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We present near-IR (NIR) and far-UV observations of the pre-transitional (gapped) disk in HD 169142 using NASA's Infrared Telescope Facility and Hubble Space Telescope. The combination of our data along with existing data sets into the broadband spectral energy distribution reveals variability of up to 45% between ~1.5-10µm over a maximum timescale of 10 yr. All observations known to us separate into two distinct states corresponding to a high near-IR state in the pre-2000 epoch and a low state in the post-2000 epoch, indicating activity within the ≲1AU region of the disk. Through analysis of the Pa β and Br γ lines in our data we derive a mass accretion rate in 2013 May of Ṁ ≈ (1.5-2.7) x 10-9Mʘyr-1. We present a theoretical modeling analysis of the disk in HD 169142 using Monte-Carlo radiative transfer simulation software to explore the conditions and perhaps signs of planetary formation in our collection of 24 yr of observations. We find that shifting the outer edge (r ≈ 0.3AU) of the inner disk by 0.05AU toward the star (in simulation of accretion and/or sculpting by forming planets) successfully reproduces the shift in NIR flux. We establish that the ~40-70AU dark ring imaged in the NIR by Quanz et al. and Momose et al. and at 7 mm by Osorio et al. may be reproduced with a 30% scaled density profile throughout the region, strengthening the link to this structure being dynamically cleared by one or more planetary mass bodies. [ABSTRACT FROM AUTHOR]

Background: This systematic review synthesizes the most recent neuroimaging procedures and machine learning approaches for the prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia. Methods: We systematically searched PubMed, SCOPUS, and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review guidelines. Results: Our search returned 2572 articles, 56 of which met the criteria for inclusion in the final selection. The multimodality framework and deep learning techniques showed potential for predicting the conversion of MCI to AD dementia. Conclusion: Findings of this systematic review identified that the possibility of using neuroimaging data processed by advanced learning algorithms is promising for the prediction of AD progression. We also provided a detailed description of the challenges that researchers are faced along with future research directions. The protocol has been registered in the International Prospective Register of Systematic Reviews– CRD42019133402 and published in the Systematic Reviews journal. [ABSTRACT FROM AUTHOR]

Background and Aim The aim of this systematic review was to quantify the association between frailty and COVID-19 in relation to mortality in hospitalised patients. Methods Medline, Embase, Web of Science and the grey literature were searched for papers from inception to 10 September 2020; the search was re-run in Medline up until the 9 December 2020. Screening, data extraction and quality grading were undertaken by two reviewers. Results were summarised using descriptive statistics, including a meta-analysis of overall mortality; the relationships between frailty and COVID-19 mortality were summarised narratively. Results A total of 2,286 papers were screened resulting in 26 being included in the review. Most studies were from Europe, half from the UK, and one from Brazil; the median sample size was 242.5, median age 73.1 and 43.5% were female. In total, 22/26 used the Clinical Frailty Scale; reported mortality ranged from 14 to 65%. Most, but not all studies showed an association between increasing frailty and a greater risk of dying. Two studies indicated a sub-additive relationship between frailty, COVID-19 and death, and two studies showed no association. Conclusions Whilst the majority of studies have shown a positive association between COVID-19-related death and increasing frailty, some studies suggested a more nuanced understanding of frailty and outcomes in COVID-19 is needed. Clinicians should exert caution in placing too much emphasis on the influence of frailty alone when discussing likely prognosis in older people with COVID-19 illness. [ABSTRACT FROM AUTHOR]