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Introduction: Previous studies have indicated the association between smooth endoplasmic reticulum aggregates (SERa+) and poorer medically assisted reproduction outcomes. However, the link between SERa+ and neonatal outcomes remains controversial and open for debate. A comprehensive meta‐analysis on the relation between SERa+ and the risk of birth defects is needed. Material and Methods: The literature search was conducted using the following databases: PubMed, Embase, Cochrane Libraries, Web of Science, and Chinese databases including China National Knowledge Infrastructure (CNKI) and Wan Fang from inception until July 2023. Risk ratio (RR) and 95% confidence interval (CI) were calculated by a fixed‐effected model, while heterogeneity was assessed by forest plots and I2 statistic. Funnel plot was produced to assess publication bias. This meta‐analysis has been registered on PROSPERO (CRD42022313387). Results: The search resulted in 122 studies, 14 of which met the inclusion criteria. The analysis of birth defects revealed a higher risk (RR = 2.17, 95%CI 1.24 to 3.81, p = 0.007) in children derived from SERa+ cycle compared to SERa‐ cycles (711 vs. 4633). Meanwhile, in a subgroup analysis, the risk of birth defects was significantly increased in the SERa+ oocytes group as compared with the sibling SERa‐ oocytes group (RR = 3.53, 95%CI 1.21 to 10.24, p = 0.02). Conclusions: To conclude, our analysis indicated that SERa+ cycles/oocytes may have a potential risk of increased additional major birth defects comparing with SERa‐ cycles/oocytes. This conclusion may provide evidence‐based support for clinicians in IVF clinical guidance and embryologists in prudent embryo selection strategy. [ABSTRACT FROM AUTHOR]

Social media platforms have been used by various actors to bypass traditional media gatekeepers to share messages, draw attention, and accumulate influence. We study how actors from peripheral groups gain influence on social media and how their social media behaviors evolve over time. Integrating online strategic performance and hybrid media literature, we hypothesize that peripheral groups perform group identities to spur social media audience reaction and news media amplification, to which they further adapt their performance. By analyzing 242 QAnon Twitter accounts using topic modeling and time series modeling, we find that their in-group solidarity and out-group animosity tweets boost retweets, but not followers; increased retweets and followers drive news media amplification largely undertaken by right-wing outlets and motivate future performance of group identity, particularly of out-group animosity. The implications of social media and news media for the growth of peripheral actors and ideologies are discussed. [ABSTRACT FROM AUTHOR]

Despite the increasing use of digital media data in communication research, a central challenge persists – retrieving data with maximal accuracy and coverage. Our investigation of keyword-based data collection practices in extant communication research reveals a one-step process, whereas our cross-disciplinary literature review suggests an iterative query expansion process guided by human knowledge and computer intelligence. Hence, we introduce the WordPPR method for keyword selection and text data retrieval, which entails four steps: 1) collecting an initial dataset using core/seed keyword(s); 2) constructing a word graph based on the dataset; 3) applying the Personalized PageRank (PPR) algorithm to rank words in proximity to the seed keyword(s) and selecting new keywords that optimize retrieval precision and recall; 4) repeating steps 1–3 to determine if additional data collection is needed. Without requiring corpus-wide sampling/analysis or extensive manual annotation, this method is well suited for data collection from large-scale digital media corpora. Our simulation studies demonstrate its robustness against parameter choice and its improvement upon other methods in suggesting additional keywords. Its application in Twitter data retrieval is also provided. By advancing a more systematic approach to text data retrieval, this study contributes to improving digital media data retrieval practices in communication research and beyond. [ABSTRACT FROM AUTHOR]

Quantifying extracellular and intracellular contributions to Cr(VI) reduction is crucial for understanding bacterial Cr(VI)-reduction mechanisms. However, this contribution under different oxygen conditions remains largely unexplored. This study quantified the extracellular/intracellular contribution to aerobic and anaerobic Cr(VI) reduction using Pseudomonas sp. HGB10, an isolated Cr(VI)-reducing bacterium, as the experimental model. Interestingly, it was found that the lower anaerobic minimum inhibitory concentration (MIC) does not necessarily imply a lower anaerobic Cr(VI)-reduction rate for HGB10. For the initial Cr(VI) concentration of 20 mg L−1, the maximum anaerobic Cr(VI)-reducing rate reached 100%, while the aerobic counterpart was only 75%, even though the value of the aerobic MIC (400 mg L−1) is twice that of the anaerobic (200 mg L−1). Additionally, the calculated extracellular contributions to aerobic and anaerobic Cr(VI) reduction were 10.76% and 55.71%, respectively, while the intracellular contributions were 68.29% and 40.38%. The sum of extracellular and intracellular contributions to Cr(VI) reduction (79.05% and 96.09%) under aerobic and anaerobic conditions was nearly balanced with the corresponding maximum values despite minor relative errors. These results indicated that anaerobic Cr(VI) reduction mainly occurred extracellularly rather than intracellularly, which differs from the existing result. Overall, our findings provide new insights into bacterial Cr(VI) reduction. [ABSTRACT FROM AUTHOR]

Centering on social media's public- and profit-oriented nature, this study theorizes how social media users are empowered and constrained when participating in platform governance through user-initiated expressions on platforms. The empirical analysis focuses on user responses before and after Elon Musk's official acquisition of Twitter, utilizing cluster analysis and topic modeling to examine the volume and content of related discourses among different Twitter user groups. Our results point to user constraint in platform governance. Although a diverse set of users, such as partisans, bots, and cryptocurrency enthusiasts, spoke up, they had diverging and sometimes conflicting objectives; and partisans dominated the conversations. There was an upsurge in user volume and activity level post-acquisition among liberal users, whose critical voices on platform governance might have bolstered platform business. Potential bots also increased in volume and amplified political topics. Our findings shed light on the challenges of user-driven platform governance, underscoring the complex interplay between platform users, economy, and governance. [ABSTRACT FROM AUTHOR]

Extending literature on political polarization and political expression, we study patterns of polarized expression by vocal partisans from opposing camps on social media. Specifically, we argue that polarized partisan expression can be characterized by three divergences: 1) different thematic emphases on the same issue; 2) response to different real-world events on the same issue; and 3) a temporal disconnect at the aggregate level. Highlighting how online expression by different partisan groups is animated by discrete concerns and events and exhibits different temporality, the three divergences in polarized partisan expression not only reflect and explain existing polarization concepts but also speak to the epistemological chasm between partisan groups. Our empirical analysis is based on Twitter discussion about the issue of immigration in the U.S. and applies topic modeling and time series analysis. Results demonstrate that liberal and conservative tweets exhibit different thematic emphases, are often spurred by different event features, and remain largely temporally independent, though both Trump's tweets and emotionally evocative events can draw simultaneous reaction from both sides. These findings suggest that opposing partisan groups not only hold different views on the same issue, but also weave different events and facts about the issue into partisan expression in response to different exogenous factors. In short, they "talk past each other." These polarized partisan expression patterns indicate a splintered public sphere, a concerning quality for deliberative democracy. [ABSTRACT FROM AUTHOR]

Extensive research reveals gender gaps in social media expression, particularly women's reduced propensity for sharing political information and opinions. We examine the impact of political defeat on the gender gap in political expression on social media by pairing Twitter data from candidate supporters with a voter file. Our results indicate that Trump's 2020 defeat reduced tweet volumes only among his female supporters, while his male supporters remained unaffected. This dampening effect was stronger for female Trump supporters who expressed their gender identity in their Twitter bios than those who did not. Tweet content remained largely unchanged for both genders. These findings enhance our understanding of how social media and political defeat together contribute to the gender expression gap and its relationship with offline political behaviors post-defeat. They also demonstrate the power of our methodological approach in revealing temporal and individual differences. [ABSTRACT FROM AUTHOR]