Long-Term Relationships between Synaptic Tenacity, Synaptic Remodeling, and Network Activity

Long term time-lapse imaging reveals that individual synapses undergo significant structural remodeling not only when driven by activity, but also when network activity is absent, raising questions about how reliably individual synapses maintain connections

Improved Formability of Mg-AZ80 Alloy under a High Strain Rate in Expanding-Ring Experiments

Magnesium alloys offer a favored alternative to steels and aluminum alloys due to their low density and relatively high specific strength. Their application potentials are, however, impeded by poor formability at room temperature. In the current work, improved formability for the commercial magnesium AZ80 alloy was attained through the application of the high-rate electro-magnetic forming (EMF) technique. With the EMF system, elongation of 0.2 was achieved while only 0.11 is obtained through quasistatic loading. Systematic microstructural and textural investigations prior, during and post deformation under high strain-rate experiments were carried out using electron back-scattered diffraction (EBSD) and other microscopic techniques. The analysis indicates that enhanced elongation is achieved as a result of the combination of deformation, comprising basal and non-basal slip systems, twinning and dynamic recrystallization. An adopted EMF-forming technique is tested which results in enhanced elongation without failure and a higher degree of dynamically annealed microstructure

Measuring and Characterizing the Human Nasal Cycle.

Nasal airflow is greater in one nostril than in the other because of transient asymmetric nasal passage obstruction by erectile tissue. The extent of obstruction alternates across nostrils with periodicity referred to as the nasal cycle. The nasal cycle is related to autonomic arousal and is indicative of asymmetry in brain function. Moreover, alterations in nasal cycle periodicity have been linked to various diseases. There is therefore need for a tool allowing continuous accurate measurement and recording of airflow in each nostril separately. Here we provide detailed instructions for constructing such a tool at minimal cost and effort. We demonstrate application of the tool in 33 right-handed healthy subjects, and derive several statistical measures for nasal cycle characterization. Using these measures applied to 24-hour recordings we observed that: 1: subjects spent slightly longer in left over right nostril dominance (left = 2.63 ± 0.89 hours, right = 2.17 ± 0.89 hours, t(32) = 2.07, p < 0.05), 2: cycle duration was shorter in wake than in sleep (wake = 2.02 ± 1.7 hours, sleep = 4.5 ± 1.7 hours, (t(30) = 5.73, p < 0.0001). 3: slower breathing was associated with a more powerful cycle (the extent of difference across nostrils) (r = 0.4, p < 0.0001), and 4: the cycle was influenced by body posture such that lying on one side was associated with greater flow in the contralateral nostril (p < 0.002). Finally, we provide evidence for an airflow cycle in each nostril alone. These results provide characterization of an easily obtained measure that may have diagnostic implications for neurological disease and cognitive state

Example of processed data from a typical subject.

<p>(A) Average filtered nasal airflow peaks over time for right (blue) and left (green) nostrils (smoothed with a 20 minute window for display). Large red rectangle highlights a portion of sleep with right dominance indicated by black bar and negative inter nostril correlation (r = -0.44). Small red rectangle highlights a portion of wake with left dominance indicated by black bar and positive inter nostril correlation (r = 0.7). (B) Laterality index graph calculated and aligned for the data presented above. Light blue shading highlights low LI amplitude in wake (mean = 0.19) and light green highlights high amplitude in sleep (mean = 0.68).</p

The nasal cycle differed in wake and sleep.

<p>(A) Mean interval length. Inset: Mean over population. (B) Distribution of wake and sleep interval lengths across subjects. (C) Inter nostril correlation. Inset: Mean over population. (D) Mean LI amplitude Inset: Mean over population. (E) Mean LI. Inset: Mean over population. (F) Distribution of wake and sleep mean LI across subjects. (G) Right and left interval means during wake and sleep. In scatter plots each dot is a subject and the diagonal line is the unit slope line (X = Y). Error bars are SE.</p

Pre-processing stages.

<p>(A) Raw data overlaid with Hilbert transform and its peaks during 2 minute time scales. (B) Hilbert transform overlaid with its peaks and average during 30 minute time scales.</p

Schematic for nasal cycle logger.

<p>(A) Schematic of electronics. (B) Printed circuit board (PCB). Component-side in green, soldering-side in blue. (C) Picture of component-side. (D) Picture of soldering-side. (E) Component layout. (F) Illustration of low Pressure Sensor (1” H₂O to 30”H₂O). (G) The device in its assembled form. (H) Respiration cannulas positioned in subject’s nares.</p

Relation between nasal cycle and body posture.

<p>(A) Mean LI amplitude directly before and after position change. Data shown for all types of position change (To right, to left, to stomach, to back etc) pooled over 23 subjects. No significant difference is observed between directly before and after position change, indicating that position change alone does not produce an artifact in LI amplitude during sleep. (B) Correlation between Laterality index and body posture. Left: mean LI for each measured body position. Right: Comparison between ‘on right’ and ‘on left’ position LI means.</p