Nomogram for Predicting Bone Development State of Female Children and Adolescents–A Fast Screening Approach Based on Pubes Stages for Growth and Development

Objective: To develop a nomogram for predicting bone development state (BDS) of female children and adolescents in a large scale.Methods: Four hundred forty-seven female students were designated as the training cohort to develop the predictive model, whereas 196 female students were used as the validation cohort to verify the established model. Bone age, height, body mass, body fat percentage, and secondary sexual characteristics were recorded, and BDS was determined with the chronological age and bone age. Multivariate logistic regression was conducted to determine the factors, and nomogram was developed and validated with the training and validation cohorts, respectively.Results: One hundred forty-seven female students were identified as BDS abnormal in the training cohort (32.9%), and 104 were determined in the validation cohort (53.1%). Age, height, weight, and pubes stage were selected for the predictive model. A nomogram was developed and showed a good estimation, with a C-index of 0.78 and a good calibration in the training cohort. Application of the nomogram to the validation cohort showed a similar C-index of 0.75 and a good calibration.Conclusion: A nomogram for predicting bone development was developed, which can provide a relatively good estimation of BDS for female children and adolescents in Chinese metropolis

For the Sustainable Development of Universities: Exploring the External Factors Impacting Returned Early Career Academic’s Research Performance in China

Early career academics are the key agents for the sustainable development of higher education institutions. In China, those who were educated overseas and have returned to Chinese universities to seek academic positions are becoming a fast-growing group. Good research performance is critical to survive in the increasingly competitive environment in academia. Improving research performance requires an understanding of the factors that facilitate or inhibit research performance. In the light of Bronfenbrenner’s ecological systems theory, this study, using a mixed-method design (20 interviewees and 136 respondents), elaborates on a number of external factors affecting returned early career academics’ research performance. Understanding these factors is helpful for the building of a favorable environment that can improve the research performance of the returned early career academics, and hence the sustainable development of universities

For the Sustainable Development of Universities: Exploring the External Factors Impacting Returned Early Career Academic’s Research Performance in China

Early career academics are the key agents for the sustainable development of higher education institutions. In China, those who were educated overseas and have returned to Chinese universities to seek academic positions are becoming a fast-growing group. Good research performance is critical to survive in the increasingly competitive environment in academia. Improving research performance requires an understanding of the factors that facilitate or inhibit research performance. In the light of Bronfenbrenner’s ecological systems theory, this study, using a mixed-method design (20 interviewees and 136 respondents), elaborates on a number of external factors affecting returned early career academics’ research performance. Understanding these factors is helpful for the building of a favorable environment that can improve the research performance of the returned early career academics, and hence the sustainable development of universities

Trajectory Prediction with Correction Mechanism for Connected and Autonomous Vehicles

Trajectory prediction of surrounding vehicles is a critical task for connected and autonomous vehicles (CAVs), helping them to realize potential dangers in the traffic environment and make the most appropriate decisions. In a practical traffic environment, vehicles may affect each other, and the trajectories may have multi-modality and uncertainty, which makes accurate trajectory prediction a challenge. In this paper, we propose an interactive network model based on long short-term memory (LSTM) and a convolutional neural network (CNN) with a trajectory correction mechanism, using our newly proposed probability forcing method. The model learns the interactions between vehicles and corrects their trajectories during the prediction process. The output is a multimodal distribution of predicted trajectories. In the experimental evaluation of the US-101 and I-80 Next-Generation Simulation (NGSIM) real highway datasets, our proposed method outperforms other contrast methods

Trajectory Prediction with Correction Mechanism for Connected and Autonomous Vehicles

Trajectory prediction of surrounding vehicles is a critical task for connected and autonomous vehicles (CAVs), helping them to realize potential dangers in the traffic environment and make the most appropriate decisions. In a practical traffic environment, vehicles may affect each other, and the trajectories may have multi-modality and uncertainty, which makes accurate trajectory prediction a challenge. In this paper, we propose an interactive network model based on long short-term memory (LSTM) and a convolutional neural network (CNN) with a trajectory correction mechanism, using our newly proposed probability forcing method. The model learns the interactions between vehicles and corrects their trajectories during the prediction process. The output is a multimodal distribution of predicted trajectories. In the experimental evaluation of the US-101 and I-80 Next-Generation Simulation (NGSIM) real highway datasets, our proposed method outperforms other contrast methods

Ferroptosis-associated gene CISD2 suppresses colon cancer development by regulating tumor immune microenvironment

Background Despite the association of ferroptosis with various tumors, the specific mechanism by which it influences colon adenocarcinoma (COAD) microenvironmental equilibrium remains elusive. This study aims to elucidate how ferroptosis affects COAD microenvironmental homeostasis and its potential impact on COAD research. Objective By employing genetic screening and single-cell analysis of tumor data, we investigated the role of ferroptosis genes in COAD microenvironmental homeostasis. The genes were correlated with immune cell infiltration in tissue samples and patient outcomes. Methods Ferroptosis-associated genes were initially identified through the FerrDb database. Utilizing the tidyverse and Seurat packages, genes with substantial expression differences were extracted, and clustering analysis was performed on the single-cell data. A Venn diagram depicted shared differential genes for ferroptosis and tumors. To screen key ferroptosis genes, further enrichment analysis and immune cell infiltration analysis were conducted. Lastly, human COAD cell lines were employed to overexpress CDGSH iron sulfur domain 2 (CISD2) through cellular assays to validate its function in COAD. Results Following screening of The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, 414 COAD patient samples and 341 normal samples were included. Through the FerrDb database, 259 ferroptosis genes were identified. Clustering the single-cell data revealed 911 tumor marker genes, of which 18 were ferroptosis genes. Analysis of variance (ANOVA) and univariate regression analysis determined that only CISD2 was statistically significantly associated with clinical outcomes. Additionally, CISD2 was found to positively correlate with activated memory T cells and negatively correlate with regulatory T cells (Tregs) and plasma cells in COAD, as well as being significantly associated with several immune-related and cancer-related pathways. CISD2 expression was elevated in most tumors, likely due to cell cycle regulation and immune system activation. Moreover, CISD2 upregulation inhibited COAD cell proliferation and enhanced 5-fluorouracil (5-FU) sensitivity. Our findings indicate, for the first time, that CISD2 governs the cell cycle and stimulates the immune system to impede COAD progression. Conclusion By modulating the cell cycle and mediating immune infiltration, CISD2 may inhibit COAD development by influencing tumor immune microenvironment equilibrium, providing valuable insights into the relevance and potential impact of the research results on the COAD research field