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"Yang, Yun-zhi"
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The prevalence and influencing factors in anxiety in medical workers fighting COVID-19 in China
The coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2 virus) has been sustained in China since December 2019, and has become a pandemic. The mental health of frontline medical staff is a concern. In this study, we aimed to identify the factors influencing medical worker anxiety in China during the COVID-19 outbreak. We conducted a cross-sectional study to estimate the prevalence of anxiety among medical staff in China from 10 February 2020 to 20 February 2020 using the Zung Self-rating Anxiety Scale (SAS) to assess anxiety, with the criteria of normal (⩽49), mild (50–59), moderate (60–70) and severe anxiety (⩾70). We used multivariable linear regression to determine the factors (e.g. having direct contact when treating infected patients, being a medical staff worker from Hubei province, being a suspect case) for anxiety. We also used adjusted models to confirm independent factors for anxiety after adjusting for gender, age, education and marital status. Of 512 medical staff in China, 164 (32.03%) had had direct contact treating infected patients. The prevalence of anxiety was 12.5%, with 53 workers suffering from mild (10.35%), seven workers suffering from moderate (1.36%) and four workers suffering from severe anxiety (0.78%). After adjusting for sociodemographic characteristics (gender, age, education and marital status), medical staff who had had direct contact treating infected patients experienced higher anxiety scores than those who had not had direct contact (𝛽 value = 2.33, confidence interval (CI) 0.65–4.00; 𝑃 = 0.0068). A similar trend was observed in medical staff from Hubei province, compared with those from other parts of China (𝛽 value = 3.67, CI 1.44–5.89; 𝑃 = 0.0013). The most important variable was suspect cases with high anxiety scores, compared to non-suspect cases (𝛽 value = 4.44, CI 1.55–7.33; 𝑃 = 0.0028). In this survey of hospital medical workers during the COVID-19 outbreak in China, we found that study participants experienced anxiety symptoms, especially those who had direct clinical contact with infected patients; as did those in the worst affected areas, including Hubei province; and those who were suspect cases. Governments and healthcare authorities should proactively implement appropriate psychological intervention programmes, to prevent, alleviate or treat increased anxiety.
Journal Article
Gene duplications and phylogenomic conflict underlie major pulses of phenotypic evolution in gymnosperms
Inferring the intrinsic and extrinsic drivers of species diversification and phenotypic disparity across the tree of life is a major challenge in evolutionary biology. In green plants, polyploidy (or whole-genome duplication, WGD) is known to play a major role in microevolution and speciation, but the extent to which WGD has shaped macroevolutionary patterns of diversification and phenotypic innovation across plant phylogeny remains an open question. Here, we examine the relationship of various facets of genomic evolution—including gene and genome duplication, genome size, and chromosome number—with macroevolutionary patterns of phenotypic innovation, species diversification, and climatic occupancy in gymnosperms. We show that genomic changes, such as WGD and genome-size shifts, underlie the origins of most major extant gymnosperm clades, and notably, our results support an ancestral WGD in the gymnosperm lineage. Spikes of gene duplication typically coincide with major spikes of phenotypic innovation, while increased rates of phenotypic evolution are typically found at nodes with high gene-tree conflict, representing historic population-level dynamics during speciation. Most shifts in gymnosperm diversification since the rise of angiosperms are decoupled from putative WGDs and instead are associated with increased rates of climatic occupancy evolution, particularly in cooler and/or more arid climatic conditions, suggesting that ecological opportunity, especially in the later Cenozoic, and environmental heterogeneity have driven a resurgence of gymnosperm diversification. Our study provides critical insight on the processes underlying diversification and phenotypic evolution in gymnosperms, with important broader implications for the major drivers of both micro- and macroevolution in plants.
By examining the relationship of various facets of genomic changes with phenotypic evolution, this study found that pulses of phenotypic innovation in gymnosperms are strongly associated with gene duplications and genomic conflict.
Journal Article
ZoomInNet: A Novel Small Object Detector in Drone Images with Cross-Scale Knowledge Distillation
Drone-based object detection has been widely applied in ground object surveillance, urban patrol, and some other fields. However, the dramatic scale changes and complex backgrounds of drone images usually result in weak feature representation of small objects, which makes it challenging to achieve high-precision object detection. Aiming to improve small objects detection, this paper proposes a novel cross-scale knowledge distillation (CSKD) method, which enhances the features of small objects in a manner similar to image enlargement, so it is termed as ZoomInNet. First, based on an efficient feature pyramid network structure, the teacher and student network are trained with images in different scales to introduce the cross-scale feature. Then, the proposed layer adaption (LA) and feature level alignment (FA) mechanisms are applied to align the feature size of the two models. After that, the adaptive key distillation point (AKDP) algorithm is used to get the crucial positions in feature maps that need knowledge distillation. Finally, the position-aware L2 loss is used to measure the difference between feature maps from cross-scale models, realizing the cross-scale information compression in a single model. Experiments on the challenging Visdrone2018 dataset show that the proposed method draws on the advantages of the image pyramid methods, while avoids the large calculation of them and significantly improves the detection accuracy of small objects. Simultaneously, the comparison with mainstream methods proves that our method has the best performance in small object detection.
Journal Article
Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced MR in Tumor Parenchyma and Peritumoral Area for Distinction of Brain Tumors
To quantitatively evaluate the diagnostic efficiency of parameters from diffusion and dynamic contrast-enhanced MR which based on tumor parenchyma (TP) and peritumoral (PT) area in classification of brain tumors.
45 patients (male: 23, female: 22; mean age: 46 y) were prospectively recruited and they underwent conventional, DCE-MR and DWI examination. With each tumor, 10-15 regions of interest (ROIs) were manually placed on TP and PT area. ADC and permeability parameters (Ktrans, Ve, Kep and iAUC) were calculated and their diagnostic efficiency was assessed.
In TP, all permeability parameters and ADC value could significantly discriminate Low- from High grade gliomas (HGG) (p<0.001); among theses parameters, Ve demonstrated the highest diagnostic power (iAUC: 0.79, cut-off point: 0.15); the most sensitive and specific index for gliomas grading were Ktrans (84%) and Kep (89%). While, in PT area, only Ktrans could help in gliomas grading (P = 0.009, cut-off point: 0.03 min-1). Moreover, in TP, mean Ve and iAUC of primary central nervous system lymphoma (PCNSL) and metastases were significantly higher than that in HGG (p<0.003). Further, in PT area, mean Ktrans (p≤0.004) could discriminate PCNSL from HGG and ADC (p≤0.003) could differentiate metastases with HGG.
Quantitative ADC and permeability parameters from Diffusion and DCE-MR in TP and PT area, especially DCE-MR, can aid in gliomas grading and brain tumors discrimination. Their combined application is strongly recommended in the differential diagnosis of these tumor entities.
Journal Article
Comparative analysis of the diffusion kurtosis imaging and diffusion tensor imaging in grading gliomas, predicting tumour cell proliferation and IDH-1 gene mutation status
Introduction
Few studies have applied diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) for the comprehensive assessment of gliomas [tumour grade, isocitrate dehydrogenase-1 (
IDH-1
) mutation status and tumour proliferation rate (Ki-67)]. This study describes the efficacy of DKI and DTI to comprehensively evaluate gliomas, compares their results.
Methods
Fifty-two patients (18 females; median age, 47.5 years) with pathologically proved gliomas were prospectively included. All cases underwent DKI examination. DKI (mean kurtosis: MK, axial kurtosis: Ka, radial kurtosis: Kr) and DTI (mean diffusivity: MD, fractional anisotropy: FA) maps of each metric was derived. Three ROIs were manually drawn.
Results
MK, Ka, Kr and FA were significantly higher in HGGs than in LGGs, whereas MD was significantly lower in HGGs than in LGGs (
P
< 0.01). ROC analysis demonstrated that MK (specificity: 100% sensitivity: 79%) and Ka (specificity: 96% sensitivity: 82%) had the same and highest (AUC: 0.93) diagnostic value. Moreover, MK, Ka, and Kr were significantly higher in grade III than II gliomas (
P
≦ 0.01). Further, DKI and DTI can significantly identify
IDH-1
mutation status (
P
≦ 0.03). Ka (sensitivity: 74%, specificity: 75%, AUC: 0.72) showed the highest diagnostic value. In addition, DKI metrics and MD showed significant correlations with Ki-67 (
P
≦ 0.01) and Ka had the highest correlation coefficient (
r
s
= 0.72).
Conclusions
Compared with DTI, DKI has great advantages for the comprehensive assessment of gliomas. Ka might serve as a promising imaging index in predicting glioma grading, tumour cell proliferation rate and
IDH-1
gene mutation status.
Journal Article
Influence of the flow field and vortex structure of patient-specific abdominal aortic aneurysm with intraluminal thrombus on the arterial wall
In this study, numerical simulations and experiments were conducted on patient-specific normal abdominal aorta and abdominal aortic aneurysm (AAA) with intraluminal thrombus (ILT) models, which were reconstructed from computed tomography angiography (CTA) images published online. A scale-adaptive simulation (SAS) of the abdominal aortic aneurysm with a posterior eccentric thrombus was performed and the reliability of the numerical simulation was verified by 2D particle image velocimetry (PIV) experimental results. The distribution of wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT) of the normal abdominal aorta and AAA were compared and discussed systematically according to the numerical simulation results under rest and exercise conditions. Numerical results indicated that ILT deposition positions were accompanied by low WSS, high OSI, and high RRT regions and were characterized by small vortex groups, which was due to the fragmentation of large vortex structures. The distribution law of the AAA wall parameters has an obvious correlation with the nearby vortex structure formation, development, fragmentation and dissipation. It was also found that high TAWSS, low OSI, and low RRT regions present in the middle and lower aneurysm walls under exercise condition reduce the risk of ILT formation and development.
Journal Article
Chromosome-level reference genome assembly for the protected resource plant, Zenia insignis
Zenia insignis
Chun, from the subfamily Dialioideae of the family Fabaceae, is a tree species of significant economic and ecological values. It is a near threatened species as per the IUCN Red List. In this study, we generated a reference genome for
Z. insignis
, with a contig N50 of 6.02 Mb, a total length of 352.84 Mb, and 97.71% of the sequences assembled into 14 pseudo-chromosomes. The BUSCO assessment score for completeness is 97.30%, and the LAI index assessment score for continuity is 14.57. The present study contributes to provide a reference genome for the subfamily Dialioideae. The reference genome will provide a valuable resource for the phylogenomic studies of the family Fabaceae and facilitate further research on
Z. insignis
.
Journal Article
Oxidative Stress Induces Neuronal Apoptosis Through Suppressing Transcription Factor EB Phosphorylation at Ser467
Background/Aims: This study determined the role and mechanism of action of transcription factor EB (TFEB) in H 2 O 2 -induced neuronal apoptosis. Methods: SH-SY5Y cells were treated with Akt inhibitor/activator and different concentrations of H 2 O 2 . Cell apoptosis was detected by flow cytometric analysis. Akt and TFEB phosphorylation and PARP cleavage were determined by Western blotting. HEK293T cells were transfected with different truncated TFEB mutants and HA-Akt-WT; SH-SY5Y cells were transfected with Flag-vector, Flag-TFEB, Flag-TFEB-S467A or Flag-TFEB-S467D; and TFEB interaction with Akt was determined by co-immunoprecipitation and GST pull-down assays. Results: A low concentration of H 2 O 2 induces TFEB phosphorylation at Ser467 and nuclear translocation, facilitating neuronal survival, whereas a high concentration of H 2 O 2 promotes SH-SY5Y cell apoptosis via suppressing TFEB Ser467 phosphorylation and nuclear translocation. The TFEB-S467D mutant is more easily translocated into the nucleus than the non-phosphorylated TFEB-S467A mutant. Further, Akt physically binds to TFEB via its C-terminal tail interaction with the HLH domain of TFEB and phosphorylates TFEB at Ser467. Mutation of TFEB-Ser467 can prevent the phosphorylation of TFEB by Akt, preventing inhibition of oxidative stress-induced apoptosis. Conclusions: Oxidative stress induces neuronal apoptosis through suppressing TFEB phosphorylation at Ser467 by Akt, providing a novel therapeutic strategy for neurodegenerative diseases.
Journal Article
Fc receptor‐like A promotes malignant behavior in renal cell carcinoma and correlates with tumor immune infiltration
Background Our study aims to investigate the mechanisms through which Fc receptor‐like A (FCRLA) promotes renal cell carcinoma (RCC) and to examine its significance in relation to tumor immune infiltration. Materials and Methods The correlation between FCRLA and data clinically related to RCC was explored using The Cancer Genome Atlas (TCGA), then validated using Gene Expression Omnibus (GEO) gene chip data. Enrichment and protein–protein interaction (PPI) network analyses were performed for FCRLA and its co‐expressed genes. FCRLA was knocked down in RCC cell lines to evaluate its impact on biological behavior. Then the potential downstream regulators of FCRLA were determined by western blotting, and rescue experiments were performed for verification. The relevance between FCRLA and various immune cells was analyzed through GSEA, TIMER, and GEPIA tools. TIDE and ESTIMATE algorithms were used to predict the effect of FCRLA in immunotherapy. Results Fc receptor‐like A was associated with clinical and T stages and could predict the M stage (AUC = 0.692) and 1–3‐ and 5‐year survival rates (AUC = 0.823, 0.834, and 0.862) of RCC patients. Higher expression of FCLRA predicted an unfavorable overall survival (OS) in TCGA‐RCC and GSE167573 datasets (p = 0.03, p = 0.04). FCRLA promoted the malignant biological behavior of RCC cells through the pERK1/2/‐MMP2 pathway and was associated with tumor immune microenvironment in RCC. Conclusion Fc receptor‐like A is positively correlated with poor outcomes in RCC patients and plays an oncogenic role in RCC through the pERK1/2‐MMP2 pathway. Patients with RCC might benefit from immunotherapy targeting FCRLA.
Journal Article