bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diversity, community composition and phylogeny of culturable fungal endophytes of Dioscorea bulbifera L.
Authors: Sharma Supriya , Dhar Manoj K , Kaul Sanjana 
Published: November 2022

Abstract

The origin of endophytic symbiosis dates long back in evolutionary history. Over the period of evolution, they have established a special relationship with their host plants. The research nowadays is focused on understanding the ecology, evolution and bioactive potential of endophytes. The current study is aimed to describe the biodiversity of culturable fungal endophytes associated with Dioscorea bulbifera L. Overall, the endophytic fungal taxa belonged to two phyla, four classes, ten orders, twenty-five genera and thirty-eight species showing abundant diversity. The class Dothidiomycetes was reported to be the richest and most abundant in terms of species richness. Diversity indices demonstrated significant diversity of fungal endophytes within and between the different tissues. Moreover, fungal isolates such as, Acrocalymma medicaginis, Curvularia lycoperscii, Talaromyces macrospora, Fusarium laceratum, Paecilomyces formosus and Microascus cirrosus obtained in this study have not been reported earlier as endophytes from any plant. The endophytic fungal isolates, Nigrospora oryzae, Flavodon flavus and Talaromyces sp., have been reported first time as endophytes from D. bulbifera L. Since, the relevance of endophyte-plant interactions is still indistinct therefore, deeper understanding of these interactions at molecular and genetic level is required to be done.
Oligoribonuclease mediates high adaptability of P. aeruginosa through metabolic conversion
Authors: Yang Lulu , Bajinka Ousman , Qi Mingming , Wang Lili , Wu Guojun , Tan Yurong 
Published: November 2022

Abstract
Oligoribonuclease (Orn) of P. aeruginosa is a highly conserved exonuclease, which can regulate the global gene expression levels of bacteria through regulation of both the nanoRNA and c-di-GMP. NanoRNA can regulate the expression of the bacterial global genome as a transcription initiator, and c-di-GMP is the most widely second messenger in bacterial cells. This study seeks to elucidate on the regulation of orn on pathogenicity of P. aeruginosa. P. aeruginosa with orn deletion was constructed by suicide plasmid homologous recombination method. The possible regulatory process of orn was analyzed by TMT quantitative labeling proteomics. Then experiments were conducted to verify the changes of Δorn on bacterial motility, virulence and biofilm formation. Bacterial pathogenicity was further detected in cell and animal skin trauma models. ELISA detection c-di-GMP concentration and colony aggregation and biofilm formation were observed by scanning electron microscope. orn deletion changed the global metabolism of P. aeruginosa and reduced intracellular energy metabolism. It leads to the disorder of the quorum sensing system, the reduction of bacterial motility and virulence factors pyocyanin and rhamnolipids. But, orn deletion enhanced pathogenicity in vitro and in vivo, a high level of c-di-GMP and biofilm development of P. aeruginosa. Orn regulates the ability of P. aeruginosa to adapt to the external environment
Characterization of Acoustic Parameters in Phases of Masticatory Sequence
Authors: Xia Yue , Wang Lu 
Published: November 2022

Abstract
Background: Chewing food produces characteristic sounds of the breakage of food. Due to the limitations of sound collection devices, there have been few studies on chewing sounds in the different phases of mastication. Thus, there has been no significant progress in the field of mastication sound. In addition, the characterization of acoustic signals in mastication remains unclear. Our aim was to investigate the correlation between mastication indicators and acoustic signals and the variations of these metrics throughout the entire phase of chewing process. Methods: Fifty-two volunteers with healthy dentition consumed natural foods (peanuts), and the mastication sounds at four stages in the mastication process were recorded by a bone-conduction microphone and further analysed by the acoustic software Praat 5.4.04. The granulometry of the expectorated food boluses was characterized by the median particle size (D50, D50a, D50b, D50c) in each of the four phases of the chewing sequence. Kinematic parameters, including the chewing cycles (CC, CCa, CCb, CCc), and the chewing frequency (CF, CFa, CFb, CFc), and acoustic parameters, including mastication sound pitch (MP, MPa, MPb, MPc) and mastication sound intensity (MI, MIa, MIb, MIc) were recorded and analysed by Praat 5.5.04. Independent samples t-tests, one-way ANOVAs and Pearson correlation analyses were used where applicable.
Results: Significant differences in the chewing cycles (CC, CCa, CCb, CCc), mastication sound intensity (MI, MIa, MIb, MIc) and granulometry of food boluses (D50, D50a, D50b, D50c) parameters were found in all four stages when compared by sex (t-test, p<0.01, p<0.01, p<0.01, respectively). Significant differences were observed in mastication sound intensity and granulometry of the food bolus group between different phases of mastication (one-way ANOVA, p<0.01, p<0.01). Comparing all of the indicators, a highly negative correlation was found between mastication sound intensity and granulometry of food boluses at each stage of mastication: MI and D50, MIa and D50a, MIb and D50b, and MIc and D50c (r=-0.94, r=-0.85, r=-0.94, r=-0.95, respectively; p<0.01). No significant correlation was found between the remaining acoustic and mastication parameters.
Conclusions: Variations in mastication sound intensity and the granulometry of the food bolus were highly correlated in all four phases of mastication. Mastication sound intensity may be a new and essential approach for studying mastication.
Decomposition of Matrix Product States into Shallow Quantum Circuits
Authors: Perdomo-Ortiz Alejandro , Rudolph Manuel , Chen Jing , Miller Jacob , Acharya Atithi 
Published: November 2022

Abstract
Tensor networks (TNs) are a family of computational methods built on graph-structured factorizations of large tensors, which have long represented state-of-the-art methods for the approximate simulation of complex quantum systems on classical computers. The rapid pace of recent advancements in numerical computation, notably the rise of GPU and TPU hardware accelerators, have allowed TN algorithms to scale to even larger quantum simulation problems, and to be employed more broadly for solving machine learning tasks. The "quantum-inspired" nature of TNs permits them to be mapped to parametrized quantum circuits (PQCs), a fact which has inspired recent proposals for enhancing the performance of TN algorithms using near-term quantum devices, as well as enabling joint quantum-classical training frameworks which benefit from the distinct strengths of TN and PQC models. However, the success of any such methods depends on efficient and accurate methods for approximating TN states using realistic quantum circuits, something which remains an unresolved question.
In this work, we compare a range of novel and previously-developed algorithmic protocols for decomposing matrix product states (MPS) of arbitrary bond dimension into low-depth quantum circuits consisting of stacked linear layers of two-qubit unitaries. These protocols are formed from different combinations of a preexisting analytical decomposition scheme with constrained optimization of circuit unitaries, and all possess efficient classical runtimes. Our experimental results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods, with even greater benefits seen in the setting of limited computational resources. Given these promising results, we expect our proposed decomposition protocol to form a useful ingredient within any joint application of TNs and PQCs, in turn further unlocking the rich and complementary benefits of classical and quantum computation.
African Society for Immunodeficiency (Asid) Guidelines for Diagnosis and Management of Inborn Errors of Immunity in Africa: Core Concept, Development and Initial Results
Authors: Goda Rayan , Sobh Ali , Nermeen Galal , Radwan Nesrine , Barbouche Mohamed-Ridha , Ben-Mustapha Imen , Bousfiha Aziz , Jeddane Leila , Mahlaoui Nizar , Elfeky Reem 
Published: November 2022

Abstract
Background and aims
The African Society for Immunodeficiency (ASID), looked to form concise region-friendly guidelines for the clinical diagnosis and management of Inborn Errors of Immunity (IEI). The main objective was to develop these guidelines to accommodate for the locally prevalent endemic diseases and the disparity of resources within the continent. Furthermore, the society aimed to publish these guidelines to increase awareness among African physicians, and facilitate patient capture, diagnosis and initial management.
Methods
The African Society for Immunodeficiency convened an African IEI guidelines taskforce, which developed an initial standard operating procedure. This document entailed the main list of IEI in need of urgent guidelines formulation, validation and review processes. The first group of diseases chosen to start the formulation of the guidelines were diseases of immune dysregulation. Simultaneously, this was associated with assigning a local African IEI guidelines working party, consisting of mainly locally established experts and young doctors.
Results
Two pilot studies were produced for the project targeting the clinical diagnosis and management of autoimmune lymphoproliferative syndrome and Immune Dysregulation with Colitis, respectively. These guidelines will ensure better patient capture, diagnosis, and management especially given local endemic diseases and lack of resources. Moreover, it shall increase local inter-centre or regional collaboration with pioneers and experts within the field inside as well as outside the African continent.
Hemorrhoidal Disease among doctors from Grade-A Tertiary Hospitals in Big Cities of China: results from web-based doctors as patients survey
Authors: Qiu Xiaoyuan , Liu Yuxin , Shi Weikun , Lin Guole 
Published: November 2022

Abstract
Background Doctors are at high risk of developing hemorrhoidal disease (HD), but it’s still not clear that how much doctors aware of this problem. OASIS (dOctors AS patIentS) study was conducted to understand the prevalence, awareness, diagnosis and treatment of HD among doctors in big cities of China.
Methods From August to October in 2020, an online survey was conducted through questionnaire among doctors from grade-A tertiary hospitals in 29 provinces across China.
Results A total of 1227 questionnaires were collected. The prevalence of HD was 56.8%, with a significant difference between internists and surgeons (P=0.01). 15.6% doctors with HD did not know well about the chronic nature of HD. 91.5% of doctors adopted general treatment, and 83.0% doctors considered that “oral medications are used only after ineffective topical medications”. Among the oral medications, the Micronized Purified Flavonoid Fraction (MPFF) performed best on the scores of the three most valuable aspects, but only 17% doctors had received treatment with MPFF.
Conclusions Doctors are at higher risk of developing HD, and HD is highly prevalent among Chinese doctors, but the awareness of that is not enough. There is a gap between the HD clinical practice and guideline recommendations even in doctors, such as late initiation of oral drug therapy and inadequate oral drug therapy. Therefore, awareness and standardized treatment of HD should be strengthened among Chinese doctors, and what’s more, ordinary people.
The changes of chromium speciation in limestone samples during simulated natural attenuation processes
Authors: Zhao Jiujiang , Zhang Jing , Liu Yongbing , Zhao Hong , Zhao Wenbo 
Published: November 2022

Abstract
To study the Cr(VI) natural attenuation processes, Cr(VI) diffusion-reaction experiments for limestone samples were conducted. After experiments, synchrotron radiation µ-XRF maps showed that for organic-rich limestone samples, most of Cr distributed close to the surface, and some high Cr spots were found to be associated with organic matters; whereas, Cr distributed evenly in the samples containing low organic matter. These results indicate that Cr(VI) reacts with organic matter in the fractures and pore space of organic-rich limestone samples, and the reducing products (Cr(III) precipitates) might aggregate and block the pore throats, which might retard the further diffusion of Cr(VI) into the rock matrix. The distributions of Cr chemical forms, which were obtained by X-ray absorption near-edge structure (XANES) spectroscopy, showed that for organic-rich limestone samples, the Cr(OH)3 fraction in the center was higher than that on the surface, whereas, for the samples containing low organic matter, no such significant difference was found. One possible explanation for these findings is that in organic-rich limestone samples, the Cr(III) hydroxides, which aggregate in the zones close to the surface, might age and transform from crystalline to the stable chemical forms of Cr(III) oxyhydroxide or even Cr(III) oxides, which could enhance the effect of Cr(VI) natural attenuation. By using synchrotron radiation based techniques, this work provides a feasible way to investigate the changes of chromium chemical forms during its diffusion-reaction processes in rock samples and can be used to study the mechanism of Cr(VI) natural attenuation.
QSAR modeling for predicting the larvicidal activity of essential oils targeting Culex pipiens pallens (Diptera: Culicidae)
Authors: Alem Samia , Driouche Youssouf , Haddag Hamza , Bouslama Zihad 
Published: November 2022

Abstract

The search for new larvicides suited for vector control of mosquitoes requires considerable time, an enormous budget, and several analytical setups.
Fortunately, the use of quantitative structure–activity relationship (QSAR) modeling allows the prediction of the larvicidal activity of structurally diverse chemicals against mosquitoes in a way quick and costless. This approach can be helpful to study for making biolarvicide with highest ability to destroy mosquito larvae.
We propose a quantitative structure-activity relationship model using two different statistical methods, multiple linear regression (MLR) and Support vector machine (SVM) for predicting the larvicidal activity of 30 compounds of essential oils (EOs) isolated from the root of Asarum heterotropoides against Culex pipiens pallens. A model with four theoretical descriptors derived from Dragon software was developed applying the genetic algorithm (GA)-variable subset selection (VSS) procedure. The statistical parameters, R2 = 0.9716, Q2LOO = 0.9595, s = 0.1690 of the model developed by MLR showed a good predictive capability for log LC50 values. The comparison between the results of MLR and SVM models showed that the SVM model present a good alternative to construct a QSAR model for the prediction of the larvicidal activity.
Whole genome sequencing of 2,023 colorectal cancers reveals mutational landscapes, new driver genes and immune interactions
Authors: Tomlinson Ian , Cornish Alex , Gruber Andreas , Houlston Richard , Sud Amit , Law Philip , Lakatos Eszter , Culliford Richard , Househam Jacob , Graham Trevor , Wood Henry , Quirke Philip , Lopez-Bigas Nuria , Arnedo-Pac Claudia , Chubb Daniel , Leathlobhair Maire Ni , Noyvert Boris , Kinnersley Ben , Cross William , Murugaesu Nirupa , Sosinsky Alona , Mitchell Jonathan , Alexandrov Ludmil , Zapata Luis , Fernandez-Tajes Juan , Thorn Steve , Sherwood Kitty , Gul Guler , Hawari Aliah , Sottoriva Andrea , Church David , Caravagna Giulio , Wedge David , Frangou Anna 
Published: November 2022

Abstract

To characterise the somatic alterations in colorectal cancer (CRC), we conducted whole-genome sequencing analysis of 2,023 tumours. We provide the most detailed high-resolution map to date of somatic mutations in CRC, and demonstrate associations with clinicopathological features, in particular location in the large bowel. We refined the mutational processes and signatures acting in colorectal tumorigenesis. In analyses across the sample set or restricted to molecular subtypes, we identified 185 CRC driver genes, of which 117 were previously unreported. New drivers acted in various molecular pathways, including Wnt (CTNND1, AXIN1, TCF3), TGF-β/BMP (TGFBR1) and MAP kinase (RASGRF1, RASA1, RAF1, and several MAP2K and MAP3K loci). Non-coding drivers included intronic neo-splice site alterations in APC and SMAD4. Whilst there was evidence of an excess of mutations in functionally active regions of the non-coding genome, no specific drivers were called with high confidence. Novel recurrent copy number changes included deletions of PIK3R1 and PWRN1, as well as amplification of CCND3 and NEDD9. Putative driver structural variants included BRD4 and SOX9 regulatory elements, and ACVR2A and ANKRD11 hotspot deletions. The frequencies of many driver mutations, including somatic Wnt and Ras pathway variants, showed a gradient along the colorectum. The Pks-pathogenic E. coli signature and TP53 mutations were primarily associated with rectal cancer. A set of unreported immune escape driver genes was found, primarily in hypermutated CRCs, most of which showed evidence of genetic evasion of the anti-cancer immune response. About 25% of cancers had a potentially actionable mutation for a known therapy. Thirty-three of the new driver genes were predicted to be essential, 17 possessed a druggable structure, and nine had a bioactive compound available. Our findings provide further insight into the genetics and biology of CRC, especially tumour subtypes defined by genomic instability or clinicopathological features.
Diverse, abundant and stable coastal RNA viruses identified by spatiotemporal metatranscriptomics
Authors: Sun Jianhua , Zheng Kaiyang , Liang Yan , Shi Mang , Han Meiaoxue , Liu Gang , Gu Chengxiang , Zhang Xin , Chen Xuechao , Gao Chen , Shao Hong , Guo Cui , He Hui , Wang Hualong , Sung Yeong Yik , Mok Wen Jye , Wong Li Lian , Wang Zongling , McMinn Andrew , Wang Min 
Published: November 2022

Abstract
The diversity and spatiotemporal dynamics of a coastal RNA virus community, was investigated focusing on the effects of a bloom of the macroalgae U. prolifera through a metatranscriptomic reconstruction of ~ 880Gb of Qingdao Coastal RNA sequences from May 2019 to December 2020. 6,079 RNA viral contigs were identified and these generated 2,351 viral operational taxonomic units within known orders. The analysis found that structural components of the coastal marine RNA virus community are diverse, abundant and stable. The viruses were mainly associated with eukaryotes from Intramacronucleata, Chlorophyta, Bacillariophyta and Dinophyceae, bacteria from Flavobacteriales and Rhodobacterales and MGII and Nitrosopumilales from archaea. The viral auxiliary metabolic genes indicate that coastal RNA viruses manipulate reprogramming of diverse host metabolisms, including carbon cycling, signaling pathways, membrane transport, transcription and translation. Together these results provide critical insights for incorporating RNA viruses into marine ecological and epidemiological models.
Progress of mental strain in German public administrations in the course of the COVID-19 pandemic
Authors: Claassen Kevin , Wrede Sammy J.S. , Kettschau Jan P. , Anjos Dominique Rodil dos , Broding Horst C. 
Published: November 2022

Abstract

Purpose
Due to the COVID-19 pandemic, an acceleration in the usage of digital working methods occurred in the setting of German public administrations. Besides the ostensible risk of infection due to the virus, compound mental stress arose for the employees. A subsequent progression of mental strain is to be examined. The aim is to estimate a residual pandemic effect approximated by controlling common influencing factors.
Methods
An online survey was conducted in 2020 and repeated 2022 among > 500 employees from three public administrations in Germany. Mental strain was measured using the Wuppertal Screening Instrument for Psychological Strain. The temporal variation was operationalized by the 1st and 2nd survey as an independent variable. For hypothesis testing, a t-test was calculated. A pooled OLS regression of the time-dependent differences was performed as a pre/post evaluation, supplemented by Breusch-Pagan and Durbin-Watson tests as well as calculation of variance inflation factors.
Results
More than 70% of the public administration’s employees experienced non-optimal mental strain. The multiple regression model showed a significant increase in mental strain as well when the influence of socio-demographic changes on the department level was controlled for (β = -0.095, t = -2.275, df = 30, p < 0.05). Children, age and university degree were significant predictors of mental strain. The R-square revealed that about 40% of the variance in the temporal variation of mental strain could be explained by the temporal variation of the independent variables.
Conclusion
The observed influential factors explain a significant proportion of the increased mental strain in German public administration workers. Still, more than half of the increase remains unexplained. Environmental influences within the observed period were largely determined by the pandemic conditions. The results place emphasis on the health-related challenges as consequences even beyond the pandemic.
Subclassification of Breast Cancer through Comprehensive Multi-omics Data to Benefit Distinct Survival Outcomes
Authors: Fan Yuxuan , Zhang Ling , Gao Zhaorong , Wei Jiayi , Wang Jun , Shi Xiujing , Guo Zhen , Wang Xiao 
Published: November 2022

Abstract

Breast cancer is a heterogeneous complex of disease consisting of several subtypes which display different biological and clinical behaviors. Traditional classification methods regarding histological types, tumor size and histological grade have limitations in classification of breast cancer subtypes. In the past decade, the development of high-throughput technologies in omics allowed us to discover breast cancer’s molecular subtypes and biomarkers. In this study, different feature selection techniques consist of t-test, least absolute shrinkage and selection operator (LASSO) and Boruta were applied to select the most significant features from the omics data, including exon expression RNA-seq, methylation450k and gene expression RNA-seq collected from The Cancer Genome Atlas (TCGA). The significant features being selected were used as inputs for machine learning classifiers for breast cancer classification. We evaluated five different classification models including random forest (RF), support vector machine (SVM), naive Bayes (NB), k-Nearest Neighbor (KNN), and multivariate adaptive regression splines (MARS). The results show that the performances of the combined model based on exon expression and gene expression RNA-seq were better than other classification methods in terms of accuracy. Interestingly, our partitioning of luminal samples by SVM, NB and MARS would have a clinical advantage over the PAM50 partition of the luminal samples though their predictions only moderately agree with PAM50 calls. Based on the methylation data, the screened four methylation-driven genes (PRDM16, ADPRHL1, SPRY1, and TBCC) were identified to associate with tumorigenesis. Moreover, survival analysis showed DNA methylation profiles improved prediction of survival outcomes for luminal A and luminal B subtypes. Our results suggested that RNA-seq, exon expression and methylation hold complementary information for classifying breast cancer subtypes. Analysis of samples using methylation data demonstrates that the sample partitions predicted by SVM, NB and MARS show a higher relation with methylation patterns. We delineated genomic epigenomic characteristic for breast cancer subtypes as well as their specific survival. Compared with the PAM50 standard, our improved and refined feature selection and classification provide diagnostic markers and may contribute to the precision of diagnosis and thus, to more personalized treatment.