The central dogma of molecular biology states that the flow of genetic information moves from DNA to RNA to protein. However, in the last decade this dogma has been challenged by new findings on ...non-coding RNAs (ncRNAs) such as microRNAs (miRNAs). More recently, long non-coding RNAs (lncRNAs) have attracted much attention due to their large number and biological significance. Many lncRNAs have been identified as mapping to regulatory elements including gene promoters and enhancers, ultraconserved regions and intergenic regions of protein-coding genes. Yet, the biological function and molecular mechanisms of lncRNA in human diseases in general and cancer in particular remain largely unknown. Data from the literature suggest that lncRNA, often via interaction with proteins, functions in specific genomic loci or use their own transcription loci for regulatory activity. In this review, we summarize recent findings supporting the importance of DNA loci in lncRNA function and the underlying molecular mechanisms via cis or trans regulation, and discuss their implications in cancer. In addition, we use the 8q24 genomic locus, a region containing interactive SNPs, DNA regulatory elements and lncRNAs, as an example to illustrate how single-nucleotide polymorphism (SNP) located within lncRNAs may be functionally associated with the individual's susceptibility to cancer.
Objective:
Narcolepsy is caused by the loss of hypocretin/orexin neurons in the hypothalamus, which is likely the result of an autoimmune process. Recently, concern has been raised over reports of ...narcolepsy in northern Europe following H1N1 vaccination.
Methods:
The study is a retrospective analysis of narcolepsy onset in subjects diagnosed in Beijing, China (1998–2010). Self‐reported month and year of onset were collected from 629 patients (86% children). Graphical presentation, autocorrelations, chi‐square, and Fourier analysis were used to assess monthly variation in onset. Finally, 182 patients having developed narcolepsy after October 2009 were asked for vaccination history.
Results:
The occurrence of narcolepsy onset was seasonal, significantly influenced by month and calendar year. Onset was least frequent in November and most frequent in April, with a 6.7‐fold increase from trough to peak. Studying year‐to‐year variation, we found a 3‐fold increase in narcolepsy onset following the 2009 H1N1 winter influenza pandemic. The increase is unlikely to be explained by increased vaccination, as only 8 of 142 (5.6%) patients recalled receiving an H1N1 vaccination. Cross‐correlation indicated a significant 5‐ to 7‐month delay between the seasonal peak in influenza/cold or H1N1 infections and peak in narcolepsy onset occurrences.
Interpretation:
In China, narcolepsy onset is highly correlated with seasonal and annual patterns of upper airway infections, including H1N1 influenza. In 2010, the peak seasonal onset of narcolepsy was phase delayed by 6 months relative to winter H1N1 infections, and the correlation was independent of H1N1 vaccination in the majority of the sample. ANN NEUROL 2011;
ABSTRACT We report the results of the statistical analysis of planetary signals discovered in MOA-II microlensing survey alert system events from 2007 to 2012. We determine the survey sensitivity as ...a function of planet-star mass ratio, q, and projected planet-star separation, s, in Einstein radius units. We find that the mass-ratio function is not a single power law, but has a change in slope at q ∼ 10−4, corresponding to ∼20 M⊕ for the median host-star mass of ∼0.6 . We find significant planetary signals in 23 of the 1474 alert events that are well-characterized by the MOA-II survey data alone. Data from other groups are used only to characterize planetary signals that have been identified in the MOA data alone. The distribution of mass ratios and separations of the planets found in our sample are well fit by a broken power-law model of the form for q > qbr and for q < qbr, where qbr is the mass ratio of the break. We also combine this analysis with the previous analyses of Gould et al. and Cassan et al., bringing the total sample to 30 planets. This combined analysis yields , n = −0.93 0.13, , and for qbr 1.7 × 10−4. The unbroken power-law model is disfavored with a p-value of 0.0022, which corresponds to a Bayes factor of 27 favoring the broken power-law model. These results imply that cold Neptunes are likely to be the most common type of planets beyond the snow line.
The Positive Matrix Factorization (PMF) receptor model and the Observation Based Model (OBM) were combined to analyze volatile organic compound (VOC) data collected at a suburban site (WQS) in the ...PRD region. The purposes are to estimate the VOC source apportionment and investigate the contributions of these sources and species of these sources to the O3 formation in PRD. Ten VOC sources were identified. We further applied the PMF-extracted concentrations of these 10 sources into the OBM and found "solvent usage 1", "diesel vehicular emissions" and "biomass/biofuel burning" contributed most to the O3 formation at WQS. Among these three sources, higher Relative Incremental Reactivity (RIR)-weighted values of ethene, toluene and m/p-xylene indicated that they were mainly responsible for local O3 formation in the region. Sensitivity analysis revealed that the sources of "diesel vehicular emissions", "biomass/biofuel burning" and "solvent usage 1" had low uncertainties whereas "gasoline evaporation" showed the highest uncertainty.
► Ten sources of VOCs were identified by the PMF receptor model in the PRD region. ► In terms of mass percentage, solvent was the largest contributor, followed by vehicle emissions. ► Solvent, diesel vehicles and biomass/biofuel burning were the top three VOC contributors to O3 formation. ► Among these three sources, ethene, toluene and m/p-xylene were responsible for O3 formation. ► Biomass/biofuel burning had low uncertainty whereas gasoline evaporation showed high uncertainty.
Solvent usage, diesel vehicular emissions and biomass/biofuel burning were the major contributors to the photochemical O3 formation in the PRD region.
Abstract
Aims
Renal inflammation, leading to fibrosis and impaired function is a major contributor to the development of hypertension. The NLRP3 inflammasome mediates inflammation in several chronic ...diseases by processing the cytokines pro-interleukin (IL)-1β and pro-IL-18. In this study, we investigated whether MCC950, a recently-identified inhibitor of NLRP3 activity, reduces blood pressure (BP), renal inflammation, fibrosis and dysfunction in mice with established hypertension.
Methods and results
C57BL6/J mice were made hypertensive by uninephrectomy and treatment with deoxycorticosterone acetate (2.4 mg/day, s.c.) and 0.9% NaCl in the drinking water (1K/DOCA/salt). Normotensive controls were uninephrectomized and received normal drinking water. Ten days later, mice were treated with MCC950 (10 mg/kg/day, s.c.) or vehicle (saline, s.c.) for up to 25 days. BP was monitored by tail-cuff or radiotelemetry; renal function by biochemical analysis of 24-h urine collections; and kidney inflammation/pathology was assessed by real-time PCR for inflammatory gene expression, flow cytometry for leucocyte influx, and Picrosirius red histology for collagen. Over the 10 days post-surgery, 1K/DOCA/salt-treated mice became hypertensive, developed impaired renal function, and displayed elevated renal levels of inflammatory markers, collagen and immune cells. MCC950 treatment from day 10 attenuated 1K/DOCA/salt-induced increases in renal expression of inflammasome subunits (NLRP3, ASC, pro-caspase-1) and inflammatory/injury markers (pro-IL-18, pro-IL-1β, IL-17A, TNF-α, osteopontin, ICAM-1, VCAM-1, CCL2, vimentin), each by 25–40%. MCC950 reduced interstitial collagen and accumulation of certain leucocyte subsets in kidneys of 1K/DOCA/salt-treated mice, including CD206+ (M2-like) macrophages and interferon-gamma-producing T cells. Finally, MCC950 partially reversed 1K/DOCA/salt-induced elevations in BP, urine output, osmolality, Na+, and albuminuria (each by 20–25%). None of the above parameters were altered by MCC950 in normotensive mice.
Conclusion
MCC950 was effective at reducing BP and limiting renal inflammation, fibrosis and dysfunction in mice with established hypertension. This study provides proof-of-concept that pharmacological inhibition of the NLRP3 inflammasome is a viable anti-hypertensive strategy.
Summary Background & aims Body composition measurement is a valuable tool for assessing nutritional status and physical fitness in a variety of clinical settings. Although bioimpedance analysis (BIA) ...can easily assess body composition, its accuracy remains unclear. We examined the accuracy of direct segmental multi-frequency BIA technique (DSM-BIA) in assessing different body composition parameters, using dual energy X-ray absorptiometry (DEXA) as a reference standard. Methods A total of 484 middle-aged participants from the Leiden Longevity Study were recruited. Agreements between DSM-BIA and DEXA for total and segmental body composition quantification were assessed using intraclass correlation coefficients and Bland–Altman plots. Results Excellent agreements were observed between both techniques in whole body lean mass (ICC female = 0.95, ICC men = 0.96), fat mass (ICC female = 0.97, ICC male = 0.93) and percentage body fat (ICC female = 0.93, ICC male = 0.88) measurements. Similarly, Bland–Altman plots revealed narrow limits of agreements with small biases noted for the whole body lean mass quantification but relatively wider limits for fat mass and percentage body fat quantifications. In segmental lean muscle mass quantification, excellent agreements between methods were demonstrated for the upper limbs (ICC female≥0.91, ICC men≥0.87) and lower limbs (ICC female≥0.83, ICC male≥0.85), with good agreements shown for the trunk measurements (ICC female = 0.73, ICC male = 0.70). Conclusions DSM-BIA is a valid tool for the assessments of total body and segmental body composition in the general middle-aged population, particularly for the quantification of body lean mass.
There is a growing attention toward personalized medicine. This is led by a fundamental shift from the 'one size fits all' paradigm for treatment of patients with conditions or predisposition to ...diseases, to one that embraces novel approaches, such as tailored target therapies, to achieve the best possible outcomes. Driven by these, several national and international genome projects have been initiated to reap the benefits of personalized medicine. Exome and targeted sequencing provide a balance between cost and benefit, in contrast to whole genome sequencing (WGS). Whole exome sequencing (WES) targets approximately 3% of the whole genome, which is the basis for protein-coding genes. Nonetheless, it has the characteristics of big data in large deployment. Herein, the application of WES and its relevance in advancing personalized medicine is reviewed. WES is mapped to Big Data "10 Vs" and the resulting challenges discussed. Application of existing biological databases and bioinformatics tools to address the bottleneck in data processing and analysis are presented, including the need for new generation big data analytics for the multi-omics challenges of personalized medicine. This includes the incorporation of artificial intelligence (AI) in the clinical utility landscape of genomic information, and future consideration to create a new frontier toward advancing the field of personalized medicine.
Gamma distribution is widely used to model lifetime data in reliability and survival analysis. In the context of one-shot device testing, encountered commonly in testing devices such as munitions, ...rockets, and automobile air-bags, either left- or right-censored data are collected instead of actual lifetimes of the devices under test. The destructive nature of one-shot devices makes it difficult to collect sufficient lifetime information on the devices. For this reason, accelerated life-tests are commonly used in which the test devices are subjected to conditions in excess of its normal use-condition in order to induce more failures, so as to obtain more lifetime information within a relatively short period of time. In this paper, we discuss the analysis of one-shot device testing data under accelerated life-tests based on gamma distribution. Both scale and shape parameters of the gamma distribution are related to stress factors through log–linear link functions. Since lifetimes of devices under this test are censored, the EM algorithm is developed here for the estimation of the model parameters. The inference on the reliability at a specific mission time as well as on the mean lifetime of the devices is also developed. Moreover, by using missing information principle, the asymptotic variance–covariance matrix of the maximum likelihood estimates under the EM framework is determined, and is then used to construct asymptotic confidence intervals for the parameters of interest. For the reliability at a specific mission time and also for the mean lifetime of the devices, transformation approaches are proposed for the construction of confidence intervals. These confidence intervals are then compared through a simulation study in terms of coverage probabilities and average widths. Recommendations are then made for an appropriate approach for the construction of confidence intervals for different sample sizes and different levels of reliability. A distance-based statistic is suggested for testing the validity of the model to an observed data. Finally, since current status data with covariates in survival analysis and one-shot device testing data with stress factors in reliability analysis share the same data structure, a real data from a toxicological study is used to illustrate the developed methods.
Three-dimensional (3D) printing technology has received great attention in the past decades in both academia and industry because of its advantages such as customized fabrication, low manufacturing ...cost, unprecedented capability for complex geometry, and short fabrication period. 3D printing of metals with controllable structures represents a state-of-the-art technology that enables the development of metallic implants for biomedical applications. This review discusses currently existing 3D printing techniques and their applications in developing metallic medical implants and devices. Perspective about the current challenges and future directions for development of this technology is also presented.
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