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Interval-censored failure time data are commonly encountered in many fields and some methods and models have been proposed for them in the literature. In the real situations, interval censoring is informative. For this problem, we propose a new frailty-based generalized estimating equation (GEE) method of the proportional hazards (PH) model with the informatively case K interval-censored failure time data. In this article, a frailty-based generalized estimating equation is developed that can yield an unbiased estimator of the cumulative hazards function. The observation process of the proposed method does not need a non homogeneous Poisson process used in many existing literatures. The asymptotic properties of the proposed method are established, and an extensive simulation study is conducted to assess the performance of the proposed procedure. In addition, an application to an AIDS clinical trial data set is presented. [ABSTRACT FROM AUTHOR]

In diagnostic studies, a continuous biomarker is often dichotomized for the diagnosis of binary disease status. Various criteria have been studied for the cut point selection of the continuous biomarker in receiver operating characteristic (ROC) analysis, in particular, the Youden index, the closest-to-(0,1) index, and the concordance probability index. Recently, Wang, Tian, and Zhao (2017) established a Wilks theorem for a smoothed empirical likelihood ratio statistic of Youden index. However, it is not directly useful for statistical inference compared to the cut point. In addition, the optimal cut point may vary with different criteria. In this article, we study smoothed empirical likelihood for optimal cut point selection with Youden index, closest-to-(0,1) criterion, and concordance probability. We develop confidence estimation for the optimal cut points based on the smoothed empirical likelihood ratio statistics. We examine the empirical performance by extensive simulation studies. We also illustrate the method with a real dataset. [ABSTRACT FROM AUTHOR]

Photothermal immunotherapy represents an effective approach for eliminating both local and metastatic tumors through priming of the tumor‐specific immune response. Cytosolic delivery of double‐stranded DNA via pH‐responsive vehicles is recently verified to activate the cyclic guanosine monophosphate–adenosine monophosphate (GMP‐AMP) synthase‐stimulator of interferon genes (cGAS‐STING) pathway, which is robust in activating both innate and adaptive antitumor immunity. Herein, multifunctional phototheranostics with excellent photothermal conversion capacity, second near‐infrared (NIR‐II) fluorescence, and cGAS‐STING activating capacity are prepared by encapsulating fish testis DNA and conjugated boron dipyrromethene tetramers with poly(lactic‐co‐glycolic acid) and poly(ethylene glycol)‐b‐poly(lactic‐co‐glycolic acid) via a CaCO3‐assisted double emulsion method. The obtained phototheranostics (coined DB4CaP NPs) after intravenous administration gradually accumulate in tumor regions, as shown by NIR‐II fluorescence imaging. Together with local 915 nm laser exposure, primary tumors in mice treated with DB4CaP NPs could be effectively eradicated, with a complete response of 83.3%. Furthermore, such DB4CaP NPs could synergize with anti‐programmed cell death protein 1 immunotherapy to suppress the growth of distant unirradiated and rechallenged tumors through activating the antitumor immune response. This study highlights a promising strategy for eradicating tumors, particularly invisible and unresectable micronodules, through NIR‐II fluorescence imaging‐guided photothermal immunotherapy. [ABSTRACT FROM AUTHOR]

This study aims to develop an MRI-based radiomics model to assess the likelihood of recurrence in luminal B breast cancer. The study analyzed medical images and clinical data from 244 patients with luminal B breast cancer. Of 244 patients, 35 had experienced recurrence and 209 had not. The patients were randomly divided into the training set (51.5 ± 12.5 years old; n = 171) and the test set (51.7 ± 11.3 years old; n = 73) in a ratio of 7:3. The study employed univariate and multivariate Cox regression along with the least absolute shrinkage and selection operator (LASSO) regression methods to select radiomics features and calculate a risk score. A combined model was constructed by integrating the risk score with the clinical and pathological characteristics. The study identified two radiomics features (GLSZM and GLRLM) from DCE-MRI that were used to calculate a risk score. The AUCs were 0.860 and 0.868 in the training set and 0.816 and 0.714 in the testing set for 3- and 5-year recurrence risk, respectively. The combined model incorporating the risk score, pN, and endocrine therapy showed improved predictive power, with AUCs of 0.857 and 0.912 in the training set and 0.943 and 0.945 in the testing set for 3- and 5-year recurrence risk, respectively. The calibration curve of the combined model showed good consistency between predicted and measured values. Our study developed an MRI-based radiomics model that integrates clinical and radiomics features to assess the likelihood of recurrence in luminal B breast cancer. The model shows promise for improving clinical risk stratification and treatment decision-making. [ABSTRACT FROM AUTHOR]

As the alternative of Cox model, the accelerated failure time (AFT) model, which simply regresses the logarithm of the survival time over the covariates, is commonly used in the analysis of interval-censored data. In this paper, we propose a novel two-component mixture-cure model for the interval-censored failure time data in the presence of a cure fraction. Specifically, the first component is a logistic regression model that describes the cure rate, and the second component is a semiparametric accelerated failure time model that describes the failure time of interest for the uncured subjects. An efficient semiparametric procedure is developed to estimate parameters in the considered model. We propose a penalized sieve maximum likelihood estimation approach with Bernstein polynomials to estimate the regression parameters quickly and accurately and the proposed procedure does not rely on the assumption of the distribution of the measurement error. The asymptotic properties of the resulting estimators are established. Extensive simulation studies conducted indicate that the proposed procedure works well for practical situations. In addition, AIDS data analysis is provided for illustration of the proposed method. [ABSTRACT FROM AUTHOR]

Fiber orientation parametrization is a fundamental issue in topology optimization of continuous fiber-reinforced composites. The conventional Euler angles-based parametrization often encounters singular points, which can be problematic. To address this challenge, the Cartesian representation-based parametrization is revisited. By leveraging the transversal isotropy property of fiber-reinforced composites, a direct mapping between the Cartesian representation of the 3D fiber orientation and the rotated stiffness matrix is established. Thus, the transformations between Euler angles and Cartesian representation have become unnecessary, simplifying implementation and avoiding associated numerical issues. Building upon the proposed Cartesian parametrization, the classical minimum compliance design problem for 3D continuous fiber-reinforced composites is formulated. Then, efficient sensitivity analysis and decoupled design variable updating strategies are developed. The effectiveness of the proposed parametrization is demonstrated through three large-scale topology optimization examples. These case studies showcase the capability of the approach to solve practical problems and achieve improved optimization outcomes. [ABSTRACT FROM AUTHOR]

Controlling the optical activity of halide perovskite materials through modulation of the coordination configurations of the metal ions is important. Herein, a novel manganese‐based halide, specifically diaquatetrakis(methyldiphenylphosphine oxide)manganese(II) tetrachloridomanganate(II), [Mn(C13H13OP)4(H2O)2][MnCl4] or [Mn(MDPPO)4(H2O)2][MnCl4] (MDPPO is methyldiphenylphosphine oxide), was synthesized through the solvothermal reaction of MnCl2 with the neutral molecule MDPPO. In this compound, [Mn(MDPPO)4(H2O)2]2+ acts as the cation, while [MnCl4]2− serves as the anion, enabling the co‐existence of tetrahedral and octahedral structures within the same system. Remarkably, the compound exhibits efficient red‐light emission at 662 nm, distinct from the green‐light emission typically observed in MnX4‐based halides. Theoretical calculations show that the red emission comes from the charge transfer from the MDPPO to the Mn2+ of [MnCl4]2−. This work provides a new perspective for the design and synthesis of red‐light‐emitting manganese‐based halides with unique structures. [ABSTRACT FROM AUTHOR]

Synthetic biology is propelling medicine into a new era through its capacity to genetically program living cells. One of the particular interests is engineering bacteria as a live and targeted therapeutic delivery system. Herein, the bacterial biohybrid (E. coli‐pE@PCN) is developed by genetically engineering Escherichia coli BL21 to overexpress catalase (E. coli‐pE) and electrostatically adsorbing nano‐sonosensitizers (PCN NPs) for enhanced and targeted sonodynamic therapy (SDT). Leveraging the ability to colonize and penetrate deep in tumors, engineered bacteria can not only sustainably express catalase to relieve tumor hypoxia, but also facilitate the enriched and expanded distribution of the carried sonosensitizer at the tumor site, so as to trigger effective SDT. More interestingly, it is found that E. coli‐pE@PCN‐based SDT can successfully inhibit the growth of subcutaneous and orthotopic colorectal tumors by inducing potent antitumor immune responses due to the released tumor‐associated antigens and native immunogenicity of bacterial pathogen‐associated molecular patterns. Furthermore, E. coli‐pE@PCN‐based SDT can not only prime a strong immune memory response to prevent tumor recurrence but also elicit a potent abscopal effect to inhibit tumor metastasis. Therefore, the programmable bacteria‐based biohybrids developed here pave an avenue to prepare next‐generation sonodynamic‐immunotherapeutics to eliminate cancer and prevent its relapse and metastasis. [ABSTRACT FROM AUTHOR]

This article investigates the estimation and variable selection procedures of single-index models when the data have non ignorable response. For estimation of the index coefficients, a new procedure based on martingale difference divergence is developed. Consistency and asymptotic normality of the proposed estimators are established. The finite sample performance of the proposed procedure is assessed through extensive simulation studies. Finally, we illustrate the proposed method through a real body fat data set. [ABSTRACT FROM AUTHOR]

Abacus‐based mental calculation (AMC) is a widely used educational tool for enhancing math learning, offering an accessible and cost‐effective method for classroom implementation. Despite its universal appeal, the neurocognitive mechanisms that drive the efficacy of AMC training remain poorly understood. Notably, although abacus training relies heavily on the rapid recall of number positions and sequences, the role of memory systems in driving long‐term AMC learning remains unknown. Here, we sought to address this gap by investigating the role of the medial temporal lobe (MTL) memory system in predicting long‐term AMC training gains in second‐grade children, who were longitudinally assessed up to fifth grade. Leveraging multimodal neuroimaging data, we tested the hypothesis that MTL systems, known for their involvement in associative memory, are instrumental in facilitating AMC‐induced improvements in math skills. We found that gray matter volume in bilateral MTL, along with functional connectivity between the MTL and frontal and ventral temporal‐occipital cortices, significantly predicted learning gains. Intriguingly, greater gray matter volume but weaker connectivity of the posterior parietal cortex predicted better learning outcomes, offering a more nuanced view of brain systems at play in AMC training. Our findings not only underscore the critical role of the MTL memory system in AMC training but also illuminate the neurobiological factors contributing to individual differences in cognitive skill acquisition. A video abstract of this article can be viewed at https://youtu.be/StVooNRc7T8. Research Highlights: We investigated the role of medial temporal lobe (MTL) memory system in driving children's math learning following abacus‐based mental calculation (AMC) training.AMC training improved math skills in elementary school children across their second and fifth grade.MTL structural integrity and functional connectivity with prefrontal and ventral temporal‐occipital cortices predicted long‐term AMC training‐related gains. [ABSTRACT FROM AUTHOR]

Organic carbon in grassland mainly exists in the soil, and root production and turnover play important roles in carbon input into the soil. However, the effects of climate change on plant root dynamics in desert steppe are unknown. We conducted an experiment in a desert steppe, which included ambient temperature (T0); temperature increased by 2 °C (T1); temperature increased by 4 °C (T2); natural precipitation (P0); precipitation increased by 25% (P1); precipitation increased by 50% (P2); and the interaction between warming and increased precipitation. Plant community aboveground characteristics; root production; and root turnover were measured. We found that the root length production of the T0P2; T1P1; T2P0; and T2P1 treatments were significantly higher than that of the T0P0 treatment, with an increment of 98.70%, 11.72%, 163.03%, and 85.14%, respectively. Three treatments with temperature increased by 2 °C (T1P0; T1P1; and T1P2) and significantly increased root turnover rate compared to the T0P0 treatment, with increases of 62.53%, 42.57%, and 35.55%, respectively. The interaction between warming and increased precipitation significantly affected the root production of the community (p < 0.01), but this interaction was non-additive. Future climate warming will benefit the accumulation of root-derived carbon in desert steppe communities. [ABSTRACT FROM AUTHOR]

Background: Process-based teaching is a new education model. SPARK case database is a free medical imaging case database. This manuscript aimed to explore the application of the process-based teaching based on SPARK case database in the practice teaching of radiology in the musculoskeletal system. Methods: 117 third year medical students were included. They were divided into Group A, B, C and D according to the curriculum arrangement. Group A and B attended the experimental class at the same time, A was the experimental group, B was the control group. Group C and D attended experimental classes at the same time, C was the experimental group, D was the control group. The experimental group used SPARK case database, while the control group used traditional teaching model for learning. The four groups of students were respectively tested after the theoretical class, before the experimental class, after the experimental class, and one week after the experimental class to compare the results. Finally, all students used SPARK case database to study, and were tested one month after the experimental class to compare their differences. Results: The scores after the theoretical class of Group A and B were (100.0 ± 25.4), (101.0 ± 23.8)(t=-0.160, P > 0.05), Group C and D were (94.7 ± 23.7), (92.1 ± 18.6)(t = 0.467, P > 0.05). The scores of Group A and B before and after the experimental class and one week after the experimental class were respectively (84.1 ± 17.4), (72.1 ± 21.3)(t = 2.363, P < 0.05), (107.6 ± 14.3), (102.1 ± 18.0)(t = 1.292, P > 0.05), (89.7 ± 24.3), (66.6 ± 23.2)(t = 3.706, P < 0.05). The scores of Group C and D were (94.0 ± 17.3), (72.8 ± 25.5)(t = 3.755, P < 0.05), (107.3 ± 20.3), (93.1 ± 20.9)(t = 2.652, P < 0.05), (100.3 ± 19.7), (77.2 ± 24.0)(t = 4.039, P < 0.05). The scores of Group A and B for one month after the experimental class were (86.6 ± 28.8), (84.5 ± 24.0)(t = 0.297, P > 0.05), and Group C and D were (95.7 ± 20.3), (91.7 ± 23.0)(t = 0.699, P > 0.05). Conclusions: The process-based teaching based on SPARK case database could improve the radiology practice ability of the musculoskeletal system of students. [ABSTRACT FROM AUTHOR]

The proportional odds (PO) model is one of the most commonly used models for regression analysis of failure time data in survival analysis. It assumes that the odds of the failure is proportional to the baseline odds at any point in time given the covariate. The model focus on the situation that the ratio of the hazards converges to unity as time goes to infinity, while the proportional hazards (PH) model has a constant ratio of hazards over time. In the paper, we consider a general type of failure time data, case K interval-censored data, that include case I or case II interval-censored data as special cases. We propose a PO model-based unified penalized variable selection procedure that involves minimizing a negative sieve log-likelihood function plus a broken adaptive ridge penalty, with the initial values obtained from the ridge regression estimator. The proposed approach allows dependent censoring, which occurs quite often and could lead to biased or misleading estimates without considering it. We show that the proposed selection method has oracle properties and the estimator is semiparametrically efficient. The numerical studies suggest that the proposed approach works well for practical situations. In addition, the method is applied to an ADNI study that motivates this investigation. [ABSTRACT FROM AUTHOR]

In automotive adhesive defect detection, manual inspection suffers from low efficiency and blind spots in human vision, which affects the performance of parts. Therefore, automated detection methods are particularly important. To address the issue of adhesive defects significantly impacting production during automated gluing processes, we propose an adhesive defect detection method for automotive applications based on the improved YOLOv8 (named YOLOv8n-SSE). First, we used the SSE (skip squeeze and excitation) attention mechanism in the backbone part to dynamically adjust the importance of different channels in our model and allow our model to selectively focus on important features. Then, the original bounding box loss function is replaced by the WIoU loss function. Experimental results demonstrate that this method improves the mAP50 of the original YOLOv8n by 3.25% and achieves an average detection speed of 7.9ms per image, equivalent to 126.58 frames per second (FPS), meeting the real-time defect detection requirements. [ABSTRACT FROM AUTHOR]

Previous neuroimaging studies on arithmetic development have mainly focused on functional activation or functional connectivity between brain regions. It remains largely unknown how brain structures support arithmetic development. The present study investigated whether early gray matter structural covariance contributes to later gain in arithmetic ability in children. We used a public longitudinal sample comprising 63 typically developing children. The participants received structural magnetic resonance imaging scanning when they were 11 years old and were tested with a multiplication task at 11 years old (time 1) and 13 years old (time 2), respectively. Mean gray matter volumes were extracted from eight brain regions of interest to anchor salience network (SN), frontal-parietal network (FPN), motor network (MN), and default mode network (DMN) at time 1. We found that longitudinal gain in arithmetic ability was associated with stronger structural covariance of the SN seed with frontal and parietal regions and stronger structural covariance of the FPN seed with insula, but weaker structural covariance of the FPN seed with motor and temporal regions, weaker structural covariance of the MN seed with frontal and motor regions, and weaker structural covariance of the DMN seed with temporal region. However, we did not detect correlation between longitudinal gain in arithmetic ability and behavioral measure or regional gray matter volume at time 1. Our study provides novel evidence for a specific contribution of gray matter structural covariance to longitudinal gain in arithmetic ability in childhood. [ABSTRACT FROM AUTHOR]

Partly interval censoring is frequently encountered in clinical trials when the failure time of an event is observed exactly for some subjects but is only known to fall within an observed interval for others. Although this kind of censoring has drawn recent attention in survival analysis, available methods typically assume that the observed interval is independent of the failure time and that all potential predictors can be fully observable. However, the above assumptions may not be valid in practice. This paper considers a new joint modeling approach to simultaneously model the failure and observation times and correlate these two stochastic processes through shared latent factors. The proposed model comprises a transformation model for the failure time of interest, a proportional hazards model for the length of censoring interval, and a factor analysis model for characterization of the latent factors. A multi-stage data augmentation procedure is introduced to tackle the challenges posed by the complex model and data structure. A Bayesian approach coupled with monotone spline approximation and Markov chain Monte Carlo techniques is developed to estimate the unknown parameters and nonparametric functions. The satisfactory performance of the proposed method is demonstrated through simulations, and it is then applied to a Framingham Heart study. [ABSTRACT FROM AUTHOR]

Emotion regulates our memory in daily life. Previous studies have shown that extrinsic emotion during encoding impairs the memory for target stimulus. However, most previous studies focused on the effects of emotion on the typical encoding without intentional retrieval. It remains unclear how emotion affects the retrieval-based encoding and memory. In the present study, we examined how encoding type (restudy versus retrieval practice) regulates emotional memory retention. We adopted a typical retrieval practice paradigm with an initial study phase, a second phase with either a restudy or a retrieval practice task, and a final recognition test. In order to create extrinsic emotional background, emotional pictures were used during the restudy and retrieval practice tasks. The recognition test was carried out 5 min or 24 h after the restudy or retrieval practice task. We found an emotional impairment effect on familiarity (5-min retention interval) under the retrieval practice condition, but not under the restudy condition, and an emotional enhancement effect on item memory (24-h retention interval) under the restudy condition, but not under the retrieval practice condition. The present study demonstrated the effect of encoding type on emotional memory and suggested a retention interval dependent effect of encoding type, contributing to the theory of emotional memory by highlighting the role of encoding type and retention interval. [ABSTRACT FROM AUTHOR]

Accurate and efficient COVID-19 diagnosis is crucial in clinical settings. However, the limited availability of labeled data poses a challenge for traditional machine learning algorithms. To address this issue, we propose Turning Point (TP), a few-shot learning (FSL) approach that leverages high-level turning point mappings to build sophisticated representations across previously labeled data. Unlike existing FSL models, TP learns using quasi-configured topological spaces and efficiently combines the outputs of diverse TP learners. We evaluated TPFSL using three COVID-19 datasets and compared it with seven different benchmarks. Results show that TPFSL outperformed the top-performing benchmark models in both one-shot and five-shot tasks, with an average improvement of 4.50% and 4.43%, respectively. Additionally, TPFSL significantly outperformed the ProtoNet benchmark by 12.966% and 11.033% in one-shot and five-shot classification problems across all datasets. Ablation experiments were also conducted to analyze the impact of variables such as TP density, network topology, distance measure, and TP placement. Overall, TPFSL has the potential to improve the accuracy and speed of diagnoses for COVID-19 in clinical settings and can be a valuable tool for medical professionals. [ABSTRACT FROM AUTHOR]

Lipiodol chemotherapeutic emulsions remain one of the main choices for the treatment of unresectable hepatocellular carcinoma (HCC) via transarterial chemoembolization (TACE). However, the limited stability of Lipiodol chemotherapeutic emulsions would lead to rapid drug diffusion, which would reduce the therapeutic benefit and cause systemic toxicity of administrated chemotherapeutics. Therefore, the development of enhanced Lipiodol-based formulations is of great significance to enable effective and safe TACE treatment. Herein, a stable water-in-oil Lipiodol Pickering emulsion (LPE) stabilized by pH-dissociable calcium carbonate nanoparticles and hemin is prepared and utilized for efficient encapsulation of lipoxygenase (LOX). The obtained LOX-loaded CaCO3&hemin-stabilized LPE (LHCa-LPE) showing greatly improved emulsion stability could work as a pH-responsive and self-fueling microreactor to convert polyunsaturated fatty acids (PUFAs), a main component of Lipiodol, to cytotoxic lipid radicals through the cascading catalytic reaction driven by LOX and hemin, thus inducing ferroptosis of cancer cells. As a result, such LHCa-LPE upon transcatheter embolization can effectively suppress the progression of orthotopic N1S1 HCC in rats. This study highlights a concise strategy to prepare pH-responsive and stable LPE-based self-fueling microreactors, which could serve as bifunctional embolic and ferroptosis-inducing agents to enable proof-of-concept transarterial ferro-embolization therapy of HCC. [ABSTRACT FROM AUTHOR]

To sustainably power ocean sensors by harvesting ocean wave energy, an annular electromagnetic generator (A-EMG) based on the principle of Faraday electromagnetic induction is proposed in this paper. The specific structure and working principle of the generator are introduced. The distribution of the magnetic field in the coil, the variation in the induced voltage and the influence of the coil parameters on the output were simulated by the COMSOL Multiphysics software version 6.0. At the same time, an experimental platform was built to test the output characteristics of the generator. Through a comparative study of the capacitor's charging characteristics, the optimal connection mode between the multiple groups of coils of the generator was preliminarily verified. Finally, the six-degree-of-freedom (6-DOF) platform was used to simulate various wave motion parameters, and the feasibility of the generator for supplying power to ocean sensors was verified. [ABSTRACT FROM AUTHOR]

Purposes: To develop a deep learning (DL) model to measure the sagittal Cobb angle of the cervical spine on computed tomography (CT). Materials and methods: Two VB-Net-based DL models for cervical vertebra segmentation and key-point detection were developed. Four-points and line-fitting methods were used to calculate the sagittal Cobb angle automatically. The average value of the sagittal Cobb angle was manually measured by two doctors as the reference standard. The percentage of correct key points (PCK), matched samples t test, intraclass correlation coefficient (ICC), Pearson correlation coefficient, mean absolute error (MAE), and Bland‒Altman plots were used to evaluate the performance of the DL model and the robustness and generalization of the model on the external test set. Results: A total of 991 patients were included in the internal data set, and 112 patients were included in the external data set. The PCK of the DL model ranged from 78 to 100% in the test set. The four-points method, line-fitting method, and reference standard measured sagittal Cobb angles were − 1.10 ± 18.29°, 0.30 ± 13.36°, and 0.50 ± 12.83° in the internal test set and 4.55 ± 20.01°, 3.66 ± 18.55°, and 1.83 ± 12.02° in the external test set, respectively. The sagittal Cobb angle calculated by the four-points method and the line-fitting method maintained high consistency with the reference standard (internal test set: ICC = 0.75 and 0.97; r = 0.64 and 0.94; MAE = 5.42° and 3.23°, respectively; external test set: ICC = 0.74 and 0.80, r = 0.66 and 0.974, MAE = 5.25° and 4.68°, respectively). Conclusions: The DL model can accurately measure the sagittal Cobb angle of the cervical spine on CT. The line-fitting method shows a higher consistency with the doctors and a minor average absolute error. [ABSTRACT FROM AUTHOR]

Empirical likelihood has been widely used in survival data analysis recently. In this paper, we combine Bayesian idea with empirical likelihood and develop a Bayesian empirical likelihood method to analyze current status data based on the linear regression model. By constructing unbiased transformation of current status data, we derive an empirical log-likelihood function. The normal prior distribution and a Metro-Hastings method are presented to make Bayesian posterior inference. The theoretical properties of the estimators are proposed. Extensive simulation studies indicate that Bayesian empirical likelihood method performs much better than the empirical likelihood method in terms of coverage probability. Finally, we apply two real data to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

Statistical analysis of right-censored failure time data has been extensively discussed in the literature as such data often occur in many fields. In this article, we propose a new Bayesian-based empirical likelihood approach for the problem under the proportional hazards model. The new method allows one to take into account the existing prior information among other advantages, and for the implementation of the method, a Metropolis–Hasting algorithm is developed. To assess the performance of the proposed approach, a simulation study is conducted and suggests that it works well. The method is applied to a set of kidney dialysis data. [ABSTRACT FROM AUTHOR]

Background: Accurate differentiation of nodular fasciitis (NF) from soft tissue sarcoma (STS) before surgery is essential for the subsequent diagnosis and treatment of patients. Purpose: To develop and evaluate radiomics nomograms based on clinical factors and magnetic resonance imaging (MRI) for the preoperative differentiation of NF from STS. Material and Methods: This retrospective study analyzed the MRI data of 27 patients with pathologically diagnosed NF and 58 patients with STS who were randomly divided into training (n = 62) and validation (n = 23) groups. Univariate and multivariate analyses were performed to identify the clinical factors and semantic features of MRI. Radiomics analysis was applied to fat-suppressed T1-weighted (T1W-FS) images, fat-suppressed T2-weighted (T2W-FS) images, and contrast-enhanced T1-weighted (CE-T1W) images. The radiomics nomograms incorporating the radiomics signatures, clinical factors, and semantic features of MRI were developed. ROC curves and AUCs were carried out to compare the performance of the clinical factors, radiomics signatures, and clinical radiomics nomograms. Results: Tumor location, size, heterogeneous signal intensity on T2W-FS imaging, heterogeneous signal intensity on CE-T1W imaging, margin definitions on CE-T1W imaging, and septa were independent predictors for differentiating NF from STS (P < 0.05). The performance of the radiomics signatures based on T2W-FS imaging (AUC = 0.961) and CE-T1W imaging (AUC = 0.938) was better than that based on T1W-FS imaging (AUC = 0.833). The radiomics nomograms had AUCs of 0.949, which demonstrated good clinical utility and calibration. Conclusion: The non-invasive clinical radiomics nomograms exhibited good performance in the differentiation of NF from STS, and they have clinical application in the preoperative diagnosis of diseases. [ABSTRACT FROM AUTHOR]

Marine buoys need to operate in high sea areas far from land for a long time. Therefore, how to provide a long-term power supply for the buoy system is critical to be addressed. Photovoltaic (PV) power supply systems are the most commonly used power supply method for marine buoys. Due to the limitations of the buoy structure and considering the rotation of the buoy in the ocean, most of the PV modules are placed in a four-sided enclosure. The output performance of the PV power supply system in this placement is affected by the tilt angle produced by waves. However, there are few relevant studies on the actual power generation performance of PV power supply systems for marine buoys, and there is a lack of methods for power generation performance analysis. In order to meet the power requirements of the marine buoy, a large design margin must be left. It increases the cost of marine buoys. In this paper, second-order Stokes waves are used to simulate waves of different levels by varying the wave height and frequency. The motion characteristics of the marine buoy are analyzed using ANSYS-AQWA under calm-rippled, smooth, slight, and moderate conditions. Combined with the tilted surface irradiance calculation model to get the variation law of solar radiation of PV modules under dynamic conditions, the effect of different tilt angle PV modules on the output of PV system under dynamic conditions was also studied. The experiments show that for every 5° increase in the tilt angle of the PV modules the output power of the system decreases by 3% on average. As the tilt angle of the PV modules increases, the impact on the system output performance is more pronounced. The output power decreased by 69.5% when the PV modules were tilted at an angle of 90°, and the PV system electrical parameters were similarly affected. By comparing the influence of different tilt angles on the power supply performance of PV modules, we optimize the design of the PV power supply system of the buoy. This enables the designers to maximize the use of limited area and space while reducing the cost and extending the power supply time and service life of the buoy. [ABSTRACT FROM AUTHOR]

Proactive control, the ability to maintain task-relevant information in preparation for upcoming targets, has been shown to critically depend on working memory. The present study aimed to investigate the development of proactive control and its relationship with working memory in school-age children. A total of 135 Chinese school-age children were recruited. Among them, 122 children (7-year-olds: 41; 9-year-olds: 41; 11-year-olds: 40) contributed useable data for both proactive control and working memory. The results showed that proactive control efficiency on an inhibition task improved significantly from the 7-year-olds to both the 9- and 11-year-olds, while proactive control efficiency on a switching task improved significantly from both the 7- and 9-year-olds to the 11-year-olds. Besides, proactive control indices correlated significantly between the inhibition and switching tasks for the 11-year-olds but not for the 7- or 9-year-olds, suggesting that consistency in proactive control engagement across tasks may be low at early primary school years but increases at later periods. Furthermore, working memory was positively correlated with proactive control efficiency for the 7-year-olds but not for the 9- or 11-year-olds, suggesting that the relationship between proactive control and working memory may decrease with age. These results were replicated in an independent sample. Altogether, the present study advances our understanding of the development of proactive control as well as its relationship with working memory in school-age children. [ABSTRACT FROM AUTHOR]

Background: The effects of Arula-7 powder (ASP) on diarrhea and intestinal barrier function associated with its regulation of intestinal microflora in calves infected with pathogenic Escherichia coli O1 (E. coli O1) were studied. Method: Twenty Holstein calves were randomly divided into four treatment groups: normal control (NC), model control (MC), 0.5 mg/kg ciprofloxacin (CIP) and 2.50 g/kg ASP groups. Results: ASP inhibited the relative abundance of Proteobacteria, Selenomonadales, and Enterobacteriales, and increased the relative abundance of Lactobacillus, Faecalibacterium, and Alloprevotella. Moreover, we demonstrated for the first time that the ASP and CIP promoted weight gain, reduced the diarrhea rate (P < 0.05), and enhanced antioxidant capacity (P < 0.05) due to the increase in average daily gain (ADG), total protein (TP), and albumin (ALB). In addition, ASP and CIP increased the expression of Zunola occludens-1 (ZO-1), Occludin, and Claudin-1 in the ileum (P < 0.05), and improved immunity due to increase levels of interleukin-2 (IL-2), interleukin-4 (IL-4), interferon-γ (IFN-γ), immunoglobulin A (IgA), and immunoglobulin G (IgG) in the serum, strengthened CD4+T levels in the ileal mucosa and reducing CD8+T and CD11c+T (P < 0.05). Conclusion: Hence, The intestinal microbiota environment formed by early intervention of ASP powder has a protective effect on the intestinal mucosal function of calves infected with pathogenic E. coli. 4nw2EB1YynqDa4Tsj5-kjP Video Abstract [ABSTRACT FROM AUTHOR]

Aims: Due to its rarity and non‐specific clinical and pathological features, low‐grade adenosquamous carcinoma (LGASC) of the breast continues to pose diagnostic challenges. Unlike other triple‐negative breast carcinomas, LGASC tends to have an indolent clinical behaviour. It is essential to recognise this lesion for accurate diagnosis and appropriate management. Methods and results: Twenty‐five cases of LGASC were identified in our archives and collaborating institutes. Cases of LGASC with dominant coexisting other type carcinomas were excluded. We studied the clinical presentation, morphological features, patterns of the commonly used immunohistochemical stains and follow‐up. In our cohort, LGASC was commonly located at the outer aspect of the breast and associated with intraductal papilloma. The morphology of LGASC is characterised by infiltrating small glands and nests with variable squamous differentiation. We also found cuffing desmoplastic (fibrolamellar) stromal change in 75% of patients and peripheral lymphocytic aggregates in 87.5% of patients. P63 and smooth muscle myosin (SMM) were the most common myoepithelial markers used to assist in diagnosis. P63 often stained peripheral tumour cells surrounding invasive glands (circumferential staining in 80% of the cases), mimicking myoepithelial cells. It also stained the small nests with squamous differentiation. However, SMM was negative in 63% of the cases. The vast majority of our cases were triple‐negative; only a few had focal and weak expressions of ER and PR. One patient who did not have excision developed lymph node metastasis. Most patients underwent excision or mastectomy with negative margins as surgical treatment; there were no recurrences or metastases in these patients with clinical follow‐ups up to 108 months. Conclusions: LGASC has some unique, although not entirely specific, morphological features and immunohistochemical staining patterns. Fibrolamellar stromal change, peripheral lymphocytic aggregates and variable staining of p63 and SMM are valuable features to facilitate the diagnosis. [ABSTRACT FROM AUTHOR]

Photodynamic therapy is a noninvasive type of phototherapy with a high capacity to boost specific antitumor immunity by causing immunogenic cell death. However, the photodynamic therapeutic potency toward solid tumors is dampened by tumor hypoxia that negatively impairs the generation of cytotoxic singlet oxygen and promotes the formation of tumor immunosuppression. Herein, fluorinated CaCO3 (CaF) nanoparticles are prepared with the addition of dopamine-conjugated perfluorosebacic acid and ferric chloride into a calcium chloride ethanol solution via an ammonium bicarbonate-mediated gas-diffusion process. After being coated with commercial lipids and hexadecylamin conjugated chlorin e6 (hCe6) via a templated self-assembly process, the yielded PEGylated nanophotosensitizer (hCe6@CaF-PEG) exhibits an effective loading efficiency to perfluoro-15-crown-5-ether (PFCE), a model perfluorocarbon molecule, and thus oxygen molecules. Upon intravenous administration, the obtained PFCE/hCe6@CaF-PEG can alleviate tumor hypoxia by working as an oxygen nanoshuttle. Together with local light emitting diode light exposure, photodynamic treatment with PFCE/hCe6@CaF-PEG can suppress the growth of primary CT26 tumors and unirradiated distant tumors, particularly when synergized with anti-PD-1 (aPD-1) immunotherapy to collectively reverse tumor immunosuppression. This work presents an effective strategy to potentiate photodynamic immunotherapy by concurrently reversing tumor hypoxia and immunosuppression. [ABSTRACT FROM AUTHOR]

For positive numbers t, p,q,c and an analytic function f(z) in an annulus R1 < |z| < R2, let Mt,ϕ,q,c(f,r) be the area integral means of f with respect to the weighted area measure ϕ' (|z| q)|z| q−2 dA(z), where R1 ≤ c < R2 . We show that Mt,ϕ,q,c(f,r) 1/p is a convex function of r if f and ϕ satisfy certain conditions. The convexities of logMt,ϕ,q,c(f,r) in r and log r can be obtained as special cases. [ABSTRACT FROM AUTHOR]

With the development of power switches and processor performance in recent years, the control frequency of inverters has been significantly improved. However, limited by technology and price, the sensor sampling frequency in large-scale industrial applications is much lower than the inverter control frequency that can be realized. This frequency mismatch limits the performance improvement of the inverter. In this article, the current and voltage at the non-sampling time are reconstructed using the current prediction control principle and the input observer theory, allowing a single-phase inverter to implement multi-sampling rate control with a low sampling frequency and high control frequency. In addition, an improved adaptive controller is designed to solve the effect of incorrect model parameters, which realizes adaptive control when the sampling frequency and control frequency are mismatched. Finally, the effectiveness of the method is verified through a simulation and experiments. The proposed method can solve the problem of high-speed switching for inverters under low-sampling-frequency conditions, improving the inverter's adaptive performance and robustness. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information and power transfer (SWIPT) technology can effectively extend the lifecycle of energy-constrained networks. In order to improve the energy harvesting (EH) efficiency and network performance in secure SWIPT networks, this paper studies the resource allocation problem based on the quantitative EH mechanism in the secure SWIPT network. Based on a quantitative EH mechanism and nonlinear EH model, a quantified power-splitting (QPS) receiver architecture is designed. This architecture is applied in the multiuser multi-input single-output secure SWIPT network. With the goal of maximizing the network throughput, the optimization problem model is established under the conditions of meeting the legal user's signal-to-interference-plus-noise ratio (SINR), EH requirements, the total transmit power of the base station, and the security SINR threshold constraints. Due to the coupling of variables, the problem is a nonconvex optimization problem. To deal with the nonconvex optimization problem, a hierarchical optimization method is adopted. Firstly, an optimization algorithm based on the optimal received power of EH circuit is proposed, and a power mapping table is constructed through the optimization algorithm, from which the optimal power ratio to meet the user's EH requirements is obtained; then, the nonconvex problem is transformed into a convex problem by using variable substitution, semidefinite relaxation, dichotomous optimization, etc. The simulation results show that compared with the power splitting receiver architecture, the input power threshold range of the QPS receiver architecture is larger, which can avoid the EH circuit falling into the saturated working area and maintain high network throughput. [ABSTRACT FROM AUTHOR]

Linear transformation models have been one type of models commonly used for regression analysis of failure time data partly due to their flexibility. More recently they have been generalised to the case where there may exist a cured subgroup or the censoring may be informative. In this paper, we consider a more complicated and general situation where both a cured subgroup and informative censoring, or more specifically informative interval censoring, exist. As pointed out in the literature, the analysis that fails to take into account either the cured subgroup or the informative censoring can yield biased estimation or misleading conclusions. For the problem, a three-component mixture cure model is presented and we develop a two-step estimation procedure with the use of B-splines to approximate unknown functions. The proposed approach is quite flexible and can be easily implemented. Also the proposed estimators of regression parameters are shown to be consistent and asymptotically normal. An extensive simulation study is conducted and suggests that the method works well for practical situations. Furthermore a real application is provided to illustrate the proposed methodology. [ABSTRACT FROM AUTHOR]

Background: Diffusion‐weighted imaging (DWI) has demonstrated great potential in predicting the expression of tumor cell proliferation and apoptosis indexes. Purpose: To evaluate the impact of four region of interest (ROI) methods on interobserver variability and apparent diffusion coefficient (ADC) values and to examine the correlation of ADC values with Ki‐67, Bcl‐2, and P53 labeling indexes (LIs) in a murine model of fibrosarcoma. Study Type: Prospective, animal model. Animal Model: A total of 22 female BALB/c mice bearing intramuscular fibrosarcoma xenografts. Field Strength/Sequence: A 3.0 T/T1‐weighted fast spin‐echo (FSE), T2‐weighted fast relaxation fast spin‐echo, and DWI PROPELLER FSE sequences. Assessment: Four radiologists measured ADC values using four ROI methods (oval, freehand, small‐sample, and whole‐volume). Immunohistochemical assessment of Ki‐67, Bcl‐2, and P53 LIs was performed. Statistical Tests: Interclass correlation coefficient (ICC), one‐way analysis of variance followed by LSD‐t post hoc analysis, and Pearson correlation test were performed. The statistical threshold was defined as a P‐value of <0.05. Results: All ROI methods for ADC measurements showed excellent interobserver agreement (ICC range, 0.832–0.986). The ADC values demonstrated significant differences among the four ROI methods. The ADC values for oval, freehand, small‐sample, and whole‐volume ROI methods showed a moderately negative correlation with Ki‐67 (r = −0.623; r = −0.629; r = −0.642, and r = −0.431) and Bcl‐2 (r = −0.590; r = −0.597; r = −0.659, and r = −0.425) LIs, but no correlation with P53 LI (r = 0.364, P = 0.104; r = 0.350, P = 0.120; r = 0.379, P = 0.091; r = 0.390, P = 0.080). Data Conclusion: The ADC value can be used to evaluate cell proliferation and apoptosis indexes in a murine model of fibrosarcoma, employing the small‐sample ROI as a reliable method. Evidence Level: 1 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Topology optimization subjected to stochastic excitations is usually computationally expensive. This work addresses this challenge by first transforming stochastic response and sensitivity analysis problems at each iteration into a series of frequency response analysis problems, and then an adaptive hybrid expansion method is employed to compute the displacement and adjoint vectors. The proposed method has two features: (1) the derivatives of the eigenpairs are not involved when computing the sensitivities of the responses, thus no special treatment is needed when repeated eigenfrequencies are present; (2) the numbers of lower-order eigenvectors and basis vectors that need to be computed can be determined adaptively according to the given accuracy. The accuracy and efficiency of the proposed method as well as the effect of the excitation frequency on the optimum designs are demonstrated by three numerical examples. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to study the landing performance of the Mars lander considering uncertain landing conditions under two landing modes. Design/methodology/approach: A dynamics analysis model for the legged Mars lander is established for landing simulation, where the nonlinear large-deformation flexible buffer rods are equivalently modeled with a rigid-body mechanism with external forces and movement limit. Sensitivities of the landing stability to various landing conditions are analyzed using the Quasi–Monte-Carlo-based Sobol' method and computer-aided landing simulations. Moreover, based on the results of sensitivity analysis, sensitive parameters are selected for estimating the safe boundaries for stability indices of rotation and clearance. Findings: It can be concluded from this study that the lander has excellent ability against overturning. The shutdown-before-touchdown strategy helps to maintain than landing pose, and the shutdown-at-touchdown strategy helps to prevent the nozzle from colliding with the surface of Mars. Practical implications: This study provides a theoretical reference to choose the better landing strategies for Mars landers considering uncertain landing conditions. Originality/value: A parameterized dynamics Mars lander model and a simplification method are proposed to simulate the landing on Mars. Uncertain landing conditions are parameterized and considered in the dynamics model. Sensitivity analysis and safe boundary methods are used to compare the landing performances with two landing strategies. [ABSTRACT FROM AUTHOR]

Interval-censored failure time and panel count data, which frequently arise in medical studies and social sciences, are two types of important incomplete data. Although methods for their joint analysis have been available in the literature, they did not consider the observation process, which may depend on the failure time and/or panel count of interest. This study considers a three-component joint model to analyze interval-censored failure time, panel counts, and the observation process within a unique framework. Gamma and distribution-free frailties are introduced to jointly model the interdependency among the interval-censored data, panel count data, and the observation process. We propose a sieve maximum likelihood approach coupled with Bernstein polynomial approximation to estimate the unknown parameters and baseline hazard function. The asymptotic properties of the resulting estimators are established. An extensive simulation study suggests that the proposed procedure works well for practical situations. An application of the method to a real-life dataset collected from a cardiac allograft vasculopathy study is presented. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the effect of prepartum diets that differ in energy density on beef cow energy metabolites and birth weight, immunity and antioxidative capabilities of neonatal calves. On d 0 (approximately 45 d before calving), 90 multiparous Angus cows (BW = 510 ± 16 kg) were randomly allocated into 1 of 9 drylot pens (10 cows/pen). Each pen was randomly assigned to a treatment condition (three pens/treatment), the cows in each treatment were assigned randomly to receive a high-energy (HE) density diet (NEm = 1.67 Mcal/kg of DM), medium-energy (ME) density diet (NEm = 1.53 Mcal/kg of DM), or low-energy (LE) density diet (NEm = 1.36 Mcal/kg of DM). Blood samples were collected − 45, − 21, − 14, and − 7 d from calving, and plasma concentrations of cortisol, glucose, total protein, β-hydroxybutyrate (BHBA), and nonesterified fatty acids (NEFAs) were measured. After calving, the birth weights, body height, body length, thoracic girth and umbilical girth of the calves in each group were recorded, and blood samples were collected for analysis of IgG, IL-2, IL-4, IL-6, total antioxidant capacity, superoxide dismutase, glutathione peroxidase, and maleic dialdehyde levels. The amounts of feed offered and orts were recorded for individual cows 4 d/wk. The results indicated that although dry matter intake (DMI) levels did not differ among the LE, ME, and or HE groups before parturition, the group that received the HE diet had higher plasma glucose concentrations and lower prepartum blood NEFA concentrations than the other groups. Birth weight, body height, thoracic girth, and levels of IL-2, cortisol, total antioxidant capacity, and superoxide dismutase were increased in calves of the HE group compared with those of the LE group. The plasma IL-4 and serum IgG concentrations tended to be decreased in the ME group compared with the HE group, and the ME group had lower maleic dialdehyde concentrations; maleic dialdehyde levels were significantly increased in the LE group compared with the HE group. Overall, these results indicate that feeding of a low-energy diet during the last 45 d before parturition has negative effects on the growth, immunity, and antioxidative capabilities of neonatal calves. Increasing maternal energy density during late gestation may be useful to improve the energy status of cows. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective optimization model for the motion synthesis of four-bar mechanisms considering the effects of revolute joint clearances. A geometric method is proposed to compute the maximum clearances-induced positioning and orientation errors. The proposed error modeling method is validated using a simple example, and the results reveal its advantages of high accuracy and fast computation compared with the widely used existing methods. A multi-objective optimization model is developed to design the four-bar mechanism with the best accuracy. The positioning and orientation errors are modeled separately and equally. Moreover, three constraints are included in the optimization to ensure that the synthesized mechanism is a compact crank-rocker or double-crank mechanism free from branch and order defects. A study case of synthesizing a four-bar mechanism passing through 6 motion points is investigated to illustrate the proposed method. Finally, conclusions and a brief discussion are given. [ABSTRACT FROM AUTHOR]

To investigate the value of the radiomic models for differentiating parasellar cavernous hemangiomas from meningiomas and to compare the classification performance with different MR sequences and classifiers. A total of 96 patients with parasellar tumors (40 cavernous hemangiomas and 56 meningiomas) were enrolled in this retrospective multiple-center study. Univariate and multivariate analyses were performed to identify the clinical factors and semantic features of MRI scans. Radiomics features were extracted from five MRI sequences using radiomics software. Three feature selection methods and six classifiers were evaluated in the training cohort to construct favorable radiomic machine-learning classifiers. The performance of different classifiers was evaluated using the AUC and compared to neuroradiologists. The detection rates of T1WI, T2WI, and CE-T1WI for parasellar cavernous hemangiomas and meningiomas were approximately 100%. In contrast, the ADC maps had the detection rate of 18/22 and 19/25, respectively, (AUC, 0.881) with 2.25 cm as the critical value diameter. Radiomics models with the SVM and KNN classifiers based on T2WI and ADC maps had favorable predictive performances (AUC > 0.90 and F-score value > 0.80). These models outperformed MRI model (AUC 0.805) and neuroradiologists (AUC, 0.756 and 0.545, respectively). Radiomic models based on T2WI and ADC and combined with SVM and KNN classifiers have the potential to be a viable method for differentiating parasellar hemangiomas from meningiomas. T2WI is more universally applicable than ADC values due to its higher detection rate for parasellar tumors. [ABSTRACT FROM AUTHOR]

This paper presents a geometrical alternative to estimate the accuracy of a deployable mechanism equipped on the Synthetic Aperture Radar (SAR) space satellite. The deployable mechanism is simplified into a planar mechanism, and the error space of the outer panel in its deployed state is modeled concerning multiple revolute joint clearances and link length tolerances. Compared with the existing methods, the advance of the proposed geometrical approach lies in that it gives expressions of the complete error mobility that the outer panel may have. After deducing the expressions, the final error space is visualized and evaluated numerically with discrete sampling points. Finally, based on the error space and the computed maximum errors, effects of tolerances on accuracy are studied and the optimal accuracy design of tolerances is obtained. The result reveals that, for the deployable mechanism discussed in this paper, effects of tolerances on the final accuracy can be eliminated without increasing the manufacturing cost. [ABSTRACT FROM AUTHOR]

Simple Summary: Characterization of the microbiota in livestock animals is of great interest for improving reproductive performances. Shifts in vaginal and uterine microbiota are well-studied, but the intestinal microbiota in ruminants during estrus is largely unknown. The intestinal microbiota of grazing Simmental cows undergoing estrus synchronization was studied in this work. The structure, composition, and function of the intestinal microbiota shifted during this process, and these shifts were mediated by reproductive hormones. To study shifts in the intestinal microbiota during estrus synchronization in ruminants, we characterized the intestinal microbiota in grazing Simmental cows and the possible mechanism that mediates this shift. Fourteen postpartum Simmental beef cows were synchronized beginning on day 0 (D0) with a controlled internal release device (CIDR), and cloprostenol was injected on D9 when the CIDR was withdrawn. Synchronization ended with timed artificial insemination on D12. Serum and rectal samples harvested on D0, D9, and D12 were analyzed to assess the reproductive hormones and microbiota. Reproductive hormones in the serum of the host were measured using enzyme-linked immunosorbent assay. The microbiota was characterized using 16S rRNA sequencing of the V3–V4 hypervariable region, alpha diversity and beta diversity analyses (principal coordinate analysis, PCoA), cladogram of the linear discriminant analysis effect size (LEfSe) analysis, and microbiota function analysis. Levels of the reproductive hormones, except gonadotropin-releasing hormone (p > 0.05), shifted among D0, D9, and D12 (p < 0.05). Decreased community diversity (Chao1 and ACE) was observed on D12 compared with D0 (p < 0.05). The beta diversity (PCoA) of the microbiota shifted markedly among D0, D9, and D12 (p < 0.05). The LEfSe analysis revealed shifts in the intestinal microbiota communities among D0, D9, and D12 (p < 0.05 and LDA cutoff >3.0). The KEGG pathway analysis showed that carbohydrate metabolism, genetic information and processing, the excretory system, cellular processes and signaling, immune system diseases, and the metabolism were altered (p < 0.05). Reproductive hormones (especially estradiol) were correlated with the alpha diversity indices, beta diversity indices, and an abundance of biomarkers of the shifting intestinal microbiota (p < 0.05). In conclusion, the structure, composition, and function of the intestinal microbiota were shifted during estrus synchronization in a grazing Simmental cow model, and these shifts were mediated by reproductive hormones. [ABSTRACT FROM AUTHOR]