Human behavior-based COVID-19 transmission in two dining spaces.

Since December 2019, the COVID-19 pandemic has rapidly disseminated globally, posing significant threats to the world. The dining spaces are high-risk indoor environments for the transmission of SARS-CoV-2, posing challenges for intervention and control. This study, based on surveillance videos from two COVID-19 outbreak cases in restaurants, obtained real data on human behaviors of close contact and surface touch. A respiratory infectious disease transmission model was developed, incorporating four transmission routes: short-range airborne, long-range airborne, fomite and large droplet. The results indicate that diners and staff spent 21.9 %-28.7 % and 17.5 %-27.8 % of their time on speaking, respectively, while spending 85.9 %-90.7 % and 83.4 %-87.6 % of their time on surface touching. The primary transmission routes were short-range (contributing 5.8 %-70.9 %) and long-range airborne (contributing 28.4 %-93.0 %), with fomite and large droplet routes contributing less than 12.0 %. Staff-only mask wearing reduced infection risk by 12.8 %-31.8 %. It is recommended that mandatory mask wearing for staff is necessary, while diners should wear masks as much as possible, and that the equivalent ventilation rate of clean fresh air is suggested to 30.0 m3/ (h·person). This study provides a scientific support to make non-pharmaceutical interventions in dinning spaces.

Optoelectronic synapses with chemical-electric behaviors in gallium nitride semiconductors for biorealistic neuromorphic functionality.

Optoelectronic synapses, leveraging the integration of classic photo-electric effect with synaptic plasticity, are emerging as building blocks for artificial vision and photonic neuromorphic computing. However, the fundamental working principles of most optoelectronic synapses mainly rely on physical behaviors while missing chemical-electric synaptic processes critical for mimicking biorealistic neuromorphic functionality. Herein, we report a photoelectrochemical synaptic device based on p-AlGaN/n-GaN semiconductor nanowires to incorporate chemical-electric synaptic behaviors into optoelectronic synapses, demonstrating unparalleled dual-modal plasticity and chemically-regulated neuromorphic functions through the interplay of internal photo-electric and external electrolyte-mediated chemical-electric processes. Electrical modulation by implementing closed or open-circuit enables switching of optoelectronic synaptic operation between short-term and long-term plasticity. Furthermore, inspired by transmembrane receptors that connect extracellular and intracellular events, synaptic responses can also be effectively amplified by applying chemical modifications to nanowire surfaces, which tune external and internal charge behaviors. Notably, under varied external electrolyte environments (ion/molecule species and concentrations), our device successfully mimics chemically-regulated synaptic activities and emulates intricate oxidative stress-induced biological phenomena. Essentially, we demonstrate that through the nanowire photoelectrochemical synapse configuration, optoelectronic synapses can be incorporated with chemical-electric behaviors to bridge the gap between classic optoelectronic synapses and biological synapses, providing a promising platform for multifunctional neuromorphic applications.

Biomimetic engineering of a neuroinflammation-targeted MOF nanozyme scaffolded with photo-trigger released CO for the treatment of Alzheimer's disease.

Alzheimer's disease (AD) is one of the most fatal and irreversible neurodegenerative diseases, which causes a huge emotional and financial burden on families and society. Despite the progress made with recent clinical use of inhibitors of acetylcholinesterase and amyloid-ß (Aß) antibodies, the curative effects of AD treatment remain unsatisfactory, which is probably due to the complexity of pathogenesis and the multiplicity of therapeutic targets. Thus, modulating complex pathological networks could be an alternative approach to treat AD. Here, a neutrophil membrane-coated MOF nanozyme (denoted as Neu-MOF/Fla) is biomimetically engineered to disturb the malignant Aß deposition-inflammation cycle and ameliorate the pathological network for effective AD treatment. Neu-MOF/Fla could recognize the pathological inflammatory signals of AD, and deliver the photo-triggered anti-inflammatory CO and MOF based hydrolytic nanozymes to the lesion area of the brain in a spontaneous manner. Based on the in vitro and in vivo studies, Neu-MOF/Fla significantly suppresses neuroinflammation, mitigates the Aß burden, beneficially modulates the pro-inflammatory microglial phenotypes and improves the cognitive defects of AD mice models. Our work presents a good example for developing biomimetic multifunctional nanotherapeutics against AD by means of amelioration of multiple symptoms and improvement of cognitive defects.

A Nanozyme-Boosted MOF-CRISPR Platform for Treatment of Alzheimer's Disease.

Rectifying the aberrant microenvironment of a disease through maintenance of redox homeostasis has emerged as a promising perspective with significant therapeutic potential for Alzheimer's disease (AD). Herein, we design and construct a novel nanozyme-boosted MOF-CRISPR platform (CMOPKP), which can maintain redox homeostasis and rescue the impaired microenvironment of AD. By modifying the targeted peptides KLVFFAED, CMOPKP can traverse the blood-brain barrier and deliver the CRISPR activation system for precise activation of the Nrf2 signaling pathway and downstream redox proteins in regions characterized by oxidative stress, thereby reinstating neuronal antioxidant capacity and preserving redox homeostasis. Furthermore, cerium dioxide possessing catalase enzyme-like activity can synergistically alleviate oxidative stress. Further in vivo studies demonstrate that CMOPKP can effectively alleviate cognitive impairment in 3xTg-AD mouse models. Therefore, our design presents an effective way for regulating redox homeostasis in AD, which shows promise as a therapeutic strategy for mitigating oxidative stress in AD.

Mechanism of neurodegeneration mediated by clonal inflammatory microglia.

Langerhans cell Histiocytosis (LCH) and Erdheim-Chester disease (ECD) are clonal myeloid disorders, associated with MAP-Kinase activating mutations and an increased risk of neurodegeneration. Surprisingly, we found pervasive PU.1+ microglia mutant clones across the brain of LCH and ECD patients with and without neurological symptoms, associated with microgliosis, reactive astrocytosis, and neuronal loss. The disease predominated in the grey nuclei of the rhombencephalon, a topography attributable to a local proliferative advantage of mutant microglia. Presence of clinical symptoms was associated with a longer evolution of the disease and a larger size of PU.1+ clones (p= 0.0003). Genetic lineage tracing of PU.1+ clones suggest a resident macrophage lineage or a bone marrow precursor origin depending on patients. Finally, a CSF1R-inhibitor depleted mutant microglia and limited neuronal loss in mice suggesting an alternative to MAPK inhibitors. These studies characterize a progressive neurodegenerative disease, caused by clonal proliferation of inflammatory microglia (CPIM), with a decade(s)-long preclinical stage of incipient disease that represent a therapeutic window for prevention of neuronal death.

Programmed system for fatigue life prediction of excavator turntables based on multi-body dynamics and finite element analysis.

This study focuses on predicting mechanical fatigue in excavator turntables, critical components susceptible to failure due to variable operational loads. While conventional methods like finite element analysis(FEA) and multiaxial fatigue criteria have been used, they are limited by the complexity and cost of obtaining real operational load spectra. To address this challenge, our research presents a comprehensive approach that integrates multi-body dynamics modeling, finite element analysis, and MATLAB-based fatigue life prediction systems. Our methodology involves creating a finite element model for stress analysis, synthesizing load spectra from operational data, and utilizing Weibull distribution to analyze load magnitude probabilities. Subsequently, MATLAB imported the load spectrum and built the fatigue prediction framework to finalize the analysis. Furthermore, we have fully open-sourced our code on an open platform, incorporating default load profiles and predictive models within the code. Key findings pinpoint areas prone to stress concentration and fatigue. Key findings identify stress concentration areas and fatigue-prone regions, providing valuable insights for design optimization and durability improvement.

A Biocompatible Hydrogen-Bonded Organic Framework (HOF) as Sonosensitizer and Artificial Enzyme for In-Depth Treatment of Alzheimer's Disease.

Current phototherapeutic approaches for Alzheimer's disease (AD) exhibit restricted clinical outcomes due to the limited physical penetration and comprised brain microenvironment of noninvasive nanomedicine. Herein, a hydrogen-bonded organic framework (HOF) based sonosensitizer is designed and synthesized. Mn-TCPP, a planar molecule where Mn2+ ion is chelated in the core with a large p-conjugated system and 4 carboxylate acid groups, has been successfully used as building blocks to construct an ultrasound-sensitive HOF (USI-MHOF), which can go deep in the brain of AD animal models. The both in vitro and in vivo studies indicate that USI-MHOF can generate singlet oxygen (1O2) and oxidize ß-amyloid (Aß) to inhibit aggregation, consequently attenuating Aß neurotoxicity. More intriguingly, USI-MHOF exhibits catalase (CAT)- and superoxide dismutase (SOD)-like activities, mitigating neuron oxidative stress and reprograming the brain microenvironment. For better crossing the blood-brain barrier (BBB), the peptide KLVFFAED (KD8) has been covalently grafted to USI-MHOF for improving BBB permeability and Aß selectivity. Further, in vivo experiments demonstrate a significant reduction of the craniocerebral Aß plaques and improvement of the cognition deficits in triple-transgenic AD (3×Tg-AD) mice models following deep-penetration ultrasound treatment. The work provides the first example of an ultrasound-responsive biocompatible HOF as non-invasive nanomedicine for in-depth treatment of AD.

Polyoxometalates: metallodrug agents for combating amyloid aggregation.

Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects ∼50 million people globally. The accumulation of amyloid-ß (Aß) plaques, a predominant pathological feature of AD, plays a crucial role in AD pathogenesis. In this respect, Aß has been regarded as a highly promising therapeutic target for AD treatment. Polyoxometalates (POMs) are a novel class of metallodrugs being developed as modulators of Aß aggregation, owing to their negative charge, polarity, and three-dimensional structure. Unlike traditional discrete inorganic complexes, POMs contain tens to hundreds of metal atoms, showcasing remarkable tunability and diversity in nuclearities, sizes, and shapes. The easily adjustable and structurally variable nature of POMs allows for their favorable interactions with Aß. This mini-review presents a balanced overview of recent progress in using POMs to mitigate amyloidosis. Clear correlations between anti-amyloid activities and structural features of POMs are also elaborated in detail. Finally, we discuss the current challenges and future prospects of POMs in combating AD.

Superior AlGaN/GaN-Based Phototransistors and Arrays with Reconfigurable Triple-Mode Functionalities Enabled by Voltage-Programmed Two-Dimensional Electron Gas for High-Quality Imaging.

High-quality imaging units are indispensable in modern optoelectronic systems for accurate recognition and processing of optical information. To fulfill massive and complex imaging tasks in the digital age, devices with remarkable photoresponsive characteristics and versatile reconfigurable functions on a single-device platform are in demand but remain challenging to fabricate. Herein, an AlGaN/GaN-based double-heterostructure is reported, incorporated with a unique compositionally graded AlGaN structure to generate a channel of polarization-induced two-dimensional electron gas (2DEGs). Owing to the programmable feature of the 2DEGs by the combined gate and drain voltage inputs, with a particular capability of electron separation, collection and storage under different light illumination, the phototransistor shows reconfigurable multifunctional photoresponsive behaviors with superior characteristics. A self-powered mode with a responsivity over 100 A W-1 and a photoconductive mode with a responsivity of ≈108 A W-1 are achieved, with the ultimate demonstration of a 10 × 10 device array for imaging. More intriguingly, the device can be switched to photoelectric synapse mode, emulating synaptic functions to denoise the imaging process while prolonging the image storage ability. The demonstration of three-in-one operational characteristics in a single device offers a new path toward future integrated and multifunctional imaging units.

Novel sunlight-induced monochloramine activation system for efficient microcontaminant abatement.

As an eco-friendly and sustainable energy, solar energy has great application potential in water treatment. Herein, simulated sunlight was for the first time utilized to activate monochloramine for the degradation of environmental organic microcontaminants. Various microcontaminants could be efficiently degraded in the simulated sunlight/monochloramine system. The average innate quantum yield of monochloramine over the wavelength range of simulated sunlight was determined to be 0.068 mol/Einstein. With the determined quantum yield, a kinetic model was established. Based on the good agreement between the simulated and measured photolysis and radical contributions to the degradation of ibuprofen and carbamazepine, the major mechanism of monochloramine activation by simulated sunlight was proposed. Chlorine radical (Cl∙) and hydroxyl radical (HO∙) were major radicals responsible for microcontaminant degradation in the system. Moreover, the model facilitated a deep investigation into the effects of different reaction conditions (pH, monochloramine concentration, and water matrix components) on the degradation of ibuprofen and carbamazepine, as well as the roles of the involved radicals. The differences between simulated and measured degradation data of each microcontaminant under all conditions were less than 10 %, indicating the strong reliability of the model. The model could also make good prediction for microcontaminant degradation in the natural sunlight/monochloramine system. Furthermore, the formation of disinfection byproducts (DBPs) was evaluated at different oxidation time in simulated sunlight/monochloramine with and without post-chloramination treatment. In real waters, organic components showed more pronounced suppression on microcontaminant degradation efficiency than inorganic ions. This study provided a systematic investigation into the novel sunlight-induced monochloramine activation system for efficient microcontaminant degradation, and demonstrated the potential of the system in practical applications.

Refinement of kinetic model and understanding the role of dichloride radical (Cl2•-) in radical transformation in the UV/NH2Cl process.

The ultraviolet/monochloramine (UV/NH2Cl) process is an emerging advanced oxidation process with promising prospects in water treatment. Previous studies developed kinetic models of UV/NH2Cl for simulating radical concentrations and pollutant degradation. However, the reaction rate constants of Cl2•- with bicarbonate and carbonate (kCl2•-, HCO3- and kCl2•-, CO32-) were overestimated in literature. Consequently, when dosing 1 mM chloride and 1 mM bicarbonate, the current models of UV/NH2Cl severely under-predicted the experimental concentrations of three important radicals (i.e., hydroxyl radical (HO•), chlorine radical (Cl•), and dichloride radical (Cl2•-)) with great deviations (> 90 %). To investigate this issue, the transformation reactions among these three radicals in UV/NH2Cl were systematically studied. For the first time, it was found that in addition to Cl•, Cl2•- was also an important parent radical of HO• in the presence of chloride, and chloride could effectively compensate the inhibitory effect of bicarbonate on HO• generation in the system. Moreover, reactions and rate constants in current models were scrutinized from corresponding literature, and the reaction rate constants of Cl2•- with bicarbonate and carbonate (kCl2•-, HCO3- and kCl2•-, CO32-) were reevaluated to be 1.47 × 105 and 3.78 × 106 M-1s-1, respectively, by laser flash photolysis. With the newly obtained rate constants, the refined model could accurately simulate concentrations of all three radicals under different chloride and bicarbonate dosages with satisfactory deviations (< 30 %). Meanwhile, the refined model performed much better in predicting pollutant degradation and radical contribution compared with the unrefined model (with the previously estimated kCl2•-, HCO3- and kCl2•-, CO32-). The results of this study enhanced the accuracy and applicability of the kinetic model of UV/NH2Cl, and deepened the understanding of radical transformation in the process.

Computational pathology: A survey review and the way forward.

Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field's future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.

Efficient conversion of propane in a microchannel reactor at ambient conditions.

The oxidative dehydrogenation of propane, primarily sourced from shale gas, holds promise in meeting the surging global demand for propylene. However, this process necessitates high operating temperatures, which amplifies safety concerns in its application due to the use of mixed propane and oxygen. Moreover, these elevated temperatures may heighten the risk of overoxidation, leading to carbon dioxide formation. Here we introduce a microchannel reaction system designed for the oxidative dehydrogenation of propane within an aqueous environment, enabling highly selective and active propylene production at room temperature and ambient pressure with mitigated safety risks. A propylene selectivity of over 92% and production rate of 19.57 mmol mCu-2 h-1 are simultaneously achieved. This exceptional performance stems from the in situ creation of a highly active, oxygen-containing Cu catalytic surface for propane activation, and the enhanced propane transfer via an enlarged gas-liquid interfacial area and a reduced diffusion path by establishing a gas-liquid Taylor flow using a custom-made T-junction microdevice. This microchannel reaction system offers an appealing approach to accelerate gas-liquid-solid reactions limited by the solubility of gaseous reactant.

ARTIFICIAL INTELLIGENCE FOR OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY-BASED DISEASE ACTIVITY PREDICTION IN AGE-RELATED MACULAR DEGENERATION.

PURPOSE: The authors hypothesize that optical coherence tomography angiography (OCTA)-visualized vascular morphology may be a predictor of choroidal neovascularization status in age-related macular degeneration (AMD). The authors thus evaluated the use of artificial intelligence (AI) to predict different stages of AMD disease based on OCTA en face 2D projections scans. METHODS: Retrospective cross-sectional study based on collected 2D OCTA data from 310 high-resolution scans. Based on OCT B-scan fluid and clinical status, OCTA was classified as normal, dry AMD, wet AMD active, and wet AMD in remission with no signs of activity. Two human experts graded the same test set, and a consensus grading between two experts was used for the prediction of four categories. RESULTS: The AI can achieve 80.36% accuracy on a four-category grading task with 2D OCTA projections. The sensitivity of prediction by AI was 0.7857 (active), 0.7142 (remission), 0.9286 (dry AMD), and 0.9286 (normal) and the specificity was 0.9524, 0.9524, 0.9286, and 0.9524, respectively. The sensitivity of prediction by human experts was 0.4286 active choroidal neovascularization, 0.2143 remission, 0.8571 dry AMD, and 0.8571 normal with specificity of 0.7619, 0.9286, 0.7857, and 0.9762, respectively. The overall AI classification prediction was significantly better than the human (odds ratio = 1.95, P = 0.0021). CONCLUSION: These data show that choroidal neovascularization morphology can be used to predict disease activity by AI; longitudinal studies are needed to better understand the evolution of choroidal neovascularization and features that predict reactivation. Future studies will be able to evaluate the additional predicative value of OCTA on top of other imaging characteristics (i.e., fluid location on OCT B scans) to help predict response to treatment.

ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model.

A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). However, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs, complicating the inference of tumor phylogenies. We introduce a new evolutionary model, the constrained k-Dollo model, that uses SNVs as phylogenetic markers but constrains losses of SNVs according to clusters of cells. We derive an algorithm, ConDoR, that infers phylogenies from targeted scDNA-seq data using this model. We demonstrate the advantages of ConDoR on simulated and real scDNA-seq data.

Construction of organic/GaN heterostructures for DUV-to-NIR broadband photodetection.

Herein, a broadband photodetector (BPD) is constructed with consistent and stable detection abilities for deep ultraviolet to near-infrared spectral range. The BPD integrates the GaN template with a hybrid organic semiconductor, PM6:Y6, via the spin-coating process, and is fabricated in the form of asymmetric metal-semiconductor-metal structure. Under an optimal voltage, the device shows consistent photoresponse within 254 to 850 nm, featuring high responsivity (10 to 60 A/W), photo-to-dark-current ratio over 103, and fast response time. These results show the potential of such organic/GaN heterojunctions as a simple and effective strategy to build BPDs for a reliable photo-sensing application in the future.

Hydrogen-bonded organic frameworks: new horizons in biomedical applications.

Hydrogen-bonded organic frameworks (HOFs) are an emerging attractive class of highly crystalline porous materials characterized by significant biocompatibility, rich chemical functionalities and well-defined porosity. The unique advantages including metal-free nature and reversible binding manner significantly distinguish HOFs from other porous materials in the biotechnology and biomedical field. However, the relevant HOF studies still remain in their infancy despite the promising and remarkable results that have been presented in recent years. Due to the intricate and dynamic nature of physiological conditions, the major challenge lies in the stability and structural diversity of HOFs in vivo. In this Tutorial Review, we summarize the common building blocks for the construction of HOF-based functional biomaterials and the latest developments in the biological field. Moreover, we highlight current challenges regarding the stability and functionalization of HOFs along with the corresponding potential solutions. This Tutorial Review will have a profound effect in future years on the design and applications of HOF-based biomaterials.

Simultaneous estimation of magnetic moment and Brownian relaxation time distributions of magnetic nanoparticles based on magnetic particle spectroscopy for biosensing application.

Magnetic nanoparticles (MNPs) exhibit unique physicochemical characteristics owing to their comparable dimensions with important biological substances, high surface-to-volume ratios, size-dependent magnetic properties, and temperature sensitivity. In this study, we present a novel method for simultaneously estimating the magnetic moment and Brownian relaxation time distribution of MNPs based on AC magnetization harmonics. We provide a detailed description of the theoretical framework and experimental procedures. The dynamics of MNP magnetization are described using the Fokker-Planck equation, and a matrix equation is established to connect the magnetic moment, Brownian relaxation time, and magnetization harmonics. By employing a non-negative linear least squares algorithm with constraints, the magnetic moment and Brownian relaxation time distributions are inversed, which are then converted into the distributions of core sizes and hydrodynamic sizes. Finally, the estimated core size distribution reconstructed from M-H curves is consistent with the hydrodynamic size distribution measured by dynamic light scattering. This method is particularly useful for facilitating quantitative magnetic immunoassays.

Spin Coherence and Spin Relaxation in Hybrid Organic-Inorganic Lead and Mixed Lead-Tin Perovskites.

Metal halide perovskites make up a promising class of materials for semiconductor spintronics. Here we report a systematic investigation of coherent spin precession, spin dephasing and spin relaxation of electrons and holes in two hybrid organic-inorganic perovskites MA0.3FA0.7PbI3 and MA0.3FA0.7Pb0.5Sn0.5I3 using time-resolved Faraday rotation spectroscopy. With applied in-plane magnetic fields, we observe robust Larmor spin precession of electrons and holes that persists for hundreds of picoseconds. The spin dephasing and relaxation processes are likely to be sensitive to the defect levels. Temperature-dependent measurements give further insights into the spin relaxation channels. The extracted electron Landé g-factors (3.75 and 4.36) are the biggest among the reported values in inorganic or hybrid perovskites. Both the electron and hole g-factors shift dramatically with temperature, which we propose to originate from thermal lattice vibration effects on the band structure. These results lay the foundation for further design and use of lead- and tin-based perovskites for spintronic applications.

Enhanced hydroxyl radical generation for micropollutant degradation in the In2O3/Vis-LED process through the addition of periodate.

Periodate (PI) as an oxidant has been extensively studied for organic foulants removal in advanced oxidation processes. Here PI was introduced into In2O3/Vis-LED process to enhance the formation of ·OH for promoting the degradation of organic foulants. Results showed that the addition of PI would significantly promote the removal of sulfamethoxazole (SMX) in the In2O3/Vis-LED process (from 9.26% to 100%), and ·OH was proved to be the dominant species in the system. Besides, the process exhibited non-selectivity in the removal of different organic foulants. Comparatively, various oxidants (e.g., peroxymonosulfate, peroxydisulfate, and hydrogen peroxide) did not markedly promote the removal of SMX in the In2O3/Vis-LED process. Electrochemical analyses demonstrated that PI could effectively receive photoelectrons, thus inhibiting the recombination of photogenerated electron-hole (e-/h+) pairs. The holes then oxidized the adsorbed H2O to generate ·OH, and the PI converted to iodate at the same time. Additionally, the removal rate of SMX reduced from 100% to 17.2% as Vis-LED wavelengths increased from 440 to 560 nm, because of the low energy of photons produced at longer wavelengths. Notably, the species of PI do not affect its ability to accept electrons, resulting in the degradation efficiency of SMX irrespective of pH (4.0-10.0). The coexistence of inorganic cations and anions (such as Cl-, CO32-/HCO3-, SO42-, Ca2+, and Mg2+) also had an insignificant effect on SMX degradation. Furthermore, the process also showed excellent degradation potential in real water. The proposed strategy provides a new insight for visible light-catalyzed activation of PI and guidance to explore green catalytic processes for high-efficiency removal of various organic foulants.