Research progress in artificial intelligence assisted diabetic retinopathy diagnosis

Diabetic retinopathy(DR)is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide.Early detection and treatment can effectively delay vision decline and even blindness in patients with DR.In recent years,artificial intelligence(AI)models constructed by machine learning and deep learning(DL)algorithms have been widely used in ophthalmology research,especially in diagnosing and treating ophthalmic diseases,particularly DR.Regarding DR,AI has mainly been used in its diagnosis,grading,and lesion recognition and segmentation,and good research and application results have been achieved.This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.

Prevalence and Influencing Factors on Fatigue of First-line Nurses Combating with COVID-19 in China:A Descriptive Cross-Sectional Study

Summary:Nurses'work-related fatigue has been recognized as a threat to nurse health and patient safety.The aim of this study was to assess the prevalence of fatigue among first-line nurses combating with COVID-19 in Wuhan,China,and to analyze its influencing factors on fatigue.A multi-center,descriptive,cross-sectional design with a convenience sample was used.The statistical population consisted of the first-line nurses in 7 tertiary general hospitals from March 3,2020 to March 10,2020 in Wuhan of China.A total of 2667 samples from 2768 contacted participants completed the investgation,with a response rate of 96.35%.Social-demographic questionnaire,work-related questionnaire,Fatigue Scale-14,Generalized Anxiety Disorder-7,Patient Health Questionnaire-9,and Chinese Perceived Stress Scale were used to conduct online survey.The descriptive statistic of nurses'social-demographic characteristics was conducted,and the related variables of work,anxiety,depression,perceived stress and fatigue were analyzed by Z-tests,nonparametric test and Pearson's correlation analysis.The significant factors which resulted in nurses'fatigue were further analyzed by multiple linear regression analysis.The median score for the first-line nurses'fatigue in Wuhan was 4(2,8).The median score of physical and mental fatigue of them was 3(1,6)and 1(0,3)respectively.According to the scoring criteria,35.06%nurses(w=935)of all participants were in the fatigue status,their median score of fatigue was 10(8,11),and the median score of physical and mental fatigue of them was 7(5,8)and 3(2,4)respectively.Multiple linear regression analysis revealed the participants in the risk groups of anxiety,depression and perceived stress had higher scores on physical and mental fatigue and the statistically significant positive correlation was observed between the variables and nurses'fatigue,the frequency of exercise and nurses'fatigue had a statistically significant negative correlation,and average daily working hours had a significantly positive correlation with nurses'fatigue,and the frequency of weekly night shift had a low positive correlation with nurses'fatigue(P<0.01).There was a moderate level of fatigue among the first-line nurses fighting against COVID-19 pandemic in Wuhan,China.Government and health authorities need to formulate and take effective intervention strategies according to the relevant risk factors,and undertake preventive measures aimed at reducing health hazards due to increased work-related fatigue among first-line nurses,and to enhance their health status and provide a safe occupational environment worldwide.Promoting both medical and nursing safety while combating with the pandemic currently is warranted.

Genetic dissection of glutathione S-transferase omega-1:identification of novel downstream targets and Alzheimer's disease pathways

Alzheimer's disease(AD)is affected by genetic factors.Polymorphisms in the glutathione S-transfe rase omega-1(Gsto1)gene have been shown by genetic correlation analyses performed in different ethnic populations to be genetic risk factors for AD.Gene expression profile data from BXD recombinant inbred mice were used in combination with genetic and bioinformatic analyses to chara cterize the mechanisms underlying regulation of Gstol variation regulation and to identify network membe rs that may contribute to AD risk or progression.Allele-specific assays confirmed that variation in Gstol expression is controlled by cis-expression quantitative trait loci.We found that Gstol mRNA levels were related to several central nervous system traits,such as glial acidic fibrillary protein levels in the caudate putamen,co rtical gray matter volume,and hippocampus mossy fiber pathway volume.We identified 2168 genes whose expression was highly correlated with that of Gsto1.Some genes were enriched for the most common neurodegenerative diseases.Some Gsto1-related genes identified in this study had previously been identified as susceptibility genes for AD,such as APP,Grin2 b,Ide,and Psenen.To evaluate the relationships between Gstol and candidate network members,we transfected astrocytes with Gstol siRNA and assessed the effect on putative downstream effecto rs.We confirmed that knockdown of Gstol had a significant influence on Pa2g4 expression,suggesting that Pa2g4 may be a downstream effector of Gstol,and that both genes intera ct with other genes in a network during AD pathogenesis.

Coral-shaped and Core-Shell Structure Copolyethylene Nanocomposites Particles Prepared by in situ Coordination Polymerization

The example of the preparation ofnano- and micro-scaled, coral-shaped and core-shell topological morphology of copolyethylene particles promoted by the novel heterogeneous non-metallocene catalyst （m-CH3PhO）TiC13/carbon nanotubes （CNTs） was reported. Mass fraction of titanium component of the catalyst was 4.0 wt% determined by ICP analysis. The catalyst system can effectively catalyze polymerization of ethylene and eopolymerization of ethylene with 1-hexene. Morphological examination of the obtained polymer particles was carried out by scanning electron microscope （SEM） and high resolution transmission electron microscope （HR-TEM） technique. The results revealed that the morphology of the nascent copolyethylene particles looked like coral shape with size in micro-scaled and featured the core-shell structure consisting of CNTs as the core and copolyethylene as the shell.