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BackgroundHepatic encephalopathy (HE) is a neurological disorder resulting from advanced liver injury. HE has a high mortality rate and poor prognosis. The pathogenesis of HE is still unclear, which has led to the lack of a satisfactory specific treatment method. There is increasing evidence that the intestinal flora affects the communication between the gut and the brain in the pathogenesis of HE. Adjusting the intestinal flora has had a beneficial effect on HE in recent studies, and the Qingchang Ligan formula (QCLG) has been shown in previous studies to regulate intestinal flora and metabolites. In this study, we established a thioacetamide-induced HE mouse model to evaluate the protective effect of QCLG on HE and explore its potential mechanism, which also demonstrated that intestinal flora dysbiosis is involved in the pathogenesis of HE.MethodsMice were intraperitoneally injected with thioacetamide (TAA, 150 mg/kg) to induce HE. Additionally, they were orally administered Qingchang Ligan Formula (QCLG) at a dose of 6.725 g/kg·d for seven days, while control mice received an equal volume of saline via gavage. Subsequently, samples were subjected to 16S ribosomal ribonucleic acid (rRNA) gene sequencing, high-performance liquid chromatography-mass spectrometry (LC-MS), and RNA-sequencing (RNA-seq) analysis.ResultQCLG improved weight loss, cognitive impairment, neurological function scores, blood ammonia, and brain gene expression of interleukin-6 (TNF-α), Interleukin-1β (IL-1β), and interleukin-6 (IL-6) induced by HE. Moreover, QCLG increased the levels of liver function indicators, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), and serum TNF-α, IL-1β, and IL-6. 16S RNA sequencing revealed increased Oscillibacter, Colidextribacter, and Helicobacter in TAA-induced mouse fecal samples. Also, the abundance of Bifidobacterium decreases TAA-induced mouse fecal samples. In contrast, QCLG treatment significantly restored the gut microbial community. Metabolomics indicated significant differences in some metabolites among the normal control, treatment, and model groups, including 5-methoxytryptophan, Daidzein, Stercobilin, and Plumieride (PLU).ConclusionQCLG can alleviate neuroinflammation and prevent HE caused by liver injury by regulating intestinal flora in mouse models.

As a water-saving method, moistube irrigation has been widely used. To ensure the effectiveness of moistube irrigation the development of an infiltration prediction model under moistube irrigation based on the interaction of multiple factors is required. In this paper, soil water infiltration tests with different bulk densities (1.2 g/cm³, 1.3 g/cm³, and 1.4 g/cm³) and textures (loamy sand, sandy loam, and clay loam) under different pressure heads (1m, 1.5m, and 2m) were designed, and the test data were analyzed by gray correlation theory. The pressure head, bulk density, clay content, silt content, sand content, and initial water content were determined as input variables, and the model structure was composed with two parameters of Kostiakov's model as output variables. Then, the genetic algorithm was used to optimize the back propagation neural network and the particle swarm algorithm to optimize the support vector machine. The soil moisture prediction model under moistube irrigation was established, finally the model was compared and analyzed. The results showed that the consistency effect of the two models was good. However, compared with the BP neural network prediction model optimized by genetic algorithm, the particle swarm algorithm optimized the support vector machine based moistube irrigation prediction model had higher accuracy. The results of this experiment can provide theoretical support for the exploration and modelling prediction of soil water infiltration under moistube irrigation.

The Black–Scholes formula is an important formula for pricing a contingent claim in complete financial markets. This formula can be obtained under the assumption that the investor’s strategy is carried out according to a self-financing criterion; hence, there arise a set of self-financing portfolios corresponding to different contingent claims. The natural questions are: If an investor invests according to self-financing portfolios in the financial market, what are the maximal and minimal distributions of the investor’s wealth on some specific interval at the terminal time? Furthermore, if such distributions exist, how can the corresponding optimal portfolios be constructed? The present study applies the theory of backward stochastic differential equations in order to obtain an affirmative answer to the above questions. That is, the explicit formulations for the maximal and minimal distributions of wealth when adopting self-financing strategies would be derived, and the corresponding optimal (self-financing) portfolios would be constructed. Furthermore, this would verify the benefits of diversified portfolios in financial markets: that is, do not put all your eggs in the same basket.

We propose and demonstrate a curvature sensor based on long-period fiber grating (LPFG) with asymmetric index modulation. The LPFG is fabricated in single-mode fiber with femtosecond laser micromachining. The grating structure is not introduced in the central fiber core, but is located off-axis with a distance of a few micrometers. Experimental results indicate that the offset distance has direct influence on the grating spectra. By utilizing such an asymmetric structure, two-dimensional vector curvature sensing can be realized. For an LPFG with an offset distance of 6 μm, the curvature sensitivity is around 29 nm/m−1 in the 0° and 180° direction and about 20 nm/m−1 in the 90° and 270° direction. The difference in curvature sensitivity in different bending directions makes the sensor capable of distinguishing the curvature orientation. The temperature response of the sensor is also experimentally investigated, and results indicate that the sensor has a very low temperature cross-sensitivity of 0.003 m−1/°C. The characteristics of high curvature sensitivity, two-dimensional bending direction identification, and compact structure make the device an ideal candidate to be applied in the field of power grid health monitoring and intelligent robotics.

A high-intensity muon source driven by a continuous-wave superconducting linac holds the potential to significantly advance the intensity frontier of muon sources. Alongside advancements in accelerator technologies, breakthroughs in muon production target and collection schemes are essential. After a brief introduction to the development of the accelerator-driven system superconducting linac, a novel muon production target is proposed, utilizing a free-surface liquid lithium jet capable of handling the heat power generated by a proton beam with an energy of 600 MeV and a current of 5 mA. It is predicted by our simulation studies that the lithium target is more efficient in surface muon production compared to the rotating graphite target. The parameter space of the front end consisting of a lithium target and a large-aperture capture solenoid is explored, from the perspective of production efficiency, capture efficiency, and characteristics of the surface muon beam.

A comparison study was conducted on the performance of the Ag2CO3 visible light catalysts synthesized in a surfactant-free microemulsion (SFME), water and water/propan-2-ol mixture, respectively. The XPS spectra show that all the synthesized Ag2CO3 products have good purity. The SEM, XRD, BET and DRS characterizations indicate that the Ag2CO3 product synthesized in the SFME template has higher crystallinity, more regular morphology, more uniform size, larger specific surface area, and stronger visible light absorption performance, thus having better catalytic photodegradation activity for rhodamine B (RhB), methylene blue (MB) and methyl orange (MO). When the degradation time reaches 45 min, the degradation rate of RhB is as high as 99.11 %. Na2CO3 has a good stabilizing effect when its concentration is 0.001 mol L−1. This research is of great significance to expand the application of SFMEs in the synthesis of high-efficiency catalytic materials.

The gastric mucosal immune system is a unique immune organ independent of systemic immunity that not only maintains nutrient absorption but also plays a role in resisting the external environment. Gastric mucosal immune disorder leads to a series of gastric mucosal diseases, including autoimmune gastritis (AIG)-related diseases, Helicobacter pylori (H. pylori)-induced diseases, and various types of gastric cancer (GC). Therefore, understanding the role of gastric mucosal immune homeostasis in gastric mucosal protection and the relationship between mucosal immunity and gastric mucosal diseases is very important. This review focuses on the protective effect of gastric mucosal immune homeostasis on the gastric mucosa, as well as multiple gastric mucosal diseases caused by gastric immune disorders. We hope to offer new prospects for the prevention and treatment of gastric mucosal diseases.

CYP 3A4 and CYP 3A5 are two important members of the human cytochrome P450 family. Although their overall structures are similar, the local structures of the active site are different, which directly leads to obvious individual differences in drug metabolic efficacy and toxicity. In this work, midazolam (MDZ) was selected as the probe substrate, and its interaction with two proteins, CYP 3A4 and CYP 3A5, was studied by molecular dynamics simulation (MD) along with the calculation of the binding free energy. The results show that two protein–substrate complexes have some similarities in enzyme–substrate binding; that is, in both complexes, Ser119 forms a high occupancy hydrogen bond with MDZ, which plays a key role in the stability of the interaction between MDZ and the enzymes. However, the complex formed by CYP 3A4 and MDZ is more stable, which may be attributed to the sandwich structure formed by the fluorophenyl group of the substrate with Leu216 and Leu482. Our study interprets the binding differences between two isoform–substrate complexes and reveals a structure–function relationship from the atomic perspective, which is expected to provide a theoretical basis for accurately measuring the effectiveness and toxicity of drugs for individuals in the era of precision medicine.

Abstract Background Sheath blight is an important disease caused by Rhizoctonia cerealis that affects wheat yields worldwide. No wheat varieties have been identified with high resistance or immunity to sheath blight. Understanding the sheath blight resistance mechanism is essential for controlling this disease. In this study, we investigated the response of wheat to Rhizoctonia cerealis infection by analyzing the cytological changes and transcriptomes of common wheat 7182 with moderate sensitivity to sheath blight and H83 with moderate resistance. Results The cytological observation showed that the growth of Rhizoctonia cerealis on the surface and its expansion inside the leaf sheath tissue were more rapid in the susceptible material. According to the transcriptome sequencing results, a total of 88685 genes were identified in both materials, including 20156 differentially expressed genes (DEGs) of which 12087 was upregulated genes and 8069 was downregulated genes. At 36 h post-inoculation, compared with the uninfected control, 11498 DEGs were identified in resistant materials, with 5064 downregulated genes and 6434 upregulated genes, and 13058 genes were detected in susceptible materials, with 6759 downregulated genes and 6299 upregulated genes. At 72 h post-inoculation, compared with the uninfected control, 6578 DEGs were detected in resistant materials, with 2991 downregulated genes and 3587 upregulated genes, and 7324 genes were detected in susceptible materials, with 4119 downregulated genes and 3205 upregulated genes. Functional annotation and enrichment analysis showed that the main pathways enriched for the DEGs included biosynthesis of secondary metabolites, carbon metabolism, plant hormone signal transduction, and plant–pathogen interaction. In particular, phenylpropane biosynthesis pathway is specifically activated in resistant variety H83 after infection. Many DEGs also belonged to the MYB, AP2, NAC, and WRKY transcription factor families. Conclusions Thus, we suggest that the normal functioning of plant signaling pathways and differences in the expression of key genes and transcription factors in some important metabolic pathways may be important for defending wheat against sheath blight. These findings may facilitate further exploration of the sheath blight resistance mechanism in wheat and the cloning of related genes.

A high sensitivity temperature sensor based on polymer and liquid modified anti-resonant reflection principle is proposed. The sensor is made of a section of liquid-filled and UV-curable adhesive coated silica capillary, sandwiched between single mode fibers. The guiding mechanism of the waveguide is affected by both the liquid inside the hollow core, and the adhesive outside the silica cladding. The location of the resonant dips are influenced by the refractive index (RI) of the liquid, while the fringe visibility (resonant strength) is tuned by the both the liquid and the adhesive. By carefully selecting the refractive index value of the infiltrated liquid, and controlling the curing time of the adhesive, sharp resonant dips can be obtained. The sensor exhibits very high temperature sensitivity against temperature. A high sensitivity of 3.369 nm/°C is achieved with an infiltration index of 1.39, in the temperature range from 25 °C to 60 °C. The detection limit of the proposed sensors are 0.04 °C. Moreover, the temperature sensitivity of the sensor is found to be decreasing with the order of resonance. The sensor is easy to fabricate and cost effective, and is applicable in both dry and wet environments, which can find wide applications in biochemical and pharmaceutical industry.

Abstract Background Olsenella uli is anaerobic or microaerophilic bacteria, commonly found in oral cavity or gastrointestinal tract, which has not been reported to be associated with lower respiratory tract infection. Herein, we report the first case of Olsenella uli infection in the lung. Case presentation A 70-year-old male farmer with no history of other respiratory tract diseases developed a cough with bloody sputum three times a day without obvious causes or other concomitant symptoms. After a period of treatment with empirical antibiotic, his condition did not improve. The computed tomography (CT) and lung biopsy results indicated bilateral pneumonia, and Olsenella uli was identified by micromorphology, sequence analysis and mass spectrometry analysis recovered from sputum. Ceftazidime, a third generation cephalosporin was used for the treatment, and the patient recovered after 10 days. Conclusions Our report suggests a causative role of gingival bacteria in the pathogenesis of pneumonia, thus early diagnosis and prompt antibiotic therapy may play a role in the treatment of Olsenella uli induced pneumonia.

BackgroundRhubarb is an important traditional Chinese medicine, and rhein is one of its most important active ingredients. Studies have found that rhein can improve ulcerative colitis by regulating gut microbes, but there are few reports on its effects on liver diseases. Therefore, this study aims to investigate these effects and underlying mechanisms.MethodsMice were given rhein (100 mg/kg), with both a normal control group and a model group receiving the same amount of normal saline for one week. Acute liver injury was induced in mice by intraperitoneal injection of D-GalN (800 mg/kg)/LPS (10 ug/kg). Samples (blood, liver, and stool) were then collected and assessed for histological lesions and used for 16S rRNA gene sequencing, high-performance liquid chromatography-mass spectrometry (LC-MS) and RNA-seq analysis.ResultsThe levels of ALT and AST in the Model group were abnormal higher compared to the normal control group, and the levels of ALT and AST were significantly relieved in the rhein group. Hepatic HE staining showed that the degree of liver injury in the rhein group was lighter than that in the model group, and microbiological results showed that norank_o:Clostridia_UCG-014, Lachnoclostridium, and Roseburia were more abundant in the model group compared to the normal control group. Notably, the rhein treatment group showed reshaped disturbance of intestinal microbial community by D-GalN/LPS and these mice also had higher levels of Verrucomicrobia, Akkermansiaceae and Bacteroidetes. Additionally, There were multiple metabolites that were significantly different between the normal control group and the model group, such as L-α-amino acid, ofloxacin-N-oxide, 1-hydroxy-1,3-diphenylpropan-2-one,and L-4-hydroxyglutamate semialdehyde, but that returned to normal levels after rhein treatment. The gene expression level in the model group also changed significantly, various genes such as Cxcl2, S100a9, Tnf, Ereg, and IL-10 were up-regulated, while Mfsd2a and Bhlhe41 were down-regulated, which were recovered after rhein treatment.ConclusionOverall, our results show that rhein alleviated D-GalN/LPS-induced acute liver injury in mice. It may help modulate gut microbiota in mice, thereby changing metabolism in the intestine. Meanwhile, rhein also may help regulate genes expression level to alleviate D-GalN/LPS-induced acute liver injury.

Abstract Background Genome-wide association studies (GWAS) that link genotype to phenotype represent an effective means to associate an individual genetic background with a disease or trait. However, single-omics data only provide limited information on biological mechanisms, and it is necessary to improve the accuracy for predicting the biological association between genotype and phenotype by integrating multi-omics data. Typically, gene expression data are integrated to analyze the effect of single nucleotide polymorphisms (SNPs) on phenotype. Such multi-omics data integration mainly follows two approaches: multi-staged analysis and meta-dimensional analysis, which respectively ignore intra-omics and inter-omics associations. Moreover, both approaches require omics data from a single sample set, and the large feature set of SNPs necessitates a large sample size for model establishment, but it is difficult to obtain multi-omics data from a single, large sample set. Results To address this problem, we propose a method of genotype-phenotype association based on multi-omics data from small samples. The workflow of this method includes clustering genes using a protein-protein interaction network and gene expression data, screening gene clusters with group lasso, obtaining SNP clusters corresponding to the selected gene clusters through expression quantitative trait locus data, integrating SNP clusters and corresponding gene clusters and phenotypes into three-layer network blocks, analyzing and predicting based on each block, and obtaining the final prediction by taking the average. Conclusions We compare this method to others using two datasets and find that our method shows better results in both cases. Our method can effectively solve the prediction problem in multi-omics data of small sample, and provide valuable resources for further studies on the fusion of more omics data.

Carbamazepine (CBZ), a commonly prescribed antiepileptic drug, in human liver, is mainly metabolized by two isoforms of cytochrome P450 (CYP), CYP3A4 and CYP3A5. Therefore, the binding of CBZ with these two enzymes plays crucial role in the biotransformation of the drug into its active metabolite. In the present work, classical molecular dynamics (MD) simulation was used to investigate the detailed interaction mechanism between CBZ and these two CYP isoforms at the atomic level. The results revealed that although CBZ can bind with the two proteins, all kinds of the interactions, including hydrogen bonds, salt bridges, hydrophobic interaction, and π-π interaction, are isoform specific. The specificity directly leads to a binding environment difference at the active sites of the two isoforms, as represented by the electrostatic surface potential maps, which further results in the varied dynamic behavior of CBZ in the two isoforms. Our research will help to deepen the understanding of the physiological functions of CYP isoforms and opens the door for the rational design and development of isoform-specific inhibitors.

Long non-coding RNAs (lncRNAs) play critical roles in cancer through gene expression and immune regulation. Identifying immune-related lncRNA (irlncRNA) characteristics would contribute to dissecting the mechanism of cancer pathogenesis. Some computational methods have been proposed to identify irlncRNA characteristics in human cancers, but most of them are aimed at identifying irlncRNA characteristics in specific cancer. Here, we proposed a new method, ImReLnc, to recognize irlncRNA characteristics for 33 human cancers and predict the pathogenicity levels of these irlncRNAs across cancer types. We first calculated the heuristic correlation coefficient between lncRNAs and mRNAs for immune-related enrichment analysis. Especially, we analyzed the relationship between lncRNAs and 17 immune-related pathways in 33 cancers to recognize the irlncRNA characteristics of each cancer. Then, we calculated the Pscore of the irlncRNA characteristics to evaluate their pathogenicity levels. The results showed that highly pathogenic irlncRNAs appeared in a higher proportion of known disease databases and had a significant prognostic effect on cancer. In addition, it was found that the expression of irlncRNAs in immune cells was higher than that of non-irlncRNAs, and the proportion of irlncRNAs related to the levels of immune infiltration was much higher than that of non-irlncRNAs. Overall, ImReLnc accurately identified the irlncRNA characteristics in multiple cancers based on the heuristic correlation coefficient. More importantly, ImReLnc effectively evaluated the pathogenicity levels of irlncRNAs across cancer types. ImReLnc is freely available at https://github.com/meihonggao/ImReLnc.

The Qingchangligan formula (QCLGF) is a traditional Chinese medicine that has significant clinical potential for patients with acute liver failure (ALF). However, the experimental evidence of the effect of QCLGF on ALF and the associated mechanisms remain elusive. We aimed to evaluate the function of QCLGF in ALF and the underlying mechanism. ALF was induced in rats by intraperitoneal injection of D-GalN (1100 mg/kg). The Qingchangligan formula was administered to the rats (6.725 g/kg · d) for 5 days, and the model group and the control group were given the same amount of physiological saline. Then 16S rRNA gene sequencing, high performance gas chromatography-mass spectrometry (GC-MS), and RNA-seq analysis were performed on the samples. The levels of ALT and AST in the ALF rats were abnormal (5322.08 ± 566.27 U/L and 7655.95 ± 1238.08 U/L, respectively) compared with the normal control (98.98 ± 6.90 U/L and 99.63 ± 10.94 U/L, respectively). The levels of ALT and AST in the QCLGF rats (2997.67 ± 469.24 U/L and 4158.40 ± 596.07 U/L, respectively) were closer the normal control group. Liver HE staining showed that the degree of liver damage in the QCLGF rats was lighter than that in the ALF rats. The overall structure of the gut microbiota after ALF was significantly altered, including Proteobacteria, Blautia, Romboutsia, Parabacteroides, UCG-008, Parasutterella, Ruminococcus, norank_f:Lachnospiraceae, the Eubacterium_xylanophilum_group, Oscillibacter, and Eisenbergiella. QCLGF balanced the structure and abundance of intestinal flora. The levels of D(+)galactose, isopropyl beta-D-1-thiogalactopyranoside and D-mannitol were lighter in the plasma of the ALF rats than in the normal control rats, but there were significantly elevated levels of those metabolites in the QCLGF rats. The gene expression changed significantly in the ALF rats. QCLGF regulated the expression of THBS1 and the KEGG pathways of carbohydrate metabolism, lipid metabolism, signal transduction, the immune system, and infectious disease: bacterial. QCLGF may alleviating intestinal flora disorder, regulating galactose metabolism and downregulating the expression of THBS1 to alleviate D-GalN induced acute liver failure.

This paper explores whether mathematical education has effects on brain development from the perspective of brain MRIs. While biochemical changes in the left middle front gyrus region of the brain have been investigated, we proposed to classify students by using MRIs from the intraparietal sulcus (IPS) region that was left untouched in the previous study. On the cropped IPS regions, the proposed model developed popular contrastive learning (CL) to solve the problem of multi-instance representation learning. The resulted data representations were then fed into a linear neural network to identify whether students were in the math group or the non-math group. Experiments were conducted on 123 adolescent students, including 72 math students and 51 non-math students. The proposed model achieved an accuracy of 90.24 % for student classification, gaining more than 5% improvements compared to the classical CL frame. Our study provides not only a multi-instance extension to CL and but also an MRI insight into the impact of mathematical studying on brain development.

miR-34, whose mimic was used on phase I clinical trial, has been extensively reported since its dysfunction in various cancers including non-small-cell lung cancer (NSCLC). However, the roles of miR-34 family members in the progression of lung squamous carcinoma (SCC) in patients who have occupational-exposure experience are unclear yet. Here, we comprehensively investigated the expression levels of miR-34 family members in SCC patients and compared the roles of them in SCC in vitro and vivo. The results showed that the average levels of miR-34a and miR-34b/c were decreased in patients. The analysis of miR-34a to miR-34b/c levels in patients graded different stages or metastases or recurrence showed that miR-34b/c was reduced earlier and more significantly than miR-34a. In vitro assays demonstrated that both miR-34a and miR-34b/c inhibits SCC cells proliferation, migration and invasion via Notch1 pathway, while miR-34b/c effects more than miR-34a does. As miR-34a was significantly decreased in cancer recurrence, the further analysis of relationship between miR-34a and stem cell adhesion molecular CD44 showed that miR-34a was significantly correlated with CD44 levels in patients. Knockdown of CD44 significantly blocked miR-34a mediated inhibition of cell migration and invasion. Treating the purified CD44hi cells with miR-34 overexpression lentivirus inhibited the tumor outgrowth. By contrast, anti-miR-34 facilitated tumor development of CD44low cells. Our study showed that miR-34 family members are negative regulator for SCC development, even though the inhibition is mediated by multiple and complicated signal pathways, which provides theoretical basis for SCC treatment and a biomarker candidate for SCC prognosis.

In current research processes, mathematical learning has significantly impacted the brain’s plasticity and cognitive functions. While biochemical changes in brain have been investigated by magnetic resonance spectroscopy, our study attempts to identify non-math students by using magnetic resonance imaging scans (MRIs). The proposed method crops the left middle front gyrus (MFG) region from the MRI, resulting in a multi-instance classification problem. Then, subspace enhanced contrastive learning is employed on all instances to learn robust deep features, followed by an ensemble classifier based on multiple-layer-perceptron models for student identification. The experiments were conducted on 123 MRIs taken from 72 math students and 51 non-math students. The proposed method arrived at an accuracy of 73.7% for image classification and 91.8% for student classification. Results show the proposed workflow successfully identifies the students who lack mathematical education by using MRI data. This study provides insights into the impact of mathematical education on brain development from structural imaging.

The enzymes in the chalcone synthase family, also known as type-III polyketide synthases (PKSs), play important roles in the biosynthesis of various plant secondary metabolites and plant adaptation to environmental stresses. There have been few detailed reports regarding the gene and tissue expression profiles of the PKS (TaPKS) family members in wheat (Triticum aestivum L.). In this study, 81 candidate TaPKS genes were identified in the wheat genome, which were designated as TaPKS1–81. Phylogenetic analysis divided the TaPKS genes into two groups. TaPKS gene family expansion mainly occurred via tandem duplication and fragment duplication. In addition, we analyzed the physical and chemical properties, gene structures, and cis-acting elements of TaPKS gene family members. RNA-seq analysis showed that the expression of TaPKS genes was tissue-specific, and their expression levels differed before and after infection with Rhizoctonia cerealis. The expression levels of four TaPKS genes were also analyzed via qRT-PCR after treatment with methyl jasmonate, salicylic acid, abscisic acid, and ethylene. In the present study, we systematically identified and analyzed TaPKS gene family members in wheat, and our findings may facilitate the cloning of candidate genes associated with resistance to sheath blight in wheat.

Abstract Sodium taurocholate cotransporting polypeptide (NTCP) is a functional receptor for hepatitis B virus (HBV) entry. However, little is known regarding whether NTCP is involved in regulating the postentry steps of the HBV life cycle. Here, we found that NTCP expression upregulated HBV transcription at the postentry step and that the NTCP-targeting entry inhibitor Myrcludex B (MyrB) effectively suppressed HBV transcription both in an HBV in vitro infection system and in mice hydrodynamically injected with an HBV expression plasmid. Mechanistically, NTCP upregulated HBV transcription via farnesoid X receptor α (FxRα)-mediated activation of the HBV EN2/core promoter at the postentry step in a manner that was dependent on the bile acid (BA)-transport function of NTCP, which was blocked by MyrB. Our findings uncover a novel role for NTCP in the HBV life cycle and provide a reference for the use of novel NTCP-targeting entry inhibitors to suppress HBV infection and replication.