Topical CpG Oligodeoxynucleotide Adjuvant Enhances the Adaptive Immune Response against Influenza A Infections

Current influenza vaccines generate humoral immunity, targeting highly variable epitopes and thus fail to achieve long-term protection. T cells recognize and respond to several highly conserved epitopes across influenza serotypes. A strategy of raising strong cytotoxic T cell memory responses to epitopes conserved across serotypes would provide cross serotype protection, eliminating the need for annual vaccination. We explored the adjuvant potential of epicutaneous (ec) and subcutaneous (sc) delivery of CpG oligodeoxynucleotide in conjunction with subcutaneous protein immunization to improve protection against influenza A virus infections using a mouse model. We found enhanced long-term protection with ecCpG compared to scCpG as demonstrated by reduced viral titers in the lungs. This correlated with increased antigen-specific CD8 T cells in the airways and the lungs. The memory T cell response after immunization with ecCpG adjuvant was comparable to memory response by priming with influenza A virus infection in the lungs. In addition, ecCpG was more efficient than scCpG in inducing the generation of IFN-γ producing CD4 T cells. The adjuvant effect of ecCpG was accompanied with its ability to modulate tissue-homing molecules on T cells that may direct them to the site of infection. Together, this work provides evidence for using ecCpG to induce strong antibody and memory T cell responses to confer protection against influenza A virus infection

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Colonic Mucosal Necrosis Following Administration of Calcium Polystryrene Sulfonate (Kalimate) in a Uremic Patient

Colonic necrosis is known as a rare complication following the administration of Kayexalate (sodium polystryrene sulfonate) in sorbitol. We report a rare case of colonic mucosal necrosis following Kalimate (calcium polystryrene sulfonate), an analogue of Kayexalate without sorbitol in a 34-yr-old man. He had a history of hypertension and uremia. During the management of intracranial hemorrhage, hyperkalemia developed. Kalimate was administered orally and as an enema suspended in 20% dextrose water to treat hyperkalemia. Two days after administration of Kalimate enema, he had profuse hematochezia, and a sigmoidoscopy showed diffuse colonic mucosal necrosis in the rectum and sigmoid colon. Microscopic examination of random colonic biopsies by two consecutive sigmoidoscopies revealed angulated crystals with a characteristic crystalline mosaic pattern on the ulcerated mucosa, which were consistent with Kayexalate crystals. Hematochezia subsided with conservative treatment after a discontinuance of Kalimate administration

Constant light enhances synchrony among circadian clock cells and promotes behavioral rhythms in VPAC(2)-signaling deficient mice

Individual neurons in the suprachiasmatic nuclei (SCN) contain an intracellular molecular clock and use intercellular signaling to synchronize their timekeeping activities so that the SCN can coordinate brain physiology and behavior. The neuropeptide vasoactive intestinal polypeptide (VIP) and its VPAC2 receptor form a key component of intercellular signaling systems in the SCN and critically control cellular coupling. Targeted mutations in either the intracellular clock or intercellular neuropeptide signaling mechanisms, such as VIP-VPAC2 signaling, can lead to desynchronization of SCN neuronal clocks and loss of behavioral rhythms. An important goal in chronobiology is to develop interventions to correct deficiencies in circadian timekeeping. Here we show that extended exposure to constant light promotes synchrony among SCN clock cells and the expression of ~24 h rhythms in behavior in mice in which intercellular signaling is disrupted through loss of VIP-VPAC2 signaling. This study highlights the importance of SCN synchrony for the expression of rhythms in behavior and reveals how non-invasive manipulations in the external environment can be used to overcome neurochemical communication deficits in this important brain system

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

Glioblastoma induces whole-brain spectral change in resting state fMRI: Associations with clinical comorbidities and overall survival

Glioblastoma, a highly aggressive form of brain tumor, is a brain-wide disease. We evaluated the impact of tumor burden on whole brain resting-state functional magnetic resonance imaging (rs-fMRI) activity. Specifically, we analyzed rs-fMRI signals in the temporal frequency domain in terms of the power-law exponent and fractional amplitude of low-frequency fluctuations (fALFF). We contrasted 189 patients with newly-diagnosed glioblastoma versus 189 age-matched healthy reference participants from an external dataset. The patient and reference datasets were matched for age and head motion. The principal finding was markedly flatter spectra and reduced grey matter fALFF in the patients as compared to the reference dataset. We posit that the whole-brain spectral change is attributable to global dysregulation of excitatory and inhibitory balance and metabolic demand in the tumor-bearing brain. Additionally, we observed that clinical comorbidities, in particular, seizures, and MGMT promoter methylation, were associated with flatter spectra. Notably, the degree of change in spectra was predictive of overall survival. Our findings suggest that frequency domain analysis of rs-fMRI activity provides prognostic information in glioblastoma patients and offers a means of noninvasively studying the effects of glioblastoma on the whole brain

Functional connectivity within glioblastoma impacts overall survival

BACKGROUND: Glioblastoma (GBM; World Health Organization grade IV) assumes a variable appearance on MRI owing to heterogeneous proliferation and infiltration of its cells. As a result, the neurovascular units responsible for functional connectivity (FC) may exist within gross tumor boundaries, albeit with altered magnitude. Therefore, we hypothesize that the strength of FC within GBMs is predictive of overall survival. METHODS: We used predefined FC regions of interest (ROIs) in de novo GBM patients to characterize the presence of within-tumor FC observable via resting-state functional MRI and its relationship to survival outcomes. RESULTS: Fifty-seven GBM patients (mean age, 57.8 ± 13.9 y) were analyzed. Functionally connected voxels, not identifiable on conventional structural images, can be routinely found within the tumor mass and was not significantly correlated to tumor size. In patients with known survival times (n = 31), higher intranetwork FC strength within GBM tumors was associated with better overall survival even after accounting for clinical and demographic covariates. CONCLUSIONS: These findings suggest the possibility that functionally intact regions may persist within GBMs and that the extent to which FC is maintained may carry prognostic value and inform treatment planning

Resting state network mapping in individuals using deep learning

INTRODUCTION: Resting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases to individual network mapping for pre-surgical planning of tumor resections. Reproducibility of these results has been shown to require a substantial amount of high-quality data, which is not often available in clinical or research settings. METHODS: In this work, we report voxelwise mapping of a standard set of RSNs using a novel deep 3D convolutional neural network (3DCNN). The 3DCNN was trained on publicly available functional MRI data acquired in RESULTS: Our results indicate this method can be applied in individual subjects and is highly resistant to both noisy data and fewer RS-fMRI time points than are typically acquired. Further, our results show core regions within each network that exhibit high average probability and low STD. DISCUSSION: The 3DCNN algorithm can generate individual RSN localization maps, which are necessary for clinical applications. The similarity between 3DCNN mapping results and task-based fMRI responses supports the association of specific functional tasks with RSNs

Optimal approaches to analyzing functional MRI data in glioma patients

BACKGROUND: Resting-state fMRI is increasingly used to study the effects of gliomas on the functional organization of the brain. A variety of preprocessing techniques and functional connectivity analyses are represented in the literature. However, there so far has been no systematic comparison of how alternative methods impact observed results. NEW METHOD: We first surveyed current literature and identified alternative analytical approaches commonly used in the field. Following, we systematically compared alternative approaches to atlas registration, parcellation scheme, and choice of graph-theoretical measure as regards differentiating glioma patients (N = 59) from age-matched reference subjects (N = 163). RESULTS: Our results suggest that non-linear, as opposed to affine registration, improves structural match to an atlas, as well as measures of functional connectivity. Functionally- as opposed to anatomically-derived parcellation schemes maximized the contrast between glioma patients and reference subjects. We also demonstrate that graph-theoretic measures strongly depend on parcellation granularity, parcellation scheme, and graph density. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: Our current work primarily focuses on technical optimization of rs-fMRI analysis in glioma patients and, therefore, is fundamentally different from the bulk of papers discussing glioma-induced functional network changes. We report that the evaluation of glioma-induced alterations in the functional connectome strongly depends on analytical approaches including atlas registration, choice of parcellation scheme, and graph-theoretical measures