Biology subjects

Ong, S.-Q.

Publications and source records attributed to Ong, S.-Q..

3 recordsLinked to original sources

bioRxiv2025

A General Method for Detection and Segmentation of Terrestrial Arthropods in Images

To better understand the status and trends of insects and other arthropods, emerging technologies like image recognition are developing rapidly. This is creating a strong demand for efficient and accurate algorithms for detection and localization of arthropods in images. Existing models have modest performance and do not generalise well to variation in scale, appearance and density of specimens, or imaging conditions. Consequently, each new application often requires manual labeling of training data and model training, which limits the uptake of image-based tools and technologies. Here, we introduce flatbug, which is a powerful and general model to count and outline insects and other terrestrial arthropods in images. The training dataset is large and diverse and represent 23 different lab- and field-based imaging systems. The best flatbug model achieves an average F 1 = 94.2% on our validation dataset. Crucially, we show that flatbug has great out-of-the-box performance and generalises well to novel contexts. When images from a given dataset are left out of model training, the performance of flatbug is only reduced by on average 7.1% for the dataset in question. By using truly stratified cross-validation, we set a precedent for robust evaluation of deep learning model performance and generalization. We also take steps towards scale- and size-agnostic arthropod detection, by developing an integrated tiling framework for inference and training. Additionally, flatbug s implementation of YOLOv8 for instance segmentation enables downstream background removal and body size estimation. The generaliseability of flatbug stems from the diversity of contexts represented in the flatbug dataset, including 113550 arthropods annotated across 6131 images. Alongside a fully documented Python package with tutorials for integration and analysis via https://github.com/darsa-group/flat-bug/, the flatbug dataset is available from https://www.doi.org/10.5281/zenodo.14761447. By providing performant models and the accompanying dataset, flatbug offers both a ready-to-use tool and a benchmark for the future. Overall, flatbug represents a significant methodological advance within arthropod image detection, with user-friendly integration for monitoring and research. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/647223v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@2d25c0org.highwire.dtl.DTLVardef@9929borg.highwire.dtl.DTLVardef@77ff28org.highwire.dtl.DTLVardef@10bd2f_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2024

Metabolomic differentiation of amino acid profiles in adult deltamethrin-resistant Aedes albopictus (L.)

Understanding the susceptibility status of mosquitoes to insecticides is critical for effective decision making regarding the use or rotation of insecticides in control programs. In this study, we demonstrated the use of amino acid profiling for the detection of deltamethrin-resistant Aedes albopictus (L.). Mosquitoes collected in the field were first tested with WHO adulticide bioassay kits, and the amino acid profiles of the resistant mosquitoes were compared with the susceptible strain of Ae. albopictus. Samples were lyophilized and derived by silylation and then analyzed by gas chromatography-mass spectrometry (GC-MS). Using standardized, known concentrations of amino acids, we quantified the amino acids in both resistant and susceptible strains. An independent t-test was performed to compare the concentrations of each amino acid between strains. Logistic regression was then performed to assess the relationship between amino acid concentrations and susceptibility status of the mosquitoes. Our results showed that the amino acids in resistant mosquitoes differed significantly from those in susceptible mosquitoes, with the exception of serine. Further regression analysis showed that seven amino acids significantly predicted susceptibility, suggesting that they are suitable as biological indicators for rapid assessment of resistance status in field mosquitoes. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/604257v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@7c3c91org.highwire.dtl.DTLVardef@6c7ad1org.highwire.dtl.DTLVardef@1f36900org.highwire.dtl.DTLVardef@172b13d_HPS_FORMAT_FIGEXP M_FIG C_FIG Identification of deltamethrin-resistant mosquitoes based on differences in the amino acid profile: Deltamethrin-susceptible and -resistant mosquito strains were lyophilised and converted into esters by silylation, which were then analysed using a gas chromatography-mass spectrometer (GC-MS). The difference between susceptible and resistant could be classified by developing a classification model with logistic regression.

zoology↗

bioRxiv2020

Implications of the COVID-19 lockdown on dengue transmission and the occurrence of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in Malaysia

The impact of movement restrictions during the COVID-19 lockdown on the existing endemic infectious disease dengue fever has generated considerable research interest. We compared the Malaysia weekly epidemiological records of dengue incidences during the period of lockdown to the trend of previous years (2015 to 2019) and a simulation at the corresponding period that expected no movement restrictions. We found that the dengue incidence declined significantly with a greater magnitude at phase 1 of lockdown, with a negative gradient of 3.2-fold steeper than the trend observed in previous years and 6.5-fold steeper than the simulation, indicating that the control of population movement did reduce dengue transmission. However, starting from phase 2 of lockdown, the dengue incidences demonstrated an elevation and earlier rebound by at least 4 weeks and grew with an exponential pattern compared to the simulation and previous years. Together with our data on Aedes mosquitoes from a district of Penang, Malaysia, we revealed that Aedes albopictus is the predominant species for both indoor and outdoor environments. The abundance of the mosquito was increasing steadily during the period of lockdown, and demonstrated strong correlation with the locally reported dengue incidences; therefore, we proposed the possible diffusive effect of vector that led to a higher acceleration of incidence rate. These findings would help authorities review the direction and efforts of the vector control strategy.

zoology↗