Tear IgE point-of-care testing for differentiating type I and type IV allergic conjunctivitis

ObjectiveThis study aimed to evaluate the diagnostic utility of point-of-care tear immunoglobulin E (IgE) testing in distinguishing between type I and type IV allergic conjunctivitis (AC), and to explore tailored treatment strategies.MethodsA total of 254 patients with perennial AC at Xiamen Eye Center were enrolled. Clinical data, including age, sex, symptoms, and signs, were collected. Tear total IgE was measured using the i-ImmunDx™ platform. Univariate and multivariate logistic regression analyses, along with ROC curve analysis, were used to assess the discriminative value of tear IgE and clinical parameters for AC subtypes.ResultsThe mean patient age was 14.11 ± 12.46 years; 182 were male. Mean conjunctivitis score was 4.09 ± 1.51, and mean tear IgE was 7.73 ± 16.76 IU/mL. Tear IgE levels negatively correlated with age (p < 0.05), and positively with conjunctival secretion, papillary hyperplasia, and conjunctivitis scores (p < 0.05). Univariate analysis showed age, tear IgE, and papillae were significantly associated with type IV AC. Multivariate analysis identified tear IgE, conjunctival papillae, and conjunctivitis score as independent predictors. ROC analysis showed an AUC of 0.896 for tear IgE (cut-off = 5.57 IU/mL; sensitivity 89.00%, specificity 77.78%). A combined model (IgE + papillae + score) improved AUC to 0.912, with sensitivity of 81.50% and specificity of 88.89%.ConclusionTear IgE effectively differentiates AC subtypes and correlates with disease severity. Patients with low IgE levels, indicative of type IV hypersensitivity, benefit from individualized anti-inflammatory therapies, supporting its role in personalized management

Identification and Characterization of Alternative Promoters, Transcripts and Protein Isoforms of Zebrafish R2 Gene

Ribonucleotide reductase (RNR) is the rate-limiting enzyme in the de novo synthesis of deoxyribonucleoside triphosphates. Expression of RNR subunits is closely associated with DNA replication and repair. Mammalian RNR M2 subunit (R2) functions exclusively in DNA replication of normal cells due to its S phase-specific expression and late mitotic degradation. Herein, we demonstrate the control of R2 expression through alternative promoters, splicing and polyadenylation sites in zebrafish. Three functional R2 promoters were identified to generate six transcript variants with distinct 5′ termini. The proximal promoter contains a conserved E2F binding site and two CCAAT boxes, which are crucial for the transcription of R2 gene during cell cycle. Activity of the distal promoter can be induced by DNA damage to generate four transcript variants through alternative splicing. In addition, two novel splice variants were found to encode distinct N-truncated R2 isoforms containing residues for enzymatic activity but no KEN box essential for its proteolysis. These two N-truncated R2 isoforms remained in the cytoplasm and were able to interact with RNR M1 subunit (R1). Thus, our results suggest that multilayered mechanisms control the differential expression and function of zebrafish R2 gene during cell cycle and under genotoxic stress

Decode-seq: a practical approach to improve differential gene expression analysis

AbstractMany differential gene expression analyses are conducted with an inadequate number of biological replicates. We describe an easy and effective RNA-seq approach using molecular barcoding to enable profiling of a large number of replicates simultaneously. This approach significantly improves the performance of differential gene expression analysis. Using this approach in medaka (Oryzias latipes), we discover novel genes with sexually dimorphic expression and genes necessary for germ cell development. Our results also demonstrate why the common practice of using only three replicates in differential gene expression analysis should be abandoned.</jats:p

Additional file 3 of Decode-seq: a practical approach to improve differential gene expression analysis

Additional file 3 Supplementary methods

Additional file 5 of Decode-seq: a practical approach to improve differential gene expression analysis

Additional file 5 Review history

Additional file 1 of Decode-seq: a practical approach to improve differential gene expression analysis

Additional file 1 Supplementary figures. Fig S1: Distribution of replicate numbers employed in surveyed GEO studies. Fig S2: Design of Decode-seq. Fig S3: Downsampling of sequencing depth. Fig S4: Performance evaluation of Decode-seq at 3-fold change level using human/mouse RNA mixes. Fig S5: Performance evaluation of Decode-seq with 10 ng and 1 ng RNA at 5-fold change level. Fig S6: Sequencing quality scores and nucleotide distribution of BRB-seq and Decode-seq. Fig S7: Spearman’s correlations of human gene UMI counts between technical replicates of Decode-seq and BRB-seq. Fig S8: DE performance of BRB-seq and Decode-seq when using different edgeR filtering parameters. Fig S9: Genetic knockout of ENSORLG00000007290 by four-guide Cas9 RNP

Additional file 2 of Decode-seq: a practical approach to improve differential gene expression analysis

Additional file 2 Supplementary tables. Table S1: Top 300 genes with sexually dimorphic expression identified in this study. Table S2: Primers and gRNAs used in this study. Table S3: Sequencing stats of all libraries sequenced in this study