Reconnecting the Sciences

During the last three years at the Illinois Mathematics and Science Academy, we have been working on a partial reconstruction of Whitehead\u27s one subject matter, a course reconnecting biology, chemistry, earth and space sciences, and physics into an Integrated Science program

Impact of Genetic Polymorphisms on Phenytoin Pharmacokinetics and Clinical Outcomes in the Middle East and North Africa Region

Background Genetic polymorphisms are known to influence outcomes with phenytoin yet effects in the Middle East and North Africa region are poorly understood. Objectives The objective of this systematic review was to evaluate the impact of genetic polymorphisms on phenytoin pharmacokinetics and clinical outcomes in populations originating from the Middle East and North Africa region, and to characterize genotypic and allelic frequencies within the region for genetic polymorphisms assessed. Methods MEDLINE (1946–3 May, 2017), EMBASE (1974–3 May, 2017), Pharmacogenomics Knowledge Base, and Public Health Genomics Knowledge Base online databases were searched. Studies were included if genotyping and analyses of phenytoin pharmacokinetics were performed in patients of the Middle East and North Africa region. Study quality was assessed using a National Institutes of Health assessment tool. A secondary search identified studies reporting genotypic and allelic frequencies of assessed genetic polymorphisms within the Middle East and North Africa region. Results Five studies met the inclusion criteria. CYP2C9, CYP2C19, and multidrug resistance protein 1 C3435T variants were evaluated. While CYP2C9*2 and *3 variants significantly reduced phenytoin metabolism, the impacts of CYP2C19*2 and *3 variants were unclear. The multidrug resistance protein 1 CC genotype was associated with drug-resistant epilepsy, but reported impacts on phenytoin pharmacokinetics were conflicting. Appreciable variability in minor allele frequencies existed both between and within countries of the Middle East and North Africa region. Conclusions CYP2C9 decrease-of-function alleles altered phenytoin pharmacokinetics in patients originating from the Middle East and North Africa region. The impacts of CYP2C19 and multidrug resistance protein 1 C3435T variants on phenytoin pharmacokinetic and clinical outcomes are unclear and require further investigation. Future research should focus on the clinical outcomes associated with phenytoin therapy.The quality of each study included in the primary review was assessed by two reviewers (RD, KW) using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, from the National Institutes of Health, National Heart, Lung, and Blood Institute [16].Scopu

Review conclusions by Ernst and Canter regarding spinal manipulation refuted

In the April 2006 issue of the Journal of Royal Society of Medicine, Ernst and Canter authored a review of the most recent systematic reviews on the effectiveness of spinal manipulation for any condition. The authors concluded that, except for back pain, spinal manipulation is not an effective intervention for any condition and, because of potential side effects, cannot be recommended for use at all in clinical practice. Based on a critical appraisal of their review, the authors of this commentary seriously challenge the conclusions by Ernst and Canter, who did not adhere to standard systematic review methodology, thus threatening the validity of their conclusions. There was no systematic assessment of the literature pertaining to the hazards of manipulation, including comparison to other therapies. Hence, their claim that the risks of manipulation outweigh the benefits, and thus spinal manipulation cannot be recommended as treatment for any condition, was not supported by the data analyzed. Their conclusions are misleading and not based on evidence that allow discrediting of a large body of professionals using spinal manipulation

Roadmap on optical energy conversion

For decades, progress in the field of optical (including solar) energy conversion was dominated by advances in the conventional concentrating optics and materials design. In recent years, however, conceptual and technological breakthroughs in the fields of nanophotonics and plasmonics combined with a better understanding of the thermodynamics of the photon energy-conversion processes reshaped the landscape of energy-conversion schemes and devices. Nanostructured devices and materials that make use of size quantization effects to manipulate photon density of states offer a way to overcome the conventional light absorption limits. Novel optical spectrum splitting and photon-recycling schemes reduce the entropy production in the optical energy-conversion platforms and boost their efficiencies. Optical design concepts are rapidly expanding into the infrared energy band, offering new approaches to harvest waste heat, to reduce the thermal emission losses, and to achieve noncontact radiative cooling of solar cells as well as of optical and electronic circuitries. Light–matter interaction enabled by nanophotonics and plasmonics underlie the performance of the third- and fourth-generation energy-conversion devices, including up- and down-conversion of photon energy, near-field radiative energy transfer, and hot electron generation and harvesting. Finally, the increased market penetration of alternative solar energy-conversion technologies amplifies the role of cost-driven and environmental considerations. This roadmap on optical energy conversion provides a snapshot of the state of the art in optical energy conversion, remaining challenges, and most promising approaches to address these challenges. Leading experts authored 19 focused short sections of the roadmap where they share their vision on a specific aspect of this burgeoning research field. The roadmap opens up with a tutorial section, which introduces major concepts and terminology. It is our hope that the roadmap will serve as an important resource for the scientific community, new generations of researchers, funding agencies, industry experts, and investors.United States. Department of Energy (DE-AC36-086038308

The association of cardioprotective medications with pneumonia-related outcomes

Introduction: Little research has examined whether cardiovascular medications, other than statins, are associated with improved outcomes after pneumonia. Our aim was to examine the association between the use of beta-blockers, statins, angiotensin converting enzyme (ACE) inhibitors, and angiotensin II receptor blockers (ARBs) with pneumonia-related outcomes. Materials and Methods: We conducted a retrospective population-based study on male patients ≥65 years of age hospitalized with pneumonia and who did not have pre-existing cardiac disease. Our primary analyses were multilevel regression models that examined the association between cardiovascular medication classes and either mortality or cardiovascular events. Results: Our cohort included 21,985 patients: 22% died within 90 days of admission, and 22% had a cardiac event within 90 days. The cardiovascular medications studied that were associated with decreased 90-day mortality included: statins (OR 0.70, 95% CI 0.63-0.77), ACE inhibitors (OR 0.82, 95% CI 0.74-0.91), and ARBs (OR 0.58, 95% CI 0.44-0.77). However, none of the medications were significantly associated with decreased cardiovascular events. Discussion: While statins, ACE inhibitors, and ARBs, were associated with decreased mortality, there was no significant association with decreased CV events. These results indicate that this decreased mortality is unlikely due to their potential cardioprotective effects

Markers of Dysglycaemia and Risk of Coronary Heart Disease in People without Diabetes: Reykjavik Prospective Study and Systematic Review

BACKGROUND: Associations between circulating markers of dysglycaemia and coronary heart disease (CHD) risk in people without diabetes have not been reliably characterised. We report new data from a prospective study and a systematic review to help quantify these associations. METHODS AND FINDINGS: Fasting and post-load glucose levels were measured in 18,569 participants in the population-based Reykjavik study, yielding 4,664 incident CHD outcomes during 23.5 y of mean follow-up. In people with no known history of diabetes at the baseline survey, the hazard ratio (HR) for CHD, adjusted for several conventional risk factors, was 2.37 (95% CI 1.79-3.14) in individuals with fasting glucose > or = 7.0 mmol/l compared to those or = 7 mmol/l at baseline were excluded, relative risks for CHD, adjusted for several conventional risk factors, were: 1.06 (1.00-1.12) per 1 mmol/l higher fasting glucose (23 cohorts, 10,808 cases, 255,171 participants); 1.05 (1.03-1.07) per 1 mmol/l higher post-load glucose (15 cohorts, 12,652 cases, 102,382 participants); and 1.20 (1.10-1.31) per 1% higher HbA(1c) (9 cohorts, 1639 cases, 49,099 participants). CONCLUSIONS: In the Reykjavik Study and a meta-analysis of other Western prospective studies, fasting and post-load glucose levels were modestly associated with CHD risk in people without diabetes. The meta-analysis suggested a somewhat stronger association between HbA(1c) levels and CHD risk

Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (Cindex) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction