The Prevalence of Fear of Childbirth and Its Association With Intolerance of Uncertainty and Coping Styles Among Pregnant Chinese Women During the COVID-19 Pandemic.

Background: Fear of childbirth (FOC) is one of the most common psychological symptoms among pregnant women and significantly relates to cesarean section, anxiety, and depression. However, it is not clear the prevalence and risk factors of FOC among Chinese pregnant women since the outbreak of the COVID-19 pandemic. Aims: The objective of this study was to examine the associations between coping styles, intolerance of uncertainty, and FOC. Method: From December 2021 to April 2022, a cross-sectional survey was conducted in two hospitals in China through convenient sampling. The cross-sectional survey was conducted among 969 pregnant women, which included the Childbirth Attitude Questionnaire (CAQ), Intolerance of Uncertainty Scale-12 (IUS-12), and Simplified Coping Style Questionnaire (SCSQ). Results: The total prevalence of FOC was 67.8%. The percentages of women with mild (a score of 28-39), moderate (40-51), and severe FOC (52-64) were 43.6, 20.2, and 4.0%, respectively. The regression results indicated that primiparas, unplanned pregnancy, few spousal support, intolerance of uncertainty, and negative coping styles were significant risk factors of FOC. Women who adopt positive coping strategies experienced a lower level of childbirth fear. Conclusion: These findings suggest that cultivating positive coping styles and obtaining sufficient childbirth information may be helpful for mothers' mental health. Regular screening assessment of perinatal psychological symptoms, such as the high level of intolerance of uncertainty and negative coping styles, should be adopted to reduce the risk of fear of childbirth.

Compassion fatigue and compassion satisfaction among Chinese midwives working in the delivery room: A cross-sectional survey.

BACKGROUND AND AIMS: Compassion fatigue can negatively affect not only healthcare professionals' physical and mental health but also the quality of care they provide and organizational outcomes. However, little is known about compassion fatigue among Chinese midwives working in the delivery room. This study aimed to examine compassion fatigue and compassion satisfaction levels among Chinese midwives working in the delivery room and correlate their compassion fatigue and compassion satisfaction. METHODS: A multisite cross-sectional study with a convenience sampling approach was conducted at 62 hospitals in Henan Province, central China, from May to July 2020. The participants were recruited through an online survey. A self-designed sociodemographic and work-related data sheet, the Social Support Rating Scale (SSRS), and the Professional Quality of Life Scale (ProQoL) were used to measure the participants'basic information, level of social support, compassion fatigue(consists of burnout and secondary traumatic stress) and compassion satisfaction. Descriptive analysis was used to describe the characteristics of the participants' social support, compassion fatigue and compassion satisfaction. Multiple linear regression analysis was employed to identify associations with the participants' sociodemographic and professional characteristics, compassion fatigue and compassion satisfaction. RESULTS: A total of 213 questionnaires were completed, 206 of which were valid (96.71%). The majority of the participants reported moderate risks for compassion satisfaction (75.24%) and burnout (59.71%) and low risks for secondary traumatic stress (61.65%). Higher job satisfaction as a midwife, lower average working hours per week in the past year, higher social support, extroverted personality, and work recognition in the past month were positively associated with compassion satisfaction, explaining 48.7% of the total variance. Always considering giving up a midwifery career, lower social support, working a day-night shift, poor health condition, more exposure to traumatic birth events per month on average in recent years, and lower job satisfaction as a midwife were negative factors for burnout, explaining 35.3% of the total variance. Four factors, including more exposure to traumatic birth events per month on average in recent years, always considering giving up a midwifery career, working a day-night shift and poor sleep quality, were negatively related to secondary traumatic stress, explaining 14.2% of the variance. CONCLUSIONS: In this study, midwives showed moderate levels of compassion satisfaction and burnout and low levels of secondary traumatic stress which should attract the attention of health institutions. A healthy and supportive work environment is crucial to midwives' health, well-being and job satisfaction. Tailored strategies such as trauma management, emotional literacy, peer and social support networks should be implemented to support midwives' compassion satisfaction, while prevent and lower midwives' burnout and secondary traumatic stress.

Toward a Coronavirus Knowledge Graph.

This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a collection of published scientific articles related to COVID-19. We combined both chemo genomic entities in AG with entities extracted from CORD-19 to expand knowledge in the COVID-19 domain. Before populating KG with those entities, we perform entity disambiguation on CORD-19 collections using Wikidata. Our newly built KG contains at least 21,700 genes, 2500 diseases, 94,000 phenotypes, and other biological entities (e.g., compound, species, and cell lines). We define 27 relationship types and use them to label each edge in our KG. This research presents two cases to evaluate the KG's usability: analyzing a subgraph (ego-centered network) from the angiotensin-converting enzyme (ACE) and revealing paths between biological entities (hydroxychloroquine and IL-6 receptor; chloroquine and STAT1). The ego-centered network captured information related to COVID-19. We also found significant COVID-19-related information in top-ranked paths with a depth of three based on our path evaluation.

LncRNA GAS8-AS1 suppresses papillary thyroid carcinoma cell growth through the miR-135b-5p/CCND2 axis.

The aim of the present study was to investigate the potential role of GAS8 antisense RNA 1 (GAS8-AS1) in papillary thyroid carcinoma (PTC). PcDNA3.1-GAS8-AS1 and si-GAS8-AS1, miR-135b-5p mimic and si-CCND2 were transfected into PTC cells. Cell proliferation was evaluated by Cell Counting Kit-8 (CCK-8). QRT-PCR was used to determine expressions of GAS8-AS1, miR-135b-5p, and CCND2, and Western blot were detected protein level of CCND2. The miRNA target gene prediction site TargetScan was used to predict potential targets of GAS8-AS1 and miR-135b-5p. Cell cycle progression was analyzed by flow cytometry. We found that GAS8-AS1 was down-regulated in PTC cell lines and inhibited proliferation and cycle of PTC cell. GAS8-AS1 directly targets miR-135b-5p, and GAS8-AS1 could regulate a downstream target of miR-135b-5p, Cyclin G2 (CCNG2), in an miR-135b-5p-mediated manner. In addition, we also proved that overexpressed GAS8-AS1 inhibited tumor formation in vivo GAS8-AS1 suppresses PTC cell growth through the miR-135b-5p/CCND2 axis.