bluuebunny/crossref_metadata_2025_split huggingface dataset:
External validation of the accuracy of cardiovascular risk prediction tools in psoriatic disease: a UK Biobank study
Authors: Hughes David M. , Yiu Zenas Z. N. , Zhao Sizheng Steven 
Published: January 2025

Abstract

Introduction
Risk prediction is important for preventing and managing cardiovascular disease (CVD). CVD risk prediction tools designed for the general population may be inaccurate in people with inflammatory diseases.

Objectives
To investigate the performance of four cardiovascular risk prediction tools (QRISK3, Framingham Risk Score, Reynolds Risk Score and SCORE) in psoriatic arthritis (PsA) and psoriasis. We also compare performance in participants with no inflammatory conditions and in people with rheumatoid arthritis (RA).

Methods
This research utilised the UK Biobank Resource. We identified participants with PsA, psoriasis and RA and calculated their cardiovascular risk using each risk tool. We assessed model calibration by comparing observed and predicted outcomes. Discrimination of 10-year risk prediction was assessed using time-dependent area under ROC curve (AUC), sensitivity, specificity, positive and negative predictive values.

Results
We included 769 individuals with PsA, 8062 with psoriasis and 4772 with RA when assessing the QRISK3 tool. Predictions for individuals with psoriasis were roughly as accurate as those with no inflammatory conditions with time-dependent AUC of 0.74 (95%CI, 0.72, 0.76) and of 0.74 (95%CI, 0.72, 0.77) respectively. In contrast, individuals with PsA obtained the least accurate predictions with an AUC of 0.70 (95%CI, 0.64, 0.76). Individuals with RA also obtained less accurate predictions with AUC of 0.72 (0.69,0.74). For the Framingham risk score, AUCs varied between 0.61 (95%CI, 0.55, 0.68) for participants with PsA and 0.71 (95%CI, 0.68, 0.74) for individuals with no inflammatory condition.

Conclusions
In general, CVD risk prediction accuracy was similar for individuals with psoriasis or no inflammatory condition, but lower for individuals with PsA or RA.

Key Points
• Cardiovascular disease risk prediction tools are inaccurate in patients with inflammatory conditions such as rheumatoid arthritis.
• CVD risk prediction was generally less accurate in people with psoriatic disease than the general population when using QRISK3, Framingham, Raynolds or SCORE tools.
• QRISK3 tended to achieve the most accurate prediction but was poorly calibrated by overestimating risk.
• QRISK3 generally overestimated risk; therefore, estimates may not need to be multiplied by 1.5 as recommended for inflammatory arthritis.
Histone lysine methyltransferases and their specific methylation marks show significant changes in mouse testes from young to older ages
Authors: Bilmez Yesim , Talibova Gunel , Tire Betul , Ozturk Saffet 
Published: January 2025

Abstract
Spermatogenesis is finely regulated by histone methylation, which is crucial for regulating gene expression and chromatin remodeling. Functional studies have demonstrated that the histone lysine methyltransferases (KMTs) SETD1B, CFP1, SETDB1, G9A, and SETD2 play pivotal roles in spermatogenesis through establishing the key histone methylation marks, H3K4me3, H3K9me2, H3K9me3, and H3K36me3, respectively. This study aimed to evaluate the spatiotemporal expression of these KMTs and methylation marks as well as senescence-associated β-galactosidase (β-GAL), transcriptional activity, and apoptosis rates in mouse testes during biological aging. In accordance with these purposes, the following groups of Balb/C mice were created: young (1- and 2-week-old), prepubertal (3- and 4-week-old), pubertal (5- and 6-week-old), postpubertal (16-, 18-, and 20-week-old), and aged (48-, 50-, and 52-week-old). The β-GAL staining gradually increased from the young to the aged groups (P < 0.01). The SETD1B, G9A, SETDB1, and SETD2 protein levels increased in spermatogonia, early and pachytene spermatocytes, and Sertoli cells of the aged group (P < 0.05). In contrast, CFP1 protein level decreased in spermatogonia, pachytene spermatocytes, round spermatids, and Sertoli cells towards the older ages (P < 0.05). Moreover, H3K4me3, H3K9me2, H3K9me3, and H3K36me3 levels increased in the aged group (P < 0.05). There was also a significant reduction in apoptosis rates in seminiferous tubules of the pubertal, postpubertal, and aged groups (P < 0.01). Consequently, accumulation of histone methylation marks due to increased expression of KMTs in spermatogenic and Sertoli cells during testicular aging may alter chromatin reprogramming and gene expression, contributing to age-related fertility loss.
Chirping across continents: variation in urban house sparrow (Passer domesticus) vocalizations across North America and Europe
Authors: González-García Fernando , Rega-Brodsky Christine C. , García-Arroyo Michelle , Bolaños Sittler Pablo , Escobar-Ibáñez Juan Fernando , García-Chávez Juan Hector , Hedblom Marcus , Heleno Ruben , Iankov Petar , Malmiga Gintaras , Martínez Fernández Alberto , McIntyre Nancy E. , Pavón-Jordán Diego , Ruvalcaba-Ortega Irene , MacGregor-Fors Ian 
Published: January 2025

Abstract
The house sparrow (Passer domesticus) is one of the most widespread invasive bird species, with numerous and dense populations established across urban-agricultural landscapes of North America. Although this species has been widely studied to identify the traits that explain its global ubiquity, descriptions of house sparrow acoustic features across its native and introduced range are limited in the literature. We recorded male house sparrow vocalizations from 13 cities across Europe and North America to quantify the structural features of its common “chirrup” vocalization. Although the basic structure and duration were consistent across the two geographic regions, the vocalizations differed in their minimum frequencies and bandwidth. In a post hoc analysis of 140 museum specimens, we found that European house sparrows had larger bills and bodies than those in North America. Thus, we propose that these frequency shifts could be a result of synergistic interactions between morphological differences, potential differences in ambient noise, acoustic overlap with other species within the soundscape, or other acoustic features of European and North American cities. House sparrows seem to be a good model for future bioacoustics studies, given their worldwide distribution and acoustic plasticity, to test hypotheses related to urbanization traits and invasion potential.
Timber harvesting was the most important factor driving changes in vegetation composition, as compared to climate and fire regime shifts, in the mixedwood temperate forests of Temiscamingue since AD 1830
Authors: Robles Daniela , Boulanger Yan , Pascual Jesus , Danneyrolles Victor , Bergeron Yves , Drobyshev Igor 
Published: January 2025

Abstract

Context
The vegetation composition of northeastern North American forests has significantly changed since pre-settlement times, with a marked reduction in conifer-dominated stands, taxonomic and functional diversity. These changes have been attributed to fire regime shifts, logging, and climate change.

Methods
In this study, we disentangled the individual effects of these drivers on the forest composition in southwestern Quebec from 1830 to 2000 by conducting retrospective modelling using the LANDIS-II forest landscape model. The model was run based on pre-settlement forest composition and fire history reconstructions, historical timber harvest records, and climate reanalysis data. We compared counterfactual scenarios excluding individual factors to a baseline historical scenario.

Results and Conclusions
Our results indicated that timber harvesting had the greatest impact on forest dynamics over the past centuries. In the absence of timber harvesting, pre-settlement species abundances were largely maintained, preserving key functional traits like fire and shade tolerance that contribute to ecosystem resilience. Increased fire activity during the settlement period contributed to the increase of early-successional aspen (Populus tremuloides), but timber harvesting played the dominant role. Fire exclusion had no influence on vegetation composition, suggesting mesophication unfolds over longer timescales than those captured in this study. Climate change, characterized by modest increases in temperature and precipitation, had a minor effect on vegetation shifts, as increased precipitation might have mitigated the adverse effects of rising temperatures. However, future climate change is projected to become a more significant driver of forest composition. These findings underscore the importance of forest restoration and continued research on past forest dynamics to better understand current and future changes.
Investigation of The Plasma Reaction Behavior of a Coke Oven Gas with Trace Oxygen in a Coaxial DBD Reactor
Authors: Nitsche Tim , Lohmann Heiko , Budt Marcus 
Published: January 2025

Abstract
The presented study shows experimental results with literature comparison for understanding of the oxygen removal in coke oven gas (COG) with plasma. The reaction of oxygen with the main COG components H2, CH4, and CO are investigated as well as the occurrence of potential side reactions as the splitting of CO2 and CH4. Further potential side reactions in the COG mixture known from literature as hydrogenation reactions are discussed in contrast to the observations of the experiments.
Utility of systemic staging in breast cancer patients with a positive sentinel lymph node biopsy
Authors: Harding Tim , O’Donoghue Patrick James , Boland Michael , Evoy Denis , McCartan Damien , Rutherford Claire , Prichard Ruth 
Published: January 2025

Abstract

Background
CT thorax, abdomen and pelvis (CT-TAP) remains the standard in the identification of metastatic disease in patients with newly diagnosed breast cancer. In patients with proven micro and macro axillary nodal metastasis, the optimal radiological technique remains controversial. A consensus on which patients with axillary nodal disease should receive radiological staging for distant disease and how this should be performed is not currently available. The aim of this study was to evaluate the yield from CT staging of the thorax, abdomen and pelvis (CT-TAP) in patients with proven nodal disease.

Methods
Patients diagnosed with invasive breast cancer with a positive sentinel lymph node biopsy (SLNB) and subsequent staging CT-TAP between 2013 and 2017 were identified. Patient demographics, clinicopathological characteristics, CT-TAP findings and further imaging requirements were documented.

Results
A total of 234 patients were identified. Of these, 164 (70%) were found to have macrometastasis and 70 (30%) to have micrometastasis or isolated tumour cells on SLNB. Within the macrometastasis cohort, abnormalities were noted on staging CT-TAP for 100 (61%) patients. Eighty of the 100 received follow-up assessment of abnormalities with 3 (2%) patients being diagnosed with distant metastatic disease. Within the micrometastasis group, abnormalities on CT-TAP staging were noted in 36 (52.1%) patients. Twenty-eight (40%) patients required further investigation and follow-up. No patient was found to have metastatic disease within this group.

Conclusion
Patients diagnosed with micrometastatic disease of the axilla following a sentinel lymph node biopsy do not require systemic staging as it fails to detect metastatic disease.
Frost forecasting through machine learning algorithms
Authors: Pérez Tárraga Javier , Castillo-Cara Manuel , Arias-Antúnez Enrique , Dujovne Diego 
Published: January 2025

Abstract
Agriculture continues to be one of the world’s main sources of income and provides great environmental, territorial and social value. However, frost is a recurring problem for farmers each year, representing a significant threat to agricultural production. In a matter of hours, temperatures below the freezing point can result in the loss of nearly the entire crop from a producer. In this article, we have analyzed and compared the application of a set of machine learning algorithms to predict the occurrence of frost events in the next 24 hours. The prediction process covers several challenges, such as data capture, processing, extracting each relevant parameter and finally building different prediction models to compared their performance. Furthermore, we have employed the Synthetic Minority Oversampling Technique (SMOTE) methodology to address the issue of imbalanced datasets, given the natural scarcity of frost events during the data sampling period. Our results show that among the machine learning algorithms we compared, the most efficient in terms of Recall score is K-Nearest Neighbor (KNN), while using the Area Under Curve (AUC) criteria, the highest score belongs to the Extra Trees algorithm, with 0.9909. Moreover, by applying the SMOTE balancing process, the AUC score of our models increased 13%, while the Recall score increased from 55% to 82%.
Determination of the performance of training algorithms and activation functions in meteorological drought index prediction with nonlinear autoregressive neural network
Authors: Gümüş Münevver Gizem , Çiftçi Hasan Çağatay , Gümüş Kutalmış 
Published: January 2025

Abstract
Analysis of long-term meteorological data is critical for monitoring climate trends and understanding the drought situation in a given region. In this study, monthly average precipitation data from the Niğde meteorological station in Turkey covering the period 1950–2020 were used. Within the scope of the study, seven different drought index methods were used for drought analysis, and the number and percentages of drought conditions were calculated according to these indices. For example, according to the Standardized Precipitation Index (SPI) method, the proportion of dry periods was determined as 16.2% and the proportion of humid periods as 83.8%. The Mann-Kendall trend analysis performed to determine the drought trends of the region revealed an increasing trend towards humidity in all indices (e.g., z = 1.299, p = 0.194 for SPI). In the study, 60-month drought forecasts covering the years 2020–2025 were realized using the Nonlinear Autoregressive Neural Network (NARNN) model, and the results were compared with the Autoregressive (AR) model. In the prediction performance analysis, the NARNN model showed superior prediction performance for all indices with lower RMSE values (e.g., NARNN RMSE = 0.977 for SPI; AR RMSE = 1.704). The prediction performances of different training algorithms and activation functions used in the NARNN model were analyzed. The best performance was obtained with the trainbr training algorithm and sigmoid activation function (e.g., RMSE = 0.997 for SPI). Based on these best parameters, more than 70% of the drought conditions during the 2020–2025 period were found to be normal or humid according to NARNN predictions. This study demonstrates the superiority of the NARNN model in nonlinear time series analyses and that it is a reliable tool, especially for future drought forecasts. In addition, comprehensive analyses with different index methods have significantly contributed to understanding the long-term drought trends in the Niğde region.
Compactness in Banach function spaces: Poincaré and Friedrichs inequalities
Authors: Bilalov Bilal , Mamedov Eminaga , Sezer Yonca , Nasibova Natavan 
Published: January 2025

Abstract
In this work, we study the relative compactness of subsets of separable subspaces

$$X_{s} \left( \Omega \right) $$

X
s

Ω

of so-called additive Banach function spaces

$$X \left( \Omega \right) $$

X

Ω

, which include the rearrangement-invariant spaces defined on the bounded domain

$$\Omega \subset R^{n}$$

Ω
⊂

R
n

. We choose

$$X_{s} \left( \Omega \right) $$

X
s

Ω

such that the infinitely differentiable functions are dense in it. Moreover, we define the Banach–Sobolev spaces

$$W_{X_{s} }^{m} \left( \Omega \right) $$

W

X
s

m

Ω

generated by the above subspaces and we study the compactness of embedding between such spaces. The obtained results are used to establish the equivalent norms on these spaces. These results allow us to prove the Poincaré and Friedrichs-type inequalities for such Sobolev spaces.
Profiling Sociodemographic Risk Factors and Clinical Outcomes of Women with Endometrial Cancer in Puerto Rico: The Central Role of Obesity and Obstetric Features
Authors: García-Irizarry Kimberly D. , Rojas-Brenes María E. , Oliveras-Torres José A. , Ortiz-Ortiz Camila N. , Cress William D. , Gordián Edna , Martínez Ricardo Gómez , Quintana-González Francisco J. , Escobar-Rodríguez Pedro F. , Muñoz-Antonia Teresita , Flores Idhaliz 
Published: January 2025

Abstract

Introduction
Incidence of endometrial cancer (EC) in Hispanic/Latina (H/L) women are higher compared to other race/ethnicities in the United States. EC is the third most common cancer and the fourth cause of cancer-related deaths in Puerto Rican women, yet demographic and clinical information is limited. High rates of EC risk factors such as obesity, diabetes mellitus type 2 (DM2) and hypertension (HTN) have been documented in the Puerto Rican population.

Objective
To describe the demographic, clinical history, lifestyle, obstetrical-gynecological, pathologic, and molecular profiles of women with EC predominantly from Southern/Central Puerto Rico.

Methods
We conducted a retrospective secondary analysis of data abstracted from the Puerto Rico Central Cancer Registry (PRCCR), self-administered questionnaires and medical records of EC cases. Descriptive statistics were conducted using SPSS V28 and RStudio.

Results
We identified 105 EC cases aged 28–82. The major risk factors were BMI ≥ 30 (72%), HTN (33%), and DM2 (20%). Endometrioid adenocarcinoma was the main histological tumor type (80%), of which 74% were Type I. Obesity and nulliparity were associated with younger age at diagnosis. Older age at diagnosis (> 65 y/o) was associated with more advanced disease.

Conclusions
This study defined the clinical-demographic profile of women with EC from Puerto Rico and identified risks factors that are associated with younger or older age at diagnosis.

Impact
Profiling the risk factors for EC may help improve diagnostic accuracy and clinical management and result in better outcomes for this under-served, under-researched cancer patient population.
Adsorptive removal of malachite green dye from aqueous solution using Cordia africana leaf as biosorbent
Authors: Teweldebrihan Meseret Dawit , Gnaro Mikiyas Abewaa , Dinka Megersa Olumana 
Published: January 2025

Abstract
An untreated biosorbent derived from the leaves of Cordia africana was utilized in this study for the first time to remove malachite green (MG) dye from aqueous solutions via batchwise adsorption. Comprehensive characterizations of the biosorbent were conducted, including Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), and determination of the pH point of zero charge (pHpzc). The adsorption process was investigated under varying operational conditions: biosorbent dosage (0.25–0.65 g/100 mL), contact time (25–50 min), initial pollutant concentration (15–45 mg/L), and solution pH (4–9). Kinetic and isothermal models were employed to evaluate the adsorption mechanism. Characterization revealed an amorphous, heterogeneous surface. The biosorbent achieved an impressive MG removal efficiency of 98.9%, with a maximum Langmuir adsorption capacity (Q

max
) of 6.25 mg/g, indicating a monolayer chemisorption process in agreement with Langmuir and pseudo-second-order kinetics models. This study highlights the cost-effectiveness and potential of Cordia africana leaf-based biosorbent as a sustainable and efficient solution for the decolorization of MG-laden industrial effluents, providing a pathway for practical, large-scale applications.
Tuning the Citizen Science Radio: Inclusion, Methodological Pluralism and 8 Billion Brains
Authors: Johnson Mark William , Varga Eliza 
Published: January 2025

Abstract
Science has always been driven by human consciousness in the context of an ambiguous environment. In modern times, the environment is characterised by sociotechnical complexities and uncertainty, rendering science fundamentally information-driven and statistically-informed, which focuses on uncertainty in contrast to the certainties of the enlightenment. In the context of this, and in the spirit of the point made initially by Popper that all people are scientific in their approach to everyday life, we must ask ‘whose uncertainties are not relevant to scientific inquiry?’ While inclusion has been a key feature of citizen science, there is a tendency for scientific control to remain with professional scientists, rather than in the hands of citizens. This paper is about new forms of coordination of citizen science activity which coordinate by tuning into citizen-level inquiry. Using the metaphor of a radio tuner, we suggest that tuning can take the form of identifying different levels of uncertainty, and selecting methods which allow for the deeper exploration of uncertainties and coordination of communities. We argue that the nineteenth century science of psychophysics alongside a topological view of scientific selection derived from Lewin’s social field theory, provides a theoretical foundation for the selection of appropriate methods in different circumstances. Ranking uncertainty with AI can steer flexible selection of methods and results, providing an inclusive science where analysis, synthesis, and experiment are left in the hands of communities and individuals.