Potential para-specific and geographical utility of Thai Green Pit Viper (Trimeresurus albolabris) Monovalent Antivenom: Neutralization of procoagulant and hemorrhagic activities of diverse Trimeresurus pit viper venoms

Yong, Mun Yee; Tan, Kae Yi; Tan, Choo Hock

doi:10.1016/j.toxicon.2021.09.021

Cited by 12 publications

(3 citation statements)

References 53 publications

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“…Vol www.nature.com/scientificreports/ Until recently, the assessment of snake venom haemorrhage was faced with the same issues. Therefore, we first developed a simple computational tool to improve accuracy of quantifying haemorrhage severity, which has since been implemented by different groups within the field [23][24][25][26][27][28][29][30][31] . This encouraged us to build a more sophisticated machine learning guided tool that further increased the accuracy, accessibility, and reproducibility of snake venom haemorrhage assessment 32 .…”

Section: Discussionmentioning

confidence: 99%

Machine-learning guided Venom Induced Dermonecrosis Analysis tooL: VIDAL

Laprade

Bartlett

Christensen

et al. 2023

Preprint

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Snakebite envenoming is a global public health issue that causes significant morbidity and mortality, particularly in low-income regions of the world. The clinical manifestations of envenomings vary depending on the snake's venom, with paralysis, haemorrhage, and necrosis being the most common and medically relevant effects. To assess the efficacy of antivenoms against dermonecrosis, a preclinical testing approach involves in vivo mouse models that mimic local tissue effects of cytotoxic snakebites in humans. However, current methods for assessing necrosis severity are time-consuming and susceptible to human error. To address this, we present the Venom Induced Dermonecrosis Analysis tool (VIDAL), a machine-learning-guided image-based solution that can automatically identify dermonecrotic lesions in mice, adjust for lighting biases, scale the image, extract lesion area and discolouration, and calculate the severity of dermonecrosis. We also introduce a new unit, the dermonecrotic unit (DnU), to better capture the complexity of dermonecrosis severity. Our tool is comparable to the performance of state-of-the-art histopathological analysis, making it an accessible, accurate, and reproducible method for assessing dermonecrosis. Given the urgent need to address the neglected tropical disease that is snakebite, high-throughput technologies such as VIDAL are crucial in developing and validating new and existing therapeutics for this debilitating disease.

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Section: Discussionmentioning

confidence: 99%

Machine-learning guided Venom Induced Dermonecrosis Analysis tooL: VIDAL

Laprade

Bartlett

Christensen

et al. 2023

Preprint

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“…In our earlier study, we were able to improve the classical rodent skin test that either uses calliper measurements or manual lesion outlining by increasing the accuracy of haemorrhage characterisation and reducing the time required for analysis in comparison to the original approach, as well to establish that HaUs accurately reflect haemoglobin content analysis (21). Therefore, our previous tool has been used in a series of later publications (28)(29)(30)(31)(32)(33)(34)(35)(36). Nevertheless, our prior approach still remained time consuming and required familiarisation with a new software and access to a colour pantone.…”

Section: Discussionmentioning

confidence: 99%

AHA: AI-guided tool for the quantification of venom-induced haemorrhage in mice

et al. 2022

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Venom-induced haemorrhage constitutes a severe pathology in snakebite envenomings, especially those inflicted by viperid species. To both explore venom activity accurately and evaluate the efficacy of viperid antivenoms for the neutralisation of haemorrhagic activity it is essential to have available a precise, quantitative tool for empirically determining venom-induced haemorrhage. Thus, we have built on our prior approach and developed a new AI-guided tool (AHA) for the quantification of venom-induced haemorrhage in mice. Using a smartphone, it takes less than a minute to take a photo, upload the image, and receive accurate information on the magnitude of a venom-induced haemorrhagic lesion in mice. This substantially decreases analysis time, reduces human error, and does not require expert haemorrhage analysis skills. Furthermore, its open access web-based graphical user interface makes it easy to use and implement in laboratories across the globe. Together, this will reduce the resources required to preclinically assess and control the quality of antivenoms, whilst also expediting the profiling of haemorrhagic activity in venoms for the wider toxinology community.

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“…In our earlier study, we were able to improve the classical rodent skin test by increasing the accuracy of haemorrhage characterisation and reducing the time required for analysis in comparison to the original approach, as well establish that HaUs accurately reflect haemoglobin content analysis 18 . Therefore, our previous tool has been used in a series of later publications [28][29][30][31][32][33][34][35][36][37]. Nevertheless, our prior approach still remained time consuming, and required familiarisation with a new software and access to a colour pantone.…”

Section: Discussionmentioning

confidence: 99%

ALOHA: AI-guided tool for the quantification of venom-induced haemorrhage in mice

Jenkins

Laprade

Sánchez

et al. 2022

Preprint

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Venom-induced haemorrhage constitutes a severe pathology in snakebite envenomings, especially those inflicted by viperid species. In order to both explore venom compositions accurately, and evaluate the efficacy of viperid antivenoms for the neutralisation of haemorrhagic activity it is essential to have available a precise, quantitative tool for empirically determining venom-induced haemorrhage. Thus, we have built on our prior approach and developed a new AI-guided tool (ALOHA) for the quantification of venom-induced haemorrhage in mice. Using a smartphone, it takes less than a minute to take a photo, upload the image, and receive accurate information on the magnitude of a venom-induced haemorrhagic lesion in mice. This substantially decreases analysis time, reduces human error, and does not require expert haemorrhage analysis skills. Furthermore, its open access web-based graphical user interface makes it easy to use and implement in laboratories across the globe. Together, this will reduce the resources required to preclinically assess and control the quality of antivenoms, whilst also expediting the profiling of hemorrhagic activity in venoms for the wider toxinology community.

show abstract

Potential para-specific and geographical utility of Thai Green Pit Viper (Trimeresurus albolabris) Monovalent Antivenom: Neutralization of procoagulant and hemorrhagic activities of diverse Trimeresurus pit viper venoms

Cited by 12 publications

References 53 publications

Machine-learning guided Venom Induced Dermonecrosis Analysis tooL: VIDAL

Machine-learning guided Venom Induced Dermonecrosis Analysis tooL: VIDAL

AHA: AI-guided tool for the quantification of venom-induced haemorrhage in mice

ALOHA: AI-guided tool for the quantification of venom-induced haemorrhage in mice

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