Multiple Sclerosis (MS) is a neurologic autoimmune disease whose exact pathophysiologic mechanisms remain to be elucidated. Recent studies have shown that the onset and progression of MS are associated with dysbiosis of the gut microbiota. Similarly, a large body of evidence suggests that mitochondrial dysfunction may also have a significant impact on the development of MS. Endosymbiotic theory has found that human mitochondria are microbial in origin and share similar biological characteristics with the gut microbiota. Therefore, gut microbiota and mitochondrial function crosstalk are relevant in the development of MS. However, the relationship between gut microbiota and mitochondrial function in the development of MS is not fully understood. Therefore, by synthesizing previous relevant literature, this paper focuses on the changes in gut microbiota and metabolite composition in the development of MS and the possible mechanisms of the crosstalk between gut microbiota and mitochondrial function in the progression of MS, to provide new therapeutic approaches for the prevention or reduction of MS based on this crosstalk.
Superlattices constructed with the wide-band-gap semiconductor ZnO and magnetic oxide FeO, both in the wurtzite structure, have been investigated using spin-polarized first-principles calculations. The structural, electronic and magnetic properties of the (ZnO)n/(w-FeO)n superlattices were studied in great detail. Two different interfaces in the (ZnO)n/(w-FeO)n superlattices were identified and they showed very different magnetic and electronic properties. Local symmetry-driven interfacial magnetization and electronic states can arise from different Fe/Zn distributions at different interfaces or spin ordering of Fe in the superlattice. The local symmetry-driven interfacial magnetization and electronic states, originating either from different Fe/Zn distribution across interfaces I and II, or by spin ordering of Fe in the superlattice, can be identified. It was also found that, in the case of the ferromagnetic phase, the electrons are more delocalized for the majority spin but strongly localized for the minority spin, which resulted in interesting spin-dependent transport properties. Our results will pave the way for designing novel spin-dependent electronic devices through the construction of superlattices from semiconductors and multiferroics.
The development of high-efficiency organic solar cells (OSCs) processed from non-halogenated solvents is crucially important for their scale-up industry production. However, owing to the difficulty of regulating molecular aggregation, there is a huge efficiency gap between non-halogenated and halogenated solvent processed OSCs. Herein, we fabricate o-xylene processed OSCs with approaching 20 % efficiency by incorporating a trimeric guest acceptor named Tri-V into the PM6:L8-BO-X host blend. The incorporation of Tri-V effectively restricts the excessive aggregation of L8-BO-X, regulates the molecular packing and optimizes the phase-separation morphology, which leads to mitigated trap density states, reduced energy loss and suppressed charge recombination. Consequently, the PM6:L8-BO-X:Tri-V-based device achieves an efficiency of 19.82 %, representing the highest efficiency for non-halogenated solvent-processed OSCs reported to date. Noticeably, with the addition of Tri-V, the ternary device shows an improved photostability than binary PM6:L8-BO-X-based device, and maintains 80 % of the initial efficiency after continuous illumination for 1380â h. This work provides a feasible approach for fabricating high-efficiency, stable, eco-friendly OSCs, and sheds new light on the large-scale industrial production of OSCs.
The treatment of spinal cord injury (SCI) is often ineffective. Additionally, SCI-induced inflammation leads to secondary injury. Current anti-inflammatory hydrophilic drugs fail to reach the nerve injury site due to the blood-brain barrier. Here, we synthesized MSR405, a new lipophilic unsaturated fatty acid derivative of Radix Isatidis and investigated its therapeutic effect in SCI model rats. Furthermore, we systematically investigated its structure, toxicity, anti-inflammatory effect, and the underlying mechanism. MSR405 was injected into the abdominal cavity of the Sprague Dawley SCI model rats, and the effect on their behavioral scores and pathology was estimated to assess the status of neurological inflammation. Our data show that MSR405 treatment significantly improved the motor function of SCI rats, and markedly suppressed the associated neuroinflammation. Moreover, MSR405 could attenuate LPS-induced inflammatory response in BV2 cells (Mouse microglia cells) in vitro. Mechanistically, MSR405 inhibits proinflammatory cytokines, supporting the anti-inflammatory response. Additionally, MSR405 can significantly block the TLR4/NF-κB signaling pathway and nitric oxide production. In summary, MSR405 reduces inflammation in SCI rats through the TLR4/NF-κB signal cascade and can inhibit neuroinflammation after spinal cord injury.
To address the limitations of LiDAR dynamic target detection methods, which often require heuristic thresholding, indirect computational assistance, supplementary sensor data, or postdetection, we propose an innovative method based on multidimensional features. Using the differences between the positions and geometric structures of point cloud clusters scanned by the same target in adjacent frame point clouds, the motion states of the point cloud clusters are comprehensively evaluated. To enable the automatic precision pairing of point cloud clusters from adjacent frames of the same target, a double registration algorithm is proposed for point cloud cluster centroids. The iterative closest point (ICP) algorithm is employed for approximate interframe pose estimation during coarse registration. The random sample consensus (RANSAC) and four-parameter transformation algorithms are employed to obtain precise interframe pose relations during fine registration. These processes standardize the coordinate systems of adjacent point clouds and facilitate the association of point cloud clusters from the same target. Based on the paired point cloud cluster, a classification feature system is used to construct the XGBoost decision tree. To enhance the XGBoost training efficiency, a Spearman's rank correlation coefficient-bidirectional search for a dimensionality reduction algorithm is proposed to expedite the optimal classification feature subset construction. After preliminary outcomes are generated by XGBoost, a double Boyer-Moore voting-sliding window algorithm is proposed to refine the final LiDAR dynamic target detection accuracy. To validate the efficacy and efficiency of our method in LiDAR dynamic target detection, an experimental platform is established. Real-world data are collected and pertinent experiments are designed. The experimental results illustrate the soundness of our method. The LiDAR dynamic target correct detection rate is 92.41%, the static target error detection rate is 1.43%, and the detection efficiency is 0.0299 s. Our method exhibits notable advantages over open-source comparative methods, achieving highly efficient and precise LiDAR dynamic target detection.
BACKGROUND AND STUDY AIMS: Gastrointestinal stromal tumors (GIST) carry a potential risk of malignancy, and the treatment of GIST varies for different risk levels. However, there is no systematic preoperative assessment protocol to predict the malignant potential of GIST. The aim of this study was to develop a reliable and clinically applicable preoperative nomogram prediction model to predict the malignant potential of gastric GIST. PATIENTS AND METHODS: Patients with a pathological diagnosis of gastric GIST from January 2015 to December 2021 were screened retrospectively. Univariate and multivariate logistic analyses were used to identify independent risk factors for gastric GIST with high malignancy potential. Based on these independent risk factors, a nomogram model predicting the malignant potential of gastric GIST was developed and the model was validated in the validation group. RESULTS: A total of 494 gastric GIST patients were included in this study and allocated to a development group (n = 345) and a validation group (n = 149). In the development group, multivariate logistic regression analysis revealed that tumor size, tumor ulceration, CT growth pattern and monocyte-to- lymphocyte ratio (MLR) were independent risk factors for gastric GIST with high malignancy potential. The AUC of the model were 0.932 (95% CI 0.890-0.974) and 0.922 (95% CI 0.868-0.977) in the development and validation groups, respectively. The best cutoff value for the development group was 0.184, and the sensitivity and specificity at this value were 0.895 and 0.875, respectively. The calibration curves indicated good agreement between predicted and actual observed outcomes, while the DCA indicated that the nomogram model had clinical application. CONCLUSIONS: Tumor size, tumor ulceration, CT growth pattern and MLR are independent risk factors for high malignancy potential gastric GIST, and a nomogram model developed based on these factors has a high ability to predict the malignant potential of gastric GIST.
Gastrointestinal Stromal Tumors , Stomach Neoplasms , Humans , Nomograms , Gastrointestinal Stromal Tumors/pathology , Retrospective Studies , Stomach Neoplasms/surgery , Stomach Neoplasms/pathology , Risk Factors
The complexity of learning problems, such as Generative Adversarial Network (GAN) and its variants, multi-task and meta-learning, hyper-parameter learning, and a variety of real-world vision applications, demands a deeper understanding of their underlying coupling mechanisms. Existing approaches often address these problems in isolation, lacking a unified perspective that can reveal commonalities and enable effective solutions. Therefore, in this work, we proposed a new framework, named Learning with Constraint Learning (LwCL), that can holistically examine challenges and provide a unified methodology to tackle all the above-mentioned complex learning and vision problems. Specifically, LwCL is designed as a general hierarchical optimization model that captures the essence of these diverse learning and vision problems. Furthermore, we develop a gradient-response based fast solution strategy to overcome optimization challenges of the LwCL framework. Our proposed framework efficiently addresses a wide range of applications in learning and vision, encompassing three categories and nine different problem types. Extensive experiments on synthetic tasks and real-world applications verify the effectiveness of our approach. The LwCL framework offers a comprehensive solution for tackling complex machine learning and computer vision problems, bridging the gap between theory and practice.
Speech recognition crucially relies on slow temporal modulations (<16 Hz) in speech. Recent studies, however, have demonstrated that the long-delay echoes, which are common during online conferencing, can eliminate crucial temporal modulations in speech but do not affect speech intelligibility. Here, we investigated the underlying neural mechanisms. MEG experiments demonstrated that cortical activity can effectively track the temporal modulations eliminated by an echo, which cannot be fully explained by basic neural adaptation mechanisms. Furthermore, cortical responses to echoic speech can be better explained by a model that segregates speech from its echo than by a model that encodes echoic speech as a whole. The speech segregation effect was observed even when attention was diverted but would disappear when segregation cues, i.e., speech fine structure, were removed. These results strongly suggested that, through mechanisms such as stream segregation, the auditory system can build an echo-insensitive representation of speech envelope, which can support reliable speech recognition.
Auditory Cortex , Speech Perception , Humans , Speech Perception/physiology , Speech Intelligibility/physiology , Brain , Auditory Cortex/physiology , Attention , Acoustic Stimulation
Invasive candidiasis caused by non-albicans species has been on the rise, with Candida glabrata emerging as the second most common etiological agent. Candida glabrata possesses an intrinsically lower susceptibility to azoles and an alarming propensity to rapidly develop high-level azole resistance during treatment. In this study, we have developed an efficient piggyBac (PB) transposon-mediated mutagenesis system in C. glabrata to conduct genome-wide genetic screens and applied it to profile genes that contribute to azole resistance. When challenged with the antifungal drug fluconazole, PB insertion into 270 genes led to significant resistance. A large subset of these genes has a role in the mitochondria, including almost all genes encoding the subunits of the F1F0 ATPase complex. We show that deleting ATP3 or ATP22 results in increased azole resistance but does not affect susceptibility to polyenes and echinocandins. The increased azole resistance is due to increased expression of PDR1 that encodes a transcription factor known to promote drug efflux pump expression. Deleting PDR1 in the atp3Δ or atp22Δ mutant resulted in hypersensitivity to fluconazole. Our results shed light on the mechanisms contributing to azole resistance in C. glabrata. This PB transposon-mediated mutagenesis system can significantly facilitate future genome-wide genetic screens.
Candida glabrata , Fluconazole , Fluconazole/metabolism , Candida glabrata/genetics , Drug Resistance, Fungal/genetics , Antifungal Agents/pharmacology , Azoles , Proton-Translocating ATPases/metabolism , Microbial Sensitivity Tests
A multifunctional single-atom nanozyme, denoted as 3D Ni,N-codoped porous carbon (Ni-NPC), was devised that exhibits remarkable adsorption capabilities and a repertoire of enzyme mimetic functions (oxidase- and peroxidase-like). These attributes stem from the distinctive mesoporous thin-shell structure and well-dispersed Ni sites. The efficient adsorption capacity of Ni-NPC was assessed with respect to three carbamate pesticides (CMPs): metolcarb, carbaryl, and isoprocarb. Moreover, a colorimetric detection method for CMP was established based on its robust peroxidase-like catalytic activity and sequential catalytic interactions with acetylcholinesterase. Furthermore, a portable colorimetric sensor based on a hydrogel sphere integrated with a smartphone platform was devised. This sensor enables rapid, on-site, and quantitative assessment of CMP, boasting an extraordinarily low detection limit of 1.5 ng mL-1. Notably, this sensor was successfully applied to the analysis of CMP levels in lake water and vegetable samples (pakchoi and rape), propelling the progress of real-time detection technologies in food and environment monitoring.
Pesticides , Smartphone , Acetylcholinesterase , Pesticides/analysis , Carbamates/chemistry , Peroxidase , Peroxidases , Colorimetry
Hyperspectral spectrum enables assessment of heavy metal content, but research on low concentration in water is limited. This study employed in situ hyperspectral data from Dalian Lake, Shanghai to develop a machine learning model for accurately determining heavy metal concentrations. Initially, we employed a combination of empirical analysis and algorithm-based analysis to identify the optimal features for retrieving Cu and Fe ions. Based on the correlation coefficients between heavy metals and water quality, the feature bands for TOC, Chl-a and TP were selected as empirical features. Algorithm-based feature selection was conducted by employing the random forest (RF) approach with the original spectrum (OR), first-order derivative reflectance (FDR), and second-order derivative reflectance (SDR). For the development of a prediction model, we utilized the Genetic Algorithm-Partial Least Squares Regression (GA-PLSR) approach for Cu and Fe ions inversion. Our findings demonstrated that the integration of both empirical features and algorithm-selected features resulted in superior performance compared to using algorithm-selected features alone. Importantly, the crucial wavelength data primarily located at 497, 665, 686, 831 and 935 nm showed superior results for Cu retrieval, while wavelengths of 700, 746, 801, 948, and 993 nm demonstrated better results for Fe retrieval. These results also displayed that the GA-PLSR model outperformed both the PLSR and RF models, exhibiting an R2 of 0.75, RMSE of 0.004, and MRE of 0.382 for Cu inversion. For Fe inversion, the GA-PLSR model outperformed other models with an R2 of 0.73, RMSE of 0.036, and MRE of 0.464. This research provides a scientific basis and data support for monitoring low concentrations of heavy metals in water bodies using hyperspectral remote sensing techniques.
Semi-transparent organic solar cells (ST-OSCs) possess significant potential for applications in vehicles and buildings due to their distinctive visual transparency. Conventional device engineering strategies are typically used to optimize photon selection and utilization at the expense of power conversion efficiency (PCE); moreover, the fixed spectral utilization range always imposes an unsatisfactory upper limit to its light utilization efficiency (LUE). Herein, a novel solid additive named 1,3-diphenoxybenzene (DB) is employed to dual-regulate donor/acceptor molecular aggregation and crystallinity, which effectively broadens the spectral response of ST-OSCs in near-infrared region. Besides, more visible light is allowed to pass through the devices, which enables ST-OSCs to possess satisfactory photocurrent and high average visible transmittance (AVT) simultaneously. Consequently, the optimal ST-OSC based on PP2+DB/BTP-eC9+DB achieves a superior LUE of 4.77%, representing the highest value within AVT range of 40-50%, which also correlates with the formation of multi-scale phase-separated morphology. Such results indicate that the ST-OSCs can simultaneously meet the requirements for minimum commercial efficiency and plant photosynthesis when integrated with the roofs of agricultural greenhouses. This work emphasizes the significance of additives to tune the spectral response in ST-OSCs, and charts the way for organic photovoltaics in economically sustainable agricultural development.
The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10-8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening.
Lung Neoplasms , Humans , Female , Lung Neoplasms/epidemiology , Lung Neoplasms/genetics , Genetic Risk Score , Genetic Predisposition to Disease , Cohort Studies , Prospective Studies , Genome-Wide Association Study , Risk Factors , Smoking/genetics , Smoking/epidemiology , China
Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.
Brain-Computer Interfaces , Humans , Electroencephalography/methods , Brain , Electrodes
IMPORTANCE: Candida auris is a recently emerged pathogenic fungus of grave concern globally due to its resistance to conventional antifungals. This study takes a whole-genome approach to explore how C. auris overcomes growth inhibition imposed by the common antifungal drug fluconazole. We focused on gene disruptions caused by a "jumping genetic element" called transposon, leading to fluconazole resistance. We identified mutations in two genes, each encoding a component of the Ubr2/Mub1 ubiquitin-ligase complex, which marks the transcription regulator Rpn4 for degradation. When either protein is absent, stable Rpn4 accumulates in the cell. We found that Rpn4 activates the expression of itself as well as the main drug efflux pump gene CDR1 by binding to a PACE element in the promoter. Furthermore, we identified an amino acid change in Ubr2 in many resistant clinical isolates, contributing to Rpn4 stabilization and increased fluconazole resistance.
In the human fungal pathogen Candida albicans, invasive hyphal growth is a well-recognized virulence trait. We employed transposon-mediated genome-wide mutagenesis, revealing that inactivating CTM1 blocks hyphal growth. CTM1 encodes a lysine (K) methyltransferase, which trimethylates cytochrome c (Cyc1) at K79. Mutants lacking CTM1 or expressing cyc1K79A grow as yeast under hyphae-inducing conditions, indicating that unmethylated Cyc1 suppresses hyphal growth. Transcriptomic analyses detected increased levels of the hyphal repressor NRG1 and decreased levels of hyphae-specific genes in ctm1Δ/Δ and cyc1K79A mutants, suggesting cyclic AMP (cAMP)-protein kinase A (PKA) signaling suppression. Co-immunoprecipitation and in vitro kinase assays demonstrated that unmethylated Cyc1 inhibits PKA kinase activity. Surprisingly, hyphae-defective ctm1Δ/Δ and cyc1K79A mutants remain virulent in mice due to accelerated proliferation. Our results unveil a critical role for cytochrome c in maintaining the virulence of C. albicans by orchestrating proliferation, growth mode, and metabolism. Importantly, this study identifies a biological function for lysine methylation on cytochrome c.
Candida albicans , Fungal Proteins , Animals , Mice , Humans , Candida albicans/metabolism , Fungal Proteins/genetics , Fungal Proteins/metabolism , Cyclic AMP/metabolism , Cytochromes c/metabolism , Hyphae , Lysine/metabolism , Morphogenesis , Gene Expression Regulation, Fungal
The degeneration of dopamine (DA) neurons is known to be associated with defects in mitochondrial biogenesis caused by aging, environmental factors, or mutations in genes, leading to Parkinson's disease (PD). As PD has not yet been successfully cured, the strategy of using small molecule drugs to protect and restore mitochondrial biogenesis is a promising direction. This study evaluated the efficacy of synthetic chiisanoside (CSS) identified in the leaves of Acanthopanax sessiliflorus to prevent PD symptoms. The results show that in the 6-hydroxydopamine (6-OHDA) model, CSS pretreatment can effectively alleviate the reactive oxygen species generation and apoptosis of SH-SY5Y cells, thereby lessening the defects in the C. elegans model including DA neuron degeneration, dopamine-mediated food sensitivity behavioral disorders, and shortened lifespan. Mechanistically, we found that CSS could restore the expression of proliferator-activated receptor gamma coactivator-1-alpha (PGC-1α), a key molecule in mitochondrial biogenesis, and its downstream related genes inhibited by 6-OHDA. We further confirmed that this is due to the enhanced activity of parkin leading to the ubiquitination and degradation of PGC-1α inhibitor protein Zinc finger protein 746 (ZNF746). Parkin siRNA treatment abolished this effect of CSS. Furthermore, we found that CSS inhibited 6-OHDA-induced expression of miR-181a, which targets parkin. The CSS's ability to reverse the 6-OHDA-induced reduction in mitochondrial biogenesis and activation of apoptosis was abolished after the transfection of anti-miR-181a and miR-181a mimics. Therefore, the neuroprotective effect of CSS mainly promotes mitochondrial biogenesis by regulating the miR-181a/Parkin/ZNF746/PGC-1α axis. CSS potentially has the opportunity to be developed into PD prevention agents.
Introduction: Every-other-day fasting (EODF) is a classical intermittent fasting (IF) mode with neuroprotective effects that promotes motor function recovery after spinal cord injury (SCI) in rats. However, its dynamic effects on the gut microbiota and spinal cord transcriptome remain unknown. Methods: In this study, 16S rRNA sequencing and RNA-seq analysis were used to investigate the effects of ad libitum (AL) and EODF dietary modes on the structural characteristics of rat gut microbiota in rats and the spinal cord transcriptome at various time points after SCI induction. Results: Our results showed that both dietary modes affected the bacterial community composition in SCI rats, with EODF treatment inducing and suppressing dynamic changes in the abundances of potentially anti-inflammatory and pro-inflammatory bacteria. Furthermore, the differentially expressed genes (DEGs) enriched after EODF intervention in SCI rats were associated with various biological events, including immune inflammatory response, cell differentiation, protein modification, neural growth, and apoptosis. In particular, significant spatiotemporal differences were apparent in the DEGs associated with neuroprotection between the EODF and AL interventions. These DGEs were mainly focused on days 1, 3, and 7 after SCI. The relative abundance of certain genera was significantly correlated with DEGs associated with neuroprotective effects in the EODF-SCI group. Discussion: Our results showed that EODF treatment may exert neuroprotective effects by modulating the transcriptome expression profile following SCI in rats. Furthermore, gut microbiota may be partially involved in mediating these effects.
Taipu River is a river spanning two provinces and one city in a demonstration area in the Yangtze River Delta on an ecologically friendly developmentand an important water source in the upper reaches of the Huangpu River in Shanghai. To understand the multi-media distribution characteristics, pollution status, and ecological risk of heavy metals in the Taipu River, the contents of heavy metals (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, and Zn) in the sediments of Taipu River were analyzed, and the pollution status and potential ecological risk were evaluated using the Nemerow comprehensive pollution index, geo-accumulation index, and potential ecological risk index methods. In addition, the health risk assessment model was used to assess the health risk of heavy metals in surface water of Taipu River. The results showed that the concentrations of Cd, Cr, Mn, and Ni in the surface water of Taipu River exceeded the class â ¢ water limit at the upstream point in spring; the concentrations of Sb exceeded the class â ¢ water limit at all points in winter; the average value of As exceeded the class â ¢ water limit in overlying water during the wet season; and the average values of As and Cd exceeded the class â ¢ water limit in pore water during the wet season. The health risk assessment of surface water implied that both adults and children had higher health risk in spring and lower health risk in other seasons. The health risk of children was significantly higher than that of adults, and it mainly came from chemical carcinogenic heavy metal elements As, Cd, and Cr. The average contents of Co, Mn, Sb, and Zn in Taipu River sediments in the four seasons all exceeded the Shanghai soil baseline; the average contents of As, Cr, and Cu in summer, autumn, and winter exceeded the Shanghai soil baseline; and the average contents of Cd, Ni, and Pb in summer and winter exceeded the Shanghai soil baseline. The evaluation results of the Nemerow comprehensive pollution index and geo-accumulation index showed that the pollution degree of the middle reaches of Taipu River was higher than that of the upper and lower reaches, and the Sb pollution was more serious. The potential ecological risk index method revealed that the Taipu River sediment was at a low risk. Cd had a high contribution in both the wet and dry seasons and could be regarded as the main heavy metal of potential ecological risk in the Taipu River sediment.
