bluuebunny/crossref_metadata_2025_split huggingface dataset:
The utility of explainable AI for MRI analysis: Relating model predictions to neuroimaging features of the aging brain
Authors: Hofmann Simon M. , Goltermann Ole , Scherf Nico , Müller Klaus-Robert , Löffler Markus , Villringer Arno , Gaebler Michael , Witte A. Veronica , Beyer Frauke 
Published: February 2025

Abstract
Deep learning models highly accurately predict brain age from MRI but their explanatory capacity is limited. Explainable artificial intelligence (XAI) methods can identify relevant voxels contributing to model estimates, yet they do not reveal which biological features these voxels represent. In this study, we closed this gap by relating voxel-based contributions to brain-age estimates, extracted with XAI, to human-interpretable structural features of the aging brain. To this end, we associated participant-level XAI-based relevance maps extracted from two ensembles of 3D-convolutional neural networks (3D-CNNs) that were trained on T1-weighted and fluid-attenuated inversion recovery images of 1855 participants (age range 18–82 years), with regional cortical and subcortical gray matter volume and thickness, perivascular spaces (PVS), and water diffusion-based fractional anisotropy of major white matter tracts. We found that all neuroimaging markers of brain aging, except for PVS, were highly correlated with the XAI-based relevance maps. Overall, the strongest correlation was found between ventricular volume and relevance (r = 0.69), and by feature, temporal-parietal cortical thickness and volume, cerebellar gray matter volume, and frontal-occipital white matter tracts showed the strongest correlations with XAI-based relevance. Our ensembles of 3D-CNNs took into account a plethora of known aging processes in the brain to perform age prediction. Some age-associated features like PVS were not consistently considered by the models, and the cerebellum was more important than expected. Taken together, we highlight the ability of end-to-end deep learning models combined with XAI to reveal biologically relevant, multi-feature relationships in the brain.
Beyond oscillations—Toward a richer characterization of brain states
Authors: Balestrieri Elio , Chalas Nikos , Stier Christina , Fehring Jana , Gil Ávila Cristina , Dannlowski Udo , Ploner Markus , Gross Joachim 
Published: February 2025

Abstract
Our moment-to-moment conscious experience is paced by transitions between states, each one corresponding to a change in the electromagnetic brain activity. One consolidated analytical choice is to characterize these changes in the frequency domain, such that the transition from one state to the other corresponds to a difference in the strength of oscillatory power, often in pre-defined, theory-driven frequency bands of interest. Nonetheless, recent computational advances allow us to explore new ways to characterize electromagnetic brain activity and its changes. Here, we assembled a set of multiple transformations aiming to describe time series in a multidimensional feature space. On an MEG dataset with 29 human participants, we tested how the features extracted in this way described some of those state transitions known to elicit prominent changes in the frequency spectrum, such as eyes-closed versus eyes-open resting-state or the occurrence of visual stimulation. We then compared the informativeness of multiple sets of features by submitting them to a multivariate classifier (SVM). We found that the new features outperformed traditional ones in generalizing states classification across participants. Moreover, some of these new features yielded systematically better decoding accuracy than the power in canonical frequency bands that has been often considered a landmark in defining these state changes. Critically, we replicated these findings, after pre-registration, in an independent EEG dataset (N = 210). In conclusion, the present work highlights the importance of enriching our perspective on the characteristics of electromagnetic brain activity, by considering other features of the signal on top of power in theory-driven frequency bands of interest.
Unveiling Divergent Trends of in Soil Erosion and Soil Organic Carbon Displacement in Response to Climate and Land-Use Changes over China
Authors: Weng Xuerou , Zhang Haicheng , Zhu Jinxin , Wang Dagang , Wang Shuo , Mei Yiwen , Luo Ming 
Published: February 2025

Abstract
Soil erosion is a widespread form of soil degradation in terrestrial ecosystems, and plays a crucial role in the dynamics of soil carbon pools. Assessing soil erosion affected by climate and land-use changes is essential for evaluating future risks and impact on soil organic carbon (SOC) displacements. The Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations have provided the basis for most such assessments, but are gradually being superseded by more recent simulations from Phase 6 (CMIP6). However, a quantitative comparison of the differences between CMIP5 (RCP8.5) and CMIP6 (SSP5-8.5) models and their impacts on soil erosion and SOC simulations has not been conducted. Therefore, this study aims to compare changes in soil erosion in response to climate change and land-use change in China based on CMIP5 and CMIP6 simulations, and assesses the impact of erosion on SOC stocks. Combining the effects of climate and land use change, the CMIP5 ensemble model projects an increase in soil erosion rates over most of China, while CMIP6 models project an average soil erosion reduction of 39 t·km−2·a−1 for the years 2031–2050 compared to the reference period. Climate and land-use changes contribute to the increased soil erosion rate by 51.75% and −28.85%, respectively, based on CMIP5, and by 32.75% and −54.01%, respectively, based on CMIP6. The CMIP6 results demonstrate less rainfall erosivity due to climate change and more pronounced mitigating effects from beneficial land-use changes on soil erosion compared to CMIP5. However, the average change in SOC displacement rate is projected to be −0.02 t·km−2·a−1 for CMIP6. The CMIP5 results suggest that soil erosion in areas other than the Tibetan Plateau will result in a rising rate of soil organic carbon displacement by 0.03 t·km−2·a−1. Therefore, it is recommended that decision-makers consider multiple dimensions such as different models and influencing factors when updating impact studies for water and soil conservation.
Barriers to HIV pre-exposure prophylaxis uptake for men who have sex with both men and women: A global scoping review
Authors: Crossman Jodie , Richardson Daniel 
Published: February 2025

Background Although PrEP is a highly effective HIV prevention method, some groups are underrepresented in PrEP uptake. Much HIV prevention research groups gay, bisexual and other men who have sex with men together; however, men who have sex with both men and women (MSWM) may have needs distinct from those who identify as exclusively gay. This scoping review aims to explore documented barriers to PrEP use among MSWM. Methods Literature was searched using four databases. Studies were included if data referring to MSWM were reported as a distinct category. Data were extracted using a standardised form, and findings were stratified into relevant categories of the social ecological framework. Results Alongside intersectional barriers, MSWM were found to have lower awareness of PrEP, and access sexual health services less than men who have sex only with men. Those who did not identify with the LGBT community often missed out on health promotion messages for this group and were less likely to be offered HIV prevention interventions. MSWM identified more stigmatisation around PrEP use than gay men. However, when aware of PrEP, MSWM were very motivated to use this intervention. Conclusions Not all MSM will identify within the LGBTQ + community and may miss out on valuable opportunities for HIV prevention. PrEP information should be widely available in a variety of health and community settings. Health care professionals should avoid assumptions when assessing patients and provide information about HIV and STI prevention to all attending sexual health services.
Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework
Authors: Karatsidis Angelos , Angelini Lorenza , Scaramozza Matthew , Bartholome Emmanuel , Clinch Susanne P , Shen Changyu , Lindemann Michael , Mazzà Claudia , Scotland Alf , van Beek Johan , Belachew Shibeshih , Craveiro Licinio 
Published: February 2025

Background: Mobility assessment is essential for monitoring disease progression in people with multiple sclerosis (PwMS). Technologies such as wearable sensors show potential for this purpose, but consensus is needed to optimize collection and interpretation of digital measures in PwMS. Objective: To propose a framework for measuring and interpreting key aspects of impaired gait in PwMS using a smartphone worn at the waist level. Methods: The framework was developed on the basis of clinical understanding and knowledge of sensor signal processing, supported by a systematic literature review (SLR). The SLR targeted articles published after 2011 that measured gait characteristics in PwMS. Findings were used to propose standardized definitions for complementary gait domains and define digital measures that should be captured for each domain. Results: The resulting framework for PwMS recommends definitions for pace, rhythm, stability, symmetry, variability, smoothness, complexity and fatigability gait domains. For each domain, a set of digital measures is described with respect to their interpretability and associated caveats. Conclusion: This framework provides recommendations for measuring complex gait patterns in PwMS using widely available technology. This work promotes the use of standardized gait domain definitions and harmonized descriptions of associated digital measures, paving the way for future validation efforts.
“Simpleness”: a qualitative description study exploring patient perspectives on the barriers and facilitators of using digital health tools to self-manage inflammatory bowel disease
Authors: Ajibulu Lekan , Chappell Kaitlyn Delaney , Seow Cynthia H. , Goodman Karen J. , Wong Karen 
Published: February 2025

Background: Inflammatory bowel disease (IBD) is a chronic condition requiring lifelong management and frequent interactions with healthcare providers. Digital health tools have the potential to enhance disease management by providing real-time data and improving care coordination. Despite their potential, there is limited evidence on patient perspectives regarding barriers and facilitators to the adoption of these tools. Objectives: To explore patient perspectives on the barriers and facilitators associated with using digital health tools for IBD self-management, focusing on the adoption of a tool called MyIBDToolkit. Design: This study employed a qualitative description approach to gather detailed insights into patient experiences. Methods: Participants with a confirmed IBD diagnosis were recruited from clinics in Alberta, Canada. Data were collected via virtual semi-structured interviews conducted between June and July 2024. Thematic analysis was used to identify key themes, and member checking ensured the credibility of the findings. Results: Eighteen interviews were conducted, reaching thematic saturation. Participants viewed MyIBDToolkit as beneficial for enhancing disease monitoring and care coordination. However, concerns about data entry burden, privacy, and engagement emerged as significant barriers. Variability in healthcare provider use of the tool was another critical concern. Conclusion: While digital health tools such as MyIBDToolkit have the potential to improve IBD self-management, addressing barriers such as usability, privacy, and sustainability is crucial. Incorporating patient feedback during the design process can enhance the effectiveness and acceptability of these tools in chronic disease management.
Tooth morbidity and its impact on oral related quality of life in elderly tribal population-The Irula experience
Authors: Sukumar Margret Beaula Alocious , Peter Roshni Mary , Joseph Alex 
Published: February 2025

Abstract

Introduction
Oral diseases are a major global health challenge, posing health and economic burdens that have profound impacts on the quality of life, disproportionately affecting marginalized populations such as tribal communities. Among scheduled tribes in India, the Irula community belongs to one of the tribes most vulnerable by poor access to health care and education. The elders in the population have increased incidence and prevalence rates of tooth morbidities-an increased incidence of caries, non-carious lesions, and periodontitis-related conditions that affect oral health related quality of life (OHQOL) dimensions.

Objectives
This study aims to assess tooth morbidity and tooth loss among older Irula community members, identify risk factors, and evaluate how oral and physical comorbidities have been associated with OHRQoL.

Methods
A cross-sectional study was conducted on elderly persons aged 60 years and above in Thiruvallur district, Tamil Nadu, India. A multi-stage random sampling technique was employed in the study. Data were collected by semi-structured questionnaires covering demographics, medical history, oral health practices, and quality of life by clinical dental examination. The tools used included the International Caries Detection and Assessment System (ICDAS) the Smith and Knight Tooth wear index for non-carious lesions, and the Community Periodontal Index for Treatment Needs (CPITN) index for periodontal disease Furthermore, quality of life assessment was carried out utilizing the Geriatric Oral Health Assessment Index (GOHAI). Subsequently, Descriptive and multivariate logistic regression analyses were performed to determine the predictors of OHRQoL.

Results
The prevalence of carious lesions was 38.5%, non-carious lesions 70%, periodontitis 70.8%, and tooth loss 53.6%. Only 2.3% of participants had restorative dental treatments. Multivariate analysis reveals that illiteracy (AOR = 0.163, p = 0.003), arthritis (AOR = 0.340, p = 0.001), carious lesions (AOR = 1.402, p = 0.031), periodontal disease (AOR = 1.663, p = 0.002), and tooth loss (AOR = 2.744, p = 0.001) affected OHRQoL significantly.

Conclusion
The results regarding the elderly community of Irula point towards the severe oral health disparities observed among them; thus, this raises an urgent need to develop a public health intervention for this eminent existing fact. Removing education and socioeconomic barriers, improving access to dental health care, and advocating culturally appropriate preventive programs could increase OHRQoL. Longitudinal study and policy-driven approaches should be carried out in future studies for sustainable health equity of the tribal population.
Dementia as a predictor of palliative care: Uncovering patient patterns based on German claims data
Authors: Rakuša Elena , Reinke Constantin , Doblhammer Gabriele , Radbruch Lukas , Schmid Matthias , Welchowski Thomas 
Published: February 2025

Abstract

Background
Palliative care aims to ensure a dignified and self-determined life for people facing the end of life. While palliative care is established for tumor diseases, it’s notably absent from German medical guidelines for other progressive diseases with an unfavorable prognosis such as dementia. This study will identify predictors of palliative care use in older patients and explore how these predictors relate to the probability of palliative care.

Methods
We used data from the largest German health insurance company of people over 50 years of age from the period 2014–2019. The analysis focused on the last year of life. Outcomes were outpatient and inpatient palliative care and predictors were demographics, comorbidities, therapeutic remedies and rehabilitation, care and medical interventions, medication and patient group. Combined logistic regression models and discrete conditional inference survival forests were used to predict the utilization of outpatient and inpatient palliative care. For evaluation we used concordance-index and calibration plots. We identified the most important predictors by using a permutation approach and the log-loss metric.

Results
The study cohort for the analysis of inpatient palliative care comprised 43,896 patients, while the cohort for the analysis of outpatient palliative care included a total of 37,430 patients. The models had appropriate discriminatory power (inpatient palliative care: concordance-index = 0.737 (95%CI = 0.721–0.754); outpatient palliative care: concordance-index = 0.689; 95%CI = 0.675–0.704) and showed appropriate calibration. A diagnosis of dementia, like a diagnosis of cancer, is predictive of inpatient palliative care and outpatient palliative care. We observed a lower probability for inpatient and for outpatient palliative care for dementia patients compared to cancer patients.

Conclusions
The findings highlight the need to focus palliative care on other patient groups besides cancer patients, such as dementia patients, and to facilitate access for all patients.
Predictive modeling of biodegradation pathways using transformer architectures
Authors: Brydon Liam , Zhang Kunyang , Dobbie Gillian , Taškova Katerina , Wicker Jörg Simon 
Published: February 2025

Abstract
In recent years, the integration of machine learning techniques into chemical reaction product prediction has opened new avenues for understanding and predicting the behaviour of chemical substances. The necessity for such predictive methods stems from the growing regulatory and social awareness of the environmental consequences associated with the persistence and accumulation of chemical residues. Traditional biodegradation prediction methods rely on expert knowledge to perform predictions. However, creating this expert knowledge is becoming increasingly prohibitive due to the complexity and diversity of newer datasets, leaving existing methods unable to perform predictions on these datasets. We formulate the product prediction problem as a sequence-to-sequence generation task and take inspiration from natural language processing and other reaction prediction tasks. In doing so, we reduce the need for the expensive manual creation of expert-based rules.
Nasal pathobiont abundance does not differ between dairy cattle with or without clinical symptoms of bovine respiratory disease
Authors: Centeno-Delphia Ruth Eunice , Long Erica A. , Ellis Audrey C. , Hofmann Sarah , Mosier Kara , Ulloa Noelmi , Cheng Johnnie Junior , Richards Andrew , Boerman Jacquelyn P. , Koziol Jennifer , Verma Mohit S. , Johnson Timothy A. 
Published: February 2025

Abstract

Background
Bovine respiratory disease (BRD) remains a significant health and economic problem to the dairy cattle industry. Multiple risk factors contribute to BRD susceptibility including the bacterial pathobionts Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis. Studies have characterized and quantified the abundance of these bacteria in the nasal cavity of cattle to infer and help disease diagnosis; nonetheless, there is still discrepancy in the results observed of when these microbes are commensal or pathogenic. Additionally, some of these studies are limited to a specific farm. The goal of this study is to compare the nasal microbiome community (diversity and composition) and the abundance of the four bacterial pathogens (by qPCR) in the nasal cavity to identify differences between dairy calves that are apparently healthy and those identified to have BRD. Nasal swabs were collected from approximately 50 apparently healthy and 50 BRD-affected calves sampled from five different dairy farms in the US (CA, IN, NY (two farms), and TX).

Results
Calves diagnosed with BRD in NY, and TX had lower nasal microbiome diversity compared to the apparently healthy calves. Differences in the nasal microbiome composition were observed between the different farms predicted by Bray-Curtis and weighted UniFrac dissimilarities. Commensal and pathobiont genera Acinetobacter, Moraxella, Psychrobacter, Histophilus, Mannheimia, Mycoplasma, and Pasteurella were prevalent in the bovine nasal microbiome regardless of farm or disease status. The BRD-pathobiont H. somni was the most prevalent pathobiont among all the samples and M. bovis the least prevalent. Only in CA was the abundance of a pathobiont different according to disease status, where M. haemolytica was significantly more abundant in the BRD-affected animals than apparently healthy animals.

Conclusions
This study offers insight into the nasal microbiome community composition in both animals diagnosed with BRD and healthy animals, and shows that the farm effect plays a more significant role in determining the microbiome community than disease status in young dairy calves.
On multiplicity of solutions to nonlinear Dirac equation with local super-quadratic growth
Authors: Liao Fangfang , Chen Tiantian 
Published: February 2025

Abstract
In this article, we study the following nonlinear Dirac equation:

−
i
α

⋅

∇

u
+
a
β
u
+
V

(

x

)

u
=
g

(

x
,
∣
u
∣

)

u
,

x
∈

R

3

.

-i\alpha \hspace{0.33em}\cdot \hspace{0.33em}\nabla u+a\beta u+V\left(x)u=g\left(x,| u| )u,\hspace{1em}x\in {{\mathbb{R}}}^{3}.

The Dirac operator is unbounded from below and above so the associated energy functional is strongly indefinite. Compared with some existing issues, the most interesting problem in this article is that we assume that the nonlinearity satisfies a local super-quadratic growth condition, which is weaker than the usual global version. This case allows the nonlinearity to be super-quadratic at some domains and asymptotically quadratic at other domains. Using variational tools together with deformation lemma, genus theory, and some special techniques, we prove the existence of ground-state solutions and infinitely many geometrically distinct solutions under local super-quadratic growth condition. Our results complement and extend the related results of Bartsch and Ding [Solutions of nonlinear Dirac equations, J. Differ. Equ. 226 (2006), 210–249] and of Chen et al. [Ground state solutions for the Dirac equation with periodic external force field, Sci. Sin. Math. (Chinese) 54 (2024), 747–764].