bluuebunny/crossref_metadata_2025_split huggingface dataset:
Explaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis
Authors: Lageman Senne B. , Jolly Amy , Sahi Nitin , Prados Ferran , Kanber Baris , Eshaghi Arman , Tur Carmen , Eierud Cyrus , Calhoun Vince D. , Schoonheim Menno M. , Chard Declan T. 
Published: January 2025

Abstract
Cognitive impairment (CI) in multiple sclerosis (MS) is only partially explained by whole-brain volume measures, but independent component analysis (ICA) can extract regional patterns of damage in grey matter (GM) or white matter (WM) that have proven more closely associated with CI. Pathology in GM and WM occurs in parallel, and so patterns can span both. This study assessed whether joint-ICA of GM and WM features better explained cognitive function compared to single-tissue ICA. 89 people with MS underwent cognitive testing and magnetic resonance imaging. Structural T1 and diffusion-weighted images were used to measure GM volumes and WM connectomes (based on fractional anisotropy weighted by the number of streamlines). ICA was performed for each tissue type separately and as joint-ICA. For each tissue type and joint-ICA, 20 components were extracted. In stepwise linear regression models, joint-ICA components were significantly associated with all cognitive domains. Joint-ICA showed the highest variance explained for executive function (Adjusted R
2 = 0.35) and visual memory (Adjusted R
2 = 0.30), while WM-ICA explained the highest variance for working memory (Adjusted R
2 = 0.23). No significant differences were found between joint-ICA and single-tissue ICA in information processing speed or verbal memory. This is the first MS study to explore GM and WM features in a joint-ICA approach and shows that joint-ICA outperforms single-tissue analysis in some, but not all cognitive domains. This highlights that cognitive domains are differentially affected by tissue-specific features in MS and that processes spanning GM and WM should be considered when explaining cognition.
The value of magnetic resonance imaging of the optic nerve for the diagnosis of multiple sclerosis in patients with optic neuritis
Authors: Pihl-Jensen Gorm , Frederiksen Jette Lautrup 
Published: January 2025

Abstract

Background
Although optic neuritis (ON) is common in multiple sclerosis (MS), lesions of the optic nerve are not included as an anatomical substrate for dissemination in space and time (DIS and DIT).

Objective
To assess the increase in sensitivity of including MRI lesions of the optic nerve for the diagnosis of MS in patients with ON.

Methods
We included patients consecutively referred with first time, monosymptomatic ON, with no known cause of the ON, who underwent orbital MRI including fat suppressed T2 and T1-sequences with and without gadolinium contrast.

Results
One hundred and twenty patients were included. Optic nerve T2 lesions and/or T1-contrast enhancement was shown in 104 patients. Sixty-three patients were diagnosed with MS at baseline. Nine patients developed MS during follow-up. The inclusion of optic nerve MRI lesions led to the diagnosis of 8 additional patients and increased sensitivity to 0.99 (95% CI 0.96–1.00) compared to 0.88 (95% CI 0.79–0.95) for 2017 criteria, while decreasing the specificity to 0.81 (95% CI 0.70–0.92) compared to 1.00.

Conclusion
Amending the diagnostic criteria for MS to include MRI lesions of the optic nerve as a substrate for DIS and DIT may increase sensitivity and lead to more rapid diagnosis of MS.
CoGames: Development of an adaptive smartphone-based and gamified monitoring tool for cognitive function in Multiple Sclerosis
Authors: Pless Silvan , Woelfle Tim , Lorscheider Johannes , Wiencierz Andrea , Reyes Óscar , Luque Carlos , Calabrese Pasquale , Granziera Cristina , Kappos Ludwig 
Published: January 2025

Abstract

Aim
As part of the development of a smartphone-based app for monitoring MS disease activity and progression (dreaMS, NCT05009160), we developed six gamified tests with multiple difficulty levels as a monitoring tool for cognition. This study quantified the relative difficulty between levels and investigated their reliability, ability to depict practice effects, and user acceptance.

Methods
Healthy volunteers played each game, covering five cognitive domains, twice per day for 11 consecutive days. Linear mixed models determined the relative difficulty of the levels. Spearman's correlation of the two daily repetitions measured test–retest reliability. Difficulty increased daily except for days 2, 6, and 11, when the easiest level (“Beginner”) was repeated to estimate practice effects. Participants rated enjoyment and other components of acceptance on a 5-point scale.

Results
We included 82 participants from April to July 2023 in Basel, Switzerland, of which 76 (51 female, age: 40.3 ± 13.9 years, range 18–69) completed the study according to protocol. Generally, mean performances decreased with higher difficulty levels. Across all levels of all games, the median test–retest correlation was 0.825 (range of medians 0.55–0.9). Mean performance in level “Beginner” improved across all games. The mean enjoyment rating was 3.9 (range: 3.1–4.3).

Conclusion
Our study showed that the CoGames yield reliable measures across different cognitive domains and difficulty levels and were enjoyable to play. The observed practice effects must be considered, but also indicate sensitivity to change. These results support the hypothesis that adaptive gamified digital tests can serve as a reliable and well-accepted monitoring tool of cognition in PwMS.
Automated analysis of spoken language differentiates multiple system atrophy from Parkinson’s disease
Authors: Šubert Martin , Tykalová Tereza , Novotný Michal , Dušek Petr , Klempíř Jiří , Rusz Jan 
Published: January 2025

Abstract

Background and objectives
Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson’s disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis of natural spontaneous speech to differentiate MSA and PD.

Methods
Spontaneous speech of 39 participants with MSA compared to 39 drug-naive PD and 39 healthy controls matched for age and sex was transcribed and linguistically annotated using automatic speech recognition and natural language processing. A quantitative analysis was performed using 6 lexical and syntactic and 2 acoustic features. Results were compared with human-controlled analysis to assess the robustness of the approach. Diagnostic accuracy was evaluated using sensitivity analysis.

Results
Despite similar disease duration, linguistic abnormalities were generally more severe in MSA than in PD, leading to high diagnostic accuracy with an area under the curve of 0.81. Compared to controls, MSA showed decreased grammatical component usage, more repetitive phrases, shorter sentences, reduced sentence development, slower articulation rate, and increased duration of pauses, whereas PD had only shorter sentences, reduced sentence development, and longer pauses. Only slower articulation rate was distinctive for MSA while unchanged for PD relative to controls. The highest correlation was found between bulbar/pseudobulbar clinical score and sentence length (r
= −0.49, p
= 0.002). Despite the relatively high severity of dysarthria in MSA, a strong agreement between manually and automatically computed results was achieved.

Discussion
Automated linguistic analysis may offer an objective, cost-effective, and widely applicable biomarker to differentiate synucleinopathies with similar clinical manifestations.
Retrospective discrimination of PNES and epileptic seizure types using blood RNA signatures
Authors: Bullinger Katie , Dhakar Monica , Pearson Andrea , Bumanglag Argyle , Guven Emine , Verma Rashi , Amini Elham , Sloviter Robert S. , DeBruyne Jason , Simon Roger P. , Meller Robert 
Published: January 2025

Abstract

Objectives
The ability to differentiate epileptic- and non-epileptic events is challenging due to a lack of reliable molecular seizure biomarker that provide a retrospective diagnosis. Here, we use next generation sequencing methods on whole blood samples to identify changes in RNA expression following seizures.

Methods
Blood samples were obtained from 32 patients undergoing video electroencephalogram (vEEG) monitoring. Blood samples were collected in PaxGene tubes at baseline (admission) and following a seizure event (4–6 h and 24 h later or discharge). EEG and video of clinical events were reviewed by the clinical team and study epileptologist and were classified as epileptic seizure, psychogenic nonepileptic spell (PNES), or other. RNA was extracted from blood and RNA expression was determined using RNA-sequencing.

Results
We show significant differences in RNA profiles between patients that did or did not experience an epileptic seizure. Compared to baseline patients with PNES show large increases in RNA expression 4–6 h and 24 h post seizure. Conversely, genes that changed following epileptic seizure showed more modest changes associated with a decrease in immune system function. Transcript usage was changed between patients with PNES and epileptic seizure at all three time points examined. Lists of genes differentially expressed following PNES or epileptic seizure vs. all baseline samples were used as classifiers for prediction. Models generated using random forest and radial support vector machine algorithms were 100% accurate at predicting both PNES and epileptic seizures.

Significance
These data suggest that blood gene expression changes may have utility to retrospectively identify patients who have suffered a seizure or seizure-like event as a cause of transient loss of consciousness.
Resistance of Pinus pinea to Bursaphelenchus xylophilus explained by the dynamic response of phytohormones, antioxidant activity, and stress-related gene expression
Authors: Nunes da Silva Marta , Santos Carla S. , Solla Alejandro , Gamir Jordi , Flors Victor , Sampedro Luis , Zas Rafael , Vasconcelos Marta W. 
Published: January 2025

Abstract

Key message
The effects of MJ on pine trees are species-specific and trigger a resistant phenotype to the PWN. A more dynamic response of hormones and gene expression in Pinus pinea explains the high resistance to Bursaphelenchus xylophilus of this species.

Abstract
Knowledge on hormonal and genetic mechanisms of pine trees in response to the pinewood nematode (PWN; Bursaphelenchus xylophilus) is limited. To describe tree defence strategies against B. xylophilus, this study used the plant stress hormone methyl jasmonate (MJ) on four pine species with different susceptibility (Pinus pinaster < P. radiata ≈ P. sylvestris < P. pinea). Three-year-old trees were sprayed with MJ at 0, 25, and 50 mM, and 2 months later challenged with the PWN. Multiple samples were taken to assess nematode content, oxidative stress, secondary metabolites, phytohormone levels, and stress-related gene expression. Nematode infestation in trees correlated negatively with the water content of needles and phenolics of stems, and positively with the concentration of indole-3-carboxylic acid in stems. MJ spray reduced in a dose-dependent manner the nematode content in P. pinaster and P. sylvestris. The effects of MJ were species-specific, although a more pronounced impact was observed in the susceptible P. pinaster species, leading to a decrease of chlorophyll and water loss and to the upregulation of the gene involved in the biosynthesis of terpenoids (AFS). After MJ spray, increased levels of JA-Ile were observed in P. pinea only. Hormone profiling, predisposition to activate antioxidant response, and gene expression in P. pinea trees provide evidence of why this species is highly resistant to B. xylophilus. On the contrary, the lack of effective hormonal changes in P. pinaster explained the lack of defence responses to B. xylophilus of this susceptible species. This study is a first approach to explore biochemical, molecular, and hormonal interactions between Pinus species and the PWN, and presents unprecedented insights into alterations induced by exogenous MJ in regulating defence mechanisms in pine trees.
Surgery for primary ventral hernias and risk of postoperative pain, nausea: a population-based register study
Authors: Ali Fathalla , Wallin Göran , Wahlin Rebecka Rubenson , Montgomery Agneta , Rogmark Peder , Sandblom Gabriel 
Published: January 2025

Abstract

Purpose
The aim of this study was to evaluate risk factors for postoperative pain and nausea after open repair for primary ventral hernias.

Method
A population-based registry study was conducted based on data assembled from the Swedish national ventral hernia repair register between January 2016 and December 2021and cross-matched with the Swedish perioperative register.

Results
Altogether 2064 open ventral hernia repairs were registered, including 816 (39.5%) performed on women. Of these, 91 (4.4%) were registered to suffer postoperative nausea or vomiting (PONV) and 403 (19.5%) postoperative pain (PP). In both univariable and multivariable logistic regression analyses, significant predictors of postoperative nausea and pain included male gender, which was associated with lower odds of both postoperative nausea (multivariable OR: 0.30, 95% CI: 0.18–0.49, P < 0.001) and postoperative pain (multivariable OR: 0.60, 95% CI: 0.44–0.83, P = 0.002). Additional predictors of postoperative nausea included emergency surgery (multivariable OR: 4.08, 95% CI: 1.10-15.08, P = 0.035), operative time > 40 min (multivariable OR: 4.15, 95% CI: 2.24–7.69, P < 0.001). Conversely total intravenous anesthesia was associated with lower incidence of PONV (multivariable OR: 0.40, 95% CI: 0.22–0.74, P = 0.003). Other factors, such as age, BMI, smoking status, ASA classification, hernia size, surgery type, operative time, and anesthesia type, were not significantly associated with postoperative pain after adjusting for other variables.

Conclusion
Postoperative nausea and vomiting (PONV) are significantly reduced with total intravenous anesthesia (TIVA) compared to inhalation anesthesia, with no notable difference in postoperative pain between the two methods.
Adaptive caching for operation-based versioning of models
Authors: Pietron Jakob , Raab Heiko , Tichy Matthias 
Published: January 2025

Abstract
In a collaborative multi-user model-driven engineering context, it becomes important to track who changed what model part how and why. Operation-based versioning addresses this need by persisting a meaningful edit history which enables a single user to navigate through a model’s evolution over time, to analyze arbitrary previous model versions, or to trace the impact of an operation. However, to load a distinct prior version, it must be restored by reapplying all previous operations, which is time-consuming and, thus, interrupts a user’s workflow. Caching with a fixed distance between caches helps to overcome this problem to the cost of increasing memory requirements. Further, there is no caching approach supporting branches, merges, and possibly resolved conflicts. We propose two advanced caching strategies for operation-based versioning capable of the previously mentioned features: zonal and adaptive caching. Both strategies reduce the memory in use by not applying the same static distance between two caches across the whole edit history. Instead, the distance increases depending on a version’s age and its distance to a branch’s head. Both strategies aim to reduce the restoration time of arbitrary prior versions below a threshold to not interrupt a user’s flow of thought. Zonal caching employs predefined distances compatible with a broad range of model sizes. In contrast, adaptive caching derives the distances individually depending on the initial time to load the model on a user’s computer and the model’s size.We conducted controlled experiments with models of varying sizes and compared the time to restore model versions and the memory in use for no caching, caching with static distances, zonal, and adaptive strategies on different computers. The developed strategies decrease the time to restore a version remarkably while using less memory than static caching. Our results show that for all considered systems and models individual adaptive caching reduces memory usage even further compared to zone-based caching while still satisfying application responsiveness requirements.
Impromptu: a framework for model-driven prompt engineering
Authors: Morales Sergio , Clarisó Robert , Cabot Jordi 
Published: January 2025

Abstract
Generative artificial intelligence (AI) systems are capable of synthesizing complex artifacts such as text, source code or images according to the instructions provided in a natural language prompt. The quality of the input prompt, in terms of both content and structure, has a large impact on the quality of the output. This has given rise to prompt engineering, the process of designing natural language prompts to best take advantage of the capabilities of generative AI systems. This paper describes , a model-driven engineering framework to support the creation, management and reuse of prompts for generative AI. offers a domain-specific language (DSL) to define multimodal prompts in a modular and tool-independent way. The language offers additional features such as versioning, prompt chaining and multi-language support. Moreover, it provides tool support to adapt prompts for specific generative AI systems, execute those prompts on a generative AI system and validate the quality of the response that is generated. is available as a Langium-based Visual Studio Code plugin.
Antifungal activity of traversianal, a diterpenoid aldehyde from Cercospora sp. ME202, against the rice blast fungus, Pyricularia oryzae
Authors: Ino Masatoshi , Kihara Junichi , Ishihara Atsushi , Ueno Makoto 
Published: January 2025

Abstract
Here, we evaluated the antifungal activity of traversianal, a diterpenoid derived from Cercospora sp. ME202, against Pyricularia oryzae, which causes rice blast. Traversianal had concentration-dependent inhibitory activity against conidial germination and inhibited hyphal growth in a TLC bioassay. Staining conidia for viability with fluorescein diacetate and propidium iodide showed that the fungicidal activity was associated with cell membrane damage over time. Pretreatment of rice leaves with traversianal before inoculation decreased the number of blast lesions. These results suggest that traversianal has potential for controlling rice blast.
A three-dimensional kinematic analysis of bipedal walking in a white-handed gibbon (Hylobates lar) on a horizontal pole and flat surface
Authors: Fujiwara Takafumi , Ito Kohta , Shitara Tetsuya , Nakano Yoshihiko 
Published: January 2025

Abstract
Gibbons, a type of lesser ape, are brachiators but also walk bipedally and without forelimb assistance, not only on the ground but also on tree branches. The arboreal bipedal walking strategy of the gibbons has been studied in previous studies in relation to two-dimensional (2D) kinematic analysis. However, because tree branches and the ground differ greatly in width, leading to a constrained foot contact point on the tree branches, gibbons must adjust their 3D joint motions of trunk and hindlimb on the tree branches. Furthermore, these motor adjustments could help minimize the center of mass (CoM) mediolateral displacement. This study investigated the kinematic adjustment mechanism necessary to enable a gibbon to walk bipedally on an arboreal-like substrate using 3D measurements. Trials were recorded with eight video cameras that were placed around the substrate. The CoM position on the body, the Cardan angles of the hindlimb joints and trunk, and spatiotemporal parameters were calculated. Asymmetry of thorax, pelvis, trunk, and left and right hindlimb joint motion was observed in the pole and flat conditions. In the pole condition, the narrower step width and the smaller range of motion of the mediolateral CoM displacement were observed with increased hip adduction and knee eversion angles. These kinematic adjustments might place the knee and foot directly under the body during the single support phase, producing a reduced step width and the amount of the mediolateral CoM displacement of a gibbon.
Germany’s macroeconomic drivers during the pandemic and inflation surge
Authors: Hohberger Stefan 
Published: January 2025

Abstract
This paper estimates a three-region macroeconomic model to analyse the key drivers of Germany’s GDP, inflation, and wage growth during the COVID-19 pandemic and inflation surge. Incorporating COVID-related demand and supply shocks, trade in commodities, and endogenous ELB periods, the results highlight that (i) the 2020–2021 downturn was primarily driven by domestic and global lockdown shocks, (ii) the 2021–2022 inflation surge resulted from rising commodity prices, recovering global demand, and supply-side pressures, and (iii) wage growth per hour was shaped by opposing demand and supply forces. The model’s estimated shocks closely align with external indicators, supporting its empirical plausibility.
AI in the classroom: Exploring students’ interaction with ChatGPT in programming learning
Authors: Güner Hacer , Er Erkan 
Published: January 2025

Abstract
As being more prevalent in educational settings, understanding the impact of artificial intelligence tools on student behaviors and interactions has become crucial. In this regard, this study investigates the dynamic interactions between students and ChatGPT in programming learning, focusing on how different instructional interventions influence their learning and AI-interaction. Conducted over three sessions, students were allowed to use ChatGPT to complete programming tasks. The first session had no guidance, the second included hands-on training in prompt writing and effective ChatGPT use, and the third provided a lab guide with sample prompts. After each session, students took a post-test on the activity’s subject. Analyzing students’ prompting behaviors, five AI interaction profiles were identified: AI-Reliant Code Generators, AI-Reliant Code Generator & Refiners, AI-Collaborative Coders, AI-Assisted Code Refiners, and AI-Independent Coders. These profiles were examined to understand their evolution across interventions and their relationship with students’ learning performance. Findings revealed significant changes in profile distribution across interventions, and a notable difference between students’ post-test scores and their AI interaction profiles. Besides, training in prompting skills and effective use of AI significantly impacted students’ interactions with AI. These insights can contribute to the knowledge of integrating generative AI tools in education, highlighting how AI can enhance teaching practices. Understanding student-AI interaction dynamics can allow educators to tailor instructional strategies for optimal learning. This study also underscores the importance of guidance on effective AI use and prompting skills, which can lead students to use AI more meaningfully for their learning.