Switcher-random-walks: a cognitive-inspired mechanism for network exploration

Semantic memory is the subsystem of human memory that stores knowledge of concepts or meanings, as opposed to life specific experiences. The organization of concepts within semantic memory can be understood as a semantic network, where the concepts (nodes) are associated (linked) to others depending on perceptions, similarities, etc. Lexical access is the complementary part of this system and allows the retrieval of such organized knowledge. While conceptual information is stored under certain underlying organization (and thus gives rise to a specific topology), it is crucial to have an accurate access to any of the information units, e.g. the concepts, for efficiently retrieving semantic information for real-time needings. An example of an information retrieval process occurs in verbal fluency tasks, and it is known to involve two different mechanisms: -clustering-, or generating words within a subcategory, and, when a subcategory is exhausted, -switching- to a new subcategory. We extended this approach to random-walking on a network (clustering) in combination to jumping (switching) to any node with certain probability and derived its analytical expression based on Markov chains. Results show that this dual mechanism contributes to optimize the exploration of different network models in terms of the mean first passage time. Additionally, this cognitive inspired dual mechanism opens a new framework to better understand and evaluate exploration, propagation and transport phenomena in other complex systems where switching-like phenomena are feasible.Comment: 9 pages, 3 figures. Accepted in "International Journal of Bifurcations and Chaos": Special issue on "Modelling and Computation on Complex Networks

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html)

The Organization of Local and Distant Functional Connectivity in the Human Brain

Information processing in the human brain arises from both interactions between adjacent areas and from distant projections that form distributed brain systems. Here we map interactions across different spatial scales by estimating the degree of intrinsic functional connectivity for the local (≤14 mm) neighborhood directly surrounding brain regions as contrasted with distant (>14 mm) interactions. The balance between local and distant functional interactions measured at rest forms a map that separates sensorimotor cortices from heteromodal association areas and further identifies regions that possess both high local and distant cortical-cortical interactions. Map estimates of network measures demonstrate that high local connectivity is most often associated with a high clustering coefficient, long path length, and low physical cost. Task performance changed the balance between local and distant functional coupling in a subset of regions, particularly, increasing local functional coupling in regions engaged by the task. The observed properties suggest that the brain has evolved a balance that optimizes information-processing efficiency across different classes of specialized areas as well as mechanisms to modulate coupling in support of dynamically changing processing demands. We discuss the implications of these observations and applications of the present method for exploring normal and atypical brain function.Psycholog

AC amplifiers with ultra-low corner frequency by using bootstrapping

A novel architecture for an AC (i.e. high-pass) amplifier is proposed allowing a drastic reduction of the cutoff frequency to the sub-Hertz range. It builds upon the classic AC configuration with a high gain amplifier and a parallel RC circuit in the feedback loop, by increasing the feedback resistance through bootstrapping. Resistance multiplying factors higher than four orders of magnitude are easily achievable. The basic principle can be applied to several practical implementations, though in this letter it is demonstrate with measurement results of an op-amp based discrete implementation.This work was financially supported by the following grants from the Spanish Research Agency: TEC2016-80396-C2-1-R and PID2019-107258RB-C32 (AEI/FEDER). M.Martincorena Arraiza was funded by the Ministry of Universities under grant BES-2017-080418

Fault detection of planetary gears based on signal space constellations

A new method to process the vibration signal acquired by an accelerometer placed in a planetary gearbox housing is proposed, which is useful to detect potential faults. The method is based on the phenomenological model and consists of the projection of the healthy vibration signals onto an orthonormal basis. Low pass components representation and Gram–Schmidt’s method are conveniently used to obtain such a basis. Thus, the measured signals can be represented by a set of scalars that provide information on the gear state. If these scalars are within a predefined range, then the gear can be diagnosed as correct; in the opposite case, it will require further evaluation. The method is validated using measured vibration signals obtained from a laboratory test bench.Grant PID2019-107258RB-C32 funded by MCIN/AEI/10.13039/501100011033. M.M.-A. has a predoctoral grant BES-2017-080418 funded by MCIN/AEI/10.13039/501100011033 and by ESF Investing in your future

Spatial competition shapes the dynamic mutational landscape of normal esophageal epithelium.

During aging, progenitor cells acquire mutations, which may generate clones that colonize the surrounding tissue. By middle age, normal human tissues, including the esophageal epithelium (EE), become a patchwork of mutant clones. Despite their relevance for understanding aging and cancer, the processes that underpin mutational selection in normal tissues remain poorly understood. Here, we investigated this issue in the esophageal epithelium of mutagen-treated mice. Deep sequencing identified numerous mutant clones with multiple genes under positive selection, including Notch1, Notch2 and Trp53, which are also selected in human esophageal epithelium. Transgenic lineage tracing revealed strong clonal competition that evolved over time. Clone dynamics were consistent with a simple model in which the proliferative advantage conferred by positively selected mutations depends on the nature of the neighboring cells. When clones with similar competitive fitness collide, mutant cell fate reverts towards homeostasis, a constraint that explains how selection operates in normal-appearing epithelium.This work was supported by grants from the Wellcome Trust to the Wellcome SangerInstitute (098051 and 296194) and Cancer Research UK Programme Grants to P.H.J.(C609/A17257 and C609/A27326). G.P. is supported by a Talento program fellowship from Comunidad de Madrid. B.A.H. and M.W.J.H. are supported by the MedicalResearch Council (Grant-in-Aid to the MRC Cancer unit grant no. MC_UU_12022/9 and NIRG to B.A.H. grant no. MR/S000216/1). M.W.J.H. acknowledges support fromthe Harrison Watson Fund at Clare College, Cambridge. B.A.H. acknowledges support from the Royal Society (grant no. UF130039). I.M. is funded by Cancer Research UK (C57387/A21777). S.D. benefited from the award of an ESPOD fellowship, 2018-21, from the Wellcome Sanger Institute and the European Bioinformatics Institute EMBL-EBI

Recurrent histone mutations in T-cell acute lymphoblastic leukaemia.

Mutations affecting key modifiable histone type 3 (H3; Supplementary Table 1) residues are frequent oncogenic events in certain solid tumours (Feinberg, et al 2016), and have also recently been implicated in a subset of acute myeloid leukaemia (AML)(Lehnertz, et al 2017). Here, we systematically reviewed the somatic mutations in >20,000 cancer specimens to identify tumours harbouring H3 mutations. In a subset of T-cell acute lymphoblastic leukaemia (T-ALL) we identified non-methionine mutations of the key modifiable H3 residues, lysine (K) 27 and 36