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  1. Rangkakulnuwat P, Sanit S, Lao-Araya M
    Trop Biomed, 2020 Jun 01;37(2):318-323.
    PMID: 33612801
    Domestic mites have been recognized as the most common allergen responsible for respiratory allergy. Herein, we report a case of anaphylaxis due to ingestion of dust mitecontaminated food. A 14-year-old boy presented to the Emergency Department with chest discomfort, wheezing, eyelid angioedema, and urticarial rash twice in a month after eating meals, including tempura fried squids and onion fritters (containing wheat flour, eggs, squid, and onion). Anaphylaxis had been diagnosed and successfully treated. The investigations showed that the patient was sensitive to house dust mites. Positive skin prick-to-prick test response to incriminated flour and negative tests to wheat allergen extract and uncontaminated flour were demonstrated. The microscopic analysis of causative cooking flour identified the presence of Dermatophagoides farinae. During the oral food challenge test, the patient was able to eat tempura-fried squids and onion fritters, made with uncontaminated flour, without any adverse reaction. Hence, oral ingestion of dust mite-contaminated food was the culprit of this severe allergic reaction.
  2. Prachasilchai W, Sanit S, Sontigun N, Chaithong U, Sukontason K, Sukontason KL
    Trop Biomed, 2020 Mar 01;37(1):251-257.
    PMID: 33612736
    Although myiasis caused by the blow fly, Chrysomya bezziana Villeneuve (Diptera: Calliphoridae), has been reported in Thailand, all of the cases were human. This study described three cutaneous myiasis cases caused by C. bezziana in dogs in Chiang Mai province, northern Thailand. The removal of fly larvae together with specific treatment to cure all cases in this study was represented.
  3. Tanajitaree C, Sanit S, Sukontason KL, Sukontason K, Somboon P, Anakkamatee W, et al.
    Trop Biomed, 2023 Mar 01;40(1):80-87.
    PMID: 37356007 DOI: 10.47665/tb.40.1.019
    Blow flies, flesh flies, and house flies can provide excellent evidence for forensic entomologists and are also essential to the fields of public health, medicine, and animal health. In all questions, the correct identification of fly species is an important initial step. The usual methods based on morphology or even molecular approaches can reach their limits here, especially when dealing with larger numbers of specimens. Since machine learning already plays a major role in many areas of daily life, such as education, business, industry, science, and medicine, applications for the classification of insects have been reported. Here, we applied the decision tree method with wing morphometric data to construct a model for discriminating flies of three families [Calliphoridae, Sarcophagidae, Muscidae] and seven species [Chrysomya megacephala (Fabricius), Chrysomya rufifacies (Macquart), Chrysomya (Ceylonomyia) nigripes Aubertin, Lucilia cuprina (Wiedemann), Hemipyrellia ligurriens (Wiedemann), Musca domestica Linneaus, and Parasarcophaga (Liosarcophaga) dux Thomson]. One hundred percent overall accuracy was obtained at a family level, followed by 83.33% at a species level. The results of this study suggest that non-experts might utilize this identification tool. However, more species and also samples per specimens should be studied to create a model that can be applied to the different fly species in Thailand.
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