Evaluation of ultrasound-assisted thrombolysis using custom liposomes in a model of retinal vein occlusion

Application of ensemble machine learning approach to assess the factors affecting size and polydispersity index of liposomal nanoparticles

Liposome nanoparticles have emerged as promising drug delivery systems due to their unique properties. Assessing particle size and polydispersity index (PDI) is critical for evaluating the quality of these liposomal nanoparticles. However, optimizing these parameters in a laboratory setting is both costly and time-consuming. This study aimed to apply a machine learning technique to assess the impact of specific factors, including sonication time, extrusion temperature, and compositions, on the size and PDI of liposomal nanoparticles. Liposomal solutions were prepared and subjected to sonication with varying values for these parameters. Two compositions: (A) HSPC:DPPG:Chol:DSPE-mPEG2000 at 55:5:35:5 molar ratio and (B) HSPC:Chol:DSPE-mPEG2000 at 55:40:5 molar ratio, were made using remote loading method. Ensemble learning (EL), a machine learning technique, was employed using the Least-squares boosting (LSBoost) algorithm to accurately model the data. The dataset was randomly split into training and testing sets, with 70% allocated for training. The LSBoost algorithm achieved mean absolute errors of 1.652 and 0.0105 for modeling the size and PDI, respectively. Under conditions where the temperature was set at approximately 60 °C, our EL model predicted a minimum particle size of 116.53 nm for composition (A) with a sonication time of approximately 30 min. Similarly, for composition (B), the model predicted a minimum particle size of 129.97 nm with sonication times of approximately 30 or 55 min. In most instances, a PDI of less than 0.2 was achieved. These results highlight the significant impact of optimizing independent factors on the characteristics of liposomal nanoparticles and demonstrate the potential of EL as a decision support system for identifying the best liposomal formulation. We recommend further studies to explore the effects of other independent factors, such as lipid composition and surfactants, on liposomal nanoparticle characteristics.

Gene expression profiling in a mouse model of retinal vein occlusion induced by laser treatment reveals a predominant inflammatory and tissue damage response

Purpose

Retinal vein occlusion (RVO) has been investigated in several laser-induced animal models using pigs, rabbits and rats. However, laser-induced RVO has been rarely reported in mice, despite the impressive number of available mutants, ease of handling and cost effectiveness. The aim of this study was to further assess the feasibility of a RVO mouse model for gene expression analysis and its possible use to investigate effects of hypoxia.

Methods

C57Bl/6J mice were injected with eosin Y for photo-sensitization. Subsequently, large retinal veins were laser-treated in one eye to induce vascular occlusion. Contralateral control eyes received non-occlusive retinal laser treatment sparing large vessels. The animals were followed for up to eight days and assessed by funduscopy, angiography, hypoxyprobe staining, histopathology and gene expression analysis by qPCR and RNA sequencing (RNAseq). Another group of mice was left untreated and studied at a single time point to determine baseline characteristics.

Results

Laser-induced RVO persisted in half of the treated veins for three days, and in a third of the veins for the whole observation period of 8 days. Funduscopy revealed large areas of retinal swelling in all laser-treated eyes, irrespective of vascular targeting or occlusion status. Damage of the outer retina, retinal pigment epithelium (RPE), and even choroid and sclera at the laser site was observed in histological sections. Genes associated with inflammation or cell damage were highly up-regulated in all laser-treated eyes as detected by RNAseq and qPCR. Retinal hypoxia was observed by hypoxyprobe staining in all RVO eyes for up to 5 days with a maximal extension at days 2 and 3, but no significant RVO-dependent changes in gene expression were detected for angiogenesis- or hypoxia-related genes.

Conclusion

The laser-induced RVO mouse model is characterized by a predominant general inflammatory and tissue damage response, which may obscure distinct hypoxia- and angiogenesis-related effects. A non-occlusive laser treatment control is essential to allow for proper data interpretation and should be mandatory in animal studies of laser-induced RVO to dissect laser-induced tissue damage from vascular occlusion effects.

Seeing through thick and through thin: Retinal manifestations of thrombophilic and hyperviscosity syndromes

The presence of retinal vasculopathy in the absence of typical predisposing factors should suggest a possible underlying hematologic abnormality. In such cases, a systemic investigation may reveal a potentially fatal hypercoagulability or hyperviscosity syndrome. Retinal vein occlusion is the most commonly encountered ophthalmic finding in such syndromes; however, abnormalities of the arterial system, the choroid, and the macula are also possible. Visual symptoms may be the only manifestation of the underlying process, making timely diagnosis by the ophthalmologist critical for both treatment and thrombotic prophylaxis. Moreover, as newer ophthalmic diagnostic technologies arise, there is an increasingly important role for eye physicians in the management of such syndromes.