To assess the diagnostic weight of sequence-specific magnetic resonance features in characterizing clinically significant prostate cancers (csPCa).We used a prospective database of 262 patients who underwent T2-weighted, diffusion-weighted, and dynamic contrast-enhanced (DCE) imaging before prostatectomy. For each lesion, two independent readers  prospectively defined nine features: shape, volume (V_Max), signal abnormality on each pulse sequence, number of pulse sequences with a marked (S_Max) and non-visible (S_Min) abnormality, likelihood of extracapsular extension (ECE) and PSA density (dPSA). Overall likelihood of malignancy was assessed using a 5-level Likert score. Features were evaluated using the area under the receiver operating characteristic curve (AUC). csPCa was defined as Gleason ≥7 cancer (csPCa-A), Gleason ≥7(4+3) cancer (csPCa-B) or Gleason ≥7 cancer with histological extraprostatic extension (csPCa-C),For csPCa-A, the Signal1 model (S_Max+S_Min) provided the best combination of signal-related variables, for both readers. The performance was improved by adding V_Max, ECE and/or dPSA, but not shape. All models performed better with DCE findings than without.When moving from csPCa-A to csPCa-B and csPCa-C definitions, the added value of V_Max, dPSA and ECE increased as compared to signal-related variables, and the added value of DCE decreased.For R1, the best models were Signal1+ECE+dPSA , Signal1+V_Max+dPSA (AUC = 0.823 [95%CI:0.760–0.893]) and Signal1+ECE+dPSA [AUC = 0.840 (95%CI:0.774–0.907)] for csPCa-A, csPCA-B and csPCA-C respectively. The AUCs of the corresponding Likert scores were 0.844 , 0.841 ) and 0.849 , respectively.For R2, the best models were Signal1+V_Max+dPSA , Signal1+V_Max (AUC = 0.813 [95%CI:0.746–0.882]) and Signal1+ECE+V_Max (AUC = 0.843 [95%CI: 0.781–0.907]) for csPCa-A, csPCA-B and csPCA-C respectively. The AUCs of the corresponding Likert scores were 0. 829 , 0.790 ) and 0.808 ), respectively.Combination of simple variables can match the Likert score’s results. The optimal combination depends on the definition of csPCa. Multiparametric Magnetic Resonance (MR) imaging can detect clinically significant prostate cancer (csPCa) with good accuracy –7. UnforBecause it is impossible to definitely characterize as benign or malignant all prostate focal lesions, the use of a 5-point subjective score has been widely encouraged to describe the level of suspicion of a given lesion , 9. ThisIn 2012, the European Society of Urogenital Radiology (ESUR) endorsed the Prostate Imaging Reporting and Data System (PIRADS) score . It was In 2015, the ESUR and the American College of Radiology endorsed the so-called PIRADS v2 score , 24 thatThe PIRADS scores were not based on an analysis of a large dataset, but rather were a result of expert opinion. As others , we hypoAs of September 2008, all patients who underwent prostate multiparametric MR imaging before radical prostatectomy at our institution (Hospices Civils de Lyon) were proposed to have their radiologic and pathologic data entered in a prospective database approved by our Institutional Review Board (Comité de Protection des Personnes Sud-Est IV). All patients gave written informed consent. The database was used for other studies evaluating prostate cancer detection rates  and accuMR examinations comprised at least T2W, DW and DCE imaging at 1.5T and 3T, but protocol parameters varied as per the standard of care at the time of the examination . Upon inFirst, readers delineated each lesion on all three MR pulse sequence images using the Osirix software . This allowed the calculation of the lesion volume on each MR pulse sequence.Second, readers specified the lesion shape on the three MR pulse sequences images, using the following list: not visible; ill-defined area with indistinct margins; linear lesion perpendicular to the capsule; linear lesion parallel to the capsule; triangular lesion; nodular lesion without mass effect on the adjacent TZ or capsule; nodular lesion with mass effect on the adjacent TZ or capsule.Third, they separately noted the degree of signal abnormality on T2W, DW and DCE images using the following qualitative 4-level scale: 0, not visible; 1, mild abnormality; 2, moderate abnormality; 3, marked abnormality.Fourth, they assessed the likelihood of extracapsular extension (ECE) using a subjective 5-level score: 1, definitely absent; 2, likely absent; 3, indeterminate; 4, likely present; 5, definitively present.Finally, they assessed the likelihood of malignancy of each lesion, using the following subjective 5-level Likert score: 1, definitely benign; 2, likely benign; 3, indeterminate; 4, likely malignant; 5, definitely malignant. Because a Likert score of 1/5 was used only in areas with normal appearance on all pulse sequences, focal lesions had, by definition, a Likert score ≥2/5.Whole-mount sections of prostatectomy specimens were obtained every 3 mm according to guidelines . A singlWe first assessed the performance of the 9 variables decribed in Then we assessed the performance of three combinations of variables related to the lesions’ signal. Signal1 model comprised S_Max and S_ Min, Signal2 model comprised S_Max, S_ Min and S_DW, and Signal3 model comprised S_T2, S_DW, S_DCE. Signal1a, Signal2a and Signal3a models used the three MR pulse sequences. Signal1b, Signal2b and Signal3b models did not use DCE imaging. In Signal2a model, S_Max and S_Min used only the results of T2W and DCE imaging since DW findings were coded by S_DW. In Signal2b model, S_Max and S_Min used only the results of T2W imaging. These models were compared to S_Max as a stand-alone, with (S_Maxa) and without (S_Maxb) use of DCE imaging.Signal1 model was selected for the rest of the analysis. The variables Shape, ECE, Vmax and dPSA were sequentially added to it. Each resulting multivariable model was assessed first using the findings of the three MR pulse sequences and then without DCE imaging.The 9 individual variables, the Signal1, Signal2 and Signal3 models, and the combinations of the Signal1 model and the variables Shape, ECE, Vmax and dPSA were also assessed using two alternative definitions for csPCa: (i) csPCa-B: Gleason ≥7(4+3) (ISUP grade group ≥3) and (ii) csPCa-C: Gleason ≥7 (ISUP Grade group ≥2) and histologically-proven extraprostatic extension .In the database, extraprostatic extension was assessed at the lesion level . This allowed combining the Gleason score and extraprostatic extension features at the lesion level.http://cran.r-project.org).The analysis units were the lesions identified by each reader. The probability that a lesion corresponded to a csPCa was modelled using a logistic regression for each of the 9 studied variables, and for the different combinations of variables described above. Receiver operating characteristic (ROC) curves were built using the probabilities of csPCa predicted by the different models. The diagnostic performance of each variable and combination of variables was quantified using the area under the ROC curve (AUC). Because the same data were used for developing the models and assessing their performance, the AUC can be overestimated. This is often referred to as optimism. We therefore used a bootstrap procedure to estimate a corrected AUC as proposed by Harrel  S1 Appe. To takeAt the time of analysis, the database contained 262 patients imaged between September 2008 and February 2013. MR imaging was performed at 1.5T on scanner A (n = 72) or at 3T on scanner B (n = 113) or C (n = 77). The patients median age, PSA level and PSA density at the time of imaging were 62 years (interquartile range (IQR), 58–66), 6.5 ng/mL  and 0.16 ng/mL/mL  respectively.R1 described 474 PZ lesions in 250 patients. Two lesions were excluded because of artefacts on DW imaging, leaving 472 lesions . R2 described 392 PZ lesions in 242 patients. Three lesions were excluded because of artefacts on DW imaging leaving 389 lesions  for R1 and 48.7% (191/389) for R2. The percentage of csPCa-B was 21.8% (103/471) for R1 and 25.8% (101/392) for R2. The percentage of csPCa-C was 20.8% (98/471) for R1 and 24.5% (96/392) for R2.For all models, AUC values were higher when DCE imaging was used, with a maximal ΔAUC of +0.039 for both readers.For R1, the Signal1a+ECE+dPSA model obtained the highest AUC (0.805 [95%CI: 0.757–0.866]). It performed better with use of DCE imaging, but the difference was not statistically significant (p = 0.104). As compared to Signal 1a model, Signal1a+ECE+dPSA model achieved a ΔAUC of +0.011, but the difference was not significant (p = 0.167).For R2, the Signal1a+Vmax+dPSA model obtained the highest AUC (0.790 [95%CI: 0.731–0.857]). It performed better with use of DCE imaging, but the difference was not statistically significant (p = 0.104). As compared to Signal 1a model, Signal1a+Vmax+dPSA model achieved a ΔAUC of +0.021, but the difference was not significant (p = 0.215).The AUC of the Likert score was 0.844 (95%CI: 0.806–0.877) for R1 and 0.829 (95%CI: 0.791–0.868) for R2. The ΔAUC with the best multivariable model  did not reach statistical significance .When DCE imaging was used, the addition of other variables to the Signal1a model tended to increase the AUC, with a maximal ΔAUC of +0.014 for R1 and +0.038 for R2. When DCE was not used, all multivariable models performed better than Signal1b model with a maximum ΔAUC of +0.033 for R1 and +0.069 for R2.For all models, AUC values were higher when DCE imaging was used, with a maximal ΔAUC of +0.035 for R1 and +0.032 for R2.The highest AUC values were obtained by the Signal1a+Vmax+dPSA model for R1 (0.823 [95%CI: 0.760–0.893]) and by the Signal1a+Vmax for R2 (0.813 [95%CI: 0.746–0.882]).The AUC of the Likert score was 0.841 (95%CI: 0.799–0.876) for R1 and 0.790 (95%CI: 0.742–0.841) for R2. The ΔAUC between the AUC of the best multivariable model and the Likert score was not significant, neither for R1 (p = 0.52) nor for R2 (p = 0.12).When DCE imaging was used, the addition of other variables to the Signal 1a model tended to increase the AUC, with a maximal ΔAUC of +0.031 for R1 and +0.076 for R2 . When DCAUC values tended to be higher when DCE imaging was used, with a maximal ΔAUC of +0.032 for R1 and +0.041 for R2. However, two models performed better without DCE imaging for reader 2, including the model providing the best AUC value.The highest AUC values were obtained by the Signal1a+ECE+dPSA model for R1 (0.840 [95%CI: 0.777–0.907]) and by the Signal1b+ECE+Vmax for R2 (0.843 [95%CI: 0.781–0.907]).The AUC of the Likert score was 0.849 (95%CI: 0.811–0.884) for R1 and 0.808 (95%CI: 0.764–0.845) for R2. The ΔAUC between the AUC of the best multivariable model and the Likert score was not significant for R1 (p = 0.49) but was significant for R2 (p = 0.006).The purpose of this study was not to build a new scoring system that could compete with existing ones, but rather to define the most informative MR features in characterizing csPCa in PZ, and to assess the relative diagnostic weight of these features, and how they could be optimally combined. Answering these questions is indeed mandatory if one wants to improve existing scores in the future.To achieve this purpose, we used a radiologic-pathologic database containing a detailed description of sequence-specific features of all lesions visible at pre-operative prostate multiparametric MR imaging. This description was made prospectively by two independent readers and was then compared to prostatectomy specimens findings used as reference.We used several definitions for csPCa since there is currently no consensus on this matter. As a primary objective, we defined csPCa as cancers with a Gleason score ≥7 because the metastatic and lethal potential of Gleason 6 cancers is low , and becUnsurprisingly, S_DW gave consistently better results than S_T2, and S_DCE for both readers, whatever the definition used for csPCa. This confirms that DW imaging is the most informative pulse sequence in PZ. Nonetheless, combining the results of the three pulse sequences into S_Max resulted in a substantial improvement in the diagnostic performance for both readers. This is in line with the good results obtained at the National Institute of Health (NIH) with an in-house score taking into account only the number of positive pulse sequences , 42, andThe Signal1-3 models consisted in three different combinations of the signal-based variables. They provided only marginal improvement as compared to S_Max. Particularly, the Signal2 model, that was an attempt to increase the diagnostic weight of DW imaging among the signal-based variables, failed to improve the characterization of csPCa. Thus, although DW imaging is the most informative pulse sequence in PZ, its optimal combination with the other pulse sequences remains to be defined.Because the Signal1 model tended to give the best results, it was selected for the next step that assessed the added value of variables that were not related to signal abnormalities. Three variables  showed consistent added value and all best multivariable models included at least one of them. Their added value over signal-based variables  tended to increase when DCE imaging was not used and when more stringent definitions of csPCa were used. Unsurprisingly, the diagnostic weight of ECE increased when the definition of csPCa included extraprostatic extension (csPCa-C), and the diagnostic weight of V_Max increased when the definition of csPCa was restricted to more aggressive tumors (csPCa-B instead of csPCa-A). Thus, an international consensus on the definition of csPCa is becoming crucial, since this will impact the scoring system to be used on multiparametric MR imaging. Interestingly, good results have recently been reported with a refinement of the NIH score combining ECE features and the number of positive pulse sequences . Our resTaking into account the shape of the lesions decreased the performance of almost all models. This strongly suggests that shape is not a good predictor of csPCa, even if the PIRADS v2 and other scoring systems , 17 use There is currently a controversy about the added value of DCE imaging, as compared to T2W and DW imaging. DCE imaging may indeed help detect small cancers, but may also increase the number of false positive findings , 44–47. In the last part of our study, we compared the best models to the Likert score prospectively assigned to each lesion. For the most experienced reader, the Likert score constantly outperformed the best model, even if the difference was never statistically significant and tended to decrease as more stringent definitions of csPCa were used. For the least experienced reader, however, the best model outperformed the Likert score for csPCa-B and csPCa-C, and the difference was statistically significant for csPCa-C. Most of the image features we used were subjective and this may be seen as a contradiction with our initial goal to obtain more objective scoring systems. Unless an entirely quantitative approach is used for all pulse sequences, subjective assessment of images remains unavoidable. Existing scoring systems share the same limitation, as shown by the PIRADS v2 score that distinguishes indistinct hypointense (score 2), mildly/moderately hypointense (score 3) or markedly hypointense (scores 4–5) lesions on ADC maps. However, our results suggest that breaking down the diagnostic process into separate features, and combining these features into predefined models may help less experienced readers better characterise MR lesions.Our study has some limitations.The description of the sequence-specific features was done prospectively. Although this could be seen as a strength of the study, it also induced two limitations. First, we were not able to compare the best models with the PIRADS v2 score that was not launched at the start of the study. However, our main purpose was not to compare our models to existing scores, but to understand the features’ relative weight in characterizing csPCa. Second, the features noted in the database for TZ lesions were mostly based on signal abnormalities. Features as homogeneous pattern, presence of a capsule, apical or anterior location, that are now known as major predictors of malignancy in TZ , 56 wereThe number of pulse sequences showing marked signal abnormality for a given lesion (S_max) was one the most informative variable for both readers, whatever the definition used for csPCa. A moderate improvement could be obtained by taking into account, in addition to S_max, the number of negative pulse sequences, the presence of extracapsular extension features, the volume of the lesion and the PSA density. The added value of the three latter variables depended on the definition used for csPCa and tended to increase when more stringent definitions were used. Removing DCE findings decreased performance in nearly all models, but the difference decreased when more stringent definitions were used for csPCa. Finally the Likert score outperformed the best multivariable models for the most experienced reader whatever the definition used for csPCa. For the other reader, the multivariable models outperformed the Likert score for csPCa-B and csPCa-C definitions, and the difference was significant for csPCa-C. This suggests that scoring systems based on semi-objective variables may help less-experienced radiologists.S1 TableTR: Repetition Time; TE: Echo time; PPA: pelvic phased array; T2w: T2 weighted imaging; Dw: Diffusion weighted imaging; DCE: dynamic contrast enhanced imaging.(DOCX)Click here for additional data file.S2 TableSd: standard deviation; IQR: interquartile range.(DOCX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.


Although starch consists of large macromolecules composed of glucose units linked by α-1,4-glycosidic linkages with α-1,6-glycosidic branchpoints, variation in starch structural and functional properties is found both within and between species. Interest in starch genetics is based on the importance of starch in food and industrial processes, with the potential of genetics to provide novel starches. The starch metabolic pathway is complex but has been characterized in diverse plant species, including pea.r locus (which conditions the round versus wrinkled seed phenotype). The genes with associated polymorphisms are involved in the substrate supply, chain elongation and branching stages of the pea carbohydrate and starch metabolic pathways.To understand how allelic variation in the pea starch metabolic pathway affects starch structure and percent amylose, partial sequences of 25 candidate genes were characterized for polymorphisms using a panel of 92 diverse pea lines. Variation in the percent amylose composition of extracted seed starch and (amylopectin) chain length distribution, one measure of starch structure, were characterized for these lines. Association mapping was undertaken to identify polymorphisms associated with the variation in starch chain length distribution and percent amylose, using a mixed linear model that incorporated population structure and kinship. Associations were found for polymorphisms in seven candidate genes plus Mendel’s The association of polymorphisms in carbohydrate and starch metabolic genes with variation in amylopectin chain length distribution and percent amylose may help to guide manipulation of pea seed starch structural and functional properties through plant breeding.The online version of this article (doi:10.1186/s12870-017-1080-9) contains supplementary material, which is available to authorized users. Pisum sativum L.), chickpea (Cicer arietinum L.), common bean (Phaseolus vulgaris) and lentil (Lens culinaris Medik.). The composition and nutritional qualities of pulses have been the subject of recent reviews , chain elongation [StSynII (rug5)] and branching [SBEI (r)].In this study, we focused on association mapping of variation in debranched starch CLD and %amylose with polymorphisms in 25 candidate genes representing 16 carbohydrate and starch metabolic enzymatic reaction classes Table . Using tn = 92) we employed, 2) the limited number (25) of candidate genes in the starch biosynthetic pathway that were characterised, and 3) that the candidate genes were partially sequenced, with a bias for intron-containing regions, therefore causal variants may have occurred outside the sequenced regions and may have been in only partial LD with variants within the sequenced regions. The genome-wide association study (GWAS) offers an alternate approach to the candidate gene-based approach for identifying genes associated with complex traits such as the composition of pea seeds, although GWAS is poor for detecting effects of minor alleles [The power of our study to identify sequence variants associated with starch CLD variation was limited. The limiting factors included: 1) the relatively small sample size  versus wrinkled (rr) lines. The mean proportion of intermediate length chains was increased in round seeded lines  also affected the mean proportion of intermediate length chains, which was higher on average for the lines with the G allele at that site.CLD affects gelatinization and pasting properties of starch , 9. As anes Fig.  with an r locus (SBEI), and a smaller effect of rb locus (AGPL1) mutations. Mutations in rug5 (StSynII) were also found to affect CLD in both developing and mature pea embryos [r, rb (AGPL1) and rug5 (StSynII) was associated with CLD variation (Table PGMP (rug3), GBSSI (lam) and SuSy (rug4), the other three genes identified, based on EMS mutations, in the above studies as being involved in starch metabolism.Mutational studies in pea have demonstrated the role of six pea seed starch biosynthetic genes in pea seed starch accumulation, structure and function , 59, 60.r locus, the major gene responsible for the difference between round and wrinkled (high amylose) pea lines, in both trials, as expected. In starch extracted from plots from the Field2011 trial, %amylose was also associated with SNPs in UPGase. For the GH2010 trial, %amylose was only associated with r locus. This likely reflects the greater variation in %amylose observed among round seeded lines in the Field2011 trial than the GH2010 trial, in which variation between round seeded lines was not significant. The effects of mutations in pea starch biosynthetic genes on %amylose have previously been determined, with rug3 (PGMP) and lam (GBSSI) reducing the % amylose content of starch compared with the wild type round seeded line, while rug5 (StSynII) and r (SBEI) mutants increased the percent amylose [p > 0.001) of amylose content with SNPs in amplified fragments of the AGPL1 (rb locus), GBSSI (lam locus) and SBEII genes. However, we did not detect association in %amylose involving SNPs in these genes. This difference that may be due to the germplasm used in the different studies or to the relatively low power of both studies due to the numbers of lines used.Variation in %amylose was associated with allelic variation in  amylose . In a re amylose  have fouSBEI (r locus) had the greatest effect on both amylose content and CLD, whereas in rice, polymorphisms in GBSS (Wx) had the greatest effect on amylose content, and SSII on gelatinization temperature [SBE3 having only a minor effect on gelatinization temperature. In maize, polymorphisms in a sucrose synthase gene (sh1), AGPL1 (sh2) and SBEIIb (ae1) were associated with amylose content and pasting properties [SSII and SBE associated with physicochemical properties, similar to the results for CLD in pea, but differed from pea in that association with GBSS was also found [As CLD and amylose content affect the physicochemical properties of starches, there are parallels, as well as contradictions, between our results and those of association mapping studies which looked at physicochemical properties of starches from other species. In pea, perature , with SBoperties , while iso found . Where tAGPS2, UGPase, StSynII), although only the mutation in StSynII resulted in a non-synonymous codon change  on protein function using PROVEAN software [UGPase gene, one of the significantly associated polymorphic SNPs occurred immediately upstream of a predicted intron acceptor cut site, hence may affect transcript splicing in lines with one or the other of the variants, a possibility that is able to be tested experimentally. Therefore, with the possible exception of the intron acceptor site variation in the UGPase gene, it is unclear whether any of the significantly associated polymorphisms identified are directly responsible for changes that would affect the CLD phenotypic variation, either through changes in coding or non-coding regions. Since only portions of the candidate genes were characterized for sequence polymorphism, it is quite possible that the significantly associated polymorphisms that were detected are in LD with the causal mutation(s) to be found in the gene regions that were not sequence characterized. It is also possible that the causal variants underlying the CLD traits do not occur in the candidate genes but in linked sequences. Our analysis of the decay of LD in this population has been limited to examining the LD within individual fragment alignments (where the maximum pairwise LD (r2) within fragments was 1.0 or nearly), which is of limited value because of the small size of these fragments, and to examining pairwise LD in pairs of fragments amplified from seven of the pea genes characterized  with UGPase (where the maximum pairwise r2 between genomic fragments from 59 to 201 and 1529–1601 on the mRNA was 0.833).Analysis of the gene context of the polymorphisms associated (FDR α ≤ 0.05) with CLD showed that most of these occurred in intronic sequences. For three of the genes, associated polymorphisms occurred in exonic regions  as having significant association with variation in %amylose. The findings were based on analysis of seed starch extracted from 92 diverse pea lines grown in two replicated trials, and on polymorphisms detected by sequencing fragments of 25 candidate genes and by scoring r locus. The r locus, which encodes SBEI, had the major effect (R2 of 83.4–88.6%), but other genes involved in substrate availability  and chain elongation (StSynII) were also associated with CLD variation, with effects ranging from 11.8 to 22.2% of the variation in mean peak area proportion at the most strongly associated peak, as determined by quantitative FACE. Examination of the sequence context of the significantly associated polymorphisms showed that most occurred in intronic regions, but a polymorphism in UGPase occurred immediately upstream of a predicted intron 3′ acceptor cut site, and a polymorphism in StSynII produced a non-synonymous mutation that was most likely to have a neutral effect on protein function. Hence, the candidate gene polymorphisms causing CLD variation in pea seed starch are in most if not all cases likely to be in full or partial LD with the associated polymorphisms that we have detected, and these causal variants may either occur within the candidate gene or in nearby sequences. Nevertheless, this study identifies sequence polymorphisms in carbohydrate and starch pathway genes, and publicly available pea lines containing the allelic variants, that can be used for further studies of genetic determination of pea seed starch structure and function, including plant breeding.We have shown that allelic variation in pea starch pathway candidate genes can have a measurable effect on amylopectin CLD. We identified polymorphisms in eight genes from the pea seed carbohydrate and starch metabolic pathway as having significant association (FDR ≤ 0.05 or FDR ≤ 0.10) with variation in debranched starch CLD, and two genes , r locus phenotype , % amylose and CLD mean molar peak area proportions for the Field2011 and GH2010 environments. (XLSX 136 kb)Pea single plant (PSP) accessions used for association mapping with Names and Collection Country from the USDA-ARS GRIN database  while the bottom panel shown correlations for n = 83 round seed lines only. (PNG 251 kb)Heat maps showing correlations between chain length distribution (CLD) mean peak area proportions for debranched starch from peas grown in GH2010 versus Field2011 trials. The colour scale ranges from blue (more strongly positive correlations) to yellow (more strongly negative correlations). The top panel shows correlations for all Additional file 3:2) within and among polymorphisms in 32 genomic fragments representing 25 candidate genes and r locus. Abbreviated candidate gene names are shown along the diagonal of the Figure. (PNG 56 kb)Heat map showing the extent of linkage disequilibrium  Principle components biplot for the first two PCs. Round seeded lines are indicated with clear circles and wrinkle seeded lines with red circles. (B) Scree plot of eigenvalues showing the variation in each component. (PNG 77 kb)Principle component analysis of population structure for Additional file 5:10(P) for the DP-environment combinations which gave associations with the lowest p-values. Results for the MLM + Q + K model (blue) and MLM + P + K model (red) are shown. The DP-environment combinations are indicated on the y-axes. (PNG 34 kb)Q-Q plots of the observed versus expected -log


Zirconia ceramics with porous structure have been prepared by solid-state reaction using yttria-stabilized zirconia and stearic acid powders. Analysis of its microstructure and phase composition revealed that a pure zirconia phase can be obtained. Our results indicated that its porosity and pore size as well as the mechanical characteristics can be tuned by changing the content of stearic acid powder. The optimal porosity and pore size of zirconia ceramic samples can be effective for the increase of surface roughness, which results in higher cell proliferation values without destroying the mechanical properties. Some dopants such as Y2O3, MgO, or CaO help stabilize the tetragonal phase of zirconia at room temperature, which is beneficial to induce T-M transformation and arrest crack propagation under force, which contributes to the material’s high toughness [0.5 range [Due to their excellent mechanical properties, zirconia ceramics have been employed in biomedical applications as early as 1969 ,3,4. Theoughness . Compare.5 range  and grea.5 range .et al. [72 osteoblast-like cells cultured on the zirconia ceramics with different surfaces. It was found that, compared with machined ones, cell proliferation values were significantly greater for surface-treated zirconia. Moreover, Yamashita et al. [Furthermore, biocompatibility is highly essential for a biomaterial, which mainly depends on the responses of cells on the materials surface, including cell attachment, cell migration, cell proliferation, and cell differentiation ,10,11. Aet al.  investiga et al.  found thSeveral treatments can obtain the needed roughness, but the most commonly employed methods are sandblasting ,22 and cInspired by desirable properties of porous scaffolds with regard to great compatibility, the aim of this study was to produce surface roughness on zirconia ceramics by synthesizing porous ceramics using stearic acid, and to investigate both mechanical properties and cell proliferation behavior as a function of stearic acid content. The null hypothesis of this study was that porous structure would increase the surface roughness of zirconia ceramics, without destroying its mechanical properties.2 indexed with PDF card #50-1089. No secondary phase or processing residue are observed.The X-ray diffraction (XRD) patterns of zirconia specimens are shown in SEM images of polished surfaces and fracture surfaces of zirconia ceramics with different stearic acid contents are shown in In similar treatments, the linear shrinkage increases slightly with the content of the stearic acid, shown in the p is the bulk porosity and ρ is the relative density). The porosities of specimens are 1.1%, 5.8% and 16% due to different mass fractions of stearic acid, which are 0 wt %, 5 wt %, and 10 wt %, respectively.As the amount of stearic acid increases, the relative density decreases due to the increase of pores by the agent. Based on relative density, the bulk porosity of porous zirconia ceramics is calculated using the following equation:Ra  of specimens with different stearic acid content. The surface roughness Ra of the dense zirconia is 20 nm on average, and that of porous specimens has an average of 50.3 nm and 70.7 nm with increasing content of stearic acid.The porous structure serves as a template for cell contact, migration proliferation, and vascularization, helping cells to attach on the surface and build a three-dimensional spreading-out structure, which promotes cell growth. On the other hand, high porosity and large pore size help the transportation of oxygen and nutrients . The porin vitro. Furthermore, the morphology of pores, to varying degrees, affects the growth of rBMSCs  with an average particle size of 90 nm and stearic acid  were used to prepare porous zirconia ceramic. Glutaraldehyde was purchased from Sinopharm Chemical Reagent Co. . FBS and rBMSCs were manufactured by Cyagen Biosciences Inc. . Trypsin and PBS were obtained from Sigma Aldrich Inc. .The starting materials, 3Y-TZP and stearic acid at 0 wt %, 5 wt %, and 10 wt %, were mixed together by alcohol-based ball milling for 12 h, respectively. The mixtures were pressed at a pressure of 4 MPa, followed by a cold isostatic pressing at 200 MPa. Furthermore, the samples were heated up to 800 °C at a rate of 100 °C/h and kept for 1 h to decompose the stearic acid completely and then sintered at 1450 °C for 2 h.VH is the Vickers hardness, P is the load and d is the diagonal of the indentation.X-ray diffraction spectroscopy  was employed to analyze the phase composition. The polished surface and fracture surface morphologies were examined by scanning election microscopy . Mean pore size distributions were analyzed using a mercury porosimeter . A Vernier caliper was used to determine the linear shrinkage by measuring the diameter of samples before and after sintering. The linear shrinkage was calculated by:E is the elastic modulus, b is the length of the shorter diagonal, b1 is the length of the longer diagonal and a is the length of the crack.The elastic modulus is inferred by using the equation:One-way analysis of variance (ANOVA) and Tukey’s multiple comparison test were used to analyze the data. The significance was set at 0.05.rBMSCs were seeded onto the as-prepared zirconia ceramic in 12-well plates with a density of 2 × 104/well, except the CCK-8 experimental group (5 × 103/well) supplemented with 1 mL DMEM in every well. At time points on day one and day five, rBMSCs were washed with PBS gently and fixed in 4% glutaraldehyd for 2 h. After dehydration in graded ethanol of 30%, 50%, 70%, 80%, 90% and 100% concentrations, rBMSCs were dried in air for 8 h and sputtered with gold prior to observation.2 at 37 °C. The absorbance of the supernatant was measured by an ELISAS at a wavelength of 450 nm.The proliferation of rBMSCs was assessed using a Cell Counting Kit 8 (CCK-8). Cells were seeded in 12-well plates with a density of 5 × 103/well and incubated in fresh DMEM for one, three, and five days. Then rBMSCs were cultured for another 4 h in CCK-8 solution (100 μL WST) in a fully humidified atmosphere with 5% COPorous zirconia ceramics have been prepared with the starting materials, 3Y-TZP and stearic acid. The mechanical properties of zirconia ceramics and proliferation of rBMSCs were investigated as a function of porosity. Our results show that the relative density gradually decreases, and the linear shrinkage increases with the stearic acid (pore-forming agent) content. The pore shape and size varies with the stearic acid content, exhibiting a remarkable effect in promoting the attachment and proliferation of rBMSCs. The porous zirconia has superior biocompatibility, especially for the specimen with a 16% porosity. These results reveal that porous zirconia ceramics are potential materials for further bioactive application.


Salmonella enterica serovar Paratyphi A is becoming a serious health problem in Asian countries particularly Pakistan, China and India and situation is aggravated by current unavailability of a licensed vaccine. This study was designed to purify the O-specific polysaccharides (OSP) produced by an isolate of Salmonella Paratyphi A from Pakistan and detect antigenicity of extracted lipopolysaccharide (LPS) and purified OSP pioneerly in South Asian region as candidate for conjugate vaccine preparation.Paratyphoid fever caused by S. Paratyphi A isolates were identified through PCR using primers of fliC-a gene (329 bp) and confirmed via nested PCR using fliC-nested primers (289 bp). Yield of the LPS of S. Paratyphi A isolate was 40 mg/L of the bacterial culture using hot phenol method. The purified LPS revealed the characteristic ladder like pattern of S. Paratyphi A LPS on SDS-PAGE with silver staining. Purified OSP obtained by acid hydrolysis yielded 23 mg/L of culture broth and was not detected by silver staining. Antigenic interaction of the purified LPS and OSP with hyper immune mice sera was confirmed by single precipitin line evaluated through immunodiffusion assay. The antigenicity was found well intact.S. Paratyphi A may have the potential to be coupled with a carrier protein to develop low cost conjugate vaccine candidates against S. Paratyphi A in paratyphoid endemic regions.The purified antigenic OSP from  S. Paratyphi A and C. Incidence rate of Paratyphoid is about 150 cases/100,000 persons/year in Pakistan, India and China. Infants, school aged children in resource poor areas and travelers experience the greatest burden of the disease in Asia  and Ty21a, however both of them have limited efficacy and they offer minimal cross-protection against paratyphoid infection sand cannot be given to children less than 2 years of age. Thus current unavailability of licensed vaccine against S. Paratyphi A is best candidate for vaccine development. In a previous report S. Paratyphi A isolated from China was conjugated with a carrier protein  was taken from National Institute for Biotechnology and Genetic Engineering , previously isolated from local hospitalized patients. The S. Paratyphi A was grown on tryptic soy broth (TSB)  at 37 °C and then subcultured on MacConkey  agar plate with overnight incubation at 37 °C. DNA extraction of overnight grown culture in TSB was carried out by chloroform-isoamyl alcohol method. Regular PCR was performed using a 25μL reaction mixture containing 5 µl of DNA template, 5 U Taq polymerase, 1.5 mM MgCl2, 50 nM dNTPs, and 40 pM of each primer. In nested PCR, 5 µl of regular PCR product was used as template  was inoculated  to a 20 L fermentor (Biostat C) containing TSB medium. The fermentation was controlled at a temperature of 32 °C with 30% dissolved oxygen and pH 7 for 11 h. The growth was supplemented with 25% sterilized glucose solution after 7 h, to enhance the carbohydrate yield. The bacterial cells were killed by addition of 1% formalin and harvested by centrifugation .The confirmed g, 50 min, 10 °C). Extraction was repeated after addition of de-ionized water and the mixture was centrifuged again . The water layer was separated and combined with previous water layer. For nucleic acids precipitation, 0.01 M sodium acetate, 0.002 M calcium chloride and 25% ethanol were added to water layer and stirred at 4 °C overnight. The supernatant was collected by centrifugation , brought to 75% ethanol using pure ethanol, and stored at 4 °C overnight. The LPS was precipitated by centrifugation , dissolved in pyrogen free water and dialyzed  against pyrogen free water and lyophilized as crude LPS. The purity of crude and purified LPS was determined by measuring the level of possible contaminants: Nucleic acid contamination was measured spectrophotometrically (LPS in 1 mg/ml in 1% SDS solution) using formula A260/20 × 100, whereas, the level of protein contamination was determined by Bradford assay. The purified LPS were collected by dissolving in buffer , dialyzing after the addition of DNase (Promega Art. # M198 A), RNase (Roth Art. # 71561) and proteinase K (Roth Art. # 75281) followed by ultra-centrifugation  as described earlier of the mixture was done after addition of one drop of 1 M calcium chloride. The supernatant containing the OSP was dialyzed against pyrogen free water and freeze-dried. The purified LPS and OSP were electrophoresed on SDS-PAGE  and visualized with silver staining . These results demonstrated the sensitive detection of our S. Paratyphi A isolate from other related enteric pathogens as previously reported  yielded 187 g of wet cell pellet. The yield of pure LPS was 40 mg/L of the culture. This yield is comparatively less than reported yield of 150 mg/L by Micoli et al.  and antibodies  vaccine are licensed to provide protection against typhoid infection but licensed vaccines against S. Paratyphi A infection are scanty  with O-specific polysaccharide conjugate (OSP) of S. Paratyphi A.The increasing frequency of S. Paratyphi A serovar specific OSP is partially O-acetylated at C-3 and this O acetylation is essential for inducing an antibody response to the OSP  of S. Paratyphi A, unlike S. Typhi, there is no capsular covering so the only antigen available is OSP. The OSP has been exploited as target for conjugate vaccines against many diseases because of their immunogenicity. The OSP of S. Typhi derived from its LPS by acid hydrolysis have been conjugated to tetanus toxoid and bovine serum albumin (BSA). These conjugates were found to be immunogenic against typhoid fever (WHO: 1994). By conjugating OSP of S. Typhi with carrier protein like diphtheria toxoid (DT) has resulted in superior antibody responses, thus becoming a potential candidate in vaccine preparation (Ali et al. S. Typhi was conjugated with tetanus toxoid and BSA (Aron et al. Escherichia coli O157 OSP was conjugated with a number of carrier proteins including exotoxin C of Clostridium welchii, BSA, rEPA (Konadu et al. Shigella dysenteriae type 1 was linked with tetanus toxoid (Chu et al. In case of ver WHO: . By conjS. Paratyphi A is a virulence factor as well as immunogenic antigen which can be used for immunization against S. Paratyphi A infections. The OSP lacks lipid A, since cleaved by ultracentrifugation, thus OSP are not visible by silver staining procedure. Our findings are in accordance with already published data relating to LPS and OSP of smooth colony forming bacteria in SDS-PAGE followed by silver staining (Konadu et al. S. Paratyphi A were checked for their purity level and found to contain 0.5% DNA and 1% protein contamination, thus conferring satisfactory purity level of these LPS and OSP of S. Paratyphi A.The OSP of S. Paratyphi A antigens, LPS and OSP was detected and these antigens were found to form evident precipitin lines in immuno-diffusion gels when tested against mice antisera raised to whole cell S. Paratyphi A. This showed that the antigenicity of the purified LPS and OSP was maintained. These results are in accordance with previous observations of antigenicity of LPS and OSP (Chu et al. S. Paratyphi A has the potential to be used as vaccine candidate alone or in conjugation with a carrier protein for immunization against paratyphoid fever in this region.The antigenicity of the purified S. Paratyphi A has the potential to be used as a vaccine candidate independently or may be conjugated with carrier protein to make low cost, specifically effective and immunogenic vaccine against paratyphoid fever.The purified OSP antigen of


Spin relaxation dynamics of holes in intrinsic GaAs quantum wells is studied using time-resolved circular dichromatic absorption spectroscopy at room temperature. It is found that ultrafast dynamics is dominated by the cooperative contributions of band filling and many-body effects. The relative contribution of the two effects is opposite in strength for electrons and holes. As a result, transient circular dichromatic differential transmission (TCD-DT) with co- and cross-circularly polarized pump and probe presents different strength at several picosecond delay time. Ultrafast spin relaxation dynamics of excited holes is sensitively reflected in TCD-DT with cross-circularly polarized pump and probe. A model, including coherent artifact, thermalization of nonthermal carriers and the cooperative contribution of band filling and many-body effects, is developed, and used to fit TCD-DT with cross-circularly polarized pump and probe. Spin relaxation time of holes is achieved as a function of excited hole density for the first time at room temperature, and increases with hole density, which disagrees with a theoretical prediction based on EY spin relaxation mechanism, implying that EY mechanism may be not dominant hole spin relaxation mechanism at room temperature, but DP mechanism is dominant possibly. It was found that spin relaxation time of electrons was dominated by the Dyakonov-Perel (DP) spin relaxation mechanism for both (001)-oriented bulk GaAs7 and two-dimensional quantum wells10, but the DP spin relaxation mechanism was suppressed so substantially in (110)-oriented GaAs quantum wells that spin relaxation time was prolonged significantly15. In contrast to the extensive studies of spin relaxation of electrons, spin relaxation of holes in bulk GaAs and quantum wells was studied much less because spin relaxation of holes was much faster than one of electrons and usually hidden by spin relaxation of electrons. Less and controversial spin relaxation times of holes were reported, and a widely variable spin relaxation time ranging from subpicosecond to tens of picoseconds has been observed22. Hilton et al. observed that spin relaxation time of heavy holes in intrinsic bulk GaAs was about 110 fs at room temperature by means of non-degenerate pump-probe circular dichromatic absorption spectroscopy16. Damen et al. studied the spin relaxation dynamics of holes in n-doped GaAs quantum wells by analyzing the decay dynamics of circular polarization of photoluminescence in the range of low temperature17, and observed a spin relaxation time of 4 ps. Amand et al. investigated the spin relaxation dynamics of holes in intrinsic GaAs quantum wells at the low temperature of 1.7 K using time evolution of the ratio of circularly polarized light-excited to linearly polarized light-excited photoluminescence intensity18, and achieved a hole spin lifetime of 2.6 ps. However, a longer spin relaxation time of holes of tens of picoseconds was also reported at low temperature22. Spin relaxation times of holes in p-dope GaAs quantum wells were measured by means of circular photogalvanic effect of THz radiation19 and time-resolved Kerr rotation beat spectroscopy20. Longer spin relaxation times of heavy holes, respectively up to ~25 ps at 4 K19 and 60 ps at 6 K20, were reported. Bar-Ad et al. reported a longer hole spin lifetime of 35~50 ps in GaAs quantum wells at 4.2 K using degenerate pump-probe circular dichromatic absorption spectroscopy21. Ostatnický et al. studied the spin relaxation of holes within excitons in intrinsic GaAs quantum wells by non-degenerate pump-probe transmission spectroscopy, and also observed a longer hole spin lifetime of 30 ps at 4 K22, and confirmed the results reported by Bar-Ad et al. Consequently, one can find that there is a larger difference between spin relaxation times of holes reported even though they were measured all at low temperature, but the cause on the larger difference is incompletely clear so far. On the other hand, spin relaxation time of holes at room temperature has not been reported for GaAs quantum wells except for bulk GaAs16. However, it is very important for the development of spintronic devices. It is very demanded to study it. Furthermore, spin relaxation mechanism of holes was still unknown for GaAs quantum wells. It was studied theoretically only for bulk GaAs23. No experimental results are available on spin relaxation mechanism of holes for either bulk GaAs or quantum wells.Spin relaxation dynamics and related relaxation mechanism of carriers in semiconductors has been attracting much attention for the demands to understand fundamental spin physics and to develop spintronics. Spin relaxation dynamics of electrons has been studied extensively in bulk GaAs semiconductorsIn this article, we study spin relaxation dynamics of holes in intrinsic GaAs quantum wells for the first time at room temperature using a simple degenerate circular dichromatic pump-probe absorption spectroscopy. A key empirical model is developed to enable extracting spin relaxation time of holes from transient circular dichromatic absorption dynamic data. Spin relaxation time of few picoseconds is obtained. Photoexcited hole density dependence of spin relaxation dynamics is studied, which reveals possible DP dominant spin relaxation mechanism of holes in intrinsic GaAs quantum wells at room temperature.24. Spin relaxation time ranging from 80 to 120 ps was observed at room temperature10.The schematic of band structure of intrinsic GaAs quantum wells is shown in Fig. −). Then, hole spin relaxation first occurs due to much faster spin relaxation rate than one of electrons, as the spin flip from |3/2> to |−3/2> spin valence band shows in Fig. −) or right-handed (σ+) circularly polarized probe pulse is used to monitor the transient differential transmission of the sample, the accumulation in |−3/2> spin band or decay in |3/2> spin band of holes should be able to be revealed. Figure −, σ−) and thick solid  lines show. A transient differential transmission for colinearly polarized pump and probe  is also measured for comparison and plotted in Fig. To avoid the photo-excitation of light holes, the central wavelength of femtosecond pulses is tuned to 841 nm whose energy is lower than the lowest energy (XH) of heavy hole excitons, which is different from nearly resonant excitation of XH by 830 nm laser in ref. − pump pulses, but spin relaxation of electrons in |1/2> spin conduction band has not taken place because spin relaxation time of electrons in the sample is larger than 80 ps.10  trace has a lowest negative plateau, which just reflects the contribution of spin relaxation of heavy holes because σ+ probe can only detect the contribution of heavy holes in |−3/2> spin valence band due to optical selection rule.  trace has also a negative plateau, but higher than one of  trace, which just reflect the different contribution of spin polarized electrons and holes to the differential transmission because the difference between the traces  and  only comes from the contribution of electrons in |−1/2> spin conduction band. As a result, the contribution of excited electrons  in |−1/2> spin conduction band can be obtained by subtracting  trace from  trace, as the dashed dot line shows in Fig. m3/2 (m denotes effective mass). For GaAs, effective mass of heavy holes is almost seven times one of electrons so that the density of state in heavy-hole valence band is almost eighteen times one in conduction band.  trace shows a positive plateau at several picoseconds, which just originates from the stronger band filling contribution of excited total electrons in |1/2> spin conduction band. Similarly, the transient contribution of alone the excited total electrons can be extracted by subtracting  trace from  trace, as the dashed dot dot line shows in Fig. Obviously, those three transient traces in Fig. −, σ+) dynamics measured at 841 nm, we have performed photon energy dependent dynamic measurement for  circularly polarized pump and probe under a constant total excitation density, as three solid lines show in the inset of Fig. −, σ+) dynamics measured at 841 nm originates from pure heavy-hole spin relaxation.To further reveal pure heavy-hole origin of unique  trace, the positive peak near zero time delay has the same origin as one in  trace has, but its fast decay has one more additional channel of spin relaxation of holes from <3/2| to <−3/2| spin valence bands besides thermalization. For  trace, the positive peak near zero time may mainly result from the coherent artifact and a weak state filling of a little amount of residual excited nonthermal electrons in <−1/2| spin conduction band. Its fast decay mainly originates from spin relaxation of holes into <−3/2| spin valence band from <3/2| spin valence band and a weak thermalization contribution of the residual excited nonthermal electrons. The little amount of residual excited nonthermal electrons comes from impure circular polarization of σ− pump and high energy tail in the spectrum of σ− pump pulses. In other words, impure σ− pump contains a small fraction of σ+ polarization which can excite a little amount of nonthermal electrons in <−1/2| spin conduction band and holes in <−3/2| spin valence band, while the high energy tail in the spectrum of σ− pump pulses can excite a little amount of nonthermal electrons in <−1/2| spin conduction band and holes in <1/2| spin valence band (excitation of light-hole excitons XL). The two residual excitations result in the little amount of nonthermal electrons into <−1/2| spin conduction band. Therefore, the information on spin relaxation of holes is contained in the fast decay process of the positive peaks in both  and  transient traces. In principle, spin relaxation lifetime of holes can be extracted by quantitatively analyzing the fast decay process in  or  transient trace. However, actually the spin relaxation of holes can be more sensitively reflected in  than in  traces because the thermalized contribution of excited nonthermal electrons is much weaker in  than in  traces. As a result,  trace will be analyzed quantitatively below to extract the spin relaxation time of holes.Next, we discuss possible origin of the positive peak near zero delay time in transient traces. For  trace, it is well known that the positive peak originates from state filling of pump-excited non-thermal carriers−, σ+) trace can be described by the following model,C(t) denotes the area-normalized cross-correlation function of pump and probe pulses and can be measured experimentally. Symbol ⊗ denotes the operation of convolution.An appropriate model needs developing quantitatively to extract the spin relaxation time of holes. Based on the above discussions,  transient trace. H(t/τs) describes the dynamics of spin relaxation of holes, while τs is just the spin relaxation time of holes. The key problem is the specific form of H(t/τs). As discussed above, pure holes can induce band filling and many-body effects simultaneously. The contribution of many-body effect to transient differential transmission is negative, while one of band filling is positive. The former is stronger than the latter in absolute amplitude so that total differential transmission is negative, as the negative plateau at a few picoseconds in  trace shows in Fig. H(t/τs) should be a sum of two components formally. One component describes the contribution of band filling, while the other component does one of many-body effect. However, the difficulty is that we don’t know how much the weight of each component is, and thus it is difficult to write out the specific form of H(t/τs). Nevertheless, we can know the total sum of the two components experimentally, as the negative plateau at a few picoseconds in  trace shows in Fig. −, σ+) transient traces have been plotted in Fig. y = c(exp(−p/Pc) − 1), is used to fit the total sum of excited hole-induced effects, as the solid line shows in the inset of Fig. Pc is a critical hole density for hole-induced transient absorption saturation, and is given as Pc = 1.17 × 1010/cm2 by the fitting.The first term in Eq.  describe8, based on rate equation of hole spin relaxation and negligible recombination of holes due to very long recombination time, the time evolution equation of hole density in |−3/2> spin valence band can be expressed by,P0 denotes total hole density excited by a σ− pump pulse.Similar to electron spin relaxation−, σ+) transient trace is obtained as,Substituting Eqs  and 3 in−, σ+) transient traces with different hole densities (P0) excited by σ− pump pulses. The experimental data (scatterred points) and best fittings (solid lines) are plotted in Fig. Equation  is used 10 cm−2. The dashed line shows the coherent artifact which is an even symmetric peak near zero time. The dashed dot line indicates thermalizing dynamics of residual excited electrons and light holes. The dot line shows the spin relaxation dynamics of excited heavy holes. It is worth stressing that the decay time (τth) of the thermalizing dynamics is extracted priorly by fitting  transient trace shown in the inset of Fig. −, σ+) transient trace. Consequently, there are only three free parameters, a, b and τs in fitting to  transient traces due to prior determination of τth. This can ensure the unique solution of parameters, a, b and τs. The extracted four parameters, a, b, τs and τth, are plotted as a function of excited carrier density in the inset of Fig. τs (filled circles) is obviously longer than τth (open circles). They are separated well. Parameters, a (open squares) and b (filled triangles), are also plotted as a function of excited carrier density in the inset of Fig. b is always stronger than a. b enhances almost linearly with excited carrier density, but a grows slowly and nonlinearly. Such an increase trend should be reasonable because coherent artifact is nonlinear effect, while the strength of thermalization is linearly dependent on pump-injected carrier density.One fitting example, showing separated three components: coherent artifact, thermalizing and spin-relaxed hole induced contributions, is plotted in Fig. τs is the first experimental report of hole spin relaxation time in GaAs/AlGaAs quantum wells at room temperature. Our τs agrees very well with reported spin lifetime of 110 fs in bulk GaAs at room temperature16 with consideration of the splitting of heavy- and light-hole valence bands in GaAs quantum wells. Taking account for weakening of spin-phonon scattering at low temperature, our τs also agrees well with reported hole lifetimes of 25–60 ps at low temperature of several Kelvins22, but disagrees with spin relaxation time of a few picoseconds reported at low temperature18.It is worth emphasizing that our et al.23 studied the effects of DP and Elliott-Yafet (EY) mechanisms on spin relaxation of holes in intrinsic and p-doped bulk GaAs theoretically, and found that spin relaxation time of holes strongly depended on hole density and lattice temperature. For intrinsic GaAs, EY mechanism was predicted to be dominated at low temperature, while DP mechanism could contribute markedly at middle temperature range and in low hole density. At room temperature, it was predicted that spin relaxation time of holes decreased with increasing hole density according to EY mechanism. However, our measured τs increases, instead of decreases with the increase of excited hole density, implying that additional mechanism besides EY, such as DP mechanism, may become dominant in GaAs quantum wells. Actually, it was already predicted and proven experimentally that a spin relaxation time of electrons increased with excited electron density in intrinsic GaAs quantum wells according to DP mechansim10. Therefore, we tend to the viewpoint that DP mechanism may be still dominant for spin relaxation of holes in intrinsic GaAs quantum wells at room temperature and in the range of low and middle hole density. Further theoretical and experimental studies on spin relaxation mechanism of holes are expected for bulk GaAs and GaAs quantum wells.The mechanism leading to spin relaxation of holes has been an open issue for either bulk GaAs or GaAs quantum wells, and was studied rarely. Shen 0.3Ga0.7As barriers, grown on semi-insulating GaAs substrate by molecular beam epitaxy along the (001) direction (z-axis). The substrate is removed by polishing first and then selective chemical etching for transmission measurements. The substrate-free GaAs/AlGaAs quantum wells film is mounted on a piece of sapphire window by Van der Waals bonding.The sample of two-dimensional quantum wells studied consists of 11 periods of 6 nm thick intrinsic GaAs wells separated by 10 nm thick AlTime-resolved degenerate circular dichromatic absorption spectroscopy is used here to study spin relaxation dynamics of heavy holes at room temperature. The experimental setup is very similar to one shown in ref.


This is a review article on treatment of bulbar urethral strictures with personal critical remarks on newer developments. As a treatment of first intention there exists 4 options : dilatation, urethrotomy, end to end anastomosis and free graft, open urethroplasty. Success rate of dilatation and visual urethrotomy after 4 years is only 20 en 40 % respectively. Laser urethrotomy could not fulfill expectations. End to end anastomosis obtains a very high success rate but is only applicable for short strictures. Free graft urethroplasty obtains success rates of ± 80 %. There is considerable debate on the best material for grafting. Buccal mucosa graft is the new wave, but this is not based on scientific data. Whether this graft should be used dorsally or ventrally is also a point of discussion. In view of the good results published with both techniques it is probably of no importance. Intraluminal stents are not indicated for complicated cases and give only good results in those cases which can easily be treated with other techniques. Metal self-retaining urethral stent , resorbable stents and endoscopic urethroplasty is briefly discussed. Redo’s and complicated urethral strictures need often other solutions. Here skin flap from the penile skin and scrotal flap can be used. Advantages and drawbracks of both are discussed. There is still a place for two-stage procedures in complicated redo's. The two-stage mesh-graft urethroplasty offers advantage over the use of scrotal skin. Some other rare techniques like substitution with bowel and pudendal thigh flap, to cover deep defects, are also discussed.


The mammalian basilar membrane (BM) consists of two collagen-fiber layers responsible for the frequency-to-place tonotopic mapping in the cochlea, which together form a flat beam over at least part of the BM width. The mechanics of hearing in rodents such as gerbil pose a challenge to our understanding of the cochlea, however, because for gerbil the two layers separate to form a pronounced arch over the remaining BM width. Moreover, the thickness and total width normally thought to determine the local stiffness, and tonotopic mapping in turn, change little along the cochlear length. A nonlinear analysis of a newly developed model, incorporating flat upper and arched lower fiber layers connected by ground substance, explains the initial plateau and subsequent quadratic increase found in measured stiffness vs. deflection curves under point loading, while for pressure loading the model accurately predicts the tonotopic mapping. The model also has applicability to understanding cochlear development and to interpreting evolutionary changes in mammalian hearing. As a result, higher frequencies excite sensory cells at the basal end of the cochlea near the stapes, while lower frequencies excite sensory cells toward the apical end near the helicotrema. Almost every structural component of the cochlea has, at one time or another, been proposed as a key resonance element responsible for this frequency-to-place cochlear mapping. However, the dominant view, backed by direct measurements pioneered by Nobel laureate Georg von Békésy2, is that the basilar membrane (BM), the structure that varies the most dramatically along the length of the cochlea, is the best candidate.As a prism separates white light into a spectrum of colors, the cochlea of the mammalian inner ear acts to mechanically separate an incoming sound signal into component frequencies. It is well established that this frequency analysis results from a process called tonotopic mapping3, cat4, and gerbil5. On its lower surface facing the scala tympani  and secondary spiral lamina , is that it contains much more ground substance between the upper and lower fiber layers than in other mammals13, such that the PZ forms a distinctively arched shape  of the BM along its length is the primary reason for the frequency–place mapping of the BM, given that the local resonance frequency is proportional to the square root of this local stiffness. Therefore, one can estimate the range of stiffness of the BM in a given species by considering the range of frequencies that the species is capable of hearing (see Table 20. The resonance frequencies computed using the SBM (see Methods Eq. 21. In the guinea pig (GP), for example, the SBM predicts a base/apex resonance-frequency ratio of 400 00 Table . This is23.The discrepancy in SBM predictions between the GP and gerbil is related to how the gerbil’s BM thickness is not uniform across its width, due to the prominent PZ arch, and how this affects measurements of its thickness. Whereas the relatively flat BM of the GP decreases in thickness by nearly a factor of 7 from base to apex, i.e., from around 7 μm to 1 μm, in the gerbil the BM thickness measurements with an arched PZ actually increase from 22.6 μm at the base to 56.5 μm at the apex, corresponding to a base/apex ratio of only 0.4 Table . The bas22 and Northwestern University24. For one, a 41-fold change in the base/apex BM point-load stiffness of the Mongolian gerbil was reported by Naidu and Mountain of the Boston group22. This is far below the expected point-load stiffness ratio, which should be around four orders of magnitude (~5000) to support the normal gerbil hearing range. Emadi et al. of the Northwestern group came somewhat closer to the expectation with a measured stiffness change of 335-fold24.There have been many attempts to measure the stiffness of the gerbil BM under a direct mechanical point load (force/displacement), such as those made by research groups at Boston University22, even though the second plateau occurs at a deflection in the 10–20 μm range, which is much higher than the normal <1 μm physiological motion of the BM of a healthy cochlea24. Under point loads causing a deflection of more than a few thicknesses of the lower arch layer, the arch will begin to buckle. Therefore, the reported second-plateau stiffness measurements are well into the nonlinear buckling region. How then is it meaningful to use the second plateau as the physiologically relevant stiffness?However, these point-load stiffness measurements as a function of increasing deflection made by both groups exhibit some unusual features, namely: (i) a long initial plateau of low stiffness, (ii) a sudden rise in stiffness, (iii) a local minimum often referred to as the ‘second plateau’ in the literature, and then (iv) a quadratic increase in stiffness for the highest point deflections. It has so far been argued that the second plateau in these stiffness–deflection curves represents the stiffness of the BM that determines the frequency–place map of the gerbil when measured at low levelsTo elucidate the gerbil point-load stiffness measurements and to provide insights into the cochlear map for the gerbil, a new model has been developed that takes into account the actual geometry of the two collagen-fiber layers, treating the upper layer as a flat beam and the lower layer as an arch in the PZ, as shown in Fig. 22. The unloading curve reveals a characteristic sign of buckling behavior of the lower arch that cannot be explained by the SBM. The ABM for the point-load stiffness measurements accounts for the large strain–displacement geometric nonlinearity and buckling, and includes the effects of the layer of soft TBCs. It is presently shown that incorporating this TBC cover layer is critical for re-interpreting the previously measured loading and unloading measurements.One feature of the point-load stiffness measurements is that the loading and unloading data show different stiffness curves at small probe deflectionsThe ABM has also been adapted to the case in which the gerbil BM is loaded via pressure in the surrounding fluid rather than a mechanical point load, to obtain the frequency–place cochlear mapping based on the linear volumetric stiffness, which is the relevant quantity for estimating the frequency–place cochlear map. The ABM is then applied to the mouse anatomy, which features a similar PZ arch structure, but with less curvature than in the gerbil. Another generalization of the ABM model is its possible extension to the gerbillinae subfamily and to the development of the BM after birth.c, the effective spring length at the arcuate zone end Le, and the elastic modulus E of the collagen-fiber bands.Model responses were first obtained using a rigid outer-pillar support and without considering the effect of the TBCs Fig. , to testc, Le, and E. The point stiffness, which is obtained as the gradient of the load–deflection curve, is plotted in the bottom row of Fig. The top row of Fig. c = 0 , initially the load–deflection curve follows almost the same path as that of the arch alone. But as the deflection increases, the internal pressure also increases. Consequently, the upper beam layer undergoes stretching and its effective stiffness increases. For lly Fig. . Thus, tlly Fig. . The minc affects the minimum of the stiffness as well as the slope of the post-minimum stiffness curve. Figure Le affects the slope of the post-minimum stiffness curves, without much effect on the stiffness minimum itself, as shown in the 7–12 μm deflection range. The variations to the Young’s modulus cause differences in the point load , namely: (i) a long initial “first plateau” stiffness region before the reference displacement of 0 μm; (ii) a sudden rise in stiffness with further displacement of the probe; (iii) a local minimum (“second plateau”), promptly followed by (iv) a quadratic increase in stiffness. The quadratic increase in stiffness is a well-known characteristic of beam behavior under a large deformation due to point or pressure loads17.The point stiffness as a function of probe depth for the gerbil PZ Fig.  exhibitset al.26 and Mountain et al.22, but they described it as noise, possibly because the behavior is contrary to the expectation of a constant stiffness followed by a monotonically increasing stiffness as predicted by the SBM.It is evident that the TBC layer, being much softer than the arch, deflects the most until it flattens fully, beyond which only the arch deflects. Thus, the TBC layer plays the role of obscuring the actual stiffness–deflection curve of the BM until it is fully compressed. This explains the long flat region , spanning over the initial deflection. This effect has been observed consistently in the measurements by Emadi tTBC and spring stiffness kTBC of the TBC layer were chosen so as to obscure the stiffness–deflection curve until near the rise in stiffness, in line with the experimental observations. This was achieved by defining the product tTBC*kTBC to be 12 μN for the basal turn and 1.9 μN for the middle turn.The thickness et al.24. The predicted slope in the post-second-plateau region above about 10 μm of deflection is in good agreement with the measurements, considering their variability (green curves). This match was obtained using an effective spring length Le of 1400 μm and 3800 μm for the basal and mid-turn locations, respectively, and a volume dispersal factor c = 0.87 for both locations. The large values of Le essentially indicate a small value of the SSL stiffness.It can be seen from the bottom row of Fig. E of the collagen fibers was taken as 2 GPa, which is close to the value reported by Miller7 (1.8 GPa). The same values of E and c also work for the apical location (10.3 mm from the base), where the predicted mid-pectinate second-plateau stiffness is also in excellent agreement with the measurements , were taken from Schweitzer et al.5 for the different locations along the cochlea, applying linear interpolation. The ratio La/Lp was taken as 0.4, similar to the values of 0.39 taken by Cooper27 and 0.43 by Miller7. The other geometric parameters are the same as for the point-load case.The BM response to pressure loading was obtained using the same value for the Young’s modulus of the fiber layers as in the point-load case (2 GPa). The total BM width 27. Ehret and Frankenreiter28 observed a similar deflection profile for the house mouse.The deflection profile of the upper fiber layer across the BM width from the PSL to the SSL, as predicted by the present model  structures30. The match is also good for the frequencies of 9.8 kHz and 1.8 kHz calculated from in vitro measurements by Emadi and Richter26 at 2.9 mm and 7.3 mm from the basal end, respectively. This establishes for the first time a frequency–place cochlear map for the gerbil BM based entirely on the reported anatomy. The SBM (solid black line with circular markers) with the same BM width, fiber volume fraction, and fiber-band thickness as the ABM is not able to match the measured cochlear map.The match between the ABM and Greenwood’s cochlear map is reasonable, keeping in mind that the present prediction is for a passive cochlea, whereas Greenwood’s relation corresponds to an In the ABM, when changing only the AZ fiber-band thickness longitudinally and keeping all the other parameters constant (red dash-dotted line), it can be seen that the AZ thickness makes a significant contribution to the slope of the frequency–place map. When both the AZ and PZ fiber-band thicknesses are varied longitudinally, the slope of the frequency map changes only slightly (red dashed line). The arch height in gerbil shows a marginal increase from the basal to apical turn, which would result in an increase in BF from base to apex. This is contrary to an expected decrease in arch height to match the frequency reduction in that direction. Like the PZ fiber-band thickness, the arch height too does not cause any significant change in BF as long as it is sufficiently high to make the PZ rigid (not shown). The remaining contribution to the cochlear map essentially comes from the addition of longitudinal variation of the BM width (changing from the red dash-dotted line to the red solid line), because the AZ width was set to be proportional to the BM width (by a factor of 0.4). In summary, the cochlear map in the Mongolian gerbil is governed primarily by the morphological parameters of the AZ.28. When the proposed ABM is used, the frequency–place map (solid red line with square markers) is more consistent with the frequency–place map based on measurements (blue line)29.When the SBM is applied to the mouse model, it does not result in the expected frequency–place tonotopic mapping when realistic anatomical parameters are chosen . We hypothesize that this shift during unloading is due to the soft TBC layer having been compressed as the BM was loaded by the probe, such that there can be more evidence of a buckled arch as the probe unloads the BM, since the TBC layer is already thinner. To illustrate this point, Fig. The Boston group36. This is why the overall BM structure is observed to have a much smaller displacement than the probe displacement. If not for the compression of the TBCs  at 2.9 mm from the basal end. Emadi and Richter26 measured the BF shift between 12 and 30 days (adult) after birth as a factor of 2 (1.0 octave) for the same location. Anatomical measurements from Schweitzer et al.5 revealed that only the thickness of the fiber bands undergoes a significant change from infant to adult stages, while the other dimensions remain mostly the same. Interpolations of the Schweitzer data at 1.2 and 4.2 mm to approximately 2.9 mm from the basal end show that the thickness of the upper and lower bands is 0.96 μm and 0.70 μm, respectively, on 12–13 postnatal days. These fiber-band thickness values increase by a factor of about 1.5 from birth to adulthood. In the present ABM, the BF of the BM at this location with a fiber-band thickness for an infant gerbil comes out to be 7.6 kHz, whereas with the adult fiber-band thickness it comes out to be 12.8 kHz , are the width and thickness of the AZ beam and the collagen-fiber volume fraction, with the PZ arch having a high-enough stiffness that its flexing deformation can be considered somewhat insignificant , because soft tissues like the collagen fibers of the BM are no longer evident in these specimens. It is possible that the estimated BM width for some of these early mammalian fossils might exhibit only moderate variation along the cochlear length, similar to that of gerbil, in which case an arch–beam BM might be the dominant mechanism for determining the frequency–place cochlear map.1 and upper flat beam thickness t2 are from Schweitzer et al.5. Other anatomical dimensions, namely the PZ width Lp and the height h, for computing the BM stiffness under a point load at the mid-point of the arch .With a localized point load, some of the ground substance will displace in the longitudinal direction, which reduces the cross-sectional area. The fraction of the remaining area of ground substance is denoted by the volume-dispersal factor X) direction with an effective stiffness of ka, parameterized in terms of a length dimension Le (kα = Eb (t1 + t2)/Le, where E is the elastic modulus, b is the effective longitudinal breadth of the model, and t1 and t2 are the respective thicknesses of the lower and upper fiber bands), which represents the in-plane stiffness of the AZ and SSL.The boundary conditions of the upper fiber band are such that the ends stretch in the horizontal .flocal at a point along the length of the BM is affected by the local fiber volume fraction vf (assuming a uniform distribution of collagen fibers), the local BM thickness t (assuming uniform thickness across the BM width), the fluid density ρf, and the local BM PZ width Lp, according to the following proportionality relationship:In an SBM, the local resonance frequency t1, height h, and span Lp, and the upper band as a beam of thickness t2. The arch and beam are coupled together through the soft ground substance, which acts as an incompressible gel. In the AZ, the two layers merge to form a beam of combined thickness t1 + t2. The transverse deflection w is restrained at the bony PSL and SSL endpoints, since these are much stiffer than the BM in the transverse direction. However, the elasticity of the PSL and SSL may allow them to move in-plane in the radial direction X. This is modeled by restraining the in-plane displacement at the SSL end and adding an axial spring of constant ks at the PSL end.The geometry of the general ABM of the BM is shown in Fig. ka represents the effective spring stiffness of the AZ and the PSL. Subsequently  as well as on the flat beam (upper fiber band). The effective longitudinal breadth b of the model is taken as equal to the diameter of the probe, since there is negligible longitudinal coupling between adjacent collagen fibers7.An analytical formulation has been developed to predict the large-deflection response of the BM under point-load measurements. First the support due to the outer pillar was considered to be rigid Fig. . Figure tly Fig. , the reaads Fig. . The gros and Ab respectively, are related to each other. However, under point loading, some amount of the ground substance in the loaded region may be pushed away to longitudinally adjacent areas. To account for this, the area displacements are related as Ab = cAs, with c ≤ 1 (SI Eq. The SI section describes the development of the equations for the ABM. A moderate-rotation geometric nonlinearity due to large deflections describes the shallow circular arch SI Eqs. –22. The 1 SI Eq. . Finally1 SI Eq.  are descA linear analysis of the pressure-load behavior was performed on the model shown in Fig. Supporting Information


Taking performance-enhancing drugs (PEDs) can cause serious and irreversible health consequences, which can ultimately lead to premature death. Some young people may take PEDs without fully understanding the ramifications of their actions or based on the advice from others. The purpose of this systematic review was to identify the main factors that predicted doping among young people. The literature was systematically reviewed using search engines, manually searching specialist journals, and pearl growing. Fifty-two studies, which included 187,288 young people aged between 10 and 21 years of age, 883 parents of adolescent athletes, and 11 adult coaches, who were interviewed regarding young athletes, were included in this review. Nine factors predicted doping among young people: gender; age; sports participation; sport type; psychological variables; entourage; ethnicity; nutritional supplements; and health harming behaviors. In regards to psychological variables, 22 different constructs were associated with doping among young people. Some psychological constructs were negatively associated with doping , whereas other were positively associated with doping . Policy makers and National Anti-Doping Organizations could use these findings to help identify athletes who are more at risk of doping and then expose these individuals to anti-doping education. Based on the current findings, it also appears that education programs should commence at the onset of adolescence or even late childhood, due to the young age in which some individuals start doping. According to the World Anti-Doping Agency's (WADA) most recent guide, doping is defined by the occurrence of at least one or more anti-doping rule violation (ADRV). There are 10 ADRVs, which included: (1) the presence of prohibited substances , or its metabolites or markers within an athlete's sample; (2) use or attempted use of a banned substance or method , (3) evading, failing, or refusing to provide a sample, (4) missing three tests within 12 months, (5) tampering or attempting to tamper with samples, (6) possessing a banned substance or method, (7) trafficking or attempt to traffic banned substances or methods, (8) administering banned substances or attempting to administer banned substances to athletes, (9) assisting or encouraging others to take banned substances, and (10) associating with individuals who are currently banned. ADRVs regularly feature in the media due to high profile cases with famous individual athletes, teams, or national organizations. Most of the cases portrayed in the media involve elite adult athletes, but it would be incorrect to assume that doping occurs exclusively among this population. The European School Survey Project on Alcohol and Other Drugs report ESPAD,  surveyedAddiction (1903 to 2017), Archives of Pediatrics and Adolescent Medicine (2000 to 2017), British Journal of Sports Medicine (1964 to 2017), Clinical Journal of Sports Medicine (1991 to 2017), European Journal of Clinical Pharmacology (1968 to 2017), International Journal of Sport and Exercise Psychology (2003 to 2017), International Journal of Sport Psychology (1994 to 2017), International Journal of Sport of Sports Medicine (1980 to 2017), Journal of Adolescent Health (1980 to 2017), Journal of Applied Sport Psychology (1989 to 2017), Journal of Child and Adolescent Substance Abuse (1990 to 2017), Journal of Clinical Sport Psychology (2007 to 2017), Journal of Drug Education (1971 to 2017), Journal of Drug Issues (1971 to 2017), Journal of Health Psychology, (1996 to 2017), Journal of Science and Medicine in Sport (1998 to 2017), Journal of Sport Behavior (1990 to 2017), Journal of Sport & Exercise Psychology (1979 to 2017), Journal of Sports Sciences (1983 to 2017), Psychology of Sport and Exercise (2000 to 2017), Medicine & Science in Sports & Exercise (1969 to 2017), Performance Enhancement & Health (2012 to 2017), Research Quarterly for Exercise and Sport (2001 to 2017), Scandinavian Journal of Medicine and Science in Sport (1991 to 2017), Sport, Exercise, and Performance Psychology (2011 to 2017), Substance Abuse Treatment, Prevention, and Policy (2006 to 2016), and The Sport Psychologist (1987 to 2017). Finally, all reference lists of included papers were searched, a strategy that is sometimes referred to as Pearl Growing ; and health harming.Thirteen studies reported an incidence of doping among young males and females, and one study explored gender differences in relation to the parents of adolescent athletes  influenced doping. Terney and McLain  found thTeachers and parents were the main source of information regarding supplements and AAS, although parents were less important by the time the students were 17 to 18 years old  and doping. All six studies  were cross-sectional. This represents a limitation of the doping literature, because only an association and not causation can be inferred from cross-sectional research. It should be noted, however, that cross-sectional research is useful at assessing the prevalence of a behavior  among a specific population  also impact upon doping, as do other behaviors such as using NS or the use of illegal drugs. These findings can be used to help identify young people at risk of doping, and many of the psychological factors can be manipulated through psychological interventions, which may help reduce the prevalence of PEDs among young people. Our findings can also inform pro-sport educational programs. Finally, as some people may take PEDs before their 10th birthday, young people should be exposed to anti-doping education before the onset of adolescence.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


Arabidopsis leaf chloroplasts typically contain five to seven semicrystalline starch granules. It is not understood how the synthesis of each granule is initiated or how starch granule number is determined within each chloroplast. An Arabidopsis mutant lacking the glucosyl-transferase, STARCH SYNTHASE 4 (SS4) is impaired in its ability to initiate starch granules; its chloroplasts rarely contain more than one large granule, and the plants have a pale appearance and reduced growth. Here we report that the chloroplastic α-amylase AMY3, a starch-degrading enzyme, interferes with granule initiation in the ss4 mutant background. The amy3 single mutant is similar in phenotype to the wild type under normal growth conditions, with comparable numbers of starch granules per chloroplast. Interestingly, the ss4 mutant displays a pleiotropic reduction in the activity of AMY3. Remarkably, complete abolition of AMY3 (in the amy3 ss4 double mutant) increases the number of starch granules produced in each chloroplast, suppresses the pale phenotype of ss4, and nearly restores normal growth. The amy3 mutation also restores starch synthesis in the ss3 ss4 double mutant, which lacks STARCH SYNTHASE 3 (SS3) in addition to SS4. The ss3 ss4 line is unable to initiate any starch granules and is thus starchless. We suggest that SS4 plays a key role in granule initiation, allowing it to proceed in a way that avoids premature degradation of primers by starch hydrolases, such as AMY3. Arabidopsis mesophyll cells, 5–7 starch granules are typically produced in each chloroplast during the day . GBSS is specialized for the synthesis of amylose, and Arabidopsis mutants lacking GBSS produce amylose-free starch (–The synthesis of both amylopectin and amylose is mediated by starch synthases (SSs),e starch . SS1, SSe starch –8. Branc starch –, 10.Arabidopsis leaves. SS4 contributes very little to the measurable starch synthase activity and does not have a major influence on amylopectin structure . However, we observed a striking reduction of an activity that could degrade both substrates. A previous study identified this band as the activity of the chloroplastic α-amylase AMY3 .To assess the involvement of starch degradation enzymes in granule initiation, we first investigated whether the activities of starch-degrading enzymes were altered in ild type A. Howevease AMY3 . This bafication A.ss4 and ss3 ss4 resulted from changes in AMY3 protein and/or transcript abundance. Proteins were extracted from young rosette leaves harvested 4 h into the day, and AMY3 abundance was examined by immunoblotting with AMY3-specific antibodies (ss4 and ss3 ss4 mutants contained far less AMY3 protein than extracts from the wild type (B). Quantification of the fluorescence signal showed that AMY3 band intensity in ss4 was on average 2.5 ± 0.9% of that observed in the wild type. AMY3 bands were very faint in ss3 ss4 and could not be accurately quantified. We used quantitative RT-PCR to determine whether these changes in AMY3 protein abundance resulted from alterations in AMY3 transcription. AMY3 transcript levels fluctuate diurnally, with peak expression at the end of day and low expression at the end of night (AMY3 transcript level in both the ss4 and ss3 ss4 mutants (C). Interestingly, there was slightly more transcript in the mutants than the wild type at both the end of day and the end of night. Thus, ss4 and ss3 ss4 mutants have less AMY3 protein than the wild type because of changes at the post-transcriptional level.We then investigated whether the diminished AMY3 activity in tibodies . Proteinild type B. Quantiof night , 18. We  mutants C. Interess4 leaves harvested during the night (D). Additionally, we tested whether AMY3 abundance was influenced by leaf age in the wild type and ss4, because the ss4 mutant contains more starch in older leaves than in young leaves . Taken together with the native PAGE gels, these data suggest that the loss of SS4 results in a pleiotropic reduction of AMY3 activity, caused directly by changes in AMY3 protein abundance.Similar changes in AMY3 abundance could be observed in he night D. Additig leaves . Exampleg leaves E. Taken ss4 and ss3 ss4 may result from a regulatory mechanism, whereby a reduced capacity for starch degradation promotes starch synthesis, compensating for the genetic impairment. To further investigate this, we crossed the amy3 knock-out mutant allele . The ss3 ss4 mutant was severely stunted in growth and even paler than ss4. In contrast, the amy3 single mutant was indistinguishable from the wild type. These phenotypes were comparable with those observed in previous studies . The ss4 mutant, as previously documented, stained much darker in older leaves than in younger leaves , accumulating ≈10% more starch than the wild type at the end of the day. Although the ss3 ss4 mutant was virtually starchless (≈3% of the wild type starch content), the amy3 ss3 ss4 mutant accumulated measurable levels of starch during the day (≈12% of the wild type starch content), which was degraded completely during the night. The loss of AMY3 can therefore increase starch content in the ss4 background and restore starch synthesis in ss3 ss4 background, suggesting that AMY3 is repressing starch accumulation in those mutants. These findings are particularly intriguing because the amy3 mutation alone has little impact on starch content.We quantified the starch content of these mutants at the end of day and end of night . Althougss4 and ss3 ss4 mutants are pale and growth-compromised because of the accumulation of ADP-glucose, the substrate for starch synthases . ss4 plants accumulated 243 nmol/g FW ADP-glucose. The amy3 ss4 mutant had significantly less ADP-glucose than ss4 (a reduction of 60%). Despite the improved growth of amy3 ss3 ss4 compared with ss3 ss4, we did not observe a significant difference in ADP-glucose content between the two mutants. However, there was overall a strong negative correlation between ADP-glucose content and plant growth determined by fresh weight (r = −0.97) (B). Visibly pale phenotypes were observed in the three mutants with the highest ADP-glucose content  .It has been proposed that ynthases . Given tmol/g FW A. ss4 pl= −0.97) B. Visiblss3 ss4) . These d4 mutant . The apsss4 mutant has dramatically reduced granule number per chloroplast. Because amy3 ss4 mutants accumulated more starch than ss4 and less ADP-glucose, we investigated whether this resulted from the production of larger starch granules or an increased number of granule initiations in the double mutant. To test this, we embedded leaf tissue from young and old leaves of wild-type and mutant plants in resin. Thin sections were cut and stained in toluidine blue to visualize starch granules using light microscopy.The ss4 mutants had either zero, one, or rarely two round granules. However, chloroplast sections with no starch granules were observed more frequently in younger leaves than old leaves. In amy3 ss4 chloroplast sections, many smaller round granules were present, in addition to some large starch granules similar to those observed in ss4. Some chloroplast sections in amy3 ss4 only contained many small granules (inset A), which was never observed in the ss4 single mutant. Unlike ss3 ss4 chloroplasts, which contained no starch, some chloroplast sections in the amy3 ss3 ss4 triple mutant contained numerous, small round starch granules (inset B). The majority of chloroplast sections of this mutant, however, still contained no starch. The loss of AMY3 can therefore increase the frequency of granules in both ss4 and ss3 ss4 mutants. No obvious difference was observed between the wild type and amy3 single mutant.Chloroplasts sections in mesophyll cells of wild-type plants had numerous flattened starch granules . No obvigranules , inset Agranules , inset Bamy3 ss4 and amy3 ss3 ss4 chloroplasts, we noted that the shape of their granules still had the distinct round morphology typical of the ss4 mutant rather than the flattened discoid shape of wild-type starch. To further investigate these differences in granule morphology, we used electron microscopy. First, we generated transmission electron microscopy images of chloroplasts in these mutants. The amy3 ss4 mutant contained rounded granules like the ss4 parent (A). Although some granules in amy3 ss3 ss4 had round morphology similar to amy3 ss4 granules, there were also some smaller granules with irregular appearance. The flattened discoid granules were only observed in the wild type and amy3 mutant. We also purified starch from rosettes and viewed it using scanning electron microscopy. Starch granules from amy3 ss4 and ss4 had distinct round morphology and were larger than wild-type granules (B). However, consistent with the light microscopy images, there was a distinct subpopulation of smaller granules in amy3 ss4. Starch from amy3 ss3 ss4 was mainly composed of very small granules, although some larger ones could be observed. The loss of SS4 therefore causes a distinct change in granule morphology that is independent from the number of granules initiated per chloroplast.Despite the numerous granules in 4 parent A. Althougranules B. Howeveamy3 ss3 ss4 mutant had a stronger phenotype than amy3 ss4, we further investigated the influence of SS3 on granule initiation and morphology. We observed chloroplast sections of ss3 and amy3 ss3 mutants by light microscopy, but the number and shape of the granules in these mutants were indistinguishable from the wild type (A). This suggests that in the presence of SS4, SS3 is dispensable in granule initiation. We also assessed whether there were pleiotropic changes in SS3 levels in amy3 ss4 mutants using native PAGE gels stained for starch synthase activity. We could detect both SS1 and SS3 activities, but both were similar between amy3 ss4 and the wild type (B). It is therefore unlikely that the amy3 ss4 mutant accumulates more starch than ss4 because of pleiotropic changes in the activity of other starch synthases.Because the ild type A. This sild type B. It is Arabidopsis  was reported in ss4  double mutant , which produces a soluble, glycogen-like polymer in place of starch granules. Introducing the amy3 mutation in this background (i.e. generating a quintuple mutant) restored insoluble granule formation . SS4 can form dimers, which may increase the efficiency of crystalline glucan formation  providing a 12-h light/12-h dark cycle, with a light intensity of 150 μmol photons m−2 s−1, a constant temperature of 20 °C, and a relative humidity of 65%. The following T-DNA insertion mutants were used in this study: ss4  at a ratio of 1 ml of medium/100 mg of tissue. Insoluble material was removed by centrifugation. Proteins in the supernatant were separated by SDS-PAGE  and subsequently transferred onto PVDF membranes using standard procedures. AMY3 antiserum, generated previously by immunizing rabbits with recombinant AMY3 protein . Reverse transcription was carried out on 2 μg of total RNA using the RevertAid reverse transcriptase kit (Thermo-Fisher Scientific). We then conducted quantitative RT-PCR to quantify AMY3 transcript levels using the Fast SYBR Green master mix together with a 7500 Fast real time PCR system (Applied Biosystems), with the following primers: forward, 5′-TGCTTACATCCTAACTCATCC-3′; and reverse, 5′-CTCTTGTCTATATTCACCTCACTC-3′. Transcript levels were calculated relative to the For staining with iodine, rosettes harvested at the end of the day were clarified in 80% (v/v) ethanol before staining in Lugol's iodine solution (Sigma), as described previously . Excess 2. Care was taken to ensure that the leaves were not shaded prior to rapid freezing. The tissue was ground and extracted using chloroform-methanol as previously described (Plant material was harvested in the light at the end of the day and immediately frozen in liquid Nescribed . ExtractLight microscopy and transmission electron microscopy analyses were carried out as previously described . For scaD. S., S. S., and S. C. Z. conceived and designed the experiments. D. S., K.-J. L., and M. S. performed the experiments. D. S. and S. C. Z. wrote the paper. All authors analyzed the results and approved the final version of the manuscript.