Identification of Prognostic Biomarkers in Papillary Thyroid Cancer and Developing Non-Invasive Diagnostic Models Through Integrated Bioinformatics Analysis.

BACKGROUND: Papillary thyroid cancer (PTC) is the most frequent subtype of thyroid carcinoma, mainly detected in patients with benign thyroid nodules (BTN). Due to the invasiveness of accurate diagnostic tests, there is a need to discover applicable biomarkers for PTC. So, in this study, we aimed to identify the genes associated with prognosis in PTC. Besides, we performed a machine learning tool to develop a non-invasive diagnostic approach for PTC. METHODS: For the study purposes, the miRNA dataset GSE130512 was downloaded from the GEO database and then analyzed to identify the common differentially expressed miRNAs in patients with non-metastatic PTC (nm-PTC)/metastatic PTC (m-PTC) compared with BTNs. The SVM was also applied to differentiate patients with PTC from those patients with BTN using the common DEMs. A protein-protein interaction network was also constructed based on the targets of the common DEMs. Next, functional analysis was performed, the hub genes were determined, and survival analysis was then executed. RESULTS: A total of three common miRNAs were found to be differentially expressed among patients with nm-PTC/m-PTC compared with BTNs. In addition, it was established that the autophagosome maturation, ciliary basal body-plasma membrane docking, antigen processing as ubiquitination & proteasome degradation, and class I MHC mediated antigen processing & presentation are associated with the pathogenesis of PTC. Furthermore, it was illustrated that RPS6KB1, CCNT1, SP1, and CHD4 might serve as new potential biomarkers for PTC prognosis. CONCLUSION: RPS6KB1, CCNT1, SP1, and CHD4 may be considered new potential biomarkers used for prognostic aims in PTC. However, performing validation tests is inevitable in the future.

Lavandula angustifolia Effects on Rat Models of Alzheimer's Disease Through the Investigation of Serum Metabolic Features Using NMR Metabolomics.

BACKGROUND: Alzheimer's Disease (AD) is the most prevalent cause of memory impairment in the elderly population, but the diagnosis and treatment of the disease is still challenging. Lavender aqueous extract has recently been shown to have the potential in clearing Amyloid-beta plaques from AD rat hippocampus. To elucidate the therapeutic mechanisms of lavender, serum metabolic fingerprint of Aß-induced rat Alzheimer's models was investigated through nuclear magnetic resonance spectrometry. METHODS: For the establishment of rat Alzheimer's models, 10 µg of Amyloid beta 1-42 was injected to male Wistar rats. The lavender aqueous extract was injected 20 days after the establishment of the models, once daily for 20 days. Serum samples were collected and metabolite fingerprints were obtained using 500 MHz 1H-NMR spectrometry, following multivariate statistical analyses. The resulted metabolites were then subjected to pathway analysis tools to reveal metabolic pathways affected by the lavender extract treatment. RESULTS: Levels of 10 metabolite markers including alanine, glutamine, serine, isoleucine, valine, carnitine, isobutyrate, pantothenate, glucose and asparagine were reversed nearly to control values after treatment with lavender extract. The results revealed that the most significantly affected pathways during treatment with lavender extract belonged to carbohydrate and amino acid metabolism, including pantothenate and CoA metabolism, glyoxilate and dicarboxylate metabolism, alanine, aspartate and glutamate metabolism, cysteine and methionine metabolism. CONCLUSION: As lavender extract reversed the direction of changes of some metabolites involved in AD pathogenesis, it was concluded that the extract might play a role in the disease improvement and serve as a potential therapeutic option for the treatment of AD. Moreover, the metabolites which were found in AD rats could serve as a potential marker panel for the disease; however, much further investigation and validation of the results is needed.

Pro-oxidant-antioxidant balance in Iranian veterans with sulfur mustard toxicity and different levels of pulmonary disorders.

OBJECTIVE: Sulfur mustard (SM) is a strong alkylating agent that primarily targets the skin, eye and lung. The current study evaluated the pro-oxidant-antioxidant balance (PAB) assay in human serum of SM-exposed patients. DESIGN AND METHODS: sera of 35 SM-exposed patients and 19 healthy volunteers were recruited. Both groups had nonsmoker and nonalcoholic people with no diseases such as diabetes, heart disease and other pulmonary diseases (COPD because of smoking, asthma and so on). All patients had documented exposure to SM. The PAB was measured. RESULTS: SM-exposed patients with normal values for pulmonary function test and severe obstructive pulmonary disease demonstrated a significant increase in PAB value in compared with healthy volunteers (the PAB values in healthy volunteers, normal and severe patients were 48.74 ± 21.07 HK, 101.45 ± 32.68 HK and 120.23 ± 31.55 HK, respectively). However, the level of oxidation is not related to the severity of disease defined by spirometry findings. A significant negative correlation was established between the PAB value and FEV1. CONCLUSIONS: The increased PAB value in chemical casualties showed that these patients are exposed to oxidative stress.

The metabolomics of airway diseases, including COPD, asthma and cystic fibrosis.

Chronic obstructive pulmonary disease (COPD), asthma and cystic fibrosis (CF) are characterized by airway obstruction and an inflammatory process. Reaching early diagnosis and discrimination of subtypes of these respiratory diseases are quite a challenging task than other chronic illnesses. Metabolomics is the study of metabolic pathways and the measurement of unique biochemical molecules generated in a living system. In the last decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. In this article, we review the current state of the metabolomics of COPD, asthma and CF with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and translation into clinic as diagnostic aids for the choice of patient-specific therapies.