Predictors of Stability/Change in Observed Parenting Patterns Across Early Childhood: A Latent Transition Approach.

Parenting has long been a topic of research based on its importance for family and child outcomes. Recent methodological advances in person-centered approaches suggest that our understanding of parenting could be further advanced by examining parenting typologies across various parenting behaviors longitudinally. Accordingly, the current study aims to examine latent transitions in parenting practice patterns across four annual assessments during early childhood and examine whether individual- and family-level factors at baseline discriminate parenting transition patterns.

Enhancing Data Science and Genomics Capacity of a Historically Black Medical College Through Interdisciplinary Training and Research Collaborations.

As data grows exponentially across diverse fields, effectively leveraging big data has become increasingly crucial. In data science and computational genomics, however, minority groups, including African Americans, are significantly underrepresented, coupled with the lack of resources and infrastructure in minority-serving institutions. This paper summarizes the second phase of our funded project that aims to enhance the data science capacity of Meharry Medical College (MMC), a Historically Black College/University (HBCU), by providing training and fostering collaborations between data scientists and researchers in basic science and biomedical fields.

Incidence, Prediction, and Prevention of Fractures After Kidney Transplantation: A Systematic Review Protocol.

Background: Kidney transplant recipients are uniquely exposed to the disordered bone metabolism associated with chronic kidney disease beginning before transplantation followed by chronic corticosteroid use after transplantation. Previous efforts to synthesize the rapidly accruing evidence regarding estimation and management of fracture risk in kidney transplant recipients are outdated and incomplete.

Objective: To synthesize the evidence informing the overall incidence, patient-specific risk prediction, and methods of prevention of fractures in patient living with a kidney transplant.

Combined effect of confinement and dielectric exclusion on ion adsorption in slits, pores, and cavities.

We present simulation results for the Donnan equilibrium between a homogeneous bulk reservoir and inhomogeneous confining geometries with varying number of restricted dimensions, . Planar slits ( = 1), cylindrical pores ( = 2), and spherical cavities ( = 3) are considered. The walls have a negative surface charge density.

Three-dimensional models: from cell culture to Patient-Derived Organoid and its application to future liposarcoma research.

Liposarcoma is one of the most common soft tissue sarcomas, however, its occurrence rate is still rare compared to other cancers. Due to its rarity, experiments are an essential approach to elucidate liposarcoma pathobiology. Conventional cell culture-based research (2D cell culture) is still playing a pivotal role, while several shortcomings have been recently under discussion.

Hsa-miR-214-3p inhibits breast cancer cell growth and improves the tumor immune microenvironment by downregulating B7H3.

Background: Immune checkpoint inhibitors play an important role in the treatment of solid tumors, but the currently used immune checkpoint inhibitors targeting programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte antigen-4 (CTLA-4) show limited clinical efficacy in many breast cancers. B7H3 has been widely reported as an immunosuppressive molecule, but its immunological function in breast cancer patients remains unclear.

Methods: We analyzed the expression of B7H3 in breast cancer samples using data from the Cancer Genome Atlas Program (TCGA) and the Gene Expression Omnibus (GEO) databases.

Moving Past the Status Quo: Redefining the Feedback Landscape for Junior Clinician-Educator Career Development.

This perspective piece addresses the challenges junior clinician-educators face as they navigate career development within academic medical centers. In addition to understanding local promotion and tenure processes and seeking mentorship, we argue that faculty feedback is an often neglected, but essential, component in clinician-educator development. We repurpose and use the MISCA model-Message, Implementation, Student, Context, and Agents-as a framework to better understand and improve feedback for faculty.

Multivariate analysis on the structure-activity parameters for nano CuO-catalyzed reduction reactions.

Understanding the origin of enhanced catalytic activity is critical to heterogeneous catalyst design. This is especially important for non-noble metal-based catalysts, notably metal oxides, which have recently emerged as viable alternatives for numerous thermal catalytic processes. For thermal catalytic reduction/hydrogenation using metal oxide nanoparticles, enhanced catalytic performance is typically attributed to increased surface area and oxygen vacancies.

Chemoenzymatic synthesis with the hyaluronan synthase; production of a multitude of defined authentic, derivatized, and analog polymers.

Hyaluronan (HA; [-3-GlcNAc-1-beta-4-GlcA-1-beta] ), an essential matrix polysaccharide of vertebrates and the molecular camouflage coating in certain pathogens, is polymerized by "HA synthase" (HAS) enzymes. Three HAS classes have been identified with biotechnological utility, but only the Class II PmHAS from Type A has been useful for preparation of very defined HA polymers in vitro. Two general chemoenzymatic strategies with different size products are possible: (1) repetitive step-wise extension reactions by sequential addition of a single monosaccharide from a donor UDP-sugar onto an acceptor (or "primer") comprised of a short glycosaminoglycan chain (e.

Virtual versus in-person didactic modalities: A national survey of emergency medicine residencies.

Background: Following the widespread shift from in-person to virtual delivery of didactics during the COVID-19 pandemic, some emergency medicine (EM) residency programs have retained virtual didactic time while others have returned exclusively to in-person didactics. In this national survey of EM residency programs, we explored the current national distribution of virtual versus in-person didactic time and the circumstances and motivators for use of each.

Methods: A cross-sectional survey with branched logic was designed via Qualtrics.

The State of Radiology Research in Ethiopia: A Scoping Review.

Background: Radiology is an essential component of modern medicine and a rapidly evolving research field. The nature and dynamic of radiology research in Ethiopia remained largely unexplored This bibliometric scoping review was done to explore the current state of radiology research in Ethiopia.

Methods: Literature search was conducted using PubMed, Scopus, Embase, Web of Science, and Google Scholar from inception to June 15, 2024.

Gamma frequency connectivity in frontostriatal networks associated with social preference is reduced with traumatic brain injury.

Among the myriad of complications associated with traumatic brain injury (TBI), impairments in social behaviors and cognition have emerged as a significant area of concern. Animal models of social behavior are necessary to explore the underlying brain mechanisms contributing to chronic social impairments following brain injury. Here, we utilize large-scale brain recordings of local field potentials to identify neural signatures linked with social preference deficits following frontal brain injury.

Comparison of different group-level templates in gradient-based multimodal connectivity analysis.

The study of large-scale brain connectivity is increasingly adopting unsupervised approaches that derive low-dimensional spatial representations from high-dimensional connectomes, referred to as gradient analysis. When translating this approach to study interindividual variations in connectivity, one technical issue pertains to the selection of an appropriate group-level template to which individual gradients are aligned. Here, we compared different group-level template construction strategies using functional and structural connectome data from neurotypical controls and individuals with autism spectrum disorder (ASD) to identify between-group differences.

Patterns of the left thalamus embedding into the connectome associated with reading skills in children with reading disabilities.

We examined how thalamocortical connectivity structure reflects children's reading performance. Diffusion-weighted MRI at 3 T and a series of reading measures were collected from 64 children (33 girls) ages 8-14 years with and without dyslexia. The topological properties of the left and right thalamus were computed based on the whole-brain white matter network and a hub-attached reading network, and were correlated with scores on several tests of children's reading and reading-related abilities.

The impact of functional correlations on task information coding.

State-dependent neural correlations can be understood from a neural coding framework. Noise correlations-trial-to-trial or moment-to-moment covariability-can be interpreted only if the underlying signal correlation-similarity of task selectivity between pairs of neural units-is known. Despite many investigations in local spiking circuits, it remains unclear how this coding framework applies to large-scale brain networks.

Cognitive abilities are associated with rapid dynamics of electrophysiological connectome states.

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, hold significant implications for cognition. However, connectome dynamics at fast (>1 Hz) timescales highly relevant to cognition are poorly understood due to the dominance of inherently slow fMRI in connectome studies. Here, we investigated the behavioral significance of rapid electrophysiological connectome dynamics using source-localized EEG connectomes during resting state ( = 926, 473 females).

Rapid dynamics of electrophysiological connectome states are heritable.

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, are a prominent feature of brain activity with broad functional implications. While infraslow (<0.1 Hz) connectome dynamics have been extensively studied with fMRI, rapid dynamics highly relevant for cognition are poorly understood.

A generative model of the connectome with dynamic axon growth.

Connectome generative models, otherwise known as generative network models, provide insight into the wiring principles underpinning brain network organization. While these models can approximate numerous statistical properties of empirical networks, they typically fail to explicitly characterize an important contributor to brain organization-axonal growth. Emulating the chemoaffinity-guided axonal growth, we provide a novel generative model in which axons dynamically steer the direction of propagation based on distance-dependent chemoattractive forces acting on their growth cones.

Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer's disease.

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer's disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved.

A spatially constrained independent component analysis jointly informed by structural and functional network connectivity.

There are a growing number of neuroimaging studies motivating joint structural and functional brain connectivity. The brain connectivity of different modalities provides an insight into brain functional organization by leveraging complementary information, especially for brain disorders such as schizophrenia. In this paper, we propose a multimodal independent component analysis (ICA) model that utilizes information from both structural and functional brain connectivity guided by spatial maps to estimate intrinsic connectivity networks (ICNs).

CoCoNest: A continuous structural connectivity-based nested family of parcellations of the human cerebral cortex.

Despite the widespread exploration and availability of parcellations for the functional connectome, parcellations designed for the structural connectome are comparatively limited. Current research suggests that there may be no single "correct" parcellation and that the human brain is intrinsically a multiresolution entity. In this work, we propose the Continuous Structural Connectivitity-based, Nested (CoCoNest) family of parcellations-a fully data-driven, multiresolution family of parcellations derived from structural connectome data.

Exploring memory-related network via dorsal hippocampus suppression.

Memory is a complex brain process that requires coordinated activities in a large-scale brain network. However, the relationship between coordinated brain network activities and memory-related behavior is not well understood. In this study, we investigated this issue by suppressing the activity in the dorsal hippocampus (dHP) using chemogenetics and measuring the corresponding changes in brain-wide resting-state functional connectivity (RSFC) and memory behavior in awake rats.

Hemodynamic cortical ripples through cyclicity analysis.

A fine-grained understanding of dynamics in cortical networks is crucial to unpacking brain function. Resting-state functional magnetic resonance imaging (fMRI) gives rise to time series recordings of the activity of different brain regions, which are aperiodic and lack a base frequency. Cyclicity analysis, a novel technique robust under time reparametrizations, is effective in recovering the temporal ordering of such time series, collectively considered components of a multidimensional trajectory.

Contrasting topologies of synchronous and asynchronous functional brain networks.

We generated asynchronous functional networks (aFNs) using a novel method called optimal causation entropy and compared aFN topology with the correlation-based synchronous functional networks (sFNs), which are commonly used in network neuroscience studies. Functional magnetic resonance imaging (fMRI) time series from 212 participants of the National Consortium on Alcohol and Neurodevelopment in Adolescence study were used to generate aFNs and sFNs. As a demonstration of how aFNs and sFNs can be used in tandem, we used multivariate mixed effects models to determine whether age interacted with node efficiency to influence connection probabilities in the two networks.