bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patient-centered assessment of treatment for alpha-1 antitrypsin deficiency: literature review to identify concepts and measures for people with alpha1-antitrypsin deficiency
Authors: Seçinti Ekin , Schantz Karolina , Delbecque Laure , Krege John , Mangrum Rikki , Curtis Sarah E. 
Published: February 2025

Abstract

Background
Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder that can result in a range of illnesses, with chronic obstructive pulmonary disease (COPD) being one of the most common. Although some people obtain genetic testing that identifies AATD, many people are unaware that they have AATD until they develop COPD, often at a younger age than is typical. Treatment for AATD consists primarily of augmentation with AAT, requiring weekly infusions of blood products for most patients. This treatment can slow disease progression and improve symptoms, but is burdensome; thus, people with AATD could benefit from additional or alternate treatments. However, to guide the development of new treatments, researchers need to identify which outcomes matter to people with AATD.

Methods
We conducted a scoping literature review to better understand patient experiences with AATD and its treatment and identify patient-reported outcome measures (PROMs) used to assess symptoms and impacts in studies of people with AATD.

Results
The review identified 44 concepts related to symptoms and disease burden, grouped into six domains (symptoms, physical function, cognitive function, emotional function, psychosocial function, and treatment burden) and 24 PROMs that have been used in research on AATD. None of the identified measures were developed specifically for people with AATD. Research on patient-focused outcomes was limited, suggesting a significant gap in knowledge.

Conclusions
People with AATD experience a variety of disease-related burdens, but this study showed there is a lack of published, in-depth studies to support selection and evaluation of patient-centered outcomes among populations of people with AATD. A limited number of PROMs have been used in research on AATD or in clinical trials of treatment, including COPD-specific measures that assess symptoms and quality of life and measures of mood, sleep, and general physical and psychosocial functioning. The current study documented the available evidence and compiled a list of potential concepts of interest, but further qualitative and quantitative studies will be needed to understand the outcomes that matter to people with AATD and to evaluate the alignment between these outcomes and available measures.
Climate change hopefulness, anxiety, and behavioral intentions among adolescents: randomized controlled trial of a brief “selfie” video intervention
Authors: Benoit Laelia , R. Lowe Sarah , Thomas Isaiah , Amsalem Doron , Martin Andrés 
Published: February 2025

Abstract

Aim
We tested the utility of showing “selfie” videos to increase adolescents’ climate change hope, agency, and behavioral intentions, and to decrease their climate anxiety.

Methods
We conducted a randomized controlled trial among healthy volunteers, ages 14 to 18, enrolled through a crowdsourcing platform. We randomly assigned participants (N = 1039) to view one of three 110-s-long video interventions featuring the same adolescent protagonist: positive (depicting an action-oriented stance); negative (defeatist stance); and control (neutral stance and unrelated content). The primary outcome was climate change hope; secondary outcomes were climate change anxiety, behavioral intention scales, and 100-point sliders about hopefulness and agency.

Results
Viewing positive “selfie” videos proved effective among adolescents in increasing hopefulness and a sense of agency regarding climate change (< 0.001), but not in decreasing climate anxiety or increasing intentions to engage in pro-environmental behaviors.

Conclusion
Brief video-based interventions featuring adolescent protagonists showed potential to increase hope and agency regarding climate change. While this single exposure did not directly affect anxiety levels or behavioral intentions, future research should examine whether repeated exposure and different "doses" of such interventions might influence these outcomes. The ubiquity and reach of social media hold promise to scale these inexpensive and specifically tailored interventions.
Swallowing disorders in cerebral palsy: a systematic review of oropharyngeal Dysphagia, nutritional impact, and health risks
Authors: Calderone Andrea , Militi David , Cardile Davide , Corallo Francesco , Calabrò Rocco Salvatore , Militi Angela 
Published: February 2025

Abstract
Cerebral palsy (CP) is a permanent disorder affecting movement and posture due to nonprogressive brain issues, often leading to various sensory, cognitive, and musculoskeletal challenges. Among these complications, oropharyngeal dysphagia (OPD) is prevalent, impacting up to 85% of children with CP and resulting in significant nutritional deficits. This systematic review aims to explore the prevalence and types of OPD in CP patients, its effects on nutritional status, and its associated health complications, emphasizing the need for thorough assessment and intervention to mitigate risks. The review adheres to PRISMA guidelines, searching five major databases (PubMed, Web of Science, Embase, Cochrane Library, and Scopus) without time range restrictions to capture studies addressing swallowing disorders and their impact on nutritional status in CP. This review has been registered on Open OSF (n) 3KUQX. Individuals with CP often experience swallowing impairments, including delayed pharyngeal transit and aspiration. Research indicates that 81.5% of kids with CP suffer from dysphagia, commonly associated with reduced motor skills and general health. Moreover, as a result of these swallowing difficulties, nutritional complications may occur, with elevated levels of gastroesophageal symptoms causing malnutrition and growth delays, which require thorough evaluations and personalized interventions for successful treatment. Tools like the Videofluoroscopic Swallowing Study were identified as primary methods for evaluation, but assessment remains limited by methodological inconsistencies. This systematic review underscores the significant health impacts of OPD in children with CP, which affects nutrition and overall well-being. Future research should address the need for standardized evaluation methods and effective interventions to balance nutritional needs with practical mealtime strategies.
Synthesis and biological activities of 3-aminoimidazo[1,2-α]pyridine compounds
Authors: Al-Qadi Isra , Hanania Michel , Warad Ismail , Al-Hajj Nisreen , Hazzam Rand , Salama Yousef , Raheem Saki , Al-Maharik Nawaf 
Published: February 2025

Abstract
Despite their importance in cancer treatment, anticancer compounds face significant challenges due to drug resistance and low specificity, creating an urgent need for the discovery of more effective alternative. Herein, we report the synthesis of eleven 3-aminoimidazole[1,2-α]pyridine compounds (9–19) employing the one-pot Groebke-Blackburn-Bienayme three-component reaction (GBB-3CR). The cytotoxicity of the synthesised compounds was evaluated against three cancer cell lines (MCF-7, HT-29, B16F10) and a normal cell (MEF). Considering effectiveness and safety, the results demonstrated that among the eleven synthesised compounds, only compounds 12 and 14 exhibited high inhibitory activity against cancer cell lines. Compound 12 with a nitro group at the C-2 position and a p-chlorophenyl group at C-3 position, showed the highest inhibitory activity against HT-29, with an IC50 of 4.15 ± 2.93 µM. Additionally, compound 14, with a tolyl moiety at the C-2 position and a p-chlorophenyl amine at C-3 position, can also be considered a promising bioactive product against B16F10, with an IC50 of 21.75 ± 0.81 µM. Further research on these compounds may yield more potent candidates for the development of new anticancer agents.

Graphic abstract
Discovery of a novel translation-machinery-associated protein that positively correlates with cellulase production
Authors: Ma Kexuan , Zhang Panpan , Zhao Jian , Qin Yuqi 
Published: February 2025

Abstract

Background
The production of cellulases by filamentous fungi is a crucial aspect of sustainable bioproduction from renewable lignocellulosic biomass. Following the transcription of cellulase genes in the nucleus, a complex pathway involving translation, folding, and secretion is required to produce extracellular cellulases. Most studies about cellulase production have focused on examining transcriptional regulatory mechanisms and enhancement of enzyme gene levels; comparatively, little is known about protein translation and secretion for cellulase production.

Results
A translation-machinery-associated (TMA) protein PoTma15 was identified in cellulosic Penicillium oxalicum. The PoTma15 is conserved in various filamentous fungi, but not in yeast, plants, or animals. All homologous proteins of PoTma15 have previously been uncharacterized. PoTma15 was initially thought to be one of the putative interactors of transcription factor PoXlnR, as it was preyed by tandem affinity purification (TAP) coupled with the mass spectrometry (TAP–MS) technique using PoXlnR as the bait. Subsequent research revealed that PoTma15 is associated with the translation machinery. The top three proteins associated with PoTma15 are orthologs of Saccharomyces cerevisiae translation-machinery-associated protein (Tma19), translation elongation factor eIF5A, and ribosomal protein S28, respectively. PoTma15 is widely distributed in fungal hyphae and positively correlates with the production of cellulases and extracellular proteins. Deleting the Potma15 gene (Δtma15) decreased cellulase production, while overexpressing the Potma15 gene (OEtma15) increased cellulase production. However, the Δtma15 mutant was not observed to have downregulated transcript levels of major (hemi)cellulase and amylase genes, compared to the P. oxalicum wild type (WT). The production of extracellular cellulases and extracellular proteins of the Δtma15 mutant was less affected by cycloheximide, an inhibitor of eukaryotic translation elongation, compared to the WT strain and OEtma15 mutant, suggesting a stronger resistance to the translation-inhibiting effects of cycloheximide in the Δtma15 mutant. The results demonstrate that PoTma15 is a translation-machinery-associated protein that affects translation elongation and, consequently, the production of enzyme proteins.

Conclusions
PoTma15 is the first TMA protein characterized in cellulosic filamentous fungi and the first TMA protein used in fungi to increase cellulase production. PoTma15’s role in the production of cellulases and total extracellular proteins suggests that not only can it be used to widen the cellulase production pathway, but can even be engineered as a target to improve the production of other heterologous protein or bioproducts using filamentous fungi as cell factories in the future.
Altered interactive dynamics of gaze behavior during face-to-face interaction in autistic individuals: a dual eye-tracking study
Authors: Tönsing Daniel , Schiller Bastian , Vehlen Antonia , Nickel Kathrin , van Elst Ludger Tebartz , Domes Gregor , Heinrichs Markus 
Published: February 2025

Abstract

Background
Previous eye-tracking research on autistic individuals has mostly examined the gaze behavior of one individual in response to social stimuli presented on a computer screen, suggesting that there is atypical gaze behavior. However, it is unknown how these findings translate to the interactive dynamics of gaze behavior during “face-to-face” encounters between two individuals. Only by analyzing the gaze behaviour of both interaction partners is it possible to determine the frequency of actual eye-contact and who initiates or breaks such periods of mutual eye gaze. The knowledge gained from this analysis could contribute to theorizing about the psychological mechanisms (e.g., gaze avoidance vs. gaze indifference) underlying autism.

Methods
The present study applied a novel dual eye-tracking setup that allows the assessment and analysis of the interactive dynamics of gaze behavior regarding (i) mutual eye gaze (i.e., eye contact), (ii) initiations, and (iii) break-ups of eye contact. Participants (37 autistic individuals, 37 age- and IQ-matched neurotypical individuals) performed a semi-standardized social interaction (i.e., Fast Friends Procedure) with a confederate (trained to interact in a standardized manner).

Results
Eye contact was reduced in interactions involving autistic individuals. Additional analyses revealed that this reduction was primarily due to the more frequent breaking of eye contact by these individuals. We also found considerable heterogeneity among autistic individuals, with atypical gaze behavior present in only about half of the sample.

Limitations
Further research is required to determine whether the interactive dynamics of gaze behavior observed in this dual eye-tracking setup can be generalized to real-world situations. Future studies could also include arousal-related physiological measures.

Conclusions
By tracking the gaze behavior of two interacting individuals, this study reveals specific atypicalities in the interactive dynamics of gaze behavior in a subset of autistic individuals, potentially informing diagnostic and therapeutic decisions. More broadly, our study highlights the added value of dual eye-tracking in elucidating the interactive nature of social encounters in both neurodiverse and neurotypical individuals.

Trial registration
The study was registered as a clinical trial before starting data collection (https://drks.de/search/en/trial/DRKS00018957; Registration Date: 12/17/2019).
Modelling epidemiological and economics processes – the case of cervical cancer
Authors: Taeger Franziska , Mende Lena , Fleßa Steffen 
Published: February 2025

Abstract
Different types of mathematical models can be used to forecast the development of diseases as well as associated costs and analyse the cost-effectiveness of interventions. The set of models available to assess these parameters, reach from simple independent equations to highly complex agent-based simulations. For many diseases, it is simple to distinguish between infectious diseases and chronic-degenerative diseases. For infectious diseases, dynamic models are most appropriate because they allow for feedback from the number of infected to the number of new infections, while for the latter Markov models are more appropriate since this feedback is not required. However, for some diseases, the aforementioned distinction is not as clear. Cervical cancer, for instance, is caused by a sexually transmitted virus, and therefore falls under the definition of an infectious disease. However, once infected, the condition can progress to a chronic disease. Consequently, cervical cancer could be considered an infectious or a chronic-degenerative disease, depending on the stage of infection. In this paper, we will analyse the applicability of different mathematical models for epidemiological and economic processes focusing on cervical cancer. For this purpose, we will present the basic structure of different models. We will then conduct a literature analysis of the mathematical models used to predict the spread of cervical cancer. Based on these findings we will draw conclusions about which models can be used for which purpose and which disease. We conclude that each type of model has its advantages and disadvantages, but the choice of model type often seems arbitrary. In the case of cervical cancer, homogenous Markov models seem appropriate if a cohort of newly infected is followed for a shorter period, for instance, to assess the impact of screening programs. For long-term consequences, such as the impact of a vaccination program, a feedback loop from former infections to the future likelihood of infections is required. This can be done using system dynamics or inhomogeneous Markov models. Discrete event or agent-based simulations can be used in the case of cervical cancer when small cohorts or specific characteristics of individuals are required. However, these models require more effort than Markov or System Dynamics models.
Staphylococcal SplA and SplB serine proteases target ubiquitin(-like) specific proteases
Authors: Glinka Felix L. , Schmöker Ole , Singh Abhishek K. , Steil Leif , Hentschker Christian , Völker Uwe , Böttcher Dominique , Lammers Michael , Cammann Clemens , Seifert Ulrike , Krüger Elke , Naumann Michael , Bröker Barbara M. , Bornscheuer Uwe T. 
Published: February 2025

Abstract

Staphylococcus aureus is a Gram-positive opportunistic pathogen that has colonized nearly 30% of the human population and can cause life-threatening infections. S. aureus exports a variety of virulence factors, such as a novel set of extracellular serine protease-like proteins (Spls). Spls are expressed by most clinical isolates of S. aureus, but their pathophysiological substrates and role during the infection are largely unknown. Here we characterized the substrate and cleavage specificity of recombinantly expressed SplA and SplB proteins. We identified a group of ubiquitin or ubiquitin-like modifying enzymes including deubiquitinating enzymes from human as well as from bacterial sources to be so far unknown SplA and SplB substrates. Distinct cleavage sites within these substrates for SplA (YLY↓T, FMY↓N) and SplB (VCD↓S) were identified by mass spectrometry and confirmed by site-directed mutagenesis of the target proteins. Since many cellular immune signaling pathways are tightly regulated by ubiquitination, the specific cleavage of ubiquitin modifying enzymes strongly suggests a specific role of Spls in manipulating immune signaling and in competing with other bacteria.
The m6A revolution: transforming tumor immunity and enhancing immunotherapy outcomes
Authors: Shi Tongguo , Zhang Huan , Chen Yueqiu 
Published: February 2025

Abstract
N6-methyladenosine (m6A), the most prevalent RNA modification in eukaryotes, plays a critical role in the development and progression of various diseases, including cancer, through its regulation of RNA degradation, stabilization, splicing, and cap-independent translation. Emerging evidence underscores the significant role of m6A modifications in both pro-tumorigenic and anti-tumorigenic immune responses. In this review, we provide a comprehensive overview of m6A modifications and examine the relationship between m6A regulators and cancer immune responses. Additionally, we summarize recent advances in understanding how m6A modifications influence tumor immune responses by directly modulating immune cells (e.g., dendritic cells, tumor-associated macrophages, and T cells) and indirectly affecting cancer cells via mechanisms such as cytokine and chemokine regulation, modulation of cell surface molecules, and metabolic reprogramming. Furthermore, we explore the potential synergistic effects of targeting m6A regulators in combination with immune checkpoint inhibitor (ICI) therapies. Together, this review consolidates current knowledge on the role of m6A-mediated regulation in tumor immunity, offering insights into how a deeper understanding of these modifications may identify patients who are most likely to benefit from immunotherapies.
Simrec: a similarity measure recommendation system for mixed data clustering algorithms
Authors: Diop Abdoulaye , El-Malki Nabil , Chevalier Max , Péninou André , Roman-Jimenez Geoffrey , Teste Olivier 
Published: February 2025

Abstract
Clustering algorithms play a pivotal role in data mining, offering powerful tools for uncovering hidden patterns and structures within datasets. These algorithms aim to divide data points into coherent groups based on similarities or dissimilarities, making it easier to explore and understand complex data. Clustering algorithms typically rely on similarity measures to assess the likeness between data points. Consequently, selecting a suitable similarity measure is crucial for achieving satisfactory clustering outcomes. However, this decision can pose significant challenges, especially for non-experts, given the plethora of similarity measures available in the literature and their performance which is closely linked to the specific dataset, clustering algorithm, and cluster validity index employed. This difficulty is even more important when considering mixed data clustering. Mixed data refers to heterogeneous data characterized by both numerical and categorical attributes. In such a context, the same similarity measure cannot be used for both types of attributes due to their different nature. Commonly, two similarity measures are combined, one for numerical attributes and one for categorical attributes. This adds a layer of complexity to the problem since it requires the selection of two similarity measures instead of just one. This paper introduces SIMREC, a similarity measure recommendation system for mixed data clustering. The system uses meta-learning to mine the relationship between dataset characteristics and similarity measures performances for different mixed data clustering algorithms and cluster validity indices. Therefore, given a mixed dataset, a mixed data clustering algorithm, and a cluster validity index, the system can recommend suitable pairs of numerical and categorical similarity measures based on the characteristics of the dataset. We implemented the proposed system using 130 pairs of similarity measures (10 numerical and 13 categorical), 4 commonly used mixed data clustering algorithms (K-Prototypes, LSH-K-Prototypes, K-Medoids, and Hierarchical Clustering), and three cluster validity indices (Silhouette, Clustering Accuracy, and Adjusted Rand Index). Our experiments on 185 publicly available mixed datasets show that the pairs of similarity measures recommended by SIMREC outperform the baseline pairs, including classically used pairs of similarity measures in the literature.
Towards scalable medical image compression using hybrid model analysis
Authors: Li Shunlei , Lu Jiajie , Hu Yingbai , Mattos Leonardo S. , Li Zheng 
Published: February 2025

Abstract
The exponential growth in medical image generation poses significant challenges for storage and management. Lossless compression of medical images is essential to reduce storage demands while ensuring image quality is preserved. Wavelet-based compression techniques, widely recognized in the literature, are commonly used to process and transmit medical images by isolating the Region of Interest (ROI) from other areas. Meanwhile, Convolutional Neural Networks (CNN) have shown promising results for medical image compression. In this study, we propose a hybrid model combining Discrete Wavelet Transforms (DWT) and CNN for medical image compression. DWT is applied to encode the ROI, while CNN is employed for non-ROI regions. Here, Singular Value Decomposition (SVD) is used to extract ROI features. We introduce the SDWTCNN framework, which integrates DWT and CNN to achieve scalable image compression with lower complexity compared to similar methods. The performance of SDWTCNN is evaluated using different performance metrics, demonstrating its effectiveness in maintaining image quality at various compression rates. Experimental results confirm the efficiency of our framework for storing and retrieving medical images in healthcare applications. Specifically, our SDWTCNN achieves 4.3 dB better performance on the BGPD dataset and 3.8 dB on the BraTS dataset than the existing best method in terms of the PSNR metric.