bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting disease‐specific survival in patients undergoing active surveillance for papillary thyroid carcinoma
Authors: Nielsen Stanton , Kuchta Kristine , Huang Grace , Zuber Samuel , Holoubek Simon , Karcioglu Amanda , Khokar Amna , Prinz Richard , Moo‐Young Tricia 
Published: December 2024

AbstractBackgroundAmerican Thyroid Association guidelines support active surveillance (AS) for low‐risk papillary thyroid cancer (PTC). We developed a calculator to aid patient selection.MethodsFrom 2004 to 2020, 148,904 PTC patients were selected from the surveillance, epidemiology, and end results (SEER) database. Univariable and multivariable analysis evaluated patient and treatment characteristics. Patients were randomly allocated into training (80%) or validation sets (20%). Coefficients generated a mathematical model to predict 5‐ and 10‐year disease‐specific survival (DSS).ResultsThe mean DSS was 15.5 years with a 5‐ and 10‐year DSS of 99.3% and 98.6%, respectively. Age, sex, race, median household income (MHI), tumor size, and nodal status were significant on multivariable analysis (p ≤ 0.05) and included variables in our calculator. 2404 patients underwent non‐operative management (NOM) and were more likely older, male, higher MHI, larger tumor size, and less nodal positivity. Area under the curve (AUC) for 5‐ and 10‐year DSS were 0.83 and 0.81, respectively, for the training set and 0.81 and 0.79, respectively, for the validation set.Example65‐year‐old White female with a 0.8 cm PTC, cN0 with a MHI ≥ $75,000, had a 10‐year predicted DSS was 95.6% with NOM and 99.3% with surgery. Alternatively, changing the patient's race to Hispanic, the 10‐year predicted DSS was 94.1% with NOM and 99.0% with surgery.ConclusionsAs awareness of AS for PTC expands, it is important to consider objective data to guide informed decision making. This validated calculator is a useful tool to predict DSS for patients considering AS for PTC.
Sulfonation of IAA in Urtica eliminates its DR5 auxin activity
Authors: Supikova Klara , Žukauskaitė Asta , Kosinova Andrea , Pěnčík Aleš , De Diego Nuria , Spíchal Lukáš , Fellner Martin , Skorepova Katerina , Gruz Jiri 
Published: December 2024

Abstract

Key message

N-Sulfonated IAA was discovered as a novel auxin metabolite in Urtica where it is biosynthesized de novo utilizing inorganic sulfate. It showed no auxin activity in DR5::GUS assay, implying possible inactivation/storage mechanism.

Abstract
A novel auxin derivative, N-sulfoindole-3-acetic acid (IAA-N-SO3H, SIAA), was discovered in stinging nettle (Urtica dioica) among 116 sulfonated metabolites putatively identified by a semi-targeted UHPLC–QqTOF-MS analysis of 23 plant/algae/fungi species. These sulfometabolites were detected based on the presence of a neutral loss of sulfur trioxide, as indicated by the m/z difference of 79.9568 Da in the MS2 spectra. The structure of newly discovered SIAA was confirmed by synthesizing its standard and comparing retention time, m/z and MS2 spectrum with those of SIAA found in Urtica. To study its natural occurrence, 73 species in total were further analyzed by UHPLC–QqTOF-MS or targeted UHPLC–MS/MS method with a limit of detection of 244 fmol/g dry weight. However, SIAA was only detected in Urtica at a concentration of 13.906 ± 9.603 nmol/g dry weight. Its concentration was > 30 times higher than that of indole-3-acetic acid (IAA), and the SIAA/IAA ratio was further increased under different light conditions, especially in continuous blue light. In addition to SIAA, structurally similar metabolites, N-sulfoindole-3-lactic acid, 4-(sulfooxy)phenyllactic acid and 4-(sulfooxy)phenylacetic acid, were detected in Urtica for the first time. SIAA was biosynthesized from inorganic sulfate in seedlings, as confirmed by the incorporation of exogenous 34S-ammonium sulfate (1 mM and 10 mM). SIAA exhibited no auxin activity, as demonstrated by both the Arabidopsis DR5::GUS assay and the Arabidopsis phenotype analysis. Sulfonation of IAA may therefore be a mechanism for IAA deactivation and/or storage in Urtica, similar to sulfonation of the jasmonates in Arabidopsis.
Coronary calcium score and emphysema extent on different CT radiation dose protocols in lung cancer screening
Authors: Ledda Roberta Eufrasia , Milanese Gianluca , Balbi Maurizio , Sabia Federica , Valsecchi Camilla , Ruggirello Margherita , Ciuni Andrea , Tringali Giulia , Sverzellati Nicola , Marchianò Alfonso Vittorio , Pastorino Ugo 
Published: December 2024

Abstract
Objectives
To assess the consistency of automated measurements of coronary artery calcification (CAC) burden and emphysema extent on computed tomography (CT) images acquired with different radiation dose protocols in a lung cancer screening (LCS) population.

Materials and methods
The patient cohort comprised 361 consecutive screenees who underwent a low-dose CT (LDCT) scan and an ultra-low-dose CT (ULDCT) scan at an incident screening round. Exclusion criteria for CAC measurements were software failure and previous history of CVD, including coronary stenting, whereas for emphysema assessment, software failure only. CT images were retrospectively analyzed by a fully automated AI software for CAC scoring, using three predefined Agatston score categories (0–99, 100–399, and ≥ 400), and emphysema quantification, using the percentage of low attenuation areas (%LAA). Demographic and clinical data were obtained from the written questionnaire completed by each participant at the first visit. Agreement for CAC and %LAA categories was measured by the k-Cohen Index with Fleiss-Cohen weights (Kw) and Intraclass Correlation Coefficient (ICC) with 95% Confidence Interval (CI).

Results
An overlap of CAC strata was observed in 275/327 (84%) volunteers, with an almost perfect agreement (Kw = 0.86, 95% CI 0.82–0.90; ICC = 0.86, 95% CI 0.79–0.90), while an overlap of %LAA strata was found in 204/356 (57%) volunteers, with a moderate agreement (Kw = 0.57, 95% CI 0.51–0.63; ICC = 0.57, 95% CI 0.21–0.75).

Conclusion
Automated CAC quantification on ULDCT seems feasible, showing similar results to those obtained on LDCT, while the quantification of emphysema tended to be overestimated on ULDCT images.

Key Points
QuestionEvidence demonstrating that coronary artery calcification and emphysema can be automatedly quantified on ultra-low-dose chest CT is still awaited.
FindingsCoronary artery calcification and emphysema measurements were similar among different CT radiation dose protocols; their automated quantification is feasible on ultra-low-dose CT.
Clinical relevanceUltra-low-dose CT-based LCS might offer an opportunity to improve the secondary prevention of cardiovascular and respiratory diseases through automated quantification of both CAC burden and emphysema extent.
Individual differences in processing multisensory information predict presence in different virtual reality environments
Authors: Glenn Callum P. , Coxon Matthew 
Published: December 2024

AbstractOne of the most notable aspects of using a head mounted display is the feeling of being ‘within’ the digitally created virtual world. Technological advances across the fields of computer science and engineering have helped to increase this sense of presence. However, there remain wide variations between individuals, which are only just beginning to be captured at a theoretical level. One potential explanation for these individual differences may be how individuals process multisensory information. In this paper we detail two studies which explored whether performance on two different multisensory tasks (the pip and pop and a redundant signals task), predict some of these differences in self-reported presence. In study 1 (N = 32), clear correlations between the multisensory task (pip and pop) and presence scores were found using an underwater simulation. This provided the first indication that individuals that were positively influenced by illusory audiovisual conjunctions were also those that had the strongest sense of presence. Study 2 (N = 68) expanded upon these results, finding again that multisensory integration (within a redundant signals task) was related to self-reports of presence using a different VR experience. In addition, it was found that this relationship could be moderated by either providing a unisensory or multisensory VR experience. Together these results suggest that individual differences in the efficiency of multisensory integration may provide an additional level of explanation not currently accounted for within theoretical models of presence formation.
Beyond the S&P 500: examining the role of external volatilities in market forecasting
Authors: Korkusuz Burak 
Published: December 2024

AbstractThis study examines the impact of various exogenous volatilities on S&P 500 volatility using HAR-RV-type models. In this regard, a diverse range of exogenous volatilities—including assets, commodities, oil, gold, bonds, interest rates, the CBOE Volatility Index (VIX), and the Economic Policy Uncertainty (EPU) index—are incorporated into the Heterogenous Autoregressive (HAR) model. The exogenous volatilities are classified into three groups: European Market Information, U.S. Market Information, and U.S. Financial and Policy-Related Information. The study aims to determine which group of information contributes most effectively to forecasting S&P 500 stock market volatility. The results reveal several noteworthy points. First, the predictive accuracy of the baseline HAR-RV model is improved by incorporating exogenous explanatory variables. Second, the combination and the kitchen-sink approaches outperform models with single exogenous regressors, particularly for the U.S. Market Information group. Third, the U.S. Market Information group demonstrates superior predictive power compared to the other two groups, highlighting the interconnected nature of U.S. financial markets.
Environmentally Resistant Flax Fiber-Reinforced Composites for Aircraft Applications: Aviation Stress Tests with Optical and Mechanical Analyses
Authors: Schulte Sarina , Schäfer Hannes , Vogel Christoph , Shah Vineet , Kroll Stephen , Siebert-Raths Andrea 
Published: December 2024

AbstractFlax fiber-reinforced composites (FFRCs) must be resistant to environmental conditions to use them for external components in aviation. It was investigated how contact with typical aviation liquids, i.e. water, jet fuel and hydraulic oil, affects the optical and mechanical properties of twill fabric epoxy resin-based FFRCs. These influences were compared to the effect of UV weathering. Samples were exposed to these conditions for up to 28 days at RT. Uncoated samples with different fiber contents served as references and were compared with coated samples. A polyurethane/epoxy-based aircraft coating system and a partially biobased automotive interior coating as a more sustainable alternative were examined. The main damage for the uncoated samples was caused by UV weathering and water. UV light leads to photo-oxidation, causing material erosion. Water is absorbed by the hydrophilic flax fibers. Subsequent swelling leads to deformation and delamination. Thus, the damage was more severe for a higher fiber content. No effect could be demonstrated by immersion in jet fuel and hydraulic oil, as they are hardly absorbed by the fibers. Both coatings showed good protection against UV weathering and delayed water absorption. Nevertheless, mechanical damage was found for the FFRC covered with the fossil coating after 28 days of immersion in water. FFRC with an appropriate coating could therefore be suitable for use in aviation, but prolonged contact with water should be avoided. Protective measures should focus on preventing water uptake and UV irradiation, as these cause significantly more damage than jet fuel and hydraulic oil.
Big data analysis: examination of the relationship between candidates’ sociodemographic characteristics and performance in the UK’s Membership of the Royal College of Physicians Part 1 examination
Authors: Johnston Peter W. , Vieira Rute , Cameron Isobel M. , Kumwenda Ben , Walker Kim A. , Cleland Jennifer A. 
Published: December 2024

AbstractBig datasets and data analytics enable granular analyses examining group differences in performance. Our focus is on differential attainment (DA) in postgraduate College (Board) examinations. We asked: Are candidates’ sociodemographic characteristics associated with performance on the UK’s Membership of the Royal College of Physicians (MRCP) Part 1 after adjusting for medical school performance (MSP) and type of medical programme? This was a retrospective longitudinal cohort study of 6040 medical graduates with linked sociodemographic data in the UK Medical Education Database qualifying from a UK medical school (2012–2014) and sitting MRCP Part 1 before October 2019. Chi-squared tests established univariable associations with MRCP performance (pass/fail first sitting MRCP Part 1). Multivariable mixed-effects logistic regression identified independent explanatory factors of success, adjusted for medical school. The odds (95% CI) of passing MRCP Part 1 exams on first sitting were greater for men (OR = 1.61, CI 1.42–1.81, p < 0.001) and those on a graduate entry programme (OR = 1.44, 1.05–1.99, p < 0.001). The odds of passing were lower as age increases (OR = 0.87, 0.85–0.90, p < 0.001), for minority ethnic (OR = 0.61, CI 0.53–0.7, p < 0.001), and gateway to medicine (OR = 0.49, CI 0.27–0.90, p = 0.02) candidates. After adjusting for MSP, odds were greater for passing in men (OR = 1.62, CI 1.24–2.11, p < 0.001) and candidates with higher MSP (OR = 4.12, CI 3.40–4.96, p < 0.001). Our findings illustrate how performance on MRCP part 1 is associated with group-level social and educational factors. This DA may be due to aspects of the assessment itself, and/or the persistent nature of social and educational disadvantage.
Staying ahead of phishers: a review of recent advances and emerging methodologies in phishing detection
Authors: Kavya S. , Sumathi D. 
Published: December 2024

Abstract
The escalating threat of phishing attacks poses significant challenges to cybersecurity, necessitating innovative approaches for detection and mitigation. This paper addresses this need by presenting a comprehensive review of state-of-the-art methodologies for phishing detection, spanning traditional machine learning techniques to cutting-edge deep learning frameworks. The review encompasses a diverse range of methods, including list-based approaches, machine learning algorithms, graph-based analysis, deep learning models, network embedding techniques, and generative adversarial networks (GANs). Each method is meticulously scrutinized, highlighting its rationale, advantages, and empirical results. For instance, deep learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), demonstrate superior detection performance, leveraging their ability to extract complex patterns from phishing data. Ensemble learning techniques and GANs offer additional benefits by enhancing detection accuracy and resilience against adversarial attacks. The impact of this review extends beyond academic discourse, informing practitioners and policymakers about the evolving landscape of phishing detection. By elucidating the strengths and limitations of existing methods, this paper guides the development of more robust and effective cybersecurity solutions. Moreover, the insights gleaned from this review lay the groundwork for future research endeavors, such as integrating contextual information, user behavior analysis, and explainable AI techniques into phishing detection systems. Ultimately, this work contributes to the collective effort to fortify digital defenses against sophisticated phishing threats, safeguarding the integrity of online ecosystems.
Criteria definition for digital requirements using hesitant fuzzy linguistic terms sets: an application to the automotive industry
Authors: Fronte Pietro , Agell Núria , Torrens Marc , Mesa Diana 
Published: December 2024

AbstractManaging a portfolio of digital products is challenging, particularly in a context of limited economic resources and workforce. Therefore, prioritization of activities and new developments is crucial. In Software Development environment, almost all well-known prioritization techniques are based on experts’ knowledge and opinion, leaving little room for a data-driven, objective approach. In this paper, we propose a methodology that adopts the Delphi framework and Hesitant Fuzzy Linguistic Term Sets for collecting experts’ opinions, evaluating perceived importance, and computing group consensus. The objective is to provide a framework to define a group-consensual set of relevant criteria that would represent the basis for a data-driven prioritization process for digital requirements. Implementation and results from a real case application in a European automotive company are presented to understand the relevance of criteria and suggest their inclusion or exclusion for prioritization purposes.
Influence of antibody–drug conjugate cleavability, drug-to-antibody ratio, and free payload concentration on systemic toxicities: A systematic review and meta-analysis
Authors: Tang Shou-Ching , Wynn Carrie , Le Tran , McCandless Martin , Zhang Yunxi , Patel Ritesh , Maihle Nita , Hillegass William 
Published: December 2024

AbstractWhile in theory antibody drug conjugates (ADCs) deliver high-dose chemotherapy directly to target cells, numerous side effects are observed in clinical practice. We sought to determine the effect of linker design (cleavable versus non-cleavable), drug-to-antibody ratio (DAR), and free payload concentration on systemic toxicity. Two systematic reviews were performed via PubMed search of clinical trials published between January 1998—July 2022. Eligible studies: (1) clinical trial for cancer therapy in adults, (2) ≥ 1 study arm included a single-agent ADC, (3) ADC used was commercially available/FDA-approved. Data was extracted and pooled using generalized linear mixed effects logistic models. 40 clinical trials involving 7,879 patients from 11 ADCs, including 9 ADCs with cleavable linkers (N = 2,985) and 2 with non-cleavable linkers (N = 4,894), were included. Significantly more composite adverse events (AEs) ≥ grade 3 occurred in patients in the cleavable linkers arm (47%) compared with the non-cleavable arm (34%). When adjusted for DAR, for grade ≥ 3 toxicities, non-cleavable linkers remained independently associated with lower toxicity for any AE (p = 0.002). Higher DAR was significantly associated with higher probability of grade ≥ 3 toxicity for any AE. There was also a significant interaction between cleavability status and DAR for any AE (p = 0.002). Finally, higher measured systemic free payload concentrations were significantly associated with higher DARs (p = 0.043). Our results support the hypothesis that ADCs with cleavable linkers result in premature payload release, leading to increased systemic free payload concentrations and associated toxicities. This may help to inform future ADC design and rational clinical application.
Constructing understanding: on the constructional information encoded in large language models
Authors: Bonial Claire , Tayyar Madabushi Harish 
Published: December 2024

AbstractWe review research related to both Construction Grammar (CxG) and Natural Language Processing showing that recent advances in probing Large Language Models (LLMs) for certain types of linguistic knowledge align with the tenets of CxG. However, our survey leads us to hypothesize that LLM constructional information may be limited to the constructions within the lower levels of postulated taxonomical “constructicons” enumerating a particular language’s constructions. Specifically, probing studies show that the constructions at the lower levels of the taxonomy, which are more substantive constructions with fixed elements corresponding to frequently used words within that construction, are a type of linguistic information accessible to LLMs. In contrast, more general, abstract constructions with schematic slots that can be filled by a variety of different words are not included in the linguistic knowledge of LLMs. We test this hypothesis on a collection of 10 distinct constructions, each of which is exhibited in 50 or more corpus instances. Our experimental results strongly support our hypothesis and lead us to conclude that, in order for LLMs to generalize to the point where purely schematic constructions can be recognized regardless of the frequency of the instantiating words (as psycholinguistic experimentation has shown people can), additional semantic resources are needed to make explicit the semantic role of the schematic slot. To ensure transparency and reproducibility, we publicly release our experimental data, including the prompts used with the model.
Historical and future winter chill for temperate fruit and nut trees in Afghanistan
Authors: Shinwari Atifullah , Caspersen Lars , Schiffers Katja , Luedeling Eike 
Published: December 2024

Abstract
Temperate fruit trees require exposure to chill and heat conditions to overcome the dormant period in winter and resume growth in spring. Rising temperatures due to climate change have already impacted winter chill accumulation in horticulturally vital growing regions worldwide. Afghanistan’s intra-regional differences make the country favorable for producing a wide range of fruits and nuts, which constitute approximately 30% of the country’s total export earnings. However, expected future temperature increases may be detrimental to the trees’ ability to fulfill their chilling requirements. To quantify this risk, we computed and mapped historical and future chill accumulation in Afghanistan. For this purpose, we used long-term daily temperature data from 1980 to 2020 for 51 hydrometeorological stations across the country. Based on the temperature data, we produced four future Shared Socioeconomic Pathway (SSP) scenarios (SSP126, SSP245, SSP370, and SSP585) for five General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We used the RMAWGEN weather generator to produce 100 synthetic realizations of weather records for historical (1980, 1990, 2000, 2010, and 2020) and future conditions (2035–2065 and 2070–2100). We quantified winter chill using the Dynamic Model. Additionally, we computed Safe Winter Chill (SWC), which is defined as the level of chill that is expected to be exceeded in 90% of years. We find that SWC has decreased in historical scenarios in the low-lying regions mainly in the eastern, southern, and parts of the northern regions, and is projected to further decrease in the future. This reveals a possible future chill risk for high chill-requiring cultivars of different fruit and nut species, including apricot, peach, plum, pistachio and almond, in these regions. In contrast, we record an increase in SWC in the northern and central regions, suggesting these regions as potentially favorable for high-chill species in the future. Our findings support fruit and nut growers in Afghanistan in adapting their orchards to match chill requirements of species and cultivars to the expected future winter chill.