| 1. |
- Schweinsberg, Martin, et al.
(författare)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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Ingår i: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Tidskriftsartikel (refereegranskat)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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| 2. |
- Baccarani, Michele, et al.
(författare)
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European LeukemiaNet recommendations for the management of chronic myeloid leukemia : 2013
- 2013
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Ingår i: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 122:6, s. 872-884
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Forskningsöversikt (refereegranskat)abstract
- Advances in chronic myeloid leukemia treatment, particularly regarding tyrosine kinase inhibitors, mandate regular updating of concepts and management. A European LeukemiaNet expert panel reviewed prior and new studies to update recommendations made in 2009. We recommend as initial treatment imatinib, nilotinib, or dasatinib. Response is assessed with standardized real quantitative polymerase chain reaction and/or cytogenetics at 3, 6, and 12 months. BCR-ABL1 transcript levels <= 10% at 3 months, <1% at 6 months, and <= 0.1% from 12 months onward define optimal response, whereas >10% at 6 months and >1% from 12 months onward define failure, mandating a change in treatment. Similarly, partial cytogenetic response (PCyR) at 3 months and complete cytogenetic response (CCyR) from 6 months onward define optimal response, whereas no CyR (Philadelphia chromosome-positive [Ph1]>95%) at 3 months, less than PCyR at 6 months, and less than CCyR from 12 months onward define failure. Between optimal and failure, there is an intermediate warning zone requiring more frequent monitoring. Similar definitions are provided for response to second-line therapy. Specific recommendations are made for patients in the accelerated and blastic phases, and for allogeneic stem cell transplantation. Optimal responders should continue therapy indefinitely, with careful surveillance, or they can be enrolled in controlled studies of treatment discontinuation once a deeper molecular response is achieved. (Blood. 2013; 122(6):872-884)
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| 3. |
- Hjorth, Timothy, et al.
(författare)
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Rationalising crystal nucleation of organic molecules in solution using artificial neural networks
- 2019
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Ingår i: CrystEngComm. - : ROYAL SOC CHEMISTRY. - 1466-8033. ; 21:3, s. 449-461
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Tidskriftsartikel (refereegranskat)abstract
- In this study, the method of artificial neural networks (ANNs) is applied to analyse the effect of various solute, solvent, and solution properties on the difficulty of primary nucleation, without bias towards any particular nucleation theory. Sets of ANN models are developed and fitted to data for 36 binary systems of 9 organic solutes in 11 solvents, using Bayesian regularisation without early stopping and 6-fold cross validation. An initial model set with 21 input parameters is developed and analysed. A refined model set with 10 input parameters is then evaluated, with an overall improvement in accuracy. The results indicate partial qualitative consistency between the ANN models and the classical nucleation theory (CNT), with the nucleation difficulty increasing with an increase in mass transport resistance and a reduction in solubility. Notably, some parameters not included in CNT, including solute molecule bond rotational flexibility, the entropy of melting of the solute, and intermolecular interactions, also exhibit explanatory importance and significant qualitative effect relationships. A high entropy of melting and solute bond rotational flexibility increase the nucleation difficulty. Stronger solute-solute or solvent-solvent interactions are correlated with a facilitated nucleation, which is reasonable in the context of desolvation. A dissimilarity between solute and solvent hydrophobicities is connected with an easier nucleation.
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| 4. |
- Stray-Pedersen, Asbjorg, et al.
(författare)
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Primary immunodeficiency diseases : Genomic approaches delineate heterogeneous Mendelian disorders
- 2017
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Ingår i: Journal of Allergy and Clinical Immunology. - : MOSBY-ELSEVIER. - 0091-6749 .- 1097-6825. ; 139:1, s. 232-245
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Tidskriftsartikel (refereegranskat)abstract
- Background: Primary immunodeficiency diseases (PIDDs) are clinically and genetically heterogeneous disorders thus far associated with mutations in more than 300 genes. The clinical phenotypes derived from distinct genotypes can overlap. Genetic etiology can be a prognostic indicator of disease severity and can influence treatment decisions. Objective: We sought to investigate the ability of whole-exome screening methods to detect disease-causing variants in patients with PIDDs. Methods: Patients with PIDDs from 278 families from 22 countries were investigated by using whole-exome sequencing. Computational copy number variant (CNV) prediction pipelines and an exome-tiling chromosomal microarray were also applied to identify intragenic CNVs. Analytic approaches initially focused on 475 known or candidate PIDD genes but were nonexclusive and further tailored based on clinical data, family history, and immunophenotyping. Results: A likely molecular diagnosis was achieved in 110 (40%) unrelated probands. Clinical diagnosis was revised in about half (60/ 110) and management was directly altered in nearly a quarter (26/ 110) of families based on molecular findings. Twelve PIDD-causing CNVs were detected, including 7 smaller than 30 Kb that would not have been detected with conventional diagnostic CNV arrays. Conclusion: This high-throughput genomic approach enabled detection of disease-related variants in unexpected genes; permitted detection of low-grade constitutional, somatic, and revertant mosaicism; and provided evidence of a mutational burden in mixed PIDD immunophenotypes.
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| 5. |
- Svärd, Michael, et al.
(författare)
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Calorimetric Properties and Solubility in Five Pure Organic Solvents of N-Methyl-D-Glucamine (Meglumine)
- 2016
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Ingår i: Journal of Chemical and Engineering Data. - : American Chemical Society (ACS). - 0021-9568 .- 1520-5134. ; 61:3, s. 1199-1204
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Tidskriftsartikel (refereegranskat)abstract
- The solid liquid solubility of the title compound has been measured by a gravimetric method in five pure organic solvents over the temperature range (283 to 323) K. The melting temperature and associated enthalpy of fusion have been determined by differential scanning calorimetry (DSC), and the heat capacity of the solid and the melt have been determined over a range of temperatures by means of temperature-modulated DSC. Melting data and the extrapolated difference in heat capacity between the melt and the solid have been used to calculate the Gibbs energy, enthalpy, and entropy of fusion and the ideal solubility from below ambient temperature to the melting point. On the basis of estimated activity coefficients at equilibrium, solutions in all the five solvents are shown to exhibit positive deviation from Raoult's law. The highest mole fraction solubility is observed in methanol, and all van't Hoff solubility curves are nonlinear. Solubility data is well correlated by a recently proposed semiempirical regression model.
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