| 1. |
- Beal, Jacob, et al.
(author)
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Robust estimation of bacterial cell count from optical density
- 2020
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Journal article (peer-reviewed)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
- Aad, G, et al.
(author)
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- 2015
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swepub:Mat__t
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| 3. |
- Wan, Lu Ming, et al.
(author)
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Heparanase Facilitates PMA-Induced Megakaryocytic Differentiation in K562 Cells via Interleukin 6/STAT3 Pathway
- 2020
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In: Thrombosis and Haemostasis. - : GEORG THIEME VERLAG KG. - 0340-6245 .- 2567-689X. ; 120:4, s. 647-657
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Journal article (peer-reviewed)abstract
- Heparanase (HPSE) is an endo-beta-D-glucuronidase that cleaves heparan sulfate and hence participates in remodeling of the extracellular matrix, leading to release of cytokines that are immobilized by binding to heparan sulfate proteoglycans (HSPGs), and consequently activating signaling pathways. This function of HPSE is correlated to its expression level that is normally very low in majority of the tissues. Exceptionally, human platelets express high level of HPSE, suggesting a unique physiological role in this cell. Using K562 cell line, we found a progressive increase of HPSE during the megakaryocytic differentiation. Analysis of a series of megakaryocytic differentiation-related heparin-binding proteins (HBPs) in the cell culture medium revealed an exclusive positive correlation between the level of interleukin 6 (IL-6) and HPSE expression. IL-6 modulated megakaryocytic differentiation through activation of STAT3. Further, we demonstrated that overexpression of HPSE potentiates megakaryocytic differentiation, whereas elimination of HPSE led to a delayed differentiation. This function of HPSE is associated with its activity, as overexpression of inactive HPSE had no effect on IL-6 production and megakaryocytic differentiation. The role of HPSE is further supported by the observation in an umbilical cord blood CD34+ cells megakaryocytic differentiation model. Our data propose a novel role for HPSE in platelets production by a HPSE/IL-6/STAT3 positive feedback loop that specifically regulates megakaryocytes maturation.
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| 4. |
- Abe, K., et al.
(author)
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Neutron tagging following atmospheric neutrino events in a water Cherenkov detector
- 2022
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In: Journal of Instrumentation. - : Institute of Physics (IOP). - 1748-0221. ; 17:10
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Journal article (peer-reviewed)abstract
- We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 +/- 9 mu s.
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| 5. |
- Kostka, Kristin, et al.
(author)
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Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS.
- 2022
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In: Clinical epidemiology. - 1179-1349. ; 14, s. 369-384
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Journal article (peer-reviewed)abstract
- Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.
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