No abstract

Leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting protein 1 (lingo-1) is selectively expressed on neurons and oligodendrocytes in the central nervous system and acts as a negative regulator in neural repair, implying a potential role in optic neuropathy. The aim of the present study was to determine whether adeno-associated virus serotype 2 (AAV2) vector-mediated transfer of lingo-1 short hairpin RNA could reduce nerve crush-induced axonal degeneration and enhance axonal regeneration following optic nerve (ON) injury in vivo. The expression of lingo-1 was knocked down in vivo using a green fluorescent protein (GFP)-tagged AAV2 encoding lingo-1 shRNA via intravitreal injection in adult Sprague-Dawley rats. Silencing effects of AAV2-lingo-1-shRNA were confirmed by detecting GFP labelling of RGCs, and by quantifying lingo-1 expression levels with reverse transcription-quantitative polymerase chain reaction and western blotting. Rats received an intravitreal injection of AAV2-lingo-1-shRNA or negative control shRNA. The ON crush (ONC) injury was performed 2 weeks after the intravitreal injection. RGC density, lesion volume of the injured ON and the visual electrophysiology [flash visual evoked potential (F-VEP)] at different time points post-injury were determined. Transduction with lingo-1-shRNA decreased lingo-1 expression levels and promoted RGC survival following ONC. Lingo-1-shRNA promoted ON tissue repair and functional recovery. The mechanism underlying the effect of AAV2-lingo-1-shRNA on RGCs may be the phosphorylation of protein kinase B (Akt) at Ser473 and activation of the Akt signaling pathway acting downstream of lingo-1. The results of the current study indicate that the inhibition of lingo-1 may enhance RGC survival and facilitate functional recovery following ON injury, representing a promising potential strategy for the repair of optic neuropathy.

The normative anthropometric parameters are fundamental to interpret the morphology of eyes and to design plastic surgery for young Chinese adults. The parameters of palpebral fissure index, canthal index, crease height, and angle of exocanthion are strong indicators of aesthetic assessment.

Objective This study aimed to preoperatively differentiate primary gastric lymphoma from Borrmann type IV gastric cancer by heterogeneity nomogram based on routine contrast-enhanced computed tomographic images. Methods We enrolled 189 patients from 2 hospitals (90 in the training cohort and 99 in the validation cohort). Subjective findings, including high-enhanced mucosal sign, high-enhanced serosa sign, nodular or an irregular outer layer of the gastric wall, and perigastric fat infiltration, were assessed to construct a subjective finding model. A deep learning model was developed to segment tumor areas, from which 1680 three-dimensional heterogeneity radiomic parameters, including first-order entropy, second-order entropy, and texture complexity, were extracted to build a heterogeneity signature by least absolute shrinkage and selection operator logistic regression. A nomogram that integrates heterogeneity signature and subjective findings was developed by multivariate logistic regression. The diagnostic performance of the nomogram was assessed by discrimination and clinical usefulness. Results High-enhanced serosa sign and nodular or an irregular outer layer of the gastric wall were identified as independent predictors for building the subjective finding model. High-enhanced serosa sign and heterogeneity signature were significant predictors for differentiating the 2 groups (all, P < 0.05). The area under the curve with heterogeneity nomogram was 0.932 (95% confidence interval, 0.863–0.973) in the validation cohort. Decision curve analysis and stratified analysis confirmed the clinical utility of the heterogeneity nomogram. Conclusions The proposed heterogeneity radiomic nomogram on contrast-enhanced computed tomographic images may help differentiate primary gastric lymphoma from Borrmann type IV gastric cancer preoperatively.