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BACKGROUND: Since its development in the 1980 s, chemical vapor deposition (CVD) diamond has found wide application in addressing various engineering challenges, owing to its outstanding characteristics, including exceptionally high hardness, excellent thermal conductivity, and remarkable stability. Notably, processing tools utilizing CVD diamond as the working material exhibit substantial potential for application in the field of mechanical manufacturing. Serving as a viable substitute for natural diamond, CVD diamond processing tools not only offer advantages in production costs but also ensure processing performance on par with natural diamonds. This presents a valuable and effective approach for achieving advanced manufacturing with high precision and low production costs. AIM OF REVIEW: The research progress of CVD diamond processing tools is comprehensively reviewed from four perspectives, encompassing the CVD process of diamonds, preparation methods, processing applications, and future development directions of CVD diamond processing tools. KEY SCIENTIFIC CONCEPTS OF REVIEW: The classification and exposition of CVD diamond deposition processes were presented. The fabrication of CVD diamond processing tools was elaborated. The machining applications of CVD diamond processing tools were then reviewed, mainly focusing on cutting and grinding processes, along with the tool wear characteristics. Finally, research challenges pertaining to CVD diamond processing tools were summarized, with insights proposed for future development opportunities and the anticipation of enhanced performance for prospective engineering applications.

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Sapphire ultrasonic vibration-assisted flexible polishing (UVAFP) is a promising technique for comprehensively improving the surface integrity of machined parts. The technique was performed on an ultra-precision machine tool with the in-situ monitoring systems in this paper, which aims to provide a new perspective for understanding the material removal mechanisms in the sapphire UVAFP process. A Taguchi L9 (43) orthogonal experiment was conducted to investigate the effects of feed distance, spindle speed, ultrasonic vibration (UV), and polishing time on the surface finish and material removal in the process. In addition, the effect of a polyurethane ball tool is not trivial. A single-factor experiment was conducted for exploring it. Based on a laser displacement measurement system and an acoustic emission sensor system, the characteristics of time-dependent ultrasonic amplitude and ultrasonic frequency for the sapphire UVAFP system were analyzed, with the effectiveness of UV demonstrated. Based on a three-component force measurement system, the characteristics of normal force and its relationship with process parameters and tool deformation were analyzed, with macro- and micro-level examined. In conclusion, this paper presents the characterization of UV and polishing force in the sapphire UVAFP process, providing novel insights into understanding the material removal mechanisms of sapphire and even more manufacturing problems.

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OBJECTIVE: This study aimed to identify a quantitative index for optical coherence tomography (OCT) images to discriminate tumours from surrounding tissues. SUBJECTS AND METHODS: Based on OCT measurements, mean grey values were determined from 432 locations on fifty-four human tissue specimens (eighteen cancerous, para-cancerous, and normal tissues each). These results were histologically evaluated by hematoxylin and eosin staining (H&E). RESULTS: The mean grey values of oral squamous cell carcinoma (OSCC) measurements were significantly different from those of the surrounding healthy tissue (p value < 0.0001), with the former being higher. The sensitivity and specificity of detecting tumourous tissue using this approach were 93 and 94%, respectively. CONCLUSIONS: OCT as a non-invasive, real-time imaging method, correlates well with H&E pathological images. It can effectively distinguish squamous cell carcinoma from normal tissues with high sensitivity and specificity and is thus expected to assist and guide tumour margin evaluation. CLINICAL RELEVANCE: This discovery highlights the potential of OCT in the objective evaluation of tumour margin during surgery.

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Water occurrence states in sewage sludge, influenced by sludge physicochemical properties, are crucial for sludge dewaterability and have recently been regarded as a research hotspot. Here, the multifold characteristics of sludge flocs during hydrothermal treatment, including rheological properties, solid-water interfacial interactions, and the polarity distribution and molecular structure of extracellular polymeric substances (EPS), were systematically investigated, and the impact of these characteristics on sludge dewaterability was explored in depth. Hydrothermal treatment at 80 °C and 100 °C induced the conversion of free water into bound water, while an increase in temperature to 180 °C resulted in a significant decrease in bound water content, approximately 4-fold lower than at 100 °C. In addition to the conventional view of decreased sludge surface hydrophilicity at high temperatures, the decline in bound water was associated with the reduction in sludge apparent viscosity. XAD resin fractionation identified the hydrophobic/hydrophilic EPS (HPO-/HPI) ratio as an important factor determining water occurrence states. Especially, hydrolysis of HPI-related hydrophilic proteins and subsequent increase in HPO-related tryptophan-like substances played a dominant role in reducing sludge viscosity and facilitating the release of bound water. Protein conformational analysis revealed that the disruption of α-helix structures and disulfide bonds significantly reduced EPS water-holding capacity, providing strong evidence for the potential of targeting these dense structure units to enhance sludge dewaterability. These findings provide a holistic understanding of multidimensional drivers of water occurrence states in sludge, and guide directions for optimizing sludge treatment efficiency through EPS modification.

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Aggravated accumulation of emerging micropollutants (EMs) in aquatic environments, especially after COVID-19, raised significant attention throughout the world for safety concerns. This article reviews the sources and occurrence of 25 anti-COVID-19 related EMs in wastewater. It should be pointed out that the concentration of anti-COVID-19 related EMs, such as antivirals, plasticizers, antimicrobials, and psychotropic drugs in wastewater increased notably after the pandemic. Furthermore, the ecotoxicity, ecological, and health risks of typical EMs before and after COVID-19 were emphatically compared and analyzed. Based on the environmental health prioritization index method, the priority control sequence of typical EMs related to anti-COVID-19 was identified. Lopinavir (LPV), venlafaxine (VLX), di(2-ethylhexyl) phthalate (DEHP), benzalkonium chloride (BAC), triclocarban (TCC), di-n-butyl phthalate (DBP), citalopram (CIT), diisobutyl phthalate (DIBP), and triclosan (TCS) were identified as the top-priority control EMs in the post-pandemic period. Besides, some insights into the toxicity and risk assessment of EMs were also provided. This review provides direction for proper understanding and controlling the EMs pollution after COVID-19, and is of significance to evaluate objectively the environmental and health impacts induced by COVID-19.

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To realize the energy and resource utilization from organic solid waste, a two-phase microbial desalination cell (TPMDC) was constructed using dewatered sludge and kitchen waste as the anode substrate. The performance of electricity generation and composting efficacy was investigated, along with a comprehensive assessment of the potential health risks associated with the land use of the resulting mixed compost products. Experimental outcomes revealed a maximum open-circuit voltage of 0.893 ± 0.005 V and a maximum volumetric power density of 0.797 ± 0.009 W/m³. After 90 days of composting enhanced by microbial electrochemistry, a significant organic matter removal rate of 31.13 ± 0.44 % was obtained, and the anode substrate electric conductivity was reduced by 30.02 ± 0.04 % based on the anode desalination. Simultaneously, there was an increase in the content of available nitrogen, phosphorus, and potassium, as well as an improvement in the seed germination index. The forms of heavy metals shifted from bioavailable to stable residual states. The non-carcinogenic hazard index (HI) values for heavy metals and polycyclic aromatic hydrocarbons (PAHs) during the land use of compost products were less than 1, and the total carcinogenic risk (TCR) values for heavy metals and PAHs were below the acceptable threshold of 10-4. The occupational population risk of infection from five pathogens was higher than that of the general public, with all risk values ranging from 8.67 × 10-8 to 1, where the highest risk was attributed to occupational exposure to Legionella. These outcomes demonstrated that the mixture of dewatered sludge and kitchen waste was an appropriate anode substrate to enhance TPMDC stability for electricity generation, and its compost products have promising land use suitability and acceptable land use risk, which will provide important guidance for the safe treatment and disposal of organic solid waste.

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Fundus photography (FP) is a crucial technique for diagnosing the progression of ocular and systemic diseases in clinical studies, with wide applications in early clinical screening and diagnosis. However, due to the nonuniform illumination and imbalanced intensity caused by various reasons, the quality of fundus images is often severely weakened, brings challenges for automated screening, analysis, and diagnosis of diseases. To resolve this problem, we developed strongly constrained generative adversarial networks (SCGAN). The results demonstrate that the quality of various datasets were more significantly enhanced based on SCGAN, simultaneously more effectively retaining tissue and vascular information under various experimental conditions. Furthermore, the clinical effectiveness and robustness of this model were validated by showing its improved ability in vascular segmentation as well as disease diagnosis. Our study provides a new comprehensive approach for FP and also possesses the potential capacity to advance artificial intelligence-assisted ophthalmic examination.

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OBJECTIVES: To investigate the potential mechanisms of shikonin in preventing and treating periodontitis using network pharmacology and molecular docking methods. MATERIALS AND METHODS: The targets of shikonin were obtained in TCMSP and SEA databases, and targets of periodontitis were gathered from the OMIM, GeneCards and Drugbank Databases. The intersecting targets were entered into the DAVID database to obtain the relevant biological functions and pathways by GO and KEGG enrichment analysis. The obtained targets were analysed the protein-protein interaction (PPI) in STRING platform. In Cytoscape 3.8.0, the network analysis function with the MCODE plug-in were used to obtain the key targets, of shikonin and periodontitis. Molecular docking and molecular dynamics simulation (MD) were used to assess the affinity between the shikonin and the key targets. RESULTS: Shikonin was screened for 22 targets and periodontitis was screened for 944 targets, the intersecting targets were considered as potential therapeutic targets. The targets played important roles in cellular response to hypoxia, response to xenobiotic stimulus and positive regulates of apoptotic process by GO enrichment analysis. 10 significant pathways were analyzed by KEGG, such as human cytomegalovirus infection and PI3K-Akt signaling pathway, etc. Cytoscape software screened the key genes including AKT1, CCL5, CXCR4, PPARG, PTEN, PTGS2 and TP53. Molecular docking and MD results showed that shikonin could bind stably to the targets. CONCLUSIONS: The present study enriched the molecular mechanisms in periodontitis with shikonin, providing potential therapeutic targets for periodontitis.

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The development of sustainable advanced energy conversion technologies and efficient pollutant treatment processes is a viable solution to the two global crises of the lack of non-renewable energy resources and environmental harm. In recent years, the interaction of biological and chemical oxidation units to utilize biomass has been extensively studied. Among these systems, bio-electro-Fenton (BEF) and photo-bio-electro-Fenton (PBEF) systems have shown prospects for application due to making rational and practical conversion and use of energy. This review compared and analyzed the electron transfer mechanisms in BEF and PBEF systems, and systematically summarized the techniques for enhancing system performance based on the generation, transfer, and utilization of electrons, including increasing the anode electron recovery efficiency, enhancing the generation of reactive oxygen species, and optimizing operational modes. This review compared the effects of different methods on the electron flow process and fully evaluated the benefits and drawbacks. This review may provide straightforward suggestions and methods to enhance the performance of BEF and PBEF systems and inspire the reader to explore the generation and utilization of sustainable energy more deeply.

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Cerebral ischemia-reperfusion injury (CIRI) is a major challenge to neuronal survival in acute ischemic stroke (AIS). However, effective neuroprotective agents remain to be developed for the treatment of CIRI. In this work, we have developed an Anti-TRAIL protein-modified and indocyanine green (ICG)-responsive nanoagent (Anti-TRAIL-ICG) to target ischemic areas and then reduce CIRI and rescue the ischemic penumbra. In vitro and in vivo experiments have demonstrated that the carrier-free nanoagent can enhance drug transport across the blood-brain barrier (BBB) in stroke mice, exhibiting high targeting ability and good biocompatibility. Anti-TRAIL-ICG nanoagent played a better neuroprotective role by reducing apoptosis and ferroptosis, and significantly improved ischemia-reperfusion injury. Moreover, the multimodal imaging platform enables the dynamic in vivo examination of multiple morphofunctional information, so that the dynamic molecular events of nanoagent can be detected continuously and in real time for early treatment in transient middle cerebral artery occlusion (tMCAO) models. Furthermore, it has been found that Anti-TRAIL-ICG has great potential in the functional reconstruction of neurovascular networks through optical coherence tomography angiography (OCTA). Taken together, our work effectively alleviates CIRI after stoke by blocking multiple cell death pathways, which offers an innovative strategy for harnessing the apoptosis and ferroptosis against CIRI.

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The release of sludge-derived heavy metals (HMs) to soil and their subsequent migration into groundwater poses a significant challenge for safe and low-carbon sludge land application. This study developed a predictive framework to simulate 60-year sludge land application, evaluating the risk of HMs pollution in the soil-groundwater environment and assessing the influence of soil and water properties. HYDRUS-2D simulations revealed that highly mobile Cu, Ni, and Zn penetrated a 10 m soil layer over a 60-year period, contributing to groundwater pollution. In contrast, Cr was easily sequestered within the topsoil layer after 5-years continuous operation. The non-equilibrium parameter α could serve as an indicator for assessing their potential risk. Furthermore, the limited soil adsorption sites for Pb (f = 0.02772) led to short-term (1-year) groundwater pollution at a 0.5 m-depth. Bayesian Networks model outcomes indicated that humic-like organics crucially influenced HMs transformation, enhancing the desorption of Cd, Cu, Ni, Pb, and Zn, while inhibiting the desorption for Cr. Additionally, electrical conductivity promoted the release of most HMs, in contrast to the Mn mineralogy in soil. This study bridges the gap between the macro-level HMs migration trends and the micro-level adsorption-desorption characteristics, providing guidance for the safe land application of sewage sludge. ENVIRONMENTAL IMPLICATION: This study introduces a framework integrating HYDRUS-2D simulations with Bayesian Networks to assess the risks of groundwater pollution by heavy metals (HMs) over a 60-year sludge application. Sludge-derived Cu, Ni, and Zn are found to penetrate soil up to 10 m and exceed safety limits, with the non-equilibrium parameter α serving as an indicator for pollution risk. The importance of nutrients from sludge-amended soil for the transformation of HMs in the subsurface environment highlights the need for enhanced sludge management, specifically through more detailed regulation of nutrient composition. These findings contribute to developing precise strategies for the long-term sludge land application.

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The addition of composite conductive materials is being increasingly recognized as a promising strategy to enhance anaerobic digestion (AD) performance. However, the influence of these materials on protein hydrolysis has been poorly documented. Here, a novel magnetic biochar derived from oil sludge and straw was synthesized using different iron sources and successfully applied in sludge AD. Experimental results revealed that magnetic biochar modified by Fe2+ exhibited excellent electron transfer capacity, moderate magnetization, diverse functional groups (e.g. C=O, C-O=O-), and abundant iron distribution. These characteristics significantly enhanced the hydrolysis of tryptophan-like components, leading to increased methane production (144.44 mL gVS-1vs 79.72 mL gVS-1 in the control test). Molecular docking analysis revealed that the binding of magnetic biochar related Fe2+ and Fe3+, onto sludge proteins via hydrogen bond played a key role in promoting subsequent protein hydrolysis. Additionally, the noteworthy conservation of protein structures from α-helix and ß-sheet to random coil, along with the breakdown of the amide I-associated C=O group and amide III-related CN and NH bonds following the addition of magnetic biochar, accelerated the degradation of sludge protein. Observation of variations in protease activity, coenzyme F420, electron transfer system (ETS), and conductivity within the AD systems, particularly the enrichment of Methanospirillum and Methanosaeta archaea, as well as the Petrimonas, Comamonas, and Syntrophomonas bacteria, suggested that magnetic biochar facilitated a conducive environment by improving hydrolysis-acidification and the direct interspecies electron transfer (DIET) process for acetoclastic methanogens. Moreover, metabolic pathways further proved that tryptophan metobalism and acetoclastic methanogenesis were both facilitated by magnetic biochar. This study provides an in-depth understanding of the impact of magnetic biochar on protein hydrolysis in sewage sludge AD.

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Biochar has been proved to improve methane production in high solids anaerobic co-digestion (HS-AcoD) of dewatered sludge (DS) and food waste (FW), but its potential mechanism for simultaneous methane production and phosphorus (P) transformation has not been sufficiently revealed. Results showed that the optimal preparation temperature and dosage of sludge-based biochar were selected as 300 °C and 0.075 g·g-1, respectively. Under this optimized condition, the methane production of the semi-continuous reactor increased by 54%, and the active phosphorus increased by 18%. The functional microorganisms, such as Methanosarcina, hydrogen-producing, sulfate-reducing, and iron-reducing bacteria, were increased. Metabolic pathways associated with sulfate reduction and methanogenesis, especially hydrogenotrophic methanogenesis, were enhanced, which in turn promoted methanogenesis and phosphorus transformation and release. This study provides theoretical support for simultaneously recovery of carbon and phosphorus resources from DS and FW using biochar.

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Ocular neovascularization is the leading cause of blindness in clinical settings. Pathological angiogenesis of the eye can be divided into corneal neovascularization (CoNV), retinal neovascularization (RNV, including diabetic retinopathy and retinopathy of prematurity), and choroidal neovascularization (CNV) based on the anatomical location of abnormal neovascularization. Although anti-Vascular endothelial growth factor (VEGF) agents have wide-ranging clinical applications and are an effective treatment for neovascular eye disease, many deficiencies in this treatment strategy remain. Recently, emerging evidence has demonstrated that macrophages are vital during the process of physiological and pathological angiogenesis. Monocyte-macrophage lineage is diverse and plastic, they can shift between different activation modes and have different functions. Due to the obvious regulatory effect of macrophages on inflammation and angiogenesis, macrophages have been increasingly studied in the field of ophthalmology. Here, we detail how macrophage activated and the role of different subtypes of macrophages in the pathogenesis of ocular neovascularization. The complexity of macrophages has recently taken center stage owing to their subset diversity and tightly regulated molecular and metabolic phenotypes. In this review, we reveal the functional and phenotypic characterization of macrophage subsets associated with ocular neovascularization, more in-depth research is needed to explore the specific mechanisms by which macrophages regulate angiogenesis as well as macrophage polarization. Targeted regulation of macrophage differentiation based on their phenotype and function could be an effective approach to treat and manage ocular neovascularization in the future.

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BACKGROUND/AIM: Probing brain tumor microvasculature holds significant importance in both basic cancer research and medical practice for tracking tumor development and assessing treatment outcomes. However, few imaging methods commonly used in clinics can noninvasively monitor the brain microvascular network at high precision and without exogenous contrast agents in vivo. The present study aimed to investigate the characteristics of microvasculature during brain tumor development in an orthotopic glioma mouse model. MATERIALS AND METHODS: An orthotopic glioma mouse model was established by surgical orthotopic implantation of U87-MG-luc cells into the mouse brain. Then, optical coherence tomography angiography (OCTA) was utilized to characterize the microvasculature progression within 14 days. RESULTS: The orthotopic glioma mouse model evaluated by bioluminescence imaging and MRI was successfully generated. As the tumor grew, the microvessels within the tumor area slowly decreased, progressing from the center to the periphery for 14 days. CONCLUSION: This study highlights the potential of OCTA as a useful tool to noninvasively visualize the brain microvascular network at high precision and without any exogenous contrast agents in vivo.

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Proteins and carbohydrates are important organics in waste activated sludge, and greatly affect methane production and microbial community composition in anaerobic digestion systems. Here, a series of co-substrates with different molecular weight were applied to investigate the interactions between microbial dynamics and the molecular weight of co-substrates. Biochemical methane production assays conducted in batch co-digesters showed that feeding high molecular weight protein and carbohydrate substrates resulted in higher methane yield and production rates. Moreover, high-molecular weight co-substrates increased the microbial diversity, enriched specific microbes including Longilinea, Anaerolineaceae, Syner-01, Methanothrix, promoted acidogenic and acetoclastic methanogenic pathways. Low-molecular weight co-substrates favored the growth of JGI-0000079-D21, Armatimonadota, Methanosarcina, Methanolinea, and improved hydrogenotrophic methanogenic pathway. Besides, Methanoregulaceae and Methanolinea were indicators of methane yield. This study firstly revealed the complex interactions between co-substrate molecular weight and microbial communities, and demonstrated the feasibility of adjusting co-substrate molecular weight to improve methane production process.

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AIM: To investigate the types of bacteria in patients with eye infections in Suzhou and their drug resistance to commonly used antibacterial drugs. METHODS: The clinical data of 155 patients were retrospectively collected in this study, and the pathogenic bacteria species and drug resistance of each pathogenic bacteria were analyzed. RESULTS: Among the 155 patients (age from 12 to 87 years old, with an average age of 57, 99 males and 56 females) with eye infections (160 eyes: 74 in the left eye, 76 in the right eye and 5 in both eyes, all of which were exogenous), 71 (45.81%) strains were gram-positive bacteria, 23 (14.84%) strains were gram-negative bacteria and 61 (39.35%) strains were fungi. Gram-positive bacteria were highly resistant to penicillin and erythromycin (78.87% and 46.48% respectively), but least resistant to vancomycin at 0. Gram-negative bacteria were highly resistant to cefoxitin and compound sulfamethoxazole (100% and 95.65% respectively), but least resistant to meropenem at 0. Comparison of the resistance of gram-positive and gram-negative bacteria to some drugs revealed statistically significant differences (P<0.05) in the resistance of both to cefoxitin, cotrimoxazole, levofloxacin, cefuroxime, ceftriaxone and ceftazidime, and both had higher rates of resistance to gram-negative bacteria than to gram-positive bacteria. The distribution of bacterial infection strains showed that Staphylococcus epidermidis was the most common strain in the conjunctiva, cornea, aqueous humor or vitreous body and other eye parts. Besides, Fusarium and Pseudomonas aeruginosa were also among the most common strains of conjunctival and corneal infections. CONCLUSION: Gram-positive bacteria are the dominant bacteria in eye infections, followed by gram-negative bacteria and fungi. Considering the resistance of gram-negative bacteria to multiple drugs, monitoring of bacteria should be strengthened in eye bacterial infections for effective prevention and control to reduce complications caused by eye infections.

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Throughout the entire process of sludge treatment and disposal, it is crucial to explore stable and efficient techniques to improve sludge dewaterability, which can facilitate subsequent resource utilization and space and cost savings. Traditional Fenton oxidation has been widely researched to enhance the performance of sludge dewaterability, which was limited by the additional energy input and the instabilities of Fe2+ and H2O2. To reduce the consumption of energy and chemicals and further break the rate-limiting step of the iron cycle, a novel and feasible method that constructed microbial fuel cell powered electro-Fenton systems (MFCⓅEFs) with ferrite and biochar electrode (MgFe2O4@BC/CF) was successfully demonstrated. The MFCⓅEFs with MgFe2O4@BC/CF electrode achieved specific resistance filtration and sludge cake water content of 2.52 × 1012 m/kg and 66.54 %. Cellular structure and extracellular polymeric substances (EPS) were disrupted, releasing partially bound water and destroying hydrophilic structures to facilitate sludge flocs aggregation, which was attributed to the oxidation of hydroxyl radicals. The consistent electron supply supplied by MFCⓅEFs and catalytically active sites on the surface of the multifunctional functional group electrode was responsible for producing more hydroxyl radicals and possessing a better oxidizing ability. The study provided an innovative process for sludge dewaterability improvement with high efficiency and low energy consumption, which presented new insights into the green treatment of sludge.

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The ubiquity of refractory organic matter in aquatic environments necessitates innovative removal strategies. Sulfate radical-based advanced oxidation has emerged as an attractive solution, offering high selectivity, enduring efficacy, and anti-interference ability. Among many technologies, sulfite activation, leveraging its cost-effectiveness and lower toxicity compared to conventional persulfates, stands out. Yet, the activation process often relies on transition metals, suffering from low atom utilization. Here we introduce a series of single-atom catalysts (SACs) employing transition metals on g-C3N4 substrates, effectively activating sulfite for acetaminophen degradation. We highlight the superior performance of Fe/CN, which demonstrates a degradation rate constant significantly surpassing those of Ni/CN and Cu/CN. Our investigation into the electronic and spin polarization characteristics of these catalysts reveals their critical role in catalytic efficiency, with oxysulfur radical-mediated reactions predominating. Notably, under visible light, the catalytic activity is enhanced, attributed to an increased generation of oxysulfur radicals and a strengthened electron donation-back donation dynamic. The proximity of Fe/CN's d-band center to the Fermi level, alongside its high spin polarization, is shown to improve sulfite adsorption and reduce the HOMO-LUMO gap, thereby accelerating photo-assisted sulfite activation. This work advances the understanding of SACs in environmental applications and lays the groundwork for future water treatment technologies.

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Introduction: Accurate identification of the myocardial texture features of fat around the coronary artery on coronary computed tomography angiography (CCTA) images are crucial to improve clinical diagnostic efficiency of myocardial ischemia (MI). However, current coronary CT examination is difficult to recognize and segment the MI characteristics accurately during earlier period of inflammation. Materials and methods: We proposed a random forest model to automatically segment myocardium and extract peripheral fat features. This hybrid machine learning (HML) model is integrated by CCTA images and clinical data. A total of 1,316 radiomics features were extracted from CCTA images. To further obtain the features that contribute the most to the diagnostic model, dimensionality reduction was applied to filter features to three: LNS, GFE, and WLGM. Moreover, statistical hypothesis tests were applied to improve the ability of discriminating and screening clinical features between the ischemic and non-ischemic groups. Results: By comparing the accuracy, recall, specificity and AUC of the three models, it can be found that HML had the best performance, with the value of 0.848, 0.762, 0.704 and 0.729. Conclusion: In sum, this study demonstrates that ML-based radiomics model showed good predictive value in MI, and offer an enhanced tool for predicting prognosis with greater accuracy.