Quantitative Link Research Articles

Effectiveness of dapagliflozin as an insulin adjunct in type 1 diabetes: a semi-mechanistic exposure-response model.

Introduction: Dapagliflozin-induced improvement of glycemic control in patients with inadequately controlled type 1 diabetes (T1D) is complicated by the delicate balance between blood glucose and exogenous insulin. In this work, we developed a semi-mechanistic population exposure-response model using pooled patient-level data to characterize the joint effect of dapagliflozin and insulin on average daily glucose concentrations and glycated hemoglobin (HbA1c) levels in patients with T1D. Methods: A non-linear mixed-effects model was developed in Monolix (Lixoft, France) and R software (R Project, www.r-project.org) using pooled patient-level data from phase 2 and phase 3 trials (NCT01498185, NCT02460978, NCT02268214). Results: Because of the apparent lack of association between bolus insulin dose and glucose concentrations measured by continuous glucose monitoring the model was able to capture the quantitative link between basal, but not bolus, insulin dose and plasma glucose. Even so, this association remained flat, with a 50% decrease in the basal insulin dose from pretreatment level, resulting in ∼5% increase in glucose exposure. Therefore, dapagliflozin efficacy was not significantly affected by the insulin dose adjustment, with 24-week HbA1c reduction on 10-mg dapagliflozin treatment changing from -0.5 [95% CI: -0.55, -0.45] to -0.42 [95%CI: -0.48, -0.36] after adjustment. At the same time, the analysis revealed ∼2-fold steeper slope of glucose-HbA1c relationship in dapagliflozin-treated patients vs. control group, suggesting the presence of additional dapagliflozin treatment-related benefits, not explained by the dapagliflozin-mediated ∼4% increase in plasma hemoglobin levels. Finally, the efficacy of 5 and 10-mg doses, represented by the mean HbA1c reduction at week 24 of dapagliflozin treatment, was shown to be notably greater than the 1- and 2.5-mg doses. Discussion: This research is an attempt to deconvolute and reconstruct dapagliflozin-HbA1c dose-response relationship in T1D by accounting for the drug's action on both daily insulin dose and plasma glucose on a subject-level. While the model is able to adequately capture the observed data, it also revealed that the variability in CGM is poorly approximated by the variability in insulin dose alone. Furthermore, the slope of CGM/HbA1c relationship may differ depending on the population and treatment scenarios. As such, a deeper dive into the physiological mechanisms is required to better quantify the intricate network of glycemic response under dapagliflozin treatment.

Rift-induced disruption of cratonic keels drives kimberlite volcanism

Kimberlites are volatile-rich, occasionally diamond-bearing magmas that have erupted explosively at Earth’s surface in the geologic past1–3. These enigmatic magmas, originating from depths exceeding 150 km in Earth’s mantle1, occur in stable cratons and in pulses broadly synchronous with supercontinent cyclicity4. Whether their mobilization is driven by mantle plumes5 or by mechanical weakening of cratonic lithosphere4,6 remains unclear. Here we show that most kimberlites spanning the past billion years erupted about 30 million years (Myr) after continental breakup, suggesting an association with rifting processes. Our dynamical and analytical models show that physically steep lithosphere–asthenosphere boundaries (LABs) formed during rifting generate convective instabilities in the asthenosphere that slowly migrate many hundreds to thousands of kilometres inboard of rift zones. These instabilities endure many tens of millions of years after continental breakup and destabilize the basal tens of kilometres of the cratonic lithosphere, or keel. Displaced keel is replaced by a hot, upwelling mixture of asthenosphere and recycled volatile-rich keel in the return flow, causing decompressional partial melting. Our calculations show that this process can generate small-volume, low-degree, volatile-rich melts, closely matching the characteristics expected of kimberlites1–3. Together, these results provide a quantitative and mechanistic link between kimberlite episodicity and supercontinent cycles through progressive disruption of cratonic keels.

PubPredict: Prediction of progression and survival in oncology leveraging publications and early efficacy data.

In oncology/hematology early phase clinical trials, efficacies were often observed in terms of response rate, depth, timing, and duration. However, the true clinical benefits that eventually support registrational purpose are progression-free survival (PFS) and/or overall survival (OS), the follow-up of which are typically not long enough in early phase trials. This gap imposes challenges in strategies for late phase drug development. In this article, we tackle the question by leveraging published study to establish a quantitative link between early efficacy outcomes and late phase efficacy endpoints. We used solid tumor cancer as disease model. We modeled the disease course of a RECISTv1.1 assessed solid tumor with a continuous Markov chain (CMC) model. We parameterize the transition intensity matrix of a CMC model based on published aggregate-level summary statistics, and then simulate subject-level time-to-event data. The simulated data is shown to have good approximation to published studies. PFS and/or OS could be predicted with the transition intensity matrix modified given clinical knowledge to reflect various assumptions on response rate, depth, timing, and duration. The authors have built a R shiny application named PubPredict, the tool implements the algorithm described above and allows customized features including multiple response levels, treatment crossover and varying follow-up duration. This toolset has been applied to advise phase 3 trial design when only early efficacy data are available from phase 1 or 2 studies.

A General Autofluorescence Method to Characterize Polymerization Progress

AbstractAn autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium‐catalyzed ring‐opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here‐developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst‐inhibitor‐stabilized formulations. Multiple‐well analysis demonstrated suitability for future high‐throughput evaluation of formulations for thermosets. The central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.

A General Autofluorescence Method to Characterize Polymerization Progress.

An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium-catalyzed ring-opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here-developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems-without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst-inhibitor-stabilized formulations. Multiple-well analysis demonstrated suitability for future high-throughput evaluation of formulations for thermosets. The central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.

Statistically representative estimators of multi-scale surface topography: example of aluminum blasted rough samples

The topography of a rough surface determines many of its physical properties, for instance, tribology, contact mechanics, optical properties etc. Nowadays, a deep understanding of such physical phenomena requires the knowledge of the topography at appropriate length scales. Apart from performing multi-scale measurements of the surface topography, it also requires the use of proper statistical estimators for the analysis of such topography maps. Moreover, when dealing with light scattering in the visible spectral range, the scale at which the estimators of local topography properties are defined is extremely important. Here we present a multi-scale and statistical study of the surface topography of blasted aluminum samples which all have rather different visual appearance. Various statistical estimators of surface topography are examined, including estimators related to the height distribution, the lateral correlation and local topology. The combination of these various estimators unveils a scale separation between a micro-scale roughness inherited from the initial cold-rolled aluminum surface and a large scale roughness fully controlled by the blasting process. A special emphasis is given to the crucial importance of length scales in the estimation of local slopes. The present analysis establishes a quantitative link between the statistical properties of the surface topography and the blasting process used to fabricate the samples.

Early-age hydration mechanism of ternary binders: Quantitative relation between microstructure evolution and strength build-up

The goal of this study is to develop a better understanding of the working mechanisms of CACC$ acceleration of OPC in the first hour and establish a quantitative link between the progress of hydration, strength build-up and associated microstructure evolution. Monitoring the progress of reaction using isothermal calorimetry in the first few minutes of hydration is difficult owing to the limitations associated with the measurement method. We have developed a method to correct the heat data in the first minutes, which along with ICP data of elements Ca, Al and S, enables a quantification of the amounts of various phases dissolving and/or precipitating at different times after acceleration. It is concluded that strength build-up is directly proportional to heat of hydration up to a certain point, irrespective of accelerator dosage. However, beyond this point, there is a change of mechanism which is likely attributed to physical effects rather than chemical ones. Additionally, it was also found that the amount of available CA controls the rate of reaction and that the impact of CAC addition to OPC follows a decay function type heat release.

Research on Productivity Evaluation Method Based on Shale Gas Well Early Flow Stage Data

Since the accurate early gas well production regime is related to the production period and final productivity, it is crucial to make better use of early flow stage production data for gas well productivity evaluation. Absolute open flow potential (AOF) and estimated ultimate recovery (EUR) are essential parameters for evaluating the productivity of shale gas wells. This study establishes new AOF calculation methods for the early production stage. The analytical model can calculate the AOF only by using stable pressure and production data in the flowback stage, which greatly improves the efficiency of productivity evaluation. Three methods have, respectively, calculated the productivity of the shale gas wells above 3500 m in the Luzhou block. The results show that well L2-3 has the highest AOF, averaging 278.1 × 10 4 m 3 / d , whereas well Y2-8 has the lowest AOF, averaging 100.2 × 10 4 m 3 / d . Different AOF calculation methods are identified for gas wells in different stages of production. For gas wells in the initial unstable flow stage, a pseudogas production index method is recommended. A water production index analysis method, with lower evaluation results, is proposed for gas wells in the flowback stage. A modern production decline analysis method is found to be preferred for calculating the EUR of deep shale gas wells. Well L2-3 has the highest average EUR of 1.26 × 10 8 m 3 , whereas well Y2-8 has the lowest average EUR of 0.42 × 10 8 m 3 . The Blasingame method is recommended for medium-to-high-production gas wells, whereas a normalized pressure integral method is suggested for low-production wells. A strong exponential quantitative link between the AOF and the EUR shows that a fracture system’s initial productivity has a significant impact on a well’s EUR. The findings of this study enrich the productivity evaluation system, increase the accuracy of productivity evaluation results, and provide theoretical support for deep shale gas wells.

Role of vehicular emissions in urban air quality: The COVID-19 lockdown experiment.

While the decrease in air pollutant concentration during the COVID-19 lockdown is well documented, neighborhood-scale and multi-city data have not yet been explored systematically to derive a generalizable quantitative link to the drop in vehicular traffic. To bridge this gap, high spatial resolution air quality and georeferenced traffic datasets were compiled for the city of London during three weeks with significant differences in traffic. The London analysis was then augmented with a meta-analysis of lower-resolution studies from 12 other cities. The results confirm that the improvement in air quality can be partially attributed to the drop of traffic density, and more importantly quantifies the elasticity (0.71 for NO2 & 0.56 for PM2.5) of their linkages. The findings can also inform on the future impacts of the ongoing shift to electric vehicles and micro-mobility on urban air quality.

Reversed‐phase high‐performance liquid chromatography analytical method development and validation for cefepime and sulbactam injection formulation assay: A quality by design approach

AbstractA trustworthy high‐performance liquid chromatography approach for the simultaneous measurement of cefepime and sulbactam was created using quality by design. Finding reliable chromatographic settings for quality peaks and suitable component separation within a manageable run time was the key objective. Critical quality attributes for risk measurement were evaluated. To create an analytical design space and create a control strategy, the quantitative link between critical material attributes and critical quality attributes was built. Acetonitrile volume, trimethylamine volume, and flow rate were the three independent parameters considered in the mathematical models. Acetonitrile:high‐performance liquid chromatography water:triethylamine and pH 6.0, adjusted with orthophosphoric acid (50.0:50:0.15, v/v/v) as the mobile phase at 1.1 ml/min, were the ideal and anticipated conditions. We obtained appropriate baseline separation of both medications in about 10 min using these ideal conditions. The main determinant of the perturbation plot responses was found to be the quantity of acetonitrile. At all three levels, the percent recoveries for both medications ranged from 99% to 99.68%. Relative standard deviations were less than 2% for both drugs' intermediate accuracy and repeatability. A straightforward, precise, and repeatable high‐performance liquid chromatography method for regular quality control testing was created as a consequence.

Stoichiometry driven tuning of physical properties in epitaxial Fe3-xCrxO4 thin films

Tuning magnetic and electronic transport properties in spinel oxides requires a faithful description between chemical composition and cation site-occupation. Here this challenge is addressed using Fe3-xCrxO4 thin films grown by oxygen-assisted molecular-beam epitaxy within a wide range of composition (0.0 ≤ x ≤ 1.2). Spectroscopic measurements (e.g., X-ray magnetic circular dichroism), refined by theoretical simulations (e.g., crystal field multiplet), are performed to establish a quantitative link between chromium content, Fe2+/Fe3+ site-occupation and macroscopic physical properties of the layers. It is found that Fe3-xCrxO4 thin films (i) delay the transition from inverse to normal spinel configuration with increasing chromium content and (ii) promote collinear spin structure, at odds with bulk material. As a result, strong antiferromagnetic interactions are preserved between spins in tetrahedral and octahedral spinel sublattices, so that chromium-rich thin films exhibit Curie temperatures above room temperature and higher magnetization. Electron hopping is also favored by this singular cation distribution and electronic band gap is smaller than expected for these thin films. The cation site-occupation is therefore a key feature to consider for applications of Fe3-xCrxO4 thin films in spintronics and photocatalysis, as it enables manipulation of magnetic properties (Curie temperature and magnetization) and band gap engineering.

A computational study of AE signal due to fiber break and fiber matrix debonding in model composite

Acoustic emission monitoring is a useful method to deal with detection and identification of damage in composite materials during mechanical tests. From an experimental point of view, it is not straightforward to establish a quantitative link between the damage sources and AE signals. Modeling and numerical simulations appear as a promising way to reach this objective. In this study, Finite Elements Modeling (FEM) was used to simulate AE signals due to fiber break and fiber/matrix debonding in a model carbon fiber composite. A specimen made of a single carbon fiber and epoxy matrix was used to experimentally validate the simulated fiber break AE signals. The objective was to compare the AE signals from a validated fiber break simulation (Fig. 1a) to the AE signals obtained from fiber/matrix debonding (with several models) and fiber break obtained in several media and to discuss the capability to detect and identify each source (Fig. 1b). The influence of the type of sensor, specimen geometry and AE source location were also studied. The proposed model was extended to identify the main parameters that influence the acoustic emission signatures. These validated results open the way to combine the experimental and the simulated data to generate a library in order to identify real-time damage mechanisms. Fig. 1: (a) Amplitude and roll-off frequency vs. source/sensor distance for experimental signals and numerical signals. (b)Evolution of Partial Power PP1 [0–125 kHz] as a function of amplitude obtained with a nano 30 sensor for several sources. Fiber break and debonding (L = 20 μm or 100 μm). EWGAE 35, Ljubljana, Slovenia, 13th – 16th Sep. www.ewg

Predictive link between systemic metabolism and cytokine signatures in the brain of apolipoprotein E ε4 mice

The ε4 variant of apolipoprotein E (APOE) is the strongest and most common genetic risk factor for Alzheimer's disease (AD). While the mechanism of conveyed risk is incompletely understood, promotion of inflammation, dysregulated metabolism, and protein misfolding and aggregation are contributors to accelerating disease. Here we determined the concurrent effects of systemic metabolic changes and brain inflammation in young (3-month-old) and aged (18-month-old) male and female mice carrying the APOE4 gene. Using functional metabolic assays alongside multivariate modeling of hippocampal cytokine levels, we found that brain cytokine signatures are predictive of systemic metabolic outcomes, independent of AD proteinopathies. Male and female mice each produce different cytokine signatures as they age and as their systemic metabolic phenotype declines, and these signatures are APOE genotype dependent. Ours is the first study to identify a quantitative and predictive link between systemic metabolism and specific pathological cytokine signatures in the brain. Our results highlight the effects of APOE4 beyond the brain and suggest the potential for bi-directional influence of risk factors in the brain and periphery.

Influence of uncertainty in geosynthetic stiffness on deterministic and probabilistic analyses using analytical solutions for three reinforced soil problems

The paper examines the quantitative influence of uncertainty in the estimate of geosynthetic reinforcement stiffness on numerical outcomes using analytical solutions for a) the maximum outward facing deformation in mechanically stabilized earth (MSE) walls, b) maximum reinforcement tensile loads and strain in MSE walls under operational conditions, and c) the mobilized reinforcement stiffness in a geosynthetic layer used to reinforce a fill over a void. The stiffness of the reinforcement is modelled using an isochronous two-parameter hyperbolic load-strain model. A linear relationship between isochronous stiffness and the ultimate tensile strength of the reinforcement is used to estimate reinforcement stiffness when product-specific creep data are not available at time of design. Solution outcomes are presented deterministically and probabilistically. The quantitative link between nominal factor of safety used in deterministic working stress design practice and reliability index is provided. The latter is preferred in modern performance-based design to quantify margins of safety within a probabilistic framework. Finally, the paper highlights the practical benefit of using product-specific isochronous secant stiffness data when available, rather than estimates of isochronous stiffness values based on reinforcement type or pooled data.

Quantifying the Impact of Charge Rate and Number of Cycles on Structural Degeneration of Li-Ion Battery Electrodes

A quantitative link between crack evolution in lithium-ion positive electrodes and the degrading performance on cells is not yet well established nor is any single technique capable of doing so widely available. Here, we demonstrate a widely accessible high-throughput approach to quantifying crack evolution within electrodes. The approach applies super-resolution scanning electron microscopy (SEM) imaging of cross-sectioned NMC532 electrodes, followed by segmentation and quantification of crack features. Crack properties such as crack intensity, crack width and length are quantified as a function of charge rate (1C, 6C, and 9C) and cycle number (25, 225, and 600 cycles). Hundreds of particles are characterized for statistical confidence in the quantitative crack measurements. The data on crack evolution is compared to electrochemical data from full cells and half cells with the NMC532 positive electrodes. We show that while crack evolution strongly correlates with capacity fade in the first 25 cycles, it does not correlate well for the following hundreds of cycles indicating that cracking may not be the dominant cause of capacity fade throughout the cycle-life of cells.

Coordination of gene expression with cell size enables Escherichia coli to efficiently maintain motility across conditions

To swim and navigate, motile bacteria synthesize a complex motility machinery involving flagella, motors, and a sensory system. A myriad of studies has elucidated the molecular processes involved, but less is known about the coordination of motility expression with cellular physiology: In Escherichia coli, motility genes are strongly up-regulated in nutrient-poor conditions compared to nutrient-replete conditions; yet a quantitative link to cellular motility has not been developed. Here, we systematically investigated gene expression, swimming behavior, cell growth, and available proteomics data across a broad spectrum of exponential growth conditions. Our results suggest that cells up-regulate the expression of motility genes at slow growth to compensate for reduction in cell size, such that the number of flagella per cell is maintained across conditions. The observed four or five flagella per cell is the minimum number needed to keep the majority of cells motile. This simple regulatory objective allows E. coli cells to remain motile across a broad range of growth conditions, while keeping the biosynthetic and energetic demands to establish and drive the motility machinery at the minimum needed. Given the strong reduction in flagella synthesis resulting from cell size increases at fast growth, our findings also provide a different physiological perspective on bacterial cell size control: A larger cell size at fast growth is an efficient strategy to increase the allocation of cellular resources to the synthesis of those proteins required for biomass synthesis and growth, while maintaining processes such as motility that are only needed on a per-cell basis.

Kinematics of persistent random walkers with two distinct modes of motion.

We study the stochastic motion of active particles that undergo spontaneous transitions between two distinct modes of motion. Each mode is characterized by a velocity distribution and an arbitrary (anti)persistence. We present an analytical formalism to provide a quantitative link between these two microscopic statistical properties of the trajectory and macroscopically observable transport quantities of interest. For exponentially distributed residence times in each state, we derive analytical expressions for the initial anomalous exponent, the characteristic crossover time to the asymptotic diffusive dynamics, and the long-term diffusion constant. We also obtain an exact expression for the time evolution of the mean square displacement over all timescales and provide a recipe to obtain higher displacement moments. Our approach enables us to disentangle the combined effects of velocity, persistence, and switching probabilities between the two states on the kinematics of particles in a wide range of stochastic active or passive processes and to optimize the transport quantities of interest with respect to any of the particle dynamics properties.

Environmental dependence of the molecular cloud lifecycle in 54 main-sequence galaxies

ABSTRACT The processes of star formation and feedback, regulating the cycle of matter between gas and stars on the scales of giant molecular clouds (GMCs; ∼100 pc), play a major role in governing galaxy evolution. Measuring the time-scales of GMC evolution is important to identify and characterize the specific physical mechanisms that drive this transition. By applying a robust statistical method to high-resolution CO and narrow-band H α imaging from the PHANGS survey, we systematically measure the evolutionary timeline from molecular clouds to exposed young stellar regions on GMC scales, across the discs of an unprecedented sample of 54 star-forming main-sequence galaxies (excluding their unresolved centres). We find that clouds live for about 1−3 GMC turbulence crossing times (5−30 Myr) and are efficiently dispersed by stellar feedback within 1−5 Myr once the star-forming region becomes partially exposed, resulting in integrated star formation efficiencies of 1−8 per cent. These ranges reflect physical galaxy-to-galaxy variation. In order to evaluate whether galactic environment influences GMC evolution, we correlate our measurements with average properties of the GMCs and their local galactic environment. We find several strong correlations that can be physically understood, revealing a quantitative link between galactic-scale environmental properties and the small-scale GMC evolution. Notably, the measured CO-visible cloud lifetimes become shorter with decreasing galaxy mass, mostly due to the increasing presence of CO-dark molecular gas in such environment. Our results represent a first step towards a comprehensive picture of cloud assembly and dispersal, which requires further extension and refinement with tracers of the atomic gas, dust, and deeply embedded stars.

A new polarization direction measurement via local Radon transform and error correction

Vectorial optical field-based spatially polarization modulation has been widely studied for polarization measurement due to its simple system structure. In this system, the polarization information is encoded in the irradiance image, and polarization measurement can be realized by image processing. The classical image processing methods could not meet the increasing demand of practical applications due to their poor computational efficiency. To address this issue, a new image processing method, combining the rapidity of local radon transform (LRT) and the precision of error correction (EC), was proposed in this paper. Firstly, the polarization direction of the light was coarsely estimated from pixels on several circles. Then, the LRT of the input image was completed while the coarsely estimated direction was the center angle for LRT. Finally, the EC was conducted to get the accurate direction depending on the quantitative link between the error of the coarse estimation and the correlation between the LRTs. Experiments on synthetic and real data demonstrate that, compared to the other state-of-the-art methods, our proposed algorithm is more robust and less time-consuming.

On the use of kinetic energy balance for the volumetric identification of drag sources of a blunt body. Application to road vehicles

A volumetric identification of drag sources is proposed using the Reynolds equation for the integral mean momentum and mean flow kinetic energy balance. This methodology works independently of the turbulence model used in CFD and relies on a physical interpretation. The approach, developed in the context of automotive engineering, is of general use. A road vehicle is indeed a complex multi-scale geometry and all the flow regions are interacting. As far as the kinetic energy of the mean flow is concerned, the main volumetric loss is production of turbulent kinetic energy at all relevant sub-scales of the body. The quantitative link to the power of the mean drag force is derived from first principles. For practical applications, the volume integral used to compute the volumetric losses can be decomposed in user-defined regions and integrated into optimization loops. Indeed, if losses in a given flow region are minimized, consequences can be precisely and quantitatively evidenced for all other regions. Applications to a model two-dimensional test case and a real car geometry are discussed.