Investigating the impacts of heavy metal(loid)s on ecology and human health in the lower basin of Hungary's Danube River: A Python and Monte Carlo simulation-based study

This study aimed to determine the environmental and health risks of the heavy metal levels in the Danube River in Hungary. The metals, including Fe, Mn, Zn, Cu, Ni, Cr, Pb, and As, were measured in the period from 2013 to 2019. The Spearman correlation and heatmap cluster analysis were utilized to determine the origin of pollution and the factors that control surface water quality. Several indices, such as the heavy metal pollution index (HPI), metal index (MI), hazard quotient oral and dermal (HQ), hazard index oral and dermal (HI), and carcinogenic risk (CR), were conducted to evaluate the potential risks for the environment and human health. The values of the HPI were between the range of 15 < HPI < 30, which indicated moderate pollution; however, the MI results showed high pollution in Dunaföldvár and Hercegszántó cities. The ecological risk (RI < 30) and HI values (< 1) showed low environmental risks and non-carcinogenic impacts of the existing metals, either on adults or children. The mean CR value of oral arsenic was 2.2E-04 and 2.5E-04 during April-September and October-March, respectively, indicating that children were the most vulnerable to arsenic-carcinogenic oral effects. While lead's CR oral values for children during April-September exceeded the threshold of 1.0E-04, chromium's oral and dermal CR values for both adults and children were 2.08E-04, 6.11E-04, 1.97E-04, and 5.82E-04 during April-September and October-March, respectively. These results demonstrate the potential carcinogenic risks related to chromium exposure within the two pathways in Hungary and highlight the need for effective measures to mitigate these risks.

Hypertriglyceridemia induced by aripiprazol: about a clinical case

Introduction

41 years-old man diagnosed of schizophrenia and peripheral spondyloarthropathy HLA-B27 (-) in treatment with methotrexate. Psychiatric background: First psychotic episode at 18, with no further medical monitoring. In 2018 he underwent a new episode consisting in auditory hallucinations, delusional ideas and clinophilia of months of evolution. He was sent to a Psychiatric Rehabilitation Unit and prescribed aripiprazole 20mg. The routine blood analysis revealed triglycerides level of 414mg/dL, with previous normal levels (123 mg/dL), without no other cause to justify it.

Objectives

To study the relationship between aripiprazole treatment and acute hypertriglyceridemia.

Methods

A clinical case is presented and available bibliography about the relation between aripiprazole and acute hypertriglyceridemia is reviewed.

Results

Hypertriglyceridemia was confirmed in the second analysis, so we concluded it was due to the start of aripiprazole, after rejecting other potential causes. Aripiprazole was replaced by cariprazine 3mg because of its similar profile. The analysis was repeated after a month and the normalization of the triglyceridemia (159mg/dL) was verified, while cholesterol levels remain stable. Moreover, the patient experienced an improvement in akathisia and sedation.

Conclusions

Although metabolic impact is not expected with aripiprazole, after reviewing the bibliography we have found a clinical trial and a case series that described this adverse effect. Our case highlights the importance of closely monitoring of patients in whom an antipsychotic treatment is started due to the high mortality and morbidity related to cardiovascular diseases.

Disclosure

No significant relationships.

Statistical optimization of a sustained-release matrix tablet of lobenzarit disodium

The statistical optimization of sustained-release matrix tablets of lobenzarit disodium salt (LDS) was performed using the central composite experiment design 2(3) for three independent variables: the amount of polymer (Eudragit RS-PO) AP, the total volume of granulation solvent VS, and the amount of filler (microcrystalline cellulose) CE. The t90% was selected as the response variable. The response surfaces were performed from a statistical mathematical model. The optimal formulation was obtained for the variables (AP = 15 mg, VS = 60 microliters, and CE = 0).