An efficient visual servo tracker for herd monitoring by UAV.

It is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average - 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.

Association of Sleep Pattern and Genetic Susceptibility with Obstructive Sleep Apnea: A Prospective Analysis of the UK Biobank.

Purpose: The prevalence of obstructive sleep apnea (OSA) is high worldwide. This study aimed to quantify the relationship between the incidence of OSA and sleep patterns and genetic susceptibility. Methods: A total of 355,133 white British participants enrolled in the UK Biobank between 2006 and 2010 with follow-up data until September 2021 were recruited. We evaluated sleep patterns using a customized sleep scoring method based on the low-risk sleep phenotype, defined as follows: morning chronotype, 7-8 hours of sleep per day, never/rarely experience insomnia, no snoring, no frequent daytime sleepiness, never/rarely nap, and easily getting up early. The polygenic risk score was calculated to assess genetic susceptibility to OSA. Cox proportional hazard models were used to evaluate the associations between OSA and sleep patterns and genetic susceptibility. Results: During a mean follow-up of 12.57 years, 4618 participants were diagnosed with OSA (age: 56.83 ± 7.69 years, women: 31.3%). Compared with those with a poor sleep pattern, participants with a normal (HR: 0.42, 95% CI: 0.38-0.46), ideal (HR: 0.21, 95% CI: 0.19-0.24), or optimal (HR: 0.15, 95% CI: 0.12-0.18) sleep pattern were significantly more likely to have OSA. The genetic susceptibility of 173,239 participants was calculated, and the results showed that poor (HR: 3.67, 95% CI: 2.95-4.57) and normal (HR: 1.89, 95% CI: 1.66-2.16) sleep patterns with high genetic susceptibility can increase the risk for OSA. Conclusion: This large-scale prospective study provides evidence suggesting that sleep patterns across seven low-risk sleep phenotypes may protect against OSA in individuals with varying degrees of genetic susceptibility.

Controlled release of vitamin A palmitate from crosslinked cyclodextrin organic framework for dry eye disease therapy.

Controlled release drug delivery systems of eye drops are a promising ophthalmic therapy with advantages of good patient compliance and low irritation. However, the lack of a suitable drug carrier for ophthalmic use limits the development of the aforementioned system. Herein, the crosslinked cyclodextrin organic framework (COF) with a cubic porous structure and a uniform particle size was synthesized and applied to solidify vitamin A palmitate (VAP) by using the solvent-free method. The VAP@COF suspension eye drops were formulated by screening co-solvents, suspending agents, and stabilizing agents to achieve a homogeneous state and improve stability. According to the in vitro release study, the VAP@COF suspension exhibited a controlled release of VAP within 12 h. Both the ex vivo corneal contact angle and in vivo fluorescence tracking indicated that the VAP@COF suspension prolonged the VAP residence time on the ocular surface. This suspension accelerated the recovery of the dry eye disease (DED) model in New Zealand rabbits. Furthermore, the suspension was non-cytotoxic to human corneal epithelial cells and non-irritation to rabbit eyes. In summary, the particulate COF is an eye-acceptable novel carrier that sustains release and prolongs the VAP residence time on the ocular surface for DED treatment.

Effect of luteolin on glioblastoma's immune microenvironment and tumor growth suppression.

BACKGROUND: Glioblastoma is the most malignant and prevalent primary human brain tumor, and the immunological microenvironment controlled by glioma stem cells is one of the essential elements contributing to its malignancy. The use of medications to ameliorate the tumor microenvironment may give a new approach for glioma treatment. METHODS: Glioma stem cells were separated from clinical patient-derived glioma samples for molecular research. Other studies, including CCK8, EdU, Transwell, and others, supported luteolin's ability to treat glioma progenitor cells. Network pharmacology and molecular docking models were used to study the drug target, and qRT-PCR, WB, and IF were used to evaluate the molecular mechanism. Intracranial xenografts were examined using HE and IHC, while macrophage polarization was examined using FC. RESULTS: We originally discovered that luteolin inhibits glioma stem cells. IL6 released by glioma stem cells is blocked during medication action and inhibits glioma stem cell proliferation and invasion via the IL6/STAT3 signaling pathway. Additionally, luteolin inhibits the secretion of TGFß1, affects the polarization function of macrophages in the microenvironment, inhibits the polarization of M2 macrophages in TAM, and further inhibits various functions of glioma stem cells by affecting the IL6/STAT3 signaling pathway, luteolin crosstalk TGFß1/SMAD3 signaling pathway, and so on. CONCLUSIONS: Through the suppression of the immunological microenvironment and inhibition of the IL6/STAT3 signaling pathway, our study determined the inhibitory effect of luteolin on glioma stem cells. This medication's dual inhibitory action, which has a significant negative impact on the glioma stem cells' malignant process, makes it both a viable anti-glioma medication and a candidate for targeted glioma microenvironment therapy.

High-precision tracking and positioning for monitoring Holstein cattle.

Enhanced animal welfare has emerged as a pivotal element in contemporary precision animal husbandry, with bovine monitoring constituting a significant facet of precision agriculture. The evolution of intelligent agriculture in recent years has significantly facilitated the integration of drone flight monitoring tools and innovative systems, leveraging deep learning to interpret bovine behavior. Smart drones, outfitted with monitoring systems, have evolved into viable solutions for wildlife protection and monitoring as well as animal husbandry. Nevertheless, challenges arise under actual and multifaceted ranch conditions, where scale alterations, unpredictable movements, and occlusions invariably influence the accurate tracking of unmanned aerial vehicles (UAVs). To address these challenges, this manuscript proposes a tracking algorithm based on deep learning, adhering to the Joint Detection Tracking (JDT) paradigm established by the CenterTrack algorithm. This algorithm is designed to satisfy the requirements of multi-objective tracking in intricate practical scenarios. In comparison with several preeminent tracking algorithms, the proposed Multi-Object Tracking (MOT) algorithm demonstrates superior performance in Multiple Object Tracking Accuracy (MOTA), Multiple Object Tracking Precision (MOTP), and IDF1. Additionally, it exhibits enhanced efficiency in managing Identity Switches (ID), False Positives (FP), and False Negatives (FN). This algorithm proficiently mitigates the inherent challenges of MOT in complex, livestock-dense scenarios.

PM2.5-induced cellular senescence drives brown adipose tissue impairment in middle-aged mice.

Airborne fine particulate matter (PM2.5) exposure is closely associated with metabolic disturbance, in which brown adipose tissue (BAT) is one of the main contributing organs. However, knowledge of the phenotype and mechanism of PM2.5 exposure-impaired BAT is quite limited. In the study, male C57BL/6 mice at three different life phases (young, adult, and middle-aged) were simultaneously exposed to concentrated ambient PM2.5 or filtered air for 8 weeks using a whole-body inhalational exposure system. H&E staining and high-resolution respirometry were used to assess the size of adipocytes and mitochondrial function. Transcriptomics was performed to determine the differentially expressed genes in BAT. Quantitative RT-PCR, immunohistochemistry staining, and immunoblots were performed to verify the transcriptomics and explore the mechanism for BAT mitochondrial dysfunction. Firstly, PM2.5 exposure caused altered BAT morphology and mitochondrial dysfunction in middle-aged but not young or adult mice. Furthermore, PM2.5 exposure increased cellular senescence in BAT of middle-aged mice, accompanied by cell cycle arrest, impaired DNA replication, and inhibited AKT signaling pathway. Moreover, PM2.5 exposure disrupted apoptosis and autophagy homeostasis in BAT of middle-aged mice. Therefore, BAT in middle-aged mice was more vulnerable to PM2.5 exposure, and the cellular senescence-initiated apoptosis, autophagy, and mitochondrial dysfunction may be the mechanism of PM2.5 exposure-induced BAT impairment.

Ni-based catalysts supported on Hbeta zeolite for the hydrocracking of waste polyolefins.

Polyolefin plastics are the most popular polymer materials worldwide, and the catalytic degradation of post-consumer polyolefins has attracted increased attention as a viable process. In this study, two types of Ni-based catalysts supported on Hbeta zeolite, Ni-Hbeta and NiS2-Hbeta, have been successfully synthesized for the hydrocracking of waste polyolefin. The experimental results indicated that the synergistic effect between Ni or NiS2 and the acidic sites of Hbeta zeolites can significantly enhance the tandem cracking and hydrogenation of polyolefin plastics, which suppresses the formation of gas products and coke. Ni-Hbeta employed as a catalyst can effectively degrade HDPE into high value liquid and gas products with high yield of 94% under 523 K and 3 MPa H2, while also exhibiting excellent cycle stability. In particular, Ni-Hbeta shows better catalytic performance than NiS2-Hbeta during the hydrocracking of HDPE at a relatively low temperature of 523 K. Furthermore, Ni-Hbeta catalyst also exhibits a remarkable capability for efficient depolymerization of unsorted post-consumer polyolefin plastics (HDPE, LDPE, PP) containing various additives and pollutants. These findings underscore the application potential of employing noble metal-free and recyclable catalysts for hydrocracking plastic waste, thereby facilitating the realization of a circular economy for plastics.

Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder.

Microbial signatures have emerged as promising biomarkers for disease diagnostics and prognostics, yet their variability across different studies calls for a standardized approach to biomarker research. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Originally developed for gut microbiome research, xMarkerFinder's adaptable design makes it applicable to various microbial habitats and data types. Distinct from existing biomarker research tools that typically concentrate on a singular aspect, xMarkerFinder uniquely incorporates a sophisticated feature selection process, specifically designed to address the heterogeneity between different cohorts, extensive internal and external validations, and detailed specificity assessments. Execution time varies depending on the sample size, selected algorithm and computational resource. Accessible via GitHub ( https://github.com/tjcadd2020/xMarkerFinder ), xMarkerFinder supports users with diverse expertise levels through different execution options, including step-to-step scripts with detailed tutorials and frequently asked questions, a single-command execution script, a ready-to-use Docker image and a user-friendly web server ( https://www.biosino.org/xmarkerfinder ).

CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides.

Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.

Isolation and Identification of Salinity-Tolerant Rhizobia and Nodulation Phenotype Analysis in Different Soybean Germplasms.

Increasing the soybean-planting area and increasing the soybean yield per unit area are two effective solutions to improve the overall soybean yield. Northeast China has a large saline soil area, and if soybeans could be grown there with the help of isolated saline-tolerant rhizobia, the soybean cultivation area in China could be effectively expanded. In this study, soybeans were planted in soils at different latitudes in China, and four strains of rhizobia were isolated and identified from the soybean nodules. According to the latitudes of the soil-sampling sites from high to low, the four isolated strains were identified as HLNEAU1, HLNEAU2, HLNEAU3, and HLNEAU4. In this study, the isolated strains were identified for their resistances, and their acid and saline tolerances and nitrogen fixation capacities were preliminarily identified. Ten representative soybean germplasm resources in Northeast China were inoculated with these four strains, and the compatibilities of these four rhizobium strains with the soybean germplasm resources were analyzed. All four isolates were able to establish different extents of compatibility with 10 soybean resources. Hefeng 50 had good compatibility with the four isolated strains, while Suinong 14 showed the best compatibility with HLNEAU2. The isolated rhizobacteria could successfully establish symbiosis with the soybeans, but host specificity was also present. This study was a preliminary exploration of the use of salinity-tolerant rhizobacteria to help the soybean nitrogen fixation in saline soils in order to increase the soybean acreage, and it provides a valuable theoretical basis for the application of saline-tolerant rhizobia.

How would autonomous vehicles behave in real-world crash scenarios?

Autonomous Vehicles (AVs) have the potential to revolutionize transportation systems by enhancing traffic safety. Safety testing is undoubtedly a critical step for enabling large-scale deployment of AVs. High-risk scenarios are particularly important as they pose significant challenges and provide valuable insights into the driving capabilities of AVs. This study presents a novel approach to assess the safety of AVs using in-depth crash data, with a particular focus on real-world crash scenarios. First, based on the high-definition video recording of the whole process prior to the crash occurrences, 453 real-world crashes involving 596 passenger cars from China In-depth Mobility Safety Study-Traffic Accident (CIMSS-TA) database were reconstructed. Pertinent static and dynamic elements needed for the construction of the testing scenarios were extracted. Subsequently, 596 testing scenarios were created via each passenger car's perspective within the simulation platform. Following this, each of the crash-involved passenger cars was replaced with Baidu Apollo, a famous automated driving system (ADS), for counterfactual simulation. Lastly, the safety performance of the AV was assessed using the simulation results. A logit model was utilized to identify the fifteen crucial scenario elements that have significant impacts on the test results. The findings demonstrated that the AV could avoid 363 real-world crashes, accounting for approximately 60.91% of the total, and effectively mitigated injuries in the remaining 233 unavoidable scenarios compared to a human driver. Moreover, the AV maintain a smoother speed in most of the scenarios. The common feature of these unavoidable scenarios is that the AV is in a passive state, and the crashes are not caused by the AV violating traffic rules, but rather caused by abnormal behavior exhibited by the human drivers. Additionally, seven specific scenarios have been identified wherein AVs are unable to avoid a crash. These findings demonstrate that, compared to human drivers, AVs can avoid crashes that are difficult for humans to avoid, thereby enhancing traffic safety.

Water-Ice Microstructures and Hydration States of Acridinium Iodide Studied by Phosphorescence Spectroscopy.

Ice has been suggested to have played a significant role in the origin of life partly owing to its ability to concentrate organic molecules and promote reaction efficiency. However, the techniques for studying organic molecules in ice are absorption-based, which limits the sensitivity of measurements. Here we introduce an emission-based method to study organic molecules in water ice: the phosphorescence displays high sensitivity depending on the hydration state of an organic salt probe, acridinium iodide (ADI). The designed ADI aqueous system exhibits phosphorescence that can be severely perturbed when the temperature is higher than 110 K at a concentration of the order of 10-5 M, indicating changes in hydration for ADI. Using the ADI phosphorescent probe, it is found that the microstructures of water ice, i.e., crystalline vs. glassy, can be strongly dictated by a trace amount (as low as 10-5 M) of water-soluble organic molecules. Consistent with cryoSEM images and temperature-dependent Raman spectral data, the ADI is dehydrated in more crystalline ice and hydrated in more glassy ice. The current investigation serves as a starting point for using more sensitive spectroscopic techniques for studying water-organics interactions at a much lower concentration and wider temperature range.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Transcriptomic Analysis of PDCoV-Infected HIEC-6 Cells and Enrichment Pathways PI3K-Akt and P38 MAPK.

Porcine Deltacoronavirus (PDCoV) is a newly identified coronavirus that causes severe intestinal lesions in piglets. However, the understanding of how PDCoV interacts with human hosts is limited. In this study, we aimed to investigate the interactions between PDCoV and human intestinal cells (HIEC-6) by analyzing the transcriptome at different time points post-infection (12 h, 24 h, 48 h). Differential gene analysis revealed a total of 3560, 5193, and 4147 differentially expressed genes (DEGs) at 12 h, 24 h, and 48 h, respectively. The common genes among the DEGs at all three time points were enriched in biological processes related to cytokine production, extracellular matrix, and cytokine activity. KEGG pathway analysis showed enrichment of genes involved in the p53 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway. Further analysis of highly expressed genes among the DEGs identified significant changes in the expression levels of BUB1, DDIT4, ATF3, GBP2, and IRF1. Comparison of transcriptome data at 24 h with other time points revealed 298 DEGs out of a total of 6276 genes. KEGG analysis of these DEGs showed significant enrichment of pathways related to viral infection, specifically the PI3K-Akt and P38 MAPK pathways. Furthermore, the genes EFNA1 and KITLG, which are associated with viral infection, were found in both enriched pathways, suggesting their potential as therapeutic or preventive targets for PDCoV infection. The enhancement of PDCoV infection in HIEC-6 was observed upon inhibition of the PI3K-Akt and P38 MAPK signaling pathways using sophoridine. Overall, these findings contribute to our understanding of the molecular mechanisms underlying PDCoV infection in HIEC-6 cells and provide insights for developing preventive and therapeutic strategies against PDCoV infection.

Molecular composition and characteristics of Sediment-adsorbed Dissolved Organic Matter (SDOM) along the coast of China.

Sediment-adsorbed Dissolved Organic Matter (SDOM) in coast plays a crucial role in the terrestrial and marine carbon cycle processes of the global environment. However, understanding the transport dynamics of SDOM along the coast of China, particularly its interactions with sediments, remains elusive. In this study, we analyzed the δ13C and δ15N stable isotopic compositions, as well as the molecular characteristics of SDOM collected from coastal areas spanning the Bohai Sea (BS), Yellow Sea (YS), East China Sea (ECS), and South China Sea (SCS), by using isotope ratio mass spectrometry and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS). We identified the predominant sources of carbon and nitrogen in coastal sediments, revealing terrigenous origins for most C and N, while anthropogenic sources dominated in the SCS. Spatial variations in SDOM chemodiversity were observed, with diverse molecular components influenced by distinct environmental factors and sediment sources. Notably, lignins and saturated compounds (such as proteins/amino sugars) were the predominant molecular compounds detected in coastal SDOM. Through Mantel tests and Spearman's correlation analysis, we elucidated the significant influence of spatial environmental factors (temperature, DO, salinity, and depth) and sediment sources on SDOM molecular chemodiversity. These findings contribute to a more comprehensive understanding of the carbon cycle dynamics along the Chinese coast.

Ginsenoside Rg5 inhibits glioblastoma by activating ferroptosis via NR3C1/HSPB1/NCOA4.

BACKGROUND: The utilization of Chinese medicine as an adjunctive therapy for cancer has recently gained significant attention. Ferroptosis, a newly regulated cell death process depending on the ferrous ions, has been proved to be participated in glioma stem cells inactivation. PURPOSE: We aim to study whether ginsenoside Rg5 exerted inhibitory effects on crucial aspects of glioma stem cells, including cell viability, tumor initiation, invasion, self-renewal ability, neurosphere formation, and stemness. METHODS: Through comprehensive sequencing analysis, we identified a compelling association between ginsenoside Rg5 and the ferroptosis pathway, which was further validated through subsequent experiments demonstrating its ability to activate this pathway. RESULTS: To elucidate the precise molecular targets affected by ginsenoside Rg5 in gliomas, we conducted an intersection analysis between differentially expressed genes obtained from sequencing and a database-predicted list of transcription factors and potential targets of ginsenoside Rg5. This rigorous approach led us to unequivocally confirm NR3C1 (Nuclear Receptor Subfamily 3 Group C Member 1) as a direct target of ginsenoside Rg5, a finding consistently supported by subsequent experimental investigations. Moreover, we uncovered NR3C1's capacity to transcriptionally regulate ferroptosis -related genes HSPB1 and NCOA4. Strikingly, ginsenoside Rg5 induced notable alterations in the expression levels of both HSPB1 (Heat Shock Protein Family B Member 1) and NCOA4 (Nuclear Receptor Coactivator 4). Finally, our intracranial xenograft assays served to reaffirm the inhibitory effect of ginsenoside Rg5 on the malignant progression of glioblastoma. CONCLUSION: These collective findings strongly suggest that ginsenoside Rg5 hampers glioblastoma progression by activating ferroptosis through NR3C1, which subsequently modulates HSPB1 and NCOA4. Importantly, this novel therapeutic direction holds promise for advancing the treatment of glioblastoma.

Rapid room-temperature phosphorescence chiral recognition of natural amino acids.

Chiral recognition of amino acids is very important in both chemical and life sciences. Although chiral recognition with luminescence has many advantages such as being inexpensive, it is usually slow and lacks generality as the recognition module relies on structural complementarity. Here, we show that one single molecular-solid sensor, L-phenylalanine derived benzamide, can manifest the structural difference between the natural, left-handed amino acid and its right-handed counterpart via the difference of room-temperature phosphorescence (RTP) irrespective of the specific chemical structure. To realize rapid and reliable sensing, the doped samples are obtained as nanocrystals from evaporation of the tetrahydrofuran solutions, which allows for efficient triplet-triplet energy transfer to the chiral analytes generated in situ from chiral amino acids. The results show that L-analytes induce strong RTP, whereas the unnatural D-analytes produce barely any afterglow. The method expands the scope of luminescence chiral sensing by lessening the requirement for specific molecular structures.

Micro-Spherical BiOI Photocatalysts for Efficient Degradation of Residual Xanthate and Gaseous Nitric Oxide.

BiOI microspheres were synthesized using the solvothermal method for the degradation of residual xanthate and gaseous nitric oxide (NO) under visible light irradiation. The as-prepared BiOI nanomaterials were then characterized using various technologies, including XRD, FE-SEM, TEM, UV-Vis DRS, and XPS. The photodegradation results show that the removal efficiency of isobutyl sodium xanthate can reach 98.08% at an initial xanthate concentration of 120 mg/L; that of NO is as high as 96.36% at an inlet NO concentration of 11 ppm. Moreover, the effects of operational parameters such as catalyst dosage, initial xanthate concentration, and pH value of wastewater on the removal of xanthate were investigated. The results of scavenging tests and full-spectrum scanning indicate that ·O2- radicals are the main active species in xanthate degradation, and peroxide xanthate is an intermediate. The reusability of BiOI was explored through cyclic experiments. Furthermore, the reaction path and the mechanism of NO removal using BiOI were analyzed, and the main active species was also ·O2-. It is concluded that BiOI photocatalysts have high potential for wastewater treatment and waste gas clean-up in the mineral industry.