To explore the effects of geniposide on insulin resistance and oxidative stress damage in polycystic ovary syndrome (PCOS) rats by regulating the nuclear factor E2-related factor 2 (Nrf2)/heme oxygenase-1(HO-1) signaling pathway.

A PCOS model was induced by gavage of letrozole for 21d and rats were randomly assigned into blank group (not modeled +normal saline), model group (modeled +normal saline), low-dose geniposide group (modeled+400 mg·kg^-1 geniposide by gavage), high-dose geniposide group (modeled+800 mg·kg^-1 geniposide by gavage), positive control group (modeled+0.34 mg·kg^-1 ethinylestradiol and cyproterone by gavage) and high-dose geniposide+ML385 group (modeled+800 mg·kg^-1 geniposide by gavage+30 mg·kg^-1 ML385 by by intraperitoneal injection), with 10 rats in each group. The levels of fasting blood glucose (FBG) and fasting insulin (FINS) were measured by blood glucose meter and enzyme-linked immunosorbent assay (ELISA) and then homeostatic model assessment of insulin resistance (HOMA-IR) was calculated. The levels of serum sex hormones and inflammatory were detected by ELISA and ovarian tissue oxidative stress index levels were detected by test kit, hematoxylin-eosin (HE) staining was used to measure the number of cystic follicles in rat ovarian tissue. TdT-media duTP nict end labeling (TUNEL) method was used to measure apoptosis of rat ovarian granulosa cells. Moreover, Western blot (WB) was used to detect apoptosis and Nrf2/HO-1 signaling pathway related protein expression in ovarian tissues.

The FBG levels in the low-dose geniposide group, high-dose geniposide group, positive control group, high-dose geniposide+ML385 group and control group, as well as the model group were (6.87±0.42), (5.21±0.28), (5.03±0.31), (8.32±0.51), (4.90±0.35) and (8.56±0.54) mmol·L^-1, respectively; FINS were (16.13±1.62), (10.46±1.37), (10.21±1.51), (20.67±1.82), (9.82±1.14) and (21.45±2.05) mIU·L^-1, respectively; HOMA-IR were 4.93±0.48、2.42±0.53、2.28±0.36、7.64±0.72、2.14±0.31 and 8.16±0.67, respectively; follicle-stimulating hormone (FSH) levels were (5.14±0.56), (7.49±0.62), (7.62±0.71), (2.95±0.54), (7.83±0.76) and (2.71±0.43) IU·L^-1, respectively; the superoxide dismutase (SOD) levels were (42.91±3.22), (56.45±4.16), (58.02±3.98), (32.16±2.85), (59.73±4.35) and (30.84±2.74) U·mg prot^-1, respectively. The relative protein expression levels of Nrf2 were 0.67±0.08, 1.10±0.12, 1.12±0.13, 0.26±0.07, 1.13±0.14 and 0.24±0.06, respectively; HO-1 were 0.61±0.07, 1.06±0.08, 1.08±0.10, 0.18±0.05, 1.09±0.11 and 0.16±0.04, respectively. The malondialdehyde (MDA) levels were (2.47±0.33), (1.39±0.21), (1.30±0.19), (3.38±0.42), (1.21±0.26) and (3.62±0.47) nmol·mg prot^-1, respectively. The number of ovarian antral follicles was 9.60±0.74, 4.30±0.57, 4.10±0.71, 14.20±0.98, 3.90±0.65 and 15.10±1.13, respectively. The ovarian granulosa cell apoptosis index was (16.27±1.16)%, (7.48±0.91)%, (7.19±0.76)%, (23.86±1.23)%, (6.94±0.85)% and (25.31±1.42)%, respectively. Compared blank group with the control group; compared model group with low-dose geniposide group, high-dose geniposide group and positive control group; compared low-dose geniposide group with high-dose geniposide group and compred high-dose geniposide group with high-dose geniposide+ML385 group, the differences of above indexes were all statistically significant (all P<0.05).

Geniposide can alleviate insulin resistance and oxidative stress damage in PCOS rats, possibly by activating the Nrf2/HO-1 signaling pathway.

To investigate the effect of paeonol (PAE) on epithelial-mesenchymal transition (EMT) and endoplasmic reticulum stress-induced apoptosis in ovarian cancer cells by regulating the microRNA-128-3p (miR-128-3p)/ never in mitosis gene A-related kinase 2 (NEK2) signaling axis.

SKOV3 cells were divided into the following groups: SKOV3 group (normal culture), PAE group (4 mmol·L^-1 PAE treatment), inhibitor-NC group (transfected with miR-128-3p inhibitor negative control), miR-128-3p inhibitor group (transfected with miR-128-3p inhibitor), si-NC group (transfected with si-NEK2 negative control), si-NEK2 group (transfected with si-NEK2), PAE+inhibitor-NC group (based on the PAE group, transfected with miR-128-3p inhibitor negative control), PAE+miR-128-3p inhibitor group (based on the PAE group, transfected with miR-128-3p inhibitor), PAE+miR-128-3p inhibitor+si-NC group (based on the PAE group, co-transfected with miR-128-3p inhibitor and si-NEK2 negative control) and PAE+miR-128-3p inhibitor+si-NEK2 group (based on the PAE group, co-transfected with miR-128-3p inhibitor and si-NEK2). Quantitative real-time polymerase chain reaction (PCR) was used to detect the relative expression levels of mRNA; immunofluorescence was used to detect the positive expression of NEK2 protein; Western blot was used to detect the relative expression levels of related proteins.

The relative expression levels of miR-128-3p in SKOV3 group, PAE group, PAE+inhibitor-NC group and PAE+miR-128-3p inhibitor group were 1.00±0.12, 2.34±0.27, 2.30±0.29 and 1.19±0.21, respectively; the relative expression levels of NEK2 mRNA were 1.00±0.13, 0.58±0.09, 0.61±0.12 and 0.93±0.18, respectively; the positive expression of NEK2 was 1.00±0.11, 0.29±0.05, 0.31±0.06 and 0.94±0.17, respectively; the relative expression levels of E-cadherin mRNA in SKOV3 group, PAE group, PAE+inhibitor-NC group, PAE+miR-128-3p inhibitor group, PAE+miR-128-3p inhibitor+si-NC group and PAE+miR-128-3p inhibitor+si-NEK2 group were 1.00±0.12, 2.25±0.29, 2.27±0.34, 1.30±0.21, 1.32±0.20 and 2.03±0.35, respectively; the relative expression levels of N-cadherin mRNA were 1.00±0.14, 0.60±0.09, 0.63±0.12, 0.92±0.17, 0.94±0.18 and 0.67±0.13, respectively; the relative expression levels of Vimentin mRNA were 1.00±0.13, 0.62±0.09, 0.66±0.11, 0.90±0.17, 0.92±0.18 and 0.71±0.13, respectively; the relative expression levels of activating transcription factor 4 (ATF4) protein were 1.00±0.11, 3.22±0.57, 3.31±0.60, 1.51±0.24, 1.49±0.21 and 2.97±0.44, respectively; the relative expression levels of CCAAT/ enhancer binding protein (C/EBP) homologous protein (CHOP) were 1.00±0.14, 3.85±0.47, 3.62±0.41, 1.31±0.17, 1.28±0.17 and 3.26±0.57, respectively; the relative expression levels of cleaved-caspase-3 were 1.00±0.13, 4.52±0.67, 4.61±0.71, 1.67±0.26, 1.69±0.31 and 4.11±0.76, respectively. The differences in the above indicators were statistically significant when comparing PAE group with SKOV3 group, PAE+miR-128-3p inhibitor group with PAE+inhibitor-NC group and PAE+miR-128-3p inhibitor+si-NEK2 group with PAE+miR-128-3p inhibitor+si-NC group (all P<0.05).

PAE suppresses EMT and promotes endoplasmic reticulum stress-induced apoptosis in ovarian cancer cells, potentially by upregulating miR-128-3p to inhibit NEK2 expression.

To explore the expression of thrombospondin-1 (THBS1) in pan-cancer and its relevance to tumor microenvironment (TME).

The discrepancies in the expression and prognostic significance of THBS1 were examined in 33 different types of tumors using TCGA and GTEx data. The correlation between THBS1 and the TME index, various factors like immune cell infiltration, tumor mutagenesis burden (TMB) and microsatellite instability(MSI) was evaluated using computational methods. The potential mechanism was also dissected by constructing interaction networks of THBS1 with other genes by GEPIA; this was validated using multiplex immunohistochemistry(mIHC) in pancreatic cancer (PAAD) tissues.

Pan-cancer analysis revealed THBS1 mRNA was differentially expressed in 17 common cancer types (all P<0.05) and differential expression of the THBS1 protein was observed in 9 cancer types (all P<0.001). Survival analysis indicated that higher THBS1 expression was significantly associated with poorer patient prognosis in various malignant tumors (P<0.05). THBS1 expression was statistically significantly correlated with cancer-associated fibroblast (CAFs) infiltration across all cancer types (P<0.05), and positively associated with the expression of multiple immune checkpoint genes, including CD274(P<0.001)、HAVCR2(P<0.001)、PDCD1LG2(P<0.001)、LAG3(P<0.001)、PDCD1(P<0.001)、CTLA4(P<0.001) and TIGIT(P<0.001). These findings suggested that THBS1 may contribute to reduced responsiveness to immunotherapy by shaping an immunosuppressive tumor microenvironment. Co-expression and enrichment analyses demonstrated that the integrin genes strongly correlated with THBS1 in pancreatic adenocarcinoma (PAAD) were ITGAV (r=0.60, P<0.001)、ITGB3 (r=0.54, P<0.001) and ITGB1 (r=0.69, P<0.001). These findings were validated in pancreatic cancer tissues: immunofluorescence co-localization analysis demonstrated a strong positive correlation between THBS1 expression and integrin ITGAV (r=0.75, P<0.001).

This study identifies THBS1 as a crucial pan-cancer prognostic biomarker and a key regulator of the TME, providing a compelling rationale for its potential as a therapeutic target in oncology.

To investigate the inhibitory effect of different doses of metformin on colorectal cancer (CRC) and its mechanism involving the regulation of bile acid metabolism and the cyclooxygenase-2 (COX-2)/prostaglandin E2 (PGE2) pathway.

A total of 60 BALB/c mice were divided into control, model, low-dose metformin, medium-dose metformin and high-dose metformin groups. A CRC model was induced using azoxymethane (AOM)/dextran sodium sulfate (DSS). Tumor number and diameter were measured with a caliper; fecal bile acid levels were detected by liquid chromatography-mass spectrometry (LC-MS); and protein expression of COX-2 and PGE2 in colon tissue was determined by immunohistochemistry.

Tumor numbers in the control, model, low-, medium- and high-dose groups were 0, 11.58±7.13, 7.83±3.38, 3.33±2.06 and 2.83±1.40, respectively; tumor diameters were 0, (2.91±0.32), (2.43±0.31), (2.11±0.37) and (1.98±0.38) mm, respectively; total bile acid concentrations were (20 989.00±306.69), (43 256.50±187.08), (32 265.26±325.08), (23 035.72±136.33) and (22 351.51±145.36) ng·g^-1, respectively; deoxycholic acid (DCA) concentrations were (3 160.14±113.31), (16 684.58±4.39), (11 544.47±7.86), (5 472.60±25.03) and (5 201.36±79.95) ng·g^-1, respectively; lithocholic acid (LCA) concentrations were (2 140.43±76.23), (14 452.6±47.82), (9 085.87±11.14), (3 145.09±54.20) and (2 955.51±38.02) ng·g^-1, respectively; cholic acid (CA) concentrations were (6 917.71±51.12), (2 051.41±88.47), (3 181.64±23.79), (5 564.01±35.45) and (5 866.10±63.80) ng·g^-1, respectively; chenodeoxycholic acid (CDCA) concentrations were (5 720.33±53.07), (1 135.43±48.38), (1 530.56±37.57), (4 060.14±37.09) and (4 542.83±27.39) ng·g^-1, respectively; taurocholic acid (TCA) concentrations were (497.24±59.29), (1 560.15±26.03), (958.13±28.00), (705.21±3.66) and (669.24±33.00) ng·g^-1, respectively; taurochenodeoxycholic acid (TCDCA) concentrations were (1 027.96±84.28), (2 918.60±122.90), (2 518.23±70.50), (1 411.36±49.15) and (1 389.87±5.80) ng·g^-1, respectively; COX-2 staining scores in the model, low-, medium- and high-dose groups were (5.75±0.97), (4.50±1.78), (2.75±1.66) and (2.67±0.89) points, respectively; PGE2 staining scores were (5.75±0.97), (4.50±1.93), (2.67±1.67) and (2.50±0.90) points, respectively; compared with the control group, the aforementioned indicators in the model group showed statistically significant differences; compared with the model group, the indicators in the low-, medium- and high-dose groups showed statistically significant differences (all P<0.05). The medium- and high-dose groups were significantly more effective than the low-dose group in reducing tumor number and diameter and regulating bile acid metabolism (P<0.05). The inhibition of COX-2/PGE2 expression was negatively correlated with the dose of metformin.

Metformin exerts anti-CRC effects through dose-dependent regulation of bile acid metabolism (reducing DCA, LCA, TCA, TCDCA and restoring CA and CDCA levels) and inhibition of the COX-2/PGE2 signaling pathway. The medium- and high-dose groups (250-500 mg·kg^-1·d^-1) show more significant effects.

To explore the effects of midazolam on the proliferation, invasion and apoptosis of colorectal cancer cells by regulating the liver kinase B1 (LKB1)/AMP-activated protein kinase (AMPK) signaling pathway.

Cell counting kit-8 method was used to detect the effects of different concentrations (5, 10, 20 and 40 μg·mL^-1) midazolam on the proliferation of HCT116 cells. 20 μg·mL^-1 midazolam was selected for the subsequent experiments. HCT116 cells were grouped into blank group (no treatment), midazolam group (20 μg·mL^-1 midazolam), si-NC group (transfected with si-NC plasmid), si-LKB1 group (transfected with si-LKB1 plasmid), midazolam+si-NC group (transfected with si-NC plasmid+20 μg·mL^-1 midazolam) and midazolam+si-LKB1 group (transfected with si-LKB1 plasmid+20 μg·mL^-1 midazolam). Flow cytometry, cell countig kit-8 (CCK-8), EdU and Transwell experiments were used to detect changes in cell apoptosis, proliferation and invasion. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to measure the LKB1 and AMPK mRNAs. Western blot was used to measure the proliferating cell nuclear antigen (PCNA), cysteinyl aspartate-specific protease 3 (caspase-3), matrix metalloproteinase 9 (MMP-9), liver kinase B1 (LKB1) and AMP-activated protein kinase (AMPK) proteins.

The EdU positive rates of the blank group, midazolam group, si-NC group, si-LKB1 group, midazolam + si-NC group and midazolam + si-LKB1 group were (62.52±6.38)%, (35.26±3.64)%, (61.95±6.24)%, (88.63±8.94)%, (36.05±3.71)% and (55.62±5.67)%, respectively; the proliferation rates were (90.85±9.04)%, (48.85±4.92)%, (91.04±8.92)%, (129.32±13.05)%, (49.05±4.98)% and (79.86±8.11)%, respectively; the apoptosis rates were (5.05±0.53)%, (20.22±2.15)%, (4.86±0.49)%, (3.11±0.35)%, (19.86±2.08)% and (8.77±0.91)%, respectively; the invasion numbers were 198.64±20.45, 122.53±12.37, 195.32±20.34, 286.61±29.33, 123.64±12.46 and 176.64±18.06, respectively; the relative expression levels of LKB1 mRNA were 0.93±0.10, 2.86±0.31, 1.08±0.12, 0.57±0.07, 2.78±0.29 and 1.55±0.17, respectively; AMPK mRNA were 1.06±0.11, 2.25±0.24, 0.98±0.10, 0.42±0.05, 2.19±0.23 and 1.35±0.15, respectively; the relative protein expression levels of PCNA were 0.79±0.08, 0.42±0.05, 0.81±0.09, 1.22±0.14, 0.46±0.05 and 0.68±0.07, respectively; Caspase-3 were 0.92±0.10, 1.44±0.16, 1.03±0.11, 0.51±0.06, 1.48±0.16 and 1.07±0.11, respectively; MMP-9 were 0.98±0.10, 0.52±0.06, 1.01±0.12, 1.53±0.17, 0.58±0.06 and 0.82±0.09, respectively; LKB1 were 0.31±0.03, 0.76±0.08, 0.34±0.04, 0.15±0.02, 0.72±0.08 and 0.45±0.05, respectively; AMPK were 0.44±0.05, 0.85±0.09, 0.42±0.05, 0.23±0.03, 0.80±0.09 and 0.57±0.06, respectively. For all these indicators, compared between the midazolam group and the blank group, the si-LKB1 group and the si-NC group, the midazolam + si-LKB1 group and the midazolam + si-NC group, and the si-LKB1 group, all showed statistically significant differences (all P<0.05).

Midazolam activates the LKB1/AMPK signaling pathway, inhibits the proliferation and invasion of colorectal cancer cells, and induces their apoptosis.

To develop a liquid chromatography-tandem mass spectrometry method for the detection of lenvatinib in quantitative dried blood spots.

Lenvatinom-[d₄] was used as the internal standard. The dried blood spot samples were extracted with acetonitrile/water (70/30) and separated on a ProChrom C₁₈ reversed-phase column (2.1 mm×100.0 mm, 3.0 μm). The mobile phase consisted of 10 mmol·L^-1 ammonium acetate solution and methanol with gradient elution. The flow rate was 0.3 mL·min^-1. The ionization was carried out under the electrospray ionization positive mode. Multiple reaction monitoring was used to detect the transitions of lenvatinib at m/z 427.1→370.0 and 338.0, as well as lenvatinib-[d₄] at m/z 431.1→370.0. The specificity, standard curve, carryover, precision and accuracy, extraction recovery, matrix effect and stability of the method were investigated.

Endogenous components in the dried blood spot matrix of blank human whole blood did not affect the determination. The optimized pretreatment employs a ostep extraction with acetonitrile/water (70/30). Lenvatinib in dried blood spots demonstrated good linearity in the range of 10-250 ng·mL^-1. The standard curve equations from three analytical batches were y=3.81×10^-2x+2.76×10^-2(r=0.999 7), y=2.0×10^-2x-4.87×10^-3(r=0.999 9), y=2.01×10^-2x-3.68×10^-3(r=0.999 7), respectively. The lower limit of quantification (LLOQ) was 10 ng·mL^-1. The intra- and inter-batch relative errors were within ±15%, and relative standard deviation (RSD) were below 15%. There was no significant matrix effect, and lenvatinib dried blood spots sample remained stable for at least 7 days at a high temperature of 45 ℃.

The method is convenient, efficient and accurate and it is suitable for the requirements of The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use M10 guideline "Bioanalytical Method Validation and Study Sample Analysis". It can be used for the determination of lenvatinib concentrations in dried blood spot samples.