Pair-switching rerandomization.

Rerandomization discards assignments with covariates unbalanced in the treatment and control groups to improve estimation and inference efficiency. However, the acceptance-rejection sampling method used in rerandomization is computationally inefficient. As a result, it is time-consuming for rerandomization to draw numerous independent assignments, which are necessary for performing Fisher randomization tests and constructing randomization-based confidence intervals. To address this problem, we propose a pair-switching rerandomization (PSRR) method to draw balanced assignments efficiently. We obtain the unbiasedness and variance reduction of the difference-in-means estimator and show that the Fisher randomization tests are valid under PSRR. Moreover, we propose an exact approach to invert Fisher randomization tests to confidence intervals, which is faster than the existing methods. In addition, our method is applicable to both nonsequentially and sequentially randomized experiments. We conduct comprehensive simulation studies to compare the finite-sample performance of the proposed method with that of classical rerandomization. Simulation results indicate that PSRR leads to comparable power of Fisher randomization tests and is 3-23 times faster than classical rerandomization. Finally, we apply the PSRR method to analyze two clinical trial datasets, both of which demonstrate the advantages of our method.

Regression-based multiple treatment effect estimation under covariate-adaptive randomization.

Covariate-adaptive randomization methods are widely used in clinical trials to balance baseline covariates. Recent studies have shown the validity of using regression-based estimators for treatment effects without imposing functional form requirements on the true data generation model. These studies have had limitations in certain scenarios; for example, in the case of multiple treatment groups, these studies did not consider additional covariates or assumed that the allocation ratios were the same across strata. To address these limitations, we develop a stratum-common estimator and a stratum-specific estimator under multiple treatments. We derive the asymptotic behaviors of these estimators and propose consistent nonparametric estimators for asymptotic variances. To determine their efficiency, we compare the estimators with the stratified difference-in-means estimator as the benchmark. We find that the stratum-specific estimator guarantees efficiency gains, regardless of whether the allocation ratios across strata are the same or different. Our conclusions were also validated by simulation studies and a real clinical trial example.

Plastic side flow and elastic recovery influences on optical diffraction effect of diamond turning: theoretical simulation and experimental verification.

Spherical/aspherical mirrors are widely used in optical systems and imaging systems, but their reflectivity is affected by the surface roughness. In this study, the effects of plastic side flow and elastic recovery on the diffraction phenomenon and reflectivity are analyzed systematically. The energy ratio of an ultra-precision turning surface is calculated by rigorous coupled-wave method, the influence of aberration on diffraction efficiency is considered in combination with the specific structural parameters of spherical/aspherical surface, and the appropriate measuring beam diameter is selected. Through predicted results and experimental observations, it can be found that with the increase of plastic side flow height, the energy ratio of zero-order diffracted light reduces, the brightness weakens, and the diffraction light spots become more obvious. This is because large plastic side flow height leads to more complex three-dimensional surface topography and great roughness P-V value. The influence of elastic recovery on the reflectivity is different from that of plastic side flow. As the elastic recovery increases, the roughness P-V value lessens. As a result, the energy ratio of zero-order diffracted light enlarges, and the brightness strengthens. This paper provides a theoretical basis for machining of spherical/aspheric mirrors with high reflectivity.

Influence of cutting parameters on system vibration and optical performance of diamond turned optics.

In this paper the influence of vibration on reflectivity is systematically analyzed. A three-dimensional topography model of a machined surface considering vibration is established first. Based on the three-dimensional morphology model, the reflectivity of a diamond turned surface is calculated by a rigorous coupled wave method. The influences of cutting parameters on the diffraction effect of a diamond turned surface are discussed. The predicted and experimental results reveal that as the vibration intensifies with an increase in cutting depth and feed rate, the peak-valley (PV) roughness of the machined surface increases, which yields an increasing diffraction effect, i.e., resulting in a decrease in reflectivity. When the spindle speed is low, the tool and workpiece have a small sliding velocity, causing a great deal of friction, which amplifies the deformation of the workpiece surface. In this case, the PV value of the machined surface roughness is large, leading to a greater diffraction effect and bad reflectivity. With the increment of spindle rotation speed, the friction is relieved quickly, but the vibration is intensified, which produces increasing reflectivity. When the spindle speed is set to about 1200r/min, the reflectivity reaches the maximum value. When the spindle speed is larger than 1200r/min, the increase of vibration is dominant, resulting in a gradual increase in PV surface roughness and a decrease in reflectivity.

How to accurately preoperative screen nipple-sparing mastectomy candidate-a nomogram for predicting nipple-areola complex involvement risk in breast cancer patients.

BACKGROUND: Nipple-sparing mastectomy (NSM) offers superior cosmetic outcomes and has been gaining wide acceptance. It has always been difficult to objectively quantify the risk of nipple-areola complex involvement (NACi). The goal was to develop a prediction model for clinical application. METHODS: Patients who had a total mastectomy (TM) between January 2016 and January 2020 at a single institute formed the development cohort (n = 578) and those who had NSM + immediate breast reconstruction (IBR) between January 2020 and January 2021 formed the validation cohort (n = 112). The prediction model was developed using univariate and multivariate logistic regression studies. Based on NACi risk variables identified in the development cohort, a nomogram was created and evaluated in the validation cohort. Meanwhile, stratified analysis was performed based on the model's risk levels and was combined with intraoperative frozen pathology (IFP) to optimize the model. RESULTS: Tumor central location, clinical tumor size (CTS) > 4.0 cm, tumor-nipple distance (TND) ≤ 1.0 cm, clinical nodal status positive (cN +), and KI-67 ≥ 20% were revealed to be good predictive indicators for NACi. A nomogram based on these major clinicopathologic variables was employed to quantify preoperative NACi risk. The accuracy was verified internally and externally. The diagnostic accuracy of IFP was 92.9%, sensitivity was 64.3%, and specificity was 96.9% in the validation group. Stratified analysis was then performed based on model risk. The diagnostic accuracy rates of IFP and NACiPM in low-risk, intermediate-risk, and high-risk respectively were 96.0%, 93.3%, 83.9%, 61.3%, 66.7%, and 83.3%. CONCLUSION: We created a visual nomogram to predict NACi risk in breast cancer patients. The NACiPM can be used to distinguish the low, intermediate, and high risk of NAC before surgery. Combined with IFP, we can develop a decision-making system for the implementation of NSM.

Regression analysis for covariate-adaptive randomization: A robust and efficient inference perspective.

Linear regression is arguably the most fundamental statistical model; however, the validity of its use in randomized clinical trials, despite being common practice, has never been crystal clear, particularly when stratified or covariate-adaptive randomization is used. In this article, we investigate several of the most intuitive and commonly used regression models for estimating and inferring the treatment effect in randomized clinical trials. By allowing the regression model to be arbitrarily misspecified, we demonstrate that all these regression-based estimators robustly estimate the treatment effect, albeit with possibly different efficiency. We also propose consistent non-parametric variance estimators and compare their performances to those of the model-based variance estimators that are readily available in standard statistical software. Based on the results and taking into account both theoretical efficiency and practical feasibility, we make recommendations for the effective use of regression under various scenarios. For equal allocation, it suffices to use the regression adjustment for the stratum covariates and additional baseline covariates, if available, with the usual ordinary-least-squares variance estimator. For unequal allocation, regression with treatment-by-covariate interactions should be used, together with our proposed variance estimators. These recommendations apply to simple and stratified randomization, and minimization, among others. We hope this work helps to clarify and promote the usage of regression in randomized clinical trials.

Bacillus strains improve growth performance via enhancing digestive function and anti-disease ability in young and weaning rex rabbits.

Numerous studies have shown that probiotic Bacillus could promote growth and enhance anti-disease ability in animal. In present study, the mixture of three Bacillus strains, which were isolated from rex rabbits and showed high cellulose, protease, and amylase activities, was added into the diet for investigating its effects on young and weaning rex rabbits. For experiment 1, 40 young rex rabbits (9 weeks old) were randomly divided into four groups and fed with diets containing 0 (NC), 1.0 × 105 cfu/g (LC), 1.0 × 106 cfu/g (MC), and 1.0 × 107 cfu/g (HC) Bacillus strains for 4 weeks. For experiment 2, 80 weaning rex rabbits (5 weeks old) were randomly divided into four groups and fed with diet containing 0 (control), 1.0 × 105 cfu/g (T-1), 1.0 × 106 cfu/g (T-2), and 1.0 × 107 cfu/g (T-3) Bacillus strains for 8 weeks. The results showed that Bacillus strains at a dose of 1.0 × 106 cfu/g significantly enhanced growth performance, increased immune organ indexes, improved serum biochemical parameters, and heightened antioxidant capacity. It also markedly improved the intestinal microbiota by increasing Lactobacillus spp., Bacillus spp. counts, and decreased Escherichia coli count. In addition, the Bacillus mixture raised the concentrations of acetic acid, propionic acid, and butyric acid as well as protease, amylase, and cellulase activities of young and weaning rex rabbits. Moreover, for weaning rex rabbits, the inclusion of Bacillus strains also upregulated the abundance of cellulolytic bacteria and improved intestinal morphology. Therefore, our results indicated that Bacillus strains could facilitate the growth of young and weaning rex rabbits by improving digestive function and anti-disease ability. KEY POINTS: • Bacillus with high extracellular enzyme activity were isolated from rex rabbits. • Bacillus could improve growth performance of young and weaning rex rabbits. • The digestive function of young and weaning rex rabbits could be improved by Bacillus.

Lasso adjustments of treatment effect estimates in randomized experiments.

We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large. Investigators often use linear multivariate regression to analyze randomized experiments instead of simply reporting the difference of means between treatment and control groups. Their aim is to reduce the variance of the estimated treatment effect by adjusting for covariates. If there are a large number of covariates relative to the number of observations, regression may perform poorly because of overfitting. In such cases, the least absolute shrinkage and selection operator (Lasso) may be helpful. We study the resulting Lasso-based treatment effect estimator under the Neyman-Rubin model of randomized experiments. We present theoretical conditions that guarantee that the estimator is more efficient than the simple difference-of-means estimator, and we provide a conservative estimator of the asymptotic variance, which can yield tighter confidence intervals than the difference-of-means estimator. Simulation and data examples show that Lasso-based adjustment can be advantageous even when the number of covariates is less than the number of observations. Specifically, a variant using Lasso for selection and ordinary least squares (OLS) for estimation performs particularly well, and it chooses a smoothing parameter based on combined performance of Lasso and OLS.

A Rail Fault Diagnosis Method Based on Quartic C2 Hermite Improved Empirical Mode Decomposition Algorithm.

For compound fault detection of high-speed rail vibration signals, which presents a difficult problem, an early fault diagnosis method of an improved empirical mode decomposition (EMD) algorithm based on quartic C2 Hermite interpolation is presented. First, the quartic C2 Hermite interpolation improved EMD algorithm is used to decompose the original signal, and the intrinsic mode function (IMF) components are obtained. Second, singular value decomposition for the IMF components is performed to determine the principal components of the signal. Then, the signal is reconstructed and the kurtosis and approximate entropy values are calculated as the eigenvalues of fault diagnosis. Finally, fault diagnosis is executed based on the support vector machine (SVM). This method is applied for the fault diagnosis of high-speed rails, and experimental results show that the method presented in this paper is superior to the traditional EMD algorithm and greatly improves the accuracy of fault diagnosis.

Hair follicle development and related gene and protein expression of skins in Rex rabbits during the first 8 weeks of life.

OBJECTIVE: We aimed to observe hair follicle (HF) development in the dorsal skin and elucidate the expression patterns of genes and proteins related to skin and HF development in Rex rabbits from birth to 8 weeks of age. METHODS: Whole-skin samples were obtained from the backs of Rex rabbits at 0, 2, 4, 6, and 8 weeks of age, the morphological development of primary and secondary HFs was observed, and the gene transcript levels of insulin-like growth factor-I (IGF-I), epidermal growth factor (EGF), bone morphogenetic protein 2 (BMP2), transforming growth factor ß-1, 2, and 3 (TGFß-1, TGFß-2, and TGFß-3) were examined using quantitative real-time polymerase chain reaction (PCR). Additionally, Wnt family member 10b (Wnt10b) and ß-Catenin gene and protein expression were examined by quantitative real-time PCR and western blot, respectively. RESULTS: The results showed significant changes in the differentiation of primary and secondary HFs in Rex rabbits during their first 8 weeks of life. The IGF-I, EGF, TGFß-2, and TGFß-3 transcript levels in the rabbits were significantly lower at 2 weeks of age than at birth and gradually increased thereafter, while the BMP2 and TGFß-1 transcript levels at 2 weeks of age were significantly higher than those at birth and gradually decreased thereafter. ß-Catenin gene expression was also significantly affected by age, while the Wnt10b transcript level was not. However, the Wnt10b and ß-catenin protein expression levels were the lowest at 2 and 4 weeks of age. CONCLUSION: Our data showed that a series of changes in HFs in dorsal skin occurred during the first 8 weeks. Many genes, such as IGF-I, EGF, BMP2, TGFß-1, TGFß-2, TGFß-3, and ß-Catenin, participated in this process, and the related proteins Wnt10b and ß-Catenin in skin were also affected by age.

Inherent structure versus geometric metric for state space discretization.

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the microcluster level, the IS approach and root-mean-square deviation (RMSD)-based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the microclusters are similar. The discrepancy at the microcluster level leads to different macroclusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macrocluster level in terms of conformational features and kinetics.

Network representation of conformational transitions between hidden intermediates of Rd-apocytochrome b562.

The folding kinetics of Rd-apocytochrome b562 is two-state, but native-state hydrogen exchange experiments show that there are discrete partially unfolded (PUF) structures in equilibrium with the native state. These PUF structures are called hidden intermediates because they are not detected in kinetic experiments and they exist after the rate-limiting step. Structures of the mimics of hidden intermediates of Rd-apocytochrome b562 are resolved by NMR. Based upon their relative stability and structural features, the folding mechanism was proposed to follow a specific pathway (unfolded → rate-limiting transition state → PUF1 → PUF2 → native). Investigating the roles of equilibrium PUF structures in folding kinetics and their interrelationship not only deepens our understanding of the details of folding mechanism but also provides guides in protein design and prevention of misfolding. We performed molecular dynamics simulations starting from a hidden intermediate and the native state of Rd-apocytochrome b562 in explicit solvent, for a total of 37.18 µs mainly with Anton. We validated our simulations by detailed comparison with experimental data and other computations. We have verified that we sampled the post rate-limiting transition state region only. Markov state model was used to analyze the simulation results. We replace the specific pathway model with a network model. Transition-path theory was employed to calculate the net effective flux from the most unfolded state towards the most folded state in the network. The proposed sequential folding pathway via PUF1 then more stable, more native-like PUF2 is one of the routes in our network, but it is not dominant. The dominant path visits PUF2 without going through PUF1. There is also a route from PUF1 directly to the most folded state in the network without visiting PUF2. Our results indicate that the PUF states are not necessarily sequential in the folding. The major routes predicted in our network are testable by future experiments such as single molecule experiment.

Endothelial indoleamine 2,3-dioxygenase protects against development of pulmonary hypertension.

RATIONALE: A proliferative and apoptosis-resistant phenotype in pulmonary arterial smooth muscle cells (PASMCs) is key to pathologic vascular remodeling in pulmonary hypertension (PH). Expression of indoleamine-2,3-dioxygenase (IDO) by vascular endothelium is a newly identified vasomotor-regulatory mechanism also involved in molecular signaling cascades governing vascular smooth muscle cell (vSMC) plasticity. OBJECTIVES: To investigate the therapeutic potential of enhanced endothelial IDO in development of PH and its associated vascular remodeling. METHODS: We used loss and gain of function in vivo studies to establish the role and determine the therapeutic effect of endothelial IDO in hypoxia-induced PH in mice and monocrotaline-induced PH in rats. We also studied PASMC phenotype in an IDO-high in vivo and in vitro tissue microenvironment. MEASUREMENTS AND MAIN RESULTS: The endothelium was the primary site for endogenous IDO production within mouse lung, and the mice lacking this gene had exaggerated hypoxia-induced PH. Conversely, augmented pulmonary endothelial IDO expression, through a human IDO-encoding Sleeping Beauty (SB)-based nonviral gene-integrating approach, halted and attenuated the development of PH, right ventricular hypertrophy, and vascular remodeling in both preclinical models of PH. IDO derived from endothelial cells promoted apoptosis in PH-PASMCs through depolarization of mitochondrial transmembrane potential and down-regulated PH-PASMC proliferative/synthetic capacity through enhanced binding of myocardin to CArG box DNA sequences present within the promoters of vSMC differentiation-specific genes. CONCLUSIONS: Enhanced endothelial IDO ameliorates PH and its associated vascular structural remodeling through paracrine phenotypic modulation of PH-PASMCs toward a proapoptotic and less proliferative/synthetic state.

Incorporation of Zinc-Strontium Phosphate into Gallic Acid-Gelatin Composite Hydrogel with Multiple Biological Functions for Bone Tissue Regeneration.

Large bone defects resulting from fractures and diseases have become a significant medical concern, usually impeding spontaneous healing through the body's self-repair mechanism. Calcium phosphate (CaP) bioceramics are widely utilized for bone regeneration, owing to their exceptional biocompatibility and osteoconductivity. However, their bioactivities in repairing healing-impaired bone defects characterized by conditions such as ischemia and infection remain limited. Recently, an emerging bioceramics zinc-strontium phosphate (ZSP, Zn2Sr(PO4)2) has received increasing attention due to its remarkable antibacterial and angiogenic abilities, while its plausible biomedical utility on tissue regeneration is nonetheless few. In this study, gallic acid-grafted gelatin (GGA) with antioxidant properties was injected into hydrogels to scavenge reactive oxygen species and regulate bone microenvironment while simultaneously incorporating ZSP to form GGA-ZSP hydrogels. The GGA-ZSP hydrogel exhibits low swelling, and in vitro cell experiments have demonstrated its favorable biocompatibility, osteogenic induction potential, and ability to promote vascular regeneration. In an in vivo bone defect model, the GGA-ZSP hydrogel significantly enhanced the bone regeneration rates. This study demonstrated that the GGA-ZSP hydrogel has pretty environmentally friendly therapeutic effects in osteogenic differentiation and massive bone defect repair.

Research on the Method of Reducing Dynamic Cutting Force in Aspheric Machining.

With the rapid development of photoelectric communication and other fields, the demand for high-precision aspheric mirrors has been increasing. Predicting dynamic cutting forces is vital in selecting machining parameters and also affects the surface quality of the machined surface. This study comprehensively considers the effects of different cutting parameters and workpiece shape parameters on dynamic cutting force. The actual width of cut, depth of cut, and shear angle are modelled while considering the effects of vibration. A dynamic cutting-force model considering the aforementioned factors is then established. Using experimental results, the model accurately predicts the average value of dynamic cutting force under different parameters and the range of fluctuation of dynamic cutting force, with a controlled relative error of about 15%. The influence of workpiece shape and workpiece radial size on dynamic cutting force is also considered. The experimental results show that the greater the surface slope, the more dramatic the dynamic cutting force fluctuations. This lays the foundation for subsequent writing on vibration suppression interpolation algorithms. The influence of the radius of the tool tip on dynamic cutting forces leads to the conclusion that to achieve the goal of reducing the fluctuation of cutting forces, diamond tools with different parameters should be selected for different feed rates. Finally, a new interpolation-point planning algorithm is used to optimize the position of interpolation points in the machining process. This proves the reliability and practicability of the optimization algorithm. The results of this study are of great significance to the processing of high-reflectivity spherical/aspheric surfaces.

A Review of Ultrathin Piezoelectric Films.

Due to their high electromechanical coupling and energy density properties, ultrathin piezoelectric films have recently been intensively studied as key materials for the construction of miniaturized energy transducers, and in this paper we summarize the research progress. At the nanoscale, even a few atomic layers, ultrathin piezoelectric films have prominent shape anisotropic polarization, that is, in-plane polarization and out-of-plane polarization. In this review, we first introduce the in-plane and out-of-plane polarization mechanism, and then summarize the main ultrathin piezoelectric films studied at present. Secondly, we take perovskite, transition metal dichalcogenides, and Janus layers as examples to elaborate the existing scientific and engineering problems in the research of polarization, and their possible solutions. Finally, the application prospect of ultrathin piezoelectric films in miniaturized energy converters is summarized.

PEG-SH-GNPs-SAPNS@miR-29a delivery system promotes neural regeneration and recovery of motor function after spinal cord injury.

Spinal cord injury (SCI) is a serious disease characterized by hemorrhage, edema, local ischemia and hypoxia, inflammatory reaction, and degeneration of the injured spinal cord, which lacks effective clinical treatments. We design a PEG-SH-GNPs-SAPNS@miR-29a delivery system to repair impaired spinal cord by building a regenerative microenvironment for the recruitment of endogenous neural stem cells. The miR-29a, as an axonal regeneration-related miRNA that overexpression of miR-29a significantly inhibits the expression of PTEN and promotes axonal regeneration of the injured spinal cord. The gold nanoparticles and self-assembling peptide hydrogel composite scaffold (PEG-SH-GNPs-SAPNS@miR-29a delivery system) applied to deliver miR-29a, which recruit endogenous neural stem cells simultaneously. Sustained release of miR-29a and recruitment of endogenous neural stem cells give rise to favorable axonal regeneration and recovery of motor function after spinal cord injury. These findings suggest that the PEG-SH-GNPs-SAPNS@miR-29a delivery system may be an alternative strategy for the treatment of SCI.

Recurring Clear Cell Odontogenic Carcinoma Involving Vertebra and Pleura: A Case Report and Literature Review.

Clear cell odontogenic carcinoma is a rare malignancy, which is vary in behavior from indolent tumor to cases with frequent recurrence and rare metastasis. In this manuscript, we report a case of clear cell odontogenic carcinoma of right lower mandible with cervical lymph node metastasis in a 50-year-old female. The tumor recurred and metastasized to vertebra and pleura after adjuvant radiation and chemotherapy, and the patient died of the disease 29 months after diagnosis. Pathologically, the tumor was composed of epithelial nests dominated by clear cells with ameloblastoma-like pattern and biphasic pattern. The tumor cells showed strong positive for AE1/AE3, KRT19, KRT5/6, P63, focal positive for KRT7, and weak positive for MUC1. Molecularly, EWSR1::ATF1 gene fusion was identified. To our knowledge, this report describes the first case of metastasis of clear cell odontogenic carcinoma involving regional lymph nodes and distant pleural and vertebral areas, demonstrating an aggressive clinical course of clear cell odontogenic carcinoma.

A genome-wide association study of coat color in Chinese Rex rabbits.

Coat color is an important phenotypic characteristic of the domestic rabbit (Oryctolagus cuniculus) and has specific economic importance in the Rex rabbit industry. Coat color varies considerably among different populations of rabbits, and several causal genes for this variation have been thoroughly studied. Nevertheless, the candidate genes affecting coat color variation in Chinese Rex rabbits remained to be investigated. In this study, we collected blood samples from 250 Chinese Rex rabbits with six different coat colors. We performed genome sequencing using a restriction site-associated DNA sequencing approach. A total of 91,546 single nucleotide polymorphisms (SNPs), evenly distributed among 21 autosomes, were identified. Genome-wide association studies (GWAS) were performed using a mixed linear model, in which the individual polygenic effect was fitted as a random effect. We detected a total of 24 significant SNPs that were located within a genomic region on chromosome 4 (OCU4). After re-fitting the most significant SNP (OCU4:13,434,448, p = 1.31e-12) as a covariate, another near-significant SNP (OCU4:11,344,946, p = 7.03e-07) was still present. Hence, we conclude that the 2.1-Mb genomic region located between these two significant SNPs is significantly associated with coat color in Chinese Rex rabbits. The well-studied coat-color-associated agouti signaling protein (ASIP) gene is located within this region. Furthermore, low genetic differentiation was also observed among the six coat color varieties. In conclusion, our results confirmed that ASIP is a putative causal gene affecting coat color variation in Chinese Rex rabbits.