CD8 T-Cell Recognition of Multiple Epitopes within Specific Gag Regions Is Associated with Maintenance of a Low Steady-State Viremia in Human Immunodeficiency Virus Type 1-Seropositive Patients

The importance of HLA class I-restricted CD8 T-cell responses in the control of human immunodeficiency virus (HIV) infection is generally accepted. While several studies have shown an association of certain HLA class I alleles with slower disease progression, it is not fully established whether this effect is mediated by HIV-specific CD8 T-cell responses restricted by these alleles. In order to study the influence of the HLA class I alleles on the HIV-specific CD8 T-cell response and on viral control, we have assessed HIV-specific epitope recognition, plasma viral load, and expression of HLA class I alleles in a cohort of HIV-seropositive bar workers. Possession of the HLA class I alleles B5801, B8101, and B0702 was associated with a low median viral load and simultaneously with a broader median recognition of Gag epitopes compared to all other HLA alleles (twofold increase) (P = 0.0035). We further found an inverse linear relationship between the number of Gag epitopes recognized and the plasma viral load (R = −0.36; P = 0.0016). Particularly, recognition of multiple epitopes within two regions of Gag (amino acids [aa] 1 to 75 and aa 248 to 500) was associated with the maintenance of a low steady-state viremia, even years after acute infection

A Multifunctional, Low Cost and Sustainable Neonatal Database System

Continuous improvement in the clinical performance of neonatal intensive care units (NICU) depends on the use of locally relevant, reliable data. However, neonatal databases with these characteristics are typically unavailable in NICUs using paper-based records, while in those using electronic records, the inaccuracy of data and the inability to customize commercial data systems limit their usability for quality improvement or research purposes. We describe the characteristics and uses of a simple, neonatologist-centered data system that has been successfully maintained for 30 years, with minimal resources and serving multiple purposes, including quality improvement, administrative, research support and educational functions. Structurally, our system comprises customized paper and electronic components, while key functional aspects include the attending-based recording of diagnoses, integration into clinical workflows, multilevel data accuracy and validation checks, and periodic reporting on both data quality and NICU performance results. We provide examples of data validation methods and trends observed over three decades, and discuss essential elements for the successful implementation of this system. This database is reliable and easily maintained; it can be developed from simple paper-based forms or used to supplement the functionality and end-user customizability of existing electronic medical records. This system should be readily adaptable to NICUs in either high- or limited-resource environments