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1.
J Nanobiotechnology ; 22(1): 134, 2024 Mar 28.
Article in English | MEDLINE | ID: mdl-38549081

ABSTRACT

BACKGROUND: Corneal neovascularization (CoNV) threatens vision by disrupting corneal avascularity, however, current treatments, including pharmacotherapy and surgery, are hindered by limitations in efficacy and adverse effects. Minocycline, known for its anti-inflammatory properties, could suppress CoNV but faces challenges in effective delivery due to the cornea's unique structure. Therefore, in this study a novel drug delivery system using minocycline-loaded nano-hydroxyapatite/poly (lactic-co-glycolic acid) (nHAP/PLGA) nanoparticles was developed to improve treatment outcomes for CoNV. RESULTS: Ultra-small nHAP was synthesized using high gravity technology, then encapsulated in PLGA by a double emulsion method to form nHAP/PLGA microspheres, attenuating the acidic by-products of PLGA degradation. The MINO@PLGA nanocomplex, featuring sustained release and permeation properties, demonstrated an efficient delivery system for minocycline that significantly inhibited the CoNV area in an alkali-burn model without exhibiting apparent cytotoxicity. On day 14, the in vivo microscope examination and ex vivo CD31 staining corroborated the inhibition of neovascularization, with the significantly smaller CoNV area (29.40% ± 6.55%) in the MINO@PLGA Tid group (three times daily) than that of the control group (86.81% ± 15.71%), the MINO group (72.42% ± 30.15%), and the PLGA group (86.87% ± 14.94%) (p < 0.05). Fluorescein sodium staining show MINO@PLGA treatments, administered once daily (Qd) and three times daily (Tid) demonstrated rapid corneal epithelial healing while the Alkali injury group and the DEX group showed longer healing times (p < 0.05). Additionally, compared to the control group, treatments with dexamethasone, MINO, and MINO@PLGA were associated with an increased expression of TGF-ß as evidenced by immunofluorescence, while the levels of pro-inflammatory cytokines IL-1ß and TNF-α demonstrated a significant decrease following alkali burn. Safety evaluations, including assessments of renal and hepatic biomarkers, along with H&E staining of major organs, revealed no significant cytotoxicity of the MINO@PLGA nanocomplex in vivo. CONCLUSIONS: The novel MINO@PLGA nanocomplex, comprising minocycline-loaded nHAP/PLGA microspheres, has shown a substantial capacity for preventing CoNV. This study confirms the complex's ability to downregulate inflammatory pathways, significantly reducing CoNV with minimal cytotoxicity and high biosafety in vivo. Given these findings, MINO@PLGA stands as a highly promising candidate for ocular conditions characterized by CoNV.


Subject(s)
Corneal Neovascularization , Minocycline , Humans , Minocycline/pharmacology , Corneal Neovascularization/drug therapy , Corneal Neovascularization/prevention & control , Microspheres , Angiogenesis , Alkalies
2.
Neurol Sci ; 45(7): 3267-3275, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38372842

ABSTRACT

PURPOSE: This study aimed to assess alterations in retinal vascular density in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) patients using optical coherence tomography angiography (OCTA) and investigate their association with MRI and cognitive features. METHODS: Twenty-five patients with CADASIL and forty healthy controls were evaluated by Cirrus HD-OCT 5000 with AngioPlex OCTA to determine changes in macular retinal vasculature. Retinal vasculature parameters between two groups were compared. The MRI lesion burden and neuropsychological scales were also examined in patients. The association between OCTA parameters and MRI/cognitive features was evaluated using partial Spearman rank correlation. RESULTS: The vessel density and perfusion density of whole image in macular region (vessel density: t = - 2.834, p = 0.005; perfusion density: t = - 2.691, p = 0.007) were significantly decreased in patients with CADASIL. Moreover, vessel density of whole image in macular region was negatively associated with Fazekas scores (ρ = - 0.457; p = 0.025) and the number of lacunar infractions (ρ = - 0.425, p = 0.038) after adjustment for age. Decreased macular vessel density and perfusion density of whole image were also associated with MoCA scores (vessel density: ρ = 0.542, p = 0.006; perfusion density: ρ = 0.478, p = 0.018) and other domain-specific neuropsychological tests (p < 0.05) after adjustment for age. CONCLUSION: Decreased retinal vascular density was associated with increased MRI lesion burden and cognitive impairment in patients with CADASIL. Our findings suggest that the degree of retinal vascular involvement, as demonstrated by OCTA, may be consistent with the severity of MRI lesions and the degree of cognitive impairment in patients.


Subject(s)
CADASIL , Cognitive Dysfunction , Retinal Vessels , Tomography, Optical Coherence , Humans , CADASIL/diagnostic imaging , CADASIL/complications , CADASIL/pathology , Male , Female , Tomography, Optical Coherence/methods , Middle Aged , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/etiology , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/pathology , Retinal Vessels/diagnostic imaging , Retinal Vessels/pathology , Magnetic Resonance Imaging , Adult , Aged
3.
Front Endocrinol (Lausanne) ; 13: 1036735, 2022.
Article in English | MEDLINE | ID: mdl-36733798

ABSTRACT

Objective: To explore intraretinal blood flow perfusion and nerve changes, as well as the correlation between them, in diabetic patients without diabetic retinopathy (NDR). Method: Eighty-six NDR patients (86 eyes) who attended the ophthalmology clinic between December 2019 and December 2021 were included. Sixty-four eyes of 64 healthy examined controls in the same period were selected as the control group. The patients underwent routine ophthalmological examination, optical coherence tomography (OCT) and OCT angiography. Results: The average thickness, minimum thickness and thickness of each quadrant except for the superior temporal quadrant of the ganglion cell-inner plexiform layer (GCIPL) in the macular area of the affected eyes in the NDR group were lower than that of the tested eyes in the control group (P < 0.05). The average retinal nerve fibre layer (RNFL) thickness of the NDR group and the superior, inferior and nasal quadrants around the optic disc of the affected eyes in the NDR group were lower compared with the tested eyes in the control group (P < 0.001, P = 0.003, P = 0.001, P = 0.009). The mean vessel length density in the parafoveal and perifoveal areas in the NDR group was positively associated with the mean GCIPL thickness in the macular area (ρ = 0.265, ρ = 0.257 and P < 0.001). No blood flow perfusion parameters in the NDR group were correlated with the RNFL thickness of the corresponding quadrant around the optic disc (P > 0.05). Conclusion: In diabetic patients without diabetic retinopathy, the superficial retinal vessel density in the macular area positively correlated with GCIPL thickness, and the superficial retinal vessel density around the optic disc was not correlated with RNFL thickness.


Subject(s)
Diabetes Mellitus , Diabetic Retinopathy , Retinal Diseases , Humans , Retinal Ganglion Cells , Nerve Fibers , Retina , Tomography, Optical Coherence/methods
4.
J Med Imaging (Bellingham) ; 6(2): 025008, 2019 Apr.
Article in English | MEDLINE | ID: mdl-31259200

ABSTRACT

Microaneurysms (MAs) play an important role in the diagnosis of clinical diabetic retinopathy at the early stage. Annotation of MAs manually by experts is laborious and so it is essential to develop automatic segmentation methods. Automatic MA segmentation remains a challenging task mainly due to the low local contrast of the image and the small size of MAs. A deep learning-based method called U-Net has become one of the most popular methods for the medical image segmentation task. We propose an architecture for U-Net, named deep recurrent U-Net (DRU-Net), obtained by combining the deep residual model and recurrent convolutional operations into U-Net. In the MA segmentation task, DRU-Net can accumulate effective features much better than the typical U-Net. The proposed method is evaluated on two publicly available datasets: E-Ophtha and IDRiD. Our results show that the proposed DRU-Net achieves the best performance with 0.9999 accuracy value and 0.9943 area under curve (AUC) value on the E-Ophtha dataset. And on the IDRiD dataset, it has achieved 0.987 AUC value (to our knowledge, this is the first result of segmenting MAs on this dataset). Compared with other methods, such as U-Net, FCNN, and ResU-Net, our architecture (DRU-Net) achieves state-of-the-art performance.

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