CD8+ T-cell responses in vaccination: Reconsidering targets and function in the context of chronic antigen stimulation

Cytotoxic CD8 T cells play important roles in eliminating infected and transformed cells. Owing to their potential for therapeutic applications, significant efforts are dedicated toward developing CD8 T cell-based vaccines. Thus far, CD8 T-cell vaccination strategies have had limited success therapeutically in contrast to those targeting antibody-based immunity. However, if the current challenges and gaps in the understanding of T-cell biology are overcome, the full potential of rational CD8 T-cell vaccine design might be realized. Here, we review recent progress in this direction, focusing on target selection and maintenance of function in the settings of chronic infections and cancers

Cubesat mission with technological demonstrator payload for high data rate downlink and health monitoring

The HyperCube payload will be composed by two different technological experiment, an high data-rate C band antenna, and a demonstrator for a remote structural health monitoring system. The first one has been thought with the aim to give Cubesats the capability to download an high quantity of data; it could be useful either if the data requiring the high data-rate downlink is on-board generated or simply retransmitted. The applications for which this payload could be used are several; an example for the first category of application is to download the data generated by another payload; the high data-rate capability could be necessary due to the narrow visibility window with the ground station, affected also by the absence of an active AOCS subsystem, which makes difficult the alignment of the on board antenna with the ground one. But the C band antenna could also be used to act as a “space–repeater”, downloading up–linked information. The second payload is related to the need to take under strictly control the health of the structures (not only the ones strictly belonging to primary structures, but also that of any subsystem component). In order to do that, smart materials are integrated into the structural component that need to be monitored; in particular, piezoelectric patches are used as sensors. As the structure is stressed, and the integrated piezoelectric sensors are subjected to mechanical deformation, they produce an electric signal; acquiring and properly studying the produced signal it is possible to monitor the mechanical condition of the structures. The health monitoring system is completed by a MicroController Unit which acquires, samples and stores the signal produced, and a transmitting system, which could be the C band antenna, or the TT&C antenna which each satellite needs

Power-law distributions in empirical data

Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of power laws is complicated by the large fluctuations that occur in the tail of the distribution -- the part of the distribution representing large but rare events -- and by the difficulty of identifying the range over which power-law behavior holds. Commonly used methods for analyzing power-law data, such as least-squares fitting, can produce substantially inaccurate estimates of parameters for power-law distributions, and even in cases where such methods return accurate answers they are still unsatisfactory because they give no indication of whether the data obey a power law at all. Here we present a principled statistical framework for discerning and quantifying power-law behavior in empirical data. Our approach combines maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov statistic and likelihood ratios. We evaluate the effectiveness of the approach with tests on synthetic data and give critical comparisons to previous approaches. We also apply the proposed methods to twenty-four real-world data sets from a range of different disciplines, each of which has been conjectured to follow a power-law distribution. In some cases we find these conjectures to be consistent with the data while in others the power law is ruled out.Comment: 43 pages, 11 figures, 7 tables, 4 appendices; code available at http://www.santafe.edu/~aaronc/powerlaws

Differentiation and Protective Capacity of Virus-Specific CD8

Noroviruses can establish chronic infections with active viral shedding in healthy humans but whether persistence is associated with adaptive immune dysfunction is unknown. We used genetically engineered strains of mouse norovirus (MNV) to investigate CD8+ T cell differentiation during chronic infection. We found that chronic infection drove MNV-specific tissue-resident memory (Trm) CD8+ T cells to a differentiation state resembling inflationary effector responses against latent cytomegalovirus with only limited evidence of exhaustion. These MNV-specific Trm cells remained highly functional yet appeared ignorant of ongoing viral replication. Pre-existing MNV-specific Trm cells provided partial protection against chronic infection but largely ceased to detect virus within 72 hours of challenge, demonstrating rapid sequestration of viral replication away from T cells. Our studies revealed a strategy of immune evasion by MNV via the induction of a CD8+ T cell program normally reserved for latent pathogens and persistence in an immune-privileged enteric niche. Chronic infections often cause T cell dysfunction, but how noroviruses (NV) evade immunity is unknown. Tomov et al. show that gut-resident T cells against NV remain functional but ignorant of chronic viral replication, suggesting that NV persists in an immune-privileged enteric niche. © 2017 Elsevier Inc

Characterization of T-bet and eomes in peripheral human immune cells.

The T-box transcription factors T-bet and Eomesodermin (Eomes) have been well defined as key drivers of immune cell development and cytolytic function. While the majority of studies have defined the roles of these factors in the context of murine T-cells, recent results have revealed that T-bet, and possibly Eomes, are expressed in other immune cell subsets. To date, the expression patterns of these factors in subsets of human peripheral blood mononuclear cells beyond T-cells remain relatively uncharacterized. In this study, we used multiparametric flow cytometry to characterize T-bet and Eomes expression in major human blood cell subsets, including total CD4(+) and CD8(+) T-cells, γδ T-cells, invariant NKT cells, natural killer cells, B-cells, and dendritic cells. Our studies identified novel cell subsets that express T-bet and Eomes and raise implications for their possible functions in the context of other human immune cell subsets besides their well-known roles in T-cells. The corrigendum regards data and text for the final figure of the manuscript, Figure 7: Subsequent analysis of T-bet levels in human lymphocytes comparing different permeabilization procedures (eBioscience FoxP3 transcription factor kit, BD Pharmingen Cytofix/Cytoperm) has revealed variable findings in the level of T-bet expression detected within certain lymphocyte populations. While this does not change our conclusions for the majority of the populations assessed in this study, B cells in particular show differences under these conditions. Specifically, permeabilization via the eBioscience FoxP3 transcription factor staining buffer set indicates that subpopulations of memory B cells express significantly higher levels of T-bet (MFI) compared to plasmablasts, and that plasmablasts express T-bet only at low levels. Subsequent RNA transcript analysis confirms that plasmablasts express T-bet RNA at a level comparable to naïve B cells. Together, in combination with fluorescence-minus-one and isotype control studies, these new findings suggest that subsets memory B cells, not plasmablasts, express the highest levels of T-bet in the B cell compartment and plasmablasts express T-bet at a lower frequency than is reported in Figure 7. Figure 7 Legend should read: (C) Histograms depicting T-bet expression levels in B-cells and NK cells from a representative donor. Histograms represent the following subsets: naïve B-cells (thick black line), memory B-cells (shaded gray), plasmablasts (thin black line), CD56bright NK cells (gray line), and CD56dim NK cells (shaded black). B-cell results section should be titled T-bet is predominantly expressed in mature memory B-cells and should read: While Eomes was undetectable in B-cells (data not shown), we found T-bet in ~10% of B-cells (Figure 7B). This T-bet expression was largely relegated to memory B-cells, with significantly lower amounts observed in transitional/immature B-cells, naïve B-cells, and plasmablasts (Figure 7B). Greater than 15% of memory B-cells expressed T-bet, a significantly higher frequency than that of all other B-cell populations, suggesting that T-bet may play a particularly important role in memory B-cell function. The discussion related to T-bet expression in plasmablasts should be reconsidered as follows: We found that T-bet is not significantly expressed in transitional/immature B-cells, naïve B-cells, and plasmablasts, but is highly expressed in subsets of memory-B cells. Reduced frequencies of T-bet expression in plasmablasts indicate a specific role for T-bet at the memory B-cell stage of development, which may no longer be necessary after further differentiation to the plasmablast stage. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest

A yeast synthetic network for in-vivo assessment of reverse engineering and modelling.

Systems biology approaches are extensively used to model and reverse engineer gene regulatory networks from experimental data. Conversely, synthetic biology allows ‘‘de novo’’ construction of a regulatory network to seed new functions in the cell. At present, the usefulness and predictive ability of modeling and reverse engineering cannot be assessed and compared rigorously. We built in the yeast Saccharomyces cerevisiae a synthetic network, IRMA, for in vivo ‘‘benchmarking’’ of reverse-engineering and modeling approaches. The network is composed of five genes regulating each other through a variety of regulatory interactions; it is negligibly affected by endogenous genes, and it is responsive to small molecules. We measured time series and steady-state expression data after multiple perturbations. These data were used to assess state-of-the-art modeling and reverse-engi- neering techniques. A semiquantitative model was able to capture and predict the behavior of the network. Reverse engineering based on differential equations and Bayesian networks correctly inferred regulatory interactions from the experimental data

Targeting the mRNA-binding protein HuR impairs malignant characteristics of pancreatic ductal adenocarcinoma cells.

Post-transcriptional regulation is a powerful mediator of gene expression, and can rapidly alter the expression of numerous transcripts involved in tumorigenesis. We have previously shown that the mRNA-binding protein HuR (ELAVL1) is elevated in human pancreatic ductal adenocarcinoma (PDA) specimens compared to normal pancreatic tissues, and its cytoplasmic localization is associated with increased tumor stage. To gain a better insight into HuR\u27s role in PDA biology and to assess it as a candidate therapeutic target, we altered HuR expression in PDA cell lines and characterized the resulting phenotype in preclinical models. HuR silencing by short hairpin and small interfering RNAs significantly decreased cell proliferation and anchorage-independent growth, as well as impaired migration and invasion. In comparison, HuR overexpression increased migration and invasion, but had no significant effects on cell proliferation and anchorage-independent growth. Importantly, two distinct targeted approaches to HuR silencing showed marked impairment in tumor growth in mouse xenografts. NanoString nCounter® analyses demonstrated that HuR regulates core biological processes, highlighting that HuR inhibition likely thwarts PDA viability through post-transcriptional regulation of diverse signaling pathways (e.g. cell cycle, apoptosis, DNA repair). Taken together, our study suggests that targeted inhibition of HuR may be a novel, promising approach to the treatment of PDA

111In-Octreoscan SPECT/CT hybrid imaging and 68Ga-DOTANOC PET/CT in neuroendocrine adenoma of the middle ear (NAME)

Neuroendocrine adenoma of the middle ear (NAME) represents a rare tumour consisting of an adenoma with mixed neuroendocrine differentiation. A 40-year-old woman was referred to our attention to further investigate the occurrence of a pathological tissue located in the mastoid process of the left temporal bone depicted by head CT and MRI scans. Histopathological examination revealed an epithelial neoplasm with neuroendocrine differentiation features, consistent with the diagnosis of NAME. In order to obtain an accurate differential diagnosis and confirmation of this rare disease, 111In-Octreoscan single photon emission computed tomography (SPECT)/CT and 68Ga-DOTANOC positron emission tomography (PET)/CT were performed, both showing overexpression of somatostatin receptors and thus corroborating the histopathological findings

Early 18F-FDG PET/CT in COVID-19

We report the case of who has been hospitalized complaining about fever in the last 4 days. Laboratory data revealed lymphocytopenia and leucopenia with an elevation of C-reactive protein and positive real-time reverse transcription-polymerase chain reaction (RT-PCR). Six days before this hospitalization, when the patient was asymptomatic, 18F-FDG PET/CT images were performed for the therapeutic control of liver metastases of colorectal cancer. Lung abnormality findings at 18F-FDG PET/CT images, unrelated to cancer metastases, but suspicious for viral infection, may suggest the presence of COVID-19 disease in its early phase before symptoms onset. Since PET/CT is more sensitive than CT scan in detecting host’s reaction, the added value of this technique could be monitoring disease progression and could be used as a biomarker of lung disease activity and therefore as an important tool for a better understanding of the factors that contribute to the progression of lung disease