6,041 research outputs found
A population study of binocular function.
As part of a genome-wide association study (GWAS) of perceptual traits in healthy adults, we measured stereo acuity, the duration of alternative percepts in binocular rivalry and the extent of dichoptic masking in 1060 participants. We present the distributions of the measures, the correlations between measures, and their relationships to other psychophysical traits. We report sex differences, and correlations with age, interpupillary distance, eye dominance, phorias, visual acuity and personality. The GWAS, using data from 988 participants, yielded one genetic association that passed a permutation test for significance: The variant rs1022907 in the gene VTI1A was associated with self-reported ability to see autostereograms. We list a number of other suggestive genetic associations (p<10(-5)).This work was supported by the Gatsby Charitable Foundation (GAT2903). J.B. was supported by a fellowship from Gonville and Caius College.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.visres.2015.02.01
Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults
This is the final version. Available from the publisher via the DOI in this record.The data that support the findings of this study are available from University
of Exeter Medical School/Oxford University but restrictions apply to the
availability of these data, which were used under license for the current
study, and so are not publicly available. Data are however available from the
authors upon reasonable request and with permission of University of Exeter
Medical School/Oxford University. R code is made available in supplementary
file (see Additional file 2).Background: There is much interest in the use of prognostic and diagnostic prediction models in all areas of
clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been
increasing at the expense of classic statistical models. Previous studies have compared performance between these
two approaches but their findings are inconsistent and many have limitations. We aimed to compare the
discrimination and calibration of seven models built using logistic regression and optimised machine learning
algorithms in a clinical setting, where the number of potential predictors is often limited, and externally validate the
models.
Methods: We trained models using logistic regression and six commonly used machine learning algorithms to
predict if a patient diagnosed with diabetes has type 1 diabetes (versus type 2 diabetes). We used seven predictor
variables (age, BMI, GADA islet-autoantibodies, sex, total cholesterol, HDL cholesterol and triglyceride) using a UK
cohort of adult participants (aged 18–50 years) with clinically diagnosed diabetes recruited from primary and
secondary care (n = 960, 14% with type 1 diabetes). Discrimination performance (ROC AUC), calibration and
decision curve analysis of each approach was compared in a separate external validation dataset (n = 504, 21% with
type 1 diabetes).
Results: Average performance obtained in internal validation was similar in all models (ROC AUC ≥ 0.94). In
external validation, there were very modest reductions in discrimination with AUC ROC remaining ≥ 0.93 for all
methods. Logistic regression had the numerically highest value in external validation (ROC AUC 0.95). Logistic
regression had good performance in terms of calibration and decision curve analysis. Neural network and gradient
boosting machine had the best calibration performance. Both logistic regression and support vector machine had
good decision curve analysis for clinical useful threshold probabilities.
Conclusion: Logistic regression performed as well as optimised machine algorithms to classify patients with type 1
and type 2 diabetes. This study highlights the utility of comparing traditional regression modelling to machine
learning, particularly when using a small number of well understood, strong predictor variables.National Institute for Health Research (NIHR
The inevitable youthfulness of known high-redshift radio galaxies
Radio galaxies can be seen out to very high redshifts, where in principle
they can serve as probes of the early evolution of the Universe. Here we show
that for any model of radio-galaxy evolution in which the luminosity decreases
with time after an initial rapid increase (that is, essentially all reasonable
models), all observable high-redshift radio-galaxies must be seen when the
lobes are less than 10^7 years old. This means that high-redshift radio
galaxies can be used as a high-time-resolution probe of evolution in the early
Universe. Moreover, this result helps to explain many observed trends of
radio-galaxy properties with redshift [(i) the `alignment effect' of optical
emission along radio-jet axes, (ii) the increased distortion in radio
structure, (iii) the decrease in physical sizes, (iv) the increase in radio
depolarisation, and (v) the increase in dust emission] without needing to
invoke explanations based on cosmology or strong evolution of the surrounding
intergalactic medium with cosmic time, thereby avoiding conflict with current
theories of structure formation.Comment: To appear in Nature. 4 pages, 2 colour figures available on request.
Also available at http://www-astro.physics.ox.ac.uk/~km
RNA helicase EIF4A1-mediated translation is essential for the GC response
EIF4A1 and cofactors EIF4B and EIF4H have been well characterised in cancers, including B cell malignancies, for their ability to promote the translation of oncogenes with structured 5' untranslated regions. However, very little is known of their roles in nonmalignant cells. Using mouse models to delete Eif4a1, Eif4b or Eif4h in B cells, we show that EIF4A1, but not EIF4B or EIF4H, is essential for B cell development and the germinal centre response. After B cell activation in vitro, EIF4A1 facilitates an increased rate of protein synthesis, MYC expression, and expression of cell cycle regulators. However, EIF4A1-deficient cells remain viable, whereas inhibition of EIF4A1 and EIF4A2 by Hippuristanol treatment induces cell death.</p
RNA helicase EIF4A1-mediated translation is essential for the GC response
EIF4A1 and cofactors EIF4B and EIF4H have been well characterised in cancers, including B cell malignancies, for their ability to promote the translation of oncogenes with structured 5' untranslated regions. However, very little is known of their roles in nonmalignant cells. Using mouse models to delete Eif4a1, Eif4b or Eif4h in B cells, we show that EIF4A1, but not EIF4B or EIF4H, is essential for B cell development and the germinal centre response. After B cell activation in vitro, EIF4A1 facilitates an increased rate of protein synthesis, MYC expression, and expression of cell cycle regulators. However, EIF4A1-deficient cells remain viable, whereas inhibition of EIF4A1 and EIF4A2 by Hippuristanol treatment induces cell death.</p
Staphylococcus aureus in the oral cavity: a three-year retrospective analysis of clinical laboratory data
OBJECTIVE: A retrospective analysis of laboratory data to investigate the isolation of Staphylococcus aureus from the oral cavity and facial area in specimens submitted to a regional diagnostic oral microbiology laboratory. METHODS: A hand search of laboratory records for a three-year period (1998-2000) was performed for specimens submitted to the regional diagnostic oral microbiology laboratory based at Glasgow Dental Hospital and School. Data were collected from forms where S. aureus was isolated. These data included demographics, referral source, specimen type, methicillin susceptibility and clinical details. RESULTS: For the period 1998-2000, there were 5,005 specimens submitted to the laboratory. S. aureus was isolated from 1,017 specimens, of which 967 (95%) were sensitive to methicillin (MSSA) and 50 (5%) were resistant to methicillin (MRSA). The 1,017 specimens were provided from 615 patients. MRSA was isolated from 37 (6%) of patients. There was an increasing incidence of S. aureus with age, particularly in the greater than 70 years age group. The most common specimen from which MSSA was isolated was an oral rinse (38%) whilst for MRSA isolates this was a tongue swab (28%). The clinical condition most commonly reported for MSSA isolates was angular cheilitis (22%). Erythema, swelling, pain or burning of the oral mucosa was the clinical condition most commonly reported for MRSA isolates (16%). Patients from whom the MSSA isolates were recovered were most commonly (55%) seen in the oral medicine clinic at the dental hospital, whilst patients with MRSA were more commonly seen in primary care settings such as nursing homes, hospices and general dental practice (51%). CONCLUSION: In line with more recent surveys, this retrospective study suggests that S. aureus may be a more frequent isolate from the oral cavity than hitherto suspected. A small proportion of the S. aureus isolates were MRSA. There were insufficient data available to determine whether the S. aureus isolates were colonising or infecting the oral cavity. However, the role of S. aureus in several diseases of the oral mucosa merits further investigation
Secondary injury and inflammation after intracerebral haemorrhage: a systematic review and meta-analysis of molecular markers in patient brain tissue
BACKGROUND: Inflammatory responses to intracerebral haemorrhage (ICH) are potential therapeutic targets. We aimed to quantify molecular markers of inflammation in human brain tissue after ICH compared with controls using meta-analysis. METHODS: We searched OVID MEDLINE (1946–) and Embase (1974–) in June 2020 for studies that reported any measure of a molecular marker of inflammation in brain tissue from five or more adults after ICH. We assessed risk of bias using a modified Newcastle-Ottawa Scale (mNOS; mNOS score 0–9; 9 indicates low bias), extracted aggregate data, and used random effects meta-analysis to pool associations of molecules where more than two independent case–control studies reported the same outcome and Gene Ontology enrichment analysis to identify over-represented biological processes in pooled sets of differentially expressed molecules (International Prospective Register of Systematic Reviews ID: CRD42018110204). RESULTS: Of 7501 studies identified, 44 were included: 6 were case series and 38 were case–control studies (median mNOS score 4, IQR 3–5). We extracted data from 21 491 analyses of 20 951 molecules reported by 38 case–control studies. Only one molecule (interleukin-1β protein) was quantified in three case–control studies (127 ICH cases vs 41 ICH-free controls), which found increased abundance of interleukin-1β protein after ICH (corrected standardised mean difference 1.74, 95% CI 0.28 to 3.21, p=0.036, I(2)=46%). Processes associated with interleukin-1β signalling were enriched in sets of molecules that were more abundant after ICH. CONCLUSION: Interleukin-1β abundance is increased after ICH, but analyses of other inflammatory molecules after ICH lack replication. Interleukin-1β pathway modulators may optimise inflammatory responses to ICH and merit testing in clinical trials
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