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Artificial intelligence application for identifying toxic plant species: A case of poisoning with Datura stramonium.

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November 2024

Department of Emergency Medicine, Aksaray Training and Research Hospital, Aksaray, Turkey; Department of Emergency Medicine, Aksaray University School of Medicine, Aksaray, Turkey.

Article Synopsis
  • Managing plant poisonings in the emergency department is complicated, mainly due to the difficulty in identifying the specific toxic plant species involved, which is critical for determining the appropriate treatment.
  • A case of a 23-year-old male who experienced severe symptoms after consuming herbal tea led to the identification of Datura stramonium (jimson weed) using AI software, as timely access to botanical expertise was unavailable.
  • The case suggests that AI tools with visual recognition can aid healthcare providers in accurately identifying toxic plants, enhancing patient safety and treatment effectiveness.
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Article Synopsis
  • The study investigates how intramuscular injections of two drugs, physostigmine and neostigmine, affect Na,K-ATPase activity in rat red blood cells after intense exercise.
  • Both drugs help reduce stress responses by lowering indicators such as adrenal ascorbic acid, stress-related red blood cell increases, and lipid peroxidation (LPO) markers.
  • The drugs appear to restore Na,K-ATPase activity affected by stress and can correct the functions of cholinergic systems in the body’s stress response mechanisms.
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On newborn non-narcotized 1-day-old (P1) and 16-day-old (P16) rats, a detailed analysis of intersystem somatovisceral interactions (ISI) mediated by decasecond (D1, 5-50 sec) range modulating rhythms was performed. Correlation interactions of the main body systems - cardiovascular, respiratory and somatomotor systems in norm and under conditions of changes in the level of cholinergic regulation were studied. Spectral correlation analysis was used to determine the participation of D1 range modulating rhythms in ISI.

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Objective: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common type of dementia. The early diagnosis of AD is an important factor for the control of AD progression. Electroencephalography (EEG) can be used for early diagnosis of AD.

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