Developmentally dependent reprogramming of the Arabidopsis floral transcriptome under sufficient and limited water availability.

BACKGROUND: Environmental stresses negatively impact reproductive development and yield. Drought stress, in particular, has been examined during Arabidopsis reproductive development at morphological and transcriptomic levels. However, drought-responsive transcriptomic changes at different points in reproductive development remain unclear. Additionally, an investigation of the entire transcriptome at various stages during flower development is of great interest. RESULTS: Here, we treat Arabidopsis plants with well-watered and moderately and severely limiting water amounts when the first flowers reach maturity and generate RNA-seq datasets for early, middle, and late phases during flower development at 5, 6, and 7 days following treatment. Under different drought conditions, flowers in different developmental phases display differential sets of drought-responsive genes (DTGs), including those that are enriched in different GO functional categories, such as transcriptional regulation and response to stresses (early phase), lipid storage (middle phase), and pollen and seed development and metabolic processes (late phase). Some gene families have different members induced at different floral phases, suggesting that similar biochemical functions are carried out by distinct members. Developmentally-regulated genes (DVGs) with differential expression among the three floral phases belong to GO terms that are similar between water conditions, such as development and reproduction, metabolism and transport, and signaling and stress response. However, for different water conditions, such similar GO terms correspond to either distinct gene families or different members of a gene family, suggesting that drought affects the expression of distinct families or family members during reproductive development. A further comparison among transcriptomes of tissues collected on different days after treatment identifies differential gene expression, suggesting age-related genes (ARGs) might reflect the changes in the overall plant physiology in addition to drought response and development. CONCLUSION: Together, our study provides new insights into global transcriptome reprogramming and candidate genes for drought response, flower development, aging and coordination among these complex biological processes.

Improving MRI-based analysis of brain structural changes in patients with hypertension via a privileged information learning algorithm.

Hypertension can lead to changes in the brain structure and function, and different blood pressure levels (2017ACC/AHA) have different effects on brain structure. It is important to analyze these changes by machine learning methods, and various characteristics can provide rich information for the analysis of these changes. However, multiple feature extraction involves complex data processing. How to make a single feature achieve the same diagnosis effect as multiple features do is worth of study. Kernel ridge regression (KRR) is a kind of machine learning method, which shows faster learning speed and generalization ability in classification tasks. In order to knowledge transfer, we use privileged information (PI) to transfer information of multiple types of feature to single feature. This allows only one feature type to be used during the test stage. In the process of feature fusion, we need to consider all the samples' attribution making the classifier better. In this work, we propose a multi-kernel KRR+ framework based on self-paced learning to analyze the changes of the brain structure in patients with different blood pressure levels. Specifically, one kind of a feature is taken as main feature, and other features are input into the multi-kernel KRR as PI. These two inputs are fed into the final KRR classifier together. In addition, a self-paced learning method is introduced into sample selecting to avoid training the classifier using samples with a large loss value firstly, which improves the generalization performance of the classifier. Experimental results show that the proposed method can make full use of the information of various features and achieve better classification performance. This shows self-paced learning based KRR can help analyze brain structure of patients with different blood pressure levels. The discriminative features may help clinicians to make judgments of hypertension degrees on brain MRI images.

Novel Phenylethanoid Glycosides Improve Hippocampal Synaptic Plasticity via the Cyclic Adenosine Monophosphate-CREB-Brain-Derived Neurotrophic Growth Factor Pathway in APP/PS1 Transgenic Mice.

INTRODUCTION: Alzheimer's disease (AD) is a major public health concern worldwide, but there are still no drugs available that treat it effectively. Previous studies have shown that phenylethanoid glycosides have pharmacological effects, which include anti-AD properties, but the underlying mechanisms by which they ameliorate AD symptoms remain unknown. METHODS: In this study, we used an APP/PS1 AD mouse model to explore the function and mechanisms underlying savatiside A (SA) and torenoside B (TB) in the treatment of AD. SA or TB (100 mg·kg-1·d-1) was orally administered to 7-month-old APP/PS1 mice for 4 weeks. Cognitive and memory functions were measured using behavioral experiments (including the Morris water maze test and the Y-maze spontaneous alternation test). Molecular biology experiments (including Western blotting, immunofluorescence, and enzyme-linked immunosorbent assays) were used to detect any corresponding changes in signaling pathways. RESULTS: The results showed that SA or TB treatment could significantly reduce cognitive impairment in APP/PS1 mice. We also showed that chronic treatment with SA/TB could prevent spine loss, synaptophysin immunoreactivity, and neuronal loss in mice, thereby improving synaptic plasticity and moderating learning and memory deficits. SA/TB administration also promoted the expression of synaptic proteins in APP/PS1 mouse brains and upregulated phosphorylation of proteins in the cyclic adenosine monophosphate (cAMP)/CREB/brain-derived neurotrophic growth factor (BDNF) pathway that are responsible for synaptic plasticity. Additionally, chronic SA/TB treatment increased the levels of BDNF and nerve growth factor (NGF) in the brains of APP/PS1 mice. Both astrocyte and microglia volumes, as well as the generation of amyloid ß, were also decreased in SA/TB-treated APP/PS1 mice compared to control APP/PS1 mice. CONCLUSION: In summary, SA/TB treatment was associated with activation of the cAMP/CREB/BDNF pathway and increased BDNF and NGF expression, indicating that SA/TB improves cognitive functioning via nerve regeneration. SA/TB is a promising candidate drug for the treatment of AD.

Non-commuting intentions during COVID-19 in Nanjing, China: A hybrid latent class modeling approach.

Non-commuting travel is essential for people to meet daily demands and regulate mental health, which is greatly disrupted due to the COVID-19 pandemic. To explore non-commuting intentions during COVID-19 across different groups of residents, this paper uses online survey data in Nanjing and constructs a hybrid latent class choice model that combines sociodemographic characteristics and psychological factors. Results showed that the respondents can be divided into two groups: the "cautious" group versus the "fearless" group. The "cautious" group with lower willingness to travel tend to be older, higher-income, higher-educated, female and full-time employees. Furthermore, the "cautious" group with higher perceived susceptibility is more obedient to government policies. In contrast, the "fearless" group is significantly affected by perceived severity and is more inclined to turn to personal protection against the pandemic. These results suggested that non-commuting trips were influenced not only by individual characteristics but also by psychological factors. Finally, the paper provides implications for the government to formulate COVID-19 management measures for the heterogeneity of different groups.

Investigating factors influencing takeout shopping demand under COVID-19: Generalized additive mixed models.

The COVID-19 pandemic severely hampered the freedom of shopping travel while increasing individuals' interest in takeout. Although many studies have examined takeout shopping, the available literature provides insufficient evidence on the factors influencing takeout shopping demand under the COVID-19. In this study, generalized additive mixed models were developed based on sampling data of takeout orders in Nanjing before, during, and post the pandemic to measure the associations between takeout shopping demand and neighborhood characteristics at the business circle scale. The results show that population density, house prices, road density, and catering all have a significant impact on takeout shopping demand, while the roles of land use (residential and company indexes) before and post the pandemic are opposite. Besides, the factors influencing the recovery of the demand before and after the pandemic were analyzed. These findings provide important insights into the development of the takeout industry in the post-pandemic era.

Inhibition of KIF20A by transcription factor IRF6 affects the progression of renal clear cell carcinoma.

BACKGROUND: Renal clear cell carcinoma (ccRCC) is one of the most common malignant tumors, whose incidence is increasing year by year. IRF6 plays an important role in the occurrence of tumors, although there is yet no report on its expression in ccRCC. METHODS: The expression of IRF6 and KIF20A in ccRCC was predicted by GEPIA and HAP databases. In addition, GEPIA database predicted the relationship between IRF6 and KIF20A expressions and the pathological staging, overall survival, and disease-free survival of ccRCC. The possible binding sites of IRF6 and KIF20A promoters were predicted by JASPAR database and verified by luciferase and ChIP assays. The specific effects of IRF6 on ccRCC cell proliferation, invasion and apoptosis were subsequently examined at both cellular level and animal level. RESULTS: The database predicted down-regulated IRF6 expression in renal carcinoma tissues and its correlation with poor prognosis. IRF6 overexpression inhibited cRCC cell proliferation, invasion and migration. In addition, up-regulated KIF20A expression in renal carcinoma tissues and its association with prognosis were also predicted. Interference with KIF20A inhibited the proliferation, invasion, and migration of ccRCC cells. Finally, we confirmed that KIF20A is a functional target of IRF6 and can partially reverse the effects of IRF6 on the proliferation, invasion and migration of ccRCC cells. CONCLUSION: Inhibition of KIF20A by transcription factor IRF6 affects cell proliferation, invasion and migration in renal clear cell carcinoma.

Molecular genetic analyses of abiotic stress responses during plant reproductive development.

Plant responses to abiotic stresses during vegetative growth have been extensively studied for many years. Daily environmental fluctuations can have dramatic effects on plant vegetative growth at multiple levels, resulting in molecular, cellular, physiological, and morphological changes. Plants are even more sensitive to environmental changes during reproductive stages. However, much less is known about how plants respond to abiotic stresses during reproduction. Fortunately, recent advances in this field have begun to provide clues about these important processes, which promise further understanding and a potential contribution to maximize crop yield under adverse environments. Here we summarize information from several plants, focusing on the possible mechanisms that plants use to cope with different types of abiotic stresses during reproductive development, and present a tentative molecular portrait of plant acclimation during reproductive stages. Additionally, we discuss strategies that plants use to balance between survival and productivity, with some comparison among different plants that have adapted to distinct environments.

Nitrogen-cycling microbial communities respond differently to nitrogen addition under two contrasting grassland soil types.

Introduction: The impact of nitrogen (N) deposition on the soil N-transforming process in grasslands necessitates further investigation into how N input influences the structural composition and diversity of soil N-cycling microbial communities across different grassland types. Methods: In this study, we selected two types of grassland soils in northwest Liaoning, temperate steppe and warm-temperate shrub, and conducted short-term N addition experiments using organic N, ammonium N, and nitrate N as sources with three concentration gradients to simulate N deposition. Illumina MiSeq sequencing technology was employed to sequence genes associated with N-cycling microbes including N-fixing, ammonia-oxidizing and denitrifying bacteria, and ammonia-oxidizing archaea. Results and discussion: The results revealed significant alterations in the structural composition and diversity of the N-cycling microbial community due to N addition, but the response of soil microorganisms varied inconsistent among different grassland types. Ammonium transformation rates had a greater impact on soils from temperate steppes while nitrification rates were more influential for soils from warm-temperate shrubs. Furthermore, the influence of the type of N source on soil N-cycling microorganisms outweighed that of its quantity applied. The ammonium type of nitrogen source is considered the most influential driving factor affecting changes in the structure of the microbial community involved in nitrogen transformation, while the amount of low nitrogen applied primarily determines the composition of soil bacterial communities engaged in nitrogen fixation and nitrification. Different groups of N-cycling microorganisms exhibited distinct responses to varying levels of nitrogen addition with a positive correlation observed between their composition, diversity, and environmental factors examined. Overall findings suggest that short-term nitrogen deposition may sustain dominant processes such as soil-N fixation within grasslands over an extended period without causing significant negative effects on northwestern Liaoning's grassland ecosystems within the next decade.

Regulation of micro- and small-exon retention and other splicing processes by GRP20 for flower development.

Pre-mRNA splicing is crucial for gene expression and depends on the spliceosome and splicing factors. Plant exons have an average size of ~180 nucleotides and typically contain motifs for interactions with spliceosome and splicing factors. Micro exons (<51 nucleotides) are found widely in eukaryotes and in genes for plant development and environmental responses. However, little is known about transcript-specific regulation of splicing in plants and about the regulators for micro exon splicing. Here we report that glycine-rich protein 20 (GRP20) is an RNA-binding protein and required for splicing of ~2,100 genes including those functioning in flower development and/or environmental responses. Specifically, GRP20 is required for micro-exon retention in transcripts of floral homeotic genes; these micro exons are conserved across angiosperms. GRP20 is also important for small-exon (51-100 nucleotides) splicing. In addition, GRP20 is required for flower development. Furthermore, GRP20 binds to poly-purine motifs in micro and small exons and a spliceosome component; both RNA binding and spliceosome interaction are important for flower development and micro-exon retention. Our results provide new insights into the mechanisms of micro-exon retention in flower development.

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surgeries. Due to the anatomical complexity and individual variability of the quadratus lumborum muscle (QLM) on ultrasound images, nerve blocks heavily rely on anesthesiologist experience. Therefore, using artificial intelligence (AI) to identify different tissue regions in ultrasound images is crucial. In our study, we retrospectively collected 112 patients (3162 images) and developed a deep learning model named Q-VUM, which is a U-shaped network based on the Visual Geometry Group 16 (VGG16) network. Q-VUM precisely segments various tissues, including the QLM, the external oblique muscle, the internal oblique muscle, the transversus abdominis muscle (collectively referred to as the EIT), and the bones. Furthermore, we evaluated Q-VUM. Our model demonstrated robust performance, achieving mean intersection over union (mIoU), mean pixel accuracy, dice coefficient, and accuracy values of 0.734, 0.829, 0.841, and 0.944, respectively. The IoU, recall, precision, and dice coefficient achieved for the QLM were 0.711, 0.813, 0.850, and 0.831, respectively. Additionally, the Q-VUM predictions showed that 85% of the pixels in the blocked area fell within the actual blocked area. Finally, our model exhibited stronger segmentation performance than did the common deep learning segmentation networks (0.734 vs. 0.720 and 0.720, respectively). In summary, we proposed a model named Q-VUM that can accurately identify the anatomical structure of the quadratus lumborum in real time. This model aids anesthesiologists in precisely locating the nerve block site, thereby reducing potential complications and enhancing the effectiveness of nerve block procedures.

Changes in grassland soil types lead to different characteristics of bacterial and fungal communities in Northwest Liaoning, China.

Introduction: Soil microbial communities are critical in regulating grassland biogeochemical cycles and ecosystem functions, but the mechanisms of how environmental factors affect changes in the structural composition and diversity of soil microbial communities in different grassland soil types is not fully understood in northwest Liaoning, China. Methods: We investigated the characteristics and drivers of bacterial and fungal communities in 4 grassland soil types with 11 sites across this region using high-throughput Illumina sequencing. Results and Discussion: Actinobacteria and Ascomycota were the dominant phyla of bacterial and fungal communities, respectively, but their relative abundances were not significantly different among different grassland soil types. The abundance, number of OTUs, number of species and diversity of both bacterial and fungal communities in warm and temperate ecotone soil were the highest, while the warm-temperate shrub soil had the lowest microbial diversity. Besides, environmental factors were not significantly correlated with soil bacterial Alpha diversity index. However, there was a highly significant negative correlation between soil pH and Shannon index of fungal communities, and a highly significant positive correlation between plant cover and Chao1 index as well as Observed species of fungal communities. Analysis of similarities showed that the structural composition of microbial communities differed significantly among different grassland soil types. Meanwhile, the microbial community structure of temperate steppe-sandy soil was significantly different from that of other grassland soil types. Redundancy analysis revealed that soil total nitrogen content, pH and conductivity were important influencing factors causing changes in soil bacterial communities, while soil organic carbon, total nitrogen content and conductivity mainly drove the differentiation of soil fungal communities. In addition, the degree of connection in the soil bacterial network of grassland was much higher than that in the fungal network and soil bacterial and fungal communities were inconsistently limited by environmental factors. Our results showed that the microbial community structure, composition and diversity of different grassland soil types in northwest Liaoning differed significantly and were significantly influenced by environmental factors. Microbial community structure and the observation of soil total nitrogen and organic carbon content can predict the health changes of grassland ecosystems to a certain extent.

Safety assessment of Enterococcus lactis based on comparative genomics and phenotypic analysis.

Enterococcus faecium is sometimes used in food production; however, its acquisition of antibiotic resistance has become an alarming health concern. The E. lactis species is closely related to E. faecium and has good probiotic potential. This study aimed to investigate the antibiotic resistance of E. lactis. We analyzed the antibiotic resistance phenotype and whole-genome sequences of 60 E. lactis isolates (23, 29, and 8 isolates from dairy products, Rice wine Koji, and human feces, respectively). These isolates showed varying degree of resistance to 13 antibiotics, and were sensitive to ampicillin and linezolid. The E. lactis genomes carried only a subset of commonly reported antibiotic resistance genes (ARGs) in E. faecium. Five ARGs were detected across the investigated E. lactis, including two universally present genes (msrC and AAC(6')-Ii) and three rarely detected ARGs (tet(L), tetM, and efmA). To identify other undescribed antibiotic resistance-encoding genes, a genome-wide association study was performed, returning 160 potential resistance genes that were associated with six antibiotics, namely chloramphenicol, vancomycin, clindamycin, erythromycin, quinupristin-dalfopristin, and rifampicin. Only around one-third of these genes encode known biological functions, including cellular metabolism, membrane transport, and DNA synthesis. This work identified interesting targets for future study of antibiotic resistance in E. lactis. The fact that the lower number of ARGs present in E. lactis supports that it may be an alternative to E. faecalis for use in the food industry. Data generated in this work is of interest to the dairy industry.

A network pharmacological-based study of the mechanism of Liuwei Dihuang pill in the treatment of chronic kidney disease.

BACKGROUND: Chronic kidney disease (CKD) is a progressive disease that poses a huge economic burden to society. Liuwei Dihuanng pill is an effective treatment for chronic kidney disease, but its treatment mechanism is unclear. The rapid development of network pharmacology has provided new strategies for studying Chinese medicine. METHOD: The traditional Chinese medicine systems pharmacology database and analysis platform was used to obtain the bioactive components and targets of Liuwei Dihuanng pill. The sources for the CKD-related targets were then obtained from the Genecards, OMIM, TTD, and DisGeNET databases. R was used to identify the intersecting genes for Liuwei Dihuang pill and CKD-related targets. Analysis of protein-protein interactions (PPI) was performed using STRING, and PPI networks and drug-component-target networks were constructed using Cytoscape software. Kyoto encyclopedia of genes and genomes pathway and gene ontology enrichment analyses were performed using R. Finally, molecular docking was performed to determine the binding activity between bioactive components and the targets. RESULT: After screening and data de-duplication of 74 active components, 209 drug targets, and 14,794 disease targets, a total of 204 drug-disease targets were acquired. Subsequently, a drug-component-target network and PPI network were established. The primary components of Liuwei Dihuang pill included quercetin, stigmasterol, kaempferol, beta-sitosterol, tetrahydroalstonine, kadsurenone, hederagenin, hancinone C, diosgenin, and sitosterol. In addition, JUN, AKT1, TP53, RELA, MAPK1, FOS, TNF, IL6, ESR1, and RXRA were identified as the main targets. Gene ontology function enrichment analysis revealed that these targets were involved in reactive oxygen species metabolic processes, responses to metal ions and to chemical stimuli, G protein-coupled amine receptor activity, and nuclear factor receptor activity. Kyoto encyclopedia of genes and genomes enrichment analysis showed that these targets were involved in the AGE-RAGE signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and so on. Molecular docking results indicated good binding activity between the core targets and core components. CONCLUSION: The potential mechanism of Liuwei Dihuanng pill in the treatment of CKD was preliminarily discussed in this study, providing a theoretical basis and evidence for further experimental research.

Different responses of soil fungal and bacterial communities to nitrogen addition in a forest grassland ecotone.

Introduction: Continuous nitrogen deposition increases the nitrogen content of terrestrial ecosystem and affects the geochemical cycle of soil nitrogen. Forest-grassland ecotone is the interface area of forest and grassland and is sensitive to global climate change. However, the structure composition and diversity of soil microbial communities and their relationship with soil environmental factors at increasing nitrogen deposition have not been sufficiently studied in forest-grassland ecotone. Methods: In this study, experiments were carried out with four nitrogen addition treatments (0 kgN·hm-2·a-1, 10 kgN·hm-2·a-1, 20 kgN·hm-2·a-1 and 40 kgN·hm-2·a-1) to simulate nitrogen deposition in a forest-grassland ecotone in northwest Liaoning Province, China. High-throughput sequencing and qPCR technologies were used to analyze the composition, structure, and diversity characteristics of the soil microbial communities under different levels of nitrogen addition. Results and discussion: The results showed that soil pH decreased significantly at increasing nitrogen concentrations, and the total nitrogen and ammonium nitrogen contents first increased and then decreased, which were significantly higher in the N10 treatment than in other treatments (N:0.32 ~ 0.48 g/kg; NH4+-N: 11.54 ~ 13 mg/kg). With the increase in nitrogen concentration, the net nitrogen mineralization, nitrification, and ammoniation rates decreased. The addition of nitrogen had no significant effect on the diversity and structure of the fungal community, while the diversity of the bacterial community decreased significantly at increasing nitrogen concentrations. Ascomycetes and Actinomycetes were the dominant fungal and bacterial phyla, respectively. The relative abundance of Ascomycetes was negatively correlated with total nitrogen content, while that of Actinomycetes was positively correlated with soil pH. The fungal community diversity was significantly negatively correlated with nitrate nitrogen, while the diversity of the bacterial community was significantly positively correlated with soil pH. No significant differences in the abundance of functional genes related to soil nitrogen transformations under the different treatments were observed. Overall, the distribution pattern and driving factors were different in soil microbial communities in a forest-grassland ecotone in northwest Liaoning. Our study enriches research content related to factors that affect the forest-grassland ecotone.

Invasion by Cenchrus spinifex changes the soil microbial community structure in a sandy grassland ecosystem.

Continuous nitrogen deposition increases the nitrogen content of terrestrial ecosystems and alters the soil nitrogen cycling process. Invasive plants have strong environmental adaptability, which can not only affect the composition and diversity of soil microbial community but also significantly affect the transformation process of soil nitrogen, leading to successful invasion. Currently, research on invasive plant soil ecosystems mainly focused on changes in soil nutrients and soil microorganisms. As an invasive annual grass weed with strong ecological adaptability, the impact of Cenchrus spinifex at different growth periods on soil environment and soil microbial structure composition and diversity in sandy grassland ecosystems is still unclear. In this study, soil samples were collected from four habitats with different degrees of invasion in situ during the vegetation and reproductive growth periods of Cenchrus spinifex. High-throughput sequencing and qPCR technology were used to analyze the changes in the composition, structure and diversity characteristics of the soil microbial communities during Cenchrus spinifex invasion. The results indicated that Cenchrus spinifex invasion had different effects on the soil environment at different growth periods, and Cenchrus spinifex had a preference for the utilization of ammonium nitrogen during vegetation growth period. Moreover, Cenchrus spinifex invasion significantly changed the composition and structure of soil bacterial communities, and the response of soil bacterial and fungal communities to the invasion was inconsistent. Additionally, the bacterial network was more stable than the fungal network. At different growth periods, Cenchrus spinifex had a significant impact on the key microbial communities of soil nitrogen cycling. The invasion increased the abundance of nifH and AOA-amoA, while decreased the abundance of AOA-amoB. Alkaline hydrolyzed nitrogen, total nitrogen and total phosphorus content were key factors that affect vegetation growth period and change the key microbial communities of nitrogen cycling. Alkaline hydrolyzed nitrogen, total phosphorus and organic carbon were key factors in reproductive growth period that alter the nitrogen cycling of key microbial communities.

Bifidobacterium animalis subsp. lactis Probio-M8 undergoes host adaptive evolution by glcU mutation and translocates to the infant's gut via oral-/entero-mammary routes through lactation.

BACKGROUND: Most previous studies attempting to prove the phenomenon of mother-to-infant microbiota transmission were observational, performed only at genus/species-level resolution, and relied entirely on non-culture-based methodologies, impeding interpretation. RESULTS: This work aimed to use a biomarker strain, Bifidobacterium animalis subsp. lactis Probio-M8 (M8), to directly evaluate the vertical transmission of maternally ingested bacteria by integrated culture-dependent/-independent methods. Our culture and metagenomics results showed that small amounts of maternally ingested bacteria could translocate to the infant gut via oral-/entero-mammary routes through lactation. Interestingly, many mother-infant-pair-recovered M8 homologous isolates exhibited high-frequency nonsynonymous mutations in a sugar transporter gene (glcU) and altered carbohydrate utilization preference/capacity compared with non-mutant isolates, suggesting that M8 underwent adaptive evolution for better survival in simple sugar-deprived lower gut environments. CONCLUSIONS: This study presented direct and strain-level evidence of mother-to-infant bacterial transmission through lactation and provided insights into the impact of milk microbiota on infant gut colonization. Video Abstract.

Analysis of factors influencing delivery e-bikes' red-light running behavior: A correlated mixed binary logit approach.

The red-light running (RLR) behavior of delivery e-bike (DEB) riders in cities has become the primary cause of traffic accidents associated with this group at signalized intersections. This study aimed to explore the influencing factors of red light running behavior and identify the differences between the DEB riders and the ordinary e-bike (OEB) riders to aid the development of countermeasures. In this study, the mixed (random parameter) binary logistic model was employed to capture the effects of unobserved heterogeneity. With this approach, factors including individual characteristics, behavioral variables, characteristics of signalized intersections, and the traffic environment were examined. Additionally, to account for the combined influence on the RLR occurrence, mixed logit framework was developed to reveal the correlations among the random parameters. The data of e-bike riders' crossing behaviors at four signalized intersections in Xi'an, China were collected, and 3335 samples were recorded. The results indicated showed that DEB riders are more likely to run red lights than OEB riders. Factors that affect RLR behaviors of the two groups are different. Factors associated with the unobserved heterogeneity include red-light stage, observation time, age and waiting position of the rider. The joint influence among random parameters further illustrates the complexity of the contributing factors of riders' crossing behavior. Results from the models provide insights into the development of intervention systems to improve the traffic safety of e-bike riders at intersections.

CT-based peritumoral radiomics signatures for malignancy grading of clear cell renal cell carcinoma.

OBJECTIVE: To evaluate the efficiency of CT-based peritumoral radiomics signatures of clear cell renal cell carcinoma (ccRCC) for malignancy grading in preoperative prediction. MATERIALS AND METHODS: 203 patients with pathologically confirmed as ccRCC were retrospectively enrolled in this study. All patients were categorized into training set (n = 122) and validation set (n = 81). For each patient, two types of volumes of interest (VOI) were masked on CT images. One type of VOIs was defined as the tumor mass volume (TMV), which was masked by radiologists delineating the outline of all contiguous slices of the entire tumor, while the other type defined as the peritumoral tumor volume (PTV), which was automatically created by an image morphological method. 1760 radiomics features were calculated from each VOI, and then the discriminative radiomics features were selected by Pearson correlation analysis for reproducibility and redundancy. These selected features were investigated their validity for building radiomics signatures by mRMR feature ranking method. Finally, the top ranked features, which were used as radiomics signatures, were input into a classifier for malignancy grading. The prediction performance was evaluated by receiver operating characteristic (ROC) curve in an independent validation cohort. RESULTS: The radiomics signatures of PTV showed a better performance on malignancy grade prediction of ccRCC with AUC of 0.807 (95% CI 0.800-0.834) in train data and 0.848 (95% CI 0.760-0.936) in validation data, while the radiomics signatures of TMV with AUC of 0.773 (95% CI 0.744-0.802) in train data and 0.810 (95% CI 0.706-0.914) in validation data. CONCLUSION: The CT-based peritumoral radiomics signature is a potential way to be used as a noninvasive tool to preoperatively predict the malignancy grades of ccRCC.

Transcriptional regulation of bark freezing tolerance in apple (Malus domestica Borkh.).

Freezing tolerance is a significant trait in plants that grow in cold environments and survive through the winter. Apple (Malus domestica Borkh.) is a cold-tolerant fruit tree, and the cold tolerance of its bark is important for its survival at low temperatures. However, little is known about the gene activity related to its freezing tolerance. To better understand the gene expression and regulation properties of freezing tolerance in dormant apple trees, we analyzed the transcriptomic divergences in the bark from 1-year-old branches of two apple cultivars, "Golden Delicious" (G) and "Jinhong" (H), which have different levels of cold resistance, under chilling and freezing treatments. "H" can safely overwinter below -30 °C in extremely low-temperature regions, whereas "G" experiences severe freezing damage and death in similar environments. Based on 28 bark transcriptomes (from the epidermis, phloem, and cambium) from 1-year-old branches under seven temperature treatments (from 4 to -29 °C), we identified 4173 and 7734 differentially expressed genes (DEGs) in "G" and "H", respectively, between the chilling and freezing treatments. A gene coexpression network was constructed according to this expression information using weighted gene correlation network analysis (WGCNA), and seven biologically meaningful coexpression modules were identified from the network. The expression profiles of the genes from these modules suggested the gene regulatory pathways that are responsible for the chilling and freezing stress responses of "G" and/or "H." Module 7 was probably related to freezing acclimation and freezing damage in "H" at the lower temperatures. This module contained more interconnected hub transcription factors (TFs) and cold-responsive genes (CORs). Modules 6 and 7 contained C-repeat binding factor (CBF) TFs, and many CBF-dependent homologs were identified as hub genes. We also found that some hub TFs had higher intramodular connectivity (KME) and gene significance (GS) than CBFs. Specifically, most hub TFs in modules 6 and 7 were activated at the beginning of the early freezing stress phase and maintained upregulated expression during the whole freezing stress period in "G" and "H". The upregulation of DEGs related to methionine and carbohydrate biosynthetic processes in "H" under more severe freezing stress supported the maintenance of homeostasis in the cellular membrane. This study improves our understanding of the transcriptional regulation patterns underlying freezing tolerance in the bark of apple branches.

Effects of Psychological Factors on Modal Shift from Car to Dockless Bike Sharing: A Case Study of Nanjing, China.

The emergence of dockless bike sharing in recent years has reduced the usage of private cars, especially usage for short-distance trips (within 2 km). In this paper, a modified technology acceptance model (TAM) is proposed to investigate from the psychological perspective drivers' willingness to shift to dockless bike sharing. The modified TAM includes the perceived usefulness of dockless bike sharing, perceived ease-of-use of dockless bike sharing, perceived health of dockless bike sharing, attitudes toward dockless bike sharing, and willingness to shift to dockless bike sharing. Data are obtained through offline communications with car drivers. The results show that two-thirds of car drivers are willing to use dockless bike sharing in short-distance trips. Perceived health, perceived ease-of-use, and perceived usefulness have significant positive effects on people's attitudes toward dockless bike sharing. As expected, people's attitudes toward dockless bike sharing are positively correlated with their willingness to shift. Policy implications are discussed to prompt the modal shift from private cars to dockless bike sharing according to the results.