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Background Daily step counts is an intuitive metric that has demonstrated success in motivating physical activity in adults and may hold potential for future public health physical activity recommendations. This review seeks to clarify the pattern of the associations between daily steps and subsequent all-cause mortality, cardiovascular disease (CVD) morbidity and mortality, and dysglycemia, as well as the number of daily steps needed for health outcomes. Methods A systematic review was conducted to identify prospective studies assessing daily step count measured by pedometer or accelerometer and their associations with all-cause mortality, CVD morbidity or mortality, and dysglycemia (dysglycemia or diabetes incidence, insulin sensitivity, fasting glucose, HbA1c). The search was performed across the Medline, Embase, CINAHL, and the Cochrane Library databases from inception to August 1, 2019. Eligibility criteria included longitudinal design with health outcomes assessed at baseline and subsequent timepoints; defining steps per day as the exposure; reporting all-cause mortality, CVD morbidity or mortality, and/or dysglycemia outcomes; adults ≥18 years old; and non-patient populations. Results Seventeen prospective studies involving over 30,000 adults were identified. Five studies reported on all-cause mortality (follow-up time 4–10 years), four on cardiovascular risk or events (6 months to 6 years), and eight on dysglycemia outcomes (3 months to 5 years). For each 1000 daily step count increase at baseline, risk reductions in all-cause mortality (6–36%) and CVD (5–21%) at follow-up were estimated across a subsample of included studies. There was no evidence of significant interaction by age, sex, health conditions or behaviors (e.g., alcohol use, smoking status, diet) among studies that tested for interactions. Studies examining dysglycemia outcomes report inconsistent findings, partially due to heterogeneity across studies of glycemia-related biomarker outcomes, analytic approaches, and sample characteristics. Conclusions Evidence from longitudinal data consistently demonstrated that walking an additional 1000 steps per day can help lower the risk of all-cause mortality, and CVD morbidity and mortality in adults, and that health benefits are present below 10,000 steps per day. However, the shape of the dose-response relation is not yet clear. Data are currently lacking to identify a specific minimum threshold of daily step counts needed to obtain overall health benefit.

Background This study investigates the cross-sectional and prospective associations between accelerometer-measured sedentary behavior and body composition from adolescence to early adulthood. Methods Data from the Santiago Longitudinal Study were analyzed ( n  = 212). Sedentary time was measured at age 16 years, and body composition (body mass index [BMI], waist circumference, waist-to-height ratio [WHtR], fat mass percentage, and lean mass percentage) was examined at both age 16 and 23 years. Adjusted linear regression models estimated associations between sedentary time, sedentary bout duration, and body composition, overall and by sex. Results In all analyses, mean sedentary bout duration was not associated with body composition. In cross-sectional analyses, more sedentary time during adolescence was significantly associated with lower BMI, waist circumference, WHtR, fat mass percentage, and higher lean mass percentage ( p  < 0.05). One standard deviation increase in daily sedentary time was prospectively associated with lower body mass index ( β  = −1.22 kg/m 2 , 95% CI: −2.02, −0.42), waist circumference ( β  = −2.39 cm, 95% CI: −4.03, −0.75), and WHtR ( β  = −0.014, 95% CI: −0.024, −0.004). Sedentary time at 16 years was not associated with changes in body composition from 16 to 23 years. Conclusions Sedentary behavior in adolescence is not adversely associated with body composition profiles in early adulthood. Impact Little is known about the effect of device-measured sedentary behavior on body composition during the transition from adolescence to early adulthood. Among participants in the Santiago Longitudinal Study, more accelerometer-measured sedentary time during adolescence was associated with lower BMI, waist circumference, and waist-to-height ratio in early adulthood though point estimates were generally small in magnitude. Sedentary behavior in adolescence was not detrimentally associated with healthy body composition profiles in early adulthood. Public health interventions aimed at reducing obesity rates could consider other behaviors, such as physical activity and healthy diet, instead of sitting time.

Objectives: Prevention of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the disease COVID-19 is a public health priority. The efficacy of non-pharmaceutical interventions such as wearing face masks to prevent SARS-CoV-2 infection has been well established in controlled settings. However, evidence for the effectiveness of face masks in preventing SARS-CoV-2 transmission within real-world settings is limited and mixed. The present systematic review evaluated the effectiveness of face mask policies and mask wearing to prevent SARS-CoV-2 transmission and COVID-19 in real-world settings. Methods: Following PRISMA guidelines, scientific databases, and gray literature, were searched through June 2023. Inclusion criteria were as follows: (1) studies/reports written in or translated to English; (2) prospectively assessed incidence of SARS-CoV-2 or COVID-19; (3) assessed the behavior and/or policy of mask-wearing; and (4) conducted in community/public settings (i.e., not laboratory). Studies were excluded if they did not parse out data specific to the effect of mask wearing (behavior and/or policy) and subsequent SARS-CoV-2 transmission or COVID-19 disease or if they relied solely on statistical models to estimate the effects of mask wearing on transmission. A total of 2616 studies were initially identified, and 470 met inclusion and exclusion criteria for full-text review. The vote counting method was used to evaluate effectiveness, and risk of bias was assessed using JBI critical appraisal tools. Results: A total of 79 unique studies met the final inclusion criteria, and their data were abstracted and evaluated. Study settings included community/neighborhood settings (n = 34, 43%), healthcare settings (n = 30, 38%), and school/universities (n = 15, 19%). A majority of studies (n = 61, 77%) provided evidence to support the effectiveness of wearing face masks and/or face mask policies to reduce the transmission of SARS-CoV-2 and/or prevention of COVID-19. Effectiveness of mask wearing did not vary substantially by study design (67–100%), type of mask (77–100%), or setting (80–91%), while 85% of masking policies specifically reported a benefit. Conclusions: This systematic literature review supports public health recommendations and policies that encourage the public to wear face masks to reduce the risk of SARS-CoV-2 infection and COVID-19 in multiple real-world settings. Effective communication strategies are needed to encourage and support the use of face masks by the general public, particularly during peak infection cycles.

This cohort study uses national data to explore the dose-response association between guideline-recommended physical activity and mortality in older adults.

We used 2012-2015 data from the Colorado Pregnancy Risk Assessment Monitoring System to describe changes in self-reported physical activity (PA) before and during pregnancy and used logistic regression to examine factors associated with regular PA. The prevalence of regular PA (ie, 30 or more minutes per day on 5 or more days per week) was 19.1% before pregnancy and decreased to 10.2% during pregnancy. At both times, adjusted odds of regular PA were lower among women who were overweight or had obesity before pregnancy than among those with normal weight. Findings suggest that most women with a recent live birth in Colorado, particularly those who are overweight or have obesity, are not obtaining many health benefits of PA either before or during pregnancy.

Data on prospective associations of accelerometer-measured physical activity, sedentary behavior, and mortality among cancer survivors are lacking. Our study examined accelerometer-measured daily physical activity (including light, moderate to vigorous, total, and steps), sedentary behavior (sitting time and mean bout duration), and mortality among cancer survivors in the Women's Health Accelerometry Collaboration. Postmenopausal women in the Collaboration who reported a cancer diagnosis at least 1 year prior to wearing an ActiGraph GT3X+ device on the hip for at least 4 of 7 days from 2011 to 2015 were included. Outcomes included all-cause, cancer-related, and cardiovascular disease (CVD)-related mortality. Covariate-adjusted Cox regression estimated hazard ratios (HRs) and 95% CIs for each physical activity and sedentary behavior measure in association with mortality. Overall, 2479 cancer survivors (mean [SD] age, 74.2 [6.7] years) were followed up for 8.3 years. For all-cause mortality (n = 594 cases), every 78.1 minutes per day in light physical activity, 96.5 minutes per day in total physical activity, 102.2 minutes per day in sitting time, and 4.8 minutes in a sitting bout duration had hazard ratios of 0.92 (95% CI = 0.84 to 1.01), 0.89 (95% CI = 0.80 to 0.98), 1.12 (95% CI = 1.02 to 1.24), and 1.04 (95% CI = 0.96 to 1.12), respectively. Linear associations for cancer mortality (n = 168) and CVD mortality (n = 109) were not statistically significant, except for steps (hazard ratio per 2469 steps/d = 0.66, 95% CI = 0.45 to 0.96) and sitting time (hazard ratio = 1.30, 95% CI = 1.02 to 1.67) for CVD mortality. Nonlinear associations showed benefits of moderate to vigorous physical activity (for all-cause and CVD mortality) and steps (all-cause mortality only) maximized at approximately 60 minutes per day and 5000-6000 steps per day, respectively. Among postmenopausal cancer survivors, higher physical activity and lower sedentary behavior was associated with reduced hazards of all-cause and CVD mortality.

Background A genome-wide association study (GWAS) correlates variation in the genotype with variation in the phenotype across a cohort, but the causal gene mediating that impact is often unclear. When the phenotype is protein abundance, a reasonable hypothesis is that the gene encoding that protein is the causal gene. However, as variants impacting protein levels can occur thousands or even millions of base pairs from the gene encoding the protein, it is unclear at what distance this simple hypothesis breaks down. Results By making the simple assumption that cis-pQTLs should be distance dependent while trans-pQTLs are distance independent, we arrive at a simple and empirical distance cutoff separating cis- and trans-pQTLs. Analyzing a recent large-scale pQTL study (Pietzner in Science 374:eabj1541, 2021) we arrive at an estimated distance cutoff of 944 kilobasepairs (95% confidence interval: 767–1,161) separating the cis and trans regimes. Conclusions We demonstrate that this simple model can be applied to other molecular GWAS traits. Since much of biology is built on molecular traits like protein, transcript and metabolite abundance, we posit that the mathematical models for cis and trans distance distributions derived here will also apply to more complex phenotypes and traits.

Small-molecule dual hydrogen-bond (H-bond) donors such as ureas, thioureas, squaramides, and guanidinium ions enjoy widespread use as effective catalysts for promoting a variety of enantioselective reactions. However, these catalysts are only weakly acidic and therefore require highly reactive electrophilic substrates to be effective. We introduce here a mode of catalytic activity with chiral H-bond donors that enables enantioselective reactions of relatively unreactive electrophiles. Squaramides are shown to interact with silyl triflates by binding the triflate counterion to form a stable, yet highly Lewis acidic, complex. The silyl triflate-chiral squaramide combination promotes the generation of oxocarbenium intermediates from acetal substrates at low temperatures. Enantioselectivity in nucleophile additions to the cationic intermediates is then controlled through a network of noncovalent interactions between the squaramide catalyst and the oxocarbenium triflate.

Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time. High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur’s ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur . IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

Freshwater hyphomycetes are a highly diverse group of fungi with a worldwide distribution and have been mostly reported from tropical and subtropical regions. During investigations of freshwater fungi from the Greater Mekong subregion in China and Thailand, sixteen freshwater hyphomycetes (three of them belong to the class Dothideomycetes while thirteen belong to the class Sordariomycetes) were collected. Based on morphology and multi-gene phylogenetic analyses, Neospadicoides thailandica, Pseudodactylaria aquatica, Sporidesmium nujiangense, Tetraploa thailandica, Vamsapriyaaquatica and Wongia fusiformis are described as new species; Aquapteridospora bambusinum is proposed as a new combination; Acrodictys liputii, Chloridium gonytrichii, Pseudoberkleasmium chiangmaiense, Pleomonodictys capensis, Sporidesmium aturbinatum and Vamsapriya indica are reported as new country records; and Sporidesmium tropicale, Sporoschisma chiangraiense and Sporoschisma longicatenatum are introduced as three new collections. In addition, a checklist of freshwater fungi from China over the last five years is also provided.