Artificial Funnel Nanochannel Device Emulates Synaptic Behavior.

Creating artificial synapses that can interact with biological neural systems is critical for developing advanced intelligent systems. However, there are still many difficulties, including device morphology and fluid selection. Based on Micro-Electro-Mechanical System technologies, we utilized two immiscible electrolytes to form a liquid/liquid interface at the tip of a funnel nanochannel, effectively enabling a wafer-level fabrication, interactions between multiple information carriers, and electron-to-chemical signal transitions. The distinctive ionic transport properties successfully achieved a hysteresis in ionic transport, resulting in adjustable multistage conductance gradient and synaptic functions. Notably, the device is similar to biological systems in terms of structure and signal carriers, especially for the low operating voltage (200 mV), which matches the biological neural potential (∼110 mV). This work lays the foundation for realizing the function of iontronics neuromorphic computing at ultralow operating voltages and in-memory computing, which can break the limits of information barriers for brain-machine interfaces.

Prognostic factors associated with early recurrence following liver resection for colorectal liver metastases: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer (CRC) is the 3rd most common malignancy with the liver being the most common site of metastases. The recurrence rate of colorectal liver metastases (CRLM) after liver resection (LR) is notably high, with an estimated 40% of patients experiencing recurrence within 6 months. In this context, we conducted a meta-analysis to synthesize and evaluate the reliability of evidence pertaining to prognostic factors associated with early recurrence (ER) in CRLM following LR. METHODS: Systematic searches were conducted from the inception of databases to July 14, 2023, to identify studies reporting prognostic factors associated with ER. The Quality in Prognostic Factor Studies (QUIPS) tool was employed to assess risk-of-bias for included studies. Meta-analysis was then performed on these prognostic factors, summarized by forest plots. The grading of evidence was based on sample size, heterogeneity, and Egger's P value. RESULTS: The study included 24 investigations, comprising 12705 individuals, during an accrual period that extended from 2007 to 2023. In the evaluation of risk-of-bias, 22 studies were rated as low/moderate risk, while two studies were excluded because of high risk. Most of the studies used a postoperative interval of 6 months to define ER, with 30.2% (95% confidence interval [CI], 24.1-36.4%) of the patients experiencing ER following LR. 21 studies were pooled for meta-analysis. High-quality evidence showed that poor differentiation of CRC, larger and bilobar-distributed liver metastases, major hepatectomy, positive surgical margins, and postoperative complications were associated with an elevated risk of ER. Additionally, moderate-quality evidence suggested that elevated levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA199), lymph node metastases (LNM) of CRC, and a higher number of liver metastases were risk factors for ER. CONCLUSION: This review has the potential to enhance the efficacy of surveillance strategies, refine prognostic assessments, and guide judicious treatment decisions for CRLM patients with high risk of ER. Additionally, it is essential to undertake well-designed prospective investigations to examine additional prognostic factors and develop salvage therapeutic approaches for ER of CRLM.

Local Structure and Crystallization Transformation of Hydrous Ferric Arsenate in Acidic H2O-Fe(III)-As(V)-SO42- Systems: Implications for Acid Mine Drainage and Arsenic Geochemical Cycling.

Hydrous ferric arsenate (HFA) is a common thermodynamically metastable phase in acid mine drainage (AMD). However, little is known regarding the structural forms and transformation mechanism of HFA. We investigated the local atomic structures and the crystallization transformation of HFA at various Fe(III)/As(V) ratios (2, 1, 0.5, 0.33, and 0.25) in acidic solutions (pH 1.2 and 1.8). The results show that the Fe(III)/As(V) in HFA decreases with decreasing initial Fe(III)/As(V) at acidic pHs. The degree of protonation of As(V) in HFA increases with increasing As(V) concentrations. The Fe K-edge extended X-ray absorption fine structure and X-ray absorption near-edge structure results reveal that each FeO6 is linked to more than two AsO4 in HFA precipitated at Fe(III)/As(V) < 1. Furthermore, the formation of scorodite (FeAsO4·2H2O) is greatly accelerated by decreasing the initial Fe(III)/As(V). The release of As(V) from HFA is observed during its crystallization transformation process to scorodite at Fe(III)/As(V) < 1, which is different from that at Fe(III)/As(V) ≥ 1. Scanning electron microscopy results show that Oswald ripening is responsible for the coarsening of scorodite regardless of the initial Fe(III)/As(V) or pH. Moreover, the formation of crystalline ferric dihydrogen arsenate as an intermediate phase at Fe(III)/As(V) < 1 is responsible for the enhanced transformation rate from HFA to scorodite. This work provides new insights into the local atomic structure of HFA and its crystallization transformation that may occur in AMD and has important implications for arsenic geochemical cycling.

Divergent adaptation strategies of abundant and rare bacteria to salinity stress and metal stress in polluted Jinzhou Bay.

Understanding how abundant (AT) and rare (RT) taxa adapt to diverse environmental stresses is vital for assessing ecological processes, yet remains understudied. We collected sediment samples from Liaoning Province, China, representing rivers (upstream of wastewater outlet), estuaries (wastewater outlets), and Jinzhou Bay (downstream of wastewater outlets), to comprehensively evaluate AT and RT adaptation strategies to both natural stressors (salinity stress) and anthropogenic stressors (metal stress). Generally, RT displayed higher α- and ß-diversities and taxonomic groups compared to AT. Metal and salinity stresses induced distinct α-diversity responses in AT and RT, while ß-diversity remained consistent. Both subcommunities were dominated by Woeseia genus. Metal stress emerged as the primary driver of diversity and compositional discrepancies in AT and RT. Notably, AT responded more sensitively to salinity stress than RT. Stress increased topological parameters in the biotic network of AT subcommunities while decreasing values in RT subcommunities, concurrently loosening interactions of AT with other taxa and strengthening interactions of RT with others in biotic networks. RT generally exhibited greater diversity of metal resistance genes compared to AT. Greater numbers of genes related to salinity tolerance was observed for the RT than for AT. Compared to AT, RT demonstrated higher diversity of metal resistance genes and a greater abundance of genes associated with salinity tolerance. Additionally, deterministic processes governed AT community assembly, reinforced by salinity stress. However, the opposite trend was observed in the RT, where the importance of stochastic process gradually increased with metal stresses. The study is centered on exploring the adaptation strategies of both AT and RT to environmental stress. It underscores the importance of future research incorporating diverse ecosystems and a range of environmental stressors to draw broader and more reliable conclusions. This comprehensive approach is essential for gaining a thorough understanding of the adaptive mechanisms employed by these microorganisms.

Automatic soft-tissue analysis on orthodontic frontal and lateral facial photographs based on deep learning.

BACKGROUND: To establish the automatic soft-tissue analysis model based on deep learning that performs landmark detection and measurement calculations on orthodontic facial photographs to achieve a more comprehensive quantitative evaluation of soft tissues. METHODS: A total of 578 frontal photographs and 450 lateral photographs of orthodontic patients were collected to construct datasets. All images were manually annotated by two orthodontists with 43 frontal-image landmarks and 17 lateral-image landmarks. Automatic landmark detection models were established, which consisted of a high-resolution network, a feature fusion module based on depthwise separable convolution, and a prediction model based on pixel shuffle. Ten measurements for frontal images and eight measurements for lateral images were defined. Test sets were used to evaluate the model performance, respectively. The mean radial error of landmarks and measurement error were calculated and statistically analysed to evaluate their reliability. RESULTS: The mean radial error was 14.44 ± 17.20 pixels for the landmarks in the frontal images and 13.48 ± 17.12 pixels for the landmarks in the lateral images. There was no statistically significant difference between the model prediction and manual annotation measurements except for the mid facial-lower facial height index. A total of 14 measurements had a high consistency. CONCLUSION: Based on deep learning, we established automatic soft-tissue analysis models for orthodontic facial photographs that can automatically detect 43 frontal-image landmarks and 17 lateral-image landmarks while performing comprehensive soft-tissue measurements. The models can assist orthodontists in efficient and accurate quantitative soft-tissue evaluation for clinical application.

Protective effects of ginsenosides on ulcerative colitis: a meta-analysis and systematic review to reveal the mechanisms of action.

BACKGROUND: Ulcerative colitis (UC) is a chronic inflammatory disease of the colon. Ginsenoside may be an ideal agent for UC treatment. However, its efficacy and safety are unknown. We aim to conduct a systematic evaluation to assess the effects and potential mechanisms of ginsenosides in animal models of UC. METHODS: Six electronic databases will be searched (PubMed, Embase, Web of Science, China Knowledge Network (CNKI), China Science and Technology Journal Database (CQVIP), and Wanfang Data Knowledge). SYRCLE list will be used to assess the quality of literature, and STATA 15.1 for data analysis. Time-dose effects analysis will be used to reveal the time-dosage response relations between ginsenosides and UC. RESULTS: Ultimately, fifteen studies involving 300 animals were included. Preliminary evidence was shown that ginsenosides could reduce Disease Activity Index (DAI) scores, weight loss, histological colitis score (HCS), spleen weight, Malondialdehyde (MDA), Myeloperoxidase (MPO) activity, interleukin-1ß (IL-1ß), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α) and increase colon length (CL), myeloperoxidase (GSH), interleukin 4 (IL-4), interleukin 10 (IL-10), Zonula Occludens-1 (ZO-1) and occludin. Results of time-dose interval analysis indicated that ginsenosides at a dosage of 5-200 mg/kg with an intervention time of 7-28 days were relatively effective. CONCLUSIONS: Preclinical evidence suggests that ginsenoside is a novel treatment for UC. And the mechanisms of ginsenosides in treating UC may involve anti-inflammatory, antioxidant, barrier protection, intestinal flora regulation, and immune regulation. Although, due to the high heterogeneity, further large-scale and high-quality preclinical studies are needed to examine the protection of ginsenosides against UC.

Wound infection and healing in minimally invasive plate osteosynthesis compared with intramedullary nail for distal tibial fractures: A meta-analysis.

To systematically explore the effects of minimally invasive plate osteosynthesis (MIPO) versus intramedullary nail (IMN) on wound infection and wound healing in patients with distal tibia fractures. A computerised search of PubMed, Web of Science, Cochrane Library, Embase, Wanfang, China Biomedical Literature Database (CBM) and China National Knowledge Infrastructure databases was performed, from their inception to October 2023, to identify relevant studies on the application of MIPO and IMN in patients with distal tibial fractures. The quality of the included literature was evaluated by two researchers based on inclusion and exclusion criteria, and basic information of the literature was collected, with wound infection, postoperative complications and wound healing time as the main indicators for analysis. Stata 17.0 software was applied for analysis. Overall, 23 papers and 2099 patients were included, including 1026 patients in the MIPO group and 1073 patients in the IMN group. The results revealed, when compared with IMN treatment, patients with distal tibia fractures who underwent MIPO treatment had a lower incidence of postoperative complications (OR = 0.33, 95% CI: 0.25-0.42, p < 0.001) and a shorter wound healing time (SMD = -1.00, 95% CI: -1.51 to -0.49, p < 0.001), but the incidence of postoperative wound infection was higher (OR = 2.01, 95% CI: 1.35-3.01, p = 0.001). Both MIPO and IMN are excellent treatments for distal tibia fractures. MIPO is effective in reducing the incidence of complications as well as shortening the time of wound healing time but increases the risk of wound infection. In clinical practice, surgeons can make individual choices based on the patient's wishes and proficiency in both techniques.

A comprehensive evaluation method for dust pollution: Digital image processing and deep learning approach.

Dust pollution poses a grave threat to both the environment and human health, especially in mining operations. To combat this issue, a novel evaluation method is proposed, integrating grayscale average (GA) analysis and deep learning (DL) in image classification. By utilizing a self-designed dust diffusion simulation system, 300 sample images were generated for analysis. The GA method establishes a correlation between grayscale average and dust mass, while incorporating fractal dimension (FD) enhances classification criteria. Both GA and DL methods were trained and compared, yielding promising results with a testing accuracy of 92.2 % and high precision, recall, and F1-score values. This approach not only demonstrates efficacy in classifying dust pollution but also presents a versatile solution applicable beyond mining to diverse dust-contaminated work environments. By combining image processing and deep learning, it offers an automated and reliable system for environmental monitoring, thereby enhancing safety standards and health outcomes in affected industries. Ultimately, this innovative method signifies a significant advancement towards mitigating dust pollution and ensuring sustainable industrial practices.

Nanomaterial-based drug-delivery system as an aid to antimicrobial photodynamic therapy in treating oral biofilm.

Diverse microorganisms live as biofilm in the mouth accounts for oral diseases and treatment failure. For decades, the prevention and treatment of oral biofilm is a global challenge. Antimicrobial photodynamic therapy (aPDT) holds promise for oral biofilm elimination due to its several traits, including broad-spectrum antimicrobial capacity, lower possibility of resistance and low cytotoxicity. However, the physicochemical properties of photosensitizers and the biological barrier of oral biofilm have limited the efficiency of aPDT. Nanomaterials has been used to fabricate nanocarriers to improve photosensitizer properties and thus enhance antimicrobial effect. In this review, we have discussed the challenges of aPDT used in dentistry, categorized the nanomaterial-delivery system and listed the possible mechanisms involved in nanomaterials when enhancing aPDT effect.

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Simultaneous stabilization of particulate and bioavailable arsenic in soils from the realgar mining area by polyacrylamide, nano-SiO2, and ferrihydrite composite materials.

Arsenic (As) contamination in realgar mining areas poses a severe environmental and health risk, highlighting the critical need for effective strategies to manage As migration, particularly in its particulate and bioavailable states. Soil erosion and water leaching serve as significant pathways for spreading As, emphasizing the imperative to curtail its mobility. In the present study, we proposed an effective strategy that combines the utilization of polyacrylamide (PAM), nano-SiO2 (NS), and ferrihydrite (Fh) to elevate the stability of As in soils from a realgar mining area. The results show that this composite material demonstrates the capability to concurrently regulate soil erosion and mitigate the leaching of bioavailable As. The combination of the three materials in the proportion of 0.5 % PAM +0.1 % NS + 1.0 % Fh can reduce the soil particulate and bioavailable As content by 99.11 % and 93.98 %, respectively. The unconfined compressive strength of the soil can be increased by about 30 % under this condition. The SEM analyses show that the addition of PAM and NS can significantly enhance the aggregation of soil particles and then reduce the soil erosion rate. These findings highlight the significant potential of the proposed approach in mitigating As contamination in soil within mining environments. The approach offers a sustainable and comprehensive solution to address the transport of heavy metal contaminants in both particulate and bioavailable states in mining areas.

Iodide and sulfite synergistically accelerate the photo-reduction and recovery of As(V) and As(III) in sulfite/iodide/UV process: Efficiency and mechanism.

Photo-reduction of arsenic (As) by hydrated electron (eaq-) and recovery of elemental arsenic (As(0)) is a promising pathway to treat As-bearing wastewater. However, previously reported sulfite/UV system needs large amounts of sulfite as the source of eaq-. This work suggests a sulfite/iodide/UV approach that is more efficient and consumes much less chemical reagents to remove As(III) and As(V) and recover valuable As(0) from wastewater, hence preventing the production of large amounts of As-containing hazardous wastes. Our results showed that more than 99.9% of As in the aqueous phase was reduced to highly pure solid As(0) (>99.5 wt%) by sulfite/iodide/UV process under alkaline conditions. Sulfite and iodide worked synergistically to enhance reductive removal of As. Compared with sulfite/UV, the addition of iodide had a substantially greater effect on As(III) (over 200 times) and As(V) (approximately 30 times) removals because of its higher absorptivity and quantum yield of eaq-. Furthermore, more than 90% of the sulfite consumption was decreased by adding a small amount of iodide while maintaining similar reduction efficiency. Hydrated electron (eaq-) was mainly responsible for As(III) and As(V) reductions and removals under alkaline conditions, while both SO3•- and reactive iodine species (e.g., I•, I2, I2•-, and I3-) may oxidize As(0) to As(III) or As(V). Acidic circumstances caused sulfite protonation and the scavenging of eaq- by competing processes. Dissolved oxygen (O2) and CO32- prevented As reduction by light blocking or eaq- scavenging actions, but Cl-, Ca2+, and Mg2+ showed negligible impacts. This study presented an efficient method for removing and recovering As from wastewater.

Mitochondrial derived vesicle-carrying protein MIGA2 promotes copper-induced autophagosomes-lysosomes fusion by regulating ATG14.

As an environmental pollution metal, copper (Cu) exposure-induced toxicity is closely related to mitochondrial damage. Mitochondrial-derived vesicles (MDVs) plays an essential role in mitochondrial quality control and cellular metabolism. However, the mechanism by which MDVs are involved in cellular metabolism under Cu exposure remains unclear. Here, the MDV-carrying protein MIGA2 was identified as a crucial molecule involved in the Cu-induced autophagosomes-lysosomes fusion. Furthermore, Cu exposure significantly promoted MDVs secretion, accompanied by a markedly increased MIGA2 expression in MDVs, as well as accelerated the autophagosomes-lysosomes fusion. However, small RNA interference of SNX9 (the MDVs secretion inductor) and MIGA2 blocked autophagic flux induced by Cu, leading to failure of autophagosomes degradation. Co-immunoprecipitation assay further demonstrated that ATG14 was a regulation target protein of MIGA2. Overexpression and knockdown of ATG14 significantly affected the autophagosomes-lysosomes fusion induced by Cu. Meanwhile, knockdown of ATG14 dramatically reversed the effect of MIGA2-overexpression in promoting autophagosomes-lysosomes fusion, while overexpression of ATG14 shows the opposite effect. These results demonstrated that MDVs-carrying MIGA2 protein promoted autophagosomes-lysosomes fusion induced by Cu. This study demonstrated that MDVs is involved in regulating organelles-to-organelles communication, providing a new insight into the toxicity mechanism of Cu exposure on hepatocytes.

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.

The identification of arsenic species produced in the dissolution of crystalline orpiment under anoxic conditions: XAS evidence.

The orpiment (As2S3) is an important secondary mineral in the geochemical process of arsenic (As) in the environment. The dissolution of orpiment has a close relationship with the migration and transformation of As. The dissolved species of As2S3 is closely related to sulfide (S-II) in the anoxic and sulfidic environment. This paper focuses on the various As species formed when As2S3 dissolved in the presence and absence of excess S-II under anoxic conditions with simulation tests via X-ray absorption spectroscopy (XAS), liquid chromatography with (hydride generation) atomic fluorescence spectrophotometry, and Raman spectroscopy. The results showed that the As produced when As2S3 dissolved in the excess S-II contained a mixture of arsenite and thioarsenite (ThioAsIII). Based on the linear combination fitting, ThioAsIII is the dominant As species (88.2 %) with arsenite as the leftover component. However, the percentage of ThioAsIII decreased to 43.7 % if As2S3 dissolved in the absence of excess S-II, indicting ThioAsIII favored under sulfidic conditions. The findings may give further insights about the role and formation mechanism of ThioAsIII in the dissolution process of As2S3. ENVIRONMENTAL IMPLICATION: The dissolution of crystallization orpiment has a close relationship with the transport of As in the environment. Qualitatively and quantitatively identification of the dissolved species of As2S3 in the presence and absence of excess S-II may be helpful for a better understanding and predicting the fate of As. The formed trithioarsenite was the dominant dissolved species compared to arsenite in the sulfidic system. It has higher mobility than AsV and AsIII, and has been found in many As-related adsorption/desorption and redox reactions. Therefore, great cautions should be given when choosing technologies to remediate the As contaminated soils and waters.

Effects of denitrification on speciation and redistribution of arsenic in estuarine sediments.

Microbially-mediated redox processes involving arsenic (As) and its host minerals significantly contribute to the mobilization of As in estuarine sediments. Despite its significance, the coupling between As dynamics and denitrification processes in these sediments is not well understood. This study employed sequential sediment extractions and simultaneous monitoring of dissolved iron (Fe), nitrogen (N), and sulfur (S) to investigate the impact of nitrate (NO3-) on the speciation and redistribution of As, alongside changes in microbial community composition. Our results indicated that NO3- additions significantly enhance anaerobic arsenite (As(III)) oxidation, facilitating its immobilization by increased adsorption onto sediment matrices in As-contaminated estuarine settings. Furthermore, NO3- promoted the conversion of As bound to troilite (FeS) and pyrite (FeS2) into forms associated with Fe oxides, challenging the previously assumed stability of FeS/FeS2-bound As in such environments. Continuous NO3- additions ensured As and Fe oxidation, thereby preventing their reductive dissolution and stabilizing the process that reduces As mobility. Changes in the abundance of bacterial communities and correlation analyses revealed that uncultured Anaerolineaceae and Thioalkalispira may be the main genus involved in these transformations. This study underscores the critical role of NO3- availability in modulating the biogeochemical cycle of As in estuarine sediments, offering profound insights for enhancing As immobilization techniques and informing environmental management and remediation strategies in As-contaminated coastal regions.

Bacterial community in the metal(loid)-contaminated marine vertical sediments of Jinzhou Bay: Impacts and adaptations.

Metal(loid) discharge has led to severe coastal contamination; however, there remains a significant knowledge gap regarding its impact on sediment profiles and depth-resolved bacterial communities. In this study, geochemical measurements (pH, nutrient elements, total and bioavailable metal(loid) content) consistently revealed decreasing nitrogen, phosphorus, and metal(loid) levels with sediment depth, accompanied by reduced alpha diversity. Principal coordinate analysis indicated distinct community compositions with varying sediment depths, suggesting a geochemical influence on diversity. Ecological niche width expanded with depth, favoring specialists over generalists, but both groups decreased in abundance. Taxonomic shifts emerged, particularly in phyla and families, correlated with sediment depth. Microbe-microbe interactions displayed intricate dynamics, with keystone taxa varying by sediment layer. Zinc and arsenic emerged as key factors impacting community diversity and composition using random forest, network analysis, and Mantel tests. Functional predictions revealed shifts in potential phenotypes related to mobile elements, biofilm formation, pathogenicity, N/P/S cycles, and metal(loid) resistance along sediment profiles. Neutral and null models demonstrated a transition from deterministic to stochastic processes with sediment layers. This study provides insights into the interplay between sediment geochemistry and bacterial communities across sediment depths, illuminating the factors shaping these ecosystems.

STSN-Net: Simultaneous Tooth Segmentation and Numbering Method in Crowded Environments with Deep Learning.

Accurate tooth segmentation and numbering are the cornerstones of efficient automatic dental diagnosis and treatment. In this paper, a multitask learning architecture has been proposed for accurate tooth segmentation and numbering in panoramic X-ray images. A graph convolution network was applied for the automatic annotation of the target region, a modified convolutional neural network-based detection subnetwork (DSN) was used for tooth recognition and boundary regression, and an effective region segmentation subnetwork (RSSN) was used for region segmentation. The features extracted using RSSN and DSN were fused to optimize the quality of boundary regression, which provided impressive results for multiple evaluation metrics. Specifically, the proposed framework achieved a top F1 score of 0.9849, a top Dice metric score of 0.9629, and an mAP (IOU = 0.5) score of 0.9810. This framework holds great promise for enhancing the clinical efficiency of dentists in tooth segmentation and numbering tasks.

Aerobic Se(IV) reducing bacteria and their reducing characteristics in estuarine sediment.

Microorganisms play a critical role in the biogeochemical cycling of selenium in natural ecosystems, particularly in reducing selenite (Se(IV)) to element selenium (Se(0)) which reduces its mobility and bioavailability. However, Se(IV)-reducing bacteria and their reducing characteristics in estuarine sediments remain inadequately understood. In this study, the reduction of Se(IV) was confirmed to be microbially driven through the cultivation of a mixture of estuarine sediment and Se(IV) under aerobic conditions. Community analysis indicates that Bacillus was primarily involved in the reduction of Se(IV). A strain with high salt tolerance (7.5 % NaCl) and Se(IV) resistance (up to 200 mM), Bacillus cereus SD1, was isolated from an estuarine sediment. The reduction of Se(IV) occurred concomitantly with the onset of microbial growth, and reduction capacity increased approximately 5-fold by adjusting the pH. In addition, Se(IV) reduction in Bacillus cereus SD1 was significantly inhibited by sulfite, and the key enzyme activity tests revealed the possible presence of a sulfite reductase-mediated Se(IV) reduction pathway. These research findings provide new insights into the bioreducing characteristics and the biogeochemical cycling of selenium in estuarine environments.

Hesperidin alleviates terbuthylazine-induced ferroptosis via maintenance of mitochondria-associated endoplasmic reticulum membrane integrity in chicken hepatocytes.

Terbuthylazine (TBA) is a common triazine herbicide used in agricultural production, which causes toxic damage in multiple tissues. Hesperidin (HSP) is a flavonoid derivative that has anti-inflammatory, antioxidant and cytoprotective effects, but its role in reducing toxic damage caused by pesticides is still unclear. In this study, we aimed to investigate the toxic effect of TBA exposure on chicken hepatocytes and the therapeutic effect of HSP on the TBA-induced hepatotoxicity. Our results demonstrated that HSP could alleviate TBA exposure-induced endoplasmic reticulum (ER) stress. Interestingly, TBA significantly disrupted the integrity of mitochondria-associated endoplasmic reticulum membrane (MAM), while HSP treatment showed the opposite tendency. In addition, TBA could significantly trigger ferroptosis in liver, and HSP treatment reversed ferroptosis under TBA exposure. These results suggested that HSP could inhibit ER stress and alleviate ferroptosis under TBA exposure via maintaining MAM integrity, which provided a novel strategy to take precautions against TBA toxicity.

Gut microbiota disorders aggravate terbuthylazine-induced mitochondrial quality control disturbance and PANoptosis in chicken hepatocyte through gut-liver axis.

Terbuthylazine (TBA) is a widely prevalent pesticide pollutant, which is a global concern due to its environmental residual. However, the toxic mechanism of TBA have not been fully solved. Here, we explored that TBA exposure disrupts the intestinal flora and aggravated disturbance of mitochondrial quality control and PANapoptosis in hepatocytes via gut-liver axis. Our findings demonstrated that TBA exposure induced significant damage to the jejunum barrier, evidenced by a marked decrease in the expression of Occludin and ZO-1. Moreover. TBA led to intestinal microflora disorder, manifested as the decreased abundance of Firmicutes, and increased abundance of the Nitrospirota, Chloroflexi, Desulfobacterota, Crenarchaeota, Myxococcota, and Planctomycetota. Meanwhile, intestinal microflora disorder affected the biological processes of lipid metabolism and cell growth and death of hepatocytes by RNA-Seq analysis. Furthermore, TBA could induced mitochondrial quality control imbalance, including mitochondrial redox disorders, lower activity of mitochondrial fusion and biogenesis decrease, and increasing level of mitophagy. Subsequently, TBA significantly increased expression levels of pyroptosis, apoptosis and necroptosis-related proteins. In general, these results demonstrated the underlying mechanisms of TBA-induced hepatotoxicity induced via the gut-liver axis, which provides a theoretical basis for further research of ecotoxicology of TBA.