Minimal surfaces in nuclear pasta with the Time-Dependent Hartree-Fock approach

In continuation to the studies of the whole variety of pasta shapes in [1], we present here calculations performed with the Hartree-Fock and time-dependent Hartree- Fock method concerning the mid-density range of pasta shapes: The slab-like, connected rod-like (p-surface) and the gyroidal shapes. On the one hand we present simulations of the dynamic formation of these shapes at fi- nite temperature. On the other hand we calculate the binding energies of these shapes for varying simulation box lengths and mean densities. All of these shapes are found to be at least metastable. The slab shape has a slightly lower energy because of the lack of curvature, but among these three configurations the gyroidal shape is metastable for the widest range in mean density

Choline: The Neurocognitive Essential Nutrient of Interest to Obstetricians and Gynecologists

Choline is an essential nutrient for proper liver, muscle, and brain functions as well as for lipid metabolism and cellular membrane composition and repair. Humans can produce small amounts of choline via the hepatic phosphatidylethanolamine N-methyltransferase pathway; however, most individuals must consume this vitamin through the diet to prevent deficiency. An individual’s dietary requirement for choline is dependent on common genetic variants in genes required for choline, folate, and one-carbon metabolism. Both the American Academy of Pediatrics and American Medical Association have recently reinforced the importance of maternal choline intake during pregnancy and lactation and recognize that failure to provide choline and other key essential nutrients during the first 1,000 days postconception may result in lifelong deficits in brain function despite subsequent nutrient repletion. Given that dietary intake for the majority of the US population, including subpopulations such as pregnant women, women of childbearing age, and vegetarians, falls well below the current adequate intake, there is a need to develop better policies and improve consumer education around the importance of this essential nutrient for human health. This comprehensive expert review summarizes the current scientific evidence on choline and health in relation to interests of obstetricians and gynecologists

Universal hidden order in amorphous cellular geometries

Partitioning space into cells with certain extreme geometrical properties is a central problem in many fields of science and technology. Here we investigate the Quantizer problem, defined as the optimisation of the moment of inertia of Voronoi cells, i.e., similarly-sized ‘sphere-like’ polyhedra that tile space are preferred. We employ Lloyd’s centroidal Voronoi diagram algorithm to solve this problem and find that it converges to disordered states associated with deep local minima. These states are universal in the sense that their structure factors are characterised by a complete independence of a wide class of initial conditions they evolved from. They moreover exhibit an anomalous suppression of long-wavelength density fluctuations and quickly become effectively hyperuniform. Our findings warrant the search for novel amorphous hyperuniform phases and cellular materials with unique physical properties

The underconsumed and underappreciated essential nutrient

Choline has been recognized as an essential nutrient by the Food and Nutrition Board of the National Academies of Medicine since 1998. Its metabolites have structural, metabolic, and regulatory roles within the body. Humans can endogenously produce small amounts of choline via the hepatic phosphatidylethanolamine N-methyltransferase pathway. However, the nutrient must be consumed exogenously to prevent signs of deficiency. The Adequate Intake (AI) for choline was calculated at a time when dietary intakes across the populationwere unknown for the nutrient. Unlike the traditional National Academy of Medicine approach of calculating an AI based on observed or experimentally determined approximations or estimates of intake by a group (or groups) of healthy individuals, calculation of the AI for choline was informed in part by a depletionrepletion study in adultmen who, upon becoming deficient, developed signs of liver damage. The AI for other gender and life-stage groups was calculated based on standard reference weights, except for infants 0 to 6 months, whose AI reflects the observedmean intake from consuming human breast milk. Recent analyses indicate that large portions of the population (ie, approximately 90% of Americans), including most pregnant and lactating women, are well below the AI for choline. Moreover, the food patterns recommended by the 2015-2020 Dietary Guidelines for Americans are currently insufficient to meet the AI for choline in most age-sex groups. An individual's requirement for choline is dependent on common genetic variants in genes required for choline, folate, and 1-carbon metabolism, potentially increasing more than one-third of the population's susceptibly to organ dysfunction. The American Medical Association and American Academy of Pediatrics have both recently reaffirmed the importance of choline during pregnancy and lactation. Newand emerging evidence suggests that maternal choline intake during pregnancy, and possibly lactation, has lasting beneficial neurocognitive effects on the offspring. Because choline is found predominantly in animal-derived foods, vegetarians and vegans may have a greater risk for inadequacy. With the 2020-2025 Dietary Guidelines for Americans recommending expansion of dietary information for pregnant women, and the inclusion of recommendations for infants and toddlers 0 to 2 years, better communication of the role that choline plays, particularly in the area of neurocognitive development, is critical. This narrative review summarizes the peer-reviewed literature and discussions from the 2018 Choline Science Summit, held in Washington, DC, in February 2018

Second order analysis of geometric functionals of Boolean models

This paper presents asymptotic covariance formulae and central limit theorems for geometric functionals, including volume, surface area, and all Minkowski functionals and translation invariant Minkowski tensors as prominent examples, of stationary Boolean models. Special focus is put on the anisotropic case. In the (anisotropic) example of aligned rectangles, we provide explicit analytic formulae and compare them with simulation results. We discuss which information about the grain distribution second moments add to the mean values.Comment: Chapter of the forthcoming book "Tensor Valuations and their Applications in Stochastic Geometry and Imaging" in Lecture Notes in Mathematics edited by Markus Kiderlen and Eva B. Vedel Jensen. (The second version mainly resolves minor LaTeX problems.

Cell shape analysis of random tessellations based on Minkowski tensors

To which degree are shape indices of individual cells of a tessellation characteristic for the stochastic process that generates them? Within the context of stochastic geometry and the physics of disordered materials, this corresponds to the question of relationships between different stochastic models. In the context of image analysis of synthetic and biological materials, this question is central to the problem of inferring information about formation processes from spatial measurements of resulting random structures. We address this question by a theory-based simulation study of shape indices derived from Minkowski tensors for a variety of tessellation models. We focus on the relationship between two indices: an isoperimetric ratio of the empirical averages of cell volume and area and the cell elongation quantified by eigenvalue ratios of interfacial Minkowski tensors. Simulation data for these quantities, as well as for distributions thereof and for correlations of cell shape and volume, are presented for Voronoi mosaics of the Poisson point process, determinantal and permanental point processes, and Gibbs hard-core and random sequential absorption processes as well as for Laguerre tessellations of polydisperse spheres and STIT- and Poisson hyperplane tessellations. These data are complemented by mechanically stable crystalline sphere and disordered ellipsoid packings and area-minimising foam models. We find that shape indices of individual cells are not sufficient to unambiguously identify the generating process even amongst this limited set of processes. However, we identify significant differences of the shape indices between many of these tessellation models. Given a realization of a tessellation, these shape indices can narrow the choice of possible generating processes, providing a powerful tool which can be further strengthened by density-resolved volume-shape correlations.Comment: Chapter of the forthcoming book "Tensor Valuations and their Applications in Stochastic Geometry and Imaging" in Lecture Notes in Mathematics edited by Markus Kiderlen and Eva B. Vedel Jense

Special Libraries, April 1933

Volume 24, Issue 3https://scholarworks.sjsu.edu/sla_sl_1933/1002/thumbnail.jp

Outpatient treatment of COVID-19 and incidence of post-COVID-19 condition over 10 months (COVID-OUT): a multicentre, randomised, quadruple-blind, parallel-group, phase 3 trial

Background: Post-COVID-19 condition (also known as long COVID) is an emerging chronic illness potentially affecting millions of people. We aimed to evaluate whether outpatient COVID-19 treatment with metformin, ivermectin, or fluvoxamine soon after SARS-CoV-2 infection could reduce the risk of long COVID. Methods: We conducted a decentralised, randomised, quadruple-blind, parallel-group, phase 3 trial (COVID-OUT) at six sites in the USA. We included adults aged 30–85 years with overweight or obesity who had COVID-19 symptoms for fewer than 7 days and a documented SARS-CoV-2 positive PCR or antigen test within 3 days before enrolment. Participants were randomly assigned via 2 × 3 parallel factorial randomisation (1:1:1:1:1:1) to receive metformin plus ivermectin, metformin plus fluvoxamine, metformin plus placebo, ivermectin plus placebo, fluvoxamine plus placebo, or placebo plus placebo. Participants, investigators, care providers, and outcomes assessors were masked to study group assignment. The primary outcome was severe COVID-19 by day 14, and those data have been published previously. Because the trial was delivered remotely nationwide, the a priori primary sample was a modified intention-to-treat sample, meaning that participants who did not receive any dose of study treatment were excluded. Long COVID diagnosis by a medical provider was a prespecified, long-term secondary outcome. This trial is complete and is registered with ClinicalTrials.gov, NCT04510194. Findings: Between Dec 30, 2020, and Jan 28, 2022, 6602 people were assessed for eligibility and 1431 were enrolled and randomly assigned. Of 1323 participants who received a dose of study treatment and were included in the modified intention-to-treat population, 1126 consented for long-term follow-up and completed at least one survey after the assessment for long COVID at day 180 (564 received metformin and 562 received matched placebo; a subset of participants in the metformin vs placebo trial were also randomly assigned to receive ivermectin or fluvoxamine). 1074 (95%) of 1126 participants completed at least 9 months of follow-up. 632 (56·1%) of 1126 participants were female and 494 (43·9%) were male; 44 (7·0%) of 632 women were pregnant. The median age was 45 years (IQR 37–54) and median BMI was 29·8 kg/m2 (IQR 27·0–34·2). Overall, 93 (8·3%) of 1126 participants reported receipt of a long COVID diagnosis by day 300. The cumulative incidence of long COVID by day 300 was 6·3% (95% CI 4·2–8·2) in participants who received metformin and 10·4% (7·8–12·9) in those who received identical metformin placebo (hazard ratio [HR] 0·59, 95% CI 0·39–0·89; p=0·012). The metformin beneficial effect was consistent across prespecified subgroups. When metformin was started within 3 days of symptom onset, the HR was 0·37 (95% CI 0·15–0·95). There was no effect on cumulative incidence of long COVID with ivermectin (HR 0·99, 95% CI 0·59–1·64) or fluvoxamine (1·36, 0·78–2·34) compared with placebo. Interpretation: Outpatient treatment with metformin reduced long COVID incidence by about 41%, with an absolute reduction of 4·1%, compared with placebo. Metformin has clinical benefits when used as outpatient treatment for COVID-19 and is globally available, low-cost, and safe. Funding: Parsemus Foundation; Rainwater Charitable Foundation; Fast Grants; UnitedHealth Group Foundation; National Institute of Diabetes, Digestive and Kidney Diseases; National Institutes of Health; and National Center for Advancing Translational Sciences

Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19

BACKGROUND Early treatment to prevent severe coronavirus disease 2019 (Covid-19) is an important component of the comprehensive response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. METHODS In this phase 3, double-blind, randomized, placebo-controlled trial, we used a 2-by-3 factorial design to test the effectiveness of three repurposed drugs - metformin, ivermectin, and fluvoxamine - in preventing serious SARS-CoV-2 infection in nonhospitalized adults who had been enrolled within 3 days after a confirmed diagnosis of infection and less than 7 days after the onset of symptoms. The patients were between the ages of 30 and 85 years, and all had either overweight or obesity. The primary composite end point was hypoxemia (≤93% oxygen saturation on home oximetry), emergency department visit, hospitalization, or death. All analyses used controls who had undergone concurrent randomization and were adjusted for SARSCoV-2 vaccination and receipt of other trial medications. RESULTS A total of 1431 patients underwent randomization; of these patients, 1323 were included in the primary analysis. The median age of the patients was 46 years; 56% were female (6% of whom were pregnant), and 52% had been vaccinated. The adjusted odds ratio for a primary event was 0.84 (95% confidence interval [CI], 0.66 to 1.09; P=0.19) with metformin, 1.05 (95% CI, 0.76 to 1.45; P=0.78) with ivermectin, and 0.94 (95% CI, 0.66 to 1.36; P=0.75) with fluvoxamine. In prespecified secondary analyses, the adjusted odds ratio for emergency department visit, hospitalization, or death was 0.58 (95% CI, 0.35 to 0.94) with metformin, 1.39 (95% CI, 0.72 to 2.69) with ivermectin, and 1.17 (95% CI, 0.57 to 2.40) with fluvoxamine. The adjusted odds ratio for hospitalization or death was 0.47 (95% CI, 0.20 to 1.11) with metformin, 0.73 (95% CI, 0.19 to 2.77) with ivermectin, and 1.11 (95% CI, 0.33 to 3.76) with fluvoxamine. CONCLUSIONS None of the three medications that were evaluated prevented the occurrence of hypoxemia, an emergency department visit, hospitalization, or death associated with Covid-19

Mean-intercept anisotropy analysis of porous media. I. Analytic formulae for anisotropic Boolean models

Purpose Structure-property relations, which relate the shape of the microstructure to physical properties such as transport or mechanical properties, need sensitive measures of structure. What are suitable fabric tensors that quantify the shape of anisotropic heterogeneous materials? The mean intercept length is among the most commonly used characteristics of anisotropy in porous media, for example, of trabecular bone in medical physics. Methods We analyze the orientation-biased Boolean model, a versatile stochastic model that represents microstructures as overlapping grains with an orientation bias towards a preferred direction. This model is an extension of the isotropic Boolean model, which has been shown to truthfully reproduce multi-functional properties of isotropic porous media. We explain the close relationship between the concept of intersections with test lines to the elaborate mathematical theory of queues, and how explicit results from the latter can be directly applied to characterize microstructures. Results In this series of two papers, we provide analytic formulas for the anisotropic Boolean model and demonstrate often overlooked conceptual shortcomings of this approach. Queuing theory is used to derive simple and illustrative formulas for the mean intercept length. It separates into an intensity-dependent and an orientation-dependent factor. The global average of the mean intercept length can be expressed by local characteristics of a single grain alone. Conclusions We thus identify which shape information about the random process the mean intercept length contains. The connection between global and local quantities helps to interpret observations and provides insights into the possibilities and limitations of the analysis. In the second paper of this series, we discuss, based on the findings in this paper, short-comings of the mean intercept analysis for (bone-)microstructure characterization. We will suggest alternative and better defined sensitive anisotropy measures from integral geometry