Enhanced analysis of real-time PCR data by using a variable efficiency model : FPK-PCR

Current methodology in real-time Polymerase chain reaction (PCR) analysis performs well provided PCR efficiency remains constant over reactions. Yet, small changes in efficiency can lead to large quantification errors. Particularly in biological samples, the possible presence of inhibitors forms a challenge. We present a new approach to single reaction efficiency calculation, called Full Process Kinetics-PCR (FPK-PCR). It combines a kinetically more realistic model with flexible adaptation to the full range of data. By reconstructing the entire chain of cycle efficiencies, rather than restricting the focus on a 'window of application', one extracts additional information and loses a level of arbitrariness. The maximal efficiency estimates returned by the model are comparable in accuracy and precision to both the golden standard of serial dilution and other single reaction efficiency methods. The cycle-to-cycle changes in efficiency, as described by the FPK-PCR procedure, stay considerably closer to the data than those from other S-shaped models. The assessment of individual cycle efficiencies returns more information than other single efficiency methods. It allows in-depth interpretation of real-time PCR data and reconstruction of the fluorescence data, providing quality control. Finally, by implementing a global efficiency model, reproducibility is improved as the selection of a window of application is avoided

Simulation of between repeat variability in real time PCR reactions

While many decisions rely on real time quantitative PCR (qPCR) analysis few attempts have hitherto been made to quantify bounds of precision accounting for the various sources of variation involved in the measurement process. Besides influences of more obvious factors such as camera noise and pipetting variation, changing efficiencies within and between reactions affect PCR results to a degree which is not fully recognized. Here, we develop a statistical framework that models measurement error and other sources of variation as they contribute to fluorescence observations during the amplification process and to derived parameter estimates. Evaluation of reproducibility is then based on simulations capable of generating realistic variation patterns. To this end, we start from a relatively simple statistical model for the evolution of efficiency in a single PCR reaction and introduce additional error components, one at a time, to arrive at stochastic data generation capable of simulating the variation patterns witnessed in repeated reactions (technical repeats). Most of the variation in C-q values was adequately captured by the statistical model in terms of foreseen components. To recreate the dispersion of the repeats' plateau levels while keeping the other aspects of the PCR curves within realistic bounds, additional sources of reagent consumption (side reactions) enter into the model. Once an adequate data generating model is available, simulations can serve to evaluate various aspects of PCR under the assumptions of the model and beyond

Effects of situation descriptions on the construct-related validity of construct-driven situational judgment tests

All data and code are available on the Open Science Framework https://osf.io/py6cm/</p

The role of situations in situational judgment tests: Effects on construct saturation, predictive validity, and applicant perceptions

Recent theorizing and empirical evidence suggesting that Situational Judgment Tests (SDI's) are more context-independent than previously thought has sparked a debate about the role of situation descriptions in S.M. To contribute to this debate and add to our understanding of how SJTs work, this article conceptually embeds SJT performance in a situation construal model and examines the effects of situation descriptions on the construct saturation and predictive validity of SJT scores, as well as on applicant perceptions. Across two studies (N = 1,092 and 578) and different Sri's, personality and cognitive ability were equally important determinants of SJT performance regardless of whether situation descriptions were presented or omitted. The effects of removing situation descriptions on the criterion-related validity of SJT scores differed depending on the breadth of the criteria. For predicting global job performance criteria (in-role performance and organizational citizenship behavior), SJT validity was not significantly affected, whereas it decreased for predicting more specific criteria (interpersonal adaptability, efficacy for teamwork). Finally, the effects of omitting situation descriptions in SJTs on applicant perceptions were either negligible or small. Implications for SJT theory, research, and design are discussed

Assessing the potential of wild yeasts for bioethanol production

Bioethanol fermentations expose yeasts to a new, complex and challenging fermentation medium with specific inhibitors and sugar mixtures depending on the type of carbon source. It is, therefore, suggested that the natural diversity of yeasts should be further exploited in order to find yeasts with good ethanol yield in stressed fermentation media. In this study, we screened more than 50 yeast isolates of which we selected five isolates with promising features. The species Candida bombi, Wickerhamomyces anomalus and Torulaspora delbrueckii showed better osmo- and hydroxymethylfurfural tolerance than Saccharomyces cerevisiae. However, S. cerevisiae isolates had the highest ethanol yield in fermentation experiments mimicking high gravity fermentations (25\ua0% glucose) and artificial lignocellulose hydrolysates (with a myriad of inhibitors). Interestingly, among two tested S. cerevisiaestrains, a wild strain isolated from an oak tree performed better than Ethanol Red, a S. cerevisiae strain which is currently commonly used in industrial bioethanol fermentations. Additionally, a W. anomalus strain isolated from sugar beet thick juice was found to have a comparable ethanol yield, but needed longer fermentation time. Other non-Saccharomycesyeasts yielded lower ethanol amounts

Phenotypic evaluation of natural and industrial Saccharomyces yeasts for different traits desirable in industrial bioethanol production

Saccharomyces cerevisiae is the organism of choice for many food and beverage fermentations because it thrives in high-sugar and high-ethanol conditions. However, the conditions encountered in bioethanol fermentation pose specific challenges, including extremely high sugar and ethanol concentrations, high temperature, and the presence of specific toxic compounds. It is generally considered that exploring the natural biodiversity of Saccharomyces strains may be an interesting route to find superior bioethanol strains and may also improve our understanding of the challenges faced by yeast cells during bioethanol fermentation. In this study, we phenotypically evaluated a large collection of diverse Saccharomyces strains on six selective traits relevant for bioethanol production with increasing stress intensity. Our results demonstrate a remarkably large phenotypic diversity among different Saccharomyces species and among S. cerevisiae strains from different origins. Currently applied bioethanol strains showed a high tolerance to many of these relevant traits, but several other natural and industrial S. cerevisiae strains outcompeted the bioethanol strains for specific traits. These multitolerant strains performed well in fermentation experiments mimicking industrial bioethanol production. Together, our results illustrate the potential of phenotyping the natural biodiversity of yeasts to find superior industrial strains that may be used in bioethanol production or can be used as a basis for further strain improvement through genetic engineering, experimental evolution, or breeding. Additionally, our study provides a basis for new insights into the relationships between tolerance to different stressors

The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology

The European Code of Cancer Practice

There are considerable disparities between the quality of cancer care and clinical outcomes for cancer patients in different European countries, regions, hospitals and communities. These have persisted despite the introduction of many European and National Cancer Plans, an extensive portfolio of clinical guidelines and the existence of evidence based guidelines for the good practice in planning cancer healthcare systems. We describe the European Code of Cancer Practice which is a citizen and patient-centred accessible widely disseminated statement of the core requirements for good clinical cancer practice. The Code sets out 10 key overarching Rights of what a patient should expect from their healthcare system each supported by a plain language explanation. The Rights highlight the importance of equal access to affordable and optimal cancer care, good quality information about an individual patient’s disease and treatment and about the quality and outcomes of the cancer service they will use. Specialised multidisciplinary cancer care teams, shared decision-making, research and innovation, a focus on quality of life, the integration of supportive and palliative care within oncology are all emphasised. There is a need for a systematic approach to supporting cancer survivors with a survivorship care plan including their rehabilitation, reintegration into society and return to work where appropriate without discrimination. The Code has been co-produced by a team of cancer patients, patient advocates and cancer professionals to bridge the gap between clinical guidelines, healthcare policies and patients’ everyday experience. It is robustly evidence-based and supported by a comprehensive review of the medical literature and evidence for good clinical practice. The Code is strongly endorsed by Europe’s professional and patient cancer organisations and the European Commission