cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14781839
title: Proteomic response of tea plants stimulated by ammonium supply

description: Ammonium (NH<sub>4</sub><sup>+</sup>) is a major nitrogen source for tea plant growth. Although NH<sub>4</sub><sup>+</sup>-induced growth of tea plants were reported, it was still unclear to elucidate the mechanism of proteins in tea plants in responding to NH<sub>4</sub><sup>+</sup> resupply. In the present study, the proteomic profiles of tea leaves under N deficiency/resupply were investigated by using LC-MS/MS and PRM technique. Compared with N deficiency, there were 247 and 328 proteins significantly expressed after 3 h and 3d of N resupplied, respectively. And compared with 3 h of N resupplied, there were 186 proteins significantly expressed after 3d of N resupplied. According to bioinformatics analysis, the results showed that different expressed proteins participated in various biological processes, such as PsbO, Pbs27, PsaN, and PsaF were involved in photosynthesis, ADH1, AOC3, URE, GDH1-2, and argD were involved in amino acid metabolism, CHI and ANR were involved in flavonoid biosynthesis, GSTF9, APX, and GSS were involved in glutathione metabolism, and PdxT and PdxS were involved in vitamin B6 metabolism. Through PPI analysis, the results showed that the interactions between different expressed proteins mainly occurred in the photosynthetic pathway. Ammonium supply has a profound impact on photosynthesis, amino acid metabolism, flavonoid biosynthesis, glutathione metabolism, and vitamin B6 metabolism.
DOI: 10.25582/data.2023-01.2720458/2291821
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731908/2291822
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731513/2291823
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732137/2291824
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731528/2291825
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2718003/2291826
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2720691/2291827
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731674/2291828
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732078/2291829
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.22121892
title: Safety and efficacy of glucocorticoids in the treatment of COVID-19: A meta-analysis of randomized control trials

description: It is unclear the efficacy and safety of glucocorticoids compared with placebo or usual care for treatment of COVID-19. Randomized controlled trials (RCTs) of corticosteroids in COVID-19 patients from 1 December 2019, to 30 June 2022, were assessed using Cochrane bias risk assessment method and improved Jadad score scale. GRADEpro was used to rate the quality of evidence for outcomes. Fifteen RCTs were included, including 10,620 patients. Glucocorticoid treatment for severe and critical COVID-19 showed lesser all-cause mortality (OR = 0.85, 95% CI [0.76, 0.94], P = 0.002) than conventional treatment. However, for mildly ill patients, neither inhaled drugs nor intravenous drugs reduced mortality (OR = 0.64, 95% CI [0.24, 1.76], P = 0.39). Glucocorticoids had no significant effect on the adverse reactions of patients (OR = 1.18, 95% CI [0.77, 1.80], P = 0.44) compared with usual care/placebo. Subgroup analysis demonstrated that dexamethasone significantly reduced the mortality of COVID-19 patients. Low-dose glucocorticoids were also associated with lower all-cause mortality. Glucocorticoids (especially dexamethasone) reduce mortality of patients with severe and critical COVID-19 with no significant effect on the incidence of adverse reactions (moderate quality). In contrast, glucocorticoids do not benefit patients with mild symptoms (low quality).
DOI: 10.6084/m9.figshare.22121892.v1
title: Safety and efficacy of glucocorticoids in the treatment of COVID-19: A meta-analysis of randomized control trials

description: It is unclear the efficacy and safety of glucocorticoids compared with placebo or usual care for treatment of COVID-19. Randomized controlled trials (RCTs) of corticosteroids in COVID-19 patients from 1 December 2019, to 30 June 2022, were assessed using Cochrane bias risk assessment method and improved Jadad score scale. GRADEpro was used to rate the quality of evidence for outcomes. Fifteen RCTs were included, including 10,620 patients. Glucocorticoid treatment for severe and critical COVID-19 showed lesser all-cause mortality (OR = 0.85, 95% CI [0.76, 0.94], P = 0.002) than conventional treatment. However, for mildly ill patients, neither inhaled drugs nor intravenous drugs reduced mortality (OR = 0.64, 95% CI [0.24, 1.76], P = 0.39). Glucocorticoids had no significant effect on the adverse reactions of patients (OR = 1.18, 95% CI [0.77, 1.80], P = 0.44) compared with usual care/placebo. Subgroup analysis demonstrated that dexamethasone significantly reduced the mortality of COVID-19 patients. Low-dose glucocorticoids were also associated with lower all-cause mortality. Glucocorticoids (especially dexamethasone) reduce mortality of patients with severe and critical COVID-19 with no significant effect on the incidence of adverse reactions (moderate quality). In contrast, glucocorticoids do not benefit patients with mild symptoms (low quality).
DOI: 10.25582/data.2023-01.2717920/2291830
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731922/2291831
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25549/usctheses-ouc11293946
title: THESIS TEMPLATE
DOI: 10.25582/data.2023-01.2717916/2291832
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2718668/2291833
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731599/2291834
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.11636154
title: MOESM9 of Receptor kinase FERONIA regulates flowering time in Arabidopsis

description: Additional file 9: Table S1. Genes with significant (&gt; 2-fold, p &lt; 0.05) expression in fer-4 compare with WT as determined by RNA-seq anaylsis.
DOI: 10.25582/data.2023-01.2720561/2291835
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.11636154.v1
title: MOESM9 of Receptor kinase FERONIA regulates flowering time in Arabidopsis

description: Additional file 9: Table S1. Genes with significant (&gt; 2-fold, p &lt; 0.05) expression in fer-4 compare with WT as determined by RNA-seq anaylsis.
DOI: 10.25582/data.2023-02.2731762/2291836
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2726032/2291837
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25549/usctheses-c3-256657
title: Meditation and round dance (Kolo) for clarinet in B?, violin, cello and piano
DOI: 10.25582/data.2023-01.2720481/2291838
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731536/2291839
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2720673/2291840
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2713160/2291841
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2713491/2291842
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.11636178
title: MOESM2 of CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

description: Additional file 2 Table S1. Table of genomic regions modeled for this study.
DOI: 10.6084/m9.figshare.11636178.v1
title: MOESM2 of CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

description: Additional file 2 Table S1. Table of genomic regions modeled for this study.
DOI: 10.25582/data.2023-01.2714760/2291843
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731705/2291844
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.11636181
title: MOESM3 of CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

description: Additional file 3 Table S2. Table of public biological datasets used for predictive modeling of genomic regions enriched in many-body principal loop participation.
DOI: 10.6084/m9.figshare.11636181.v1
title: MOESM3 of CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

description: Additional file 3 Table S2. Table of public biological datasets used for predictive modeling of genomic regions enriched in many-body principal loop participation.
DOI: 10.25582/data.2023-02.2731833/2291845
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.11636184
title: MOESM4 of CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

description: Additional file 4 Table S3. Table of LILY [64] annotations for super-enhancer, enhancer, and promoter genomic regions.
DOI: 10.25582/data.2023-01.2722563/2291846
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.11636184.v1
title: MOESM4 of CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci from deconvolved single cells

description: Additional file 4 Table S3. Table of LILY [64] annotations for super-enhancer, enhancer, and promoter genomic regions.
DOI: 10.25582/data.2023-01.2713668/2291847
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732187/2291848
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731895/2291849
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732136/2291850
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2717947/2291851
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.10062734.v1
title: Visualization from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: visualization.R is the script to perform statistical analysis.
DOI: 10.6084/m9.figshare.10062731
title: reputationdynamics from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: reputationdynamics.m is the script to calculate reputation of firms.
DOI: 10.6084/m9.figshare.10062737.v1
title: Perron from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: perron.m is the function file to calculate eigen value.
DOI: 10.25582/data.2023-01.2719543/2291852
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.10062743.v1
title: firm_properties.csv from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: This file contains the id, integrated control value and operating value of firms.
DOI: 10.6084/m9.figshare.10062737
title: Perron from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: perron.m is the function file to calculate eigen value.
DOI: 10.6084/m9.figshare.14256995.v1
title: Additional file 7 of A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations

description: Additional file 7. Predictions of potential lncRNA-disease association on Dataset2
DOI: 10.25582/data.2023-02.2732084/2291853
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.10062752
title: Eigen from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: eigen.txt contains the eigen values of the ownership network.
DOI: 10.6084/m9.figshare.10062734
title: Visualization from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: visualization.R is the script to perform statistical analysis.
DOI: 10.6084/m9.figshare.10062749
title: ownership network.txt from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: This file describes the ownership network used in the paper. Each line i,j,w denotes the ownership between firm i and firm j with weight w.
DOI: 10.6084/m9.figshare.14256974
title: Additional file 1 of A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations

description: Additional file 1. AUROC and AUPR values of VGAELDA in 5 times
DOI: 10.25582/data.2023-01.2720507/2291854
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.10062746
title: Network from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: network.txt contains a list of weighted edges. Each line i,j,w describes ownership between firm i and firm j.
DOI: 10.6084/m9.figshare.10062746.v1
title: Network from The interdependence of corporate reputation and ownership: a network approach to quantify reputation

description: network.txt contains a list of weighted edges. Each line i,j,w describes ownership between firm i and firm j.
DOI: 10.6084/m9.figshare.14256992.v1
title: Additional file 6 of A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations

description: Additional file 6. Predictions of potential lncRNA-disease association on Dataset1
DOI: 10.6084/m9.figshare.14256995
title: Additional file 7 of A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations

description: Additional file 7. Predictions of potential lncRNA-disease association on Dataset2
DOI: 10.25582/data.2023-01.2720566/2291855
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.14256974.v1
title: Additional file 1 of A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations

description: Additional file 1. AUROC and AUPR values of VGAELDA in 5 times
DOI: 10.25582/data.2023-02.2732073/2291856
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.20024411.v1
title: ANALYSIS AND RESEARCH ON THE KEY FACTORS OF SPORTS IN MAINTAINING HUMAN HEALTH

description: ABSTRACT Introduction The research on the promotion of physical fitness of the human body by exercise has also attracted widespread attention in sports and rehabilitation medicine. Object This article uses ultrasound to study the bone density health of the human body, thereby establishing the relationship between sports and bone density health. We hope to use the research results of this article to improve people’s awareness of sports health. Method We used ultrasound to test the bone mineral density of two groups of students (exercise group and non-exercise group) to explore the relationship between different sports items and the students’ bone mineral density. Results There is a significant difference in bone density between the two groups of students. There is no gender difference in bone density. Conclusion Students need to strengthen physical exercise in the growth and development stage to improve bone density. Level of evidence II; Therapeutic studies - investigation of treatment results.
DOI: 10.6084/m9.figshare.20024418.v1
title: EFFECT OF METABOLIC ENZYMES ON ACCELERATION ABILITY IN EXERCISE FATIGUE

description: ABSTRACT Introduction Study the relationship between the metabolic enzyme and the biological image, filtered by an adaptive filtering algorithm. Objective The research aims to In this study, human metabolic enzymes were evaluated by electrocardiogram and electromyogram images, and an adaptive filtering algorithm removed the noises in the images. Methods The electrocardiogram and electromyogram images at different periods were obtained, and the calculation method and application scope of the adaptive filtering algorithm were analysed. Results Adaptive filter was designed by the combination of adaptive filtering algorithm and dynamic information. Therefore, the artefact of the image was removed. Conclusions The adaptive filtering algorithm can effectively remove the noise or artefact in electrocardiogram and electromyogram signals. The optimal image information can be obtained. Level of evidence II; Therapeutic studies - investigation of treatment results.
DOI: 10.6084/m9.figshare.20024221
title: Nebulizer versus metered dose inhaler with space chamber (MDI spacer) for acute asthma and chronic obstructive pulmonary disease exacerbation: attitudes of patients and healthcare providers in the COVID-19 era

description: Short-acting bronchodilators for asthma and chronic obstructive pulmonary disease (COPD) exacerbations are commonly delivered by nebulizers although administration using metered dose inhaler with space chamber (MDI spacer) has been shown to be equally efficacious. There are few studies examining patients’ and healthcare providers’ attitudes on the two administration methods in adults. This study explores patients’ and healthcare providers’ attitudes on the use of nebulizer versus MDI spacer for acute asthma and COPD exacerbations in adults. Patients admitted for asthma or COPD exacerbations, doctors, and nurses in a university-affiliated hospital were surveyed from 1 April 2021 to 30 September 2021 regarding their views on the effectiveness, ease of use, preparation and administration, side effects, and infection risk of the two administration methods. Ninety-nine patients, 103 doctors, and 650 nurses completed the survey. 60.6% of patients perceived nebulizer to be more effective. Patients who found nebulizer more comfortable were more likely to prefer nebulizer (OR 43.97, <i>p</i> = 0.01), while those who associated it with a greater infection risk were less likely to prefer nebulizer (OR 0.15, <i>p</i> = 0.03). 49.5% of doctors and 49.1% of nurses perceived nebulizer to be more effective, compared to 10.7% and 34.5%, respectively, for MDI spacer. Effectiveness and patient comfort influenced doctors’ and nurses’ preference for nebulizer while ease of preparation and administration influenced nurses’ preference only. Patients and healthcare providers perceived nebulizer to be more effective. Factors unique to each group influenced their preference for nebulizer.
DOI: 10.6084/m9.figshare.20024429
title: IMPROVED BIOLOGICAL IMAGE TRACKING ALGORITHM OF ATHLETE’S CERVICAL SPINE HEALTH

description: ABSTRACT Introduction This paper research an improved biological image tracking algorithm of athlete’s cervical spine health under color feedback. Objective A new algorithm is proposed to improve the accuracy of detection and tracking. Methods In this study, the first thing is to apply the color feedback algorithm to improve and optimize the Improved Camshift algorithm. The optimized algorithm was used to track the center of the image, and the video was processed frame by frame. The center position of the tracking frame was obtained. Results The average number of head twists per person is 39 times. Among the three groups, children twisted the least, and older adults twisted the most. Conclusion The algorithm proposed in this study has certain effectiveness and superiority and can be well applied to detecting the number of head twists during exercise. Level of evidence II; Therapeutic studies - investigation of treatment results.
DOI: 10.25582/data.2023-01.2718732/2291857
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.20024415.v1
title: APPLICATION OF BACK PROPAGATION NEURAL NETWORK IN SPORTS FATIGUE INDICATORS

description: ABSTRACT Introduction High-intensity rehabilitation training will produce exercise fatigue. Objective A backpropagation (BP) network neural algorithm is proposed to predict sports fatigue based on electromyography (EMG) signal images. Methods The principal component analysis algorithm is used to reduce the dimension of EMG signal features. The knee joint angle is estimated by the regularized over-limit learning machine algorithm and the BP neural network algorithm. Results The RMSE value of the regularized over-limit learning machine algorithm is lower than that of the BP neural network algorithm. At the same time, the ρ value of the regularized over-limit learning machine algorithm is closer to 1, indicating its higher accuracy. Conclusions The model training time of the regularized over-limit learning machine algorithm has been greatly reduced, which improves efficiency. Level of evidence II; Therapeutic studies - investigation of treatment results.
DOI: 10.6084/m9.figshare.20024429.v1
title: IMPROVED BIOLOGICAL IMAGE TRACKING ALGORITHM OF ATHLETE’S CERVICAL SPINE HEALTH

description: ABSTRACT Introduction This paper research an improved biological image tracking algorithm of athlete’s cervical spine health under color feedback. Objective A new algorithm is proposed to improve the accuracy of detection and tracking. Methods In this study, the first thing is to apply the color feedback algorithm to improve and optimize the Improved Camshift algorithm. The optimized algorithm was used to track the center of the image, and the video was processed frame by frame. The center position of the tracking frame was obtained. Results The average number of head twists per person is 39 times. Among the three groups, children twisted the least, and older adults twisted the most. Conclusion The algorithm proposed in this study has certain effectiveness and superiority and can be well applied to detecting the number of head twists during exercise. Level of evidence II; Therapeutic studies - investigation of treatment results.
DOI: 10.6084/m9.figshare.20024418
title: EFFECT OF METABOLIC ENZYMES ON ACCELERATION ABILITY IN EXERCISE FATIGUE

description: ABSTRACT Introduction Study the relationship between the metabolic enzyme and the biological image, filtered by an adaptive filtering algorithm. Objective The research aims to In this study, human metabolic enzymes were evaluated by electrocardiogram and electromyogram images, and an adaptive filtering algorithm removed the noises in the images. Methods The electrocardiogram and electromyogram images at different periods were obtained, and the calculation method and application scope of the adaptive filtering algorithm were analysed. Results Adaptive filter was designed by the combination of adaptive filtering algorithm and dynamic information. Therefore, the artefact of the image was removed. Conclusions The adaptive filtering algorithm can effectively remove the noise or artefact in electrocardiogram and electromyogram signals. The optimal image information can be obtained. Level of evidence II; Therapeutic studies - investigation of treatment results.