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Remdesivir (RDV, GS-5734) is currently the only FDA-approved antiviral drug for the treatment of SARS CoV-2 infection. The drug is approved for use in adults or children 12-years or older who are hospitalized for the treatment of COVID-19 on the basis of an acceleration of clinical recovery for inpatients with this disease. Unfortunately, the drug must be administered intravenously, restricting its use to those requiring hospitalization for relatively advanced disease. RDV is also unstable in plasma and has a complex activation pathway which may contribute to its highly variable antiviral efficacy in SARS-CoV-2 infected cells. Potent orally bioavailable antiviral drugs for early treatment of SARS-CoV-2 infection are urgently needed and several including molnupiravir and PF-07321332 are currently in clinical development. We focused on making simple, orally bioavailable lipid analogs of Remdesivir nucleoside (RVn, GS-441524) that are processed to RVn-monophosphate, the precursor of the active RVn-triphosphate, by a single-step intracellular cleavage. In addition to high oral bioavailability, stability in plasma and simpler metabolic activation, new oral lipid prodrugs of RVn had submicromolar anti-SARS-CoV-2 activity in a variety of cell types including Vero E6, Calu-3, Caco-2, human pluripotent stem cell (PSC)-derived lung cells and Huh7.5 cells. In Syrian hamsters oral treatment with ODBG-P-RVn was well tolerated and achieved therapeutic levels in plasma above the EC90 for SARS-CoV-2. The results suggest further evaluation as an early oral treatment for SARS-CoV-2 infection to minimize severe disease and reduce hospitalizations.

Several recent studies have employed item response theory (IRT) to rank incorrect responses to commonly used research-based multiple-choice assessments. These studies use Bock's nominal response model (NRM) for applying IRT to categorical (nondichotomous) data, but the response rankings only utilize half of the parameters estimated by the model. We present a mathematical argument for why this practice of using half of the NRM parameters when ranking responses is appropriate based on the primary question of multiple-choice tests: How can we use students' responses to test items to estimate their overall knowledge levels? We provide additional motivation for this practice by recognizing the similarities between Bock's NRM and the probability function of the canonical ensemble with degenerate energy states. As physicists often do, we exploit these mathematical similarities to gain new insights into the meaning of the IRT parameters and a richer understanding of the relationship between these parameters and student knowledge.

For this year's career issue, LCGC North America teamed up with the American Chemical Society Subdivision on Chromatography and Separations Chemistry to ask the analytical chemistry community what skills new employees in the field need to succeed. In this report, we analyze the survey results and explore how they can inform the future of analytical chemistry curriculum development., For the past six decades, and likely even longer, analytical chemists have debated the question of what should be taught in analytical chemistry courses (1). Many inherently believe that the [...]

BACKGROUNDAn increase in intrahepatic triglyceride (IHTG) is the hallmark feature of nonalcoholic fatty liver disease (NAFLD) and is decreased by weight loss. Hepatic de novo lipogenesis (DNL) contributes to steatosis in individuals with NAFLD. The physiological factors that stimulate hepatic DNL and the effect of weight loss on hepatic DNL are not clear.METHODSHepatic DNL, 24-hour integrated plasma insulin and glucose concentrations, and both liver and whole-body insulin sensitivity were determined in individuals who were lean (n = 14), obese with normal IHTG content (n = 26), or obese with NAFLD (n = 27). Hepatic DNL was assessed using the deuterated water method corrected for the potential confounding contribution of adipose tissue DNL. Liver and whole-body insulin sensitivity was assessed using the hyperinsulinemic-euglycemic clamp procedure in conjunction with glucose tracer infusion. Six subjects in the obese-NAFLD group were also evaluated before and after a diet-induced weight loss of 10%.RESULTSThe contribution of hepatic DNL to IHTG-palmitate was 11%, 19%, and 38% in the lean, obese, and obese-NAFLD groups, respectively. Hepatic DNL was inversely correlated with hepatic and whole-body insulin sensitivity, but directly correlated with 24-hour plasma glucose and insulin concentrations. Weight loss decreased IHTG content, in conjunction with a decrease in hepatic DNL and 24-hour plasma glucose and insulin concentrations.CONCLUSIONSThese data suggest hepatic DNL is an important regulator of IHTG content and that increases in circulating glucose and insulin stimulate hepatic DNL in individuals with NAFLD. Weight loss decreased IHTG content, at least in part, by decreasing hepatic DNL.TRIAL REGISTRATIONClinicalTrials.gov NCT02706262.FUNDINGThis study was supported by NIH grants DK56341 (Nutrition Obesity Research Center), DK20579 (Diabetes Research Center), DK52574 (Digestive Disease Research Center), and RR024992 (Clinical and Translational Science Award), and by grants from the Academy of Nutrition and Dietetics Foundation, the College of Natural Resources of UCB, and the Pershing Square Foundation.

We demonstrate an axisymmetric inverse-designed metalens to improve the performance of zone-plate-array lithography (ZPAL), one of the maskless lithography approaches, that offer a new paradigm for nanoscale research and industry. First, we derive a computational upper bound for a unit-cell-based axisymmetric metalens. Then, we demonstrate a fabrication-compatible inverse-designed metalens with 85.50% transmission normalized focusing efficiency at 0.6 numerical aperture at 405 nm wavelength; a higher efficiency than a theoretical gradient index lens design (79.98%). We also demonstrate experimental validation for our axisymmetric inverse-designed metalens via electron beam lithography. Metalens-based maskless lithography may open a new way of achieving low-cost, large-area nanofabrication.

This essay proposes that efforts at assessing the contribution of faith-based schools to faith formation be grounded in an account of student vocation framed by Christian practices. We identify gaps in research on assessment of school effectiveness and suggest that a focus on the present vocation of students may fruitfully connect faith and school-based learning practices. On this basis, we describe a framework for viewing assessment through a practices lens by identifying Christian practices that orient learning practices. We also briefly introduce the Practicing Faith Survey, a new tool based on this approach.

Decreased adipose tissue oxygen tension and increased HIF-1α expression can trigger adipose tissue inflammation and dysfunction in obesity. Our current understanding of obesity-associated decreased adipose tissue oxygen tension is mainly focused on changes in oxygen supply and angiogenesis. Here, we demonstrate that increased adipocyte O2 demand, mediated by ANT2 activity, is the dominant cause of adipocyte hypoxia. Deletion of adipocyte Ant2 improves obesity-induced intracellular adipocyte hypoxia by decreasing obesity-induced adipocyte oxygen demand, without effects on mitochondrial number or mass, or oligomycin-sensitive respiration. This led to decreased adipose tissue HIF-1α expression and inflammation with improved glucose tolerance and insulin resistance in both a preventative or therapeutic setting. Our results suggest that ANT2 may be a target for the development of insulin sensitizing drugs and that ANT2 inhibition might have clinical utility.

One desired outcome of introductory physics instruction is that students will develop facility with reasoning quantitatively about physical phenomena. Little research has been done regarding how students develop the algebraic concepts and skills involved in reasoning productively about physics quantities, which is different from either understanding of physics concepts or problem-solving abilities. We introduce the Physics Inventory of Quantitative Literacy (PIQL) as a tool for measuring "Quantitative Literacy," a foundation of mathematical reasoning, in the context of introductory physics. We present the development of the PIQL and evidence of its validity for use in calculus-based introductory physics courses. Unlike "concept" inventories, the PIQL is a "reasoning" inventory, and can be used to assess reasoning over the span of students' instruction in introductory physics. Although mathematical reasoning associated with the PIQL is taught in prior mathematics courses, pretest and post-test scores reveal that this reasoning is not readily used by most students in physics, nor does it develop as part of physics instruction--even in courses that use high-quality, research-based curricular materials. As has been the case with many inventories in physics education, we expect use of the PIQL to support the development of instructional strategies and materials--in this case, designed to meet the course objective that all students become quantitatively literate in introductory physics.

This piece captures a mutual growth experience between David Smith and a student in his graduate class, Joyce Azaki. They share the transformative interaction both parties can experience as lecturer and student when teaching and learning is positioned as an opportunity for hospitality. This powerful story of faith-shaping practice calls educators to pause, reflect, and consider the shifts they can make in practice, allowing others to flourish. [ABSTRACT FROM AUTHOR]

Poor maternal nutrition during gestation negatively affects offspring growth and metabolism. To evaluate the impact of maternal nutrient restriction and realimentation on metabolism in the fetal liver, skeletal muscle, and circulation, on day 50 of gestation, ewes (n = 48) pregnant with singletons were fed 100% (CON) or 60% (RES) of requirements until day 90 of gestation, when a subset of ewes (n = 7/treatment) were euthanized, and fetal samples were collected. The remaining ewes were maintained on a current diet (CON-CON, n = 6; RES-RES, n = 7) or switched to an alternative diet (CON-RES, RES-CON; n = 7/treatment). On day 130 of gestation, the remaining ewes were euthanized, and fetal samples were collected. Fetal liver, longissimus dorsi (LD), and blood metabolites were analyzed using LC-MS/MS, and pathway enrichment analysis was conducted using MetaboAnalyst. Then, 600, 518, and 524 metabolites were identified in the liver, LD, and blood, respectively, including 345 metabolites that were present in all three. Nutrient restriction was associated with changes in amino acid, carbohydrate, lipid, and transulfuration/methionine metabolic pathways, some of which were alleviated by realimentation. Fetal age also affected metabolite abundance. The differential abundance of metabolites involved in amino acid, methionine, betaine, and bile acid metabolism could impact fetal epigenetic regulation, protein synthesis, lipid metabolism, and signaling associated with glucose and lipid metabolism. [ABSTRACT FROM AUTHOR]

Identifying students at risk of failing a course has potential benefits, such as recommending the At-Risk students to various interventions that could improve pass rates. The challenges however, are firstly in measuring how effective these interventions are, i.e. measuring treatment effects, and secondly, to not only predict overall (average) treatment effects, but also individual treatment effects. Previous work has used machine learning (ML) to estimate treatment effects by training models on treatment and control groups and using these models to predict counterfactuals. This is called the machine learning for predicting treatment effects, or MLTE method, in this study. This paper extends this previous work by (1) being the first to compare, or validate, the MLTE method, with the traditional propensity score matching (PSM) method; (2) using the MLTE method to compute not only global, but also subgroup and individual (heterogeneous) treatment effects and (3) by developing a method that combines the MLTE method with methods such as SHAP (SH apley A dditive exP lanations), to predict final grades, predict individual treatment effects and characterize individual students. This is a comparative study between control and experimental groups, using observational data from a first year engineering mechanics course. Students could self-select to attend extra weekly tutorials (called the intervention), resulting in treatment and control groups. The aim was to measure the treatment effects of the intervention by comparing the difference in outcomes between treated and control groups. One of the main results was to develop a method for not only predicting final grades for subgroups and individuals, but also predicting treatment effects. This is valuable for predicting how a student/subgroup would perform and whether the intervention would benefit them. It allows for determining which types of students (or subgroups) would benefit from the intervention. This method shows the most promise for catering to individual students by not only predicting individual students' final grades (mean absolute errors of between 6% and 8% were computed), but also predicting by how much the intervention would benefit the student (individual treatment effect, ITE) and by characterizing these students using SHAP. In terms of the ML models used, tree-based models performed the best in predictions. The method developed in this study therefore promises much for using ML to help individual students pass a course by identifying individuals that will receive the most benefit from the intervention.

The use of open-source materials is growing in popularity throughout higher education. This Communication investigates the impact on student performance in a second-year undergraduate analytical chemistry course when an open-source textbook is assigned. For two separate semesters, approximately 80 students were enrolled in such a course across five sections. Both student populations had no statistically significant difference across a variety of demographic comparisons, and both achieved a nearly identical average score on the ACS Analytical Chemistry exam provided as the final cumulative test in both semesters. Thus, no detrimental effect was observed when transitioning a course to an open-source textbook, while providing the advantage of utilizing a more affordable option for students amid the overall rising cost of higher education.

Using a qualitative analysis of school artifacts, this article analyzes the documentary record of one Christian school system's experience with technological change. It focuses on documentary evidence for how the concept of Christian discernment was deployed to situate new technologies within a Christian discourse. The idea of discernment shifted in emphasis as new technologies were implemented. The theologically rooted concept of discernment both shaped and was shaped by the ongoing effort to manage technological change. Examining this evolution offers an empirical contribution to discussions of how Christian schools can sustain an integrity of fit between faith and practice.

The "Vision and Change" report called for the biology community to mobilize around teaching the core concepts of biology. This essay describes a collection of resources developed by several different groups that can be used to respond to the report's call to transform undergraduate education at both the individual course and departmental levels. First, we present two frameworks that help articulate the "Vision and Change" core concepts, the "BioCore Guide" and the Conceptual Elements (CE) Framework, which can be used in mapping the core concepts onto existing curricula and designing new curricula that teach the biology core concepts. Second, we describe how the "BioCore Guide" and the CE Framework can be used alongside the Partnership for Undergraduate Life Sciences Education curricular rubric as a way for departments to self-assess their teaching of the core concepts. Finally, we highlight three sets of instruments that can be used to directly assess student learning of the core concepts: the Biology Card Sorting Task, the Biology Core Concept Instruments, and the Biology-Measuring Achievement and Progression in Science instruments. Approaches to using these resources independently and synergistically are discussed.

Mathematical reasoning skills are a desired outcome of many introductory physics courses, particularly calculus-based physics courses. Novices can struggle to understand the many roles signed numbers play in physics contexts, and recent evidence shows that unresolved struggle can carry over to subsequent physics courses. Positive and negative quantities are ubiquitous in physics, and the sign carries important and varied meanings. The mathematics education research literature documents the cognitive challenge of conceptualizing negative numbers as mathematical objects--both for experts, historically, and for novices as they learn. We contribute to the small but growing body of research in physics contexts that examines student reasoning about signed quantities and reasoning about the use and interpretation of signs in mathematical models. In this paper we present a framework for categorizing various meanings and interpretations of the negative sign in physics contexts, inspired by established work in algebraic contexts from the mathematics education research community. Such a framework can support innovation that can catalyze deeper mathematical conceptualizations of signed quantities in the introductory courses and beyond.

Research-based assessment instruments (RBAIs) are ubiquitous throughout both physics instruction and physics education research. The vast majority of analyses involving student responses to RBAI questions have focused on whether or not a student selects correct answers and using correctness to measure growth. This approach often undervalues the rich information that may be obtained by examining students' particular choices of incorrect answers. In the present study, we aim to reveal some of this valuable information by quantitatively determining the relative correctness of various incorrect responses. To accomplish this, we propose an assumption that allows us to define relative correctness: students who have a high understanding of Newtonian physics are likely to answer more questions correctly and also more likely to choose better incorrect responses than students who have a low understanding. Analyses using item response theory align with this assumption, and Bock's nominal response model allows us to uniquely rank each incorrect response. We present results from over 7000 students' responses to the Force and Motion Conceptual Evaluation.