bluuebunny/crossref_metadata_2025_split huggingface dataset:
Canadian Kidney Transplant Professionals’ Perspectives on Precision Medicine and Molecular Matching in Kidney Allocation
Authors: Affdal Aliya , Ballesteros Fabian , Malo Marie-Françoise , Sancho Carina , Cochran-Mavrikakis Savannah-Lou , Bryan Stirling , Keown Paul , Sapir-Pichhadze Ruth , Fortin Marie-Chantal 
Published: December 2023

Background.
Antibody-mediated rejection is an important cause of kidney transplant loss. A new strategy requiring application of precision medicine tools in transplantation considers molecular compatibility between donors and recipients and holds the promise of improved immunologic risk, preventing rejection and premature graft loss. The objective of this study was to gather Canadian transplant professionals’ perspectives on molecular compatibility in kidney transplantation.

Methods.
Seventeen Canadian transplant professionals (14 nephrologists, 2 nurses, and 1 surgeon) participated in semistructured interviews in 2021. The interviews were digitally recorded, transcribed, and analyzed using the qualitative description approach.

Results.
Participants identified fair access to transplantation as the most important principle in kidney allocation. Molecular compatibility was viewed as a promising innovation. However, participants were concerned about increased waiting times, negative impact on some patients, and potential problems related to the adequacy of information explaining this new technology. To mitigate the challenges associated with molecular matching, participants suggested integrating a maximum waiting time for molecular-matched kidneys and expanding the program nationally/internationally.

Conclusions.
Molecular matching in kidney transplantation is viewed as a promising technology for decreasing the incidence of antibody-mediated rejection and improving graft survival. Further studies are needed to determine how to ethically integrate this technology into the kidney allocation algorithm.
Trabecular Bone Score Improves Early After Successful Kidney Transplantation Irrespective of Antiresorptive Therapy and Changes in Bone Mineral Density
Authors: Strømmen Ruth C. , Godang Kristin , Finnes Trine E. , Smerud Knut T. , Reisæter Anna V. , Hartmann Anders , Åsberg Anders , Bollerslev Jens , Pihlstrøm Hege K. 
Published: December 2023

Background.
Trabecular bone score (TBS) is a new tool to assess trabecular bone microarchitecture based on standard dual-energy x-ray absorptiometry (DXA) of lumbar spine images. TBS may be important to assess bone quality and fracture susceptibility in kidney transplant recipients (KTRs). This study aimed to investigate the effect of different bone therapies on TBS in KTRs.

Methods.
We reanalyzed DXA scans to assess TBS in 121 de novo KTRs at baseline, 10 wk, and 1 y. This cohort, between 2007 and 2009, participated in a randomized, placebo-controlled trial evaluating the effect of ibandronate versus placebo in addition to vitamin D and calcium.

Results.
Although bone mineral density (BMD) Z scores showed a subtle decrease in the first weeks, TBS Z scores increased from baseline to 10 wk for both treatment groups, followed by a slight decline at 12 mo. When comparing treatment groups and adjusting for baseline TBS, there were no differences found in TBS at 12 mo (P = 0.419). Correlation between TBS and BMD at baseline was weak (Spearman’s ρ = 0.234, P = 0.010), and change in TBS was not correlated with changes in lumbar spine BMD in either of the groups (ρ = 0.003, P = 0.973).

Conclusions.
Treatment with ibandronate or vitamin D and calcium did not affect bone quality as measured by TBS in de novo KTRs, but TBS increased early, irrespective of intervention. Changes in TBS and BMD during the study period were not correlated, indicating that these measurements reflect different aspects of bone integrity. TBS may complement BMD assessment in identifying KTRs with a high fracture risk.
Order and change in art: towards an active inference account of aesthetic experience
Authors: Van de Cruys Sander , Frascaroli Jacopo , Friston Karl 
Published: December 2023

How to account for the power that art holds over us? Why do artworks touch us deeply, consoling, transforming or invigorating us in the process? In this paper, we argue that an answer to this question might emerge from a fecund framework in cognitive science known as predictive processing (a.k.a. active inference). We unpack how this approach connects sense-making and aesthetic experiences through the idea of an ‘epistemic arc’, consisting of three parts (curiosity, epistemic action and aha experiences), which we cast as aspects of active inference. We then show how epistemic arcs are built and sustained by artworks to provide us with those satisfying experiences that we tend to call ‘aesthetic’. Next, we defuse two key objections to this approach; namely, that it places undue emphasis on the cognitive component of our aesthetic encounters—at the expense of affective aspects—and on closure and uncertainty minimization (order)—at the expense of openness and lingering uncertainty (change). We show that the approach offers crucial resources to account for the open-ended, free and playful behaviour inherent in aesthetic experiences. The upshot is a promising but deflationary approach, both philosophically informed and psychologically sound, that opens new empirical avenues for understanding our aesthetic encounters.This article is part of the theme issue ‘Art, aesthetics and predictive processing: theoretical and empirical perspectives’.
Metaphors or mechanism? Predictive coding and a (brief) history of empirical study of the arts
Authors: Leder Helmut , Pelowski Matthew 
Published: December 2023

Predictive processing (PP) offers an intriguing approach to perception, cognition, but also to appreciation of the arts. It does this by positing both a theoretical basis—one might say a ‘metaphor’—for how we engage and respond, placing emphasis on mismatches rather than fluent overlap between schema and environment. Even more, it holds the promise for translating metaphor into neurobiological bases, suggesting a means for considering mechanisms—from basic perceptions to possibly even our complex, aesthetic experiences. However, while we share the excitement of this promise, the history of empirical or psychological aesthetics is also permeated by metaphors that have progressed our understanding but which also tend to elude translation into concrete, mechanistic operationalization—a challenge that can also be made to PP. We briefly consider this difficulty of convincing implementation of PP via a brief historical outline of some developments in the psychological study of aesthetics and art in order to show how these ideas have often anticipated PP but also how they have remained at the level of rather metaphorical and difficult-to-measure concepts. Although theoretical in scope, we hope that this commentary will spur researchers to reflect on PP with the aim of translating metaphorical explanations into well-defined mechanisms in future empirical study.
This article is part of the theme issue ‘Art, aesthetics and predictive processing: theoretical and empirical perspectives’.
LLM Instruction-Example Adaptive Prompting (LEAP) Framework for Clinical Relation Extraction
Authors: Zhou Huixue , Li Mingchen , Xiao Yongkang , Yang Han , Zhang Rui 
Published: December 2023

ABSTRACTObjectiveTo investigate the demonstration in Large Language Models (LLMs) for clinical relation extraction. We focus on examining two types of adaptive demonstration: instruction adaptive prompting, and example adaptive prompting to understand their impacts and effectiveness.Materials and MethodsThe study unfolds in two stages. Initially, we explored a range of demonstration components vital to LLMs’ clinical data extraction, such as task descriptions and examples, and tested their combinations. Subsequently, we introduced the Instruction-Example Adaptive Prompting (LEAP) Framework, a system that integrates two types of adaptive prompts: one preceding instruction and another before examples. This framework is designed to systematically explore both adaptive task description and adaptive examples within the demonstration. We evaluated LEAP framework’s performance on the DDI and BC5CDR chemical interaction datasets, applying it across LLMs such as Llama2-7b, Llama2-13b, and MedLLaMA_13B.ResultsThe study revealed thatInstruction + Options + Examplesand its expanded form substantially raised F1-scores over the standardInstruction + Optionsmode. LEAP framework excelled, especially with example adaptive prompting that outdid traditional instruction tuning across models. Notably, the MedLLAMA-13b model scored an impressive 95.13 F1 on the BC5CDR dataset with this method. Significant improvements were also seen in the DDI 2013 dataset, confirming the method’s robustness in sophisticated data extraction.ConclusionThe LEAP framework presents a promising avenue for refining LLM training strategies, steering away from extensive finetuning towards more contextually rich and dynamic prompting methodologies.
The effect of long-term sleep disruption on the brain – looking beyond amyloid
Authors: Mentink L.J. , van Osch M.J.P. , Bakker L.J. , Olde Rikkert M.G.M. , Beckmann C.F. , Claassen J.A.H.R. , Haak K.V. 
Published: December 2023

AbstractThe mechanism underlying the possible causal association between long-term sleep disruption and Alzheimer’s disease remains unclear [1]. A hypothesised pathway through increased brain amyloid load was not confirmed in previous work in our cohort of maritime pilots with long-term work-related sleep disruption [2]. Here, using functional MRI, T2-FLAIR and Arterial Spin Labeling MRI scans, we explored alternative neuroimaging biomarkers related to both sleep disruption and AD: resting-state network co-activation and between-network connectivity of the default mode network (DMN), salience network (SAL) and frontoparietal network (FPN), vascular damage and cerebral blood flow (CBF).We acquired data of 16 maritime pilots (56 ± 2.3 years old) with work-related long-term sleep disruption (23 ± 4.8 working years) and 16 healthy controls (59 ± 3.3 years old), with normal sleep patterns (Pittsburgh Sleep Quality Index ≤ 5). Maritime pilots did not show altered co-activation in either the DMN, FPN, or SAL and no differences in between-network connectivity. We did not detect increased markers of vascular damage in maritime pilots, and additionally, maritime pilots did not show altered CBF-patterns compared to healthy controls.In summary, maritime pilots with long-term sleep disruption did not show neuroimaging markers indicative of preclinical AD compared to healthy controls. These findings do not resemble those of short-term sleep deprivation studies. This could be due to resiliency to sleep disruption or selection bias, as participants have already been exposed to and were able to deal with sleep disruption for multiple years, or to compensatory mechanisms [3]. This suggests the relationship between sleep disruption and AD is not as strong as previously implied in studies on short-term sleep deprivation, which would be beneficial for all shift workers suffering from work-related sleep disruptions.
Reduced Lateralization of Multiple Functional Brain Networks in Autistic Males
Authors: Peterson Madeline , Prigge Molly B. D. , Floris Dorothea L. , Bigler Erin D. , Zielinski Brandon , King Jace B. , Lange Nicholas , Alexander Andrew L. , Lainhart Janet E. , Nielsen Jared A. 
Published: December 2023

AbstractBackgroundAutism spectrum disorder has been linked to a variety of organizational and developmental deviations in the brain. One such organizational difference involves hemispheric lateralization, which may be localized to language-relevant regions of the brain or distributed more broadly.MethodsIn the present study, we estimated brain hemispheric lateralization in autism based on each participant’s unique functional neuroanatomy rather than relying on group-averaged data. Additionally, we explored potential relationships between the lateralization of the language network and behavioral phenotypes including verbal ability, language delay, and autism symptom severity. We hypothesized that differences in hemispheric asymmetries in autism would be limited to the language network, with the alternative hypothesis of pervasive differences in lateralization. We tested this and other hypotheses by employing a cross-sectional dataset of 118 individuals (48 autistic, 70 neurotypical). Using resting-state fMRI, we generated individual network parcellations and estimated network asymmetries using a surface area-based approach. A series of multiple regressions were then used to compare network asymmetries for eight significantly lateralized networks between groups.ResultsWe found significant group differences in lateralization for the left-lateralized Language (d = −0.89), right-lateralized Salience/Ventral Attention-A (d = 0.55), and right-lateralized Control-B (d = 0.51) networks, with the direction of these group differences indicating less asymmetry in autistic individuals. These differences were robust across different datasets from the same participants. Furthermore, we found that language delay stratified language lateralization, with the greatest group differences in language lateralization occurring between autistic individuals with language delay and neurotypical individuals.LimitationsThe generalizability of our findings is restricted due to the male-only sample and greater representation of individuals with high verbal and cognitive performance.ConclusionsThese findings evidence a complex pattern of functional lateralization differences in autism, extending beyond the Language network to the Salience/Ventral Attention-A and Control-B networks, yet not encompassing all networks, indicating a selective divergence rather than a pervasive one. Furthermore, a differential relationship was identified between Language network lateralization and specific symptom profiles (namely, language delay) of autism.
Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data*
Authors: Ellis Charles A. , Miller Robyn L. , Calhoun Vince D. 
Published: December 2023

AbstractWhile deep learning methods are increasingly applied in research contexts for neuropsychiatric disorder diagnosis, small dataset size limits their potential for clinical translation. Data augmentation (DA) could address this limitation, but the utility of EEG DA methods remains relatively underexplored in neuropsychiatric disorder diagnosis. In this study, we train a model for major depressive disorder diagnosis. We then evaluate the utility of 6 EEG DA approaches. Importantly, to remove the bias that could be introduced by comparing performance for models trained on larger augmented training sets to models trained on smaller baseline sets, we also introduce a new baseline trained on duplicate training data to better. We lastly examine the effects of the DA approaches upon representations learned by the model with a pair of explainability analyses. We find that while most approaches boost model performance, they do not improve model performance beyond that of simply using a duplicate training set without DA. The exception to this is channel dropout augmentation, which does improve model performance. These findings suggest the importance of comparing EEG DA methods to a baseline with a duplicate training set of equal size to the augmented training set. We also found that some DA methods increased model robustness to frequency (Fourier transform surrogates) and channel (channel dropout) perturbation. While our findings on EEG DA efficacy are restricted to our dataset and model, we hope that future studies on deep learning for small EEG datasets and on new EEG DA methods will find our findings helpful.
Automating literature screening and curation with applications to computational neuroscience
Authors: Ji Ziqing , Guo Siyan , Qiao Yujie , McDougal Robert A. 
Published: December 2023

ABSTRACTObjectiveModelDB (https://modeldb.science) is a discovery platform for computational neuroscience, containing over 1800 published model codes with standardized metadata. These codes were mainly supplied from unsolicited model author submissions, but this approach is inherently limited. We estimate we have captured only around one-third of NEURON models and lower fractions for other simulators. To more completely characterize the state of computational neuroscience modeling work, we aim to identify works containing results derived from computational neuroscience approaches and their standardized associated metadata (e.g. cell types, research topics).Materials and MethodsKnown computational neuroscience work from ModelDB and identified neuroscience work queried from PubMed were included in our study. After pre-screening with SPECTER2, GPT-3.5 and GPT-4 were used to identify likely computational neuroscience work and their relevant metadata.ResultsSPECTER2, GPT-4, and GPT-3.5 demonstrated varied but high abilities in identification of computational neuroscience work. GPT-4 achieved 96.9% accuracy and GPT-3.5 improved from 54.2% to 85.5% through instruction-tuning and Chain of Thought. GPT-4 also showed high potential in identifying relevant metadata annotations.DiscussionDue to computational limitations, we only used each paper’s title and abstract, partially leading to false negatives. Further efforts should be devoted to including more training data and further improving current LLMs through fine-tuning approaches.ConclusionNLP and LLM techniques can be added to ModelDB to facilitate further model discovery, and will contribute to a more standardized and comprehensive framework for establishing domain-specific resources.
Predictive Model for Severe Coronary Artery Calcification in ESKD Patients
Authors: Tang Xinfang , Qian Hanyang , Zeng Ming , Huang Hui , Lu Shijiu , Wang Jing , Li Fan , Bian Anning , Ye Xiaoxue , Yang Guang , Ma Kefan , Xing Changying , Xu Yi , Wang Ningning 
Published: December 2023

AbstractIntroductionThe Agatston coronary artery calcification score (CACS) is an assessment index for coronary artery calcification (CAC). This study aims to explore the characteristics of CAC in end-stage kidney disease (ESKD) patients and establish a predictive model to assess the risk of severe CAC in patients.MethodsCACS of ESKD patients was assessed using an electrocardiogram-gated coronary computed tomography (CT) scan with the Agatston scoring method. A predictive nomogram model was established based on stepwise regression. An independent validation cohort comprised of patients with ESKD from multicentres.Results369 ESKD patients were enrolled in the training set, and 127 patients were included in the validation set. In the training set, the patients were divided into three subgroups: no calcification (CACS = 0, n = 98), mild calcification (0 < CACS ≤ 400, n = 141) and severe calcification (CACS > 400, n = 130). Among the four coronary branches, the left anterior descending branch (LAD) accounted for the highest proportion of calcification. Stepwise regression analysis showed that age, dialysis vintage, β-receptor blocker, calcium-phosphorus product (Ca × P), and alkaline phosphatase (ALP) level were independent risk factors for severe CAC. A nomogram that predicts the risk of severe CAC in ESKD patients has been internally and externally validated, demonstrating high sensitivity and specificity.ConclusionCAC is both prevalent and severe in ESKD patients. In the four branches of the coronary arteries, LAD calcification is the most common. Our validated nomogram model, based on clinical risk factors, can help predict the risk of severe coronary calcification in ESKD patients who cannot undergo coronary CT analysis.
Six-month mortality has decreased for patients with curative treatment for head and neck cancer in Sweden
Authors: Talani Charbél , Högmo Anders , Laurell Göran , Mäkitie Antti , Farnebo Lovisa 
Published: December 2023

AbstractBackgroundIn general, survival outcome for head and neck cancer (HNC) patients has improved. However, mortality within six months after diagnosis with curative intent remains high. The aim of this study was to identify risk factors for early death among patients with curative treatment, and furthermore, to analyze whether the risk of early death changed over the recent years.Material and MethodThis real-world, population-based, nationwide study from the Swedish Head and Neck Cancer Register (SweHNCR) included 16,786 patients with curative treatment decision at the multidisciplinary tumor board from 2008 to 2020.ResultsDuring the study period a total of 618 (3.7%) patients with curative-intended treatment died within six months from diagnosis. Patients diagnosed between 2008–2012 had a six-month mortality rate of 4.7% compared to 2.5% for patients diagnosed 2017–2020, indicating a risk reduction of 53% (p <0.001) for death within six months. The mean time to radiation therapy in the 2008–2012 cohort was 38 days, compared to 22 days for the 2017– 2020 cohort, (p<0.001). The mean time to surgery from diagnosis was 22 days in 2008–2012, compared to 15 days for the 2017–2020 cohort, (p <0.001).Females had a 20% lower risk of dying within six months compared to males (p =0.013). For every year older the patient was at diagnosis, a 4.8% (p <0.001) higher risk of dying within six months was observed. Patients with a WHO score of 1 had approximately 2.4-times greater risk of early death compared to WHO 0 patients (p <0.001). The risk of early death among WHO 4 patients was almost 28 times higher than for WHO 0 patients (p <0.001)ConclusionsWe found that the risk of early death decreased significantly from 2008 to 2020. During this period the mean time to the start of treatment, was significantly reduced both for surgery and oncological treatment regimes. Among patients with a curative treatment intention, increased risk of early death was associated with male sex, older age, advanced disease, increased WHO score, and a hypopharyngeal tumor site.Brief description*The risk of early death decreased significantly from 2008 to 2020.*Time from diagnosis to treatment decreased between 2008 to 2020.*Among patients with a curative treatment intention, increased risk of early death was associated with male sex, older age, advanced disease, increased WHO score, and a hypopharyngeal tumor site.Ethical ConsiderationsThe Regional Ethical Review Board in Gothenburg and Lund reviewed and approved the study, (Gothenburg, number 299–14, T230-17 and Lund 2020-01972). This study was carried out in accordance with the current Helsinki Declaration of the World Medical Association from 2013. Data are available upon request.