Exploring the influence of sulfadiazine-induced stress on antibiotic removal and transformation pathway using microalgae Chlorella sp.

Sulfadiazine (SDZ) is a kind of anti-degradable antibiotics that is commonly found in wastewater, but its removal mechanism and transformation pathway remain unclear in microalgal systems. This study investigated the effects of initial algae concentration and SDZ-induced stress on microalgal growth metabolism, SDZ removal efficiency, and transformation pathways during Chlorella sp. cultivation. Results showed that SDZ had an inhibitory effect on the growth of microalgae, and increasing the initial algal biomass could alleviate the inhibitory effect of SDZ. When the initial algal biomass of Chlorella sp. was increased to 0.25 g L-1, the SDZ removal rate could reach 53.27%-89.07%. The higher the initial algal biomass, the higher the SOD activity of microalgae, and the better the protective effect on microalgae, which was one of the reasons for the increase in SDZ removal efficiency. Meanwhile, SDZ stress causes changes in photosynthetic pigments, lipids, total sugars and protein content of Chlorella sp. in response to environmental changes. The main degradation mechanisms of SDZ by Chlorella sp. were biodegradation (37.82%) and photodegradation (23%). Most of the degradation products of SDZ were less toxic than the parent compound, and the green algae were highly susceptible to SDZ and its degradation products. The findings from this study offered valuable insights into the tradeoffs between accumulating microalgal biomass and antibiotic toxic risks during wastewater treatment, providing essential direction for the advancement in future research and full-scale application.

Retromolar intubation for the general anesthesia of maxillofacial fracture patients.

BACKGROUND: Evaluate the possibility of retromolar intubation for general anesthesia in patients with maxillofacial fractures. METHODS: The medical records of 54 patients with maxillofacial fractures who visited the Oral and Maxillofacial Surgery Department of Nantong First People's Hospital from January 2020 to August 2022 were collected. The retromolar areas of each patient were measured from the coronal CT images, and correlated with the patient's age, sex, type of fracture (i.e., maxillary fracture, mandibular fracture, or complex fracture of multiple maxillofacial bones), and the presence of the third molar (verified from 3D CT). The dimensions of the retromolar areas were finally compared with the outer diameter (OD) of standard endotracheal tubes (ETTs), most importantly the size 7.5 ETT (OD 10.3 mm) for male and the size 7.0 ETT (OD 9.8 mm) for female. RESULTS: The survey included 38 male and 16 female patients, with an average age of 44.1 and 54.3 years, respectively. The dimensions of the retromolar area (height × width) were as follows: male, (9.39 ± 1.77) mm × (12.08 ± 0.98) mm on the left and (9.81 ± 2.23) mm × (11.77 ± 1.08) mm on the right; female, (8.82 ± 1.53) mm × (10.51 ± 1.00) mm on the left and (9.73 ± 1.60) mm × (10.63 ± 1.58) mm on the right. The width was always larger than the OD of the routinely used ETT, but the height could be smaller by less than 1 mm. However, the oral mucosa can be compressed to allow the ETT to fit in the retromolar area. CONCLUSIONS: The retromolar area provided appropriate space to place a reinforced ETT for patients with maxillofacial fractures needing general anesthesia that must not interfere with intermaxillary ligation. Retromolar intubation can help maxillofacial fracture surgeries that focus on occlusal restoration.

Dynamic Routings in Satellite Networks: An Overview.

The Satellite network is an important part of the global network. However, the complex architecture, changeable constellation topology, and frequent inter-satellite connection switching problems bring great challenges to the routing designs of satellite networks, making the study of the routing methods in satellite networks a research hotspot. Therefore, this paper investigates the latest existing routing works to tackle the dynamic routing problems in satellite networks. The architecture and development of satellite networks are presented and analyzed first. Afterward, dynamic routing problems in satellite networks are analyzed in detail based on the time-varying network topology. According to the latest works, the advanced satellite network routing schemes, including single-layer and multi-layer dynamic routing are introduced and analyzed. In addition, the merits, shortcomings, and applications of these schemes are analyzed and summarized. Finally, potential technologies and future directions are discussed.

Synthesis, fungicidal activity, and 3D-QSAR of tetrazole derivatives containing phenyloxadiazole moieties.

In an effort to discover new agents with good fungicidal activities against CDM (cucumber downy mildew), a series of tetrazole derivatives containing phenyloxadiazole moieties were designed and synthesized. The EC50 values for fungicidal activities against CDM were determined. Bioassay results indicated that most synthesized compounds exhibited potential in vivo fungicidal activity against CDM. A CoMFA (comparative molecular field analysis) model based on the bioactivity was developed to identify some primary structural quality for the efficiency. The values of q2 and r2 for the established model were 0.791 and 0.982 respectively, which reliability and predict abilities were verified. Three analogues (q3, q4, q5) were designed and synthesized based on the model. All these compounds exhibited significant fungicidal activity on CDM with the EC50 of 1.43, 1.52, 1.77 mg·L-1. This work could provide a useful instruction for the further structure optimization.

Strategy for Intercorrelation Identification between Metabolome and Microbiome.

Accumulating evidence points to the strong and complicated associations between the metabolome and the microbiome, which play diverse roles in physiology and pathology. Various correlation analysis approaches were applied to identify microbe-metabolite associations. Given the strengths and weaknesses of the existing methods and considering the characteristics of different types of omics data, we designed a special strategy, called Generalized coRrelation analysis for Metabolome and Microbiome (GRaMM), for the intercorrelation discovery between the metabolome and microbiome. GRaMM can properly deal with two types of omics data, the effect of confounders, and both linear and nonlinear correlations by integrating several complementary methods such as the classical linear regression, the emerging maximum information coefficient (MIC), the metabolic confounding effect elimination (MCEE), and the centered log-ratio transformation (CLR). GRaMM contains four sequential computational steps: (1) metabolic and microbial data preprocessing, (2) linear/nonlinear type identification, (3) data correction and correlation detection, and (4) p value correction. The performances of GRaMM, including the accuracy, sensitivity, specificity, false positive rate, applicability, and effects of preprocessing and confounder adjustment steps, were evaluated and compared with three other methods in multiple simulated and real-world datasets. To our knowledge, GRaMM is the first strategy designed for the intercorrelation analysis between metabolites and microbes. The Matlab function and an R package were developed and are freely available for academic use (comply with GNU GPL.V3 license).

Evaluation of metabolite-microbe correlation detection methods.

Different correlation detection methods have been specifically designed for the microbiome data analysis considering the compositional data structure and different sequencing depths. Along with the speedy development of omics studies, there is an increasing interest in discovering the biological associations between microbes and host metabolites. This raises the need of finding proper statistical methods that facilitate the correlation analysis across different omics studies. Here, we comprehensively evaluated six different correlation methods, i.e., Pearson correlation, Spearman correlation, Sparse Correlations for Compositional data (SparCC), Correlation inference for Compositional data through Lasso (CCLasso), Mutual Information Coefficient (MIC), and Cosine similarity methods, for the correlations detection between microbes and metabolites. Three simulated and two real-world data sets (from public databases and our lab) were used to examine the performance of each method regarding its specificity, sensitivity, similarity, accuracy, and stability with different sparsity. Our results indicate that although each method has its own pros and cons in different scenarios, Spearman correlation and MIC outperform the others with their overall performances. A strategic guidance was also proposed for the correlation analysis between microbe and metabolite.

MCEE 2.0: more options and enhanced performance.

A confounding factor is an unstudied factor that affects one or more of the variables that are being studied in an investigation, so the presence of a confounder may lead to inaccurate or biased results. It is well recognized that physiological and environmental factors such as race, diet, age, gender, blood pressure, and diurnal cycle affect mammalian metabolism. To eliminate the noise introduced by confounders into metabolomics studies, a GUI-based method denoted metabolic confounding effect elimination (MCEE) was developed and has since been applied successfully in a wide range of metabolomics studies. To keep up with recent developments in computational metabolomics and a growing number of user requests, an upgraded version of MCEE with more options and enhanced performance was designed and developed. Besides the generalized linear model (GLM) method, a multivariate method for selecting affected metabolites-canonical correlation analysis (CCA)-was introduced, which accounts for complicated correlations and collinearity within the metabolome. Multiple confounders are acceptable and can be identified and processed separately or simultaneously. The effectiveness of this new version of MCEE as well as the pros and cons of the two methodological options were examined using three simulated data sets (a basic model, a model with different sample size ratios, and a sparse model) and two real-world data sets (a human type 2 diabetes mellitus data set and a human arthritis data set). As well as presenting the results of this examination of the new version of MCEE, some instructions on appropriate method selection and parameter setting are provided here. The freely available MATLAB code for MCEE with a GUI has also been updated accordingly at https://github.com/chentianlu/MCEE-2.0 . Graphical abstract.

MCEE: a data preprocessing approach for metabolic confounding effect elimination.

It is well recognized that physiological and environmental factors such as race, age, gender, and diurnal cycles often have a definite influence on metabolic results that statistically manifests as confounding variables. Currently, removal or controlling of confounding effects relies heavily on experimental design. There are no available data processing techniques focusing on the compensation of their effects. We therefore proposed a new method, Metabolic confounding effect elimination (MCEE), to remove the influence of specified confounding factors and make the data more accurate. The method consists of three steps: metabolites grouping, confounder-related metabolites selection, and metabolites modification. Its effectiveness and advantages were evaluated comprehensively by several simulated models and real datasets, and were compared with two typical methods, the principal component analysis (PCA)- and the direct orthogonal signal correction (DOSC)-based methods. MCEE is simple, effective, and safe, and is independent of sample number, association degree, and missing value. Hence, it may serve as a good complement to existing metabolomics data preprocessing methods and aid in better understanding the metabolic and biological status of interest. Graphical Abstract Algorithm flow and demo performance of MCEE.

Sonodegradation of cyanidin-3-glucosylrutinoside: degradation kinetic analysis and its impact on antioxidant capacity in vitro.

BACKGROUND: As an alternative preservation method for thermal treatment, ultrasound comprises a novel non-thermal processing technology that can significantly avoid undesirable nutritional changes. However, the recent literature indicates that anthocyanin degradation occurs when ultrasound is applied in juice at high amplitude parameters. Such work has mainly focussed on the effect of ultrasound on stability, the antioxidant capacity of cyanidin-3-glucosylrutinoside (Cy-3-glc-rut) and the correlation between anthocyanin degradation and ·OH generation in a simulated system. RESULTS: The spectral intensities of Cy-3-glc-rut at 518 and 282 nm decreased with increasing ultrasound power and treatment time. The degradation of Cy-3-glc-rut was consistent with first-order reaction kinetics (r2 > 0.9000) and there was a good linear correlation between anthocyanin degradation and hydroxyl radical formation induced by ultrasound (r2 = 0.9258). Moreover, a decrease in the antioxidant activity of Cy-3-glc-rut after ultrasound evaluated by the 1,1-diphenyl-2-picrylhydrazyl and ferric reducing antioxidant power methods was observed. CONCLUSION: Overall, the results of the present study show that ultrasound will accelerate the degradation of Cy-3-glc-rut with the growth of power over time. © 2016 Society of Chemical Industry.

Photoproduction of reactive intermediates from dissolved organic matter in coastal seawater around an urban metropolis in South China: Characterization and predictive modeling.

Chromophoric dissolved organic matter (CDOM) is an important photochemical precursor to reactive intermediates (RIs) (e.g., excited triplet states of chromophoric dissolved organic matter (3CDOM⁎), hydroxyl radicals (·OH), and singlet oxygen (1O2)) in aquatic systems to drive the photodegradation of contaminants. There have been limited studies on the photoproduction of RIs in coastal seawater CDOM in Asia, which impedes our ability to model the lifetimes and fates of contaminants in these coastal seawater systems. Hong Kong is an urban metropolis in South China, whose coastal seawater is susceptible to anthropogenic activities from the surrounding areas and the nearby Pearl River. We investigated the photoproduction of RIs in seawater around Hong Kong during the wet vs. dry season. Higher intensities of fluorescent components, dissolved organic carbon concentration ([DOC]), apparent quantum yields of RIs (ΦRIs), and steady-state concentrations of photogenerated RIs ([RIs]ss) were observed for samples collected in the areas closest to the Pearl River during the wet season. Lower humification degrees and ΦRIs but higher intensities of fluorescent components and [RIs]ss were generally observed for the wet season samples compared to the dry season samples. Statistical analysis revealed strong significant correlations (Spearman |r| > 0.6, p < 0.05) between ΦRIs and the absorbance properties (including the absorbance ratio E2:E3, spectral slope coefficients S350-400, and spectral slope ratio SR) of CDOM, and between [RIs]ss and the quantity-reflected properties (including the fluorescence intensity of humic-like components) of CDOM. Our modeling analyses combining orthogonal partial least squares and stepwise multiple linear regression showed excellent prediction strengths for [1O2]ss and [3CDOM⁎]ss (R2adj > 0.7) when [DOC] and the chemical and optical properties of CDOM were used as predictor variables. These modeling results demonstrate the feasibility of predicting the concentrations and quantum yields of RIs in seawater around Hong Kong, and potentially other coastal cities in South China, from easily measurable chemical and optical properties.

Effects of Hydrothermal Pretreatment and Anaerobic Digestion of Pig Manure on the Antibiotic Removal and Methane Production.

Whether advanced biological waste treatment technologies, such as hydrothermal pretreatment (HTP) integrated anaerobic digestion (AD), could enhance the removal of different antibiotics remains unclear. This study investigated the outcome of antibiotics and methane productivity during pig manure treatment via HTP, AD, and HTP + AD. Results showed improved removal efficiency of sulfadiazine (SDZ), oxytetracycline (OTC), and enrofloxacin (ENR) with increased HTP temperatures (70, 90, 120, 150, and 170 °C). OTC achieved the highest removal efficiency of 86.8% at 170 °C because of its high sensitivity to heat treatment. For AD, SDZ exhibited resistance with a removal efficiency of 52.8%. However, OTC and ENR could be removed completely within 30 days. When HTP was used prior to AD, OTC and ENR could achieve complete removal. However, residual SDZ levels reduced to 20% and 16% at 150 and 170 °C, respectively. The methanogenic potential showed an overall upward trend as the HTP temperature increased. Microbial analysis revealed the antibiotics-induced enrichment of specific microorganisms during AD. Firmicutes were the dominant bacterial phylum, with their abundance positively correlated with the addition of antibiotics. Methanobacterium and Methanosarcina emerged as the dominant archaea that drove methane production during AD. Thus, HTP can be a potential pretreatment before AD to reduce antibiotic-related risks in manure waste handling.

Electrolyte Engineering with Tamed Electrode Interphases for High-Voltage Sodium-Ion Batteries.

Sodium-ion batteries (SIBs) hold great promise for next-generation grid-scale energy storage. However, the highly instable electrolyte/electrode interphases threaten the long-term cycling of high-energy SIBs. In particular, the instable cathode electrolyte interphase (CEI) at high voltage causes persistent electrolyte decomposition, transition metal dissolution, and fast capacity fade. Here, this work proposes a balanced principle for the molecular design of SIB electrolytes that enables an ultra-thin, homogeneous, and robust CEI layer by coupling an intrinsically oxidation-stable succinonitrile solvent with moderately solvating carbonates. The proposed electrolyte not only shows limited anodic decomposition thus leading to a thin CEI, but also suppresses dissolution of CEI components at high voltage. Consequently, the tamed electrolyte/electrode interphases enable extremely stable cycling of Na3V2O2(PO4)2F (NVOPF) cathodes with outstanding capacity retention (>90%) over 3000 cycles (8 months) at 1 C with a high charging voltage of 4.3 V. Further, the NVOPF||hard carbon full cell shows stable cycling over 500 cycles at 1 C with a high average Coulombic efficiency (CE) of 99.6%. The electrolyte also endows high-voltage operation of SIBs with great temperature adaptability from -25 to 60 °C, shedding light on the essence of fundamental electrolyte design for SIBs operating under harsh conditions.

Darwin3: a large-scale neuromorphic chip with a novel ISA and on-chip learning.

Spiking neural networks (SNNs) are gaining increasing attention for their biological plausibility and potential for improved computational efficiency. To match the high spatial-temporal dynamics in SNNs, neuromorphic chips are highly desired to execute SNNs in hardware-based neuron and synapse circuits directly. This paper presents a large-scale neuromorphic chip named Darwin3 with a novel instruction set architecture, which comprises 10 primary instructions and a few extended instructions. It supports flexible neuron model programming and local learning rule designs. The Darwin3 chip architecture is designed in a mesh of computing nodes with an innovative routing algorithm. We used a compression mechanism to represent synaptic connections, significantly reducing memory usage. The Darwin3 chip supports up to 2.35 million neurons, making it the largest of its kind on the neuron scale. The experimental results showed that the code density was improved by up to 28.3× in Darwin3, and that the neuron core fan-in and fan-out were improved by up to 4096× and 3072× by connection compression compared to the physical memory depth. Our Darwin3 chip also provided memory saving between 6.8× and 200.8× when mapping convolutional spiking neural networks onto the chip, demonstrating state-of-the-art performance in accuracy and latency compared to other neuromorphic chips.

Bile acid signaling in the regulation of whole body metabolic and immunological homeostasis.

Bile acids (BAs) play a crucial role in nutrient absorption and act as key regulators of lipid and glucose metabolism and immune homeostasis. Through the enterohepatic circulation, BAs are synthesized, metabolized, and reabsorbed, with a portion entering the vascular circulation and distributing systemically. This allows BAs to interact with receptors in all major organs, leading to organ-organ interactions that regulate both local and global metabolic processes, as well as the immune system. This review focuses on the whole-body effects of BA-mediated metabolic and immunological regulation, including in the brain, heart, liver, intestine, eyes, skin, adipose tissue, and muscle. Targeting BA synthesis and receptor signaling is a promising strategy for the development of novel therapies for various diseases throughout the body.

Preparation and characterization of high molecular weight vinyl-containing poly[(3,3,3-trifluoropropyl)methylsiloxane.

Prior to crosslinking and vulcanization, fluorosilicone rubber is a linear polymer. This linear polymer contains 3,3,3,-trifluoropropyl methyl siloxane links, a few methyl vinyl siloxane links, and is formed by co-polymerization of 1,3,5-trimethyl-1,3,5-tris(3,3,3-trifluoropropyl) cyclotrisiloxane (D3F) with 2,4,6,8-tetramethyl-2,4,6,8-tetravinylcyclotetrasiloxane (V4) under alkaline conditions. To improve the performance of fluorosilicone rubber, three key points should be considered during the synthesis of vinyl-containing high-molecular-weight linear fluorosilicone polymers (fluorosilicone raw rubber): first, avoid the generation of low molecular weight equilibrium by-products; second, eliminate the influence of impurities; and third, increase the copolymerization participation rate of monomer V4. From the three aspects above, this study optimized the reaction conditions for the synthesis of high-molecular-weight linear fluorosilicone polymers containing vinyl. Various factors influencing polymerization were thoroughly investigated. These factors include the initiation system, accelerator, equilibrium reaction, feeding ratio, feeding sequence, neutralization mode, impurity content, etc.

Biophysical impacts of earth greening can substantially mitigate regional land surface temperature warming.

Vegetation change can alter surface energy balance and subsequently affect the local climate. This biophysical impact has been well studied for forestation cases, but the sign and magnitude for persistent earth greening remain controversial. Based on long-term remote sensing observations, we quantify the unidirectional impact of vegetation greening on radiometric surface temperature over 2001-2018. Here, we show a global negative temperature response with large spatial and seasonal variability. Snow cover, vegetation greenness, and shortwave radiation are the major driving factors of the temperature sensitivity by regulating the relative dominance of radiative and non-radiative processes. Combined with the observed greening trend, we find a global cooling of -0.018 K/decade, which slows down 4.6 ± 3.2% of the global warming. Regionally, this cooling effect can offset 39.4 ± 13.9% and 19.0 ± 8.2% of the corresponding warming in India and China. These results highlight the necessity of considering this vegetation-related biophysical climate effect when informing local climate adaptation strategies.

Brucella abortus modulates macrophage polarization and inflammatory response by targeting glutaminases through the NF-κB signaling pathway.

Objectives: The mechanism of Brucella infection regulating macrophage phenotype has not been completely elucidated until now. This study aimed to determine the mechanism of Brucella abortus in the modulation of macrophage phenotype using RAW264.7 cells as a model. Materials and methods: RT-qPCR, ELISA and flow cytometry were used to detect the inflammatory factor production and phenotype conversion associated with M1/M2 polarization of macrophages by Brucella abortus infection. Western blot and immunofluorescence were used to analyze the role of nuclear factor kappa B (NF-κB) signaling pathway in regulation of Brucella abortus-induced macrophage polarization. Chromatin immunoprecipitation sequencing (Chip-seq), bioinformatics analysis and luciferase reporter assay were used to screen and validate NF-κB target genes associated with macrophage polarization and further verify its function. Results: The results demonstrate that B. abortus induces a macrophage phenotypic switch and inflammatory response in a time-dependent manner. With the increase of infection time, B. abortus infection-induced M1-type increased first, peaked at 12 h, and then decreased, whereas the M2-type decreased first, trough at 12 h, and then increased. The trend of intracellular survival of B. abortus was consistent with that of M2 type. When NF-κB was inhibited, M1-type polarization was inhibited and M2-type was promoted, and the intracellular survival of B. abortus increased significantly. Chip-seq and luciferase reporter assay results showed that NF-κB binds to the glutaminase gene (Gls). Gls expression was down-regulated when NF-κB was inhibited. Furthermore, when Gls was inhibited, M1-type polarization was inhibited and M2-type was promoted, the intracellular survival of B. abortus increased significantly. Our data further suggest that NF-κB and its key target gene Gls play an important role in controlling macrophage phenotypic transformation. Conclusions: Taken together, our study demonstrates that B. abortus infection can induce dynamic transformation of M1/M2 phenotype in macrophages. Highlighting NF-κB as a central pathway that regulates M1/M2 phenotypic transition. This is the first to elucidate the molecular mechanism of B. abortus regulation of macrophage phenotype switch and inflammatory response by regulating the key gene Gls, which is regulated by the transcription factor NF-κB.

Local temperature responses to actual land cover changes present significant latitudinal variability and asymmetry.

Land cover changes (LCCs) affect surface temperatures at local scale through biophysical processes. However, previous observation-based studies mainly focused on the potential effects of virtual afforestation/deforestation using the space-for-time assumption, while the actual effects of all types of realistic LCCs are underexplored. Here, we adopted the space-and-time scheme and utilized extensive high-resolution (1-km) satellite observations to perform the first such assessment. We showed that, from 2006 to 2015, the average temperature in the areas with LCCs increased by 0.08 K globally, but varied significantly across latitudes, ranging from -0.05 to 0.18 K. Cropland expansions dominated summertime cooling effects in the northern mid-latitudes, whereas forest-related LCCs caused warming effects elsewhere. These effects accounted for up to 44.6% of overall concurrent warming, suggesting that LCC influences cannot be ignored. In addition, we revealed obvious asymmetries in the actual effects, i.e., LCCs with warming effects occurred more frequently, with stronger intensities, than LCCs with cooling effects. Even for the mutual changes between two covers in the same region, warming LCCs generally had larger magnitudes than their cooling counterparts due to asymmetric changes in transition fractions and driving variables. These novel findings, derived from the assessment of actual LCCs, provide more realistic implications for land management and climate adaptation policies.

Hyodeoxycholic acid alleviates non-alcoholic fatty liver disease through modulating the gut-liver axis.

Non-alcoholic fatty liver disease (NAFLD) is regarded as a pandemic that affects about a quarter of the global population. Recently, host-gut microbiota metabolic interactions have emerged as distinct mechanistic pathways implicated in the development of NAFLD. Here, we report that a group of gut microbiota-modified bile acids (BAs), hyodeoxycholic acid (HDCA) species, are negatively correlated with the presence and severity of NAFLD. HDCA treatment has been shown to alleviate NAFLD in multiple mouse models by inhibiting intestinal farnesoid X receptor (FXR) and upregulating hepatic CYP7B1. Additionally, HDCA significantly increased abundances of probiotic species such as Parabacteroides distasonis, which enhances lipid catabolism through fatty acid-hepatic peroxisome proliferator-activated receptor alpha (PPARα) signaling, which in turn upregulates hepatic FXR. These findings suggest that HDCA has therapeutic potential for treating NAFLD, with a unique mechanism of simultaneously activating hepatic CYP7B1 and PPARα.

Environmental photochemistry of organic UV filter butyl methoxydibenzoylmethane: Implications for photochemical fate in surface waters.

With the widespread use of sunscreen and other personal care products, organic ultraviolet filters (OUVFs) have become widely detected in the aquatic environment. Direct and indirect photolysis are important transformation pathways of OUVFs in aquatic environments, so their transformation products (TPs) are also chemicals of concern. Butyl methoxydibenzoylmethane (BMDBM) is one of the most commonly used OUVFs worldwide due to its ability to absorb ultraviolet light across a wide range of wavelengths, and it is ubiquitously detected in aquatic environments. In this study, we investigated the photodegradation of BMDBM through direct photolysis and hydroxyl radical (•OH) photooxidation. TPs were identified using ultrahigh performance liquid chromatography-high resolution mass spectrometry, and reaction mechanisms were proposed. Our results showed that the photodegradation rates for both enol and keto tautomer forms of BMDBM during direct photolysis and •OH photooxidation were similar. The formation of TPs resulted from α-cleavage and decarbonylation reactions involving the keto form of BMDBM. Comparisons of the kinetic data and TPs revealed that the direct photolysis mechanism was a significant sink for BMDBM even during •OH photooxidation. Evaluations of environmental properties based on the predicted physicochemical properties of BMDBM and TPs suggests that some of the TPs will have higher mobility than BMDBM. The quantitative structure-activity relationship (QSAR) approach was used to evaluate the ecotoxicity of BMDBM and the identified TPs. Most TPs were found to be less ecotoxic than BMDBM; however, TPs that had a diphenyl ring structure could be more ecotoxic than BMDBM. Overall, this study provides new insights into the photochemical behavior and ecotoxicity of BMDBM and its TPs, which are important for assessing the fate, persistence, accumulation, and adverse impacts of these compounds in aquatic environments.