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  • 1.
    Anlind, Nils
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Eriksson, Alexandra
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Gromova, Arina
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Hong, Marcus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Ljungström, Sara
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Markstedt, Olof
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Marknadsanalys av proteinstandarder för kvantitativ masspektrometri2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    QPrEST är en ny intern standard för absolut kvantifiering av proteiner utvecklat av företaget Atlas Antibodies AB. I en marknad där det redan finns etablerade standarder kan det vara svårt att konkurrera ut de nuvarande produkterna. Därför har denna rapport gjorts vilken består av en marknadsanalys av nuvarande standarder, statistisk undersökning av publicerade artiklar inom absolut kvantitativ proteomik samt en global kundundersökning med 35 svarande. Resultaten har legat till grund för förbättringsförslag till Atlas Antibodies AB för bättre marknadsföring och lansering av sin nya produkt, QPrEST. Slutsatsen från denna rapport är att Atlas Antibodies AB måste nischa in sin produkt till kvantifiering av ett målprotein då det är där standarden presterar bäst.

  • 2.
    Ladhani, Laila
    et al.
    KTH, School of Electrical Engineering (EES), Micro and Nanosystems.
    Pardon, Gaspard
    KTH, School of Electrical Engineering (EES), Micro and Nanosystems.
    Meeuws, Hanne
    Janssen Diagnostics.
    van Wesenbeeck, Liesbeth
    Janssen Diagnostics.
    Schmidt, Kristiane
    Janssen Diagnostics.
    Stuyver, Lieven
    Janssen Diagnostics .
    van der Wijngaart, Wouter
    KTH, School of Electrical Engineering (EES), Micro and Nanosystems.
    Sampling and detection of airborne influenza virus towards point-of-care applications2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, PlosONEArticle in journal (Refereed)
    Abstract [en]

    Airborne transmission of the influenza virus contributes significantly to the spread of this infectious pathogen, particularly over large distances when carried by aerosol droplets with long survival times. Efficient sampling of virus-loaded aerosol in combination with a low limit of detection of the collected virus could enable rapid and early detection of airborne influenza virus at the point-of-care setting. Here, we demonstrate a successful sampling and detection of airborne influenza virus using a system specifically developed for such applications. Our system consists of a custom-made electrostatic precipitation (ESP)-based bioaerosol sampler that is coupled with downstream quantitative polymerase chain reaction (qPCR) analysis. Aerosolized viruses are sampled directly into a miniaturized collector with liquid volume of 150 μL, which constitutes a simple and direct interface with subsequent biological assays. This approach reduces sample dilution by at least one order of magnitude when compared to other liquid-based aerosol bio-samplers. Performance of our ESP-based sampler was evaluated using influenza virus-loaded sub-micron aerosols generated from both cultured and clinical samples. Despite the miniaturized collection volume, we demonstrate a collection efficiency of at least 10% and sensitive detection of a minimum of 3721 RNA copies. Furthermore, we show that an improved extraction protocol can allow viral recovery of down to 303 RNA copies and a maximum sampler collection efficiency of 47%. A device with such a performance would reduce sampling times dramatically, from a few hours with current sampling methods down to a couple of minutes with our ESP-based bioaerosol sampler.

  • 3.
    Lundstedt, Erik Torbjörn
    et al.
    AcureOmics AB.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Gabrielsson, Jon Robert
    AcureOmics AB.
    Ekström, Gunilla
    Anamar AB.
    METABOLIC PROFILES2012Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    Abstract: The invention relates to the use of endogenous metabolites to produce a metabolic profile of a disorder or disease in a subject, e.g. an autoimmune disease, in particular rheumatoid arthritis, and the analysis of such metabolic profiles in order to find disturbances in such profiles in a subject which are caused by or correlated with the said diseases or disorders. Such disturbances can be normalised by treatment of the subject with specified compounds, particularly N-(2-chloro-3,4-dimethoxybenzylideneamino)guanidine or an aminoguanidine.

  • 4.
    Nordesjö, Olle
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Pontén, Victor
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Herman, Stephanie
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Ås, Joel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Jamal, Sabri
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Nyberg, Alona
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Ett sannolikhetsbaserat kvalitetsmått förbättrar klassificeringen av oförväntade sekvenser i in situ sekvensering2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In situ sequencing is a method that can be used to localize differential expression of mRNA directly in tissue sections, something that can give valuable insights to many statest of disease. Today, many of the registered sequences from in situ sequencing are lost due to a conservative quality measure used to filter out incorrect sequencing reads. There is room for improvement in the performance of the current method for base calling since the technology is in an early stage of development. We have performed exploratory data analysis to investigate occurrence of systematic errors, and corrected for these by using various statistical methods. The primary methods that have been investigated are the following:

    I) Correction of emission spectra overlap resulting in spillover between channels.

    II) A probability-based interpretation of intensity data, resulting in a novel quality measure and an alternative classifier based on supervised learning.

    III) Analysis of occurrence of cycle dependent effects, e.g. incomplete dehybridization of fluorescent probes.

    We suggest the following:

    • Implementation and evaluation of the probability-based quality measure
    • Development and implementation of the proposed classifier
    • Additional experiments to investigate the possible occurrence of incomplete dehybridization
  • 5.
    Periyannan Rajeswari, Prem Kumar
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Soderberg, Lovisa M
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Andersson Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Jönsson, Håkan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Color-coded bead based readout from droplet PCR for the detection of pathogen biomarkersManuscript (preprint) (Other academic)
    Abstract [en]

    We present a workflow using fluorescent color-coded Luminex beads to detect the

    outcome of droplet PCR assay. The assay was performed to detect three important

    poultry pathogens: avian influenza, infectious laryngotracheitis virus and

    campylobacter. Droplet-based TaqMan PCR has been commonly used for detection

    of rare and significant biomarkers in clinical samples. However, the spectral overlap

    of fluorescent TaqMan probes limits the detection to 5 different targets in a single

    assay. The color codes of the Luminex detection beads allowed accurate classification

    of the different bead sets used in this assay concurrently. The target-specific capture

    probes coupled to distinct bead sets enabled capture and detection of target DNA in

    the droplet. The capture assay detected target DNA of all three poultry pathogens with

    high specificity, from samples with average target concentration of 1 template per

    droplet. This workflow demonstrates that the detection panel of droplet PCR assay

    can be increased to potentially detect multiple targets in a sample by utilizing the

    scalability offered by the color-coded detection beads.

  • 6. Zambrano, Jesús
    et al.
    Krustok, Ivo
    Nehrenheim, Emma
    Carlsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    A simple model for algae-bacteria interaction in photo-bioreactors2016In: Algal Research, ISSN 0340-7969, E-ISSN 2050-1560, Vol. 19, 155-161 p.Article in journal (Refereed)
    Abstract [en]

    This work presents a simple model to describe the consortia of algae-bacteria in a photo-bioreactor. The model is inspired by the Activated Sludge Model (ASM) structure, which includes different process rates and stoichiometric parameters. The model comprises two main biomass populations (algae and bacteria), two dissolved substrates (ammonium and nitrate) and two dissolved gases (oxygen and carbon dioxide) in the reactor. The model was calibrated with data from batch experiments performed in two lab-scale photo-bioreactors. A sensitivity analysis was done to identify the parameters to be considered for the model calibration. Results indicate that the maximum algae and bacteria growth rate, bacteria growth yield and half-saturation constant for carbon were the most sensitive parameters. Moreover, the comparison between the experiments and the model shows good agreement in terms of predicting the ammonium, nitrate and oxygen concentrations in the photobioreactor.

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