Postsynaptic α1-Adrenergic vasoconstriction is impaired in young patients with vasovagal syncope and is corrected by nitric oxide synthase inhibition

BACKGROUND: Syncope is a sudden transient loss of consciousness and postural tone with spontaneous recovery; the most common form is vasovagal syncope (VVS). During VVS, gravitational pooling excessively reduces central blood volume and cardiac output. In VVS, as in hemorrhage, impaired adrenergic vasoconstriction and venoconstriction result in hypotension. We hypothesized that impaired adrenergic responsiveness because of excess nitric oxide can be reversed by reducing nitric oxide. METHODS AND RESULTS: We recorded cardiopulmonary dynamics in supine syncope patients and healthy volunteers (aged 15-27 years) challenged with a dose-response using the α1-agonist phenylephrine (PE), with and without the nitric oxide synthase inhibitor N(G)-monomethyl-L-arginine, monoacetate salt (L-NMMA). Systolic and diastolic pressures among control and VVS were the same, although they increased after L-NMMA and saline+PE (volume and pressor control for L-NMMA). Heart rate was significantly reduced by L-NMMA (P<0.05) for control and VVS compared with baseline, but there was no significant difference in heart rate between L-NMMA and saline+PE. Cardiac output and splanchnic blood flow were reduced by L-NMMA for control and VVS (P<0.05) compared with baseline, while total peripheral resistance increased (P<0.05). PE dose-response for splanchnic flow and resistance were blunted for VVS compared with control after saline+PE, but enhanced after L-NMMA (P<0.001). Postsynaptic α1-adrenergic vasoconstrictive impairment was greatest in the splanchnic vasculature, and splanchnic blood flow was unaffected by PE. Forearm and calf α1-adrenergic vasoconstriction were unimpaired in VVS and unaffected by L-NMMA. CONCLUSIONS: Impaired postsynaptic α1-adrenergic vasoconstriction in young adults with VVS can be corrected by nitric oxide synthase inhibition, demonstrated with our use of L-NMMA

Open Access and Education Resources (OAER) and the analysis of University and Library Websites in Pakistan

The abrupt transition to online teaching and learning during COVID-19 has necessitated the need of providing information sources and textbooks online. The Open Access and Education Resources (OAER) have the potential to fill the gap which may have occurred due to fiscal constraints and budget cuts within Higher Education Institutions in developing countries. This study highlights the importance of OAER movement, its emergence as a strong information resource and its contribution in teaching and learning in higher education. The study also examines the current state and utilization of OAER resources in Pakistani higher education institutions. The authors have used two methods for completing this study. Literature review of OAER and the analysis of Pakistani higher education institution’s websites including their library websites. The study recommends to consider this valuable resource and advocating its use, creation and adaptation in Pakistani Higher Education Institutions at a national level. The study also focusses on the roles academic libraries and librarians could play in creating an awareness of OAER at their institutions and recommends policy level strategies which could lead to inclusion and promotion of OAER into the academic and research endeavors of faculty, students and researchers

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability distributions. An alternative view is that the brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property takes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that the inference strategies employed by humans may deviate from Bayes-optimal integration when the computational demands are high

Activity in perceptual classification networks as a basis for human subjective time perception

Despite being a fundamental dimension of experience, how the human brain generates the perception of time remains unknown. Here, we provide a novel explanation for how human time perception might be accomplished, based on non-temporal perceptual classification processes. To demonstrate this proposal, we build an artificial neural system centred on a feed-forward image classification network, functionally similar to human visual processing. In this system, input videos of natural scenes drive changes in network activation, and accumulation of salient changes in activation are used to estimate duration. Estimates produced by this system match human reports made about the same videos, replicating key qualitative biases, including differentiating between scenes of walking around a busy city or sitting in a cafe or office. Our approach provides a working model of duration perception from stimulus to estimation and presents a new direction for examining the foundations of this central aspect of human experience

Broadband, Polarization-Sensitive Photodetector Based on Optically-Thick Films of Macroscopically Long, Dense, and Aligned Carbon Nanotubes

Increasing performance demands on photodetectors and solar cells require the development of entirely new materials and technological approaches.Wereport on the fabrication and optoelectronic characterization of a photodetector based on optically-thick films of dense, aligned, and macroscopically long single-wall carbon nanotubes. The photodetector exhibits broadband response from the visible to the mid-infrared under global illumination, with a response time less than 32 ms. Scanning photocurrent microscopy indicates that the signal originates at the contact edges, with an amplitude and width that can be tailored by choosing different contact metals. A theoretical model demonstrates the photothermoelectric origin of the photoresponse due to gradients in the nanotube Seebeck coefficient near the contacts. The experimental and theoretical results open a new path for the realization of optoelectronic devices based on three-dimensionally organized nanotubes

Sharing vocabularies: towards horizontal alignment of values-driven business functions

This paper highlights the emergence of different ‘vocabularies’ that describe various values-driven business functions within large organisations and argues for improved horizontal alignment between them. We investigate two established functions that have long-standing organisational histories: Ethics and Compliance (E&C) and Corporate Social Responsibility (CSR). By drawing upon research on organisational alignment, we explain both the need for and the potential benefit of greater alignment between these values-driven functions. We then examine the structural and socio-cultural dimensions of organisational systems through which E&C and CSR horizontal alignment can be coordinated to improve synergies, address tensions, and generate insight to inform future research and practice in the field of Business and Society. The paper concludes with research questions that can inform future scholarly research and a practical model to guide organizations’ efforts towards inter-functional, horizontal alignment of values-driven organizational practice

Warming of Central European lakes and their response to the 1980s climate regime shift

Lake surface water temperatures (LSWTs) are sensitive to atmospheric warming and have previously been shown to respond to regional changes in the climate. Using a combination of in situ and simulated surface temperatures from 20 Central European lakes, with data spanning between 50 and ∼100 years, we investigate the long-term increase in annually averaged LSWT. We demonstrate that Central European lakes are warming most in spring and experience a seasonal variation in LSWT trends. We calculate significant LSWT warming during the past few decades and illustrate, using a sequential t test analysis of regime shifts, a substantial increase in annually averaged LSWT during the late 1980s, in response to an abrupt shift in the climate. Surface air temperature measurements from 122 meteorological stations situated throughout Central Europe demonstrate similar increases at this time. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems. Quantifying the response of LSWT increase to large-scale and abrupt climatic shifts is essential to understand how lakes will respond in the future

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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Temporal regularity of the environment drives time perception

It’s reasonable to assume that a regularly paced sequence should be perceived as regular, but here we show that perceived regularity depends on the context in which the sequence is embedded. We presented one group of participants with perceptually regularly paced sequences, and another group of participants with mostly irregularly paced sequences (75% irregular, 25% regular). The timing of the final stimulus in each sequence could be varied. In one experiment, we asked whether the last stimulus was regular or not. We found that participants exposed to an irregular environment frequently reported perfectly regularly paced stimuli to be irregular. In a second experiment, we asked participants to judge whether the final stimulus was presented before or after a flash. In this way, we were able to determine distortions in temporal perception as changes in the timing necessary for the sound and the flash to be perceived synchronous. We found that within a regular context, the perceived timing of deviant last stimuli changed so that the relative anisochrony appeared to be perceptually decreased. In the irregular context, the perceived timing of irregular stimuli following a regular sequence was not affected. These observations suggest that humans use temporal expectations to evaluate the regularity of sequences and that expectations are combined with sensory stimuli to adapt perceived timing to follow the statistics of the environment. Expectations can be seen as a-priori probabilities on which perceived timing of stimuli depend