The impact of digital contact tracing on the SARS-CoV-2 pandemic-a comprehensive modelling study.

Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions ( R 0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.

Proposed search for a fourth neutrino with a PBq antineutrino source.

Several observed anomalies in neutrino oscillation data can be explained by a hypothetical fourth neutrino separated from the three standard neutrinos by a squared mass difference of a few eV(2). We show that this hypothesis can be tested with a PBq (ten kilocurie scale) (144)Ce or (106)Ru antineutrino beta source deployed at the center of a large low background liquid scintillator detector. In particular, the compact size of such a source could yield an energy-dependent oscillating pattern in event spatial distribution that would unambiguously determine neutrino mass differences and mixing angles.

Glucose- and glucokinase-controlled mal gene expression in Escherichia coli.

MalT is the central transcriptional activator of all mal genes in Escherichia coli. Its activity is controlled by the inducer maltotriose. It can be inhibited by the interaction with certain proteins, and its expression can be controlled. We report here a novel aspect of mal gene regulation: the effect of cytoplasmic glucose and glucokinase (Glk) on the activity and the expression of MalT. Amylomaltase (MalQ) is essential for the metabolism of maltose. It forms maltodextrins and glucose from maltose or maltodextrins. We found that glucose above a concentration of 0.1 mM blocked the activity of the enzyme. malQ mutants when grown in the absence of maltodextrins are endogenously induced by maltotriose that is derived from the degradation of glycogen. Therefore, the fact that glk malQ(+) mutants showed elevated mal gene expression finds its explanation in the reduced ability to remove glucose from MalQ-catalyzed maltodextrin formation and is caused by a metabolically induced MalQ(-) phenotype. However, even in mutants lacking glycogen, Glk controls endogenous induction. We found that overexpressed Glk due to its structural similarity with Mlc, the repressor of malT, binds to the glucose transporter (PtsG), releasing Mlc and thus increasing malT repression. In addition, even in mutants lacking Mlc (and glycogen), the overexpression of glk leads to a reduction in mal gene expression. We interpret this repression by a direct interaction of Glk with MalT concomitant with MalT inhibition. This repression was dependent on the presence of either maltodextrin phosphorylase or amylomaltase and led to the inactivation of MalT.

Maltose and maltodextrin utilization by Bacillus subtilis.

Bacillus subtilis can utilize maltose and maltodextrins that are derived from polysaccharides, like starch or glycogen. In this work, we show that maltose is taken up by a member of the phosphoenolpyruvate-dependent phosphotransferase system and maltodextrins are taken up by a maltodextrin-specific ABC transporter. Uptake of maltose by the phosphoenolpyruvate-dependent phosphotransferase system is mediated by maltose-specific enzyme IICB (MalP; synonym, GlvC), with an apparent K(m) of 5 microM and a V(max) of 91 nmol . min(-1) . (10(10) CFU)(-1). The maltodextrin-specific ABC transporter is composed of the maltodextrin binding protein MdxE (formerly YvdG), with affinities in the low micromolar range for maltodextrins, and the membrane-spanning components MdxF and MdxG (formerly YvdH and YvdI, respectively), as well as the energizing ATPase MsmX. Maltotriose transport occurs with an apparent K(m) of 1.4 microM and a V(max) of 4.7 nmol . min(-1) . (10(10) CFU)(-1).