Like many other transit modes, the metro provides stop-to-stop services rather than door-to-door services, so its use undeniably involves first- and last-mile issues. Understanding the determinants of the first- and last-mile mode choice is essential. Existing literature, however, mostly overlooks the mode choice effects of traffic safety perception and attitudes toward the mode. To this end, based on a face-to-face questionnaire survey in Shenzhen, China, this study uses the two-sample t-test to confirm the systematic differences in traffic safety perception and attitudes between different subgroups and develops a series of multinomial logistic (MNL) models to identify the determinants of first- and last-mile mode choice for metro commuters. The results of this study show that: (1) Walking is the most frequently used travel mode, followed by dockless bike-sharing (DBS) and buses; (2) Variances in traffic safety perception and attitude exist across gender and location; (3) Vehicle-related crash risks discourage metro commuters from walking to/from the metro station but encourage them to use DBS and buses as feeder modes; (4) DBS–metro integration is encouraged by the attitude that DBS is quicker than buses and walking, and positive attitudes toward the bus and DBS availability are decisive for the bus–metro and DBS–metro integration, respectively; and (5) Substantial differences exist in the mode choice effects of traffic safety perception and attitudes for access and egress trips. This study provides a valuable reference for metro commuters’ first- and last-mile travel mode choice, contributing to developing a sustainable urban transport system.

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two lncRNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC.

Human fetal adrenal glands produce substantial amounts of dehydroepiandrosterone (DHEA), which is one of the most important precursors of sex hormones. However, the underlying biological mechanism remains largely unknown. Herein, we sequenced human fetal adrenal glands and gonads from 7 to 14 gestational weeks (GW) via 10× Genomics single-cell transcriptome techniques, reconstructed their location information by spatial transcriptomics. Relative to gonads, adrenal glands begin to synthesize steroids early. The coordination among steroidogenic cells and multiple non-steroidogenic cells promotes adrenal cortex construction and steroid synthesis. Notably, during the window of sexual differentiation (8–12 GW), key enzyme gene expression shifts to accelerate DHEA synthesis in males and cortisol synthesis in females. Our research highlights the robustness of the action of fetal adrenal glands on gonads to modify the process of sexual differentiation.

Background: To construct a prognostic risk model of bladder cancer (BC) from the perspective of long non-coding RNAs (lncRNAs) and ferroptosis, in order to guide clinical prognosis and identify potential therapeutic targets. Methods: In-hours BC samples were collected from 4 patients diagnosed with BC, who underwent radical cystectomy. Single cell transcriptome sequencing was performed and Seurat package were used for quality control and secondary analysis. LncRNAs expression profiles of BC samples were extracted from The Cancer Genome Atlas database. And sex, age, tumor, node, metastasis stage and other clinical data was downloaded at the same time. Ferroptosis-related lncRNAs were identified by co-expression analysis. We constructed a risk model by Cox regression and least absolute shrinkage and selection operator regression analyses. The predictive strength of the risk model for overall survival (OS) of patients with BC was evaluated by the log-rank test and Kaplan–Meier method. Finally, the enrichment analysis was performed and visualized. Results: We identified and included 15 prognostic ferroptosis-related lncRNAs (AL356740.1, FOXC2AS1, ZNF528AS1, LINC02535, PSMB8AS1, AL590428.1, AP000347.2, OCIAD1-AS1, AP001347.1, AC104986.2, AC018926.2, LINC00867, AC099518.4, USP30-AS1, and ARHGAP5-AS1), to build our ferroptosis-related lncRNAs risk model. Using this risk model, BC patients were divided into high and low-risk groups, and their respective survival lengths were calculated. The results showed that the OS of the low-risk group was significantly longer than that of the high-risk group. A nomogram was utilized to predict the survival rate of BC patients. As indicated in the nomogram, risk score was the most important indicator of OS in patients with BC. The ferroptosis-related lncRNAs risk model is an independent tool for prognostic risk assessment in patients with BC. Single cell transcriptome sequencing suggests that ferroptosis-related lncRNAs express specifically in BC tumor microenvironment. AL356740.1, LINC02535 and LINC00867 were mainly expressed in tumor cells. Conclusion: The risk model based on the ferroptosis-related lncRNAs and the genomic clinico-pathological nomogram could be used to accurately predict the prognosis of patients with BC. The lncRNAs used to build this model might become potential therapeutic targets in the future.