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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.
    Bagge, Joakim
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Hedman, Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Smedsrud, Sabina
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Svärdström, Cornelia
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Söderberg, Elisabeth
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Valdez, Fernando
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
    Utveckling av metodik för påvisning och typning av Listeria i livsmedelskedjan2017Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
  • 3.
    Ladhani, Laila
    KTH, School of Electrical Engineering and Computer Science (EECS), Micro and Nanosystems.
    An electrostatic sampling device for point-of-care detection of bioaerosols2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Bioaerosols are not only a significant factor of air quality but contribute greatly to the spread of infectious diseases, specifically through expired pathogen-laden aerosols. Clear examples of airborne transmission include: the recent influenza pandemic of 2009, the ongoing tuberculosis epidemic, and yearly norovirus out- breaks, which affect millions of people worldwide and pose serious threats to public healthcare systems. Given these acute concerns and the critical lack of knowledge of the field, it is important to develop methods for sampling and detecting these air- borne pathogens. Specifically, detection at the point-of-care can play an important role in improving the outcome of patient care by providing rapid and convenient diagnostics.

    Electrostatic precipitation has emerged as a promising sampling tool for bio- aerosols, which together with a rapid analysis technique, can provide a powerful and integrated approach to pathogen detection or disease diagnosis at the point- of-care. Moreover, such a sampling-detection scheme could be a potentialy non- invasive breath sampling tool for diagnosis of respiratory infectious diseases.

    This thesis presents a sampling device based on electrostatic precipitation, for capture of bioaerosols, and designed for use at point-of-care settings. A multi-point- to-plane electrode configuration allows charging of aerosol particles and direct air- to-liquid capture within a miniaturized volume with potentential for concatenation with on-site detection methods. Performance of the device was evaluated, using non-biological aerosols, for geometric (inter-electrode distance), electrical (inter- electrode potential and corona current), and aerosol parameters (particle size and gas velocity). Moreover, four different collector designs were investigated for im- proved collection efficiency and other features suitable for point-of-care settings (e.g. easy sample extraction and minimized volume).

    The device was then validated, using bioaerosols, both in vitro and in vivo. In vitro validation was performed by capturing aerosolized influenza virus and analyz- ing the device collection efficiency. Lastly, prototype devices, designed for point- of-care, were validated in vivo with patients at the clinical setting. A pilot study was performed to capture exhaled pathogens from infected patients, with success- ful capture of exhaled bacteria.

  • 4.
    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.

  • 5.
    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.

  • 6.
    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
  • 7.
    Oresic, Matej
    Örebro University, School of Medical Sciences. Systems Biology and Bioinformatics, VTT Technical Research Centre of Finland, Espoo, Finland.
    Obesity and psychotic disorders: uncovering common mechanisms through metabolomics2012In: Disease Models and Mechanisms, ISSN 1754-8403, E-ISSN 1754-8411, Vol. 5, no 5, p. 614-620Article in journal (Refereed)
    Abstract [en]

    Primary obesity and psychotic disorders are similar with respect to the associated changes in energy balance and co-morbidities, including metabolic syndrome. Such similarities do not necessarily demonstrate causal links, but instead suggest that specific causes of and metabolic disturbances associated with obesity play a pathogenic role in the development of co-morbid disorders, potentially even before obesity develops. Metabolomics - the systematic study of metabolites, which are small molecules generated by the process of metabolism - has been important in elucidating the pathways underlying obesity-associated co-morbidities. This review covers how recent metabolomic studies have advanced biomarker discovery and the elucidation of mechanisms underlying obesity and its co-morbidities, with a specific focus on metabolic syndrome and psychotic disorders. The importance of identifying metabolic markers of disease-associated intermediate phenotypes - traits modulated but not encoded by the DNA sequence - is emphasized. Such markers would be applicable as diagnostic tools in a personalized healthcare setting and might also open up novel therapeutic avenues.

  • 8.
    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.

  • 9.
    Rivas, Lourdes
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Reuterswärd, Philippa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Rasti, Reza
    Herrmann, Björn
    Mårtensson, Andreas
    Alfvén, Tobias
    Gantelius, Jesper
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Andersson-Svahn, Helene
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    A vertical flow paper-microarray assay with isothermal DNA amplification for detection of Neisseria meningitidis2018In: Talanta: The International Journal of Pure and Applied Analytical Chemistry, ISSN 0039-9140, E-ISSN 1873-3573, Vol. 183, p. 192-200Article in journal (Refereed)
    Abstract [en]

    Paper-based biosensors offer a promising technology to be used at the point of care, enabled by good performance, convenience and low-cost. In this article, we describe a colorimetric vertical-flow DNA microarray (DNA-VFM) that takes advantage of the screening capability of DNA microarrays in a paper format together with isothermal amplification by means of Recombinase Polymerase Amplification (RPA). Different assay parameters such as hybridization buffer, flow rate, printing buffer and capture probe concentration were optimized. A limit of detection (LOD) of 4.4 nM was achieved as determined by tabletop scanning. The DNA-VFM was applied as a proof of concept for detection of Neisseria meningitidis, a primary cause of bacterial meningitis. The LOD was determined to be between 38 and 2.1Å~106 copies/VFM assay, depending on the choice of DNA capture probes. The presented approach provides multiplex capabilities of DNA microarrays in a paper-based format for future point-of-care applications.

  • 10.
    Söderberg, Lovisa
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fonseca, Pedro
    Karolinska Intitutet, Department of Oncology and Pathology.
    Panaretakis, Theocharis
    Karolinska Intitutet, Department of Oncology and Pathology.
    Jönsson, Håkan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Detection of single exosomes in microfluidic droplets by RT-PCR amplification of 18S RNA contentManuscript (preprint) (Other academic)
    Abstract [en]

    We present a workflow for reverse transcription-PCR (RT-PCR) in microfluidic droplets to identify exosomes based on their RNA content. Available techniques for exosome detection have been limited to size or surface markers which limit their diagnostic capabilities. Exosome detection based on RNA content could be developed to be used as a diagnostic, prognostic or predictive tool for cancer based on specific RNA biomarkers in liquid biopsies. In this manuscript we demonstrate a high throughput method for the amplification of exosome derived 18S RNA in microfluidic droplets. Automated image analysis using open source software was applied to distinguish and count PCR-positive droplets with fluorescent intensity over a set threshold. We benchmark our workflow against picoliter scale RT-PCR on serially diluted exosome samples and demonstrate the ability of the droplet based workflow to correctly rank exosome samples based on exosome concentration.  This represents a key step towards a quantitative analysis of exosomal RNA content and the sorting of single exosomes by their RNA content.

  • 11. 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 2211-9264, Vol. 19, p. 155-161Article 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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