bluuebunny/crossref_metadata_2025 huggingface dataset:
Hsa_circ_0031608: A Potential Modulator of VSMC Phenotype in the Rupture of Intracranial Aneurysms
Authors: Wang Chuanchuan , Luo Yin , Tang Haishuang , Yan Yazhou , Chang Xiaozan , Zhao Rui , Li Qiang , Yang Pengfei , Hong Bo , Xu Yi , Huang Qinghai , Liu Jianmin
Published: March 2022

Background and Purpose

Phenotypic modulation of vascular smooth muscle cells (VSMCs) plays an important role in the development of intracranial aneurysms (IAs). Growing evidence has demonstrated that circular RNAs (circRNAs) may serve as a potential modulator of VSMC phenotype in various vascular diseases. This study aimed to assess the potential function of circRNAs in the rupture of IAs and VSMC phenotypic modulation.

Methods

Using surgically dissected human ruptured (n = 8) and unruptured (n = 8) IA lesions, differentially expressed circRNAs were screened by transcriptomic sequencing and verified using qRT-PCR. Based on the screened circRNA, we predicted and screened the combined miRNA and downstream mRNAs to construct circRNA-miRNA-mRNA networks. Further in vitro experiments were performed to investigate the relationship between the validated circRNA and the phenotypic switching of VSMCs.

Results

We found 1,373 differentially expressed genes in ruptured versus unruptured aneurysms. The top five dysregulated circRNAs were selected for qRT-PCR validation. We found hsa_circ_0031608 was both highly expressed in ruptured IAs and pro-inflammatory transformation of VSMCs. Then, a regulatory circRNA-miRNA-mRNA with one circRNA node, six miRNA nodes, and 84 mRNA nodes was constructed. GO analysis and KEGG pathway enrichment analysis were performed on mRNAs in the network. Then, a PPI network was built based on these mRNAs and five hub genes were identified (FOXO3, DICER1, CCND2, IGF1R, and TNRC6B) by the cytoHubba plugin in Cytoscape software. In vitro, overexpression of hsa_circ_0031608 influenced the expression of VSMC phenotypic markers validated by qPCR and Western blotting. Furthermore, hsa_circ_0031608 promoted the migration and proliferation capacity of VSMCs.

Conclusion

hsa_circ_0031608 regulated the phenotypic modulation of VSMCs and played an important role in the rupture of IAs. The specific mechanism should be further studied and confirmed.
Prognostic Value of Prognostic Nutritional Index in Patients With Colorectal Cancer Undergoing Surgical Treatment
Authors: Xie Hailun , Wei Lishuang , Yuan Guanghui , Liu Mingxiang , Tang Shuangyi , Gan Jialiang
Published: March 2022

Background

To investigate the relationship between prognostic nutritional index (PNI) and the survival of patients with colorectal cancer (CRC) undergoing surgical treatment.

Methods

In total 1,014 CRC patients who underwent surgical treatment were enrolled. Logistic regression analysis was used to identify the features that influenced postoperative complications in CRC patients. Restricted cubic spline was used to assess the dose-response relationship between PNI and survival in CRC patients. Kaplan-Meier method and log-rank test were used to compare survival differences between groups of CRC patients. Cox proportional risk regression models was used to assess independent risk factors for progression-free survival (PFS) and overall survival (OS) of CRC patients.

Results

Low PNI was associated with high tumor burden, invasive pathological features, and poor host status. Compared with patients with high PNI, patients with low PNI have a higher incidence of complications and longer hospital stay. Low PNI was an independent risk factor for postoperative complications in CRC patients. for every SD increased in PNI, the risk of poor prognosis for CRC patients was reduced by 2.3% (HR = 0.977, 95%CI = 0.962–0.993, p = 0.004) in PFS, and 2.3% (HR = 0.977, 95%CI = 0.962–0.993, p = 0.004) in OS. PNI was an independent prognostic factor affecting the PFS and OS of CRC patients. Finally, we constructed the PNI-based nomograms to predict postoperative complications, 1–5 years PFS and OS in CRC patients. Concordance index and calibration curve indicated that the PNI-based nomograms have moderate prediction accuracy.

Conclusion

PNI is an independent risk factor affecting postoperative complications, PFS and OS of CRC patients, and is a useful supplement to the TNM stage.
Prevention of High-Fat Diet-Induced Hypercholesterolemia by Lactobacillus reuteri Fn041 Through Promoting Cholesterol and Bile Salt Excretion and Intestinal Mucosal Barrier Functions
Authors: Lu Mengyao , Sun Jin , Zhao Yuning , Zhang Haowen , Li Xinyue , Zhou Jingbo , Dang Hongyang , Zhang Jidong , Huang Wenjing , Qi Ce , Li Duo
Published: March 2022

Objectives:

Lactobacillus reuteri Fn041 (Fn041) is a probiotic isolated from immunoglobulin A coated microbiota in the human breast milk of Gannan in China with a low incidence of hypercholesterolemia. This study aims to explore the role and mechanism of Fn041 in preventing hypercholesterolemia caused by a high-fat diet in mice.

Methods

C57BL/6N mice were fed a low-fat diet or a high-fat diet and gavage with Fn041 and Lactobacillus rhamnosus GG (LGG) for 8 weeks.

Results

Both Fn041 and LGG prevented the occurrence of hypercholesterolemia, liver and testicular fat accumulation. In addition, a high-fat diet causes intestinal dysbiosis and mucosal barrier damage, which is associated with hypercholesterolemia. Fn041 prevented the high-fat diet-induced reduction in alpha diversity of intestinal microbiota and intestinal mucosal barrier damage. Fn041 treatment significantly increased fecal total cholesterol and total bile acids.

Conclusions

Fn041 prevented hypercholesterolemia by enhancing cholesterol excretion and mucosal barrier function.
Correlation Between IVIM-DWI Parameters and Pathological Classification of Idiopathic Orbital Inflammatory Pseudotumors: A Preliminary Study
Authors: Pu Jian , Liang Yi , He Qian , Shao Ju-Wei , Zhou Min-Jie , Xiang Shu-Tian , Li Ying-Wen , Li Jian-Bo , Ji Shun-Jun
Published: March 2022

Objective

To investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and the pathological classification of idiopathic orbital inflammatory pseudotumors (IOIPs).

Methods

Nineteen patients who were diagnosed with IOIPs (a total of 24 affected eyes) between November 2018 and December 2020 were included in the study. All the patients underwent magnetic resonance imaging orbital plain scans and IVIM-DWI multiparameter scans before an operation. The true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were obtained. Based on histopathology, the lesions were divided into three types: lymphocytic infiltration, fibrosclerotic, and mixed. The correlation between IVIM-DWI parameters and pathological classification was tested with the histopathological results as the gold standard. The data were analyzed using SPSS version 17.0, with P < 0.05 defined as significant.

Results

Among the 19 patients (24 eyes) affected by IOIP, there were no significant differences between IOIP pathological classification and gender or age (P > 0.05). There were statistically significant differences between the D and f values for different pathological types of IOIP and IVIM parameters (P < 0.05), and there was no significant difference in D* value between the different pathological types (P > 0.05).

Conclusion

The D and f values showed correlation with different types of IOIP, and the sensitivity of the D value was higher than that of the f value. The D* value showed no significant distinction between pathological types of IOIP.
Development and Validation of a Novel Prognostic Nomogram Combined With Desmoplastic Reaction for Synchronous Colorectal Peritoneal Metastasis
Authors: Qin Xiusen , Zhao Mingpeng , Deng Weihao , Huang Yan , Cheng Zhiqiang , Chung Jacqueline Pui Wah , Chen Xufei , Yang Keli , Chan David Yiu Leung , Wang Hui
Published: March 2022

Purpose

The prognostic value of desmoplastic reaction (DR) has not been investigated in colorectal cancer (CRC) patients with synchronous peritoneal metastasis (SPM). The present study aimed to identify whether DR can predict overall survival (OS) and develop a novel prognostic nomogram.

Methods

CRC patients with SPM were enrolled from a single center between July 2007 and July 2019. DR patterns in primary tumors were classified as mature, intermediate, or immature according to the existence and absence of keloid-like collagen or myxoid stroma. Cox regression analysis was used to identify independent factors associated with OS and a nomogram was developed subsequently.

Results

One hundred ninety-eight and 99 patients were randomly allocated into the training and validation groups. The median OS in the training group was 36, 25, and 12 months in mature, intermediate, and immature DR categories, respectively. Age, T stage, extraperitoneal metastasis, differentiation, cytoreductive surgery (CRS), hyperthermic intraperitoneal chemotherapy (HIPEC), and DR categorization were independent variables for OS, based on which the nomogram was developed. The C-index of the nomogram in the training and validation groups was 0.773 (95% CI 0.734–0.812) and 0.767 (95% CI 0.708–0.826). The calibration plots showed satisfactory agreement between the actual outcome and nomogram-predicted OS probabilities in the training and validation cohorts.

Conclusions

DR classification in the primary tumor is a potential prognostic index for CRC patients with SPM. The novel prognostic nomogram combined with DR classification has good discrimination and accuracy in predicting the OS for CRC patients with SPM.
Solitary Celiac Lymph Node Metastasis Has a Better Long-Term Survival Compared With Solitary Mediastinal Lymph Node Metastasis in Esophagectomy of Esophageal Squamous Cell Cancer: A Propensity Score Matching Analysis
Authors: Li Kun-Kun , Bao Tao , Wang Ying-Jian , Zhao Xiao-Long , Long Jiang , Xie Xian-Feng , Guo Wei
Published: March 2022

Background

The prognostic benefit of extensive lymphadenectomy remains controversial in esophageal squamous cell carcinoma (ESCC). The purpose of this retrospective study was to investigate the potential effect of solitary mediastinal (SM) lymph node metastasis and solitary celiac (SC) lymph node metastasis on the short- and long-term outcomes for patients who underwent minimally invasive McKeown esophagectomy.

Methods

From September 2009 to December 2020, a total of 934 cases were diagnosed with ESCC and underwent minimally invasive McKeown esophagectomy in our department; 223 cases met the inclusion and exclusion criteria. Propensity score matching (PSM) was utilized to contrast the postoperative results and long-term survival of Group 1 (SM) and Group 2 (SC). Univariate and multivariate Cox proportional hazards regression analyses were used on possible predictors of survival.

Results

One hundred forty-seven patients were available for outcome comparison after PSM. The postoperative results were not significantly different between the two groups. In terms of long-term survival, the 5-year disease-free survival (DFS) was 37.6% and 57.3% (p = 0.191) and 5-year disease-specific survival (DSS) was 39.7% and 68.4% (p = 0.028) for Group 1 (SM) and Group 2 (SC), respectively. Univariate and multivariate Cox proportional hazards regression analyses showed that body mass index (BMI), pathologic stage (pStage), and SC/SM grouping had significant hazard ratios (HRs), which suggested that SC is associated with better DSS.

Conclusion

This cohort study showed that SC lymph node metastasis has a better long-term survival compared with SM lymph node metastasis in esophagectomy of ESCC. The results challenge the current understanding and need confirmation in further research.
ACE2 Expression in Organotypic Human Airway Epithelial Cultures and Airway Biopsies
Authors: Chen Qianyu , Langenbach Shenna , Li Meina , Xia Yuxiu C. , Gao Xumei , Gartner Matthew J. , Pharo Elizabeth A. , Williams Sinéad M. , Todd Shawn , Clarke Nadeene , Ranganathan Sarath , Baker Michelle L. , Subbarao Kanta , Stewart Alastair G.
Published: March 2022

Coronavirus disease 2019 (COVID-19) caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an acute respiratory disease with systemic complications. Therapeutic strategies for COVID-19, including repurposing (partially) developed drugs are urgently needed, regardless of the increasingly successful vaccination outcomes. We characterized two-dimensional (2D) and three-dimensional models (3D) to establish a physiologically relevant airway epithelial model with potential for investigating SARS-CoV-2 therapeutics. Human airway basal epithelial cells maintained in submerged 2D culture were used at low passage to retain the capacity to differentiate into ciliated, club, and goblet cells in both air-liquid interface culture (ALI) and airway organoid cultures, which were then analyzed for cell phenotype makers. Airway biopsies from non-asthmatic and asthmatic donors enabled comparative evaluation of the level and distribution of immunoreactive angiotensin-converting enzyme 2 (ACE2). ACE2 and transmembrane serine proteinase 2 (TMPRSS2) mRNA were expressed in ALI and airway organoids at levels similar to those of native (i.e., non-cultured) human bronchial epithelial cells, whereas furin expression was more faithfully represented in ALI. ACE2 was mainly localized to ciliated and basal epithelial cells in human airway biopsies, ALI, and airway organoids. Cystic fibrosis appeared to have no influence on ACE2 gene expression. Neither asthma nor smoking status had consistent marked influence on the expression or distribution of ACE2 in airway biopsies. SARS-CoV-2 infection of ALI cultures did not increase the levels of selected cytokines. Organotypic, and particularly ALI airway cultures are useful and practical tools for investigation of SARS-CoV-2 infection and evaluating the clinical potential of therapeutics for COVID-19.
A Mini-Review of Flavone Isomers Apigenin and Genistein in Prostate Cancer Treatment
Authors: Ji Xiaozhen , Liu Kai , Li Qingyue , Shen Qun , Han Fangxuan , Ye Qingmei , Zheng Caijuan
Published: March 2022

The initial responses to standard chemotherapies among prostate cancer (PCa) patients are usually significant, while most of them will finally develop drug resistance, rendering them with limited therapies. To discover new regimens for the treatment of PCa including resistant PCa, natural products, the richest source of bioactive compounds, can serve as a library for screening and identifying promising candidates, and flavones such as apigenin and genistein have been used in lab and clinical trials for treating PCa over decades. In this mini-review, we take a look into the progress of apigenin and genistein, which are isomers, in treating PCa in the past decade. While possessing very similar structure, these two isomers can both target the same signaling pathways; they also are found to work differently in PCa cells. Given that more combinations are being developed and tested, genistein appears to be the more promising option to be approved. The anticancer efficacies of these two flavones can be confirmed by in-vitro and in-vivo studies, and their applications remain to be validated in clinical trials. Information gained in this work may provide important information for new drug development and the potential application of apigenin and genistein in treating PCa.
Is the Anisotropic Tilt Angle Necessary in the Turbulence Spectrum of Refractive-Index Fluctuations?
Authors: Zhai Chao
Published: March 2022

With the deepening of atmospheric turbulence research, scientists have discovered that the anisotropy of turbulence cells cannot be ignored. The anisotropic non-Kolmogorov turbulence model is more in line with the actual situation of atmospheric turbulence. However, the recent experimental results of Korotkova et al. and Beason et al. display that the turbulence cell has an anisotropic tilt angle, that is, the long axis of the turbulence cell may not be horizontal to the ground but has a certain angle with the ground. Therefore, it is urgent to analyze whether the anisotropic tilt angle is necessary in the turbulence spectrum. In this study, we develop the anisotropic non-Kolmogorov turbulence spectra for the horizontal and vertical links in the presence of the anisotropic tilt angle. Then, based on these spectra, the analytical expressions of the scintillation index for the horizontal and vertical links are derived under weak fluctuation condition. The results indicate that the anisotropic tilt angle is necessary in the vertical link but not in the horizontal link.
Contrastive Graph Learning for Social Recommendation
Authors: Zhang Yongshuai , Huang Jiajin , Li Mi , Yang Jian
Published: March 2022

Owing to the strength in learning representation of the high-order connectivity of graph neural networks (GNN), GNN-based collaborative filtering has been widely adopted in recommender systems. Furthermore, to overcome the data sparsity problem, some recent GNN-based models attempt to incorporate social information and to design contrastive learning as an auxiliary task to assist the primary recommendation task. Existing GNN and contrastive-learning-based recommendation models learn user and item representations in a symmetrical way and utilize social information and contrastive learning in a complex manner. The above two strategies lead to these models being either ineffective for datasets with a serious imbalance between users and items or inefficient for datasets with too many users and items. In this work, we propose a contrastive graph learning (CGL) model, which combines social information and contrastive learning in a simple and powerful way. CGL consists of three modules: diffusion, readout, and prediction. The diffusion module recursively aggregates and integrates social information and interest information to learn representations of users and items. The readout module takes the average value of user embeddings from all diffusion layers and item embeddings at the last diffusion layer as readouts of users and items, respectively. The prediction module calculates prediction rating scores with an interest graph to emphasize interest information. Three different losses are designed to ensure the function of each module. Extensive experiments on three benchmark datasets are implemented to validate the effectiveness of our model.
A Useful Blood Flow Restriction Training Risk Stratification for Exercise and Rehabilitation
Authors: Nascimento Dahan da Cunha , Rolnick Nicholas , Neto Ivo Vieira de Sousa , Severin Richard , Beal Fabiani Lage Rodrigues
Published: March 2022

Blood flow restriction training (BFRT) is a modality with growing interest in the last decade and has been recognized as a critical tool in rehabilitation medicine, athletic and clinical populations. Besides its potential for positive benefits, BFRT has the capability to induce adverse responses. BFRT may evoke increased blood pressure, abnormal cardiovascular responses and impact vascular health. Furthermore, some important concerns with the use of BFRT exists for individuals with established cardiovascular disease (e.g., hypertension, diabetes mellitus, and chronic kidney disease patients). In addition, considering the potential risks of thrombosis promoted by BFRT in medically compromised populations, BFRT use warrants caution for patients that already display impaired blood coagulability, loss of antithrombotic mechanisms in the vessel wall, and stasis caused by immobility (e.g., COVID-19 patients, diabetes mellitus, hypertension, chronic kidney disease, cardiovascular disease, orthopedic post-surgery, anabolic steroid and ergogenic substance users, rheumatoid arthritis, and pregnant/postpartum women). To avoid untoward outcomes and ensure that BFRT is properly used, efficacy endpoints such as a questionnaire for risk stratification involving a review of the patient’s medical history, signs, and symptoms indicative of underlying pathology is strongly advised. Here we present a model for BFRT pre-participation screening to theoretically reduce risk by excluding people with comorbidities or medically complex histories that could unnecessarily heighten intra- and/or post-exercise occurrence of adverse events. We propose this risk stratification tool as a framework to allow clinicians to use their knowledge, skills and expertise to assess and manage any risks related to the delivery of an appropriate BFRT exercise program. The questionnaires for risk stratification are adapted to guide clinicians for the referral, assessment, and suggestion of other modalities/approaches if/when necessary. Finally, the risk stratification might serve as a guideline for clinical protocols and future randomized controlled trial studies.
The Role of Parietal Epithelial Cells in the Pathogenesis of Podocytopathy
Authors: Li Zhi-hang , Guo Xiao-yan , Quan Xiao-ying , Yang Chen , Liu Ze-jian , Su Hong-yong , An Ning , Liu Hua-feng
Published: March 2022

Podocytopathy is the most common feature of glomerular disorder characterized by podocyte injury- or dysfunction-induced excessive proteinuria, which ultimately develops into glomerulosclerosis and results in persistent loss of renal function. Due to the lack of self-renewal ability of podocytes, mild podocyte depletion triggers replacement and repair processes mostly driven by stem cells or resident parietal epithelial cells (PECs). In contrast, when podocyte recovery fails, activated PECs contribute to the establishment of glomerular lesions. Increasing evidence suggests that PECs, more than just bystanders, have a crucial role in various podocytopathies, including minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, diabetic nephropathy, IgA nephropathy, and lupus podocytopathy. In this review, we attempt to dissect the diverse role of PECs in the pathogenesis of podocytopathy based on currently available information.
Reticulate Evolution in AA-Genome Wild Rice in Australia
Authors: Hasan Sharmin , Furtado Agnelo , Henry Robert
Published: March 2022

The wild rice gene pool, i.e., AA-genome, in Australia is geographically and genetically distinct from that in Asia. Two distinct taxa are found growing together in northern Australia,Oryza meridionalis(including annual and perennial forms) and anOryza rufipogonlike taxa that have been shown to have a chloroplast genome sequence that is closer to that ofO. meridionalisthan toO. rufipogonfrom Asia. Rare plants of intermediate morphology have been observed in the wild despite a reported reproductive barrier between these two species. We now report the resequencing of plants from 26 populations including both taxa and putative hybrids. A comparison of chloroplast and nuclear genome sequences indicated re-combinations that demonstrated hybridisation in both directions. Individuals with intermediate morphology had high nuclear genome heterozygosity consistent with a hybrid origin. An examination of specific genes (e.g., starch biosynthesis genes) revealed the presence of heterozygotes with alleles from both parents suggesting that some wild plants were early generation hybrids. These plants may have low cross-fertility preserving the continuation of the two distinct species. Repeated backcrossing of these rare hybrids to one parent would explain the plants exhibiting chloroplast capture. These observations suggest that reticulate evolution is continuing in wildOryzapopulations and may have been a key process in rice evolution and domestication.
CmNDB1 and a Specific Domain of CmMYB1 Negatively Regulate CmMYB1-Dependent Transcription of Nitrate Assimilation Genes Under Nitrogen-Repleted Condition in a Unicellular Red Alga
Authors: Zhou Baifeng , Shima Hiroki , Igarashi Kazuhiko , Tanaka Kan , Imamura Sousuke
Published: March 2022

Nitrogen assimilation is an essential process that controls plant growth and development. Plant cells adjust the transcription of nitrogen assimilation genes through transcription factors (TFs) to acclimatize to changing nitrogen levels in nature. However, the regulatory mechanisms of these TFs under nitrogen-repleted (+N) conditions in plant lineages remain largely unknown. Here, we identified a negative domain (ND) of CmMYB1, the nitrogen-depleted (−N)-activated TF, in a unicellular red alga Cyanidioschyzon merolae. The ND deletion changed the localization of CmMYB1 from the cytoplasm to the nucleus, enhanced the binding efficiency of CmMYB1 to promoters of nitrate assimilation genes, and increased the transcripts of nitrate assimilation genes under +N condition. A pull-down assay using an ND-overexpressing strain combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis helped us to screen and identify an unknown-function protein, the CmNDB1. Yeast two-hybrid analysis demonstrated that CmNDB1 interacts with ND. Similar to ND deletion, CmNDB1 deletion also led to the nucleus localization of CmMYB1, enhanced the promoter-binding ratio of CmMYB1 to the promoter regions of nitrate assimilation genes, and increased transcript levels of nitrate assimilation genes under +N condition. Thus, these presented results indicated that ND and CmNDB1 negatively regulate CmMYB1 functions under the +N condition in C. merolae.
A Hyperspectral Data 3D Convolutional Neural Network Classification Model for Diagnosis of Gray Mold Disease in Strawberry Leaves
Authors: Jung Dae-Hyun , Kim Jeong Do , Kim Ho-Youn , Lee Taek Sung , Kim Hyoung Seok , Park Soo Hyun
Published: March 2022

Gray mold disease is one of the most frequently occurring diseases in strawberries. Given that it spreads rapidly, rapid countermeasures are necessary through the development of early diagnosis technology. In this study, hyperspectral images of strawberry leaves that were inoculated with gray mold fungus to cause disease were taken; these images were classified into healthy and infected areas as seen by the naked eye. The areas where the infection spread after time elapsed were classified as the asymptomatic class. Square regions of interest (ROIs) with a dimensionality of 16 × 16 × 150 were acquired as training data, including infected, asymptomatic, and healthy areas. Then, 2D and 3D data were used in the development of a convolutional neural network (CNN) classification model. An effective wavelength analysis was performed before the development of the CNN model. Further, the classification model that was developed with 2D training data showed a classification accuracy of 0.74, while the model that used 3D data acquired an accuracy of 0.84; this indicated that the 3D data produced slightly better performance. When performing classification between healthy and asymptomatic areas for developing early diagnosis technology, the two CNN models showed a classification accuracy of 0.73 with regards to the asymptomatic ones. To increase accuracy in classifying asymptomatic areas, a model was developed by smoothing the spectrum data and expanding the first and second derivatives; the results showed that it was possible to increase the asymptomatic classification accuracy to 0.77 and reduce the misclassification of asymptomatic areas as healthy areas. Based on these results, it is concluded that the proposed 3D CNN classification model can be used as an early diagnosis sensor of gray mold diseases since it produces immediate on-site analysis results of hyperspectral images of leaves.
Precision Detection of Dense Plums in Orchards Using the Improved YOLOv4 Model
Authors: Wang Lele , Zhao Yingjie , Liu Shengbo , Li Yuanhong , Chen Shengde , Lan Yubin
Published: March 2022

The precision detection of dense small targets in orchards is critical for the visual perception of agricultural picking robots. At present, the visual detection algorithms for plums still have a poor recognition effect due to the characteristics of small plum shapes and dense growth. Thus, this paper proposed a lightweight model based on the improved You Only Look Once version 4 (YOLOv4) to detect dense plums in orchards. First, we employed a data augmentation method based on category balance to alleviate the imbalance in the number of plums of different maturity levels and insufficient data quantity. Second, we abandoned Center and Scale Prediction Darknet53 (CSPDarknet53) and chose a lighter MobilenetV3 on selecting backbone feature extraction networks. In the feature fusion stage, we used depthwise separable convolution (DSC) instead of standard convolution to achieve the purpose of reducing model parameters. To solve the insufficient feature extraction problem of dense targets, this model achieved fine-grained detection by introducing a 152 × 152 feature layer. The Focal loss and complete intersection over union (CIOU) loss were joined to balance the contribution of hard-to-classify and easy-to-classify samples to the total loss. Then, the improved model was trained through transfer learning at different stages. Finally, several groups of detection experiments were designed to evaluate the performance of the improved model. The results showed that the improved YOLOv4 model had the best mean average precision (mAP) performance than YOLOv4, YOLOv4-tiny, and MobileNet-Single Shot Multibox Detector (MobileNet-SSD). Compared with some results from the YOLOv4 model, the model size of the improved model is compressed by 77.85%, the parameters are only 17.92% of the original model parameters, and the detection speed is accelerated by 112%. In addition, the influence of the automatic data balance algorithm on the accuracy of the model and the detection effect of the improved model under different illumination angles, different intensity levels, and different types of occlusions were discussed in this paper. It is indicated that the improved detection model has strong robustness and high accuracy under the real natural environment, which can provide data reference for the subsequent orchard yield estimation and engineering applications of robot picking work.
Construction of a Quantitative Genomic Map, Identification and Expression Analysis of Candidate Genes for Agronomic and Disease-Related Traits in Brassica napus
Authors: Raboanatahiry Nadia , Chao Hongbo , He Jianjie , Li Huaixin , Yin Yongtai , Li Maoteng
Published: March 2022

Rapeseed is the second most important oil crop in the world. Improving seed yield and seed oil content are the two main highlights of the research. Unfortunately, rapeseed development is frequently affected by different diseases. Extensive research has been made through many years to develop elite cultivars with high oil, high yield, and/or disease resistance. Quantitative trait locus (QTL) analysis has been one of the most important strategies in the genetic deciphering of agronomic characteristics. To comprehend the distribution of these QTLs and to uncover the key regions that could simultaneously control multiple traits, 4,555 QTLs that have been identified during the last 25 years were aligned in one unique map, and a quantitative genomic map which involved 128 traits from 79 populations developed in 12 countries was constructed. The present study revealed 517 regions of overlapping QTLs which harbored 2,744 candidate genes and might affect multiple traits, simultaneously. They could be selected to customize super-rapeseed cultivars. The gene ontology and the interaction network of those candidates revealed genes that highly interacted with the other genes and might have a strong influence on them. The expression and structure of these candidate genes were compared in eight rapeseed accessions and revealed genes of similar structures which were expressed differently. The present study enriches our knowledge of rapeseed genome characteristics and diversity, and it also provided indications for rapeseed molecular breeding improvement in the future.
Strategies of the Party Selectorate: The Two-Level Game in District Selections in Germany’s Mixed Member Electoral System
Authors: Reiser Marion
Published: March 2022

The article investigates how the opportunity structure and contextual factors influence the selectorates’ strategies in the process of candidate selection. The article argues that these strategies are an under-researched but important explanatory and dynamic link between the parties’ goals and context factors of candidate selection on the one side and the adopted selection criteria and the outcome of candidate selection on the other side. Based on a mixed-methods design, the study scrutinizes the selectorates’ strategies at district selections in Germany’s mixed-member electoral system. The analysis reveals that the local selectorates adopt the traditional inward oriented selection criteria to find the best candidate for the local party branch if the district seat is safe for the party. If, however, the seat is not safe, the selectorates prioritize the electoral goal over the local party organizational goal and strategically adapt the selection criteria to the opportunity structure. By considering both local inter-party competition and regional intra-party competition, they either take up a local voters’ perspective or anticipate the selection criteria of the state party lists in order to increase the chances for a seat in parliament. Thus, due to the mixed-member electoral system, the prevalence of dual candidacies, and decentralized candidate selection methods, intra-party selection in German districts is a two-level game.
Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store
Authors: Khatri Jaikishan , Marín-Morales Javier , Moghaddasi Masoud , Guixeres Jaime , Giglioli Irene Alice Chicchi , Alcañiz Mariano
Published: March 2022

Virtual reality (VR) is a useful tool to study consumer behavior while they are immersed in a realistic scenario. Among several other factors, personality traits have been shown to have a substantial influence on purchasing behavior. The primary objective of this study was to classify consumers based on the Big Five personality domains using their behavior while performing different tasks in a virtual shop. The personality recognition was ascertained using behavioral measures received from VR hardware, including eye-tracking, navigation, posture and interaction. Responses from 60 participants were collected while performing free and directed search tasks in a virtual hypermarket. A set of behavioral features was processed, and the personality domains were recognized using a statistical supervised machine learning classifier algorithm via a support vector machine. The results suggest that the open-mindedness personality type can be classified using eye gaze patterns, while extraversion is related to posture and interactions. However, a combination of signals must be exhibited to detect conscientiousness and negative emotionality. The combination of all measures and tasks provides better classification accuracy for all personality domains. The study indicates that a consumer’s personality can be recognized using the behavioral sensors included in commercial VR devices during a purchase in a virtual retail store.
The Daily Rhythmic Changes of Undergraduate Students’ Emotions: An Analysis Based on Tencent Tweets
Authors: Liu Run-Xiang , Liu Huan
Published: March 2022

Emotional stability is of great importance for undergraduates and has significant predictive power for mental health. Emotions are associated with individuals’ daily lives and routines. Undergraduates commonly post their opinions and feelings on social networks, providing a huge amount of data for studying their emotional states and rhythms. Based on the construction of the emotion dictionary of undergraduates’ Tencent tweets (TTs)—a social network for users to share their life situations and express emotions and feelings to friends—we used big data text analysis technology to analyze the emotion words in 45,996 Tencent tweets published by 894 undergraduates. Then, we used hierarchical linear modeling to further analyze the daily rhythms of undergraduate students’ emotions and how demographic variables are associated with the daily rhythmic changes. The results were as follows: (1) Undergraduates tweeted about more positive emotions than negative emotions (love was most common and fear was the least common); (2) The emotions in undergraduates’ tweets changed considerably from 1 a.m. to 6 a.m., but were fairly stable during the day; (3) There was a rising trend in the frequency of using emotion words in Tencent tweets during the day as each hour progressed, and there was a higher increase in positive emotion than negative emotion; and (4) The word frequencies and daily rhythms of emotions varied depending on demographic variables. Gender was correlated with the frequencies of gratitude and the daily rhythms of anger. As the grade increased, the frequency of emotion words in most subcategories in TTs decreased and the fluctuation in daily rhythms became smaller. There was no significant difference in the frequency and daily rhythm of emotion words used in TTs based on having had a left-behind experience. The results of the present study provided emotion expression in social networks in Chinese collectivist culture. This study added new evidence to support the notion that positive and negative emotions are independent dimensions.
How Does Chinese Outward Foreign Direct Investment Respond to Host Country Cultural Tolerance and Trust?
Authors: Liu Haiyue , Wang Yuhan , Zhang Qin , Jiang Jie
Published: March 2022

Based on 2010 to 2019 Chinese outward foreign direct investment (OFDI) panel data from 39 host countries, this paper studies the relationships between host country cultural characteristics and Chinese OFDI. The OLS regression results show that the cultural tolerance and trust in the host countries are significantly positively correlated with Chinese OFDI, which are robust according to the system GMM tests. Further analysis reveals that cultural tolerance is more positively related to Chinese OFDI in host countries with higher legislation and economic freedom, while cultural trust is positively associated with Chinese OFDI in host countries with lower legislation and economic freedom. In addition, higher cultural tolerance and trust promote Chinese OFDI in countries with greater cultural distance. Unlike traditional studies based on cultural distance in international trade, using more representative cultural characteristics, this paper provides references to Chinese OFDI decision-making based on the root characteristics associated with heterogeneous cultural influences.
Assessment of Fear of Failure Among Medical Students at King Saud University
Authors: Alabduljabbar Abeer , Almana Lyan , Almansour Alanoud , Alshunaifi Aljoharah , Alobaid Nada , Alothaim Norah , Shaik Shaffi Ahamed
Published: March 2022

Background

Fear of failure (FoF) is described as a “dispositional tendency to avoid failure in achievement settings.” It may potentially and adversely affect students’ ability to perform well in their educational activities.

Objectives

To measure FoF among medical students at King Saud University, FoF between men and women, academic levels, grade point average (GPA), and other factors among medical students were compared.

Method

A cross-sectional observational study was carried out using a stratified random sampling method. A total of 455 medical students completed “the Performance Failure Appraisal Inventory” during the academic year 2019–2020 at King Saud University, Riyadh, Saudi Arabia.

Results

The results showed that the mean of FoF was −0.3117. Moreover, higher levels of fear of devaluing one’s self-estimate were seen in women, and higher levels of fear of important others losing interest were seen in men. A significant relation was seen between different academic levels and fear of shame and embarrassment, fear of upsetting important others, as well as FoF. Higher levels of FoF were seen in those who had a GPA below 3.5 and a GPA greater than 4.9. Also, it was high in students who were not interested in studying medicine. The Cronbach’s α value of 0.93 of all items indicates good internal consistency, and the factor analysis confirms five items of an instrument.

Conclusion

The overall level of FoF was low among medical students at King Saud University. However, the domains and levels of FoF differed significantly according to gender, academic level, GPA, and interest in studying medicine.
Frontline Mongolian Healthcare Professionals and Adverse Mental Health Conditions During the Peak of COVID-19 Pandemic
Authors: Tsogbadrakh Basbish , Yanjmaa Enkhjargal , Badamdorj Oyungoo , Choijiljav Dorjderem , Gendenjamts Enkhjargal , Ayush Oyun-erdene , Pojin Odonjil , Davaakhuu Battogtokh , Sukhbat Tuya , Dovdon Baigalmaa , Davaasuren Oyunsuren , Stark Azadeh
Published: March 2022

Background

The relatively young and inexperienced healthcare professionals in Mongolia faced with an unprecedent service demand in response to the COVID-19 pandemic. Due to the small size of the healthcare workforce the Mongolian Health Ministry had no choice but to mandate continuous and long workhours from the healthcare workforce. Many of the healthcare professionals exhibited signs and symptoms of mental health disorders. This study aimed to discern the prevalence various mental health concerns, i.e., depression, anxiety and stress, insomnia, and to discern the factors that increased susceptibility to mental health disorders among frontline healthcare professionals providing healthcare services for COVID-19 patients in Mongolia.

Methods

A Cross-sectional research design was implemented. We collected data from 965 healthcare professional, randomly selected from 18 government hospitals, in four regions of Mongolia. Data were collected using the Depression Anxiety Stress-21, the General Self-Efficacy Scale, and the Insomnia Severity Index instruments. We constructed the scale of Pandemic Response Symptoms (PaReSy) which captured stress, depression, and anxiety. Data were analyzed using descriptive statistics, Kruskal–Wallis statistical test and multinominal logistic regression analysis.

Results

Prevalence of depression (52.3%, CI 95%: 49.1–55.5%), anxiety (70.2%, CI 95%: 67.2–73.0%), and stress (35.8%, CI 95%: 32.7–38.9%) was documented among Mongolian healthcare professionals. Perception of self-efficacy reduced susceptibility to PaReSy either at mild/moderate (OR = 0.948, 95% CI = 0.911–0.988, P = 0.011) or severe/extremely severe level (OR = 0.911, 95% CI = 0.861–0.963, P = 0.001). Within each stratum of insomnia, the risk of experiencing PaReSy increased almost linearly both in the category of mild/moderate PaReSy and in the category of severe/extremely severe PaReSy.

Conclusion

Improving self-efficacy and sleeping quality can assist healthcare workers to manage depression, anxiety, and stress. Findings provide important evidence to implement measures and strategies to assist healthcare professionals in low- and middle-income countries to constructively address their mental health concerns and needs.
Curriculum Leadership of Rural Teachers: Status Quo, Influencing Factors and Improvement Mechanism-Based on a Large-Scale Survey of Rural Teachers in China
Authors: Wang Xinyu , Chen Junyuan , Yue Wei , Zhang Yishi , Xu Fenghua
Published: March 2022

Revealing the general status quo of teacher curriculum leadership has great theoretical, policy, and practical significance. However, large-scale empirical investigations in this area are rare, and there is even less attention to the current situation of rural teacher curriculum leadership. Based on the survey of 2,966 rural teachers in 20 provinces of China, this paper presented the status quo of rural teacher curriculum leadership and examined influencing factors through multiple linear regression analysis. It was found that curriculum leadership of rural teachers was at a low level with backward leadership views, lack of practical ability, and low sense of identity. Regression analysis demonstrated that individual field factors had a significant impact on teachers’ curriculum leadership. Specifically, the higher the teachers’ leadership willingness, trust in others, and self-efficacy, the higher the curriculum leadership. The school field was also an important influential aspect. In particular, the formation of a common vision and teacher community by the school and the appropriate empowerment of the principal had a significant positive impact on the curriculum leadership of rural teachers. Based on these key findings, several improvement suggestions are put forward at the end, which can be used as references for other countries to develop improvement plans on rural teacher curriculum leadership.
Predictive Factors of the Entrepreneurial Performance of Undergraduates
Authors: Shaowei Qu , Tianhua Li , Miao Zhang
Published: March 2022

College students have gradually become the main force of entrepreneurship in mass entrepreneurship and innovation. However, their entrepreneurial performance was not as good as expected. We have carried out research to analyze the predictive factors of entrepreneurial performance of college students and put forward targeted suggestions, hoping to be helpful to improve their entrepreneurial performance of them. Based on questionnaire data obtained from 2,097 college student entrepreneurs, this study uses the structural equation model to analyze the predictive factors of the entrepreneurial performance of college students. The survey results of the questionnaire show that both personal and behavioral factors influence the entrepreneurial performance of college students. In this study, personal factors in this study mainly include entrepreneurial willingness, personality, and ability of entrepreneurs. Behavioral factors mainly refer to the positive behaviors of entrepreneurs that can affect entrepreneurial performance.
The Resting-State Neural Network of Delay Discounting
Authors: Yang Fan , Li Xueting , Hu Ping
Published: March 2022

Delay discounting is a common phenomenon in daily life, which refers to the subjective value of a future reward decreasing as a function of time. Previous studies have identified several cortical regions involved in delay discounting, but the neural network constructed by the cortical regions of delay discounting is less clear. In this study, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to measure the spontaneous neural activity in a large sample of healthy young adults and used the Monetary Choice Questionnaire to directly measure participants’ level of delay discounting. To identify the neural network of delay discounting at rest, we used an individual difference approach to explore brain regions whose spontaneous activities were related to delay discounting across the whole brain. Then, these brain regions served as seeds to identify the neural network of delay discounting. We found that the fractional amplitude of low-frequency fluctuations (fALFF) of the left insula were positively correlated to delay discounting. More importantly, its connectivity to the anterior cingulate cortex was read out for participants’ behavioral performance in the task of delay discounting. In short, our study provides empirical evidence that insula-anterior cingulate cortex connectivity may serve as a part of the neural network for delay discounting.
Interrelationship Amongst University Student Perceived Learning Burnout, Academic Self-Efficacy, and Teacher Emotional Support in China’s English Online Learning Context
Authors: Yang Gang , Sun Wenwen , Jiang Renfeng
Published: March 2022

This study seeks to explore the impact of learning burnout on university students’ English learning effect in the online environment. Through a large sample questionnaire survey, the study uses structural equation modelling to measure the interactions amongst university students’ English online learning burnout (EOLB), academic self-efficacy (AEE), and teacher emotional support (TES), thereby analysing and summarising the characteristics of their impacts on students’ online learning satisfaction. The results from the data analysis show that AEE plays a mediating role between students’ EOLB and learning satisfaction, and TES plays a moderating role between students’ EOLB and AEE, which all eventually influence students’ online learning effect manifested in aspects such as behaviour, cognition, and emotion. Given the results, the study further provides suggestions for alleviating university students’ EOLB, which can be used to optimise English online teaching design and learning practice.