Nonparametric Statistics

Ramachandran, Kandethody M.; Tsokos, Chris P.

doi:10.1016/b978-0-12-817815-7.00012-9

Cited by 48 publications

(63 citation statements)

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“…The data were found to be not normally distributed (p < 0.001), so to compare the usage of green space before and after the pandemic between essential workers and nonessential workers and between females and males we performed a non-parametric Mann-Whitney U test. We tested the null hypothesis that the two groups had identical distributions and the alternative hypothesis that the group medians were different [42,43]. The significance level was set at p < 0.05.…”

Section: Discussionmentioning

confidence: 99%

Has the Pandemic Altered Public Perception of How Local Green Spaces Affect Quality of Life in the United Kingdom?

Crossley

Russo

2022

Sustainability

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Green spaces unquestionably improve both physical and mental health, but there is little information on how they affect quality of life. This study investigates whether the public perception of how local green spaces and their impact on quality of life have altered as a result of restrictions imposed by the U.K.’s SARS-CoV-2 pandemic containment strategy. Qualitative data were collected using an online questionnaire distributed via social media platforms and postal flyers. The results clearly demonstrate that 90% of participants believe that green spaces improved their quality of life during the pandemic, with over 85% thinking that green spaces will continue to have a positive impact on their quality of life once the pandemic is over. Whether this is a permanent change in public thinking or a short-term adaptation to the stresses of the pandemic can be assessed in future research studies. More detailed research is required to understand more clearly the aspects and types of green spaces that are the most valuable for improving quality of life so that future ones can be designed to provide maximum benefits.

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Section: Discussionmentioning

confidence: 99%

Has the Pandemic Altered Public Perception of How Local Green Spaces Affect Quality of Life in the United Kingdom?

Crossley

Russo

2022

Sustainability

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“…Moreover, the same ML/DL framework has been trained on the multi PI-RADS development set and evaluated on the multi PI-RADS test set. In order to consider the variability in the AUROC measurement due to the randomness of our test data, we drew additional bootstrap test sets of size equal to the original test set’s one ( 67 , 68 ). Briefly, we randomly sampled, with replacement, the original test set data at the lesion level.…”

Section: Methodsmentioning

confidence: 99%

Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI

et al. 2022

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Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa aggressiveness, for which a biopsy is required, is fundamental for patient management. Currently, multiparametric (mp) MRI is strongly recommended before biopsy. Quantitative assessment of mpMRI might provide the radiologist with an objective and noninvasive tool for supporting the decision-making in clinical practice and decreasing intra- and inter-reader variability. In this view, high dimensional radiomics features and Machine Learning (ML) techniques, along with Deep Learning (DL) methods working on raw images directly, could assist the radiologist in the clinical workflow. The aim of this study was to develop and validate ML/DL frameworks on mpMRI data to characterize PCas according to their aggressiveness. We optimized several ML/DL frameworks on T2w, ADC and T2w+ADC data, using a patient-based nested validation scheme. The dataset was composed of 112 patients (132 peripheral lesions with Prostate Imaging Reporting and Data System (PI-RADS) score ≥ 3) acquired following both PI-RADS 2.0 and 2.1 guidelines. Firstly, ML/DL frameworks trained and validated on PI-RADS 2.0 data were tested on both PI-RADS 2.0 and 2.1 data. Then, we trained, validated and tested ML/DL frameworks on a multi PI-RADS dataset. We reported the performances in terms of Area Under the Receiver Operating curve (AUROC), specificity and sensitivity. The ML/DL frameworks trained on T2w data achieved the overall best performance. Notably, ML and DL frameworks trained and validated on PI-RADS 2.0 data obtained median AUROC values equal to 0.750 and 0.875, respectively, on unseen PI-RADS 2.0 test set. Similarly, ML/DL frameworks trained and validated on multi PI-RADS T2w data showed median AUROC values equal to 0.795 and 0.750, respectively, on unseen multi PI-RADS test set. Conversely, all the ML/DL frameworks trained and validated on PI-RADS 2.0 data, achieved AUROC values no better than the chance level when tested on PI-RADS 2.1 data. Both ML/DL techniques applied on mpMRI seem to be a valid aid in predicting PCa aggressiveness. In particular, ML/DL frameworks fed with T2w images data (objective, fast and non-invasive) show good performances and might support decision-making in patient diagnostic and therapeutic management, reducing intra- and inter-reader variability.

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“…PANNZER2 [ 105 ] and InterProScan [ 106 , 107 ] were used to predict the functions associated with proteins. All the statistical analyses were performed in an R statistical environment (version 3.6.3) [ 108 , 109 ].…”

Section: Methodsmentioning

confidence: 99%

Proteomic Analysis Reveals Enzymes for β-D-Glucan Formation and Degradation in Levilactobacillus brevis TMW 1.2112

Bockwoldt

Meng

Ludwig

et al. 2022

IJMS

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Bacterial exopolysaccharide (EPS) formation is crucial for biofilm formation, for protection against environmental factors, or as storage compounds. EPSs produced by lactic acid bacteria (LAB) are appropriate for applications in food fermentation or the pharmaceutical industry, yet the dynamics of formation and degradation thereof are poorly described. This study focuses on carbohydrate active enzymes, including glycosyl transferases (GT) and glycoside hydrolases (GH), and their roles in the formation and potential degradation of O2-substituted (1,3)-β-D-glucan of Levilactobacillus (L.) brevis TMW 1.2112. The fermentation broth of L. brevis TMW 1.2112 was analyzed for changes in viscosity, β-glucan, and D-glucose concentrations during the exponential, stationary, and early death phases. While the viscosity reached its maximum during the stationary phase and subsequently decreased, the β-glucan concentration only increased to a plateau. Results were correlated with secretome and proteome data to identify involved enzymes and pathways. The suggested pathway for β-glucan biosynthesis involved a β-1,3 glucan synthase (GT2) and enzymes from maltose phosphorylase (MP) operons. The decreased viscosity appeared to be associated with cell lysis as the β-glucan concentration did not decrease, most likely due to missing extracellular carbohydrate active enzymes. In addition, an operon was discovered containing known moonlighting genes, all of which were detected in both proteome and secretome samples.

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Nonparametric Statistics

Cited by 48 publications

References 0 publications

Has the Pandemic Altered Public Perception of How Local Green Spaces Affect Quality of Life in the United Kingdom?

Has the Pandemic Altered Public Perception of How Local Green Spaces Affect Quality of Life in the United Kingdom?

Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI

Proteomic Analysis Reveals Enzymes for β-D-Glucan Formation and Degradation in Levilactobacillus brevis TMW 1.2112

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