63 research outputs found
Toxicity of Waterpipe Tobacco Smoking: the Role of Flavors, Sweeteners, Humectants, and Charcoal
Waterpipe tobacco (WPT) smoking is a public health concern, particularly among youth and young adults. The global spread of WPT use has surged since the introduction of pre-packaged flavored and sweetened WPT, which is widely marketed as a safer tobacco alternative. Besides flavorants and sugars, WPT additives include humectants, which enhance the moisture and sweetness of WPT, act as solvents for flavors, and impart smoothness to the smoke, thus increasing appeal to users. In the United States (U.S.), unlike cigarette tobacco flavoring (with the exception of menthol), there is no FDA product standard or policy in place prohibiting sales of flavored WPT. Research has shown that the numerous fruit, candy, and alcohol flavors added to WPT entice individuals to experience those flavors, putting them at an increased risk of exposure to WPT smoke-related toxicants. Additionally, burning charcoal briquettes-used as a heating source for WPT-contributes to the harmful health effects of WPT smoking. This review presents existing evidence on the potential toxicity resulting from humectants, sugars, and flavorants in WPT, and from the charcoal used to heat WPT. The review discusses relevant studies of inhalation toxicity in animal models and of biomarkers of exposure in humans. Current evidence suggests that more data are needed on toxicant emissions in WPT smoke to inform effective tobacco regulation to mitigate the adverse impact of WPT use on human health
A Review of the Toxicity of Ingredients in E-Cigarettes, Including Those Ingredients Having the Fda\u27s generally Recognized As Safe (GRAS) Regulatory Status for Use in Food.
Some firms and marketers of electronic cigarettes (e-cigarettes; a type of electronic nicotine delivery system (ENDS)) and refill liquids (e-liquids) have made claims about the safety of ingredients used in their products based on the term GRAS or Generally Recognized As Safe (GRAS). However, GRAS is a provision within the definition of a food additive under section 201(s) (21 U.S.C. 321(s)) of the U.S. Federal Food Drug and Cosmetic Act (FD&C Act). Food additives and GRAS substances are by the FD&C Act definition intended for use in food, thus safety is based on oral consumption; the term GRAS cannot serve as an indicator of the toxicity of e-cigarette ingredients when aerosolized and inhaled (i.e., vaped). There is no legal or scientific support for labeling e-cigarette product ingredients as GRAS . This review discusses our concerns with the GRAS provision being applied to e-cigarette products and provides examples of chemical compounds that have been used as food ingredients but have been shown to lead to adverse health effects when inhaled. The review provides scientific insight into the toxicological evaluation of e-liquid ingredients and their aerosols to help determine the potential respiratory risks associated with their use in e-cigarettes
Distinct clinical phenotypes in paediatric cancer patients with sepsis are associated with different outcomes:an international multicentre retrospective study
Background: Identifying phenotypes in sepsis patients may enable precision medicine approaches. However, the generalisability of these phenotypes to specific patient populations is unclear. Given that paediatric cancer patients with sepsis have different host response and pathogen profiles and higher mortality rates when compared to non-cancer patients, we determined whether unique, reproducible, and clinically-relevant sepsis phenotypes exist in this specific patient population. Methods: We studied patients with underlying malignancies admitted with sepsis to one of 25 paediatric intensive care units (PICUs) participating in two large, multi-centre, observational cohorts from the European SCOTER study (n = 383 patients; study period between January 1, 2018 and January 1, 2020) and the U.S. Novel Data-Driven Sepsis Phenotypes in Children study (n = 1898 patients; study period between January 1, 2012 and January 1, 2018). We independently used latent class analysis (LCA) in both cohorts to identify phenotypes using demographic, clinical, and laboratory data from the first 24 h of PICU admission. We then tested the association of the phenotypes with clinical outcomes in both cohorts. Findings: LCA identified two distinct phenotypes that were comparable across both cohorts. Phenotype 1 was characterised by lower serum bicarbonate and albumin, markedly increased lactate and hepatic, renal, and coagulation abnormalities when compared to phenotype 2. Patients with phenotype 1 had a higher 90-day mortality (European cohort 29.2% versus 13.4%, U.S. cohort 27.3% versus 11.4%, p < 0.001) and received more vasopressor and renal replacement therapy than patients with phenotype 2. After adjusting for severity of organ dysfunction, haematological cancer, prior stem cell transplantation and age, phenotype 1 was associated with an adjusted OR of death at 90-day of 1.9 (1.04–3.34) in the European cohort and 1.6 (1.2–2.2) in the U.S. cohort. Interpretation: We identified two clinically-relevant sepsis phenotypes in paediatric cancer patients that are reproducible across two international, multicentre cohorts with prognostic implications. These results may guide further research regarding therapeutic approaches for these specific phenotypes. Funding: Part of this study is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.</p
Distinct clinical phenotypes in paediatric cancer patients with sepsis are associated with different outcomes:an international multicentre retrospective study
Background: Identifying phenotypes in sepsis patients may enable precision medicine approaches. However, the generalisability of these phenotypes to specific patient populations is unclear. Given that paediatric cancer patients with sepsis have different host response and pathogen profiles and higher mortality rates when compared to non-cancer patients, we determined whether unique, reproducible, and clinically-relevant sepsis phenotypes exist in this specific patient population. Methods: We studied patients with underlying malignancies admitted with sepsis to one of 25 paediatric intensive care units (PICUs) participating in two large, multi-centre, observational cohorts from the European SCOTER study (n = 383 patients; study period between January 1, 2018 and January 1, 2020) and the U.S. Novel Data-Driven Sepsis Phenotypes in Children study (n = 1898 patients; study period between January 1, 2012 and January 1, 2018). We independently used latent class analysis (LCA) in both cohorts to identify phenotypes using demographic, clinical, and laboratory data from the first 24 h of PICU admission. We then tested the association of the phenotypes with clinical outcomes in both cohorts. Findings: LCA identified two distinct phenotypes that were comparable across both cohorts. Phenotype 1 was characterised by lower serum bicarbonate and albumin, markedly increased lactate and hepatic, renal, and coagulation abnormalities when compared to phenotype 2. Patients with phenotype 1 had a higher 90-day mortality (European cohort 29.2% versus 13.4%, U.S. cohort 27.3% versus 11.4%, p < 0.001) and received more vasopressor and renal replacement therapy than patients with phenotype 2. After adjusting for severity of organ dysfunction, haematological cancer, prior stem cell transplantation and age, phenotype 1 was associated with an adjusted OR of death at 90-day of 1.9 (1.04–3.34) in the European cohort and 1.6 (1.2–2.2) in the U.S. cohort. Interpretation: We identified two clinically-relevant sepsis phenotypes in paediatric cancer patients that are reproducible across two international, multicentre cohorts with prognostic implications. These results may guide further research regarding therapeutic approaches for these specific phenotypes. Funding: Part of this study is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.</p
Cardiovascular risk associated with the use of glitazones, metformin and sufonylureas: meta-analysis of published observational studies
BACKGROUND: The results of observational studies evaluating and comparing the cardiovascular safety of glitazones, metformin and sufonylureas are inconsistent.To conduct and evaluate heterogeneity in a meta-analysis of observational studies on the risk of acute myocardial infarction (AMI) or stroke in patients with type 2 diabetes using non-insulin blood glucose–lowering drugs (NIBGLD). METHODS: We systematically identified and reviewed studies evaluating NIBGLD in patients with type 2 diabetes indexed in Medline, Embase, or the Cochrane Library that met prespecified criteria. The quality of included studies was assessed with the RTI item bank. Results were combined using fixed- and random-effects models, and the Higgins I(2) statistic was used to evaluate heterogeneity. Sensitivity analyses by study quality were conducted. RESULTS: The summary relative risk (sRR) (95 % CI) of AMI for rosiglitazone versus pioglitazone was 1.13 (1.04–1.24) [I(2) = 55 %]. In the sensitivity analysis, heterogeneity was reduced [I(2) = 16 %]. The sRR (95 % CI) of stroke for rosiglitazone versus pioglitazone was 1.18 (1.02–1.36) [I(2) = 42 %]. There was strong evidence of heterogeneity related to study quality in the comparisons of rosiglitazone versus metformin and rosiglitazone versus sulfonylureas (I(2) ≥ 70 %). The sRR (95 % CI) of AMI for sulfonylurea versus metformin was 1.24 (1.14–1.34) [I(2) = 41 %] and for pioglitazone versus metformin was 1.02 (0.75–1.38) [I(2) = 17 %]. Sensitivity analyses decreased heterogeneity in most comparisons. CONCLUSION/INTERPRETATION: Sulfonylureas increased the risk of AMI by 24 % compared with metformin; an imprecise point estimate indicated no difference in risk of AMI when comparing pioglitazone with metformin. The presence of heterogeneity precluded any conclusions on the other comparisons. The quality assessment was valuable in identifying methodological problems in the individual studies and for analysing potential sources of heterogeneity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12872-016-0187-5) contains supplementary material, which is available to authorized users
Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects
Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination
No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study
It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest
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