Lead (Pb) and the Risk of Alzheimer’s disease or cognitive decline: A systematic review

Modulation of gut microbiota with probiotics as a strategy to counteract endogenous and exogenous neurotoxicity

The existing data demonstrate that probiotic supplementation affords protective effects against neurotoxicity of exogenous (e.g., metals, ethanol, propionic acid, aflatoxin B1, organic pollutants) and endogenous (e.g., LPS, glucose, Aβ, phospho-tau, α-synuclein) agents. Although the protective mechanisms of probiotic treatments differ between various neurotoxic agents, several key mechanisms at both the intestinal and brain levels seem inherent to all of them. Specifically, probiotic-induced improvement in gut microbiota diversity and taxonomic characteristics results in modulation of gut-derived metabolite production with increased secretion of SFCA. Moreover, modulation of gut microbiota results in inhibition of intestinal absorption of neurotoxic agents and their deposition in brain. Probiotics also maintain gut wall integrity and inhibit intestinal inflammation, thus reducing systemic levels of LPS. Centrally, probiotics ameliorate neurotoxin-induced neuroinflammation by decreasing LPS-induced TLR4/MyD88/NF-κB signaling and prevention of microglia activation. Neuroprotective mechanisms of probiotics also include inhibition of apoptosis and oxidative stress, at least partially by up-regulation of SIRT1 signaling. Moreover, probiotics reduce inhibitory effect of neurotoxic agents on BDNF expression, on neurogenesis, and on synaptic function. They can also reverse altered neurotransmitter metabolism and exert an antiamyloidogenic effect. The latter may be due to up-regulation of ADAM10 activity and down-regulation of presenilin 1 expression. Therefore, in view of the multiple mechanisms invoked for the neuroprotective effect of probiotics, as well as their high tolerance and safety, the use of probiotics should be considered as a therapeutic strategy for ameliorating adverse brain effects of various endogenous and exogenous agents.

Environmental Substances Associated with Alzheimer's Disease-A Scoping Review

Alzheimer’s disease (AD) is the most common form of dementia, prevalent in approximately 50–70% of the dementia cases. AD affects memory, and it is a progressive disease interfering with cognitive abilities, behaviour and functioning of the person affected. In 2015, there were 47 million people affected by dementia worldwide, and the figure was estimated to increase to 75 million in 2030 and to 132 million by 2050. In the framework of European Human Biomonitoring Initiative (HBM4EU), 18 substances or substance groups were prioritized for investigation. For each of the priority substances, a scoping document was prepared. Based on these scoping documents and complementary review of the recent literature, a scoping review of HBM4EU-priority substances which might be associated with AD was conducted. A possible association between risk of AD and pesticides was detected. For mercury (Hg), association is possible but inconsistent. Regarding cadmium (Cd) and arsenic (As), the results are inconsistent but inclined towards possible associations between the substances and the risk of disease. The evidence regarding lead (Pb) was weaker than for the other substances; however, possible associations exist. Although there is evidence of adverse neurological effects of environmental substances, more research is needed. Environmental chemical exposure and the related hazards are essential concerns for public health, and they could be preventable.

Characterization and within-site variation of environmental metal concentrations around a contaminated site using a community-engaged approach

Historic industrial activity led to extensive lead and arsenic contamination within residential areas of East Chicago, Indiana, United States. Although remediation is underway, community concerns about this contamination remain. Therefore, the goal for this analysis was to characterize environmental contamination in soil within and around these areas. A total of 228 samples from 32 different sites (addresses) were collected by community members or study staff. These were analyzed for metals using portable x-ray fluorescence or inductively coupled plasma ̶ optical emission spectroscopy. Concentrations exceeding EPA screening levels were found for 42% of the soil arsenic samples, 35% of the soil lead samples, and 79% of the soil manganese samples; a few samples also contained elevated copper or zinc. Concentrations above EPA screening levels were identified both within and outside of the formally designated contaminated area. Roughly 30% of all sites had at least one sample above and one sample below the screening level for arsenic, lead, and manganese. For sites within the contaminated area, more than 90% (arsenic), 60% (lead) and 60% (manganese) of the samples exceeded EPA screening levels. There was a significant association of proximity to the historic industrial site with elevated soil concentrations of arsenic and lead; a similar association was present for manganese. These results are consistent with existing data for lead and arsenic and we additionally report elevated concentrations of manganese and a high within-site variability of all metal concentrations. These findings should be considered in future remediation efforts.

Using a matrix-analytical approach to synthesizing evidence solved incompatibility problem in the hierarchy of evidence

OBJECTIVES

The hierarchy of evidence presupposes linearity and additivity of effects, as well as commutativity of knowledge structures. It thereby implicitly assumes a classical theoretical model.

STUDY DESIGN AND SETTING

This is an argumentative article that uses theoretical analysis based on pertinent literature and known facts to examine the standard view of methodology.

RESULTS

We show that the assumptions of the hierarchical model are wrong. The knowledge structures gained by various types of studies are not sequentially indifferent, that is, do not commute. External validity and internal validity are at least partially incompatible concepts. Therefore, one needs a different theoretical structure, typical of quantum-type theories, to model this situation. The consequence of this situation is that the implicit assumptions of the hierarchical model are wrong, if generalized to the concept of evidence in total.

CONCLUSION

The problem can be solved by using a matrix-analytical approach to synthesizing evidence. Here, research methods that produce different types of evidence that complement each other are synthesized to yield the full knowledge. We show by an example how this might work. We conclude that the hierarchical model should be complemented by a broader reasoning in methodology.