bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and metabolomic characterization of potent anti-MRSA phloroglucinol derivatives from Dryopteris crassirhizoma Nakai (Polypodiaceae)
Authors: Bhowmick Sumana , Beckmann Manfred , Shen Jianying , Mur Luis A. J. 
Published: October 2022

Traditional Chinese medicine (TCM) has been used to treat infectious diseases and could offer potential drug leads. This study evaluates the in vitro antimicrobial activities from commercially sourced Dryopteris crassirhizoma Nakai (Polypodiaceae) whose authenticity was confirmed by DNA barcoding based on the ribulose bisphosphate carboxylase (rbcL) gene. Powdered rhizomes were sequentially extracted using n-hexane, dichloromethane, ethyl acetate, and methanol at ambient temperature. The dried extracts at different concentrations were tested for antimicrobial activities against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, methicillin-resistant Staphylococcus aureus (MRSA), and Mycobacterium smegmatis. D. crassirhizoma extracts exhibited significant antimicrobial activities only against MRSA (minimum inhibitory concentration: 3.125 μg/ml n-hexane extract). Activity-led fractionations of D. crassirhizoma and characterization by ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) targeted a fraction (A3), with two anti-MRSA phloroglucinol derivatives, flavaspidic acid AB and norflavaspidic acid AB—being greatly enriched in the latter. The impact of A3 on MRSA cells was examined using untargeted metabolomic analysis and compared to that of other established antibiotics (all treatments normalized to MIC50 at 6 h). This suggested that norflavaspidic acid AB had distinctive effects, one of which involved targeting bioenergetic transformation, metabolism, and particularly acetyl-CoA, on MRSA cells. No cytotoxicity was observed for the norflavaspidic acid AB-enriched fraction against murine HepG2 cells. This study requires further experimental validation but can have indicated a naturally available compound that could help counter the threat of clinically relevant strains with antibiotic resistance.
Astragalus saponins and its main constituents ameliorate ductular reaction and liver fibrosis in a mouse model of DDC-induced cholestatic liver disease
Authors: Zhang Linzhang , Hu Yonghong , Qi Shenglan , Zhang Congcong , Zhou Qun , Zhang Dingqi , Mu Yongping , Zhang Hua , Chen Gaofeng , Liu Ping , Chen Jiamei , Liu Wei 
Published: October 2022

Cholestatic liver disease (CLD) is a chronic liver disease characterized by ductular reaction, inflammation and fibrosis. As there are no effective chemical or biological drugs now, majority of CLD patients eventually require liver transplantation. Astragali radix (AR) is commonly used in the clinical treatment of cholestatic liver disease and its related liver fibrosis in traditional Chinese medicine, however its specific active constituents are not clear. Total astragalus saponins (ASTs) were considered to be the main active components of AR. The aim of this study is to investigate the improvement effects of the total astragalus saponins (ASTs) and its main constituents in cholestatic liver disease. The ASTs from AR was prepared by macroporous resin, the content of saponins was measured at 60.19 ± 1.68%. The ameliorative effects of ASTs (14, 28, 56 mg/kg) were evaluated by 3, 5-Diethoxycarbonyl-1, 4-dihydrocollidine (DDC)-induced CLD mouse model. The contents of hydroxyproline (Hyp), the mRNA and protein expression of cytokeratin 19 (CK19) and α-smooth muscle actin (α-SMA) in liver tissue were dose-dependently improved after treatment for ASTs. 45 astragalus saponins were identified in ASTs by UHPLC-Q-Exactive Orbitrap HRMS, including astragaloside I, astragaloside II, astragaloside III, astragaloside IV, isoastragaloside I, isoastragaloside II, cycloastragenol, etc. And, it was found that ductular reaction in sodium butyrate-induced WB-F344 cell model were obviously inhibited by these main constituents. Finally, the improvement effects of astragaloside I, astragaloside II, astragaloside IV and cycloastragenol (50 mg/kg) were evaluated in DDC-induced CLD mice model. The results showed that astragaloside I and cycloastragenol significantly improved mRNA and protein expression of CK19 and α-SMA in liver tissue. It suggested that astragaloside I and cycloastragenol could alleviate ductular reaction and liver fibrosis. In summary, this study revealed that ASTs could significantly inhibit ductular reaction and liver fibrosis, and astragaloside I and cycloastragenol were the key substances of ASTs for treating cholestatic liver disease.
Precision frequency transfer with fiber frequency combs
Authors: Fermann Martin E. , Lee Kevin F. , Li Peng , Rolland Antoine , Jiang Jie 
Published: October 2022

We review methods for precision transfer of frequencies across broad optical wavelength ranges. Single-branch supercontinuum generation allows for a frequency transfer stability of &lt; 1 × 10−17in 1 s across an octave. With supercontinuum stitching, highly coherent supercontinuum spectra spanning across more than two octaves are generated. With noise cancellation techniques a relative frequency transfer stability of ≈ 2 × 10−18in 1 s can be achieved. Highly stable frequency transfer along with a maximization of power per mode at multiple freely selectable frequency bands is further enabledviapulse shaping techniques. We also include a brief review of general fiber combs and research aimed at frequency extension of frequency combs covering the whole spectral range from the XUV to the mid IR, power scaling of frequency combs as well as low noise microwave and mmwave technology enabled with frequency combs.
Reproducible phantom for quality assurance in abdominal MRI focussing kidney imaging
Authors: Wolf Marcos , Kommer Stefan , Fembek Sebastian , Dröszler Uwe , Körner Tito , Berg Andreas , Schmid Albrecht Ingo , Moser Ewald , Meyerspeer Martin 
Published: October 2022

Quality assurance (QA) in magnetic resonance imaging (MRI) requires test objects. ‘Phantoms’ provided by MR manufacturers are homogeneously filled spheres or cylinders, and commercially available products are often too small for abdominal imaging, particularly for enlarged polycystic kidneys. Here we present the design, manufacturing and testing of a dedicated, yet versatile, abdominal MRI phantom, that can be reproduced with relatively low costs. The phantom mimics a human abdomen in size and shape and comprises seven test fluids, representing various tissue types at 3 T. The conductivity and permittivity of the test fluids match the average abdomen and kidney with a relative permittivity (ε) 65 and 72 as well as conductivity 0.6 and 0.7 S/m, respectively. The T1 and T2 relaxation times cover healthy average abdomen and kidney tissue values (T1(abd): 856 ms and T1(kid): 1,106 ms; T2(abd): 52 ms and T2(kid): 67 ms), intermediate (T1: 1,183 ms and 1,271 ms; T2: 128 and 189 ms), and disease values for (polycystic) kidney (T1: 1,428 ms, 1,561 ms and 1763 ms; T2: 319 ms, 424 and 647 ms). T1 and T2 relaxation times were stable over 73 weeks. Our reasonably priced, durable and reproducible abdominal phantom enables single and multi-center QA for future collaborative studies aiming for various challenges around abdominal and, particularly, kidney imaging.
Through network pharmacology and molecular docking to explore the underlying mechanism of Artemisia annua L. treating in abdominal aortic aneurysm
Authors: Jia Longyuan , Jing Yuchen , Wang Ding , Cheng Shuai , Fu Chen , Chu Xiangyu , Yang Chenye , Jiang Bo , Xin Shijie 
Published: October 2022

Background: Abdominal aortic aneurysm (AAA) is a degenerative disease that causes health problems in humans. However, there are no effective drugs for the treatment of AAA. Artemisia annua L. (A. annua) is a traditional herbal that has been widely used in cardiovascular disease. Based on network pharmacology and molecular docking technology, this study predicted the practical components and potential mechanisms of A. annua inhibiting the occurrence and development of AAA.Methods: The main active ingredients and targets of A. annua were screened through the TCMSP database; the GeneCards, OMIM, PharmGkb, and TTD databases were used to search for the targeted genes of AAA and map them to the targets of the active ingredients to obtain the active ingredient therapy of A. annua. The targets of AAA were to construct a protein interaction network through the STRING platform. R software was used to carry out the enrichment analysis of GO and KEGG for relevant targets, and Cytoscape was used to construct the active ingredient-target network prediction model of A. annua. Finally, AutoDock Vina was used to verify the results of the active ingredients and critical targets.Results: The main active ingredients obtained from A. annua for the treatment of AAA include quercetin, luteolin, kaempferol, isorhamnetin, and artemetin, as well as 117 effective targets, including RELA, MAPK14, CCND1, MAPK1, AKT1, MYC, MAPK8, TP53, ESR1, FOS, and JUN. The 11 targeted genes might play a key role in disease treatment. Enriched in 2115 GO biological processes, 159 molecular functions, 56 cellular components, and 156 KEGG pathways, inferred that its mechanism of action might be related to PI3K-Akt signaling pathway, fluid shear stress, atherosclerosis, and AGE-RAGE signaling pathway. Molecular docking results showed that the top five active components of A. annua had a good affinity for core disease targets and played a central role in treating AAA. The low binding energy molecular docking results provided valuable information for the development of drugs to treat AAA.Conclusion: Therefore, A. annua may have multiple components, multiple targets, and multiple signaling pathways to play a role in treating AAA. A. annua may have the potential to treat AAA.
Comparative transcriptome profiling reveals the role of phytohormones and phenylpropanoid pathway in early-stage resistance against powdery mildew in watermelon (Citrullus lanatus L.)
Authors: Yadav Vivek , Wang Zhongyuan , Guo Yanliang , Zhang Xian 
Published: October 2022

Yield and fruit quality loss by powdery mildew (PM) fungus is a major concern in cucurbits, but early-stage resistance mechanisms remain elusive in the majority of cucurbits. Here, we explored the comparative transcriptomic dynamics profiling of resistant line ZXG1755 (R) and susceptible line ZXG1996 (S) 48 h post-inoculation in watermelon seedlings to check precise expression changes induced by Podosphaera. xanthii race ‘2F’. Phenotypic responses were confirmed by microscopy and endogenous levels of defense and signaling related phytochromes were detected higher in resistant lines. In total, 7642 differently expressed genes (DEGs) were detected, and 57.27% of genes were upregulated in four combinations. DEGs were predominantly abundant in the KEGG pathway linked with phenylpropanoid biosynthesis, plant hormone and transduction, and phenylalanine metabolism, whereas GO terms of defense response, response to fungus, and chitin response were predominant in resistant lines, evidencing significant defense mechanisms and differences in the basal gene expression levels between these contrasting lines. The expression of selected DEGs from major pathways (hormonal, lignin, peroxidase, sugar) were validated via qRT-PCR. Detailed analysis of DEGs evidenced that along with other DEGs, genes including PR1 (Cla97C02G034020) and PRX (Cla97C11G207220/30, Cla97C02G045100 and Cla97C02G049950) should be studied for their potential role. In short, our study portrayed strong evidence indicating the important role of a complex network associated with lignin biosynthesis and phytohormone related downstream mechanisms that are responsible for incompatible interaction between PM and watermelon resistance line.
A wheat spike detection method based on Transformer
Authors: Zhou Qiong , Huang Ziliang , Zheng Shijian , Jiao Lin , Wang Liusan , Wang Rujing 
Published: October 2022

Wheat spike detection has important research significance for production estimation and crop field management. With the development of deep learning-based algorithms, researchers tend to solve the detection task by convolutional neural networks (CNNs). However, traditional CNNs equip with the inductive bias of locality and scale-invariance, which makes it hard to extract global and long-range dependency. In this paper, we propose a Transformer-based network named Multi-Window Swin Transformer (MW-Swin Transformer). Technically, MW-Swin Transformer introduces the ability of feature pyramid network to extract multi-scale features and inherits the characteristic of Swin Transformer that performs self-attention mechanism by window strategy. Moreover, bounding box regression is a crucial step in detection. We propose a Wheat Intersection over Union loss by incorporating the Euclidean distance, area overlapping, and aspect ratio, thereby leading to better detection accuracy. We merge the proposed network and regression loss into a popular detection architecture, fully convolutional one-stage object detection, and name the unified model WheatFormer. Finally, we construct a wheat spike detection dataset (WSD-2022) to evaluate the performance of the proposed methods. The experimental results show that the proposed network outperforms those state-of-the-art algorithms with 0.459 mAP (mean average precision) and 0.918 AP50. It has been proved that our Transformer-based method is effective to handle wheat spike detection under complex field conditions.
Risk factors for worsening of somatic symptom burden in a prospective cohort during the COVID-19 pandemic
Authors: Engelmann Petra , Löwe Bernd , Brehm Thomas Theo , Weigel Angelika , Ullrich Felix , Addo Marylyn M. , Schulze zur Wiesch Julian , Lohse Ansgar W. , Toussaint Anne 
Published: October 2022

IntroductionLittle is known about risk factors for both Long COVID and somatic symptoms that develop in individuals without a history of COVID-19 in response to the pandemic. There is reason to assume an interplay between pathophysiological mechanisms and psychosocial factors in the etiology of symptom persistence.ObjectiveTherefore, this study investigates specific risk factors for somatic symptom deterioration in a cohort of German adults with and without prior SARS-CoV-2 infection.MethodsGerman healthcare professionals underwent SARS-CoV-2 IgG antibody testing and completed self-rating questionnaires at baseline and 21 months later between April 2020 and February 2022. Differences in variables between the time points were analyzed and a regression analysis was performed to predict somatic symptom deterioration at follow-up.ResultsSeven hundred fifty-one adults completed both assessments. Until follow-up, n = 58 had contracted SARS-CoV-2 confirmed by serology. Between baseline and follow-up, signs of mental and physical strain increased significantly in the sample. Symptom expectations associated with COVID-19 and a self-reported history of COVID-19, but not serologically confirmed SARS-CoV-2 infection, significantly predicted somatic symptom deterioration at follow-up. A further predictor was baseline psychological symptom burden.ConclusionsThis study supports a disease-overarching biopsychosocial model for the development of burdensome somatic symptoms during the COVID-19 pandemic and supports research findings that symptom burden may be more related to the psychosocial effects of the pandemic than to infection itself. Future studies on Long COVID should include SARS-CoV-2 negative control groups and consider symptom burden prior to infection in order to avoid an overestimation of prevalence rates.
RETRACTED: Empirical analysis of the integration mechanism of explicit and implicit education on the ideological and political education and impact on mental health: The perspective of new media
Authors: Hui Dong 
Published: October 2022

BackgroundEducation nowadays should be a combination of explicit and implicit education, which can effectively improve the effectiveness of ideological and political education, promote the development of ideological and political education in universities, and ensure the quality of ideological and political education in universities. This study makes an empirical analysis of the integration mechanism of explicit education and implicit education of ideological and political education from the perspective of new media.Materials and methodsA total of 1,050 students were included from the polytechnic university of China in the analysis. Questions regarding age, sex, source of information collections, Internet time, type of browsers used, and the influence of the Internet were asked of the students. The nine-item Patient Health Questionnaire was administered to measure the students' depressive symptoms. A comprehensive study was done to prove the depressive symptoms in students from the perspective of new media.ResultsA total of 78 % of students collected information from the Internet, and 1 % of students collected information from books. Most of the students spent more than 1 h on the Internet per day. It was concluded from the data that 245 college students were always influenced by the Internet, accounting for 24%, and 730 college students were occasionally influenced by the Internet, accounting for 73%. Forty-two college students do not influence the Internet, accounting for 4%. It can be seen that 95.6% of college students will be affected by the Internet compared with those who will never be affected by the Internet. Therefore, the new media network has high popularity among college students, as online time accounts for a large proportion of their study time.ConclusionFrom the perspective of new media, the integration of explicit and implicit education in ideological and political education is feasible. In today's information age, education implementers need to use a large number of new media images to enable students to accept education in the integration mechanism. From the perspective of new media, it is also necessary to innovate the forms of reports, establish the integration mechanism of explicit education and implicit education, strengthen educational links and interactive exchanges, and promote university education.
Examining the influences on the use of behavioural science within UK local authority public health: Qualitative thematic analysis and deductive mapping to the COM-B model and Theoretical Domains Framework
Authors: Moffat Abby , Cook Erica Jane , Chater Angel Marie 
Published: October 2022

BackgroundBehavioural science and its contribution towards improving public health is receiving increased recognition. Yet, the translation of these insights into public health practice is under-researched. This study explored the factors influencing the use of behavioural science within public health at a local authority level.MethodsFourteen local authority staff (n = 13 female) in the south of England participated in semi-structured interviews, which were analysed inductively to identify key themes. These were later mapped deductively to the COM-B model and Theoretical Domains Framework.FindingsNine themes were identified as factors that influence the use of behavioural science in local authority public health: (1) “Limited past experience,” (2) “Narrow understanding,” (3) “Perceived value of behavioural science,” (4) “Translational gap from theory-to-practice,” (5) “No protected time,” (6) “Old ways of working,” (7) “Political influence and organisational culture,” (8) “Relationships with key stakeholders,” (9) “Access to behavioural science resources”. Deductive mapping of these themes revealed that five of the COM constructs (excluding Physical Capability) and eleven of the TDF domains influenced behavioural science use, with “Social influences” and “Knowledge” being the most prominent.DiscussionUse of behavioural science within local authority public health practice is limited and inconsistent. For it to be successfully implemented, there must be an understanding of its role and value, alongside strategies to overcome a translational gap from theory to practice. Public health teams would benefit from protected time to enable application and strategies to break old habits of using a common-sense approach. System-wide buy-in, particularly related to senior leadership and system partners is needed, which would benefit from organisational and political culture change. Training opportunities, practical resources and expert in-house support should be considered a priority across public health teams.
Predictors for adherent behavior in the COVID-19 pandemic: A cross-sectional telephone survey
Authors: Siebenhofer Andrea , Könczöl Clemens , Jeitler Klaus , Schmid Daniela , Elliott Phillip , Avian Alexander 
Published: October 2022

BackgroundDuring the COVID-19 pandemic, protective measures have been prescribed to prevent or slow down the spread of the SARS-CoV-2 virus and protect the population. Individuals follow these measures to varying degrees. We aimed to identify factors influencing the extent to which protective measures are adhered to.MethodsA cross-sectional survey (telephone interviews) was undertaken between April and June 2021 to identify factors influencing the degree to which individuals adhere to protective measures. A representative sample of 1,003 people (age &gt;16 years) in two Austrian states (Carinthia, Vorarlberg) was interviewed. The questionnaire was based on the Health Belief Model, but also included potential response-modifying factors. Predictors for adherent behavior were identified using multiple regression analysis. All predictors were standardized so that regression coefficients (β) could be compared.ResultsOverall median adherence was 0.75 (IQR: 0.5–1.0). Based on a regression model, the following variables were identified as significant in raising adherence: higher age (β = 0.43, 95%CI: 0.33–0.54), social standards of acceptable behavior (β = 0.33, 95%CI: 0.27–0.40), subjective/individual assessment of an increased personal health risk (β = 0.12, 95%CI: 0.05–0.18), self-efficacy (β = 0.06, 95%CI: 0.02–0.10), female gender (β = 0.05, 95%CI: 0.01–0.08), and low corona fatigue (behavioral fatigue: β = −0.11, 95%CI: −0.18 to −0.03). The model showed that such aspects as personal trust in institutions, perceived difficulties in adopting health-promoting measures, and individual assessments of the risk of infection, had no significant influence.ConclusionsThis study reveals that several factors significantly influence adherence to measures aimed at controlling the COVID-19 pandemic. To enhance adherence, the government, media, and other relevant stakeholders should take the findings into consideration when formulating policy. By developing social standards and promoting self-efficacy, individuals can influence the behavior of others and contribute toward coping with the pandemic.