Biology subjects

Ho, I.

Publications and source records attributed to Ho, I..

3 recordsLinked to original sources

bioRxiv2025

Schistosomiasis parasite enhance transmission rates via interfacial swimming

Schistosomiasis is a disease of poverty that affects over 240 million people worldwide despite an ecological paradox: cercariae larvae are short-lived (12 hours), sparse in the water body, and entrained by flows exceeding their swimming speeds - conditions that should limit host-finding. We resolve this paradox by demonstrating that cercariae utilize a physics-based strategy: they actively accumulate at the air-water interface, transforming inefficient three-dimensional search into effective two-dimensional exploration, increasing host-encounter efficiency by a thousand fold. Our biophysical models demonstrate that this behavior emerges from weight-asymmetric morphology, enabling an embodied algorithm for surface-seeking swimming modes without complex neural control. Surface-swimming cercariae benefit from near-zero vertical flows near the surface, allowing them to remain there while exploiting wind-driven currents for long-distance dispersal. We identify the air-water interface as a critical transmission micro-habitat, suggesting new physical intervention strategies targeting this interface to mitigate transmission of this highly infectious disease.

biophysics↗

bioRxiv2024

Bridging Domains in Chronic Lower Back Pain: Large Language Models and Ontology-driven Strategies for Knowledge Graph Construction

Link prediction and entity resolution play pivotal roles in uncovering hidden relationships within networks and ensuring data quality in the era of heterogeneous data integration. This paper explores the utilization of large language models to enhance link prediction, particularly through knowledge graphs derived from transdisciplinary literature. Investigating zero-shot entity resolution techniques, we examine the impact of ontology-based and large language model approaches on the stability of link prediction results. Through a case study focusing on chronic lower back pain research, we analyze workflow decisions and their influence on prediction outcomes. Our research underscores the importance of robust methodologies in improving predictive accuracy and data integration across diverse domains.

bioinformatics↗

bioRxiv2021

Neural dynamics of parametrically modulated human mechanical pain determined using whole-brain quantitative perfusion imaging.

Arterial spin labelling (ASL) FMRI is a powerful tool to noninvasively image tonic and ongoing pain states in both healthy participants and patients. We used ASL to image the neural correlates of extended, parametrically modulated mechanical pain in healthy human participants. The aims of this study were to: i) assess if force-calibrated pin-prick probes could safely and robustly evoke tonic mechanical pain; ii) determine the neural correlates of the parametric changes in both the "force" of the stimulus and the "intensity" of the perception that this elicits using ASL; and iii) provide an initial assessment of the capacity for ALFF to differentiate painful versus non-painful tonic stimuli based on changes in the dynamics of the evoked signal. Our data confirm that it is possible to employ a stimulus force-locked design to induce robust, well maintained ongoing mechanical pain and to observe significant changes in rCBF relative to underlying component processes such as monitoring graded changes in the force applied to the skin (dACC, aMCC, pMCC, PCC, SI, SII, putamen, thalamus and the insula (anterior and posterior subsections); ipsilateral amygdala and hypothalamus; and the contralateral DLPFC) and tracking changes in the perceived intensity of the experience (: bilateral dACC, aMCC, pMCC, PCC, thalamus, SII and the cerebellum; and contralateral SI, insula (including the dpIns). Further exploration of the data using analyses targeting the spectral frequency aspects of the rCBF signal observed reveals that a collection of regions (e.g. the contralateral VLPFC, inferior frontal gyrus, insula (anterior, mid and posterior subsections), SII, putamen, OFC, amygdala, and the hippocampus) exhibit unique perfusion dynamics during extended painful stimulation compared to non-painful touch. Results from this study provide further validation for the application of ASL to image experimental pain in healthy human subjects while interrogation of the data offers unique insight into the dynamic signal changes underlying the perception of a tonic mechanical pain experience.

neuroscience↗