Metacognition and lifelong e-learning: a contextual and cyclical process

Metacognition is arguably an important conceptualisation within the area of lifelong e- learning, with many theorists and practitioners claiming that it enhances the learning process. However, the lifelong, cyclical and flexible aspects of 'before', 'during' and 'after' metacognitions within lifelong e-learning (inclusive of whether an 'input' necessarily leads to a completed 'output') seem marginal within current areas of practical and theoretical debate. This article analyses Reeves's (1997) model of web-based learning in the context of the ADAPT project; a study of lifelong learners based in small and medium sized enterprises. The article focuses upon an analysis of this model's view of metacognition, and in the light of the project findings and literature review, aims to put forward an extended and expanded version of the model with reference to lifelong e-learnin

Modeling the Subsurface Structure of Sunspots

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local helioseismology is the only means by which we can investigate subphotospheric structure. However, as current linear inversion techniques do not yet allow helioseismology to probe the internal structure with sufficient confidence to distinguish between the monolith and cluster models, the development of physically realistic sunspot models are a priority for helioseismologists. This is because they are not only important indicators of the variety of physical effects that may influence helioseismic inferences in active regions, but they also enable detailed assessments of the validity of helioseismic interpretations through numerical forward modeling. In this paper, we provide a critical review of the existing sunspot models and an overview of numerical methods employed to model wave propagation through model sunspots. We then carry out an helioseismic analysis of the sunspot in Active Region 9787 and address the serious inconsistencies uncovered by \citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find that this sunspot is most probably associated with a shallow, positive wave-speed perturbation (unlike the traditional two-layer model) and that travel-time measurements are consistent with a horizontal outflow in the surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic

Role of the microbiome in regulating bone metabolism and susceptibility to osteoporosis

The human microbiota functions at the interface between diet, medication-use, lifestyle, host immune development and health. It is therefore closely aligned with many of the recognised modifiable factors that influence bone mass accrual in the young, and bone maintenance and skeletal decline in older populations. While understanding of the relationship between micro-organisms and bone health is still in its infancy, two decades of broader microbiome research and discovery supports a role of the human gut microbiome in the regulation of bone metabolism and pathogenesis of osteoporosis as well as its prevention and treatment. Pre-clinical research has demonstrated biological interactions between the microbiome and bone metabolism. Furthermore, observational studies and randomized clinical trials have indicated that therapeutic manipulation of the microbiota by oral administration of probiotics may influence bone turnover and prevent bone loss in humans. In this paper, we summarize the content, discussion and conclusions of a workshop held by the Osteoporosis and Bone Research Academy of the Royal Osteoporosis Society in October, 2020. We provide a detailed review of the literature examining the relationship between the microbiota and bone health in animal models and in humans, as well as formulating the agenda for key research priorities required to advance this field. We also underscore the potential pitfalls in this research field that should be avoided and provide methodological recommendations to facilitate bridging the gap from promising concept to a potential cause and intervention target for osteoporosis

Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology

Publisher Copyright: © 2022, The Author(s).Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (ORIDD = 0.92, P = 1.6 × 10−39; ORdorsalgia = 0.92, P = 7.2 × 10−15) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10−11); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes.Peer reviewe

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits

Large-Eddy Simulations of Magnetohydrodynamic Turbulence in Heliophysics and Astrophysics

We live in an age in which high-performance computing is transforming the way we do science. Previously intractable problems are now becoming accessible by means of increasingly realistic numerical simulations. One of the most enduring and most challenging of these problems is turbulence. Yet, despite these advances, the extreme parameter regimes encountered in space physics and astrophysics (as in atmospheric and oceanic physics) still preclude direct numerical simulation. Numerical models must take a Large Eddy Simulation (LES) approach, explicitly computing only a fraction of the active dynamical scales. The success of such an approach hinges on how well the model can represent the subgrid-scales (SGS) that are not explicitly resolved. In addition to the parameter regime, heliophysical and astrophysical applications must also face an equally daunting challenge: magnetism. The presence of magnetic fields in a turbulent, electrically conducting fluid flow can dramatically alter the coupling between large and small scales, with potentially profound implications for LES/SGS modeling. In this review article, we summarize the state of the art in LES modeling of turbulent magnetohydrodynamic (MHD) ows. After discussing the nature of MHD turbulence and the small-scale processes that give rise to energy dissipation, plasma heating, and magnetic reconnection, we consider how these processes may best be captured within an LES/SGS framework. We then consider several special applications in heliophysics and astrophysics, assessing triumphs, challenges,and future directions

Functional Annotation of ESR1 Gene Fusions in Estrogen Receptor-Positive Breast Cancer

RNA sequencing (RNA-seq) detects estrogen receptor alpha gene (ESR1) fusion transcripts in estrogen receptor-positive (ER+) breast cancer, but their role in disease pathogenesis remains unclear. We examined multiple ESR1 fusions and found that two, both identified in advanced endocrine treatment-resistant disease, encoded stable and functional fusion proteins. In both examples, ESR1-e6>YAP1 and ESR1-e6>PCDH11X, ESR1 exons 1–6 were fused in frame to C-terminal sequences from the partner gene. Functional properties include estrogen-independent growth, constitutive expression of ER target genes, and anti-estrogen resistance. Both fusions activate a metastasis-associated transcriptional program, induce cellular motility, and promote the development of lung metastasis. ESR1-e6>YAP1- and ESR1-e6>PCDH11X-induced growth remained sensitive to a CDK4/6 inhibitor, and a patient-derived xenograft (PDX) naturally expressing the ESR1-e6>YAP1 fusion was also responsive. Transcriptionally active ESR1 fusions therefore trigger both endocrine therapy resistance and metastatic progression, explaining the association with fatal disease progression, although CDK4/6 inhibitor treatment is predicted to be effective. Lei et al. show that transcriptionally active estrogen receptor gene (ESR1) fusions identified from late-stage, treatment-refractory estrogen receptor-positive (ER+) breast cancer drive pan-endocrine therapy resistance and metastatic progression. Growth of breast tumors driven by ESR1 fusions at primary and metastatic sties can be suppressed with a CDK4/6 inhibitor

Fast determination of the relative elemental and organic carbon content of aerosol samples by on-line single-particle aerosol time-of-flight mass spectrometry.

Different particulate matter (PM) samples were investigated by on-line single-particle aerosol time-of-flight mass spectrometry (ATOFMS). The samples consist of soot particulates made by a diffusion flame soot generator (combustion aerosol standard, CAST), industrially produced soot material (printex), soot from a diesel passenger car as well as ambient particulates (urban dust (NIST) and road tunnel dust). Five different CAST soot particle samples were generated with different elemental carbon (EC) and organic carbon (OC) content. The samples were reaerosolized and on-line analyzed by ATOFMS, as well as precipitated on quartz filters for conventional EC/OC analysis. For each sample ca. 1000 ATOFMS single-particle mass spectra were recorded and averaged. A typical averaged soot ATOFMS mass spectrum shows characteristic carbon cluster peak progressions (Cn+) as well as hydrogen-poor carbon cluster peaks (CnH(1-3)+). These peaks are originated predominately from the elemental carbon (EC) content of the particles. Often additional peaks, which are not due to carbon clusters, are observed, which either are originated from organic compounds (OC-organic carbon), or from the non-carbonaceous inorganic content of the particles. By classification of the mass spectral peaks as elemental carbon (i.e., the carbon cluster progression peaks) or as peaks originated from organic compounds (i.e., molecular and fragment ions), the relative abundance of elemental (EC) and organic carbon (OC) can be determined. The dimensionless TC/EC values, i.e., the ratio of total carbon content (TC, TC = OC + EC) to elemental carbon (EC), were derived from the ATOFMS single-particle aerosol mass spectrometry data. The EC/TC values measured by ATOFMS were compared with the TC/EC values determined by the thermal standard techniques (thermooptical and thermocoulometric method). A good agreement between the EC/TC values obtained by on-line ATOFMS and the offline standard method was found