bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis
Authors: Ravano Veronica , Andelova Michaela , Piredda Gian Franco , Sommer Stefan , Caneschi Samuele , Roccaro Lucia , Krasensky Jan , Kudrna Matej , Uher Tomas , Corredor-Jerez Ricardo A. , Disselhorst Jonathan A. , Maréchal Bénédicte , Hilbert Tom , Thiran Jean-Philippe , Richiardi Jonas , Horakova Dana , Vaneckova Manuela , Kober Tobias 
Published: July 2024

Abstract
Background and objectives
In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes.

Methods
We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue.

Results and conclusions
Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.
Epiploic steal: is this concept the key to reducing colorectal anastomotic leak rates?
Authors: Sarofim Mina 
Published: July 2024

Abstract
Purpose
Ensuring optimal colonic perfusion is a critical step in every colorectal anastomosis. The aim of this study is to describe the concept of epiploic steal.

Methods
A literature review was performed to identify studies evaluating anastomotic blood supply. The fundamental principle of epiploic steal is outlined.

Results
Epiploic steal has not been previously evaluated in the literature, and likely has a negative effect on colonic blood supply. Resection of colonic epiploicae may improve perfusion at the distal most lengths of a mobilised colonic conduit where the anastomosis requires it.

Conclusion
This novel concept has the potential to change practice and reduce colorectal anastomotic leak rates. Further clinical studies are required.
Data-driven exploratory method investigation on the effect of dyslexia education at brain connectivity in Turkish children: a preliminary study
Authors: Gengeç Benli Şerife , İçer Semra , Demirci Esra , Karaman Zehra Filiz , Ak Zeynep , Acer İrem , Sağır Gizem Rüveyda , Aker Ebru , Sertkaya Büşra 
Published: July 2024

AbstractDyslexia is a specific learning disability that is neurobiological in origin and is characterized by reading and/or spelling problems affecting the development of language-related skills. The aim of this study is to reveal functional markers based on dyslexia by examining the functions of brain regions in resting state and reading tasks and to analyze the effects of special education given during the treatment process of dyslexia. A total of 43 children, aged between 7 and 12, whose native language was Turkish, participated in the study in three groups including those diagnosed with dyslexia for the first time, those receiving special education for dyslexia, and healthy children. Independent component analysis method was employed to analyze functional connectivity variations among three groups both at rest and during the continuous reading task. A whole-brain scanning during task fulfillment and resting states revealed that there were significant differences in the regions including lateral visual, default mode, left frontoparietal, ventral attention, orbitofrontal and lateral motor network. Our results revealed the necessity of adding motor coordination exercises to the training of dyslexic participants and showed that training led to functional connectivity in some brain regions similar to the healthy group. Additionally, our findings confirmed that impulsivity is associated with motor coordination and visuality, and that the dyslexic group has weaknesses in brain connectivity related to these conditions. According to our preliminary results, the differences obtained between children with dyslexia, group of dyslexia with special education and healthy children has revealed the effect of education on brain functions as well as enabling a comprehensive examination of dyslexia.
Targeting CD73 limits tumor progression and enhances anti-tumor activity of anti-PD-1 therapy in intrahepatic cholangiocarcinoma
Authors: Sun Bao-Ye , Zhang Dai , Gan Wei , Wu Jing-Fang , Wang Zhu-Tao , Sun Guo-Qiang , Zhou Jian , Fan Jia , Yi Yong , Hu Bo , Zhang Bo-Heng , Qiu Shuang-Jian 
Published: July 2024

Abstract
Background & aims
Patients with intrahepatic cholangiocarcinoma (iCCA) respond poorly to immune checkpoint blockades (ICBs). In this study, we aimed to dissect the potential mechanisms underlying poor response to ICBs and explore a rational ICB-based combination therapy in iCCA.

Methods
scRNA-seq dataset GSE151530 was analyzed to investigate the differentially expressed genes in malignant cells following ICBs therapy. RNA-seq analysis and western blot assays were performed to examine the upstream and downstream signaling pathways of CD73. Subcutaneous tumor xenograft models were utilized to investigate the impact of CD73 on iCCA growth. Plasmid AKT/NICD-induced spontaneous murine iCCAs were used to explore the therapeutic efficacy of CD73 enzymatic inhibitor AB680 combined with PD-1 blockade. Time-of-flight mass cytometry (CyTOF) was conducted to identify the tumor-infiltrating immune cell populations and their functional changes in murine iCCAs treated with AB680 in combination with PD-1 antibody.

Results
scRNA-seq analysis identified elevated CD73 expression in malignant cells in response to ICBs therapy. Mechanistically, ICBs therapy upregulated CD73 expression in malignant cells via TNF-α/NF-κB signaling pathway. In vivo studies revealed that CD73 inhibition suppressed the growth of subcutaneous tumors, and achieved synergistic depression effects with gemcitabine and cisplatin (GC). Adenosine produced by CD73 activates AKT/GSK3β/β-catenin signaling axis in iCCA cells. CD73 inhibitor AB680 potentiates anti-tumor efficacy of PD-1 antibody in murine iCCAs. CyTOF analysis showed that AB680 combined with anti-PD-1 therapy promoted the infiltration of CD8+ T, CD4+ T cells, and NK cells in murine iCCAs, while simultaneously decreased the proportions of macrophages and neutrophils. Moreover, AB680 combined with anti-PD-1 significantly upregulated the expression of Granzyme B, Tbet and co-stimulatory molecule ICOS in infiltrating CD8+ T cells.

Conclusions
CD73 inhibitor AB680 limits tumor progression and potentiates therapeutic efficacy of GC chemotherapy or anti-PD-1 treatment in iCCA. AB680 combined with anti-PD-1 therapy effectively elicits anti-tumor immune response.
Promoting diagnostic reasoning in teacher education: the role of case format and perceived authenticity
Authors: Bichler Sarah , Sailer Michael , Bauer Elisabeth , Kiesewetter Jan , Härtl Hanna , Fischer Martin R. , Fischer Frank 
Published: July 2024

AbstractTeachers routinely observe and interpret student behavior to make judgements about whether and how to support their students’ learning. Simulated cases can help pre-service teachers to gain this skill of diagnostic reasoning. With 118 pre-service teachers, we tested whether participants rate simulated cases presented in a serial-cue case format as more authentic and become more involved with the materials compared to cases presented in a whole case format. We further investigated whether participants with varying prior conceptual knowledge (what are symptoms of ADHD and dyslexia) gain more strategic knowledge (how to detect ADHD and dyslexia) with a serial-cue versus whole case format. We found that the case format did not impact authenticity ratings but that learners reported higher involvement in the serial-cue case format condition. Bayes factors provide moderate evidence for the absence of a case format effect on strategic knowledge and strong evidence for the absence of an interaction of case format and prior knowledge. We recommend using serial-cue case formats in simulations as they are a more authentic representation of the diagnostic reasoning process and cognitively involve learners. We call for replications to gather more evidence for the impact of case format on knowledge acquisition. We suggest a further inquiry into the relationship of case format, involvement, and authenticity but think that a productive way forward for designing authentic simulations is attention to aspects that make serial-cue cases effective for diverse learners. For example, adaptive feedback or targeted practice of specific parts of diagnostic reasoning such as weighing evidence.
An Extended Neck Position is Likely to Produce Cervical Spine Injuries Through Buckling in Accidental Head-First Impacts During Rugby Tackling
Authors: Silvestros Pavlos , Quarrington Ryan D. , Preatoni Ezio , Gill Harinderjit S. , Jones Claire F. , Cazzola Dario 
Published: July 2024

AbstractCatastrophic cervical spine injuries in rugby often occur during tackling. The underlying mechanisms leading to these injuries remain unclear, with neck hyperflexion and buckling both proposed as the causative factor in the injury prevention literature. The aim of this study was to evaluate the effect of pre-impact head–neck posture on intervertebral neck loads and motions during a head-first rugby tackle. Using a validated, subject-specific musculoskeletal model of a rugby player, and computer simulations driven by in vivo and in vitro data, we examined the dynamic response of the cervical spine under such impact conditions. The simulations demonstrated that the initial head–neck sagittal-plane posture affected intervertebral loads and kinematics, with an extended neck resulting in buckling and supraphysiologic intervertebral shear and flexion loads and motions, typical of bilateral facet dislocation injuries. In contrast, an initially flexed neck increased axial compression forces and flexion angles without exceeding intervertebral physiological limits. These findings provide objective evidence that can inform injury prevention strategies or rugby law changes to improve the safety of the game of rugby.
Predicting the Average Charring Rate of Mass Timber Using Data-Driven Methods for Structural Calculations
Authors: Amin Rikesh , Mo Yaxin , Richter Franz , Kurzer Christoph , Werther Norman , Rein Guillermo 
Published: July 2024

AbstractEngineered timber is increasingly in demand for tall buildings due to its positive impact on building sustainability. However, quick adoption raises fire engineering questions regarding flammability and structural performance. Understanding the behaviour of timber in fire is crucial, particularly for structural calculations of tall buildings. The charring rate of timber plays a significant role in its structural performance because the loss of cross section reduces the load bearing capacity of the element. Eurocode-5 (EC5) provides a simple method to calculate the charring rate and it is widely adopted for design in many countries while more complex physics-based models exist but are rarely used for design. For example, we want to know when EC5 underpredicts or overpredicts and by how much. This paper compares different data-driven methods, including statistical and artificial intelligence algorithms, for predicting the average charring rate of timber in fire. A new database of charring rates, VAQT, was created comprised of 231 furnace tests of timber products found in the scientific and technical literature. Statistical methods such as ridge regression (λ = 0.001) predict the charring rate with a minimum 11% error whilst EC5 predicts with 27% error. A trained neural network predicts the charring rate with minimum 9% error. This paper presents a novel database of timber charring experiments and provides a set of data-driven predictive models, all of which calculate the average charring rate with a significantly higher accuracy than EC5 for a wide range of mass timber products.
Educator Knowledge of Childhood Conduct Problems and Callous-Unemotional Traits
Authors: Fleming Georgette E. , Boulton Antonia L. , Prasad Ashneeta H. , Kershaw Kelly A. , Kimonis Eva R. 
Published: July 2024

AbstractResearch evaluating mental health literacy (MHL) of adults who support children with mental health difficulties is relatively scarce. To date, no studies have investigated educator knowledge of conduct problems and callous-unemotional (CU) traits. This is a significant gap in the literature since conduct problems are among the most prevalent childhood mental disorders, while CU traits are associated with poor academic, behavioral, and social outcomes in school settings. In the current study, we assessed educators’ knowledge of the characteristics and management of conduct problems and CU traits. Participants were N = 390 preschool and primary/elementary school educators (Mage = 38.62 years, SD = 11.66; 91% woman-identifying; 71% White) who completed a Knowledge Test and survey assessing educator characteristics and various student-educator outcomes. Averaged across items, educators scored 57.1% on the Knowledge Test. We identified gaps in educator knowledge with respect to identifying characteristics associated with distinct domains of externalizing difficulties and evidence-based management strategies. Educators’ years of experience and accreditation status were not associated with knowledge. Paraeducators had significantly lower knowledge scores than teachers and leadership. Unexpectedly, greater knowledge was not associated with better student-teacher relationship quality or more positive perceptions of students with conduct problems. Findings support the need for universal MHL programs focused on conduct problems and CU traits, especially among paraeducators, while also suggesting that more intensive interventions may be required to improve educator-student relationship quality.
Multi-channel anomaly detection using graphical models
Authors: Namoano Bernadin , Latsou Christina , Erkoyuncu John Ahmet 
Published: July 2024

AbstractAnomaly detection in multivariate time-series data is critical for monitoring asset conditions, enabling prompt fault detection and diagnosis to mitigate damage, reduce downtime and enhance safety. Existing literature predominately emphasises temporal dependencies in single-channel data, often overlooking interrelations between features in multivariate time-series data and across multiple channels. This paper introduces G-BOCPD, a novel graphical model-based annotation method designed to automatically detect anomalies in multi-channel multivariate time-series data. To address internal and external dependencies, G-BOCPD proposes a hybridisation of the graphical lasso and expectation maximisation algorithms. This approach detects anomalies in multi-channel multivariate time-series by identifying segments with diverse behaviours and patterns, which are then annotated to highlight variations. The method alternates between estimating the concentration matrix, which represents dependencies between variables, using the graphical lasso algorithm, and annotating segments through a minimal path clustering method for a comprehensive understanding of variations. To demonstrate its effectiveness, G-BOCPD is applied to multichannel time-series obtained from: (i) Diesel Multiple Unit train engines exhibiting faulty behaviours; and (ii) a group of train doors at various degradation stages. Empirical evidence highlights G-BOCPD's superior performance compared to previous approaches in terms of precision, recall and F1-score.
Religious Belief Among Women in Australia: Characteristics and Role in Influencing Children’s Health-Related Quality of Life and Lifestyle
Authors: Bahrampour Abbas , Scuffham Paul , Cross Megan , Ng Shu-Kay 
Published: July 2024

Abstract
Religiosity can be an important factor in women’s health-related behaviour, attitudes, and decision-making. Evidence however, regarding the religiosity of mothers and its influence on child health, is scarce. Based on a large population-based cohort in Australia, we aim to examine the religiosity of women in Australia and the association of maternal religiosity with children’s health-related quality of life (HRQOL) and lifestyle. Our findings indicate that (1) maternal religious involvement was higher for women with higher education levels, ascertained religious values in decision-making, and abstinence from binge drinking in the household, (2) maternal religiosity positively influenced their children’s HRQOL, (3) children of mothers who were more religious had less worries or fewer school-work problems, but the children of mothers with stronger religious beliefs used more internet/computer during the week but had less time playing games on weekends. This study provides additional specificity to inform future health interventions in religious community contexts to enhance the positive influence of maternal religious belief for better development of their children.
Counting meromorphic differentials on $${\mathbb {C}\mathbb {P}}^1$$
Authors: Buryak Alexandr , Rossi Paolo 
Published: July 2024

AbstractWe give explicit formulas for the number of meromorphic differentials on $$\mathbb{C}\mathbb{P}^1$$

C

P

1

with two zeros and any number of residueless poles and for the number of meromorphic differentials on $$\mathbb{C}\mathbb{P}^1$$

C

P

1

with one zero, two poles with unconstrained residue and any number of residueless poles, in terms of the orders of their zeros and poles. These are the only two finite families of differentials on $$\mathbb{C}\mathbb{P}^1$$

C

P

1

with vanishing residue conditions at a subset of poles, up to the action of $$\textrm{PGL}(2,\mathbb {C})$$

PGL
(
2
,
C
)

. The first family of numbers is related to triple Hurwitz numbers by simple integration and we show its connection with the representation theory of $$\textrm{SL}_2(\mathbb {C})$$

SL
2

(
C
)

and the equations of the dispersionless KP hierarchy. The second family has a very simple generating series, and we recover it through surprisingly involved computations using intersection theory of moduli spaces of curves and differentials.
Enhancing flood wave modelling of reservoir failure: a comparative study of structure-from-motion based 2D and 3D methodologies
Authors: Lee Jong-hyuk , Lee Sang-ik , Jeong Youngjoon , Seo Byung-hun , Kim Dong-su , Seo Ye-jin , Her Younggu , Choi Won 
Published: July 2024

AbstractPredicting flood wave propagation from reservoir failures is critical to practical flood hazard assessment and risk management. Flood waves are sensitive to topography, channel geometry, structures, and natural features along floodplain paths. Thus, the accuracy of flood wave modelling depends on how precisely those features are represented. This study introduces an enhancing approach to flood wave modelling by accurately representing three-dimensional objects in floodplains using the structure-from-motion (SfM). This method uses an unmanned aerial vehicle to capture topographic complexities and account for ground objects that impact flood propagation. Using the three-dimensional volume of fluid numerical approach significantly improves an enhanced representation of turbulent flow dynamics and computational efficiency, especially in handling large topography datasets. Reproductions from this enhanced three-dimensional approach were validated against recent reservoir failure observations and contrasted with traditional two-dimensional models. The results revealed that the suggested three-dimensional methodology achieved a significant 84.4% reproducibility when juxtaposed with actual inundation traces. It was 35.5%p more accurate than the two-dimensional diffusion wave equation (DWE) and 17.1%p more than the shallow water equation (SWE) methods in predicting flood waves. This suggests that the reproducibility of the DWE and SWE decreases compared to the three-dimensional approach when considering more complex floodplains. These results demonstrate that three-dimensional flood wave analysis with the SfM methodology is optimal for effectively minimising topographic and flood wave reproduction errors across extensive areas. This dual reduction in errors significantly enhances the reliability of flood hazard assessments and improves risk management by providing more precise and realistic predictions of flood waves.
Co-seismic and rainfall-triggered landslide hazard susceptibility assessment for Uganda derived using fuzzy logic and geospatial modelling techniques
Authors: Oleng Morris , Ozdemir Zuhal , Pilakoutas Kypros 
Published: July 2024

AbstractUganda has suffered from many damaging landslides like the 1966 Rwenzori, 1994 Kisomoro and 2010 Bududa events. Despite escalating landslide risks exacerbated by rapid deforestation, urbanization and population growth coupled with a substandard building stock, comprehensive national co-seismic and rainfall-induced landslide hazard and risk maps for Uganda do not exist. This study therefore aims to conduct landslide hazard assessment and zonation for Uganda using a geospatial-based fuzzy logic methodology. In this methodology, landslide frequency ratios obtained for the 1966 Toro and 1994 Kisomoro earthquakes are assigned to the stochastic event-based probabilistic seismic hazard map derived using OpenQuake-engine. The available co-seismic and rainfall-induced landslide inventory datasets are used to derive the distribution of landslide frequency ratios based on geology, topographic slope position index, slope aspect, slope angle, distance from streams, and proximity to major active faults. The spatial distribution of fuzzy membership functions obtained from frequency ratios are overlaid and aggregated to produce landslide susceptibility maps showing relative probabilities of landslide occurrences across Uganda. Results indicate that the highest overall landslide hazard susceptibility is expected in areas comprising highly weathered outcropping rocks of precambrian granites, dominantly metasedimentary, and granulites and gneisses geologies within 40 km from major active faults; where the bedrock peak ground acceleration ≥ 0.1 g, topographic position index ≥ 3.8, slope gradient ≥ 10°, and the distance from streams ≤ 1.25 km. These findings can inform Uganda’s directorate of disaster preparedness and management towards pioneering the development of co-seismic landslide risk mitigation measures for the country.