DIABETES AND TECHNOLOGY FOR INCREASED ACTIVITY (DaTA)

Physical inactivity is a primary target for prevention of cardiovascular disease and type 2 diabetes. Rural Canadians are at increased risk of metabolic syndrome - a clustering of risk factors preceding these conditions. This study investigated feasibility and effectiveness of a stage-matched physical activity intervention using novel self­ monitoring technologies in rural adults with metabolic syndrome. Adherence to self­ monitoring protocols was \u3e94%. Stage of change increased by 1 stage (p=0.001). Physical activity increased from 5579 ± 1964 steps/day at week 1 to 7818 ± 4235 steps/day at week 8 (p=0.02). V02max increased by 17% (p\u3c0.05). BMI decreased from 33.1 to 32.7 (p=0.016). Participants were comfortable using the technology, found it easy- to-use, of low burden, and perceived it positively. This pilot study shows that this stage- matched technology intervention for increased physical activity was feasible and effective in high-risk adults in rural Ontario

Safety, immunogenicity, and reactogenicity of BNT162b2 and mRNA-1273 COVID-19 vaccines given as fourth-dose boosters following two doses of ChAdOx1 nCoV-19 or BNT162b2 and a third dose of BNT162b2 (COV-BOOST): a multicentre, blinded, phase 2, randomised trial

Background Some high-income countries have deployed fourth doses of COVID-19 vaccines, but the clinical need, effectiveness, timing, and dose of a fourth dose remain uncertain. We aimed to investigate the safety, reactogenicity, and immunogenicity of fourth-dose boosters against COVID-19.Methods The COV-BOOST trial is a multicentre, blinded, phase 2, randomised controlled trial of seven COVID-19 vaccines given as third-dose boosters at 18 sites in the UK. This sub-study enrolled participants who had received BNT162b2 (Pfizer-BioNTech) as their third dose in COV-BOOST and randomly assigned them (1:1) to receive a fourth dose of either BNT162b2 (30 µg in 0·30 mL; full dose) or mRNA-1273 (Moderna; 50 µg in 0·25 mL; half dose) via intramuscular injection into the upper arm. The computer-generated randomisation list was created by the study statisticians with random block sizes of two or four. Participants and all study staff not delivering the vaccines were masked to treatment allocation. The coprimary outcomes were safety and reactogenicity, and immunogenicity (antispike protein IgG titres by ELISA and cellular immune response by ELISpot). We compared immunogenicity at 28 days after the third dose versus 14 days after the fourth dose and at day 0 versus day 14 relative to the fourth dose. Safety and reactogenicity were assessed in the per-protocol population, which comprised all participants who received a fourth-dose booster regardless of their SARS-CoV-2 serostatus. Immunogenicity was primarily analysed in a modified intention-to-treat population comprising seronegative participants who had received a fourth-dose booster and had available endpoint data. This trial is registered with ISRCTN, 73765130, and is ongoing.Findings Between Jan 11 and Jan 25, 2022, 166 participants were screened, randomly assigned, and received either full-dose BNT162b2 (n=83) or half-dose mRNA-1273 (n=83) as a fourth dose. The median age of these participants was 70·1 years (IQR 51·6–77·5) and 86 (52%) of 166 participants were female and 80 (48%) were male. The median interval between the third and fourth doses was 208·5 days (IQR 203·3–214·8). Pain was the most common local solicited adverse event and fatigue was the most common systemic solicited adverse event after BNT162b2 or mRNA-1273 booster doses. None of three serious adverse events reported after a fourth dose with BNT162b2 were related to the study vaccine. In the BNT162b2 group, geometric mean anti-spike protein IgG concentration at day 28 after the third dose was 23 325 ELISA laboratory units (ELU)/mL (95% CI 20 030–27 162), which increased to 37 460 ELU/mL (31 996–43 857) at day 14 after the fourth dose, representing a significant fold change (geometric mean 1·59, 95% CI 1·41–1·78). There was a significant increase in geometric mean anti-spike protein IgG concentration from 28 days after the third dose (25 317 ELU/mL, 95% CI 20 996–30 528) to 14 days after a fourth dose of mRNA-1273 (54 936 ELU/mL, 46 826–64 452), with a geometric mean fold change of 2·19 (1·90–2·52). The fold changes in anti-spike protein IgG titres from before (day 0) to after (day 14) the fourth dose were 12·19 (95% CI 10·37–14·32) and 15·90 (12·92–19·58) in the BNT162b2 and mRNA-1273 groups, respectively. T-cell responses were also boosted after the fourth dose (eg, the fold changes for the wild-type variant from before to after the fourth dose were 7·32 [95% CI 3·24–16·54] in the BNT162b2 group and 6·22 [3·90–9·92] in the mRNA-1273 group).Interpretation Fourth-dose COVID-19 mRNA booster vaccines are well tolerated and boost cellular and humoral immunity. Peak responses after the fourth dose were similar to, and possibly better than, peak responses after the third dose

Myopic risk-seeking: The impact of narrow decision bracketing on lottery play

Decision framing, Bracketing, State lotteries, Myopic loss aversion, Peanuts effect, Gambling, C91, D81, I30,

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software

Constraining the magnitude of the Chiral Magnetic Effect with Event Shape Engineering in Pb-Pb collisions at sNN\sqrt{s_{\rm NN}} = 2.76$ TeV

In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow $v_2$ reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb-Pb collisions at $\sqrt{s_{_{\rm NN}}} =2.76$ TeV. The two-particle correlator $\langle \cos(\varphi_\alpha - \varphi_\beta) \rangle$, calculated for different combinations of charges $\alpha$ and $\beta$, is almost independent of $v_2$ (for a given centrality), while the three-particle correlator $\langle \cos(\varphi_\alpha + \varphi_\beta - 2\Psi_2) \rangle$ scales almost linearly both with the event $v_2$ and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on $v_2$ points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10-50% centrality interval is found to be 26-33% at 95% confidence level

Constraining the magnitude of the chiral magnetic effect with event shape engineering in Pb–Pb collisions at √sNN=2.76 TeV

In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow v2 reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb–Pb collisions at √sNN=2.76 TeV. The two-particle correlator 〈cos⁡(φα−φβ)〉, calculated for different combinations of charges α and β, is almost independent of v2 (for a given centrality), while the three-particle correlator 〈cos⁡(φα+φβ−2Ψ2)〉 scales almost linearly both with the event v2 and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on v2 points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10–50% centrality interval is found to be 26–33% at 95% confidence level