The dysfunctional host response to influenza A H7N9: a potential treatment option?

The newly emerging human pathogen influenza A H7N9 represents a potentially major threat to human health. The virus was first shown to be pathogenic in humans in 2013, and outbreaks continue to occur in China to the present time. The current incident mortality rate is disturbingly high despite the frequent use of antiviral therapy and intensive care management. If the virus gains the capacity for efficient person-to-person transmission, a global influenza pandemic could ensue with devastating consequences. In the absence of an effective vaccine, targeted regulation of the host immune response by immune modulators might be considered. Readily available, approved drugs with immune-modulating activities might prove to be a treatment option in combination with existing antiviral agents and supportive care

Meeting the Challenge of Influenza Pandemic Preparedness in Developing Countries

One-sentence summary for table of contents: These countries should consider using inexpensive generic agents to confront the next pandemic

Agreement in the scoring of respiratory events and sleep among international sleep centers.

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Abstract STUDY OBJECTIVES: The American Academy of Sleep Medicine (AASM) guidelines for polysomnography (PSG) scoring are increasingly being adopted worldwide, but the agreement among international centers in scoring respiratory events and sleep stages using these guidelines is unknown. We sought to determine the interrater agreement of PSG scoring among international sleep centers. DESIGN: Prospective study of interrater agreement of PSG scoring. SETTING: Nine center-members of the Sleep Apnea Genetics International Consortium (SAGIC). MEASUREMENTS AND RESULTS: Fifteen previously recorded deidentified PSGs, in European Data Format, were scored by an experienced technologist at each site after they were imported into the locally used analysis software. Each 30-sec epoch was manually scored for sleep stage, arousals, apneas, and hypopneas using the AASM recommended criteria. The computer-derived oxygen desaturation index (ODI) was also recorded. The primary outcome for analysis was the intraclass correlation coefficient (ICC) of the apnea-hypopnea index (AHI). The ICCs of the respiratory variables were: AHI = 0.95 (95% confidence interval: 0.91-0.98), total apneas = 0.77 (0.56-0.87), total hypopneas = 0.80 (0.66-0.91), and ODI = 0.97 (0.93-0.99). The kappa statistics for sleep stages were: wake = 0.78 (0.77-0.79), nonrapid eye movement = 0.77 (0.76-0.78), N1 = 0.31 (0.30-0.32), N2 = 0.60 (0.59-0.61), N3 = 0.67 (0.65-0.69), and rapid eye movement = 0.78 (0.77-0.79). The ICC of the arousal index was 0.68 (0.50-0.85). CONCLUSION: There is strong agreement in the scoring of respiratory events among the SAGIC centers. There is also substantial epoch-by-epoch agreement in scoring sleep variables. Our results suggest that centralized scoring of PSGs may not be necessary in future research collaboration among international sites where experienced, well-trained scorers are involved.NHLBI P01 HL094307 HL093463 Tzagournis Medical Research Endowment Funds of The Ohio State Universit

Компьютерное моделирование поддержки жизненного цикла производства полупроводниковых изделий

В работе рассматриваются проблема моделирования процессов в электронной промышленности как целостной системы. Приводятся результаты математического моделирования реальных данных с предприятия полупроводниковой индустрии Томска. В качестве независимой переменной выступает процент выхода годных изделий, остальные переменные представляют собой технологические параметры и результаты промежуточного контроля на всем протяжении технологического маршрута. Дается алгоритм выявления групп переменных, значимо влияющих на выход годных изделий, и исключения незначимых переменных для построения прогноза. Результаты имеют практическое значение для решения проблемы анализа больших объемов данных в производстве полупроводниковых приборов.The paper deals with the problem of modeling processes in the electronics industry as an integrated system. The results of mathematical modeling of real data from the enterprise of the semiconductor industry of Tomsk are presented. As an independent variable is the percentage of yield of suitable products, the remaining variables are the technological parameters and the results of intermediate control throughout the entire technological route.An algorithm is provided for identifying groups of variables that significantly affect the yield of good products, and eliminating insignificant variables for constructing a forecast. The results are of practical importance for solving the problem of analyzing large amounts of data in the production of semiconductor devices

Plant-made vaccines in support of the Millennium Development Goals

Vaccines are one of the most successful public health achievements of the last century. Systematic immunisation programs have reduced the burden of infectious diseases on a global scale. However, there are limitations to the current technology, which often requires costly infrastructure and long lead times for production. Furthermore, the requirement to keep vaccines within the cold-chain throughout manufacture, transport and storage is often impractical and prohibitively expensive in developing countries—the very regions where vaccines are most needed. In contrast, plant-made vaccines (PMVs) can be produced at a lower cost using basic greenhouse agricultural methods, and do not need to be kept within such narrow temperature ranges. This increases the feasibility of developing countries producing vaccines locally at a small-scale to target the specific needs of the region. Additionally, the ability of plant-production technologies to rapidly produce large quantities of strain-specific vaccine demonstrates their potential use in combating pandemics. PMVs are a proven technology that has the potential to play an important role in increasing global health, both in the context of the 2015 Millennium Development Goals and beyond

A genome-wide association search for type 2 diabetes genes in African Americans.

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes