bluuebunny/crossref_metadata_2025_split huggingface dataset:
Online Book Fairs during the COVID-19 Pandemic
Authors: Nguyen Hoang , Nguyen Hoang Viet , Le Ngoc Bao , Pham Thi Thu Thuy , Nguyen Ninh 
Published: May 2021

Abstract
Online book fairs are being held in Vietnam to replace traditional offline events that have been shelved owing to the COVID-19 crisis. This study aims to explore book consumers’ perceptions regarding digital book fairs and their evaluation of the first-ever national online book fair held in Vietnam. In-depth interviews were conducted to obtain insights from people who had attended the online book event. The findings provide acceptance of and support for the organization of digital book fairs during the COVID-19 pandemic. Attendees generally appreciated the convenience of the national online book fair and the promotional programmes offered by various publishers and distributors. Furthermore, some attendees enjoyed the novelty of the event and the feeling of being included in the reading community. Nevertheless, most of the attendees highlighted several limitations, especially the lack of social and face-to-face interaction. These findings have implications for online book fair organizers, publishers, and book distributors alike.
Nonlinear finite-element analysis of embedment behavior of metal washer in bolted timber joints
Authors: Teranishi Masaki , Matsubara Doppo , Wakashima Yoshiaki , Shimizu Hidemaru , Kitamori Akihisa 
Published: May 2021

AbstractThe pretensioning force in bolted joints enhances the lateral strength of the connections, and causes the embedment of metal washers into wood. Despite the significance of embedment behavior in the design of bolted joints, its mechanism has yet to be fully understood. In this study, the mechanism of the embedment of a metal washer into wood along the radial direction was examined through three-dimensional nonlinear finite-element analysis (FEA). The FEA results were validated by comparing them with experimental results for nine metal washers with different geometries. Moreover, the sensitivity of embedment stiffness and yield load to wooden material constants was also investigated. The numerical results showed good qualitative and quantitative agreement with the experimental results. In addition, the embedment stiffness and yield load were sensitive to the yield stress and Young’s modulus of wood in the radial and tangential directions. The determination of these mechanical properties of wood through material testing is important for reproducing the behavior of the embedment of a metal washer into wood and accurately estimating the yield load and initial stiffness using FEA. This will play a significant role in designing bolted joints.
A tri-tuple coordinate system derived for fast and accurate analysis of the colored de Bruijn graph-based pangenomes
Authors: Guo Jindan , Pang Erli , Song Hongtao , Lin Kui 
Published: May 2021

Abstract
Background
With the rapid development of accurate sequencing and assembly technologies, an increasing number of high-quality chromosome-level and haplotype-resolved assemblies of genomic sequences have been derived, from which there will be great opportunities for computational pangenomics. Although genome graphs are among the most useful models for pangenome representation, their structural complexity makes it difficult to present genome information intuitively, such as the linear reference genome. Thus, efficiently and accurately analyzing the genome graph spatial structure and coordinating the information remains a substantial challenge.

Results
We developed a new method, a colored superbubble (cSupB), that can overcome the complexity of graphs and organize a set of species- or population-specific haplotype sequences of interest. Based on this model, we propose a tri-tuple coordinate system that combines an offset value, topological structure and sample information. Additionally, cSupB provides a novel method that utilizes complete topological information and efficiently detects small indels (< 50 bp) for highly similar samples, which can be validated by simulated datasets. Moreover, we demonstrated that cSupB can adapt to the complex cycle structure.

Conclusions
Although the solution is made suitable for increasingly complex genome graphs by relaxing the constraint, the directed acyclic graph, the motif cSupB and the cSupB method can be extended to any colored directed acyclic graph. We anticipate that our method will facilitate the analysis of individual haplotype variants and population genomic diversity. We have developed a C +  + program for implementing our method that is available at https://github.com/eggleader/cSupB.
Contrastive self-supervised clustering of scRNA-seq data
Authors: Ciortan Madalina , Defrance Matthieu 
Published: May 2021

Abstract
Background
Single-cell RNA sequencing (scRNA-seq) has emerged has a main strategy to study transcriptional activity at the cellular level. Clustering analysis is routinely performed on scRNA-seq data to explore, recognize or discover underlying cell identities. The high dimensionality of scRNA-seq data and its significant sparsity accentuated by frequent dropout events, introducing false zero count observations, make the clustering analysis computationally challenging. Even though multiple scRNA-seq clustering techniques have been proposed, there is no consensus on the best performing approach. On a parallel research track, self-supervised contrastive learning recently achieved state-of-the-art results on images clustering and, subsequently, image classification.

Results
We propose contrastive-sc, a new unsupervised learning method for scRNA-seq data that perform cell clustering. The method consists of two consecutive phases: first, an artificial neural network learns an embedding for each cell through a representation training phase. The embedding is then clustered in the second phase with a general clustering algorithm (i.e. KMeans or Leiden community detection). The proposed representation training phase is a new adaptation of the self-supervised contrastive learning framework, initially proposed for image processing, to scRNA-seq data. contrastive-sc has been compared with ten state-of-the-art techniques. A broad experimental study has been conducted on both simulated and real-world datasets, assessing multiple external and internal clustering performance metrics (i.e. ARI, NMI, Silhouette, Calinski scores). Our experimental analysis shows that constastive-sc compares favorably with state-of-the-art methods on both simulated and real-world datasets.

Conclusion
On average, our method identifies well-defined clusters in close agreement with ground truth annotations. Our method is computationally efficient, being fast to train and having a limited memory footprint. contrastive-sc maintains good performance when only a fraction of input cells is provided and is robust to changes in hyperparameters or network architecture. The decoupling between the creation of the embedding and the clustering phase allows the flexibility to choose a suitable clustering algorithm (i.e. KMeans when the number of expected clusters is known, Leiden otherwise) or to integrate the embedding with other existing techniques.
Glycyrrhizin improves the pathogenesis of psoriasis partially through IL-17A and the SIRT1-STAT3 axis
Authors: Qiong Huang , Han Ling , Zhang Nanxue , Chen Huyan , Yan Kexiang , Zhang Zhenghua , Ma Ying , Xu Jinhua 
Published: May 2021

Abstract
Background
The anti-inflammatory effect of glycyrrhizin has been widely recognized, while the specific mechanism of glycyrrhizin in psoriasis remains poorly understood.

Results
In the imiquimod-induced mouse model of psoriasis (IMD), we found that glycyrrhizin can substantially improve the adverse symptoms in mice. The hematoxylin-eosin staining results showed that glycyrrhizin can also improve the pathological state of skin cells in IMD mice. Using enzyme-linked immunosorbent assay (ELISA), we found that glycyrrhizin substantially inhibited the expression of IL-17A and IFN-γ in the serum of IMD mice. In order to simulate the effect of IL-17A on keratinocytes in psoriasis, we treated HaCaT cells with 100 ng/mL IL-17A (IL-17A-HaCaT cells) for 48 h. Then, using cell-counting kit-8 (CCK-8) and ELISA assays, we found that glycyrrhizin inhibited the proliferation of IL-17A-HaCaT cells and reversed the promotion of IL-6, CCL20, and TNF-α induced by IL-17A. Further, western blotting (WB) results indicated that glycyrrhizin promoted the expression of SIRT1 and inhibited the expression of STAT3 and phosphorylated STAT3 (p-STAT3). By treating IL-17A-HaCaT cells with EX-527 (a potent and selective inhibitor of SIRT1), combined with CCK-8 and WB experiments, we initially found that EX-527 inhibited the proliferation of IL-17A-HaCaT cells and promoted the expression of STAT3, p-STAT3, and acetylated STAT3 (a-STAT3). However, when glycyrrhizin was added at the same time, the proliferation of IL-17A-HaCaT cells increased, and the expression of STAT3, p-STAT3, and a-STAT3 reduced. We then knocked down the expression of SIRT1 via small interfering RNA in IL-17A-HaCaT cells, and the results were consistent with those of EX-527.

Conclusions
Together, these results indicated that glycyrrhizin improved psoriasis by inhibiting the expression of IL-17A and IFN-γ in vivo and suppressed the proliferation of IL-17A-HaCaT cells and the expression of STAT3, p-STAT3, and a-STAT3 by upregulating SIRT1 in vitro.
Potential of fecal microbiota for detection and postoperative surveillance of colorectal cancer
Authors: Yao Qiulin , Tang Meifang , Zeng Liuhong , Chu Zhonghua , Sheng Hui , Zhang Yuyu , Zhou Yuan , Zhang Hongyun , Jiang Huayan , Ye Mingzhi 
Published: May 2021

Abstract
Background
Colorectal cancer (CRC) is one of the most common cancers. In recent studies, the gut microbiota has been reported to be potentially involved in aggravating or favoring CRC development. However, little is known about the microbiota composition in CRC patients after treatment. In this study, we explored the fecal microbiota composition to obtain a periscopic view of gut microbial communities. We analyzed microbial 16S rRNA genes from 107 fecal samples of Chinese individuals from three groups, including 33 normal controls (NC), 38 CRC patients (Fa), and 36 CRC post-surgery patients (Fb).

Results
Species richness and diversity were decreased in the Fa and Fb groups compared with that of the NC group. Partial least squares discrimination analysis showed clustering of samples according to disease with an obvious separation between the Fa and NC, and Fb and NC groups, as well as a partial separation between the Fa and Fb groups. Based on linear discriminant analysis effect size analysis and a receiver operating characteristic model, Fusobacterium was suggested as a potential biomarker for CRC screening. Additionally, we found that surgery greatly reduced the bacterial diversity of microbiota in CRC patients. Some commensal beneficial bacteria of the intestinal canal, such as Faecalibacterium and Prevotella, were decreased, whereas the drug-resistant Enterococcus was visibly increased in CRC post-surgery group. Meanwhile, we observed a declining tendency of Fusobacterium in the majority of follow-up CRC patients who were still alive approximately 3 y after surgery. We also observed that beneficial bacteria dramatically decreased in CRC patients that recidivated or died after surgery. This revealed that important bacteria might be associated with prognosis.

Conclusions
The fecal bacterial diversity was diminished in CRC patients compared with that in NC. Enrichment and depletion of several bacterial strains associated with carcinomas and inflammation were detected in CRC samples. Fusobacterium might be a potential biomarker for early screening of CRC in Chinese or Asian populations. In summary, this study indicated that fecal microbiome-based approaches could be a feasible method for detecting CRC and monitoring prognosis post-surgery.
The genetic basis of water‐use efficiency and yield in lettuce
Authors: Damerum Annabelle , Smith Hazel K. , Clarkson GJJ , Truco Maria José , Michelmore Richard W. , Taylor Gail 
Published: May 2021

Abstract
Background
Water supply limits agricultural productivity of many crops including lettuce. Identifying cultivars within crop species that can maintain productivity with reduced water supply is a significant challenge, but central to developing resilient crops for future water-limited climates. We investigated traits known to be related to water-use efficiency (WUE) and yield in lettuce, a globally important leafy salad crop, in a recombinant inbred line (RIL) lettuce mapping population, produced from a cross between the cultivated Lactuca sativa L. cv. Salinas and its wild progenitor L. serriola L.

Results
Wild and cultivated lettuce differed in their WUE and we observed transgressive segregation in yield and water-use traits in the RILs. Quantitative trait loci (QTL) analysis identified genomic regions controlling these traits under well-watered and droughted conditions. QTL were detected for carbon isotope discrimination, transpiration, stomatal conductance, leaf temperature and yield, controlling 4–23 % of the phenotypic variation. A QTL hotspot was identified on chromosome 8 that controlled carbon isotope discrimination, stomatal conductance and yield under drought. Several promising candidate genes in this region were associated with WUE, including aquaporins, late embryogenesis abundant proteins, an abscisic acid-responsive element binding protein and glutathione S-transferases involved in redox homeostasis following drought stress were also identified.

Conclusions
For the first time, we have characterised the genetic basis of WUE of lettuce, a commercially important and water demanding crop. We have identified promising candidate genomic regions determining WUE and yield under well-watered and water-limiting conditions, providing important pre-breeding data for future lettuce selection and breeding where water productivity will be a key target.
Differences in morphological and physiological features of citrus seedlings are related to Mg transport from the parent to branch organs
Authors: Jia Yamin , Xu Hao , Wang Yuwen , Ye Xin , Lai Ningwei , Huang Zengrong , Yang Lintong , Li Yan , Chen Li-Song , Guo Jiuxin 
Published: May 2021

Abstract
Background
In this study, we aimed to test the hypothesis that magnesium (Mg) remobilization in citrus plants is regulated by Mg supply and contributes to differences in the growth of the parent and branch organs. Citrus seedlings were grown in sand under Mg deficient (0 mmol Mg2+ L−1, -Mg) and Mg sufficient (2 mmol Mg2+ L−1, + Mg) conditions. The effects on biomass, Mg uptake and transport, gas exchange and chlorophyll fluorescence, as well as related morphological and physiological parameters were evaluated in different organs.

Results
Mg deficiency significantly decreased plant biomass, with a decrease in total plant biomass of 39.6%, and a greater than twofold decrease in the branch organs compared with that of the parent organs. Reduced photosynthesis capacity was caused by a decreased in pigment levels and photosynthetic electron transport chain disruption, thus affecting non-structural carbohydrate accumulation and plant growth. However, the adaptive responses of branch leaves to Mg deficiency were greater than those in parent leaves. Mg deficiency inhibited plant Mg uptake but enhanced Mg remobilization from parent to branch organs, thus changing related growth variables and physiological parameters, including protein synthesis and antioxidant enzyme activity. Moreover, in the principal components analysis, these variations were highly clustered in both the upper and lower parent leaves, but highly separated in branch leaves under the different Mg conditions.

Conclusions
Mg deficiency inhibits the growth of the parent and branch organs of citrus plants, with high Mg mobility contributing to differences in physiological metabolism. These findings suggest that Mg management should be optimized for sustainable citrus production.
Favipiravir for the treatment of patients with COVID-19: a systematic review and meta-analysis
Authors: Manabe Toshie , Kambayashi Dan , Akatsu Hiroyasu , Kudo Koichiro 
Published: May 2021

Abstract
Background
Favipiravir possesses high utility for treating patients with COVID-19. However, research examining the efficacy and safety of favipiravir for patients with COVID-19 is limited.

Methods
We conducted a systematic review of published studies reporting the efficacy of favipiravir against COVID-19. Two investigators independently searched PubMed, the Cochrane Database of Systematic Reviews, MedRxiv, and ClinicalTrials.gov (inception to September 2020) to identify eligible studies. A meta-analysis was performed to measure viral clearance and clinical improvement as the primary outcomes.

Results
Among 11 eligible studies, 5 included a comparator group. Comparing to the comparator group, the favipiravir group exhibited significantly better viral clearance on day 7 after the initiation of treatment (odds ratio [OR] = 2.49, 95% confidence interval [CI] = 1.19–5.22), whereas no difference was noted on day 14 (OR = 2.19, 95% CI = 0.69–6.95). Although clinical improvement was significantly better in the favipiravir group on both days 7 and 14, the improvement was better on day 14 (OR = 3.03, 95% CI = 1.17–7.80) than on day 7 (OR = 1.60, 95% CI = 1.03–2.49). The estimated proportions of patients with viral clearance in the favipiravir arm on days 7 and 14 were 65.42 and 88.9%, respectively, versus 43.42 and 78.79%, respectively, in the comparator group. The estimated proportions of patients with clinical improvement on days 7 and 14 in the favipiravir group were 54.33 and 84.63%, respectively, compared with 34.40 and 65.77%, respectively, in the comparator group.

Conclusions
Favipiravir induces viral clearance by 7 days and contributes to clinical improvement within 14 days. The results indicated that favipiravir has strong possibility for treating COVID-19, especially in patients with mild-to-moderate illness. Additional well-designed studies, including examinations of the dose and duration of treatment, are crucial for reaching definitive conclusions.
Shedding of infectious SARS-CoV-2 by hospitalized COVID-19 patients in relation to serum antibody responses
Authors: Glans Hedvig , Gredmark-Russ Sara , Olausson Mikaela , Falck-Jones Sara , Varnaite Renata , Christ Wanda , Maleki Kimia T. , Karlberg Maria Lind , Broddesson Sandra , Falck-Jones Ryan , Bell Max , Johansson Niclas , Färnert Anna , Smed-Sörensen Anna , Klingström Jonas , Bråve Andreas 
Published: May 2021

Abstract
Background
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global pandemic. The understanding of the transmission and the duration of viral shedding in SARS-CoV-2 infection is still limited.

Objectives
To assess the timeframe and potential risk of SARS-CoV-2 transmission from hospitalized COVID-19 patients in relation to antibody response.

Method
We performed a cross-sectional study of 36 COVID-19 patients hospitalized at Karolinska University Hospital. Patients with more than 8 days of symptom duration were sampled from airways, for PCR analysis of SARS-CoV-2 RNA and in vitro culture of replicating virus. Serum SARS-CoV-2-specific immunoglobulin G (IgG) and neutralizing antibodies titers were assessed by immunofluorescence assay (IFA) and microneutralization assay.

Results
SARS-CoV-2 RNA was detected in airway samples in 23 patients (symptom duration median 15 days, range 9–53 days), whereas 13 patients were SARS-CoV-2 RNA negative (symptom duration median 21 days, range 10–37 days). Replicating virus was detected in samples from 4 patients at 9–16 days. All but two patients had detectable levels of SARS-CoV-2-specific IgG in serum, and SARS-CoV-2 neutralizing antibodies were detected in 33 out of 36 patients. Total SARS-CoV-2-specific IgG titers and neutralizing antibody titers were positively correlated. High levels of both total IgG and neutralizing antibody titers were observed in patients sampled later after symptom onset and in patients where replicating virus could not be detected.

Conclusions
Our data suggest that the presence of SARS-Cov-2 specific antibodies in serum may indicate a lower risk of shedding infectious SARS-CoV-2 by hospitalized COVID-19 patients.
A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma
Authors: Huang Guichuan , Zhang Jing , Gong Ling , Huang Yi , Liu Daishun 
Published: May 2021

AbstractBackgroundLung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of the major histological subtypes. Although numerous biomarkers have been found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is insufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival in patients with LUSC.MethodsThe mRNA expression files and LUSC clinical information were obtained from The Cancer Genome Atlas (TCGA) dataset.ResultsBased on Gene Set Enrichment Analysis (GSEA), we found 5 glycolysis-related gene sets that were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were performed to choose prognostic-related gene signatures. Based on a Cox proportional regression model, a risk score for a three-gene signature (HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis indicated that the risk score for this three-gene signature can be used as an independent prognostic indicator in LUSC. Additionally, based on the cBioPortal database, the rate of genomic alterations in the HKDC1, ALDH7A1, and MDH1 genes were 1.9, 1.1, and 5% in LUSC patients, respectively.ConclusionA glycolysis-based three-gene signature could serve as a novel biomarker in predicting the prognosis of patients with LUSC and it also provides additional gene targets that can be used to cure LUSC patients.