PD-L1-PD-1 interactions limit effector regulatory T cell populations at homeostasis and during infection.

Phenotypic and transcriptional profiling of regulatory T (Treg) cells at homeostasis reveals that T cell receptor activation promotes Treg cells with an effector phenotype (eTreg) characterized by the production of interleukin-10 and expression of the inhibitory receptor PD-1. At homeostasis, blockade of the PD-1 pathway results in enhanced eTreg cell activity, whereas during infection with Toxoplasma gondii, early interferon-γ upregulates myeloid cell expression of PD-L1 associated with reduced Treg cell populations. In infected mice, blockade of PD-L1, complete deletion of PD-1 or lineage-specific deletion of PD-1 in Treg cells prevents loss of eTreg cells. These interventions resulted in a reduced ratio of pathogen-specific effector T cells: eTreg cells and increased levels of interleukin-10 that mitigated the development of immunopathology, but which could compromise parasite control. Thus, eTreg cell expression of PD-1 acts as a sensor to rapidly tune the pool of eTreg cells at homeostasis and during inflammatory processes.

Structural basis of flagellar motility regulation by the MogR repressor and the GmaR antirepressor in Listeria monocytogenes.

The pathogenic Listeria monocytogenes bacterium produces the flagellum as a locomotive organelle at or below 30°C outside the host, but it halts flagellar expression at 37°C inside the human host to evade the flagellum-induced immune response. Listeria monocytogenes GmaR is a thermosensor protein that coordinates flagellar expression by binding the master transcriptional repressor of flagellar genes (MogR) in a temperature-responsive manner. To understand the regulatory mechanism whereby GmaR exerts the antirepression activity on flagellar expression, we performed structural and mutational analyses of the GmaR-MogR system. At or below 30°C, GmaR exists as a functional monomer and forms a circularly enclosed multidomain structure via an interdomain interaction. GmaR in this conformation recognizes MogR using the C-terminal antirepressor domain in a unique dual binding mode and mediates the antirepressor function through direct competition and spatial restraint mechanisms. Surprisingly, at 37°C, GmaR rapidly forms autologous aggregates that are deficient in MogR neutralization capabilities.

Systematic transition from boundary extension to contraction along an object-to-scene continuum.

After viewing a picture of an environment, our memory of it typically extends beyond what was presented, a phenomenon referred to as boundary extension. But, sometimes memory errors show the opposite pattern-boundary contraction-and the relationship between these phenomena is controversial. We constructed virtual three-dimensional environments and created a series of views at different distances, from object close-ups to wide-angle indoor views, and tested for memory errors along this object-to-scene continuum. Boundary extension was evident for close-scale views and transitioned parametrically to boundary contraction for far-scale views. However, this transition point was not tied to a specific position in the environment (e.g., the point of reachability). Instead, it tracked with judgments of the best-looking view of the environment, in both rich-object and low-object environments. We offer a dynamic-tension account, where competition between object-based and scene-based affordances determines whether a view will extend or contract in memory. This study demonstrates that boundary extension and boundary contraction are not two separate phenomena but rather two parts of a continuum, suggesting a common underlying mechanism. The transition point between the two is not fixed but depends on the observer's judgment of the best-looking view of the environment. These findings provide new insights into how we perceive and remember a view of environment.

Evaluation of a smartphone-operated point-of-care device using loop-mediated isothermal amplification technology for rapid and remote detection of SARS-CoV-2.

During the SARS-CoV-2 pandemic, rapid and sensitive detection of SARS-CoV-2 has been of high importance for outbreak control. Reverse transcriptase polymerase chain reaction (RT-PCR) is the current gold standard, however, the procedures require an equipped laboratory setting and personnel, which have been regularly overburdened during the pandemic. This often resulted in long waiting times for patients. In contrast, reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) is a simple, cost-efficient, and fast procedure, allowing for rapid and remote detection of SARS-CoV-2. In the current study, we performed a clinical evaluation of a new point-of-care test system based on LAMP-technology for SARS-CoV-2 detection, providing a result within 25 min (1copy™ COVID-19 MDx Kit Professional system). We tested 112 paired nasopharyngeal swabs, collected in the COVID-19 Ghent University Hospital test center, using the 1copy™ COVID-19 MDx Kit Professional system, and RT-PCR as the reference method. The test system was found to have a clinical sensitivity of 93.24% (69/74) (95% confidence interval [CI]: 84.93%-97.77%) and specificity of 97.37% (37/38) (95% CI: 86.19%-99.93%). Due to its easy smartphone operation and ready-to-use reagents, it ought to be easily applied in for instance general practices, pharmacies, nursing homes, schools, and companies. This would facilitate an efficient SARS-CoV-2 outbreak control and quarantine policy, as diagnosis can occur sooner in a near-patient setting.

Developing new intermuscular coordination patterns through an electromyographic signal-guided training in the upper extremity.

BACKGROUND: Muscle synergies, computationally identified intermuscular coordination patterns, have been utilized to characterize neuromuscular control and learning in humans. However, it is unclear whether it is possible to alter the existing muscle synergies or develop new ones in an intended way through a relatively short-term motor exercise in adulthood. This study aimed to test the feasibility of expanding the repertoire of intermuscular coordination patterns through an isometric, electromyographic (EMG) signal-guided exercise in the upper extremity (UE) of neurologically intact individuals. METHODS: 10 participants were trained for six weeks to induce independent control of activating a pair of elbow flexor muscles that tended to be naturally co-activated in force generation. An untrained isometric force generation task was performed to assess the effect of the training on the intermuscular coordination of the trained UE. We applied a non-negative matrix factorization on the EMG signals recorded from 12 major UE muscles during the assessment to identify the muscle synergies. In addition, the performance of training tasks and the characteristics of individual muscles' activity in both time and frequency domains were quantified as the training outcomes. RESULTS: Typically, in two weeks of the training, participants could use newly developed muscle synergies when requested to perform new, untrained motor tasks by activating their UE muscles in the trained way. Meanwhile, their habitually expressed muscle synergies, the synergistic muscle activation groups that were used before the training, were conserved throughout the entire training period. The number of muscle synergies activated for the task performance remained the same. As the new muscle synergies were developed, the neuromotor control of the trained muscles reflected in the metrics, such as the ratio between the targeted muscles, number of matched targets, and task completion time, was improved. CONCLUSION: These findings suggest that our protocol can increase the repertoire of readily available muscle synergies and improve motor control by developing the activation of new muscle coordination patterns in healthy adults within a relatively short period. Furthermore, the study shows the potential of the isometric EMG-guided protocol as a neurorehabilitation tool for aiming motor deficits induced by abnormal intermuscular coordination after neurological disorders. TRIAL REGISTRATION: This study was registered at the Clinical Research Information Service (CRiS) of the Korea National Institute of Health (KCT0005803) on 1/22/2021.

Radotinib Decreases Prion Propagation and Prolongs Survival Times in Models of Prion Disease.

The conversion of cellular prion protein (PrPC) into pathogenic prion isoforms (PrPSc) and the mutation of PRNP are definite causes of prion diseases. Unfortunately, without exception, prion diseases are untreatable and fatal neurodegenerative disorders; therefore, one area of research focuses on identifying medicines that can delay the progression of these diseases. According to the concept of drug repositioning, we investigated the efficacy of the c-Abl tyrosine kinase inhibitor radotinib, which is a drug that is approved for the treatment of chronic myeloid leukemia, in the treatment of disease progression in prion models, including prion-infected cell models, Tga20 and hamster cerebellar slice culture models, and 263K scrapie-infected hamster models. Radotinib inhibited PrPSc deposition in neuronal ZW13-2 cells that were infected with the 22L or 139A scrapie strains and in cerebellar slice cultures that were infected with the 22L or 263K scrapie strains. Interestingly, hamsters that were intraperitoneally injected with the 263K scrapie strain and intragastrically treated with radotinib (100 mg/kg) exhibited prolonged survival times (159 ± 28.6 days) compared to nontreated hamsters (135 ± 9.9 days) as well as reduced PrPSc deposition and ameliorated pathology. However, intraperitoneal injection of radotinib exerted a smaller effect on the survival rate of the hamsters. Additionally, we found that different concentrations of radotinib (60, 100, and 200 mg/kg) had similar effects on survival time, but this effect was not observed after treatment with a low dose (30 mg/kg) of radotinib. Interestingly, when radotinib was administered 4 or 8 weeks after prion inoculation, the treated hamsters survived longer than the vehicle-treated hamsters. Additionally, a pharmacokinetic assay revealed that radotinib effectively crossed the blood-brain barrier. Based on our findings, we suggest that radotinib is a new candidate anti-prion drug that could possibly be used to treat prion diseases and promote the remission of symptoms.

Genetic and immunological characterization of commercial infectious bronchitis virus vaccines used in Korea.

The aim of the study was to investigate the genetic and immunogenic features of commercial vaccines against infectious bronchitis virus (IBV), which is a major contagious pathogen of poultry. Although numerous vaccines have been developed based on the genetic characteristics of field strains, the continual emergence of variants decreases vaccine efficacy and cross-protection. To address this issue, we compared the S1 gene sequences of three IBV vaccines commercially available in Korea with those of various field isolates. Phylogenetic analysis showed that the vaccine strains clustered into two different lineages. Comparison of commercial vaccines with their parental viruses showed that most of the genetic variability occurred around hypervariable regions (HVRs). Conversely, antigenic stimulation with commercial vaccines and regional IBV variants was not sufficient to alter major immune cell phenotypes. Our study suggests that vaccines should be selected carefully based on their genetic background because genetic variability can affect the antigenicity of vaccines and host immune responses.

Effects of anodal stimulation and motor practice on limb-kinetic apraxia in Parkinson's disease.

Limb-kinetic apraxia, the loss of the ability to make precise, independent but coordinated finger and hand movements affects quality of life in patients with Parkinson's disease. We aimed to examine the effects of anodal transcranial direct current stimulation of the left posterior parietal cortex and upper extremity motor practice on limb-kinetic apraxia in Parkinson's disease. This study was conducted in a randomized, double-blind, sham-controlled fashion. Patients confirmed to have Parkinson's disease were recruited. Twenty-eight participants completed the study and were randomized to two groups: anodal or sham stimulation. For participants assigned to active stimulation, anodal stimulation of the left posterior parietal cortex was performed using 2 mA current for 20 min. Patients received anodal or sham stimulation, followed by motor practice in both groups. The primary outcome measure was time-performing sequential buttoning and unbuttoning, and several secondary outcome measures were obtained. A statistically significant interaction between stimulation type and timepoint on time taken to perform buttoning and unbuttoning was found. Patients who received anodal stimulation were found to have a significant decrease in sequential buttoning and unbuttoning time immediately following stimulation and at 24 h in the medication-ON state, compared to the medication-OFF state (31% and 29% decrease, respectively). Anodal stimulation of the left posterior parietal cortex prior to motor practice appears to be effective for limb-kinetic apraxia in Parkinson's disease. Future long-term, multi-session studies looking at the long-term effects of anodal stimulation and motor practice on limb-kinetic apraxia in Parkinson's disease may be worthwhile.

Loss of IL-27Rα Results in Enhanced Tubulointerstitial Fibrosis Associated with Elevated Th17 Responses.

Clinical and experimental studies have established that immune cells such as alternatively activated (M2) macrophages and Th17 cells play a role in the progression of chronic kidney disease, but the endogenous pathways that limit these processes are not well understood. The cytokine IL-27 has been shown to limit immune-mediated pathology in other systems by effects on these cell types, but this has not been thoroughly investigated in the kidney. Unilateral ureteral obstruction was performed on wild-type and IL-27Rα-/- mice. After 2 wk, kidneys were extracted, and the degree of injury was measured by hydroxyproline assay and quantification of neutrophil gelatinase-associated lipocalin mRNA. Immune cell infiltrate was evaluated by immunohistochemistry and flow cytometry. An anti-IL-17A mAb was subsequently administered to IL-27Rα-/- mice every 2 d from day of surgery with evaluation as described after 2 wk. After unilateral ureteral obstruction, IL-27 deficiency resulted in increased tissue injury and collagen deposition associated with higher levels of chemokine mRNA and increased numbers of M2 macrophages. Loss of the IL-27Rα led to increased infiltration of activated CD4+ T cells that coproduced IL-17A and TNF-α, and blockade of IL-17A partially ameliorated kidney injury. Patients with chronic kidney disease had elevated serum levels of IL-27 and IL-17A, whereas expression of transcripts for the IL-27RA and the IL-17RA in the tubular epithelial cells of patients with renal fibrosis correlated with disease severity. These data suggest that endogenous IL-27 acts at several points in the inflammatory cascade to limit the magnitude of immune-mediated damage to the kidney.

Smartphone Sensor-Based Human Motion Characterization with Neural Stochastic Differential Equations and Transformer Model.

With many conveniences afforded by advances in smartphone technology, developing advanced data analysis methods for health-related information from smartphone users has become a fast-growing research topic in the healthcare field. Along these lines, this paper addresses smartphone sensor-based characterization of human motions with neural stochastic differential equations (NSDEs) and a Transformer model. NSDEs and modeling via Transformer networks are two of the most prominent deep learning-based modeling approaches, with significant performance yields in many applications. For the problem of modeling dynamical features, stochastic differential equations and deep neural networks are frequently used paradigms in science and engineering, respectively. Combining these two paradigms in one unified framework has drawn significant interest in the deep learning community, and NSDEs are among the leading technologies for combining these efforts. The use of attention has also become a widely adopted strategy in many deep learning applications, and a Transformer is a deep learning model that uses the mechanism of self-attention. This concept of a self-attention based Transformer was originally introduced for tasks of natural language processing (NLP), and due to its excellent performance and versatility, the scope of its applications is rapidly expanding. By utilizing the techniques of neural stochastic differential equations and a Transformer model along with data obtained from smartphone sensors, we present a deep learning method capable of efficiently characterizing human motions. For characterizing human motions, we encode the high-dimensional sequential data from smartphone sensors into latent variables in a low-dimensional latent space. The concept of the latent variable is particularly useful because it can not only carry condensed information concerning motion data, but also learn their low-dimensional representations. More precisely, we use neural stochastic differential equations for modeling transitions of human motion in a latent space, and rely on a Generative Pre-trained Transformer 2 (GPT2)-based Transformer model for approximating the intractable posterior of conditional latent variables. Our experiments show that the proposed method can yield promising results for the problem of characterizing human motion patterns and some related tasks including user identification.

Wireless Kitchen Fire Prevention System Using Electrochemical Carbon Dioxide Gas Sensor for Smart Home.

This paper presents a wireless kitchen fire prevention system that can detect and notify the fire risk caused by gas stoves. The proposed system consists of two modules. The sensor module detects the concentration of carbon dioxide (CO2) near the gas stove and transmits the monitoring results wirelessly. The alarm module, which is placed in other places, receives the data and reminds the user of the stove status. The sensor module uses a cost-efficient electrochemical CO2 sensor and embeds an in situ algorithm that determines the status of the gas stove based on the measured CO2 concentration. For the wireless communication between the modules, on-off keying (OOK) is employed, thereby achieving a longer battery lifetime of the alarm module, low cost, and simple implementation. To increase the lifetime further, a wake-up function based on passive infrared (PIR) sensing is employed in the alarm module. Our system can successfully detect the on state of the stove within 40 s and the off state within 200 s. Thanks to the low-power implementation, in situ algorithm, and wake-up function, the alarm module's expected battery lifetime is extended to about two months.

Coding of Navigational Distance and Functional Constraint of Boundaries in the Human Scene-Selective Cortex.

For visually guided navigation, the use of environmental cues is essential. Particularly, detecting local boundaries that impose limits to locomotion and estimating their location is crucial. In a series of three fMRI experiments, we investigated whether there is a neural coding of navigational distance in the human visual cortex (both female and male). We used virtual reality software to systematically manipulate the distance from a viewer perspective to different types of a boundary. Using a multivoxel pattern classification employing a linear support vector machine, we found that the occipital place area (OPA) is sensitive to the navigational distance restricted by the transparent glass wall. Further, the OPA was sensitive to a non-crossable boundary only, suggesting an importance of the functional constraint of a boundary. Together, we propose the OPA as a perceptual source of external environmental features relevant for navigation.SIGNIFICANCE STATEMENT One of major goals in cognitive neuroscience has been to understand the nature of visual scene representation in human ventral visual cortex. An aspect of scene perception that has been overlooked despite its ecological importance is the analysis of space for navigation. One of critical computation necessary for navigation is coding of distance to environmental boundaries that impose limit on navigator's movements. This paper reports the first empirical evidence for coding of navigational distance in the human visual cortex and its striking sensitivity to functional constraint of environmental boundaries. Such finding links the paper to previous neurological and behavioral works that emphasized the distance to boundaries as a crucial geometric property for reorientation behavior of children and other animal species.

Transcriptome analysis of primary chicken cells infected with infectious bronchitis virus strain K047-12 isolated in Korea.

Infectious bronchitis virus (IBV), an avian coronavirus, is highly contagious. Chickens with IBV infection develop acute pathogenesis in multiple organs, including the respiratory and urogenital tracts. Frequent recombination in the spike (S) glycoprotein gene has made vaccine strategies ineffective. To understand IBV pathogenesis, we analyzed the genetic distance between Korean IBV isolates and other coronaviruses, including SARS-CoV-2. To obtain comprehensive information about early immune responses such as innate cytokine production and associated immune regulation during IBV infection, we infected primary chicken embryonic kidney cells and performed transcriptome analysis. We observed that the functional pathways of innate immunity are regulated and confirmed expression of genes that coordinate early immune responses. Understanding the immune profile of the host cell may assist in vaccine development.

Alterations in intermuscular coordination underlying isokinetic exercise after a stroke and their implications on neurorehabilitation.

BACKGROUND: Abnormal intermuscular coordination limits the motor capability of stroke-affected upper limbs. By evaluating the intermuscular coordination in the affected limb under various biomechanical task constraints, the impact of a stroke on motor control can be analyzed and intermuscular coordination-based rehabilitation strategies can be developed. In this study, we investigated upper limb intermuscular coordination after a stroke during isokinetic movements. METHODS: Sixteen chronic stroke survivors and eight neurologically intact individuals were recruited. End-point forces and electromyographic activities of the shoulder and elbow muscles were measured while the participants performed isokinetic upper limb movements in a three-dimensional space. Intermuscular coordination of the stroke survivors and the control participants was quantified in the form of muscle synergies. Then, we compared the number, composition, and activation coefficients of muscle synergies and the end-point force between the groups. The correlation between the alteration of muscle synergies and the level of motor impairment was investigated. RESULTS: Four and five muscle synergies in the stroke and control groups were observed, respectively. The composition of muscle synergies was comparable between the groups, except that the three heads of the deltoid muscle were co-activated and formed one synergy in the stroke group, whereas those muscles formed two synergies in the control group. When the number of muscle synergies between the groups matched, the comparable composition of muscle synergies was observed in both groups. Alternatively, the modulation of synergy activation coefficients was altered after a stroke. The severity of motor impairments was negatively correlated with the similarity of the post-stroke synergies with respect to the mean control synergies. CONCLUSIONS: Stroke-affected upper limbs seemed to modularize the activation of the shoulder and elbow muscles in a fairly similar way to that of neurologically intact individuals during isokinetic movements. Compared with free (i.e., unconstrained) movement, exercise under biomechanical constraints including the isokinetic constraint might promote the activation of muscle synergies independently in stroke survivors. We postulated the effect of biomechanical constraints on the intermuscular coordination and suggested a possible intermuscular coordination-based rehabilitation protocol that provides the biomechanical constraint appropriate to a trainee throughout the progress of rehabilitation.

Predicting Human Motion Signals Using Modern Deep Learning Techniques and Smartphone Sensors.

The global adoption of smartphone technology affords many conveniences, and not surprisingly, healthcare applications using wearable sensors like smartphones have received much attention. Among the various potential applications and research related to healthcare, recent studies have been conducted on recognizing human activities and characterizing human motions, often with wearable sensors, and with sensor signals that generally operate in the form of time series. In most studies, these sensor signals are used after pre-processing, e.g., by converting them into an image format rather than directly using the sensor signals themselves. Several methods have been used for converting time series data to image formats, such as spectrograms, raw plots, and recurrence plots. In this paper, we deal with the health care task of predicting human motion signals obtained from sensors attached to persons. We convert the motion signals into image formats with the recurrence plot method, and use it as an input into a deep learning model. For predicting subsequent motion signals, we utilize a recently introduced deep learning model combining neural networks and the Fourier transform, the Fourier neural operator. The model can be viewed as a Fourier-transform-based extension of a convolution neural network, and in these experiments, we compare the results of the model to the convolution neural network (CNN) model. The results of the proposed method in this paper show better performance than the results of the CNN model and, furthermore, we confirm that it can be utilized for detecting potential accidental falls more quickly via predicted motion signals.

A 60% Edible Ethanolic Extract of Ulmus davidiana Inhibits Vascular Endothelial Growth Factor-Induced Angiogenesis.

As abnormal angiogenesis is associated with exacerbation of various diseases, precise control over angiogenesis is imperative. Vascular endothelial growth factor (VEGF), the most well-known angiogenic factor, binds to VEGF receptor (VEGFR), activates various signaling pathways, and mediates angiogenesis. Therefore, blocking the VEGF-induced angiogenic response-related signaling pathways may alleviate various disease symptoms through inhibition of angiogenesis. Ulmus davidiana is a safe natural product that has been traditionally consumed, but its effects on endothelial cells (ECs) and the underlying mechanism of action are unclear. In the present study, we focused on the effect of a 60% edible ethanolic extract of U. davidiana (U60E) on angiogenesis. U60E inhibited the VEGF-mediated proliferation, tube formation, and migration ability of ECs. Mechanistically, U60E inhibited endothelial nitric oxide synthase activation and nitric oxide production by blocking the protein kinase B signaling pathway activated by VEGF and consequently inhibiting proliferation, tube formation, and migration of ECs. These results suggest that U60E could be a potential and safe therapeutic agent capable of suppressing proangiogenic diseases by inhibiting VEGF-induced angiogenesis.

Co-Evolution of Predator-Prey Ecosystems by Reinforcement Learning Agents.

The problem of finding adequate population models in ecology is important for understanding essential aspects of their dynamic nature. Since analyzing and accurately predicting the intelligent adaptation of multiple species is difficult due to their complex interactions, the study of population dynamics still remains a challenging task in computational biology. In this paper, we use a modern deep reinforcement learning (RL) approach to explore a new avenue for understanding predator-prey ecosystems. Recently, reinforcement learning methods have achieved impressive results in areas, such as games and robotics. RL agents generally focus on building strategies for taking actions in an environment in order to maximize their expected returns. Here we frame the co-evolution of predators and preys in an ecosystem as allowing agents to learn and evolve toward better ones in a manner appropriate for multi-agent reinforcement learning. Recent significant advancements in reinforcement learning allow for new perspectives on these types of ecological issues. Our simulation results show that throughout the scenarios with RL agents, predators can achieve a reasonable level of sustainability, along with their preys.

The role of macrophages in protective and pathological responses to Toxoplasma gondii.

The ability of Toxoplasma gondii to cause clinical disease in immune-competent and immune-deficient hosts coupled with its ease of use in vitro and availability of murine models has led to its use as a model organism to study how the immune system controls an intracellular infection. This article reviews the studies that established the role of the cytokine IFN-γ in the activation of macrophages to control T gondii and the events that lead to the mobilization and expansion of macrophage populations and their ability to limit parasite replication. Macrophages also have pro-inflammatory functions that promote protective NK and T-cell activities as well as regulatory properties that facilitate the resolution of inflammation. Nevertheless, while macrophages are important in determining the outcome of infection, T gondii has evolved mechanisms to subvert macrophage activation and can utilize their migratory activities to promote dissemination and these two properties underlie the ability of this parasite to persist and cause disease.

Recombinant adenovirus carrying a core neutralizing epitope of porcine epidemic diarrhea virus and heat-labile enterotoxin B of Escherichia coli as a mucosal vaccine.

Porcine epidemic diarrhea virus (PEDV) targets the intestinal mucosa in pigs. To protect against PEDV invasion, a mucosal vaccine is utilized effectively. In this study, we generated a recombinant adenovirus vaccine encoding the heat-labile enterotoxin B (LTB) and the core neutralizing epitope (COE) of PEDV (rAd-LTB-COE). The fusion protein LTB-COE was successfully expressed by the recombinant adenovirus in HEK293 cells, and the immunogenicity of the vaccine candidate was assessed in BALB/c mice and piglets. Three intramuscular or oral vaccinations with rAd-LTB-COE at two-week intervals induced robust humoral and mucosal immune responses. Moreover, a cell-mediated immune response was promoted in immunized mice, and the neutralizing antibody inhibited both the vaccine strain and the emerging PEDV isolate. Immunization experiments in piglets revealed that rAd-LTB-COE was immunogenic and induced good immune responses in piglets. Further studies are required to evaluate the efficacy of rAd-LTB-COE against a highly virulent PEDV challenge.

Cytokine- and TCR-Mediated Regulation of T Cell Expression of Ly6C and Sca-1.

Ly6C and Sca-1 (Ly6A/E) are Ly6 family GPI-anchored surface molecules that are differentially expressed by multiple immune populations. Ly6C expression has been used to distinguish short-lived effector CD4+ T cells from memory precursor effector cells, whereas Sca-1 has been used in the identification of CD8+ memory stem cells. This study examines the expression patterns of these molecules and establishes that, in vitro, IL-27, type I IFN, and IFN-γ are potent inducers of Ly6C and Sca-1 in naive mouse CD4+ and CD8+ T cells, whereas TGF-ß limits their expression. The induction of Ly6C and Sca-1 by IL-27 and IFN-γ is dependent on STAT1, but not STAT3 or T-bet. In mouse splenocytes, at homeostasis, Ly6C and Sca-1 expression was not restricted to effector cells, but was also found at various levels on naive and memory populations. However, in response to infection with Toxoplasma gondii, pathogen-specific T cells expressed high levels of these molecules and in this context, endogenous IL-27 and IFN-γ were required for the expression of Ly6C but not Sca-1. Together, these findings highlight the TCR-dependent and cytokine-mediated signals that modulate T cell expression of Ly6C and Sca-1 in vitro and in vivo during infection.