Application of non-mydriatic fundus photography-assisted telemedicine in diabetic retinopathy screening

BACKGROUND Early screening and accurate staging of diabetic retinopathy(DR)can reduce blindness risk in type 2 diabetes patients.DR’s complex pathogenesis involves many factors,making ophthalmologist screening alone insufficient for prevention and treatment.Often,endocrinologists are the first to see diabetic patients and thus should screen for retinopathy for early intervention.AIM To explore the efficacy of non-mydriatic fundus photography(NMFP)-enhanced telemedicine in assessing DR and its various stages.METHODS This retrospective study incorporated findings from an analysis of 93 diabetic patients,examining both NMFP-assisted telemedicine and fundus fluorescein angiography(FFA).It focused on assessing the concordance in DR detection between these two methodologies.Additionally,receiver operating characteristic(ROC)curves were generated to determine the optimal sensitivity and specificity of NMFP-assisted telemedicine,using FFA outcomes as the standard benchmark.RESULTS In the context of DR diagnosis and staging,the kappa coefficients for NMFPassisted telemedicine and FFA were recorded at 0.775 and 0.689 respectively,indicating substantial intermethod agreement.Moreover,the NMFP-assisted telemedicine’s predictive accuracy for positive FFA outcomes,as denoted by the area under the ROC curve,was remarkably high at 0.955,within a confidence interval of 0.914 to 0.995 and a statistically significant P-value of less than 0.001.This predictive model exhibited a specificity of 100%,a sensitivity of 90.9%,and a Youden index of 0.909.CONCLUSION NMFP-assisted telemedicine represents a pragmatic,objective,and precise modality for fundus examination,particularly applicable in the context of endocrinology inpatient care and primary healthcare settings for diabetic patients.Its implementation in these scenarios is of paramount significance,enhancing the clinical accuracy in the diagnosis and therapeutic management of DR.This methodology not only streamlines patient evaluation but also contributes substantially to the optimization of clinical outcomes in DR management.

Drug discovery and potential gene and pathway associated with polycystic ovary syndrome through text mining and biomedical databases

Objectives:Polycystic ovary syndrome(PCOS)is a common endocrine disease in women of childbearing age.Although it is a leading cause of menstrual disorders,infertility,obesity,and other diseases,its molecular mechanism remains unclear.This study aimed to analyze the target genes,pathways,and potential drugs for PCOS through text mining.Methods:First,three different keywords("polycystic ovary syndrome","obesity/adiposis",and"anovulation")were uploaded to GenCLiP3 to obtain three different gene sets.We then chose the common genes among these gene sets.Second,we performed gene ontology and signal pathway enrichment analyses of these common genes,followed by protein-protein interaction(PPI)network analysis.Third,the most significant gene module clustered in the protein-protein network was selected to identify potential drugs for PCOS via gene-drug analysis.Results:A total of 4291 genes related to three different keywords were obtained through text mining,72 common genes were filtered among the three gene sets,and 69 genes participated in PPI network construction,of which 23 genes were clustered in the gene modules.Finally,six of the 23 genes were targeted by 30 existing drugs.Conclusions:The discovery of the six genes(CYP19A1,ESR1,IGF1R,PGR,PTGS2,and VEGFA)and 30 targeted drugs,which are associated with ovarian steroidogenesis(P<0.001),may be used in potential therapeutic strategies for PCOS.

Identifying miRNA biomarkers of polycystic ovary syndrome through text mining

Objective:Polycystic ovary syndrome(PCOS)is an endocrine disorder with diverse clinical manifestations that often occurs in women of childbearing age.However,its molecular pathogenesis remains unclear,and this study aimed to identify miRNA targets in PCOS through text mining and database analysis.Methods:First,three different sets of text mining genes(TMGs)associated with"polycystic ovary syndrome","obesity/adiposis",and"anovulation"keywords were retrieved from the GenCLiP3 database,and overlapping genes were selected.Second,Gene ontology annotation and biological pathway enrichment analyses of these overlapping TMGs were performed,followed by protein-protein interaction(PPI)network analysis.Third,genes in the gene module clustered in the PPI were selected to predict potential miRNAs for PCOS via miRNA-mRNA analysis.Results:A total of 4291 TMGs related to three different keywords were obtained through text mining;72 intersect TMGs were retained among the three gene sets,and 62 TMGs participated in the establishment of the PPI network,of which 18 were aggregated in the gene module.Finally,11 miRNAs that simultaneously bound to two TMGs(IGF1,ESR1,MAPK1,NAMPT,PIK3CA,and SERPINE1)could be prioritized as targets to study PCOS.Conclusion(s):The discovery of 11 miRNAs(miR-301a-3p,miR-301b-3p,miR-3666,miR-454-3p,miR-130a-3p,miR-130b-3p,miR-4295,miR-190a-3p,miR-5011-5p,miR-548c-3p,and miR-4799-5p)and 6 TMGs,which are associated with the HIF-1 signaling pathway(P=4.799E-08),could be used as potential targets for PCOS.

A new class of HIV-1 inhibitors and the target identification via proteomic profiling

Anti-HIV screening with the MT-4/MTT assay on a focused library of structurally diverse natural products has led to the discovery of a group of steroids with potent activities, which include four new ergostane-type steroids, named amotsterols A-D(1-4), together with two known analogs. Among them, the most potent amotsterol D(4) exhibited anti-HIVactivity against wildtype and some clinically relevant multidrug resistant HIV-1 strains. Subsequent studies on its target identification through a proteomic approach found that compound 4 might target PKM2, a rate limiting enzyme of glycolysis, in host cells to restrict HIV replication. The docking model of compound 4 to PKM2 showed that the two hydroxyl groups of 4 form hydrogen bonds with the two parallel Y390 in each subunit of PKM2 separately, and the ring C of 4 is sandwiched between the two parallel aromatic rings of F26. The identified hit compound may have the potential to be further developed as a novel anti-HIVagent. These results demonstrated that an integrated approach, which combines new chemical structures and phenotypic screening with a proteomic approach, could not only identify novel HIV-1 inhibitors, but also elucidate the unknown targets of compound interactions in antiviral drug discovery.