BEVITAL AS

Logistics & Quality Control

Over 20 years of experience in handling thousands of samples on a monthly basis has materialized into optimized procedures for sample handling, software for data integration, and implementation of quality controls. Our procedures and logistics are set up to avoid human errors, minimize preanalytical variation and assay drift, and maintain adequate assay performance in terms of accuracy, precision and low sample consumption.

1. Quality control

Each set of 96 vials contains 6 vials with calibrators, 3 with control plasma samples with known biomarker concentrations and one vial without biomarker (blank, to control for carry over). The calibrators are diagonally located (from upper left to lover right corner) across the sample tray to verify positioning of the tray in the autosampler. Large stock solutions of plasma calibrator and control plasma are prepared in sufficient amount to last for years, to minimize chance of assay drift over time. These stocks are aliquoted and stored at -80 °C. New stock are calibrated by comparison with the previous validated stock solution by analysing about 1000 parallel samples over one month. BEVITAL participates in external quality control programs for total homocysteine, MMA, cystatin C (DEKS), vitamin D (DEQAS), 24 amino acids, 3-hydroxybutyrate, creatinine (ERNDIM), vitamin K (KEQAS), 5-methyltetrahydrofolate, cobalamin and hsCRP (LABQUALITY).

2. Validation across platforms

Some stable metabolites are measured at two or three platforms (methods), but against the same calibrators. These metabolites are total homocysteine (tHcy), total cysteine (tCys), cystathionine (Cysta), methionine (Met), tryptophan (Trp), kynurenine (Kyn), histidine (His), ornithine (Orn) and trimethylamine N-oxide (TMAO). For these analytes, the above-mentioned software calculates the ratios between concentrations obtained by different platforms. Analysis on each platform requires separate pipetting of sample and reagents and separate organization of vials into the sample tray. Therefore, analytical errors related to sample identification, handling, pipetting and organization as well as instrumental performance are likely to be discovered as metabolite ratio(s) different from 1. This ensures adequate sample handling and logistics but also minimizes the possibility of assay interference.

3. Data integration

Raw data from the separate platforms and analysis sets are integrated and fully handled by in-house designed QC software and database. Data files from separate platforms are merged and spread between parallel runs as well as summary statistics are calculated. Customers receive a detailed report of all measured concentrations including full insights into quality controls. 

4. Minimizing sample consumption and analyte degradation

Logistics have been established to minimize consumption of samples to be analyzed on more than one platform and to avoid pre-analytical degradation after sampling and during repeated freezing/thawing.

5. Long-term assay drift (LAD)

LAD refers to systematic rather than random changes in measured analyte concentrations that may take place over months or years. This may result in slight differences in central estimates and/or distribution when comparing values from repeated analyses carried out years apart. LAD most likely occurs when first measurements are carried out shortly after the method has been launched (new method), is detected in large sample series, and is occasionally observed for biobank samples in spite of no detectable changes in levels for longitudinal control samples. Possible explanations include column replacement, altered instrument performance, and method optimization. To avoid bias from LAD, BEVITAL measures sample series for each project within a short time period, when no deliberate changes or optimization in method design are undertaken. BEVITAL strongly discourages composing data sets where samples from comparison groups are analyzed at different time points. Possible bias from LAD may be reduced but not totally avoided by value correction based on overlapping (bridging) samples or control plasma.

6. Analysis of metabolites and biomarkers in extract from cells or tissues

The methods used by BEVITAL have been developed and validated for analyses of metabolites in plasma, serum and/or urine. Occasionally, customers request analysis in cell or tissue extracts. In such cases, the method has to be validated and optimized for the actual extract and extraction procedure, to secure adequate performance of the method.

February 16, 2026
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Per Christian Eriksen

Øivind

Per Magne Ueland has been Professor at the University of Bergen 1987-2018. He is one of the founders of Bevital AS and the scientific advisor in Bevital since 2023. His interests includes biomarkers related to nutrition, inflammation, ageing and life-style related chronic diseases. Per is committed to the development of precise, high-throughput mass spectrometry methods, tailored for metabolic profiling of biobank specimens from large cohorts.

Ove completed his education in Biomedical Science at the Western Norway University of Applied Sciences, supplemented by specialized training in Electrical Engineering and Electronics at the Royal Norwegian Naval Training Establishment and the National Institute of Technology. With many years of experience as a biomedical scientist in hospital laboratories—specializing primarily in microbiology—he brings a unique blend of clinical and technical expertise to his work. Ove focuses on the design and prototyping of electronics, as well as the service and maintenance of laboratory instrumentation, ensuring that technical equipment and workflows remain precise and reliable for research-focused activities.

Lena holds a master`s degree in biology from the University in Bergen. At Bevital she works with LC-MS/MS anlyses focusing on accurate and reliable testing of biological samples. She is dedicated to ensuring precise and high-quality results that contribute to reliable scientific outcomes and support ongoing research efforts.

Marit holds a degree in chemical engineering from Bergen Ingeniørhøyskole, which is now part of the Western Norway University of Applied Sciences. She works with quantitative analysis and method development on LC-MS/MS at the laboratory of Bevital AS.

Randi holds a Master of Science in Chemical Process Engineering from the Norwegian University of Science and Technology (NTNU). She has been part of Bevital since its very beginning, contributing her expertise primarily to the LC-MS/MS platforms, but also to the microbiological assays. In 2021, she stepped into the role of Manager/CEO, where she is dedicated to strengthening Bevital’s innovative profile and ensuring the company’s continued growth and success. She is especially motivated by advancing research that improves health insights and by fostering collaboration that drives scientific and technological progress.

Ove completed a bachelor’s degree in Biomedical Laboratory Sciences at the Western Norway University of Applied Sciences in Bergen. With extensive experience in method development and expertise in GC-MS/MS, he specializes in optimizing analytical techniques for research-focused studies. At Bevital, Ove is dedicated to advancing laboratory methods and workflows, contributing to innovative research through precise and reliable analytical solutions.

Lene holds a bachelor’s degree in Biomedical Laboratory Science from the Western Norway University of Applied Sciences, where she is also completing her master’s degree in Medical Laboratory Technology, expected to graduate in 2026. Her master’s thesis focuses on method validation in fatty acid analysis. At Bevital, she works with GC-MS/MS analyses, routinely performing SCFA measurements and emphasizing accurate and reliable testing of biological samples. With her strong laboratory background, Lene is committed to delivering high-quality results that support medical research.

Klaus earned his PhD in physics from the University of Münster in Germany. For more than thirty years he has specialized in Time‑of‑Flight mass spectrometry, contributing innovative approaches to SNP genotyping and protein quantification. Together with his colleague Lene Njåstad, he oversees Bevital’s Olink Proteomics service. He also leads Bevital’s website and media design efforts, ensuring a clear and informative public presence.

Adrian holds a PhD in diabetes research, along with bachelor’s and master’s degrees in biomedical science and public health, respectively. With over 20 years of experience in laboratory science, he leads high-precision metabolite analyses and method development at Bevital. His expertise centers on quantifying biomarkers, metabolite classes, and metabolic pathways related to nutrition, cardiovascular and neurodegenerative diseases, and cancer. Adrian is committed to advancing research quality and actively collaborates nationally and internationally, leveraging targeted metabolomics to support innovative, multidisciplinary research.

Statistical power is the probability that a statistical test will correctly reject a false null hypothesis (H0​) when a specific alternative hypothesis (H1​) is true. H0​ is the null hypothesis, which states there is no effect or no difference. H1​ is the alternative hypothesis, which states there is a real effect or difference. Alpha (α) is the probability of a Type I error (a false positive), which is the risk of incorrectly rejecting the H0​ when it is actually true. You set this value before the experiment, commonly at 0.05. Beta (β) is the probability of a Type II error (a false negative), which is the risk of failing to reject the H0​ when it is actually false.

Power is calculated as 1−β. Increasing power means you are decreasing the probability of making a Type II error.

Several factors can be adjusted to increase the power of a statistical test:

  • Effect Size: This is the magnitude of the difference you are trying to detect. A larger effect size is easier to detect, thus increasing power. 

  • Sample Size: The number of observations in a study. A larger sample size provides more information about the population, reducing the margin of error and increasing the power to detect a true effect.

  • Variation: Refers to the spread or standard deviation of the data within the population. Less variation makes it easier to distinguish a real effect from random noise, thereby increasing power.

  • Alpha (): Increasing the alpha level (e.g., from 0.05 to 0.10) also increases power, but at the cost of a higher risk of a Type I error. This trade-off is often undesirable.

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Walzik, David; Wenzel, Charlotte; Strotkötter, Jule Elisabeth; Hoenen, Leon; Chirino, Tiffany Y Wences; Trebing, Sina; McCann, Adrian; Ueland, Per Magne; Zimmer, Philipp; Joisten, Niklas

Systemic metabolite kinetics mirror skeletal muscle energy metabolism during acute aerobic exercise Journal Article

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Preoperative plasma short- and branched-chain fatty acids in relation to risk of complications after colorectal cancer surgery: a prospective cohort study Journal Article

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Linde, Anja; Gerdts, Eva; Fevang, Bjørg T; Ulvik, Arve; Ueland, Per M; Meyer, Klaus; Kringeland, Ester; Midtbø, Helga

Factors associated with left ventricular mass during disease modifying antirheumatic drug therapy in patients with rheumatoid arthritis: the Joint Heart study Journal Article

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Wenzel, Charlotte; Walzik, David; Wences, Tiffany; Trebing, Sina; Meyer, Klaus; Groll, Andreas; Zimmer, Philipp; Joisten, Niklas

Immunological Protein Signature During Acute Exercise Journal Article

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Kvestad, Ingrid; Ulak, Manjeswori; McCann, Adrian; Chandyo, Ram K; Hysing, Mari; Schwinger, Catherine; Ranjitkar, Suman; Ueland, Per Magne; Basnet, Sudha; Strand, Tor A

The effect of vitamin B12 supplementation during pregnancy on early motor performance. Secondary analyses from a double-blinded randomized controlled trial Journal Article

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Kupjetz, Marie; Langeskov-Christensen, Martin; Riemenschneider, Morten; Inerle, Stefan; Ligges, Uwe; Gaemelke, Tobias; Patt, Nadine; Bansi, Jens; Gonzenbach, Roman Rudolf; Reuter, Marcel; Rosenberger, Friederike; Meyer, Tim; McCann, Adrian; Ueland, Per Magne; Eskildsen, Simon Fristed; Nygaard, Mikkel Karl Emil; Joisten, Niklas; Hvid, Lars; Dalgas, Ulrik; Zimmer, Philipp

Persons With Multiple Sclerosis Reveal Distinct Kynurenine Pathway Metabolite Patterns: A Multinational Cross-Sectional Study Journal Article

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Sandvig, Heidi Vihovde; Saltvedt, Ingvild; Edwin, Trine Holt; Aam, Stina; Alme, Katinka Nordheim; Eldholm, Rannveig Sakshaug; Lydersen, Stian; Mollnes, Tom Eirik; Munthe-Kaas, Ragnhild; Ueland, Per Magne; Ulvik, Arve; Wethal, Torgeir; Knapskog, Anne-Brita

Associations between systemic inflammation and cognitive trajectories post-stroke Journal Article

In: Sci Rep, vol. 15, no. 1, pp. 42791, 2025, ISSN: 2045-2322.

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Knudsen, Andreas Dehlbæk; Gelpi, Marco; Suarez-Zdunek, Moises A; Loft, Josefine A; Ueland, Per Magne; Ostrowski, Sisse Rye; Midttun, Øivind; Martinez, Esteban; Nielsen, Susanne D

Inhibition of Th1-type immune responses in persons with HIV with current statin exposure Journal Article

In: AIDS, 2025, ISSN: 1473-5571.

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Bråtveit, Marianne; Strømland, Pouda P; Laupsa-Borge, Johnny; Skumsnes, Lillian; Dagsland, Vigdis H; Kvistad, Silje; Vogt, Elinor C; McCann, Adrian; Thorsen, Håvard L; Diamantopoulos, Andreas P; Nedrebø, Bjørn Gunnar; Mellgren, Gunnar; Dankel, Simon N

A Very-Low Energy Fast Involves Increased Adipose Inflammatory Gene Expression: A 6-Day Feeding Trial (FASTOMICS-6) Journal Article

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Dhar, Indu; Svingen, Gard Ft; Ulvik, Arve; Bjørnestad, Espen Ø; Sagen, Jørn V; Nygård, Ottar K

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Jørgensen, Silje F; Braadland, Peder R; Ueland, Thor; Fraz, Mai S A; Michelsen, Annika E; Holm, Kristian; Osnes, Liv T; Trøseid, Marius; Ueland, Per Magne; Fevang, Børre; Aukrust, Pål; Hov, Johannes R

Tryptophan-kynurenine metabolites associate with inflammation and immunologic phenotypes in common variable immunodeficiency Journal Article

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Vilar, Ana; Bayes-Marin, Ivet; Álvarez-Salazar, Samantha; Piqueras-Marques, Jorge; Vila, Santiago Batlle; Forero, Carlos G

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Bjørkevoll, Sol Maja G; O'Keeffe, Maria; Konijnenberg, Carolien; Solvik, Beate S; Sødal, Alida F; Kaldenbach, Siri; McCann, Adrian; Ueland, Per M; Kvestad, Ingrid; Ersvær, Elisabeth; Holten-Andersen, Mads N; Bakken, Kjersti S; Strand, Tor A

Infant vitamin B12 status and its predictors - cross-sectional baseline results from an ongoing randomized controlled trial Journal Article

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Holthuijsen, Daniëlle D B; van Roekel, Eline H; Bours, Martijn J L; Ueland, Per M; Breukink, Stéphanie O; Janssen-Heijnen, Maryska L G; Konsten, Joop L; Keulen, Eric T P; McCann, Adrian; Brezina, Stefanie; Gigic, Biljana; Kok, Dieuwertje E; Ulrich, Cornelia M; Weijenberg, Matty P; Eussen, Simone J P M

Modeling how iso-caloric macronutrient substitutions are longitudinally associated with plasma kynurenines in colorectal cancer survivors up to 12 months post-treatment Journal Article

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Valim, Valéria; Oliveira, Fabíola R; Miyamoto, Samira T; Serrano, Érica V; Balarini, Gabriela M; Tanure, Leandro A; Ferreira, Gilda A; Zandonade, Eliana; Brun, Johan G; Jonsson, Malin; Maeland, Elisabeth; Ulvik, Arve; Ueland, Per Magne; Jonsson, Roland; Mydel, Piotr M

Kynurenines and neopterin are interferon-gamma-inducible biomarkers for Sjögren's disease Journal Article

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Bakker, Lieke; Ramakers, Inez H G B; van Greevenbroek, Marleen M J; Backes, Walter H; Jansen, Jacobus F A; Schram, Miranda T; van der Kallen, Carla J H; Schalkwijk, Casper G; Wesselius, Anke; Ulvik, Arve; Ueland, Per M; Verhey, Frans R J; Eussen, Simone J P M; Köhler, Sebastian

The kynurenine pathway and markers of neurodegeneration and cerebral small vessel disease: The Maastricht Study Journal Article

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Gordon, Shane; Hoey, Leane; McNulty, Helene; Keenan, Jordan; Pangilinan, Faith; Brody, Lawrence C; Ward, Mary; Strain, J J; McAnena, Liadhan; McCann, Adrian; Molloy, Anne M; Cunningham, Conal; McCarroll, Kevin; Hughes, Catherine F

Associations of one-carbon metabolism, related B-vitamins and ApoE genotype with cognitive function in older adults: identification of a novel gene-nutrient interaction Journal Article

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Belen, Sergen; Patt, Nadine; Kupjetz, Marie; Ueland, Per M; McCann, Adrian; Gonzenbach, Roman; Bansi, Jens; Zimmer, Philipp

Vitamin B status is related to disease severity and modulated by endurance exercise in individuals with multiple sclerosis: a secondary analysis of a randomized controlled trial Journal Article

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Dahl, Tuva B; Aftab, Friha; Prebensen, Christian; Berdal, Jan-Erik; Ueland, Thor; Barratt-Due, Andreas; Riise, Anne Ma Dyrhol; Ueland, Per Magne; Hov, Johannes R; Trøseid, Marius; Aukrust, Pål; Gregersen, Ida; Myhre, Peder L; Omland, Torbjørn; Halvorsen, Bente

Imidazole propionate is increased in severe COVID-19 and correlates with cardiac involvement Miscellaneous

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Park, Jin Young; Puyvelde, Heleen Van; Regazzetti, Lea; Clasen, Joanna L; Heath, Alicia K; Eussen, Simone; Ueland, Per Magne; Johansson, Mattias; Biessy, Carine; Zamora-Ros, Raul; Huerta, José María; Sánchez, Maria-Jose; Ocke, Marga; Schulze, Matthias B; Schiborn, Catarina; Braaten, Tonje Bjørndal; Skeie, Guri; Sacerdote, Carlotta; Castilla, Jesús; Karlsson, Therese; Johansson, Ingegerd; Kyrø, Cecilie; Tjønneland, Anne; Tong, Tammy Y N; Katzke, Verena; Bajracharya, Rashmita; Lasheras, Cristina; Midttun, Øivind; Vollset, Stein Emil; Vineis, Paolo; Masala, Giovanna; Amiano, Pilar; Tumino, Rosario; Baldassari, Ivan; Weiderpass, Elisabete; Riboli, Elio; Gunter, Marc J; Freisling, Heinz; Rinaldi, Sabina; Muller, David C; Huybrechts, Inge; Ferrari, Pietro

Association Between Dietary Intake and Blood Concentrations of One-Carbon-Metabolism-Related Nutrients in European Prospective Investigation into Cancer and Nutrition Journal Article

In: Nutrients, vol. 17, no. 12, 2025, ISSN: 2072-6643.

Abstract | Links | BibTeX

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