BackgroundThere are multiple studies in different countries regarding the prevalence of vitamin D deficiency. These studies showed high prevalence of vitamin D deficiency in Asian countries. This study tries to elucidate the prevalence of vitamin D deficiency and its influencing factors in population of Tehran.Methods1210 subjects 20–64 years old were randomly selected. 25 (OH) D serum levels were measured. Duration of exposure to sunlight, the type of clothing and level of calcium intake and BMI were quantified based on a questionnaire.ResultsA high percentage of vitamin D deficiency was defined in the study population. Prevalence of severe, moderate and mild Vitamin D deficiency was 9.5%, 57.6% and 14.2% respectively. Vitamin D serum levels had no significant statistical relation with the duration of exposure to sunlight, kind of clothing and BMI. Calcium intake in the normal vitamin D group was significantly higher than the other groups (714.67 ± 330.8 mg/day vs 503.39 ± 303.1, 577.93 ± 304.9,595.84 ± 313.6). Vitamin D serum levels in young and middle aged females were significantly lower than the older group.ConclusionsVitamin D deficiency has a high prevalence in Tehran. In order to avoid complications of vitamin D deficiency, supplemental dietary intake seems essential.

Background: Osteoporosis is an important public health problem in older adults. It is more common in postmenopausal women and not only gives rise to morbidity but also markedly diminishes the quality of life in this population. There is lack of information about the risk factor of osteoporosis in developing countries. In this study we aimed to assess the risk factors for osteoporosis in postmenopausal women from selected BMD centers of two developing Asian countries (Iran and India).

Vitamin D (Vit D) is an essential element for the regulation of serum calcium, phosphate, and alkaline phosphatase (Alk Ph). Because the Vit D serum level is not usually measured directly, Vit D deficiency is diagnosed indirectly by changes in serum calcium, phosphate, and Alk Ph leves. The current study assessed the status of these biochemical parameters in subjects with different degrees of Vit D deficiency. We selected 1,210 subjects, between 20 and 69 years old, randomly from the Tehran population. Subjects with diseases or medications that modified bone metabolism were excluded from the study. Serum 25(OH) D, calcium, phosphate, Alk Ph, and parathyroid hormone (PTH) levels were measured and the status of these biochemical parameters was compared in subjects with different degrees of Vit D deficiency. Vit D deficiency was diagnosed in 79.6% of the subjects. Different degrees of Vit D deficiency were classified as follows: group 1, severe; group 2, moderate; and group 3, mild. Serum PTH levels in the Vit D-deficient groups were significantly higher than that in group 4 (normal Vit D). Serum calcium and phosphate levels in groups 1 and 2 were significantly lower than those in groups 3 and 4. No significant difference was seen in serum Alk Ph in the groups with different degrees of Vit D deficiency. The sensivity for at least one biochemical variable (calcium, phosphorus, or Alk Ph) for the detection of severe, moderate, and mild Vit D deficiency was 24.2%, 13.8%, and 6%, respectively. When the serum 25(OH) D level was reduced to less than 25 nmol/l (groups 1 and 2), the effects of Vit D deficiency on calcium and phosphate levels were obvious. Therefore, the usual biochemical parameters (calcium, phosphate, Alk Ph) alone do not have sufficient sensitivity to detect mild deficiency of Vit D.

Skin as the outer layer covers the body. Wounds can affect this vital organ negatively and disrupt its functions. Wound healing as a biological process is initiated immediately after an injury. This process consists of three stages: inflammation, proliferation, remodeling. Generally, these three stages occur continuously and timely. However, some factors such as infection, obesity and diabetes mellitus can interfere with these stages and impede the normal healing process which results in chronic wounds. Financial burden on both patients and health care systems, negative biologic effect on the patient's general health status and reduction in quality of life are a number of issues which make chronic wounds as a considerable challenge. During recent years, along with advances in the biomedical sciences, various surgical and non-surgical therapeutic methods have been suggested. All of these suggested treatments have their own advantages and disadvantages. Recently, cell-based therapies and regenerative medicine represent promising approaches to wound healing. Accordingly, several types of mesenchymal stem cells have been used in both preclinical and clinical settings for the treatment of wounds. Adipose-derived stromal cells are a cost-effective source of mesenchymal stem cells in wound management which can be easily harvest from adipose tissues through the less invasive processes with high yield rates. In addition, their ability to secrete multiple cytokines and growth factors, and differentiation into skin cells make them an ideal cell type to use in wound treatment. This is a concise overview on the application of adipose-derived stromal cells in wound healing and their role in the treatment of chronic wounds.

Background Non-alcoholic fatty liver disease (NAFLD) is much more frequent and more severe, including cirrhosis, hepatocellular carcinoma in patients with type 2 diabetes. Coffee is a complex beverage with hundreds of compounds whereas caffeine and chlorogenic acid are the most abundant bioactive compounds. The published epidemiological data demonstrating beneficial associations between all categories of coffee exposure and ranges of liver outcomes are rapidly growing; however, the main contributors and cause-effect relationships have not yet been elucidated. To address existing knowledge gaps, we sought to determine the efficacy and safety of 6 months chlorogenic acid and/or caffeine supplementation in patients with type 2 diabetes affected by NAFLD. Methods This trial was carried out at two Diabetes Centers to assess the effects of supplementation with daily doses of 200 mg chlorogenic acid, 200 mg caffeine, 200 mg chlorogenic acid plus 200 mg caffeine or placebo (starch) in patients with type 2 diabetes and NAFLD. The primary endpoint was reduction of hepatic fat and stiffness measured by FibroScan, and changes in serum hepatic enzymes and cytokeratin − 18 (CK-18) levels. Secondary endpoints were improvements in metabolic (including fasting glucose, homeostasis model assessment-estimated insulin resistance (HOMA-IR), hemoglobin A1c (HBA1C), C-peptide, insulin and lipid profiles) and inflammatory (including nuclear factor k-B (NF-KB), tumor necrosis factor (TNF-α), high sensitive- C reactive protein(hs-CRP)) parameters from baseline to the end of treatment. Results Neither chlorogenic acid nor caffeine was superior to placebo in attenuation of the hepatic fat and stiffness and other hepatic outcomes in patients with diabetes and NAFLD. Except for the lower level of total cholesterol in caffeine group (p = 0.04), and higher level of insulin in chlorogenic acid plus caffeine group (p = 0.01) compared with placebo, there were no significant differences among the treatment groups. Conclusion These findings do not recommend caffeine and/or chlorogenic acid to treat NAFLD in type 2 diabetes patients. Trial registration IRCT201707024010N21. Registered 14 September 2017.

A new series of biscoumarin derivatives 3a-n were synthesized and evaluated for their α-glucosidase inhibitory activities. The reaction of the 4aminocoumarin with benzaldehyde derivatives led to the formation of the title compounds in good yields. All the synthesized compounds showed potent αglucosidase inhibitory activity with IC50 ranging from 20.0 ± 0.7 to180.1 ± 0.8 µM, in comparison with acarbose as the standard drug (IC50 = 750.0 1.5 µM). Among the synthesized compounds, 3,3'-(p-tolylmethylene)bis(4-amino-2Hchromen-2-one) 3c was found to be the most active compound with an IC50 value of 20.0 ± 0.7 µM. Kinetic study exhibited that compound 3c was a competitive inhibitor against α-glucosidase (Ki = 22.4 µM). In silico docking study for the most potent compound 3c was also performed.

Cancer is defined as a large group of diseases that is associated with abnormal cell growth, uncontrollable cell division, and may tend to impinge on other tissues of the body by different mechanisms through metastasis. What makes cancer so important is that the cancer incidence rate is growing worldwide which can have major health, economic, and even social impacts on both patients and the governments. Thereby, the early cancer prognosis, diagnosis, and treatment can play a crucial role at the front line of combating cancer. The onset and progression of cancer can occur under the influence of complicated mechanisms and some alterations in the level of genome, proteome, transcriptome, metabolome etc. Consequently, the advent of omics science and its broad research branches (such as genomics, proteomics, transcriptomics, metabolomics, and so forth) as revolutionary biological approaches have opened new doors to the comprehensive perception of the cancer landscape. Due to the complexities of the formation and development of cancer, the study of mechanisms underlying cancer has gone beyond just one field of the omics arena. Therefore, making a connection between the resultant data from different branches of omics science and examining them in a multi-omics field can pave the way for facilitating the discovery of novel prognostic, diagnostic, and therapeutic approaches. As the volume and complexity of data from the omics studies in cancer are increasing dramatically, the use of leading-edge technologies such as machine learning can have a promising role in the assessments of cancer research resultant data. Machine learning is categorized as a subset of artificial intelligence which aims to data parsing, classification, and data pattern identification by applying statistical methods and algorithms. This acquired knowledge subsequently allows computers to learn and improve accurate predictions through experiences from data processing. In this context, the application of machine learning, as a novel computational technology offers new opportunities for achieving in-depth knowledge of cancer by analysis of resultant data from multi-omics studies. Therefore, it can be concluded that the use of artificial intelligence technologies such as machine learning can have revolutionary roles in the fight against cancer.

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