Dipole localization, a fundamental challenge in electromagnetic source imaging, inherently constitutes an optimization problem aimed at solving the inverse problem of electric current source estimation within the human brain. The accuracy of dipole localization algorithms is contingent upon the complexity of the forward model, often referred to as the head model, and the signal-to-noise ratio (SNR) of measurements. In scenarios characterized by low SNR, often corresponding to deep-seated sources, existing optimization techniques struggle to converge to global minima, thereby leading to the localization of dipoles at erroneous positions, far from their true locations. This study presents a novel hybrid algorithm that combines simulated annealing with the traditional quasi-Newton optimization method, tailored to address the inherent limitations of dipole localization under low-SNR conditions. Using a realistic head model for both electroencephalography (EEG) and magnetoencephalography (MEG), it is demonstrated that this novel hybrid algorithm enables significant improvements of up to 45% in dipole localization accuracy compared to the often-used dipole scanning and gradient descent techniques. Localization improvements are not only found for single dipoles but also in two-dipole-source scenarios, where sources are proximal to each other. The novel methodology presented in this work could be useful in various applications of clinical neuroimaging, particularly in cases where recordings are noisy or sources are located deep within the brain.

Osteoporosis is a widespread skeletal disease characterized by low bone mass and microarchitectural deterioration, leading to fragile bones and high fracture risk[1]. Current therapies, such as bisphosphonates and RANKL inhibitors, are effective at reducing bone loss but suffer from poor targeting, low oral bioavailability[2], and significant side effects. We propose a novel nanoparticle-based therapeutic strategy to address these limitations. In this research proposal, a dual-targeted, stimuli-responsive nanoparticle (NP) system is designed for the precision treatment of osteoporosis. The NP consists of a biodegradable poly (lactic-co-glycolic acid) (PLGA) core loaded with the anti-resorptive drug risedronate [3]. The NP is functionalized with two targeting ligands: one ligand confers strong binding to bone mineral (hydroxyapatite), and a second ligand specifically targets osteoclasts or bone resorption sites (e.g. a RANKL-mimetic peptide). Additionally, the NP is coated with a pH-sensitive polymer (such as poly(L-histidine) or a chitosan derivative) that remains stable at physiological pH but triggers drug release in the acidic microenvironment of active bone resorption sites. We hypothesize that this dual-targeted, acid-responsive NP will preferentially deliver risedronate to osteoporotic bone lesions, enhancing local efficacy while minimizing off-target exposure.This proposal outlines the rationale and design of the nanoparticle system, the synthesis and formulation methods, and detailed experimental plans for in vitro and in vivo testing. In vitro studies will evaluate NP characterization, pH-responsive drug release, bone-binding affinity, cellular uptake by osteoclasts, and anti-resorptive efficacy in cell culture. In vivo studies will utilize an ovariectomized osteoporotic rodent model to assess oral bioavailability, biodistribution to bone, therapeutic efficacy in improving bone density and strength, and safety profile compared to free risedronate. We will also include comparisons to single-target or non-responsive nanoparticle variants to demonstrate the advantages of the dual-targeted, stimuli-responsive approach. By integrating dual targeting and stimuli-triggered release, this strategy aims to significantly improve the precision of osteoporosis treatment. The expected outcome is a nanoparticle therapy that achieves higher drug concentration at bone lesions, greater inhibition of bone resorption, and fewer systemic side effects than current treatments. If successful, this research will pave the way for a new class of targeted osteoporosis therapeutics with improved efficacy and patient compliance.

Cytochrome c oxidase (CCO) is widely regarded as the primary photoacceptor underlying photobiomodulation (PBM), in which light absorption stimulates mitochondrial respiration by promoting electron transfer through CCO. Single-molecule plasmonic nanopore measurements were used to examine cytochrome c (CC)–CCO interactions across three excitation wavelengths spanning the near-infrared range, which is preferred for PBM studies in vivo due to increased tissue penetration. Wavelength-dependent measurements of CC–CCO interactions were performed under normoxic, hypoxic, and allosterically inhibited conditions, revealing distinct interaction populations that are obscured in ensemble measurements. CC–CCO interactions were resolved into short-duration, long-duration, and heterogeneous populations for all wavelengths and oxygenation conditions. The short-duration population was selectively and substantially depleted by both hypoxia and ADDA5-mediated allosteric inhibition, supporting its assignment as a distinct, putative electron-transfer-associated interaction state. Allosteric inhibition strongly favored the long-duration population, whereas hypoxia predominantly increased heterogeneous duration interactions, consistent with non-specific binding. Under normoxia, 820 nm and 905 nm produced statistically comparable population fractions of the putative electron-transfer-active population, whereas the corresponding population fraction at 1064 nm was significantly lower but remained substantial. The short-duration binding population kinetics remained largely unchanged across wavelength and oxygenation states, indicating that these conditions primarily altered access to the CCO binding site rather than affecting its binding lifetime. These findings reveal the previously unresolved heterogeneity in CC–CCO interactions and provide a single-molecule framework for understanding how the excitation wavelength and oxygenation state may influence molecular interactions relevant to PBM efficiency.