Nucleic acids labeled with a fluorophore/quencher pair are widely used as probes in biomedical research and molecular diagnostics. Here we synthesized novel DNA molecular beacons double labeled with the identical dyes (R6G, ROX and Cy5) at 5′- and 3′-end and studied their photo physical properties. We demonstrated that fluorescence quenching by formation of the homo dimer exciton in such molecular beacons allows using them in homogeneous assays. Further, we developed and evaluated homo Yin-Yang DNA probes labeled with identical dyes and used them for detection of low copy HIV RNA by RT-qPCR. They demonstrated improved sensitivity (LLQ: 10 vs 30 copies mL-1) in comparison to commercially available Abbott RealTime HIV-1 kit based on VICBHQ dyes both for model mixtures (naive human plasma with added deactivated HIV-1 virus) and for preliminarily confirmed 36 clinical samples (4 vs 1 positive ones for low-copy samples).
After a protracted history, neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream (Kamiya, 2011; Linden, 2014; Sitaram et al., 2017). A debate now centres on the extent to which neurofeedback alters brain function and behaviour, and the mechanisms through which neurofeedback operates (e.g., neurofeedback-specific versus nonspecific). A series of correspondences in Lancet Psychiatry (Micoulaud-Franchi & Fovet, 2016; Pigott et al., 2017; Schönenberg et al., 2017b, 2017a; Thibault & Raz, 2016a, 2016b) and Brain (Fovet et al., 2017; Schabus, 2017, 2018; Schabus et al., 2017; Thibault, Lifshitz, & Raz, 2017, 2018; Witte, Kober, & Wood, 2018) discusses the theoretical arguments and empirical data backing the involvement of these two mechanisms.
Intracortical microstimulation (ICMS) of the primary somatosensory cortex (S1) can produce percepts that mimic somatic sensation and, thus, has potential as an approach to sensorize prosthetic limbs. However, it is not known whether ICMS could recreate active texture exploration-the ability to infer information about object texture by using one's fingertips to scan a surface. Here, we show that ICMS of S1 can convey information about the spatial frequencies of invisible virtual gratings through a process of active tactile exploration. Two rhesus monkeys scanned pairs of visually identical screen objects with the fingertip of a hand avatar-controlled first via a joystick and later via a brain-machine interface-to find the object with denser virtual gratings. The gratings consisted of evenly spaced ridges that were signaled through individual ICMS pulses generated whenever the avatar's fingertip crossed a ridge. The monkeys learned to interpret these ICMS patterns, evoked by the interplay of their voluntary movements and the virtual textures of each object, to perform a sensory discrimination task. Discrimination accuracy followed Weber's law of just-noticeable differences (JND) across a range of grating densities; a finding that matches normal cutaneous sensation. Moreover, 1 monkey developed an active scanning strategy where avatar velocity was integrated with the ICMS pulses to interpret the texture information. We propose that this approach could equip upper-limb neuroprostheses with direct access to texture features acquired during active exploration of natural objects.
The Internet comprises a decentralized global system that serves humanity's collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a "human brain/cloud interface" ("B/CI"), would be based on technologies referred to here as "neuralnanorobotics." Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain. Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain's ∼86 × 109 neurons and ∼2 × 1014 synapses. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood-brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (synaptobots). They would then wirelessly transmit up to ∼6 × 1016 bits per second of synaptically processed and encoded human-brain electrical information via auxiliary nanorobotic fiber optics (30 cm3) with the capacity to handle up to 1018 bits/sec and provide rapid data transfer to a cloud based supercomputer for real-time brain-state monitoring and data extraction. A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge. Other anticipated applications include myriad opportunities to improve education, intelligence, entertainment, traveling, and other interactive experiences. A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as "transparent shadowing" (TS). Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family.
Previously, the mathematical models (CoMPaS and CoM-III) of primary tumor (PT) growth and secondary distant metastases (sdMTS) growth of breast cancer (BC) considering TNM classification have been presented (Tyuryumina E., Neznanov A.; 2017, 2018). Goal: To detect the earliest diagnostics period of visible sdMTS via CoMPaS and CoM-III.
The article includes the observation of the cloud services and technologies usage. The article contains a review of mathematical analysis of cardiac information using cloud technology, which produces storage, analysis and forecasting on the basis of owned data. In addition, the authors consider the possibility of integrating cloud technologies with external systems. The massive use of mobile devices for the removal of the electrocardiogram (ECG) leads to a quantitative increase of the patients number available for ECG investigation. Thus, there are new opportunities to research the oscillatory processes of long-term dynamics of the individual state of the cardiovascular system (CVS) of any patient. The article demonstrates new opportunities the long-term continuous monitoring of the patients CVS, which allows identifying regularities of the dynamics of the CVS. Also this article comprises the observation of the existence of an adequate model of CVS as a distributed nonlinear self-oscillating system of the class model returns the Fermi-Pasta-Ulam (FPU).
The idea of forced external synchronization of the heart dynamics by the canonical FPU spectrum with a purpose to lower the rate of its desynchronization in some pathological cases has been hypothesized by the authors. It was concluded that a heart being a multi resonant distributed dynamic ion containing system may be resonantly influenced by applying to it the canonical FPU electromagnetic spectrum, which can supposedly decrease the rate of desynchronization in the ECG Fourier spectrum for example in case of arrhythmia. The complex FPU recurrences found in the deep-water dynamics studies were compared with real ECG Fourier images in a sequence of time periods. For choosing the appropriate form of the external FPU canonical spectrum, the two different forms of the ECG Fourier spectra were studied: a rectangular pulse spectrum and exponential pulse spectrum. The two functions were taken to form the external synchronizing canonical FPU recurrence spectrum and were put into the right part of the equations of the previously developed mathematical model as perturbing functions. The computer study of the model simulating arrhythmia with a synchronizing perturbing part in a form of the canonical FPU recurrence spectrum changed the solutions of the model to the forms characteristic for normally functioning heart. Thus, the hypothesis has been confirmed,
Increasing evidence suggests that neuronal communication is a defining property of functionally specialized brain networks and that it is implemented through synchronization between population activities of distinct brain areas. The detection of long-range coupling in electroencephalography (EEG) and magnetoencephalography (MEG) data using conventional metrics (such as coherence or phase-locking value) is by definition contaminated by spatial leakage. Methods such as imaginary coherence, phase-lag index or orthogonalized amplitude correlations tackle spatial leakage by ignoring zero-phase interactions. Although useful, these metrics will by construction lead to false negatives in cases where true zero-phase coupling exists in the data and will underestimate interactions with phase lags in the vicinity of zero. Yet, empirically observed neuronal synchrony in invasive recordings indicates that it is not uncommon to find zero or close-to-zero phase lag between the activity profiles of coupled neuronal assemblies. Here, we introduce a novel method that allows us to mitigate the undesired spatial leakage effects and detect zero and near zero phase interactions. To this end, we propose a projection operation that operates on sensor-space cross-spectrum and suppresses the spatial leakage contribution but retains the true zero-phase interaction component. We then solve the network estimation task as a source estimation problem defined in the product space of interacting source topographies. We show how this framework provides reliable interaction detection for all phase-lag values and we thus refer to the method as Phase Shift Invariant Imaging of Coherent Sources (PSIICOS). Realistic simulations demonstrate that PSIICOS has better detector characteristics than existing interaction metrics. Finally, we illustrate the performance of PSIICOS by applying it to real MEG dataset recorded during a standard mental rotation task. Taken together, using analytical derivations, data simulations and real brain data, this study presents a novel source-space MEG/EEG connectivity method that overcomes previous limitations and for the first time allows for the estimation of true zero-phase coupling via non-invasive electrophysiological recordings.
Cardiovascular disease associated with metabolic syndrome has a high prevalence, but the mechanistic basis of metabolic cardiomyopathy remains poorly understood. We characterised the cardiac transcriptome in a murine metabolic syndrome (MetS) model (LDLR−/−; ob/ob, DKO) relative to the healthy, control heart (C57BL/6, WT) and the transcriptional changes induced by ACE-inhibition in those hearts. RNA-Seq, differential gene expression and transcription factor analysis identified 288 genes differentially expressed between DKO and WT hearts implicating 72 pathways. Hallmarks of metabolic cardiomyopathy were increased activity in integrin-linked kinase signalling, Rho signalling, dendritic cell maturation, production of nitric oxide and reactive oxygen species in macrophages, atherosclerosis, LXR-RXR signalling, cardiac hypertrophy, and acute phase response pathways. ACE-inhibition had a limited effect on gene expression in WT (55 genes, 23 pathways), and a prominent effect in DKO hearts (1143 genes, 104 pathways). In DKO hearts, ACE-I appears to counteract some of the MetS-specific pathways, while also activating cardioprotective mechanisms. We conclude that MetS and control murine hearts have unique transcriptional profiles and exhibit a partially specific transcriptional response to ACE-inhibition.