Season, household registry and isolated birth defects: a population-based case-control study in Danyang, China.

BACKGROUND: A birth population-based study was conducted in Danyang, Jiangsu Province, to evaluate major birth defects in emerging regions in China with similar maternal and neonatal care conditions. METHODS: We conducted a population-based study in a cohort of infants born in Danyang from 2014 to 2021, including 55 709 perinatal infants. Four categories of isolated birth defects were defined as cases: congenital heart defects (CHDs; n=2138), polydactyly (n=145), cleft lip with or without palate (CL/P; n=76) and accessory auricles (n=93). Infants with congenital malformations were identified by the Chinese Birth Defects Monitoring Network. RESULTS: Compared with autumn, conception in spring (OR=1.31 [1.16-1.48]) and winter (OR=1.39 [1.23-1.58]) was associated with an increased risk of CHD. Increased risk of CHD, CL/P and accessory auricles was significantly associated with non-local registered residence (OR=1.17 [1.07-1.28], OR=2.73 [1.52-4.88] and OR=2.11 [1.20-3.71], respectively). Individuals of Han nationality were less likely to have polydactyly (OR=0.23 [0.05-0.98]). CONCLUSIONS: The season of pregnancy was significantly associated with CHDs. Offspring of mothers with non-local registered hometown had greater risks of CHDs, CL/P and accessory auricles.

Roles of ferroptosis in type 1 diabetes induced spermatogenic dysfunction.

Diabetes mellitus (DM) is a widespread metabolic disease presenting with various complications, including spermatogenic dysfunction. However, the underlying mechanisms are still unclear. Ferroptosis, a novel type of programmed cell death, is associated with much metabolic diseases. Here, we investigated the role of ferroptosis in spermatogenic dysfunction of streptozotocin (STZ)-induced type 1 diabetic mice (diabetic mice), high glucose (HG)-treated GC-2 cells (HG cells) as well as testicular tissues of diabetic patients. We found an accumulation of iron, elevated malondialdehyde level and reduced glutathione level in the testis tissues of diabetic mice and HG cells. Histological examination showed a decrease in spermatogenic cells and spermatids within the seminiferous tubules as well as mitochondrial shrinkage in the testis tissues of diabetic mice. Ferrostatin-1 (Fer-1), the inhibitor of ferroptosis, mitigated ferroptosis-associated iron overload, lipid peroxidation accumulation and spermatogenic dysfunction of diabetic mice. Furthermore, we observed a downregulation of GPX4, FTL and SLC7A11 in diabetic mice and HG cells. Fer-1 treatment and GPX4 overexpression counteracted the effects of HG on cell viability, reactive oxygen species, lipid peroxidation and glutathione via inhibition of ferroptosis. Moreover, we found an elevation of ferroptosis in testicular tissues of diabetic patients. Taken together, our results identify the crucial role of ferroptosis in diabetic spermatogenic dysfunction and ferroptosis may be a promising therapeutic target to improve spermatogenesis in diabetic patients.

A DFT study of sulforaphane adsorption on the group III nitrides (B12N12, Al12N12 and Ga12N12) nanocages.

In this paper, the adsorption behavior of group III nitrides (B12N12, Al12N12, and Ga12N12) nanocages to sulforaphane (SF) anticancer medicine were studied by density functional theory (DFT). The adsorption energy, solvation energy, desorption time and related quantum molecular descriptors were calculated in neutral and acidic solutions. When the drugs were adsorbed to nanocages, the structure of nanocages and drugs changed after adsorption, indicating that the process was effective adsorption. The adsorption energy and solvation energy of the complexes created after adsorption were negative values, which indicated that the structure of complexes formed by adsorption were stable. According to charge decomposition analysis (CDA) and natural bonding orbitals (NBO), drugs act as charge donors and nanocages act as charge acceptors, so that the charge flows from drugs to nanocages. Thermodynamic calculations demonstrate that drugs adsorption on nanocages is a spontaneous exothermic process. The calculation of quantum molecular descriptors confirmed that drugs adsorption on nanocages increased the chemical reactivity and solubility of drugs, which facilitated its transfer in biological fluids. Both interaction region index (IRI) and topological analysis of atom in molecule (AIM) revealed Van Der Waals interaction between drugs and nanocages. Protonation studies demonstrated that acidic circumstances could improve the polarity of complexes, increase the solvation effect, and boost drugs release in target cancer cells. The results of this work indicate that X12N12(X = B, Al, Ga) nanocages can be used as the delivery vehicle of SF drug.Communicated by Ramaswamy H. Sarma.

Field test of quantum key distribution over aerial fiber based on simple and stable modulation.

We have developed a simple time-bin phase encoding quantum key distribution system, using the optical injection locking technique. This setup incorporates both the merits of simplicity and stability in encoding, and immunity to channel disturbance. We have demonstrated the field implementation of quantum key distribution over long-distance deployed aerial fiber automatically. During the 70-day field test, we achieved approximately a 1.0 kbps secure key rate with stable performance. Our work takes an important step toward widespread implementation of QKD systems in diverse and complex real-life scenarios.

Time-bin phase-encoding quantum key distribution using Sagnac-based optics and compatible electronics.

In this work, we present a new time-bin phase-encoding quantum key distribution (QKD), where the transmitter utilizes an inherently stable Sagnac-type interferometer, and has comparable electrical requirements to existing polarization or phase encoding schemes. This approach does not require intensity calibration and is insensitive to environmental disturbances, making it both flexible and high-performing. We conducted experiments with a compact QKD system to demonstrate the stability and secure key rate performance of the presented scheme. The results show a typical secure key rate of 6.2 kbps@20 dB and 0.4 kbps@30 dB with channel loss emulated by variable optical attenuators. A continuous test of 120-km fiber spool shows a stable quantum bit error rate of the time-bin basis within 0.4%∼0.6% over a consecutive 9-day period without any adjustment. This intrinsically stable and compatible scheme of time-bin phase encoding is extensively applicable in various QKD experiments, including BB84 and measurement-device-independent QKD.

Identification of pyroptosis-related subtypes and comprehensive analysis of characteristics of the tumor microenvironment infiltration in clear cell renal cell carcinoma.

Pyroptosis is a kind of programmed cell death triggered by the inflammasome. Growing evidence has revealed the crucial utility of pyroptosis in tumors. However, the potential mechanism of pyroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, we systematically analyze the genetic and transcriptional alterations of pyroptosis-related genes (PRGs) in ccRCC, identify pyroptosis-related subtypes, analyze the clinical and microenvironmental differences among different subtypes, develop a corresponding prognostic model to predict the prognosis of patients, and interpret the effect of pyroptosis on ccRCC microenvironment. This study provides a new perspective for a comprehensive understanding of the role of pyroptosis in ccRCC and its impact on the immune microenvironment, and a reliable scoring system was established to predict patients' prognosis.

Construction and validation of programmed cell death-based molecular clusters for prognostic and therapeutic significance of clear cell renal cell carcinoma.

As the dominant histological subtype of kidney cancer, clear cell renal cell carcinoma (ccRCC) poorly responds to conventional chemotherapy and radiotherapy. Although novel immunotherapies such as immune checkpoint inhibitors could have a durable effect in treating ccRCC patients, the limited availability of dependable biomarkers has restricted their application in clinic. In the study of carcinogenesis and cancer therapies, there has been a recent emphasis on researching programmed cell death (PCD). In the current study, we discovered the enriched and prognostic PCD in ccRCC utilizing gene set enrichment analysis (GSEA) and investigate the functional status of ccRCC patients with different PCD risks. Then, genes related to PCD that had prognostic value in ccRCC were identified for the conduction of non-negative matrix factorization to cluster ccRCC patients. Next, the tumor microenvironment, immunogenicity, and therapeutic response in different molecular clusters were analyzed. Among PCD, apoptosis and pyroptosis were enriched in ccRCC and correlated with prognosis. Patients with high PCD levels were related to poor prognosis and a rich but suppressive immune microenvironment. PCD-based molecular clusters were identified to differentiate the clinical status and prognosis of ccRCC. Moreover, the molecular cluster with high PCD levels may correlate with high immunogenicity and a favorable therapeutic response to ccRCC. Furthermore, a simplified PCD-based gene classifier was established to facilitate clinical application and used transcriptome sequencing data from clinical ccRCC samples to validate the applicability of the gene classifier. We thoroughly extended the understanding of PCD in ccRCC and constructed a PCD-based gene classifier for differentiation of the prognosis and therapeutic efficacy in ccRCC.

Identification of a basement membrane-based risk scoring system for prognosis prediction and individualized therapy in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) belongs to one of the 10 most frequently diagnosed cancers worldwide and has a poor prognosis at the advanced stage. Although multiple therapeutic agents have been proven to be curative in ccRCC, their clinical application was limited due to the lack of reliable biomarkers. Considering the important role of basement membrane (BM) in tumor metastasis and TME regulation, we investigated the expression of BM-related genes in ccRCC and identified prognostic BM genes through differentially expression analysis and univariate cox regression analysis. Then, BM-related ccRCC subtypes were recognized through consensus non-negative matrix factorization based on the prognostic BM genes and evaluated with regard to clinical and TME features. Next, utilizing the differentially expressed genes between the BM-related subtypes, a risk scoring system BMRS was established after serial analysis of univariate cox regression analysis, lasso regression analysis, and multivariate cox regression analysis. Time-dependent ROC curve revealed the satisfactory prognosis predictive capacity of BMRS with internal, and external validation. Multivariate analysis proved the independent predictive ability of BMRS and a BMRS-based nomogram was constructed for clinical application. Some featured mutants were discovered through genomic analysis of the BMRS risk groups. Meanwhile, the BMRS groups were found to have distinct immune scores, immune cell infiltration levels, and immune-related functions. Moreover, with the help of data from The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC), the potential of BMRS in predicting therapeutic response was evaluated and some possible therapeutic compounds were proposed through ConnectivityMap (CMap). For the practicability of BMRS, we validated the expression of BMRS-related genes in clinical samples. After all, we identified BM-related ccRCC subtypes with distinct clinical and TME features and constructed a risk scoring system for the prediction of prognosis, therapeutic responses, and potential therapeutic agents of ccRCC. As ccRCC systemic therapy continues to evolve, the risk scoring system BMRS we reported may assist in individualized medication administration.

Downregulation of FXYD2 Is Associated with Poor Prognosis and Increased Regulatory T Cell Infiltration in Clear Cell Renal Cell Carcinoma.

Background: FXYD2, a gene coding for the γ subunit of Na+/K+-ATPase, was demonstrated to involve in carcinogenesis recently. However, the specific role of FXYD2 in clear cell renal cell carcinoma (ccRCC) remains unknown. The current study was conducted to investigate the expression, biological function, and potentially immune-related mechanisms of FXYD2 in ccRCC. Materials and methods. The data from TCGA-KIRC, ICGC, GEO, Oncomine, ArrayExpress, TIMER, HPA datasets, and our clinical samples were used to determine and validate the expression level, prognostic roles, and potentially immune-related mechanisms in ccRCC. Cell function assays were performed to investigate the biological role of FXYD2 in vitro. Results: FXYD2 was identified to be downregulated in ccRCC tissue compared to normal tissue, which was confirmed by our RT-PCR, WB, and IHC analyses. Kaplan-Meier survival analysis and Cox regression analysis suggested that downregulated FXYD2 could independently predict poor survival of ccRCC patients. Through the ESTIMATE algorithm, ssGSEA algorithm, CIBERSORT algorithm, TIMER database, and our laboratory experiment, FXYD2 was found to correlate with the immune landscape, especially regulatory T cells (Treg), in ccRCC. Gain-of-function experiment revealed that FXYD2 could restrain cell proliferation, migration, and invasion in vitro. Functional enrichment analysis illustrated that TGF-ß-SMAD2/3, Notch, and PI3K-Akt-mTOR signaling pathways may be potential signaling pathways of FXYD2 in ccRCC. Conclusions: Downregulation of FXYD2 is associated with ccRCC tumorigenesis, poor prognosis, and increased Treg infiltration in ccRCC, which may be related to TGF-ß-SMAD2/3, Notch, and PI3K-Akt-mTOR signaling pathways. This will probably provide a novel prognostic marker and potential therapeutic target for ccRCC.

Quantitative Analysis of Contrast-Enhanced Ultrasound That Can Be Used to Evaluate Angiogenesis during Patellar Tendon Healing in Rats.

Objective: To investigate the efficacy of contrast-enhanced ultrasound (CEUS) in quantitatively evaluating angiogenesis during patellar tendon healing in rats. Methods: A total of 40 Sprague-Dawley rats were used in this study. The patellar tendons of 30 rats (60 limbs) that underwent incision and suture were treated as the operation group and monitored after 7, 14, and 28 days. The normal patellar tendons of 10 rats (20 limbs) were treated as the control group and monitored on day 0. The ultrasound examination was used to evaluate the structure and blood perfusion of the patellar tendon. Immunohistochemistry was used to assess angiogenesis, and the biomechanical test was used to verify functional recovery of the patellar tendon. Results: The tendons in the operation group were significantly thickened compared with those in the control group (p < 0.01). The peak intensity (PI) in CEUS of the tendons showed a clear difference at each time point after the surgery (p < 0.01). PI increased in the operation group with a maximum on day 7, and then gradually decreased until day 28 when PI was close to the basic intensity (BI) in the control group (p > 0.05). It was consistent with the change of the CD31-positive staining areas representing angiogenesis of the injured patellar tendons. The PI was positively correlated with the CD31-positive staining area fraction (R = 0.849, p < 0.001). The failure load and tensile strength of the repaired patellar tendons in the operation group increased over time. The PI showed negative correlations with the failure load (R = -0.787, p < 0.001) and tensile strength (R = -0.714, p < 0.001). Conclusion: The PI in CEUS could quantitatively reflect the time-dependent change in the blood supply of the healing site, and the PI correlated with histologic and biomechanical properties of the healing tendon. Quantitative analysis of contrast-enhanced ultrasound could be a useful method to evaluate angiogenesis in healing tendons.

Effect of hydrostatic pressure on the structural, elastic, and optoelectronic properties of vacancy-ordered double perovskite Cs2PdBr6.

The vacancy-ordered double perovskite Cs2PdBr6 has the advantages of good optoelectronic properties, environmental friendliness, and high stability. It has been experimentally confirmed by researchers as an optoelectronic material with broad application prospects and research value, and is regarded as a potential substitute for lead halide perovskites. In this paper, based on the first-principles calculations in the framework of density functional theory, the crystal structure, elastic, electronic, and optical properties of Cs2PdBr6 under hydrostatic pressure of 0-6 GPa have been investigated with a step size of 0.5 GPa. The calculated results obtained under the condition of 0 GPa hydrostatic pressure are in good agreement with the existing experimental values. When the hydrostatic pressure is applied, the crystal structure parameters of Cs2PdBr6 appear nonlinear changes, but it can still maintain a stable cubic crystal structure. With the increase of pressure, the bulk modulus, shear modulus, and Young's modulus of Cs2PdBr6 increase gradually, and its ductility also improves gradually. Hydrostatic pressure can reduce the bandgap value of Cs2PdBr6, thereby enhancing the optoelectronic properties such as absorption and conductivity. In summary, hydrostatic pressure can change the bandgap value of Cs2PdBr6, improve its optoelectronic performance, and make it more suitable for use as the light-absorbing layer in solar cells.

High-throughput screening of stable and efficient double inorganic halide perovskite materials by DFT.

Perovskite solar cells have become the most promising third-generation solar cells because of their superior physical-chemical properties and high photoelectric conversion efficiency. However, the current obstacles to commercialization of perovskite solar cells are their poor stability and harmful elements. How to find high-efficiency, high-stability and non-toxic perovskite materials from thousands of possible perovskite crystals is the key to solve this problem. In this paper, the inorganic halide double perovskite A2BX6 and its crystal structure are considered, and the data mining algorithm in informatics is introduced into the high-throughput computing data to analyze various elements in nature to study the perovskite materials that can meet the requirements of high performance. The photoelectric conversion properties and stability of 42 inorganic double perovskite materials are studied based on density functional theory (DFT). The results show that the tolerance factors of 39 crystals are between 0.8 and 1.10, indicating that these crystals have stable perovskite structure. In addition, the dielectric function, PDOS, elastic modulus, shear modulus and poison's ratio of these crystals are analyzed. According to the above theoretical simulation results, three candidate materials for ideal light absorption are presented. This can provide a theoretical basis for the industrial application of perovskite solar cells.

Integrative Analysis of the Genomic and Immune Microenvironment Characteristics Associated With Clear Cell Renal Cell Carcinoma Progression: Implications for Prognosis and Immunotherapy.

Unlike early clear cell renal cell carcinoma (ccRCC), locally advanced and metastatic ccRCC present poor treatment outcomes and prognosis. As immune checkpoint inhibitors have achieved favorable results in the adjuvant treatment of metastatic ccRCC, we aimed to investigate the immunogenomic landscape during ccRCC progression and its potential impact on immunotherapy and prognosis. Using multi-omics and immunotherapy ccRCC datasets, an integrated analysis was performed to identify genomic alterations, immune microenvironment features, and related biological processes during ccRCC progression and evaluate their relevance to immunotherapy response and prognosis. We found that aggressive and metastatic ccRCC had higher proportions of genomic alterations, including SETD2 mutations, Del(14q), Del(9p), and higher immunosuppressive cellular and molecular infiltration levels. Of these, the Del(14q) might mediate immune escape in ccRCC via the VEGFA-VEGFR2 signaling pathway. Furthermore, immune-related pathways associated with ccRCC progression did not affect the immunotherapeutic response to ccRCC. Conversely, cell cycle pathways not only affected ccRCC progression and prognosis, but also were related to ccRCC immunotherapeutic response resistance. Overall, we described the immunogenomic characteristics of ccRCC progression and their correlations with immunotherapeutic response and prognosis, providing new insights into their prediction and the development of novel therapeutic strategies.

Theoretical exploration of mechanical, electronic structure and optical properties of aluminium based double halide perovskite.

The mechanical, electronic structure and optical properties of aluminium based double halide perovskite were calculated by density functional theory. The formation energy and elastic constant confirm the stability of the cubic perovskite materials. The materials are all ductile and suitable for flexible photovoltaic and optoelectronic devices. The band gap values vary from 0.773 eV to 3.430 eV, exactly corresponding to the range of ideal band gap values for good photoresponse. The band structure analysis shows that all the materials possess small effective mass, which indicates a good transport of carriers. And these materials have a broad energy range of optical absorption for utilization and a detector of photons. Moreover, less expensive K2AgAlBr6 were investigated for comparison with materials containing a cesium element, and according to the results, is also a candidate for photoelectronic devices due to the similar properties.

Bayesian analysis under accelerated failure time models with error-prone time-to-event outcomes.

We consider accelerated failure time models with error-prone time-to-event outcomes. The proposed models extend the conventional accelerated failure time model by allowing time-to-event responses to be subject to measurement errors. We describe two measurement error models, a logarithm transformation regression measurement error model and an additive error model with a positive increment, to delineate possible scenarios of measurement error in time-to-event outcomes. We develop Bayesian approaches to conduct statistical inference. Efficient Markov chain Monte Carlo algorithms are developed to facilitate the posterior inference. Extensive simulation studies are conducted to assess the performance of the proposed method, and an application to a study of Alzheimer's disease is presented.

Censored quantile regression based on multiply robust propensity scores.

Censored quantile regression has elicited extensive research interest in recent years. One class of methods is based on an informative subset of a sample, selected via the propensity score. Propensity score can either be estimated using parametric methods, which poses the risk of misspecification or obtained using nonparametric approaches, which suffer from "curse of dimensionality." In this study, we propose a new estimation method based on multiply robust propensity score for censored quantile regression. This method only requires one of the multiple candidate models for propensity score to be correctly specified, and thus, it provides a certain level of resistance to the misspecification of parametric models. Large sample properties, such as the consistency and asymptotic normality of the proposed estimator, are thoroughly investigated. Extensive simulation studies are conducted to assess the performance of the proposed estimator. The proposed method is also applied to a study on human immunodeficiency viruses.

A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction. METHODS: The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature. RESULTS: Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8+ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature. CONCLUSION: Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

Theoretical Study on the Carrier Mobility and Optical Properties of CsPbI3 by DFT.

The advantages of organic-inorganic hybrid halide perovskites and related materials, such as high absorption coefficient, appropriate band gap, excellent carrier mobility, and long carrier life, provide the possibility for the preparation of low-cost and high-efficiency solar cell materials. Among the inorganic materials, CsPbI3 is paid more attention to by researchers as CsPbI3 has incomparable advantages. In this paper, based on density functional theory (DFT), we first analyze the crystal structure, electronic properties, and work function of two common bulk structures of CsPbI3 and their slices, and then, we study the carrier mobility, exciton binding energy, and light absorption coefficient. Considering that CsPbI3 contains heavy elements, the spin-orbit coupling (SOC) effect was also considered in the calculation. The highest mobility is that electrons of the cubic structure reach 1399 cm2 V-1 S-1 after considering the SOC effect, which is equal to that of traditional solar cells (such as Si-based, PbSe, and PbTe). The lowest exciton binding energy is 101 meV in the cubic bulk structure, which is beneficial to the separation of photogenerated carriers. In the visible region, the absorption coefficient of the cubic structure is the best among all structures, reaching 105 cm-1. Through the study of mobility, exciton binding energy, and light absorption coefficient, it is found that the cubic bulk structure in all structures of CsPbI3 has the best photoelectric performance. This paper can provide some guidance for the experimental preparation of CsPbI3 as a potential high-efficiency solar cell material.

Bayesian quantile nonhomogeneous hidden Markov models.

Hidden Markov models are useful in simultaneously analyzing a longitudinal observation process and its dynamic transition. Existing hidden Markov models focus on mean regression for the longitudinal response. However, the tails of the response distribution are as important as the center in many substantive studies. We propose a quantile hidden Markov model to provide a systematic method to examine the entire conditional distribution of the response given the hidden state and potential covariates. Instead of considering homogeneous hidden Markov models, which assume that the probabilities of between-state transitions are independent of subject- and time-specific characteristics, we allow the transition probabilities to depend on exogenous covariates, thereby yielding nonhomogeneous Markov chains and making the proposed model more flexible than its homogeneous counterpart. We develop a Bayesian approach coupled with efficient Markov chain Monte Carlo methods for statistical inference. Simulations are conducted to assess the empirical performance of the proposed method. The proposed methodology is applied to a cocaine use study to provide new insights into the prevention of cocaine use.

Identifying 4 Novel lncRNAs as Potential Biomarkers for Acute Rejection and Graft Loss of Renal Allograft.

Acute rejection (AR) after kidney transplant is one of the major obstacles to obtain ideal graft survival. Reliable molecular biomarkers for AR and renal allograft loss are lacking. This study was performed to identify novel long noncoding RNAs (lncRNAs) for diagnosing AR and predicting the risk of graft loss. The several microarray datasets with AR and nonrejection specimens of renal allograft downloaded from Gene Expression Omnibus database were analyzed to screen differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). Univariate and multivariate Cox regression analyses were used to identify optimal prognosis-related DElncRNAs for constructing a risk score model. 39 common DElncRNAs and 185 common DEmRNAs were identified to construct a lncRNA-mRNA regulatory relationship network. DElncRNAs were revealed to regulate immune cell activation and proliferation. Then, 4 optimal DElncRNAs, ATP1A1-AS1, CTD-3080P12.3, EMX2OS, and LINC00645, were selected from 17 prognostic DElncRNAs to establish the 4-lncRNA risk score model. In the training set, the high-risk patients were more inclined to graft loss than the low-risk patients. Time-dependent receiver operating characteristics analysis revealed the model had good sensitivity and specificity in prediction of 1-, 2-, and 3-year graft survival after biopsy (AUC = 0.891, 0.836, and 0.733, respectively). The internal testing set verified the result well. Gene set enrichment analysis which expounded NOD-like receptor, the Toll-like receptor signaling pathways, and other else playing important role in immune response was enriched by the 4 lncRNAs. Allograft-infiltrating immune cells analysis elucidated the expression of 4 lncRNAs correlated with gamma delta T cells and eosinophils, etc. Our study identified 4 novel lncRNAs as potential biomarkers for AR of renal allograft and constructed a lncRNA-based model for predicting the risk of graft loss, which would provide new insights into mechanisms of AR.