Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced optical computing. ...Traditional experimental implementations need N
units such as Mach-Zehnder interferometers (MZIs) for an input dimension N to realize typical computing operations (convolutions and matrix multiplication), resulting in limited scalability and consuming excessive power. Here, we propose the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing using two ultracompact diffractive cells (Fourier transform operation) and only N MZIs. The footprint and energy consumption scales linearly with the input data dimension, instead of the quadratic scaling in the traditional ONN framework. A ~10-fold reduction in both footprint and energy consumption, as well as equal high accuracy with previous MZI-based ONNs was experimentally achieved for computations performed on the MNIST and Fashion-MNIST datasets. The integrated diffractive optical network (IDNN) chip demonstrates a promising avenue towards scalable and low-power-consumption optical computational chips for optical-artificial-intelligence.
Aims
Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have ...recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes.
Methods
We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non‐type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin‐containing islets along with multiple insulin‐deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data autoantibodies, type 1 diabetes genetic risk score (T1D‐GRS), and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC‐ROC).
Results
Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D‐GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC‐ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C‐peptide median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non‐type 1 diabetes; P < 0.0001.
Conclusions
Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C‐peptide‐based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible.
Parts of this study were presented in form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19–22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6–8 March 2019.
What’s new?
Misclassification of diabetes at diagnosis is common due to an overlap in the clinical features of type 1 and type 2 diabetes.
Combining clinical features and biomarkers in a diagnostic model improved discrimination of diabetes type, defined by insulin deficiency (measured by C‐peptide assays), over use of any single characteristic.
No diabetes classification studies have used pancreatic histology to define type 1 diabetes.
A diagnostic model, developed using diabetes type defined by C‐peptide level as an outcome, validates against histologically defined insulin deficiency.
C‐peptide provides a robust surrogate definition of type 1 diabetes that can be used in diagnostic model development.
Our study provides the first histological evidence for a clinical diagnostic model having utility to identify type 1 diabetes in clinical practice.
Some perfluoroalkyl and polyfluoroalkyl substances (PFASs) have become widespread pollutants detected in human and wildlife samples worldwide. The main objective of this study was to assess temporal ...trends of PFAS concentrations in human blood in Australia over the last decade (2002–2011), taking into consideration age and sex trends.
Pooled human sera from 2002/03 (n=26); 2008/09 (n=24) and 2010/11 (n=24) from South East Queensland, Australia were obtained from de-identified surplus pathology samples and compared with samples collected previously from 2006/07 (n=84). A total of 9775 samples in 158 pools were available for an assessment of PFASs. Stratification criteria included sex and age: <16years (2002/03 only); 0–4 (2006/07, 2008/09, 2010/11); 5–15 (2006/07, 2008/09, 2010/11); 16–30; 31–45; 46–60; and >60years (all collection periods). Sera were analyzed using on-line solid-phase extraction coupled to high-performance liquid chromatography–isotope dilution-tandem mass spectrometry.
Perfluorooctane sulfonate (PFOS) was detected in the highest concentrations ranging from 5.3–19.2ng/ml (2008/09) to 4.4–17.4ng/ml (2010/11). Perfluorooctanoate (PFOA) was detected in the next highest concentration ranging from 2.8–7.3ng/ml (2008/09) to 3.1–6.5ng/ml (2010/11). All other measured PFASs were detected at concentrations <1ng/ml with the exception of perfluorohexane sulfonate which ranged from 1.2–5.7ng/ml (08/09) and 1.4–5.4ng/ml (10/11). The mean concentrations of both PFOS and PFOA in the 2010/11 period compared to 2002/03 were lower for all adult age groups by 56%. For 5–15year olds, the decrease was 66% (PFOS) and 63% (PFOA) from 2002/03 to 2010/11. For 0–4year olds the decrease from 2006/07 (when data were first available for this age group) was 50% (PFOS) and 22% (PFOA).
This study provides strong evidence for decreasing serum PFOS and PFOA concentrations in an Australian population from 2002 through 2011. Age trends were variable and concentrations were higher in males than in females. Global use has been in decline since around 2002 and hence primary exposure levels are expected to be decreasing. Further biomonitoring will allow assessment of PFAS exposures to confirm trends in exposure as primary and eventually secondary sources are depleted.
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•Decreasing serum PFOS and PFOA in an Australian population (2002–2011)•PFOS and PFOA both decreased 56% from 2002/03 to 2010/11 in adults.•For 5–15years, PFOS and PFOA decreased 66% and 63% from 2002/03 to 2010/11.•For 0–4years, PFOS and PFOA decreased 50% and 22% from 2006/07 to 2010/11.•Age trends were variable and concentrations were higher in males than in females.
Hippocampal volume change over time, measured with MRI, has huge potential as a marker for Alzheimer's disease. The objectives of this study were: (i) to test if constant and accelerated hippocampal ...loss can be detected in Alzheimer's disease, mild cognitive impairment and normal ageing over short periods, e.g. 6–12 months, with MRI in the large multicentre setting of the Alzheimer's Disease Neuroimaging Initiative (ADNI); (ii) to determine the extent to which the polymorphism of the apolipoprotein E (ApoE) gene modulates hippocampal change; and (iii) to determine if rates of hippocampal loss correlate with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, such as the β-amyloid (Aβ1–42) and tau proteins (tau). The MRI multicentre study included 112 cognitive normal elderly individuals, 226 mild cognitive impairment and 96 Alzheimer's disease patients who all had at least three successive MRI scans, involving 47 different imaging centres. The mild cognitive impairment and Alzheimer's disease groups showed hippocampal volume loss over 6 months and accelerated loss over 1 year. Moreover, increased rates of hippocampal loss were associated with presence of the ApoE allele ɛ4 gene in Alzheimer's disease and lower CSF Aβ1–42 in mild cognitive impairment, irrespective of ApoE genotype, whereas relations with tau were only trends. The power to measure hippocampal change was improved by exploiting correlations statistically between successive MRI observations. The demonstration of considerable hippocampal loss in mild cognitive impairment and Alzheimer's disease patients over only 6 months and accelerated loss over 12 months illustrates the power of MRI to track morphological brain changes over time in a large multisite setting. Furthermore, the relations between faster hippocampal loss in the presence of ApoE allele ɛ4 and decreased CSF Aβ1–42 supports the concept that increased hippocampal loss is an indicator of Alzheimer's disease pathology and a potential marker for the efficacy of therapeutic interventions in Alzheimer's disease.
The Transiting Exoplanet Survey Satellite (TESS) recently observed 18 transits of the hot Jupiter WASP-4b. The sequence of transits occurred 81.6 11.7 s earlier than had been predicted, based on data ...stretching back to 2007. This is unlikely to be the result of a clock error, because TESS observations of other hot Jupiters (WASP-6b, 18b, and 46b) are compatible with a constant period, ruling out an 81.6 s offset at the 6.4 level. The 1.3 day orbital period of WASP-4b appears to be decreasing at a rate of ms per year. The apparent period change might be caused by tidal orbital decay or apsidal precession, although both interpretations have shortcomings. The gravitational influence of a third body is another possibility, though at present there is minimal evidence for such a body. Further observations are needed to confirm and understand the timing variation.
Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current ...classification system. The human leucocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.
Dense genotype data from the HLA region, from the Immunochip array for 5043 JIA cases and 14 390 controls, were used to impute single-nucleotide polymorphisms, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.
We identified category-specific associations and have demonstrated for the first time that rheumatoid factor (RF)-negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.
The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and aetiology and facilitate transition from paediatric to adult services.
Background. During the 2012-2013 influenza season, there was cocirculation of influenza A(H3N2) and 2 influenza lineage viruses in the United States. Methods. Patients with acute cough illness for ≤7 ...days were prospectively enrolled and had swab samples obtained at outpatient clinics in 5 states. Influenza vaccination dates were confirmed by medical records. The vaccine effectiveness (VE) was estimated as 100% × (1 - adjusted odds ratio) for vaccination in cases versus test-negative controls. Results. Influenza was detected in 2307 of 6452 patients (36%); 1292 (56%) had influenza A(H3N2), 582 (25%) had influenza B/Yamagata, and 303 (13%) had influenza B/Victoria. VE was 49% (95% confidence interval CI, 43%-55%) overall, 39% (95% CI, 29%-47%) against influenza A(H3N2), 66% (95% CI, 58%-73%) against influenza B/Yamagata (vaccine lineage), and 51% (95% CI, 36%-63%) against influenza B/Victoria. VE against influenza A(H3N2) was highest among persons aged 50-64 years (52%; 95% CI, 33%-65%) and persons aged 6 months-8 years (51%; 95% CI, 32%-64%) and lowest among persons aged ≥65 years (11%; 95% CI, -41% to 43%). In younger age groups, there was evidence of residual protection from receipt of the 2011-2012 vaccine 1 year earlier. Conclusions. The 2012-2013 vaccines were moderately effective in most age groups. Cross-lineage protection and residual effects from prior vaccination were observed and warrant further investigation.
State-of-the-art radial-velocity (RV) exoplanet searches are currently limited by RV signals arising from stellar magnetic activity. We analyze solar observations acquired over a 3 yr period during ...the decline of Carrington Cycle 24 to test models of RV variation of Sun-like stars. A purpose-built solar telescope at the High Accuracy Radial-velocity Planet Searcher for the Northern hemisphere (HARPS-N) provides disk-integrated solar spectra, from which we extract RVs and log R HK ′ . The Solar Dynamics Observatory (SDO) provides disk-resolved images of magnetic activity. The Solar Radiation and Climate Experiment (SORCE) provides near-continuous solar photometry, analogous to a Kepler light curve. We verify that the SORCE photometry and HARPS-N log R HK ′ correlate strongly with the SDO-derived magnetic filling factor, while the HARPS-N RV variations do not. To explain this discrepancy, we test existing models of RV variations. We estimate the contributions of the suppression of convective blueshift and the rotational imbalance due to brightness inhomogeneities to the observed HARPS-N RVs. We investigate the time variation of these contributions over several rotation periods, and how these contributions depend on the area of active regions. We find that magnetic active regions smaller than 60 Mm2 do not significantly suppress convective blueshift. Our area-dependent model reduces the amplitude of activity-induced RV variations by a factor of two. The present study highlights the need to identify a proxy that correlates specifically with large, bright magnetic regions on the surfaces of exoplanet-hosting stars.
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