Transport Model Research Articles

Upgrading In Vitro Digestion Protocols with Absorption Models

Intestinal digestion and absorption are complex processes; thus, it is a challenge to imitate them realistically. There are numerous approaches available, with different disadvantages and advantages. The simplest methods to mimic absorption are the non-cell-based transport models but these lack important characteristics of enterocytes of the intestine. Therefore, the most often used method is to measure absorption through viable mammalian cells (most commonly Caco-2 cells, cultured on membrane insert plates), which not only assures the incorporation of brush border enzymes (responsible for the final digestion of peptides and disaccharides), it also simulates the absorption process. This means that influx/efflux transporter-facilitated transport, carrier-mediated transport, endocytosis, and transcytosis is also imitated besides passive diffusion. Still, these also lack the complexity of intestinal epithelium. Organoids or ex vivo models are a better approach if we want to attain precision but the highest accuracy can be achieved with microfluidic systems (gut-on-a-chip models). We propose that more research is necessary, and food absorption should also be studied on gut-on-a-chips, especially with fragmented organoids. Our review supports the choices of a proper intestinal epithelium model, which may have a key role in functional food development, nutrition studies, and toxicity assessment.

Numerical investigation on effects of swirl and offset ratio on hydro-thermal transport phenomena and irreversibility generation of turbulent jet flow

The combined influence of offset jet and imposition of swirling motion is crucial because many macro-level electronic devices and heat exchanger systems involve such types of configuration. The mutual impact of the offset ratio and swirl number along with a range of Reynolds numbers is taken into account to briefly discuss the primary laws (first and second) of thermodynamics associated with the prescribed problem. An open channel with variable nozzle height is assumed under forced convective flow conditions. The flow physics associated with the prescribed problem has been solved numerically with an improvised [Formula: see text] turbulent (shear stress transport) model. The intricate interplay between the swirl intensity and the offset upon the thermal and entropy generation characteristics has been revealed in the average Nusselt number, local variation of skin friction coefficient, and total entropy generation by varying the distinct embedded control parameters. The results indicate that a higher range of Reynolds number leads to a high value of average Nusselt number unrelatedly of swirl number and offset ratio. However, the improvement of thermal performance does not depend only upon the heat transfer characteristics but also the total irreversibility should be optimized. In that regard, a swirl ratio of 0.5 with an offset ratio of 3 provides optimized configurations irrespective of all other parameters.

Mitigating Disparate Elevation Differences between Adjacent Topobathymetric Data Models Using Binary Code

Integrating coastal topographic and bathymetric data for creating regional seamless topobathymetric digital elevation models of the land/water interface presents a complex challenge due to the spatial and temporal gaps in data acquisitions. The Coastal National Elevation Database (CoNED) Applications Project develops topographic (land elevation) and bathymetric (water depth) regional scale digital elevation models by integrating multiple sourced disparate topographic and bathymetric data models. These integrated regional models are broadly used in coastal and climate science applications, such as sediment transport, storm impact, and sea-level rise modeling. However, CoNED’s current integration method does not address the occurrence of measurable vertical discrepancies between adjacent near-shore topographic and bathymetric data sources, which often create artificial barriers and sinks along their intersections. To tackle this issue, the CoNED project has developed an additional step in its integration process that collectively assesses the input data to define how to transition between these disparate datasets. This new step defines two zones: a micro blending zone for near-shore transitions and a macro blending zone for the transition between high-resolution (3 m or less) to moderate-resolution (between 3 m and 10 m) bathymetric datasets. These zones and input data sources are reduced to a multidimensional array of zeros and ones. This array is compiled into a 16-bit integer representing a vertical assessment for each pixel. This assessed value provides the means for dynamic pixel-level blending between disparate datasets by leveraging the 16-bit binary notation. Sample site RMSE assessments demonstrate improved accuracy, with values decreasing from 0.203–0.241 using the previous method to 0.126–0.147 using the new method. This paper introduces CoNED’s unique approach of using binary code to improve the integration of coastal topobathymetric data.

Wildfire-related PM2.5 and cause-specific cancer mortality

Wildfires have devastating effects on society and public health. However, little evidence from population-based cohort has been performed to analyze the relationship of wildfire-related PM2.5, an important component of wildfire smoke, with cancer-specific mortality. We aimed to explore this relationship and identify vulnerable populations in UK with lower levels of wildfire-related PM2.5 exposure. The study consisted of 492394 participants (age: 38–73 years) recruited by UK Biobank during 2004–2010. The cumulative wildfire-related PM2.5 within 10 kilometers of residence over three years was used as exposure, which was assessed by chemical transport and machine learning models. A time-varying Cox regression was utilized to explore the relationship of exposure with diverse cancer-specific mortality outcomes. Subgroup analyses of a range of potential modifiers were performed. Each 10 μg/m3 increment of 3-year cumulative exposure was related to a 0.4 % greater risk of total cancer (95 %CI: 1.001–1.007), a 1.1 % greater risk of lung cancer (95 %CI: 1.004–1.018), and a 2.7 % greater risk of lip, oral cavity and pharynx (LOP) cancer (95 %CI: 1.005–1.049). Higher vulnerability in the wildfire-related PM2.5-lung cancer relationship was found among participants being retired than those with other employment status. Even lower levels of exposure to PM2.5 from wildfires were related to elevated mortality risks for cancer from total, lung, LOP, highlighting the importance of wildfire prevention and control. Further investigations are warranted to enrich and extend existing knowledge in this field.

Interplay of natural and anthropogenic factors in sediment dynamics and trace element distribution in Güllük Gulf, western Türkiye: A comprehensive geochemical and hydrodynamic analysis

Güllük Gulf, located in the southeastern Aegean Sea, is significantly impacted by diverse human activities, including urban development, tourism, and intensive aquaculture. This study aims to assess the spatial distribution of trace metals in the Gulf's sediments, identify their sources, and evaluate their environmental impacts to inform effective management strategies. It also examines sediment transport patterns, which are crucial in influencing the distribution and concentration of pollutants. Establishing background concentration levels for various elements provides a baseline to assess pollution levels and identify deviations due to anthropogenic impact. Sediment samples were collected from 45 stations and analyzed for grain size, organic carbon, carbonate content, and concentrations of 26 elements. Contamination was assessed using indices such as Enrichment Factor (EF), Geoaccumulation Index (Igeo), Contamination Factor (Cf), Degree of Contamination (Cdeg), Pollution Load Index (PLI), Modified Pollution Index (MPI), and Toxic Risk Index (TRI). Statistical analyses, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify pollution sources. Results indicated that Güllük Gulf's sediments are predominantly sandy, with significant silt and clay fractions in sheltered bays. Organic carbon content averaged 1.68%, with higher values near urban and aquaculture areas. Trace metal concentrations exhibited notable spatial variability, with elevated levels of Pb, Cu and Zn in specific areas, indicating both natural and anthropogenic sources. PCA identified five significant factors contributing to metal presence, linking them to lithogenic origins, aquaculture activities, and industrial inputs. TRI results showed moderate toxic risk in Asin Bay, primarily due to Ni, As and Cr. The sediment transport model of Güllük Gulf, crucial in understanding regional pollution dynamics, revealed a complex interplay of hydrodynamic forces. The study underscores the significant environmental impact of human activities on sediment quality in Güllük Gulf. Elevated trace metal levels near aquaculture sites emphasize the need for stringent environmental management practices. Effective strategies should include regular monitoring, sustainable aquaculture practices, and stakeholder engagement to mitigate environmental impacts and preserve the Gulf's ecological integrity. This comprehensive approach provides crucial insights for future research and environmental management policies aimed at addressing the complex challenges facing Güllük Gulf.

Groundwater protection around Makkah sewage treatment plant using hydrological and transport models

Makkah is depicted environmentally by scarcity of rainfall, elevated temperatures, and increasing rates of evaporation. These ambience factors have driven the city to a reduction in the water balance. The main water resources in Makkah are renewable groundwater aquifers. Despite numerous studies concerned in the assessment of groundwater quality in Makkah, this paper presents the groundwater pollution remediation near Makkah sewage treatment plant. The methodology of this study depends on the simulation of four scenarios of groundwater remediation under the treated effluent of Makkah sewage plant. These scenarios are injection wells of clean water (with and without surface recharge of the effluent Makkah sewage plant), discharge wells for the contaminated aquifer, and slurry wall to constrict the spread of aquifer pollutants. The simulation is performed using the hydrological model (MODFLOW) and transport model in groundwater systems (MT3D). The results revealed that the case of discharge wells was the best one for cleaning the aquifer. In contrast, the worst case was the injection wells with surface recharge causing the pollution spread over the whole area. The case of using the slurry wall proved an efficient approach for controlling the pollution spread through the path of Makkah sewage plant effluent flow.

Effect of upper body venoarterial ECMO on systemic hemodynamics and oxygenation: A computational study

BackgroundThis study seeks to quantify the effects of upper body veno-arterial extracorporeal membrane oxygenation (VA ECMO) on the anatomical distribution of oxygen delivery in the setting of hypoxic respiratory failure and provide new insights that will guide clinical use of this support strategy to bridge patients to lung transplant. MethodsEmploying a patient-specific vascular geometry and a quantitative model of oxygen transport, computational simulations were performed to determine hemodynamics and oxygen delivery in the ascending and descending aorta, left and right coronary arteries, and great vessels during upper body VA ECMO support. Oxygen content in ECMO circuit blood flow was varied while considering different degrees of lung failure severity. Using lumped parameter models to dynamically apply perfusion boundary conditions, hemodynamic parameters and oxygen content were analyzed to assess the effect of ECMO supply titration. ResultsThe results emphasize the importance of anatomical distribution for tissue oxygen delivery in severe lung failure, with ECMO-derived flow primarily augmenting oxygen content in specific vascular beds. They also demonstrate that although cannulating the subclavian artery can enhance cerebral oxygen delivery, its ability to ensure sufficient oxygen delivery to the coronary circulation seems to be comparatively restricted. ConclusionsThe oxygen delivery to a specific vascular area is primarily determined by the oxygen content in the source of perfusion. Caution is advised with upper body VA ECMO for patients with hypoxic respiratory failure and right ventricle dysfunction, due to potential coronary ischemia. Management of these patients is challenging due to disease progression and organ availability uncertainties.

A numerical investigation to assess changes to displacement front and by-passed zones employing kinetic interface-sensitive tracer

An important aspect in groundwater remediation is to understand changes of multiphase fluid front morphology and stagnant regions on macro scale. However, the prediction of those changes during two-phase flow remains a challenging task due to the interplay of various physical factors. Recent laboratory experiments have demonstrated tracers' ability to predict deformation in the front of a two-phase flow system by utilizing a new reactive tracer known as, the kinetic interface sensitive tracer (KIS). This research employs a reactive transport model coupled with a macro-scale two-phase flow model to numerically analyse how viscosity ratio, capillary number, and heterogeneities on the tracer's signal and its impact the frontal deformation. One homogeneous and two heterogeneous types of porous media are considered. The background porous medium is a fine-grained, low-permeability medium, with a coarser, high-permeability lenses, generating heterogeneous material properties. The high-permeability lenses account for 25 % of the total model area and are arranged in either periodic or random patterns. The findings are evaluated using four parameters (effective front length, swept area, front roughness, and transition zone length). The flow patterns dominating the shape of the front are characterized by the viscous and capillary forces i.e. capillary number and the viscosity ratio between the two fluids. The results show that changes in flow regimes can be quantified using effective front length, thus employing the effective front length the viscous fingering regions can be quantified. Furthermore, front roughness and transition zone length are extracted and their relevance to the by-passed zones is presented. The slope of the reactive KIS tracer breakthrough curve, plotted on a phase diagram, can also be used to predict the existence of the by-passed zones for a low viscosity ratio. Finally, changes in front roughness and transition zone length induced by the inclusions are correlated to the slope of the KIS tracer BTC. The findings of this study can contribute to a better understanding of the impact of different flow regimes on the KIS tracer breakthrough signals and the linkages between the tracer signals and the front sizes.

Systems mapping of bidirectional endosomal transport through the crowded cell

Kinesin and dynein-dynactin motors move endosomes and other vesicles bidirectionally along microtubules, a process mainly studied under invitro conditions. Here, we provide a physiological bidirectional transport model following color-coded, endogenously tagged transport-related proteins as they move through a crowded cellular environment. Late endosomes (LEs) surf bidirectionally on Protrudin-enriched endoplasmic reticulum (ER) membrane contact sites, while hopping and gliding along microtubules and bypassing cellular obstacles, such as mitochondria. During bidirectional transport, late endosomes do not switch between opposing Rab7 GTPase effectors, RILP and FYCO1, or their associated dynein and KIF5B motor proteins, respectively. In the endogenous setting, far fewer motors associate with endosomal membranes relative to effectors, implying coordination of transport with other aspects of endosome physiology through GTPase-regulated mechanisms. We find that directionality of transport is provided in part by various microtubule-associated proteins (MAPs), including MID1, EB1, and CEP169, which recruit Lis1-activated dynein motors to microtubule plus ends for transport of early and late endosomal populations. At these microtubule plus ends, activated dynein motors encounter the dynactin subunit p150glued and become competent for endosomal capture and minus-end movement in collaboration with membrane-associated Rab7-RILP. We show that endosomes surf over the ER through the crowded cell and move bidirectionally under the control of MAPs for motor activation and through motor replacement and capture by endosomal anchors.

Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter.

Global geophysical satellite-derived ambient fine particulate matter (PM2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R 2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM2.5 from columnar AOD.

Coupled adsorption/precipitation (Γ/Π) modelling of scale inhibitor transport in porous media using the coupled isotherm, AΓΠ(c)

Scale inhibitor (SI) “squeeze” treatments are widely used operations in production assurance to prevent inorganic scales as one of the main flow assurance problems. In these treatments, a high concentration SI slug is injected (“squeezed”) into the porous medium, retained in the formation rock, and is gradually produced back at relatively small concentrations that can prevent (or significantly reduce) scale formation. The retention of SI in the formation is governed by coupled mechanisms of adsorption (Γ) and precipitation (Π) of SI species in the system. To design such SI treatments in an optimized manner, it is important to have good mathematical models of both the transport and the coupled interactions of adsorption/precipitation (Γ/Π) processes. In this study, a 1D advection-dispersion-reaction transport model has been developed, considering the coupled Γ/Π retention processes, and it is used to model linear core flood systems. The parameters for the equilibrium Γ/Π model can be derived from the routine bulk SI “apparent adsorption” tests that are usually conducted before any treatments. From previous works, equilibrium adsorption isotherm, Γ(c), is used to describe the adsorption behavior in such systems. However, although the precipitation kinetics are “fast” (almost at equilibrium), the kinetics of SI dissolution are “slow” and is therefore modelled by a kinetic rate law. From the derived dimensionless form of the transport-Γ/Π model equations, it is shown that the system is governed by 4 dimensionless numbers, NA, NP, NPe and NDa, which are the adsorption number, the precipitation number, the Peclet number, and the Damköhler number, respectively. The shape of the adsorption isotherm also plays a very important part in the extent and form of the effluent SI returns from the linear system. The developed model was then employed to carry out a series of sensitivity calculations relating to coupled adsorption/precipitation (Γ/Π) processes. Both equilibrium and kinetic SI precipitation were modelled coupled with the equilibrium SI adsorption, and the effect of these processes on the form and extent of the SI effluents was assessed. A range of sensitivities was then carried out to determine the effect of a wide range of parameters, including the effects of flow rate and shut-in periods on the kinetic dissolution effluent behavior. The findings from this work present the most clear explanation to date of why and how “precipitation squeezes” can greatly extend squeeze lifetime. A novel feature of this analysis is to show how the role of precipitation and adsorption changes over the various stages of the return effluent by developing plots of the %SI adsorbed on the rock, in the precipitate, and the mobile fluid phase.

Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modeling on large scales

Mathematical modeling aids in understanding large-scale erosion and sedimentation. However, sediment transport models calibration is constrained by data scarcity. This study explores the use of remote sensing (RS) imagery to supplement observed data, addressing three key questions: (1) How can high-resolution RS data be obtained using cloud-based methods for hydro-sediment applications, considering river changes? (2) What are the benefits of RS data in data-scarce conditions? (3) How can RS data improve hydro-sediment modeling in data-deficient regions? We developed a method to acquire large-scale RS data using Google Earth Engine (GEE) to obtain red and infrared reflectance from satellite imagery. After filtering errors, the data were used to calibrate a hydro-sediment model. Results showed that RS data, when combined with observed data, provided similar outcomes but performed better for lower values. Calibration with RS data alone improved the Kling-Gupta Efficiency (KGE) by 5%–18% and correlation by 5%–15%. Key conclusions are: (I) Cloud-based calibration is superior to using limited virtual stations; (II) RS data effectively complements observed data in hydro-sediment modeling; (III) Calibration using only RS data is beneficial in ungauged basins and preferable to no calibration.

Measuring thermal diffusivity and gap conductance in uranium nitride and Zircaloy relevant for microreactor applications

Heat transfer across nuclear fuels and structural interfaces is an important factor for evaluating the performance of nuclear power systems. Specifically, heat generated as nuclear fuel fissions must be transported through the cladding material and through the reactor to reach the steam turbine for power generation. As new microreactor designs emerge, maximizing the efficiency of this heat transfer process becomes crucial to make them commercially viable. This article examines thermal diffusivity and gap conductance in uranium nitride (UN) fuel and Zircaloy-4 (Zry4) cladding using light flash analysis (LFA). Thermal diffusivity measurements were made on monolithic UN pellets and Zry4 exposed to carbon at peak operating temperatures of microreactors and show that carbon ingress has a minimal effect on thermal diffusivity when compared with identical materials not exposed to carbon. Evaluation of gap conductance at the UN-Zry4 interface was done using one-dimensional two-layer thermal transport models as a function of applied pressure. The results show that increasing pressure on the UN-Zry4 interface leads to gains in gap conductance per unit area in fuel-cladding assemblies at microreactor operating temperatures. While many other variables are expected to influence UN-Zry4 interfacial gap conductance (e.g. contact surface roughness, porosity, localized heating, environmental gas pressure), the work offers a demonstration of using a conventional LFA apparatus to determine this parameter at elevated temperatures.

Self-diffusion is temperature independent on active membranes.

Molecular transport maintains cellular structures and functions. For example, lipid and protein diffusion sculpts the dynamic shapes and structures on the cell membrane that perform essential cellular functions, such as cell signaling. Temperature variations in thermal equilibrium rapidly change molecular transport properties. The coefficient of lipid self-diffusion increases exponentially with temperature in thermal equilibrium, for example. Hence, maintaining cellular homeostasis through molecular transport is hard in thermal equilibrium in the noisy cellular environment, where temperatures can fluctuate widely due to local heat generation. In this paper, using both molecular and lattice-based modeling of membrane transport, we show that the presence of active transport originating from the cell's cytoskeleton can make the self-diffusion of the molecules on the membrane robust to temperature fluctuations. The resultant temperature-independence of self-diffusion keeps the precision of cellular signaling invariant over a broad range of ambient temperatures, allowing cells to make robust decisions. We have also found that the Kawasaki algorithm, the widely used model of lipid transport on lattices, predicts incorrect temperature dependence of lipid self-diffusion in equilibrium. We propose a new algorithm that correctly captures the equilibrium properties of lipid self-diffusion and reproduces experimental observations.

Determining Rates of Molecular Secretion from Supernatant Concentration Measurements in a 3D-Bioprinted Human Liver Tissue Model.

The secretion rate of albumin is a key indicator of function in liver tissue models used for hepatotoxicity and pharmacokinetic testing. However, it is not generally clear how to determine molecular secretion rates from measurements of the molecular concentration in supernatant media. Here, we develop computational and analytical models of molecular transport in an experimental system that enable determination of albumin secretion rates based on measurements of albumin concentration in supernatant media. The experimental system is a 3D-bioprinted human liver tissue construct embedded in a 3D culture environment made from packed microgel particles swollen in liquid growth media. The mathematical models reveal that the range of albumin synthesis rates necessary to match experimentally measured albumin concentrations corresponds to reaction-limited conditions, where a steady state of albumin spatial distribution is rapidly reached between media exchanges. Our results show that temporally resolved synthesis rates can be inferred from serial concentration measurements of collected supernatant media. This link is critical to confidently assessing in vitro tissue performance in applications where critical quality attributes must be quantified, like in drug development and screening.

Georeferenced X (formerly twitter) data as a proxy of mobility behaviour: case study of Norway

Georeferenced messages on social media represent a powerful data source to gain a different perspective for estimating mobility behaviour, which is still mainly based on travel surveys. These data are openly available, yet few studies have explored their potential. This paper assesses the feasibility of large-scale Twitter data as a proxy of human mobility behaviour to complement traditional travel surveys, and for calibration and validation of transport models. Almost 12 million Tweets from more than 90,000 users were further analysed to detect the trip patterns at municipality level in Norway from 2012 to 2022. Results showed that the mobility patterns changed between 2014 and 2019 for the travel survey, as for 2019 most of the reported trips were short and concentrated in the densely populated areas of the country, where most respondents lived, triggering a lack of information for certain areas. In contrast, Twitter data presented a more stable data source along both years with similar population distribution and average trip length. Although Twitter data have limitations in relation to the socio-demographic information of the users, it could complement the travel survey given the broader spatial and temporal distribution of this large-scale data.

Environmental fate and transport of PFAS in wastewater treatment plant effluent discharged to rapid infiltration basins

Fate and transport of per- and polyfluoroalkyl substances (PFAS) in wastewater treatment plant (WWTP) effluent discharged to rapid infiltration basins (RIBs) is investigated using data from 26 WWTPs in Michigan, USA. PFAS were found to accumulate in groundwater downgradient from RIBs with median groundwater-effluent enrichment factors for ten commonly detected, terminal-form perfluoroalkyl acids (PFAAs) ranging from 1.3 to 5.2. Maximum contaminant levels for drinking water were exceeded in groundwater at all WWTPs with available PFAS data. Numerical models of unsaturated fluid flow and PFAS transport honoring RIB site properties, such as median vertical separation distance to the water table and a realistic range of area-normalized effluent fluxes, show long-chain PFAS undergo significant delays from air-water interface (AWI) adsorption, requiring up to 15 times longer to reach maximum mass flux to the saturated zone under low-flux conditions, where AWI area is 2.5 times greater. Short-chain PFAS commonly detected in effluent are only minimally affected by AWI adsorption and show little to no attenuation under high-flux conditions. The nonlinear inverse relationship between water content and AWI area highlights the important role of AWI adsorption in modulating unsaturated transport of long-chain PFAS to underlying groundwater due to the broad range of flux rates applied to RIB systems.

Semi-infinite Simple Exclusion Process: From Current Fluctuations to Target Survival.

The symmetric simple exclusion process (SEP), where diffusive particles cannot overtake each other, is a paradigmatic model of transport in the single-file geometry. In this model, the study of currents has attracted a lot of attention, but so far most results are restricted to two geometries: (i)a finite system between two reservoirs, which does not conserve the number of particles but reaches a nonequilibrium steady state, and (ii)an infinite system which conserves the number of particles but never reaches a steady state. Here, we obtain an expression for the full cumulant generating function of the integrated current in the important intermediate situation of a semi-infinite system connected to a reservoir, which does not conserve the number of particles and never reaches a steady state. This results from the determination of the full spatial structure of the correlations, which we infer to obey the very same closed equation recently obtained in the infinite geometry and argue to be exact. Besides their intrinsic interest, these results allow us to solve two open problems: the survival probability of a fixed target in the SEP, and the statistics of the number of particles injected by a localized source.

Evaluation of the Bioavailability of Iodine and Arsenic in Raw and Cooked Saccharina japonica Based on Simulated Digestion/Caco-2 Cell Model.

Kelp is a traditional healthy food due to its high nutritional content; however, its relatively high contents of iodine and arsenic have raised concerns about its edible safety. This study explored the effects of different cooking treatments on the contents of iodine and arsenic in kelp, evaluated the bioaccessibility and bioavailability of iodine and arsenic in kelp using in vitro digestion, and compared the differences in the transport characteristics of iodine in kelp and KIO3 using a Caco-2 monolayer cell transport model. The results show that the content of target elements that reached systemic circulation could be reduced by cooking and gastrointestinal digestion. The highest reductions in iodine and arsenic were 94.4% and 74.7%, respectively, which were achieved by boiling for 10 min. The bioaccessibility and bioavailability of iodine and arsenic were significantly improved by a cooking treatment. However, the contents of iodine and arsenic decreased significantly, with the bioaccessibility of iodine reducing from 3188.2 μg/L to 317.0 μg/L and that of arsenic reducing from 32.5 μg/L to 18.1 μg/L in the gastric phase after boiling. The findings also show that the efficiency of iodine transport in kelp and KIO3 was positively correlated with the transport time and negatively correlated with the concentration of iodine. With the increase in the iodine concentration, the rate of iodine transport in kelp decreased from 63.93% to 3.14%, but that of KIO3 was stable at around 35%, which indicates that the absorption efficiency of iodine from kelp was limited, even when too much kelp was ingested. In conclusion, the edible safety of kelp is significantly improved after cooking. The risk of excessive iodine and arsenic intake caused by consuming kelp is extremely low, and as an effective iodine supplement source, kelp has higher edible safety compared with KIO3. This study clarifies the safety of algae based on iodine and arsenic contents and also provides a basis for the formulation of food safety standards.

Investigating the relative accuracy of GPS, GSM and CDR data for inferring spatiotemporal travel trajectories

AbstractThe potential of passively generated big data sources in transport modelling is well‐recognised. However, assessing their accuracy and suitability for policymaking remains challenging due to the lack of ground‐truth (GT) data for validation. This study evaluates the accuracy of inferring human mobility patterns from global positioning system (GPS), call detail records (CDR), and global system for mobile communication (GSM) data. Using outputs from an agent‐based simulation platform (MATSim) as ‘synthetic GT’ (SGT), synthetic GPS, CDR, and GSM data were generated, considering their positional disturbances and conventional spatiotemporal resolutions. Mobility information, including activity location, departure time, and trajectory distance, derived from the synthetic data, was compared with SGT to evaluate the accuracy of passive trajectory data at both disaggregate and aggregate levels. The results indicated a higher accuracy of GPS data in identifying stay locations at high resolution. But, GSM data at a lower resolution effectively accounted for over 80% of the variability in stay locations. Comparisons of departure time distribution and travel distance revealed higher measurement errors in GSM and CDR data than in GPS data. The proposed simulation‐based accuracy assessment framework will aid transport planners select the most suitable data for specific analyses and understand the potential margin of error involved.