Efficacy and safety of colchicine for atrial fibrillation prevention: An updated meta-analysis of randomized controlled trials.

BACKGROUND: Atrial fibrillation (AF), the most common arrhythmia, is closely related to inflammation. Colchicine has the potent anti-inflammatory effects. Several randomized clinical trials (RCTs) have evaluated the efficacy and safety of colchicine in the prevention of AF but the results are inconsistent. OBJECTIVE: The purpose of our study was to evaluate the impact of colchicine on AF. METHOD AND RESULTS: PubMed, EMBASE, Web of Science, Cochrane Library and ClinicalTrials.gov were searched for related studies until Jan 8, 2024. A total of 17 studies including 16,238 participants were included. Compared to the placebo group, there were fewer incidences of AF in the colchicine group (RR: 0.75, 95%CI: 0.68-0.83, P < 0.001). The incidence of overall adverse events and overall gastrointestinal intolerance did not differ significantly between the two groups. However, diarrhea, nausea, and discontinuation occurred more frequently in patients treated with colchicine. CONCLUSION: Colchicine can prevent patients from the incidence of AF, regardless of the mean age of patients, type of atrial fibrillation, maintenance dose, duration of colchicine use, cumulative daily dose, and follow-up time with more diarrhea, nausea and discontinuation. These adverse events can be avoided by low doses (0.5 mg once daily) and long period time of colchicine use.

MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.

MOTIVATION: Protein-protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achieved outstanding performance in predicting PPIS. However, these studies often neglect the modeling of information at different scales in the graph and the symmetry of protein molecules within three-dimensional space. RESULTS: In response to this gap, this paper proposes the MEG-PPIS approach, a PPIS prediction method based on multi-scale graph information and E(n) equivariant graph neural network (EGNN). There are two channels in MEG-PPIS: the original graph and the subgraph obtained by graph pooling. The model can iteratively update the features of the original graph and subgraph through the weight-sharing EGNN. Subsequently, the max-pooling operation aggregates the updated features of the original graph and subgraph. Ultimately, the model feeds node features into the prediction layer to obtain prediction results. Comparative assessments against other methods on benchmark datasets reveal that MEG-PPIS achieves optimal performance across all evaluation metrics and gets the fastest runtime. Furthermore, specific case studies demonstrate that our method can predict more true positive and true negative sites than the current best method, proving that our model achieves better performance in the PPIS prediction task. AVAILABILITY AND IMPLEMENTATION: The data and code are available at https://github.com/dhz234/MEG-PPIS.git.

Machine learning in internet financial risk management: A systematic literature review.

Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.

Improving salt-tolerant artificial consortium of Bacillus amyloliquefaciens for bioconverting food waste to lipopeptides.

High-salt content in food waste (FW) affects its resource utilization during biotransformation. In this study, adaptive laboratory evolution (ALE), gene editing, and artificial consortia were performed out to improve the salt-tolerance of Bacillus amyloliquefaciens for producing lipopeptide under FW and seawater. High-salt stress significantly decreased lipopeptide production in the B. amyloliquefaciens HM618 and ALE strains. The total lipopeptide production in the recombinant B. amyloliquefaciens HM-4KSMSO after overexpressing the ion transportor gene ktrA and proline transporter gene opuE and replacing the promoter of gene mrp was 1.34 times higher than that in the strain HM618 in medium containing 30 g/L NaCl. Lipopeptide production under salt-tolerant consortia containing two strains (HM-4KSMSO and Corynebacterium glutamicum) and three-strains (HM-4KSMSO, salt-tolerant C. glutamicum, and Yarrowia lipolytica) was 1.81- and 2.28-fold higher than that under pure culture in a medium containing FW or both FW and seawater, respectively. These findings provide a new strategy for using high-salt FW and seawater to produce value-added chemicals.

Joint toxicity of cadmium (II) and microplastic leachates on wheat seed germination and seedling growth.

Cadmium (Cd) pollution ranks first in soils (7.0%) and microplastics usually have a significant adsorption capacity for it, which could pose potential threats to agricultural production and human health. However, the joint toxicity of Cd and microplastics on crop growth remains largely unknown. In this study, the toxic effects of Cd2+ and two kinds of microplastic leachates, polyvinyl chloride (PVC) and low-density polyethylene (LDPE), on wheat seed germination and seedlings' growth were explored under single and combined conditions. The results showed that Cd2+ solution and two kinds of microplastic leachates stimulated the wheat seed germination process but inhibited the germination rate by 0-8.6%. The combined treatments promoted wheat seed germination but inhibited the seedlings' growth to different degrees. Specifically, the combination of 2.0 mg L-1 Cd2+ and 1.0 mgC L-1 PVC promoted both seed germination and seedlings' growth, but they synergistically increased the antioxidant enzyme activity of seedlings. The toxicity of the PVC leachate to wheat seedlings was stronger than LDPE leachate. The addition of Cd2+ could alleviate the toxicity of PVC leachate on seedlings, and reduce the toxicity of LDPE leachate on seedlings under the same concentration class combinations but aggravated stress under different concentration classes, consistent with the effect on seedlings' growth. Overall, Cd2+, PVC, and LDPE leachates have toxic effects on wheat growth, whether treated under single or combined treatments. This study has important implications for the joint toxicity of Cd2+ solution and microplastic leachates in agriculture.

Effects of Dityrosine on Lactic Acid Metabolism in Mice Gastrocnemius Muscle During Endurance Exercise via the Oxidative Stress-Induced Mitochondria Damage.

Dityrosine (Dityr) has been detected in commercial food as a product of protein oxidation and has been shown to pose a threat to human health. This study aims to investigate whether Dityr causes a decrease in lactic acid metabolism in the gastrocnemius muscle during endurance exercise. C57BL/6 mice were administered Dityr or saline by gavage for 13 weeks and underwent an endurance exercise test on a treadmill. Dityr caused a severe reduction in motion displacement and endurance time, along with a significant increase in lactic acid accumulation in the blood and gastrocnemius muscle in mice after exercise. Dityr induced significant mitochondrial defects in the gastrocnemius muscle of mice. Additionally, Dityr induced serious oxidative stress in the gastrocnemius muscle, accompanied by inflammation, which might be one of the causes of mitochondrial dysfunction. Moreover, significant apoptosis in the gastrocnemius muscle increased after exposure to Dityr. This study confirmed that Dityr induced oxidative stress in the gastrocnemius muscle, which further caused significant mitochondrial damage in the gastrocnemius muscle cell, resulting in decreased capacity of lactic acid metabolism and finally affected performance in endurance exercise. This may be one of the possible mechanisms by which highly oxidized foods cause a decreased muscle energy metabolism.

[Application of the follower arm endoscope holder in type i tympanoplasty].

Objective:To investigate the surgical outcomes and safety of the follower arm endoscope holder in assisting type Ⅰ tympanoplasty. Methods:The clinical data of 16 patients who underwent type Ⅰ tympanoplasty at the Department of Otorhinolaryngology, Peking Union Medical College Hospital, from November 2022 to September 2023 were retrospectively analyzed, among which 8 cases were operated by traditional otoscopy and 8 cases were operated by supported endoscopy.The surgical procedure was analyzed and the completion of supported endoscopic operation was observed, while the duration of the operation, the time consumed by the main steps, the frequency of wiping the lenses, the perioperative complications, and the improvement of the postoperative hearing were recorded and statistically analyzed. Results:Supporting endoscopic technology achieved real-time suction of bleeding, simultaneous traction and separation of tissues, precise removal of calcified spots on the inner side of the eardrum, trimming of the external auditory canal flap, stable separation of the handle of the malleus and the eardrum, and tensioned repositioning of the skin-cartilage flap. The average duration of surgery, time for external auditory canal flap preparation, and time for repositioning the skin-cartilage flap were reduced in the supporting endoscopic surgery group compared to the control group. The average lens wiping frequency was significantly lower in the supporting endoscopic surgery group compared to the control group. There was no statistically significant difference in postoperative hearing improvement between the two groups, and no infections or the need for secondary surgery due to eardrum re-perforation occurred postoperatively. Conclusion:Supported endoscopy technology realizes the need for endoscopic two-handed operation and convenient switching between one and two hands, accomplishes many operations that cannot be done by traditional endoscopic surgery, solves the problems of previous intraoperative one-handed operation and image instability, shortens the average operation time compared with traditional otoscopic surgery, and decreases the frequency of intraoperative wiping of the lens significantly compared with traditional otoscopic surgery, which is potentially worthwhile in terms of shortening the learning curve.

Passive exercise is an effective alternative to HRT for restoring OVX induced mitochondrial dysfunction in skeletal muscle.

Background: Postmenopausal women are more prone to develop muscle weakness, which is strongly associated with impairment of mitochondrial function in skeletal muscle. This study aimed to examine the impact of a passive exercise modality, whole-body vibration training (WBVT), on muscle mitochondrial function in ovariectomized (OVX) mice, in comparison with 17ß-estradiol (E2) replacement. Methods: Female C57BL/6J mice were assigned to four groups: sham operation control group (Sham), ovariectomized group (OVX), OVX with E2 supplement group (OVX+E), and OVX with WBVT group (OVX+W). The estrous cycle, body weight, body composition, and muscle strength of the mice were monitored after the operation. Serum E2 level was assessed by enzyme-linked immunosorbent assay (ELISA). The ATP levels were determined using a luciferase-catalyzed bioluminescence assay. The activity of mitochondrial respiration chain complexes was evaluated using high-resolution respirometry (O2K). Expression levels of oxidative phosphorylation (OXPHOS), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α), and mitochondrial transcription factor A (TFAM) were detected using western blotting. Results: We observed decreased muscle strength and impaired mitochondrial function in the skeletal muscle of OVX mice. The vibration training alleviated these impairments as much as the E2 supplement. In addition, the vibration training was superior to the ovariectomy and the estradiol replacement regarding the protein expression of PGC-1α and TFAM. Conclusion: WBVT improves the OVX-induced decline in muscle strength and impairment of mitochondrial function in the skeletal muscle. This passive exercise strategy may be useful as an alternative to E2 replacement for preventing menopausal muscular weakness. Further studies are needed to understand the effects of WBVT on various physiological systems, and precautions should be taken when implementing it in patient treatment.

Nuclear membrane protein SUN2 promotes replication of flaviviruses through modulating cytoskeleton reorganization mediated by NS1.

Cytoskeleton is extensively recruited by flaviviruses for their infection. In this study, we uncovered an essential role of a nuclear membrane protein, SAD1/UNC84 domain protein 2 (SUN2) linking cytoskeleton and nucleoskeleton in the flavivirus replication. CRISPR/Cas9-mediated knockout of SUN2, but not SUN1, significantly reduces the replication of Zika virus (ZIKV), dengue virus (DENV), and Japanese encephalitis virus (JEV). In contrast, SUN2 does not affect the infection of non-flaviviridae RNA viruses. All three regions of SUN2 are required for its proviral effect. Mechanistically, SUN2 facilitates rearrangement of cytoskeleton and formation of replication organelles induced by viral infection, and hence promotes viral RNA synthesis. SUN2 is required for the interaction between cytoskeleton actin and ZIKV nonstructural protein 1 (NS1). Expression of dominant negative Nesprin-1 and Nesprin-2, which connect SUN2 to cytoskeleton proteins, alleviates the interaction between actin and NS1 and reduces viral replication levels. In a neonatal mouse infection model, SUN2 knockout dramatically alleviates the in vivo ZIKV replication and development of neuropathology. This work elucidates that recruitment of cytoskeleton proteins by flavivirus is coordinated by nuclear membrane proteins SUN2 and Nesprins, providing evidence for a link between nuclear membrane proteins and flavivirus infection.

Graph-Based Fusion of Imaging, Genetic and Clinical Data for Degenerative Disease Diagnosis.

Graph learning methods have achieved noteworthy performance in disease diagnosis due to their ability to represent unstructured information such as inter-subject relationships. While it has been shown that imaging, genetic and clinical data are crucial for degenerative disease diagnosis, existing methods rarely consider how best to use their relationships. How best to utilize information from imaging, genetic and clinical data remains a challenging problem. This study proposes a novel graph-based fusion (GBF) approach to meet this challenge. To extract effective imaging-genetic features, we propose an imaging-genetic fusion module which uses an attention mechanism to obtain modality-specific and joint representations within and between imaging and genetic data. Then, considering the effectiveness of clinical information for diagnosing degenerative diseases, we propose a multi-graph fusion module to further fuse imaging-genetic and clinical features, which adopts a learnable graph construction strategy and a graph ensemble method. Experimental results on two benchmarks for degenerative disease diagnosis (Alzheimers Disease Neuroimaging Initiative and Parkinson's Progression Markers Initiative) demonstrate its effectiveness compared to state-of-the-art graph-based methods. Our findings should help guide further development of graph-based models for dealing with imaging, genetic and clinical data.

De-Pinning Fermi Level and Accelerating Surface Kinetics with an ALD Finish Boost the Fill Factor of BiVO4 Photoanodes to 44.

With the rapid development of performance and long-term stability, bismuth vanadate (BiVO4 ) has emerged as the preferred photoanode in photoelectrochemical tandem devices. Although state-of-the-art BiVO4 photoanodes realize a saturated photocurrent density approaching the theoretical maximum, the fill factor (FF) is still inferior, pulling down the half-cell applied bias photon-to-current efficiency (HC-ABPE). Among the major fundamental limitations are the Fermi level pinning and sluggish surface kinetics at the low applied potentials. This work demonstrates that the plasma-assisted atomic layer deposition technique is capable of addressing these issues by seamlessly installing an angstrom-scale FeNi-layer between BiVO4 and electrolyte. Not only this ultrathin FeNi layer serves as an efficient OER cocatalyst, more importantly, it also effectively passivates the surface states of BiVO4 , de-pins the surface Fermi level, and enlarges the built-in voltage, allowing the photoanode to make optimal use of the photogenerated holes for achieving high FF up to 44% and HC-ABPE to 2.2%. This study offers a new approach for enhancing the FF of photoanodes and provides guidelines for designing efficient unassisted solar fuel devices.

Edge sulfur vacancies riched MoS2 nanosheets assist PEDOT:PSS flexible film ammonia sensing enhancement for wireless greenhouse vegetables monitoring.

Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is a promising NH3 sensing material owing to its super high electrical conductivity, excellent environmental stability, and reversible doping/dedoping nature. However, the low sensitivity and sluggish recovery rate limit its further application in gas sensors. Herein, exfoliated layered MoS2 nanosheets with large-specific surface area and abundant edge sulfur (S) vacancies are utilized to assist PEDOT:PSS and achieve ideal improvement in NH3 sensing performance at room temperature (RT), including high response values, fast response/recovery ability, and excellent sensing stability in complex environment. MoS2 nanosheets are combined with PEDOT:PSS to construct p-n heterojunction, the S vacancies can improve carrier transfer rate and serve as conductive bridge, effective active sites for NH3 adsorption, this series of performance improvement strategies is the significance of this work. Meanwhile, the density-functional theory (DFT), current-voltage (I-V), and in-situ FITR are firstly employed to discuss the sensing mechanisms in detail. Furthermore, integrating MoS2/PEDOT:PSS flexible sensor into a designed printed circuit board to intelligent, visual, and wireless real-time monitoring the NH3 resistance information in a simulated greenhouse vegetables equipment through the smartphone APP has also been successfully implemented.

Bio-inspired Ti3C2Tx MXene composite coating for enhancing corrosion resistance of aluminum alloy in acidic environments.

Aluminum alloy (Al alloy) suffers from severe corrosion in acidic solution. Two-dimensional (2D) MXene-based composite coatings show great prospects for corrosion protection on metals used in special conditions. The composite coatings still face challenges in complex functionalization and orientation control. In harsh conditions, the long-term ability and roles of MXene in corrosion protection are still not clear. Here, a bio-inspired myristic-calcium chloride-Ti3C2Tx MXene (MA + CaCl2 + MXene) composite coating is successfully prepared on aluminum alloy (Al alloy) by electrodeposition process. Electrochemical tests, surface morphology, and chemical composition are analyzed to investigate the corrosion resistance and protection mechanism of the MXene coating in acidic solution (0.5 M H2SO4 + 2 ppm HF). As a result, the incorporation of MXene can significantly reduce corrosion current density (7.498 × 10-8 A/cm2) by âˆ¼ 5 orders of magnitude and impedance modulus at 0.01 Hz (|Z|0.01 Hz) value of the composite coating is 196.8 Ω·cm2, which is over 4 times higher than that of bare Al alloy (40.74 Ω·cm2) after immersion test for 72 h. Furthermore, the in-situ corrosion test confirms the enhanced corrosion resistance of the MA + CaCl2 + MXene composite coating. The MXene can increase coating thickness to 23.6 ± 0.4 µm, reduce porosity to (5.845 ± 1) × 10-5, decrease the diffusion coefficients of H+ to (1.587 ± 0.3) × 10-9 cm2/s, and enhance the adhesion of the coating to the substrate (the delamination time exceeds 5 h), thus providing improved anti-corrosion ability. This strategy opens up new prospects for construction of 2D MXene-based anti-corrosion coatings.

Prompt Hole Extraction Suppresses V5+ Dissolution and Sustains Large-Area BiVO4 Photoanodes for Over 2100 h Water Oxidation.

Nanostructured bismuth vanadate (BiVO4) is at the forefront of emerging photoanodes in photoelectrochemical tandem devices for solar water splitting owing to the suitable band edge position and efficient charge separation capability. However, the (photo)chemical corrosion involving V5+ dissolution limits the long-term stability of BiVO4. Herein, guided by DFT calculations, we introduce an ALD-derived NiOx catalyst layer on BiVO4 to stabilize the surface Bi-O bonds, facilitate hole extraction, and thus suppress the V5+ dissolution. At the same time, the ALD NiOx catalyst layer could efficiently suppress the surface recombination and accelerate the surface OER kinetics, boosting the half-cell applied bias photon-to-current efficiency of BiVO4 to 2.05%, as well as a fill factor of 47.1%. By adding trace NaVO3 to the electrolyte, the NiOx/BiVO4 photoanode with an illumination area of 10.5 cm2 shows a record operational stability of more than 2100 h.

Accurate Segmentation and Tracking of Chorda Tympani in Endoscopic Middle Ear Surgery with Artificial Intelligence.

Objective: We introduce a novel endoscopic middle ear surgery dataset specifically designed for evaluating deep learning (DL)-based semantic segmentation of chorda tympani. Methods: We curated a dataset comprising 8240 images from 25 patients, divided into a training set (20%, 1648 images), validation set (5%, 412 images), and test set (75%, 6180 images). We employed data enhancement techniques to expand the picture size of the training and validation sets by 5 times (training set: 8240 images, verification set: 2060 images). Subsequently, we employed a multistage transfer learning training method to establish, train, and validate various convolutional neural networks. Results: On the validation set of 2060 labeled images, our proposed network achieved good results, with the U-net exhibiting the highest effectiveness (mIOU = 0.8737, mPA = 0.9263). Furthermore, when applied to the test dataset of 6180 raw images and contrasted with the prediction of otologists, the overall performance of the U-net was excellent (accuracy = 0.911, precision = 0.9823, sensitivity = 0.8777, specificity = 0.9714). Conclusions: Our findings demonstrate that DL can be successfully employed for automatic segmentation of chorda tympani in endoscopic middle ear surgery, yielding high-performance results. This study validates the potential feasibility of future intelligent navigation technologies to assist in endoscopic middle ear surgery.

Monthly runoff prediction based on variational modal decomposition combined with the dung beetle optimization algorithm for gated recurrent unit model.

Highly accurate monthly runoff forecasts play a pivotal role in water resource management and utilization. This article proposes a coupling of variational modal decomposition (VMD) and the dung beetle optimization algorithm (DBO) with the gated recurrent unit (GRU) to establish a new monthly runoff forecasting model: the VMD-DBO-GRU. Initially, historical runoff data are decomposed via VMD. Subsequently, the parameters of the GRU are optimized using the DBO, and the decomposed monthly runoff components are inputted into the GRU neural network. Finally, the predictions for each component are consolidated to provide monthly runoff predictions. The model is then validated using monthly runoff data from the Ansha reservoir in Fujian, collected from 1980 to 2020. The results demonstrate a higher prediction accuracy of the VMD-DBO-GRU model compared to BP, SVM, GRU, VMD-GRU, DBO-GRU, and EMD-GRU models, providing a new alternative for conducting monthly runoff prediction.

RNA-binding deficient TDP-43 drives cognitive decline in a mouse model of TDP-43 proteinopathy.

TDP-43 proteinopathies including frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) are neurodegenerative disorders characterized by aggregation and mislocalization of the nucleic acid-binding protein TDP-43 and subsequent neuronal dysfunction. Here, we developed endogenous models of sporadic TDP-43 proteinopathy based on the principle that disease-associated TDP-43 acetylation at lysine 145 (K145) alters TDP-43 conformation, impairs RNA-binding capacity, and induces downstream mis-regulation of target genes. Expression of acetylation-mimic TDP-43K145Q resulted in stress-induced nuclear TDP-43 foci and loss of TDP-43 function in primary mouse and human-induced pluripotent stem cell (hiPSC)-derived cortical neurons. Mice harboring the TDP-43K145Q mutation recapitulated key hallmarks of FTLD, including progressive TDP-43 phosphorylation and insolubility, TDP-43 mis-localization, transcriptomic and splicing alterations, and cognitive dysfunction. Our study supports a model in which TDP-43 acetylation drives neuronal dysfunction and cognitive decline through aberrant splicing and transcription of critical genes that regulate synaptic plasticity and stress response signaling. The neurodegenerative cascade initiated by TDP-43 acetylation recapitulates many aspects of human FTLD and provides a new paradigm to further interrogate TDP-43 proteinopathies.

BDE-209-induced genotoxicity, intestinal damage and intestinal microbiota dysbiosis in zebrafish (Danio Rerio).

The environmental presence of polybrominated diphenyl ethers (PBDEs) is ubiquitous due to their wide use as brominated flame retardants in industrial products. As a common congener of PBDEs, decabromodiphenyl ether (BDE-209) can pose a health risk to animals as well as humans. However, to date, few studies have explored BDE-209's toxic effects on the intestinal tract, and its relevant mechanism of toxicity has not been elucidated. In this study, adult male zebrafish were exposed to BDE-209 at 6 µg/L, 60 µg/L and 600 µg/L for 28 days, and intestinal tissue and microbial samples were collected for analysis to reveal the underlying toxic mechanisms. Transcriptome sequencing results demonstrated a dose-dependent pattern of substantial gene differential expression in the group exposed to BDE-209, and the differentially expressed genes were mainly concentrated in pathways related to protein synthesis and processing, redox reaction, and steroid and lipid metabolism. In addition, BDE-209 exposure caused damage to intestinal structure and barrier function, and promoted intestinal oxidative stress, inflammatory response, apoptosis and steroid and lipid metabolism disorders. Mechanistically, BDE-209 induced intestinal inflammation by increasing the levels of TNF-α and IL-1ß and activating the NFκB signaling pathway, and might induce apoptosis through the p53-Bax/Bcl2-Caspase3 pathway. BDE-209 also significantly inhibited the gene expression of rate-limiting enzymes such as Sqle and 3ßhsd (p < 0.05) to inhibit cholesterol synthesis. In addition, BDE-209 induced lipid metabolism disorders through the mTOR/PPARγ/RXRα pathway. 16S rRNA sequencing results showed that BDE-209 stress reduced the richness and diversity of intestinal microbiota, and reduced the abundance of probiotics (e.g., Bifidobacterium and Faecalibacterium). Overall, the results of this study help to clarify the intestinal response mechanism of BDE-209 exposure, and provide a basis for evaluating the health risks of BDE-209 in animals.