbates the pre‐existing impaired Frank‐Starling response in these patients.Exercise pulmonary hypertension causes substantial diastolic ventricular interaction on exercise in some patients with  This study demonstrates that diastolic ventricular interaction develops with exercise in a non‐obese sub‐phenotype of patients with heart failure with preserved ejection fraction.Exercise testing is essential in patients with heart failure with preserved ejection fraction to identify exercise induced pulmonary hypertension and screen for diastolic ventricular interaction.Diastolic ventricular interaction represents a novel therapeutic target for heart failure with preserved ejection fraction patients, for whom effective therapies are currently lacking.Heart failure with preserved ejection fraction (HFpEF) accounts for approximately half of all patients with heart failure.While there are typically subtle abnormalities of contractile function in HFpEF despite a normal left ventricular ejection fraction,In experimental models of acute pulmonary hypertension (PHT), the associated increase in right ventricular diastolic volume stretches the pericardium, increasing pericardial pressure. Diastolic filling of the left ventricle is then constrained by the pericardium , and by the right ventricle via the interventricular septum . In an experimental model, the position and shape of the interventricular septum at end‐diastole was shown to be highly correlated with the pressure difference between the 2 ventricles at end‐diastole, which reflects the true LV “preload”.We hypothesized that, similar to these acute experimental models of RV pressure overload, the acute increase in PAP occurring during exercise in patients with HFpEF would also lead to the development of DVI, further aggravating the abnormal diastolic filling in these patients and exacerbating the impairment of the Frank‐Starling mechanism.2, <85% of predicted normal), and a pattern of gas exchange indicating a cardiac basis for the exercise limitation .2 for age and sex were taken from a statement on exercise standards from the writing group of the American Heart Association.The data that support the findings of this study are available from the corresponding author upon reasonable request. Thirty consecutive patients with clinically stable HFpEF were recruited from a community‐based echocardiography study to investigate the incidence of HFpEF in people in the UK aged >60 years.2 >90% predicted for age and sex) and normal resting echocardiograms and ECGs. Patients fasted for at least 4 hours before the exercise tests and avoided caffeine for 24 hours before the study visits. Medications were taken as usual. The study was approved by the North of Scotland National Health Service (NHS) Research Ethics Committee, Aberdeen, UK. All procedures were performed in accordance with the Declaration of Helsinki and followed written informed consent.Age and sex matched HT controls were recruited from hypertension clinics at the Aberdeen Royal Infirmary, Aberdeen, UK, and the Norfolk and Norwich University Hospitals, Norwich, UK. Healthy volunteers were recruited from the community study and matched for age and sex. All controls underwent cardiopulmonary exercise testing and had normal exercise capacity  was undertaken while patients exercised using an electronically‐braked bicycle . Peak heart rate and workload achieved during cardiopulmonary exercise testing were used to create the exercise protocol for each subject, aiming to achieve maximum heart rate in 8 to 10 minutes. Echocardiography settings were set to a low mechanical index of <0.2. Intravenous transpulmonary echocardiographic contrast  was then given, and a resting mid‐ventricular parasternal short axis view was obtained below the mitral leaflets, just above the papillary muscle insertion points. At peak exercise, a further 1 mL Sonovue was injected, and the parasternal short axis window was recorded as above. Apical 4‐ and 2‐chamber views were also obtained at rest and peak exercise to measure LV volumes. No study participants developed significant mitral regurgitation during exercise, as assessed following lysis of microbubbles with a high mechanical index impulse.Images were exported into ImageJ/Fiji ;Using the “Septal Radius Calculator” plug‐in, LV area (A) was measured at end‐diastole by tracing the endocardial border (with the papillary muscles included);ri) was then automatically calculated from A, using the equation for the area of a circle, ri=A/π;The “idealized” radius (r); andThe endocardial borders of the septum were then traced for the left ventricle, and right ventricle between the RV insertion points, to calculate the septal radius of curvature  masked to the clinical status of the subject, and the mean of the measurements from these 2 investigators was used. The intra‐observer and inter‐observer variability of diastolic NRC was <10%. The normalized radius of curvature (NRC) of the left ventricle at end‐diastole was measured using the operator‐independent method described by Dong et alLV end‐diastolic volume (LVEDV) was measured in apical 4‐ and 2‐chamber windows at rest and at peak‐exercise, by the Simpson bi‐plane method.r/ri) with Pearson's r=0.86.While right ventricular systolic pressure (RVSP) can be measured relatively accurately at rest using the tricuspid regurgitant jet velocity plus an assumed right atrial pressure (based on collapse of the inferior vena cava during inspiration),t test, assuming equal variance if possible, otherwise unequal variances were used. To control the type‐I error rate, we used Bonferroni adjustment for the 2‐way comparisons, declaring significance if the P value was ≤0.017 . The Kruskal–Wallis test was used for non‐normally distributed data, and 2‐way comparisons were made using the Mann–Whitney U test. Categorical variables were compared between groups using Fisher exact test. The relationship between variables was assessed using scatter plots and Pearson r, or Spearman rho where the data were not normally distributed. All analyses were undertaken using Stata version 14.1/SE  and R version 3.2.3 .Values are expressed as mean±SE of the mean (SEM). Baseline characteristics and outcome measures of the 3 groups were compared using ANOVA for continuous measures, with Bartlett's test to assess equality of variance. When the test was significant, each 2‐way comparison was tested using a 2 (P<0.001). HFpEF patients also had an altered chronotropic response to exercise, and a higher percentage were on beta‐blocker and aspirin therapy. No patients were on loop diuretic therapy. There was a trend towards higher resting brain natriuretic peptide (BNP) levels in HFpEF patients, but this was not statistically significant (P=0.08). Left atrial volume index (LAVI) was not significantly different between HFpEF and hypertensive patients (P=0.27), but both were larger than Healthy controls (P<0.001). However, LV mass indexed to body surface area (LVMI) was greater in HFpEF patients compared with hypertensive (P=0.02) and Healthy controls (P<0.001).The baseline characteristics of study participants are shown in Table P=0.80). At peak exercise, NRC increased significantly in HFpEF patients only , with non‐significant increases observed in hypertensive  and Healthy controls . ΔNRC was greater in HFpEF compared to both hypertensive (P=0.002) and Healthy controls (P<0.001). Peak NRC was higher in the HFpEF patients (1.54±0.07) compared with hypertensive  and healthy controls . Although there was a trend towards a higher NRC on exercise in hypertensive versus healthy controls (P=0.05) this was not statistically significant following the pre‐specified Bonferroni's adjustment .As shown in Table ve P=0.00 and Healve P=0.00 and HealP=0.002; Table P=0.0049 and P=0.011, respectively).Resting end‐systolic NRC was higher in HFpEF patients than hypertensive controls (1.21±0.02 versus 1.16±0.02), and higher in hypertensive controls compared with healthy controls (1.16±0.02 versus 1.11±0.02), implying higher resting right ventricular systolic pressures. However, this difference was statistically significant between HFpEF and Healthy only (P=0.007) , but there was no significant correlation in healthy controls .There was a positive correlation between peak diastolic NRC and systolic NRC on exercise in HFpEF  Figure . A positP<0.001) and in hypertensive controls . However, LVEDV failed to increase appropriately during exercise in HFpEF , and indeed fell in 13 patients. The change in LVEDV was significantly different between HFpEF and healthy (P<0.001) and HFpEF and hypertensive (P=0.014) controls. In the HFpEF patient group, there was a modest negative correlation between ΔLVEDV and peak NRC  and hypertensive controls  on exercise, but failed to increase appropriately in HFpEF . Indeed, SV fell in the 13 HFpEF patients who failed to increase their LVEDV. In HFpEF patients, ΔSV trended towards a modest negative correlation with ΔNRC , however this was lost when considering the HFpEF group alone .Stroke volume (SV) was also similar at rest in all 3 groups Table . SV incrIn this study, we show that, during exercise, marked flattening of the interventricular septum occurs at end‐diastole in HFpEF patients, but not in hypertensive or normotensive controls, indicating the development of DVI. The degree of DVI was modestly inversely correlated with the increase in LVEDV on exercise. Our findings suggest that DVI is an important mechanism aggravating the pre‐existing diastolic abnormality in HFpEF, contributing to the limitation of utilization of the Frank‐Starling mechanism on exercise, and to exercise limitation.HFpEF is poorly understood, and no established therapies exist, despite its estimated economic burden of $54 billion annually worldwide.PHT is common in HFpEF, being present in >80% of patients and strongly associated with mortality in a community‐based study of 244 patients.2) HFpEF patient population.In health, pericardial pressure is little more than zero, and the end‐diastolic pressure of the thin‐walled RV is similar.In the current study, we confirmed our hypothesis that the development of PHT on exercise would lead to the development of DVI in patients with HFpEF. At rest, the end‐diastolic NRC was similar in patients and hypertensive and normotensive controls, and was close to 1, indicating that the left ventricle was almost circular in the short axis; however, on exercise it substantially increased in patients with HFpEF but not in the control groups. These observations indicate a reduction in the end‐diastolic trans‐septal pressure gradient, reducing the effective LV preload and, via the Frank‐Starling mechanism, the stroke volume. Consistent with this, LVEDV increased during exercise in normotensive and hypertensive controls, but remained unchanged in patients. Indeed, LVEDV fell in 13 HFpEF patients. The change in LVEDV during exercise exhibited a modest negative correlation with peak end‐diastolic NRC on exercise, and a trend was seen with SV, indicating contribution of the development of DVI to the loss of the Frank‐Starling mechanism on exercise. While the mean change in LVEDV on exercise was close to zero in patients, the standard deviation was wide, indicating substantial heterogeneity in response Table . It is nThese observations may have therapeutic implications. For example, agents that can reduce PAP, particularly during exercise, may be beneficial. We have shown that short‐term intravenous sodium nitrite therapy (50 μg/kg per minute for 5 minutes) improves hemodynamics by increasing stroke volume and reduces pulmonary vascular resistance without significant effects on mean arterial pressure in patients with HFrEF.The tricuspid regurgitant jet velocities were not obtained in a sufficient number of patients in our study to give estimations of RVSP. Independently of this, as discussed already, the use of tricuspid regurgitant jet velocities with exercise‐stress echocardiography to estimate RVSP is problematic, and rendered invalid because of marked swings in intrathoracic pressure which preclude estimation of RA pressure.Catecholamines, such as those released with exercise, have been shown to diminish the correlation between E/E′ and LV filling pressures.Substantial end‐systolic flattening of the septum (implying severe PHT) develops on exercise in a substantial proportion of HFpEF patients, resulting in DVI and pericardial constraint. LVEDP during exercise is increased in HFpEF because of dynamic slowing of LV active relaxation, together with increased passive LV stiffness.This work was funded by the British Heart Foundation, project grant reference PG/13/4/29811.None.


P > 0.05).The drug nitisinone  has been used for the treatment of hereditary tyrosinemia type‐1 since 1991. Nitisinone effectively blocks the metabolism of tyrosine to prevent the formation of the toxic compound succinylacetone (and precursor fumarylacetoacetate) in affected children. Monitoring of plasma drug levels and urine succinylacetone can be used to assess compliance and adequate dose of drug. We present retrospective data from patient monitoring for over 10 years that provide validation of a target therapeutic range for nitisinone of 40 to 60 μmol/L. The target nitisinone range is justified as valid based on reduction of succinylacetone excretion. There was no statistical significance in succinylacetone excretion in mmol/mol creatinine above a level of 40 μmol/L plasma NTBC ( FAformic acidFAHfumarylacetoacetate hydrolaseFDAFood and Drug AdministrationGCMSgas chromatography/mass spectrometryHT‐1hereditary tyrosinemia type 1ISinternal standardLC‐MS/MSliquid chromatography‐tandem mass spectrometryNTBC2‐[2‐nitro‐4‐trifluoromethylbenzoyl]‐cyclohexane‐1,3‐dioneSUACsuccinylacetoneTDMtherapeutic drug monitoring1The drug nitisinone (2‐(2‐nitro‐4‐trifluoromethylbenzoyl)‐cyclohexane‐1,3‐dione; NTBC) was initially approved by the FDA as Orfadin  in January 2002 for use in Hereditary Tyrosinemia type 1 (HT‐1) . Prior to FDA approval, Orfadin was listed as an orphan drug in 1995 by the Office for Orphan Product Development. NTBC was originally considered for use as an herbicide due to its inhibition of 4‐hydroxyphenylpyruvate dioxygenase.Tyrosinemia type 1 is an autosomal recessive condition caused by a deficiency of fumarylacetoacetate hydrolase (FAH). Symptoms typically develop in early infancy (<6 months of age) or before 2 years of life.In the United States, most states include detection of plasma succinylacetone as target for HT‐1 in their newborn screening algorithms. Treatment with NTBC is most effective if patients are diagnosed early, making this an ideal disease for newborn screening. When children are detected by newborn screening and treatment (both low protein diet and NTBC) initiated early, patients show excellent clinical outcome without liver or renal disease.The blood concentration of NTBC generally recommended is 40 to 60 μmol/L.22.113C5‐succinylacetone), obtained from Cambridge Isotope Laboratory was included in the extraction, and used for quantitation. Target ion for quantitation was 212 m/z for succinylacetone, and 217 m/z for the internal standard. A qualifier ion was used for peak identification confirmation; 227 m/z for succinylacetone and 232 for internal standard. The assay has an analytical measurement range of 0.2 to 40 μmol/L, with dilution above 40 μmol/L to 400 μmol/L.Succinylacetone was measured by selected ion monitoring gas chromatography/mass spectrometry (GC/MS) in splitless mode. One milliliter of urine was acidified, extracted with ethylacetate and ether, dried down, and derivatized with BSTFA.2.2NTBC was measured by liquid chromatography/tandem mass spectrometry (LC‐MS/MS).3Data were segregated by NTBC level as follows: <20, 20‐30, 30‐40, 40‐50, 50‐60, and > 60 μmol/L. In reviewing all the data, mean succinylacetone excretion was 0.61 μmol/L (SD 1.2) and 0.15 mmol/mol creatinine (SD 0.32). Mean NTBC was 47.0 μmol/L (SD 16.7). Average succinylacetone excretion decreased at increasing NTBC plasma levels as follows:P > 0.05; paired t test for a comparison of two means, Graph Pad, 2018). There was no statistical significance in excretion in mmol/mol creatinine above a level of 40 μmol/L plasma NTBC (P > 0.05) , twice daily. Dose is titrated based on biochemical and or clinical response (Orfadin prescribing information). Although low in toxicity, the most common adverse reactions are elevated tyrosine (>10%), thrombocytopenia, leukopenia, conjunctivitis, corneal opacity, keratitis, photophobia, eye pain, cataracts, granulocytopenia, rash, and alopecia  (Orfadin prescribing information). The half‐life is 54 hours. Although succinylacetone can be measured as a marker for biochemical response to adequate NTBC dose, NTBC can also be measured for TDM to ensure compliance and adequate dose, or to assess toxicity if suspected. We have no correlating NTBC dosage or time of blood draw information, dietary information, or blood tyrosine levels in this data set. A more complete prospective study would include this information. The intention of this publication is only to compare urine succinylacetone excretion with concurrent NTBC blood levels, and provide some support for a practice already in place. Laboratory instructions to providers, however, recommend blood collection for NTBC levels 30 minutes prior to the next dose. This is standard for monitoring of trough drug levels. We assume most of the patient drug levels are measured at steady state.Our laboratory has routinely monitored both urine succinylacetone excretion and plasma NTBC levels in patients on treatment for HT‐1. Treatment should lead to normalized porphyrin metabolism, minimal excretion of succinylacetone, and undetectable plasma succinylacetone, although it may take up to 3 months before the level of plasma succinylacetone is normalized after the start of NTBC treatment. An argument can be made for measurement of plasma succinylacetone as a better measure for monitoring endogenous succinylacetone. It is true that measurement in plasma is likely to be more reproducible, as plasma measurement avoids variation in extraction due to urine concentration differences, and the need to relate excretion to creatinine concentration. In this retrospective data set, only urine succinylacetone and plasma NTBC were requested and measured. Our conclusions correlate well, however, with those of Kienstra et al.,Since 99% of treated patients monitored at our institution who had NTBC levels over 40 μmol/L also had succinylacetone excretion <1.5 μmol/L and < 0.25 mmol/mole creatinine, and there was no statistical significance in the excretion level in patients with NTBC above 40 μmol/L, we feel the target for blood levels of 40 to 60 μmol/LThe authors have no conflict of interest.Rhona Jack contributed to conception and design, data acquisition, statistical analysis, interpretation of data, writing, editing, and guarantor.C. Ronald Scott contributed to conception, interpretation of data, critical editing, and review.


BG90‐2, IR64, Sahel 108, WAT311‐WAS‐B‐B‐23‐7‐1, WAT339‐TGR‐5‐2, and WITA 10) had high head rice yield and low chalkiness. Of the varieties in this group, Sahel 108 had the highest paddy yield in three of the four trials. IR64 and Afrihikari had intermediate and low amylose content, respectively, with the rest being high‐amylose varieties. Another group of varieties consisting of B6144F‐MR‐6‐0‐0, C74, IR31851‐96‐2‐3‐2‐1, ITA222, Jaya, Sahel 305, WITA 1, and WITA 2 had high paddy yield but poor head rice yield and chalkiness. The use of materials from these two groups of varieties could accelerate breeding for high yielding rice varieties with better grain quality for local production in West Africa.Rice breeding in West Africa has been largely skewed toward yield enhancement and stress tolerance. This has led to the variable grain quality of locally produced rice in the region. This study sought to assess variations in the agronomic and grain quality traits of some rice varieties grown in this region, with a view to identifying sources of high grain yield and quality that could serve as potential donors in their breeding programs. Forty‐five varieties were grown under irrigated conditions in Benin and Senegal with two trials in each country. There were wide variations in agronomic and grain quality traits among the varieties across the trials. Cluster analysis using paddy yield, head rice yield, and chalkiness revealed that 68% of the total variation could be explained by five varietal groupings. One group comprising seven varieties (Afrihikari,  In West Africa, the increasing demand for rice surpasses local production. Thus, many countries rely on imports to meet consumer demands. To meet the production deficit, rice breeding programs in this region have focused mainly on yield enhancement and adaptation to the harsh production environments than on improving grain quality  assess varietal difference in agronomic traits including rice paddy yield and grain quality characteristics; (2) quantify the effects of environment and genotype by environment interaction on them; and (3) identify varieties that combine high paddy yield, high head rice yield, and low chalkiness that could be exploited in breeding programs.22.1The following 45 rice varieties obtained from the Genetic Resources Unit of the Africa Rice Center (AfricaRice) were evaluated in this study: BG90‐2, C74, IR1529‐680‐3, IR31785‐58‐1‐2‐3‐3, IR31851‐96‐2‐3‐2‐1, IR64, Jaya, Kogoni 91‐1, Sahel 108, Sahel 177, Sahel 201, Sahel 217, Sahel 222, Sahel 305, Sahel 328, Sahel 329, and WAS161‐B‐9‐3; Afrihikari, Bouake 189, FKR19 (Tox728‐1), FKR54 (WABIR12979), NERICA‐L 19, WAT100‐TGR‐2‐4, WAT307‐WAS‐B‐24‐8‐4‐4‐2, WAT311‐WAS‐B‐B‐23‐7‐1, WAT317‐WAS‐B‐B‐55‐4‐3, WAT339‐TGR‐5‐2, WAT343‐TGR‐1‐1, WAT50‐TGR‐4‐1, WITA 1, WITA 2, WITA 3, WITA 4, WITA 6, WITA 7, WITA 10 and WITA 12, three mangrove varieties—WAR42‐82‐2‐3‐1, WAR77‐3‐2‐2, and WAR87‐10‐2‐2‐9; and B6144F‐MR‐6‐0‐0, ITA123, ITA222, WAB337‐B‐B‐7‐H4, and WAB506‐125‐3.2.22 day) for most of the year, and higher temperature amplitudes. In comparison, the Benin site has higher annual rainfall and humidity, and lower solar radiation and temperature amplitudes  in both 2011 and 2012 at the AfricaRice experimental station in Cotonou . In Senegal, the first trial was established in February 2012 (dry season) and the second trial in July 2012 (wet season) at the AfricaRice experimental station, Ndiaye . Cotonou is located in the subhumid zone, whereas Ndiaye is located in the arid zone  at transplanting time and 40 kg N/ha as urea at 4 weeks after transplanting. Pests and diseases were controlled as and when required. Weeds were manually removed, when required.The number of days to heading was recorded in each plot. Plant height  was measured at maturity on five randomly selected hills. Twelve plants were then randomly chosen from each plot and harvested to determine the number of panicles, number of grains per panicle, and paddy grain yield. Paddy yield was adjusted to 14% moisture content.2.3After harvesting 12 hills, the remaining plants less one border row was used for grain quality evaluation. Harvested paddy was dried in the sun to a moisture content of 18% and then dried in the shade to between 12% and 14% moisture content. The dried samples were kept in paper bags and equilibrated at laboratory temperature for 1 month prior to grain quality evaluation.2.3.1Rice samples were dehusked in a THU‐34A Satake Testing Rice Husker . The brown rice obtained was polished in a Ricepal 32  rice polisher. Milled rice was separated into whole and broken grains using a Satake Test Rice Grader . Head rice yield was calculated using the following equations: 2.3.2Chalkiness and grain dimensions were determined using S21 Rice Statistic Analyzer  as described by Graham‐Acquaah, Manful, Ndindeng, and Tchatcha  with sli2.3.3Apparent amylose content was measured using the standard iodine colorimetric method ISO 6647‐2‐2011. Absorbance of the solution was measured using an AutoAnalyzer 3  at 600 nm, and apparent amylose content was quantified from a standard curve generated from absorbance values of four well‐known standard rice varieties .2.3.4The pasting properties of rice flour samples were measured using a Rapid Visco‐Analyzer (RVA) model super4  and Thermocline for Windows (TCW3) software. The general pasting method 162 ICC,  for flou2.4Analysis of variance using linear mixed models regression (REML) analysis was run in “R” version 3.2.2  for all the agronomic and grain quality traits except for the interaction on apparent amylose content and grain shape, given by the length‐to‐width ratio  ranged from 364 to 981 (Benin 2011), 329 to 701 (Benin 2012), 57 to 1,199 , and 398 to 1,040 . Similarly, the number of days to heading ranged from 88 to 105 (Benin 2011), 74 to 101 (Benin 2012), 101 to 233 , and 76 to 112 . The largest ranges in yield and days to heading were observed in the dry season in Senegal because some of the varieties were not adapted to dry season conditions, especially the longer day length in that season. There were large varietal differences in head rice yield than total milling yield. Head rice yields (%) ranged from 8 to 62 (Benin 2011), 6 to 51 (Benin 2012), 19 to 66 , and 15 to 60 . The ranges for grain chalkiness, grain dimensions , apparent amylose content, peak viscosity, and setback viscosity were similar across the four trials. The apparent amylose contents of the varieties in this study covered the range of low‐ to high‐amylose content. None of the varieties tested was waxy or had very low amylose content (<10% AAC).Paddy yield  across the four trials. Paddy yield and number of panicles had positive correlations (r = .48–.77). None of the agronomic traits was correlated consistently with any of the grain quality traits. Among the grain quality traits, there were positive correlations between brown rice yield and total milling yield, and between total milling yield and head rice yield. Apparent amylose content was negatively correlated with head rice yield, grain width, and breakdown viscosity, whereas it was positively correlated with length‐to‐width ratio and setback viscosity. Peak viscosity had a positive correlation with breakdown viscosity and a negative correlation with setback viscosity.Pearson's correlation coefficients were computed to ascertain pairwise relationships among the traits for each trial. Table 3.3Ward's hierarchical cluster analyses on paddy yield, head rice yield, and chalkiness across the four trials identified five variety clusters (referred to as Clusters 1–5) that could explain 68% of total variation Figure . ClusterFurthermore, of the 45 varieties, paddy yield of Sahel 108 ranked 13th (Benin 2011), 11th (Benin 2012), 5th , and 5th . Sahel 108 also had the most stable head rice yield (42%–53%) among the varieties in this cluster, and, on average over the four trials, the lowest grain chalkiness and the 4th most stable chalkiness level. Afrihikari gave the highest mean head rice yield within this cluster and its head rice yield ranked 1st (Benin 2011), 9th (Benin 2012), 2nd , and 3rd  of the 45 varieties. All the varieties in this cluster, except Afrihikari  and IR64 , had high‐amylose contents (AAC > 25%).Cluster 2 comprised eight varieties—B6144F‐MR‐6‐0‐0, C74, IR31851‐96‐2‐3‐2‐1, ITA222, Jaya, Sahel 305, WITA 1, and WITA 2  of varieties were influenced to a lesser extent by environment. This suggests that data from multilocational trials might be less important for evaluating these traits, and the selection of breeding lines using these traits might be made based on a single trial as their heritability was also high. Between amylose content and RVA paste properties, amylose content was more stable to environment effects. As apparent amylose content is associated with pasting properties of rice, similar variability could have been expected. However, diversity in pasting properties was wider confirming differences in pasting properties of varieties with similar amylose content  provide an option for crossing with higher yielding varieties to improve their grain qualities. Varieties such as Sahel 108, IR64, and Jaya could serve as donors for improving both paddy yield and grain quality, and as reference checks in multilocation trials to identify new breeding lines that combine these traits.5ryza glaberrima, within the region is needed to reveal the diversity that could be exploited in regional breeding programs. Also, given the nature of the effect of the environment on head rice yield and chalkiness, these traits need to be carefully evaluated during varietal screening together with climatic data particularly where climatic conditions and crop durations vary during the rice growing season.Current market demands in West Africa require target outputs of rice breeding programs to be aligned toward improved grain quality traits together with higher paddy yield. This study reveals that there exist wide variations in the agronomic and grain quality traits of rice varieties available in West Africa. The apparent diversity in these traits offers the potential to develop new varieties with high paddy yield and grain quality traits to meet consumer requirements. Sahel 108, IR64, and Jaya can be utilized to breed for high yield combined with good grain quality, and serve as references in multilocational trials. Further systematic screening of available rice varieties, including O


Allergic immune‐mediated hypersensitivity reactions are known potential complications of enzyme replacement therapy. Sebelipase alfa, recombinant lysosomal acid lipase (LAL), is a potentially life‐altering treatment for patients with LAL deficiency. There is very little information on the diagnosis and management of immediate hypersensitivity reactions to this drug. Here we present three unique cases of hypersensitivity reactions to sebelipase alfa, spanning a broad age spectrum from infancy to adulthood, each managed with successful rapid desensitization. Infusion reactions and allergic hypersensitivity reactions can have overlapping features including wheezing, dyspnea, tachycardia, hypotension, and flushing.2A 47‐year‐old Caucasian male with LAL deficiency and cerebral palsy tolerated sebelipase alfa 1 mg/kg every other week without reaction until week 12, when he developed diffuse urticaria, conjunctival injection, rhinorrhea, tachycardia, and tachypnea 90 minutes into infusion. The infusion was stopped and he was given dexchlorpheniramine 5 mg intravenous (IV) and hydrocortisone 100 mg IV with resolution of symptoms within an hour. Two weeks later, after pretreatment with dexchlorpheniramine 5 mg IV and paracetamol 1000 mg IV 15 minutes prior, he again developed diffuse rash, conjunctival injection, rhinorrhea, and tachypnea 88 minutes into the infusion. The same rescue treatment was administered with similar results as the prior infusion. Serum tryptase was 4.7 ng/mL (reference <13.0 ng/mL). Skin prick testing (SPT) and intradermal testing (IDT) to sebelipase alfa were performed per study protocol, with SPT at concentrations of 1:1000 (0.002 mg/mL) and 1:100 (0.02 mg/mL) and IDT at 1:1000. SPT was negative and IDT was positive with development of a 6‐mm wheal. Drug‐specific IgG antibodies were not detectable. Basophil activation test performed by a central lab was positive. Desensitization to sebelipase alfa was recommended based on clinical anaphylaxis and positive skin testing.Five attempts were made to desensitize the patient to the full dose of 1 mg/kg of sebelipase alfa using a protocol ranging from 9 to 15 steps with initial concentrations as low as 0.001% of the target dose. Before each desensitization, the patient received dexchlorpheniramine 5 mg IV 1 hour prior; the first two attempts also included methylprednisolone 60 mg IV. Within 3‐6 hours of starting each desensitization, the patient developed a diffuse pruritic rash responsive to dexchlorpheniramine 5 mg IV and methylprednisolone 40‐60 mg IV. For the first three desensitizations, the desensitization protocol was then completed without recurrence of symptoms. In the fourth attempt, the patient developed a diffuse pruritic rash and conjunctival injection 70 minutes after initial resolution and the infusion was stopped and methylprednisolone (60 mg IV) was administered. Symptoms resolved within an hour. In the fifth attempt, he had multiple recurrences of diffuse pruritic rash precluding completion, despite dexchlorpheniramine doses. His target dose of sebelipase alfa was reduced to 0.35 mg/kg every other week, which he tolerated by desensitization. Over the following weeks, his desensitization protocol was shortened and simplified without reaction, without dose escalation. The initial tolerated protocol and the final abbreviated protocol are shown  intramuscular (IM) and hydrocortisone 25 mg IM with resolution of symptoms. For the sixth infusion, she received premedication with chlorphenamine 1.25 mg IM and hydrocortisone 25 mg IM, and the infusion rate was slowed to start at 0.5 mL/h and increased 0.5 mL/h every 30 minutes. After administration of 6.1 mL, she developed facial flushing, tachycardia, hypoxia, respiratory distress, and stridor. She received epinephrine IM (150 μg of a 1:1000 solution), nebulized epinephrine (1 mL of a 1:10000 solution), hydrocortisone 25 mg IM, and chlorphenamine 1.25 mg IM with resolution of symptoms. SPT 2 weeks later was negative at 1:1000 and 1:100, and IDT was not done. Antidrug antibodies were detected at a titer of 1:96 after the fifth infusion, previously negative. She additionally tested positive for neutralizing antibodies to sebelipase alfa and cell uptake inhibition at titer of 1:500. Preceding baseline serum tryptase levels were within normal limits. Based on the clinical diagnosis of anaphylaxis, desensitization was recommended.She tolerated desensitization with an 8‐step protocol with 3‐hour intervals, to a target dose of 0.35 mg/kg, without premedication Table . The tar4A 13‐year old Caucasian male with LAL deficiency started on sebelipase alfa at a dose of 1 mg/kg. He developed a pruritic truncal rash 5‐7.5 hours after completion of his first 2‐hour infusion, which was done without pretreatment. The rash resolved with diphenhydramine. He received prednisone 25 mg per os (PO) and cetirizine 10 mg PO premedication for his second infusion, but 8.5 hours post‐infusion he developed oropharyngeal angioedema, dyspnea, difficulty speaking, and a diffuse pruritic rash. Symptoms resolved within an hour of treating with diphenhydramine 25 mg PO. Tryptase was not drawn. SPT and IDT to sebelipase alfa were performed, with SPT at 1:1000 and 1:100 and IDT at 1:1000, 1:100, and 1:10 (0.2 mg/mL). All were negative at the standard reading time of 15 minutes after placement. He then developed a reaction several hours later at the testing site. He had no detectable antidrug antibodies. As his reactions and skin testing conversion occurred several hours after leaving the hospital, he did not have a clinician‐observed reaction, but he and his parents were known to be reliable historians. His history of late‐onset reaction with features consistent with anaphylaxis, worsening upon re‐exposure despite premedication, and possible delayed positive skin testing suggested an immunologically mediated hypersensitivity, so desensitization was recommended.Initial desensitization was done without premedication to a goal dose of 0.35 mg/kg, with a 10‐step protocol delivered at 2 hours per step , a carbohydrate moiety.The delay in skin test results in case 3 without an immediate phase response, in conjunction with the delayed anaphylactic clinical reaction, could be consistent with immune activation by a metabolite of the drug or presentation of the drug only after it is taken up into the lysosome. There are multiple mechanisms for anaphylaxis, the predominant being IgE‐mediated and direct mast cell activation, but IgG‐ and complement‐mediated mechanisms have also been described in animals.The biological mechanism behind desensitization remains unknown, and new desensitization protocols are developed with careful consideration to what has worked historically as well as the novel aspects of the desired drug and the nature of the patient's reaction.We believe this is the first reported case series of successful rapid desensitization to sebelipase alfa. In this case series, desensitization was a successful treatment option for patients with both immediate and delayed‐onset reactions suggestive of anaphylaxis and allowed these patients to continue treatment with ERT.This article does not contain any studies with animal subjects performed by any of the authors.All authors contributed to the planning, conduct, and reporting of the work described in the article. M.F.H. and A.Y.L. accept full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish.M.F.H., A.Y.L., and A.J.A. declare that they have no conflict of interest. G.M.E. received funding for the conduct of clinical studies from Alexion Pharmaceuticals, Inc. S.V. has been a consultant for Alexion Pharmaceuticals, Inc., received honoraria and travel grants from Alexion Pharmaceuticals, Inc. N.F.A. has been a consultant for Alexion Pharmaceuticals, Inc.For all studies, the protocol, amendments, and subject informed consent were reviewed and approved by an institutional review board (IRB) or independent ethics committee (IEC) prior to initiation of the study. The studies were conducted according Good Clinical Practice (GCP) and International Conference on Harmonisation (ICH) guidelines, applicable government regulations, and Institutional research policies and procedures.Written informed consent was obtained for all studies.6


Circular RNAs (circRNAs) participate in gene regulation and malignant tumor progression, including uterine cervical cancer (CC). In this study, the expression profile of circRNAs in CC was detected using circRNA microarrays. Then, we selected hsa_circ_0000745 for further examination from the significantly dysregulated circRNAs. Proliferation assays, Transwell assays, quantitative reverse transcription polymerase chain reaction, western blot analysis and tumorigenesis tests in vivo were used to validate the role of hsa_circ_0000745 in CC. hsa_circ_0000745 was upregulated in CC, and its level positively correlated with the level of its linear messenger RNA isoform. Patients with poorly differentiated tumors or vascular/lymphatic invasion presented higher expression of hsa_circ_0000745. The role of hsa_circ_0000745 was illuminated by knocking down hsa_circ_0000745 in CC cells, and the results revealed that reducing hsa_circ_0000745 inhibited cell proliferation, migration, and invasion in CC by upregulating E‐cadherin (E‐cad) expression. In summary, as a tumor promoter in CC, hsa_circ_0000745 enhances the cell's ability to proliferate, migrate, and invade by reducing the expression of E‐cad. hsa_circ_0000745 is a candidate target for the treatment of CC in the clinic. Hsa_circ_0000745 is upregulated and functions as a tumor promoter in cervical cancer. Hsa_circ_0000745 enhances the cell's ability to proliferate, migrate, and invade by reducing the expression of E‐cadherin in cervical cancer. Functionally, downregulation of circ‐0745 obviously suppressed the proliferation, migration, and invasion of CC cells. According to our findings, circ‐0745 promoted CC cell proliferation and metastasis; therefore, circ‐0745 represents a potential prognostic and therapeutic marker for CC patients.In this study, a circRNA microarray analysis was conducted to detect the aberrantly expressed circRNAs in CC tissues. hsa_circ_0000745 (hereafter referred to as circ‐0745) was selected for in‐depth study among the dysregulated circRNAs because of its significantly abnormal expression according to the microarray result. circ‐0745 is transcribed from the sperm antigen with calponin homology and coiled‐coil domains 1  criteria.2.2SiHa and CaSki cells were from the gynecological laboratory at Qilu Hospital, China. SiHa and CaSki cells were cultured in α‐minimum essential medium  and Roswell Park Memorial Institute 1640 (Gibco‐BRL), adding 10% fetal bovine serum (Gibco‐BRL), respectively.2.3All samples were ground into powder and RNAs were extracted with TRIzol . The purity and quantity of the RNAs in the specimens were evaluated using a NanoDrop ND‐1000 .t tests. Significantly differentially expressed circRNAs were defined as circRNAs with a fold change >2.0 and a p value <.05. The clinicopathological data from the patients are shown in Table We selected five pairs of SCC tissues and paracancerous tissues from patients. The circRNA microarray  was conducted following the manufacturer's protocol. The detected circRNAs in two groups were analyzed by the false discovery rate and paired 2.4SPECC1 messenger RNA (mRNA) using qRT‐PCR analysis. SuperScript III RT (Invitrogen) was used to synthesize complementary DNA from 3 µg of total RNA. The PCR mixture contained 2 µl of the complementary DNA templates, a 1 × final concentration of SYBR Green , and the specific primers. The sequences of the primers synthesized by Biosune  are shown in Table SPECC1 mRNA were calculated with 2−ΔΔCt method.RNAs from 59 paired samples were utilized to measure the expression of circ‐0745 and the linear 2.5Three small interfering RNAs (siRNAs) and a negative siRNA control (si‐NC) were synthesized . The siRNAs targeted the junction site of circ‐0745 and the sequences of siRNAs are shown in Table 2.6After transfection with siRNAs, cells were seeded and viability was measured after culture for 0, 24, 48, and 72 hr by adding Cell Counting Kit‐8 reagents  and incubating at 37°C for 2 hr. All tests were conducted at least three times. The absorbance of the cells at 450 nm was detected using a Model 680 Microplate Reader .The transfected cells were collected and labeled with Annexin V‐FITC  and propidium iodide (Sigma). The respective fluorescence intensities were detected on a Beckman Gallios flow cytometer .2.74 cells were placed into chambers of Transwell inserts without basement membrane coating; for the invasion test, 5 × 104 cells were seeded in chambers of Transwell inserts with a basement membrane coating. After 24 hr, nonmigratory or noninvasive cells were wiped and the cells migrating through the membrane were counted under a microscope .Transwell chambers (Corning) without and with a basement membrane coating (Corning) were used to detect the mobility of transfected CC cells, respectively. For migration test, 2.5 × 102.8The sequence of siRNA‐2 was inserted a lentiviral vector for the stable knocked down of circ‐0745 (named sh‐circ‐0000745). sh‐circ‐0000745 and an empty lentiviral vector as nonsense control  were constructed containing the green fluorescent protein gene and a puromycin resistance gene. CaSki cells were transfected and selected with puromycin  to obtain stable cell clones.7 stably transfected CaSki cells were subcutaneously injected into the backs of female BALB/c mice (5 weeks old). The tumors were monitored weekly. The mice were killed after 4 weeks, and tumors were excised and assessed.All animal care and experimental procedures were conducted according to the standards of the National Institutes of Health and approved by the Animal Protection and Use Committee of Shandong University. First, 102.9After transfected for 48 hr, CaSki and SiHa cells were lysed with radioimmunoprecipitation assay buffer (Sigma). Proteins were extracted and electrophoresed on 10% sodium dodecyl sulfate‐polyacrylamide gels, then transferred to nitrocellulose filter membranes. The membranes were incubated overnight with a primary E‐cadherin antibody  and glyceraldehyde 3‐phosphate dehydrogenase (GAPDH) antibody . Then a horseradish peroxidase‐conjugated secondary antibody  was used. Protein bands were visualized using a FluroChem E system  and the signals were quantified. GAPDH was measured as a loading control.2.10SD. Comparisons between two groups were performed using Student's t test. Correlation analysis was performed with Pearson's analysis. Differences were considered significant at p < .05. All statistical analyses were performed with SPSS 18.0.Data are presented as the means ± 33.1Overall, 3,008 human circRNAs were detected in SCC tissue and normal cervical tissue cells. One hundred seventy‐eight circRNAs exhibited abnormal expression in SCC samples (fold change > 2.0), indicating their dysregulation. Volcano plot filtering showed the expression patterns of circRNA among the samples Figure a.Further analysis found that there were 77 upregulated and 101 downregulated circRNAs in SCC tissues compared with the levels in the paired control group. Classification of the 77 upregulated circRNAs revealed 68 exonic, 3 intronic, 1 antisense, and 5 intragenic circRNAs .In SiHa and CaSki cells, specifically designed siRNAs were used to knockdown circ‐0745 expression. circ‐0745 expression was significantly reduced in cells transfected with siRNA‐2; this construct was used in all subsequent analyses Figure a. Comparπ/6. The volume of neoplasms in the sh‐circ_0000745 group was markedly smaller than in the control , accession number GSE102686.The circRNA microarray data of this study are openly available in the NCBI Gene Expression Omnibus (GEO) DataSets (


To investigate the clinical efficacy of a multi‐strain probiotic product on bowel habits and microbial profile in participants with functional constipation.10 CFU/day), consisting of Lactobacillus acidophilus DDS‐1, Bifidobacterium animalis subsp. lactis UABla‐12, Bifidobacterium longum UABl‐14 and Bifidobacterium bifidum UABb‐10 over 4 weeks. Outcomes included the patient assessment of constipation‐symptom (PAC‐SYM) questionnaire, stool frequency and consistency, and microbial profile.This was a randomized, double‐blind, placebo‐controlled and parallel‐arm study. Altogether 94 otherwise healthy adults aged 18 to 65 years with symptoms of functional constipation were randomized as part of the intention‐to‐treat population. The participants received a placebo or the probiotic product (1.5 × 10P < 0.001) over the study period. The probiotic group showed a faster normalization of stool frequency and consistency, with most participants achieving a normalized profile after 1 week. Fecal samples of the probiotic group exhibited higher relative abundance of Ruminococcaceae (P = 0.0047), including the Ruminococcus genus, and lower relative abundance of Erysipelotrichaceae (P = 0.0172) at end‐point compared with baseline. Placebo group samples showed similar abundance profiles over the study, with the exception of Clostridiaceae, which was lower at the study end‐point (P = 0.0033). Among treated participants, all four probiotic strains were significantly more abundant after the intervention.There were no significant between‐group differences in the PAC‐SYM score, despite significant within‐group differences (No significant differences were observed in symptomology, with both groups showing a more than 20% improvement. However, the probiotic helped modulate bowel function earlier than the placebo, with a corresponding shift to a more fibrolytic microbiota. Previous studies have found chronic constipation to be related to dysbiosisThe clinical management of functional constipation remains challenging. Current management options include diet and lifestyle changes, as well as the use of bulking agents, stool softeners, osmotic and stimulant laxatives, and prescription drugs.Probiotics are defined as “live microorganisms that, when administered in adequate amounts, confer a health benefit to the host”.Lactobacillus acidophilus DDS‐1, Bifidobacterium animalis subsp. lactis UABla‐12, B. longum UABl‐14 and B. bifidum UABb‐10, was previously shown, in a pilot clinical trial, to improve symptomology in participants with irritable bowel syndrome.A probiotic blend, consisting of 22.1http://clinicaltrials.gov under registration number NCT02418507, and was conducted according to the CONSORT 2010 Statement.This study was conducted in accordance with the ethical principles that have their origins in the Declaration of Helsinki and subsequent amendments. Notice of authorization for the study (File no. 208099) was granted by the Natural and Non‐Prescription Health Products Directorate . An institutional review board  provided unconditional approval for the study (IRB reference no. Pro00011887). The clinical trial was registered on Adults aged 18 to 65 years with symptoms of functional constipation were recruited at KGK Science . The included participants met the requirements of Rome III criteria for functional constipation based on self‐reporting over the past 3 months, with symptom onset beginning within the previous 6 months. Additionally, participants were required to have an average stool type of <3 on the Bristol stool scale (BSS), as assessed over a 2‐week run‐in period and agreed to maintain their current level of physical activity throughout the trial period. Exclusion criteria included women who were pregnant, breastfeeding, or intended to get pregnant, those with type I or type II diabetes, cancer, neurological disorders, immunocompromised conditions, major diseases of the cardiovascular, renal, hepatic, gastrointestinal, pulmonary or endocrine systems, a history of gastrointestinal complications (such as inflammatory bowel disease and ulcers) or abdominal surgery, a history of heavy drinking or an allergy or sensitivity to the test product ingredient. The use of antibiotics, probiotics, fiber supplements or prebiotic fiber and enriched foods were prohibited within 4 weeks prior to screening and during the trial. All participants provided their voluntary, written, informed consent prior to their inclusion.2.2This was a prospective, randomized, placebo‐controlled, double‐blind and parallel‐arm study. Investigational visits took place at screening and at baseline (d 0), mid‐point (d 15 ± 3) and end‐point (d 29 ± 3) of the 4‐week intervention period. At screening, the participants’ complete medical history, concomitant therapies and inclusion criteria were reviewed, their characteristics and vital sign measures were recorded and fasted blood was collected for hematological and biochemical assessments.Participants meeting the screening criteria entered a 2‐week run‐in period, which involved the completion of a daily bowel habit diary, 3‐day food records and a physical activity questionnaire. Eligibility was confirmed at baseline, and included a review of their inclusion criteria, a physical examination, vital sign assessments, weight and body mass index (BMI) measurements, completion of patient assessment of constipation ‐ symptom (PAC‐SYM) and patient assessment of constipation ‐ quality of life (PAC‐QoL) questionnaires, and, if applicable, a urine pregnancy test. The study diaries, including the records of daily bowel habits, food and physical activity questionnaires were collected. Eligible participants were randomized to receive placebo or probiotic capsules (1:1). All study personnel were blinded to the product. The randomization list was computer‐generated with a block size of 4. The block size was not disclosed to the investigators and allocation was blinded to the participants as well as the site staff. Enrolled participants were instructed to take one capsule per day, before or during a meal, beginning at the day after randomization (d 1).Throughout the intervention period, patients recorded their daily bowel habits, 3‐day food records, physical activity and compliance. Participants returned for investigational visits after weeks 2 and 4 of the intervention period, which included the completion of PAC‐SYM and PAC‐QoL questionnaires and the collection of study diary information. Fecal sample collection was performed prior to baseline and the end of study visits for microbial profiling analysis.2.3L. acidophilus DDS‐1, B. animalis subsp. lactis UABla‐12, B. longum UABl‐14 and B. bifidum UABb‐10. Placebo and probiotic capsules (size 1 hypromellose) were prepared in accordance with US Food and Drug Administration good manufacturing practices at UAS Laboratories . Probiotic capsules contained a potency of not less than (NLT) 1.5 × 1010 colony‐forming units (CFU)/capsule, of which L. acidophilus, B. animalis subsp. lactis, B. longum and B. bifidum were present in CFU/capsule ratios of 44:52:2:2, respectively. They were formulated with lyophilized probiotic blend (57 mg) and rice maltodextrin (280 mg). Placebo capsules were formulated with rice maltodextrin (337 mg). Both capsules contained minimal but identical quantities of fructooligosaccharide (7 mg), magnesium stearate (4 mg) and silica (2 mg). The probiotic and placebo capsules were identical in appearance and taste.The probiotic product contained four strains: 2.4The primary outcome was the change in the PAC‐SYM score after week 4 of the intervention, while secondary outcomes included the change in the PAC‐QoL, stool consistency and frequency, microbial profile, strain recovery, and safety parameters over the intervention period. The PAC‐SYM questionnaire2.5Participants collected fecal samples, as close as possible but prior to week 0 and 4 visits, inside a specimen collection hat, which ensured no contact with toilet water or urine. Samples were maintained at −80°C until analysis. Sample DNA isolation, library preparation and microbial profiling of fecal samples were performed by Second Genome . DNA isolation and DNA quantification utilized the MoBio PowerMag Microbiome kit  and the Qubit Quant‐iT dsDNA High Sensitivity Kit , respectively. DNA was subsequently amplified with fusion primers for the 16S V4 region, which incorporated Illumina  adapters and indexing barcodes.de novo OTU were determined. Each representative OTU sequence was assigned a taxonomic classification using mothur's Bayesian classifier, which was trained against the Greengenes reference database of 16S rRNA gene sequences clustered at 99%.The paired‐end reads were merged using USEARCH,Alpha diversity  and beta diversity  metrics were calculated. For the latter, Bray‐Curtis dissimilarity was used to calculate the abundance‐weighted sample pair‐wise differences.2.6L. acidophilus, B. animalis subsp. lactis, B. longum, and B. bifidum strains  target region was amplified individually from genomic DNA with primer sequences specific to the ns Table . The PCR2.7The primary efficacy outcome on which the sample size calculation was based was the change in the PAC‐SYM score between groups from week 0 to week 4 of the intervention period. Assuming alpha equaled to 5% and a power of 80%, the sample size was estimated with a difference in PAC‐SYM of 4.08 units between groups, and a standard deviation (SD) of 6.36 units. The above assumptions were based on prior studies with probioticP value of < 0.05 was regarded as significant. Descriptive statistics are presented as mean ± SD, or median and interquartile range (IQR) for continuous variables or as numbers and percentages for qualitative variables. Differences in baseline characteristics were assessed using an independent Student's t‐test or a non‐parametric Mann‐Whitney‐Wilcoxon test for continuous variables, or Fisher's exact test for categorical variables, respectively. To test the differences between groups over the intervention period, an analysis of covariance (ANCOVA) was used, taking into account covariates that were identified by multiple linear regression. The dependent variable was the change in the value of the variable (or its logarithmic transform) at the later visit; the intervention was the factor of interest, and the value of the variable (or its logarithmic transform) at the baseline visit was a covariate. The following variables at baseline were prespecified as possible confounders: sex, BMI, age, baseline physical activity, alcohol consumption, and smoking habits. These variables were included in the model as additional covariates, and a reduced set of confounders were identified by stepwise regression. The final reduced model was used for the formal ANCOVA test. For intractably non‐normal variables, the non‐parametric Mann‐Whitney U test was used to compare changes from baseline between the placebo and probiotic groups. Microbial profiling and strain recovery assessments utilized a paired Wilcoxon signed‐rank test to identify significant differences between week 0 and week 4 of the intervention period. The Mann‐Whitney U test was employed on unpaired genomic delta data.The primary and secondary objectives were assessed on the intention‐to‐treat (ITT) population. All the statistical analyses were performed using the R statistical package version 3.2.3 . Significance tests were two‐sided, and a 33.1A total of 248 participants were screened for the study from May 2015 through April 2016. In all 94 participants were randomized as part of the ITT population, with 46 participants in the placebo group and 48 in the probiotic group . Diastolic blood pressure was lower in the probiotic group ; however, the absolute difference was similar to that in systolic blood pressure  and was not significant when accounting for multiple comparisons. The ITT population comprised more women (75.5%) than men (24.5%). The participants were deemed to have functional constipation per Rome III criteria. There were no significant differences in parameters of functional constipation, including PAC‐SYM, PAC‐QoL, BSS and CSBM at baseline .The baseline characteristics of the ITT population are presented in Table 3.3P = 0.014), but no within‐group changes were observed over the study period (Table P > 0.05). Using the IPAQ scoring protocol, weekly physical activity was estimated and categorized as sedentary/light, moderate, or vigorous intensity. Between the two groups, there were no significant differences in the total exercise scores, including vigorous, moderate, and sedentary domains (P > 0.05).A dietary assessment of macronutrients was performed throughout the study period. The probiotic group showed a higher carbohydrate caloric intake at baseline (od Table . Further3.4P > 0.05) when comparing probiotic group with the placebo group (Table P < 0.001). However, significant within‐group reductions (P < 0.001) were observed in the placebo group as well. Similarly, PAC‐SYM abdominal, rectal, and stool subscales (Table P < 0.001), in probiotic‐treated participants. However, similar within‐group reductions (P < 0.001) were observed in the placebo group. The assessment of the PAC‐QoL total score did not show significant differences between groups at week 4 (P > 0.05), with both groups showing significant within‐group reductions (P < 0.001). Similarly PAC‐QoL physical discomfort, psychological discomfort, worries and concerns, and satisfaction subscales (Table P < 0.01).There was no significant difference in the PAC‐SYM total score at week 4 (up Table . Particies Table  showed ses Table  were sig3.5P = 0.03), after the first week of intervention (Table P > 0.05) as both groups approached a normal stool consistency at the end of study. While a placebo response in stool consistency was observed, this response was delayed compared with participants receiving the probiotic product.Participants receiving the probiotic showed a significant improvement in average stool consistency compared to the placebo group P = 0.0, after tP = 0.057). As compared to baseline, the mean weekly CSBM of the probiotic group increased by 1.29 units (P < 0.001), 1.86 units (P < 0.001), 2.21 units (P < 0.001) and 2.00 units (P < 0.001) after weeks 1, 2, 3, and 4, respectively. There was a nearly 2‐fold increase in weekly CSBM over the course of the study in participants receiving the probiotic. In comparison, the mean weekly CSBM of the placebo group increased by 0.21 units (P = 0.575), 1.03 units (P = 0.009), 1.60 units (P < 0.001) and 0.90 units (P = 0.023), after weeks 1, 2, 3, and 4, respectively. A subgroup analysis was also performed in participants with severe or very severe hard stool symptoms at baseline (Table P < 0.05). However, no between‐group differences were observed at later time points.Between the two groups, there were no significant differences in average stool frequency, as assessed by CSBM per week. However, there was a trend for participants receiving the probiotic to have a greater number of CSBM, as compared with the placebo group, over the first week of intervention  at week 0 and week 4. In contrast, the placebo group samples had significantly lower OTU richness at week 4 as compared with baseline while Shannon diversity, which considered richness and evenness of OTU, did not change Figure .P = 0.044) at week 4 as compared with week 0, while the probiotic group samples had a lower relative abundance of Tenericutes (P < 0.001) at week 4 than week 0. The abundance of the three most abundant taxa at the phylum level, Firmicutes, Actinobacteria and Bacteroidetes, did not differ significantly over time in both groups. Among the most abundant families, probiotic group samples had significantly higher relative abundance of Ruminococcaceae (P = 0.0047) and lower relative abundance of Erysipelotrichaceae (P = 0.0172) at week 4 compared to week 0. Within the probiotic group, two Ruminococcaceae genera, including Ruminococcus, were significantly more abundant in the week 4 samples. Placebo group samples showed similar abundance profiles at baseline and end‐point, with the exception of Clostridiaceae, which decreased over the course of the study (P = 0.0033). The increased abundance of Ruminococcaceae and decreased abundance of Tenericutes in the probiotic group and the decreased abundance of Clostridiaceae in the placebo group met the significance threshold after adjusting for multiple comparison testing.Figure P = 0.012) and BSS score (P = 0.001), contributed to overall beta diversity. Dietary data from the food records was assessed and was found to not be correlated to the beta diversity of the samples.Regarding beta diversity, samples did not cluster or separate according to time point in either group. However, it was determined that sex  pathway abundances between week 0 and week 4 in the probiotic or placebo groups. Among KEGG orthologs, in participants receiving probiotic, 10 features had an unadjusted  0 Table . However3.8B. animalis subsp. lactis (P < 0.001), B. bifidum (P = 0.001), B. longum (P < 0.001) and L. acidophilus (P = 0.003) were significantly more abundant in week 4 as compared with week 0 , albeit with high heterogeneity.L. casei Shirota strain failed to show a significant amelioration in stool consistency (SMD: +0.26).The current study enrolled on average middle‐aged, predominately female participants, with normal to overweight BMI, representing a typical cross‐section of the functional constipation population.L. acidophilus and B. bifidum helped normalize intestinal transit.Bifidobacterium and Lactobacillus.Faecalibacterium, Roseburia, and Coprococcus, have been reported to be directly correlated with colonic transit.Faecalibacterium, in particular, is among the most plentiful butyrate producers.Bacteroides, were shown to be inversely correlated with colonic transit,The gastrointestinal microbiota has been reported to play a role in gut motility. Early studies in germ‐free rats demonstrated delayed gastric emptying and colonic transit in comparison with their conventional counterparts.The current study demonstrated a significantly higher relative abundance of Ruminococcaceae within the probiotic group over the study period. In contrast, the placebo group showed a significant decrease in Clostridiaceae. Ruminococcaceae, the second most abundant Firmicutes family in gut environment,In the probiotic group the increase in Ruminococcaceae appeared to coincide with a decrease in Erysipelotrichaceae. This is potentially of interest, as members of the latter appear to be enriched in metabolic disordersWhile probiotic products are ultimately supported by randomized controlled trials demonstrating health benefits, it is also of importance to assess the presence of the live organisms post‐transit.Placebo response can be high in participants with bowel disorders, potentially leading to altered outcomes reported by the patient, and the power calculation for the current study may have underestimated this response. The study did not include a placebo run‐in period. The inclusion of such a period may have helped control the placebo response of participants entering the trial by excluding high responders.In summary, the multi‐strain probiotic product was shown to be well tolerated but did not significantly affect symptomology, in part due to a significant placebo response. Nevertheless, the probiotic exhibited potential in modulating bowel habits and microbial profile in participants with functional constipation.This study was sponsored by UAS Laboratories. Christopher J. Martoni and Gregory Leyer are employees of UAS Laboratories but were not involved in the study conduct, data management or statistical analysis.Supplemental Table 1. Quantitative polymerase chain reaction (qPCR) primer sequences to assess fecal recovery and identification of probiotic strainsSupplemental Table 2. Patient assessment ofconstipation ‐ symptoms (PAC‐SYM) and patient assessment of constipation ‐ qualityof life (PAC‐QoL) subscale scores over the intervention period in participants receiving placebo or probiotic capsules.Supplemental Table 3. Changes from baseline in stool consistency and frequency in subgroup of participants with severe or very severe hard stool symptoms at baseline.Supplemental Table 4. KEGG pathway abundances with an absolute fold‐change greater than two over the intervention period.Supplemental Table 5. Hematology data at screening and after intervention period.Supplemental Table 6. Biochemistry data at screening and after intervention period.Supplemental Table 7. Blood pressure (BP), heart rate, and weight data at screening and after intervention period.Supplemental Table 8. Summary of adverse events (AEs) over entire study period (n).Click here for additional data file.