Experimental Artifacts Research Articles

Is there a u-shaped relationship between load levels and fatigue and recovery? An examination of possible mechanisms

In a previous study, an unexpected u-shaped relationship was observed between load level and fatigue/recovery responses. Moderate load levels resulted in lower perceived discomfort, pain, and fatigue, and shorter recovery times compared to either low or high load levels. This phenomenon has been reported in other studies, but no article has examined the possible mechanisms that might explain this u-shaped relationship. In this paper, we re-examined the previously published data and found that the phenomenon does not appear to be due to the experimental artefact; the u-shape may be due to unexpectedly lower fatigue effects at moderate loads, and higher fatigue effects at lower loads. We then conducted a literature review and identified several possible physiological, perceptual, and biomechanical explanatory mechanisms. No single mechanism explains the entirety of the phenomenon. Further research is needed on the relationship between work exposures, fatigue, and recovery, and the mechanisms related to the u-shaped relationship. Practitioner summary: We examine a previously observed u-shaped relationship between load level and fatigue/recovery, where moderate force resulted in lower perceived fatigue and shorter recovery times. A u-shaped fatigue response suggests that simply minimising load levels might not be an optimal approach to reduce the risk of workplace injuries.

DecodeSTORM: A user-friendly ImageJ plug-in for quantitative data analysis in single-molecule localization microscopy

Quantitative data analysis in single-molecule localization microscopy (SMLM) is crucial for studying cellular functions at the biomolecular level. In the past decade, several quantitative methods were developed for analyzing SMLM data; however, imaging artifacts in SMLM experiments reduce the accuracy of these methods, and these methods were seldom designed as user-friendly tools. Researchers are now trying to overcome these difficulties by developing easy-to-use SMLM data analysis software for certain image analysis tasks. But, this kind of software did not pay sufficient attention to the impact of imaging artifacts on the analysis accuracy, and usually contained only one type of analysis task. Therefore, users are still facing difficulties when they want to have the combined use of different types of analysis methods according to the characteristics of their data and their own needs. In this paper, we report an ImageJ plug-in called DecodeSTORM, which not only has a simple GUI for human–computer interaction, but also combines artifact correction with several quantitative analysis methods. DecodeSTORM includes format conversion, channel registration, artifact correction (drift correction and localization filtering), quantitative analysis (segmentation and clustering, spatial distribution statistics and colocalization) and visualization. Importantly, these data analysis methods can be combined freely, thus improving the accuracy of quantitative analysis and allowing users to have an optimal combination of methods. We believe DecodeSTORM is a user-friendly and powerful ImageJ plug-in, which provides an easy and accurate data analysis tool for adventurous biologists who are looking for new imaging tools for studying important questions in cell biology.

In situ compression of micropillars under coherent X-ray diffraction: a case study of experimental and data-analysis constraints.

Micropillar compression is a method of choice to understand mechanics at small scale. It is mainly studied with electron microscopy or white-beam micro-Laue X-ray diffraction. The aim of the present article is to show the possibilities of the use of diffraction with a coherent X-ray beam. InSb micropillars in epitaxy with their pedestals (i.e. their support) are studied in situ during compression. Firstly, an experiment using a collimated beam matching the pillar size allows determination of when the sample enters the plastic regime, independently of small defects induced by experimental artefacts. A second experiment deals with scanning X-ray diffraction maps with a nano-focused beam; despite the coherence of the beam, the contributions from the pedestal and from the micropillar in the diffraction patterns can be separated, making possible a spatially resolved study of the plastic strain fields. A quantitative measurement of the elastic strain field is nevertheless hampered by the fact that the pillar diffracts at the same angles as the pedestal. Finally, no image reconstructions were possible in these experiments, either in situ due to a blurring of the fringes during loading or post-mortem because the defect density after yielding was too high. However, it is shown how to determine the elastic bending of the pillar in the elastic regime. Bending angles of around 0.3° are found, and a method to estimate the sample's radius of curvature is suggested.

Single cell preparations of Mycobacterium tuberculosis damage the mycobacterial envelope and disrupt macrophage interactions.

For decades, investigators have studied the interaction of Mycobacterium tuberculosis (Mtb) with macrophages, which serve as a major cellular niche for the bacilli. Because Mtb are prone to aggregation, investigators rely on varied methods to disaggregate the bacteria for these studies. Here, we examined the impact of routinely used preparation methods on bacterial cell envelope integrity, macrophage inflammatory responses, and intracellular Mtb survival. We found that both gentle sonication and filtering damaged the mycobacterial cell envelope and markedly impacted the outcome of infections in mouse bone marrow-derived macrophages. Unexpectedly, sonicated bacilli were hyperinflammatory, eliciting dramatically higher TLR2-dependent gene expression and elevated secretion of IL-1β and TNF-α. Despite evoking enhanced inflammatory responses, sonicated bacilli replicated normally in macrophages. In contrast, Mtb that had been passed through a filter induced little inflammatory response, and they were attenuated in macrophages. Previous work suggests that the mycobacterial cell envelope lipid, phthiocerol dimycocerosate (PDIM), dampens macrophage inflammatory responses to Mtb. However, we found that the impact of PDIM depended on the method used to prepare Mtb. In conclusion, widely used methodologies to disaggregate Mtb may introduce experimental artifacts in Mtb-host interaction studies, including alteration of host inflammatory signaling, intracellular bacterial survival, and interpretation of bacterial mutants.

Simulation-based inference of single-molecule force spectroscopy.

Single-molecule force spectroscopy (smFS) is a powerful approach to studying the microscopic mechanisms of molecular self-organization in biological cells and complex materials. However, extracting quantitative reduced models from these experiments is still challenging because coupling the molecule with the ever-present experimental measuring device introduces artifacts that blur the measurements. Performing statistical inference within the Bayesian framework is an attractive way to extract quantitative models from smFS experiments. But even minimalistic models lead to mathematically intractable likelihoods---ubiquitous in the computational sciences---that hinder standard approaches based on likelihood optimization. We develop a computational framework that performs Bayesian inference to extract reduced models based on diffusive dynamics on a free energy landscape. We build on a new generation of likelihood-free inference methods called simulation-based inference (SBI). By encoding a parametric mechanistic model into a simulator in combination with probabilistic deep learning, SBI enables us to directly estimate the Bayesian posterior, avoiding any likelihood calculation. Using synthetic data, we show how we can systematically disentangle the measurement of hidden molecular properties from experimental artifacts. By integrating physics-based parametric models with machine learning density estimation, SBI enables accurate Bayesian inference for models with an intractable likelihood. It paves the way for more complex and realistic models that would otherwise be ruled out due to their mathematical intractability. SBI is general, conceptually transparent, easy to use, and broadly applicable to other types of biophysical experiments.

Non-stationary noise analysis of whole-cell currents from CHO hERG expression systems.

The modelling literature for hERG ion channels consists of many different models that do not agree well on estimates of the open probability of the channel. The current used for the estimation of the parameters has several possible sources of noise in whole-cell current recordings: stochastic gating of ion channels; biological variability in expression and regulation of subunits and signaling; and experimental artefacts. When fitting models, noise is usually simplified and modeled as i.i.d. Gaussian noise, but in this study, we look into other possible mechanistic or statistical descriptions. Having a better noise model adds information that has been neglected up to now and should lead to a more dependable model and predictions. We aim to add information from the observed noise to test and enhance models’ descriptions of open probability by improving parameter estimation using non-stationary noise theory. This theory describes stochastic gating by assuming ion channels open/close independently of each other following a binomial distribution and predicts a quadratic relationship between the mean and variance of the number of open channels. We test this theory in experimental current measurements of potassium channels (hERG) from a CHO expression line. Moreover, we also look for other possible correlations - between the variance of the mean current and the current magnitude, voltage or time. Identifying the most relevant noise sources and adding them to our likelihood function will improve the inferences about model parameters and mechanistic modelling of the ion channels.

Is Nematicity in Cuprates Real?

In La2-xSrxCuO4 (LSCO), a prototype high-temperature superconductor (HTS) cuprate, a nonzero transverse voltage is observed in zero magnetic fields. This is important since it points to the breaking of the rotational symmetry in the electron fluid, the so-called electronic nematicity, presumably intrinsic to LSCO (and other cuprates). An alternative explanation is that it arises from extrinsic factors such as the film’s inhomogeneity or some experimental artifacts. We confront this hypothesis with published and new experimental data, focusing on the most direct and sensitive probe—the angle-resolved measurements of transverse resistivity (ARTR). The aggregate experimental evidence overwhelmingly refutes the extrinsic scenarios and points to an exciting new effect—intrinsic electronic nematicity.

Scalable and customizable parallel flow-through reactors to quantify biological processes related to contaminant attenuation by photosynthetic wetland microbial mats

Shallow, unit process open water wetlands harbor a benthic microbial mat capable of removing nutrients, pathogens, and pharmaceuticals at rates that rival or exceed those of more traditional systems. A deeper understanding of the treatment capabilities of this non-vegetated, nature-based system is currently hampered by experimentation limited to demonstration-scale field systems and static lab-based microcosms that integrate field-derived materials. This limits fundamental mechanistic knowledge, extrapolation to contaminants and concentrations not present at current field sites, operational optimization, and integration into holistic water treatment trains. Hence, we have developed stable, scalable, and tunable laboratory reactor analogs that offer the capability to manipulate variables such as influent rates, aqueous geochemistry, light duration, and light intensity gradations within a controlled laboratory environment. The design is composed of an experimentally adaptable set of parallel flow-through reactors and controls that can contain field-harvested photosynthetic microbial mats (“biomat”) and could be adapted for analogous photosynthetically active sediments or microbial mats. The reactor system is contained within a framed laboratory cart that integrates programable LED photosynthetic spectrum lights. Peristaltic pumps are used to introduce specified growth media, environmentally derived, or synthetic waters at a constant rate, while a gravity-fed drain on the opposite end allows steady-state or temporally variable effluent to be monitored, collected, and analyzed. The design allows for dynamic customization based on experimental needs without confounding environmental pressures and can be easily adapted to study analogous aquatic, photosynthetically driven systems, particularly where biological processes are contained within benthos. The diel cycles of pH and dissolved oxygen (DO) are used as geochemical benchmarks for the interplay of photosynthetic and heterotrophic respiration and likeness to field systems. Unlike static microcosms, this flow-through system remains viable (based on pH and DO fluctuations) and has at present been maintained for more than a year with original field-based materials.•Lab-scale flow-through reactors enable controlled and accessible exploration of shallow, open water constructed wetland function and applications.•The footprint and operating parameters minimize resources and hazardous waste while allowing for hypothesis-driven experiments.•A parallel negative control reactor quantifies and minimizes experimental artifacts.

Comprehensive Study in Open-Set Iris Presentation Attack Detection

Research in presentation attack detection (PAD) for iris recognition has largely moved beyond evaluation in “closed-set” scenarios, to emphasize ability to generalize to presentation attack types not present in the training data. This paper offers multiple contributions to understand and extend the state-of-the-art in open-set iris PAD. First, it describes the most authoritative evaluation to date of iris PAD. We have curated the largest publicly-available image dataset for this problem, drawing from 26 benchmarks previously released by various groups, and adding 150,000 images being released with this paper, to create a set of 450,000 images representing authentic iris and seven types of presentation attack instrument (PAI). We formulate a leave-one-PAI-out evaluation protocol, and show that even the best algorithms in the closed-set evaluations exhibit catastrophic failures on multiple attack types in the open-set scenario. This includes algorithms performing well in the most recent LivDet-Iris 2020 competition, which may come from the fact that the LivDet-Iris protocol emphasizes sequestered images rather than unseen attack types. Second, we evaluate the accuracy of five open-source iris presentation attack algorithms available today, one of which is newly-proposed in this paper, and build an ensemble method that beats the winner of the LivDet-Iris 2020 by a substantial margin. This paper demonstrates that closed-set iris PAD, when all PAIs are known during training, is a solved problem, with multiple algorithms showing very high accuracy, while open-set iris PAD, when evaluated correctly, is far from being solved. The newly-created dataset, new open-source algorithms, and evaluation protocol, all made publicly available with this paper, provide experimental artifacts that researchers can use to measure progress on this important problem.

Vapors Are Lost to Walls, Not to Particles on the Wall: Artifact-Corrected Parameters from Chamber Experiments and Implications for Global Secondary Organic Aerosol.

Atmospheric models of secondary organic aerosol (OA) (SOA) typically rely on parameters derived from environmental chambers. Chambers are subject to experimental artifacts, including losses of (1) particles to the walls (PWL), (2) vapors to the particles on the wall (V2PWL), and (3) vapors to the wall directly (VWL). We present a method for deriving artifact-corrected SOA parameters and translating these to volatility basis set (VBS) parameters for use in chemical transport models (CTMs). Our process involves combining a box model that accounts for chamber artifacts (Statistical Oxidation Model with a TwO-Moment Aerosol Sectional model (SOM-TOMAS)) with a pseudo-atmospheric simulation to develop VBS parameters that are fit across a range of OA mass concentrations. We found that VWL led to the highest percentage change in chamber SOA mass yields (high NOx: 36-680%; low NOx: 55-250%), followed by PWL (high NOx: 8-39%; low NOx: 10-37%), while the effects of V2PWL are negligible. In contrast to earlier work that assumed that V2PWL was a meaningful loss pathway, we show that V2PWL is an unimportant SOA loss pathway and can be ignored when analyzing chamber data. Using our updated VBS parameters, we found that not accounting for VWL may lead surface-level OA to be underestimated by 24% (0.25 μg m-3) as a global average or up to 130% (9.0 μg m-3) in regions of high biogenic or anthropogenic activity. Finally, we found that accurately accounting for PWL and VWL improves model-measurement agreement for fine mode aerosol mass concentrations (PM2.5) in the GEOS-Chem model.

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

Experimental Benchmarking of Redox Flow Cells

There are increasing numbers of scientific articles dedicated to developments in the field of redox flow batteries. To date it is most common to provide efficiency values as a measure of performance. However, there are no agreed standard experimental conditions for these measurements, and so their merit as a tool for comparing different innovations among research groups is put into question. In the following manuscript, various experimental precautions are outlined to reduce experimental artefacts. Original experimental measurements on vanadium flow cells, together with data from the literature, are examined to explore efficiencies and two alternative benchmarking metrics: resistivity and self-discharge current density. The sensitivity of these parameters to current density, temperature, flow rate and state-of-charge range are examined, from which it is concluded that resistivity and self-discharge current density exhibit superior properties to efficiencies for quantifying flow battery improvements.

Scanning Electron Microscopy to Study the Nucleation and Growth Phenomena in Liquid Electrolytes under Operando Conditions

Scanning Electron Microscopy (SEM), while being amongst the most widespread analytical instrumentation, is not widely used to study nucleation and growth (NG) phenomena in liquids. This is, partially due to insufficient exposure of the electrochemical research community to its capabilities. Here, we report on a simple but versatile custom-made setup for liquid phase (LP) SEM to access chemically and electrochemically driven NG processes in liquids. In addition, we will reveal the experimental artifacts and limitations of the technique related to radiation damage of the liquids. Finally, we will discuss a few recent developments in beam damage-free LP SEM imaging in liquids.

Terahertz tyrosine modes

We have measured the terahertz spectrum of pure l-tyrosine at nineteen temperatures in the range 6K to 300K using a synchrotron as the source of radiation. By fitting the temperature dependence of the observed modes with a Bose–Einstein model, we determine unequivocal low-frequency modes of l-tyrosine at absolute zero temperature occur at 1.02 ± 0.01, 1.61 ± 0.01, 1.97 ± 0.01, and 2.19 ± 0.01THz. This determination is consistent with the more reliable of the earlier measurements. We conclude that many of the recently reported features in the terahertz spectrum of l-tyrosine are experimental artefacts.

(Invited) The Long Reach of Impedance Measurements: From Flow Cells and Dielectrics to Experimental Artifacts

The motivation for this presentation is to bring into perspective experience in collecting and interpreting impedance data and put this in interesting and relevant form in front of specialists in electronic materials and processing.Impedance spectroscopy became very popular among electrochemists ever since most modern potentiostats started incorporating hardware for collecting impedance and software, for interpretation of putative equivalent circuits. The popularity stems both from usefulness of the method, when judiciously applied, and from the ease to obtain graphs suitable for pondering their meaning. In fact, the method became so commonplace that it acquired the acronym EIS which electrochemists somewhat vainly explain as the electrochemical impedance spectroscopy even though in many situations, it is spectroscopy just electrical as there may not be electrochemical processes even going on.The current turnkey potentiostats give capable electronic instrumentation to hands of people who do not need to be experts in electronic circuitry. This can lead to overinterpretation of data, particularly at higher frequencies. We will show on a case study how real-life input impedance of the instrument, which is typically and often successfully, ignored in data interpretation, can contribute to appearance of additional elements in fitted equivalent circuits.With the turnkey hardware is also provided powerful software as a tool for assignment of physical or chemical properties of the studied sample. On a case study of a dielectric electronic material with a leakage we will show how interpretation with overlooked leakage contribution leads to incorrect interpretation of material permittivity, indicating its frequency dependence.The attached figure shows impedance response of an active mass in a lead-acid battery studied for purpose of modern application for energy recuperation. This is one data set for an active lead acid mass 80 % discharged from a series of a full set of 0-100% discharged and 0-100% charged steps. The interpretation complication arises from the high frequency data (emphasized in the inset), where an inductor as an element in equivalent circuit might be called for. We will demonstrate how this response can be contributed to the real-life behavior of the impedance analyzer itself. Figure 1

(Invited) The Long Reach of Impedance Measurements: From Flow Cells and Dielectrics to Experimental Artifacts

Several ideas gained over the research involving energy conversion and storage and also teaching about these subjects is presented. In particular, dealing with data reporting and impedance interpretation of experimental artifacts is presented. Some aspects of energy conversion and storage that may bring up skepticism are also discussed.

Choice of DNA extraction method affects detection of bacterial taxa from retail chicken breast

BackgroundSequence-based methods for the detection of bacteria such as 16S rRNA amplicon sequencing and metagenomics can provide a comprehensive view of the bacterial microbiome of food. These methods rely on the detection of gene sequences to indicate the presence of viable bacteria. This indirect form of detection can be prone to experimental artefacts. Sample handling and processing are key sources of variation that require standard approaches. Extracting sufficient quantities of high quality DNA from food matrices is challenging because target bacterial species are usually minor components of the microbiota and foods contain an array of compounds that are inhibitory to downstream DNA applications. Here, three DNA extraction methods are compared for their ability to extract high quality bacterial DNA from retail chicken breast rinses, with or without enrichment. Method performance was assessed by comparing ease of use, DNA yield, DNA quality, PCR amplicon yield, and the detection of bacterial taxa by 16S rRNA amplicon sequencing.ResultsAll three DNA extraction methods yielded DNA of sufficient quantity and quality to perform quantitative PCR and 16S rRNA amplicon sequencing. The extraction methods differed in ease of use, with the two commercial kits (PowerFood, PowerSoil) offering considerable time and cost savings over a hybrid method that used laboratory reagents for lysis and commercial column based kits for further purification. Bacterial richness as determined by 16S rRNA amplicon sequencing was similar across the three DNA extraction methods. However, differences were noted in the relative abundance of bacterial taxa, with significantly higher abundance of Gram-positive genera detected in the DNA samples prepared using the PowerFood DNA extraction kit.ConclusionThe choice of DNA extraction method can affect the detection of bacterial taxa by 16S rRNA amplicon sequencing in chicken meat rinses. Investigators should be aware of this procedural bias and select methods that are fit for the purposes of their investigation.

Contextuality, Complementarity, Signaling, and Bell Tests

This is a review devoted to the complementarity–contextuality interplay with connection to the Bell inequalities. Starting the discussion with complementarity, I point to contextuality as its seed. Bohr contextuality is the dependence of an observable’s outcome on the experimental context; on the system–apparatus interaction. Probabilistically, complementarity means that the joint probability distribution (JPD) does not exist. Instead of the JPD, one has to operate with contextual probabilities. The Bell inequalities are interpreted as the statistical tests of contextuality, and hence, incompatibility. For context-dependent probabilities, these inequalities may be violated. I stress that contextuality tested by the Bell inequalities is the so-called joint measurement contextuality (JMC), the special case of Bohr’s contextuality. Then, I examine the role of signaling (marginal inconsistency). In QM, signaling can be considered as an experimental artifact. However, often, experimental data have signaling patterns. I discuss possible sources of signaling—for example, dependence of the state preparation on measurement settings. In principle, one can extract the measure of “pure contextuality” from data shadowed by signaling. This theory is known as contextuality by default (CbD). It leads to inequalities with an additional term quantifying signaling: Bell–Dzhafarov–Kujala inequalities.

Comprehensive Multi-compartment Sampling for Quantification of Long-Term Accumulation of PAHs in Soils.

Long-term accumulation in the soils of ubiquitous organic pollutants such as many polycyclic aromatic hydrocarbons (PAHs) depends on deposition from the atmosphere, revolatilization, leaching, and degradation processes such as photolysis and biodegradation. Quantifying the phase distribution and fluxes of these compounds across environmental compartments is thus crucial to understand the long-term contaminant fate. The gas-phase exchange between soil and atmosphere follows chemical fugacity gradients that can be approximated by gas-phase concentrations, yet which are difficult to measure directly. Thus, passive sampling, measured sorption isotherms, or empirical relationships to estimate sorption distribution have been combined in this study to determine aqueous (or gas) phase concentrations from measured bulk concentrations in soil solids. All these methods have their strengths and weaknesses but agree within 1 order of magnitude except for ex situ passive samplers employed in soil slurries, which estimated much lower concentrations in soil water and gas likely due to experimental artifacts. In field measurements, PAH concentrations determined in the atmosphere show a pronounced seasonality with some revolatilization during summer and gaseous deposition during winter, but overall dry deposition dominates annual mean fluxes. The characteristic patterns of PAHs in the different phases (gas phase, atmospheric passive samplers, bulk deposition, and soil solids) confirm the expected compound-specific distribution pattern and behavior. Since revolatilization fluxes in summer are only minor and wet and dry deposition is ongoing, our results clearly show that the PAH loads in topsoils will continue to increase.

Essay of Different Proportion of Protein on Growth of juvenile Distichodus antonii schilthius 1891.l. In vivo in Kisangani (D. R. Congo.)

The present work was carried out in 201 at Facultural Institute of Agronomic Science of Yangambi in the province of Tshopo (RDC) and focuses on the Essay of different proportion of protein on growth of juvenile Distichodus antonii schilthius 1891.l. In vivo in Kisangani (D. R. Congo.) The objective pursued by this work was of study the performance of growth of juvenile of Distichodus antonii schilthius vivo in. Methodology and results: It resulted from the study that Distichodus antonii has doubled weight during all the experience. According to the t test of STUDENT calculated between the gain of body mass of fish fed with the food R1 continent 300% of protein and the R2 continent 25 % of protein showed a non significant difference (P<0,05). The SGR (Specific Growth Rate ‘‘SGR’’) appeared meaningfully and significantly correlated to the fed. The results of mortality rate during this experience did not seem being correlated to the different diet but rather to the manipulation of fish and other experimental protocols artefacts. The protein content of the carcasses of Distichodus varied of 117, 40% for the food R1 and 135, 84% for the food R2. The diet R2 appeared performing compared to the diet R1 according to body protein gain by unit of consumed protein and for the weight gain by unit of consumed protein by Distichodus antonii.