Bevacizumab-induced immune thrombocytopenia in an ovarian cancer patient with mixed connective tissue disease: case report and literature review

Drug-induced immune thrombocytopenia is an adverse reaction marked by accelerated destruction of blood platelets. In cancer therapy, thrombocytopenia has many other causes including bone marrow suppression induced by chemotherapeutic agents, infection, and progression of cancer; drug-induced thrombocytopenia can easily be misdiagnosed or overlooked. Here, we present a case of an ovarian cancer patient with a history of mixed connective tissue disease who underwent surgery followed by treatment with paclitaxel, cisplatin, and bevacizumab. The patient developed acute isolated thrombocytopenia after the sixth cycle. Serum antiplatelet antibody testing revealed antibodies against glycoprotein IIb. After we analyzed the whole therapeutic process of this patient, drug-induced immune thrombocytopenia was assumed, and bevacizumab was conjectured as the most probable drug. Thrombocytopenia was ultimately successfully managed using recombinant human thrombopoietin, prednisone, and recombinant human interleukin-11. We provide a summary of existing literature on immune thrombocytopenia induced by bevacizumab and discuss related mechanisms and triggers for drug-induced immune thrombocytopenia. The present case underscores the potential of bevacizumab to induce immune-mediated thrombocytopenia, emphasizing the need for heightened vigilance towards autoimmune diseases or an autoimmune-activated state as plausible triggers for rare drug-induced immune thrombocytopenia in cancer therapy

Arginine starvation impairs mitochondrial respiratory function in ASS1-deficient breast cancer cells.

Autophagy is the principal catabolic response to nutrient starvation and is necessary to clear dysfunctional or damaged organelles, but excessive autophagy can be cytotoxic or cytostatic and contributes to cell death. Depending on the abundance of enzymes involved in molecule biosynthesis, cells can be dependent on uptake of exogenous nutrients to provide these molecules. Argininosuccinate synthetase 1 (ASS1) is a key enzyme in arginine biosynthesis, and its abundance is reduced in many solid tumors, making them sensitive to external arginine depletion. We demonstrated that prolonged arginine starvation by exposure to ADI-PEG20 (pegylated arginine deiminase) induced autophagy-dependent death of ASS1-deficient breast cancer cells, because these cells are arginine auxotrophs (dependent on uptake of extracellular arginine). Indeed, these breast cancer cells died in culture when exposed to ADI-PEG20 or cultured in the absence of arginine. Arginine starvation induced mitochondrial oxidative stress, which impaired mitochondrial bioenergetics and integrity. Furthermore, arginine starvation killed breast cancer cells in vivo and in vitro only if they were autophagy-competent. Thus, a key mechanism underlying the lethality induced by prolonged arginine starvation was the cytotoxic autophagy that occurred in response to mitochondrial damage. Last, ASS1 was either low in abundance or absent in more than 60% of 149 random breast cancer biosamples, suggesting that patients with such tumors could be candidates for arginine starvation therapy

Mapping the Relationship Among Political Ideology, CSR Mindset, and CSR Strategy: A Contingency Perspective Applied to Chinese Managers

The literature on antecedents of corporate social responsibility (CSR) strategies of firms has been predominately content driven. Informed by the managerial sense-making process perspective, we develop a contingency theoretical framework explaining how political ideology of managers affects the choice of CSR strategy for their firms through their CSR mindset. We also explain to what extent the outcome of this process is shaped by the firm’s internal institutional arrangements and external factors impacting on the firm. We develop and test several hypotheses using data collected from 129 Chinese managers. The results show that managers with a stronger socialist ideology are likely to develop a mindset favouring CSR, which induces the adoption of a proactive CSR strategy. The CSR mindset mediates the link between socialist ideology and CSR strategy. The strength of the relationship between the CSR mindset and the choice of CSR strategy is moderated by customer response to CSR, industry competition, the role of government, and CSR-related managerial incentives

Factors influencing Chinese female expatriates' performance in international assignments

The current literature is mixed regarding what factors determine expatriate performance. In this study, we developed and tested a model to examine the relationship among family problems, expatriate-efficacy, host-country nationals' (HCNs') prejudice against women, perceived organizational support (POS) and Chinese female expatriate performance in international assignments. Our results indicated that HCNs' prejudice against women had a significant negative relationship and expatriate-efficacy had a significant positive relationship with female expatriate performance. POS and family problems moderated the relationship between HCNs' prejudice against women and female expatriate performance. However, family problems were not significantly related to female expatriate performance. Implications for research and practice are discussed

Fault Diagnosis of Hydraulic Pumps Using PSO-VMD and Refined Composite Multiscale Fluctuation Dispersion Entropy

Multiscale fluctuation dispersion entropy (MFDE) has been proposed to measure the dynamic features of complex signals recently. Compared with multiscale sample entropy (MSE) and multiscale fuzzy entropy (MFE), MFDE has higher calculation efficiency and better performance to extract fault features. However, when conducting multiscale analysis, as the scale factor increases, MFDE will become unstable. To solve this problem, refined composite multiscale fluctuation dispersion entropy (RCMFDE) is proposed and used to improve the stability of MFDE. And a new fault diagnosis method for hydraulic pumps using particle swarm optimization variational mode decomposition (PSO-VMD) and RCMFDE is proposed in this paper. Firstly, PSO-VMD is adopted to process the original vibration signals of hydraulic pumps, and the appropriate components are selected and reconstructed to get the denoised vibration signals. Then, RCMFDE is adopted to extract fault information. Finally, particle swarm optimization support vector machine (PSO-SVM) is adopted to distinguish different work states of hydraulic pumps. The experiments prove that the proposed method has higher fault recognition accuracy in comparison with MSE, MFE, and MFDE

Effect of Solution Treatment Temperature on Microstructural Evolution, Precipitation Behavior, and Comprehensive Properties in UNS S32750 Super Duplex Stainless Steel

The changes of microstructures, element distribution, and comprehensive properties were studied to explore their interactions with each other, induced by solution treatment of UNS S32750 super duplex stainless steel. The results showed that the ferrite content improved, while the austenite content declined as the temperature increased. From 900 to 1000 °C, the σ phase existing at α/γ grain boundaries and in ferrite grains gradually dissolved. At 1050 °C, the microstructures consisted of only ferrite and austenite. From 1050 to 1300 °C, the Cr2N precipitated in ferrite and gradually grew and coarsened. The impact energy and pitting potential of UNS S32750 first improved and then weakened, while the hardness is the opposite, owing to the combined effects of element distribution, microstructures, and precipitates. In the presence of the σ phase, the corrosion resistance and mechanical properties of UNS S32750 correspond directly to the σ phase fraction. Subsequently, the rise in temperature promoted γ → α phase transformation, and the elements partitioning ratios of Cr and Mo declined, resulting in reduced toughness and corrosion resistance and a rise in hardness. Consequently, when the solution treatment temperature is 1050 °C, the α/γ ratio of UNS S32750 approached 1:1, with excellent overall properties

RESEARCH ON FAULT DIAGNOSIS METHOD OF ROTATING MACHINERY BASED ON REFINED IMPROVED MULTISCALE FAST SAMPLE ENTROPY (MT)

To solve the problems of low computational efficiency and missing amplitude information existing in the current multiscale sample entropy（MSE） method when extracting features of complex series, refined improved multiscale fast sample entropy（RIMFSE） is presented. Firstly, fast sample entropy is employed to substitute traditional sample entropy, and the calculation cost is greatly reduced by improving the matching mechanism of reconstructed vectors. After that, the improved multiscale expansion method is applied to replace the traditional coarse-grained method, thereby avoiding the loss of amplitude information. Based on this, a new rotating machinery fault diagnosis method is proposed in combination with the max-relevance and min-redundancy（mRMR） method and the support vector machine（SVM） classifier. Two fault data sets of gearbox and bearing are used to verify the performance of the presented method; meanwhile, the presented method is compared with existing methods such as MSE, composite MSE（CMSE） and refined composite MSE（RCMSE）. The results show that compared with MSE, CMSE and RCMSE, the proposed method enjoys significant advantages in terms of robustness, calculation efficiency and recognition accuracy, thereby providing a new idea for rotating machinery fault diagnosis based on entropy feature

An Integrated Health Condition Detection Method for Rotating Machinery Using Refined Composite Multivariate Multiscale Amplitude-Aware Permutation Entropy

With a view to realizing the fault diagnosis of rotating machinery effectively, an integrated health condition detection approach for rotating machinery based on refined composite multivariate multiscale amplitude-aware permutation entropy (RCmvMAAPE), max-relevance and min-redundancy (mRmR), and whale optimization algorithm-based kernel extreme learning machine (WOA-KELM) is presented in this paper. The approach contains two crucial parts: health detection and fault recognition. In health detection stage, multivariate amplitude-aware permutation entropy (mvAAPE) is proposed to detect whether there is a fault in rotating machinery. Afterward, if it is detected that there is a fault, RCmvMAAPE is employed to extract the initial fault features that represent the fault states from the multivariate vibration signals. Based on the multivariate expansion and multiscale expansion of amplitude-aware permutation entropy, RCmvMAAPE enjoys the ability to effectively extract state information on multiple scales from multichannel series, thereby overcoming the defect of information loss in traditional methods. Then, mRmR is adopted to screen the sensitive features so as to form sensitive feature vectors, which are input into the WOA-KELM classifier for fault classification. Two typical rotating machinery cases are conducted to prove the effectiveness of the raised approach. The experimental results demonstrate that mvAAPE shows excellent performance in fault detection and can effectively detect the fault of rotating machinery. Meanwhile, the feature extraction method based on RCmvMAAPE and mRmR, as well as the classifier based on WOA-KELM, shows superior performance in feature extraction and fault recognition, respectively. Compared with other fault identification methods, the raised method enjoys better performance and the average fault recognition accuracy of the two typical cases in this paper can all reach above 98%

Study on dynamic variation law of stability of inner dumping pressure foot in the southern slope of Xinjiang South Open-pit Mine

In order to explore the stability change law of the south slope during the process of the inner dumping pressure foot in the south open pit coal mine in Xinjiang, this paper studied the dynamic change law of the slope stability during the process of the inner dumping pressure foot in the south open pit coal mine by means of numerical simulation and theoretical analysis. Firstly, the FLAC3D strength reduction method was used to simulate the process of the inner dumping pressure foot in the south slope, and the variation rule of the potential sliding surface position and stability coefficient in the process of the inner dumping pressure foot in the south slope was obtained. The optimal geometrical parameters of material cross section in the south side of the southern open-pit mine are obtained. Based on the numerical simulation results, the limit equilibrium theoretical model of the inner dumping pressure foot in the south slope was established, and the calculation formula of the stability coefficient of the middle south wall in the process of the inner dumping pressure foot was deduced. The evolution law of slope stress in the process of pressing foot in the south slope is expounded and the mechanism of the change of the position of the potential slip surface and the improvement of the stability of the middle south wall in the process of the inner dumping pressure foot was expounded