The nutraceuticals market is vast, encompassing many different products with inconsistent levels of evidence available to support their use. This overview represents a Western perspective of the ...nutraceuticals market, with a brief comparison with that in China, as an illustration of how individual health supplements increase and decrease in popularity in regional terms. Recent changes in sales patterns, mainly taken from the US market, are summarized and a selection of five newer products, which have not been subject to extensive recent review are profiled: astaxanthin, a carotenoid found in red algae, seafood, salmon and trout, as an antioxidant; cannabidiol, a non‐euphoric marijuana ingredient used as mood enhancer and for painful/inflammatory conditions; modified extracts of ginseng used in new indications including dementia and space travel; monk fruit, a non‐sugar high intensity sweetener and nigella seed, a popular food ingredient and Asian medicine, which has experienced an extraordinary rise in sales recently.
Linked Articles
This article is part of a themed section on The Pharmacology of Nutraceuticals. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v177.6/issuetoc
Drugging the Cancers Addicted to DNA Repair Nickoloff, Jac A; Jones, Dennie; Lee, Suk-Hee ...
JNCI : Journal of the National Cancer Institute,
11/2017, Volume:
109, Issue:
11
Journal Article
Peer reviewed
Open access
Defects in DNA repair can result in oncogenic genomic instability. Cancers occurring from DNA repair defects were once thought to be limited to rare inherited mutations (such as BRCA1 or 2). It now ...appears that a clinically significant fraction of cancers have acquired DNA repair defects. DNA repair pathways operate in related networks, and cancers arising from loss of one DNA repair component typically become addicted to other repair pathways to survive and proliferate. Drug inhibition of the rescue repair pathway prevents the repair-deficient cancer cell from replicating, causing apoptosis (termed synthetic lethality). However, the selective pressure of inhibiting the rescue repair pathway can generate further mutations that confer resistance to the synthetic lethal drugs. Many such drugs currently in clinical use inhibit PARP1, a repair component to which cancers arising from inherited BRCA1 or 2 mutations become addicted. It is now clear that drugs inducing synthetic lethality may also be therapeutic in cancers with acquired DNA repair defects, which would markedly broaden their applicability beyond treatment of cancers with inherited DNA repair defects. Here we review how each DNA repair pathway can be attacked therapeutically and evaluate DNA repair components as potential drug targets to induce synthetic lethality. Clinical use of drugs targeting DNA repair will markedly increase when functional and genetic loss of repair components are consistently identified. In addition, future therapies will exploit artificial synthetic lethality, where complementary DNA repair pathways are targeted simultaneously in cancers without DNA repair defects.
Introduction to propensity scores Williamson, Elizabeth J; Forbes, Andrew
Respirology (Carlton, Vic.),
July 2014, Volume:
19, Issue:
5
Journal Article
Peer reviewed
Open access
Although randomization provides a gold-standard method of assessing causal relationships, it is not always possible to randomly allocate exposures. Where exposures are not randomized, estimating ...exposure effects is complicated by confounding. The traditional approach to dealing with confounding is to adjust for measured confounding variables within a regression model for the outcome variable. An alternative approach--propensity scoring--instead fits a regression model to the exposure variable. For a binary exposure, the propensity score is the probability of being exposed, given the measured confounders. These scores can be estimated from the data, for example by fitting a logistic regression model for the exposure including the confounders as explanatory variables and obtaining the estimated propensity scores from the predicted exposure probabilities from this model. These estimated propensity scores can then be used in various ways-matching, stratification, covariate-adjustment or inverse-probability weighting-to obtain estimates of the exposure effect. In this paper, we provide an introduction to propensity score methodology and review its use within respiratory health research. We illustrate propensity score methods by investigating the research question: 'Does personal smoking affect the risk of subsequent asthma?' using data taken from the Tasmanian Longitudinal Health Study.
Purpose
The BCL-2 family of anti-apoptotic proteins, BCL-2, BCL-XL and MCL-1, can mediate survival of some types of cancer. DT2216 is a PROteolysis-TArgeting Chimera (PROTAC) that degrades BCL-XL ...specifically and is in phase 1 trials. We sought to define the frequency and mechanism of resistance to DT2216 in T-cell acute lymphoblastic leukemia (T-ALL) cell lines.
Methods
We measured cell survival and protein levels of BCL-XL, BCL-2, MCL-1 and the pro-apoptotic BIM in 13 distinct T-ALL cell lines after exposure to varying concentrations of DT2216.
Results
We identified concentrations of DT2216 which were cytotoxic to each T-ALL cell line.
These concentrations have no correlation with the initial protein levels of BCL-XL, BCL-2, MCL-1 or BIM in each cell line. However, there was a correlation between survival to DT2216 and the efficiency of degradation of BCL-XL by DT2216. Only one cell line, SUP-T1, had significant resistance to DT2216, defined as an IC50 above what is achievable in murine tumors in vivo.
Conclusion
Resistance to DT2216 is rare in a wide variety of T-ALL cells but when it occurs is correlated with decreased BCL-XL degradation. Resistance to DT2216 in T-ALL is not predicted by initial BCL-XL or BIM protein levels, or BCL-2 or MCL-1 levels before or after treatment. These data imply that a phase 2 clinical trial of DT2216 in T-ALL should be widely available and not limited to a subset of patients.
Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide
. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches ...for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. COVID-19-related death was associated with: being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53-1.65)); greater age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29-1.69) and 1.45 (1.32-1.58), respectively). We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far. More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly.
Astaxanthin: How much is too much? A safety review Brendler, Thomas; Williamson, Elizabeth Mary
Phytotherapy research,
December 2019, 2019-Dec, 2019-12-00, 20191201, Volume:
33, Issue:
12
Journal Article
Peer reviewed
Astaxanthin (AX)‐containing preparations are increasingly popular as health food supplements. Evaluating the maximum safe daily intake of AX is important when setting dose levels for these products ...and currently, there are discrepancies in recommendations by different regulatory authorities. We have therefore conducted a review of approved dose levels, clinical trials of natural AX, and toxicological studies with natural and synthetic AX. Recommended or approved doses varied in different countries and ranged between 2 and 24 mg. We reviewed 87 human studies, none of which found safety concerns with natural AX supplementation, 35 with doses ≥12 mg/day. An acceptable daily intake (ADI) of 2 mg as recently proposed by European Food Safety Authority was based on a toxicological study in rats using synthetic AX. However, synthetically produced AX is chemically different from natural AX, so results with synthetic AX should not be used in assessing natural AX safety. In addition, few safety studies have been conducted in either humans or animals with synthetic AX. We therefore recommend the ADI for natural AX to be based only on studies conducted with natural AX and further studies to be conducted with synthetic AX (including human clinical trials) to establish a separate ADI for synthetic AX.
Abstract Objective Missing data are a pervasive problem, often leading to bias in complete records analysis (CRA). Multiple imputation (MI) via chained equations is one solution, but its use in the ...presence of interactions is not straightforward . Study Design and Setting We simulated data with outcome Y dependent on binary explanatory variables X and Z and their interaction XZ. Six scenarios were simulated (Y continuous and binary, each with no interaction, a weak and a strong interaction), under 5 missing data mechanisms. We use DAGs to identify when CRA and MI would each be unbiased. We evaluate the performance of CRA, MI without interactions, MI including all interactions, and stratified imputation. We also illustrated these methods using a simple example from the National Child Development Study (NCDS). Results MI excluding interactions is invalid, and resulted in biased estimates and low coverage. When XZ was zero, MI excluding interactions gave unbiased estimates but over-coverage. MI including interactions and stratified MI gave equivalent, valid inference in all cases. In the NCDS example, MI excluding interactions incorrectly concluded there was no evidence for an important interaction. Conclusions Epidemiologists carrying out MI should ensure that their imputation model(s) are compatible with their analysis model.
Abstract
Marginal structural models (MSMs) are commonly used to estimate causal intervention effects in longitudinal nonrandomized studies. A common challenge when using MSMs to analyze observational ...studies is incomplete confounder data, where a poorly informed analysis method will lead to biased estimates of intervention effects. Despite a number of approaches described in the literature for handling missing data in MSMs, there is little guidance on what works in practice and why. We reviewed existing missing-data methods for MSMs and discussed the plausibility of their underlying assumptions. We also performed realistic simulations to quantify the bias of 5 methods used in practice: complete-case analysis, last observation carried forward, the missingness pattern approach, multiple imputation, and inverse-probability-of-missingness weighting. We considered 3 mechanisms for nonmonotone missing data encountered in research based on electronic health record data. Further illustration of the strengths and limitations of these analysis methods is provided through an application using a cohort of persons with sleep apnea: the research database of the French Observatoire Sommeil de la Fédération de Pneumologie. We recommend careful consideration of 1) the reasons for missingness, 2) whether missingness modifies the existing relationships among observed data, and 3) the scientific context and data source, to inform the choice of the appropriate method(s) for handling partially observed confounders in MSMs.
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