Investigating strontium isotope linkage between biominerals (uroliths), drinking water and environmental matrices.

This study presents the mineralogy and strontium isotope ratio (87Sr/86Sr) of 21 pathological biominerals (bladder and kidney stones) collected from patients admitted between 2018 and 2020 at the Department of Urology of the San Pio Hospital (Benevento, southern Italy). Urinary stones belong to the calcium oxalate, purine or calcium phosphate mineralogy types. Their corresponding 87Sr/86Sr range from 0.707607 for an uricite sample to 0.709970 for a weddellite one, and seem to be partly discriminated based on the mineralogy. The comparison with the isotope characteristics of 38 representative Italian bottled and tap drinking waters show a general overlap in 87Sr/86Sr with the biominerals. However, on a smaller geographic area (Campania Region), we observe small 87Sr/86Sr differences between the biominerals and local waters. This may be explained by external Sr inputs for example from agriculture practices, inhaled aerosols (i.e., particulate matter), animal manure and sewage, non-regional foods. Nevertheless, biominerals of patients that stated to drink and eat local water/wines and foods every day exhibited a narrower 87Sr/86Sr range roughly matching the typical isotope ratios of local geological materials and waters, as well as those of archaeological biominerals from the same area. Finally, we conclude that the strontium isotope signature of urinary stones may reflect that of the environmental matrices surrounding patients, but future investigations are recommended to ultimately establish the potential for pathological biominerals as reliable biomonitoring proxies, taking into the account the contribution of the external sources of Sr.

observational studies: propensity score analysis of non-randomized data.

The randomized controlled trial (RCT) is considered to be the "gold standard" for providing evidence on drug efficacy. However, particularly for answering long-term questions in chronic diseases such as multiple sclerosis (MS), RCTs are often not feasible because of their size, duration, ethical constraints and costs. Data derived from observational studies complement information provided by RCTs. A major issue is that observational studies are more exposed and prone to biases, which can partly be addressed through rigorous study design or statistical analysis. Propensity score (PS) techniques are the most frequently used. PS is the probability that an individual would receive a certain treatment based on his/her pretreatment characteristics. This score is being widely used in many therapeutic areas and also in MS to adjust for the uncontrolled assignment of treatment in observational studies. However, since PS cannot adjust for unmeasured or unknown confounders, the conclusions from an observational study may not be considered as strong as those from RCTs.