Universal high-frequency monitoring methods of river water quality in China based on machine learning.

The in-situ high-frequency monitoring of total nitrogen (TN) and total phosphorus (TP) in rivers is a challenge and key to instant water quality judgment and early warning. Based on the physical and chemical association between TN/TP and sensor-measurable predictors, we proposed a novel "indirect" measurement method for TN and TP in rivers. This method combines the timeliness of multi-sensor and the accuracy of intelligent algorithms, utilizing 188,629 data sets from 131 water monitoring stations across China. Under 5 algorithms and 4 predictor group scenarios, the results showed that: (1) extra tree regression (ETR) with 6 predictors exhibited the best precision, and mean determination coefficient (R2) of TN and TP inversion across 131 stations reached 0.78 ±â€¯0.25 and 0.79 ±â€¯0.22 respectively; (2) among 6 potential predictors, the importance degrees of temperature, electrical conductivity, NH4-N, and turbidity were large than pH and dissolved oxygen (DO), and >80 % of stations exhibited acceptable prediction accuracy (R2 > 0.6) when the number of predictors (P) ranged from 4 to 6, which showed good tolerability to predictor variations; (3) the accurate classification rate of water quality standard (ACRws) of all stations based on TN and TP reached 90.41 ±â€¯6.96 % and 92.33 ±â€¯6.41 %; (4) in 9 regions/basins of China, this method showed universal application potential with no significant prediction difference. Compared with laboratory test, water quality automatic monitoring station, and remote sensing inversion, the proposed method has high-frequency, high-precision, regional adaptability, low cost, and stable operation under rainy, cloudy, and nighttime conditions. The new method may provide important technological support for timely pollutant tracing, pre-warning, and emergency control for river pollution.

High-temperature-insensitivity high-power Yb-doped fiber laser directly in-band pumping by 1018 nm laser diodes.

In this Letter, we demonstrate a high-power ytterbium-doped fiber laser (YDFL) based on a directly in-band pumping scheme (DIPS) which employs 1018 nm laser diodes (LDs) as pump sources. The wavelength of the LDs is designed theoretically, considering the distribution of Yb3+ absorption cross section (σa) as well as quantum defect (QD). The flat distribution of σa around 1018 nm ensures excellent temperature insensitivity and flexibility for the YDFL. Besides, lower QD and more compact structure promise higher optical-to-optical (O-O) and electrical-to-optical (E-O) efficiencies. Based on the experimental setup, as the cooling temperature of the 1018 nm LDs ranges from 6 to 23°C, an output power of 2 kW level is achieved that varies by only 2.01% without adjusting the operating current of the LDs subjectively. The output power is then scaled up to 5 kW level. Furthermore, there is a great potential to achieve higher output power and E-O efficiency in YDFLs based on the DIPS.

Construction of Fire Safe Thermoplastic Polyurethane/Reduced Graphene Oxide Hierarchical Composites with Electromagnetic Interference Shielding.

Incorporating outstanding flame retardancy and electromagnetic interference shielding effectiveness (EMI SE) into polymers is a pressing requirement for practical utilization. In this study, we first employed the principles of microencapsulation and electrostatic interaction-driven self-assembly to encapsulate polyethyleneimine (PEI) molecules and Ti3C2Tx nanosheets on the surface of ammonium polyphosphate (APP), forming a double-layer-encapsulated structure of ammonium polyphosphate (APP@PEI@Ti3C2Tx). Subsequently, flame-retardant thermoplastic polyurethane (TPU) composites were fabricated by melting the flame-retardant agent with TPU. Afterwards, by using air-assisted thermocompression technology, we combined a reduced graphene oxide (rGO) film with flame-retardant TPU composites to fabricate hierarchical TPU/APP@PEI@Ti3C2Tx/rGO composites. We systematically studied the combustion behavior, flame retardancy, and smoke-suppression performance of these composite materials, as well as the flame-retardant mechanism of the expansion system. The results indicated a significant improvement in the interface interaction between APP@PEI@Ti3C2Tx and the TPU matrix. Compared to pure TPU, the TPU/10APP@PEI@1TC composite exhibited reductions of 84.1%, 43.2%, 62.4%, and 85.2% in peak heat release rate, total heat release, total smoke release, and total carbon dioxide yield, respectively. The averaged EMI SE of hierarchical TPU/5APP@PEI@1TC/rGO also reached 15.53 dB in the X-band.

AKI-Pro score for predicting progression to severe acute kidney injury or death in patients with early acute kidney injury after cardiac surgery.

BACKGROUND: No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. METHODS: In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. RESULTS: The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P < 0.05). CONCLUSIONS: The AKI-Pro score is a new clinical tool that could assist clinicians to identify early AKI patients at high risk for AKI progression or death.

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest in developing COVID-19 serology tests to monitor population-level immunity. To address this critical need, we designed a paper-based multiplexed vertical flow assay (xVFA) using five structural proteins of SARS-CoV-2, detecting IgG and IgM antibodies to monitor changes in COVID-19 immunity levels. Our platform not only tracked longitudinal immunity levels but also categorized COVID-19 immunity into three groups: protected, unprotected, and infected, based on the levels of IgG and IgM antibodies. We operated two xVFAs in parallel to detect IgG and IgM antibodies using a total of 40 µL of human serum sample in <20 min per test. After the assay, images of the paper-based sensor panel were captured using a mobile phone-based custom-designed optical reader and then processed by a neural network-based serodiagnostic algorithm. The serodiagnostic algorithm was trained with 120 measurements/tests and 30 serum samples from 7 randomly selected individuals and was blindly tested with 31 serum samples from 8 different individuals, collected before vaccination as well as after vaccination or infection, achieving an accuracy of 89.5%. The competitive performance of the xVFA, along with its portability, cost-effectiveness, and rapid operation, makes it a promising computational point-of-care (POC) serology test for monitoring COVID-19 immunity, aiding in timely decisions on the administration of booster vaccines and general public health policies to protect vulnerable populations.

Whole-brain Mapping of Inputs and Outputs of Specific Orbitofrontal Cortical Neurons in Mice.

The orbitofrontal cortex (ORB), a region crucial for stimulus-reward association, decision-making, and flexible behaviors, extensively connects with other brain areas. However, brain-wide inputs to projection-defined ORB neurons and the distribution of inhibitory neurons postsynaptic to neurons in specific ORB subregions remain poorly characterized. Here we mapped the inputs of five types of projection-specific ORB neurons and ORB outputs to two types of inhibitory neurons. We found that different projection-defined ORB neurons received inputs from similar cortical and thalamic regions, albeit with quantitative variations, particularly in somatomotor areas and medial groups of the dorsal thalamus. By counting parvalbumin (PV) or somatostatin (SST) interneurons innervated by neurons in specific ORB subregions, we found a higher fraction of PV neurons in sensory cortices and a higher fraction of SST neurons in subcortical regions targeted by medial ORB neurons. These results provide insights into understanding and investigating the function of specific ORB neurons.

Nutritional Strategies for Muscle Atrophy: Current Evidence and Underlying Mechanisms.

Skeletal muscle can undergo detrimental changes in various diseases, leading to muscle dysfunction and atrophy, thus severely affecting people's lives. Along with exercise, there is a growing interest in the potential of nutritional support against muscle atrophy. This review provides a brief overview of the molecular mechanisms driving skeletal muscle atrophy and summarizes recent advances in nutritional interventions for preventing and treating muscle atrophy. The nutritional supplements include amino acids and their derivatives (such as leucine, ß-hydroxy, ß-methylbutyrate, and creatine), various antioxidant supplements (like Coenzyme Q10 and mitoquinone, resveratrol, curcumin, quercetin, Omega 3 fatty acids), minerals (such as magnesium and selenium), and vitamins (such as vitamin B, vitamin C, vitamin D, and vitamin E), as well as probiotics and prebiotics (like Lactobacillus, Bifidobacterium, and 1-kestose). Furthermore, the study discusses the impact of a combined approach involving nutritional support and physical therapy to prevent muscle atrophy, suggests appropriate multi-nutritional and multi-modal interventions based on individual conditions to optimize treatment outcomes, and enhances the recovery of muscle function for patients. By understanding the molecular mechanisms behind skeletal muscle atrophy and implementing appropriate interventions, it is possible to enhance the recovery of muscle function and improve patients' quality of life.

Unveiling the A-to-I mRNA editing machinery and its regulation and evolution in fungi.

A-to-I mRNA editing in animals is mediated by ADARs, but the mechanism underlying sexual stage-specific A-to-I mRNA editing in fungi remains unknown. Here, we show that the eukaryotic tRNA-specific heterodimeric deaminase FgTad2-FgTad3 is responsible for A-to-I mRNA editing in Fusarium graminearum. This editing capacity relies on the interaction between FgTad3 and a sexual stage-specific protein called Ame1. Although Ame1 orthologs are widely distributed in fungi, the interaction originates in Sordariomycetes. We have identified key residues responsible for the FgTad3-Ame1 interaction. The expression and activity of FgTad2-FgTad3 are regulated through alternative promoters, alternative translation initiation, and post-translational modifications. Our study demonstrates that the FgTad2-FgTad3-Ame1 complex can efficiently edit mRNA in yeasts, bacteria, and human cells, with important implications for the development of base editors in therapy and agriculture. Overall, this study uncovers mechanisms, regulation, and evolution of RNA editing in fungi, highlighting the role of protein-protein interactions in modulating deaminase function.

Allergens induce upregulated IL-18 and IL-18Rα expression in blood Th2 and Th17 cells of patients with allergic asthma.

Allergic asthma (AA) is closely associated with the polarization of T helper (Th)2 and Th17 cells. Interleukin (IL)-18 acts as an inducer of Th2 and Th17 cell responses. However, expressions of IL-18 and IL-18 receptor alpha (IL-18Rα) in blood Th2 and Th17 cells of patients with AA remain unclear. We therefore investigated their expressions in Th2 and Th17 cells using flow cytometric analysis, quantitative real-time PCR (qPCR), and murine AA model. We observed increased proportions of Th2, Th17, IL-18+, IL-18+ Th2, and IL-18+ Th17 cells in blood CD4+ T cells of patients with AA. Additionally, house dust mite seemed to upregulate further IL-18 expression in Th2 and Th17, and upregulate IL-18Rα expression in CD4+ T, Th2, and Th17 cells of AA patients. It was also found that the plasma levels of IL-4, IL-17A, and IL-18 in AA patients were elevated, and they were correlated between each other. In ovalbumin (OVA)-induced asthma mouse (AM), we observed that the percentages of blood CD4+ T, Th2, and Th17 cells were increased. Moreover, OVA-induced AM expressed higher level of IL-18Rα in blood Th2 cells, which was downregulated by IL-18. Increased IL-18Rα expression was also observed in blood Th2 cells of OVA-induced FcεRIα-/- mice. Collectively, our findings suggest the involvement of Th2 cells in AA by expressing excessive IL-18 and IL-18Rα in response to allergen, and that IL-18 and IL-18Rα expressing Th2 cells are likely to be the potential targets for AA therapy.

Maternal immune activation induces sex-dependent behavioral differences in a rat model of schizophrenia.

Background: Maternal immune activation (MIA) is a mature means to construct a schizophrenia model. However, some preclinical studies have reported that a MIA-induced schizophrenia model seemed to have gender heterogeneity in behavioral phenotype. On the other hand, the MIA's paradigms were diverse in different studies, and many details could affect the effect of MIA. To some extent, it is not credible and scientific to directly compare the gender differences of different MIA programs. Therefore, it is necessary to study whether the sex of the exposed offspring leads to behavioral differences on the premise of maintaining a consistent MIA mode. Methods: An animal model of schizophrenia was established by the administration of 10 mg/kg Poly (I: C) when dams were on day 9 of gestation. Then, a number of female and male offspring completed a series of behavioral tests during postnatal days 61-75. Results: Compared with the female control group (n = 14), female MIA offspring (n = 12) showed a longer movement distance (d = 1.07, p < 0.05) and higher average speed (d = 1.08, p < 0.05) in the open field test (OFT). In the Y maze test, the percentage of entering the novel arm of female MIA offspring was lower (d = 0.92, p < 0.05). Compared with the male control group (n = 14), male MIA offspring (n = 13) displayed less movement distance (d = 0.93, p < 0.05) and a lower average speed (d = 0.94, p < 0.05) in the OFT. In the Y maze test, the proportion of exploration time in the novel arm of male MIA offspring was lower (d = 0.96, p < 0.05). In the EPM, male MIA offspring showed less time (d = 0.85, p < 0.05) and a lower percentage of time spent in the open arms (d = 0.85, p < 0.05). Male MIA offspring also had a lower PPI index (76 dB + 120 dB, d = 0.81, p < 0.05; 80 dB + 120 dB, d = 1.45, p < 0.01). Conclusions: Our results showed that the behavioral phenotypes induced by prenatal immune activation were highly dependent on the sex of the offspring.

See farther and more: a master-slave UAVs based synthetic optical aperture imaging system with wide and dynamic baseline.

An open challenge remained in designing an optical system to capture the aerial image with a wide field of view (FoV) and high resolution. The optical system of one camera from a single unmanned aerial vehicle (UAV) can hardly promise the FoV and resolution. The conventional swarm UAVs can form the camera array with a short or fixed baseline. They can capture the images with a wide FoV and high resolution, but the cost is the requirement of many UAVs. We aim to design a camera array with a wide and dynamic baseline to reduce the demand for UAVs to organize a synthetic optical aperture. In this thought, we propose a master-slave UAVs-based synthetic optical aperture imaging system with a wide and dynamic baseline. The system consists of one master UAV and multiple slave UAVs. Master and slave UAVs provide the global and local FoVs, respectively, and improve the efficiency of image acquisition. In such a system, fusing UAV images becomes a new challenge due to two factors: (i) the small FoV overlap of slave UAVs and (ii) the gap in resolution scale from slave to master UAV images. To deal with it, a coarse-to-fine stitching method is proposed to stitch up the multi-view images into one to obtain a wide FoV with high resolution. A video stabilization method has also been designed for the proposed imaging system. Challenges caused by wide and dynamic baselines can thus be solved by the above methods. Actual data experiments demonstrate that the proposed imaging system achieves high-quality imaging results.

Skin mottling score assesses peripheral tissue hypoperfusion in critically ill patients following cardiac surgery.

BACKGROUND: Skin mottling is a common manifestation of peripheral tissue hypoperfusion, and its severity can be described using the skin mottling score (SMS). This study aims to evaluate the value of the SMS in detecting peripheral tissue hypoperfusion in critically ill patients following cardiac surgery. METHODS: Critically ill patients following cardiac surgery with risk factors for tissue hypoperfusion were enrolled (n = 373). Among these overall patients, we further defined a hypotension population (n = 178) and a shock population (n = 51). Hemodynamic and perfusion parameters were recorded. The primary outcome was peripheral hypoperfusion, defined as significant prolonged capillary refill time (CRT, > 3.0 s). The characteristics and hospital mortality of patients with and without skin mottling were compared. The area under receiver operating characteristic curves (AUROC) were used to assess the accuracy of SMS in detecting peripheral hypoperfusion. Besides, the relationships between SMS and conventional hemodynamic and perfusion parameters were investigated, and the factors most associated with the presence of skin mottling were identified. RESULTS: Of the 373-case overall population, 13 (3.5%) patients exhibited skin mottling, with SMS ranging from 1 to 5 (5, 1, 2, 2, and 3 cases, respectively). Patients with mottling had lower mean arterial pressure, higher vasopressor dose, less urine output (UO), higher CRT, lactate levels and hospital mortality (84.6% vs. 12.2%, p < 0.001). The occurrences of skin mottling were higher in hypotension population and shock population, reaching 5.6% and 15.7%, respectively. The AUROC for SMS to identify peripheral hypoperfusion was 0.64, 0.68, and 0.81 in the overall, hypotension, and shock populations, respectively. The optimal SMS threshold was 1, which corresponded to specificities of 98, 97 and 91 and sensitivities of 29, 38 and 67 in the three populations (overall, hypotension and shock). The correlation of UO, lactate, CRT and vasopressor dose with SMS was significant, among them, UO and CRT were identified as two major factors associated with the presence of skin mottling. CONCLUSION: In critically ill patients following cardiac surgery, SMS is a very specific yet less sensitive parameter for detecting peripheral tissue hypoperfusion.

Adaptive dynamic self-learning grey wolf optimization algorithm for solving global optimization problems and engineering problems.

The grey wolf optimization algorithm (GWO) is a new metaheuristic algorithm. The GWO has the advantages of simple structure, few parameters to adjust, and high efficiency, and has been applied in various optimization problems. However, the orginal GWO search process is guided entirely by the best three wolves, resulting in low population diversity, susceptibility to local optima, slow convergence rate, and imbalance in development and exploration. In order to address these shortcomings, this paper proposes an adaptive dynamic self-learning grey wolf optimization algorithm (ASGWO). First, the convergence factor was segmented and nonlinearized to balance the global search and local search of the algorithm and improve the convergence rate. Second, the wolves in the original GWO approach the leader in a straight line, which is too simple and ignores a lot of information on the path. Therefore, a dynamic logarithmic spiral that nonlinearly decreases with the number of iterations was introduced to expand the search range of the algorithm in the early stage and enhance local development in the later stage. Then, the fixed step size in the original GWO can lead to algorithm oscillations and an inability to escape local optima. A dynamic self-learning step size was designed to help the algorithm escape from local optima and prevent oscillations by reasonably learning the current evolution success rate and iteration count. Finally, the original GWO has low population diversity, which makes the algorithm highly susceptible to becoming trapped in local optima. A novel position update strategy was proposed, using the global optimum and randomly generated positions as learning samples, and dynamically controlling the influence of learning samples to increase population diversity and avoid premature convergence of the algorithm. Through comparison with traditional algorithms, such as GWO, PSO, WOA, and the new variant algorithms EOGWO and SOGWO on 23 classical test functions, ASGWO can effectively improve the convergence accuracy and convergence speed, and has a strong ability to escape from local optima. In addition, ASGWO also has good performance in engineering problems (gear train problem, ressure vessel problem, car crashworthiness problem) and feature selection.

Deficiency of purinergic P2X4 receptor alleviates experimental autoimmune hepatitis in mice.

Purinergic P2X4 receptor (P2X4R) has been shown to have immunomodulatory properties in infection, inflammation, and organ damage including liver regeneration and fibrosis. However, the mechanisms and pathophysiology associated with P2X4R during acute liver injury remain unknown. We used P2X4R-/- mice to explore the role of P2X4R in three different models of acute liver injury caused by concanavalin A (ConA), carbon tetrachloride, and acetaminophen. ConA treatment results in an increased expression of P2X4R in the liver of mice, which was positively correlated with higher levels of aspartate aminotransferase and alanine aminotransferase in the serum. However, P2X4R gene ablation significantly reduced the severity of acute hepatitis in mice caused by ConA, but not by carbon tetrachloride or acetaminophen. The protective benefits against immune-mediated acute hepatitis were achieved via modulating inflammation (Interleukin (IL)-1ß, IL-6, IL-17A, interferon-γ, tumor necrosis factor-α), oxidative stress (malondialdehyde, superoxide dismutase, glutathione peroxidase, and catalase), apoptosis markers (Bax, Bcl-2, and Caspase-3), autophagy biomarkers (LC3, Beclin-1, and p62), and nucleotide oligomerization domain-likereceptorprotein 3(NLRP3) inflammasome-activated pyroptosis markers (NLRP3, Gasdermin D, Caspase-1, ASC, IL-1ß). Additionally, administration of P2X4R antagonist (5-BDBD) or agonist (cytidine 5'-triphosphate) either improved or worsened ConA-induced autoimmune hepatitis, respectively. This study is the first to reveal that the absence of the P2X4 receptor may mitigate immune-mediated liver damage, potentially by restraining inflammation, oxidation, and programmed cell death mechanisms. And highlight P2X4 receptor is essential for ConA-induced acute hepatitis.

Virtual Staining of Nonfixed Tissue Histology.

Surgical pathology workflow involves multiple labor-intensive steps, such as tissue removal, fixation, embedding, sectioning, staining, and microscopic examination. This process is time-consuming and costly and requires skilled technicians. In certain clinical scenarios, such as intraoperative consultations, there is a need for faster histologic evaluation to provide real-time surgical guidance. Currently, frozen section techniques involving hematoxylin and eosin (H&E) staining are used for intraoperative pathology consultations. However, these techniques have limitations, including a turnaround time of 20 to 30 minutes, staining artifacts, and potential tissue loss, negatively impacting accurate diagnosis. To address these challenges, researchers are exploring alternative optical imaging modalities for rapid microscopic tissue imaging. These modalities differ in optical characteristics, tissue preparation requirements, imaging equipment, and output image quality and format. Some of these imaging methods have been combined with computational algorithms to generate H&E-like images, which could greatly facilitate their adoption by pathologists. Here, we provide a comprehensive, organ-specific review of the latest advancements in emerging imaging modalities applied to nonfixed human tissue. We focused on studies that generated H&E-like images evaluated by pathologists. By presenting up-to-date research progress and clinical utility, this review serves as a valuable resource for scholars and clinicians, covering some of the major technical developments in this rapidly evolving field. It also offers insights into the potential benefits and drawbacks of alternative imaging modalities and their implications for improving patient care.

Increased CO2 fixation enables high carbon-yield production of 3-hydroxypropionic acid in yeast.

CO2 fixation plays a key role to make biobased production cost competitive. Here, we use 3-hydroxypropionic acid (3-HP) to showcase how CO2 fixation enables approaching theoretical-yield production. Using genome-scale metabolic models to calculate the production envelope, we demonstrate that the provision of bicarbonate, formed from CO2, restricts previous attempts for high yield production of 3-HP. We thus develop multiple strategies for bicarbonate uptake, including the identification of Sul1 as a potential bicarbonate transporter, domain swapping of malonyl-CoA reductase, identification of Esbp6 as a potential 3-HP exporter, and deletion of Uga1 to prevent 3-HP degradation. The combined rational engineering increases 3-HP production from 0.14 g/L to 11.25 g/L in shake flask using 20 g/L glucose, approaching the maximum theoretical yield with concurrent biomass formation. The engineered yeast forms the basis for commercialization of bio-acrylic acid, while our CO2 fixation strategies pave the way for CO2 being used as the sole carbon source.

Virtual histological staining of unlabeled autopsy tissue.

Traditional histochemical staining of post-mortem samples often confronts inferior staining quality due to autolysis caused by delayed fixation of cadaver tissue, and such chemical staining procedures covering large tissue areas demand substantial labor, cost and time. Here, we demonstrate virtual staining of autopsy tissue using a trained neural network to rapidly transform autofluorescence images of label-free autopsy tissue sections into brightfield equivalent images, matching hematoxylin and eosin (H&E) stained versions of the same samples. The trained model can effectively accentuate nuclear, cytoplasmic and extracellular features in new autopsy tissue samples that experienced severe autolysis, such as COVID-19 samples never seen before, where the traditional histochemical staining fails to provide consistent staining quality. This virtual autopsy staining technique provides a rapid and resource-efficient solution to generate artifact-free H&E stains despite severe autolysis and cell death, also reducing labor, cost and infrastructure requirements associated with the standard histochemical staining.

Autophagic degradation of MVBs in LSECs promotes Aldosterone induced-HSCs activation.

BACKGROUND AND AIMS: The important role of extracellular vesicles (EVs) in liver fibrosis has been confirmed. However, EVs derived from liver sinusoidal endothelial cells (LSECs) in the activation of hepatic stellate cells (HSCs) and liver fibrosis is still unclear. Our previous work demonstrated that Aldosterone (Aldo) may have the potential to regulate EVs from LSECs via autophagy pathway. Thus, we aim to investigate the role of Aldo in the regulation of EVs derived from LSECs. APPROACH AND RESULTS: Using an Aldo-continuous pumping rat model, we observed that Aldo-induced liver fibrosis and capillarization of LSECs. In vitro, transmission electron microscopy (TEM) revealed that stimulation of Aldo led to the upregulation of autophagy and degradation of multivesicular bodies (MVBs) in LSECs. Mechanistically, Aldo upregulated ATP6V0A2, which promoted lysosomal acidification and subsequent autophagy in LSECs. Inhibiting autophagy with si-ATG5 adeno-associated virus (AAV) in LSECs effectively mitigated Aldo-induced liver fibrosis in rats. RNA sequencing and nanoparticle tracking (NTA) analyses of EVs derived from LSECs indicated that Aldo result in a decrease in both the quantity and quality of EVs. We also observed a reduction in the protective miRNA-342-5P in EVs derived from Aldo-treated LSECs, which may play a critical role in HSCs activation. Target knockdown of EV secretion with si-RAB27a AAV in LSECs led to the development of liver fibrosis and HSC activation in rats. CONCLUSION: Aldo-induced Autophagic degradation of MVBs in LSECs promotes a decrease in the quantity and quality of EVs derived from LSECs, resulting in the activation of HSCs and liver fibrosis under hyperaldosteronism. Modulating the autophagy level of LSECs and their EV secretion may represent a promising therapeutic approach for treating liver fibrosis.