bluuebunny/crossref_metadata_2025_split huggingface dataset:
First record of preying behaviour of Achelous spinimanus
Authors: da Silva Alexandre R. , Kassuga Alexandre D. 
Published: November 2024

AbstractAchelous spinimanus, a species of swimming crab found along the Western Atlantic from the USA to Brazil, inhabits coastal areas up to 90 m deep across various substrates. While these crabs are known to be omnivorous, the extent of their predatory behaviour remains unclear. This note documents the first record of A. spinimanus actively preying on live fish. In the observed interaction, the fish was still alive and moving its operculum and mouth while being eaten. The observation was made during a night dive at Ilha dos Porcos, Arraial do Cabo, Brazil, where a crab was seen preying on a live Malacoctenus zaluari. The behaviour suggests that A. spinimanus may employ sit‐and‐wait strategy, utilizing its strong chelipeds for capturing prey. Such records are crucial for understanding the trophic dynamics and ecological roles of marine species, emphasizing the importance of both scientific and citizen science contributions to biodiversity knowledge. This finding also underscores the importance of further research on the feeding and behavioural ecology of portunids.
Red cell specifications for blood group matching in patients with haemoglobinopathies: An updated systematic review and clinical practice guideline from the International Collaboration for Transfusion Medicine Guidelines
Authors: Wolf Julia , Blais‐Normandin Isabelle , Bathla Aarti , Keshavarz Homa , Chou Stella T. , Al‐Riyami Arwa Z. , Josephson Cassandra D. , Massey Edwin , Hume Heather A. , Pendergrast Jacob , Denomme Gregory , Grubovic Rastvorceva Rada M. , Trompeter Sara , Stanworth Simon J. ,   the International Collaboration for Transfusion Medicine Guidelines (ICTMG)
Published: November 2024

SummaryRed blood cell (RBC) antigen matching beyond ABO and RhD is commonly recommended for patients with sickle cell disease (SCD) and thalassaemia. We present an updated systematic literature review to inform evidence‐based guidelines on RBC matching. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool was used to develop recommendations. Six new observational studies (4 prospective, 2 retrospective) were identified. The six studies reported on 583 patients in total, including cross‐over designs, with sample sizes from 10 to 343. Studies were heterogeneous, utilising varying degrees of RBC matching and different definitions for ‘extended’ matching. All reported on alloimmunisation. One study reported on molecular matching. The reported prevalence of alloimmunisation using limited matching was 0%–50% and with extended matching was 0%–24%. Eighty‐two patients were alloimmunised before study entry. The risk of bias across studies was moderate to critical. The guideline panel recommends that ABO, RhDCcEe, and K‐compatible RBCs are selected for individuals with SCD and thalassaemia, even in the absence of alloantibodies, and that RBCs which are antigen‐negative to already existing clinically significant antibodies are chosen. There is a need for comparative research to define the benefit, impact, cost‐effectiveness, and feasibility of extended RBC matching strategies to prevent alloimmunisation.
Methodology and clinical utility of longitudinal UBA1 tracking in VEXAS syndrome
Authors: Gurnari Carmelo , Galossi Elisa , Lumia Eleonora , Piciocchi Alfonso , Divona Mariadomenica , Casciani Elisa , Romano Francesca , Diral Elisa , Tomelleri Alessandro , Caroni Federico , Vitale Antonio , Bergonzi Gregorio Maria , Condorelli Annalisa , Battipaglia Giorgia , Morsia Erika , Crisà Elena , Triggianese Paola , Savi Arianna , Cardamone Chiara , Dragani Matteo , Rivoli Giulia , Pilo Federica , Firinu Davide , Plebani Sara , D'Agostino Francesco , D'Ambrosio Alessandro , Sockel Katja , Papayannidis Cristina , Salmoiraghi Silvia , Pane Fabrizio , Bocchia Monica , Cantarini Luca , Frigeni Marco , Campochiaro Corrado , Dagna Lorenzo , Greco Raffaella , Ciceri Fabio , Spinelli Orietta , Thiede Christian , Voso Maria Teresa 
Published: November 2024

SummaryVacuoles, E1 enzyme, X‐linked, autoinflammatory, somatic (VEXAS) is a haemato‐inflammatory syndrome genetically defined by somatic mutations in the X‐linked UBA1 gene, typically Val/Thr/Leu substitutions at the Met41 hotspot. Clinical manifestations are heterogeneous and refractory to most haemato‐rheumatological treatments. To date, no guidelines exist for the management of VEXAS, and scarce is the evidence on methodology and clinical significance of longitudinal UBA1 clonal burden evaluation upon therapy. Here, we validated a method to quantify UBA1 clonal burden and explored its applicability in patients with VEXAS. Given the different treatment interactions, droplet digital polymerase chain reaction (ddPCR) may allow for informed therapeutic decisions and implementation of personalized strategies.
The design of external reference pricing schemes and the choice of reference countries and pricing rules
Authors: Birg Laura 
Published: November 2024

AbstractExternal reference pricing imposes a price cap for drugs based on prices in other countries. I study the choice of reference countries and pricing rules in a three‐country framework. If the manufacturer sells to all three countries, the minimum price rule yields the lowest drug price. If the referencing country is sufficiently large, the manufacturer may not export to reference countries under the minimum price rule. External reference pricing creates the incentive for the reference countries also to adopt external reference pricing. Thus, external reference pricing results in price convergence.
Mother–child collaboration in an Indigenous community: Changing and enduring across generations
Authors: Rogoff Barbara , Aceves‐Azuara Itzel 
Published: November 2024

AbstractChanges in family life related to globalization may include reduction in the collaborativeness observed in many Indigenous American communities. The present study examined longitudinal changes and continuities in collaboration in a Guatemalan Maya community experiencing rapid globalization. Fluid collaboration was widespread 3 decades ago among triads of mothers and 1‐ to 6‐year‐olds in 24 Mayan families exploring novel objects during home visits (Dayton et al., 2022). However, in the “same” situation 30 years later, 22 mother–child triads of their relatives spent half as much time in collaboration among all three people. This aligns with globalizing changes and with the pattern of Dayton et al.'s middle‐class European American families. Nonetheless, the Mayan families maintained harmonious interactions, in line with preserving important cultural values.
Horseradish peroxidase‐catalysed coloration of silk and cotton fabrics with phenols
Authors: Baek Na‐won , Lee Shin‐hee 
Published: November 2024

AbstractEnzymatic dyeing is an environmentally friendly and energy‐efficient dyeing method conducted at low temperatures, making it an important option for sustainable dyeing processing technology. This study investigated the enzymatic dyeing of cotton and silk fabrics using six phenolic monomers (catechol, hydroquinone, 2‐aminophenol, 4‐aminophenol, 1,4‐phenylenediamine and 2,5‐diaminobenzenesulphonic acid) via oxidative polymerisation catalysed by horseradish peroxidase (HRP). The research explored the colouring mechanism, functional attributes and dyeability of the fabrics. The polymerisation mechanism of the polymer was elucidated through liquid chromatography–tandem mass spectrometry, while the functional and morphological characteristics of the dyed fabric were examined via Fourier transform–infrared spectroscopy, thermogravimetric analysis and scanning electron microscopy imaging. The dyed fabric underwent dyeability assessments, including colour depth analysis and various fastness tests. Under mild reaction conditions, nearly all the phenolic monomers successfully dyed both the silk and cotton fabrics using HRP. The dyed fabrics demonstrated enhanced thermal stability and dyeability. However, the cotton fabrics exhibited worse dyeability and fastness than the silk fabrics, with noticeable stains on their surfaces when dyed with certain phenols. These findings underscore the suitability of enzymatic oxidative dyeing for protein fibres over vegetable fibres, as well as the importance of tailoring enzymatic dyeing processes for vegetable fibres.
Utilization of the Liver‐First Approach in Combined Lung‐Liver Transplant Provides Comparable Outcomes to the Traditional Lung‐First Approach: A UNOS Study
Authors: Guo Yizhan , Ryan John , Chan Ernest , Furukawa Masashi , Hage Chadi A. , Sanchez Pablo G. 
Published: November 2024

ABSTRACTMultiorgan transplantation is offered to a selected group of patients every year. The sequence in which organs are transplanted depends on ischemic time graft tolerance and the sickest organ first strategy. In the case of Lung‐Liver transplantation, lung allografts are usually implanted before the liver. There are some theoretical advantages to a liver‐first strategy and a few centers have reported a series of cases that spark a growing interest in the feasibility and potential benefits of this approach. In this contemporary study of the United Network for Organ Sharing (UNOS) database, we evaluate and report outcomes using either strategy.
Diabetes distress and depression in type 2 diabetes. A cross‐sectional study in 18,000 individuals in the Central Denmark region
Authors: Dalsgaard Else‐Marie , Graversen Susanne Boel , Bjerg Lasse , Sandbaek Annelli , Laurberg Tinne 
Published: November 2024

AbstractAimsType 2 diabetes is linked to psychological distress and a doubled risk of depression. This study aims to characterize individuals with type 2 diabetes experiencing diabetes distress and/or depression in relation to lifestyle and metabolic outcomes.MethodsA population‐based survey in 2020 targeted individuals with type 2 diabetes (aged 18–75 years) in the Central Denmark Region. This cross‐sectional study assessed diabetes distress (using Problem‐Area‐in‐Diabetes‐scale) and depression (via hospital diagnosis and prescribed medication) as exposures. Logistic regression, adjusting for potential confounders, compared exposed and non‐exposed groups on lifestyle habits, metabolic factors and medication usage related to cardio‐metabolic risks.ResultsOf 18,222 respondents with type 2 diabetes (46% response rate), 11% had depression, 14% had diabetes distress and 4% had both. Compared to those with neither condition, those with depression were more often smokers (OR: 2.0, 95% CI: 1.8; 2.3) and sedentary in leisure time (OR: 2.0, 95% CI: 1.8; 2.2). Diabetes distress was associated with elevated HbA1c (OR: 1.8, 95% CI: 1.5; 2.0) and treatment with insulin (OR: 1.8, 95% CI: 1.6; 2.0). Half with diabetes distress displayed stable blood glucose levels. Those with both conditions had a higher risk of sedentary behaviour (OR: 2.7, 95% CI: 2.3; 3.2), clinical insomnia (OR: 6.5, 95% CI: 5.5; 7.7) and low self‐rated health (OR: 7.5, 95% CI: 6.3; 9.0) than those with either psychological condition in isolation.ConclusionsThis study emphasizes the importance of recognizing distinct features and risk factors associated with diabetes distress and depression in individuals with type 2 diabetes. Tailored care strategies for comorbid mental health issues are crucial for comprehensive management.
Improving survey quality using paradata: Lessons from a field survey in India
Authors: Goel Deepti , Abraham Rosa 
Published: November 2024

AbstractMotivationWhen collecting evidence from the field, the quality of the data determines the reliability of the analysis. When data are collected in the field by enumerators, the latter's performance needs to be monitored to avoid errant behaviour that could compromise data quality.PurposeWe show how paradata on the process of data collection itself can improve enumerator performance, using a household survey in India as a case study.Approach and methodsWe conducted action research to improve data quality in the India Working Study conducted in early 2020 in Karnataka and Rajasthan. We designed indicators (flags) from the paradata to mark potential deviant enumerator behaviour in the early stages of the survey. Flagged enumerators were contacted by supervisors who provided constructive feedback. We then measured the performance of the flagged enumerators over the remainder of the survey.We were able to benchmark specific groups of enumerators facing similar field conditions, namely location and gender of respondents. This allowed us to compare enumerators to a subset of their peers, rather than the entire set of enumerators.FindingsOur feedback improved enumerator behaviour in the field: flagged enumerators subsequently spent more time on a core module of the questionnaire.Policy implicationsIn any survey, two objectives compete: completing a fixed number of interviews per day to reduce costs versus enumerators spending enough time with each respondent to collect meaningful data. To strike a balance between these competing demands, we recommend tracking three paradata indicators: count of completed interviews; average time per completed interview; and ratio of completed to initiated interviews.We recommend using paradata to improve the quality of data when surveying, thereby reducing standard errors for estimates based on the data and leading to more reliable analysis.
Diagnostic Window Prior to a Haematological Cancer Diagnosis and the Association With Patient Pathways: A Nationwide Register‐Based Cohort Study on Healthcare Utilization in Denmark
Authors: Virgilsen Line Flytkjær , Vedsted Peter , Jensen Henry , Frederiksen Henrik , El‐Galaly Tarec Christoffer , Rasmussen Linda Aagaard 
Published: November 2024

ABSTRACTObjectivesThis study investigated healthcare utilisation in general practice and hospitals in the 2 years preceding a diagnosis of haematological cancer and the association with patient pathways.MethodsThe nationwide register‐based cohort study included 12 994 patients diagnosed with leukaemia, multiple myeloma and lymphoma in 2014–2018 and 10 matched references. Patient pathways were analysed in unplanned routes (acute admission up to 1 month's prior diagnosis) and elective routes (other routes, e.g., cancer patient pathways).ResultsFemale patients in unplanned diagnostic pathways had more contacts to general practice from 19 months before the diagnosis compared to their matched references; with IRR increasing from 1.14 (95% confidence interval (CI) 1.05–1.24) to 2.27 (95% CI 2.13–2.41) at 30–60 days before the diagnosis. Female patients had more point‐of‐care tests, hospital contacts and radiological investigations at 17, 24 and 17 months, respectively, before diagnosis compared to their references. Similar patterns were seen for male patients, although with a later onset of increase. No healthcare use variations were seen between patients diagnosed in unplanned versus elective pathways.ConclusionsIncreased healthcare utilisation was seen in general practice and hospitals up to 24 months preceding a diagnosis, which may indicate a diagnostic window for detecting haematological cancer earlier.
High‐dose folic acid use and cancer risk in women who have given birth: A register‐based cohort study
Authors: Vegrim Håkon Magne , Dreier Julie Werenberg , Igland Jannicke , Alvestad Silje , Gilhus Nils Erik , Gissler Mika , Leinonen Maarit K. , Tomson Torbjörn , Zoega Helga , Christensen Jakob , Bjørk Marte‐Helene 
Published: November 2024

AbstractObjectiveThis study was undertaken to study whether high‐dose folic acid (>1 mg daily) use is associated with an increased risk of cancer in all women who have given birth and in women with epilepsy. High‐dose folic acid supplementation during pregnancy has been linked to increased cancer risk in children born to mothers with epilepsy.MethodsWe identified women with their first pregnancy in Denmark (1997–2017), Norway (2005–2017), and Sweden (2006–2017) using medical birth registers, linking individual data across nationwide health registers and statistical agencies. Exposure was defined as filled prescriptions for high‐dose folic acid, considered time‐varyingly. The primary outcome was the first malignant cancer diagnosis. Hazard ratios (HRs) of cancer after high‐dose folic acid exposure were estimated using Cox proportional hazard models with 95% confidence intervals (CIs), adjusted for confounders including antiseizure medication (ASM) use, and stratified by maternal epilepsy diagnosis. A 6‐month time lag was applied, as cancer is unlikely to develop immediately.ResultsWith up to 21 years of follow‐up, we identified 1 465 785 women who gave birth, including 64 485 (4.4%) exposed to high‐dose folic acid. In the exposed group, 755 cancer cases were observed (208 per 100 000 person‐years, 95% CI = 193.8–223.5), compared with 18 702 cases in the unexposed group (164 per 100 000 person‐years, 95% CI = 161.5–166.2), yielding a 20% increased cancer risk overall (adjusted HR = 1.2, 95% CI = 1.1–1.2). This risk was attenuated after the 6‐month lag analysis (adjusted HR = 1.1, 95% CI = 1.04–1.2). The risk for non‐Hodgkin lymphoma was increased in all analyses (n = 28, adjusted HR = 2.0, 95% CI = 1.3–2.9). The association between high‐dose folic acid use and overall cancer risk was similar in those with epilepsy regardless of ASM use (adjusted HR = 1.3, 95% CI = 1.0–1.8).SignificanceHigh‐dose folic acid use was associated with increased overall cancer risk in women who have given birth, with a consistent association with non‐Hodgkin lymphoma, including those with epilepsy, regardless of ASM use.
A Social Group Chatbot System by Multiple Topics Tracking and Atkinson‐Shiffrin Memory Model Using AI Agents Collaboration
Authors: Zhang Guoshuai , Wu Jiaji , Jeon Gwanggil , Wang Penghui 
Published: November 2024

ABSTRACTThe widespread use of Internet has accelerated the explosive growth of data, which in turn leads to information overload and information confusion. This makes it difficult for us to communicate effectively in social groups, thereby intensifying the demands for emotional companionship. Therefore, we propose a novel social group chatting framework based on Large Language Model (LLM) powered multiple autonomous agents collaboration in this article. Specifically, BERTopic is used to extract topics from history chatting content for each social group everyday, and then multiple topics tracking is realised through multi‐level association by adaptive time sliding‐window mechanism and optimal matching. Furthermore, we use topic tracking architecture and prompts to design and implement an AI Chatbot system with different characters that can conduct natural language conversations with users in online social group. LLM, as the controller and coordinator of the whole AI Chatbot for sub‐tasks, allows different AI Agents to autonomously decide whether to participate in current topic, how to generate response, and whether to propose a new topic. Each AI Agent has their own multi‐store memory system based on the Atkinson‐Shiffrin model. Finally, we construct a verification environment based on online game that is consistent with real society. Subjective and objective evaluation methods were deployed to perform qualitative and quantitative analyses to demonstrate the performance of our AI Chatbot system.
Dragon Boat Optimization: A Meta‐Heuristic for Intelligent Systems
Authors: Li Xiang , Lan Long , Lahza Husam , Yang Shaowu , Wang Shuihua , Yang Wenjing , Liu Hengzhu , Zhang Yudong 
Published: November 2024

ABSTRACTDragon boat racing, a popular aquatic folklore team sport, is traditionally held during the Dragon Boat Festival. Inspired by this event, we propose a novel human‐based meta‐heuristic algorithm called dragon boat optimization (DBO) in this paper. It models the unique behaviours of each crew member on the dragon boat during the race by introducing social psychology mechanisms (social loafing, social incentive). Throughout this process, the focus is on the interaction and collaboration among the crew members, as well as their decision‐making in various situations. During each iteration, DBO implements different state updating strategies. By accurately modelling the crew's behaviour and employing adaptive state update strategies, DBO consistently achieves high optimization performance, as validated by comprehensive testing on 29 benchmark functions and 2 structural design problems. Experimental results indicate that DBO outperforms 7 and 16 state‐of‐the‐art meta‐heuristic algorithms across these test functions and problems, respectively.
Enhancing Psychologists' Understanding Through Explainable Deep Learning Framework for ADHD Diagnosis
Authors: Rehman Abdul , Lin Jerry Chun‐Wei , Heldal Ilona 
Published: November 2024

ABSTRACTAttention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that is challenging to diagnose and requires advanced approaches for reliable and transparent identification and classification. It is characterised by a pattern of inattention, hyperactivity and impulsivity that is more severe and more frequent than in individuals with a comparable level of development. In this paper, an explainable framework based on a fine‐tuned hybrid Deep Neural Network (DNN) and Recurrent Neural Network (RNN) called HyExDNN‐RNN model is proposed for ADHD detection, multi‐class categorization and decision interpretation. This framework not only detects ADHD but also provides interpretable insights into the diagnostic process so that psychologists can better understand and trust the results of the diagnosis. We use the Pearson correlation coefficient for optimal feature selection and machine and deep learning models for experimental analysis and comparison. We use a standardised technique for feature reduction, model selection and interpretation to accurately determine the diagnosis rate and ensure the interpretability of the proposed framework. Our framework provided excellent results on binary classification, with HyExDNN‐RNN achieving an F1‐score of 99% and 94.2% on multi‐class categorization. XAI approaches, in particular SHapley Additive exPlanations (SHAP) and Permutation Feature Importance (PFI), provided important insights into the importance of features and the decision logic of models. By combining AI with human expertise, we aim to bridge the gap between advanced computational techniques and practical psychological applications. These results demonstrate the potential of our framework to assist in ADHD diagnosis and interpretation.