The study elucidates the importance of TSPL in pancreatic ductal adenocarcinoma (PDAC), by analyzing: i) TSLP levels in PDAC cell-line supernatants and plasma from patients with locally-advanced/metastatic PDAC, pre- and post-treatment with different chemotherapeutic protocols, in comparison with healthy donors; ii) TSLP and OX40L expression in PDAC and normal pancreatic tissues, by immunohistochemistry; iii) OX40L expression on ex vivo-generated normal DCs in the presence of tumor-derived TSLP, by flow cytometry; iv) clinical relevance in terms of diagnostic and prognostic value and influence on treatment modality and response.Thymic stromal lymphopoietin (TSLP) has emerged as an important, but contradictory, player conditioning tumor growth. In certain contexts, by driving T helper (h) 2 responses via tumor-associated OX40 Ligand (OX40L)ex vivo in the presence of TSLP-rich-cell supernatants, displayed increased expression of OX40L, reduced by the addition of a neutralizing anti-TSLP polyclonal antibody. OX40L+ cells were detected in pancreatic tumor inflammatory infiltrates. Abnormally elevated TSLP levels were detected in situ in tumor cells and, systemically, in locally-advanced/metastatic PDAC patients. Of the chemotherapeutic protocols applied, gemcitabine plus oxaliplatin (GEMOX) significantly increased circulating TSLP levels. Elevated plasma TSLP concentration was associated with shorter overall survival and increased risk of poor outcome. Plasma TSLP measurement successfully discriminated PDAC patients from healthy controls.Some PDAC cell lines, such as BxPC-3, expressed both TSLP mRNA and protein. Normal DCs, generated These data show that TSLP secreted by pancreatic cancer cells may directly impact PDAC biology and patient outcome. Figure vs. 0 (0–24), p = 0.005] . Conversely, when PDAC were classified by degree of tumor differentiation, well-differentiated tumors (grade 1) showed greater TSLP expression than did poorly-differentiated tumors (grades 2/3 plus 3) , while moderately-differentiated tumors (grade 2) expressed similar TSLP levels both to well-differentiated tumors  and poorly-differentiated tumors   was thus assessed in terms of OX40L expression. As Figure +/OX40L+). Conversely, DCs differentiated in the presence of BxPC-3 cell-CM displayed a significant rise in OX40L expression vs. untreated DCs . The CM of Capan-2 cell line, which produces TSLP in trace amounts, induced a slight but not statistically-significant increase in OX40L expression in DCs compared to DCs control . The expression of OX40L on the surface of DCs generated in the presence of BxPC-3 cell-CM was partially, but significantly, reduced (34%) by the use of a neutralizing anti-TSLP polyclonal antibody with proven blocking efficacy   on the ) Figure .+ cells in vivo, immunohistochemical analysis of OX40L was performed on the same tissue samples analyzed for TSLP expression. Figure p > 0.05). When PDAC were classified by degree of tumor differentiation , p = 0.002]. By contrast, no significant difference was found between well-differentiated and moderately/poorly-differentiated tumors .To verify whether TSLP, produced locally by malignant pancreatic ductal cells, was also able to induce infiltration of OX40Ln Figure , moderatp = 0.430) , with no significant difference in IRS terms  Figure . When th) Figure .p = 0.041 and p = 0.050, respectively)] . Unexpectedly, there were no statistically-significant correlations between TSLP IRS and either inflammatory infiltrate or cancer cell OX40L IRS .If the IRS were subdivided by degree of tumor differentiation, moderately-differentiated tumors appeared to express more OX40L on malignant cells than did well- or poorly-differentiated ones  Figure . Moreovevs. 4.65 (0–9.6) pg/ml, p = 0.040] : 5.74 (0–152.9) pg/ml vs. metastatic patients’ TSLP at time 0: 5.74 (0–38.63) pg/ml vs. 5.74 (0–152.89) pg/ml; p = 0.860] and the Spearman correlation test , respectively.To clarify the clinical significance of these findings in locally-advanced or metastatic pancreatic cancer, the relationship between presence of metastasis and pre-chemotherapy (time 0) plasma TSLP levels was evaluated. No significant difference and no correlation were detected, by the Mann-Whitney test .To further evaluate the potential clinical utility of TSLP as diagnostic serum marker, ROC curve analysis was used to discriminate between PDAC patients and healthy volunteers. The cutoff value of 4.76 ng/ml was associated with the highest diagnostic accuracy [in vitro and in situ, can elaborate TSLP, a cytokine known to promote type 2 activation/maturation of resident tumor DCs. This original finding offers a fresh interpretation of the aberrant deviation of immunity that, in this cancer, may contribute to tumor progression. This study shows that: i) some established pancreatic carcinoma cell lines, e.g. BxPC-3, express both TSLP mRNA and protein; ii) TSLP-rich CM from BxPC-3 cells, in a portion of normal DCs generated ex vivo, induce expression of the Th2 polarizing molecule OX40L, partially reversed in the presence of a neutralizing anti-TSLP polyclonal antibody; iii) both tumor infiltrating inflammatory cells and PDAC cells express the OX40L molecule; iv) abnormally elevated TSLP levels may exist in situ in tumor cells and, systemically, in locally-advanced/metastatic PDAC patients; v) among patients on different chemotherapeutic protocols, those receiving GEMOX display significantly elevated circulating TSLP levels; vi) circulating TSLP levels show promise as a diagnostic predictor for PDAC; vii) increased plasma TSLP is an independent prognostic risk factor for poor outcome.This explorative study found that PDAC cells themselves, both It is increasingly clear that TSLP, known to be important in allergy, is also critically involved in the control of tumor growth and metastasis, having different effects depending on context, cellular source, and target . In addiin vitro study and flow cytometry analysis found that some normal myeloid DCs, generated ex vivo in the presence of BxPC-3 cell-CM (but not in that of TSLP-negative Capan-2 cell-CM) express OX40L, a molecule fundamental for optimal induction of primary and memory Th2 responses. However, this effect was only attenuated when the BxPC-3 cell-CM was pre-treated with a neutralizing anti-TSLP polyclonal antibody. This antibody recognizes both short and long TSLP isoforms, suggesting that, in PDAC, TSLP is not the only factor conditioning DCs for Th2 priming. This hypothesis appears reasonable, taking into account that the cytokine IL-18 - one of the most important Th1 cytokines in the presence of IL-12, but that, in its absence, behaves as the Th2 cytokine - induces OX40L in DCs [in vitro and in situ, constitutively express IL-18 [The study shows that, of three PDAC cell lines analyzed , only the latter synthesized relevant levels of TSLP. Interestingly, both L in DCs . PDAC cein vivo, suggesting further immune-response manipulation in promoting tumor growth in the tumor itself.The human tissue microarray study shows that most of the PDAC tissues analyzed expressed TSLP protein at both malignant-cell and stroma levels.. The present study demonstrated that, in addition to CAFs , PDAC ce+CD25+ Treg cells, which might help tumor cells escape the host immune system [reg pool found in PDCA patients [TSLP elaboration is not solely a PDAC-cell-associated phenomenon. An increasing number of studies have focused on the complicated role of TSLP in several cancers: it is tumor-promoting in some instances, and tumor-inhibiting in others. It has been shown that breast-cancer-derived TSLP, but not tumor-infiltrating fibroblasts, drives tumor-promoting inflammatory Th2 cells present in the malignant microenvironment . In lunge system . Notablypatients , 6. Morepatients , 25, andpatients . The invpatients , 28. Conpatients , skin capatients , 31 and patients , suggestThe existence of two isoforms of TSLP controlled by two different promoter regions, and responsible for two opposing biological actions, may explain this paradoxical role of TSLP in malignancies. In the light of this recent finding, since the IHC analysis on PDAC tissue samples reported here did not distinguish between the two TSLP isoforms, and no correlation was found between TLPS protein expression levels and disease stage, the potential roles of the two isoforms in this disease remains to be determined. However, it appears likely that local quantitative and/or qualitative perturbations in the TSLP isoform or TSLP receptor expression may be an initiating and/or driving force, contributing to cancer formation and progression.in vitro studies on the contribution of TSLP-rich CM from malignant pancreatic cells to OX40L+ DC generation, IHC analysis on PDAC tissue microarray was performed to determine the presence of the OX40L molecule in cell infiltrate of primary PDAC. Most tumors were infiltrated with OX40L+ cells, likely DCs; these, among tumor-infiltrating cells with APC capability, have both the numerical advantage and the broadest range of antigen presentation [To complement the present entation . SurprisThe role of OX40L in the polarization of Th cells is complex. OX40L is not constitutively expressed, but can be induced on APCs upon CD40 and Toll-like receptor engagement or cytokine signals. TSLP and IL-18 have been shown to potently induce OX40L expression on DCs , 34. The+ Treg cells accumulating in the tumor tissue; they may also enhance chronic inflammatory responses, promoting tumor invasion and metastasis. Conversely, OX40L+ cancer cells can exploit pathways present in normal tissue to establish a microenvironment facilitating tumor development.OX40L-expressing cells infiltrating the PDAC site may contribute to create inadequate or immunosuppressive events, with the help of OX40in vitro results, where OX40L-induction on DCs, generated in the presence of BxPC-3 cell-CM, was only partially TSLP-dependent. It provides further evidence that, in PDAC as in allergic inflammation, local TSLP-activated DCs can promote Th2 differentiation in a unique manner (dependent on OX40L and on the lack of production of IL-12), and that IL-18 may cooperatively potentiate the inflammatory Th2 cell responses, furthering tumor progression.Unexpectedly, OX40L expression levels in the PDAC tissue samples were not correlated with those of TSLP, evaluated in parallel. However, this is in line with in situ study performed by IHC on early stage PDAC tissue samples , it is tempting to speculate that TSLP release occurs early in PDAC tumorigenesis and, once established, remains constant during the late phase of tumor progression.Since TSLP is a secreted protein, and is highly expressed in pancreatic tumor tissues, plasma TSLP levels were measured in a group of locally-advanced/metastatic PDAC patients, and its potential clinical significance was assessed. It emerged, for the first time, that circulating TSLP  was significantly elevated in PDAC patients in comparison with normal subjects, independently of disease stage. The patients enrolled in this systemic analysis had advanced disease. In the light of the results of the et al. in a murine model: TSLP-stimulated CD4+ Th2 cells were found to be key mediators of the antitumor immune response that blocks early stages of both breast and pancreatic cancer development, protecting the animals from advanced cancer and metastasis. In particular, in the presence of systemic TSLP, spontaneous pancreatic tumors transferred to K14-TSLPtg mice grew less than those in WT mice, with a significant increase in GATA3+ Th2 infiltrating cell numbers [This is contrasted by findings reported by Demehri  numbers .in vivo. This assumption is corroborated by ex vivo experiments showing that DCs from healthy subjects, generated in the presence of BxPC-3 cell-CM containing TSLP, expressed higher levels of OX40L surface. The mechanisms regulating TSLP expression and secretion from cancer cells, including a potential link with oncogenic events, remain to be established.However, these two possibilities are not contradictory, taking into account emerging evidence that TSLP exists in two different isoforms exerting opposing biological effects. It is thus tempting to hypothesize that, in early-stage PDAC, the prevalence of the short TSLP isoform, predominantly produced by cells that are still well/moderately-differentiated, may control tumor growth. But, in response to as-yet-unidentified stimuli altering the local microenvironment, the induced long TSLP isoform then takes over, affecting the course of the disease. At the systemic level, altered circulating levels of TSLP may negatively influence the frequency, composition, and functional activity of DC populations Interestingly, univariate and multivariate analysis showed elevated circulating TSLP levels to be significantly associated with poorer survival, and to be an independent indicator of prognosis, respectively. As yet, no directly comparable data are available. However, in WT mice, serum levels of TSLP correlated positively with malignant breast-tumor cells and melanoma growth, indicating the importance of TSLP in tumor progression . MoreoveIn investigating the ability of TSLP to discriminate between patients and controls, ROC analysis showed that the cutoff value of 4.76 ng/ml had the greatest diagnostic accuracy. However, further longitudinal data are required to confirm this observation.Systemic chemotherapy still remains a standard of care for the treatment of PDAC patients with unresectable locally-advanced and metastatic disease. In this study, among the several therapeutic protocols used, only the double-drug combination GEMOX was found to modulate plasma TSLP levels. These results are in line with research showing that chemotherapeutic agents may have immunomodulating properties and functional interactions . HoweverAlthough this patient series is not extensive, when the clinical response to different treatments is evaluated some tentative findings emerge. The clinical response to GEMOX (which is associated to a rise in plasma TSLP levels) was less favorable than GEM alone. However, pretreatment circulating TSLP levels did not predict the response to any regimen.Taken together, these clinical observations are consistent with the hypothesis that, in advanced-stage PDAC, high local and peripheral TSLP levels could have undesirable effects, producing an immune response that is both inappropriate and persistent. This assumption is highlighted by the importance of TSLP as an independent prognostic factor. Further investigation will thus be needed, in a large cohort of patients with early-stage operable cancer.+ and CD8+ T cells, as an effective means of augmenting immunity and overcoming mechanisms used by tumors to evade destruction. The results of this study are consistent with the notion that local and systemic tumor-derived TSLP may, with other concomitant immune-suppressive cytokine pathways, contribute to limiting the anti-tumor therapeutic responses to DC-based vaccines in PDAC. However, TSLP’s emerging ambiguous role in tumor immunology complicates the decision over how to manipulate TSLP, or its signaling pathway, in managing cancer patients. Additional studies will be required to reveal the mechanistic basis of the tumor-promoting vs. tumor-suppressive effects of TSLP in different cancers, before TSLP can be recognized as a potential target for therapeutic intervention.The goals of cancer immunotherapy are to activate and expand tumor-specific CD4PDAC-derived cell lines Capan-2, BxPC-3 (ATCC HTB-80 and CRL-1687) and PT-45  were cultured in RPMI 1640 medium supplemented with 10% FCS  and regularly tested for mycoplasma contamination using Hoechst dye H33258 . Immortalized human pancreatic ductal epithelial cells HPDE6-E6E7 (H6c7) were generously provided by Dr. Ming-Sound Tsao, Cancer Center/Princess Margaret Hospital, University Health Network, Toronto, Ontario, Canada . CM were2 on days 1 and 8 every 21 days); GEM (1000 mg/m2 on day 1) plus oxaliplatin (OX) (100 mg/m2 on day 2 every 14 days); bevacizumab (5 mg/kg every 14 days) plus capecitabine (825 mg/m2/b.i.d.) and concomitant radiotherapy (50.4 Gy in 28 cycles) (BEV+CAPE+RT), following the study protocol; 5-fluorouracil (5-FU) (500 mg/m2) plus levofolinate calcium . After the first restaging, responses (assessed by the RECIST criteria) were as follows: 2 complete remission (CR), 4 partial remission (PR), 32 stable disease (SD) and 31 disease progression (PD) .The series comprised 82 patients with locally-advanced or metastatic PDAC admitted to the Department of Medical Oncology, Città della Salute e della Scienza Hospital, Turin, Italy, enrolled into the study between May 2010 and March 2012; patients with serious infections or severe allergic disease were excluded. None of the participants had received chemo/radio therapy before entering the study. All participants signed an informed consent form; study procedures were in accordance with the Declaration of Helsinki. Before starting chemotherapy, patients were staged following the International Union Against Cancer (UICC) TNM system. Patients’ clinical-pathological details are in Table Patient follow-up continued until death or March 2012. 65 patients died . 17 patients were alive at completion of the study. Survival was 51.2% at 1 year after diagnosis.n = 10). Ex vivo-generated DCs were obtained as described elsewhere [Peripheral blood mononuclear cells (PBMC) were isolated from heparinized blood samples from healthy donors  or irrelevant control IgG were added to BxPC-3 cell-CM at the concentration used to neutralize TSLP biological activity (40 ng/ml) as reported above. Samples were incubated for 30 min at r.t. After addition of Protein A/G agarose beads (Thermo Fisher Scientific)  the samples were incubated o.n. at 4° C under agitation, and then centrifuged twice at 420 g for 5 min to ensure complete removal of agarose beads.TSLP was measured in the CM of PDAC cell lines and in plasma from PDAC patients and healthy donors, as well as in Bx-PC-3 cell-CM depleted of TSLP by immunoprecipitation, using an ELISA kit (Thermo Fisher Scientific). Minimum detectable quantity: 8 pg/ml. The manufacturer of the ELISA kit was not able to indicate the TSLP isoform recognized.Total RNA was extracted from Capan-2, BxPC-3 and PT-45 cell lines, and from appropriate positive controls, using TRIzol Reagent (Thermo Fisher Scientific). To remove traces of genomic DNA, total RNAs (1 µg) were treated with DNase I and reverse-transcribed to cDNAs using SuperScript II (Thermo Fisher Scientific).Real time RT-PCR was performed in duplicate using SYBR Green real time PCR master mix  in iCycler iQ system (Bio-Rad). The specific primers used to amplify TLPS and β-actin genes were, respectively: FW: CGTGGTGGGAAGAGTTTA and RW: CAGTTAGTGAAGTCGTAAGT; FW: GCGAGAAGATGACCCAGATC and RW: GGATAGCACAGCCTGGATAG. TSLP RNA expression levels, reported as arbitrary units relative to β-actin, were calculated by the Gene Expression Analysis Real-Time PCR Detection System Ò Software Tool for iCycler iQ (Bio-Rad).+ cells in the fraction of HLA-DR+ cells. Statistical analyses were based on at least 30,000 events gated on the population of interest.Expression of OX40L (CD252) was analyzed on normal DCs generated in the conditions reported above. The cells were double stained with a phycoerythrin-cyanine 5.1 (PC5)-conjugated anti-HLA-DR monoclonal antibody (mAb)  and fluorescein isothiocyanate (FITC) anti-OX40L mAb . Cells were analyzed by flow cytometry in a Coulter Epics XL Cytometer (Beckman Coulter) using the Expo32 software (Beckman Coulter). Results are expressed as the percentage of OX40Ln = 11 well-differentiated, n = 2 moderately-differentiated, n = 1 moderately/poorly-differentiated, n = 3 poorly-differentiated; from 13 male and 25 female patients, aged 41–74 years, median age 67.5; n = 9 disease stage I, n = 23 stage II, n = 2 stage III, and n = 3 stage IV) and 8 healthy pancreatic tissue samples   were used to identify and localize TSLP and OX40L proteins by IHC. TMA slides were processed for IHC as described elsewhere [® kit . Staining intensity was evaluated by a semiquantitative method, using the immunoreacting score (IRS) proposed by Remmele and Stegner [Commercial tissue microarrays (TMA) containing 38 PDAC tissue samples  or patient death from any cause. Survival probabilities were calculated using the Kaplan–Meier Method. Survival curves were compared using the Log-Rank Test (Mantel-Cox). The feasibility of using plasma TSLP as a biomarker for differentiating cases from normal controls was assessed by receiver-operating characteristic (ROC) curve analysis. P values < 0.05 were considered statistically significant. Statistical analysis was performed with SPSS Statistics for Windows, Version 22.0 .The Mann-Whitney Rank Sum Test, Kruskal-Wallis One Way Analysis of Variance by Ranks or Student’s


Human T-cell lymphotropic virus type 1 (HTLV-1) and hepatitis B virus coinfection is frequent in certain Indigenous Australian populations, but its outcome remains unknown. We report a higher degree of HTLV-1 clonal expansion than in those with HTLV-1 alone. The prevalence of human T-cell lymphotropic virus type 1 (HTLV-1) and hepatitis B virus (HBV) coinfection is high in certain Indigenous Australian populations, but its impact on HTLV-1 has not been described. We compared 2 groups of Indigenous adults infected with HTLV-1, either alone or coinfected with HBV. The 2 groups had a similar HTLV-1 proviral load, but there was a significant increase in clonal expansion of HTLV-1–infected lymphocytes in coinfected asymptomatic individuals. The degree of clonal expansion was correlated with the titer of HBV surface antigen. We conclude that HTLV-1/HBV coinfection may predispose to HTLV-1–associated malignant disease. Strongyloides stercoralis, control the clonal abundance of HTLV-1–infected T cells less efficiently than non-coinfected individuals [Human T-cell lymphotropic virus type 1 (HTLV-1) and hepatitis B virus (HBV) are 2 oncogenic viruses endemic among Indigenous Australians in Central Australia . HTLV-1 ividuals . The aimThe study was approved by the Central Australian Human Research Ethics Committee (HREC-14–217). All patients gave informed consent in their primary languages.Plasma, peripheral blood buffy coat cells , or periHBV viral load and hepatitis B quantitative serology for the hepatitis B surface antigen (HBsAg) were processed by the Victoria Infectious Diseases Reference Laboratory, Melbourne, Australia.Strongyloides serology status was assessed by an in-house enzyme-linked immunosorbent assay.Genomic DNA (gDNA) was extracted from peripheral blood buffy coats  or from tax, and TaqMan MGB probe (5ʹ-FAM-CATGATTTCCGGGCCTTGC-MGBNFQ-3ʹ) (250 nM) (Thermo Scientific), and (×20) PrimePCR ddPCR copy number assay: ribonuclease P/MRP 30 kDa subunit (RPP30-HEX) human primer/probe mix (Bio-Rad), and (×2) Bio-Rad Supermix for Probes (no deoxyuridine triphosphate).The HTLV-1 proviral load was measured as previously described  by droplAll samples were run in duplicate, and the reported HTLV-1 subtype c (HTLV-1c) proviral load is the mean of the 2 measurements. The T-cell population was determined by measuring the loss of the Dβ1-Jβ1.1 intergenic sequences, as previously described .tax copies per 106 T cells. The ddPCR limit of detection for HTLV-1 proviral load was determined to be 98 copies per 106 T cells.The HTLV-1 proviral load was determined as the mean number of gag open reading frame, adapted to HTLV-1c, 5LTRFW1c: 5ʹ- CTCGCTTCTTTCCCTCACG-3ʹ, 5LTRRV1c: 5ʹ-GCGCTACGAGGGAAGATTTG-3ʹ. Amplified LTR products were Sanger sequenced (accession numbers: MG783271–MG783311) and the sequences were used to design primers for ligation-mediated polymerase chain reaction (LM-PCR) and sequencing: these primers were specific for HTLV-1c sequences  of the HTLV-1 provirus was amplified using primers targeting the end of the 5ʹ LTR (RU5) and the beginning of the equences  based onhttp://www.R-project.org/). As previously described, the oligoclonality index (an application of the Gini index) is a measure of the frequency dispersion of a cell population, and ranges from zero to 1 [https://cran.rproject.org/web/packages/ineq/index.html) on samples with >5 unique integration sites, and adjusted for type I error [Statistical analysis was carried out using R version 3.4.1  presenting to ASH and found to be HBsAg positive were eligible for recruitment. ASH is the only medical facility serving a 1 × 10HTLV-1 parameters for HBV/HTLV-1–coinfected subjects were compared with those of asymptomatic HTLV-1–monoinfected subjects recruited from December 2008 to November 2013 inclusive ; the sel4 proviral copies per 106 T cells) was not significantly different from that of HTLV-1–monoinfected asymptomatic subjects . The degree of oligoclonal expansion of infected lymphocytes is measured by the oligoclonality index [P = .0003). Three patients , but was not correlated with the HTLV-1 proviral load  remained significant even when this patient was omitted. Nonetheless the correlation between qHBsAg titers and HTLV-1 oligoclonality index remained marginally significant .There was no correlation between the HBV load and either the oligoclonality index or the proviral load of HTLV-1 . The titral load . All patl status  except oStrongyloides–HTLV-1 coinfection and subjects with infective dermatitis [S. stercoralis [S. stercoralis [Strongyloides [Contrary to rmatitis , 11, HBVrcoralis , 11 and rcoralis  and in prcoralis .The posigyloides .Although previous work did not indicate an association between HBsAg positivity and the presence of HTLV-1 infection in a multivariate model [In the present study, the coinfected group had a higher median age than monoinfected subjects . However+FoxP3+ regulatory T cells [Also, there was a wide variation in proviral load (up to 68-fold) within each group, as reported previously in both asymptomatic carriers and patients with inflammatory disease. Our results raise the question whether the impact of HBV coinfection on T-cell clonality is to alter the nature or magnitude of specific T-cell populations, for example, by stimulating T-cell proliferation, expression of CD25 , or the T cells .In this study we quantified the impact of coinfection with HBV on HTLV-1 clonality and proviral load. Serological and epidemiological studies also suggest that the coinfection may limit the control of HBV infection . FinallyThe Journal of Infectious Diseases online . Supplementary materials consist of data provided by the author that are published to benefit the reader. The posted materials are not copyedited. The contents of all supplementary data are the sole responsibility of the authors. Questions or messages regarding errors should be addressed to the author.Supplementary materials are available at Supplemental_Figure and Table-1Click here for additional data file.Supplemental_Table_2Click here for additional data file.Supplemental_Table_3Click here for additional data file.


Pediatric glioblastoma multiforme is an uncommon and highly mortal brain cancer. New therapeutic treatments are being intensively investigated by researchers in order to extend the survival of patients. The immune checkpoint inhibitor nivolumab in the treatment of pediatric glioblastoma multiforme is currently under review; it is a human immunoglobulin G4 monoclonal antibody that works against the programmed cell death protein 1 receptor, designed to enhance an immunologic reaction against cancer cells. Herein, we describe the first report of a bilateral optic neuritis induced by nivolumab in a grade 4 glioblastoma multiforme patient. The current standard treatment for the newly diagnosed pediatric glioblastoma multiforme (GBM) is surgical debulking followed by radiation therapy and chemotherapy. However, a 5-year survival rate is less than 10%, and the median survival is 1–2 years [The immune checkpoint inhibitor nivolumab has been shown to improve antitumour response in a number of different advanced malignancies in different studies. The treatment of pediatric GBM is currently under review. It is a human immunoglobulin G4 monoclonal antibody that works against the programmed cell death protein 1 receptor, and is designed to enhance an immunologic reaction against cancer cells. On the other hand, using immune checkpoint inhibitors may cause an autoimmune phenomenon, including pneumonitis, hepatitis, vitiligo, colitis, hypophysitis, pruritis, arthritis, nephritis, neurologic syndromes , and autoimmune hemolytic anemia . Herein,2/day peroral for 5 days; every 4 weeks for 10 cycles) and bevacizumab  plus irinotecan  as first and second-line treatments. However, in the control magnetic resonance imaging, the tumor showed progression despite these treatments. Therefore, we began to use nivolumab as a third-line treatment.The patient was a 9 year old male with a 10-day history of severe headache, vomiting, and numbness in the right arm and foot. Bilateral papilledema was found at the ophthalmic examination. Magnetic resonance imaging (MRI) displayed a mass with homogenous contrast enhancement in the left brain hemisphere and brainstem . On the Nivolumab therapy was started at a dose of 3 mg/kg intravenously every two weeks. Two days after the second dose, the patient was admitted to the hospital with a rapidly progressive decline in visual acuity of the eyes. On ophthalmic examination, the visual acuity of the right eye was counting fingers at 1 m and was very low on his left eye (limited to light perception). At the posterior segment examination, there was an optic disc swelling bilaterally. Other vital findings, such as blood electrolyte levels and neurological examination, were normal. An urgent MRI showed bilateral thickening of the optic nerves suggestive of optic neuritis, with normal intracranial pressure . BilaterAs a treatment option, nivolumab and other immune checkpoint inhibitors are beginning to be preferred in daily clinical practice by researchers. Therefore, immune-related adverse events have significantly increased, however, the adverse events are reported to be less undoubtedly in clinical studies. For example, pneumonitis, type I diabetes mellitus, pruritis, encephalitis, myasthenia gravis, hepatitis, thyroiditis, colitis and other autoimmune diseases can emerge in any part of the body ,3. To thIn one case reported by de Velasco and colleagues, nivolumab was associated with uveitis after cycle 28  and in another case reported by Karlin and colleagues, the patient developed bilateral uveitis after cycle 10  ,5. In coAccording to some clinical studies, a pulse dose of steroids can be used for optic neuritis . In the In the pediatric period, bilateral optic neuritis is more common in the younger age-group (<10) as compared to the older age-group (≥10). Waldman and colleagues found that optic neuritis is correlated with age . For eveClinical presentation of optic neuritis may be dramatic, however, the visual outcome of optic neuritis in children, especially in younger children, is fairly good. Wilejto and colleagues evaluated 36 cases with optic neuritis in Canada and found that the visual acuity of 39 of 47 eyes (83%) recovered to ≥20/40 after 2.4 years . Mizota Probably, nivolumab is responsible for the optic neuritis seen in this patient because of the short duration of time between nivolumab initiation and decrease in visual acuity in this case. Nivolumab, a human immunoglobulin G4 monoclonal antibody against programmed cell death protein 1 receptor, blocks T cell inhibition and stimulates the immunologic response towards cancer cells, however, it may also reduce the self-tolerance of the immune system and may cause an autoimmune phenomenon. Presumably, because of this mechanism the optic neuritis developed bilaterally in our case ,13.Bilateral optic neuritis as an adverse event of nivolumab therapy has not been reported yet. It is the first known report of bilateral optic neuritis associated with nivolumab in childhood. Nivolumab may stimulate many unknown autoimmune disorders and these may become possible limiting factors in the clinical usage of the drug. Further work is also needed to determine the association between nivolumab and optic neuritis.


We further observed a declining sensitivity of LAImax to annual rainfall over 56% of the tropical savannas, spatially overlapping with areas of increased woody cover and altered rainfall climatology. This suggests a climate-induced shift in the coexistence of woody and herbaceous vegetation in savanna ecosystems, possibly caused by altered hydrological conditions with significance for land cover and associated biophysical effects such as surface albedo and evapotranspiration.Tropical savannas comprise mixed woodland grassland ecosystems in which trees and grasses compete for water resources thereby maintaining the spatial structuring of this ecosystem. A global change in rainfall climatology may impact the structure of tropical savanna ecosystems by favouring woody plants, relative to herbaceous vegetation. Here we analysed satellite data and observed a relatively higher increase in woody vegetation (5%) as compared to the increase in annual maximum leaf area index (LAI Changing rainfall patterns may drive changes in the structure of tropical savanna. Here Zhang et al. use satellite data from global tropical savannas, and find evidence to suggest that altered rainfall may be favouring woody plants over herbaceous plants in these ecosystems. Changing patterns in one of these controlling factors can lead to an imbalance of this coexistence, ultimately causing changes in the structure and functioning of savanna ecosystems. It has been well documented that increasing pressure by herbivores (in particular livestock) favours woody plants at the detriment of herbaceous vegetation, causing a phenomenon termed woody encroachment, which is widespread across global savannas5 and in particular in Sub-Saharan Africa6. Moreover, a declining fire frequency has been observed7, also known to sustain the growth of woody vegetation in savanna ecosystems5. Recently, increased atmospheric CO2 concentrations were suggested to increase the growth rate of trees relative to grasses10. The impact from changes in rainfall on the vegetation production (comprising both herbaceous and woody foliage mass) is well documented from analyses covering global drylands11. Likewise, global syntheses of the impact on woody vegetation (based on benchmark tree cover maps) evidence the close relationship between rainfall climatology and the density of woody plants12. At local scale, it has been found that changing rainfall climatology  in drylands has led to increased growth of woody plants2. This is because woody plant vegetation does not require an even temporal distribution of rainfall over the wet season to the same degree as herbaceous vegetation and is able to use water from the deeper soil layers2. Consequently, altered rainfall climatology supposedly can give woody plants an advantage over herbaceous vegetation with shallow rooted systems13. This advantage might also be associated with a decrease in the susceptibility of juvenile woody vegetation to the controls induced by fires and herbivores3.Tropical savanna ecosystems are characterized by the coexistence of woody and herbaceous vegetation14, which may be expected to affect the structure and functioning of terrestrial ecosystems16, including water balance15, vegetation productivity17 and ecosystem composition16. Yet, our current knowledge on the impact of rainfall extremes on the competition between woody and herbaceous plants is based on only a few plot-based experimental studies19, as it is challenging to assess woody vegetation trends from global long-term optical satellite imagery systems. Recently, a few studies exploited the complementary use of optical and passive microwave satellite data to study temporal changes in woody cover21. However, no global scale study has yet documented temporal long-term changes in both woody vegetation and green vegetation production and examined the underlying controls, including an analysis of changing rainfall climatology.A global increase in rainfall extremes has been observed in recent decadesmax and woody cover for global tropical savannas (see Methods) and find a higher increase in woody vegetation as compared with the increase in LAImax. We further observe a widespread declining sensitivity of LAImax to annual rainfall for tropical savannas. These results suggest that altered hydrological conditions have caused a shift in the coexistence of woody and herbaceous vegetation in savanna ecosystems.Here, we use satellite data of rainfall, LAImax) derived from optical satellite data to study changes in savanna photosynthetic primary production. LAImax is an indicator of the total green production22, including the foliage mass from both herbaceous and woody vegetation , which has been shown to be closely related to woody cover in both drylands and humid regions21, was used as a proxy for woody vegetation. VODmin senses the water content of all woody vegetation components, including the stem and branches, and the impact of herbaceous plants on the VODmin signal is weak21. We found that VODmin estimated woody cover increase was significantly higher (expressed by z-scores) than the increase in LAImax (p < 0.05), especially for areas with a mean annual rainfall less than 1000 mm yr−1 , presumably caused by deforestation21, but also higher rainfall in moist tropical drylands can lead to reduced productivity23. We further analysed changes in the sensitivity of LAImax to annual rainfall , expressed by the slope of a linear regression between LAImax and annual rainfall over a 15-year moving-window period. We found that a majority (56%) of the global savanna areas experienced a reduced sensitivity over the period 1982–2015, and 68% of these areas  coincided with areas of increased woody cover. More specifically, the higher the change in annual rainfall and increase in woody cover, the stronger the observed decrease in sensitivity between LAImax and annual rainfall   Fig. .Fig. 1Ch24. We found that factors related to inter-annual dynamics in rainfall climatology  were primary factors controlling changes in woody cover with relative weights of 47% for all tropical savannas, 78% in arid, 67% in semi-arid and 36% in humid regions   with results varying across rainfall regimes  and changes in woody cover. We found a similar pattern between changes in woody cover and changes in rainfall variables along the entire rainfall gradient, with the strongest changes happening in arid and semi-arid regions Fig. . The senmes Fig. . For arimes Fig. .max to annual rainfall was evident over all continents . As increased heavy rainfall frequency has been documented to favour woody vegetation2, supported by a biophysical explanation of the phenomenon5, we analysed the impact of heavy rainfall frequency on changes in woody cover   Fig. . Howevermax towards annual rainfall  in savannas reacts mainly to the rainfall conditions of a given year33. At the same time, we find that increases in woody vegetation (as measured by the water content of the entire woody plant) were higher as compared with increases in LAImax, and this was, at global scale, largely controlled by rainfall climatology. Increases in woody cover were mainly found in areas with a decreasing sensitivity between LAImax and annual rainfall, suggesting that woody vegetation benefits more from the increased annual rainfall as compared with LAImax. A possible explanation is found in the altered rainfall climatology . Here, we found a strong relationship between increases in woody cover and increases in the frequency of heavy rainfall events, which has also been demonstrated at experimental sites19. Since herbaceous vegetation is known to be vulnerable to an uneven seasonal distribution of rainfall34, altered rainfall climatology is likely to affect the coexistence of woody and herbaceous vegetation, e.g., favouring the expansion of the ranges of woody plants13. This effect would imply that large-scale woody encroachment reported in savanna ecosystems2 is at least partly driven by changes in the rainfall regime. This further implies a pronounced change in the functioning of global savanna ecosystems within the last 30 years, which would have a profound impact on the biodiversity, carbon-storage capacity and provisioning of these ecosystems.Our study shows global increases in LAI29. A strong influence of El Niño/La Nina events on vegetation has been reported in several regions of the world, notably via the impact on rainfall16. From a wider climatic perspective, the increasing frequency of La Niña/El Niño events with global warming suggested by some recent studies36 would lead to an increase in the frequency of heavy rainfall episodes and droughts37, which could further favour woody vegetation. Experimental studies have demonstrated that increased CO2 positively affected vegetation productivity, particularly the growth of woody plants38. However, the contribution of CO2 fertilization on the global greening and large-scale woody encroachment is difficult to quantify and global evidence based on observational data has not yet been established40. Our results do not exclude the possibility of a “CO2 effect”, but suggest, from a global perspective, woody cover increases in tropical savannas to be influenced by altered rainfall climatology, including a higher annual rainfall, higher frequency of extreme rainfall events and number of rainy days induced by climate change.Moreover, the results may contribute explaining the phenomenon of the greening of global drylands41 and CHIRPS satellite-based daily rainfall estimates at 0.05° spatial resolution42, both resampled to 0.25° . CRU rainfall was used to calculate the relationship between LAI and annual rainfall. Heavy rainfall frequency were extracted from CHIRPS using the number of rainy days (≥ 1 mm day−1) for 1982—2015 above the 90th percentile of observed daily rainfall, the number of rainy days and rainfall intensity were calculated for each year.We used monthly climatic data  with a spatial resolution of 0.5° (1982–2015) from the University of East Anglia’s Climate Research Unit CRU TS 443. This dataset was provided with a bi-monthly temporal resolution in a 1/12° spatial resolution from 1982 to 2015. LAImax is an indicator of the total green vegetation production22, including the foliage mass from both herbaceous and woody vegetation. The growing season maximum leaf area index (LAImax) was used to study changes in savanna photosynthetic primary production. The LAImax was resampled to a 0.25° spatial resolution using nearest neighbour interpolation to match the VOD pixel size.We used the latest version of GIMMS3g LAI v1 that was generated by training the GIMMS3g v1 NDVI  with MODIS LAI using an artificial neutral network44 and has been shown to better reflect the woody vegetation signal20. The data were retrieved from satellite passive-microwave observations and several merged sensors at a spatial resolution of 0.25˚ from 1992 to 201245. We followed the approach of Brandt et al.21 who found a strong linear correlation between annual minimum VOD values and woody cover over Africa  and transformed the annual minimum VOD values to the unit woody cover (%) by multiplication with 64.46. By using the seasonal minimum, we also minimized the influence of annual herbaceous vegetation and avoided saturation effects over dense forests21.Contrary to LAI, vegetation optical depth (VOD) is sensitive to the water content of both the green and non-green woody parts of vegetation41. The differences in human population density between 2015 and 2000 were based on the Gridded Population of the World (GPWv4)46 dataset. Mean annual burned fraction for 1997–2012 from the Global Fire Emissions Database (GFED4s)47 was used to analyse the impact of changes in fire activity. Soil organic carbon (SOC) and sand fraction were extracted from the Harmonized World Soil Database (HWSD v1.2)48. The elevation extracted from the Shuttle Radar Topography Mission data (SRTM 90 m)49. All datasets collected were resampled to a 0.25° spatial resolution using nearest neighbour interpolation .Additional datasets, including dynamic environmental/demography variables  and static environmental variables , were used to study the relationship between changed herbaceous/woody vegetation and rainfall climatology changes. Trends in air temperature and solar radiation (represented by cloud cover) for 1992–2012 were calculated using the CRU TS4 datasets50. To minimize the human footprint on the analyses conducted, global land cover (GLC-SHARE) data51 were used to mask out cropland areas with a cropped percentage above 70%. ESA CCI land cover (https://www.esa-landcover-cci.org/) from 2010 was used to mask irrigated areas. Additionally, ESA CCI land cover was used to limit our analysis to savanna vegetation by masking out water areas.We defined the areal extent of tropical savannas based on the ecoregion classification by Olson et al.max) and annual rainfall over a 15-year moving window to derive the beta coefficient , which is frequently used as a measure of the sensitivity of vegetation to variation in rainfall. Variables were normalized at each grid point by the inter-annual standard deviation in each study period prior to linear regression analysis. A non-parametric Theil–Sen trend analysis was then applied to detect trends in βLAI-Rainfall and the Mann–Kendall (MK) test was applied to evaluate βLAI-Rainfall trends at the 95% significance level (p < 0.05) taking temporal autocorrelation into account. Trends in woody cover and rainfall climatology variables were also calculated using this method. Here, the MK significance test based on linear trends was avoided as a linear response of changes in woody cover to changes in rainfall climatology variables was not to be expected. Moreover, due to the high inter-annual variability of climatology, significant trends could not be expected52. Welch’s unequal variances t test was used to test for significant difference between temporal changes in LAImax and woody cover.We performed a linear regression between herbaceous vegetation  change in annual rainfall; (2) change in heavy rainfall frequency; (3) change in rainy days; (4) change in annual air temperature; (5) change in solar radiation; (6) change in human population density; (7) change in burned area fraction; (8) mean annual rainfall; (9) coefficient of inter-annual rainfall variability; (10) soil organic carbon; (11) elevation; (12) sand fraction. The model was run for tropical savannas (All) and its sub-regions including arid (< 300 mm yr−1), semi-arid (300–700 mm yr−1) and humid regions (> 700 mm yr−1) divided according to mean annual rainfall during 1992–2012. Each variable xi was normalized as Xi = (xi –x)/σ(x) (where x and σ(x) are the mean and standard deviation of xi) before modelling the data and all analysis were conducted in R.The relative weights of the controlling factors on changes in woody cover were estimated using the LMG method (a bootstrapping technique)Further information on experimental design is available in the Supplementary InformationPeer Review FileReporting Summary


During embryonic development, diffusible signaling molecules called morphogens are thought to determine cell fates in a concentration-dependent way. Yet, in mammalian embryos, concentrations change rapidly compared to the time for making cell fate decisions. Here, we use human embryonic stem cells (hESCs) to address how changing morphogen levels influence differentiation, focusing on how BMP4 and Nodal signaling govern the cell-fate decisions associated with gastrulation. We show that BMP4 response is concentration dependent, but that expression of many Nodal targets depends on rate of concentration change. Moreover, in a self-organized stem cell model for human gastrulation, expression of these genes follows rapid changes in endogenous Nodal signaling. Our study shows a striking contrast between the specific ways ligand dynamics are interpreted by two closely related signaling pathways, highlighting both the subtlety and importance of morphogen dynamics for understanding mammalian embryogenesis and designing optimized protocols for directed stem cell differentiation.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see ssed see . Mammalian development depends crucially on diffusible signaling molecules called morphogens, that are thought to determine cell fates in a concentration-dependent manner , and proThese concepts have begun to be explored in mammalian cell culture systems. For the Nκfb pathway, an intricate relation between ligand dynamics, signaling response and target gene activation was found . FurtherGastrulation is the first differentiation event of the embryo proper, when the germ layers are formed and the body axes are established. Nodal and BMP4 are morphogens crucial for gastrulation in vertebrates . In the Micropatterned human embryonic stem cells (hESCs) self-organize into reproducible spatial domains corresponding to each of the germ layers and were recently established as a method to recapitulate human gastrulation in vitro . This syTo investigate how sudden increases in BMP4 and Nodal levels are interpreted by hESCs, we performed live imaging of hESCs with GFP:SMAD4 in the endogenous locus , and quaAlthough TGFβ signaling through SMAD4 has been shown to adapt in C2C12 cells , the molTo understand the mechanism of this inhibition, we first considered fitting our FRAP data to a model in which the entire population of SMAD4 is free to shuttle between the nucleus and cytoplasm. In this case, bleaching reduces the total pool of observable GFP-SMAD4 molecules but the nuclear to cytoplasmic intensity ratio depends only on the kinetic constants, and therefore would recover to the same value following bleaching. However, we observed that this ratio systematically decreases after nuclear bleaching . This suNODAL, WNT3, and their inhibitors LEFTY1 and CER1 were sustained upon Activin treatment  and BRACHYURY (BRA) showed a stronger response and were stably reactivated following adaptation on longer time scales  and comparing the response with the response to a single step to the same final dose . If cellBMP ramp . As noteBMP ramp . FinallyBMP ramp .Morphogens control cell fate, and the dependence of transcription of mesodermal and endodermal genes on Activin rate of increase suggests rapid Activin increase may boost differentiation to these fates. We hypothesized that exposing cells to repeated rapid increases by pulsing the level of Activin could enhance this effect. To rigorously test this hypothesis, we grew cells in differentiation conditions and compared pulses that switch between high and low doses of Activin with a sustained high Activin dose while performing media changes at the same times (‘dummy pulses’) . Each puTo test whether rapid concentration increases are relevant to endogenous Nodal during embryonic patterning, we turned to micropatterned colonies of hESCs treated with BMP4. These colonies differentiate in a spatial pattern with reproducible rings of extraembryonic cells and all three germ layers, and represent a model for the patterning associated with gastrulation in the human embryo . Nodal sTo distinguish these hypotheses, we used live imaging to observe SMAD4 signaling in micropatterned colonies during the 42 hr in which these patterns form a-c. The Our work shows that morphogens in the mammalian embryo do not act in a purely concentration-dependent matter and has revealed an important role for Activin/Nodal rate of change in specifying cell fate as a consequence of adaptive signaling. Adaptive signaling could serve to restrict the response to a narrow competence window or to separate the multiple roles of a single morphogen by using distinct dynamics to selectively activate different target genes, effectively expanding the information content of the morphogen gradient . It is cActivin and Nodal are generally thought of as text-book morphogens acting in a concentration-dependent manner . This isOur results are in contrast to those for another well-characterized system, the patterning of the neural tube by Shh, which has also been shown to be adaptive and regulates cell fate decisions through a described gene regulatory network . In thatSeveral lines of reasoning argue that adaptation in Activin/Nodal signaling follows a different mechanism, with consequences for cell fate. The signaling behavior of our system is qualitatively different, as there is no tradeoff between concentration and duration of strong signaling. Longer exposure to ligand does not increase the duration of signaling because the system has already adapted, and reactivating the pathway can only be achieved by pulsing rather than extending the duration of ligand exposure. Interestingly, there is a low level of baseline signaling following adaptation which is maintained by continued ligand exposure. Given the distinct classes of target genes we found responding to each aspect of the signal (baseline and adaptive pulse), this may demonstrate the principle that dynamic signals relay more information through a single pathway, with one set of target genes responding to signal duration, and another to rapid signal increase.In addition to the qualitative behavior being inconsistent with a system that integrates signal, like the neural tube, our quantitative data and mathematical modeling rule out the mechanism that would most naturally implement such a behavior, namely adaptation through degradation. First, our FRAP measurements show that the adapted state is kinetically distinct from the pre-signaling state, while the degradation model would predict a return to the same state. Second, we show analytically in Appendix 1 that a model based on upstream feedback cannot account for our dynamic measurements because in order to adapt through receptor degradation, the timescale for recovery must be slower than that for adaptation, which is not what we find in our pulsing experiments. It will be interesting to elucidate the genetic network that interprets adaptive Nodal signaling and to compare it with the one that interprets Shh.Our conclusions regarding signaling dynamics rely on nuclear localization of Smads as a proxy for signaling activity. The validity of this measure is supported by strong correlation between SMAD2 nuclear localization and pSMAD2 levels, as well as the fact that transcriptional activity of a number of direct targets mirrors nuclear SMAD4 both in this paper and in previous work . Althougb response where it allows cells to sense the rate of increase of environmental stress . The identity of these cells as pluripotent cells was confirmed via triple staining for pluripotency markers OCT4, SOX2, and NANOG. All cells were routinely tested for mycoplasma contamination and found negative.4 cells per cm2 and grown with rock-inhibitor Y27672 . This ensured uniform response to exogenous ligand and minimized the effect of secondary endogenous signaling. Unless otherwise indicated in the figures, experiments in The cell lines and their maintenance are described in https://github.com/idse/stemcells for further analysis (https://github.com/elifesciences-publications/stemcells). Live imaging was done on an Olympus/Andor spinning disk confocal microscope with a 40×, NA 1.25 silicon oil objective. Immunofluorescence data for FRAP experiments were done on an Olympus FV1200 laser scanning confocal microscope using a 100x NA 1.49 oil objective. To deal with cell movement recovery, curves were obtained by reading out a polygon defined by the interpolation between the initial bleach window and a manually defined polygonal nuclear mask in the final frame. Supplemental Information describes the mathematical model for nuclear localization of Smad4 which is shown schematically in For qPCR experiments, ESI017 cells were grown in 24-well plates. RNA was extracted using Ambion RNAqueous-Micro Total RNA Isolation Kit and cDNA synthesis was performed with Invitrogen SuperScript Vilo cDNA Synthesis Kit according to the manufacturer’s instructions. Measurements were performed with SYBR green and the primers in the For pulse and dose response experiments in For micropatterned colonies, we followed the protocol in Fixing and immunostaining of cells was done as described in All experiments were performed at least twice. Data shown are from representative experiments, except for FRAP data, where data from multiple experiments are pooled because of the difficulty of performing FRAP on a sufficient number of cells in a given experiment. Error bars on single-cell data  are standard error over cells. Full distributions are also provided to show cell-to-cell variability. Error bars on qRT-PCR data are over technical replicates due to the difficulty of quantitatively comparing biological replicates, likely owing to differences in culture densities, timing between seeding and ligand stimulation, and other culture variables, however, multiple biological replicates were performed in all cases. Error bars in micropatterning experiments are standard deviation over colonies. For single-cell imaging experiments, at least 600 cells were measured for each condition, for FRAP experiments at least 12 cells were measured for each condition, and for micropatterning experiments at least five colonies were analyzed for each condition.Supplemental information includes four figures, three movies, and an Appendix on mathematical modeling. In the interests of transparency, eLife includes the editorial decision letter, peer reviews, and accompanying author responses.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed.] Overall, the suggestion that TGFβ and BMP signaling kinetics  could be quite different is intriguing. The Discussion is excellently written, and appropriately emphasizes that a mechanistic understanding of the kinetics with which these pathways signal could greatly enrich both stem cell and developmental biology.Major critiques:1) SMAD4. The authors measure the activity of the TGFβ as well as BMP pathways by principally assessing a single metric: SMAD4 nuclear localization. However it is controversial whether SMAD4 localization as a single metric can accurately describe the total levels of TGFβ and BMP pathway activity. There are some reports that only a subset of TGFβ target genes require SMAD4 . If there is SMAD4-independent TGFβ signaling, it is therefore plausible that certain TGFβ target genes could still be transcribed  in the window of time when SMAD4 is not in the nucleus . If so, SMAD4 nuclear localization might only partially readout TGFβ signaling, which could therefore complicate the interpretation of the authors' data. Indeed, the authors show that upon ACTIVIN exposure for 5 hours , a number of TGFβ target genes  still continue to be transcribed , indicating the possibility that SMAD4 nuclear localization does not completely reflect the degree/extent of TGFβ signaling. Could the authors perform luciferase reporter assays of ACTIVIN-treated hESCs to examine whether TGFβ transcriptional responses are truly transient?We thank the reviewer for this suggestion. We have attempted to perform luciferase assays using two different TGFb responsive promoters described in the literature (3TP and CAGA), however, neither showed a strong response to Activin treatment in hESCs, indicating that there are likely cell-type specific cofactors necessary for these promoters. In agreement with this, we found by qPCR that the PAI1 gene, from which the 3TP promoter was derived, is also not induced by Activin treatment in hESCs. We agree with the reviewer that this is an important issue. We believe there are two possible, not mutually exclusive, interpretations of the gene expression data. (1) Most transcription is Smad4 dependent but low levels of Smad4 are sufficient for some genes. These genes are maintained by the baseline in Smad4 following adaptation and yield sustained transcription. (2) Only a subset of genes are Smad4 dependent, while others can be induced by Smad2 alone. Since Smad2 is more sustained, these genes are sustained. Of course, one of the explanations may be true for some genes and the other for other genes. We attempted to distinguish between these possibilities by using CRISPR/Cas9 to knock out Smad4 but we found that we were unable to maintain pluripotent Smad4-KO cells. We believe that the dataset presented accurately captures the fact that there are multiple different kinetic behaviors of downstream target genes. We have expanded our discussion to better reflect the different possible explanations.It would be preferable for the authors to perform live imaging of endogenously-expressed, labeled SMAD2/3 or SMAD1/5/8 proteins to examine their subcellular localization upon ACTIVIN or BMP treatment, respectively, but this is unreasonable to ask the authors to conduct in a short span of time. Barring those experiments, the authors might want to confine their conclusions to refer to "SMAD4-dependent TGFβ and BMP signaling" as opposed to "TGFβ and BMP signaling". For instance, would it be more accurate to specifically say that SMAD4-dependent TGFβ signaling  is transient and adaptive?We agree with the reviewer that it would be of interest to perform live cell imaging with Smad1 and Smad2, but that these experiments are beyond the scope of the present paper. We note that immunofluorescence data for the activity of these signal transducers are presented in the supplementary data. As suggested, we also now explicitly clarify at the beginning of the results that we are referring to SMAD4-dependent TGFb and BMP signaling, but as this language is cumbersome, we use the shorthand “TGFb and BMP signaling” throughout. Finally, we believe that the discussion we incorporated on the dynamics of Smad2 vs Smad4 (see previous answer) also highlights this important point.2) SMAD4 signal-to-noise ratio. Their live imaging data suggests that upon ligand stimulation, the increase in nuclear SMAD4 is modest . This is rather surprising, because one might anticipate a massive change in SMAD4 levels is needed to drive large transcriptional changes. The modest SMAD4 signal-to-noise ratio also raises questions about the authors' subsequent and quite detailed analysis of temporal dynamics, adaptation and so on. Why is the signal-to-noise ratio so modest? One possibility is that there are high nuclear SMAD4 levels in the steady-state , perhaps because the authors' hESCs are grown in mTeSR1 , which contains 2 ng/mL of TGFβ1 , and would be expected to lead to some level of basal nuclear SMAD4. What if the authors transiently pulsed their hESCs with a TGFβ inhibitor before performing the various ACTIVIN and BMP stimulations, would this reduce their background and thus enhance the signal-to-noise ratio?We agree with the reviewer that the measured changes in Smad4 are likely smaller than the increase in the active Smad complexes which mediate transcription. Background stimulation from the TGFb1 in mTeSR1 does not explain the small change as adding the Activin inhibitor reduced the baseline Smad2 levels but not those of Smad4. This can be seen in Figure 1—figure supplement 1G, where the data are scaled so that the levels with SB are 1. The higher levels of SMAD2 compared to SMAD4 prior to Activin treatment show that SB reduces these baseline levels. We believe that the relatively small increase in nuclear Smad4 results from the fact that Smads are present in the nucleus even in the absence of stimulation, as under all conditions Smads shuttle between the nucleus and cytoplasm. So that even when the pathway is inactive, there is some Smad in the nucleus . Also, background fluorescence which is present in both the nucleus and the cytoplasm will tend to bring the ratios closer to 1 both before and after stimulation, resulting in reduced fold changes. In any event, the nuclear to cytoplasmic ratio will be a monotonically increasing function of the total Smad4 in the nucleus, and so is a suitable reporter for Smad levels. We chose to use this ratio instead of absolute levels as it tends to remove noise associated with variations in Smad expression, cell size, and imaging artifacts, and we have found empirically that it is a more reliable and reproducible metric for signaling. We point out that the peak to baseline signaling ratio is not the same thing as signal to noise, which would be either of those levels relative to the standard deviation around that level. The significance of the difference between the two signaling states would be best captured by a statistical test such as Kolmogorov-Smirnov and the differences before and after stimulation are highly significant.Minor critiques:1) Figure 1H-J should be more clearly labeled and explained.We have substantially expanded the discussion of the FRAP experiments and split these off into a separate figure in order to clarify.2) "Error bars" erroneously merged into 1 word .This has been corrected.3) Data in the Nemashkalo et al., 2017, paper (by the same authors) seems to already suggest that BMP4 leads to sustained SMAD4 signaling, therefore it seems appropriate for Heemskerk et al. to cite this earlier work, as their Figure 1 seems to be confirming-and extending beyond-this earlier paper.We have added this citation.4) There seem to be some strange artifacts in certain subpanels. For instance why does the orange line in Figure 3B  jitter at regular intervals? It makes sense that the blue lines in Figure 3B,E would jitter (as they might correlate with each step of the ligand concentration increase) but not the orange line in Figure 3B.We believe that these artifacts result from slight perturbations to the imaging due to the media replacement. Although we could remove these by smoothing, we prefer to present the data as is without manipulation. We have added a note to figure caption explaining these artifacts to avoid confusion.5) Similarly, in Figure 4B (red line: pulses), there seem to be discontinuous spikes in SMAD4 whenever the media is changed.See answer to point 4.6) The authors conclude that BMP4 induces sustained, whereas ACTIVIN induces transient, SMAD4 signaling, yet in Figure 4 they suggest that BMP4 might induce endogenous TGFβ signaling. One alternate interpretation of the authors' data is that maybe BMP4 itself induces a transient SMAD4 response, but that by secondarily inducing TGFβ signaling, this latter wave of TGFβ might lead to sustained SMAD4.To exclude this possibility we have examined treatment with BMP together with a TGFb inhibitor and Activin together with a BMP inhibitor. These data support our conclusion that BMP signaling is sustained while Activin signaling is transient .7) Another oddity is in Figure 3C. If hESCs sense the absolute concentration of BMP4 ligand, one would expect that at low levels of BMP, they would respond weakly and at higher levels of BMP, they would respond strongly. Yet in Figure 3C, at the 2-3 hr timepoint, the "ramp" cells  express HAND1 mRNA almost as highly as the "step" cells . The only other interpretation I can think of is that maybe the low BMP4 levels in the blue line (at 2-3 hrs) are super-threshold already.We thank the reviewer for pointing this out, and we discovered an error in our previous data – the earlier ramp was performed in steps of 1 ng/ml to 10 ng/ml, whereas we intended to use data from a ramp to 3 ng/ml in steps of 0.3 ng/ml. This slower ramp does show a slightly slower increase, particularly in the SMAD4 signaling. Nonetheless, the reviewer is correct that the ramp reaches the levels of the step quickly. The explanation for this is that the BMP dose response  shows that there is a relatively sharp threshold in BMP signaling over which full activation is achieved. This agrees with our previous data , as well as from other labs who have suggested that BMP responses are close to binary . Thus, it only takes a few steps in the ramp to reach full activation of the pathway. We note that the dose of BMP will have a graded effect on integrated signaling due to the decay in time of signaling at low doses . We have revised our discussion of this experiment to reflect this, and of the BMP dose-response to better highlight the sharp transition between off and on.Reviewer #2:[…] Overall, this study brings a quantitative perspective to a central developmental pathway, and should help to further strengthen a growing sense that dynamics are critically important in the behavior of many developmental signaling pathways. It suggests that controlling ligand dynamics could facilitate directed differentiation protocols. It should therefore be of broad interest, and we support publication.Below, we describe several issues that could be addressed to strengthen the work in a revised manuscript:Major comments:Figures 1 and Figure 1—figure supplement 1F together show that BMP4 triggers a more stable nuclear localization of BMP-responsive Smad1, while activin results in adaptive nuclear localization of Nodal-responsive Smad2/3. However, the cross-pathway dynamics are unclear. Does BMP4 affect Smad2/3 and does Activin/Nodal affect Smad1, and if so, with what dynamics? This control is important to support the authors claim that the difference in dynamics results from distinct pathway-specific transducers.We thank the reviewer for this suggestion. To address this issue, we have performed additional experiments in which each pathway is stimulated while the other is inhibited. The results show that BMP has no effect on the dynamics downstream of Activin while Activin/Nodal signaling has a small negative effect on the response to BMP so that inhibiting Activin during BMP signaling gives a stronger response. These data are now included as Figure 1G,H.Figure 2, B and D, present gene sets that show qualitatively different dynamic response to Activin. The authors suggest the interesting possibility that these sets have different sensitivities to Smad4. However, an alternative explanation could be a difference in RNA half-lives, with the monotonic responses in Figure 2D resulting from stable mRNAs that accumulate over time, effectively integrating the response. Is it possible to discriminate between these explanations (e.g. by examining nascent or intronic RNA), or at least discuss these two possibilities?To examine this possibility, we have performed gene expression experiments in which we inhibited Activin/Nodal signaling and examined target gene expression in time. If the differences in gene expression dynamics were due to differences in mRNA half-life, we would expect that transcripts that are stably induced in response to Activin stimulation would persist following pathway inhibition. However, we find that targets including Lefty, Nodal, and Nanog which are activated in a sustained manner rapidly decline upon inhibition of the pathway with the small molecule inhibitor SB431542. Thus, different mRNA stabilities cannot explain our gene expression results. This data is now included in Figure 3—figure supplement 1G and discussed in the text. In addition, while not impossible, it would be surprising if the different transcriptional dynamics of HAND1 in response to BMP4 vs Activin in Figure 3C and of Noggin in the supplementary data for Figure 3 were due to differential modulation of RNA life time as it is the same transcript being induced. The more natural interpretation is that this directly reflects SMAD4 dependent transcriptional activity.Figure 3 presents an elegant comparison between ramps (staircases) and steps of BMP and Activin. The results are striking. However, two issues complicate interpretation. First, the ramp and step differ in total integrated signaling over time, making it difficult, from this single experiment, to disentangle the roles of ligand concentration and dynamics. The simplest way to address this might be to also include a step of half the amplitude, or to do a ramp at double the slope.We now include data on a faster ramp, as suggested, and find that the response is still strongly reduced from step stimulation, however it is stronger than the slower ramp. These data support our conclusion that the time-derivative of concentration is the key determinant of the response rather than the integrated signal and are now presented in Figure 4G,H. We also point out that signaling responses are coincident by the end of the experiment, so that integrated signaling response to the ramp will never catch up with integrated signaling response to step, even if it were allowed to run longer to get to the same integrated ligand exposure.Second, based on Figure 1 and Figure 1—figure supplement 1B-C, which shows dose-dependent responses to BMP concentration, we would expect the ramp response in Figure 3B to depend on ligand dose and therefore to grow slowly over time. Why does it step up so rapidly?The BMP dose response  shows that there is a relatively sharp threshold in BMP signaling over which full activation is achieved. This agrees with our previous data , as well as from other labs who have suggested that BMP responses are close to binary . Thus, it only takes a few steps in the ramp to reach full activation of the pathway. We have revised our discussion of this experiment to reflect this, and of the BMP dose-response to better highlight the sharp transition between off and on.In Figure 3, rate responsive behavior is demonstrated by comparing a step to a ramp. Does the Nodal pathway act as a quantitative sensor of the rate of increase of Activin, or does it exhibit some kind of rate threshold? This could be answered by showing how response depends quantitatively on the ramp slope. A mathematical model of the adaptation process could help to provide insight into the expected behavior here.We now include data showing intermediate rates of increase which yield intermediate responses in the Smad4 signaling . We also note that the supplement includes a model of the adaptation process that generates behavior consistent with these experiments .Rate-responsiveness in other systems. Work in bacteria  showed similar rate-responsive behavior in the sigB stress response system, where two kinds of stresses activate sigB in different ways, with one input showing rate-responsive behavior, assayed by temporal "ramps" of different slopes. In that system the mechanism of rate responsiveness has been determined. It would be interesting to discuss the similarity (and differences) in signal processing behaviors between these very different biological systems.We now cite this paper in the discussion, however, as our focus is on adaptation in developmental signaling, we feel a detailed discussion of this paper is beyond the scope of our manuscript.In Figure 4, the authors suggest that during development the moving Smad4 signaling front is responsible for the activation of Brachyury expression. Although strong evidence for adaptative and rate sensing responses to Nodal/ActivinA ligands is provided for sparse hESCs cultures, the micropattern experiment cannot distinguish between a rate sensing mechanism and a pure concentration sensing mechanism. Even though Brachyury responds with higher expression to Activin pulses in sparse hESC cultures, these two experimental conditions differ in both the time scales and the number of pulses cells could perceive  per hour, and traveling at least 150 µm to fully cover the spatial domain of brachyury expression. Since no data on dynamics of endogenous Nodal expression is provided, it remains unknown if, over time, ligand concentration is locally increasing (or oscillating) on a timescale relevant to Brachyury induction. As result, in the micropattern, in which responses to BMP and endogenous Nodal co-occur, it is unclear if cells are sensing absolute ligand concentration and/or a rapid increase in ligand concentration. Experimentally determining Nodal dynamics in micropatterns remains difficult, and perturbing its dynamics would require significant cell line engineering. Thus, an alternative avenue to support the claim that in the gastrulating human embryo expression of fate determinants results from rate sensing of ligand increments could be to computationally compare whether patterning triggered by adaptation to Nodal achieved by rate sensing rate qualitatively or quantitatively differs from patterning the mesoderm through sensing absolute ligand concentrations. What new or different emergent properties result from sensing rates as opposed to just concentrations?While we agree in principle that these data in isolation are also consistent with sensing ligand concentration, we note that this experiment does provide an important test, and could have resulted in data disproving our model. The most straightforward hypothesis would be that a static gradient of Nodal signaling is formed, peaks in the region of future mesendoderm, and cells read this gradient. Had this been true, it would have shown that the rate of increase is not relevant to the patterning that occurs. Our data disproved this hypothesis. The fact that there is a rapidly moving wave of signal activation in micropatterned colonies together with our experiments in Figures 1 – 3 (now 1 – 5) that demonstrate that cells respond to the rate of Activin/Nodal increase strongly suggest that cells in micropatterning colonies are also responding to the rate of increase. We agree that direct demonstration would require measurement of Nodal protein dynamics but believe this to be beyond the scope of this manuscript. We also note that the consequences of reading rate of increase during patterning were modeled theoretically in Sorre et al., 2014.Relation to other dynamic encoding systems: This study provides an important advance in understanding the role of dynamics in core mammalian signaling systems. But the relationship to other work on dynamic signal encoding in signaling pathways, as reviewed for example in Purvis and Lahav (2013), Behar and Hoffmann (2010), etc. is minimal. Specifically, it would be useful to know which aspects of the Nodal system in hES resemble or differ from phenomena observed in other pathways or other cell types. For example, different target programs are activated by sustained vs pulsatile activation of p53 and Notch, among other pathways. Also, a recent report  studied the response of C2C12 cells to TGFb ligands, which belong to the Activin/Nodal family and are also transduced by Smads2/3, and showed that the pathway senses fold changes. How does this fold change detection relate to the adaptive rate-responsive behavior observed here? Discussion of these issues would help to connect this study to the broader literature and unify results from multiple studies.We now cite and briefly discuss the work on p53 and NFkB mentioned above, however, as our focus is on adaptation in developmental signaling, we feel a detailed discussion is beyond the scope of our manuscript. Our results on ramps and pulses are not consistent with fold change detection and so we do not discuss this in the paper.Minor Comments:In Figure 2, please include the base of the log on the y axis: is it 2, E, or something else?It is base 2. We have now clarified this in the figure legend.In Figure 1E there is an orange line near the y-axis. It remains unclear if this line represents the fact that after photobleaching Smad4 fluorescence does not recover to the original amplitude.The orange line represents data from the photobleaching experiment. The drop near the y-axis is the actual bleaching event. We have now clarified this point in the figure legend.Reviewer #3:[…] Perhaps the biggest suggestion I can make with regards to the work is that it is a bit too dense and hard to grasp. Overall the work follows three parts: 1) An analysis of mechanism for adaptation using innovative combination of FRAP and parameter identification of ODE model. 2) analysis of gene expression dynamics response to dynamic SMAD4, and 3) implication of the differences in response dynamics on overall self-organization patterns in the in-vitro gastrulation model. I will refer to these as parts 1-3 below for brevity.I am not sure why the authors restricted themselves to only four figures, although I can make an educated guess;). To make the paper easier to follow I strongly recommend to take advantage of eLife lack of restriction on length and number of figures and use the space to elaborate much more about the work.In part 1 the author only use two paragraphs on main text to explain a lot of stuff. To understand the adaptation and the FRAP experiments one has to think about two different math models that use a parameter fitting procedure to identify underlying mechanisms. The material is mostly in the supp text, but supp text should not replace main text rather provide more details for completeness. I recommend to move some of the material from supp mat to the main text, explain the FRAP procedure, show the alternative fits for different parameters etc. This part can easily take 2-3 figures.We thank the reviewer for these suggestions. We have now expanded the paper to 6 figures, including expanding the discussion in the FRAP section with material from the supplement.Similarly, part II seemed rushed. The authors show how some genes follow SMAD4 dynamics and some do not. But the sparse text doesn't allow them to go into details, what is different about these genes? Is it RNA halflife? Even without additional experiments, few simple models would be very helpful to understand Figure 2A-D. I am not sure I got the point of panels 2EF, so either explain that in more details or remove those. The different gene expression response to different stimuli regimes  is very nice with its demonstration of the role of SMAD4 dynamics.We have now included additional data on gene expression that rule out differences in RNA half-life (see response to reviewer 2 above). We have also expanded the discussion to better explain the gene expression data in Figures 2EF .Finally, the last part is very short and descriptive, The author measure different SMADs over space and time, show that there are different responses and that these change gene expression. I was left a bit confused as to why these differences arise? What aspect of self-organization is in play to cause these patterns. The fact that all these results are described in a single paragraphs of 322 words might be part of the problem.We have now split this into two figures and expanded the explanation. We hope it is clearer now.Minor Comments:1) The use of SMAD4 signaling in figure titles should be replaced with y-axis label saying SMAD4_{nuc}We now use the label Smad4 (N:C) throughout to indicate that what we are measuring the ratio of nuclear to cytoplasmic Smad4.2) The cartoon in Figure 2 is confusing, why don't all the no sequestered dots recover?Fluorescent proteins which have been bleached never recover regardless of sequestration. In the cartoon, the non-sequestered fluorescent dots simply re-equilibrate between the nucleus and cytoplasm while the sequestered ones remain in place. We have expanded the discussion of this figure and hope it is now clearer.


Magnaporthe oryzae and Pseudomonas syringae. Notably, JA may act as a core signal in the phytohormone signaling network.Plant hormones play central roles in plant growth, developmental processes, and plant response to biotic and abiotic stresses. On the one hand, plant hormones may allocate limited resources to the most serious stresses; on the other hand, the crosstalks among multiple plant hormone signaling regulate the balance between plant growth and defense. Many studies have reported the mechanism of crosstalks between jasmonic acid (JA) and other plant hormones in plant growth and stress responses. Based on these studies, this paper mainly reviews the crosstalks between JA and other plant hormone signaling in regulating the balance between plant growth and defense response. The suppressor proteins JASMONATE ZIM DOMAIN PROTEIN (JAZ) and MYC2 as the key components in the crosstalks are also highlighted in the review. We conclude that JA interacts with other hormone signaling pathways  to regulate plant growth, abiotic stress tolerance, and defense resistance against hemibiotrophic pathogens such as  Under multiple environmental stresses, plant hormones allocate limited resources to respond to the most serious stress  and deveArabidopsis. In Arabidopsis, at least two pathways are responsible for JA biosynthesis, namely, the α-linolenic acid (18:3) initial octadecane pathway and hexadecatrienoic acid (16:3) initial hexadecane pathway , auxin , cytokinin (CK), brassinosteroids (BRs), abscisic acid (ABA), ethylene (ET), jasmonic acid (JA), salicylic acid (SA), and strigolactone (SL). In recent decades, JA biosynthesis has been widely investigated in monocotyledons and dicotyledons, especially in  pathway . In thes pathway .JA is widely distributed in plants as a natural plant growth regulator . The impCOI1 to be stabilized  is assembled into SCF E3 ubiquitin ligase complex SCFabilized . As an Fignaling . In the JAZ protein contains two conserved protein–protein interaction domains, ZIM and Jas . The JasIn contrast to the positive regulation of JAZ in plant growth, MYC TFs  negatively regulate gene expression in cell cycle, thereby inhibiting plant growth . As the COI1 protein, JAZ, and MYC constitute the core signal transduction mechanism of JA signaling and have been proven to be the intersection of other signal transduction pathways under various stresses . The JAZWhen JA–Ile content is high in rice, OsCOI1 interacts with OsJAZ to form a complex, JAZ protein is degraded, and the transcription of OsbHLH148 in the JA signal module is rapidly activated to induce drought tolerance. High levels of JA–Ile induce OsMYC2 to selectively bind to the G-box-like motif in the promoter region of OsJAZ10 to activate transcription activity, induce the expression of early JA-responsive genes, and thereby resist bacterial pathogens .COI1, which binds to JAZs for ubiquitination and degradation through the 26S proteasome pathway. The competitive binding and degradation of JAZ repressors can further release the downstream TFs such as MYCs, resulting in the activation of JA responses by MYCs  is kept very low plants but can be rapidly activated in response to various stresses such as insect feeding or wounding. Then JA signaling is perceived by JA receptor COI1, an important component of SCF by MYCs .To sum up, the three main core components of JA signaling play an important role in plant growth, development, and response to biotic or abiotic stresses. When exogenous JA or extreme stress is applied, the concentration and application time may affect the transcriptional activities of different components in the JA signal module. Therefore, according to the JA metabolic pathway under stress conditions, corresponding stress-tolerance breeding may be developed to improve crop resistance in agriculture.The crosstalk between plant hormones is the core of plant stress response . JA doesASA1) and auxin content, so JA regulates the biosynthesis of auxin and further regulates the expression of JAZ1 and root growth. On the other hand, JA induces the formation of a complex of COI1 and JAZ and leads to the degradation of JAZ, thereby activating the transcriptional activities of MYB21/MYB24 and inducing flower development. Notably, MYC2 inhibits the expressions of PLETHORAs (PTL1 and PTL2) and counteracts the auxin–TIR–AUX/IAA–ARF signaling, so as to regulate root growth  and induces its expression, thereby resisting the infection of necrotrophic pathogens and hemibiotrophic pathogens   . TherefoOsDI1 and OsDWARF at the early and late stages of BR biosynthesis, respectively, and anthocyanin accumulation and activates defense response. On the other hand, high concentration of BR activates BR signaling cascades including BR receptor BRI1, BR-related kinase BAK1, and BR-related TFs to induce the expressions of downstream genes such as BES1 and BZR1, thereby regulating plant responses to abiotic stresses  and further inhibits JA biosynthesis as well as the activities of MYB21 and MYB24 , DAD1, allene oxide cyclase (AOC), LOX2, and AOS1 are induced -CBF transcriptional cascade signaling pathway plays a central role in plant cold stress response . ICE1 an induced , and bio induced  and JA–G induced .A. thaliana, and the increase of OPDA content is related to the decrease of stomatal aperture and improved drought resistance  as well as MYC2 , AvrB, and HopZ1a. The most widely known example of JA-mediated plant–pathogen interaction is regulated by COR. COR is an active substance similar to JA–Ile in structure and function, with two moieties including coronamic acid and coronafacic acid (P. syringae infection (Many pathogenic variants of hemibiotrophic bacteria cic acid . On the cic acid . On the nfection . In addinfection . Therefonfection .Arabidopsis (Arabidopsis protein RPM1-INTERACTING PROTEIN 4 (RIN4) appears to be involved ; among them are main defense responses . The pla2+ and the reaction of kinase-TF-downstream genes. At present, there are still a lot of questions or gaps in understanding the crosstalks between JA and other hormones in plant stress responses, especially in the perception of multiple environmental signals. With the development of protein interaction omics, the complex protein interaction network may provide more clues to the understanding of complex stress signaling perception and protein complex-mediated plant hormone crosstalks.In recent decades, although the JA signaling pathway has been extensively investigated, the current understanding of its role in different environmental stresses is limited, due to the complex networks and crosstalk between multiple stresses and multiple signaling pathways. So far, the molecular mechanism of JA signaling in stress responses remains elusive. Compared with unidentified components, the identified components in plant hormone signaling pathways are limited. In addition, so many receptors and kinases exist in the cell membrane, and different environmental stresses may activate multiple enzymes, with a series of activation of secondary messengers such as CaThe plant hormone signaling network is complex and changeable. Although “omics” methods have achieved global analyses of gene expression and protein spectrum changes to some extent, the data still fail to fully understand the dynamic spatial and temporal processes of plant hormone signaling networks in the balance between plant growth and defense resistance . MoreoveJY, GD, CL, LL, GH, YZ, and CW conceived the topic. GD, CL, and LL collected the data about jasmonate acid and crosstalking of JA and other plant hormones. GH, YZ, and CW collected the data about abiotic and biotic stresses. JY performed the network analysis and worked with other co-authors to complete the manuscript.The work was supported by grants from the national Key Research and Development Program of China (2016YFD100600) and NSFC (31860483 and 31400073) and Program for Innovative Research Team  in the University of Yunnan Province and State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan at Yunnan Agricultural University.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Hepatozoon parasites (Apicomplexa: Adeleorina) using both microscopic examination and sequencing of partial 18S rRNA sequences. Positive samples were compared to published sequences in a phylogenetic framework. The results indicate that genets can be infected with Hepatozoon felis. A Cape fox was infected with Hepatozoon canis, whereas the sequence from an infected rodent fell within a group of parasites primarily recovered from other rodents and snakes.Samples of gerbils and their potential predators were screened for the presence of  Despite their obviously important role in ecosystems, information about the diversity and distribution of many parasite groups is still scarce. Molecular screening for parasites has the potential to greatly improve this knowledge, but has lagged behind advances in assessing free-living organisms  in North Africa. It is clearly essential to screen more geographic regions for Hepatozoon prevalence, to improve estimates of diversity, to assess potential trophic pathways and to identify which genetic lineages can be found in diverse hosts. When this can be combined with microscopic assessments, there is an added benefit that morphological variability in gamonts can be assessed and parasitaemia levels recorded.Hepatozoonosis is a vector-borne infectious disease caused by intracellular haemogregarine parasites (Apicomplexa: Adeleorina), which has been particularly studied in domestic dogs and cats owing to their veterinary importance Baneth . The comt Baneth . TherefoGerbilliscus leucogaster) from three neighbouring farms in the Free State province, South Africa (27°50’ S 26°03’ E), were screened for Hepatozoon using PCR amplification and sequencing of a partial 18S rRNA fragment typically used to detect and identify these parasites  found on R34, close to Hoopstad, Free State province (27°43’11.8” S 25°48’50.4” E); one adult female small-spotted genet (Genetta genetta) found close to Molepo Dam, Limpopo province; and one adult male slender mongoose  found close to Blouberg Nature Reserve, Limpopo province. Molecular methodologies followed standard procedures  from 43 Bushveld gerbils  and Bayesian inferences (BI) were used to estimate phylogenetic relationships. ML analysis was performed using the software PhyML 3.0  from Mauritania (one nucleotide difference). The single genet sample was also infected, and this sample is a sister taxon to a sequence from a parasite identified as H. felis from a domestic cat. Although various studies using microscopy have identified genets as a host for Hepatozoon  parasites not only common in felids, but here identified in a member of the family Viverridae. Only one of the gerbils was infected (sample code G13H), and this sample falls within a clade comprising samples from various small mammals, but also snakes (Based on the molecular screening, three samples were positive, and all were found to be infected with patozoon . Overallpatozoon . The sino snakes . This iso snakes . Examinio snakes .Hepatozoon infections. Firstly, this is the first confirmation that genets can be infected with what is apparently H. felis, based on the molecular data. Secondly, we confirm the presence of H. canis in the Cape fox in South Africa, with a genetic lineage very similar to that found in foxes in North Africa. Finally, the rodents tested were mostly negative, unlike other studies that have found a high prevalence in rodents. The single positive sample, the first sequenced from this host species, showed a clear relationship with other Hepatozoon species from other rodent hosts. Thus, the major clades (Hepatozoon in tortoises from South Africa have recently revised taxonomic conclusion (e.g. Cook et al. These results allow us to draw several new inferences regarding r clades  are rein