Identification and isolation of antigen-specific cytotoxic T lymphocytes with an automated microraft sorting system

The simultaneous measurement of T cell function with recovery of individual T cells would greatly facilitate characterizing antigen-specific responses both in vivo and in model systems

Effects of elevated [CO2 ] on maize defence against mycotoxigenic Fusarium verticillioides.

Maize is by quantity the most important C4 cereal crop; however, future climate changes are expected to increase maize susceptibility to mycotoxigenic fungal pathogens and reduce productivity. While rising atmospheric [CO2 ] is a driving force behind the warmer temperatures and drought, which aggravate fungal disease and mycotoxin accumulation, our understanding of how elevated [CO2 ] will effect maize defences against such pathogens is limited. Here we report that elevated [CO2 ] increases maize susceptibility to Fusarium verticillioides proliferation, while mycotoxin levels are unaltered. Fumonisin production is not proportional to the increase in F. verticillioides biomass, and the amount of fumonisin produced per unit pathogen is reduced at elevated [CO2 ]. Following F. verticillioides stalk inoculation, the accumulation of sugars, free fatty acids, lipoxygenase (LOX) transcripts, phytohormones and downstream phytoalexins is dampened in maize grown at elevated [CO2 ]. The attenuation of maize 13-LOXs and jasmonic acid production correlates with reduced terpenoid phytoalexins and increased susceptibility. Furthermore, the attenuated induction of 9-LOXs, which have been suggested to stimulate mycotoxin biosynthesis, is consistent with reduced fumonisin per unit fungal biomass at elevated [CO2 ]. Our findings suggest that elevated [CO2 ] will compromise maize LOX-dependent signalling, which will influence the interactions between maize and mycotoxigenic fungi

Mobilization of pro-inflammatory lipids in obese Plscr3-deficient mice

Metabolic profiling of mice deficient in phospholipid scramblase 3 reveals a possible molecular link between obesity and inflammation

Activated lymphocyte recruitment into the tumor microenvironment following preoperative sipuleucel-T for localized prostate cancer.

BackgroundSipuleucel-T is a US Food and Drug Administration-approved immunotherapy for asymptomatic or minimally symptomatic metastatic castration-resistant prostate cancer (mCRPC). Its mechanism of action is not fully understood. This prospective trial evaluated the direct immune effects of systemically administered sipuleucel-T on prostatic cancer tissue in the preoperative setting.MethodsPatients with untreated localized prostate cancer were treated on an open-label Phase II study of sipuleucel-T prior to planned radical prostatectomy (RP). Immune infiltrates in RP specimens (posttreatment) and in paired pretreatment biopsies were evaluated by immunohistochemistry (IHC). Correlations between circulating immune response and IHC were assessed using Spearman rank order.ResultsOf the 42 enrolled patients, 37 were evaluable. Adverse events were primarily transient, mild-to-moderate and infusion related. Patients developed T cell proliferation and interferon-γ responses detectable in the blood following treatment. Furthermore, a greater-than-three-fold increase in infiltrating CD3(+), CD4(+) FOXP3(-), and CD8(+) T cells was observed in the RP tissues compared with the pretreatment biopsy (binomial proportions: all P < .001). This level of T cell infiltration was observed at the tumor interface, and was not seen in a control group consisting of 12 concurrent patients who did not receive any neoadjuvant treatment prior to RP. The majority of infiltrating T cells were PD-1(+) and Ki-67(+), consistent with activated T cells. Importantly, the magnitude of the circulating immune response did not directly correlate with T cell infiltration within the prostate based upon Spearman's rank order correlation.ConclusionsThis study is the first to demonstrate a local immune effect from the administration of sipuleucel-T. Neoadjuvant sipuleucel-T elicits both a systemic antigen-specific T cell response and the recruitment of activated effector T cells into the prostate tumor microenvironment

A computational model of binding thermodynamics: The design of cyclin-dependent kinase 2 inhibitors

The cyclin-dependent protein kinases are important targets in drug discovery because of their role in cell cycle regulation. In this computational study, we have applied a continuum solvent model to study the interactions between cyclin-dependent kinase 2 (CDK2) and analogues of the clinically tested anticancer agent flavopiridol. The continuum solvent model uses Coulomb's law to account for direct electrostatic interactions, solves the Poisson equation to obtain the electrostatic contributions to solvation energy, and calculates scaled solvent-accessible surface area to account for hydrophobic interactions. The computed free energy of binding gauges the strength of protein-ligand interactions. Our model was first validated through a study on the binding of a number of flavopiridol derivatives to CDK2, and its ability to identify potent inhibitors was observed. The model was then used to aid in the design of novel CDK2 inhibitors with the aid of a computational sensitivity analysis. Some of these hypothetical structures could be significantly more potent than the lead compound flavopiridol. We applied two approaches to gain insights into designing selective inhibitors. One relied on the comparative analysis of the binding pocket for several hundred protein kinases to identify the parts of a lead compound whose modifications might lead to selective compounds. The other was based on building and using homology models for energy calculations. The homology models appear to be able to classify ligand potency into groups but cannot yet give reliable quantitative results

Charge optimization of the interface between protein kinases and their ligands

Abstract: Examining the potential for electrostatic complementarity between a ligand and a receptor is a useful technique for rational drug design, and can demonstrate how a system prioritizes interactions when allowed to optimize its charge distribution. In this computational study, we implemented the previously developed, continuum solvent-based charge optimization theory with a simple, quadratic programming algorithm and the UHBD Poisson-Boltzmann solver. This method allows one to compute the best set of point charges for a ligand or ligand region based on the ligand and receptor shape, and the receptor partial charges, by optimizing the binding free energy obtained from a continuumsolvent model. We applied charge optimization to a fragment of the heat-stable protein kinase inhibitor (PKI) of protein kinase A (PKA), to three flavopiridol inhibitors of CDK2, and to cyclin A which interacts with CDK2 to regulate the cell cycle. We found that a combination of global (involving every charge) and local (involving only charges in a local region) optimization can give useful hints for designing better inhibitors. Although some parts of an inhibitor may already contribute significantly to binding, we found that they could still be the most important targets for modifications to obtain stronger binders. In studying the binding of flavopiridol inhibitors to CDK2, comparable binding affinity could be obtained regardless of whether the net charges of the inhibitors were constrained to Ϫ2, Ϫ1, 0, 1, or 2 during the optimization. This provides flexibility in inhibitor design when a certain net charge of the inhibitor is desired in addition to strong binding affinity. For the study of the PKA-PKI and CDK2-cyclin A interfaces, we identified residues whose charge distributions are already close to optimal and those whose charge distributions could be refined to further improve binding

Computational steering of a multi-objective evolutionary algorithm for engineering design

The execution process of an evolutionary algorithm typically involves some trial and error. This is due to the difficulty in setting the initial parameters of the algorithm—especially when little is known about the problem domain. This problem is magnified when applied to many-objective optimisation, as care is needed to ensure that the final population of candidate solutions is representative of the trade-off surface. We propose a computational steering system that allows the engineer to interact with the optimisation routine during execution. This interaction can be as simple as monitoring the values of some parameters during the execution process, or could involve altering those parameters to influence the quality of the solutions produced by the optimisation process. The implementation of this steering system should provide the ability to tailor the client to the hardware available, for example providing a lightweight steering and visualisation client for use on a PDA

MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma

Glioblastomas (GBMs) diffusely infiltrate the brain, making complete removal by surgical resection impossible. The mixture of neoplastic and nonneoplastic cells that remain after surgery form the biological context for adjuvant therapeutic intervention and recurrence. We performed RNA-sequencing (RNA-seq) and histological analysis on radiographically guided biopsies taken from different regions of GBM and showed that the tissue contained within the contrast-enhancing (CE) core of tumors have different cellular and molecular compositions compared with tissue from the nonenhancing (NE) margins of tumors. Comparisons with the The Cancer Genome Atlas dataset showed that the samples from CE regions resembled the proneural, classical, or mesenchymal subtypes of GBM, whereas the samples from the NE regions predominantly resembled the neural subtype. Computational deconvolution of the RNA-seq data revealed that contributions from nonneoplastic brain cells significantly influence the expression pattern in the NE samples. Gene ontology analysis showed that the cell type-specific expression patterns were functionally distinct and highly enriched in genes associated with the corresponding cell phenotypes. Comparing the RNA-seq data from the GBM samples to that of nonneoplastic brain revealed that the differentially expressed genes are distributed across multiple cell types. Notably, the patterns of cell type-specific alterations varied between the different GBM subtypes: the NE regions of proneural tumors were enriched in oligodendrocyte progenitor genes, whereas the NE regions of mesenchymal GBM were enriched in astrocytic and microglial genes. These subtypespecific patterns provide new insights into molecular and cellular composition of the infiltrative margins of GBM

Validation of the HADRIAN system with a train station design case study

The HADRIAN (Human Anthropometric Data Requirements Investigation & Analysis) human modelling system is under development at Loughborough University as part of the EPSRC funded AUNT-SUE (Accessibility and User Needs in Transport for Sustainable Urban Environments) project. The HADRIAN system aims to foster a ‘design for all’ ethos by allowing ergonomists and designers to see the effects of different kinds of disability on the physical capabilities of elderly and disabled people. This system is based upon the long established SAMMIE system (System for Aiding Man Machine Interaction Evaluation), and uses data collected from 102 elderly and disabled individuals (Joint range of motion and anthropometry, ability to use steps and stairs, lifts escalators etc.). The HADRIAN system allows three dimensional CAD data of new products to be imported, with subsequent analysis using all of 102 sample members. The 102 sample includes a stature range of 1st% UK female to 99th%ile UK male, and also includes a range of disabilities that have been assessed using scales from Martin et al (1994). In this way the needs of people with specific conditions, such as arthritis, can be demonstrated and where possible, design accommodation can be improved. This paper describes the validation activity that is underway with the HADRIAN system. The validation reflects the transport focus of the AUNT SUE project by using HADRIAN to analyse the user interaction points that people encounter when using the Docklands Light Railway in London. This includes the use of ticket machines, the use of the train station infrastructure such as lifts and steps and stairs, and the use of ATMs to obtain cash. The validation is being performed by comparing the predicted results from HADRIAN and the abilities of users when performing real life tasks such as retrieving a ticket from a machine, or pressing a floor button when in a lift