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Bioaerosols in Animal Houses
Published in Christopher S. Cox, Christopher M. Wathes, Bioaerosols Handbook, 2020
Bioaerosols can play an essential part in the etiology of animal disease. Some infectious diseases of farm livestock have a simple etiology and obey Koch’s postulates of causation. An important example is foot and mouth disease. Others have a far more complex etiology in which a host of environmental and biological factors combine to tip the balance in favor of disease. Examples of these are shown in Table 20.1.85 A third important class comprises non-infectious diseases, e.g., allergies such as obstructive pulmonary disease of horses. This simplified analysis of disease categories helps to determine the purpose of bioaerosol sampling in animal houses (Table 20.2).
Epigenotoxicity: a danger to the future life
Published in Journal of Environmental Science and Health, Part A, 2023
Farzaneh Kefayati, Atoosa Karimi Babaahmadi, Taraneh Mousavi, Mahshid Hodjat, Mohammad Abdollahi
Due to the low technology of epigenetic measurements and the high cost of large-scale epigenetic epidemiological studies, a lack of data is observed.[8] In this situation, gathering diffused epigenetic studies is important since epigenetic concepts and mechanisms are a new route to disease prevention and treatment. This article primarily investigated the mechanism of epigenetics, followed by introducing important environmental factors playing roles in this regard. Then, the relation between epigenotoxicity and the incidence of various diseases was thoroughly discussed by reviewing recent clinical trials and epidemiological studies. Unlike previous review articles, in this paper several factors including environmental and genetic factors, have been investigated simultaneously contributing to the etiology of the diseases. For each disease, environmental and epigenetic factors with the relevant mechanism were described separately. In this way, we understand that in addition to genetics, environmental factors play a role in causing widespread diseases. This connection is sometimes ignored, and many need help understanding the lack of connection between these factors.
Erythemato-Squamous Diseases Prediction and Interpretation Using Explainable AI
Published in IETE Journal of Research, 2022
Abhishek Singh Rathore, Siddhartha Kumar Arjaria, Manish Gupta, Gyanendra Chaubey, Amit Kumar Mishra, Vikram Rajpoot
Many researchers are working in the field of feature selection. In addition to computer vision, researchers put their findings in feature selection using rough set methods [48–52] to find out hidden patterns. Sinha and Namdev [53] used the rough set theory to find out the best features for skin diseases. The study has not provided a detailed study of the different features. The machine learning algorithms yield accurate results, but the interpretability of the results is a more important issue and cannot be ignored. It certainly helps to understand what is going wrong with the patients and contemporary research is also focused on tracing the etiology of the diseases. Shin [54] and Chazette & Schneider [55] highlighted the Implications of Explainable AI on trust and awareness. Lots of studies have been published dedicated to the application of XAI in the healthcare system [56–59]. Khodabandehloo et al. [60] developed HealthXAI using XAI for monitoring the cognitive decline in elderly people. Lauritsen et al. [61] proposed an XAI-based model for the prediction of acute critical illness based on early warning scores from electronic health records. Carrieri et al. [62] identified variations in skin microbiome composition that are connected to phenotypic differences using XAI.