Intentional intoxication with natural hallucinogenic substances such as hallucinogenic mushrooms continues to be a major problem in the US and Europe, particularly in the harbor complex of northwest Poland (Pomerania). A case is described of Psilocybe intoxication in an 18-year-old man resulting in Wolff-Parkinson-White syndrome, arrhythmia, and myocardial infarction. The indole concentrations of hallucinogenic mushrooms may predict the risk for adverse central nervous system and cardiac toxicity.
This study presents the fatal case of a young man who was admitted to the ICAU due to sudden cardiac arrest. An interview revealed that the patient had taken some unspecified crystals. From the moment of admission, his condition deteriorated dramatically as a result of increasing circulatory insufficiency. After a few hours, sudden cardiac arrest occurred again and the patient was pronounced dead. In the course of a medicolegal autopsy, samples of biological material were preserved for toxicology tests and histopathological examination. The analysis of samples using the LC-MS/MS technique revealed the presence of α-PVP in the following concentrations: blood-174 ng/mL, urine-401 ng/mL, brain-292 ng/g, liver-190 ng/g, kidney-122 ng/g, gastric contents-606 ng/g. The study also presents findings from the parallel histopathological examination. Based on these findings, cardiac arrest secondary to intoxication with alpha-PVP was determined as the direct cause of the patient's death.
In the past 5 years at our institution, 12 cases involving the ingestion of chlorpropamide 3-15 g were fatal. We report a 23-year-old woman with an estimated ingestion of chlorpropamide 5-10 g. Initial cardiovascular collapse, attributed to the blockade of potassium channel transport, responded to intensive support including 3 days of cardiac pacing. Urinary excretion of chlorpropamide and hypoglycemia persisted until day 27. The toxic mechanisms and high risk of chlorpropamide are summarized. A fatal therapeutic dose ratio as low as 4:1 has made this antidiabetic agent obsolete.
BackgroundLung cancer diagnosis in tissue material with commonly used histological techniques is sometimes inconvenient and in a number of cases leads to ambiguous conclusions. Frequently advanced immunostaining techniques have to be employed, yet they are both time consuming and limited. In this study a proteomic approach is presented which may help provide unambiguous pathologic diagnosis of tissue material.MethodsLung tissue material found to be pathologically changed was prepared to isolate proteome with fast and non selective procedure. Isolated peptides and proteins in ranging from 3.5 to 20 kDa were analysed directly using high resolution mass spectrometer (MALDI-TOF/TOF) with sinapic acid as a matrix. Recorded complex spectra of a single run were then analyzed with multivariate statistical analysis algorithms (principle component analysis, classification methods). In the applied protocol we focused on obtaining the spectra richest in protein signals constituting a pattern of change within the sample containing detailed information about its protein composition. Advanced statistical methods were to indicate differences between examined groups.ResultsObtained results indicate changes in proteome profiles of changed tissues in comparison to physiologically unchanged material (control group) which were reflected in the result of principle component analysis (PCA). Points representing spectra of control group were located in different areas of multidimensional space and were less diffused in comparison to cancer tissues. Three different classification algorithms showed recognition capability of 100% regarding classification of examined material into an appropriate group.ConclusionThe application of the presented protocol and method enabled finding pathological changes in tissue material regardless of localization and size of abnormalities in the sample volume. Proteomic profile as a complex, rich in signals spectrum of proteins can be expressed as a single point in multidimensional space and than analysed using advanced statistical methods. This approach seems to provide more precise information about a pathology and may be considered in futer evaluation of biomarkers for clinical applications in different pathology. Multiparameter statistical methods may be helpful in elucidation of newly expressed sensitive biomarkers defined as many factors "in one point".
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