Allergen, chemical stimulation and viral infection can each trigger the production of TSLP from epithelial cells, resulting in airway inflammation and airway hyperresponsiveness, leading to the symptoms of asthma. Genetic variations, including TSLP single nucleotide polymorphism rs1837253, result in the onset of asthma, and high levels of TSLP and Th2 cytokines in the lung are observed in the airway in asthma patients. TSLP and IL‐33, a member of the IL‐1 family that drives type 2 responses with increased production of cytokines, including IL‐4, are highly produced in the bronchial epithelium, endothelial cells, mast cells, neutrophils, fibroblasts and submucosa, causing airway obstruction. IL‐4 increases permeability of the airway epithelium by reducing levels of filaggrin and adhesion molecules, and it also increases the expression of IL‐33 and TSLP, leading to the promotion of a Th2 response.Atopic dermatitis (AD) is a chronic disease characterised by skin inflammation and pruritis. AD is heterogenous with multifactorial pathogenesis, including genetic predisposition as well as environmental and immunological factors. Genetic variants of TSLP affect the severity and persistence of AD, and DNA demethylation of a specific region of the TSLP promoter contributes to TSLP expression in skin lesions of AD patients and perturbed expression of filaggrin. Histamine, a key mediator of allergic diseases, was reported to upregulate TSLP expression in human keratinocytes and nasal epithelial cells by binding to the histamine H4 receptor, suggesting that histamine can promote TSLP‐dependent atopic disease.3The role of TSLP in type 2 immune responses in allergic diseases, including asthma, has been extensively studied, and recent studies have revealed additional roles for this cytokine in infectious diseases, cancer, fat metabolism and inflammatory diseases.+ T cells. One study reported that TSLP does not affect the control of primary influenza infection or viral‐specific CD8+ T‐cell responses. Another study showed that TSLP is required for the expansion and activation of virus‐specific effector CD8+ T cells in the lung during primary infection but concluded that this was due to an indirect effect based on TSLP‐induced IL‐15 production by CD11b+ inflammatory DCs, which in turn acts on CD8+ T cells, rather than from direct effects of TSLP on CD8+ T cells. Studies using adoptive co‐transfer models of wild‐type and −/−Crlf2 TCR transgenic cells also differed related to the actions of TSLP on CD8+ T cells, with TSLP either enhancing primary CD8+ T‐cell responses or limiting their responses during primary influenza infection.−/−Crlf2 mice vs. co‐transfer models) and virus strains used . Recently, TSLP was reported to limit the memory CD8+ T‐cell recall response against secondary infection with influenza virus.During airway infection with influenza virus, pulmonary epithelial cells produce inflammatory cytokines, including TSLP, that alter the immune response in the lungs. In primary infection with influenza virus, there are conflicting reports regarding the role of TSLP on CD8Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which causes COVID‐19, is associated with cytokine storm characterised by Th1 and Th2 inflammation. Interestingly, TSLP was also induced in COVID‐19 patients, and high TSLP levels correlated with greater severity of COVID‐19. Thus, TSLP might promote this disease, and targeting TSLP is worthy of further evaluation as a possible therapeutic strategy to inhibit Th2 responses in COVID‐19 patients.+ T cells. In contrast, other studies have suggested that TSLP can have tumour‐suppressive activity in breast cancers and cutaneous T‐cell lymphoma.TSLP has also been reported to have roles in cancer.41), asthma control and health‐related quality of life compared with placebo.1, and fewer hospitalisations and emergency room visits compared with the placebo group , was approved by the US Food and Drug Administration in 2021 as an add‐on maintenance treatment for patients aged ≥12 years with severe, uncontrolled asthma. A phase 2 trial  showed that tezepelumab reduced clinically significant asthma exacerbations by up to 71% and improved prebronchodilator forced expiratory volume in 1 s (FEVGiven the evidence for multiple functions of TSLP in diseases beyond allergy, it is possible that tezepelumab may have beneficial impact on some of these diseases as well, and further study is warranted regarding targeting TSLP in a broader range of conditions.The authors declare no conflicts of interest.


A) receptor complex plays a central role in the modulation of anxiety. Conditioned fear and anxiety-like behaviors have many similarities at the neuroanatomical and pharmacological levels. The radioactive GABA/BZR receptor antagonist, fluorine-18-labeled flumazenil, [18F]flumazenil, behaves as a potential PET imaging agent for the evaluation of cortical damage of the brain in stroke, alcoholism, and for Alzheimer disease investigation. The main goal of our study was to investigate a fully automated nucleophilic fluorination system, with solid extraction purification, developed to replace traditional preparation methods, and to detect underlying expressions of contextual fear and characterize the distribution of GABAA receptors in fear-conditioned rats by [18F]flumazenil. A carrier-free nucleophilic fluorination method using an automatic synthesizer with direct labeling of a nitro-flumazenil precursor was implemented. The semi-preparative high-performance liquid chromatography (HPLC) purification method (RCY = 15–20%) was applied to obtain high purity [18F]flumazenil. Nano-positron emission tomography (NanoPET)/computed tomography (CT) imaging and ex vivo autoradiography were used to analyze the fear conditioning of rats trained with 1–10 tone-foot-shock pairings. The anxiety rats had a significantly lower cerebral accumulation  of fear conditioning. Our rat autoradiography results also supported the findings of PET imaging. Key findings were obtained by developing straightforward labeling and purification procedures that can be easily adapted to commercially available modules for the high radiochemical purity of [18F]flumazenil. The use of an automatic synthesizer with semi-preparative HPLC purification would be a suitable reference method for new drug studies of GABAA/BZR receptors in the future. Clinical studies have demonstrated that the γ-aminobutyric acid type A (GABA Anxiety disorders, which are characterized by excessive worries, motor tension, and fatigue, can be clinically subdivided into several categories, including generalized anxiety disorder, panic disorder, social anxiety, agoraphobia, post-traumatic stress disorder, and obsessive-compulsive disorder ,2,3,4,5.Generally, the goal of fear and anxiety research is to identify the neurobiological mechanisms of brain pathogenesis, and understand how to treat the potentially devastating effects of anxiety disorders in humans . NumerouA receptors are widely distributed in the brain. The majority of GABAA receptors are composed of two α subunits, two β subunits, and one γ subunit in numerous combinations, which may confer different physiological and pharmacological activities -flumazenil, a confirmed benzene diazo salt-specific antagonist, began in 1981, and the compound is widely used in clinical practice since 2008 [18F]flumazenil, with an identical structure to [11C]flumazenil, was shown to have pharmacokinetic, peripheral metabolism, and PET imaging characteristics similar to [11C]flumazenil in a cynomolgus monkey [18F]flumazenil PET has evolved to be one of the most useful radiopharmaceuticals for the PET imaging of GABAA receptors, with potential as a clinical tool for analyzing localization of the epileptogenic zone in pre-surgical evaluations of drug-resistant temporal lobe epilepsy (TLE), with excellent sensitivity and anatomical resolution or level ,25. Prepnce 2008 ,27,28,29s monkey ,31. flumazenil and applied the product for anxiety animal model in vivo neurologic imaging. We were able to exploit the gradient mobile phase of the high-performance liquid chromatography (HPLC) to enhance the purity of [18F]flumazenil, to achieve high yield radiochemical pure results, and use [18F]flumazenil for NanoPET/CT imaging and ex vivo autoradiography to characterize the distribution of GABAA receptors in a rat model of anxiety. We expect that these results will promote straightforward labeling with, and purification of, [18F]flumazenil, and provide more insight into the properties of GABAA receptors in vivo, and their relevance in anxiety disorders.This study automated the synthesis of [18F]flumazenil was produced from the nitroflumazenil precursor via a standard nucleophilic substitution fluorination reaction, as shown in 18F]flumazenil, with a radiochemical purity > 95% after radio-HPLC and radio-thin layer chromatography (TLC). In an amber glass vial, the radiochemical purity of [18F]flumazenil in 30% ethanol remained > 90% at 8 h after the end of synthesis (EOS) at room temperature  of 80 dB, and a foot-shock of 1.2 mA (US) administered for 3 s A. The beThe effect of the number of CS-US pairings was also elucidated. The rats exhibited high levels of freezing with successive foot-shock presentations, indicating a comparable level of learning during training. Thus, we settled on a 10-trial procedure to establish an animal model of anxiety. Inspection of individual behavioral data showed considerable variability within each group. Therefore, we selected the best responders for subsequent imaging and autoradiographic analyses.A receptor availability in fear-conditioned rats. In the autoradiograms of sections taken 30 min after injection of [18F]flumazenil, the specific localization of GABAA receptors in each rat brain was examined   B.A receptors in the brain, as imaged by [18F]flumazenil PET, is shown in 18F]flumazenil, each time frame was observed in 10 min in both fear-conditioned rats and normal rats.The regional distribution of GABAIndividual dynamic images were automatically co-registered to each rat brain region template. ROIs, including the prefrontal cortex, cortex, hippocampus, amygdala, and pons, were extracted from a set of previously constructed regions. Finally, time-activity curves were generated by projecting predefined ROIs onto the dynamic images .18F]flumazenil in the four target regions, and conversely for the fear-conditioned rats  on the distribution of [18F]flumazenil were evaluated, using ex vivo autoradiography and pre-treatment with 0.01–10 mg/kg diazepam for NanoPET/CT in vivo imaging. In ex vivo autoradiography, treatment with diazepam displayed a marked decrease of [18F]flumazenil accumulated in all brain regions . Pre-treatment with higher concentrations of diazepam resulted in fewer GABAA receptors being available for binding, and [18F]flumazenil was eliminated from the brain at a rapid rate , and the procedure has been difficult to automate, resulting 18F radioactive decay [18F]flumazenil was 90 min, and the obtained [18F]flumazenil exhibited high radiochemical purity (radio-HPLC (>90%) and radio-TLC (>90%), in 18F]flumazenil.Previously, flumazenil was previously carried out using acetonitrile and water as the mobile phase [18F]flumazenil demonstrated good stability, maintaining a purity of up to 90%, after 8 h in ethyl acetate:ethanol (80/20) at room temperature  [A receptor availability using [18F]flumazenil PET in a rat model of anxiety. We found a significant reduction in GABAA receptor availability in the amygdala, prefrontal cortex, cortex, and hippocampus in fear-conditioned animals. Our rat autoradiography results also supported the PET imaging findings.In the present study, we used flumazenil PET to visualize GABAA receptor distribution in vivo in an animal model of anxiety. By utilizing [18F]flumazenil NanoPET imaging, we observed a global reduction in GABAA receptor availability in rats expressing contextual fear compared to controls. Furthermore, the specific binding ratios of [18F]flumazenil were significantly reduced in the brain regions of the prefrontal cortex, cortex, amygdala, and hippocampus in fear-conditioned rats, which clearly depicts the effects of fear conditioning on GABAA receptors. Our findings have demonstrated that the specific binding ratios of the GABAA receptor are profoundly influenced by brain regions, such as the amygdala, prefrontal cortex, cortex, and hippocampus, suggesting that these brain regions may be involved in processing and storing conditioned fear memory.This is the first study to utilize flumazenil, indicating that the structural modification of [18F]flumazenil results will show in high affinity for GABAA/cBZRs  fluoride was produced via the 18O  18F reaction on an enriched [18O]water target, and irradiated with a proton beam (17 μA) using an EBCO TR30/15 cyclotron . After irradiation, the nucleophilic substitution reaction based on [18F]F−/H2[18O]O was transferred to a semi-automated TRACERlab FX-FN synthesis module . Aqueous [18F]fluoride/H2[18O]O was passed through an anion exchange cartridge   preconditioned with K2CO3. The fixed [18F]F− was eluted from the cartridge with a solution of Kryptofix 2.2.2 and K2CO3. After azeotropic evaporation, 10 mg of nitroflumazenil in 1 mL of dimethylformamide (DMF) was added to the [18F]F−/Kryptofix 2.2.2/K+ complex. Fluorination proceeded for 15 min at 150 °C. The reaction mixture was then cooled to 50 °C, diluted with 2 mL of water, and passed through a Waters Alumina-N cartridge for solid phase extraction. Then, [18F]flumazenil was purified via solid phase extraction and passed through the Waters Alumina-N cartridge. [18F]flumazenil was purified using semi-preparative HPLC  . The product was collected and its radiochemical purity and stability were measured using radio-HPLC (Waters and Aligent 1100 and the Perkin Elmer’s Radiomatic 150 TR) and radio-TLC (BIOSCAN Autochanger 3000 type) .All of the chemicals were purchased from commercial vendors and were of pharmaceutical grade. [18F]flumazenil solution was performed using HPLC and radio-TLC. An Agilent series 1100 HPLC  equipped with ultraviolet and radioactivity detectors (Bioscan Flow count and the Perkin Elmer’s Radiomatic 150 TR) was used to analyze the radioactive [18F]flumazenil, with the mobile phase (H3PO4/acetonitrile = 70:30) delivered at 1 mL/min. The identity of [18F]flumazenil was confirmed by comparing the retention times with those of unlabeled flumazenil. TLC was carried out on a Merck Si-60 plate, and an ethyl acetate:ethanol (80/20) solution was applied to develop the TLC plates . The stability was investigated, and the radiochemical purity of [18F]flumazenil was monitored while it was stored in 30% ethanol at room temperature for 2, 4, 6, and 8 h.Quality control of the final injectable flumazenil, via the lateral tail vein, 2 h after the fear-conditioning experiments. The animals were sacrificed by the administration of carbon dioxide 30 min after the injection. The brains were rapidly removed, placed in optimal cutting temperature compound (OCT) embedding medium, and frozen with powdered dry ice. The brains were cut into 20 μm thick sagittal sections on a cryostat , thaw-mounted on gelatin-coated microscope slides, and air dried at 25 °C. The slides containing the brain sections were exposed to a film  in an autoradiographic cassette for 72 h. The optical densities of the autoradiograms were determined with an image analysis system using the FLA-5000 and MultiGauge ver 2.0 software .The fear-conditioned and control rats (three rats per group) received an injection of 37 MBq/200 μL [The specific binding ratio in all target regions  could be obtained using the pons as a reference region. Specific binding ratios were calculated using the following equation: (target region–reference region)/reference region.18F]flumazenil (37 MBq/200 μL) via the lateral tail vein. The apparent behavioral status and vital signs of the rats were monitored during the scan to adjust for anesthesia. The temperature of the animals was maintained at 37 °C. For the PET study, the rats were positioned in a NanoPET/CT PLUS system , using the dynamic mode for data acquisition from 0 to 60 min .In an independent experiment, rats were transported to an imaging facility 2 h after receiving 10 tone-foot-shock pairings. The fear-conditioned and control rats (five rats per group) were anesthetized with 3% isoflurane gas and injected intravenously with flumazenil labeling. After 10 min of pretreatment with diazepam (BZR agonist) through intraperitoneal injection , the rats received an injection of 37 MBq/200 μL [18F]flumazenil. The pre-treated rats were imaged using NanoPET/CT following the same procedures described above for the control rats. Occupancy (%) = (ROI of control group brain region − ROI of pretreated group brain region/ROI of control group brain region) × 100%.In vivo competitive binding of 200 µg diazepam  in the brain was investigated in normal rats using flumazenil. The results demonstrate that this fully automated nucleophilic [18F]fluorination system can replace traditional methods, and the product of [18F]flumazenil can be utilized in PET imaging. To quantify GABAA availability in in vivo NanoPET/CT and ex vivo autoradiography in an animal model of anxiety.The straightforward radio-labeling and purification procedure described in this study can be easily adapted by commercially available modules for the high radiochemical purity of [


The T cell receptor is a multi-subunit complex that carries out a range of recognition tasks for multiple lymphocyte types and translates recognition into signals that regulate survival, growth, differentiation, and effector functions for innate and adaptive host defense. Recent advances include the cryo-electron microscopy-based structure of the extracellular and transmembrane components of the complex, new information about coupling to intracellular partners, lateral associations in the membrane that all add to our picture of the T cell signaling machinery, and how signal termination relates to effector function. This review endeavors to integrate structural and biochemical information through the lens of the immunological synapse- the critical interface with the antigen-presenting cell. TCRs are made up of one of two pairs of variable subunits, one pair being between TCRα-TCRβ and the other TCRγ-TCRδ. The genes encoding the TCR mRNAs are generated by somatic gene rearrangement of germline coding segments with additional random sequence information introduced during the joining process; this leads to a huge potential repertoire for both αβ and γδ receptors2. This variability is the cornerstone of adaptive immunity through recognition of peptide-MHC complexes by αβ TCR but is also used to build a number of stereotyped receptor rearrangements that enable innate-like TCR αβ and TCR γδ T cells that participate in immediate responses to pathogens in parallel with other effectors of innate immunity. The TCR αβ innate-like receptors include examples that recognize lipid antigens associated with CD1d3, referred to as invariant NK T cells (iNKT), and B vitamin metabolites associated with MR14, referred to as mucosal activated invariant T cells (MAIT). A large subset of blood T cells using variable segments γ2 and γ9 recognize cholesterol metabolites through butyrophilins5. These recognition processes can be superimposed on different effector programs, including cell-mediated killing and help for immune responses against intracellular, extracellular or multicellular pathogens.The T cell receptor (TCR) is restricted in its expression to T lymphocytes, but this is hardly a restriction. T lymphocytes carry out diverse functions in innate and adaptive recognition, and this is important to keep in mind when thinking about the signaling capabilities of the TCR6. The invariant subunits have cytoplasmic domains with pairs of tyrosine residues spaced to provide binding sites for the non-receptor tyrosine kinase ζ-associated protein of 70 kDa (ZAP70) after phosphorylation by lymphocyte kinase (LCK)7. ZAP70 then phosphorylates linker of activated T cells (LAT), which recruits a number of additional adapters, phospholipase Cγ (PLCγ) and complexes containing son of sevenless (SOS) to enable downstream signaling based on cytoplasmic Ca2+ increase, diacylglycerol and mitogen-activated kinase cascade initiation via the small GTPase RAS10. While different types of TCR bind diverse ligands, these are uniformly recognized on the surface of other cells rather than in solution. TCR signaling, therefore takes place in the context of synapsis between the T cell and an antigen-presenting cell11. Recent work on how this signaling cascade is initiated and sustained in the context of an immunological synapse will be the focus of this review.Signal transduction through TCR is based on a tyrosine kinase cascade. Both TCRαβ and TCRγδ subunits have a short cytoplasmic domain with no known signaling potential. Signaling through a tyrosine kinase cascade is carried out by the invariant subunits of the complex. The variable TCR heterodimers complex with three invariant dimers with the composition CD3ε-CD3δ, CD3ε-CD3γ and CD247 (ζ-homodimer) through a well-ordered process driven by transmembrane domain interactions12  and requires a close approach of the T cell and antigen-presenting cells to within 13–14 nm, referred to as close contacts. This process is facilitated by adhesion molecules that reach out over greater distances and others that appear to fit into this same 13–14 nm space, leading to a proposal of a complex synapsis with at least two intermembrane spacings12 . Kupfer 19. Expression of CD45 with intact phosphatase domains, but truncated extracellular domains, which would not be excluded from close contacts, has been shown to either rescue TCR signaling or inhibit it21. CD45 can be seen as a gatekeeper19 that promotes ligand discrimination while ensuring high sensitivity18. A model of CD45 exclusion from close contacts formed by TCR and other immunoreceptors combined with kinetic proofreading, referred to as kinetic segregation (KS), has become an important framework for immunoreceptor signaling across innate and adaptive immunity25. The time frames involved in kinetic segregation are on the order of a few seconds, which also represents the time frame of initial T cell triggering. Immunological synapses may last from minutes to hours, and immune responses involving innate and memory T cells can be mobilized in hours, but the first adaptive response to a pathogen, involving proliferation of rare naïve precursors, takes days to weeks to develop. CD45 is expressed on most hematopoietic cells, which thus are all equipped with a system for activation of tyrosine kinase cascades upon close contact with adjacent cells or objects - a synapse sensor!Manipulation of CD45 in T cells is complicated by the essential role of CD45 to activate Lck through de-phosphorylation of the C-terminal tyrosine, which is generated through action of C-terminal src kinase (CSK)26. Cross-linking of TCR with soluble ligands spaced less than 9 nm apart triggers T cells28. There are a number of mechanisms by which TCR clustering could lead to CD45 exclusion on a ~20 nm length scale without an IS. One possibility is lipid phase separation around clustered TCR that leads to highly localized CD45 exclusion based on mismatch of transmembrane domains29. It has also been noted that acute selective inhibition of CSK can lead to TCR triggering without any manipulation of CD4530. TCR clustering involved a phase separation process driven by interaction of the CD3ε tail with LCK. This phase separation process is self-limiting in that phosphorylation of CD3ε by LCK leads to recruitment of CSK, which favors dispersal of the TCR clusters in the absence of CD4531. At higher pMHC density, the clusters may become resistant to dispersal, leading to graded activation of phosphatidylinositol 3-kinase (PI3K) and ITK32. The ability of ITAM-based signaling to progress in the absence of CD45 exclusion is relevant in the setting of chimeric antigen receptors and bispecific T cell engagers, which can be designed to establish close contacts or greater intermembrane separation33. Furthermore, CSK recruitment through CD3ε phosphorylation may be less inhibitory in settings where CD45 is not as effectively excluded34.T cells can be activated without CD45 exclusion through IS formation. For example, nanoscale engineering to generate stimulatory substrates that prevented exclusion of endogenous CD45 from sites of TCR clustering revealed that CD45 exclusion was not essential for TCR tyrosine phosphorylation if the TCR were clustered to within less than 50 nm, but the ability to exclude CD45 was required for TCR phosphorylation when TCR were > 50 nm apart37. Catch bonds increase the duration of the TCR-pMHC interaction at ~ 10 pM force39. An interesting dilemma inherent to reconciling KS and mechanical models is that the mode of prolongation of binding can involve a significant increase in the length of the complex37, such that the binding is prolonged, but CD45 exclusion may be impaired through a local increase in membrane separation. In contrast, allosteric models for TCR signaling, in which ligand binding causes changes in conformation that are transmitted through the extracellular and transmembrane regions to change the conformation of the cytoplasmic tails, may operate in parallel with CD45 exclusion to alter the outcome of ligand binding. The cytoplasmic domains of the CD3ε and CD247, and the costimulatory CD28, all interact at rest with the inner leaflet of the plasma membrane through hydrophobic and charge-based interactions at the lipid bilayer41. These interactions are released during activation due in part to translocation of some of the acidic phospholipids to the outer leaflet of the plasma membrane42. Different allosteric models have been proposed, for example, based on exposure of cryptic epitopes in the receptor complex35, effects of small molecules that bind to the TCR on signaling43, or mutations that destabilize the transmembrane domain packing44. Conformational changes in the TCR could potentially change the local phospholipid environment, eject cholesterol, or promote dissociation of the cytoplasmic domains to become accessible to kinases and phosphatases46.Conformational changes in the TCR have been invoked in the context of TCR engagement by ligands in the absence or presence of ~10 pN forces acting in the interface47 to a cryo-electron microscopy (cryo-EM) structure of the TCRαβ-CD3-CD247 complex in a detergent micelle48 and, most recently, to an engineered, high-affinity TCRαβ-CD3-CD247 complex in a detergent micelle interacting with its pMHC49. At face value, the earlier crystal structures and newer cryo-EM structures support a rigid body model for the TCR. In all cases, there have been minimal changes in the TCR structures with or without interaction with the pMHC. The cryo-EM structure extends this observation to the CD3 extracellular domains and the transmembrane helices. However, a recent study demonstrates a cholesterol binding-dependent change in the conformation of the transmembrane helices TCRαβ-CD3-CD247 detergent micelle complex50. This resonates with earlier data mentioned above that cholesterol binding helps keep the TCRαβ-CD3-CD247 complex in an inactive conformation46. Other multi-transmembrane-spanning proteins in detergent micelles display different structures than observed in phospholipid bilayers51. Thus, it will still be valuable to determine TCRαβ-CD3-CD247 structure in a bilayer environment with and without monovalent and multivalent ligation, in addition to collecting additional examples of TCRαβ-CD3-CD247 structures and complexes in detergent micelles. Extension to TCRγδ-CD3-CD247 would also be exciting.The structural picture of the TCR has evolved from the prior state-of-the-art crystallographic information on the interaction of variable chains of the TCR with pMHC and other ligands49. This fits with the notion that the TCR-pMHC interaction should fit into an interface stabilized by the CD2-CD58 adhesion system, as proposed earlier17. However, another recent study showed that the CD2-CD58 interaction actually decreased the 2D affinity of the TCR-pMHC in the same interface by nearly 2-fold. This suggests that the CD2-CD58 and TCR-pMHC would have slightly different intermembrane spacings23. Direct measurements on the CD2-CD48 interaction, which is very similar to CD58, show that it prefers a spacing of 12.8 nm15. Direct measurements of the intermembrane spacing in contacts dominated by TCR-pMHC averaged 13.1 nm with a modal distance of 14 nm 97, and some of the TCR are released into the central IS by ectocytosis100. The choice between ectocytosis to release an extracellular vesicle versus endocytosis leading to degradation or recycling is based on different clathrin adapters, HRS for ectocytosis, recruited first, and EPN1 for endocytosis, recruited later99  diglyceride content103, which favors hexagonal over bilayer lipid phases and may lead to unstable vesicles104. Consistent with this, at 90 minutes after initiation of IS formation by CD8+ CTL, no lipid bilayer-based vesicles were recovered from the target side of the synaptic cleft, but only glycoprotein particles with a shell of thrombospondins containing cytotoxic proteins105. Lipid vesicles were recovered only when FAS was incorporated into the target membrane, which captures vesicles containing FASLG106. Thus, TCR signaling is terminated through a process of ectocytosis, but this same process gives birth to important effectors and serial killing.Does the central accumulation of TCR in the IS sustain signaling or terminate it? Signal termination by TCR endocytosis and either recycling or degradation has long been observed later99 . In help107. Another recent study looked at multiple inputs and outputs with analysis of time-course data through a neural network and concluded that two parameters were needed to quantify T cell ligand discrimination108. Discrimination can be encoded in receptors, but also in the downstream signaling networks. For example, thymocytes are more sensitive than mature T cells as they need to be positively selected by self-pMHC, which mature T cells then ignore. At least part of the signaling program responsible for this shift is coordinated by microRNAs in thymocytes that down-regulate proteins that dampen signaling in mature T cells109. Memory T cells and innate-like T cells may even further attenuate signaling pathways to balance their higher abundance110, and use the highly sensitive TCR as a pattern recognition receptor1. More work is needed to integrate the contributions of CD45 exclusion, TCR allostery, auto-costimulation and signal termination to quantitative aspects of discrimination in the context of boosting natural T cell activation and T cell engineering to cope with challenges of infection, cancer and autoimmunity.T cells not only need to recognize pMHC or other ligands with high sensitivity but must be able to discriminate between similar ligands to, for example, recognize a mutated self-protein in a tumor or autoimmunity triggered by pathogen-associated proteins that are similar to self. Similar problems are faced by TCRαβ and TCRγδ used for innate recognition, namely that the TCR platform may have evolved into innate recognition roles when the self and pathogen-associated patterns are closely related, leading to requirement for greater discrimination than in other pattern recognition systems. Recently, discrimination has been quantified as a single parameter that captures the trade-off between sensitivity and binary decisions


The α/β hydrolase KARRIKIN INSENSITIVE 2 (KAI2) functions as a receptor for a yet undiscovered phytohormone, provisionally termed KAI2 ligand (KL). In addition, it perceives karrikin, a butenolide compound found in the smoke of burnt plant material. KAI2-mediated signaling is involved in regulating seed germination and in shaping seedling and adult plant morphology, both above and below ground. It also governs responses to various abiotic stimuli and stresses and shapes biotic interactions. KAI2-mediated signaling is being linked to an elaborate cross-talk with other phytohormone pathways such as auxin, gibberellin, abscisic acid, ethylene and salicylic acid signaling, in addition to light and nutrient starvation signaling. Further connections will likely be revealed in the future. This article summarizes recent advances in unraveling the function of KAI2-mediated signaling and its interaction with other signaling pathways. Arabidopsis thaliana, which do usually not experience fire (Arabidopsis identified KARRIKIN INSENSITIVE 2 (KAI2), encoding an α/β hydrolase protein, as being required for KAR-mediated seed germination  (Karrikins (KARs) are butenolide compounds that were first identified as active components of smoke from burnt plant material that can stimulate the germination of dormant seeds from fire-following plants . Criticance fire . Reversemination . Subsequmination . Howevermination . Importaand (KL)  which liMAX2 leads to ubiquitination and subsequent degradation of KAR response–specific members of the SUPPRESSOR OF MAX2-LIKE (SMXL) protein family (SMAX1 and SMXL2) -type E3 ubiquitin ligase complex called MORE AXILLIARY GROWTH 2 (MAX2) . Activatd SMXL2) . SMAX1 wignaling .MAX2 is also involved in signal transduction upon perception of carotenoid-derived plant hormones called strigolactones (SLs) (max2 mutants show both KAR- and SL-related phenotypes. SLs are perceived by the KAI2-related receptor DWARF14 (D14) which together with SCFMAX2 leads to the degradation of SL response–specific members of the SMXL protein family   , and max mutants . Furthertes KAI2 .Here, we focus on KAR/KL signaling and review the current knowledge on the biological roles of KAI2 in plant development, stress tolerance and interaction with microorganisms. Additionally, we highlight that KAI2 is an indispensable player in the intricate interlacing of phytohormone signaling pathways.KAI2 result in enhanced primary dormancy of Arabidopsis seeds (htl-3 mutant (mutated in KAI2) is impaired in rac-GR24-mediated induction of a key ABA catabolism gene CYP707A and the gene encoding the transcription factor WRKY33, which regulates CYP707A expression, possibly resulting in ABA accumulation and promotion of dormancy  suggesting only partial dependence on canonical GA signaling  of GA signaling  and D14 in an additive manner .Interestingly, for  species  In rice,e manner . Interes4l alike , suggestreatment . Howevers as d14 . A d53 kArabidopsis kai2 mutants at a later stage of development include elongated petioles and increased blade length and width contrary to the effects of d14  have the same length as wild-type root hairs  SYNTHASE 7 (ACS7), involved in ethylene biosynthesis, to regulate root system architecture. smax1 mutants produce higher amounts of ethylene than the wild type and exhibit increased expression of ACS7 causing longer root hairs and shorter primary roots. The phenotypes could be fully rescued by treating with the ethylene biosynthesis inhibitor 2-aminoethoxyvinyl glycine and the ethylene signaling inhibitor, AgNO3  in the epidermis above the lateral root cap (LRC), the LRC, the root tip and the stele; and of the auxin exporter PIN-FORMED2 (PIN2) in the meristematic zone of the root tip. This seems to optimize the auxin level in epidermal cells above the LRC, promoting root hair elongation. Furthermore, AUX1 and PIN2 are required for KAR- and ACC-mediated root hair elongation, placing them downstream of KAR as well as ethylene signaling. Thus, a KAI2-ethylene-auxin-signaling cascade commands root hair growth in Arabidopsis  clade containing SL receptor D14 homologs, divergent bryophyte KAI2s and D14-LIKE 2 (DLK2) homologs   . Interesesponses . This suesponses .Marchantia polymorpha has two eu-KAI2 orthologs, MpKAI2a and MpKAI2b, and one each of MpMAX2 and MpSMXL  (Marchantia.The liverwort d MpSMXL . Phenotysponses) , indicatMpsmxl mutation can fully suppress the thallus angle, the gemma cell number and partially the thallus area phenotype. However, it shows the same reduction in the gemma area as Mpkai2a  for 4 d and transferred back to optimal conditions (20°C), kai2 seeds experience a reduced germination success compared to wild-type seeds and compared to kai2 seeds continuously incubated at 20°C , possibly from increased GLUTATHIONE PEROXIDASE3 (GPX3) and GPX7 expression. Furthermore, increased root hair length and root-to-shoot ratio in smax1smxl2 compared to the wild type demonstrate a stronger drought tolerance response  from its soil reservoirs makes it poorly available to plants - and PHR1-LIKE (PHL1)-dependent manner . The fungi colonize the root cortical cells forming highly branched hyphal structures, the arbuscules, which are sites for the transfer of nutrients to the plant such as phosphorus and nitrogen. In return, the fungus receives carbohydrates and lipids . Each stD14L (rice ortholog of Arabidopsis KAI2), results in inability of AM fungi to penetrate the root epidermis , known to be required for the expression of SL biosynthesis genes (DWARF 27 (D27), CAROTENOID CLEAVAGE DIOXYGENASE 7 and 8 (CCD7 and CCD8), which are required for the production of SL precursors, and CYP711A2, which is involved in the production of orobanchol , such as SYMBIOSIS RECEPTOR-LIKE KINASE (SYMRK), 2+/CALMODULIN-DEPENDENT PROTEIN KINASECa (CCaMK) and CYCLOPS (LysM-RECEPTOR-LIKE KINASE 2 (LysM-RLK2) [NOD FACTOR RECEPTOR 5 (NFR5)], which may be involved in the perception of fungal lipochitooligosaccharide (LCO) signals  (barley homolog of NFR5) and KAR treatment could induce RLK10 in a D14L-dependent manner , whereas surprisingly smax1 as well as smxl6/7/8 can suppress the susceptibility phenotype of max2. However, the resistance phenotype is specific to KAI2 signaling, and the authors suggest that SMXL6/7/8 are somehow required for SMAX1 function , SYSTEMIC ACQUIRED RESISTANCE DEFICIENT 1 (SARD1), NON-RACE-SPECIFIC DISEASE RESISTANCE 1 (NDR1), PHYTOALEXIN DEFICIENT 4 (PAD4), TGA1A‐RELATED GENE 3 (TGA3) and NAC TRANSCRIPTION FACTOR-LIKE 9 (NTL9) to list a few in the initial stages of the infection, and this was rescued by smax1  and Botrytis cinerea (in Arabidopsis leaves)  . PerhapsSince the discovery of the KAR receptor KAI2 , our knoent-5DS (dGR24ent-5DS) activates KAI2 signaling more strongly in Arabidopsis, B. distachyon and M. polymorpha as compared to GR24ent-5DS and does not induce signaling via D14 (Selaginella moellendorffii KAI2 binds dGR24ent-5DS in vitro and shows activation in a heterologous system, which otherwise does not occur upon either KAR or GR24ent-5DS treatment (We still lack knowledge on the identity of KL and enzymes involved in its biosynthesis. Targeted in silico modeling led to a sesquiterpene lactone , while e via D14 . Additioreatment .M. truncatula by ectopic expression of NSP2 requires KAI2, and inhibition of colonization in nsp2 nsp2l double mutants is suppressed by smax1 mutation (It has been speculated that NSP transcription factors may regulate the KL biosynthesis pathway . They armutation . It willDespite some indications of KAI2-signaling interactions with other phytohormone pathways, we certainly do not know the whole range of interactions and in most cases, direct molecular connections to these other pathways remain to be uncovered. Particularly, we are missing knowledge about SMAX1 targets. These may differ depending on the scenario regulated by SMAX1. SMAX1 interactomes in different tissues and under different conditions may lead us to these targets. Major exciting questions remain to be answered.


An understanding of neuroimmune signaling has become central to a description of how alcohol causes addiction and how it damages people with an AUD. It is well known that the neuroimmune system influences neural activity via changes in gene expression. This review discusses the roles played by CNS Toll-like receptor (TLR) signaling in the response to alcohol. Also discussed are observations in Drosophila that show how TLR signaling pathways can be co-opted by the nervous system and potentially shape behavior to a far greater extent and in ways different than generally recognized. For example, in Drosophila, TLRs substitute for neurotrophin receptors and an NF-κB at the end of a TLR pathway influences alcohol responsivity by acting non-genomically. In the United States, approximately 5% of individuals have an alcohol-use disorder (AUD) and, excluding COVID-19 infection, a third of preventable deaths are attributed to alcohol misuse . ChoicesMany consequences of alcohol misuse are linked to Toll-like receptor (TLR) pathways, which mediate alcohol-induced immune and neuroimmune activation that can lead to organ damage and to neurodegeneration (reviewed in ). AlcohoDrosophila melanogaster Toll gene. The gene was identified in a genetic screen for mutations that interfere with dorsal-ventral patterning of the fly embryo [In Drosophila, Toll receptor signaling was first shown to have a central role in dorsal-ventral pattern formation (see the review ) and wasy embryo . The firy embryo .The use of Toll signaling in dorsal-ventral pattern formation is not conserved in vertebrates . HoweverHumans have eleven TLR family members (TLR1-10 plus Cd180), rodents have thirteen , while Drosophila have nine ,13,14. MTLRs are usually divided into cell surface receptors and intracellular endosomal receptors. Most of our understanding of the subcellular localization of TLRs comes from the analysis of immune cells. In immune cells, it was considered dogma that the cell membrane Toll-like receptors are TLR1, 2, 4, 5, and 6 and the endosomal Toll-like receptors are TLR3, 7, 8, 9, and in mice, 11, 12, and 13. However, recent evidence indicates that this segregation is not absolute. TLR4 was shown to also signal from the endosome ,18 and fTLR1, 2, and 6 respond to diacylated and/or triacylated lipopeptides, TLR4 responds to bacterial lipopolysaccharides, and TLR5 responds to flagellin. TLR3, 7, 8, 9, and 13 respond to non-self nucleic acids, while TLR11 responds to microbial protein antigens and TLR11 and TLR12 respond to parasitic protein antigens ,18,22.Intracellular adaptor proteins that associate with TLRs determine which transcription factors are activated when the receptor is stimulated. TLR1, TLR2, TLR4, TLR5, TLR6, TLR7, TLR8, and TLR9 signal through the MyD88 adapter, while TLR3 and intracellular TLR4 signal through the TRIF adapter. MYD88 signaling is best known for its activation of NFKBs but can also cause AP1 and CREB activation. TRIF signaling leads to the activation of an IRF-type transcription factor  and, in a delayed fashion, TRIF signaling can also activate NFKB transcription factors  . Activation of GABAAR α2-associated TLR4 was shown to stimulate the CREB transcription factor. At least in the VTA, CREB activation promotes increased corticotropin-releasing factor (CRF) and tyrosine hydroxylase gene expression. In a feedback loop, activation of CRF can further stimulate TLR4. The GABAAR α2/TLR4 signaling combination was reported to promote binge alcohol drinking in rats and RNAi experiments showed that knockdown of either GABAAR α2 or TLR4 reduces binge drinking [The neuronal GABAdrinking ,30. ThesAR receptors [However, not all studies showed a reliable connection between alcohol drinking and TLR4 (itemized in ). A repoeceptors .However, TLR4 clearly has a role in alcohol-induced proinflammatory responses and the cognitive problems associated with inflammation ,26,27. IAlthough TLR4 by itself does not directly affect alcohol consumption, other TLR receptors appear to. With regard to the propensity to drink alcohol, the genetic ablation of the TLR2 gene in mice decreases alcohol drinking in both the continuous access two-bottle choice paradigm, and the intermittent access drinking-in-the-dark paradigm  . Many cchannels . Furtherpendence  and in mpendence ). Non-impendence .Dif gene. Confirmation that Toll signaling through the Dif NF-κB was relevant for the change in alcohol sensitivity was demonstrated in an epistasis experiment in which alcohol resistance produced by a Toll gain-of-function allele could be suppressed by a heterozygous Dif loss-of-function allele . Such aDif gene showed that it produced two classes of mRNA via alternative mRNA splicing . In flies, the relevant I-κB is encoded by the activity ,69. Instactivity ,69,70. Tdorsal expressed two protein isoforms. However, in 2015, Zhou et al. [At the time that the original NMJ studies were conducted, the researchers did not know that u et al.  showed tIn the study of Wijesekera et al. , it was Immunohistochemical staining shows that DifB is not expressed in fat bodies but, instead, is expressed in the brain where it is abundant in the mushroom bodies and moderately abundant in the antennal lobes and ventral nerve cord. Whereas DifA is not obviously expressed in the adult CNS. The mushroom bodies play a central role in learning and memory , and in Dif expression in the Kenyon cell neurons of the mushroom bodies and in the antennal lobes (ey, Imp, and sNPF genes. Strikingly, Dif is at least as good a Kenyon cell identifier as are these recognized marker genes.SCope analysis of single-cell sequencing data  confirmeal lobes . In singImmunohistochemical staining can provide insight into the subcellular localization of proteins in the insect CNS. Fly central nervous system neurons are organized into neuropil comprised of synapse-rich axonal-dendritic projections surrounded by a rind of neuronal cell bodies ,83. ThusThe non-overlapping expression of DifA and DifB results in distinct functional consequences when DifA expression is suppressed and when DifB expression is suppressed. A mutation that specifically eliminates DifA causes severe immunosuppression, but does not affect alcohol sensitivity. Conversely, a DifB-specific mutation does not seem important for immunity but results in increased alcohol sensitivity. Flies have compartmentalized distinct functions of Dif into different alternative splice variant isoforms (Dif NF-κB [We were interested in identifying which Toll-like receptors might signal through Dif in the brain. if NF-κB . It is yDif is at a good position for implementing this TLR function. There is evidence that mammalian NF-κBs are also well-positioned to directly modulate synaptic activity. Some mammalian NF-κBs also localize to the synapse, and in response to Ca2+, some transition into the membrane—a localization at odds with a nuclear function [Components of the Drosophila TLR signaling pathways act in ways that are not yet observed in mammals. Clearly, in the fly CNS, the neuroimmune system or at least components of the neuroimmune system were co-opted to directly modulate behavior via signaling through a TLR pathway. The non-nuclear NF-κB encoded by function . Furtherfunction  showed tBecause of their importance in immunity, TLR signaling molecules and NF-κB transcription factors are some of the most highly studied proteins in mammals. From these studies, the range of functions performed by these entities is well known and led to assumptions concerning how they act. Despite this, studying the proteins in an animal distantly related to any mammal highlights new capabilities of these molecules and new ways that neurons can co-opt immune signaling pathways for a different purpose. The demonstrated potential for novel use of innate signaling molecules by an insect CNS should lead one to suspect that the CNS of other animals might also find such uses beneficial. The fact that they were not reported to occur in Mammalia may arise from preconceptions concerning what these proteins can do. Certainly, the outsized role played by neuroimmune signaling in modulating behaviors associated with alcohol-use disorders was originally surprising. Perhaps work from Drosophila is indicating additional surprises await in the relationship between alcohol responses and how neuroimmune signaling modulates neural activity.


RIG-I is an essential innate immune receptor that responds to infection by RNA viruses. The RIG-I signaling cascade is mediated by a series of post-translational modifications, the most important of which is ubiquitination of the RIG-I Caspase Recruitment Domains (CARDs) by E3 ligase Riplet. This is required for interaction between RIG-I and its downstream adapter protein MAVS, but the mechanism of action remains unclear. Here we show that Riplet is required for RIG-I signaling in the presence of both short and long dsRNAs, establishing that Riplet activation does not depend upon RIG-I filament formation on long dsRNAs. Likewise, quantitative Riplet-RIG-I affinity measurements establish that Riplet interacts with RIG-I regardless of whether the receptor is bound to RNA. To understand this, we solved high-resolution cryo-EM structures of RIG-I/RNA/Riplet complexes, revealing molecular interfaces that control Riplet-mediated activation and enabling the formulation of a unified model for the role of Riplet in signaling. Riplet conjugates K63-Ub chain to RIG-I in order to induce a robust antiviral response, but the mechanism of action remains unclear. Here, the authors show that Riplet recognizes RIG-I regardless of its RNA-bound status and promotes RIG-I signaling independent of RIG-I oligomerization. It is critical that we understand molecular mechanisms of RIG-I activation in order to develop new therapeutic strategies against viral infection, cancer, and other disorders of immune function.The innate immune receptor RIG-I (Retinoic acid inducible gene-I) is an indispensable first-line defender against infection by RNA viruses, including coronavirus and influenza viruses that have caused severe pandemics1. The most well-characterized example is the K63-linked ubiquitination of RIG-I signaling domains , which enhances RIG-I signaling by stabilizing RIG-I in an active conformation9. When RIG-I forms a complex with viral RNAs in the cytosol, it undergoes a structural change that exposes its signaling domains (CARDs)10, resulting in an activated conformation that is modified by covalent conjugation with K63-Ubiquitin chains. The K63-Ub chains are thought to help bring together CARDs from different activated RIG-I molecules, thereby forming a stable CARDs tetramer11 that binds to the MAVS adapter protein , thereby inducing MAVS aggregation on mitochondria via RIG-I-CARDs:MAVS-CARD interactions9, thereby leading to IFN (interferon) activation and a rapid antiviral signaling cascade.Post-Translational Modifications (PTMs) are essential during the process of RIG-I signaling, where they act by repressing or activating the RIG-I sensor15. These studies have shown that Riplet is not only a ligase, but that it also forms a specific complex with RIG-I. These previous studies utilized long RNA molecules to stimulate the RIG-I receptor, which has resulted in a model for Riplet-mediated RIG-I activation that rests on two concepts: 1. A requirement for Riplet to interact with RIG-I that has oligomerized as a filament on long dsRNA molecules. 2. Given that Riplet forms a homodimer, it was proposed to act as a physical bridge between RIG-I residues on different RIG-I/RNA filaments, thereby forming giant plaques that stimulate signaling. While these aspects of the Riplet model were reasonable given the information available at the time, new information on the RIG-I signaling mechanism has made it important to re-evaluate the physical basis for Riplet function. For example, it has been unambiguously shown that RIG-I forms functional signaling complexes on short RNA duplexes that are unable to form filaments18. In addition, cell biology and imaging have now established that, during the timeframe of signaling, RIG-I does not form massive aggregated complexes or plaques20. There is no experimental evidence for the formation of tangled filaments in the mechanism of RIG-I signaling, and it has been established that RIG-I readily signals without them21. Given these issues, we wanted to take a fresh look at the physical structure of functional Riplet/RIG-I complexes in order to better understand the molecular basis for signaling.Years of work in many labs have established that the E3 ligase Riplet (RING finger protein leading to RIG-I activation) activates RIG-I signaling by conjugating K63-Ub chains to RIG-I CARDsIn this work, to better understand the molecular basis for Riplet recognition of RIG-I/RNA complexes, we present a series of Riplet-RIG-I complexes and examine Riplet-mediated RIG-I activation by different types of RNA ligands. The resulting data establish that Riplet activates RIG-I in complex with very short dsRNAs, thereby negating the requirement for RNA-based filaments in the mechanism of RIG-I activation. Intriguingly, Riplet forms RIG-I complexes with moderate affinity, with and without RNA, suggesting that Riplet is constitutively associated with RIG-I in the cytoplasm. We developed a pipeline for determining single particle cryo-EM structures of RIG-I:RNA:Riplet ternary complexes using full-length proteins. This work reveals that Riplet recognizes a relatively small, rigid region on the surface of RIG-I, thereby providing a structural explanation for Riplet affinity for both apo and RNA-bound RIG-I. By combining this data with mutational functional analysis and AlphaFold predictions of unresolved Riplet domains, we develop a unified model for RIG-I activation by E3 ligase Riplet.19. Indeed, p3SLR14 induces IFN responses comparable to long dsRNAs from polyinosinic:polycytidylic acid [poly(I:C)] and Sendai virus (SeV)19. Consistent with this, p3SLR14 stimulated IFN activation at similar level to long RNA molecules  HEK293T cell line , CC domain , and C-terminal PrySpry domain  from Riplet by replacing it with a set of flexible GS (Gly-Ser) linkers (GS repeats with 52 and 14 amino acids). Surprisingly, in the cell-based IFN reporter assay, we found that replacement of the CC domain still induced comparable IFN response to that of wildtype Riplet  of different Riplet constructs to RIG-I with and without RNA, revealing the kinetic and thermodynamic parameters governing the association between Riplet and RIG-I. Surprisingly, full-length Riplet recognizes both apo-RIG-I and RIG-I:p3SLR14 complex with similar, moderate affinity  to measure the binding affinity  compared to p3SLR14-bound RIG-I (0.7 µM). Whereas deletion of the RING only moderately affected the binding affinity of Riplet to p3dsRNA24:RIG-I (10 nM), deletion of both, RING and CC domains, severely reduced the binding affinity to 1.4 µM.These data indicate that RIG-I recognition is primarily led by the PrySpry domain, supported by the CC domain, and that the RING domain has a small influence on RIG-I recognition.D  indicated that this complex was just below the level of stability needed to obtain a complex under cryo-EM conditions Fig. , which i22, we obtained three different structures of the bidentate RIG-I:p3dsRNA24:Riplet complex, solved at 3.2, 4.0, and 3.9 Å , the second RIG-I is not bound at the opposite terminus at all, but instead binds to a proximal internal duplex site. This results in a head-to-tail arrangement between bound Riplet molecules Fig. . Like otAs the second RIG-I in each structure recognizes different types of RNA sites, the two PrySpry domains bind to RIG-I from different approach angles, revealing variable distances between them, ranging from 58 Å to 101 Å , consistent with the low affinity between Riplet and apo-RIG-I/RIG-I:p3SLR14 (0.7 µM). At this interface, the Riplet PrySpry domain uses several loops to recognize a rigid motif composed of an α-helix in the outer surface of the RIG-I Hel2 domain  in the dimeric interface of the RING and CC domains . These findings suggest that Riplet RING might form a dimer to perform Ub conjugation like other TRIM E3 ligases under physiological conditions27 and it may explain why the CC-removal mutant still activates the IFN response  induce the same amount of Riplet-mediated RIG-I signaling indicates that there is no apparent mechanistic benefit for Riplet to associate with multiple RIG-I units that are bound on longer RNAs. That said, the results we report here were obtained in a reporter construct that may not reflect the activation constraints that are seen in all cell types or in all types of viral infection. Our structural results indicate that Riplet forms a flexible dimer capable of bridging multiple RIG-I molecules that are bound at variable positions along an RNA duplex, and this may expand the functionality of Riplet under different types of conditions. Indeed, the binding data show that such double-anchoring of Riplet to a single RNA/RIG-I complex can enhance Riplet affinity, which may increase the probability of ubiquitination and facilitate the signaling cascade in certain cellular contexts. On the other hand, our findings clearly show that RIG-I signaling is not dependent on the formation of Riplet-mediated bridges between different RNA molecules, or multiple RIG-I-coated filaments, nor is signaling contingent on Riplet gathering of tangled, interconnected species. Rather, Riplet potentiates RIG-I signaling upon binding to a single RNA, whether bound at one site or two along the RNA lattice.23. Given the differences in amino acid identity and conservation along the PrySpry binding surface, the interface visualized in this study explains the specificity of RIG-I for Riplet rather than the structurally related Trim25 ligase.By examining the structural features of individual Riplet domains and exploring their effects through domain deletions, we provide insights into the function and specificity of each domain. The PrySpry domain and its interface with RIG-I are clearly visualized in our cryo-EM structures. Consistent with earlier results using a PrySpry fusion protein, a conserved network of aromatic and charged amino acids line the interface between Hel2 helix and the loops projecting from the Pry-Spry beta sheet. As noted previously, this interface of Riplet is architecturally similar to that formed by the Trim25 E3 ligase. However, the specific amino acids constituting the Trim25 binding surface are different from those mediating Riplet PrySpry interaction with RIG-I. Consistent with this, Trim25 is not observed to ubiquitinate RIG-I and EMSA studies show that Trim25 does not have affinity for RIG-I29, and these appear to be redundant, as no individual Lys residue has ever been reproducibly identified as a critical residue for RIG-I activation by undergoing K63-Ub conjugation32. Indeed, single mutation of each of CARD Lys residue only slightly reduces the IFN response in the presence of p3SLR14  and Riplet-KO HEK293T cells were grown in high glucose Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% heat inactivated fetal bovine serum (HI-FBS) at 37 °C with 5% COE.coli cells, respectively. RIG-I and Riplet were cloned into both plasmids. RIG-I and Riplet truncates and mutants were generated using Q5 Site-Directed Mutagenesis Kit (NEB). pUNO1-Riplet-ΔRING (94–432)/ ΔPrySpry (1–248)/ RING (1–93)/ PrySpry (249–432)/ CCto52aaGS (120–183 to GS linker containing 52 amino acids)/ CCto14aaGS (120–183 to GS linker containing 14 amino acids) were cloned. pET-SUMO-Riplet-ΔRING(94–432)/ PrySpry(249–432) were cloned.The pUNO1 (Invivogen) and ChampionTM pET SUMO (Thermo) vectors were used for protein expression in mammalian and 21. In brief, 100 µl of HEK293T cells at a concentration of 200,000 cells/ml in Dulbecco’s Modified Eagle Medium  supplemented with 10% heat-inactivated Fetal Bovine Serum  was seeded into each well of 96-well plate (Corning). 24 h after the seeding, the cells of each well were transfected with 3.4 ng of pUNO1-RIG-I/Riplet unless specified, 3.4 ng of pRL-TK (Renilla luciferase reporter plasmid) and 34 ng of IFN-β/Firefly using the lipofectamine 2000 transfection reagent (ThermoFisher). The RIG-I expression was allowed to proceed for 6 h, at which point the cells of each well were challenged with 0.2 µg of RNAs using lipo2000 reagent. In all, 12–16 h after the stimulation, the HEK293T cells were lysed and the IFN-β induction was measured using the Dual-Luciferase Reporter Assay System (Promega) and a Synergy Neo2 Hybrid Multi-Mode Reader with Gen5 software (Biotek). The IFN-β induction level, the relative luminescence unit , is the firefly luciferase activity normalized to the renilla luciferase activity. The data were further processed with GraphPad Prism.The IFN-β induction assay was implemented to test RIG-I and Riplet mutants using different RNA duplexes33. The previously reported sgRNA was cloned to PX459 (addgene) and it was expected to cause single indel in exon 1 of Riplet gene located on Chr 1712. After puromycin selection, the surviving cells were plated as single cells to 96-well plates. Then the single-cell colonies were applied to IFN-β induction assay and the cells that were not stimulated by p3SLR14 were selected for subsequent evaluation using genotyping and immunoblotting. As there are three copies of Chr 17 in HEK293T cell, the genotyping revealed three different frameshift mutants in the Riplet-KO cells. Consistently, the immunoblotting showed a clear band of Riplet in the lane of parental cells, but no corresponding band in the Riplet-KO cells with the previously reported anti-Riplet primary antibody  using conventional CRISPR-Cas9 techniques22. In brief, RIG-I and Riplet were fused to an N-terminal 6xHis tag and a SUMO tag, followed by ULP1 digestion site in ChampionTM pET SUMO vector, respectively (ThermoFisher Scientific). These constructs were overexpressed in E.coli Rosetta™ 2(DE3) Singles™ Competent Cells (Millipore Sigma). RIG-I and Riplet expression was induced by IPTG (0.5 mM) when OD600 reached 0.6 and proceeded for 20–24 h at 16 °C. The pellets were lysed in buffer  supplemented with EDTA-free Protease Inhibitor Cocktail (Sigma), followed by nickel affinity chromatography using Ni-NTA Superflow beads (Qiagen). RIG-I and Riplet were treated by ULP1 to remove the SUMO tag. RIG-I was further purified by cation exchange and size exclusion chromatography, using a HiTrap Heparin HP column  and then a Superdex 200 Increase 10/300 GL column , while Riplet was only applied to size exclusion chromatography using the same column. RIG-I and Riplet were pooled in a storage buffer  for use in further experiments. RIG-I and Riplet used in cryo-EM studies were pooled in buffer without glycerol.The human RIG-I and Riplet proteins were expressed and purified34, and evaluated for purity by mass spectrometry (Novatia). Briefly, base deprotection was performed in a 1:1 mixture of 30% ammonium hydroxide (JT Baker) and 40% methylamine (Sigma) at 65 °C for 10 min. The supernatant was cooled on ice and evaporated to dryness in a new vial. With the addition of 500 µl absolute ethanol, the solution was evaporated to dryness. In order to deprotect the 2’-OH groups, the pellet was incubated with 500 µl of 1 M solution of tetrabutylammonium fluoride (TBAF) in Tetrahydrofuran (Sigma) at RT for 36 h. Then with addition of 500 µl 2 M sodium acetate (pH 6.0), the solution was evaporated to about 500 µl, extracted with 3 × 800 µl ethyl acetate, following ethanol precipitation. The RNA oligonucleotides were purified using 16% urea-denaturing polyacrylamide gel and its purity was assessed by mass spectrometry (Novatia). The stem-loop RNA (p3SLR50) was in-vitro transcribed, purified, and evaluated36. In brief, the p3SLR50 was in-vitro transcribed using T7 RNA polymerase with synthetic dsDNA template (Integrated DNA Technologies) containing 2’-OMe modifications on the first two nucleotides of the 5’ terminus of the negative-sense strand. A 100 µl transcription solution contains 1 µg of annealed template, 40 mM Tris-HCl (pH 8.0), 22 mM MgCl2, 10 mM DTT, 2 mM spermidine, 0.01% Triton X-100, 5 mM of each NTPs, 40 U of RNaseOUT™ Recombinant Ribonuclease Inhibitor (Thermo Fisher), and 5 µl of T7 RNA polymerase. With 12-hour incubation at 37 °C, the transcribed p3SLR50 was purified by gel extraction from 12 to 20% urea denaturing polyacrylamide gel and its purity was assessed by mass spectrometry (Novatia). RNA duplexes (p3dsRNA24) and stem-loop RNA  were annealed and stabilized before use in experiments. Specifically, two-stranded RNA duplexes (260 µM) were annealed by rapidly heating to 99 °C and slowly cooling over 1 hour to 4 °C in annealing buffer (200 mM NaCl) on a Thermocycler. The p3SLR14, p2SLR14, and p3SLR50 were heated to 90 °C for 2 min and then snap-cooled on ice for 30 min. The purity of annealed duplex RNAs was assessed by running samples on a 15% native polyacrylamide gel and visualized by Amersham Typhoon (GE). Sequences of the RNAs used in this study are shown in Supplementary Fig. RNA oligonucleotides  were synthesized in-house using an automated MerMade synthesizer  with phosphoramidites from Glen Research using standard phosphoramidite chemistry. Oligonucleotides were deprotected and gel purified as previously describedRIG-I was biotinylated for measuring binding affinity to Riplet. With Avi tag (N- GLNDIFEAQKIEWHE-C) fused to the N-terminal of RIG-I, the purification of Avi-tagged RIG-I was described above. The Avi tag was biotinylated by BirA in buffer  at 30 °C for 40 min (Avidity). The biotinylated RIG-I was further purified by size exclusion chromatography, using a Superdex 200 Increase 10/300 GL column , and pooled in a storage buffer  for use in further experiments. The biotinylated RIG-I was evaluated by immunoblotting.a) and dissociation (Kd), and binding affinity (KD = Kd/Ka) were obtained by fitting 1:1 model, which were summarized in Supplementary Fig. The interactions between Riplet and RIG-I:p3SLR14, RIG-I:p3dsRNA24, and apo-RIG-I were characterized by SPR using Pioneer FE SPR System with Pioneer FE software (Sartorius). The biotinylated RIG-I was incubated with p3SLR14 and p3dsRNA24 in ratio of 1:1.5 and 2.4:1 at 4 °C overnight, respectively, following 500 nM samples were immobilized to SADH sensor chip already immobilized with Streptavidin (Sartorius). The dilutions  of Riplet-FL, Riplet-ΔRING, and Riplet-PrySpry were applied to the chip at flow rate of 50 µl/min (279 µl) and dissociation time of 180 s in OneStep mode, which allows the measurement of binding affinity from a single analyte concentration injection. Data analysis was performed using Qdat software (Sartorius). The kinetics including rate constants of association  were incubated at room temperature for 30 min, then 2.5 uM Riplet was added to the solution following incubation at RT for 30 min. Formation of the complex was assessed by running samples on a 6% native polyacrylamide gel staining with GelRed (Biotium) and visualized by Amersham Typhoon (GE).To prepare RIG-I:RNA:Riplet complexes, purified RIG-I, RNA, and Riplet were mixed in an 8:1:8 molar ratio and incubated overnight at 4 °C. The RIG-I:RNA:Riplet complexes were separated using a Superdex 200 Increase 10/300 GL column . The complexes were pooled in size-exclusion buffer  and concentrated with a 50 kD Amicon Ultra-0.5 Centrifugal Filter Unit (Millipore Sigma). The absorbance was estimated using a Nanodrop (ThermoFisher) for concentration quantification.To prepare for freezing cryo-EM grids, the fresh samples were obtained and concentrated. The RIG-I:RNA:Riplet complexes were concentrated to 1.1 mg/ml. The Quantifoil holey carbon R1.2/1.3 300 mesh Cu grids (Ted Pella) were glow discharged using the PELCO easiGlow™ Glow Discharge Cleaning System (Ted Pella) for 35 s at 25 mA. With purified RIG-I:RNA:Riplet complexes (3.5 µl) applied onto the grids, the grids were blotted and plunged to the liquid ethane for flash freezing using a Vitrobot Mark IV (ThermoFisher). The blotting conditions for all grids were similar, under conditions of 22 °C and 100% humidity with force −4. Blotting times were 2 s for RIG-I:RNA:Riplet complexes. The frozen grids were all transferred and kept in liquid nitrogen prior to use in data collection.37. For the RIG-I:RNA:Riplet complexes, 3420 micrographs were collected at a nominal magnification of 105,000 ×, corresponding to calibrated pixel size of 0.839 Å/pix, with a defocus range of −1.0 to −2.5 µm. Each micrograph contains 40 frames and was collected with an exposure rate of 8.51 e-/pix/s and total electron exposure of 60 e-/Å2. The statistics of data acquisition are summarized in Supplementary Table Cryo-EM data were acquired at the HHMI Janelia Research Campus on a Titan Krios transmission electron microscope (ThermoFisher) operating at 300 keV and equipped with a Gatan K3 Summit direct electron detector using SerialEM software at super-resolution mode38. The micrographs were dose-weighted and beam-induced motion corrected through MotionCor239. The non-dose-weighted and motion corrected micrographs were used to estimate the CTF parameters using CTFFIND440. Micrographs were selected based on the Total motion and image resolution, and further selected by manual screening.The dataset was processed through Relion41, and a soft mask was applied to implement the 3D classification without particle alignment. Three different maps were generated. The end-end complex, end-transition complex and end-inter complex contained 204,993, 68,414, and 19,143 particles, which were subjected to 3D refinement, Ctfrefine, and Byaesian polishing, following a final 3D refinement42. The postprocessing yielded a map at global resolution of 3.2 Å, 4.0 Å, and 3.9 Å, sharpened with B-factor of −76.00 Å2, −131.39 Å2 and −88.73 Å2, according to the FSC = 0.143 criterion43. The strategy and statistics of data processing are summarized in Supplementary Fig. For the RIG-I:RNA:Riplet complex, 1,852,320 particles were initially picked from 3330 selected micrographs using the 3D reference of RIG-I:RNA:Riplet complex reconstructed from a cryo-EM dataset collected on a 200 KeV Glacios with Gatan K2 Summit direct electron detector located at Yale Cryo-EM facility. The particles were subjected to several rounds of 2D classification. Particles from all 2D classes containing a 2:1:2 RIG-I:RNA:Riplet were selected. The selected particles were then used to generate the initial model through Relion, and subjected to several rounds of 3D classification. Half of map is at high resolution, while the other half show low-resolution feathers. To improve the resolution, the worse half in the 3D map generated above was kept through Chimera44. The end-end complex was used as the initial search model for end-semi-closed-end complex and end-inter complex. All models were built and manually adjusted in Coot45. Then the models were refined against the cryo-EM maps using phenix.real_space_refine within phenix and refmac5 within the ccpem software suit46. Models were validated using Comprehensive validation (cryo-EM) in phenix47. All maps and models were further validated through the PDB validation server. The statistics of model building, refinement, and validation are summarized in Supplementary Table http://www.pymol.org/) and Chimera41.For the end-end complex, PDB ID 7TNX and 7JL1 were used as the initial search model for building into the cryo-EM map, using molrep in the ccpem software suit, respectively48, and the results were rendered using ESPript 3.0 (https://espript.ibcp.fr)49.The Riplet protein sequences from multiple mammals were aligned using Clustal Omegahttps://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb)25. To ensure the predication of dimer, the protein sequence was added twice, separated by colon symbol. The structures with highest plDDT values were selected for further analysis.The tertiary structures of full-length Riplet (1–432), RING domain (1–94) and CC domain (120–240) were predicted using ColabFold: AlphaFold2 using MMseqs2 (Further information on research design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data


We aimed to identify the immune and Toll-like receptor (TLR) signaling pathway related feature lncRNAs to construct the diagnostic nomograms for acute ischemic stroke (AIS). Two AIS-associated expression profiles GSE16561 and GSE22255 were downloaded from NCBI Gene Expression Omnibus, the former was the training set and the latter was the validation set. The differential expression genes (DEGs) and lncRNAs (DElncRNAs) related to TLR signaling pathway were identified between AIS and control groups. The single sample gene set enrichment analysis (ssGSEA) was applied to evaluate the immune infiltration. The immune and TLR signaling pathway related DElncRNAs were determined. Three optimization algorithms were utilized to select the immune and TLR signaling pathway related feature lncRNAs to construct the diagnostic nomograms of AIS. Based on the lncRNA signature, a ceRNA network was constructed. 37 DEGs and 28 DElncRNAs related to TLR signaling pathway were identified in GSE16561. 16 immune cell types exhibited significant differences in distribution between AIS and control groups. 28 immune and TLR signaling pathway related DElncRNAs were determined. 8 immune and TLR signaling pathway related feature lncRNAs were selected. The diagnostic nomograms of AIS performed well in both datasets. A ceRNA network was constructed consisting of 7 immune and TLR signaling pathway related feature lncRNAs as well as 19 AIS related miRNAs and 21 TLR signaling pathway related genes. LINC00173, LINC01089, LINC02210, MIR600HG, SNHG14, TP73-AS1, LINC00680 and CASC2 may be the potential biomarkers of AIS diagnosis, and TLR signaling pathway may be a promising immune related therapeutic target for AIS. Acute ischemic stroke (AIS) is defined by the sudden interruption of focal cerebral blood flow caused by thrombosis or embolism2. Currently, the therapeutic options of AIS are limited, and intravenous thrombolysis and endovascular thrombectomy are available for the appropriate patients3. However, aiming at restoring cerebral blood flow, both approaches are time-critical, and the narrow therapeutic time windows limit their widespread applications among patients, prompting the demand and development of novel therapeutic strategies that target the underlying mechanisms of cellular damage and recovery in the brain and periphery, such as the immune response5. The immune system is involved in the occurrence and progression of AIS, and plays a multifaceted role in the disease6. The Toll-like receptor (TLR) signaling pathway is the major innate immune response mechanism that mediates cerebral ischemic injury7. Activation of TLRs signal after ischemic insults triggers the initiation of downstream inflammatory cascades and the production of cytokines and chemokines, and further induces the immune responses, which could be either neuroprotective or detrimental to AIS8. Therefore, considering the important role of TLR signaling pathway in the pathogenesis of AIS, it may be a promising avenue for future immunotherapy of a large spectrum of AIS patients.Stroke is one of the leading causes of death and disability globally, most of which are ischemic10. LncRNAs participate in the development of ischemic stroke through various signaling pathways and biological processes following cerebral ischemic injury, including immune response, inflammation, cell apoptosis, autophagy and angiogenesis, suggesting that lncRNAs might hold a potential to be the novel biomarkers and targets in the diagnosis and treatment for AIS, and elucidating the biological roles and molecular regulation mechanisms of lncRNAs involved in the pathogenesis of AIS could contribute to the management and therapeutics for AIS patients12.Studies have reported that long non-coding RNAs (lncRNAs) were differentially expressed in ischemic stroke patients and post-ischemic mouse models to modulate the downstream gene transcription in response to ischemic injuryHerein, based on expression profiles from AIS patients, we identified the immune and TLR signaling pathway related lncRNAs through ssGSEA, and then different optimization algorithms were applied to further select feature lncRNAs. Using the lncRNA signature, the diagnostic nomograms were constructed with good performance. Combining immune and TLR signaling pathway related feature lncRNAs as well as AIS related miRNAs and TLR signaling pathway related genes, a ceRNA network was constructed which improved the knowledge of how these feature lncRNAs act in the TLR signaling pathway. The immune and TLR signaling pathway related feature lncRNAs may be the candidate biomarkers of AIS diagnosis, providing the potential for TLR signaling pathway as the promising immune related therapeutic target for AIS.http://www.ncbi.nlm.nih.gov/geo/), which provides an invaluable resource of publicly available gene expression data. GSE16561 was served as the training set, while GSE22255 was the validation set. In GSE16561, peripheral whole blood samples were obtained from 39 AIS patients and 24 healthy controls, and the platform was GPL6883 Illumina HumanRef-8 v3.0 expression beadchip. In GSE22255, whole blood samples were collected from 20 cases and 20 controls, and the platform was GPL570 Affymetrix Human Genome U133 Plus 2.0 Array. The detailed annotation files of two platforms were downloaded from Ensembl (http://asia.ensembl.org/index.html) to re-annotate the array data to gain the expression levels of mRNAs and lncRNAs.Two AIS-associated expression profiles GSE16561 and GSE22255 were downloaded from NCBI Gene Expression Omnibus (http://www.gsea-msigdb.org/gsea/downloads.jsp), which contained the information of 186 KEGG pathways and the corresponding gene sets (Supplementary Table https://cytoscape.org/). The lncRNAs involved in the significant DEG-DElncRNA co-expression pairs were considered to be associated with TLR signaling pathway.The Molecular Signatures Database (MSigDB) is a collection of the annotated gene sets that are divided into 9 major collections. KEGG subset of Canonical Pathways in C2 collection (curated gene sets) was downloaded from MsigDB , GSVA package in R3.6.1 was applied to assess the immune infiltration of samples in GSE16561. 28 immune cell types and their marker genes were obtained from Bindea et al.In the training set GSE16561, three optimization algorithms were applied for the feature lncRNA selection, including least absolute shrinkage and selection operator (LASSO), recursive feature elimination (RFE) and random forest (RF), which were implemented by lars package, caret package and randomForest package in R3.6.1, respectively. The intersection of three feature lncRNA sets was served as the immune and TLR signaling pathway related lncRNA signature.The nomogram was constructed by rms package in R3.6.1, and then decision curve analysis was performed by rmda package in R3.6.1 to evaluate the net benefit of the nomogram. The nomogram was also built in the validation set GSE22255 to verify the efficiency of the diagnostic model.http://www.cuilab.cn/hmdd) that experimentally supported human miRNA and disease associations14. Then, associations between the immune and TLR signaling pathway related feature lncRNAs and miRNAs associated with AIS were explored using DIANA-LncBasev2 , which provided experimentally supported and in silico predicted miRNA recognition elements (MREs) on lncRNAs15. The threshold was set as score > 0.7. Next, on this basis, the mRNA targets of the AIS-associated miRNAs were searched in the starBase v2.0 (http://starbase.sysu.edu.cn/)16. Genes that were both mRNA targets and DEGs associated with TLR signaling pathway were reserved. Finally, a ceRNA network was constructed by combining the lncRNA-miRNA interactions  and miRNA-mRNA interactions , which was visualized by Cytoscape3.6.1.The AIS-associated miRNAs were downloaded from the Human microRNA Disease Database (HMDD) v3.2  and 37 DEGs associated with TLR signaling pathway (34 up-regulated and 3 down-regulated) were identified Fig. . Based oThe immune infiltration of samples in GSE16561 was assessed by the ssGSEA method Fig. A, and 16LASSO, RFE and RF algorithms were applied to optimize the immune and TLR signaling pathway related lncRNAs, which screened 15, 8 and 28 feature lncRNAs, respectively (Supplementary Table Based on the lncRNA signature, a nomogram was constructed in the training set GSE16561, and the calibration curve for the diagnosis of disease demonstrated a good agreement between the nomogram and actual observation Fig. A. The DC25 miRNAs associated with AIS were obtained from HMDD v3.2. Associations between the immune and TLR signaling pathway related feature lncRNAs and miRNAs associated with AIS were explored by DIANA-LncBasev2, and 57 associations were derived including 7 feature lncRNAs and 19 miRNAs (Supplementary Table 1. With the approved treatment of AIS are limited, new therapies are needed that can improve the clinical outcome. As transmembrane receptors, TLRs are important components of the innate immune system that mediate cerebral ischemic injury and play a crucial role in the pathogenesis of AIS17. Therefore, a better understanding of molecular mechanisms of TLR signaling pathway contributes to the development of immunotherapy of AIS targeting the endogenous immune response.The global burden of stroke has increased in the past few years18. B cells seem to be both beneficial and detrimental in stroke19. The pharmacological depletion of B cells with anti-CD20, its depleting antibody, prevented the appearance of delayed cognitive deficits following stroke20.We applied ssGSEA for the immune infiltration analysis and found that 16 immune cell types exhibited significant differences in distribution between AIS and control groups, including activated CD8 T cell, central memory CD8 T cell, effector memory CD8 T cell, activated CD4 T cell, gamma delta T cell, regulatory T cell, activated B cell, memory B cell, natural killer cell, CD56dim natural killer cell, activated dendritic cell, plasmacytoid dendritic cell, macrophage, mast cell, monocyte and neutrophil. Gelderblom et al. also observed that T lymphocytes, neutrophils, macrophages and dendritic cells were increased in the infarcted hemisphere23. LINC01089 is a tumor-suppressive lncRNA in gastric cancer and lung cancer26. MIR600HG is a prognostic target of pancreatic ductal adenocarcinoma prediction, and suppresses metastasis in colorectal cancer28. TP73-AS1 regulates the progression of many tumors, such as glioblastoma and breast cancer30. CASC2 inhibits gliomas malignancy31. SNHG14 induces the activation of microglia in cerebral infarction32. However, there is lack of direct evidence regarding the practical roles of these immune and TLR signaling pathway related feature lncRNAs in AIS, which needs further investigation.The feature lncRNA selection was carried out by different optimization algorithms. Several immune and TLR signaling pathway related feature lncRNAs were obtained, including LINC00173, LINC01089, LINC02210, MIR600HG, SNHG14, TP73-AS1, LINC00680 and CASC2. Using the lncRNA signature, the diagnostic nomograms performed well in both the training set and the validation set. The knowledge of these feature lncRNA functions is poor, and previous studies linked them with cancers. For instance, LINC00173 is associated with the tumorigenesis of various cancers, including glioma, lung squamous cell carcinoma and colorectal cancerIn order to demonstrate how the immune and TLR signaling pathway related feature lncRNAs act in AIS, we explored their AIS related miRNA targets and the downstream TLR signaling pathway related target genes to construct a ceRNA network. For example, SNHG14 regulates 17 miRNAs, such as miR-145, of which target genes are TAB2, IRF7 and MAP3K8. MiR-22 is modulated by 4 lncRNAs, including LINC00680, MIR600HG, TP73-AS1 and SNHG14, and has 6 target genes which are MAPK1, MAPK14, MAP2K4, FOS, STAT1 and RAC1. The regulatory network around the immune and TLR signaling pathway related feature lncRNAs is complex, however, it provides clues for the lncRNA-based immunotherapy for AIS.There are several limitations in the present study. The datasets were limited and the sample sizes were small. Further experiments are required to explore the roles of these immune and TLR signaling pathway related feature lncRNAs and their regulatory mechanisms in the pathogenesis of AIS. Prospective researches are warranted to further demonstrate the diagnostic model in AIS patients.In conclusion, several immune and TLR signaling pathway related feature lncRNAs may be the candidate biomarkers of AIS diagnosis, including LINC00173, LINC01089, LINC02210, MIR600HG, SNHG14, TP73-AS1, LINC00680 and CASC2, providing the potential for TLR signaling pathway as the promising avenue for AIS immune therapeutic target.Supplementary Figure S1.Supplementary Figure S2.Supplementary Legends.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.Supplementary Table S6.Supplementary Table S7.


Our recent study found that another purine derivative, paraxanthine, has neuroprotective effects similar to those of caffeine and UA. These purine derivatives can promote neuronal cysteine uptake through excitatory amino acid carrier protein 1 (EAAC1) to increase neuronal glutathione (GSH) levels in the brain. This review summarizes the GSH-mediated neuroprotective effects of purine derivatives. Considering the fact that GSH depletion is a manifestation in the brains of AD and PD patients, administration of purine derivatives may be a new therapeutic approach to prevent or delay the onset of these neurodegenerative diseases.Numerous basic studies have reported on the neuroprotective properties of several purine derivatives such as caffeine and uric acid (UA). Epidemiological studies have also shown the inverse association of appropriate caffeine intake or serum urate levels with neurodegenerative diseases such as Alzheimer disease (AD) and Parkinson’s disease (PD). The well-established neuroprotective mechanisms of caffeine and UA involve adenosine A A variety of purine derivatives are produced from purine nucleotides  by metabolic processes occurring mainly in the liver. For instance, adenine nucleotides are metabolized to produce ATP, ADP, AMP, adenosine, inosine, hypoxanthine, and xanthine, and finally uric acid (UA). Caffeine , a naturally occurring purine derivative, is metabolized into several dimethylxanthines including paraxanthine, theophylline, and theobromine, and finally into UA derivatives.2A receptor (A2AAR) antagonizing activity that is involved in neuroprotection [Each purine derivative has a particular physiological activity, and several purine derivatives such as adenosine, guanosine, caffeine, paraxanthine, theophylline, theobromine, and UA have been shown to possess neuroprotective activities ,6,7,8,9.otection . The neuotection ,11. The otection ,13,14,15otection ,17,18,19otection ,21. GSH otection ,23. Therotection ,21. Increasing GSH levels is a neuroprotective mechanism that increases antioxidant activity in neurons. It is widely accepted that neuroprotective processes can be classified into three major mechanisms: (i) suppressing excessive neuronal stimulation, (ii) maintaining antioxidant activity in neurons, and (iii) detoxification of xenobiotics . Intrace−  [The intracellular presence of the antioxidants such as ascorbate, UA, and α-tocopherol help to preserve neuronal GSH levels by doing the work of protecting cells against oxidative stress through other means ,41,42,43: 23657)   . A polymHigh serum UA levels cause some critical diseases such as gout, cardiovascular disease, hypertension, and renal disease , while iAlthough some conflicting results have been reported , a signiA strong correlation of plasma antioxidant levels with both mild cognitive impairment and AD has been observed ,86. FurtAs mentioned above, some studies have supported the potential role of hyperuricemia to prevent AD, while other studies have reported conflicting results or have failed to demonstrate any significant association ,96. AlthBy treatment with urate-lowering agents, patients with gout maintain lower serum UA levels over long periods of time. One might think that low serum UA levels would impair neurons by increasing oxidative stress in the brain. However, use of urate-lowering drugs  is not correlated with any increase in the risk of dementia . TreatmeSerum UA levels are maintained by food digestion, purine synthesis, metabolism, and purine excretion into urine. The net excretion of UA in urine is determined by the balance between UA re-absorption and secretion within the proximal tubule, and each process is mediated by its specific transporter . Since uUA is also produced during ATP metabolism through the following steps : (1) ATP2 mediate hypoxanthine oxidation to form xanthine and the end metabolite, UA, concomitant with super oxide anions (O2−). Therefore, the lack of XO in the brain may protect neurons from such oxidative stress. In vivo preclinical study has shown that UA protects hippocampal neurons after ischemia reperfusion in rats [In 1981, Granger et al. and McCord et al. ,108 hypo in rats .In terms of the mechanism by which UA in blood is involved in neuroprotection in the brain, Amaro et al.  argued t+/K+ ATPase and synaptic transmission [Other than nucleic acids, the typical intracellular purine derivative is ATP, which acts as an energy source for driving neuronal activity. Huge amounts of ATP  are produced in nervous tissues to maintain energy for Nasmission ,112,113.smission ,115,116 smission  and is asmission ,119,120 ATP is converted to ADP, AMP, adenosine, inosine, hypoxanthine, and xanthine and finally yields UA in the peripheral tissues . These p1 receptor (A1AR) and A2AAR  ,122,123.As described in the Introduction and illustrated in UA has antioxidant activity ,129,130 UA both acts as a scavenger of ROS and peroxynitrite  and prev2AAR receptor antagonism , while that of caffeine is AThere are numerous examples of UA’s direct neuroprotective roles. UA protects PC12 cells from 6-OHDA-induced cell injury by increasing levels of both GSH and superoxide dismutase (SOD) protein . UA treaUA also has an indirect neuroprotective activity by increasing GSH levels in astrocytes. UA treatment activates Nrf2 and leads to upregulation of gene expression of the GCLM, which enhances GSH production in astrocytes  Table 3Table 3. 2AAR antagonism is observed in the developing retina [Nrf2 activation is another indirect mechanism by which purine derivatives provide neuroprotection. Nrf2 activation was observed when caffeine was treated as a neuroprotective agent in lipopolysaccharide (LPS)-induced oxidative stress model mice  and cadmg retina , it is s1AR and A2AAR antagonisms, because an A2AAR antagonist, SCH58261, did not increase GSH levels in hippocampal slices [1AR  and UA (1 to 10 µM) provided neuroprotection by increasing GSH levels in the brain. The upregulation of GSH synthesis is mediated by increasing Cys uptake via EAAC1 in hippocampal slices . In addil slices , and becIn astrocytes, guanosine upregulates GCL, glutamine synthetase (GS), and GSH reductase (GR), resulting in elevated GSH levels ,137 Tab. The inc1AR and A2AAR , A2AAR (IC50 = 0.150 µM), adenosine A2B receptor  (IC50 = 15.4 µM), and adenosine A3 receptor  (IC50 = 6.5 µM), which are variously activated, depending on adenosine concentrations [1AR is the most abundant in the brain. Adenosine reduces neuronal excitability and firing rate via A1AR stimulation [1AR stimulation by adenosine induces neuroprotection in cultured neurons and ischemia model of rats [1AR stimulation in animal models of ischemia [1AR stimulation inhibits Ca2+ entry into the presynaptic terminal, resulting in a reduction in neurotransmitter release [2AAR stimulation in the brain induces neuronal excitability and synaptic transmission [2AAR antagonists such as KW-6002 (istradefylline), which is xanthine-based compound, protect nigral dopaminergic cells from damage induced by 6-OHDA in rats or by MPTP in mice [2AAR lowered the dopaminergic neurotoxicity in PD model animals [1AR agonism and A2AAR antagonism [Adenosine is another purine that has neuroprotective activities. Since the 1940s, adenosine has been used clinically for cardiac protection and vasodilation . Adenositrations ,148,149 IC50 = 0. µM, adenmulation ,152. A1Aischemia . A1AR st release ,155,156  release ,158. In smission ,159. Spe in mice . Genetic animals . These r2AAR receptor, as well as its previously described category (ii) role of increasing intracellular GSH levels via Cys uptake. Methylxanthines such as caffeine and theophylline are known for their bronchoprotective effects. The molecular mechanisms include adenosine receptor antagonism  and phosphodiesterase inhibition  [1AR antagonism is involved in the stimulus effects of caffeine [2AAR antagonism [1AR and A2AAR [1AR or the A2AAR, suggesting that this effect is independent of AR activity. It is accepted that the neuroprotective activities of caffeine are mediated by A2AAR inhibition [Caffeine is another purine that offers category (i) neuroprotection through the A 400 µM)  (Table 2 400 µM) , it is e 400 µM) ,162. A1Acaffeine . Of thestagonism , and thend A2AAR ,166. Thehibition . Caffeinhibition . MechaniThere are a few other, less pervasive mechanisms responsible for neuroprotective activities of purines. UA promotes pro-survival pathways such as activating PI3K/Akt, and MEK/ERK in the brain. For example, UA treatment (200 µM UA) prevents dopamine (DA) neuron loss and behavioral deficits in 6-OHDA treated rat by recovery of Akt/GSK3β signaling  Table 3Table 3. Ya et al.  have shoParaxanthine at a concentration of 800 µM has a neuroprotective activity for dopaminergic neurons . Its neuATP itself has no neuroprotective activity corresponding to categories (i) and (ii) in 2AAR, increasing GSH levels via Cys uptake may play an important role in the neuroprotective activities of purine derivatives. As described above, the neuroprotective mechanisms of purine derivatives are mainly due to adenosine receptor modulation and upregulation of the synthesis of proteins that are involved in increasing antioxidative activity or activating pro-survival pathways in cells. Many receptor activities develop tolerance to their antagonists , i.e., cSeveral purine derivatives exhibit neuroprotective activity mediated by increasing neuronal GSH levels, which can be due to not only induction of GSH synthesis-related enzymes, but also the upregulation of GSH levels explained by promoting EAAC1-mediated Cys uptake, which is a commonly seen after treatment with caffeine, UA, or paraxanthine.The upregulation of GSH levels may enhance antioxidative activity in neurons and appears to be effective in preventing the incidence and progression of neurodegenerative disease. Further studies to investigate how purine derivatives increase GSH levels by promoting EAAC1-mediated Cys uptake would provide valuable insights into neuroprotection by purine derivative treatment. These studies of purine derivative biochemistry could lead to novel preventions and treatments for the growing burden of neurodegenerative disease in aging societies worldwide.