Hd 1 analyser

Manufactured by Quanterix

Sourced in United States

The HD-1 Analyser is a laboratory instrument designed for the detection and quantification of various analytes in biological samples. It utilizes advanced detection technologies to provide precise and reliable measurements. The core function of the HD-1 Analyser is to perform sensitive and accurate analyses, enabling researchers and clinicians to gain insights into their samples.

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Lab products found in correlation

Simoa nf light advantage assay, by Quanterix (1 mentions)

Close spelling variants of this product

Simoa HD-1 Analyser

4 protocols using hd 1 analyser

Long-term Serum Biomarker Analysis

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Non-fasting blood samples were collected from each consenting participant immediately after the interview. Samples were processed directly in the study centre within 2 h. After centrifugation, serum and plasma aliquots were prepared for long-term storage at − 80 °C. While the plasma aliquots had been depleted by other analyses in the previous decades, the serum aliquots had remained frozen for 22 years. Only serum aliquots were used in this analysis.
Serum NfL and tau were quantified with commercially available kits on the single molecule array HD-1 analyser (Quanterix, Lexington, MA, USA), as previously described [24 (link), 25 (link)]. Samples were run in duplicate by board-certified technicians blinded to clinical information. The coefficients of variation for all samples reported were < 20%.

Rübsamen N., Maceski A., Leppert D., Benkert P., Kuhle J., Wiendl H., Peters A., Karch A, & Berger K. (2021). Serum neurofilament light and tau as prognostic markers for all-cause mortality in the elderly general population—an analysis from the MEMO study. BMC Medicine, 19, 38.

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MRI-based Evaluation of Neuroradiological Findings

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The same neuroradiologist evaluated all MRI images. The MRI images were acquired with a 3-Tesla MRI scanner. The MRI scanning protocols include T2-weighted turbo spin-echo images, T1-weighted 3-dimensional (3-D) turbo field echo images, T2-weighted 3-D Flair sequence image, Diffusion-weighted imaging, Susceptibility weighted imaging sequence and T1-weighted 3-D sequence image after intravenous contrast. The MRI was graded by the number of affected anatomical sites visualised by post-contrast enhanced lesions. Supratentorial meningeal enhancement, infratentorial meningeal enhancement, parenchymal enhancement, and enhancing lesions in the cervical spine, thoracic spine, lumbar spine, or cauda equina all give one point each [8 (link)]. A score of 0 points was graded no enhancement, 1–2 points were graded mild enhancement, and a score of 3–6 points was graded moderate/severe enhancement.
NFL in the CSF and plasma were analysed using a commercially available NF Kit (Quanterix©, Billerica, MA, USA) for the Single Molecule Array (Simoa^®) HD-1 Analyser) according to the manufacturer’s procedure. In-house CSF and plasma pools were used as internal controls and included in each assay for evaluating assay performance. The total coefficient of variation was <12%.

Byg K.E., Nielsen H.H., Sejbaek T., Madsen J.S., Olsen D.A., Nguyen N., Kindt A., Grauslund J., Illes Z, & Ellingsen T. (2021). Elevated Neurofilament Light Chain in Cerebrospinal Fluid and Plasma Reflect Inflammatory MRI Activity in Neurosarcoidosis. Brain Sciences, 11(2), 238.

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Plasma Amyloid-β Measurement Protocol

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One 0.5 ml aliquot of plasma from each individual was thawed to room temperature over 1 h and vortexed for 2 s. Next, 0.3 ml was pipetted into a 1.5 ml polypropylene tube for centrifugation at 13 000g for 10 min; 0.1 ml of the supernatant was pipetted onto each of two plates, for analysing amyloid-β₄₀ and amyloid-β₄₂, respectively. Samples were analysed in duplicate, using the same batch of reagents (Simoa Aβ40 and Aβ42 kits), on the same HD-1 Analyser (Quanterix) at UCL. Results were accepted if the intra-assay coefficient of variation (CV) across the duplicates was <15%. Run validation controls prepared using stock peptide solutions from the kits indicated inter-assay CV < 30%.

Keshavan A., Pannee J., Karikari T.K., Rodriguez J.L., Ashton N.J., Nicholas J.M., Cash D.M., Coath W., Lane C.A., Parker T.D., Lu K., Buchanan S.M., Keuss S.E., James S.N., Murray-Smith H., Wong A., Barnes A., Dickson J.C., Heslegrave A., Portelius E., Richards M., Fox N.C., Zetterberg H., Blennow K, & Schott J.M. (2021). Population-based blood screening for preclinical Alzheimer’s disease in a British birth cohort at age 70. Brain, 144(2), 434-449.

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Neurofilament Light as Biomarker in RRMS

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Blood samples were not systematically collected as part of the original study protocol, but 133 of the 166 participants with longitudinal follow‐up had at least one plasma or serum samples available for analysis. A mean of 1.5 samples (range 1–3) were available for each participant in the study, with sample availability well balanced between those defined as having a good or poor outcome (Table 1). Most samples analyzed were plasma. As serum and plasma NfL are strongly correlated in RRMS (r = 0.89–0.96), and the proportion of plasma and serum samples were well balanced between the two outcome groups (Table 1), we included all plasma and serum samples in the analysis without adjustment (Hendricks et al., 2019 (link), Sejbaek et al., 2019 (link)).
Samples were collected at the time of clinical assessments and stored at −80°C until the time of analysis. All samples were analyzed in duplicate using the Quanterix Simoa NF‐light advantage assay on a HD‐1 Analyser (Quanterix, Billerica, MA, USA). Recent reports have highlighted the benefits of analyzing NfL as age‐ and body mass index (BMI)‐adjusted Z‐scores (Benkert et al., 2022 (link)). Since access to the required control and BMI data were not available for this historical cohort, we analyzed NfL without adjustment, but included age as a covariate in all multivariable analyses.

Williams T., Heslegrave A., Zetterberg H., Miszkiel K.A., Barkhof F., Ciccarelli O., Brownlee W.J, & Chataway J. (2022). The prognostic significance of early blood neurofilament light chain concentration and magnetic resonance imaging variables in relapse‐onset multiple sclerosis. Brain and Behavior, 12(9), e2700.

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