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Neurons in visual area V4 modulate their responses depending on the figure-ground (FG) organization in natural images containing a variety of shapes and textures. To clarify whether the responses depend on the extents of the figure and ground regions in and around the classical receptive fields (CRFs) of the neurons, we estimated the spatial extent of local figure and ground regions that evoked FG-dependent responses (RF-FGs) in natural images and their variants. Specifically, we applied the framework of spike triggered averaging (STA) to the combinations of neural responses and human-marked segmentation images (FG labels) that represent the extents of the figure and ground regions in the corresponding natural image stimuli. FG labels were weighted by the spike counts in response to the corresponding stimuli and averaged over. The bias due to the nonuniformity of FG labels was compensated by subtracting the ensemble average of FG labels from the weighted average. Approximately 50% of the neurons showed effective RF-FGs, and a large number exhibited structures that were similar to those observed in virtual neurons with ideal FG-dependent responses. The structures of the RF-FGs exhibited a subregion responsive to a preferred side (figure or ground) around the CRF center and a subregion responsive to a non-preferred side in the surroundings. The extents of the subregions responsive to figure were smaller than those responsive to ground in agreement with the Gestalt rule. We also estimated RF-FG by an adaptive filtering (AF) method, which does not require spherical symmetry (whiteness) in stimuli. RF-FGs estimated by AF and STA exhibited similar structures, supporting the veridicality of the proposed STA. To estimate the contribution of nonlinear processing in addition to linear processing, we estimated nonlinear RF-FGs based on the framework of spike triggered covariance (STC). The analyses of the models based on STA and STC did not show inconsiderable contribution of nonlinearity, suggesting spatial variance of FG regions. The results lead to an understanding of the neural responses that underlie the segregation of figures and the construction of surfaces in intermediate-level visual areas.

Neurons in visual area V4 modulate their responses depending on the figure-ground (FG) organization in natural images containing a variety of shapes and textures. To clarify whether the responses depend on the extents of the figure and ground regions in and around the classical receptive fields (CRFs) of the neurons, we estimated the spatial extent of local figure and ground regions that evoked FG-dependent responses (RF-FGs) in natural images and their variants. Specifically, we applied the framework of spike triggered averaging (STA) to the combinations of neural responses and human-marked segmentation images (FG labels) that represent the extents of the figure and ground regions in the corresponding natural image stimuli. FG labels were weighted by the spike counts in response to the corresponding stimuli and averaged over. The bias due to the nonuniformity of FG labels was compensated by subtracting the ensemble average of FG labels from the weighted average. Approximately 50% of the neurons showed effective RF-FGs, and a large number exhibited structures that were similar to those observed in virtual neurons with ideal FG-dependent responses. The structures of the RF-FGs exhibited a subregion responsive to a preferred side (figure or ground) around the CRF center and a subregion responsive to a non-preferred side in the surroundings. The extents of the subregions responsive to figure were smaller than those responsive to ground in agreement with the Gestalt rule. We also estimated RF-FG by an adaptive filtering (AF) method, which does not require spherical symmetry (whiteness) in stimuli. RF-FGs estimated by AF and STA exhibited similar structures, supporting the veridicality of the proposed STA. To estimate the contribution of nonlinear processing in addition to linear processing, we estimated nonlinear RF-FGs based on the framework of spike triggered covariance (STC). The analyses of the models based on STA and STC did not show inconsiderable contribution of nonlinearity, suggesting spatial variance of FG regions. The results lead to an understanding of the neural responses that underlie the segregation of figures and the construction of surfaces in intermediate-level visual areas.

Segmentation of a natural scene into objects and background is a fundamental but challenging task for recognizing objects. Investigating intermediate-level visual cortical areas with a focus on local information is a crucial step towards understanding the formation of the cortical representations of figure and ground. We examined the activity of a population of macaque V4 neurons during the presentation of natural image patches and their respective variations. The natural image patches were optimized to exclude the influence of global context but included various characteristics of local stimulus. Around one fourth of the patch-responsive V4 neurons exhibited significant modulation of firing activity that was dependent on the positional relation between the figural region of the stimulus and the classical receptive field of the neuron. However, the individual neurons showed low consistency in figure-ground modulation across a variety of image patches (55-62%), indicating that individual neurons were capable of correctly signaling figure and ground only for a limited number of stimuli. We examined whether integration of the activity of multiple neurons enabled higher consistency across a variety of natural patches by training a support vector machine to classify figure and ground of the stimuli from the population firing activity. The integration of the activity of a few tens of neurons yielded discrimination accuracy much greater than that of single neurons (up to 85%), suggesting a crucial role of population coding for figure-ground discrimination in natural images.

Antibodies against influenza virus neuraminidase (NA) protein prevent releasing of the virus from host cells and spreading of infection foci and are considered the 'second line of defence' against influenza. Haemagglutinin inhibition antibody-low responders (HI-LRs) are present among influenza split vaccine recipients. The NA inhibition (NAI) antibody response in vaccinees is worth exploring, especially those in the HI-LRs population. We collected pre- and post-vaccination sera from 61 recipients of an inactivated, monovalent, split vaccine against A/H1N1pdm09 and acute and convalescent sera from 49 unvaccinated patients naturally infected with the A/H1N1pdm09 virus during the 2009 influenza pandemic. All samples were subjected to haemagglutinin inhibition (HI), NAI and neutralisation assays. Most paired sera from naturally infected patients exhibited marked elevation in the NAI activity, and seroconversion rates (SCR) among HI-LRs and HI-responders (HI-Rs) were 60% and 87%, respectively; however, those from vaccinees displayed low increase in the NAI activity, and the SCR among HI-LRs and HI-Rs were 0% and 12%, respectively. In both HI-LRs and HI-Rs, vaccination with the inactivated, monovalent, split vaccine failed to elicit the NAI activity efficiently in the sera of the naive population, compared with the natural infection. Hence, the improvement of influenza vaccines is warranted to elicit not only HI but also NAI antibodies.

Human metapneumovirus (HMPV) has been a notable etiological agent of acute respiratory infection in humans, but it was not discovered until 2001, because HMPV replicates only in a limited number of cell lines and the cytopathic effect (CPE) is often mild. To promote the study of HMPV, several groups have generated green fluorescent protein (GFP)-expressing recombinant HMPV strains (HMPVGFP). However, the growing evidence has complicated the understanding of cell line specificity of HMPV, because it seems to vary notably among HMPV strains. In addition, unique A2b clade HMPV strains with a 180-nucleotide duplication in the G gene (HMPV A2b180nt-dup strains) have recently been detected. In this study, we re-evaluated and compared the cell line specificity of clinical isolates of HMPV strains, including the novel HMPV A2b180nt-dup strains, and six recombinant HMPVGFP strains, including the newly generated recombinant HMPV A2b180nt-dup strain, MG0256-EGFP. Our data demonstrate that VeroE6 and LLC-MK2 cells generally showed the highest infectivity with any clinical isolates and recombinant HMPVGFP strains. Other human-derived cell lines (BEAS-2B, A549, HEK293, MNT-1, and HeLa cells) showed certain levels of infectivity with HMPV, but these were significantly lower than those of VeroE6 and LLC-MK2 cells. Also, the infectivity in these suboptimal cell lines varied greatly among HMPV strains. The variations were not directly related to HMPV genotypes, cell lines used for isolation and propagation, specific genome mutations, or nucleotide duplications in the G gene. Thus, these variations in suboptimal cell lines are likely intrinsic to particular HMPV strains.

The adoptive transfer of effector T cells combined with lymphodepletion has demonstrated promising antitumor effects in mice and humans, although the availability of tumor-specific T cells is limited. We and others have also demonstrated that the transfer of polyclonal naïve T cells induces tumor-specific effector T cells and enhances antitumor immunity after lymphodepletion. Because tumors have been demonstrated to induce immunosuppressive networks and regulate the function of T cells, obtaining a sufficient number of fully functional naïve T cells that are able to differentiate into tumor-specific effector T cells remains difficult. To establish culture methods to obtain a large number of polyclonal T cells that are capable of differentiating into tumor-specific effector T cells, naïve T cells were activated with anti-CD3 mAbs in vitro. These cells were stimulated with IL-2 and IL-7 for the CD8 subset or with IL-7 and IL-23 for the CD4 subset. Transfer of these hyperexpanded T cells after lymphodepletion showed significant antitumor efficacy, and tumor-specific effector T cells were primed from these expanded T cells in tumor-bearing hosts. Moreover, these ex vivo-expanded T cells maintained T cell receptor diversity and showed long-term persistence of memory against specific tumors. Further analyses revealed that combination therapy consisting of vaccination with dendritic cells that were co-cultured with irradiated whole tumor cells and the transfer of ex vivo-expanded T cells significantly enhanced antitumor immunity. These results indicate that the transfer of ex vivo-expanded polyclonal T cells can be combined with other immunotherapies and augment antitumor effects.

LSD1, a lysine-specific histone demethylase, is overexpressed in several types of cancers and linked to poor outcomes. In breast cancer, the significance of LSD1 overexpression is not clear. We have performed an in silico analysis to assess the relationship of LSD1 expression to clinical outcome. We demonstrate that LSD1 overexpression is a poor prognostic factor in breast cancer, especially in basal-like breast cancer, a subtype of breast cancer with aggressive clinical features. This link is also observed in samples of triple negative breast cancer. Interestingly, we note that overexpression of LSD1 correlates with down-regulation of BRCA1 in triple negative breast cancer. This phenomenon is also observed in in vitro models of basal-like breast cancer, and is associated with an increased sensitivity to PARP inhibitors. We propose therefore that high expression levels of the demethylase LSD1 is a potential prognostic factor of poor outcome in basal-like breast cancer, and that PARP inhibition may be a therapeutic strategy of interest in this poor prognostic subtype with overexpression of LSD1.

Type I interferons (IFNs) are secreted by many cell types upon stimulation via pattern recognition receptors and bind to IFN-α/β receptor (IFNAR), which is composed of IFNAR1 and IFNAR2. Although type I IFNs are well known as anti-viral cytokines, limited information is available on their role during fungal infection. In the present study, we addressed this issue by examining the effect of IFNAR1 defects on the host defense response to Cryptococcus neoformans. In IFNAR1KO mice, the number of live colonies was lower and the host immune response mediated not only by Th1 but also by Th2 and Th17-related cytokines was more accelerated in the infected lungs than in WT mice. In addition, mucin production by bronchoepithelial cells and expression of MUC5AC, a major core protein of mucin in the lungs, were significantly higher in IFNAR1KO mice than in WT mice. This increase in mucin and MUC5AC production was significantly inhibited by treatment with neutralizing anti-IL-4 mAb. In contrast, administration of recombinant IFN-αA/D significantly suppressed the production of IL-4, but not of IFN-γ and IL-17A, in the lungs of WT mice after cryptococcal infection. These results indicate that defects of IFNAR1 led to improved clearance of infection with C. neoformans and enhanced synthesis of IFN-γ and the IL-4-dependent production of mucin. They also suggest that type I IFNs may be involved in the negative regulation of early host defense to this infection.

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception.