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In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22-1.2 μm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.

For most graduate writers, acclimating to doctoral-level inquiry is fraught with numerous tensions, whether regarding the development of scholarly identity (Gardner et al., 2014), navigating graduate school's newly decentralized sources for support (Simpson, 2012), or mastering the writing and research conventions that govern disciplinary practice. Using a Cultural Historical Activity Theory (CHAT) framework, this case study analyzes the first-term experiences of Miranda, a first-year PhD student from the field of gerontology (who is also a co-author), and the tensions she feels around the drafting and revision of a single paper. Drawing from Engeström (1987), we theorize Miranda's challenges around motive, authority, and expert feedback as comprising three "contradictions" engendered by the contemporary activity system of doctoral-level learning-to-write, contradictions that at once challenge the writer's going presumptions about writing even while they enable new concepts and solutions to emerge. This analysis finally encourages researchers to take a wide, cultural-historical view of the many contexts in which doctoral students write during their first terms, including the instructor-led classroom, the larger culture of the program and institution, and the current high-pressure realities of doctoral-level academic study in the United States.

Abstract Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (encoded by IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKε. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a regulatory pathway involving rs2297550, Ikaros, and IKKε implicated by human genetics in risk for SLE.

Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of Asian-Ancestry (AsA) disproportionately experience more severe SLE compared to individuals of European-Ancestry (EA), including increased renal involvement and tissue damage. However, the mechanisms underlying elevated severity in the AsA population remain unclear. Here, we utilized available gene expression data and genotype data based on all non-HLA SNP associations in EA and AsA SLE patients detected using the Immunochip genotyping array. We identified 2778 ancestry-specific and 327 trans-ancestry SLE-risk polymorphisms. Genetic associations were examined using connectivity mapping and gene signatures based on predicted biological pathways and were used to interrogate gene expression datasets. SLE-associated pathways in AsA patients included elevated oxidative stress, altered metabolism and mitochondrial dysfunction, whereas SLE-associated pathways in EA patients included a robust interferon response (type I and II) related to enhanced cytosolic nucleic acid sensing and signaling. An independent dataset derived from summary genome-wide association data in an AsA cohort was interrogated and identified similar molecular pathways. Finally, gene expression data from AsA SLE patients corroborated the molecular pathways predicted by SNP associations. Identifying ancestry-related molecular pathways predicted by genetic SLE risk may help to disentangle the population differences in clinical severity that impact AsA and EA individuals with SLE.

In the age of computing, there still exist many schools that do not offer computer science courses. The reason can be esoteric to designers of interventions, curricula, and policies. This study aims to answer the research question: "What do school officials perceive as barriers to and supports for offering computer science courses at their school?" This article provides a case study of four public high schools in the state of Georgia to better understand the barriers to adopting computer science. Interviews conducted with school principals, counselors, and teachers were thematically analyzed to study each case. The pattern that emerged from these themes is framed by structuration theory, wherein the structures (school policies, resources, and courses) influence the agents (teachers, students, the community), and in turn, the agents influence the structures. This framing provides insights into what attributes can be supports for or barriers against schools offering computer science courses.

Microglia are central to pathogenesis in many neurological conditions. Drugs targeting colony-stimulating factor-1 receptor (CSF1R) to block microglial proliferation in preclinical disease models have shown mixed outcomes, thus the therapeutic potential of this approach remains unclear. Here, we show that CSF1R inhibitors given by multiple dosing paradigms in the Tg2541 tauopathy mouse model cause a sex-independent reduction in pathogenic tau and reversion of non-microglial gene expression patterns toward a normal wild type signature. Despite greater drug exposure in male mice, only female mice have functional rescue and extended survival. A dose-dependent upregulation of immediate early genes and neurotransmitter dysregulation are observed in the brains of male mice only, indicating that excitotoxicity may preclude functional benefits. Drug-resilient microglia in male mice exhibit morphological and gene expression patterns consistent with increased neuroinflammatory signaling, suggesting a mechanistic basis for sex-specific excitotoxicity. Complete microglial ablation is neither required nor desirable for neuroprotection and therapeutics targeting microglia must consider sex-dependent effects.

Emotional support animals are increasingly common in residence halls. This study examines the benefits and challenges of having an Emotional Support Animal (ESA) while living in campus housing, from the perspective of the animals' owners and their roommates. Using a mixed methods case study approach, we collected qualitative and quantitative data via an online survey and in-person focus groups. The following themes emerged as benefits of emotional support animals, as identified by participants: improved or maintained mental health, motivation to take care of oneself, and increased social interactions. Challenges included having to disclose one's mental health diagnosis, needing to educate others about their emotional support animal, sharing it with others, ESA-related expenses, availability of pet supplies, barriers to respite care, transportation and parking difficulties, potential pet loss, and the difficulty of obtaining a letter from a health professional as part of the application process to have an ESA on campus. Despite these challenges, participants reported that the mental, social, and physical health benefits of having an emotional support animal far outweighed the challenges and helped them function personally and academically. [Discussion questions developed by Laura Glasgow.]

Background and Context: Computational thinking (CT) is a critical part of computing education in middle school. The existing practices of collaboration and collaborative design activities at this education level pairs well with CT practices, but this interaction has previously been under-explored in the existing literature. Objective: In this study, we investigate whether students can learn CT through collaborative design activities and what patterns emerge over time and across instructional phases. Method: We coded 6.3 hours of video observations for CT practices to create visualizations of 10-second segments of middle school students programming together. We use these visualizations to unpack nuances regarding how students demonstrate CT practices. Additionally, we provide three vignettes to highlight the interactions between students within and across the three instructional phases. Findings: The findings suggest that middle school students can learn CT concepts and practices through collaborative design activities. The results demonstrate the patterns of CT practices and detail the transitions between each CT practice over time within a small group. Implications: This study applies novel analysis techniques on student interaction data to examine CT through collaborative design. By bridging a CT framework with collaborative design activities, this study enhances the understanding of CT in collaborating, learning, and creating computing project-based designs.

Educators across disciplines are implementing lessons and activities that integrate computing concepts into their curriculum to broaden participation in computing. Out of myriad important introductory computing skills, it is unknown which--and to what extent--these concepts are included in these integrated experiences, especially when compared to concepts commonly taught in introductory computer science courses. Thus, it is unclear how integrated computing activities serve the goal of broadening participation in computing. To address this deficit, we compiled a database of 81 integrated computing activities, constructed a framework of fundamental programming concepts, and scored each activity in the database for the presence of each concept. We also analyzed frequency and patterns of scores across different activity features, including discipline, programming language, student age, and duration of activity. Analysis showed that concepts which appear most frequently in integration activities largely did not align with concepts taught most frequently in introductory programming courses. We argue that our findings can inform the way teacher educators frame integrated computing activities for their students as well as the decisions they make when determining the types of computing integration activities they introduce to their students. We also discuss implications for treating integration activities as prior knowledge in introductory programming courses.

This paper describes the development and implementation of a yearlong integrated English Language Arts (ELA) and computational thinking (CT) curriculum that has been adapted to meet the needs of multilingual students. The integration of computational thinking into K-12 literacy instruction has only been examined in a handful of studies, and little is known about how such integration supports the development of CT for multilingual students. We conducted a qualitative case study on curricular implementation in a general education classroom with large numbers of students designated as English learners. Results from detailed field notes revealed that the strategic application of instructional practices was implemented in the service of building on students' existing literacy skills to teach CT concepts and dispositions. The CT and literacy framework put forth in this study can be used as an analytic framework to highlight how instructional strategies mobilize the existing literacy and CT resources of linguistically diverse students. Based on our findings, we discuss recommendations for future integrated ELA-CT curricula.

PurposeQuantitative in vivo [18F]-(2S,4R)4-fluoroglutamine ([18F]4-FGln or more simply [18F]FGln) metabolic kinetic parameters are compared with activity levels of glutamine metabolism in different types of hepatocellular carcinoma (HCC).MethodsFor this study, we used two transgenic mouse models of HCC induced by protooncogenes, MYC, and MET. Biochemical data have shown that tumors induced by MYC have increased levels of glutamine metabolism compared to those induced by MET. One-hour dynamic [18F]FGln PET data were acquired and reconstructed for fasted MYC mice (n = 11 tumors from 7 animals), fasted MET mice (n = 8 tumors from 6 animals), fasted FVBN controls (n = 8 normal liver regions from 6 animals), nonfasted MYC mice (n = 16 tumors from 6 animals), and nonfasted FVBN controls (n = 8 normal liver regions from 3 animals). The influx rate constants (K 1) using the one-tissue compartment model were derived for each tumor with the left ventricular blood pool input function.ResultsInflux rate constants were significantly higher for MYC tumors (K 1 = 0.374 ± 0.133) than for MET tumors (K 1 = 0.141 ± 0.058) under fasting conditions (P = 0.0002). Rate constants were also significantly lower for MET tumors (K 1 = 0.141 ± 0.135) than normal livers (K 1 = 0.332 ± 0.179) under fasting conditions (P = 0.0123). Fasting conditions tested for MYC tumors and normal livers did not result in any significant difference with P values > 0.005.ConclusionHigher influx rate constants corresponded to elevated levels of glutamine metabolism as determined by biochemical assays. The data showed that there is a distinctive difference in glutamine metabolism between MYC and MET tumors. Our study has demonstrated the potential of [18F]FGln PET imaging as a tool to assess glutamine metabolism in HCC tumors in vivo with a caution that it may not be able to clearly distinguish HCC tumors from normal liver tissue.

We present a technique for measuring the interactions between pairs of colloidal particles in two optical traps. This method is particularly suitable for measuring strongly attractive potentials, an otherwise challenging task. The interaction energy is calculated from the distribution of inter-particle separations by accounting for the contribution from the optical traps with arbitrary trap profiles. The method is simple to implement and applicable to different types of pair potentials and optical trapping geometries. We apply the method to measure dipolar pair interactions in experiments with paramagnetic colloids in external magnetic fields. We obtain consistent and accurate results in all regimes, from strongly attractive to repulsive potentials. By means of computer simulations, we demonstrate that the proposed method can be successfully applied to systems with complex pair interactions characterized by multiple attractive and repulsive regimes, which are ubiquitous in soft and biological matter. [ABSTRACT FROM AUTHOR]

Coastal observations along the Texas coast are valuable for many stakeholders in diverse domains. However, the management of the collected data has been limited, creating gaps in hydrological and atmospheric datasets. Among these, water and air temperature measurements are particularly crucial for water temperature predictions, especially during freeze events. These events can pose a serious threat to endangered sea turtles and economically valuable fish, which can succumb to hypothermic stunning, making them vulnerable to cold-related illness or death. Reliable and complete water and air temperature measurements are needed to provide accurate predictions of when cold-stunning events occur. To address these concerns, the focus of this paper is to describe the method used to create a complete 10-year dataset that is representative of the upper Laguna Madre, TX using multiple stations and various gap-filling methods. The raw datasets consist of a decade's worth of air and water temperature measurements within the Upper Laguna Madre from 2012 to 2022 extracted from the archives of the Texas Coastal Ocean Observation Network and the National Park Service. Large portions of data from the multiple stations were missing from the raw datasets, therefore a systematic gap-filling approach was designed and applied to create a near-continuous dataset. The proposed imputation method consists of three steps, starting with a short gap interpolation method, followed by a long gap-filling process using nearby stations, and finalized by a second short gap interpolation method. This systematic data imputation approach was evaluated by creating random artificial gaps within the original datasets, filling them using the proposed data imputation method, and assessing the viability of the proposed methods using various performance metrics. The evaluation results help to ensure the reliability of the newly imputed dataset and the effectiveness of the data imputation method. The newly created dataset is a valuable resource that transcends the local cold-stunning issue, offering viable utility for analyzing temporal variability of air and water temperatures, exploring temperature interdependencies, reducing forecasting uncertainties, and refining natural resource and weather advisory decision-making processes. The cleaned dataset with minimal gaps (