bluuebunny/crossref_metadata_2025_split huggingface dataset:
The potential of hyperpolarised 13C-MRI to target glycolytic tumour core in prostate cancer
Authors: Sushentsev Nikita , McLean Mary A. , Warren Anne Y. , Brodie Cara , Jones Julia , Gallagher Ferdia A. , Barrett Tristan 
Published: June 2022

Abstract
Hyperpolarised [1-13C]pyruvate MRI (HP-13C-MRI) is an emerging metabolic imaging technique that has shown promise for evaluating prostate cancer (PCa) aggressiveness. Accurate tumour delineation on HP-13C-MRI is vital for quantitative assessment of the underlying tissue metabolism. However, there is no consensus on the optimum method for segmenting HP-13C-MRI, and whole-mount pathology (WMP) as the histopathological gold-standard is only available for surgical patients. Although proton MRI can be used for tumour delineation, this approach significantly underestimates tumour volume, and metabolic tumour segmentation based on HP-13C-MRI could provide an important functional metric of tumour volume. In this study, we quantified metabolism using HP-13C-MRI and segmentation approaches based on WMP maps, 1H-MRI-derived T2-weighted imaging (T2WI), and HP-13C-MRI-derived total carbon signal-to-noise ratio maps (TC-SNR) with an SNR threshold of 5.0. 13C-labelled pyruvate SNR, lactate SNR, TC-SNR, and the pyruvate-to-lactate exchange rate constant (kPL) were significantly higher when measured using the TC-SNR-guided approach, which also corresponded to a significantly higher tumour epithelial expression on RNAscope imaging of the enzyme catalysing pyruvate-to-lactate metabolism (lactate dehydrogenase (LDH)). However, linear regression and Bland-Altman analyses demonstrated a strong linear relationship between all three segmentation approaches, which correlated significantly with RNA-scope-derived epithelial LDH expression. These results suggest that standard-of-care T2WI and TC-SNR maps could be used as clinical reference tools for segmenting localised PCa on HP-13C-MRI in the absence of the WMP gold standard. The TC-SNR-guided approach could be used clinically to target biopsies towards highly glycolytic tumour areas and therefore to sample aggressive disease with higher precision.

Key Points
• T2WI- and TC-SNR-guided segmentations can be used in all PCa patients and do not explicitly require WMP maps.
• Agreement between the three segmentation approaches is biologically validated by their strong relationship with epithelial LDH mRNA expression.
• The TC-SNR-guided approach can potentially be used to identify occult disease on1H-MRI and target the most glycolytically active regions.
Variation of plagioclase shape with size in intermediate magmas: a window into incipient plagioclase crystallisation
Authors: Mangler Martin F. , Humphreys Madeleine C. S. , Wadsworth Fabian B. , Iveson Alexander A. , Higgins Michael D. 
Published: June 2022

AbstractVolcanic rocks commonly display complex textures acquired both in the magma reservoir and during ascent to the surface. While variations in mineral compositions, sizes and number densities are routinely analysed to reconstruct pre-eruptive magmatic histories, crystal shapes are often assumed to be constant, despite experimental evidence for the sensitivity of crystal habit to magmatic conditions. Here, we develop a new program (ShapeCalc) to calculate 3D shapes from 2D crystal intersection data and apply it to study variations of crystal shape with size for plagioclase microlites (l < 100 µm) in intermediate volcanic rocks. The smallest crystals tend to exhibit prismatic 3D shapes, whereas larger crystals (l > 5–10 µm) show progressively more tabular habits. Crystal growth modelling and experimental constraints indicate that this trend reflects shape evolution during plagioclase growth, with initial growth as prismatic rods and subsequent preferential overgrowth of the intermediate dimension to form tabular shapes. Because overgrowth of very small crystals can strongly affect the external morphology, plagioclase microlite shapes are dependent on the available growth volume per crystal, which decreases during decompression-driven crystallisation as crystal number density increases. Our proposed growth model suggests that the range of crystal shapes developed in a magma is controlled by the temporal evolution of undercooling and total crystal numbers, i.e., distinct cooling/decompression paths. For example, in cases of slow to moderate magma ascent rates and quasi-continuous nucleation, early-formed crystals grow larger and develop tabular shapes, whereas late-stage nucleation produces smaller, prismatic crystals. In contrast, rapid magma ascent may suppress nucleation entirely or, if stalled at shallow depth, may produce a single nucleation burst associated with tabular crystal shapes. Such variation in crystal shapes have diagnostic value and are also an important factor to consider when constructing CSDs and models involving magma rheology.
Action goals and the praxis network: an fMRI study
Authors: Michalowski Bartosz , Buchwald Mikolaj , Klichowski Michal , Ras Maciej , Kroliczak Gregory 
Published: June 2022

AbstractThe praxis representation network (PRN) of the left cerebral hemisphere is typically linked to the control of functional interactions with familiar tools. Surprisingly, little is known about the PRN engagement in planning and execution of tool-directed actions motivated by non-functional but purposeful action goals. Here we used functional neuroimaging to perform both univariate and multi-voxel pattern analyses (MVPA) in 20 right-handed participants who planned and later executed, with their dominant and non-dominant hands, disparate grasps of tools for different goals, including: (1) planning simple vs. demanding functional grasps of conveniently vs. inconveniently oriented tools with an intention to immediately use them, (2) planning simple—but non-functional—grasps of inconveniently oriented tools with a goal to pass them to a different person, (3) planning reaching movements directed at such tools with an intention to move/push them with the back of the hand, and (4) pantomimed execution of the earlier planned tasks. While PRN contributed to the studied interactions with tools, the engagement of its critical nodes, and/or complementary right hemisphere processing, was differently modulated by task type. E.g., planning non-functional/structural grasp-to-pass movements of inconveniently oriented tools, regardless of the hand, invoked the left parietal and prefrontal nodes significantly more than simple, non-demanding functional grasps. MVPA corroborated decoding capabilities of critical PRN areas and some of their right hemisphere counterparts. Our findings shed new lights on how performance of disparate action goals influences the extraction of object affordances, and how or to what extent it modulates the neural activity within the parieto-frontal brain networks.
Homeopathy effects in patients during oncological treatment: a systematic review
Authors: Wagenknecht Anna , Dörfler Jennifer , Freuding Maren , Josfeld Lena , Huebner Jutta 
Published: June 2022

Abstract
Purpose
In this systematic review we included clinical studies from 1800 until 2020 to evaluate evidence of the effectiveness of homeopathy on physical and mental conditions in patients during oncological treatment.

Method
In February 2021 a systematic search was conducted searching five electronic databases (Embase, Cochrane, PsychInfo, CINAHL and Medline) to find studies concerning use, effectiveness and potential harm of homeopathy in cancer patients.

Results
From all 1352 search results, 18 studies with 2016 patients were included in this SR. The patients treated with homeopathy were mainly diagnosed with breast cancer. The therapy concepts include single and combination homeopathic remedies (used systemically or as mouth rinses) of various dilutions. Outcomes assessed were the influence on toxicity of cancer treatment (mostly hot flashes and menopausal symptoms), time to drain removal in breast cancer patients after mastectomy, survival, quality of life, global health and subjective well-being, anxiety and depression as well as safety and tolerance. The included studies reported heterogeneous results: some studies described significant differences in quality of life or toxicity of cancer treatment favouring homeopathy, whereas others did not find an effect or reported significant differences to the disadvantage of homeopathy or side effects caused by homeopathy. The majority of the studies have a low methodological quality.

Conclusions
For homeopathy, there is neither a scientifically based hypothesis of its mode of action nor conclusive evidence from clinical studies in cancer care.
Trusting deep learning natural-language models via local and global explanations
Authors: Ventura Francesco , Greco Salvatore , Apiletti Daniele , Cerquitelli Tania 
Published: June 2022

AbstractDespite the high accuracy offered by state-of-the-art deep natural-language models (e.g., LSTM, BERT), their application in real-life settings is still widely limited, as they behave like a black-box to the end-user. Hence, explainability is rapidly becoming a fundamental requirement of future-generation data-driven systems based on deep-learning approaches. Several attempts to fulfill the existing gap between accuracy and interpretability have been made. However, robust and specialized eXplainable Artificial Intelligence solutions, tailored to deep natural-language models, are still missing. We propose a new framework, named T-EBAnO, which provides innovative prediction-local and class-based model-global explanation strategies tailored to deep learning natural-language models. Given a deep NLP model and the textual input data, T-EBAnO provides an objective, human-readable, domain-specific assessment of the reasons behind the automatic decision-making process. Specifically, the framework extracts sets of interpretable features mining the inner knowledge of the model. Then, it quantifies the influence of each feature during the prediction process by exploiting the normalized Perturbation Influence Relation index at the local level and the novel Global Absolute Influence and Global Relative Influence indexes at the global level. The effectiveness and the quality of the local and global explanations obtained with T-EBAnO are proved on an extensive set of experiments addressing different tasks, such as a sentiment-analysis task performed by a fine-tuned BERT model and a toxic-comment classification task performed by an LSTM model. The quality of the explanations proposed by T-EBAnO, and, specifically, the correlation between the influence index and human judgment, has been evaluated by humans in a survey with more than 4000 judgments. To prove the generality of T-EBAnO and its model/task-independent methodology, experiments with other models (ALBERT, ULMFit) on popular public datasets (Ag News and Cola) are also discussed in detail.
Developing a digital transformation process in the manufacturing sector: Egyptian case study
Authors: Abdallah Yasser Omar , Shehab Essam , Al-Ashaab Ahmed 
Published: June 2022

AbstractDigital transformation is of crucial importance in the manufacturing industry, especially after the COVID-19 pandemic because of the increasing need for remote working and socially distanced workplaces. However, there is a lack of a clear and well-defined process to implement digital transformation in manufacturing. This paper aims to identify the most critical stages to implementing digital transformation in the manufacturing sector. Twenty-one structured interviews with experienced specialists in digitalisation in the manufacturing sector in the Egyptian economy were held and used the Best–Worst Method to analyse the data as an analysis tool for a multiple criteria decision making (MCDM) approach. The digital transformation process comprises eight stages covering technology, management, communications, and customer elements. The main contribution of this work stage is the balance between the different elements of digital transformation—digital technologies, leadership and strategy, people and business processes—to create an integrated 8-step process of digital transformation in the manufacturing sector of developing economies such as the Egyptian economy.
Testing the informal care model: intrapersonal change in care provision intensity during the first lockdown of the COVID-19 pandemic
Authors: Raiber Klara , Verbakel Ellen , de Boer Alice 
Published: June 2022

AbstractInformal care, meaning taking health-related care of people in their own social network, is a topic that gets more and more attention in social science research because the pressure on people to provide informal care is rising due to ageing societies and policy changes. The Informal Care Model developed by Broese van Groenou and de Boer (Eur J Ageing 13(3):271–279, 2016) provides a theoretical foundation to understand under what conditions a person provides informal care. We test this theoretical model by applying it to intrapersonal changes in informal care provision during the first COVID-19 lockdown in the Netherlands in Spring 2020. Data from the LISS panel from two time points, March 2020 and data from July over the period of April/May 2020, were analysed with multinominal multilevel regression analysis (N = 1270 care situations of 1014 caregivers). Our results showed that the individual determinants (Do I have to?, Do I want to?, and especially Can I?) discussed in the Informal Care Model (apart from a series of control variables) are contributing substantially to the understanding of intrapersonal changes in care provision during the first lockdown and by that, we found empirical support for the theoretical model. We conclude that on top of its original purpose to explain between-individual differences in informal caregiving using static indicators, the Informal Care Model is also useful to explain intrapersonal changes in informal caregiving using dynamic indicators.
Four new members of the family Cytophagaceae: Chryseosolibacter histidini gen. nov., sp. nov., Chryseosolibacter indicus gen. nov., sp. nov., Dawidia cretensis, gen. nov., sp. nov., and Dawidia soli, gen. nov., sp. nov. isolated from diverse habitat
Authors: Octaviana Senlie , Lorenczyk Stefan , Ackert Frederike , Fenske Linda , Wink Joachim 
Published: June 2022

AbstractFour novel strains were isolated: PWU4T and PWU20T were both from soil in Germany, PWU5T was isolated from soil in India and PWU37T was obtained from sheep faeces collected on the Island of Crete. Cells of each were observed to be Gram-negative, strictly aerobic, rod shaped, and to grow optimally between 28 and 34 °C, between pH 7.0 and 8.0 and without the addition of NaCl. The strains were found to be catalase and oxidase-negative and able to grow on most mono- and disaccharides, a few polysaccharides and organic acids. Their predominant menaquinone was identified as MK-7. Their major fatty acids were identified as C16:1ω7c (PWU4T and PWU20T) and C16:1ω5c (PWU5T and PWU37T). The DNA G + C contents of strains PWU4T, PWU20T, PWU5T and PWU37T were determined to be 50.2 mol%, 51.6 mol %, 39.8 mol% and 53.8 mol%, respectively. The 16S rRNA gene sequence analysis revealed that the close relatives Ohtaekwangia koreensis 3B-2T and Ohtaekwangia kribbensis 10AOT share less than 93.8% sequence similarity. The strains were classified in two groups, where PWU4T and PWU20T share 93.0% sequence similarity, and PWU5T and PWU37T share 97.5% sequence similarity. However, the members of each group were concluded to represent different species based on the low average nucleotide identity (ANI) of their genomes, 69.7% and 83.8%, respectively. We propose that the four strains represent four novel species of two new genera in the family Cytophagaceae. The type species of the novel genus Chryseosolibacter is Chryseosolibacter histidini gen. nov., sp. nov. with the type strain PWU4T (= DSM 111594T = NCCB 100798T), whilst strain PWU20T (= DSM 111597T = NCCB 100800T) is the type strain of a second species, Chryseosolibacter indicus sp. nov. The type species of the novel genus Dawidia is Dawidia cretensis gen. nov., sp. nov. with the type strain PWU5T (= DSM 111596T = NCCB 100799T), whilst strain PWU37T (= DSM 111595T = NCCB 100801T) is the type stain of a second species, Dawidia soli sp. nov.
Online routing and searching on graphs with blocked edges
Authors: Shiri Davood , Tozan Hakan 
Published: June 2022

AbstractWe study routing and searching decisions of a search-and-detection (SDT) team on a road network under online uncertainty setting. Given an undirected edge-weighted bounded graph, a static target is positioned at an unknown vertex among potential target vertices in the graph. A non-negative search cost is given on each of the potential target vertices. The target is detected once the SDT searches its corresponding vertex. There may be some non-recoverable online blockages in the graph, but the existence of blockages is unknown to the SDT initially. If a blockage exists in the graph, it is disclosed online once the SDT visits one of its end-vertices. The graph stays connected when the blockages are omitted from it. The SDT begins from a certain vertex and aims to identify a route without any blocked edges which detects the target with minimum total traveling and search cost. We analyze this problem from a competitive analysis perspective under two scenarios with and without blockages. For the scenario with blockages, we provide a tight lower bound on the competitive ratio of deterministic solutions, an optimal deterministic solution, a randomized solution with a bounded expected competitive ratio, together with lower and upper bounds on the expected competitive ratio of the optimal randomized solutions. For the scenario without blockages, we provide tight lower bounds as well as optimal deterministic and randomized solutions.
XPS and material properties of raw and oxidized carbide-derived carbon and their application in antifreeze thermal fluids/nanofluids
Authors: Almanassra Ismail W. , Zakaria Yahya , Kochkodan Viktor , Mroue Kamal , Zekri Atef , Atieh Muataz Ali , Al-Ansari Tareq 
Published: June 2022

AbstractIn this study, the stability, thermal conductivity and viscosity of carbide-derived carbon antifreeze thermal fluids were explored. The study also compares the results between antifreeze suspensions prepared using oxidized CDC and emulsified CDC using gum arabic. At first, the raw CDC was oxidized with oxygen by acid treatment and the Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy results revealed an increase in the oxygen content and oxygen functional groups in oxidized CDC. The two-step method was utilized for CDC thermal fluids preparation. Sedimentation visualization and zeta potential testing were employed to investigate stability of nanofluids with time. The stability results revealed that the oxidized CDC has better stability and higher zeta potential values than the emulsified CDCs; however, both mixtures demonstrated stable suspensions for three months. Viscosity measurements showed that the gum arabic CDC suspensions have a higher viscosity than the oxidized CDC; the viscosity was growing with CDC and gum arabic loadings and decreased with temperature. The thermal conductivity analysis was carried out using a lambda analyzer in a temperature range of 288–338 K with a CDC mass loading range of 0.05–0.3 mass%. The experimental outcomes demonstrated that oxidized CDC suspension has better thermal conductivity than gum arabic emulsified CDC. The highest improvement in thermal conductivity was 25.6% using 0.3 mass% of oxidized CDC at 338 K. Moreover, raising the gum arabic mass loading was found to reduce the thermal conductivity enhancement. Therefore, according to the results, the oxidized CDC antifreeze suspensions can perform better than the emulsified CDC.
Graphical abstract
Feature ranking for semi-supervised learning
Authors: Petković Matej , Džeroski Sašo , Kocev Dragi 
Published: June 2022

AbstractThe data used for analysis are becoming increasingly complex along several directions: high dimensionality, number of examples and availability of labels for the examples. This poses a variety of challenges for the existing machine learning methods, related to analyzing datasets with a large number of examples that are described in a high-dimensional space, where not all examples have labels provided. For example, when investigating the toxicity of chemical compounds, there are many compounds available that can be described with information-rich high-dimensional representations, but not all of the compounds have information on their toxicity. To address these challenges, we propose methods for semi-supervised learning (SSL) of feature rankings. The feature rankings are learned in the context of classification and regression, as well as in the context of structured output prediction (multi-label classification, MLC, hierarchical multi-label classification, HMLC and multi-target regression, MTR) tasks. This is the first work that treats the task of feature ranking uniformly across various tasks of semi-supervised structured output prediction. To the best of our knowledge, it is also the first work on SSL of feature rankings for the tasks of HMLC and MTR. More specifically, we propose two approaches—based on predictive clustering tree ensembles and the Relief family of algorithms—and evaluate their performance across 38 benchmark datasets. The extensive evaluation reveals that rankings based on Random Forest ensembles perform the best for classification tasks (incl. MLC and HMLC tasks) and are the fastest for all tasks, while ensembles based on extremely randomized trees work best for the regression tasks. Semi-supervised feature rankings outperform their supervised counterparts across the majority of datasets for all of the different tasks, showing the benefit of using unlabeled in addition to labeled data.
Possible association of rotavirus IgG with cytokine expression levels and dyslipidemia in rotavirus-infected type 1 diabetic children
Authors: Khalil Rehab G. , Abdel-Moneim Adel , Arafa Amany A. , Allam Gamal , El-Senousy Waled M. , Mabrouk Doaa 
Published: June 2022

Abstract
Background
Rotavirus (RV) has been postulated as a viral trigger for the onset of autoimmune disorders, such as type 1 diabetes (T1D). This study aimed to examine the conceivable association of RV IgG with cytokine levels and dyslipidemia in the pathogenesis of pediatric T1D.

Methods
This study included 30 healthy controls and 80 children with T1D who were divided into two groups based on the time since their T1D diagnosis: newly diagnosed (ND ≤ 1 year; n = 30) and previously diagnosed (PD > 1 year; n = 50). ND and PD patients were also separated into negative and positive according to IgG detection (RV IgG−, ND−, and PD−; RV IgG+, ND+, and PD+).

Results
Positive polymerase chain reaction for RVs was evidenced in 7.5% of children with T1D. Anti-RV IgG was 30% and 36% in ND and PD, respectively, compared to healthy controls (2 of 30, 6.6%; P < 0.05). Fasting blood sugar and hemoglobin A1c significantly increased in PD+ compared to PD−. Interferon-γ and interleukin (IL)-15 levels significantly increased. IL-12 and IL-22 mRNA expression was upregulated in ND+ patients compared to that in ND− patients. IL-37 mRNA expression was significantly downregulated in ND− and ND+ patients compared to that in healthy controls. Total cholesterol and high- and low-density lipoprotein-cholesterol levels were significantly lower in PD+ than in PD−; whereas triglyceride levels were higher than those in healthy controls.

Conclusions
This study suggested that anti-RV IgG may have a role in the pathogenesis, development, and progression of T1D, and RV infections are implicated in dyslipidemia and inflammation status.