bluuebunny/crossref_metadata_2025_split huggingface dataset:
Insolation-triggered Eurasian Ice Sheets collapse initiates the Last Termination
Authors: Liu Yanguang , Dong Wu , Li Siqi , Eiríksson Jón , Guðmundsdóttir Esther , Rosenthal Yair , Hu Ningjing , Fan Dejiang , Zhang Xu 
Published: January 2025

Abstract

The collapse of Northern Hemisphere ice sheets has been deemed as a trigger for the chain of positive climate feedback during glacial terminations in Quaternary. Increasing boreal summer insolation is considered the ultimate driver of their collapse, however, the initiating mechanisms remain elusive. Here we report an unambiguous warming trend in the southern Nordic Seas, which coincides with the initial phase of Northern Hemisphere summer insolation increase at the end of the Last Glacial Maximum. A subsequent phase of surface cooling is observed, closely corresponding to the massive freshwater discharge attributed to the meltwater pulse at 19ka BP. Our reconstructions demonstrate that the initial collapse of Northern Hemisphere ice sheets during the Last Termination occurred in Eurasian Ice Sheet, driven by a chain of oceanic responses to the insolation increase. Specifically, increasing boreal insolation induced a northward migration of the mid-latitude Westerlies under a positive NAO phase, promoting poleward oceanic heat transport and hence subsequent warming in Nordic Seas, thereby accelerating the ablation of the marine-based Eurasian Ice Shelves. This led to a catastrophic release of icebergs into Nordic Seas, eventually triggering a series of ocean circulation feedbacks that further promoted the deglaciation.
Serotonin 2A Receptor Attenuates Psoriatic Inflammation by Suppressing IL-23 Secretion in Monocyte-derived Langerhans Cells
Authors: Lee Yungling , Tan Yeh Fong , Yeh Chen-Yun , Hsu Sheng-Yun , Lu Chun-Hao , Tsai Ching-Hui , Chiang Pei-Chuan , Weng Hao-Jui , Tsai Tsen-Fang 
Published: January 2025

Abstract

Anecdotal evidence has suggested an association between psychiatric drugs and psoriasis but consensus is absent due to contradicting reports and the mechanism remains poorly defined. Here, we investigated the role played by serotonin 2A receptor (HTR2A), a receptor commonly targeted by psychiatric drugs, in regulating psoriasis. HTR2A antagonistic drugs worsened psoriatic outcome and HTR2A modulation reduced psoriatic inflammation. Using Imiquimod-induced psoriasiform model, HTR2A-deficient mice experienced exacerbated inflammation. Hematopoietic cells, particularly monocyte-derived Langerhans cells (moLC), were responsible for this phenotype. Mechanistically, the exacerbated inflammation is due to increased interleukin-23 (IL-23) secretion and HTR2A suppresses it by inhibiting activation of the non-canonical NFkB pathway. Serotonin is the putative agonist modulating HTR2A attenuating psoriatic inflammation. Lastly, our findings in mice were also validated clinically. Our data demonstrate serotonin modulates HTR2A, attenuating psoriatic inflammation by suppressing IL-23 secretion via inhibiting non-canonical NFkB pathway in moLCs.
Synergistic Effects of Diabetes and Smoking on Ticagrelor Antiplatelet Activity in ACS Patients Undergoing PCI
Authors: Elkenay Nasima Mohamed , Almasswary Adel , Sabah Zia ul , Agiba Nadia Ahmad , Elmahdy Hanaa Kamel , Elsherbiny Eman Aziz Yousef , Said Salwa Rashad Aly , Ewis Ahmed Mohamed , Ahmed Marwan Sayed Mohamed , Saleh Rayyh Abdelazeem Mohammad , Saleh Bothayna I , Alghamdi Huda S , Tahs Randa Sabour Elshahat , Radwan Enas Elsebaee Elsaid , Elmalah Abeer Ahmed 
Published: January 2025

Abstract

Background:Diabetes and smoking are well-established risk factors that enhance platelet reactivity in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI).
Objective:To compare the combined (synergistic), individual effects of smoking and diabetes, and the absence of these risk factors on the antiplatelet efficacy of ticagrelor in ACS patients undergoing PCI.
Methods: A total of 400 patients participated in this study. Patients were stratified into four groups based on their smoking and diabetes status: Group I (diabetic Smokers), Group II (diabetic non-smokers), Group III (non-diabetic smokers), and Group IV (non-diabetic non-smokers), with 100 patients in each group. All patients received a 180 mg loading dose of ticagrelor immediately prior to PCI. Maximum platelet aggregation (MPA) and Platelet Reactivity Index (PRI) were assessed at baseline and at four hours post-loading dose administration of ticagrelor to evaluate antiplatelet activity.
Results: Baseline characteristics were comparable across all groups except for smoking and diabetes status. Group I (diabetic smokers) had a significantly higher proportion of individuals with high PRI compared to Group II (p=0.002), Group III (p=0.001), and Group IV (p=0.001), with no significant differences between Group II and Group III (p=1.000), Group II and Group IV (p=0.758), or Group III and Group IV (p=0.798). For high MPA, Group I also had significantly higher percentages compared to Group II (p=0.0005), Group III (p<0.0001), and Group IV (p=0.002), with no significant differences between Group II and Group III (p=0.712), Group II and Group IV (p=1.000), or Group III and Group IV (p=0.943). Multivariate logistic regression identified the combination of diabetes and smoking as a significant independent predictor for high PRI (adjusted OR: 2.24; 95% CI: 1.21-4.16; p=0.010) and high MPA (adjusted OR: 2.65; 95% CI: 1.08-6.48; p=0.031).
Conclusion: ACS patients who are both smokers and diabetics undergoing PCI may exhibit reduced responsiveness to the antiplatelet effects of ticagrelor, warranting closer clinical attention to optimize their management.
GWAS highlights the neuronal contribution to multiple sclerosis susceptibility
Authors: De Jager Philip , Zeng Lu , Khan Atlas , Lama Tsering , Chitnis Tanuja , Weiner Howard , Wang Gao , Fujita Masashi , Zipp Frauke , Taga Mariko , Kiryluk Krzysztof 
Published: January 2025

Abstract

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type. The expression of IL7 and STAT3 are affected only in inhibitory neurons, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.
Benchmarking State of the Art Website Embedding Methods for Effective Processing and Analysis in the Public Sector
Authors: Gerber Jonathan , Saxer Jasmin , Kreiner Bruno , Weiler Andreas 
Published: January 2025

Abstract

The ability to understand and process websites is crucial across various domains. It lays the foundation for machine understanding of websites. Specifically, website embedding proves invaluable when monitoring local government websites within the context of digital transformation. In this paper, we present a comparison of different state-of-the-art website embedding methods and their capability of creating a reasonable website embedding for our specific task. The models consist of visual, mixed, and textual-based embedding methods. We compare the models with a baseline model which embeds the header section of a website. We measure the performance of the models using zero-shot and transfer learning. We evaluate the performance of the models on three different datasets. Additionally to the embedding scoring, we evaluate the classification performance on these datasets. From the zero-shot models Homepage2Vec with visual, a combination of visual and textual embedding, performs best in general over all datasets. When applying transfer learning, MarkupLM, a markup language-based model, outperforms the others in both cluster scoring as well as precision and F1-score in the classification task. However, time is an important factor when it comes to processing large data quantities. Thus, when additionally considering the time needed, our baseline model is a good alternative, being 1.88 times faster with a maximum decrease of 10 % in the F1-score.
Transcriptional regulation of the non-homologous end joining gene Ligase IV by an intronic regulatory element directs thymocyte development
Authors: Collins Patrick , Estrada Matthew , Gebhardt Christopher , Salem Mariam , Sharma Kruthika , Bassing Craig , Oltz Eugene 
Published: January 2025

Abstract

Double-strand breaks represent the most dangerous form of DNA damage, and in resting cells, these breaks are sealed via the non-homologous end joining (NHEJ) factor Ligase IV (LIG4). Excessive NHEJ may be genotoxic, necessitating multiple mechanisms to control NHEJ activity. However, a clear mechanism of transcriptional control for them has not yet been identified. Here, we examine mechanisms governing Lig4 transcription in mammals, finding that most tissues maintain very low levels of LIG4 production. Select tissues upregulate LIG4, employing different strategies for genomic regulation. In developing lymphocytes, the Lig4 locus is devoid of long-range chromatin contacts; instead, its expression and role in immune development depend upon a promoter-proximal intronic regulatory element. Deletion of the Lig4 intronic regulatory element results in thymocyte-specific loss of Lig4 upregulation, defects in lymphocyte development and altered antigen receptor rearrangement. Our findings show the NHEJ gene, Lig4, is transcriptionally controlled to support stage-specific function concurrent with programmed DSBs. Moreover, we provide an example of how DNA cis-regulatory elements very close to a promoter can have substantial transcriptional effects.
The impact of pediatric obsessive-compulsive disorder on school attendance and school functioning: a case for supported education
Authors: Cruz Lorena Fernández de la , Rautio Daniel , Wickberg Frida , Gordan Cecilia , Silverberg-Mörse Maria , Mataix-Cols David 
Published: January 2025

Abstract

School-related functional impairment is common in children and adolescents with obsessive-compulsive disorder (OCD). However, little is known about the characteristics of youth with OCD who struggle in school, whether these struggles interfere with treatment outcomes, and whether treatment improves school-related function. Among 385 youth with OCD at a specialist clinic (mean age [sd] = 13.7 [2.5]; 63.1% girls), 21.6% had partial or no school attendance at intake. Among those who received specialist treatment (n = 322), outcomes were similar in those with no or partial attendance vs. those with full attendance, although the latter group needed fewer treatment sessions and were less likely to be on psychotropic medication. At post-treatment, 10.5% still had partial or no school attendance, and 22.8% of youths and 33.3% of parents reported significant school impairment, regardless of response status. Some youth with OCD may benefit from specific supported education and return to school strategies to complement regular evidence-based interventions.
Leveraging Information Technology Tools to Create Cost-Effective Alternatives: Using Google Sheets as a Platform for Competitive Debate and Public Speaking Tabulation.
Authors: Osei-Wusu Franco , Asiedu William , Yeboah Donald , Kar Shuvajyoti , Muntaka Siddique Abubakr , Appiah Joel Kwesi 
Published: January 2025

Abstract

Traditional web-based tabulation systems used for extracurriculars like debate competitions, while offering robust features, usually pose cost and accessibility challenges for respective stakeholders in the debate community within academic settings. Such challenges tend to limit participation, frequency of organization, or the smooth running of such events. In this paper, we leverage Google Sheets’ inherent features like Apps Script, Google Forms, real-time collaboration, and cloud functionality to create a cost-effective alternative, Tab XYZ, for debate and public speaking tabulation purposes. We examine and compare the proposed system’s key functionalities and architecture to a widely used conventional web-based platform, Tabbycat, through a comprehensive evaluation via metrics such as user satisfaction, ease of setup, cost-effectiveness, system reliability, data security and privacy, and error handling and management. After rigorous testing involving a diverse group of 435 users across five different debate and public speaking tournaments, results confirmed Tab XYZ's superior cost-effectiveness, comparable user satisfaction, robust data security through Google's infrastructure, and timely setup process. Additionally, the experiments revealed that the proposed system presented user-friendly and robust error handling and data recovery capabilities through offline functionality. Finally, this study presents a pathway for leveraging the integration of readily available Information Technology tools, such as Google Sheets and its features, to create innovative solutions for specialized problems within educational settings, to elude the burden of cost and accessibility that usually come with conventional approaches
Competencies for Undergraduate Dental Education in the African Context: A Qualitative Study in Four Dental Schools
Authors: Mutebi Annet Kutesa , Boamah Matthew Owusu , Ogundipe Olufemi Kolawole , Maart Ronel D 
Published: January 2025

Abstract

Background: Core competencies for new dental graduates have been established in various regions globally to harmonise educational standards and facilitate the migration of health workers. This has led to numerous curricular comparison studies, such as North America, Western Europe, and Asia. However, such efforts across the African continent are scarce. It is unclear how dental curricula in Sub-Saharan Africa compare, leading to potential variations in the skills and attributes of dental graduates from different countries. This study aimed to explore dental educators' views on the competencies required for dental graduates to practice in the 21st century at four Sub-Saharan African dental schools.
Methods: A cross-sectional qualitative study employing an exploratory descriptive approach was conducted between January and June 2023. Focus group discussions were held at four dental schools: University of the Western Cape (South Africa), Makerere University (Uganda), University of Ghana, and Obafemi Awolowo University (Nigeria). Dental educators were purposively sampled. Data were collected using unstructured interview guides focusing on competencies required upon graduation, their appropriateness to society, and suitability for 21st-century practice in Africa. Data were transcribed verbatim and analyzed using content analysis.
Findings: The study included 34 participants, with an even distribution of males and females. Seven themes emerged as essential competencies for dental graduates: clinical competence and skills, global and local competencies, technology and advanced tools, community and preventive dentistry, professionalism and ethical values, educational structure and assessment, and business aspects of dentistry. Participants emphasized the need for practical skills in various fields of dentistry, community diagnosis, and practice. They highlighted the importance of incorporating advanced technologies, professionalism, ethical standards, communication, and business skills into the curriculum.
Conclusion: The study revealed a consensus among dental educators on the necessity for more practical skills and community-oriented practice for dental graduates in Sub-Saharan Africa. The findings underscore the need for a unified curriculum across the continent to ensure consistent competency standards. Incorporating advanced technologies, professionalism, ethical standards, communication, and business skills into dental education is crucial for preparing graduates to meet the demands of modern dental practice while being responsive to the African context and maintaining global relevance.
Exploring the Association Between Hemoglobin Glycation Index and Cognitive Function in Older Adults with Hypertension: A Cross-Sectional Study
Authors: Ding Hong , Kang Tingyue , Gao Wenbo , Wang Qi , Liu Shu , Zhang Xiaowei , Yu Jing 
Published: January 2025

Abstract

Background
The Hemoglobin Glycation Index (HGI) quantifies the difference between the actual and expected values of glycosylated hemoglobin (HbA1c), a marker that has been closely linked to various adverse health outcomes. Nonetheless, a significant gap exists in the current literature concerning the association between HGI and cognitive function. This study aims at testing such association in older adults with hypertension, a topic that has not yet been extensively investigated.
Methods
A linear regression model between glycated hemoglobin A1c (HbA1c) levels and fasting plasma glucose (FPG) was constructed for the calculation of the HGI. The cross-sectional study focused on evaluating the cognitive function of hypertensive individuals (≥ 60 years old), based on the data from the 2011–2014 National Health and Nutrition Examination Survey (NHANES), by using a series of standardized tests, including the Word List Learning (CERAD-WL) and Delayed Recall (CERAD-DR) tests from the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST). Weighted logistic and linear regression models served for evaluating the effect of HGI on hypertensive patients’ cognitive function. Restricted cubic spline (RCS) curves assisted in detecting the underlying nonlinear associations between HGI and cognitive outcomes. Furthermore, subgroup analyses and interaction tests were performed to gain deeper insights into these associations.
Results
The study included 1023 participants ≥ 60 years old from 2011–2014 NHANES. Higher HGI was accompanied by lower DSST score (P = 0.009). In the fully adjusted model, participants in the highest quartile (Q4) of HGI possessed a lower DSST score (β = 0.01, 95% CI 0.00–0.41) versus the lowest quartile (Q1), and were more likely to exhibit low cognitive function as evaluated by the DSST (OR = 2.21, 95% CI 0.98–5.03). According to the results from RCS analysis, HGI presented a linear relevance to cognitive function scores in older adults with hypertension. No significant statistical interaction was detected between these variables.
Conclusion
High HGI was an important risk factor leading to reduced cognitive performance in hypertensive patients, ensuring HGI to be used for effectively predicting patients’ cognitive decline.
Patterns and PredictOrS of HIV Treatment FaIlures in Pediatric EnrOlled ClieNts in a Tertiary HeAlth Care FaciLity in Southeast Nigeria - POSITIONAL study
Authors: Ogbuagu Chukwuanugo , Ogbuagu Ekenechukwu , Emelumadu Obiageli , Edokwe Emeka , Okereke Uzoma , Okwuchukwu Heavenah , Ezeama Nkiru , Uwakwe Richard 
Published: January 2025

Abstract

Introduction:
Managing pediatric HIV remains a critical challenge, especially in low- and middle-income countries like Nigeria, where healthcare resources are limited, and the HIV burden is high. This study explored the prevalence and determinants of antiretroviral treatment (ART) failure among children in the region. Key factors such as demographic characteristics, clinical parameters, and adherence levels were analyzed to identify predictors of treatment failure. By addressing these factors, the research aims to enhance management strategies, improve outcomes, and contribute to achieving viral suppression. This effort underscores the importance of targeted interventions to improve the quality of life for children living with HIV in resource-limited settings.
Method:
A retrospective cross-sectional study aimed to identify the patterns and predictors of pediatric HIV treatment failure at Nnamdi Azikiwe University Teaching Hospital (NAUTH) in Nnewi, Southeast Nigeria using medical records data of enrolled pediatric HIV patients over five years, from January 2019 to December 2023.
Result:
The study population comprised individuals enrolled in the pediatric clinic of the healthcare facility. Most participants were female (50.6%) and students (44.8%). The pattern showed that most participants were underweight at baseline (81.0%), most respondents adhered well to their regimen (99.7%), and a high percentage achieved undetectable viral loads (76.4%). The data indicated significant improvements in both CD4 counts and BMI over time, highlighting the positive impact of the treatment and management strategies employed. Virological failure was the most common predictor of treatment failure. Also, younger age at ART initiation, higher baseline viral load, and lower baseline CD4 count were significant predictors of treatment failure. Limited access to second-line ART options and inconsistent viral load monitoring were significant healthcare system-related barriers, reflecting the resource challenges in many LMICs.
Conclusion:
The findings from the study provided valuable insights into the patterns and predictors of pediatric HIV treatment failure at NAUTH Nnewi, Southeast Nigeria, highlighted the complex interplay between patient-related and healthcare system factors in managing pediatric HIV, and underscored the need for targeted interventions to improve treatment outcomes in this vulnerable population.
COLLAR: Combating Low-rank Temporal Latent Representation for High-dimensional Multivariate Time Series Prediction using Dynamic Koopman Regularization
Authors: Nie Siyu , An Simin , Peng Qifa , Su Yong 
Published: January 2025

Abstract

Recent advancements in high-dimensional multivariate time series forecasting have yielded promising outcomes by effectively capturing temporal dynamics within a low-dimensional latent subspace. While Recurrent Neural Networks (RNNs) excel at learning temporal models in reduced-dimensional spaces, the simplistic structure of the decoder fails to capture the diversity present in the observed data. Conversely, introducing a more intricate encoder might exacerbate the risk of overfitting. In response to this susceptibility, we propose COLLAR – an innovative architecture that employs dynamic linearized regularization. COLLAR aims to reconcile the inherent nonlinear temporal structures present in low-dimensional subspaces with the linear evolution of multivariate time series. Specifically, we utilize the Auto-Encoder (AE) as the backbone, facilitating the factorization of multivariable time series into a low-dimensional subspace. We construct a nonlinear prediction model for latent sequences using Gated Recurrent Units (GRU). To learn linear dynamics, we integrate the data-driven Koopman operator with a modified AE architecture to generate linear dynamics regularization terms, thereby constraining the uncertainty in nonlinear prediction. The eigenfunctions derived from the Koopman operator provide intrinsic coordinates that globally linearize the dynamics, enabling the prediction of the next state to depend solely on the current state. The proposed approach is evaluated across five publicly available datasets and outperforms several competitive baselines. The code and models are available at https://github.com/Nsyyyy/COLLAR.