Tn1012 st

Manufactured by ADInstruments

Sourced in Australia

The TN1012/ST is a laboratory equipment product designed for data acquisition and analysis. It is a versatile device that can be used to measure and record various types of signals and data. The product's core function is to capture, process, and store data from experiments or other research applications.

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Lab products found in correlation

Bio amp fe231, by ADInstruments (2 mentions) Mlt0380 d, by ADInstruments (2 mentions) Powerlab 16 35, by ADInstruments (2 mentions) Powerlab 2 26 acquisition device, by ADInstruments (2 mentions) Whole body scanner, by Siemens (1 mentions) Powerlab 8 35, by ADInstruments (1 mentions)

7 protocols using tn1012 st

Multimodal Monitoring of Vital Signs

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Blood pressure, respiratory rate, and heart rate were monitored using an electrophysiological data acquisition system (PowerLab 16/35, AD Instruments, Castle Hill, Australia). Mean blood pressure was measured at the carotid artery with a 24G catheter using a reusable BP transducer (MLT0380/D, AD Instruments, Castle Hill, Australia). The carotid artery was also used to collect blood samples and to create a haemorrhage. The tail vein was cannulated for intravenous fluid infusion. Respiratory rate and heart rate were measured non-invasively and recorded (Figure 1). The respiration rate was calculated using PowerLab-connected pulse transducers (TN1012/ST, AD Instruments, Castle Hill, Australia). Heart rate was measured using PowerLab-connected biological amplifiers (Bio Amp FE231, AD Instruments, Castle Hill, Australia).

Saracoglu A., Saracoglu K.T., Ergun I.S., Yildirim M., Akca M., Demirtas C, & Tetik S. (2022). The effects of hydroxyethyl starch and gelatine on lung tissue and coagulation during the resuscitation of rats with traumatic haemorrhagic shock. Anaesthesiology Intensive Therapy, 54(5), 393-401.

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Autonomic Nervous System Dysregulation and Cognition

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As autonomic nervous system dysregulation and, specifically, heart rate variability (HRV) are implicated in the pathophysiology of obesity [26 (link)], we measured HRV using a pulse transducer (TN1012/ST; ADInstruments, Sydney, Australia) that attached to the participant's thumb and connected to a PowerLab 2/26 acquisition device (ML826; ADInstruments).
Baseline eye blink rate (EBR) positively correlates with central dopamine function [27 (link)], which has been shown to vary with BMI and which is suggested to play a role in the association between BMI and cognitive function [28 (link)]. Therefore, concurrently with the HRV measurement, a 5‐minute video of participants' faces was recorded using a webcam while they were instructed to let their mind wander but to not fall asleep. The total number of blinks for each participant was averaged over the recording period to produce EBR in blinks per minute.

Chen H.A., Hovens I.B., Davis X.S., Hutelin Z., Wall K.M, & Small D.M. (2022). Identification of a novel link between adiposity and visuospatial perception. Obesity (Silver Spring, Md.), 31(2), 423-433.

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Multiparameter Biometrics in Rodents

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Hemoglobin oxygen saturation, respiratory rate per minute, heart rate, and core temperature were measured noninvasively and recorded. Blood pressure, respiratory rate, and heart rate were monitored using an electrophysiological data acquisition system (PowerLab 16/35, AD Instruments, Castle Hill, Australia). Blood pressure was measured at the carotid artery with a 24-catheter employing a reusable BP transducer (MLT0380/D, AD Instruments, Castle Hill, Australia). The carotid artery was also used to collect blood samples and to generate hemorrhage. The tail vein of rats was cannulated for IV fluid infusion. Respiratory rate and heart rate were measured non-invasively and recorded. The respiration rate was measured using PowerLab-connected pulse transducers (TN1012/ST, AD Instruments, Castle Hill, Australia). Heart rate was measured using PowerLab-connected biological amplifiers (Bio Amp FE231, AD Instruments, Castle Hill, Australia).

Saraçoğlu K.T., Saraçoğlu A., Yıldırım M., Demirtaş C., Akça M., Serdoğan F., Ergün İ.S., Tetik Ş, & Pençe S. (2023). Effects of Different Crystalloid Fluids on Renal Tissue in an Experimental Model of Hemorrhagic Shock. Turkish Journal of Anaesthesiology and Reanimation, 51(5), 380-387.

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High-Resolution rs-fMRI at 7T with Multimodal Recordings

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A group of 12 healthy subjects (6M/6F, 28±1 years old) was studied on a 7 T Siemens whole-body scanner equipped with a custom-built 32-channel radiofrequency loop coil head array for signal reception, and a detunable band-pass birdcage coil for radiofrequency transmission. A rs-fMRI dataset with a duration of approximately 5 minutes, was collected using a simultaneous-multi-slice (SMS) echo-planar-imaging (EPI) sequence, with echo time (TE) = 32 ms, repetition time (TR) = 2500 ms, flip angle = 75°, field of view=264 × 198 mm². A total of 123 sagittal slices, covering the whole brain with 1.1 mm isotropic resolution, were acquired in an interleaved order with a GRAPPA acceleration factor of 3 (Griswold et al., 2002 (link)), echo-spacing = 0.82 ms, and SMS factor = 3. A whole-brain T₁-weighted structural image was also collected using a multi-echo MPRAGE sequence with 1 mm isotropic resolution (van der Kouwe et al., 2008 (link)) . Cardiac and respiratory data were simultaneously recorded using a pulse transducer (TN1012/ST, ADInstruments) placed on the subject’s left index finger, and a pneumatic belt (UFI Model 1132 Pneumotrace II, UFI) strapped around the subjects’ upper abdomen, respectively. Both cardiac and respiratory recordings were acquired with a sampling rate of 1000 Hz, simultaneously with a tag signaling the fMRI volume triggers.

Pinto J., Nunes S., Bianciardi M., Dias A., Silveira L.M., Wald L.L, & Figueiredo P. (2017). Improved 7 Tesla resting-state fMRI connectivity measurements by cluster-based modeling of respiratory volume and heart rate effects. NeuroImage, 153, 262-272.

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Interoceptive Accuracy Measurement Protocol

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Interoceptive accuracy was measured prior to the experimental task using the “heartbeat counting paradigm”13 (link). Participants internally counted their heartbeats during four intervals (25s, 35s, 45s, and 100s) presented in random order. The start and end of the period was signalled by an auditory cue delivered by Eprime via the headphones. The real heart rate was recorded using a pulse transducer (Adinstruments; TN1012/ST), which was attached to the index finger using a Velcro fastener. All participants reported that they could not feel their pulse on the finger. These two measures were used to calculate an accuracy index as described in13 (link).

Azevedo R.T., Aglioti S.M, & Lenggenhager B. (2016). Participants’ above-chance recognition of own-heart sound combined with poor metacognitive awareness suggests implicit knowledge of own heart cardiodynamics. Scientific Reports, 6, 26545.

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Quantifying Corneal Axial Motion by OCT Imaging

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Corneal axial motion was quantified as the change in axial distance (Fig. 1a) by OCT imaging in the absence of any stimulation. Two healthy human volunteers with no history of ocular disease were involved in this study. The IOPs of their individual left eyes were 15 and 14 mm Hg, as measured by Icare ic200 eye tonometer (Icare Oy, Vanda, Finland). The corneal apex positions of their left eyes were tracked by OCT over a time course and were then decomposed in the frequency domain to ascertain the effects of respiration and heartbeat cycles. During corneal position tracking, subjects were allowed to blink, and eye motions were analyzed in the intervals between blinks. The blink interval was usually 3 to 20 seconds. Corneal positions were tracked at least 30 seconds and at most 2 minutes. The pulse rate was measured from a pressure transducer sensing (TN1012/ST, ADInstruments Inc., Colorado Springs, CO) at the subjects’ fingertip of left hands. Ocular position changes owing to inspiration and expiration were noted as a low-frequency sinusoidal pattern as shown in previous studies.⁵¹ (link) We recorded the onset of inspiration and expiration by having subjects press a button to annotate the eye motion record. Heartrate, respiration, and eye position were synchronized using a data acquisition system (PowerLab 8/35, ADInstruments Inc.).⁵² (link)

Lan G., Gu B., Larin K.V, & Twa M.D. (2020). Clinical Corneal Optical Coherence Elastography Measurement Precision: Effect of Heartbeat and Respiration. Translational Vision Science & Technology, 9(5), 3.

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Autonomic Nervous System and Obesity

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As autonomic nervous system (ANS) dysregulation and specifically heart rate variability (HRV) is implicated in the pathophysiology of obesity (26 ), we measured HRV using a pulse transducer (TN1012/ST ADInstruments; Colorado Springs, CO) that attached to the participant’s thumb and connected to a PowerLab 2/26 acquisition device (ML826 ADInstruments).
Baseline eye blink rate (EBR) positively correlates with central dopamine function (27 (link)), which has been shown to vary with BMI and is suggested to play a role in the association between BMI and cognitive function (28 ). Therefore, concurrently with the HRV measurement, a 5-minute video of the participant’s face was recorded using a webcam while they were instructed to let their mind wander but not fall asleep. The total number of blinks for each participant was averaged over the recording period to produce EBR in blinks/min.

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