Deep Learning for Single-Molecule Science

Exploring and making predictions based on single-molecule data can be challenging, not only due to the sheer size of the datasets, but also because a priori knowledge about the signal characteristics is typically limited and poor signal-to-noise ratio. For example, hypothesis-driven data exploration, informed by an expectation of the signal characteristics, can lead to interpretation bias or loss of information. Equally, even when the different data categories are known, e.g., the four bases in DNA sequencing, it is often difficult to know how to make best use of the available information content. The latest developments in Machine Learning (ML), so-called Deep Learning (DL) offers an interesting, new avenues to address such challenges. In some applications, such as speech and image recognition, DL has been able to outperform conventional Machine Learning strategies and even human performance. However, to date DL has not been applied much in single-molecule science, presumably in part because relatively little is known about the 'internal workings' of such DL tools within single-molecule science as a field. In this Tutorial, we make an attempt to illustrate in a step-by-step guide how one of those, a Convolutional Neural Network, may be used for base calling in DNA sequencing applications. We compare it with a Support Vector Machine as a more conventional ML method, and and discuss some of the strengths and weaknesses of the approach. In particular, a 'deep' neural network has many features of a 'black box', which has important implications on how we look at and interpret data

New technologies for examining neuronal ensembles in drug addiction and fear

Correlational data suggest that learned associations are encoded within neuronal ensembles. However, it has been difficult to prove that neuronal ensembles mediate learned behaviours because traditional pharmacological and lesion methods, and even newer cell type-specific methods, affect both activated and non-activated neurons. Additionally, previous studies on synaptic and molecular alterations induced by learning did not distinguish between behaviourally activated and non-activated neurons. Here, we describe three new approaches—Daun02 inactivation, FACS sorting of activated neurons and c-fos-GFP transgenic rats — that have been used to selectively target and study activated neuronal ensembles in models of conditioned drug effects and relapse. We also describe two new tools — c-fos-tTA mice and inactivation of CREB-overexpressing neurons — that have been used to study the role of neuronal ensembles in conditioned fear

Predictions for the future of kallikrein-related peptidases in molecular diagnostics

Kallikrein-related peptidases (KLKs) form a cancer-related ensemble of serine proteases. This multigene family hosts the most widely used cancer biomarker that is PSA-KLK3, with millions of tests performed annually worldwide. The present report provides an overview of the biomarker potential of the extended KLK family (KLK1-KLK15) in various disease settings and envisages approaches that could lead to additional KLK-driven applications in future molecular diagnostics. Particular focus is given on the inclusion of KLKs into multifaceted cancer biomarker panels that provide enhanced diagnostic, prognostic and/or predictive accuracy in several human malignancies. Such panels have been described so far for prostate, ovarian, lung and colorectal cancers. The role of KLKs as biomarkers in non-malignant disease settings, such as Alzheimer’s disease and multiple sclerosis, is also commented upon. Predictions are given on the challenges and future directions regarding clinically oriented KLK research

Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications

A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”

Sources of stakeholder salience in the responsible investment movement: why do investors sign the Principles for Responsible Investment?

Since its inception in 2006, the United Nations-backed Principles for Responsible Investment (PRI) have grown to over 1300 signatories representing over $45 trillion. This growth is not slowing down. In this paper, we argue that there is a set of attributes which make the PRI salient as a stakeholder and its claim to sign the six PRI important to institutional investors. We use Mitchell et al.’s (Acad Manag Rev 22:853–886, 1997) theoretical framework of stakeholder salience, as extended by Gifford (J Bus Eth 92:79–97, 2010). We use as evidence confidential data from the annual survey of signatories carried out by the PRI in a 5-year period between 2007 and 2011. The findings highlight pragmatic and organizational legitimacy, normative and utilitarian power, and management values as the attributes that contribute most to the salience of the PRI as a stakeholder

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli

Changes in Seizure Frequency and Test-Retest Scores on the Wechsler Adult Intelligence Scale

Test-retest performance on the Wechsler Adult Intelligence Scale (WAIS) of two groups of adult epilepsy patients are presented and compared. In one group, Seizures Improved (SI) group, seizure frequency had decreased during the test-retest interval, and in the other group, Seizures Unimproved (SU) group, the number of seizures had either increased or stayed the same over the test-retest interval. The SI group showed a significant test-retest improvement on WAIS Verbal IQ, Performance 1Q, and Full Scale IQ, as well as on eight of 11 WAIS subtests. In comparison, the SU group showed significant increases only on the Performance IQ and Object Assembly subtest. Furthermore, differences between the two groups were observed in the pattern of test-retest changes seen on the Performance measures relative to the Verbal measures. The results suggest that change in seizure frequency is one of the factors associated with test-retest changes in the intellectual functioning of epilepsy patients. RÉSUMÉ Les rÉsultats obtenus À I‘Échelle de WAIS (Wechsler Adults Intelligence Scale) a partir d'une passation I (test) et d'une passation II (retest) chez deux groupes d'Épileptiques adultes sont prÉsentÉs et compares: (a) Dans un groupe la frequence des crises a diminue dur-ant I'intervalle “test-retest” (c'est a dire dans I'inter-valle separant la passation I (test) de la passation II (retest): Groupe des crises ameliorees (SI: seizures improved), (b) Dans l'autre groupe le nombre des crises au contraire a augmente ou bien est reste iden-tique au cours de I'intervalle “test-retest”: Groupe des crises non ameliorees (SU: seizures unimproved). Le groupe des “crises ameliorees” montre une amelioration significative tant sur le plan du QIV (quotient de I'echelle verbale), que du QIP (quotient de I'echelle performance) et du QIG (quotient global), ainsi que de 8 des subtests parmi les onze que contien I'echelle. En comparaison le groupe des “crises non ameliorees” ne montre une amelioration significative qu'au niveau du QIP et en particulier sur le subtest d'assemblage d'ob-jets (celui-ci faisant partie de I'echelle performance). De plus, on observe entre les deux groupes des differences du “type” des modifications entrainees par la situation “test-retest”, sur les rÉsultats obtenus a I'echelle performance et ceux obtensus a I'echelle verbale. Ces rÉsultats permettent de suggerer que, dans le fonctionnement intellectuel des sujets epileptiques, les changements dans la frequence des crises sont un des facteurs a mettre en correlation avec les changements observes a partir de la situation “test-retest”. RESUMEN Se compararon dos grupos de adultos con epilepsia por medio del rendimiento en dos tests de WAIS. En un grupo, la frecuencia de los ataques habia disminuido en el intervalo entre el primer test y el segundo [grupo con mejoria (SI)], mientras que en el otro el mimero de crisis no habia variado o habia au-mentado [grupo sin mejoria (SU)]. El grupo SI mostro una mejoria en laescala verbal CI, en la realizacion CI, en la escala total de CI y en los subtests WAIS. En comparacion, el grupo SU solo mostro un aumento significativo en la realizacion CI y en el subtest de Reunion de Objetos. Ademas, se observaron diferen-cias entre los dos grupos en lo que respecta a la prim-era y a la segunda prueba en la realizacion de las medidas verbales. Los resultados sugieren que los cambios en la frecuencia de los ataques juegan un papel en lo que respecta a funciÓn intelectual cuando se compara el primer WAIS con el segundo. ZUSAMMENFASSUNG Test und Retest Ergebnisse im WAIS von 2 Gruppen erwachsener Epileptiker werden dargestellt und ver-glichen. In einer Gruppe hatte die Anfallshaufigkeit wahrend des Test-Retest-Intervalls abgenommen– verbesserte Gruppe (SI)–und in einer anderen Gruppe war die Anfallshaufigkeit entweder gestiegen oder gleich geblieben wahrend des Test-Retest-Intervalls– unveranderte Gruppe (SU). Die SI-Gruppe zeigte signifikante Verbesserung zwischen Test und Retest im Verbal-IQ des WAIS, im Handlungsteil und im Gesamt-IQ ebenso wie in 8 von 11 WAIS Subtests. Im Vergleich hierzu zeigte die SU-Gruppe signifikante Verbesserung nur im Handlungs-IQ und im Objekte-zuordnungs-Subtest. Weiterhin wurden Unterschiede zwischen den beiden Gruppen im Muster der Test-Retest-Veranderungen im Verhaltnis des Handlung-steils zum Verbalteil bemerkt. Die Ergebnisse lassen vermuten, dalJ die Veranderung der Anfallshaufigkeit einer der Faktoren ist, der hinsichtlich der in-tellektuellen Funktion anfallskranker Patienten Bezie-hungen zu den Veranderungen des Test-Retest-Ergeb-nis aufweist.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65457/1/j.1528-1157.1981.tb04334.x.pd

Functional identification of biological neural networks using reservoir adaptation for point processes

The complexity of biological neural networks does not allow to directly relate their biophysical properties to the dynamics of their electrical activity. We present a reservoir computing approach for functionally identifying a biological neural network, i.e. for building an artificial system that is functionally equivalent to the reference biological network. Employing feed-forward and recurrent networks with fading memory, i.e. reservoirs, we propose a point process based learning algorithm to train the internal parameters of the reservoir and the connectivity between the reservoir and the memoryless readout neurons. Specifically, the model is an Echo State Network (ESN) with leaky integrator neurons, whose individual leakage time constants are also adapted. The proposed ESN algorithm learns a predictive model of stimulus-response relations in in vitro and simulated networks, i.e. it models their response dynamics. Receiver Operating Characteristic (ROC) curve analysis indicates that these ESNs can imitate the response signal of a reference biological network. Reservoir adaptation improved the performance of an ESN over readout-only training methods in many cases. This also held for adaptive feed-forward reservoirs, which had no recurrent dynamics. We demonstrate the predictive power of these ESNs on various tasks with cultured and simulated biological neural networks

Robot Assisted Training for the Upper Limb after Stroke (RATULS): study protocol for a randomised controlled trial.

BACKGROUND: Loss of arm function is a common and distressing consequence of stroke. We describe the protocol for a pragmatic, multicentre randomised controlled trial to determine whether robot-assisted training improves upper limb function following stroke. METHODS/DESIGN: Study design: a pragmatic, three-arm, multicentre randomised controlled trial, economic analysis and process evaluation. SETTING: NHS stroke services. PARTICIPANTS: adults with acute or chronic first-ever stroke (1 week to 5 years post stroke) causing moderate to severe upper limb functional limitation. Randomisation groups: 1. Robot-assisted training using the InMotion robotic gym system for 45 min, three times/week for 12 weeks 2. Enhanced upper limb therapy for 45 min, three times/week for 12 weeks 3. Usual NHS care in accordance with local clinical practice Randomisation: individual participant randomisation stratified by centre, time since stroke, and severity of upper limb impairment. PRIMARY OUTCOME: upper limb function measured by the Action Research Arm Test (ARAT) at 3 months post randomisation. SECONDARY OUTCOMES: upper limb impairment (Fugl-Meyer Test), activities of daily living (Barthel ADL Index), quality of life (Stroke Impact Scale, EQ-5D-5L), resource use, cost per quality-adjusted life year and adverse events, at 3 and 6 months. Blinding: outcomes are undertaken by blinded assessors. Economic analysis: micro-costing and economic evaluation of interventions compared to usual NHS care. A within-trial analysis, with an economic model will be used to extrapolate longer-term costs and outcomes. Process evaluation: semi-structured interviews with participants and professionals to seek their views and experiences of the rehabilitation that they have received or provided, and factors affecting the implementation of the trial. SAMPLE SIZE: allowing for 10% attrition, 720 participants provide 80% power to detect a 15% difference in successful outcome between each of the treatment pairs. Successful outcome definition: baseline ARAT 0-7 must improve by 3 or more points; baseline ARAT 8-13 improve by 4 or more points; baseline ARAT 14-19 improve by 5 or more points; baseline ARAT 20-39 improve by 6 or more points. DISCUSSION: The results from this trial will determine whether robot-assisted training improves upper limb function post stroke. TRIAL REGISTRATION: ISRCTN, identifier: ISRCTN69371850 . Registered 4 October 2013

A Novel Protein Isoform of the Multicopy Human NAIP Gene Derives from Intragenic Alu SINE Promoters

The human neuronal apoptosis inhibitory protein (NAIP) gene is no longer principally considered a member of the Inhibitor of Apoptosis Protein (IAP) family, as its domain structure and functions in innate immunity also warrant inclusion in the Nod-Like Receptor (NLR) superfamily. NAIP is located in a region of copy number variation, with one full length and four partly deleted copies in the reference human genome. We demonstrate that several of the NAIP paralogues are expressed, and that novel transcripts arise from both internal and upstream transcription start sites. Remarkably, two internal start sites initiate within Alu short interspersed element (SINE) retrotransposons, and a third novel transcription start site exists within the final intron of the GUSBP1 gene, upstream of only two NAIP copies. One Alu functions alone as a promoter in transient assays, while the other likely combines with upstream L1 sequences to form a composite promoter. The novel transcripts encode shortened open reading frames and we show that corresponding proteins are translated in a number of cell lines and primary tissues, in some cases above the level of full length NAIP. Interestingly, some NAIP isoforms lack their caspase-sequestering motifs, suggesting that they have novel functions. Moreover, given that human and mouse NAIP have previously been shown to employ endogenous retroviral long terminal repeats as promoters, exaptation of Alu repeats as additional promoters provides a fascinating illustration of regulatory innovations adopted by a single gene