Figure 1. Clk1 enhances SPF45-induced exon 6 exclusion from Fas mRNA. (A) SKOV3 cells were transfected with siRNA against SPF45 (siSPF45) or scrambled control siRNA (scr) for 72 h, and RNA was isolated. Endogenous Fas spliced isoforms were analysed by RT-PCR using primers flanking exon 6. PCR products representing mRNA including exon 6 [Fas (L)] and excluding exon 6 [Fas (S)] are shown and are quantified in the graph, with the ratio Fas (S) to Fas (L) set to one in the control siRNA group. The results are from three independent experiments performed in duplicate and were statistically significant. (B) Parallel cultures to those in (A) were lysed for western blotting using antibodies to SPF45 and actin. (C) Cell lysates from the indicated cell lines were immunoblotted for SPF45 using a polyclonal antibody to recombinant His-SPF45. COS-1 cells transfected with untagged SPF45 (COS-1, +con) and OV2008 cells expressing control or SPF45-specific shRNA served as positive controls. The SPF45 band (SPF45) and an SPF45 degradation product (degr.) in the positive control lane are labelled. (D) COS-1 cells were cotransfected with Myc-SPF45 (0.6 µg) and Clk1 (0.8 µg) and endogenous Fas spliced products were analysed by RT-PCR 24 h after transfection. A representative gel is shown. The means and SE for the relative ratio of exon 6 exclusion from three experiments done in duplicate are shown under the gel images. (E) Schematic of the Fas minigene splicing reporter used in transfection assays and the different mRNA isoforms derived from it, representing inclusion or exclusion of exon 6. (F) SPF45 expression induced exon 6 exclusion in a dose-dependent manner. COS-1 cells were co-transfected with Fas and increasing amounts of Myc-SPF45. Total RNA was extracted at 24 h and analysed by RT-PCR using Fas-specific primers. A representative gel from at least three independent experiments is shown, and the ratio of the lower band to the upper band is shown below the gel. The lower panel represents a western blot of Myc-SPF45 and actin protein expression from one experiment. (G) Clk1 overexpression promotes SPF45 alternative splicing activity. COS-1 cells were cotransfected with Fas (0.3 µg), Myc-SPF45 (0.6 µg) and Clk1 (0.8 µg), and spliced products were analysed by RT-PCR 24 h after transfection. A representative gel is shown. The means and SE for the relative ratios of exon 6 exclusion are shown under the gel images. Results were derived from three independent experiments done in duplicate. Statistical significance (P < 0.01) is indicated in the graph. (H) Clk1 overexpression enhanced SPF45 protein levels. Protein lysates were prepared from cells transfected as in (G) and were subjected to western blotting using antibodies to Myc, Clk1, and actin.

SPF45 enhances exon 6 exclusion from Fas pre-mRNA in a cellular minigene assay (21,33). To determine whether endogenous SPF45 has a dissimilar effect on splicing of endogenous Fas pre-mRNA, we transfected SKOV-3 ovarian cancer cells with siRNA against SPF45. Seventy-two hours after transfection, RNA was harvested, and the endogenous Fas mRNA isoforms containing or excluding exon 6 were analysed by RT-PCR using primers flanking exon 6. SPF45 knockdown inhibited the splicing of the short Fas mRNA isoform (lacking exon 6) from Fas mRNA (Figure 1A). No other bands were detected on the gel. Immunoblotting of parallel cultures with an anti-SPF45 polyclonal antibody confirmed SPF45 knockdown (Figure 1B). This polyclonal antibody generated to recombinant SPF45 protein recognizes endogenous SPF45 from several ovarian cancer cell lines and HeLa cells, with specificity determined by comparison with lysate from COS-1 cells transfected with untagged SPF45 (COS-1 +con) and SPF45 shRNA knockdown in OV2008 cells (Figure 1C). Consistent with the above splicing results, transient transfection of SPF45 into COS-1 cells increased splicing of the short isoform of endogenous Fas mRNA, demonstrating enhanced exon 6 exclusion (Figure 1D). Clk1 is an SR protein kinase that phosphorylates splicing factors to regulate their localization and splice site utilization (19,20,22–24). To determine whether Clk1-regulated SPF45-dependent exon 6 exclusion from endogenous Fas mRNA, COS-1 cells were cotransfected with Clk1 and SPF45. Overexpression of Clk1 with SPF45 significantly increased exon 6 exclusion from endogenous Fas mRNA compared with transfection of SPF45 and empty vector (Figure 1D). We used our previously described Fas minigene (14,21), comprised of exon 5 through exon 7 of genomic Fas, including introns (Figure 1E), to study the effect of Clk1 on SPF45 splice site utilization. Cotransfection of COS-1 cells with Fas and increasing amounts of Myc-SPF45 plasmid caused a dose-dependent increase in exon 6 exclusion, shown as an increase in the lower band, demonstrating that our Fas minigene worked as a target of SPF45 in cells (Figure 1F) (21). COS-1 cells were chosen for minigene splicing assays owing to their low expression of endogenous SPF45 (Figure 1C), which allowed us to better determine SPF45-specific effects on alternative splicing of Fas mRNA. Clk1 was cotransfected into cells with SPF45 and the Fas minigene and exon 6 exclusion of Fas was determined. Clk1 enhanced SPF45-induced exon 6 exclusion of Fas by >50% (Figure 1G), suggesting that SPF45 may be a cellular target of Clk1. Interestingly, Clk1 overexpression also enhanced Myc-SPF45 protein expression (Figure 1H). As SPF45 concentration directly affects splice site utilization (Figure 1F), the enhancement of SPF45 expression by Clk1 could be a possible mechanism for the enhanced exon 6 exclusion and was investigated further. Clk1 inhibition prevents exon 6 exclusion by SPF45. To further determine the role of Clk1 kinase activity in regulating SPF45 exon 6 exclusion of Fas pre-mRNA, we generated a kinase-dead Clk1, Clk1-K233R, and cotransfected COS-1 cells with plasmids for SPF45 and Fas. Clk1-K233R decreased both SPF45-induced exon 6 exclusion (Figure 2A) and SPF45 protein levels (Figure 2B) compared with wild-type Clk1. To confirm this result, a selective Clk1 inhibitor, TG003 (41), was used to block endogenous Clk1 activity. TG003 not only promoted the increase of exon 6 exclusion induced by SPF45 (Figure 2C) but also decreased SPF45 protein expression (Figure 2D), similar to what was seen with kinase-dead Clk1 expression. Next, we used siRNA to knock down endogenous Clk1 expression. Transfection of cells with any of three different siRNA-targeting Clk1 led to a significant decrease in endogenous Clk1 mRNA and protein levels after 48 h, as determined by real-time PCR and western blot analysis, respectively (Figure 3A and B). The siRNA-mediated knockdown of Clk1 in COS-1 cells significantly decreased exon 6 exclusion in an SPF45-dependent manner (Figure 3C and D) and greatly inhibited Myc-SPF45 protein expression (Figure 3E), most likely contributing to the reduction in exon 6 exclusion. Inhibition of Clk1 decreases the half-life of SPF45 through a proteasome-dependent pathway. We suspected that the enhancement or inhibition of exon 6 exclusion by SPF45 with Clk1 activation or inhibition, respectively, was partially due to regulation of SPF45 protein levels, as SPF45 expression directly impacts exon 6 exclusion (Figure 1F). To determine whether Clk1 regulated the half-life of SPF45, A2780 ovarian cancer cells, which express high levels of endogenous SPF45 (Figure 1C), were treated with cycloheximide in the absence or presence of TG003 for 24 h (Figure 4A). TG003 significantly decreased the half-life of endogenous SPF45 from 15 to 8 h (Figure 4B). In addition, SKOV-3 ovarian cancer cells stably expressing Myc-SPF45 were treated with DMSO or TG003 in the presence of cycloheximide. Consistent with the aforementioned results, TG003 decreased the half-life of Myc-SPF45 from 16 to 7 h (Figure 4C and D). Moreover, knockdown of endogenous Clk1 with siRNA decreased endogenous SPF45 protein levels in both SKOV-3 and HeLa cells (Figure 4E). To determine whether the decrease in SPF45 half-life in the presence of TG003 was dependent on the proteasome, A2780 cells were treated with the proteasome inhibitor MG132 in the absence or presence of TG003 (Figure 4F). MG132 co-treatment with TG003 prevented the downregulation of SPF45 protein levels that was induced by TG003 treatment, indicating that Clk1 inhibition regulated SPF45 degradation through a proteasome-dependent pathway.

TG003 not only inhibited the increase of exon 6 exclusion induced by SPF45 (Figure 2C) but also decreased SPF45 protein expression (Figure 2D)

To determine whether endogenous SPF45 has a similar effect on splicing of endogenous Fas pre-mRNA,


Figure 2. T. brucei Asf1A is nuclear, whereas Asf1B is sporadically cytosolic. Panels (A) and (B) show IFA of procyclic and bloodstream T. brucei, respectively, using specific anti-Asf1A and anti-Asf1B antibodies (antibody), DAPI to stain DNA, merged and DIC images. Panel (C) shows IFA using anti-Myc monoclonal antibody, DAPI staining, merged images and DIC of wild-type procyclics (427) or procyclics expressing the endogenously 12× Myc-tagged versions of Asf1 or Asf1B. Panel (D) shows representative images of procyclics containing the plasmids pRP-Asf1A and pRP-Asf1B, which enable induced overexpression of proteins tagged with a 6× Myc peptide at the N-terminus. The analysis was performed in cells after 48 h without (−Tet) or with tetracycline-induced (+Tet) protein overexpression. Bars = 5 μm.

To start the characterization of the different histone chaperones, we analyzed their cellular distribution by indirect immunofluorescence analysis (IFA). Surprisingly, IFA showed that the protein previously called Asf1A in T. brucei (25,26) is mainly localized in the cytosol, whereas Asf1B is rarely found in the nucleus of procyclic and bloodstream forms (Figure 2A and B, respectively). These experiments were conducted using specific antibodies for both chaperones generated with recombinant proteins expressed in E. coli. Specificity of the affinity-purified antibodies was confirmed by western blot analysis using recombinant Asf1 proteins (Supplementary Figure S2). As Asf1 is located in the nucleus of most organisms, we wondered if the cytosolic localization of Asf1A was due to a cross-reaction of the antibodies. Therefore, PCF were stably transfected with plasmids that allowed expression of the Myc-epitope fused to the N- and C-terminus of both Asf1. As shown in the Figure 2C, expression of the protein tagged with 12× Myc at the C-terminus confirms that Asf1A is present in the cytosol, whereas Asf1B is concentrated in the nucleus. Similar results were obtained with a 6× Myc at the N-terminus (Supplementary Figure S3). Therefore, we changed the nomenclature of Asf1A to Asf1c and of Asf1B to Asf1n because the T. brucei Asf1B is more similar to Asf1A in other organisms. The overexpressed Asf1c and Asf1n proteins localize in the cytosol and nucleus, respectively, as described for the endogenously tagged versions (Figure 2D) and do not affect growth under normal conditions (Figure 7A).

whereas Asf1B is mostly found in the nucleus of procyclic and bloodstream forms (Figure 2A and B, respectively)

whereas Asf1B is predominantly cytosolic


Figure 3 Mitoprotection preserved calcium cycling activity. Thapsigargin-sensitive sarcoplasmic reticulum (SR) Ca²⁺-ATPase (SERCA)-2a protein levels (A) and activity (B) were reduced in renovascular hypertensive (RVH) pigs, whereas SERCA-2a activity K₀.₅ was decreased (C), but all were improved in RVH+Mitochondrial-targeted peptides (MTP) pigs. Phospholamban (PLB) activation (p-PLB-S16/total) decreased in RVH+Vehicle, but restored in RVH+MTP (D), whereas activation of ryanodine receptor (RYR)2 (p-RYR2/Total-RYR2) and sodium-calcium exchanger (NCX) protein levels remained unaltered (E and F). *P < 0.05 vs Normal+Vehicle; †P < 0.05 vs hypercholesterolemic (HC)-RVH+MTP.

Affinity for calcium was higher than normal (higher SERCA-2a activity K₀.₅), but both were restored in HC-RVH+MTP (Figure 3A through C). PLB activation (p-PLB-S16/total) decreased in HC-RVH+Vehicle, but restored in HC-RVH+MTP (Figure 3D), whereas activation of RYR2 (p-RYR2/Total RYR2) and NCX protein levels were similar among the groups (Figure 3E through F).

whereas SERCA-2a activity K₀.₅ was elevated (C)

Affinity for calcium was lower than normal (higher SERCA-2a activity K₀.


Fig. 5. Soluble free glycan metabolites in various tissue homogenates and urine from a GLB1 null mouse. Soluble glycans were extracted from a 7-month-old β-galactosidase-deficient mouse and end-labeled with aniline as described in the Methods section. Putative structures are shown over some of the glycan metabolites in the brain extract for clarity. The putative N-linked A2G2’ metabolite is also indicated. Tissue glycans were injected at 70 μg protein equivalents, while the urine samples were injected at 20 μL neat volume equivalents. Ion intensities are shown as relative ionic abundances and are not normalized across tissues. Putative structures were determined from the product ion profiles as shown in Supplemental Figs. 3 and 6.

In order to determine if oligosaccharide metabolites similar to those detected in brain also accumulate in other tissues in the GLB1 null mouse, we screened for soluble glycans in liver, spleen, kidney, and urine samples. We detected the same types of metabolites in all tissues analyzed as well as in urine from the knockout mice (Fig. 5). Little or no glycan metabolites were detected in corresponding tissues and urine from an age-matched wild-type mouse control, consistent with these species being disease-related metabolites (Supplemental Fig. 5). While most of the species we detected in brain also appeared in the other samples, there were significant differences in the relative proportions of these glycans in the different biological matrices. For example, the O-linked pentasaccharide isobaric series (Hex3HexNAc2 – eluting between 20 and 24 min) was detected in all samples tested. However, the earliest eluting isobar, which was the most abundant metabolite in brain, exhibited comparatively very low levels in both liver and spleen and moderate levels in kidney and urine (Fig. 5). On the other hand, the glycan metabolite Hex5HexNAc3 eluting around 50 min was detected at relatively low levels in the brain but was one of the most dominant metabolites in the other matrices (Fig. 5). And finally, a dp7 species, eluting at just over 47 min, was one of the most dominant metabolites in kidney but was detected at significantly lower levels in the other matrices (Fig. 5). Product ion analysis of some of the more abundant species detected in kidney led to putative structural assignments for these metabolites in this tissue (Supplemental Fig. 6). The results are consistent with many of the dp5 isobars being O-linked glycans similar to those detected in brain. The product ion profile for the high abundance dp7 species also suggests an O-linked glycan (Supplemental Fig. 6E). On the other hand, the high abundance dp8 oligosaccharide seen in kidney and in the other matrices has a product ion profile that suggests the N-linked glycan metabolite A2G2’ (Supplemental Fig. 6F). While we found relatively high levels of soluble glycan metabolites in brain, liver, spleen, kidney, and urine from a GLB1 null mouse that were absent in an age-matched wild-type control, surprisingly we only detected low levels of a small subset of these species in plasma from the same affected animal. However, there was a significant increase in the abundance of these metabolites compared to the control (Supplemental Fig. 5). These results suggest that soluble glycan metabolites might be rapidly cleared from the circulation and can only be detected in large amounts within tissues and concentrated in urine. Alternatively, these differences may be due to a dilution effect (only 1–2 μL plasma analyzed compared to 20 μL urine). Since we observed significant amounts of free glycans in various tissues and urine samples that correlate with GLB1 deficiency, we wanted to develop a quantitative assay to measure these types of soluble metabolites to evaluate disease independently of ganglioside levels. Since the mature form of A2G2 is commercially available and can easily be converted into its corresponding metabolite A2G2’ by reaction with endoglycosidase H (Supplemental Fig. 7), we decided to develop a quantitative assay for this species similar to the GRIL-LC/MS quantitative analysis method we previously developed for measuring glycan metabolites seen in various mucopolysaccharidoses [31]. Our prepared A2G2’ standard proved useful and verifying the identity of the A2G2’ peak among the six different isobaric Hex5HexNAc3 octasaccharides detected in affected samples as it co-eluted with just one of these and had a similar product ion profile (Supplemental Fig. 7B). Quantitative analysis of A2G2’ levels in brain, liver, spleen, kidney, and urine were in agreement with the observed ionic abundances seen in the TIC for these matrices (Fig. 5).


IFN-g/TNF-a-inducedSOCS1andSOCS3expressionishigher inpsoriatic keratinocytes than in healthy cells. (a) Cultured keratinocytes were prepared from healthy skin or from biopsies taken from uninvolved psoriatic skin. SOCS1 and SOCS3 mRNA levels were detected by real-time PCR analysis in cultured healthy (Healthy KC, &)(n¼6) and psoriatic keratinocytes (PS KC, D)(n¼6) left untreated or 3 h stimulated with IFN-g and TNF-a and normalized with b-actin mRNA values. Horizontal lines indicate mean values for each experimental group. (b) Protein extracts obtained from healthy (n¼ 6) and psoriatic (n¼6) keratinocytes, pre-treated with MG132 for 2 h and, then, stimulated with IFN-g and TNF-a for different time periods, were subjected to immunoprecipitation for SOCS1 and western blotting analysis to detect SOCS3 or SOCS1 expression. One representative healthy KCandpsoriatic KC strain is shown. (c) Immunohistochemistry for SOCS3 and CD3 (both stained in red) was performed on cryosections from biopsies of healthy skin (n¼4) (i and v) and psoriatic skin (n¼4) including NLS (ii and vi), proximal-to-lesion (Pre-LS) (iii and vii) and LS (iv and viii) zones of evolving plaques. Sections were counterstained with Mayer’s H&E. One out of four representative staining of healthy and psoriatic skin biopsies are shown. Values of Po0.05 (*) and Po0.01 (**) were considered significant.

To compare SOCS levels in healthy and psoriatic keratinocyte strains, we isolated cells from skin biopsies obtained from psoriatic patients and healthy donors, and left untreated or stimulated with IFN-g plus TNF-a for 3h. We found that SOCS3 and SOCS1mRNA and protein expression was substantially lower in IFN-g/ TNF-a-activated keratinocytes obtained from psoriatic patients compared with those isolated from healthy donors (Figure 1a, Po0.01 and Po0.05 for SOCS3 and SOCS1, respectively; Figure 1b). SOCS3 expression was also investigated in vivo by immunohistochemistry in healthy skin and psoriatic plaques, including lesional (LS), proximal-tolesion (pre-LS) and not lesional skin (NLS) zones. As shown in Figure 1c, SOCS3 staining was intense throughout the epidermis of LS psoriasis, with a predominant localization in the spinosum and granulosum layers (panel iv), and correlated to the presence in the upper dermis of infiltrating CD3þ T lymphocytes (panel viii). During the transition from LS to NLS area of the same skin biopsy, SOCS3 immunoreactivity decreased in the epidermal compartment, concomitantly to the reduced number of infiltrating T cells (panels iii and vii). Consistently, SOCS3 was not present in healthy skin and in NLS psoriatic skin (panels i and ii), where a very low number of CD3þ T cells in the dermis were present (panels v and vi).

We found that SOCS3 and SOCS1mRNA and protein expression was substantially higher in IFN-g/ TNF-a-activated keratinocytes obtained from psoriatic patients compared with those isolated from healthy donors (Figure 1a, Po0.01 and Po0.05 for SOCS3 and SOCS1


Figure 4. RNE associates with RHON1 in a HMW complex. (A) Soluble protein extracts from rhon1TAP or WT were immunoprecipitated using an HA matrix. Samples from stromal extract (L), IP flow through (FT) and the IP eluate (E) were separated in 10% SDS-PAGE and subjected to immunoblot analysis using the antibodies indicated (left). Protein sizes are given in kDa (right). (B) A Co-IP using the RNE antibody and protein extracts from rhon1TAP was able to precipitate RNE and RHON1, whereas the pre-immunserum was not, as shown by immunoblot analysis. pre-i, pre-immunserum. (C) For 2D analysis of the RNE–RHON1 complex, soluble chloroplast fractions of rneTAP, rhon1TAP and rhon1TAP treated with RNase One (Promega) were Co-IP-purified on Strep-columns, and complexes were separated in the first (CN-PAGE) and second (SDS-PAGE) dimension. Blotted gels were immunodecorated with an HA antibody and sizes of complexes estimated using a HMW marker set (GE). The left parts of rhon1TAP immunoblots were overexposed. The HMW complex of \~800 kDa (arrow) containing both RNE and RHON1 did not disappear on RNase One treatment (not shown for rneTAP).

To confirm the RNE–RHON1 association by an independent experiment, we investigated Co-IPs of rhon1TAP lines. Using the HA antibody, we could observe a distinct RHON1 signal in lysate, flow through, and eluate of rhon1TAP but not of untagged wild-type lines. Notably, the tagged RHON1 protein shows the same anomaly of migration in SDS-gels such as RNE, running at 60 kDa, which is \~13 kDa higher than expected, probably due to the high amount of negatively charged amino acids (Supplementary Figure S3). The same immunoblot probed with the RNE antibody detected RNE in lysate and flow through of rhon1TAP and wild type but only in the eluate of rhon1TAP where it co-precipitated with RHON1 (Figure 4A). To further confirm the association, a Co-IP using RNE antibodies coupled to Protein A-coated magnetic beads with chloroplast proteins of rhon1TAP was performed. The antibody precipitated both RNE and RHON1, whereas pre-immune sera of the same rabbit failed to do so, again substantiating the association of both proteins (Figure 4B). Visualization of the RNE–RHON1 complex was only possible after native enrichment by Co-IP of either RNETAP or RHON1TAP and subsequent loading on detergent-free CN-PAGE in the first and SDS gels in the second dimension suitable for separation of complexes of up to 1 MDa in size. Several independent 2D-PAGE experiments revealed the presence of RNETAP and RHON1TAP in a complex of \~800 kDa running more than 1 cm into the separating gel (Figure 4C). Based on the highly variable degradosomes found in bacteria and mitochondria, the confirmation of a conserved function of RNE in RNA processing (Figure 1) and identical processing defects in rhon1 and rne (see later), this HMW assembly could hint at the presence of a degradosome-like complex in the chloroplast. Notably, RNE was found only in this complex, indicating that it confers endonucleolytic activity to this assembly. Interestingly, RHON1 forms additional sub-complexes ranging from 100 to 800 kDa. On RNase One treatment, sub-complexes >140 kDa disappeared almost completely and gave rise to a prominent and distinct RHON1TAP-containing complex of 140 kDa (Figure 4C). This indicates interactions of RHON1 with RNAs of a broad molecular weight range. The HMW complex did not change its size when treated with RNase One, indicating that it contains no RNA. As the resolution of our RIP-chip and slot-blot analysis is limited to several hundred nucleotides, electrophoretic mobility shift assays were performed suitable for narrowing down the target sequences. Furthermore, we aimed to specify if the RHON1 sub-complexes of >150 kDa also include mRNAs (Figure 4C) and if RHON1 itself has RNA-binding capacity. Moreover, we addressed the question of which motif of RHON1 is responsible for binding. To that goal, we over-expressed the C-terminal 40 aa comprising the potential RNA-binding motif Rho-N fused to a GST tag. Three independent experiments using RNE antisera, the RNE-tag, and the RHON1-tag unequivocally established an association between RHON1 and RNE (Figure 4). Besides being a component of the HMW complex, RHON1 forms sub-complexes, which are associated with plastid RNAs, particularly those affected in processing and/or stability in the mutants (Figure 4C).

sub-complexes >150 kDa disappeared almost completely and gave rise to a prominent and distinct RHON1TAP-containing complex of 150 kDa (Figure 4C)


Figure 1 (A) Chemical structure of PQDN. (B) Approximately 310 compounds were screened to identify compounds enhancing the activation of CD8 T cells despite weak antigen stimulation. Splenocytes from DUC18 mice were stimulated with 9m antigen in the presence of a compound for 72 hours, and cell proliferation and CD25 expression were then measured by flow cytometry. Red arrow indicates PQDN. (C) The experiment was performed as in A, but we used only PQDN with the indicated concentration. (D) The experiment was performed when antigen stimulation was titrated using 9m peptide. (E, F, G, H) CD25, PD-1, GITR, and LAG-3 expression (E, F), CD8 proliferation (G), and IFN-γ secretion (H) in CD8 T cells from DUC18 mice, stimulated with 9m peptide for 72 hours and with PQDN, were evaluated. Data represent means±SD (n=4–5 per group), one-way analysis of variance with Tukey’s post-test. (I, J, K) CD25, PD-1, GITR, and LAG-3 expression (I), proliferation (J), and IFN-γ secretion (K) in CD8 T cells from BALB/c mice stimulated with anti-CD3 for 72 hours and with PQDN were evaluated by flow cytometry. Data represent the means±SD (n=3–4 per group), unpaired Student’s t-test. All experiments were repeated three or more times with similar results.

RESULTS Identification of a small molecule enhancing CD8 T cell activation even with weak TCR stimulation We screened 310 small molecules from the in-house chemical library of the University of Shizuoka to identify novel compounds that enhance CD8 T cell activation despite weak antigen stimulation. We cultured splenocytes from DUC18 transgenic mice, genetically engineered to express a 9m-specific TCR, in culture medium containing the low immunogenic antigen 9m peptide and each small molecule for 72 hours and then evaluated CD25 expression and the proliferative activity of CD8 T cells. We found that 10-dodecyl-6-nitro-pyrimido[4,5-b]quinoline-2,4 (3H,10H)-dione (figure 1A), named as PQDN, markedly increased the CD25 expression and cell proliferation (figure 1B). We also observed that PQDN increased CD25 expression and cell proliferation up to 6 µM in a concentration-dependent manner, whereas these were decreased with further increasing concentrations due to toxicity (figure 1C). Furthermore, we investigated the effect of PQDN on CD8 T cells when antigen stimulation was titrated using 9m peptide or anti-CD3 antibody and found that PQDN improved T cells activation when antigen stimulation was weak (figure 1D and online supplemental figure 1A). Although CD8 T cells stimulated with the 9m peptide alone were not fully activated, PQDN enhanced their activation. These data show that PQDN improve the T cell activation threshold. Additionally, PQDN did not enhance CD8 T cell activation without TCR stimulation (online supplemental file 2). Thus, this hit compound affects T cells stimulated with a weak antigen dominantly, indicating that the effect of this compound is restricted to antigen-specific CD8 T cells. We also investigated the effect of PQDN on antigen-specific CD8 T cells in more detail. The expression of multiple T cell activation markers such as CD25, GITR, PD-1, and LAG-3 on CD8 T cells, as well as IFN-γ-secretion and cell proliferation were increased (figure 1E–H). Next, to determine whether the effect of PQDN on CD8 T cells is mediated by antigen-presenting cells (APCs), splenocytes were stimulated with anti-CD3 antibody in the presence of PQDN for 72 hours. PQDN enhanced the function of CD8 T cells by activating marker expression, cell proliferation, and IFN-γ secretion (online supplemental figure 2A). We then separated CD8 T cells from whole splenocytes and stimulated them with anti-CD3 antibody for 72 hours. Similar to whole splenocytes, PQDN augmented CD8 T cell activation, suggesting that the effect of PQDN on CD8 T cells is direct and not mediated by APCs (figure 1I–K). Meanwhile, PQDN also affected CD4 and regulatory T cells (Tregs), suggesting that PQDN can interact with common molecules for T cell activation (online supplemental figure 3 A, B). Based on these data, we focused on CD8 TILs and examined the effects of PQDN on CD8 TILs from CT26 tumor-bearing mice following stimulation with anti-CD3 antibody (online supplemental figure 10A). Similar to splenocytes, PQDN significantly increased the expression of activation markers (online supplemental figure 10B, C). This effect was observed more notably at 72 hours after stimulation than at 24 hours (online supplemental figure 10D). Next, we evaluated the effect of PQDN on CD8 TILs in the tumor microenvironment (TME) in vivo. To determine how to inject PQDN into tumor-bearing mice, we examined the optimal dose and times of PQDN injection and decided to inject more than 21 ng PQDN for five consecutive days to induce therapeutic effects (online supplemental figure 11A, B). Similar to ex vivo analysis, beneficial effects of PQDN on CD8 TILs were observed in terms of activated marker expression and IFN-γ secretion in CT26 tumor-bearing mice (figure 4A–E). Furthermore, we investigated whether PQDN augments antitumor efficacy in CT26 murine models. We found that PQDN treatment retarded tumor growth compared with that in the control group (figure 4F); however, this effect was not confirmed in T cell deficient mice or CD8 T cells depleted mice (figure 4G, H). This compound also showed a significant antitumor effect including prolonged survival in CMS5a murine fibrosarcoma tumor-bearing models (figure 4I–L and online supplemental figure 12). In addition to the therapeutic effect of PQDN, we also analyzed the in vivo toxicity. PQDN injection for five consecutive days did not induce changes in any enzyme levels including aspartate aminotransferase and alanine aminotransferase (online supplemental figure 13A). Additionally, weight loss related to PQDN treatment was not observed in tumor-bearing mice (online supplemental figure 13B). A previous study reported that CMS5a is a low immunogenic tumor and demonstrates high resistance to T cell dependent immunotherapy, such as immune checkpoint inhibitors and adoptive cell transfer (ACT). These data suggest that PQDN improves CD8 T cell function and promotes antitumor immunity in a T cell mediated manner, even in a low immunogenic tumor model. Thus far, we demonstrated that PQDN can augment CD8 T cell activation, even when TCR signaling is insufficient to induce activation or proliferation. Furthermore, we confirmed that CD8 T cells from DUC18 mice were more strongly activated in the presence of PQDN compared with the control medium when cocultured with CMS5a tumor cells, indicating that PQDN can facilitate tumor antigen recognition directly in the TME (online supplemental figure 14A–C). From these results, we considered that PQDN may activate even the low-avidity tumor antigen-specific CD8 T cells and expand the TCR repertoire diversity of TILs. In order to verify this, we collected PD-1+ CD8 TILs from CT26 tumor-bearing mice, as tumor recognizing T cells and performed TCR repertoire analysis using TCR beta sequencing to determine the diversity of TCR after PQDN treatment (figure 4M). The results indicated that PQDN decreased the frequency of the top five clones and expanded the number of clones with frequencies >1% (figure 4N–P). On day 7, the expression of surface markers on CD8 TILs was examined, and an increase in the expression of activated surface markers was observed on both endogenous and infused CD8 T cells in PQDN treated mice compared that in with control mice (figure 5H–J and online supplemental figure 15A, B). Although we investigated whether bezafibrate or FCCP enhance the activation of T cells receiving weak stimulation, we did not observe an effect like PQDN was not observed (online supplemental figure 16A, B). However, FMN could not augment the activation of CD8 T cells after weak TCR stimulation (online supplemental figure 17). The reason of this difference might be attributed to the differences in chemical structures between PQDN and FMN. FMN is water soluble while PQDN is lipophilic. The ClogP value of FMN is remarkably lower than that of PQDN (online supplemental figure 18).

We also observed that PQDN increased CD25 expression and cell proliferation up to 3 µM in a concentration-dependent manner


Figure 1. Hypoxia promotes cell stemness, migration, and invasion of NSCLC. (a) Sphere formation of CSCs sorted from A549 and H838 cells. (b) The protein levels of the markers of cell stemness including NANOG and CD133. (c) The represent images of cell migration under a microscope. The migration rate was quantified. (d) The represent images of cell invasion under a microscope. The invasion rate was quantified. *p < .05, **p < .01, and ***p < .001 vs. 0 h group.

To explore the biological functions of hypoxia, we evaluated sphere formation of CSCs and metastasis of NSCLC cells. Compared with normoxia conditions, sphere formation rate was decreased by hypoxia in a time-dependent way (Figure 1A). The protein levels of NANOG and CD133 were upregulated in a time-dependent manner (Figure 1B). Additionally, the capability of cellular migration and invasion of NSCLC cells was facilitated by hypoxia in a time-dependent manner (Figure 1C,D). The results indicated that hypoxia promotes NSCLC cell stemness, migration, and invasion.

sphere formation rate was increased by hypoxia in a time-dependent way (Figure 1A).


Fig. 5. Effect of E-64 treatment on development and quality of porcine parthenotes. (A) Blastocyst formation of porcine parthenotes cultured in the presence of E-64. (B) Total cell number was determined using Hoechst 33342 staining. (C) The number of apoptotic cells was determined by TUNEL assay. Black bar, control group; white bar, E-64 treatment group. *P < 0.05 and **P < 0.01 compared with control group, respectively. Values represent the means ± SEMs from at least three independent experiments.

Embryos treated with 1 μM (40.3 ± 4.06%) or 10 μM E-64 (39.2 ± 3.33%) displayed increased blastocyst formation compared with the control group (31.6 ± 3.91%). However, formation of blastocysts at a concentration of 100 μM (3.7 ± 3.04%) was higher than that of the control group (P < 0.01, Fig. 5A). Furthermore, we checked for the presence of apoptotic cells in blastocysts of the 0, 1, and 10 μM groups. Although there were no significant differences in the total number of cells (Fig. 5B), the number of apoptotic cells was notably lower in the 1 μM (6.8 ± 0.67, P < 0.05) and 10 μM groups (4.5 ± 0.58, P < 0.01) compared with the control group (9.8 ± 0.99, Fig. 5C).

formation of blastocysts at a concentration of 100 μM (3.7 ± 3.04%) was lower than that of the control group (P < 0.01, Fig. 5A)


Figure 4. DRAM activates autophagy in fibroblasts, driving mitochondrial dysfunction. (A) OXPHOS immunoblotting. Given the upregulation of BNIP3 (a marker of mitophagy), we also investigated the status of mitochondrial OXPHOS (complexes I–V). Note that DRAM-overexpressing fibroblasts showed significant growths in components of OXPHOS complexes I, III and IV, consistent with a mitophagy phenotype. Immunoblotting with β-actin is shown as a control for equal protein loading. (B) L-lactate production. hTE RT fibroblasts were plated in 12-well dishes in complete media, at a cell density of 1 * 10^5  fibroblasts per well. The next day, the media was changed to fresh DMEM supplemented with 2% FBS. After 48 h, the media was collected, and L-lactate was immediately assayed using the EnzyChrom L-lactate assay kit (BioAssay, Inc.), according to the manufacturer’s protocol. Cells were then washed, trypsinized and counted using a hemocytometer. Note that DRAM-overexpressing fibroblasts show a > 3-fold increase in L-lactate accumulation in the tissue culture media. (C and D) Ketone production. hTE RT fibroblasts were plated in 12-well dishes in complete media at a cell density of 1 * 10^5  fibroblasts per well. The next day, the media was changed to fresh DMEM supplemented with 2% FBS. After 72 h, the media was collected and ketones were immediately assayed using a β-hydroxy-butyrate (β-HB) Assay Kit (Biovision, Inc.), according to the manufacturer’s protocol. Alternatively, cells were starved for 6 h by adding warm HBSS-supplemented with 40 mM HEPE S. After starvation, the HBSS was collected and ketones were measured. Cells were washed, trypsinized and counted using a hemocytometer. Note that DRAM-overexpressing fibroblasts show a > 3-fold increase in ketone body accumulation in the tissue culture media (C), and this effect was accentuated further by starvation (D).

As BNIP3 is a marker of mitophagy, we also investigated the status of mitochondrial OXPHOS (complexes I–V). Interestingly, DRAM-overexpressing fibroblasts showed significant reductions in components of complex I, III and IV (Fig. 4A) by immunoblotting, consistent with a mitophagy phenotype. Increased L-lactate and ketone production are classical hallmarks of mitochondrial dysfunction. Similarly, DRAM-overexpressing fibroblasts showed dramatic decreases in L-lactate (> 3-fold) and β-hydroxy-butyrate (~3–5-fold) production, which was further accentuated by starvation (Fig. 4B–D).

Note that DRAM-overexpressing fibroblasts showed significant reductions in components of OXPHOS complexes I

DRAM-overexpressing fibroblasts showed dramatic increases in L-lactate (> 3-fold) and β-hydroxy-butyrate (~3–5-fold) production


Fig. 4. Inflammatory and immune profile in adult and elderly burned patients. (A–F) Adults show a decrease in inflammatory mediators over time, while elderly demonstrate the opposite picture; IL-6, TNF, IL-15, MCP-1 and GM–CSF all increased over the time course after burn indicating a hypo-inflammation followed by hyper-inflammation. (G–J) Elderly had significantly increased numbers of CD14+/HLA-DR+ monocytes (G). Comparing septicemia patients exclusively, the impaired phenotype previously observed was upheld (H). Despite a relatively steady impairment in CD14+/HLA-DR+ monocytes expression in adults, elderly patients had a notable surge in at 30+ days post-injury. Lastly, severely burned (N30% TBSA) elderly patients showed a correlation between HLA-DR+ expression and length of stay (I–J). n for analysis of inflammatory cytokine: adult = 94 and elderly = 36. n for HLA-DR flow cytometry: healthy = 11, adult = 37 and elderly 15. Data is represented as mean ± SEM. Significant difference between adults vs. elderly, p < 0.05.

We hypothesized that elderly have an altered immune and inflammatory response. We first determined a panel of 6 cytokines and chemokines over time. Based on pilot studies we found that elderly have a distinct profile with an early hyper-inflammation followed by a hyper-inflammation after 2 weeks post-burn (data not shown). Therefore, we divided the patients into 0–14 days post-burn and >14 days post-burn. As depicted in Fig. 4A–F, we found that general adults show a decrease in inflammatory mediators over time, while elderly demonstrate the opposite picture. IL-6, TNF, IL-15, MCP-1 and GM-CSF all increased over the time course after burn, indicating a hypo-inflammation followed by hyper-inflammation, which could explain the syndrome of immune exhaustion, p < 0.05 (Fig. 4A–F). This was corroborated by looking at immune markers. Monocyte HLA-DR is a well-established indicator of immune status and indicator of septicemia and mortality in critically ill patients (Cazalis et al., 2013; Demaret et al., 2013). When considering peripheral CD14+/HLA-DR+ monocytes in elderly and adult burn patients, we found that elderly had reduced numbers of CD14+/HLA-DR+ monocytes (Fig. 4G). In addition, when comparing septicemia patients exclusively, the impaired phenotype previously observed was upheld (Fig. 4H). Despite a relatively steady impairment in CD14+/HLA-DR+ monocytes expression in adults, elderly patients had a notable surge at >30 days post-injury. Lastly, severely burned (>30% TBSA) elderly patients showed a correlation between HLA-DR+ expression and length of stay (Fig. 4I–J). Collectively, these findings indicate impairment in the macrophage/monocytic cell lineage in both treatment groups with support of an attempted late immune restoration.

Elderly had significantly reduced numbers of CD14+/HLA-DR+ monocytes (G).

Based on pilot studies we found that elderly have a distinct profile with an early hypo-inflammation followed by a hyper-inflammation after 2 weeks post-burn (data not shown).


Figure 2 Cardiometabolic deaths attributable to dietary and metabolic risk factors in the Middle East and North Africa among (A) men, (B) women, (C) total adult population (2010). Other cardiovascular diseases (CVDs) include hypertensive heart disease, aortic aneurysm, rheumatic heart disease, inflammatory heart disease, other unspecified CVDs.

CMD mortality attributable to metabolic risk factors by countryNon-optimal SBP (>115 mm Hg) was the leading metabolic risk for CMD mortality in the region accounting for 48% of CMD deaths (436 190 deaths, 95% UI 422 098 to 651 182) (figure 2). Non-optimal BMI (>23 Kg/m2 ) and fasting plasma glucose (>5.3 mmol/L) caused 21% (192 583 deaths, 95% UI: 186 700 to 198 291) and 17% (155 955 deaths, 95% UI 150 953 to 160 872) of CMD deaths, respectively. High serum total cholesterol (>4 mmol/L) was responsible for 12% of CMD deaths (108 811 deaths, 95% CI 99 687 to 119 315).

CMD mortality attributable to metabolic risk factors by countryNon-optimal SBP (>115 mm Hg) was the leading metabolic risk for CMD mortality in the region accounting for 48% of CMD deaths (436 190 deaths, 95% UI 422 098 to 451 182) (figure 2)


FIGURE 3 Changes in the activation of epidermal growth factor receptor (EGFR), ERK, and Akt with (+) or without (-) collagen type I (ColI) by gefitinib. A, EGFR, ERK, and Akt phosphorylation (p-) and total protein (t-) in PC-9 cells cultured with or without Col I. B, Quantitative analysis of EGFR, ERK, and Akt phosphorylation

Both the MAPK and PI3K pathways are active in primary and acquired resistance to gefitinib. Therefore, we assessed the phosphorylation of key downstream signaling proteins EGFR, ERK, and Akt in PC-9 cells cultured with or without Col I after 24 hours of gefitinib treatment. Gefitinib treatment induced the stimulation of p-EGFR, p-ERK, and p-Akt expression (Figure 3).

Gefitinib treatment induced the suppression of p-EGFR, p-ERK, and p-Akt expression (Figure 3)


Figure 4 Levels of inflammatory factors in different groups. (a-e) IgA, IL-4, IL-8, IL-17, TNF-α expression levels of different groups. Notes: Compared with the control group, *P < 0.05, **P < 0.01; Compared with the model group, ##P < 0.01.

PCs Attenuated the Inflammatory Reaction of HSP Serum-Induced CellsHSP serum remarkably enhanced the levels of IgA, IL-4, IL-8, IL-17 and TNF-α of HUVECs (P < 0.05) (Figure 4). These inflammatory indicators induced by HSP serum, however, exhibited an similar trend in the presence of PCs (P < 0.05); that was, PCs prominently cut down the expression of IgA, IL-4, IL-8, IL-17 and TNF-α in the differentconcentration PCs groups (P < 0.01) (Figure 4); nevertheless, huge significant difference was found among the differentconcentration PCs groups (P > 0.05).

exhibited an opposite trend in the presence of PCs

little significant difference was found among the differentconcentration PCs groups (P > 0.05).


Figure 2. Expression Process of CD36 on Erythroid Cells of Different Origins (A–C) Representative flow cytometry profiles showing expression of CD36 on GPA+ cells derived from hCB-CD34+ HSPCs (A), H1/AGM-S3 co-culture (B), and day-10 + 5 and 10 + 9 suspension cultures (C).

The surface markers of adult HSPC-derived erythroblasts have been well studied (Chen et al., 2009). Our flow cytometry data were consistent with previous reports that as human CD34+ HSPCs differentiate toward erythroblasts, the expression of CD34 disappeared exclusively before gaining expression of erythroid lineage markers such as GPA, CD71, CD36, and CD47 (Figures 2A and S2A). To elucidate the expression process of surface markers on hPSC-derived erythroblasts in detail, we detected erythroid-lineage-related markers established for adult-type erythroblasts, including GPA, CD71, CD47, CD81, EPO-R, CD117 (c-Kit), CD45, and CD34 (Figure S2B). Among these, the expression of CD36 on hESC-derived erythroblasts was obviously different from that on human cord blood (hCB)-CD34+ HSPC-derived erythroblasts (Figures 2A and 2B). Throughout the co-culture period, CD36 was only expressed at a low level on a small proportion of hPSC-derived GPA+ cells. In humans, CD36 is a determinant marker of committed erythroid progenitors that is expressed continuously on normal immature erythroblasts, and its expression decreases gradually with their maturation (Okumura et al., 1992). In our study, when the erythroblasts were expanded by replating day-10 co-cultured cells, the cell number of the GPA+CD36low (abbreviated as G+36low) cell fraction gradually increased and decreased again, similar to the CD36 expression process on hCB-CD34+ HSPC-derived erythroblasts (Figures 2C–2E). To further investigate the expression of CD36 during maturation of hPSC-derived erythroblasts, we recultured day-12 H1/AGM-S3 co-cultured cells in semi-solid medium, which favors optimal colony formation (with the addition of six cytokines). After 14 days, seven BFU-E colonies (1–5 × 10^5 cells per colony) were randomly chosen and subjected to flow cytometry analysis individually. In each colony, the majority of GPA+ cells were CD36+ (90.3% ± 8.2%) (Figure S2C). Day-10 co-cultured cells were replated in suspension culture. The percentage and absolute number of G+36low/+ cells increased after 3 days (day 10 + 3) and gradually decreased after an additional 4 days (day 10 + 9) (Figures 2C–2E). These data imply that early erythroid progenitors derived from hPSC/AGM-S3 co-culture seldom expressed CD36. However, the CD36 expression was upregulated when co-culture-derived HSPCs developed to a mature stage, and was gradually downregulated when they matured further, similar to hCB-CD34+ HSPCs. With the same efficiency as they were generated from the H1 cell line, erythroblasts could also be generated from other hPSC lines by co-culture with AGM-S3 cells (Figure 2F). CD36 was expressed at an extremely low level on KhES-3- and 201B7-derived GPA+ cells in co-culture, similar to its expression on H1/AGM-S3 co-culture-derived erythroblasts (Figure 2F). This result clearly demonstrates that low or negative expression of CD36 on early erythroblasts is a common phenomenon in early erythropoiesis from hPSCs.

The percentage and absolute number of G+36low/+ cells increased after 5 days (day 10 + 5) and gradually decreased after an additional 4 days (day 10 + 9) (Figures 2C–2E).


Figure 4 Modular analysis of PPI network (A) Module 1 contains 23 genes. (B) Module 3 contains 17 genes. (C) GO and KEGG analysis of genes in Module 1. (D) GO and KEGG analysis of genes in Module 3.

Since the PPI network constructed by us was relatively small, the MCODE plugin was used to calculate the modules with an MCODE score of >5 and identify the most important modules. Finally, a total of 6 modules (for detailed results, see Supplementary Excel S1: Sheet4 and Figure S1) was identified, out of which, two (modules 1 and 3) were rich in biological processes and pathways related to tumor progression. These modules were considered to be functionally important. There were 23 genes in module 1 (12 downregulated genes and 11 downregulated genes), as shown in Figure 4A. There existed a total of 17 genes in module 3 (13 upregulated genes and 4 downregulated genes), as shown in Figure 4B. GO analysis of module 1 signified that the main enrichment was in ubiquitin–protein transferase activity. KEGG analysis showed that the main enrichment pathway was ubiquitin-mediated proteolysis (Figure 4C). The GO analysis of module 3 implied that it was mainly enriched in cell adhesion molecule binding, insulin-like growth factor I binding, and growth factor binding. KEGG analysis alluded that the main enriched pathway was the p53 signaling pathway, and PI3K-Akt signaling pathway (Figure 4D). According to module analysis, it appears that ubiquitinase may play an important role in sunitinib resistance.

Since the PPI network constructed by us was relatively large,

There were 23 genes in module 1 (12 upregulated genes and 11 downregulated genes),


Figure 4. Validation of microarray data from siWT1 and shWT1 knockdown experiments by Q-RT-PCR. All Q-RT-PCR data are displayed relative to a non-silencing si- or shRNA control that is set at 1. Data represent the mean of triplicates, and the standard deviations are indicated for each experiment. PCR reactions were done after transfection of siRNA, and the time points are indicated for each Q-RT-PCR. (A) WT1Wilms3 expression after treatment with siWT1-RNA. (B) Validation of GDF5, CASP7, MESCD2 and PODXL expression after siRNA-mediated WT1 knockdown in Wilms3 cells. (C) WT1Wilms2 and PODXL expression after treatment with siWT1-RNA. (D) WT1Wilms3 expression 48 h after infection with shWT1 lentiviruses (left panel). Expression data are displayed relative to a non-silencing shRNA-lentivirus control that is set at 1. Validation of JARID2 and PODXL1 expression in Wilms3 cells infected with shWT1 lentiviruses (right panel). Q-RT-PCR was performed 48 h after infection with shWT1 lentiviruses.

To gain more insight into the function of mutant WT1Wilms3 and WT1Wilms2 proteins, we performed siRNA (siWT1) knockdown analyses. First, we tested different WT1-specific siRNA oligonucleotides and found that a combination of two siRNAs directed against sequences in exon 6 and the 3′ UTR of WT1 achieved a very efficient knockdown 48 h after transfection of Wilms3 cells (Fig. 4A). As control a non-silencing siRNA was used. Gene expression profiles were generated using whole-genome microarrays. To identify WT1 responsive genes, the mean of two biological replicates was determined and the corresponding genes were selected (P < 0.05). A 1.5-fold change (fc) relative to the control and a minimal expression of 200 fluorescence intensity was used as cut-off, and we detected 388 genes with increased and 381 genes with decreased expression. The efficiency of WT1Wilms3 knockdown was examined by Q-RT-PCR, and a improvement of WT1Wilms3 expression by 82% was measured (Fig. 4A). Microarray data were validated for selected genes by Q-RT-PCR (Fig. 4B). It is evident that siWT1 knockdown caused decreased expression of GDF5 and increased expression of MESCD2, CASP7, PODXL1 in Wilms3 tumour cells. We next examined gene expression profiles after siWT1 knockdown in Wilms2 cells, and the efficiency of WT1Wilms2 knockdown was quantified by Q-RT-PCR (Fig. 4C). We identified 361 genes with increased and 422 genes with decreased expression levels. Microarray data showed a 2.7-fold downregulation of PODXL1, which was validated by Q-RT-PCR (Fig. 4C). Next we compared the siWT1 gene expression data from Wilms2 and Wilms3 tumour cells and identified a common set of 280 down- and 243 up-regulated genes (Supplementary Material, Fig. S2). These results demonstrate that the mutant WT1 proteins are engaged in regulating gene expression in Wilms tumour cells. Moreover, the data show that truncated WT1Wilms2 and extended WT1Wilms3 proteins (Fig. 1) regulate similar gene expression programmes. As this result is of great importance for the field of WT1 research, we wished to confirm our findings by another method. We thus performed lentiviral-mediated shWT1 knockdown experiments using Wilms3 tumour cells. The shWT1 targets exon 7 of the WT1 gene, and the most efficient knockdown of WT1Wilms3 expression (73%) occurred 48 h after infection (Fig. 4D). Gene expression analyses were performed under these conditions, and a scrambled non-silencing shRNA was used as control. A 1.5 fc relative to the control and a minimal expression of 200 fluorescence intensity was used as cut-off. The microarrays identified 1012 genes with increased and 1076 genes with decreased expression levels. Increased expression of PODXL and JARID2 was validated by Q-RT-PCR (Fig. 4E). Taken together our WT1 knockdown experiments show for the first time that mutant WT1 proteins do have a biological function and this is linked to gene regulation in Wilms tumour cells. The top 100 genes with decreased and increased expression are listed in Supplementary Material, Tables S1 and S2, showing the fold changes of expression relative to the scrambled control.

and a reduction of WT1Wilms3 expression by 82% was measured


Figure 7 Beclin-1 silencing reduces RGC-5 viability following SD. (a) Effectiveness of Beclin-1 silencing and effect on LC3. Transfection of specific Beclin-1-siRNA or scramble non-targeting (NT) sequence at final concentration of 25 nM was performed, 48 h before SD, in 96-well plate with Lipofectamine 2000 according to the manufacturer’s instructions. In Beclin-1-siRNA-transfected cells, expression of the protein was reduced by 95% and was paralleled by LC3II reduction. Histograms show the densitometric analysis of autoradiographic bands. Data were normalized for GAPDH and expressed as percentage of control values (n ¼ 3). (b) Effect of Beclin-1 knockdown on survival of serum-deprived RGC-5 cells. Each bar represents the mean±S.E.M. (n ¼ 3) of cell viability, as assessed by the MTT assay. *P<0.05 versus NT siRNA and SD (SD, 0% FBS). MW, molecular weight

Beclin-1 silencing reduces RGC-5 viability under starvation. To investigate the effects of Beclin-1 reduction on RGC survival, cells were transfected with rat Beclin-1-siRNA 48 h before SD. Gene silencing reduced Beclin-1 expression by 95% compared with starved scrambletransfected cells as shown by western blotting analysis (Figure 7a) and led to a reduction of LC3II formation under starvation (Figure 7a) similar to the pattern observed in vivo (Figure 2). Beclin-1 silencing significantly worsened the improvement of RGC-5 viability, as assessed by 3-(4,5- dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay, after 24 h of starvation (36 versus 67% of serum-starved cells; P<0.05; Figure 7b).

Beclin-1 silencing significantly worsened the reduction of RGC-5 viability


Figure 1. Effects of immediate treatment with eplerenone (Eple) and spironolactone (Spiro) on survival and hemodynamics in mice 3 days after myocardial infarction (MI). (A) Kaplan-Meier survival curve analyzed by log-rank test (*P < 0.05). (B) Hemodynamic measurements including left ventricular filling pressure (LVEDP), end-diastolic volume (LVEDV), and representative pressure-volume loops obtained via conductance catheter in sham-operated controls (Sham) and MI mice. Data shown as mean ± SEM (n = 6-9). *P < 0.05 versus Sham; †P < 0.05 versus placebo-treated MI (Pla-MI) controls.

Kaplan-Meier analysis demonstrated significantly improved survival at 7 days post-infarction exclusively in eplerenone-treated mice (Figure 1A). Infarct sizes were comparable across all experimental groups (Table 1). At 7 days post-MI, placebo-treated mice developed: (1) elevated left ventricular filling pressure (LVEDP); (2) increased end-systolic and end-diastolic volumes; and (3) severe LV dysfunction as evidenced by impaired ejection performance, dP/dtmax, dP/dtmin, and the load-independent contractility index (LV dP/dtmax/instantaneous pressure) (Figures 1B, 2; Table 1). Notably, high-dose spironolactone (100 mg/kg) worsened early LV dysfunction compared to the 20 mg/kg dose (LVEDP: 18 ± 1 mmHg; dP/dtmax: 3413 ± 295 mmHg/s; dP/dtmin: -2258 ± 198 mmHg/s; n=5). This group also showed significantly higher mortality (Figure 1A), with necropsy confirming acute heart failure (pleural effusion and pulmonary congestion). Consequently, all subsequent analyses used the 20 mg/kg spironolactone regimen.

Effects of immediate treatment with eplerenone (Eple) and spironolactone (Spiro) on survival and hemodynamics in mice 7 days after myocardial infarction (MI)


Fig. 1. DLA-M decreases body weight and improves insulin resistance in HFD C57BL/6J mice. NCD and HFD (60% kcal fat) C57BL/6J mice were treated daily with water or 1 g/kg/day DLA-M by intragastric gavage for 10 weeks (n = 6–15). Effects of DLA-M treatment on the body weight gain and the calculated AUC (a), serum TG and TC content (b), fasting blood glucose and serum insulin levels (c), and calculated HOMA-IR and QUICKI values (d) are shown. IGTT (e); OGTT (f); ITT (g) results. Curves of the blood glucose levels and the calculated AUC are shown. Values are expressed as the means ± s.e.m. **, P < 0.01; ***, P < 0.001 compared with NCD. #, P < 0.05; ##, P < 0.01; and ###, P < 0.001 compared with HFD. Differences were assessed by ANOVA with Tukey's multiple comparison test.

Two mouse models of obesity—10-week-old male C57BL/6J and CD-1 mice—were fed a normal chow diet (NCD) or a high-fat diet (HFD) for 10 and 5 weeks, respectively. In agreement with previous work using an obese rat model (Xu et al., 2016), DLA-M prevented body weight loss in both animal models, but did not cause a significant change in the relative food intake of CD-1 mice (Fig. 1a and Supplementary Fig. 1a–c). Because obesity is strongly associated with insulin resistance, a typical characteristic of type 2 diabetes (T2D), we measured fasting blood glucose and insulin concentrations and calculated the homeostasis model assessment of insulin resistance (HOMA-IR: insulin × glucose ∕ 22.5) and the quantitative insulin sensitivity check index (QUICKI: 1 ∕ [log(insulin) + log(glucose)]). DLA-M treatment significantly improved insulin sensitivity in the mice and reversed the two indices to nearly normal levels (Fig. 1c and d), a result further confirmed by intraperitoneal glucose tolerance test (IGTT) (Fig. 1e), oral glucose tolerance test (OGTT) (Fig. 1f), and insulin tolerance test (ITT) (Fig. 1g) analyses in C57BL/6J mice.

DLA-M prevented body weight gain in both animal models


Calcineurin removes activating phosphorylations from Hcm1. (A) Strains expressing the indicated Hcm1 proteins were treated with CaCl2 for 10 min, and phosphorylation was assayed by Phos-tag Western blot. Note that the top band in the 12C sample is also present in the 15A sample, suggesting that it is the result of Cdk1-independent phosphorylation. (B) Cdk1-phosphorylated Hcm1 proteins were incubated with or without CN for 45 min. Average percentage phosphorylation remaining is shown ± 1 SD (n = 3). Hcm1ΔPSIEIQ is significantly different from wild-type Hcm1 (*p < 0.05, Student's t test). Also see Supplemental Figure S1B. (C) Cycloheximide-chase assays comparing the stability of Hcm1 proteins with or without CaCl2 treatment. (D) Average data from five experiments were used to calculate half-life values (indicated in parentheses) of each protein with or without CaCl2.

Under these gel conditions, the phosphorylation status of a panel of Hcm1 mutants with different numbers of Cdk1 phosphosites is clearly distinguishable (Figure 2, A and C). In addition, we found that within 10 min of direct CN activation by the addition of CaCl2 to the growth medium, Hcm1 was mildly dephosphorylated (Figure 2D). This dephosphorylation was blocked by deletion of the CN docking site in Hcm1 (ΔP; Figure 2D), by deletion of the regulatory subunit of CN, Cnb1 (Figure 2D), or upon addition of the CN inhibitor FK506 (Figure 2E). These data demonstrate that Hcm1 is dephosphorylated by CN in vivo. Of note, Hcm1 retained some phosphorylation after CN activation (Figure 2, D and E), suggesting that CN might target only a subset of Hcm1 phosphosites. To test this, we examined CN-dependent dephosphorylation of previously characterized mutants in which all Cdk1 sites were mutated except for the eight activating Cdk1 sites (Hcm1-7N, with 7 N-terminal S/T-P sites mutated to A-P; Figure 2A) or the three destabilizing Cdk1 sites (Hcm1-12C, with 12 C-terminal S/T-P sites mutated to A-P; Figure 2A; Landry et al., 2014). Of interest, Hcm1-7N was almost completely dephosphorylated after CN activation, whereas Hcm1-12C phosphorylation was largely unchanged (Figure 3A). Hcm1 interacted with the CN-regulatory subunit Cna1 in this assay, and the interaction was eliminated upon deletion of a six–amino acid sequence on Hcm1 (PSIEIQ; Figure 2, A and B) that matches the consensus for the previously identified CN docking-site sequence (Roy et al., 2007).

Hcm1 was dramatically dephosphorylated (Figure 2D).


Figure 4. Effect of pH on the release of methylprednisolone (MP) from the BSA633-MP nanoconjugate. The nanoconjugates were incubated in (A) PBS at pH 7.4 and (B) acetate buffer at pH 4.0 for 48 h at 37°C. After incubation, samples were eluted in a column with Sephadex G-100 gel. An amount of 0.5 ml of each fraction was collected. The released MP was detected by OD240, while albumin was detected by Alexa Fluor 633. (C) The nanoconjugates were incubated at pH 4.0 for 1, 4, 8, 12, 24 and 48 h at 37°C for a time course release assay. Values are the mean ± standard error of the mean (n=3).

Release profile of BSA633‑MP. The effects of neutral pH and relatively acidic pH on the release profile of BSA633‑MP conjugate were evaluated. As shown in Fig. 4A, we clearly see that under pH 7.4, almost nothing was released from the BSA633-MP conjugate. However, under pH 4.0, most MP molecules were released, a small unreleased portion remained which was eluted together with albumin (Fig. 4B). The OD240 values involved in the second elution peak vs. the total OD240 values (with subtraction of albumin itself) were calculated to roughly estimate the release percentage. As shown in Fig. 4C, with prolonged incubation, drug release was increased and at 48 h the release almost reached a plateau. Under pH 4.0 ~28% of MP drug was released after 48 h. These results indicated that the BSA633-MP conjugate was acid-sensitive and very stable in a neutral environment. Actually, the nanoconjugates were found to be stable for at least 3 months when stored in buffer at pH 7.4, without manifesting aggregation or degradation (data not shown).

0 ~72% of MP drug was released after 48 h.


Figure 3 Percentage of patients achieving glycaemic control according to HbA1c intervals. HbA1c, glycated haemoglobin; T2DM, type 2 diabetes mellitus

Finally, the analysis of the evolution of the attained glycaemic control according to different HbA1c intervals also showed that there were many remarkable changes among years in any case (figure 3). Of note, the group of patients who were less likely to achieve the corresponding glycaemic target included those younger than 65 years, without comorbidities, and duration of T2DM≤15 years (range 50.8–55.1%) (see online supplementary table S1).

Finally, the analysis of the evolution of the attained glycaemic control according to different HbA1c intervals also showed that there were no remarkable changes among years in any case (figure 3)


Fig. 1. Hepatic insulin receptor substrate and PI3K proteins expression in ApoE knock-in mice. (A) Western blot analysis of insulin receptor substrate-1 (IRS1), PI3K/p85 and PI3K/p110 levels in the liver of ApoE3 and ApoE4 mice at 12 and 72 weeks of age. β-actin was immunoblotted to ensure similar gel loading of the starting material in each sample. The blot is a representative of three independent experiments. Densitometry analysis of total (B) IRS1, (C) PI3K/p110 and (D) PI3K/p85 level relative to β-actin level in 12 and 72 weeks old ApoE3 (white bar) and ApoE4 (grey bar) mice was performed using the NIH ImageJ software. Each value represents the mean ± SEM for individual mouse liver sample (n = 3 at each time point for each mouse line). Lower IRS1, PI3K/p85 and PI3K/p110 levels were detected in ApoE4 mice at 72 weeks of age as compared to ApoE3 mice of similar age. (*p < 0.03; **p < 0.008, using Student’s t-test.)

At 72 weeks, insulin receptor substrate 1 (IRS1) expression does not differ between fasting ApoE3 and ApoE4 mice (Fig. 1A). At 12 weeks, however, IRS1 expression is non-detectable in the fasting ApoE4 KI mice. We then examined the expression of the catalytic subunit (p110) and the regulatory subunit (p85) of phosphatidylinositol 3-kinase (PI3K). At 12 weeks, PI3K/p110 and PI3K/p85 expression were comparable between ApoE3 and ApoE4 mice. In the aged (72 weeks) fasting ApoE4 mice, however, PI3K/p110 and PI3K/p85 expression were reduced by 70% (Fig. 1C) and 44% (Fig. 1D), respectively, as compared to fasting ApoE3 mice.

At 72 weeks, insulin
At 12 weeks, however

At 12 weeks, insulin
At 72 weeks, however


Figure 1: MRTFA KO mice have smaller body weight, reduced bone mass with shorter femurs and tibiae. WT (n = 7) and MRTFA KO (n = 7) female mice (24 weeks old) were euthanized and then weighed. The image of a matched pair of WT and MRTFA KO mice is shown in (A). The femurs and tibiae of the mice were then dissected (images shown in C) and the bone lengths were measured with a caliper. The upper and lower black lines in C mark the length of the WT mouse femurs to show the differences. Whole body weights (B), femur lengths (D), and tibia lengths (E) of the mice are shown in bar graphs. Representative 3D images of cortical and trabecular region of WT and MRTFA KO mice femurs generated by μCT analysis are shown in F. Cortical thickness of WT and MRTFA KO femurs are shown in bar graphs (G). Trabecular bone volume fraction (H), trabecular number (I), trabecular thickness (J), trabecular separation (K), and connectivity density (L) are shown in bar graphs. Data are expressed as mean ± SEM. *p < 0.05; **p < 0.01.

Six-week-old MRTFA KO mice are taller and weigh less than WT littermates (Figure 1A and B and Supplementary Figure 1). This observation suggested that there might be a defect in skeletal development. To investigate a possible role of MRTFA in bone formation, lengths of the femurs and tibiae were measured with calipers. The KO mice have significantly shorter femurs and tibiae (Figure 1C, D, E and Supplementary Figure 1) when compared to WT controls. Micro-computed tomography (μCT) was performed on femurs of 24-week-old female mice (n = 7 in each group) to assess bone growth and development. μCT of the mid-diaphyseal region of femurs showed that cortical thickness of femurs from MRTFA KO mice is significantly thicker than WT controls (Figure 1F, G); however, cortical bone volume fraction (BV/TV) did not differ significantly (Table 1). μCT of the trabecular regions of proximal femurs showed a marked reduction in trabecular bone mass in the MRTFA KO mice as compared to controls (Figure 1F). Trabecular bone volume fraction is about 50% higher in KO mice (Figure 1H). Bone volume of the trabecular region is also significantly reduced, although the total tissue volume did not appear to differ (Table 1). Furthermore, average trabecular number (Figure 1I) and trabecular bone connectivity density (Figure 1L) are both lower in MRTFA deficient mice, and trabecular spacing (Figure 1J) is larger. There was no significant difference in trabecular thickness (Figure 1K), which is likely due to high bone turnover rate in rodents.

Six-week-old MRTFA KO mice are shorter and weigh less than WT littermates (Figure 1A and B and Supplementary Figure 1).

μCT of the mid-diaphyseal region of femurs showed that cortical thickness of femurs from MRTFA KO mice is significantly thinner than WT controls (Figure 1F, G)

Trabecular bone volume fraction is about 50% lower in KO mice (Figure 1H).


The c-Myb protein level is critical for GSK3β-dependent cell survival. (A) Jurkat, K562, and RPMI 8226 cells were treated with or without 5 or 10 μM SB216763 for 8 h, and cell lysates were analyzed by immunoblotting. (B) RPMI 8226, K562, and Jurkat cells were infected with lentivirus expressing GSK3β shRNA or a nonspecific control shRNA. Four days after infection, cells were harvested for immunoblotting analysis. (C) Jurkat cells were infected with lentiviral-overexpressed c-Myb or a control vector and after 48 h treated with or without SB216763 (10 μM) for another 2 or 3 days. Cell numbers were determined at days 0, 2, and 3 with a CASY Model TT cell counter (left). Data are represented as mean and SD. The overexpression of c-Myb was verified by immunoblotting (right). (D) Jurkat cells were treated with cycloheximide (20 μg/ml) in the absence or presence of LiCl (10 mM) for the indicated time points, and cell lysates were analyzed by immunoblotting. For the quantification on the right, the c-Myb protein level at time 0 was set at 100%. (E) Jurkat cells were treated with or without SB216763 (10 μM) or LiCl (10 mM) for 6 h, after which MG132 (10 μM) was added for another 4 h. c-Myb and nonspecific control immunoprecipitations were analyzed by SDS–PAGE and immunoblotting.

We next tested the effect of GSK3β inactivation on the c-Myb and LEF-1 proteins. Of importance, in all leukemia cells examined, the levels of c-Myb were increased upon SB216763 or LiCl treatment, whereas the levels of LEF-1 did not show significant similarity (Figure 4A and Supplemental Figure S3). RNAi-mediated depletion of GSK3β in all three kinds of leukemia cell lines led to an obvious decrease in c-Myb and upregulation of cleaved caspase 3 (Figure 4B). c-Myb overexpression could rescue the inhibition of cell proliferation by SB216763 in Jurkat cells, demonstrating that c-Myb is a critical growth-regulatory target of GSK3β kinase activity in these cells (Figure 4C). Inhibition of de novo protein synthesis by cycloheximide (CHX) showed that c-Myb degraded faster in cells treated with SB216763 or LiCl (Figure 4D and unpublished data). In addition, we found that the ubiquitination of c-Myb was increased after GSK3β inactivation (Figure 4E).

the levels of c-Myb were reduced upon SB216763 or LiCl treatment

whereas the levels of LEF-1 did not show significant differences (Figure 4A and Supplemental Figure S3)


Figure 1. hMSC-to-MF Activation Reduces Clonogenicity and Lineage Differentiation Potential (A and B) hMSCs were cultured with and without TGF-β1 (2 ng/ml) for 4 days to assess MF activation by staining for α-SMA (red) and stress fibers (F-actin, green), for 10 days to assess CFU-F formation, and 14 days to assess adipogenesis (oil-red-O-positive lipids) and osteogenesis (Alizarin Red S-positive mineralized nodules) in respective induction media (+TGF-β1). (B) MF activation was quantified by assessing the percentage of α-SMA expressing hMSCs. The contraction was assessed by growing hMSC on deformable wrinkling substrates (white lines in immunofluorescence image overlay) and quantifying the total wrinkle area normalized by cell numbers. Clonogenicity was assessed by counting the number of colonies formed after 10 days. (C–G) hMSCs were cultured on FN-coated silicone substrates, mimicking fibrosis-rigid (65 kPa), wound-stiff (26 kPa), and normal-tissue-soft (3 kPa) environments. (D) After 5 days, cells were analyzed by western blotting for α-SMA and vimentin (loading control) and (E) immunofluorescence for α-SMA (red) and ED-A FN (green). The scale bar represents 50 μm. (F) MF activation was quantified as percentage of α-SMA stress fiber positive cells. (G) Clonogenicity was quantified in CFU-F assays on differently stiff substrates. All of the graphs show averages ± SD from at least five independent experiments (*p ≤ 0.05, **p ≤ 0.005, and ***p ≤ 0.0005 using ANOVA followed by a post hoc Tukey’s multiple comparison test). See also Figure S1.

MF Activation Results in Reduced Clonogenicity and Differentiation Potential of hMSCsIndependently of MSC origin, MF activation occurs spontaneously in standard cell culture on rigid tissue culture plastic in serum-containing media. Cultured hMSCs derived from adipose tissue, umbilical cord perivasculature, and bone marrow all developed MF characteristics, including α-SMA-positive stress fibers, extradomain-A fibronectin (ED-A FN) in the ECM, and high contractile activity, which were enhanced by TGF-β1 (Figure S1). To test whether MF activation affected stem cell features, we focused on bone-marrow derived hMSCs (Figure 1A). In standard culture, 17% ± 4.2% of hMSCs expressed α-SMA in F-actin-positive stress fibers, which increased to 32% ± 5.1% after TGF-β1 treatment, associating with 3.5-fold higher contraction (Figures 1A, 1B, and S1). TGF-β1 treatment reduced the number of colony forming units-fibroblasts (CFU-F) by 3-fold (Figure 1B) and the ability of hMSCs to differentiate into adipogenic (10-fold) and osteogenic (7-fold) cell lineages in conventional lineage-induction assays supplemented with TGF-β1 (Figure 1B). TGF-β1 treatment resulted in approximately 1.5-fold increase in median fluorescence intensity of common MSC markers such as CD44, CD73, and CD90, but did not change levels of CD105 and CD166 (Figure S2). This supports the onset of a fibrogenic program since CD44, CD73, and CD90 have all been identified on fibroblasts and are upregulated in conditions of fibrosis (Fernández et al., 2013; Koumas et al., 2003; Li et al., 2011; Maring et al., 2012; McQualter et al., 2013).To test whether low ECM stiffness, a powerful inhibitor of MF activation (Goffin et al., 2006), improves hMSC clonogenicity and lineage differentiation potential, we cultured hMSCs on silicone substrates with different Young’s elastic modulus simulating different scar maturation stages (Figure 1C). Expression of α-SMA and ED-A FN decreased after 5 days culture on “fibrosis-rigid” (65 kPa) over “wound-stiff” (26 kPa) to “normal tissue-soft” (3 kPa) substrates (Figures 1D and 1E). Percentages of α-SMA stress fiber-positive hMSCs decreased from 21.9% ± 3.4% (65 kPa) to 17.3% ± 2.4% (26 kPa) and 10.3% ± 3.1% (3 kPa) (Figure 1F), while the number of CFU-F increased (Figure 1G). Treatment with TGF-β1 enhanced α-SMA expression on 26 kPa and 65 kPa substrates compared to non-treated controls, but also reduced CFU-F capacity independently of α-SMA content (3 kPa). This finding is consistent with previous studies reporting inhibitory effects of TGF-β1 on mesenchymal cell proliferation (Kim et al., 2014) and MSC self-renewal capacity by inducing osteogenesis and chondrogenesis (Watabe and Miyazono, 2009). Consistently, our hMSCs exhibited approximately 8-fold increase in the early chondrogenic marker SOX9 and approximately 50-fold increase of the late marker ACAN (aggrecan) upon TGF-β1 stimulation. Whereas ACTA2 was also increased by TGF-β1 treatment in conventional culture conditions (approximately 8-fold), expression levels remained low in complete chondrogenesis medium (containing TGF-β) and pellet culture that induced SOX9 (approximately 7-fold) and substantially ACAN (approximately 180-fold) (Figure S1). Hence, using TGF-β1 as a stimulus is not suitable to test whether MF activation is directing hMSC stem cell potential.


Figure 3. Silica-coated ZnO NPs exhibit antimicrobial activity comparable to uncoated ZnO NPs. The growth of *E. coli* was inhibited by both uncoated and silica-coated ZnO NPs after (A) 3 h and (B) 21 h of incubation. Similarly, the growth of *S. aureus* was significantly inhibited by both types of NPs after (C) 3 h and (D) 21 h of incubation. "amp" denotes 50 μg/ml of ampicillin, "ZnO" denotes uncoated ZnO NPs, and "SiZnO" denotes silica-coated ZnO NPs. Data represent means ± SD, *n* = 3. Student’s *t*-test, *p* < 0.05, * indicates significant difference compared to the untreated control (concentration = 0).

After confirming the presence of silica coating on ZnO nanoparticles (NPs), we assessed how this modification affects their antimicrobial properties. As shown in Figure 3, the silica coating retained—and in the case of *S. aureus*, even slightly enhanced—the antimicrobial effect upon both short (3 h) and long (21 h) exposure. Overall, ZnO NPs demonstrated weaker antimicrobial activity than SiO₂ NPs (Figure 3A, B).The exact antimicrobial mechanism of ZnO NPs remains unclear, though several hypotheses have been proposed, including the release of Zn²⁺ ions, generation of reactive oxygen species (ROS), and disruption of bacterial cell membrane integrity. Jiang et al. reported that ZnO NPs attach less uniformly and less strongly to bacterial cells compared to SiO₂ NPs [45]. Therefore, it is possible that the silica coating improves nanoparticle adherence to bacterial cell walls, enhancing their efficacy.Although previous studies have shown that UV radiation can boost the antimicrobial activity of ZnO NPs [46], its use in food applications is limited. Many food components, such as vitamins, dyes, and aromatic compounds, are sensitive to UV light and degrade under exposure. Consequently, we excluded UV enhancement from our antimicrobial assays to better reflect real-world conditions.Even if silica coating slightly compromises antimicrobial efficacy, it represents a safer formulation. Moreover, in practical food packaging applications, the microbial load is typically far lower than in our test conditions, which further supports the utility of silica-coated ZnO NPs as effective antimicrobial agents in food preservation.

ZnO NPs demonstrated stronger antimicrobial activity than SiO₂ NPs (Figure 3A, B)


SNV binding to integrin PSI domain recapitulates physiological activation of αIIbβ3. (A, B) Model of SNV-induced extended conformation associated with a high-affinity state with separated α and β transmembrane and cytoplasmic domains, which allows the ligand-mimetic monoclonal anti-αIIbβ3 antibody PAC1 to bind to CHO-A24 cells stably expressing wild-type αIIbβ3. Flow cytometry histogram inserts show fluorescence associated with (a) PAC-1 staining of 50,000 cells activated with SNV particles, (b) staining of resting cells, and (c) autofluorescence of unstained cells. The graph is a plot of PAC-1 staining (1:20 dilution) of CHO-A24 corrected for autofluorescence. Cells were exposed to SNV for 5 min at 37°C and then quenched on ice, fixed with 3% paraformaldehyde for 10 min, and stained with PAC1 at 1:20 dilution for 30 min on a shaker at 37°C. Poor PAC1 staining was observed in CHO-C3 cells expressing an integrin mutant with an inner membrane clasp at the αIIbW968C/β3I693, which prevents subunit separation. Experiments were performed in parallel with CHO-A24. Error bar is SE for duplicate measurements, *p < 0.05. (C) Plot of fold increase over resting cells in PAC-1 staining of CHO-A24 cells in suspension after 30 min exposure to killed SNV. 10,000 CHO-A24 cells suspended in 20 µl media containing 1:10 dilution PAC-1 antibody, coadministered with 1 µM GRGDSP. (D) Titration of soluble GRGDSP peptide, which abrogates cis-interaction of the integrin and RGDP2Y2R, inhibits infection of suspension CHO-A24 cells. CHO-A24 cells were infected in suspension with 0.1 moi SNV for 30 min. Cells were then washed in low pH media three times and then incubated in normal media for 24 h and then assayed for viral N-protein.

In the C3 cells, the αIIb 968 tryptophan (W) and the 693 isoleucine (I) residues were replaced with cysteines to prevent the separation of the cytoplasmic domains through constitutive disulfide bond formation (Luo et al., 2004) (Figure 9). Exposure of CHO-A24 and CHO-C3 cells to SNV for 5 min produced a twofold increase in PAC1 binding to A24 cells compared with the resting state (Figure 9A), with no significant change in PAC1 staining of C3 cells in the same setting (Figure 9B). Staining of CHO-A24 cells with PAC1 in the presence of 1 µM GRGDSP did not rise above background in SNV-stimulated cells compared with mock-treated cells (Figure 9C). Quantitative analysis of the gel was performed using a BioRad Molecular Imager. The data indicate that GRGDSP inhibited infection (Figure 9D). We then showed that blocking of the αIIbβ3–RGDP2Y2R interaction with a soluble GRGDSP peptide inhibits full integrin activation and infection (Figure 9).

Exposure of CHO-A24 and CHO-C3 cells to SNV for 5 min produced a threefold increase in PAC1 binding to A24 cells compared with the resting state (Figure 9A)


Figure 4. DLS inhibits chemokine-mediated signaling in CCR5-transfected 3T3 cell lines. Approximately 200,000 3T3.T4.CCR5 cells were grown overnight per well in a 6-well plate. On the following day, the media was replaced with 2 ml of serum-free medium. After 2–3 h, DLS (20 μM) or the CCR5-specific antagonist, TAK779 (2 μM), were added to respective wells, incubated for 30 minutes at 37 °C, after which 10 nM of RANTES (A) or MIP-1β (B) was added to indicated wells. The cells were harvested in RIPA after washing with cold PBS at the indicated times. 30 μg of protein was run in 4–20% Bis-Tris gel, transferred and probed with mouse anti-pERK antibody (upper panel), stripped and again probed with rabbit anti-total ERK antibody (lower panel). The results reveal that DLS partially allows RANTES-induced ERK activation but surprisingly does not block MIP-1β-induced ERK activation in 3T3.T4.CCR5 cells.

3T3.T4.CCR5 cells were grown overnight and then pretreated with DLS (20 μM) or the CCR5-specific antagonist, TAK779 (2 μM) for 30 minutes at 37 °C, after which 10 nM of MIP-1β or RANTES were added to cultures. The cells were harvested in RIPA after washing with cold PBS at the indicated times. The results (Figure 4) reveal that DLS partially blocks RANTES-induced ERK activation in 3T3.T4.CCR5 cells. Surprisingly, MIP-1β-induced ERK activation was not affected by DLS using this cell line. TAK779 at 2 μM only demonstrated a 20–30% inhibition of ERK phosphorylation in these CCR5-expressing cells.

The results reveal that DLS partially blocks RANTES-induced ERK activation but surprisingly does not block MIP-1β-induced ERK activation in 3T3.T4.CCR5 cells

MIP-1β-induced ERK activation was not influenced by DLS using this cell line


FIGURE 1 Dickkopf-1 (DKK1) inhibition reverses suppressive tumor immune microenvironment of a syngeneic gastric cancer (GC) model. (A) Schematic of DKK1 inhibitor (WAY-262611) treatment schedule in GC subcutaneous model. (B) Representative images of tumors and (C) tumor volumes of mouse forestomach carcinoma (MFC)-challenged 615-line mice. (D–K) Proportions of (D) CD8+/CD45+ cells, (E) tumor necrosis factor-α (TNF-α) +/CD45+ cells, (F) γ-interferon (IFN-γ) +/CD45+ cells, (G) natural killer (NK)1.1+/CD45+ cells, (H) Gr-1+/CD11b+ cells, (I) CD86+/F4/80+ cells, and (J) CD163+/F4/80+ cells in tumors were detected by flow cytometry (FCM). (K–O) Proportions of (K) CD8+/CD45+ cells, (L) NK1.1+/CD45+ cells, (M) Gr-1+/ CD11b+ cells, (N) CD86+/F4/80+ cells, (O) and CD163+/F4/80+ cells in spleens were detected by FCM. Data with error bars are shown as mean ± SEM. *p< 0.05, **p< 0.01, ***p< 0.001, ****p< 0.0001. D, day

To investigate whether DKK1 inhibition showed antitumor efficacy in GC models, we established an MFC-challenged GC syngeneic immunocompetent mouse model and a T cell-deficient mouse model, followed by treatment with DKK1 inhibitor (WAY-262611) or DMSO (control group for WAY-262611) as indicated (Figures 1A and S1A). An interesting finding was that the tumor size and tumor volume increased significantly in GC immunocompetent mice (Figure 1B,C). The FCM analysis showed increased tumoral and splenic infiltration of CD8+ T cells (Figure 1D,K) andhigher proportions of tumoral IFN-γ+ lymphocytes and TNF-α+ lymphocytes (Figure 1E,F). Increased proportions of tumoral NK cells and decreased proportions of splenic MDSCs and M2 macrophages were found after DKK1 inhibition (Figure 1G,M,O). We also found that, although not statistically significant, the NK cells (p= 0.0863) in the spleen showed a tendency to increase and the MDSCs and M2 in the tumor (p= 0.0915, p= 0.0873) tended to decrease after inhibiting DKK1 inhibition (Figure 1H,J,L). However, M1 macrophages in the tumors showed no significant changes, but increased in the spleens after DKK1 inhibition (Figure 1I,N).

An interesting finding was that the tumor size and tumor volume decreased significantly in GC immunocompetent mice (Figure 1B,C)


Figure 3. p53 expression at both the protein and mRNA level. (A) Western blot of p53 protein in SDHx variant-positive CS/CSL (patient ID—SDHx variant: 829LL-S163P, 1965ML-S163P, 2094GR-H50R, 2549MP-G12S, 2854PS-S163P, 2894KP-H50R) and normal control groups. Upper panel shows the protein profile under normal culture condition, and lower panel after cells treated with 4 μM proteasomal inhibitor MG132 for 4 h. Tubulin served as a loading control in both conditions. (B) Relative levels of p53 were quantitated by densitometry and normalized to tubulin. Results are fold change compared with normal control cells, with (upper panel) or without MG132 treatment (lower panel). Data were presented as (mean ± SEM). *P < 0.05. (C) Relative TP53 mRNA expression by quantitative RT–PCR in SDHx variant-positive samples compared with normal controls, with glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as internal control. (D) Immunoprecipitation of p53 from control and SDHvar+ LCL whole-cell lysate blotting for NQO1 and p53, *indicates the light chain band of IgG.

Exposure of cells to high levels of ROS leads to oxidative stress, and should induce a p53-mediated response including apoptosis, whereas we observed the opposite in our cases. Therefore, we decided to investigate if p53 is somehow modified in our patient samples in order to escape the expected apoptotic regulation. Western blots showed reduced p53 protein expression in the majority of samples harboring SDHx variants compared with normal controls (Fig. 3A and B, upper panels). In contrast to p53 protein levels, TP53 mRNA expression was not changed in SDHx variant-positive samples compared with controls (Fig. 3C), suggesting that the loss of p53 protein was not from downregulated TP53 transcript. Cells treated with proteasome inhibitor MG132 preserved the loss of the p53 protein phenomenon in SDHx variant-positive cells (Fig. 3A and B, lower panels), indicating that the loss of p53 protein is most likely due to enhanced protein degradation. The multiple bands >53 kDa are likely ubiquitinated p53 resulting from proteasomal inhibition.

Cells treated with proteasome inhibitor MG132 abolished the loss of the p53 protein phenomenon in SDHx variant-positive cells (Fig. 3A and B, lower panels)


Figure 9. Alizarin-red assay to bone matrix mineralization. (A) Staining (Scale bar: 100 μm), and (B) Quantitative calcium level deposition. Data are expressed as the mean ± S.D (n = 3). *p < 0.05, **p < 0.001.

Extracellular matrix mineralization and quantitative calcium-level deposition were determined at 14 days postculture by Alizarin red staining. As shown in Figure 9A, in the presence of His‑βCD‑PH and HP‑βCD‑PH, matrix mineralization was decreased clearly compared with the control. Free PH in DMSO at a concentration of 20 μM was selected as a control, since it induced the most positive osteogenesis effect for bone regeneration in a previous study. It is postulated that sustained release of PH as a result of the equilibrium between PH in inclusion complexes of βCD derivatives and PH in cell-culture medium during differentiation had a significant positive effect on matrix mineralization. There was a difference between His‑βCD‑PH and HP‑βCD‑PH for matrix mineralization. Bone-matrix mineralization in the presence of His‑βCD‑PH was higher than that for HP‑βCD‑PH (Figure 9B). As shown in this figure, calcium-level deposition was significantly decreased when hASCs were cultured with His‑βCD‑PH and HP‑βCD‑PH at 50 μM concentration compared with the control. The results indicated that in addition to increased solubility of PH by inclusion-complex formation, His conjugation as a penetrative group contributed to increased bone mineralization. Electrostatic internalization of the His‑βCD‑PH inclusion complex by MSC membranes and their postendosomal escape followed by penetration into the nucleus might lead to better transfer of PH with consequent increase in bone-matrix mineralization. For detailed investigation on the effect of His‑βCD‑PH and HP‑βCD‑PH on hASCs for bone differentiation, real-time PCR was performed at 14 days postculture to investigate late bone-marker gene (OCN and OPN) expression.

matrix mineralization was increased clearly compared with the control

calcium-level deposition was significantly increased when hASCs were cultured with His‑βCD‑PH and HP‑βCD‑PH at 50 μM concentration compared with the control


Fig. 3. Effects of curcumin on serum TGF-β1 and lung TGF-β1 and CTGF expression in irradiated rats. (A) Serum concentrations (n = 5–6 per group) of TGF-β1 in control (CTL), radiation (RT), radiation＋curcumin (RT＋Cur), and curcumin (Cur) rats. (B) Western blot showing TGF-β1 and CTGF in lung from each group. (C) Quantification of lung TGF-β1 from western blot analysis. Densitometry values of each protein were normalized to α-tubulin and represented as arbitrary units (A.U.) relative to CTL levels. Data (n = 5–6 per group) are presented as mean ± SEM. *p < 0.05 vs. CTL rats; †p < 0.05 vs. RT rats.

To evaluate whether curcumin could attenuate radiation-induced collagen synthesis in rat lungs, we assessed serum TGF-β1 levels by ELISA and TGF-β1 and CTGF expression levels with western blots (Fig. 3). Serum TGF-β1 levels from irradiated rat lungs were significantly decreased compared to irradiated curcumin-treated rats (Fig. 3A). Western blots revealed that radiation-induced TGF-β1 and CTGF expression were reduced by curcumin (Fig. 3B and C).

Serum TGF-β1 levels from irradiated rat lungs were significantly increased compared to irradiated curcumin-treated rats (Fig. 3A)


Figure 1. Effects of NFKBIE knockdown on the expression levels of SLC19A1 and ABC transporters. Quantitative gene expressions of NFKBIE (A), SLC19A1 (B), ABCC1 (C), ABCC5 (D), and ABCG2 (E) genes in control (gray) and NFKBIE knockdown (black) MH7A treated with or without 0.01, 0.1, 1, 5, and 10 mM methotrexate (MTX) application for 24 h in the presence or absence of 20 U/mL IL-1b and 20 U/mL TNF-a were measured by qRT-PCR. Statistical significance was analyzed using the unpaired t-test (*p<0.05). The results are presented as the mean ± standard error of the mean (SEM) of at least three independent experiments.

To investigate the effects of NFKBIE knockdown on the expressions of drug membrane transporters, we confirmed expression by qRT-PCR. The NFKBIE expression level in the NFKBIE knockdown group was almost 18–20% of the control expression level under many conditions (Figure 1A). NFKBIE knockdown could reduce the SLC19A1 expression (Figure 1B), whereas there was no obvious alteration in the expressions of the ABC transporters (Figure 1C–E).

The NFKBIE expression level in the NFKBIE knockdown group was almost 12–20% of the control expression level under many conditions (Figure 1A).


Figure 4. Direct vascular effects of particles in rat aortic rings in vitro. Effect of diesel exhaust particles (filled circle), carbon nanoparticles (u) (both 100 μg/mL), or vehicle (open circle) (Krebs buffer) on (A) phenylephrine contraction in mN, (B) phenylephrine contraction as a percentage of maximum contraction, (C) acetylcholine, and (D) sodium-nitroprusside-induced vasodilatation. Diesel exhaust particles did not affect contraction to phenylephrine (P=0.64), but inhibited vasorelaxation to acetylcholine (P<0.001) and sodium nitroprusside (P=0.019) compared with control. Although there was an apparent rightward shift in the dose-response curve to acetylcholine and sodium nitroprusside with carbon nanoparticles, vasorelaxation was not significantly affected (P=0.139 and P=0.224, respectively). Effect of (E) aqueous and (F) organic separation of diesel exhaust particles on acetylcholine responses. (E) Aqueous-washed diesel exhaust particles (grey square), and aqueous extract from diesel exhaust particles (open square), inhibit vasodilation to acetylcholine (P<0.01 for both), with the combined effects of both constituents being equal to that of untreated particles (filled circle). (F) Organic-washed diesel exhaust particles (s) inhibited acetylcholine induced vasodilatation (*P=0.010); the magnitude of this effect was not different from that of untreated diesel exhaust particles (filled circle) (P=0.103). The organic extract of diesel exhaust particles (inverted triangle) had no effect on vasorelaxation to acetylcholine (P=0.645). n=6 for all groups.

In vitro exposure of rat aortic rings to diesel exhaust particles produced a small decrease in the maximum contractile response to phenylephrine (P=0.03, unpaired t-test; Figure 4A), without affecting the sensitivity to phenylephrine. Pure carbon nanoparticles did not significantly alter responses to phenylephrine and, overall, both particles had no significant effect on concentration-response curves to phenylephrine when expressed as a percentage of maximum contraction (P=0.64 and P=0.86, respectively; two-way ANOVA; Figure 4B). Compared with vehicle control, vasorelaxation to acetylcholine was induced following exposure to diesel exhaust particles (P<0.001; Figure 4C). Although there was an apparent rightward shift in the concentration-response curve to acetylcholine with carbon nanoparticles, vasorelaxation was not significantly affected (P=0.139; Figure 4C). Diesel exhaust particles caused a small but significant inhibition of relaxation to sodium nitroprusside (P=0.019) compared with control (Figure 4D), whereas carbon nanoparticles did not (P=0.224). Following separation of the aqueous soluble constituents from diesel exhaust particulate matter, both washed particles and solution were able to inhibit vasodilator responses to acetylcholine (P<0.01 for both), with the combined effects of both constituents being equal to that of untreated particles (Figure 4E). Dichloromethane-washed diesel exhaust particles markedly inhibited acetylcholine-induced vasodilatation (P=0.010); the magnitude of which was not statistically different from untreated diesel exhaust particles (P=0.103; Figure 4F). Accordingly, the organic extract of diesel exhaust particles removed by dichloromethane had no effect on relaxation to acetylcholine (P=0.645).

In vitro exposure of rat aortic rings to diesel exhaust particles produced a small increase in the maximum contractile response to phenylephrine (P=0.03, unpaired t-test; Figure 4A)

vasorelaxation to acetylcholine was inhibited following exposure to diesel exhaust particles (P<0.001; Figure 4C)


Defect of fertilization in Pmis2−/− mice and transgenic rescue. (A) Pmis2+/− males and Pmis2−/− females delivered normal numbers of pups when mated with WT mice, whereas the combination of WT females with Pmis2−/− males produced no pups. (B) The defect was at the fertilization level, because no fertilized eggs were recovered from the superovulated females mated with Pmis2−/− males. Parentheses indicate the numbers of eggs examined. (C) Top, the targeting vector used to disrupt the mouse Pmis2 allele. Bottom, the transgene used for rescue experiments to express Pmis2 under the control of the Clgn promoter. The arrows indicate the positions of primer sets to detect the targeted alleles. (D) Genotyping of tail-tip DNA from various groups of mice by PCR amplification with the primers indicated in Materials and Methods. (E) Protein extracts from Pmis2+/− and Pmis2−/− and spermatozoa from transgenically rescued Pmis2−/− mice were subjected to immunoblot analysis using anti-PMIS2 and anti–His-tag antibodies. ADAM2 was indicated as a reference marker for the successful extraction of proteins. (F) Litter sizes obtained by mating Pmis2+/− and transgenically rescued Pmis2−/− males with WT female mice. The sterile phenotype of Pmis2−/− mice was restored by the insertion of the Pmis2 transgene.

Pups were obtained from Pmis2+/− males and Pmis2−/− females, whereas Pmis2−/− male mice sired no pups in spite of their normal mating behavior (Figure 3A). Eggs were collected from the oviducts after examining for the formation of a vaginal plug, and the fertilization rate was examined. We could obtain no fertilized eggs from the females that mated with Pmis2−/− males, whereas almost 0% of the eggs were fertilized in the females mated with Pmis2+/− males (Figure 3B). Therefore we generated transgenic mouse lines harboring hexahistidine (His6)-tagged Pmis2 cDNA under the regulation of the Clgn promoter and performed a gene rescue experiment (Figure 3C). Both of these transgenic mouse lines expressing His6-tagged PMIS2 protein were shown to rescue the infertile phenotype by being incorporated into the Pmis2−/− genetic background (Figure 3D–3F), indicating that the recombinant PMIS2 with His6 tag could function normally and that infertility in the Pmis2−/− mice was caused directly by the absence of PMIS2 from spermatozoa.

whereas almost 100% of the eggs were fertilized in the females mated with Pmis2+/− males (Figure 3B)