B1 cells were first described

by Hayakawa et al. in mice as a small population of splenic B cells expressing a pan-T cell marker, CD5, and spontaneously secreting immunoglobulin (Ig)M [1]. They represent a unique subset of B cells ontogenetically and phenotypically and are functionally distinct from conventional B2 cells. B1 cells are generated in liver and bone marrow during the fetal and neonatal period and populate predominantly coelomic cavities and intestinal lamina propria [2-4]. When the peripheral pool is established further de-novo AZD8055 datasheet generation is maintained, mainly by self-renewal [5]. One of the characteristic features of B1 cells is the enrichment of their repertoire for poly- and self-reactive specificities. Hayakawa et al. suggested that B1 cells may be positively selected for their auto-antigenic specificity [6]. Although B1 cells present antigens efficiently and can prime T cells, their major role lies in the secretion of

natural immunoglobulins in the absence of exogenous antigenic stimulation [7]. These low-affinity polyreactive IgM/IgA antibodies are encoded typically by germline sequences with minimal somatic mutations and non-templated nucleotide insertions [8]. Natural immunoglobulins work not only as an instant defence against invading pathogens, Romidepsin chemical structure but also as a ‘silent’ non-inflammatory clearance mechanism for apoptotic bodies and other

altered self-antigens [9-11]. Most of our current knowledge about the B1 cell role in the immune system is based on experiments in mice. Although much effort has been made to find a human homologue of murine B1 cells, its existence remains controversial. Recently, a ‘novel’ human B1 cell phenotype, CD20+CD27+CD43+CD70–, was proposed as this specific B cell subset showed three key features of B1 cells (spontaneous IgM secretion, tonic intracellular signalling and efficient T cell stimulation) [12]. Subsequently, further division of CD27+ B cells known as memory B cells into ‘true’ memory B cells (CD27+CD43–) and ‘B1’ cells (CD27+CD43+) Methamphetamine was suggested according to their CD43 expression [12]. At least two other innate-like B cell subsets have been described in humans, which resemble murine B1 cells both phenotypically and functionally. One of these, termed ‘unswitched’ IgM+IgD+ memory B cells, were demonstrated to be circulating counterparts of splenic marginal zone B cells [13]. The other population comprised CD21lowCD23– CD38lowCD86hi B cells with polyclonal unmutated IgM and IgD, similar to murine B1 cells. These were found to be expanded in peripheral tissues such as the bronchoalveolar space [14]. These cells were described initially in some patients with common variable immunodeficiency (CVID), especially in those with splenomegaly and granulomatous disease [15].

In this study, we discuss the different molecular approaches for typing C. glabrata isolates. Recent advances in the use of molecular biology-based techniques have enabled investigators to develop typing systems with greater sensitivities. Several molecular genotypic approaches have

been developed for fast and accurate identification of C. glabrata in vitro. These techniques have been widely used to study diverse aspects such as nosocomial transmission. Molecular typing of C. glabrata could also provide information on strain variation, such as microvariation and microevolution. LY2606368 “
“Clinical diagnosis of invasive fungal infections (IFIs) is sometimes difficult, and obtaining an accurate assessment of trends concerning the prevalence of IFIs is a challenge. The aim of this study was to determine trends in the prevalence of IFIs from an autopsy survey. The retrospective review of autopsy records stored in Toho University was performed on all documented cases with fungal infection from 1955 to 2006. A total of 411 cases of IFIs were detected among 10 297 autopsies. The prevalence of candidiasis decreased from 3.6% (1981–93) to 2.0% VX-765 cost (1994–2006), and that of aspergillosis increased throughout the 52-year period and reached 2.0% (1994–2006). The prevalence of IFIs in the patient group comprising haematological disorders was significantly higher (19.9%) than in other patient groups (2.9%), of which the odds ratio was 18.4 for mucormycosis

and 10.0 for aspergillosis. The lung was the most common organ involved irrespective of major fungal species, and most cases with candidiasis showed multiple-organ infection. Results confirmed the increasing prevalence of aspergillosis and high risk of IFIs in the patient group with haematological disorders. IFIs

were also detected in an immunocompromised state caused not only by primary disease but also by treatment with anti-tumour drugs and corticosteroids. “
“There are discrepancies in the literature regarding the prevalence of tinea pedis in psoriasis. The aim of this investigation was to conduct a cross-sectional study of the prevalence of tinea pedis in psoriasis compared Urease to atopic dermatitis patients and normal controls. We enrolled 232 psoriatic patients, 190 atopic dermatitis patients and 202 normal controls, between the years 2010 and 2013. The prevalence of tinea pedis was 13.8% in psoriasis patients, not significantly different from that in atopic dermatitis patients 8.4% (P = 0.092)), but significantly higher than in normal controls 7.4% (P = 0.043). Both gender and age affected the prevalence of tinea pedis in psoriasis and normal controls, while only age affected the prevalence of tinea pedis in atopic dermatitis. Regarding gender, there was higher prevalence of tinea pedis in men: 19.1% (P = 0.019) in psoriasis and 12.1% (P = 0.013) in normal controls. Age affected the prevalence of tinea pedis in normal controls (P < 0.001), psoriasis patients (P = 0.

After 120 hrs, the mortality rate in WSSV-injected F. indicus experimental groups (5 and 35 g/L) was significantly higher than for F. indicus exposed to 25 and

15 g/L salinities. During the experimental period (0–120 hrs), biochemical variables, namely total protein, carbohydrate, and lipid concentrations, were measured in hemolymph of both experimental and control groups. Acute salinity changes induced an increase in protein variations across the tested salinity ranges in shrimp. After 24 hrs, THC and PO activity decreased significantly whereas RB, alkaline phosphatase and acid phosphatase activities increased in shrimps kept at the lower salinities of 5, 15 and 35 g/L. Concomitant with the rapid emergence of shrimp culture industries, effective disease management strategies Dabrafenib clinical trial have become necessary. WSSV is a lethal

viral disease that affects cultured and captured PI3K Inhibitor Library screening commercially important shrimp species and many other crustaceans [1]. In farmed shrimp, this virus reportedly causes 100% cumulative mortality in 2–10 days [1-4]. WSSV is an enveloped, ellipsoid, large (∼300 kb), double stranded DNA virus. In the infected tiger shrimp Penaeus monodon, common signs of the disease include appearance of white spots on the carapace, reddish discoloration around soft tissues, anorexia, lethargy and swelling acetylcholine of branchiostegites [2]. Although WSSV has been formally recognized since 1992, the International Committee on the Taxonomy of Viruses has designated this virus as a new genus, Whispovirus, family Nimaviridae [5]. Disease is the end result of complex interactions between host, pathogen and environment. In this context, water salinity is considered one of the most important environmental factors for shrimp because it influences metabolism, oxygen consumption, feeding rate, growth, molting, survival and

tolerance to toxic metabolites [6]. Hemocytes counts, which correlate with prophenoloxidase (proPO), respiratory burst, SOD, and phagocytic activity have been used as indices of immune capability in penaeid shrimps [7]. Hemolymph metabolic variables such as proteins, glucose, cholesterol, triacylglycerol, have been found to vary in response to captivity stress, temperature alterations, depleted dissolved oxygen and high ambient ammonia [8]. Biochemical variables in hemolymph have also been identified as indicators of stress related to onset of shrimp disease. In the last 10 years, substantial progress has been made in quantifying WSSV in infected animals. Owing to the unavailability of immortal cell lines to determine viral load of viable virus, quantitative PCR has been the main method used for quantification. Dhar et al.

Goat anti-CRAMP Ab (M-13) (Santa Cruz Biotechnology, Santa Cruz, CA, USA) and rabbit anti-CRAMP Ab were used as capture and detection antibody, respectively. Titration was performed with CRAMP peptide and a standard curve was constructed. Briefly, M-13 was coated onto an ELISA plate (Nalgene Nunc, Rochester, NY, USA) at a concentration of 0.5 μg/mL in PBS

overnight at RT. After two washes with PBST, the plate was blocked with 100 μL of Blocking One (Nacalai Tesque, Kyoto, Japan) for 1 hr at RT. The samples at appropriate dilutions in triplicate were added to the plates along with the standard. The plates were incubated for 1 hr at RT, washed twice with PBST and then incubated for 1.5 hr with rabbit anti-CRAMP Ab (0.2 μg/mL) at RT. After two washes, an appropriate Selleckchem BMS-777607 dilution of HRP-conjugated AZD1208 goat anti-rabbit IgG F(ab’)2 (MP Biomedicals, Solon, OH, USA) was added, followed by incubation for 1 hr at RT. After two washes, the reagent 3,3,5,5-tetramethyl benzidine (Nacalai Tesque) was added as substrate/coloring agent. The absorbance was measured at 450 nm. The detection limit of the ELISA was 0.2 ng/mL. The supernatants of BALF obtained as described above were condensed by acetone precipitation and SDS-PAGE applied using Ready gels (4% T stacking gel and 10–20% T resolving gel) from Bio-Rad (Hercules, CA, USA). For Western blotting, proteins were electrotransferred from the gel to PVDF membrane

(Bio-Rad). Nonspecific binding was blocked by incubation of the membrane in Blocking One (Nacalai Tesque). Primary rabbit anti-CRAMP Ab was

used at a dilution 1:4000. Secondary HRP-conjugated goat anti-rabbit IgG F(ab’)2 (MP Biomedicals) was used at a dilution of 1:5000. Bands were visualized using an ECL Advance Western blotting detection kit (GE healthcare, Buckinghamshire, UK). Cathelin-related antimicrobial peptide antigens in neutrophils were detected by indirect immunofluorescence. In brief, BALF pellets prepared as described above were fixed on glass slides with methanol for 10 min at RT and washed with PBS for 10 min. The samples were incubated with 1 μg/mL of rabbit anti-CRAMP Ab and normal serum as control for 1 hr at RT. After washing with PBS for 10 min, Liothyronine Sodium they were incubated with a secondary Alexa Flour 488 goat anti-rabbit IgG Ab (Molecular Probes, Eugene, OR, USA) and Hoechst 33342 (Dojindo, Kumamoto, Japan) at 1 μg/mL each for 1 hr at RT. The cells were viewed on an inverted fluorescence microscope (Eclipse Ti; Nikon, Tokyo, Japan), and the images captured by using a CCD camera (Nikon digital sight DS-Qi1Mc). A mercury lamp was used for fluorescence excitation of Alexa Flour 488 (495 nm) and Hoechst 33342 (352 nm). BALB/c mice (5 weeks old) were intraperitoneally injected with 1 mL of thioglycolate broth (Nissui, Tokyo, Japan). Five hours later, exudate cells were harvested; approximately 90% of them were determined to be neutrophils by Giemsa staining. The neutrophils (5 × 105 cells) were stimulated with M.

13 Both studies contrasted samples from donor lungs that later developed PGD against donor lungs that did not. For the GSE9102 study, cDNA microarray data as pre-processed by the authors were used, and covered expression measurements for 6727 Ensembl build 55

human genes (http://jul2009.archive.ensembl.org). When several probes were available for the same gene, the probe displaying the most significant differential Seliciclib clinical trial expression was selected to represent that gene. For the GSE8021 study, the original raw data were processed as follows. Affymetrix Human Genome U133A 2.0 Array probes were remapped to 11894 different Ensembl build 55 human genes.14 Using these redefined probe sets, probe intensities were summarized and made comparable between arrays by quantile normalization as implemented in the Robust Multi-Array Average expression measure.15 It was possible to identify corresponding gene expression for 242 of the 272 proteins on the antigen microarray (89%). For each antigen and detection antibody, differential reactivity between patients without PGD (n = 19) and patients with PGD (n = 20) was evaluated by calculating ratios (fold-changes), t-statistics and P-values. For each gene measured, differential expression between donor lungs developing PGD (16 and 10) and those that did not (34 and 16) were similarly evaluated by

ratios, t-statistics and P-values. Multiple testing was controlled using the false discovery rate.16 A human protein interaction network was created by pooling human interaction https://www.selleckchem.com/products/H-89-dihydrochloride.html data from several of the largest databases.17 Coverage was further mafosfamide increased by transferring data from model organisms. A network-wide confidence score for all interactions, based on network topology, experimental type and interaction reproducibility, was then established. The reliability of this score as a measure of interaction confidence was confirmed by fitting a calibration curve of the score against a high-confidence set of about 35 000 human interactions. As previously described,8 all interactions with a confidence score above 0·154

were included, resulting in a network containing approximately 154 000 unique interactions between approximately 12 500 human proteins. Out of the 272 proteins on the antigen microarray, 260 (96%) were among these. As described previously,8 the statistical significance of the number of proteins in a network (the size) extracted from a given larger set of proteins, was estimated by randomly selecting sets of proteins of the same size, each time recording the size of the largest network possible to extract. For 107 such randomizations, the proportion of random sets of proteins for which equally sized or larger networks could be extracted, establishes the P-value of the network extracted from the original protein set. Over-represented biological processes among proteins in networks were identified by hypergeometric testing of gene ontology terms.

However, the mechanisms of GCI formation are not fully understood. Cellular machinery for the formation of aggresomes has been linked to the biogenesis of the Lewy body, a characteristic α-synuclein-containing inclusion of Parkinson’s disease and dementia with Lewy bodies. Here, we examined whether GCIs contain the components of aggresomes by immunohistochemistry. AZD9668 Methods: Sections from five patients with MSA were stained immunohistochemically with antibodies against aggresome-related proteins and analysed in comparison with sections from five patients with no neurological disease. We evaluated the presence or absence

of aggresome-related proteins in GCIs by double immunofluorescence and immunoelectron selleck chemicals microscopy. Results: GCIs were clearly immunolabelled with antibodies against aggresome-related proteins, such as γ-tubulin, histone deacetylase 6 (HDAC6) and 20S proteasome subunits. Neuronal cytoplasmic inclusions (NCIs) were also immunopositive for these aggresome-related proteins. Double immunofluorescence staining and quantitative

analysis demonstrated that the majority of GCIs contained these proteins, as well as other aggresome-related proteins, such as Hsp70, Hsp90 and 62-kDa protein/sequestosome 1 (p62/SQSTM1). Immunoelectron microscopy demonstrated immunoreactivities for γ-tubulin and HDAC6 along the fibrils comprising GCIs. Conclusions: Our results indicate that GCIs, and probably NCIs, share at least some characteristics with aggresomes in terms of their protein components. Therefore, GCIs and NCIs may be another manifestation of aggresome-related inclusion bodies observed in neurodegenerative diseases. “
“Fasciculation and elongation protein zeta-1 (FEZ1) is a critical regulator 3-mercaptopyruvate sulfurtransferase of dopaminergic neurone differentiation and dopamine release. However, to date, few studies evaluating the expression patterns of FEZ1 in Parkinson’s disease (PD) have been reported. The aim of this study was to investigate the expression and cellular localization of FEZ1 in a rat model of PD and to explore the role

of FEZ1 in PD pathogenesis. Male Sprague–Dawley rats were randomly divided into two groups: a PD group and a sham group. A model of PD was established by injecting 6-Hydroxydopamine Hydrobromide (6-OHDA) into the right medial forebrain bundle of rats. Sham-lesioned rats were infused with equivalent amounts of saline and served as controls. The expression levels of FEZ1 mRNA and protein in striatum and substantia nigra were examined by real-time polymerase chain reaction (PCR) and by Western blot analysis respectively. Immunohistochemistry was performed to identify the cellular localization of FEZ1 in sham-lesioned and PD rats. Western blot and real-time PCR analyses demonstrated that FEZ1 was present in normal rat brain striatum and substantia nigra. After the 6-OHDA injection, FEZ1 expression gradually increased, peaked and then decreased.

Finally, TRAM mediates TLR4 signalling exclusively 7 acting as a bridging adapter to recruit TRIF to the TLR4 complex. Regarding Mal, studies have shown that Mal interacts with MyD88, TRIF and TRAM 7, 8, but not SARM (data not shown). Although the adaptors are believed to participate in the activation of TLR signalling cascades, a number of recent studies highlight the role of TLR adaptors in the negative regulation

of alternative TLR 6, 9. Regarding the IFN-β gene itself, transcriptional activation requires assembly of a multiprotein complex to form the IFN-β “enhanceosome” 10 which is divided into four positive regulatory domains (PRD) whereby ATF-2/c-Jun binds to the PRDIV element within the IFN-β enhancer region and is activated by Tamoxifen supplier JNK. IRF3 and IRF7 are activated by ligand-mediated phosphorylation upon which they are rapidly translocated to the nucleus where they bind the PRDI-III enhancer element within the IFN-β promoter 10. Using gene-targeted mice, recent studies have shown that both IRF3 and IRF7 play essential roles in Type I IFN-β expression 11, 12. Regarding NF-κB (p50:RelA), phosphorylated NF-κB translocates to the nucleus where it binds to the PRDII element within the IFN-β enhancer 10; the role of p50, RelA and c-Rel in IFN-β gene induction is relatively

minor 13. Taken together, these studies suggest that IRF are the master Barasertib regulators of IFN-β gene induction and that NF-κB plays a relatively minor role. Understanding how pro-inflammatory TLR adaptors can modulate non-cognate TLR in certain situations has many implications, not the least of which is a comprehensive understanding of the interplay between various TLR that are likely activated during microbial infections. Although the ability of TLR adaptors to activate specific signalling pathways has been well defined, the ability to negatively regulate non-cognate TLR signalling

cascades requires further investigation 9, 13. Recently, it has been Montelukast Sodium shown that MyD88 negatively regulates TLR3/TRIF-induced corneal inflammation 9. Also, potentiation of poly(I:C)-mediated IL-6 induction and JNK phosphorylation was observed in Mal−/− BM-derived macrophages (BMDM) when compared with WT BMDM 6. Herein, we provide the first detailed mechanistic analysis of how TLR signalling may be counterregulated by non-canonical mechanisms. As shown in Fig. 1A, following quantitative real-time RT-PCR measurements, we demonstrate that although stimulation of WT BMDM, expressing TLR3 endosomally 14, with poly(I:C) resulted in IFN-β gene induction, a significantly greater induction of IFN-β was evident in Mal−/− BMDM. In contrast to poly(I:C), we found comparable levels of IFN-β induction in WT and Mal-deficient BMDM stimulated with the TLR7 ligand, R848 and the TLR9 ligand, CpG (Supporting Information Fig. 1).

In this report, we applied NNAlign to peptide–MHC class II binding data for five HLA-DP and six HLA-DQ molecules to characterize their specificities and binding motifs. The binding data were obtained from the publication by Wang et al.7 They comprise a total of 17 092 measured peptide–MHC affinities, with an average of over 1500 measurements per allelic variant. Each data set was split in five random subsets and, each time excluding PF-01367338 chemical structure one subset, a network was trained on the remaining four subsets. We set the motif length to nine amino acids, and for all the remaining parameters we used the default values of the NNAlign web server: sequences were presented to the networks using Blosum encoding,13

hidden layers were composed of three neurons, training lasted 500 iterations per training example, starting from five different initial configurations for each cross-validation

Proteasomal inhibitors fold, subsets for cross-validation were created using a homology clustering at 80% to reduce similarity between subsets, using the best four networks for each cross-validation step. The resulting 20 networks in each ensemble, trained on different subsets of the data and from alternative initial conditions, capture motifs that can be different from each other to some extent. They often place the alignment core in a different register, and might disagree on the exact boundaries of the motif. The offset correction algorithm described by Andreatta et al.12 proved extremely efficient in correcting for this disagreement, allowing re-alignment of different networks to a common core. This alignment procedure creates a position-specific scoring matrix (PSSM) representation of the motif of

each network, and then aligns the matrices to maximize the information content of the combined core. We used a slightly modified version of the algorithm described in detail in a previous publication,12 where PSSMs are extended at both ends with background frequencies before alignment, so allowing the PSSMs to be aligned on a window Selleckchem Nutlin3 of the same length as the matrices. This process assigns to each PSSM, and its relative network, an offset value that quantifies the shift distance from other networks. Note that the alignment procedure does not guarantee that the final combined register corresponds to the biologically correct register (in the case of peptide–MHC binding, the nine-amino-acid stretch bound in the MHC binding cleft), but rather to the window with the maximum information content. In most of the cases informative positions are also biologically important positions, so the core register would be in the correct place. However, if either terminal of the core has very weak information content (i.e. no particular amino acid preference at terminal positions), the sequences might possibly, although aligned correctly, all be shifted by one or more positions with respect to the biologically correct core register.

ELISAs were developed using o-phenyl diamine dihydrochloride (OPD) substrate (Sigma) in sodium citrate buffer, this website pH 5, plus H2O2. H2SO4 (12·5%) was used to stop the OPD reaction, and plates were read at

490 nm using Softmax™ Pro software (MDS Analytical Technologies, Sunnyvale, CA). Modulation of the CD3–TCR complex in peripheral blood was analyzed by flow cytometry 2 and 24 hr after each dose when mice were dosed every 24 hr and 2 and 72 hr after each dose when mice were dosed every 72 hr. Following red blood cell lysis, cells were stained using murine antibodies to CD3 (145-2C11), CD4 (RM4-5), CD8 (53-6.7) and TCR-β (H57-597) (BD Biosciences, San Jose, CA). Molecules of equivalent soluble fluorochrome (MESF) values were generated Y-27632 in vitro using Quantam™ fluorescein isothiocyanate (FITC) MESF microspheres as per the manufacturer’s instructions (Bangs Laboratories,

Fisher, IN). FoxP3 expression was evaluated using a FoxP3 staining kit (NRRF30 clone; eBioscience, San Diego, CA), as per the manufacturer’s instructions. Fluorescent cells were analyzed by flow cytometry using FACScalibur (BD Biosciences). In Study B, serum was collected before and after treatment and analyzed for the murine C-peptide I content by ELISA, according to the manufacturer’s instructions (ALPCO, Salem, NH). In Study B, pancreata were fixed in formalin, processed and embedded in paraffin. Inositol monophosphatase 1 Sections of 4–5 μm in thickness were stained with haematoxylin and eosin. Islet inflammation was evaluated using light microscopy by a board-certified veterinary pathologist (Charles River Laboratories, Wilmington, MA). Peri-insulitis inflammation was scored as: 0 = normal (no leucocytes);

1 = minimal (< 5 leucocytes in any islet); 2 = mild (6–20 leucocytes in the ‘most severe’ islet); 3 = moderate (21–50 leucocytes in the ‘most severe’ islet); 4 = marked (> 50 leucocytes in the ‘most severe’ islet); or 5 = severe (> 50 leucocytes in > 1 islet). MESF values were analyzed using repeated-measures analysis of variance (anova), with treatment and time as factors. Lymphocyte count data were analyzed by one-way anova. Pairwise treatment group comparisons for these analyses were carried out using the corresponding t-tests. Fisher’s exact test was used for pairwise treatment group comparisons of proportion data. Exploratory comparisons between post-treatment remission and diabetic groups were made using t-tests (quantitative data), Fisher’s exact test (proportion data), or the chi-square test (categorical data). P-values were not adjusted for multiple comparisons.

At the functional level, rat splenocytes and IHLs have been shown to secrete IFN-γ and IL-4 in response to stimulation with α-GalCer [12, 13] in a CD1d-dependent fashion ([13] and this study). α-GalCer-loaded mouse or human CD1d tetramers bind very poorly to the rat iNKT-TCR [12] (Monzon-Casanova, Herrmann, unpublished data). This is in contrast to the mouse and the human, both of which show CD1d/iNKT-TCR cross-species reactivity

[1], but it explains why a discrete population was not observed among rat IHLs using mouse CD1d tetramers [12]. Furthermore, former attempts to identify rat iNKT cells using surrogate markers have also failed as no cell population has yet been found with the features predicted for iNKT cells based on their mouse counterparts. Instead, rat NKR-P1A/B-positive PD-0332991 mw T cells are found in the spleen and the liver at similar frequencies, show no BV8S2 or BV8S4 bias, produce IFN-γ but not IL-4, and most of them express CD8β [9, 12, 14-16]. In the present study, newly generated rat CD1d dimers allowed us to identify rat iNKT cells for the first time in the F344 inbred rat strain.

Importantly, these cells are more similar to human than mouse iNKT cells in terms of frequencies, CD8 expression, and expansion upon in vitro stimulation with α-GalCer. In addition, we found a nearly complete lack of iNKT cells in the widely used LEW rat strain. These findings identify the rat as a closely matching animal model to study the biology and the therapeutic use of iNKT cells in humans.

The negligible binding of rat iNKT-TCR to Enzalutamide datasheet α-GalCer-loaded mouse CD1d tetramers [14] prompted us to generate syngeneic CD1d dimers. Rat and mouse CD1d dimers were loaded with α-GalCer or vehicle only (DMSO) as a control and were used to stain IHLs derived from F344 rats and from C57BL/6 mice (Fig. 1). Rat α-GalCer-CD1d dimers Phospholipase D1 bound to a small but distinct population of F344 IHLs, which was missing when rat vehicle-CD1d dimers were used. As expected, very few rat cells were stained by mouse α-GalCer-CD1d dimers (when comparing with the vehicle control), but in contrast, a subpopulation of mouse iNKT cells was stained with rat α-GalCer-CD1d dimers. These results are consistent with our previous functional data [12]. The differences between the iNKT-cell frequencies of C57BL/6 mice and F344 rats are noteworthy. In C57BL/6 mice, more than 50% of all αβ T cells in the liver (30% of total IHLs) were detected with mouse α-GalCer-CD1d dimers, while in F344 rats, iNKT cells constituted only 1.05% of all αβ T cells (0.24% of total IHLs; Fig. 1 and Supporting Information Table 1). In both species positive α-GalCer-CD1d-dimer-stained T cells expressed low TCR levels, a feature of iNKT cells. In line with the particular homing preferences of iNKT cells, more iNKT cells were found in the liver (0.24%) as compared with what was found in the spleen (0.013%) of F344 inbred rats (Fig.