Integration Toolkit Research Articles

MOTH: Memory-Efficient On-the-Fly Tiling of Histological Image Annotations Using QuPath.

The emerging usage of digitalized histopathological images is leading to a novel possibility for data analysis. With the help of artificial intelligence algorithms, it is now possible to detect certain structures and morphological features on whole slide images automatically. This enables algorithms to count, measure, or evaluate those areas when trained properly. To achieve suitable training, datasets must be annotated and curated by users in programs like QuPath. The extraction of this data for artificial intelligence algorithms is still rather tedious and needs to be saved on a local hard drive. We developed a toolkit for integration into existing pipelines and tools, like U-net, for the on-the-fly extraction of annotation tiles from existing QuPath projects. The tiles can be directly used as input for artificial intelligence algorithms, and the results are directly transferred back to QuPath for visual inspection. With the toolkit, we created a convenient way to incorporate QuPath into existing AI workflows.

Splicekit: an integrative toolkit for splicing analysis from short-read RNA-seq.

Analysis of alternative splicing using short-read RNA-seq data is a complex process that involves several steps: alignment of reads to the reference genome, identification of alternatively spliced features, motif discovery, analysis of RNA-protein binding near donor and acceptor splice sites, and exploratory data visualization. To the best of our knowledge, there is currently no integrative open-source software dedicated to this task. Here, we introduce splicekit, a Python package that provides and integrates a set of existing and novel splicing analysis tools for conducting splicing analysis. The software splicekit is open-source and available at Github (https://github.com/bedapub/splicekit) and via the Python Package Index.

Chroma: A MATLAB package and open-source platform for biomarker data processing and automatic index calculations

The molecular ratio indices of biological markers (biomarkers), such as the Carbon Preference Index (CPI) or Paq, are frequently used as proxies for paleoclimatic and palaeoecological conditions. These indices are regularly extracted from the relative abundances of target molecules detected by a Gas Chromatography analyzer with a Flame Ionization Detector (GC-FID). Despite their use in biogeochemical studies for over a half-century, it remains common procedure to quantify the abundance of individual compounds by manual integration of chromatogram peaks (i.e., interpret baselines visually and characterize peaks by hand), which is time consuming and can lead to inconsistent results. Here, we introduce a new MATLAB package (Chroma) for the automatic detection and integration of standard-referenced biomarker abundances and the calculation of a variety of established hydrocarbon indices commonly reported in the published literature. The algorithm identifies the detector response timing of specific target peaks in a sample chromatogram by cross-referencing to a standard (e.g., Mix-A6, Schimmelmann, Indiana University Bloomington), then calculates the peak areas for an approximation of molecular abundance. This new toolkit for automatic and rapid integration of GC-acquired data provides a consistent and reproducible approach for the calculation of hydrocarbon indices and offers a standardized inter-laboratory platform for data comparisons and exchange. We validate the utility of the Chroma package with the chromatograms of plant wax n-alkanes, a widely used proxy for ecology and hydrology, from six stratigraphic sections in the Tibetan Plateau. Chroma is an effective tool for efficient data processing and will continuously evolve to accommodate extended uses in related areas of biomarker research beyond n-alkanes.

Exploring perceptions of and attitudes towards tanning with school children, parents/carers and educators in Wales: A mixed methods study protocol for the SunChat study.

Skin cancer comprises half of all cancers in England and Wales. Most skin cancers can be prevented with safer sun exposure. As over exposure as a child can greatly increase future skin cancer risk, early and accessible sun safety education and promotion of sun safe behaviours is critical. Scientists agree there is no such thing as a 'safe tan', yet the public, including children, often have positive perceptions of tanned skin. To protect against future skin cancer, it is important to understand and address these misconceptions. The Curriculum for Wales with its area for Health and Well-being, and autonomy for schools in designing curriculum content, presents an ideal way to facilitate this exploration. Gather data regarding perceptions towards tanning to explore the perceived effects of a tan on health.Inform the development and testing of an educational toolkit for integration within the Curriculum for Wales to encourage positive health behaviours and attitudes of school children towards tanning and sun exposure. SunChat is a mixed methods exploratory study comprising three work streams: Workshops with school children to understand their perceptions on tanning.An online multiple-choice survey with parents/carers to understand perceptions, attitudes and behaviours towards tanning both for themselves and their children.An informal focus group with primary school educators to explore challenges in engaging with the school community around the Health and Well-being Area in the Curriculum for Wales. To date, there has been no work in Wales exploring children's, parents/carers', and educators' perceptions of tanning and how healthier attitudes can be encouraged. This study will engage with participants to scope current perceptions on tanning and the perceived effects tanning has on health. Findings will feed into future toolkit and curriculum development for health in schools in Wales and beyond.

Integration using Schwinger Parametrization

This paper draws attention to an underappreciated method for evaluating certain types of definite integrals. The method relies on a substitution in the Eulerian integral for the Legendre gamma function, and has become known in some quarters as a Schwinger parametrization. We present some examples to illustrate the utility of this technique in the hope that by doing so we may convince the reader that it makes a valuable addition to one’s integration toolkit.

Multiplex Marker-Less Genome Integration in Pichia pastoris Using CRISPR/Cas9.

Pichia pastoris is known for its excellent protein expression ability. As an industrial methyl nutritional yeast, it can effectively utilize methanol as the sole carbon source, serving as a potential platform for C1 biotransformation. Unfortunately, the lack of synthetic biology tools in P. pastoris limits its broad applications, particularly when multigene pathways should be manipulated. Here, the CRISPR/Cas9 system is established to efficiently integrate multiple heterologous genes to construct P. pastoris cell factories. In this protocol, with the 2,3-butanediol (BDO) biosynthetic pathway as a representative example, the procedures to construct P. pastoris cell factories are detailed using the established CRISPR-based multiplex genome integration toolkit, including donor plasmid construction, competent cell preparation and transformation, and transformant verification. The application of the CRISPR toolkit is demonstrated by the construction of engineered P. pastoris for converting methanol to BDO. This lays the foundation for the construction of P. pastoris cell factories harboring multi-gene biosynthetic pathways for the production of high-value compounds.

Expansion of YALIcloneHR toolkit for Yarrowia lipolytica combined with Golden Gate and CRISPR technology.

Metabolic Engineering of yeast is a critical approach to improving the production capacity of cell factories. To obtain genetically stable recombinant strains, the exogenous DNA is preferred to be integrated into the genome. Previously, we developed a Golden Gate toolkit YALIcloneNHEJ, which could be used as an efficient modular cloning toolkit for the random integration of multigene pathways through the innate non-homologous end-joining repair mechanisms of Yarrowia lipolytica. We expanded the toolkit by designing additional building blocks of homologous arms and using CRISPR technology. The reconstructed toolkit was thus entitled YALIcloneHR and designed for gene-specific knockout and integration. To verify the effectiveness of the system, the gene PEX10 was selected as the target for the knockout. This system was subsequently applied for the arachidonic acid production, and the reconstructed strain can accumulate 4.8% of arachidonic acid. The toolkit will expand gene editing technology in Y. lipolytica, which would help produce other chemicals derived from acetyl-CoA in the future.

Advanced Practitioners as Agents of Change: Leveraging Quality Improvement to Improve Practice

Scientific innovation in hematology and oncology is constant and increasingly complex, requiring individual clinicians and institutions to effectively integrate standards of care across the diverse hematology and oncology landscape into practice. Effective integration of evolving diagnostics, risk models, new therapeutics and novel treatment strategies, and practice regulation requirements requires ongoing practice improvement efforts and an infrastructure to implement change. Advanced practitioners (APs) are poised to serve as agents of change based on their clinical presence, clinical expertise, familiarity with critical members of the interdisciplinary team, communication skills, and ability to envision and actualize optimized workflows. Through practice analysis, workflow optimization, role delineation, and effective utilization and tailoring of documentation in the electronic health record, APs can lead implementation strategies to improve patient outcomes. In this article, we will review the essential role APs play as agents of change to implement best practice models using quality improvement (QI) processes. The principles of QI as a strategy for practice improvement, including strategies and tools for successful practice analysis, workflow optimization, outcome analysis, implementation, and sustainability of change, will be reviewed. Proposed elements of a QI and practice integration toolkit for APs and a series of QI exemplars, including an Advanced Practitioner Society for Hematology and Oncology (APSHO)-led QI initiative and AP-led QI initiatives, will be summarized.

Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning.

Differentiating cancer subtypes is crucial to guide personalized treatment and improve the prognosis for patients. Integrating multi-omics data can offer a comprehensive landscape of cancer biological process and provide promising ways for cancer diagnosis and treatment. Taking the heterogeneity of different omics data types into account, we propose a hierarchical multi-kernel learning (hMKL) approach, a novel cancer molecular subtyping method to identify cancer subtypes by adopting a two-stage kernel learning strategy. In stage 1, we obtain a composite kernel borrowing the cancer integration via multi-kernel learning (CIMLR) idea by optimizing the kernel parameters for individual omics data type. In stage 2, we obtain a final fused kernel through a weighted linear combination of individual kernels learned from stage 1 using an unsupervised multiple kernel learning method. Based on the final fusion kernel, k-means clustering is applied to identify cancer subtypes. Simulation studies show that hMKL outperforms the one-stage CIMLR method when there is data heterogeneity. hMKL can estimate the number of clusters correctly, which is the key challenge in subtyping. Application to two real data sets shows that hMKL identified meaningful subtypes and key cancer-associated biomarkers. The proposed method provides a novel toolkit for heterogeneous multi-omics data integration and cancer subtypes identification.

Electronic prescribing systems in hospitals to improve medication safety: a multimethods research programme

Electronic prescribing systems in hospitals to improve medication safety: a multimethods research programme

Fractional order modelling and robust multi-model intelligent controllers’ synthesis for ACP1000 nuclear power plant

In this research work, a third generation Pressurized Water Reactor (PWR) type Nuclear Power Plant (NPP) of 1100 MWe rating called Advanced Chinese PWR (ACP1000) NPP is adopted. The research and development work is mainly encompassed of addition of third steam generator loop, hybrid programming platforms, fractional order modular modelling and intelligent controllers. The ACP1000 NPP is comprised of primary loop, secondary loop and balance of plant (BOP). The ACP1000 nonlinear dynamics is precisely modelled with greater efficiency using fractional order differential equations. The entire plant is modelled into eighteen modules in a fractional order framework in Visual Basic (VB) environment. The eighteen modules are governed by nine controllers. Controllers are configured in a fashion of an adaptive neuro-fuzzy inference system (ANFIS). An innovative multi input single output (MISO) ANFIS virtual instrument (VI) is designed for training and configuring controllers in LabVIEW. The developed MISO ANFIS VI in combination is implemented for multi-input multi output (MIMO) ANFIS controllers in parallel computing framework. The variable transfer between fractional order multi- modular framework in VB (FO- MMF-VB) and robust intelligent ANFIS controllers in LabVIEW (RI-ANFIS-LV) is established in client server configuration and system exec VI for calling external code in VB. This hybrid programming framework of Visual Basic and LabVIEW is actually a development of LabVIEW Visual Basic Integration (LabVb) Toolkit used to evaluate the closed loop transient performance of ACP1000 nuclear power plant. Various parameters are simulated for dynamic transient simulations under load manoeuvring from 100% power to 50% power. The results are analysed and validated against benchmark design data and Preliminary Safety Analysis Report (PSAR). All the results are within the protection systems design limits under normal operating conditions.

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence

Quantitative assessment of cellular forces and motion advanced considerably over the last four decades. These advancements provided the framework to examine insightful mechanical signaling processes in cell culture systems. However, the field currently faces three problems: lack of quality standardization of the acquired data, technical errors in data analysis and visualization, and perhaps most importantly, the technology remains largely out of reach for common cell biology laboratories. To overcome these limitations, we developed a new experimental platform - Integrative Toolkit to Analyze Cellular Signals (iTACS). iTACS consists of two components: Acquisition and Training Module (AcTrM) and Analysis and Visualization Module (AnViM). AcTrM is based on µManager - an NIH-ImageJ-based microscope control software - and facilitates user self-training and automation of common image acquisition protocols. AnViM is based on NIH-ImageJ and facilitates user-friendly automation of data analysis and insightful visualization of results. These experiments involve culturing adherent cells on hydrogels, imaging fiducial markers embedded in the hydrogel, and finally extracting from these images a comprehensive mechanical characterization of the cells. Currently, iTACS enables the user to analyze and track a wide array of properties, including morphology, motion, cytoskeletal forces, and fluorescence of individual cells and their neighboring region. The quality standardization issue was addressed in AcTrM with, a reference image-guided refocusing technique. The technical issues in data analysis were addressed in AnViM with a multi-pronged image segmentation procedure, a user-friendly approach to identify boundary conditions, and a novel cellular property-based data visualization. AcTrM is designed to facilitate the straightforward transformation of basic fluorescence microscopes into experimental cell mechanics rigs, and AnViM is equipped to enable users to measure cellular mechanical signals without requiring an engineering background. iTACS will be available to the research community as an open-source suite with community-driven development capabilities.

Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence.

Quantitative assessment of cellular forces and motion advanced considerably over the last four decades. These advancements provided the framework to examine insightful mechanical signaling processes in cell culture systems. However, the field currently faces three problems: lack of quality standardization of the acquired data, technical errors in data analysis and visualization, and perhaps most importantly, the technology remains largely out of reach for common cell biology laboratories. To overcome these limitations, we developed a new experimental platform - Integrative Toolkit to Analyze Cellular Signals (iTACS). iTACS consists of two components: Acquisition and Training Module (AcTrM) and Analysis and Visualization Module (AnViM). AcTrM is based on µManager - an NIH-ImageJ-based microscope control software - and facilitates user self-training and automation of common image acquisition protocols. AnViM is based on NIH-ImageJ and facilitates user-friendly automation of data analysis and insightful visualization of results. These experiments involve culturing adherent cells on hydrogels, imaging fiducial markers embedded in the hydrogel, and finally extracting from these images a comprehensive mechanical characterization of the cells. Currently, iTACS enables the user to analyze and track a wide array of properties, including morphology, motion, cytoskeletal forces, and fluorescence of individual cells and their neighboring region. The quality standardization issue was addressed in AcTrM with, a reference image-guided refocusing technique. The technical issues in data analysis were addressed in AnViM with a multi-pronged image segmentation procedure, a user-friendly approach to identify boundary conditions, and a novel cellular property-based data visualization. AcTrM is designed to facilitate the straightforward transformation of basic fluorescence microscopes into experimental cell mechanics rigs, and AnViM is equipped to enable users to measure cellular mechanical signals without requiring an engineering background. iTACS will be available to the research community as an open-source suite with community-driven development capabilities.

The Art of Arriving: A New Methodological Approach to Reframing “Refugee Integration”

The main objective of the transdisciplinary and arts-based research project “The Art of Arriving: Reframing ‘Refugee Integration’” is to explore the transformative potential of the arts for the sociology of migration and integration. By creating a real-world laboratory where sociologists accompany artists as they create, and recipients while they interpret aesthetic expressions, the project focuses on the process of refugees’ arriving. The aim is to examine if and how the meaning-making processes involved in creating and interpreting art can foster alternative views about “refugee integration” and extend or even revise the traditional sociological toolkit for understanding integration. The article discusses the methodological implications of the planned transdisciplinary multimethod approach by paying particular attention to the different logics of knowledge production in science and the arts. Additionally, it sheds light on the benefits associated with the mutual translation between sociology and various fields of art, which is mediated through the process of creating and interpreting aesthetic expressions in the context of refugee migration.

Development of Learning Equipment Learning Implementation Plan (RPP) Integration of Character Education in Pancasila and Citizenship Education Subjects (PPKN) at Smp Negeri 20 Makassar

This research is development research that aims to produce a Learning Toolkit for Integrated RPP Character Education in Pancasila and Citizenship Education (PPKn) subjects at SMP Negeri 20 Makassar which meets the valid criteria with the subject of this research as many as 30 students in SMP Negeri 20 Makassar in Class VIIA. The desired product in this research is a valid, practical, and effective RPP Learning Tool for Character Education Integration. The product consists of three components, namely: lesson plans, student books, and teacher's books. This developmental research process refers to the 4-D model This model is a learning development approach system that is carried out covering 4 stages, namely defining, designing, developing and disseminating. The results showed that the Learning Toolkit for Integrated Character Education RPP that was developed was declared valid based on the validator's assessment and the results of a limited trial carried out for two trials. The validity of the Learning Toolkit for Integration of Character Education RPP is measured based on the assessment of the results of the validation of experts (validators) who meet the validity criteria, namely (1) RPP with a strong relevance category with a validity coefficient of 3.92 with the "Very Valid" category, (2) student books with the "Valid" category with a validity value of 4.10, (3) Teacher's Books in the "Valid" category with a validity value of 4.30. This shows that the resulting Character Education Integration RPP Learning Toolkit is in the valid category.

ModPhred: an integrative toolkit for the analysis and storage of nanopore sequencing DNA and RNA modification data.

DNA and RNA modifications can now be identified using nanopore sequencing. However, we currently lack a flexible software to efficiently encode, store, analyze and visualize DNA and RNA modification data. Here, we present ModPhred, a versatile toolkit that facilitates DNA and RNA modification analysis from nanopore sequencing reads in a user-friendly manner. ModPhred integrates probabilistic DNA and RNA modification information within the FASTQ and BAM file formats, can be used to encode multiple types of modifications simultaneously, and its output can be easily coupled to genomic track viewers, facilitating the visualization and analysis of DNA and RNA modification information in individual reads in a simple and computationally efficient manner. ModPhred is available at https://github.com/novoalab/modPhred, is implemented in Python3, and is released under an MIT license. Docker images with all dependencies preinstalled are also provided. Supplementary data are available at Bioinformatics online.

An Automated In Vitro Experimental Platform to Analyze Structure, Motion and Forces in Adherent Cells

Background Commonly used optical imaging and data analysis tools employ hardware and software technologies that are nearly antiquated. The lag in translation and implementation of advances in electronic devices, computational approaches and mathematical analysis into common experimental cell biology tools is a major constraint on the pace of growth in our knowledge of cellular physiology. Here we present Integrative Toolkit to Analyze Cellular Signals (iTACS) which enhances performance of microscope hardware and enables cellular biologists to readily examine a wide variety of cellular properties. Methods Using μManager - a NIH-ImageJ-based image acquisition application - we have developed an Acquisition and Training Module (AcTrM) which enables users to set up simultaneous measurements of traditional optical properties and a variety of physical properties of adherent cells. AcTrM facilitates user training through brief directions included in the graphical interface. To increase productivity and improve workflow of a shared microscope facility, AcTrM includes the ability to remove the sample from the microscope and resume the measurements at the precise physical spot automatically correcting small errors in position. This feature is particularly important for accurate measurement of physical forces in adherent cells. In addition to AcTrM, we have developed an Analysis and Visualization Module (AnViM) which enables users to quantify a wide variety of properties from the acquired data without mastering the underlying technical background. AnViM can be used in an interactive or batch processing mode on a personal or a cloud computer. It enables quantitative assessment of the properties including cellular shape, size, orientation, speed and direction of motion, tractions exerted on the substrate and on neighboring cells, contractile and shear moments, and similar wide variety of physical properties of the region neighboring each cell. AnViM interface enables the user to provide highly technical input in a more relatable manner. AcTrM and AnViM are the two key components of iTACS and they were primarily programmed primarily using Beanshell scripts and ImageJ macros. Results and Conclusion We collected input from users of various educational backgrounds to optimize the graphical user interface of AcTrM and AnViM. We successfully tested the functionality of iTACS in various experimental situations including rapid response of cells to fluid shear stress or pharmacological compounds, slow response in the context of cellular migration or growth from subconfluent to a confluent monolayer. iTACS has enabled us to identify a mechanistic fingerprint of adherent cellular monolayers and discover fundamental laws that govern mechanical behavior of adherent cells. Such studies require state-of-the-art engineering tools that were so far confined to a very few labs that have the necessary engineering background. iTACS now brings these and other novel engineering tools at the fingertips of experimental cell biologists.

SpaceHub: A high-performance gravity integration toolkit for few-body problems in astrophysics

ABSTRACT We present the open source few-body gravity integration toolkit SpaceHub. SpaceHub offers a variety of algorithmic methods, including the unique algorithms AR-Radau, AR-Sym6, AR-ABITS, and AR-chain+ which we show outperform other methods in the literature and allow for fast, precise, and accurate computations to deal with few-body problems ranging from interacting black holes to planetary dynamics. We show that AR-Sym6 and AR-chain+, with algorithmic regularization, chain algorithm, active round-off error compensation and a symplectic kernel implementation, are the fastest and most accurate algorithms to treat black hole dynamics with extreme mass ratios, extreme eccentricities, and very close encounters. AR-Radau, the first regularized Radau integrator with round off error control down to 64 bits floating point machine precision, has the ability to handle extremely eccentric orbits and close approaches in long-term integrations. AR-ABITS, a bit efficient arbitrary precision method, achieves any precision with the least CPU cost compared to other open source arbitrary precision few-body codes. With the implementation of deep numerical and code optimization, these new algorithms in SpaceHub prove superior to other popular high precision few-body codes in terms of performance, accuracy, and speed.

Answers About Complementary and Integrative Medicine—Autism Toolkit

Answers About Complementary and Integrative Medicine—Autism Toolkit

The ripples of modernity: How we can extend paleoanthropology with the extended evolutionary synthesis.

Contemporary understandings of paleoanthropological data illustrate that the search for a line defining, or a specific point designating, "modern human" is problematic. Here we lend support to the argument for the need to look for patterns in the paleoanthropological record that indicate how multiple evolutionary processes intersected to form the human niche, a concept critical to assessing the development and processes involved in the emergence of a contemporary human phenotype. We suggest that incorporating key elements of the Extended Evolutionary Synthesis (EES) into our endeavors offers a better and more integrative toolkit for modeling and assessing the evolution of the genus Homo. To illustrate our points, we highlight how aspects of the genetic exchanges, morphology, and material culture of the later Pleistocene complicate the concept of "modern" human behavior and suggest that multiple evolutionary patterns, processes, and pathways intersected to form the human niche.