Biology subjects

Loo, S.

Publications and source records attributed to Loo, S..

7 recordsLinked to original sources

bioRxiv2026

Alpha-range neural oscillations are associated with multiple dynamic brain networks

We asked whether alpha range (8-12 Hz) EEG neural oscillations, a robust indicator of cortical excitability, are associated with dynamic BOLD brain networks. Two independent EEG-fMRI resting-state datasets (discovery: n = 94 and replication: n = 33) show that low- and high-alpha periods are associated with dynamic BOLD coactivation patterns (dCAPS) involving multiple dynamic networks rather than a single static network. Unique BOLD dCAPs consisting of visual cortex activation along with sensorimotor and attention networks in addition to the posterior thalamus, were mainly associated with periods of low-alpha power. However, overlapping BOLD dCAPs consisting of default, control, and attention networks were associated with periods of both low- and high-alpha power. The results suggest low-alpha dCAPS contain unique temporal-dependent configurations related to visual, sensorimotor, and attention networks while both low- and high-alpha dCAPs consist of overlapping temporal-dependent configurations involving CON, DMN, and attention networks involved in internal and external cognition. These findings reconcile discrepancies across static connectivity EEG-fMRI findings by showing that distinct transient BOLD configurations are associated with similar patterns of alpha EEG modulation in visual cortex, providing a dynamic framework for the gating function of alpha oscillations.

neuroscience↗

bioRxiv2026

Spectral and non-spectral EEG measures in the prediction of working memory task performance and psychopathology

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examined whether scalp electroencephalography (EEG) data features beyond spectral power, including waveform shape, broadband spectral structure, and signal complexity, provide complementary information for predicting cognitive and clinical outcomes. EEG was recorded from 200 adults spanning a broad range of neuropsychiatric symptom severity while they completed three WM task paradigms: Sternberg spatial WM (SWM), delayed face recognition (DFR), and dot pattern expectancy (DPX). Separate machine learning models were trained on EEG features from the encoding, delay, and probe phase of each task to predict participants task accuracy, reaction time (RT) variability, WM capacity, and psychopathology scores (Brief Psychiatric Rating Scale). A split-half analytic framework was used, with cross-validated model development in an exploratory dataset (N=100) and evaluation of statistically significant models in a held-out validation dataset (N=100). In the exploratory dataset, SWM task data best predicted WM capacity, DPX task data predicted RT variability, and DFR task data predicted psychopathology, suggesting that these three WM paradigms engage distinct neural processes relevant to different outcomes. No models reliably predicted task accuracy. Models incorporating features beyond spectral power generally outperformed power-only models, and task-derived features outperformed resting-state-derived features. However, only those models predicting WM capacity and RT variability generalized to the validation dataset; models predicting psychopathology did not. These findings demonstrate functional heterogeneity across WM paradigms, show that complementary EEG features enhance predictive modeling, and highlight the importance of rigorous validation for identifying robust brain-behavior relationships.

neuroscience↗

bioRxiv2023

Ginsentide TP1 Protects Hypoxia-Induced Dysfunction and ER Stress-Linked Apoptosis

Hypoxia-induced vascular endothelial dysfunction (VED) is a significant contributor to several severe human conditions, including heart disease, stroke, dementia, and cancer. However, current treatment options for VED are limited due to a lack of understanding of the underlying disease mechanisms and therapeutic leads. We recently discovered a heat-stable microprotein in ginseng, known as ginsentide TP1 that has been shown to reduce vascular dysfunction in cardiovascular disease models. In this study, we use a combination of functional assays and quantitative pulsed SILAC proteomics to determine new proteins synthesized in hypoxia and to show that ginsentide TP1 provides protection for human endothelial cells against hypoxia and ER stress. We found that hypoxia activates various pathways related to endothelium activation and monocyte adhesion, which in turn, impairs nitric oxide (NO) synthase activity, reduces NO bioavailability, and increases the production of reactive oxygen species that contribute to VED. Additionally, hypoxia triggers endoplasmic reticulum stress and initiates apoptotic signaling pathways associated with cardiovascular pathology. Treatment with ginsentide TP1 reduced surface adhesion molecule expression prevented activation of the endothelium and leukocyte adhesion, restored protein hemostasis, and reduced ER stress to protect against hypoxia-induced cell death. Ginsentide TP1 also restored NO signaling and bioavailability, reduced oxidative stress, and protected endothelial cells from endothelium dysfunction. In conclusion, this study shows that the molecular pathogenesis of VED induced by hypoxia can be mitigated by treatment with ginsentide TP1, which could be one of the key bioactive compounds responsible for the "cure-all" effect of ginseng. This research may lead to the development of new therapies for cardiovascular disorders.

pharmacology and toxicology↗

bioRxiv2023

Decoding the Cure-all Effects of Ginseng

Ginseng has been known as a "cure-all" traditional medicine to treat various illnesses and as an adaptogen to relieve stress. However, the known active compounds of ginseng are small-molecule metabolites. Here we report ginsentides, which are disulfide-dense, super-stable and cell-penetrating peptides with 31-33 amino acids, as active compounds and adaptogens that restore homeostasis in response to stress. Using mass spectrometry-based target identification and functional studies, we show that ginsentides promote vasorelaxation by producing nitric oxide through endothelial cells via the PI3K/Akt signaling pathway. Ginsentides were also found to alleviate 1-adrenergic receptor overactivity by reversing phenylephrine-induced constriction of the aorta, decrease monocyte adhesion to endothelial cells via CD166/ESAM/CD40, inhibit P2Y12 receptors, reduce platelet aggregation, and thrombus formation in the lung. Orally administered ginsentides were effective in anti-stress behavior using animal models of tail suspension and forced swimming tests. Together, these results suggest that ginsentides interact with multiple systems to restore homeostasis by reversing stress-induced physiological changes and provide new insights into the panacea medicinal effects of ginseng.

pharmacology and toxicology↗

bioRxiv2022

Genomic, transcriptomic, and metabolomic analysis of Traditional Chinese Medicine plant Oldenlandia corymbosa reveals the biosynthesis and mode of action of anti-cancer metabolites

Natural products from traditional medicinal plants are valuable candidates for clinical cancer therapy. Plants from the Oldenlandia-Hedyotis complex are popular ingredients of Traditional Chinese Medicine (TCM), however a major hurdle in the plant bioprospecting process of TCM plants is that the active metabolites, their biosynthetic pathways, and mode of action are often unknown. We show that Oldenlandia corymbosa extracts are active against breast cancer cell lines. To study the genes involved in the biosynthesis of active compounds in this medicinal plant, we assembled a high-quality genome. We show that the main active compound is ursolic acid and that abiotic stresses cause changes in anti-cancer activity, metabolite composition, and gene expression of plants. To reveal the mode of action of ursolic acid, we show that cancer cells undergo mitotic catastrophe, and we identify three high-confidence protein binding targets by Cellular Thermal Shift Assay (CETSA) and reverse docking.

plant biology↗

bioRxiv2019

The Role of Gene Encoding Variation of DRD4 in the Relationship between Inattention and Seasonal Daylight

Daylight is the strongest synchronizer of human circadian rhythms. The circadian pathway hypothesis posits that synchrony between daylight and the circadian system relates to (in)attention. The dopamine neurotransmitter system is implicated in regulating the circadian system as well as in (attention)-deficit hyperactivity disorder [ADHD]. We studied the role of functional genetic variation in the gene encoding of dopamine-receptor-D4 (DRD4) in the relationship between inattention and seasonal daylight (changes). Gene-by-environment (GxE) mega-analyses were performed across eight studies including 3757 adult participants (with and without ADHD). We tested 1) the Spring-focus hypothesis, in which attention in 7R-carriers normalizes with increasing daylight levels preceding measurement, 2) the Summer-born ADHD hypothesis, in which 7R-carriers report more inattention when born in spring/summer than in autumn/winter, 3) the Winter-born ADHD hypothesis, opposing the second hypothesis. The Spring-focus hypothesis was upheld (1386 ADHD, 760 controls; d=-0.16 between periods); 7R-carriers reported even less inattention than 7R-non-carriers after winter solstice (d=0.27 between genotype-groups). Results were diagnosis-independent. Sensitivity analyses at individual study level confirmed the circannual patterns for 7R-carriers. Incorporating geographic changes into the independent measure, we also calculated changes in sunlight levels. This approach likewise showed that inattention correlated negatively with increasing light levels in 7R-carriers (r=-.135). Results emphasize peripheral effects of dopamine and the effects of (seasonal) daylight changes on cognition.

genetics↗

bioRxiv2019

Symptom Severity in Youths with Attention Deficit Hyperactivity Disorder Associated with Normalizing Effects of Treatment on fMRI Response during a Stop Signal Task

Inhibitory control deficits represent one of many core cognitive deficits in Attention-Deficit/Hyperactivity Disorder (ADHD). Neuroimaging studies suggest that individuals with ADHD exhibit atypical engagement of neural systems during response inhibition, but the exact nature of this phenotype is obscured by mixed findings. We tested whether drug-free youths with ADHD (n=30, ages 7-14 years, 10 female) exhibited atypical neural correlates of response inhibition, as measured with a stop signal task and fMRI, compared to matched controls. We next investigated medication effects and whether there was a relationship between symptom severity and medication effects on the fMRI-evaluated signal. Finally, we tested for a significant difference between effects of monotherapy and combined pharmacological treatment. Patients showed significantly slower stop signal response time and lower percent inhibition, but no significant differences in the neural correlates of response inhibition relative to controls. However, patients showed significantly elevated signal in frontostriatal regions during responses. Prefrontal signal in patients was positively associated with reaction time variability in patients, and change (medicated - drug free) in the prefrontal signal was significantly associated with symptom scores, such that patients with elevated symptoms had greater BOLD signal reduction following treatment. Medication significantly improved go response time median and variability as well as stop signal reaction time, but there were no significant effects of medication or treatment type on BOLD signal. These findings challenge the notion of frontostriatal hypoactivation during response inhibition as a biomarker for ADHD and suggest that symptom severity may be associated with response to medication.

neuroscience↗