2 research outputs found
Factors affecting changes in the intraocular pressure after phacoemulsification surgery
AIM: To assess the changes in anterior chamber parameters and examine the factors associated with changes in the intraocular pressure(IOP)in individuals who have undergone phacoemulsification surgery.METHODS: It was a longitudinal analysis of secondary clinical data collected from 105 non-glaucomatous eyes(of 82 patients)undergoing a cataract surgery. We studied the association between anterior chamber parameters, grade of cataract, demographics, and changes in the IOP over a period of 3wk. We also evaluated the association between the pressure-depth(PD)ratio and changes in the IOP during this time.RESULTS: The mean age [standard deviation(SD)] of the 82 patients was 60.1(7.8)years. The mean SD IOP was 15.06(3.36)mmHg pre-operatively; it increased to 15.75(4.21)mmHg on day one(P=0.20). In the multifactorial models, the mean IOP was -1.715 \〖95% confidence intervals(CI): -2.795, -0.636\〗 mmHg on day 21(±5)compared with the pre-operative values. The anterior chamber depth(ACD), axial length, age, sex, and grade of cataract were not significantly associated with changes in the IOP. Each unit increase in the PD ratio was associated with an increase in the mean IOP by 1.289 mmHg(95% CI: 0.906, 1.671). After adjusting for pre-operative PD ratio, none of the other variables(ACD, axial length, temporal angle)were significantly associated with changes in mean IOP.CONCLUSION: The PD ratio was the single most important factor associated with the changes in post-operative IOP over 3wk post surgery
A multi-omic analysis of human naïve CD4+ T cells
Background: Cellular function and diversity are orchestrated by complex interactions of fundamental biomolecules including DNA, RNA and proteins. Technological advances in genomics, epigenomics, transcriptomics and proteomics have enabled massively parallel and unbiased measurements. Such high-throughput technologies have been extensively used to carry out broad, unbiased studies, particularly in the context of human diseases. Nevertheless, a unified analysis of the genome, epigenome, transcriptome and proteome of a single human cell type to obtain a coherent view of the complex interplay between various biomolecules has not yet been undertaken. Here, we report the first multi-omic analysis of human primary naïve CD4+ T cells isolated from a single individual. Results: Integrating multi-omics datasets allowed us to investigate genome-wide methylation and its effect on mRNA/protein expression patterns, extent of RNA editing under normal physiological conditions and allele specific expression in naïve CD4+ T cells. In addition, we carried out a multi-omic comparative analysis of naïve with primary resting memory CD4+ T cells to identify molecular changes underlying T cell differentiation. This analysis provided mechanistic insights into how several molecules involved in T cell receptor signaling are regulated at the DNA, RNA and protein levels. Phosphoproteomics revealed downstream signaling events that regulate these two cellular states. Availability of multi-omics data from an identical genetic background also allowed us to employ novel proteogenomics approaches to identify individual-specific variants and putative novel protein coding regions in the human genome. Conclusions: We utilized multiple high-throughput technologies to derive a comprehensive profile of two primary human cell types, naïve CD4+ T cells and memory CD4+ T cells, from a single donor. Through vertical as well as horizontal integration of whole genome sequencing, methylation arrays, RNA-Seq, miRNA-Seq, proteomics, and phosphoproteomics, we derived an integrated and comparative map of these two closely related immune cells and identified potential molecular effectors of immune cell differentiation following antigen encounter