Optimized rat models better mimic patients with irinotecan-induced severe diarrhea

Irinotecan-induced severe diarrhea (IISD) not only limits irinotecan's application but also significantly affects patients' quality of life. However, existing animal models often inadequately represent the dynamics of IISD development, progression, and resolution across multiple chemotherapy cycles, yielding non-reproducible and highly variable response with limited clinical translation. Our studies aim to establish a reproducible and validated IISD model that better mimics the pathophysiology progression observed in patients, enhancing translational potential. We investigated the impact of dosing regimens (including different dose, infusion time, and two cycles of irinotecan administration), sex, age, tumor-bearing conditions, and irinotecan formulation on the IISD incidence and severity in mice and rats. Lastly, we investigated above factors' impact on pharmacokinetics of irinotecan, intestinal injury, and carboxylesterase activities. In summary, we successfully established a standard model establishment procedure for an optimized IISD model with highly reproducible severe diarrhea incidence rate (100%) and a low mortality rate (11%) in F344 rats. Additionally, the rats tolerated at least two cycles of irinotecan chemotherapy treatment. In contrast, the mouse model exhibited suboptimal IISD incidence rates (60%) and an extremely high mortality rate (100%). Notably, dosing regimen, age and tumor-bearing conditions of animals emerged as critical factors in IISD model establishment. In conclusion, our rat IISD model proves superior in mimicking pathophysiology progression and characteristics of IISD in patients, which stands as an effective tool for mechanism and efficacy studies in future chemotherapy-induced gut toxicity research.

Miniaturization of an enclosed electrospinning process to enhance reproducibility in the fabrication of rapidly dissolving cell-based biosensors

There is broad interest in producing electrospun films embedded with biological materials. It is well known that electrospinning requires careful control of the process conditions, especially the environmental conditions such as relative humidity (RH). Given that commercial electrospinning systems are expensive (> $10,000) and are typically too large to be used in standard biological safety cabinets (BSC), we designed and built a miniaturized electrospinning box (E-Box) that will fit inside a BSC, and the RH can be easily controlled using simple instrumentation (gas cylinder, regulator, needle valve, rotameter). It uses an inexpensive computerized numerical control machine to control the spinneret positioning and collector rotational speed-all the parts for the device (except the syringe pump and voltage supply) can be purchased for approximately $1000. We demonstrate the usefulness of our design in optimizing the production of Escherichia coli-embedded pullulan-trehalose films to be used as rapidly dissolving biosensors for environmental monitoring. At a fixed electrospinning recipe, we showed that decreasing the RH from approximately 48% to 22% resulted in the average fiber diameter increasing from 240 (± 11) nm to 314 (± 8) nm. We also demonstrate the usefulness of our design in performing sequential electrospinning experiments to evaluate process performance reproducibility. For example, from just 1 mL of a polymer solution, we produced 16 electrospun films (approximately 3 cm by 8 cm each)-from those films we hole-punched approximately 80 biosensor discs which were then used in subsequent experiments to determine the amount of two different biocides (Grotan BK and triclosan) in aqueous samples. The technique developed in this study is ideal for creating electrospun materials in high quantities that are highly reproducible through the precise control of RH.

Determination of a positive response in the Ames Salmonella mutagenicity assay

Genetic toxicology tests are used to categorize substances as genotoxic and potentially carcinogenic. In general, test results are designated as mutagenic, not mutagenic, or inconclusive and, depending on its potential use and applicable regulations, a mutagenic result can restrict or remove a substance from further development, or assign limits to its use. In these tests, mutation responses form a continuum without a clear delineation between an increase over the background, untreated, mutant frequency and a frequency that would define the test substance as a mutagen and a potential carcinogenic hazard. This situation is illustrated using the Salmonella mutagenicity (Ames) test which is the initial, and often only, test used to characterize substances as mutagenic or nonmutagenic. It has its widest use by industry and regulatory authorities to identify potential carcinogens among chemicals in development. The OECD Test Guideline No. 471 has been adopted by regulatory agencies internationally, and describes the minimum requirements for a negative response, but does not provide a specific approach for evaluating the test data. The most widely used criterion for making yes-or-no mutagenicity decisions is a 2- or 3-fold increase over the background (solvent) mutant frequency. Other approaches rely on formal statistics and/or expert judgment. These approaches and recently proposed modifications are evaluated here. Recommendations are made that are in conformity with the OECD guideline and are based on biological relevance and the biology of the mutagenic response rather than on arbitrary decision points (e.g., ≥2-fold increase or p ≤ .05).

Longitudinal home-cage automated assessment of climbing behavior shows sexual dimorphism and aging-related decrease in C57BL/6J healthy mice and allows early detection of motor impairment in the N171-82Q mouse model of Huntington's disease

Monitoring the activity of mice within their home cage is proving to be a powerful tool for revealing subtle and early-onset phenotypes in mouse models. Video-tracking, in particular, lends itself to automated machine-learning technologies that have the potential to improve the manual annotations carried out by humans. This type of recording and analysis is particularly powerful in objective phenotyping, monitoring behaviors with no experimenter intervention. Automated home-cage testing allows the recording of non-evoked voluntary behaviors, which do not require any contact with the animal or exposure to specialist equipment. By avoiding stress deriving from handling, this approach, on the one hand, increases the welfare of experimental animals and, on the other hand, increases the reliability of results excluding confounding effects of stress on behavior. In this study, we show that the monitoring of climbing on the wire cage lid of a standard individually ventilated cage (IVC) yields reproducible data reflecting complex phenotypes of individual mouse inbred strains and of a widely used model of neurodegeneration, the N171-82Q mouse model of Huntington's disease (HD). Measurements in the home-cage environment allowed for the collection of comprehensive motor activity data, which revealed sexual dimorphism, daily biphasic changes, and aging-related decrease in healthy C57BL/6J mice. Furthermore, home-cage recording of climbing allowed early detection of motor impairment in the N171-82Q HD mouse model. Integrating cage-floor activity with cage-lid activity (climbing) has the potential to greatly enhance the characterization of mouse strains, detecting early and subtle signs of disease and increasing reproducibility in preclinical studies.

Controlling organoid symmetry breaking uncovers an excitable system underlying human axial elongation

The human embryo breaks symmetry to form the anterior-posterior axis of the body. As the embryo elongates along this axis, progenitors in the tail bud give rise to tissues that generate spinal cord, skeleton, and musculature. This raises the question of how the embryo achieves axial elongation and patterning. While ethics necessitate in vitro studies, the variability of organoid systems has hindered mechanistic insights. Here, we developed a bioengineering and machine learning framework that optimizes organoid symmetry breaking by tuning their spatial coupling. This framework enabled reproducible generation of axially elongating organoids, each possessing a tail bud and neural tube. We discovered that an excitable system composed of WNT/FGF signaling drives elongation by inducing a neuromesodermal progenitor-like signaling center. We discovered that instabilities in the excitable system are suppressed by secreted WNT inhibitors. Absence of these inhibitors led to ectopic tail buds and branches. Our results identify mechanisms governing stable human axial elongation.

Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data

Feature selection is indispensable in microbiome data analysis, but it can be particularly challenging as microbiome data sets are high dimensional, underdetermined, sparse and compositional. Great efforts have recently been made on developing new methods for feature selection that handle the above data characteristics, but almost all methods were evaluated based on performance of model predictions. However, little attention has been paid to address a fundamental question: how appropriate are those evaluation criteria? Most feature selection methods often control the model fit, but the ability to identify meaningful subsets of features cannot be evaluated simply based on the prediction accuracy. If tiny changes to the data would lead to large changes in the chosen feature subset, then many selected features are likely to be a data artifact rather than real biological signal. This crucial need of identifying relevant and reproducible features motivated the reproducibility evaluation criterion such as Stability, which quantifies how robust a method is to perturbations in the data. In our paper, we compare the performance of popular model prediction metrics (MSE or AUC) with proposed reproducibility criterion Stability in evaluating four widely used feature selection methods in both simulations and experimental microbiome applications with continuous or binary outcomes. We conclude that Stability is a preferred feature selection criterion over model prediction metrics because it better quantifies the reproducibility of the feature selection method.

Reproducible Spectrum and Hyperspectrum Data Analysis Using NeXL

NeXL is a collection of Julia language packages (libraries) for X-ray microanalysis data processing. NeXLCore provides basic atomic and X-ray physics data and models including support for microanalysis-related data types for materials and k-ratios. NeXLMatrixCorrection provides algorithms for matrix correction and iteration. NeXLSpectrum provides utilities and tools for energy-dispersive X-ray spectrum and hyperspectrum analysis including display, manipulation, and fitting. NeXL is integrated with the Julia language infrastructure. NeXL builds on the Gadfly plotting library and the DataFrames tabular data library. When combined with the DrWatson package, NeXL can provide a highly reproducible environment in which to process microanalysis data. Data availability and reproducible data analysis are two keys to scientific reproducibility. Not only should readers of journal articles have access to the data, they should also be able to reproduce the analysis steps that take the data to final results. This paper will both discuss the NeXL framework and provide examples of how it can used for reproducible data analysis.

Heritability in corpus callosum morphology and its association with tool use skill in chimpanzees (Pan troglodytes): Reproducibility in two genetically isolated populations

The corpus callosum (CC) is the major white matter tract connecting the left and right cerebral hemispheres. It has been hypothesized that individual variation in CC morphology is negatively associated with forebrain volume (FBV) and this accounts for variation in behavioral and brain asymmetries as well as sex differences. To test this hypothesis, CC surface area and thickness as well as FBV was quantified in 221 chimpanzees with known pedigrees. CC surface area, thickness and FBV were significantly heritable and phenotypically associated with each other; however, no significant genetic association was found between FBV, CC surface area and thickness. The CC surface area and thickness measures were also found to be significantly heritable in both chimpanzee cohorts as were phenotypic associations with variation in asymmetries in tool use skill, suggesting that these findings are reproducible. Finally, significant phenotypic and genetic associations were found between hand use skill and region-specific variation in CC surface area and thickness. These findings suggest that common genes may underlie individual differences in chimpanzee tool use skill and interhemispheric connectivity as manifest by variation in surface area and thickness within the anterior region of the CC.

Developing a Rational, Optimized Product of Centella asiatica for Examination in Clinical Trials: Real World Challenges

Botanical products are frequently sold as dietary supplements and their use by the public is increasing in popularity. However, scientific evaluation of their medicinal benefits presents unique challenges due to their chemical complexity, inherent variability, and the involvement of multiple active components and biological targets. Translation away from preclinical models, and developing an optimized, reproducible botanical product for use in clinical trials, presents particular challenges for phytotherapeutic agents compared to single chemical entities. Common deficiencies noted in clinical trials of botanical products include limited characterization of the product tested, inadequate placebo control, and lack of rationale for the type of product tested, dose used, outcome measures or even the study population. Our group has focused on the botanical Centella asiatica due to its reputation for enhancing cognition in Eastern traditional medicine systems. Our preclinical studies on a Centella asiatica water extract (CAW) and its bioactive components strongly support its potential as a phytotherapeutic agent for cognitive decline in aging and Alzheimer's disease through influences on antioxidant response, mitochondrial activity, and synaptic density. Here we describe our robust, scientific approach toward developing a rational phytotherapeutic product based on Centella asiatica for human investigation, addressing multiple factors to optimize its valid clinical evaluation. Specific aspects covered include approaches to identifying an optimal dose range for clinical assessment, design and composition of a dosage form and matching placebo, sourcing appropriate botanical raw material for product manufacture (including the evaluation of active compounds and contaminants), and up-scaling of laboratory extraction methods to available current Good Manufacturing Practice (cGMP) certified industrial facilities. We also address the process of obtaining regulatory approvals to proceed with clinical trials. Our study highlights the complexity of translational research on botanicals and the importance of identifying active compounds and developing sound analytical and bioanalytical methods for their determination in botanical materials and biological samples. Recent Phase I pharmacokinetic studies of our Centella asiatica product in humans (NCT03929250, NCT03937908) have highlighted additional challenges associated with designing botanical bioavailability studies, including specific dietary considerations that need to be considered.

Skyline Batch: An Intuitive User Interface for Batch Processing with Skyline

Skyline Batch is a newly developed Windows forms application that enables the easy and consistent reprocessing of data with Skyline. Skyline has made previous advances in this direction; however, none enable seamless automated reprocessing of local and remote files. Skyline keeps a log of all of the steps that were taken in the document; however, reproducing these steps takes time and allows room for human error. Skyline also has a command-line interface, enabling it to be run from a batch script, but using the program in this way requires expertise in editing these scripts. By formalizing the workflow of a highly used set of batch scripts into an intuitive and powerful user interface, Skyline Batch can reprocess data stored in remote repositories just by opening and running a Skyline Batch configuration file. When run, a Skyline Batch configuration downloads all necessary remote files and then runs a four-step Skyline workflow. By condensing the steps needed to reprocess the data into one file, Skyline Batch gives researchers the opportunity to publish their processing along with their data and other analysis files. These easily run configuration files will greatly increase the transparency and reproducibility of published work. Skyline Batch is freely available at https://skyline.ms/batch.url.

Credible Mendelian Randomization Studies in the Presence of Selection Bias Using Control Exposures

Selection bias is increasingly acknowledged as a limitation of Mendelian randomization (MR). However, few methods exist to assess this issue. We focus on two plausible causal structures relevant to MR studies and illustrate the data-generating process underlying selection bias via simulation studies. We conceptualize the use of control exposures to validate MR estimates derived from selected samples by detecting potential selection bias and reproducing the exposure-outcome association of primary interest based on subject matter knowledge. We discuss the criteria for choosing the control exposures. We apply the proposal in an MR study investigating the potential effect of higher transferrin with stroke (including ischemic and cardioembolic stroke) using transferrin saturation and iron status as control exposures. Theoretically, selection bias affects associations of genetic instruments with the outcome in selected samples, violating the exclusion-restriction assumption and distorting MR estimates. Our applied example showing inconsistent effects of genetically predicted higher transferrin and higher transferrin saturation on stroke suggests the potential selection bias. Furthermore, the expected associations of genetically predicted higher iron status on stroke and longevity indicate no systematic selection bias. The routine use of control exposures in MR studies provides a valuable tool to validate estimated causal effects. Like the applied example, an antagonist, decoy, or exposure with similar biological activity as the exposure of primary interest, which has the same potential selection bias sources as the exposure-outcome association, is suggested as the control exposure. An additional or a validated control exposure with a well-established association with the outcome is also recommended to explore possible systematic selection bias.

Paste Aging Spontaneously Tunes TiO2 Nanoparticles into Reproducible Electrosprayed Photoelectrodes

In this study, the spontaneous microstructure tuning of TiO₂ was observed by aging the ethanol/water TiO₂ paste for up to 20 days at ambient conditions. A dynamic light scattering study reveals that it formed the outstanding reproducible TiO₂ microstructure with a ∼200 nm average particle size and stabilizes in 6 to 20 days under an ambient atmosphere. Interestingly, the as-deposited day 15 sample spontaneously changed its crystallinity upon keeping the paste at ambient conditions; meanwhile the day 0 sample showed an amorphous structure. A dense, uniform, and stable TiO₂ electrode was cast on a fluorine doped-tin oxide substrate using the electrospray technique. We exploit the spontaneous evolution of the TiO₂ nanopowder to revisit the fabrication procedure of the TiO₂ photoelectrode for dye-sensitized solar cells (DSSCs). The controlled microstructure TiO₂ film was used in DSSCs, which, to the best of our knowledge, achieved the highest power conversion efficiency of 9.65% using N719 dye in sensitizing the TiO₂ photoanode.

Urogenital atrophy: The 'unknown factors' challenging current practice

Urogenital atrophy occurs as a result of the effect of estrogen deficiency on the tissue quality in the vulva, vagina, urethra and bladder. It is a common consequence of the menopause, with possibly up to 80% of women experiencing symptoms. Despite a number of different diagnostic methods, there is no validated objective method by which to confirm the diagnosis in clinical practice and research settings. Education, for women and clinicians, is called for to support diagnosis and treatment. However, before this can be of global benefit, development of an accessible and reproducible diagnostic test is required. Current assessment methods include routine history and clinical examination, with the clinician's opinion based on their subjective observations. A vaginal smear to assess the ratio of superficial to parabasal cells and measurement of the pH of the vaginal secretions is more commonly used in research settings. A number of formulae have been postulated to facilitate the diagnosis including the Vaginal Health Index, the Vulval Health Index, the Genitourinary Syndrome of the Menopause assessment tool, the Genital Health Clinical Evaluation and vaginal biopsy and assessment of the vaginal microbiome. However, none of these potential methods of assessment has been validated. This article focuses on what we do not know about urogenital atrophy including the prevalence, the most appropriate terminology, aetiology, pathogenesis and the most objective and reproducible method of assessment.

Magnetic Iron Oxide Nanoparticle (IONP) Synthesis to Applications: Present and Future

Iron oxides are chemical compounds which have different polymorphic forms, including γ-Fe2O3 (maghemite), Fe3O4 (magnetite), and FeO (wustite). Among them, the most studied are γ-Fe2O3 and Fe3O4, as they possess extraordinary properties at the nanoscale (such as super paramagnetism, high specific surface area, biocompatible etc.), because at this size scale, the quantum effects affect matter behavior and optical, electrical and magnetic properties. Therefore, in the nanoscale, these materials become ideal for surface functionalization and modification in various applications such as separation techniques, magnetic sorting (cells and other biomolecules etc.), drug delivery, cancer hyperthermia, sensing etc., and also for increased surface area-to-volume ratio, which allows for excellent dispersibility in the solution form. The current methods used are partially and passively mixed reactants, and, thus, every reaction has a different proportion of all factors which causes further difficulties in reproducibility. Direct active and complete mixing and automated approaches could be solutions to this size- and shape-controlled synthesis, playing a key role in its exploitation for scientific or technological purposes. An ideal synthesis method should be able to allow reliable adjustment of parameters and control over the following: fluctuation in temperature; pH, stirring rate; particle distribution; size control; concentration; and control over nanoparticle shape and composition i.e., crystallinity, purity, and rapid screening. Iron oxide nanoparticle (IONP)-based available clinical applications are RNA/DNA extraction and detection of infectious bacteria and viruses. Such technologies are important at POC (point of care) diagnosis. IONPs can play a key role in these perspectives. Although there are various methods for synthesis of IONPs, one of the most crucial goals is to control size and properties with high reproducibility to accomplish successful applications. Using multiple characterization techniques to identify and confirm the oxide phase of iron can provide better characterization capability. It is very important to understand the in-depth IONP formation mechanism, enabling better control over parameters and overall reaction and, by extension, properties of IONPs. This work provides an in-depth overview of different properties, synthesis methods, and mechanisms of iron oxide nanoparticles (IONPs) formation, and the diverse range of their applications. Different characterization factors and strategies to confirm phase purity in the IONP synthesis field are reviewed. First, properties of IONPs and various synthesis routes with their merits and demerits are described. We also describe different synthesis strategies and formation mechanisms for IONPs such as for: wustite (FeO), hematite (α-Fe2O3), maghemite (ɤ-Fe2O3) and magnetite (Fe3O4). We also describe characterization of these nanoparticles and various applications in detail. In conclusion, we present a detailed overview on the properties, size-controlled synthesis, formation mechanisms and applications of IONPs.

Specification and Distribution of Vocabularies Among Consortial Partners

Due to the variety of different software systems and disparate observational databases, the need for a uniform data representation rises. Common data models (CDM) support the harmonisation of data. A powerful but compact software setup and a minimum vocabulary set has been composed via Docker to facilitate analysis of data across ten university hospitals. The presented approach also creates the possibility to use a concise database which is easy to deploy.

Portable and platform-independent MR pulse sequence programs

PURPOSE

To introduce a new sequence description format for vendor-independent MR sequences that include all calculation logic portably. To introduce a new MRI sequence development approach which utilizes flexibly reusable modules.

METHODS

The proposed sequence description contains a sequence module hierarchy for loop and group logic, which is enhanced by a novel strategy for performing efficient parameter and pulse shape calculation. These calculations are powered by a flow graph structure. By using the flow graph, all calculations are performed with no redundancy and without requiring preprocessing. The generation of this interpretable structure is a separate step that combines MRI techniques while actively considering their context. The driver interface is slim and highly flexible through scripting support. The sequences do not require any vendor-specific compiling or processing step. A vendor-independent frontend for sequence configuration can be used. Tests that ensure physical feasibility of the sequence are integrated into the calculation logic.

RESULTS

The framework was used to define a set of standard sequences. Resulting images were compared to respective images acquired with sequences provided by the device manufacturer. Images were acquired using a standard commercial MRI system.

CONCLUSIONS

The approach produces configurable, vendor-independent sequences, whose configurability enables rapid prototyping. The transparent data structure simplifies the process of sharing reproducible sequences, modules, and techniques.

Virus-Induced Asthma/Wheeze in Preschool Children: Longitudinal Assessment of Airflow Limitation Using Impulse Oscillometry

: Several researchers have assessed the utility of Impulse Oscillometry System (IOS) in diagnosing and evaluating the severity of respiratory diseases in childhood, but none has investigated the impact of the fluctuations of IOS parameters in an individualized manner. In this two-year prospective study, we aimed to longitudinally evaluate changes in airflow limitation and bronchodilator responsiveness in steroid-naïve four- to six-year-old children during a virus-induced wheezing episode, with IOS pulmonary resistance parameters set at 5 (R5) and 20 (R20) Hz. Moreover, feasibility and reproducibility, in addition to the diagnostic properties of these parameters were examined. Lung function was assessed every six weeks (baseline), within the first 48 hours following an acute wheezing episode (Day 0), after 10, and after 30 days. Forty-three out of 93 recruited children (4.5 ± 0.4 years old) experienced a wheezing episode during the study period. All children were able to perform the IOS effort in an acceptable and highly reproducible manner. R5 and R20 fluctuated independently of atopy, age, height, and weight. On Day 0, R5 values were significantly lower than the respective baseline values and returned to individual baseline levels within 10 days. Post-bronchodilation R5 values were similar to the baseline ones, reflecting a reversible airway obstruction on Day 0. Response to bronchodilation (ΔR5) was significantly more pronounced on Day 0. ΔR5 values lower than -20.5% had a sensitivity of 70% and a specificity of 76% and could accurately identify up to 75% of the examined preschoolers. This study provides evidence in favor of the objective utility of IOS as an easy, highly reproducible, and sensitive technique to assess clinically significant fluctuations and bronchodilation responses suggestive of airflow limitation. Reference values although necessary are suboptimal, utilizing the personal best values as personal reference is useful and reliable.

Organizing and running bioinformatics hackathons within Africa: The H3ABioNet cloud computing experience

The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous computing environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. Building on the network's Standard Operating Procedures (SOPs) for common genomic analyses, H3ABioNet arranged its first Cloud Computing and Reproducible Workflows Hackathon in 2016, with the purpose of translating those SOPs into analysis pipelines able to run on heterogeneous computing environments and meeting the needs of H3Africa research projects. This paper describes the preparations for this hackathon and reflects upon the lessons learned about its impact on building the technical and scientific expertise of African researchers. The workflows developed were made publicly available in GitHub repositories and deposited as container images on Quay.io.

Organizing and running bioinformatics hackathons within Africa: The H3ABioNet cloud computing experience

The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous computing environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. Building on the network’s Standard Operating Procedures (SOPs) for common genomic analyses, H3ABioNet arranged its first Cloud Computing and Reproducible Workflows Hackathon in 2016, with the purpose of translating those SOPs into analysis pipelines able to run on heterogeneous computing environments and meeting the needs of H3Africa research projects. This paper describes the preparations for this hackathon and reflects upon the lessons learned about its impact on building the technical and scientific expertise of African researchers. The workflows developed were made publicly available in GitHub repositories and deposited as container images on Quay.io.

A reproducible robust likelihood approach to inference about marginal characteristics of binary data in paired settings

We introduce a robust likelihood approach to inference about marginal distributional characteristics for paired data without modeling correlation/joint probabilities. This method is reproducible in that it is applicable to paired settings with various sizes. The virtue of the new strategy is elucidated via testing marginal homogeneity in paired triplet scenario. We use simulations and real data analysis to demonstrate the merit of our robust likelihood methodology.

Bioengineering the microanatomy of human skin

Recreating the structure of human tissues in the laboratory is valuable for fundamental research, testing interventions, and reducing the use of animals. Critical to the use of such technology is the ability to produce tissue models that accurately reproduce the microanatomy of the native tissue. Current artificial cell‐based skin systems lack thorough characterisation, are not representative of human skin, and can show variation. In this study, we have developed a novel full thickness model of human skin comprised of epidermal and dermal compartments. Using an inert porous scaffold, we created a dermal construct using human fibroblasts that secrete their own extracellular matrix proteins, which avoids the use of animal‐derived materials. The dermal construct acts as a foundation upon which epidermal keratinocytes were seeded and differentiated into a stratified keratinised epithelium. In‐depth morphological analyses of the model demonstrated very close similarities with native human skin. Extensive immunostaining and electron microscopy analysis revealed ultrastructural details such as keratohyalin granules and lamellar bodies within the stratum granulosum, specialised junctional complexes, and the presence of a basal lamina. These features reflect the functional characteristics and barrier properties of the skin equivalent. Robustness and reproducibility of in vitro models are important attributes in experimental practice, and we demonstrate the consistency of the skin construct between different users. In summary, a new model of full thickness human skin has been developed that possesses microanatomical features reminiscent of native tissue. This skin model platform will be of significant interest to scientists researching the structure and function of human skin.

Open science, reproducibility, and transparency in ecology

Reproducibility is a key tenet of the scientific process that dictates the reliability and generality of results and methods. The complexities of ecological observations and data present novel challenges in satisfying needs for reproducibility and also transparency. Ecological systems are dynamic and heterogeneous, interacting with numerous factors that sculpt natural history and that investigators cannot completely control. Observations may be highly dependent on spatial and temporal context, making them very difficult to reproduce, but computational reproducibility can still be achieved. Computational reproducibility often refers to the ability to produce equivalent analytical outcomes from the same data set using the same code and software as the original study. When coded workflows are shared, authors and editors provide transparency for readers and allow other researchers to build directly and efficiently on primary work. These qualities may be especially important in ecological applications that have important or controversial implications for science, management, and policy. Expectations for computational reproducibility and transparency are shifting rapidly in the sciences. In this work, we highlight many of the unique challenges for ecology along with practical guidelines for reproducibility and transparency, as ecologists continue to participate in the stewardship of critical environmental information and ensure that research methods demonstrate integrity.

Radio Frequency Detection and Characterization of Water-Ethanol Solution through Spiral-Coupled Passive Micro-Resonator Sensor

We present a microfabricated spiral-coupled passive resonator sensor realized through integrated passive device (IPD) technology for the sensitive detection and characterization of water-ethanol solutions. In order to validate the performance of the proposed device, we explicitly measured and analyzed the radio frequency (RF) characteristics of various water-ethanol solution compositions. The measured results showed a drift in the resonance frequency from 1.16 GHz for deionized (DI) water to 1.68 GHz for the solution containing 50% ethanol, whereas the rejection level given by the reflection coefficient decreased from −29.74 dB to −14.81 dB. The obtained limit of detection was 3.82% volume composition of ethanol in solution. The derived loaded capacitance was 21.76 pF for DI water, which gradually decreased to 8.70 pF for the 50% ethanol solution, and the corresponding relative permittivity of the solution decreased from 80.14 to 47.79. The dissipation factor increased with the concentration of ethanol in the solution. We demonstrated the reproducibility of the proposed sensor through iterative measures of the samples and the study of surface morphology. Successive measurement of different samples had no overlapping and had very minimum bias between RF characteristics for each measured sample. The surface profile for bare sensors was retained after the sample test, resulting a root mean square (RMS) value of 11.416 nm as compared to 10.902 nm for the bare test. The proposed sensor was shown to be a viable alternative to existing sensors for highly sensitive water-ethanol concentration detection.

Using the Seven Bridges Cancer Genomics Cloud to Access and Analyze Petabytes of Cancer Data

Next-generation sequencing has produced petabytes of data, but accessing and analyzing these data remain challenging. Traditionally, researchers investigating public datasets like The Cancer Genome Atlas (TCGA) would download the data to a high-performance cluster, which could take several weeks even with a highly optimized network connection. The National Cancer Institute (NCI) initiated the Cancer Genomics Cloud Pilots program to provide researchers with the resources to process data with cloud computational resources. We present protocols using one of these Cloud Pilots, the Seven Bridges Cancer Genomics Cloud (CGC), to find and query public datasets, bring your own data to the CGC, analyze data using standard or custom workflows, and benchmark tools for accuracy with interactive analysis features. These protocols demonstrate that the CGC is a data-analysis ecosystem that fully empowers researchers with a variety of areas of expertise and interests to collaborate in the analysis of petabytes of data. © 2017 by John Wiley & Sons, Inc.

Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance

This is a practical example of a powerful research strategy: putting together data from studies covering a diversity of conditions can yield a scientifically sound grasp of the phenomenon when the individual observations failed to provide definitive understanding. The rationale is that defining a realistic, quantitative, explanatory hypothesis for the whole set of studies, brings about a “consilience” of the often competing hypotheses considered for individual data sets. An internally consistent conjecture linking multiple data sets simultaneously provides stronger evidence on the characteristics of a system than does analysis of individual data sets limited to narrow ranges of conditions. Our example examines three very different data sets on the clearance of salicylic acid from humans: a high concentration set from aspirin overdoses; a set with medium concentrations from a research study on the influences of the route of administration and of sex on the clearance kinetics, and a set on low dose aspirin for cardiovascular health. Three models were tested: (1) a first order reaction, (2) a Michaelis-Menten (M-M) approach, and (3) an enzyme kinetic model with forward and backward reactions. The reaction rates found from model 1 were distinctly different for the three data sets, having no commonality. The M-M model 2 fitted each of the three data sets but gave a reliable estimates of the Michaelis constant only for the medium level data (K_m = 24±5.4 mg/L); analyzing the three data sets together with model 2 gave K_m = 18±2.6 mg/L. (Estimating parameters using larger numbers of data points in an optimization increases the degrees of freedom, constraining the range of the estimates). Using the enzyme kinetic model (3) increased the number of free parameters but nevertheless improved the goodness of fit to the combined data sets, giving tighter constraints, and a lower estimated K_m = 14.6±2.9 mg/L, demonstrating that fitting diverse data sets with a single model improves confidence in the results. This modeling effort is also an example of reproducible science available at html://www.physiome.org/jsim/models/webmodel/NSR/SalicylicAcidClearance