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Current methods for single-molecule orientation localization microscopy (SMOLM) require optical setups and algorithms that can be prohibitively slow and complex, limiting widespread adoption for biological applications. We present POLCAM, a simplified SMOLM method based on polarized detection using a polarization camera, which can be easily implemented on any wide-field fluorescence microscope. To make polarization cameras compatible with single-molecule detection, we developed theory to minimize field-of-view errors, used simulations to optimize experimental design and developed a fast algorithm based on Stokes parameter estimation that can operate over 1,000-fold faster than the state of the art, enabling near-instant determination of molecular anisotropy. To aid in the adoption of POLCAM, we developed open-source image analysis software and a website detailing hardware installation and software use. To illustrate the potential of POLCAM in the life sciences, we applied our method to study α-synuclein fibrils, the actin cytoskeleton of mammalian cells, fibroblast-like cells and the plasma membrane of live human T cells., (© 2024. The Author(s).)

Background: The advent of Julia as a sophisticated and dynamic programming language in 2012 represented a significant milestone in computational programming, mathematical analysis, and statistical modeling. Having reached its stable release in version 1.9.0 on May 7, 2023, Julia has developed into a powerful and versatile instrument. Despite its potential and widespread adoption across various scientific and technical domains, there exists a noticeable knowledge gap in comprehending its utilization within biological sciences., The Aim of Review: This comprehensive review aims to address this particular knowledge gap and offer a thorough examination of Julia's fundamental characteristics and its applications in biology., Key Scientific Concepts of the Review: The review focuses on a research gap in the biological science. The review aims to equip researchers with knowledge and tools to utilize Julia's capabilities in biological science effectively and to demonstrate the gap. It paves the way for innovative solutions and discoveries in this rapidly evolving field. It encompasses an analysis of Julia's characteristics, packages, and performance compared to the other programming languages in this field. The initial part of this review discusses the key features of Julia, such as its dynamic and interactive nature, fast processing speed, ease of expression manipulation, user-friendly syntax, code readability, strong support for multiple dispatch, and advanced type system. It also explores Julia's capabilities in data analysis, visualization, machine learning, and algorithms, making it suitable for scientific applications. The next section emphasizes the importance of using Julia in biological research, highlighting its seamless integration with biological studies for data analysis, and computational biology. It also compares Julia with other programming languages commonly used in biological research through benchmarking and performance analysis. Additionally, it provides insights into future directions and potential challenges in Julia's applications in biology., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Production and hosting by Elsevier B.V.)

Detailed method descriptions are essential for reproducibility, research evaluation, and effective data reuse. We summarize the key recommendations for life sciences researchers and research institutions described in the European Commission PRO-MaP report., Competing Interests: M.L. is a current employee of PLOS. E.G. is a former Editor in Chief of PLOS Biology. V.S. was the founding Executive Director of PLOS and one of the launch editors for PLOS Biology. A.C. is a former PLOS employee. As is noted in the author affiliations, some of the experts who contributed to these guidelines are employed by protocol repositories, protocol journals or publishers that publish protocol papers, methods papers, protocol journals or methods journals. S.B.L. is employed with the European Food Safety Authority (EFSA) in the Unit PREV that provides scientific and administrative support to the Panel on Plant Protection Products and their Residues in the area Assess Dept. However, the present article is published under the sole responsibility of the author/s and may not be considered as an EFSA scientific output. The positions and opinions presented in this article are those of the author/s alone and do not represent the views/any official position or scientific works of EFSA. To know about the views or scientific outputs of EFSA, please consult its website under http://www.efsa.europa.eu. M.B. was an employee of the NC3R. His role included promoting the ARRIVE guidelines and coordinating the RIVER recommendations working group., (Copyright: © 2024 Batista Leite et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Images are at the core of most modern biological experiments and are used as a major source of quantitative information. Numerous algorithms are available to process images and make them more amenable to be measured. Yet the nature of the quantitative output that is useful for a given biological experiment is uniquely dependent upon the question being investigated. Here, we discuss the 3 main types of information that can be extracted from microscopy data: intensity, morphology, and object counts or categorical labels. For each, we describe where they come from, how they can be measured, and what may affect the relevance of these measurements in downstream data analysis. Acknowledging that what makes a measurement 'good' is ultimately down to the biological question being investigated, this review aims at providing readers with a toolkit to challenge how they quantify their own data and be critical of conclusions drawn from quantitative bioimage analysis experiments., (© 2023 European Molecular Biology Laboratory (EMBL) and The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

Modern life science research is a collaborative effort. Few research groups can single-handedly support the necessary equipment, expertise and personnel needed for the ever-expanding portfolio of technologies that are required across multiple disciplines in today's life science endeavours. Thus, research institutes are increasingly setting up scientific core facilities to provide access and specialised support for cutting-edge technologies. Maintaining the momentum needed to carry out leading research while ensuring high-quality daily operations is an ongoing challenge, regardless of the resources allocated to establish such facilities. Here, we outline and discuss the range of activities required to keep things running once a scientific imaging core facility has been established. These include managing a wide range of equipment and users, handling repairs and service contracts, planning for equipment upgrades, renewals, or decommissioning, and continuously upskilling while balancing innovation and consolidation., (© 2024 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches 1-6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations 7-14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems., (© 2023. The Author(s).)

Micrograph comparison remains useful in bioscience. This technology provides researchers with a quick snapshot of experimental conditions. But sometimes a two- condition comparison relies on researchers' eyes to draw conclusions. Our Bioimage Analysis, Statistic, and Comparison (BASIN) software provides an objective and reproducible comparison leveraging inferential statistics to bridge image data with other modalities. Users have access to machine learning-based object segmentation. BASIN provides several data points such as images' object counts, intensities, and areas. Hypothesis testing may also be performed. To improve BASIN's accessibility, we implemented it using R Shiny and provided both an online and offline version. We used BASIN to process 498 image pairs involving five bioscience topics. Our framework supported either direct claims or extrapolations 57% of the time. Analysis results were manually curated to determine BASIN's accuracy which was shown to be 78%. Additionally, each BASIN version's initial release shows an average 82% FAIR compliance score., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

A panoply of new tools for tracking single particles and molecules has led to an explosion of experimental data, leading to novel insights into physical properties of living matter governing cellular development and function, health and disease. In this Perspective, we present tools to investigate the dynamics and mechanics of living systems from the molecular to cellular scale via single-particle techniques. In particular, we focus on methods to measure, interpret, and analyse complex data sets that are associated with forces, materials properties, transport, and emergent organisation phenomena within biological and soft-matter systems. Current approaches, challenges, and existing solutions in the associated fields are outlined in order to support the growing community of researchers at the interface of physics and the life sciences. Each section focuses not only on the general physical principles and the potential for understanding living matter, but also on details of practical data extraction and analysis, discussing limitations, interpretation, and comparison across different experimental realisations and theoretical frameworks. Particularly relevant results are introduced as examples. While this Perspective describes living matter from a physical perspective, highlighting experimental and theoretical physics techniques relevant for such systems, it is also meant to serve as a solid starting point for researchers in the life sciences interested in the implementation of biophysical methods.

Every quarter, The FEBS Journal presents some of its "hidden gems"-original research and review-type articles that provide a significant advance or discuss recent developments in the molecular or cellular life sciences. These articles are of high value to the scientific community, and we like to take the opportunity to promote these contributions from previous issues of the journal, as we feel their scientific content merits a boost in exposure., (© 2021 Federation of European Biochemical Societies.)

This review discusses the philosophical foundations of what used to be called "the scientific method" and is nowadays often known as the scientific attitude. It used to be believed that scientific theories and methods aimed at the truth especially in the case of physics, chemistry and astronomy because these sciences were able to develop numerous scientific laws that made it possible to understand and predict many physical phenomena. The situation is different in the case of the biological sciences which deal with highly complex living organisms made up of huge numbers of constituents that undergo continuous dynamic processes; this leads to novel emergent properties in organisms that cannot be predicted because they are not present in the constituents before they have interacted with each other. This is one of the reasons why there are no universal scientific laws in biology. Furthermore, all scientific theories can only achieve a restricted level of predictive success because they remain valid only under the limited range of conditions that were used for establishing the theory' in the first place. Many theories that used to be accepted were subsequently shown to be false, demonstrating that scientific theories always remain tentative and can never be proven beyond and doubt. It is ironical that as scientists have finally accepted that approximate truths are perfectly adequate and that absolute truth is an illusion, a new irrational sociological phenomenon called Post-Truth conveyed by social media, the Internet and fake news has developed in the Western world that is convincing millions of people that truth simply does not exist. Misleading information is circulated with the intention to deceive and science denialism is promoted by denying the remarkable achievements of science and technology during the last centuries. Although the concept of intentional design is widely used to describe the methods that biologists use to make discoveries and inventions, it will be argued that the term is not appropriate for explaining the appearance of life on our planet nor for describing the scientific creativity of scientific investigators. The term rational for describing the development of new vaccines is also unjustified. Because the analysis of the COVID-19 pandemic requires contributions from biomedical and psycho-socioeconomic sciences, one scientific method alone would be insufficient for combatting the pandemic., (Copyright © 2021. Published by Elsevier Inc.)

In the philosophy of science, we can consider debates about the nature of non-causal explanations in general (e.g. Reutlinger, Saatsi 2018; Lange 2017) and then especially those in the life sciences (e.g. Huneman, 2018; Kostić 2020). These debates are accompanied by the development of a new mechanism that is becoming the major response to the nature of scientific explanation in the life sciences (e.g. Craver, Darden 2013; Craver 2006); and also by the development of a design explanation (e.g. Eck, Mennes 2016) that represents a modern variant of a functional explanation. In this paper, we will methodically: 1. evaluate the plurality of explanatory strategies in contemporary science (chapter 2). 2. describe the mechanical philosophy and mechanistic explanation (Glennan 2016; Craver, Darden 2013, etc.) (chapter 3). 3. explicate the role of mechanisms in code biology (Barbieri 2015, 2002, etc.) and its relation to the new mechanism (chapter 4). 4. fulfill the main goal of the paper - to apply mechanistic explanations in code biology (Barbieri 2019, etc.) and to apply their suitability for this scientific domain (chapter 5)., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Communication of science through online media has become a primary means of disseminating and connecting science with a public audience. However, online media can come in many forms and stories of scientific discovery can be told by many individuals. We tested whether the relationship of a spokesperson to the science story being told (i.e., the narrative perspective) influences how people react and respond to online science media. We created five video stimuli that fell into three treatments: a scientist presenting their own research (male or female), a third-party summarizing research (male or female), and an infographic-like video with no on-screen presenter. Each of these videos presented the same fabricated science story about the discovery of a new ant species (Formicidae). We used Qualtrics to administer and obtain survey responses from 515 participants (~100 per video). Participants were randomly assigned to one of the videos and after viewing the stimulus answered questions assessing their perceptions of the video (trustworthiness and enjoyment), the spokesperson (trustworthiness and competence), scientists in general (competence and warmth), and attitudes towards the research topic and funding. Participants were also asked to recall what they had seen and heard. We determined that when participants watched a video in which a scientist presented their own research, participants perceived the spokesperson as having more expertise than a third-party presenter, and as more trustworthy and having more expertise than the no-spokesperson stimuli. Viewing a scientist presenting their own work also humanized the research, with participants more often including a person in their answer to the recall question. Overall, manipulating the narrative perspective of the source of a single online video communication effort is effective at impacting immediate objective outcomes related to spokesperson perceptions, but whether those objectives can positively influence long-term goals requires more investigation., Competing Interests: The authors have declared that no competing interests exist.

The article deals with the different organisational units in current bioethics, and their main characteristics concerning life sciences. Three out of four organisational units of current bioethics jeopardise the autonomy of life sciences by establishing rules, regulations and laws, regulating and restricting life sciences. Only the integration of bioethics in life science serves the interests of life sciences.

Scientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries. Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. Several strategies exist to overcome the problem of multiple hypothesis testing. We aim to summarize critical statistical concepts and widely used correction approaches while also draw attention to frequently misinterpreted notions of statistical inference. We provide a step-by-step description of each multiple-testing correction method with clear examples and present an easy-to-follow guide for selecting the most suitable correction technique. To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at www.multipletesting.com and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm (step-down), the Hochberg (step-up) corrections, allows to calculate False Discovery Rates (FDR) and q-values. The current summary provides a much needed practical synthesis of basic statistical concepts regarding multiple hypothesis testing in a comprehensible language with well-illustrated examples. The web tool will fill the gap for life science researchers by providing a user-friendly substitute for command-line alternatives., Competing Interests: The authors B. Gy. and O. M declare no potential conflicts of interest. The author B. W. received salary from the commercial company A5 Genetics Ltd, Hungary. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Europe PMC (https://europepmc.org) is a database of research articles, including peer reviewed full text articles and abstracts, and preprints - all freely available for use via website, APIs and bulk download. This article outlines new developments since 2017 where work has focussed on three key areas: (i) Europe PMC has added to its core content to include life science preprint abstracts and a special collection of full text of COVID-19-related preprints. Europe PMC is unique as an aggregator of biomedical preprints alongside peer-reviewed articles, with over 180 000 preprints available to search. (ii) Europe PMC has significantly expanded its links to content related to the publications, such as links to Unpaywall, providing wider access to full text, preprint peer-review platforms, all major curated data resources in the life sciences, and experimental protocols. The redesigned Europe PMC website features the PubMed abstract and corresponding PMC full text merged into one article page; there is more evident and user-friendly navigation within articles and to related content, plus a figure browse feature. (iii) The expanded annotations platform offers ∼1.3 billion text mined biological terms and concepts sourced from 10 providers and over 40 global data resources., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

This article examines why many studies fail to replicate statistically significant published results. We address this issue within a general statistical framework that also allows us to include various questionable research practices (QRPs) that are thought to reduce replicability. The analyses indicate that the base rate of true effects is the major factor that determines the replication rate of scientific results. Specifically, for purely statistical reasons, replicability is low in research domains where true effects are rare (e.g., search for effective drugs in pharmacology). This point is under-appreciated in current scientific and media discussions of replicability, which often attribute poor replicability mainly to QRPs., Competing Interests: RU, JM No competing interests declared, (© 2020, Ulrich and Miller.)

The Förster resonance energy transfer (FRET) melting assay intends to evaluate the unfolding, denaturation process of DNA secondary structures, and its stabilization using compounds known as DNA binders, some of which are highly specific for G-quadruplex DNAs versus duplex DNAs. First, students determined the melting temperature (T m ) of DNA sequences double labeled with 5'-FAM (fluorescein) and 3'-TAMRA (tetramethylrhodamine) in the absence of DNA binders. Second, they determined the melting temperature of the DNAs in the presence of DNA binders by monitoring fluorescence. After completing this experiment, students understood that this method allows a semiquantitative analysis to test a variety of DNA binders against DNA secondary structures, and it can be used to rapidly identify the most promising drug candidates in the drug development stages at the basic research level., (© 2020 International Union of Biochemistry and Molecular Biology.)

Programming or querying usually presupposes some degree of technical familiarity with the syntax of a language and the peculiarity of the objects it manipulates to produce useful information. The degree of abstractions supported in a language helps lessen the depth of such familiarity needed, and aids in improving access to and usability of these resources. To help biologists concentrate more on their science questions and not on how to compute it, several successful workflow orchestration languages and systems have been proposed. Despite their popularity, significant limitations reduce their usability and limit applicability in novel applications. In this paper, we present a visual language, called VisFlow, for workflow orchestration using heterogeneous and distributed resources. We advance the idea that once resources are minimally described and abstracted, arbitrary workflows can be designed solely using query primitives supported in VisFlow. Its capabilities can be augmented by including computational artifacts in the form of library functions written in R, Python, and Java, or even in SQL and XQuery, making it a truly extensible system. We discuss its salient features and illustrate its capabilities using a substantial set of examples.

We review the nature of interdisciplinary research in relation to One Health, a perspective on human-animal health which would appear to merit close interdisciplinary cooperation to inform public health policy. We discuss the relationship between biological sciences, epidemiology and the social sciences and note that interdisciplinary work demands attention be given to a range of often neglected epistemological and methodological issues. Epidemiologists may sometimes adopt social science techniques as "bolt-ons" 1 to their research without having a complete understanding of how the social sciences work. The paper introduces a range of social science concepts and applies them to the challenges of understanding and practicing participatory and local epidemiology. We consider the problem of co-production of knowledge about One Health and zoonotic diseases in relation to funding structures, working in large international teams and explore some of the often-neglected realities of working across disciplines and cultures. We do this in part by applying the concept of value-chain to the research process., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Recent developments within micro-computed tomography (μCT) imaging have combined to extend our capacity to image tissue in three (3D) and four (4D) dimensions at micron and sub-micron spatial resolutions, opening the way for virtual histology, live cell imaging, subcellular imaging and correlative microscopy. Pivotal to this has been the development of methods to extend the contrast achievable for soft tissue. Herein, we review the new capabilities within the field of life sciences imaging, and consider how future developments in this field could further benefit the life sciences community.

Novel enzymatic microsystems have strong prospects in chemical and biological analysis due to their low consumption of reagents, fast analysis time, easy manipulation and satisfactory portability. Nanomaterials (NMs) provide a favorable platform for integrating enzymes into microsystems with enhanced selectivity and sensitivity. Various NM-enzyme immobilization strategies applied in the fabrication of capillary-based and chip-based enzymatic microsystems are summarized in this manuscript. We focus on highlighting the advantages of employing NM-based enzymatic microsystems for enantioseparation, inhibitor screening, bioreaction and biosensing. Innovative nanocomposites and NM-functionalized monoliths used to construct multienzymatic microsystems are also illustrated. The general development trend identified in this review indicates that the application of NMs has significantly improved enzymatic microsystem performance., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Microscopy techniques are widely used in life sciences to study cells and tissues. Fluorescence microscopy, for example, is a very common method in many laboratories. While reliable and strong fluorescence signals are a clear advantage of this method, the labelling procedure with fluorescent dyes, the availability of required antibodies or the potentially necessary genetic modifications of the studied organism all introduce potential complications. By contrast, confocal Raman microscopy is a label-free and non-destructive imaging technique. In contrast to infrared microscopy, it is easily applicable in aqueous environments. Different microscope setups and combinations allow for the examination of various solid and liquid samples, even in their typical environments. The article demonstrates the analyzing capability of confocal Raman microscopy and correlative techniques through application examples of eukaryotic and prokaryotic cells, and cancerous and normal tissues and shows how confocal Raman microscopy provides valuable information for a more comprehensive understanding of the investigated sample., (Copyright © 2018 WITec Wissenschaftliche Instrumente und Technologie GmbH. Published by Elsevier Masson SAS.. All rights reserved.)

Achieving adequate bioscience learning and assessment in pre registration nursing programs has been problematic for many decades. This has been discussed extensively in national and international health care literature. Despite this, the quantity and quality of bioscience content appears currently in many UK registered nursing programs, to be in a period of decline. Sub optimal bioscience knowledge of registered nurses has been consistently correlated with avoidable morbidity and mortality. An increasing evidence base indicates that a higher level of educated registered nurse, leads to improved health outcomes. It is therefore clear that continuing to fail to address the bioscience problem in nursing education has the potential to incur considerable adverse impact on the UK populations' health. The recent publication of new Nursing and Midwifery Council (NMC) standards of proficiency for registered nurses, and standards for pre-registration nursing programs require nurse education providers across the UK, to write new curriculum. The purpose of this discussion paper is to present the case for enhanced bioscience content within these., (Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.)

Visiting the Bio Imaging Search Engine (BISE) (Bio, BISE, Engine, http://biii.eu/, Imaging, Search) website at the time of writing this article, almost 1200 open source assets (components, workflows, collections) were found. This overwhelming range of offer difficults the fact of making a reasonable choice, especially to newcomers. In the following chapter, we briefly sketch the advantages of the open source software (OSS) particularly used for image analysis in the field of life sciences. We introduce both the general OSS idea as well as some programs used for image analysis. Even more, we outline the history of ImageJ as it has served as a role model for the development of more recent software packages. We focus on the programs that are, to our knowledge, the most relevant and widely used in the field of light microscopy, as well as the most commonly used within our facility. In addition, we briefly discuss recent efforts and approaches aimed to share and compare algorithms and introduce software and data sharing good practices as a promising strategy to facilitate reproducibility, software understanding, and optimal software choice for a given scientific problem in the future.

We develop a model describing how false paradigms may persist, hindering scientific progress. The model features two paradigms, one describing reality better than the other. Tenured scientists display homophily: They favor tenure candidates who adhere to their paradigm. As in statistics, power is the probability (absent any bias) of denying tenure to scientists adhering to the false paradigm. The model shows that because of homophily, when power is low, the false paradigm may prevail. Then, only an increase in power can ignite convergence to the true paradigm. Historical case studies suggest that low power comes either from lack of empirical evidence or from reluctance to base tenure decisions on available evidence., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Affinity capillary electrophoresis (ACE) analyzes noncovalent interactions between ligands and analytes based on changes in their electrophoretic mobility. This technique has been widely used to investigate various biomolecules, mainly proteins, polysaccharides and hormones. ACE is becoming a technique of choice to validate high throughput screening results, since it is very predictively working in realistic and relevant media, e.g. in body fluids. It is highly recommended to incorporate ACE as a powerful analytical tool to properly prepare animal testing and preclinical studies. The interacting molecules can be found free in solution or can be immobilized to a solid support. Thus, ACE is classified in two modes, free solution ACE and immobilized ACE. Every ACE mode has advantages and disadvantages. Each can be used for a variety of applications. This review covers literature of scopus and SciFinder data base in the period from 2016 until beginning 2018, including the keywords "affinity capillary electrophoresis", "immunoaffinity capillary electrophoresis", "immunoassay capillary electrophoresis" and "immunosorbent capillary electrophoresis". More than 200 articles have been found and 112 have been selected and thoroughly discussed. During this period, the data processing and the underlying calculations in mobility shift ACE (ms ACE), frontal analysis ACE (FA ACE) and plug-plug kinetic capillary electrophoresis (ppKCE) as mostly applied free solution techniques have substantially improved. The range of applications in diverse free solution and immobilized ACE techniques has been considerably broadened., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Natural forming clay halloysite is an emerging nanomaterial carrier for sustained drug delivery. These 50 nm diameter aluminosilicate tubes, with inner - alumina and outer - silica surface layers, can be loaded with 10-30 wt% of drug molecules, DNA and enzymes. The opposite charge of the inner and outer halloysite surface allow for selective drug adsorption inside or outside the clay nanotubes. The drug loaded halloysite enhanced the zeta potential of minus 50-60 mV allowing for stable aqueous nanocolloids. Halloysite nanoformulations provide an extended 10-20 h release profile, and may be functionalized (e.g., clogging tubes' end with polymers extending release time to 1-2 weeks or allowing for triggered release), which renders these clay nanostructures as promising controlled delivery systems. Recent studies demonstrate the potential of abundantly available halloysite clay nanotubes for life science applications, from drug delivery via oral or topical administration, to tissue scaffolds and regenerative medicine, while assessing their cellular internalization, stability, biosafety and biocompatibility are featured. The benefits and limitations of halloysite clay nanotubes are discussed, as well as the directions for future developments., (Copyright © 2018 Elsevier B.V. All rights reserved.)

This special issue covers a wide range of topics in computational biology, such as database construction, sequence analysis and function prediction with machine learning methods, disease-related diagnosis, drug-target and drug discovery, and electronic health record system construction.

Deep Learning has boosted artificial intelligence over the past 5 years and is seen now as one of the major technological innovation areas, predicted to replace lots of repetitive, but complex tasks of human labor within the next decade. It is also expected to be 'game changing' for research activities in pharma and life sciences, where large sets of similar yet complex data samples are systematically analyzed. Deep learning is currently conquering formerly expert domains especially in areas requiring perception, previously not amenable to standard machine learning. A typical example is the automated analysis of images which are typically produced en-masse in many domains, e. g., in high-content screening or digital pathology. Deep learning enables to create competitive applications in so-far defined core domains of 'human intelligence'. Applications of artificial intelligence have been enabled in recent years by (i) the massive availability of data samples, collected in pharma driven drug programs (='big data') as well as (ii) deep learning algorithmic advancements and (iii) increase in compute power. Such applications are based on software frameworks with specific strengths and weaknesses. Here, we introduce typical applications and underlying frameworks for deep learning with a set of practical criteria for developing production ready solutions in life science and pharma research. Based on our own experience in successfully developing deep learning applications we provide suggestions and a baseline for selecting the most suited frameworks for a future-proof and cost-effective development., Competing Interests: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Daniel Siegismund, Stephan Heyse and Stephan Steigele are employed by Genedata AG., (© Georg Thieme Verlag KG Stuttgart · New York.)

Background: Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences., Results: The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat., Conclusions: Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases.

A common understanding of expectations and requirements is critical for boosting research-driven business opportunities in open innovation (OI) settings. Transparent communication requires common definitions and standards for OI to align the expectations of both parties. Here, we suggest a five-level classification system for OI models, reflecting the degree of openness. The aim of this classification system is to reduce contract negotiation complexity and times between two parties looking to engage in OI. Systematizing definitions and contractual terms for OI in the life sciences helps to reduce entry barriers and boosts collaborative value generation. By providing a contractual framework with predefined rules, science will be allowed to move more freely, thus maximizing the potential of OI., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Meta-analysis is the quantitative, scientific synthesis of research results. Since the term and modern approaches to research synthesis were first introduced in the 1970s, meta-analysis has had a revolutionary effect in many scientific fields, helping to establish evidence-based practice and to resolve seemingly contradictory research outcomes. At the same time, its implementation has engendered criticism and controversy, in some cases general and others specific to particular disciplines. Here we take the opportunity provided by the recent fortieth anniversary of meta-analysis to reflect on the accomplishments, limitations, recent advances and directions for future developments in the field of research synthesis.

Background: Nursing students find bioscience subjects challenging. Bioscience exams pose particular concerns for these students, which may lead to students adopting a surface-approach to learning., Objectives: To promote student collective understanding of bioscience, improve their confidence for the final exam, and improve deeper understanding of bioscience., Design: In order to address exam anxiety, and improve student understanding of content, this student engagement project involved nursing students collaborating in small groups to develop multiple-choice questions and answers, which became available to the entire student cohort., Settings: This study was conducted at two campuses of an Australian university, within a first year bioscience subject as part of the undergraduate nursing programme., Participants: All students enrolled in the subject were encouraged to attend face-to-face workshops, and collaborate in revision question writing. Online anonymous questionnaires were used to invite student feedback on this initiative; 79 respondents completed this feedback., Methods: Students collaborated in groups to write revision questions as part of in-class activities. These questions were made available on the student online learning site for revision. An online feedback survey was deployed at the conclusion of all workshops for this subject, with questions rated using a Likert scale., Results: Participants indicated that they enjoyed the opportunity to collaborate in this activity, and almost all of these respondents used these questions in their exam preparation. There was strong agreement that this activity improved their confidence for the final exam. Importantly, almost two-thirds of respondents agreed that writing questions improved their understanding of content, and assisted in their active reflection of content., Conclusions: Overall, this initiative revealed various potential benefits for the students, including promoting bioscience understanding and confidence. This may improve their long-term understanding of bioscience for nursing practice, as registered nurses' bioscience knowledge can impact on patient outcomes., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

The impact of light-sheet fluorescence microscopy (LSFM) is visible in fields as diverse as developmental and cell biology, anatomical science, biophysics and neuroscience. Although adoption among biologists has been steady, LSFM has not displaced more traditional imaging methods despite its often-superior performance. One reason for this is that the field has largely conformed to a do-it-yourself ethic, although the challenges of big image data cannot be overstated. With the most powerful implementations of LSFM available to only a few groups worldwide, the scope of this technique is unnecessarily limited. Here we elucidate the key developments and define a simple set of underlying principles governing LSFM. In doing so, we aim to clarify the decisions to be made for those who wish to develop and use bespoke light-sheet systems and to assist in identifying the best approaches to apply this powerful technique to myriad biological questions.

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A biorepository of human samples is essential to support the research of life science. Lymphoblastoid B cell line (LCL), which is easy to be prepared and can reproduce indefinitely, is a convenient form of sample preservation. LCLs are established from human B cells transformed by Epstein-Barr virus (EBV). Chinese National Immortalized Cell Bank has preserved human LCLs from different ethnic groups in China. As there are many studies on the nature of LCLs and public available resources with genome-wide data for LCLs, they have been widely applied in genetics, immunology, pharmacogenetics/genomics, regenerative medicine, cancer pathogenesis and immunotherapy, screening and generation of fully human neutralizing monoclonal antibodies and study on EBV pathogenesis. Here, we review the characteristics of LCLs and their contributions to scientific research, and introduce preserved samples in Chinese National Immortalized Cell Bank to the scientific community. We hope this bank can support more areas in the scientific research.

Background: Synchrotron radiation (SR) sources provide diverse X-ray methods for the investigation of structure-function relationships in biological macromolecules., Scope of Review: Recent developments in SR sources and in the X-ray tools they offer for life sciences are reviewed. Specifically, advances in macromolecular crystallography, small angle X-ray solution scattering, X-ray absorption and fluorescence spectroscopy, and imaging are discussed with examples., Major Conclusions: SR sources offer a range of X-ray techniques that can be used in a complementary fashion in studies of biological systems at a wide range of resolutions from atomic to cellular scale. Emerging applications of X-ray techniques include the characterization of disordered proteins, noncrystalline and nonequilibrium systems, elemental imaging of tissues, cells and organs, and detection of time-resolved changes in molecular structures., General Significance: X-ray techniques are in the center of hybrid approaches that are used to gain insight into complex problems relating to biomolecular mechanisms, disease and possible therapeutic solutions. This article is part of a Special Issue entitled "Science for Life". Guest Editors: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo., (Copyright © 2016 Elsevier B.V. All rights reserved.)