Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study.

BackgroundTo determine if mammographic features from deep learning networks can be applied in breast cancer to identify groups at interval invasive cancer risk due to masking beyond using traditional breast density measures.MethodsFull-field digital screening mammograms acquired in our clinics between 2006 and 2015 were reviewed. Transfer learning of a deep learning network with weights initialized from ImageNet was performed to classify mammograms that were followed by an invasive interval or screen-detected cancer within 12 months of the mammogram. Hyperparameter optimization was performed and the network was visualized through saliency maps. Prediction loss and accuracy were calculated using this deep learning network. Receiver operating characteristic (ROC) curves and area under the curve (AUC) values were generated with the outcome of interval cancer using the deep learning network and compared to predictions from conditional logistic regression with errors quantified through contingency tables.ResultsPre-cancer mammograms of 182 interval and 173 screen-detected cancers were split into training/test cases at an 80/20 ratio. Using Breast Imaging-Reporting and Data System (BI-RADS) density alone, the ability to correctly classify interval cancers was moderate (AUC = 0.65). The optimized deep learning model achieved an AUC of 0.82. Contingency table analysis showed the network was correctly classifying 75.2% of the mammograms and that incorrect classifications were slightly more common for the interval cancer mammograms. Saliency maps of each cancer case found that local information could highly drive classification of cases more than global image information.ConclusionsPre-cancerous mammograms contain imaging information beyond breast density that can be identified with deep learning networks to predict the probability of breast cancer detection

CRP1, a Protein Localized in Filopodia of Growth Cones, Is Involved in Dendritic Growth

The cysteine-rich protein (CRP) family is a subgroup of LIM domain proteins. CRP1, which cross-links actin filaments to make actin bundles, is the only CRP family member expressed in the CNS with little known about its function in nerve cells. Here, we report that CRP1 colocalizes with actin in the filopodia of growth cones in cultured rat hippocampal neurons. Knockdown of CRP1 expression by short hairpin RNA interference results in inhibition of filopodia formation and dendritic growth in neurons. Overexpression of CRP1 increases filopodia formation and neurite branching, which require its actin-bundling activity. Expression of CRP1 with a constitutively active form of Cdc42, a GTPase involved in filopodia formation, increases filopodia formation in COS-7 cells, suggesting cooperation between the two proteins. Moreover, we demonstrate that neuronal activity upregulates CRP1 expression in hippocampal neurons via Ca²⁺ influx after depolarization. Ca²⁺/calmodulin-dependent protein kinase IV (CaMKIV) and cAMP response element binding protein mediate the Ca²⁺-induced upregulation of CRP1 expression. Furthermore, CRP1 is required for the dendritic growth induced by Ca²⁺ influx or CaMKIV. Together, these data are the first to demonstrate a role for CRP1 in dendritic growth.Keywords: Kinase-IV, Hippocampal neurons, Crysteine-rich protein-1, Muscle differentiation, Actin cytoskeleton, binding protein, TRPC6 channels, Spine morphology, Lim domain, Gene expressionThis is the publisher’s final pdf. The published article is copyrighted by Society for Neuroscience and can be found at: http://www.jneurosci.org/

The chlorine isotope fingerprint of the lunar magma ocean

The Moon contains chlorine that is isotopically unlike that of any other body yet studied in the Solar System, an observation that has been interpreted to support traditional models of the formation of a nominally hydrogen-free (“dry”) Moon. We have analyzed abundances and isotopic compositions of Cl and H in lunar mare basalts, and find little evidence that anhydrous lava outgassing was important in generating chlorine isotope anomalies, because ^(37)Cl/^(35)Cl ratios are not related to Cl abundance, H abundance, or D/H ratios in a manner consistent with the lava-outgassing hypothesis. Instead, ^(37)Cl/^(35)Cl correlates positively with Cl abundance in apatite, as well as with whole-rock Th abundances and La/Lu ratios, suggesting that the high ^(37)Cl/^(35)Cl in lunar basalts is inherited from urKREEP, the last dregs of the lunar magma ocean. These new data suggest that the high chlorine isotope ratios of lunar basalts result not from the degassing of their lavas but from degassing of the lunar magma ocean early in the Moon’s history. Chlorine isotope variability is therefore an indicator of planetary magma ocean degassing, an important stage in the formation of terrestrial planets

Current research into brain barriers and the delivery of therapeutics for neurological diseases: a report on CNS barrier congress London, UK, 2017.

This is a report on the CNS barrier congress held in London, UK, March 22-23rd 2017 and sponsored by Kisaco Research Ltd. The two 1-day sessions were chaired by John Greenwood and Margareta Hammarlund-Udenaes, respectively, and each session ended with a discussion led by the chair. Speakers consisted of invited academic researchers studying the brain barriers in relation to neurological diseases and industry researchers studying new methods to deliver therapeutics to treat neurological diseases. We include here brief reports from the speakers

Restricting promotions of ‘less healthy’ foods and beverages by price and location: a big data application of UK Nutrient Profiling Models to a retail product dataset

The UK government plans to limit price-based and location-based promotions for products high in saturated fat, salt and sugars. The 2004/5 UK nutrient profile model (NPM) is the proposed legislative basis, but may be superseded by the draft 2018 NPM. This study develops an algorithm to apply both NPMs to a large food composition database (FCDB), and assesses implementation challenges. UK NPMs were applied algorithmically to the myfood24 FCDB, representing ~45,000 retail products. Pass-rates - indicating free or restricted promotions - and micronutrient compositions were compared. Challenges were assessed and recommendations addressed the legislation’s public consultation questions. For products in scope (75% of total), 6% fewer passed the 2018 NPM (36%, p<0.001) compared with the 2004/5 NPM (42%). Beverages showed the greatest reduction in pass-rate (75%). Under both models, micronutrient contents (per 100 g of product) were generally lower for products which passed; except folate, vitamin C and vitamin D that were no different for passed and failed products. Compared with products passing the 2004/5 NPM, products passing the 2018 NPM on average had marginally higher amounts of iron (0.05 mg, 95% CI: 0.02, 0.08, p<0.001) and magnesium (1.00 mg, 95% CI: 0.00, 1.17, p=0.029), but marginally lower levels of calcium (-0.42 mg, 95% CI: -2.00, -0.40, p=0.025). Missing ingredient information and heterogeneous product categories were challenges for both NPMs. Free sugar calculation further complicated 2018 NPM application. To balance feasibility and public health benefit, the proposed legislative basis may not be appropriate

Nonminimal Couplings in the Early Universe: Multifield Models of Inflation and the Latest Observations

Models of cosmic inflation suggest that our universe underwent an early phase of accelerated expansion, driven by the dynamics of one or more scalar fields. Inflationary models make specific, quantitative predictions for several observable quantities, including particular patterns of temperature anistropies in the cosmic microwave background radiation. Realistic models of high-energy physics include many scalar fields at high energies. Moreover, we may expect these fields to have nonminimal couplings to the spacetime curvature. Such couplings are quite generic, arising as renormalization counterterms when quantizing scalar fields in curved spacetime. In this chapter I review recent research on a general class of multifield inflationary models with nonminimal couplings. Models in this class exhibit a strong attractor behavior: across a wide range of couplings and initial conditions, the fields evolve along a single-field trajectory for most of inflation. Across large regions of phase space and parameter space, therefore, models in this general class yield robust predictions for observable quantities that fall squarely within the "sweet spot" of recent observations.Comment: 17pp, 2 figs. References added to match the published version. Published in {\it At the Frontier of Spacetime: Scalar-Tensor Theory, Bell's Inequality, Mach's Principle, Exotic Smoothness}, ed. T. Asselmeyer-Maluga (Springer, 2016), pp. 41-57, in honor of Carl Brans's 80th birthda

Agreement between an online dietary assessment tool (myfood24) and an interviewer-administered 24-h dietary recall in British adolescents aged 11–18 years

myfood24 Is an online 24-h dietary assessment tool developed for use among British adolescents and adults. Limited information is available regarding the validity of using new technology in assessing nutritional intake among adolescents. Thus, a relative validation of myfood24 against a face-to-face interviewer-administered 24-h multiple-pass recall (MPR) was conducted among seventy-five British adolescents aged 11–18 years. Participants were asked to complete myfood24 and an interviewer-administered MPR on the same day for 2 non-consecutive days at school. Total energy intake (EI) and nutrients recorded by the two methods were compared using intraclass correlation coefficients (ICC), Bland–Altman plots (using between and within-individual information) and weighted κ to assess the agreement. Energy, macronutrients and other reported nutrients from myfood24 demonstrated strong agreement with the interview MPR data, and ICC ranged from 0·46 for Na to 0·88 for EI. There was no significant bias between the two methods for EI, macronutrients and most reported nutrients. The mean difference between myfood24 and the interviewer-administered MPR for EI was −230 kJ (−55 kcal) (95 % CI −490, 30 kJ (−117, 7 kcal); P=0·4) with limits of agreement ranging between 39 % (3336 kJ (−797 kcal)) lower and 34 % (2874 kJ (687 kcal)) higher than the interviewer-administered MPR. There was good agreement in terms of classifying adolescents into tertiles of EI (κ w =0·64). The agreement between day 1 and day 2 was as good for myfood24 as for the interviewer-administered MPR, reflecting the reliability of myfood24. myfood24 Has the potential to collect dietary data of comparable quality with that of an interviewer-administered MPR

Continuous reactive crystallization of pharmaceuticals using impinging jet mixers

For reactive crystallization of pharmaceuticals that show a rapid reaction rate, low solubility of active pharmaceutical ingredient and hence a large supersaturation, it was found in a recent study that a process design which integrates an impinging jet mixer and batch stirred tank produces high quality crystals. The current investigation examines if the short processing time of reactive crystallization permits the impinging jet mixer—stirred tank design to be modified to operate in a continuous mode. The new design combines an impinging jet mixer for feed introduction and reaction with a continuous stirred tank reactor (CSTR) and tubular reactor for crystal growth. A study of reactive crystallization of sodium cefuroxime (an antibiotic), using first a 1L CSTR then scaling to a 50L CSTR, found that the new design produces crystals of higher crystallinity, narrower particle size, and improved product stability, than batch crystallizers