Ten simple rules on how to write a standard operating procedure.

Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.

A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing.

The instant of turn switch (TS) in alpine skiing has been assessed with a variety of sensors and TS concepts. Despite many published methodologies, it is unclear which is best or how comparable they are. This study aimed to facilitate the process of choosing a TS method by evaluating the accuracy and precision of the methodologies previously used in literature and to assess the influence of the sensor type. Optoelectronic motion capture, inertial measurement units, pressure insoles, portable force plates, and electromyography signals were recorded during indoor treadmill skiing. All TS methodologies were replicated as stated in their respective publications. The method proposed by Supej assessed with optoelectronic motion capture was used as a comparison reference. TS time differences between the reference and each methodology were used to assess accuracy and precision. All the methods analyzed showed an accuracy within 0.25 s, and ten of them within 0.05 s. The precision ranged from ~0.10 s to ~0.60 s. The TS methodologies with the best performance (accuracy and precision) were Klous Video, Spörri PI (pressure insoles), Martinez CTD (connected boot), and Yamagiwa IMU (inertial measurement unit). In the future, the specific TS methodology should be chosen with respect to sensor selection, performance, and intended purpose.

Prevention and Management of Pseudoverrucous Lesions: A Review and Case Scenarios.

GENERAL PURPOSE: To present the associated risk factors, prevention measures, and assessment and management of pseudoverrucous lesions specific to a surgically created ileal conduit, as well as three clinical scenarios illustrating this condition. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After participating in this educational activity, the participant will:1. Define pseudoverrucous lesions.2. Identify the risk factors for stoma complications such as pseudoverrucous lesions.3. Select the appropriate routine care procedures to teach patients following stoma creation to help prevent pseudoverrucous lesions.4. Choose the recommended treatment options for patients who develop pseudoverrucous lesions.

Pseudoverrucous lesions are a late peristomal complication that occurs most commonly in people with urinary stomas. Impairment of the peristomal skin can result in pouching system leaks that can translate into odor, embarrassment, and diminished quality of life. Prevention is key to maintaining smooth, dry skin and intact psyche. Treatment revolves around outpatient postoperative follow-up, refitting the pouching system to eliminate moisture impacting the peristomal area, modification of pouching system wear time, acidification of the urine, and intensive education. This review includes three case scenarios to support early, intermediate, and late-stage intervention guidelines. Some interventions were successful; one case remains unresolved.

Transmembrane Nox4 topology revealed by topological determination by Ubiquitin Fusion Assay, a novel method to uncover membrane protein topology.

The NADPH oxidase Nox4 is a multi-pass membrane protein responsible for the generation of reactive oxygen species that are implicated in cellular signaling but may also cause pathological situations when dysregulated. Although topological organization of integral membrane protein dictates its function, only limited experimental data describing Nox4's topology are available. To provide deeper insight on Nox4 structural organization, we developed a novel method to determinate membrane protein topology in their cellular environment, named Topological Determination by Ubiquitin Fusion Assay (ToDUFA). It is based on the proteolytic capacity of the deubiquitinase enzymes to process ubiquitin fusion proteins. This straightforward method, validated on two well-known protein's topologies (IL1RI and Nox2), allowed us to discriminate rapidly the topological orientation of protein's domains facing either the nucleocytosolic or the exterior/luminal compartments. Using this method, we were able for the first time to determine experimentally the topology of Nox4 which consists of 6 transmembrane domains with its N- and C-terminus moieties facing the cytosol. While the first, third and fifth loops of Nox4 protein are extracellular; the second and fourth loops are located in the cytosolic side. This approach can be easily extended to characterize the topology of all others members of the NADPH oxidase family or any multi-pass membrane proteins. Considering the importance of protein topology knowledge in cell biology research and pharmacological development, we believe that this novel method will represent a widely useful technique to easily uncover complex membrane protein's topology.

Indirect determination of mercury(II) by using magnetic nanoparticles, CdS quantum dots and mercury(II)-binding aptamers, and quantitation of released CdS by graphite furnace AAS.

This work describes an aptamer based method for highly sensitive determination of Hg(II). A Hg(II)-binding ssDNA aptamer was linked to silica-coated magnetic nanoparticles (magNPs). Then, a conjugate composed of graphene and CdS quantum dots (Gr-CdS) was linked to the complementary ssDNA. On mixing the two components, a duplex of type magNP-dsNNA-Gr/CdS is generated. If Hg(II) is added, it wills capturing the aptamer, and this leads to the release of Gr/CdS because of the formation of a stable thymine-Hg2+-thymine link. External magnetic force is used to remove the remaining complex. The released graphene-CdS is decomposed by HNO3 and injected into a graphite furnace AAS. The detectable amount of Cd is proportional to the concentration of Hg(II) in the sample. Under the optimal conditions, the method has a linear response in the 2.50 aM to 0.25 nM Hg(II) concentration range, and the detection limit is as low as 7.6 aM (at S/N = 3). It has high selectivity for Hg(II) over other metal ions. Graphical abstract.

Stable transgenesis in Astyanax mexicanus using the Tol2 transposase system.

BACKGROUND: Astyanax mexicanus is a well-established fish model system for evolutionary and developmental biology research. These fish exist as surface forms that inhabit rivers and 30 different populations of cavefish. Despite important progress in the deployment of new technologies, deep mechanistic insights into the genetic basis of evolution, development, and behavior have been limited by a lack of transgenic lines commonly used in genetic model systems. RESULTS: Here, we expand the toolkit of transgenesis by characterizing two novel stable transgenic lines that were generated using the highly efficient Tol2 system, commonly used to generate transgenic zebrafish. A stable transgenic line consisting of the zebrafish ubiquitin promoter expresses enhanced green fluorescent protein ubiquitously throughout development in a surface population of Astyanax. To define specific cell-types, a Cntnap2-mCherry construct labels lateral line mechanosensory neurons in zebrafish. Strikingly, both constructs appear to label the predicted cell types, suggesting many genetic tools and defined promoter regions in zebrafish are directly transferrable to cavefish. CONCLUSION: The lines provide proof-of-principle for the application of Tol2 transgenic technology in A. mexicanus. Expansion on these initial transgenic lines will provide a platform to address broadly important problems in the quest to bridge the genotype-phenotype gap.

Data-Independent Acquisition for the Orbitrap Q Exactive HF: A Tutorial.

Data-independent acquisition (DIA) is a powerful mass spectrometric technique to perform both protein identification and quantification of complex protein samples. Setting up DIA methods on Orbitrap analyzers requires a thorough overview of the actions the Orbitrap mass spectrometers carry out. This Tutorial is written with the intention to give an overview of the important parameters to consider as well as which measurements to carry out to get the most out of your DIA method when setting it up on an Orbitrap mass analyzer. Instead of giving the optimal DIA settings, all steps in the construction and optimization of the DIA method are shown and discussed in a way that allows tailored DIA methods. They key steps are building the spectral library after sample fractionation, deciding upon the number of data points per chromatographic peak, determining the scan times of each mass spectrometric step, constructing various DIA methods using these data, and evaluating their performance. This proposed DIA method development strategy was tested on digested lysates from Pseudomonas aeruginosa and compared with conventional DDA analysis to put the DIA results into perspective.

Development of a Parallel Reaction Monitoring-MS Method To Quantify IGF Proteins in Dogs and a Case of Nonislet Cell Tumor Hypoglycemia.

Nonislet-cell tumor hypoglycemia (NICTH) is a rare paraneoplastic phenomenon well described in dogs and humans. Tumors associated with NICTH secrete incompletely processed forms of insulin-like growth factor-II (IGF-II), commonly named big IGF-II. These forms have increased bioavailability and interact with the insulin and IGF-I receptor causing hypoglycemia and growth-promoting effects. Immunoassays designed for human samples have been used to measure canine IGF-I and -II, but they possess some limitations. In addition, there are no validated methods for measurement of big IGF-II in dogs. In the present study, a targeted parallel reaction monitoring MS-based method previously developed for cats has been optimized and applied to simultaneously quantify the serum levels of IGF-I, IGF-II, and IGFBP-3, and for the first time, the levels of big IGF-II in dogs. This method allows the absolute quantification of IGF proteins using a mixture of QPrEST proteins previously designed for humans. The method possesses good linearity and repeatability and has been used to evaluate the IGF-system in a dog with NICTH syndrome. In this dog, the levels of big IGF-II decreased by 80% and the levels of IGF-I and IGFBP-3 increased approximately 20- and 4-times, respectively, after removal of the tumor.

PTML Model of Enzyme Subclasses for Mining the Proteome of Biofuel Producing Microorganisms.

Predicting enzyme function and enzyme subclasses is always a key objective in fields such as biotechnology, biochemistry, medicinal chemistry, physiology, and so on. The Protein Data Bank (PDB) is the largest information archive of biological macromolecular structures, with more than 150 000 entries for proteins, nucleic acids, and complex assemblies. Among these entries, there are more than 4000 proteins whose functions remain unknown because no detectable homology to proteins whose functions are known has been found. The problem is that our ability to isolate proteins and identify their sequences far exceeds our ability to assign them a defined function. As a result, there is a growing interest in this topic, and several methods have been developed to identify protein function based on these innovative approaches. In this work, we have applied perturbation theory to an original data set consisting of 19 187 enzymes representing all 59 subclasses present in the protein data bank. In addition, we developed a series of artificial neural network models able to predict enzyme-enzyme pairs of query-template sequences with accuracy, specificity, and sensitivity greater than 90% in both training and validation series. As a likely application of this methodology and to further validate our approach, we used our novel model to predict a set of enzymes belonging to the yeast Pichia stipites. This yeast has been widely studied because it is commonly present in nature and produces a high ethanol yield by converting lignocellulosic biomass into bioethanol through the xylose reductase enzyme. Using this premise, we tested our model on 222 enzymes including xylose reductase, that is, the enzyme responsible for the conversion of biomass into bioethanol.

A Rapid Array-Based Approach to N-Glycan Profiling of Cultured Cells.

Typically, N-glycosylation studies done on cultured cells require up to millions of cells followed by lengthy preparation to release, isolate, and profile N-glycans. To overcome these limitations, we report a rapid array-based workflow for profiling N-glycan signatures from cells, adapted from imaging mass spectrometry used for on-tissue N-glycan profiling. Using this approach, N-glycan profiles from a low-density array of eight cell chambers could be reported within 4 h of completing cell culture. Approaches are demonstrated that account for background N-glycans due to serum media. Normalization procedures are shown. The method is robust and reproducible, requiring as few as 3000 cells per replicate with a 3-20% coefficient of variation to capture label-free profiles of N-glycans. Quantification by stable isotopic labeling of N-glycans in cell culture is demonstrated and adds no additional time to preparation. Utility of the method is demonstrated by measurement of N-glycan turnover rates due to induction of oxidative stress in human primary aortic endothelial cells. The developed method and ancillary tools serve as a foundational launching point for rapid profiling of N-glycans ranging from high-density arrays down to single cells in culture.

An efficient method to generate xenograft tumor models of acute myeloid leukemia and hepatocellular carcinoma in adult zebrafish.

Zebrafish is emerging as a promising model for the study of human cancers. Several xenograft models of zebrafish have been developed, particularly in larval stages (<48 h post fertilization) when the immune system of fish is not developed. However, xenografting in adult zebrafish requires laborious and transient methods of immune suppression (γ- irradiation or dexamethasone) that limits engraftment and survival of the tumor or fail to recapitulate specific characteristics of malignancies. Thus, the availability of a simple protocol to successfully engraft adult zebrafish, remains a challenge. The current study addresses this limitation and describes a robust method of xenografting in adult zebrafish. We describe a protocol that involves pre-conditioning of Casper, a pigmentation mutant of zebrafish with busulfan that led to a higher rate of engraftment of hepatocellular carcinoma and acute myeloid leukemia cells. To further ascertain the homing characteristics of the injected cancer cells, we transplanted adult zebrafish by two routes of administration and then studied their compartmentalization. This model presents a valuable alternative to rodents to study the biology of these cancers and also a cost-effective platform for evaluation of potential anti-cancer agents.

Reprogramming of bone marrow derived mesenchymal stromal cells to human induced pluripotent stem cells from pediatric patients with hematological diseases using a commercial mRNA kit.

The potential use of patient-specific induced pluripotent stem cells (hiPSCs) in the study and treatment of hematological diseases requires the setup of efficient and safe protocols for hiPSC generation. We aimed to adopt a reprogramming method for large-scale production of integration-free patient-specific hiPSC-lines in our stem cell processing laboratory, which supports a pediatric hematopoietic stem cell transplant unit located at a tertiary care children's hospital. We describe our 5-year experience in generation of hiPSC-lines from human bone marrow-derived mesenchymal stromal cells (BM-MSCs) using synthetic mRNAs encoding reprogramming factors. We generated hiPSC-lines from pediatric patients with ß-Thalassemia, Sickle Cell Anemia, Blackfan-Diamond Anemia, Severe Aplastic Anemia, DOCK8 Immunodeficiency and 1 healthy control. After optimization of the reprogramming procedure, average reprogramming efficiency of BM-MSCs was 0.29% (range 0.25-0.4). The complete reprogramming process lasted 14-16 days. Three to five hiPSC-colonies per sample were selected, expanded to 5 culture passages and then frozen. The whole procedure took an average time of 1.8 months (range 1.6-2.2). The hiPSC-lines expressed embryonic stem cell markers and exhibited pluripotency. This mRNA reprogramming method can be applicable in a hematopoietic stem cell culture lab setting and would be useful for the clinical translation of patient-specific hiPSCs.

Interactions between PHD3-Bromo of MLL1 and H3K4me3 Revealed by Single-Molecule Magnetic Tweezers in a Parallel DNA Circuit.

Single-molecule force spectroscopy is a powerful tool to directly measure protein-protein interactions (PPI). The high specificity and precision of PPI measurements made it possible to reveal detailed mechanisms of intermolecular interactions. However, protein aggregation due to specific or nonspecific interactions is among the most challenging problems in PPI examination. Here, we propose a strategy of a parallel DNA circuit to probe PPI using single-molecule magnetic tweezers. In contrast to PPI examination using atomic force microscopy, microspheres as probes used in magnetic tweezers avoided the single-probe issue of a cantilever. Negatively charged DNA as a linker circumvented the severe aggregation in the PPI construct with a protein linker. The unnatural amino acid encoded in proteins of interest expanded the choices of biorthogonal conjugation. We demonstrated how to apply our strategy to probe the PPI between the PHD3-Bromo and the histone H3 methylated at K4, a critical epigenetic event in leukemia development. We found a rupture force of 12 pN for breaking the PPI, which is much higher than that required to peel DNA off from a nucleosome, 3 pN. We expect that our methods will make PPI measurements of mechanics and kinetics with great precision, facilitating PPI-related research, e.g., PPI-targeted drug discovery.

A modified association test for rare and common variants based on affected sib-pair design.

Current genome-wide association analysis has identified a great number of rare and common variants associated with common complex traits, however, more effective approaches for detecting associations between rare and common variants with common diseases are still demanded. Approaches for detecting rare variant association analysis will compromise the power when detecting the effects of rare and common variants simultaneously. In this paper, we extend an existing method of testing for rare variant association based on affected sib pairs (TOW-sib) and propose a variable weight test for rare and common variants association based on affected sib pairs (abbreviated as VW-TOWsib). The VW-TOWsib can be used to achieve the purpose of detecting the association of rare and common variants with complex diseases. Simulation results in various scenarios show that our proposed method is more powerful than existing methods for detecting effects of rare and common variants. At the same time, the VW-TOWsib also performs well as a method for rare variant association analysis.

Model confidence bounds for variable selection.

In this article, we introduce the concept of model confidence bounds (MCB) for variable selection in the context of nested models. Similarly to the endpoints in the familiar confidence interval for parameter estimation, the MCB identifies two nested models (upper and lower confidence bound models) containing the true model at a given level of confidence. Instead of trusting a single selected model obtained from a given model selection method, the MCB proposes a group of nested models as candidates and the MCB's width and composition enable the practitioner to assess the overall model selection uncertainty. A new graphical tool-the model uncertainty curve (MUC)-is introduced to visualize the variability of model selection and to compare different model selection procedures. The MCB methodology is implemented by a fast bootstrap algorithm that is shown to yield the correct asymptotic coverage under rather general conditions. Our Monte Carlo simulations and real data examples confirm the validity and illustrate the advantages of the proposed method.

Scalable estimation and regularization for the logistic normal multinomial model.

Clustered multinomial data are prevalent in a variety of applications such as microbiome studies, where metagenomic sequencing data are summarized as multinomial counts for a large number of bacterial taxa per subject. Count normalization with ad hoc zero adjustment tends to result in poor estimates of abundances for taxa with zero or small counts. To account for heterogeneity and overdispersion in such data, we suggest using the logistic normal multinomial (LNM) model with an arbitrary correlation structure to simultaneously estimate the taxa compositions by borrowing information across subjects. We overcome the computational difficulties in high dimensions by developing a stochastic approximation EM algorithm with Hamiltonian Monte Carlo sampling for scalable parameter estimation in the LNM model. The ill-conditioning problem due to unstructured covariance is further mitigated by a covariance-regularized estimator with a condition number constraint. The advantages of the proposed methods are illustrated through simulations and an application to human gut microbiome data.

A two-stage experimental design for dilution assays.

Dilution assays to determine solute concentration have found wide use in biomedical research. Many dilution assays return imprecise concentration estimates because they are only done to orders of magnitude. Previous statistical work has focused on how to design efficient experiments that can return more precise estimates, however this work has not considered the practical difficulties of implementing these designs in the laboratory. We developed a two-stage experiment with a first stage that obtains an order of magnitude estimate and a second stage that concentrates effort on the most informative dilution to increase estimator precision. We show using simulations and an empirical example that the best two-stage experimental designs yield estimates that are remarkably more accurate than standard methods with equivalent effort. This work demonstrates how to utilize previous advances in experimental design in a manner consistent with current laboratory practice. We expect that multi-stage designs will prove to be useful for obtaining precise estimates with minimal experimental effort.

Simulation-selection-extrapolation: Estimation in high-dimensional errors-in-variables models.

Errors-in-variables models in high-dimensional settings pose two challenges in application. First, the number of observed covariates is larger than the sample size, while only a small number of covariates are true predictors under an assumption of model sparsity. Second, the presence of measurement error can result in severely biased parameter estimates, and also affects the ability of penalized methods such as the lasso to recover the true sparsity pattern. A new estimation procedure called SIMulation-SELection-EXtrapolation (SIMSELEX) is proposed. This procedure makes double use of lasso methodology. First, the lasso is used to estimate sparse solutions in the simulation step, after which a group lasso is implemented to do variable selection. The SIMSELEX estimator is shown to perform well in variable selection, and has significantly lower estimation error than naive estimators that ignore measurement error. SIMSELEX can be applied in a variety of errors-in-variables settings, including linear models, generalized linear models, and Cox survival models. It is furthermore shown in the Supporting Information how SIMSELEX can be applied to spline-based regression models. A simulation study is conducted to compare the SIMSELEX estimators to existing methods in the linear and logistic model settings, and to evaluate performance compared to naive methods in the Cox and spline models. Finally, the method is used to analyze a microarray dataset that contains gene expression measurements of favorable histology Wilms tumors.

Integrated automated particle tracking microfluidic enables high-throughput cell deformability cytometry for red cell disorders.

Investigating individual red blood cells (RBCs) is critical to understanding hematologic diseases, as pathology often originates at the single-cell level. Many RBC disorders manifest in altered biophysical properties, such as deformability of RBCs. Due to limitations in current biophysical assays, there exists a need for high-throughput analysis of RBC deformability with single-cell resolution. To that end, we present a method that pairs a simple in vitro artificial microvasculature network system with an innovative MATLAB-based automated particle tracking program, allowing for high-throughput, single-cell deformability index (sDI) measurements of entire RBC populations. We apply our technology to quantify the sDI of RBCs from healthy volunteers, Sickle cell disease (SCD) patients, a transfusion-dependent beta thalassemia major patient, and in stored packed RBCs (pRBCs) that undergo storage lesion over 4 weeks. Moreover, our system can also measure cell size for each RBC, thereby enabling 2D analysis of cell deformability vs cell size with single cell resolution akin to flow cytometry. Our results demonstrate the clear existence of distinct biophysical RBC subpopulations with high interpatient variability in SCD as indicated by large magnitude skewness and kurtosis values of distribution, the "shifting" of sDI vs RBC size curves over transfusion cycles in beta thalassemia, and the appearance of low sDI RBC subpopulations within 4 days of pRBC storage. Overall, our system offers an inexpensive, convenient, and high-throughput method to gauge single RBC deformability and size for any RBC population and has the potential to aid in disease monitoring and transfusion guidelines for various RBC disorders.

Phospholipase A2 Receptor Antibody IgG4 Subclass Improves Sensitivity and Specificity in the Diagnosis of Idiopathic Membranous Nephropathy.

AIMS: The aim of this study was to develop a new method for detecting anti-phospholipase A2 receptor-IgG4 to improve the sensitivity and specificity in the diagnosis of idiopathic membranous nephropathy (IMN). METHODS: A highly sensitive quantitative assay was developed for the detection of serum anti-phospholipase A2 receptor-IgG4 with europium chelation by time-resolved fluoroimmunoassay (TRFIA), and a mouse anti-human IgG4 tracer was prepared using europium chelation for detection. The specificity and sensitivity of anti-phospholipase A2 receptor-IgG4 in the diagnosis of IMN were further assessed in patients with different kidney diseases. RESULTS: The detection limit of anti-PLA2R-IgG4 was 0.69 ng/mL. The measurement range of anti-PLA2R-IgG4 TRFIA was 0.69-2,500 ng/mL. Mean serum anti-PLA2R-IgG4 was 21.27 ± 15.15 ng/mL in 45 healthy volunteers, 31.08 ± 18.17 ng/mL in 29 IgA nephropathy patients, 49.10 ± 34.32 ng/mL in 8 lupus nephropathy patients, and 10,324.11 ± 17,030.40 ng/mL in 30 IMN patients. The anti-PLA2R-IgG4 cutoff concentration was >161.2 ng/mL with the sensitivity of 90.0% and specificity of 100% in the diagnosis of IMN. However, the cutoff for other kidney diseases was lower than 161.2 ng/mL. CONCLUSION: The serum anti-phospholipase A2 receptor IgG4 detected with the method developed in this study has higher sensitivity and higher specificity than total IgG in the diagnosis of IMN.