The animal experimental protocol was approved by the Ethics Committee of the People's Hospital of Hebei Province and complied with international regulations for the management of experimental animals. A total of 40 male C57BL/6J mice (6 weeks old, weighing 21.0-23.0 g) were purchased from Beijing Weitong Lihua Experimental Animal Center [license no. SCXK (Beijing) 2016-0006] and maintained at the Animal Laboratory of the Clinical Research Center of Hebei General Hospital under a 12-h light/dark cycle with free access to food and water.

Animal food was purchased from Beijing Huafukang Biotechnology Co., Ltd. [ordinary feed D12450J (calorie composition: 20% protein, 70% carbohydrate and 10% fat; 3.85 kcal/g) and high-fat feed D12492 (calorie composition: 20% protein, carbohydrates 20 and 60% fat; 5.24 kcal/g)].

The C57BL/6J mice were randomly divided into the control (CON, n=10) and HFD (n=30) groups. The CON group was provided with ordinary feed, and the HFD group was provided with the high-fat feed. After 8 weeks, an intraperitoneal glucose tolerance test (IPGTT) was performed. According to the weight of the mice, 2 g/kg glucose in saline were injected intraperitoneally, and the blood glucose concentration was measured by blood sampling from the tail vein using a blood glucose meter (Johnson & Johnson) at 0, 15, 30, 60 and 120 min, as previously described (10,11). The area under the curve (AUC) was calculated to confirm a glucose metabolic disorder and to determine whether the insulin resistance model was successfully established.

The mice in the HFD group were randomly divided into three groups as follows: 10 mice in the HFD control group, 10 mice in the HFD + RSV group, and 10 mice in the HFD + MET group. RSV (Sigma-Aldrich; Merck KGaA) at a concentration of 100 mg/kg/day and MET (Sangon Biotech (Shanghai) Co., Ltd.) at a concentration of 250 mg/kg/day were administered to the mice. The CON and HFD groups were administered a 0.9% sodium solution containing 0.1% DMSO daily. The sodium solution was administered to the stomach, and the IPGTT was performed after 8 weeks. The doses of RSV and MET were similar to those used in previous studies using rodents (12,13). RSV was used at 100 mg/kg/day and MET at 250 mg/kg/day in preliminary experiments to attenuate insulin resistance. A previous study proved that RSV (100 mg/kg/day) used in mice did not cause damage to liver function (14). In addition, in a previous study, the authors demonstrated that 100 mg/kg/day RSV did not damage liver function (15). Animal and food weights were recorded weekly throughout the experiment.

Following 8 weeks of RSV and MET treatments, and 72 h after the final IPGTT, 3 mice from each group were randomly selected and injected intraperitoneally with insulin (Sigma-Aldrich; Merck KGaA) at 1.5 IU/40 g at 20 min prior to anesthesia (mice were anesthetized by an intraperitoneal injection of 2% pentobarbital sodium at 45 mg/kg). All mice were euthanized by cervical dislocation, and blood was then collected by cardiac puncture. The liver was rapidly excised and weighed; a small section was fixed in 4% paraformaldehyde, and the remaining tissues were rapidly frozen in liquid nitrogen and then transferred to a −80°C freezer for storage.

According to the fasting blood glucose and insulin concentration, a QUICKI was obtained (16). QUICKI value=1/(lgI0 + lgG0), where I0 is fasting insulin and G0 is fasting blood glucose.

The liver tissue samples fixed in 4% paraformaldehyde were dehydrated with gradient alcohol solutions (100, 95, 80 and 75%), embedded in paraffin, and then sectioned serially at a thickness of 5 µm. The sections were deparaffinized and stained with hematoxylin for 5 min at 25°C (Wuhan Servicebio Technology Co., Ltd.). The sections were then differentiated with 70% ethanol for 10 sec, followed by washing with distilled water. Finally, the sections were stained with eosin for 5 min at 25°C (Wuhan Servicebio Technology Co., Ltd.), dehydrated and sealed with resin. The morphological characteristics of the liver sections were observed under a light microscope (Nikon Corporation).

The collected tissues were frozen and sectioned at a thickness of 5-10 nm. The sections were placed in an Oil Red O solution for 5-15 min at 25°C (Wuhan Servicebio Technology Co., Ltd.) while being protected from light and then differentiated with 75% alcohol, followed by washing with distilled water. After staining the nuclei with hematoxylin for 2 min at 25°C), the sections were washed with distilled water until the nuclei became blue for 5-10 min and then sealed glycerin-gelatin. The morphological characteristics of the sections were observed under an optical microscope (Nikon Corporation).

Total protein was extracted from the liver tissues using RIPA buffer (Wuhan Servicebio Technology Co., Ltd.) and the protein concentration was determined using a BCA kit (Thermo Fisher Scientific, Inc.). SDS-PAGE separation gels (8, 10 and 12%) were prepared at various concentrations according to the molecular weight of the target protein. Following electrophoresis, the proteins were transferred to a PVDF membrane that was blocked with 5% dry skim milk for 3 h at 25°C. Primary antibodies diluted in blocking solution were as follows: β-actin (mouse antibody, 1:1,000; cat. no. 3700S); t-PI3K (rabbit antibody, 1:2,000; cat. no. 4249S); p-PI3K (Tyr 458; rabbit antibody, 1:1,000; cat. no. 17366S); t-Akt rabbit antibody, 1:2,000; cat. no. 4691S); p-Akt (Ser 473) rabbit antibody, 1:1,000 cat. no. 4060S) (all from Cell Signaling Technology, Inc.); forkhead box O1 (FOXO1) (rabbit antibody, 1:1,000; cat. no. 18592-1-AP); glucose-6-phosphatase catalytic subunit 1 (G6PC) (rabbit antibody, 1:2,000 cat. no. 22169-1-AP) (all from ProteinTech Group, Inc.); phosphoenolpyruvate carboxykinase 1 (PCK1; PEPCK) (rabbit antibody, 1:1,000 cat. no. 702748; Thermo Fisher Scientific, Inc.); HRP-labeled goat anti-rabbit IgG antibody and goat anti-mouse IgG antibody (1:8,000; cat. no. L3012-2; and 1:3,000, cat. no. L3032-2 respectively; both from Signalway Antibody LLC). The primary antibodies were incubated with the membrane at 4°C overnight, followed by washing three times (10 min each time) with TBST (20% Tween), followed by incubation with the secondary antibodies at room temperature for 50 min, and washing three times (10 min each time) with TBST (20% Tween). A gel imaging instrument was used to capture specific protein bands. ImageJ software 1.8.0 (National Institutes of Health) was used to measure the densitometric values of the protein bands. Normalization was performed by incubating the same membrane with an antibody against β-actin for 2 h at 25°C).

Total RNA was extracted from the mouse liver tissues using TRIzol^® reagent (Thermo Fisher Scientific, Inc.), and the RNA concentration was determined using a NanoDrop 2000 (Thermo Fisher Scientific, Inc.). RNA was reverse transcribed into cDNA (RR047A) using a PrimeScript™ RT reagent kit with a gDNA Eraser kit and amplified using a SYBR^® Premix Ex Taq™ II kit (RR820A; Takara Bio, Inc.). PCR was performed using the Applied Biosystems 7300 apparatus (Applied Biosystems; Thermo Fisher Scientific, Inc.) at 95°C for 10 min, followed by 40 cycles for 15 sec at 95°C, 15 sec at 95°C and 15 sec at 60°C. The 2^−ΔΔCq method (17) was used to normalize the gene expression levels to β-actin. The primer sequences are listed in Table I. Primers for the lncRNAs were designed by Shanghai Simomics based on lncRNA sequences from the NONCODE database (http://www.noncode.org/).

A total of four liver samples each were selected from the CON, HFD, HFD + RSV and HFD + MET groups, and total RNA was extracted using an RNeasy mini kit (Qiagen GmbH) and TruSeq™ RNA sample preparation reagents (Illumina, Inc.). A cassette (Illumina, Inc.) was used to construct a sequencing library. The purified library was verified using the Qubit^® 2.0 Fluorometer (Thermo Fisher Scientific, Inc.) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc.) for the insert size and calculated molarity. Finally, sequencing was performed on an Illumina NovaSeq 6000 (Illumina, Inc.). The library was constructed and sequenced by Shanghai Simomics. The high-throughput sequencing results were uploaded to the Gene Expression Omnibus database (accession no. GSE137840).

Fragments were counted within each gene segment to calculate the fragments per kilobase million (FPKM) value for each gene (18). The differential expression of genes between groups was then analyzed. After calculating the P-value, multiple hypothesis test correction was performed by controlling the false discovery rate (FDR). The corrected P-value is termed the Q-value. Fold changes in differential expression were calculated based on the FPKM value, and the log2 (fold change) was then calculated to subsequently screen differentially expressed genes, as previously described (19). Both lncRNAs and mRNAs were obtained from databases [lncRNAs: RefSeq (https://www.ncbi.nlm.nih.gov/refseq/), Ensembl (https://asia.ensembl.org/index.html) and GenBank (https://www.ncbi.nlm.nih.gov/); mRNAs: NONCODE (http://www.noncode.org/) and Ensembl].

To investigate the main biological functions and pathways related to the differentially expressed genes, each gene was annotated based on the GO and KEGG databases. Fisher's exact test or Chi-squared test were used to calculate the number of differentially expressed genes, and the hypergeometric test was then used for statistical analysis to select the GO and KEGG entries that were significantly enriched for the differentially expressed genes. After the calculated P-value was corrected by multiple hypothesis testing, a Q-value ≤0.05 was used as the threshold. Meeting this condition was defined as the GO and KEGG results that were significantly enriched for differentially expressed genes.

The mRNA that interacts with lncRNA is termed the target gene of lncRNA. cis target gene prediction involved the identification of mRNAs in the 10 kb range of lncRNA upstream and downstream on the genome as the target gene of the lncRNA. The prediction of trans target genes was based on the principle of sequence complementary pairing, using blast alignment to obtain mRNA complementary to lncRNA. RNAplex 0.2 software (University of Leipzig, Leipzig, Germany) was used to calculate the thermodynamic parameter values of lncRNAs and mRNAs following complementary pairing. The result above the software threshold ranges was selected as the target gene of the lncRNA.

All data were analyzed using SPSS 22.0 software (SPSS, Inc.). The results are expressed as the mean ± standard deviation. An independent samples t-test (Student's t-test) was used for two-sample comparisons with data demonstrating a normal distribution. Multiple groups were compared using one-way analysis of variance (ANOVA) followed by Tukey's or Tamhane's test. P<0.05 was considered to indicate statistically significant differences. For lncRNA and mRNA expression, significant level changes were expressed as a Q-value <0.05, and the absolute value of fold change was greater than or equal to twice the change.

At the end of week 8, IPGTTs were performed on the two groups of mice. The mice in the HFD group had significantly higher blood glucose levels than those in the CON group at 0, 30, 60 and 120 min (Fig. 1A). Compared with the CON group, the AUC in the HFD group was significantly increased (Fig. 1B), indicating that the model of insulin resistance was successfully established.

As shown by the results of the IPGTT, compared with the CON group, the HFD group had significantly higher blood glucose levels at 0, 15, 30, 60 and 120 min (Fig. 1C). Compared with the HFD group, the HFD + RSV and HFD + MET groups had significantly decreased blood glucose levels at 30, 60 and 120 min. No statistically significant difference in glucose levels was observed between the HFD + MET and HFD + RSV groups (Fig. 1C). Compared with the CON group, the AUC in the HFD group was significantly increased. Compared with the HFD group, the AUC in the HFD + RSV and HFD + MET groups was significantly decreased. Similarly, compared with the HFD + RSV group, the AUC in the HFD + MET group did not differ significantly (Fig. 1D).

Compared with the CON group, the fasting blood glucose and insulin levels in the HFD group were significantly increased and the QUICKI value was significantly decreased. Compared with the HFD group, the fasting blood glucose and insulin levels in HFD + RSV and HFD + MET groups were significantly decreased, and the QUICKI value was significantly increased. Compared with the HFD + RSV group, significant differences were observed in fasting blood glucose levels in the HFD + MET group, the insulin level was significantly decreased and the QUICKI value was significantly increased (Fig. 1E-G).

The liver structure of the mice in the CON group was clear and intact, the cytoplasm was uniformly stained red, and essentially, no lipid droplets were vacuolated (Fig. 2A). However, the structure in the HFD group was disordered and fuzzy, and a large number of large lipid droplet vacuoles were observed in the cytoplasm (Fig. 2B). The liver structures in the HFD + RSV and HFD + MET groups were clear, and the cytoplasm was stained red. A small number of smaller lipid droplet vacuoles were observed in the cytoplasm. Compared with the HFD + RSV group, the number of lipid droplet vacuoles was markedly decreased in the HFD + MET group (Fig. 2C and D).

The liver structure in the CON group was clear with blue nuclei (Fig. 2E). In the HFD group, a large number of orange-red lipid droplets were deposited, and a large number of lipid droplet vacuoles were observed in the cytoplasm (Fig. 2F). Compared with the HFD group, the orange-red lipid droplet deposition and lipid droplet vacuoles were markedly decreased in the HFD + RSV group. Compared with the HFD + RSV group, the orange-red lipid droplet deposition and lipid droplet vacuoles were markedly decreased in the HFD + MET group. Orange-red lipid droplets were less evident, and intracellular cytoplasmic lipid droplet vacuoles were essentially absent (Fig. 2G and H).

The expression of lncRNAs and mRNAs in the livers of mice in the HFD + RSV and HFD + MET groups was determined using high-throughput sequencing and comparisons were made between the groups. A total of 55 differentially expressed lncRNAs (21 upregulated and 34 downregulated) (Table II) and 19 mRNAs with a differential expression (8 upregulated and 11 downregulated) (Table III) were detected. A heatmap (Fig. 3A and B), volcano plot (Fig. 4A and B) and scatter plot (Fig. 4C and D) were used to reveal the trend distribution and approximate numbers of lncRNAs and mRNAs with a differential expression.

From the 55 lncRNAs with a differential expression in the HFD + RSV and HFD + MET groups, four randomly selected lncRNAs upregulated in the HFD + RSV group (NONMMUT042412.2, NON MMU T0 06741.2, NON MMU T148967.1 and NONMMUT034936.2) (Fig. 5A-D) and four lncRNAs downregulated in the HFD + RSV group (NONMMUT022720.2, NONMMUT020098.2, NONMMUT051900.2 and NONMMUT051843.2) (Fig. 5E-H) were used to verify the sequencing results using RT-qPCR. Apart from NONMMUT051843.2, the expression levels of the other seven lncRNAs were consistent with the sequencing results in the HFD + RSV and HFD + MET groups. Compared with the CON group, apart from the expression levels of NONMMUT148967.1 and NONMMUT051843.2 in the HFD group, those of the other lncRNAs differed significantly. Compared with the HFD group, apart from the expression levels of NONMMUT006741.2, NONMMUT022720.2, NONMMUT051900.2 and NONMMUT051843.2, those of the other lncRNAs in the HFD + RSV group differed significantly.

GO analysis includes 'Biological Process (BP)', 'Molecular Function (MF)' and 'Cellular Component (CC)'. The meaningful BPs in the top 30 mRNA enrichments of the GO analysis mainly included 'chemical homeostasis', 'homeostatic process' and 'cellular lipid metabolic process'. CC mainly included 'cytoplasmic vesicle' and 'intracellular vesicle'. MF included 'molecular function regulator' and 'hydrolase activity' (Fig. 6A). KEGG pathway analysis revealed the signaling pathways in which mRNAs with major differences were involved. The top 30 pathway enrichments included 'mineral absorption' and the 'PI3K-Akt signaling pathway'. Among these, the PI3K/Akt signaling pathway is related to the liver insulin resistance model of the HFD-fed mice (Fig. 6B). This pathway We selected and the closely related target gene predicted was G6PC through pathway analysis. Among the eight verified lncRNAs, NONMMUT034936.2 exhibited a similar trend in expression as this target gene, as discussed below.

The mRNA levels of several key molecules in the PI3K/Akt signaling pathway, namely PI3K, Akt, FOXO1, G6PC and PEPCK, were compared in the livers of mice in the CON, HFD, HFD + RSV, and HFD + MET groups using RT-qPCR. No significant differences in the mRNA expression levels of PI3K and Akt were observed among these four groups (Fig. 7A and B). Compared with the CON group, the mRNA levels of FOXO1, G6PC and PEPCK were significantly increased in the HFD group, and those in the HFD + RSV and HFD + MET groups were significantly decreased compared with those in the HFD group. Compared with the HFD + RSV group, the mRNA levels of FOXO1, G6PC and PEPCK in the HFD + MET group were significantly decreased (Fig. 7C-E).

The same key molecules were selected to verify and compare their protein levels using western blot analyhsis in the four groups of mouse liver tissues (Fig. 8A). Compared with the CON group, the levels of p-PI3K and p-Akt in the HFD group were significantly decreased (Fig. 8C and E), while those of FOXO1, G6PC and PEPCK were significantly increased (Fig. 8F-H). Compared with the HFD group, the levels of p-PI3K and p-Akt in the HFD + RSV and HFD + MET groups were significantly increased (Fig. 8C and E), while those of FOXO1, G6PC and PEPCK were significantly decreased (Fig. 8F-H). Compared with the HFD + RSV group, the HFD + MET group exhibited significantly increased expression levels of p-PI3K and p-Akt (Fig. 8C and E), and significantly decreased expression levels of FOXO1, G6PC and PEPCK (Fig. 8F and H). No significant differences were observed in the total PI3K and Akt expression levels among the four groups (Fig. 8B and D). The aforementioned results indicate that RSV may attenuate insulin resistance via the PI3K/Akt signaling pathway (Fig. 9).