Guidelines for measuring cardiac physiology in mice Lindsey, Merry L; Kassiri, Zamaneh; Virag, Jitka A I ...
American journal of physiology. Heart and circulatory physiology,
04/2018, Letnik:
314, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Cardiovascular disease is a leading cause of death, and translational research is needed to understand better mechanisms whereby the left ventricle responds to injury. Mouse models of heart disease ...have provided valuable insights into mechanisms that occur during cardiac aging and in response to a variety of pathologies. The assessment of cardiovascular physiological responses to injury or insult is an important and necessary component of this research. With increasing consideration for rigor and reproducibility, the goal of this guidelines review is to provide best-practice information regarding how to measure accurately cardiac physiology in animal models. In this article, we define guidelines for the measurement of cardiac physiology in mice, as the most commonly used animal model in cardiovascular research. Listen to this article's corresponding podcast at http://ajpheart.podbean.com/e/guidelines-for-measuring-cardiac-physiology-in-mice/ .
Quantitative size, shape, and texture features derived from computed tomographic (CT) images may be useful as predictive, prognostic, or response biomarkers in non-small cell lung cancer (NSCLC). ...However, to be useful, such features must be reproducible, non-redundant, and have a large dynamic range. We developed a set of quantitative three-dimensional (3D) features to describe segmented tumors and evaluated their reproducibility to select features with high potential to have prognostic utility. Thirty-two patients with NSCLC were subjected to unenhanced thoracic CT scans acquired within 15 min of each other under an approved protocol. Primary lung cancer lesions were segmented using semi-automatic 3D region growing algorithms. Following segmentation, 219 quantitative 3D features were extracted from each lesion, corresponding to size, shape, and texture, including features in transformed spaces (laws, wavelets). The most informative features were selected using the concordance correlation coefficient across test–retest, the biological range and a feature independence measure. There were 66 (30.14 %) features with concordance correlation coefficient ≥ 0.90 across test–retest and acceptable dynamic range. Of these, 42 features were non-redundant after grouping features with
R
2
Bet
≥ 0.95. These reproducible features were found to be predictive of radiological prognosis. The area under the curve (AUC) was 91 % for a size-based feature and 92 % for the texture features (runlength, laws). We tested the ability of image features to predict a radiological prognostic score on an independent NSCLC (39 adenocarcinoma) samples, the AUC for texture features (runlength emphasis, energy) was 0.84 while the conventional size-based features (volume, longest diameter) was 0.80. Test–retest and correlation analyses have identified non-redundant CT image features with both high intra-patient reproducibility and inter-patient biological range. Thus making the case that quantitative image features are informative and prognostic biomarkers for NSCLC.
This installment of Computer’s series highlighting the work published in IEEE Computer Society journals comes from IEEE Transactions on Parallel and Distributed Systems.
Reproducibility in Chemical Research Bergman, Robert G.; Danheiser, Rick L.
Angewandte Chemie (International ed.),
10/2016, Letnik:
55, Številka:
41
Journal Article
Recenzirano
Odprti dostop
“… To what extent is reproducibility a significant issue in chemical research? How can problems involving irreproducibility be minimized? … Researchers should be aware of the dangers of unconscious ...investigator bias, all papers should provide adequate experimental detail, and Reviewers have a responsibility to carefully examine papers for adequacy of experimental detail and support for the conclusions …” Read more in the Editorial by Robert G. Bergman and Rick L. Danheiser.
MPs have called for a clearer focus from research funders, publishers, and academic institutions to ensure that research is transparent and reproducible.1 A report from the House of Commons Science, ...Innovation, and Technology Select Committee says that the integrity of some scientific research has been called into question because of difficulties in replicating findings. The research funding system, which provided relatively short term grants from research projects, contributed to “short termism” among researchers and created the conditions for increasingly unstable academic careers. “Scientific progress requires transparency: being able to reproduce analysis to check research findings are robust,” said Greg Clark, committee chair.
El objetivo de este estudio fue examinar la fiabilidad absoluta de las pruebas de estimación de la flexibilidad de la musculatura del tríceps sural ROM-sóleo y ROM-gemelo a través de un diseño de ...medidas repetidas. 40 jugadores profesionales de futbol sala completaron 3 sesiones de evaluación del ROM articular de la dorsi-flexión del tobillo con rodilla flexionada (ROM-sóleo) y extendida (ROM-gemelo) con un intervalo de 2 semanas entre sesiones consecutivas. La fiabilidad absoluta fue examinada mediante el cálculo de los estadísticos cambio en la media (CM) entre sesiones de valoración, porcentaje del error típico (CVET) e índice de correlación intraclase (ICC). Los resultados del actual estudio demuestran que las pruebas ROM-sóleo y ROM-gemelo presentan una elevada fiabilidad absoluta (CM <2%; CVET <6.5%; ICC > 0.8).
BackgroundInter-modality agreement allows interchangeable use of imaging modalities that is crucial for clinical decision-making, while the reproducibility of a technique is fundamental for ...monitoring disease progression or response to treatment. We aimed to investigate the test-retest reproducibility and inter-modality agreement of transthoracic echocardiography (TTE) and cardiac magnetic resonance (CMR) imaging in assessing left ventricular (LV) and left atrial (LA) myocardial deformation in people with type 2 diabetes mellitus (T2D).MethodsParticipants with T2D and no cardiovascular disease underwent TTE and CMR on the same day and again 11± 4 days later. Images were analysed using TomTec-ARENA (v2.4, 2D-CPA) for TTE, where Medis Suite (v3.1, medical imaging system) was used for CMR images. LV global longitudinal strain (GLS) was calculated using an average of 2-, 3- and 4-chamber values and LV mid-circumferential strain (LV_MCS) was calculated from the mid short-axis cine at papillary muscles level. In addition, LA strain (LAS), corresponding to LA reservoir, conduit, and booster pump (contraction function), was calculated using the average of 4- and 2-chamber values. The exact same analysis technique was used for both imaging modalities, and blinded analysis was performed by the same observer.Results10 participants with T2D (mean age 65.6±7.3 years, 50% male) were studied. The LV_MCS and reservoir LAS were significantly lower on CMR compared to TTE, though there was no difference in GLS, with narrow limits of agreement between CMR and TTE values. Of all strain parameters, GLS had the best test-retest reproducibility, with almost identical bias and limits of agreement on Bland-Altman analysis and similar CoV (~15%). The test-retest reproducibility for LV_MCS and reservoir LAS were better on CMR than TTE (table 1 & figure 1). TTE was more reproducible for conduit LAS (CoV 18.5%, ICC =0.80).Abstract 4 Table 1Test-retest reproducibility of myocardial deformation in TTE and CMR Parameter Scan 1 (Mean±SD) Scan 2 (Mean±SD) Bias (Limits of agreement) ICC ICC_p-value CoV (%) TTE LV_GLS (%) −17.2±2.4 −16.8±1.6 −0.37 (−5.44, 4.70) 0.36 0.272 15.25 LV_MCS (%) −25.4±4.0 −23.9±2.8 −1.54 (−11.9, 8.86) 0.4 0.686 21.53 LAS_r (%) 33.8±3.7 31.4±6.8 2.45 (−10.9, 15.8) 0.35 0.26 20.9 LAS_cd (%) 16.7±3.4 15.0±4.2 1.64 (−4.11, 7.38) 0.8 0.008* 18.5 LAS_bp (%) 17.1±3.2 16.3±4.4 0.81 (−9.17, 10.8) 0.23 0.362 30.4 CMR LV_GLS (%) −17.4±2.2 −17.0±2.5 −0.37 (−5.11, 4.36) 0.65 0.078 14.1 LV_MCS (%) −19.9±2.0 −19.2±3.6 −0.66 (−7.18, 5.86) 0.53 0.146 17 LAS_r (%) 29.2±6.5 27.9±7.8 1.26 (−9.74, 12.3) 0.83 0.009* 19.6 LAS_cd (%) 15.1±6.0 12.6±5.3 2.57 (−7.30, 12.4) 0.73 0.024* 36.3 LAS_bp (%) 14.0±5.9 15.4±6.0 −1.31 (−11.4, 8.73) 0.78 0.020* 34.9 Abbreviations: LV_GLS= Left ventricular global longitudinal strain, LV_MCS= Left ventricular mid circumferential strain, LAS_r = Left atrial strain at reservoir phase, LAS_cd = Left atrial strain at conduit phase, LAS_bp = Left atrial strain at booster pump phase.Abstract 4 Figure 1Bland-Altman plot for test-retest reproducibility of LV global longitudinal strain and LA reservoir strain in TTE and CMRConclusionBoth CMR and TTE gave similar values for GLS, with good inter-modality agreement and equally good test-retest reproducibility, suggesting the potential use of both modalities for monitoring GLS in disease and in response to treatment. The test-retest reproducibility of LV_MCS and reservoir LAS was better on CMR, whilst TTE was better for assessing conduit LAS.
Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions
...(for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping
(the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations
. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys ...contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science.
We rewrote the entire ImageJ codebase, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements. This next-generation ImageJ, called "ImageJ2" in places where the distinction matters, provides a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace.
Scientific imaging benefits from open-source programs that advance new method development and deployment to a diverse audience. ImageJ has continuously evolved with this idea in mind; however, new and emerging scientific requirements have posed corresponding challenges for ImageJ's development. The described improvements provide a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs. Future efforts will focus on implementing new algorithms in this framework and expanding collaborations with other popular scientific software suites.
PDF
