Role of Rapamycin and 3-MA in oxidative damage of HLECs caused by two doses of UVB radiation

Background:This study compared the role of autophagy regulators Rapamycin and 3-MA in oxidative damage and apoptosis of human lens epithelial cells(HLECs)caused by two doses of Ultraviolet Radiation B(UVB).Methods:HLECs were irradiated with UVB,and two doses of UVB damage models were constructed.After treatment with autophagy regulators,cell damage tests such as CCK-8,LDH activity,and Ros detection were performed.Western blotting was used to detect the levels of autophagy-related proteins and apoptosis-related proteins.Quantitative real-time PCR(RT-qPCR)was used to detect the mRNA leve of secondary antioxidant enzymes.Flow cytometry was used to examine cell viability and apoptosis.Finally,the proportion of autophagy and apoptosis was observed by electron microscope.Results:Autophagy inhibitor 3-MA promoted oxidative damage and apoptosis of HLECs at low doses of UVB(5 mJ/cm2),which corresponds to 1.3 h of exposure to sunlight in human eyes.Under the high dose of UVB(50mJ/cm2),which is equivalent to 13 h of exposure to sunlight in human eyes,the autophagy inducer Rapamycin caused more extensive oxidative damage and apoptosis of HLECs.3-MA was able to reduce this damage,indicating that moderate autophagy is necessary for HLECs to cope with mild oxidative stress.For high dose UVBinduced oxidative stress,the use of 3-MA inhibiting autophagy is more beneficial to reduce cell damage and apoptosis.The mechanisms include degradation of damaged organelles,regulation of the expression of antioxidant enzymes HO-1,NQO1,GCS and regulation of apoptosis-related proteins.Conclusions:Autophagy played different roles in HLECs oxidative stress induced by two doses of UVB.It provides new ideas for reducing oxidative damage and apoptosis of HLECs to prevent or delay the progression of agerelated cataract(ARC).

Pavement crack image acquisition methods and crack extraction algorithms:A review

The extraction of pavement cracks is always a hard task in image processing.In airport and road construction,cracking is the main factor for pavement damage,which can decrease the quality of pavement and affect transportation seriously.Cracks also exist in other artificial or natural objects,such as buildings,bridges,tunnels,etc.Among all the object images,pavement crack images are the most complex,so the image processing and analysis for them is harder than other crack images.From the early image acquisition based on photography technology to the current 3 D laser scanning technology,the pavement crack image acquisition technology is becoming more convenient and efficient,but there are still challenges in the automatic processing and recognition of cracks in images.From the early global thresholding to deep learning algorithms,the research for crack extraction has been developed for about 40 years.There are many methods and algorithms that are satisfactory in pavement crack applications,but there is no standard until today.Therefore,in order to know the developing history and the advanced research,we have collected a number of literature in this research topic for summarizing the research artwork status,and giving a review of the pavement crack image acquisition methods and2 D crack extraction algorithms.Also,for image acquisition methods and pavement crack image segmentation,more detailed comparison and discussions are made.

The barriers to global eye care equity and the role of digital innovations

1.Introduction Ophthalmology has benefited from a myriad of digital innovations ranging from simple virtual clinics to complex deep-learning imaging analysis.1 With an increasingly ageing global population,the need for population eye health planning is paramount and should be recognised as an essential aspect of overall health.2 However,high-quality eye health services are often not universally delivered.This is especially the case in low middle-income countries(LMICs),whose populations suffer far more in blindness and visual impairment compared to wealthier countries.3 Numerous social determinants,including low education levels,poverty,physical distance,and socio-cultural situations,can all contribute towards inequitable access to eye care services.4 New modes of healthcare delivery proposed by digital innovations have the potential to reduce inequity.