Implementation of an ST-Segment Elevation Myocardial Infarction Bypass Protocol in the Northern United Arab Emirates.

OBJECTIVE: The aim was to evaluate the translation of an ST-segment elevation myocardial infarction (STEMI) bypass protocol to the outcomes of patients with acute coronary syndrome in the Emirate of Ras al-Khaimah in the United Arab Emirates (UAE). METHODS: A prospective cohort study was conducted, which included all patients who had a prehospital 12-lead electrocardiogram (ECG) performed by ambulance crews. Analysis of those who were identified as having STEMI and who subsequently underwent percutaneous coronary intervention (PCI) was performed. RESULTS: A total of 152 patients had a 12-lead ECG performed during the pilot study period (February 24, 2016-August 31, 2016) with 118 included for analysis. Mean patient age was 52 years. There were 87 male (74%) and 31 female (26%) patients. Twenty-nine patients suffered a STEMI, and data were available for 11 who underwent PCI. There was no mortality, and no major adverse cardiac events were reported. The median door-to-balloon (D2B) time was 73 min (range 48-124), and 81% of patients had a D2B time < 90 min. Discharge data were available for six patients: All were discharged home with no impediments to rehabilitation. CONCLUSION: This pilot study has demonstrated agreement with the existing literature surrounding prehospital ECG and PCI activation in an unstudied STEMI population and in a novel clinical setting. It has demonstrated a D2B time of < 90 min in over 80% of STEMI patients, and a faster mean D2B time than self-presentations (mean 77 min vs. 113 min), with no associated mortality or major adverse cardiac events.

Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period.

Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.

Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks.

In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics.

The upregulation of specific interleukin (IL) receptor antagonists and paradoxical enhancement of neuronal apoptosis due to electrode induced strain and brain micromotion.

The high mechanical mismatch between stiffness of silicon and metal microelectrodes and soft cortical tissue, induces strain at the neural interface which likely contributes to failure of the neural interface. However, little is known about the molecular outcomes of electrode induced low-magnitude strain (1-5%) on primary astrocytes, microglia and neurons. In this study we simulated brain micromotion at the electrode-brain interface by subjecting astrocytes, microglia and primary cortical neurons to low-magnitude cyclical strain using a biaxial stretch device, and investigated the molecular outcomes of induced strain in vitro. In addition, we explored the functional consequence of astrocytic and microglial strain on neural health, when they are themselves subjected to strain. Quantitative real-time PCR array (qRT-PCR Array) analysis of stretched astrocytes and microglia showed strain specific upregulation of an Interleukin receptor antagonist - IL-36Ra (previously IL-1F5), to ≈ 1018 and ≈ 236 fold respectively. Further, IL-36Ra gene expression remained unchanged in astrocytes and microglia treated with bacterial lipopolysaccharide (LPS) indicating that the observed upregulation in stretched astrocytes and microglia is potentially strain specific. Zymogram and western blot analysis revealed that mechanically strained astrocytes and microglia upregulated matrix metalloproteinases (MMPs) 2 and 9, and other markers of reactive gliosis such as glial fibrillary acidic protein (GFAP) and neurocan when compared to controls. Primary cortical neurons when stretched with and without IL-36Ra, showed a ≈ 400 fold downregulation of tumor necrosis factor receptor superfamily, member 11b (TNFRSF11b). Significant upregulation of members of the caspase cysteine proteinase family and other pro-apoptotic genes was also observed in the presence of IL-36Ra than in the absence of IL-36Ra. Adult rats when implanted with microwire electrodes showed upregulation of IL-36Ra (≈ 20 fold) and IL-1Ra (≈ 1500 fold) 3 days post-implantation (3 DPI), corroborating in vitro results, although these transcripts were drastically down regulated by ≈ 20 fold and ≈ 1488 fold relative to expression levels 3 DPI, at the end of 12 weeks post-implantation (12 WPI). These results demonstrate that IL receptor antagonists may be negatively contributing to neuronal health at acute time-points post-electrode implantation.

Implanted neural interfaces: biochallenges and engineered solutions.

Neural interfaces are connections that enable two-way exchange of information with the nervous system. These connections can occur at multiple levels, including with peripheral nerves, with the spinal cord, or with the brain; in many instances, fundamental biophysical and biological challenges are shared across these levels. We review these challenges, including selectivity, stability, resolution versus invasiveness, implant-induced injury, and the host-interface response. Subsequently, we review the engineered solutions to these challenges, including electrode designs and geometry, stimulation waveforms, materials, and surface modifications. Finally, we consider emerging opportunities to improve neural interfaces, including cellular-level silicon to neuron connections, optical stimulation, and approaches to control inflammation. Overcoming the biophysical and biological challenges will enable effective high-density neural interfaces for stimulation and recording.