Action Research for Improving At-Risk Students\u27 Literacy Skills: The professional development of three Florida teachers through their journeys integrating technology, poetry and multiculturalism for literacy intervention

Abstract This study focuses on three case studies of three Florida teachers’ action research projects focusing on improving at-risk students’ literacy skills through innovative instructional technology, culturally-relevant poetry and bilingual teaching. The teachers, White, African American and Latina, describe their research journeys, the literacy teaching strategies they used and the outcomes on their students’ achievement. The case studies are then analyzed focusing on the effects the action research projects had on the participating teachers. The analysis explores transformative processes in the teachers’ epistemological shifts, acquisition of skills, attitudes and dispositions, as well as professional development and personal transformation. The findings indicate that action research is an important tool leading to improved classroom practice, leadership agency and a stronger commitment toward emancipatory educational action

A SkyMapper view of the large magellanic cloud: The dynamics of stellar populations

We present the first SkyMapper stellar population analysis of the Large Magellanic Cloud (hereafter LMC), including the identification of 3578 candidate Carbon Stars through their extremely red g − r colours. Coupled with Gaia astrometry, we analyse the distribution and kinematics of this Carbon Star population, finding the LMC to be centred at (RA, Dec.) = (80.90 ◦ ± 0.29, −68.74 ◦ ± 0.12), with a bulk proper motion of (μ α , μ δ ) = (1.878 ± 0.007, 0.293 ± 0.018) mas yr −1 and a disc inclination of i = 25.6 ◦ ± 1.1 at position angle θ = 135.6 ◦ ± 3.3 ◦ . We complement this study with the identification and analysis of additional stellar populations, finding that the dynamical centre for red giant branch stars is similar to that seen for the Carbon Stars, whereas for young stars the dynamical centre is significantly offset from the older populations. This potentially indicates that the young stars were formed as a consequence of a strong tidal interaction, probably with the Small Magellanic Cloud. In terms of internal dynamics, the tangential velocity profile increases linearly within ∼3 kpc, after which it maintains an approximately constant value of V rot = 83.6 ± 1.7 km s−1 until ∼7 kpc. With an asymmetric drift correction, we estimate the mass within 7 kpc to be M LMC (< 7 kpc) = (2.5 ± 0.1) × 10 10 M ⊙ and within the tidal radius (∼30 kpc) to be M LMC (< 30 kpc) = (1.06 ± 0.32) × 10 11 M ⊙ , consistent with other recent measurements.ZW gratefully acknowledges financial support through a the Dean’s International Postgraduate Research Scholarship from the Physics School of the University of Sydney. DM holds an Australian Research Council (ARC) Future Fellowship (FT160100206). We thank the anonymous reviewer for their constructive suggestions. The national facility capability for SkyMapper has been funded through ARC LIEF grant LE130100104 from the Australian Research Council, awarded to the University of Sydney, the Australian National University, Swinburne University of Technology, the University of Queensland, the University of Western Australia, the University of Melbourne, Curtin University of Technology, Monash University and the Australian Astronomical Observator

On the origin of the Monoceros Ring - I. Kinematics, proper motions, and the nature of the progenitor

TheMonoceros Ring (MRi) structure is an apparent stellar overdensity that has been postulated to entirely encircle the Galactic plane and has been variously described as being due to lineof- sight effects of the Galactic warp and flare or of extragalactic origin (via accretion). Despite being intensely scrutinized in the literature for more than a decade, no studies to date have been able to definitively uncover its origins. Here we use N-body simulations and a genetic algorithm to explore the parameter space for the initial position, orbital parameters, and, for the first time, the final location of a satellite progenitor. We fit our models to the latest Pan-STARRS data to determine whether an accretion scenario is capable of producing an inplane ring-like structure matching the known parameters of the MRi. Our simulations produce streams that closely match the location, proper motion, and kinematics of the MRi structure. However, we are not able to reproduce the mass estimates from earlier studies based on Pan- STARRS data. Furthermore, in contrast to earlier studies, our best-fitting models are those for progenitors on retrograde orbits. If the MRi was produced by satellite accretion, we find that its progenitor has an initial mass upper limit of ~ 1010M⊙ and the remnant is likely located behind the Galactic bulge, making it difficult to locate observationally. While our models produce realistic MRi-like structures, we cannot definitively conclude that the MRi was produced by the accretion of a satellite galaxy.RRL acknowledges support by the Chilean Ministry of Economy, Development, and Tourism’s Millennium Science Initiative through grant IC120009, awarded to the Millennium Institute of Astrophysics (MAS). RRL also acknowledges support from the STFC/Newton Fund ST/M007995/1 and the CONICYT/Newton Fund DPI20140114. BCC acknowledges the support of the Australian Research Council through Discovery project DP150100862. AYQH was supported by a National Science Foundation Graduate Research Fellowship under Grant No. DGE-1144469. The authors acknowledge the University of Sydney HPC service at the University of Sydney for providing HPC resources that have contributed to the research results reported within this paper

Mental health of migrants with pre-migration exposure to armed conflict: a systematic review and meta-analysis.

BACKGROUND Exposure to armed conflict has been associated with negative mental health consequences. We aimed to estimate the prevalence of generalised anxiety disorder, major depressive disorder, and post-traumatic stress disorder among migrants exposed to armed conflict. METHODS In this systematic review and meta-analysis, we searched online databases (Cochrane Library, Embase, LILACS, PsycInfo [via Ovid], PubMed, and Web of Science Core Collection) for relevant observational studies published between Jan 1, 1994, and June 28, 2021. We included studies that used standardised psychiatric interviews to assess generalised anxiety disorder, major depressive disorder, or post-traumatic stress disorder among migrants (refugees or internally displaced persons; aged ≥18 years) with pre-migration exposure to armed conflict. We excluded studies in which exposure to armed conflict could not be ascertained, studies that included a clinical population or people with chronic diseases that can trigger the onset of mental disease, and studies published before 1994. We used a random effects model to estimate each mental health disorder's pooled prevalence and random effects meta-regression to assess sources of heterogeneity. Two independent reviewers assessed the risk of bias for each study using the Joanna Briggs Institute Checklist for Prevalence Studies. The protocol was registered with PROSPERO, CRD42020209251. FINDINGS Of the 13 935 studies identified, 34 met our inclusion criteria; these studies accounted for 15 549 migrants. We estimated a prevalence of current post-traumatic stress disorder of 31% (95% CI 23-40); prevalence of current major depressive disorder of 25% (17-34); and prevalence of generalised anxiety disorder of 14% (5-35). Younger age was associated with a higher prevalence of current post-traumatic stress disorder (odds ratio 0·95 [95% CI 0·90-0·99]), lifetime post-traumatic stress disorder (0·88 [0·83-0·92]), and current generalised anxiety disorder (0·87 [0·78-0·97]). A longer time since displacement was associated with a lower lifetime prevalence of post-traumatic stress disorder (0·88 [0·81-0·95]) and major depressive disorder (0·81 [0·77-0·86]). Migrating to a middle-income (8·09 [3·06-21·40]) or low-income (39·29 [11·96-129·70]) country was associated with increased prevalence of generalised anxiety disorder. INTERPRETATION Migrants who are exposed to armed conflict are at high risk of mental health disorders. The mental health-care needs of migrants should be assessed soon after resettlement, and adequate care should be provided, with particular attention paid to young adults. FUNDING Marie Skłodowska-Curie Actions (Horizon 2020-COFUND), MinCiencias (Colombia), and Swiss National Science Foundation

Artificial intelligence for neurodegenerative experimental models

INTRODUCTION: Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS: Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS: Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION: AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. Highlights: There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery.</p

Analysis of SARS-CoV-2 antibody seroprevalence in Northern Ireland during 2020–2021

BackgroundWith the spread of SARS-CoV-2 impacting upon public health directly and socioeconomically, further information was required to inform policy decisions designed to limit virus spread during the pandemic. This study sought to contribute to serosurveillance work within Northern Ireland to track SARS-CoV-2 progression and guide health strategy.MethodsSera/plasma samples from clinical biochemistry laboratories were analysed for anti-SARS-CoV-2 antibodies. Samples were assessed using an Elecsys anti-SARS-CoV-2 or anti-SARS-CoV-2 S ECLIA (Roche) on an automated cobas e 801 analyser. Samples were also assessed via an anti-SARS-CoV-2 ELISA (Euroimmun). A subset of samples assessed via the Elecsys anti-SARS-CoV-2 ECLIA were subsequently analysed in an ACE2 pseudoneutralisation assay using a V-PLEX SARS-CoV-2 Panel 7 for IgG and ACE2 (Meso Scale Diagnostics).ResultsAcross three testing rounds (June–July 2020, November–December 2020 and June–July 2021 (rounds 1–3 respectively)), 4844 residual sera/plasma specimens were assayed for anti-SARS-CoV-2 antibodies. Seropositivity rates increased across the study, peaking at 11.6 % (95 % CI 10.4%–13.0 %) during round 3. Varying trends in SARS-CoV-2 seropositivity were noted based on demographic factors. For instance, highest rates of seropositivity shifted from older to younger demographics across the study period. In round 3, Alpha (B.1.1.7) variant neutralising antibodies were most frequently detected across age groups, with median concentration of anti-spike protein antibodies elevated in 50–69 year olds and anti-S1 RBD antibodies elevated in 70+ year olds, relative to other age groups.ConclusionsWith seropositivity rates of &lt;15 % across the assessment period, it can be concluded that the significant proportion of the Northern Ireland population had not yet naturally contracted the virus by mid-2021

Artificial intelligence for neurodegenerative experimental models

INTRODUCTION: Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS: Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS: Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION: AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. HIGHLIGHTS: There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery

Metabolic phenotyping reveals a reduction in the bioavailability of serotonin and kynurenine pathway metabolites in both the urine and serum of individuals living with Alzheimer’s disease

Funder: Medical Research Council; doi: http://dx.doi.org/10.13039/501100000265Funder: Alzheimer's research ukFunder: Alzheimer's societyFunder: InnomedFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272Abstract: Background: Both serotonergic signalling disruption and systemic inflammation have been associated with the pathogenesis of Alzheimer’s disease (AD). The common denominator linking the two is the catabolism of the essential amino acid, tryptophan. Metabolism via tryptophan hydroxylase results in serotonin synthesis, whilst metabolism via indoleamine 2,3-dioxygenase (IDO) results in kynurenine and its downstream derivatives. IDO is reported to be activated in times of host systemic inflammation and therefore is thought to influence both pathways. To investigate metabolic alterations in AD, a large-scale metabolic phenotyping study was conducted on both urine and serum samples collected from a multi-centre clinical cohort, consisting of individuals clinically diagnosed with AD, mild cognitive impairment (MCI) and age-matched controls. Methods: Metabolic phenotyping was applied to both urine (n = 560) and serum (n = 354) from the European-wide AddNeuroMed/Dementia Case Register (DCR) biobank repositories. Metabolite data were subsequently interrogated for inter-group differences; influence of gender and age; comparisons between two subgroups of MCI - versus those who remained cognitively stable at follow-up visits (sMCI); and those who underwent further cognitive decline (cMCI); and the impact of selective serotonin reuptake inhibitor (SSRI) medication on metabolite concentrations. Results: Results revealed significantly lower metabolite concentrations of tryptophan pathway metabolites in the AD group: serotonin (urine, serum), 5-hydroxyindoleacetic acid (urine), kynurenine (serum), kynurenic acid (urine), tryptophan (urine, serum), xanthurenic acid (urine, serum), and kynurenine/tryptophan ratio (urine). For each listed metabolite, a decreasing trend in concentrations was observed in-line with clinical diagnosis: control > MCI > AD. There were no significant differences in the two MCI subgroups whilst SSRI medication status influenced observations in serum, but not urine. Conclusions: Urine and serum serotonin concentrations were found to be significantly lower in AD compared with controls, suggesting the bioavailability of the neurotransmitter may be altered in the disease. A significant increase in the kynurenine/tryptophan ratio suggests that this may be a result of a shift to the kynurenine metabolic route due to increased IDO activity, potentially as a result of systemic inflammation. Modulation of the pathways could help improve serotonin bioavailability and signalling in AD patients

Metabolic phenotyping reveals a reduction in the bioavailability of serotonin and kynurenine pathway metabolites in both the urine and serum of individuals living with Alzheimer's disease.

Funder: Medical Research Council; doi: http://dx.doi.org/10.13039/501100000265Funder: Alzheimer's research ukFunder: Alzheimer's societyFunder: InnomedFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272BACKGROUND: Both serotonergic signalling disruption and systemic inflammation have been associated with the pathogenesis of Alzheimer's disease (AD). The common denominator linking the two is the catabolism of the essential amino acid, tryptophan. Metabolism via tryptophan hydroxylase results in serotonin synthesis, whilst metabolism via indoleamine 2,3-dioxygenase (IDO) results in kynurenine and its downstream derivatives. IDO is reported to be activated in times of host systemic inflammation and therefore is thought to influence both pathways. To investigate metabolic alterations in AD, a large-scale metabolic phenotyping study was conducted on both urine and serum samples collected from a multi-centre clinical cohort, consisting of individuals clinically diagnosed with AD, mild cognitive impairment (MCI) and age-matched controls. METHODS: Metabolic phenotyping was applied to both urine (n = 560) and serum (n = 354) from the European-wide AddNeuroMed/Dementia Case Register (DCR) biobank repositories. Metabolite data were subsequently interrogated for inter-group differences; influence of gender and age; comparisons between two subgroups of MCI - versus those who remained cognitively stable at follow-up visits (sMCI); and those who underwent further cognitive decline (cMCI); and the impact of selective serotonin reuptake inhibitor (SSRI) medication on metabolite concentrations. RESULTS: Results revealed significantly lower metabolite concentrations of tryptophan pathway metabolites in the AD group: serotonin (urine, serum), 5-hydroxyindoleacetic acid (urine), kynurenine (serum), kynurenic acid (urine), tryptophan (urine, serum), xanthurenic acid (urine, serum), and kynurenine/tryptophan ratio (urine). For each listed metabolite, a decreasing trend in concentrations was observed in-line with clinical diagnosis: control > MCI > AD. There were no significant differences in the two MCI subgroups whilst SSRI medication status influenced observations in serum, but not urine. CONCLUSIONS: Urine and serum serotonin concentrations were found to be significantly lower in AD compared with controls, suggesting the bioavailability of the neurotransmitter may be altered in the disease. A significant increase in the kynurenine/tryptophan ratio suggests that this may be a result of a shift to the kynurenine metabolic route due to increased IDO activity, potentially as a result of systemic inflammation. Modulation of the pathways could help improve serotonin bioavailability and signalling in AD patients