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Abstract Background Homoeologs are defined as homologous genes resulting from allopolyploidy. Bread wheat, Triticum aestivum, is an allohexaploid species with many homoeologs. Homoeolog expression bias, referring to the relative contribution of homoeologs to the transcriptome, is critical for determining the traits that influence wheat growth and development. Asymmetric transcription of homoeologs has been so far investigated in a tissue or organ-specific manner, which could be misleading due to a mixture of cell types. Results Here, we perform single nuclei RNA sequencing and ATAC sequencing of wheat root to study the asymmetric gene transcription, reconstruct cell differentiation trajectories and cell-type-specific gene regulatory networks. We identify 22 cell types. We then reconstruct cell differentiation trajectories that suggest different origins between epidermis/cortex and endodermis, distinguishing bread wheat from Arabidopsis. We show that the ratio of asymmetrically transcribed triads varies greatly when analyzing at the single-cell level. Hub transcription factors determining cell type identity are also identified. In particular, we demonstrate that TaSPL14 participates in vasculature development by regulating the expression of BAM1. Combining single-cell transcription and chromatin accessibility data, we construct the pseudo-time regulatory network driving root hair differentiation. We find MYB3R4, REF6, HDG1, and GATAs as key regulators in this process. Conclusions Our findings reveal the transcriptional landscape of root organization and asymmetric gene transcription at single-cell resolution in polyploid wheat.

The prevalence of anxiety and depression is high among men who have sex with men (MSM), but limited studies focus on their development trends. This study examined the prevalence and influencing factors of anxiety and depression in HIV-negative MSM. In this study, 711 subjects were followed up every 24 weeks for 96 weeks. A group-based trajectory model was used to identify different development trends and a logistic regression model was used to explore the influencing factors of different trajectories. Low, moderate, and high anxiety groups accounted for 32.56, 56.12, and 11.32%; and low and high depression groups accounted for 73.90 and 26.10%. High anxiety was associated with a lower education degree, little HIV-related knowledge, and other characteristics (more agreed that “HIV is a threat to me/my family,” had high frequency of seeking sexual partners via the Internet, had a history of sexually transmitted disease (STD), and a sense of discrimination by doctors). High depression was associated with a lower education degree, little HIV-related knowledge, being bisexual and the following characteristics: they felt that HIV infection rate of MSM around them was high, and more agreed that “HIV is a threat to me/my family,” had a high frequency of seeking sexual partners through the Internet and alcohol drinking, had a history of STD, and felt being discriminated against by doctors and others. There is heterogeneity in the development trends of anxiety and depression. We need to improve intervention in the mental health of MSM, especially those with high anxiety and depression development trends.Clinical Trial Registration[http://www.chictr.org.cn/showproj.aspx?proj=5716], identifier [ChiCTR-TRC-13003849].

Abstract Background A high rate of cesarean delivery has become a cause of global concern. Although the rate of cesarean delivery has declined over recent years, it remains at a high level largely because of cesarean delivery on maternal request (CDMR). Unnecessary cesarean delivery has limited significance in benefiting maternal and infant physical health; in some ways, it might pose potential risks instead. With the implementation of the “Two-child Policy” in China, an increasing number of women plan to have a second child. Accordingly, how to handle the CDMR rate in China remains an important issue. Methods Data were collected from a longitudinal follow-up study conducted in Chongqing, China, from 2018 to 2019. A structured questionnaire was administered to subjects for data collection. Basic information, including demographic characteristics, living habits, medical history, and follow-up data of pregnant women, as well as their families and society, was collected. Additionally, delivery outcomes were recorded. Logistic regression was performed to analyze the factors influencing CDMR. Results The rate of cesarean delivery in Chongqing, China was 36.01 %, and the CDMR rate was 8.42 %. Maternal request (23.38 %), fetal distress (22.73 %), and pregnancy complications (9.96 %) were the top three indications for cesarean delivery. Logistic regression analysis showed that older age (OR = 4.292, 95 % CI: 1.984–9.283) and being a primiparous woman (OR = 6.792, 95 % CI: 3.230-14.281) were risk factors for CDMR. In addition, CDMR was also associated with factors such as the tendency to choose cesarean delivery during late pregnancy (OR = 5.525, 95 % CI: 2.116–14.431), frequent contact with mothers who had undergone vaginal deliveries (OR = 0.547, 95 % CI: 0.311–0.961), and the recommendation of cesarean delivery by doctors (OR = 4.071, 95 % CI: 1.007–16.455). Conclusions “Maternal request” has become the primary indication for cesarean delivery. The occurrence of CDMR is related to both the personal factors of women during pregnancy and others. Medical institutions and obstetricians should continue popularizing delivery knowledge among pregnant women, enhancing their own professional knowledge about delivery, adhering to the standard indications for cesarean delivery, and providing pregnant women with adequate opportunities for attempting vaginal delivery.

PurposeThe purpose is to accurately identify women at high risk of developing cervical cancer so as to optimize cervical screening strategies and make better use of medical resources. However, the predictive models currently in use require clinical physiological and biochemical indicators, resulting in a smaller scope of application. Stacking-integrated machine learning (SIML) is an advanced machine learning technique that combined multiple learning algorithms to improve predictive performance. This study aimed to develop a stacking-integrated model that can be used to identify women at high risk of developing cervical cancer based on their demographic, behavioral, and historical clinical factors.MethodsThe data of 858 women screened for cervical cancer at a Venezuelan Hospital were used to develop the SIML algorithm. The screening data were randomly split into training data (80%) that were used to develop the algorithm and testing data (20%) that were used to validate the accuracy of the algorithms. The random forest (RF) model and univariate logistic regression were used to identify predictive features for developing cervical cancer. Twelve well-known ML algorithms were selected, and their performances in predicting cervical cancer were compared. A correlation coefficient matrix was used to cluster the models based on their performance. The SIML was then developed using the best-performing techniques. The sensitivity, specificity, and area under the curve (AUC) of all models were calculated.ResultsThe RF model identified 18 features predictive of developing cervical cancer. The use of hormonal contraceptives was considered as the most important risk factor, followed by the number of pregnancies, years of smoking, and the number of sexual partners. The SIML algorithm had the best overall performance when compared with other methods and reached an AUC, sensitivity, and specificity of 0.877, 81.8%, and 81.9%, respectively.ConclusionThis study shows that SIML can be used to accurately identify women at high risk of developing cervical cancer. This model could be used to personalize the screening program by optimizing the screening interval and care plan in high- and low-risk patients based on their demographics, behavioral patterns, and clinical data.

Stability control for soft and broken surrounding rock of roadways is one important segment of mining support. Taking 1412 Roadway of a mine in Guizhou province as a research background, this paper studies the large deformation of surrounding rock and the failure of bolts and cables. The deformation and failure mechanism are analyzed by related theoretical analysis and field survey. Then, the feasibility of the composite controlling scheme, bolts and cables + grouting + steel tube concrete support, is verified by theoretical analysis, numerical simulation, and industrial test. Following results can be obtained: main reasons leading to the deformation of surrounding rock and the failure of cables and blots in the roadway are low strength and poor self-stability of surrounding rock, complex stress environment, low support resistance, and lack of reinforced support in crucial supporting sites; the control scheme can reduce the surrounding rock deformation by 40%, which meets the requirements of field application so that this practice can provide some guidance for other similar projects.