Systematic Quantification Research Articles

Resolving morphogenesis into quantifiable cell behaviours.

Morphogenesis is extremely diverse, but its systematic quantification to determine the physical mechanisms that produce different phenotypes is possible by quantifying the underlying cell behaviours. These are limited and definable: they consist of cell proliferation, orientation of cell division, cell rearrangement, directional matrix production, cell addition/subtraction and cell size/shape change. Although minor variations in these categories are possible, in sum they capture all possible morphogenetic behaviours. This article summarises these processes, discusses their measurement, and highlights some salient examples.

Preprint Highlight: Automatic detection of spatiotemporal signaling patterns in cell collectives.

Propagation of signal between cells drives many biological processes, but the field lacks systematic quantification methods. This study presents Automatic Recognition of COllective Signalling (ARCOS), a general-purpose computational method to visualize and quantify intercellular propagation of signaling events. The method detects single-cell signaling activation events, groups these events across space and time, and extracts quantitative measurements of the spatiotemporal dynamics of collective signaling events. The authors demonstrated the application of ARCOS on diverse experimental systems, with implementation and documentation publicly available in R and Python and as a NAPARI plugin. ARCOS could be used to explore and decipher rules governing emergent collective cell dynamics.

Nano-porosity effects on corrosion rate of Zr alloys using nanoscale microscopy coupled to machine learning

Porosity throughout the zirconium oxide films plays a crucial role in the corrosion behavior and oxidation kinetics of Zr alloys, as it likely provides pathways for oxidizing and hydriding species through the oxide. In addition, it is known that substrate texture can affect the corrosion rate, although the detailed mechanisms are unclear. In this work, Zircaloy-4 was oxidized for up to 120 days at 260 and 360 °C in autoclave. Nano porosity was characterized by transmission electron microscope and precisely quantified by both manual counting as well as a newly developed, grayscale-value-difference-based, machine learning method. The oxide/substrate crystal structure, including suboxide and oxide phases, was investigated by ASTAR and directly correlated to the local pore density. The pore density shows a complex evolution as functions of oxide and metal grain orientations, oxide depth, temperature, and exposure time. Corrosion rate, substrate texture, and oxide texture are shown to affect pore density throughout the pre-transition zirconium oxide films. Two oxide growth modes (lattice-match and stress-driven) were studied, and the latter one was found to have much better resistance to corrosion and pore formation. The development of ML-based method enables a high-throughput measurement of nanopores in ZrO2, enabling rapid and systematic quantification of pore density in multiple oxides formed at different exposure times, temperatures, and substrate orientations.

Microbial containment device: A platform for comprehensive analysis of microbial metabolism without sample preparation.

Metabolomics is a mainstream strategy for investigating microbial metabolism. One emerging application of metabolomics is the systematic quantification of metabolic boundary fluxes – the rates at which metabolites flow into and out of cultured cells. Metabolic boundary fluxes can capture complex metabolic phenotypes in a rapid assay, allow computational models to be built that predict the behavior of cultured organisms, and are an emerging strategy for clinical diagnostics. One advantage of quantifying metabolic boundary fluxes rather than intracellular metabolite levels is that it requires minimal sample processing. Whereas traditional intracellular analyses require a multi-step process involving extraction, centrifugation, and solvent exchange, boundary fluxes can be measured by simply analyzing the soluble components of the culture medium. To further simplify boundary flux analyses, we developed a custom 96-well sampling system—the Microbial Containment Device (MCD)—that allows water-soluble metabolites to diffuse from a microbial culture well into a bacteria-free analytical well via a semi-permeable membrane. The MCD was designed to be compatible with the autosamplers present in commercial liquid chromatography-mass spectrometry systems, allowing metabolic fluxes to be analyzed with minimal sample handling. Herein, we describe the design, evaluation, and performance testing of the MCD relative to traditional culture methods. We illustrate the utility of this platform, by quantifying the unique boundary fluxes of four bacterial species and demonstrate antibiotic-induced perturbations in their metabolic activity. We propose the use of the MCD for enabling single-step metabolomics sample preparation for microbial identification, antimicrobial susceptibility testing, and other metabolic boundary flux applications where traditional sample preparation methods are impractical.

Remote sensing of broad-scale controls on large river anabranching

River patterns reflect complex geomorphological processes and affect ecosystems and human development along floodplains. Physical controls on anabranching development have been studied primarily at local scales on relatively small rivers (i.e., discharge <1000 m3 s−1). However, there has been little systematic quantification of river anabranching (development of stable multiple channels) for large rivers globally. Here, we use remote sensing, cloud computing, and geospatial analysis to explore the importance of water surface slope, floodplain topography, sediment supply, substrate lithology, and permafrost to anabranching throughout 20 of the world's largest river basins. We use Landsat-derived surface water extent to compute an anabranching index (Ai) for ∼1 M km of river reaches, and compare it with global datasets of water surface slope, available floodplain extent, substrate lithology, and permafrost. We find that ∼49 ± 19% of large-river mainstems are anabranching, ranging from at least ∼17% (Mekong) to as much as ∼84% (Ob’). At the basin scale, anabranching channels comprise at least ∼17% (Yenisey) to as much as ∼55% (Kolyma) of all Landsat-observable river reaches, with a mean global value of 35 ± 11%. Anabranching channel patterns are most commonly associated with low water surface slope (normalized slope < 0.2; absolute slope < 0.2 m km−1) accompanying wide floodplains (normalized floodplain width > 0.6; absolute width > 42 km). Cross-sectionally averaged channel width increases in the most intensely anabranching reaches, suggesting net sediment storage due to reduced stream power. Unconsolidated sedimentary substrates promote both the prevalence and intensity of anabranching, whereas the presence of permafrost enhances intensity only. Overall, our results identify pervasive channel anabranching and some important control mechanisms throughout the world's large river basins, with strong implications for satellite-based discharge retrievals. We conclude that global analyses afforded by remote sensing and cloud computing offer additional, complementary approaches to traditional field-based approaches for understanding large river geomorphic processes and channel forms.

Design, development and utility validation of TIPA: a tool for inspection performance assessment

Objectives. Workplace inspection supports improving the working environment. Changes in workplaces following inspections are construed as the inspection's outcome. This study aimed to develop a tool for inspection performance assessment (TIPA) based on identified inspection prerequisites and evaluate the tool's appropriateness for performance assessment. Methods. Occupational safety and health experts ranked the prerequisites for effective inspection performance, based on their experiences and perception of importance of the prerequisites. The outcome formed the basis for weighting and assignment of values to the prerequisite subgoals. An assessment tool interface, with which inspectors can assess their workplace inspection performance was designed. Inspectors from different national authorities provided feedback on the tool's appropriateness for measuring inspection performance. Results. Results showed much agreement between the inspectors. A five-level performance consideration based on inspection performance index attained was implemented. High average ratings for the test criteria were obtained, with high inter-rater consistency, and reliability. Conclusion. TIPA provides a systematic inspection performance quantification supporting inspectors' self-actualization, improving performance. Furthermore, the tool's generality allows for use irrespective of the inspection area without affecting inspection areas' specificity adjustments. In addition, the ease of use adds to its utility, with agreement on the tool's appropriateness for inspection performance assessment.

Quantifying research interests in 7,521 mammalian species with h-index: a case study.

BackgroundTaxonomic bias is a known issue within the field of biology, causing scientific knowledge to be unevenly distributed across species. However, a systematic quantification of the research interest that the scientific community has allocated to individual species remains a big data problem. Scalable approaches are needed to integrate biodiversity data sets and bibliometric methods across large numbers of species. The outputs of these analyses are important for identifying understudied species and directing future research to fill these gaps.FindingsIn this study, we used the species h-index to quantity the research interest in 7,521 species of mammals. We tested factors potentially driving species h-index, by using a Bayesian phylogenetic generalized linear mixed model (GLMM). We found that a third of the mammals had a species h-index of zero, while a select few had inflated research interest. Further, mammals with higher species h-index had larger body masses; were found in temperate latitudes; had their humans uses documented, including domestication; and were in lower-risk International Union for Conservation of Nature Red List categories. These results surprisingly suggested that critically endangered mammals are understudied. A higher interest in domesticated species suggested that human use is a major driver and focus in mammalian scientific literature.ConclusionsOur study has demonstrated a scalable workflow and systematically identified understudied species of mammals, as well as identified the likely drivers of this taxonomic bias in the literature. This case study can become a benchmark for future research that asks similar biological and meta-research questions for other taxa.

Establishing reduced-order process-structure linkages from phase field simulations of dendritic grain growth during solidification

Establishing a rigorous quantitative relationship between solidification parameters and microstructure is critical for facilitating the fabrication of metallic components with desired properties. Conventional approaches are time and effort intensive and lack a rigorous framework for the systematic and accurate quantification of microstructure. In this study, a novel data science approach is applied to extract high-value, computationally low-cost process-structure linkages from phase field simulations of dendritic grain growth during solidification. Reduced-order measures, which are adequate for identifying the salient features of microstructures and evaluating the effects of solidification process parameters, are obtained through two-point statistics and principal component analysis. Building on these reduced-order measures, computationally efficient surrogate models are established using various regression methods. It is demonstrated that the surrogate model with the best predictive performance can provide good predictions of not only the reduced-order measures but also the two-point statistics. Moreover, it is found that some reduced-order measures exhibit very complex relations with process parameters, which results in poor prediction accuracy. Compared with discarding the features with inaccurately predicted values, including them may lead to worse recovery of higher-order microstructure statistics. These results highlight the importance of microstructure feature selection in the improvement of prediction accuracy.

A New Enthalpy of Formation Test Set Designed for Organic Fluorine Containing Compounds (Adv. Theory Simul. 8/2022)

A New Enthalpy of Formation Test Set for Finding Organic Fluorine Containing Compounds Density functional theory often performs worse predicting gas phase enthalpy of formation for fluorine compounds than it does for other systems. The numerical bias somewhat lacks a systematic quantification; the evaluation of various commonly used computational levels will facilitate research on fluorine chemistry. In article 2200093, Si, Yu and co-workers propose a new test set for fluorine containing compounds, and quantitatively analyze the differences induced by various computational levels and strategies.

P-615 Lack of analytical interference of dydrogesterone in progesterone immuno-assays: a multi-laboratory spike and recovery study of widespread used assays

Abstract Study question Does dydrogesterone (DYD) and its active metabolite 20-α-dihydrodydrogesterone (DHD) interfere with routinely used progesterone assays? Summary answer This multi-laboratory spike-and-recovery study does not indicate any relevant interference of DYD/DHD within routinely used progesterone assays. What is known already Progesterone (P4), a sex steroid, is measured in serum or plasma by competitive immunoassay or Liquid Chromatography mass spectrometry (LC-MS) in a variety of clinical contexts. One potential limitation of steroid hormone immunoassays is interference caused by compounds with structural similarity to the target steroid of the assay. Dydrogesterone, an orally active close stereoisomer of progesterone, is used for various indications in women’s health, including luteal phase support. To date, the potential interference of DYD/DHD with P4 immunoassays has not systematically been studied. Study design, size, duration The present systematic in-vitro study investigated potential interferences of DYD/DHD in seven widely used, commercially available P4 immunoassays and a LC-MS method over a range of concentrations of DYD/DHD and P4. The study was performed in collaboration with participants in the endocrine section of the Dutch foundation for quality assessments in medical laboratories. For each assay method, each laboratory received a set of nine blinded human plasma samples (containing different P4 and/or DYD/DHD concentrations). Participants/materials, setting, methods Routine human plasma samples were anonymized and pooled to create three graded concentration levels of progesterone (P4 high, P4 medium, P4 low). Each pooled P4 plasma sample (6-7 ml) was spiked at high, medium and “none” DYD/DHD concentration and was divided into 0.5 ml aliquots. The blinded aliquots were analyzed by seven different laboratories with their routine progesterone assay (six different immunoassays and LC-MS assay, respectively). Main results and the role of chance High, medium, and low P4 samples had concentrations of approximately 60 nmol/l progesterone, 20 nmol/l progesterone and &amp;lt;10 nmol/l (male plasma), respectively. The immuno- assays tested were Immulite 200XPI (Siemens Healthineers), Advia Centaur (Siemens Healthineers), Atellica (Siemens Healthineers), Architect I2000 (Abbott Diagnostics), Cobas 8000 (Roche Diagnostics), UniCel DxI 800 (Beckman-Coulter) and LC-MS (Agilent). The sample recovery rate (P4 result obtained by the assays tested for sample spiked with DYD/DHD, divided by the result obtained for the corresponding sample with no DYD/DHD x 100) was within a +/-10% window for the medium P4 and high P4 concentrations, but more variable for the low P4 samples. The latter is, however, attributable to high inter- and intra-method variability, especially at low P4 concentrations. The P4 plasma concentrations generally showed considerable inter-assay variability at each concentration level, with Immunlite 2000 at the lower end and Cobas 8000/801 and Dxi at the higher end of the reported results for the High and Medium P4 samples as compared to LC-MS. The study confirms the inherent method variability of P4 immunoassays casting doubts on the clinical use of P4 cut-offs to guide clinical management, especially at low concentrations. Limitations, reasons for caution Only one sample per concentration level was provided to the laboratories which didn't allow for a systematic quantification of intra-method variability. The concentrations of DYD/DHD haven't been verified by means of a validated bioanalytical method. Measurement of DYD and DHD is to date only feasible by a highly-selective LC-MS method. Wider implications of the findings The present study is strongly indicative that relevant interference of DYD/DHD does not exist. This finding implies that a clinician can reliably distinguish P4 concentrations from DYD/DHD concentrations in a blood sample within a routine care-setting. Trial registration number not applicable

Systematic Quantification of Waste Compositions: A Case Study for Waste of Electric and Electronic Equipment Plastics in the European Union

Waste Electric and Electronic Equipment (WEEE) is a prominent and increasing waste stream for which the Commission of the European Union has put in place ambitious recycling targets. However, these targets can only be achieved by ensuring that both industry and governments develop adequate infrastructure and policies for recycling plastics in an economically and technically optimal manner. Unfortunately, a quantitative overview of WEEE plastics covering the composition of waste streams down to the product component level and describing polymer and additive concentrations, is currently lacking. This hinders policymakers and recyclers in making strategic decisions regarding WEEE plastics recycling. Therefore, a novel method is proposed in this paper combining experimental results with findings from prior literature in order to provide sound quantitative insights into the volume and characteristics of the plastics content of WEEE collected in the European Union. The provided overview was obtained through a combination of proprietary experimental data and a statistical data integration method. More specifically, over 3800 samples awere analysed through manual composition analysis, FTIR, and XRF. The obtained results were integrated with data from prior literature through a novel data integration methodology based on linear opinion pools. The obtained results confirm that distinct plastic types can be found in different product categories and that flame retardants are only found in high concentrations in specific waste streams or components thereof. Hence, the presented analysis provides a quantitative substantiation for the separate collection and treatment of specific waste streams in order to reduce the complexity of the mix of plastic types and allow for the more cost-efficient and higher quality recycling of plastics.

Monitoring One-carbon metabolism by mass spectrometry for early diagnosis of cirrhosis and HCC

Introduction: Liver cancer represents one of the most frequent causes of death by cancer, ranked as the sixth most prevalent and the second in lethality. Hepatocellular carcinoma (HCC) is the predominant type of liver cancer and presents an increasing incidence during the last years. Late diagnosis is one of the reasons explaining the low survival rate of HCC patients (5 years survival after diagnosis below 20%). Remarkably, 80% of HCC cases develop in cirrhotic tissue (1). Main risk factors for HCC are well known and include hepatitis B and C viral infections or abusive alcohol consumption. However, the underlying molecular mechanisms remain unknown and its research will lead to the characterization of new biomolecular markers for the early diagnosis, prognosis and therapy of HCC. Metabolic remodeling is a common feature among several hepatic disorders, from steatosis to HCC (2). Tumoral hepatocytes modify their metabolism to satisfy cancer’s proliferative requirements. One-carbon metabolism (OCM) plays a fundamental role maintaining the differentiation and quiescent state of hepatocytes, and is recognized as the link between intermediate metabolism and epigenetic regulation. Owing to these reasons, it might be a potential source of biomarkers for early diagnosis and prognosis of HCC. Accordingly, it has been demonstrated that some OCM enzymes are differentially expressed in murine HCC models (3). Materials and methods: We have developed a robust targeted mass spectrometry-based method, using SRM mode (Selected Reaction Monitoring), for the systematic quantification of 13 enzymes that participate in OCM. For this purpose, purified synthetic heavy standard peptides, as well as OCM recombinant proteins have been used. Sixty-four human liver samples, including 28 control samples, 21 tumoral samples and15 cirrhotic samples have been used. Results and conclusions: We have demonstrated that there is a profound remodeling of the OCM cycle in HCC versus control samples, while cirrhotic samples tend to show intermediate expression levels between both physiological situations. Machine learning- based analysis of our results suggests that monitoring a panel of functionally related proteins might be useful for future clinical developments and improve the management of HCC patients. However, further experiments with larger cohorts are required to confirm these findings. References 1) Ryerson, A. B., et al (2016). Annual Report to the Nation on the Status of Cancer, 1975-2012, featuring the increasing incidence of liver cancer. Cancer, 122(9), 1312-1337. 2) Vander Heiden, et al (2009). Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science, 324(5930), 1029-1033 3) Mora, M. I., Corrales, F. J., et al (2017). Prioritizing popular proteins in liver cancer: remodelling one-carbon metabolism. Journal of proteome research, 16(12), 4506-4514.

Stagnation point heat flux characterization under numerical error and boundary conditions uncertainty

The numerical simulation of hypersonic atmospheric entry flows is a challenging problem. Prediction of quantities of interest, such as surface heat flux and pressure, is strongly influenced by the mesh quality using conventional second-order spatial accuracy schemes while depending on boundary conditions, which may generally suffer from uncertainty. This paper illustrates one of the first systematic quantification of the numerical error and the uncertainty-induced variability for the simulation of hypersonic flows. Specifically, a mesh-convergence study using grid adaptation tools is coupled with surrogate-based approaches to Uncertainty Quantification. The illustrative example is the simulation of the EXPERT vehicle of the European Space Agency employing the US3D solver. First, we show the benefits in using mesh adaptation to simulate hypersonic flows under uncertainty. On the one hand, this practice reduces the numerical uncertainty associated with each prediction and, on the other hand, allows us to obtain a more reliable surrogate model for Uncertainty Quantification by preventing non-physical heat flux values.Secondly, we perform a sensitivity analysis to compare the numerical uncertainty associated with a given mesh with the UQ-induced variability for a specific quantity of interest. In the case considered, the impact of the numerical uncertainty turned out to be at least one order of magnitude less than the quantity of interest variability. This result indicates the possibility of using coarse and adapted meshes for future UQ studies.

Endoscopic-assisted paramedian supracerebellar infratentorial approach to the posterior portion of the third ventricle: anatomical study and surgical cases.

To date, morphometrical data providing a systematic quantification of accessibility and operability parameters to the boundaries of the posterior portion of the third ventricle (PTV) when applying an endoscopic-assisted paramedian supracerebellar infratentorial approach (EPSIA) are lacking. We performed an anatomical study and complemented our findings with surgical cases. Eight EPSIAs towards the PTV were performed in cadaveric specimens. Optimal approach angles (OA), surgical freedom (SF) and operability indexes (Oi) to the PTV boundaries were assessed. Additionally, a 54-year-old man and 33-year-old woman were operated on PTV tumors applying the EPSIA. Sagittal OA to ventricle's roof and floor was 36±1.4° and 25.5±3.5° respectively, axial OA to the ipsilateral and contralateral ventricle's wall were 9.5±1.3° and 28.5±1.6°. SF was maximal on the contralateral wall (121.2±19.3mm2), followed by the roof (112.7±18.8mm2), floor (106.6±19.2mm2) and ipsilateral wall (94.1±15.7mm2). SF was significantly lower along the ipsilateral compared the contralateral wall (P<0.01) and roof (P<0.05). Facilitated surgical maneuvers with multiangled exposure were possible up to 8.5±1.07mm anterior to ventricle's entrance, whereas surgical maneuvers were possible but difficult up to 15.25±3.7mm. Visualization of more anterior was possible up to a distance of 27±2.9mm, but surgical maneuvers were barely feasible. EPSIA enabled successful resection of both PTV tumors and postoperative course was uneventful. EPSIA can be effective for approaching the PTV, enabling surgery along all boundaries, but especially on its roof and contralateral wall. In the not-enlarged ventricle, surgical maneuvers are feasible up to the level of the Monro foramen, becoming more limited anteriorly.

Potential risks of treating bacterial infections with a combination of β-lactam and aminoglycoside antibiotics: A systematic quantification of antibiotic interactions in E. coli blood stream infection isolates.

SummaryBackgroundTreatment of Blood Stream Infections (BSIs) with a combination of a β-lactam and an aminoglycoside antibiotic is widely used in intensive care units (ICUs) around the world. However, no studies have systematically examined how these drugs interact and potentially influence the antimicrobial efficacy of the overall treatment.MethodsWe collected 500 E. coli isolates from the Uppsala University hospital that were isolated from blood of patients with suspicion of infection. Of those we tested the efficacy of combinations of 2 common β-lactam antibiotics (Ampicillin and Cefotaxime) combined with 2 common aminoglycosides (Gentamicin and Tobramycin) on 254 isolates. The efficacy of all 4 pairwise combinations in inhibiting bacterial growth was then examined on all susceptible strains. That was done by quantifying the Fractional Inhibitory index (FICi), a robust metric for antibiotic combinatorial behaviour, of all possible treatments on every strain. When non additive interactions were identified, results of the original screen were verified with time kill assays. Finally, combination behaviours were analysed for potential cross correlations.FindingsOut of the 4 antibiotic combinations screened none exhibited synergistic effects on any of the 254 strains. On the contrary all 4 exhibited important antagonistic effects on several isolates. Specifically, the combinations of AMP-GEN and CTX-GEN were antagonistic in 1.97% and 1.18% of strains respectively. Similarly, the combinations of AMP-TOB were antagonistic on 0.78% of all strains. PCA analysis revealed that an important factor on the responses to the combination treatments was the choice of a specific aminoglycoside over another. Subsequent cross correlation analysis revealed that the interaction profiles of combinations including the same aminoglycoside are significantly correlated (Spearman's cross correlation test p<0.001).InterpretationThe findings of this study elucidate potential risks of the common combination treatment for blood stream infections. They also demonstrate, previously unquantified metrics on how antibiotics in combination therapies are not interchangeable with others of the same class. Finally, they reiterate the need for case-by-case testing of antibiotic interactions in a clinical setting.FundingThis work was funded by grants to DIA from the Swedish Research Council, the Wallenberg foundation and the Swedish Strategic Research Foundation.

New systematically measured sand mining budget for the Mekong Delta reveals rising trends and significant volume underestimations

The river beds of the Mekong Delta are some of the most intensively sand mined places in the world. However, sand mining budgets remain limited to rough and indirect estimates. Here, we provide a first systematic, field-based estimation of the Mekong Delta’s sand mining budget. This budget overcomes the limitations of relying on officially declared statistics and bathymetric surveys of short channel reaches. We applied Sentinel-1 radar imagery to monitor the distribution of sand mining activities using boat metrics-driven mining intensity maps correlated with a field-based bathymetry difference map which were derived from two extensive bathymetric surveys conducted in 2014 and 2017. The two surveys cover ∼ 100 km in the Tiền River, reaching approximately 15% of the Mekong Delta. We then extrapolated the Tiền River findings to the broader Vietnamese Mekong Delta from 2015 to 2020 and measured a continuous increase of the extraction budget by ∼ 25% between 2015 (38 Mm3/yr) and 2020 (47 Mm3/yr). We estimated a total sand mining budget of 254 Mm3 during the 6-year study period with an average annual rate of ∼ 42 Mm3. Our field-based annual rates are higher than both official declarations provided and estimates from previous studies which implies that a substantial portion of the sand mining budget remains unaccounted for. Riverbed sand mining remains a key threat to the Mekong Delta as it contributes to a multitude of other environmental threats including dam construction effects on sedimentation, ongoing subsidence, sea level rise and recurring saltwater intrusion. This study offers a new approach that can be implemented elsewhere to allow for systematic monitoring and quantification of sand mining activities that are vital for assessing future projections on environmental impacts.

Quantification of Microbial Robustness in Yeast.

Stable cell performance in a fluctuating environment is essential for sustainable bioproduction and synthetic cell functionality; however, microbial robustness is rarely quantified. Here, we describe a high-throughput strategy for quantifying robustness of multiple cellular functions and strains in a perturbation space. We evaluated quantification theory on experimental data and concluded that the mean-normalized Fano factor allowed accurate, reliable, and standardized quantification. Our methodology applied to perturbations related to lignocellulosic bioethanol production showed that the industrial bioethanol producing strain Saccharomyces cerevisiae Ethanol Red exhibited both higher and more robust growth rates than the laboratory strain CEN.PK and industrial strain PE-2, while a more robust product yield traded off for lower mean levels. The methodology validated that robustness is function-specific and characterized by positive and negative function-specific trade-offs. Systematic quantification of robustness to end-use perturbations will be important to analyze and construct robust strains with more predictable functions.

Prior Signal Acquisition Software Versions for Orbitrap Underestimate Low Isobaric Mass Tag Intensities, Without Detriment to Differential Abundance Experiments.

Tandem mass tags (TMTs) enable simple and accurate quantitative proteomics for multiplexed samples by relative quantification of tag reporter ions. Orbitrap quantification of reporter ions has been associated with a characteristic notch region in intensity distribution, within which few reporter intensities are recorded. This has been resolved in version 3 of the instrument acquisition software Tune. However, 47% of Orbitrap Fusion, Lumos, or Eclipse submissions to PRIDE were generated using prior software versions. To quantify the impact of the notch on existing quantitative proteomics data, we generated a mixed species benchmark and acquired quantitative data using Tune versions 2 and 3. Intensities below the notch are predominantly underestimated with Tune version 2, leading to overestimation of the true differences in intensities between samples. However, when summarizing reporter ion intensities to higher-level features, such as peptides and proteins, few features are significantly affected. Targeted removal of spectra with reporter ion intensities below the notch is not beneficial for differential peptide or protein testing. Overall, we find that the systematic quantification bias associated with the notch is not detrimental for a typical proteomics experiment.

Melatonin Application Alleviates Stress-Induced Photosynthetic Inhibition and Oxidative Damage by Regulating Antioxidant Defense System of Maize: A Meta-Analysis.

Melatonin is effective in modulating metabolism and regulating growth and development in many plants under biotic and abiotic stress. However, there is no systematic quantification of melatonin effects on maize growth, gas exchange, chlorophyll content, and the antioxidant defense system. A meta-analysis was conducted on thirty-two currently available published articles to evaluate the effect of stress types, study types, and maize varieties on response ratio (lnRR++) of “melatonin” to “control (no melatonin)” on plant growth, enzyme activities, gas exchange parameters, and photosynthetic pigments. Our findings revealed that melatonin application overall increased plant height, leaf area, root length, fresh and dry root weight and shoot weight, superoxide dismutase (SOD), peroxide (POD), catalase (CAT), ascorbate peroxidase (APX), soluble sugar and protein, photosynthetic rate, stomatal conductance, transpiration rate, chlorophyll, and carotenoid in maize leaf under stress conditions. In contrast, melatonin application decreased the levels of hydrogen peroxide (H2O2), superoxide anion (O2−), malondialdehyde (MDA), and electrolyte leakage. The categorical meta-analysis demonstrated that melatonin application to chilling stress resulted in higher SOD activity followed by salt stress. Melatonin application to all stress types resulted in higher POD, CAT and APX activities, except Cd stress, which had no effect on POD and decreased CAT by 38% compared to control. Compared to control, melatonin resulted in lower reactive oxygen species (ROS) and electrolyte leakage under no stress, Cd, drought, salt, lead, heat, and chilling stress in all study types (pot, growth chamber, hydroponic, and field), except O2 content which was not affected in pot and growth chamber studies. It was concluded that melatonin alleviates oxidative damage by improving stress tolerance, regulating the antioxidant defense system, and increasing leaf chlorophyll content compared to control.

A predictive multiphase model of silica aerogels for building envelope insulations

This work develops a systematic uncertainty quantification framework to assess the reliability of prediction delivered by physics-based material models in the presence of incomplete measurement data and modeling error. The framework consists of global sensitivity analysis, Bayesian inference, and forward propagation of uncertainty through the computational model. The implementation of this framework on a new multiphase model of novel porous silica aerogel materials is demonstrated to predict the thermomechanical performances of a building envelope insulation component. The uncertainty analyses rely on sampling methods, including Markov-chain Monte Carlo and a mixed finite element solution of the multiphase model. Notable features of this work are investigating a new noise model within the Bayesian inversion to prevent biased estimations and characterizing various sources of uncertainty, such as measurements variabilities, model inadequacy in capturing microstructural randomness, and modeling errors incurred by the theoretical model and numerical solutions.