Vitamin D insufficiency is associated with various disease processes. We determined whether consumption of a diet supplemented with HyD®, a 25-hydroxycholecalciferol (25(OH)D3) source, would safely increase plasma 25(OH)D3 concentrations in Golden Retrievers with low vitamin D status. We hypothesised that dietary supplementation with HyD® would rapidly increase and sustain plasma 25(OH)D3 levels in healthy Golden Retrievers with low vitamin D status compared with supplementation with vitamin D3. Of fifty-seven privately owned dogs recruited with written owner consent, eighteen dogs with low vitamin D status were identified and sorted between two groups to have similar initial plasma 25(OH)D3 concentrations, sex distributions, ages and body weights. Dogs of each group were fed a dry dog food supplemented with either 16 μg/kg of 25(OH)D3 as HyD® (n 10) or 81 μg/kg of cholecalciferol (D3) (n 8) for 4 months. Plasma 25(OH)D3 concentrations were determined monthly. A significant time effect (P < 0⋅001) and time by group interaction (P = 0⋅0045) were found for monthly determined plasma 25(OH)D3 concentrations. Dogs fed the HyD®-supplemented diet experienced a 40⋅5 % rise in plasma 25(OH)D3 values after 1 month (P < 0⋅001) and no change thereafter. Plasma 25(OH)D3 values of dogs supplemented with vitamin D3 did not increase (P > 0⋅05) and were less than values of dogs supplemented with HyD® (P = 0⋅044). With few exceptions, average haematologic, biochemical and urinalyses results remained within the reference range for both groups. Dietary supplementation with HyD® is sufficient to safely increase and sustain plasma 25(OH)D3 levels in healthy dogs.

The health and economic outcomes of the COVID-19 pandemic will in part be determined by how effectively experts can communicate information to the public and the degree to which people follow expert recommendation. Using a survey experiment conducted in May 2020 with almost 5,000 respondents, this paper examines the effect of source cues and message frames on perceptions of information credibility in the context of COVID-19. Each health recommendation was framed by expert or nonexpert sources, was fact- or experience-based, and suggested potential gain or loss to test if either the source cue or framing of issues affected responses to the pandemic. We find no evidence that either source cue or message framing influence people’s responses – instead, respondents’ ideological predispositions, media consumption, and age explain much of the variation in survey responses, suggesting that public health messaging may face challenges from growing ideological cleavages in American politics.

The study of a turbulent premixed flame often involves analysing quantities conditioned to different iso-surfaces of a reactive scalar field. Under the influence of turbulence, such a surface is deformed and translated. To track the surface motion, the displacement speed ($S_d$) of the scalar field respective to the local flow velocity is widely used and this quantity is currently receiving growing attention. Inspired by the apparent benefits from a simple decomposition of $S_d$ into contributions due to (i) curvature, (ii) normal diffusion and (iii) chemical reaction, this work aims at deriving and exploring new evolution equations for these three contributions averaged over the reaction surface. Together with a previously obtained $S_d$-evolution equation, the three new equations are presented in a form that emphasizes the decomposition of $S_d$ into three terms. This set of equations is also supplemented with a curvature-evolution equation, hence providing a new perspective to link the flame topology and its propagation characteristics. Using two direct numerical simulation databases obtained from constant-density and variable-density reaction waves, all the derived equations and the term-wise decomposition relations are demonstrated to hold numerically. Comparison of the simulated results indicates that the thermal expansion weakly affects the key terms in the considered evolution equations. Thermal expansion can cause variations in the averaged $S_d$ and its decomposed parts through multiple routes more than introducing a dilatation term. The flow plays a major role to influence the key terms in all equations except the curvature one, due to a cancellation between negatively and positively curved surface elements.

The aim of this study was to explore the frequency and distribution of gene mutations that are related to isoniazid (INH) and rifampin (RIF)-resistance in the strains of the multidrug-resistant tuberculosis (MDR-TB) Mycobacterium tuberculosis (M.tb) in Beijing, China. In this retrospective study, the genotypes of 173 MDR-TB strains were analysed by spoligotyping. The katG, inhA genes and the promoter region of inhA, in which genetic mutations confer INH resistance; and the rpoB gene, in which genetic mutations confer RIF resistance, were sequenced. The percentage of resistance-associated nucleotide alterations among the strains of different genotypes was also analysed. In total, 90.8% (157/173) of the MDR strains belonged to the Beijing genotype. Population characteristics were not significantly different among the strains of different genotypes. In total, 50.3% (87/173) strains had mutations at codon S315T of katG; 16.8% (29/173) of strains had mutations in the inhA promoter region; of them, 5.5% (15/173) had point mutations at −15 base (C→T) of the inhA promoter region. In total, 86.7% (150/173) strains had mutations at rpoB gene; of them, 40% (69/173) strains had mutations at codon S531L of rpoB. The frequency of mutations was not significantly higher in Beijing genotypic MDR strains than in non-Beijing genotypes. Beijing genotypic MDR-TB strains were spreading in Beijing and present a major challenge to TB control in this region. A high prevalence of katG Ser315Thr, inhA promoter region (−15C→T) and rpoB (S531L) mutations was observed. Molecular diagnostics based on gene mutations was a useful method for rapid detection of MDR-TB in Beijing, China.

An acute gastroenteritis (AGE) outbreak caused by a norovirus occurred at a hospital in Shanghai, China, was studied for molecular epidemiology, host susceptibility and serological roles. Rectal and environmental swabs, paired serum samples and saliva specimens were collected. Pathogens were detected by real-time polymerase chain reaction and DNA sequencing. Histo-blood group antigens (HBGA) phenotypes of saliva samples and their binding to norovirus protruding proteins were determined by enzyme-linked immunosorbent assay. The HBGA-binding interfaces and the surrounding region were analysed by the MegAlign program of DNAstar 7.1. Twenty-seven individuals in two care units were attacked with AGE at attack rates of 9.02 and 11.68%. Eighteen (78.2%) symptomatic and five (38.4%) asymptomatic individuals were GII.6/b norovirus positive. Saliva-based HBGA phenotyping showed that all symptomatic and asymptomatic cases belonged to A, B, AB or O secretors. Only four (16.7%) out of the 24 tested serum samples showed low blockade activity against HBGA-norovirus binding at the acute phase, whereas 11 (45.8%) samples at the convalescence stage showed seroconversion of such blockade. Specific blockade antibody in the population played an essential role in this norovirus epidemic. A wide HBGA-binding spectrum of GII.6 supports a need for continuous health attention and surveillance in different settings.

Biological materials represent a major source of inspiration to engineer protein-based polymers that can replicate the properties of living systems. Combined with our ability to control the molecular structure of proteins at the single amino acid level, this results in a vast array of attractive possibilities for materials science, an interest that is undeniably related to simplified procedures in gene synthesis, cloning, and biotechnological production. In parallel, it has been increasingly appreciated that living organisms exploit liquid–liquid phase separation (LLPS) to fabricate extracellular structures. In this article, we discuss the central role of protein LLPS in the fabrication of selected biological structures, including biological adhesives and hard biomolecular composites, and how physicochemical lessons from these systems are being replicated in synthetic analogs. Recent translational applications of protein LLPS are highlighted, notably aqueous-resistant adhesives, stimuli-responsive therapeutics carriers, and matrix materials for green structural composites.

Research on flight emissions at airports is very important for environmental policymaking. This study analysed the trend of aircraft air pollutant emissions at mainland China airports from 1990 to 2017, mainly focusing on standard landing and take-off (LTO) cycles. Total flight movements increased 29-fold from 1990 to 2017 at Chinese airports. Over the same period, the emissions of NOx, SOx, CO, hydrocarbons (HC), and particulate matter (PM) increased 46, 27, 12, 5, and 4 times, respectively. Emissions at the 216 public airports showed a growth trend. It was estimated that in 2017, Chinese airports emitted 12,875 kilotons of CO2, 59 kilotons of NOx, 3 kilotons of SOx, 38 kilotons of CO, 5 kilotons of HC, and 0.4 kilotons of PM. The largest 30 airports produced 68.2% of the total emissions. Emissions from B737-800, A320, A321, B737-700, A330-300, and A319 aircraft accounted for more than 75% of aircraft LTO emissions at Chinese airports in 2017. Results show that average emissions per passenger have decreased for CO2, CO, HC, SOx, PM, and NOx from 1990 to 2017.

Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.

We apply conformal mapping to find the evolving shapes of a dissolving cylinder in a potential flow. Similar equations can be used to describe melting in a flowing liquid phase. Results are compared with microfluidic experiments and numerical simulations. Shapes predicted by conformal mapping agree almost perfectly with experimental observations, after a modest (20 %) rescaling of the time. Finite-volume simulations show that the differences with experiment are connected to the underlying assumptions of the analytical model: potential flow and diffusion-limited dissolution. Approximate solutions of the equations describing the evolution of the shape of the undissolved solid can be derived from a Laurent expansion of the mapping function from the unit circle. Asymptotic expressions for the evolution of the area of the disk and the shift in its centre of mass have been derived at low and high Péclet number. Analytic approximations to the leading-order Laurent coefficients provide additional insight into the mechanisms underlying pore-scale dissolution.

In order to elucidate the physical connection between the propulsive performance and the unsteadiness of jet flow, the transient development of the impulse and thrust of laminar starting jets with finite fluid discharged is investigated numerically for cases with different velocity programmes and jet stroke ratios. The simulation quantitatively demonstrates that the impulse and thrust generated are highly sensitive to the jet kinematics and its near-wake dynamics. The momentum flux contribution to the jet impulse is found to be significant and is associated closely with the jet kinematics. On the other hand, although the over pressure effect at the jet initiation stage has been identified previously as the main reason for the enhanced propulsive performance of the starting jet, the current results indicate that its contribution is in fact weakened by the negative local pressure, induced by the formation of the leading vortex ring as well as jet development during the deceleration stage. Contrary to the effects of the leading vortex ring, the stopping vortex formed near the nozzle exit plane during the jet deceleration stage is found to contribute positively to the pressure impulse production, albeit it is relatively small. By augmenting the over pressure effect and mitigating the negative-pressure effect, the cases with the fast acceleration and slow deceleration velocity programme is capable of producing the maximum pressure impulse, leading to additional impulse production over what would be expected from the jet momentum flux alone.

Graphlet counting is a widely explored problem in network analysis and has been successfully applied to a variety of applications in many domains, most notatbly bioinformatics, social science, and infrastructure network studies. Efficiently computing graphlet counts remains challenging due to the combinatorial explosion, where a naive enumeration algorithm needs O(Nk) time for k-node graphlets in a network of size N. Recently, many works introduced carefully designed combinatorial and sampling methods with encouraging results. However, the existing methods ignore the fact that graphlet counts and the graph structural information are correlated. They always consider a graph as a new input and repeat the tedious counting procedure on a regular basis even if it is similar or exactly isomorphic to previously studied graphs. This provides an opportunity to speed up the graphlet count estimation procedure by exploiting this correlation via learning methods. In this paper, we raise a novel graphlet count learning (GCL) problem: given a set of historical graphs with known graphlet counts, how to learn to estimate/predict graphlet count for unseen graphs coming from the same (or similar) underlying distribution. We develop a deep learning framework which contains two convolutional neural network models and a series of data preprocessing techniques to solve the GCL problem. Extensive experiments are conducted on three types of synthetic random graphs and three types of real-world graphs for all 3-, 4-, and 5-node graphlets to demonstrate the accuracy, efficiency, and generalizability of our framework. Compared with state-of-the-art exact/sampling methods, our framework shows great potential, which can offer up to two orders of magnitude speedup on synthetic graphs and achieve on par speed on real-world graphs with competitive accuracy.

In this paper, the generation of relativistic electron mirrors (REM) and the reflection of an ultra-short laser off the mirrors are discussed, applying two-dimension particle-in-cell simulations. REMs with ultra-high acceleration and expanding velocity can be produced from a solid nanofoil illuminated normally by an ultra-intense femtosecond laser pulse with a sharp rising edge. Chirped attosecond pulse can be produced through the reflection of a counter-propagating probe laser off the accelerating REM. In the electron moving frame, the plasma frequency of the REM keeps decreasing due to its rapid expansion. The laser frequency, on the contrary, keeps increasing due to the acceleration of REM and the relativistic Doppler shift from the lab frame to the electron moving frame. Within an ultra-short time interval, the two frequencies will be equal in the electron moving frame, which leads to the resonance between laser and REM. The reflected radiation near this interval and corresponding spectra will be amplified due to the resonance. Through adjusting the arriving time of the probe laser, a certain part of the reflected field could be selectively amplified or depressed, leading to the selective adjustment of the corresponding spectra.

Antibiotics are designed to affect gut microbiota and subsequently gut homeostasis. However, limited information exists about short- and long-term effects of early antibiotic intervention (EAI) on gut homeostasis (especially for the small intestine) of pigs following antibiotic withdrawal. We investigated the impact of EAI on specific bacterial communities, microbial metabolites and mucosal immune parameters in the small intestine of later-growth-stage pigs fed with diets differing in CP levels. Eighteen litters of piglets were fed creep feed with or without antibiotics from day 7 to day 42. At day 42, pigs within each group were offered a normal- or low-CP diet. Five pigs per group were slaughtered at days 77 and 120. At day 77, EAI increased Enterobacteriaceae counts in the jejunum and ileum and decreased Bifidobacterium counts in the jejunum and ileum (P < 0.05). Moreover, tryptamine, putrescine, secretory immunoglobulin (Ig) A and IgG concentrations in the ileum and interleukin-10 (IL-10) mRNA and protein levels in the jejunum and ileum were decreased in pigs with EAI (P < 0.05). At day 120, EAI only suppressed Clostridium cluster XIVa counts in the jejunum and ileum (P < 0.05). These results suggest that EAI has a short-term effect on specific bacterial communities, amino acid decarboxylation and mucosal immune parameters in the small intestine (particularly in the ileum). At days 77 and 120, feeding a low-CP diet affected Bifidobacterium, Clostridium cluster IV, Clostridium cluster XIVa and Enterobacteriaceae counts in the jejunum or ileum (P < 0.05). Moreover, feeding a low-CP diet increased the concentrations of Igs in the jejunum and decreased pro-inflammatory cytokines levels in the jejunum and ileum (P < 0.05). At day 120, feeding a low-CP diet increased short-chain fatty acid concentrations, reduced ammonia and spermidine concentrations and up-regulated genes related to barrier function in the jejunum and ileum (P < 0.05). These results suggest that feeding a low-CP diet changes specific bacterial communities and intestinal metabolite concentrations and modifies mucosal immune parameters. These findings contribute to our understanding on the duration of the impact of EAI on gut homeostasis and may provide basis data for nutritional modification in young pigs after antibiotic treatment.