Background: Neck vessel imaging is often performed in hyperacute stroke to allow neurointerventionalists to estimate access complexity. This study aimed to assess clinician agreement on catheterization strategies based on imaging in these scenarios. Methods: An electronic portfolio of 60 patients with acute ischemic stroke was sent to 53 clinicians. Respondents were asked: (1) the difficulty of catheterization through femoral access with a regular Vertebral catheter, (2) whether to use a Simmons or reverse-curve catheter initially, and (3) whether to consider an alternative access site. Agreement was assessed using Fleiss’ Kappa statistics. Results: Twenty-two respondents (7 neurologists, 15 neuroradiologists) completed the survey. Overall there was slight interrater agreement (κ=0.17, 95% CI: 0.10–0.25). Clinicians with >50 cases annually had better agreement (κ=0.22) for all questions than those with fewer cases (κ=0.07). Agreement did not significantly differ by imaging modality: CTA (κ=0.18) and MRA (κ=0.14). In 40/59 cases (67.80%), at least 25% of clinicians disagreed on whether to use a Simmons or reverse-curve catheter initially. Conclusions: Agreement on catheterization strategies remains fair at best. Our results suggest that visual assessment of pre-procedural vessels imaging is not reliable for the estimation of endovascular access complexity.

Background: Attitudes toward aging influence many health outcomes, yet their relationship with cognition and Alzheimer’s disease (AD) remains unknown. To better understand their impact on cognition and AD risk, we examined whether positive attitudes predict better cognition and diminished risk on AD biomarkers. Methods: A subsample of older adults with a family history of AD (n=54; women=39) from the McGill PREVENT-AD cohort participated in this study. Participants completed the Attitudes to Ageing Questionnaire (AAQ-24), providing three scores: psychosocial loss, psychological growth and physical change. Participants underwent cognitive testing (Rey Auditory Verbal Learning Test, RAVLT; Delis-Kaplan Executive Function System-Color Word Interference Test, D-KEFS-CWIT), and AD blood-based biomarker assessments (p-tau217, Aβ42/40). Regression models tested associations, adjusting for covariates (age, sex, education, depression, APOE4), and were Bonferroni corrected. Results: Positive attitudes were associated with better recall and recognition (RAVLT) and improved word reading, colour naming, switching, and inhibition (D-KEFS-CWIT) (p<0.00077), while negative attitudes showed the opposite pattern. Negative attitudes were correlated with lower Aβ42/40 ratios, while positive attitudes were linked to lower p-tau217 (p<0.0167). Conclusions: These findings demonstrate that positive attitudes predict better cognition and a lower risk profile for AD biomarkers, suggesting that life outlook may be an early disease feature or a risk factor.

OBJECTIVES/GOALS: Antibiotic treatment sets the stage for intestinal domination by Candida albicanswhich is necessary for development of invasive disease, but the resources driving this bloom remain poorly defined. We sought to determine these factors in order to design novel prophylaxis strategies for reducing gastrointestinal (GI) colonization. METHODS/STUDY POPULATION: We initially developed a generalizable framework, termed metabolic footprinting to determine the metabolites C. albicanspreferentially uses in the mouse GI tract. After identifying the metabolites C. albicansutilizes, we usedin vitro growth assays in the presence and absence of oxygen to validate out metabolomics findings. We next determined if a probiotic E. coli that utilizes oxygen would reduce C. albicanscolonization compared to a mutant E. coli that could not respire oxygen. Finding that oxygen was a necessary resource, we utilized germ-free mice to determine if Clostridiaspp. known to reduce GI oxygen would prevent C. albicanscolonization. Lastly, we sought to see if 5-aminosalicylic acid (5-ASA) could prevent C. albicanscolonization. RESULTS/ANTICIPATED RESULTS: We found that C. albicans preferentially utilizes simple carbohydrates including fructo-oligosaccharides (e.g., 1-kestose), disaccharides (e.g., β-gentiobiose), and alcoholic sugars (e.g., sorbitol) and is able to grow in vitro on minimal media supplemented with either of these nutrients. However, in the hypoxic environment that is found in the “healthy” colon, C. albicans cannot utilize these nutrients. We next found that pre-colonization in a mouse model with a probiotic E. coli significantly reduced C. albicanscolonization, but the mutant E. coli had no effect on colonization. We next showed that Clostridia supplementation restored GI hypoxia and reduced C. albicanscolonization. Remarkably, we found that 5-ASA significantly reduced GI colonization of C. albicans. DISCUSSION/SIGNIFICANCE: We have shown that C. albicans requires oxygen to colonize the GI tract. Importantly, we found that 5-ASA can prevent an antibiotic mediated bloom of C. albicans by restoring GI hypoxia, which warrants additional studies to determine if 5-ASA can be used as an adjunctive prophylactic treatment in high risk patients.

The presence of a mean magnetic field aligned with the direction of the acceleration greatly modifies the development of the Rayleigh–Taylor instability (RTI). High resolution direct numerical simulations of the Boussinesq–Navier–Stokes equations under the magnetohydrodynamics approximation reveal that, after an initial damping of the perturbations at the interface between the two miscible fluids, a rapid increase of the mixing layer is observed. Structures are significantly stretched in the vertical direction because magnetic tension prevents small-scale shear instabilities. When the vertical turbulent velocity exceeds the Alfvén velocity, the flow transitions to turbulence, structures break and an enhanced mixing occurs with strong dissipation. Afterwards, the mixing zone slows down and its growth rate is decreased compared to the hydrodynamic case. For larger magnitudes of the mean magnetic field, a strong anisotropy persists, and an increased fraction of potential energy injected into the system is lost into turbulent magnetic energy: as a consequence, the mixing zone growth rate is decreased even more. This phenomenology is embedded in a general buoyancy-drag equation, derived from simplified equations that reflect the large-scale dynamics, in which the drag coefficient is increased by the presence of turbulent magnetic energy.

Modeling complex dynamical systems with only partial knowledge of their physical mechanisms is a crucial problem across all scientific and engineering disciplines. Purely data-driven approaches, which only make use of an artificial neural network and data, often fail to accurately simulate the evolution of the system dynamics over a sufficiently long time and in a physically consistent manner. Therefore, we propose a hybrid approach that uses a neural network model in combination with an incomplete partial differential equations (PDEs) solver that provides known, but incomplete physical information. In this study, we demonstrate that the results obtained from the incomplete PDEs can be efficiently corrected at every time step by the proposed hybrid neural network—PDE solver model, so that the effect of the unknown physics present in the system is correctly accounted for. For validation purposes, the obtained simulations of the hybrid model are successfully compared against results coming from the complete set of PDEs describing the full physics of the considered system. We demonstrate the validity of the proposed approach on a reactive flow, an archetypal multi-physics system that combines fluid mechanics and chemistry, the latter being the physics considered unknown. Experiments are made on planar and Bunsen-type flames at various operating conditions. The hybrid neural network—PDE approach correctly models the flame evolution of the cases under study for significantly long time windows, yields improved generalization and allows for larger simulation time steps.

Background: Sample entropy (SampEn) can quantify the unpredictability of a physiological signal. We sought to assess if SampEn on EEG could reflect recent seizure activity. Methods: Charts of all patients undergoing an outpatient EEG between January and March 2018 were reviewed to assess seizure occurrences in the follow-up period between the two clinical visits surrounding the EEG. 9s-EEG segments were extracted at pre-specified time points. SampEn was calculated for all segments and values aggregated at the 25thpercentile. We performed a multivariate zero-inflated analysis to test the association between SampEn and seizure rate around the EEG, after controlling for age, presence of IED, presence of abnormal slowing, and presence of a focal brain lesion. Results: 269 EEGs were screened and 133 met inclusion criteria (112 patients). 80 EEGs (60%) were from patients with epilepsy, of which 47 had at least one seizure within the year preceding the EEG. Remaining EEGs were from patients who were deemed not to have epilepsy at last follow-up. Each 1SD decrease in SampEn was associated with a 3.93-fold increase in the rate of daily seizures (95% CI: 1.19–12.99, p = 0.02). Conclusions: Sample entropy of EEG is a potential objective method to assess contemporary seizure occurrence.

Reaction networks are commonly used within the mathematical biology and mathematical chemistry communities to model the dynamics of interacting species. These models differ from the typical graphs found in random graph theory since their vertices are constructed from elementary building blocks, i.e. the species. We consider these networks in an Erdös–Rényi framework and, under suitable assumptions, derive a threshold function for the network to have a deficiency of zero, which is a property of great interest in the reaction network community. Specifically, if the number of species is denoted by n and the edge probability by $p_n$, then we prove that the probability of a random binary network being deficiency zero converges to 1 if $p_n\ll r(n)$ as $n \to \infty$, and converges to 0 if $p_n \gg r(n)$ as $n \to \infty$, where $r(n)=\frac{1}{n^3}$.

Background: Sample entropy (SampEn) can quantify the unpredictability of a physiological signal. We sought to assess if SampEn on EEG could reflect recent seizure activity. Methods: Charts of all patients undergoing an outpatient EEG between January and March 2018 were reviewed to assess seizure occurrences in the follow-up period between the two clinical visits surrounding the EEG. 9s-EEG segments were extracted at pre-specified time points. SampEn was calculated for all segments and values aggregated at the 25thpercentile. We performed a multivariate zero-inflated analysis to test the association between SampEn and seizure rate around the EEG, after controlling for age, presence of IED, presence of abnormal slowing, and presence of a focal brain lesion. Results: 269 EEGs were screened and 133 met inclusion criteria (112 patients). 80 EEGs (60%) were from patients with epilepsy, of which 47 had at least one seizure within the year preceding the EEG. Remaining EEGs were from patients who were deemed not to have epilepsy at last follow-up. Each 1SD decrease in SampEn was associated with a 3.93-fold increase in the rate of daily seizures (95% CI: 1.19–12.99, p = 0.02). Conclusions: Sample entropy of EEG is a potential objective method to assess contemporary seizure occurrence.

Self-amplified spontaneous emission (SASE) free electron laser (FEL) devices have disclosed an unexpected interplay between the laser intensity growth and regions of the electron bunch of the order of the coherence length. They are usually identified with the bunch slice and contribute to the laser dynamics with their own characteristics. The dynamical effects inducing geometrical and phase space misalignment of bunch slice in X-ray operating FELs can be traced back to a plethora of phenomena, both in the Linac accelerating section or inside the beam transport optic magnet. They are responsible for spoiling of the beam projected qualities and, if not corrected properly, induce an increase of the saturation length and a decreasing of the output power. We discuss the inclusion of these effects in models employing scaling formulae.

There is a need for accurate, inexpensive and field-friendly methods to assess body composition in children. Bioelectrical impedance analysis (BIA) is a promising approach; however, there have been limited validation and use among young children in resource-poor settings. We aim to develop and validate population-specific prediction equations for estimating total fat mass (FM), fat free-mass (FFM) and percentage body fat (PBF) in Vietnamese children (4–7 years) using reactance and resistance from BIA, anthropometric variables and demographic information. We conducted a cross-sectional survey of 120 children. Body composition was measured using dual-energy X-ray absorptiometry (DXA), BIA and anthropometry. To develop prediction equations, we split all data into development (70 %) and validation datasets (30 %). The model performance was evaluated using predicted residual error sum of squares, root mean squared error (RMSE), mean absolute error (MAE) and R2. We identified a top performing model with the least number of parameters (age, sex, weight and resistance index or resistance and height), low RMSE (FM 0·70, FFM 0·74, PBF 3·10), low MAE (FM 0·55, FFM 0·62, PBF 2·49), high R2 (FM 0·95, FFM 0·92, PBF 0·82) and the least difference between predicted values and actual values from DXA (FM 0·03 kg or 0·01 sd, FFM 0·06 kg or 0·02 sd, PBF 0·27 % or 0·04 sd). In conclusion, we developed the first valid and highly predictive equations to estimate FM, FFM and PBF in Vietnamese children using BIA. These findings have important implications for future research on the double burden of disease and risks associated with overweight and obesity in young children.

Q fever (caused by Coxiella burnetii) is thought to have an almost world-wide distribution, but few countries have conducted national serosurveys. We measured Q fever seroprevalence using residual sera from diagnostic laboratories across Australia. Individuals aged 1–79 years in 2012–2013 were sampled to be proportional to the population distribution by region, distance from metropolitan areas and gender. A 1/50 serum dilution was tested for the Phase II IgG antibody against C. burnetii by indirect immunofluorescence. We calculated crude seroprevalence estimates by age group and gender, as well as age standardised national and metropolitan/non-metropolitan seroprevalence estimates. Of 2785 sera, 99 tested positive. Age standardised seroprevalence was 5.6% (95% confidence interval (CI 4.5%–6.8%), and similar in metropolitan (5.5%; 95% CI 4.1%–6.9%) and non-metropolitan regions (6.0%; 95%CI 4.0%–8.0%). More males were seropositive (6.9%; 95% CI 5.2%–8.6%) than females (4.2%; 95% CI 2.9%–5.5%) with peak seroprevalence at 50–59 years (9.2%; 95% CI 5.2%–13.3%). Q fever seroprevalence for Australia was higher than expected (especially in metropolitan regions) and higher than estimates from the Netherlands (2.4%; pre-outbreak) and US (3.1%), but lower than for Northern Ireland (12.8%). Robust country-specific seroprevalence estimates, with detailed exposure data, are required to better understand who is at risk and the need for preventive measures.