An integrated electronic tag-based vertical flow assay (e-VFA) with micro-sieve and AlGaN/GaN HEMT sensors for multi-target detection in actual saliva.

Vertical flow assay (VFA) is an effective point-of-care (POC) diagnostic tool for widespread application. Nevertheless, the lack of multi-target detection and multi-signal readout capability still remains a challenge. Herein, a brand new VFA scheme for multi-target saliva detection based on electronic tags was proposed, where AlGaN/GaN HEMT sensors modified with different bio-receptors as electronic tags endowed the VFA with multi-target detection capability. In addition, the use of electronic tags instead of optical tags allowed the VFA to simultaneously carry out direct multi-target readouts, which ensure effective POC diagnostics for saliva analysis. Moreover, by integrating a hydrophilically optimized micro-sieve, impurities like sticky filaments, epidermal cells and other large-scale charged particles in saliva were effectively screened, which enabled the direct detection of saliva using AlGaN/GaN HEMT sensors. Glucose, urea, and cortisol were selected to verify the feasibility of the multi-target e-VFA scheme, and the results showed that the limit of detection (LOD) was as low as 100 aM. The linear response was demonstrated in the dynamic range of 100 aM to 100 µM, and the specificity, long-term stability and validity of the actual saliva test were also verified. These results demonstrated that the as-proposed e-VFA has potential for application in saliva detection for simultaneous multi-target detection, and it is expected to achieve the real-time detection of more biological targets in saliva.

Ba2Ga2F6(IO3)(PO4): the first fluoride-containing iodate-phosphate with a 1D [Ga2F6(IO3)(PO4)]4- helix chain.

Herein, the first F-containing iodate-phosphate, namely Ba2Ga2F6(IO3)(PO4), was prepared via a hydrothermal reaction, in which HPF6 (70 wt% solution in water) was used as the source of both fluoride and phosphate anions for the first time. Ba2Ga2F6(IO3)(PO4) features an unprecedented 1D [Ga2F6(IO3)(PO4)]4- helix chain, composed of a 1D Ga(1)(IO3)O4F chain via the bridging of 0D Ga(2)(PO4)F5. The UV-Vis spectrum shows that Ba2Ga2F6(IO3)(PO4) has a wide bandgap with a short-UV absorption edge (4.35 eV; 253 nm). Birefringence measurement under a polarizing microscope shows that Ba2Ga2F6(IO3)(PO4) displays a moderate birefringence of 0.072@550 nm, which is consistent with the value (0.070@550 nm) obtained by DFT calculations, indicating that Ba2Ga2F6(IO3)(PO4) has potential applications as a short-UV birefringent material. This study highlights the crucial role played by the incorporation of specific functional groups into compounds, shedding light on their contribution to promising inorganic functional materials.

Hg16O12(NO3)6F2(H2O): A Mercury-Rich Nitrate Oxyfluoride with Diverse Triple-Coordinated Mercury-Based Units That Exhibits an Unparalleled [(Hg16O12F2(H2O))6+]∞ Cationic Framework and a Large Birefringence.

Designing new compounds based on anion regulation has been widely favored due to the production of diverse crystal structures and excellent optical properties. Here, a new nitrate oxyfluoride, Hg16O12(NO3)6F2(H2O), has been obtained through a hydrothermal reaction. It crystallizes in the centric Ibca space group and shows a novel three-dimensional [(Hg16O12F2(H2O))6+]∞ cationic framework composed of interconnected HgO2F, HgO3, and HgO2(H2O) units, with isolated NO3- groups as balanced anions to build the whole structure. Notably, the HgO2F and HgO2(H2O) units are first presented here among mercury (Hg)-based compounds. Additionally, Hg16O12(NO3)6F2(H2O) exhibits a large birefringence of 0.17 at 546 nm. This work enriches the multiformity of Hg-based compounds and provides a route for developing promising birefringent materials.

Real-time free spectral range measurement based on a correlated resonance-tracking technology.

In this paper, we present a real-time measurement technology for the free spectral range (FSR) of an ultrahigh-aspect-ratio silicon nitride (Si3N4) waveguide ring resonator (WRR). Two different correlated resonant modes were tracked by two optical single-sideband frequency-shifted lights to eliminate interference noise in the Pound-Drever-Hall error signals. A relative precision of 0.1474 ppm was achieved for a 35 mm WRR with FSR = 1,844,944.5 kHz and finesse (F) = 13.2. Furthermore, a cross-correlation of 0.913 between FSR-calculated and thermistor-measured temperatures indicated a high correlation between the real-time FSR and room temperature. We believe this technology is currently the best way to realize low-finesse (F < 50) real-time FSR measurements in the GHz range.

From H12C4N2CdI4 to H11C4N2CdI3: a highly polarizable CdNI3 tetrahedron induced a sharp enhancement of second harmonic generation response and birefringence.

In this study, we identify a novel class of second-order nonlinear optical (NLO) crystals, non-π-conjugated piperazine (H10C4N2, PIP) metal halides, represented by two centimeter-sized, noncentrosymmetric organic-inorganic metal halides (OIMHs), namely H12C4N2CdI4 (P212121) and H11C4N2CdI3 (Cc). H12C4N2CdI4 is the first to be prepared, and its structure contains a CdI4 tetrahedron, which led to a poor NLO performance, including a weak and non-phase-matchable second harmonic generation (SHG) response of 0.5 × KH2PO4 (KDP), a small birefringence of 0.047 @1064 nm and a narrow bandgap of 3.86 eV. Moreover, H12C4N2CdI4 is regarded as the model compound, and we further obtain H11C4N2CdI3via the replacement of CdI4 with a highly polarizable CdNI3 tetrahedron, which results in a sharp enhancement of SHG response and birefringence. H11C4N2CdI3 exhibits a promising NLO performance including 6 × KDP, 4.10 eV, Δn = 0.074 @1064 nm and phase matchability, indicating that it is the first OIMH to simultaneously exhibit strong SHG response (>5 × KDP) and a wide bandgap (>4.0 eV). Our work presents a novel direction for designing high-performance NLO crystals based on organic-inorganic halides and provides important insights into the role of the hybridized tetrahedron in enhancing the SHG response and birefringence.

Understanding the Microstructure Evolution of 8Cr4Mo4V Steel under High-Dose-Rate Ion Implantation.

In this study, the effect of microstructure under various dose rates of plasma immersion ion implantation on 8Cr4Mo4V steel has been investigated for crystallite size, lattice strain and dislocation density. The phase composition and structure parameters including crystallite size, dislocation density and lattice strain have been investigated by X-ray diffraction (XRD) measurements and determined from Scherrer's equation and three different Williamson-Hall (W-H) methods. The obtained results reveal that a refined crystallite size, enlarged microstrain and increased dislocation density can be obtained for the 8Cr4Mo4V steel treated by different dose rates of ion implantation. Compared to the crystallite size (15.95 nm), microstrain (5.69 × 10-3) and dislocation density (8.48 × 1015) of the dose rate of 2.60 × 1017 ions/cm2·h, the finest grain size, the largest microstrain and the highest dislocation density of implanted samples can be achieved when the dose rate rises to 5.18 × 1017 ions/cm2·h, the effect of refining is 26.13%, and the increment of microstrain and dislocation density are 26.3% and 45.6%, respectively. Moreover, the Williamson-Hall plots are fitted linearly by taking ßcosθ along the y-axis and 4sinθ or 4sinθ/Yhkl or 4sinθ(2/Yhkl)1/2 along the x-axis. In all of the W-H graphs, it can be observed that some of the implanted samples present a negative and a positive slope; a negative and a positive slope in the plot indicate the presence of compressive and tensile strain in the material.

Optimizing extinguishing angle of 6MF-30 pneumatic extinguisher for wildland fire-fighting based on CFD and experiments.

The 6MF-30 pneumatic extinguisher is a widely utilized and efficient tool for combating wildland fires. However, using incorrect extinguishing angles can diminish its effectiveness. This study aimed to determine the optimal extinguishing angle for the 6MF-30 pneumatic extinguisher by conducting computational fluid dynamics simulations and experimental verification. The findings revealed that ground roughness did not significantly affect the optimal extinguishing angle or the attenuation of jet velocity near the fan outlet region. The study determined that an optimal extinguishing angle of 37° applies to lossless ground, natural grassland, grassland with artificial disturbance, and enclosed grassland. Furthermore, among the selected angles, the highest rate of jet velocity reduction was observed at 45°, whereas the slowest reduction occurred at 20° and 25°. These findings offer valuable insights and recommendations for enhancing the efficacy of wildland fire-fighting when employing the 6MF-30 pneumatic extinguisher.

Air volume flow rate optimization of the guide vanes in an axial flow fan based on DOE and CFD.

The unreasonable design of guide vanes in the axial fan could have negative effects. In order to enhance the performance, the relationship between the air volume flow rate of the selected axial fan and geometric parameters of guide vanes is firstly analysed by DOE and CFD, and optimal parameters are found by the Gaussian Process method. Results show that the number and total chord of guide vanes have a nonlinear effect on the air volume flow, and the total chord of vanes is the main factor in affecting calculation results. For the particular configuration studied here, the optimal design of guide vanes shows that lessening the chord of vanes by 38 mm and increasing the number of the vanes to 18 could produce more airflow under the same rotation speed.

ScAlN Film-Based Piezoelectric Micromechanical Ultrasonic Transducers with Dual-Ring Structure for Distance Sensing.

Piezoelectric micromechanical ultrasonic transducers (pMUTs) are new types of distance sensors with great potential for applications in automotive, unmanned aerial vehicle, robotics, and smart homes. However, previously reported pMUTs are limited by a short sensing distance due to lower output sound pressure. In this work, a pMUT with a special dual-ring structure based on scandium-doped aluminum nitride (ScAlN) is proposed. The combination of a dual-ring structure with pinned boundary conditions and a high piezoelectric performance ScAlN film allows the pMUT to achieve a large dynamic displacement of 2.87 µm/V and a high electromechanical coupling coefficient (kt2) of 8.92%. The results of ranging experiments show that a single pMUT achieves a distance sensing of 6 m at a resonant frequency of 91 kHz, the farthest distance sensing registered to date. This pMUT provides surprisingly fertile ground for various distance sensing applications.

Leveraging Deep Neural Networks for Estimating Vickers Hardness from Nanoindentation Hardness.

This research presents a comprehensive analysis of deep neural network models (DNNs) for the precise prediction of Vickers hardness (HV) in nitrided and carburized M50NiL steel samples, with hardness values spanning from 400 to 1000 HV. By conducting rigorous experimentation and obtaining corresponding nanoindentation data, we evaluated the performance of four distinct neural network architectures: Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory network (LSTM), and Transformer. Our findings reveal that MLP and LSTM models excel in predictive accuracy and efficiency, with MLP showing exceptional iteration efficiency and predictive precision. The study validates models for broad application in various steel types and confirms nanoindentation as an effective direct measure for HV hardness in thin films and gradient-variable regions. This work contributes a validated and versatile approach to the hardness assessment of thin-film materials and those with intricate microstructures, enhancing material characterization and potential application in advanced material engineering.

Case report: Application of nonsurgical method in saving transplant renal vein thrombosis caused by acute diarrhea.

Transplant renal vein thrombosis is a rare complication after kidney transplantation, which can seriously threaten graft survival. Though the measures like thrombolytic therapy or operative intervention could be taken to deal with this complication, allograft loss is the most common outcome. Thus, early finding as well as decisive intervention is crucial to saving the graft. Here we present a 46-year-old male patient who underwent kidney transplantation from a cadaveric donor who developed a transplant renal venous thrombosis induced by acute diarrhea more than 1 year after renal transplantation with an initial symptom of sudden anuria and pain in the graft area. Subsequently, serum creatinine levels increased to 810.0 µmol/L. Pelvic CT showed increased vascular density of the transplanted kidney, and contrast-enhanced ultrasound confirmed venous thrombosis. The patient was treated with heparin sodium alone and diuresis gradually resumed. After more than 1 year of follow-up, serum creatinine returned to the baseline level prior to thrombosis. Our case indicates that quick ancillary examination and treatment without hesitation would be indispensable in rescuing allografts with renal vein thrombus. Unfractionated heparin can be recommended as an effective treatment for mid-long-term renal transplantation patients with renal vein thrombosis.

Donor Death Category Is an Effect Modifier Between Cold Ischemia Time and Post-transplant Graft Function in Deceased-Donor Kidney Transplant Recipients.

Objectives: We aimed to analyze the effect of cold ischemia time (CIT) on post-transplant graft function through mixed-effect model analysis to reduce the bias caused by paired mate kidneys. Methods: We reviewed all kidney transplantation records from 2015 to 2019 at our center. After applying the exclusion criteria, 561 cases were included for analysis. All donor characteristics, preservation and matching information, and recipient characteristics were collected. Transplant outcomes included delayed graft function (DGF) and estimated glomerular filtration rate (eGFR). Generalized linear mixed models were applied for analysis. We also explored potential effect modifiers, namely, donor death category, expanded criteria donors, and donor death causes. Results: Among the 561 cases, 79 DGF recipients developed DGF, and 15 recipients who died after surgery were excluded from the eGFR estimation. The median stable eGFR of the 546 recipients was 60.39 (47.63, 76.97) ml/min/1.73 m2. After adjusting for confounding covariates, CIT had a negative impact on DGF incidence [odds ratio = 1.149 (1.006, 1.313), P = 0.041]. In the evaluation of the impact on eGFR, the regression showed that CIT had no significant correlation with eGFR [ß = -0.287 (-0.625, 0.051), P = 0.096]. When exploring potential effect modifiers, only the death category showed a significant interaction with CIT in the effect on eGFR (P interaction = 0.027). In the donation after brain death (DBD) group, CIT had no significant effect on eGFR [ß = 0.135 (-0.433, 0.702), P = 0.642]. In the donation after circulatory death/donation after brain death followed by circulatory death (DCD/DBCD) group, CIT had a significantly negative effect on eGFR [ß= -0.700 (-1.196, -0.204), P = 0.006]. Compared to a CIT of 0-6 h, a CIT of 6-8 or 8-12 h did not decrease the post-transplant eGFR. CIT over 12 h (12-16 h or over 16 h) significantly decreased eGFR. With the increase in CIT, the regenerated eGFR worsened (P trend = 0.011). Conclusion: Considering the effect of paired mate kidneys, the risk of DGF increased with prolonged CIT. The donor death category was an effect modifier between CIT and eGFR. Prolonged CIT did not reduce the eGFR level in recipients from DBDs but significantly decreased the eGFR in recipients from DCDs/DBCDs. This result indicates the potential biological interaction between CIT and donor death category.

Unveiling the Electronic Structure of Grain Boundaries in Anatase with Electron Microscopy and First-Principles Modeling.

Polycrystalline anatase titanium dioxide has drawn great interest, because of its potential applications in high-efficiency photovoltaics and photocatalysts. There has been speculation on the electronic properties of grain boundaries but little direct evidence, because grain boundaries in anatase are challenging to probe experimentally and to model. We present a combined experimental and theoretical study of anatase grain boundaries that have been fabricated by epitaxial growth on a bicrystalline substrate, allowing accurate atomic-scale models to be determined. The electronic structure in the vicinity of stoichiometric grain boundaries is relatively benign to device performance but segregation of oxygen vacancies introduces barriers to electron transport, because of the development of a space charge region. An intrinsically oxygen-deficient boundary exhibits charge trapping consistent with electron energy loss spectroscopy measurements. We discuss strategies for the synthesis of polycrystalline anatase in order to minimize the formation of such deleterious grain boundaries.

Highly Sensitive Uric Acid Detection Based on a Graphene Chemoresistor and Magnetic Beads.

In this study, we developed a low-cost, reusable, and highly sensitive analytical platform for the detection of the human metabolite uric acid (UA). This novel analysis platform combines the graphene chemoresistor detection technique with a magnetic bead (MB) system. The heterojunction (single-layer graphene and HfO2 thin-film material) of our graphene-based biosensor worked as a transducer to detect the pH change caused by the specific catalytic reaction between UA and uricase, and hence acquires a UA concentration. Immobilization of uricase on MBs can decouple the functionalization steps from the sensor surface, which allows the sensor to be reusable. Our microsensor platform exhibits a relatively lower detection limit (1 µM), high sensitivity (5.6 mV/decade), a linear range (from 1 µM to 1000 µM), and excellent linearity (R2 = 0.9945). In addition, interference assay and repeatability tests were conducted, and the result suggests that our method is highly stable and not affected by common interfering substances (glucose and urea). The integration of this high-performance and compact biosensor device can create a point-of-care diagnosis system with reduced cost, test time, and reagent volume.

Signature Panel of 11 Methylated mRNAs and 3 Methylated lncRNAs for Prediction of Recurrence-Free Survival in Prostate Cancer Patients.

BACKGROUND: Radical prostatectomy is the main treatment for prostate cancer (PCa), a common cancer type among men. Recurrence frequently occurs in a proportion of patients. Therefore, there is a great need to early screen those patients to specifically schedule adjuvant therapy to improve the recurrence-free survival (RFS) rate. This study aims to develop a biomarker to predict RFS for patients with PCa based on the data of methylation, an important heritable contributor to carcinogenesis. METHODS: Methylation expression data of PCa patients were downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus database (GSE26126), and the European Bioinformatics Institute (E-MTAB-6131). The stable co-methylation modules were identified by weighted gene co-expression network analysis. The genes in modules were overlapped with differentially methylated RNAs (DMRs) screened by MetaDE package in three datasets, which were used to screen the prognostic genes using least absolute shrinkage and selection operator analyses. The prognostic performance of the prognostic signature was assessed by survival curve analysis. RESULTS: Five co-methylation modules were considered preserved in three datasets. A total of 192 genes in these 5 modules were overlapped with 985 DMRs, from which a signature panel of 11 methylated messenger RNAs and 3 methylated long non-coding RNAs was identified. This signature panel could independently predict the 5-year RFS of PCa patients, with an area under the receiver operating characteristic curve (AUC) of 0.969 for the training TCGA dataset and 0.811 for the testing E-MTAB-6131 dataset, both of which were higher than the predictive accuracy of Gleason score (AUC = 0.689). Also, the patients with the same Gleason score (6-7 or 8-10) could be further divided into the high-risk group and the low-risk group. CONCLUSION: These results suggest that our prognostic model may be a promising biomarker for clinical prediction of RFS in PCa patients.

Neural network based 3D tracking with a graphene transparent focal stack imaging system.

Recent years have seen the rapid growth of new approaches to optical imaging, with an emphasis on extracting three-dimensional (3D) information from what is normally a two-dimensional (2D) image capture. Perhaps most importantly, the rise of computational imaging enables both new physical layouts of optical components and new algorithms to be implemented. This paper concerns the convergence of two advances: the development of a transparent focal stack imaging system using graphene photodetector arrays, and the rapid expansion of the capabilities of machine learning including the development of powerful neural networks. This paper demonstrates 3D tracking of point-like objects with multilayer feedforward neural networks and the extension to tracking positions of multi-point objects. Computer simulations further demonstrate how this optical system can track extended objects in 3D, highlighting the promise of combining nanophotonic devices, new optical system designs, and machine learning for new frontiers in 3D imaging.

Single-cell transcriptomics provides new insights into the role of fibroblasts during peritoneal fibrosis.

BACKGROUND: The contributions of various types of cell populations in dialysis-related peritoneal fibrosis are poorly understood. Single-cell RNA sequencing brings single-cell level resolution to the analysis of cellular transcriptomics, which provides a new way to further characterize the distinct roles and functional states of each cell population during peritoneal fibrosis. METHODS: Single-cell transcriptomics from normal peritoneal tissues of six patients, from effluent of patients with short-term peritoneal dialysis (less than 2 weeks, n = 6), and from long-term peritoneal dialysis patients (more than 6 years, n = 4) were analyzed. RESULTS: We identified a distinct cell component between samples among different groups. Functional analysis of the differentially expressed genes identified cell type specific biological processes relevant to different fibrosis stages. Well-known key molecular mechanisms participating in the pathophysiology of peritoneal fibrosis were vitrified, and some of them were found to be restricted to specific cell types. Gradually growing enrichment of PI3K/AKT/mTOR pathway and impairment of oxidative phosphorylation in mesothelial cells and fibroblasts were found from healthy control, short-term dialysis, to long-term dialysis, respectively. The fibroblasts' population obtained from the patients, who received peritoneal dialysis, showed a functional characteristic of immune-chemotaxis and immune response, which was characterized by broadly significant increase in the expression of interleukins, chemokines, cytokines, and human leukocyte antigens. Furthermore, we described the intercellular crosstalk networks based on receptor-ligand interactions, and highlighted a central role of fibroblasts in regulating the key mechanisms of peritoneal fibrosis through crosstalk with other cells. CONCLUSIONS: In summary, despite describing information for fibrogenic molecular mechanisms in the resolution level of individual cell populations, this work identifies the significant functional evolution of fibroblasts during peritoneal fibrosis. This study also reveals the intercellular receptor-ligand interactions in which the fibroblasts serve as a major node, eventually providing new insights into the role of fibroblasts during disease pathogenesis.

Fabrication and Mechanical Properties of Cr2AlC MAX Phase Coatings on TiBw/Ti6Al4V Composite Prepared by HiPIMS.

The high-power impulse magnetron sputtering (HiPIMS) technique is widely used owing to the high degree of ionization and the ability to synthesize high-quality coatings with a dense structure and smooth morphology. However, limited efforts have been made in the deposition of MAX phase coatings through HiPIMS compared with direct current magnetron sputtering (DCMS), and tailoring of the coatings' properties by process parameters such as pulse width and frequency is lacking. In this study, the Cr2AlC MAX phase coatings are deposited through HiPIMS on network structured TiBw/Ti6Al4V composite. A comparative study was made to investigate the effect of average power by varying frequency (1.2-1.6 kHz) and pulse width (20-60 µµs) on the deposition rate, microstructure, crystal orientation, and current waveforms of Cr2AlC MAX phase coatings. X-ray diffraction (XRD), scanning electron microscopy (SEM), and atomic force microscopy (AFM) were used to characterize the deposited coatings. The influence of pulse width was more profound than the frequency in increasing the average power of HiPIMS. The XRD results showed that ex situ annealing converted amorphous Cr-Al-C coatings into polycrystalline Cr2AlC MAX phase. It was noticed that the deposition rate, gas temperature, and roughness of Cr2AlC coatings depend on the average power, and the deposition rate increased from 16.5 to 56.3 nm/min. Moreover, the Cr2AlC MAX phase coatings produced by HiPIMS exhibits the improved hardness and modulus of 19.7 GPa and 286 GPa, with excellent fracture toughness and wear resistance because of dense and column-free morphology as the main characteristic.

Deep Learning Algorithms for the Prediction of Posttransplant Renal Function in Deceased-Donor Kidney Recipients: A Preliminary Study Based on Pretransplant Biopsy.

BACKGROUND: Posttransplant renal function is critically important for kidney transplant recipients. Accurate prediction of graft function would greatly help in deciding acceptance or discard of allocated kidneys. METHODS: : Whole-slide images (WSIs) of H&E-stained donor kidney biopsies at × 200 magnification between January 2015 and December 2019 were collected. The clinical characteristics of each donor and corresponding recipient were retrieved. Graft function was indexed with a stable estimated glomerular filtration rate (eGFR) and reduced graft function (RGF). We used convolutional neural network (CNN)-based models, such as EfficientNet-B5, Inception-V3, and VGG19 for the prediction of these two outcomes. RESULTS: In total, 219 recipients with H&E-stained slides of the donor kidneys were included for analysis [biopsies from standard criteria donor (SCD)/expanded criteria donor (ECD) was 191/28]. The results showed distinct improvements in the prediction performance of the deep learning algorithm plus the clinical characteristics model. The EfficientNet-B5 plus clinical data model showed the lowest mean absolute error (MAE) and root mean square error (RMSE). Compared with the clinical data model, the area under the receiver operating characteristic (ROC) curve (AUC) of the clinical data plus image model for eGFR classification increased from 0.69 to 0.83. In addition, the predictive performance for RGF increased from 0.66 to 0.80. Gradient-weighted class activation mappings (Grad-CAMs) showed that the models localized the areas of the tubules and interstitium near the glomeruli, which were discriminative features for RGF. CONCLUSION: Our results preliminarily show that deep learning for formalin-fixed paraffin-embedded H&E-stained WSIs improves graft function prediction accuracy for deceased-donor kidney transplant recipients.

Carbamylated erythropoietin regulates immune responses and promotes long-term kidney allograft survival through activation of PI3K/AKT signaling.

Modulation of alloimmune responses is critical to improving transplant outcome and promoting long-term graft survival. To determine mechanisms by which a nonhematopoietic erythropoietin (EPO) derivative, carbamylated EPO (CEPO), regulates innate and adaptive immune cells and affects renal allograft survival, we utilized a rat model of fully MHC-mismatched kidney transplantation. CEPO administration markedly extended the survival time of kidney allografts compared with the transplant alone control group. This therapeutic effect was inhibited when the recipients were given LY294002, a selective inhibitor of the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway or anti-EPO receptor (EPOR) antibody, in addition to CEPO. In vitro, CEPO inhibited the differentiation and function of dendritic cells and modulated their production of pro-inflammatory and anti-inflammatory cytokines, along with activating the PI3K/AKT signaling pathway and increasing EPOR mRNA and protein expression by these innate immune cells. Moreover, after CD4+ T cells were exposed to CEPO the Th1/Th2 ratio decreased and the regulatory T cell (Treg)/Th17 ratio increased. These effects were abolished by LY294002 or anti-EPOR antibody, suggesting that CEPO regulates immune responses and promotes kidney allograft survival by activating the PI3K/AKT signaling pathway in an EPOR-dependent manner. The immunomodulatory and specific signaling pathway effects of CEPO identified in this study suggest a potential therapeutic approach to promoting kidney transplant survival.