Biology subjects

Lim, J.-S.

Publications and source records attributed to Lim, J.-S..

3 recordsLinked to original sources

bioRxiv2021

Strategic infarct locations for post-stroke depressive symptoms: a lesion- and disconnection-symptom mapping study

BackgroundDepression is the most common neuropsychiatric complication after stroke. Infarct location is associated with post-stroke depressive symptoms (PSDS), but it remains debated which brain structures are critically involved. We performed a large-scale lesion-symptom mapping study to identify infarct locations, and white matter disconnections, associated with PSDS. MethodsWe included 553 patients (age 69{+/-}11 years, 42% female) with acute ischemic stroke. PSDS were measured using the 30-item Geriatric Depression Scale (GDS-30). Multivariable support vector regression (SVR)-based analyses were performed both at the level of individual voxels (SVR-VLSM) and predefined regions of interest (SVR-ROI) to relate infarct location to PSDS. We externally validated our findings in an independent stroke cohort (N=459). Finally, disconnectome-based analyses were performed using SVR-VLSM, in which white matter fibers disconnected by the infarct were analyzed instead of the infarct itself. Results: Infarcts in the right amygdala, right hippocampus and right pallidum were consistently associated with PSDS (permutation-based p<0.05) in SVR-VLSM and SVR-ROI. External validation (N=459) confirmed the association between infarcts in the right amygdala and pallidum, but not the right hippocampus, and PSDS. Disconnectome-based analyses revealed that disconnections in the right parahippocampal white matter, right thalamus and pallidum, and right anterior thalamic radiation were significantly associated (permutation-based p<0.05) with PSDS. ConclusionsInfarcts in the right amygdala and pallidum, and disconnections of right limbic and frontal cortico-basal ganglia-thalamic circuits, are associated with PSDS. Our findings provide a comprehensive and integrative picture of strategic infarct locations for PSDS, and shed new light on pathophysiological mechanisms of depression after stroke.

neuroscience↗

bioRxiv2021

Modelling the deathbed of ASF-infected wild boars in South Korea using 2019-2020 national surveillance data

In September 2019, African swine fever (ASF) was reported in South Korea for the first time. Since then, more than 651 ASF cases in wild boars and 14 farm outbreaks have been notified in the country. The purpose of this study was to characterize the spatial distribution of ASF-positive wild boar carcasses to identify the risk factors associated with the presence of ASF and number of ASF-positive wild boar carcasses in the affected areas. To achieve this objective, we divided the study into two periods (October 2, 2019, to January 19, 2020, and January 19 to April 28, 2020) and aggregated the number of reported ASF-positive carcasses into a regular grid of hexagons. To account for imperfect detection, we adjusted spatial zero-inflated Poisson regression models to the number of ASF-positive wild boar carcasses per hexagons. During the first study period, only proximity to North Korea was identified as a risk factor for the presence of African swine fever virus (ASFV). In addition, there were more reports in the affected hexagons with a high habitat suitability for wild boar, low heat load index (HLI), and high human density. During the second study period, proximity to an ASF-positive carcass reported during the first period was the only significant risk factor for the presence of ASF-positive carcasses. Additionally, high HLI and low elevation were associated with an increased number of ASF-positive carcasses reported in the affected hexagons. Although the proportion of ASF-affected hexagons increased from 0.06 (95% credible interval [CrI]: 0.05-0.07) to 0.09 (95% CrI: 0.08-0.10), the probability of reporting ASF-affected hexagons increased substantially from 0.49 (95% CrI: 0.41-0.57) to 0.73 (95% CrI: 0.66-0.81) between the two study periods. These results can be used to further advance risk-based surveillance.

ecology↗

bioRxiv2020

Generative lesion pattern decomposition of cognitive impairment after stroke

Cognitive impairment is a frequent and disabling sequela of stroke. There is however incomplete understanding of how lesion topographies in the left and right cerebral hemisphere brain interact to cause distinct cognitive deficits. We integrated machine learning and Bayesian hierarchical modeling to enable hemisphere-aware analysis of 1080 subacute ischemic stroke patients with deep profiling [~]3 months after stroke. We show relevance of the left hemisphere in the prediction of language and memory assessments, while global cognitive impairments were equally well predicted by lesion topographies from both sides. Damage to the hippocampal and occipital regions on the left were particularly informative about lost naming and memory function. Global cognitive impairment was predominantly linked to lesioned tissue in supramarginal and angular gyrus, the postcentral gyrus as well as the lateral occipital and opercular cortices of the left hemisphere. Hence, our analysis strategy uncovered that lesion patterns with unique hemispheric distributions are characteristic of how cognitive capacity is lost due to ischemic brain tissue damage.

neuroscience↗