Proteomic profiling of thyroid tissue in patients with obesity and benign diffuse goiter

Goiter is a term to describe the enlargement of the thyroid gland. The pathophysiology and molecular changes behind development of diffuse benign goiter remains unclear. The present study targeted to identify and describe the alterations in the thyroid tissue proteome from patients (obese euthyroid) with benign diffuse goiter (BDG) using proteomics approach. Thyroid tissue samples, from 7 age and sex matched, patients with BDG and 7 controls were obtained at the time of surgery. An untargeted proteomic analysis of the thyroid tissue was performed out utilizing two-dimensional difference (2D-DIGE) in gel electrophoresis followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for identification of the proteins. Progenesis software was used to identify changes in expression of tissue proteins and found statistically significant differences in abundance in a total of 90 proteins, 46 up and 44 down (1.5-fold change, ANOVA, p ≤ 0.05) in BDG compared to the control group. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of signalling pathways linked to ERK1/2, Glutathione peroxidase and NADPH oxidase associated to organismal injury and abnormalities, endocrine system disorders and cancer. The thyroid tissue proteome in patients with BDG revealed a significant decrease in thyroglobulin along with dysregulation of glycolysis and an increase in prooxidant peroxidase enzymes. Dysregulation of metabolic pathways related to glycolysis, redox proteins, and the proteins associated with maintaining the cytoskeletal structure of the thyrocytes was also identified

Differential Expression Profile and Genetic Variants of MicroRNAs Sequences in Breast Cancer Patients

The technology available for cancer diagnosis and prognosis is not yet satisfactory at the molecular level, and requires further improvements. Micro RNAs (miRNAs) have been recently reported as useful biomarkers in diseases including cancer. We performed a miRNA expression profiling study using peripheral blood from breast cancer patients to detect and identify characteristic patterns. A total of 100 breast cancer patients and 89 healthy patients were recruited for miRNA genotyping and expression profiling. We found that hs-miR-196a2 in premenopausal patients, and hs-miR-499, hs-miR-146a and hs-miR-196a2 in postmenopausal patients, may discriminate breast cancer patients from healthy individuals. In addition, we found a significant association between two microRNA polymorphisms (hs-miR-196a2 and hs-miR-499) and breast cancer risk. However, no significant association between the hs-miR-146a gene and breast cancer risk was found. In summary, the study demonstrates that peripheral blood miRNAs and their expression and genotypic profiles can be developed as biomarkers for early diagnosis and prognosis of breast cancer

Bacterial Infections among Patients with Chronic Diseases at a Tertiary Care Hospital in Saudi Arabia

Infections caused by multi-drug-resistant bacteria in patients with chronic diseases have been associated with high mortality and morbidity. While few reports have evaluated bacterial infections in multiple chronic disease patients, the focus of the current study was to investigate the prevalence of bacterial infections and the susceptibility profiles of causative strains among various groups of patients suffering from chronic diseases. Microbiological reports of patients suffering from cancer, diabetes mellitus, cardiovascular diseases, kidney diseases, and skin burns were retrospectively collected from a tertiary hospital in Saudi Arabia. Approximately 54.2% of recruited patients were males, and positive urine was the most prevalent specimen associated with kidney disease patients (25%). Escherichia coli isolates were predominant among cardiovascular, kidney, and cancer patients. Staphylococcus aureus was commonly detected in diabetics and those with burns. Although resistance patterns varied based on the type of specimens and underlying diseases, Escherichia coli showed limited resistance to colistin, carbapenems, and tigecycline, while S. aureus demonstrated susceptibility to ciprofloxacin, gentamicin, and rifampin. These observations are crucial for clinicians and policymakers to ensure effective treatment plans and improve outcomes in these patients with comorbidity

Characteristics of breast cancer patients.

<p>Characteristics of breast cancer patients.</p

Relative expression of microRNAs with respect to genotype pattern.

<p>miRNAs were determined using SYBR Green MicroRNA Assays adopting Quantitative Real Time PCR. Normalization was performed with the small nuclear RNU1A in blood samples. Total RNA including small RNA was isolated from blood samples from healthy subjects and breast cancer patients using the Blood RNA Isolation Kit (Qiagen, Germany). cDNA was subjected to Real Time PCR using microRNAs assays (Qiagen, Germany). Data derived from quantitative real-time PCR and presented in ΔCT of relative threshold cycles indicating fold changes over normal subjects.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030049#s2" target="_blank">Results</a> are mean values of triplicate experiments. Bars denote standard error (SEM). P-values of the statistical evaluations of miRNA levels were determined by Mann and Whitney-U test.</p

Relative expression of microRNAs in breast cancer cases and control subjects.

<p>Total RNA including small RNA was isolated from blood samples from healthy subjects and breast cancer patients using the Blood RNA Isolation Kit (Qiagen, Germany). cDNA was subjected to Real Time PCR using microRNAs assays (Qiagen, Germany). Data derived from quantitative real-time PCR and presented in ΔCT of relative threshold cycles indicating fold changes over normal subjects. Normalization was performed with the small nuclear RNU1A in blood samples. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030049#s2" target="_blank">Results</a> are mean values of triplicate experiments. Bars denote standard error (SEM). P-values of the statistical evaluations of miRNA levels were determined by Mann and Whitney-U test.</p

Distribution of microRNA gene allelic variants and Odds ratio with 95% CI in breast cancer patients and control subjects.

<p>Distribution of microRNA gene allelic variants and Odds ratio with 95% CI in breast cancer patients and control subjects.</p