Human intervention study to assess the effects of supplementation with olive leaf extract on peripheral blood mononuclear cell gene expression

Olive leaf extract (OLE) has been used for many years for its putative health benefits, but, to date, scientific evidence for the basis of these effects has been weak. Although recent literature has described a link between ailments such as cardiovascular disease, diabetes and cancer and a protective effect of polyphenols in the OLE, the mode of action is still unclear. Here, we describe a double-blinded placebo (PBO)-controlled trial, in which gene expression profiles of peripheral blood mononuclear cells from healthy male volunteers (n = 29) were analysed to identify genes that responded to OLE, following an eight-week intervention with 20 mL daily consumption of either OLE or PBO. Differences between groups were determined using an adjusted linear model. Subsequent analyses indicated downregulation of genes important in inflammatory pathways, lipid metabolism and cancer as a result of OLE consumption. Gene expression was verified by real-time PCR for three genes (EGR1, COX-2 and ID3). The results presented here suggest that OLE consumption may result in health benefits through influencing the expression of genes in inflammatory and metabolic pathways. Future studies with a larger study group, including male and female participants, looking into direct effects of OLE on lipid metabolism and inflammation are warranted

Identification of potential anticancer activities of novel ganoderma lucidum extracts using gene expression and pathway network analysis

Ganoderma lucidum (lingzhi) has been used for the general promotion of health in Asia for many centuries. The common method of consumption is to boil lingzhi in water and then drink the liquid. In this study, we examined the potential anticancer activities of G. lucidum submerged in two commonly consumed forms of alcohol in East Asia: malt whiskey and rice wine. The anticancer effect of G. lucidum, using whiskey and rice wine-based extraction methods, has not been previously reported. The growth inhibition of G. lucidum whiskey and rice wine extracts on the prostate cancer cell lines, PC3 and DU145, was determined. Using Affymetrix gene expression assays, several biologically active pathways associated with the anticancer activities of G. lucidum extracts were identified. Using gene expression analysis (real-time polymerase chain reaction [RT-PCR]) and protein analysis (Western blotting), we confirmed the expression of key genes and their associated proteins that were initially identified with Affymetrix gene expression analysis

Tumor Necrosis Factor Receptor Superfamily, Member 1B Haplotypes Increase or Decrease the Risk of Inflammatory Bowel Diseases in a New Zealand Caucasian Population

Inflammatory bowel diseases (IBDs) comprising Crohn disease (CD) and ulcerative colitis (UC) are chronic inflammatory conditions with polygenic susceptibility. Interactions between TNF-alpha and TNF-alpha receptor play a fundamental role in inflammatory response. This study investigates the role that selected single nucleotide polymorphisms (SNPs) and haplotypes in the TNF-alpha receptor (TNSFRSF1B) gene play in the risk of IBD in a New Zealand Caucasian population. DNA samples from 388 CD, 405 UC, 27 indeterminate colitis patients, and 293 randomly selected controls, from Canterbury, New Zealand were screened for 3 common SNPs in TNSFRSF1B: rs1061622 (c.676T > C), rs1061624 (c.*1663A > G), and rs3397 (c.*1690T > C), using TaqMan technologies. Carrying the rs1061624 variant decreased the risk of UC in the left colon (OR 0.73, 95% CI = 0.54–1.00) and of being a smoker at diagnosis (OR 0.62; 95% CI = 0.40–0.96). Carrying the rs3397 variant decreased the risk of penetrating CD (OR 0.62, 95% CI = 0.40–0.95). Three marker haplotype analyses revealed highly significant differences between CD patients and control subjects (χ2 = 29.9, df = 7, P = .0001) and UC cases and controls (χ2 = 46.3, df = 7, P < .0001). We conclude that carrying a 3-marker haplotype in the TNSFRSF1B gene may increase (e.g., haplotype of GGC was 2.9-fold more in the CD or UCpatients) or decrease (e.g., TGT was 0.47-fold less in UC patients) the risk of IBD in a New Zealand Caucasian population

Tumor Necrosis Factor Receptor Superfamily, Member 1B Haplotypes Increase or Decrease the Risk of Inflammatory Bowel Diseases in a New Zealand Caucasian Population

Inflammatory bowel diseases (IBDs) comprising Crohn disease (CD) and ulcerative colitis (UC) are chronic inflammatory conditions with polygenic susceptibility. Interactions between TNF-alpha and TNF-alpha receptor play a fundamental role in inflammatory response. This study investigates the role that selected single nucleotide polymorphisms (SNPs) and haplotypes in the TNF-alpha receptor (TNSFRSF1B) gene play in the risk of IBD in a New Zealand Caucasian population. DNA samples from 388 CD, 405 UC, 27 indeterminate colitis patients, and 293 randomly selected controls, from Canterbury, New Zealand were screened for 3 common SNPs in TNSFRSF1B: rs1061622 (c.676T > C), rs1061624 (c.*1663A > G), and rs3397 (c.*1690T > C), using TaqMan technologies. Carrying the rs1061624 variant decreased the risk of UC in the left colon (OR 0.73, 95% CI = 0.54–1.00) and of being a smoker at diagnosis (OR 0.62; 95% CI = 0.40–0.96). Carrying the rs3397 variant decreased the risk of penetrating CD (OR 0.62, 95% CI = 0.40–0.95). Three marker haplotype analyses revealed highly significant differences between CD patients and control subjects (χ2 = 29.9, df = 7, P = .0001) and UC cases and controls (χ2 = 46.3, df = 7, P < .0001). We conclude that carrying a 3-marker haplotype in the TNSFRSF1B gene may increase (e.g., haplotype of GGC was 2.9-fold more in the CD or UCpatients) or decrease (e.g., TGT was 0.47-fold less in UC patients) the risk of IBD in a New Zealand Caucasian population

Nucleotide-binding oligomerization domain containing 1 (NOD1) haplotypes and single nucleotide polymorphisms modify susceptibility to inflammatory bowel diseases in a New Zealand caucasian population: a case-control study

<p>Abstract</p> <p>Background</p> <p>The nucleotide-binding oligomerization domain containing 1 (<it>NOD1</it>) gene encodes a pattern recognition receptor that senses pathogens, leading to downstream responses characteristic of innate immunity. We investigated the role of <it>NOD1 </it>single nucleotide polymorphisms (SNPs) on IBD risk in a New Zealand Caucasian population, and studied Nod1 expression in response to bacterial invasion in the Caco2 cell line.</p> <p>Findings</p> <p>DNA samples from 388 Crohn's disease (CD), 405 ulcerative colitis (UC), 27 indeterminate colitis patients and 201 randomly selected controls, from Canterbury, New Zealand were screened for 3 common SNPs in <it>NOD1</it>, using the MassARRAY^®iPLEX Gold assay. Transcriptional activation of the protein produced by <it>NOD1 </it>(Nod1) was studied after infection of Caco2 cells with <it>Escherichia coli </it>LF82. Carrying the rs2075818 G allele decreased the risk of CD (OR = 0.66, 95% CI = 0.50–0.88, p < 0.002) but not UC. There was an increased frequency of the three SNP (rs2075818, rs2075822, rs2907748) haplotype, CTG (p = 0.004) and a decreased frequency of the GTG haplotype (p = 0.02).in CD. The rs2075822 CT or TT genotypes were at an increased frequency (genotype p value = 0.02), while the rs2907748 AA or AG genotypes showed decreased frequencies in UC (p = 0.04), but not in CD. Functional assays showed that Nod1 is produced 6 hours after bacterial invasion of the Caco2 cell line.</p> <p>Conclusion</p> <p>The <it>NOD1 </it>gene is important in signalling invasion of colonic cells by pathogenic bacteria, indicative of its' key role in innate immunity. Carrying specific SNPs in this gene significantly modifies the risk of CD and/or UC in a New Zealand Caucasian population.</p

Age of red blood cells and mortality in the critically ill

INTRODUCTION: In critically ill patients, it is uncertain whether exposure to older red blood cells (RBCs) may contribute to mortality. We therefore aimed to evaluate the association between the age of RBCs and outcome in a large unselected cohort of critically ill patients in Australia and New Zealand. We hypothesized that exposure to even a single unit of older RBCs may be associated with an increased risk of death. METHODS: We conducted a prospective, multicenter observational study in 47 ICUs during a 5-week period between August 2008 and September 2008. We included 757 critically ill adult patients receiving at least one unit of RBCs. To test our hypothesis we compared hospital mortality according to quartiles of exposure to maximum age of RBCs without and with adjustment for possible confounding factors. RESULTS: Compared with other quartiles (mean maximum red cell age 22.7 days; mortality 121/568 (21.3%)), patients treated with exposure to the lowest quartile of oldest RBCs (mean maximum red cell age 7.7 days; hospital mortality 25/189 (13.2%)) had an unadjusted absolute risk reduction in hospital mortality of 8.1% (95% confidence interval = 2.2 to 14.0%). After adjustment for Acute Physiology and Chronic Health Evaluation III score, other blood component transfusions, number of RBC transfusions, pretransfusion hemoglobin concentration, and cardiac surgery, the odds ratio for hospital mortality for patients exposed to the older three quartiles compared with the lowest quartile was 2.01 (95% confidence interval = 1.07 to 3.77). CONCLUSIONS: In critically ill patients, in Australia and New Zealand, exposure to older RBCs is independently associated with an increased risk of death

Health care utilization and outcomes in older adults after Traumatic Brain Injury: A CENTER-TBI study

Introduction The incidence of Traumatic Brain Injury (TBI) is increasingly common in older adults aged ≥65 years, forming a growing public health problem. However, older adults are underrepresented in TBI research. Therefore, we aimed to provide an overview of health-care utilization, and of six-month outcomes after TBI and their determinants in older adults who sustained a TBI. Methods We used data from the prospective multi-center Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. In-hospital and post-hospital health care utilization and outcomes were described for patients aged ≥65 years. Ordinal and linear regression analyses were performed to identify determinants of the Glasgow Outcome Scale Extended (GOSE), health-related quality of life (HRQoL), and mental health symptoms six-months post-injury. Results Of 1254 older patients, 45% were admitted to an ICU with a mean length of stay of 9 days. Nearly 30% of the patients received inpatient rehabilitation. In total, 554/1254 older patients completed the six-month follow-up questionnaires. The mortality rate was 9% after mild and 60% after moderate/severe TBI, and full recovery based on GOSE was reported for 44% of patients after mild and 6% after moderate/severe TBI. Higher age and increased injury severity were primarily associated with functional impairment, while pre-injury systemic disease, psychiatric conditions and lower educational level were associated with functional impairment, lower generic and disease-specific HRQoL and mental health symptoms. Conclusion The rate of impairment and disability following TBI in older adults is substantial, and poorer outcomes across domains are associated with worse preinjury health. Nonetheless, a considerable number of patients fully or partially returns to their preinjury functioning. There should not be pessimism about outcomes in older adults who survive.publishedVersio

Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research

No abstract available

Prognostic Models for Global Functional Outcome and Post-Concussion Symptoms Following Mild Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15. We used ordinal logistic regression to model the relationship between predictors and the GOSE, and linear regression to model the relationship between predictors and the Rivermead Post-concussion Symptoms Questionnaire (RPQ) total score. First, we studied a pre-specified Core model. Next, we extended the Core model with other clinical and sociodemographic variables available at presentation (Clinical model). The Clinical model was then extended with variables assessed before discharge from hospital: early post-concussion symptoms, CT variables, biomarkers, or all three categories (extended models). In a subset of patients mostly discharged home from the emergency department, the Clinical model was extended with 2-3–week post-concussion and mental health symptoms. Predictors were selected based on Akaike's Information Criterion. Performance of ordinal models was expressed as a concordance index (C) and performance of linear models as proportion of variance explained (R2). Bootstrap validation was used to correct for optimism. We included 2376 mTBI patients with 6-month GOSE and 1605 patients with 6-month RPQ. The Core and Clinical models for GOSE showed moderate discrimination (C = 0.68 95% confidence interval 0.68 to 0.70 and C = 0.70[0.69 to 0.71], respectively) and injury severity was the strongest predictor. The extended models had better discriminative ability (C = 0.71[0.69 to 0.72] with early symptoms; 0.71[0.70 to 0.72] with CT variables or with blood biomarkers; 0.72[0.71 to 0.73] with all three categories). The performance of models for RPQ was modest (R2 = 4% Core; R2 = 9% Clinical), and extensions with early symptoms increased the R2 to 12%. The 2-3-week models had better performance for both outcomes in the subset of participants with these symptoms measured (C = 0.74 [0.71 to 0.78] vs. C = 0.63[0.61 to 0.67] for GOSE; R2 = 37% vs. 6% for RPQ). In conclusion, the models based on variables available before discharge have moderate performance for the prediction of GOSE and poor performance for the prediction of PPCS. Symptoms assessed at 2-3 weeks are required for better predictive ability of both outcomes. The performance of the proposed models should be examined in independent cohorts.publishedVersio

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations