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The recovery of gold from industrial effluents is crucial for environmental conservation, sustainable resource management, and promoting the green development of gold resources. We designed a Zr-based MOF (UKM-78) by incorporating functional organic ligands that resemble amino groups, using MOFs' inherent sieving effect for ion separation. This novel material exhibited enhanced gold recovery under acidic conditions, with an adsorption capacity three times and an adsorption rate four times higher than those of nonfunctionalized UKM-77. Notably, UKM-78 efficiently captured gold solutions at concentrations as low as 1 ppm and achieved an adsorption rate exceeding 90%, owing to the electrostatic interactions and coordination between its functionalized groups and the synergistic effect of its porous structure. Despite multiple regeneration cycles, UKM-78 retains 99.4% of its adsorption capacity. X-ray photoelectron spectroscopy (XPS), kinetic studies, and thermodynamics collectively demonstrated that Au(III) binding on UKM-78 involved cooperative electrostatic interactions and chemical adsorption through coordination. This study highlights the potential of MOFs for efficient and sustainable recovery of gold from complex waste streams.
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The burden of rheumatoid arthritis (RA) has gradually elevated, increasing the need for medical resource redistribution. Forecasting RA patient arrivals can be helpful in managing medical resources. However, no relevant studies have been conducted yet. This study aims to construct a long short-term memory (LSTM) model, a deep learning model recently developed for novel data processing, to forecast RA patient arrivals considering meteorological factors and air pollutants and compares this model with traditional methods. Data on RA patients, meteorological factors and air pollutants from 2015 to 2022 were collected and normalized to construct moving average (MA)- and autoregressive (AR)-based and LSTM models. After data normalization, the root mean square error (RMSE) was adopted to evaluate models' forecast ability. A total of 2422 individuals were enrolled. Not using the environmental data, the RMSEs of the MA- and AR-based models' test sets are 0.131, 0.132, and 0.117 when the training set: test set ratio is 2:1, 3:1, and 7:1, while they are 0.110, 0.130, and 0.112 for the univariate LSTM models. Considering meteorological factors and air pollutants, the RMSEs of the MA- and AR-based model test sets were 0.142, 0.303, and 0.164 when the training set: test set ratio is 2:1, 3:1, and 7:1, while they were 0.108, 0.119, and 0.109 for the multivariable LSTM models. Our study demonstrated that LSTM models can forecast RA patient arrivals more accurately than MA- and AR-based models for datasets of all three sizes. Considering the meteorological factors and air pollutants can further improve the forecasting ability of the LSTM models. This novel method provides valuable information for medical management, the optimization of medical resource redistribution, and the alleviation of resource shortages.
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Poluentes Atmosféricos , Artrite Reumatoide , Previsões , Conceitos Meteorológicos , Humanos , Artrite Reumatoide/epidemiologia , Artrite Reumatoide/etiologia , Previsões/métodos , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/efeitos adversos , Feminino , Masculino , Pessoa de Meia-Idade , Aprendizado Profundo , Poluição do Ar/efeitos adversos , Poluição do Ar/análiseRESUMO
Real-time performance and reliability are two critical indicators in cyber-physical production systems (CPPS). To meet strict requirements in terms of these indicators, it is necessary to solve complex job-shop scheduling problems (JSPs) and reserve considerable redundant resources for unexpected jobs before production. However, traditional job-shop methods are difficult to apply under dynamic conditions due to the uncertain time cost of transmission and computation. Edge computing offers an efficient solution to this issue. By deploying edge servers around the equipment, smart factories can achieve localized decisions based on computational intelligence (CI) methods offloaded from the cloud. Most works on edge computing have studied task offloading and dispatching scheduling based on CI. However, few of the existing methods can be used for behavior-level control due to the corresponding requirements for ultralow latency (10 ms) and ultrahigh reliability (99.9999% in wireless transmission), especially when unexpected computing jobs arise. Therefore, this paper proposes a dynamic resource prediction scheduling (DRPS) method based on CI to achieve real-time localized behavior-level control. The proposed DRPS method primarily focuses on the schedulability of unexpected computing jobs, and its core ideas are (1) to predict job arrival times based on a backpropagation neural network and (2) to perform real-time migration in the form of human-computer interaction based on the results of resource analysis. An experimental comparison with existing schemes shows that our DRPS method improves the acceptance ratio by 25.9% compared to the earliest deadline first scheme.
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A 5G system is an advanced solution for industrial wireless motion control. However, because the scheduling model of 5G new radio (NR) is more complicated than those of other wireless networks, existing real-time scheduling algorithms cannot be used to improve the 5G performance. This results in NR resources not being fully available for industrial systems. Supervised learning has been widely used to solve complicated problems, and its advantages have been demonstrated in multiprocessor scheduling. One of the main reasons why supervised learning has not been used for 5G NR scheduling is the lack of training datasets. Therefore, in this paper, we propose two methods based on optimization modulo theories (OMT) and satisfiability modulo theories (SMT) to generate training datasets for 5G NR scheduling. Our OMT-based method contains fewer variables than existing work so that the Z3 solver can find optimal solutions quickly. To further reduce the solution time, we transform the OMT-based method into an SMT-based method and tighten the search space of SMT based on three theorems and an algorithm. Finally, we evaluate the solution time of our proposed methods and use the generated dataset to train a supervised learning model to solve the 5G NR scheduling problem. The evaluation results indicate that our SMT-based method reduces the solution time by 74.7% compared to existing ones, and the supervised learning algorithm achieves better scheduling performance than other polynomial-time algorithms.
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Wolf-Hirschhorn syndrome (WHS) is a contiguous gene deletion condition. The WHS core phenotype includes developmental delays, intellectual disabilities, seizures, and distinctive facial features. Various other comorbidities have also been reported, such as hearing loss, heart defects, as well as eye problems and kidney problems. In this report, we present a case of WHS accompanied by hyperparathyroidism and hypercalcemia, which has not been previously reported. A girl was born at 37 weeks of gestation by vaginal delivery. She was small for the gestational age (2,045 g) and admitted to neonatal intensive care unit. She had typical WHS facial features and was found to have bilateral small kidneys associated with transient metabolic acidosis and renal insufficiency. She had right-sided sensorineural hearing loss, a small atrial septal defect, and colpocephaly and hypoplasia of corpus callosum. She had a single seizure which was well controlled with an oral antiepileptic medication. Cytogenetic studies demonstrated a large terminal chromosome 4p deletion (21.4 Mb) and 4p duplication (2.1 Mb) adjacent to the deletion. A unique finding in this patient is her consistently elevated levels of parathyroid hormone and serum calcium, suggesting hyperparathyroidism. We present this rare case along with a review of the literature and hope to draw an attention to a potential relationship between WHS and hyperparathyroidism.
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The increasingly large structure of neural networks makes it difficult to deploy on edge devices with limited computing resources. Network pruning has become one of the most successful model compression methods in recent years. Existing works typically compress models based on importance, removing unimportant filters. This paper reconsiders model pruning from the perspective of structural redundancy, claiming that identifying functionally similar filters plays a more important role, and proposes a model pruning framework for clustering-based redundancy identification. First, we perform cluster analysis on the filters of each layer to generate similar sets with different functions. We then propose a criterion for identifying redundant filters within similar sets. Finally, we propose a pruning scheme that automatically determines the pruning rate of each layer. Extensive experiments on various benchmark network architectures and datasets demonstrate the effectiveness of our proposed framework.
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Oxygen supply for ischemic brain tissue during stroke is critical to neuroprotection. Remote ischemic conditioning (RIC) treatment is effective for stroke. However, it is not known whether RIC can improve brain tissue oxygen supply. In current study, we employed a mouse model of stroke created by middle cerebral artery occlusion (MCAO) to investigate the effect of RIC on oxygen supply to the ischemic brain tissue using a hypoxyprobe system. Erythrocyte oxygen-carrying capacity and tissue oxygen exchange were assessed by measuring oxygenated hemoglobin and oxygen dissociation curve. We found that RIC significantly mitigated hypoxic signals and decreased neural cell death, thereby preserving neurological functions. The tissue oxygen exchange was markedly enhanced, along with the elevated hemoglobin P50 and right-shifted oxygen dissociation curve. Intriguingly, RIC markedly elevated 2,3-biphosphoglycerate (2,3-BPG) levels in erythrocyte, and the erythrocyte 2,3-BPG levels were highly negatively correlated with the hypoxia in the ischemic brain tissue. Further, adoptive transfusion of 2,3-BPG-rich erythrocytes prepared from RIC-treated mice significantly enhanced the oxygen supply to the ischemic tissue in MCAO mouse model. Collectively, RIC protects against ischemic stroke through improving oxygen supply to the ischemic brain tissue where the enhanced tissue oxygen delivery and exchange by RIC-induced 2,3-BPG-rich erythrocytes may play a role.
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2,3-Difosfoglicerato/metabolismo , Isquemia Encefálica/sangue , Eritrócitos/metabolismo , Precondicionamento Isquêmico , Acidente Vascular Cerebral/sangue , Animais , Encéfalo/irrigação sanguínea , Isquemia Encefálica/fisiopatologia , Modelos Animais de Doenças , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Acidente Vascular Cerebral/fisiopatologiaRESUMO
Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic neoplasm that exhibits myelodysplastic and myeloproliferative characteristics with heterogeneous clinical and pathological features. There are limited publications on the ethnic and racial disparity of cytogenetics and genomics in CMML patients. This study aims to define the cytogenetic and molecular landscape in Hispanic CMML patients from Puerto Rico and explore its possible clinical significance. One hundred and eleven (111) Hispanic CMML patients from Puerto Rico were diagnosed in our institute from 2009 to 2018. Karyotypes were available in one hundred and seven (107) patients. Seventeen (17) patients had abnormal karyotypes (17/107, 16%). Compared to previously published data, Hispanic CMML patients in this study had significantly lower rates of overall cytogenetic abnormalities (16% vs 27-28%, p < 0.05) and trisomy 8 (2% vs 7%, p < 0.05). Among one hundred and eleven (111) Hispanic CMML patients, 40-gene myeloid molecular profile tests were performed in fifty-six (56) CMML patients. Gene mutations were identified in fifty-four (54) patients (96%). The most frequent mutated genes were: TET2, SRSF2, ASXL1, ZRSR2, DNMT3A, NRAS, CBL, and RUNX1. Twenty-nine (29) out of fifty-six (56) patients (29/56, 52%) had mutated TET2/wild type ASXL1 (muTET2/wtASXL1). Previous studies indicated that mutated ASXL1, DNMT3A, NRAS, RUNX1, and SETBP1 may associate with an unfavorable prognosis and muTET2/wtASXL1 may associate with a favorable prognosis in CMML patients. Compared to previously published data, Hispanic CMML patients from Puerto Rico in this study had significantly lower mutation rates in ASXL1 and SETBP1, and a higher rate of muTET2/wtASXL1. The findings raise the possibility of a favorable prognosis in Hispanic CMML patients.
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Remote ischemic preconditioning (RIPC) is an effective regimen for neuroprotection in ischemic stroke. Exosomes are extracellular vesicles released into the blood, where they can transfer signals throughout the body. Several studies have demonstrated that RIPC leads to many changes in circulating exosomes. However, the role of RIPC-induced exosomes in neuroprotection remains to be determined. In the current study, we demonstrate that infusion of enriched plasma exosomes from RIPC-treated mice significantly attenuates infarction size in a murine model of cerebral ischemia compared to control group receiving infusion of exosomes from non-RIPC-treated mice. Further studies show that infusion of RIPC-exosomes markedly improves neurological functions. In line with the above findings, we find that the level of hypoxia inducible transcription factor (HIF)-1α is significantly higher in plasma exosomes from mice subjected to RIPC than those from control mice, which could have contributed to the RIPC-exosome-induced neuroprotection through HIF-1α-induced signals including the enhanced tolerance to hypoxia. To our knowledge, this is the first to demonstrate RIPC protects against cerebral ischemia through inducing neuroprotective exosomes.
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Isquemia Encefálica , Exossomos , Precondicionamento Isquêmico , Neuroproteção/fisiologia , Animais , Isquemia Encefálica/metabolismo , Exossomos/metabolismo , Exossomos/transplante , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Masculino , Camundongos , Camundongos Endogâmicos C57BLRESUMO
Antigen specificity is a primary goal in developing curative therapies for autoimmune disease. Dendritic cells (DCs), as the most effective antigen presenting cells in the body, represent a key target to mediate restoration of antigen-specific immune regulation. Here, we describe an injectable, dual-sized microparticle (MP) approach that employs phagocytosable â¼1 µm and nonphagocytosable â¼30 µm MPs to deliver tolerance-promoting factors both intracellularly and extracellularly, as well as the type 1 diabetes autoantigen, insulin, to DCs for reprogramming of immune responses and remediation of autoimmunity. This poly(lactic-co-glycolic acid) (PLGA) MP system prevented diabetes onset in 60% of nonobese diabetic (NOD) mice when administered subcutaneously in 8 week old mice. Prevention of disease was dependent upon antigen inclusion and required encapsulation of factors in MPs. Moreover, administration of this "suppressive-vaccine" boosted pancreatic lymph node and splenic regulatory T cells (Tregs), upregulated PD-1 on CD4+ and CD8+ T cells, and reversed hyperglycemia for up to 100 days in recent-onset NOD mice. Our results demonstrate that a MP-based platform can reeducate the immune system in an antigen-specific manner, augment immunomodulation compared to soluble administration of drugs, and provide a promising alternative to systemic immunosuppression for autoimmunity.
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The major metabolic feature of diabetes is hyperglycemia which has been linked to the diabetes inflammatory processes, and diabetes-related vulnerability to infection. In the present study, we assessed how glucose affected PBMCs in type I interferon (IFN) production and subsequent signaling. We found that the moderately elevated glucose promoted, and high glucose suppressed type I IFN production, respectively. Pre-exposure to high glucose rendered monocytes more sensitive to IFN-α stimulation with heightened signaling, whereas, instantaneous addition of high glucose did not exhibit such effect. Consistent with this finding, the mRNA levels of IFN-α-induced IRF-7 in PBMCs were positively correlated with HbA1c levels of diabetes patients. Additionally, we found that high glucose promoted the production of other proinflammatory cytokines/chemokines. This study suggests that hyperglycemia may affect the inflammatory process in diabetes via promoting proinflammatory cytokines, as well as the host defense against microbial infections through impeding type I IFN production and signaling.
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Complicações do Diabetes/imunologia , Glucose/metabolismo , Hiperglicemia/imunologia , Infecções/imunologia , Inflamação/imunologia , Interferon Tipo I/metabolismo , Monócitos/imunologia , Adolescente , Adulto , Criança , Feminino , Hemoglobinas Glicadas/metabolismo , Humanos , Imunidade , Fator Regulador 7 de Interferon/genética , Fator Regulador 7 de Interferon/metabolismo , Masculino , Lectina 1 Semelhante a Ig de Ligação ao Ácido Siálico/metabolismo , Transdução de Sinais , Células THP-1 , Adulto JovemRESUMO
Dendritic cell (DC) immunotherapy has been effective for prevention of type 1 diabetes (T1D) in NOD mice but fails to protect if initiated after active autoimmunity. As autoreactivity expands inter- and intramolecularly during disease progression, we investigated whether DCs unpulsed or pulsed with ß cell antigenic dominant determinants (DD), subdominant determinants (SD), and ignored determinants (ID) could prevent T1D in mice with advanced insulitis. We found that diabetes was significantly delayed by DC therapy. Of interest, DCs pulsed with SD or ID appeared to provide better protection. T lymphocytes from DC-treated mice acquired spontaneous proliferating capability during in vitro culture, which could be largely eliminated by IL-2 neutralizing antibodies. This trend maintained even 29 weeks after discontinuing DC therapy and appeared antigen-independent. Furthermore, CD4+Foxp3+ T regulatory cells (Tregs) from DC-treated mice proliferated more actively in vitro compared to the controls, and Tregs from DC-treated mice showed significantly enhanced immunosuppressive activities in contrast to those from the controls. Our study demonstrates that DC therapy leads to long-lasting immunomodulatory effects in an antigen-dependent and antigen-independent manner and provides evidence for peptide-based intervention during a clinically relevant window to guide DC-based immunotherapy for autoimmune diabetes.
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Células Dendríticas/fisiologia , Diabetes Mellitus Tipo 1/terapia , Imunoterapia Adotiva/métodos , Subpopulações de Linfócitos T/imunologia , Linfócitos T Reguladores/imunologia , Animais , Apresentação de Antígeno , Autoantígenos/imunologia , Autoantígenos/metabolismo , Autoimunidade , Diferenciação Celular , Proliferação de Células , Células Cultivadas , Diabetes Mellitus Tipo 1/imunologia , Modelos Animais de Doenças , Epitopos de Linfócito T/imunologia , Epitopos de Linfócito T/metabolismo , Feminino , Fatores de Transcrição Forkhead/metabolismo , Humanos , Tolerância Imunológica , Epitopos Imunodominantes/imunologia , Epitopos Imunodominantes/metabolismo , Imunomodulação , Células Secretoras de Insulina/imunologia , Células Secretoras de Insulina/metabolismo , Ativação Linfocitária , Camundongos , Camundongos Endogâmicos NODRESUMO
Myeloid-derived suppressor cells (MDSCs) are identified as a heterogeneous population of cells with the function to suppress innate as well as adaptive immune responses. The initial studies of MDSCs were primarily focused on the field of animal tumor models or cancer patients. In cancer, MDSCs play the deleterious role to inhibit tumor immunity and to promote tumor development. Over the past few years, an increasing number of studies have investigated the role of MDSCs in autoimmune diseases. The beneficial effects of MDSCs in autoimmunity have been reported by some studies, and thus, immunosuppressive MDSCs may be a novel therapeutic target in autoimmune diseases. There are some controversial findings as well. Many questions such as the activation, differentiation, and suppressive functions of MDSCs and their roles in autoimmune diseases remain unclear. In this review, we have discussed the current understanding of MDSCs in autoimmune diseases.
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Doenças Autoimunes/imunologia , Doenças Autoimunes/terapia , Células Supressoras Mieloides/imunologia , Animais , Autoimunidade/fisiologia , HumanosRESUMO
Glycans possess significant chemical diversity; glycan binding proteins (GBPs) recognize specific glycans to translate their structures to functions in various physiological and pathological processes. Therefore, the discovery and characterization of novel GBPs and characterization of glycan-GBP interactions are significant to provide potential targets for therapeutic intervention of many diseases. Here, we report the biochemical, functional, and structural characterization of a 130-amino-acid protein, Y3, from the mushroom Coprinus comatus Biochemical studies of recombinant Y3 from a yeast expression system demonstrated the protein is a unique GBP. Additionally, we show that Y3 exhibits selective and potent cytotoxicity toward human T-cell leukemia Jurkat cells compared with a panel of cancer cell lines via inducing caspase-dependent apoptosis. Screening of a glycan array demonstrated GalNAcß1-4(Fucα1-3)GlcNAc (LDNF) as a specific Y3-binding ligand. To provide a structural basis for function, the crystal structure was solved to a resolution of 1.2 Å, revealing a single-domain αßα-sandwich motif. Two monomers were dimerized to form a large 10-stranded, antiparallel ß-sheet flanked by α-helices on each side, representing a unique oligomerization mode among GBPs. A large glycan binding pocket extends into the dimeric interface, and docking of LDNF identified key residues for glycan interactions. Disruption of residues predicted to be involved in LDNF/Y3 interactions resulted in the significant loss of binding to Jurkat T-cells and severely impaired their cytotoxicity. Collectively, these results demonstrate Y3 to be a GBP with selective cytotoxicity toward human T-cell leukemia cells and indicate its potential use in cancer diagnosis and treatment.
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Agaricales/metabolismo , Coprinus/metabolismo , Proteínas Fúngicas/metabolismo , Polissacarídeos/metabolismo , Sequência de Aminoácidos , Apoptose/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Cristalografia por Raios X , Proteínas Fúngicas/química , Proteínas Fúngicas/farmacologia , Células HEK293 , Humanos , Células Jurkat , Modelos Moleculares , Ligação Proteica , Conformação Proteica , Multimerização Proteica , Homologia de Sequência de AminoácidosRESUMO
Wireless sensor networks (WSNs) are widely applied in industrial manufacturing systems. By means of centralized control, the real-time requirement and reliability can be provided by WSNs in industrial production. Furthermore, many approaches reserve resources for situations in which the controller cannot perform centralized resource allocation. The controller assigns these resources as it becomes aware of when and where accidents have occurred. However, the reserved resources are limited, and such incidents are low-probability events. In addition, resource reservation may not be effective since the controller does not know when and where accidents will actually occur. To address this issue, we improve the reliability of scheduling for emergency tasks by proposing a method based on a stealing mechanism. In our method, an emergency task is transmitted by stealing resources allocated to regular flows. The challenges addressed in our work are as follows: (1) emergencies occur only occasionally, but the industrial system must deliver the corresponding flows within their deadlines when they occur; (2) we wish to minimize the impact of emergency flows by reducing the number of stolen flows. The contributions of this work are two-fold: (1) we first define intersections and blocking as new characteristics of flows; and (2) we propose a series of distributed routing algorithms to improve the schedulability and to reduce the impact of emergency flows. We demonstrate that our scheduling algorithm and analysis approach are better than the existing ones by extensive simulations.
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Type 1 diabetes (T1D) has been associated with both genetic and environmental factors. Increasing incidence of T1D worldwide is prompting researchers to adopt different approaches to explain the biology of T1D, beyond the presence and activity of autoreactive lymphocytes. In this review, we propose inflammatory pathways as triggers for T1D. Within the scope of those inflammatory pathways and in understanding the pathogenesis of disease, we suggest that viruses, in particular Coxsackieviruses, act by causing a type 1 interferonopathy within the pancreas and the microenvironment of the islet. As such, this connection and common thread represents an exciting platform for the development of new diagnostic, treatment and/or prevention options.
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Infecções por Coxsackievirus/imunologia , Diabetes Mellitus Tipo 1/imunologia , Interferons/metabolismo , Pancreatopatias/virologia , Animais , Microambiente Celular , Imunidade Inata , Ilhotas Pancreáticas/imunologia , Pancreatopatias/imunologia , Transdução de SinaisRESUMO
T cells engineered with chimeric antigen receptor (CAR) have been successfully applied to treat advanced refractory B cell malignancy. However, many challenges remain in extending its application toward the treatment of solid tumors. The immunosuppressive nature of tumor microenvironment is considered one of the key factors limiting CAR-T efficacy. One negative regulator of Tcell activity is lymphocyte activation gene-3 (LAG-3). We successfully generated LAG-3 knockout Tand CAR-T cells with high efficiency using CRISPR-Cas9 mediated gene editing and found that the viability and immune phenotype were not dramatically changed during in vitro culture. LAG-3 knockout CAR-T cells displayed robust antigen-specific antitumor activity in cell culture and in murine xenograft model, which is comparable to standard CAR-T cells. Our study demonstrates an efficient approach to silence immune checkpoint in CAR-T cells via gene editing.
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Antígenos CD/imunologia , Sistemas CRISPR-Cas/imunologia , Receptores de Antígenos de Linfócitos T/imunologia , Animais , Linhagem Celular Tumoral , Edição de Genes/métodos , Tolerância Imunológica/imunologia , Camundongos , Camundongos Knockout , Microambiente Tumoral/imunologia , Ensaios Antitumorais Modelo de Xenoenxerto , Proteína do Gene 3 de Ativação de LinfócitosRESUMO
Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones.
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Our previous study demonstrated that transfusion of ultraviolet B-irradiated immature dendritic cells (UVB-iDCs) induced alloantigen-specific tolerance between two different strains of mice. Programmed death-1 (PD-1) and programmed death ligand-1 (PD-L1) have been suggested to play an important role in maintaining immune tolerance. In the present study, we seek to address whether PD-1/PD-L1 plays a role in the maintenance of UVB-iDC-induced tolerance. We first observe that the UVB-iDC-induced alloantigen-specific tolerance can be maintained for over 6 weeks. Supporting this, at 6 weeks after tolerance induction completion, alloantigen-specific tolerance is still able to be transferred to syngeneic naïve mice through adoptive transfer of CD4+ T cells. Furthermore, skin transplantation study shows that the survival of allogeneic grafts is prolonged in those tolerant recipients. Further studies show that PD-1/PD-L1 interaction is essential for maintaining the induced tolerance as blockade of PD-1/PD-L1 by anti-PD-L1 antibodies largely breaks the tolerance at both cellular and humoral immunological levels. Importantly, we show that PD-1/PD-L1 interaction in tolerant mice is also essential for controlling alloantigen-responding T cells, which have never experienced alloantigens. The above findings suggest that PD-1/PD-L1 plays a crucial role in maintaining immune tolerance induced by UVB-iDCs, as well as in actively controlling effector T cells specific to alloantigens.