Insulin-like growth factor 1 mRNA expression in the uterus of streptozotocin-treated diabetic mice

Short-Term Treatment of Metformin and Glipizide on Oxidative Stress, Lipid Profile and Renal Function in a Rat Model with Diabetes Mellitus

Background: Oxidative stress, lipid profile and renal functions are well-known conventional risk factors for diabetes mellitus (DM). Metformin and gliclazide are popularly used monotherapy drugs for the treatment of DM. Aims: This study aims to assess the short-term treatment of single and dual therapy of glipizide/metformin on oxidative stress, glycemic control, serum lipid profiles and renal function in diabetic rats. Methods: DM was induced in rats with streptozotocin (STZ), then five different treatments were applied, including group I (untreated healthy control), group II (diabetic and untreated), group III (diabetic and treated with metformin), group IVI (diabetic and treated with glipizide) and group V (diabetic and treated with a combination of metformin and glipizide. Lipid peroxidation (LPO), nitric oxide (NO), total antioxidant capacity (TAC), fasting blood glucose (FBG), glycated hemoglobin (HbA1c), total cholesterol, triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), creatinine and urea were measured. Results: Compared to the untreated DM group, FBG and HbA1c were significantly reduced in the DM groups (p < 0.01) treated with metformin (159.7 mg/dL & 6.7%), glipizide (184.3 mg/dL & 7.3%) and dual therapy (118 mg/dL & 5.2%), respectively. Treatment with dual therapy and metformin significantly decreased LPO and NO levels but increased TAC in diabetic rats more than glipizide compared to untreated diabetic rats. Furthermore, metformin (19.8 mg/dL, p < 0.001), glipizide (22.7 mg/dL, p < 0.001), and dual therapy (25.7 mg/dL, p < 0.001) significantly decreased urea levels in the treated rats compared to untreated DM rats (32.2 mg/dL). Both drugs and their combination exhibited a substantial effect on total cholesterol, HDL, LDL and atherogenic index. Conclusions: These results suggest that the therapeutic benefits of metformin and glipizide are complementary. Metformin exhibited superior performance in improving glycemic control and decreasing oxidative stress, while glipizide was more effective against dyslipidemia. These findings could be helpful for the treatment of future vascular patients, antilipidemic medicines and antioxidant therapy to improve the quality of life.

Thymoquinone Lowers Blood Glucose and Reduces Oxidative Stress in a Rat Model of Diabetes

The aim of the present study was to assess the short-term effects of Thymoquinone (TQ) on oxidative stress, glycaemic control, and renal functions in diabetic rats. DM was induced in groups II and III with a single dose of streptozotocin (STZ), while group I received no medication (control). The rats in groups I and II were then given distilled water, while the rats in group III were given TQ at a dose of 50 mg/kg body weight/day for 4 weeks. Lipid peroxidase, nitric oxide (NO), total antioxidant capacity (TAC), glycated haemoglobin (HbA1c), lipid profiles, and renal function were assessed. Moreover, the renal tissues were used for histopathological examination. STZ increased the levels of HbA1c, lipid peroxidase, NO, and creatinine in STZ-induced diabetic rats in comparison to control rats. TAC was lower in STZ-induced diabetic rats than in the control group. Furthermore, rats treated with TQ exhibited significantly lower levels of HbA1c, lipid peroxidase, and NO than did untreated diabetic rats. TAC was higher in diabetic rats treated with TQ than in untreated diabetic rats. The histopathological results showed that treatment with TQ greatly attenuated the effect of STZ-induced diabetic nephropathy. TQ effectively adjusts glycaemic control and reduces oxidative stress in STZ-induced diabetic rats without significant damaging effects on the renal function.

Uncovering the dosage-dependent roles of Arid1a in gastric tumorigenesis for combinatorial drug therapy

Gastric cancer (GC) is one of the most common deadly cancers in the world. Although patient genomic data have identified AT-rich interaction domain 1A (ARID1A), a key chromatin remodeling complex subunit, as the second most frequently mutated gene after TP53, its in vivo role and relationship to TP53 in gastric tumorigenesis remains unclear. Establishing a novel mouse model that reflects the ARID1A heterozygous mutations found in the majority of human GC cases, we demonstrated that Arid1a heterozygosity facilitates tumor progression through a global loss of enhancers and subsequent suppression of the p53 and apoptosis pathways. Moreover, mouse genetic and single-cell analyses demonstrated that the homozygous deletion of Arid1a confers a competitive disadvantage through the activation of the p53 pathway, highlighting its distinct dosage-dependent roles. Using this unique vulnerability of Arid1a mutated GC cells, our combined treatment with the epigenetic inhibitor, TP064, and the p53 agonist, Nutlin-3, inhibited growth of Arid1a heterozygous tumor organoids, providing a novel therapeutic option for GC.

Predicting diabetes mellitus genes via protein-protein interaction and protein subcellular localization information

BACKGROUND

Diabetes mellitus characterized by hyperglycemia as a result of insufficient production of or reduced sensitivity to insulin poses a growing threat to the health of people. It is a heterogeneous disorder with multiple etiologies consisting of type 1 diabetes, type 2 diabetes, gestational diabetes and so on. Diabetes-associated protein/gene prediction is a key step to understand the cellular mechanisms related to diabetes mellitus. Compared with experimental methods, computational predictions of candidate proteins/genes are cheaper and more effortless. Protein-protein interaction (PPI) data produced by the high-throughput technology have been used to prioritize candidate disease genes/proteins. However, the false interactions in the PPI data seriously hurt computational methods performance. In order to address that particular question, new methods are developed to identify candidate disease genes/proteins via integrating biological data from other sources.

RESULTS

In this study, a new framework called PDMG is proposed to predict candidate disease genes/proteins. First, the weighted networks are building in terms of the combination of the subcellular localization information and PPI data. To form the weighted networks, the importance of each compartment is evaluated based on the number of interacted proteins in this compartment. This is because the very different roles played by different compartments in cell activities. Besides, some compartments are more important than others. Based on the evaluated compartments, the interactions between proteins are scored and the weighted PPI networks are constructed. Second, the known disease genes are extracted from OMIM database as the seed genes to expand disease-specific networks based on the weighted networks. Third, the weighted values between a protein and its neighbors in the disease-related networks are added together and the sum is as the score of the protein. Last but not least, the proteins are ranked based on descending order of their scores. The candidate proteins in the top are considered to be associated with the diseases and are potential disease-related proteins. Various types of data, such as type 2 diabetes-associated genes, subcellular localizations and protein interactions, are used to test PDMG method.

CONCLUSIONS

The results show that the proteins/genes functionally exerting a direct influence over diabetes are consistently placed at the head of the queue. PDMG expands and ranks 445 candidate proteins from the seed set including original 27 type 2 diabetes proteins. Out of the top 27 proteins, 14 proteins are the real type 2 diabetes proteins. The literature extracted from the PubMed database has proved that, out of 13 novel proteins, 8 proteins are associated with diabetes.

Activated vitamin D3 and pro-activated vitamin D3 attenuate induction of permanent changes caused by neonatal estrogen exposure in the mouse vagina

Exposure of mice to a high dose of estrogens including diethylstilbestrol (DES) during the neonatal period modifies the developmental plan of the genital tract, which leads to various permanent changes in physiology, morphology and gene expression. These changes include development of an abnormal vaginal epithelium lined with hyperplastic mucinous cells accompanied by Tff1 gene expression in mice. Here, the influence of vitamin D on the direct effect of estrogen on the developing mouse vagina was examined. The mid-vagina of neonatal mice was cultured in a serum-free medium containing estradiol-17β (E₂) and various concentrations of 1,25-dihydroxyvitamin D₃ (1,25(OH)₂D) ex vivo and then was transplanted under the renal capsule of ovariectomized host mice for 35 days. Exposure to E₂ alone caused the vaginal tissue to develop estrogen-independent epithelial hyperplasia and to express TFF1 mRNA, while addition of a low nanomolar amount of 1,25(OH)₂D added at the same time as E₂ to the culture medium attenuated the effects of estrogen. Expression of vitamin D receptor was also evident in the neonatal mouse vagina. Interestingly, addition of 25-hydroxyvitamin D₃, a pro-activated form of vitamin D, at the micromolar level was found to be potent in disrupting the developmental effects of E₂, while cholecalciferol was not at least at the dose examined. Correspondingly, expression of Cyp27B1, a kidney-specific 25-hydroxyvitamin D hydroxylase, was evident in the neonatal mouse vagina when examined by RT-PCR. In addition, simultaneous administration of 1,25(OH)₂D successfully attenuated DES-induced ovary-independent hyperplasia in the vagina in neonatal mice in vivo. Thus, manipulation of vitamin D influenced the harmful effects of estrogens on mouse vaginal development.