Extending libSedML to support CellML models

libSedML is a collection of libraries and tools developed in support of the Simulation Experiment Markup Language ("SED-ML":http://sed-ml.org/). "libSedML":http://libsedml.sourceforge.net/ is implemented in C# and provides libraries for processing SED-ML documents and for running the numerical simulations required for the encoded simulation experiment(s). SED-ML supports models encoded in any encoding format, although predominantly expected to be an XML based encoding. To date, however, libSedML has only supported performing simulations using models encoded in the Systems Biology Markup Language ("SBML":http://sbml.org/). The presented project looked at using the "CellML API":http://cellml.org/tools/api to extend libSedML to support simulations using models encoded in CellML.

Using the CellML API, command line utility programs were written (in C++) which performed the functions required by libSedML in order to perform numerical simulations of CellML models. Namely, this involved performing the described simulation with the given CellML model and producing the simulation results in a text file. libSedML was then extended to use these command line utilities as required in the performance of the described simulation experiment. A CellML model specific simulation wizard was also added to libSedML

Sociodemographic factors and social media use in 9-year-old children:the Generation R Study

Abstract Background We aimed to investigate the associations between sociodemographic factors and instant messaging and social network site exposure among 9-year-old children. Methods Data of 4568 children from the Generation R study, a population-based cohort study performed in Rotterdam, the Netherlands, were analyzed. Instant messaging exposure was defined as using online chat applications such as MSN, chat boxes, WhatsApp, and Ping. Social network site exposure was defined as using Hyves or Facebook. A series of multiple logistic regression analyses were performed, adjusting for covariates. Results Children of low educated mothers had a higher odds ratio (OR) for instant messaging (OR: 1.44, 95% CI: 1.12, 1.86) and social network site exposure (OR: 1.73, 95% CI: 1.13, 2.66) than their counterparts. Being a child from a single-parent family was associated with instant messaging (OR: 1.48, 95% CI: 1.16, 1.88) and social network site exposure (OR: 1.34, 95% CI: 1.01, 1.78) more often than their counterparts. Children of low educated fathers (OR: 1.48, 95% CI: 1.12, 1.95) or from families with financial difficulties (OR: 1.28, 95% CI: 1.04, 1.59) were associated with a higher OR of social network site exposure than their counterparts. Conclusion The findings suggest that several indicators of lower social position are associated with higher social network site and instant messaging exposure among 9-year-old children. More research is needed in younger children to understand the determinants and impact of social media use

Social Media Use and Health-Related Quality of Life Among Adolescents:Cross-sectional Study

BACKGROUND: Using social media is a time-consuming activity of children and adolescents. Health authorities have warned that excessive use of social media can negatively affect adolescent social, physical, and psychological health. However, scientific findings regarding associations between time spent on social media and adolescent health-related quality of life (HRQoL) are not consistent. Adolescents typically use multiple social media platforms. Whether the use of multiple social media platforms impacts adolescent health is unclear. OBJECTIVE: The aim of this study was to examine the relationship between social media use, including the number of social media platforms used and time spent on social media, and adolescent HRQoL. METHODS: We analyzed the data of 3397 children (mean age 13.5, SD 0.4 years) from the Generation R Study, a population-based cohort study in the Netherlands. Children reported the number of social media platforms used and time spent on social media during weekdays and weekends separately. Children’s HRQoL was self-reported with the EuroQol 5-dimension questionnaire–youth version. Data on social media use and HRQoL were collected from 2015 to 2019. Multiple logistic and linear regressions were applied. RESULTS: In this study, 72.6% (2466/3397) of the children used 3 or more social media platforms, and 37.7% (1234/3276) and 58.3% (1911/3277) of the children used social media at least 2 hours per day during weekdays and weekends, respectively. Children using more social media platforms (7 or more platforms) had a higher odds of reporting having some or a lot of problems on “having pain or discomfort” (OR 1.55, 95% CI 1.20 to 1.99) and “feeling worried, sad or unhappy” (OR 1.99, 95% CI 1.52 to 2.60) dimensions and reported lower self-rated health (β –3.81, 95% CI –5.54 to –2.09) compared with children who used 0 to 2 social media platforms. Both on weekdays and weekends, children spent more time on social media were more likely to report having some or a lot of problems on “doing usual activities,” “having pain or discomfort,” “feeling worried, sad or unhappy,” and report lower self-rated health (all P<.001). CONCLUSIONS: Our findings indicate that using more social media platforms and spending more time on social media were significantly related to lower HRQoL. We recommend future research to study the pathway between social media use and HRQoL among adolescents

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier- transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models

High-Dimensional Fixed Effects Profiling Models and Applications in End-Stage Kidney Disease Patients: Current State and Future Directions

Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or “flagging” of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies

Abnormal synergistic gait mitigation in acute stroke using an innovative ankle–knee–hip interlimb humanoid robot: A preliminary randomized controlled trial

Abnormal spasticity and associated synergistic patterns are the most common neuromuscular impairments affecting ankle–knee–hip interlimb coordinated gait kinematics and kinetics in patients with hemiparetic stroke. Although patients with hemiparetic stroke undergo various treatments to improve gait and movement, it remains unknown how spasticity and associated synergistic patterns change after robot-assisted and conventional treatment. We developed an innovative ankle–knee–hip interlimb coordinated humanoid robot (ICT) to mitigate abnormal spasticity and synergistic patterns. The objective of the preliminary clinical trial was to compare the effects of ICT combined with conventional physical therapy (ICT-C) and conventional physical therapy and gait training (CPT-G) on abnormal spasticity and synergistic gait patterns in 20 patients with acute hemiparesis. We performed secondary analyses aimed at elucidating the biomechanical effects of Walkbot ICT on kinematic (spatiotemporal parameters and angles) and kinetic (active force, resistive force, and stiffness) gait parameters before and after ICT in the ICT-C group. The intervention for this group comprised 60-min conventional physical therapy plus 30-min robot-assisted training, 7 days/week, for 2 weeks. Significant biomechanical effects in knee joint kinematics; hip, knee, and ankle active forces; hip, knee, and ankle resistive forces; and hip, knee, and ankle stiffness were associated with ICT-C. Our novel findings provide promising evidence for conventional therapy supplemented by robot-assisted therapy for abnormal spasticity, synergistic, and altered biomechanical gait impairments in patients in the acute post-stroke recovery phase. Trial Registration: Clinical Trials.gov identifier NCT03554642 (14/01/2020)

Change in neighborhood socioeconomic status and childhood weight status and body composition from birth to adolescence

Background: We aim to assess the associations between the change in neighborhood socioeconomic score (SES) between birth and 6 years and childhood weight status and body composition from 6 to 13 years.Methods: Data for 3909 children from the Generation R Study, a prospective population-based cohort in the Netherlands were analyzed. The change in neighborhood SES between birth and 6 years was defined as static-high, static-middle, static-low, upward, and downward mobility. Child body mass index (BMI), overweight and obesity (OWOB), fat mass index (FMI) and lean mass index (LMI) were measured at age 6, 10, and 13 years. The associations were explored using generalized estimating equations. The effect modification by child sex was examined. Results: In total, 19.5% and 18.1% of children were allocated to the upward mobility and downward mobility neighborhood SES group. The associations between the change in neighborhood SES and child weight status and body composition were moderated by child sex (p &lt; 0.05). Compared to girls in the static-high group, girls in the static-low group had relatively higher BMI-SDS (β, 95% confidence interval (CI): 0.24, 0.09–0.40) and higher risk of OWOB (RR, 95% CI: 1.98, 1.35–2.91), together with higher FMI-SDS (β, 95% CI: 0.27, 0.14–0.41) and LMI-SDS (β, 95% CI: 0.18, 0.03–0.33). The associations in boys were not significant. Conclusions: An increased BMI and fat mass, and higher risk of OWOB from 6 to 13 years were evident in girls living in a low-SES neighborhood or moving downward from a high- to a low-SES neighborhood. Support for children and families from low-SES neighborhoods is warranted.</p

Dialysate Potassium and Mortality in a Prospective Hemodialysis Cohort.

BackgroundStudies examining the association of dialysate potassium concentration and mortality in hemodialysis patients show conflicting findings. We hypothesized that low dialysate potassium concentrations are associated with higher mortality, particularly in patients with high pre-dialysis serum potassium concentrations.MethodsWe evaluated 624 hemodialysis patients from the prospective Malnutrition, Diet, and Racial Disparities in Kidney Disease study recruited from 16 outpatient dialysis facilities over 2011-2015 who underwent protocolized collection of dialysis treatment characteristics every 6 months. We examined the association of dialysate potassium concentration, categorized as 1, 2, and 3 mEq/L, with all-cause mortality risk in the -overall cohort, and stratified by pre-dialysis serum potassium (&lt; 5 vs. ≥5 mEq/L) using case-mix adjusted Cox models.ResultsIn baseline analyses, dialysate potassium concentrations of 1&nbsp;mEq/L were associated with higher mortality, whereas concentrations of 3 mEq/L were associated with similar mortality in the overall cohort (reference: 2 mEq/L): adjusted hazard ratios (aHRs; 95% CI) 1.70 (1.01-2.88) and 0.95 (0.64-1.39), respectively. In analyses stratified by serum potassium, baseline dialysate potassium concentrations of 1 mEq/L were associated with higher mortality in patients with serum potassium ≥5 mEq/L but not in those with serum potassium &lt; 5 mEq/L: aHRs (95% CI) 2.87 (1.51-5.46) and 0.74 (0.27-2.07), respectively (p interaction = 0.04). These findings were robust with incremental adjustment for serum potassium, potassium-binding resins, and potassium-modifying medications.ConclusionLow (1 mEq/L) dialysate potassium -concentrations were associated with higher mortality, particularly in hemodialysis patients with high pre-dialysis serum potassium. Further studies are needed to identify therapeutic strategies that mitigate inter-dialytic serum potassium accumulation and subsequent high dialysate serum potassium gradients in this population

Association of thyroid status prior to transition to end-stage renal disease with early dialysis mortality.

BackgroundAdvanced chronic kidney disease (CKD) patients, including those receiving dialysis, have a high prevalence of thyroid dysfunction. Although hypothyroidism is associated with higher death risk in end-stage renal disease (ESRD) patients, no studies have examined whether thyroid status in the pre-ESRD period impacts mortality after dialysis initiation.MethodsAmong US veterans with CKD identified from the national Veterans Affairs database that transitioned to dialysis over the period from October 2007 to September 2011, we examined the association of pre-ESRD serum thyrotropin (TSH) levels averaged over the 1-year pre-dialysis ('prelude') period with all-cause mortality in the first year following dialysis initiation.ResultsAmong 15 335 patients in the 1-year prelude cohort, TSH levels &gt;5.0 mIU/L were associated with higher mortality in expanded case-mix Cox models (reference: TSH 0.5-5.0 mIU/L): adjusted hazard ratio (aHR) [95% confidence interval (CI) 1.20 (1.07-1.33). Similar findings were observed for TSH &gt;5.0 mIU/L and mortality in the 2- and 5-year cohorts: aHRs (95% CI) 1.11 (1.02-1.21) and 1.15 (1.07-1.24), respectively. Analyses of finer gradations of TSH in the 1-year prelude cohort demonstrated that incrementally higher levels &gt;5.0 mIU/L were associated with increasingly higher mortality in expanded case-mix models (reference: TSH 0.5-3.0 mIU/L): aHRs (95% CI) 1.18 (1.04-1.33) and 1.28 (1.03-1.59) for TSH levels &gt;5.0-10.0 mIU/L and &gt;10.0 mIU/L, respectively. In the 2- and 5-year cohorts, mortality associations persisted most strongly for those with TSH &gt;10.0 mIU/L, particularly after laboratory covariate adjustment.ConclusionsAmong new ESRD patients, there is a dose-dependent relationship between higher pre-ESRD TSH levels &gt;5.0 mIU/L and post-ESRD mortality. Further studies are needed to determine the impact of TSH reduction with thyroid hormone supplementation in this population

Thyroid Status and Death Risk in US Veterans With Chronic Kidney Disease.

OBJECTIVE:Given that patients with non-dialysis-dependent chronic kidney disease (NDD-CKD) have a disproportionately higher prevalence of hypothyroidism compared with their non-CKD counterparts, we sought to determine the association between thyroid status, defined by serum thyrotropin (TSH) levels, and mortality among a national cohort of patients with NDD-CKD. PATIENTS AND METHODS:Among 227,422 US veterans with stage 3 NDD-CKD with 1 or more TSH measurements during the period October 1, 2004, to September 30, 2012, we first examined the association of thyroid status, defined by TSH categories of less than 0.5, 0.5 to 5.0 (euthyroidism), and more than 5.0 mIU/L, with all-cause mortality. We then evaluated 6 granular TSH categories: less than 0.1, 0.1 to less than 0.5, 0.5 to less than 3.0, 3.0 to 5.0, more than 5.0 to 10.0, and more than 10.0 mIU/L. We concurrently examined thyroid status, thyroid-modulating therapy, and mortality in sensitivity analyses. RESULTS:In expanded case-mix adjusted Cox analyses, compared with euthyroidism, baseline and time-dependent TSH levels of more than 5.0 mIU/L were associated with higher mortality (adjusted hazard ratios [aHRs] [95% CI], 1.19 [1.15-1.24] and 1.23 [1.19-1.28], respectively), as were baseline and time-dependent TSH levels of less than 0.5 mIU/L (aHRs [95% CI], 1.18 [1.15-1.22] and 1.41 [1.37-1.45], respectively). Granular examination of thyroid status showed that incrementally higher TSH levels of 3.0 mIU/L or more were associated with increasingly higher mortality in baseline and time-dependent analyses, and TSH categories of less than 0.5 mIU/L were associated with higher mortality (reference, 0.5-&lt;3.0 mIU/L) in baseline analyses. In time-dependent analyses, untreated and undertreated hypothyroidism and untreated hyperthyroidism were associated with higher mortality (reference, spontaneous euthyroidism), whereas hypothyroidism treated-to-target showed lower mortality. CONCLUSION:Among US veterans with NDD-CKD, high-normal TSH (≥3.0 mIU/L) and lower TSH (&lt;0.5&nbsp;mIU/L) levels were associated with higher death risk. Interventional studies identifying the target TSH range associated with the greatest survival in patients with NDD-CKD are warranted