Memory-Augmented Graph Neural Networks: A Neuroscience Perspective

Graph neural networks (GNNs) have been extensively used for many domains where data are represented as graphs, including social networks, recommender systems, biology, chemistry, etc. Recently, the expressive power of GNNs has drawn much interest. It has been shown that, despite the promising empirical results achieved by GNNs for many applications, there are some limitations in GNNs that hinder their performance for some tasks. For example, since GNNs update node features mainly based on local information, they have limited expressive power in capturing long-range dependencies among nodes in graphs. To address some of the limitations of GNNs, several recent works started to explore augmenting GNNs with memory for improving their expressive power in the relevant tasks. In this paper, we provide a comprehensive review of the existing literature of memory-augmented GNNs. We review these works through the lens of psychology and neuroscience, which has established multiple memory systems and mechanisms in biological brains. We propose a taxonomy of the memory GNN works, as well as a set of criteria for comparing the memory mechanisms. We also provide critical discussions on the limitations of these works. Finally, we discuss the challenges and future directions for this area

MicroRNA-143 is downregulated in breast cancer and regulates DNA methyltransferases 3A in breast cancer cells

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Circulating microRNAs as Specific Biomarkers for Breast Cancer Detection

Background: We previously showed microRNAs (miRNAs) in plasma are potential biomarkers for colorectal cancer detection. Here, we aimed to develop specific blood-based miRNA assay for breast cancer detection. Methodology/Principal Findings: TaqMan-based miRNA profiling was performed in tumor, adjacent non-tumor, corresponding plasma from breast cancer patients, and plasma from matched healthy controls. All putative markers identified were verified in a training set of breast cancer patients. Selected markers were validated in a case-control cohort of 170 breast cancer patients, 100 controls, and 95 other types of cancers and then blindly validated in an independent set of 70 breast cancer patients and 50 healthy controls. Profiling results showed 8 miRNAs were concordantly up-regulated and 1 miRNA was concordantly down-regulated in both plasma and tumor tissue of breast cancer patients. Of the 8 up-regulated miRNAs, only 3 were significantly elevated (p<0.0001) before surgery and reduced after surgery in the training set. Results from the validation cohort showed that a combination of miR-145 and miR-451 was the best biomarker (p<0.0001) in discriminating breast cancer from healthy controls and all other types of cancers. In the blind validation, these plasma markers yielded Receiver Operating Characteristic (ROC) curve area of 0.931. The positive predictive value was 88% and the negative predictive value was 92%. Altered levels of these miRNAs in plasma have been detected not only in advanced stages but also early stages of tumors. The positive predictive value for ductal carcinoma in situ (DCIS) cases was 96%. Conclusions: These results suggested that these circulating miRNAs could be a potential specific biomarker for breast cancer screening. © 2013 Ng et al.published_or_final_versio

TL1A/DR3 axis involvement in the inflammatory cytokine network during pulmonary sarcoidosis

BACKGROUND: TNF-like ligand 1A (TL1A), a recently recognized member of the TNF superfamily, and its death domain receptor 3 (DR3), firstly identified for their relevant role in T lymphocyte homeostasis, are now well-known mediators of several immune-inflammatory diseases, ranging from rheumatoid arthritis to inflammatory bowel diseases to psoriasis, whereas no data are available on their involvement in sarcoidosis, a multisystemic granulomatous disease where a deregulated T helper (Th)1/Th17 response takes place. METHODS: In this study, by flow cytometry, real-time PCR, confocal microscopy and immunohistochemistry analyses, TL1A and DR3 were investigated in the pulmonary cells and the peripheral blood of 43 patients affected by sarcoidosis in different phases of the disease (29 patients with active sarcoidosis, 14 with the inactive form) and in 8 control subjects. RESULTS: Our results demonstrated a significant higher expression, both at protein and mRNA levels, of TL1A and DR3 in pulmonary T cells and alveolar macrophages of patients with active sarcoidosis as compared to patients with the inactive form of the disease and to controls. In patients with sarcoidosis TL1A was strongly more expressed in the lung than the blood, i.e., at the site of the involved organ. Additionally, zymography assays showed that TL1A is able to increase the production of matrix metalloproteinase 9 by sarcoid alveolar macrophages characterized, in patients with the active form of the disease, by reduced mRNA levels of the tissue inhibitor of metalloproteinase (TIMP)-1. CONCLUSIONS: These data suggest that TL1A/DR3 interactions are part of the extended and complex immune-inflammatory network that characterizes sarcoidosis during its active phase and may contribute to the pathogenesis and to the progression of the disease

Climate change and water resources in arid regions : uncertainty of the baseline time period

Recent climate change studies have given a lot of attention to the uncertainty that stems from general circulation models (GCM), greenhouse gas emission scenarios, hydrological models and downscaling approaches. Yet, the uncertainty that stems from the selection of the baseline period has not been studied. Accordingly, the main research question is as follows: What would be the differences and/or the similarities in the evaluation of climate change impacts between the GCM and the delta perturbation scenarios using different baseline periods? This article addresses this issue through comparison of the results of two different baseline periods, investigating the uncertainties in evaluating climate change impact on the hydrological characteristics of arid regions. The Lower Zab River Basin (Northern Iraq) has been selected as a representative case study. The research outcomes show that the considered baseline periods suggest increases and decreases in the temperature and precipitation (P), respectively, over the 2020, 2050 and 2080 periods. The two climatic scenarios are likely to lead to similar reductions in the reservoir mean monthly flows, and subsequently, their maximum discharge is approximately identical. The predicted reduction in the inflow for the 2080–2099 time period fluctuates between 31 and 49% based on SRA1B and SRA2 scenarios, respectively. The delta perturbation scenario permits the sensitivity of the climatic models to be clearly determined compared to the GCM. The former allows for a wide variety of likely climate change scenarios at the regional level and are easier to generate and apply so that they could complement the latter

Feller Processes: The Next Generation in Modeling. Brownian Motion, L\'evy Processes and Beyond

We present a simple construction method for Feller processes and a framework for the generation of sample paths of Feller processes. The construction is based on state space dependent mixing of L\'evy processes. Brownian Motion is one of the most frequently used continuous time Markov processes in applications. In recent years also L\'evy processes, of which Brownian Motion is a special case, have become increasingly popular. L\'evy processes are spatially homogeneous, but empirical data often suggest the use of spatially inhomogeneous processes. Thus it seems necessary to go to the next level of generalization: Feller processes. These include L\'evy processes and in particular Brownian motion as special cases but allow spatial inhomogeneities. Many properties of Feller processes are known, but proving the very existence is, in general, very technical. Moreover, an applicable framework for the generation of sample paths of a Feller process was missing. We explain, with practitioners in mind, how to overcome both of these obstacles. In particular our simulation technique allows to apply Monte Carlo methods to Feller processes.Comment: 22 pages, including 4 figures and 8 pages of source code for the generation of sample paths of Feller processe

Reduced haemodynamic response in the ageing visual cortex measured by absolute fNIRS

The effect of healthy ageing on visual cortical activation is still to be fully explored. This study aimed to elucidate whether the haemodynamic response (HDR) of the visual cortex altered as a result of ageing. Visually normal (healthy) participants were presented with a simple visual stimulus (reversing checkerboard). Full optometric screening was implemented to identify two age groups: younger adults (n = 12, mean age 21) and older adults (n = 13, mean age 71). Frequency-domain Multi-distance (FD-MD) functional Near-Infrared Spectroscopy (fNIRS) was used to measure absolute changes in oxygenated [HbO] and deoxygenated [HbR] haemoglobin concentrations in the occipital cortices. Utilising a slow event-related design, subjects viewed a full field reversing checkerboard with contrast and check size manipulations (15 and 30 minutes of arc, 50% and 100% contrast). Both groups showed the characteristic response of increased [HbO] and decreased [HbR] during stimulus presentation. However, older adults produced a more varied HDR and often had comparable levels of [HbO] and [HbR] during both stimulus presentation and baseline resting state. Younger adults had significantly greater concentrations of both [HbO] and [HbR] in every investigation regardless of the type of stimulus displayed (p<0.05). The average variance associated with this age-related effect for [HbO] was 88% and [HbR] 91%. Passive viewing of a visual stimulus, without any cognitive input, showed a marked age-related decline in the cortical HDR. Moreover, regardless of stimulus parameters such as check size, the HDR was characterised by age. In concurrence with present neuroimaging literature, we conclude that the visual HDR decreases as healthy ageing proceeds

A massive, quiescent galaxy at redshift of z=3.717

In the early Universe finding massive galaxies that have stopped forming stars present an observational challenge as their rest-frame ultraviolet emission is negligible and they can only be reliably identified by extremely deep near-infrared surveys. These have revealed the presence of massive, quiescent early-type galaxies appearing in the universe as early as z$\sim$2, an epoch 3 Gyr after the Big Bang. Their age and formation processes have now been explained by an improved generation of galaxy formation models where they form rapidly at z$\sim$3-4, consistent with the typical masses and ages derived from their observations. Deeper surveys have now reported evidence for populations of massive, quiescent galaxies at even higher redshifts and earlier times, however the evidence for their existence, and redshift, has relied entirely on coarsely sampled photometry. These early massive, quiescent galaxies are not predicted by the latest generation of theoretical models. Here, we report the spectroscopic confirmation of one of these galaxies at redshift z=3.717 with a stellar mass of 1.7$\times$10$^{11}$ M$_\odot$ whose absorption line spectrum shows no current star-formation and which has a derived age of nearly half the age of the Universe at this redshift. The observations demonstrates that the galaxy must have quickly formed the majority of its stars within the first billion years of cosmic history in an extreme and short starburst. This ancestral event is similar to those starting to be found by sub-mm wavelength surveys pointing to a possible connection between these two populations. Early formation of such massive systems is likely to require significant revisions to our picture of early galaxy assembly.Comment: 6 pages, 7 figures. This is the final preprint corresponding closely to the published version. Uploaded 6 months after publication in accordance with Nature polic

Malignancy risk analysis in patients with inadequate fine needle aspiration cytology (FNAC) of the thyroid

Background Thyroid fine needle aspiration cytology (FNAC) is the standard diagnostic modality for thyroid nodules. However, it has limitations among which is the incidence of non-diagnostic results (Thy1). Management of cases with repeatedly non-diagnostic FNAC ranges from simple observation to surgical intervention. We aim to evaluate the incidence of malignancy in non-diagnostic FNAC, and the success rate of repeated FNAC. We also aim to evaluate risk factors for malignancy in patients with non-diagnostic FNAC. Materials and Methods Retrospective analyses of consecutive cases with thyroid non diagnostic FNAC results were included. Results Out of total 1657 thyroid FNAC done during the study period, there were 264 (15.9%) non-diagnostic FNAC on the first attempt. On repeating those, the rate of a non-diagnostic result on second FNAC was 61.8% and on third FNAC was 47.2%. The overall malignancy rate in Thy1 FNAC was 4.5% (42% papillary, 42% follicular and 8% anaplastic), and the yield of malignancy decreased considerably with successive non-diagnostic FNAC. Ultrasound guidance by an experienced head neck radiologist produced the lowest non-diagnostic rate (38%) on repetition compared to US guidance by a generalist radiologist (65%) and by non US guidance (90%). Conclusions There is a low risk of malignancy in patients with a non-diagnostic FNAC result, commensurate to the risk of any nodule. The yield of malignancy decreased considerably with successive non-diagnostic FNAC