| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)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. |
- Bobbert, Peter A., et al.
(författare)
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Operational Stability of Organic Field-Effect Transistors
- 2012
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Ingår i: Advanced Materials. - : Wiley-VCH Verlag. - 0935-9648 .- 1521-4095. ; 24:9, s. 1146-1158
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Tidskriftsartikel (refereegranskat)abstract
- Organic field-effect transistors (OFETs) are considered in technological applications for which low cost or mechanical flexibility are crucial factors. The environmental stability of the organic semiconductors used in OFETs has improved to a level that is now sufficient for commercialization. However, serious problems remain with the stability of OFETs under operation. The causes for this have remained elusive for many years. Surface potentiometry together with theoretical modeling provide new insights into the mechanisms limiting the operational stability. These indicate that redox reactions involving water are involved in an exchange of mobile charges in the semiconductor with protons in the gate dielectric. This mechanism elucidates the established key role of water and leads in a natural way to a universal stress function, describing the stretched exponential-like time dependence ubiquitously observed. Further study is needed to determine the generality of the mechanism and the role of other mechanisms.
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| 3. |
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| 4. |
- Mathijssen, Simon G. J., et al.
(författare)
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Charge trapping at the dielectric of organic transistors visualized in real time and space
- 2008
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Ingår i: Advanced Materials. - : Wiley-VCH Verlag. - 0935-9648 .- 1521-4095. ; 20:5, s. 975-
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Tidskriftsartikel (refereegranskat)abstract
- Scanning Kelvin probe microscopy demonstrates that water-induced charge trapping at the SiO2 dielectric visualized in real time and space - is responsible for the commonly observed gate-bias-induced threshold-voltage shift in organic field-effect transistors. When a bias is applied to the electrodes, charges are injected onto the SiO2 (see background of the figure). When the contacts are grounded, the charges are released again (foreground picture).
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| 5. |
- Sharma, Abhinav, et al.
(författare)
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Clinical consequences of bleeding among individuals with a recent acute coronary syndrome : Insights from the APPRAISE-2 trial
- 2019
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Ingår i: American Heart Journal. - : MOSBY-ELSEVIER. - 0002-8703 .- 1097-6744. ; 215, s. 106-113
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Tidskriftsartikel (refereegranskat)abstract
- Background Patients with a recent acute coronary syndrome (ACS) receiving oral antiplatelets and anticoagulants are at risk for bleeding and subsequent adverse non-bleeding-related events. Methods In this post hoc analysis, we evaluated 7,392 high-risk patients (median follow-up 241 days) with a recent ACS randomized to apixaban or placebo in APPRAISE-2. Clinical events during a 30-day period after Thrombolysis in Myocardial Infarction (TIMI) major/minor bleeding were analyzed using unadjusted and adjusted Cox proportional-hazards models. Results In total, 153 (2.1%) patients experienced TIMI major/minor bleeding during follow-up. Bleeding risk for patients on triple therapy (apixaban, thienopyridine, and aspirin) was increased compared with those on dual therapy (apixaban plus aspirin: hazard ratio [HR] 2.02, 95% CI 1.08-3.79; thienopyridine plus aspirin: HR 1.99, 95% CI 1.41-2.83). Those receiving apixaban/aspirin had similar bleeding risk compared with those receiving thienopyridine/aspirin (HR 1.01, 95% CI 0.53-1.95). Patients who experienced TIMI major/minor bleeding had an increased risk of 30-day all-cause mortality (HR 24.7, 95% CI 15.34-39.66) and ischemic events (HR 6.7, 95% CI 3.14-14.14). Conclusions In a contemporary cohort of high-risk patients after ACS, bleeding was associated with a significantly increased risk of subsequent ischemic events and mortality regardless of antithrombotic or anticoagulant strategy. Patients receiving apixaban plus aspirin had a similar bleeding risk compared with those receiving thienopyridine plus aspirin. Interventions to improve outcomes in patients after ACS should include strategies to optimize the reduction in ischemic events while minimizing the risk of bleeding.
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| 6. |
- Sharma, Abhinav, et al.
(författare)
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Clinical Events Classification (CEC) in Clinical Trials : Report on the Current Landscape and Future Directions - Proceedings from the CEC Summit 2018
- 2022
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Ingår i: American Heart Journal. - : Elsevier. - 0002-8703 .- 1097-6744. ; 246, s. 93-104
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Tidskriftsartikel (refereegranskat)abstract
- Importance: Clinical events adjudication is pivotal for generating consistent and comparable evidence in clinical trials. The methodology of event adjudication is evolving, but research is needed to develop best practices and spur innovation.Observations: A meeting of stakeholders from regulatory agencies, academic and contract research organizations, pharmaceutical and device companies, and clinical trialists convened in Chicago, IL, for Clinical Events Classification (CEC) Summit 2018 to discuss key topics and future directions. Formal studies are lacking on strategies to optimize CEC conduct, improve efficiency, minimize cost, and generally increase the speed and accuracy of the event adjudication process. Major challenges to CEC discussed included ensuring rigorous quality of the process, identifying safety events, standardizing event definitions, using uniform strategies for missing information, facilitating interactions between CEC members and other trial leadership, and determining the CEC's role in pragmatic trials or trials using real-world data. Consensus recommendations from the meeting include the following: 1) ensure an adequate adjudication infrastructure; 2) use negatively adjudicated events to identify important safety events reported only outside the scope of the primary endpoint; 3) conduct further research in the use of artificial intelligence and digital/mobile technologies to streamline adjudication processes; and 4) emphasize the importance of standardizing event definitions and quality metrics of CEC programs.Conclusions and Relevance: As novel strategies for clinical trials emerge to generate evidence for regulatory approval and to guide clinical practice, a greater understanding of the role of the CEC process will be critical to optimize trial conduct and increase confidence in the data generated.
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| 7. |
- Sharma, Abhinav, et al.
(författare)
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Development and prognostic validation of a three-level NHG-like deep learning-based model for histological grading of breast cancer
- 2024
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Ingår i: Breast Cancer Research. - 1465-5411 .- 1465-542X. ; 26:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Histological grade is a well-known prognostic factor that is routinely assessed in breast tumours. However, manual assessment of Nottingham Histological Grade (NHG) has high inter-assessor and inter-laboratory variability, causing uncertainty in grade assignments. To address this challenge, we developed and validated a three-level NHG-like deep learning-based histological grade model (predGrade). The primary performance evaluation focuses on prognostic performance. Methods: This observational study is based on two patient cohorts (SöS-BC-4, N = 2421 (training and internal test); SCAN-B-Lund, N = 1262 (test)) that include routine histological whole-slide images (WSIs) together with patient outcomes. A deep convolutional neural network (CNN) model with an attention mechanism was optimised for the classification of the three-level histological grading (NHG) from haematoxylin and eosin-stained WSIs. The prognostic performance was evaluated by time-to-event analysis of recurrence-free survival and compared to clinical NHG grade assignments in the internal test set as well as in the fully independent external test cohort. Results: We observed effect sizes (hazard ratio) for grade 3 versus 1, for the conventional NHG method (HR = 2.60 (1.18–5.70 95%CI, p-value = 0.017)) and the deep learning model (HR = 2.27, 95%CI 1.07–4.82, p-value = 0.033) on the internal test set after adjusting for established clinicopathological risk factors. In the external test set, the unadjusted HR for clinical NHG 2 versus 1 was estimated to be 2.59 (p-value = 0.004) and clinical NHG 3 versus 1 was estimated to be 3.58 (p-value < 0.001). For predGrade, the unadjusted HR for predGrade 2 versus 1 HR = 2.52 (p-value = 0.030), and 4.07 (p-value = 0.001) for preGrade 3 versus 1 was observed in the independent external test set. In multivariable analysis, HR estimates for neither clinical NHG nor predGrade were found to be significant (p-value > 0.05). We tested for differences in HR estimates between NHG and predGrade in the independent test set and found no significant difference between the two classification models (p-value > 0.05), confirming similar prognostic performance between conventional NHG and predGrade. Conclusion: Routine histopathology assessment of NHG has a high degree of inter-assessor variability, motivating the development of model-based decision support to improve reproducibility in histological grading. We found that the proposed model (predGrade) provides a similar prognostic performance as clinical NHG. The results indicate that deep CNN-based models can be applied for breast cancer histological grading.
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| 8. |
- Sharma, Abhinav, et al.
(författare)
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Use of Biomarkers to Predict Specific Causes of Death in Patients With Atrial Fibrillation : Insights From the ARISTOTLE Trial
- 2018
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Ingår i: Circulation. - : LIPPINCOTT WILLIAMS & WILKINS. - 0009-7322 .- 1524-4539. ; 138:16, s. 1666-1676
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Tidskriftsartikel (refereegranskat)abstract
- Background: Atrial fibrillation is associated with an increased risk of death. High-sensitivity troponin T, growth differentiation factor-15, NT-proBNP (N-terminal pro-B-type natriuretic peptide), and interleukin-6 levels are predictive of cardiovascular events and total cardiovascular death in anticoagulated patients with atrial fibrillation. The prognostic utility of these biomarkers for cause-specific death is unknown. Methods: The ARISTOTLE trial (Apixaban for the Prevention of Stroke in Subjects With Atrial Fibrillation) randomized 18201 patients with atrial fibrillation to apixaban or warfarin. Biomarkers were measured at randomization in 14798 patients (1.9 years median follow-up). Cox models were used to identify clinical variables and biomarkers independently associated with each specific cause of death. Results: In total, 1272 patients died: 652 (51%) cardiovascular, 32 (3%) bleeding, and 588 (46%) noncardiovascular/nonbleeding deaths. Among cardiovascular deaths, 255 (39%) were sudden cardiac deaths, 168 (26%) heart failure deaths, and 106 (16%) stroke/systemic embolism deaths. Biomarkers were the strongest predictors of cause-specific death: a doubling of troponin T was most strongly associated with sudden death (hazard ratio [HR], 1.48; P<0.001), NT-proBNP with heart failure death (HR, 1.62; P<0.001), and growth differentiation factor-15 with bleeding death (HR, 1.72; P=0.028). Prior stroke/systemic embolism (HR, 2.58; P>0.001) followed by troponin T (HR, 1.45; P<0.0029) were the most predictive for stroke/ systemic embolism death. Adding all biomarkers to clinical variables improved discrimination for each cause-specific death. Conclusions: Biomarkers were some of the strongest predictors of cause-specific death and may improve the ability to discriminate among patients' risks for different causes of death. These data suggest a potential role of biomarkers for the identification of patients at risk for different causes of death in patients anticoagulated for atrial fibrillation. Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00412984.
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