Treatable Traits in Elderly Asthmatics from the Australasian Severe Asthma Network: A Prospective Cohort Study.

BACKGROUND: Data on treatable traits (TTs) in different populations are limited. OBJECTIVE: To assess TTs in elderly patients with asthma and compare them to younger patients, to evaluate the association of TTs with future exacerbations, and to develop an exacerbation prediction model. METHODS: We consecutively recruited 521 participants at West China Hospital, Sichuan University based on the Australasian Severe Asthma Network, classified as elderly (n = 62) and nonelderly (n = 459). Participants underwent a multidimensional assessment to characterize the TTs and were then followed up for 12 months. TTs and their relationship with future exacerbations were described. Based on the TTs and asthma control levels, an exacerbation prediction model was developed, and the overall performance was externally validated in an independent cohort. RESULTS: A total of 38 TTs were assessed. Elderly patients with asthma had more chronic metabolic diseases, fixed airflow limitation, emphysema, and neutrophilic inflammation, whereas nonelderly patients with asthma exhibited more allergic characteristics and psychiatric diseases. Nine traits were associated with increased future exacerbations, of which exacerbation prone, upper respiratory infection-induced asthma attack, cardiovascular disease, diabetes, and depression were the strongest. A model including exacerbation prone, psychiatric disease, cardiovascular disease, upper respiratory infection-induced asthma attack, noneosinophilic inflammation, cachexia, food allergy, and asthma control was developed to predict exacerbation risk and showed good performance. CONCLUSIONS: TTs can be systematically assessed in elderly patients with asthma, some of which are associated with future exacerbations, proving their clinical utility of evaluating them. A model based on TTs can be used to predict exacerbation risk in people with asthma

An examination of the Apo-1/Fas promoter Mva I polymorphism in Japanese patients with multiple sclerosis

BACKGROUND: The Apo-1/Fas (CD95) molecule is an apoptosis-signaling cell surface receptor belonging to the tumor necrosis factor (TNF) receptor family. Both Fas and Fas ligand (FasL) are expressed in activated mature T cells, and prolonged cell activation induces susceptibility to Fas-mediated apoptosis. The Apo-1/Fas gene is located in a chromosomal region that shows linkage in multiple sclerosis (MS) genome screens, and studies indicate that there is aberrant expression of the Apo-1/Fas molecule in MS. METHODS: Mva I polymorphism on the Apo-1/Fas promoter gene was detected by PCR-RFLP from the DNA of 114 Japanese patients with conventional MS and 121 healthy controls. We investigated the association of the Mva I polymorphism in Japanese MS patients using a case-control association study design. RESULTS: We found no evidence that the polymorphism contributes to susceptibility to MS. Furthermore, there was no association between Apo-1/Fas gene polymorphisms and clinical course (relapsing-remitting course or secondary-progressive course). No significant association was observed between Apo-1/Fas gene polymorphisms and the age at disease onset. CONCLUSIONS: Overall, our findings suggest that Apo-1/Fas promoter gene polymorphisms are not conclusively related to susceptibility to MS or the clinical characteristics of Japanese patients with MS

Constraints on Nucleon Decay via "Invisible" Modes from the Sudbury Neutrino Observatory

Data from the Sudbury Neutrino Observatory have been used to constrain the lifetime for nucleon decay to ``invisible'' modes, such as n -> 3 nu. The analysis was based on a search for gamma-rays from the de-excitation of the residual nucleus that would result from the disappearance of either a proton or neutron from O16. A limit of tau_inv > 2 x 10^{29} years is obtained at 90% confidence for either neutron or proton decay modes. This is about an order of magnitude more stringent than previous constraints on invisible proton decay modes and 400 times more stringent than similar neutron modes.Comment: Update includes missing efficiency factor (limits change by factor of 2) Submitted to Physical Review Letter

Factor analysis of self-treatment in diabetes mellitus: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Self-treatment is a treatment of oneself without professional help, which may cause health-related consequences. This investigation examined the self-treatment behaviors in patients with diabetes mellitus in Iran/kashan.</p> <p>Methods</p> <p>The patients who referred to the clinic of diabetes and those who were admitted to the General hospital in the city of Kashan due to diabetes mellitus were asked to participate in this cross-sectional study. For data collection, The 25 item questionnaire of Likert scale type with four scales was used. Factor analysis was performed to define the patterns of self-treatment.</p> <p>Results</p> <p>398 patients participated in the study. The mean age of the study population was 54.9 ± 12.9 years. The majority (97%) had type 2 diabetes. 50% of patients reported self- treatment. The self-treatment score was 45.8 ± 8.8 (25-100). Female gender, lower education and co-morbid illnesses of hypertension, hyperlipidemia and cardiac disease had significant relationship with self-treatment. The factor analysis procedure revealed seven factors that explained the 43% of variation in the self-treatment. These seven factors were categorized as knowledge, deficiencies of formal treatments, available self-treatment methods, physician related factors, the tendency to use herbal remedies, underlying factors such as gender and factors related to diabetes.</p> <p>Conclusions</p> <p>There is a medium tendency for self-treatment in diabetic patients. The assessment of self-treatment practices must be an essential part of patients' management in diabetes care.</p

Cosmogenic neutron production at the Sudbury Neutrino Observatory

Neutrons produced in nuclear interactions initiated by cosmic-ray muons present an irreducible background to many rare-event searches, even in detectors located deep underground. Models for the production of these neutrons have been tested against previous experimental data, but the extrapolation to deeper sites is not well understood. Here we report results from an analysis of cosmogenically produced neutrons at the Sudbury Neutrino Observatory. A specific set of observables are presented, which can be used to benchmark the validity of geant4 physics models. In addition, the cosmogenic neutron yield, in units of 10-4 cm2/(g·μ), is measured to be 7.28±0.09(stat)-1.12+1.59(syst) in pure heavy water and 7.30±0.07(stat)-1.02+1.40(syst) in NaCl-loaded heavy water. These results provide unique insights into this potential background source for experiments at SNOLAB

Improving the physician-patient cardiovascular risk dialogue to improve statin adherence

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to evaluate the effectiveness of a patient education program developed to facilitate statin adherence.</p> <p>Methods</p> <p>A controlled trial was designed to test the effectiveness of a multifaceted patient education program to facilitate statin adherence. The program included a brief, in-office physician counseling kit followed by patient mailings. The primary end point was adherence to filling statin prescriptions during a 120-day period. Patients new to statins enrolled and completed a survey. Data from a national pharmacy claims database were used to track adherence.</p> <p>Results</p> <p>Patients new to statin therapy exposed to a patient counseling and education program achieved a 12.4 higher average number of statin prescription fill days and were 10% more likely to fill prescriptions for at least 120 days (<it>p </it>= .01).</p> <p>Conclusion</p> <p>Brief in-office counseling on cardiovascular risk followed by patient education mailings can be effective in increasing adherence. Physicians found a one-minute counseling tool and pocket guidelines useful in counseling patients.</p

An inflammation-based prognostic score (mGPS) predicts cancer survival independent of tumour site: a Glasgow Inflammation Outcome Study

INTRODUCTION: A selective combination of C-reactive protein and albumin (termed the modified Glasgow Prognostic Score, mGPS) has been shown to have prognostic value, independent of tumour stage, in lung, gastrointestinal and renal cancers. It is also of interest that liver function tests such as bilirubin, alkaline phosphatase and gamma-glutamyl transferase, as well as serum calcium, have also been reported to predict cancer survival. The aim of the present study was to examine the relationship between an inflammation-based prognostic score (mGPS), biochemical parameters, tumour site and survival in a large cohort of patients with cancer. METHODS: Patients (n = 21 669) who had an incidental blood sample taken between 2000 and 2006 for C-reactive protein, albumin and calcium (and liver function tests where available) and a diagnosis of cancer were identified. Of this group 9608 patients who had an ongoing malignant process were studied (sampled within 2 years before diagnosis). Also a subgroup of 5397 sampled at the time of diagnosis (sampled within 2 months prior to diagnosis) were examined. Cancers were grouped by tumour site in accordance with International Classification of Diseases 10 (ICD 10). RESULTS: On follow up, there were 6005 (63%) deaths of which 5122 (53%) were cancer deaths. The median time from blood sampling to diagnosis was 1.4 months. Increasing age, male gender and increasing deprivation was associated with a reduced 5-year overall and cancer-specific survival (all P &lt; 0.001). An elevated mGPS, adjusted calcium, bilirubin, alkaline phosphatase, aspartate transaminase, alanine transaminase and gamma-glutamyl transferase were associated with a reduced 5-year overall and cancer-specific survival (independent of age, sex and deprivation in all patients sampled), as well as within the time of diagnosis subgroup (all P &lt; 0.001). An increasing mGPS was predictive of a reduced cancer-specific survival in all cancers (all P &lt; 0.001). CONCLUSION: The results of the present study indicate that the mGPS is a powerful prognostic factor when compared with other biochemical parameters and independent of tumour site in patients with cancer

A re-randomisation design for clinical trials

Background: Recruitment to clinical trials is often problematic, with many trials failing to recruit to their target sample size. As a result, patient care may be based on suboptimal evidence from underpowered trials or non-randomised studies. Methods: For many conditions patients will require treatment on several occasions, for example, to treat symptoms of an underlying chronic condition (such as migraines, where treatment is required each time a new episode occurs), or until they achieve treatment success (such as fertility, where patients undergo treatment on multiple occasions until they become pregnant). We describe a re-randomisation design for these scenarios, which allows each patient to be independently randomised on multiple occasions. We discuss the circumstances in which this design can be used. Results: The re-randomisation design will give asymptotically unbiased estimates of treatment effect and correct type I error rates under the following conditions: (a) patients are only re-randomised after the follow-up period from their previous randomisation is complete; (b) randomisations for the same patient are performed independently; and (c) the treatment effect is constant across all randomisations. Provided the analysis accounts for correlation between observations from the same patient, this design will typically have higher power than a parallel group trial with an equivalent number of observations. Conclusions: If used appropriately, the re-randomisation design can increase the recruitment rate for clinical trials while still providing an unbiased estimate of treatment effect and correct type I error rates. In many situations, it can increase the power compared to a parallel group design with an equivalent number of observations

Neutrophil swarming and extracellular trap formation play a significant role in Alum adjuvant activity

There are over 6 billion vaccine doses administered each year, most containing aluminium-based adjuvants, yet we still do not have a complete understanding of their mechanisms of action. Recent evidence has identified host DNA and downstream sensing as playing a significant role in aluminium adjuvant (aluminium hydroxide) activity. However, the cellular source of this DNA, how it is sensed by the immune system and the consequences of this for vaccination remains unclear. Here we show that the very early injection site reaction is characterised by inflammatory chemokine production and neutrophil recruitment. Intravital imaging demonstrates that the Alum injection site is a focus of neutrophil swarms and extracellular DNA strands. These strands were confirmed as neutrophil extracellular traps due to their sensitivity to DNAse and absence in mice deficient in peptidylarginine deiminase 4. Further studies in PAD4−/− mice confirmed a significant role for neutrophil extracellular trap formation in the adjuvant activity of Alum. By revealing neutrophils recruited to the site of Alum injection as a source of the DNA that is detected by the immune system this study provides the missing link between Alum injection and the activation of DNA sensors that enhance adjuvant activity, elucidating a key mechanism of action for this important vaccine component

Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells

<p>Abstract</p> <p>Background</p> <p>The ability to predict the spatial frequency of relapses in multiple sclerosis (MS) would enable physicians to decide when to intervene more aggressively and to plan clinical trials more accurately.</p> <p>Methods</p> <p>In the current study our objective was to determine if subsets of genes can predict the time to the next acute relapse in patients with MS. Data-mining and predictive modeling tools were utilized to analyze a gene-expression dataset of 94 non-treated patients; 62 patients with definite MS and 32 patients with clinically isolated syndrome (CIS). The dataset included the expression levels of 10,594 genes and annotated sequences corresponding to 22,215 gene-transcripts that appear in the microarray.</p> <p>Results</p> <p>We designed a two stage predictor. The first stage predictor was based on the expression level of 10 genes, and predicted the time to next relapse with a resolution of 500 days (error rate 0.079, p < 0.001). If the predicted relapse was to occur in less than 500 days, a second stage predictor based on an additional different set of 9 genes was used to give a more accurate estimation of the time till the next relapse (in resolution of 50 days). The error rate of the second stage predictor was 2.3 fold lower than the error rate of random predictions (error rate = 0.35, p < 0.001). The predictors were further evaluated and found effective both for untreated MS patients and for MS patients that subsequently received immunomodulatory treatments after the initial testing (the error rate of the first level predictor was < 0.18 with p < 0.001 for all the patient groups).</p> <p>Conclusion</p> <p>We conclude that gene expression analysis is a valuable tool that can be used in clinical practice to predict future MS disease activity. Similar approach can be also useful for dealing with other autoimmune diseases that characterized by relapsing-remitting nature.</p