793 research outputs found
Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients.
Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols
Phylogenetic and structural analysis of centromeric DNA and kinetochore proteins
BACKGROUND: Kinetochores are large multi-protein structures that assemble on centromeric DNA (CEN DNA) and mediate the binding of chromosomes to microtubules. Comprising 125 base-pairs of CEN DNA and 70 or more protein components, Saccharomyces cerevisiae kinetochores are among the best understood. In contrast, most fungal, plant and animal cells assemble kinetochores on CENs that are longer and more complex, raising the question of whether kinetochore architecture has been conserved through evolution, despite considerable divergence in CEN sequence. RESULTS: Using computational approaches, ranging from sequence similarity searches to hidden Markov model-based modeling, we show that organisms with CENs resembling those in S. cerevisiae (point CENs) are very closely related and that all contain a set of 11 kinetochore proteins not found in organisms with complex CENs. Conversely, organisms with complex CENs (regional CENs) contain proteins seemingly absent from point-CEN organisms. However, at least three quarters of known kinetochore proteins are present in all fungi regardless of CEN organization. At least six of these proteins have previously unidentified human orthologs. When fungi and metazoa are compared, almost all have kinetochores constructed around Spc105 and three conserved multi-protein linker complexes (MIND, COMA, and the NDC80 complex). CONCLUSION: Our data suggest that critical structural features of kinetochores have been well conserved from yeast to man. Surprisingly, phylogenetic analysis reveals that human kinetochore proteins are as similar in sequence to their yeast counterparts as to presumptive Drosophila melanogaster or Caenorhabditis elegans orthologs. This finding is consistent with evidence that kinetochore proteins have evolved very rapidly relative to components of other complex cellular structures
Neuroimaging of serotonin transporters in post-stroke pathological crying
Pathological crying (PC) is a neuropsychiatric disorder characterized by an excessive tendency towards crying after brain damage. To elucidate the role of serotonin neurotransmission for PC, a pilot study was performed using single photon emission computed tomography with [123I]β-CIT to estimate central (midbrain/pons and thalamus/hypothalamus) serotonin transporter (SERT) densities in 15 stroke patients who did or did not have PC. SERT binding ratios in midbrain/pons were significantly lower in the PC subgroup
In operandi observation of dynamic annealing: a case study of boron in germanium nanowire devices
We report on the implantation of boron in individual, electrically contacted germanium nanowires with varying diameter and present a technique that monitors the electrical properties of a single device during implantation of ions. This method gives improved access to study the dynamic annealing ability of the nanowire at room temperature promoted by its quasi-one-dimensional confinement. Based on electrical data, we find that the dopant activation efficiency is nontrivially diameter dependent. As the diameter decreases, a transition from a pronounced dynamic-annealing to a radiation-damage dominated regime is observed
Communicating the Neuroscience of Psychopathy and Its Influence on Moral Behavior : Protocol of Two Experimental Studies
Neuroscience has identified brain structures and functions that correlate with psychopathic tendencies. Since psychopathic traits can be traced back to physical neural attributes, it has been argued that psychopaths are not truly responsible for their actions and therefore should not be blamed for their psychopathic behaviors. This experimental research aims to evaluate what effect communicating this theory of psychopathy has on the moral behavior of lay people. If psychopathy is blamed on the brain, people may feel less morally responsible for their own psychopathic tendencies and therefore may be more likely to display those tendencies. An online study will provide participants with false feedback about their psychopathic traits supposedly based on their digital footprint (i.e., Facebook likes), thus classifying them as having either above-average or below-average psychopathic traits and describing psychopathy in cognitive or neurobiological terms. This particular study will assess the extent to which lay people are influenced by feedback regarding their psychopathic traits, and how this might affect their moral behavior in online tasks. Public recognition of these potential negative consequences of neuroscience communication will also be assessed. A field study using the lost letter technique will be conducted to examine lay people's endorsement of neurobiological, as compared to cognitive, explanations of criminal behavior. This field and online experimental research could inform the future communication of neuroscience to the public in a way that is sensitive to the potential negative consequences of communicating such science. In particular, this research may have implications for the future means by which neurobiological predictors of offending can be safely communicated to offenders.Peer reviewe
Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies
fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factor
Silicon Photonic Architecture for Training Deep Neural Networks with Direct Feedback Alignment
There has been growing interest in using photonic processors for performing
neural network inference operations; however, these networks are currently
trained using standard digital electronics. Here, we propose on-chip training
of neural networks enabled by a CMOS-compatible silicon photonic architecture
to harness the potential for massively parallel, efficient, and fast data
operations. Our scheme employs the direct feedback alignment training
algorithm, which trains neural networks using error feedback rather than error
backpropagation, and can operate at speeds of trillions of multiply-accumulate
(MAC) operations per second while consuming less than one picojoule per MAC
operation. The photonic architecture exploits parallelized matrix-vector
multiplications using arrays of microring resonators for processing
multi-channel analog signals along single waveguide buses to calculate the
gradient vector for each neural network layer in situ. We also experimentally
demonstrate training deep neural networks with the MNIST dataset using on-chip
MAC operation results. Our novel approach for efficient, ultra-fast neural
network training showcases photonics as a promising platform for executing AI
applications.Comment: 15 pages, 6 figure
NADH Nitrate Reductase and NAD(P)H Nitrate Reductase in Genetic Variants and Regenerating Callus of Maize
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