Effect of Multi-sensory Stimulation on Neuromuscular Development of Premature Infants

Background: preterm birth is considered as a risk factor for developmental disabilities, which can lead to long-term effects on the nervous system of children.Objectives: The aim of this study was to determine the effect of multi-sensory stimulation on neurodevelopment of premature infants.Materials & Methods: In this two-group double-blind clinical trial conducted from June to August 2016 in Iran, 80 preterm infants were randomly divided into two groups. The Intervention group received multisensory stimulation for 12 min per session, 5 sessions per wk along with routine NICU care the control group received ward's routine care. Neuromuscular Maturity each infant was assessed by New Ballard Score.Results: The intervention group showed higher Neuromuscular Maturity compared to the control group. The Posture, Arm Recoil, Popliteal angle and Heel to ear were statistically significant between the groups.Conclusions: The results shows that Multi-sensory stimulation can have beneficial effects on the development of neuromuscular in premature infants.Keyword: Multisensory stimulation. Neurodevelopmen. premature infant

In vitro percutaneous penetration test overview

Skin is a detailed, organized, and intricate niche in the human body. Topical and transdermal drugs are unique, in that their absorption is quite different from other routes of administration (oral, intramuscular, intravenous, etc.,.). A robust amount of research is required to approve the use of a drug—in vivo, in vitro, and ex vivo studies collectively help manufacturers and government agencies with approval of various compounds. Use of human and animal studies poses ethical and financial concerns, making samples difficult to use. In vitro and ex vivo methods have improved over the past several decades—results show relevance when compared to in vivo methods. The history of testing is discussed, followed by a detailed account of known complexities of skin and the current state of percutaneous penetration

Association of dietary energy density with cardiometabolic risk factors and metabolic syndrome in Tehranian older adults

Introduction: The objective of this study was to evaluate the association between the consumption of an energy-dense diet and cardiometabolic risk factors in Iranian older adults. Methods: This cross-sectional study was conducted on 226 older adults who were living in Tehran, Iran. Dietary energy density (DED) was calculated as energy per weight of food, kcal/g. The usual intake of participants was measured using a validated semi-quantitative food frequency questionnaire. Anthropometric measurements, fasting blood sugar, serum lipid profile and blood pressure and were assessed. The metabolic syndrome was defined according to National Cholesterol Education Program Adult Treatment Panel-III (NCEP ATP III). Results: Those who were in the third tertile of DED compared to the first tertile had 19% lower odds of having the cardiometabolic risk factors and metabolic syndrome (MetS) 0.81 (0.39,1.68) but the association was no significant (P=0.58). There was a significant inverse association between DED and systolic blood pressure (SBP) (β=-0.14, P=0.03) and diastolic blood pressure (DBP) (β=-0.17, P=0.01). We did not find any significant association between intake of energy-dense foods and serum levels of triglyceride (TG) (P=0.62), fasting blood sugar (FBS) (P=0.06), high-density lipoprotein (HDL) (P=0.72) and waist circumference (WC) (P=0.28). Conclusion: DED is negatively associated with SBP and DBP in Iranian older adults. Prospective studies are needed to establish a causal link between DED and MetS and risk factors of cardiovascular disease (CVD)

The association between plant-based diet indices and metabolic syndrome in Iranian older adults

BACKGROUND: We investigated the association between plant-based diets indices - an overall plant-based diet index; a healthful plant-based diet index; and an unhealthful plant-based diet index - and metabolic syndrome among Iranian older adults.AIM: We aimed to examine the relationship between plant-based diet indices and metabolic syndrome.METHODS: This cross-sectional study included 178 older adults (51 men and 127 women), with a mean age of 67.04 (60-83) who were referred to health centers in Tehran, Iran. Blood and urine samples were collected to measure serum total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. We created an overall plant-based diet index, healthful plant-based diet index, and unhealthful plant-based diet index from semi-quantitative food-frequency questionnaire data. Anthropometric measures were done.RESULTS: Our crude model results showed that triglycerides, systolic and diastolic blood pressure, fasting blood sugar, high-density lipoprotein cholesterol, and waist circumference did not significantly differ between tertiles of plant-based diet index and healthful plant-based diet index; also triglycerides, systolic and diastolic blood pressure, fasting blood sugar, and waist circumference did not significantly differ between tertiles of unhealthful plant-based diet index, but high-density lipoprotein cholesterol significantly differed between tertiles of unhealthful plant-based diet index. After adjusting for confounders the results remained non-significant for plant-based diet index but high-density lipoprotein cholesterol was significant for healthful and unhealthful plant-based diet indices. There was also no significant association between plant-based diet index (OR: 1.11; 95% CI: 0.53-2.33), healthful plant-based diet index (OR: 0.81; 95% CI: 0.39-1.68), and unhealthful plant-based diet index (OR: 0.81; 95% CI: 0.38-1.72) with metabolic syndrome, even after adjustment for confounders.CONCLUSIONS: Our findings showed that plant-based diets are not significantly associated with risk of metabolic syndrome in older adults. To confirm the veracity of these findings, more studies should be conducted.</p

Increased serum potassium affects renal outcomes: a post hoc analysis of the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) trial

To assess the effect of an angiotensin receptor blocker (ARB) on serum potassium and the effect of a serum potassium change on renal outcomes in patients with type 2 diabetes and nephropathy. We performed a post hoc analysis in patients with type 2 diabetes participating in the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) study. Renal outcomes were defined as a composite of doubling of serum creatinine or end-stage renal disease. At month 6, 259 (38.4%) and 73 (10.8%) patients in the losartan group and 151 (22.8%) and 34 (5.1%) patients in the placebo group had serum potassium a parts per thousand yen5.0 mmol/l and a parts per thousand yen5.5 mmol/l, (p <0.001), respectively. Losartan was an independent predictor for serum potassium a parts per thousand yen5.0 mmol/l at month 6 (OR 2.8; 95% CI 2.0-3.9). Serum potassium at month 6 a parts per thousand yen 5.0 mmol/l was in turn associated with increased risk for renal events (HR 1.22; 95% CI 1.00-1.50), independent of other risk factors. Adjustment of the overall treatment effects for serum potassium augmented losartan's renoprotective effect from 21% (6-34%) to 35% (20-48%), suggesting that the renoprotective effects of losartan are offset by its effect on serum potassium. In this study, we found that treatment with the ARB losartan is associated with a high risk of increased serum potassium levels, which is in turn associated with an increased risk of renal outcomes in patients with diabetes and nephropathy. Whether additional management of high serum potassium would further increase the renal protective properties of losartan is an important clinical question

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (ly-. ing bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine -learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sen-sitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential