Wx, SSI, SSIIa, SBEI, SBEIIa and SBEIIb) in indica and japonica rices opens an opportunity to produce a new variety with more favourable grain starch quality. However, there is limited information about the effects of these six gene allele combinations on starch structure and properties. A recombinant inbred line population from a cross between indica and japonica varieties offers opportunities to combine specific alleles of the six genes.The genetic diversity of six starch biosynthetic genes (indica vs japonica) effects of six starch biosynthetic genes on starch structure, functional properties, and abundance of granule bound proteins in rice grains were investigated in a common genetic background using a recombinant inbred line population. The indica Wx (Wxi) allele played a major role while indica SSI (SSIi), japonica SSIIa (SSIIaj) and indica SBEI (SBEIi) alleles had minor roles on the increase of amylose content. SSIIaj and japonica SBEIIb (SBEIIbj) alleles had a major and a minor role on high ratio of ∑DP ≤ 10 to ∑DP ≤ 24 fractions (RCL10/24), respectively. Both major alleles (Wxi and SSIIaj) reduced peak viscosity (PV), onset, peak and end gelatinization temperatures (GTs) of amylopectin, and increased amylose-lipid complex dissociation enthalpy compared with their counterpart-alleles, respectively. SBEIIai and SBEIIbj decreased PV, whereas SSIi and SBEIIbj decreased FV. SBEIi reduced setback viscosity and gelatinization enthalpy. RCL10/24 of chain length distribution in amylopectin is negatively correlated with PV and BD of paste property and GTs of thermal properties. We also report RILs with superior starch properties combining Wxi, SSIj, SSIIaj, SBEIi and SBEIIbj alleles. Additionally, a clear relation is drawn to starch biosynthetic gene alleles, starch structure, properties, and abundance of granule bound starch biosynthetic enzymes inside starch granules.The allelic (Wxi and SSIIaj alleles play major roles, while SSIi, SBEIi, SBEIIai and SBEIIbj alleles have minor roles in the determination of starch properties between indica and japonica rice through starch structural modification. The combination of these alleles is a key factor for starch quality improvement in rice breeding programs. RCL10/24 value is critical for starch structure and property determination.Rice  The diversity of starch properties between indica and japonica varieties have been widely studied, and the alleles of genes that affect the traits have been found through a number of approaches  of rice starch, affecting the cooking and eating properties, is determined by the activity of granule-bound starch synthase I (GBSSI) encoded by the ely Sano . They caely Sano  that resely Sano  and its SSIIa in rice were reported earlier, and up to 9 SNP alleles were identified   and intermediate chains (DP 12 to 21), increases in short chains (DP ≤ 10) and intermediate chains (DP 24 to 34) and a reduction in the onset, peak and end gelatinization temperature  is a long linear glucose polymer (~1% branched points) which is synthesised by GBSSI, through adding ADP-glucose to existing α-(1–4) glucan chains  on starch structure and properties were studied in a common genetic background, using a recombinant inbred line (RIL) population derived from crossing IR64  and Nipponbare . With two alleles (i or j) for six different genes there are 64 potential combinations theoretically. In this work we have compared i or j alleles for each gene in a common background, with 12 combinations representing 64 as a whole. Different approaches such as amylose content assay using size-exclusion chromatography, chain length determination by capillary electrophoresis (CE), rapid viscosity analysis (RVA), and differential scanning calorimetry (DSC) were performed to analyse the starch structure and properties of these samples. Starch granule bound proteins (GBPs) were analysed to study the relation between those proteins and starch structure and properties.In this study, the polymorphic effects of six starch biosynthetic genes (i vs j) for each of the 6 genes. Thus we segregated the RILs into six allele groups according to the allele combinations  differing in their alleles , whereas Wxj allele group contained 11.1 ~ 18.4% , with parental lines IR64 (21.2%) and Nipponbare (11.8%) fitting in their respective Wx groups. Between the Wxi allele group (containing average 22.0% amylose) and the Wxj allele group (containing average 13.1% amylose), the former contained ~9% significantly higher AC than the latter. Within Wxi allele group, starch samples from Wxi allele lines contained significantly higher AC (35.3%) than all other allele groups, and starch from SSIi (22.8%) and SSIIaj (20.9%) alleles contained higher AC than other four alleles   contained significantly higher AC than those from other four allele groups, among which AC was not significantly different.Although the h Figure . Six allnes IR64 1.2% and SSIIai played a major role, while SBEIIbi played a minor role in accumulating intermediate chains (DP12 ~ 22). The differences in % normalised distribution were obtained by subtracting the CLD of japonica allele from indica allele in each gene group, respectively  of CLD. Our present study showed the RCL10/24 value was 0.16 for IR64 and 0.29 for Nipponbare  and low percentage of short and intermediate chain fraction  in the starch. In terms of the longer chain fraction (∑DP > 24), SSIIaj was the highest but not significantly different to a few other alleles in the group  comparing to SBEIIai and SBEIIbj alleles. Tr was the least diverse RVA parameter in this analysis, showing only about 30 and 10 RVU significant increase in SSIj and SBEIIbi alleles comparing to their counterpart-alleles, respectively. Significant differences in BD were obtained in Wx, SSI, SSIIa and SBEIIa allele groups, with the greatest (~70 RVU) between SSIIai and SSIIaj alleles. Compared to their counterparts, the values of BD were increased by ~40 RVU in Wxj allele, and ~30 RVU in SSIi and SBEIIaj alleles. In terms of FV, significant variations were found in Wx, SSI and SBEIIb allele groups, with the highest (~40 RVU) between SSIi and SSIj alleles, ~30 and 15 RVU in Wx and SBEIIb allele groups, respectively. The significant variations of SB were 42 RVU in Wx group and 28 RVU in SSIIa group. Less than 10 RVU increase of SB in both SSIj and SBEIj alleles were also significantly different. Significant differences in PT were determined between SSI alleles (0.6 min) and Wx group (0.2 min). The PT values were mainly clustered into the two Wx alleles groups, while IR64 was the lowest. Notably, the SSIIaj allele starch exhibited remarked differences in paste viscosities from all the others including parental controls.IR64 and Nipponbare showed significant differences in all parameters except for FV Table . RILs in1To, 1Tp and 1Te, and those of the second peak as 2To, 2Tp, 2Te. 1ΔH was named for the amylopectin gelatinization enthalpy, and 2ΔH for the dissociation enthalpy of amylose-lipid complexes. As shown in Table SSIIaj allele had a major effect, while Wxi allele played a minor role in decreasing 1Tp. However, SSIj, SSIIaj and Wxi alleles increased 2ΔH.Consistent with previous studies, two primary peaks were observed in DSC curves for rice wholemeal samples: the first one was the initial gelatinization peak at 65 ~ 85°C of amylopectin; the second one at around 105°C was the amylose-lipid complex dissociation peak  and pasting properties (PV) of starches  compared to their counterpart-alleles. This correlation again confirms starch paste and thermal properties are negatively regulated by the ratio of amylose produced in the grains.Starch AC has been reported to be negatively correlated with the gelatinization  containing a SSI allele from an indica rice on a japonica rice background and concluded the variation in SSI alleles between indica and japonica rice hardly affected starch peak viscosity and gelatinization temperatures. The SSIIaj allele starch showing more short chains and less intermediate chains was determined with a remarkably high RCL10/24. This variation led to distinctive characteristics of starch properties with the lowest PV, BD, and lowest gelatinization temperatures. Despite other alleles within Wxi allele group showed lower PV and BD than IR64, they were comparable in RCL10/24 values. Consequently, these alleles barely contribute to the variations of RVA and DSC characteristics within the Wxi allele group. Within the Wxj allele group, the SSIIai allele was prevalent showing similar CLD patterns, which was significantly different from Nipponbare. The SBEIIbj allele had a significantly higher RCL10/24 value comparing to SBEIIbi, but it was much lower than that of Nipponbare. The SBEIIbj allele had abundant short chains in amylopectin with lower PV, Tr and lower FV and lower 1Te than SBEIIbi allele.Previous studies showed that short chains (DP 6 ~ 10) and intermediate (DP 11 ~ 24) chains of amylopectin are the major components of amylopectin structure in rice endosperms Hizukuri . The varo et al.  studied CL10/24 is negatively correlated with starch viscosity and thermal gelatinization properties. An increase of RCL10/24 can reduce the PV values of RVA and gelatinization temperature of DSC due to the increase of short chains proportion and/or decrease of intermediate chains proportion. SSIIaj is a major allele and SBEIIbj is a minor allele in the determination of RCL10/24 in this study. Interestingly, starch PV and gelatinization temperatures of the SSIIaj allele are even lower than Nipponbare, though the SSIIaj allele RCL10/24 is smaller. This is because SSIIaj allele combines with Wxi allele in the corresponding RILs. Such changes of starch properties were also reported by Umemoto et al.  and Wxi (high AC), with minor alleles, SBEIi and SBEIIbj.Given all the analyses above, Ro et al.  through Wx allele group showed significant variation in the abundance of GBSSI in the starch granule of rice grains. RILs with the Wxj allele contained a relatively low abundance of GBSSI and a low level of starch AC compared with those with the Wxi allele. This was consistent with previous studies which demonstrated that Wxj allele produces low levels of mature enzymes  parental lines [cultivars IR64 (indica pollen donor) and Nipponbare (japonica acceptor)] were used for producing a RIL population. Four F2 seeds from one F1 seed were produced (kindly provided by Dr. Narayana Upadhyaya). Only one F2 plant was used for producing all RILs in this study. The detailed steps for selecting RILs for six allele groups are listed in Figure Two rice  ethanol. After centrifugation at 3000 g, the genomic DNA in the pellet was then dissolved in 50 μl MilliQ water.indica derived from IR64 were assigned as Wxi, SSIi, SSIIai, SBEIi, SBEIIai and SBEIIbi, and corresponding japonica alleles derived from Nipponbare were named as Wxj, SSIj, SSIIaj, SBEIj, SBEIIaj and SBEIIbj. The alleles were segregated in different combinations during subculture, and F5 homozygotes were used for further analyses.The genotypes of RILs for the selected genes in the study were identified based on a PCR approach using published markers , SSIIai, SBEIIaj and SBEIIbj (line 3-6-9), and SSIIai, SBEIIai and SBEIIbj (line 3-6-20), respectively. RIL line 3–14 was homozygous at SSIi, SSIIai, SBEIi, SBEIIaj and SBEIIi, and heterozygous at Wx. Wxi and Wxj alleles were obtained in lines 3-14-12 and line 3-14-13 lines in the F4 progeny.Three F3 RILs  from one F2 line were used for the further selection of different combinations of the 6 genes by self-pollination due to their homozygosity and heterozygosity of six different genes in three F3 lines. Line 3–5 was homozygous for Whole grains of each line (approximately 100 ~ 150 mg) were ground in a capsule with ball bearing using an ESPE CapMix™ . Grinding was done for 30 sec three times. The wholemeal flour was then washed with 0.005% NaOH by vigorous vortexing for 2 minutes followed by filtration through 0.5 mm nylon sieves. Each sample was then washed three times by vortex mixing and centrifugation at 5000 g for 5 min. The starch pellet was resuspended in a phosphate buffer  containing proteinase K (50 μg/ml) and incubated at 37°C for 2 hrs. After 5 min centrifugation at 5000 g, the pellet was suspended in water and centrifuged. Thus water wash was repeated three times. The starch pellet was then washed with acetone, centrifuged and the residual starch was air dried at 37°C overnight.The amylose content of samples was determined by analysing debranched starches using size-exclusion chromatography (SEC) with Ultrahydrogel  as described previously  were ground into flour in a stainless steel capsule on a ball bearing machine  for starch property analysis. A Rapid Visco Analyzer  was used to determine starch paste viscosity parameters of the selected RILs. Three grams of rice grain wholemeal for each of three plants of each RIL were used for analyses. The program setting for the RVA comprised the following stages: hold at 60°C for 2 min, heat to 95°C over 6 min, hold at 95°C for 4 min, cool to 50°C over 4 min, and hold at 50°C for 4 min. The software Thermocline  was used for data collection and analysis.A Differential Scanning Calorimeter  was used to determine the calorimetry profiles of flour samples of 3 different plants with triplicate for each RIL. For each line, 60 mg of flour was weighed and mixed with water at ratio of 1.76 : 1. Afterwards, 3 aliquots with 45 mg of each prepared from the starch-water premixed product were transferred to DSC pans separately, and used as replicates. The pans were then sealed and placed on the bench at room temperature to equilibrate overnight. A heating rate of 10°C min was used to heat the samples at 30 ~ 130°C. Data was analysed using the instrument software provided by the manufacturer.The starch prepared from mature grains by the method described above was used for preparing GBPs of each line. Following the procedures by Rahman et al.  with somSupernatants (25 μl) containing GBPs of each sample together with 5 μl of marker were loaded onto SDS-PAGE gels, respectively. SDS-PAGE was conducted in Nu-PAGE 4-12% gradient gels (Invitrogen) via MOPS-Tris-SDS buffer system containing  and operated at 20 mA constant current per gel in an Xcell SureLock™ Mini Cell (Invitrogen). After electrophoresis, gels were stained by Sypro Ruby stain (Bio-Rad) following the manufacturer’s instructions, and then visualized under a UV transilluminator . MagicMark™ XP Western Standard protein ladders (Invitrogen) were used to estimate the molecular weight of protein bands.p < 0.01, looking at variations among the RILs.Statistical analyses were performed using Genstat version 9. Analysis of variance was performed for starch AC, amylopectin structure, RVA and DSC characteristics to obtain the least significant differences at


Rheumatology is at a very exciting stage in its long and illustrious history. New biological therapies have revolutionized the treatment of immune-mediated inflammatory diseases. The genetic, epigenetic and environmental mechanisms that drive musculoskeletal diseases are giving up their secrets, and patients are much more involved in the decisions that matter to them… “nothing about us without us”. These rapid advances in musculoskeletal medicine suggest that finally Cinderella has come to the ball!Arthritis Research & Therapy (AR&T) and whom is the journal aimed at?Musculoskeletal medicine is a broad field, which encompasses many clinical and scientific disciplines that are already served by excellent journals. So what is unique about In its first decade, AR&T under the guidance of its founding Editors has established itself as a leading journal for the community of researchers and clinicians interested in the science of musculoskeletal medicine. It is open access, links basic science with clinical advances and enjoys independence and a freedom to be innovative; for example, it was the first open-access journal in the field. We believe that this is key for our continued growth.What will be our editorial focus as we work with our illustrious editorial team to steer the journal as it enters its second decade? Our goal is to ensure that the journal serves and is served by a loyal and engaged scientific and clinical community. That is why we have followed our founders’ policy of having two Editors-in-Chief: one a clinician, the other a scientist. We also believe that, more than ever before, the best developments and discoveries occur through collaborations across various academic centres worldwide. This is why our two Editors are from different continents and our Section Editors are from all over the world. We will continue to seek out genuine translational science that has delivered such stunning advances and at the same time we will adapt to changes in the scientific landscape. To achieve this, we have set ourselves the following objectives.Firstly, we will continue to expand the remit of the journal to include other rheumatic diseases such as osteoarthritis, crystal arthritis, lupus and the connective tissue diseases. Although AR&T has traditionally focused on translational research, it has not published many pivotal clinical trials. Therefore, we will try to publish the best clinical trials and outcome studies, including those that report on health economic evaluation.Secondly, we aim to continue to publish research of the highest quality related to basic biological processes. We will accomplish this by attracting manuscripts that report the use of cutting-edge technologies that link clinical and radiologic phenotypes with genomic, transcriptomic, epigenomic and proteomic measurements in clinical samples from patients with musculoskeletal disease, thereby generating new insights and hypotheses about disease pathogenesis.Thirdly, we will reinvigorate our reviewer base by promoting the role of junior faculty and, in particular, postdoctoral fellow researchers. These young investigators represent the future of our specialty and need our encouragement and support as they work to generate insights and therapies for the future. We would like these young members of the journal to become the new backbone of our review process. We will also highlight the research of junior fellows by using podcasts. This junior generation are our future and they deserve attention in promoting their outstanding work. They are very competent and comfortable with new technologies yet often feel undervalued and under-represented.Fourthly, we will work with specialty societies to highlight novel ongoing research at their meetings in an aim to expand the research scope and reportage of the journal.Finally, we will focus on editorials that highlight cutting-edge areas of rheumatic disease that are published in our journal as well as others.So how will we achieve these goals? We have established a new editorial structure with an international selection of outstanding and expert investigators. These new Section Editors will oversee six general research themes: David Pisetsky (USA) – Immunology and Pathology; Maya Buch (UK) – Pharmacology and Therapeutics; Laure Gossec (France) – Epidemiology and Clinical Trials; Edward Schwarz (USA) – Outcomes and Imaging; Kazuhiko Yamamoto (Japan) – Genetics and Epigenetics; and Thomas Pap (Germany) – Bone and Cartilage Biology.We have moved over to an easy-to-use online editorial management system that will improve our governance and editorial consistency and enhance the turnaround rate for manuscripts. It will also allow us to monitor the review process and tell us whether we are accomplishing what we said we would. We have refreshed and will continue to revise our pool of Associate Editors and Board Members so that we have more involvement from junior faculty. We are also fully aware that reviewer fatigue is a problem throughout academia. Therefore, our Associate Editors and Board Members will commit to reviewing at least six manuscripts a year. They will also act as our advocates for the journal to the scientific, clinical and patient populations that we serve.Our ultimate aim is to be not only a trusted, internationally respected rheumatic disease journal but one that expands the boundaries of musculoskeletal disease research and identifies with an empowered scientific and clinical community. Thus, although impact factors do matter, we are not obsessed by them. We believe that by engaging with our research community we will attract the best research that will ultimately lead to an increased impact factor and enhance our international recognition. As the new Editors we invite you to join us in this new mission for AR&T.


The number of educational resources created for emergency medicine and critical care (EMCC) that incorporate social media has increased dramatically. With no way to assess their impact or quality, it is challenging for educators to receive scholarly credit and for learners to identify respected resources. The Social Media index (SMi) was developed to help address this.We used data from social media platforms  for EMCC blogs and podcasts to derive three normalized  formulas. The most statistically robust formula was assessed for 1) temporal stability using repeated measures and website age, and 2) correlation with impact by applying it to EMCC journals and measuring the correlation with known journal impact metrics.The logarithmic version of the SMi containing four metrics was the most statistically robust. It correlated significantly with website age  and repeated measures through seven months . When applied to EMCC journals, it correlated significantly with all impact metrics except number of articles published. The strongest correlations were seen with the Immediacy Index  and Article Influence Score .The SMi’s temporal stability and correlation with journal impact factors suggests that it may be a stable indicator of impact for medical education websites. Further study is needed to determine whether impact correlates with quality and how learners and educators can best utilize this tool. The number of educational blogs and podcasts in emergency medicine and critical care (EMCC) has increased dramatically in the past decade,st century equivalent of textbooks and lectures,Unfortunately, minimal research has been done to date on how to critically appraise the quality of secondary resources in medical education. Blogs and podcasts could be viewed as the 21New metrics are needed to assess the impact of blogs and podcasts in a similar way that impact factors assess journals. The journal impact factor (JIF) and Eigenfactor™ metrics were developed to illustrate the scientific importance of traditionally published academic literature.Alternative metrics  that assess online engagement through a broad range of measures have been found to correlate with the citations of journal articles,In this paper we propose and define the Social Media index (SMi), a new metric that combines various altmetrics to measure the impact of websites as a whole. It differs from the metrics previously described in that it combines social media followership with composite website rankings into a score for a website rather than an article, blog post, or journal. It was derived using open-access EMCC podcasts and blogs because of the large number of these resources available.BoringEMAcademic Life in Emergency Medicine.21The SMi was developed by the lead author of this paper (BT). Pilot versions have previously been published on the emergency medicine blogs Life in the Fast Lane (http://lifeinthefastlane.com) website. We conducted a retrospective keyword search using Google in November 2013 using the terms:  AND (podcast OR blog) to identify any websites missed using the other processes. All websites found were reviewed and included in the study if they hosted freely accessible blogs or podcasts related to EMCC, were written in English, were active within the previous six months, and were not hosted on an institution’s or medical journal’s website.We obtained a list of 245 EMCC websites using a previously described methodology.a priori to provide a broad range of literature of relevance to EMCC physicians. As categorized by the 2012 Journal Citation Report Journal Impact Factor,New England Journal of Medicine, Journal of the American Medical Association, Lancet, British Medical Journal, and PLOS Med) and all “emergency medicine” and “critical care” journals composed in English were considered for inclusion. Journals with Facebook and Twitter accounts were included in the analysis.Journal inclusion criteria were decided The five variables described in We gathered data on all five metrics from the included EMCC websites for four consecutive weeks between December 29, 2013 and January 19, 2014 and again on July 27, 2014. The final collection point was initially planned for six months; however, the authors were unavailable to collect data until nearly seven months. On each date, data for all websites were collected within a single 12-hour period by one of two authors  and audited by a third (BT). Data were gathered on the EMCC journals on January 20, 2014, within 24 hours of the website data collection on January 19, 2014.We initially calculated the SMi using raw data. However, due to high skewness, modified versions were calculated using logarithmically transformed data and ordinal data. In all formulas each of the five metrics was given equal weight by normalizing the individual values relative to the highest value. We then added the scores for each component to calculate the SMi.The rankings of the SMi and each of its components were calculated separately for EMCC website and journals. This allowed the relative rank and impact of each website and journal to be assessed in their respective category.We calculcated descriptive statistics for the website SMi and each of its components. We determined its temporal stability by correlating its values at one time point with its values one week, two weeks, three weeks, and seven months later. We also determined the correlation between the SMi on December 29, 2013, and the age of each website.We measured the correlation between traditional journal impact metrics , the journal SMi score, and the components of the journal SMi . Spearman rank correlations were used for the analysis due to the non-linear monotonic associations present in the data. We used a two-sided alpha of 0.05 to determine statistical significance.One hundred sixty-three of 245 (66.5%) of the websites and 29 of 44 (65.9%) of the journals met the outlined inclusion criteria. The mean (SD) and median (IQR) age of EMCC websites was 2.9 (1.9) years and 2.0 (2.0) years with the oldest being 12 years old.We assessed five selected variables for inclusion in the SMi, but Google+ was excluded because few (6.7%) of the websites had substantive accounts (>100 followers). Substantive accounts were available for a much greater proportion of websites on Alexa (95.7% ranked), PageRank (76.7% rated >0), Twitter (71.8% had >100 followers) and Facebook (25.2% had >100 likes).The formulas that we considered are listed below where A=Alexa; P=PageRank; T=Twitter; F=Facebook; x=blog, podcast, or journal; m=maximum value; Rx= rank of x . The fouAlthough the logarithmic and ordinal versions of the SMi were highly correlated (Spearman r>0.95), the logarithmic version of the SMi (logSMi) was judged to have the best operational characteristics because it was the most normally distributed and least subject to skewness of the individual components. Therefore, it was selected as the definitive SMi formula for further evaluation and henceforth will be referred to as the SMi.The SMi was significantly correlated with website age  and itself over one-week, two-week, three-week, and seven-month periods:December 29, 2013 to January 5, 2014, r=0.991, p-value<0.001; December 29, 2013 to January 12, 2014, r=0.796, p-value<0.001; December 29, 2013 to January 19, 2014, r=0.806, p-value<0.001; December 29, 2013 to July 27, 2014, r=0.929, p-value<0.001.The SMi demonstrated a wide range with normal distribution. For websites the mean (SD) was 4.52 (1.65), with a range from 1.06 to 9.40. When applied to the included journals the SMi had a mean (SD) of 6.27 (1.30) with a range from 3.84 to 9.26.New England Journal of Medicine  and JAMA  had high social media followership for journals.Social media followership for websites and journals varied widely across each component of the SMi . ECG ExpNew England Journal of Medicine (9.26), British Medical Journal (9.09), and JAMA (8.75). The large increase in SMi, by approximately one standard deviation, between American Journal of Critical Care and Lancet illustrates the jump from specialty-specific EMCC journals to general medical journals. The highest ranked emergency medicine-specific journals were Annals of Emergency Medicine (6.61), Emergency Medicine Journal (6.22), and Academic Emergency Medicine (5.96).Ranked in their own media categories by SMi  and 3b, Traditional journal impact metrics correlated significantly with journal SMi score . The strWhen assessed alone, each of the journal SMi components also correlated with traditional journal impact metrics . This waRegardless of one’s beliefs in the merit of using secondary sources such as blogs and podcasts for medical education, their rapid growth12The SMi has several characteristics that make it a viable measurement of impact for learners, educators, and administrators. First, learners, educators, and administrators can apply these publically available metrics and transparent SMi formula without permission or cost. Second, our assessments of the SMi’s temporal attributes suggest that it measures long-term impact, rather than spikes in popularity. Furthermore, it is not unduly influenced by longevity, suggesting it is possible for new resources to be recognized.Because no gold standard exists to measure social media educational resource impact, we examined how the SMi formula for journal websites would perform in comparison to traditionally recognized journal impact metrics. Our data found that a journals’ online followership, as quantified by the SMi formula, correlates with these metrics. Its particularly strong correlation with the Immediacy IndexTwo of the four components of the SMi, Alexa Rank and Google PageRank, focus on website traffic and inbound links.The other two components of the SMi, Twitter Followers and Facebook Likes, also correlated with traditional journal impact factors. This is unsurprising as the altmetrics of individual articles have been shown to correlate with future citations,To further the research agenda on the assessment of social media educational resources, our research group is in the process of deriving a quality assessment tool for blogs and podcasts using education literature and data from modified Delphi surveys of stakeholders. Future studies will assess the validity of this quality assessment tool and its correlation with the SMi. Our hypothesis that followership is a surrogate marker of quality will continue to be tested and modified with this research.http://aliem.com/social-media-index. Additionally, as online resources are developed outside of EMCC we anticipate calculating rankings for medical education blogs and podcasts in other health professions.Moving forward, we are designing a program that will gather the required data, calculate the SMi, and update a webpage on a weekly basis. The results will be openly accessible on the website Whenever an evaluation tool is developed that openly defines the individually measured components, it becomes possible to ‘game’ the system.29There are many other social media platforms used by blogs and podcasts that were excluded from the SMi. Not taking these platforms into account may underscore websites that use platforms such as Google+, YouTube, and iTunes to distribute their content. However, due to the small number of websites using these platforms (Google+ and YouTube) and lack of publicly available metrics (iTunes) they were excluded from the current iteration of the SMi. As social media continues to evolve, the SMi may be modified to accommodate trends in its use.In this study the SMi was derived using a subpopulation of medical education websites (blogs and podcasts) focused on a relatively specific field (EMCC). This was done intentionally to provide a homogenous group of websites for derivation of the SMi. However, its generalizability would be strengthened if it were applied successfully to other online educational products from various fields of medicine. Follow-up studies using the methodology outlined in this study and websites/journals from other specialties could provide further validity evidence for the SMi.The selection of time intervals to assess the temporal stability of the SMi was somewhat arbitrary. We intended to demonstrate short-term stability with the weekly intervals and medium-term stability with follow-up approximately six months later; however, other time intervals could have been selected. We cannot speculate as to how this would have affected our results. While the collection of our final data point was slightly delayed, the strong week-to-week correlation at the beginning of the study suggests it would have been unlikely to change our results.The number of educational websites continues to grow, especially in the field of EMCC. The SMi has the potential to be a stable and accessible indicator of their impact. If the results of this study can be replicated it would benefit medical professionals by identifying resources for learners and assessing scholarly impact of educators that are using these media. Regardless of whether the SMi becomes the gold standard for the assessment of impact for online medical education resources, it should contribute to the discussion towards the development and validation of impact and quality metrics.


Including results from unpublished randomized controlled trials (RCTs) in a systematic review may ameliorate the effect of publication bias in systematic review results. Unpublished RCTs are sometimes described in abstracts presented at conferences, included in trials registers, or both. Trial results may not be available in a trials register and abstracts describing RCT results often lack study design information. Complementary information from a trials register record may be sufficient to allow reliable inclusion of an unpublished RCT only available as an abstract in a systematic review.ClinicalTrials.gov. Two persons extracted verbatim primary and non-primary outcomes reported in the abstract and ClinicalTrials.gov record. We compared each abstract outcome with all ClinicalTrials.gov outcomes and coded matches as complete, partial, or no match.We identified 496 abstracts describing RCTs presented at the 2007 to 2009 Association for Research in Vision and Ophthalmology (ARVO) meetings; 154 RCTs were registered in ClinicalTrials.gov primary or non-primary outcome. Among 705 non-primary outcomes, 56 (8%) agreed completely, 205 (29%) agreed partially, and 444 (63%) had no match with a ClinicalTrials.gov primary or non-primary outcome. Among the 258 outcomes partially agreeing, we found additional information on the time when the outcome was measured more often in ClinicalTrials.gov than in the abstract (141/258 (55%) versus 55/258 (21%)). We found no association between the presence of non-matching “new” outcomes and year of registration, time to registry update, industry sponsorship, or multi-center status.We identified 800 outcomes in 152 abstracts (95 primary [51 abstracts] and 705 [141 abstracts] non-primary outcomes). No outcomes were reported in 2 abstracts. Of 95 primary outcomes, 17 (18%) agreed completely, 53 (56%) partially, and 25 (26%) had no match with a ClinicalTrials.gov. Complementary additional descriptive information may be present for outcomes reported in both sources. However, ARVO abstract authors also present outcomes not reported in ClinicalTrials.gov and these may represent analyses not originally planned.Conference abstracts may be a valuable source of information about results for outcomes of unpublished RCTs that have been registered in  Researchers depend on randomized controlled trial (RCT) findings reported in publications to help inform the design of future studies and assess the effectiveness and harms of a health intervention. Systematic reviewers synthesize the findings from similar but separate trials to estimate an average effect of an intervention; several factors threaten the validity of that estimate, potentially affecting many stakeholders–clinicians, funders, researchers, patients and policy makers –3. For eChalmers and Glasziou identified four places where waste can occur in the research enterprise, including lack of “accessible full publications” and “unbiased and usable reports” . SystemaClinicalTrials.gov for approved drugs and devices within 12 months of study completion to include primary, principal secondary, and safety outcomes from the trial results. However, reporting results from all outcomes named in the protocol is not required [ClinicalTrials.gov is a rich source of information about study design and execution [Trial registration is increasingly being required for many trials for publication, by regulatory bodies , or locarequired  nor do arequired , 10. Currequired  even thoConference abstracts with no associated full publication may provide additional information for a systematic review and are often a source of unpublished, null and negative trial results. Because about 40% of RCT results initially reported in conference abstracts are not published in full, even after 9 years , the InsAnother way to look at the problem, however, is that if conference abstracts and trials registers inform us about the existence of unpublished trials we might otherwise not have known about, then trial registry information could supplement the conference abstract information. Conversely, conference abstracts could provide results for outcomes or results that are not reported in a trials register.ClinicalTrials.gov [ClinicalTrials.gov. Our goal was to determine whether outcome information from the trial registry could supplement incomplete data on outcomes described in conference abstracts, and to assess the presence and types of discrepancies in outcomes reported between the two sources.For our study, we selected abstracts presented at the Association for Research in Vision and Ophthalmology (ARVO) conference because any conference abstract submitted to ARVO from 2007 onward and describing trial findings is required to be registered. We found that the majority of RCTs described in ARVO abstracts and that reported trial registration were in fact registered with ials.gov . Our objWe previously described the methods for identification of reports of RCTs presented in conference abstracts at annual ARVO meetings from 2007 through 2009 . BrieflyClinicalTrials.gov website . We classified a trial registration number as valid if there was a corresponding record in ClinicalTrials.gov. We excluded abstracts where the ClinicalTrials.gov record did not describe a population with an eye condition or a population in which one of the trial goals was treatment of or prevention of an eye condition. We also excluded abstracts that described secondary analyses of trial data, nested case-control studies, ancillary studies, and methodological studies associated with an RCT, and abstracts where the ClinicalTrials.gov report clearly stated that the assignment to treatment was not randomized. For RCTs with valid registration numbers, the tabular view of the ClinicalTrials.gov record was accessed on the Internet and hardcopies printed during May and June 2009. If a single trial, as designated by a single ClinicalTrials.gov registration number, was identified in multiple abstracts describing trial findings, we used information from all abstracts to compare with the ClinicalTrials.gov record.The trial registration number included in the abstract was entered in the search function of the ClinicalTrials.gov report on pre-tested paper data collection forms as previously reported [ClinicalTrials.gov report. Outcome data were collected by recording the outcome(s) exactly as written in both sources and recording whether each outcome was classified as a primary or non-primary outcome. For ARVO abstracts, we defined a primary outcome to be any outcome explicitly described as a primary outcome; all other outcomes named in the abstract were classified as non-primary outcomes. For ClinicalTrials.gov records, we defined only the outcome included in the Primary Outcome field in the tabular view of the record as a primary outcome; all other outcomes named in the ClinicalTrials.gov record were classified as non-primary outcomes, including those reported as secondary or safety outcomes. Discrepancies in data abstraction were resolved by consensus between the two abstractors.Two persons (RWS and LH) independently extracted similar information on study design characteristics from both the abstract and from the reported . All datClinicalTrials.gov, we listed each outcome reported in the abstract for a study and then compared each separately with the list of outcomes for that study as reported in ClinicalTrials.gov. We first assessed agreement between each outcome and the primary outcome recorded in ClinicalTrials.gov. If there was no match, we then assessed agreement with each non-primary outcome listed in ClinicalTrials.gov. Agreement was classified as complete agreement, partial agreement, or no agreement. We defined complete agreement as outcomes that were either identical word-for-word, or had synonymous or almost the same wording. For example, we considered the primary outcome in the abstract written as “clinical cure ” to be synonymous with the primary outcome in ClinicalTrials.gov “clinical cure on test of cure visit at day 9, defined as score of 0 for bulbar conjunctival infection and a score of 0 for conjunctival purulent discharge”. In another example, we classified pairs as having “partial agreement” when the abstract stated the outcomes was “visual acuity at 6 months using ETDRS charts” while the ClinicalTrials.gov record stated simply “visual acuity”; we recorded that additional information was provided by the abstract . We classified the additional outcome information by time point when outcome was measured or ‘other’  because it would not be reasonable to expect an abstract to include all outcomes reported in ClinicalTrials.gov. Discrepancies in classification of agreement between the two data abstractors were resolved by consensus.Because there were multiple outcomes reported in both the abstract and a priori hypothesis, we did not perform a sample size calculation. All data were entered into an Access 2010 database . Analyses, including descriptive analyses and χ2 tests to examine differences in proportions, were performed using SAS, version 9.3 .Because we had no ClinicalTrials.gov . We identified 800 outcomes in 152 abstracts; there were no outcomes reported in 2 abstracts. We classified 95 outcomes in 51 abstracts as primary outcomes and 705 outcomes in 141 abstracts as non-primary outcomes  of ClinicalTrials.gov records, and information on the time point when the primary outcome was to be measured for 72% of them (89/124). There was no primary outcome reported in the ClinicalTrials.gov “Primary Outcome” field for 15 of the primary outcomes reported in 11 abstracts. Comparison of the remaining 80 primary outcomes (reported in 40 abstracts), with the primary outcome recorded in ClinicalTrials.gov, resulted in 14 (18%) agreeing completely, 39 (49%) agreeing partially, and 27 classified as not matching , 3 agreed exactly and 14 agreed partially with a non-primary outcome in ClinicalTrials.gov; 25 remained unmatched and were classified as “new” outcomes  agreed exactly and 95 (13%) agreed partially with a secondary or safety outcome reported in ClinicalTrials.gov; 444 (63%) were not reported in ClinicalTrials.gov and were classified as “new” outcomes  agreed partially with the primary outcome reported in omes see .ClinicalTrials.gov, while all abstracts had at least one outcome that agreed exactly  or partially , with a primary or secondary outcome recorded in ClinicalTrials.gov. However, 111 abstracts (73%) had at least one outcome that had no matching outcome in ClinicalTrials.gov.Altogether, across the 152 abstracts reporting any outcome, 96 (63%) reported an outcome that agreed exactly  or partially  with a primary outcome recorded in ClinicalTrials.gov  had not updated the original trial registration. Examining updated records only, the mean (SD) and median time from registration to the most recent update was 1.58 (1.12) years and 1.58 years, respectively. We found no association between the presence of a “new” outcome and either of these measures of registration time (data not shown).We explored factors that could be associated with the presence of a “new” primary outcome or non-primary outcome. We first looked at information on time of initial trial registration. The date of trial registration ranged from 1999 to 2008, with a median registration date of November 2006. Twenty-six of 152 trial records in ClinicalTrials.gov record; there was no statistically significant association between industry sponsorship and the presence of a new outcome; 58% (65/111) of abstracts with a new outcome versus 49% (20/41) without a new outcome had industry sponsorship . Multicenter status was likewise not associated with a new outcome (40/111 (36%) versus 15/41 (37%); OR = 0.98; 95% CI = 0.47 to 2.06).We also explored whether there was an association between industry sponsorship or multi-center status and the presence of a “new” outcome. Eighty-five trials (56%) received industry sponsorship as noted in either the abstract or the ClinicalTrials.gov see ClinicalTrials.gov for 17 (44%), and in both sources for 3 (8%) primary outcomes. Of the 205 non-primary outcomes that were in partial agreement, 110 (54%) were described in more detail in ClinicalTrials.gov, and 64 (32%) in more detail in the abstract. The remaining 31 (15%) outcomes in 21 pairs classified as partially agreeing had non-overlapping additional information in both sources. ClinicalTrials.gov was present on the time point when an outcome was measured. The occurrence of ‘other’ information was about the same for both sources.Further examination of the 39 primary outcomes that we classified as partially agreeing showed that although these agreed by domain, additional information related to the time point when the outcome was measured or ‘other’ information  was present in one source but not the other  of outcomes described as a primary outcome in the abstract were also described as a primary outcome in ClinicalTrials.gov.In our study we found that among 152 ARVO abstracts reporting an outcome, 63% (96/152) reported at least one outcome that matched a primary outcome in the ClinicalTrials.gov could supplement the limited information found in an ARVO conference abstract, facilitating inclusion of conference abstracts in a systematic review when there is no corresponding full publication or an outcome was reported in the abstract that a systematic reviewer wanted to include. The reverse might also be important, i.e. the information in a conference abstract may complement what is recorded in a trials register. ClinicalTrials.gov often has no results [ClinicalTrials.gov is likely to have more detailed design information than a conference abstract [The original goal of this study was to see if the design information recorded in  results , and thuabstract , it is aClinicalTrials.gov, and always by outcome domain. Other elements were inconsistently reported both in the ARVO abstract and in the ClinicalTrials.gov record. For example, among the primary outcomes reported in ClinicalTrials.gov, there was no associated time point when the outcome was measured in 28% (35/124) of the cases with an entry in the “Primary Outcome” field. On the other hand, when the outcome domain reported in the abstract matched that in ClinicalTrials.gov, we found the associated time point in ClinicalTrials.gov more often than in the abstract. This reporting pattern may be due to the requirement by ClinicalTrials.gov to include the time point when reporting outcomes. In contrast, other elements  were reported in one or the other sources with about equal frequency. Current recommendations as stated by Zarin [ClinicalTrials.gov “parallel the level of specificity described in the protocol”, suggesting that all five elements defining an outcome, as described above, should be included in the trials register record.Elements that are used to describe a trial outcome include the domain , time point at which the outcome is measured, method of measurement , method of aggregation , and specific metric  , 20. ManClinicalTrials.gov report for each RCT described in this report to look for posted publications and study results. As of 12 January 2015, there was at least one full length publication listed for 42% (64/154), and results posted for 23% (35/154) of RCTs described in the ARVO abstracts included in this report in ClinicalTrials.gov. Thus, trial results may be available for only about half  of the RCTs described in this report. RCT results were not required to be posted in ClinicalTrials.gov until 2009, however, so systematic reviewers who want to include an RCT that is neither published nor has results posted can obtain more information by accessing both the ARVO abstract and ClinicalTrial.gov than either one alone. We intend to continue to examine the RCTs reported here by systematically identifying all full length publications specifically reporting the results presented in the abstract and comparing the results described in the abstract with those presented in the full length publication and in ClinicalTrials.gov, if present.Based on historical patterns , we expeClinicalTrials.gov record. The large proportion of “new” outcomes reported in abstracts but not found in ClinicalTrials.gov, raises concerns about the possibility of selective outcome reporting in the abstract. This finding is in agreement with investigators who compared outcomes reported in abstracts, trial protocols, full-text publications and registries [We found that about three quarters of ARVO abstracts reported one or more primary or non-primary outcomes that could not be found in the gistries –31. For gistries . Norris gistries . Selectigistries . Other igistries , 31. TheClinicalTrials.gov record.Mathieu et al also showed a higher likelihood of reporting outcomes when results were statistically significant or when industry sponsorship was declared and outcomes favored industry’s drug In addition . We did ClinicalTrials.gov website defines which outcomes are to be entered, including primary, secondary, and “other pre-specified” outcomes. This latter category is defined in the ClinicalTrials.gov website as “Any other measurements, excluding post hoc measures, that will be used to evaluate the intervention(s)”[ClinicalTrials.gov register, and contribute to the presence of “new” outcomes. For example, investigators may not be able to register specific harms outcomes simply because the adverse event is unknown at the time of registration, but report these adverse events in conference abstracts. It would be of value for ClinicalTrials.gov to require inclusion of all outcomes in the future, noting which were pre-specified and which were added after trial inception. Alternatively, investigators’ failure to update the required primary and secondary outcomes entered in the trial registry may contribute to the presence of “new” outcomes. Since it is allowed, investigators may not be entering all pre-specified RCT outcomes in the ClinicalTrials.gov record, perhaps with outcomes reported in the conference abstracts deemed to be less important or ancillary. Because non-primary outcomes are not used to determine sample size and contribute to power calculations for trials, they may be considered less important by study investigators. On the other hand, a non-primary outcome may be considered a reasonable topic for presentation at a conference. Another possible reason for our finding of “new” outcomes in the ARVO abstract is that investigators may have elected to submit an abstract describing a post hoc outcome solely for the purpose of attendance at a conference. Currently, a ClinicalTrials.gov report serves as a proxy for a study protocol. However, comparison of the data elements recommended by SPIRIT for reporting trial protocols is much more detailed that a ClinicalTrials.gov report [Rather than selective outcome reporting, our findings may be due to the trial registration process. Instructions for registration at the ntion(s)”. Any outv report  and thisClinicalTrials.gov and the information does not agree. Certainly, a systematic reviewer would want to report the result of any outcome from an abstract with a matching outcome (primary or non-primary) in ClinicalTrials.gov. However, when the outcomes differ, systematic reviewers should consider how to proceed. For “new” outcomes not reported in ClinicalTrials.gov, a first step would be to investigate whether there is a corresponding full length publication or publically available protocol. Alternatively, the systematic reviewer could request information directly from the study investigators. In cases where these options are not available, and the outcome of interest is not listed in ClinicalTrials.gov, the systematic reviewer has the option of following the IOM recommendation to include trial results reported only in a conference abstract. Because results from abstracts that remain unpublished are less likely to show positive effects of a study intervention[Our findings beg the question of what systematic reviewers should do when outcome information is recorded on both an abstract and ervention, it woulClinicalTrials.gov prior to those dates. Instructions for registration when these trials were registered were not as explicit as 2015 instructions nor were quality control measures as rigorous. In 2013 there was still concern about the level of detail required for describing an outcome in ClinicalTrials.gov, however [ClinicalTrials.gov with results data presented in conference abstracts offers a viable alternative for obtaining more complete information about unpublished trials for use in systematic reviews than from either source alone.Several limitations of our study should be noted. Because we only looked at abstracts from ARVO, our study is limited to vision research and applicability of our findings to other areas of healthcare is uncertain. Other areas of healthcare may not have the proportion of “new” primary or non-primary outcomes reported in abstracts that we observed for ARVO abstracts. Secondly, we looked at abstracts that were presented in 2007, 2008 and 2009, and the trials they describe were registered at S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.


We present a heart transplant patient at his 17th year of uncomplicated follow-up. Within a frame of routine check out several tests were performed. With such a long and uneventful follow-up some degree of graft reinnervation could be anticipated. However, the patient's electrocardiogram and exercise parameters seemed largely inconclusive in this regard. The exercise heart rate dynamics were suggestive of only mild, if any parasympathetic reinnervation of the graft with persisting sympathetic activation. On the other hand, traditional heart rate variability (HRV) indices were inadequately high, due to erratic rhythm resulting from interference of the persisting recipient sinus node or non-conducted atrial parasystole. New tools, originated from network representation of time series, by visualization short-term dynamical patterns, provided a method to discern HRV increase due to reinnervation from other reasons. In patients with end-stage heart disease, heart transplantation (HTx) is associated with significant improvement in survival and in quality of life. However, after HTx multiple adverse events may occur, including acute rejections, graft failure, infections, allograft vasculopathy and arrhythmias including atrial fibrillation, all of which adversely affect long term survival. Complete denervation of the transplant significantly affects reactivity of transplanted heart and hemodynamics of circulation , PET with C-11 hydroxyephedrine, MIBI-SPECT and others, and proved non-uniform and occurring at variable time  dynamics were suggestive of only mild, if any parasympathetic reinnervation of the graft with persisting sympathetic activation via plasma catecholamines. On the other hand, traditional HRV indices were inadequately high, due to erratic rhythm resulting from interference of the persisting recipient sinus node or non-conducted atrial parasystole.To elucidate post-HTx HRV values , new tools are clearly needed. Here we represent the short-term dynamics of nocturnal RR-intervals by the novel complex network tools  showed normal coronary arteries without features of graft vasculopathy. Last myocardial biopsy performed in 2013 showed no signs of cellular rejection (ACR Grade 0 R). Standard graded cycle ergometry exercise test limited by exhaustion was performed (target HR was not used). Resting heart rate (82 beats/min) and BP values (140/84 mmHg), slowly increased up to 100 beats/min and 185/90 mmHg, respectively over 7 min. Maximal workload achieved was 75 W. During recovery phase a delayed HR recovery was noted, with HR gradually returning to its baseline value over 9 min.24-h Holter monitoring was performed. The recording was first analyzed using Del Mar Impresario Software. Time domain and frequency domain analysis of HRV was carried out, preceded by visual inspection of the automatic ECG recording. All supraventricular and ventricular extrasystoles were excluded. The nocturnal 6-h part was determined following the evident day-night switch in the length of RR-intervals. Highly irregular sinus rhythm pattern erratic rhythm - together with values of basic indices of HRV can be seen in Figure For additional analysis, a transition network—a novel network tool of time series representation , results in persistently elevated resting heart rate and decreased chronotropic reserve  or fixed (a year after HTx) or structured irregular (with erratic rhythms). Obviously, our analysis can be extrapolated to larger group of subjects, especially, in a follow-up study because development of arrhythmias increases with time passed after the HTx (Thajudeen et al., Further research based on augmented pool of data is needed, to assess clinical applicability of the new tools and their potential to provide additional insight in graft electrophysiology beyond standard surrogate measures of reinnervation, such as classical HRV analysis and HR response to workload. High vigilance and advanced diagnostic tools to assess allograft status are mandatory to allow for appropriate intervention in allograft-related syndromes that may emerge with improved survival of patients after transplantation.The study complied with the Declaration of Helsinki and was approved by the Bioethics Commission for Research of the Medical University of Gdańsk. The written informed consent was obtained from the study subject.JW, DM, and MG: substantial contributions to the conception and design of the work; JW: the acquisition of the data; KD: interpretation of data, revising it critically for important intellectual conent; MG: final approval of the version to be published; JW, DM: analysis, and interpretation of data, drafting the work, revising it critically for important intellectual content and approval of the final version to be submitted; the final revision of the resubmission. All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.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 thaliana mutants lacking the SS4 isoform of starch synthase have strongly reduced numbers of starch granules per chloroplast, suggesting that SS4 is necessary for the normal generation of starch granules. To establish whether it plays a direct role in this process, we investigated the circumstances in which granules are formed in ss4 mutants.ss4 leaf development, and in ss4 mutants carrying mutations or transgenes that affect starch turnover or chloroplast volume.Starch granule numbers and distribution and the accumulation of starch synthase substrates and products were investigated during ss4 leaves have no starch granules, but accumulate high concentrations of the starch synthase substrate ADPglucose. Granule numbers are partially restored by elevating the capacity for glucan synthesis  or by increasing the volumes of individual chloroplasts (via introduction of arc mutations). However, these granules are abnormal in distribution, size and shape.We found that immature SS4 is an essential component of a mechanism that coordinates granule formation with chloroplast division during leaf expansion and determines the abundance and the flattened, discoid shape of leaf starch granules. For examination of roots, plants were grown on Phytogel with nutrients (ss4-1 mutant and the double mutant ss3ss4 were described in ss4-3 mutant (SALK_096130) was used unless otherwise stated. It carries a T-DNA insertion in intron 4 of the SS4 gene, + 2186 bp from the start codon. The sex1-8 (gwd) mutant (SALK_077211) was described in GWD, lacks detectable GWD protein, and is phenotypically indistinguishable from the null mutant sex1-3 (arc mutants were: arc3-2 (SALK_057144), arc5-2 (SAIL_71_D11), arc6-5 (SAIL_693_G04) and arc10-2 (SALK_073878)  recombination. Using Gateway® LR clonase™ II recombination, glgA was transferred into the binary vector pB7WGY2, modified to contain a chloroplast targeted transit peptide (cTP) sequence  upstream and in frame with the N-terminal YFP . The resulting GS-containing construct (YFP-GS) was transformed into ss3ss4 double mutant plants. Four independent GS-transformed plants  were obtained by Basta® resistance screening. Transgene expression was confirmed by YFP fluorescence observation using a Zeiss LSM510 confocal fluorescence microscope.The full-length coding sequence of glycogen synthase SS4 gene are shown in Fig. S8, and oligonucleotide primers are in Table S1. PCR products SS4A and SS4B were cloned into the GATEWAY-ready pCR8/GW/TOPO TA entry plasmid and transferred into the destination vector to create pOpOff2(hyg)::SS4A and pOpOff2(hyg)::SS4B. These plus an empty vector were separately transformed into plants. Transformants were selected on media containing hygromycin, and single-copy homozygous lines were produced.Dexamethasone-inducible constructs were made with the pOpOff2(hyg) destination vector system , digested with RQ1-DNAse (Promega), and used for cDNA synthesis. Semi-quantitative PCR was carried out with oligonucleotide primers listed in Table S1, using the TUBULIN gene as a control. For starch analysis, samples were taken at the end of the night and the day following the final spraying .Ten-day-old plants were sprayed with 30 μM dexamethasone daily, 10 h into the 12-h light period, for 10 d. For measurements of Sample preparation for electron and light microscopy was as described by Analysis of chain lengths was as described by Starch, soluble glucans and sugars were extracted and assayed enzymatically (−1). Extracts (32-μl) were loaded onto nondenaturing polyacrylamide gels containing 0.3% (w/v) glycogen. After incubation for 16 h at 20°C in 100 mM HEPES-NaOH, pH 7.5, 2 mM DTT, 10% (v/v) glycerol, 0.5 mM EDTA, 0.5 M Na-citrate, 2 mM ADPglucose, starch and glycogen synthase activities were revealed by iodine staining.Starch synthase activity was assayed according to www.sigmaaldrich.com). Electrophoresis and immunoblotting were as described by An antiserum was raised commercially in rabbits using the synthetic peptide DIGHDDGKNLDNIT (present in SS4 but not other starch synthase isoforms). Antibodies were affinity-purified using this peptide. Leaf tissue was powdered in liquid nitrogen then extracted in Laemmli sample buffer containing SDS and 1% (v/v) protease inhibitor cocktail , less degradation of starch during the night (measured as end-of-day minus end-of-night starch contents) and higher end-of-night starch contents .As reported previously .We examined whether loss of SS4 affected starch content in the primary root cap, a region of high starch content in wild-type plants. Starch in the columella cells is essential for the normal gravitropic response of the root . There wss4 leaves, but are immediately degraded. To examine this possibility, we introduced into the ss4 background a mutation that blocks starch degradation in wild-type plants. The sex1 mutation affects glucan, water dikinase (GWD), a starch-phosphorylating enzyme that renders the surface of the starch granule accessible to starch degrading enzymes at night . Mature leaves had high starch contents at the end of both the day and the night. However, immature leaves contained very little starch and most chloroplasts appeared to contain no granules  revealed less than two-fold differences between their ADPglucose concentrations and those of wild-type plants , because these mutants contain even fewer starch granules than the ss4 mutant  from 4 mutant . Indeed,Agrobacterium GS was introduced into ss3ss4 plants as a fusion protein consisting of an N-terminal Rubisco small subunit chloroplast transit peptide, then a yellow fluorescent protein (YFP), then GS . Examination of four independent GS-transformed ss3ss4 plants with confocal fluorescence microscopy confirmed that the protein was targeted to chloroplasts. Analysis of crude extracts of leaves by nondenaturing PAGE on gels containing glycogen revealed abundant GS activity in these plants .ss3ss4 mutants . Importantly, both the distribution and the nature of starch granules in the GS-expressing plants were very different from those of wild-type plants. In leaf sections, starch granules were visible in some chloroplasts but not in others. Furthermore, chloroplasts of a single cell appeared to contain a huge range of granule morphologies and sizes  mutants have few, giant chloroplasts per mesophyll cell, but the same number of starch granules per unit chloroplast volume as wild-type plants  and 25 (arc10) chloroplasts per cell, compared with ∼100 chloroplasts per wild-type cell, not shown). Nondenaturing PAGE analysis revealed no differences in activities of starch synthase isoforms other than SS4 between the parental and double mutant lines .In order to test this idea, we examined the impact on granule formation in the ss4 parent in that starch granules were visible in some chloroplasts in sections of immature leaves  and starch turnover was comparable with that of the arc parent and wild-type plants . However, starch synthesis in double mutants was different in several respects from that of arc and wild-type plants. Although some chloroplasts in immature ss4 leaves contained granules, others apparently contained none . Granule numbers per unit chloroplast volume appeared to be lower than in wild-type plants throughout leaf expansion. In both immature and mature leaves, the range of granule sizes was larger in double mutants than in ss4 or arc mutants, or wild-type plants . Thus, although granule formation in the absence of SS4 started earlier during leaf expansion development in arc mutant backgrounds than in a wild-type background, it was highly sporadic and qualitatively different from that in wild-type plants.The double mutants differed from the ants Figs, S5. TheSS4 gene, and examined the consequences for granule numbers and starch turnover.Taken together, the observations above suggest that the primary effect of loss of SS4 is a strongly delayed and infrequent formation of new starch granules during leaf development. The alterations in granule number and starch turnover in mature leaves may be secondary consequences of this effect. To distinguish more clearly between primary and secondary effects, we reduced SS4 concentrations in mature rosettes by inducing expression of an RNAi hairpin construct targeted at the SS4 gene sequence, under the control of a dexamethasone-inducible promoter . Transgenic plants were treated with dexamethasone daily for 10 d. For each construct, one line showing strong reductions in SS4 protein was selected for further study. Before dexamethasone treatment, SS4 transcript and protein concentrations were the same in transgenic lines and wild-type plants. SS4 protein concentrations were unaffected by dexamethasone treatment in wild-type controls . In transgenic lines, SS4 transcript levels declined to very low values within 24–48 h of the first dexamethasone treatment and remained low. Concentrations of SS4 protein fell slowly to undetectable levels over the first 7 d of dexamethasone treatment , but diel starch turnover was at least 94% of that in wild-type plants and more than twice that in ss4 plants. There was little or no difference between transgenic and control plants in whole-rosette starch content at the end of the day, average granule radius .We investigated whether the amount of SS4 in a wild-type leaf limits starch granule formation. This possibility is suggested by a report that transgenic Arabidopsis plants with elevated concentrations of SS4 protein have increased rates of starch synthesis (SS4ss4-3) plants. As expected, both mature and immature leaves had approximately half the SS4 protein content of wild-type plants   Figs, S9. Thuss4 mutant plants. Granules appear only at a later stage of leaf expansion, and granule numbers per chloroplast are much lower in mature leaves than in wild-type plants.Our results show that SS4 is essential for the coordinated formation of starch granules that occurs during leaf expansion. In wild-type plants, chloroplasts have multiple starch granules from a very early stage of leaf development  some granules were present in immature leaves and starch turnover was comparable with that of wild-type plants, but granule distribution, shape and size remained highly variable. Thus, large chloroplast volumes permit more frequent formation of granules and higher starch turnover in the absence of SS4, but do not restore the coordinated production of typical transitory starch granules seen in wild-type leaves.Third, in ss4 phenotype with those of mutants lacking other components of the pathways of starch synthesis and degradation suggests that SS4 has an exclusive and direct role in granule formation. Several features of the ss4 phenotype are also seen in other starch mutants. For example the starch synthesis mutant pgm1 and the starch degradation mutant sex1 – lacking plastidial phosphoglucomutase and glucan, water dikinase, respectively – have reduced growth rates, elevated daytime concentrations of sugars . The loss of gravitropism in roots of ss4 mutants is highly likely to be a consequence of reduced formation of granules in the root cap. We observed a negative correlation between root cap starch content and deviation of the root from vertical growth. Reduced gravitropic responses have been observed previously in roots of Arabidopsis mutants with reduced starch contents  are still capable of starch synthesis and turnover  and chloroplast volume (by introduction of arc mutations) did not restore normal granule morphology even though they increased the frequency of granule formation in immature leaves. Thus, the mechanism of granule formation in leaves in the presence of SS4 appears to be qualitatively different from that in its absence. It is interesting to note that flattened, discoid granules are found in leaves but not in other plant organs. Starch granules in nonphotosynthetic organs are generally rounded with a distinct core or hilum, resembling the leaf starch granules of ss4 mutants. However, SS4 appears to be necessary for normal granule initiation in root caps as well as leaves, suggesting that it interacts with different granule-initiation mechanisms in the two organs.Starch granules in leaves of ent core . Manipulde novo during photosynthesis (Phaseolus vulgaris) can elongate both maltose and maltotriose (Agrobacterium glycogen synthase, if its sole function is to provide small oligosaccharides on which other starch synthases can act. An alternative explanation (n-terminal part of the protein. Coiled-coil domains can mediate protein–protein interactions (What is the function of SS4 in granule initiation? As discussed above, it seems to be an essential part of a mechanism that generates a specific ‘primer’ on which other starch synthases can act, leading to granule formation. The primer might simply be small malto-oligosaccharides, perhaps elaborated by SS4 from ADPglucose alone or from maltose, which is produced totriose . It is alanation  is that ractions . FurtherSS4ss4 heterozygotes with half the wild-type concentrations of SS4 protein were indistinguishable from those of wild-type plants. Second, normal starch metabolism was restored in ss4 mutant plants by transgenic expression of SS4 at concentrations far below those in wild-type plants. These results imply that the tight relationship between stromal volume and numbers of starch granules is not simply a function of numbers of SS4 protein molecules, but is determined by a complex mechanism of which SS4 is an essential but nonlimiting component. In this light, it is interesting that overexpression of SS4 in wild-type Arabidopsis plants results in increased rates of leaf starch synthesis and up to 50% more starch at the end of the day (Although SS4 is required for the formation of normal transitory starch granules, it is unlikely that its concentration exerts significant control over the numbers of granules initiated in wild-type plants. First, granule numbers in


There is a wide range of mechanical properties of spinal ligaments documented in literature. Due to the fact that ligaments contribute in stabilizing the spine by limiting excessive intersegmental motion, those properties are of particular interest for the implementation in musculoskeletal models. The aim of this study was to investigate the effect of varying ligament stiffness on the kinematic behaviour of the lumbar spine.A musculoskeletal model with a detailed lumbar spine was modified according to fluoroscopic recordings and corresponding data files of three different subjects. For flexion, inverse dynamics analysis with a variation of the ligament stiffness matrix were conducted. The influence of several degrees of ligament stiffness on the lumbar spine model were investigated by tracking ligament forces, disc forces and resulting moments generated by the ligaments. Additionally, the kinematics of the motion segments were evaluated.An increase of ligament stiffness resulted in an increase of ligament and disc forces, whereas the relative change of disc force increased at a higher rate at the L4/L5 level (19 %) than at the L3/L4 (10 %) level in a fully flexed posture. The same behaviour applied to measured moments with 67 % and 45 %. As a consequence, the motion deflected to the lower levels of the lumbar spine and the lower discs had to resist an increase in loading.Higher values of ligament stiffness over all lumbar levels could lead to a shift of the loading and the motion between segments to the lower lumbar levels. This could lead to an increased risk for the lower lumbar parts. Back muscles stabilize the spine and they are supported by ligaments which limit excessive intersegmental motions . SeveralDuring the last decade, simulations have been used quite intensively to study biomechanics of the lumbar spine. A lumbar spine model was developed  and usedIn order to get a more realistic musculoskeletal model an increased level of detail is needed and in fact this is part of current developments in musculoskeletal research. Both, spinal muscles and ligaments are necessary to understand spinal loading conditions and to accurately predict forces as well as moments. However, the influence of input parameters such as ligament stiffness is not easy to determine. Especially in the case of musculoskeletal models which involve muscle recruitment the mechanical model gets complex.To identify mechanical properties of spinal ligaments, several in-vitro studies have been carried out –11. The In this study, three different musculoskeletal models each with a detailed lumbar spine were used for simulations with the AnyBody Modeling System . All inverse dynamics computations were conducted with a polynomial muscle recruitment of the third order . In contThe data of the fluroscopic measurements was provided by Ortho Kinematics, Inc. . It can be obtained by contacting the company . All the study participants provided written informed consent for the study. The fluoroscopic recordings were produced during a controlled standing flexion-extension movement. As the motion normalizer bent the trunk, about 180 radiographs were captured and image analysis software identified the vertebrae on each frame. The x- and y-coordinates of the vertices which belonged to the lumbar vertebral bodies L3 to S1 were collected in a data file. This data was used to determine each centre of rotation between the motion segments L3/L4, L4/L5 and L5/S1 . AfterwaThe basis for the simulation model Fig.  was avaiThe muscle apparatus was implemented as described by published data . They weThe intervertebral discs were modelled as spherical joints with three rotational degrees of freedom and their stiffness properties were defined according to a linear relationship .The lumbar ligaments  were defined as linear single force components, which generated a tensile force when stretched beyond their slack length. This length was defined in an upright standing posture. Stiffness and failure strain parameters were taken from literature data , 9. SincThe geometries of the lumbar vertebrae were morphed through segmentation of clinical computed tomographic images and each facet joint was designed with the help of a surface contact, where all contact forces between two articular processes were computed using contact area, stiffness and penetration depth. A first validation was performed with published data .Three different models were generated for the purpose of this study. Therefore, body height and weight of each subject was implemented for a correct scaling of the body components. Additionally, the positions of the spherical joints between L3 to L5 were adapted according to the calculated centres of rotation from fluroscopy measurement. Moreover, the range of motion (ROM) of the simulation model was adjusted to the range of motion from the experiments.The values and ranges of failure strain and stiffness parameters for the ligaments were taken from an in-vitro experiment . Each liInfluences of different sets of the ligament stiffness matrix were analysed by tracking ligament forces, joint forces and resulting moments generated by the ligaments with respect to the corresponding centre of rotation. Subsequently, the kinematics of the lumbar segments were evaluated by comparing the angles between the upper endplates.Locations of centres of rotation were calculated and ligament forces, joint forces and resulting moments generated by ligaments were tracked and visualised in relation to the flexion movement in 33 simulations. The simulations consisted of 11 individual sets of the ligament stiffness matrix for three different subjects. Additionally, range of motion of the motion segments were determined by evaluating the angles between the according upper endplates.The calculation of centres of rotation resulted in good agreement with the published data  for subjFigure The resulting moments generated by the ligaments with respect to the corresponding centre of rotation resulted in a total range of 2 to 26 Nm with higher absolute values in the L3/L4 segment compared to the L4/L5 segment. The highest values were obtained around the medio-lateral axis of the joint and are shown in Fig. %= minimum ligament stiffness, 100 % = maximum ligament stiffness) in conjunction with the ROM of the fluoroscopy data. The changes in L3/L4 of subjects one and two for the model (ModelΔφL3L4) and the fluoroscopy data (X- rayΔφL3L4) agree well at mean ligament stiffness. Furthermore, the ROM of the L4/L5 motion segment for the model (ModelΔφL4L5) and the experiment (X- rayΔφL4L5) match well regarding subject one and two, especially at minimum stiffness. However, a certain discrepancy was determined for the ROM at L5/S1 (ModelΔφL5S1 and X- rayΔφL5S1) for all three subjects.The ROM of each segment was calculated via the angles between the upper endplates of adjacent vertebrae. It is visualised as a function of the stiffness in Fig. ModelΔφL1L2, ModelΔφL2L3, ModelΔφL3L4) of all three subjects decreased with increasing ligament stiffness. In contrast, the lower segments  showed an increase of the range of motion with increasing stiffness.Finally, the ROM of the upper motion segments  of subject three was almost zero at minimum ligament stiffness. This was probably caused by the large displacement of the centres of rotation for subject three in comparison to the experimental values [ModelΔφL5S1) did not agree very well with data of the fluoroscopic recordings (X- rayΔφL5S1) for all subjects. This was probably caused by missing modifications of the corresponding centres of rotation however the calculations at this level did not return reasonable results. The small motion amplitude measured from the fluoroscopic recordings led to the defective calculations. This problem was also reported in literature [While the simulations of subjects one and two showed comparable results, results for subject three revealed a different behaviour. For instance, the range of motion of the modelled L4/L5 motion segment (l values  and the terature .However, the outcome of the simulations for all three subjects indicated that a rising ligament stiffness could cause a transfer of the motion and the loads to the lower lumbar segments. The growth rate of both result parameters was smaller in the upper lumbar parts. The deflection of the motion was clearly shown by the results for the ROM which decreased at the upper lumbar levels and at the same time increased at the lower levels. Even though, the absolute values for moments generated by ligaments were higher at the L3/L4 level compared to the L4/L5 level, the gain in intervertebral joint forces, ligament forces and moments induced from the ligament stiffness changes were higher at the lower segment.These findings may be of particular interest for subject-specific simulations of the lumbar spine. They indicate that it is important to use a reasonable range of values for ligament stiffness to predict realistic results for the loading force and kinematics of the lumbar spine. Otherwise, simulations could lead to an overestimation of the kinematics and kinetics of the lower lumbar parts.Additionally, the results could be relevant for degenerations connected with an increase of the stiffness for all lumbar levels. In these instances, this study implies that in case of a higher stiffness the lower lumbar motion segments may have to provide more motion and more resistance to increasing loads. As a result, discs within the lower lumbar range may potentially degenerate most rapidly.There are some limitations to this work. The values of the ligament stiffness were altered uniformly over all lumbar levels neglecting changes in the distribution between the levels. Furthermore, the values were determined using only one publication  and to oThis study showed that higher values of ligament stiffness over all levels of the lumbar spine could lead to a shift of the loading to the lower lumbar levels. Furthermore, the kinematics of the lumbar spine showed a trend towards increased lower lumbar flexion. Overall, the results indicate that high stiffness values of the lumbar ligaments lead to an increased risk for the lower lumbar parts.


Cold-induced sweetening (CIS) is the accumulation of reducing sugars in potato tubers at low storage temperatures. It is undesirable because it results in dark fry products. Our study evaluated the relationship between genetic resistance to CIS and two starch parameters, amylose content and starch granule size. We found that the amylose content in four CIS-resistant varieties was higher than that in five susceptible varieties. Amylose content was influenced not only by variety but also storage, production year, and field location. However, interactions between amylose content and environmental variables were not detected. In contrast, starch granule size was not associated with CIS resistance. No effect of storage on starch granule size was detected, and interactions among variety, production year, and field location were observed. Tuber starch amylose content should be considered a source of variability for CIS. Worldwide, most potatoes are produced in temperate regions, where the bulk of the crop is harvested during a narrow window of time in the fall. Even in tropical regions where year round agriculture is possible, potato is often grown in one season, in rotation with other crops during the year. Consequently, most of the crop is harvested in a short period of time and must be stored to provide a consistent supply throughout the year. Tubers are typically stored at cold temperatures to reduce shrinkage due to respiration and to minimize losses to tuber-borne pathogens. Cold-stored tubers, however, accumulate the reducing sugars glucose and fructose  were grown at the Hancock, Wisconsin, Agricultural Experiment Station in 2010, 2011, and 2012. They were also grown in a field plot near Antigo, Wisconsin, in 2011 and 2012. The trial was not carried out in Antigo in 2010 because there was insufficient seed available. The Hancock trial was planted on 4 May 2010, 8 June 2011, and 8 May 2012, while the Antigo trial was planted on 23 May 2011 and 10 May 2012. Vines were chemically killed in late August and plots were harvested at Hancock on 3 September 2010, 6 October 2011, and 11 September 2012, and at Antigo on 3 October 2011 and 2 October 2012. In all trials, two replications of five plant plots were grown for each variety in a randomized complete block design. At harvest, 10 medium size tubers were randomly selected. Two were processed  within 1 week of harvest. These comprised the fresh sample. Four tubers were stored at 4°C and four were stored at 6°C. After 50 days, the tubers were removed from cold storage. Two tubers from each storage temperature were processed as described above to provide tissue for the stored treatment. The remaining two tubers from each storage temperature were reconditioned at 18°C for 34 days and then processed to provide tissue for the reconditioning treatment. Lyophilized tuber samples were ground in a Wiley mill with a 40 mesh screen.μL 45% (w/v) perchloric acid. After a 4-min incubation period at room temperature, 16 mL of distilled water was added to the solution and mixed by vortexing. After nonsoluble material settled to the bottom of the tube, 40 μL of solution was transferred to a microtiter plate (avoiding the pipetting of any particles) and mixed with 50 μL of Lugol's iodine solution (6 g KI + 0.4 g I2 in 2 mL of water). Each sample was mixed by pipetting and the plate was placed on a Bio Tek ELX800 microplate spectrophotometer . Absorbances at 550 and 620 nm were read immediately. Percent amylose was determined after comparing the amylose to amylopectin ratio of each sample (620 nm absorbance/550 nm absorbance) with a standard curve generated from amylose  and amylopectin (Sigma No. A8515) solutions at different concentrations  and the lowest amylose content (Atlantic and Yukon Gold). Samples from fresh and 6°C stored tubers collected at Hancock and Antigo in 2011 and 2012 were evaluated. Each sample was added to a microscope slide and stained with iodine. Four fields of view of each sample were photographed at 100× magnification. Then, using digital imaging software  with a model including effects for variety, treatment , field location, year, and interactions among the main effects. Means separation was carried out using Fisher's protected least significant difference (LSD) test atP < 0.0001) on amylose content, with the highest amylose levels in the CIS-resistant varieties  for percent amylose in tuber starch were not significant, so analysis of variance was carried out on the entire data set. There was a significant effect of variety P < 0.000 on amyloα-amylase  on percent amylose, with higher amylose contents in tubers stored at 6°C, with or without reconditioning, than the other three treatments   Table. Within ed) Table. The difP < 0.0001) on amylose content, with a higher mean at Hancock than Antigo (TableP < 0.0001) on amylose content, with higher means in 2012 and 2010 than in 2011 , but generally not interactions were reported for starch digestibility properties in a study that evaluated 12 potato varieties in six environments across 2 years  and location by year (P < 0.0001) interactions for mean starch granule surface area. Other interactions were not significant. Therefore, in subsequent analyses, starch granule size analyses were carried out separately for each year.For the starch granule size data set, analysis of variance revealed significant treatment by year (P = 0.0086) and location (P = 0.0176) on starch granule size. In 2012, there was also a significant effect of variety (P < 0.0001) and location (P < 0.0001). In both years, though, there was no significant difference between fresh and stored tubers for mean starch granule surface area. In contrast to amylose content, there was no difference in starch granule size between CIS-resistant and -susceptible varieties (TableP = 0.3012) or 2012 (P = 0.7218). Starch granules from tubers grown at Hancock were smaller than those at Antigo in 2011 but larger than those at Antigo in 2012 (TableIn 2011, there was a significant effect of variety (ies Table. When da012 Table. The CIS012 Table.Amylose content in tuber starch of potato varieties with resistance to cold-induced sweetening was higher than that of susceptible varieties. In contrast, starch granule size did not differ between resistant and susceptible varieties. Amylose content should be considered when developing and evaluating potato varieties for resistance to cold-induced sweetening.