Nonalcoholic fatty liver disease (NAFLD) is a common chronic liver disease worldwide. Osteocalcin plays an important role in energy metabolism. In this study, we investigated the mechanism of action of chemically synthesized osteocalcin (csOCN) in ameliorating NAFLD. We demonstrated for the first time that csOCN attenuates lipid accumulation in the liver and hepatocytes by modulating CD36 protein expression. In addition, we found that the expression of p-AMPK, FOXO1 and BCL6 decreased and the expression of CD36 increased after OA/PA induction compared to the control group, and these effects were reversed by the addition of csOCN. In contrast, the therapeutic effect of csOCN was inhibited by the addition of AMPK inhibitors and BCL6 inhibitors. This finding suggested that csOCN regulates CD36 expression via the AMPK-FOXO1/BCL6 axis. In NAFLD mice, oral administration of csOCN also activated the AMPK pathway and reduced CD36 expression. Molecular docking revealed that osteocalcin has a docking site with CD36. Compared to oleic acid and palmitic acid, osteocalcin bound more strongly to CD36. Laser confocal microscopy results showed that osteocalcin colocalized with CD36 at the cell membrane. In conclusion, we demonstrated the regulatory role of csOCN in fatty acid uptake pathways for the first time; it regulates CD36 expression via the AMPK-FOXO1/BCL6 axis to reduce fatty acid uptake, and it affects fatty acid transport by may directly binding to CD36. There are indications that csOCN has potential as a CD36-targeted drug for the treatment of NAFLD.

UNASSIGNED: Nonalcoholic fatty liver disease (NAFLD) is recognized as one of the most common chronic liver diseases worldwide. This study aims to assess the efficacy of automated machine learning (AutoML) in the identification of NAFLD using a population-based cross-sectional database.
UNASSIGNED: All data, including laboratory examinations, anthropometric measurements, and demographic variables, were obtained from the National Health and Nutrition Examination Survey (NHANES). NAFLD was defined by controlled attenuation parameter (CAP) in liver transient ultrasound elastography. The least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection. Six algorithms were utilized on the H2O-automated machine learning platform: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), eXtreme Gradient Boosting (XGBoost), and Deep Learning (DL). These algorithms were selected for their diverse strengths, including their ability to handle complex, non-linear relationships, provide high predictive accuracy, and ensure interpretability. The models were evaluated by area under receiver operating characteristic curves (AUC) and interpreted by the calibration curve, the decision curve analysis, variable importance plot, SHapley Additive exPlanation plot, partial dependence plots, and local interpretable model agnostic explanation plot.
UNASSIGNED: A total of 4177 participants (non-NAFLD 3167 vs NAFLD 1010) were included to develop and validate the AutoML models. The model developed by XGBoost performed better than other models in AutoML, achieving an AUC of 0.859, an accuracy of 0.795, a sensitivity of 0.773, and a specificity of 0.802 on the validation set.
UNASSIGNED: We developed an XGBoost model to better evaluate the presence of NAFLD. Based on the XGBoost model, we created an R Shiny web-based application named Shiny NAFLD (http://39.101.122.171:3838/App2/). This application demonstrates the potential of AutoML in clinical research and practice, offering a promising tool for the real-world identification of NAFLD.

Gut microbiota acts as a critical regulator in the development of nonalcoholic fatty liver disease (NAFLD), making probiotics a promise therapeutic strategy. Studies are needed to identify beneficial Bacteroides strains against NAFLD. Bacteroides ovatus (B. ovatus) may also exhibit therapy effect on NAFLD. The aim of this work was to evaluate the effect of B. ovatus on NAFLD and examine the mechanism. C57BL/6 J male mice were randomly divided into three groups: a control group (NCD) that received control standard diet, a model group (M) with high-fat and high-cholesterol (HFHC) diet, and M_Bo group that was fed HFFC supplemented with B. ovatus. Treatment with B. ovatus could reduce body weight, prevent hepatic steatohepatitis and liver injury. Mechanistically, B. ovatus induced changes of gut microbial diversity and composition, characterized by a decreased Firmicutes/Bacteroidetes (F/B) ratio in M_Bo group mice, a lower abundance of Proteobacteria, Verrucomicrobiota at phylum level and Ruminococcus_torques_group, Ruminococcus_gauvreauii_group, Erysipelatoclostridium at genus level, simultaneously a remarkablely higher fecal abundance of Lachnospiraceae_NK4A136_group, norank_f__Oscillospiraceae, Colidextribacter. Compared with M group, mice treated with B. ovatus showed an markedly altered fecal short chain fatty acids (SCFAs), a decline in serum levels of lipopolysaccharide (LPS), CD163, IL-1β, TNF-α, reduced macrophages in livers. Additionally, B. ovatus treatment caused downregulation of genes involved in denovo lipogenesis (such as Srebfl, Acaca, Scd1, Fasn), which was accompanied by the upregulation of genes related with fatty acid oxidation (such as Ppara). In conclusion, this study provides evidence that B. ovatus could ameliorate NAFLD by modulating the gut-liver axis.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) may contribute to osteoporosis. Berberine is a traditional Chinese medicine and was recently shown to be beneficial in NAFLD. However, little is known about its impact on bone loss induced by NAFLD.
OBJECTIVE: We aimed to explore the role of berberine in bone loss and determine its underlying mechanisms in NAFLD.
METHODS: C57BL/6 mice were fed a high-fat high-fructose high-glucose diet (HFFGD) for 16 weeks to establish a NAFLD mouse model. The mice were administered berberine (300 mg/kg/d) by gavage, and fatty liver levels and bone loss indicators were tested.
RESULTS: Berberine significantly improved HFFGD-induced weight gain, hepatic lipid accumulation and increases in serum liver enzymes, thereby alleviating NAFLD. Berberine increased trabecular number (Tb. N), trabecular thickness (Tb. Th), bone volume to tissue volume ratio (BV/TV), and decreased trabecular separation (Tb. Sp) and restored bone loss in NAFLD. Mechanistically, berberine significantly inhibited ferroptosis and 4-hydroxynonenal (4-HNE), prostaglandin-endoperoxide synthase 2 (PTGS2), and transferrin (TF) levels and increased ferritin heavy chain (FTH) levels in the femurs of HFFGD-fed mice. Moreover, berberine also activated the solute carrier family 7 member 11 (SLC7A11)/glutathione (GSH)/glutathione peroxidase 4 (GPX4) signaling pathway.
CONCLUSIONS: Berberine significantly ameliorates bone loss induced by NAFLD by activating the SLC7A11/GSH/GPX4 signaling pathway and inhibiting ferroptosis. Therefore, berberine may serve as a therapeutic agent for NAFLD-induced bone loss.

BACKGROUND: Fatty liver disease (FLD) poses a significant global health concern worldwide, with its classification into nonalcoholic fatty liver disease (NAFLD) and alcoholic fatty liver disease (AFLD) contingent upon the presence or absence of chronic and excessive alcohol consumption. The absence of specific therapeutic interventions tailored to FLD at various stages of the disease renders its treatment exceptionally arduous. Despite the fact that FLD and hyperlipidemia are intimately associated, there is still debate over how lipid-lowering medications affect FLD. Proprotein Convertase Subtilisin/ Kexin type 9 (PCSK9) is a serine protease predominantly synthesized in the liver, which has a crucial impact on cholesterol homeostasis. Research has confirmed that PCSK9 inhibitors have prominent lipid-lowering properties and substantial clinical effectiveness, thereby justifying the need for additional exploration of their potential role in FLD.
OBJECTIVE: Through a comprehensive literature search, this review is to identify the relationship and related mechanisms between PCSK9, lipid metabolism and FLD. Additionally, it will assess the pharmacological mechanism and applicability of PCSK9 inhibitors (including naturally occurring PCSK9 inhibitors, such as conventional herbal medicines) for the treatment of FLD and serve as a guide for updating the treatment protocol for such conditions.
METHODS: A comprehensive literature search was conducted using several electronic databases, including Pubmed, Medline, Embase, CNKI, Wanfang database and ClinicalTrials.gov, from the inception of the database to 30 Jan 2024. Key words used in the literature search were \"fatty liver\", \"hepatic steatosis\", \"PCSK9\", \"traditional Chinese medicine\", \"herb medicine\", \"botanical medicine\", \"clinical trial\", \"vivo\", \"vitro\", linked with AND/OR. Most of the included studies were within five years.
RESULTS: PCSK9 participates in the regulation of circulating lipids via both LDLR dependent and independent pathways, and there is a potential association with de novo lipogenesis. Major clinical studies have demonstrated a positive correlation between circulating PCSK9 levels and the severity of NAFLD, with elevated levels of circulating PCSK9 observed in individuals exposed to chronic alcohol. Numerous studies have demonstrated the potential of PCSK9 inhibitors to ameliorate non-alcoholic steatohepatitis (NASH), potentially completely alleviate liver steatosis, and diminish liver impairment. In animal experiments, PCSK9 inhibitors have exhibited efficacy in alleviating alcoholic induced liver lipid accumulation and hepatitis. Traditional Chinese medicine such as berberine, curcumin, resveratrol, piceatannol, sauchinone, lupin, quercetin, salidroside, ginkgolide, tanshinone, lunasin, Capsella bursa-pastoris, gypenosides, and Morus alba leaves are the main natural PCS9 inhibitors. Excitingly, by inhibiting transcription, reducing secretion, direct targeting and other pathways, traditional Chinese medicine exert inhibitory effects on PCSK9, thereby exerting potential FLD therapeutic effects.
CONCLUSIONS: PCSK9 plays an important role in the development of FLD, and PCSK9 inhibitors have demonstrated beneficial effects on lipid regulation and FLD in both preclinical and clinical studies. In addition, some traditional Chinese medicines have improved the disease progression of FLD by inhibiting PCSK9 and anti-inflammatory and antioxidant effects. Consequently, the inhibition of PCSK9 appears to be a promising therapeutic strategy for FLD.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. With an increasing number of patients, NAFLD has been identified as a risk factor for Hepatocellular Carcinoma (HCC). The precise pathophysiology of NAFLD-related HCC has not been completely understood recently.
OBJECTIVE: We analyzed the hub genes related to NAFLD and HCC to predict the risk of NAFLD progressing to HCC.
METHODS: Two datasets of NAFLD were used to identify differentially expressed genes. Lasso-Cox regression analysis was performed to determine a gene model to predict the risk of the progression from NAFLD to HCC. Three validation datasets were analyzed to evaluate the performance of the gene model, including normal and NAFLD with fibrosis, NAFLD with fibrosis and NAFLD-related HCC, and normal and NASH-related HCC.
RESULTS: Seven genes, including COL1A1, TIPM1, VCAN, FOS, CD79A, CXCL9, and VWF, were identified as the hub genes, and then a gene model was constructed. By calculating, the area under the receiver operating characteristic curves (AUCs) for risk prediction were 0.97, 0.886, and 0.751 in the three validation datasets, respectively. Gene set enrichment analysis indicated that the MAPK, TGFβ, p53, PPAR, insulin signaling pathways, and fatty acid metabolism were significantly upregulated in the high-risk group. GTPase activity and intrinsic apoptotic signaling pathway had significant upregulation in the low-risk group.
CONCLUSIONS: The seven hub genes may predict the risk of NAFLD developing into HCC by mediating the potential molecular mechanism, which could be used as biomarkers for predicting the progression, diagnosis, and treatment of NAFLD.

OBJECTIVE: The role of prolactin (PRL) in glucolipid metabolism was inconsistent, and there were few studies on the metabolic role of PRL in obese patients. The study aims to explore association between PRL level and metabolic disorders in male obese patients.
METHODS: A retrospective study was conducted. Eighty-nine male patients with obesity were included, and their clinical data were recorded.
RESULTS: A total of 89 male obese patients were included in this study. Their average age was 24.5 ± 9.0 years and BMI was 42.8 ± 9.1 kg/m2. The average waist circumference and body fat percentage was 129.6 ± 19.6 cm and 42.9 ± 8.0%, respectively. The median prolactin levels were 10.0 ng/ml (range: 3.93-30.1 ng/ml). 79.0% (49/62) of these patients presented with NAFLD and 77.3% (68/88) of them was dyslipidemia. Further, serum prolactin level was positively correlated with BMI (r = 0.225, P = 0.034), body fat percentage (r = 0.326, P = 0.017), ALT (r = 0.273, P = 0.011) and AST (r = 0.245, P = 0.029). Compared with low PRL group (<10 ng/ml), the incidence of morbid obesity and NAFLD was higher in high PRL group (morbid obesity: 71.1% vs 45.5%, P = 0.018 and NAFLD: 91.2% vs 64.3%, P = 0.013). In addition, the risk of NAFLD and morbid obesity in high PRL group (>10 ng/ml) was higher than low PRL group (OR:5.187, 95%CI 1.194-22.544, P = 0.028 and OR: 4.375, 95% CI 1.595-11.994, P = 0.004). The increased risk of NAFLD and morbid obesity in the high PRL group still existed after adjusting for age and Testosterone.
CONCLUSIONS: Serum prolactin levels were positively associated with deterioration of metabolic indexes in male obese patients, as well as NAFLD and morbid obesity.

There is a need to assess the severity of steatosis caused by Nonalcoholic Fatty Liver Disease (NAFLD). We explored new techniques in which Ultrasound-Guided Attenuation Parameter (UGAP), Liver Steatosis Analysis (LiSA) and Hepatorenal Index (HRI) can be applied to the grading of steatosis.
We enrolled 120 patients with or without NAFLD in this study who underwent UGAP, LiSA, HRI and controlled attenuation parameter (CAP) measurements in our hospital from September 2022 to April 2023. Spearman correlation coefficient was used to calculate the correlation between UGAP, LiSA, HRI and CAP values, and the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic accuracy of UGAP, LiSA, and HRI for different grades of steatosis.
The cohort was classified into four groups based on means of CAP: S0 (no steatosis): 30/120, S1 (mild): 30/120, S2 (moderate): 15/120, and S3 (severe): 45/120. The cut-off values and areas under the receiver operating characteristic curve (AUC) of UGAP, LiSA and HRI for predicting different grades of steatosis were: S≥S1:227dB/m (AUC=0.904), 241dB/m (AUC=0.873), 1.19 (AUC=0.696); S≥S2:251dB/m (AUC=0.978), 264dB/m (AUC=0.913), 1.37 (AUC=0.770); S=S3:263dB/m (AUC=0.962), 289dB/m (AUC=0.923), 1.45 (AUC=0.809). The diagnostic efficacy of UGAP and LiSA was significantly better than HRI, and there were statistically significant differences (all p<0.05). A strong correlation was found between UGAP, LiSA and CAP values (UGAP: r=0.865; LiSA: r=0.810), moderate correlation between HRI and CAP values (r=0.476).
Both UGAP and LiSA have a strong correlation with CAP and are more accurate than HRI in diagnosing different grades of hepatic steatosis, which can be widely used in the diagnosis of liver steatosis.

BACKGROUND: In recent years, spectral CT-derived liver fat quantification method named multi-material decomposition (MMD) is playing an increasingly important role as an imaging biomarker of hepatic steatosis. However, there are various measurement ways with various results among different researches, and the impact of measurement methods on the research results is unknown. The aim of this study is to evaluate the reproducibility of liver fat volume fraction (FVF) using MMD algorithm in nonalcoholic fatty liver disease (NAFLD) patients when taking blood vessel, location, and iodine contrast into account during measurement.
METHODS: This retrospective study was approved by the institutional ethics committee, and the requirement for informed consent was waived because of the retrospective nature of the study. 101 patients with NAFLD were enrolled in this study. Participants underwent non-contrast phase (NCP) and two-phase enhanced CT scanning (late arterial phase (LAP) and portal vein phase (PVP)) with spectral mode. Regions of interest (ROIs) were placed at right posterior lobe (RPL), right anterior lobe (RAL) and left lateral lobe (LLL) to obtain FVF values on liver fat images without and with the reference of enhanced CT images. The differences of FVF values measured under different conditions (ROI locations, with/without enhancement reference, NCP and enhanced phases) were compared. Friedman test was used to compare FVF values among three phases for each lobe, while the consistency of FVF values was assessed between each two phases using Bland-Altman analysis.
RESULTS: Significant difference was found between FVF values obtained without and with the reference of enhanced CT images. There was no significant difference about FVF values obtained from NCP images under the reference of enhanced CT images between any two lobes or among three lobes. The FVF value increased after the contrast injection, and there were significant differences in the FVF values among three scanning phases. Poor consistencies of FVF values between each two phases were found in each lobe by Bland-Altman analysis.
CONCLUSIONS: MMD algorithm quantifying hepatic fat was reproducible among different lobes, while was influenced by blood vessel and iodine contrast.

Nonalcoholic fatty liver disease (NAFLD) is a spectrum of chronic liver disease characterized. The condition ranges from isolated excessive hepatocyte triglyceride accumulation and steatosis (nonalcoholic fatty liver (NAFL), to hepatic triglyceride accumulation plus inflammation and hepatocyte injury (nonalcoholic steatohepatitis (NASH)) and finally to hepatic fibrosis and cirrhosis and/or hepatocellular carcinoma (HCC). However, the mechanism driving this process is not yet clear. Obtain sample microarray from the GEO database. Extract 6 healthy liver samples, 74 nonalcoholic hepatitis samples, 8 liver cirrhosis samples, and 53 liver cancer samples from the GSE164760 dataset. We used the GEO2R tool for differentially expressed genes (DEGs) analysis of disease progression (nonalcoholic hepatitis healthy group, cirrhosis nonalcoholic hepatitis group, and liver cancer cirrhosis group) and necroptosis gene set. Gene set variation analysis (GSVA) is used to evaluate the association between biological pathways and gene features. The STRING database and Cytoscape software were used to establish and visualize protein-protein interaction (PPI) networks and identify the key functional modules of DEGs, drawn factor-target genes regulatory network. Gene Ontology (GO) and KEGG pathway enrichment analyses of DEGs were also performed. Additionally, immune infiltration patterns were analyzed using the cibersort, and the correlation between immune cell-type abundance and DEGs expression was investigated. We further screened and obtained a total of 152 intersecting DEGs from three groups. 23 key genes were obtained through the MCODE plugin. Transcription factors regulating common differentially expressed genes were obtained in the hTFtarget database, and a TF target network diagram was drawn. There are 118 nodes, 251 edges, and 4 clusters in the PPI network. The key genes of the four modules include METAP2, RPL14, SERBP1, EEF2; HR4A1; CANX; ARID1A, UBE2K. METAP2, RPL14, SERBP1 and EEF2 was identified as the key hub genes. CREB1 was identified as the hub TF interacting with those gens by taking the intersection of potential TFs. The types of key gene changes were genetic mutations. It can be seen that the incidence of key gene mutations is 1.7% in EEF2, 0.8% in METAP2, and 0.3% in RPL14, respectively. Finally, We found that the most significant expression differences of the immune infiltrating cells among the three groups, were Tregs and M2, M0 type macrophages. We identified four hub genes METAP2, RPL14, SERBP1 and EEF2 being the most closely with the process from NASH to cirrhosis to HCC. It is beneficial to examine and understand the interaction between hub DEGs and potential regulatory molecules in the process. This knowledge may provide a novel theoretical foundation for the development of diagnostic biomarkers and gene-related therapy targets in the process.