Maternal Cognitions and the Origins of Early Sensorimotor Based Play in Infants Born Preterm

Maternal cognitions are beliefs, perceptions, and expectations that guide parenting practices. For at-risk infants born prematurely, these maternal constructs may influence the caregiving environment and opportunities for motor experience. The impact of maternal cognitions on motor development in infants born preterm is not well-documented. This three-part dissertation systematically explores: 1) the nature and extent of existing evidence supporting the link between maternal cognitions and motor development of infants born preterm, 2) if maternal perception of infant vulnerability as measured by an adapted Vulnerable Baby Scale (VBS) can be validly and reliably quantified in mothers of infants born preterm and near term-adjusted age, prior to discharge from the Newborn Intensive Care Unit (n=41), and finally, 3) the relationship between maternal cognitions, specifically perception of infant vulnerability and parenting confidence, and sensorimotor based maternal-infant play interactions (n=7) at near-term infant adjusted age. Existing evidence from a scoping review, though contradictory, implicates a plausible link between maternal cognitions such as depression, decreased parenting confidence, and increased maternal perception of infant vulnerability and a variety of adverse infant developmental outcomes including motor. Psychometric testing of an adapted VBS demonstrated strong content validity and test-retest reliability, moderate internal consistency. A component factor analysis aligned the self-report measure with three primary and relevant constructs: worries about baby, protective care practices, and perceptions about general health. Finally, mixed method analysis of mother-infant sensorimotor play interactions prior to NICU discharge revealed parenting confidence scores were not correlated with maternal or infant sociodemographic variables; perception of infant health vulnerability scores were correlated with maternal age and infant movement duration; inversely correlated with infant exploratory behaviors, and frequency of maternal alerting behaviors. Despite uncertainty, Mothers demonstrated foundational knowledge about interactive play and intuitively used both alerting and soothing sensorimotor strategies to engage with infants born preterm. Further study is warranted to determine if parent-mediated, early-infancy play may be targeted as a NICU developmental risk screening or intervention approach

Sitting Postural Control in Infants With Typical Development, Motor Delay, or Cerebral Palsy

Purpose: To determine whether infants born full-term, infants born preterm with motor delays, and infants born preterm who have a diagnosis of cerebral palsy (CP) differed in postural control at the emergence of early sitting. Methods: Thirty infants born at term who were developing typically, 6 infants born preterm who were later diagnosed with CP, and 5 infants born preterm who were delayed in motor development participated in this study. Center-of-pressure data from unsupported sitting were recorded and analyzed using measures of both amount and temporal organization of center-of-pressure variability. Results: Infants born full-term, infants born preterm with motor delays, and infants born preterm who have a diagnosis of CP exhibited dissimilar movement-control strategies at the onset of sitting. Conclusions: The present findings may be helpful in directing and testing intervention protocols for infants born preterm

Comparison Between Standard HABIT and HABIT-VR: Hand-Arm Function and Patient Acceptability Differences​

https://digitalcommons.unmc.edu/surp2022/1002/thumbnail.jp

Object Permanence and the Relationship to Sitting Development in Infants With Motor Delays

Purpose: This study examines object permanence development in infants with motor delays (MD) compared with infants with typical development (TD) and in relation to sitting skill. Methods: Fifty-six infants with MD (mean age = 10 months) and 36 with TD (mean age = 5.7 months) were assessed at baseline and then at 1.5, 3, and 6 months postbaseline. A scale was developed to measure object permanence (Object Permanence Scale [OPS]), and the Gross Motor Function Measure sitting subsection (GMFM-SS), and the Bayley Scales of Infant and Toddler Development, 3rd Edition (Bayley-III) were administered. Results: Interrater reliability of the OPS was excellent and correlation between the OPS and Bayley-III cognitive scores was moderately positive. Compared with TD, infants with MD were delayed in development of object permanence but demonstrated increased understanding over time and as sitting skills improved. Conclusion: In children with MD, object permanence, as quantified by the OPS, emerges in conjunction with sitting skill

Polyclonal human antibodies against glycans bearing red meat-derived non-human sialic acid N-glycolylneuraminic acid are stable, reproducible, complex and vary between individuals: Total antibody levels are associated with colorectal cancer risk.

BACKGROUND: N-glycolylneuraminic acid (Neu5Gc) is a non-human red-meat-derived sialic acid immunogenic to humans. Neu5Gc can be metabolically incorporated into glycan chains on human endothelial and epithelial surfaces. This represents the first example of a "xeno-autoantigen", against which circulating human "xeno-autoantibodies" can react. The resulting inflammation ("xenosialitis") has been demonstrated in human-like Neu5Gc-deficient mice and contributed to carcinoma progression via antibody-mediated inflammation. Anti-Neu5Gc antibodies have potential as biomarkers for diseases associated with red meat consumption such as carcinomas, atherosclerosis, and type 2 diabetes. METHODS: ELISA assays measured antibodies against Neu5Gc or Neu5Gc-glycans in plasma or serum samples from the Nurses' Health Studies, the Health Professionals Follow-up Study, and the European Prospective Investigation into Cancer and Nutrition, including inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over 1-3 years in archived samples. We also assessed associations between antibody levels and coronary artery disease risk (CAD) or red meat intake. A glycan microarray was used to detected antibodies against multiple Neu5Gc-glycan epitopes. A nested case-control study design assessed the association between total anti-Neu5Gc antibodies detected in the glycan array assay and the risk of colorectal cancer (CRC). RESULTS: ELISA assays showed a wide range of anti-Neu5Gc responses and good inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over time, but these antibody levels did not correlate with CAD risk or red meat intake. Antibodies against Neu5Gc alone or against individual Neu5Gc-bearing epitopes were also not associated with colorectal cancer (CRC) risk. However, a sialoglycan microarray study demonstrated positive association with CRC risk when the total antibody responses against all Neu5Gc-glycans were combined. Individuals in the top quartile of total anti-Neu5Gc IgG antibody concentrations had nearly three times the risk compared to those in the bottom quartile (Multivariate Odds Ratio comparing top to bottom quartile: 2.98, 95% CI: 0.80, 11.1; P for trend = 0.02). CONCLUSIONS: Further work harnessing the utility of these anti-Neu5Gc antibodies as biomarkers in red meat-associated diseases must consider diversity in individual antibody profiles against different Neu5Gc-bearing glycans. Traditional ELISA assays for antibodies directed against Neu5Gc alone, or against specific Neu5Gc-glycans may not be adequate to define risk associations. Our finding of a positive association of total anti-Neu5Gc antibodies with CRC risk also warrants confirmation in larger prospective studies

Galaxy Zoo: CANDELS barred discs and bar fractions

The formation of bars in disc galaxies is a tracer of the dynamical maturity of the population. Previous studies have found that the incidence of bars in discs decreases from the local Universe to z ~ 1, and by z > 1 simulations predict that bar features in dynamically mature discs should be extremely rare. Here, we report the discovery of strong barred structures in massive disc galaxies at z ~ 1.5 in deep rest-frame optical images from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey. From within a sample of 876 disc galaxies identified by visual classification in Galaxy Zoo, we identify 123 barred galaxies. Selecting a subsample within the same region of the evolving galaxy luminosity function (brighter than L*), we find that the bar fraction across the redshift range 0.5 ≤ z ≤ 2 (fbar = 10.7+6.3 -3.5 per cent after correcting for incompleteness) does not significantly evolve.We discuss the implications of this discovery in the context of existing simulations and our current understanding of the way disc galaxies have evolved over the last 11 billion yearsPeer reviewedFinal Accepted Versio

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Galaxy Zoo: CANDELS barred discs and bar fractions

The formation of bars in disc galaxies is a tracer of the dynamical maturity of the population. Previous studies have found that the incidence of bars in discs decreases from the local Universe to z ∼ 1, and by z>1 simulations predict that bar features in dynamically mature discs should be extremely rare. Here, we report the discovery of strong barred structures in massive disc galaxies at z ∼ 1.5 in deep rest-frame optical images from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey. From within a sample of 876 disc galaxies identified by visual classification in Galaxy Zoo, we identify 123 barred galaxies. Selecting a subsample within the same region of the evolving galaxy luminosity function (brighter than L*), we find that the bar fraction across the redshift range 0.5 ≤ z ≤ 2 ( $f_{{\rm bar}} = 10.7^{+6.3}_{-3.5}$ per cent after correcting for incompleteness) does not significantly evolve. We discuss the implications of this discovery in the context of existing simulations and our current understanding of the way disc galaxies have evolved over the last 11 billion year

Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability

Background Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models. Methods We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD. Conclusions The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.PTDC/EEI-SII/1937/2014; SFRH/BD/95846/2013; SFRH/BD/118872/2016info:eu-repo/semantics/publishedVersio