Molecular interactions of dioxins and DLCs with the ketosteroid receptors: an in silico risk assessment approach

Dioxins and dioxin-like compounds (DLCs) are the ones with poor water solubility and low volatility, resistant to physical, chemical and biological processes, persistent in the environment even under extreme conditions. Due to lipophilic nature, they get adhered to the fatty material and concentrate through biomagnification and bioaccumulation, thereby easily getting incorporated into food chains, paving the way to endocrine disruption via modulation of various human receptors. This in turn leads to certain adverse health effects. In the present study, a total of 100 dioxins and DLCs were taken and their binding pattern was assessed with the ketosteroid receptors, i.e. androgen (hAR), glucocorticoid (hGR), progesterone (hPR) and mineralocorticoid (hMR) in comparison to the corresponding natural steroids and a known endocrine disrupting xenobiotic, Bisphenol A (BPA). Most of the DLCs, particularly those bearing hydroxyl (-OH) group showed considerable affinities with ketosteroid receptors. On comparing D scores of all the dioxins and DLCs against all four receptors, compound 8-hydroxy-3,4-dichlorodibenzofuran(8-OH-DCDF) exhibited least D score of -9.549?kcal mol^?1 against hAR. 3,8-Dihydroxy-2-chlorodibenzofuran(3,8-DiOH-CDF), 4′-hydroxy-2,3,4,5-tetrachlorobiphenyl (4′-OH-TCB) and 4-hydroxy-2,2′,5′-trichlorobiphenyl(4-OH-TCB) also showed comparable molecular interactions with the ketosteroid receptors. These interactions mainly include H-bonding, π–π stacking, hydrophobic, polar and van der Waals’ interactions. In contrast, BPA and some natural ligands tested in this study showed lower binding affinities with these receptors than certain DLCs reported herein, i.e. certain DLCs might be more toxic than the proven toxic agent, BPA. Such studies play a pivotal role in the risk assessment of exposure to dioxins and DLCs on human health.     

Creating conditions for good nursing by attending to the spiritual

biro a.l. (2012) Journal of Nursing Management  20, 1002–1011
Creating conditions for good nursing by attending to the spiritual Aim To note similarities, differences, and gaps in the literature on good nursing and spiritual care. Background Good nursing care is essential for meeting patient health needs. With growing recognition of the role of spirituality in health, understanding spiritual care as it relates to good nursing is important, especially as spiritual care has been recognized as the most neglected area of nursing care. Methods Nursing research, reports and discussion articles from a variety of countries were reviewed on the topics of good nursing, spiritual care and spirituality. Key issues A nurse’s spirituality and the nurse–patient relationship are integral to spiritual care and good nursing. Conclusions There are many commonalities between good nursing and spiritual care. Personal attributes of the nurse are described in similar terms in research on spiritual care and good nursing. Professional attributes common to good nursing and spiritual care are the nurse–patient relationship, assessment skills and communication skills. Implications for nursing management Good nursing through spiritual care is facilitated by personal spirituality, training in spiritual care and a culture that implements changes supportive of spiritual care. Further research is needed to address limitations in the scope of literature.     

Risk assessment of Pakistani individuals for diabetes (RAPID)

ObjectiveTo develop and evaluate a risk score to predict people at high risk of developing type 2 diabetes in Pakistan.MethodologyCross sectional data regarding primary prevention of diabetes in Pakistan. Diabetes risk score was developed by using simple parameters namely age, waist circumference, and family history of diabetes. Odds ratios of the model were used to assign a score value for each variable and the diabetes risk score was calculated as the sum of those scores.ResultsWe externally validated the score using two data from 1264 subjects and 856 subjects aged 25 years and above from two separate studies respectively. Validating this score using the first data from the second screening study gave an area under the receive operator characteristics curve [AROC] of 0.758. A cut point of 4 had a sensitivity of 47.0% and specificity of 88% and in the second data AROC is 0.7 with 44% sensitivity and 89% specificity.ConclusionsA simple diabetes risk score, based on a set of variables can be used for the identification of high risk individuals for early intervention to delay or prevent type 2 diabetes in Pakistani population.