Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making

Modern medicine requires generalised approaches to the synthesis and integration of multimodal data, often at different biological scales, that can be applied to a variety of evidence structures, such as complex disease analyses and epidemiological models. However, current methods are either slow and expensive, or ineffective due to the inability to model the complex relationships between data modes which differ in scale and format. We address these issues by proposing a cross-modal deep learning architecture and co-attention mechanism to accurately model the relationships between the different data modes, while further reducing patient diagnosis time. Differentiating Parkinson's Disease (PD) patients from healthy patients forms the basis of the evaluation. The model outperforms the previous state-of-the-art unimodal analysis by 2.35%, while also being 53% more parameter efficient than the industry standard cross-modal model. Furthermore, the evaluation of the attention coefficients allows for qualitative insights to be obtained. Through the coupling with bioinformatics, a novel link between the interferon-gamma-mediated pathway, DNA methylation and PD was identified. We believe that our approach is general and could optimise the process of medical evidence synthesis and decision making in an actionable way

Modelling the hygroscopic growth factors of aerosol material containing a large water-soluble organic fraction, collected at the Storm Peak Laboratory

The compositions of six aggregated aerosol samples from the Storm Peak site have been comprehensively analysed (Hallar et al., 2013), focusing particularly on the large water-extractable organic fraction which consists of both high molecular weight organic compounds and a range of acids and sugar-alcohols. The contribution of the soluble organic fraction of atmospheric aerosols to their hygroscopicity is hard to quantify, largely because of the lack of a detailed knowledge of both composition and the thermodynamic properties of the functionally complex compounds and structures the fraction contains. In this work we: (i) develop a means of predicting the relative solubility of the compounds in the water-extractable organic material from the Storm Peak site, based upon what is known about their chemical composition; (ii) derive the probable soluble organic fraction from comparisons of model predictions with the measured hygroscopicity; (iii) test a model of the water uptake of the total aerosol (inorganic plus total water-extractable organic compounds). Using a novel UNIFAC-based method, different assignments of functional groups to the high molecular weight water soluble organic compounds (WSOC) were explored, together with their effects on calculated hygroscopic growth factors, constrained by the known molecular formulae and the double bond equivalents associated with each molecule. The possible group compositions were compared with the results of ultrahigh resolution mass spectrometry measurements of the organic material, which suggest large numbers of alcohol (–OH) and acid (–COOH) groups. A hygroscopicity index (HI) was developed. The measured hygroscopic growth is found to be consistent with a dissolution of the WSOC material that varies approximately linearly with RH, such that the dissolved fraction is about 0.45–0.85 at 90% relative humidity when ordering by HI, depending on the assumptions made. This relationship, if it also applies to other types of organic aerosol material, provides a simple approach to calculating both water uptake and CCN activity (and the κ parameter for hygroscopic growth). The hygroscopicity of the total aerosol was modelled using a modified Zdanovskii-Stokes-Robinson approach as the sum of that of the three analysed fractions: inorganic ions (predicted), individual organic acids and “sugar alcohols” (predicted), and the high molecular weight WSOC fraction (measured). The calculated growth factors broadly agree with the measurements, and validate the approach taken. The insights into the dissolution of the organic material seem likely to apply to other largely biogenic aerosols from similar remote locations

An Exploration of AGN and Stellar Feedback Effects in the Intergalactic Medium via the Low Redshift Lyman-α\alpha Forest

We explore the role of galactic feedback on the low redshift Lyman-$\alpha$ (Ly$\alpha$)~forest ($z \lesssim 2$) statistics and its potential to alter the thermal state of the intergalactic medium. Using the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) suite, we explore variations of the AGN and stellar feedback models in the IllustrisTNG and Simba sub-grid models. We find that both AGN and stellar feedback in Simba play a role in setting the Ly$\alpha$ forest column density distribution function (CDD) and the Doppler width ($b$-value) distribution. The Simba AGN jet feedback mode is able to efficiently transport energy out to the diffuse IGM causing changes in the shape and normalization of the CDD and a broadening of the $b$-value distribution. We find that stellar feedback plays a prominent role in regulating supermassive black hole growth and feedback, highlighting the importance of constraining stellar and AGN feedback simultaneously. In IllustrisTNG, the AGN feedback variations explored in CAMELS do not affect the Ly$\alpha$ forest, but varying the stellar feedback model does produce subtle changes. Our results imply that the low-$z$ Ly$\alpha$ forest can be sensitive to changes in the ultraviolet background (UVB), stellar and black hole feedback, and that AGN jet feedback in particular can have a strong effect on the thermal state of the IGM.Comment: 26 pages, 11 figures, 2 tables, submitted to Ap

Trophic structuring of modularity alters energy flow through marine food webs

Food web interactions govern how ecosystems respond to climate change and biodiversity loss. Modularity, where subgroups of species interact more often with each other than with species outside their subgroup, is a key structural feature which has been linked to food web stability. We sought to address the lack of understanding of how modularity varies among ecosystems by comparing the structure of four highly resolved marine food webs and the importance of functional traits for predicting module membership. Modules in two offshore networks were partitioned largely by trophic level, creating an interdependence among them, whereas modules in two semi-enclosed bays were generally separated into energy channels with less trophic separation and containing distinct basal resources, providing greater redundancy in the flow of energy through the network. Foraging habitat and mobility predicted module membership in all networks, whilst body mass and foraging strategy also differentiated modules in the offshore and bay ecosystems, respectively. Environmental heterogeneity may be a key factor driving the differences in modularity and the relative importance of functional traits for predicting module membership. Our results indicate that, in addition to overall network modularity, the trophic structure of modules within food webs should be considered when making inferences about ecosystem stability

Sound transmission loss of hierarchically porous composites produced by hydrogel templating and viscous trapping techniques

© 2017 the Partner Organisations. We have developed two different methods for fabrication of hierarchically porous composites which are environmentally friendly, inexpensive and give a large amount of control over the composite microstructure. The hydrogel bead templating method involved introducing a slurry of hydrogel beads as templates into a gypsum slurry that, upon drying, left pores reflecting their size. The overall porosity reflected the volume percentage of hydrogel bead slurry used. Using mixtures of large and small hydrogel beads in controlled volume ratios as templates, we produced hierarchically porous gypsum composites that had tailorable microstructures at the same overall porosity. The viscous trapping method involved utilisation of an aqueous solution of a thickening agent, methylcellulose, during the setting process of an aqueous gypsum slurry. The methylcellulose solution traps the hydrated gypsum particles in solution and stops their sedimentation as the continuous gypsum network forms, allowing formation of an expanded microstructure. This method allows a good degree of control over the porosity which is directly controlled by the volume percentage of methylcellulose solution used. The mechanical strength of the porous composites decreased as the porosity increased. The composites with smaller pores had increased compressional strength and Young's modulus compared to the ones produced with large pores, at constant porosity. The hierarchically porous gypsum composites showed an intermediate Young's modulus and an increased compressional strength. We also studied the sound transmission loss of these hierarchically porous composites. We found that the ones produced by the viscous trapping method had a lower sound transmission loss over the frequency range investigated as the overall porosity was increased. We demonstrated the effect of the composite pore size at a constant porosity on the sound transmission loss. Our experiments showed that porous composites with large pores showed increased sound transmission loss at lower sound frequencies compared to those with small pores. As the sound frequency increased, the difference between their STL spectra decreased and at the higher frequency range (>2420 Hz) the composites with smaller pores began to perform better. The hierarchically porous composite had an intermediate STL spectrum, suggesting a way of tailoring the hierarchically porous structure at constant porosity to achieve desired sound insulating properties at certain frequencies

Aggressive breast cancer in western Kenya has early onset, high proliferation, and immune cell infiltration

Background Breast cancer incidence and mortality vary significantly among different nations and racial groups. African nations have the highest breast cancer mortality rates in the world, even though the incidence rates are below those of many nations. Differences in disease progression suggest that aggressive breast tumors may harbor a unique molecular signature to promote disease progression. However, few studies have investigated the pathology and clinical markers expressed in breast tissue from regional African patient populations. Methods We collected 68 malignant and 89 non-cancerous samples from Kenyan breast tissue. To characterize the tumors from these patients, we constructed tissue microarrays (TMAs) from these tissues. Sections from these TMAs were stained and analyzed using immunohistochemistry to detect clinical breast cancer markers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 receptor (HER2) status, Ki67, and immune cell markers. Results Thirty-three percent of the tumors were triple negative (ER-, PR-, HER2-), 59 % were ER+, and almost all tumors analyzed were HER2-. Seven percent of the breast cancer patients were male, and 30 % were <40 years old at diagnosis. Cancer tissue had increased immune cell infiltration with recruitment of CD163+ (M2 macrophage), CD25+ (regulatory T lymphocyte), and CD4+ (T helper) cells compared to non-cancer tissue. Conclusions We identified clinical biomarkers that may assist in identifying therapy strategies for breast cancer patients in western Kenya. Estrogen receptor status in particular should lead initial treatment strategies in these breast cancer patients. Increased CD25 expression suggests a need for additional treatment strategies designed to overcome immune suppression by CD25+ cells in order to promote the antitumor activity of CD8+ cytotoxic T cells

Atypical functional connectivity during unfamiliar music listening in children with autism

Background: Atypical processing of unfamiliar, but less so familiar, stimuli has been described in Autism Spectrum Disorder (ASD), in particular in relation to face processing. We examined the construct of familiarity in ASD using familiar and unfamiliar songs, to investigate the link between familiarity and autism symptoms, such as repetitive behavior. Methods: Forty-eight children, 24 with ASD (21 males, mean age = 9.96 years ± 1.54) and 24 typically developing (TD) controls (21 males, mean age = 10.17 ± 1.90) completed a music familiarity task using individually identified familiar compared to unfamiliar songs, while magnetoencephalography (MEG) was recorded. Each song was presented for 30 s. We used both amplitude envelope correlation (AEC) and the weighted phase lag index (wPLI) to assess functional connectivity between specific regions of interest (ROI) and non-ROI parcels, as well as at the whole brain level, to understand what is preserved and what is impaired in familiar music listening in this population. Results: Increased wPLI synchronization for familiar vs. unfamiliar music was found for typically developing children in the gamma frequency. There were no significant differences within the ASD group for this comparison. During the processing of unfamiliar music, we demonstrated left lateralized increased theta and beta band connectivity in children with ASD compared to controls. An interaction effect found greater alpha band connectivity in the TD group compared to ASD to unfamiliar music only, anchored in the left insula.Conclusion: Our results revealed atypical processing of unfamiliar songs in children with ASD, consistent with previous studies in other modalities reporting that processing novelty is a challenge for ASD. Relatively typical processing of familiar stimuli may represent a strength and may be of interest to strength-based intervention planning.info:eu-repo/semantics/publishedVersio

Sero-epidemiological survey and risk factors associated with brucellosis in dogs in south-western Nigeria

Introduction: In Nigeria, there is limited information on brucellosis particularly in dogs, despite its public health implications. We undertook a sero-epidemiological survey of brucellosis in dogs to determine the prevalence of the disease and associated risk factors for its occurrence in Nigeria. Methods: A cross-sectional study was conducted to screen dogs in south-western Nigeria for antibodies to Brucella sp using the rapid slide agglutination test (RSA) and Rose Bengal test (RBT), with positive samples confirmed respectively by serum agglutination test (SAT) and competitive enzyme linked immunosorbent assay (cELISA). Data were analyzed with STATA-12. Results: From the 739 dog sera tested, 81 (10.96%) were positive by RSA and 94 (12.72%) by RBT; these were corroborated with SAT (4/81; 4.94%) and cELISA (1/94; 1.06%), respectively. Logistic regression identified location (OR=0.04; 95% CI: 0.02-0.09), breed (OR=1.71; 95% CI: 1.34-2.19), age (OR=0.10; 95% CI: 0.04- 0.30) and management system (OR=8.51; 95% CI: 1.07-68.05) as risk factors for Brucella infection by RSA. However, location (OR=10.83; 95% CI: 5.48-21.39) and history of infertility (OR=2.62; 95% CI: 1.41-4.84) were identified as risk factors using RBT. Conclusion: Given the 10.96% to 12.72% seroprevalence of brucellosis recorded in this study, we advocate control of the disease in dogs, and public health education for those at risk of infection. Again, further studies are required to elucidate the role of dogs in the epidemiology of brucellosis in Nigeria considering the conducive human-animal interface and ecological factors responsible for the transmission of the disease.Pan African Medical Journal 2016; 2

Inherent limits of light-level geolocation may lead to over-interpretation

In their 2015 Current Biology paper, Streby et al. [1] reported that Golden-winged Warblers (Vermivora chrysoptera), which had just migrated to their breeding location in eastern Tennessee, performed a facultative and up to “>1,500 km roundtrip” to the Gulf of Mexico to avoid a severe tornadic storm. From light-level geolocator data, wherein geographical locations are estimated via the timing of sunrise and sunset, Streby et al. [1] concluded that the warblers had evacuated their breeding area approximately 24 hours before the storm and returned about five days later. The authors presented this finding as evidence that migratory birds avoid severe storms by temporarily moving long-distances. However, the tracking method employed by Streby et al. [1] is prone to considerable error and uncertainty. Here, we argue that this interpretation of the data oversteps the limits of the used tracking technique. By calculating the expected geographical error range for the tracked birds, we demonstrate that the hypothesized movements fell well within the geolocators’ inherent error range for this species and that such deviations in latitude occur frequently even if individuals remain stationary