To evaluate post-operative complications of circumcision requiring surgical reintervention.st, 2015 to May 31st, 2016. Retrospective analysis of medical records of patients submitted to circumcision from May 1 A total of 2,441 circumcisions were performed; in that, 1,940 using Plastibell and 501 by the classic technique. Complications requiring surgical reintervention were found in 3.27% of patients. When separated by surgical technique, 3.4% of circumcisions using Plastibell device required reoperation, as compared to 3% of conventional technique (p=0.79). Preputial stenosis was most frequently found in classic circumcision, with statistical significance (p<0.001). Bleeding was more frequent when using Plastibell device, but the difference was not statistically different (p=0.37). Patients’ age was also evaluated to investigate if this variable influenced on the postoperative outcome, but no significant difference was found. There was no statistically significant difference when comparing complications between the different techniques performed at this hospital. Preputial stenosis was most frequently found in the classic circumcision, while bleeding was more prevalent when using Plastibell device. Patients’ age did not influence in complications. When age was limited to 1 to 4 years, it was noted that 1.1% of these children were circumcised within this period.2Circumcision is one of the most ancient surgical procedures, and today is frequently performed by pediatric surgeons. In large American reviews, the circumcision rates in newborns can reach up to 61.1%, and many operations are related to cultural indications, and not only for medical reasons.The benefits of surgery include prevention of urinary infection and pyelonephritis, decrease in penile cancer rates, as well as a reduction in sexually transmitted diseases. Nevertheless, like other procedures, it is not exempt from complications.1 Bleeding is the most common complication of circumcision, with an incidence of up to 1% in recent retrospective studies. Meticulous attention to hemostasis during the procedure, and adequate compression on the skin suture can prevent this complication in most cases. Even so, there may be dislodgment of clots.1 In general, late complications are associated with remaining skin inclusions and the incomplete removal of the prepuce, which can result in wound contraction and scarring of the distal portion of the prepuce, leading to its stenosis. The fibrotic ring may, then, result in true phimosis, requiring reoperation in about 2% of cases.1Severe complications are rare.3 Some pediatric urologists consider that adolescent patients have a greater risk of postoperative bleeding, but this association has not been duly confirmed by literature.4The complication rates depend on multiple factors, including anatomical anomalies, clinical comorbidities, surgical technique used, and age of patients.To evaluate circumcision complications and compare them with the different surgical techniques used, and the influence of patient age in the postoperative complications.st, 2015, and May 31st, 2016, at the Hospital Pequeno Príncipe, in Curitiba, State of Paraná, Brazil. The present study was approved by the Ethics Committee of the organization, official opinion number 1.602.963, CAAE: 56993816.0.0000.0097.This was a retrospective study, by means of the analysis of medical records of 2,441 patients submitted to circumcision between May 1Two different surgical techniques were used, and patients were divided into two groups. The choice was based on the personal opinion and experience of each surgeon. The sample included patients operated on by 19 different surgeons, 6 of whom were residents in pediatric surgery.All patients were operated on based on medical indication, and no newborn underwent surgery. Some similarities were noted among the two groups: blockage of the dorsal penile nerve was performed in all patients under general anesthesia, and no prophylactic antibiotic was used.The first technique, performed on 501 patients, consisted of classic circumcision. The redundant prepuce was retracted, the adhesions to the glans were released, and after skin excision, hemostasis was performed with an electrocautery. Approximation of the skin and mucosal borders was done with absorbable suture (Catgut 5-0).The second technique consisted of the use of Plastibell. The redundant prepuce was pulled upwards, and the device was positioned between the prepuce and the glans. The size of the ring was chosen according to the size of the glans. A non-absorbable suture was tied around the device, and the distal prepuce was excised. No bandaging was used, and in the immediate postoperative phase, topical neomycin was used. This group consisted of 1,940 patients.All cases were analyzed, and the sample consisted of 80 patients who presented with complications requiring surgical reintervention. The data collected was name, age on the day of surgery, surgical technique used, complications, and surgical treatment given after complication.® and analyzed using Fisher’s exact test. A p value <0.05 was considered significant.The data were tabulated using Microsoft Office ExcelOf the total 2,441 circumcisions performed at the service during the period evaluated , 80 . Considering that no significant difference was demonstrated (p=0.37), we can only affirm that there was a greater tendency towards bleeding with the use of Plastibell . The presence of bleeding was most prevalent in cases in which the ring was used  patients. Three of them presented with hemorrhage and need for immediate surgical reintervention . When long-term complications were evaluated, we noted 32 cases, the majority of little clinical significance . Complications directly related to the use of the ring occurred in 6 (5.4%) patients – five of them with significant postoperative pain, and one who presented Plastibell retention by the foreskin, requiring manual removal. The complication rates did not show correlation with the size of the ring used, and were similar in the different age ranges.10 The incidence of early complications with the use of the plastic device reported by Bastos Netto et al., was similar to that of the conventional technique, and corroborates data of our study.10Plastibell was initially used to perform circumcisions in 1956. Since then, its use has been increasingly more widespread and frequent with satisfactory success rates, although there are reports of complications associated with its use.11 as the most common early complication with the use of Plastibell, and the rates varied from 2.5 to 4%. In general, bleeding results from the inappropriate ligature of the cord that holds the plastic ring, predisposing foreskin retraction and dislodgement of the ring.10 In this study, bleeding was the second most frequent complication of Plastibell use, following paraphimosis caused by dislodgement of the plastic ring – a complication that has not been previously analyzed in literature, but which, in this study, was responsible for the highest rate of reoperation among all patients.Several studies described bleeding9 of cases. Some authors10 recommended surgical revision as soon as possible in patients with preputial stenosis or redundant prepuce, in order to avoid this complication.Four patients from this study presented with postoperative balanoposthitis associated with preputial stenosis, the latter considered a late complication associated primarily with the greater quantity of foreskin that is maintained, and with the process of local scarring. Previous literature demonstrated the incidence of this infectious complication can be as high as 15%12 Assessing the complications using the Clavien-Dindo classification13 for surgical complications, the classes IIIa and IIIb  were emphasized in this study. No cases of class IV (life-threatening complications) were found. Another recently published study proposed a classification of circumcision complications by separating them into five different grades: I for skin problems; II, isolated urethral lesion; III, amputation of the glans; IV, lesion of the corpus cavernosum; and V, total loss of the phallus.14 According to this recent classification, this article did not present with complication among those considered most severe.Some severe complications with potential anatomical, functional, and psychological sequelae have already been reported, such as amputation of the glans, lesion of the corpus cavernosum, ablation of the penis, iatrogenic micropenis, and penile amputation.As to the limitations of the study, we highlight the fact of being conducted at single center, where different surgeons were involved in the procedures, including residents under training, which could have influenced the clinical progress in some patients.There was no statistically significant difference when comparing complications among the different surgical techniques used at this service. Preputial stenosis was more often observed in patients operated on by the conventional technique, whereas bleeding tended to be more frequent with the use of Plastibell. Paraphimosis due to dislodgement of the plastic ring was a frequent complication that required surgical reintervention. The age of patients did not influence in presence of complications.


To solve this problem, we constructed a Bayesian probabilistic framework that circumvents the limitations of previous reference correction methods that required protein resonance assignment and/or three-dimensional protein structure. Our algorithm named Bayesian Model Optimized Reference Correction (BaMORC) can detect and correct 13C chemical shift referencing errors before the protein resonance assignment step of analysis and without three-dimensional structure. By combining the BaMORC methodology with a new intra-peaklist grouping algorithm, we created a combined method called Unassigned BaMORC that utilizes only unassigned experimental peak lists and the amino acid sequence. Unassigned BaMORC kept all experimental three-dimensional HN(CO)CACB-type peak lists tested within ± 0.4 ppm of the correct 13C reference value. On a much larger unassigned chemical shift test set, the base method kept 13C chemical shift referencing errors to within ± 0.45 ppm at a 90% confidence interval. With chemical shift assignments, Assigned BaMORC can detect and correct 13C chemical shift referencing errors to within ± 0.22 at a 90% confidence interval. Therefore, Unassigned BaMORC can correct 13C chemical shift referencing errors when it will have the most impact, right before protein resonance assignment and other downstream analyses are started. After assignment, chemical shift reference correction can be further refined with Assigned BaMORC. These new methods will allow non-NMR experts to detect and correct 13C referencing error at critical early data analysis steps, lowering the bar of NMR expertise required for effective protein NMR analysis.Poor chemical shift referencing, especially for The online version of this article (10.1007/s10858-018-0202-5) contains supplementary material, which is available to authorized users. Nuclear magnetic resonance (NMR) is a highly versatile analytical technique for studying molecular configuration, conformation, and dynamics, especially of biomacromolecules such as proteins Saitô . Several1H, 13C and 15N chemical shifts CACB-type peak lists , which detects and corrects 13C chemical shift entries (datasets) as described in the Methods. Each dataset contains the protein sequence and the corresponding NMR chemical shifts. One point worth mentioning is that most of the datasets are not complete: i.e., there are fewer assigned residues than would be expected from the protein sequence. However, missing resonance assignments are common due to a myriad of experimental conditions, especially conformational flexibility in the protein structure that leads to intermediate chemical exchange. Using the secondary structure information accompanying the NMR chemical shift data provided by the RefDB, we associated residue-specific Cα and Cβ chemical shifts and then sub-grouped them by amino acid and secondary structure type, as shown in Supplemental Fig. 1 for 19 of the 20 common amino acids (not including glycine) in proteins and for the secondary structure types helix, sheet, and coil. The univariate Cα and Cβ chemical shift distributions are multimodal, with most of the modes being secondary structure specific , weakening the covariance calculated between these chemical shifts. Therefore, we used quality control measures provided by the RefDB to evaluate the performance of the referencing and to select a subset of entries for deriving amino acid- and secondary structure-specific covariances between Cα and Cβ chemical shifts  and covariances (Cov) are described in Eqs. α and Cβ chemical shifts, since these shifts may come from separate spectral sources. Matrix E-Revised showed the best performance among the pure statistical models, exhibiting the closest 13C reference correction of 0.00 ppm for BMR6032 entry, as shown in Supplemental Fig. 2 and Supplemental Table 3. The performance of Matrix E-Revised as illustrated in Fig. i is the helix,beta strand,coil.We created an unordered pair of Cogy see “”. The caα/Cβ bivariate statistical models on the observed amino acid content frequencies α/Cβ bivariate statistical models using observed Cα/Cβ chemical shifts in the RefDB associated with specific amino acid and secondary structure types. The observed amino acid content frequencies α and Cβ chemical shifts in real datasets. The calculation of the prediction overlap matrix and predictor weights is described in the “Figure α/Cβ bivariate statistical models with the prediction overlap matrix, while ignoring glycine residues. The BaMORC method improves the comparison of the predicted and observed amino acid and secondary structure frequencies more than 2.5-fold by modifying Y with the prediction overlap matrix to create The BaMORC method combines the E-Revised covariance method used in the chi-squared-based Cα chemical shift distributions for beta sheet and coil secondary structure types for glycine residues. This is illustrated by the universally-high prediction-overlap values for glycine predictors as shown in Supplemental Fig. 3. The high values would significantly inflate the product of the matrix multiplication, which will greatly influence the residuals over the range of overlapping Cα chemical shift distributions. Thus, in the final implementation of the BaMORC methodology we ignored glycine residues.We also tried to add glycine-specific predictors in the BaMORC method. However, the inclusion glycine statistical models had mediocre performance in comparison to using only the 57 non-glycine predictors. This is illustrated in Supplemental Fig. 4, which shows a bimodal distribution of reference correction values with a 90% confidence interval of ± 0.82 ppm and absolute length of 1.64 ppm. The cause of the poor performance appears rooted in the complete overlap of Cα and Cβ chemical shifts. Therefore, missing chemical shift data is a real issue that must be addressed. Accordingly, we tested the performance of the BaMORC method using unassigned datasets generated from the RefDB with varying amounts of missing 13C spin systems. First, we constructed datasets with 100% completion by removing amino acid sequences for missing Cα and Cβ chemical shift values for 568 entries with 95% or greater starting completion. Then, we incrementally removed 5% of the 13C spin systems and tested the performance. Figure 13C spin system data are present. The overall performance of BaMORC does not appreciably deteriorate until approximately 70% of the 13C spin systems were missing. Even, with 50% of the spin systems missing, the absolute length of the 90% confidence interval is less than 1 ppm, with the reference corrections within ± 0.6 ppm. Therefore, BaMORC is very robust to missing 13C chemical shift data.Protein NMR datasets are typically incomplete from the perspective of what resonances are expected based on the protein sequence. This incompleteness is due to a host of experimental issues that prevent the detection of all protein resonances. In the RefDB itself, only 568 out of the 1557 entries include 90% or more of the expected CTo test the performance of our method in a real-life situation, we removed all of the secondary structure information from the RefDB data and used the sequence-based secondary structure predictions generated from JPred4 . Among 1557 entries, the correlation optimization filtered down to 729 entries for calculating optimal covariances. The resulting improvement between the inaccurate covariances and the optimal covariances is illustrated in Fig. 13C-assigned peak lists, we see an opportunity to further refine covariance statistics. According to our estimates, about 180,000 13C-assigned peaks are required in the BMRB for the next generation of covariance analysis. Currently, the BMRB contains approximately 11,500 13C-assigned peaks.During the development of the BaMORC methodology, we addressed several issues regarding chemical shift data quality in the RefDB entries, which are derived from the BMRB. The reference correction of BMRB protein entries provided by the RefDB was a starting point that enabled the derivation of amino acid and secondary-structure-specific expected values and variances for CWe have tested the performance of the general BaMORC method in detecting reference correction values under various conditions. The reference correction values were within ± 0.45 ppm of the SHIFTX determined references at the 90% IQR with an absolute length of 0.73 ppm for datasets derived from the RefDB. The typical NMR dataset includes approximately 85% of the expected spin systems. Therefore, we tested our algorithm on incomplete data by incrementally removing a certain percentage of the data from each dataset tested. The robustness of the algorithm is stunning: it performs very well, maintaining referencing correction within  ppm range of the correct value at the 90% confidence level, even when 50% of the data are randomly removed. This robustness is achieved because the algorithm uses a non-parametric approach (i.e. a comparison of expected and predicted amino acid frequencies). Additionally, keeping reference correction within ± 0.6 ppm of the correct value is very important for accurate amino acid typing used in protein resonance assignment analysis and for accurate secondary structure analysis from chemical shifts. When carbon chemical shift referencing accuracy is outside the  ppm range, the relative error rate in amino acid and secondary structure prediction increases dramatically as illustrated by the increase in residuals in Supplemental Fig. 6.α/Cβ correlation and subsequent reference correction performance by BaMORC. Also, two of the experimental peak lists had a carbon chemical shift reference deviation that was over 2 ppm. Peak lists with large chemical shift referencing errors is the exact situation that Unassigned BaMORC was designed to detect and correct, so that a scientist does not waste time and effort trying to utilize such highly miss-referenced peak lists for downstream analyses, especially protein resonance assignment. The resulting assignments would be error prone and their chemical shifts would propagate error during structure determination. But even more subtle deviations in the 0.6–2.0 ppm range can have a significant impact on assignment and structural error. But Unassigned BaMORC has a demonstrated performance in keeping carbon chemical shift referencing within the ± 0.4 ppm range.Also, this performance on spin system datasets derived from the RefDB completely translates to the real-world use-case where real, unassigned, experimental HN(CO)CACB peak lists are utilized. All peak list data were manually peak-picked. There are extra peaks in the data, which could be artifacts or from additional resonances due to multiple local protein conformations. Table The computation time is scaled primarily on the number of probabilistic amino acid predictions performed, which in turn is dependent on the size of the data and the number of reference refinement steps; however, there are user-controllable settings allowing a trade-off between accuracy and computation time. By default, 50 incremental steps are employed in both rounds of reference scanning. The first round of scanning is performed over the range of  ppm in increments of 0.2 ppm, and the second round of scanning is centered at the results from the first round of scanning over the range of  ppm in increments of 0.04 ppm, resulting in 100 proposals , which for a 10 kDa protein, typically takes approximately 3 min to process on a standard desktop computer. More precisely, the algorithm has a number of stages, each with a different theoretical computational complexity. The grouping stage consists of two steps: registration and spin system grouping. The computational complexity of the registration stage is optimized to α and Cβ chemical shifts is identical and independent, following a bivariate normal distribution, and the shapes of the distribution are well-represented by ellipses. Although we expect the algorithm to be robust to morphologically similar distributions, such as flat-top clusters or low-aspect-ratio ellipses, the algorithm is certainly not designed for the analysis of very small proteins or peptides. In addition, the presence of paramagnetic compounds, ring current effects, and deuteration shift effects will generate outlier chemical shift values that significantly deviate from the expected values derived from the RefDB dataset.An issue facing any model-based approach to data analysis is the validity of the model assumptions. The most important model assumptions here are that each pair of CThe default assumptions stipulate that each input dataset is at least 50% complete, meaning that the number of missing spin systems should not represent more than 50% of the expected number of spin systems based on the protein sequence. In practice, we found datasets with greater than 70% completion produced consistent reference correction values. If the user wishes to statistically demonstrate the applicability of our approach to a problem, they can employ the residual (sum of the absolute difference) plot. We have thoroughly tested our defaults assumptions on a wide variety of protein scenarios  and found the correction results to be largely insensitive to protein classification. However, we recognize that there are extreme examples like disordered proteins for which these choices may not be advised. As with all Bayesian analyses, it should be remembered that the prior parameters should genuinely represent the subjective prior beliefs.13C chemical shift referencing using HN(CO)CACB-type peak lists. The focus on 13C chemical shift referencing is pragmatic from three perspectives: (i) Cα and Cβ provide the most information about amino acid type, which is central to the BaMORC methodology; (ii) accurate 13C chemical shifts have the greatest impact on protein resonance assignment and other downstream analyses; and (iii) grouping of the HN(CO)CACB peaks into spin systems is more robust than for other NMR experiments. Likewise, Assigned BaMORC is designed to use assigned Cα and Cβ chemical shifts for reference correction after initial chemical shift assignment, but before other downstream analyses. However, we are pursuing further improvements to the methodology and current implementations. We see a host of possible improvements that would extend the methodology to correct 1H and 15N chemical shift referencing and allow the application of the method to peak lists derived from other types of NMR experiments as well. Though, some of the improvements will require further evaluation and refinement of the chemical shifts from BMRB and RefDB entries and may require waiting until sufficient assigned peak lists are present in these public scientific repositories. For instance, developing an extension to handle intrinsically disordered proteins (IDPs) would likely require more than the 176 IDP BMRB entries available as of May 2018.Unassigned BaMORC is currently designed to correct α and Cβ chemical shift data to generate accurate 13C reference correction within ± 0.45 ppm at the 90% confidence level on RefDB derived test datasets. BaMORC also demonstrates robust performance, keeping the 13C reference correction within ± 0.6 ppm at the 90% confidence level even with up to 50% of the 13C chemical shift data missing. Keeping the reference correction within 0.6 ppm of the correct value is very important for accurate amino acid typing to be used in protein resonance assignment analysis. The Unassigned BaMORC method utilizes unassigned Cα and Cβ chemical shift data from HN(CO)CACB-type experimental peak lists to generate accurate 13C referencing correction within ± 0.4 ppm for all 10 HN(CO)CACB-type experimental peak lists tested. The Assigned BaMORC method utilizes assigned Cα and Cβ chemical shift data to generate accurate 13C chemical shift reference correction within ± 0.22 ppm at a 90% confidence interval. Unassigned BaMORC can correct 13C chemical shift referencing at the beginning of protein NMR analysis, when accurate 13C chemical shift referencing is needed the most for accurate protein resonance assignment, structure determination, and other downstream analyses. Assigned BaMORC can refine the referencing once assignments are made. Additionally, the underlying BaMORC method is robust to missing 13C chemical shift data, which addresses the real-world situation of incomplete 13C resonance detection. Therefore, the BaMORC methods will allow non-NMR experts to detect and correct 13C referencing error at critical early data analysis steps, lowering the bar of NMR expertise required for effective protein NMR analysis.The BaMORC method utilizes unassigned C1 on May 4th, 2015  entries using the SHIFTX-predicted chemical shifts based on corresponding 3D protein structures in the Protein Data Bank (PDB), which is managed by the international collaboration known as the worldwide Protein Data Bank (wwPDB) α and Cβ chemical shift information. Statistics were also calculated from the resulting data and verified using the results reported in the RefDB. Based on amino acid and secondary structure, we subdivided the data into 60 classes based on 20 amino acid types and three secondary structure types. In the early part of the methods development, we ignored the glycine classes and only employed the other classes representing the 19 amino acids with Cβ resonances.For each RefDB entry, we first parsed the text data files with the extension of “.str.corr”, which are mostly in NMR-STAR 2 format, with additional sections added by RefDB, with a short R script that uses crafted regular expressions to clean and convert the relevant assigned chemical shift data into a tab-based format for parsing. The reason for this conversion step is to remove unnecessary metadata, missing values, blank spaces, and section breaks. In this conversion, we retained the full sequence, residue position, amino acid typing, secondary structure, and Cα–Cβ pair into two clusters based on the smallest Euclidean distance from cluster centroids. Then, it uses iterative techniques to re-calculate the centroids and re-group the data until the centroids converge. To verify the clustering results, we compared the means and standard deviations of the two new subgroups with statistics reported in the RefDB. It is worth mentioning that even though the statistics from RefDB included two-state cysteines, there are no labels on any specific cysteine in the RefDB NMR data.From Fig. α and Cβ for each group. We first calculated the mean . Thus, we first compared the two RMSD values, using the RMSD comparison equation Q, as shown in Fig. We employed the root mean squared deviation (RMSD) as the criterion for selecting subgroups. The RMSD is recorded in every data file in the RefDB. The RMSD is a measurement of the confidence interval of the population mean  for each single data point. This statistic is calculated from Student’s t-test. The higher the RMSD value, the less accurate the corrected data. In our methodology, we have two RMSDs from the Cα–Cβ bivariate distributions overlap almost completely, as shown in Fig. α and Cβ chemical shift values, to predict the α and Cβ chemical shifts, we calculated the probabilities of the 57 classes. Likewise, we used every glycine Cα chemical shift to calculate the probabilities for the three glycine classes. For example, for every data point of an alanine-beta strand, we calculated the probabilities of all of the classes. Then, we performed normalization across the columns and finally obtained a Sixteen of the 19 amino acid Cα/Cβ bivariate statistical models approximate the real distributions. Hence, we used the real distributions to calculate the prediction overlap between the bivariate statistical models and represented this overlap as prior information in the form of a prediction overlap matrix. Moreover, we employed the diagonal elements of this matrix  as weightsIn nature, amino acid chemical shift distributions are not ideal; i.e., the CThe overall optimization approach can be simplified into the following residual equation which is minimized as showing in Eq. To calculate the 13C chemical shifts. To calculate the probability, we first need to transform each pair of the chemical shifts to a Chi square value using Eq. 13C chemical shifts. For a given NMR dataset with The bottom right flowchart in Fig. The search range is typically limited to − 5 to 5 ppm centered around the current reference value of 0. The algorithm first evenly samples 50 candidate reference correction values in the range from − 5 to + 5. Each of the candidate values is applied in the whole dataset, and the difference between the estimated and actual amino acid composition frequency is calculated. The one value that minimizes the difference is the raw correction value, α/Cβ pair in BaMORC to only 1 probability calculation CACB), for 1H and 15N. Next, it groups peaks into spin system clusters using the derived match tolerance values. Then, the algorithm checks whether any ungrouped peaks remain and, if so, creates a new peak list and attempts to register it again itself again to determine new, larger match tolerances that can be used to group peaks into spin systems.The spin system grouping algorithm, as illustrated in Fig. 13C chemical shifts derived from pairs of grouped HN(CO)CACB peaks. Using these pairs of 13C chemical shifts and the same BaMORC analysis pipeline reports an optimized correction value as a reference. Eventually, Unassigned BaMORC applies this correction value to all of the Cα and Cβ chemical shifts and prints out a text file, that including all of the corrected peak lists in the final output.The reference correction methodology is essentially BaMORC. The input of the algorithm is the output from the grouping methodology, which are pairs of Below is the link to the electronic supplementary material.Supplementary material 1 (DOCX 3962 KB)


It has also been shown, theoretically, that for planar tensor encoding (PTE), the direction‐averaged diffusion‐weighted MRI signal decays as 1/b. We aimed to confirm this theoretical prediction in vivo. We then considered the direction‐averaged signal for arbitrary b‐tensor shapes and different tissue substrates to look for other conditions under which a power‐law exists.It has been shown, theoretically and in vivo, that using the Stejskal‐Tanner pulsed‐gradient, or linear tensor encoding (LTE), and in tissue exhibiting a “stick‐like” diffusion geometry, the direction‐averaged diffusion‐weighted MRI signal at high b‐values  gradients.b power law for PTE. Moreover, our analysis showed that using an axisymmetric b‐tensor a power‐law only exists under very specific conditions: (a) “stick‐like” tissue geometry and purely LTE or purely PTE waveforms; and (b) "pancake‐like" tissue geometry and a purely LTE waveform.Our in vivo results confirmed the predicted 1/A complete analysis of the power‐law dependencies of the diffusion‐weighted signal at high b‐values has been performed. Only three specific forms of encoding result in a power‐law dependency, pure linear and pure PTE when the tissue geometry is “stick‐like” and pure LTE when the tissue geometry is "pancake‐like". The different exponents of these encodings could be used to provide independent validation of the presence of different tissue geometries in vivo. In the statistical model developed by Yablonskiy et al,b for large b, while the other studies1/b.Diffusion MRI (dMRI) provides a tool to study brain tissue based on the Brownian motion of water moleculesThe aforementioned studies all used the conventional  pulsed‐gradient diffusion encoding,This approach has been utilized by several groups for extracting microstructural information.In this study, we investigate the effect of different b‐tensor encodings on the diffusion signal at high b‐values. To remove the effect of fiber orientation distribution,b. We then consider, more generally, the direction‐averaged signal for arbitrary b‐tensor shapes and different tissue substrates to determine the conditions under which the power‐law exists. We establish the range of b‐values over which we observe any power‐law scaling, including considerations of signal amplitude compared to the noise, and the impact of the number of encoding directions on any power‐law decay. Finally, we consider how observation of a power‐law signal dependence with more than one gradient wave‐form could help to provide a “cross‐validation” for specific tissue geometries.In this work, we confirm in vivo the theoretical prediction2B=b/3(1-bΔ)I3+bbΔggT, where g is the diffusion gradient direction and the b‐value, b, is defined as the trace of the b‐matrix. The eigenvalues of the b‐matrix areb‖,b⊥(1) andb⊥(2) whereb⊥(1)=b⊥(2)=b⊥ andb‖ is the largest.bΔ is defined asbΔ=(b||-b⊥)/(b||+2b⊥). ChangingbΔ, we can generate different types of b‐tensor encoding. For LTE, PTE, and STE,bΔ=1,-1/2, and 0, respectively.In multi‐dimensional diffusion MRI, the b‐matrix is defined as an axisymmetric second‐order tensor,S is the normalized diffusion signal andD‖ andD⊥ are the parallel and perpendicular diffusivities, respectively. We use the subscript “e” and “a” to denote parameters of the extra‐axonal and the axonal compartments, respectively.For the powder‐averaged signal, the diffusion attenuation is a function of the orientation‐invariant aspects of the diffusion and the encoding. The compartment diffusion attenuation is (Equation (34) inHere, we study the effect of axisymmetric b‐tensor shape on the diffusion‐weighted signal at high b‐values.2.1bΔ=1 and assuming stick‐like geometry,D⊥=0 in Equation Sic∝b-1/2. The sensitivity of MR to axon radius would alter theb-1/2 scalingIn LTE,bΔ=-1/2 andSic has the following form: bDa||≫1; therefore, the diffusion signal can be approximated by the following equation (see Appendix A): N depends on thebDa|| value ≪1, and can be neglected.For large b‐values, the extra‐axonal signal decays exponentially faster than the intra‐axonal compartment,x) in Equation x → ∞, but large values ofbDa‖ would suppress the signal to immeasurable levels, and therefore there are practical bounds on the value ofbDa‖ that can be achieved. Therefore, we compared the original signal in Equation N andbDa‖ NormbΔ=0 andSic=exp(-b3Da||). For large b‐values, both intra‐ and extra‐axonal signals decay exponentially fast,exp(-bDa‖3)≪1,exp(-b(De‖+2De⊥)3)≪1 and both of them are negligible. Therefore, the STE does not provide a considerable signal for large b‐values in a two‐compartment model.In STE,2.2bΔ≠0 to cover all b‐tensor shapes betweenbΔ=-0.5 (PTE) tobΔ=1 (LTE).Here, we consider the general case of an axisymmetric b‐tensor2.2.1D‖≠0. In this case, to have a power‐law relationship between the signal and the b‐value, the exponential termexp[-b(D‖+2D⊥-bΔ(D‖-D⊥))/3] should go to one and thereforeD‖+2D⊥-bΔ(D‖-D⊥)=0. ForD‖≠0,D⊥/D‖=(bΔ-1)/(bΔ+2) which is only physically plausible  forbΔ-1≥0, but the maximum value thatbΔ can take is one, and thereforeD⊥ has to be zero, that is, the tissue geometry has to be that of a stick, and the b‐tensor has to be a pure LTE to have a power‐law relationship. IfD‖=0 then we have the imaginary error function and therefore there is a power‐law relationship for the pancake‐like tissue geometry.As noted above, in this range, the error function in Equation 2.2.2-0.5≤bΔ<0, as in Equation -0.5<bΔ<0 which is not physically plausible for the left side of the equation . Therefore, the only possible case is to have D⊥=0 which again means stick‐like tissue geometry and bΔ=-0.5 which is pure PTE. Clearly the exponential term will become zero if and only if bΔ=-0.5, and thus, the 1/b signal form will occur if and only if the b‐tensor shape has just 2 non‐zero eigenvalues, that is, pure PTE. Thus, for stick‐like geometries, there are only two b‐tensor shapes for which a power‐law exists: pure linear and pure planar. Moreover, for pancake‐shape tissue geometries, a power‐law exists if and only if the encoding geometry is pure LTE.Conversely, in the range b power law. The S∝b-1 dependence is valid for an intermediate range of diffusion weightings while the asymptotic behavior of the signal decay is determined by a steeper decay.Herberthson et al33.1s/mm2] with a step‐size of 500 s/mm2. The noise is considered Rician with SNR = 150 for the b0 image, which is practically feasible using the Connectom scanner with an echo time of 88 ms.f1,f2, andf3 are the intra‐axonal, extra‐axonal, and the sphere signal fraction respectively, W(n) is the Watson ODF,Sec is the extra‐axonal signal,Scyl is the signal attenuation of the impermeable cylindersSsph is the restricted diffusion inside the spherical compartment in the presence of b‐tensor encodingf1 = 0.65,Da‖=2μm2/ms,De‖=2μm2/ms,De⊥=0.25,0.5,0.75μm2/ms and κ = 11] and axon radiusri, come from the bins of the histograms in.ris weighted byri2. In histology, there is a possibility of tissue shrinkage. To account for this change, the axon radius values are multiplied with three shrinkage factors η = 0, 1, 1.5.η = 0 case simulates the effect of zero‐radius axons.Synthetic data were generated with 60 diffusion encoding gradient orientations uniformly distributed on the unit sphereRs=8μm to consider the effect of combining the environments on the power‐law scaling.The third compartment is simulated as a sphere with zero radius (dot) and a sphere with radiusSn and S are the noisy and noise‐free signal, respectively, andNr andNi are the normal distributed noise in the real and imaginary images respectively with a standard deviation of σ.https://github.com/maryamafzali/PTE_Cylinder-).The noisy diffusion‐weighted signal is modeled according to the following: 3.2Two healthy participants who showed no evidence of a clinical neurologic condition were scanned in this study that was conducted with approval of the Cardiff University School of Psychology ethics committee. Diffusion‐weighted images were acquired with 60 gradient directions for PTE on a 3T Connectom MR imaging system . Twenty axial slices with a voxel size of 4 mm isotropic  and a 64 × 64 matrix size, TE = 88 ms, TR = 3000 ms, were obtained for each individual.To take full advantage of q‐space trajectory imaging, it is imperative to respect the constraints imposed by the hardware, while at the same time maximizing the diffusion encoding strength. Sjolund et als/mm2 with a step size of 1000 s/mm2 and each shell had the same 60 diffusion encoding gradient orientations uniformly distributed on the unit sphere. One b0 image was acquired between each b‐value shell as a reference.Diffusion data were acquired for 10 b‐value shells from 1000 to 10 000 The data were denoisedD=rrT(D‖-D⊥)+D⊥I, whereD|| andD⊥ are the parallel and perpendicular diffusivity, r is the tensor principal direction and I is the identity matrix. We used S =  exp (−trace(BD)) to simulate diffusion‐weighted signal for linear and PTE. The b‐matrix for LTE and PTE is defined asBLTE=bggT, andBPTE=b/2(I-ggT), respectively, where g is the gradient direction and the b‐value, b, is the trace of b‐matrix. The orientation, r, was rotated in 512 different directions to consider the effect of rotation. We usedb=7000-10000s/mm2 with a step size of1000s/mm2. We changeD|| andD⊥, while keeping the mean diffusivity ofMD=1.0μm2/ms and set FA = 0.95 because the impact of rotational variance is most pronounced at high anisotropy. The direction averaged signal was calculated and the coefficient of variation (CV) across all 512 orientations was estimated using CV = SD/E where SD and E are the standard deviation and mean value, respectively. The threshold was set to CV < 0.01 and the minimum number of directions to meet this condition was calculated.In order to find the minimum number of directions necessary to have a rotationally invariant signal powder average, we used the method proposed by Szczepankiewicz et al.4S^/S for3<bDa‖<20 and 4 < N < 21. The selected range ofbDa‖ is compatible with the range of b‐values that we can obtain from the Connectom scanner and also the range ofDa‖ that exists in the brain.bDa‖ (N≤⌊bDa‖⌋ where ⌊...⌋ denotes the floor function) to have the minimum error (S^/S is close to one). As the number of terms goes beyond thebDa‖, the error increases. Table N, for different error threshold values (0.01‐0.06). When the error threshold is 0.02, we can approximate Equation bDa‖≥14. For the error threshold of 0.06, the maximumbDa‖ to approximate the signal with the first term is 3.Figure bDa‖≥14). One of the challenges with the high b‐values is the noise, as the signal amplitude can be close to the noise floor. Therefore, here we find the maximum value ofbDa‖ that we can use before hitting this rectified noise floor (see Appendix C).Diffusion MRI is an inherently low SNR measurement technique, particularly when strong diffusion weightings are utilized. To reach the level that enables us to approximate the planar diffusion signal in Equation The noise in complex MR data is normally distributed, whereas the noise in magnitude images is Rician distributed.bDa‖ as a function of SNR for different encoding schemes and different noise floors. The maximum value ofbDa‖ that can be used while staying above the noise floor increases when SNR increases, but the rate of this change is different for different encoding schemes. The maximumbDa‖ value (bDa‖max) is proportional to the square of SNR, (bDa‖max∼SNR2) for LTE, where this relationship is linear for PTE (bDa‖∼SNR) and it is logarithmic for STE (bDa‖∼ln(SNR)). Based on this plot, if SNR = 50 the values ofbDa‖max for linear, planar and STE schemes are around 312, 21 and 9 respectively. The SNR in our data is around 150 therefore the measured signal values in our experiment are higher than the noise level. For this SNR, thebDa‖max for linear, planar and STE schemes are around 15 625, 100 and 16 respectively.Figure f3=0) as a function of 1/b for three different perpendicular diffusivities and three different shrinkage factors. The result of the power‐law fit (S=βb-α) is represented by the red dashed line and the α and β values are reported in each plot. The trust‐region‐reflective algorithm is used for optimization with a fixed initial value (α = 1 and β = 0.2). The goodness of fit is evaluated using the Bayesian information criterion (BIC).f = 0.65,Da‖=2μm2/ms, therefore if the approximation in Equation β ≈ 0.325 and α ≈ 1 indicate that the fit approximately matches the theory.Figure b<=4000s/mm2) compared to LTE (20‐32 directionsb<=4000s/mm2), to provide a rotationally invariant signal powder average, making it more efficient for achieving rotational invariance. Figure 1000<b<10000s/mm2). This was obtained using the method proposed by Szczepankiewicz et al.7000<b<10000s/mm2), the minimum number of encoding directions for rotational invariance is 45 for PTE and almost 80 for LTE.Szczepankiewicz et alα using LTE compared to PTE. An insufficient number of diffusion directions in powder averaging may cause the break of power‐law scaling. Therefore, we have to consider this when computing a powder average at very high b‐values. In Figure α‐values deviate considerably from the theoretical value . The deviation is most likely attributable to the non‐zero perpendicular diffusivity, and also the shrinkage factor, η, chosen for the simulations. In Figure η = 1.5 andDe⊥=0.75μm2/ms matching the results of simulations in.α, versus “still water” (a.k.a. “dot”) signal fraction for PTE and LTE on the simulated data withD⊥=0.75(μm2/ms). Note that over thef3 range of0<f3<0.02, the α for LTE doesn’t change by more than two percent, and thus is relatively insensitive to the presence of the still water fraction. In contrast, the PTE profile shows a much stronger dependence on the dot water fraction, with a rapid deviation from the “pure stick”, α‐value of 1, as the dot fraction increases.Figure α in the presence of a spherical compartment  with a radius ofRs=8μm. The estimated values of alpha from these simulations are in the range of 1.2‐1.5, increasing monotonically withf3. This range is remarkably close to the values found in vivo in gray matter, which were in the range 1.2‐1.7 ⟩)/(2/π⟨MB(x)⟩) where 〈.〉 denotes the average operator. The estimation of the signal was performed using the average of several ROIs (with 4 voxels) with a high direction‐averaged signal,MS(x), for the same b‐value. . The parameter of noise σ is estimated from only noise pixels in the background, where the signal is known to follow a Rayleigh distribution. Using the mean of a Rayleigh,E{M(x)}=π/2σ, we can estimateσ^=2/π⟨MB(x)⟩. SNR in WM ranged from 7.5 to 10.3 forb=10000s/mm2 and between 130 and 150 for the non‐diffusion weighted image (b = 0).A rough estimation of the SNR was performed, using pixels from the signal area and from the background,b ≤ 10 000), the FA and α map, the power‐law fit over white matter voxels, and the histogram of the α values in white matter, gray matter, CSF. For high b‐values (7000<b<10000s/mm2), the amount of the signal is considerable compared to the noise and the white matter structure is completely clear in the images because of high SNR.Figure α ≈ 1 which confirms the validity of the signal approximation using the first term in Equation The results show that the data are well described by power‐law behavior, with β is estimated from the fitting of equationS/S0=βb-α and based on Equation β≈f/Da||. In Figure β = 0.31. If we assume the intracellular signal fraction, f, is around 0.6 then the intra‐neurite diffusivityDa|| will be around2μm2/ms, which is feasible. To segment the brain image into different tissues, we used FAST (FMRIB’s Automated Segmentation Tool) in FSL.α value is close to one, supporting the theory. In gray matter and CSF, the exponent is larger . According to the theory outlined above, this would be consistent with a lack of pure “stick‐like” geometry in these tissue components. The spatial resolution of the data must be recognized, that is, with 4 mm isotropic voxels, obtaining a “pure” GM signal and “pure” CSF signal is challenging. It is likely that the intermediate exponent in the GM between that of the WM and CSF is partly attributable to a partial volume effect, and partly attributable to the inadequacy of the model for gray matter architecture. The α‐value in the gray matter seems surprising because a substantial portion of gray matter is composed of neurites where the stick model seems plausible. The deviation away from an α‐value of 1 could, however, potentially be explained by differences in water exchange times between white and gray matter. For example, if the exchange time in gray matter is comparable to the diffusion time of our experiment, perhaps as a result of high permeability (compared to in white matter), then the “stick‐like” behavior would not be observed, leading to a deviation of the α‐value away from unity. The exponent in gray matter is similar to the one obtained using the combination of “stick + sphere”.The constant term α in white matter, gray matter and CSF for two different subjects. The mean value in WM is around one, in the gray matter it is around 1.5 and for CSF around 2.Table 5s/mm2. In white matter, the average value of the estimated exponent is around one; and (2) proof that there are only 3 specific conditions under which a power‐law exists (for axisymmetric b‐tensor): pure LTE or PTE for pure stick‐like geometry and pure LTE for pure pancake‐like geometry. To the best of our knowledge, no pure pancake‐like geometries exist in the human brain and so in vivo validation of this latter result is impossible.The main findings of this paper are twofold: (1) confirmation in silico and in vivo, of a power‐law relationship between the direction‐averaged DWI signal and the b‐value using PTE, as given by Equation Returning to the case of a power‐law with PTE, for smaller b‐values, this behavior must break down as the DWI signal of PTE cannot be approximated by Equation The exponent of approximately one for white matter using PTE is consistent with the large b‐value limit  predicted for a model of water confined to sticks Equation .b-1/2‐scaling for LTE has previously been suggested byb for large b. Some other models,TheS∼b-1 for PTE, this power‐law relationship is also reported by Herberthson et al.α value for PTE is much more sensitive to the inclusion of a still‐water compartment than LTE. If using LTE alone, one might erroneously conclude from an alpha value very close to 0.5, that only stick‐like geometries exist—even in the presence of a non‐negligible dot fraction. In contrast, as seen in Figure α is only close to 1 when the still‐water component is zero, which confers an advantage of PTE over LTE for identifying pure stick‐like geometry. This likely arises because at a given high b‐value the proportional contribution to the total signal from the dot‐compartment is larger for the PTE signal (decays as 1/b) than it is for the LTE signal (decays as1/b). One might therefore consider using PTE alone for identifying pure stick‐like geometry. However, given that the SNR per unit b is, by definition, much lower with PTE than with LTE, we recommend that PTE and LTE are used in combination as a way of “cross‐validating” pure stick‐like geometry. Finally, we observed a larger alpha value in the gray matter than in white matter. This difference in exponents was previously reported for LTE by McKinnon et al,This work interprets the diffusion‐weighted MRI signal decay at high b‐values in the form of6s/mm2. In white matter, the in vivo exponent characterizing this decrease is close to one‐half, for LTE and one for PTE. These experimental results are consistent with theoretical predictions for the signal decay at large b‐values for tissue in which axonal water diffusion is confined to sticks when there is no sensitivity to the axonal diameter, undulation, curvature and so on. Any sensitivity to the diameter or curvature of axon, will change this power law. Obtaining an exponent of −1 for PTE and −1/2 for LTE could provide useful cross‐validation of the presence of stick‐like geometries in tissue. A complete analysis of the power‐law dependencies of the diffusion‐weighted signal at high b‐values has been performed. Only two forms of encoding result in a power‐law dependency, pure linear and pure PTE. The different exponents of these encodings could be used to provide independent validation of the presence of stick‐like geometries in vivo where, due to the slower decay, LTE is the most SNR efficient method. Deviation from the 1/√b power‐law in “stick‐like” geometries has been used recently to demonstrate sensitivity to the perpendicular diffusivity inside axons,b, that has previously only been reported theoretically for PTE. The power‐law relationship in PTE was observed over the b‐value range of 7000 to 10 000 s/mm2. We also showed that a power‐law relationship only exists in an extremely limited set of conditions: 1. The substrate under investigation has “stick‐like” geometry and the b‐tensor shape is purely linear  or purely planar  or 2. The substrate under investigation has "pancake‐like" geometry and the b‐tensor shape is purely linear. A power law will not exist for any other axysymmetric b‐tensor. The effect of dot and spherical compartments on the signal decay was also investigated. The results show that LTE is not sensitive to small contributions of dot and spherical compartment. In contrast, the exponent in PTE shows sensitivity to the presence of other such compartments.This work explores the diffusion‐weighted MRI signal decay at high b‐values for PTE and STE complementing and extending previous works on LTE. By exploring diffusion averaged signals, we conclude that the signal from STE decays exponentially for all the range of b‐values. The intra‐axonal signal does not decay exponentially as a function of b for linear and planar tensor encoding in high b‐values. The direction‐averaged DWI signal of PTE and LTE decreases with increasing b‐values as a power law, for b‐values ranging from 7000 to 10 000


Bladder cancer is one of the most common cancers among men in industrialized countries and on the global level incidence and mortality rates are increasing. In spite of progress in surgical treatment and chemotherapy, the prognosis remains poor for patients with muscle-invasive bladder cancer. Therefore, there is a great need for the development of novel therapeutic approaches. The human amniotic membrane (hAM) is a multi-layered membrane that comprises the innermost part of the placenta. It has unique properties that make it suitable for clinical use, such as the ability to promote wound healing and decrease scarring, low immunogenicity, and immunomodulatory, antimicrobial and anticancer properties. This study aimed to investigate the effect of (i) hAM-derived cells and (ii) hAM scaffolds on the growth dynamics, proliferation rate, and invasive potential of muscle-invasive bladder cancer T24 cells. Our results show that 24 and 48 h of co-culturing T24 cells with hAM-derived cells (at 1:1 and 1:4 ratios) diminished the proliferation rate of T24 cells. Furthermore, when seeded on hAM scaffolds, namely (1) epithelium of hAM (e-hAM), (2) basal lamina of hAM , and (3) stroma of hAM (s-hAM), the growth dynamic of T24 cells was altered and proliferation was reduced, even more so by the e-hAM scaffolds. Importantly, despite their muscle-invasive potential, the T24 cells did not disrupt the basal lamina of hAM scaffolds. Furthermore, we observed a decrease in the expression of epithelial-mesenchymal transition (EMT) markers N-cadherin, Snail and Slug in T24 cells grown on hAM scaffolds and individual T24 cells even expressed epithelial markers E-cadherin and occludin. Our study brings new knowledge on basic mechanisms of hAM affecting bladder carcinogenesis and the results serve as a good foundation for further research into the potential of hAM-derived cells and the hAM extracellular matrix to serve as a novel bladder cancer treatment. Approximately 549,400 people were diagnosed with bladder cancer worldwide in 2018 and as its incidence continues to increase, bladder cancer is classified among the five most common malignancies in industrialized countries . OverallThere are two main clinical phenotypes of bladder cancer, namely non-muscle-invasive bladder cancer and muscle-invasive bladder cancer. At initial diagnosis, 75% of cases are non-muscle invasive bladder cancer and 25% are muscle-invasive bladder cancer. Moreover, 50–70% of patients with non-muscle-invasive bladder cancer have recurrences after surgical removal of the primary tumor, and 10–20% of those also progress to muscle-invasive bladder cancer . The devThe human amniotic membrane (hAM) is the innermost layer of the fetal membranes, which protects the embryo and later the fetus. hAM is composed of a monolayer of human amniotic epithelial cells (hAEC), the basal lamina and thick avascular stroma, which is further divided into the compact layer, a layer of human amniotic mesenchymal stromal cells (hAMSC) and a spongy layer . Moreove1. The use of hAM is relevant also in the field of urology, which has been demonstrated by several in vitro and in vivo studies. Previously we have shown that hAM as a scaffold enables the development of tissue-engineered urothelium, which is in molecular and ultrastructural properties comparable to native urothelium  were collected from healthy women serologically negative for HIV, hepatitis B and C, after vaginal delivery or cesarean section at term after obtaining informed written consent according to the guidelines set by the Comitato Etico Provinciale of Brescia number NP 2243 (19/01/2016), Italy. For the preparation of primary urothelial cells, porcine urinary bladders were obtained from a local abattoir. The experiments were approved by the Veterinary Administration of the Slovenian Ministry of Agriculture and Forestry in compliance with the Animal Health Protection Act and the Instructions for Granting Permits for Animal Experimentation for Scientific Purposes (U34453-15/2013/2).The use of hAM was approved by the National Medical Ethics Committee of the Republic of Slovenia (decree numbers 43/12/09 and 0120-179/2018/5) and prepared according to the standard procedures . Briefly4 cells/cm2 and cultured at 37°C and 5% CO2 in culture medium A-DMEM+F12 as described previously  was used as a model of muscle-invasive bladder cancer cells (passages 5–30). The T24 cells were seeded at seeding density of 5 × 10eviously . The cul4 cells/cm2 and cultured at 37°C and 5% CO2 in RPMI completed medium composed of RPMI 1640 medium  supplemented with 10% fetal bovine serum (FBS) , 2 mM L-glutamine , 100 U/mL penicillin , and 100 μg/mL streptomycin .The CFPAC-1 cell line that originated from human pancreatic adenocarcinoma , Saos-2 cell line that originated from human bone osteosarcoma , and human fibroblasts isolated from a skin biopsy. Skin-derived fibroblasts were obtained after informed consent as described by 5 cells/cm2. When the NPU cells reached confluence, they were cultured in the culture medium without serum, but with a physiological calcium concentration of 2.7 mM. The NPU cells were maintained at 37°C and 5% CO2 for 3 weeks. The experiments were approved by the Veterinary Administration of the Slovenian Ministry of Agriculture and Forestry in compliance with the Animal Health Protection Act and the Instructions for Granting Permits for Animal Experimentation for Scientific Purposes.Primary normal porcine urothelial cell cultures (NPU cells) were established as described previously  and cultg) and hAMSC were passed through 100-μm and 70-μm cell strainers and then centrifuged. Then hAMSC (p0) were plated (seeding density 1 × 104 cells/cm2) and cultured at 37°C and 5% CO2 in DMEM complete medium supplemented with 10% heat-inactivated fetal bovine serum , 2 mM L-glutamine , 100 U/ml penicillin and 100 μg/ml streptomycin or cryopreserved in 10% DMSO (Sigma-Aldrich) supplemented with 90% FBS until use. When hAMSC reached confluence, they were subcultured at a seeding density 1 × 104/cm2.Isolation of hAEC and hAMSC from human term placentas was performed as described previously . Brieflyg for 10 min and the cell suspensions were filtered through a 70 μm cell strainer , centrifuged again, plated  and cultured at 37°C and 5% CO2 in DMEM/F12 complete medium. When hAEC reached confluence, they were subcultured at a seeding density 4 × 104/cm2.For hAEC isolation, hAM was cut into pieces (15 cm × 15 cm) which were incubated for 10 min at 37°C in PBS containing 0.5 mM EDTA and 100 U/ml penicillin and 100 μg/ml streptomycin, followed by a 5-min incubation in 1× trypsin/EDTA solution  at 37°C. The debris was discarded and the pieces were incubated for 10 min at 37°C in 1× trypsin-EDTA solution, followed by washing in PBS and they were digested a second time in 1× trypsin/EDTA for 10 min at 37°C. Cells from digestions were collected and centrifuged at 300 For phenotype evaluation, hAEC and hAMSC were trypsinized and then washed with FACS buffer  and 0.1% FBS (Sigma-Aldrich) in PBS), followed by a 20-min incubation at 4°C with anti-human fluorescein isothiocyanate- (FITC) or phyoerythrin- (PE) or allophycocyanin (APC)-conjugated antibodies or isotype controls (specified bellow) with 20 ml/ml polyglobin  prepared in PBS with 1% BSA to block non-specific binding. After incubation, the cells were washed with FACS buffer and the dead cells were eliminated by the propidium iodide (PI) staining. The following clones of the monoclonal antibodies were used: CD73 (clone AD2), CD90 (5E10), CD45 (HI30), CD105 (266), CD13 (L138), CD66b (G10F5) , and CD324 (67A4) .4 cells/well and 4 × 104 cells/well. For non-contact experiments, hAMSC, hAEC, CFPAC-1, Saos-2, and skin-derived human fibroblast cells were plated in the upper compartment  of transwell chambers (1 × 104 cells/transwell and 4 × 104 cells/transwell of RPMI complete medium). hAMSC, hAEC, CFPAC-1, Saos-2, and fibroblast cells were gamma-irradiated to block their proliferation ensuring the maintenance of the correct ratio during co-culture . Therefore, any proliferation observed would be attributed only to the T24 cell line, which was added after 24 h to each well in direct contact with hAMSC, hAEC, CFPAC-1, Saos-2, and skin-derived human fibroblast cells or in the lower compartment of transwell chambers (seeding density 1 × 104 cells/well in A-DMEM+F12 complete medium). After additional 24 and 48 h in culture, the proliferation of cancer cells was assessed by adding [3H]-thymidine  for 16–18 h and then by harvesting the cells with a Filtermate Harvester . Thymidine incorporation was measured by using a microplate scintillation and luminescence counter .The effect of amniotic-derived cells on the proliferation of T24 cells was evaluated either in direct contact or with physical separation using transwell chambers, as described previously . BrieflyThermolysin from Bacillus thermoproteolyticus rokko, Sigma-Aldrich, United States) at 37°C. After incubation, d-hAM scaffolds were rinsed with PBS and incubated for 15 min at room temperature on a shaker to remove cellular debris.Human amniotic membrane was manually separated from the chorion and washed with sterile phosphate-buffered saline (PBS), which contained antibiotics  and an antimycotic . Then hAM was cut into pieces (4 cm × 4 cm) and cryopreserved at –80°C in MEM  and glycerol (volume ratio 1:1) until use. After thawing at room temperature, hAMs were washed with sterile PBS (two times for 5 min) and A-DMEM+F12 culture medium (two times for 5 min). Next, the hAMs were fastened in membrane holders of 14 or 25 mm in diameter  with the amniotic epithelium facing up  or with the hAM stromal side facing up . To obtain d-hAM, hAEC were removed by a 15 min incubation in the proteolytic enzyme thermolysin  and transmission and scanning electron microscopy.Before seeding, T24 cells were labeled with a fluorescent dye DiI (Invitrogen). Briefly, T24 cells were incubated in a mixture of the DiI dye  and A-DMEM+F12 culture medium (1:1000) and incubated at 37°C for 30 min. Next, T24 cells were rinsed with culture medium (three times for 5 min). Labeled T24 cells were seeded on hAM scaffolds and synthetic scaffolds  at a seeding density of 5 × 10To evaluate the growth of T24 cells on hAM scaffolds and synthetic scaffolds, T24 cells were observed with an inverted fluorescence microscope Eclipse TE300 . Namely, on days 1, 2, 3, 7, 14, and 21 we took seven images of each scaffold at random positions. The area of the hAM scaffolds covered with T24 cells was evaluated with ImageJ software , measuriThe proliferation rate of T24 cells grown on hAM and synthetic scaffolds was analyzed by labeling the proliferating cells with the Click-it Plus EdU Alexa Fluor 488 Imaging Kit  and subsequent analysis with ImageJ software. Briefly, 24 h before the analysis the T24 cells grown on hAM and synthetic scaffolds were incubated in the culture medium A-DMEM+F12 supplemented with 10 μM 5-ethynyl-2 ′-deoxyuridine (EdU). To evaluate the proliferation of hAM-derived cells, the e-hAM scaffolds alone were incubated in the culture medium A-DMEMCF12 supplemented with 10 μM EdU. After 24 h, hAM scaffolds and synthetic scaffolds were fixed for 15 min with 4% formaldehyde at room temperature, washed three times with 3% BSA/PBS, permeabilized with 0.5% Triton-X-100 in PBS and incubated at room temperature for 20 min. After permeabilization, samples were washed three times with 3% BSA/PBS. To stain the proliferating T24 cells, Click-it Plus reaction buffer containing AlexaFluor picolyl azide was prepared according to the manufacturer’s instructions and samples were incubated with the reaction buffer at room temperature for 30 min. Afterward, samples were washed three times with 3% BSA/PBS, nuclei were stained with DAPI and samples were examined with a fluorescence microscope AxioImager.Z1 equipped with ApoTome . Furthermore, 10 images for each sample were taken and the ratio of proliferating cells was analyzed with the ImageJ software.To prepare paraffin sections, hAM scaffolds with T24 cells were fixed with 4% formaldehyde (w/v) overnight and then paraffin sections were prepared as previously described . BrieflyFor immunofluorescence, hAM scaffolds and synthetic scaffolds with T24 cells were fixed in (a) 4% formaldehyde (w/v) for 15 min, washed in PBS for 30 min, embedded in OCT and then cryosections were prepared, and (b) in ice-cold absolute ethanol for 20 min at room temperature. After blocking in 3% BSA/PBS for 45 min, samples were incubated in polyclonal anti-collagen IV antibody , rabbit polyclonal anti-N-cadherin antibody , rabbit polyclonal anti-occludin antibody , mouse polyclonal anti-E-cadherin antibody  and rabbit polyclonal anti-Snail + Slug antibody  overnight at 4°C. As a positive control for occludin and E-cadherin stainings, the NPU cells were analyzed. The next day samples were washed in PBS and then incubated in goat anti-rabbit and goat anti-mouse IgG conjugated with Alexa Fluor 488 or Alexa Fluor 555 for 2 h at room temperature . Afterward, DAPI was applied to stain nuclei. Samples were examined with the inverted fluorescence microscope Eclipse TE300  and a fluorescence microscope AxioImager.Z1 equipped with ApoTome .20, 0.5 M TRIS HCl, 10% Sodium Dodecyl Sulfate (SDS) supplemented with a cocktail of protease and phosphatase inhibitors . Total protein quantity was determined using the Pierce BCA Protein Assay Kit . Protein extracts (50 μg) were separated using 4–20% Novex WedgeWell Tris-Glycine Gels  and then transferred onto the nitrocellulose membranes . The membranes were blocked with 5% skim milk in 0.1% Tris-buffered saline/Tween 20 (TBS-T) for 1 h at room temperature. Next, the membranes were incubated overnight with primary antibodies: anti-N-cadherin , anti-Snail + Slug , anti-actin , anti-collagen IV  at 4°C with gentle shaking. Next day, the membranes were washed with TBS-T and incubated with HRP-conjugated goat anti-rabbit IgG antibody  for 1 h at room temperature with gentle shaking. Finally, SuperSignal West Pico Chemiluminescent Substrate  was used to visualize the bands. Densitometric analysis was performed using the Image J software. Actin served as a loading control.For Western blot analysis, T24 cells grown on hAM and synthetic scaffolds were lysed in ice-cold extraction buffer, comprised of a deionized HHuman amniotic membrane scaffolds and synthetic scaffolds with T24 cells were prepared for transmission and scanning electron microscopy as described previously . Brieflyt-test or two-way analysis of variance (ANOVA) when appropriate, adjusted by Tukey’s or Sidak’s method. Statistical analysis was performed using Prism 8 . p-values of <0.05 were considered statistically significant.All data were calculated from 3 to 5 biological samples of hAM and at least 3–10 technical repeats for each biological sample. Data are presented as mean ± SE. Statistical analysis was performed using a two-tailed Student’s The authors declare that all data supporting the findings of this study are available within the manuscript. All information about the materials and methods used are available also in the Protocols.io database .p < 0.05) and 11% (ratio 1:1), respectively. Moreover, when grown in co-culture with hAEC, the percentage of proliferating T24 cells significantly decreased by approximately 52%  and 30% , respectively (p < 0.001) and 21% , while hAEC inhibited T24 cell proliferation by 57%  and 31%   .To investigate if any anti-proliferative effects were observed also in absence of cell-contact, co-cultures were physically separated by a transwell system. In this non-contact setting, we did observe a slight decrease of T24 proliferation after both 24 h  and 48 hp < 0.001), but not when cultured at 1:1 ratio   and Saos-2 cells which have an epithelial-like morphology similar to hAEC, or with skin-derived fibroblasts which are stromal cells similar to hAMSC. Co-culture with CFPAC-1 cells for 24 h  and 48 hificant) . Insteadificant)  and 48 hificant) , at bothWhen cultured in the transwell system, CFPAC-1, Saos-2, or skin-derived human fibroblast cells were unable to decrease T24 cell proliferation at both ratios tested and both after 24 h  and 48 hp < 0.001). Moreover, on the e-hAM and s-hAM scaffolds the T24 cells grew in a monolayer or, in rare exceptions, in two layers . Our results show that hAM basal lamina remained intact even after 3 weeks in culture with T24 cells in all hAM scaffolds. The T24 cells did not invade the extracellular matrix of any of the hAM scaffolds .To further evaluate the invasive potential of T24 cells grown on hAM scaffolds, we examined the expression of N-cadherin, a hallmark of epithelial-to-mesenchymal transition (EMT), which results in the acquisition of an aggressive tumor phenotype with enhanced migratory and invasive capacity . We haveNext, we examined the expression of transcription factors Snail and Slug, which are markers of EMT  and are Next, we examined the expression of epithelial markers, such as E-cadherin and occludin and performed ultrastructural analysis of T24 cells. We found that individual T24 cells expressed E-cadherin when grown on e-hAM and s-hAM scaffolds . E-cadheSimilarly, individual T24 cells grown on hAM scaffolds also expressed occludin . On the The ultrastructural analysis of T24 cells on hAM and synthetic scaffolds showed that in general, T24 cells were more tightly attached to each other when grown on the hAM scaffolds compared to synthetic scaffolds, where large intercellular spaces were observed . MoreoveDespite high initial response rates to multiagent chemotherapy, the median survival for patients with muscle-invasive bladder cancer is 15 months and the 5-year survival rate is only 15% , 2005, bHerein, we show that both hAMSC and hAEC reduce the proliferation of T24 cells, when cultured in direct contact with T24 cells and especially when cultured at a 1:4 T24:hAM cell ratio.Our results show some heterogeneity between different biological samples, which can be attributed to placenta donor heterogeneity and also to heterogeneity among cells derived from different parts of the hAM. As 0/G1 phase and prevention of cell cycle progression to S phase , confirm that the decrease in proliferation of T24 cells in presence of hAM-derived cells is not due to a simple decreased surface area available for cell growth or to the irradiation process. When T24 cells were cultured in contact with Saos-2 cells for 48 h and at a ratio of 1:4, or when T24 cells were cultured with skin-derived human fibroblasts, we observed a reduction of their proliferation, indicating that the anti-proliferative effects of hAM-derived cells are in common with other cell types of mesodermal origin. The inhibitory effects of human fibroblasts are not surprising considering that they share immunosuppressive properties similar to mesenchymal stromal cells . Moreove S phase . Similar S phase . Additio S phase . To concFurther, to address if the anti-proliferative effect on T24 was mediated by secreted factors, we prevented the cell contact between T24 and hAM-derived cells through the use of transwell system. In this experimental setting, we did not observe a significant decrease of T24 proliferation, suggesting the need of cell-contact in the hAM-derived cells reduction of T24 cell proliferation. These results are in accordance with previously reported data, showing only a mild attenuation of cell growth of breast cancer cells induced by human umbilical cord MSC when cultured in transwell system, compared to the predominantly effect observed in direct cell-contact , or withTo test whether hAM as a whole, i.e., hAM extracellular matrix with hAM cells, also has anticancer effects, we seeded cancer urothelial T24 cells on the hAM scaffolds. Our results show that T24 cells possess an altered growth dynamic when seeded on hAM scaffolds. Furthermore, in concordance with results of growth dynamics, we have shown that hAM scaffolds diminish the proliferative potential of T24 cells.The growth-inhibitory effect of hAM scaffolds was most prominent in the first 3 days after seeding and it subsequently decreased. However, it is important to point out that the beneficial effects of hAM scaffolds persisted for at least 3 weeks after seeding . We assume that most of the various molecules responsible for the anticancer effect were rinsed and thus removed from the hAM scaffolds in the first days of culture, first due to rinsing with PBS during the preparation of scaffolds, and then during replenishing of culture medium during culture on the scaffolds. Moreover, this could also explain why d-hAM scaffolds had the lowest effect on the T24 cells since the preparation of d-hAM scaffolds includes additional rinsing steps due to the treatment with thermolysin and additionally, also depletion of hAEC in d-hAM scaffolds could contribute to lessened growth-inhibitory effect of d-hAM scaffolds.The T24 cell line  is derived from a patient with a transitional cell carcinoma of the urinary bladder. This muscle-invasive cell line has been extensively used in bladder cancer research and several studies evaluated its invasiveness . For exaIn solid cancers local invasion and metastasis account for more than 90% of mortality . FurtherFurthermore, as the expression of N-cadherin is a hallmark of muscle-invasive cancer cells, we evaluated its expression in T24 cells grown on hAM scaffolds and the synthetic scaffolds after 3 weeks in culture. Our results show that hAM scaffolds diminish the expression of N-cadherin in T24 cells, as only a few of the T24 cells grown on hAM scaffolds expressed N-cadherin, while all T24 cells grown on the synthetic scaffolds expressed N-cadherin. Furthermore, even though N-cadherin is junctional protein and is typically expressed in lateral plasma membrane of adjacent cells, in most T24 cells grown on hAM scaffolds, its expression was mostly present in the cytoplasm, and not at the cell periphery.It is known that N-cadherin is required for pro-migratory signaling and cell-cell adhesion between invasive cells . Shih anSnail and Slug are zinc-finger transcription factors that serve as suppressors of E-cadherin transcription and promote EMT . FurtherImportantly, we have also shown that individual T24 cells grown on hAM scaffolds expressed adherence junctional protein E-cadherin and occludin, one of the key components of tight junctions, which are otherwise not expressed by the T24 cells. Furthermore, T24 cells grown on hAM scaffolds were more tightly attached to each other when grown on the hAM scaffolds and also individual T24 cells on the hAM scaffolds developed some signs of the apico-basal polarity. Therefore, these changes in ultrastructure could be associated with cell cycle arrest and also decreased migration and invasion potential of muscle-invasive bladder cancer cells.Radical cystectomy is the standard of care for muscle-invasive bladder cancer. Besides being associated with considerable morbidity and mortality, this procedure also results in a lower quality of life. New approaches allowing organ preservation are being developed, most of them including chemotherapy and radiation after aggressive transurethral tumor resection .in vivo by several researchers, used hAM for augmentation after partial cystectomy in rat and dog models. Importantly, researchers report the successful regeneration of bladder mucosa and neovascularization of bladder tissue , and Comitato Etico Provinciale of Brescia number NP 2243 (19/01/2016), Italy. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by The experiments were approved by the Veterinary Administration of the Slovenian Ministry of Agriculture and Forestry in compliance with the Animal Health Protection Act and the Instructions for Granting Permits for Animal Experimentation for Scientific Purposes.TZR, UDJ, LT, AJ, MM, EV, PBS, and MK performed the experiments. TZR, UDJ, LT, AJ, MM, EV, PBS, ARS, OP, and MK interpreted the results, reviewed and edited the manuscript, and approved the final manuscript. TZR wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.