Defining vulnerability subgroups among pregnant women using pre-pregnancy information: a latent class analysis.

BACKGROUND: Early detection of vulnerability during or before pregnancy can contribute to optimizing the first 1000 days, a crucial period for children's development and health. We aimed to identify classes of vulnerability among pregnant women in the Netherlands using pre-pregnancy data on a wide range of social risk and protective factors, and validate these classes against the risk of adverse outcomes. METHODS: We conducted a latent class analysis based on 42 variables derived from nationwide observational data sources and self-reported data. Variables included individual, socioeconomic, lifestyle, psychosocial and household characteristics, self-reported health, healthcare utilization, life-events and living conditions. We compared classes in relation to adverse outcomes using logistic regression analyses. RESULTS: In the study population of 4172 women, we identified five latent classes. The largest 'healthy and socioeconomically stable'-class [n = 2040 (48.9%)] mostly shared protective factors, such as paid work and positively perceived health. The classes 'high care utilization' [n = 485 (11.6%)], 'socioeconomic vulnerability' [n = 395 (9.5%)] and 'psychosocial vulnerability' [n = 1005 (24.0%)] were characterized by risk factors limited to one specific domain and protective factors in others. Women classified into the 'multidimensional vulnerability'-class [n = 250 (6.0%)] shared multiple risk factors in different domains (psychosocial, medical and socioeconomic risk factors). Multidimensional vulnerability was associated with adverse outcomes, such as premature birth and caesarean section. CONCLUSIONS: Co-existence of multiple risk factors in various domains is associated with adverse outcomes for mother and child. Early detection of vulnerability and strategies to improve parental health and well-being might benefit from focussing on different domains and combining medical and social care and support.

Transforming maternity care: obstetric partnerships as a policy instrument for integration.

Increasing continuity in Dutch maternity care is considered pivotal to improve safety and client-centeredness. Closer collaboration between the historically relatively autonomous professionals and organizations in maternity care is deemed conditional to reach this goal, both by maternity care professionals and policy makers. Governmental policy therefore strives for organizational and financial integration. One of the policy measures has been to stimulate interprofessional and interorganizational collaboration through local obstetric partnerships. This study aimed to gain insight into whether this policy measure supported professionals in reaching the policy aim of increasing integration in the maternity care system. We therefore conducted 73 semistructured interviews with maternity care professionals in the region Northwest Netherlands, from 2014 to 2016. Respondents expressed much willingness to intensify interprofessional and interorganizational collaboration and experienced obstetric partnerships as contributing to this. As such, stimulating integration through obstetric partnerships can be considered a suitable policy measure. However, collaborating within the partnerships simultaneously highlighted deep-rooted dividing structures (organizational, educational, legal, financial) in the maternity care system, especially at the systemic level. These were experienced to hinder collaboration, but difficult for the professionals to influence, as they lacked knowledge, skills, resources and mandate. A lack of clear and timely guidance and support from policy, counterbalancing these barriers, limited partnerships' potential to unify professionals and integrate their services.

An efficient procedure to assist in the re-parametrization of structurally unidentifiable models.

An efficient method that assists in the re-parametrization of structurally unidentifiable models is introduced. It significantly reduces computational demand by combining numerical and symbolic identifiability calculations. This hybrid approach facilitates the re-parametrization of large unidentifiable ordinary differential equation models, including models where state transformations are required. A model is first assessed numerically, to discover potential structurally unidentifiable parameters. We then use symbolic calculations to confirm the numerical results, after which we describe the algebraic relationships between the unidentifiable parameters. Finally, the unidentifiable parameters are substituted with new parameters and simplification ensures that all the unidentifiable parameters are eliminated from the original model structure. The novelty of this method is its utilisation of numerical results, which notably reduces the number of symbolic calculations required. We illustrate our procedure and the detailed re-parametrization process in 5 examples: (1) an immunological model, (2) a microbial growth model, (3) a lung cancer model, (4) a JAK/STAT model, and (5) a small linear model with a non-scalable re-parametrization.

Determining minimal output sets that ensure structural identifiability.

The process of inferring parameter values from experimental data can be a cumbersome task. In addition, the collection of experimental data can be time consuming and costly. This paper covers both these issues by addressing the following question: "Which experimental outputs should be measured to ensure that unique model parameters can be calculated?". Stated formally, we examine the topic of minimal output sets that guarantee a model's structural identifiability. To that end, we introduce an algorithm that guides a researcher as to which model outputs to measure. Our algorithm consists of an iterative structural identifiability analysis and can determine multiple minimal output sets of a model. This choice in different output sets offers researchers flexibility during experimental design. Our method can determine minimal output sets of large differential equation models within short computational times.

Repeatability and reliability of muscle relaxation properties induced by motor cortical stimulation.

Impaired muscle relaxation is a feature of many neuromuscular disorders. However, few tests are available to quantify muscle relaxation. Transcranial magnetic stimulation (TMS) of the motor cortex can induce muscle relaxation by abruptly inhibiting corticospinal drive. The aim of our study was to investigate whether repeatability and reliability of TMS-induced relaxation are greater than voluntary relaxation. Furthermore, effects of sex, cooling, and fatigue on muscle relaxation properties were studied. Muscle relaxation of deep finger flexors was assessed in 25 healthy subjects (14 men and 11 women, age 39.1 ± 12.7 and 45.3 ± 8.7 yr, respectively) with handgrip dynamometry. All outcome measures showed greater repeatability and reliability in TMS-induced relaxation compared with voluntary relaxation. The within-subject coefficient of variability of normalized peak relaxation rate was lower in TMS-induced relaxation than in voluntary relaxation (3.0% vs. 19.7% in men and 6.1% vs. 14.3% in women). The repeatability coefficient was lower (1.3 vs. 6.1 s-1 in men and 2.3 vs. 3.1 s-1 in women) and the intraclass correlation coefficient was higher (0.95 vs. 0.53 in men and 0.78 vs. 0.69 in women) for TMS-induced relaxation compared with voluntary relaxation. TMS enabled demonstration of slowing effects of sex, muscle cooling, and muscle fatigue on relaxation properties that voluntary relaxation could not. In conclusion, repeatability and reliability of TMS-induced muscle relaxation were greater compared with voluntary muscle relaxation. TMS-induced muscle relaxation has the potential to be used in clinical practice for diagnostic purposes and therapy effect monitoring in patients with impaired muscle relaxation. NEW & NOTEWORTHY Transcranial magnetic stimulation (TMS)-induced muscle relaxation demonstrates greater repeatability and reliability compared with voluntary relaxation, represented by the ability to demonstrate typical effects of sex, cooling, and fatigue on muscle relaxation properties that were not seen in voluntary relaxation. In clinical practice, TMS-induced muscle relaxation could be used for diagnostic purposes and therapy effect monitoring. Furthermore, fewer subjects will be needed for future studies when using TMS to demonstrate differences in muscle relaxation properties.

R0: Host Longevity Matters.

The basic reproduction ratio, R0, is a fundamental concept in epidemiology. It is defined as the total number of secondary infections brought on by a single primary infection, in a totally susceptible population. The value of R0 indicates whether a starting epidemic reaches a considerable part of the population and causes a lot of damage, or whether it remains restricted to a relatively small number of individuals. To calculate R0 one has to evaluate an integral that ranges over the duration of the infection of the host. This duration is, of course, limited by remaining host longevity. So, R0 depends on remaining host longevity and in this paper we show that for long-lived hosts this aspect may not be ignored for long-lasting infections. We investigate in particular how this epidemiological measure of pathogen fitness depends on host longevity. For our analyses we adopt and combine a generic within- and between-host model from the literature. To find the optimal strategy for a pathogen from an evolutionary point of view, we focus on the indicator [Formula: see text], i.e., the optimum of R0 as a function of its replication and mutation rates. These are the within-host parameters that the pathogen has at its disposal to optimize its strategy. We show that [Formula: see text] is highly influenced by remaining host longevity in combination with the contact rate between hosts in a susceptible population. In addition, these two parameters determine whether a killer-like or a milker-like strategy is optimal for a given pathogen. In the killer-like strategy the pathogen has a high rate of reproduction within the host in a short time span causing a relatively short disease, whereas in the milker-like strategy the pathogen multiplies relatively slowly, producing a continuous small amount of offspring over time with a small effect on host health. The present research allows for the determination of a bifurcation line in the plane of host longevity versus contact rate that forms the boundary between the milker-like and killer-like regions. This plot shows that for short remaining host longevities the killer-like strategy is optimal, whereas for very long remaining host longevities the milker-like strategy is advantageous. For in-between values of host longevity, the contact rate determines which of both strategies is optimal.

Observability of Complex Systems: Finding the Gap.

For a reconstruction of state and parameter values in a dynamic system model, first the question whether these values can be uniquely determined from the data must be answered. This structural model property is known as observability or, in case of parameter calibration only, identifiability. Testing a given model for observability is a well studied problem in the systems and control sciences. However, it is increasingly difficult, if not impossible, to address this property for large size models that, nowadays, are frequently used. We demonstrate the application of a recently developed algorithm that overcomes this problem and is remarkably efficient. As an illustration we show how an observability analysis for a Chinese Hamster Ovary Cell model (34 states, 117 parameters), a JAKSTAT signalling model (31 states, 51 parameters), and a MAP Kinase model (100 states, 88 parameters) can be established in a very short time.

Characterization of sarcoplasmic reticulum Ca(2+) ATPase pumps in muscle of patients with myotonic dystrophy and with hypothyroid myopathy.

Sarcoplasmic/endoplasmic reticulum Ca(2+) ATPase (SERCA) pumps play the major role in lowering cytoplasmic calcium concentration in skeletal muscle by catalyzing the ATP-dependent transport of Ca(2+) from the cytosol to the lumen of the sarcoplasmic reticulum (SR). Although SERCA abnormalities have been hypothesized to contribute to the dysregulation of intracellular Ca(2+) homeostasis and signaling in muscle of patients with myotonic dystrophy (DM) and hypothyroid myopathy, the characterization of SERCA pumps remains elusive and their impairment is still unclear. We assessed the activity of SR Ca(2+)-ATPase, expression levels and fiber distribution of SERCA1 and SERCA2, and oligomerization of SERCA1 protein in muscle of patients with DM type 1 and 2, and with hypothyroid myopathy. Our data provide evidence that SR Ca(2+) ATPase activity, protein levels and muscle fiber distribution of total SERCA1 and SERCA2, and SERCA1 oligomerization pattern are similar in patients with both DM1 and DM2, hypothyroid myopathy and in control subjects. We prove that SERCA1b, the neonatal isoform of SERCA1, is expressed at protein level in muscle of patients with DM2 and, in lower amount, of patients with DM1. Our present study demonstrates that SERCA function is not altered in muscle of patients with DM and with hypothyroid myopathy.

RYR1-related myopathies: a wide spectrum of phenotypes throughout life.

BACKGROUND AND PURPOSE: Although several recent studies have implicated RYR1 mutations as a common cause of various myopathies and the malignant hyperthermia susceptibility (MHS) trait, many of these studies have been limited to certain age groups, confined geographical regions or specific conditions. The aim of the present study was to investigate the full spectrum of RYR1-related disorders throughout life and to use this knowledge to increase vigilance concerning malignant hyperthermia. METHODS: A retrospective cohort study was performed on the clinical, genetic and histopathological features of all paediatric and adult patients in whom an RYR1 mutation was detected in a national referral centre for both malignant hyperthermia and inherited myopathies (2008-2012). RESULTS: The cohort of 77 non-related patients (detection rate 28%) included both congenital myopathies with permanent weakness and 'induced' myopathies such as MHS and non-anaesthesia-related episodes of rhabdomyolysis or hyperCKemia, manifested throughout life and triggered by various stimuli. Sixty-one different mutations were detected, of which 24 were novel. Some mutations are present in both dominant (MHS) and recessive modes (congenital myopathy) of inheritance, even within families. Histopathological features included an equally wide spectrum, ranging from only subtle abnormalities to prominent cores. CONCLUSIONS: This broad range of RYR1-related disorders often presents to the general paediatric and adult neurologist. Its recognition is essential for genetic counselling and improving patients' safety during anaesthesia. Future research should focus on in vitro testing by the in vitro contracture test and functional characterization of the large number of RYR1 variants whose precise effects currently remain uncertain.

Phase segregation through transient network formation in a binary particle suspension in simple shear: application to dough.

In this paper we describe a viscoelastic type of phase separation in a simulated binary fluid with a sticky and an inert component, without any external gradients. Phase segregation under simple shear occurs due to transient network formation of the sticky component, expelling the inert particles from the network. When model parameters are adjusted to reduce network formation and rearrangement, the segregation effect is significantly smaller or absent. The behavior is independent of shear rate; segregation increases mainly with shear strain. The model is applied to wheat dough. Recent experiments have shown that prolonged shear flow of wheat dough can even give macroscopic segregation.

Modelling the impact of HIV on the populations of South Africa and Botswana.

We develop and use mathematical models that describe changes in the South African population over the last decades, brought on by HIV and AIDS. We do not model all the phases in HIV progression but rather, we show that a relatively simple model is sufficient to represent the data and allows us to investigate important aspects of HIV infection: firstly, we are able to investigate the effect of awareness on the prevalence of HIV and secondly, it enables us to make a comparison between South Africa and Botswana. A comparison is made between two models: a model that does not reflect awareness of the devastating impact of HIV and AIDS, and a model with an added psychological awareness factor. Both models are fitted to data that reflects the incidence of HIV and AIDS within South Africa. This allows us to examine the impact of psychological awareness. We show that inclusion of the effect of awareness is absolutely necessary to arrive at a model description that satisfactorily fits the available HIV and AIDS data for South Africa. We also show that a relatively simple modelling of awareness (as opposed to more complex mathematical techniques that have been used in past studies) is sufficient to accurately describe the observed patterns in the data. Even though awareness alone is not sufficient to eradicate any disease and other control strategies should be explored and implemented concurrently with educational campaigns, we are able to conclude (through thorough model analyses procedures) that the current level of awareness in South Africa is far below the level that is effectively required to eradicate HIV from the South African population. The awareness model is also fitted to HIV-related data for Botswana and we compare the results with the South African case. Though the effect of awareness is currently estimated at a much higher level in Botswana, other factors such as poorer health care and cultural differences may play a role in limiting the ability of awareness to combat HIV in Botswana.

Crop management impacts the efficiency of quantitative trait loci (QTL) detection and use: case study of fruit load×QTL interactions.

Mapping studies using populations with introgressed marker-defined genomic regions are continuously increasing knowledge about quantitative trait loci (QTL) that correlate with variation in important crop traits. This knowledge is useful for plant breeding, although combining desired traits in one genotype might be complicated by the mode of inheritance and co-localization of QTL with antagonistic effects, and by physiological trade-offs, and feed-back or feed-forward mechanisms. Therefore, integrating advances at the genetic level with insight into influences of environment and crop management on crop performance remains difficult. Whereas mapping studies can pinpoint correlations between QTL and phenotypic traits for specific conditions, ignoring or overlooking the importance of environment or crop management can jeopardize the relevance of such assessments. Here, we focus on fruit load (a measure determining competition among fruits on one plant) and its strong modulation of QTL effects on fruit size and composition. Following an integral approach, we show which fruit traits are affected by fruit load, to which underlying processes these traits can be linked, and which processes at lower and higher integration levels are affected by fruit load (and subsequently influence fruit traits). This opinion paper (i) argues that a mechanistic framework to interpret interactions between fruit load and QTL effects is needed, (ii) pleads for consideration of the context of agronomic management when detecting QTL, (iii) makes a case for incorporating interacting factors in the experimental set-up of QTL mapping studies, and (iv) provides recommendations to improve efficiency in QTL detection and use, with particular focus on model-based marker-assisted breeding.

MYCN and ALKF1174L are sufficient to drive neuroblastoma development from neural crest progenitor cells.

Neuroblastoma is an embryonal tumor with a heterogeneous clinical course. The tumor is presumed to be derived from the neural crest, but the cells of origin remain to be determined. To date, few recurrent genetic changes contributing to neuroblastoma formation, such as amplification of the MYCN oncogene and activating mutations of the ALK oncogene, have been identified. The possibility to model neuroblastoma in mice allows investigation of the cell of origin hypothesis in further detail. Here we present the evidence that murine neural crest progenitor cells can give rise to neuroblastoma upon transformation with MYCN or ALK(F1174L). For this purpose we used JoMa1, a multipotent neural crest progenitor cell line, which is kept in a viable and undifferentiated state by a tamoxifen-activated c-Myc transgene (c-MycER(T)). Expression of MYCN or ALK(F1174L), one of the oncogenic ALK variants identified in primary neuroblastomas, enabled these cells to grow independently of c-MycER(T) activity in vitro and caused formation of neuroblastoma-like tumors in vivo in contrast to parental JoMa1 cells and JoMa1 cells-expressing TrkA or GFP. Tumorigenicity was enhanced upon serial transplantation of tumor-derived cells, and tumor cells remained susceptible to the MYC-inhibitor, NBT-272, indicating that cell growth depended on functional MYCN. Our findings support neural crest progenitor cells as the precursor cells of neuroblastoma, and indicate that neuroblastomas arise as their malignant progeny.

Candidate mechanisms underlying atypical progesterone profiles as deduced from parameter perturbations in a mathematical model of the bovine estrous cycle.

The complex interplay of physiological factors that underlies fertility in dairy cows was investigated using a mechanistic mathematical model of the dynamics of the bovine estrous cycle. The model simulates the processes of follicle and corpus luteum development and its relations with key hormones that interact to control these processes. Several factors may perturb the regular oscillatory behavior of a normal estrous cycle, and such perturbations are likely the effect of simultaneous changes in multiple parameters. The objective of this paper was to investigate how multiple parameter perturbation changes the behavior of the estrous cycle model, so as to identify biological mechanisms that could play a role in the development of cystic ovaries. Cystic ovaries are a common reason for reproductive failure in dairy cows, but much about the causes of this disorder remains unknown. We investigated in which region of the parameter space the model predicts a normal cycle, and when a progesterone pattern occurred with delayed ovulation (indicating a cystic follicle) or delayed luteolysis (indicating a persistent corpus luteum). Perturbation of the initial values for all parameters simultaneously showed 2 specific parameter configurations leading to delayed ovulation or delayed luteolysis immediately. The most important parameter changes in these 2 configurations involve the regulation of corpus luteum functioning, luteolytic signals, and GnRH synthesis, suggesting that these mechanisms are likely involved in the development of cystic ovaries. In the multidimensional parameter space, areas exist in which the parameter configurations resulted in normal cycles. These areas may be separated by areas in which irregular cycle patterns occurred. These irregular patterns thus mark the transition from one stable (normal) situation to another. Interestingly, within a series, there were some cycles with delayed ovulation and some with delayed luteolysis in these patterns. This could represent a situation of resumption of normal cyclicity (e.g., after parturition). In conclusion, the method of parameter perturbation used in the present study is an effective tool to find parameter configurations that lead to progesterone profiles associated with delayed ovulation and delayed luteolysis. Thereby, the model helps to generate hypotheses regarding the underlying cause of the development of cystic ovaries, which could be investigated in future experiments.

Oncogenic activation of FOXR1 by 11q23 intrachromosomal deletion-fusions in neuroblastoma.

Neuroblastoma tumors frequently show loss of heterozygosity of chromosome 11q with a shortest region of overlap in the 11q23 region. These deletions are thought to cause inactivation of tumor suppressor genes leading to haploinsufficiency. Alternatively, micro-deletions could lead to gene fusion products that are tumor driving. To identify such events we analyzed a series of neuroblastomas by comparative genomic hybridization and single-nucleotide polymorphism arrays and integrated these data with Affymetrix mRNA profiling data with the bioinformatic tool R2 (http://r2.amc.nl). We identified three neuroblastoma samples with small interstitial deletions at 11q23, upstream of the forkhead-box R1 transcription factor (FOXR1). Genes at the proximal side of the deletion were fused to FOXR1, resulting in fusion transcripts of MLL-FOXR1 and PAFAH1B2-FOXR1. FOXR1 expression has only been detected in early embryogenesis. Affymetrix microarray analysis showed high FOXR1 mRNA expression exclusively in the neuroblastomas with micro-deletions and rare cases of other tumor types, including osteosarcoma cell line HOS. RNAi silencing of FOXR1 strongly inhibited proliferation of HOS cells and triggered apoptosis. Expression profiling of these cells and reporter assays suggested that FOXR1 is a negative regulator of fork-head box factor-mediated transcription. The neural crest stem cell line JoMa1 proliferates in culture conditional to activity of a MYC-ER transgene. Over-expression of the wild-type FOXR1 could functionally replace MYC and drive proliferation of JoMa1. We conclude that FOXR1 is recurrently activated in neuroblastoma by intrachromosomal deletion/fusion events, resulting in overexpression of fusion transcripts. Forkhead-box transcription factors have not been previously implicated in neuroblastoma pathogenesis. Furthermore, this is the first identification of intrachromosomal fusion genes in neuroblastoma.

Accumulation of human EGF in nectar of transformed plants of Nicotiana langsdorffii x N. sanderae and transfer to honey by bees.

Honey has been used successfully in wound healing for thousands of years. The peptide hormone human epidermal growth factor (hEGF) is also known to have a beneficial effect in various wound healing processes via mechanisms that differ from those for honey. In this study, we show that hEGF can be incorporated into honey via nectar. Plants of Nicotiana langsdorffii x N. sanderae were transformed with the gene for hEGF, equipped with a nectary-targeted promoter and a signal sequence for secretion to nectar. These plants accumulated hEGF in the nectar. The maximum hEGF concentration recorded with ELISA in these plants is 2.5 ng·ml⁻¹. There is a significant linear relationship (P<0.001) between hEGF concentration and induction of hEGF-receptor phosphorylation. Since the flower morphology of these plants did not allow production of honey from their nectar, we used feeding solutions, spiked with synthetic hEGF, to study transfer of this peptide into honey through bee activity. Transfer of hEGF from a feeding solution to honey by bees occurred with retention of the hEGF concentration and the capacity to induce hEGF-receptor phosphorylation. These observations indicate that plants can function as a production platform for honey containing biologically active peptides, which may enhance wound healing and other biological processes.

Cyclin D1 is a direct transcriptional target of GATA3 in neuroblastoma tumor cells.

Almost all neuroblastoma tumors express excess levels of Cyclin D1 (CCND1) compared to normal tissues and other tumor types. Only a small percentage of these neuroblastoma tumors have high-level amplification of the Cyclin D1 gene. The other neuroblastoma tumors have equally high Cyclin D1 expression without amplification. Silencing of Cyclin D1 expression was previously found to trigger differentiation of neuroblastoma cells. Overexpression of Cyclin D1 is therefore one of the most frequent mechanisms with a postulated function in neuroblastoma pathogenesis. The cause for the Cyclin D1 overexpression is unknown. Here we show that Cyclin D1 overexpression results from transcriptional upregulation. To identify upstream regulators, we searched in mRNA profiles of neuroblastoma tumor series for transcription factors with expression patterns correlating to Cyclin D1. GATA3 most consistently correlated to Cyclin D1 in four independent data sets. We identified a highly conserved GATA3 binding site 27 bp upstream of the Cyclin D1 transcriptional start. Chromatin immune precipitation confirmed binding of GATA3 to the Cyclin D1 promoter. Overexpression of GATA3 induced Cyclin D1 promoter activity, which decreased after site-directed mutagenesis of the GATA3 binding site in the Cyclin D1 promoter. Silencing of GATA3 resulted in reduced Cyclin D1 promoter activity and reduced Cyclin D1 mRNA and protein levels. Moreover, GATA3 silencing caused differentiation that was similar to that caused by Cyclin D1 inhibition. These finding implicate GATA3 in Cyclin D1 overexpression in neuroblastoma.