Development of Restricted and Repetitive Behaviors from 2-19: Stability and Change in Repetitive Sensorimotor, Insistence on Sameness, and Verbal Behaviors in a Longitudinal Study of Autism

This study examined trajectories of repetitive sensorimotor (RSM), insistence on sameness (IS), and verbal RRBs from ages 2-19 in a well-characterized longitudinal cohort. We also tested the factor structure of the ADI-R restricted and repetitive behavior (RRB) domain at age 19 and the inclusion of a verbal RRBs factor, in addition to previously identified RSM and IS factors, at ages 9 and 19. The ADI-R was administered to 193 participants at five timepoints from 2 to 19. Confirmatory factor analysis (CFA) was used to examine the factor structure of ADI-R RRB data. Change in RRB subtypes was examined using group-based trajectory modeling and multilevel modeling. RSM and IS behaviors generally decreased from 2 to 19, with some participants experiencing increases from ages 2-9. 46.46% of participants experienced increasing verbal RRBs from 2 to 9, followed by a plateau from 9 to 19. The remaining participants had few to no verbal RRBs throughout development. Multilevel modeling indicated ADOS CSS scores were associated with change in RSM trajectories only. Child IQ was not associated with change in any RRB trajectories. CFA indicated previously-derived RSM and IS factors fit age 19 ADI-R data well. The inclusion of a third factor, verbal RRBs, worsened goodness-of-fit statistics and was ultimately omitted. Our findings suggest the RRB factor structure of the ADI remains consistent into early adulthood and illustrate developmental continuity and change in RRBs. For autistic individuals with fluent speech, RRB presentation may be influenced by verbal ability in ways that are highly variable, but clinically meaningful.

Mechanical modeling of the maturation process for tissue-engineered implants: Application to biohybrid heart valves

The development of tissue-engineered cardiovascular implants can improve the lives of large segments of our society who suffer from cardiovascular diseases. Regenerative tissues are fabricated using a process called tissue maturation. Furthermore, it is highly challenging to produce cardiovascular regenerative implants with sufficient mechanical strength to withstand the loading conditions within the human body. Therefore, biohybrid implants for which the regenerative tissue is reinforced by standard reinforcement material (e.g. textile or 3d printed scaffold) can be an interesting solution. In silico models can significantly contribute to characterizing, designing, and optimizing biohybrid implants. The first step towards this goal is to develop a computational model for the maturation process of tissue-engineered implants. This paper focuses on the mechanical modeling of textile-reinforced tissue-engineered cardiovascular implants. First, an energy-based approach is proposed to compute the collagen evolution during the maturation process. Then, the concept of structural tensors is applied to model the anisotropic behavior of the extracellular matrix and the textile scaffold. Next, the newly developed material model is embedded into a special solid-shell finite element formulation with reduced integration. Finally, our framework is used to compute two structural problems: a pressurized shell construct and a tubular-shaped heart valve. The results show the ability of the model to predict collagen growth in response to the boundary conditions applied during the maturation process. Consequently, the model can predict the implant's mechanical response, such as the deformation and stresses of the implant.

Improving microalgae growth modeling of outdoor cultivation with light history data using machine learning models: A comparative study

Accurate prediction of microalgae growth is crucial for understanding the impacts of light dynamics and optimizing production. Although various mathematical models have been proposed, only a few of them have been validated in outdoor cultivation. This study aims to investigate the use of machine learning algorithms in microalgae growth modeling. Outdoor cultivation data of Phaeodactylum tricornutum in flat-panel airlift photobioreactors for 50 days were used to compare the performance of Long Short-Term Memory (LSTM) and Support Vector Regression (SVR) with traditional models, namely Monod and Haldane. The results indicate that the machine learning models outperform the traditional models due to their ability to utilize light history as input. Moreover, the LSTM model shows an excellent ability to describe the light acclimation effect. Last, two potential applications of these models are demonstrated: 1) use as a biomass soft sensor and 2) development of an optimal harvest strategy for outdoor cultivation.

Musings on intrinsic cardiomyocyte cell cycle activity and myocardial regeneration

Although the myocardial renewal rate in the adult mammalian heart is quite low, recent studies have identified genetic variants which can impact the degree of cardiomyocyte cell cycle reentry. Here we use the compound interest law to model the level of regenerative growth over time in mice exhibiting different rates of cardiomyocyte cell cycle reentry following myocardial injury. The modeling suggests that the limited ability of S-phase adult cardiomyocytes to progress through cytokinesis, rather than the ability to reenter the cell cycle per se, is a major contributor to the low levels of intrinsic regenerative growth in the adult myocardium.

Semicontinuous and batch ozonation combined with peroxymonosulfate for inactivation of microalgae in ballast water

The Ballast Water Management Convention (BWMC) establishes limits regarding the permissible number of viable organisms in discharged ballast water. Ozone as a ballast water treatment is interesting because it can be generated in-situ and has strong oxidant power. Additionally, some oxidants can be formed in reaction with seawater, especially brominated compounds, that assist in inactivating microorganisms. The objective of this study is to assess the efficacy of semicontinuous and batch ozonation as well as their combination with peroxymonosulfate salt (PMS) as methods to be used to ensure compliance with regulation D2 of the BWMC using Tetraselmis suecica as a standard microorganism. Growth modeling method was employed to determine the inactivation achieved by the treatments. The results show that ozone is an effective treatment for accomplishing the D2 of the BWMC. Batch ozonation is more efficient than semicontinuous ozonation probably because of the brominated compounds formed during the ozone saturation of the water. The oxidants that are developed during the ozonation of seawater prolong the residual effect of the treatment throughout the days of storage with practically no presence of them in the ballast tanks at 72 h. The addition of the PMS increases the inactivation in the semicontinuous ozonation, but a threshold concentration of ozone is needed to observe the synergistic effect of both oxidants. No increase is associated with the combination of O₃ and PMS in the case of batch ozonation.

Longitudinal PTSD symptom trajectories: Relative contributions of state anxiety, depression, and emotion dysregulation

BACKGROUND

Prospective research on the development and trajectory of PTSD symptoms after a traumatic event is crucial for assessment and early intervention. Further, examining predictors of PTSD pathology provides a better conceptualization of the temporal course of PTSD in trauma victims.

METHODS

The present study examined PTSD symptom severity in individuals presenting to the emergency department (ED) following a traumatic event. Participants (N = 147) were assessed at four timepoints: 2-weeks, 3-months, between 6 and 9 months, and 12-months after ED admission. Growth curve modeling was conducted to examine changes in PTSD symptom severity over time. Age, sex, state anxiety, trait anxiety, emotion dysregulation, depression, and trauma type (motor vehicle accident [MVA] and assault), and PTSD diagnosis were included as covariates in the model.

RESULTS

Results demonstrated that baseline PTSD symptom severity was positively associated with severity of depression and state (but not trait) anxiety, emotion dysregulation, and PTSD diagnosis. Results also revealed significant associations with PTSD symptom changes over time; greater state anxiety and depression symptoms at baseline were associated with steeper declines in PTSD symptoms over time.

LIMITATIONS

Data were collected at only four timepoints over the course of 12-months. Results may be different with more measurement points over longer periods and inclusion of pre-, peri- and post-trauma risk factors.

CONCLUSIONS

Results illustrate the relevance of assessing state anxiety, depression, and emotion dysregulation in following trauma victims for trauma-related psychopathology over the course of time to alleviate the negative impact of the same.

Interpreting the effectiveness of a summer reading program: The eye of the beholder

In applying a methods-oriented approach to evaluation, this study interpreted the effectiveness of a summer reading program from three different stakeholder perspectives: practitioners from the school district, the funding agency supporting the program, and the policymakers considering mandating summer school. Archival data were obtained on 2330 students reading below benchmark in Grades 2-5. After propensity score matching participants to peers who did not attend the summer program, the final sample consisted of 630 students. Pre-to-posttest growth models revealed positive effects in Grades 2-4 (standardized slopes of .40-.54), but fifth graders demonstrated negligible improvement (standardized slope of .15). The standardized mean differences of propensity score matched treatment and control group students indicated null effects in all grade levels (d = -.13 to .05). Achieving proficient reading performance also was not attributable to summer school participation. Findings underscore the importance of operationalizing effectiveness in summative evaluation.

Recent growth trends of conifers across Western Europe are controlled by thermal and water constraints and favored by forest heterogeneity

Tree growing conditions are changing rapidly in the face of climate change. Capturing tree-growth response to such changes across environmental contexts and tree species calls for a continuous forest monitoring over space. Based on >10,000 tree-ring measurements sampled across the systematic grid of the continuous French national forest inventory (NFI) over the 2006-2016 period, we evaluated the radial growth trends of eight conifer tree species prevalent in European forests across their native and introduced ranges and various bioclimatic contexts (n = 16 forest systems). For each forest system, radial increments were filtered out from tree, plot, soil and climatic normal influences to isolate environment-driven growth signals and quantify residual time-series. Associated growth trends across forest systems were then confronted against environmental variables (e.g. short-term averages and trends in seasonal climate). Trends for a given species were systematically more positive in cooler contexts (higher elevations or northern distribution margins) than in warmer contexts (plains). Decreases and increases in precipitation regimes were found to be associated with negative and positive tree growth trends, respectively. Remarkably, positive growth trends were mainly observed for native forest systems (7/9) and negative trends for introduced systems (5/7). Native forests showed a more heterogeneous forest structure as compared to introduced forests that, in line with observed positive dependence of tree growth trends onto both water availability and forest heterogeneity, appears to modulate the competitive pressure on water resource with ongoing summer maximum temperature increase. Over a short annually-resolved study period, we were able to capture tree growth responses coherent with climate change across diverse forest ecosystems. With ongoing accumulation of data, the continuous French NFI hence arises as powerful support to monitoring climate change effects on forests.

Frailty and depression: Reciprocal influences or common causes?

BACKGROUND

Previous research demonstrated substantial associations between frailty and depression in late life, but it remains unclear whether this relationship is best explained by reciprocal influences of these variables or by common causes. This study investigated the interdependencies between frailty and depression across time by examining cross-lagged effects within individuals, while accounting for variability in baseline levels and long-term development between individuals.

METHODS

We modeled longitudinal data from six panel waves gathered in the Survey of Health, Ageing and Retirement in Europe, covering a time period of up to 14 years. The total sample size was N = 58,152 individuals aged 50 years or older. Frailty was based on a deficit accumulation frailty index and depressive symptoms were measured with the EURO-D scale. We used a latent curve model with structured residuals for statistical analysis.

RESULTS

The results did not demonstrate relevant cross-lagged effects of frailty and depression at the within-person level. However, within-person increases in frailty were accompanied by within-person increases in depression at the same point in time. At the between-person level, it showed that individuals with higher levels and steeper trajectories in frailty also tend to show higher levels and steeper trajectories in depression.

CONCLUSION

These findings question the notion that frailty and depression reciprocally influence each other over the course of time, but rather indicate that frailty and depression might be both affected by common causes, in both the short and the long term.

Antibiotic dry cow therapy, somatic cell count, and milk production: Retrospective analysis of the associations in dairy herd recording data using multilevel growth models

Antibiotic dry cow therapy (DCT) is an important part of most mastitis control programs. Updating DCT recommendations is an ongoing topic due to the global problem of antimicrobial resistance. Finland, along with other Nordic countries, has implemented selective DCT for decades. Our study analyzed Dairy Herd Improvement (DHI) information from 241 Finnish farmers who participated in a survey about their drying-off practices. The aim was to evaluate herd-level associations between milk somatic cell count (SCC), milk production, and various antimicrobial DCT approaches both cross-sectionally in 2016 and longitudinally in 2012-2016. The three DCT approaches in the study were selective, blanket, and no DCT use. An additional aim was to evaluate whether dynamic changes occurred in herd-average SCC and annual milk production over five years, and whether these potential changes differed between different DCT approaches. The method for the longitudinal analyses was growth modeling with random coefficient models. Differences in SCC and milk production between farms with different DCT approaches were minor. Regardless of the farm's DCT approach, annual milk production increased over the years, while average SCC was reasonably constant. The variability in SCC and milk production across all DCT groups was low between years, and most of the variability was between farms. Compared to other milking systems, farms with automatic milking system (AMS) had higher SCC, and in 2016 higher milk production. The results of this study suggest that it is possible to maintain low herd-average SCC and good milk production when using selective DCT and following the guidelines for prudent antimicrobial use. Average SCC and milk production varied across the herds, suggesting that advice on DCT practices should be herd-specific. The methodology of growth modeling using random coefficient models was applicable in analyzing longitudinal data, in which the time frame was relatively short and the number of herds was limited.

Effect of ripening time on bacteriological and physicochemical goat milk cheese characteristics

Cheese ripening involves lactose metabolism, lipolysis and proteolysis, which are affected by many factors. The aim of this study was to assess changes due to ripening (90 days) of goat milk cheese through bacteriological and physicochemical analysis in order to verify if, at the end of ripening period, this cheese could be considered "lactose-free". Three batches of the goat milk cheese were manufactured and ripened at 10 °C and 80% relative humidity for 90 days. Titratable acidity increased by about 59 °D due to carbohydrate degradation and organic acid production. However, pH (5.31-5.25) remained constant. Lactococcus was the dominant cheese microbiota, acting in the fermentation of lactose (1.17-0.06 mg/g) and lactic acid production (5.49-s10.01 mg/g). Thus, ripening time was decisive for bacteriological and physicochemical goat milk cheese characteristics.

When neighborhoods matter: Developmental timing and youth reading achievement and problem behaviors

Consistent evidence links neighborhood socioeconomic status with children's development outcomes. However, it is less clear precisely whether or when neighborhoods are most strongly associated with children's socioemotional functioning and achievement. Couched in bioecological and developmental theory, this study tests two models of neighborhood effects: childhood and adolescent exposure. We used the Project on Human Development in Chicago Neighborhoods, a longitudinal, multi-cohort study of children in Chicago in the 1990s and 2000s. We examined two cohorts of children, early childhood and adolescence, to compare the relative associations between neighborhood socioeconomic advantage and disadvantage, as measured by U.S. Census data. We conducted multilevel latent growth models (MLGMs), investigating children's initial status and growth in reading, internalizing and externalizing behaviors across the three developmental periods by neighborhood characteristics, controlling for a rich set of child- and family-level covariates. Results provided some support for the childhood and adolescent exposure models, but not precisely as hypothesized.

The dynamic course of peripartum depression across pregnancy and childbirth

OBJECTIVE

Peripartum depression (PPD) pertaining to depression in pregnancy and postpartum is one of the most common complications around childbirth with enduring adverse effects on mother and child health. Although psychiatric symptoms may improve or worsen over time, relatively little is known about the course of PPD symptoms and possible fluctuations.

METHODS

We applied a person-centered approach to examine PPD symptom patterns across pregnancy and childbirth. 824 women were assessed at three time points: first trimester (T1), third trimester (T2), and again at eight weeks (T3) postpartum. We assessed PPD symptoms, maternal mental health history, and childbirth variables.

RESULTS

Growth mixture modeling (GMM) analysis revealed four discrete PPD symptom trajectory classes including chronic PPD (1.1%), delayed (10.2%), recovered (7.2%), and resilient (81.5%). Delivery complications were associated with chronic PPD but also with the recovered PPD trajectory class. History of mental health disorders was associated with chronic PPD and the delayed PPD class.

CONCLUSION

The findings underscore that significant changes in a woman's depression level can occur across pregnancy and childbirth. While a minority of women experience chronic PDD, for others depression symptoms appear to significantly alleviate over time, suggesting a form of recovery. Our findings support a personalized medicine approach based on the woman's symptom trajectory. Future research is warranted to identify the mechanisms underlying modifications in PPD symptoms severity and those implicated in recovery.

Two-Year Impact of Prevention Programs on Adolescent Depression: an Integrative Data Analysis Approach

This paper presents the first findings of an integrative data analysis of individual-level data from 19 adolescent depression prevention trials (n = 5210) involving nine distinct interventions across 2 years post-randomization. In separate papers, several interventions have been found to decrease the risk of depressive disorders or elevated depressive/internalizing symptoms among youth. One type of intervention specifically targets youth without a depressive disorder who are at risk due to elevated depressive symptoms and/or having a parent with a depressive disorder. A second type of intervention targets two broad domains: prevention of problem behaviors, which we define as drug use/abuse, sexual risk behaviors, conduct disorder, or other externalizing problems, and general mental health. Most of these latter interventions improve parenting or family factors. We examined the shared and unique effects of these interventions by level of baseline youth depressive symptoms, sociodemographic characteristics of the youth (age, sex, parent education, and family income), type of intervention, and mode of intervention delivery to the youth, parent(s), or both. We harmonized eight different measures of depression utilized across these trials and used growth models to evaluate intervention impact over 2 years. We found a significant overall effect of these interventions on reducing depressive symptoms over 2 years and a stronger impact among those interventions that targeted depression specifically rather than problem behaviors or general mental health, especially when baseline symptoms were high. Implications for improving population-level impact are discussed.

From phytoaccumulation to post-harvest use of water fern for landfill management

We examined the potential of Azolla japonica as a remediating plant for leachate channels and post-accumulation use as fertilizer for landfill slope. The harvested biomass of Azolla after one month grown in leachate was 254% that of the initial biomass and the predicted annual harvestable biomass of Azolla using a growth model was 32 times that of the initial biomass. Na, Fe, Mn, Mg, and P were accumulated in Azolla at very high concentrations. Such rapid increase of biomass and high accumulation rates suggest that this plant could be an excellent remediating plant. The post-harvest use of Azolla as compost was studied for the management and use of phytoaccumulating Azolla. Metal contents of Azolla compost were below permissible limits for co-composting material. Nitrogen, organic matter, P, and Mg content of the Azolla compost improved the soil condition of the landfill and enhanced ecophysiological responses of the plants. The application of Azolla compost can improve management of sanitary landfills, including the restoration of vegetation. Considering its ease of harvesting, high accumulation rates, harvestable biomass and suitability for composting, Azolla can provide a suitable solution for sustainable management of leachate channels and landfill slopes.

Perinatal exposure to chlordecone and infant growth

BACKGROUND

The intensive use of chlordecone (an organochlorine insecticide) in the French West Indies until 1993 resulted in a long-term soil and water contamination. Chlordecone has known hormonal properties and exposure through contaminated food during critical periods of development (gestation and early infancy) may affect growth.

OBJECTIVES

We aimed to assess the impact of prenatal and postnatal exposure to chlordecone on the growth of children from the TIMOUN mother-child cohort.

METHODS

Chlordecone was determined in cord plasma at birth (N=222) and in breast milk samples (at 3 months). Dietary chlordecone intake was estimated at 7 and 18 months, with food-frequency questionnaires and food-specific contamination data. Anthropometric measurements were taken at the 3-, 7- and 18-month visits and measurements reported in the infants' health records were noted. Structured Jenss-Bayley growth models were fitted to individual height and weight growth trajectories. The impact of exposure on growth curve parameters was estimated directly with adjusted mixed non-linear models. Weight, height and body mass index (BMI), and instantaneous height and weight growth velocities at specific ages were also analyzed relative to exposure.

RESULTS

Chlordecone in cord blood was associated with a higher BMI in boys at 3 months, due to greater weight and lower height, and in girls at 8 and 18 months, mostly due to lower height. Postnatal exposure was associated with lower height, weight and BMI at 3, 8 and 18 months, particularly in girls.

CONCLUSION

Chlordecone exposure may affect growth trajectories in children aged 0 to 18 months.

Modeling the sustainability of community health networks: novel approaches for analyzing collaborative organization partnerships across time

Sustainability is important if community health organizations are to be effective in collaborating to achieve long term health goals. We present a multi-method set of longitudinal analyses examining structural markers applied to a group of organizations brought together to reduce cancer disparities among older African American adults. At the overall network level, sustainability was seen in the growth of outgoing connections and multiplexity. Results of hierarchical clustering analyses identified distinct patterns of collaborative activation over time at the relationship level. Growth modeling indicated the effects of continuing network membership and participation in collaborative events on several structural markers of sustainability. Results of these analyses provide longitudinal indicators for how collaborations among partner organizations impacted their likelihood of continuing in the community network program. The strategy presented here introduces novel methods to assist with planning and evaluation of future community based public health endeavors.

Diminution of 2,3,5-triphenyltetrazolium chloride toxicity on Listeria monocytogenes growth by iron source addition to the culture medium

Tetrazolium salts (TTZ) such as 2,3,5-triphenyltetrazolium chloride (TTC) are readily reduced by bacterial populations of various genus. The reduced form of these redox indicators is conspicuously colored allowing a quick and easy detection of growth. The studies are mainly confined to Gram negative bacteria because of an important toxic effect of tetrazolium salts on Gram positive bacteria. Indeed, we observed an important impact of different tetrazolium salts on Listeria monocytogenes growth, curiously limited to an increase in the duration of the lag phase. In this study, we demonstrate that increasing the iron concentration in a medium containing TTC leads to a significant decrease of the lag phase. L. monocytogenes growth was kinetically measured and growth parameters were estimated using the Baranyi model. While lag phase diminution was found to be iron concentration dependent, growth rate was not affected. Addition of iron enables growth of some strains totally inhibited by a 0.4 g/l of TTC and for the other a significant reduction of the latency is observed. The nature of the mechanism resulting in a decrease of the observed lag phase remains unclear. Then, the use of iron supplementation may be proposed to overcome the inhibitory effect of TTC on L. monocytogenes.