Explore the vast range of titles available.

Back pain and postural abnormalities are increasingly prevalent among primary school children and may persist into adulthood. This randomized controlled trial evaluated a 12-week web-based preventive back-care intervention for 141 children aged 6–11 years. The intervention group ( n  = 71) received exercise and back-oriented education videos, while the control group ( n  = 70) received only educational videos regarding general health promotion. Outcomes included short-term goals such as postural evaluation, back pain, and postural endurance, as well as prevention-oriented outcomes including trunk endurance, functional mobility, back-related knowledge, and psychological well-being (self-compassion and self-concept), complemented by parent-reported information. Exploratory analyses examined subgroup differences in program response. The intervention significantly increased back-related knowledge ( p  < .001, partial η² = 0.228) and positive self-compassion ( p  = .011, partial η² = 0.045), but did not lead to significant group differences in posture, back pain prevalence, trunk muscle endurance, functional mobility, self-concept, negative self-compassion, or daily sitting time. Adherence varied, and postural assessment was limited by the lack of a standard medical examination, which should be considered when interpreting the results. These findings highlight challenges in digital health promotion for young children and suggest that future programs may benefit from increased interactivity, parental involvement, and in-person components to effectively support spinal health in this age group.

Plant-associated microorganisms have been shown to critically affect host physiology and performance, suggesting that evolution and ecology of plants and animals can only be understood in a holobiont (host and its associated organisms) context. Host-associated microbial community structures are affected by abiotic and host factors, and increased attention is given to the role of the microbiome in interactions such as pathogen inhibition. However, little is known about how these factors act on the microbial community, and especially what role microbe-microbe interaction dynamics play. We have begun to address this knowledge gap for phyllosphere microbiomes of plants by simultaneously studying three major groups of Arabidopsis thaliana symbionts (bacteria, fungi and oomycetes) using a systems biology approach. We evaluated multiple potential factors of microbial community control: we sampled various wild A. thaliana populations at different times, performed field plantings with different host genotypes, and implemented successive host colonization experiments under lab conditions where abiotic factors, host genotype, and pathogen colonization was manipulated. Our results indicate that both abiotic factors and host genotype interact to affect plant colonization by all three groups of microbes. Considering microbe-microbe interactions, however, uncovered a network of interkingdom interactions with significant contributions to community structure. As in other scale-free networks, a small number of taxa, which we call microbial \"hubs,\" are strongly interconnected and have a severe effect on communities. By documenting these microbe-microbe interactions, we uncover an important mechanism explaining how abiotic factors and host genotypic signatures control microbial communities. In short, they act directly on \"hub\" microbes, which, via microbe-microbe interactions, transmit the effects to the microbial community. We analyzed two \"hub\" microbes (the obligate biotrophic oomycete pathogen Albugo and the basidiomycete yeast fungus Dioszegia) more closely. Albugo had strong effects on epiphytic and endophytic bacterial colonization. Specifically, alpha diversity decreased and beta diversity stabilized in the presence of Albugo infection, whereas they otherwise varied between plants. Dioszegia, on the other hand, provided evidence for direct hub interaction with phyllosphere bacteria. The identification of microbial \"hubs\" and their importance in phyllosphere microbiome structuring has crucial implications for plant-pathogen and microbe-microbe research and opens new entry points for ecosystem management and future targeted biocontrol. The revelation that effects can cascade through communities via \"hub\" microbes is important to understand community structure perturbations in parallel fields including human microbiomes and bioprocesses. In particular, parallels to human microbiome \"keystone\" pathogens and microbes open new avenues of interdisciplinary research that promise to better our understanding of functions of host-associated microbiomes.

Growth in the use of drones has been exponential in various fields due to their adaptable and cross-disciplinary functions. Incorporating this new technology into K–12 classrooms can be useful in engaging students and expanding their understanding of technology in the scientific workplace; however, beginners may run into challenges in designing meaningful lessons. To tackle the seemingly daunting task of using drones effectively for education, this article walks a novice instructor through various self-reflective questions in order to properly introduce a drone lesson and includes a number of resources to ensure proper safety and legal measures.

Background Traumatic shock is the leading cause of preventable death with most patients dying within the first six hours from arriving to the hospital. This underscores the importance of prehospital interventions, and growing evidence suggests prehospital transfusion improves survival. Optimizing transfusion triggers in the prehospital setting is key to improving outcomes for patients in hemorrhagic shock. Our objective was to identify factors associated with early in-hospital transfusion requirements available to prehospital clinicians in the field to develop a simple algorithm for prehospital transfusion, particularly for patients with occult shock. Methods We included trauma patients transported by a single critical care transport service to a level I trauma center between 2012 and 2019. We used logistic regression, Fast and Frugal Trees (FFTs), and Bayesian analysis to identify factors associated with early in-hospital blood transfusion as a potential trigger for prehospital transfusion. Results We included 2,157 patients transported from the scene or emergency department (ED) of whom 207 (9.60%) required blood transfusion within four hours of admission. The mean age was 47 (IQR = 28 – 62) and 1,480 (68.6%) patients were male. From 13 clinically relevant factors for early hospital transfusions, four were incorporated into the FFT in following order: 1) SBP, 2) prehospital lactate concentration, 3) Shock Index, 4) AIS of chest (sensitivity = 0.81, specificity = 0.71). The chosen thresholds were similar to conventional ones. Using conventional thresholds resulted in lower model sensitivity. Consistently, prehospital lactate was among most decisive factors of hospital transfusions identified by Bayesian analysis (OR = 2.31; 95% CI 1.55 – 3.37). Conclusions Using an ensemble of frequentist statistics, Bayesian analysis and machine learning, we developed a simple, clinically relevant prehospital algorithm to help identify patients requiring transfusion within 4 h of hospital arrival.

Most organisms use daily light/dark cycles as timing cues to control many essential physiological processes. In plants, growth rates of the embryonic stem (hypocotyl) are maximal at different times of day, depending on external photoperiod and the internal circadian clock. However, the interactions between light signaling, the circadian clock, and growth-promoting hormone pathways in growth control remain poorly understood. At the molecular level, such growth rhythms could be attributed to several different layers of time-specific control such as phasing of transcription, signaling, or protein abundance. To determine the transcriptional component associated with the rhythmic control of growth, we applied temporal analysis of the Arabidopsis thaliana seedling transcriptome under multiple growth conditions and mutant backgrounds using DNA microarrays. We show that a group of plant hormone-associated genes are coexpressed at the time of day when hypocotyl growth rate is maximal. This expression correlates with overrepresentation of a cis-acting element (CACATG) in phytohormone gene promoters, which is sufficient to confer the predicted diurnal and circadian expression patterns in vivo. Using circadian clock and light signaling mutants, we show that both internal coincidence of phytohormone signaling capacity and external coincidence with darkness are required to coordinate wild-type growth. From these data, we argue that the circadian clock indirectly controls growth by permissive gating of light-mediated phytohormone transcript levels to the proper time of day. This temporal integration of hormone pathways allows plants to fine tune phytohormone responses for seasonal and shade-appropriate growth regulation.

We used hybridization to the ATH1 gene expression array to interrogate genomic DNA diversity in 23 wild strains (accessions) of Arabidopsis thaliana (arabidopsis), in comparison with the reference strain Columbia (Col). At <1% false discovery rate, we detected 77,420 single-feature polymorphisms (SFPs) with distinct patterns of variation across the genome. Total and pair-wise diversity was higher near the centromeres and the heterochromatic knob region, but overall diversity was positively correlated with recombination rate (R² = 3.1%). The difference between total and pair-wise SFP diversity is a relative measure contrasting diversifying or frequency-dependent selection, similar to Tajima's D, and can be calibrated by the empirical genome-wide distribution. Each unique locus, centered on a gene, has a diversity and selection score that suggest a relative role in past evolutionary processes. Homologs of disease resistance (R) genes include members with especially high levels of diversity often showing frequency-dependent selection and occasionally evidence of a past selective sweep. Receptor-like and S-locus proteins also contained members with elevated levels of diversity and signatures of selection, whereas other gene families, bHLH, F-box, and RING finger proteins, showed more typical levels of diversity. SFPs identified with the gene expression array also provide an empirical hybridization polymorphism background for studies of gene expression polymorphism and are available through the genome browser http://signal.salk.edu/cgi-bin/AtSFP.

The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300–0.1 hPa) and are provided on a common latitude–pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O3) and water vapor (H2O), major long-lived trace gases (SF6, N2O, HF, CCl3F, CCl2F2, NOy), trace gases with intermediate lifetimes (HCl, CH4, CO, HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO, NO2, NOx, N2O5, HNO4), halogens (BrO, ClO, ClONO2, HOCl), and other minor species (OH, HO2, CH2O, CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979–2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO, NO2, and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the “golden age” of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020).

Plant-associated microorganisms have been shown to critically affect host physiology and performance, suggesting that evolution and ecology of plants and animals can only be understood in a holobiont (host and its associated organisms) context. Host-associated microbial community structures are affected by abiotic and host factors, and increased attention is given to the role of the microbiome in interactions such as pathogen inhibition. However, little is known about how these factors act on the microbial community, and especially what role microbe-microbe interaction dynamics play. We have begun to address this knowledge gap for phyllosphere microbiomes of plants by simultaneously studying three major groups of Arabidopsis thaliana symbionts (bacteria, fungi and oomycetes) using a systems biology approach. We evaluated multiple potential factors of microbial community control: we sampled various wild A. thaliana populations at different times, performed field plantings with different host genotypes, and implemented successive host colonization experiments under lab conditions where abiotic factors, host genotype, and pathogen colonization was manipulated. Our results indicate that both abiotic factors and host genotype interact to affect plant colonization by all three groups of microbes. Considering microbe-microbe interactions, however, uncovered a network of interkingdom interactions with significant contributions to community structure. As in other scale-free networks, a small number of taxa, which we call microbial \"hubs,\" are strongly interconnected and have a severe effect on communities. By documenting these microbe-microbe interactions, we uncover an important mechanism explaining how abiotic factors and host genotypic signatures control microbial communities. In short, they act directly on \"hub\" microbes, which, via microbe-microbe interactions, transmit the effects to the microbial community. We analyzed two \"hub\" microbes (the obligate biotrophic oomycete pathogen Albugo and the basidiomycete yeast fungus Dioszegia) more closely. Albugo had strong effects on epiphytic and endophytic bacterial colonization. Specifically, alpha diversity decreased and beta diversity stabilized in the presence of Albugo infection, whereas they otherwise varied between plants. Dioszegia, on the other hand, provided evidence for direct hub interaction with phyllosphere bacteria. The identification of microbial \"hubs\" and their importance in phyllosphere microbiome structuring has crucial implications for plant-pathogen and microbe-microbe research and opens new entry points for ecosystem management and future targeted biocontrol. The revelation that effects can cascade through communities via \"hub\" microbes is important to understand community structure perturbations in parallel fields including human microbiomes and bioprocesses. In particular, parallels to human microbiome \"keystone\" pathogens and microbes open new avenues of interdisciplinary research that promise to better our understanding of functions of host-associated microbiomes.

Brunkard et al . propose that the identification of novel LEAFY sequences contradicts our model of evolution through promiscuous intermediates. Based on the debate surrounding land plant phylogeny and on our analysis of these interesting novel sequences, we explain why there is no solid evidence to disprove our model.

Brunkard et al . propose that the identification of novel LEAFY sequences contradicts our model of evolution through promiscuous intermediates. Based on the debate surrounding land plant phylogeny and on our analysis of these interesting novel sequences, we explain why there is no solid evidence to disprove our model.