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Semi-hydrogenation of alkynes to prepare alkenes is an important reaction in the petrochemical and fine chemical industries. The use of conventional Pd nanoparticle-based catalysts is limited by alkyne over-hydrogenation and low Pd utilization. In this study, a nitrogen-doped mesoporous carbon material (m-NC), which was rich in defect sites after Zn volatilization, was fabricated by the carbonization of ZIF-8. Ultrafine PdCo bimetallic nanoclusters with Co atom-modified Pd active site electronic and compositional structure were highly dispersed and confined in m-NC. As-obtained Pd0.43Co1/m-NC was used for the semi-hydrogenation of alkynes and it exhibited high selectivity with high conversion under mild reaction conditions. Pd0.43Co1/m-NC also exhibited excellent stability in leaching tests and maintained its catalytic activity for at least nine reaction cycles. The highly dispersed active sites in Pd0.43Co1/m-NC served as the active sites for the catalytic semi-hydrogenation of alkynes; as a regulator, the second metal Co effectively improved selectivity, and m-NC endowed the catalyst with excellent stability. The research work presented here may provide a foundation for the design of highly active, selective, and stable Pd-based bimetallic catalysts for selective hydrogenation. [ABSTRACT FROM AUTHOR]

As one of the critical technologies for performance evaluation of automated vehicles, the test scenario generation has been widespread concerned. In this paper, we propose a novel test scenario generation technology based on optimized Latin Hypercube Sampling (OLHS) and Test Matrix method (TM), named HIS-MPSO, which is efficient to generate the test scenario that consider the complexity, coverage, and potential relationships of factors. Based on naturalistic driving data, numerous car-following scenarios are generated by HIS-MPSO. Then, an adaptive cruise control system (ACC) are evaluated in terms of the tracking errors, comfort, and safety using the generated scenarios. Results show that compared with other existing OLHS algorithms, the HIS-MPSO can better restore the relationships among test factors existed in realistic traffic scenarios. [ABSTRACT FROM AUTHOR]

Simple Summary: Guanine nucleotide-binding protein-like 3-like (GNL3L) is a novel GTP-binding nucleolar protein. In this study, we analyzed the expression, prognosis, and immune roles of GNL3L in pan-cancer from multiple omics analyses. The final results showed that GNL3L is differentially expressed in a variety of cancers, plays a prognostic role, and has good immune value. Moreover, GNL3L may affect the occurrence of cancer through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, we established an esophageal cancer (ESCA) prediction model with strong predictive ability and proved that GNL3L can significantly affect the proliferation ability of esophageal cancer cells through clone formation assays. In conclusion, GNL3L is an important biomarker. Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a novel, evolutionarily conserved, GTP-binding nucleolar protein. This study aimed to investigate the expression, prognosis, and immune value of GNL3L in pan-cancer from multiple omics analyses. Firstly, the expression and prognostic value of GNL3L in pan-cancer were discussed using the TIMER2 database, the GEPIA database, the cBioportal database, COX regression analysis, and enrichment analysis. The association of GNL3L with tumor mutational burden (TMB), tumor microsatellite instability (MSI), mismatch repair (MMR) genes, and immune cells was then analyzed. Finally, an esophageal cancer (ESCA) prediction model was established, and GNL3L clone formation assays were performed. The final results showed that GNL3L is differentially expressed in the vast majority of cancers, is associated with the prognosis of various cancers, and may affect cancer occurrence through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, it was found that the correlation between GNL3L and TMB, MSI, MMR, and various immune cells is significant. The established ESCA prediction model had a strong predictive ability, and GNL3L could significantly affect the proliferation of esophageal cancer cells. In conclusion, GNL3L may serve as an important prognostic biomarker and play an immunomodulatory role in tumors. [ABSTRACT FROM AUTHOR]

In this study, a three‐dimensional (3D) finite‐difference time‐domain (FDTD) approach utilizing time‐domain weighted Laguerre polynomials (WLPs) and space‐domain isotropic–dispersion (ID) finite‐difference scheme is presented (i.e., 3D ID‐WLP‐FDTD). The method exhibits unconditional stability and comprehensively improved performance such as lower anisotropic numerical dispersion error. To demonstrate its advantage, it is applied in an example of the propagation of a plane wave in a 3D cavity. The results calculated by the proposed ID‐WLP‐FDTD method and the conventional 3D WLP‐FDTD are compared, which shows that the proposed method can achieve reduced anisotropic numerical dispersion error while consuming less calculation time and hardware resources. [ABSTRACT FROM AUTHOR]

Data usually resides on a manifold, and the minimal dimension of such a manifold is called its intrinsic dimension. This fundamental data property is not considered in the generative adversarial network (GAN) model along with its its variants; such that original data and generated data often hold different intrinsic dimensions. The different intrinsic dimensions of both generated and original data may cause generated data distribution to not match original data distribution completely, and it certainly will hurt the quality of generated data. In this study, we first show that GAN is often unable to generate simulation data, holding the same intrinsic dimension as the original data with both theoretical analysis and experimental illustration. Next, we propose a new model, called Hausdorff GAN, which removes the issue of different intrinsic dimensions and introduces the Hausdorff metric into GAN training to generate higher quality data. This provides new insights into the success of Hausdorff GAN. Specifically, we utilize a mapping function to map both original and generated data into the same manifold. We then calculate the Hausdorff distance to measure the difference between the mapped original data and the mapped generated data, toward pushing generated data to the side of original data. Finally, we conduct extensive experiments (using MNIST, CIFAR10, and CelebA datasets) to demonstrate the significant performance improvement of the Hausdorff GAN in achieving the largest Inception Score and the smallest Frechet inception distance (FID) score as well as producing diverse generated data at different resolutions. [ABSTRACT FROM AUTHOR]

The liver toxicity of alkylphenols (APs) has been demonstrated in animal studies. However, relevant epidemiological evidence is still lacking in humans, especially during pregnancy. We obtained the levels of biochemical indicators of liver function in early (<13 weeks, mean gestation=9.80±1.96 weeks) and late (≥32 weeks, mean gestation = 37.23±2.45 weeks) pregnancies from 219 pregnant women in the Guangxi Zhuang birth cohort from 2015–2017. We also examined the serum levels of APs in these pregnant women in early pregnancy. The present study aimed to investigate the correlations between the exposure of pregnant women to APs and their serum liver function indices. The results of the generalized linear model (GLM) in this study revealed that nonylphenol (NP) was positively correlated with total bilirubin (TBIL) (P=0.04) in early pregnancy, and 4-n-nonylphenol (4-N-NP) was negatively correlated with glutamyl transferase (GGT) (P=0.012). In late pregnancy, NP was positively associated with TBIL (P=0.002), and 4-tert-octylphenol (4-T-OP) was positively correlated with alanine aminotransferase (ALT) (P=0.02). Restricted cubic spline (RCS) results revealed dose response relationships between NP and TBIL (Poverall=0.011) and between 4-N-NP and GGT (Poverall=0.007) in early pregnancy. In late pregnancy, there were dose response relationships between NP and TBIL (Poverall=0.001) and between 4-T-OP and ALT (Poverall=0.033). There was also a dose response relationship between NP volume and GGT with an inverted 'U' shape (Poverall=0.041, Pnonlinear=0.012). Bayesian kernel machine regression modeling (BKMR) revealed that TBIL increased significantly (P<0.05) with increasing levels of coexposure to APs in both early and late pregnancy. Overall, exposure to APs during pregnancy affects maternal liver function to varying degrees. The present study provides new epidemiological evidence that exposure to alkylphenols in pregnant women interferes with liver function. • The first study to link APs exposure during pregnancy to maternal liver function. • Different APs affect liver function variably during early and late pregnancy. • BKMR analysis shows significant TBIL increase with APs coexposure in pregnancy. [ABSTRACT FROM AUTHOR]

• Unveiled Tan sheep MB purification and confirmed identity via LC-MS/MS analysis. • NO-induced transformation in MbFeⅢ observed by UV–visible and Raman spectroscopy. • AlphaFold2 and docking simulations reveal stable MbFeⅡNO structure. • DFT highlights chemical stability and role of distal histidine in MbFeⅡNO. • Theoretical and experimental synergy elucidates pigment protein dynamics. Color of meat remains crucial quality attribute that attracts attention of researchers worldwide. Various strategies have been employed to manipulate meat color by generating nitric oxide (NO), which interacts with myoglobin (Mb) to yield the pinkish-red pigment, nitrosomyoglobin (MbFeⅡNO). However, the formation mechanism of MbFeⅡNO warrants further exploration at the molecular-structural level for meat pigmentation. Here, Tan sheep Mb was purified and characterized its primary structure via LC-MS/MS, which found it to be identical to sheep Mb. Circular dichroism spectroscopy revealed 70.05 % α-helix content in the secondary structure of Tan sheep Mb. UV-visible and resonance Raman spectroscopy monitored NO bonding in Tan sheep Mb, revealing that NO displaced H 2 O of MbFeⅢ, forming MbFeⅢNO, which subsequently transformed into low-spin six-coordination MbFeⅡNO. Additionally, three-dimensional structure of Tan sheep Mb was constructed utilizing Alphafold2, and theoretical simulations and calculations were performed through molecular docking and DFT. Results confirmed the synergistic effect of the strong metal-ligand and hydrogen bonding interactions among the NO, heme iron, and distal sites significantly contributed to the stable formation of MbFeⅡNO. Overall, this study offers a novel perspective on the mechanism of NO binding in Mb, potentially guiding the development of innovative strategies to mitigate meat color deterioration. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • A two-step hydrothermal and calcination route was used to prepare NiGa 2 O 4 @C@CeO 2. • The NiGa 2 O 4 @C@CeO 2 sensor exhibits excellent triethylamine gas sensitive property. • The NiGa 2 O 4 @C@CeO 2 sensor also shows terrific selectivity and reusability for TEA. • The superior TEA gas sensing mechanism of the heterostructure was also investigated. Metal oxide heterostructures have been demonstrated excellent candidates acting as novel gas sensors with outstanding sensitivity and selectivity. In this work, a hierarchical NiGa 2 O 4 @C@CeO 2 heterostructure with corn-like NiGa 2 O 4 microcrystals covered by a thin carbon layer and then anchored with numerous amounts of external CeO 2 nanoparticles was prepared through the combination of hydrothermal and a subsequent calcination method. The NiGa 2 O 4 @C@CeO 2 composite demonstrates an excellent selective triethylamine (TEA) detection performance with a response of 11.1 towards 20 ppm TEA and a fast response/recovery time of 81 s/38 s. It also shows terrific selectivity for TEA when mixed with else interfering substances, along with prolonged reusability for at least 15 days. The enhanced TEA sensing performance can be ascribed to the significant improvement of conductivity and effective carrier transfer at the interface. This work provides a feasible method to fabricate metal oxide sensors with improved gas sensing performance. [ABSTRACT FROM AUTHOR]

Author(s): Wenting Fan[sup.1] , Huimin Qian[sup.2] , Wenkang Shang[sup.3] , Chen Ying[sup.1] , Xuedi Zhang[sup.4] , Song Cheng[sup.4] , Bing Gu[sup.1,5,6] and Ping Ma[sup.1,5,6] Background Shigellosis is major health burden [...]

This paper researches the identification problem for the unknown parameters of the multivariate equation-error autoregressive systems. Firstly, the original identification model is decomposed into several sub-identification models according to the number of system outputs. Then, based on the characteristic that the information vector and the parameter vector are common among the sub-identification models, the coupling identification concept is used to propose a partially coupled generalized stochastic gradient algorithm. Furthermore, by expanding the scalar innovation of each subsystem model to the innovation vector, a partially coupled multi-innovation generalized stochastic gradient algorithm is proposed. Finally, the numerical simulations indicate that the proposed algorithms are effective and have good parameter estimation performances. [ABSTRACT FROM AUTHOR]

Global food production faces immense pressure, much of which can be attributed to climate change. A detailed evaluation of the impact of climate change on the yield of staple crops in Kazakhstan, a major food exporter, is required for more scientific planting management. In this study, the Mann–Kendall test and Theil–Sen Median slope were used to determine climate trends and staple food yields over the past 30 years; random forest was used to analyze the importance of monthly climatic factors; states were classified according to climatic factors through systematic clustering method; and lastly, the influence of climate on yield was analyzed using panel regression models. The upward trend in wind speed and potato yield throughout Kazakhstan was apparent. Furthermore, barley and wheat yields had increased in the southeast. We determined that for wheat, frostbite should be prevented after the warmer winters in the high-latitude areas. Except for July–August in the low-latitude areas, irrigation water should be provided in the other growth periods and regions. As similar effects were reported for barley, the same preventive measures would apply. For potatoes, tuber rot, caused by frost or excessive precipitation in May, should be prevented in high-latitude areas; soil dryness should be alleviated during the germination and seedling stages in low-latitude areas; and irrigation and cooling should be maintained during tuber formation and maturation. Furthermore, hot dry air in March and April could damage the crops. [ABSTRACT FROM AUTHOR]

Objective. We aimed to analyze the correlation between the level of skin advanced glycation end products (AGEs) in type 2 diabetes mellitus (T2DM) patients and the diabetic retinopathy (DR) staging in different traditional Chinese medicine (TCM) syndromes. Methods. 416 T2DM patients were divided into normal group, nonproliferative diabetic retinopathy (NPDR) group (mild, moderate, and severe), and proliferative diabetic retinopathy (PDR) group according to the DR grade. Patients' height, weight, fasting blood glucose (FBG), hemoglobin A1C (HbA1c), blood lipid, renal function, and skin AGEs were measured. According to TCM syndrome differentiation criteria, 230 patients with T2DM and DR were divided into I. qi and yin deficiency, collateral stasis group; II. liver and kidney deficiency, eye collaterals loss group; and III. yin and yang deficiency, blood stasis, and phlegm coagulation group. Results. The skin AGEs levels of different DR staging groups were statistically significant (P < 0.05), and the skin AGEs levels in the mild and moderate NPDR groups were significantly higher (P < 0.05) than those of the normal group. It was significantly higher (P < 0.05) in the severe NPDR group than in the normal group, mild and moderate NPDR groups. The skin AGEs levels of the PDR group were significantly higher (P < 0.05) than the normal group, mild and moderate NPDR groups. It was positively correlated with DR stage, HbA1c, total cholesterol (TC), low-density lipoprotein (LDL), and urine metal analysis (UMA) (r = 0.467, 0.411, 0.413, 0.503, 0.424, P < 0.05). The skin AGEs levels of the qi and yin deficiency and collaterals stasis syndrome group were significantly higher (P < 0.05) than in the liver and kidney deficiency and eye collaterals loss groups. It was also significantly higher (P < 0.05) in yin and yang deficiency, blood stasis, and phlegm coagulation syndrome groups than in qi and yin deficiency and collaterals stasis syndrome groups. Conclusion. There is a positive correlation between skin AGEs and DR staging in T2DM patients. Skin AGEs level is predictive for the risk of DR complications in T2DM patients and is vital in assessing DR degree per TCM syndrome type. [ABSTRACT FROM AUTHOR]

This article focuses on the microstructure and mechanism analysis of the novel coating MgO– B2O3–SiO2–Zn prepared by plasma spraying and flame spraying on the SUS304 alloy substrate. Firstly, the crystal compositions of the powders were analyzed by XRD (X-ray diffraction). Secondly, the surface and cross section microstructures of the coating were observed by SEM (Scanning Electron Microscope) and EPMA (electron probe microanalysis) in order to study the mechanism of the thermal insulation performance. It is concluded that, the microstructure, different thickness and compositions have various effect on heat insulation. [ABSTRACT FROM AUTHOR]

Aims: To explore the function of phosphorylation of KAP1 (p-KAP1) at the serine-824 site (S824) in the proliferation and apoptosis of endogenous neural stem cells (NSCs) after cerebral ischemic/reperfusion (I/R). Methods: The apoptosis and proliferation of C17.2 cells transfected with the p-KAP1-expression plasmids and the expression of proliferation cell nuclear antigen (PCNA) and p-KAP1 were detected by immunofluorescence and Western blotting after the Oxygen Glucose deprivation/reperfusion model (OGD/R). The interaction of p-KAP1 and CUL4A with PCNA was analyzed by immunoprecipitation. In the rats MCAO model, we performed the adeno-associated virus (AAV) 2/9 gene delivery of p-KAP1 mutants to verify the proliferation of endogenous NSCs and the colocalization of PCNA and CUL4A by immunofluorescence. Results: The level of p-KAP1 was significantly down-regulated in the stroke model in vivo and in vitro. Simulated p-KAP1(S824) significantly increased the proliferation of C17.2 cells and the expression of PCNA after OGD/R. Simulated p-KAP1(S824) enhanced the binding of p-KAP1 and PCNA and decreased the interaction between PCNA and CUL4A in C17.2 cells subjected to OGD/R. The AAV2/9-mediated p-KAP1(S824) increased endogenous NSCs proliferation, PCNA expression, p-KAP1 binding to PCNA, and improved neurological function in the rat MCAO model. Conclusions: Our findings confirmed that simulated p-KAP1(S824) improved the survival and proliferation of endogenous NSCs. The underlying mechanism is that highly expressed p-KAP1(S824) promotes binding to PCNA, and inhibits the binding of CUL4A to PCNA. This reduced CUL4A-mediated ubiquitination degradation to increase the stability of PCNA and promote the survival and proliferation of NSCs. [ABSTRACT FROM AUTHOR]

Regression models with a functional response and functional covariate have received significant attention recently. While various nonparametric and semiparametric models have been developed, there is an urgent need for model selection and diagnostic methods. In this article, we develop a unified framework for estimation and model selection in nonparametric function-on-function regression. We propose a general nonparametric functional regression model with the model space constructed through smoothing spline analysis of variance (SS ANOVA). The proposed model reduces to some of the existing models when selected components in the SS ANOVA decomposition are eliminated. We propose new estimation procedures under either L1 or L2 penalty and show that the combination of the SS ANOVA decomposition and L1 penalty provides powerful tools for model selection and diagnostics. We establish consistency and convergence rates for estimates of the regression function and each component in its decomposition under both the L1 and L2 penalties. Simulation studies and real examples show that the proposed methods perform well. Technical details and additional simulation results are available in online . [ABSTRACT FROM AUTHOR]

Smoothing splines have been used pervasively in nonparametric regressions. However, the computational burden of smoothing splines is significant when the sample size n is large. When the number of predictors d ≥ 2 , the computational cost for smoothing splines is at the order of O (n 3) using the standard approach. Many methods have been developed to approximate smoothing spline estimators by using q basis functions instead of n ones, resulting in a computational cost of the order O (n q 2) . These methods are called the basis selection methods. Despite algorithmic benefits, most of the basis selection methods require the assumption that the sample is uniformly distributed on a hypercube. These methods may have deteriorating performance when such an assumption is not met. To overcome the obstacle, we develop an efficient algorithm that is adaptive to the unknown probability density function of the predictors. Theoretically, we show the proposed estimator has the same convergence rate as the full-basis estimator when q is roughly at the order of O [ n 2 d / { (p r + 1) (d + 2) } ] , where p ∈ [ 1 , 2 ] and r ≈ 4 are some constants depend on the type of the spline. Numerical studies on various synthetic datasets demonstrate the superior performance of the proposed estimator in comparison with mainstream competitors. Supplementary files for this article are available online. [ABSTRACT FROM AUTHOR]

To develop a framework, using Louisiana as a case study, for estimating the potential cost savings to individual states if families were able to meet current recommendations for breastfeeding. Using cost-analyses methods, cost savings, as well as, case and death reductions of infant illnesses and deaths on four selected infant diseases (respiratory tract infections, gastroenteritis, necrotizing enterocolitis, and Sudden Infant Death Syndrome) were calculated utilizing the most recent data of breastfeeding and low/very low birth weight rates in Louisiana. To estimate the incidence of a disease in exclusive breastfed infants and formula fed infants respectively, we used the following formula: x = s/br + 1 - b. Here 'x' is the incidence rate of one disease in formula fed infants, 's' is the overall incidence of the disease, 'b' is current breastfeeding rate and 'r' is the odds ratios in favor of breastfeeding. A total of $216,103,368 could be saved and 18 infant deaths prevented, by these four conditions alone, if 90% of newborns in Louisiana were exclusive breastfed for the first 6 months of life ($186,371,125 in savings and 16 infant deaths prevented with 80% compliance). Increased rates of breastfeeding to the level of Healthy People 2020 goals and beyond would yield significant cost savings to Louisiana. Other US states can use the presented framework to demonstrate cost savings associated with breastfeeding promotion and support interventions in their respective states. Keywords Exclusive breastfeeding * Cost-savings Mortality and morbidity prevention, Introduction Breastfeeding is an effective, low cost prevention strategy for improving the health of the maternal and child populations in both developed and developing nations [1]. A systematic review and [...]

Background: As a novel form of programmed cell death, necroptosis is related to multiple tumor types and their immune microenvironments. However, its association with glioma has not been clarified. Methods: Necroptosis genes were obtained from the Gene Set Enrichment Analysis (GSEA) database. RNA-seq and clinical data were downloaded from TCGA and CGGA databases. A necroptosis gene signature was constructed based on univariate and multivariate Cox regression analyses. Next, survival analysis, independent prognostic analysis, and nomogram were performed to assess and verify the model. Subsequently, we analyzed the tumor microenvironment (TME) and immune cell infiltration via ESTIMATE and CIBERSORTx algorithms. Finally, the response of glioma patients in the TCGA database to immune checkpoint inhibitor (ICI) therapy was predicted using the Tumor Immune Dysfunction and Exclusion (TIDE) database. Results: Of the seven prognostic necroptosis genes, RIPK1, RIPK3, FAS, and FADD were used to construct the risk signature that accurately predicts the prognosis of glioma patients. Functional enrichment results suggest that necroptosis is correlated with immune response and angiogenesis. Immune analysis revealed that necroptosis can boost inflammatory activity and attract immunosuppressive cell infiltration to form a chronic inflammatory microenvironment, promoting glioma growth. Additionally, glioma patients in the TCGA cohort with high necroptosis gene expression exhibited a better response to ICI therapy predicted by the TIDE algorithm. Conclusion: We constructed a necroptosis gene signature, which has the potential for use as a biomarker for predicting glioma patients' prognosis, revealing the association between necroptosis and the immune microenvironment, and serving as a reference for immune therapy. [ABSTRACT FROM AUTHOR]

We aimed to investigate the expression levels of GABA and GABAA receptor α1 and α2 subunits in patients with major depressive disorder (MDD) during onset and remission. 48 patients with MDD during onset and 45 patients with MDD during remission who were treated in our university were selected. Moreover, the control group included 46 healthy volunteers recruited in the community. The depression and anxiety symptoms were assessed by Hamilton Depression (HAMD) Scale and Hamilton Anxiety (HAMA) Scale. ELISA was used to determine the serum GABA levels. The mRNA expression of GABAA receptor α1 and α2 subunits in peripheral blood were detected by RT-PCR. The expression levels of serum GABA and of GABAA receptor α1 and α2 subunits in MDD depression attack group were notably decreased in comparison with those in MDD remission group and control group ((4.10 ± 0.73) v.s. (5.91 ± 1.25) and (5.83 ± 1.17) umol/L, F = 5.61, p < 0.001; (0.53 ± 0.32) v.s. (0.91 ± 0.18) and (0.93 ± 0.21), F = 8.37, p < 0.001; (1.45 ± 0.86) v.s. (2.33 ± 1.49) and (2.28 ± 1.50), F = 8.23, p < 0.001). However, there were no marked difference in the levels of these three indices between the MDD remission group and the control group (p > 0.05). Serum GABA levels were negatively correlated with HAMA total score (r = −0.34, p = 0.02), HAMD total score (r = −0.46, p = 0.01) and depression core symptom score (r = −0.32, p = 0.03). During the onset of MDD, there may be GABA neuronal dysfunction and abnormal expression of GABAA receptor subunits, and those changes showed a state change, which gradually returned to normal during remission. [ABSTRACT FROM AUTHOR]

Intestinal microbiota is an important prognostic factor for allogeneic hematopoietic stem cell transplantation (allo-HSCT), but its role in predicting survival has not been determined. Here, stool samples at day 15 ± 1 posttransplant were obtained from 209 patients at two centers. Microbiota was examined using 16S rRNA sequencing. The microbiota diversity and abundance of specific bacteria (including Lachnospiraceae, Ruminococcaceae, Erysipelotrichaceae, and Enterobacteriaceae) were assigned a value of 0 or 1 depending on whether they were positive or negative associated with survival, respectively. An accumulated intestinal microbiota (AIM) score was generated, and patients were divided into low- and high-score groups. A low score was associated with a better 3-year cumulative overall survival (OS) as well as lower mortality than a high score (88.5 vs. 43.9% and 7.1 vs. 35.8%, respectively; both P < 0.001). In multivariate analysis, a high score was found to be an independent risk factor for OS and transplant-related mortality (hazard ratio = 5.68 and 3.92, respectively; P < 0.001 and 0.003, respectively). Furthermore, the AIM score could serve as a predictor for survival (area under receiver operating characteristic curve = 0.836, P < 0.001). Therefore, the intestinal microbiota score at neutrophil recovery could predict survival following allo-HSCT. [ABSTRACT FROM AUTHOR]