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Two oxidative degradation impurities of sugammadex sodium have been successfully synthesized under stress conditions and isolated by preparative high performance liquid chromatography, which would be extremely difficult to prepare stochiometrically by conventional methods due to their structural complexity. Characteristic fragmentation pattern observed by mass spectrometry for sugammadex series compounds helped distinguish the two regioisomeric di-sulfoxide impurities. Confirmed by nuclear magnetic resonance analysis, Impurity I was identified as ortho-disulfoxide sugammadex and Impurity II as meta-disulfoxide sugammadex. It is the first time detailed structures of these two impurities are reported. Additionally, HPLC analysis also indicated the observance of these two impurities in long-term stored sugammadex sodium finished pharmaceutical product but absence in three pilot batches of sugammadex sodium drug substance which met ICH requirements. The compounded analysis technique has proven to be successful and reliable, and we hope that it could be well applied to structure identification for other sugammadex impurities and will be beneficial for other researchers focusing on this field.

Background The novel coronavirus disease 2019(COVID-19) caused by SARS-CoV-2 that belongs to betacoronaviruseis, and is an enveloped, single and positive-stranded RNA virus. In this study, we describe the production and characterization of four monoclonal antibodies (mAb) with neutralization activities. Methods Thirteen mAbs that identified positive were characterized by neutralization assays, binding affinities identification, and ELISA to evaluate the immunocompetence. The genes of neutralizing antibodies were sequenced and analyzed. Results All mAbs recognized two different epitopes respectively, including RBD and hFc, and the binding affinities are also different. Four of nine mAbs that can recognize the epitopes of RBD are conformation neutralizing antibodies that have high binding affinity and neutralization ability. Based on the sequencing, the mAbs are unique antibodies with specificity. Conclusions We characterized thirteen monoclonal antibodies, four of which are neutralizing antibodies and identified unique antibodies with specificity. The results highlight the promise of antibody-based therapeutics and provide the structural basis of rational vaccine design.

Rotating shaft–disk–blade (RSDB) system is one of the most important parts of turbomachinery, such as aero-engine, gas turbine and power plant. The coupling vibration of RSDB system with blade crack is vital for the blade health monitoring and crack detection of rotating blade. This study aims at addressing the dynamic modeling and steady-state coupling vibration mechanism of RSDB system with blade crack. First and foremost, on the basis of the stress state at crack section, an improved analytical breathing crack model (modified stress-based breathing crack model, MSBCM) for rotating blade is proposed. The validity of the proposed breathing crack model is verified by comparing the results obtained by MSBCM, finite element contact crack model and conventional analytical crack models. The comparative results suggest that MSBCM is of high fidelity and behaves best among the analytical crack models. Subsequently, a comprehensive dynamic model of the coupling vibration for RSDB system with blade crack is formulated on the basis of continuum beam theory and Lagrange equation. The shaft bending, shaft torsion, blade bending and blade radial deformation are comprehensively considered in this model. The validity of the proposed dynamic model is verified through comparison with finite element simulation and experimentation results. By introducing the proposed MSBCM, the dynamic coupling vibration model of the RSDB system with blade crack is formulated. At last, the steady-state coupling vibration mechanism of two typical structures for RSDB system is comprehensively investigated. It is suggested that the shaft torsional vibration is much more sensitive to blade crack than the shaft bending vibration be, which indicates that the vibration features of shaft torsional vibration may offer indicators for the presence of blade crack.

A novel and scalable process is developed for the industrial synthesis of vadadustat. The four-step process is one step shorter compared to the reported routes with an increase in total yield to 49...

This study aims at investigating the nonlinear dynamic behavior of rotating blade with transverse crack. A novel nonlinear rotating cracked blade model (NRCBM), which contains the spinning softening, centrifugal stiffening, Coriolis force, and crack closing effects, is developed based on continuous beam theory and strain energy release rate method. The rotating blade is considered as a cantilever beam fixed on the rigid hub with high rotating speed, and the crack is deemed to be open and close continuously in a trigonometric function way with the blade vibration. It is verified by the comparison with a finite element-based contact crack model and bilinear model that the proposed NRCBM can well capture the dynamic characteristics of the rotating blade with breathing crack. The dynamic behavior of rotating cracked blade is then investigated with NRCBM, and the nonlinear damage indicator (NDI) is introduced to characterize the non-linearity caused by blade crack. The results show that NDI is a distinguishable indicator for the severity level estimation of the crack in rotating blade. It is found that severe crack (i.e., a closer crack position to blade root as well as larger crack depth) is expected to heavily reduce the stiffness of rotating blade and apparently result in a lower resonant frequency. Meanwhile, the super-harmonic resonances are verified to be distinguishable indicators for diagnosing the crack existence, and the third-order super-harmonic resonances can serve as an indicator for the presence of severe crack since it only distinctly appears when the crack is severe.

Blade tip timing (BTT) is a noncontact blade vibration measurement method for rotating blade condition monitoring. However, it is difficult to install a once-per-revolution (OPR) probe due to the internal environment limitation of an engine. To solve this problem, an OPR-free BTT method is proposed in this article. Compared with the existing OPR-free methods that are based on blade displacement, this method is based on blade spacing change (BSC). In addition, a probe layout selection method based on minimum redundancy linear array (MRLA) is introduced to reduce the redundancy of the acquired signal. Simulations are conducted to prove that the proposed probe layout selection method has a stronger signal extraction capability and better robustness. The experiment is conducted to show that BSC is an alternative way for rotating blade condition monitoring and the technical route of this article is feasible.

Blade health monitoring (BHM) is an important technology to ensure safe operation of turbine machinery. The blade tip timing (BTT) method is a non-contact approach of vibration monitoring that is widely used for aero-engines. A BTT signal can be characterized as nonuniform and sub-Nyquist sampled (i.e., under-sampled). For nonuniform sampling, the least squares (LS) fitting method has long been used to reconstruct the spectrum. However, the under-sampling of the BTT signal causes the spectrum obtained by LS fitting aliasing. The iterative reweighted LS periodogram (IRLSP) can eliminate the aliasing caused by sub-Nyquist and nonuniform sampling. This method weakens the frequency aliasing through the method of reweighted iteration, but the consequence of this operation is that the amount of calculation is greatly increased. Thus, we propose an adaptive iterative approach (AIA) based on the IRLSP that combines a priori information of the blade. The main contribution of this method is to improve the computational efficiency for processing the BTT signal and the effect of anti-aliasing. These two points mean that this method is expected to become a real-time blade vibration monitoring method. We combined a finite element model with modal testing to perform simulations and verify the improvement with AIA. A large number of experiments were also performed to verify the effectiveness of our approach for BHM.

Background Antegrade cerebral perfusion (ACP), including unilateral and bilateral, is most commonly used for cerebral protection in aortic surgery. There is still no consensus on the superiority of the two methods. Our research aimed to investigate the clinical effects of u-ACP and b-ACP. Methods 321 of 356 patients with type A aortic dissection were studied retrospectively. 124 patients (38.6%) received u-ACP, and 197 patients (61.4%) received b-ACP. We compared the incidence of postoperative neurological complications and other collected data between two groups. Besides, we also analyzed perioperative variables to find the potential associated factors for neurological dysfunction (ND). Results For u-ACP group, 54 patients (43.5%) had postoperative neurological complications, including 22 patients (17.7%) with permanent neurologic dysfunction (PND) and 32 patients (25.8%) with temporary neurologic dysfunction (TND). For b-ACP group, 47 patients (23.8%) experienced postoperative neurological complications, including 16 patients (8.1%) of PND and 31 patients (15.7%) of TND. The incidence of PND and TND were significantly different between two groups along with shorter CPB time (p = 0.016), higher nasopharyngeal temperature (p≦0.000), shorter ventilation time (p = 0.018), and lower incidence of hypoxia (p = 0.022). Furthermore, multivariate stepwise logistic regression analysis confirmed that preoperative neurological dysfunction (OR = 1.20, p = 0.028), CPB duration (OR = 3.21, p = 0.002), and type of cerebral perfusion (OR = 1.48, p = 0.017) were strongly associated with postoperative ND. Conclusions In our study, it was observed that b-ACP procedure exhibited shorter CPB time, milder hypothermia, shorter ventilation time, lower incidence of postoperative hypoxia, and neurological dysfunction compared to u-ACP. Meanwhile, the incidence of ND was independently associated with three factors: preoperative neurological dysfunction, CPB time, and type of cerebral perfusion.

Blade tip timing (BTT) is an effective noncontact measurement technology for rotating blade health monitoring. However, due to the mismatching between the high-speed rotation and the limited amount of probes, the signal collected from the BTT system is severely undersampled, which induces the difficulty in feature extraction. Multiple signal classification (MUSIC) has the potential to overcome the undersampled problem once the probes are properly placed. Whereas, if traditional MUSIC is directly used in BTT, the accuracy of frequency identification cannot be high enough and the identified number of frequency components is also severely restrained. To address these two problems, an improved MUSIC is proposed as an alternative methodology to extract the blade vibration frequency for BTT. Based on the orthogonality of the signal subspace and the noise subspace from undersampled signal, the presented method can effectively identify the vibration frequency components from the undersampled signal of BTT.

Vibration signal analysis has become one of the important methods for machinery fault diagnosis. The extraction of weak fault features from vibration signals with heavy background noise remains a challenging problem. In this article, we first introduce the idea of algorithm-aware sparsity-assisted methods for fault feature enhancement, which extends model-aware sparsity-assisted fault diagnosis and allows a more flexible and convenient algorithm design. In the framework of algorithm-aware methods, we define the generalized structured shrinkage operators and construct the generalized structured shrinkage algorithm (GSSA) to overcome the disadvantages of $l_{1} $ -norm regularization-based fault feature enhancement methods. We then perform a series of simulation studies and two experimental cases to verify the effectiveness of the proposed method. In addition, comparisons with model-aware methods, including basis pursuit denoising and windowed-group-lasso, and fast kurtogram further verify the advantages of GSSA for weak fault feature enhancement.

Blade tip timing (BTT) methods have been increasingly implemented for blade health monitoring (BHM). However, there are two drawbacks of current signal analysis methods preventing them from applying to online monitoring: first, current online monitoring requires the manual judgment of the resonance region, which is time-consuming. Second, existing BTT resonance signal analysis methods are not suitable for online monitoring. The spectral-analysis-based method presents spectral aliasing, while the computational complexity of the sparse-based method is usually high. In this article, we propose an adaptive online BHM method that includes two steps: automatic resonance region recognition and parameters identification in resonance area. For the former step, we demonstrate different methods for synchronous and asynchronous resonances, use the cross correlation to judge the occurrence of synchronous vibration, and use the linear estimation to determine the appearance of asynchronous vibration. For the latter step, an iterative adaptive least-squares periodogram is adopted for its tradeoff between spectral aliasing and computational complexity. The effectiveness of the above steps is first verified using different simulation data separately. Then, the laboratory data are used to test the effectiveness of the whole method. Finally, the online monitoring function of the proposed method is verified by the engineering data with both synchronous and asynchronous resonances.

Two unknown solution degradants were found during the dissolution testing in 0.1-M HCl for olmesartan medoxomil (OLM) tablets. The structure of the degradants was identified and characterized by liquid chromatography-ultraviolet (LC-UV), liquid chromatography with tandem mass spectrometry (LC-MS/MS), and nuclear magnetic resonance (NMR) and demonstrated to be cyclization of tetrazole and benzene in the olmesartan (OL) and OLM structures. A series of studies including stress studies, simulation studies, and mechanism-based studies were performed to reveal the potential mechanisms that lead to the formation of the unknown degradants. The study results demonstrated that the degradation was catalyzed with radicals that originated from the metal ions leached from the inner surface of high-performance liquid chromatography (HPLC) glass vials with dissolved oxygen under acidic condition. Prerinsing the glass vials with acidic solution dissolved with EDTA can effectively avoid the generation of such oxidative impurities. The present work provides new insights into the understanding of degradation pathways of OLM, which might support the development of OLM tablets.

Quality control is very important during the development of 3-valent (16/18/58), 9-valent (6/11/16/18/31/33/45/52/58), and 15-valent human papillomavirus (HPV) vaccines (6/11/16/18/31/33/35/39/45/52/56/58/59/68). All 3-valent, 9-valent, and 15-valent HPV vaccines contain the HPV16 antigen; therefore, a detection method that can specifically identify HPV16 in vaccines is urgently required. This study aimed to develop and characterize monoclonal antibodies to assemble a highly specific HPV16 detection kit. The HPV16 L1 pentameric protein developed as an immunogen was used to prepare monoclonal antibodies. From the pool of prepared monoclonal antibodies, we selected 4G12 and 5A6 to screen and evaluate their subtypes, specificity, neutralizing activity, serum competition, binding affinity, and gene sequencing. After these characterizations, an enzyme-linked immunosorbent assay kit for these monoclonal antibodies was developed, and excellent quality was demonstrated in the assessment of linearity, repeatability, and specificity. The developed detection kit has great potential for wide use in clinical testing and quality control in vaccine production processes.

Currently, human papillomavirus (HPV) vaccines are in short supply, so the development of HPV vaccines has a broad market prospect. The 3-, 9-, and 15-valent HPV vaccines developed by ourselves all contain HPV58-derived antigen components. It is important to detect HPV 58 during vaccine production. Here, we introduced a development process of HPV58 type-specific antibodies and a detection kit. Briefly, HPV58 L1-Virus Like Particles (VLPs) were used as antigens to immunize mice, followed by extraction of the ascites to prepare hybridoma cells. After culturing, the supernatants containing secreted antibodies were harvested, purified, and screened to obtain monoclonal antibodies (mAbs). In the pool of attained monoclonal antibodies, we selected 2F7 and 2G7 to evaluate their subtypes, specificity, neutralizing activity, serum competition, binding affinity and gene sequencing. Finally, an enzyme-linked immunosorbent assay (ELISA) detection kit was assembled with 2F7 and 2G7 mAbs which possessed high specificity to HPV58 L1-VLPs. The detection kit developed by 2F7 and 2G7 could be adopted to specifically detect HPV58 L1 protein with good linearity and detection range, which could be widely used in clinical testing and quality control in the production of HPV vaccines. Abbreviations: BSA: Bovine serum albumin; CDRs: Complementarity-determining regions; CV: Coefficient of variation; DTT: Dithiothreitol; ELISA: Enzyme-linked immunosorbent assay; HAT: Hypoxanthine-aminopterin-thymidine; HPV: Human Papillomavirus; IC50: 50% inhibition rate; IC90: 90% inhibition rate; mAbs: Monoclonal antibodies; VLP: Virus-like particle

Rotating blade is one of the most important components for turbomachinery. Blade crack is one of the most common and dangerous failure modes for rotating blade. Therefore, the fault mechanism and feature extraction of blade crack are vital for the safety assurance of turbomachinery. This study is aimed at the nonlinear dynamic model of rotating blade with transverse crack and the prior feature extraction of blade crack faults based on the vibration responses. First and foremost, a high-fidelity breathing crack model (HFBCM) for rotating blade is proposed on the basis of criterion for stress states at crack section. Since HFBCM is physically deduced from the perspective of energy dissipation and the coupling between centrifugal stress and bending stress is considered, the physical interpretability and the accuracy of the crack model are enhanced comparing with conventional models. The validity of the proposed HFBCM is verified through the comparison study among HFBCM, conventional crack models, and finite element-based contact crack model (FECCM). It is suggested that HFBCM behaves best among the analytical models and matches well with FECCM. With the proposed HFBCM, the nonlinear vibration responses are investigated, and four types of blade crack detection indicators for rotating blade and their quantification method are presented. The numerical study manifests that all these indicators can well characterize the occurrence and severity of crack faults for rotating blade. It is indicated that these indicators can serve as the crack-monitoring indexes.

A novel six-step synthesis of 7,8-difluoro-6,11-dihydrodibenzo[b,e]thiepin-11-ol (1) is described. Starting with 3,4-difloro-2-methylbenzoic acid and using diphenyl disulfide as an ideal sulfur sou...

Blade Tip Timing (BTT) method is increasingly implemented for rotating blade health monitoring for its non-contact property. However, the BTT data is usually highly undersampled as only a few sensors could be installed on the case. Due to the limited number of sensors installed, the arrangement can have a significant impact on BTT data quality. Different from the exhaustive method used in previous researches, in this paper, a mathematical model guided by optimizing objective is proposed for sensor configuration. Considering the dimensional characteristics of the sampling matrix, this paper no longer uses a single matrix coherence value as the optimization target, but adopts the Equiangular tight frame matrix as the goal of the whole sampling matrix. Moreover, this paper first considers the physical constraints of the actual installation and modal prior on the sensor arrangement. The physical constraints fused equiangular tight frame method is then solved by an alternating minimization approach. In addition, considering the disadvantages of the previous vibration parameter identification algorithms in terms of amplitude recovery and noise filtering, an iterative reweighted L1-norm based parameter identification method is applied to obtain the vibration parameters from the highly undersampled BTT data with better amplitude reconstruction accuracy. Both the simulation and experiment results are given to verify the effectiveness of the developed methods.