Establishment of a protocol for rapidly expanding Epstein-Barr-virus-specific cytotoxic T cells with enhanced cytotoxicity.

Background: Lytic Epstein-Barr virus (EBV) infection plays a major role in the pathogenesis of nasopharyngeal carcinoma (NPC). For patients with recurrent or metastatic NPC and resistant to conventional therapies, adoptive cell therapy using EBV-specific cytotoxic T cells (EBV-CTLs) is a promising option. However, the long production period (around 3 to 4 weeks) and low EBV-CTL purity (approximately 40% of total CD8 T cells) in the cell product limits the application of EBV-CTLs in clinics.

Characterization of tumoricidal activities mediated by a novel immune cell regimen composing interferon-producing killer dendritic cells and tumor-specific cytotoxic T lymphocytes.

Background: Although immune cell therapy has long been used for treating solid cancer, its efficacy remains limited. Interferon (IFN)-producing killer dendritic cells (IKDCs) exhibit cytotoxicity and present antigens to relevant cells; thus, they can selectively induce tumor-associated antigen (TAA)-specific CD8 T cells and may be useful in cancer treatment. Various protocols have been used to amplify human IKDCs from peripheral sources, but the complexity of the process has prevented their widespread clinical application.

May I see what you see? Predicting visual features from neuronal activity.

Understanding brain response to audiovisual stimuli is a key challenge in understanding neuronal processes. In this paper, we describe our effort aimed at reconstructing video frames from observed functional MRI images. We also demonstrate that our model can predict visual objects.

Identifying and analyzing sepsis states: A retrospective study on patients with sepsis in ICUs.

Sepsis accounts for more than 50% of hospital deaths, and the associated cost ranks the highest among hospital admissions in the US. Improved understanding of disease states, progression, severity, and clinical markers has the potential to significantly improve patient outcomes and reduce cost. We develop a computational framework that identifies disease states in sepsis and models disease progression using clinical variables and samples in the MIMIC-III database.

AIKYATAN: mapping distal regulatory elements using convolutional learning on GPU.

Background: The data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specific functional annotation problem, within the bounds of the hardware constraints and the model's complexity. In our system AIKYATAN, we annotate distal epigenomic regulatory sites, e.

Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.

Background: Gene expression is mediated by specialized cis-regulatory modules (CRMs), the most prominent of which are called enhancers. Early experiments indicated that enhancers located far from the gene promoters are often responsible for mediating gene transcription. Knowing their properties, regulatory activity, and genomic targets is crucial to the functional understanding of cellular events, ranging from cellular homeostasis to differentiation.

Subset selection of high-depth next generation sequencing reads for de novo genome assembly using MapReduce framework.

Background: Recent progress in next-generation sequencing technology has afforded several improvements such as ultra-high throughput at low cost, very high read quality, and substantially increased sequencing depth. State-of-the-art high-throughput sequencers, such as the Illumina MiSeq system, can generate ~15 Gbp sequencing data per run, with >80% bases above Q30 and a sequencing depth of up to several 1000x for small genomes. Illumina HiSeq 2500 is capable of generating up to 1 Tbp per run, with >80% bases above Q30 and often >100x sequencing depth for large genomes.

The efficacy of a novel vaccine approach using tumor cells that ectopically express a codon-optimized murine GM-CSF in a murine tumor model.

Granulocyte macrophage-colony stimulating factor (GM-CSF) is a potent immunomodulatory cytokine that is known to facilitate vaccine efficacy by promoting the development and prolongation of both humoral and cellular immunity. Here, we investigated a novel vaccine approach using a human papillomavirus (HPV)-16 E6/E7-transformed cell line, TC-1, that ectopically expresses a codon-optimized 26-11-2015 murine GM-CSF (cGM-CSF). Ectopically expressing cGM-CSF in TC-1 (TC-1/cGM) cells significantly increased expression of a GM-CSF that was functionally identical to wt GM-CSF by 9-fold compared with ectopically expressed wild type GM-CSF in TC-1 cells (TC-1/wt).