bluuebunny/crossref_metadata_2025_split huggingface dataset:
SP-DTI: Subpocket-Informed Transformer for Drug-Target Interaction Prediction
Authors: Liu Sizhe , Liu Yuchen , Xu Haofeng , Xia Jun , Li Stan Z 
Published: January 2025

Abstract

Motivation
Drug–target interaction (DTI) prediction is crucial for drug discovery, significantly reducing costs and time in experimental searches across vast drug compound spaces. While deep learning has advanced DTI prediction accuracy, challenges remain: (i) existing methods often lack generalizability, with performance dropping significantly on unseen proteins and cross-domain settings; (ii) current molecular relational learning often overlooks subpocket-level interactions, which are vital for a detailed understanding of binding sites.

Results
We introduce SP-DTI, a subpocket-informed transformer model designed to address these challenges through: (i) detailed subpocket analysis using the Cavity Identification and Analysis Routine (CAVIAR) for interaction modeling at both global and local levels, and (ii) integration of pre-trained language models into graph neural networks to encode drugs and proteins, enhancing generalizability to unlabeled data. Benchmark evaluations show that SP-DTI consistently outperforms state-of-the-art models, achieving a ROC-AUC of 0.873 in unseen protein settings, an 11% improvement over the best baseline.

Availability and implementation
The model scripts are available at https://github.com/Steven51516/SP-DTI.

Contact and Supplementary Information
For correspondence, please contact xiajun@westlake.edu.cn. Supplementary data are available online at Bioinformatics.
Evolutionary and environmental influences on life history traits in Neotropical microteiid lizards
Authors: Oliveira Bruno Halluan S , Colli Guarino R , Vitt Laurie J , Costa Gabriel C , Mesquita Daniel O 
Published: January 2025

Abstract
We examine the life history traits of microteiid lizards (families Alopoglossidae and Gymnophthalmidae), focusing on how environmental variables and female body size influence reproductive traits. We compiled life history data from 34 Neotropical microteiid species. We assess phylogenetic signals and the influence of climatic variables on these traits by employing comparative phylogenetic methods. Our results indicate significant phylogenetic signals in most life history traits, suggesting evolutionary structure within these lizard clades. Clutch size (number of eggs) does not vary within microteiid species such that increasing reproductive investment by increasing clutch size is not an option. We found positive correlations between female body size and egg volume. This finding supports our prediction that lizards with a fixed clutch size will exhibit reproductive compensation by producing larger eggs. Our environmental analyses reveal that less arid conditions favour larger body and egg sizes, while increased precipitation and seasonality positively influence reproductive investment, leading to higher relative clutch mass and larger egg volumes. Conversely, higher mean annual temperatures negatively impact reproductive traits. These findings highlight the adaptive strategies of microteiid lizards in response to diverse and fluctuating environmental conditions, balancing reproductive investment and offspring survival to optimize their success across varying habitats.
Prevalence of Chronic Hand Eczema in adults: A cross-sectional survey of over 60,000 respondents in the general population in Canada, France, Germany, Italy, Spain, and the United Kingdom
Authors: Apfelbacher Christian , Bewley Anthony , Molin Sonja , Fargnoli Maria Concetta , Giménez-Arnau Ana Maria , Brignoli Lysel , Rault Bleuenn , Norlin Jenny M , Skaaby Tea , Crépy Marie-Noëlle 
Published: January 2025

Abstract

Background
The lack of attention to Chronic Hand Eczema (CHE) and the lack of a specific International Classification of Diseases code for CHE may have limited the assessment of CHE prevalence. To date, prevalence estimates have primarily been derived from (partly small) single-country studies.

Objectives
To estimate the annual prevalence of self-reported physician-diagnosed CHE across socio-demographic characteristics among adults in Canada, France, Germany, Italy, Spain, and the United Kingdom (UK).

Methods
In this observational Chronic Hand Eczema epidemiology, Care, and Knowledge of real-life burden (CHECK) study, a questionnaire was administered to adults between 18 and 69 years old in the general population, recruited through online panels. Quotas and minor weighting adjustments were performed to ensure that the participants were representative of the general population regarding sex, age, region, employment status, urban/rural setting, and, in the UK only, ethnicity. Additional weights were applied to account for population size differences when aggregating country results. Information on self-reported physician-diagnosed CHE was collected. CHE was defined, in accordance with the European Society of Contact Dermatitis, as having hand eczema continuously for three months or more or at least two flares in the past 12 months. CHE annual prevalence with 95% confidence intervals (CIs) was determined for each country, and by subgroups of sex, age, employment, and urban/rural.

Results
Among 60,131 participants, 2,847 self-reported physician-diagnosed CHE, yielding an annual prevalence of 4.7% (CI: 4.6-4.9). Subgroup analyses revealed the CHE prevalence was significantly higher in females than males (5.6% [5.4-5.9] vs. 3.8% [3.6-4.1]; P&lt;0.001), in employed versus unemployed participants (5.3% [5.1-5.6] vs. 3.3% [3.1-3.6]; P&lt;0.001), and in urban versus rural residents (5.0% [4.8-5.2] vs. 3.7% [3.4-4.1]; P&lt;0.001). The prevalence was highest among those aged 30-39 years (6.5% [6.0-7.0]) and lowest in those aged 60-69 years (2.6% [2.3-3.0]).

Conclusions
This large multi-national study is the first to assess CHE prevalence in Europe and Canada using a consistent definition across a broad geographical population. This study reveals that CHE is a common skin disease with annual prevalence of 4.7%, with higher prevalence among females, individuals aged 30-39, those employed, and those living in urban areas.
Predictive value of dynamic contrast-enhanced breast magnetic resonance imaging and diffusion-weighted imaging findings for sentinel lymph node metastasis in early-stage invasive breast cancer
Authors: Coskun Bilge Almila , Esen Bostanci Isil 
Published: January 2025

Abstract

Objectives
This retrospective study aimed to evaluate the predictive value of the preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) findings of mass lesions for predicting sentinel lymph node (SLN) metastasis in early breast cancer.

Methods
A total of 310 patients with suspicious mass lesions detected in preoperative MRI who subsequently underwent surgery and SLN biopsy (SLNB) between September 2015 and September 2022 were analysed. The relationship between DCE-MRI and DWI findings and SLNB positivity was analysed.

Results
SLNB was positive for SLN metastasis in 108 of 310 lesions. Younger age (P = 0.001) and larger lesion size (P &lt; 0.001) were found to be associated with SLNB positivity. Findings associated with SLN metastasis included peritumoural oedema in 53%, adjacent vessel sign (AVS) in 81%, and increased whole-breast vascularity (WBV) in 58% of patients with positive SLNB (P &lt; 0.001). The SLNB positivity rate was higher in mass lesions with DCE-MRI findings of heterogenous enhancement pattern (P = 0.003), medium or rapid initial phase enhancement (P = 0.001), and washout delayed phase kinetic curve (P = 0.001). It was found that lower tumoural apparent diffusion coefficient (ADC) values (P = 0.003) and higher peritumoural/tumoural ADC ratios (P = 0.018) increased the probability of encountering SLN metastasis.

Conclusions
Patient age, presence of peritumoural oedema, presence of AVS, increased WBV, and initial phase kinetic curve of the lesions on MRI were found to be associated with SLN metastasis.

Advances in knowledge
We found that younger age and MR findings obtained from the perilesional area of breast cancer may be helpful in the preoperative prediction of SLN metastasis.
From offshore renewable energy to green hydrogen: addressing critical questions
Authors: Kumarasamy Sudhakar , Selvanathan Shanmuga Priya , Ghazali Mohd Fairusham 
Published: January 2025

Abstract
Addressing climate change and navigating the energy transition are more urgent than ever. Several researchers agree that renewable energy adoption and industrial decarbonization are essential pathways forward. As sectors like transportation and heating become increasingly electrified, energy demand is expected to rise, necessitating innovative solutions. Green and blue hydrogen, touted as potential game changers, hold promise in this transition but require advanced electrolysis technologies, sustainable materials, high-pressure storage systems, and optimized system designs for energy efficiency, safety, and scalability to enable large-scale implementation. This study discusses the critical aspects of offshore green hydrogen production, focusing on key findings related to production methods, electrolyzer technologies, and their associated challenges. Key findings highlight that the levelized cost of hydrogen is significantly influenced by the cost of electricity from offshore wind farms, capital expenditure on electrolyzers, and the logistics of offshore platforms, pipelines, and storage. Hydrogen storage advancements, including metal hydrides and chemical carriers, are vital for realizing green hydrogen’s potential as an energy vector. Additionally, the industrial-scale production of green hydrogen through electrolysis powered by offshore wind offers promising pathways for decarbonizing energy systems. The study also emphasizes the critical role of collaboration between local and international policy stakeholders, industrial partnerships, and institutional support in shaping a favorable future for hydrogen in the global energy transition.
A Multianalyte Machine Learning Model to Detect Wrong Blood in Complete Blood Count Tube Errors in a Pediatric Setting
Authors: Graham Brendan V , Master Stephen R , Obstfeld Amrom E , Wilson Robert B 
Published: January 2025

Abstract

Background
Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving upon current single-analyte delta check methodology. However, WBIT detection model performance has not been assessed in a real-world, low-prevalence context. To estimate real-world positive predictive values, we propose a methodology to assess WBIT detection models by evaluating the impact of missing data and by using a “low prevalence” validation data set.

Methods
We trained a range of model specifications using various predictors in a pediatric setting. We assessed the top-performing model on a modified, “low prevalence” validation data set across a range of probability thresholds. Model performance was also compared to a pre-positive patient identification (pre-PPID) dataset.

Results
An Extreme Gradient Boosting (XGBoost) model with minimal preprocessing performed the best for both complete blood count with differential white cell count (CBC with Diff) tests (accuracy 0.9715) and complete blood count without differential white cell count (CBC without Diff) tests (accuracy 0.9647). Assessment on a downsampled, “low prevalence” validation data set resulted in estimated positive predictive values ranging from 0.01 to 0.67 (CBC with Diff) and 0.01 to 0.75 (CBC without Diff), depending on the probability threshold chosen. A comparison of prospective performance to PPID data demonstrated a large decrease in estimated WBIT errors.

Conclusions
We find that ML models can accurately predict WBITs in a primarily pediatric setting. Evaluating model performance across a range of probability thresholds minimizes the number of false positives while still providing added safety benefits. The decrease in estimated WBITS post-PPID implementation shows the potential safety benefits of a WBIT model for hospitals not using PPID when collecting laboratory specimens.
DisGeNet: a disease-centric interaction database among diseases and various associated genes
Authors: Hu Yaxuan , Guo Xingli , Yun Yao , Lu Liang , Huang Xiaotai , Jia Songwei 
Published: January 2025

Abstract
The pathogenesis of complex diseases is intricately linked to various genes and network medicine has enhanced understanding of diseases. However, most network-based approaches ignore interactions mediated by noncoding RNAs (ncRNAs) and most databases only focus on the association between genes and diseases. Based on the mentioned questions, we have developed DisGeNet, a database focuses not only on the disease-associated genes but also on the interactions among genes. Here, the associations between diseases and various genes, as well as the interactions among these genes are integrated into a disease-centric network. As a result, there are a total of 502 688 interactions/associations involving 6697 diseases, 5780 lncRNAs (long noncoding RNAs), 16 135 protein-coding genes, and 2610 microRNAs stored in DisGeNet. These interactions/associations can be categorized as protein–protein, lncRNA–disease, microRNA–gene, microRNA–disease, gene–disease, and microRNA–lncRNA. Furthermore, as users input name/ID of diseases/genes for search, the interactions/associations about the search content can be browsed as a list or viewed in a local network-view.
Database URL: https://disgenet.cn/
Do socioeconomic factors impair uptake of neoadjuvant therapy for patients with locoregional oesophageal cancer?
Authors: Jindani Rajika , Rodriguez-Quintero Jorge Humberto , Loh Isaac , Ha Grace , Olivera Justin , Rosario Justin , Zhu Roger , Kamel Mohamed K , Vimolratana Marc , Chudgar Neel P , Stiles Brendon M 
Published: January 2025

Abstract

OBJECTIVES
The benefits of neoadjuvant therapy prior to surgery for patients with locally advanced oesophageal cancer have been well established by multiple trials. However, there may be socioeconomic barriers impacting equitable administration. We aim to identify whether disparities exist in the uptake of neoadjuvant therapy among patients with loco-regional oesophageal cancer.

METHODS
We queried the National Cancer Database to identify patients with clinical stage II–III oesophageal cancer who underwent surgical resection (2006–2020). Logistic regression was performed to identify associations between sociodemographic factors and uptake of neoadjuvant therapy. In propensity score-matched groups, survival was evaluated using the Kaplan–Meier method.

RESULTS
Among 19 748 clinical stage II–III patients, 85% (n = 16 781) received neoadjuvant therapy and 15% (n = 2967) underwent upfront surgery. Rates of neoadjuvant uptake increased over time. On multivariable analysis after adjusting by clinical stage, factors associated with lower rates of neoadjuvant therapy included older age (age ≥70, adjusted odds ratio 0.52; 95% confidence interval 0.47–0.57; P &lt; 0.001), female sex (0.76; 0.69–0.85; P &lt; 0.001), Black race (0.77; 0.63–0.94; P = 0.009), more comorbidities (0.76; 0.65–0.85; P &lt; 0.001) and government rather than private insurance (0.84; 0.76–0.93; P &lt; 0.001). In a propensity-matched cohort accounting for these variables, neoadjuvant treatment was associated with improved 5-year overall survival compared to upfront surgery (41.1% vs 35.4%, P &lt; 0.001).

CONCLUSIONS
Several sociodemographic factors are associated with the delivery of neoadjuvant therapy in patients with oesophageal cancer, including age, sex, race, and insurance status. Interventions can be put into place to target vulnerable patients and ensure equitable delivery of care.
Exercising Planetary Jurisdiction: On the Legality and Legitimacy of Unilaterally Mitigating Planetary Ecological Footprints
Authors: Buser Andreas 
Published: January 2025

Abstract
International environmental law is increasingly depicted as being insufficient to prevent intertwined ‘planetary crises’ – notably, climate change and the advent of a sixth mass extinction of species. Perceived shortcomings in multilateral environmental treaties and their implementation have prompted policy-makers, particularly within the European Union, to rely more heavily on unilateral regulatory instruments aimed at addressing planetary crises beyond national borders. Examples include the Carbon Border Adjustment Mechanism, legal corporate sustainability due diligence instruments and import restrictions on products linked to deforestation. The exercise of jurisdiction to tackle planetary crises – referred to here as planetary jurisdiction – raises urgent concerns regarding the legality and legitimacy of unilateral regulation with extraterritorial reach. For some, such unilateral regulation is much needed and responds to a moral responsibility or even legal obligation; for others, exercising planetary jurisdiction is tantamount to ‘regulatory imperialism’. In this complex normative landscape, this article provides a nuanced perspective. Based on scientific insights, it highlights that the effects of planetary crises on the population of regulating states strengthen arguments for the permissibility of exercising planetary jurisdiction under customary international law and even support a human rights obligation for states to address their planetary footprint. Such an obligation, however, can be exercised in various ways, many of which would better align with considerations of equity and justice along North-South lines than existing forms of exercising planetary jurisdiction. Drawing from international environmental law, international trade law and human rights law, this article analyses the extent to which regulators face legal requirements to better address participatory and distributional concerns discussed under the heading of planetary justice.
The Association Between Multilingual Experience Factors and Cognitive Functioning in Older Adults: A Lifelines Study
Authors: van den Berg Floor , Brouwer Jelle , Loerts Hanneke , Knooihuizen Remco , Keijzer, Merel 
Published: January 2025

Abstract

Objectives
The complex life experience of speaking two or more languages has been suggested to preserve cognition in older adulthood. This study aimed to investigate this further by examining the relationship between multilingual experience variables and cognitive functioning in a large cohort of older adults in the diversely multilingual north of the Netherlands.

Method
A total of 11,332 older individuals participating in the Lifelines Cohort Study completed a language experience questionnaire. From this cohort, a subset was selected (n = 3,972, aged 59–86) for whom complete demographic and cognitive data were available and who had learned at least two languages to evaluate the association between multilingual experience variables and cognitive functioning. Cognitive functioning was assessed using the Cogstate Brief Battery, which measures processing speed, attention, working memory, and recognition memory.

Results
A linear regression analysis revealed that a higher number of languages learned was related to better performance on all subtasks. In addition, a later onset of acquisition of the second language (L2) was associated with better attention. These effects were independent of demographic variables such as age, education level, income level, and country of birth.

Discussion
The results demonstrate that in our cohort only the experience factors of the number of languages learned and L2 onset of acquisition related to cognitive functioning. Our evidence supports the idea that there is a positive relationship between multilingual experiences and cognitive functioning in older adulthood, but more longitudinal work is needed to establish whether learning multiple languages can potentially promote healthy aging.
Evaluation and Modification of the Multifactorial Model of Driving Safety Among Older Adults
Authors: Tian Junyan , Mogle Jacqueline , Anstey Kaarin J , Ross Lesley A 
Published: January 2025

Abstract

Background and Objectives
Cognitive, visual, and physical performance are associated with driving safety. However, there are few comprehensive models that empirically evaluate how such factors together affect driving safety in older adults. The present study used structural equation modeling (SEM) to evaluate Anstey’s original Multifactorial Model of Driving Safety (MMDS) (2005) as well as a modified MMDS that incorporates recent research.

Research Design and Methods
We used the baseline data from the Advanced Cognitive Training for Independent and Vital Elderly study. Participants (n = 2,391) were drivers with a reported mean age of 73.28 (SD = 5.70; range 65–91), 75.7% White, and 73.3% women.

Results
Using SEM, Anstey’s original MMDS did not achieve adequate fit (CFI = 0.850, TLI = 0.777, RMSEA = 0.074). However, the modified MMDS had a good fit (CFI = 0.961, TLI = 0.934, RMSEA = 0.040). We found that better physical function was correlated with less driving avoidance (β = 0.28, p &lt; .01) and a lower crash risk (β = −0.14, p &lt; .01). Better cognitive abilities were associated with less driving avoidance (β = 0.08, p &lt;.01) and better self-reported driving quality (β = 0.19, p &lt; .01). Driving avoidance partially mediated the relationship between physical function and crash.

Discussion and Implications
This study highlights the importance of cognition and physical function in older adults safe driving. Implications for future directions and public policy considerations are discussed. Future research should examine possible dynamic changes between these predictors and driving in a longitudinal model.
xRead: a coverage-guided approach for scalable construction of read overlapping graph
Authors: Kong Tangchao , Wang Yadong , Liu Bo 
Published: January 2025

Abstract

Background
The development of long-read sequencing is promising for the high-quality and comprehensive de novo assembly for various species around the world. However, it is still challenging for assemblers to handle thousands of genomes, tens of gigabase-level assembly sizes, and terabase-level datasets efficiently, which is a bottleneck to large-scale de novo sequencing studies. A major cause is the read overlapping graph construction that state-of-the-art tools usually have to cost terabyte-level RAM space and tens of days for large genomes. Such lower performance and scalability are not suited to handle the numerous samples being sequenced.

Findings
Herein, we propose xRead, a novel iterative overlapping graph construction approach that achieves high performance, scalability, and yield simultaneously. Under the guidance of its coverage-based model, xRead converts read-overlapping to heuristic read-mapping and incremental graph construction tasks with highly controllable RAM space and faster speed. It enables the processing of very large datasets (such as the 1.28 Tb Ambystoma mexicanum dataset) with less than 64 GB RAM and obviously lower time costs. Moreover, benchmarks suggest that it can produce highly accurate and well-connected overlapping graphs, which are also supportive of various kinds of downstream assembly strategies.

Conclusions
xRead is able to break through the major bottleneck to graph construction and lays a new foundation for de novo assembly. This tool is suited to handle a large number of datasets from large genomes and may play important roles in many de novo sequencing studies.