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Abstract Background American/Black and Latine (AABL) young/emerging adults living with HIV in the United States (US) have consistently failed to meet targets for HIV care/medication engagement. Among this population, those with non-suppressed HIV viral load are understudied, along with immigrants and those with serious socioeconomic deprivation. Guided by social action theory, we took a mixed methods approach (sequential explanatory design) to describe sociodemographic, background, and contextual factors, and their relationships to HIV management, among a diverse cohort. Methods Participants (N = 271) received structured baseline assessments and HIV viral load testing. Primary outcomes were being well-engaged in HIV care and HIV viral suppression. A subset (N = 41) was purposively sampled for maximum variability for in-depth interviews. Quantitative data were analyzed with descriptive statistics and logistic regression, and used to develop a research question about life contexts. Qualitative data were analyzed with directed content analysis, and the joint display method was used to integrate results. Results Participants were 25 years old, on average (SD = 2). The majority (59%) were Latine/Hispanic and the reminder African American/Black. Almost all were assigned male sex at birth (96%) and sexual minorities (93%). Half (49%) were born outside the US and 33% spoke primarily Spanish. They were diagnosed with HIV four years prior on average (SD = 3). Most were well-engaged in HIV care (72%) and evidenced viral suppression (81%). Speaking Spanish was associated with a higher odds of care engagement, and adverse childhood experiences and income from federal benefits were associated with a lower odds. None of the factors predicted viral suppression. Qualitative results highlighted both developmentally typical (insufficient financial resources, unstable housing) and atypical challenges (struggles with large bureaucracies, HIV disclosure, daily medication use). Federal benefits and the local HIV social services administration were critical to survival. Immigrant participants came to the US to escape persecution and receive HIV care, but HIV management was often disrupted. Overall qualitative results highlighted both risk and protective factors, and resilience. Qualitative results added detail, nuance, and richness to the quantitative findings. Conclusions The present study advances what is known about the backgrounds and contexts of diverse and understudied AABL young/emerging adults living with HIV.

In many decision tasks, we have a set of alternative choices and are faced with the problem of how to use our latent beliefs and preferences about each alternative to make a single choice. Cognitive and decision models typically presume that beliefs and preferences are distilled to a scalar latent strength for each alternative, but it is also critical to model how people use these latent strengths to choose a single alternative. Most models follow one of two traditions to establish this link. Modern psychophysics and memory researchers make use of signal detection theory, assuming that latent strengths are perturbed by noise, and the highest resulting signal is selected. By contrast, many modern decision theoretic modeling and machine learning approaches use the softmax function (which is based on Luces choice axiom; Luce, 1959) to give some weight to non-maximal-strength alternatives. Despite the prominence of these two theories of choice, current approaches rarely address the connection between them, and the choice of one or the other appears more motivated by the tradition in the relevant literature than by theoretical or empirical reasons to prefer one theory to the other. The goal of the current work is to revisit this topic by elucidating which of these two models provides a better characterization of latent processes in m -alternative decision tasks, with a particular focus on memory tasks. In a set of visual memory experiments, we show that, within the same experimental design, the softmax parameter β varies across m -alternatives, whereas the parameter d of the signal-detection model is stable. Together, our findings indicate that replacing softmax with signal-detection link models would yield more generalizable predictions across changes in task structure. More ambitiously, the invariance of signal detection model parameters across different tasks suggests that the parametric assumptions of these models may be more than just a mathematical convenience, but reflect something real about human decision-making.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] This manuscript presents a case study of an introductory physics student who, during the remote learning conditions imposed during the COVID-19 pandemic, found inspiration within a new, open-inquiry, project-based, laboratory curriculum designed at Portland State University. The phenomenon investigated by the study subject was intriguing to both the student and the lab instructors for its unfamiliar and instructive optical effect: a ring-shaped pattern or halo created by a laser diffusely reflected in a shallow body of water. Drawing on classwork and interview responses, this study shows that the subject achieved many expected curriculum outcomes, particularly with respect to experimental design and data analysis tasks, indicating that the course's open-inquiry structure can be effective while offering students a free choice of what to investigate in a laboratory class. Additionally, the case study shows that the halo phenomenon is pedagogically rich as it combines refraction, diffuse reflection, and total internal reflection in a nontrivial way, thereby answering calls by physics education researchers for more complex, realistic examples in geometric optics instruction. Finally, this case also highlights challenges students may experience interpreting diffuse reflection and determining the position of optical features beyond image formation, not commonly a focus of introductory physics courses, textbooks, and education research.

Nucleus Pulposus (NP) Replacement is a developing surgical methodology for the treatment of pathology related to degeneration of intervertebral discs (IVDs). This article provides necessary context regarding the pathologies treated with this technology, the biomechanical structure and function of the IVD, and the procedures this technology aims to replace. Primarily, it provides an overview and discussion of commercial and experimental preformed and in situ curing prosthesis designs reported in the scientific literature and summarizes the results of biomechanical and clinical studies evaluating their efficacy. Contextual and updated information on the most recent research into NP replacement with novel hydrogel and tissue engineering (TE) strategies is described. Replacement of the NP allows for potential improvement in the treatment of degenerative spinal pathologies through minimally invasive surgical techniques.

Polyaryletherketones (PAEKs) are a family of durable, multifunctional, thermoplastic biopolymers. This article first provides necessary context and thorough information regarding the mechanical, physical, chemical, crystalline, and shape memory properties of PAEKs as well as critical details regarding manufacturing. Additionally, it provides an update on the clinical and biomedical uses of PAEKs by summarizing the most recent and groundbreaking applications of these thermopolymers. PAEKs have been used clinically in fields including orthopedics, craniofacial and cardiothoracic surgery, as well as cardiovascular and dental medicine. Other applications include tissue engineering, post-surgical antibiotic delivery, antimicrobial applications, anti-cancer drug delivery, and 3D printing. Of importance, PAEKs have comparable mechanical strength and elastic modulus to human bone, which enable PAEKs to serve as a viable alternative to metal-based implants. Given their remarkable properties, and ability to be specifically and rapidly manufactured through 3D printing, PAEKs will continue to be a subject of biomedical research and serve a vital role in medical applications.

Water structure and dynamics can be key modulators of adsorption, separations, and reactions at soft material interfaces, but systematically tuning water environments in an aqueous, accessible, and functionalizable material platform has been elusive. This work leverages variations in excluded volume to control and measure water diffusivity as a function of position within polymeric micelles using Overhauser dynamic nuclear polarization spectroscopy. Specifically, a versatile materials platform consisting of sequence-defined polypeptoids simultaneously offers a route to controlling the functional group position and a unique opportunity to generate a water diffusivity gradient extending away from the polymer micelle core. These results demonstrate an avenue not only to rationally design the chemical and structural properties of polymer surfaces but also to design and tune the local water dynamics that, in turn, can adjust the local activity for solutes.

Background and objectivesPrevious studies suggest that lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer disease (AD) and AD-related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.MethodsWe included dementia-free participants from 9 diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5-20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (

Alzheimer's disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals-16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.

Polyethylene terephthalate glycol, PETG, is a miscible, transparent thermoplastic known to have strong tensile properties, high ductility, as well as resistance to heat and chemical insults. PETG may be manufactured in several ways, most notably 3D printing modalities. As such, PETG has emerged as a viable biomaterial for a variety of medical applications such as tissue engineering, dentistry, optometry, vascular health, cardiology, orthopedics, neurology, gynecology, and surgery. PETG also serves a valuable role in biomedical research and engineering by offering improvements in cell studies, drug carriers, and anti-bacterial measures. Further medical research and innovation utilizing PETG will better characterize its value as an inexpensive and versatile biomaterial.

Abstract Bioengineering and drug delivery technologies play an important role in bridging the gap between basic scientific discovery and clinical application of therapeutics. To identify the optimal treatment, the most critical stage is to diagnose the problem. Often these two may occur simultaneously or in parallel, but in this review, we focus on bottom‐up approaches in understanding basic immunologic phenomena to develop targeted therapeutics. This can be observed in several fields; here, we will focus on one of the original immunotherapy targets—cancer—and one of the more recent targets—regenerative medicine. By understanding how our immune system responds in processes such as malignancies, wound healing, and medical device implantation, we can isolate therapeutic targets for pharmacologic and bioengineered interventions.

The human placenta is a multifunctional, disc-shaped temporary fetal organ that develops in the uterus during pregnancy, connecting the mother and the fetus. The availability of large-scale datasets on the gene expression of placental cell types and scholarly articles documenting adverse pregnancy outcomes from maternal infection warrants the use of computational resources to aid in knowledge generation from disparate data sources. Using maternal Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection as a case study in microbial infection, we constructed integrated datasets and implemented visual analytics resources to facilitate robust investigations of placental gene expression data in the dimensions of flow, curation, and analytics. The visual analytics resources and associated datasets can support a greater understanding of SARS-CoV-2-induced changes to the human placental expression levels of 18,882 protein-coding genes and at least 1233 human gene groups/families. We focus this report on the human aquaporin gene family that encodes small integral membrane proteins initially studied for their roles in water transport across cell membranes. Aquaporin-9 (AQP9) was the only aquaporin downregulated in term placental villi from SARS-CoV-2-positive mothers. Previous studies have found that (1) oxygen signaling modulates placental development; (2) oxygen tension could modulate AQP9 expression in the human placenta; and (3) SARS-CoV-2 can disrupt the formation of oxygen-carrying red blood cells in the placenta. Thus, future research could be performed on microbial infection-induced changes to (1) the placental hematopoietic stem and progenitor cells; and (2) placental expression of human aquaporin genes, especially AQP9.

Circulating total-tau levels can be used as an endophenotype to identify genetic risk factors for tauopathies and related neurological disorders. Here, we confirmed and better characterized the association of the 17q21 MAPT locus with circulating total-tau in 14,721 European participants and identified three novel loci in 953 African American participants (4q31, 5p13, and 6q25) at P

Recent network-based approaches leverage graph theoretic analyses to study individual differences in semantic networks and how they relate to other cognitive processes. However, it remains ambiguous whether individual differences captured via semantic network analyses reflect true differences in latent knowledge representations, or strategic differences in how people approach semantic relatedness tasks. To determine the robustness of content- and structure- based metrics of individual semantic networks we test their reliability across different tasks. We find both weighted and unweighted graph theoretic representations can predict individual differences in connections between semantic units across tasks. Furthermore, node centrality, a content-based metric which captures relative ‘importance’ of units within a network, is reliable across tasks, but metrics of structural properties of semantic networks, i.e. average clustering coefficient and shortest path length, are less robust. These results highlight the importance of validating graph-theoretic measures in the study of individual differences in semantic memory.

Dual phase xenon detectors are widely used in experimental searches for galactic dark matter particles. The origin of single electron backgrounds following prompt scintillation and proportional scintillation signals in these detectors is not fully understood, although there has been progress in recent years. In this paper, we describe single electron backgrounds in 83mKr calibration events and their correlation with drift and extraction fields, using the Particle Identification in Xenon at Yale (PIXeY) dual-phase xenon time projection chamber. The single electron background induced by the Fowler-Nordheim (FN) effect is measured, and its electric field dependence is quantified. The photoionization of grids and impurities by prompt scintillation and proportional scintillation also contributes to the single electron background.

Abstract Background SARS-CoV-2, the agent responsible for the COVID-19 pandemic, enters cells through viral spike glycoprotein binding to the cellular receptor, angiotensin-converting enzyme 2 (ACE2). Given the lack of effective antivirals targeting SARS-CoV-2, we previously utilized systematic evolution of ligands by exponential enrichment (SELEX) and selected fluoro-arabino nucleic acid (FANA) aptamer R8-9 that was able to block the interaction between the viral receptor-binding domain and ACE2. Methods Here, we further assessed FANA-R8-9 as an entry inhibitor in contexts that recapitulate infection in vivo. Results We demonstrate that FANA-R8-9 inhibits spike-bearing pseudovirus particle uptake in cell lines. Then, using an in-vitro model of human airway epithelium (HAE) and SARS-CoV-2 virus, we show that FANA-R8-9 significantly reduces viral infection when added either at the time of inoculation, or several hours later. These results were specific to the R8-9 sequence, not the xeno-nucleic acid utilized to make the aptamer. Importantly, we also show that FANA-R8-9 is stable in HAE culture secretions and has no overt cytotoxic effects. Conclusions Together, these results suggest that FANA-R8-9 effectively prevents infection by specific SARS-CoV-2 variants and indicate that aptamer technology could be utilized to target other clinically-relevant viruses in the respiratory mucosa.

Abstract Due to the limited capacity of mammals to regenerate complex tissues, researchers have worked to understand the mechanisms of tissue regeneration in organisms that maintain that capacity. One example is the MRL/MpJ mouse strain with unique regenerative capacity in ear pinnae that is absent from other strains, such as the common C57BL/6 strain. The MRL/MpJ mouse has also been associated with an autoimmune phenotype even in the absence of the mutant Fas gene described in its parent strain MRL/lpr. Due to these findings, the differences between the responses of MRL/MpJ versus C57BL/6 strain are evaluated in volumetric muscle injury and subsequent material implantation. One salient feature of the MRL/MpJ response to injury is robust adipogenesis within the muscle. This is associated with a decrease in M2‐like polarization in response to biologically derived extracellular matrix scaffolds. In pro‐fibrotic materials, such as polyethylene, there are fewer foreign body giant cells in the MRL/MpJ mice. As there are reports of both positive and negative influences of adipose tissue and adipogenesis on wound healing, this model can provide an important lens to investigate the interplay between stem cells, adipose tissue, and immune responses in trauma and material implantation.