Picture a pasture open to all (...) As a rational being, each herdsman seeks to maximize his gain. Explicitly or implicitly, more or less consciously, he asks, "What is the utility to me of adding one more animal to the herd?" This utility has one negative and one positive component. 1) The positive component is a function of the increment of one animal. Since the herdsman receives all the proceeds from the sale of the additional animal, the positive utility is nearly +1. 2) The negative component is a function of the additional overgrazing created by one more animal. Since, however, the effects of overgrazing are shared by all the herdsmen, the negative utility for any particular decision-making herdsman is only a fraction of -1. Adding together the component partial utilities, the rational herdsman concludes that the only sensible course for him to pursue is to add another animal to the herd. And another; and another...

CRISPR-based technologies have emerged as powerful tools to alter genomes and mark chromosomal loci, but an inexpensive method for generating large numbers of RNA guides for whole genome screening and labeling is lacking. Using a method that permits library construction from any source of DNA, we generated guide libraries that label repetitive loci or a single chromosomal locus in Xenopus egg extracts and show that a complex library can target the E. coli genome at high frequency.

For many families, young children's engagement with screen-based technology is an ongoing concern in terms of physical, social and cognitive development. They are uneasy with the difficulty children have disengaging from screens and concerned that this behavior is obsessive or a sign of addiction. However, technology is recognized as having a "rightful role" in early childhood contexts. This scoping paper reports on a review of literature relating to digital play for children aged birth to five years, with the aim of further understanding digital wellbeing. Csikszentmihalyi's flow theory serves as a theoretical framework for understanding why many young children enjoy digital play and become deeply engaged, with a disconnect between how young children and adults perceive digital play. Concerns about children's deep immersion with digital play are interrogated to understand the connections with perceived addictive traits. The review highlights the critical importance of supporting children's agency and digital citizenship skills from a young age, including the ability to critique content, balance screen-time with non-screen time and to develop self-control and self-regulation as a means to promote long-term positive outcomes for children in their digital lifeworlds and beyond.

The ability to perturb individual genes in genome-wide experiments has been instrumental in unraveling cellular and disease properties. Here we introduce, describe the assembly, and demonstrate the use of comprehensive and versatile transcription activator-like effector (TALE) libraries. As a proof of principle, we built an 11-mer library that covers all possible combinations of the nucleotides that determine the TALE-DNA binding specificity. We demonstrate the versatility of the methodology by constructing a constraint library, customized to bind to a known p53 motif. To verify the functionality in assays, we applied the 11-mer library in yeast-one-hybrid screens to discover TALEs that activate human SCN9A and miR-34b respectively. Additionally, we performed a genome-wide screen using the complete 11-mer library to confirm known genes that confer cycloheximide resistance in yeast. Considering the highly modular nature of TALEs and the versatility and ease of constructing these libraries we envision broad implications for high-throughput genomic assays.

Glycan/lectin interactions drive a wide range of recognition and signal transduction processes within nature. However, their measurement is complicated or limited by the analytical tools available. Most technologies require fluorescently labelled proteins (e.g. microarrays) or expensive infrastructure (such as surface plasmon resonance). This also limits their application in biosensing, especially for low-resource settings, where detection of pathogens based on glycan binding could speed up diagnosis. Here we employ a library-oriented approach to immobilise a range of monosaccharides onto polymer-stabilised gold nanoparticles to enable rapid and high-throughput evaluation of their binding specificities with a panel of lectins. The red to blue colour shift upon gold nanoparticle aggregation is used as the output, removing the need for labelled protein, enabling compatibility with 96-well microplates. Furthermore, we demonstrate the use of a flatbed scanner (or digital camera) to extract biophysical data, ensuring that only minimal resources are required. Finally, linear discriminant analysis is employed to demonstrate how the glyconanoparticles can be applied as a multiplexed biosensor capable of identifying pathogenic lectins without the need for any infrastructure and overcoming some of the issues of lectin promiscuity.

Data-independent acquisition-mass spectrometry (DIA-MS) is the method of choice for deep, consistent, and accurate single-shot profiling in bottom-up proteomics. While classic workflows for targeted quantification from DIA-MS data require auxiliary data-dependent acquisition (DDA) MS analysis of subject samples to derive prior-knowledge spectral libraries, library-free approaches based on in silico prediction promise deep DIA-MS profiling with reduced experimental effort and cost. Coverage and sensitivity in such analyses are however limited, in part, by the large library size and persistent deviations from the experimental data. We present MSLibrarian, a new workflow and tool to obtain optimized predicted spectral libraries by the integrated usage of spectrum-centric DIA data interpretation via the DIA-Umpire approach to inform and calibrate the in silico predicted library and analysis approach. Predicted-vs-observed comparisons enabled optimization of intensity prediction parameters, calibration of retention time prediction for deviating chromatographic setups, and optimization of the library scope and sample representativeness. Benchmarking via a dedicated ground-truth-embedded experiment of species-mixed proteins and quantitative ratio-validation confirmed gains of up to 13% on peptide and 8% on protein level at equivalent FDR control and validation criteria. MSLibrarian is made available as an open-source R software package, including step-by-step user instructions, at https://github.com/MarcIsak/MSLibrarian.

Traditional small-molecule drug discovery is a time-consuming and costly endeavor. High-throughput chemical screening can only assess a tiny fraction of drug-like chemical space. The strong predictive power of modern machine-learning methods for virtual chemical screening enables training models on known active and inactive compounds and extrapolating to much larger chemical libraries. However, there has been limited experimental validation of these methods in practical applications on large commercially available or synthesize-on-demand chemical libraries. Through a prospective evaluation with the bacterial protein-protein interaction PriA-SSB, we demonstrate that ligand-based virtual screening can identify many active compounds in large commercial libraries. We use cross-validation to compare different types of supervised learning models and select a random forest (RF) classifier as the best model for this target. When predicting the activity of more than 8 million compounds from Aldrich Market Select, the RF substantially outperforms a naïve baseline based on chemical structure similarity. 48% of the RF's 701 selected compounds are active. The RF model easily scales to score one billion compounds from the synthesize-on-demand Enamine REAL database. We tested 68 chemically diverse top predictions from Enamine REAL and observed 31 hits (46%), including one with an IC50 value of 1.3 μM.

A rapid and effective method to identify disease-specific antibodies from clinical patients is important for understanding autoimmune diseases and for the development of effective disease therapies. In neuromyelitis optica (NMO), the identification of antibodies targeting the aquaporin-4 (AQP4) membrane protein traditionally involves the labor-intensive and time-consuming process of single B-cell sorting, followed by antibody cloning, expression, purification, and analysis for anti-AQP4 activity. To accelerate patient-specific antibody discovery, we compared two unique approaches for screening anti-AQP4 antibodies from yeast antibody surface display libraries. Our first approach, cell-based biopanning, has strong advantages for its cell-based display of native membrane-bound AQP4 antigens and is inexpensive and simple to perform. Our second approach, FACS screening using solubilized AQP4 antigens, permits real-time population analysis and precision sorting for specific antibody binding parameters. We found that both cell-based biopanning and FACS screening were effective for the enrichment of AQP4-binding clones. These screening techniques will enable library-scale functional interrogation of large natively paired antibody libraries for comprehensive analysis of anti-AQP4 antibodies in clinical samples and for robust therapeutic discovery campaigns.

To explore if consumer interest in digital health products (DHPs), changed following the COVID-19 pandemic and the lockdown measures that ensued.

Next-generation sequencing techniques empower selection of ligands from phage-display libraries because they can detect low abundant clones and quantify changes in the copy numbers of clones without excessive selection rounds. Identification of errors in deep sequencing data is the most critical step in this process because these techniques have error rates >1%. Mechanisms that yield errors in Illumina and other techniques have been proposed, but no reports to date describe error analysis in phage libraries. Our paper focuses on error analysis of 7-mer peptide libraries sequenced by Illumina method. Low theoretical complexity of this phage library, as compared to complexity of long genetic reads and genomes, allowed us to describe this library using convenient linear vector and operator framework. We describe a phage library as N × 1 frequency vector n = ||ni||, where ni is the copy number of the ith sequence and N is the theoretical diversity, that is, the total number of all possible sequences. Any manipulation to the library is an operator acting on n. Selection, amplification, or sequencing could be described as a product of a N × N matrix and a stochastic sampling operator (Sa). The latter is a random diagonal matrix that describes sampling of a library. In this paper, we focus on the properties of Sa and use them to define the sequencing operator (Seq). Sequencing without any bias and errors is Seq = Sa IN, where IN is a N × N unity matrix. Any bias in sequencing changes IN to a nonunity matrix. We identified a diagonal censorship matrix (CEN), which describes elimination or statistically significant downsampling, of specific reads during the sequencing process.

Creating a cDNA library for deep mRNA sequencing (mRNAseq) is generally done by random priming, creating multiple sequencing fragments along each transcript. A 3'-end-focused library approach cannot detect differential splicing, but has potentially higher throughput at a lower cost, along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) that correct PCR bias. Here, we compare an implementation of such a 3'-digital gene expression (3'-DGE) approach with "conventional" random primed mRNAseq. Given our particular datasets on cultured human cardiomyocyte cell lines, we find that, while conventional mRNAseq detects ~15% more genes and needs ~500,000 fewer reads per sample for equivalent statistical power, the resulting differentially expressed genes, biological conclusions, and gene signatures are highly concordant between two techniques. We also find good quantitative agreement at the level of individual genes between two techniques for both read counts and fold changes between given conditions. We conclude that, for high-throughput applications, the potential cost savings associated with 3'-DGE approach are likely a reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable many larger scale studies focusing on not only differential expression analysis, but also quantitative transcriptome profiling.

Digital PCR is an exciting new field for molecular analysis, allowing unprecedented precision in the quantification of nucleic acids, as well as the fine discrimination of rare molecular events in complex samples. We here present a novel technology for digital PCR, Crystal Digital PCR™, which relies on the use of a single chip to partition samples into 2D droplet arrays, which are then subjected to thermal cycling and finally read using a three-color fluorescence scanning device. This novel technology thus allows three-color multiplexing, which entails a different approach to data analysis. In the present publication, we present this innovative workflow, which is both fast and user-friendly, and discuss associated data analysis issue, such as fluorescence spillover compensation and data representation. Lastly, we also present proof-of-concept of this three-color detection system, using a quadriplex assay for the detection of EGFR mutations L858R, L861Q and T790M.

Quantification of massively parallel sequencing libraries is important for acquisition of monoclonal beads or clusters prior to clonal amplification and to avoid large variations in library coverage when multiple samples are included in one sequencing analysis. No gold standard for quantification of libraries exists. We assessed eight methods of quantification of libraries by quantifying 54 amplicon, six capture, and six shotgun fragment libraries. Chemically synthesized double-stranded DNA was also quantified. Light spectrophotometry, i.e. NanoDrop, was found to give the highest concentration estimates followed by Qubit and electrophoresis-based instruments (Bioanalyzer, TapeStation, GX Touch, and Fragment Analyzer), while SYBR Green and TaqMan based qPCR assays gave the lowest estimates. qPCR gave more accurate predictions of sequencing coverage than Qubit and TapeStation did. Costs, time-consumption, workflow simplicity, and ability to quantify multiple samples are discussed. Technical specifications, advantages, and disadvantages of the various methods are pointed out.

The purposes of this survey were to determine the nature and extent of collaboration between health sciences libraries and their information technology (IT) departments, to identify strengths and issues connected to this relationship, and to provide examples demonstrating exceptional collaborative success.

Big bibliographic datasets hold promise for revolutionizing the scientific enterprise when combined with state-of-the-science computational capabilities. Yet, hosting proprietary and open big bibliographic datasets poses significant difficulties for libraries, both large and small. Libraries face significant barriers to hosting such assets, including cost and expertise, which has limited their ability to provide stewardship for big datasets, and thus has hampered researchers' access to them. What is needed is a solution to address the libraries' and researchers' joint needs. This article outlines the theoretical framework that underpins the Collaborative Archive and Data Research Environment project. We recommend a shared cloud-based infrastructure to address this need built on five pillars: 1) Community-a community of libraries and industry partners who support and maintain the platform and a community of researchers who use it; 2) Access-the sharing platform should be accessible and affordable to both proprietary data customers and the general public; 3) Data-Centric-the platform is optimized for efficient and high-quality bibliographic data services, satisfying diverse data needs; 4) Reproducibility-the platform should be designed to foster and encourage reproducible research; 5) Empowerment-the platform should empower researchers to perform big data analytics on the hosted datasets. In this article, we describe the many facets of the problem faced by American academic libraries and researchers wanting to work with big datasets. We propose a practical solution based on the five pillars: The Collaborative Archive and Data Research Environment. Finally, we address potential barriers to implementing this solution and strategies for overcoming them.

The widening gap between innovations in the medical field and the dissemination of such information to doctors may affect the quality of care. Offline computer-based digital education (OCDE) may be a potential solution to overcoming the geographical, financial, and temporal obstacles faced by doctors.

This study assessed the book collection of five selected medical libraries in the Philippines, based on Doodys' Essential Purchase List for basic sciences and clinical medicine, to compare the match and non-match titles among libraries, to determine the strong and weak disciplines of each library, and to explore the factors that contributed to the percentage of match and non-match titles.

Circular RNA (circRNA) is a noncoding RNA class with important implications for gene expression regulation, mostly by interaction with other RNA species or RNA-binding proteins. While the commonly applied short-read Illumina RNA-sequencing techniques can be used to detect circRNAs, their full sequence is not revealed. However, the complete sequence information is needed to analyze potential interactions and thus the mechanism of action of circRNAs. Here, we present an improved protocol to enrich and sequence full-length circRNAs by using the Oxford Nanopore long-read sequencing platform. The protocol involves an enrichment of lowly abundant circRNAs by exonuclease treatment and negative selection of linear RNAs. Then, a cDNA library is created and amplified by PCR. This protocol provides enough material for several sequencing runs. The library is used as input for ligation-based sequencing together with native barcoding. Stringent quality control of the libraries is ensured by a combination of Qubit, Fragment Analyzer and qRT-PCR. Multiplexing of up to 4 libraries yields in total more than 1-2 Million reads per library, of which 1-2% are circRNA-specific reads with >99% of them full-length. The protocol works well with human cancer cell lines. We further provide suggestions for the bioinformatic analysis of the created data, as well as the limitations of our approach together with recommendations for troubleshooting and interpretation. Taken together, this protocol enables reliable full-length analysis of circRNAs, a noncoding RNA type involved in a growing number of physiologic and pathologic conditions. Metadata Associated content. https://dx.doi.org/10.17504/protocols.io.rm7vzy8r4lx1/v2.

Recently, there has been a co-evolution of mammalian libraries and diverse microfluidic approaches for therapeutic antibody hit discovery. Mammalian libraries enable the preservation of full immune repertoires, produce hit candidates in final format and facilitate broad combinatorial bispecific antibody screening, while several available microfluidic methodologies offer opportunities for rapid high-content screens. Here, we report proof-of-concept studies exploring the potential of combining microfluidic technologies with mammalian libraries for antibody discovery. First, antibody secretion, target co-expression and integration of appropriate reporter cell lines enabled the selection of in-trans acting agonistic bispecific antibodies. Second, a functional screen for internalization was established and comparison of autocrine versus co-encapsulation setups highlighted the advantages of an autocrine one cell approach. Third, synchronization of antibody-secreting cells prior to microfluidic screens reduced assay variability. Furthermore, a display to secretion switchable system was developed and applied for pre-enrichment of antibody clones with high manufacturability in conjunction with subsequent screening for functional properties. These case studies demonstrate the system's feasibility and may serve as basis for further development of integrated workflows combining manufacturability sorting and functional screens for the identification of optimal therapeutic antibody candidates.

Engineering cell factories for producing biofuels and pharmaceuticals has spurred great interests to develop rapid and efficient synthetic biology tools customized for modular pathway engineering. Along the way, combinatorial gene expression control through modification of regulatory element offered tremendous opportunity for fine-tuning gene expression and generating digital-like genetic circuits. In this report, we present an efficient evolutionary approach to build a range of regulatory control elements. The reported method allows for rapid construction of promoter, 5'UTR, terminator and trans-activating RNA libraries. Synthetic overlapping oligos with high portion of degenerate nucleotides flanking the regulatory element could be efficiently assembled to a vector expressing fluorescence reporter. This approach combines high mutation rate of the synthetic DNA with the high assembly efficiency of Gibson Mix. Our constructed library demonstrates broad range of transcriptional or translational gene expression dynamics. Specifically, both the promoter library and 5'UTR library exhibits gene expression dynamics spanning across three order of magnitude. The terminator library and trans-activating RNA library displays relatively narrowed gene expression pattern. The reported study provides a versatile toolbox for rapidly constructing a large family of prokaryotic regulatory elements. These libraries also facilitate the implementation of combinatorial pathway engineering principles and the engineering of more efficient microbial cell factory for various biomanufacturing applications.