By 13,000 BP human populations were present across North America, but the exact date of arrival to the continent, especially areas south of the continental ice sheets, remains unclear. Here we ...examine patterns in the stratigraphic integrity of early North American sites to gain insight into the timing of first colonization. We begin by modeling stratigraphic mixing of multicomponent archaeological sites to identify signatures of stratigraphic integrity in vertical artifact distributions. From those simulations, we develop a statistic we call the Apparent Stratigraphic Integrity Index (ASI), which we apply to pre- and post-13,000 BP archaeological sites north and south of the continental ice sheets. We find that multiple early Beringian sites dating between 13,000 and 14,200 BP show excellent stratigraphic integrity. Clear signs of discrete and minimally disturbed archaeological components do not appear south of the ice sheets until the Clovis period. These results provide support for a relatively late date of human arrival to the Americas.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host-pathogen associations and ...short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with 'ancient DNA' data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10
to 10
nucleotide substitutions per site year
. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria.
Shigella are human-adapted Escherichia coli that have gained the ability to invade the human gut mucosa and cause dysentery(1,2), spreading efficiently via low-dose fecal-oral transmission(3,4). ...Historically, S. sonnei has been predominantly responsible for dysentery in developed countries but is now emerging as a problem in the developing world, seeming to replace the more diverse Shigella flexneri in areas undergoing economic development and improvements in water quality(4-6). Classical approaches have shown that S. sonnei is genetically conserved and clonal(7). We report here whole-genome sequencing of 132 globally distributed isolates. Our phylogenetic analysis shows that the current S. sonnei population descends from a common ancestor that existed less than 500 years ago and that diversified into several distinct lineages with unique characteristics. Our analysis suggests that the majority of this diversification occurred in Europe and was followed by more recent establishment of local pathogen populations on other continents, predominantly due to the pandemic spread of a single, rapidly evolving, multidrug-resistant lineage.
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Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
IMPORTANCE: Bedside monitor alarms alert nurses to life-threatening physiologic changes among patients, but the response times of nurses are slow. OBJECTIVE: To identify factors associated with ...physiologic monitor alarm response time. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study used 551 hours of video-recorded care administered by 38 nurses to 100 children in a children’s hospital medical unit between July 22, 2014, and November 11, 2015. EXPOSURES: Patient, nurse, and alarm-level factors hypothesized to predict response time. MAIN OUTCOMES AND MEASURES: We used multivariable accelerated failure-time models stratified by each nurse and adjusted for clustering within patients to evaluate associations between exposures and response time to alarms that occurred while the nurse was outside the room. RESULTS: The study participants included 38 nurses, 100% (n = 38) of whom were white and 92% (n = 35) of whom were female, and 100 children, 51% (n = 51) of whom were male. The race/ethnicity of the child participants was 45% (n = 45) black or African American, 33% (n = 33) white, 4% (n = 4) Asian, and 18% (n = 18) other. Of 11 745 alarms among 100 children, 50 (0.5%) were actionable. The adjusted median response time among nurses was 10.4 minutes (95% CI, 5.0-15.8) and varied based on the following variables: if the patient was on complex care service (5.3 minutes 95% CI, 1.4-9.3 vs 11.1 minutes 95% CI, 5.6-16.6 among general pediatrics patients), whether family members were absent from the patient’s bedside (6.3 minutes 95% CI, 2.2-10.4 vs 11.7 minutes 95% CI, 5.9-17.4 when family present), whether a nurse had less than 1 year of experience (4.4 minutes 95% CI, 3.4-5.5 vs 8.8 minutes 95% CI, 7.2-10.5 for nurses with 1 or more years of experience), if there was a 1 to 1 nursing assignment (3.5 minutes 95% CI, 1.3-5.7 vs 10.6 minutes 95% CI, 5.3-16.0 for nurses caring for 2 or more patients), if there were prior alarms requiring intervention (5.5 minutes 95% CI, 1.5-9.5 vs 10.7 minutes 5.2-16.2 for patients without intervention), and if there was a lethal arrhythmia alarm (1.2 minutes 95% CI, −0.6 to 2.9 vs 10.4 minutes 95% CI, 5.1-15.8 for alarms for other conditions). Each hour that elapsed during a nurse’s shift was associated with a 15% longer response time (6.1 minutes 95% CI, 2.8-9.3 in hour 2 vs 14.1 minutes 95% CI, 6.4-21.7 in hour 8). The number of nonactionable alarms to which the nurse was exposed in the preceding 120 minutes was not associated with response time. CONCLUSIONS AND RELEVANCE: Response time was associated with factors that likely represent the heuristics nurses use to assess whether an alarm represents a life-threatening condition. The nurse to patient ratio and physical and mental fatigue (measured by the number of hours into a shift) represent modifiable factors associated with response time. Chronic alarm fatigue resulting from long-term exposure to nonactionable alarms may be a more important determinant of response time than short-term exposure.
Neural crest cells migrate throughout the embryo, but how cells move in a directed and collective manner has remained unclear. Here, we perform the first single-cell transcriptome analysis of cranial ...neural crest cell migration at three progressive stages in chick and identify and establish hierarchical relationships between cell position and time-specific transcriptional signatures. We determine a novel transcriptional signature of the most invasive neural crest Trailblazer cells that is consistent during migration and enriched for approximately 900 genes. Knockdown of several Trailblazer genes shows significant but modest changes to total distance migrated. However, in vivo expression analysis by RNAscope and immunohistochemistry reveals some salt and pepper patterns that include strong individual Trailblazer gene expression in cells within other subregions of the migratory stream. These data provide new insights into the molecular diversity and dynamics within a neural crest cell migratory stream that underlie complex directed and collective cell behaviors.
Abstract Background Associations of bone mineral density (BMD) with specific food components, including dietary fiber and isoflavones (that have a negative association with serum estrogen), are ...unclear and need to be determined, particularly in populations more likely to consume large amounts of these nutrients (such as young athletes). Objective To determine dietary intake of specific food components in athletes with oligoamenorrhea (OA) compared to athletes with eumenorrhea (EA) and nonathletes (NA), and associations of the dietary intake of these nutrients with lumbar spine BMD. Design and subjects This cross-sectional study evaluated 68 OA, 24 EA, and 26 NA individuals aged 14 to 23 years. Measurements included 4-day food records, a dual x-ray absorptiometry scan evaluating lumbar spine BMD and body composition, and hormone levels. Multivariate analysis was used to estimate associations of nutrients with lumbar spine BMD. Results Compared with EA and NA, OA had higher intake of fiber, phytic acid, and vegetable protein (all P values <0.0001). Intake of isoflavones, genistein, and daidzein was higher in OA than NA ( P =0.003 and P= 0.0002, respectively). OA had lower consumption of energy from saturated fatty acids than NA ( P =0.002). After controlling for confounders such as body weight, menstrual status (indicative of estrogen status), calcium intake, and serum vitamin D (known BMD determinants), lumbar spine BMD z scores were inversely associated with dietary fiber (β=–.30; P =0.01), vegetable protein (β= –.28; P =0.02), phytic acid (β=–.27; P =0.02), genistein (β=–.25; P =0.01), and daidzein (β=–.24; P =0.01), and positively associated with percent energy from fatty acids (β=.32; P =0.0006). Conclusions Compared with EA and NA, OA had a higher dietary intake of fiber, vegetable protein, and phytic acid, which were inversely associated with lumbar spine BMD z scores. Further studies are needed to assess dietary recommendations for OA to optimize bone accrual.
Rapid response systems (RRSs) aim to identify and rescue hospitalized patients whose condition is deteriorating before respiratory or cardiac arrest occurs. Previous studies of RRS implementation ...have shown variable effectiveness, which may be attributable in part to barriers preventing staff from activating the system.
To proactively identify barriers to calling for urgent assistance that exist despite recent implementation of a comprehensive RRS in a children's hospital.
Qualitative study using open-ended, semistructured interviews of 27 nurses and 30 physicians caring for patients in general medical and surgical care areas.
The following themes emerged: (1) Self-efficacy in recognizing deteriorating conditions and activating the medical emergency team (MET) were considered strong determinants of whether care would be appropriately escalated for children in a deteriorating condition. (2) Intraprofessional and interprofessional hierarchies were sometimes challenging to navigate and led to delays in care for patients whose condition was deteriorating. (3) Expectations of adverse interpersonal or clinical outcomes from MET activations and intensive care unit transfers could strongly shape escalation-of-care behavior (eg, reluctance among subspecialty attending physicians to transfer patients to the intensive care unit for fear of inappropriate management).
The results of this study provide an in-depth description of the barriers that may limit RRS effectiveness. By recognizing and addressing these barriers, hospital leaders may be able to improve the RRS safety culture and thus enhance the impact of the RRS on rates of cardiac arrest, respiratory arrest, and mortality outside the intensive care unit.
Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important ...component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance.
We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models.
Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Woolly mammoths in mainland Alaska overlapped with the region's first people for at least a millennium. However, it is unclear how mammoths used the space shared with people. Here, we use detailed ...isotopic analyses of a female mammoth tusk found in a 14,000-year-old archaeological site to show that she moved ~1000 kilometers from northwestern Canada to inhabit an area with the highest density of early archaeological sites in interior Alaska until her death. DNA from the tusk and other local contemporaneous archaeological mammoth remains revealed that multiple mammoth herds congregated in this region. Early Alaskans seem to have structured their settlements partly based on mammoth prevalence and made use of mammoths for raw materials and likely food.
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