The LIF detection system (Figure 1 ) had a 488 nm laser (CrystaLaser; Reno, NV) aimed into a Zeiss Axio Observer.A1 inverted microscope (Jena, Germany) fitted with a Chroma ET-488 nm laser bandpass set (Rockingham, VT). Laser power exiting the 20x microscope objective was 4.8 mW. The microscope was fitted with a Hamamatsu PMT (Bridgewater, NJ) with a Stanford Research Systems SR-560 preamplifier (Sunnyvale, CA). Analog PMT voltage signal was converted to digital using a NI USB-6212 analog-to-digital converter (ADC; National Instruments; Austin, TX) and recorded at 20 Hz using LabVIEW software (National Instruments). μCE voltages were controlled using two high voltage power supplies (Stanford Research Systems) and a custom designed voltage switching box. Platinum electrodes ran from this box to the microchip reservoirs to apply the injection and separation voltages. Microchips were operated using pinched sample loading [33 ] with a 60 sec injection time as described previously [34 ]. Separation fluorescence signal was measured 2 cm down the channel from the intersection. All separations were performed at room temperature [35 (link)–36 (link)].
Ni usb 6212
Manufactured by National Instruments
Sourced in United States, Morocco
The NI USB-6212 is a multifunction data acquisition (DAQ) device from National Instruments. It provides 16 analog input channels, two analog output channels, and 16 digital input/output channels. The device connects to a computer via a USB interface and is suitable for a variety of measurement and control applications.
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Lab products found in correlation
9 protocols using ni usb 6212
1
Microfluidic Separation with LIF Detection
2
Cerebrovascular Responses to Exercise
3
Electrode Placement for EEG-based BCI
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Ag/AgCl electrodes (Ambu Neuroline 720, Ambu, Ballerup, Denmark) applied for EEG measurements were positioned according to the international 10–20 standard, on the C3, Oz, and Cz locations. Two scalp EEG channels were used: Oz referenced to Cz (SSVEP-BCI channel) and C3 referenced to Cz (ERD-BCI channel). Ground electrode was placed on the forehead. Impedances of the skin electrode junctions were maintained below 5 kΩ. Signals were amplified 20 k times and hardware band-pass filtered over the range 0.1–40 Hz, using PSYLAB EEG8 biological amplifier combined with PSYLAB SAM unit (Contact Precision Instruments, London, UK). Signals were digitized with 500 Hz sampling frequency using NI USB-6212 (National Instruments, Austin, TX, USA) card.
4
Cerebrovascular Dynamics Measurement
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Data was collected at 500 Hz via an analog-to-digital unit (NI-USB-6212, National Instruments) and custom-written code within MATLAB (v2014a, TheMathworks Inc, Natick, Massachusetts). 38 (link) Beat-to-beat data was processed offline using the QRS complex of the ECG. 38 (link) The left MCAv signals for CON was used for analysis. However, if left MCAv was not obtainable or had noise, the right MCAv signal was used. 38 (link) In individuals post-stroke, the ipsilesional hemisphere's MCAv signal was used to compare to CON.
5
Electrohydrodynamic Printing Technique
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The printer setup consisted of a printer head and a platform. The printer head was configured with a glass nanopipette held in a three‐axis translation stage and the platform was composed of a three‐axis stepping motorized stage with a 50 nm precision (XA05A, ZA05A, Kohzu Precision), an indium tin oxide (ITO)‐coated glass plate placed on the stage as a back electrode, and a substrate on the back electrode. During EHD printing, the pipette‐substrate gap was fixed to 5 µm and programmed electric pulses with a voltage amplitude of 360 V and a length ranging from 4 s to 5 ms were applied to the back electrode using a pulse generator (NI USB‐6212, National Instruments) with an amplifier (AMJ‐2B10, Matsusada Precision Inc.). The entire EHD printing process was monitored in real‐time by using a side‐view optical microscope consisting of a long working distance objective (50×, 0.55 NA, Mitutoyo Plan Apo) and a CCD camera (DCC1545M, Thorlabs). The printing was performed under controlled relative humidity (30%) by mass flow controllers (SLA5800, brooks instrument) and controlled temperature (25 ℃) inside a custom‐made environment enclosure.
6
Cerebrovascular Response Quantification Protocol
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Raw data acquisition occurred through an analog‐to‐digital unit (NI‐USB‐6212, National Instruments) and custom written software operating in MATLAB (v2014a, The Mathworks Inc. Natick, MA). Sampling of all variables was at 500 Hz and then interpolated to 2.0 Hz. As in our previous work, three‐second averages were calculated and smoothed using a 9‐s sliding window average. (Alwatban et al., 2020 ; Billinger et al., 2017 ; Kaufman et al., 2019 ; Kempf & A., Lui, Y., 2019 ; Ward et al., 2018 ) We used R version 3.2.4 (R Core team, Vienna, Austria) with the “nls” function package to model the response. Data with RR intervals > 5 Hz or changes in peak blood flow velocity of > 10 cm/s in a single cardiac cycle were considered artifact and censored. If an acquisition consisted of > 15% censored cardiac cycles, the entire sample was discarded. The cerebrovascular response (CVR) was calculated as the difference between the mean MCAv sampled between minute 3 and 4.5 during steady‐state exercise and the resting MCAv (mean MCAv over the first 90 s of the 8‐min recording). (Kaufman et al., 2019 ; Kempf & A., Lui, Y., 2019 ; Sisante et al., 2019 ) The percent change in MCAv from rest to exercise (%ΔMCAv) was calculated as the CVR divided by resting MCAv multiplied by 100. The CVR and %ΔMCAv were calculated separately for the stroke‐affected and non‐affected sides in each participant.
7
Multimodal Behavior Tracking and Analysis
8
Multimodal Monitoring of Cerebrovascular Dynamics
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Individuals were instrumented with the following equipment: (1) transcranial Doppler ultrasound (Multigon Industries Inc., Yonkers, NY), an adjustable headband, and 2‐MHz transcranial Doppler ultrasound probes for acquisition of MCAv (cm×s−1). The transcranial Doppler ultrasound sonographer was blinded to the side of stroke and entered the room only after the participant was set up to find the MCAv signal; (2) A 5‐lead ECG (Cardiocard, Nasiff Associates, Central Square, NY) recorded heart rate (HR); (3) beat‐to‐beat MAP was obtained from the left middle finger (Finometer, Finapres Medical Systems, Amsterdam, The Netherlands); and (4) nasal cannula and capnograph (BCI Capnocheck Sleep 9004 Smiths Medical, Dublin, OH). We monitored PETCO2 to ensure participants did not hyperventilate,8 resulting in lower PETCO2 and cerebral artery vasoconstriction. Raw data acquisition occurred through an analog‐to‐digital unit (NI‐USB‐6212, National Instruments) and custom‐written software operating in MATLAB (v2014a, The Mathworks Inc., Natick, MA).
9
Optical Trapping Apparatus Calibration
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The optical trapping apparatus (Fig. 1a) is a simplified setup of the one that we described in detail elsewhere. 13 Briefly, a collimated 330 mW, 980 nm laser beam (unless mentioned, all opto-mechanical components were obtained from Thorlabs, Dachau, Germany) with variable power is coupled to the optical path of a standard microscope chassis (Olympus CH, Tokyo, Japan). To form the optical trap, the laser beam is tightly focused in the flow cell by a high-numerical aperture objective (Neofluar 100× 1.3 NA, Zeiss, Germany). The position of a trapped particle is monitored by the transmitted laser light, which, after collection by an air condenser (Olympus, Tokyo, Japan), is cast on a quadrant photodetector (QPD). The analog difference signals that encode the bead position are digitized (NI USB-6212, National Instruments, Austin, TX, US) and analyzed using a custom-written LabVIEW routine.
The trap stiffness κ and the detector response were calibrated by recording the power spectrum of the position signal of the trapped bead and applying the equipartition theorem. 14 The thermal motion of the trapped particle is detected by the QPD and transformed into a Lorentzian power spectrum. Fig. 2 shows the power spectrum (black) of a 4.39 μm particle in water at 20 °C for several laser powers. The linear optical trapping stiffness κ for small particle displacements (
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The trap stiffness κ and the detector response were calibrated by recording the power spectrum of the position signal of the trapped bead and applying the equipartition theorem. 14 The thermal motion of the trapped particle is detected by the QPD and transformed into a Lorentzian power spectrum. Fig. 2 shows the power spectrum (black) of a 4.39 μm particle in water at 20 °C for several laser powers. The linear optical trapping stiffness κ for small particle displacements (
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