An investigation into the impact of volumetric rescanning and fractionation treatment on dose homogeneity in liver cancer proton therapy.

The Pencil Beam Scanning (PBS) technique in modern particle therapy offers a highly conformal dose distribution but poses challenges due to the interplay effect, an interaction between respiration-induced organ movement and PBS. This study evaluates the effectiveness of different volumetric rescanning strategies in mitigating this effect in liver cancer proton therapy. We used a Geant4-based Monte Carlo simulation toolkit, 'TOPAS,' and an image registration toolbox, 'Elastix,' to calculate 4D dose distributions from 5 patients' four-dimensional computed tomography (4DCT). We analyzed the homogeneity index (HI) value of the Clinical Tumor Volume (CTV) at different rescan numbers and treatment times. Our results indicate that dose homogeneity stabilizes at a low point after a week of treatment, implying that both rescanning and fractionation treatments help mitigate the interplay effect. Notably, an increase in the number of rescans doesn't significantly reduce the mean dose to normal tissue but effectively prevents high localized doses to tissue adjacent to the CTV. Rescanning techniques, based on statistical averaging, require no extra equipment or patient cooperation, making them widely accessible. However, the number of rescans, tumor location, diaphragm movement, and treatment fractionation significantly influence their effectiveness. Therefore, deciding the number of rescans should involve considering the number of beams, treatment fraction size, and total delivery time to avoid unnecessary treatment extension without significant clinical benefits. The results showed that 2-3 rescans are more clinically suitable for liver cancer patients undergoing proton therapy.

Steady decrease in systemic sclerosis mortality rates at younger ages over the past five decades.

OBJECTIVE: We aimed to assess SSc mortality by age in the general population over the past five decades. METHODS: This is a population-based study using a national mortality database and the census data for all US residents. We calculated the proportions of deaths for SSc and for all other causes (non-SSc) by age, and calculated age-standardized mortality rates (ASMRs) for SSc and non-SSc, and the ratio of SSc-ASMR to non-SSc-ASMR by age groups for each year from 1968 through 2015. We performed joinpoint regression to estimate the average annual percent change (AAPC) for each of these parameters. RESULTS: SSc was recorded as the underlying cause of death in 5457 decedents aged ≤44 years, 18 395 aged 45-64, and 22 946 aged ≥65 from 1968 through 2015. At ages ≤44, the proportion of annual deaths decreased more for SSc than for non-SSc: AAPC, -2.2% (95% CI, -2.4% to -2.0%) for SSc vs -1.5% (-1.9% to -1.1%) for non-SSc. Consistently, SSc-ASMR decreased from 1.0 (95% CI, 0.8-1.2) in 1968 to 0.4 (0.3-0.5) per million persons in 2015, a cumulative decrease of 60% at an AAPC of -1.9% (95% CI, -2.5% to -1.2%) at ages ≤44. The SSc-ASMR:non-SSc-ASMR ratio also decreased [cumulative -20%; AAPC -0.3% (95% CI, -1.15% to 0.55%)] in the ≤44-years group. In contrast, those aged ≥65 experienced a steep increase in the SSc-ASMR [cumulative 187.0%; AAPC 2.0% (95% CI, 1.8-2.2)] and the SSc-ASMR:non-SSc-ASMR ratio [cumulative 395.4%; AAPC 3.3% (95% CI, 2.9-3.7)]. CONCLUSION: Mortality for SSc has steadily decreased at younger ages over the past five decades.

Worsening premature death burden gap from systemic sclerosis in men and black persons: A US nationwide population-based study.

Objective: Male sex and black race incur poor prognosis in systemic sclerosis (SSc). There is no nationwide population-based assessment of premature SSc death burden by sex and race. Methods: This is a population-based study comprising all recorded SSc deaths across the United States. We constructed histograms depicting the number of SSc deaths for each age by sex and race, and calculated the cumulative percent death at each age and the median age of death. We determined the odds ratios for the risk of premature death from SSc by sex and race. We then calculated the percent of total SSc deaths for different age groups by sex and race from 1970 to 2015. We performed chi-square test with Yates's correction and quantified the odds ratio (OR) with 95% confidence interval (CI). Results: The median age of SSc death was 63 years in males versus 68 years in females, and 57 years in blacks versus 70 years in whites. The odds for SSc death before 65 years age was 1.8 (95% CI, 1.6-2.0) for males compared with females and 5.1 (95% CI, 4.4-6.0) for blacks compared with whites. The higher odds for premature death in males than in females was similar for both races. Differences in the proportions of premature deaths from 1970 to 2015 increased between males and females (-5% to 17%) and between blacks and whites (14% to 36%). Conclusion: Males and black persons die of SSc at younger ages. The worsening premature death burden gap between the two sexes and races over the last five decades is troublesome.

Commensal gut microbiota-derived acetate and propionate enhance heart adaptation in response to cardiac pressure overload in mice.

Background: The gut microbiota plays a vital role in maintaining tissue homeostasis and regulating disease pathophysiology; however, the underlying mechanisms remain to be elucidated. We previously showed that mice depleted of gut microbiota with antibiotics (ABX mice) were more prone to cardiac rupture after infarction, suggesting that the gut microbiota impacts cardiac structural remodeling following injury. Here, we aimed to determine whether the gut microbiota is required for adaptive cardiac remodeling in response to pressure overload stress. Methods: Transverse aortic constriction (TAC) surgery was performed and cardiac function was evaluated by echocardiography and catheterization, followed by mechanical tests and extracellular matrix (ECM) studies. Germ-free mice with cecal microbiota transplantation were used for validation. 16S ribosomal DNA sequencing and PICRUSt2 analysis were applied to predict the key metabolic pathways. ABX mice were supplemented with the derived metabolic products and their efficacy was tested. To elucidate the underlying mechanism, we isolated mouse primary cardiac fibroblasts and treated them with the metabolites. Lastly, G-coupled protein receptor 41 (GPR41) and GPR43 double knockdown cardiac fibroblasts were generated and the anti-fibrogenic effect of metabolites was determined. Results: Cardiac hypertrophy and dysfunction were more severe in ABX-TAC mice compared to the controls. Moreover, TAC-induced fibrosis was more profound in ABX hearts, which was accompanied by disrupted ECM structure making the heart tissues mechanically weaker and more brittle. Reconstruction of healthy gut microbiota in germ-free mice successfully restored cardiac function and prevented excessive fibrosis and ECM disarray under stress. Furthermore, functional prediction identified acetate and propionate as critical mediators in the gut microbiota-modulated cardiac mechanics. Supplementation of acetate and propionate improved heart function, attenuated fibrosis, and reversed ECM disarray after TAC. In addition, treating primary cardiac fibroblasts with acetate and propionate attenuated cell contraction, inhibited myofibroblast formation, and reduced collagen formation after TGF-ß1 stimulus. Finally, knocking down GPR41 and GPR43 receptors in cardiac fibroblasts blunted the inhibitory effects of acetate and propionate. Conclusions: The gut microbiota is a potential therapeutic target for cardiac ECM remodeling and heart structural integrity. By establishing a healthy gut microbiome or replenishing the derived metabolites, we could improve cardiac health under dysbiosis after pressure-overload stress.

Consensus Treatment Plans for Severe Pediatric Antineutrophil Cytoplasmic Antibody-Associated Vasculitis.

OBJECTIVE: There is no standardized approach to the treatment of pediatric antineutrophil cytoplasmic antibody-associated vasculitis (AAV). Because of the rarity of pediatric AAV, randomized trials have not been feasible. The present study of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) was undertaken to establish consensus treatment plans (CTPs) for severe pediatric AAV to enable the future study of comparative effectiveness and safety. METHODS: A workgroup of CARRA members (rheumatologists and nephrologists) formed the AAV Workgroup. This group performed a literature review on existing evidence-based treatments and guidelines for the management of AAV. They determined that the target population for CTP development was patients <18 years of age with new-onset granulomatosis with polyangiitis (GPA), microscopic polyangiitis, or renal-limited AAV (eosinophilic GPA was excluded), with presentation confined to those with severe disease (i.e., organ- or life-threatening). Face-to-face consensus conferences employed nominal group techniques to identify treatment strategies for remission induction and remission maintenance, data elements to be systematically collected, and outcomes to be measured over time. RESULTS: The pediatric AAV Workgroup developed 2 CTPs for each of the remission induction and remission maintenance of severe AAV. A glucocorticoid-weaning regimen for induction and maintenance, a core data set, and outcome measures were also defined. A random sample of CARRA membership voted acceptance of the CTPs for remission induction and remission maintenance, with a 94% (75 of 80) and 98% (78 of 80) approval rate, respectively. CONCLUSION: Consensus methodology established standardized CTPs for treating severe pediatric AAV. These CTPs were in principle accepted by CARRA-wide membership for the evaluation of pragmatic comparative effectiveness in a long-term registry.

Generalized methodology for radiomic feature selection and modeling in predicting clinical outcomes.

Background.Quantitative radiomic features of medical images could provide clinical significance in assisting decision-making, but the existing feature selection and modeling methods are usually parameter-dependent. We aim to develop and validate a generalized radiomic method applicable to a variety of clinical outcomes.Methods and materials.A generalized methodology for radiomic feature selection and modeling ('GRFM' for short), including two-step feature selection and logistic regression, was proposed for studying clinical outcomes correlations. The two-step feature selection consists of Pearson correlation analysis followed by a sequential forward floating selection algorithm to identify robust feature subsets. We also applied an adaptive searching strategy to systematically determine globally optimal parameters, rather than relying on preset parameters. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of three outcomes: lymph node metastasis of gastric cancer (GC), the five-year survival status of high-grade osteosarcoma (HOS), and the pathological grade of pancreatic neuroendocrine tumors (pNETs).Results.The optimal Pearson thresholds were 0.85, 0.80 and 0.75, and the optimal feature numbers were 11, 14 and 8 in GC, HOS and pNETs, respectively. The AUC values of the three predictive models combined with the corresponding parameters were 0.9017 versus 0.9026, 0.7652 versus 0.7113, and 0.8438 versus 0.8212 for the training and validation cohorts, showing promissing generality and classifier performance .Conclusion.The proposed method was helpful in predicting different clinical outcomes, and has potential application as a general and noninvasive prediction tool to guide clinical decision-making in various cancer sites.

Trends in Systemic Sclerosis Mortality Over Forty-Eight Years, 1968-2015: A US Population-Based Study.

OBJECTIVE: To identify secular trends associated with systemic sclerosis (SSc) mortality over a 48-year period. METHODS: Using national mortality data compiled by the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research, and population data from the US Census Bureau, we calculated an age-standardized mortality rate (ASMR) for SSc and non-SSc (all other causes), and we also calculated the ratio of the SSc ASMR to the non-SSc ASMR for each year from 1968 to 2015. We then used a joinpoint regression model to evaluate mortality trends overall and by sex and race. RESULTS: From 1968 to 2015, there were 46,798 deaths with SSc recorded as the "underlying" cause of death and 106,058,839 non-SSc deaths. There were an additional 9,063 deaths with SSc recorded as a "contributing" cause of death from 1999 to 2015. Whereas the non-SSc ASMR decreased throughout the 48-year time period, the SSc ASMR increased from 1968 to 2000, followed by decreases each year from 2001 to 2015. The SSc ASMR also decreased for deaths where SSc was a contributing cause from 1999 to 2015. Women and Black persons had higher SSc ASMRs and SSc ASMR to non-SSc ASMR ratios than men and White persons, respectively. Additionally, SSc ASMRs and SSc ASMR to non-SSc ASMR ratios increased at higher rates in women and White persons than in men and Black persons, respectively, during the initial three decades. CONCLUSION: Mortality attributable to SSc increased from 1968 to 2000, followed by a steady decline from 2001 to 2015. However, SSc mortality relative to non-SSc mortality remains high. SSc mortality has disproportionately changed by sex and race over the 48-year period assessed in the present study.

Integrating tumor and nodal radiomics to predict lymph node metastasis in gastric cancer.

BACKGROUND: To develop and validate a radiomics method via integrating tumor and lymph node radiomics for the preoperative prediction of lymph node (LN) status in gastric cancer (GC). MATERIALS AND METHODS: We retrospectively collected 170 contrast-enhanced abdominal CT images from GC patients. Five times repeated random hold-out experiment was employed. Tumor and nodal radiomics features were extracted from each individual tumor and LN respectively, and then multi-step feature selection was performed. The optimal tumor and nodal features were selected using Pearson correlation analysis and sequential forward floating selection (SFFS) algorithm. After feature fusion, the SFFS algorithm was used to develop radiomics signatures. The performance of the radiomics signatures developed based on logistic regression classifier was further analyzed and compared using the area under the receiver operating characteristic curve (AUC). RESULTS: The AUC values, reported as mean ± standard deviation, were 0.9319 ± 0.0129 and 0.8546 ± 0.0261 for the training and validation cohorts respectively. The radiomic signatures could predict LN status, especially in T2-stage, diffuse-type and moderately/well differentiated GC. After integrating clinicopathologic information, the radiomic-clinicopathologic model (training cohort, 0.9432 ± 0.0129; validation cohort, 0.8764 ± 0.0322) showed a better discrimination capability than other radiomics models and clinicopathologic model. The radiomic-clinicopathologic model also showed superior performance to the gastroenterologist' decision in all experiments, and outperformed the radiologist in some experiments. CONCLUSION: Our proposed method presented good predictive performance and great potential for predicting LNM in GC. As a noninvasive preoperative prediction tool, it can be helpful for guiding the prognosis and treatment decision-making in GC patients.

Extracting and Selecting Robust Radiomic Features from PET/MR Images in Nasopharyngeal Carcinoma.

OBJECTIVES: This work aims to study the variation, robustness, and feature redundancy of PET/MR radiomic features in the primary tumor of nasopharyngeal carcinoma (NPC). PROCEDURES: PET/MR scans of 21 NPC patients were used in this study. The primary tumor volumes were defined using PET, T2-weighted-MR (T2-MR), and diffusion-weighted MR (DW-MR) images. A random-dilation-erosion method was used to simulate 10 sets of tumor volumes for identifying features invariant with manual segmentation uncertainties. Feature robustness was evaluated against imaging modalities, pixel sizes, slice thickness, and grey-level bin sizes using intraclass correlation coefficient (ICC) and spearman correlation coefficient. Feature redundancy was analyzed using the hierarchical cluster analysis. RESULTS: Voxel size of 0.5 × 0.5 × 1.0 mm3 was found optimal for robust feature extraction from PET and MR. Normalized grey level of 64 and 128 was suggested for PET and MR, respectively. The features from wavelet-transformed images were less stable than those from the original images. The robustness analysis and volume correlation analysis identified 335 (62.04 %) PET features, 240 (44.44 %) T2-MR features, and 366 (67.78 %) DW-MR features. The cluster analysis grouped PET, T2-MR, and DW-MR features into 106, 83, and 133 representative features, respectively. CONCLUSIONS: The present study analyzed and identified robust features extracted from tumor volumes on PET/MR, which can provide guidance and promote standardization for PET/MR radiomic studies in NPC.

A multi-organ cancer study of the classification performance using 2D and 3D image features in radiomics analysis.

The purpose of this study was to investigate the predictive performance of 2D and 3D image features across multi-organ cancers using multi-modality images in radiomics studies. In this retrospective study, we included 619 patients with three different cancer types (intrahepatic cholangiocarcinoma (ICC), high-grade osteosarcoma (HOS), pancreatic neuroendocrine tumors (pNETs)) and four clinical end points (early recurrence (ER), lymph node metastasis (LNM), 5-year survival and histologic grade). The image features included fifty-eight 2D image features and fifty-eight 3D image features. The 3D image features were extracted based on the 3D tumor volumes. The 2D image features were extracted based on 2D tumor region, which was the layer with the maximum tumor diameter within the 3D tumor volume. The predictive performance of individual 2D and 3D image feature was measured using the area under the receiver operating characteristic curve (AUC) with univariate analysis. Radiomics signatures were further developed using multivariable analysis with 4-fold cross-validation method. Using univariate analysis, we found that more 3D image features showed the statistically predictive capabilities than 2D image features across all the included cancer types. By comparing the predictive performance of radiomics signatures developed by 2D and 3D image features, we observed better prediction performance in radiomics signatures based on 3D image features than those based on 2D image features for patients with ICC and HGO. Meanwhile, the signatures based on 2D and 3D image features performed closely in the pNETs dataset with the clinical end point of the histologic grade. The reason for this inconsistent result might be that the gross tumor volumes of pNETs were generally small. The tumor heterogeneity was mostly presented in the middle several layers within the tumor volume. Both 2D and 3D image features have certain predictive capacities. By contrast, the 3D image features show better or close predictive performance than 2D image features using both univariate analysis and multivariate analysis. In brief, 3D image features are recommended in radiomics studies.

Brief Report: Lupus-An Unrecognized Leading Cause of Death in Young Females: A Population-Based Study Using Nationwide Death Certificates, 2000-2015.

OBJECTIVE: Mortality statistics from the Centers for Disease Control and Prevention (CDC) are used for planning health care policy and allocating resources. The CDC uses these data to compile its annual ranking of leading causes of death based on a selected list of 113 causes. Systemic lupus erythematosus (SLE) is not included on this list. Since the ranking is a useful tool for assessing the relative burden of cause-specific mortality, this study was undertaken to rank SLE deaths among the CDC's leading causes of death to see whether SLE is a significant cause of death among females. METHODS: Death counts for the female population of the US were obtained from the CDC's Wide-ranging Online Data for Epidemiologic Research database and then grouped by age and race/ethnicity. Data on the leading causes of death were obtained from the Web-based Injury Statistics Query and Reporting System database. RESULTS: During 2000-2015, there were 28,411 deaths of females with SLE recorded as an underlying or contributing cause of death. SLE ranked among the top 20 leading causes of death in females between 5 and 64 years of age. SLE ranked tenth among those ages 15-24 years, fourteenth among those ages 25-34 years and 35-44 years, and fifteenth among those ages 10-14 years. For African American and Hispanic females, SLE ranked fifth among those ages 15-24 years, sixth among those ages 25-34 years, and eighth or ninth among those ages 35-44 years, after the 3 common external injury causes of death were excluded from the analysis. CONCLUSION: SLE is among the leading causes of death in young females, underscoring its impact as an important public health issue.

Author Correction: Interrogation of γ-tubulin alleles using high-resolution fitness measurements reveals a distinct cytoplasmic function in spindle alignment.

A correction to this article has been published and is linked from the HTML version of this paper. The error has not been fixed in the paper.

Spatial cues and not spindle pole maturation drive the asymmetry of astral microtubules between new and preexisting spindle poles.

In many asymmetrically dividing cells, the microtubule-organizing centers (MTOCs; mammalian centrosome and yeast spindle pole body [SPB]) nucleate more astral microtubules on one of the two spindle poles than the other. This differential activity generally correlates with the age of MTOCs and contributes to orienting the mitotic spindle within the cell. The asymmetry might result from the two MTOCs being in distinctive maturation states. We investigated this model in budding yeast. Using fluorophores with different maturation kinetics to label the outer plaque components of the SPB, we found that the Cnm67 protein is mobile, whereas Spc72 is not. However, these two proteins were rapidly as abundant on both SPBs, indicating that SPBs mature more rapidly than anticipated. Superresolution microscopy confirmed this finding for Spc72 and for the γ-tubulin complex. Moreover, astral microtubule number and length correlated with the subcellular localization of SPBs rather than their age. Kar9-dependent orientation of the spindle drove the differential activity of the SPBs in astral microtubule organization rather than intrinsic differences between the spindle poles. Together, our data establish that Kar9 and spatial cues, rather than the kinetics of SPB maturation, control the asymmetry of astral microtubule organization between the preexisting and new SPBs.

46-Year Trends in Systemic Lupus Erythematosus Mortality in the United States, 1968 to 2013: A Nationwide Population-Based Study.

BACKGROUND: No large population-based studies have been done on systemic lupus erythematosus (SLE) mortality trends in the United States. OBJECTIVE: To identify secular trends and population characteristics associated with SLE mortality. DESIGN: Population-based study using a national mortality database and census data. SETTING: United States. PARTICIPANTS: All U.S. residents, 1968 through 2013. MEASUREMENTS: Joinpoint trend analysis of annual age-standardized mortality rates (ASMRs) for SLE and non-SLE causes by sex, race/ethnicity, and geographic region; multiple logistic regression analysis to determine independent associations of demographic variables and period with SLE mortality. RESULTS: There were 50 249 SLE deaths and 100 851 288 non-SLE deaths from 1968 through 2013. Over this period, the SLE ASMR decreased less than the non-SLE ASMR, with a 34.6% cumulative increase in the ratio of the former to the latter. The non-SLE ASMR decreased every year starting in 1968, whereas the SLE ASMR decreased between 1968 and 1975, increased between 1975 and 1999, and decreased thereafter. Similar patterns were seen in both sexes, among black persons, and in the South. However, statistically significant increases in the SLE ASMR did not occur among white persons over the 46-year period. Females, black persons, and residents of the South had higher SLE ASMRs and larger cumulative increases in the ratio of the SLE to the non-SLE ASMR (31.4%, 62.5%, and 58.6%, respectively) than males, other racial/ethnic groups, and residents of other regions, respectively. Multiple logistic regression showed independent associations of sex, race, and region with SLE mortality risk and revealed significant racial/ethnic differences in associations of SLE mortality with sex and region. LIMITATIONS: Underreporting of SLE on death certificates may have resulted in underestimates of SLE ASMRs. Accuracy of coding on death certificates is difficult to ascertain. CONCLUSION: Rates of SLE mortality have decreased since 1968 but remain high relative to non-SLE mortality, and significant sex, racial, and regional disparities persist. PRIMARY FUNDING SOURCE: None.

Approach to Membranous Lupus Nephritis: A Survey of Pediatric Nephrologists and Pediatric Rheumatologists.

OBJECTIVE: To describe treatment practices for childhood pure membranous lupus nephritis (MLN). METHODS: Survey study of Childhood Arthritis and Rheumatology Research Alliance and American Society of Pediatric Nephrology members. RESULTS: There were 117 respondents who completed the survey (60 pediatric nephrologists, 57 pediatric rheumatologists). Steroids and nonsteroid immunosuppression (NSI) were routinely used by the majority for MLN. Mycophenolate mofetil was the favored initial NSI. Nephrologists used steroids (60% vs 93%) and NSI (53% vs 87%) less often than did rheumatologists for MLN without nephrotic syndrome (NS). CONCLUSION: Pediatric rheumatologists and nephrologists both recommend steroids and NSI for children with MLN, with or without NS.

Interrogation of γ-tubulin alleles using high-resolution fitness measurements reveals a distinct cytoplasmic function in spindle alignment.

γ-Tubulin has a well-established role in nucleating the assembly of microtubules, yet how phosphorylation regulates its activity remains unclear. Here, we use a time-resolved, fitness-based SGA approach to compare two γ-tubulin alleles, and find that the genetic interaction profile of γtub-Y362E is enriched in spindle positioning and cell polarity genes relative to that of γtub-Y445D, which is enriched in genes involved in spindle assembly and stability. In γtub-Y362E cells, we find a defect in spindle alignment and an increase in the number of astral microtubules at both spindle poles. Our results suggest that the γtub-Y362E allele is a separation-of-function mutation that reveals a role for γ-tubulin phospho-regulation in spindle alignment. We propose that phosphorylation of the evolutionarily conserved Y362 residue of budding yeast γ-tubulin contributes to regulating the number of astral microtubules associated with spindle poles, and promoting efficient pre-anaphase spindle alignment.

Clinical practice variation and need for pediatric-specific treatment guidelines among rheumatologists caring for children with ANCA-associated vasculitis: an international clinician survey.

BACKGROUND: Because pediatric antineutrophil cytoplasmic antibody-associated vasculitis is rare, management generally relies on adult data. We assessed treatment practices, uptake of existing clinical assessment tools, and interest in pediatric treatment protocols among rheumatologists caring for children with granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA). METHODS: A needs-assessment survey developed by an international working group of pediatric rheumatologists and two nephrologists was circulated internationally. Data were summarized with descriptive statistics. Pearson's chi-square tests were used in inferential univariate analyses. RESULTS: The 209 respondents from 36 countries had collectively seen ~1600 children with GPA/MPA; 144 had seen more than two in the preceding 5 years. Standardized and validated clinical assessment tools to score disease severity, activity, and damage were used by 59, 63, and 36%, respectively; barriers to use included lack of knowledge and limited perceived utility. Therapy varied significantly: use of rituximab rather than cyclophosphamide was more common among respondents from the USA (OR = 2.7 [1.3-5.5], p = 0.0190, n = 139), those with >5 years of independent practice experience (OR = 3.8 [1.3-12.5], p = 0.0279, n = 137), and those who had seen >10 children with GPA/MPA in their careers (OR = 4.39 [2.1-9.1], p = 0.0011, n = 133). Respondents who had treated >10 patients were also more likely to continue maintenance therapy for at least 24 months (OR = 3.0 [1.4-6.4], p = 0.0161, n = 127). Ninety six percent of respondents believed in a need for pediatric-specific treatment guidelines; 46% supported adaptation of adult guidelines while 69% favoured guidelines providing a limited range of treatment options to allow comparison of effectiveness through a registry. CONCLUSIONS: These data provide a rationale for developing pediatric-specific consensus treatment guidelines for GPA/MPA. While pediatric rheumatologist uptake of existing clinical tools has been limited, guideline uptake may be enhanced if outcomes of consensus-derived treatment options are evaluated within the framework of an international registry.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden dynamics within protein interaction networks.