The spherical encompassing final chamber of the planktonic foraminifera Orbulina universa is a prime example of a complex character whose evolution has been documented by a sequence of intermediate forms. However, the mechanism that induced evolution of the spherical chamber remain unclear. Here we show that shortly after the emergence of Orbulina, documented throughout the oceans, a convergent evolutionary transition occurred in the semi-isolated Paratethys, leading to the emergence of the endemic Velapertina, which occupied a similar niche to Orbulina in the surface waters. Using X-ray computed tomography scanning, we show that the evolution of the encompassing final chamber involved the same sequence of steps in both lineages, combining a progressively spherical shell shape with changes in the position, number, and sizes of apertures. The similarity in the sequence of character acquisitions suggests structural determinism in the way foraminiferal shells are constructed and the presence of natural selection favoring a spherical morphology. Collectively, the emergence of spherical chambers in the two lineages at a similar time suggests that the evolution of this spectacular complex character occurred in response to a singular environmental driver.

We study large sample properties of likelihood ratio tests of the unit-root hypothesis in an autoregressive model of arbitrary order. Earlier research on this testing problem has developed likelihood ratio tests in the autoregressive model of order 1, but resorted to a plug-in approach when dealing with higher-order models. In contrast, we consider the full model and derive the relevant large sample properties of likelihood ratio tests under a local-to-unity asymptotic framework. As in the simpler model, we show that the full likelihood ratio tests are nearly efficient, in the sense that their asymptotic local power functions are virtually indistinguishable from the Gaussian power envelopes. Extensions to sieve-type approximations and different classes of alternatives are also considered.

The 2022 update of the Canadian Stroke Best Practice Recommendations (CSBPR) for Acute Stroke Management, 7th edition, is a comprehensive summary of current evidence-based recommendations, appropriate for use by an interdisciplinary team of healthcare providers and system planners caring for persons with an acute stroke or transient ischemic attack. These recommendations are a timely opportunity to reassess current processes to ensure efficient access to acute stroke diagnostics, treatments, and management strategies, proven to reduce mortality and morbidity. The topics covered include prehospital care, emergency department care, intravenous thrombolysis and endovascular thrombectomy (EVT), prevention and management of inhospital complications, vascular risk factor reduction, early rehabilitation, and end-of-life care. These recommendations pertain primarily to an acute ischemic vascular event. Notable changes in the 7th edition include recommendations pertaining the use of tenecteplase, thrombolysis as a bridging therapy prior to mechanical thrombectomy, dual antiplatelet therapy for stroke prevention, 1 the management of symptomatic intracerebral hemorrhage following thrombolysis, acute stroke imaging, care of patients undergoing EVT, medical assistance in dying, and virtual stroke care. An explicit effort was made to address sex and gender differences wherever possible. The theme of the 7th edition of the CSBPR is building connections to optimize individual outcomes, recognizing that many people who present with acute stroke often also have multiple comorbid conditions, are medically more complex, and require a coordinated interdisciplinary approach for optimal recovery. Additional materials to support timely implementation and quality monitoring of these recommendations are available at www.strokebestpractices.ca.

For a pseudo-Anosov flow $\varphi $ without perfect fits on a closed $3$-manifold, Agol–Guéritaud produce a veering triangulation $\tau $ on the manifold M obtained by deleting the singular orbits of $\varphi $. We show that $\tau $ can be realized in M so that its 2-skeleton is positively transverse to $\varphi $, and that the combinatorially defined flow graph $\Phi $ embedded in M uniformly codes the orbits of $\varphi $ in a precise sense. Together with these facts, we use a modified version of the veering polynomial, previously introduced by the authors, to compute the growth rates of the closed orbits of $\varphi $ after cutting M along certain transverse surfaces, thereby generalizing the work of McMullen in the fibered setting. These results are new even in the case where the transverse surface represents a class in the boundary of a fibered cone of M. Our work can be used to study the flow $\varphi $ on the original closed manifold. Applications include counting growth rates of closed orbits after cutting along closed transverse surfaces, defining a continuous, convex entropy function on the ‘positive’ cone in $H^1$ of the cut-open manifold, and answering a question of Leininger about the closure of the set of all stretch factors arising as monodromies within a single fibered cone of a $3$-manifold. This last application connects to the study of endperiodic automorphisms of infinite-type surfaces and the growth rates of their periodic points.

Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.

OBJECTIVES/GOALS: Identification of COVID-19 patients at risk for deterioration following discharge from the emergency department (ED) remains a clinical challenge. Our objective was to develop a prediction model that identifies COVID-19 patients at risk for return and hospital admission within 30 days of ED discharge. METHODS/STUDY POPULATION: We performed a retrospective cohort study of discharged adult ED patients (n = 7,529) with SARS-CoV-2 infection from 116 unique hospitals contributing to the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER). The primary outcome was return hospital admission within 30 days. Models were developed using Classification and Regression Tree (CART), Gradient Boosted Machine (GBM), Random Forest (RF), and least absolute shrinkage and selection (LASSO) approaches. RESULTS/ANTICIPATED RESULTS: Among COVID-19 patients discharged from the ED on their index encounter, 571 (7.6%) returned for hospital admission within 30 days. The machine learning (ML) models (GBM, RF,: and LASSO) performed similarly. The RF model yielded a test AUC of 0.74 (95% confidence interval [CI] 0.71–0.78) with a sensitivity of 0.46 (0.39-0.54) and specificity of 0.84 (0.82-0.85). Predictive variables including: lowest oxygen saturation, temperature; or history of hypertension,: diabetes, hyperlipidemia, or obesity, were common to all ML models. DISCUSSION/SIGNIFICANCE: A predictive model identifying adult ED patients with COVID-19 at risk for return hospital admission within 30 days is feasible. Ensemble/boot-strapped classification methods outperform the single tree CART method. Future efforts may focus on the application of ML models in the hospital setting to optimize allocation of follow up resources.

Yarkoni's analysis clearly articulates a number of concerns limiting the generalizability and explanatory power of psychological findings, many of which are compounded in infancy research. ManyBabies addresses these concerns via a radically collaborative, large-scale and open approach to research that is grounded in theory-building, committed to diversification, and focused on understanding sources of variation.

Monoclonal antibody therapeutics to treat coronavirus disease (COVID-19) have been authorized by the US Food and Drug Administration under Emergency Use Authorization (EUA). Many barriers exist when deploying a novel therapeutic during an ongoing pandemic, and it is critical to assess the needs of incorporating monoclonal antibody infusions into pandemic response activities. We examined the monoclonal antibody infusion site process during the COVID-19 pandemic and conducted a descriptive analysis using data from 3 sites at medical centers in the United States supported by the National Disaster Medical System. Monoclonal antibody implementation success factors included engagement with local medical providers, therapy batch preparation, placing the infusion center in proximity to emergency services, and creating procedures resilient to EUA changes. Infusion process challenges included confirming patient severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity, strained staff, scheduling, and pharmacy coordination. Infusion sites are effective when integrated into pre-existing pandemic response ecosystems and can be implemented with limited staff and physical resources.

We show that if a countable structure M in a finite relational language is not cellular, then there is an age-preserving $N \supseteq M$ such that $2^{\aleph _0}$ many structures are bi-embeddable with N. The proof proceeds by a case division based on mutual algebraicity.

Storytelling is increasingly recognized as a culturally relevant, human-centered strategy and has been linked to improvements in health knowledge, behavior, and outcomes. The Community Engagement Program of the Johns Hopkins Institute for Clinical and Translational Research designed and implemented a storytelling training program as a potentially versatile approach to promote stakeholder engagement. Data collected from multiple sources, including participant ratings, responses to open-ended questions, and field notes, consistently pointed to high-level satisfaction and acceptability of the program. As a next step, the storytelling training process and its impact need to be further investigated.

Background: Urine cultures are the most common microbiological tests in the outpatient setting and heavily influence treatment of suspected urinary tract infections (UTIs). Antibiotics for UTI are usually prescribed on an empiric basis in primary care before the urine culture results are available. However, culture results may be needed to confirm a UTI diagnosis and to verify that the correct antibiotic was prescribed. Although urine cultures are considered as the gold standard for diagnosis of UTI, cultures can easily become contaminated during collection. We determined the prevalence, predictors, and antibiotic use associated with contaminated urine cultures in 2 adult safety net primary care clinics. Methods: We conducted a retrospective chart review of visits with provider-suspected UTI in which a urine culture was ordered (November 2018–March 2020). Patient demographics, culture results, and prescription orders were captured for each visit. Culture results were defined as no culture growth, contaminated (ie, mixed flora, non-uropathogens, or ≥3 bacteria isolated on culture), low-count positive (growth between 100 and 100,000 CFU/mL), and high-count positive (>100,000 CFU/mL). A multivariable multinomial logistic regression model was used to identify factors associated with contaminated culture results. Results: There were 1,265 visits with urine cultures: 264 (20.9%) had no growth, 694 (54.9%) were contaminated, 159 (12.6%) were low counts, and 148 (11.7%) were high counts. Encounter-level factors are presented in Table 1. Female gender (adjusted odds ratio [aOR], 15.8; 95% confidence interval [CI], 10.21–23.46; P < .001), pregnancy (aOR, 13.98; 95% CI, 7.93–4.67; P < .001), and obesity (aOR, 1.9; 95% CI 1.31–2.77; P < .001) were independently associated with contaminated cultures. Of 264 patients whose urine cultures showed no growth, 36 (14%) were prescribed an antibiotic. Of 694 patients with contaminated cultures, 153 (22%) were prescribed an antibiotic (Figure 1). Conclusions: More than half of urine cultures were contaminated, and 1 in 5 patients were treated with antibiotics. Reduction of contamination should improve patient care by providing a more accurate record of the organism in the urine (if any) and its susceptibilities, which are relevant to managing future episodes of UTI in that patient. Optimizing urine collection represents a diagnostic stewardship opportunity in primary care.

Funding: This study was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (grant no. UM1AI104681). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Disclosures: None

Table 1.

Figure 1.

Magnetic reconnection is explored on the Terrestrial Reconnection Experiment (TREX) for asymmetric inflow conditions and in a configuration where the absolute rate of reconnection is set by an external drive. Magnetic pileup enhances the upstream magnetic field of the high-density inflow, leading to an increased upstream Alfvén speed and helping to lower the normalized reconnection rate to values expected from theoretical consideration. In addition, a shock interface between the far upstream supersonic plasma inflow and the region of magnetic flux pileup is observed, important to the overall force balance of the system, thereby demonstrating the role of shock formation for configurations including a supersonically driven inflow. Despite the specialized geometry where a strong reconnection drive is applied from only one side of the reconnection layer, previous numerical and theoretical results remain robust and are shown to accurately predict the normalized rate of reconnection for the range of system sizes considered. This experimental rate of reconnection is dependent on system size, reaching values as high as 0.8 at the smallest normalized system size applied.

Dynamic changes in microRNAs in oocyte and cumulus cells before and after maturation may explain the spatiotemporal post-transcriptional gene regulation within bovine follicular cells during the oocyte maturation process. miR-20a has been previously shown to regulate proliferation and differentiation as well as progesterone levels in cultured bovine granulosa cells. In the present study, we aimed to demonstrate the function of miR-20a during the bovine oocyte maturation process. Maturation of cumulus–oocyte complexes (COCs) was performed at 39°C in an humidified atmosphere with 5% CO2 in air. The expression of miR-20a was investigated in the cumulus cells and oocytes at 22 h post culture. The functional role of miR-20a was examined by modulating the expression of miR-20a in COCs during in vitro maturation (IVM). We found that the miR-20a expression was increased in cumulus cells but decreased in oocytes after IVM. Overexpression of miR-20a increased the oocyte maturation rate. Even though not statistically significant, miR-20a overexpression during IVM increased progesterone levels in the spent medium. This was further supported by the expression of STAR and CYP11A1 genes in cumulus cells. The phenotypes observed due to overexpression of miR-20a were validated by BMP15 supplementation during IVM and subsequent transfection of BMP15-treated COCs using miR-20a mimic or BMPR2 siRNA. We found that miR-20a mimic or BMPR2 siRNA transfection rescued BMP15-reduced oocyte maturation and progesterone levels. We concluded that miR-20a regulates oocyte maturation by increasing cumulus cell progesterone synthesis by simultaneous suppression of BMPR2 expression.

Genetic susceptibility to late maturity alpha-amylase (LMA) in wheat (Triticum aestivum L.) results in increased alpha-amylase activity in mature grain when cool conditions occur during late grain maturation. Farmers are forced to sell wheat grain with elevated alpha-amylase at a discount because it has an increased risk of poor end-product quality. This problem can result from either LMA or preharvest sprouting, grain germination on the mother plant when rain occurs before harvest. Whereas preharvest sprouting is a well-understood problem, little is known about the risk LMA poses to North American wheat crops. To examine this, LMA susceptibility was characterized in a panel of 251 North American hard spring wheat lines, representing ten geographical areas. It appears that there is substantial LMA susceptibility in North American wheat since only 27% of the lines showed reproducible LMA resistance following cold-induction experiments. A preliminary genome-wide association study detected six significant marker-trait associations. LMA in North American wheat may result from genetic mechanisms similar to those previously observed in Australian and International Maize and Wheat Improvement Center (CIMMYT) germplasm since two of the detected QTLs, QLMA.wsu.7B and QLMA.wsu.6B, co-localized with previously reported loci. The Reduced height (Rht) loci also influenced LMA. Elevated alpha-amylase levels were significantly associated with the presence of both wild-type and tall height, rht-B1a and rht-D1a, loci in both cold-treated and untreated samples.