| 1. |
- Hedman, Johannes, et al.
(author)
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A ranking index for quality assessment of forensic DNA profiles
- 2010
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In: BMC Research Notes. - : BioMed Central Ltd. - 1756-0500. ; 3:290
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Journal article (peer-reviewed)abstract
- BackgroundAssessment of DNA profile quality is vital in forensic DNA analysis, both in order to determine the evidentiary value of DNA results and to compare the performance of different DNA analysis protocols. Generally the quality assessment is performed through manual examination of the DNA profiles based on empirical knowledge, or by comparing the intensities (allelic peak heights) of the capillary electrophoresis electropherograms.ResultsWe recently developed a ranking index for unbiased and quantitative quality assessment of forensic DNA profiles, the forensic DNA profile index (FI) (Hedman et al. Improved forensic DNA analysis through the use of alternative DNA polymerases and statistical modeling of DNA profiles, Biotechniques 47 (2009) 951-958). FI uses electropherogram data to combine the intensities of the allelic peaks with the balances within and between loci, using Principal Components Analysis. Here we present the construction of FI. We explain the mathematical and statistical methodologies used and present details about the applied data reduction method. Thereby we show how to adapt the ranking index for any Short Tandem Repeat-based forensic DNA typing system through validation against a manual grading scale and calibration against a specific set of DNA profiles.ConclusionsThe developed tool provides unbiased quality assessment of forensic DNA profiles. It can be applied for any DNA profiling system based on Short Tandem Repeat markers. Apart from crime related DNA analysis, FI can therefore be used as a quality tool in paternal or familial testing as well as in disaster victim identification.
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| 2. |
- Freyhult, Eva, et al.
(author)
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Fisher: a program for the detection of H/ACA snoRNAs using MFE secondary structure prediction and comparative genomics - assessment and update
- 2008
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In: BMC Research Notes. - : Springer Science and Business Media LLC. - 1756-0500. ; 1:49, s. 1-8
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Journal article (peer-reviewed)abstract
- BackgroundThe H/ACA family of small nucleolar RNAs (snoRNAs) plays a central role in guiding the pseudouridylation of ribosomal RNA (rRNA). In an effort to systematically identify the complete set of rRNA-modifying H/ACA snoRNAs from the genome sequence of the budding yeast, Saccharomyces cerevisiae, we developed a program - Fisher - and previously presented several candidate snoRNAs based on our analysis [1]. FindingsIn this report, we provide a brief update of this work, which was aborted after the publication of experimentally-identified snoRNAs [2] identical to candidates we had identified bioinformatically using Fisher. Our motivation for revisiting this work is to report on the status of the candidate snoRNAs described in [1], and secondly, to report that a modified version of Fisher together with the available multiple yeast genome sequences was able to correctly identify several H/ACA snoRNAs for modification sites not identified by the snoGPS program [3]. While we are no longer developing Fisher, we briefly consider the merits of the Fisher algorithm relative to snoGPS, which may be of use for workers considering pursuing a similar search strategy for the identification of small RNAs. The modified source code for Fisher is made available as supplementary material. ConclusionOur results confirm the validity of using minimum free energy (MFE) secondary structure prediction to guide comparative genomic screening for RNA families with few sequence constraints.
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| 3. |
- Bölenius, Karin, et al.
(author)
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A content validated questionnaire for assessment of self reported venous blood sampling practices
- 2012
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In: BMC Research Notes. - : Springer Science and Business Media LLC. - 1756-0500. ; 5, s. 39-
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Journal article (peer-reviewed)abstract
- BACKGROUND: Venous blood sampling is a common procedure in health care. It is strictly regulated by national and international guidelines. Deviations from guidelines due to human mistakes can cause patient harm. Validated questionnaires for health care personnel can be used to assess preventable "near misses"--i.e. potential errors and nonconformities during venous blood sampling practices that could transform into adverse events. However, no validated questionnaire that assesses nonconformities in venous blood sampling has previously been presented. The aim was to test a recently developed questionnaire in self reported venous blood sampling practices for validity and reliability.FINDINGS: We developed a questionnaire to assess deviations from best practices during venous blood sampling. The questionnaire contained questions about patient identification, test request management, test tube labeling, test tube handling, information search procedures and frequencies of error reporting. For content validity, the questionnaire was confirmed by experts on questionnaires and venous blood sampling. For reliability, test-retest statistics were used on the questionnaire answered twice. The final venous blood sampling questionnaire included 19 questions out of which 9 had in total 34 underlying items. It was found to have content validity. The test-retest analysis demonstrated that the items were generally stable. In total, 82% of the items fulfilled the reliability acceptance criteria.CONCLUSIONS: The questionnaire could be used for assessment of "near miss" practices that could jeopardize patient safety and gives several benefits instead of assessing rare adverse events only. The higher frequencies of "near miss" practices allows for quantitative analysis of the effect of corrective interventions and to benchmark preanalytical quality not only at the laboratory/hospital level but also at the health care unit/hospital ward.
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| 4. |
- Prahm, Cosima, et al.
(author)
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Combining two open source tools for neural computation (BioPatRec and Netlab) improves movement classification for prosthetic control
- 2016
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In: BMC Research Notes. - : Springer Science and Business Media LLC. - 1756-0500. ; 9:1
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Journal article (peer-reviewed)abstract
- Background: Controlling a myoelectric prosthesis for upper limbs is increasingly challenging for the user as more electrodes and joints become available. Motion classification based on pattern recognition with a multi-electrode array allows multiple joints to be controlled simultaneously. Previous pattern recognition studies are difficult to compare, because individual research groups use their own data sets. To resolve this shortcoming and to facilitate comparisons, open access data sets were analysed using components of BioPatRec and Netlab pattern recognition models. Methods: Performances of the artificial neural networks, linear models, and training program components were compared. Evaluation took place within the BioPatRec environment, a Matlab-based open source platform that provides feature extraction, processing and motion classification algorithms for prosthetic control. The algorithms were applied to myoelectric signals for individual and simultaneous classification of movements, with the aim of finding the best performing algorithm and network model. Evaluation criteria included classification accuracy and training time. Results: Results in both the linear and the artificial neural network models demonstrated that Netlab's implementation using scaled conjugate training algorithm reached significantly higher accuracies than BioPatRec. Conclusions: It is concluded that the best movement classification performance would be achieved through integrating Netlab training algorithms in the BioPatRec environment so that future prosthesis training can be shortened and control made more reliable. Netlab was therefore included into the newest release of BioPatRec (v4.0).
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| 5. |
- Yadav, Sandhya, et al.
(author)
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Comparison and optimization of protein extraction and two-dimensional gel electrophoresis protocols for liverworts
- 2020
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In: BMC Research Notes. - : Springer Nature. - 1756-0500. ; 13:1
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Journal article (peer-reviewed)abstract
- Objective Liverworts possess historical adaptive strategies for abiotic stresses because they were the first plants that shifted from water to land. Proteomics is a state-of-the-art technique that can capture snapshots of events occurring at the protein level in many organisms. Herein, we highlight the comparison and optimization of an effective protein extraction and precipitation protocol for two-dimensional gel electrophoresis (2-DE) of liverworts. Results We compared three different protein extraction methods, i.e.,1.5 M Tris-HCl (pH 8.8), 50 mM Tris-HCl (pH 7.5), and polyvinylpolypyrrolidone (PVPP) extraction, followed by three precipitation methods, i.e., 80% ethanol, 80% acetone, and 20% tricholoroacetic acid (TCA)-acetone, in a liverwort Dumortiera hirsuta. Among these methods, 50 mM Tris-HCl (pH 7.5) extraction, followed by 20% TCA-acetone precipitation, appeared to be more suitable for 2-DE. Furthermore, we performed modifications during protein washing, re-solubilization in rehydration buffer and isoelectric focusing (IEF). The modifications provided us better results in terms of protein yield, resolution, spot numbers, and intensities for 2-DE gels of D. hirsuta and other two liverworts, i.e., Marchantia paleacea and Plagiochasma appendiculatum. Furthermore, we randomly selected spots from the 2-DE gel of D. hirsuta and identified using mass spectrometry, which confirms the applicability of this protocol for liverworts proteomics.
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