Roles of Oxidative Stress in Polycystic Ovary Syndrome and Cancers

Oxidative stress (OS) has received extensive attention in the last two decades, because of the discovery that abnormal oxidation status was related to patients with chronic diseases, such as diabetes, cardiovascular, polycystic ovary syndrome (PCOS), cancer, and neurological diseases. OS is considered as a potential inducing factor in the pathogenesis of PCOS, which is one of the most common complex endocrine disorders and a leading cause of female infertility, affecting 4%–12% of women in the world, as OS has close interactions with PCOS characteristics, just as insulin resistance (IR), hyperandrogenemia, and chronic inflammation. It has also been shown that DNA mutations and alterations induced by OS are involved in cancer pathogenesis, tumor cell survival, proliferation, invasion, angiogenesis, and so on. Furthermore, recent studies show that the females with PCOS are reported to have an increasing risk of cancers. As a result, the more serious OS in PCOS is regarded as an important potential incentive for the increasing risk of cancers, and this study aims to analyze the possibility and potential pathogenic mechanism of the above process, providing insightful thoughts and evidences for preventing cancer potentially caused by PCOS in clinic

Online ride-hailing regulation: a simulation study based on evolutionary game theory

Game theory contributes to the quantitative study of online ride-hailing regulations; however, prior game models of the online ride-hailing market fail to comprehensively consider government regulation strategies as well as multiple stakeholders in various regulation contexts. This study constructs two system dynamic models of evolutionary games among online ride-hailing platforms, drivers, and passengers. One is the basic model not subject to government regulations, while the other considers government regulations systematically regarding penalty policy, incentive policy, policy adaptability, and public participation. By solving and simulating the model, we study evolutionary stable strategies to control fluctuations in the game process. The results show that an unregulated online ride-hailing system is volatile, and government regulations help stabilize the system. The effect of government regulations can be optimized by adopting a dynamic penalty with a greater initial force, considering platforms as agents in incentive policy, improving policy adaptability, and rewarding public participation

Service quality management of online car-hailing based on PCN in the sharing economy

Online car-hailing has successfully integrated the sharing economy into the transportation industry. However, with its rapid development, service issues remain a challenge, and continuously improving service quality is a key factor for the sustainable growth of online car-hailing and the sharing economy. In this study, we implement LSTM text classification, sentiment analysis and frequent itemset mining of the electronic word-of-mouth (eWOM) of the online car-hailing platform, Didi Chuxing (DiDi), to identify existing service issues. Then, we depict the service process network of online car-hailing by using process chain network (PCN) to analyze and locate service issues. Finally, we analyze service optimization and innovation for online car-hailing by proposing corresponding service quality optimization suggestions based on the optimization principles of PCN. By constructing a service quality management research framework of online car-hailing in the sharing economy, we contribute to the literature on service science and the sharing economy and provide practical implications for sharing economy platforms to establish data-driven strategies of operation management

Changes in Service Quality of Sharing Accommodation: Evidence from Airbnb

As consumers' perceptions of quality change over time, service providers should track the dynamic changes in service quality and adjust their services to adapt to these changes. In the context of sharing accommodation, although many studies have focused on evaluating service quality, the dynamic changes in service quality over time remain unexplored. This study aims to explore the dynamic changes in the service quality of sharing accommodation. We propose a novel framework that uses deep learning and SERVQUAL to analyze online reviews of sharing accommodation services, thus contributing to the literature from a dynamic perspective. Using a 10-year-span longitudinal dataset of Airbnb's online reviews of San Francisco's listings (n1 = 366,643), we construct a weakly supervised topic model that extracts service quality topics from online reviews and then classifies reviews into irrelevant-topics and relevant-topics. Each relevant-topic review is mapped to one of the SERVQUAL dimensions, combined with its sentiment analysis score, which constitutes the output of text mining. We then analyze the dynamic changes in the service quality. The results show that both the overall service quality and that in each dimension of SERVQUAL exhibit a slight downward trend. We obtain the similar results for the Beijing longitudinal dataset (n2 = 251,081), which confirms that the downward trend in service quality is not unique to San Francisco. We discuss the reasons for this trend and provide managerial guidance for the platform and its hosts

Iridoids with Genipin Stem Nucleus Inhibit Lipopolysaccharide-Induced Inflammation and Oxidative Stress by Blocking the NF-κB Pathway in Polycystic Ovary Syndrome

Background/Aims: Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, and it is usually characterized by chronic inflammation, oxidative stress, and altered microRNA expression. The aim of this study is to investigate how the effects of iridoids with genipin stem nucleus inhibit PCOS complications. The interactions between iridoids were investigated, as well. Methods: The chronic inflammation cell model was induced using lipopolysaccharide (LPS) in the RAW 264.7 and KGN cell lines. Levels of mRNA and protein expression were quantified using real time-quantitative polymerase chain reaction (RT-qPCR) and western blot analysis, respectively. The target of the iridoids was identified using the drug affinity responsive target stability (DARTS) method. The ability to scavenge free radicals was evaluated using the DPPH radical scavenging method and the ultra oxygen anion (O2-) radical scavenging method. Results: The cells recovered from the inflammatory conditions and showed significantly decreased levels of interleukins after treatment with iridoids. The iridoids were demonstrated to target NF-κB, inhibit the phosphorylation and degradation of IκB, inhibit the nuclear entry of NF-κB, and inhibit the expression of inflammatory factors. Though only genipin showed an efficient ability to scavenge O2-, the iridoids, IκB inhibitor (BAY 11-7085), and NF-κB inhibitor (PDTC) could inhibit LPS-induced oxidative stress on the cells, indicating that the iridoids exert their anti-oxidant effects via the NF-κB pathway. The expression levels of microRNAs (miRNAs) were also altered by LPS, but the iridoids could scarcely rescue the abnormal condition. Conclusion: Chronic inflammation may be an important incentive for oxidative stress and abnormal microRNA expression in PCOS, and iridoids can protect patients from inflammatory damage by regulating the NF-κB pathway

The complete chloroplast genome of a medical herb, Potentilla parvifolia Fisch. (Rosaceae), from Qinghai-Tibet Plateau in China

Potentilla parvifolia Fisch. (Rosaceae) is one of the genuine medicinal materials in Qinghai-Tibet Plateau, China. Here we report the first chloroplast (cp) genome of P. parvifolia using Illumina NovaSeq 6000 platform. The length of its complete cp genome is 152,898 bp, containing four sub-regions; a large single copy region (LSC) of 84,160 bp and a small single copy region (SSC) of 18,128 bp are separated by a pair of inverted repeat regions (IRs) of 25,305bp. The complete cp genome of P. parvifolia contains 130 genes, including 85 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The overall GC content of the cp genome is 37.2%. The phylogenetic analysis, based on 17 cp genomes, suggested that P. parvifolia is closely related to P. fruticosa L. and Fragaria species

Ultrasound-Assisted Extraction of Flavonoids from <i>Potentilla fruticosa</i> L. Using Natural Deep Eutectic Solvents

A series of natural deep eutectic solvents (NADESs) were prepared with choline chloride, betaine, and a variety of natural organic acids in order to find new environmentally-friendly green solvents to replace the traditional solvents. The NADESs were employed to extract flavonoids from Potentilla fruticosa L. (PFL) with the help of ultrasound. The eutectic solvent diluted with an appropriate amount of water improved the extraction ability of flavonoids due to the decrease of solution viscosity. The microstructure of the raw sample and the samples subjected to ultrasonic bath in different solutions were observed using scanning electron microscope (SEM) to determine the role of the NADESs in the extraction process. The DPPH method and glucose consumption method were used to study the antioxidant and hypoglycemic ability of flavonoid compounds in PFL. Single factor method and response surface methodology (RSM) were designed to analyze the effects of three extraction parameters, including solvent/solid ratio, ultrasonic power, and extraction time, on the extraction yield, antioxidant capacity, and hypoglycemic capacity, and the corresponding second-order polynomial prediction models were established. The optimal extraction conditions for the maximum extraction yield, antioxidant capacity, and hypoglycemic capacity were predicted by RSM, and the reliability of RSM simulation results was verified by a one-off experiment

ETA-mediated anti-TNF-α therapy ameliorates the phenotype of PCOS model induced by letrozole.

Chronic inflammation is a typical characteristic of polycystic ovary syndrome (PCOS), in which, tumor necrosis factor (TNF)-α plays an important role. We investigated whether anti-TNF-α therapy can alleviate the core phenotypes of PCOS. In pubertal female Wistar rats, release pellets of letrozole (LET) were administered continuously for 90 days to induce PCOS-like phenotypes, followed by treatment with etanercept (ETA), a TNF-α inhibitor. ETA significantly inhibited increases in body weight and androgen, TNF-α, and MCP-1 levels, excessive recruitment of lipid droplets, altered levels of pre-adipose differentiation markers, and abnormal development of follicles. In addition, TNF-α and testosterone (T) levels in the rat sera were significantly positively correlated. Further experiments were performed to investigate the relationship between TNF-α and androgen. Persistent exposure of the RAW 264.7 cell line to low doses of testosterone significantly enhanced TNF-α expression and activated the NF-κB signaling pathway, which were blocked by ETA. Furthermore, treatment with TNF-α promoted the production of testosterone in KGN granulosa cells by reducing CYP19A1 expression, whereas ETA treatment blocked this process. In conclusion, anti-TNF-α therapy with ETA may be an efficient method to alleviate PCOS, whose underlying mechanism may be associated with its ability to reduce excessive androgen levels