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Abstract The analysis of biomarkers in biological fluids, also known as liquid biopsies, is seen with great potential to diagnose complex diseases such as cancer with a high sensitivity and minimal invasiveness. Although it can target any biomolecule, most liquid biopsy studies have focused on circulating nucleic acids. Historically, studies have aimed at the detection of specific mutations on cell-free DNA (cfDNA), but recently, the study of cell-free RNA (cfRNA) has gained traction. Since 2020, a handful of cfDNA tests have been approved for therapy selection by the FDA, however, no cfRNA tests are approved to date. One of the main drawbacks in the field of RNA-based liquid biopsies is the low reproducibility of the results, often caused by technical and biological variability, a lack of standardized protocols and insufficient cohorts. In this review, we will identify the main challenges and biases introduced during the different stages of biomarker discovery in liquid biopsies with cfRNA and propose solutions to minimize them.

The analysis of biomarkers in biological fluids, also known as liquid biopsies, is seen with great potential to diagnose complex diseases such as cancer with a high sensitivity and minimal invasiveness. Although it can target any biomolecule, most liquid biopsy studies have focused on circulating nucleic acids. Historically, studies have aimed at the detection of specific mutations on cell-free DNA (cfDNA), but recently, the study of cell-free RNA (cfRNA) has gained traction. Since 2020, a handful of cfDNA tests have been approved for therapy selection by the FDA, however, no cfRNA tests are approved to date. One of the main drawbacks in the field of RNA-based liquid biopsies is the low reproducibility of the results, often caused by technical and biological variability, a lack of standardized protocols and insufficient cohorts. In this review, we will identify the main challenges and biases introduced during the different stages of biomarker discovery in liquid biopsies with cfRNA and propose solutions to minimize them. [ABSTRACT FROM AUTHOR]

Simple Summary: Transposable elements (TEs) are repetitive sequences comprising more than one third of the human genome with the original ability to change their location within the genome. Owing to their repetitive nature, the quantification of TEs results often challenging. RNA-seq is a useful tool for genome-wide TEs quantification, nevertheless it also presents technical issues, including low reads mappability and erroneous quantification derived from the transcription of TEs fragments embedded in canonical transcripts. Fragments derived from TEs are found within the introns of most genes, which led to the hypothesis that intron retention (IR) can affect the unbiased quantification of TEs expression. Performing meta-analysis of public RNA-seq datasets, here we observe that IR can indeed impact the quantification of TEs by increasing the number of reads mapped on intronic TE copies. Our work highlights a correlation between IR and TEs expression measurement by RNA-seq that should be taken into account to achieve reliable TEs quantification, especially in samples characterized by extensive IR, because differential IR might be confused with differential TEs expression. Transposable elements (TEs), also known as "jumping genes", are repetitive sequences with the capability of changing their location within the genome. They are key players in many different biological processes in health and disease. Therefore, a reliable quantification of their expression as transcriptional units is crucial to distinguish between their independent expression and the transcription of their sequences as part of canonical transcripts. TEs quantification faces difficulties of different types, the most important one being low reads mappability due to their repetitive nature preventing an unambiguous mapping of reads originating from their sequences. A large fraction of TEs fragments localizes within introns, which led to the hypothesis that intron retention (IR) can be an additional source of bias, potentially affecting accurate TEs quantification. IR occurs when introns, normally removed from the mature transcript by the splicing machinery, are maintained in mature transcripts. IR is a widespread mechanism affecting many different genes with cell type-specific patterns. We hypothesized that, in an RNA-seq experiment, reads derived from retained introns can introduce a bias in the detection of overlapping, independent TEs RNA expression. In this study we performed meta-analysis using public RNA-seq data from lymphoblastoid cell lines and show that IR can impact TEs quantification using established tools with default parameters. Reads mapped on intronic TEs were indeed associated to the expression of TEs and influence their correct quantification as independent transcriptional units. We confirmed these results using additional independent datasets, demonstrating that this bias does not appear in samples where IR is not present and that differential TEs expression does not impact on IR quantification. We concluded that IR causes the over-quantification of intronic TEs and differential IR might be confused with differential TEs expression. Our results should be taken into account for a correct quantification of TEs expression from RNA-seq data, especially in samples in which IR is abundant. [ABSTRACT FROM AUTHOR]

Background: Despite the effect of 25 years of evidence-based medicine, the problem of bias is still prevalent in clinical research and its publication and in clinical practice. Its effect can lead to flawed research, misleading publications and ultimately patient harm. Aim: To draw attention to the commonest types of bias and how they influence clinical research, thinking and practice. Methods: This is not a systematic review but draws on the authors’ personal experience as clinical researchers, teachers, systematic reviewers and as arbiters of conflicts of interest for Cochrane. We describe the ones most relevant to oncology and give examples mainly from the literature on pulmonary metastasectomy. Results: There are two broad kinds of bias: technical bias, seen in the way research is conducted and published, and cognitive bias, the way in which beliefs, previous experience and thinking influence practice. The examples illustrate how common and diverse they are. Conclusion: These biases are widespread and influential and may actually cause harm. We are all susceptible to them and need to recognise them in ourselves and others and in what we read.

This paper aims at measuring productivity and efficiency of China’s three most important grain crops–rice, wheat and maize–as well as identifying the main directions of technical change prevailing in their production. The bias-corrected Malmquist production indices are employed to measure the technical changes (TCs) in terms of input-saving or input-using in China’s grain production, by using provincial aggregate data obtained from the National Farm Production Costs and Returns Survey. The research covers the period of 2003–2013. Application of the bias-corrected Malmquist index showed a labor-saving technical change against all the remaining inputs for the three crops under analysis. The highest frequencies of fertilizer- and machinery-using, labor-saving technical changes were observed for wheat farming. Therefore, a reduction in labor intensity should be the most promising for wheat if compared with rice and maize.

Microbial single cell analysis has led to discoveries that are beyond what can be resolved with population-based studies. It provides a pristine view of the mechanisms that organize cellular physiology, unbiased by population heterogeneity or uncontrollable environmental impacts. A holistic description of cellular functions at the single cell level requires analytical concepts beyond the miniaturization of existing technologies, defined but uncontrolled by the biological system itself. This review provides an overview of the latest advances in single cell technologies and demonstrates their potential. Opportunities and limitations of single cell microbiology are discussed using selected application-related examples. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Whether or not to biopsy the metastasis in recurrent breast cancer has become mired in controversy. Several studies have shown an important discordance of the immunohistochemical (IHC) determinations for ER, PR and HER2 between primary (PT) and recurrent tumors (RT). Yet it remains unknown within this what impact technical issues have. The aim of our study was to assess whether technical variability might have an impact on the concordance between PT and RT. Methods: IHC determinations in paired biopsies from PT and RT were compared under routine vs study conditions. In the former, pathological analysis reproduced the conditions used in the routine of a University Pathology Department. In the latter, in a technical bias-minimizing manner, samples were re-assessed at the same timing and by two independent observers. Results: 128 paired biopsies from 64 patients were analyzed under both conditions. Concordance under routine vs study conditions for ER was 66% vs 93.4% (p = 0.001), for PR 58.7% vs 80.3% (p = 0.064) and for HER2 86.8% vs 96.8% (p = 0.25). Kappa index under routine versus study conditions for ER was 0.27 vs 0.79 (p = 0.002), for PR 0.26 vs 0.39 (p = 0.47) and for HER2 0.67 vs 0.9 (p = 0.14). Conclusions: Although discordance rate between PT and RT decreased under conditions minimizing technical issues, some discordant cases appeared not to be subjected to this confounding factor. Either for clinical practice or for future studies reassessment of PT in recurrent breast cancer should be encouraged. [Copyright &y& Elsevier]

This paper addresses the issue with contradictory outcomes of cost-benefit analyses (CBA) performed on the same project that can be seen in many Norwegian public-investment projects. Different stakeholders may order "their own" appraisals of a specific project, which sometimes conclude quite differently from the other appraisals. This phenomenon is explored by studying the appraisals performed on eight Norwegian public-investment projects. Each of the projects analysed have been subject to many appraisals, which have all been compared and analysed. The following research questions have been explored: (1) How may various appraisals of the same project differ? (2) How may clients be able to influence the results of the appraisals? (3) How may the challenge with differing results, technical bias and low transparency of the appraisals be addressed in order to help decision-makers evaluate the various outcomes of CBAs? The findings show that the appraisals did vary in the projects studied; for some of them, quite substantially. The differences between appraisals were mostly related to the benefit side of the projects, both regarding which types of benefits were quantified and how they were measured and monetised. Important project-specific assumptions also differed among the appraisals. The findings indicate that the clients ordering the appraisals may have impacted the outcome of the appraisals by, for example, impacting project specific assumptions and demanding certain methodologies and standards to be used when quantifying and valuing benefits. A CBA can never be a complete, objective description of the matters under consideration. However, it is crucial that the appraisals are transparent and report on important factors that have large impact on the results so that decision-makers can evaluate the various appraisals and are able to use the information from them in decision-making processes. • Contradictory outcomes of CBAs appear when they are performed on the same public-investment project. • Differences are mostly related to types of benefits quantified and how they are measured and monetised. • Various opportunities exist for the clients who order the CBAs, to impact the results. [ABSTRACT FROM AUTHOR]