When a curling rock slides on an ice sheet with an initial rotation, a lateral movement occurs, which is known as the curling phenomenon. The force of friction between the curling rock and the ice sheet changes continually with changes in the environment; thus, the sport of curling requires great skill and experience. The throwing of the curling rock is a great challenge in robot design and control, and existing curling robots usually adopt a combination scheme of a wheel chassis and gripper that differs significantly from human throwing movements. A hexapod curling robot that imitates human kicking, sliding, pushing, and curling rock rotating was designed and manufactured by our group, and completed a perfect show during the Beijing 2022 Winter Olympics. Smooth switching between the walking and throwing tasks is realized by the robot's morphology transformation based on leg configuration switching. The robot's controlling parameters, which include the kicking velocity vk , pushing velocity vp , orientation angle θc , and rotation velocity ω , are determined by aiming and sliding models according to the estimated equivalent friction coefficient μequ and ratio e of the front and back frictions. The stable errors between the target and actual stopping points converge to 0.2 and 1.105 m in the simulations and experiments, respectively, and the error shown in the experiments is close to that of a well-trained wheelchair curling athlete. This robot holds promise for helping ice-makers rectify ice sheet friction or assisting in athlete training.
This paper addresses a multi-agent scheduling problem with uniform parallel machines owned by a resource agent and competing jobs with dynamic arrival times that belong to different consumer agents. All agents are self-interested and rational with the aim of maximizing their own objectives, resulting in intense resource competition among consumer agents and strategic behaviors of unwillingness to disclose private information. Within the context, a centralized scheduling approach is unfeasible, and a decentralized approach is considered to deal with the targeted problem. This study aims to generate a stable and collaborative solution with high social welfare while simultaneously accommodating consumer agents' preferences under incomplete information. For this purpose, a dynamic iterative auction-based approach based on a decentralized decision-making procedure is developed. In the proposed approach, a dynamic auction procedure is established for dynamic jobs participating in a real-time auction, and a straightforward and easy-to-implement bidding strategy without price is presented to reduce the complexity of bid determination. In addition, an adaptive Hungarian algorithm is applied to solve the winner determination problem efficiently. A theoretical analysis is conducted to prove that the proposed approach is individually rational and that the myopic bidding strategy is a weakly dominant strategy for consumer agents submitting bids. Extensive computational experiments demonstrate that the developed approach achieves high-quality solutions and exhibits considerable stability on large-scale problems with numerous consumer agents and jobs. A further multi-agent scheduling problem considering multiple resource agents will be studied in future work.
Existing microfabricated atomic vapor cells have only one optical channel, which is insufficient for supporting the multiple orthogonal beams required by atomic devices. In this study, we present a novel wafer-level manufacturing process for fabricating multi-optical-channel atomic vapor cells and an innovative method for batch processing the inner sidewalls of millimeter glass holes to meet optical channel requirements. Surface characterization and transmittance tests demonstrate that the processed inner sidewalls satisfy the criteria for an optical channel. In addition, the construction of an integrated processing platform enables multilayer non-isothermal anode bonding, the filling of inert gases, and the recovery and recycling of noble gases. Measurements of the absorption spectra and free-induction decay signals of xenon-129 (129Xe) and xenon-131 (131Xe) under different pump-probe schemes demonstrate the suitability of our vapor cell for use in atomic devices including atomic gyroscopes, dual-beam atomic magnetometers, and other optical/atomic devices. The proposed micromolding technology has broad application prospects in the field of optical-device processing.
Electroencephalography (EEG) analysis extracts critical information from brain signals, enabling brain disease diagnosis and providing fundamental support for brain–computer interfaces. However, performing an artificial intelligence analysis of EEG signals with high energy efficiency poses significant challenges for electronic processors on edge computing devices, especially with large neural network models. Herein, we propose an EEG opto-processor based on diffractive photonic computing units (DPUs) to process extracranial and intracranial EEG signals effectively and to detect epileptic seizures. The signals of the EEG channels within a second-time window are optically encoded as inputs to the constructed diffractive neural networks for classification, which monitors the brain state to identify symptoms of an epileptic seizure. We developed both free-space and integrated DPUs as edge computing systems and demonstrated their applications for real-time epileptic seizure detection using benchmark datasets, that is, the Children's Hospital Boston (CHB)–Massachusetts Institute of Technology (MIT) extracranial and Epilepsy-iEEG-Multicenter intracranial EEG datasets, with excellent computing performance results. Along with the channel selection mechanism, both numerical evaluations and experimental results validated the sufficiently high classification accuracies of the proposed opto-processors for supervising clinical diagnosis. Our study opens a new research direction for utilizing photonic computing techniques to process large-scale EEG signals and promote broader applications.
Wide-angle imaging and spectral detection play vital roles in tasks such as target tracking, object classification, and anti-camouflage. However, limited by their intrinsically different architectures, as determined by frequency dispersion requirements, their simultaneous implementation in a shared-aperture system is difficult. Here, we propose a novel concept to realize reconfigurable dual-mode detection based on electrical-control tunable metasurfaces. As a proof-of-concept demonstration, the simultaneous implementation of wide-angle imaging and polarization-spectral detection in a miniature shared-aperture meta-optical system is realized for the first time via the electrical control of cascaded catenary-like metasurfaces. The proposed system supports the imaging (spectral) resolution of approximately 27.8 line-pairs per millimeter (lp·mm−1; ∼80 nm) for an imaging (spectral) mode from 8 to 14 μm. This system also bears a large field of view of about 70°, enabling multi-target recognition in both modes. This work may promote the miniaturization of multifunctional optical systems, including spectrometers and polarization imagers, and illustrates the potential industrial applications of meta-optics in biomedicine, security, space exploration, and more.
This study proposes an image-based visual servoing (IBVS) method based on a velocity observer for an unmanned aerial vehicle (UAV) for tracking a dynamic target in Global Positioning System (GPS)-denied environments. The proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target. A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is proposed. The depth model ensures image feature accuracy and image trajectory smoothness in rotating target tracking. The relative velocities of the UAV and the dynamic target are estimated using the proposed velocity observer. Thanks to the velocity observer, translational velocity measurements are not required, and the control chatter caused by noise-containing measurements is mitigated. An integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the anti-disturbance ability. The stability of the velocity observer and IBVS controller is analyzed using the Lyapunov method. Comparative simulations and multistage experiments are conducted to illustrate the tracking stability, anti-disturbance ability, and tracking robustness of the proposed method with a dynamic rotating target.
Resonantly enhanced dielectric sensing has superior sensitivity and accuracy because the signal is measured from relative resonance shifts that are immune to signal fluctuations. For applications in the Internet of Things (IoT), accurate detection of resonance frequency shifts using a compact circuit is in high demand. We proposed an ultracompact integrated sensing system that merges a spoof surface plasmon resonance sensor with signal detection, processing, and wireless communication. A software-defined scheme was developed to track the resonance shift, which minimized the hardware circuit and made the detection adaptive to the target resonance. A microwave spoof surface plasmon resonator was designed to enhance sensitivity and resonance intensity. The integrated sensing system was constructed on a printed circuit board with dimensions of 1.8 cm × 1.2 cm and connected to a smartphone wirelessly through Bluetooth, working in both frequency scanning mode and resonance tracking mode and achieving a signal-to-noise ratio of 69 dB in acetone vapor sensing. This study provides an ultracompact, accurate, adaptive, sensitive, and wireless solution for resonant sensors in the IoT.
The purpose of this research was to develop a chitosan sulfobetaine (CS-SNCC) film via the solution-casting method as a biodegradable antibacterial material for biomedical applications. Chitosan and monochloro-triazine sulfobetaine were used as the raw materials for CS-SNCC preparation, and Fourier-transform infrared (FTIR), ultraviolet–visible (UV-Vis), energy-dispersive X-ray (EDX), and X-ray photoelectron spectroscopy (XPS) spectra were used to characterize and analyze the structure of the synthesized CS-SNCC. Furthermore, the swelling property, thermal stability, biodegradability, cytocompatibility, and antibacterial properties of the CS-SNCC film were comprehensively investigated and compared with those of the chitosan film. The results for the film's enzymatic biodegradation behavior show that the CS-SNCC film undergoes a weight loss of 45.54% after 21 days of incubation. In addition, the CS-SNCC film effectively resists bacterial adhesion, prevents the formation of bacteria biofilms, and exhibits high antibacterial activity, with inactivation rates of 93.43% for Escherichia coli and 91.00% for Staphylococcus aureus. Moreover, the CS-SNCC film shows good cellular activity and cytocompatibility according to the cytotoxicity results. Therefore, the prepared biodegradable, cytocompatible, antibacterial, and biofilm-controlling CS-SNCC film has potential for biomedical applications.
Due to their tunable acidity, shape selectivity, and excellent stability, zeolites are of great importance as solid acid materials in industrial catalysis. Tuning the properties of the acid sites in zeolites allows for the rational design and fabrication of catalysts for target reactions. Dimethyl ether (DME) carbonylation, a critical chain-growth reaction for C1 resource utilization, is selectively catalyzed by the Brønsted acid sites within the eight-membered rings (8-MRs) of mordenite (MOR). It is anticipated that strengthening the Brønsted acidity—particularly in 8-MRs—will improve the catalytic performance of MOR. In this work, density functional theory (DFT) calculations are first employed and the results used to design a modified MOR with stannum (Sn) and to predict the corresponding changes in acidity. Guided by the theoretical studies, a series of Sn-modified MOR are synthesized via a defect-engineering and subsequent heteroatom-substitution strategy. After partial desilication, isolated tetrahedral Sn species in an open configuration are successfully synthesized for the first time, within which tetrahedrally coordinated Al sites are preserved. An acidic characterization is used to confirm that the acidity of the Brønsted acid sites is enhanced by the introduction of the Sn species; as a result, the sample exhibits excellent activity in DME carbonylation reaction. Kinetic and DFT studies reveal that this strengthened acidity facilitates the adsorption of DME and reduces the activation barriers of DME dissociation and acetyl formation, accounting for the improved activity. The work demonstrates mechanistic insights into the promoting effects of strong acidity on DME carbonylation and offers a promising strategy to precisely control the acidic strength of zeolites.
The distribution pattern of metals as active centers on a substrate can influence the peroxymonosulfate (PMS) activation and contaminants degradation. Herein, atomic layer deposition is applied to prepare Cu single atom (SA-Cu), cluster (C-Cu), and film (F-Cu) decorated MXene catalysts by regulating the number of deposition cycles. In comparison with SA-Cu-MXene (adsorption energy (Eads) = −4.236 eV) and F-Cu-MXene (Eads = −3.548 eV), PMS is shown to adsorb preferably on the C-Cu-MXene surface for activation (Eads = −5.435 eV), realizing higher utilization efficiency. More SO4·− are generated in C-Cu-MXene/PMS system with steady-state concentration and 1–3 orders of magnitude higher than those in the SA-Cu-MXene and F-Cu-MXene activated PMS systems. Particularly, the contribution of SO4·− oxidation to sulfamethoxazole (SMX) degradation followed the order, C-Cu-MXene (97.3%) > SA-Cu-MXene (90.4%) > F-Cu-MXene (71.9%), realizing the larger SMX degradation rate in the C-Cu-MXene/PMS system with the degradation rate constants (k) at 0.0485 min−1. Additionally, SMX degradation routes in C-Cu-MXene/PMS system are found with fewer toxic intermediates. Through this work, we highlighted the importance of guided design of heterogeneous catalysts in the PMS system. Appropriate metal distribution patterns need to be selected according to the actual water treatment demand. Metal sites could be then fully utilized to produce specific active species to improve the utilization efficiency of the oxidants.
The life-cycle assessment method, which originates from general products and services, has gradually come to be applied to investigations of the life-cycle carbon emissions (LCCE) of buildings. A literature review was conducted to clarify LCCE implications, calculations, and reductions in the context of buildings. A total of 826 global building carbon emission calculation cases were obtained from 161 studies based on the framework of the building life-cycle stage division stipulated by ISO 21930 and the basic principles of the emission factor (EF) approach. The carbon emission calculation methods and results are discussed herein, based on the modules of production, construction, use, end-of-life, and supplementary benefits. According to the hotspot distribution of a building’s carbon emissions, carbon reduction strategies are classified into six groups for technical content and benefits analysis, including reducing the activity data pertaining to building materials and energy, reducing the carbon EFs of the building materials and energy, and exploiting the advantages of supplementary benefits. The research gaps and challenges in current building LCCE studies are summarized in terms of research goals and ideas, calculation methods, basic parameters, and carbon reduction strategies; development suggestions are also proposed.
High-precision and efficient structural response prediction is essential for intelligent disaster prevention and mitigation in building structures, including post-earthquake damage assessment, structural health monitoring, and seismic resilience assessment of buildings. To improve the accuracy and efficiency of structural response prediction, this study proposes a novel physics-informed deep-learning-based real-time structural response prediction method that can predict a large number of nodes in a structure through a data-driven training method and an autoregressive training strategy. The proposed method includes a Phy-Seisformer model that incorporates the physical information of the structure into the model, thereby enabling higher-precision predictions. Experiments were conducted on a four-story masonry structure, an eleven-story reinforced concrete irregular structure, and a twenty-one-story reinforced concrete frame structure to verify the accuracy and efficiency of the proposed method. In addition, the effectiveness of the structure in the Phy-Seisformer model was verified using an ablation study. Furthermore, by conducting a comparative experiment, the impact of the range of seismic wave amplitudes on the prediction accuracy was studied. The experimental results show that the method proposed in this paper can achieve very high accuracy and at least 5000 times faster calculation speed than finite element calculations for different types of building structures.
Flexible thermoelectric materials play an important role in smart wearables, such as wearable power generation, self-powered sensing, and personal thermal management. However, with the rapid development of Internet of Things (IoT) and artificial intelligence (AI), higher standards for comfort, multifunctionality, and sustainable operation of wearable electronics have been proposed, and it remains challenging to meet all the requirements of currently reported thermoelectric devices. Herein, we present a multifunctional, wearable, and wireless sensing system based on a thermoelectric knitted fabric with over 600 mm·s−1 air permeability and a stretchability of 120%. The device coupled with a wireless transmission system realizes self-powered monitoring of human respiration through an mobile phone application (APP). Furthermore, an integrated thermoelectric system was designed to combine photothermal conversion and passive radiative cooling, enabling the characteristics of being powered by solar-driven in-plane temperature differences and monitoring outdoor sunlight intensity through the APP. Additionally, we decoupled the complex signals of resistance and thermal voltage during deformation under solar irradiation based on the anisotropy of the knitted fabrics to enable the device to monitor and optimize the outdoor physical activity of the athlete via the APP. This novel thermoelectric fabric-based wearable and wireless sensing platform has promising applications in next-generation smart textiles.
n-caproate, which is produced via chain elongation (CE) using waste biomass, can supply various fossil-derived products, thus advancing the realization of carbon neutrality. Ammonia released from the degradation of nitrogen-rich waste biomass can act as a nutrient or an inhibitor in anaerobic bioprocesses, including CE, with the distinction being primarily dependent on its concentration. Currently, the optimal concentration of ammonia and the threshold of toxicity for open-culture n-caproate production using ethanol as an electron donor, along with the underlying mechanisms, remain unclear. This study revealed that the optimal concentration of ammonia for n-caproate production was 2 g∙L−1, whereas concentrations exceeding this threshold markedly suppressed the CE performance. Exploration of the mechanism revealed the involvement of two forms of ammonia (i.e., ammonium ions and free ammonia) in this inhibitory behavior. High ammonia levels (5 g∙L−1) induced excessive ethanol oxidation and suppressed the reverse β-oxidation (RBO) process, directly leading to the enhanced activities of enzymes (phosphotransacetylase and acetate kinase) responsible for acetate formation and diminished activities of butyryl-coenzyme A (CoA): acetyl-CoA transferase, caproyl-CoA: butyryl-CoA transferase, and caproyl-CoA: acetyl-CoA transferase that are involved in the syntheses of n-butyrate and n-caproate. Furthermore, the composition of the microbial community shifted from Paraclostridium dominance (at 0.1 g∙L−1 ammonia) to a co-dominance of Fermentimonas, Clostridium sensu stricto 12, and Clostridium sensu stricto 15 at 2 g∙L−1 ammonia. However, these CE-functional bacteria were mostly absent in the presence of excessive ammonia (5 g∙L−1 ammonia). Metagenomic analysis revealed the upregulation of functions such as RBO, fatty acid synthesis, K+ efflux, adenosine triphosphatase (ATPase) metabolism, and metal cation export in the presence of 2 g∙L−1 ammonia, collectively contributing to enhanced n-caproate production. Conversely, the aforementioned functions (excluding metal cation export) and K+ influx were suppressed by excessive ammonia, undermining both ammonia detoxification and n-caproate biosynthesis. The comprehensive elucidation of ammonia-driven mechanisms influencing n-caproate production, as provided in this study, is expected to inspire researchers to devise effective strategies to alleviate ammonia-induced inhibition.
As indispensable parts of greenhouses and plant factories, agricultural covering films play a prominent role in regulating microclimate environments. Polyethylene covering films directly transmit the full solar spectrum. However, this high level of sunlight transmission may be inappropriate or even harmful for crops with specific photothermal requirements. Modern greenhouses are integrated with agricultural covering materials, heating, ventilation, and air conditioning (HVAC) systems, and smart irrigation and communication technologies to maximize planting efficiency. This review provides insight into the photothermal requirements of crops and ways to meet these requirements, including new materials based on passive radiative cooling and light scattering, simulations to evaluate the energy consumption and environmental conditions in a greenhouse, and data mining to identify key biological growth factors and thereby improve new covering films. Finally, future challenges and directions for photothermal-management agricultural films are elaborated on to bridge the gap between lab-scale research and large-scale practical applications.
Light is a fundamental environmental factor for living organisms on earth—not only as a primary energy source but also as an informational signal. In fungi, light can be used as an indicator for both time and space to control important physiological and morphological responses. Botrytis cinerea (B. cinerea) is a devastating phytopathogenic fungus that exploits light cues to optimize virulence and the balance between conidiation and sclerotia development, thereby improving its dispersal and survival in ecosystems. However, the components and mechanisms underlying these processes remain obscure. Here, we identify a novel light-signaling component in B. cinerea, BcCfaS, which encodes a putative cyclopropane fatty-acyl-phospholipid synthase. BcCfaS is strongly induced by light at the transcriptional level and plays a crucial role in regulating photomorphogenesis. Deletion of BcCfaS results in reduced vegetative growth, altered colony morphology, impaired sclerotial development, and enhanced conidiation in a light-dependent manner. Moreover, the mutant exhibits serious defects in stress response and virulence on the host. Based on a lipidomics analysis, a number of previously unknown fungal lipids and many BcCfaS-regulated lipids are identified in B. cinerea, including several novel phospholipids and fatty acids. Importantly, we find that BcCfaS controls conidiation and sclerotial development by positively regulating methyl jasmonate (MeJA) synthesis to activate the transcription of light-signaling components, revealing for the first time the metabolic base of photomorphogenesis in fungi. Thus, we propose that BcCfaS serves as an integration node for light and lipid metabolism, thereby providing a regulatory mechanism by which fungi adapt their development to a changing light environment. These new findings provide an important target for antifungal design to prevent and control fungal disease.
The increasing demand for wastewater treatment has become a notable trend for addressing global water scarcity. However, composite fouling is a significant challenge for wastewater distribution engineering systems. This study provides an approach using nanobubbles (NBs) to control composite fouling. The antifouling capacities of three types of NBs (oxygen, nitrogen, and helium), six oxygen concentrations, and two application procedures (prevention and removal) are investigated. The results show that NBs effectively mitigate composite fouling—including biofouling, inorganic scaling, and particulate fouling—in comparison with the no-NBs group. More specifically, hydroxyl radicals generated by the self-collapse of NBs oxidize organics and kill microorganisms in wastewater. The negatively charged surfaces of the NBs transform the crystalline form of CaCO3 from calcite to looser aragonite, which reduces the likelihood of ion precipitation. Furthermore, the NBs gas-liquid interfaces act as gas "bridges" between colloidal particles, enhancing the removal of particles from wastewater. While oxygen NBs have greater anti-fouling capacity than nitrogen and helium NBs, oxygen NBs at low concentrations (∼5%) increase total fouling. Lastly, although the NBs inhibit the growth of fouling, they do not significantly remove the already adhered fouling in no-NBs treated groups. This study anticipates that the application of NBs will address the significant fouling issue for various wastewater distribution engineering systems in order to meet the global challenge of sustainable water supplies.
There is currently no effective targeted therapeutic strategy for the treatment of central nervous system acute lymphoblastic leukemia (CNS-ALL). Integrin α6 is considered a potential target for CNS-ALL diagnosis and therapy because of its role in promoting CNS-ALL disease progression. The targeted peptide D(RWYD) (abbreviated RD), with nanomolar affinity to integrin α6 was identified by peptide scanning techniques such as alanine scanning, truncation, and D-substitution. Herein, we developed a therapeutic nanoparticle based on the α6-targeted peptide for treating CNS-ALL. The self-assembled proapoptotic nanopeptide D(RWYD)–D(KLAKLAK)2–GD(FFY) (abbreviated RD–KLA–Gffy) contains the α6-targeted peptide RD, the well-known proapoptotic peptide D(KLAKLAK)2 (abbreviated KLA) and the self-assembling tetrapeptide GD(FFY) (abbreviated Gffy). The functional mechanism of RD–KLA–Gffy is clarified using different experiments. Our results demonstrate that RD–KLA–Gffy is highly enriched in CNS-ALL lesions and induces tumor cell apoptosis, thus reducing CNS-ALL disease burden and prolonging the survival of CNS-ALL mice without obvious toxicity. Moreover, the combined use of RD–KLA–Gffy and methotrexate (MTX) shows a potent antitumor effect in treating CNS-ALL, indicating that RD–KLA–Gffy plays an important role in suppressing CNS-ALL progression either as a single agent or in combination with MTX, which shows promise for application in CNS-ALL therapy.
Intestinal homeostasis is maintained by specialized host cells and the gut microbiota. Wnt/β-catenin signaling is essential for gastrointestinal development and homeostasis, and its dysregulation has been implicated in inflammation and colorectal cancer. Axin1 negatively regulates activated Wnt/β-catenin signaling, but little is known regarding its role in regulating host–microbial interactions in health and disease. Here, we aim to demonstrate that intestinal Axin1 determines gut homeostasis and host response to inflammation. Axin1 expression was analyzed in human inflammatory bowel disease datasets. To explore the effects and mechanism of intestinal Axin1 in regulating intestinal homeostasis and colitis, we generated new mouse models with Axin1 conditional knockout in intestinal epithelial cell (IEC; Axin1ΔIEC) and Paneth cell (PC; Axin1ΔPC) to compare with control (Axin1LoxP; LoxP: locus of X-over, P1) mice. We found increased Axin1 expression in the colonic epithelium of human inflammatory bowel disease (IBD). Axin1ΔIEC mice exhibited altered goblet cell spatial distribution, PC morphology, reduced lysozyme expression, and enriched Akkermansia muciniphila (A. muciniphila). The absence of intestinal epithelial and PC Axin1 decreased susceptibility to dextran sulfate sodium-induced colitis in vivo. Axin1ΔIEC and Axin1ΔPC mice became more susceptible to dextran sulfate sodium (DSS)-colitis after cohousing with control mice. Treatment with A. muciniphila reduced DSS-colitis severity. Antibiotic treatment did not change the IEC proliferation in the Axin1Loxp mice. However, the intestinal proliferative cells in Axin1ΔIEC mice with antibiotic treatment were reduced compared with those in Axin1ΔIEC mice without treatment. These data suggest non-colitogenic effects driven by the gut microbiome. In conclusion, we found that the loss of intestinal Axin1 protects against colitis, likely driven by epithelial Axin1 and Axin1-associated A. muciniphila. Our study demonstrates a novel role of Axin1 in mediating intestinal homeostasis and the microbiota. Further mechanistic studies using specific Axin1 mutations elucidating how Axin1 modulates the microbiome and host inflammatory response will provide new therapeutic strategies for human IBD.
Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease without effective treatment. The traditional Chinese medicine formulation Pien Tze Huang (PTH) can suppress inflammatory diseases. Here, we evaluate the effects of PTH on the evolution of NASH and its underlying mechanisms. We found that PTH prevented the development of steatohepatitis induced by various dietary models, including a high-fat high-cholesterol (HFHC) diet, choline-deficient high-fat diet (CD-HFD), and methionine- and choline-deficient (MCD) diet, along with significant suppression of liver injury, hepatic triglyceride, and lipid peroxidation. Moreover, ten days of PTH treatment after the onset of NASH significantly ameliorated MCD diet-induced steatosis and liver injury in mice. Through the metagenomic sequencing of stool samples, we found that PTH administration restored the gut microbiota with enrichment of probiotics including Lactobacillus acidophilus (L. acidophilus), Lactobacillus plantarum, Lactococcus lactis, and Bacillus subtilis. The enriched L. acidophilus prevented MCD diet-induced steatohepatitis. In addition, PTH restored the gut barrier function in mice with steatohepatitis, as evidenced by reduced intestinal permeability, decreased serum lipopolysaccharides (LPS) level, and increased epithelial tight-junction protein E-cadherin expression. Our metabolomic analysis via liquid chromatography-mass spectrometry profiling identified the alteration in the metabolism of bile acids in the portal vein of PTH-treated mice. We further confirmed that an intact gut microbiota is necessary for PTH to exhibit anti-steatohepatitis effects. In conclusion, PTH protects against steatohepatitis development by modulating the gut microbiota and metabolites. PTH is a potential promising prophylactic and therapeutic option for patients with NASH.