Tutorial review of error evaluation in experimental water research at the example of membrane filtration.

Experimental water research lacks clear methodology to estimate experimental error. Especially when natural waters are involved, the characterization tools bear method-specific artifacts while the varying environmental conditions prevent regular repeats. This tutorial review identifies common mistakes, and proposes a practical procedure to determine experimental errors at the example of membrane filtration. Statistical analysis is often applied to an insufficient number of repeated measurements, while not all error sources and contributions are considered. This results in an underestimation of the experimental error. Variations in relevant experimental parameters need to be investigated systematically, and the related errors are quantified as a half of the variation between the max and min values when standard deviation is not applicable. Error of calculated parameters (e.g. flux, pollutant removal and mass loss) is estimated by applying error propagation, where weighing contributions of the experimental parameters are considered. Appropriate judgment and five-time repetition of a selected experiment under identical conditions are proposed to validate the propagated experimental error. For validation, the five repeated data points should lie within the estimated error range of the error bar. The proposed error evaluation procedure is adaptable in experimental water research and intended for researchers to identify the contributing factors of an experimental error and carry out appropriate error quantification and validation. The most important aim is to raise awareness of the necessity to question error methodology and reproducibility of experimental data, to produce and publish high quality research.

Interplay of the forces governing steroid hormone micropollutant adsorption in vertically-aligned carbon nanotube membrane nanopores.

Vertically-aligned carbon nanotube (VaCNT) membranes allow water to conduct rapidly at low pressures and open up the possibility for water purification and desalination, although the ultralow viscous stress in hydrophobic and low-tortuosity nanopores prevents surface interactions with contaminants. In this experimental investigation, steroid hormone micropollutant adsorption by VaCNT membranes is quantified and explained via the interplay of the hydrodynamic drag and friction forces acting on the hormone, and the adhesive and repulsive forces between the hormone and the inner carbon nanotube wall. It is concluded that a drag force above 2.2 × 10-3 pN overcomes the friction force resulting in insignificant adsorption, whereas lowering the drag force from 2.2 × 10-3 to 4.3 × 10-4 pN increases the adsorbed mass of hormones from zero to 0.4 ng cm-2. At a low drag force of 1.6 × 10-3 pN, the adsorbed mass of four hormones is correlated with the hormone-wall adhesive (van der Waals) force. These findings explain micropollutant adsorption in nanopores via the forces acting on the micropollutant along and perpendicular to the flow, which can be exploited for selectivity.

Identification and semi-quantification of protein allergens in complex mixtures using proteomic and AllerCatPro 2.0 bioinformatic analyses: a proof-of-concept investigation.

The demand for botanicals and natural substances in consumer products has increased in recent years. These substances usually contain proteins and these, in turn, can pose a risk for immunoglobulin E (IgE)-mediated sensitization and allergy. However, no method has yet been accepted or validated for assessment of potential allergenic hazards in such materials. In the studies here, a dual proteomic-bioinformatic approach is proposed to evaluate holistically allergenic hazards in complex mixtures of plants, insects, or animal proteins. Twelve commercial preparations of source materials (plant products, dust mite extract, and preparations of animal dander) known to contain allergenic proteins were analyzed by label-free proteomic analyses to identify and semi-quantify proteins. These were then evaluated by bioinformatics using AllerCatPro 2.0 (https://allercatpro.bii.a-star.edu.sg/) to predict no, weak, or strong evidence for allergenicity and similarity to source-specific allergens. In total, 4,586 protein sequences were identified in the 12 source materials combined. Of these, 1,665 sequences were predicted with weak or strong evidence for allergenic potential. This first-tier approach provided top-level information about the occurrence and abundance of proteins and potential allergens. With regards to source-specific allergens, 129 allergens were identified. The sum of the relative abundance of these allergens ranged from 0.8% (lamb's quarters) to 63% (olive pollen). It is proposed here that this dual proteomic-bioinformatic approach has the potential to provide detailed information on the presence and relative abundance of allergens, and can play an important role in identifying potential allergenic hazards in complex protein mixtures for the purposes of safety assessments.

Desilification of phytolith exacerbates the release of arsenic from rice straw.

Arsenic (As) turnover in rice paddy agro-ecosystems has received much attention because As can enter the food chain through its accumulation in rice, thereby affecting human health. Returning straw to soil is a common practice to retain nutrients for soil and crops, but it also cycles As within the rice paddy field ecosystems. However, there is still a lack of detailed understanding of the fate of As in rice straw, and how or to what extent it is recycled back into the soil environment. This study aims to elucidate the relationship between the microstructure of rice straw and the release of As during rice straw decomposition. The microstructure of rice straw was found to comprise both organic and silica (phytolith) components. These two constituents are inter-embedded to form a composite-like structure that contains up to 6.48 mg As Kg-1. The 30-day batch experiments revealed that the biochemical release of As simultaneously depends upon the decomposition of the organic component and the desilicification of the silica component. Accompanying the release of As was the release of other elements such as Fe, Al, P and S. These elements can further interact with As to form less mobile compounds. The introduction of either Trichoderma harzianum or Bacillus velezensis was expected to accelerate the decomposition of rice straw, and enhance the silica dissolution, hence contributing to an increase in the As release. Despite these expectations, our observations showed the opposite effects. Microorganisms presumably have facilitated the change in solution chemistry or the inclusion of As into the newly-formed precipitates. The biochemical decomposition process can reduce straw particle size, while the negatively-charge surface will involve microsized straw particles in the electrostatic interaction, thereby favoring the dispersibility state. Therefore, the co-transport of micro-sized straw particles with As under field conditions should not be neglected.

OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning.

Federated learning (FL) has emerged as a promising approach to collaboratively train machine learning models across multiple edge devices while preserving privacy. The success of FL hinges on the efficiency of participating models and their ability to handle the unique challenges of distributed learning. While several variants of Vision Transformer (ViT) have shown great potential as alternatives to modern convolutional neural networks (CNNs) for centralized training, the unprecedented size and higher computational demands hinder their deployment on resource-constrained edge devices, challenging their widespread application in FL. Since client devices in FL typically have limited computing resources and communication bandwidth, models intended for such devices must strike a balance between model size, computational efficiency, and the ability to adapt to the diverse and non-IID data distributions encountered in FL. To address these challenges, we propose OnDev-LCT: Lightweight Convolutional Transformers for On-Device vision tasks with limited training data and resources. Our models incorporate image-specific inductive biases through the LCT tokenizer by leveraging efficient depthwise separable convolutions in residual linear bottleneck blocks to extract local features, while the multi-head self-attention (MHSA) mechanism in the LCT encoder implicitly facilitates capturing global representations of images. Extensive experiments on benchmark image datasets indicate that our models outperform existing lightweight vision models while having fewer parameters and lower computational demands, making them suitable for FL scenarios with data heterogeneity and communication bottlenecks.

Sorption of oxytetracycline to microsized colloids under concentrated salt solution: A perspective on terrestrial-to-ocean transfer of antibiotics.

The sorption of antibiotics on soil minerals and their cotransport have been widely studied for the past few years; however, these processes in concentrated salt solutions (estuary-like conditions) are not fully understood. This study aims to determine the possible sorption of oxytetracycline (OTC) on various natural and synthesized microsized minerals (including haematite, goethite, kaolinite, bentonite, lateritic, kaolinitic and illitic soil clays) under conditions mimicking pure, fresh, brackish and sea waters. The sorption of OTC was found to decrease in surface charge (herein zeta potential), hence altering the colloidal properties of the materials used. The sorption capacities of soil clays for OTC follow the inequality illitic soil clay > kaolinitic soil clay > lateritic soil clay, and the sorption capacities were found to decrease at higher salt concentrations. Seawater can intensify the release of the sorbed OTC from soil clay surfaces while favouring the coaggregation of the remaining OTC with soil clays. This implies that the long-range transport of OTC or other similar antibiotics can be governed by the mineralogical composition/properties of the suspended particles. More importantly, increasing salt concentrations in estuaries may form a chemical barrier at which limited amounts of OTC/antibiotics can pass through, while the remaining OTC/antibiotics can be favoured to aggregate simultaneously with suspended mineral particles.

Application of AllerCatPro 2.0 for protein safety assessments of consumer products.

Foreign proteins are potentially immunogenic, and a proportion of these are able to induce immune responses that result in allergic sensitization. Subsequent exposure of sensitized subjects to the inducing protein can provoke a variety of allergic reactions that may be severe, or even fatal. It has therefore been recognized for some time that it is important to determine a priori whether a given protein has the potential to induce allergic responses in exposed subjects. For example, the need to assess whether transgene products expressed in genetically engineered crop plants have allergenic properties. This is not necessarily a straightforward exercise (as discussed elsewhere in this edition), but the task becomes even more challenging when there is a need to conduct an overall allergenicity safety assessment of complex mixtures of proteins in botanicals or other natural sources that are to be used in consumer products. This paper describes a new paradigm for the allergenicity safety assessment of proteins that is based on the use of AllerCatPro 2.0, a new version of a previously described web application model developed for the characterization of the allergenic potential of proteins. Operational aspects of AllerCatPro 2.0 are described with emphasis on the application of new features that provide improvements in the predictions of allergenic properties such as the identification of proteins with high allergenic concern. Furthermore, the paper provides a description of strategies of how AllerCatPro 2.0 can best be deployed as a screening tool for identifying suitable proteins as ingredients in consumer products as well as a tool, in conjunction with label-free proteomic analysis, for identifying and semiquantifying protein allergens in complex materials. Lastly, the paper discusses the steps that are recommended for formal allergenicity safety assessment of novel consumer products which contain proteins, including consideration and integration of predicted consumer exposure metrics. The article therefore provides a holistic perspective of the processes through which effective protein safety assessments can be made of potential allergenic hazards and risks associated with exposure to proteins in consumer products, with a particular focus on the use of AllerCatPro 2.0 for this purpose.

Earthworms can mobilize soil arsenic through their casts.

The mobilization of arsenic (As) in paddy soil has received much attention because it might accelerate the transfer of As from soil to rice. This study aims to elucidate whether earthworms can mobilize As through their casts. Cast samples were collected from 23 different paddy fields in the Red River delta. We first analysed different forms of As through fractionation and then performed batch experiments under reducing conditions to identify factors that govern the mobility of As in casts. Because the dissociation of casts may induce colloids that carry As, the colloidal properties of cast suspensions were also examined. The median value of As in casts (obtained from aqua regia digestion) was 5.11 mg kg-1, which was lower than that in the surrounding soil (6.7 mg kg-1). Compared with the surrounding soil, casts contain less As, possibly because cast As is more labile and more easily lost due to leaching. Various processes, including the reductive dissolution of Fe oxides, decomposition of organic matter, and sorption competition of soluble anionic substances, such as P, Si and DOC, were found to strongly correlate with the release of As from casts. We propose that earthworms, via their casts, may accelerate the As cycle in paddy soils, potentially intensifying As exposure to human health. The dissociation of cast could release colloids containing As; therefore, the cotransport of As with cast-induced colloids should also be considered in future works.

Contrastive encoder pre-training-based clustered federated learning for heterogeneous data.

Federated learning (FL) is a promising approach that enables distributed clients to collaboratively train a global model while preserving their data privacy. However, FL often suffers from data heterogeneity problems, which can significantly affect its performance. To address this, clustered federated learning (CFL) has been proposed to construct personalized models for different client clusters. One effective client clustering strategy is to allow clients to choose their own local models from a model pool based on their performance. However, without pre-trained model parameters, such a strategy is prone to clustering failure, in which all clients choose the same model. Unfortunately, collecting a large amount of labeled data for pre-training can be costly and impractical in distributed environments. To overcome this challenge, we leverage self-supervised contrastive learning to exploit unlabeled data for the pre-training of FL systems. Together, self-supervised pre-training and client clustering can be crucial components for tackling the data heterogeneity issues of FL. Leveraging these two crucial strategies, we propose contrastive pre-training-based clustered federated learning (CP-CFL) to improve the model convergence and overall performance of FL systems. In this work, we demonstrate the effectiveness of CP-CFL through extensive experiments in heterogeneous FL settings, and present various interesting observations.

Sorption of cosmetic and personal care polymer ingredients to iron oxides, clay minerals and soil clays: An environmental perspective.

The increasing daily use of cosmetic and personal care ingredients (CPCIs) requires improved understanding of the fate and impacts of CPCIs in environmental systems. Effects of CPCIs on colloidal properties of various geocolloids such as iron oxides (goethite, haematite), clay minerals (kaolinite, bentonite) and soil clays (kaolinitic-, illitic- and lateritic soil clays) were studied by tracking time-resolved changes in zeta potential (ζ) and observing suspended particle density. Two polymers representing anionic CPCIs, i.e., polyacrylate crosspolymer-11 (PC11) and cationic CPCIs, i.e., polyDADMAC (PD) show contrast effects on ζ and colloidal properties of the selected materials. While PC11 tended to associate with Fe oxides, PD can be adsorbed by clay minerals and soil clays. The neutralization due to the sorption of either PC11 or PD onto opposite-charge sign surface sites can lower the net surface charge of the materials, thereby enhancing electrostatic attraction, stimulating particle size growth, and eventually intensifying co-aggregation. The observed colloidal properties of iron oxides, clay minerals and soil clays under the presence of PC11 and PD may reflect what are happening in many aquatic environments where CPCIs co-exist with various mineral colloids. Therein, CPCIs likely delay the transport of the opposite-charge sign colloids, while they increase the dispersibility and transportability of the same-charge sign colloids. This implies that intensifying presence of a given CPCI could have selective effects on colloid systems. As a whole, CPCIs can change the fate and the final destination of mineral colloids and themselves; therefore, their effects and relevant treatment techniques need to be included into the future agenda.

Self-Organizing Democratized Learning: Toward Large-Scale Distributed Learning Systems.

Emerging cross-device artificial intelligence (AI) applications require a transition from conventional centralized learning systems toward large-scale distributed AI systems that can collaboratively perform complex learning tasks. In this regard, democratized learning (Dem-AI) lays out a holistic philosophy with underlying principles for building large-scale distributed and democratized machine learning systems. The outlined principles are meant to study a generalization in distributed learning systems that go beyond existing mechanisms such as federated learning (FL). Moreover, such learning systems rely on hierarchical self-organization of well-connected distributed learning agents who have limited and highly personalized data and can evolve and regulate themselves based on the underlying duality of specialized and generalized processes. Inspired by Dem-AI philosophy, a novel distributed learning approach is proposed in this article. The approach consists of a self-organizing hierarchical structuring mechanism based on agglomerative clustering, hierarchical generalization, and corresponding learning mechanism. Subsequently, hierarchical generalized learning problems in recursive forms are formulated and shown to be approximately solved using the solutions of distributed personalized learning problems and hierarchical update mechanisms. To that end, a distributed learning algorithm, namely DemLearn, is proposed. Extensive experiments on benchmark MNIST, Fashion-MNIST, FE-MNIST, and CIFAR-10 datasets show that the proposed algorithm demonstrates better results in the generalization performance of learning models in agents compared to the conventional FL algorithms. The detailed analysis provides useful observations to further handle both the generalization and specialization performance of the learning models in Dem-AI systems.

Coaggregation of micro polystyrene particles and suspended minerals under concentrated salt solution: A perspective of terrestrial-to-ocean transfer of microplastics.

This study evaluates the colloidal stability of polystyrene microplastics (PSMPs) in the presence of various mineral colloids. Although PSMPs were highly dispersive, they were found to be involved in the aggregation of each mineral colloid. The efficiency of mineral colloids to stimulate the coaggregation of PSMPs follows the order bentonite > kaolinitic soil clay > illitic soil clay > kaolinite > goethite > haematite. Surface charge density is likely a crucial factor that determines the efficiency of mineral colloids. In concentrated salt solution, PSMPs together with mineral colloids can be involved in various continuous and simultaneous electrochemical processes such as charge neutralization, double electric layer compression, van der Waals attraction stimulation and heteroaggregation. These processes may also occur in the estuary environments, where suspended mineral colloids may play an ultimate role in reducing the transport of microplastics into oceans while also intensifying microplastic enrichment in coastal sediments.

Early predictors of visual and axonal outcomes after acute optic neuritis.

Background: Predicting long-term visual outcomes and axonal loss following acute optic neuritis (ON) is critical for choosing treatment. Predictive models including all clinical and paraclinical measures of optic nerve dysfunction following ON are lacking. Objectives: Using a prospective study method, to identify 1 and 3 months predictors of 6 and 12 months visual outcome (low contrast letter acuity 2.5%) and axonal loss [retinal nerve fiber layer thickness and multifocal evoked potential (mfVEP) amplitude] following acute ON. Methods: In total, 37 patients of acute ON onset were evaluated within 14 days using between-eye asymmetry of visual acuity, color vision (Ishihara plates), optical coherence tomography, mfVEP, and optic nerve magnetic resonance imaging [magnetic transfer ratio (MTR) and diffusion tensor imaging (DTI)]. Results: Visual outcome at 6 and 12 months was best predicted by Ishihara asymmetry at 1 and 3 months following ON onset. Axonal loss at 6 and 12 months was reliably predicted by Ishihara asymmetry at 1 month. Optic nerve MTR and DTI at 3 months post-acute ON could predict axonal loss at 6 and 12 months. Conclusions: Simple Ishihara asymmetry testing 1 month after acute ON onset can best predict visual outcome and axonal loss at 6 and 12 months in a clinical or research setting.

Tracking Eye Movements for Diagnosis in Myasthenia Gravis: A Comprehensive Review.

BACKGROUND: Around 60%--75% of myasthenia gravis (MG) patients initially present with nonspecific ocular symptoms. Failed recognition of these symptoms may delay the diagnosis of MG up to 5 years or more, leading to a reduced likelihood of remission and increased morbidity. Current diagnostic tests are either poorly sensitive for patients presenting with ocular symptoms alone or are time consuming, invasive, require a high level of technical expertise, and generally are universally difficult to obtain. This review will explore quantitative eye and pupil tracking as a potential noninvasive, time-effective, and less technically demanding alternative to current diagnostic tests of MG. EVIDENCE ACQUISITION: Comprehensive literature review. RESULTS: Thirty-two publications using oculography for the diagnosis of MG and 6 studies using pupillometry were evaluated. In MG patients, extra ocular muscle fatigue was evident in reports of intersaccadic, intrasaccadic and postsaccadic abnormalities, changes in optokinetic nystagmus, slow eye movements, disconjugate saccades, and pupillary constrictor muscle weakness. CONCLUSIONS: Our review identified several potentially useful variables that derive from oculography and pupillometry studies that could assist with a timely diagnosis of MG. Limitations of this review include heterogeneity in design, sample size, and quality of the studies evaluated. There is a need for larger, well-designed studies evaluating eye-tracking measures in the diagnosis of MG, especially for patients presenting with purely ocular symptoms.

AllerCatPro 2.0: a web server for predicting protein allergenicity potential.

Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict protein allergenicity potential with better accuracy than other computational methods and new features that help assessors making informed decisions. AllerCatPro 2.0 predicts the similarity between input proteins using both their amino acid sequences and predicted 3D structures towards the most comprehensive datasets of reliable proteins associated with allergenicity. These datasets currently include 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens with manual expert curation from the databases of WHO/International Union of Immunological Societies (IUIS), Comprehensive Protein Allergen Resource (COMPARE), Food Allergy Research and Resource Program (FARRP), UniProtKB and Allergome. Various examples of profilins, autoimmune allergens, low allergenic proteins, very large proteins, and nucleotide input sequences showcase the utility of AllerCatPro 2.0 for predicting protein allergenicity potential. The AllerCatPro 2.0 web server is freely accessible at https://allercatpro.bii.a-star.edu.sg.

Comparative effects of crystalline, poorly crystalline and freshly formed iron oxides on the colloidal properties of polystyrene microplastics.

Colloid-sized microplastics (MPs) are ubiquitous in aquatic environments and can share the same transport route together with various crystalline, poorly crystalline and freshly formed iron oxides. However, the colloidal interactions between these colloid constituents are not fully understood. This study was designed to investigate the colloidal properties of polystyrene microplastics (PSMPs) under the influence of haematite, goethite, ferrihydrite and freshly formed Fe oxide (FFFO). Dynamic light scattering was coupled with a test tube method to observe changes in the surface charge and colloidal dynamics of suspensions of PSMPs and Fe oxides. The overall effects on the aggregation of PSMPs are found to decrease in the following order: FFFO > ferrihydrite > goethite > haematite. The effects of these Fe oxides are found to strongly depend on pH. While the crystalline oxides play a dominant role in the acidic environment, poorly crystalline oxides show greater effects on PSMP aggregation in an alkaline environment. Heteroaggregation due to decreasing electrostatic interactions is the major mechanism that governs the colloidal dynamics of PSMPs and Fe oxides. It can be inferred that the copresence of Fe oxides and MPs can delay the transport of MPs or even change the destination for MPs.

Polyacrylate crosspolymer-11 enhances soil clay dispersibility: An indication for inadvertent environmental impacts from personal care and cosmetic ingredients.

Polymer ingredients are commonly found in personal care and cosmetic industry and their "leakages" into the environment have recently been warned as an emerging environmental risk. Daily use of personal care and cosmetic products can inadvertently release large amounts of polymer ingredients into water courses. However, their fate and interaction with other constituents, especially colloids (e.g., clays), have not been fully understood. This study primarily evaluates the colloidal dynamics of soil clays under the presence of polyacrylate crosspolymer-11 (PC11) (a common ingredient of cosmetic and personal care products) with the aim of identifying possible induced changes in the clay-accumulated environments, e.g., soil and sediment. The test-tube experiments were coupled with a particle charge detector to mutually evaluate the colloidal dynamics and surface charge properties of the soil clays. It was revealed that adsorption of PC11 onto the clays shifted clay surface to more negative, thereby intensifying repulsive force and favouring the dispersion state of the soil clays. This implies that various polymer ingredients can act in the same way in stabilizing clay dispersion or even altering the fate of the soil clays. As the growing consumption of personal care and cosmetic products will likely continue, it requires a tighter consideration of the possible impacts of polymer ingredient residues, not limited to dispersion-induced effects, in various clay-accumulated environments such as paddy fields, river mouths or mangroves.

Restoration impacts on rates of denitrification and greenhouse gas fluxes from tropical coastal wetlands.

Forested coastal wetlands are globally important systems sequestering carbon and intercepting nitrogen pollution from nutrient-rich river systems. Coastal wetlands that have suffered extensive disturbance are the target of comprehensive restoration efforts. Accurate assessment of restoration success requires detailed mechanistic understanding of wetland soil biogeochemical functioning across restoration chrono-sequences, which remains poorly understood for these sparsely investigated systems. This study investigated denitrification and greenhouse gas fluxes in mangrove and Melaleuca forest soils of Vietnam, using the 15N-Gas flux method. Denitrification-derived N2O was significantly higher from Melaleuca than mangrove forest soils, despite higher potential rates of total denitrification in the mangrove forest soils (8.1 ng N g-1 h-1) than the Melaleuca soils (6.8 ng N g-1 h-1). Potential N2O and CO2 emissions were significantly higher from the Melaleuca soils than from the mangrove soils. Disturbance and subsequent recovery had no significant effect on N biogeochemistry except with respect to the denitrification product ratio in the mangrove sites, which was highest from the youngest mangrove site. Potential CO2 and CH4 fluxes were significantly affected by restoration in the mangrove soils. The lowest potential CO2 emissions were observed in the mid-age plantation and potential CH4 fluxes decreased in the older forests. The mangrove system, therefore, may remove excess N and improve water quality with low greenhouse gas emissions, whereas in Melaleucas, increased N2O and CO2 emissions also occur. These emissions are likely balanced by higher carbon stocks observed in the Melaleuca soils. These mechanistic insights highlight the importance of ecosystem restoration for pollution attenuation and reduction of greenhouse gas emissions from coastal wetlands. Restoration efforts should continue to focus on increasing wetland area and function, which will benefit local communities with improved water quality and potential for income generation under future carbon trading.

Thermal induced changes of rice straw phytolith in relation to arsenic release: A perspective of rice straw arsenic under open burning.

On-site open burning is a common practice for handling rice straw, but its negative impacts, e.g., biomass loss and air pollution, are largely debated worldwide. To address the negative effects of open burning, many efforts have been made to 'ignite' worldwide bans. However, these bans are likely based on a singular view in which some positive aspects of open burning are overlooked. In this study, we aimed to determine the thermal-induced changes of straw and straw arsenic (As) under open burning and heat-treatments (in the temperature range from 300 to 900 °C). It was found that silica phase in rice straw (so-called phytolith) can encapsulate As in its structure. Open burning or heat-treatment of straw resulted in a tighter association of As and phytolith, thereby reducing dissolution of As. We proposed an opinion that open burning causes air pollution, but it can increase the activity of phytolith in sequestrating As, enabling delayed As cycle in rice ecosystems. The combat of on-site open burning of rice straw to reduce air pollution will alter straw handling routines, thereby changing the cycle of straw phytolith and the route of straw As.