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- 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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- Aad, G, et al.
(author)
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- 2015
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swepub:Mat__t
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| 7. |
- Ayoub, Ali, et al.
(author)
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Effect of plasticizers and polymer blends for processing softwood kraft lignin as carbon fiber precursors
- 2021
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In: Cellulose. - : Springer Science and Business Media LLC. - 0969-0239 .- 1572-882X. ; 28:2, s. 1039-1053
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Journal article (peer-reviewed)abstract
- Plasticizers depress the glass transition temperature (T-g) of polymers and produce a flowable material at lower temperatures. The use of plasticizers to depress T-g of lignin is important, since at high processing temperatures lignin crosslinks, making it intractable. The goal of this study was to assess plasticizers and polymer blends for the ability to retard a commercial softwood kraft lignin from crosslinking and also serve as thermal and rheological property modifiers during thermal processing in the attempt to produced moldable and spinnable lignin for lignin and carbon fiber products. The T-g of the lignin and the lignin mixed with various amounts of plasticizers and with different thermo-mechanical mixing were determined using differential scanning calorimetry. The T-g and the change in heat capacity at the glass transition (Delta C-p) decreased and increased, respectively, about linearly within this plasticizers range with increased plasticizer weight percentage. Gel permeation chromatography results for extruded lignin as well as extruded lignin-plasticizer blends with glycerol, N-allyurea, citric acid with and without sodium hypophosphite, and oleic acid indicate that the presence of these materials reduced the rate of molecular weight increase at temperatures between 100 and 200 degrees C. Continuous, homogenous films and fibers could be produced by thermal processing with plasticized lignin samples and plasticized lignin-polymer blends, but not with lignin alone. These fibers could be carbonized, yielding up to about 50% of carbon. The present findings have shown the advantages of plasticizers in thermally processing a commercial softwood kraft lignin.
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- Brownstein, Catherine A., et al.
(author)
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An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge
- 2014
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In: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 15:3, s. R53-
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Journal article (peer-reviewed)abstract
- Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
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- Cheng, Jianlin, et al.
(author)
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Estimation of model accuracy in CASP13
- 2019
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In: Proteins. - : Wiley. - 0887-3585 .- 1097-0134. ; 87:12, s. 1361-1377
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Journal article (peer-reviewed)abstract
- Methods to reliably estimate the accuracy of 3D models of proteins are both a fundamental part of most protein folding pipelines and important for reliable identification of the best models when multiple pipelines are used. Here, we describe the progress made from CASP12 to CASP13 in the field of estimation of model accuracy (EMA) as seen from the progress of the most successful methods in CASP13. We show small but clear progress, that is, several methods perform better than the best methods from CASP12 when tested on CASP13 EMA targets. Some progress is driven by applying deep learning and residue‐residue contacts to model accuracy prediction. We show that the best EMA methods select better models than the best servers in CASP13, but that there exists a great potential to improve this further. Also, according to the evaluation criteria based on local similarities, such as lDDT and CAD, it is now clear that single model accuracy methods perform relatively better than consensus‐based methods.
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- Hou, Muzhou, et al.
(author)
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Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
- 2018
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In: Energies. - : MDPI. - 1996-1073. ; 11:12
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Journal article (peer-reviewed)abstract
- Accurate global solar radiation prediction is highly essential for related research on renewable energy sources. The cost implication and measurement expertise of global solar radiationemphasize that intelligence prediction models need to be applied. On the basis of long-term measured daily solar radiation data, this study uses a novel regularized online sequential extreme learning machine, integrated with variable forgetting factor (FOS-ELM), to predict global solar radiation at Bur Dedougou, in the Burkina Faso region. Bayesian Information Criterion (BIC) is applied to build the seven input combinations based on speed (Wspeed), maximum and minimum temperature (Tmax and Tmin), maximum and minimum humidity (Hmax and Hmin), evaporation (Eo) and vapor pressure deficiency (VPD). For the difference input parameters magnitudes, seven models were developed and evaluated for the optimal input combination. Various statistical indicators were computed for the prediction accuracy examination. The experimental results of the applied FOS-ELM model demonstrated a reliable prediction accuracy against the classical extreme learning machine (ELM) model for daily global solar radiation simulation. In fact, compared to classical ELM, the FOS-ELM model reported an enhancement in the root mean square error (RMSE) and mean absolute error(MAE) by (68.8–79.8%). In summary, the results clearly confirm the effectiveness of the FOS-ELM model, owing to the fixed internal tuning parameters.
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