Biology subjects

Fox, T.

Publications and source records attributed to Fox, T..

5 recordsLinked to original sources

bioRxiv2026

SpectroBird: Event-Level Vocalization Detection and Curation for Avian Ecology

Passive acoustic monitoring often summarizes long recordings as fixed-window presence predictions, but many ecological questions require records of individual vocal events: how many occurred, when they occurred, whether they overlapped, how long they lasted, what frequency band they occupied, and whether each event was complete enough for structural measurement. We address this event-level measurement problem with SpectroBird, a spectrogram-based method for localizing and curating avian vocalizations in noisy field recordings. SpectroBird first applies a detection-localization model to identify candidate vocalizations as time-frequency boxes. An event-consolidation step merges repeated detections from overlapping windows while preserving overlapping vocalizations as separate events. A completeness-curation model then classifies each consolidated event as complete or incomplete before downstream event-level analysis. We demonstrate SpectroBird on breeding-season Hume's Leaf Warbler buzz vocalizations recorded in the Himalaya across a 3,200-3,800 m elevational gradient. Under shared window-level scoring, the detection-localization model remained competitive with AST and YOLOv11-cls baselines while retaining event timing and frequency bounds; event-level evaluation achieved AP > 0.999 for complete buzzes. Applied to two field seasons, the resulting event records showed that duration of complete buzzes declined with elevation, complete-buzz occurrence showed no simple elevation trend, and relative day-of-year occurrence patterns were strongly correlated between years. These results show how event-level detection and curation can support ecological analyses that depend on individual vocalizations rather than fixed-window presence alone.

bioinformatics↗

bioRxiv2023

Solid Tumor Treatment via Augmentation of Bioactive C6 Ceramide Levels with Thermally Ablative Focused Ultrasound

Sparse scan partial thermal ablation (TA) with focused ultrasound (FUS) may be deployed to treat solid tumors and increase delivery of systemically administered therapeutics. Further, C6-ceramide-loaded nanoliposomes (CNLs), which rely upon the enhanced permeation and retention (EPR) effect for delivery, have shown promise for treating solid tumors and are being tested in clinical trials. Here, our objective was to determine whether CNLs synergize with TA in the control of 4T1 breast tumors. CNL-monotherapy of 4T1 tumors yielded significant intratumoral bioactive C6 accumulation by the EPR effect, but tumor growth was not controlled. TA increased bioactive C6 accumulation by [~]12.5-fold over the EPR effect. In addition, TA+CNL caused shifts in long-chain to very-long-chain ceramide ratios (i.e., C16/24 and C18/C24) that could potentially contribute to tumor control. Nonetheless, these changes in intratumoral ceramide levels were still insufficient to confer tumor growth control beyond that achieved when combining with TA with control "ghost" nanoliposomes (GNL). While this lack of synergy could be due to increased "pro-tumor" sphingosine-1-phosphate (S1P) levels, this is unlikely because S1P levels exhibited only a moderate and statistically insignificant increase with TA+CNL. In vitro studies showed that 4T1 cells are highly resistant to C6, offering the most likely explanation for the inability of TA to synergize with CNL. Thus, while our results show that sparse scan TA is a powerful approach for markedly enhancing CNL delivery and generating "anti-tumor" shifts in long-chain to very-long-chain ceramide ratios, resistance of the tumor to C6 can still be a rate-limiting factor for some solid tumor types.

bioengineering↗

bioRxiv2021

A morphometric double dissociation: cortical thickness is more related to aging; surface area is more related to cognition

The thickness and surface area of cortex are genetically distinct aspects of brain structure, and may be affected differently by age. However, their potential to differentially predict age and cognitive abilities has been largely overlooked, likely because they are typically aggregated into the commonly used measure of volume. In a large sample of healthy adults (N=647, aged 18-88), we investigated the brain-age and brain-cognition relationships of thickness, surface area, and volume, plus five additional morphological shape metrics. Cortical thickness was the metric most strongly associated with age cross-sectionally, as well as exhibiting the steepest longitudinal change over time (subsample N=261, aged 25-84). In contrast, surface area was the best single predictor of age-residualized cognitive abilities (fluid intelligence), and changes in surface area were most strongly associated with cognitive change over time. These findings were replicated in an independent dataset (N=1345, aged 18-93). Our results suggest that cortical thickness and surface area make complementary contributions the age-brain-cognition triangle, and highlight the importance of considering these volumetric components separately.

neuroscience↗

bioRxiv2020

Stretch and Twist of HEAT Repeats Leads to Activation of DNA-PK Kinase

Phosphatidylinositol 3-kinase-related kinases (PIKKs) are composed of conserved FAT and kinase domains (FATKIN) along with varied solenoid structures made of HEAT repeats. These kinases are activated in response to cellular stress signals, but the mechanisms governing activation and regulation remain unresolved. For DNA-dependent protein kinase (DNA-PK), all existing structures represent inactive states with resolution limited to 4.3 [A] at best. Here we report the cryoEM structures of DNA-PKcs (catalytic subunit) bound to a DNA end, or complexed with Ku70/80 and DNA, in both inactive and activated forms at resolutions of 3.7 [A] overall, and 3.2 [A] for FATKIN. These structures reveal the sequential transition of DNA-PK from inactive to activated forms. Most notably, activation of the kinase involves previously unknown stretching and twisting within individual solenoid segments and coordinated shifts of neighboring segments in opposite directions. This unprecedented structural plasticity of helical repeats may be a general feature of HEAT-repeat proteins.

biochemistry↗

bioRxiv2020

Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge

The SAMPL Challenges aim to focus the biomolecular and physical modeling community on issues that limit the accuracy of predictive modeling of protein-ligand binding for rational drug design. In the SAMPL5 log D Challenge, designed to benchmark the accuracy of methods for predicting drug-like small molecule transfer free energies from aqueous to nonpolar phases, participants found it difficult to make accurate predictions due to the complexity of protonation state issues. In the SAMPL6 log P Challenge, we asked participants to make blind predictions of the octanol-water partition coefficients of neutral species of 11 compounds and assessed how well these methods performed absent the complication of protonation state effects. This challenge builds on the SAMPL6 pKa Challenge, which asked participants to predict pKa values of a superset of the compounds considered in this log P challenge. Blind prediction sets of 91 prediction methods were collected from 27 research groups, spanning a variety of quantum mechanics (QM) or molecular mechanics (MM)-based physical methods, knowledge-based empirical methods, and mixed approaches. There was a 50% increase in the number of participating groups and a 20% increase in the number of submissions compared to the SAMPL5 log D Challenge. Overall, the accuracy of octanol-water log P predictions in SAMPL6 Challenge was higher than cyclohexane-water log D predictions in SAMPL5, likely because modeling only the neutral species was necessary for log P and several categories of method benefited from the vast amounts of experimental octanol-water log P data. There were many highly accurate methods: 10 diverse methods achieved RMSE less than 0.5 log P units. These included QM-based methods, empirical methods, and mixed methods with physical modeling supported with empirical corrections. A comparison of physical modeling methods showed that QM-based methods outperformed MM-based methods. The average RMSE of the most accurate five MM-based, QM-based, empirical, and mixed approach methods based on RMSE were 0.92{+/-}0.13, 0.48{+/-}0.06, 0.47{+/-}0.05, and 0.50{+/-}0.06, respectively.

biophysics↗